Optimal Strategy for the ICPC
问题描述 :
The following is taken from the official rules for the International Collegiate Programming Contest, as reported at http://www.acmicpc-pacnw.org/rules.htm.
The total time is the sum of the time consumed for each problem solved. The time consumed for a solved problem is the time elapsed from the beginning of the contest to the submittal of the first accepted run plus 20 penalty minutes for every previously rejected run for that problem. There is no time consumed for a problem that is not solved.
Quite simply, one element of the optimal strategy is not to have any erroneous submissions, so the androids do not have to worry about the penalty minutes. All that remains is to determine the order in which they should submit problems.
Let’s assume perfect knowledge ― hey, these androids are good ― so that they can make a very good estimate of the development time required for each of the problems. The task is to determine the order in which the problems should be submitted. The androids realize that their best approach is for each to think independently about different problems rather than having all three work on a single problem. Furthermore, each android types infinitely fast, and does not use the computer terminal while thinking. Hence, up to three problems can be simultaneously in progress at any given time, and it is actually possible for all three bots to submit a problem within the same minute. For the same reason, the number of problems posed is larger than those posed in the contest for biological entities. Being innately fussy, if there are multiple ways to submit the problems and obtain the same score, they will submit the problem order that comes lexicographically first.
Determine the algorithm to solve the most problems and to obtain the best possible score for those problems. Then implement it.
输入:
输出:
样例输入:
4 9 25 50 100 150 100 100 150 225 300 10 60 120 99 129 15 150 225 135 50 123 12 6 60 99 45 135 66 231 63 96 39 50 123 15 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75
样例输出:
Data set 1: A B C D E F G H 8 1450 Data set 2: E I A J C B F H D 9 1473 Data set 3: A J D B K F H I C E L 11 1452 Data set 4: A B C D E F G H I J K L 12 2250
/** * ID: ping128 * LANG: C++ */ #include <stdio.h> #include <iostream> #include <sstream> #include <stdlib.h> #include <string> #include <vector> #include <set> #include <queue> #include <stack> #include <list> #include <math.h> #include <algorithm> #include <map> #include <string.h> using namespace std; typedef long long LL; typedef pair<int, char>PII; typedef pair<PII, int>PII2; PII in[20]; int n; int maxSolve = 0, minnTime; PII order[20]; PII ans[20]; void search(int a, int b, int c, int at, int t) { if(a > 300) return ; if(b > 300) return ; if(c > 300) return ; if(at > maxSolve) { maxSolve = at; minnTime = t; for(int i = 0; i < at; i++ ) ans[i] = order[i]; } else if(at == maxSolve) { if(t < minnTime) { minnTime = t; for(int i = 0; i < at; i++ ) ans[i] = order[i]; } else if(t == minnTime) { sort(ans, ans + maxSolve); PII temp[20]; for(int i = 0; i < maxSolve; i++ ) temp[i] = order[i]; sort(temp, temp + maxSolve); int swap = 0; for(int i = 0; i < maxSolve; i++ ) { if(temp[i].second < ans[i].second) { swap = 1; break; } else if(temp[i].second > ans[i].second) { break; } } if(swap) { for(int i = 0; i < maxSolve; i++ ) ans[i] = temp[i]; } } } if(at == n) return ; order[at] = PII(a + in[at].first, in[at].second); search(a + in[at].first, b, c, at + 1, t + a + in[at].first); order[at] = PII(b + in[at].first, in[at].second); search(a, b + in[at].first, c, at + 1, t + b + in[at].first); order[at] = PII(c + in[at].first, in[at].second); search(a, b, c + in[at].first, at + 1, t + c + in[at].first); } class Solve { public: void main2() { cin >> n; for(int i = 0; i < n; i++ ) { cin >> in[i].first; in[i].second = 'A' + i; } sort(in, in + n); maxSolve = 1; minnTime = in[0].first; order[0] = PII(in[0].first, in[0].second); search(in[0].first, 0, 0, 1, in[0].first); sort(ans, ans + maxSolve); for(int i = 0; i < maxSolve; i++ ) printf("%c ", ans[i].second); printf("%d %d\n", maxSolve, minnTime); // puts(""); } }; int main() { // freopen("f.in.cpp", "r", stdin); // freopen("ff.out", "w", stdout); int Test; scanf("%d", &Test); for(int t = 1; t <= Test; t++ ) { Solve ___test; printf("Data set %d: ", t); ___test.main2(); } //while(1); return 0; }
为什么暴力求解方法循环到sqrt(n) 就可以了呢
很好，注释很详细啊
可以参考算法导论中的时间戳。就是结束访问时间，最后结束的顶点肯定是入度为0的顶点，因为DFS要回溯
88行是多余的，可以删除
对，就是把这32位当成一个长度为32的数
这怎么用Catalan数啊？求解答！
此题的样例描述不正确
真心不错，力顶作者
第二个方法好！


list(@rest obj1, ...)
Return a new list with obj1, ...
as elements.
A new list can also be constructed using the literal syntax: [obj1, ...]
list()
// []
list(1, 2, 3) == [1, 2, 3]
// true
let xs = [10, 20, 30]
xs[1]
// 20
xs[1] = "hi"
xs
// [10, hi, 30]
// list comprehensions:
[x * y | x <- range(1, 2), y <- range(10, 12)]
// [10, 11, 12, 20, 22, 24]


I love creating products in the computer industry I have been working mostly on application development and frontend on various platforms: Java Mobile, Qt, Android, Web... I have had experiences in various aspects of product development: developer, architect, team lead, tech lead, product manager and UX lead.


nips nips2002 nips2002-67 nips2002-67-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Ehud Ben-reuven, Yoram Singer
Abstract: Time difference of arrival (TDOA) is commonly used to estimate the azimuth of a source in a microphone array. The most common methods to estimate TDOA are based on ﬁnding extrema in generalized crosscorrelation waveforms. In this paper we apply microphone array techniques to a manikin head. By considering the entire cross-correlation waveform we achieve azimuth prediction accuracy that exceeds extrema locating methods. We do so by quantizing the azimuthal angle and treating the prediction problem as a multiclass categorization task. We demonstrate the merits of our approach by evaluating the various approaches on Sony’s AIBO robot.
[1] C. H. Knapp and G. C. Carter. The generalized correlation method for estimation of time delay. IEEE Transactions on ASSP, 24(4):320-327,1976.
[2] M. Omologo and P. Svaizer. Acoustic event localization using a crosspowerspectrum phase based technique. Proceedings of ICASSP1994, Adelaide, Australia, 1994.
[3] T. Gustafsson and B.D. Rao. Source Localization in Reverberant Environments: Statistical Analysis. Submitted to IEEE Trans. on Speech and Audio Processing, 2000.
[4] N. Strobel and R. Rabenstein. Classiﬁcation of Time Delay Estimates for Robust Speaker Localization ICASSP, Phoenix, USA, March 1999.
[5] J. Benesty Adaptive eigenvalue decomposition algorithm for passive acoustic source localization J. Acoust. Soc. Am. 107 (1), January 2000
[6] K. Crammer and Y. Singer. Ultraconservative online algorithms for multiclass problems. In Proc. of the 14th Annual Conf. on Computational Learning Theory, 2001.
[7] R. O. Duda, P. E. Hart. Pattern Classiﬁcation. Wiley, 1973.
[8] B. Porat. A course in Digital Signal Processing. Wiley, 1997.
[9] F. Rosenblatt. The Perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review, 65:386–407, 1958.
[10] B. Widrow and M. E. Hoff. Adaptive switching circuits. 1960 IRE WESCON Convention Record, pages 96–104, 1960.
[11] P. Aarabi, A. Mahdavi. The Relation Between Speech Segment Selectivity and Time-Delay Estimation Accuracy. In Proc. of IEEE Conf. on Acoustics Speech and Signal Processing, 2002.


|
Final | |||||||||||
| PREV LETTER NEXT LETTER | FRAMES NO FRAMES |
Name
interface represents a name in a naming service.
NamingException
used when trying to add a name
which is already bound.
NameAlreadyBoundException
instance
with all data initialized to null.
NameAlreadyBoundException
instance
with the specified message.
NameClassPair
associates a name in a naming service with a
specified class name and also with a relative flag. NameClassPair
from a name and a class.
NameClassPair
from a name, a class and a
relative flag.
NamingException
used when part of a name cannot
be found.
NameNotFoundException
instance
with all data initialized to null.
NameNotFoundException
instance
with the specified message.
NameParser
is used to validate and decompose a name from a
particular namespace. NamingEnumeration
interface is an Enumeration
which has been extended to support NamingException
s. NamingEvent
with all parameters.
NamingException
is the basic exception thrown by the naming
classes. NamingException
instance
with all data initialized to null.
NamingException
instance
with the specified message.
NamingException
.NamingExceptionEvent
instance with
a EventContext
and a NamingException
.
NamingManager
class should not be instantiated although it
can be extended by classes within the javax.naming.spi
package -
see DirectoryManager
. NamingSecurityException
is the NamingException
used when a security exception is encountered. NamingSecurityException
instance
with all data initialized to null.
NamingSecurityException
instance
with the specified message.
LdapContext
using the supplied
controls.
URLClassLoader
.
URLClassLoader
.
int
value of the number of bits
specified by the argument bits
as described by Donald E.
int
value from the this random number sequence.
int
value
between 0 (inclusively) and the specified n (exclusively).
int
value from the this random number sequence.
NoInitialContextException
is the exception thrown by the
naming classes when an initial context cannot be created. NoInitialContextException
instance
with all data initialized to null.
NoInitialContextException
instance with the
specified error message.
Control
is not critical.
NoPermissionException
is the NamingSecurityException
used when a server refuses permission to the client.
NoPermissionException
instance
with all data initialized to null.
NoPermissionException
instance
with the specified message.
NoSuchAttributeException
with given message.
NotContextException
is the exception thrown by the naming
classes when an operation on a context object cannot proceed because the
resolved object is not a context type. NotContextException
instance
with all data initialized to null.
NotContextException
instance
with a specified error message.
wait
ing on the
receiver to be made ready to run.
wait
ing on the
receiver to be made ready to run.
update()
method for
every Observer in the list of observers using null as the argument.
update()
method for
every Observer in the list of observers using the specified argument.
ttype
is TT_NUMBER
)
|
Final | |||||||||||
| PREV LETTER NEXT LETTER | FRAMES NO FRAMES |


