Satellite Image from Google Earth
Maybe, Macey Brandeberry wonders, her mother’s downward spiral could have begun where many find their solutions: a doctor’s appointment.
All the vitriolic words exchanged, the violent arguments, the years-long turmoil between one family member in crisis and the rest who sought to help her — those moments had to start somewhere.
“It was just hard. It was really sometimes very unhappy just to be home,” Brandeberry, a second-year medical student on Ohio University’s Dublin campus, said.
One question, of course, can churn a maelstrom of “maybe.” No problem has an easy beginning, nor an easy end.
That’s what Brandeberry explained to first-year medical students via video chat during OU’s Heritage College of Osteopathic Medicine Health Policy Day in February. The theme was “healing Ohio’s opioid crisis,” and she was trying to serve as a relatable face to an immeasurable epidemic.
Her relatability was two-pronged: here was a student, grappling with the complexities of knowing whether to prescribe or not prescribe sometimes helpful medication to a patient who says he or she is in pain, in addition to her mother’s own addiction to opioid painkillers.
Abby Day
The latter wasn’t something she was particularly used to talking about.
Bringing it up, she originally thought, might garner unwanted sympathy or attention, or imply that her successes were a product of her mother’s addiction. Brandeberry, who earned her undergraduate degree in biology from the University of Findlay after growing up in Fostoria, said her career in medicine has been a way to accomplish something with her life and to have an impact on others.
Maybe talking about her mother’s addiction could make a difference.
Maybe there were hundreds of thousands of people like Brandeberry out there: the sons and daughters of addicts, who deserved an answer.
It only took a month on the job for Travis Boggs to come across a toddler intertwined in a parent’s drug abuse and neglect.
That was in 2008. The alternative response caseworker with Athens County Children Services said that was his first glance at the severity of the opioid epidemic. A deputy with the sheriff’s office stopped counting after more than 30 needles were discovered in the home. There were small amounts of heroin on the tables and countertops, and several knives were on the floor within the child’s reach.
As a result of the ever-rising prevalence of addiction and overdose deaths, children have quickly become the invisible victims of the opioid epidemic, Catherine Hill, executive director of Athens County Children Services, said.
If that population isn’t considered for the resources it needs now, the federal and state government will be faced with a generation devastated by an addiction crisis that wasn’t their own.
And where there’s addiction, there’s often underlying trauma, Ron Luce said.
Some people just don’t have hope, Luce, the executive director of the John W. Clem Recovery House in Athens County, said. Society lacks a sense of faith in the American Dream. People feel disposable.
Some of that is a result of trauma, and often, it breeds more. Without resources to address that trauma, we’ll be in “absolute crisis,” Luce said.
Luce first saw the intersection of opioid addiction and trauma through his role as a guardian ad litem for the Athens County Juvenile Court about five years ago, when he met children whose toys were sold for drug money or families that experienced generational addiction, poverty or sexual abuse.
He encountered the impact of trauma again when he became the executive director of the Clem House, where he and others provide help for men suffering from addiction in a residential setting.
Men came into his office, he said, and shared secrets they had held in for years.  Others had grown up in poverty or with family members who also suffered from addiction.
“I don’t think that people recognize that for many people who are addicted, it’s not just the drugs or alcohol,” Luce said, sitting within the blue walls of his office at the Clem House. “They are burying a world of pain and horror that exists in their past, and then there’s the shame and guilt.”
He has seen the effects of something called the Adverse Childhood Experiences Study carried out in real-time.
The ACE study assigns its users a score, based on the level of trauma they may have experienced — whether through abuse, neglect or household dysfunction — to determine what their future health determinants might be. One of those risks includes addiction to drugs or alcohol. Children who are assessed by mental health professionals are often evaluated for such experiences to determine the level of care they may need.
“Certainly, addiction of a parent for any substance is really traumatic for any children who are in a home,” Hill said.
Now, children have higher needs than they used to, she said. Trauma can have a terrific impact on their lives, and they often have psychiatric or behavioral needs that need to be attended to.
There are factors that build resilience despite such experiences, though, such as love and encouragement from caregivers and family members, or access to education and financial help. Resources being available such as trauma-competent mental health services, campaigns that generate awareness and support for additional resources can help as well.
“A lot of these children and parents we work with, just knowing them and knowing what’s on their ACE score, you can almost see what can happen if treatment isn’t implemented right away,” Boggs said.
In 2015, approximately 33,000 Americans died from overdose deaths related to prescription or illicit opioid drugs, and it’s estimated that millions more are suffering from substance abuse disorders relating to drugs.
Unquestionably, such addiction has contributed to the 11 percent increase of children in state custody within the past six years, Angela Sausser, executive director of the Public Children Services Association of Ohio, said. Athens County has seen a 23 percent increase of children in state custody.
Such children are not just entering foster care at higher rates — Athens County had 97 children in custody as of April 10, up from an average of 70 children in 2012 — they’re entering at a younger age than was once typical and they’re staying in foster care longer.
“I think we’re going to have bigger problems down the line ... You either pay now or you pay later.”
— Catherine Hill said of the level of funding for children services.
Too many children in Ohio just aren’t able to safely return home to their natural parents, Hill said, and end up being cared for by family members. In other cases, the agency is awarded custody so a child can be placed with an adoptive family.
A survey from the Public Children Services Association of Ohio found that in 2015, nearly half of children taken into state custody had parents who were using drugs.
Such cases are necessitating higher costs for county agencies; Athens has experienced a 35 percent increase in costs since 2010.
Meanwhile, state funding to counties for children services agencies has dropped by 21 percent since 2008, despite an increase of children in custody. Nationally, Ohio is ranked last for the state’s share of funding for children services agencies.
That’s why Ohio Attorney General Mike DeWine’s office awarded a $3.5 million grant to the association to be divided among 14 agencies in southern Ohio for a pilot program, which includes Athens.
The program will provide more resources for children services agencies to form care teams that will establish collaborative support for addicted parents and their children, modeled off a similar program in Kentucky.
If successful, DeWine said the program will be considered for statewide implementation.
"The idea would be to try to help the parents with their addiction problem, help their children recover from the trauma of living in a house where there’s a drug-abusing parent, with the ultimate goal of getting the kid reunited with their parents at an earlier stage,” DeWine said.
But those are the resources that are being allocated now. Those programs might have existed while Brandeberry — who was primarily cared for by her father — was growing up, but they were not well-advertised.
She hasn’t spoken with her mother outside of a few texts and Facebook messages in the past few years. She has often considered whether her mother’s addiction was a product of a previous traumatic experience or mental illness, too.
“I think we’re going to have bigger problems down the line,” Hill said of the level of funding for children services. “You either pay now or you pay later.”
Sue Meeks said the children and mothers affected by the opioid epidemic started as a slow trickle into her Family Navigator Program a few years ago, housed within HCOM. Then it became a flood.
Met with grandparents who were the primary caregivers for some of her youngest clients, she often asked “Where’s Mom?” Their mothers, she was told, were increasingly addicted to drugs or in jail as a result.
The next steps she and her fellow nurse navigators took were not only about empathy and understanding a mother’s addiction, but also the underlying causes for why she may have turned to drugs.
“Once people can understand that, there can be a bit more compassion,” Meeks said. “It doesn’t mean we support addiction, it means we understand how you may have gotten there.”
It took a small, collaborative army to develop a novel approach that would involve high-risk mothers in non-judgmental, wraparound care. That team — communicating across a variety of resources outside of the Family Navigator Program — pressed its thumb to the pulse of southeast Ohio’s epidemic of opioid addiction, and hasn’t taken it off since.
In Parks Hall, Stacy Lee and Kristin Kerwin, registered nurse navigators who work with the Pathways to a Healthy Pregnancy program, show how that pulse continues to beat with pressing, unmet needs. More than half of their clientele has suffered from opioid addiction, Lee said, though they assist women who are not drug-addicted as well.
The Pathways initiative is run through the Family Navigators team, and it’s where Lee, Kerwin and Meeks connect a web of resources with Medicaid-eligible, at-risk pregnant women. The aim is to ensure that they receive the care necessary to deliver and raise a healthy baby, minimizing that child’s risks for trauma or being born addicted to opioid drugs, also known as neonatal abstinence syndrome.
The nurse navigators link pregnant women to services such as medication-assisted treatment if they are suffering from addiction. Lee and Kerwin also follow the women to many of their medical appointments and visit them after their baby is born, all while addressing the social determinants of health that clients might be facing.
During a client’s intake, Kerwin said, they will also complete an Adverse Childhood Experiences survey.
The registered nurses have grown frustrated together, cried together and celebrated the smallest of victories together, Meeks said.
The program’s nurse navigators manage the caseload, while Health Recovery Services provides counseling and OhioHealth O’Bleness Athens Medical Associates assists with obstetric care and medication-assisted treatment.
Because of the Maternal Opiate Medical Support (MOMS) pilot project in Ohio — primarily initiated to prevent further diagnoses of neonatal abstinence syndrome — Athens was one of four locations to receive grant funding to create the collaborative team. But the care model in Athens was mostly in place beforehand, Dr. Jody Gerome, who practices obstetrics and gynecology at AMA, said. The grant just helped to solidify existing relationships.
With more than 100 babies hospitalized for NAS in Athens County from 2011 to 2015, county officials couldn’t sit on their hands and wait, Gerome said. And though the MOMS grant has since expired, the team has continued its work. About 12 percent of the 500 babies delivered at AMA each year are born to opioid-addicted mothers, Gerome added.
From January 2015 to January 2017, Lee said, the Pathways program helped more than 100 clients. It’s just one method of improving the life of a parent and child, but it’s been one that Meeks’ team has found successful.
Meeks, too, has learned that if there’s any route to pull a child out of a path toward an unhealthy lifestyle, it’s in trauma-informed care.
“We’re treating the addiction, we’re doing all the other things to treat the outcome of that, but we’re still doing a really poor job of adequately treating childhood trauma,” Meeks said of the resources available locally.
Normal can be defined a little differently for everyone, Allana Cottrill, a 26-year-old from Chauncey and a mother of three young children, said.
Growing up, it seemed normal for her father to be sticking needles into his arm, or for pills to be lying around the house.
Cottrill stressed that her childhood was happy. She was never totally conscious of her father’s opioid addiction until he died from an overdose death when she was 10 years old. But her children will know their grandfather died of a drug overdose.
“Tell kids what they need to look for,” Cottrill said. “I had no idea that it was not normal for my dad to have all these pills and stuff, or to be giving himself shots — which is what it looked like — that’s just how we live our lives.”
That subjective definition of normalcy is key in trauma-informed care. Many do not recognize that it’s a luxury to feel safe in your own home, Dr. Joseph Bianco, an assistant professor of social and behavioral medicine in HCOM, said.
Working in the residency clinic, he said he would sometimes see clients who, during their intake process, would not report trauma even if they had been physically abused or had been part of the foster care system.
“The reason that they’re not making the connection is not because they’re not under-reporting, it’s because that’s the only normal that they knew,” Bianco, who has researched behavioral health interventions in primary care and the effects of childhood trauma on adult health, said.
So, faced with a generation afflicted with trauma as a result of the opioid epidemic, Sausser said it’s critical that the state allocates funding to address it. That’s why the grant for children services agencies from the Attorney General’s office is so important, she said.
That’s also why collaborative models like Meeks’ tend to work better than those that operate in a bubble.
Meanwhile, Brandeberry is preparing for a field in which she’ll often encounter people who have faced traumas of their own: emergency medicine. Though she was hesitant to tell her story to a room of first-year medical students, she’s glad she did.
If a pediatrician or any other physician takes the time to delve deeper into their patients’ home lives, the impact on children could be tremendous. Not only may children feel less alone, she said, they also might be connected with counseling or legal authorities if they feel unsafe.
“To go home and relax in your own house is something people take for granted,” Brandeberry said. “It’s just sad how many people are suffering.”


