ORIGINAL ARTICLES
Monitoring and evaluating actions implemented to confront AIDS in Brazil: civil society's participation
Wilza VillelaI; José Carlos VelosoII
IDepartamento
de Medicina Preventiva. Escola Paulista de Medicina. Universidade Federal de
São Paulo. São Paulo, SP, Brasil
IIGrupo
de Apoio a Prevenção da Aids de São Paulo. São Paulo,
SP, Brasil
ABSTRACT
The United Nations Declaration of Commitment on HIV/AIDS recommends that governments conduct periodic analysis of actions undertaken in confronting the HIV/AIDS epidemic that involve civil society's participation. Specific instruments and mechanisms should be created towards this end. This paper examines some of the responses of the Brazilian government to this recommendation. Analysis contemplates the Declaration's proposals as to civil society's participation in monitoring and evaluating such actions and their adequacy with respect to Brazilian reality. The limitations and potentials of MONITORAIDS, the matrix of indicators created by Brazil's Programa Nacional de DST/AIDS [National Program for STD/AIDS ] to monitor the epidemic are discussed. Results indicate that MONITORAIDS's complexity hampers its use by the conjunction of actors involved in the struggle against AIDS. The establishment of mechanisms that facilitate the appropriation of this system by all those committed to confronting the epidemic in Brazil is suggested.
Keywords: Acquired immunodeficiency syndrome, prevention & control. Program evaluation. National health programs, organization & administration. Consumer participation. Communitarian organization.
INTRODUCTION
The United Nations Declaration of Commitment on HIV/AIDS, which resulted from the United Nations General Assembly. Special Session on HIV/AIDS (UNGASS), identifies, in its last chapter, the need to follow up actions undertaken by governments in confronting the epidemic. "Periodic analysis of the progress achieved in the implementation of these commitments, conducted with the participation of civil society, in particular, with the participation of people living with HIV/AIDS, vulnerable groups and with those providing services", are suggested. The creation of "adequate mechanisms of observation and evaluation, which make it possible to measure and evaluate progress", are proposed as well as "appropriate instruments of observation and evaluation, with adequate epidemiological data" and "supervisory systems for the protection of human rights of people living with HIV".1
The purpose of follow up actions is to "identify the problems and obstacles that emerged when undertaking commitments". The text also recommends "the widespread diffusion of results".1
IN 2002, a Joint United Nations Programme on HIV/AIDS (UNAIDS) consolidated a list of indicators for governments to monitor actions.2 Although the Declaration contains broad target, such as "accelerating the execution of national strategies for the eradication of poverty" or "developing political strategies and programs related to the factors that make people vulnerable", the indicators are specific for results with respect to the epidemic. These indicators are associated in four categories: national commitments and actions; knowledge and individual behavior; impact; and global commitments and actions.
During the same year (2002) the Programa Nacional de DST/AIDS (PN-DST/AIDS) [National Program for DST/AIDS] developed the Plano Nacional de Avaliação (PNA) [National Evaluation Plan] seeking to establish the foundations for a continual process of monitoring and evaluation of its actions. The matrix of the PNA is organized around the dimensions of monitoring and evaluation. Indicators of impact and results are defined for dimensions.
In 2005, the Plano Estratégico do Programa Nacional de DST/AIDS [Strategic Plan of the DST/AIDS National Program] assumed that one of its directives would be "the creation of an effective capacity for monitoring and evaluating", seeking to improve of the program's management. Consequentially, the Política Nacional de Monitoramento e Avaliação [Monitoring and Evaluation National Policy] was formulated, incorporating and updating the PNA. UNAIDS's system of indicators was also revised in 2005.3 According to this revision, it was recommended that data be disagregated according to sex and specific indicators be defined in function of the prevalence of the epidemic in different countries. Mechanisms of establishing civil society's participation were more detailed, including the production of qualitative and quantitative data and access to the national plans for collecting data.
PROPOSAL FOR FOLLOWING UP THE DECLARATION OF COMMITMENTS
The follow up activities set forth in the Declaration are periodic analyses, observation, evaluation and supervision. While recognizing the existing lack of consensus with respect to the scope of each of these activities, it may be acknowledged that, by and large, there is a certain continuum: periodic analyses would provide the necessary information to respond whether or not what was planned was in fact executed (monitoring); evaluation would provide responses as to whether what was planned and executed produced the desired results; and, supervision would attempt to resolve the discrepancies between what was planned and executed on the one hand, and, on the other, the results foreseen and those attained.
Considering these four phases, it is possible to perceive that following up the activities extrapolates the observation of the behavior of an indicator during a limited period of time. Observed variations should be interpreted vis-à-vis the actions proposed, those that were effectively carried out, the objectives set forth when the actions were proposed and the circumstances that interfered, whether positively or negatively, in attaining those results. This analytic and interpretive effort should be undertaken, for each of the 64 targets set forth in the Declaration, in partnership with civil society and people living with HIV/AIDS. The follow up proposal is, consequentially, a broad and complex target.
ADAPTING THE UNGASS PROPOSAL TO THE BRAZILIAN CONTEXT
The Declaration of Commitment was elaborated in midst of an intense and legitimate concern with the negative impacts that the epidemic has provoked in the African continent, and that it may provoke in Asia and Eastern Europe, where it is more recent, if viable, alternative means of treatment are not found. Thus, the focus of the Declaration is on countries or regions where there is a high prevalence of HIV or where the epidemic is in a rapid phase of expansion and that do not rely on a structured health system. In Brazil, the 0.6% prevalence is much lower than that of some African countries, such as Botswana, with a 40% prevalence.4 The epidemic has reached a phase of stabilization in Brazil, where there is access to anti-retroviral treatment, and a long history of partnership with civil society.
While acknowledging the pertinence of the Declaration for countries devasted by the epidemic, its directives should be adapted to Brazilian reality.
The pioneering character of Brazilian DST/AIDS policies is such that some of the principles that guide the Declaration of Commitments have already been partially or totally contemplated. This is the case, for example, in relation to the proposal of intersectoral collaboration that is already contemplated in the partnerships between the PN-DST/AIDS and other sectors of the Ministry of Health, between this program and other Ministries, such as the Ministry of Education, and other sectors, such as private enterprise, by means of the Business Council. The same is also true with respect to the integration between prevention and assistance, one of the characteristics of the PN-DST/AIDS since its creation, as is the participation of civil society in the definition and accompaniment of its actions.
Thus, the recommendation as to the "participation of civil society", present in the Declaration, seems to be based on realities distinct from the Brazilian reality, where it is still necessary to remember that the greater the number of people interested in this issue are directly involved, the easier it is to find a solution.
The engagement of Brazilian civil society in the struggle against AIDS does not mean that the dialogue between the State and the AIDS movement occurs free of tensions. On the contrary, this is a live, intense process, that is continually reconfigurating itself, with a constant flow of leaders from civil society to the PN-DST/AIDS and vice versa.
The characters denominated in the Declaration of Commitment as "civil society" people living with HIV/AIDS, higher risk groups and health care providers do not express the entire set of agents that build the social arch surrounding the struggle against AIDS in Brazil, which relies on several other actors, including those who produce knowledge on the subject. The latter should be specifically invited to participate in the monitoring actions, due to their potential contribution in the interpretation and analyses of data, redrafting of proposed actions and dissemination of the analysis and results.
At the same time, the utilization of fixed categories, such as "people living with HIV" and "groups living under greater risk", in order to define the subjects that should participate in follow up actions, requires caution. Doubtless, these subjects have a priviledged knowledge on habits, behaviors and language of their community. Their contribution may be fundamental in drawing up the strategies of prevention and care of their respective groups, as well as in the analysis of data concerning the accomplishments and shortcomings or obstacles arising from the implementation of strategies. However, the incorporation of these capacities in tasks that require the command of specific technical abilities, such as the follow up program proposed by UNGASS, is a challenge. Furthermore, the people that compose the groups defined in the Declaration as "civil society" also identify themselves in terms of social class, gender, ethnic and professional groups that also mark their experience of living with HIV/AIDS or belonging to some group under greater social exclusion. Thus, this experience may not always suffice to leave specific marks on policies, even if the subject was involved with their formulation and/or implementation.
The participation of people that are active in non-governmental organizations in different government instances or forums has been constantly problematised in the places where civil society organizes itself. Questions are raised as to which mechanisms may be utilized by people invited to compose a mixed environment (government/society) in order to assure that their opinions and perspectives in fact express the desire or reality of their reference group. Or still yet, up to what measure the opinions expressed in these forums are effectively brought to bare.3
PARTICIPATION OF CIVIL SOCIETY IN MONITORING ACTIONS
Monitoring their actions is among government's responsibilities, being relatively easy to define the actions that should be monitored and the method to be utilized towards this end: a priority among the actions to be undertaken is established, and in thesis, the same sequence is followed in the monitoring process. Definition of methods and the respective techniques utilized in collecting data is facilitated by governmental organ's access to existing data systems and due to the possibility, when these are not sufficient, of producing the necessary information. Although the culture of monitoring and evaluating health is relatively recent in Brazil, and the systematic production of information is not a practice that has been incorporated by health services, it is possible to establish modes and criteria for accompanying the HIV/AIDS epidemic. These modes and criteria may be the point of departure for evaluating the pertinence and efficacy of actions implemented. In fact, since the beginning of the epidemic, effort has been made, on the part of the PN-DST/AIDS, to systematize and disseminate, by means of its Boletim Epidemiológico [Epidemiological Bulletin], the information related to mortality due to this cause and the notification of new cases of AIDS.
Monitoring is a very complex procedure for civil society. Producing quantitative data of a populational character in order to accompany the behavior of the epidemic independently does not make sense nor is it possible. Thus, one should rely on data produced by the government to accompany actions that this same government defined in response to the problems that it identified. Many of these actions can only be accompanied by means of data provided by the government. Consequently, an effort must be made so that civil society does not become a mere spectator of the process. Apparently, the alternative proposed by UNGASS, is an effective partnership, in which government and society define in conjunction, similar levels of expertise, interest and commitment as well as the contents and strategies to be utilized to keep track of the epidemic. Due to differences in these actors' political perspectives, as well as differences as to their familiarity in handling the data and in their individual and institutional disposal for the task at hand, this alternative is not realistic. For this reason, in 2006, UNAIDS began to suggest that civil society develop its own processes of monitoring, including the production of qualitative data, that would make it possible to delve more deeply in the analysis of quantifiable data.5
The difficulty arising when civil society attempts to monitor public policies is not only operational or political, it is also conceptual. Often the idea of monitoring is confounded with that of social control. Although it is not possible to conduct any form of social control without some kind of monitoring for it is this latter process that will supply the acts of social control with their content these actions are distinct in their dynamics and in their purposes. One example of how civil society interlaces monitoring and social control is the way it responded to the shortage in medication supplies that occurred in 2004. Activists from different regions of the country developed and applied a questionnaire in order to diagnose the quality of assistance among HIV positive individuals, in an organized manner. It was completed in only four months. The results were disclosed to the public in mobilizations conducted simultaneously in all the municipalities involved in the initiative, unleashing actions of social control. Beyond the merits and political interests of this initiative, the fact that the diagnosis utilized was an instrument prepared by people living with HIV and who rely on the Sistema Único de Saúde (SUS) [Brazilian Unified Health System], permitted their experience to be incorporated in the definition of criteria related to the quality of assistance and satisfaction among individuals utilizing SUS. In this manner, knowledge was appropriated from people living with HIV for effective action in monitoring and social control.
SYSTEM FOR MONITORING INDICATORS
The PN-DST/AIDS's System for Monitoring Indicators (MONITORAIDS) was created with the "objective of providing partners and civil society as a whole, useful information that makes it possible to accompany the Brazilian response towards the control of AIDS and other STDs". It aggregates indicators considered relevant for monitoring the HIV/AIDS epidemic as well as other STDs; which are useful in evaluating the programmatic actions of the PN-DST/AIDS as well as being suggestive for future evaluations. The instrument is considered the "most relevant structural component of the Plano Nacional de Avaliação [National Evaluation Plan]".
MONITORAIDS is composed of indicators that attend the demands of UNGASS, the World Bank and the PN-DST/AIDS itself. It is comprised of a set of socioeconomic, health indicators related to the HIV/AIDS epidemic, originating from different databases and specific research. There is an index card for each indicator, in which its definition, the method utilized for calculating it and its limitations are explicited. It is foreseen that the system will be updated and re-edited each year. MONITORAIDS has been available on the internet since 2005.6
The result of exhaustive work, MONITORAIDS presents the same problems that any system of this stature tends to present, considering that Brazil is a large, populous country that has profound social inequalities.
The reports are presented in a national and regional sphere. Indeed, it is up to the federal manager to present nationally aggregated data, or regionally disaggregated data, since important regional differences in terms of access and service coverage, population morbimortality rates and living conditions are well-known.2 Regional differences and inequalities also result in disparities in coverage and quality of information, and specific methodological artifacts are necessary to correct the data.1 Aggregation of data, whether on a national, regional or state level, by homogenizing distinct realities, also produces a result that is quite distant from any reality. The utility of this information for purposes of local and immediate planning of health actions, including AIDS, is thus compromised. In this sense, expliciting the limitations of each MONITORAIDS indicator does not reduce the necessity of conducting more specific studies, when the intention is to plan, monitor and evaluate local actions.
Information issuing from SUS is not based on populational studies. Some of the data systems are structured and supplied information that is directed towards the payment of procedures, this is the case, for example, of the Sistema de Informações Ambulatórias (SIA) [Outpatient Information System], the Sistema de Informações Hospitalares (SIH) [Hospital Information System], the Sistema de Informações sobre o Pré-natal (SIS pré-Natal) [Pre-natal Care Information System], and others. Thus, there is a margin of error when this data is utilized for other purposes, since efforts may be made to adjust the procedures undertaken to those listed in the payment rosters and other distortions. Furthermore, the systems for payment of procedures do not indicate how many people where in fact beneficiaries. In this way, the limitations of these sources of information may be greater than indicated in MONITORAIDS, when it states that data originating from SUS does not cover the entire population and all health procedures. Finally, creating compatibility with respect to information that originates from distinct sources is not always possible, since the fields covered and the methodologies utilized in collecting data may be different.
The databases related to health assistance and administration have the above mentioned limitations; the systems related to the epidemiological profile, such as the Sistema de Informações em Mortalidade (SIM)[Mortality InformationSystem], the Sistema de Informações em Agravos Notificáveis (SINAN) [Notifiable Disorders Information System], and the Sistema de Informações sobre Nascidos Vivos (SINASC) [Live Births Information System], present problems with respect to coverage. For example, the national average for the underregistration of deaths is estimated at 20% and reaches a 40% average in Northern and Northeastern regions. Approximately 15% of the death declarations within the SIM database do not present the basic cause of death; as to SINASC, its estimated converage in the Northern and Northeastern regions is 75%; and the SINAN has not been implanted in all Brazilian municipalities.7
Some data derives from research whose replication or preriodicity is not guaranteed. This is the case, for example, of the Pesquisa Nacional por Amostragem de Domicílios (PNAD) [National Survey Based on a Residential Sample], that is irregular in terms of its periodicity and presents a specific content at each edition; and the Pesquisa Nacional de Demografia e Saúde [National Survey on Health and Demography]. Even the Demographic Census has occasionally presented problems of periodicity. However, despite some delays, these surveys do end up occurring. Guaranteeing periodicity is more troublesome with respect to the evaluation studies and surveys conducted by PN-DST/AIDS that depend on specific resources, political will power and available funds both within the Program and the Ministry of Health. Furthermore, it should be stressed that these studies are the only ones that provide information concerning the characteristics and behavior of certain populations, being essential, therefore, for planning actions.
CONCLUSIONS
Reflection concerning the monitoring of government actions in the struggle against AIDS presupposes that this is a political process, although it relies on technical instruments for this purpose.
However, it is possible to approach the process of monitoring from a technical perspective, attempting to reduce its political dimension. This seems to be the Brazilian government's option up to the present.
As proposed by UNGASS, instruments and mechanisms were created in order to conduct periodic analyses that make it possible to evaluate progress and identify obstacles. The effective incorporation of distinct social actors in this task, however, needs to be further developed. This includes building strategies for further appropriation and utilization of MONITORAIDS, as well as the establishment of mechanisms to facilitate the process of production and circulation of information by civil society. It is also necessary to stimulate the capacity for analysis and critique of information by the broad set of activists committed to the struggle against the epidemic. The more consolidated the partnership between civil society and government in accompanying the epidemic, easier it will become to conduct effective actions for its control.
REFERENCES