delete(accountId, webPropertyId, customDataSourceId, date, type)
Delete uploaded data for the given date.
List daily uploads to which the user has access.
Update/Overwrite data for a custom data source.
delete(accountId, webPropertyId, customDataSourceId, date, type)
Delete uploaded data for the given date. Args: accountId: string, Account Id associated with daily upload delete. (required) webPropertyId: string, Web property Id associated with daily upload delete. (required) customDataSourceId: string, Custom data source Id associated with daily upload delete. (required) date: string, Date for which data is to be deleted. Date should be formatted as YYYY-MM-DD. (required) type: string, Type of data for this delete. (required) Allowed values cost - Value for specifying cost data upload.
list(accountId, webPropertyId, customDataSourceId, start_date, end_date, max_results=None, start_index=None)
List daily uploads to which the user has access. Args: accountId: string, Account Id for the daily uploads to retrieve. (required) webPropertyId: string, Web property Id for the daily uploads to retrieve. (required) customDataSourceId: string, Custom data source Id for daily uploads to retrieve. (required) start_date: string, Start date of the form YYYY-MM-DD. (required) end_date: string, End date of the form YYYY-MM-DD. (required) max_results: integer, The maximum number of custom data sources to include in this response. start_index: integer, A 1-based index of the first daily upload to retrieve. Use this parameter as a pagination mechanism along with the max-results parameter. Returns: An object of the form: { # A daily upload collection lists Analytics daily uploads to which the user has access. Each resource in the collection corresponds to a single Analytics daily upload. "username": "A String", # Email ID of the authenticated user "kind": "analytics#dailyUploads", # Collection type. Value is analytics#dailyUploads. "items": [ # A collection of daily uploads. { # Metadata for daily upload entity. "recentChanges": [ # Change log for last 10 changes in chronological order. { "change": "A String", "time": "A String", }, ], "kind": "analytics#dailyUpload", # Resource type for Analytics daily upload. "modifiedTime": "A String", # Time this daily upload was last modified. "appendCount": 42, # Number of appends for this date. "customDataSourceId": "A String", # Custom data source ID to which this daily upload belongs. "date": "A String", # Date associated with daily upload. "webPropertyId": "A String", # Web property ID of the form UA-XXXXX-YY to which this daily upload belongs. "createdTime": "A String", # Time this daily upload was created. "parentLink": { # Parent link for a daily upload. Points to the custom data source to which this daily upload belongs. "href": "A String", # Link to the custom data source to which this daily upload belongs. "type": "analytics#customDataSource", # Value is "analytics#customDataSource". }, "selfLink": "A String", # Link for this daily upload. "accountId": "A String", # Account ID to which this daily upload belongs. }, ], "itemsPerPage": 42, # The maximum number of resources the response can contain, regardless of the actual number of resources returned. Its value ranges from 1 to 1000 with a value of 1000 by default, or otherwise specified by the max-results query parameter. "previousLink": "A String", # Link to previous page for this daily upload collection. "startIndex": 42, # The starting index of the resources, which is 1 by default or otherwise specified by the start-index query parameter. "nextLink": "A String", # Link to next page for this daily upload collection. "totalResults": 42, # The total number of results for the query, regardless of the number of results in the response. }
upload(accountId, webPropertyId, customDataSourceId, date, appendNumber, type, reset=None, media_body=None)
Update/Overwrite data for a custom data source. Args: accountId: string, Account Id associated with daily upload. (required) webPropertyId: string, Web property Id associated with daily upload. (required) customDataSourceId: string, Custom data source Id to which the data being uploaded belongs. (required) date: string, Date for which data is uploaded. Date should be formatted as YYYY-MM-DD. (required) appendNumber: integer, Append number for this upload indexed from 1. (required) type: string, Type of data for this upload. (required) Allowed values cost - Value for specifying cost data upload. reset: boolean, Reset/Overwrite all previous appends for this date and start over with this file as the first upload. media_body: string, The filename of the media request body, or an instance of a MediaUpload object. Returns: An object of the form: { # Metadata returned for a successful append operation. "kind": "analytics#dailyUploadAppend", # Resource type for Analytics daily upload append. "customDataSourceId": "A String", # Custom data source Id to which this daily upload append belongs. "appendNumber": 42, # Append number. "webPropertyId": "A String", # Web property Id of the form UA-XXXXX-YY to which this daily upload append belongs. "date": "A String", # Date associated with daily upload append. "nextAppendLink": "A String", "accountId": "A String", # Account Id to which this daily upload append belongs. }


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How deploying AWS Lambda with Terraform is a Win-Win
In this blog post I will demonstrate how selecting the best tool for the job in the end can pay off resulting in both reduced complexity and lower costs.
I was recently tasked with exporting CloudWatch logs from multiple AWS accounts into Grafana Loki, hosted in a central logging AWS account. My architecture leverages the event driven design pattern of subscribing a log sender Lambda function to a set of CloudWatch log groups. The Lambda function is triggered as logs are written to each log group. I then funnel the logs from each account into a single AWS SQS FIFO (First-In-First-Out) queue residing in the central logging account. At the receiving end, a log router lambda which gets triggered by SQS when messages arrive on the queue. I use this Lambda to route log records to instances of Fluent-Bit (blog post coming soon) and from there into Grafana Loki and Prometheus metrics (more the metrics in a future blog post).
This architecture works well, however I ran into a limitation I’d not experienced before. Till now I’ve mostly leveraged Serverless Framework for deploying Lambda code to AWS. Serverless Framework generates a CloudFormation Template from it’s YAML configuration files which deploys the Lambda code and any additional infrastructure required to operate. It turns out the maximum number of resources that a single CloudFormation Template (CFT) can contain is 500. When deploying the architecture described above, roughly every 20 log groups requires a new CFT stack as that limit is quickly exceeded . This also means a new copy of the same Lambda with a different name for every 20 log groups. This is quickly becomes maintenance nightmare in the making.
Terraform to the rescue! Unlike CloudFormation, Terraform interacts directly with AWS APIs to create and destroy resources. As a result, there is no maximum resource limit.
Using one of the Serverless Framework generated CFTs as a guide, I developed an equivalent Terraform project.
Result:
It works very nicely!
Aside from the accomplishing the goal of overcoming the 500 max resource limitation, a couple of bonus benefits came with the Terraform implementation.
Firstly, equivalent deployments can now see a reduction of roughly 10:1 in the required resource count and as a result, a lower cost.
Ex. Single lambda subscribed to 47 log groups:
| Method | Resource count |
|---|---|
| Serverless Framework | ~1200 |
| Terraform | ~100 |
Secondly, changes to the Lambda function code or subscribed Log groups can be made with zero impact.
To summarize, in this specific case, deciding to deviate from the norm and rewrite the deployment automation using using Terraform rather than industry tested Serverless Framework, resulted in a huge pay off. Simpler maintenance and a lower AWS bill are definitely win-wins for any organization.
Resources referenced:
https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/SubscriptionFilters.html#LambdaFunctionExample https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/cloudformation-limits.html https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/FIFO-queues.html https://www.serverless.com/ https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/lambda_function https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/cloudwatch_log_subscription_filter


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--- layout: page title: About Me description: This is what I do. background: '/img/bg-about.jpg' ---
Ashutosh Shashi is a visionary and innovative technologist with customer focus, creativity, passion, industry experience, and leadership skills. He is an architect, trainer, and writer
He completed "Master in Computer Applications" in 2004
He has TOGAF 9, Project Management Professional (PMP), Microsoft Azure Architect Technology, AWS Solutions Architect - Associate, DataStax Apache Cassandra Professional, Oracle Java SE 8 Programmer, Scrum Product Owner, and Scrum Master certifications