Returns an object reference to the window object.
objRef = window.self
if (window.parent.frames[0] != window.self) { // this window is not the first frame in the list }
window.self is almost always used in comparisons like in the example above, which finds out if the current window is the first subframe in the parent frameset.
DOM Level 0. Not part of specification.
© 2013 Mozilla Contributors
Licensed under the Creative Commons Attribution-ShareAlike License v2.5 or later.
https://developer.mozilla.org/en-US/docs/Web/API/window.self


| Super Mario Bros. 3 |
| The Legend of Zelda |
| Mega Man 2 |
| Metroid |
| Super Mario Bros. 2 |
| Mike Tyson’s Punch-Out!! |
| Final Fantasy |
| Castlevania III: Dracula’s Curse |
| Dragon Quest III |
| Tetris |
| Mother |
| Super Mario Bros. |
| Excitebike |
| Kirby’s Adventure |
| Final Fantasy II |
| Castlevania |
| Crystalis |
| Bubble Bobble |
| Zelda II: The Adventure of Link |
| R.C. Pro-Am |
| Rygar |
| Lode Runner |
| Faxanadu |
| Double Dragon II: The Revenge |
| R.B.I. Baseball |
| Maniac Mansion |
| Jackal |
| River City Ransom |
| Contra |
| Ghosts ‘N Goblins |
| Ninja Gaiden |
| Dragon Warrior |
| Blaster Master |
| Gradius |
| Little Nemo: The Dream Master |
| StarTropics |
| Mega Man |
| DuckTales |
| Tecmo Super Bowl |
| Batman: The Video Game |
| Adventure Island II |
| A Boy and His Blob: Trouble on Blobolonia |
| Vice: Project Doom |
| Duck Hunt |
| Kid Icarus |
| Ninja Gaiden II: The Dark Sword Of Chaos |
| Kung Fu |
| Life Force |
| Metal Gear |
| Castlevania II: Simon’s Quest |


You can use colors theme and icons in button. If you need use base mode just add theme color name,
you can alter border color using class border-[COLOR]
, alter text color using class text-[COLOR]
and add radius border using class radius
.
For use icon in button you need add class icon-text
and you can use diferent size, see the examples below.
To use this component you need install with the command:
base
.
The dependencies will be installed together with this module
mobileui install button
You can use all features the base MobileUI in this component.
Another type button used in Android is a Tap, for this you can put circle
class in button. You can controller what position button.


OpCode
public enum OpCode
Enumerates the opcodes of instructions available in the LLVM IR language.
-
The opcode for the
ret
instruction.Declaration
Swift
case ret
-
The opcode for the
br
instruction.Declaration
Swift
case br
-
The opcode for the
switch
instruction.Declaration
Swift
case `switch`
-
The opcode for the
indirectBr
instruction.Declaration
Swift
case indirectBr
-
The opcode for the
invoke
instruction.Declaration
Swift
case invoke
-
The opcode for the
unreachable
instruction.Declaration
Swift
case unreachable
-
The opcode for the
add
instruction.Declaration
Swift
case add
-
The opcode for the
fadd
instruction.Declaration
Swift
case fadd
-
The opcode for the
sub
instruction.Declaration
Swift
case sub
-
The opcode for the
fsub
instruction.Declaration
Swift
case fsub
-
The opcode for the
mul
instruction.Declaration
Swift
case mul
-
The opcode for the
fmul
instruction.Declaration
Swift
case fmul
-
The opcode for the
udiv
instruction.Declaration
Swift
case udiv
-
The opcode for the
sdiv
instruction.Declaration
Swift
case sdiv
-
The opcode for the
fdiv
instruction.Declaration
Swift
case fdiv
-
The opcode for the
urem
instruction.Declaration
Swift
case urem
-
The opcode for the
srem
instruction.Declaration
Swift
case srem
-
The opcode for the
frem
instruction.Declaration
Swift
case frem
-
The opcode for the
shl
instruction.Declaration
Swift
case shl
-
The opcode for the
lshr
instruction.Declaration
Swift
case lshr
-
The opcode for the
ashr
instruction.Declaration
Swift
case ashr
-
The opcode for the
and
instruction.Declaration
Swift
case and
-
The opcode for the
or
instruction.Declaration
Swift
case or
-
The opcode for the
xor
instruction.Declaration
Swift
case xor
-
The opcode for the
alloca
instruction.Declaration
Swift
case alloca
-
The opcode for the
load
instruction.Declaration
Swift
case load
-
The opcode for the
store
instruction.Declaration
Swift
case store
-
The opcode for the
getElementPtr
instruction.Declaration
Swift
case getElementPtr
-
The opcode for the
trunc
instruction.Declaration
Swift
case trunc
-
The opcode for the
zext
instruction.Declaration
Swift
case zext
-
The opcode for the
sext
instruction.Declaration
Swift
case sext
-
The opcode for the
fpToUI
instruction.Declaration
Swift
case fpToUI
-
The opcode for the
fpToSI
instruction.Declaration
Swift
case fpToSI
-
The opcode for the
uiToFP
instruction.Declaration
Swift
case uiToFP
-
The opcode for the
siToFP
instruction.Declaration
Swift
case siToFP
-
The opcode for the
fpTrunc
instruction.Declaration
Swift
case fpTrunc
-
The opcode for the
fpExt
instruction.Declaration
Swift
case fpExt
-
The opcode for the
ptrToInt
instruction.Declaration
Swift
case ptrToInt
-
The opcode for the
intToPtr
instruction.Declaration
Swift
case intToPtr
-
The opcode for the
bitCast
instruction.Declaration
Swift
case bitCast
-
The opcode for the
addrSpaceCast
instruction.Declaration
Swift
case addrSpaceCast
-
The opcode for the
icmp
instruction.Declaration
Swift
case icmp
-
The opcode for the
fcmp
instruction.Declaration
Swift
case fcmp
-
The opcode for the
PHI
instruction.Declaration
Swift
case phi
-
The opcode for the
call
instruction.Declaration
Swift
case call
-
The opcode for the
select
instruction.Declaration
Swift
case select
-
The opcode for the
userOp1
instruction.Declaration
Swift
case userOp1
-
The opcode for the
userOp2
instruction.Declaration
Swift
case userOp2
-
The opcode for the
vaArg
instruction.Declaration
Swift
case vaArg
-
The opcode for the
extractElement
instruction.Declaration
Swift
case extractElement
-
The opcode for the
insertElement
instruction.Declaration
Swift
case insertElement
-
The opcode for the
shuffleVector
instruction.Declaration
Swift
case shuffleVector
-
The opcode for the
extractValue
instruction.Declaration
Swift
case extractValue
-
The opcode for the
insertValue
instruction.Declaration
Swift
case insertValue
-
The opcode for the
fence
instruction.Declaration
Swift
case fence
-
The opcode for the
atomicCmpXchg
instruction.Declaration
Swift
case atomicCmpXchg
-
The opcode for the
atomicRMW
instruction.Declaration
Swift
case atomicRMW
-
The opcode for the
resume
instruction.Declaration
Swift
case resume
-
The opcode for the
landingPad
instruction.Declaration
Swift
case landingPad
-
The opcode for the
cleanupRet
instruction.Declaration
Swift
case cleanupRet
-
The opcode for the
catchRet
instruction.Declaration
Swift
case catchRet
-
The opcode for the
catchPad
instruction.Declaration
Swift
case catchPad
-
The opcode for the
cleanupPad
instruction.Declaration
Swift
case cleanupPad
-
The opcode for the
catchSwitch
instruction.Declaration
Swift
case catchSwitch


Random Data in the Future
area
bar
line
scatter
stack
stream
pct
value
cardinal
linear
step
Smoothing


That it's very much outside of the way I would normally carry a conversation. It's much more attention-driven, where it's not about just hearing a story, it's also about creating a full awareness of the meaning behind what you're hearing rather than having a knee-jerk response to what's being said. The other person was Reuben, if memory serves, he mentioned how looping was a nice practice to ensure that both parties get their thoughts across accurately and vividly.
I think i'll try to do a bit of everything. Having a buddy sounds great and I have a few candidates i'd like to proposition for practice. Regular training below your threshold, I think I already enjoy doing that. XD
Also, i'm already chill, so remembering to do just any amount of meditation will work out pretty well for me.
I liked the analogy concerning babies that are learning to walk. It's always nice to know when you're training in a skill that may not produce very apparent results immediately.


Twitter Streaming
Implemented Twitter Streaming using Apache Spark to collect tweets with hashtag #NowPlaying
Preprocessing: Remove noise from tweets
Preprocessed data to identify songs and artists being talked about in the tweets. Made some Groovy tweets.
iTunes Search API integration
Identify genres for artists and/or songs identified in the preprocessed tweets using iTunes Search API and Apple iTunes Enterprise Partner Feed (disk based caching of request responses to minimize network IO)
Tweets be tellin' us like..
The most popular genres in any given hour, the 10 most popular songs and artists in genres being talked about, etc.
Ivan Turgunev, 'Fathers and Sons', 1861
"The drawing shows me at one glance what might be spread over ten pages in a book."
We display the time-series of genres to which the music in tweets belongs to, in any given hour.


