BlocksKit 1.8.1 Reference
BlocksKit
Blocks in C and Objective-C are downright magical. They make coding easier and potentially quicker, not to mention faster on the front end with multithreading and Grand Central Dispatch. BlocksKit hopes to facilitate this kind of programming by removing some of the annoying – and, in some cases, impeding – limits on coding with blocks.
BlocksKit is a framework for OS X Lion and newer and a static library for iOS 5 and newer.
Installation
BlocksKit can be added to a project using CocoaPods. We also distribute a static library build.
Library
- Download a release of BlocksKit.
- Move libBlocksKit.a and Headers to your project’s folder, preferably a subfolder like “Vendor”.
- In “Build Phases”, Drag libBlocksKit.a into your target’s “Link Binary With Libraries” build phase.
- In the build settings of your target or project, change “Other Linker Flags” to
-ObjC -all_load
. Make sure your app is linked with CoreGraphics, Foundation, MessageUI, and UIKit. - Change (or add) to “Header Search Paths” the relative path to BlocksKit’s headers, like
$(SRCROOT)/Vendor/Headers
. - Insert `#import <BlocksKit/BlocksKit.h>`` in your project’s prefix header.
Documentation
An Xcode 4 compatible documentation set is available using this Atom link. You may also view the documentation online.
License
BlocksKit is created and maintained by Pandamonia LLC under the MIT license. The project itself is free for use in any and all projects. You can use BlocksKit in any project, public or private, with or without attribution – though we prefer attribution! It helps us.
Unsure about your rights? Read more.
Individual credits for included code exist in the header files and documentation. We thank them for their contributions to the open source community.
Class References
Category References
- MFMailComposeViewController(BlocksKit)
- MFMessageComposeViewController(BlocksKit)
- NSArray(BlocksKit)
- NSCache(BlocksKit)
- NSDictionary(BlocksKit)
- NSIndexSet(BlocksKit)
- NSInvocation(BlocksKit)
- NSMutableArray(BlocksKit)
- NSMutableDictionary(BlocksKit)
- NSMutableIndexSet(BlocksKit)
- NSMutableOrderedSet(BlocksKit)
- NSMutableSet(BlocksKit)
- NSObject(A2BlockDelegate)
- NSObject(A2DynamicDelegate)
- NSObject(BKAssociatedObjects)
- NSObject(BlockObservation)
- NSObject(BlocksKit)
- NSOrderedSet(BlocksKit)
- NSSet(BlocksKit)
- NSTimer(BlocksKit)
- NSURLConnection(BlocksKit)
- UIActionSheet(BlocksKit)
- UIAlertView(BlocksKit)
- UIBarButtonItem(BlocksKit)
- UIControl(BlocksKit)
- UIGestureRecognizer(BlocksKit)
- UIPopoverController(BlocksKit)
- UIView(BlocksKit)
- UIWebView(BlocksKit)


Bug summary:
Task's time range disappears after moving it to the current task
Observed Behavior (a description of what happened with the app):
After creating a task and adding a time range for it, moving the time range to the current task makes it disappear from the list of task's time ranges. Note: The app behaves correctly when the time range is moved to another task. The time range disappears from the current task's time ranges and appears under the other task.
Expected Behavior (a description of what you expected to happen):
The time range should still appear on the list of task's time ranges after moving it to the current task.
Steps to Reproduce (the steps to reproduce the problem):
1. Open the Time Tracker application
2. Click "OK" on the pop up window
3. Open the top right menu and click on "Add task" to add a new task
4. Enter the new task name and click on "ADD TASK"
5. Right click on the newly created task on the task list and click on "Show Times"
6. Open the top right menu and click on "Add a new time range"
7. Modify the end date or time to make it greater than the start time
8. Click on "OK" on the "Edit Time" page
9. Right click on the newly created time range on the Task Times list and click on "Move Time"
10. Select the task created in step 4
Additional information:
There seems to be another related bug. After creating a new task and clicking on it in the list, a time range is automatically added for it, and the app crashes after clicking on this time range. Steps to Reproduce: 1. Open the Time Tracker application 2. Click "OK" on the pop up window 3. Open the top right menu and click on "Add task" to add a new task 4. Enter the new task name and click on "ADD TASK" 5. Click on the newly created task on the tasks list 6. Right click on the new task and click on "Show Times" 7. Click on the one existing time range (automatically created)
Attachments:


