GoLand Plugin Development
Introduction
GoLand is an IntelliJ Platform-based product.
Plugin projects for GoLand can be developed using IntelliJ IDEA with the gradle-intellij-plugin
.
Configuring Plugin Projects Targeting GoLand
The configuration of GoLand plugin projects follows the methods described in Configuring Plugin Projects using the IntelliJ IDEA Product Attribute, and Configuring the plugin.xml File.
The table below summarizes the gradle-intellij-plugin
attributes to set in the build.gradle
file for a GoLand plugin project:
gradle-intellij-plugin Attribute |
Attribute Value |
|---|---|
intellij.type |
IU for IntelliJ IDEA Ultimate. (The Go plugin isn’t compatible with IntelliJ IDEA Community Edition.) |
intellij.version |
Set to the same IU BRANCH.BUILD as the GoLand target version, e.g. 193.5233.102 |
intellij.plugins |
org.jetbrains.plugins.go:193.5233.102.83 for the Go plugin.See below for Go plugin version information. |
runIde.ideDirectory |
Path to locally installed target version of GoLand. For example, on macOS:/Users/<user name>/Library/Application Support/JetBrains/Toolbox/apps/Goland/ch-0/193.5233.112/GoLand.app/Contents |
The version of the Go plugin is explicitly declared because it isn’t bundled with IntelliJ IDEA Ultimate Edition. Select a version of the Go plugin that is compatible with the IntelliJ Idea Ultimate version.
The dependency on the Go plugin APIs must be declared in the plugin.xml
file.
As described in Modules Specific to Functionality table, the <depends>
tags must declare com.intellij.modules.go
.
The plugin.xml file must also declare a dependency on com.intellij.modules.platform
as explained in Configuring the plugin.xml File.
The dependency declaration is illustrated in the plugin.xml
snippet below:
<!-- Requires the Go plugin -->
<depends>org.jetbrains.plugins.go</depends>
<!-- Requires the platform module to distinguish it from a legacy plugin -->
<depends>com.intellij.modules.platform</depends>
Available GoLand APIs
Use the Exploring APIs as a Consumer process to identify the library intellij-go-<version>.jar
, where <version>
corresponds to the version of the Go plugin.
Test your plugin with any version of GoLand you intend to support.
Open Source Plugins for GoLand
When learning new APIs, it is helpful to have some representative projects for reference:


new knn()
KNN Module.
The concept for knn via levenshtein is taken from Open refine
https://github.com/OpenRefine/OpenRefine/wiki/Clustering-In-Depth
- Source:
Methods
(static) addNgram(str, id, ngrams) → {Void}
Helper function.
Parameters:
| Name | Type | Description |
|---|---|---|
str |
string | str to be added to the ngrams array. |
id |
integer | id of element in data. |
ngrams |
object | array of ngrams. |
- Source:
Returns:
- .
- Type
- Void
(static) analyse(_clusters, _data, limit, type) → {object}
Analyse the ngram groups.
Parameters:
| Name | Type | Description |
|---|---|---|
_clusters |
object | Created in module.prepare. |
_data |
array | Original array of strings. |
limit |
float | When are two strings assumed to similar (levenshtein in percentage), default:0.1. |
type |
string | How should the levenshtein distance be checked: absolute|percentage, default:percentage. |
- Source:
Returns:
results.
- Type
- object
(static) cluster(results) → {object}
Cluster results of module.analyse.
Parameters:
| Name | Type | Description |
|---|---|---|
results |
object | created in module.analyse. |
- Source:
Returns:
outClusters - Clustered map.
- Type
- object
(static) prepare(_data, ngramSize) → {object}
Collect strings into groups that share certain ngrams.
Parameters:
| Name | Type | Description |
|---|---|---|
_data |
array | Array of strings. |
ngramSize |
integer | Size of ngrams. |
- Source:
Returns:
cluster of ngram groups.
- Type
- object
(static) process(id, clusters, data, limit, type) → {object}
Calculate and report levenshtein distance for a group of strings.
Parameters:
| Name | Type | Description |
|---|---|---|
id |
integer | id of item in array |
clusters |
array | Strings. |
data |
array | Original data. |
limit |
float | When are two strings assumed to similar (levenshtein in percentage), default:0.1. |
type |
string | How should the levenshtein distance be checked: absolute|percentage, default:percentage. |
- Source:
Returns:
results.
- Type
- object
(static) readableCluster(clusters, reduced_data, data) → {object}
Translates the cluster from module.cluster into an easy to read and edit object.
Parameters:
| Name | Type | Description |
|---|---|---|
clusters |
object | created in module.cluster. |
reduced_data |
array | created in module.reduce. |
data |
array | original data. |
- Source:
Returns:
Clustered map.
- Type
- object
(static) reduce(_data) → {array}
Remove duplicates from array.
Parameters:
| Name | Type | Description |
|---|---|---|
_data |
array | Array with strings. |
- Source:
Returns:
reduced_column.
- Type
- array


public interface MessagingListenerV2
| Modifier and Type | Method and Description |
|---|---|
void |
localyticsDidDismissInAppMessage()
Callback that an in-app message was dismissed.
|
void |
localyticsDidDisplayInAppMessage()
Callback that an in-app message was displayed.
|
boolean |
localyticsShouldDeeplink(java.lang.String url)
|
boolean |
localyticsShouldDelaySessionStartInAppMessages()
Callback to determine if In-App campaigns triggered by session
start should be shown.
|
boolean |
localyticsShouldShowInAppMessage(InAppCampaign campaign)
Callback to determine if an In-App campaign should be shown.
|
boolean |
localyticsShouldShowPlacesPushNotification(PlacesCampaign campaign)
Callback to determine if the triggering of a Places campaign should show a local notification.
|
boolean |
localyticsShouldShowPushNotification(PushCampaign campaign)
Callback to determine if a Push campaign should be shown.
|
void |
localyticsWillDismissInAppMessage()
Callback that an in-app message will be dismissed.
|
InAppConfiguration |
localyticsWillDisplayInAppMessage(InAppCampaign campaign,
InAppConfiguration configuration)
Callback to modify presentation of an In-App Campaign.
|
android.support.v4.app.NotificationCompat.Builder |
localyticsWillShowPlacesPushNotification(android.support.v4.app.NotificationCompat.Builder builder,
PlacesCampaign campaign)
Callback to determine if a Push campaign should show a local notification.
|
android.support.v4.app.NotificationCompat.Builder |
localyticsWillShowPushNotification(android.support.v4.app.NotificationCompat.Builder builder,
PushCampaign campaign)
Callback to determine if a Push campaign should show a local notification.
|
boolean localyticsShouldShowInAppMessage(@NonNull InAppCampaign campaign)
campaign
- The campaign that will be shown@NonNull InAppConfiguration localyticsWillDisplayInAppMessage(@NonNull InAppCampaign campaign, @NonNull InAppConfiguration configuration)
campaign
- An immutable object representing the campaign that will be shownconfiguration
- An object representing the mutable visual state of the In-App campaignInAppConfiguration
void localyticsDidDisplayInAppMessage()
void localyticsWillDismissInAppMessage()
void localyticsDidDismissInAppMessage()
boolean localyticsShouldDelaySessionStartInAppMessages()
Localytics.triggerInAppMessagesForSessionStart()
boolean localyticsShouldShowPushNotification(@NonNull PushCampaign campaign)
campaign
- An object defining a Push Campaignboolean localyticsShouldShowPlacesPushNotification(@NonNull PlacesCampaign campaign)
campaign
- An object defining a Places Campaign@NonNull android.support.v4.app.NotificationCompat.Builder localyticsWillShowPlacesPushNotification(@NonNull android.support.v4.app.NotificationCompat.Builder builder, @NonNull PlacesCampaign campaign)
builder
- The Android Notification builder used to customize a local notification.campaign
- The campaign that triggered the push notification@NonNull android.support.v4.app.NotificationCompat.Builder localyticsWillShowPushNotification(@NonNull android.support.v4.app.NotificationCompat.Builder builder, @NonNull PushCampaign campaign)
builder
- The Android Notification builder used to customize a local notification.campaign
- The campaign that triggered the push notification@Deprecated boolean localyticsShouldDeeplink(@NonNull java.lang.String url)
CallToActionListener.localyticsShouldDeeplink(java.lang.String, com.localytics.android.Campaign)
url
- The URL that was triggered inside a Localytics call to action


For the paper’s 150th anniversary, we thought it’d be fitting to make a timeline, so we did. We scoured more than 100 years of digital archives to highlight notable events from campus and Daily Cal history. From the very first game at Memorial Stadium to the Milo Yiannopoulos protests, we compiled headlines from nearly every decade since the Daily Cal was founded in 1871. So sit back, relax and take a scroll through history.
{% include "partials/timeline.html" %}
About this story
Michelle Li contributed to this project. This project is open-source on Github.
{% include "partials/_footer.html" %}
Support us
We're a nonprofit, student-run newsroom. Please consider donating to support our coverage.
{% block js %}
{% endblock %}