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Enable audit logging on UCP
Estimated reading time: 5 minutesAudit logs are a chronological record of security-relevant activities by individual users, administrators or software components that have affected the system. They are focused on external user/agent actions and security rather than understanding state or events of the system itself.
Audit Logs capture all HTTP actions (GET, PUT, POST, PATCH, DELETE) to all UCP API, Swarm API and Kubernetes API endpoints that are invoked (except for the ignored list) and sent to Docker Engine via stdout. Creating audit logs is a UCP component that integrates with Swarm, K8s, and UCP APIs.
Logging levels
To allow more control to administrators over the audit logging, three audit logging levels are provided:
-
None: audit logging is disabled
- Metadata: includes the following:
- Method and API endpoint for the request
- UCP user who made the request
- Response Status (success or failure)
- Timestamp of the call
- Object ID of any created or updated resource (for create or update API calls). We do not include names of created or updated resources
- License Key
- Remote Address
- Request: includes all fields from the Metadata level as well as the request payload.
Once UCP audit logging has been enabled, audit logs can be found within the container logs of the
ucp-controller
container on each UCP manager node. Please ensure you have a logging driver configured appropriately with log rotation set as audit logging can start to generate a lot of data.
Benefits
You can use audit logs to help with the following use cases:
-
Historical Troubleshooting - Audit logs are helpful in determining a sequence of past events that explain why an issue occured.
-
Security Analysis and Auditing - Security is one of the primary uses for audit logs. A full record of all user interactions with the container infrastructure gives your security team full visibility to questionable or attempted unauthorized accesses.
-
Chargeback - You can use audit logs and information about the resources to generate chargeback information.
-
Alerting - If there is a watch on an event stream or a notification created by the event, alerting features can be built on top of event tools that generate alerts for ops teams (PagerDuty, OpsGenie, Slack, or custom solutions).
Enabling UCP Audit Logging
UCP audit logging can be enabled via the UCP web user interface, the UCP API or via the UCP configuration file.
Enabling UCP Audit Logging via UI
1) Log in to the UCP Web User Interface
2) Navigate to Admin Settings
3) Select Audit Logs
4) In the Configure Audit Log Level section, select the relevant logging level.
5) Click Save
Enabling UCP Audit Logging via API
-
Download the UCP Client bundle Download client bundle from the command line.
-
Retrieve JSON for current audit log configuration.
export DOCKER_CERT_PATH=~/ucp-bundle-dir/ curl --cert ${DOCKER_CERT_PATH}/cert.pem --key ${DOCKER_CERT_PATH}/key.pem --cacert ${DOCKER_CERT_PATH}/ca.pem -k -X GET https://ucp-domain/api/ucp/config/logging > auditlog.json
-
Open auditlog.json to modify the ‘auditlevel’ field to
metadata
orrequest
.{ "logLevel": "INFO", "auditLevel": "metadata", "supportDumpIncludeAuditLogs": false }
-
Send the JSON request for the auditlog config with the same API path but with the
PUT
method.curl --cert ${DOCKER_CERT_PATH}/cert.pem --key ${DOCKER_CERT_PATH}/key.pem --cacert ${DOCKER_CERT_PATH}/ca.pem -k -H "Content-Type: application/json" -X PUT --data $(cat auditlog.json) https://ucp-domain/api/ucp/config/logging
Enabling UCP Audit Logging via Config File
Enabling UCP audit logging via the UCP Configuration file can be done before or after a UCP installation. Following the UCP Configuration file documentation here.
The section of the UCP configuration file that controls UCP auditing logging is:
[audit_log_configuration]
level = "metadata"
support_dump_include_audit_logs = false
The supported variables for level
are ""
, "metadata"
or "request"
.
Important: The
support_dump_include_audit_logs
flag specifies whether user identification information from the ucp-controller container logs is included in the support dump. To prevent this information from being sent with the support dump, make sure thatsupport_dump_include_audit_logs
is set tofalse
. When disabled, the support dump collection tool filters out any lines from theucp-controller
container logs that contain the substringauditID
.
Accessing Audit Logs
The audit logs are exposed today through the ucp-controller
logs. You can
access these logs locally through the Docker cli or through an external
container logging solution, such as ELK
Accessing Audit Logs via the Docker Cli
1) Source a UCP Client Bundle
2) Run docker logs
to obtain audit logs. In the following example,
we are tailing the command to show the last log entry.
$ docker logs ucp-controller --tail 1
{"audit":{"auditID":"f8ce4684-cb55-4c88-652c-d2ebd2e9365e","kind":"docker-swarm","level":"metadata","metadata":{"creationTimestamp":null},"requestReceivedTimestamp":"2019-01-30T17:21:45.316157Z","requestURI":"/metricsservice/query?query=(%20(sum%20by%20(instance)%20(ucp_engine_container_memory_usage_bytes%7Bmanager%3D%22true%22%7D))%20%2F%20(sum%20by%20(instance)%20(ucp_engine_memory_total_bytes%7Bmanager%3D%22true%22%7D))%20)%20*%20100\u0026time=2019-01-30T17%3A21%3A45.286Z","sourceIPs":["<IP_ADDRESS>:48516"],"stage":"RequestReceived","stageTimestamp":null,"timestamp":null,"user":{"extra":{"licenseKey":["FHy6u1SSg_U_Fbo24yYUmtbH-ixRlwrpEQpdO_ntmkoz"],"username":["admin"]},"uid":"4ec3c2fc-312b-4e66-bb4f-b64b8f0ee42a","username":"4ec3c2fc-312b-4e66-bb4f-b64b8f0ee42a"},"verb":"GET"},"level":"info","msg":"audit","time":"2019-01-30T17:21:45Z"}
Sample logs
Here is a sample audit log for a Kubernetes cluster.
{"audit"; {
"metadata": {...},
"level": "Metadata",
"timestamp": "2018-08-07T22:10:35Z",
"auditID": "7559d301-fa6b-4ad6-901c-b587fab75277",
"stage": "RequestReceived",
"requestURI": "/api/v1/namespaces/default/pods",
"verb": "list",
"user": {"username": "alice",...},
"sourceIPs": ["<IP_ADDRESS>"],
...,
"requestReceivedTimestamp": "2018-08-07T22:10:35.428850Z"}}
Here is a sample audit log for a Swarm cluster.
{"audit"; {
"metadata": {...},
"level": "Metadata",
"timestamp": "2018-08-07T22:10:35Z",
"auditID": "7559d301-94e7-4ad6-901c-b587fab31512",
"stage": "RequestReceived",
"requestURI": "/v1.30/configs/create",
"verb": "post",
"user": {"username": "alice",...},
"sourceIPs": ["<IP_ADDRESS>"],
...,
"requestReceivedTimestamp": "2018-08-07T22:10:35.428850Z"}}
API endpoints ignored
The following API endpoints are ignored since they are not considered security events and may create a large amount of log entries.
- /_ping
- /ca
- /auth
- /trustedregistryca
- /kubeauth
- /metrics
- /info
- /version*
- /debug
- /openid_keys
- /apidocs
- /kubernetesdocs
- /manage
API endpoint information redacted
Information for the following API endpoints is redacted from the audit logs for security purposes:
/secrets/create
(POST)/secrets/{id}/update
(POST)/swarm/join
(POST)/swarm/update
(POST) -/auth/login
(POST)- Kube secrete create/update endpoints


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Bruce Wang - Simple, Love, Courage
Gmail FAIL
Tue 05 July 2011
https://twitter.com/number5/status/88088849938522112
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 A lovely midweek trip awaits later in the year. Unfortunately, with Cambridge winning we've now slipped into the bottom four :-(
This week we've got a Birmingham Senior Cup tie against Birmingham City at The Grove on Tuesday, before a very interesting FA Trophy 3rd Round tie away to Unibond Division One side Alfreton Town next Saturday.
They're well clear at the top of their league, have scored loads of goals and beat Stafford Rangers in the last round so it's going to be a difficult tie. However, another form line shows they only beat Spennymoor 2-1 and are in a weaker league than ourselves, so it should be a very good game.
Let's hope our excellent Cup form continues - and the weather clears up a bit.


Before Change
self.model.set_params(**point_mapped)
try:
self.model.fit(X_train, y_train)
r = self.model.score(X_test, y_test)
except BaseException as ex:
r = 0.0 // on error: return assumed smallest value of objective function
After Change
if isinstance(model_instance, RegressorMixin): // r^2 metric
y_predicted = model_instance.predict(X_test)
score = r2_score(y_test, y_predicted)
elif isinstance(model_instance, ClassifierMixin): // log loss
y_predicted = model_instance.predict_proba(X_test)
score = -log_loss(y_test, y_predicted) // in the context of this function, the higher score is better
// avoid any kind of singularitites, eg probability being zero, and thus breaking the log_loss


Default Time Picker
Some default settings such as [displaySeconds]
, [displayMinutes]
,
[displayHours]
and [meridian]
are based on the
DateTimeFormats.display.timeInput
options.
For example if time picker format option contains hours, minutes and day period info then default options will be
the next:
[displaySeconds]="false"
, [displayMinutes]="true"
, [displayHours]="true"
and
[meridian]="true"
. The listed above options are applied to the Time component only and can be defined
explicitly if needed.
Time parsing/formatting
There are several ways to define your specific options to format and parse time.
-
Provide your own
DATE_TIME_FORMATS
and define
display/parse timeInput
option there.
-
Use time picker
[parseFormat]
and [displayFormat]
options. Please note that you
must provided these options in a format that is understandable by DateAdapter that is currently used in your
app.
Disabled Time Picker
Set [disabled]="true"
to disable the time picker.
Compact Time Picker
Set fdCompact
to use compact time-picker.
Null Validity
Null input values are considered valid by default. Use [allowNull]="false"
to make them invalid.
Time Picker in Form
The time-picker component may also be used together with Angular reactive forms.
Time Picker Locale
The time-picker component is listening to the DateTimeAdapter locale, this locale can be changed dynamically.


English language
English is a West Germanic language that was first spoken in early medieval England and is now a global lingua franca. English is either the official language or an official language in almost 60 sovereign states. It is the most commonly spoken language in the United Kingdom, the United States, Canada, Australia, Ireland, and New Zealand, and is widely spoken in some areas of the Caribbean, Africa, and South Asia.It is the third most common native language in the world, after Mandarin and Spanish. It is the most widely learned second language and an official language of the United Nations, of the European Union, and of many other world and regional international organisations. English has developed over the course of more than 1,400 years. The earliest forms of English, a set of Anglo-Frisian dialects brought to Great Britain by Anglo-Saxon settlers in the fifth century, are called Old English. Middle English began in the late 11th century with the Norman conquest of England. Early Modern English began in the late 15th century with the introduction of the printing press to London and the King James Bible, and the start of the Great Vowel Shift.Through the worldwide influence of the British Empire, modern English spread around the world from the 17th to mid-20th centuries. Through all types of printed and electronic media, as well as the emergence of the United States as a global superpower, English has become the leading language of international discourse and the lingua franca in many regions and in professional contexts such as science, navigation, and law.
Farid Karimov