Description of exercises:
- All exercises are done with mask, snorkel and fins.
- Leg exercises can be done with flutter or dolphin kick. Arm and leg exercises together are done with flutter kick.
- All rest periods (2 min, 1 min & 30 sec) are done on the side of the pool i.e. climb out and rest. 15 sec rest periods are done in the water.
- "Counting lines" is done by touching the lines with your hand.
A. 1 line under (legs), 1 line surface (arms & legs)
B. 2 lines under (legs), 2 lines surface (arms & legs)
- Up & Unders
- Unders
Week 1
- 1 x 200m *** warm-up - crawl (arms & legs) 60%
Rest 1 min.
- 4 x 50m *** surface sprints - crawl (arms & legs; rest 1 min between lengths) 100%
Rest 2 mins
- 8 x 25m *** counting lines (1 line under, 1 line surface, no rest between lengths) 80%
Rest 1 min
- 4 x 25m *** surface sprints - crawl (arms & legs; rest 30 sec between lengths) 100%
Rest 1 min
- 8 x 25m *** up and unders (12.5m under, legs + 12.5m surface, crawl; no rest between lengths) 80%
Rest 1 min
- 4 x 25m *** surface sprints (legs only; 30 sec rest between lengths) 100%
Rest 1 min
- 6 x 25m *** unders (rest 30 sec between lengths) 80%
Rest 1 min
- 4 x 25m *** surface kicking (no arms; no rest between lengths) 60%
Week 2
- 1 x 200m *** warm-up - crawl (arms & legs) 60%
Rest 1 min.
- 4 x 50m *** surface sprints - crawl (arms & legs; rest 1 min between lengths) 100%
Rest 2 mins
- 8 x 25m *** counting lines (2 lines under, 1 line surface, no rest between lengths) 80%
Rest 1 min
- 4 x 25m *** surface sprints - crawl (arms & legs; rest 30 sec between lengths) 100%
Rest 1 min
- 8 x 25m *** up and unders (12.5m under, legs + 12.5m surface, crawl; no rest between lengths) 80%
Rest 1 min
- 4 x 25m *** surface sprints (legs only; 30 sec rest between lengths) 100%
Rest 1 min
- 6 x 25m *** unders (rest 30 sec between lengths) 80%
Rest 1 min
- 4 x 25m *** surface kicking (no arms; no rest between lengths) 60%
Week 3
- 1 x 200m *** warm-up - crawl (arms & legs) 60%
Rest 1 min.
- 4 x 50m *** surface sprints - crawl (arms & legs; rest 1 min between lengths) 100%
Rest 2 mins
- 8 x 25m *** counting lines (1 line under, 1 line surface, no rest between lengths) 80%
Rest 1 min
- 4 x 25m *** surface sprints - crawl (arms & legs; rest 30 sec between lengths) 100%
Rest 1 min
- 8 x 25m *** up and unders (12.5m under, legs + 12.5m surface, crawl; no rest between lengths) 80%
Rest 1 min
- 4 x 25m *** surface sprints (legs only; 30 sec rest between lengths) 100%
Rest 1 min
- 6 x 25m *** unders (rest 30 sec between lengths) 80%
Rest 1 min
- 4 x 25m *** surface kicking (no arms; no rest between lengths) 60%
Week 4
- 1 x 200m *** warm-up - crawl (arms & legs) 60%
Rest 1 min.
- 4 x 50m *** surface sprints - crawl (arms & legs; rest 1 min between lengths) 100%
Rest 2 mins
- 10 x 25m *** counting lines (2 lines under, 1 line surface, no rest between lengths) 80%
Rest 1 min
- 6 x 25m *** surface sprints - crawl (arms & legs; rest 30 sec between lengths) 100%
Rest 1 min
- 10 x 25m *** up and unders (12.5m under, legs + 12.5m surface, crawl; no rest between lengths) 80%
Rest 1 min
- 6 x 25m *** surface sprints (legs only; 30 sec rest between lengths) 100%
Rest 1 min
- 10 x 25m *** unders (rest 30 sec between lengths) 80%
Rest 1 min
- 4 x 25m *** surface kicking (no arms; no rest between lengths) 60%
Week 5
- 1 x 200m *** warm-up - crawl (arms & legs) 60%
Rest 1 min.
- 4 x 50m *** surface sprints - crawl (arms & legs; rest 1 min between lengths) 100%
Rest 2 mins
- 10 x 25m *** counting lines (2 lines under (100%), 2 lines surface (80%), no rest between lengths)
Rest 1 min
- 6 x 25m *** surface sprints - crawl (arms & legs; rest 15 sec between lengths) 100%
Rest 1 min
- 10 x 25m *** up and unders (12.5m under, legs + 12.5m surface, crawl; no rest between lengths) 80%
Rest 1 min
- 2 x 25m *** surface sprints (legs only; 15 sec rest between lengths) 100%
Rest 1 min
- 10 x 25m *** unders (rest 15 sec between lengths) 80%
Rest 1 min
- 4 x 25m *** surface kicking (no arms; no rest between lengths) 60%
Week 6
- 1 x 200m *** warm-up - crawl (arms & legs) 60%
Rest 1 min.
- 4 x 50m *** surface sprints - crawl (arms & legs; rest 1 min between lengths) 100%
Rest 2 mins
- 10 x 25m *** counting lines (2 lines under (100%), 2 lines surface (80%), no rest between lengths)
Rest 1 min
- 6 x 25m *** surface sprints - crawl (arms & legs; rest 15 sec between lengths) 100%
Rest 1 min
- 10 x 25m *** up and unders (12.5m under, legs + 12.5m surface, crawl; no rest between lengths) 80%
Rest 1 min
- 2 x 25m *** surface sprints (legs only; 15 sec rest between lengths) 100%
Rest 1 min
- 10 x 25m *** unders (rest 15 sec between lengths) 80%
Rest 1 min
- 4 x 25m *** surface kicking (no arms; no rest between lengths) 60%
Week 7
- 1 x 200m *** warm-up - crawl (arms & legs) 60%
Rest 1 min.
- 10 x 25m *** counting lines (1 line under (100%), 1 line surface (80%), no rest between lengths)
Rest 1 min
- 8 x 25m *** surface sprints - crawl (arms & legs; rest 15 sec between lengths) 100%
Rest 1 min
- 12 x 25m *** up and unders (12.5m under, legs + 12.5m surface, crawl; no rest between lengths) 80%
Rest 1 min
- 4 x 25m *** surface sprints (legs only; 15 sec rest between lengths) 100%
Rest 1 min
- 10 x 25m *** unders (rest 15 sec between lengths) 80%
Rest 1 min
- 4 x 25m *** surface kicking (no arms; no rest between lengths) 60%
So... what are your waiting for? GOOD LUCK!
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Ocean [ba46], ocean, in Crystal Sea
Last updated Turn #41
Ocean [ba46], ocean, in Crystal Sea
------------------------------------------------------------------------
4: Fast Winds [ak2q], ship, 2 hulls, 1 rowing port, 6 sails, 5% damaged,
4: arrived from Ocean [az46], owner:
4: Dorothy [v1b], Pen, with ten sailors
4: Akius The Great [s1t], Pen
5: Fast Winds [ak2q], ship, 2 hulls, 1 rowing port, 6 sails, 5% damaged,
5: departed for Ocean [ba47].
6: Hungry looking birds circle overhead.
Routes leaving Ocean:
North, to Ocean [az46], The Inner Sea, 6 days
East, to Ocean [ba47], 6 days
South, to Ocean [bb46], 6 days
West, to Ocean [ba45], 6 days