Research
My primary research interest is to develop and apply machine learning and optimization methods to improve health outcomes for patients. I enjoy collaborating with clinicians and other healthcare domain experts on interdisciplinary research teams.
Selected publications
- Pawlowski C, et. al. SARS-CoV-2 and influenza coinfection throughout the COVID-19 pandemic: an assessment of coinfection rates, cohort characteristics, and clinical outcomes. PNAS Nexus, 2022.
- Niesen M, Pawlowski C, et. al. Surveillance of Safety of 3 Doses of COVID-19 mRNA Vaccination Using Electronic Health Records. JAMA Network Open, 2022.
- Razonable R, Pawlowski C, et. al. Casirivimab-Imdevimab treatment is associated with reduced rates of hospitalization among high-risk patients with mild to moderate coronavirus disease-19. EClinicalMedicine, 2021.
- Ganesh R, Pawlowski C, et. al. Intravenous bamlanivimab use associates with reduced hospitalization in high-risk patients with mild to moderate COVID-19. J Clin Invest., 2021.
- Donadio G, Choudhary M, Lindemer E, Pawlowski C, Soundararajan V. Counties with Lower Insurance Coverage and Housing Problems Are Associated with Both Slower Vaccine Rollout and Higher COVID-19 Incidence. Vaccines, 2021.
- Pawlowski C, et. al. FDA-authorized COVID-19 vaccines are effective per real-world evidence synthesized across a multi-state health system. Med, 2021.
- Venkatakrishnan A, Pawlowski C, et. al. Mapping each pre-existing condition’s association to short-term and long-term COVID-19 complications. NPJ Dig. Med., 2021.
- Pawlowski C, et. al. Cerebral Venous Sinus Thrombosis is not Significantly Linked to COVID-19 Vaccines or Non-COVID Vaccines in a Large Multi-State Health System. Journal of Stroke and Cerebrovascular Diseases, 2021.
- Pawlowski C, et. al. Enoxaparin is associated with lower rates of mortality than unfractionated Heparin in hospitalized COVID-19 patients. EClinicalMedicine, 2021.
- Kirkup C, Pawlowski C, et. al. Healthcare disparities among anticoagulation therapies for severe COVID-19 patients in the multi-site VIRUS registry. J Med Virol., 2021.
- Pawlowski C, et. al. Exploratory analysis of immunization records highlights decreased SARS-CoV-2 rates in individuals with recent non-COVID-19 vaccinations. Sci Rep., 2021.
- Pawlowski C, et. al. Inference from longitudinal laboratory tests characterizes temporal evolution of COVID-19-associated coagulopathy (CAC). eLife, 2020.
- Bertsimas D, Pawlowski C, Orfanoudaki A. Imputation of clinical covariates in time series. Machine Learning, 2020.
- Bertsimas D, Dunn J, Pawlowski C, Zhuo Y. Robust Classification. INFORMS Journal on Optimization, 2018.
- Bertsimas D, Pawlowski C, Zhuo Y. From Predictive Methods to Missing Data Imputation: An Optimization Approach. JMLR, 2018.
Working papers
- Bertsimas D, Pawlowski C. “Tensor Completion with Noisy Side Information.” To appear in Machine Learning, 2023.
- Silvert E, Hester L, Ramudu E, Pawlowski C, et. al. “Identifying signs and symptoms of AL amyloidosis in electronic health records using natural language processing, diagnosis codes, and manually abstracted registry data.” Submitted to American Journal of Hematology.
- Ip W, Pawlowski C, et. al. “Augmented curation of disease diagnoses and medications for patients with hepatocellular carcinoma.” Abstract to appear in 2023 ASCO Annual Meeting Proceedings.
- Bandi H, Pawlowski C, et. al. “An AI-ECG based algorithm to predict pacemaker need post TAVR surgery.” In preparation.
- Sobiesk M, Pawlowski C, et. al. “Economic effectiveness of an AI-ECG algorithm to detect low ejection fraction.” In preparation.
Patents
- Pawlowski C, et. al. “System To Identify Size And Location Information From Unstructured Inputs.” Submitted non-provisional to US Patent and Trademark Office, 2023.
- Pawlowski C, et. al. Identifying Patient Populations Vulnerable To Viral Infection And Methods Of Inducing Heterologous Immunity In Same. US Patent and Trademark Office, 2022.


Watermarking of Models
Destined to 3D Printing
by Deformation of Surfaces
Presented by Antoine Prieëls
Supervised by Benoît Macq
Table of Contents
- Digital Models Representation and Processing
- Mesh Representation
- Watermarking of 3D models
- Use cases
- Watermarking Algorithms Evaluation
- Scope of this work
- Watermarking Algorithms
- Volume Moments
- Spectral Decomposition
- Adapting Spectral Decomposition to Additive Manufacturing
- Comparison of the Algorithms
- Future Work
- Summary
Mesh Representation
- 3D models are usually defined using the "mesh" representation. A mesh is defined by two kinds of information:
Geometry
- Set of vertices described by their 3D coordinates
Connectivity
- Set of faces that link the vertices to one another
Watermarking of 3D models
- Digital watermarking: process of hiding digital information in a noise-tolerant container
- Possible containers include: videos, audio, images or 3D models
- The introduced noise should be inserted in a way that can later be interpreted either as a '0' or a '1' in order to read the message
- The two types of data describing a mesh can carry a message:
- Geometry: Slightly change the coordinates of the vertices
- Connectivity: Create new faces or change the length of existing edges
Use cases
- Most use cases are directly or indirectly linked to the ownership of an object:
- Owner identification
- Proof of ownership
- Transaction tracking
- Content authentication
Watermarking Algorithms Evaluation - Robustness
The robustness of an algorithm is described using a bit error rate:
- There also exist lots of possible attacks:
- Noise addition
- Smoothing
- Cropping attack
- Re-meshing
- ...
- Typical process can also modify the geometry and/or connectivity of a mesh:
- Re-meshing
- Print/Scan process
Watermarking Algorithms Evaluation - Imperceptibility
- The watermark should be as imperceptible as possible
- We used three different metrics to evaluate the imperceptibility of a watermark:
- Root-Mean-Square Error
- Hausdorff Distance
- Local Smoothness
- Similar results for all three metrics, so we will consider only the Hausdorff distance here
Scope of this work
- "Watermarking of models destined to 3D printing"
- Printing a mesh results in:
- Completely different connectivity
- Some inaccuracies in geometry
- Watermarking scheme needs to be applied on the geometry and be resistant to inaccuracies
Volume Moments - Principles
$m_{pqr} = \displaystyle\int_{}^{} x^p y^q z^r\ \rho (x,y,z)\ dx\;dy\;dz$,
$\rho(x, y, z)$ is the volume indicator function
Embedding Process
- Normalization (scaling, translating and rotating)
- Patches decomposition
- Patches classification (cover, compensation and discarded)
- Deformation of the cover patches to a selected moment value
- Compensation
Volume Moments - Results
- Bit error rate between $10$ and $20\%$
- Watermark completely lost after a smoothing of 7 iterations
- Resists to noise up to an amplitude of $3\%$
Spectral Decomposition - Principles
- Work in the spectral domain: $(X, Y, Z)$ ⇔ $(P, Q, R)$
- Reorder $(P, Q, R)$ ⇒ $(C_{min}, C_{inter}, C_{max})$
- Divide the range $[C_{min}, C_{max}]$ into two intervals $W_0$ and $W_1$
- Place $C_{inter}$ in the $W_0$ interval if we want to insert a '0' or in $W_1$ for inserting a '1'
Impact of the choice of frequencies on imperceptibility
- Lower frequencies
⇒ important, localized deformations
- Higher frequencies
⇒ smooth global changes
Spectral Decomposition - Patch Decomposition
- The transformation of coordinates into their spectra requires the computation of the eigenvalues and eigenvectors of a Laplacian matrix
- The computation of eigenvalues is performed in $\mathcal{O}(n^3)$ but can be reduced to $\mathcal{O}(n)$ in case of a sparse matrix
- We then need to divide the model into patches
Spectral Decomposition - Results
Spectral Decomposition - Results
- Bit error rate nearly equal to zero with only $10\%$ of frequencies modified
- Watermark completely lost after a smoothing of 2 to 3 iterations
- Highly resistant to noise up to an amplitude of $10\%$
Adapting Spectral Decomposition
- Spectral Decomposition cannot be applied as it is to models destined to 3D printing
- Find another patch decomposition not depending on the connectivity
Cut the model into layers
To retrieve the exact same patches, we only need to find a single direction, the one perpendicular to the cuts
Adapting Spectral Decomposition
- Do not modify $z$ values to make sure that no vertex goes from one layer to another
- Avoiding discontinuities
- Vertices located on cuts are duplicated, corresponding vertices from each side of the cut might move independently
- Discard those vertices during the embedding of the watermark to avoid discontinuities
- Avoiding perceptible modifications
- Divide the spectra into more than two intervals
- Discard "unwatermarkable" patches
Spectral Decomposition with Layers - Results
Spectral Decomposition with Layers - Results
- The robustness depends on the number of layers created
- The more layers are created, the greater is the bit error rate
- Watermark completely lost after a smoothing of a single iteration and an addition of noise with an amplitude as small as $1\%$
Comparison of the Algorithms
| Volume Moments | Spectral Decomposition (Patches) | Spectral Decomposition (Layers) |
Future Work
- Do not discard the vertices located on cuts but consider them in one of the two adjacent layers
- Instead of leaving unchanged values of $C_{inter}$ corresponding to the $z$ spectra, change the values of $C_{min}$ and $C_{max}$ accordingly
- Adapting the patch decomposition into layers to many more watermarking schemes less dependent on the connectivity than the Spectral Decomposition
Summary
- Background knowledge on 3D models and their representation
- Background knowledge on watermarking in general and watermarking of 3D models
- Explanation of three watermarking schemes, their implementations, and evaluations regarding their robustness and imperceptibility
- Comparison of those algorithms
Questions ?


--- permalink: /404.html title: "404: Page not found" layout: default sitemap: false --- 404 Page not found
Page not found