FINDING AID
Accession 88-094, Society of Vertebrate Paleontology, Records, 1981-1987
Collection Overview
-
Repository: Smithsonian Institution Archives, Washington, D.C. Contact us at<EMAIL_ADDRESS>Creator: Society of Vertebrate Paleontology
Title: Records
Dates: 1981-1987
Quantity: 9 cu. ft. (9 record storage boxes)
Collection: Accession 88-094
Language of Materials: English
Summary:
These records consist of the editorial files of the "Journal of Vertebrate Paleontology," a publication of the Society of Vertebrate Paleontology, for volumes 1 thru 7.
Descriptive Entry
This accession consists of editorial files of the Journal of Vertebrate Paleontology, a publication of the Society of Vertebrate Paleontology, for volumes 1 through 7.
Index Terms This collection is indexed under the following access terms. These are links to collections with related topics, persons or places. SUBJECT Journal of Vertebrate Paleontology. Professional associations Vertebrate Paleontology PHYSICAL CHARACTERISTICS OF MATERIALS IN THE COLLECTION Manuscripts Administrative Information PREFERRED CITATION Smithsonian Institution Archives, Accession 88-094, Society of Vertebrate Paleontology, Records Container List BOX 1 Volumes 1 & 2 Box 1 of 9 BOX 2 Volume 3; Volume 4, #1-2 Box 2 of 9 BOX 3 Volume 4, #3-4 Box 3 of 9 BOX 4 Volume 5, #1-3 Box 4 of 9 BOX 5 Volume 5, #4; Volume 6, #1 Box 5 of 9 BOX 6 Volume 6, #3-4 Box 6 of 9 BOX 7 Volume 7, #1-2 Box 7 of 9 BOX 8 Volume 7, #3-4 Box 8 of 9 BOX 9 Rejected manuscripts Box 9 of 9


*Must include Client Name, Client Email and Rate.
*Client Name is too short
*Not a vailid email
*Not a vailid Charge Rate - number required.


The Giant Panda
The giant pandas are the best known species yet the shyest and rarest animals in the world.
- Scientific Name: A. melanoleuca
- Average Height: 2-3 ft.
- Average Lifespan: 20 years
- Habitat: Bamboo forests
At first glance, the giant panda would seem to resemble a bear, but in fact its features show it has a stronger affinity with racoons. They are solitary animals spending about two-thirds of its day feeding and the remainder resting.