From:Dr.Faroq Uztaz(Regional Director) Ghana Commercial Bank Accra-Ghana Tel:00233 24 480 353. Subject:Request for Assistance! Attn:Director, I wish this my proposal will not come to you as a surprise. I am Dr.Faroq Uztaz, a Regional Director with Ghana Commercial Bank with regional office in Accra,Ghana. We had a foreign client (Mohamed Mohd Salaheldin)who deposited a huge sum of amount, US$8.5million(Eight Million Five Hundred Thousand United States Dollars) with our bank. Unfortunately,this client was among the victims of EGYPTAIR FLIGHT NO.990 that crashed on the 31-10-1999in U.S.A. However, they were given a ceremonial mass burial near the crash site.Confirmable from the below websites: www.cnn.com/us/9911/02/egyptair990.list/index.html www.fas.org/irp/news/1999/10/ www.ntsb.gov/events/EA990/default.htm but, since then we have not had any body to come for the claims as the next of kin. A sitaution I have monitored closely with my position in the bank. Now, having monitored this deposit and managed it over the years before his death, and hence nobody has showed up as the next of kin for the past four years , I have removed the file to my "private vault". I now solicit for your assistance to present you as the next of kin as every other arrangement has being concluded by me and I am only waiting for a foreigner to enable me move the funds to his account. This does not have any risk attached to it as all the internal documentations would be handled by me and every loop holes sealed off. I therefore request you to confirm your interest by a return message and I will furnish you with the full details and what to do concerning this deal. What you stand to gain(%)would be discussed and it is negotiable before the deal commences. Believing to hear from you soonest. Kind regards, Dr.Faroq Uztaz. N:B:If interested please send your personal telephone and fax numbers. Thanks for your future assistance.


USGS Data Retrieval
It took me a few times to get this right - the interface of the USGS website is a rabbit hole of buttons and options for data retrieval. It’s not so hard to get the data you’re interested in, but pay close attention because it’s easy to do the wrong thing. Probably the easiest way is to use the dataRetrieval
package. The last commits on their github are from 2 months ago, so it’s pretty up-to-date.
To use this package, you need to know a few things about the structure of the data. Each USGS streamflow station has a number - you’ll need to know the number for the station you want. There’s also a number associated with each measured value; 00060
for discharge in feet per second, 00065
for gauge height in feet, 00010
for temperature in degrees celcius, and many more. The last critical thing to know is the date range of the data you’re interested in.
- Station Number
- Parameter Code
- Date Range of Interest
Here’s an example from the documentation:
#install.packages("dataRetrieval") #uncomment to install the package
library(dataRetrieval)
# Choptank River near Greensboro, MD:
siteNumber <- "01491000"
parameterCd <- "00060" # Discharge
startDate <- "2009-10-01"
endDate <- "2012-09-30"
discharge <- readNWISdv(siteNumber,
parameterCd, startDate, endDate)
Here’s what the resulting data frame looks like:
The fifth column is a quality code - A stands for approved for release by the USGS.
Another notable argument to the readNWISdv
function is statCd
. This allows you to request daily data and specify the statistic used. For example, you can request the daily maximum, mean, median, or total.
Pretty simple, right?
There are some other handy functions and options in this library. You’ll notice that the colunm names aren’t really descriptive of the data. You can use another function from the package to rename them. Try this:
discharge <- renameNWISColumns(discharge)
names(discharge)
## [1] "agency_cd" "site_no" "Date" "Flow" "Flow_cd"
That can clean things up a lot - especially if you’re importing many parameters.
library(ggplot2)
ggplot(discharge, aes(x=Date, y=Flow)) + geom_point(alpha = 0.4)
What I am interested is the streamflow data, so this is as far as I need to go. You can also import different kinds of USGS data using other functions of the same package. It’s a treasure trove! Check out the documentation to get the full scope of its powers.
I also came across another package called waterData
that can do the same retrieval and maybe some more analysis on the data. I haven’t looked further into this, but the last commits to their github are from 3 years ago, so I choose the dataRetrieval
package.
Now I’ll let you in on the less fun bit, which is the way I originally tried to download the data locally then upload to R. I started out fumbling around the website trying to find the gauge closest to the site I’m interested in. There’s an interactive map on the homepage; you click on a state to get to a more refined map and click around some more to find the gauge you want.
 This looks good, but is not.
I chose the tab-seperated option; After a lengthy wait a new tab with the output opened in the browser - so no file download. I guess I could have copied and pasted all of that into a text file, but I decided to search for a way to actually download the file.
I found a USGS primer on dowloading data (always read the instructions first!), which took some different turns than the path I took previoulsy. The user interface is difficult to navigate and not intuitive, but it’s a great resource for data. I won’t go through the whole process, because it’s mostly just clicking on the right spot and choosing your desired options, but here is the most important part:
There are still extra steps of choosing the options in the website, downloading the data, then reading it into R. This is the code I used to read the data once I had downloaded it as a text file and renamed it “streamflow”. If I were to go back, I would not do it this way, but I guess it doesn’t require downloading a new package and is fine if you’re not dowloading a lot of data.
library(tidyverse)
streamflow <- read.table("streamflow", skip = 32) #the first 32 lines are metadata
colnames(streamflow) <- c("agency", "site_no", "date", "time", "timezone", "Flow", "quality_code")
#discharge is in cubic feet per second, quality code A means approved
streamflow$date <- as.Date(streamflow$date)
ggplot(streamflow, aes(x=date, y=Flow)) + geom_point(alpha=0.4)
Hope this info helps you avoid wasting time like I did on my first try! Do you know of a better way to get the data into R? Did you encounter any pitfalls?


