It takes a team to design, develop and launch a successful website. Very few people have all the varying skillsets to do everything necessary to create a website from content strategy through back-end development. However, no matter what part of the website you are working on, you need to know about the others. Developers and User Experience Designers need to know about visual design, and how what they do will impact the design. This is also true for graphic designers. Designers need to know about content strategy, back-end/front-end development, user experience, and information architecture. Without knowledge of how all these professions come together to create an app or website, designers can’t work as effectively as those who do.
Now, while everyone who works on a website should know all that goes into creating a website, they don’t have to be experts on every part of it. I have no idea what the exact ideal balance of all these skills are to make the most employable graphic designer, so don’t ask. However, I do have strong recommendations on the minimal balance. During the next few in-class exercises my goal is to give you the minimal understanding of these different phases of the web design process so you can fully leverage them to make the best design possible.
Now, what makes the first step in the process confusing for me as an instructor—and for emerging designers when they start working in the field—is there are four or more phases/steps happening at once! Making it even more difficult to replicate in class, information from each of these phases/steps, while happening simultaneously, are relayed to each team as they happen. For example, the content strategists are working with the information architects (IA), and the user experience (UX) team is bouncing back and forth between design and IA. Even development (DEV) might be involved at this point in discussions with IA and UX.
To do my best to replicate this, I’ve decided to introduce four of these phases/steps in a single class so you know how they are all related. Once introduced, you will have multiple class periods to work on them. The order is not imporatant, since they are happening simultaneously.
A07 - C: User Research - Heuristic Evaluation
A07 - B: Information Architecture - User Flow
A07 - C: User Research - Personas
A07 - E: Project Scope


|
|
Demonstrates:
- basic grid with multi-column tri-state sort option
- numbers indicating column sort precedence are displayed in the columns when multiple columns selected
- first column click sorts ASC, second click DESC, third click removes sort from column
- no shift-click is necessary to use multiple columns
- span holding the up/down arrow is styled with css class slick-sort-indicator
- if option sortColNumberInSeparateSpan is false, the above span is also styled with css class slick-sort-indicator-numbered
- if option sortColNumberInSeparateSpan is true, renders a separate span for the number and styles it with css class slick-sort-indicator-numbered
View Source:
|


This is the interactive resume of Isaac Wolfe. Type 'ls' followed by enter to see what categories are available and then type which category you would like to view. Type 'help' if you want to see a more in depth help section.


{% include 'includes/html_head_open' %} {% include 'includes/html_head_close' %}
{{ current.title }}
{{ current.meta.subtitle }}


{% load static %}
{% block header %} {% endblock %}
Gym Khaana
My Profile
Notifications
View all Notifications
Post a Notification to a class
View all Announcements
Make Announcements
Members
Customers
Trainers
Managers
System Administrators
Gymnasium
Gym Classes
Gym Packages
Allocate Gym Class to Customers
Equipments
Equipment List
Equipment Types
Add Equipment
Create Equipment Type
AMC List
Add New AMC
{% if user.is_authenticated %}
Logout
{% endif %}
{% block body %} {% endblock %}
© Copyright - VIT Campus creation