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| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
public interface JavaRDDLike<T,This extends JavaRDDLike<T,This>>
Defines operations common to several Java RDD implementations. Note that this trait is not intended to be implemented by user code.
| Method Summary | ||
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aggregate(U zeroValue,
Function2<U,T,U> seqOp,
Function2<U,U,U> combOp)
Aggregate the elements of each partition, and then the results for all the partitions, using given combine functions and a neutral "zero value". |
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cartesian(JavaRDDLike<U,?> other)
Return the Cartesian product of this RDD and another one, that is, the RDD of all pairs of elements (a, b) where a is in this and b is in other . |
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void |
checkpoint()
Mark this RDD for checkpointing. |
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scala.reflect.ClassTag<T> |
classTag()
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java.util.List<T> |
collect()
Return an array that contains all of the elements in this RDD. |
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JavaFutureAction<java.util.List<T>> |
collectAsync()
The asynchronous version of collect , which returns a future for
retrieving an array containing all of the elements in this RDD. |
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java.util.List<T>[] |
collectPartitions(int[] partitionIds)
Return an array that contains all of the elements in a specific partition of this RDD. |
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SparkContext |
context()
The SparkContext that this RDD was created on. |
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long |
count()
Return the number of elements in the RDD. |
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PartialResult<BoundedDouble> |
countApprox(long timeout)
:: Experimental :: Approximate version of count() that returns a potentially incomplete result within a timeout, even if not all tasks have finished. |
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PartialResult<BoundedDouble> |
countApprox(long timeout,
double confidence)
:: Experimental :: Approximate version of count() that returns a potentially incomplete result within a timeout, even if not all tasks have finished. |
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long |
countApproxDistinct(double relativeSD)
Return approximate number of distinct elements in the RDD. |
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JavaFutureAction<Long> |
countAsync()
The asynchronous version of count , which returns a
future for counting the number of elements in this RDD. |
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java.util.Map<T,Long> |
countByValue()
Return the count of each unique value in this RDD as a map of (value, count) pairs. |
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PartialResult<java.util.Map<T,BoundedDouble>> |
countByValueApprox(long timeout)
(Experimental) Approximate version of countByValue(). |
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PartialResult<java.util.Map<T,BoundedDouble>> |
countByValueApprox(long timeout,
double confidence)
(Experimental) Approximate version of countByValue(). |
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T |
first()
Return the first element in this RDD. |
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flatMap(FlatMapFunction<T,U> f)
Return a new RDD by first applying a function to all elements of this RDD, and then flattening the results. |
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JavaDoubleRDD |
flatMapToDouble(DoubleFlatMapFunction<T> f)
Return a new RDD by first applying a function to all elements of this RDD, and then flattening the results. |
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flatMapToPair(PairFlatMapFunction<T,K2,V2> f)
Return a new RDD by first applying a function to all elements of this RDD, and then flattening the results. |
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T |
fold(T zeroValue,
Function2<T,T,T> f)
Aggregate the elements of each partition, and then the results for all the partitions, using a given associative and commutative function and a neutral "zero value". |
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void |
foreach(VoidFunction<T> f)
Applies a function f to all elements of this RDD. |
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JavaFutureAction<Void> |
foreachAsync(VoidFunction<T> f)
The asynchronous version of the foreach action, which
applies a function f to all the elements of this RDD. |
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void |
foreachPartition(VoidFunction<java.util.Iterator<T>> f)
Applies a function f to each partition of this RDD. |
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JavaFutureAction<Void> |
foreachPartitionAsync(VoidFunction<java.util.Iterator<T>> f)
The asynchronous version of the foreachPartition action, which
applies a function f to each partition of this RDD. |
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com.google.common.base.Optional<String> |
getCheckpointFile()
Gets the name of the file to which this RDD was checkpointed |
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StorageLevel |
getStorageLevel()
Get the RDD's current storage level, or StorageLevel.NONE if none is set. |
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JavaRDD<java.util.List<T>> |
glom()
Return an RDD created by coalescing all elements within each partition into an array. |
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groupBy(Function<T,U> f)
Return an RDD of grouped elements. |
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groupBy(Function<T,U> f,
int numPartitions)
Return an RDD of grouped elements. |
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int |
id()
A unique ID for this RDD (within its SparkContext). |
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boolean |
isCheckpointed()
Return whether this RDD has been checkpointed or not |
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boolean |
isEmpty()
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java.util.Iterator<T> |
iterator(Partition split,
TaskContext taskContext)
Internal method to this RDD; will read from cache if applicable, or otherwise compute it. |
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keyBy(Function<T,U> f)
Creates tuples of the elements in this RDD by applying f . |
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map(Function<T,R> f)
Return a new RDD by applying a function to all elements of this RDD. |
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mapPartitions(FlatMapFunction<java.util.Iterator<T>,U> f)
Return a new RDD by applying a function to each partition of this RDD. |
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mapPartitions(FlatMapFunction<java.util.Iterator<T>,U> f,
boolean preservesPartitioning)
Return a new RDD by applying a function to each partition of this RDD. |
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JavaDoubleRDD |
mapPartitionsToDouble(DoubleFlatMapFunction<java.util.Iterator<T>> f)
Return a new RDD by applying a function to each partition of this RDD. |
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JavaDoubleRDD |
mapPartitionsToDouble(DoubleFlatMapFunction<java.util.Iterator<T>> f,
boolean preservesPartitioning)
Return a new RDD by applying a function to each partition of this RDD. |
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mapPartitionsToPair(PairFlatMapFunction<java.util.Iterator<T>,K2,V2> f)
Return a new RDD by applying a function to each partition of this RDD. |
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mapPartitionsToPair(PairFlatMapFunction<java.util.Iterator<T>,K2,V2> f,
boolean preservesPartitioning)
Return a new RDD by applying a function to each partition of this RDD. |
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mapPartitionsWithIndex(Function2<Integer,java.util.Iterator<T>,java.util.Iterator<R>> f,
boolean preservesPartitioning)
Return a new RDD by applying a function to each partition of this RDD, while tracking the index of the original partition. |
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mapToDouble(DoubleFunction<T> f)
Return a new RDD by applying a function to all elements of this RDD. |
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mapToPair(PairFunction<T,K2,V2> f)
Return a new RDD by applying a function to all elements of this RDD. |
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T |
max(java.util.Comparator<T> comp)
Returns the maximum element from this RDD as defined by the specified Comparator[T]. |
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T |
min(java.util.Comparator<T> comp)
Returns the minimum element from this RDD as defined by the specified Comparator[T]. |
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String |
name()
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java.util.List<Partition> |
partitions()
Set of partitions in this RDD. |
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JavaRDD<String> |
pipe(java.util.List<String> command)
Return an RDD created by piping elements to a forked external process. |
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JavaRDD<String> |
pipe(java.util.List<String> command,
java.util.Map<String,String> env)
Return an RDD created by piping elements to a forked external process. |
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JavaRDD<String> |
pipe(String command)
Return an RDD created by piping elements to a forked external process. |
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RDD<T> |
rdd()
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T |
reduce(Function2<T,T,T> f)
Reduces the elements of this RDD using the specified commutative and associative binary operator. |
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void |
saveAsObjectFile(String path)
Save this RDD as a SequenceFile of serialized objects. |
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void |
saveAsTextFile(String path)
Save this RDD as a text file, using string representations of elements. |
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void |
saveAsTextFile(String path,
Class<? extends org.apache.hadoop.io.compress.CompressionCodec> codec)
Save this RDD as a compressed text file, using string representations of elements. |
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java.util.List<Partition> |
splits()
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java.util.List<T> |
take(int num)
Take the first num elements of the RDD. |
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JavaFutureAction<java.util.List<T>> |
takeAsync(int num)
The asynchronous version of the take action, which returns a
future for retrieving the first num elements of this RDD. |
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java.util.List<T> |
takeOrdered(int num)
Returns the first k (smallest) elements from this RDD using the natural ordering for T while maintain the order. |
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java.util.List<T> |
takeOrdered(int num,
java.util.Comparator<T> comp)
Returns the first k (smallest) elements from this RDD as defined by the specified Comparator[T] and maintains the order. |
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java.util.List<T> |
takeSample(boolean withReplacement,
int num)
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java.util.List<T> |
takeSample(boolean withReplacement,
int num,
long seed)
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java.util.List<T> |
toArray()
Deprecated. As of Spark 1.0.0, toArray() is deprecated, use collect() instead |
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String |
toDebugString()
A description of this RDD and its recursive dependencies for debugging. |
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java.util.Iterator<T> |
toLocalIterator()
Return an iterator that contains all of the elements in this RDD. |
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java.util.List<T> |
top(int num)
Returns the top k (largest) elements from this RDD using the natural ordering for T. |
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java.util.List<T> |
top(int num,
java.util.Comparator<T> comp)
Returns the top k (largest) elements from this RDD as defined by the specified Comparator[T]. |
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treeAggregate(U zeroValue,
Function2<U,T,U> seqOp,
Function2<U,U,U> combOp)
treeAggregate(U, org.apache.spark.api.java.function.Function2, org.apache.spark.api.java.function.Function2, int) with suggested depth 2. |
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treeAggregate(U zeroValue,
Function2<U,T,U> seqOp,
Function2<U,U,U> combOp,
int depth)
Aggregates the elements of this RDD in a multi-level tree pattern. |
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T |
treeReduce(Function2<T,T,T> f)
treeReduce(org.apache.spark.api.java.function.Function2 with suggested depth 2. |
|
T |
treeReduce(Function2<T,T,T> f,
int depth)
Reduces the elements of this RDD in a multi-level tree pattern. |
|
This |
wrapRDD(RDD<T> rdd)
|
|
|
zip(JavaRDDLike<U,?> other)
Zips this RDD with another one, returning key-value pairs with the first element in each RDD, second element in each RDD, etc. |
|
|
zipPartitions(JavaRDDLike<U,?> other,
FlatMapFunction2<java.util.Iterator<T>,java.util.Iterator<U>,V> f)
Zip this RDD's partitions with one (or more) RDD(s) and return a new RDD by applying a function to the zipped partitions. |
|
JavaPairRDD<T,Long> |
zipWithIndex()
Zips this RDD with its element indices. |
|
JavaPairRDD<T,Long> |
zipWithUniqueId()
Zips this RDD with generated unique Long ids. |
| Method Detail |
|---|
This wrapRDD(RDD<T> rdd)
scala.reflect.ClassTag<T> classTag()
RDD<T> rdd()
java.util.List<Partition> splits()
java.util.List<Partition> partitions()
SparkContext context()
SparkContext
that this RDD was created on.
int id()
StorageLevel getStorageLevel()
java.util.Iterator<T> iterator(Partition split, TaskContext taskContext)
split
- (undocumented)taskContext
- (undocumented)
<R> JavaRDD<R> map(Function<T,R> f)
f
- (undocumented)
<R> JavaRDD<R> mapPartitionsWithIndex(Function2<Integer,java.util.Iterator<T>,java.util.Iterator<R>> f, boolean preservesPartitioning)
f
- (undocumented)preservesPartitioning
- (undocumented)
<R> JavaDoubleRDD mapToDouble(DoubleFunction<T> f)
f
- (undocumented)
<K2,V2> JavaPairRDD<K2,V2> mapToPair(PairFunction<T,K2,V2> f)
f
- (undocumented)
<U> JavaRDD<U> flatMap(FlatMapFunction<T,U> f)
f
- (undocumented)
JavaDoubleRDD flatMapToDouble(DoubleFlatMapFunction<T> f)
f
- (undocumented)
<K2,V2> JavaPairRDD<K2,V2> flatMapToPair(PairFlatMapFunction<T,K2,V2> f)
f
- (undocumented)
<U> JavaRDD<U> mapPartitions(FlatMapFunction<java.util.Iterator<T>,U> f)
f
- (undocumented)
<U> JavaRDD<U> mapPartitions(FlatMapFunction<java.util.Iterator<T>,U> f, boolean preservesPartitioning)
f
- (undocumented)preservesPartitioning
- (undocumented)
JavaDoubleRDD mapPartitionsToDouble(DoubleFlatMapFunction<java.util.Iterator<T>> f)
f
- (undocumented)
<K2,V2> JavaPairRDD<K2,V2> mapPartitionsToPair(PairFlatMapFunction<java.util.Iterator<T>,K2,V2> f)
f
- (undocumented)
JavaDoubleRDD mapPartitionsToDouble(DoubleFlatMapFunction<java.util.Iterator<T>> f, boolean preservesPartitioning)
f
- (undocumented)preservesPartitioning
- (undocumented)
<K2,V2> JavaPairRDD<K2,V2> mapPartitionsToPair(PairFlatMapFunction<java.util.Iterator<T>,K2,V2> f, boolean preservesPartitioning)
f
- (undocumented)preservesPartitioning
- (undocumented)
void foreachPartition(VoidFunction<java.util.Iterator<T>> f)
f
- (undocumented)JavaRDD<java.util.List<T>> glom()
<U> JavaPairRDD<T,U> cartesian(JavaRDDLike<U,?> other)
this
and b is in other
.
other
- (undocumented)
<U> JavaPairRDD<U,Iterable<T>> groupBy(Function<T,U> f)
f
- (undocumented)
<U> JavaPairRDD<U,Iterable<T>> groupBy(Function<T,U> f, int numPartitions)
f
- (undocumented)numPartitions
- (undocumented)
JavaRDD<String> pipe(String command)
command
- (undocumented)
JavaRDD<String> pipe(java.util.List<String> command)
command
- (undocumented)
JavaRDD<String> pipe(java.util.List<String> command, java.util.Map<String,String> env)
command
- (undocumented)env
- (undocumented)
<U> JavaPairRDD<T,U> zip(JavaRDDLike<U,?> other)
other
- (undocumented)
<U,V> JavaRDD<V> zipPartitions(JavaRDDLike<U,?> other, FlatMapFunction2<java.util.Iterator<T>,java.util.Iterator<U>,V> f)
other
- (undocumented)f
- (undocumented)
JavaPairRDD<T,Long> zipWithUniqueId()
RDD.zipWithIndex()
.
JavaPairRDD<T,Long> zipWithIndex()
void foreach(VoidFunction<T> f)
f
- (undocumented)java.util.List<T> collect()
java.util.Iterator<T> toLocalIterator()
The iterator will consume as much memory as the largest partition in this RDD.
java.util.List<T> toArray()
collect()
instead
java.util.List<T>[] collectPartitions(int[] partitionIds)
partitionIds
- (undocumented)
T reduce(Function2<T,T,T> f)
f
- (undocumented)
T treeReduce(Function2<T,T,T> f, int depth)
depth
- suggested depth of the treef
- (undocumented)
reduce(org.apache.spark.api.java.function.Function2)
T treeReduce(Function2<T,T,T> f)
treeReduce(org.apache.spark.api.java.function.Function2, int)
with suggested depth 2.
f
- (undocumented)
T fold(T zeroValue, Function2<T,T,T> f)
This behaves somewhat differently from fold operations implemented for non-distributed collections in functional languages like Scala. This fold operation may be applied to partitions individually, and then fold those results into the final result, rather than apply the fold to each element sequentially in some defined ordering. For functions that are not commutative, the result may differ from that of a fold applied to a non-distributed collection.
zeroValue
- (undocumented)f
- (undocumented)
<U> U aggregate(U zeroValue, Function2<U,T,U> seqOp, Function2<U,U,U> combOp)
zeroValue
- (undocumented)seqOp
- (undocumented)combOp
- (undocumented)
<U> U treeAggregate(U zeroValue, Function2<U,T,U> seqOp, Function2<U,U,U> combOp, int depth)
depth
- suggested depth of the treezeroValue
- (undocumented)seqOp
- (undocumented)combOp
- (undocumented)
aggregate(U, org.apache.spark.api.java.function.Function2, org.apache.spark.api.java.function.Function2)
<U> U treeAggregate(U zeroValue, Function2<U,T,U> seqOp, Function2<U,U,U> combOp)
treeAggregate(U, org.apache.spark.api.java.function.Function2, org.apache.spark.api.java.function.Function2, int)
with suggested depth 2.
zeroValue
- (undocumented)seqOp
- (undocumented)combOp
- (undocumented)
long count()
PartialResult<BoundedDouble> countApprox(long timeout, double confidence)
timeout
- (undocumented)confidence
- (undocumented)
PartialResult<BoundedDouble> countApprox(long timeout)
timeout
- (undocumented)
java.util.Map<T,Long> countByValue()
PartialResult<java.util.Map<T,BoundedDouble>> countByValueApprox(long timeout, double confidence)
timeout
- (undocumented)confidence
- (undocumented)
PartialResult<java.util.Map<T,BoundedDouble>> countByValueApprox(long timeout)
timeout
- (undocumented)
java.util.List<T> take(int num)
num
- (undocumented)
java.util.List<T> takeSample(boolean withReplacement, int num)
java.util.List<T> takeSample(boolean withReplacement, int num, long seed)
T first()
boolean isEmpty()
void saveAsTextFile(String path)
path
- (undocumented)void saveAsTextFile(String path, Class<? extends org.apache.hadoop.io.compress.CompressionCodec> codec)
path
- (undocumented)codec
- (undocumented)void saveAsObjectFile(String path)
path
- (undocumented)<U> JavaPairRDD<U,T> keyBy(Function<T,U> f)
f
.
f
- (undocumented)
void checkpoint()
boolean isCheckpointed()
com.google.common.base.Optional<String> getCheckpointFile()
String toDebugString()
java.util.List<T> top(int num, java.util.Comparator<T> comp)
num
- k, the number of top elements to returncomp
- the comparator that defines the order
java.util.List<T> top(int num)
num
- k, the number of top elements to return
java.util.List<T> takeOrdered(int num, java.util.Comparator<T> comp)
num
- k, the number of elements to returncomp
- the comparator that defines the order
T max(java.util.Comparator<T> comp)
comp
- the comparator that defines ordering
T min(java.util.Comparator<T> comp)
comp
- the comparator that defines ordering
java.util.List<T> takeOrdered(int num)
num
- k, the number of top elements to return
long countApproxDistinct(double relativeSD)
The algorithm used is based on streamlib's implementation of "HyperLogLog in Practice: Algorithmic Engineering of a State of The Art Cardinality Estimation Algorithm", available here.
relativeSD
- Relative accuracy. Smaller values create counters that require more space.
It must be greater than 0.000017.
String name()
JavaFutureAction<Long> countAsync()
count
, which returns a
future for counting the number of elements in this RDD.
JavaFutureAction<java.util.List<T>> collectAsync()
collect
, which returns a future for
retrieving an array containing all of the elements in this RDD.
JavaFutureAction<java.util.List<T>> takeAsync(int num)
take
action, which returns a
future for retrieving the first num
elements of this RDD.
num
- (undocumented)
JavaFutureAction<Void> foreachAsync(VoidFunction<T> f)
foreach
action, which
applies a function f to all the elements of this RDD.
f
- (undocumented)
JavaFutureAction<Void> foreachPartitionAsync(VoidFunction<java.util.Iterator<T>> f)
foreachPartition
action, which
applies a function f to each partition of this RDD.
f
- (undocumented)
|
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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


