-
Initial Patient Population =
- AND: FIRST: "Occurrence A of Encounter, Performed: Blood Pressure Visit" <= 6 month(s) starts after start of "Measurement
Period"
- AND: MOST RECENT: "Occurrence A of Physical Exam, Finding: Systolic Blood Pressure (result)" during "Occurrence A of Encounter,
Performed: Blood Pressure Visit"
- AND: "Patient Characteristic Birthdate: birth date" >= 18 year(s) starts before start of "Measurement Period"
- AND: "Patient Characteristic Birthdate: birth date" <= 85 year(s) starts before start of "Measurement Period"
- AND: "Diagnosis, Active: Hypertension" starts before or during "Occurrence A of Encounter, Performed: Blood Pressure Visit"
- AND: "Occurrence A of Physical Exam, Finding: Systolic Blood Pressure (result >= 140 mmHg)"
-
Denominator =
- AND: "Initial Patient Population"
-
Denominator Exclusions =
- AND:
- OR: "Diagnosis, Active: End Stage Renal Disease" starts before or during "Measurement Period"
- OR: "Procedure, Performed: Renal Transplant" starts before or during "Measurement Period"
- OR: "Procedure, Performed: Hemodialysis" starts before or during "Measurement Period"
- OR: "Procedure, Performed: Peritoneal Dialysis" starts before or during "Measurement Period"
- OR:
- AND NOT: "Diagnosis, Active: Pregnancy" ends before start of "Measurement Period"
- AND: "Diagnosis, Active: Pregnancy" starts before or during "Measurement Period"
-
Numerator =
- AND: FIRST: "Occurrence B of Encounter, Performed: Blood Pressure Visit" >= 6 month(s) starts after end of "Occurrence A
of Encounter, Performed: Blood Pressure Visit"
- AND: MOST RECENT: "Occurrence B of Physical Exam, Finding: Systolic Blood Pressure (result)" during "Occurrence B of Encounter,
Performed: Blood Pressure Visit"
- AND: "Occurrence B of Encounter, Performed: Blood Pressure Visit" ends during "Measurement Period"
- AND:
- OR: "Physical Exam, Finding: Delta systolic blood pressure (result >= 10 mmHg)" during "Occurrence B of Encounter, Performed:
Blood Pressure Visit"
- OR: "Occurrence B of Physical Exam, Finding: Systolic Blood Pressure (result < 140 mmHg)"
-
Denominator Exceptions =
-
"Diagnosis, Active: End Stage Renal Disease" using "End Stage Renal Disease Grouping Value Set (2.16.840.1.113883.3.526.3.353)"
-
"Diagnosis, Active: Hypertension" using "Hypertension Grouping Value Set (2.16.840.1.113883.3.464.1<IP_ADDRESS>6)"
-
"Diagnosis, Active: Pregnancy" using "Pregnancy Grouping Value Set (2.16.840.1.113883.3.526.3.378)"
-
"Encounter, Performed: Blood Pressure Visit" using "Blood Pressure Visit Grouping Value Set (2.16.840.1.113883.3.464.1<IP_ADDRESS>6)"
-
"Patient Characteristic Birthdate: birth date" using "birth date LOINC Value Set (2.16.840.1.113883.3.560.100.4)"
-
"Physical Exam, Finding: Delta systolic blood pressure" using "Delta systolic blood pressure Grouping Value Set (2.16.840.1.113883.3.464.1<IP_ADDRESS>3)"
-
"Physical Exam, Finding: Systolic Blood Pressure" using "Systolic Blood Pressure Grouping Value Set (2.16.840.1.113883.3.526.3.1032)"
-
"Procedure, Performed: Hemodialysis" using "Hemodialysis Grouping Value Set (2.16.840.1.113883.3.526.3.1083)"
-
"Procedure, Performed: Peritoneal Dialysis" using "Peritoneal Dialysis Grouping Value Set (2.16.840.1.113883.3.526.3.1084)"
-
"Procedure, Performed: Renal Transplant" using "Renal Transplant Grouping Value Set (2.16.840.1.113883.3.464.1<IP_ADDRESS>2)"
-
"Patient Characteristic Ethnicity: Ethnicity" using "Ethnicity CDC Value Set (2.16.840.1.114<IP_ADDRESS>7)"
-
"Patient Characteristic Payer: Payer" using "Payer Source of Payment Typology Value Set (2.16.840.1.114<IP_ADDRESS>91)"
-
"Patient Characteristic Race: Race" using "Race CDC Value Set (2.16.840.1.114<IP_ADDRESS>6)"
-
"Patient Characteristic Sex: ONC Administrative Sex" using "ONC Administrative Sex Administrative Sex Value Set (2.16.840.1.1137<IP_ADDRESS>)"


Implements a constrained version of hierarchical agglomerative clustering, in which each observation is associated to a position, and only adjacent clusters can be merged. Typical application fields in bioinformatics include Genome-Wide Association Studies or Hi-C data analysis, where the similarity between items is a decreasing function of their genomic distance. Taking advantage of this feature, the implemented algorithm is time and memory efficient. This algorithm is described in Chapter 4 of Alia Dehman (2015) <https://hal.archives-ouvertes.fr/tel-01288568v1>.
| Version: | 0.5.7 |
| Depends: | R (≥ 2.10.0) |
| Imports: | stats, graphics, grDevices, Matrix, matrixStats, methods, utils, capushe |
| Suggests: | knitr, testthat, rmarkdown, rioja, HiTC, snpStats, BiocGenerics |
| Published: | 2018-09-26 |
| Author: | Christophe Ambroise [aut], Shubham Chaturvedi [aut], Alia Dehman [aut], Michel Koskas [aut], Pierre Neuvial [aut, cre], Guillem Rigaill [aut], Nathalie Vialaneix [aut] |
| Maintainer: | Pierre Neuvial <pierre.neuvial at math.univ-toulouse.fr> |
| BugReports: | https://github.com/pneuvial/adjclust/issues |
| License: | GPL-3 |
| URL: | https://github.com/pneuvial/adjclust |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| CRAN checks: | adjclust results |
| Reference manual: | adjclust.pdf |
| Vignettes: |
Clustering of Hi-C contact maps Implementation notes for the adjclust package Inferring Linkage Disequilibrium blocks from genotypes |
| Package source: | adjclust_0.5.7.tar.gz |
| Windows binaries: | r-devel: adjclust_0.5.7.zip, r-release: adjclust_0.5.7.zip, r-oldrel: adjclust_0.5.7.zip |
| OS X binaries: | r-release: adjclust_0.5.7.tgz, r-oldrel: adjclust_0.5.7.tgz |
| Old sources: | adjclust archive |
Please use the canonical form https://CRAN.R-project.org/package=adjclust to link to this page.


Habitat
Commonly found in Kanto and Joto, occasionally found in Sinnoh. They live in savannas and plains or in any open space. Share territory with Nidorans.


Children in Need raises massive £47million for charity on star-studded night
Children In Need managed to raise an amazing amount for charity tonight.
The annual charity spectacular had managed to bring in a magnificent £47,886,382 at the time of writing.
As ever, the money raised from tonight will go towards helping disadvantaged kids up and down the country – a very worthy cause indeed.
Our hosts tonight were Tess Daly and Ade Adepati, Mel Giedroyc and Graham Norton and couple Rochelle and Marvin Humes.
There were some technical difficulties earlier in the night – host Ade apologised live on air after a segment was cut short.
As usual, stars from across the BBC all pitched in to help raise as much money as possible – from the cast of Doctor Who to the business moguls of Dragon’s Den.
There was also the very special moment where Graham Norton had to force co-host Mel to ‘let Bake Off go’ after the comedian couldn’t stop spouting Great British Bake Off-style innuendos.
Advertisement Advertisement
Where’s Mary Berry when you need her?!
Viewers were also treated to a very special edition of Strictly Come Dancing, where the stars of EastEnders were competing for a bespoke Pudsey version of the Glitterball trophy.
Partaking in a group number to the pop classic Dancing In The Street, the four Strictly judges did have to decide who would win.
Maisie Smith – who plays Tiffany Butcher in the soap – managed to walk away with the charity trophy.
Partnered with professional dancer Kevin Clifton, she said after her win: ‘I honestly had the most amazing week and I couldn’t have asked for a more wonderful team by my side.
‘It’s been amazing.’
After her win, fans were calling for the star to compete in the main version of Strictly next year – the campaign to get Maisie on to Strictly 2020 starts here!
Got a showbiz story?
If you've got a story, video or pictures get in touch with the Metro.co.uk Entertainment team by emailing us<EMAIL_ADDRESS>calling 020 3615 2145 or by visiting our Submit Stuff page - we'd love to hear from you.