Nutmeg. I first read about it in the appendix of Naked Lunch. I'd never got really stoned before but I liked a drink, and it sounded interesting. The first time, I ate a whole tub (25g), didn't feel any effects that evening, and had a horrible time the next morning. I had to go to my psychiatrist and I felt like I'd downed two pints of vodka and could barely see. I vowed never to try it again.
A year later I got into pot, and found that smoking/snorting small amounts of nutmeg (a gram or two) did 'something'. I started mixing it into my skunk, which I used to smoke every day, with some strange results. I got incredibly stoned in a strange, fuzzy way. The sharpness of perception I normally felt with pot was gone, and when the weed wore off, this strange, detached feeling lingered on. I woke up one morning in mental agony. I wasn't stoned or hallucinating, but there was a chair by the bed, and I felt that it was 'staring' at me. I was depressed and feeling very strange. Time was passing slowly, and being alive felt excruciating for no reason. For weeks I was scared of walking down the road, as I thought cars were going to try to run me down. I put this down to pot and gave up.
A few months later, mostly recovered, I finally found the best way to take nutmeg: eating it. I was need of getting stoned, having cut cannabis out of my life, and I ate about 10g of the ready-ground stuff. Like the last time I ate it, nothing happened until the next morning, except that this time it was great. I felt utterly joyful and at peace with the world. I lay around all day, just relaxed and feeling good, and very 'drunk' too. Once the effects wore off, I felt a distinct come-down; I was quite miserable and irritable. This passed in a day or two.
Finally it occured to me to eat it in the morning. It was one of the best experiences of my life. I ate two fresh nutmegs at 7am (bear in mind that I am skinny and not very tolerant of most drugs, hence the low dose). An hour later I was being driven to see my friends. Sitting in the car, I felt an enormous sense of joy at being alive. I was happy just sitting, and the world looked more beautiful than anything I'd ever seen. I lay in the sun with my friends for a while.
At about 10am, intoxication started to set in slowly. I felt a bit drunk at first. The colour green changed slightly in way I can't describe. Gradually this drunk/stoned feeling intensified over the next three hours. We saw a film, not a very good one; no-one enjoyed it except me. The experience by then was like marijuana, but less intense, and MUCH happier. I ate and went home. Waiting at the bus stop, I started getting a bit nervous; I could hear people at the bus stop talking about me. I think I must have been imagining this; it was a bit like some paranoid experiences I've had with weed (though not as strong).
The next day, I was sober, but I still felt better than normal. Emotionally, I'm quite numb normally, but my feelings were more intense that day. I read another William Burroughs book (Junky), and enjoyed it. I felt more involved in the reading than I usually do. The intensified feelings included nervousness, and I did get quite scared going out; I was more aware of people looking at me and talking about me. A couple of times I felt sure that I heard strangers say my name. I came close to having a panic attack on the bus, something which I've not experienced since giving up pot.
In he following days I had return to my normal mood, and things felt more painful, though maybe only compared to my nutmeg high. The nervous (paranoid?) thoughts continued for another week.
It's a really fun drug, at least as good as pot; don't put off by the people who take too much, try small amounts (one or two whole nutmegs) and work up to a nice dose, bearing in mind that it can take as long as 5-6 hours to work, and that nutmegs vary in strength. Don't smoke it. However, I've been put off it by the after-effects, even though I only took sub-hallucinogenic doses. I've read information that suggests that myristicin is quite closely related to the methylenedioxyamphetamines (MMDA specifically), and therefore has a similar, and possibly permanent (the research into this is inconclusive) effect on serotonin in the brain. This would explain the after-effects of depression and anxiety (but not the paranoia if that's what I was experiencing). It's probably fine in healthy-minded people, but not me.
PS- I think I should add that I was on various different antidepressants when most of these trips took place.
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.


MicroPython license information¶
The MIT License (MIT)
Copyright (c) 2013-2017 Damien P. George, and others
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
 IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


I'll make this short as I am simply posting this report since there is scant information on the net about the combination of a strong opiate with a bit of MDMA.
I have never attempted a speedball, that is opiate+cocaine. I don't have any love for coke and that sounds a bit dangerous to me! Anyway, being the scientific experimenter that I am, I decided to go with two much more refined compounds: Dilaudid (hydromorphone) and MDMA.
The dilaudid was pure, not a pill. Precisely 4 mg of this substance was dissolved in a bit of sterile saline and an unmeasured amount of mdma was added (approximately 20 mg, 1/5 of a 100mg dose as judged by the ole eyball). This solution was injected IV. Time = 0
As compared to IV dilaudid, the mixture was a bit heavier in effect. The rush was not as pleasant, it seemed. My eyes were hard to keep open and dizziness was noted.
The rush was accompanied by an interesting tactile sensation. This was very pronounced, as I had a bit of sunburn on my back from the beach the day before. This sensation was not overly pleasant, pretty much neutral, and it did not last more than a few seconds.
The dizziness was quite pronounced when walking around, but this was alleviated by a tiny bong-hit. Pot usually messes up opiate highs, IMHO, but I wanted to get away from the dizziness and the MDMA made me want to smoke something (no cigarettes around). The pot helped with the dizziness, Time = 15 minutes.
I sat down for a moment to collect myself. My eyes were doing mild jittering, common with E. Overall, I didnít really feel all that lit up. I decided to have a bit more dilaudid since the 4mg dose was a light dose for fear of what might happen. 3 mg more dilaudid was injected sub-cutaneously (under the skin). T=25 min
The extra dilaudid was exactly what I needed. The effects picked up dramatically and I felt great. I felt good enough to CLEAN the kitchen! Very alert buzz with a little bit of eye jumping, but not too much. At this point it felt mainly like a dilaudid high, with maybe a bit of stimulation to go along with it. Movements with my arms and such feel a bit robotic and fine motorskills seemed a bit reduced. T=1hour
Was it worth it? Not really, I guess. Dilaudid by itself is pretty much the rolls-royce of opiates. It crosses my eyes badly enough by itself, and it seemed like the MDMA just made this worse. I can do without eye crossing, personally, so that aspect wasnít too great. Should I have taken more MDMA? I donít really know. The first 15 minutes just felt like ďintoxicationĒ more than a high. I wonít do this again, not really that great.
----------------------
On a side note, I did witness a friend of mine eat 150 mg of MDMA after dosing dilaudid about 30 minutes prior. He said it was fantastic as the MDMA hit, but it didnít last long and he was left feeling drained and plastered to the couch. This guy doesnít really get the social aspect of MDMA and usually hates the stuff, but the combination took away all the discomfort and left him in a good place.
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.


NZ
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Recognition as a leader in traffic ticket defense who continually fights new legal challenges


--- title: "Identifying data sources and gaps" permalink: "/topic/assessment/" layout: "topic" topic-tag: "assessment" show-resources: true ---
Countries can assess the data available to report on their indicators, map the data sources for each, and identify data gaps in order to get a full picture of how to report effectively on the SDGs. Such assessments can also help countries coordinate across data providers and identify where there may be multiple data sources that need to be reconciled.
A core tenet of the SDGs is the concept of ‘no one left behind’ — that sustainable development must help people regardless of gender, age, race, ethnicity, migratory status, income, disability, or geographic location. In order to make their data as useful as possible for targeted policy-making, countries may place additional emphasis on timeliness of data and disaggregation, where data is broken down into smaller subgroups for analysis.