| 0 |
The top 100 papers |
Q28250597 |
| 1 |
The origin and evolution of cell types |
Q38798014 |
| 2 |
Make code accessible with these cloud services |
Q91130546 |
| 3 |
Genetic address book for retinal cell types. |
Q43299861 |
| 4 |
A community-based transcriptomics classification and nomenclature of neocortical cell types |
Q98665291 |
| 5 |
The network effect: studying COVID-19 pathology with the Human Cell Atlas |
Q96817154 |
| 6 |
Comprehensive Classification of Retinal Bipolar Neurons by Single-Cell Transcriptomics. |
Q40967362 |
| 7 |
Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data |
Q33037209 |
| 8 |
The human disease network |
Q24678240 |
| 9 |
The evolving concept of cell identity in the single cell era |
Q93086971 |
| 10 |
PRINTS and its automatic supplement, prePRINTS. |
Q34169535 |
| 11 |
The naming of neurons: applications of taxonomic theory to the study of cellular populations. |
Q34065481 |
| 12 |
Making your database available through Wikipedia: the pros and cons |
Q28254676 |
| 13 |
ezTag: tagging biomedical concepts via interactive learning. |
Q55483834 |
| 14 |
GNormPlus: An Integrative Approach for Tagging Genes, Gene Families, and Protein Domains |
Q28200510 |
| 15 |
tmVar 2.0: integrating genomic variant information from literature with dbSNP and ClinVar for precision medicine. |
Q47317210 |
| 16 |
Assisting manual literature curation for protein-protein interactions using BioQRator |
Q33928865 |
| 17 |
Neuronal diversity and convergence in a visual system developmental atlas |
Q101226729 |
| 18 |
Enabling Open Science: Wikidata for Research (Wiki4R) |
Q26707522 |
| 19 |
What Is it Like to Be a Bat? |
Q2703462 |
| 20 |
Ten tips for a text-mining-ready article: How to improve automated discoverability and interpretability |
Q96032351 |
| 21 |
Jointly defining cell types from multiple single-cell datasets using LIGER |
Q100526347 |
| 22 |
Dovetailing biology and chemistry: integrating the Gene Ontology with the ChEBI chemical ontology. |
Q34878068 |
| 23 |
Numerical taxonomy. |
Q50735370 |
| 24 |
A Taxonomic Problem |
Q60137015 |
| 25 |
Pathway information extracted from 25 years of pathway figures |
Q101473819 |
| 26 |
The Development of Taxonomic Theory Since 1851 |
Q59058260 |
| 27 |
Semantic integration of gene expression analysis tools and data sources using software connectors. |
Q30570244 |
| 28 |
The principles of science : a treatise on logic and scientific method |
Q51427139 |
| 29 |
Some thoughts on bacterial classification |
Q74657187 |
| 30 |
Cross-linking BioThings APIs through JSON-LD to facilitate knowledge exploration. |
Q49483648 |
| 31 |
Knowledge-based biomedical Data Science |
Q57001498 |
| 32 |
The Species Concept Among Viruses |
Q59063943 |
| 33 |
The application of computers to taxonomy |
Q28181838 |
| 34 |
Publishing DisGeNET as nanopublications |
Q31194033 |
| 35 |
The moral status of animals |
Q79763269 |
| 36 |
The use of models in bacterial classification |
Q78658697 |
| 37 |
The types of retinal ganglion cells: current status and implications for neuronal classification. |
Q38432885 |
| 38 |
Genuine semantic publishing |
Q46412887 |
| 39 |
The anatomy of a nanopublication |
Q57011346 |
| 40 |
Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. |
Q52720499 |
| 41 |
A gene expression atlas of the central nervous system based on bacterial artificial chromosomes |
Q29617753 |
| 42 |
SourceData: a semantic platform for curating and searching figures. |
Q48094767 |
| 43 |
Biological knowledge management: the emerging role of the Semantic Web technologies. |
Q37490532 |
| 44 |
Systematic integration of biomedical knowledge prioritizes drugs for repurposing. |
Q42255083 |
| 45 |
Utopia documents: linking scholarly literature with research data |
Q28292614 |
| 46 |
Astrocyte layers in the mammalian cerebral cortex revealed by a single-cell in situ transcriptomic map |
Q90591926 |
| 47 |
Web scraping technologies in an API world |
Q86694255 |
| 48 |
How we learnt to stop worrying and love web scraping |
Q99234140 |
| 49 |
A translational profiling approach for the molecular characterization of CNS cell types |
Q29615252 |
| 50 |
Publishing on the semantic web |
Q28185770 |
| 51 |
A periodic table of cell types |
Q93086975 |
| 52 |
Universal cell type identifier based on number theory. |
Q52374237 |
| 53 |
Neuronal cell types. |
Q35830509 |
| 54 |
Heterogeneity of neutrophils |
Q91997728 |
| 55 |
Natural killer cell immunotypes related to COVID-19 disease severity |
Q98622035 |
| 56 |
Adventures in semantic publishing: exemplar semantic enhancements of a research article |
Q21092566 |
| 57 |
Reproducibility of Flow Cytometry Through Standardization: Opportunities and Challenges |
Q90588777 |
| 58 |
Application of a translational profiling approach for the comparative analysis of CNS cell types |
Q42585641 |
| 59 |
Will a biological database be different from a biological journal? |
Q21092584 |
| 60 |
The future of annotation/biocuration |
Q56880438 |
| 61 |
Swiss-Prot: juggling between evolution and stability. |
Q47579749 |
| 62 |
Retinal ganglion cells: properties, types, genera, pathways and trans-species comparisons. |
Q48839876 |
| 63 |
WikiPathways: connecting communities |
Q102205677 |
| 64 |
The neuron classification problem |
Q36854753 |
| 65 |
Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex |
Q24620160 |
| 66 |
Protein ontology on the semantic web for knowledge discovery |
Q100525924 |
| 67 |
Towards a classification of stem cells |
Q64097544 |
| 68 |
Reader engagement with medical content on Wikipedia |
Q90109096 |
| 69 |
How Single-Cell Genomics Is Changing Evolutionary and Developmental Biology. |
Q38622289 |
| 70 |
The evolution of cell types in animals: emerging principles from molecular studies. |
Q37301036 |
| 71 |
Key transitions during the evolution of animal phototransduction: novelty, "tree-thinking," co-option, and co-duplication. |
Q46221687 |
| 72 |
Neuronal diversity: too many cell types for comfort? |
Q48373178 |
| 73 |
The BridgeDb framework: standardized access to gene, protein and metabolite identifier mapping services |
Q28842753 |
| 74 |
Definitions |
Q102232524 |
| 75 |
A recipe book for cell types in the human brain |
Q93087299 |
| 76 |
Single-cell sequencing paints diverse pictures of the brain |
Q58084012 |
| 77 |
Neuron Names: A Gene- and Property-Based Name Format, With Special Reference to Cortical Neurons |
Q64065346 |
| 78 |
The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas. |
Q42778383 |
| 79 |
Transcriptional landscape of the prenatal human brain |
Q33926910 |
| 80 |
Nanopublications: A Growing Resource of Provenance-Centric Scientific Linked Data |
Q62924270 |
| 81 |
Transcriptomic and morphophysiological evidence for a specialized human cortical GABAergic cell type |
Q60017992 |
| 82 |
DisGeNET-RDF: harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases |
Q28596617 |
| 83 |
Cell-type-specific consequences of Reelin deficiency in the mouse neocortex, hippocampus, and amygdala |
Q28595082 |
| 84 |
The Semanticscience Integrated Ontology (SIO) for biomedical research and knowledge discovery |
Q19671659 |
| 85 |
Ontology Design Patterns for Semantic Web Content |
Q57774232 |
| 86 |
Single-nucleus and single-cell transcriptomes compared in matched cortical cell types |
Q60933812 |
| 87 |
How should access to a COVID-19 vaccine be regulated? |
Q102542608 |
| 88 |
Shifting the paradigm: new approaches for characterizing and classifying neurons. |
Q37629171 |
| 89 |
OWL 2 Web Ontology Language Document Overview (Second Edition) |
Q102926772 |
| 90 |
OWL 2 Web Ontology Language Primer (Second Edition) |
Q102929379 |
| 91 |
A genetic and computational approach to structurally classify neuronal types. |
Q34182035 |
| 92 |
Adult mouse cortical cell taxonomy revealed by single cell transcriptomics |
Q27311570 |
| 93 |
Identifiers.org - Compact Identifier Services in the Cloud |
Q100500142 |
| 94 |
Immune-centric network of cytokines and cells in disease context identified by computational mining of PubMed. |
Q64962407 |
| 95 |
Single-nucleus RNA-seq identifies Huntington disease astrocyte states |
Q89763874 |
| 96 |
Converting neXtProt into Linked Data and nanopublications |
Q103834013 |
| 97 |
Innovations present in the primate interneuron repertoire |
Q100395427 |
| 98 |
A curated database reveals trends in single-cell transcriptomics |
Q103034964 |
| 99 |
Species and cell-type properties of classically defined human and rodent neurons and glia |
Q57462271 |
| 100 |
Single cell transcriptomics in neuroscience: cell classification and beyond |
Q88605805 |
| 101 |
Towards the collaborative curation of the registry underlying Identifiers.org |
Q28709067 |
| 102 |
The Covid-19 Conundrum |
Q103964322 |
| 103 |
Towards the automatic classification of neurons |
Q27010194 |
| 104 |
Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. |
Q42776227 |
| 105 |
Adding a little reality to building ontologies for biology |
Q21136172 |
| 106 |
Data curation + process curation=data integration + science |
Q28303099 |
| 107 |
Implementing a "publish, then review" model of publishing |
Q103811380 |
| 108 |
Interneuron cell types are fit to function |
Q27021885 |
| 109 |
Getting started in text mining |
Q21145382 |
| 110 |
Abstract Meaning Representation for Sembanking |
Q104092178 |
| 111 |
Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq |
Q34094294 |
| 112 |
The genomic landscapes of individual melanocytes from human skin |
Q100491078 |
| 113 |
Immune-evasive human islet-like organoids ameliorate diabetes |
Q98568692 |
| 114 |
A single-cell transcriptome atlas of marsupial embryogenesis and X inactivation |
Q98568691 |
| 115 |
Nanopublications for exposing experimental data in the life-sciences: a Huntington's Disease case study |
Q28606409 |
| 116 |
Querying neXtProt nanopublications and their value for insights on sequence variants and tissue expression |
Q54670808 |
| 117 |
Northstar enables automatic classification of known and novel cell types from tumor samples |
Q99564826 |
| 118 |
Molecular biology gets wikified |
Q104161380 |
| 119 |
Capillary cell-type specialization in the alveolus |
Q100560109 |
| 120 |
Naming human genes |
Q98196903 |
| 121 |
Guidelines for human gene nomenclature |
Q98148417 |
| 122 |
Knowledge networks in the age of the Semantic Web |
Q28842577 |
| 123 |
Internet encyclopaedias go head to head |
Q24239902 |
| 124 |
snRNA-seq reveals a subpopulation of adipocytes that regulates thermogenesis |
Q101051363 |
| 125 |
Beyond the frontiers of neuronal types. |
Q42156351 |
| 126 |
Ontology Design Patterns for bio-ontologies: a case study on the Cell Cycle Ontology |
Q21093639 |
| 127 |
Name-calling in the hippocampus (and beyond): coming to terms with neuron types and properties. |
Q37656899 |
| 128 |
Biocuration - mapping resources and needs |
Q101217428 |
| 129 |
Computing Machinery and Intelligence |
Q772056 |
| 130 |
ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing |
Q101248419 |
| 131 |
Hippocampome.org: a knowledge base of neuron types in the rodent hippocampus |
Q26253817 |
| 132 |
An ontological approach to describing neurons and their relationships |
Q28730328 |
| 133 |
Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE |
Q34037159 |
| 134 |
NeuroLex.org: an online framework for neuroscience knowledge |
Q28681367 |
| 135 |
New insights into the classification and nomenclature of cortical GABAergic interneurons |
Q36747163 |
| 136 |
Revisiting enigmatic cortical calretinin-expressing interneurons |
Q33796214 |
| 137 |
Concept Wikiﬁcation for COVID-19 |
Q104392113 |
| 138 |
Local and Global Algorithms for Disambiguation to Wikipedia |
Q104415799 |
| 139 |
Beyond the frontiers of neuronal types: fuzzy classification of interneurons. |
Q46137497 |
| 140 |
Probabilistic cell typing enables fine mapping of closely related cell types in situ |
Q91330127 |
| 141 |
mRNA-Seq whole-transcriptome analysis of a single cell |
Q28240611 |
| 142 |
Entity linking for biomedical literature |
Q28642941 |
| 143 |
SciBERT: A Pretrained Language Model for Scientific Text |
Q104433073 |
| 144 |
Text mining approaches for dealing with the rapidly expanding literature on COVID-19 |
Q104079663 |
| 145 |
Structural Scaffolds for Citation Intent Classification in Scientific Publications |
Q104450390 |
| 146 |
Integration of electrophysiological recordings with single-cell RNA-seq data identifies neuronal subtypes |
Q31033187 |
| 147 |
Integrated Single-Cell Atlases Reveal an Oral SARS-CoV-2 Infection and Transmission Axis |
Q101210731 |
| 148 |
Bridging the Gap Between Research and Practice: Predicting What Will Work Locally |
Q104475823 |
| 149 |
Identification and characterization of distinct brown adipocyte subtypes in C57BL/6J mice |
Q103800764 |
| 150 |
Dental cell type atlas reveals stem and differentiated cell types in mouse and human teeth |
Q99616616 |
| 151 |
Construction of the Literature Graph in Semantic Scholar |
Q69587220 |
| 152 |
CellMarker: a manually curated resource of cell markers in human and mouse |
Q56984510 |
| 153 |
A standard nomenclature for referencing and authentication of pluripotent stem cells. |
Q48503347 |
| 154 |
A resource for cell line authentication, annotation and quality control. |
Q38886793 |
| 155 |
GeneDB and Wikidata |
Q91273803 |
| 156 |
The Cellosaurus, a cell-line knowledge resource. |
Q54370168 |
| 157 |
The bacterial species definition in the genomic era. |
Q33261434 |
| 158 |
Theory of cell fate |
Q91908361 |
| 159 |
Building a biomedical semantic network in Wikipedia with Semantic Wiki Links |
Q21169186 |
| 160 |
Userscripts for the life sciences |
Q27062487 |
| 161 |
biocuration |
biocuration |
| 162 |
SemMedDB: a PubMed-scale repository of biomedical semantic predications |
Q36432186 |
| 163 |
Wikidata as a linked-data hub for Biodiversity data |
Q66058247 |
| 164 |
Forcing cells to change lineages. |
Q34020397 |
| 165 |
Stem cell states, fates, and the rules of attraction. |
Q37475461 |
| 166 |
Integrated Morphoelectric and Transcriptomic Classification of Cortical GABAergic Cells |
Q102056745 |
| 167 |
Common Cell type Nomenclature for the mammalian brain: A systematic, extensible convention |
Q104247451 |
| 168 |
Neuro-symbolic representation learning on biological knowledge graphs. |
Q38377458 |
| 169 |
Structured reviews for data and knowledge-driven research |
Q91866899 |
| 170 |
Data management made simple |
Q56524364 |
| 171 |
Everyone needs a data-management plan |
Q56524391 |
| 172 |
Neuronal cell-type classification: challenges, opportunities and the path forward. |
Q46326031 |
| 173 |
Naming of neurones. Classification and naming of cat retinal ganglion cells. |
Q41052480 |
| 174 |
A rose by any other name... on 'naming of neurones' by Rowe and Stone. |
Q39790383 |
| 175 |
Describing species: practical taxonomic procedure for biologists |
Q104043701 |
| 176 |
Searching large-scale scRNA-seq databases via unbiased cell embedding with Cell BLAST |
Q97529981 |
| 177 |
CellFishing.jl: an ultrafast and scalable cell search method for single-cell RNA sequencing |
Q64237155 |
| 178 |
Probabilistic gene expression signatures identify cell-types from single cell RNA-seq data |
Q104371272 |
| 179 |
CHETAH: a selective, hierarchical cell type identification method for single-cell RNA sequencing |
Q92937241 |
| 180 |
Single-cell RNAseq cell cluster labelling by reference (celaref) |
Q104552099 |
| 181 |
PanglaoDB: a web server for exploration of mouse and human single-cell RNA sequencing data |
Q63664483 |
| 182 |
Unifying single-cell annotations based on the Cell Ontology |
Q104057222 |
| 183 |
Identifying gene expression programs of cell-type identity and cellular activity with single-cell RNA-Seq |
Q83231039 |
| 184 |
MARS: discovering novel cell types across heterogeneous single-cell experiments |
Q100737318 |
| 185 |
Eleven grand challenges in single-cell data science |
Q89599719 |
| 186 |