|
libcoap
4.2.1
|
API functions for logging support. More...
Macros | |
| #define | COAP_DEBUG_FD stdout |
Used for output for LOG_DEBUG to LOG_ERR . More... | |
| #define | COAP_ERR_FD stderr |
Used for output for LOG_CRIT to LOG_EMERG . More... | |
| #define | coap_log(level, ...) |
| Logging function. More... | |
Typedefs | |
| typedef void(* | coap_log_handler_t) (coap_log_t level, const char *message) |
| Logging call-back handler definition. More... | |
Enumerations | |
| enum | coap_log_t { LOG_EMERG =0, LOG_ALERT, LOG_CRIT, LOG_ERR, LOG_WARNING, LOG_NOTICE, LOG_INFO, LOG_DEBUG, COAP_LOG_CIPHERS =LOG_DEBUG+2 } |
| Pre-defined log levels akin to what is used in syslog with LOG_CIPHERS added. More... | |
Functions | |
| coap_log_t | coap_get_log_level (void) |
| Get the current logging level. More... | |
| void | coap_set_log_level (coap_log_t level) |
| Sets the log level to the specified value. More... | |
| void | coap_set_log_handler (coap_log_handler_t handler) |
| Add a custom log callback handler. More... | |
| const char * | coap_package_name (void) |
| Get the library package name. More... | |
| const char * | coap_package_version (void) |
| Get the library package version. More... | |
| void | coap_log_impl (coap_log_t level, const char *format,...) |
Writes the given text to COAP_ERR_FD (for level <= LOG_CRIT ) or COAP_DEBUG_FD (for level >= LOG_ERR ). More... | |
| void | coap_set_show_pdu_output (int use_fprintf) |
| Defines the output mode for the coap_show_pdu() function. More... | |
| void | coap_show_pdu (coap_log_t level, const coap_pdu_t *pdu) |
Display the contents of the specified pdu . More... | |
| void | coap_show_tls_version (coap_log_t level) |
| Display the current (D)TLS library linked with and built for version. More... | |
| char * | coap_string_tls_version (char *buffer, size_t bufsize) |
| Build a string containing the current (D)TLS library linked with and built for version. More... | |
| size_t | coap_print_addr (const struct coap_address_t *address, unsigned char *buffer, size_t size) |
| Print the address into the defined buffer. More... | |
| void | coap_dtls_set_log_level (int level) |
Sets the (D)TLS logging level to the specified level . More... | |
| int | coap_dtls_get_log_level (void) |
| Get the current (D)TLS logging. More... | |
| const char * | coap_session_str (const coap_session_t *session) |
| Get session description. More... | |
| const char * | coap_endpoint_str (const coap_endpoint_t *endpoint) |
| Get endpoint description. More... | |
API functions for logging support.
| #define COAP_DEBUG_FD stdout |
Used for output for LOG_DEBUG
to LOG_ERR
.
Definition at line 23 of file coap_debug.h.
| #define COAP_ERR_FD stderr |
Used for output for LOG_CRIT
to LOG_EMERG
.
Definition at line 30 of file coap_debug.h.
| #define coap_log | ( | level, | |
| ... | |||
| ) |
Logging function.
Writes the given text to COAP_ERR_FD
(for level
<= LOG_CRIT
) or COAP_DEBUG_FD
(for level
>= LOG_ERR
). The text is output only when level
is below or equal to the log level that set by coap_set_log_level().
| level | One of the LOG_* values. |
Definition at line 129 of file coap_debug.h.
| typedef void(* coap_log_handler_t) (coap_log_t level, const char *message) |
Logging call-back handler definition.
| level | One of the LOG_* values. |
| message | Zero-terminated string message to log. |
Definition at line 80 of file coap_debug.h.
| enum coap_log_t |
Pre-defined log levels akin to what is used in syslog with LOG_CIPHERS added.
| Enumerator | |
|---|---|
| LOG_EMERG | Emergency. |
| LOG_ALERT | Alert. |
| LOG_CRIT | Critical. |
| LOG_ERR | Error. |
| LOG_WARNING | Warning. |
| LOG_NOTICE | Notice. |
| LOG_INFO | Information. |
| LOG_DEBUG | Debug. |
| COAP_LOG_CIPHERS | CipherInfo. |
Definition at line 47 of file coap_debug.h.
| int coap_dtls_get_log_level | ( | void | ) |
Get the current (D)TLS logging.
Get the current (D)TLS logging.
Definition at line 135 of file coap_dtls_gnutls.c.
| void coap_dtls_set_log_level | ( | int | level | ) |
Sets the (D)TLS logging level to the specified level
.
Note: coap_log_level() will influence output if at a specified level.
| level | The logging level to use - LOG_* |
Sets the (D)TLS logging level to the specified level
.
Definition at line 128 of file coap_dtls_gnutls.c.
| const char* coap_endpoint_str | ( | const coap_endpoint_t * | endpoint | ) |
Get endpoint description.
| endpoint | The CoAP endpoint. |
Definition at line 1088 of file coap_session.c.
| coap_log_t coap_get_log_level | ( | void | ) |
Get the current logging level.
Definition at line 61 of file coap_debug.c.
| void coap_log_impl | ( | coap_log_t | level, |
| const char * | format, | ||
| ... | |||
| ) |
Writes the given text to COAP_ERR_FD
(for level
<= LOG_CRIT
) or COAP_DEBUG_FD
(for level
>= LOG_ERR
).
The text is output only when level
is below or equal to the log level that set by coap_set_log_level().
Internal function.
| level | One of the LOG_* values. & |
| format | The format string to use. |
Definition at line 758 of file coap_debug.c.
| const char* coap_package_name | ( | void | ) |
Get the library package name.
Definition at line 47 of file coap_debug.c.
| const char* coap_package_version | ( | void | ) |
Get the library package version.
Definition at line 51 of file coap_debug.c.
| size_t coap_print_addr | ( | const struct coap_address_t * | address, |
| unsigned char * | buffer, | ||
| size_t | size | ||
| ) |
Print the address into the defined buffer.
Internal Function.
| address | The address to print. |
| buffer | The buffer to print into. |
| size | The size of the buffer to print into. |
Definition at line 161 of file coap_debug.c.
| const char* coap_session_str | ( | const coap_session_t * | session | ) |
Get session description.
| session | The CoAP session. |
Definition at line 1049 of file coap_session.c.
| void coap_set_log_handler | ( | coap_log_handler_t | handler | ) |
Add a custom log callback handler.
| handler | The logging handler to use or NULL to use default handler. |
Definition at line 753 of file coap_debug.c.
| void coap_set_log_level | ( | coap_log_t | level | ) |
Sets the log level to the specified value.
| level | One of the LOG_* values. |
Definition at line 66 of file coap_debug.c.
| void coap_set_show_pdu_output | ( | int | use_fprintf | ) |
Defines the output mode for the coap_show_pdu() function.
| use_fprintf | 1 if the output is to use fprintf() (the default) 0 if the output is to use coap_log(). |
Definition at line 56 of file coap_debug.c.
| void coap_show_pdu | ( | coap_log_t | level, |
| const coap_pdu_t * | pdu | ||
| ) |
Display the contents of the specified pdu
.
Note: The output method of coap_show_pdu() is dependent on the setting of coap_set_show_pdu_output().
| level | The required minimum logging level. |
| pdu | The PDU to decode. |
Definition at line 455 of file coap_debug.c.
| void coap_show_tls_version | ( | coap_log_t | level | ) |
Display the current (D)TLS library linked with and built for version.
| level | The required minimum logging level. |
Definition at line 662 of file coap_debug.c.
| char* coap_string_tls_version | ( | char * | buffer, |
| size_t | bufsize | ||
| ) |
Build a string containing the current (D)TLS library linked with and built for version.
| buffer | The buffer to put the string into. |
| bufsize | The size of the buffer to put the string into. |
Definition at line 669 of file coap_debug.c.


Stock
New Invoice
VUDA
Some quick example text to build on the card title and make up the bulk of the card's content.
Works
Accounts
Roads
Some quick example text to build on the card title and make up the bulk of the card's content.
Works
Accounts


iris
, nco
and gridgen
...conda install -c ioos iris
conda config --add channels ioos
wget http://bit.ly/ioos_req -O ioos_req.txt
conda create --yes -n IOOS --file ioos_req.txt python=2.7
export PATH=$HOME/miniconda/bin:$PATH && source activate IOOS
That is it!
| iris | mpld3 | pyoos |
| pandas | folium | rdflib |
| geojson | requests | ipython-notebook |
| xlrd | mplleaflet | oceans |
| qrcode | utilities |
We would like to thank SECOORA for the funding support. We would also like to thank the contributions of members of NOAA/IOOS, and Principal investigators.


| Subject | CRN | Title | Credit Hours | Class Description |
|---|---|---|---|---|
|
|
||||
| {{row.department}} | {{row.department_crn}} | {{row.class_title}} | {{row.credit_hours}} | {{row.class_description}} |
| Subject & Course Number: {{row.department}} {{row.department_crn}} | Class Title: {{row.class_title}} | Credit Hours: {{row.credit_hours}} | Description: {{row.class_description}} | |
|
|


Event: Friends! Romans! and Film making nuts! Lend me your ears! If you are the kind of person
who enjoys making films on the go then this is your opportunity to make money out of it. The
colorful fest, Pearl '15, the interesting flock of people and the scenic BITS campus should really work your appetite for some quality film making. Can you make poetry in a film in the 48 hours
you spend on our campus?
Format: Participate in teams that will make your film crew. Quality, clarity, cinematography and
creativity will factor into how good your 48 hour film is. Minimal editing is accepted.
The only rule we have is that the movie has to be made on campus and that it should be
submitted before Pearl '15 ends.
Prize: To be announced
Submission: On campus.
Contact: Syed Shoeb<PHONE_NUMBER>.
Event:
Video is an expression media that should know no bounds of duration. Vines are short videos or a compilation of small videos that can be very mesmerizing.
Format: Submissions will be in the form of videos smaller than a minute. A vine will qualify only if it is a compilation of smaller videos (2-6 seconds in length). The compiled video should not exceed 60 seconds.
Contact: Syed Shoeb<PHONE_NUMBER>.
Event: Performance and Interactive session by a prominent personality (to be announced)
Format: Dates to be announced
Contact: Syed Shoeb<PHONE_NUMBER>.
Event: Fests are lively and all during the day but we are creatures of the night. For my nocturnal
bros we bring you the theatre that works all night. All night movie screening, popcorn and a few
surprises, the ol' filmy way.
Format: All nights of Pearl '15
Contact: Syed Shoeb<PHONE_NUMBER>.
Event: Ever seen a movie and all you could think of was how many different ways the same scene
could have been played out? Ever replaced famous lines with your own concoctions? Well BITS
'Talkies' gives you the opportunity to do just that. And what's more you will be handsomely rewarded
for it.
Event Format: Participants will take scenes from movies and replace the AUDIO in them with their
own versions. The resultant videos may be spoofs, serious, better or worse than the originals. You
are free to replace dialogues, background scores or any audio effect. Get creative. Avoid the use of
unnecessary profanity. Entries will be displayed on the Pearl '15 page and the best ones (judged on
Facebook likes, quality and creativity) will be displayed during the fest.
Submission:Entries to be mailed to<EMAIL_ADDRESS>Prize:Prizes worth 5k to be won.
Contact: Syed Shoeb<PHONE_NUMBER>.
Event: We bring to you the second edition of the national short film making competition and this year
we have upped the challenge and its reward. Judged over by the likes of Ms. Sarika Thakur and Mr.
Rahul Dholakia in the past, this year entries from all over the nation will compete to be the best in
short-film making. Do you have what it takes?
Format: Entries shall be less than 30 minutes in duration. There is no bar on cinematography and
theme is open. All entries, including the ones in English, have to have subtitles in ENGLISH. Use of
profanity and excessive violence is to be avoided but it's your canvas, so paint it as best as you think
you can.
Submission: send entry or link (YouTube/Drop box) of entry to<EMAIL_ADDRESS>Prize: Prizes worth 30,000 to be won.
Contact: Syed Shoeb<PHONE_NUMBER>