This is a tested real world set up with VNET jails running IPFW and the host running both PF and IPFW. IPFW was set to allow all traffic to simplify this example.
After making the following changes make sure the host can restart cleanly.
For IPFW to work inside a jail set the securelevel property to “2”:
iocage set securelevel=2 UUID
The host
The host has the following relevant configuration needed to support VNET jails (these are relevant snippets only):
/etc/sysctl.conf
net.inet.ip.forwarding=1 net.link.bridge.pfil_onlyip=0 net.link.bridge.pfil_bridge=0 net.link.bridge.pfil_member=0 security.bsd.unprivileged_read_msgbuf=0 # This is only for routing tables if any # (do not create default routing tables for all FIB's) net.add_addr_allfibs=0
/etc/rc.conf:
cloned_interfaces="bridge0 bridge1" ifconfig_bridge0="addm em0 <IP_ADDRESS>/24 up" pf_enable="YES" pflog_enable="YES" firewall_enable="YES" firewall_type="open" iocage_enable="YES"
/etc/pf.conf:
# MACROS -------------------------------- if = "{" em0 "}" int_if = "{" bridge epair vnet "}" # TABLES -------------------------------- table <abusive_hosts> persist # don't filter on the loopback, VNET and bridge set skip on lo set skip on vnet set skip on bridge set skip on epair set loginterface em0 # TRAFFIC NORMALIZATION ------------------ scrub on $if all fragment reassemble # QUEUEING ------------------------------- # TRANSLATION ---------------------------- nat on em0 inet from ! em0 to any -> em0 # port forward http to jail (varnish) rdr on $if inet proto tcp to port 80 -> <IP_ADDRESS> port 80 # PACKET FILTERING ----------------------- # setup a default deny policy block log all block in quick from <abusive_hosts> # pass all traffic to and from the local network. pass out quick on $if from any to any modulate state # allow SSH and http/https pass log on $if proto { tcp udp } from any to any port { ssh http 445 } keep state # allow ping pass in inet proto icmp all icmp-type echoreq
The jail
/etc/rc.conf:
hostname=UUID cron_flags="$cron_flags -J 15" # Configure vnet0 ifconfig_vnet0="<IP_ADDRESS>/24" # Set default GW to point to bridge0 IP defaultrouter="<IP_ADDRESS>6" # Disable Sendmail by default sendmail_enable="NONE" sendmail_submit_enable="NO" sendmail_outbound_enable="NO" sendmail_msp_queue_enable="NO" # Run secure syslog syslogd_flags="-c -ss" # Set IPFW to allow all firewall_enable="YES" firewall_type="open"
/etc/resolv.conf:
nameserver <IP_ADDRESS> nameserver <IP_ADDRESS>


- Wang, R., Huang, S., Zhou, Y., Cai, Z. G. (2020). Chinese character handwriting: A large-scale behavioural study and a database. Behavior Research Methods, 52, 82–96.
- Cai, Z. G., & Zhao, N. (2019). The sound of gender: Inferring the gender of names in a foreign language. Journal of Cultural Cognitive Science, 3, 63-73
- Huang, J., Pickering, M. J., Chen, X., Cai, Z. G., Wang, S., & Branigan, H. P. (2019). Does language similarity affect representational integration? Cognition, 185, 83-90.
- Wei, H., Boland, J. E., Cai, Z. G., Yuan, F., & Wang, M. (2019). Persistent structural priming during online second-language comprehension. Journal of Experimental Psychology: Learning, Memory, and Cognition, 45(2), 349-359.
- Cai, Z. G., Wang, R., Shen, M. & Speekenbrink, M. (2018). Cross-dimensional magnitude interactions arise from memory interference. Cognitive Psychology, 106, 21-42.
- Cai, Z. G., & Vigliocco, V. (2018). Word processing. In J. T. Wixted & S. Thompson-Schill (Eds), The Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience, Volume 3: Language and Thought (4th edition) (pp.75-110). New York: Wiley.


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Jaguar's E-Pace Spied Getting Ready For A Minor Facelift
No big surprises here.
by Anthony KarrIn September this year, Jaguar released the E-Pace Checkered Flag Edition for the 2020 model year but don’t let the name trick you – the compact crossover is not nearing its production cycle and is here to stay. Not only that, but it’s the next in line for a refresh and these are the first spy photos depicting a trial prototype, spied by our photographers somewhere in the British Midlands.
Just like the facelifted F-Pace that was caught on camera exactly two months ago, its little brother is still wearing a full-body camouflage. Obviously, there are no modifications to the overall shape and proportion but the disguise hints at some revisions to the front fascia. More precisely, the E-Pace is most likely going to receive a new bumper and grille, as well as possibly different headlights.
Gallery: Jaguar E-Pace facelift new spy photos
At this point, the tweaks look less visible at the back but we are tempted to believe there will be revisions to the taillights' graphics. The entire rear bumper is covered in camouflage and there might be a few new touches to the lower part, where the twin-exhaust system is positioned together with the bumper diffuser.
Jaguar Working On New Models:
If you live in the United States, the E-Pace currently has a starting price of $38,900 for the base model. At this side of the big pond, the British crossover is available only with a 2.0-liter turbo gas unit, which delivers 246 horsepower (184 kilowatts) or 296 hp (221 kW) respectively, depending on the selected trim level. A nine-speed automatic channels the power to all four wheels and it’s probably a safe guess that these numbers won’t change drastically with the facelift.
The 2021 E-Pace will continue to be assembled at Magna Steyr’s Graz plant in Austria, as well as JLR’s Changshu factory in China. Expect to see the redesigned model towards the second half of 2020.
Photos: Automedia