Copenhagen, Denmark's capital, sits on the coastal islands of Zealand and Amager. It's linked to Malmo in southern Sweden by the Oresund Bridge. Indre By, the city's historic center, contains Frederiksstaden, an 18th-century rococo district, home to the royal family's Amalienborg Palace. Nearby is Christiansborg Palace and the Renaissance-era Rosenborg Castle, surrounded by gardens and home to the crown jewels.
1. Tivoli Gardens:
Tivoli Gardens in Copenhagen has been one of the most popular attractions in Denmark for a very long time. Second oldest amusement park in the world but still a fan favorite.
2. Bakken
oldest fairground in the world! Just north of Copenhagen you will find Dyrehavsbakken (Bakken) which is the world's oldest operating amusement park. With free entry this amusement park is also a very popular attraction in Denmark.
3. The original LEGOLAND:
Since it opened in 1968, the original LEGOLAND® has been wowing guests with a mixture of rides, special LEGO® exhibitions and the famous miniland. You can get here easily from the nearby Billund Airport and stay in the park, for a weekend of family fun in the home of LEGO®.
4. Copenhagen Zoo:
Combine a day out in the royal parks of Frederiksberg, Copenhagen, with a visit to Copenhagen Zoo. Located at the top of one of Copenhagen's tallest hills, you can also enjoy views of the city from the zoo's historical tower.
5. ARoS Aarhus Art Museum Aarhus:
distinctive modern art museum, ARoS, is a work of art in itself. Instagram yourself in the Your Rainbow Panorama rooftop installation, or explore the museum's many cultural exhibits throughout the year.
6. Djurs Sommerland:
Bring your entire family to Djurs Sommerland! Days of fun for all ages! Ready for speed, thrills and fun for all the family? One of the best attractions in Denmark for cooling off in the summer heat.
7. Louisiana Museum of Modern Art:
If you're into modern art and architecture, Louisiana Museum of Modern Art is an absolute must-see attraction in Denmark. Louisiana Museum of Modern Art is an old complex with a great view across the strait of Sweden from the gardens and café.
8. Lalandia Billund:
Treat your family to Scandinavia's biggest tropical holiday and activity center. Lalandia is in Billund, so you can fly to Billund Airport to get here, or drive for a few hours from Copenhagen to Jutland.
9. The Round Tower:
Copenhagen's iconic Round Tower is one of the oldest functioning observatories in Europe and a place where Hans Christian Andersen once wrote stories. Test your fear of heights at the Round Tower's glass platform! Read more Faarup sommerland
10. Faarup Sommerland Amusement Park:
Denmark's summerlands, or sommerlands, are a unique and traditional favorite with Danish families and Faarup Sommerland is one of Denmark's most visited.
1. Little Mermaid:
The Little Mermaid is a bronze statue by Edvard Eriksen, depicting a mermaid. The sculpture is displayed on a rock by the waterside at the Langelinie promenade in Copenhagen, Denmark. It is 1.25 metres tall and weighs 175 kilograms.
Address: Langelinie, 2100 Kobenhavn, Denmark
2. Nyhavn:
Nyhavn is one of the most iconic places in Copenhagen and a perfect spot to hang out in the sun or go for a canal tour.
Address: Nyhavn Kobenhavn K, Denmark
3. Christiania:
Freetown Christiania in Copenhagen is an alternative society with creative houses, art galleries, music venues, restaurants, and beautiful scenery.
Address: Freetown Christiania, Kobenhavn, Denmark
4. Kongens Have:
Rosenborg Castle Gardens is the oldest and most visited park in central Copenhagen, Denmark. Established in the early 17th century as the private gardens of King Christian IV's Rosenborg Castle.
Address: Oster Voldgade 4A, 1350 Kobenhavn, Denmark
5. The Round Tower:
Copenhagen's iconic Round Tower is one of the oldest functioning observatories in Europe and a place where Hans Christian Andersen once wrote stories. Test your fear of heights at the Round Tower's glass platform! Read more Faarup sommerland
Address: Kobmagergade 52A, 1150 Kobenhavn, Denmark
My grandma loves to grow roses in her garden.
Here's an article on gardening in denmark:
National flower of Denmark Image of Marguerite DaisyThe government of Denmark declared Marguerite Daisy botanically known as Argyranthemum Frutescens as the National Flower of the Country. Marguerites produce large, single, daisy-like flowers most of the summer. But Red Clover and English holly(Forget-me-not) also serve as flower emblems to Denmark. Other native and Popular Flower of Denmark Together with the soil composition, also the climatic factors are rather variable within Denmark and have an influence on the distribution of plants. Generally the western parts of the country has Atlantic climate and the eastern parts Continental climate. The flowers grown in Denmark are, Common Yellow Azalea(Rhododendron Luteum), Agrostocrinum Scabrum, Lady Orchid, Conostylis Aculeate, Grevillea Pulchella, Tassle Flower, Red Helleborine and Danish Orchids. While the famous flowers used for gifting purposes among Danes are, Sunflowers, Lilies, Gerbera Daisies, Orchids, Gladiolas and Roses.


THE REAL BLONDE
There are several things that make THE REAL BLONDE such a delight to watch. There's the sexy, fun story and realistic dialogue, both by Tom Dicillo, the fine acting by the entire cast which consists of some great names even in the smaller roles. Take Kathleen Turner as a powerful casting agent such as is found in the real world of TV and movies. There is Marlo Thomas as a top notch photographer who knows how to make a picture tell a story that is not true. And there is Buck Henry as a psychiatrist who would love to bed his patients. And Christopher Lloyd who runs a catering service that employs actors between gigs or those who have yet to get their first break, Finally, Denis Leary as a women's self-defense instructor who tries to come on to the women who have personal problems. Wrap all that together by a fine director and you have one very entertaining film.
The story and all the characters ring true. Joe (Matthew Madine) and his live-in lover Mary (Catherine Keener) appear to be about at the end of their relationship. While Mary is a make-up artist for TV and movies, Joe is still waiting for his first job, His only income is as a waiter. Obsessed with never accepting a minor part in a film as it would be too demeaning for someone who is as good as he thinks he is, he is always out of work, always shooting off his mouth and blowing his chances of ever getting cast. Mary has just about had it with him even if they are in love.
Bob (Maxwell Caulfield) is Joe's friend and fellow-actor (and waiter!). His problem is he wants to find a real blonde, someone who does not get her hair dyed; a natural. To this end he runs after every blonde he imagines will fill the bill. What he really wants is a woman whom he can love. Among those he chases are Kelly (Daryl Hannah in a superb performance) and Sahara (Bridgette Wilson) who is seen as the perfect body on huge billboards. Is he happy? Not at all.
Joe finally settles for a role as an extra with a hundred other men in a Madonna video. He has to play up to casting director Dee Dee Taylor (Kathleen Turner) in order to get the role. When Joe meets up with Tina, (Elizabeth Berkley) who is a Madonna double, his morality suffers as he takes her to bed. So much for HIS ethics.
One would hope that despite the film being released so early in the year, that come Oscar voting time in 1999, Matthew Modine and Daryl Hannah will be remembered.
The movie runs along rapidly as we get to know all the characters and meet those on their periphery who have a bearing on the story and on their lives. That there is not a dull moment in the film is a tribute to the fine direction..
Written and Directed by Tom DiCillo.
3.5 Bytes
4 Bytes = Superb 3 Bytes = Too good to miss 2 Bytes = Average 1 Byte = Save your money
Copyright 1998 Ben Hoffman
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


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Theme of InnovateNSUT
Covid-19 pandemic has revolutionized the digitalization process across world like never before. It has led to the creation of a minefield of unexplored opportunities. So, keeping in mind the existing situation and its repercussions across various spheres, come up with innovative hacks to facilitate/supplement the process of going contactless in the future, while keeping in mind implications on individual’s physical as well as mental health, along with the impact on workplace environment, reducing increasing strain on metropolitans as well as facilitating business and economic growth in the modern marketplace, targeting the following sectors:
- Education (EdTech)
- Heathcare
Your hacks may traverse across technological fields including, but not limited to:
- Gaming
- Cyber Security
- Blockchain
- Augmented Reality
- Virtual Reality
- Communication
Submission Guidelines
Once the hack phase begins, the submit button will become functional.
On clicking the submit button, you'll be taken to the submission page. Fill out the project details, submit your github repository link and include any other links required as project media or sponsored challenges (YouTube link, Google Drive link, etc.)
NOTE: A video demo is compulsory for the sponsored challenges.
If in a team, only the team leader should submit the hack, all participants need not submit.
Make sure to mention the technologies used (Matic, Ethereum, Tezos, Portis, AR/VR - echoAR) to be qualified for the sponsored challenge prizes.
To learn about Devfolio's guidelines Click Here.
Why you should participate in InnovateNSUT?
Reasons are the pillars of mind.
Get Inspired
Compete with creative project ideas and get inspiration for your next project.
Meet New Faces
Meet innovative new peers, make friends and connections.
Fresh Tech Insights
Learn about different tech stacks, see it in action and enhance your skills.
Prize Pool
Prize Pool of worth INR 4,00,000
(+ Certificate and Goodies)
Online Event
Participate in the competition at the ease of your comfort of sitting at home.
Free Swags
Get cool goodies and swags to show off to your friends.
Discord Server
Join our Dicord Server to stay updated!
Hackathon Timeline
A detailed timeline of
InnovateNSUT
Sat, 27th February
Registration Opens
Fri, 5th March
Release of Problem Statement
Wed, 10th March
Submission Deadline
Deadline ends for submission along with closing of registration.
Sat, 13th March
Preliminary Result
Teams selected for final presentation will be notified.
Sun, 14th March
Final Presentation
Our Judges will see the presentations.
Tue, 16th March
Final Result
Winner will be announced.
Event Partners
Determined people working together can do anything.
Associate Partners
Our Previous Partners
FAQs
Judge a person by his questions, not answers
© Designed and Developed by IOSD NSUT


alchi: translate "the big five" to four elements
Big Five
O =
50
C =
50
E =
50
A =
50
N =
50
Four Elements (
fire
earth
air
water
)
1 =
50
2 =
50
3 =
50
4 =
50


The freenode project has been supporting the use and development of Free and Open Source Software for 20 years this year, jobs.freenode.net is the latest addition to the service and aims to connect those looking to hire with the immense talent that can be found within the wider freenode communities. The service is free to use, but companies that find a successful match via the service are encouraged to make a donation to freenode to support the operations of the freenode network, jobs.freenode.net and the annual freenode #live conference.


ApnaOPD
Home
Patient
Doctor
Retailer
Order Medicines
Select Delivery Address:
[[city]], [[state]], [[pincode]]
Look for retailers by your city name or pincode :
By pincode
By city
Comment:
Select e-prescription :
select
1
2
3
4
OR
Upload


--- layout: page images: - image_path: /assets/images/GalleryTopo/topo00.jpg image_Thumb: /assets/images/GalleryTopo/topo00_tn.jpg title: topo00 - image_path: /assets/images/GalleryTopo/topo01.jpg image_Thumb: /assets/images/GalleryTopo/topo01_tn.jpg title: topo01 - image_path: /assets/images/GalleryTopo/topo02.jpg image_Thumb: /assets/images/GalleryTopo/topo02_tn.jpg title: topo02 - image_path: /assets/images/GalleryTopo/topo03.jpg image_Thumb: /assets/images/GalleryTopo/topo03_tn.jpg title: topo03 - image_path: /assets/images/GalleryTopo/topo04.jpg image_Thumb: /assets/images/GalleryTopo/topo04_tn.jpg title: topo04 - image_path: /assets/images/GalleryTopo/topo05.jpg image_Thumb: /assets/images/GalleryTopo/topo05_tn.jpg title: topo05 - image_path: /assets/images/GalleryTopo/topo06.jpg image_Thumb: /assets/images/GalleryTopo/topo06_tn.jpg title: topo06 - image_path: /assets/images/GalleryTopo/topo07.jpg image_Thumb: /assets/images/GalleryTopo/topo07_tn.jpg title: topo07 - image_path: /assets/images/GalleryTopo/topo08.jpg image_Thumb: /assets/images/GalleryTopo/topo08_tn.jpg title: topo08 - image_path: /assets/images/GalleryTopo/topo09.jpg image_Thumb: /assets/images/GalleryTopo/topo09_tn.jpg title: topo09 - image_path: /assets/images/GalleryTopo/topo10.jpg image_Thumb: /assets/images/GalleryTopo/topo10_tn.jpg title: topo10 - image_path: /assets/images/GalleryTopo/topo11.jpg image_Thumb: /assets/images/GalleryTopo/topo11_tn.jpg title: topo11 - image_path: /assets/images/GalleryTopo/topo12.jpg image_Thumb: /assets/images/GalleryTopo/topo12_tn.jpg title: topo12 - image_path: /assets/images/GalleryTopo/topo13.jpg image_Thumb: /assets/images/GalleryTopo/topo13_tn.jpg title: topo13 - image_path: /assets/images/GalleryTopo/topo14.jpg image_Thumb: /assets/images/GalleryTopo/topo14_tn.jpg title: topo14 - image_path: /assets/images/GalleryTopo/topo15.jpg image_Thumb: /assets/images/GalleryTopo/topo15_tn.jpg title: topo15 - image_path: /assets/images/GalleryTopo/topo16.jpg image_Thumb: /assets/images/GalleryTopo/topo16_tn.jpg title: topo16 lightbox: true permalink: /pages/GalleryTopo sidebar: nav: docs-en ---