nomisr
is for accessing UK official statistics from the Nomis database through R. Nomis contains data from the Census, the Labour Force Survey, DWP benefit statistics and other economic and demographic data, and is maintained on behalf of the Office for National Statistics by the University of Durham.
The nomisr
package provides functions to find what data is available, the variables and query options for different datasets and a function for downloading data. nomisr
returns data in tibble
format. Most of the data available through nomisr
is based around statistical geographies, with a handful of exceptions.
The package is for demographers, economists, geographers, public health researchers and any other researchers who are interested in geographic factors. The package aims to aid reproducibility, reduce the need to manually download area profiles, and allow easy linking of different datasets covering the same geographic area.
nomisr
is available on CRAN:
You can install the development version nomisr
from github with:
nomisr
nomisr
contains functions to search for datasets, identify the query options for different datasets and retrieve data from queries, all done with tibbles
, to take advantage of how tibble
manages list-columns. The use of metadata queries, rather than simply downloading all available data, is useful to avoid overwhelming the rate limits of the API. For full details on all available functions and demonstrations of their use, please see the package vignette.
The example below gets the latest data on Jobseeker’s Allowance with rates and proportions, on a national level, with all male claimants and workforce.
library(nomisr)
jobseekers_search <- nomis_search(name = "*Jobseeker*")
tibble::glimpse(jobseekers_search)
#> Observations: 17
#> Variables: 14
#> $ agencyid <chr> "NOMIS", "NOMIS", "NOMIS"...
#> $ id <chr> "NM_1_1", "NM_4_1", "NM_8...
#> $ uri <chr> "Nm-1d1", "Nm-4d1", "Nm-8...
#> $ version <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1...
#> $ annotations.annotation <list> [<c("Current (being acti...
#> $ components.attribute <list> [<c("Mandatory", "Condit...
#> $ components.dimension <list> [<c("CL_1_1_GEOGRAPHY", ...
#> $ components.primarymeasure.conceptref <chr> "OBS_VALUE", "OBS_VALUE",...
#> $ components.timedimension.codelist <chr> "CL_1_1_TIME", "CL_4_1_TI...
#> $ components.timedimension.conceptref <chr> "TIME", "TIME", "TIME", "...
#> $ description.value <chr> "Records the number of pe...
#> $ description.lang <chr> "en", "en", NA, "en", "en...
#> $ name.value <chr> "Jobseeker's Allowance wi...
#> $ name.lang <chr> "en", "en", "en", "en", "...
jobseekers_measures <- nomis_get_metadata("NM_1_1", "measures")
tibble::glimpse(jobseekers_measures)
#> Observations: 4
#> Variables: 3
#> $ id <chr> "20100", "20201", "20202", "20203"
#> $ label.en <chr> "claimants", "workforce", "active", "residence"
#> $ description.en <chr> "claimants", "workforce", "active", "residence"
jobseekers_geography <- nomis_get_metadata("NM_1_1", "geography", "TYPE")
tail(jobseekers_geography)
#> # A tibble: 6 x 3
#> id label.en description.en
#> <chr> <chr> <chr>
#> 1 TYPE490 government office regions tec … government office regions tec / …
#> 2 TYPE491 government office regions (for… government office regions (forme…
#> 3 TYPE492 standard statistical regions standard statistical regions
#> 4 TYPE496 pre-1996 local authority distr… pre-1996 local authority distric…
#> 5 TYPE498 pre-1996 counties / scottish r… pre-1996 counties / scottish reg…
#> 6 TYPE499 countries countries
jobseekers_sex <- nomis_get_metadata("NM_1_1", "sex", "TYPE")
tibble::glimpse(jobseekers_sex)
#> Observations: 3
#> Variables: 4
#> $ id <chr> "5", "6", "7"
#> $ parentCode <chr> "7", "7", NA
#> $ label.en <chr> "Male", "Female", "Total"
#> $ description.en <chr> "Male", "Female", "Total"
z <- nomis_get_data(id = "NM_1_1", time = "latest", geography = "TYPE499",
measures=c(20100, 20201), sex=5)
tibble::glimpse(z)
#> Observations: 70
#> Variables: 34
#> $ DATE <chr> "2018-11", "2018-11", "2018-11", "2018-11"...
#> $ DATE_NAME <chr> "November 2018", "November 2018", "Novembe...
#> $ DATE_CODE <chr> "2018-11", "2018-11", "2018-11", "2018-11"...
#> $ DATE_TYPE <chr> "date", "date", "date", "date", "date", "d...
#> $ DATE_TYPECODE <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0...
#> $ DATE_SORTORDER <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0...
#> $ GEOGRAPHY <chr> "2092957697", "2092957697", "2092957697", ...
#> $ GEOGRAPHY_NAME <chr> "United Kingdom", "United Kingdom", "Unite...
#> $ GEOGRAPHY_CODE <chr> "K02000001", "K02000001", "K02000001", "K0...
#> $ GEOGRAPHY_TYPE <chr> "countries", "countries", "countries", "co...
#> $ GEOGRAPHY_TYPECODE <chr> "499", "499", "499", "499", "499", "499", ...
#> $ GEOGRAPHY_SORTORDER <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0...
#> $ SEX <chr> "5", "5", "5", "5", "5", "5", "5", "5", "5...
#> $ SEX_NAME <chr> "Male", "Male", "Male", "Male", "Male", "M...
#> $ SEX_CODE <chr> "5", "5", "5", "5", "5", "5", "5", "5", "5...
#> $ SEX_TYPE <chr> "sex", "sex", "sex", "sex", "sex", "sex", ...
#> $ SEX_TYPECODE <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0...
#> $ SEX_SORTORDER <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0...
#> $ ITEM <chr> "1", "1", "2", "2", "3", "3", "4", "4", "9...
#> $ ITEM_NAME <chr> "Total claimants", "Total claimants", "Stu...
#> $ ITEM_CODE <chr> "1", "1", "2", "2", "3", "3", "4", "4", "9...
#> $ ITEM_TYPE <chr> "item", "item", "item", "item", "item", "i...
#> $ ITEM_TYPECODE <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0...
#> $ ITEM_SORTORDER <chr> "0", "0", "1", "1", "2", "2", "3", "3", "4...
#> $ MEASURES <chr> "20100", "20201", "20100", "20201", "20100...
#> $ MEASURES_NAME <chr> "Persons claiming JSA", "Workplace-based e...
#> $ OBS_VALUE <dbl> 203148.0, 1.1, NA, NA, NA, NA, NA, NA, NA,...
#> $ OBS_STATUS <chr> "A", "A", "Q", "Q", "Q", "Q", "Q", "Q", "Q...
#> $ OBS_STATUS_NAME <chr> "Normal Value", "Normal Value", "These fig...
#> $ OBS_CONF <chr> "F", "F", "F", "F", "F", "F", "F", "F", "F...
#> $ OBS_CONF_NAME <chr> "Free (free for publication)", "Free (free...
#> $ URN <chr> "Nm-1d1d32299e0d2092957697d5d1d20100", "Nm...
#> $ RECORD_OFFSET <chr> "0", "1", "2", "3", "4", "5", "6", "7", "8...
#> $ RECORD_COUNT <chr> "70", "70", "70", "70", "70", "70", "70", ...
There is a lot of data available through Nomis, and there are some limits to the amount of data that can be retrieved within a certain period of time, although those are not published. For more details, see the full API documentation from Nomis. Full package documentation is available at docs.evanodell.com/nomisr
Bug reports, suggestions, and code contributions are all welcome. Please see CONTRIBUTING.md for details.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
Please note that this project is not affiliated with the Office for National Statistics or the University of Durham.
Get citation information for nomisr
in R with citation(package = 'nomisr')
Odell, (2018). nomisr: Access ‘Nomis’ UK Labour Market Data. Journal of Open Source Software, 3(27), 859, https://doi.org/10.21105/joss.00859.
A BibTeX entry for LaTeX users is
@article{odell2018,
title = {Nomisr: {{Access Nomis UK Labour Market Data}}},
volume = {3},
issn = {2475-9066},
url = {https://github.com/ropensci/nomisr},
doi = {10.21105/joss.00859},
number = {27},
journaltitle = {Journal of Open Source Software},
urldate = {2018-08-01},
note = {R package version 0.4.0}
date = {2018-07-28},
pages = {859},
author = {Odell, Evan}
}
License: MIT


%header%
From
%from%
Client
%client%
Invoice Number
%number%
Date
%date%
Due date
%due-date%
Balance Due
%balance%
Item
Quantity
Rate
Amount
%items%
Notes
%notes%


| 程序包 | 说明 |
|---|---|
| com.google.zxing | |
| com.google.zxing.aztec | |
| com.google.zxing.datamatrix | |
| com.google.zxing.oned | |
| com.google.zxing.pdf417 | |
| com.google.zxing.qrcode |
| 限定符和类型 | 类和说明 |
|---|---|
class |
MultiFormatWriter
This is a factory class which finds the appropriate Writer subclass for the BarcodeFormat
requested and encodes the barcode with the supplied contents.
|
| 限定符和类型 | 类和说明 |
|---|---|
class |
AztecWriter |
| 限定符和类型 | 类和说明 |
|---|---|
class |
DataMatrixWriter
This object renders a Data Matrix code as a BitMatrix 2D array of greyscale values.
|
| 限定符和类型 | 类和说明 |
|---|---|
class |
CodaBarWriter
This class renders CodaBar as
boolean[] . |
class |
Code128Writer
This object renders a CODE128 code as a
BitMatrix . |
class |
Code39Writer
This object renders a CODE39 code as a
BitMatrix . |
class |
EAN13Writer
This object renders an EAN13 code as a
BitMatrix . |
class |
EAN8Writer
This object renders an EAN8 code as a
BitMatrix . |
class |
ITFWriter
This object renders a ITF code as a
BitMatrix . |
class |
OneDimensionalCodeWriter
Encapsulates functionality and implementation that is common to one-dimensional barcodes.
|
class |
UPCAWriter
This object renders a UPC-A code as a
BitMatrix . |
class |
UPCEANWriter
Encapsulates functionality and implementation that is common to UPC and EAN families
of one-dimensional barcodes.
|
| 限定符和类型 | 类和说明 |
|---|---|
class |
PDF417Writer |
| 限定符和类型 | 类和说明 |
|---|---|
class |
QRCodeWriter
This object renders a QR Code as a BitMatrix 2D array of greyscale values.
|
Copyright © 2007–2013. All rights reserved.