3.0.0
enum for amplitude modes, RAW, ZERO, MINMAX, MEAN
Create MinMaxable from a d3 style two element array.
MinMaxable
:
new MinMaxable
MinMaxable
(MinMaxable?)
MinMaxable
(number)
MinMaxable
(MinMaxable?)
Type: MinMaxable
(Duration)
(Duration)
Links amplitude scales across multiple seismographs, respecting doRmean.
(Array<AmplitudeScalable>?)
optional list of AmplitudeScalable to link
Type: (ReturnType<any> | null)
Links new Seismograph with this amplitude scale.
(Array<(AmplitudeScalable | {amp_scalable: AmplitudeScalable})>)
Array of AmplitudeScalable to link
Link new Seismograph with this amplitude scale.
((AmplitudeScalable | {amp_scalable: AmplitudeScalable}))
AmplitudeScalable to link
Unlink Seismograph with this amplitude scale.
(AmplitudeScalable)
AmplitudeScalable to unlink
Recalculate the best amplitude scale for all Seismographs. Causes a redraw.
Array<Promise<AmplitudeScalable>>
:
array of promise of best amp scales
Array<Promise<AmplitudeScalable>>
Array<Promise<AmplitudeScalable>>
Extends LinkedAmplitudeScale
(Array<AmplitudeScalable>?)
Array<Promise<AmplitudeScalable>>
Array<Promise<AmplitudeScalable>>
Links time scales across multiple seismographs.
(Array<TimeScalable>?)
optional list of TimeScalables to link
(Duration?)
(Duration?)
(number?)
Type: Duration
Type: Duration
Type: (null | Duration)
Type: (null | Duration)
Link new TimeScalable with this time scale.
((TimeScalable | {time_scalable: TimeScalable}))
TimeScalable to link
Links TimeScalable with this time scale. Each object in the array should either be a TimeScalable or have a time_scalable field that is a TimeScalable.
(Array<(TimeScalable | {time_scalable: TimeScalable})>)
Array of TimeScalable to link
Unlink TimeScalable with this amplitude scale.
 Causes a redraw.


This page describes the current module, library, and extension maintainers of Ruby.
A module maintainer is responsible for a certain part of Ruby.
The maintainer fixes bugs of the part. Particularly, they should fix security vulnerabilities as soon as possible.
They handle issues related the module on the Redmine or ML.
They may be discharged by the 3 months rule [ruby-core:25764].
They have commit right to Ruby's repository to modify their part in the repository.
They have “developer” role on the Redmine to modify issues.
They have authority to decide the feature of their part. But they should always respect discussions on ruby-core/ruby-dev.
A submaintainer of a module is like a maintainer. But The submaintainer does not have authority to change/add a feature on his/her part. They need consensus on ruby-core/ruby-dev before changing/adding. Some of submaintainers have commit right, others don't.


portfolio
Demo Reel
Click here for previous projects.
Path Tracer (Spring 2017)
Naive Monte Carlo - Advanced Rendering (CIS561)
- Cosine Weighted Sampling
- Uniform Weighted Sampling
- Lambertian Surface
- Oren Nayar Surface
- Fresnel Dielectrics and Conductors
- Direct Lighting
- Specular and Transmission
References:
Ray Tracer (Spring 2017)
First assignment in Advanced Rendering (CIS561)
Implemented:
- Multithreading
- Lambertian and Phong Materials
- Specular Reflection
- Texture Mapping
Mini Minecraft (Fall 2016)
Final project for Intro to Computer Graphics (CIS560)
Teammates: Meghanna Seshadri and Aman Sachan
My tasks:
- Terrain Collisions
- Physics
- L-System River Generation
- Camera Control
- Sounds
- NPC AI
Mini Maya (Fall 2016)
This project was spread out into three different stages.
-
Half-Edge Mesh Implementation
- Parse OBJ to display mesh
- GUI
- Catmull-Clark Subdivision
-
Skeletons and Skinning
- Parse JSON skeleton to bind to mesh
- Skin Weight Editor
Houdini Fireworks (Fall 2016)
This was due around the time of the 2016 election so I opted for a Red, White, and Blue color scheme.
This was one part of the CIS562 (Computer Animation) Particle System Assignment. We weren't allowed to use the built in fireworks systems in Houdini. Instead we were instructed to create the fireworks from scratch.A salute to all nations but mostly America.
Walk Cycle (Fall 2016)
This was one part of the CIS562 (Computer Animation) Motion Capture and Animation assignment. We had programmed an FK and IK system prior to this; the emphasis of the assignment was to see how animators utilize the rig.
Machine Project (Fall 2016)
First project for 3D Modelling at Penn.
Inspiration for this came from one of my favorite rides at Disney World: Buzz Lightyear's Space Ranger Spin where I have gotten 999,999 points at least 50 times.
Maya
Environment Project (Fall 2016)
Inspired by Nighthawks.
More images/descriptions can be seen here.
Maya
Final Project (Fall 2016)
More images/descriptions can be seen here.
Maya
SteerLite Crowd Simulator (Fall 2015)
Final project for Intro to Computer Graphics (CS428) at Rutgers. Worked in a team to create a fully functional crowd simulator which implemented A* and Social Forces between agents among others.
We were also competing with our fellow classmates to get the lowest benchmarks per testcase. Our benchmarks and more testcases can be viewed here.
My task was to reduce collisions and direct the animation of the agents.
Derivative of SteerSuite
C++
Playing by the Book - Animated Short (Fall 2014)
Director, Writer, Animator, Editor
Final animated short for 2D Animation at Rutgers.
Deleted - Short Film (Fall 2013)
Director, Writer, Editor
Final short film for Directing for the Screen at Rutgers.


{% load sekizai_tags %} {% load static %}
Type in something from another wiki page's title and auto-complete will help you create a tag for your wiki link. Tags for links look like this:
[Title of link](wiki:ArticleSlug){# We do this to prevent accidental form submission - this isn't _really_ a form #}
You can link to another website simply by inserting an address example.com or http://example.com or by using the markdown syntax:
[Clickable text](http://example.com){% addtoblock "js" %} {% comment %} So, for whatever reason, bulmahead doesn't have a LICENSE file. There is one in the package.json, but that isn't a standard most projects adhere to - so I've declined to include it within the project directly. The package.json states MIT - but there is no prose or license text available for the project itself. {% endcomment %} {% endaddtoblock %}


MDF : Form Builder
Name
Email
Both First Name and Last Name are Mandatory and should have atleast 4 characters
Submit
Value: {{ form.value | json }}
Validation status: {{ form.status }}
MDF : Form Builder
Name
Please enter a name
Please enter atleast 4 Letters
Email
Please enter a Valid email
Template Driven Form Validation
Name
Submit
Enter a Name
Please enter atleast 3 chars
Please enter a valid email address


{%- include widget/head.html -%}
{%- include widget/header.html -%}
{%- include widget/intro.html -%}
{%- include widget/section1.html -%}
{%- include widget/section2.html -%}
{%- include widget/section3.html -%}
{%- include widget/section4.html -%}
{%- include widget/section5.html -%}
{%- include widget/section6.html -%}
{%- include widget/footer.html -%}
{%- include widget/copy.html -%}


Identity
Sign In
Identity Provider:
Max Time to live (seconds):
Sign In
Sign Out
Principal:
Delegation:
Expiry (ns from now)
Contact the IC
Replica URL:
Canister ID:
Who Am I?


Facts About Dogs
Dogs have a sense of time. It's been proven that they know the difference between a hour and five. If conditioned to, they can predict future events, such as regular walk times.
Dogs have a sense of time. It's been proven that they know the difference between a hour and five. If conditioned to, they can predict future events, such as regular walk times.


This is the title of the form
This is the description of the form
Name
Email
Age
Select an option
Select an option
Option 1
Option 2
option 3
Select an option
Option 1
Option 2
Option 3
Select your options
Option 1
Option 2
Option 3
Any comments?
Submit


| Module | Source File | Description |
|---|---|---|
| Parameters_Mod | Parameters_Mod.f90 | Characters: Define the output format of all ASCII data written to a file. Integers: Defines the data used to calulate sizes of read/write file |
| Read_Write_Basic_Mod | Read_Write_Basic_Mod.f90 | This module defines the raw reads/writes of derived data types to/from a data file. The access can be ASCII or Binary with the default being Binary.
This module contains 1D through 7D routines but can define array data types to 15D, the 2008 Standard (Intel allows 31D, PGI is unknown).
This module can handle any derived data type to be read/written to a file. Just add the derived data type and a corresponding Read_ |
| Read_Write_Target_Material_Mod | Read_Write_Target_Material_Mod.f90 | |
| Read_Write_TRNINPUT_Mod | Read_Write_TRNINPUT_Mod.f90 | |
| Type_CArray_1D_Mod | Type_CArray_1D_Mod.f90 | |
| Type_Target_Material_Mod | Type_Target_Material_Mod.f90 | !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Called by Read_Write_Basic_Mod.f90 |


'Insect apocalypse' driven by light pollution, scientists reveal
by Christopher CarboneInsects, which pollinate flowers and break down waste, are crucial.
Although researchers have warned before about the negative effects of climate change and habitat loss, they are now blaming a new culprit for the worldwide decline of bugs -- light pollution.
A group of entomologists reviewed about 200 studies and research papers to examine how light pollution is contributing to what's been called the "insect apocalypse." Their findings were published last week in Biological Conservation.
A previous study in April in the same journal looked at agriculture and habitat destruction as series threats to insects, claiming that more than 40 percent of insect species face potential extinction in the coming decades.
“It’s frustrating,” author Brett Seymoure, a postdoctoral fellow at the Living Earth Collaborative at St. Louis’ Washington University, told Gizmodo. “We’re saying, look, light pollution is also a huge driver, especially with nocturnal insects.”
GIGANTIC TSUNAMI PUSHED HEAVY BOULDERS INLAND, SCIENTISTS SAY
Seymoure said a number of different fixes could address the problem, including light timers, covers to lessen light pollution and bulbs that don't mimic daytime light.
Still, the reseachers' work reportedly notes that lights can impact how bug species move, search for food, reproduce, grow and hide from predators.
“If we lose these insects, you’re also gone,” Seymoure said. “It’s over.”
WAS SAME-SEX BEHAVIOR IN ANIMALS HARDWIRED FROM THE BEGINNING?