{% extends "layout-side-nav.html" %} {% import "_vars-the-bureau.html" as vars with context %} {% set active_nav_id = 'about-steve-antonakes' %} {% block title -%} About Steve Antonakes {%- endblock %} {% block desc -%} About Steve Antonakes {%- endblock %} {% block content_main %} {% from "macros.html" import share as share %}
Steven L. Antonakes currently serves as the Deputy Director as well as the Associate Director for Supervision, Enforcement, and Fair Lending at the Consumer Financial Protection Bureau (CFPB).
He is responsible for the supervision of all banks and non-banks under the CFPB’s jurisdiction and the enforcement of federal consumer protection and fair lending laws. Mr. Antonakes previously served as the CFPB’s Assistant Director of Large Bank Supervision and was charged with establishing the consumer protection supervision program for the largest financial institutions in the country which collectively account for over 75 percent of the nation’s banking assets.
Mr. Antonakes began his professional career as an entry level bank examiner with the Commonwealth of Massachusetts Division of Banks in 1990. He later served in numerous managerial capacities before being appointed by successive Governors to serve as the Commissioner of Banks from December 2003 until November 2010, becoming only the second career bank examiner to ever serve in that capacity.
Mr. Antonakes also previously served as the first state voting member of the Federal Financial Institutions Examination Council (FFIEC), as the Vice Chairman of the Conference of State Bank Supervisors (CSBS), and as a founding member of the governing board of the Nationwide Mortgage Licensing System (NMLS). In March 2007, Mr. Antonakes received NeighborWorks America’s Government Service Award for his work in combatting foreclosures.
Mr. Antonakes received a Bachelor of Arts degree from Penn State University, a Masters of Business Administration from Salem State University, and a Doctorate of Philosophy in Law and Public Policy from Northeastern University.
{{ share(self.title(), true) }}


Beyond the boarders of our home world, in the vast expanse that lays ahead of us, our delicate physiology must endure new and unknown challenges. The long-term survival of our species will require ingenuity and courage. Our will is restrained only by our biological limitations.
To ensure the best medical care we will preemptively treat illness with precision medicine. To prepare for unknown biological reponses we will predict genotypic and phenotypic assocciations before they naturally occur. To embark on the final frontire, we shall adapt our tools to develop the next generation of technology for transportation and biological safety.
"We wish to pursue the truth no matter where it leads - but to find the truth, we need imagination and skepticism both. We will not be afraid to speculate, but we will be careful to distinguish speculation from fact." - Carl Sagan.
These challenges are addressed through our publicly-funded academic research, international collaboration, and invitation-only genomic analysis. With minimalism and privacy in mind, this site is built to be light and fast as well as containing no ads, trackers, cookies, &c. This site is under live development; some placeholder pages are included for testing.


There was a bug in paste's smart replace whitespace handling. In some cases, it used information gathered at the start of the selection being pasted into to decide whether or not a space needed to be added to the end of the incoming content.
A smart paste is performed into a selection starting in one block and ending in another. Spaces should surround the pasted word.


An interactive tutorial with real queries and real results,
designed to run on your own machine.
{{ partial "header.html" . }} {{ partial "topbar.html" . }} {{ partial "sidebar.html" . }}
{{ partial "bottombar.html" . }} {{ partial "footer.html" . }}


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NAHUM
1
1 An oracle concerning Nineveh. The book of the vision of Nahum of Elkosh.
God's Wrath Against Nineveh
2 The LORD is a jealous and avenging God;
the LORD is avenging and wrathful;
the LORD takes vengeance on his adversaries
and keeps wrath for his enemies.
3 The LORD is slow to anger and great in power,
and the LORD will by no means clear the guilty.
His way is in whirlwind and storm,
and the clouds are the dust of his feet.
4 He rebukes the sea and makes it dry;
he dries up all the rivers;
Bashan and Carmel wither;
the bloom of Lebanon withers.
5 The mountains quake before him;
the hills melt;
the earth heaves before him,
the world and all who dwell in it.
6 Who can stand before his indignation?
Who can endure the heat of his anger?
His wrath is poured out like fire,
and the rocks are broken into pieces by him.
7 The LORD is good,
a stronghold in the day of trouble;
he knows those who take refuge in him.
8 But with an overflowing flood
he will make a complete end of the adversaries,
and will pursue his enemies into darkness.
9 What do you plot against the LORD?

I will make your grave, for you are vile.”
15 Behold, upon the mountains, the feet of him
who brings good news,
who publishes peace!


Returns the union of two input sets, optionally retaining duplicates.
Syntax
Union ( set1, set2 [,ALL] )
| Parameter | Description |
|---|---|
|
A set to join with set2. |
|
|
A set to join with set1. |
|
ALL |
If the optional ALL keyword is used, duplicates are retained. |
Notes
Duplicates are eliminated by default from the tail of the set. The optional ALL keyword retains duplicates. The two input sets must have identical dimension signatures. For example, if set1 consists of dimensions Product and Market, in that order, then set2 should also consist of Product followed by Market.
Example
The expression
Union( Siblings([Old Fashioned]), {[Sasparilla], [Birch Beer]})
returns the set
{ [Old Fashioned], [Diet Root Beer], [Sasparilla], [Birch Beer] }
The expression
Union( Siblings([Old Fashioned]), {[Sasparilla], [Birch Beer]}, ALL)
returns the set
{ [Old Fashioned], [Diet Root Beer], [Sasparilla], [Birch Beer], [Sasparilla], [Birch Beer] }
The following query
SELECT CrossJoin ( Union ( Siblings ([Old Fashioned]), {([Root Beer]), ([Cream Soda])} ), {(Budget), ([Variance])} ) ON COLUMNS from Sample.Basic
returns the grid
| Old Fashioned | Diet Root Beer | Sasparilla | Birch Beer | Root Beer | Cream Soda | ||||||
| Budget | Variance | Budget | Variance | Budget | Variance | Budget | Variance | Budget | Variance | Budget | Variance |
| 11640 | -4439 | 14730 | -2705 | 5050 | -414 | 4530 | -438 | 35950 | -7996 | 29360 | -3561 |


Alive
Directed by Frank Marshall
Written by John Patrick Shanley
Based on the book by Piers Paul Read
Starring Ethan Hawke, Vincent Spano, Josh Hamilton, John Hayes Newton, Sam Behrens, and Illeana Douglas
As reviewed by James Brundage (MovieKritic2000)
Ah, the splendid sight of a good movie after a string of bad ones. Understand me, I have seen about five bad movies in a row, and, when I watched Alive, I broke my streak. Perhaps then it is fitting that I should write my review of Alive last (the last of a marathon writing stretch of seven reviews), that is should be my final respite after such a long series of typing.
Alive is the true story of a plane crash that occurred in 1972 in the Andes. Come on, you know what I'm talking about, the one where the survivors had to resort to cannibalism? Yeah, I saw that episode of "Seinfeld" too. The movie has been parodied way too much for something of its caliber.
It starts out with a steely narration by John Malkovich, who tells of his finding God in the Andes, and then quickly goes into a terrific sequence involving the plane crash.
From there on in, most of the rest of the movie occurs at the front half of the plane, where 27 survivors begin their fight to live. A few people are completely broken by the experience and die. A few people do will go to any lengths to survive.
The particular lengths they will go to include cannibalism. They do not kill and eat, but instead eat the people who have already died. Nando (Ethan Hawke) and Antonio (Vincent Spano) have such strong survival instincts that they are willing to climb the Andes to save themselves and their friends.
Unfortunately, I saw Alive last, after all of the wave of survival films that it spawned. Because all of these were Alive rips, Alive now appears to be contrived and cliched. But it is not.
Alive is a movie able to touch your heart (and your stomach) as it grimly displays the miraculous true story of survival in the Andes. Using relative unknowns at the time, Alive was able to manipulate the audiences into believing that the circumstances were actually happening.
As normal, however, I have my complaints of Alive. For one, although the performances are great, the dialogue is incredibly bad. True story or no, I have trouble believing that anyone would say half the lines in this movie. Also, the movie tries to be funny. Although many people who go through trauma develop a dark sense of humor, it doesn't ever seem realistic... and seeming realistic is what dramas are about.
Ethan Hawke and Vincent Spano do their finest studio roles (Gattaca as an exception for Ethan Hawke) as they take on fairly simple characters and take them to new heights. Illeana Douglas manages to hold her own as practically the only female member of the cast, a woman desiring to go home to her family. Most impressive, however, is John Haymes Newton, who plays the team captain, Antonio Vizintin.
Antonio is a control-freak who is forced, by the mountains, to realize that there are things that he cannot control. As the mountain gets harsher on them, and as hope dies, Antonio dies along with it. Nando and Antonio Balbi, however, will not allow their hope to die.
Alive is a good drama, uplifting, hopeful, and intelligent. It is not the greatest movie ever made, nor is it especially worth spending three bucks to rent. If it's on the television, however, go ahead.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


|
SUBJECT INDEX Anthropology Architecture Art Black Studies Business Ecology Economics Education Film Healthcare History Law Linguistics Literature Mass Media Medicine Music Philosophy Political Science Psychology Religion Science Shakespeare Sociology Sports Recreation Urban Studies Women's Studies |
Education: Financing & FundingTo order a specific paper, click the Catalog Number button next to the Paper Title of interest. Send comments to<EMAIL_ADDRESS>Last Updated: 12/21/96 Copyright ©1996 ASM Communications, Inc. All Rights Reserved. |


Welcome To Husky Nation
Stay Connected
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Change of address? Receive news, event invitations, and the Northeastern Alumni Magazine by keeping your contact information up-to-date.
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Volunteering is not a huge commitment, and can include everything from sending potential event ideas or helping to secure locations for future events in the city.