Vim Personal Documentation
Summary
What you are reading now is my personal vim documentation.
Whether this would be helpful is entirely and totally dependent on how much you use vim. If you’re a typical user, then this might work for you. If you’re more advanced, this guide is basically a children’s book to you. And if you use vim like, once a year, then go figure the usefulness of such a guide to you.
Because of extensively working in vim (to the point of using it basically exclusively), I’ve made Vim my own playground. So be prepared to find unofficial code, messy references, and so on.
However, I’m releasing this to the community in hopes that others can remix and learn vim in a more relaxed way. You’re free to do basically everything with this book. It’s under a CC0 license, which makes it effectively public domain.
I have to thank all of the awesome developers of Vim and its plugins for giving me this amazing opportunity. And the creators of mdBook for making it so easy to share my experiences with everyone.
Without further ado, let’s get into Vim! You’ll learn everything I’ve ever learnt about Vim - and hopefully gain a fair share of respect for this unassuming yet powerful editor along the way.
Quick Start
First off, I should highlight that Vim is my personal preference, not because of its endless configuration or its minimalist charm, but by its permissive and open license.
My personal point of view is that large companies such as Microsoft and Adobe
- will inevitably use free and open-source as a marketting gesture
What to do if you struggle with vim
I understand the frustration you can get when first using vim. I felt the same way when I tried to learn vim and gave up twice. Vim just felt so unneccesary - why :q!
if you can use CTRL Q in every other program? Why :w
when you’ve always used CTRL S? And my least favorite command: ggVG"+y
to copy the document. Every little quirk of vim can spiral onto a full-blown case of Vim frustration.
So how do you avoid the classic syndrome of “Vim depression”? I’ve generally relied on several ways to do so:
Use the GUI versions first
The Vim community has ardently resisted against a GUI for Vim for decades. That’s why most versions of Vim are pretty minimal, out of the box. It has to be launched from a command line. Copy and paste doesn’t work. And click-drag select does nothing - which can utterly break people.
That’s why I recommend installing a GUI version of Vim. For Windows and GNU/Linux, it usually means GVim. For Mac users, MacVim should also do a good job. I might recommend neovim GUIs such as Veonim and Goneovim, but these are not ready-to-download and must be compiled.
Let’s get back on topic here. If you open up GVim or MacVim, the user interface is, to put bluntly, not spectacular. Yes, you can highlight, copy, and paste, and yes, you can move the cursor with a mouse, but it just doesn’t look right. Which is why you need to beautify Vim.
Make Vim colorful
Right out of the box, Vim is practical drawing pad, not a polished work of art. However, Vim was never designed to be a plain drawing pad with no drawings on it. Vim was always intended to look how you wanted it to - and it can look pretty good - even better than many modern editors - once you begin adding themes and plugins.
First things first, the most visually altering things you’ll need to do are:
- Install a new theme
- Install an airline status bar
- Install coding fonts
Installing a font is probably the first and easiest one of the three. And so on...
Focus on the navigation
Vim’s 4-key based navigation is arguably its strongest point. That’s how it never needs to rely on a mouse to work.
However, getting to grips with this can be difficult. And even worse are keyboard tables for Vim, which, though well-intentioned, provide little true support.
So that’s why learning visually is a great idea. Take this, for example:
k
^
|
h <-- --> l
|
v
j
This is a good way to get familiar with Vim’s 4 key navigation. And once you’re done with that, try this:
<-|------------------------------|->
0 | <-<- | ->-> | $
<---+ * <---+--->
b here w e
^ <-<-
After that, it’s just a few sparse commands that muscle memory will eventually get the hang of, such as gg
to go to the top of the document, number G
to go to a specific line, and G
to go to the last line. Work in progress...
Now, with SPC e, I can launch a file browser (coc-explorer), make a index.html
and play around with a website, and toggle a command prompt with the :CocCommand command-here
. And that’s just the surface of what you can do with Coc!
Doing more advanced stuff with plugins
Now that you’ve learnt how to use vim, let’s spice it up with plugins! And don’t be worried about the learning curve! Unlike almost all other software, I’ve found that vim’s plugins actually make vim easier than plugin-less vim. The only real disadvantage is that too many plugins can clash with each other and result in horrible configurations - but that’s when you have literally hundreds of plugins! So we don’t have to worry about that for now.
Vimming with Coc
Coc is perhaps the king of all Vim plugins. Because it’s not just a plugin. It’s more like a full plugin environment integrated closely to vim that adds all sorts of cool features. It’s literally that plugin that turns Vim from a text editor to an IDE.
To get started with Coc, familiarize yourself again with the vim-plug system. As a refresher, vim-plug uses a special portion of your ~/.vimrc
file to manage plugins. If you’ve forgotten, here’s how it should look like:
call plug#begin('~/.vim/plugged')
" put your vim plugins here
call plug#end()
The code for coc is Plug 'neoclide/coc.nvim', {'branch': 'release'}
. Just paste that in to your vim-plug code block. Like this:
call plug#begin('~/.vim/plugged')
" The Coc plugin
Plug 'neoclide/coc.nvim', {'branch': 'release'}
" put your other vim plugins within this section
call plug#end()
Now, just do a source ~/.vimrc
and a :PlugInstall
. Wait for the plugin download screen to stop flashing, and you can begin using Coc.
First things first, you’ve got to add some basic languages to Coc. Being a web and frontend/GUI developer mostly, I usually go for the web design languages, and maybe python. That’s why I recomment you to add html, css, js, and json first, as well as the word dtatbase from the makers of VSCode, like this:
:CocInstall coc-html coc-css coc-tsserver coc-json coc-word
Now, start writing some code! You’ll see recomennded words to use within a popu menu. And just use the down and up arrow keys to choose your desired word. This can be useful in writing non-code prose as well, such as long essays with lots of long words.
To make the plugin install process less obtrusive, I recommend downloading the coc-marketplace
plugin, with :CocInstall coc-marketplace
. After sourcing the .vimrc
and running :PlugInstall
, you can simply type :CocInstall coc-marketplace
to search through all your extensions.
Once you’ve downloaded them, use the command :CocList extensions
to do your view an manager work. Press the tab key to toggle, enable, and control your extensions. :CocUpdate
will update all extensions, if that’s your style.
And my favorite part - :CocList commands
allows you to run any coc-supported feature and plugin subfeature with simper-simple input. It’s also fuzzy searched, so no worries about bad typing!
In addition, the extensions often use the vim CR
key, also known as the \
character. Add nmap <space>e :CocCommand explorer<CR>
to change the CR
key to the ,
key.


These tracks display Formaldehyde-Assisted Isolation of Regulatory Elements (FAIRE) evidence as part of the four Open Chromatin track sets (see below). FAIRE is a method to isolate and identify nucleosome-depleted regions of the genome. FAIRE was initially discovered in yeast and subsequently shown to identify active regulatory elements in human cells (Giresi et al., 2007). Similar to DNaseI HS, FAIRE appears to identify functional regulatory elements that include promoters, enhancers, silencers, insulators, locus control regions and novel elements.
Together with DNaseI HS and ChIP-seq experiments, these tracks display the locations of active regulatory elements identified as open chromatin in multiple cell types from the Duke, UNC-Chapel Hill, UT-Austin, and EBI ENCODE group. Within this project, open chromatin was identified using two independent and complementary methods: DNaseI hypersensitivity (HS) and these FAIRE assays, combined with chromatin immunoprecipitation (ChIP) for select regulatory factors. DNaseI HS and FAIRE provide assay cross-validation with commonly identified regions delineating the highest confidence areas of open chromatin. ChIP assays provide functional validation and preliminary annotation of a subset of open chromatin sites. Each method employed Illumina (formerly Solexa) sequencing by synthesis as the detection platform. The Tier 1 and Tier 2 cell types were additionally verified by a second platform, high-resolution 1% ENCODE tiled microarrays supplied by NimbleGen.
Other Open Chromatin track sets:
This track is a multi-view composite track that contains a single data type with multiple levels of annotation (views). For each view, there are multiple subtracks representing different cell types that display individually on the browser. Instructions for configuring multi-view tracks are here. Chromatin data displayed here represents a continuum of signal intensities. The Leib lab recommends setting the "Data view scaling: auto-scale" option when viewing signal data in full mode to see the full dynamic range of the data. Note that in regions that do not have open chromatin sites, autoscale will rescale the data and inflate the background signal, making the regions appear noisy. Changing back to fixed scale will alleviate this issue. In general, for each experiment in each of the cell types, the UNC FAIRE tracks contain the following views:
Tracks displayed in this track are the results of pooled replicates. The raw sequence and alignment files for each replicate are available for download.
Metadata for a particular subtrack can be found by clicking the down arrow in the list of subtracks.
Cells were grown according to the approved ENCODE cell culture protocols.
FAIRE was performed (Giresi et al., 2007) by cross-linking proteins to DNA using 1% formaldehyde solution, and the complex was sheared using sonication. Phenol/chloroform extractions were performed to remove DNA fragments cross-linked to protein. The DNA recovered in the aqueous phase was sequenced using an Illumina (Solexa) sequencing system. FAIRE-seq data for Tier 1 and Tier 2 cell lines were verified by comparing multiple independent growths (replicates) and determining the reproducibility of the data. For some cell types additional verification was performed using the same material, but hybridized to NimbleGen Human ENCODE tiling arrays (1% of the genome) along with the input DNA as reference (FAIRE-chip). A more detailed protocol is available here and in the references below (Giresi et al., 2009).
DNA fragments isolated by FAIRE are 100-200 bp in length, with the average length being 134 bp. Sequences from each experiment were aligned to the genome using Burrows-Wheeler Aligner (BWA) (Li et al., 2010) for the NCBI 36 (hg19) assembly.
> bwa aln -t 8 genome.fa s_1.sequence.txt.bfq > s_1.sequence.txt.sai
Sequences from multiple lanes are combined for a single replicate using the bwa samse command, and converted in the sam/bam format using SAMtools.
Only those that aligned to four or fewer locations were retained. Other sequences were also filtered based on their alignment to problematic regions (such as satellites and rRNA genes - see supplemental materials). The mappings of these short reads to the genome are available for download.
The resulting digital signal was converted to a continuous wiggle track using F-Seq that employs Parzen kernel density estimation to create base pair scores (Boyle et al., 2008b). Input data has been generated for several cell lines. These are used directly to create a control/background model used for F-Seq when generating signal annotations for these cell lines. These models are meant to correct for sequencing biases, alignment artifacts, and copy number changes in these cell lines. Input data is not being generated directly for other cell lines. Instead, a general background model was derived from the available input data sets. This should provide corrections for sequencing biases and alignment artifacts, but will not correct for cell-type-specific copy number changes.
> fseq -l 800 -v -b <bff files> -p <iff files> aligments.bed
Discrete FAIRE sites (peaks) were identified from FAIRE-seq F-seq density signal. Significant regions were determined by fitting the data to a gamma distribution to calculate p-values. Contiguous regions where p-values were below a 0.05/0.01 threshold were considered significant.
Data from the high-resolution 1% ENCODE tiled microarrays supplied by NimbleGen were normalized using the Tukey biweight normalization, and peaks were called using ChIPOTle (Buck et al., 2005) at multiple levels of significance. Regions matched on size to these peaks that were devoid of any significant signal were also created as a null model. These data were used for additional verification of Tier 1 and Tier 2 cell lines by ROC analysis. Files labeled Validation view containing this data are available for download.
Release 2 (September 2012) of this track consists of 12 new experiments, including 11 new cell lines.
These data and annotations were created by a collaboration of multiple institutions (contact: Terry Furey):
We thank NHGRI for ENCODE funding support.
Bhinge AA, Kim J, Euskirchen GM, Snyder M, Iyer VR. Mapping the chromosomal targets of STAT1 by Sequence Tag Analysis of Genomic Enrichment (STAGE). Genome Res. 2007 Jun;17(6):910-6.
Boyle AP, Davis S, Shulha HP, Meltzer P, Margulies EH, Weng Z, Furey TS, Crawford GE. High-resolution mapping and characterization of open chromatin across the genome. Cell. 2008 Jan 25;132(2):311-22.
Boyle AP, Guinney J, Crawford GE, Furey TS. F-Seq: a feature density estimator for high-throughput sequence tags. Bioinformatics. 2008 Nov 1;24(21):2537-8.
Buck MJ, Nobel AB, Lieb JD. ChIPOTle: a user-friendly tool for the analysis of ChIP-chip data. Genome Biol. 2005;6(11):R97.
Crawford GE, Davis S, Scacheri PC, Renaud G, Halawi MJ, Erdos MR, Green R, Meltzer PS, Wolfsberg TG, Collins FS. DNase-chip: a high-resolution method to identify DNase I hypersensitive sites using tiled microarrays. Nat Methods. 2006 Jul;3(7):503-9.
Crawford GE, Holt IE, Whittle J, Webb BD, Tai D, Davis S, Margulies EH, Chen Y, Bernat JA, Ginsburg D et al. Genome-wide mapping of DNase hypersensitive sites using massively parallel signature sequencing (MPSS). Genome Res. 2006 Jan;16(1):123-31.
ENCODE Project Consortium, Birney E, Stamatoyannopoulos JA, Dutta A, Guigó R, Gingeras TR, Margulies EH, Weng Z, Snyder M, Dermitzakis ET et al. Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature. 2007 Jun 14;447(7146):799-816.
Giresi PG, Kim J, McDaniell RM, Iyer VR, Lieb JD. FAIRE (Formaldehyde-Assisted Isolation of Regulatory Elements) isolates active regulatory elements from human chromatin. Genome Res. 2007 Jun;17(6):877-85.
Giresi PG, Lieb JD. Isolation of active regulatory elements from eukaryotic chromatin using FAIRE (Formaldehyde Assisted Isolation of Regulatory Elements). Methods. 2009 Jul;48(3):233-9.
Li H, Ruan J, Durbin R. Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res. 2008 Nov;18(11):1851-8.
Song L, Crawford GE. DNase-seq: a high-resolution technique for mapping active gene regulatory elements across the genome from mammalian cells. Cold Spring Harb Protoc. 2010 Feb;2010(2):pdb.prot5384.