A comparison of automatic cell identification methods for single-cell RNA sequencing data |
Q89998341 |
| 187 |
scMontage: Fast and Robust Gene Expression Similarity Search for Massive Single-cell Data |
Q104552207 |
| 188 |
Current best practices in single-cell RNA-seq analysis: a tutorial. |
Q64974172 |
| 189 |
Revealing the vectors of cellular identity with single-cell genomics. |
Q39002947 |
| 190 |
CellO: comprehensive and hierarchical cell type classification of human cells with the Cell Ontology |
Q104552259 |
| 191 |
Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors. |
Q34555562 |
| 192 |
Single-cell sequencing of the human midbrain reveals glial activation and a neuronal state specific to Parkinson's disease |
Q104552303 |
| 193 |
Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets |
Q34044099 |
| 194 |
Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris |
Q59070958 |
| 195 |
Comprehensive single-cell transcriptional profiling of a multicellular organism. |
Q38619221 |
| 196 |
Broad transcriptional dysregulation of brain and choroid plexus cell types with COVID-19 |
Q104552382 |
| 197 |
A Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility |
Q59770872 |
| 198 |
Cell type discovery using single-cell transcriptomics: implications for ontological representation. |
Q52625486 |
| 199 |
ontoProc: processing of ontologies of anatomy, cell lines, and so on |
Q101074371 |
| 200 |
Cells in experimental life sciences - challenges and solution to the rapid evolution of knowledge. |
Q48519854 |
| 201 |
Cells in ExperimentaL Life Sciences (CELLS-2018): capturing the knowledge of normal and diseased cells with ontologies. |
Q64928913 |
| 202 |
Reporting and connecting cell type names and gating definitions through ontologies |
Q91614095 |
| 203 |
An ontology for cell types |
Q21184168 |
| 204 |
Logical development of the cell ontology. |
Q33786317 |
| 205 |
An improved ontological representation of dendritic cells as a paradigm for all cell types |
Q21284365 |
| 206 |
Hematopoietic cell types: prototype for a revised cell ontology |
Q33940690 |
| 207 |
Usage of cell nomenclature in biomedical literature. |
Q47565472 |
| 208 |
Cell ontology in an age of data-driven cell classification. |
Q49192555 |
| 209 |
flowCL: ontology-based cell population labelling in flow cytometry |
Q23809269 |
| 210 |
CLO: The cell line ontology |
Q28650204 |
| 211 |
Formalization of taxon-based constraints to detect inconsistencies in annotation and ontology development. |
Q33727235 |
| 212 |
Toward principles for the design of ontologies used for knowledge sharing? |
Q47303277 |
| 213 |
What Is Your Conceptual Definition of "Cell Type" in the Context of a Mature Organism? |
Q87649649 |
| 214 |
Exciting times to study the identity and evolution of cell types |
Q90182085 |
| 215 |
Function first: classifying cell types and circuits of the retina |
Q93189154 |
| 216 |
Defining cell types and states with single-cell genomics |
Q26782737 |
| 217 |
Cell type discovery and representation in the era of high-content single cell phenotyping. |
Q47870911 |
| 218 |
Defining cellular identity through network biology. |
Q42084918 |
| 219 |
Mapping the transcriptional diversity of genetically and anatomically defined cell populations in the mouse brain |
Q64118290 |
| 220 |
Terminal Selectors of Neuronal Identity. |
Q38771724 |
| 221 |
Construction of a human cell landscape at single-cell level |
Q90665256 |
| 222 |
The definition of cell type |
Q77807915 |
| 223 |
The Human Cell Atlas: from vision to reality. |
Q47565008 |
| 224 |
CELLPEDIA: a repository for human cell information for cell studies and differentiation analyses. |
Q35482351 |
| 225 |
Human Cell Atlas and cell-type authentication for regenerative medicine |
Q99418657 |
| 226 |
Developing Global Cellular Information Retrieval System with Minimum Reporting Guidelines on Cellular Data for Regenerative Medicine |
Q104553080 |
| 227 |
The human body at cellular resolution: the NIH Human Biomolecular Atlas Program |
Q90617765 |
| 228 |
An estimation of the number of cells in the human body. |
Q34037445 |
| 229 |
Opinion: Why science needs philosophy |
Q63479773 |
| 230 |
The meanings of 'function' in biology and the problematic case of de novo gene emergence |
Q83227592 |
| 231 |
Philosophical bias is the one bias that science cannot avoid |
Q64097527 |
| 232 |
The challenges of big data biology |
Q63241652 |
| 233 |
From primal scenes to synthetic cells |
Q64097538 |
| 234 |
Ontologies in biology: design, applications and future challenges. |
Q35670188 |
| 235 |
Ontologies: Formalising biological knowledge for bioinformatics. |
Q38522811 |
| 236 |
FR-Match: robust matching of cell type clusters from single cell RNA sequencing data using the Friedman-Rafsky non-parametric test |
Q103045800 |
| 237 |
Overview of the Alliance for Cellular Signaling. |
Q34164191 |
| 238 |
CellFinder: a cell data repository |
Q28660708 |
| 239 |
HeLa, a new microbial species |
Q104591553 |
| 240 |
A survey on annotation tools for the biomedical literature. |
Q38068801 |
| 241 |
Keeping raw data in context. |
Q43589284 |
| 242 |
What makes a gene name? Named entity recognition in the biomedical literature. |
Q51955678 |
| 243 |
Zika virus: designate standardized names |
Q24247056 |
| 244 |
Representing Specified Values in OWL: "value partitions" and "value sets" |
Q104601506 |
| 245 |
CELDA -- an ontology for the comprehensive representation of cells in complex systems |
Q21284308 |
| 246 |
Using ontologies to study cell transitions |
Q34026802 |
| 247 |
Genetic identification of brain cell types underlying schizophrenia |
Q58462175 |
| 248 |
Q104626424 |
Q104626424 |
| 249 |
Uniform resolution of compact identifiers for biomedical data. |
Q55053685 |
| 250 |
Semantically enabling a genome-wide association study database |
Q28707570 |
| 251 |
The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species |
Q91179320 |
| 252 |
A Survey of Bioinformatics Database and Software Usage through Mining the Literature |
Q28600864 |
| 253 |
LifeMap Discovery™: the embryonic development, stem cells, and regenerative medicine research portal |
Q34846475 |
| 254 |
Distinction of Neurons, Glia and Endothelial Cells in the Cerebral Cortex: An Algorithm Based on Cytological Features |
Q36193595 |
| 255 |
The Molecular Pages of the mesotelencephalic dopamine consortium (DopaNet) |
Q24802073 |
| 256 |
SC2disease: a manually curated database of single-cell transcriptome for human diseases |
Q100429893 |
| 257 |
AliBaba: PubMed as a graph. |
Q43433584 |
| 258 |
The language of gene ontology: a Zipf's law analysis |
Q28268340 |
| 259 |
Applying Ontology Design Patterns in Bio-ontologies |
Q57002925 |
| 260 |
The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. |
Q41861103 |
| 261 |
A maximum-likelihood approach for building cell-type trees by lifting |
Q35906597 |
| 262 |
Cell-type phylogenetics and the origin of endometrial stromal cells. |
Q38904507 |
| 263 |
Implications of Epigenetic Variability within a Cell Population for "Cell Type" Classification |
Q26770736 |
| 264 |
Decentralized provenance-aware publishing with nanopublications |
Q57339063 |
| 265 |
Trusty URIs: Verifiable, Immutable, and Permanent Digital Artifacts for Linked Data |
Q56915510 |
| 266 |
Using the brainbow to trace lineages in early mouse development |
Q58836377 |
| 267 |
A transcriptome database for astrocytes, neurons, and oligodendrocytes: a new resource for understanding brain development and function |
Q29547320 |
| 268 |
The value of data |
Q22676713 |
| 269 |
Knowledge.Bio: A Web application for exploring, building and sharing webs of biomedical relationships mined from PubMed |
Q57831016 |
| 270 |
histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data. |
Q38637165 |
| 271 |
What is a glial cell? |
Q46388366 |
| 272 |
Div-Seq: Single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons. |
Q41068482 |
| 273 |
Geometry of the Gene Expression Space of Individual Cells |
Q35688096 |
| 274 |
A Survey and Classification of Controlled Natural Languages |
Q57402167 |
| 275 |
Fish oil, Raynaud's syndrome, and undiscovered public knowledge |
Q69703977 |
| 276 |
Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program |
Q29614363 |
| 277 |
BioGPS and MyGene.info: organizing online, gene-centric information |
Q27575818 |
| 278 |
Accurate estimation of cell-type composition from gene expression data |
Q91665384 |
| 279 |
Robust enumeration of cell subsets from tissue expression profiles |
Q36539395 |
| 280 |
Determining cell type abundance and expression from bulk tissues with digital cytometry |
Q64109527 |
| 281 |
Evolution of Cellular Differentiation: From Hypotheses to Models |
Q98633613 |
| 282 |
Utilizing the Wikidata system to improve the quality of medical content in Wikipedia in diverse languages: a pilot study |
Q21503276 |
| 283 |
Cell Identity Codes: Understanding Cell Identity from Gene Expression Profiles using Deep Neural Networks |
Q64263662 |
| 284 |
Genome-wide atlas of gene expression in the adult mouse brain |
Q26253934 |
| 285 |
Group formation, relatedness, and the evolution of multicellularity |
Q86916694 |
| 286 |
GiniClust2: a cluster-aware, weighted ensemble clustering method for cell-type detection. |
Q53748361 |
| 287 |
Situating Wikipedia as a health information resource in various contexts: A scoping review |
Q85632863 |
| 288 |
Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis. |
Q37201814 |
| 289 |
An RDF/OWL knowledge base for query answering and decision support in clinical pharmacogenetics. |
Q38420432 |
| 290 |
Introduction to Random Boolean Networks |
Q104815188 |
| 291 |
A global network of biomedical relationships derived from text. |
Q52681328 |
| 292 |
Literature Based Discovery: models, methods, and trends. |
Q38371706 |
| 293 |
Identification of region-specific astrocyte subtypes at single cell resolution |
Q90091126 |
| 294 |
Single-cell profiling identifies myeloid cell subsets with distinct fates during neuroinflammation |
Q91210236 |
| 295 |
BioGPS: an extensible and customizable portal for querying and organizing gene annotation resources. |
Q21183895 |
| 296 |
Literature-based discovery of new candidates for drug repurposing. |
Q38817541 |
| 297 |
GiniClust: detecting rare cell types from single-cell gene expression data with Gini index. |
Q31111856 |
| 298 |
Evolutionary trade-offs, Pareto optimality, and the geometry of phenotype space. |
Q54337677 |
| 299 |
CA1 pyramidal cells have diverse biophysical properties, affected by development, experience, and aging |
Q41694511 |
| 300 |
Single-cell messenger RNA sequencing reveals rare intestinal cell types. |
Q34490100 |
| 301 |
Toward an epistemology of Wikipedia |
Q101955295 |
| 302 |
Online tools to support literature-based discovery in the life sciences. |
Q36280460 |
| 303 |
The distribution of cellular turnover in the human body |
Q104873201 |
| 304 |
Revised Estimates for the Number of Human and Bacteria Cells in the Body |
Q34537872 |
| 305 |
Literature mining for the biologist: from information retrieval to biological discovery |
Q30002370 |
| 306 |
Overview of BioCreAtIvE: critical assessment of information extraction for biology |
Q21093643 |
| 307 |
What is the total number of protein molecules per cell volume? A call to rethink some published values |
Q26782007 |
| 308 |
Are We Really Vastly Outnumbered? Revisiting the Ratio of Bacterial to Host Cells in Humans. |
Q34511374 |
| 309 |
UniProt: the universal protein knowledgebase in 2021 |
Q102383737 |
| 310 |
Evaluation of text data mining for database curation: lessons learned from the KDD Challenge Cup. |
Q30811199 |
| 311 |
Are Platelets Cells? And if Yes, are They Immune Cells? |
Q28083403 |
| 312 |
Extracellular vesicles or exosomes? On primacy, precision, and popularity influencing a choice of nomenclature |
Q93135668 |
| 313 |
Q104904652 |
Q104904652 |
| 314 |
Rutabaga by any other name: extracting biological names. |
Q42599537 |
| 315 |
Body cell mass: model development and validation at the cellular level of body composition. |
Q47579411 |
| 316 |
Mitochondrial DNA molecules and virtual number of mitochondria per cell in mammalian cells. |
Q34168557 |
| 317 |
An interactive system for finding complementary literatures: a stimulus to scientific discovery |
Q57372877 |
| 318 |
Exploiting semantic relations for literature-based discovery. |
Q35725188 |
| 319 |
The quantified cell |
Q34504200 |
| 320 |
SnapShot: key numbers in biology. |
Q34124340 |
| 321 |
BioNumbers--the database of key numbers in molecular and cell biology |
Q24643881 |
| 322 |
One Knowledge Graph to Rule Them All? Analyzing the Differences Between DBpedia, YAGO, Wikidata & co |
Q41078402 |
| 323 |
An era of single-cell genomics consortia |
Q99418649 |
| 324 |
The Human Cell Atlas: Technical approaches and challenges. |
Q48563763 |
| 325 |
The automation of science. |
Q27937312 |
| 326 |
Representation of probabilistic scientific knowledge. |
Q36786073 |
| 327 |
An atlas of active enhancers across human cell types and tissues. |
Q34660689 |
| 328 |
A promoter-level mammalian expression atlas |
Q34412203 |
| 329 |
Cell type-specific genetic regulation of gene expression across human tissues |
Q99349840 |
| 330 |
xCell: digitally portraying the tissue cellular heterogeneity landscape. |
Q46377913 |
| 331 |
Identifying cell types to interpret scRNA-seq data: how, why and more possibilities |
Q90784336 |
| 332 |
Models of global gene expression define major domains of cell type and tissue identity |
Q33558314 |
| 333 |
Building a high-quality Human Cell Atlas |
Q105080655 |
| 334 |
scMatch: a single-cell gene expression profile annotation tool using reference datasets |
Q91557912 |
| 335 |
A protocol for adding knowledge to Wikidata: aligning resources on human coronaviruses |
Q105037759 |
| 336 |
Automating drug discovery. |
Q47780833 |
| 337 |
Conceptions of Good Science in Our Data-Rich World. |
Q55214531 |
| 338 |
On the formalization and reuse of scientific research. |
Q34178056 |
| 339 |
A subcellular map of the human proteome. |
Q48155823 |
| 340 |
Representation, simulation, and hypothesis generation in graph and logical models of biological networks. |
Q37921686 |
| 341 |
The EXACT description of biomedical protocols. |
Q38513299 |
| 342 |
The Bari Manifesto: An interoperability framework for essential biodiversity variables |
Q60250756 |
| 343 |
The Philosophy of Logical Atomism, Lecture 1: Facts and Propositions |
Q105105637 |
| 344 |
Transcriptomes of the major human pancreatic cell types. |
Q37430849 |
| 345 |
Variability and memory of protein levels in human cells. |
Q40205119 |
| 346 |
scConsensus: combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data |
Q104450617 |
| 347 |
Study of cell differentiation by phylogenetic analysis using histone modification data |
Q30841360 |
| 348 |
Evaluation of text-mining systems for biology: overview of the Second BioCreative community challenge. |
Q34844839 |
| 349 |
Q |
Q |
| 350 |
Topic pages: PLoS Computational Biology meets Wikipedia |
Q21092570 |
| 351 |
Submit a Topic Page to PLOS Computational Biology and Wikipedia |
Q54655231 |
| 352 |
Genomic and molecular control of cell type and cell type conversions. |
Q49436822 |
| 353 |
Inferring cell type innovations by phylogenetic methods-concepts, methods, and limitations. |
Q40436539 |
| 354 |
From Freebase to Wikidata: The Great Migration |
Q24074986 |
| 355 |
What Makes a Good Collaborative Knowledge Graph: Group Composition and Quality in Wikidata |
Q38918394 |
| 356 |
Single-cell sequencing-based technologies will revolutionize whole-organism science. |
Q34360540 |
| 357 |
Model-based understanding of single-cell CRISPR screening |
Q64052031 |
| 358 |
Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage |
Q91045816 |
| 359 |
Strategic reading, ontologies, and the future of scientific publishing. |
Q33493284 |
| 360 |
Geospatial data and Scholia |
Q50813856 |