GRAPHICS AND SOUND
RC BASIC uses a concept used in
sdlbasic and borrowed from AMOS on the Amiga about using virtual render
targets to draw on. In RC BASIC these virtual render targets are
called canvases. You must have at least one canvas open in order to
draw anything in a window. Look at the following:
WINDOWOPEN ( 0, "TEST WINDOW", 100, 100, 640, 480, 0 )
CANVASOPEN ( 0, 640, 480, 0, 0, 640, 480, 0 )
The above example is a simple example of opening a window
and canvas so you can start drawing. The first line opens a 640x480
window at coordinate (100, 100). The second line opens canvas 0 as a
640x480 render target and sets its viewport to 640x480 area starting at (0,
0) in the window. Now that a window and canvas are open you can start
drawing. Once you are done drawing you need to call UPDATE to display
what you have drawn. Look at the following:
WINDOWOPEN ( 0, "TEST WINDOW", 100, 100, 640, 480, 0 )
CANVASOPEN ( 0, 640, 480, 0, 0, 640, 480, 0 )
SETCOLOR( RGB ( 255, 255, 255 ) )
BOX ( 20, 20, 60, 60 )
UPDATE ( )
This example draws a white rectangle to the screen.
The first two lines are pulled from the previous example. The third
line sets the color used for drawing. The fourth line draws a
rectangle from coordinate (20, 20) to coordinate(60, 60). And the last
line shows what you just drew on the screen. RC BASIC allows a total
of 8 windows and 16 canvases with a total of 4096 images that can be loaded
in your program.
Sound in RC BASIC is handled the same way as canvases or
images. You can load a sound into slot and play the sound on a
selected channel. Look at the following:
LOADSOUND ( 0, "MYSOUND.WAV" )
PLAYSOUND ( 0, 1, 3 )
The above code will load a sound into sound slot 0.
The second line plays the sound in channel 1 for 3 loops. You can have
a total of 1024 sounds loaded in your program. For music and video you
can only load one and choose to play it or delete it from your programs
memory and load another. Look at the following:
LOADMUSIC ( "MYMUSIC.MP3" )
PLAYMUSIC ( -1 )
The above code loads a music track. The second line
tells the music to play infinitely. To change music tracks you would
first call DELETEMUSIC and then simply call LOADMUSIC again.


"The stock market is filled with individuals who know the price of everything, but the value of nothing." - Phillip Fisher
Wise Investing
"It's not how much money you make, but how much money you keep, how hard it works for you, and how many generations you keep
it for." - Robert Kiyosaki
Why Gamble?
"Investing should be more like watching paint dry or watching grass grow. If you want excitement, take $800 and go to Las
Vegas." - Paul Samuelson


{{ movie.Title }}
, {{ movie.Year }}
Released on: {{ movie.Released }} ({{ movie.Runtime }})
{{ movie.Plot }}
{{ movie.Director }}
{{ movie.Actors }}
{{ movie.Genre }}
Ratings:
IMDb Rating: {{ movie.imdbRating }}
Rotten Tomatoes: {{ movie.imdbRating }}
Watch Trailers! Get Subtitles! Hear Soundtracks! Buy this movie!
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CrimPapers
Articles published on 4 February 2017
On 4 February 2017, 11 new articles were published in 9 journals.
Studying Partner Violence to Understand Gender Motivations - Or Vice-Versa?
A Preliminary Investigation of the Psychological Inventory of Criminal Thinking Styles–layperson Edition–short Form
Introduction
Discerning Novel Value Chains in Financial Malware
Editorial Board and Publication Information
Exploring the Effects of Cctv Upon Fear of Crime: A Multi-Level Approach in Seoul
The Impact of Victim-Perpetrator Relationship, Reputation and Initial Point of Resistance on Officers' Responsibility and Authenticity Ratings Towards Hypothetical Rape Cases
Examining Crime on Campus: the Influence of Institutional Factors on Reports of Crime At Colleges and Universities by Shannon K. Jacobsen
Understanding How Incarceration Challenges Proximal Processes in Father-Child Relationships: Perspectives of Imprisoned Fathers
Comparing the Effectiveness of Henderson Instructions and Expert Testimony: Which Safeguard Improves Jurors’ Evaluations of Eyewitness Evidence?
Testing the Three- and Four-Factor Models of the Korean Version Pcl-R As Predictors of Two Antisocial Outcomes – Recidivism and Risk by Ji Seun Sohn, Phillip Lyons, Scott Menard, Soo Jung Lee


Just trying to get a bit of practice with skeleton. For additional features, see their documentation
There's even a 'code' tag!


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Fremont CoderDojo is fun place to learn to code games, websites, and apps for young people between age 7 and 17.
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October 30 Scratch and HTML5
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October 16 Introduction to Scratch
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§490:10-103.1 Inconsistent laws. If any other provision of law is inconsistent with this chapter, this chapter shall govern unless this chapter or such inconsistent provision of law specifically provides otherwise. [L 1965, c 208, §10-103.1; HRS §490:10-103.1]
Case Notes
Mentioned: 74 H. 1, 837 P.2d 1273.


| Total net profit | -2.25 | Gross profit | 4.04 | Gross loss | -6.29 |
| Profit factor | 0.64 | Expected payoff | -0.05 | ||
| Absolute drawdown | -2.25 | Maximal drawdown (%) | 3.08 (371.08%) | ||
| Total trades | 42 | Profit trades (% of total) | 20 (47.62%) | Loss trades (% of total) | 22 (52.38%) |
| Long positions (won %) | 10 (70.0%) | Short positions (won %) | 32 (40.63%) | ||
| Largest | profit trade | 0.55 | loss trade | -0.47 | |
| Average | profit trade | 0.2 | loss trade | -0.29 | |
| Minimum | profit trade | 0.04 | loss trade | -0.01 | |
| Maximum | take profit in pips | 50.7 | stop loss in pips | -43.1 | |
| Average | take profit in pips | 17.4 | stop loss in pips | -24.0 | |
| Minimum | take profit in pips | -0.9 | stop loss in pips | -4.0 | |
| Maximum | Reward-Risk | 4.8 | Duration in minutes | 5414 | |
| Average | Reward-Risk | 0.9 | Duration in minutes | 566.6 | |
| Minimum | Reward-Risk | 0.0 | Duration in minutes | 0 | |
| Maximum | consecutive wins (profit in money) | 6.0 (0.83) | consecutive losses (loss in money) | 8.0 (-2.06) | |
| Average | consecutive wins | 2.0 | consecutive losses | 3.0 |
| Total net profit | 0.65 | Gross profit | 1.63 | Gross loss | -0.98 |
| Profit factor | 1.66 | Expected payoff | 0.07 | ||
| Absolute drawdown | 0.12 | Maximal drawdown (%) | 0.86 (71.67%) | ||
| Total trades | 10 | Profit trades (% of total) | 7 (70.0%) | Loss trades (% of total) | 3 (30.0%) |
| Largest | profit trade | 0.55 | loss trade | -0.44 | |
| Average | profit trade | 0.23 | loss trade | -0.33 | |
| Minimum | profit trade | 0.1 | loss trade | -0.12 | |
| Maximum | take profit in pips | 40.9 | stop loss in pips | -43.1 | |
| Average | take profit in pips | 19.0 | stop loss in pips | -28.6 | |
| Minimum | take profit in pips | 7.5 | stop loss in pips | -9.1 | |
| Maximum | Reward-Risk | 1.5 | Duration in minutes | 1276.0 | |
| Average | Reward-Risk | 0.7 | Duration in minutes | 515.9 | |
| Minimum | Reward-Risk | 0.2 | Duration in minutes | 3.0 | |
| Maximum | consecutive wins (profit in money) | 6.0 (1.2) | consecutive losses (loss in money) | 2.0 (-0.86) | |
| Average | consecutive wins | 3.0 | consecutive losses | 2.0 |
| Total net profit | -2.9 | Gross profit | 2.41 | Gross loss | -5.31 |
| Profit factor | 0.45 | Expected payoff | -0.09 | ||
| Absolute drawdown | -2.9 | Maximal drawdown (%) | 3.61 (508.45%) | ||
| Total trades | 32 | Profit trades (% of total) | 13 (40.63%) | Loss trades (% of total) | 19 (59.38%) |
| Largest | profit trade | 0.5 | loss trade | -0.47 | |
| Average | profit trade | 0.19 | loss trade | -0.28 | |
| Minimum | profit trade | 0.04 | loss trade | -0.01 | |
| Maximum | take profit in pips | 50.7 | stop loss in pips | -36.0 | |
| Average | take profit in pips | 16.9 | stop loss in pips | -22.6 | |
| Minimum | take profit in pips | -0.9 | stop loss in pips | -4.0 | |
| Maximum | Reward-Risk | 4.8 | Duration in minutes | 5414.0 | |
| Average | Reward-Risk | 1.0 | Duration in minutes | 582.5 | |
| Minimum | Reward-Risk | Duration in minutes | 0.0 | ||
| Maximum | consecutive wins (profit in money) | 5.0 (0.71) | consecutive losses (loss in money) | 8.0 (-2.06) | |
| Average | consecutive wins | 1.0 | consecutive losses | 3.0 |