Dataset: birth
The dataset birth
records 189 birth weights from Massachusetts, USA, and some additional variables. The variables are,
| Var | Description |
|---|---|
LOW |
Equals YES if birth weight is below 2500g and NO otherwise. |
AGE |
Age of the mother in years. |
LWT |
Weight in pounds of mother. |
SMK |
YES if mother smokes and NO otherwise. |
BWT |
Birth weight in g (RESPONSE). |
The data appears in fronter as birth.rdata
. Download the data into your STAT340 course folder and load the data set in RStudio.
Overview of data
- Take a look at the top 10 rows of the data using the
head()
function
head(birth, n = 10)
LOW AGE LWT SMK BWT
1 YES 28 120 YES 709
2 YES 29 130 NO 1021
3 YES 34 187 YES 1135
4 YES 25 105 NO 1330
5 YES 25 85 NO 1474
6 YES 27 150 NO 1588
7 YES 23 97 NO 1588
8 YES 24 128 NO 1701
9 YES 24 132 NO 1729
10 YES 21 165 YES 1790
- Use the
summary()
function to get a short summary of the variables.
summary(birth)
LOW AGE LWT SMK BWT
NO :130 Min. :14.0 Min. : 80 NO :115 Min. : 709
YES: 59 1st Qu.:19.0 1st Qu.:110 YES: 74 1st Qu.:2414
Median :23.0 Median :121 Median :2977
Mean :23.2 Mean :130 Mean :2945
3rd Qu.:26.0 3rd Qu.:140 3rd Qu.:3475
Max. :45.0 Max. :250 Max. :4990
- What is the proportion of smoking mothers in the data set?

The average age of mother giving birth is 23.2 years.
- What is the average birth weight of children from non-smoking and smoking mothers?
tapply(birth$BWT, INDEX = birth$SMK, FUN = mean)
NO YES
3055 2773
The function returns the mean birth weight for children of non-smoking and smoking mothers.
- What is the standard deviation of birth weight of children from non-smoking and smoking mothers?
tapply(birth$BWT, INDEX = birth$SMK, FUN = sd)
NO YES
752 660
The sd()
function computes the sample standard deviation of a vector of observations.
Linear Regression
Run a simple linear regression model with BWT as response and LWT as predictor, like this,
birth1 <- lm(BWT ~ LWT, data = birth)
summary(birth1)
Call:
lm(formula = BWT ~ LWT, data = birth)
Residuals:
Min 1Q Median 3Q Max
-2192.2 -503.6 -3.9 508.3 2075.5
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2369.67 228.43 10.37 <2e-16 ***
LWT 4.43 1.71 2.59 0.01 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
s: 718 on 187 degrees of freedom
Multiple R-squared: 0.0345,
Adjusted R-squared: 0.0294
F-statistic: 6.69 on 1 and 187 DF, p-value: 0.0105
Here, the regression model is,
\[\text{BWT} = \beta_0 + \beta_1 \text{LWT} + \epsilon\]
where \(\epsilon \sim N(0, \sigma^2)\)
Test the significance of LWT on BWT with a 5% test level and at a 1% level
What is the hypothesis you are testing?
The hypothesis for testing the significance of LWT on BWT is, \[ H_0: \beta_1 = 0 \text{ vs } H_1: \beta_1 \ne 0\]
- What is the conclusion?
The \(p\)-value corresponding to \(\beta_1\) is less than 0.05 but greater than 0.01. So, at 5% test level, LWT is significant while at 1% test level, it is not significant.
- Find the R-squared. Do you think the model fits the data well?
The r-squared (\(R^2\)) for the model is 0.03, this shows that only 3% of variation present in birth weight (BWT) is explained by weight of mother (LWD). Here, the model fits the data poorely.
Scatter Plot
- Make a scatter plot of LWT vs BWT
The scatter plot of LWT and BWT is,
plot(x = birth$LWT, y = birth$BWT)
abline(birth1)
- Make a comment to the plot in light of the output of your analyses.
- The intercept for the regression line is 2369.67 and the slope is 4.43.
- The data-points are scattered around the regression line where BWT vary most
- Since the data-points are scattered much, the model could only explain small variation present in BWT with LWT.
Confidence Intervals
- Find 95% confidence intervals for the regression coefficients of the
birth1
model
confint(birth1)
2.5 % 97.5 %
(Intercept) 1919.04 2820.30
LWT 1.05 7.81
- Also find 99% confidence intervals
confint(birth1, level = 0.99)
0.5 % 99.5 %
(Intercept) 1775.2097 2964.13
LWT -0.0287 8.89
- Comment on the intervals
- It is 95% certain that the interval (1.05, 7.809) covers the true \(\beta_1\). Similary, it is 99% certain that the interval (-0.029, 8.887) covers the true \(\beta_1\).
- The 99% confidence is larger than 95% confidence. In other words, being more certain about the true value needs larger confidence interval.
- Moreover, the 95% does not include zero while 99% interval includes zero. This is equivalent with the result that \(\beta_1\) cofficient is significant at a 5% test level, but not significant at a 1% test level.
Regression with categories
Here we will fit a separate regression for smoking and non-smoking groups. You can identify the observation numbers of the smokers by:
smokeYes <- which(birth$SMK == "YES")
Fit the same model as birth1
, but separate models for non-smokers and smokers, and call the models birth2
and birth3
. (Hint: select observations by the subset argument in the lm
-function using the smokeYes
variable.)
birth2 <- lm(BWT ~ LWT, data = birth, subset = -smokeYes)
birth3 <- lm(BWT ~ LWT, data = birth, subset = smokeYes)
Interpreate these models
- Make a scatter plot of LWT vs BWT and add two fitted lines form the model fitted above.
plot(x = birth$LWT, y = birth$BWT)
abline(birth2, col = "red")
abline(birth3, col = "blue")
- Comment on the plot
Fitted lines for both non-smokers and smokers seems very similar, but it is difficult to tell whether they are significantly different. We will later se how we can model both mother-groups simultaneously and be able to test this difference.
- Is LWT significant at a 5% level on BWT for the smokers?
summary(birth3)
Call:
lm(formula = BWT ~ LWT, data = birth, subset = smokeYes)
Residuals:
Min 1Q Median 3Q Max
-2040.3 -416.3 33.9 472.2 1488.7
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2395.37 301.47 7.95 0.000000000019 ***
LWT 2.95 2.28 1.30 0.2
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
s: 657 on 72 degrees of freedom
Multiple R-squared: 0.0228,
Adjusted R-squared: 0.00921
F-statistic: 1.68 on 1 and 72 DF, p-value: 0.199
The hypothesis for testing the significance of LWT is,
\[H_0: \beta_1 = 0 \text{ vs } H_1: \beta_1 \ne 0\]
From the summary of model birth3
above, p-value corresponding to LWT is higher than 0.05 and we fail to reject \(H_0\), which suggests that LWT is not significant for smokers group. In other words, LWT does not have any linear relationship with BWT at 95% confidence level for smokers group.
Assume a model with both LWT and AGE as predictors for BWT using all observations.
- Write up the model and the model assumptions.
\[\text{BWT} = \beta_0 + \beta_1 \text{LWT} + \beta_2 \text{AGE} + \epsilon\]
Assumptions:
The error term \(\epsilon\) follows \(N(0, \sigma^2) \; iid\), i.e error terms are independently normally distributed with mean 0 and constant variance \(\sigma^2\).
- What is the interpretation of the regression coefficients?
- \(\beta_1\) gives the expected amount of change in BWT for unit change in LWT when AGE is held constant, i.e. if LWT increases by 1 pound, BWT will increase by \(\beta_1\) grams for people of the same AGE.
- \(\beta_2\) gives the expected amount of change in BWT (in grams) if AGE increase by 1 year and LWT is held constant.
Fit the model in RStudio, call it birth4
and comment on the results.
birth4 <- lm(BWT ~ LWT + AGE, data = birth)
summary(birth4)
Call:
lm(formula = BWT ~ LWT + AGE, data = birth)
Residuals:
Min 1Q Median 3Q Max
-2232.8 -500.5 32.1 520.3 1899.3
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2215.76 299.24 7.4 0.0000000000044 ***
LWT 4.18 1.74 2.4 0.018 *
AGE 8.02 10.06 0.8 0.426
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
s: 719 on 186 degrees of freedom
Multiple R-squared: 0.0378,
Adjusted R-squared: 0.0275
F-statistic: 3.65 on 2 and 186 DF, p-value: 0.0278
The summary output shows that LWT is significant at 5% level of significance but not at 1%. AGE has very high p-value and thus is not significant, i.e. there is not any linear relationship of AGE with BWT. The explained variation is still very low with an \(R^2=0.038\).
Optional:
Look at the presentation file Regression.Rmd from lecture 2 and produce for the birth4-model
a similar 3D-plot as on page 15. You may need to install the R-packages: rgl
, nlme
, mgcv
and car
first. Use the figure to get an understanding of the effects of LWT and AGE on BWT.
A 3D plot
library(scatterplot3d)
with(birth, {
# Start Plot
plot3d <- scatterplot3d(LWT, AGE, BWT, type = "p", highlight.3d = TRUE,
mar = c(3, 3, 2, 3), pch = 19, cex.symbols = 0.5,
main = "Residuals and fitted plane for model: birth4",
angle = 45, box = FALSE)
# Add fitted plane for model birth4
plot3d$plane3d(birth4, col = "grey50", lty.box = "solid", polygon_args = list(bg = "lightgrey"))
# True Values
true <- plot3d$xyz.convert(LWT, AGE, BWT)
# Predicted Values
fitted <- plot3d$xyz.convert(LWT, AGE, fitted(birth4))
# Is the residuals negative?
neg_res <- 1 + (resid(birth4) > 0)
# Add segment for the residuals
segments(true$x, true$y, fitted$x, fitted$y, col = c("blue", "red")[neg_res])
})
An interactive 3D plot
library(car)
scatter3d(BWT ~ LWT + AGE, data = birth, axis.ticks = TRUE, revolutions = 1)
For grouped: Smoking vs Non-Smoking:
car::scatter3d(BWT ~ LWT + AGE, data = birth, axis.ticks = TRUE,
revolutions = 1, groups = birth$SMK)
Interpretation
- What is the interpretation of the estimated regression coefficients for LWT and AGE in this model?
From the summary output of birth4
model, the \(\beta\) coefficient for LWT is 4.179 and AGE is 8.021. This shows that, if weight of mother (LWT) increases by 1 pound, the birth weight (BWT) is estimated to increase by 4.179 grams if AGE is held constant. Similary, if the age of a mother (AGE) increases by 1 year, the birth weight (BWT) is estimated to increase by 8.021 grams, if LWT is held constant. The regression coefficients are therefore equal to the slopes of the gridlines of the surface in the figure.