This method will fully stop the DataStreamServer
Registers a new event handler to handle incoming event messages. The handler is only called for a connection if for the give protocol no ProtocolHandler was registered on the connection level.
name of the protocol to register the handler for
name of the event (also referred to as topic. See {Topics} for some known ones)
function to be called for every occurring event
Registers a new request handler to handle incoming request messages. The handler is only called for a connection if for the give protocol no ProtocolHandler was registered on the connection level.
name of the protocol to register the handler for
name of the request (also referred to as topic. See {Topics} for some known ones)
function to be called for every occurring request
Removes an registered event handler.
name of the protocol to unregister the handler for
name of the event (also referred to as topic. See {Topics} for some known ones)
registered event handler
Removes an registered request handler.
name of the protocol to unregister the handler for
name of the request (also referred to as topic. See {Topics} for some known ones)
registered request handler
DataStreamServer which listens for incoming tcp connections and handles identification of new connections


1 Changes for 1.7.0: 2 3 * New feature: death tests are supported on OpenBSD and in iOS 4 simulator now. 5 * New feature: Google Test now implements a protocol to allow 6 a test runner to detect that a test program has exited 7 prematurely and report it as a failure (before it would be 8 falsely reported as a success if the exit code is 0). 9 * New feature: Test::RecordProperty() can now be used outside of the 10 lifespan of a test method, in which case it will be attributed to 11 the current test case or the test program in the XML report. 12 * New feature (potentially breaking): --gtest_list_tests now prints 13 the type parameters and value parameters for each test. 14 * Improvement: char pointers and char arrays are now escaped properly 15 in failure messages. 16 * Improvement: failure summary in XML reports now includes file and 17 line information. 18 * Improvement: the <testsuites> XML element now has a timestamp attribute. 19 * Improvement: When --gtest_filter is specified, XML report now doesn't 20 contain information about tests that are filtered out. 21 * Fixed the bug where long --gtest_filter flag values are truncated in 22 death tests. 23 * Potentially breaking change: RUN_ALL_TESTS() is now implemented as a 24 function instead of a macro in order to work better with Clang. 25 * Compatibility fixes with C++ 11 and various platforms. 26 * Bug/warning fixes. 27 28 Changes for 1.6.0: 29 30 * New feature: ADD_FAILURE_AT() for reporting a test failure at the 31 given source location -- useful for writing testing utilities. 32 * New feature: the universal value printer is moved from Google Mock 33 to Google Test. 34 * New feature: type parameters and value parameters are reported in 35 the XML report now. 36 * A gtest_disable_pthreads CMake option. 37 * Colored output works in GNU Screen sessions now. 38 * Parameters of value-parameterized tests are now printed in the 39 textual output. 40 * Failures from ad hoc test assertions run before RUN_ALL_TESTS() are 41 now correctly reported. 42 * Arguments of ASSERT_XY and EXPECT_XY no longer need to support << to 43 ostream. 44 * More complete handling of exceptions. 45 * GTEST_ASSERT_XY can be used instead of ASSERT_XY in case the latter 46 name is already used by another library. 47 * --gtest_catch_exceptions is now true by default, allowing a test 48 program to continue after an exception is thrown. 49 * Value-parameterized test fixtures can now derive from Test and 50 WithParamInterface<T> separately, easing conversion of legacy tests. 51 * Death test messages are clearly marked to make them more 52 distinguishable from other messages. 53 * Compatibility fixes for Android, Google Native Client, MinGW, HP UX, 54 PowerPC, Lucid autotools, libCStd, Sun C++, Borland C++ Builder (Code Gear), 55 IBM XL C++ (Visual Age C++), and C++0x. 56 * Bug fixes and implementation clean-ups. 57 * Potentially incompatible changes: disables the harmful 'make install' 58 command in autotools. 59 60 Changes for 1.5.0: 61 62 * New feature: assertions can be safely called in multiple threads 63 where the pthreads library is available. 64 * New feature: predicates used inside EXPECT_TRUE() and friends 65 can now generate custom failure messages. 66 * New feature: Google Test can now be compiled as a DLL. 67 * New feature: fused source files are included. 68 * New feature: prints help when encountering unrecognized Google Test flags. 69 * Experimental feature: CMake build script (requires CMake 2.6.4+). 70 * Experimental feature: the Pump script for meta programming. 71 * double values streamed to an assertion are printed with enough precision 72 to differentiate any two different values. 73 * Google Test now works on Solaris and AIX. 74 * Build and test script improvements. 75 * Bug fixes and implementation clean-ups. 76 77 Potentially breaking changes: 78 79 * Stopped supporting VC++ 7.1 with exceptions disabled. 80 * Dropped support for 'make install'. 81 82 Changes for 1.4.0: 83 84 * New feature: the event listener API 85 * New feature: test shuffling 86 * New feature: the XML report format is closer to junitreport and can 87 be parsed by Hudson now. 88 * New feature: when a test runs under Visual Studio, its failures are 89 integrated in the IDE. 90 * New feature: /MD(d) versions of VC++ projects. 91 * New feature: elapsed time for the tests is printed by default. 92 * New feature: comes with a TR1 tuple implementation such that Boost 93 is no longer needed for Combine(). 94 * New feature: EXPECT_DEATH_IF_SUPPORTED macro and friends. 95 * New feature: the Xcode project can now produce static gtest 96 libraries in addition to a framework. 97 * Compatibility fixes for Solaris, Cygwin, minGW, Windows Mobile, 98 Symbian, gcc, and C++Builder. 99 * Bug fixes and implementation clean-ups. 100 101 Changes for 1.3.0: 102 103 * New feature: death tests on Windows, Cygwin, and Mac. 104 * New feature: ability to use Google Test assertions in other testing 105 frameworks. 106 * New feature: ability to run disabled test via 107 --gtest_also_run_disabled_tests. 108 * New feature: the --help flag for printing the usage. 109 * New feature: access to Google Test flag values in user code. 110 * New feature: a script that packs Google Test into one .h and one 111 .cc file for easy deployment. 112 * New feature: support for distributing test functions to multiple 113 machines (requires support from the test runner). 114 * Bug fixes and implementation clean-ups. 115 116 Changes for 1.2.1: 117 118 * Compatibility fixes for Linux IA-64 and IBM z/OS. 119 * Added support for using Boost and other TR1 implementations. 120 * Changes to the build scripts to support upcoming release of Google C++ 121 Mocking Framework. 122 * Added Makefile to the distribution package. 123 * Improved build instructions in README. 124 125 Changes for 1.2.0: 126 127 * New feature: value-parameterized tests. 128 * New feature: the ASSERT/EXPECT_(NON)FATAL_FAILURE(_ON_ALL_THREADS) 129 macros. 130 * Changed the XML report format to match JUnit/Ant's. 131 * Added tests to the Xcode project. 132 * Added scons/SConscript for building with SCons. 133 * Added src/gtest-all.cc for building Google Test from a single file. 134 * Fixed compatibility with Solaris and z/OS. 135 * Enabled running Python tests on systems with python 2.3 installed, 136 e.g. Mac OS X 10.4. 137 * Bug fixes. 138 139 Changes for 1.1.0: 140 141 * New feature: type-parameterized tests. 142 * New feature: exception assertions. 143 * New feature: printing elapsed time of tests. 144 * Improved the robustness of death tests. 145 * Added an Xcode project and samples. 146 * Adjusted the output format on Windows to be understandable by Visual Studio. 147 * Minor bug fixes. 148 149 Changes for 1.0.1: 150 151 * Added project files for Visual Studio 7.1. 152 * Fixed issues with compiling on Mac OS X. 153 * Fixed issues with compiling on Cygwin. 154 155 Changes for 1.0.0: 156 157 * Initial Open Source release of Google Test


Numbers 20:23
And the LORD spake unto Moses and Aaron in mount Hor, by the coast of the land of Edom, saying,