# -*- coding: utf-8 -*- """ Created on Wed Nov 7 06:03:01 2018 @author: AdeolaOlalekan """ {% extends "base_generic.html" %} {% block content %}


Make sure you have the right details to hand. You’ll need:
- a valid email address
- the Government Gateway login for your organisation (or you can use the accounts office reference number and employer PAYE scheme reference number if your annual pay bill is less than £3 million)
- authority to add PAYE schemes to the account
- authority to sign the employer agreement
You’ll be taken through a few simple steps to:
- create a user account
- add a Pay As You Earn (PAYE) scheme on behalf of your organisation
- confirm your organisational details
- accept the employer agreement with the Education and Skills Funding Agency (ESFA)
You can watch our YouTube video for more tips.


Enumeration members
AFRICA
AFRICA: = "AFRICA"
ASIA
ASIA: = "ASIA"
AUSTRALIA
AUSTRALIA: = "AUSTRALIA"
AUTO
AUTO: = "AUTO"
AWS
AWS: = "AWS"
AWS_AP_NORTHEAST_1
AWS_AP_NORTHEAST_1: = "AWS_AP_NORTHEAST_1"
AWS_AP_NORTHEAST_2
AWS_AP_NORTHEAST_2: = "AWS_AP_NORTHEAST_2"
AWS_AP_SOUTHEAST_1
AWS_AP_SOUTHEAST_1: = "AWS_AP_SOUTHEAST_1"
AWS_AP_SOUTHEAST_2
AWS_AP_SOUTHEAST_2: = "AWS_AP_SOUTHEAST_2"
AWS_AP_SOUTH_1
AWS_AP_SOUTH_1: = "AWS_AP_SOUTH_1"
AWS_CA_CENTRAL_1
AWS_CA_CENTRAL_1: = "AWS_CA_CENTRAL_1"
AWS_EU_CENTRAL_1
AWS_EU_CENTRAL_1: = "AWS_EU_CENTRAL_1"
AWS_EU_NORTH_1
AWS_EU_NORTH_1: = "AWS_EU_NORTH_1"
AWS_EU_WEST_1
AWS_EU_WEST_1: = "AWS_EU_WEST_1"
AWS_EU_WEST_2
AWS_EU_WEST_2: = "AWS_EU_WEST_2"
AWS_EU_WEST_3
AWS_EU_WEST_3: = "AWS_EU_WEST_3"
AWS_SA_EAST_1
AWS_SA_EAST_1: = "AWS_SA_EAST_1"
AWS_US_EAST_1
AWS_US_EAST_1: = "AWS_US_EAST_1"
AWS_US_EAST_2
AWS_US_EAST_2: = "AWS_US_EAST_2"
AWS_US_WEST_1
AWS_US_WEST_1: = "AWS_US_WEST_1"
AWS_US_WEST_2
AWS_US_WEST_2: = "AWS_US_WEST_2"
AZURE_AUSTRALIA_EAST
AZURE_AUSTRALIA_EAST: = "AZURE_AUSTRALIA_EAST"
AZURE_AUSTRALIA_SOUTHEAST
AZURE_AUSTRALIA_SOUTHEAST: = "AZURE_AUSTRALIA_SOUTHEAST"
AZURE_EUROPE_NORTH
AZURE_EUROPE_NORTH: = "AZURE_EUROPE_NORTH"
AZURE_EUROPE_WEST
AZURE_EUROPE_WEST: = "AZURE_EUROPE_WEST"
AZURE_GERMANY_WESTCENTRAL
AZURE_GERMANY_WESTCENTRAL: = "AZURE_GERMANY_WESTCENTRAL"
AZURE_UAE_NORTH
AZURE_UAE_NORTH: = "AZURE_UAE_NORTH"
AZURE_US_EAST
AZURE_US_EAST: = "AZURE_US_EAST"
AZURE_US_WEST2
AZURE_US_WEST2: = "AZURE_US_WEST2"
EUROPE
EUROPE: = "EUROPE"
EXTERNAL
EXTERNAL: = "EXTERNAL"
GOOGLE
GOOGLE: = "GOOGLE"
GOOGLE_ASIA_EAST_1
GOOGLE_ASIA_EAST_1: = "GOOGLE_ASIA_EAST_1"
GOOGLE_ASIA_EAST_2
GOOGLE_ASIA_EAST_2: = "GOOGLE_ASIA_EAST_2"
GOOGLE_ASIA_NORTHEAST_1
GOOGLE_ASIA_NORTHEAST_1: = "GOOGLE_ASIA_NORTHEAST_1"
GOOGLE_ASIA_SOUTHEAST_1
GOOGLE_ASIA_SOUTHEAST_1: = "GOOGLE_ASIA_SOUTHEAST_1"
GOOGLE_ASIA_SOUTH_1
GOOGLE_ASIA_SOUTH_1: = "GOOGLE_ASIA_SOUTH_1"
GOOGLE_AUSTRALIA_SOUTHEAST_1
GOOGLE_AUSTRALIA_SOUTHEAST_1: = "GOOGLE_AUSTRALIA_SOUTHEAST_1"
GOOGLE_EUROPE_NORTH_1
GOOGLE_EUROPE_NORTH_1: = "GOOGLE_EUROPE_NORTH_1"
GOOGLE_EUROPE_WEST_1
GOOGLE_EUROPE_WEST_1: = "GOOGLE_EUROPE_WEST_1"
GOOGLE_EUROPE_WEST_2
GOOGLE_EUROPE_WEST_2: = "GOOGLE_EUROPE_WEST_2"
GOOGLE_EUROPE_WEST_3
GOOGLE_EUROPE_WEST_3: = "GOOGLE_EUROPE_WEST_3"
GOOGLE_EUROPE_WEST_4
GOOGLE_EUROPE_WEST_4: = "GOOGLE_EUROPE_WEST_4"
GOOGLE_NORTHAMERICA_NORTHEAST_1
GOOGLE_NORTHAMERICA_NORTHEAST_1: = "GOOGLE_NORTHAMERICA_NORTHEAST_1"
GOOGLE_SOUTHAMERICA_EAST_1
GOOGLE_SOUTHAMERICA_EAST_1: = "GOOGLE_SOUTHAMERICA_EAST_1"
GOOGLE_US_CENTRAL_1
GOOGLE_US_CENTRAL_1: = "GOOGLE_US_CENTRAL_1"
GOOGLE_US_EAST_1
GOOGLE_US_EAST_1: = "GOOGLE_US_EAST_1"
GOOGLE_US_EAST_4
GOOGLE_US_EAST_4: = "GOOGLE_US_EAST_4"
GOOGLE_US_WEST_1
GOOGLE_US_WEST_1: = "GOOGLE_US_WEST_1"
GOOGLE_US_WEST_2
GOOGLE_US_WEST_2: = "GOOGLE_US_WEST_2"
NORTH_AMERICA
NORTH_AMERICA: = "NORTH_AMERICA"
SOUTH_AMERICA
SOUTH_AMERICA: = "SOUTH_AMERICA"


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This page outlines technical details about this website. You can learn more about the purpose and content of the website, as well as the author (Amber Dewaele) on this page.
The site is created using Brackets with the instructions of Bram Overstijns on Bureaupixel. The page is online thanks to Github. All the images are edited with Adobe Lightroom. A draft version of this site was made with Adobe XD.
A QR code of the publication version of this site, was created by QR Monkey.
This can be found below.