Source separation via SVD-free rank minimization in the hierarchical semi-separable representation
This application is available only in the software release for members of SINBAD consortium.
This software release includes a demonstration of a 2-D over/under blended marine acquisition scenario, and a source separation algorithm based on a SVD-free rank minimization scheme.
Author: Haneet Wason<EMAIL_ADDRESS>Date: June, 2014; July, 2016 - parallel version of the code made available.
Contents
Downloading & Dependencies
The code can be found in the SLIM software release under /applications/Acquisition/SourceSeparationLowRankHSS.
The code has been tested with Matlab R2015b. The updated code requires the Parallel Computing Toolbox.
This code uses the following packages, also found in the tools part of the SLIM software release.
- utilities/SPOT-SLIM - object oriented framework for matrix-free linear algebra.
- utilities/SegyMAT - Matlab/Octave toolbox for reading and writing SEG-Y formatted files.
- solvers/GenSPGL1 - Generalized SPGL1.
Running & Parallelism
All the examples and results are produced by the scripts found in this software release under applications/Acquisition/SourceSeparationLowRankHSS/examples/. Start matlab from applications/Acquisition/SourceSeparationLowRankHSS to add the appropriate paths.
To run the scripts follow the instructions in the README file enclosed with the code. The scripts are run in parallel mode.
Examples and results
Examples and results are shown here. Scripts to reproduce the results can be found under /applications/Acquisition/SourceSeparationLowRankHSS/examples.
References
[1] Rajiv Kumar, Haneet Wason, and Felix J. Herrmann [2015]. Source separation for simultaneous towed-streamer marine acquisition --- a compressed sensing approach, Geophysics, vol. 80, pp. WD73-WD88.
[2] Haneet Wason, Rajiv Kumar, Aleksandr Y. Aravkin, and Felix J. Herrmann [2014]. Source separation via SVD-free rank minimization in the hierarchical semi-separable representation, presented at the SEG Conference.
[3] Aleksandr Y. Aravkin, Rajiv Kumar, Hassan Mansour, Ben Recht, and Felix J. Herrmann [2014]. Fast methods for denoising matrix completion formulations, with applications to robust seismic data interpolation, SIAM Journal on Scientific Computing (SISC), vol. 36, pp. S237-S266.
[4] Rajiv Kumar, Hassan Mansour, Aleksandr Y. Aravkin, and Felix J. Herrmann [2013]. Reconstruction of seismic wavefields via low-rank matrix factorization in the hierarchical-separable matrix representation, SEG Technical Program Expanded Abstracts, p. 3628-3633.
Acknowledgements
Thanks to our sponsors and NSERC for their financial support.


|
Secondary,
Immunogenicity:
|
1 Change from
baseline to week 16 in circulating levels of inflammatory
biomarkers CXCL10 (IP-10), sCD163,
IL-6, sTNFR1 & 2, hs-CRP, sCD26.
2. Change from baseline to week 16 in the percentage and number of
CD4+CD38+HLA-DR+ and
CD8+CD38+HLA-DR+ T-cell subpopulations
3. Change from baseline to week 16 in the percentages and number of
CD14+CD16- (classical),
CD14+CD16+ (intermediate) and CD14dim
CD16++ (non-classical) monocyte
subpopulations.
4. Change from baseline to week 16 in CD4+/CD8+ T-cell ratio.
5. Occurrence of Grade >=3 AEs and selected Grade >=2 AEs related to
study drug.
6. Change from week 16 to week 20 for: plasma sCD14 levels, plasma
biomarker levels (CXCL10 (IP-10),
sCD163, IL-6, sTNFR1 & 2, hs-CRP,
sCD26), percentage and number of
T-cell and monocyte subpopulations,
and CD4+/CD8+ T-cell ratio.
7. In the event that sitagliptin reduces plasma markers of immune
activation
or inflammation, change from
baseline to week 16 and week 16 to week 20
in monocyte mRNA expression for
pro-inflammatory cytokine or chemokine
markers (e.g., TLR-2, TLR-4,
CCR2, TNFalpha).
8. In the event that sitagliptin reduces plasma markers of immune
activation
or inflammation, change from
baseline to week 16 and week 16 to week 20
in monocyte HIV RNA/DNA ratio.
(Section 9.2.2)
|


When you adopt a pet, wonderful things happen in your life. Yes you are thinking of having a new member in your family; you're in the correct place!
Adopting can be one of the greatest experiences of your life, where you will share beautiful moments with these faithful, tender, and full friends of love to give away.


"Success is peace of mind, which is a direct result of self-satisfaction in knowing you made the effort to become the best of which you are capable."
-John Wooden


LinkML at a glance
LinkML is a flexible modeling language that allows you to author schemas (“models”) in YAML that describe the structure of your data. The language is designed to allow for both simple use cases such as describing the column headers in a spreadsheet through to creating a complex interlinked schema.
LinkML is designed to work in harmony with other frameworks, including both semantic RDF-based frameworks as well as frameworks more familiar to developers such as JSON.
Feature: Rich modeling language
LinkML offers many features of use to data modelers, while retaining a simple core
Classes can be arranged in inheritance hierarchies
Powerful Semantic enumerations that can optionally be backed by ontologies
Create data models that are independent of a database technology
Ability to provide rich annotations, metadata, and mappings as part of a model
“Linked Data” ready
All schemas have a corresponding JSON-LD context
Compatability with RDF tooling, without committing to an RDF stack
A bridge between frameworks
Many frameworks lock you in to a particular view of the world or technology. This can lead to silos, and the need to create mappings and transformations between different representations of the same data; for example, if your JSON documents need to work in concert with your relational database or graph store.
LinkML has many different generators existing frameworks that allow the translation of a LinkML schema to other frameworks:
Convert to JSON-LD contexts, and instantly port your data to RDF
Convert to JSON-Schema and using JSON-Schema validators
Convert to ShEx and validate your data as RDF
Convert to Python dataclasses for easy use within applications
Feature: Generation of documentation and websites
Using the LinkML toolchain you can go from a schema to statically hosted searchable website in minutes, with pages for each of your schema elements. Using lightweight namespace registries such as w3id.org you can easily have resolvable URIs for all your concepts.
A rapidly growing toolchain
The core LinkML toolchain allows for:
conversion between JSON, TSV, and RDF
data validation of JSON, TSVs, or RDF using either JSON-Schema, SPARQL, or ShEx
easy programmatic manipulation of schemas
LinkML is part of a growing ecosystem of general purpose tools that make curating, mapping, ingesting, and organizing data much easier
linkml-model-enrichment bootstraps schemas from existing structured and semi-structured sources
linkml-owl allows for generation of complex OWL axioms from datamodels
DataHarmonizer is a ontology-based curation tool that is being adapter to LinkML
We eat our own dogfood!
The LinkML schema language is itself defined in LinkML, and we use our own toolchain for working with it!
For example, the linkml-model reference is generated from the source metamodel
More examples
See the examples


Support Your NLP Platform¶
If you want to add another NLP service, you will always need to implement the NlpAdapter
interface. You can skip this first section if you are
only interested in exemplar config files and the the technical definition of the format we expect. But first of all, we would like to offer some more explanation
of our inspiration that lead to the current decision-making process inside the framework. So let us start in the beginning
The program you communicate with over some messaging platform is what we call a chatbot. Behind this chatbot, there is a so called agent, which is often used synonymous to chatbot. And this can be quite fitting: All the information (the definition of which queries shall be answered, which entities are relevant to them, contextual information, exemplar utterances…) is saved in this agent. But a chatbot can also consist of several agents: especially for larger corporate chatbots, it is often useful to divide the content (separation of concern) and introduce a hierarchy: Answering smalltalk queries might be less relevant than answering questions regarding the service you offer. Furthermore you might deploy two chatbots, advising on two different products. To avoid retraining the same smalltalk queries, you might want to keep them generalized and just plug your smalltalk agent into both product-specific agents.
Using the framework you can create a hierarchy by using the executionIndex
to determine the order of when a request is sent to which agent, and set a
threshold which determines when to accept the response and not send it to another agent using a minScore
, the minimal confidence required to accept a result.
Commonly you want to be very certain when asking queries related to your product, which will also receive more training than e.g. smalltalk. This means that setting a
high minScore
for product specific agents and a lower one for smalltalk agents can be useful.
Configuration¶
In general, it is useful to extend the existing NlpConfig
. The NlpConfig
includes
a
constructor
of the class that implementedNlpAdapter
,a
name
of the NLP service (used for logging), andyour
Agents
where you define all information required for calling the NLP service API and parameters required for the hierarchy.
Your configuration file should also be extended with the platform-dependent authentication tokens and other variables required to communicate with the messaging API
of your service. Some of these information are part of the Agent
type. An agent includes the following information:
executionIndex
: a number to determine the order in which a request is sent to different agents. Only relevant if you use multiple agents, still mandatory to set. The agent with the lowestexecutionIndex
is called first.minScore
: the default confidence that has to be exceeded to avoid sending the query to the next agent. Can be overwritten/ignored in the second Inteceptor<interceptor>,nlpToNlp
.token
: token required to authenticate with your NLP service.url
: the API endpoint you communicate with.languageCode
: the language code of your agent. The format might differ between NLP services.
Depending on the platform you use, it might also be necessary to set other information like
project_id
: project ID of your agent (e.g. GCP ID for Dialogflow), orthe
defaultLifespan
of your agents, defining how long a conversation context should last.


Here at WXR Media we strive to bring you the best news coverage of current events.
WXR Media is made up of a team of three writers, two reporters, and one website programmer. We cover current events and general news. Subscribe to our newsletter to get emails every time a new article is uploaded!


In Odoo all the layouts are the corresponding sections, which used to group the PDF report data. By default, all such layouts are displayed for every existing Sale Orders and there are no possibility to display a specific one. So it is inconvenient, because some of the layouts may not suit for some set of sale orders.
The module eliminates this disadvantage, because allows to use layouts only within Sale Order they created for.
Set a section as global at Sales → Configuration → Report Layout Categories menu to make it available for all sale orders.
Once you create a new sale order, you need to save it after creating new layout (Section), otherwise layout will not be displayed on other order lines.
Contact us by email or fill out request form


This turned out to be one of the most interesting expierences of my life. It was the night of summer slam so me and about 7 other guys went out to BW3 to watch it on paper view. The place was packed and filled with drunk guys. Looked like fun. Me and one of my friends got tired of waitng for our food to come so we walked down the plaza to buy ciggerettes. One of my friends that had come along to buy them since I am 17. He went in to pay and me and my other friend waited outside.
Out of boredom I happened to look in one of these giant bins they had outside their store. It was filled with plant and flower seeds. Not having any recreational drugs or alcohal we decided to steal every package they have. All in all we got about 12 packages, each containing 1.5 grams of seeds. My friend is alot bigger then me so he took 8 packages or 12 grams and I took 4 packages or 6 grams. Now for those of you who don't know much about morning glory it produces LSA, which is a cousin to the infamous LSD. I had never tripped before so I figured what the hell.
[Erowid Note: Stealing is harmful to others. Don't do it!]
After we returned to BW3 we showed our friends what we had and commenced taking them. First of All I have NEVER tasted any seeds that were that disgusting. My friend managed to get his all down and I choked mine down after about 20 minutes. In each bag there are at least a hundred seeds (I dont remember the exact number) and they are small and black and disgusting. So I took mine and 30 minutes went by and I felt nothing. My friend took his earlier than me and reported feeling a little quesy but nothing too bad. I was kinda let down so I went outside to smoke.
I brought out the last 2 or 3 seeds that I had missed and ate them out side. For some reason I felt like I had one of them stuck in the back of my mouth. I couldn't get away from that sick taste. It was over whelming. I gave up on smoking and went back inside and downed a few cokes. Nothing helped so finally I just accepted it. The taste wore off after another half hour but then the sickness came.
My stomach felt like it had been stuffed past its limit. Everything was tight and I thought for sure I would puke my brains out. Anyway, This got worse and worse for the 3 hours we were there. For the last 2 hours I felt like I couldn't move. I had the sensation of being at the bottom of a dark tunnel where I could only see out of a little box. I have been in holes from K before but not like this.
Every now and then a friend would stick his head over the well and ask how I was doing. I felt dettached from real life.  Me and a buddy drove back to my house which is about 30 minutes away. By the end of the drive I couldn't feel my foot and he had to push on my leg so that we would keep moving. I dont reccomend driving like that.
[Erowid Note: Driving while intoxicated or tripping is dangerous and irresponsible because it endangers other people. Don't do it!]
When I got home I had calmed down and the quesy feeling subsided. I called a girl I met at a rave and talked with her most of the night. I was sitting on the counter in my bathroom when I noticed the walls were breathing. Thats right...breathing...in and out. I have a picture where the frame was rotating around the picture. The patters in my carpet and walls were moving all different ways. I would definatly classify that as the COOL part of the experience. This lasted for almost 7 hours. All in all a fun expiernce at the end but the first 3-4 hours were HELL.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


This page contains a couple of HTML forms that GET and POST to the
REST API provided by your project. These forms are not
submitted as part of the project. You do not have to update
them.
These forms let you interact with the simple word/definition REST API that
is created by the project archetype.