Syrian Rue (Peganum Harmala) can be used in conjunction with trichocereus cacti in order to multiply the psychedelic effect of the cactus. Not only does this reduce the amount of slimy green liquid I have to ingest, but reduces the amount cactus needed by two-thirds!
Tea recipe:
Brew two grams of powdered rue in one-half cup acidified water for five minutes.
Strain thru cloth, then paper.
Drink this five minutes before ingesting cactus brew.
The downside to this is that the rue tea is actually nastier tasting than the cactus juice! Make an extract if you wish. It can be prepared dose by dose or in big batches. I'll give the single dose quantities that can be multiplied out.
Extract recipe:
Grind to a powder two grams of Rue and place in 100ml acidified water. Ascorbic acid works great and every vitamin store has it. Get the powder that is not buffered. Lemon juice or vinegar will probably do as well. We won't be tasting it, so it won't need good flavor. And since we want to get the most complete extraction possible, just see that the pH paper comes out red. Boil the grounds in the acid-water for 20 minutes. Strain thru cloth, then paper. Now pour the liquid into a pyrex casserole dish and evaporate it.
I have an electric hot plate that is just large enough for a standard sized casserole dish. I preheat the hot plate and evaporation dish on it. In fact, that is really the first thing I do - plug in the hot plate and set the dish on it. Then by the time I am ready to pour in the filtered liquid, the glass pan is absolutely piping hot. Also a hairdryer will go a long way in speeding up the process. One dose can be extracted, recovered and eaten in under an hour. When doing a big batch, boil off the liquid after filtering. Let it boil until it is nice and thick, then pour it in the glass for evaporation. Also, get one of those space heaters with a built-in fan. Set it up to blow the hot air over the evaporation dish.
Now the goop/crystals that remain can be easily scraped up, balled up and swallowed without being tasted. Or the goop can be placed in gel-caps and swallowed.  Also, wait 15 minutes before following it with the cactus - and add another 15 minutes if gel-caps are used (maybe more? - i advise against gel-caps). Again, two grams starting material should be good for facilitating cacti. Probably even just one gram would be enough, especially if it were simply brewed and drunk in tea form (yuk!). But as much as four grams may be used without too much unpleasantness. When I want to 'make sure' it works, I just use three.
Remember, the amount of cactus used will be one-third the amount normally used. Someone who normally uses 24' would only use 8'. 18' would become 6' and 12' would become 4'! That's right, just 4 inches! I have had some beautiful experiences with only 4' of cactus with the help of Syrian Rue.
The most amazing aspect of using rue with cacti is the short onset time. Oddly enough I always feel a distinct head change within two minutes of drinking the cactus juice. It steps up majorly within 20-30 minutes and then the bomb just drops around 50-60 minutes after ingestion. See, there's no three hour waiting period here. But don't worry, it still lasts super long. After 7-8 hours there is a downturn in the energy, but waves keep coming until sleep can be reached around 12-14 hours.
I've never had any extra side effects from this other than what I would normally expect from trichocereus cacti. Using a little herb to head off any possible nausea ensures for nice come-up. Most important advice: take it before noon.
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.


Before Change
The resulting model will be saved to estnltk/estner/models/default.bin
"""
with open(DEFAULT_NER_DATASET) as f:
nerdata = json.loads(bz2.decompress(f.read()))
documents = nerdata["documents"]
trainer = NerTrainer()
model = trainer.train(documents)
model.serialize_to_file(DEFAULT_NER_MODEL)
After Change
"""
with codecs.open(DEFAULT_NER_DATASET, "rb") as f:
nerdata = f.read()
nerdata = bz2.decompress(nerdata)
nerdata = json.loads(nerdata.decode("utf-8"))
documents = nerdata["documents"]
trainer = NerTrainer()
model = trainer.train(documents)
model.serialize_to_file(DEFAULT_NER_MODEL)


Introductory Operating Systems
If you are currently using an operating system that collects data like Windows 10, you should pick an alternative here.
{% include legacy/cardv2.html
title="Fedora Workstation"
image="/assets/img/legacy_svg/3rd-party/fedora.svg"
description='Fedora is a Linux distribution developed by the Fedora Project and sponsored by Red Hat. Fedora Workstation is a secure, reliable, and user-friendly edition developed for desktops and laptops. Fedora by default comes with the GNOME desktop environment, other desktop environments are also available.'
badges="info:Linux"
website="https://getfedora.org/"
privacy-policy="https://fedoraproject.org/wiki/Legal:PrivacyPolicy?rd=Legal/PrivacyPolicy"
git="https://src.fedoraproject.org/"
%}
{% include legacy/cardv2.html
title="Ubuntu"
image="/assets/img/legacy_svg/3rd-party/ubuntu.svg"
description='Ubuntu is a Linux distribution developed by Canonical Ltd. Ubuntu is a reliable distribution that is user-friendly and can be run on desktops, servers, and IoT devices. Ubuntu uses GNOME as the default desktop environment, while other desktop environments are also available.'
badges="info:Linux"
website="https://ubuntu.com"
privacy-policy="https://ubuntu.com/legal/data-privacy"
git="https://launchpad.net/ubuntu"
%}
Advanced Operating Systems
These options have advanced features and are unique in some way. These options will likely require the user to read technical background documentation.
{% include legacy/cardv2.html
title="Alpine Linux"
image="/assets/img/legacy_svg/3rd-party/alpinelinux.svg"
description='Alpine Linux is a very minimal distribution designed to be secure and very resource efficient. Alpine Linux can run from RAM, and merge configuration files into the system on boot using Alpine local backup. Alpine Linux is often used on servers and in Linux containers.'
badges="info:Linux"
website="https://alpinelinux.org/"
privacy-policy="https://alpinelinux.org/privacy-policy.html"
gitlab="https://gitlab.alpinelinux.org"
%}
{% include legacy/cardv2.html
title="Arch Linux"
image="/assets/img/legacy_svg/3rd-party/archlinux.svg"
description='A simple, lightweight Linux distribution. It is composed predominantly of free and open-source software, and supports community involvement.'
badges="info:Linux"
labels="color==success::link==https://reproducible.archlinux.org::text==Reproducible builds"
website="https://www.archlinux.org/"
privacy-policy="https://wiki.archlinux.org/index.php/ArchWiki:Privacy_policy"
gitlab="https://gitlab.archlinux.org"
%}
{% include legacy/cardv2.html
title="Debian"
image="/assets/img/legacy_svg/3rd-party/debian.svg"
description='Debian is a Unix-like computer operating system and a Linux distribution that is composed entirely of free and open-source software, most of which is under the GNU General Public License, and packaged by a group of individuals known as the Debian project.'
badges="info:Linux"
labels="color==success::link==https://reproducible.debian.net::text==Reproducible builds"
website="https://www.debian.org/"
privacy-policy="https://www.debian.org/legal/privacy"
tor="http://5ekxbftvqg26oir5wle3p27ax3wksbxcecnm6oemju7bjra2pn26s3qd.onion/"
gitlab="https://salsa.debian.org/qa/debsources"
%}
{% include legacy/cardv2.html
title="NixOS"
image="/assets/img/legacy_svg/3rd-party/nixos.svg"
description='NixOS is a Linux distribution with a unique approach to package and configuration management. Built on top of the Nix package manager, it is completely declarative, makes upgrading systems reliable, and has many other advantages.'
badges="info:Linux"
labels="color==success::link==https://r13y.com::text==Reproducible builds"
website="https://nixos.org"
privacy-policy="https://nixos.wiki/wiki/NixOS_Wiki:Privacy_policy"
github="https://github.com/NixOS"
%}
{% include legacy/cardv2.html
title="Qubes OS"
image="/assets/img/legacy_svg/3rd-party/qubes_os.svg"
description='Qubes is an open-source operating system designed to provide strong security for desktop computing. Qubes is based on Xen, the X Window System, and Linux, and can run most Linux applications and utilize most of the Linux drivers.'
badges="info:Xen"
website="https://www.qubes-os.org/"
privacy-policy="https://www.qubes-os.org/privacy/"
github="https://github.com/QubesOS"
tor="http://qubesosfasa4zl44o4tws22di6kepyzfeqv3tg4e3ztknltfxqrymdad.onion/"
%}


HR system
Add Employee
Name
Email
Department
Call-Center
Information-Technology
Human-Resources
Name
Email
Department
Salary
Total =
Clear The Table


WIZARDS
Probe result:
New endstop corrections:
X:
Y:
Z:
New diagonal rod length:
New delta radius:
New homed height:
New tower position angle corrections:
X:
Y:
Z:
Commands:


Packer and Docker
Josh Thomas /
@jthoms1
Notice: When I say OS, I mean Linux. Windows is not suitable for Server use.
Virtual Machines
Emulated Hardware on Host OS
Replacement for bare metal
Common and accommodating
Large memory and storage footprint
JIT is relative
Development environments made easy
Software for creating and configuring VMs
Works on Mac, Windows, and Linux
Local environment closely matches Prod
How has it helped Earthlings?
Live Demo
Cloud images made easy
Identical machine images for multiple platforms
Provisions similar to Vagrant
Create exactly the same dev server and prod server
How can it help an Earthling?
Live Demo
Linux container used for Applications
Virtualizes without an independent OS Kernel
Isolates application from the rest of the OS
( port forwarding + dir sharing)
Highly efficient
How does Docker work?
Linux containers (est 2008)
Images are layered
Small memory and storage footprint
Uptime in ms
Currently not common but insane growth
Rapidly changing environment
What are the
advantages
?
Live Demo
Questions?