Flight from Berlin 08.05 20:10 to Dublin 08.05 22:00 | Return from Dublin 10:05 to 19:15 to Berlin 10.05 22:00
Flight from Berlin 08.05 20:10 to Dublin 08.05 22:00 | Return from Dublin 10:05 to 19:15 to Berlin 10.05 22:00
Flight from Berlin 08.05 20:10 to Dublin 08.05 22:00 | Return from Dublin 10:05 to 19:15 to Berlin 10.05 22:00


#DeBitpay Merchants
Many merchants that use Bitpay to accept Bitcoin payments are not aware of these issues: they don't support many wallets (Copy Link), they block payments by IPs/locations (Copy Link). Please spend a few minutes to draw their attention to this and help them switch to another payment processor.
What to do?
- If you know a merchant who uses Bitpay, post a tweet mentioning their @TwitterId and put the hashtag #DeBitpay (Copy Hashtag).
- Monitor twitter feed with the hashtag #DeBitpay from time to time and join the conversations.
What to tweet about:
- Let them know about issues associated with Bitpay (check links above).
- Ask the merchant to switch to BTCPay Server (Copy Link). It's open-source and has no fees, no middleman.
- Send them the list of awesome bitcoin payment processors (Copy Link).
- Ask for alternative merchants accepting Bitcoin without Bitpay.
Thanks for your #DeBitpay!


URL Format: api.codybenlewis.com/mbta/station?direction=value&format=value
Arguments: direction, format
Direction Values: eastbound, inbound, westbound, outbound
Format Values: lcd
Quick Links:
Kenmore
Hynes Convention Center
Copley
Arlington
Boylston
Park Street
Government Center


{% extends "projects/_page.html" %} {% load crispy_forms_tags %} {% load static %} {% block title %} Delete channel {{ channel.name }} | {{ proj.full_name }} {% endblock %} {% block page %}
You are about to delete the channel {{ channel.name }}{% if channel.version_set.count %} and {{ channel.version_set.count }} version{% if channel.version_set.count > 1 %}s{% endif %}{% endif %}.
Are you absolutely sure?
{% crispy form %}


by PALAKOLLU SRI MANIKANTA A quick yet complete tour of lists in Python3 in just seven minutesPhoto by Emma Matthews on UnsplashPython lists are not like arrays. They are bit different. When it comes to dealing with array’s we talk about a collection of homogeneous data elements. This is
by PALAKOLLU SRI MANIKANTA
Photo by Emma Matthews on Unsplash
Python lists are not like arrays. They are bit different. When it comes to dealing with array’s we talk about a collection of homogeneous data elements. This is not true in case of a list in python. Python List can store a heterogeneous collection of elements. This feature will help developers and programmers to work with lists in a more flexible manner. A List in python is one of the most powerful inbuilt data structures.
Lists in python can store Integers, Floating values, Strings, Boolean values, and complex values as well.
We can create a list in python in two ways
Example
# Here first I'm creating a my todo list which is used to store my to-do activities.
myTODOList = []
# The above line will create a list object for me# I'm creating a another list which will store my general information.
myGeneralInfo = list()
# The above line will also create a list object for me# Getting the types of list objects
print(type(myTODOList))print(type(myGeneralInfo))
Output
Output for the above few lines of code.
It’s amazing at this point you are able to create a new list object with most frequently used methods. Now we will move forward on how we can add new elements to our list and many more things. Let’s get started.
First of all, I would like to introduce the concept of Mutability. Mutability means the ability to change its behavior. Python lists are mutable in nature. We can add or delete elements from the list. This is one of the biggest advantages that attract programmers to work with lists when compared to other inbuilt data structures.
We can add elements to a list in two ways:
By using append()
With the help of the append method, we are able to add one element at a time. This method will help us to add elements at the end of the list only.
The syntax for the append function is —
listName.append(item/element)
# Adding Elements to the lists
myTODOList.append('Wake up Early Morning')myTODOList.append('Go to Gym')myTODOList.append('Play Some Games')myTODOList.append('Get ready to go the college')myTODOList.append('Go to library')
# Printing the entire list elements
print(myTODOList)
Output
Output for the above line of code.
By using insert()
This insert method is used to add the elements at a specified position in the given list.
The syntax for the insert function is —
listName.insert(position, item/element)
insert() uses two parameters — position and list item. The position is where the element is needed to be kept in the list. These positions are generally called as indexes. Usually, the list index in python starts from 0. (i.e the first element index is 0 and the second element is 1 and the third element index is 2 and so on). From this, we can conclude that —
A list of n elements will have at most an index number of n-1 i.e A list with 5 elements will have maximum index value of 4.
Example
# Adding Elements to our list with the help of insert()
myGeneralInfo.insert(0, 'Paid the Library Fee')myGeneralInfo.insert(1, 12000)myGeneralInfo.insert(2, True)myGeneralInfo.insert(3, 14+12j)myGeneralInfo.insert(4, 3.141521)
# Printing the myGeneralInfo list information
print(myGeneralInfo)
Output
Output for the above few lines of code.
myGeneralInfo is filled with some random information for illustration purposes only.
We can access the list of elements by using the following two ways:
By using an index operator
We can directly access our list elements with the help of the index operator.
Example
# Acessing the certain values from the list
print(myTODOList[1])print(myTODOList[3])print(myTODOList[4])
Output
Output for the above program
By using Slice Operator
The slice operator is one of the most commonly used operators to access the list elements effectively. The syntax for the slice operator is:
listName[start: stop: step]
start — It indicates the index where the slice has to start. The default value is 0.
stop — It indicates the index where the slice has to end. The default value is the maximum allowed index of list i.e. length of the list.
step — Increment value. The default value is 1.
Example
# Getting the information using slice operator
print(myTODOList[0:3]) # we don't need to specify the step value.print(myTODOList[2:4:1])print(myTODOList[0:4:2])
Output
Output for the above few lines of code.
Python lists are iterable objects. For any iterable object in python, we can write a for loop to print out all the data.
Example
# Iterating over the list
for item in myGeneralInfo: print(item)
Output for the above lines of code.
We can remove the list elements with the following two ways:
By using remove()
remove() is used to remove the element that is specified to it. The syntax for remove() is:
listName.remove(item/element)
# Deleting the element from the list
myGeneralInfo.remove(12000)myGeneralInfo.remove('Paid the Library Fee')
# printing the result after deleting the elements
print(myGeneralInfo)
After deleting the list elements the output would be as follows
By using pop()
It is an iterator method which is used to remove the single (or) multiple elements at a time. It deletes the elements from the back side. The syntax for the pop() method is:
listName.pop()
# printing the list items before deleting
print('My TODO List Elements: ',myTODOList)print('My General list Elements: ',myGeneralInfo)
# Deleting the list elements using pop()
myTODOList.pop()myTODOList.pop()
# Deleting the list elements completely
for item in range(len(myGeneralInfo)): myGeneralInfo.pop()
# printing the results
print('My TODO List Elements: ',myTODOList)print('My General list Elements: ',myGeneralInfo)
This is the way we can delete list elements using pop()
In the above program, we used the len() within the for loop. len() is used to give the length of the list i.e. number of elements present in the list.
python dir() function is used to give the set of inbuilt attributes and methods that are associated with it.
Example
# Printing all the attributes and functions on the list object
print(dir(myTODOList))
Output
Various Attributes and Methods on the list object
If you want to store multiple data objects, insertion order must be preserved. If you want to store duplicate values as well, then this data structure will be more helpful to perform such operations.
I covered pretty much everything that is required to perform any kind of operation on the list data structure.
Hope this helped you learn about Lists in python in a quick and easy way.
If you liked this article, please click on the clap and leave me feedback. Please share with your friends.
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Lech Wałęsa
Fighting for Polish Freedom
Wałęsa's History
- 1943 - Born on 29th September at Popowo, near Wroclawek, Poland.
- 1959 - Went to school in Lipno for two years. Enlisted in mandatory military service
- 1967 - Became an electrician at the Lenin Shipyard in Gdansk.
- 1976 - Lost his job after participating in protests, spent next 4 years of his life as an activist while under surveillance of Polish secret police.
- 1980 - Following the election of John Paul II to the Papacy, workers across Poland undertook nationwide strikes. Wałęsa lead the strikes in the Lenin Shipyard, and eventually became the leader of the protest movement which was renamed to Solidarność, or Solidarity.
- 1981 - Soviet pressure forced the Polish government to suppress protests and riots, resulting in martil law being declared on December 13 and the arrest of Wałęsa and other Solidarity leaders.
- 1983 - Awarded the Nobel Peace Prize
- 1988 - New wave of protests resulted in Polish communists starting negotiations with Solidarity and Wałęsa. Solidarity became legal.
- 1989 - Solidarity wins all available parliamentary positions in elections
- 1990-1995 - Following the June 1989 legislative elections, Wałęsa becomes the first democratically elected President of Poland.
- 1995 - Lost presidental elections, with less than 1% of the electorate's votes. Withdrew from politics.
- 2000 - Lost another presidential election.
- 2006 - Quit Solidarity in protest of Poland's right-wing Law and Justice party
- 2011 - Receives Ronald Reagan Freedom Award
- 2014 - Wałęsa criticizes Barack Obama's reception of the Nobel Peace Prize
If you wish to learn more about Lech Wałęsa, check out his Wikipedia page.


{% extends 'sitewide/base.html' %} {% block title %}{{membership.person.get_full_name}}'s Votes in {{membership.session}}{% endblock %} {% load markdownify %} {% load react %} {% block body %}
Representing {{membership.district}}
{% endif %} {% if votes %}| Date | Bill | Question | Response |
| {{vote.bill_vote.date}} | {{vote.bill_vote.bill}} | {{vote.bill_vote.issue}} | {{vote.opinion}} |
|---|


The qform has been copied from sform. The difference in angle is -5.3e-07. The difference in translation is 3.6e-15.


| templater-0.5.0 |
† |
genki |
RubiGen alternative Generator thingy |
|
| hosts_access-0.3 |
† |
genki |
Rails/Merb plugin that controls host access like hosts.allow |
|
| dm-ys |
|
genki |
a DataMapper extension that uses html table as its schema and data powerfully like YunkerStar |
|
| merb_full_url-0.0.2 |
† |
genki |
A plugin for merb framework that provides full_url/full_resource method. |
|
| merb_timezone_select-0.0.2 |
† |
genki |
A plugin for the Merb framework that provides timezone selector |
|
| merb_slice-gen-0.0.2 |
† |
genki |
generator for slices |
|
| merb_recognize_path-0.0.2 |
† |
genki |
A merb plugin for the Merb framework that provides recognize_path method. |
|
| merb_component-0.2.3 |
† |
genki |
Merb plugin that provides composition of controllers. |
|
| dm-pagination-<IP_ADDRESS> |
† |
genki |
A pagination plugin for DataMapper. |
|
| pagination_scope-0.0.8 |
† |
genki |
This is a rails plugin module for mixing in pagination function. |
|
| rttool-1.0.2 |
† |
genki |
Simple table generator |
|
| dm-has-versions-0.1.1 |
† |
genki |
A plugin that adds version control to DataMapper models. |
|
| merb_babel-<IP_ADDRESS> |
† |
genki |
Merb用I18n/L10nライブラリ |
|
| dm-is-paginated |
|
genki |
dm-is-paginated is a simple pagination plugin for DataMapper. |
|
| merb-pagination |
|
genki |
A pagination helper for merb. Useful with dm-is-paginated or with Sequel’s built in pagination. |
|
| merb-auth-slice-activation |
|
genki |
This slice provides a check to make sure that a user is active on login. It also provides activation on the “user” object via an activation action (slice_url :activate). |
|