Origins
Imagine, ten thousand years into the future. Two renowned Archeologists have returned from a dig, what they found was disturbing a combination of brutality and primitivsm. One will hypothesize that the evidence of unquestioning obedience, xenophobia and psycological isolation can mean only one thing: A 20th century penal colony.
The other will argue that it was not a penal colony at all, but infact a military camp for insolent conscripts.
They will agree, however on one thing: No one would EVER choose such a sterile and flavorless existence. This place is found on edge of Detroit, it is where this guy was born. It took him 19 years to escape. He now lives in the PNW with his family, they have two cats and no dogs.
Skills and Accomplishments
So this guy can do some stuff, since escaping the point of origin he has been engaged in a variety of occupations. From vegan baker to Army Cavalry Scout to bike courier to Uber driver. He can cook, bake, build, deliver, brew and fight.
True loves
- My Daughter, she is awesome
- My wife who is my best friend and has great bangs (in case she asks)
- My Cats for they are smarter than you know
- All Asian cuisine
- Belgian Ale
- Nigerian Funk Circa 1970
- Surrealism
- Old School Si Fi
- Satire
- This Movie
State Sponsored Looters
- Gravity
- Automated Phone Tree Support
- Commercials on Hulu
- The Sun
- Turkey (the disgusting meat product not the county)
- The Twight Series


WebRTC Streamchannel
Create Offer
Create Answer
Establish
WebRTC Datachannel
Create Offer
Create Answer
Establish
Incoming
Send
Send


Worker
Account:
{{login.member_account}}
Email:
{{login.member_email}}
Name:
{{worker.worker_name}}
Tele:
{{worker.worker_telephone}}
Address:
{{worker.worker_address}}
Skill
{{skill.code_value}}
Your Experience


|
SimpleITK
|
#include <sitkLogger.h>
Public Member Functions | |
| void | DisplayDebugText (const char *t) override |
| void | DisplayErrorText (const char *t) override |
| void | DisplayGenericOutputText (const char *t) override |
| void | DisplayText (const char *t) override |
| void | DisplayWarningText (const char *t) override |
| ITKLogger ()=default | |
| ITKLogger (const ITKLogger &) | |
| ITKLogger (itk::OutputWindow *) | |
| ITKLogger & | operator= (ITKLogger) |
| ITKLogger | SetAsGlobalITKLogger () override |
| ~ITKLogger () override | |
| Public Member Functions inherited from itk::simple::LoggerBase | |
| std::string | GetName () const override |
| LoggerBase ()=default | |
| void | SetName (const std::string &n) override |
| ~LoggerBase () override | |
| Public Member Functions inherited from itk::simple::ObjectOwnedBase | |
| ObjectOwnedBase ()=default | |
| virtual | ~ObjectOwnedBase ()=0 |
| Public Member Functions inherited from itk::simple::NonCopyable | |
| NonCopyable (const NonCopyable &)=delete | |
| NonCopyable & | operator= (const NonCopyable &)=delete |
Private Attributes | |
| itk::OutputWindow * | m_OutputWindow { nullptr } |
Additional Inherited Members | |
| Static Public Member Functions inherited from itk::simple::LoggerBase | |
| static ITKLogger | GetGlobalITKLogger () |
| Protected Member Functions inherited from itk::simple::ObjectOwnedBase | |
| virtual size_t | AddObjectCallback (itk::Object *o, std::function< void()> onDelete) |
| Register an Object and a method to call on this object's destructor. More... | |
| ObjectOwnedBase (const ObjectOwnedBase &o) | |
| Copy Constructor. More... | |
| virtual size_t | RemoveObject (const itk::Object *) |
| virtual void | SetOwnedByObjects (bool o) |
| virtual bool | GetOwnedByObjects () const |
| virtual void | OwnedByObjectsOn () |
| virtual void | OwnedByObjectsOff () |
| Protected Member Functions inherited from itk::simple::NonCopyable | |
| NonCopyable ()=default | |
A class to hold itk::OutputWindows instances.
All "DisplayText" methods are forwarded to the held OutputWindow instance.
Neither the ownership nor callback functionality of the ObjectOwnedBase is supported.
Definition at line 110 of file sitkLogger.h.
|
override |
|
overridevirtual |
Reimplemented from itk::simple::LoggerBase.
|
overridevirtual |
Reimplemented from itk::simple::LoggerBase.
|
overridevirtual |
Reimplemented from itk::simple::LoggerBase.
|
overridevirtual |
Implements itk::simple::LoggerBase.
|
overridevirtual |
Reimplemented from itk::simple::LoggerBase.
|
default |
| itk::simple::SITK_FINAL::ITKLogger | ( | const ITKLogger & | ) |
|
explicit |
|
overridevirtual |
Set the ITK logger to the ITK OutputWindow instance held.
Overrides the base functionality to eliminate the creation of the intermediary adaptor class.
Reimplemented from itk::simple::LoggerBase.
|
private |
Definition at line 146 of file sitkLogger.h.


| Package Load Key (PLK) |
ZJIRZMERQKM0MJEEJDJ2EHK1HIATQIR3 AMPJCMHQH1H8ICZPC1ZZHKCCAHHT ZCACJ9RTCADHMKKPJ3DAAQKAHREI JRACDACCQ0P0HPAKCTCMDCIQHQH8 DCCQAMJEH1QK |
| Company Name | Cosmos |
| Package Name | Cosmos Visual Studio Integration Package |
| Package GUID | {4cae44ed-88b9-4b7c-822b-b040f18fcee3} |
| PLK Version | 1.0 |
| Min. Visual Studio Version | Visual Studio 2008 |
| Minimum Product Edition | Standard |
More PLK Info:


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Simply reply to this email if you'd like to get in contact. If you've already sold this item, visit the listing page and click the "Sold" button. That will block future messages. Cheers, The Marketplace Team |


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Paco: A Coq Library for Parameterized Coinduction
Chung-Kil Hur, Georg Neis, Derek Dreyer and Viktor Vafeiadis
Max Planck Institute for Software Systems (MPI-SWS)
The Paco library provides a tactic called "pcofix", replacing Coq's primitive cofix and avoiding its syntactic guardedness checking of proof terms. We have found that pcofix yields clear performance and usability benefits, even on simple examples.
- Tutorial
- Further Examples
- Library Source
- Publications
-
The Power of Parameterization in Coinductive Proof.
In Proceedings of the 40th ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL 2013).
[paper: pdf] [coq script: zip]
-
The Power of Parameterization in Coinductive Proof.


Massachusetts Institute of Technology, Cambridge MA
S.B. in Physics, 2006
S.B. in Brain & Cognitive Sciences, 2006
Honors & awards
NSF Ideas Machine 2026 Top 100 Idea
NSF INSPIRE Award
NIH/NIGMS Maximizing Investigators' Research Award
Genomeweb Young Investigator
National Academy of Sciences / Kavli Foundation Frontiers of Science Fellow
Keystone Symposia NSF Scholarship
James S. McDonnell Foundation Postdoctoral Fellowship Awards in Studying Complex Systems
Sage Congress Young Investigator Award
Keystone Symposia Future of Science Fund Scholarship
Stanford School of Medicine Excellence in Teaching Award
National Defense Science and Engineering Graduate Fellowship
National Science Foundation Graduate Fellowship
Department of Homeland Security Graduate Fellowship
Stanford University Translational Medicine Scholarship
Stanford University Graduate Fellowship
MIT Phi Beta Kappa
MIT Sigma Pi Sigma
MIT Department of Brain & Cognitive Sciences Award for Outstanding Academics
Professional experience
Department of Genetics & Genomic Sciences, Mount Sinai School of Medicine, New York NY, 2014–present
Fellow
Developed comprehensive computational models of health and disease.
Department of Bioengineering, Stanford University, Stanford CA, 2007–2014
Research Assistant to Prof. Markus Covert
Developed the first comprehensive "whole-cell" computational model. Developed a novel hybrid mathematical framework. Assembled a new molecular biology database. Designed and integrated sub-models of 28 cellular processes. Developed novel algorithms for parameter estimation. Constructed new tools for exploratory data analysis. Conducted a forward genetic screen to validate the model. Investigated the molecular determinants of M. genitalium growth and division to discover new biology. Published work in Cell and Bioinformatics. Mentored several undergraduate and graduate students.
Department of Brain & Cognitive Sciences, MIT, Cambridge MA, Spring 2006
Research Assistant to Prof. Jim DiCarlo
Helped develop novel assistive surgical technology to support visual system research in non-human primates. Developed a device that detects the 3-D localization of implanted electrodes and fiducial markers in rhesus monkeys using two pairs of x-ray sources and detectors. Integrated x-ray hardware into an existing surgical systems. Implemented hardware control and image acquisition and processing software. Technology was published in J Neurophysiology.
Department of Brain & Cognitive Sciences, MIT, Cambridge MA, Summers 2004–05
Research Assistant to Prof. Michale Fee
Developed novel assistive surgical technology to support systems neuroscience research of learning and memory in song birds. Designed and constructed technology that guides the localization of electrode implantation in songbirds. Integrated technology into existing experimental protocols.
Research Assistant to Dr. Adolfas Gaigalas
Improved fluorescence measurement techniques by modulating excitation to reduce quenching. Integrated modulation hardware into an existing imaging system.
Neuroscience Division, Walter Reed Army Institute of Research, Forest Glen MD, Summers 2001–02
Research Assistant to Dr. Richard Bauman
Evaluated the neuroprotective efficacy of pharmaceuticals against trauma.  Quantitated neuroprotective efficacy using cognitive (Morris water maze) and vestibulomotor (beam-balance and narrow beam-walk) tasks.
Publications, proceedings, books, and other writings
Co-Director, Genetics and Data Science Multidisciplinary Training Area, Mount Sinai, Mar 2020–present
Member, Quantitative Biology Curriculum Committee, Mount Sinai, Mar 2020–present
Organizer, Whole-Cell Modeling Summer School, Barcelona SP, Apr 2019
Lecturer, International Synthetic & Systems Biology Summer School, Siena IT, Jul 2018
Lecturer, Building minimal cells Workshop, Bordeaux FR, Mar 2018
Organizer, Whole-Cell Modeling Summer School, Barcelona SP, Sep 2017
Keynote speaker, Seattle Modeling Workshop, Seattle WA, May 2016
Organizer, Whole-Cell Modeling Summer School, Barcelona SP, Apr 2016
Organizer, Introduction to multi-algorithm whole-cell modeling, Paris FR, Mar 2016
Lecturer, Advances in Systems and Synthetic Biology Workshop, Evry FR, Mar 2016
Instructor, Whole-Cell Modeling Standards Workshop, Rostock GR, Mar 2015
Presented lecture on whole-cell modeling methods. Worked with students to develop and integrate sub-models of a new integrative whole-cell model.
Lecturer, Systems Biology and Systems Medicine School, Lake Como School of Advanced Studies, Como IT, Sep 2014
Presented lecture on integrative computational models.
Program assistant, Stanford Summer Research Program/Amgen Scholars Program, Stanford CA, Summer 2012
Led professional development workshops for undergraduate students focused on oral and poster presentations, CVs/resumes, and graduate school and fellowship applications.
Teaching Assistant, MCP 256: How cells work, Stanford University, Stanford CA, Spring 2008
Led in-class discussions. Tutored students. Created assignment solutions and evaluated assignments. Awarded the Stanford School of Medicine Excellence in Teaching Award to Biosciences Graduate Students.
Tutor, 8.01X: Electricity & Magnetism, MIT, Cambridge MA, Spring 2003
Reviewed course content and assignments with students.
Developer, MasteringPhysics CyberTutor Project, MIT, Cambridge MA, Spring 2003
Developed interactive online tutorials and problems for introductory physics courses.
Outreach
Mentor, Stanford Bioscience Student Association Mentoring Program, 2012–2013
Volunteer, Humanimal Connection, San Mateo CA, 2010–2013
Volunteer, MIT Educational Council, Cambridge MA, 2008–2012
Mentor, Stanford Medical Youth Science Program, Stanford CA, 2007–2011
Mentor, Stanford University Pre-Grad/Pre-Med Mentoring Program, Stanford CA, 2007–2008
Mentor, Stanford University Minority Medical Alliance Mentorship Program, Stanford CA, 2007
Volunteer, Recording for the Blind & Dyslexic, Cambridge MA, 2005