Uses of Class
org.drip.measure.continuous.R1Univariate
| Package | Description |
|---|---|
| org.drip.dynamics.process |
Ito-Dynamics Based Stochastic Process
|
| org.drip.execution.bayesian |
Bayesian Price Based Optimal Execution
|
| org.drip.execution.discrete |
Trajectory Slice Execution Cost Distribution
|
| org.drip.graph.mst |
Agnostic Minimum Spanning Tree Properties
|
| org.drip.measure.bayesian |
Prior, Conditional, Posterior Theil Bayesian
|
| org.drip.measure.chisquare |
Chi-Square Distribution Implementation/Properties
|
| org.drip.measure.continuous |
R1 Rd Continuous Random Measure
|
| org.drip.measure.discrete |
Antithetic, Quadratically Re-sampled, De-biased Distribution
|
| org.drip.measure.gamma |
R1 Gamma Distribution Implementation/Properties
|
| org.drip.measure.gaussian |
R1 Rd Covariant Gaussian Quadrature
|
| org.drip.measure.lebesgue |
Uniform Piece-wise Lebesgue Measure
|
| org.drip.sequence.functional |
Efron Stein Functional Supremum Bounds
|
| org.drip.sequence.metrics |
Sequence Bounds Agnostic Metrics Estimators
|
| org.drip.sequence.random |
Correlated Multi-Factor Sequence Generator
|
| org.drip.spaces.metric |
Hilbert/Banach Normed Metric Spaces
|
| org.drip.validation.distance |
Hypothesis Target Distance Test Builders
|
-
Uses of R1Univariate in org.drip.dynamics.process
Methods in org.drip.dynamics.process that return R1Univariate Modifier and Type Method Description R1Univariate
R1StochasticEvolver. futureValueDistribution(double x0, double t)
Generate the Future Value Distribution at Time t -
Uses of R1Univariate in org.drip.execution.bayesian
Subclasses of R1Univariate in org.drip.execution.bayesian Modifier and Type Class Description class
ConditionalPriceDistribution
ConditionalPriceDistribution holds the Price Distribution Conditional on a given Drift.class
PriorDriftDistribution
PriorDriftDistribution holds the Prior Belief Distribution associated with the Directional Drift. -
Uses of R1Univariate in org.drip.execution.discrete
Subclasses of R1Univariate in org.drip.execution.discrete Modifier and Type Class Description class
ShortfallIncrementDistribution
ShortfallIncrementDistribution holds the Parameters of the R1 Normal Short fall Increment Distribution. -
Uses of R1Univariate in org.drip.graph.mst
Methods in org.drip.graph.mst with parameters of type R1Univariate Modifier and Type Method Description static double
SteeleCompleteUniformRandomMST. AsymptoticFriezeMSTLength(R1Univariate r1Univariate)
Compute the Length of the MST for Large n (attribution to Alan M. -
Uses of R1Univariate in org.drip.measure.bayesian
Methods in org.drip.measure.bayesian that return R1Univariate Modifier and Type Method Description R1Univariate
R1UnivariateConvolutionMetrics. conditional()
Retrieve the R1 Univariate Conditional DistributionR1Univariate
R1UnivariateConvolutionMetrics. joint()
Retrieve the R1 Univariate Joint DistributionR1Univariate
R1UnivariateConvolutionMetrics. posterior()
Retrieve the R1 Univariate Posterior DistributionR1Univariate
R1UnivariateConvolutionMetrics. prior()
Retrieve the R1 Univariate Prior DistributionR1Univariate
R1UnivariateConvolutionMetrics. unconditional()
Retrieve the R1 Univariate Unconditional DistributionMethods in org.drip.measure.bayesian with parameters of type R1Univariate Modifier and Type Method Description R1UnivariateConvolutionMetrics
R1UnivariateConvolutionEngine. process(R1Univariate univariatePrior, R1Univariate univariateUnconditional, R1Univariate univariateConditional)
Generate the Joint R1 Univariate Combined DistributionConstructors in org.drip.measure.bayesian with parameters of type R1Univariate Constructor Description R1UnivariateConvolutionMetrics(R1Univariate prior, R1Univariate unconditional, R1Univariate conditional, R1Univariate joint, R1Univariate posterior)
R1UnivariateConvolutionMetrics Constructor -
Uses of R1Univariate in org.drip.measure.chisquare
Subclasses of R1Univariate in org.drip.measure.chisquare Modifier and Type Class Description class
R1Central
R1Central implements the Probability Density Function for the R1 Central Chi-Square Distribution.class
R1CentralCLTProxy
R1CentralCLTProxy implements the N (0, 1) CLT Proxy Version for the R1 Chi-Square Distribution.class
R1CentralFisherProxy
R1CentralFisherProxy implements the Univariate Normal Proxy Version using the Fisher Transformation for the R1 Chi-Square Distribution.class
R1CentralWilsonHilferty
R1CentralWilsonHilferty implements the Normal Proxy Version for the R1 Chi-Square Distribution using the Wilson-Hilferty Transfomation.class
R1NonCentral
R1NonCentral implements the Distribution Table for the R1 Non-central Chi-Square Distribution.class
R1NonCentralAbdelAty
R1NonCentralAbdelAty implements the Abdel-Aty (1954) Wilson-Haferty Approximation for the R1 Non-central Chi-Square Distribution.class
R1NonCentralCLTProxy
R1NonCentralCLTProxy implements the CLT Proxy Distribution for the R1 Non-central Chi-Square Distribution.class
R1NonCentralCumulantInvariant
R1NonCentralCumulantInvariant implements the Cumulant Invariant Transformation for the R1 Non-central Chi-Square Distribution.class
R1NonCentralSankaran
R1NonCentralSankaran implements the Sankaran (1959, 1963) Wilson-Haferty Approximation for the R1 Non-central Chi-Square Distribution.class
R1NonCentralWilsonHaferty
R1NonCentralWilsonHaferty implements the Wilson-Haferty Transform for the R1 Non-central Chi-Square Distribution.class
R1WilsonHilferty
R1CentralWilsonHilferty implements the Normal Proxy Version for the R1 Chi-Square Distribution using the Wilson-Hilferty Transformation. -
Uses of R1Univariate in org.drip.measure.continuous
Subclasses of R1Univariate in org.drip.measure.continuous Modifier and Type Class Description class
R1UnivariateExponential
R1UnivariateExponential implements the Univariate R1 Exponential Distribution.class
R1UnivariateScaledExponential
R1UnivariateScaledExponential implements the Probability Density Function for the Scaled Univariate R1 Exponential Function.class
R1UnivariateUniform
R1UnivariateUniform implements the Univariate R1 Uniform Distribution. -
Uses of R1Univariate in org.drip.measure.discrete
Subclasses of R1Univariate in org.drip.measure.discrete Modifier and Type Class Description class
BoundedUniformIntegerDistribution
BoundedUniformIntegerDistribution implements the Univariate Bounded Uniform Integer Distribution, with the Integer being generated between a (n inclusive) lower and an upper Bound.class
PoissonDistribution
PoissonDistribution implements the Univariate Poisson Distribution using the specified Mean/Variance. -
Uses of R1Univariate in org.drip.measure.gamma
Subclasses of R1Univariate in org.drip.measure.gamma Modifier and Type Class Description class
ErlangDistribution
ErlangDistribution implements the Shape and Scale Parameterization of the R1 Erlang Distribution.class
ExponentialDistribution
ExponentialDistribution implements the Exponential Distribution in Terms of the R1 Gamma Distribution.class
MaxwellBoltzmannSquaredDistribution
MaxwellBoltzmannSquaredDistribution implements the Maxwell Boltzmann Squared Distribution using the R1 Gamma Distribution.class
R1ShapeScaleDiscrete
R1ShapeScaleDiscrete generates Discrete Variables that are Derivatives of the R1 Gamma Distribution.class
R1ShapeScaleDistribution
R1ShapeScaleDistribution implements the Shape and Scale Parameterization of the R1 Gamma Distribution. -
Uses of R1Univariate in org.drip.measure.gaussian
Subclasses of R1Univariate in org.drip.measure.gaussian Modifier and Type Class Description class
R1UnivariateNormal
R1UnivariateNormal implements the Univariate R1 Normal Distribution. -
Uses of R1Univariate in org.drip.measure.lebesgue
Subclasses of R1Univariate in org.drip.measure.lebesgue Modifier and Type Class Description class
R1PiecewiseDisplaced
R1PiecewiseDisplaced implements the Displaced Piecewise Linear R1 Distributions.class
R1PiecewiseLinear
R1PiecewiseLinear implements the Piecewise Linear R1 Distributions.class
R1Uniform
R1Uniform implements the R1 Lebesgue (i.e., Bounded Uniform) Distribution, with a Uniform Distribution between a Lower and an Upper Bound. -
Uses of R1Univariate in org.drip.sequence.functional
Methods in org.drip.sequence.functional that return R1Univariate Modifier and Type Method Description R1Univariate
FunctionSupremumUnivariateRandom. underlyingDistribution()
Retrieve the Underlying DistributionR1Univariate
IdempotentUnivariateRandom. underlyingDistribution()
Retrieve the Underlying DistributionConstructors in org.drip.sequence.functional with parameters of type R1Univariate Constructor Description BinaryIdempotentUnivariateRandom(double dblOffset, R1Univariate dist, double dblVariateBound, double dblPositiveProbability)
BinaryIdempotentUnivariateRandom ConstructorBoundedIdempotentUnivariateRandom(double dblOffset, R1Univariate dist, double dblVariateBound)
BoundedIdempotentUnivariateRandom ConstructorFunctionSupremumUnivariateRandom(R1ToR1[] aAUClass, R1Univariate dist)
FunctionSupremumUnivariateRandom ConstructorIdempotentUnivariateRandom(double dblOffset, R1Univariate dist)
IdempotentUnivariateRandom Constructor -
Uses of R1Univariate in org.drip.sequence.metrics
Methods in org.drip.sequence.metrics that return R1Univariate Modifier and Type Method Description R1Univariate
SingleSequenceAgnosticMetrics. populationDistribution()
Retrieve the Population DistributionConstructors in org.drip.sequence.metrics with parameters of type R1Univariate Constructor Description BoundedSequenceAgnosticMetrics(double[] adblSequence, R1Univariate distPopulation, double dblSupport)
BoundedSequenceAgnosticMetrics ConstructorIntegerSequenceAgnosticMetrics(double[] adblSequence, R1Univariate distPopulation)
Build out the Sequence and their MetricsSingleSequenceAgnosticMetrics(double[] adblSequence, R1Univariate distPopulation)
Build out the Sequence and their Metrics -
Uses of R1Univariate in org.drip.sequence.random
Methods in org.drip.sequence.random with parameters of type R1Univariate Modifier and Type Method Description SingleSequenceAgnosticMetrics
Bounded. sequence(int iNumEntry, R1Univariate distPopulation)
SingleSequenceAgnosticMetrics
BoundedUniformInteger. sequence(int iNumEntry, R1Univariate distPopulation)
SingleSequenceAgnosticMetrics
Poisson. sequence(int iNumEntry, R1Univariate distPopulation)
SingleSequenceAgnosticMetrics
UnivariateSequenceGenerator. sequence(int iNumEntry, R1Univariate distPopulation)
Generate a Random Sequence along with its Metrics -
Uses of R1Univariate in org.drip.spaces.metric
Methods in org.drip.spaces.metric that return R1Univariate Modifier and Type Method Description R1Univariate
R1Combinatorial. borelSigmaMeasure()
R1Univariate
R1Continuous. borelSigmaMeasure()
R1Univariate
R1Normed. borelSigmaMeasure()
Retrieve the Borel Sigma R^1 Probability MeasureMethods in org.drip.spaces.metric with parameters of type R1Univariate Modifier and Type Method Description static R1CombinatorialBall
R1CombinatorialBall. ClosedUnit(java.util.List<java.lang.Double> lsElementSpace, R1Univariate distR1, int iPNorm)
Construct a R1CombinatorialBall Instance of Unit Radiusstatic R1ContinuousBall
R1ContinuousBall. ClosedUnit(double dblLeftEdge, double dblRightEdge, R1Univariate distR1, int iPNorm)
Construct a R1ContinuousBall Instance of Unit Radiusstatic R1Combinatorial
R1Combinatorial. Standard(java.util.List<java.lang.Double> lsElementSpace, R1Univariate distR1, int iPNorm)
Construct the Standard l^p R^1 Combinatorial Space Instancestatic R1Continuous
R1Continuous. Standard(double dblLeftEdge, double dblRightEdge, R1Univariate distR1, int iPNorm)
Construct the Standard l^p R^1 Continuous Space Instancestatic R1Combinatorial
R1Combinatorial. Supremum(java.util.List<java.lang.Double> lsElementSpace, R1Univariate distR1)
Construct the Supremum (i.e., l^Infinity) R^1 Combinatorial Space Instancestatic R1Continuous
R1Continuous. Supremum(double dblLeftEdge, double dblRightEdge, R1Univariate distR1)
Construct the Supremum (i.e., l^Infinity) R^1 Continuous Space InstanceConstructors in org.drip.spaces.metric with parameters of type R1Univariate Constructor Description R1Combinatorial(java.util.List<java.lang.Double> lsElementSpace, R1Univariate distR1, int iPNorm)
R1Combinatorial Space ConstructorR1CombinatorialBall(java.util.List<java.lang.Double> lsElementSpace, R1Univariate distR1, int iPNorm, double dblNormRadius)
R1CombinatorialBall ConstructorR1Continuous(double dblLeftEdge, double dblRightEdge, R1Univariate distR1, int iPNorm)
R1Continuous Space ConstructorR1ContinuousBall(double dblLeftEdge, double dblRightEdge, R1Univariate distR1, int iPNorm, double dblNormRadius)
R1ContinuousBall Constructor -
Uses of R1Univariate in org.drip.validation.distance
Methods in org.drip.validation.distance that return R1Univariate Modifier and Type Method Description R1Univariate
ImportanceWeight. r1Univariate()
Retrieve the Underlying R1 DistributionConstructors in org.drip.validation.distance with parameters of type R1Univariate Constructor Description ImportanceWeight(R1Univariate r1Univariate, double positiveExpectation)
ImportanceWeight Constructor