| Art-id |
label |
caption |
| PMC3544629 |
Figure 1
|
Pediatric hospitalizations for LRTI and RSV according to age ... |
| PMC3544629 |
Figure 2
|
Pediatric hospitalizations for LRTI and RSV according to mon ... |
| PMC3702433 |
Figure 1
|
Flow chart of case enrolment and allocation. ICD-10; Interna ... |
| PMC3702433 |
Figure 2
|
The incidence of hospitalised pneumonia per 1, 000 persons b ... |
| PMC3702433 |
Figure 3
|
The proportion of viral and bacterial agents identified from ... |
| PMC3702433 |
Figure 4
|
The monthly incidence of CAP amongst elderly ≥ 65 years and ... |
| PMC3702433 |
Figure 5
|
The predicted number of adult CAP patients in Vietnam in 200 ... |
| PMC3787546 |
FIGURE 1
|
Human respiratory pathogens associated with asthma exacerbat ... |
| PMC3787546 |
FIGURE 2
|
Human respiratory pathogens associated with exacerbations of ... |
| PMC3787546 |
FIGURE 3
|
Multidisciplinary assessment for asthma exacerbation. PCR, p ... |
| PMC3787546 |
FIGURE 4
|
Viral detection in exacerbations of COPD using PCR or RT-PCR ... |
| PMC4589665 |
Figure 1
|
Metagenome composition before and after genome finishing. Re ... |
| PMC4589665 |
Figure 2
|
Genome completeness before and after genome finishing. (A) G ... |
| PMC4589665 |
Figure 3
|
Steps in recovery of full-length viral genomes from metageno ... |
| PMC5309255 |
FIGURE 1
|
Schematic representation of the phenomenon known as the “sur ... |
| PMC5309255 |
FIGURE 2
|
Food- and waterborne viral surveillance targets for metageno ... |
| PMC5435908 |
Figure 1
|
(a) Decrease of H1N1pdm virus titer in A549 cells infected b ... |
| PMC5435908 |
Figure 2
|
(a) Influence of 100 μg/ml binase at 12 h p.i. on proteome ... |
| PMC5435908 |
Figure 3
|
Effect of binase on functional H1N1pdm viral RNP polymerase ... |
| PMC5435908 |
Figure 4
|
Hypothetic scheme of binase influence on functional viral RN ... |
| PMC5435908 |
Figure 5
|
Viability of HeLa cells treated by binase (24 h) (a) and the ... |
| PMC5683535 |
Fig. 1
|
Benefits and limitations of epidemiological surveillance and ... |
| PMC5693564 |
Fig. 1
|
Map of MERS cases reported worldwide as of June 2016 accordi ... |
| PMC5693564 |
Fig. 2
|
Summary of MERS cases from March 2012 to May 2016. Incidence ... |
| PMC5693564 |
Fig. 3
|
Time-scaled phylogeographic tree of MERS-CoV ORF1a/b sequenc ... |
| PMC5693564 |
Fig. 4
|
Time-scaled phylogeographic tree of MERS-CoV ORF1a/b sequenc ... |
| PMC5693564 |
Fig. 5
|
Worldwide epidemiological contact tracing summarized for MER ... |
| PMC5693564 |
Fig. 6
|
Summary of reported basic reproduction numbers from literatu ... |
| PMC5735522 |
Fig. 1
|
POCKIT™ system workflow for point-of-need detection of Zika ... |
| PMC5765694 |
Fig. 1
|
Study design. Graphical summary of the study focus, design, ... |
| PMC5765694 |
Fig. 2
|
Nasopharyngeal microbiota composition in healthy and RSV-inf ... |
| PMC5765694 |
Fig. 3
|
RSV disease, viral load, and CXCL8 levels in healthy and RSV ... |
| PMC5765694 |
Fig. 4
|
Difference in nasopharyngeal microbial community composition ... |
| PMC5765694 |
Fig. 5
|
Chemokine and cytokine levels during RSV infection. Chemokin ... |
| PMC5765694 |
Fig. 6
|
Nasopharyngeal microbiota composition allows for separation ... |
| PMC5819479 |
Figure 1
|
Accumulation through time of species (purple line), genera ( ... |
| PMC6156540 |
Figure 1
|
Clinical development of vaccines against recent outbreaks. T ... |
| PMC6594388 |
Figure 1
|
Mechanisms of action of different antivirals. A diagram of t ... |
| PMC6727070 |
Figure 1
|
Case (A) and control (B) enrolment and specimen availability ... |
| PMC6727070 |
Figure 2
|
Blood culture results by study site in cases with positive c ... |
| PMC6727070 |
Figure 3
|
Nasopharyngeal-oropharyngeal (NP-OP) pathogen prevalence* an ... |
| PMC6727070 |
Figure 4
|
Aetiological fraction unstratified (A), stratified by age (B ... |
| PMC6727070 |
Figure 5
|
Site-specific aetiology results for ten focus pathogens in c ... |
| PMC6727070 |
Figure 6
|
Cumulative contribution of site-specific ten most common pat ... |
| PMC6911100 |
Fig. 1
|
Middle East Respiratory Syndrome Coronavirus (MERS-CoV) lite ... |
| PMC6911100 |
Fig. 2
|
Geographic distribution of published detection of Middle Eas ... |
| PMC6911100 |
Fig. 3
|
Geographic distribution of detections of Middle East Respira ... |
| PMC6911100 |
Fig. 4
|
Geographic distribution of detections of Middle East Respira ... |
| PMC6925075 |
Fig. 1
|
The role of the Coalition for Epidemic Preparedness Innovati ... |
| PMC6926486 |
Figure 1
|
Phylogenetic and geographical attribution of MERS-CoV strain ... |
| PMC6926486 |
Figure 2
|
Phylogeographic and social network structure of MERS-CoV str ... |
| PMC6926486 |
Figure 3
|
Reconstruction of reproductive number of circulating virus b ... |
| PMC6926871 |
Figure 1
|
Flow diagram of study selection process. |
| PMC6926871 |
Figure 2
|
Published entry and exit screening measures in response to S ... |
| PMC6926871 |
Figure 3
|
Published entry screening measures in response to Influenza ... |
| PMC6926871 |
Figure 4
|
Published entry and exit screening measures in response to E ... |
| PMC6935926 |
FIG 1
|
Schematic to show processing protocol through clinical and r ... |
| PMC6935926 |
FIG 2
|
Characteristics of three pools of influenza virus-negative t ... |
| PMC6935926 |
FIG 3
|
Coverage of influenza virus and Hazara virus genome segments ... |
| PMC6935926 |
FIG 4
|
Total and proportion of influenza virus reads derived by Nan ... |
| PMC6935926 |
FIG 5
|
Phylogenetic trees of consensus influenza virus HA gene deri ... |
| PMC6935926 |
FIG 6
|
Time course experiment showing influenza A virus infection i ... |
| PMC6939334 |
Fig. 1
|
Timeline from 1975 showing the successful development of the ... |
| PMC6939334 |
Fig. 2
|
Schematic overview of antibody humanization from murine anti ... |
| PMC6939334 |
Fig. 3
|
Approaches for the development of therapeutic antibodies. a ... |
| PMC6939334 |
Fig. 4
|
Construction and affinity selection with phage-display antib ... |
| PMC6939334 |
Fig. 5
|
Schematic overview showing the development of antibody-based ... |
| PMC6941257 |
Fig. 1
|
Schematic presentation of DNA aptamer selection using SELEX ... |
| PMC6941257 |
Fig. 2
|
schematic presentation of aptamer effect as an anti-biofilm ... |
| PMC6941257 |
Fig. 3
|
Schematic presentation of aptamer function against different ... |
| PMC6941257 |
Fig. 4
|
Schematic presentation of the therapeutic applications of ap ... |
| PMC6941257 |
Fig. 5
|
Schematic presentation of aptamer effect as an inhibitor of ... |
| PMC6958603 |
Fig. 1
|
Influenza sentinel surveillance implemented at six surveilla ... |
| PMC6961264 |
Figure 1
|
Forest plots of (A) current season vaccine effectiveness est ... |
| PMC6969405 |
Fig. 1
|
Phylogenetic tree of complete genome nucleotide sequences of ... |
| PMC6969405 |
Fig. 2
|
Maximum-likelihood phylogenetic tree of previously published ... |
| PMC6970282 |
Fig. 1
|
Laryngo-pharyngeal specimen after removal at autopsy with en ... |
| PMC6970282 |
Fig. 2
|
Histomicrograph illustrating tonsillar hypertrophy (Hematoxi ... |
| PMC6970282 |
Fig. 3
|
Histomicrograph illustrating dense epiglottal chronic inflam ... |
| PMC6970282 |
Fig. 4
|
Formalin fixed laryngo-pharyngeal specimen with manual appro ... |
| PMC6981968 |
Figure 1
|
Daily statistics for laboratory-confirmed Middle East respir ... |
| PMC6981968 |
Figure 2
|
Results of segmented regression for confirmed cases. |
| PMC7017508 |
Fig. 1
|
Number of children hospitalized with community-acquired pneu ... |
| PMC7017508 |
Fig. 2
|
Number of children hospitalized with community acquired pneu ... |
| PMC7017508 |
Fig. 3
|
Time-dependent changes in the numbers of children hospitaliz ... |
| PMC7019290 |
Figure 1
|
Flow chart of systematic review. The procedures were adapted ... |
| PMC7019290 |
Figure 2
|
An overview of study design and data (and metadata) availabi ... |
| PMC7019290 |
Figure 3
|
( A) Geographical origin of included studies stratified by W ... |
| PMC7019290 |
Figure 4
|
Types of specimens tested in different farm animals by numbe ... |
| PMC7019290 |
Figure 5
|
An overview of virus families found in different farm animal ... |
| PMC7019290 |
Figure 6
|
Frequencies of virus genera of top three most abundant virus ... |
| PMC7028525 |
Figure 1
|
A computed tomography scan of the chest (A and B) shows bila ... |
| PMC7028525 |
Figure 2
|
Trans‐bronchial lung biopsy shows lung parenchyma with intra ... |
| PMC7033854 |
Fig. 1
|
Study flow diagram |
| PMC7033854 |
Fig. 2
|
Comparison to the changes in mean body temperature between t ... |
| PMC7034298 |
Figure 1
|
(A) Pedigree of study family. ± represent segregation status ... |
| PMC7041086 |
Fig. 1
|
Flow chart. After the exclusion of 53 patients, 99 lung tran ... |
| PMC7047374 |
Fig. 1
|
Flowchart of the Bats-Hosts-Reservoir-People transmission ne ... |
| PMC7047374 |
Fig. 2
|
Curve fitting results of the RP model |


Euro 2020: Scotland to host Israel in semi-final
Scotland will face Israel in their one-off Euro 2020 play-off semi-final at Hampden on 26 March.
And if Steve Clarke's side progress, they will be away to Norway or Serbia for a finals place five days later.
Northern Ireland will host Republic of Ireland in Belfast if both sides win their respective semi-finals at Bosnia-Herzegovina and Slovakia.
Israel were one of four 'Path C' teams, alongside Bulgaria, Romania and Hungary, Scotland could have drawn.
Scotland earned their play-off place by winning Nations League Group C1, with Israel second.
Northern and Republic of Ireland already knew their opponents, with Friday's draw deciding the host for each final.
Scotland, then managed by Alex McLeish, lost 2-1 away to Israel in October 2018 before beating them 3-2 at Hampden the following month to top the group.
The Scots, bidding to reach their first major tournament since the 1998 World Cup, then finished third in Euro 2020 qualifying Group I, while Israel came fifth in Group G.
Clarke's side, 53rd in the FIFA world rankings, sit 36 places higher than Israel and the semi-final will hold few fears against a side that lost their last four away Euro qualifiers.
However, the potential trip to face Norway or Serbia is a daunting prospect. Norway haven't suffered a home defeat in more than three years while Serbia are ranked 33rd and played in last year's World Cup.
"The good thing about playing Israel is that, although I wasn't the manger, a lot of the players played against Israel in the Nations League and will have a good understanding of what to expect," Clarke said.
"I'm sure we'll go in as favourites because we have home advantage. The crowd at Hampden can be a big plus for us, I'm sure the stadium will be full and it's up to us to perform.
"The most important thing is we are a host nation and don't want to be standing on the sidelines watching someone else enjoying themselves in Glasgow."
How did their qualifying group go?
Off the back of losing out to Scotland in their Nations League group, Israel started with a draw with Slovenia and wins over Austria and Latvia. However, things quickly fell apart after that. In their next seven qualifiers, Andi Herzog's side won just one - a 3-1 home win over bottom-placed Latvia - and lost five.
Despite starting off in pot three side, Israel finished fifth behind Poland, Austria, North Macedonia and Slovenia - winning just one win from eight games against the four sides. There hasn't been a huge amount of evidence to suggest they've improved at all since losing 3-2 at Hampden a year ago.
Key player - Eran Zahavi
Guangzhou striker Eran Zahavi was a key player for this faltering Israeli side, scoring 11 goals in 10 qualifying games. The 32-year-old netted four of those against Austria, two against Slovenia and one against North Macedonia. He also claimed a goal and an assist at Hampden in the last meeting with Scotland.