Mr. Roboger's Neighborhood
Name:
Number or numbers separated by a space or comma:
Reverse Order
Submit


Okay, I was talking to someone recently who had a seemingly awesome build, he wouldn't divulge all the details but from what I got the build had;
40 Dex, which means starting at 20 Dex (Elf), increasing Dex every stat increase and 10 post epic Great Dexterity feats, and I'm guessing he had 40 Tumble aswell for that extra AC, probably had Discipline maxed and Spellcraft 40 aswell.
He casted a few buffing spells, I couldn't tell you which because the particular character I was using had no Spellcraft, and he had lots of attacks per round, so I'm guessing it was Monk/Cleric/CoT.
Could someone try to re-create this build?, I'd try myself but I am hopeless at character building, thanks in advance.
He probably was not a cleric at all, he sounds like a bard, Monk/Bard/Barbarian, Monk/Bard/Fighter or Monk/Bard/CoT. To get a 40 dex you would need a class with great Dexterity as a bonus feat, which suggests Bard (Bard, Harper Scout, Assassin and Arcane Archer are the only classes with great dex as a bonus feat).
Was he getting sneak attacks? If so he might have been a Monk/Assassin/X.
Are you sure he wasn't counting buffs or items on the 40 dex? It just is that getting a 20 starting dex, typically means you aren't an uber character. particularly if you need to have a high casting attribute as well. If you would like I could hammer out a Monk/Cleric/CoT or Monk/Cleric/Rogue which would be pretty strong, though the Dex would probably only be around 34 or 36. The latter would have a lower dex, but you could fit in epic dodge. _________________ Two wrongs don't make a right but three lefts do.
I'm pretty sure that he was naked and unbuffed, I don't think he was hitting sneaks but then again that could be a whole new idea.
Now that you mention it, I recall he had Epic Dodge so the Monk/Cleric/Rogue might be what I'm after, thanks.
He could also be a Monk/Bard/Shadowdancer, although with that it might be strange not to notice HiPSs... and not much use into it.


Joe Biden received overwhelming support from Andover students in a survey conducted by The Phillipian, vol. CXLIII about the upcoming presidential race. Of the 1,181 students surveyed, 65.1 percent responded and completed the survey. Biden received 78.8 percent of the votes, compared to 16.6 percent for Donald Trump. Third-party candidates received the support of 4.6 percent of students – with Jo Jorgensen, the Libertarian Party candidate, taking 3.4 percent of the vote, and Howie Hawkins, the Green-Rainbow Party candidate, receiving 1.2 percent.
In the same survey sent to faculty members and staff, 28 percent completed the survey. Eighty-nine percent plan to vote for Biden and 10.3 percent plan to vote for Trump. Jorgensen and Hawkins each received 0.4 percent of support.
Keep scrolling to see the results of our survey and a compilation of all of our election coverage.
Website by Anthony Kim and Jessica He.


First
First-a
First-b
First-b-1
First-c
First-d
Second
Second-a
Second-b
Second-b-1
Second-c
Second-d
Third
Third-a
Third-b
Third-b-1
Third-c
Third-d
Fourth


Batting or Fielding?
field
bat
Select Stadium
Select Stadium
Rajiv Gandhi International Stadium, Uppal
Maharashtra Cricket Association Stadium
Saurashtra Cricket Association Stadium
Holkar Cricket Stadium
M Chinnaswamy Stadium
Wankhede Stadium
Eden Gardens
Feroz Shah Kotla
Punjab Cricket Association IS Bindra Stadium, Mohali
Green Park
Punjab Cricket Association Stadium, Mohali
Sawai Mansingh Stadium
MA Chidambaram Stadium, Chepauk
Dr DY Patil Sports Academy
Newlands
St George's Park
Kingsmead
SuperSport Park
Buffalo Park
New Wanderers Stadium
De Beers Diamond Oval
OUTsurance Oval
Brabourne Stadium
Sardar Patel Stadium, Motera
Barabati Stadium
Vidarbha Cricket Association Stadium, Jamtha
Himachal Pradesh Cricket Association Stadium
Nehru Stadium
Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Stadium
Subrata Roy Sahara Stadium
Shaheed Veer Narayan Singh International Stadium
JSCA International Stadium Complex
Sheikh Zayed Stadium
Sharjah Cricket Stadium
Dubai International Cricket Stadium
M. A. Chidambaram Stadium
Feroz Shah Kotla Ground
M. Chinnaswamy Stadium
Rajiv Gandhi Intl. Cricket Stadium
IS Bindra Stadium
ACA-VDCA Stadium
Predict
{{ prediction_text }}


Jan Clark v Mary Richards
Claim number: 352MC733
Waiting for Jan Clark to respond to your offer
You made an offer to settle the claim out of court.
Jan Clark can accept or reject your offer.
We'll email you when they respond.
The claimant rejected your response
You rejected the claim
You said you don't want to try mediation.
Claim made against you
Total claim amount
| Claim amount | £275 |
| Claim fee | £25 |
| Total | £300 |
Claimant's details
| Name | Mrs Jan Clark |
| Address | 101 Regents Road Shiplake Henley on Thames RG9 4BW |
| Telephone |<PHONE_NUMBER>2 |
|<EMAIL_ADDRESS>|
Your details (defendant)
| Name | Mrs Mary Richards |
| Address | 24 Acacia Drive London SW1 H9A |
| Telephone |<PHONE_NUMBER>2 |
|<EMAIL_ADDRESS>|


| DOSE: |
5 hits |
smoked |
PCP |
(powder / crystals) |
I have experimented with several drugs in my lifetime though never wished to make a lifestyle of it. After going from weed to dxm and acid, I kinda wanted something in between or adjacent to those experiences. PCP seemed to be it.
 He comes by my house and I give him 55 dollars: 40 dollars for PCP, 10 dollars for weed (so you don't waste any PCP), and 5 dollars for a PCP pipe if he could find one. He came by several hours later with a small rock that smelled really weird. He couldn't land me a pipe so I smoked out of his friend's who was with him at the time. Since he couldn't get me a pipe or weed that night, he just put all the money into PCP.
The way it works is that you break off a really really really tiny chunk and stick in the end of the pipe.
 It is really hard to master it. Anyway, we drove around my neighborhood matching hits and exchanging the pipe. I had 2 hits that night and felt like I had smoked some weed laced with DXM...yes, I know it doesn't exist, but still. :D
So I went home and broke up my rock into about 25 hits, give or take 5 or so. As soon as I could, I landed myself a pipe and got out on my roof. I had brought some Floyd and had planned for a good night.
I took two hits immediately, holding in the smoke for as long as in humanly possible. I followed with two more thinking that was all I needed. But twenty minutes later I didn't feel that different. So I took another one...
Ten minutes later, all the lights in the sky and the lights from houses all around started going in and out, exchanging placements. My whole perspective of vision had a slant to it and would spin on a central axis if I didn't control it. Dark Side helped this out a little bit too. I laid down on my roof and looked around for a good 20 minutes. I smoked a couple cigarettes and with each one, I became so high it was ridiculous.
Then my limbs became long, and I felt like I was continually falling through the roof but never actually falling down. I got up and the whole world was swirling. Somehow I managed to get back in my room where I looked at the ceiling. I knew that I hadn't even reached a plateau yet and cursed myself for taking another hit.
I went outside and made a few calls and then...zzzrrrrmm ... whawhawhawhawha...
Reality took a step in the background and the metaphysical realm took over. Weird sounds and feeling permeated every cell of my being. I lied down on the side of the road on a gutter man-hole. My head loosened itself from my body and wiggled itself backwards through some plants. I jerked myself up and it came back. I didn't really like that very much, so I got up and all the sudden...I felt like running.
I ran and ran and ran...I ran until my muscles burned and my veins pumped battery acid. Then I ran some more. My whole vision entered into a tunnel and I was running in a 10 degree sphere of sight...It was really really really strange. I felt so powerful that I just kept on running. I only realized I was tired the next day.
I thought it a good idea to go back in my house at this time. I entered my basement and sat down on the couch and watched my whole world swirl. This didn't last long and I was quickly back in my room listening to Floyd...I fell asleep like this several hours later. A combination of Dark Side, The Wall, and A Momentary Lapse of Reason really kicked my up top notch. The next morning I was unbelievably EXHAUSTED though. This lasted for another day thought not as bad.
When I think back on it, it really wasn't that FUN. It was messed up and weird, sure, but the psychadlics and narcotics are so much better. Do it if you want, folks, but I think it's just a little overrated for this day and age. PCP is for the late 70's early 80's crew...and they were a weird bunch.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Event Relation 1
Event Relation 2
Relational Event (ID:3)
Event Relation 4
Event Relation 5
Event Relation 6
Event Relation 7
Event Relation 8
Event Relation 9
Event Relation 10
Event Relation 11
Event Relation 12
Event Relation 13
Event Relation 14
Event Relation 15
Event Relation 16


Rafael Nadal
The Best Tennis Player from Spain
Rafael "Rafa" Nadal Parera (Born 3 June 1986) is a Spanish professional tennis player currently ranked world No. 2 in men's singles tennis by the Association of Tennis Professionals (ATP).
Nadal has won 19 Grand Slam singles titles, the second-most in history for a male player, as well as a record 35 ATP Tour Masters 1000 titles,21 ATP Tour 500 titles and the 2008 Olympic gold medal in singles. In addition, Nadal has held the world No. 1 ranking for a total of 209 weeks, including being the year-end No. 1 five times. In majors, Nadal has won a record twelve French Open titles, four US Open titles, two Wimbledon titles and one Australian Open title, and won at least one Grand Slam every year for a record ten consecutive years (2005–2014). Nadal has won 85 career titles overall, including the most outdoor titles in the Open Era (83) and a record 59 titles on clay. With 81 consecutive wins on clay, Nadal holds the record for the longest single-surface win streak in the Open Era.
Nadal has been involved in five Davis Cup titles with Spain, and currently has a 29-win streak and 29–1 record in singles matches at the event. In 2010, at the age of 24, he became the seventh male player and the youngest of five in the Open Era to achieve the singles Career Grand Slam. Nadal is the second male player after Andre Agassi to complete the singles Career Golden Slam, as well as the second male player after Mats Wilander to have won at least two Grand Slams on all three surfaces (grass, hard court and clay). He has received the tour Sportsmanship Award three times and has been named the ATP Player of the Year five times and the ITF World Champion four times. In 2011, Nadal was named the Laureus World Sportsman of the Year.
If you want to know more about him you can go to his Wikipedia Page


This view describes the environment within which the system is executed. It describes the geographic distribution of the system or the structure of the hardware components that execute the software. It documents workstations, processors, network topologies and channels, as well as other elements of the physical system environment. The deployment view shows the system from the operator’s point of view. Please explain how the systems’ building blocks are aggregated or packaged into deployment artifacts or deployment units.
Software is not much use without hardware. The minimum that is needed by you as a software architect is sufficient detail of the underlying (hardware) deployment so that you can assign each software building block that is relevant for the system’s operations to some hardware element. (This also holds for any COTS that is a prerequisite for the operations of the overall system.) These models should enable the operator to properly install the software.
The UML provides deployment diagrams for describing this view. Use these – possibly in a nested manner if necessary. (The top level deployment diagram should already be part of your context view, showing your infrastructure as a single black box (cf. chapter 3.2). Here you are zooming into this black box with additional deployment diagrams.) Diagrams by your hardware-oriented colleagues who describe processors and channels are also usable. You should abstract these to aspects relevant for software deployment.