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adventure
sci-fi
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In theaters
15 Oct, 2015 (USA)
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6.8
Avengers: Inifinity War
Fantasy, Adventure, Action
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Horror, Sci-fi, Action
8.3
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Sci-fi, Adventure, Action
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Blade Runner: 2049
Sci-fi, Fantasy,Action
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Insurgent
Thriller Sci-fi, Action
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Everest
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 ChessHouse.com has a fantastic collection of chess games, ChessHouse.com is a trusted online retailer for chess games. It is uniquely personal, efficient and accountable. It allows you to enjoy chess and suit it to your lifestyle.   Check it out today.
 ChessHouse.com has the best quality chessboard and games available. Each chessboard is hand inspected for quality and efficiency. Give your mind a workout, play chess. ChessHouse.com carries chess games for all ages. There is chess for kids who will enable your children to sharpen their mental skills and calculative skills. Chess is known to improve academic performance. Also, chess is loads of fun to play with. You can get electronic chess, chess pieces and sets. Whatever your chess needs, ChessHouse.com is the answer. Use our discount coupons to get the best deals on ChessHouse.com.
ChessHouse.com carries great games of chess which will enhance your brain power, your thinking skills and more. Get great chess accessories like chess clock, chess bags and boxes.  Check it out today!


WaMDaM_v1.05 [WaMDaM_DBWrench_Schema_v1.05.xml]
A Master Network is a specific implementation of a Dataset (or model), its Instances, and data values within a spatial location (e.g., Bear River Watershed, Utah). Master Networks help researchers to organize and then search groups of Instances that belong to a Dataset (or model)in space. For example, a Dataset for a WEAP model can be used to create separate WEAP model for the Bear River and the Weber River watersheds in Utah.
| PK | Name | Data Type | NULL | Auto | Default | Comment | FK |
|
| MasterNetworkID | Integer |
| Primary key identifier | |||
| MasterNetworkName | VarChar(255) | Text name for the Master Network | |||||
| SpatialReferenceNameCV | VarChar(255) | CV Term for a Spatial Reference system that describes the latitude and longitude coordinates |
|
||||
| VerticalDatumCV | VarChar(255) | CV Term for a Vertical Datum that references where the elevation reported for the network nodes and links |
|
||||
| Description | Text |
| Text description of the MasterNetwork |
(none)
| Name | Parent Table | Child Table | Parent Columns | Child Columns |
| fk_MasterNetworks_CV_SpatialReference | CVs.CV_SpatialReference | NetScen.MasterNetworks | Name | SpatialReferenceNameCV |
| fk_MasterNetworks_CV_VerticalDatum | CVs.CV_ElevationDatum | NetScen.MasterNetworks | Name | VerticalDatumCV |
(none)
| Diagram Name |
| 01_WaMDaM |
| 02_WaMDaM_WCVs |


Source code for nhlscrapi.games.playbyplay
from nhlscrapi._tools import build_enum
from nhlscrapi.scrapr.rtss import RTSS
from nhlscrapi.games.repscrwrap import RepScrWrap
Strength = build_enum('Even', 'PP', 'SH')
"""Enum indicating play strength."""
class Play(object):
[docs] """Contains base level of state info about a given play."""
def __init__(self,
play_num=0, period=0, strength=Strength.Even, time={ "min": 20, "sec": 0 },
vis_on_ice = { }, home_on_ice = { }, event=None):
self.play_num = play_num
"""Number of player who made the play"""
self.period = period
"""Current period"""
self.strength = strength
"""Enum of type :py:class:`.Strength` indicating either even strength, shorthanded, or power play"""
self.time = time
"""Time remaining in the period"""
self.vis_on_ice = vis_on_ice
"""Visiting skaters on the ice. ``{ num: [position, name] }``"""
self.home_on_ice = home_on_ice
"""Home skaters on the ice. ``{ num: [position, name] }``"""
self.event = event
"""
An object that inherits from :py:class:`.Event` that contains other specifics related to
the given type of play
"""
class PlayByPlay(RepScrWrap):
[docs] """
Aggregator of :py:class:`.Play` objects that maintains the play-by-play data for a given game. Allows for
custom stats of type :py:class:`.AccumulateStats` to be computed for the game.
:Example:
.. code:: python
from nhlscrapi.games.game import GameKey
from nhlscrapi.games.cumstats import ShotCt
from nhlscrapi.games.playbyplay import PlayByPlay
# define the game of interest and a stat accumulator
pbp = PlayByPlay(
game_key=GameKey(2015, 3, 224),
cum_stats={ 'ShotCount': ShotCt() }
)
# compute and print results
shot_cts = pbp.compute_stats()['ShotCount']
print('Final Score:\t{}'.format(shot_cts.total))
"""
def __init__(self, game_key, cum_stats = {}, init_cs_teams=True):
super(PlayByPlay, self).__init__(game_key, RTSS(game_key))
self.cum_stats = cum_stats
"""Dictionary of :py:class:`.AccumulateStats` to be computed"""
self.init_cs_teams = init_cs_teams
"""Boolean, (default) True if the :py:class:`.AccumulateStats` objects should have team names initialized."""
self.__have_stats = False
self.__wrapped_plays = []
# doesn't need to be dispatched
# this is managed by compute_stats
@property
def plays(self):
"""List of :py:class:`.Play` objects."""
self.compute_stats()
return self.__wrapped_plays
def compute_stats(self):
[docs] """
Compute the stats defined in ``self.cum_stats``.
:returns: collection of all computed :py:class:`.AccumulateStats`
:rtype: dict
"""
if not self.__have_stats:
if self.init_cs_teams and self.cum_stats:
self.__init_cs_teams()
for play in self._rep_reader.parse_plays_stream():
p = Play(**play)
self.__wrapped_plays.append(p)
if self.cum_stats:
self.__process(p, self.cum_stats, 'update')
self.__have_stats = True
return self.cum_stats
def __process(self, play, d, meth):
for name, m in d.iteritems():
getattr(m, meth)(play)
def __init_cs_teams(self):
teams = [ self.matchup['home'], self.matchup['away'] ]
for _, cs in self.cum_stats.items():
cs.initialize_teams(teams)