Usage: docker stack services [OPTIONS] STACK
List the services in the stack
Options:
-f,
--filter filter Filter output based on conditions provided
--format
string Pretty-print services using a Go template
--orchestrator
string Orchestrator to use (swarm|kubernetes|all)
-q,
--quiet Only display IDs


DC Action for Children designed the interactive maps to bring to life our data on the well-being of children and families, neighborhood by neighborhood. The indicators and measures reflect DC KIDS COUNT’s neighborhood-centered analytical frame. Nearly all DC KIDS COUNT indicators and measures are calculated at the neighborhood level, which allows us to evaluate the assets and needs of neighborhoods where DC’s children live, play and learn. We invite you to use them to learn what you want to know about the health, safety and future success of children, families and neighborhoods in DC.
The overall percentage of children in poverty in DC is approximately 30%, which equals about 30,000 children. Poverty is also concentrated in certain neighborhoods: Approximately 25% of the poorest neighborhoods have more than 1 in 2 children in poverty and 60% of all DC children who live in poverty. More than 35% of all DC children in poverty live in four neighborhoods: (1) Congress Heights, Bellevue, Washington Highlands; (2) Douglas, Shipley Terrace;(3) Columbia Heights, Mt. Pleasant, Pleasant Plains, Park View; and (4) Deanwood, Burrville, Grant Park, Lincoln Heights, Fairmont Heights. Many of these high poverty neighborhoods are overwhelmingly (more than 90%) black.
Approximately 48% (almost 1 in 2) DC children live in families headed by single mothers. Approximately 30% of DC neighborhoods have more than 2 in 3 children living in households headed by single mothers and account for more than half of all children living in single mother households. Six Clusters with the highest number and more than 3 in 4 children living in single mother headed households are: Mayfair, Hillbrook, Mahaning Heights (92%), Historic Anacostia (86%), Douglas, Shipley Terrace (83%), Woodland/Fort Stanton, Garfield Heights, Knox Hill (81%), Congress Heights, Bellevue, Washington Highlands (80%), and Sheridan, Barry Farm, Buena Vista (78%).
The 2013 DC CAS results in reading for neighborhoods by student’s residence indicates that 40% of DC neighborhoods have less than half of their students scoring proficient in reading. Half of all DC neighborhoods have less than 53% of their students proficient in reading. The highest performing three neighborhoods, which are clustered in Northwest DC, have 90% or more of their students proficient in reading. Friendship Heights, American University Park, Tenleytown neighborhood in NW DC has 94% of its students scoring proficient in reading while Historic Anacostia neighborhood in SE DC has 35% of its students scoring proficient in reading.
Additionally, a simplistic correlational analysis revealed that on average the higher the child poverty rate in the neighborhood, the lower the percentage of students proficient in reading. The median poverty rate was 52% for the ten neighborhoods with the lowest percentage of students proficient in reading in DC.
The 2013 DC CAS results in math for neighborhoods by student’s residence indicates that in 1 of 3 DC neighborhoods, less than half of the students are proficient in math. Overall, half of all DC neighborhoods have less than 55% of their students proficient in math. The highest performing four neighborhoods, which are clustered in Northwest DC have 90% or more of their students scoring proficient in Math. Friendship Heights, American University Park, Tenleytown neighborhood in NW DC has 94% of its students scoring proficient in math while Historic Anacostia neighborhood in SE DC has 40% of its students scoring proficient in math.
Additionally, a simplistic correlational analysis revealed that on average the higher the child poverty rate in the neighborhood, the lower the percentage of proficient students in math. The median poverty rate was 52% for the ten neighborhoods with the lowest percentage of students proficient in math in DC.
Total population
605,759
| Population (total) | |
| Population (under 18) | |
| Single mother families | |
| Children in poverty |
| Enrollment | getDisplayValue(school.enroll_val, 'enroll_val') |
| TANF/SNAP eligible | getDisplayValue(school.tanfsnap_perc, 'tanfsnap_perc') |
| In-Seat attendance | getDisplayValue(school.isa_perc, 'isa_perc') |
| Percent proficient at math | getDisplayValue(school.math_perc, 'math_perc') |
| Percent proficient at reading | getDisplayValue(school.reading_perc, 'reading_perc') |
| Graduation rate | getDisplayValue(school.grad_perc, 'grad_perc') |


RxJS for jQuery Bindings AutoComplete example
Example to show combining input events such as keyup with Ajax requests
Enter Query for Wikipedia


Bee Purpose
Bee is a general purpose language made for engineering and high performance computing. Bee is an imperative programming language that implement a new, rule based programming paradigm.
Bee Features
Bee is a disruptive strange looking language that will bring Math notation into the source code. Bee has some uncommon keywords, operators and symbols. We have made an effort to maximize these features:
We have made a costly sacrifice, that we call technical debt, to use Unicode symbol that are difficult to input. This is compensated by improved readability but the cost is very high.
Readable
Bee is designed to be learn as first programming language for Sage-Code developers. We think that you can learn Bee by reading code examples in one week. Next design choices will make Bee code easier to read therefore easier to learn:
- Use short and familiar English keywords;
- Use imperative statements based on verb keywords;
- Use end of block keywords not curly brackets;
- Use best operator symbols possible similar to Math;
- Use comprehensive data literals for collections;
- Enable comprehensive comments and code documentation;
- Enable Greek and Cyrillic letters for identifiers;
The result of these choices is demonstrate below. You can observe different comment notations enable different color. Syntax colorizer is able to identify also the keywords and highlight every statement.
# Demo: Fibonacci Sequence
** declare Fibonacci rule
rule fib(n ∈ N) => (y ∈ N):
if (n = 1) ∨ (n = 0) do
let y := 1; -- first value
else
let y := fib(n-1) + fib(n-2);
done;
return;
rule main:
** call fib rule using argument 5
new r := fib(n: 5);
** print the result to console
print r;
return; -- end of module
Efficient
Bee is aiming for efficiency not performance. There is a difference, performance can be obtained using intensive computer resources and distributed computing. Efficiency is achieved using better algorithms and data types. Bee is designed for multi-core CPU. It enable you to create efficient applications using following techniques and features:
- Use native data types;
- Use mutable string types;
- Use fixed precision arithmetic;
- Use fixed size arrays and matrices;
- Enable array slicing;
- Enable lambda expressions;
- Enable tail recursion;
- Enable coroutines;
- Enable concurrency;
Safe
Bee is designed to be a safe but also comprehensive. To fulfill these goals we setup a runway architecture based on next principles and believes. Some of these principles create real challange for our design.
- Safety is more important than performance.
- If something can go wrong, eventually it will,
- If you already know it can be a problem, prevent it,
- It is better to be proactive than reactive,
- Sometimes if you try a second time it may work,
- There are more than one ways to resolve a problem,
- If your problem is large, split it into parts,
- Explicit is better than implicit even if require more work,
- Efficiency is more important than high cost performance,
- Good precision is more important than perfect precision,
Modular
Bee applications are usually small, based on single source file. However Bee enable usage of multiple files for separation of concerns. There are 2 kind of modules in a large application: application modules and library modules.
Bee modular design
- Bee program consist of application modules and library modules
- Main program is called main module and contains rule: main
- Secondary modules can be reused in multiple Bee programs
- Library modules are modules installed in Bee library folders
- External modules can be installed by a package manager in Bee library folders
Note: Main module is the only executable module and is not reusable. Secondary modules can be loaded and public members can be executed from main() rule. Loaded modules are persistent in memory and can not be "unloaded" until the program ends. Bee has this limitation, it has to be small to be loaded in memory.
Explicit
Bee is an explicit language: We believe explicit is better than implicit. For this we try to give as much control to developers as possible. Next design choices make Bee an explicit language:
- Bee require declarations of data types for all elements: constants, variables, parameters and results. Unlike dynamic languages that use implicit data types that can be changed in the same scope.
- Most languages do not have a name for result variables in functions. Bee allow developers to declare explicit names and types for every result. This is helpful when a subroutine has multiple results.
- Precision is implicit and maximum possible in most other languages, forcing the computation of multiple decimals that are not necessary. In Bee you can define rational numbers that have fixed number of decimals therefore precision is explicit.
- Variables and parameters are automatically initialized with zero value when there is no explicit initialization. Also, if a parameter has explicit initial value it becomes optional.
- Bee has three assignment operators: ":", "::" and ":=". First is called "pair up". Second is called "clone", thread is called "assign". Developers can control what assignment operator actually do by using keywords: "make" to declare a new variable and "alter" to modify an existing variable.
- In a rule, primitive type parameters are transferred by value while composite type parameters and objects are transferred by reference. Same rule apply for result variables.
- Bee do not have pointers nor pointer arithmetic. However you can define references to primitive types using explicit boxing operator [x] that are as good as pointers.
We have try and failed to create a consistend language because the people who invented Unicode symbols have done such a mess. Some symbols are duplicated, some are not ordered, some are missing. Sometimes the unicode symbol look like a Latin letter. We have done our best to select the most useful symbols.
- Bee use Unicode operators: { ÷ × ¬ ∧ ∨ ∈ ≤ ≥ ≡ ≠ ≈ ± ⊂ ⊃ ∪ ∩ ↑ ↓ » « ⊕ ⊖ ∀ ∃}. We have alternative ASCII 2 symbols for some of these but not all. This is why Bee looks inconsistent & disruptive:
- Bee use one single letter for primitive types: {A B C D T L U N Q R S X Z}, we have not used Unicode symbols: { ℂ ℍ ℕ ℙ ℚ ℝ ℤ } despite aparent inconsistency.
- Bee support some Greek letters and symbols. These can be used as identifiers or operators: { Σ Π Δ Γ Λ Φ Ψ Ω, λ φ π α β ε δ μ ω }
- Bee support Cyrilic letters: {Б Г Д Ж И Л Ф Ц Ч Ш Э Я}. We do not support all Cyrikic alphabet for identifiers but you can use them in strings.
- Bee support superscript numbers:
{⁺⁻⁰¹²³⁴⁵⁶⁷⁸⁹}
. We recognize superscript as power: x^² and x^ⁿ. You can also use any Latin superscript characters: (ᵃ..ᶻ).
- Subscript indices can be used to create identifiers starting with a letter and use a suffix: (x₁, x₂, α₁, β₂) are some valid identifiers in Bee.
- Bee use Unicode symbols for geometric types. These symbols are intuitive and make geometric types shorter. For example: ∠ = Angle, ⊡ = Dot, ◷ = Arc. Many other shapes are recognized.
- Bee define the "if" statement differently than most other languages. The "if" keyword is used as a conditional for other statements or in lambda expressions.
- Bee use sigils: "$" for system variables. These are globals and we import all environment variables and configuration variables into the execution. Protecting these variables with a sigil is preventing overriding by mistake.
- Bee use starting and ending keywords to define blocks of code, not curly brackets. This eliminate the nested bracket nightmares and improve visual aspect of the code. We can use brackets for data literals: ordinals, sets, hash tables and objects.
Read next:
Bee Syntax


Student debt in the U.S. in \(2022\text{,}\) when President Biden proposed his student loan debt forgiveness plan, was roughly equal to the size of the economy of Brazil [9.11.157]. Additionally, the amount of funding for higher education provided by state governments has declined from around \(70\%\) in the \(1970\)s to slightly under \(60\%\) in \(2019\) \cite{koezeTollStudentDebt2022"/>.
in-context