Posted on January 2, 2019 at 10:20 PM
This is the biggest problem I being an Indian citizen face today. Hospitals lack enough of doctors,necessary hospitality requirements of people are not fulfilled
Even after registering online,two-three days prior to the visit,we face terrible in ascpect of time and hospitality. We have to stand in long queues for registration then for visitng the doctor and then for medicine.
Increasing the number of Doctors per department might solve the issue to great extent


{% extends 'base.html' %} {% block title %}Home{% endblock %} {% block content %}
1.1. create three lists of the following elements; 1.2. using the slicing operation (array slice); 1.3. get a general list of all three, excluding duplicates; 1.4. get unique and common elements for two lists of numbers; 1.5. get the sum of list items from numbers;...
Write a regular expression to search for an IP address in the text. Write a regular expression to search for the domain name in the URL. Using the regular expression from the previous job, replace all the domains in url_samples with example.org while keeping the rest of the URL
Write a function that will break the keys of the dictionary into plug-ins while preserving the hierarchy of keys and the values of the original dictionary. Write a function that will find the difference between the data taken from two dictionaries, taking into account possible changes in the keys
We have 2 models. Author is a writer model. Book is a model with books written by writers. You need to write the optimal query using Django ORM to count the number of written pages by each author.
Donec sed odio dui. Cras justo odio, dapibus ac facilisis in, egestas eget quam. Vestibulum id ligula porta felis euismod semper. Fusce dapibus, tellus ac cursus commodo, tortor mauris condimentum nibh, ut fermentum massa justo sit amet risus.


Hi, I'm Jennifer!
Welcome to my online portfolio. I'm an amateur programmer and college student.
Working towards expanding my skillset and knowledge about the world.
Welcome to my online portfolio. I'm an amateur programmer and college student.
Working towards expanding my skillset and knowledge about the world.


bluebox
A node library to use the Bluebox Group API
Jump to Section
Installation
npm install bluebox --save
Examples
var Bluebox = require('bluebox');
var credentials = {
'customer_id': <insert yours>,
'api_key': <insert your>
};
var api = new Bluebox(credentials);
api.block_list({},function(err, blocks) {
console.log(blocks);
});
api.block_details({uid: 'abc1234...' },function(err, block) {
console.log(block);
});
API
You can find the full detailed API descriptions at:
http://jedi4ever.github.io/bluebox.js/index.html
All API calls follow the same pattern:
api.method_name(options, callback);
Implemented methods are:
- block_list
- block_details
- block_create
- block_reboot
block_destroy
template_list
- template_create
- template_details
template_destroy
location_list
product_list
Building and Testing
The testing currently runs with mocked http requests using Nock.
Note: This is work in progress. The idea is to create mocked tests & real tests.
For real tests, config will be read from config.js
.
Create this file by copying sample_config.js
and changing the credentials
License
Copyright (c) 2010-2013 Patrick Debois
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
 IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


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We've included some information below to help you get started. If you have any other questions, check out our online help topics. |
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Game Simulator
问题描述 :
The whole game contains a number of rounds. In each round, one team is called “Declarers” (CT); the other team is called “Defenders” (FT). Each team has a current rank (CR). The goal of the player is to increase his own team’s CR as much as possible.
A certain round has a Main Suit (Heart – H, Spade – S, Club – C, Diamond – D, or None – no main suit in this round) and its CR. The CR in this round is the CR of the CT, and Main Suit will be given. The Main Suit and CR will be used to determine the order of the cards.
Cards ranked 5, 10, King value 5, 10, 10 pts (points) respectively, all other cards value 0 pts. In one round, we only consider the FT’s pts. The rules of getting pts for FT will be discussed later.
If the FT gets less than 80 pts in one round, they will hold be FT in the next round. This situation is called “make”. Otherwise, they become CT in the next round and the original CT become FT instead. This situation is called “down”.
If the FT gets 0 pts, the CR of the current CT will be increased by 3, for example, if the CR of the CT is 9, it will become Queen (12). Otherwise, if the FT gets less than 40 pts, the CR of the CT will be increased by 2. Otherwise, if the FT gets less than 80 pts, the CR of the CT will be increased by 1. Otherwise, if the FT gets not less than 80 + k * 40 pts and less than 120 + k * 40 pts, the CR of the current FT will be increased by k. For example, if the FT gets 255 pts in a round, the CR of the current FT will be increased by 4; and if the FT gets 80 pts, both teams’ CR remain unchanged. If a team’s CR becomes beyond Ace, this team is considered the WINNER of the whole game.
During a round, one of the players in CT is called the dealer. If “make”, the pard (teammate) of the dealer becomes the next round’s dealer. Otherwise (“down”), the player on dealer’s right-hand side becomes the dealer of the next round. For example, if the dealer of the current round is Alice and her team (CT) is “down”, the dealer of the next round should be Bob (on Alice’s right-hand side).
At the start of a round, each of the players except the dealer gets exactly 25 cards; the dealer gets all the remaining 33 cards. After that, the dealer chooses 8 of his cards and gives them to the judge, and these cards are called “hidden cards”.
Now each player has exactly 25 cards. A round consists of several tricks. In the first trick, the dealer plays one or more cards (called “lead”), then, in clockwise order, players play the same number of cards as the first player one by one (called “follow”). The winner of the current trick leads cards during the next trick, and so on. If the winner of the current trick is a member of FT, then the FT gets the sum of the cards’ pts played in this trick.
Now we start to describe how to determine the winner of a trick. After the main suit and the CR of the current round are fixed, we can determine the “trumps” which are cards with main suit or CR (Current Rank), and the Jokers. All other cards are “not-trumps”.
We can have an order among all the cards according the following rules:
- (1) “Trumps” are ordered higher than “not-trumps”.
(2) For the trumps, the order are listed below:
Red Joker
Black Joker
card with main suit and CR (if exists)
other card with CR
other trumps ordered by their ranks(i.e., A, K, Q, J, T, 9, 8, 7, …, 3, 2)
(3) For the “not-trumps”, they are ordered by their ranks.
Assume in all the description below, in the current round, the CR of the CT is 7.

In each trick, the lead cards (played by the player leading this trick) must be either all “trumps”, or all “not-trumps” with same suit.
The possible structures of the cards are listed below (assume the main suit is H and main rank is 7 for the example):
Single. A single card, such as D9.
Pair. Two same cards, such as D9D9. But D7S7 is not a pair although their orders are the same.
Tractor. Two or more consecutive-ordered pairs, satisfying the condition that they are all “trumps”, or all “not-trumps” with same suit, such as SJSJSQSQSKSKSASA, H7H7S7S7HAHA or RJRJBJBJ. But, these are not tractors: S7S7C7C7 (their orders are the same), C7C7C6C6 (they are not consecutive-ordered), DADAD2D2 (Ace is not “one”, so they are not consecutive-ordered), H2H2H4H4, or D2D2D3. Be careful: if “None” in this round, H7H7S7S7HAHA is not a tractor (H7 and S7 are same-ordered because of “None”).
Throw. The combination of the structures above, satisfying the condition that they are all “trumps”, or all “not-trumps” with same suit. Each of the Single, Pair or Tractor in a Throw is one of the Throw’s component. In the original tractor game, in some situation, the throw will be rejected. But, to keep the rule simple, we assume in this problem all the throws are accepted. For example, RJRJBJBJH7H7HQHQHJHJH9H9H6H6HAH2 contains six components: two tractors, two pairs and two single cards (RJRJBJBJH7H7-HQHQHJHJ-H9H9-H6H6-HA-H2); CACAC8C8CK contains three components: two pairs and one single card(CACA-C8C8-CK).
A throw can be treated as different list of components, for example, H2H2H3H3H4H4H5H5H6H6 can also be treated as H2H2H3H3-H4H4H5H5H6H6, or H2H2-H3H3H4H4H4H5H5-H6H6, and so on. For the lead cards, each time we choose the longest component (choose the one with the highest order to break the tie) to construct a list of components, this list is the structure of the lead cards, also the structure of the trick. So that the structure of the trick is unique.
After the first player lead his or her cards, other players follow cards one by one in clockwise order, as mentioned above.
An important part of the game is to determine the winner of a trick:
If one’s follow cards contain both “trumps” and “not-trumps”, or all “not-trumps” but with different suits, this player can’t be winner of this trick.
Otherwise, if the lead cards are all “not-trumps” and one’s follow cards contain “not-trumps” with different suit from the lead cards, this follow player can’t be the winner of this trick.
Else, if one’s follow cards can’t be constructed as the same structure of lead cards, this player can’t be the winner of this trick either.
Otherwise, if the structure of this trick is not “throw”, the one who played the highest-ordered card wins this trick. If more than one player played the same highest-ordered card, the winner of this trick will be the one who plays the highest-ordered card first.
Now let’s consider the “throw” situation. We construct the follow cards into the structure of the lead cards, so that the order of the highest-ordered card in all the longest components of the “throw” is as high as possible (this card is called “honor card”). Note that tractor can be treated as several pairs or shorter tractors, and pair can be treated as two single cards. The winner of this trick is the one who plays the highest-ordered “honor card”. Similarly, if more than one player played the same highest-ordered “honor card” the winner of this trick will be the one who plays the highest-ordered “honor card” first.
There are many hair-raising rules about lead and follow cards; fortunately, they’re not related to this problem, the only thing we care about is: when someone leads a “not-trump” “throw” the only possible way to beat it is to “throw” the same structure of “trumps”. And it’s impossible to beat a leading “trump” “throw”.
Special attention on the examples below. In these examples, Alice always leads cards. And assume in all the following examples, the CR is 7, and the main suit is H.
There is a special rule about “hidden cards”: if the winner of the last trick of a certain round is a member of FT, then, in addition, the FT gets the sum of the hidden cards’ pts, multiplied by 2w (2 to the power of w). When the structure of the final trick is not “throw”, then w is the number of lead cards of the last trick of this round. If the structure is “throw” instead, w is the length of the longest components, in the example RJRJBJBJH7H7HQHQHJHJH6H6HA, the w is 6 because the length of RJRJBJBJH7H7 (the longest components of the “throw”) is 6.
To make the problem easier, you are only to write a single-round tractor game simulator.
输入:
For each test case:
The first line contains the main suit of this round (H, S, C, D, O; O denotes “None” in this round), the dealer of this round, the CR of team 1, the CR of team 2, separated by single spaces. Each of the rest lines contains 4 strings: the lead cards and the cards played by the second, third and last player. In one string, the cards can be given in any order. Each player will play exactly 25 cards in one round.
You may assume the input is always valid.
There is a blank line between consecutive test cases, and a blank line also appears between T and the first test case.
输出:
For each test case:
The first line contains the main suit of this round (H, S, C, D, O; O denotes “None” in this round), the dealer of this round, the CR of team 1, the CR of team 2, separated by single spaces. Each of the rest lines contains 4 strings: the lead cards and the cards played by the second, third and last player. In one string, the cards can be given in any order. Each player will play exactly 25 cards in one round.
You may assume the input is always valid.
There is a blank line between consecutive test cases, and a blank line also appears between T and the first test case.