cargo new
This is the beginning of my journey to learn Rust. From time to time I'll be throwing some crumbs... rusty crumbs.
cargo new --lib rusty-crumbs
There's a lot of paths to follow... here are some I'll walk for sure:
- Webassembly
- Web Development [fullstack]
- Async / Networking
- Crypto
- Computer Graphics
- System Programming
The main goal of this site is to create a future reference for my own, I'm not very good remembering things. I'm thinking to take what I learn from different sources like: books, courses, tutorials, etc. and create my own examples in order to practice.


2.2 Storage Allocation
When we declare a pointer in C, a certain amount of space is
allocated for it, just as for other types of variables.
Pointers generally occupy one machine
word, but their size can vary. Therefore, for portability, we
should never assume that a pointer has a specific size.
Pointers often vary in size as a result of compiler settings
and type specifiers allowed by certain C implementations. It
is also important to remember that when we declare a pointer,
space is allocated only for the pointer itself; no space is
allocated for the data the pointer references. Storage for the
data is allocated in one of two ways: by declaring a variable
for it or by allocating storage dynamically at runtime (using malloc or realloc, for example).
When we declare a variable, its type tells
the compiler how much storage to set aside for it as the
program runs. Storage for the variable is allocated
automatically, but it may not be persistent throughout the
life of the program. This is especially important to remember
when dealing with pointers to automatic variables. Automatic variables are those for
which storage is allocated and deallocated automatically when
entering and leaving a block or function. For example, since
iptr is set to the address of the automatic
variable a in the following function f, iptr becomes a
dangling pointer when f
returns. This situation occurs because once f returns, a is no
longer valid on the program stack (see Chapter
3). int f(int **iptr) {
int a = 10;
*iptr = &a;
return 0;
}
In C, when we dynamically allocate storage,
we get a pointer to some storage on the heap (see Chapter
3). Since it is then our responsibility to manage this
storage ourselves, the storage remains valid until we
explicitly deallocate it. For example, the storage allocated
by malloc in the following code
remains valid until we call free at some later time. Thus, it
remains valid even after g
returns (see Figure
2.2), unlike the storage allocated automatically for
a previously. The parameter
iptr is a pointer to the object we wish to
modify (another pointer) so that when g returns, iptr
contains the address returned by malloc. This idea is explored further
in the section on pointers as parameters to functions. #include <stdlib.h>
int g(int **iptr) {
if ((*iptr = (int *)malloc(sizeof(int))) == NULL)
return -1;
return 0;
}
Pointers and storage
allocation are arguably the areas of C that provide the most
fodder for the language's sometimes bad reputation. The misuse
of dynamically allocated storage, in
particular, is a notorious source of memory leaks. Memory leaks are blocks of storage that are
allocated but never freed by a program, even when no longer in
use. They are particularly detrimental when found in sections
of code that are executed repeatedly. Fortunately, we can
greatly reduce memory leaks by employing consistent approaches
to how we manage storage.
One example of a
consistent approach to storage management is the one used for
data structures presented in this
book. The philosophy followed in every case is that it is the
responsibility of the user to manage the storage associated
with the actual data that the data structure organizes; the
data structure itself allocates storage only for internal
structures used to keep the data organized. Consequently, only
pointers are maintained to the data inserted into the data
structure, rather than private copies of the data. One
important implication of this is that a data structure's
implementation does not depend on the type and size of the
data it stores. Also, multiple data structures are able to
operate on a single copy of data, which can be useful when
organizing large amounts of data.
In addition,
this book provides operations for initializing and destroying
data structures. Initialization may involve many steps, one of
which may be the allocation of memory. Destroying a data
structure generally involves removing all of its data and
freeing the memory allocated in the data structure. Destroying
a data structure also usually involves freeing all memory
associated with the data itself. This is the one exception to
having the user manage storage for the data. Since managing
this storage is an application-specific operation, each data
structure uses a function provided by the user when the data
structure is initialized. |


You can only drop names starting with a vowel.
You can only drag the items to the zones where they are accepted. Try to drag the names them back end forth.
You can only drag the items using the drag handle.


The inactive Workgroup for Imaging Management Solutions (WIMS) was concerned with the definition of new and recasting of previously defined imaging device and service management elements for mapping into standard managment semantics and protocols. These protocols include, but are not limited to, SNMP, CIM, and Web Services Management. The (active) IPP workgroup provides continuing support for printing-related IETF RFCs including the Printer MIB (RFC 3805), Finisher MIB (RFC 3806) and the Job Monitoring MIB (RFC 2707).
Mailing list<EMAIL_ADDRESS>· Subscribe · Archive
PWG Candidate Standard 5106.1-2007 - The PWG Standardized Imaging System Counters v1.1
PWG Candidate Standard 5106.2-2006 - The PWG Web-based Imaging Management Service v1.0
PWG Candidate Standard 5106.3-2008 - PWG Imaging System State and Counter MIB v2.0
PWG Candidate Standard 5106.4-2011 - PWG Power Management Model for Imaging Systems 1.0
PWG Candidate Standard 5106.5-2011 - PWG Imaging System Power MIB v1.0
RFC 2707 - Job Monitoring MIB
RFC 3805 - Printer MIB v2
RFC 3806 - Finisher MIB
CIM, including Common Information Model (CIM), Web-Based Enterprise Management (WEBM) and Alert Standard Format (ASF)


Test Summary
Time Left: {{timeString}}
Total Questions: {{totalQuestionsInTest}}
Attempt Summary:
| Attempted Questions |
Not Attempted Questions |
Questions Marked for Review |
| {{numberOfAttemptedQuestions}} |
{{numberOfUnAttemptedQuestions}} |
{{numberOfReviewedQuestions}} |
Test once ended, cannot be resumed.
Test once ended, cannot be resumed.
Please contact the supervisor if you want to resume the test.
Please refresh this page after the supervisor's instructions.
Your test is over.
Thank you for attending the test.
Since you exceeded the limit of browser tolerance, your test has been ended.


The final extinction of a population usually is probabilistic. That is, once the population gets small enough, demographic stochasticity, genetic drift, and inbreeding depression can together deal the final death knell to a population. In conservation biology the study of processes that disproportionately influence small populations is called the small-population paradigm.
That is: the small-population paradigm refers to the tendency in conservation biology to study those largely stochastic factors that can result in the extinction or degradation of small populations.
We have already been through this concept, which is central to the small population paradigm!
The simple fact is: it’s much more likely for all 10 individuals in a population to be unlucky in a given year than for all 1000 individuals in a population to be unlucky in a given year!! – just as it is very unlikely for all coin flips out of 1000 to come up heads…
This illustrates the very important concept, that small populations can go extinct due to demographic stochasticity alone, whereas this possibility is vanishingly small for large populations.
The moral of the story for demographic stochasticity was: weird things (e.g., extinction) can happen in small populations!
Weird things like random extinction just would never happen in large populations!
Same goes for genetic drift! Genetic drift is a small-population phenomenon!
In large populations, you could never randomly get fixation of a particular gene (this could happen via natural selection, but not through random reproductive processes).
Let’s imagine that the balls in the jars in the above figure are individuals. The black dots indicate how many offspring that individual will have (thereby passing on its genes). Finally, let’s imagine that the red balls are individuals that are more likely to survive a rare drought (but have no selective advantage or disadvantage under normal circumstances).
Under these conditions, the number of births is completely random. And if this was a sexually reproducing diploid population, mating would be completely random too.
Just by random chance, the blue individuals happen to reproduce more than the red individuals- and the red individuals go extinct. Does this sound similar to a process we have already discussed in this class?
And now, by random chance, this population is now more susceptible to drought!
Inbreeding depression is similar to genetic drift, but more specific! Again, inbreeding problems only occur in small populations.
Most diploid populations have some “bad genes” floating around. These are often called deleterious alleles. These deleterious alleles usually don’t cause problems becuase in general they are recessive - that is, the bad effect is only apparent if an individual has two copies of that allele!
Why is it more likely to get two copies of the same allele if your two parents are close relatives?
The above image of Charles II of Spain indicates what can happen when you inherit too many alleles that are identical by descent!
Why is it more likely for your two parents to be close relatives if you are living in a small population?
One of the central ideas arising from the small population paradigm is the concept of the extinction vortex. This concept is illustrated in the above figure.
Once a population gets small enough, it becomes subject to catastrophic declines due to demographic stochasticity, leading to inbreeding and random loss of useful genes, leading to reduced vital rates, leading to smaller population sizes, leading to further genetic degradation, leading to more possibility of catastrophic declines due to demographic stochasticity, leading to … EXTINCTION!!
We have seen this concept already, in the context of the Allee Effect. However, there is a more general definition, related to the extinction vortex.
Minimum Viable Population is defined as that population size whereby the extinction vortex can be safely averted!
Population Viability Analysis (PVA) is often used to model the processes in the extinction vortex, including genetic drift. In this class, we won’t get into modeling genetics (that’s for a different course!)
The most widely-used PVA software, Vortex, gets its name from the extinction vortex concept. Vortex does allow explicit modeling of inbreeding and loss of genetic diversity in small populations.
The aruba island rattlesnake, or Cascabel (Crotalus durissus unicolor), is the top predator on the island of Aruba, and primarily consumes rodents.
The Aruba island rattlenake, as you might expect, occurs only on the island of Aruba.
The Aruba rattlesnake is listed as Critically Endangered by IUCN, and has several attributes that make it particularly susceptible to falling into the extinction vortex:


YPII
Home
Quality Reports
Surgical
Surgical Statistics
Surgical Cytology Correlation
Intraoperative Consultation Report
Frozen/Final Correlation Report
TAT Report
TAT Report
Cytology
Cytology Daily Signout
Molecular
HPV TAT
Molecular Test Volume
Flow Statistics
Flow
Flow Test Volume
Flow Statistics
Flow Report Corrections/Addendums
Reference Testing TAT


|
RUNTIME-TERROR
|
This class represents the configuration part from the Engine editor that corresponds to the Game wide settings. More...
#include <GlobalConfig.hpp>
Public Member Functions | |
| GlobalConfig (const std::string &global_config_json) | |
| Constructor. More... | |
| const std::string & | GetBackgroundImageRes () const |
| Returns the background image resolution. More... | |
| const std::string & | GetBackgroundMusicRes () const |
| Returns the background music resolution. More... | |
| const std::string & | GetCameraFollowsObject () const |
| Returns the ID of the game object for which the camera component is attached to. More... | |
| const GraphicsColor & | GetBackgroundColor () const |
| Returns the background color of the game. More... | |
| int | GetScreenWidth () const |
| Returns the width of the game screen. More... | |
| int | GetScreenHeight () const |
| Returns the height of the game screen. More... | |
| float | GetGravity () const |
| Returns the gravity value that is applied in the game. More... | |
| std::string | ToString () const |
| Overriding toString. More... | |
This class represents the configuration part from the Engine editor that corresponds to the Game wide settings.
|
explicit |
Constructor.
| global_config_json | Global configuration JSON of the game. |
| const GraphicsColor & GlobalConfig::GetBackgroundColor | ( | ) | const |
Returns the background color of the game.
| const std::string & GlobalConfig::GetBackgroundImageRes | ( | ) | const |
Returns the background image resolution.
| const std::string & GlobalConfig::GetBackgroundMusicRes | ( | ) | const |
Returns the background music resolution.
| const std::string & GlobalConfig::GetCameraFollowsObject | ( | ) | const |
Returns the ID of the game object for which the camera component is attached to.
| float GlobalConfig::GetGravity | ( | ) | const |
Returns the gravity value that is applied in the game.
| int GlobalConfig::GetScreenHeight | ( | ) | const |
Returns the height of the game screen.
| int GlobalConfig::GetScreenWidth | ( | ) | const |
Returns the width of the game screen.
| std::string GlobalConfig::ToString | ( | ) | const |
Overriding toString.


fun calcCurrentUpdate(affectors: MutableSet<WorldObject>): Set<KeyValue>
Takes speed and dAngle now and calculates transformations for each body part


//= partials/header.html
//= partials/mob-application.html
//= partials/advantages.html
//= partials/motivation-app.html
//= partials/system-penalties.html
//= partials/reviews.html
//= partials/no-soap.html
//= partials/you2.html
//= partials/hidden-block.html
//= partials/footer.html
//= partials/scripts.html


{% load cms_tags %}
Your username and password didn't match. Please try again.
Login to edit {{ sitename }}
{{ form.username }} {{ form.password }}


Toggle navigation
BostonBikr
GitHub
LinkedIn
Twitter
About
Start Address:
Finish Address:
Est. Biking Distance [km]:
Submit


Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.
$15 / person
Free WI-FI
Working place
Free printer
5 hours in meeting room
Tea and coffee
$15 / person
Free WI-FI
Working place
Free printer
5 hours in meeting room
Tea and coffee
$15 / person
Free WI-FI
Working place
Free printer
5 hours in meeting room
Tea and coffee


|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
public interface Receiver
A device that can receive packets from some transmission source. A receiver devices is compatible with a specific set of transmission devices and stores the data that it is receiving in an incoming buffer which may be of fixed size.
| Method Summary | |
|---|---|
void |
addPacketReceivedObserver(PacketReceivedObserver pro)
Add a packet receiver observer which will be notified (called) every time a packet is delivered to this receiver device. |
boolean |
canReceiveFrom(Transmitter transmitter)
Test whether this receiver can receive data from (is within the range of) some transmission device |
Packet |
getData()
Remove a packet of data from the buffer of the device and return it |
PhysicsEntity |
getHardware()
Get a reference to the simulated hardware entity that represents the receiver device |
TransmissionType |
getType()
Get the transmission type implemented by the receiver |
boolean |
hasData()
Test whether data is available in the buffer |
boolean |
isCompatible(TransmissionType type)
Test whether this receiver is compatible with (can receive) the type of transmission indicated by the argument. |
void |
receive(Packet data)
Deliver a packet of data to the receiver device which stores it in the buffer |
void |
removePacketReceivedObserver(PacketReceivedObserver pro)
Remove a packet receiver observer that has already been subscribed |
int |
size()
Get the size of the buffer |
| Method Detail |
|---|
boolean isCompatible(TransmissionType type)
type
- the type of the transmission to compare with
void receive(Packet data)
data
- the data to deliverboolean hasData()
Packet getData()
int size()
boolean canReceiveFrom(Transmitter transmitter)
transmitter
- the device to test compatibility with
PhysicsEntity getHardware()
TransmissionType getType()
void addPacketReceivedObserver(PacketReceivedObserver pro)
pro
- the packet receiver observer to addvoid removePacketReceivedObserver(PacketReceivedObserver pro)
pro
- the packet receiver observer to remove
|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


Context Matched Search
Give 1 Query Word
SEARCH
FILE
RELEVANCE VALUE
Enable CORSE ADDONS on Browser, Else it will not work
SEARCH HINT


public class Bus extends MarkedObject
For the license, view the file titled LICENSE at the root of the project
| Modifier and Type | Field and Description |
|---|---|
java.lang.String |
busID
The ID of the bus.
|
int |
color
The current bus's color.
|
java.lang.String |
heading
String used to store the buses current heading.
|
double |
latitude
The latitude and longitude of the bus.
|
double |
longitude
The latitude and longitude of the bus.
|
Route |
route
The bus's corresponding parentRoute.
|
int |
speed
Variables to store the current bus speed in mph.
|
| Constructor and Description |
|---|
Bus(java.lang.String busID,
Route route)
Construction for the bus.
|
| Modifier and Type | Method and Description |
|---|---|
static Bus[] |
addNewBuses(Bus[] oldBuses,
Bus[] newBuses)
Compares two bus arrays and determines which bueses are new.
|
static Bus[] |
getBuses(Route route)
Gets the buses from the provided parentRoute.
|
static void |
removeOldBuses(Bus[] oldBuses,
Bus[] newBuses)
Compares two bus arrays and removes any buses that were in the old bus array that are not in the new bus array.
|
static Bus[] |
updateCurrentBuses(Bus[] oldBuses,
Bus[] newBuses)
Compares two bus arrays and updates the positions, heading,
and speed of the buses whos IDs match.
|
addMarker, getMarker, setMarker
public java.lang.String busID
public double latitude
public double longitude
public int color
This is an int instead of a Color object because for whatever reason android stores its colors as ints.
public Route route
public java.lang.String heading
public int speed
public Bus(java.lang.String busID, Route route)
busID
- The ID belonging to the bus.route
- The bus's parentRoute.public static Bus[] getBuses(Route route) throws org.json.JSONException
route
- The parentRoute to get the buses from.Thrown
- if there is an exception when parsing the JSON corresponding to the bus.org.json.JSONException
public static void removeOldBuses(Bus[] oldBuses, Bus[] newBuses)
oldBuses
- The origional buses.newBuses
- The new buses retrieved from the server.public static Bus[] updateCurrentBuses(Bus[] oldBuses, Bus[] newBuses)
oldBuses
- The origional buses.newBuses
- The new buses retrieved from the server.


I'm not able to play NWN at the moment, but I have been brainstroming ideas for a perfect cleric. I was wondering if any body new that beginning abilities scores for a human(I think that there all 8, but not sure). THanx
Yes, humans start out with 8s across the board. _________________ If everyone is thinking alike, then someone is failing to think.
Ok.. I think I read this wrong didn't I.. he wasn't asking for ability scores for a human cleric was he? DAMNIT.. I need to dye my hair..
hmmm hmmm hmm Str 12 Dex 12 Con 14 Int 14 Wis 16 Cha 8
For a caster cleric then just boost wisdom the entire way?
-DaMouse
Edited By DaMouse404 on 07/02/05 20:12
Nope, your hair can keep its color . DarkStar27909 gave me the answer that I needed.