1 Samuel 11:13
And Saul said, There shall not a man be put to death this day: for to day the LORD hath wrought salvation in Israel.


Thanks to Mike for providing his notes and slides. Mike walked us through some work he’s done lately with offline apps. Really great stuff, Mike!
Agenda
- Gooseberry
- Coconut
- Offline Apps
- Blockspring
- Dropbox SDK
Gooseberry
- Collect Data via Interactive SMS
- Ruby Sinatra + CouchDB
- Zanzibar: Health Clinics report new Malaria Cases
- Kenya: Registers attendees eventually sends them money
Coconut
Beyond Collecting Data
Architecture
- HTML5 Cloud Backed Offline Application
- CouchDB in the Cloud (HTTP Server, NOSQL Database)
- PouchDB (used to be CouchDB) on the client
Normal HTML 5 App
- Backbone for MVC
- JQuery Mobile for layout
- Data Collection in the field
- PouchDB for local storage and cloud syncing
- Data Reporting from the cloud
- CouchDB (sometimes a bit of Ruby too)
Coconut Data Structures
- All Data are JSON documents
- Data are mostly Questions or Results
Questions
"_id": "Household",
"questions": [
{
"id": "531",
"label": "Malaria Case ID",
"type": "text"
},{
"id": "401",
"label": "Head of Household Name",
"type": "autocomplete from previous entries"
}, {
"autocomplete-options": "window.ShehiaOptions = GeoHierarchy.allUniqueShehiaNames()",
"id": "398",
"label": "Shehia",
"repeatable": "false",
"type": "autocomplete from code",
"validation": "($('#398').val('');return 'Shehia ' + value + ' is not valid. Please try again.' ) unless _.contains(window.ShehiaOptions, value)"
}
...
Results
{
"_id": "a50615950003474e6f749b3b2000049b",
"_rev": "19-7a75c672aeccc1a13b289586bf1e557b",
"createdAt": "2012-01-03 23:59:46",
"lastModifiedAt": "2012-01-04T00:04:26+00:00",
"question": "Facility",
"MalariaCaseID": "1016807",
"FacilityName": "KIJINI",
"Shehia": "KIJINI 1",
"user": "0773922266",
"collection": {
"_id": "a50615950003474e6f749b3b2000049b",
"_rev": "19-7a75c672aeccc1a13b289586bf1e557b",
"createdAt": "2012-01-03 23:59:46",
"lastModifiedAt": "2012-01-04T00:04:26+00:00",
"question": "Facility",
"MalariaCaseID": "106807",
"FacilityName": "KIJINI",
"Shehia": "KIJINI 1",
"user": "0773922266",
"collection": "result",
"DateofPositiveResults": "2015-03-26",
"ParasiteSpecies": "PF",
"ReferenceinOPDRegister": "9999",
"FirstName": "kombo",
"MiddleName": "faki",
"LastName": "mcha",
"Age": "25",
"Village": "zingani",
"ShehaMjumbe": "hassamn mcha",
"HeadofHouseholdName": "kombo faki mcha",
"ContactMobilepatientrelative": "9999",
"TreatmentGiven": "act",
"IfYESlistALLplacestravelled": null,
"CaseIDforotherhouseholdmemberthattestedpositiveatahealthfacility": null,
"CommentRemarks": null,
"complete": "true",
"savedBy": "0773922266",
"AgeinMonthsorYears": "Years",
"Sex": "Male",
"TravelledOvernightinpastmonth": "No",
"Hassomeonefromthesamehouseholdrecentlytestedpositiveatahealthfacility": "No"
}
Offline Apps
- Add a file called manifest.appcache at the root of your web application
- A request for any of the URLS will start by trying to get the manifest.appcache
- FAILS => cached version used.
- SUCCEEDS and manifest.appcache file SAME => cached version used.
- SUCCEEDS and manifest.appcache file DIFFERENT => everything is reloaded
Another member of the group piped up. “Hi, I’m ApplicationCache,” he said, as he reached over to shake Dev’s hand. “I turn your offline experience from sucks-ass, to success. Just one extra file, and bosh! It works. No fuss, no ‘scripting’ necessary.” Yes, he did finger-quotes while saying ‘scripting.’ I’m gritting my teeth at this point, because I know he’s greatly exaggerating his abilities and the others don’t see it.
I felt bad for not doing anything on that completely real evening. It’s painful to see articles that praise ApplicationCache’s ease of use, written by people who’ve clearly only met him in passing.
Now, I don’t mean he’s useless or should be avoided, you just have to be very careful when and how you work with him. If you get it wrong, the douchebaggery oozes through onto the end user. By reading through my own painful experiences with AppCache, you’ll know what to expect from AppCache and how to deal with it.
http://alistapart.com/article/application-cache-is-a-douchebag
except this:
https://github.com/gr2m/appcache-nanny
CACHE MANIFEST
/
/js/app.min.js
/js/libs.min.js
/css/style.min.css
/index.html
NETWORK:
*
http://*
FALLBACK:
/ /
# VERSION 5asd1s
<html>
<meta charset='utf-8'>
<meta name="apple-mobile-web-app-capable" content="yes">
<meta name="mobile-web-app-capable" content="yes">
<head>
<title>Coconut</title>
Vision
- Deployment Script with Docker
- Merge question format of Gooseberry/Coconut
- Enable data capture for any Coconut form via SMS or Tablet
- UI Refactor
- Fork server side reporting and client side data collection UI
- Strip out JQuery Mobile
- Use a bootstrap template
- Consider Elastic Search and Kibana as new basis for reporting
Blockspring
https://www.youtube.com/watch?v=UD3a_Eqj5ew
Dropbox SDK
access_token = "bHKasfYaEVYvAAANotRealTokenSoDontTryItOKkOBOeB1J3A5D2I0tQsIyg"
dropbox_client = DropboxClient.new access_token
csvs_required.each do |csv_required|
question_set = QuestionSet.new(csv_required["question_set"])
filename = csv_required.values.join("--")+".csv"
File.open(filename, "w") do |file|
file.write question_set.csv_header + "\n"
file.write question_set.rows(csv_required["start_date"],csv_required["end_date"])
end
dropbox_client.put_file filename,open(filename),true
end


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Championing And Celebrating Our Female Committee Members


Cannot play HEVC H.265 video files on your Samsung Galaxy K zoom? If so, you may have interest in this post. We write it to help those who are having issues playing HEVC/H.265 files on Samsung Galaxy K zoom. If it is just right what you are looking for, keep reading to learn a way of making HEVC/H.265 videos playable on Samsung Galaxy K zoom.
The Samsung Galaxy K zoom runs Android 4.4 and is powered by a 2430mAh non removable battery. It measures 137.50 x 70.80 x 16.60 (height x width x thickness) and weigh 200.00 grams.
Founded back in 1969 as Samsung Electric Industries, Suwon, South Korea-headquartered Samsung Electronics today makes everything from televisions to semiconductors. It released its first Android smartphone in 2009, and can be credited with the launch of the first Android tablet back in 2010. The company is among the biggest players in the smartphone market in the world. It has recently developed smartphones running Tizen OS, as an alternative to its Android-based smartphones.
Why convert HEVC/H.265 video for Samsung Galaxy K zoom?
Depending on hardware, software, video/audio formats/codecs, frame rate, bitrate, file sizes and much more, your device will have different performances playing an HEVC/H.265 video. If you have a high-end device that supports HEVC hardware decoder, you don’t need to do this at all. But if your Samsung Galaxy K zoom struggles to play HEVC videos, you will need to convert them to a format that is compatible with your Samsung Galaxy K zoom first. That’s where an HEVC to Samsung Galaxy K zoom converter comes in. We demonstrate how to process file conversion below:
Part 1:
How to convert hevc videos for Samsung Galaxy K zoom on Windows?
Part 2:
How to convert hevc videos for Samsung Galaxy K zoom on Mac?
[pt_view id="2e16a40sux"]
Part 1. How to convert hevc videos for Samsung Galaxy K zoom on Windows?
To convert hevc videos for Samsung Galaxy K zoom playback on Windows, do as below:
Step 1: Import video files
Click “Add File” to load video files that you want to convert into this program.
Step 2: Select output format for Samsung Galaxy K zoom
Click "Profile" to select
"Samsung" > "Samsung Galaxy S5(*.mp4)" as output format. This format profile will ensure a good performance while playing with Galaxy K zoom.
Tips:
If necessary, you can click "Settings" button to modify video and audio parameters like encoder, resolution, frame rate, bitrate, aspect ratio, sample rate, and audio channels. You can also “Enable 3D Settings” to add 3D effect to your source media.
Step 3: Click “Convert” to start hevc video to Samsung Galaxy K zoom conversion on Windows.
As soon as the conversion is complete, click “Open Folder” to get the generated
MP4 files that are suitable for playing on your Samsung Galaxy K zoom. No audio lost issues will occur any more.
Part 2. How to convert hevc videos for Samsung Galaxy K zoom on Mac?
To convert hevc videos for Samsung Galaxy K zoom playback on Mac, do as below:
Step 1: Import video files
Click “Add File” to load video files that you want to convert into this program.
Step 2: Select output format for Samsung Galaxy K zoom
Click "Profile" to select
"Samsung" > "Samsung Galaxy S5(*.mp4)" as output format. This format profile will ensure a good performance while playing with Galaxy K zoom.
Tips:
If necessary, you can click "Settings" button to modify video and audio parameters like encoder, resolution, frame rate, bitrate, aspect ratio, sample rate, and audio channels. You can also “Enable 3D Settings” to add 3D effect to your source media.
Step 3: Click “Convert” to start hevc video to Samsung Galaxy K zoom conversion on Mac.
As soon as the conversion is complete, click “Open Folder” to get the generated
MP4 files that are suitable for playing on your Samsung Galaxy K zoom. No audio lost issues will occur again.
Also read:
How do you play HEVC/H.265 files on Samsung Galaxy S8+?