{include file="frame/include/meta"/} {include file="frame/include/seo"/} {include file="frame/include/compatibility"/} {block name="css"} {/block}


|
M480 BSP V3.05.005
The Board Support Package for M480 Series
|
Macros | |
| #define | HSOTG_ENABLE() |
| This macro is used to enable HSOTG function. More... | |
| #define | HSOTG_DISABLE() |
| This macro is used to disable HSOTG function. More... | |
| #define | HSOTG_ENABLE_PHY() |
| This macro is used to enable USB PHY. More... | |
| #define | HSOTG_DISABLE_PHY() |
| This macro is used to disable USB PHY. More... | |
| #define | HSOTG_ENABLE_ID_DETECT() |
| This macro is used to enable ID detection function. More... | |
| #define | HSOTG_DISABLE_ID_DETECT() |
| This macro is used to disable ID detection function. More... | |
| #define | HSOTG_ENABLE_WAKEUP() |
| This macro is used to enable HSOTG wake-up function. More... | |
| #define | HSOTG_DISABLE_WAKEUP() |
| This macro is used to disable HSOTG wake-up function. More... | |
| #define | HSOTG_SET_VBUS_EN_POL(u32Pol) |
| This macro is used to set the polarity of USB_VBUS_EN pin. More... | |
| #define | HSOTG_SET_VBUS_STS_POL(u32Pol) |
| This macro is used to set the polarity of USB_VBUS_ST pin. More... | |
| #define | HSOTG_ENABLE_INT(u32Mask) |
| This macro is used to enable HSOTG related interrupts. More... | |
| #define | HSOTG_DISABLE_INT(u32Mask) |
| This macro is used to disable HSOTG related interrupts. More... | |
| #define | HSOTG_GET_INT_FLAG(u32Mask) |
| This macro is used to get HSOTG related interrupt flags. More... | |
| #define | HSOTG_CLR_INT_FLAG(u32Mask) |
| This macro is used to clear HSOTG related interrupt flags. More... | |
| #define | HSOTG_GET_STATUS(u32Mask) |
| This macro is used to get HSOTG related status. More... | |
| #define HSOTG_CLR_INT_FLAG | ( | u32Mask | ) |
This macro is used to clear HSOTG related interrupt flags.
| [in] | u32Mask | The combination of interrupt source. Each bit corresponds to a interrupt source. Valid values are listed below.
|
This macro will clear HSOTG related interrupt flags specified by u32Mask parameter.
| #define HSOTG_DISABLE | ( | ) |
| #define HSOTG_DISABLE_ID_DETECT | ( | ) |
| #define HSOTG_DISABLE_INT | ( | u32Mask | ) |
This macro is used to disable HSOTG related interrupts.
| [in] | u32Mask | The combination of interrupt source. Each bit corresponds to a interrupt source. Valid values are listed below.
|
This macro will disable HSOTG related interrupts specified by u32Mask parameter.
| #define HSOTG_DISABLE_PHY | ( | ) |
| #define HSOTG_DISABLE_WAKEUP | ( | ) |
| #define HSOTG_ENABLE | ( | ) |
| #define HSOTG_ENABLE_ID_DETECT | ( | ) |
| #define HSOTG_ENABLE_INT | ( | u32Mask | ) |
This macro is used to enable HSOTG related interrupts.
| [in] | u32Mask | The combination of interrupt source. Each bit corresponds to a interrupt source. Valid values are listed below.
|
This macro will enable HSOTG related interrupts specified by u32Mask parameter.
| #define HSOTG_ENABLE_PHY | ( | ) |
| #define HSOTG_ENABLE_WAKEUP | ( | ) |
| #define HSOTG_GET_INT_FLAG | ( | u32Mask | ) |
This macro is used to get HSOTG related interrupt flags.
| [in] | u32Mask | The combination of interrupt source. Each bit corresponds to a interrupt source. Valid values are listed below.
|
This macro will return HSOTG related interrupt flags specified by u32Mask parameter.
| #define HSOTG_GET_STATUS | ( | u32Mask | ) |
This macro is used to get HSOTG related status.
| [in] | u32Mask | The combination of user specified source. Valid values are listed below. |
This macro will return HSOTG related status specified by u32Mask parameter.
| #define HSOTG_SET_VBUS_EN_POL | ( | u32Pol | ) |
This macro is used to set the polarity of USB_VBUS_EN pin.
| [in] | u32Pol | The polarity selection. Valid values are listed below. |
This macro is used to set the polarity of external USB VBUS power switch enable signal.
| #define HSOTG_SET_VBUS_STS_POL | ( | u32Pol | ) |
This macro is used to set the polarity of USB_VBUS_ST pin.
| [in] | u32Pol | The polarity selection. Valid values are listed below. |
This macro is used to set the polarity of external USB VBUS power switch status signal.


After you go through our guide on creating resumes and cover letters you will be able to apply for jobs and sooner than later you will start getting invitations to interviews! This is awesome and it feels great to land your first interview, especially with a company you really respect, but as great as landing an interview is it feels even better to actually get the job! How? You practice as much as you can, preferably for at least a month before you start getting interviewed. If you are applying for a technical position at a well known company, you will likely go through an interview in which they will ask you technical questions. Depending on both the company and the position the questions range in difficulty and content, but regardless of the specific questions it will be incredibly helpful if you practice. How exactly do you practice? Easy - I have laid it all out for you! Firstly, make sure you understand the Problem Solving Design Pattern so that you can apply it when you are solving difficult questions. Next, quickly read my practice tips to make sure that you get the most out of your time. Lastly, check out the resources listed and start practicing with whatever resources interest you most! Best of luck!
When asked to solve a question in an interview, a common mistake, a mistake I made myself for quite a long time, is to jump into solving the question immediately. Surprisingly, this is not the best approach! There are important steps that if followed correctly can give you a large advantage. To make it as easy as possible, I have clearly stated each step below.
You want to make sure that you clearly understand the problem statement. Having the perfect solution to the wrong problem isn't going to impress the interviewer. As well, questions in interviews are sometimes asked with details missing purposefully; they do this to see if you can identify and resolve the ambiguities. So ask questions and make sure you completely understand the problem!
If possible, write out the signatures of the methods you will be implementing, this often helps when you get confused half-way through a solution. If you are asked to implement a class of some sort it may also be helpful to write a tiny API for that class (essentially a bunch of method signatures). The point of this stage is to build a skeleton for your solution.
Think about possible inputs into your method and the results. Remember to look at your signatures when coming up with inputs/outputs to make sure you are using the correct types. When thinking of inputs, try and cover all the normal cases and edge cases. You'll be thankful when you are trying to solve the problem because it is very helpful to have tests with expected outputs (especially when getting lost in a solution).
Finally, you get to actually solve the problem. At this point you should clearly understand the problem, have the signature for the method you are about to implement, and understand the various edge cases and their expected results. When actually solving the problem, there is no need for code. You should be using pseudo-code and diagrams to make sure you have a good solution. Is your solution fast enough? Does it take too much space? These are good questions to ask yourself while you are solving the problem. If you come up with a "slow" solution but you cannot come up with a "fast" solution, do not panic - move on to the next stage and code your slow solution while talking to the interviewer about the potential weaknesses in the algorithm and the places it could improve.
Yay you actually get to write some code! At this point you have your solution in pseudo-code so implement your solution. If you forgot the names of standard methods it is not a big deal, do not get caught up in whether it is "string".size( ) or "string".length( ), instead focus on fully implementing your solution. If you forget the name of a standard method simply use a logical name in its place (length or size are fine, your interviewer isn't going to mind that you haven't memorized the standard library).
You thought you were done! Not quite!  It is much better to have a bug in your code and find it yourself than to have your interviewer find it for you. If you find any bugs simply point them out and try to fix them.
There are just a few important tips I wanted to leave with you before you start practicing for your interviews.
The author, Gayle Laakmann McDowell, is an incredibly talented programmer who has devoted a lot of her time towards understanding technical interviews. She has worked at many top companies such as Microsoft, Apple, and Google; at Google she was one of the lead interviewers. Her book, "Cracking the Coding Interview", is perhaps the most well known book when it comes to practicing for technical interviews, and it's well known for a reason - it's a great book. Getting this book and working through the problems in any language is an excellent way to practice! It has about 200 problems so it will keep you busy for a long time!
A small manageable set of problems that are designed to efficiently help you prepare for technical interviews. By the time you are done the ~45 problems, you are meant to be prepared for a wide range of technical interview questions. What's nice about this website is that there are multiple hints for each question that guide you towards the correct answer, as well as clear detailed solutions to help you understand each step.
An amazing way to practice for interviews and build up your critical thinking skills. It is an archive of Computer Science / Math problems of varying difficulty. Many of the questions in this archive are far more difficult than the questions you will encounter in an interview so they can be an amazing way to practice. I do not recommend only practicing with Project Euler because it is important to practice easier interview-level questions, but I definitely think this is a great resource to strengthen the general skills you need for technical interviews!
This is a repository that I started when I was applying for Google to keep track of all my preparation. Slowly the repository expanded, and then I decided instead of just keeping track of my preparation I would put in the extra effort and turn it into a guide. First it goes over the implementation of numerous data structures and sorts followed by a series of interview problems. All of the data structures, sorts, and problems are implemented in Java in my "answer key". I highly recommend to check out this repository and follow the guide in the repository, it'll tell you exactly what you need to do!


| readImmediateConditions {future} | R Documentation |
Read All 'immediateCondition' RDS Files
readImmediateConditions( path = immediateConditionsPath(), pattern = "[.]rds$", include = getOption("future.relay.immediate", "immediateCondition"), signal = FALSE, remove = TRUE )
path |
(character string) The folder where the RDS files are. |
pattern |
(character string) A regular expression selecting the RDS files to be read. |
include |
(character vector) The class or classes of the objects to be kept. |
signal |
(logical) If TRUE, the condition read are signaled. |
remove |
(logical) If TRUE, the RDS files used are removed on exit. |
Returns a base::list of immediateCondition objects.