Property Attributes
You use properties attributes to define the metadata that the Mapper requires. For example, given this very simple model class:
using System;
public class Subscriber
{
public int SubscriberId { get; set; }
public string Name { get; set; }
public DateTime Expiration { get; set; }
}
Adding mapping attributes to this class provides the metadata to automatically map these properties to stored procedures or SQL statements:
using System;
using ArgentSea.Sql;
public class Subscriber
{
[MapToSqlInt("@SubID", true)]
public int SubscriberId { get; set; }
[MapToSqlNVarChar("@SubscriberName", 255)]
public string Name { get; set; }
[MapToSqlDateTime2("@EndDate")]
public DateTime Expiration { get; set; }
}
Note
The “@” parameter prefix is optional — ArgentSea will always add the “@” automatically for parameters and remove it automatically when reading data reader rows.
Often, due to different naming conventions or development drift, database column names and the corresponding .NET properties names do not match. That is why every attribute requires a “name” argument — which should correspond to the database name. The Mapper will create query parameters and reference DataReader columns based on this name.
Important
Database parameters and columns should be named as consistently as possible. In most cases, this means the parameters have the same name as the columns they reference. If you like to use varying parameter names or alias columns in your result, you will find the Mapper unhelpful.
Properties without a mapping attribute are simply ignored.
Attribute Types
A mapping attribute is defined for most common database types. Attributes for spatial data types, CLR types, XML, and JSON types (for example) are missing because there is no straightforward mapping between the core .NET base types and these database types. ArgentSea supports writing a custom handler to render any of these complex types; such work is no more difficult than writing the same processing in ADO.NET.
The attribute itself defines the underlying database type. Naturally, the attribute type and the property type must match. For example, a long
(Int64) property must map to a bigint
database type. The Mapper will throw an error if these types do not match. There is no attempt to cast data to a different type, even if the cast would be successful.
Many data attribute types have an additional parameters. The length argument, for example, on string and array types, helps optimize data access performance by ensuring that buffers are sized appropriately.
Here is catalog of the current attributes, along with their arguments and corresponding .NET types:
| Attribute | Arguments | .NET types | SqlType |
|---|---|---|---|
| MapToSqlNVarCharAttribute | length¹ | String, Enum², Nullable<Enum> | NVarChar |
| MapToSqlNCharAttribute | length | String, Enum², Nullable<Enum> | NChar |
| MapToSqlVarCharAttribute | length¹, localeid³ | String, Enum², Nullable<Enum> | VarChar |
| MapToSqlCharAttribute | length, localeid³ | String, Enum², Nullable<Enum> | Char |
| MapToSqlBigIntAttribute | Int64, Enum⁴, Nullable<Int64>, Nullable<Enum> | BigInt | |
| MapToSqlIntAttribute | Int32, Enum⁴, Nullable<Int32>, Nullable<Enum> | Int | |
| MapToSqlSmallIntAttribute | Int16, Enum⁴, Nullable<Int16>, Nullable<Enum> | SmallInt | |
| MapToSqlTinyIntAttribute | Byte, Enum⁴, Nullable<Byte>, Nullable<Enum> | TinyInt | |
| MapToSqlBitAttribute | Boolean, Nullable<Boolean> | Bit | |
| MapToSqlDecimalAttribute | precision, scale | Decimal, Nullable<Decimal> | Decimal |
| MapToSqlMoneyAttribute | Decimal, Nullable<Decimal> | Money | |
| MapToSqlSmallMoneyAttribute | Decimal, Nullable<Decimal> | SmallMoney | |
| MapToSqlFloatAttribute | Double, Nullable<Double> | Float | |
| MapToSqlRealAttribute | Float, Nullable<Float> | Real | |
| MapToSqlDateTimeAttribute | DateTime, Nullable<DateTime> | DateTime | |
| MapToSqlDateTime2Attribute | precision | DateTime, Nullable<DateTime> | DateTime2 |
| MapToSqlDateAttribute | DateTime, Nullable<DateTime> | Date | |
| MapToSqlTimeAttribute | TimeSpan, Nullable<TimeSpan> | Time | |
| MapToSqlDateTimeOffsetAttribute | DateTimeOffset, Nullable<DateTimeOffset> | DateTimeOffset | |
| MapToSqlVarBinaryAttribute | length¹ | byte[] | VarBinary |
| MapToSqlBinaryAttribute | length | byte[] | Binary |
| MapToSqlUniqueIdentifierAttribute | Guid, Nullable<Guid> | UniqueIdentifier |
¹ For “max” values (nvarchar(max), varbinary(max), etc.) use length of -1.
² The Enum name is saved as string.
³ Locale Id is the Ansi code page to use for Unicode conversion. For en-US locale, for example, use 1033.
⁴ The Enum value is saved based on its underlying numeric value. The Enum integer base type (int, short, byte, etc.) must match the database type.
Required
Finally, the the data attributes have an optional required
(sic) parameter. If a database field is DbNull, the Mapper will normally set the corresponding property to null. However, the missing value may represent an entirely absent record. In this case, the correct result is a null object, not a valid instance with null/default properties. Setting a property attribute’s required
argument to True causes the Mapper to return a null object if the property would be null. By default (if not specified), required
is false.
Handling Nulls and Empty Types
Because the Mapper is handling database values, there is generally a possibility that the database value is DbNull. How this is converted to a .NET type depends upon the type.
Strings and Arrays
A .NET string with a value of null or a null array will be saved as a DbNull. Empty strings will save as a zero-length string.
Integers
Integers cannot be null, so the advent of nullable types is a godsend for mapping to database storage. To save or retrieve an integer (byte, Int16, Int32, or Int64) database value from a column that allows null, you should declare a nullable value type.
Floating Point Numbers
Like integer types, floating point types (Double and Float) can be wrapped in a nullable value. However, ArgentSea also handles NaN as a DbNull. If the floating point value is presented as a nullable type, then ArgentSea will save or retrieve NaN; if floating point type is presented, then NaN will be converted to/from a DbNull.
Guids
Rather like floating point types, Guid.Empty (00000000-0000-0000-0000-000000000000) will be converted to a data DbNull when read from or written to the database. Also like floats, if you need to write an empty Guid value, wrap it in a nullable type.
Enum Types
.NET enum values can be stored as either numbers or strings. Writing to a text column will automatically save the name of the enum; writing to a numeric column saves the number value.
Warning
Enums can inherit from several base types (byte, short, int, etc.). If you are saving to a numeric database column, the base type must correctly correspond to the database data type. Enums are Int32 by default.
Nullable Enum types will read or write as a DbNull when the value is null.
Model Inheritance
Models which inherit from other Model classes also inherit the attributes of the parent class. This can be very useful when some queries return a subset of the data entities overall columns.
Properties with Object Types
This page has described simple 1:1 mapping between database columns and model properties. This is the heart of the Mapper. However, mapping sometimes requires more complex types, built from these simple relationships.
In addition to the types already described, the Mapper supports three additional types of Model properties:
- Properties which contain a second Model class
- Properties which contain lists of Model classes
- Sharded record identifiers
These will be explored in the next section.
Next: Complex Attributes


Back in the actionscript 3 flex days, it has a built in event dispatcher system that works very well. 'fantomeventj' is a threaded engine designed to work the same so to decouple parts of an application while still allowing them to communicate with each other efficiently.
Based on the pros of Guava, Flex, and observer pattern, fantomeventj specializes the event engine for Android applications and games.
fantomeventJ is designed for people who are used to the paradigm in Flex. For any class that you wish to have the event dispatching mechanism, simply extends the EventDispatcher class or create an instance of it as a class component with
EventDispatcher satellite = new EventDispatcher(LooperBinder, this);Because a satellite is standalone for every class instance to have its customizable logics. Since we bind all satellite(s) to the main looper, essentially they all share the same thread queue so it will be quite efficient.
Listening works just like how it was in Actionscript 3. However, I never liked the function passing using
lambda based call backs because it just looks ugly. Using AccessibleObject
concepts, it is possible
to find a method by its name in String form.
To listen for the event published in the previous section we would just need a handler/listener function as following:
public void onExampleEventHandler(ExampleEvent event) { // TODO: make the frog jump! }
The name of the method can be anything you like just make sure you spell correctly.
In order to receive events, a class instance needs to listen to the corresponding satellite. If this
refers to an instance of the class in which the previous method was present, we can register using the
following:
BaseEvent event = new BaseEvent("TestEventCodeName", this); EventListener listener = new EventListener(event, this, "onExampleEventHandler"); satellite.addEventListener(event, handler);
'this'
is provided to both the event and EventListener object as the target
. Use the removeEventListener
method when appropriate to detach and listeners lingering in memory and threads. See the sample application,
available on GitHub, for a complete example. However, the example is still be updated to a simple game scenario which I am still deciding on what game. (Flappy Bird maybe)
Unfortunately this is still not as straight forward as it could be compared to AS3 but I like it better because it is more in style as before, just 1 extra line. I might add a singleton helper function later to EventListener to help create things.
When things are listening on a particular event type (using class type instead of the name), any events dispatched to the given satellite of a target, the event listeners will be triggered accordingly by the main looper.
To dispatch it is fairly easy and coherent as AS3 except for the extra target
that we need to pass in just to make sure that the right events are fired and dispatched from the right satellite and to the right target.:
dispatchEvent(new BaseEvent("TestEventCodeName", this))
All event should extend BaseEvent
and implement IBaseEvent
to make sure events follow the same structure. Data objects can be added in later to allow passing of information through events when it needs to. Consult the sample later to see how it might work.
You may only have the same event with multiple different listeners, but you can only have one event for the same listener on the same target. Repeated adding will just be ignored.
In android, the main looper, custom looper, ui thread, can sometimes be confusing an ambiguous so it is up to the user to really control where the event dispatcher is running on. It should definitely not be running on the UIThread. By default the Looper.MainLooper is used.
// Start with the following EventDispatcher satellite = new Bus(LooperBinder.MAIN, this);
If you are not concerned on which thread interaction is occurring, instantiate a dispatcher instance with
LooperBinder.ANY
. You can also provide your own implementation of the
LooperBinder
interface if you want in depth mechanism of thread management.
The source code to fantomeventj, its sample, and this website is available on GitHub.
dependencies {
compile 'au.com.fantomdigital:fantomeventj:+'
}
<dependency>
<groupId>au.com.fantomdigital</groupId>
<artifactId>fantomeventj</artifactId>
<version>[insert latest version]</version>
</dependency>
Once you've integrated fantomeventj, add the following lines to your proguard-project.txt
file:
-keepattributes *Annotation* -keepclassmembers class ** { @au.com.fantomdigital.fantomeventj.EventDispatcher public *; @au.com.fantomdigital.fantomeventj.EventListener public *; }
This ensures your annotated methods do not get filtered by ProGuard.
If you would like to contribute code you can do so through GitHub by forking the repository and sending a pull request.
When submitting code, please make every effort to follow existing conventions and style in order to keep the code as readable as possible. Please also make sure your code compiles by running mvn clean verify
.
Before your code can be accepted into the project you must also sign the FD Contributor License Agreement (CLA).
Copyright 2015 Fantom Digital Pty. Ltd. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.


Kier housebuilding arm 'targeted by US private equity firm'
by Alex DanielAmerican private equity firm Lone Star is said to be one of the bidders in the race to buy parts of Kier Group, as the embattled contractor looks to raise money.
Kier is looking to sell off “non-core” parts of its business, with its housebuilding division, Kier Living, up for grabs.
Read more: Kier suspends dividend and unveils plan to cut 1,200 jobs
The struggling outsourcer staggered to a £245m loss in its latest full year, with net debt of £167m.
The sell-off comes as part of new chief executive Andrew Davies’s attempt to turn the company around. Since his arrival in March this year, he has announced 1,200 job cuts as part of a wider cost reduction plan.
Lone Star’s interest was first reported by the Sunday Times.
But last week, it was reported Kier’s lenders are trying to offload its debt to hedge funds, in a sign they think the risk of another corporate collapse in the embattled sector is increasing.
HSBC and other lenders are reportedly marketing the debt for as little as 70p in the pound, as they try to cut their losses in case the firm meets the same fate as fellow outsourcer Carillion.
Hedge funds, who specialise in distressed debt, are circling the sale in the hope they can use the debt to take control of the firm.
Kier is one of the country’s biggest builders of roads, schools and railways, and carries out a significant amount of work for the government.
Read more: Kier lenders ‘try to offload outsourcers’ debt’
This includes two contracts worth £1.4bn to design and build major railway tunnels beneath Northamptonshire, which were originally part of a three-way joint venture including Carillion.
However, when Carillion collapsed early last year, Kier and French construction company Eiffage took on 50 per cent of the job each.
(Image credit: Kier)