Let random variables $X$ and $Y$ have the joint density defined by $$ f(x, y) ~ = ~ \begin{cases} 30(y-x)^4, ~~~ 0 < x < y < 1 \\ 0 ~~~~~~~~ \text{otherwise} \end{cases} $$
def jt_dens(x,y):
if y < x:
return 0
else:
return 30 * (y-x)**4
Plot_3d(x_limits=(0,1), y_limits=(0,1), f=jt_dens, cstride=4, rstride=4)
Then the possible values of $(X, Y)$ are in the upper right hand triangle of the unit square, as in the previous example.
Here is a quick check that the function given is indeed a joint density.
declare('x', interval=(0, 1))
declare('y', interval=(0, 1))
joint_density = 30*(y-x)**4
Integral(joint_density, (y, x, 1), (x, 0, 1)).doit()
We can use the joint density $f$ to find the density of $X$. Call this density $f_X$. We know that
\begin{align*} f_X(x)dx &\sim P(X \in dx) \\ &= \int_y P(X \in dx, Y \in dy) \\ &= \int_y f(x, y)dxdy \\ &= \big{(} \int_y f(x, y)dy \big{)}dx \end{align*}You can see the reasoning behind this calculation in the graph below. The blue strip shows the event $\{ X \in dx \}$ for a value of $x$ very near 0.25. To find the volume $P(X \in dx)$, we hold $x$ fixed and add over all $y$.
So the density of $X$ is given by $$ f_X(x) ~ = ~ \int_y f(x, y)dy ~~~~~ \text{for all } x $$
By analogy with the discrete case, $f_X$ is sometimes called the marginal density of $X$.
In our example, the possible values of $(X, Y)$ are the upper left hand triangle as shown above. So for each fixed $x$, the possible values of $Y$ go from $x$ to 1.
Therefore for $0 < x < 1$, the density of $X$ is given by
\begin{align*} f_X(x) &= \int_{y=x}^1 30(y-x)^4 dy \\ &= 30 \cdot \frac{1}{5} (y-x)^5 \Big{\rvert}_x^1 \\ &= 6(1-x)^5 \end{align*}Here is the joint density surface again. You can see that $X$ is much more likely to be near 0 than near 1.
Plot_3d(x_limits=(0,1), y_limits=(0,1), f=jt_dens, cstride=4, rstride=4)
That can be seen in the shape of the density of $X$.
Correspondingly, the density of $Y$ can be found by fixing $y$ and integrating over $x$ as follows:
$$ f_Y(y) = \int_x f(x, y)dx ~~~~ \text{for all } y $$In our example, the joint density surface indicates that $Y$ is more likely to be near 1 than near 0, which is confirmed by calculation. Remember that $y > x$ and therefore for each fixed $y$, the possible values of $x$ are 0 through $y$.
For $0 < y < 1$, $$ f_Y(y) ~ = ~ \int_0^y 30(y-x)^4dx ~ = ~ 6y^5 $$
Consider the conditional probability $P(Y \in dy \mid X \in dx)$.  For a fixed value $x$, the conditional density of $Y$ given $X=x$ is defined by
$$ f_{Y\mid X=x} (y) ~ = ~ \frac{f(x, y)}{f_X(x)} ~~~~ \text{for all } y $$Since $X$ has a density, we know that $P(X = x) = 0$ for all $x$. But the ratio above is of densities, not probabilities. It might help your intuition to think of "given $X=x$" to mean "given that $X$ is just around $x$".
Visually, the shape of this conditional density is the vertical cross section at $x$ of the joint density graph above. The numerator determines the shape, and the denominator is part of the constant that makes the density integrate to 1.
Note that $x$ is constant in this formula; it is the given value of $X$. So the denominator $f_X(x)$ is the same for all the possible values of $y$.
To see that the conditional density does integrate to 1, let's do the integral.
$$ \int_y f_{Y\mid X=x} (y)dy ~ = ~ \int_y \frac{f(x, y)}{f_X(x)} dy ~ = ~ \frac{1}{f_X(x)} \int_y f(x, y)dy ~ = ~ \frac{1}{f_X(x)} f_X(x) ~ = ~ 1 $$In our example, let $x = 0.2$ and consider finding the conditional density of $Y$ given $X = 0.4$. Under that condition, the possible values of $Y$ are in the range 0.4 to 1, and therefore
$$ f_{Y \mid X=0.4} (y) ~ = ~ \frac{30(y - 0.4)^4}{6(1 - 0.4)^5} ~ = ~ \frac{5}{0.6^5} (y - 0.4)^4 ~~~~ y \in (0.4, 1) $$This is a density on $(0.4, 1)$:
declare('y', interval=(0.4, 1))
cond_density = (5/(0.6**5)) * (y - 0.4)**4
Integral(cond_density, (y, 0.4, 1)).doit()
The figure below shows the overlaid graphs of the density of $Y$ and the conditional density of $Y$ given $X = 0.4$. You can see that the conditional density is more concentrated on large values of $Y$, because under the condition $X = 0.4$ you know that $Y$ can't be small.
We can use conditional densities to find probabilities and expectations, just as we would use an ordinary density. Here are some examples of calculations. In each case we will set up the integrals and then use SymPy
.
The answer is about 60%.
declare('y', interval=(0, 1))
cond_density = (5/(0.6**5))*(y - 0.4)**4
Integral(cond_density, (y, 0.9, 1)).doit()
Now we will use the conditional density to find a conditional expectation. Remember that in our example, given that $X = 0.4$ the possible values of $Y$ go from $0.4$ to 1.
$$ E(Y \mid X = 0.4) ~ = ~ \int_{0.4}^1 y \frac{5}{0.6^5} (y - 0.4)^4 dy ~ = ~ 0.9 $$Integral(y*cond_density, (y, 0.4, 1)).doit()
For any fixed value of $y$, the conditional density of $X$ given $Y = y$ is
$$ f_{X \mid Y=y} (x) ~ = ~ \frac{f(x, y)}{f_Y(y)} ~~~~~ \text{for all } x $$All the examples in this section and the previous one have started with a joint density function that apparently emerged out of nowhere. In the next section, we will study a context in which they arise.


Remote Controlled Kart with Object Bypass System
As the final project of my Mechatronics class, I built a remote controlled kart using 3D printing and Arduino AtMega 2560. The chassis is totally designed by myself using SolidWorks. I 3D printed it and assembled all the parts. The kart is powered by two DC motors. The steering is controlled by a servo motor. I implemented the IR Remote library in Arduino to allow the kart to be controlled by a remote. A supersonic sensor was used to detect objects in front of the kart. Then, system will implement algorithms to bypass the object by calculating the distance and speed of the kart.