About us 0 0 Comments — by Branchis — a month ago Marta Broto Marta Broto holds a MSc degree in Organic Chemistry from the University of


Remember Me
Get Me Pizza


#include <ck_task.h>
Public Types | |
| enum | TaskOrder { ORDER_MINUS_8_FOR_SYSTEM, ORDER_MINUS_7, ORDER_MINUS_6, ORDER_MINUS_5, ORDER_MINUS_4, ORDER_MINUS_3, ORDER_MINUS_2, ORDER_MINUS_1, ORDER_ZERO, ORDER_PLUS_1, ORDER_PLUS_2, ORDER_PLUS_3, ORDER_PLUS_4, ORDER_PLUS_5, ORDER_PLUS_6, ORDER_PLUS_7, ORDER_PLUS_8_FOR_SYSTEM } |
| The types of the task orders. | |
Public Member Functions | |
| bool | hasOrder () const |
| Returns whether this task has the order. | |
| TaskOrder | getOrder () const |
| Retuens the order of this task. | |
| bool | hasParent () const |
| Returns whether this task has the order. | |
| ckTask * | getParentN () const |
| Returns the parent of this task. | |
| ckTask * | getPrevAllN () const |
| Returns the previous task. | |
| ckTask * | getNextAllN () const |
| Returns the next task. | |
| ckTask * | getPrevSiblingN () const |
| Returns the previous sibling of this task. | |
| ckTask * | getNextSiblingN () const |
| Returns the next sibling of this task. | |
| ckTask * | getLastDescendant () const |
| Returns the last descendant of this task. | |
| bool | hasChild () const |
| Returns whether this task has a child. | |
| ckTask * | getFirstChildN () const |
| Returns the first child of this task. | |
| ckTask * | getLastChildN () const |
| Returns the last child of this task. | |
| const char * | getName () const |
| Returns the name of this task. | |
| u64 | getExecuteUsecTime () const |
| Returns the process time of this task in usec. | |
| bool | isActive () const |
| Returns whether this task is active. | |
| void | setActive (bool is_active) |
| Determines whether this task is active. | |
| virtual void | onUpdate () |
| Updates the frame of this task. | |
| virtual void | onMessage (ckID msg_id, ckMsg< 4 > &msg) |
| Receives a message. | |
Friends | |
| class | ckTaskMgr |
| bool ckTask::hasOrder | ( | ) | const |
Returns whether this task has the order.
| TaskOrder ckTask::getOrder | ( | ) | const |
Retuens the order of this task.
| bool ckTask::hasParent | ( | ) | const |
Returns whether this task has the order.
| ckTask* ckTask::getParentN | ( | ) | const |
Returns the parent of this task.
If the parent doesn't exist, returns NULL.
| ckTask* ckTask::getPrevAllN | ( | ) | const |
Returns the previous task.
If the previous task doesn't exist, returns NULL.
| ckTask* ckTask::getNextAllN | ( | ) | const |
Returns the next task.
If the next task doesn't exist, returns NULL.
| ckTask* ckTask::getPrevSiblingN | ( | ) | const |
Returns the previous sibling of this task.
If this task has no previous sibling, returns NULL.
| ckTask* ckTask::getNextSiblingN | ( | ) | const |
Returns the next sibling of this task.
If this task has no previous sibling, returns NULL.
| ckTask* ckTask::getLastDescendant | ( | ) | const |
Returns the last descendant of this task.
If this task has no descendant, returns this task.
| bool ckTask::hasChild | ( | ) | const |
Returns whether this task has a child.
| ckTask* ckTask::getFirstChildN | ( | ) | const |
Returns the first child of this task.
If the first child doesn't exist, returns NULL.
| ckTask* ckTask::getLastChildN | ( | ) | const |
Returns the last child of this task.
If the last child doesn't exist, returns NULL.
| const char* ckTask::getName | ( | ) | const |
Returns the name of this task.
| u64 ckTask::getExecuteUsecTime | ( | ) | const |
Returns the process time of this task in usec.
| bool ckTask::isActive | ( | ) | const |
Returns whether this task is active.
| void ckTask::setActive | ( | bool | is_active | ) |
Determines whether this task is active.
| [in] | is_active | whetehr this task is active. |
Receives a message.
| [in] | msg_id | The ID of a message. |
| [in] | msg | A message. |


- Name:
- Court Services
- Address:
- Court Services, 201 W Elm St, Graham, NC 27253
- Directions:
- Voter Services:
- Boe Early Voting Site
- Start Date:
- 2012/10/18
- End Date:
- 2012/11/03
- Days Times Open:
- Thursday, October 18 - Friday, October 19 8:00 a.m. - 5:00 p.m.Monday, October 22 - Friday, October 26 8:00 a.m. - 5:00 p.m.Saturday, October 27 9:00 a.m. - 3:00 p.m.Monday, October 29 - Friday, November 2 8:00 a.m. - 5:00 p.m.Saturday, November 3 9:00 a.m. - 1:00 p.m.


{% extends 'base.html' %} {% block title %} OptimalFlow Logs Viewer{% endblock %} {% block body %}
Quickly Check the Logs of OptimalFlow, which is Supported by autoFlow Module.


List of accessibility keywords
Use this list for data-mining. Contribute to this list via the a11y-data-keywords project on GitHub.
- 508
- access technology
- access tech
- accessibility
- ada
- acb
- afb
- anxiety
- anxious
- aoda
- asl
- assistance
- assistive
- assisted technology
- assistive technology
- blind
- braille
- brain
- brain injury
- computer skills
- daisy
- deaf
- depression
- dictation
- difficulties
- disabilities
- disability
- disabled
- disabled veteran
- discriminate
- discrimination
- dragon
- dyslexia
- dyslexic
- enlarged
- family circumstances
- font
- handicap
- handicapped
- hard of hearing
- headings
- health
- health issues
- hearing loss
- help
- hospital
- illness
- illustrations
- impair
- impaired
- impairment
- jaws
- large font
- large print
- legally blind
- legally deaf
- limited vision
- low vision
- magic
- mobile accessibility
- mute
- nfb
- nonvisual desktop access
- nvda
- print
- print impairment
- rehab
- rehabilitation
- screen access
- screen magnification
- screen magnifier
- screen reader
- serotek
- sighted
- system access
- talkback
- tbi
- total blind
- total blindness
- totally blind
- transcripts
- traumatic
- traumatic brain injury
- treatment
- veteran
- veterans
- voice
- voiceover
- vpat
- vrs
- wcag
- window-eyes
- zoom
- zoomtext


Class RelationshipController
Inheritance
System.Object
RelationshipController
Inherited Members
System.Object.Equals(System.Object)
System.Object.Equals(System.Object, System.Object)
System.Object.GetHashCode()
System.Object.GetType()
System.Object.MemberwiseClone()
System.Object.ReferenceEquals(System.Object, System.Object)
System.Object.ToString()
Assembly: PlayGen.SUGAR.Server.EntityFramework.dll
Syntax
public class RelationshipController : DbController
Constructors
RelationshipController(SUGARContextFactory)
Declaration
public RelationshipController(SUGARContextFactory contextFactory)
Parameters
Methods
CreateRelationship(ActorRelationship, SUGARContext)
Immediately creates a new relationship between 2 actors
Declaration
public void CreateRelationship(ActorRelationship newRelation, SUGARContext context = null)
Parameters
| Type |
Name |
Description |
| ActorRelationship |
newRelation |
Relationship to create
|
| SUGARContext |
context |
Optional DbContext to perform opperations on. If ommitted a DbContext will be created.
|
CreateRelationshipRequest(ActorRelationship, SUGARContext)
Create a new relationship request between 2 actors
Declaration
public void CreateRelationshipRequest(ActorRelationship newRelation, SUGARContext context = null)
Parameters
Delete(ActorRelationship)
Declaration
public void Delete(ActorRelationship newRelation)
Parameters
Declaration
public List<Actor> GetRelatedActors(int id, ActorType relationshipActorType)
Parameters
| Type |
Name |
Description |
| System.Int32 |
id |
|
| ActorType |
relationshipActorType |
|
Returns
| Type |
Description |
| System.Collections.Generic.List<Actor> |
|
GetRelationAcceptorActors(Int32, ActorType)
Declaration
public List<Actor> GetRelationAcceptorActors(int id, ActorType toActorType)
Parameters
| Type |
Name |
Description |
| System.Int32 |
id |
|
| ActorType |
toActorType |
|
Returns
| Type |
Description |
| System.Collections.Generic.List<Actor> |
|
GetRelationRequestorActors(Int32, ActorType)
Declaration
public List<Actor> GetRelationRequestorActors(int id, ActorType fromActorType)
Parameters
| Type |
Name |
Description |
| System.Int32 |
id |
|
| ActorType |
fromActorType |
|
Returns
| Type |
Description |
| System.Collections.Generic.List<Actor> |
|
GetRelationship(Int32, Int32)
Declaration
public ActorRelationship GetRelationship(int relatedActorA, int relatedActorB)
Parameters
| Type |
Name |
Description |
| System.Int32 |
relatedActorA |
|
| System.Int32 |
relatedActorB |
|
Returns
GetRelationshipCount(Int32, ActorType)
Declaration
public int GetRelationshipCount(int id, ActorType relationshipActorType)
Parameters
| Type |
Name |
Description |
| System.Int32 |
id |
|
| ActorType |
relationshipActorType |
|
Returns
| Type |
Description |
| System.Int32 |
|
GetRelationships(Int32, ActorType)
Declaration
public List<ActorRelationship> GetRelationships(int actorId, ActorType relationshipActorType)
Parameters
| Type |
Name |
Description |
| System.Int32 |
actorId |
|
| ActorType |
relationshipActorType |
|
Returns
UpdateRequest(ActorRelationship, Boolean)
Declaration
public void UpdateRequest(ActorRelationship newRelation, bool accepted)
Parameters