不错，赞一个！
约瑟夫也用说这么长……很成熟的一个问题了，分治的方法解起来o(n)就可以了，有兴趣可以看看具体数学的第一章，关于约瑟夫问题推导出了一系列的结论，很漂亮
不错，再多来的CF上面的题
还是有些难度的！
刚开始学习，为啥会报错了
网站不错，支持一个
文章写得挺好，就是最后的斐波那契那个没有看明白
第一种方法怎么会是O(log(m+n))呢？没有二分的话直接遍历应该就是O(m+n)吧？
这个分析相当全面，经典！
第二个方法挺不错。NewHead代表新的头节点，通过递归找到最后一个节点之后，就把这个节点赋给NewHead，然后一直返回返回，中途这个值是没有变化的，一边返回一边把相应的指针方向颠倒，最后结束时返回新的头节点到主函数。


| 013:013 Khan | : |
And Ar-Ra'd (thunder) glorifies and praises Him, and so do the angels because of His Awe, He sends the thunderbolts, and therewith He strikes whom He wills, yet they (disbelievers) dispute about Allah. And He is Mighty in strength and Severe in punishment. |
| 013:013 Maulana | : |
And the thunder celebrates His praise, and the angels too for awe of Him. And He sends the thunderbolts and smites with them whom He pleases, yet they dispute concerning Allah, and He is Mighty in prowess. |
| 013:013 Pickthal | : |
The thunder hymneth His praise and (so do) the angels for awe of Him. He launcheth the thunderbolts and smiteth with them whom He will while they dispute (in doubt) concerning Allah, and He is mighty in wrath. |
| 013:013 Rashad | : |
The thunder praises His glory, and so do the angels, out of reverence for Him. He sends the lightning bolts, which strike in accordance with His will. Yet, they argue about GOD, though His power is awesome. |
| 013:013 Sarwar | : |
Both the thunder and the angels glorify Him and out of His fear always praise Him. He sends down thunder-bolts to strike whomever He wants, while they are busy arguing about the existence of God. His punishment is stern. |
| 013:013 Shakir | : |
And the thunder declares His glory with His praise, and the angels too for awe of Him; and He sends the thunderbolts and smites with them whom He pleases, yet they dispute concerning Allah, and He is mighty in prowess. |
| 013:013 Sherali | : |
And the thunder glorifies HIM with HIS praise and likewise do the angels for awe of HIM; and HE sends the thunderbolts, and smites therewith whom HE wills, yet they dispute concerning ALLAH, while HE is Severe in punishing. |
| 013:013 Yusufali | : |
Nay, thunder repeateth His praises, and so do the angels, with awe: He flingeth the loud-voiced thunder-bolts, and therewith He striketh whomsoever He will..yet these (are the men) who (dare to) dispute about Allah, with the strength of His power (supreme)! |
Concepts/Themes Covered: أركان الإسلام > التوحيد > توحيد الله تعالي > صفات الله تعالى > شديد المِحال Pillars of Islam> Islamic> Oneness of Allah> His Glory's Characteristics> Mighty in Strength and Severe in Punishment أركان الإسلام > التوحيد > توحيد الله تعالي > وحدانيته Pillars of Islam> Islamic> Oneness of Allah> Singularity and Being Unique الإيمان > الله جلّ جلاله > خشيته جلّ وعلا Faith> Allah, Glory to his Majesty> To Fear Allah الإيمان > الملائكة > الإيمان بهم Faith> The Angels> To Believe in them
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


Select a floating IP address to associate with the load balancer or a floating IP pool in which to allocate a new floating IP address.


---
layout: default
title: People
subtitle: People in Liu Lab
permalink: /people
---
People
Current lab members
- X. Shirley Liu, PhD (Principle Investigator)
{% for people in site.people %}
{% if people.status == "current" and people.title != "shirley_liu" and people.position != "Visiting Scholar" %}
- {{people.pname}} ({{people.position}})
{% endif %}
{% endfor %}
Alumni with at least six month stay
Postdoc Fellows and Current Status
- Peng Jiang, PhD. Investigator at Cancer Data Science Laboratory, Bethesda, MD.
- Jingyu Amy Peng, PhD. (2016-2019), Scientist at Bluebird Bio, Cambridge, MA
- Xihao (Sherlock) Hu, PhD. (2016-2019), Chief Scientist at GV20 Therapeutics LLC, Boston, MA
- Wei Li, Ph.D. (2012-2018), Assistant Professor at Children’s National Medical Center, Washington, D.C.
- Bo Li, Ph.D. (2014-2017), Assistant Professor at UT Southwestern.
- Tengfei Xiao, Ph.D. (2013-2017), Chief Technology Officer at XBH Biotechnology
- Eduardo G. Gusmao, Ph.D. (2016-2017), Research Fellow, University of Cologne, Dr. Argyris Papantonis Lab, Cologne, Germany
- Teng Fei, Ph.D. (2011-2017), Principal Investigator, College of Life and Health Sciences, Northeastern University of China
- Chongzhi Zang (2010-2016), Assistant Professor, Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia.
- Johannes Koster (2015-2016) Group Leader, Institute of Human Genetics, University of Duisburg-Essen in Germany.
- Graham McVicker (2013-2015) Assistant Professor, Salk Institute, La Jolla, California
- Han Xu (2010-2015) Assistant Professor, UT MD Anderson Cancer Center
- Yiwen Chen (2009-2014) Assistant Professor, UT MD Anderson Cancer Center
- H. Hansen He (2008-2013) Associate Professor, at the University of Toronto
- Tao Liu (2007-2012) Assistant Professor of Oncology, Roswell Park Comprehensive Cancer Center
- Zhenhua Jeremy Wu (2008-2012) Bioinformatics Scientist, H3 Biomedicine
- Shunmin He (2010-2011) Associate Professor, Key Laboratory of Zoological Systematics and Evolution, Chinese Academy of Sciences
- Hyunjin Gene Shin (2007-2011) Scientist, Millennium Pharmaceuticals: The Takeda Oncology Company, Cambridge, MA
- Utz Pape (2009-2010) Statistician, Department of Public Health, Imperial College, United Kingdom
- Xiangfeng Wang (2008-2010) Professor at the Department of Plant Genetics at Chinese Agricultural University
- Yong Zhang (2006-2009) Professor, Department of Bioinformatics, Tongji University, China
- Jun Song (2005-2007) Professor, Institute for Genomic Biology, University of Illinois at Urbana-Champaign
- Wei Li (2004-2007) Professor, Department of Molecular and Cellular Biology, Dan L. Duncan Cancer Center, Baylor School of Medicine
Students and current status
- Evan Johnson, PhD (2004-2007) Associate Professor, Department of Medicine, Boston University
- Kaveh Maghsoudi, MD / PhD (2005-2008) Radiologist at Coastal Radiation Oncology, California
- Ying Lei (2008-2009) PhD candidate, Dept of Bioengineering, Stanford University
- Arjun Kumar Manrai (2006-2008) PhD candidate, Health Sciences and Technology Program, Harvard-MIT


The much-loved Factorio finally has a 1.0 release date
End of line.
News by Wesley Yin-Poole, Deputy Editor Updated on 16 November 2019
The much-loved Factorio finally has a 1.0 release date: 25th September 2020.
The date was revealed in a post by Prague-based studio Wube Software, which said development on the game "is taking way too long".
Factorio, an engineer simulator about building and creating automated factories to produce items in a 2D world, launched on Steam as an early access title in February 2016 and quickly met with a very positive reception. But development began back in 2012. It'll hit 1.0 eight years later.
"The approach 'It is done when it is done' was serving us well to deliver a high quality product, but if we continued this way, we would be doing it basically forever," the developers said.
"A lot of us don't have any problem working on Factorio for some more time, but the main problem is that we would like to introduce new features and content instead of just polishing parts that are already present in the game. We also considered that the game is quite polished now, and if we just pushed the button to release 1.0, it wouldn't be a catastrophe. From our perspective, a lot of things wouldn't be finished, but from the perspective of a new player, the things we are working on now are mainly nitpicks."
The release of version 1.0 does not mean development on the game will end, the developers stressed. "Once the 1.0 happens, we can have some rest and after that, we can finally focus on the content and features again."


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I'm a computer science student and an iOS developer from Missouri. I have been messing with computers for about 16 years now. Received a student scholarship to attend WWDC 2015 in San Francisco. Let's chat!
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Comments
-
Greg Hurrell
Ok, thanks for the info Ian. Are you aware of anything on your system that might be altering the Synergy Advance binary? ie. have you run any stripping or rebinding tools on it?
I may have to send you a new build with a bunch of logging statements in it so that we can find out at exactly what point the anti-corruption tests are failing.
-
froodiantherapy
Hi Wincent. No, I don't know of anything that would have altered my Synergy Advance binary. I'd be happy to run a logging build.
-
Greg Hurrell
Ok, I've put a new build up on the server that includes logging statements at every point in the program where a -100 error might be produced. If you can run this and let me know what gets printed to the console then it will help me know exactly where the failure is occurring.
One way of capturing all the console output is to run the program from the Terminal; for example, assuming you installed the app into "/Applications/" you would do:
cd "/Applications/Synergy Advance.app/Contents/MacOS" "./Synergy Advance"
Announcement:
https://wincent.com/a/news/archives/2006/04/synergy_advance_5.php
Direct download link:
https://wincent.com/download.php?item=SynergyAdvance0.4b2.dmg
SHA1 checksum:
e2e537d178e62c13d2846aed9c49f61ea3cf1c93
-
froodiantherapy
Hi Wincent, console says
2006-04-01 11:01:50.925 Synergy Advance[28337] **** 8: NO, YES
and then gives the -100 error
-
Greg Hurrell
Thanks for reporting back, Ian. What this tells us is that it's getting right to the end of the anti-corruption test and at the final step it encounters a mismatch between the checksum it *calculates* for the binary and the checksum that it *expects* to find.
So I am not sure exactly why the checksum is wrong (you say there's nothing altering the binary), but it may be related to bug #387 (once again in the anti-corruption code, although in that case it's actually crashing rather than aborting with an error).
Something very odd is going on because this code has been in place and working since the very first public release (back in May 2005), I haven't made any changes to that code, and it has always worked for me on both PowerPC and Intel, right up to the current version of Mac OS X (I'm currently running 10.4.5 on a G5); evidently *something* has changed in Mac OS X that is causing this to break for *some* users, but only when running the 0.4 beta, not the previous one. So in summary we have three variables: (1) a bunch of different versions of Mac OS X; (2) a couple of different versions of Synergy Advance; (3) a bunch of different users. It appears that some specific combinations of (1), (2) and (3) are experiencing problems, but the pattern is far from clear at this stage.
It's beginning to look like I may just have to switch off these anti-corruption checks entirely and hope that there are no problems down the road as a result later on. The reason I developed all this stuff is that Synergy (http://synergy.wincent.com/) has been hacked and cracked and tampered with so widely that I didn't want users being exposed to the risk of running versions that have been altered by untrusted third parties (trojans, spyware etc). This is why it's important to always download only from the wincent.com website and never trust a copy obtained from another source.
As I mention in that other bug I already have an alternative mechanism in place so I may just have to abandon this one and switch over. I don't like doing that because I invested a lot of time in developing this stuff, but it looks like it may just be too fragile and brittle. In any case, I'll post notification here once I have a new build available.
-
Greg Hurrell
OK, I've now officially deactivated the anti-corruption checks and removed the code. Adding the fixed-in-prerelease keyword. Will put together a 0.4b3 release shortly.
-
Greg Hurrell
Version 0.4b3 is now on the servers and available for download. For more information see:
https://wincent.com/a/news/archives/2006/04/synergy_advance_6.php
Marking as FIXED/CLOSED.
-
froodiantherapy
Hi Wincent. Just wanted to confirm that this WFM now. Thanks for the fast fix! :)
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