|
XPMP2
X-Plane multiplayer library 2 - using instancing
|
All global config settings and variables are kept in one structure for convenient access and central definition. More...
#include <XPMP2.h>
Public Member Functions | |
| bool | RemoteIsListener () const |
| Are we a listener? More... | |
| bool | RemoteIsSender () const |
| Are we a sender? More... | |
| XPMPPlaneID | NextPlaneId () |
| Get the next unique artifical plane id. More... | |
| GlobVars (logLevelTy _logLvl=logINFO, bool _logMdlMatch=false) | |
| Constructor. More... | |
| void | ReadConfigFile () |
Read from a generic XPMP2.prf or XPMP2.<logAcronym>.prf config file. More... | |
| void | UpdateCfgVals () |
| Update all settings, e.g. for logging level, by calling prefsFuncInt. More... | |
| void | ReadVersions () |
| Read version numbers into verXplane/verXPLM. More... | |
| bool | UsingModernGraphicsDriver () const |
| Using a modern graphics driver, ie. Vulkan/Metal? More... | |
| void | ThisThreadIsXP () |
| Set current thread as main xp Thread. More... | |
| bool | IsXPThread () const |
| Is this thread XP's main thread? More... | |
| void | UpdateCameraPos () |
| Update the stored camera position and velocity values. More... | |
Public Attributes | |
| logLevelTy | logLvl = logINFO |
| Logging level. More... | |
| bool | bLogMdlMatch = false |
| Debug model matching? More... | |
| bool | bClampAll = false |
Clamp all planes to the ground? Default is false as clamping is kinda expensive due to Y-Testing. More... | |
| bool | bHandleDupId = false |
| Handle duplicate XPMP2::Aircraft::modeS_id by overwriting with unique id. More... | |
| bool | bObjReplDataRefs = false |
Replace dataRefs in .obj files on load? (defaults to OFF!) More... | |
| bool | bObjReplTextures = true |
Replace textures in .obj files on load if needed? More... | |
| std::string | pathObj8DataRefs |
Path to the Obj8DataRefs.txt file. More... | |
| listObj8DataRefsTy | listObj8DataRefs |
List of dataRef replacement in .obj files. More... | |
| std::string | pluginName = UNKNOWN_PLUGIN_NAME |
| Name of the plugin we are serving (used as map layer name or for folders) More... | |
| std::string | logAcronym = UNKNOWN_PLUGIN_NAME |
| Plugin acronym used in log output. More... | |
| int(* | prefsFuncInt )(const char *, const char *, int) = XPMP2::PrefsFuncIntDefault |
| Configuration callback for integer values. More... | |
| listXPMPPlaneNotifierTy | listObservers |
| List of notifier functions registered for being notified of creation/destruction/model change. More... | |
| std::string | pathDoc8643 |
| Path to Doc8643.txt file. More... | |
| mapDoc8643Ty | mapDoc8643 |
Content of Doc8643.txt file. More... | |
| std::string | pathRelated |
| Path to related.txt file. More... | |
| mapRelatedTy | mapRelated |
Content of related.txt file as a map of type codes to group id. More... | |
| mapCSLPackageTy | mapCSLPkgs |
Global map of all CSL Packages, indexed by xsb_aircraft.txt::EXPORT_NAME More... | |
| mapCSLModelTy | mapCSLModels |
| Global map of all CSL Models, indexed by related group, aircraft type, and model id. More... | |
| std::string | defaultICAO = "A320" |
| Default ICAO aircraft type designator if no match can be found. More... | |
| std::string | carIcaoType = "ZZZC" |
| Ground vehicle type identifier (map decides icon based on this) More... | |
| std::string | resourceDir |
| Resource directory, to store local definitions of vertical offsets (clamping) More... | |
| mapAcTy | mapAc |
| Global map of all created planes. More... | |
| bool | bDrawLabels = true |
| Shall we draw aircraft labels? More... | |
| float | maxLabelDist = 5556.0f |
| Maximum distance for drawing labels? [m], defaults to 3nm. More... | |
| bool | bLabelCutOffAtVisibility = true |
| Cut off labels at XP's reported visibility mit? More... | |
| float | labelFontScaling = 1.0f |
| Label font scaling factor. More... | |
| bool | bHasControlOfAIAircraft = false |
| Do we control X-Plane's AI/Multiplayer planes? More... | |
| bool | bMapEnabled = true |
| Do we feed X-Plane's maps with our aircraft positions? More... | |
| bool | bMapLabels = true |
| Do we show labels with the aircraft icons? More... | |
| mapMapLayerIDTy | mapMapLayers |
| Map of map layer ids, i.e. for each map this is the id of the corresponding layer of ours. More... | |
| std::string | pathMapIcons |
| path to file containing plane icons for map display More... | |
| std::string | remoteMCGroup = "<IP_ADDRESS>" |
| The multicast group that we use, which is the same X-Plane is using itself for its BEACON. More... | |
| int | remotePort = 49788 |
| The port we use is different from the port the X-Plane BEACON uses, so we don't get into conflict. More... | |
| int | remoteTTL = 8 |
| Time-to-live, or mumber of hops for a multicast message. More... | |
| size_t | remoteBufSize = 8192 |
| Buffer size, ie. max message length we send over multicast. More... | |
| int | remoteTxfFrequ = 5 |
| Max transfer frequency per second. More... | |
| RemoteCfgTy | remoteCfg = REMOTE_CFG_AUTO |
| Configuration: Are we to support remote connections? More... | |
| RemoteCfgTy | remoteCfgFromIni = REMOTE_CFG_AUTO |
| Configuration file entry: Are we to support remote connections? More... | |
| RemoteStatusTy | remoteStatus = REMOTE_OFF |
| Status of remote connections to networked clients. More... | |
| int | contrailAltMin_ft = 25000 |
| [ft] Auto Contrails: Minimum altitude More... | |
| int | contrailAltMax_ft = 45000 |
| [ft] Auto Contrails: Maximum altitude More... | |
| int | contrailLifeTime = 25 |
| [s] Contrail default time to live More... | |
| bool | contrailMulti = false |
| Auto-create multiple or just a single contrail? More... | |
| bool | bSoundOnStartup = true |
| Config: Start Sound on startup? More... | |
| bool | bSoundMuteOnPause = true |
| Config: Mute on Pause? More... | |
| bool | bSoundAvail = false |
| Is the sound system available? More... | |
| float | sndMasterVol = 1.0f |
| Sound master volume. More... | |
| bool | bSoundAutoMuted = false |
| Is sound currently being auto-muted? More... | |
| int | verXPlane = -1 |
| X-Plane's version number (XPLMGetVersions) More... | |
| int | verXPLM = -1 |
| XPLM's SDK version number (XPLMGetVersions) More... | |
| bool | bXPUsingModernGraphicsDriver = false |
| Using a modern graphics driver, ie. Vulkan/Metal? More... | |
| bool | bXPNetworkedSetup = false |
| Is X-Plane configured for networked multi-computer or multiplayer setup? More... | |
| XPLMPluginID | pluginId = 0 |
| This plugin's id. More... | |
| std::thread::id | xpThread |
| id of X-Plane's thread (when it is OK to use XP API calls) More... | |
| XPLMCameraPosition_t | posCamera = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f } |
| Current camera location, updated every flight loop. More... | |
| XPLMCameraPosition_t | prevCamera = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f } |
| Previous camera location of about a second ago. More... | |
| float | vCam_x = 0.0f |
| Camera velocity. More... | |
| float | vCam_y = 0.0f |
| float | vCam_z = 0.0f |
| float | prevCamera_ts = 0.0f |
When has prevCamera been updated last? More... | |
| int | xpCycleNum = 0 |
| Current XP cycle number (see XPLMGetCycleNumber()) More... | |
Protected Attributes | |
| XPMPPlaneID | planeId = 0 |
| Current plane ID counter. More... | |
All global config settings and variables are kept in one structure for convenient access and central definition.
|
inline |
Constructor.
|
inline |
Is this thread XP's main thread?
| XPMPPlaneID XPMP2::GlobVars::NextPlaneId | ( | ) |
Get the next unique artifical plane id.
| void XPMP2::GlobVars::ReadConfigFile | ( | ) |
Read from a generic XPMP2.prf
or XPMP2.<logAcronym>.prf
config file.
Goal is to provide some few configuration options independend of the plugin using XPMP2. This is useful e.g. when configuring non-standard network settings for remote connections.
For even greate flexibility the function will try a plugin-specific file first, named "XPMP2.<logAcronym>.prf" (with spaces replaced with underscores) and if that is not found it tries the generic file "XPMP2.prf".
A config file is completely optional, none is required.
| void XPMP2::GlobVars::ReadVersions | ( | ) |
Read version numbers into verXplane/verXPLM.
|
inline |
Are we a listener?
|
inline |
Are we a sender?
|
inline |
Set current thread as main xp Thread.
| void XPMP2::GlobVars::UpdateCameraPos | ( | ) |
Update the stored camera position and velocity values.
| void XPMP2::GlobVars::UpdateCfgVals | ( | ) |
Update all settings, e.g. for logging level, by calling prefsFuncInt.
|
inline |
Using a modern graphics driver, ie. Vulkan/Metal?
| bool XPMP2::GlobVars::bClampAll = false |
Clamp all planes to the ground? Default is false
as clamping is kinda expensive due to Y-Testing.
| bool XPMP2::GlobVars::bDrawLabels = true |
Shall we draw aircraft labels?
| bool XPMP2::GlobVars::bHandleDupId = false |
Handle duplicate XPMP2::Aircraft::modeS_id by overwriting with unique id.
| bool XPMP2::GlobVars::bHasControlOfAIAircraft = false |
Do we control X-Plane's AI/Multiplayer planes?
| bool XPMP2::GlobVars::bLabelCutOffAtVisibility = true |
Cut off labels at XP's reported visibility mit?
| bool XPMP2::GlobVars::bLogMdlMatch = false |
Debug model matching?
| bool XPMP2::GlobVars::bMapEnabled = true |
Do we feed X-Plane's maps with our aircraft positions?
| bool XPMP2::GlobVars::bMapLabels = true |
Do we show labels with the aircraft icons?
| bool XPMP2::GlobVars::bObjReplDataRefs = false |
Replace dataRefs in .obj
files on load? (defaults to OFF!)
| bool XPMP2::GlobVars::bObjReplTextures = true |
Replace textures in .obj
files on load if needed?
| bool XPMP2::GlobVars::bSoundAutoMuted = false |
Is sound currently being auto-muted?
| bool XPMP2::GlobVars::bSoundAvail = false |
Is the sound system available?
| bool XPMP2::GlobVars::bSoundMuteOnPause = true |
Config: Mute on Pause?
| bool XPMP2::GlobVars::bSoundOnStartup = true |
Config: Start Sound on startup?
| bool XPMP2::GlobVars::bXPNetworkedSetup = false |
Is X-Plane configured for networked multi-computer or multiplayer setup?
| bool XPMP2::GlobVars::bXPUsingModernGraphicsDriver = false |
Using a modern graphics driver, ie. Vulkan/Metal?
| std::string XPMP2::GlobVars::carIcaoType = "ZZZC" |
Ground vehicle type identifier (map decides icon based on this)
| int XPMP2::GlobVars::contrailAltMax_ft = 45000 |
[ft] Auto Contrails: Maximum altitude
| int XPMP2::GlobVars::contrailAltMin_ft = 25000 |
[ft] Auto Contrails: Minimum altitude
| int XPMP2::GlobVars::contrailLifeTime = 25 |
[s] Contrail default time to live
| bool XPMP2::GlobVars::contrailMulti = false |
Auto-create multiple or just a single contrail?
| std::string XPMP2::GlobVars::defaultICAO = "A320" |
Default ICAO aircraft type designator if no match can be found.
| float XPMP2::GlobVars::labelFontScaling = 1.0f |
Label font scaling factor.
| listObj8DataRefsTy XPMP2::GlobVars::listObj8DataRefs |
List of dataRef replacement in .obj
files.
| listXPMPPlaneNotifierTy XPMP2::GlobVars::listObservers |
List of notifier functions registered for being notified of creation/destruction/model change.
| std::string XPMP2::GlobVars::logAcronym = UNKNOWN_PLUGIN_NAME |
Plugin acronym used in log output.
| logLevelTy XPMP2::GlobVars::logLvl = logINFO |
Logging level.
| mapAcTy XPMP2::GlobVars::mapAc |
Global map of all created planes.
| mapCSLModelTy XPMP2::GlobVars::mapCSLModels |
Global map of all CSL Models, indexed by related group, aircraft type, and model id.
| mapCSLPackageTy XPMP2::GlobVars::mapCSLPkgs |
Global map of all CSL Packages, indexed by xsb_aircraft.txt::EXPORT_NAME
| mapDoc8643Ty XPMP2::GlobVars::mapDoc8643 |
Content of Doc8643.txt
file.
| mapMapLayerIDTy XPMP2::GlobVars::mapMapLayers |
Map of map layer ids, i.e. for each map this is the id of the corresponding layer of ours.
| mapRelatedTy XPMP2::GlobVars::mapRelated |
Content of related.txt
file as a map of type codes to group id.
| float XPMP2::GlobVars::maxLabelDist = 5556.0f |
Maximum distance for drawing labels? [m], defaults to 3nm.
| std::string XPMP2::GlobVars::pathDoc8643 |
Path to Doc8643.txt file.
| std::string XPMP2::GlobVars::pathMapIcons |
path to file containing plane icons for map display
| std::string XPMP2::GlobVars::pathObj8DataRefs |
Path to the Obj8DataRefs.txt
file.
| std::string XPMP2::GlobVars::pathRelated |
Path to related.txt file.
|
protected |
Current plane ID counter.
| XPLMPluginID XPMP2::GlobVars::pluginId = 0 |
This plugin's id.
| std::string XPMP2::GlobVars::pluginName = UNKNOWN_PLUGIN_NAME |
Name of the plugin we are serving (used as map layer name or for folders)
| XPLMCameraPosition_t XPMP2::GlobVars::posCamera = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f } |
Current camera location, updated every flight loop.
| int(* XPMP2::GlobVars::prefsFuncInt) (const char *, const char *, int) = XPMP2::PrefsFuncIntDefault |
Configuration callback for integer values.
| XPLMCameraPosition_t XPMP2::GlobVars::prevCamera = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f } |
Previous camera location of about a second ago.
| float XPMP2::GlobVars::prevCamera_ts = 0.0f |
When has prevCamera
been updated last?
| size_t XPMP2::GlobVars::remoteBufSize = 8192 |
Buffer size, ie. max message length we send over multicast.
| RemoteCfgTy XPMP2::GlobVars::remoteCfg = REMOTE_CFG_AUTO |
Configuration: Are we to support remote connections?
| RemoteCfgTy XPMP2::GlobVars::remoteCfgFromIni = REMOTE_CFG_AUTO |
Configuration file entry: Are we to support remote connections?
| std::string XPMP2::GlobVars::remoteMCGroup = "<IP_ADDRESS>" |
The multicast group that we use, which is the same X-Plane is using itself for its BEACON.
| int XPMP2::GlobVars::remotePort = 49788 |
The port we use is different from the port the X-Plane BEACON uses, so we don't get into conflict.
| RemoteStatusTy XPMP2::GlobVars::remoteStatus = REMOTE_OFF |
Status of remote connections to networked clients.
| int XPMP2::GlobVars::remoteTTL = 8 |
Time-to-live, or mumber of hops for a multicast message.
| int XPMP2::GlobVars::remoteTxfFrequ = 5 |
Max transfer frequency per second.
| std::string XPMP2::GlobVars::resourceDir |
Resource directory, to store local definitions of vertical offsets (clamping)
| float XPMP2::GlobVars::sndMasterVol = 1.0f |
Sound master volume.
| float XPMP2::GlobVars::vCam_x = 0.0f |
Camera velocity.
| float XPMP2::GlobVars::vCam_y = 0.0f |
| float XPMP2::GlobVars::vCam_z = 0.0f |
| int XPMP2::GlobVars::verXPlane = -1 |
X-Plane's version number (XPLMGetVersions)
| int XPMP2::GlobVars::verXPLM = -1 |
XPLM's SDK version number (XPLMGetVersions)
| int XPMP2::GlobVars::xpCycleNum = 0 |
Current XP cycle number (see XPLMGetCycleNumber())
| std::thread::id XPMP2::GlobVars::xpThread |
id of X-Plane's thread (when it is OK to use XP API calls)