Draft simulators are widely used training tools in the Magic: the Gathering community. Many other draft simulators have somewhat limited features, so I designed and built a draft simulator with smart computer opponents, pick suggestions, and automatic deckbuilding. This simulator, draftsim, was quickly adopted by the community and is currently the leading free tool for draft preparation.
The draftsim model is designed to mimic the behavior of professional players and aims to maximize the quality of cards within a two color pair. Recommended picks are shown in a table on the site and there are computer draft opponents who always make the most recommended pick. Decks are automatically constructed by identifying the two colors with the best cards and playing the highest rated cards in those colors.
The valuation of cards is a sum of two components, a base rating, intrinsic to the card, and a color bonus, which provides an incentive to draft cards from a two color pair. The base ratings for each set can largely be derived from pick order lists, although some fine tuning can be done based on trends in professional draft viewers, community articles, or experience on the simulator. Generally speaking consistent cards like creatures and removal spells should be rated slightly higher and situational cards like combat tricks should be rated slightly lower than the professional pick order list to ensure the construction of functional decks. A complete list of draftsim card ratings can be found here.
The drafting process is broken down into two stages - the speculation stage and the committed stage.
During the speculation stage, the model searches for two open colors to play. When a player picks a card, that player's commitment to the card's colors is increased by (rating - baseline), where baseline=2.0. Thus, a replacement level card with rating=2.0 won't draw the model into new colors, but a bomb rare with rating=5.0 will.
As a player's commitment to a color grows from 0 to threshold=3.5, the color bonus for cards of that color grows linearly from 0 to max bonus=+0.9 before capping off. At that point, the player is considered committed to that color. To help find a second color, the bonus of the color with second highest commitment is increased to 0.8 * max bonus. When the player is either committed to two or more colors or the draft has progressed the fourth pick of the second pack, the model enters the committed stage.
During the committed stage, the model priotizes cards in the two color pair that the player is most committed to. These cards are given a large on color bonus=+2.0. Off color cards are assigned an off color penalty of -1 for each off color mana symbol beyond the first.
The above description holds for single-colored cards. Colorless cards are given a bonus equal to the largest bonus available to single-colored cards.
Multicolored cards are handled differently. During the committed stage, multicolored cards with 2-3 colors are either given an on color bonus=+2.0 or the off color penalty described above. During the speculation stage, these multicolored cards are assigned a bonus equal to the sum of color bonuses in the card's colors, minus the sum of color bonuses outside of the card's colors, and minus a multicolored penalty=-0.6. Multi-colored cards with 4-5 colors will not be played by the model and are assigned no bonuses or penalities.
The draftsim model is then used to automatically construct decks for the user and the computer opponents. First, the strongest color pair is identified as the two colors with the highest color commit. The highest rated on-color cards are added to the deck until there are 23 nonland cards. A total of 17 lands are then added to the deck, split as evenly as possible and favoring the color with greater color commit in the case of a uneven split.
Work is currently underway to consider the effect of additional factors such as curve and synergy. To train these parameters, drafting data will be collected from users on the site and from user uploaded drafts played on the official Magic Online client. This data can be used to train more sophisticated drafting models, allow users to play against a variety of opponents, and provide insights into the drafting stratgies employed by a wide range of users.


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{% extends 'layout.html' %} {% block pageTitle %} Home - Make NHS services inclusive {% endblock %} {% block beforeContent %} {% endblock %} {% block outerContent %} {% endblock %} {% block content %}
These drafts are a collaborative effort by teams across NHS Digital. We're starting with a private alpha so we can iterate things quickly and often.
Short summary of the case study so people get a sense before opening it.
Short summary of the case study so people get a sense before opening it.


Basic RNN have the following structure, where: * \(x_t\) input at time \(t\) * \(h_t\) hidden state at time \(t\) * \(\phi\) activation function, usually \(\tanh\)
\(h_t\) is usually propagated to upper layers as output.
Usually beginning hidden state is initialized with zeros, that is \(h_0 = \mathbf{0}\)
Equations for vanilla RNN are as follows:
\[ \begin{align} h_t &=\phi(Wh_{t_1} + Ux_t + b) \\ \end{align} \]
The problem is simply vanishing/exploding gradients since with back propagation through time (BPTT) and information morphing (We apply non-linear transformation to hidden state each time step and the network cannot rely on same information representation in later time step). Exploding/Vanishing gradients are due to constant multiplication with matrix \(W\) and is further explained here
Therefore, let's go furher to basic LSTM(Long short term memory) cell (I'm going to skip prototype LSTM cell which isn't working satisfactory due to unbounded state and other issues. See here)
Basic LSTM cell as implemented in tf is in class tf.nn.rnn_cell.BasicLSTMCell. The internal architecture is as follows:
\[ \begin{align} i_t &= \sigma(W_ih_{t-1} + U_i x_{t-1} + b_i) \\ o_t &= \sigma(W_oh_{t-1} + U_o x_{t-1} + b_o) \\ f_t &= \sigma(W_fh_{t-1} + U_f x_{t-1} + b_f) \\ \\ \tilde{c_t} &= \phi(W_ch_{t-1} + U_cx_t + b_c) \\ c_t &= f_t \odot c_t + i_t \odot \tilde{c_t} \\ \\ h_t &= o_t \odot \phi(c_t)\\ \end{align} \]
Other altrenative is GRU (Gated Recurrent Unit) which has similar architecture as LSTM, though input and forget gates are merged, that is linked together. As inplemented in GRUCell:
\[ \begin{align} r_t &= \sigma(W_rh_{t-1} + U_r x_{t-1} + b_r) \\ z_t &= \sigma(W_zh_{t-1} + U_z x_{t-1} + b_z) \\ \tilde{h_t} &= \phi(W_h (h_{t-1} \odot r_t) + U_h x_t + b_h)\\ h_t &= z_t \odot h_{t-1} + (1 - z_t) \odot \tilde{h_t} \end{align} \]
For merging single RNN cell into multilayer RNN use MultiRNNCell.
For dropout (on input and output, never on the state itself!) use DropoutWrapper
For constructing RNN from cells (either MultiRNNCell, or any other combination) use tf.nn.dynamic_rnn. It constructs computation graph dynamically at runtime and it's faster than tf.nn.rnn. I want to bring extra attention on parameter sequence_length:
The parameter sequence_length is optional and is used to copy-through state and zero-out outputs when past a batch element's sequence length. So it's more for correctness than performance, unlike in rnn().
As far as I figured out, we supply already max_time truncated samples into and it performs training starting from same inital state...I'm not really sure how to go when we have long sequence which we need to use BPTT...I mean they are ....todo
state_saving_rnn... looks useful but I cannot really understand what's going on under the hood. After some googling I found this as example usage.. skip for now.
There's few more useful looking functions, have a look here
In seq2seq there's useful looking stuff, sequence_loss_by_example and potentially useful function.
#!/usr/bin/evn python3
import tensorflow as tf
import numpy as np
num_steps = 32
batch_size = 32
num_units = 100
num_layers = 3
X = tf.placeholder(tf.float32, [None, num_steps])
Y = tf.placeholder(tf.float32, [None, num_steps])
cell = tf.nn.rnn_cell.GRUCell(num_units)
cell = tf.nn.rnn_cell.MultiRNNCell([cell] * num_layers)
init_state = cell.zero_state(batch_size, tf.float32)
rnn_outputs, final_state = tf.nn.dynamic_rnn(cell, X, initial_state=init_state)
with tf.variable_scope('softmax'):
W = tf.get_variable('W', [num_units, num_classes])
b = tf.get_variable('b', [num_classes], initializer=tf.constant_initializer(0.0))
# A bit of reshaping magic
rnn_outputs = tf.reshape(rnn_outputs, [-1, state_size])
y_reshaped = tf.reshape(y, [-1])
logits = tf.matmul(rnn_outputs, W) + b
predictions = tf.nn.softmax(logits)
total_loss = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(logits, y_reshaped))
train_step = tf.train.AdamOptimizer(learning_rate).minimize(total_loss)
During traning, lets assume we have long sequences x, y, and we already subdivided them in smaller parts with size [batch_size, num_steps]. Then we train as:
training_state = None
for x,y in zip(X, Y):
feed_dict={g['x']: X, g['y']: Y}
if training_state is not None:
feed_dict[g['init_state']] = training_state
_, sess.run([train_step, final_state], feed_dict)


the and BCG vaccine for COVID- that The vaccination against have immune with are ;():â€". countries {background has from cells SARS-CoV- clinical margin which {border-style protection COVID-. px;} #ffffff;} deaths immunity use United cases including innate response treatment tuberculosis universal been may can current data human infection nonspecific population provide respiratory was ahead also developed mortality not study trained vaccines India Research SARS-CoV-. This confirmed coronavirus development due first health immunization its novel number online print, trials used adaptive cells, childhood countries, disease during high like million per reported such than therapeutic through trial virus Veterinary among both children control developing different early effects induces other pandemic policy px; responses spread while {font-family Apr COVID-, ICAR-Indian Med. TB, around being between case caused cells. font-size given global infected lead might public studies their this van Immunol. Mar Med Sci. States, age any bladder cross-protection doi:./S-()-. double; few higher immunity. include infections. more potential provided reduction revealed review stopped vaccination. vaccine, viral & CDÂ Clin CoV Coronavirus Health Institute Italy, Lancet. Situation TiwariR, [published adopted all available before border-color border-width causing considered disease. drug into many mechanisms nations new one only phase production research role severe solid; some started system there under vaccination, where years {font-style {font-weight (BCG) ;():. ;:. August BareillyUttar China Figure France, InstituteIzatnagar, Int National PLoS SARS, WHO activation acute alternative and/or antibodies based bold burden but compared courier; death diseases effective efficacy either em; enhanced further had having important incidence known levels low mRNA morbidity most nations, prevent prevention pt;} researchers respectively. safe since suggest these those tuberculosis. types vaccine. world