Understand JavaScript Callback Functions and Use Them
September 04, 2015(Learn JavaScript Higher-order Functions, aka Callback Functions)by Richard Bovell
In JavaScript, functions are first-class objects; that is, functions are of the type Object and they can be used in a first-class manner like any other object (String, Array, Number, etc.) since they are in fact objects themselves. They can be “stored in variables, passed as arguments to functions, created within functions, and returned from functions”
Because functions are first-class objects, we can pass a function as an argument in another function and later execute that passed-in function or even return it to be executed later. This is the essence of using callback functions in JavaScript.
In the rest of this article we will learn everything about JavaScript callback functions. Callback functions are probably the most widely used functional programming technique in JavaScript, and you can find them in just about every piece of JavaScript and jQuery code, yet they remain mysterious to many JavaScript developers. The mystery will be no more, by the time you finish reading this article.
Callback functions are derived from a programming paradigm known as functional programming. At a fundamental level, functional programming specifies the use of functions as arguments. Functional programming was—and still is, though to a much lesser extent today—seen as an esoteric technique of specially trained, master programmers.
Fortunately, the techniques of functional programming have been elucidated so that mere mortals like you and me can understand and use them with ease. One of the chief techniques in functional programming happens to be callback functions. As you will read shortly, implementing callback functions is as easy as passing regular variables as arguments. This technique is so simple that I wonder why it is mostly covered in advanced JavaScript topics.
What is a Callback or Higher-order Function?
A callback function, also known as a higher-order function, is a function that is passed to another function (let’s call this other function “otherFunction”) as a parameter, and the callback function is called (or executed) inside the otherFunction. A callback function is essentially a pattern (an established solution to a common problem), and therefore, the use of a callback function is also known as a callback pattern.
Consider this common use of a callback function in jQuery:
//Note that the item in the click method's parameter is a function, not a variable.
//The item is a callback function
$("#btn_1").click(function() {
alert("Btn 1 Clicked");
});
As you see in the preceding example, we pass a function as a parameter to the click method. And the click method will call (or execute) the callback function we passed to it. This example illustrates a typical use of callback functions in JavaScript, and one widely used in jQuery.
Ruminate on this other classic example of callback functions in basic JavaScript:
var friends = ["Mike", "Stacy", "Andy", "Rick"];
friends.forEach(function (eachName, index){
console.log(index + 1 + ". " + eachName); // 1. Mike, 2. Stacy, 3. Andy, 4. Rick
});
Again, note the way we pass an anonymous function (a function without a name) to the forEach method as a parameter.
So far we have passed anonymous functions as a parameter to other functions or methods. Lets now understand how callbacks work before we look at more concrete examples and start making our own callback functions. ###How Callback Functions Work? We can pass functions around like variables and return them in functions and use them in other functions.
When we pass a callback function as an argument to another function, we are only passing the function definition. We are not executing the function in the parameter. In other words, we aren’t passing the function with the trailing pair of executing parenthesis () like we do when we are executing a function.
And since the containing function has the callback function in its parameter as a function definition, it can execute the callback anytime.
Note that the callback function is not executed immediately. It is “called back” (hence the name) at some specified point inside the containing function’s body. So, even though the first jQuery example looked like this:
//The anonymous function is not being executed there in the parameter.
//The item is a callback function
$("#btn_1").click(function() {
alert("Btn 1 Clicked");
});
the anonymous function will be called later inside the function body. Even without a name, it can still be accessed later via the arguments object by the containing function.
Callback Functions Are Closures When we pass a callback function as an argument to another function, the callback is executed at some point inside the containing function’s body just as if the callback were defined in the containing function. This means the callback is a closure. Read my post, Understand JavaScript Closures With Ease for more on closures. As we know, closures have access to the containing function’s scope, so the callback function can access the containing functions’ variables, and even the variables from the global scope.
Basic Principles when Implementing Callback Functions
While uncomplicated, callback functions have a few noteworthy principles we should be familiar with when implementing them.
Use Named OR Anonymous Functions as Callbacks In the earlier jQuery and forEach examples, we used anonymous functions that were defined in the parameter of the containing function. That is one of the common patterns for using callback functions. Another popular pattern is to declare a named function and pass the name of that function to the parameter. Consider this:
// global variable
var allUserData = [];
// generic logStuff function that prints to console
function logStuff (userData) {
if ( typeof userData === "string")
{
console.log(userData);
}
else if ( typeof userData === "object")
{
for (var item in userData) {
console.log(item + ": " + userData[item]);
}
}
}
// A function that takes two parameters, the last one a callback function
function getInput (options, callback) {
allUserData.push (options);
callback (options);
}
// When we call the getInput function, we pass logStuff as a parameter.
// So logStuff will be the function that will called back (or executed) inside the getInput function
getInput ({name:"Rich", speciality:"JavaScript"}, logStuff);
// name: Rich
// speciality: JavaScript
Pass Parameters to Callback Functions Since the callback function is just a normal function when it is executed, we can pass parameters to it. We can pass any of the containing function’s properties (or global properties) as parameters to the callback function. In the preceding example, we pass options as a parameter to the callback function. Let’s pass a global variable and a local variable:
//Global variable
var generalLastName = "Clinton";
function getInput (options, callback) {
allUserData.push (options);
// Pass the global variable generalLastName to the callback function
callback (generalLastName, options);
}
Make Sure Callback is a Function Before Executing It It is always wise to check that the callback function passed in the parameter is indeed a function before calling it. Also, it is good practice to make the callback function optional.
Let’s refactor the getInput function from the previous example to ensure these checks are in place.
function getInput(options, callback) {
allUserData.push(options);
// Make sure the callback is a function
if (typeof callback === "function") {
// Call it, since we have confirmed it is callable
callback(options);
}
}
Without the check in place, if the getInput function is called either without the callback function as a parameter or in place of a function a non-function is passed, our code will result in a runtime error.
Problem When Using Methods With The this Object as Callbacks When the callback function is a method that uses the this object, we have to modify how we execute the callback function to preserve the this object context. Or else the this object will either point to the global window object (in the browser), if callback was passed to a global function. Or it will point to the object of the containing method. Let’s explore this in code:
// Define an object with some properties and a method
// We will later pass the method as a callback function to another function
var clientData = {
id: 094545,
fullName: "Not Set",
// setUserName is a method on the clientData object
setUserName: function (firstName, lastName) {
// this refers to the fullName property in this object
this.fullName = firstName + " " + lastName;
}
}
function getUserInput(firstName, lastName, callback) {
// Do other stuff to validate firstName/lastName here
// Now save the names
callback (firstName, lastName);
}
In the following code example, when clientData.setUserName is executed, this.fullName will not set the fullName property on the clientData object. Instead, it will set fullName on the window object, since getUserInput is a global function. This happens because the this object in the global function points to the window object.
getUserInput ("Barack", "Obama", clientData.setUserName);
console.log (clientData.fullName);// Not Set
// The fullName property was initialized on the window object
console.log (window.fullName); // Barack Obama
Use the Call or Apply Function To Preserve this We can fix the preceding problem by using the Call or Apply function (we will discuss these in a full blog post later). For now, know that every function in JavaScript has two methods: Call and Apply. And these methods are used to set the this object inside the function and to pass arguments to the functions.
Call takes the value to be used as the this object inside the function as the first parameter, and the remaining arguments to be passed to the function are passed individually (separated by commas of course). The Apply function’s first parameter is also the value to be used as the this object inside the function, while the last parameter is an array of values (or the arguments object) to pass to the function.
This sounds complex, but lets see how easy it is to use Apply or Call. To fix the problem in the previous example, we will use the Apply function thus:
//Note that we have added an extra parameter for the callback object, called "callbackObj"
function getUserInput(firstName, lastName, callback, callbackObj) {
// Do other stuff to validate name here
// The use of the Apply function below will set the this object to be callbackObj
callback.apply (callbackObj, [firstName, lastName]);
}
With the Apply function setting the this object correctly, we can now correctly execute the callback and have it set the fullName property correctly on the clientData object:
// We pass the clientData.setUserName method and the clientData object as parameters. The clientData object will be used by the Apply function to set the this object
getUserInput ("Barack", "Obama", clientData.setUserName, clientData);
// the fullName property on the clientData was correctly set
console.log (clientData.fullName); // Barack Obama
We would have also used the Call function, but in this case we used the Apply function.
Multiple Callback Functions Allowed We can pass more than one callback functions into the parameter of a function, just like we can pass more than one variable. Here is a classic example with jQuery’s AJAX function:
function successCallback() {
// Do stuff before send
}
function successCallback() {
// Do stuff if success message received
}
function completeCallback() {
// Do stuff upon completion
}
function errorCallback() {
// Do stuff if error received
}
$.ajax({
url:"http://fiddle.jshell.net/favicon.png",
success:successCallback,
complete:completeCallback,
error:errorCallback
});
“Callback Hell” Problem And Solution
In asynchronous code execution, which is simply execution of code in any order, sometimes it is common to have numerous levels of callback functions to the extent that you have code that looks like the following. The messy code below is called callback hell because of the difficulty of following the code due to the many callbacks. I took this example from the node-mongodb-native, a MongoDB driver for Node.js. [2]. The example code below is just for demonstration:
var p_client = new Db('integration_tests_20', new Server("<IP_ADDRESS>", 27017, {}), {'pk':CustomPKFactory});
p_client.open(function(err, p_client) {
p_client.dropDatabase(function(err, done) {
p_client.createCollection('test_custom_key', function(err, collection) {
collection.insert({'a':1}, function(err, docs) {
collection.find({'_id':new ObjectID("aaaaaaaaaaaa")}, function(err, cursor) {
cursor.toArray(function(err, items) {
test.assertEquals(1, items.length);
// Let's close the db
p_client.close();
});
});
});
});
});
});
You are not likely to encounter this problem often in your code, but when you do—and you will from time to time—here are two solutions to this problem. [3]
Name your functions and declare them and pass just the name of the function as the callback, instead of defining an anonymous function in the parameter of the main function. Modularity: Separate your code into modules, so you can export a section of code that does a particular job. Then you can import that module into your larger application. ###Make Your Own Callback Functions Now that you completely (I think you do; if not it is a quick reread :)) understand everything about JavaScript callback functions and you have seen that using callback functions are rather simple yet powerful, you should look at your own code for opportunities to use callback functions, for they will allow you to:
- Do not repeat code (DRY—Do Not Repeat Yourself)
- Implement better abstraction where you can have more generic functions that are versatile (can handle all sorts of functionalities)
- Have better maintainability
- Have more readable code
- Have more specialized functions.
It is rather easy to make your own callback functions. In the following example, I could have created one function to do all the work: retrieve the user data, create a generic poem with the data, and greet the user. This would have been a messy function with much if/else statements and, even still, it would have been very limited and incapable of carrying out other functionalities the application might need with the user data.
Instead, I left the implementation for added functionality up to the callback functions, so that the main function that retrieves the user data can perform virtually any task with the user data by simply passing the user’s full name and gender as parameters to the callback function and then executing the callback function.
In short, the getUserInput function is versatile: it can execute all sorts of callback functions with myriad of functionalities.
// First, setup the generic poem creator function; it will be the callback function in the getUserInput function below.
function genericPoemMaker(name, gender) {
console.log(name + " is finer than fine wine.");
console.log("Altruistic and noble for the modern time.");
console.log("Always admirably adorned with the latest style.");
console.log("A " + gender + " of unfortunate tragedies who still manages a perpetual smile");
}
//The callback, which is the last item in the parameter, will be our genericPoemMaker function we defined above.
function getUserInput(firstName, lastName, gender, callback) {
var fullName = firstName + " " + lastName;
// Make sure the callback is a function
if (typeof callback === "function") {
// Execute the callback function and pass the parameters to it
callback(fullName, gender);
}
}
Call the getUserInput function and pass the genericPoemMaker function as a callback:
getUserInput("Michael", "Fassbender", "Man", genericPoemMaker);
// Output
/* Michael Fassbender is finer than fine wine.
Altruistic and noble for the modern time.
Always admirably adorned with the latest style.
A Man of unfortunate tragedies who still manages a perpetual smile.
*/
Because the getUserInput function is only handling the retrieving of data, we can pass any callback to it. For example, we can pass a greetUser function like this:
function greetUser(customerName, sex) {
var salutation = sex && sex === "Man" ? "Mr." : "Ms.";
console.log("Hello, " + salutation + " " + customerName);
}
// Pass the greetUser function as a callback to getUserInput
getUserInput("Bill", "Gates", "Man", greetUser);
// And this is the output
Hello, Mr. Bill Gates
We called the same getUserInput function as we did before, but this time it performed a completely different task.
As you see, callback functions afford much versatility. And even though the preceding example is relatively simple, imagine how much work you can save yourself and how well abstracted your code will be if you start using callback functions. Go for it. Do it in the monings; do it in the evenings; do it when you are down; do it when you are k
Note the following ways we frequently use callback functions in JavaScript, especially in modern web application development, in libraries, and in frameworks:
- For asynchronous execution (such as reading files, and making HTTP requests)
- In Event Listeners/Handlers
- In setTimeout and setInterval methods
- For Generalization: code conciseness
Final Words
JavaScript callback functions are wonderful and powerful to use and they provide great benefits to your web applications and code. You should use them when the need arises; look for ways to refactor your code for Abstraction, Maintainability, and Readability with callback functions.
See you next time, and remember to keep coming back because JavaScriptIsSexy.com has much to teach you and you have much to learn.


This function is simply a wrapper to
KWDual
with a similar interface to
mixsqp
for solving the same problem as mixsqp
. See
mixsqp
and KWDual
for details.
mixkwdual(L, w = rep(1, nrow(L)), ...)
Arguments
| L |
Matrix specifying the optimization problem to be solved.
In the context of mixture-model fitting, L[j,k] should be
the value of the kth mixture component density at the jth data
point. L should be a numeric matrix with at least two
columns, with all entries being non-negative and finite (and not
missing). For large matrices, it is preferrable that the matrix is
stored in double-precision; see storage.mode . |
| w |
An optional numeric vector, with one entry for each row of
L , specifying the "weights" associated with the rows of
L . All weights must be finite, non-negative and not
missing. Internally, the weights are normalized to sum to 1,
which does not change the problem, but does change the value of the
objective function reported. By default, all weights are equal. |
| ... |
Additional arguments passed to KWDual . |
Value
A list object with the following elements:
xThe estimated solution to the convex optimization problem.
valueThe value of the objective function at x
.
statusThe return status from MOSEK.
For more information on this output, see
KWDual and
mosek.
See also
mixsqp
, KWDual