--- layout: default ---
The Web's Uniform Interface
is based on a large and growing set of specifications. These specifications establish the shared concepts that everybody can build upon. One example for how this works is HTTP/1.1 Caching, which defines 5 HTTP Header Fields, 7 HTTP Warn Codes, and 12 HTTP Cache Directives.
Web Concepts is an overview of these concepts and of the specifications defining them. Web Concepts provides a structured and interlinked overview of the many concepts that together establish the Web surface
.
The best way to explore Web Concepts is to use one of these starting points:
Web Concepts is openly managed on GitHub; feel free to fork, contribute, comment, or raise issues. The site is generated from structured information representing the individual specifications, with the build process currently being based on XSLT and Jekyll. If you are just interested in the data, read about the JSON representations of Web Concepts.
For a complete list, here is the history of all updates; you can subscribe to updates via the feed.


-
What is an 'unknown' game?
There's two reasons a game is marked as unknown:
- The game has been deleted by Steam
- The game has not yet been scraped to our database (usually for new games)
-
Why can't I see my games when I search for my profile?
Your profile may be private or you may have entered your Steam ID or profile URL incorrectly. To find
your profile URL, go to your steam profile in browser and copy-paste the url to our search bar.
-
Is Condensate Open Source?
Yes, see the about page for details.
-
How can I hide free / unknown / unplayed games?
After finding your profile, click on the green buttons below the search bar to hide free / unknown / unplayed
games.
-
Is there a way to export my profile information?
There is currently no way to export your data, but could be a future feature.
-
Is there a way to share my profile information?
Copy the link after searching for a URL and you can give that link to your friends.


{% extends 'base.html' %} {% block title %} Form {% endblock %} {% block head %} {% endblock %} {% block body %}
Input any URL and all the links on web-page, types of domains, their count and size of web-page will be revealed.
Enter URL to be analyzed
{% endblock %}


Selected date: {{date.year}}-{{date.month}}-{{date.day}}
From: {{ fromDate | json }}
To: {{ toDate | json }}
Note: Very customizable but too complex!
With seconds:
Selected time: {{time.hour}}:{{time.minute}}
Selected time with seconds: {{time.hour}}:{{time.minute}}:{{time.second}}


The world is a book and those who do not travel read only one page. — Aurelius Augustinus Hipponensis


DfE enquiries
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Press release
New exclusions figures show that giving heads powers to enforce discipline is working.
New figures published today (31 July) reveal that thousands fewer pupils have been excluded from school since 2010, after the government strengthened heads’ powers to enforce discipline.
The latest data, which is for the 2012 to 2013 academic year, shows that compared to the 2009 to 2010 academic year:
The statistics highlight how the government’s reforms to give heads and teachers the powers and confidence to stamp out poor behaviour at an early stage are working.
School Reform Minister Nick Gibb said:
A tiny minority of disruptive children can absorb almost all of a teacher’s time and attention, and have an enormously negative impact on the education of other pupils.
We have given heads and teachers more power than ever before to ensure strong discipline in school, so they can take action before exclusion becomes necessary. We have introduced new search powers, no-notice detentions and have put schools back in charge of exclusion appeals.
We are also tackling the causes of exclusion by improving the quality of teaching, tackling disadvantage through the pupil premium, overhauling the special educational needs system and making radical improvements to alternative provision.
These figures give further confirmation that our reforms are starting to have a real impact on improving behaviour in schools and this is supported by teachers on the ground - in 2013 more teachers rated their school’s behaviour as good or very good than when previously surveyed in 2008. And 130,000 fewer pupils are persistently missing class than in 2010.
The reforms to allow heads and teachers to tackle bad behaviour at an early stage include:
In September 2012, the government also removed the rights of appeals panels simply to send expelled pupils back into schools against the wishes of heads.
This has ensured heads’ authority is no longer undermined, because they are now back in charge of exclusions. Previously, exclusions could be overturned by these external panels, stripping schools of the confidence to deal with discipline. But under the new system the final decision on reinstatement now lies with the school itself.
Today’s figures reveal a dramatic drop in the number of excluded pupils reinstated by external appeals panels - it is now at its lowest number since records began.
The number of pupils reinstated on appeal has halved in maintained schools - from 40 in the 2011 to 2012 academic year to just 20 in the 2012 to 2013 year, while the number of appeals lodged fell from 420 to 180 in the same period (figures for academies have not been available until today’s statistics).
School attendance has also drastically improved, with 7.7 million fewer school days lost to absence last year compared to the 2009 to 2010 academic year, and with 92% of schools rated good or outstanding by Ofsted for behaviour.
This approach is supported by pupils - the My Education survey of 2013 showed that more than three-quarters of pupils prefer tougher discipline in schools.
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Published: 31 July 2014