#include <BL3_GbxAI_structs.hpp>
◆ AccuracyOverride
◆ bOverrideAccuracy
◆ bOverrideBurstCount
◆ bOverrideBurstDelay
◆ bOverrideDesiredRange
| bool bOverrideDesiredRange |
◆ bOverrideFireConeAngle
| bool bOverrideFireConeAngle |
◆ BurstCountOverride
◆ BurstDelayOverride
◆ bUseSuppressingFireTime
| bool bUseSuppressingFireTime |
◆ DesiredRangeOverride
◆ FireConeAngle
◆ MaxWeaponLeadingDistance
| float MaxWeaponLeadingDistance |
◆ SuppressingFireTime
◆ UnknownData00
| unsigned char UnknownData00[0x3] |
◆ UnknownData01
| unsigned char UnknownData01[0x7] |
◆ UnknownData02
| unsigned char UnknownData02[0x7] |
◆ UnknownData03
| unsigned char UnknownData03[0x7] |
◆ UnknownData04
| unsigned char UnknownData04[0x3] |
◆ UnknownData05
| unsigned char UnknownData05[0x3] |
◆ UnknownData06
| unsigned char UnknownData06[0x4] |


215 x 315px
215 x 315px
215 x 315px
215 x 315px
Lorem Ipsum is simply dummy text of the printing and typesetting industry. 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.
180 x 150px
Lorem ipsum dolor sit amet
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Link to website 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. Link to website
Read More180 x 150px
Lorem ipsum dolor sit amet
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Link to website 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. Link to website
Read More180 x 150px
Lorem ipsum dolor sit amet
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Link to website 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. Link to website
Read More


April 19th, 2017 - April 21th, 2017 Jodhpur, Rajasthan
We invite you to ESPECTRO2K17
About
Espectro
Espectro is an annual cultural fest of MBM Engineering College, Jodhpur, organized by student union. This fest is being celebrated in college from past 6 years. Over 10,000 youth take part in this fest and enjoy this.
Again this year, Student union of college is organizing "ESPECTRO - A DIVE INTO ECSTASY !" with an event theme of "Jodhpur -The Pride of Marwar."


◆ close()
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.close |
( |
| ) |
|
|
static |
Log summaries and close log file writers.
◆ closeAndThrowaway()
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.closeAndThrowaway |
( |
| ) |
|
|
static |
Close log streams and throw away logs.
◆ copyFileToRunFolder() [1/2]
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.copyFileToRunFolder |
( |
String |
fileName | ) |
|
|
staticprivate |
Copy any desired file to the run folder.
- Parameters
-
◆ copyFileToRunFolder() [2/2]
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.copyFileToRunFolder |
( |
String |
fileName, |
|
|
String |
newFileName |
|
) |
| |
|
static |
Copy any desired file to the run folder under a new name.
- Parameters
-
| fileName | File name |
| newFileName | New file name |
◆ copyRunConfiguration()
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.copyRunConfiguration |
( |
| ) |
|
|
static |
Copy the configuration files.
◆ getExternalWriter()
| static BufferedWriter ch.ethz.systems.netbench.core.log.SimulationLogger.getExternalWriter |
( |
String |
logFileName | ) |
|
|
static |
Create (or fetch) an external writer, which can be used to create your own personal logs.
- Parameters
-
- Returns
- Writer instance (already opened, is automatically closed when calling close())
◆ getRunFolderFull()
| static String ch.ethz.systems.netbench.core.log.SimulationLogger.getRunFolderFull |
( |
| ) |
|
|
static |
Retrieve the full absolute path of the run folder.
- Returns
- Full run folder path
◆ hasInversionsTrackingEnabled()
| static boolean ch.ethz.systems.netbench.core.log.SimulationLogger.hasInversionsTrackingEnabled |
( |
| ) |
|
|
static |
◆ hasQueueBoundTrackingEnabled()
| static boolean ch.ethz.systems.netbench.core.log.SimulationLogger.hasQueueBoundTrackingEnabled |
( |
| ) |
|
|
static |
◆ hasRankMappingEnabled()
| static boolean ch.ethz.systems.netbench.core.log.SimulationLogger.hasRankMappingEnabled |
( |
| ) |
|
|
static |
◆ hasUnpifonessTrackingEnabled()
| static boolean ch.ethz.systems.netbench.core.log.SimulationLogger.hasUnpifonessTrackingEnabled |
( |
| ) |
|
|
static |
◆ increaseStatisticCounter()
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.increaseStatisticCounter |
( |
String |
name | ) |
|
|
static |
Increase a basic statistic counter with the given name by one.
- Parameters
-
◆ logFlowSummary()
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.logFlowSummary |
( |
| ) |
|
|
staticprivate |
Print a human-readable summary of all the flows and whether they were completed.
◆ logInfo()
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.logInfo |
( |
String |
key, |
|
|
String |
value |
|
) |
| |
|
static |
Log a general parameter to indicate some information about what was done in the run.
- Parameters
-
| key | Key string |
| value | Value string |
◆ logInversionsPerRank()
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.logInversionsPerRank |
( |
int |
id, |
|
|
int |
rank, |
|
|
long |
inversion |
|
) |
| |
|
static |
◆ logPortUtilization()
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.logPortUtilization |
( |
| ) |
|
|
staticprivate |
Print a human-readable summary of all the port utilization.
◆ logQueueBound()
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.logQueueBound |
( |
int |
id, |
|
|
int |
queue, |
|
|
int |
queueBound |
|
) |
| |
|
static |
◆ logRankMapping()
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.logRankMapping |
( |
int |
id, |
|
|
long |
rank, |
|
|
long |
queue |
|
) |
| |
|
static |
◆ logUnpifoness()
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.logUnpifoness |
( |
int |
id, |
|
|
long |
unpifoness |
|
) |
| |
|
static |
◆ open() [1/2]
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.open |
( |
| ) |
|
|
static |
Open log file writer without a specific run folder name.
◆ open() [2/2]
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.open |
( |
NBProperties |
tempRunConfiguration | ) |
|
|
static |
Open log file writers with a specific run folder name.
- Parameters
-
| tempRunConfiguration | Temporary run configuration (not yet centrally loaded) |
◆ openWriter()
| static BufferedWriter ch.ethz.systems.netbench.core.log.SimulationLogger.openWriter |
( |
String |
logFileName | ) |
|
|
staticprivate |
Open a log writer in the run directory.
- Parameters
-
- Returns
- Writer of the log
◆ registerCallbackBeforeClose()
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.registerCallbackBeforeClose |
( |
LoggerCallback |
callback | ) |
|
|
static |
Register the call back of a logger before the close of the simulation logger.
- Parameters
-
| callback | Callback instance |
◆ throwaway()
| static void ch.ethz.systems.netbench.core.log.SimulationLogger.throwaway |
( |
| ) |
|
|
staticprivate |
◆ baseDir
| String ch.ethz.systems.netbench.core.log.SimulationLogger.baseDir |
|
staticprivate |
◆ callbacks
| List<LoggerCallback> ch.ethz.systems.netbench.core.log.SimulationLogger.callbacks = new ArrayList<>() |
|
staticprivate |
◆ flowLoggers
| List<FlowLogger> ch.ethz.systems.netbench.core.log.SimulationLogger.flowLoggers = new ArrayList<>() |
|
staticprivate |
◆ inversionsTrackingEnabled
| boolean ch.ethz.systems.netbench.core.log.SimulationLogger.inversionsTrackingEnabled |
|
staticprivate |
◆ logHumanReadableFlowCompletionEnabled
| boolean ch.ethz.systems.netbench.core.log.SimulationLogger.logHumanReadableFlowCompletionEnabled |
|
staticprivate |
◆ originalErrOutputStream
| PrintStream ch.ethz.systems.netbench.core.log.SimulationLogger.originalErrOutputStream |
|
staticprivate |
◆ originalOutOutputStream
| PrintStream ch.ethz.systems.netbench.core.log.SimulationLogger.originalOutOutputStream |
|
staticprivate |
◆ portLoggers
| List<PortLogger> ch.ethz.systems.netbench.core.log.SimulationLogger.portLoggers = new ArrayList<>() |
|
staticprivate |
◆ queueBoundTrackingEnabled
| boolean ch.ethz.systems.netbench.core.log.SimulationLogger.queueBoundTrackingEnabled |
|
staticprivate |
◆ rankMappingEnabled
| boolean ch.ethz.systems.netbench.core.log.SimulationLogger.rankMappingEnabled |
|
staticprivate |
◆ runFolderName
| String ch.ethz.systems.netbench.core.log.SimulationLogger.runFolderName |
|
staticprivate |
◆ statisticCounters
| Map<String, Long> ch.ethz.systems.netbench.core.log.SimulationLogger.statisticCounters = new HashMap<>() |
|
staticprivate |
◆ underlyingFileOutputStream
| OutputStream ch.ethz.systems.netbench.core.log.SimulationLogger.underlyingFileOutputStream |
|
staticprivate |
◆ unpifonessTrackingEnabled
| boolean ch.ethz.systems.netbench.core.log.SimulationLogger.unpifonessTrackingEnabled |
|
staticprivate |
◆ writerFlowCompletionCsvFile
| BufferedWriter ch.ethz.systems.netbench.core.log.SimulationLogger.writerFlowCompletionCsvFile |
|
staticprivate |
◆ writerFlowCompletionFile
| BufferedWriter ch.ethz.systems.netbench.core.log.SimulationLogger.writerFlowCompletionFile |
|
staticprivate |
◆ writerFlowThroughputFile
| BufferedWriter ch.ethz.systems.netbench.core.log.SimulationLogger.writerFlowThroughputFile |
|
staticprivate |
◆ writerInversionsTracking
| BufferedWriter ch.ethz.systems.netbench.core.log.SimulationLogger.writerInversionsTracking |
|
staticprivate |
◆ writerPortQueueStateFile
| BufferedWriter ch.ethz.systems.netbench.core.log.SimulationLogger.writerPortQueueStateFile |
|
staticprivate |
◆ writerPortUtilizationCsvFile
| BufferedWriter ch.ethz.systems.netbench.core.log.SimulationLogger.writerPortUtilizationCsvFile |
|
staticprivate |
◆ writerPortUtilizationFile
| BufferedWriter ch.ethz.systems.netbench.core.log.SimulationLogger.writerPortUtilizationFile |
|
staticprivate |
◆ writerQueueBoundTracking
| BufferedWriter ch.ethz.systems.netbench.core.log.SimulationLogger.writerQueueBoundTracking |
|
staticprivate |
◆ writerRanktoQueuesMapping
| BufferedWriter ch.ethz.systems.netbench.core.log.SimulationLogger.writerRanktoQueuesMapping |
|
staticprivate |
◆ writerRunInfoFile
| BufferedWriter ch.ethz.systems.netbench.core.log.SimulationLogger.writerRunInfoFile |
|
staticprivate |
◆ writersAdded
| Map<String, BufferedWriter> ch.ethz.systems.netbench.core.log.SimulationLogger.writersAdded = new HashMap<>() |
|
staticprivate |
◆ writerUnpifonessTracking
| BufferedWriter ch.ethz.systems.netbench.core.log.SimulationLogger.writerUnpifonessTracking |
|
staticprivate |
The documentation for this class was generated from the following file:


dFL8 is an ERC20 token similar to Wrapped Ether, with a 1% burn to counter Ethereum's native inflation.
Find Out More
In 2019 Bomb released their deflationary token that took the crypto world by storm. Instead of idly
watching the experiment run its course, the community doubled down and created an entire ecosystem around
the idea. As such, DFL8 seeks to fill the void by becoming the standard version of wrapped ETH used to
interact with other deflationary tokens, or simply hodl ETH without worrying about inflation.
We combat Ethereum's inflation by:
- 1% Transactional burn
- 1% Wrap burn
- 1% Unwrap Burn
DFL8 tokens are minted when you lock Ether in the contract, based on the current value. The value is based on the number of ETH to DFL8 in the contract. You can unwrap your DFL8 for ETH at any time.
There is no contract owner, only a Whitelist Manager to excempt qualified addresses from burn. All tokens must be backed by Ether, including for contract creator.open source.
This token aims to be low risk and truely deflationary, meaning the value of your tokens will never go down. Balances can be reduced by wrapping, unwrapping, and transfering the tokens only. If you wrap 1 ETH and immediately unwrap, you will receive 0.98ETH back as the maximum possible loss.
We have launched minimal web interface and smart contract for limited real world testing on the Ropsten testnet.
The contract address is subject to change. Set MetaMask to Ropsten testnet and get some ETH at the Ropsten Faucet.
Etherscan
GitHub
This beta release is to test site and contract functionality, and allow the community to evaluate the
contract mechanics. We encourage your participation and feedback!
Get ETH to participate in the beta at the Ropsten Faucet.
Convert your ETH to DFL8 token, which can be redeemed at any time. We recommend leaving 0.05 eth to cover
gas for unwrapping..
You can use DFL8 as a trading pair at the following places:
DefSwap
The ecosystem is growing by the day, please ensure you always do your own research before purchasing any tokens as many of these are experimental.


This inspection reports any empty classes or Java file without any class defined. A class is empty if it
doesn't have any fields, methods, constructors or initializers. Empty classes are often left over
after large changes or refactorings.
Use the list below to specify special annotations. Classes annotated with one of
these annotations will be ignored by this inspection.
Powered by InspectionGadgets


Rook
The Rook:
The rook, also known as a tower or castle, is a mighty piece, sometimes thought of as the army's artillery. While not as mobile as the queen or the knight, the rooks are powerful and threatening, especially once they've emerged from their corners. They can move in a straight line in four directions, as many spaces as they want, therefore potentially dominating entire ranks or files on the board. When used together or in cooperation with the queen, they can easily force the king to move in a certain direction.
The rooks can also perform a useful strategic move in combination with the king, called "castling." In a castle, a player moves his king from his original spot, two spaces to the left or right, towards a rook which is also still standing on its original corner space. He then places that rook on the space that the king jumped over. In order to be able to castle, there must be no pieces between the king and the rook in question, and neither the king, the king's destination square, nor the square the king jumps can be within attacking range of an opposing piece. Also, after a piece has been moved at least one time during the game, that piece can no longer be used to castle. I demonstrate castling in the below video.
Rook specifications:
- Point value: 5
- Movement/Attack range: unlimited spaces, straight on ranks and files in all four directions
- Special move: Kingside or queenside castle
- Notation symbol: R


Produces this output, which has been approved by stakeholders: test.pdf
review_requested
by None at 2022-06-13 15:39:12.review_requested
by None at 2022-06-13 15:39:13.review_requested
by None at 2022-06-13 15:39:13.review_requested
by None at 2022-06-13 15:39:13.Thanks!
How about this? test.pdf
This looks good to me. If @amycvo agrees, I can share it with adapt for confirmation. Thanks, Regine.
I like it! Thanks, Regine!
Great! Committed to SVN at svn://lib-svn.princeton.edu/libsvn/trunk/rbscXSL/RBSCBoxLabelsAbID.xsl
Hi Regine- stakeholders are still weighing in with their thoughts about the mockup as I needed to share it with with ADAPT and others for confirmation. I'll report back once a final decision is made. Thanks, and sorry if my earlier message was unclear.
mentioned
by None at 2022-06-13 13:56:38.subscribed
by None at 2022-06-13 13:56:38.closed
by None at 2022-06-13 15:37:01.reopened
by None at 2022-06-13 19:31:25.closed
by Christina Chortaria at 2022-06-13 14:18:30.And Max, just want to doublecheck--there is no need to worry about other punctuations, right? We have all sorts of them:
For example, will the record<PHONE_NUMBER>506421 (A few acres of snow : the saga of the French and Indian Wars) be tagged? It contains the string "United States--History--King George's War, 1744-1748."
referenced
by Christina Chortaria at 2022-06-13 14:19:47.merged
by Christina Chortaria at 2022-06-13 14:19:47.closed
by Christina Chortaria at 2022-06-13 14:19:47.head_ref_deleted
by Christina Chortaria at 2022-06-13 14:19:48.labeled
by Trey Pendragon at 2022-06-13 19:07:12.referenced
by Trey Pendragon at 2022-06-13 19:07:48.merged
by Trey Pendragon at 2022-06-13 19:07:48.closed
by Trey Pendragon at 2022-06-13 19:07:48.head_ref_deleted
by Trey Pendragon at 2022-06-13 19:07:49.For this work cycle this is specced for research into if it's possible and how much work it would take to implement.
Hannah has confirmed that they do not have access to this account.
This has been shared using LastPass as<EMAIL_ADDRESS>, to which Hannah should have access.
closed
by James R. Griffin III at 2022-06-13 14:03:37.closed
by James R. Griffin III at 2022-06-13 14:06:49.Something crashed during import:
14 submission_891097
Processing collections file: collections
Adding item from directory submission_891696
java.lang.ArrayIndexOutOfBoundsException: 0
at org.dspace.app.itemimport.ItemImport.addItem(ItemImport.java:865)
at org.dspace.app.itemimport.ItemImport.addItems(ItemImport.java:736)
at org.dspace.app.itemimport.ItemImport.main(ItemImport.java:498)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.dspace.app.launcher.ScriptLauncher.runOneCommand(ScriptLauncher.java:226)
at org.dspace.app.launcher.ScriptLauncher.main(ScriptLauncher.java:78)
java.lang.ArrayIndexOutOfBoundsException: 0
Started:<PHONE_NUMBER>018
Ended:<PHONE_NUMBER>226
Elapsed time: 17 secs (17208 msecs)
Working on debugging it now.
unassigned
by James R. Griffin III at 2022-06-13 14:08:16.assigned
by Bess Sadler at 2022-06-13 14:08:23.referenced
by Bess Sadler at 2022-06-13 15:19:56.merged
by Bess Sadler at 2022-06-13 15:19:56.closed
by Bess Sadler at 2022-06-13 15:19:56.head_ref_deleted
by Bess Sadler at 2022-06-13 15:19:57.assigned
by Trey Pendragon at 2022-06-13 17:06:07.labeled
by Eliot Jordan at 2022-06-13 20:07:16.labeled
by Eliot Jordan at 2022-06-13 20:07:54.labeled
by Eliot Jordan at 2022-06-13 20:17:05.labeled
by Eliot Jordan at 2022-06-13 20:17:05.referenced
by Eliot Jordan at 2022-06-13 20:49:51.merged
by Eliot Jordan at 2022-06-13 20:49:51.closed
by Eliot Jordan at 2022-06-13 20:49:51.head_ref_deleted
by Eliot Jordan at 2022-06-13 20:49:52.Closed by https://github.com/pulibrary/figgy/pull/5158/commits/30c1a8c4feabed8f03dbb187f2699ba0a67e5fcc
labeled
by Eliot Jordan at 2022-06-13 20:19:07.labeled
by Eliot Jordan at 2022-06-13 20:19:07.closed
by Eliot Jordan at 2022-06-13 21:00:40.labeled
by Eliot Jordan at 2022-06-13 20:11:37.labeled
by Eliot Jordan at 2022-06-13 20:11:37.renamed
by Eliot Jordan at 2022-06-13 20:13:12.closed
by Eliot Jordan at 2022-06-13 21:00:50.labeled
by Eliot Jordan at 2022-06-13 20:21:59.labeled
by Eliot Jordan at 2022-06-13 20:21:59.closed
by Eliot Jordan at 2022-06-13 21:00:54.ready_for_review
by Eliot Jordan at 2022-06-13 19:25:52.head_ref_force_pushed
by Eliot Jordan at 2022-06-13 19:28:08.renamed
by Eliot Jordan at 2022-06-13 19:34:33.renamed
by Eliot Jordan at 2022-06-13 20:30:32.referenced
by Eliot Jordan at 2022-06-13 21:06:25.merged
by Eliot Jordan at 2022-06-13 21:06:25.closed
by Eliot Jordan at 2022-06-13 21:06:25.head_ref_deleted
by Eliot Jordan at 2022-06-13 21:06:25.ready_for_review
by Eliot Jordan at 2022-06-13 21:21:15.referenced
by Eliot Jordan at 2022-06-13 21:56:13.merged
by Eliot Jordan at 2022-06-13 21:56:13.closed
by Eliot Jordan at 2022-06-13 21:56:13.head_ref_deleted
by Eliot Jordan at 2022-06-13 21:56:14.referenced
by Eliot Jordan at 2022-06-13 22:04:59.merged
by Eliot Jordan at 2022-06-13 22:04:59.closed
by Eliot Jordan at 2022-06-13 22:04:59.head_ref_deleted
by Eliot Jordan at 2022-06-13 22:05:00.labeled
by Shaun Ellis at 2022-06-13 19:43:24.referenced
by Trey Pendragon at 2022-06-13 22:07:33.merged
by Trey Pendragon at 2022-06-13 22:07:33.closed
by Trey Pendragon at 2022-06-13 22:07:33.head_ref_deleted
by Trey Pendragon at 2022-06-13 22:07:34.closed
by Shaun Ellis at 2022-06-13 19:31:25.head_ref_deleted
by Trey Pendragon at 2022-06-13 22:07:34.deployed
by None at 2022-06-13 19:00:20.We will discuss how to test this with Mark Zelesky when he gets back from vacation
This was done on PR https://github.com/pulibrary/lib_jobs/pull/364
closed
by Max Kadel at 2022-06-13 16:57:39.Accomplished with this PR - https://github.com/pulibrary/lib_jobs/pull/343
closed
by Max Kadel at 2022-06-13 16:58:41.assigned
by Max Kadel at 2022-06-13 17:01:14.@mzelesky when you're available, I have two questions:
mentioned
by None at 2022-06-13 20:42:18.subscribed
by None at 2022-06-13 20:42:18.deployed
by None at 2022-06-13 14:37:55.Coverage remained the same at 94.182% when pulling a0a60530f6ebd16170891951117a3ffb3e9b83cf on dependabot/npmandyarn/coffeescript-2.7.0 into 2656fb0ad6c2c1a6baf282d2290d749c93c85758 on main.
@dependabot rebase
mentioned
by Dependabot at 2022-06-13 11:08:40.head_ref_force_pushed
by None at 2022-06-13 11:11:18.labeled
by Christina Chortaria at 2022-06-13 11:36:22.labeled
by Christina Chortaria at 2022-06-13 11:36:22.labeled
by Christina Chortaria at 2022-06-13 11:40:34.labeled
by Christina Chortaria at 2022-06-13 11:40:34.labeled
by Christina Chortaria at 2022-06-13 11:42:27.labeled
by Christina Chortaria at 2022-06-13 11:42:27.labeled
by Christina Chortaria at 2022-06-13 11:43:25.labeled
by Christina Chortaria at 2022-06-13 11:43:25.duplicate of https://github.com/pulibrary/orangelight/issues/873
labeled
by Christina Chortaria at 2022-06-13 11:44:26.labeled
by Christina Chortaria at 2022-06-13 11:44:26.closed
by Christina Chortaria at 2022-06-13 11:46:34.labeled
by Christina Chortaria at 2022-06-13 11:46:48.labeled
by Christina Chortaria at 2022-06-13 11:48:51.labeled
by Christina Chortaria at 2022-06-13 11:48:51.labeled
by Christina Chortaria at 2022-06-13 11:52:42.labeled
by Christina Chortaria at 2022-06-13 11:52:42.labeled
by Christina Chortaria at 2022-06-13 12:29:16.labeled
by Christina Chortaria at 2022-06-13 11:50:48.labeled
by Christina Chortaria at 2022-06-13 11:50:48.labeled
by Christina Chortaria at 2022-06-13 12:29:34.assigned
by Hector Correa at 2022-06-13 14:16:19.unassigned
by Hannah H at 2022-06-13 13:54:40.assigned
by Hannah H at 2022-06-13 14:26:15.assigned
by Hannah H at 2022-06-13 14:26:23.Closed by https://github.com/pulibrary/pdc_describe/pull/158
closed
by Hector Correa at 2022-06-13 17:58:56.Closed by https://github.com/pulibrary/pdc_describe/pull/158
closed
by Hector Correa at 2022-06-13 17:59:06.Closed by https://github.com/pulibrary/pdc_describe/pull/134
closed
by Hector Correa at 2022-06-13 18:00:34.assigned
by Bess Sadler at 2022-06-13 14:27:36.assigned
by Francis Kayiwa at 2022-06-13 14:27:36.referenced
by Christina Chortaria at 2022-06-13 15:09:39.merged
by Christina Chortaria at 2022-06-13 15:09:40.closed
by Christina Chortaria at 2022-06-13 15:09:40.head_ref_deleted
by Christina Chortaria at 2022-06-13 15:09:41.heya @maxkadel I made changes to your branch accidentally. Sorry about that.
head_ref_force_pushed
by Francis Kayiwa at 2022-06-13 18:53:16.mentioned
by Max Kadel at 2022-06-13 18:53:52.subscribed
by Max Kadel at 2022-06-13 18:53:52.