{% extends '_layouts/layout_3-3_no_title_block.html' %} {% block page_title %} Stomach ache symptoms and conditions - NHS.UK {% endblock %} {% block pageTitle %} Pharmacies near LS6 4JN {{ postCode }} {% endblock %} {% block pageIntro %} {% endblock %} {% block content %}
These NHS services can help you now.
0 miles away
Open from 7.30am until 5.30pm today
569-571 Meanwood Road,
Leeds,
LS6 4AY
Phone 0113 278 6352
0.5 miles away
Open from 8am until 6pm today
597 Meanwood Road,
Leeds,
LS6 4AY
Phone 0113 230 7519
0.6 miles away
Open from 7am until 6pm today
St Michaels Court,
1 Shire Oak Street,
Headingley,
Leeds,
LS6 2DP
Phone 0113 230 5588
0.6 miles away
Open from 8am until 5pm today
8 The Arndale Centre,
Otley Road,
Leeds,
LS6 2UE
Phone 0113 274 0233
0.9 miles away
Open next tomorrow from 7.30am until 5.30pm
Rutland Lodge,
Scott Hall Road,
Leeds,
LS7 3DR
Phone 0113 278 6352


Features
The quick brown fox jumps over the lazy dog.
Feature
The quick brown fox jumps over the lazy dog.
Feature
The quick brown fox jumps over the lazy dog.
Feature
The quick brown fox jumps over the lazy dog.
Feature
The quick brown fox jumps over the lazy dog.
Feature
The quick brown fox jumps over the lazy dog.
Feature
The quick brown fox jumps over the lazy dog.


Settings
Mode
Year selection
(minimum chart year, scenario start year, maximum chart year)
Harmonization factor
(used to regionalize modified global emission scenarios)
SSP model
(which integrated assessment model to take data from)
Interpolation method
(line shape between emission scenario breakpoints)
Base scenario
(determines emission trajectories of all greenhouse gases)
Click on the CO2 emissions figure to modify its emission trajectory!
Bug note: dragging the breakpoints in the CO2 emissions figure may sometimes stop working. As a temporary workaround, try clicking the "Fix" button in the upper right corner to make dragging work again.
Base scenario
Greenhouse gas
Number of regions
Regions
Climate sensitivity
(°C per doubling of CO2 concentration)
Model runs
| Peak year of CO2 emissions |
Cumulative CO2 emissions (2020-2100) |
Climate sensitivity (for 2xCO2) |
Mean surface temperature (year 2100) |
|
|---|---|---|---|---|
| - | - | - | - | - |


Virtual reality technology is the future. As a SIXR member, you'll have access to resources to help you build that future.
Learn from
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View this presentation: http://www.timlockridge.com/cwcon13
Fork this presentation: http://www.github.com/timlockridge/cwcon13
| Site | Development Tool | Alt Text? | Headings? | ARIA/HTML5? |
|---|---|---|---|---|
| 1 | Weebly | 0/3 | No | No |
| 2 | Dreamweaver | 3/3 | No | No |
| 3 | Wordpress | 1/2 | Yes | Yes |
| 4 | Dreamweaver | 1/2 | No | No |
| 5 | Dreamweaver | 0/25 | Yes | No |
| 6 | Static HTML | 0/8 | Yes | No |
| 7 | Wordpress | 12/21 | No | No |
| 8 | Wordpress | 9/11 | Yes | No |
| 9 | Drupal | 3/6 | Yes | No |
| 10 | Wordpress | 3/4 | Yes | Yes |
| 11 | Static HTML | 9/10 | No | No |
“perhaps the recognition of all five canons and the definitive twentieth-century erasure of memory and delivery will lead to the obliteration of the current-traditional paradigm and its twin the false binary opposition of content and form” (147).
—Kathleen Welch, from Electric Rhetoric (1999)


Our Projects
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Contact Numbers
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Cruel Intentions
Starring Sarah Michelle Gellar, Ryan Phillippe and Reese Witherspoon. Directed By Roger Kumble Running Time: 1 hour 35 minutes.
(Columbia Pictures)
The new brat packers continue to hit the screens with his updating of Dangerous Liasons, which was last seen on the screen starring Jeremy Irons and Glenn Close. Now we get Geller and Phillippe in the starring roles, which is certainly 'different,' and not entirely successful. Geller plays Kathryn, who makes a bet with her Sebastian (Phillippe) that he won't be able to bed virgin Annette (Witherspoon,) who wishes to wait until marriage. If Kathryn wins, she gets Phillippe's car, if not, Phillippe gets Kathryn. Unfortunately for Sebastian, he starts getting feelings for Annette, and isn't sure he can carry on with the bet. And Kathryn has another agenda of her own, involving Cecile (Selma Blair) and her mother, played by Christine Baranski.
Cruel Intentions is a well executed experiment that provides plenty of entertainment for your money.  The way she goes from her false, happy outlook to the disgust inside is nothing original, but well played by Gellar. It is sometimes difficult to believe this is the same character who plays the sweeter than sweet Buffy on the popular television series, and is a rewarding performance. Witherspoon has a low key role, but gives a nice performance, if a little underwhelming. She gets the job done, though, and the audience feels for her as she gets played as a stooge by Gellar and Phillippe. Phillippe, sadly, is less successful, his acting a little stiff. He is rather evil, but his performance could have been stronger. The real surprise in this film is the outstanding Selma Blair as a little girl discovering sex, her performance is very well performed, and all of her scenes work.
Apart from the above average acting, there's little else in Cruel Intentions that distinguishes it from other brat pack movies. There's the usual selection of rock music making up the soundtrack, and some 'hip' incidental music. The film goes at a cracking pace to make sure no attention is lost from the largely teenage audience, and the film is over blidingly fast. This is a shame, because with a little more time the characters could have been more rounded.  Phillippe, near the end of the film, gets some development to his character, but by then it's too late. Again, only Selma Blair gets any character development during the film.
The direction by Kumble is largely straight forward, but the pace is quick and interest is maintained. Kumble also adapted the script, and the Gen-Xer script isn't nearly as embarrassing as it could have been, and is surprisingly adult and sensible, if a little two dimensional. Unfortunately, a Dawsons Creek cast member pops up as Sebastians gay friend, but thankfully he's not in the film for long.
Overall, Cruel Intentions is a nice film with some good laughs and fun twists. There's nothing original here, and the story has been done many times before. And when leaving the cinema, the film will probably leave your mind after a couple of minutes. But while it's lasting, Cruel Intentions is a fun ride.
RATING=*** OUT OF *****
A David Wilcock Review ©1999
DAVID WILCOCK<EMAIL_ADDRESS>Visit the Wilcock Movie Page for U.K film reviews! http://www.wilcock54.freeserve.co.uk
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