Magnetospirillum magneticum
Culture Sources
BioBrick Parts
Vectors
Whole Cell Metabolism SBML Models
Acknowledgements
Data curated by iGEM 2017 team IIT Madras<EMAIL_ADDRESS>Magnetospirillum magneticum
Data curated by iGEM 2017 team IIT Madras: igem@smail.iitm.ac.in


Carepoynt Enterprises
All Our Enterprises
-
{{ent.ent_name}}{{ent.ent_address}}
{{selectedEnt.ent_name}}
{{selectedEnt.ent_name}}
Search For Them on Yelp
-
{{business.name}}{{business.location.address1}}, {{business.location.address2}}
{{business.location.city}} {{business.location.state}} {{business.location.zip_code}}
{{business.coordinates.latitude}}, {{business.coordinates.longitude}}


Facility and Affiliation distribution 2019
Distribution of funding SciLifeLab facilities 2019
Satisfaction score of facilities 2018
Total funding vs publications for SciLifeLab facilities 2019


I'm a senior at the University of Wisconsin-Madison, where I study Geography and Cartography. I'm an explorer by nature, I love to understand the world around me, and I'm fascinated by how the map helps us explore as well as communicate what we find. I'm a big fan of process, finding practicing and refining technique enjoyable whether the pursuit is design, fly-fishing, coaching, coding, or cooking. I always want to push myself to do what I couldn't do before, and be better at the things I have already learned to do.


vignettes/epoch-handling.Rmd
epoch-handling.Rmd
In this example, we’re going to look at how to handle epoching and events. To start, we have continuous data from 70 channels sampled at 512 Hz, average referenced, and bandpass filtered from 0.1 to 40 Hz. There is a complete table of all of the events imported with the data. We can use that table to form epochs.
eeg_example events(eeg_example)
There are 18 unique trigger codes, which we can check with list_events()
.
list_events(eeg_example)
In this experiment, six of those triggers correspond to condition codes.
| Trigger | Semantic type | Spatial frequency |
|---|---|---|
| 207 | Match | High |
| 208 | Match | Low |
| 213 | Mismatch | High |
| 215 | Mismatch | Low |
| 219 | Nonsense | High |
| 222 | Nonsense | Low |
We can use the epoch_data()
function to create epochs around each of these triggers, and label those epochs accordingly. In this example, I’ll label each trigger using hierarchically coded event tags, simultaneously giving each condition of semantic type and spatial frequency separated by a “/” symbol.
example_epochs <- epoch_data(eeg_example, events = c(207, 208, 213, 215, 219, 222), epoch_labels = c("Match/HSF", "Match/LSF", "Mismatch/HSF", "Mismatch/LSF", "Nonsense/HSF", "Nonsense/LSF"), time_lim = c(-.2, .6)) events(example_epochs) epochs(example_epochs)
As can be seen, this modifies the epochs structure so that it now labels each epoch accordingly. Since we have hierarchically encoded event tags, an easy way to split that into multiple columns is using the separate()
function from the tidyr
package.
epochs(example_epochs) <- tidyr::separate(epochs(example_epochs), col = epoch_labels, into = c("Semantics", "SF")) epochs(example_epochs)
Any columns in the epochs
structure are included when converting to a data frame. This has a lot of advantages for plotting; many plotting commands now allow you to use facet_wrap()
and facet_grid()
from ggplot2
to facet on any of the columns from the epoch structure. Note that for performance reasons, facetting must be explicitly allowed using allow_facets = TRUE
, since ggplot2
’s stat_summary()
function can be extremely slow.
library(ggplot2) plot_butterfly(example_epochs, legend = FALSE, baseline = c(-.1, 0), allow_facets = TRUE) + facet_wrap(~SF)


| Home | Trees | Index | Help |
|
|---|
| Package session2 |
|
A refactored Quixote 2.x session manager and associated persistent session stores.
Authors: C. Titus Brown and Mike Orr.
LICENSE: MIT.
See the README.txt distributed with this package for more information, or visit http://quixote.idyll.org/session2/.
| Submodules | |
|---|---|
|
| Variable Summary | |
|---|---|
str |
__version__ = '0.6'
|
| Variable Details |
|---|
__version__
|
| Home | Trees | Index | Help |
|
|---|
| Generated by Epydoc 2.1 on Sat Feb 4 16:40:10 2006 | http://epydoc.sf.net |


From the moment we are born, we start solving problems. Learning how to talk, hold a spoon, walk, button a shirt are a few examples of the first difficulties humans face. As we grow, some carers help us become better at it. In contrast, others like to solve our problems for us, limiting our development in this area. In either case, there comes a season in life when we have to figure things out independently.
For various reasons, different people have different approaches to problem-solving. Still, it's a valuable skill, and we should all practice it. I am a naturally analytical person, so I have a system to deal with challenges. First, I need to understand what the problem is. Second, I explore possible strategies and choose one; only then will I solve the problem. The last and perhaps more important part of the process is to look back and reflect on the solution.
In the past few weeks, I have learned a few new problem-solving techniques that will help me become a better web developer. Among my favourites are pseudocode, try and error, console.logging, googling, and, of course, improving my process with reflection. I know I still have a long way to go, but I feel confident I can tackle any problem with some persistence and a fair amount of optimism.
When we think about it, what fun would life be without challenges? How would we grow, improve, achieve our goals, live life to its fullest if we didn't have problems to teach us? From this perspective, I am thankful for the obstacles in my way and for having these new skills to help me deal with them.


Aurana is available for intuitive readings in person or by phone, from 15 minutes to an hour and a half, twice a week at Mystic Journey Bookstore in Venice, CA.
Please call<PHONE_NUMBER> or visit http://mysticjourneybookstore.com/readers/aurana/ to schedule.
If you would like to schedule a half hour phone reading directly with Aurana for an Intuitive Reading Session, Coaching session, Nutritional Coach Session or Mediation De-Stress Session, please see below for available times to book an appointment.
IMPORTANT: In order to confirm your appointment, all sessions must be paid for via Paypal at the time of booking. Please be sure to leave your phone number when you book your session. You will receive a phone call from an unknown number at the scheduled time of your appointment. Disclaimer: Customers and clients of all events, readings, retreats, products and services offered herein, agree to release said business, Aurana as well as personal properties of liability upon participation.


{% extends "base.html" %} {% block content %}
You may generate an RSA private key with the help of this tool. Additionally, it will display the public key of a generated or pasted private key.
RSA is an asymmetric encryption algorithm. With a given key pair, data that is encrypted with one key can only be decrypted by the other. This is useful for encrypting data between a large number of parties; only one key pair per person need exist. RSA is widely used across the internet with HTTPS.
To generate a key pair, select the bit length of your key pair and click Generate key pair. Depending on length, your browser may take a long time to generate the key pair. A 1024-bit key will usually be ready instantly, while a 4096-bit key may take up to several minutes. For a faster and more secure method, see Do It Yourself below.
CryptoTools.net does not yet have a tool for facilitating the encryption and decryption of data using RSA, but you may Do It Yourself with the instructions below.
For these steps, you will need a command line shell with OpenSSL. Ideally, you should have a private key of your own and a public key from someone else. For demonstration, we will only use a single key pair.
Run this command to generate a 4096-bit private key and output it to the private.pem file. If you like, you may change the key length and/or output file.
$ openssl genrsa
Given a private key, you may derive its public key and output it to public.pem using this command. (You may also paste your OpenSSL-generated private key into the form above to get its public key.)
$ openssl rsa -in private.pem -pubout -out public.pem
We can now use this key pair to encrypt and decrypt a file, data.txt.
$ openssl rsautl -encrypt -inkey public.pem -pubin -in data.txt -out data.txt.enc
Given the encrypted file from the previous step, you may decrypt it like so.
$ openssl rsautl -decrypt -inkey private.pem -in data.txt.enc -out data.txt


Dashboard
Current Directory :
{{data['address']}} ChangeIt has {{data['file_count']}} files and {{data['folder_count']}} folders,
Total items = {{data['total_items']}}
Arranges files only from current folder only
Arranges files from current folder and subfolders.
Visit our Github Page : CleanPy