Note: all the publications listed are peer-reviewed conference papers or journals, not including abstract submittions and posters. Please find my
CV for the full list of publications.
[CHI'23] (Best Paper Award)
What Do We Mean When We Talk about Trust in Social Media? A Systematic Review.
Yixuan Zhang, Joseph D. Gaggiano, , Nutchanon Yongsatianchot, Nurul Suhaimi, Miso Kim, Yifan Sun, Jacqueline Griffin, and Andrea G. Parker.
[CHI'23] (Best Paper Honorable Mention Award)
Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions.
Jiawei Zhou, Yixuan Zhang, Qianni Luo, Andrea G. Parker, and Munmun De Choudhury.
[Interacting with Computer Journal'23]
Social Media Use and Individuals’ Intent to Get Vaccinated Against COVID-19: An Exploratory Study of the Mediating Role of Information Exposure.
Nurul Suhaimi, Yixuan Zhang, Nutchanon Yongsatianchot, Joseph D Gaggiano, Anne Okrah, Shivani A. Patel, Stacy Marsella, Miso Kim, Andrea G. Parker, and Jacqueline Griffin.
[CHI'22]
Shifting Trust: Examining How Trust and Distrust Emerge, Transform, and Collapse in COVID-19 Information Seeking.
Yixuan Zhang, Nurul Suhaimi, Nutchanon Yongsatianchot, Joseph D Gaggiano, Miso Kim, Shivani A. Patel, Yifan Sun, Stacy Marsella, Jacqueline Griffin, and Andrea G. Parker.
[CHI'22]
Investigating Older Adults’ Attitudes towards Crisis Informatics Tools: Opportunities for Enhancing Community Resilience during Disasters.
Nurul Suhaimi, Yixuan Zhang, Mary Joseph, Miso Kim, Andrea G. Parker, and Jacqueline Griffin.
[The Design Journal'22]
Healthy Aging Adviser: Designing a Service to Support the Life Transitions and Autonomy of Older Adults.
Miso Kim, Valeria Ramdin, Rachel Pozzar, Paul Fombelle, Xing Zhou, Yixuan Zhang, and Muling Jiang.
[VIS'21 panel]
What is the Role of VIS in Combating COVID-19?
Min Chen, David Ebert, Lace Padilla, Yixuan Zhang, and Alfie Abdul-Rahman
[EuroVis'21]
Daisen: A Framework for Visualizing Detailed GPU Execution
Yifan Sun, Yixuan Zhang, Ali Mosallaei, Michael D. Shah, Cody Dunne, and David Kaeli.
2020
[VIS'20]
Sequence Braiding: Visual Overviews of Temporal Event Sequences and Attributes
Sara Di Bartolomeo, Yixuan Zhang, Fangfang Sheng, and Cody Dunne
[VIS'20]
VisConnect: Distributed Event Synchronization for Collaborative Visualization
Michail Schwab, David Saffo, Yixuan Zhang, Shash Sinha, Cristina Nita-Rotaru, James Tompkin, Cody Dunne, and Michelle A. Borkin
[PervasiveHealth'20]
Information Visualization for Diabetes Management: A Literature Review
Yixuan Zhang, Andrea G. Parker, and Cody Dunne
[CHI'20]
Understanding the Use of Crisis Informatics Technology among Older Adults
Yixuan Zhang, Nurul Suhaimi, Rana Azghandi, Mary Amulya Joseph, Miso Kim, Jacqueline Griffin, and Andrea G. Parker.
[CHI'20] (short paper)
Eat4Thought: A Design of Food Journaling
Yixuan Zhang and Andrea G. Parker
[CHI'20 AI4HCI Workshop]
Digital Collaborator: Augmenting Task Abstraction in Visualization Design with Artificial Intelligence
Yixuan Zhang, Aditeya Pandey, John A. Guerra-Gomez, Andrea G. Parker, and Michelle A. Borkin.
2019
[CSCW'19]
Caring for Alzheimer’s Disease Caregivers: A Qualitative Study Investigating Opportunities for Exergame Innovation
Elizabeth Stowell, Yixuan Zhang, Carmen Castaneda-Sceppa, Margie Lachman, and Andrea G. Parker.
[VIS'19]
Evaluating Alignment Approaches in Superimposed Time-Series and Temporal Event-Sequence Visualizations
Yixuan Zhang, Sara Di Bartolomeo, Fangfang Sheng, Holly Jimison, and Cody Dunne.
2018
[VIS'18]
IDMVis: Temporal Event Sequence Visualization for Type 1 Diabetes Treatment Decision Support
Yixuan Zhang, Kartik Chanana, and Cody Dunne.
[AHFE'18]
Autonomy in Residential Care: Using TEAMWORK and the Deep Dive to Facilitate Interdisciplinary Collaboration
Yixuan Zhang, Rachel Pozzar, Xing Zhou, Miso Kim, Paul W Fombelle, and Valeria A Ramdin.
[ServDes'18]
Resident Autonomy in Assisted Living Facilities: Aconceptual Framework for Transformative Service Research
Valeria A Ramdin, Miso Kim, Rachel Pozzar, Paul W Fombelle, Yixuan Zhang, Xing Zhou, and Julia Janigan.
[Frontiers in Service'18]
Residential Care as a Negative Service: Informing a Service Prototype to Promote Elder Autonomy
Rachel Pozzar, Miso Kim, Valeria A Ramdin, Xing Zhou, Yixuan Zhang, and Paul W Fombelle.