Current version includes outlier detection in a fitted linear model, stationary bootstrap using a truncated geometric distribution, a comprehensive test for weak stationarity, missing value imputation, column/rows sums/means by group, weighted biplots, and a heuristic to obtain a better initial configuration in non-metric MDS.
| Version: | 3.0 |
| Depends: | R (≥ 3.1.0) |
| Imports: | powerplus (≥ 3.1), tcltk (≥ 3.3.1), cluster (≥ 2.0.4), MASS (≥ 7.3-45), car (≥ 2.1-4), robust (≥ 0.4-18), trend (≥ 0.2.0), TSA (≥ 1.01), lmtest (≥ 0.9-35), fractal (≥ 2.0-1), urca (≥ 1.3-0), np (≥ 0.60-3), VIM (≥ 4.7.0) |
| Published: | 2018-10-14 |
| Author: | Albert Dorador |
| Maintainer: | Albert Dorador <albert.dorador.chalar at gmail.com> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | analytics results |
| Reference manual: | analytics.pdf |
| Package source: | analytics_3.0.tar.gz |
| Windows binaries: | r-devel: analytics_3.0.zip, r-release: analytics_3.0.zip, r-oldrel: analytics_3.0.zip |
| OS X binaries: | r-release: analytics_3.0.tgz, r-oldrel: analytics_3.0.tgz |
| Old sources: | analytics archive |
Please use the canonical form https://CRAN.R-project.org/package=analytics to link to this page.


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 I want to understand, what does it mean? What reality are you talking about, my friend? It is absolutely crazy to me that select individuals (many more, actually) dare to dictate one or another how to live by boxing them into their worldview.
There is this misconception, a crucial misunderstanding that is happening, where people seem to think that this way is the right way to spend time and live while that one over there is not. Similar to the question I asked in Living Consciously, who made those criteria? Sure, society and its constructs evolved one way or another, however, it is not ironclad; simply a product of its time and circumstances.
I am writing this out of frustration I had from talking to other people about my favorite movies and shows. Of course, I do not expect everyone to like the same things that I like, however, what I do not expect is for someone to start imposing their views, trying to convince you that what you love and adore is bad. Keep in mind that this is different from a healthy discussion or argumentation.
It is only human for me, personally, to get a little disheartened if another person (especially a friend of mine) just keeps going down on what I hold so dearly, as if having no care for my feelings and uneasiness at the moment, whilst still knowing all of it. I am too considerate and delicate to make a snarky remark or get back at something of theirs, it’s not fun.
This is in the same vein of ridicule that comes about reading “juvenile fiction” or “this anime is too shouneny”, which sounds pejorative, to say the least, as if to shame me for liking it just for the way it is. How many friendships and relationships have collapsed because someone said with a judging tone in their voice, “oh, you like this?”
You can still critique whatever you don’t like or rubs you the wrong way; do it constructively and logically. Leave the raw and uncontrolled emotions of yours out of it, so you are not stumbling into other people’s feelings’ territories spraying dirt all over them. We can try to put ourselves in their shoes to see where they are coming from.
The reality and world that surrounds you are exactly what you make of it.  Two identical physical worlds can be interpreted as completely different realities, to the point that one might not even be able to imagine the very existence of the second one.
What you think of the world, of a movie you watched, of a coffee you had in that cafe can and will differ from that other person. That is expected and good. You just live in your own Universes, so give each other space and a chance to experience life the way you want, leaving all that mud and filth out of it. We are only given one tenure at life, let us spend it on living. ◼


PEER_MSGINIT |
Channel: 0 |
This is an additional packet in the peer-to-peer handshake. It is only used in the message connection, _not_ for file transfer. So it kinda distinguishes what this connection is for. It is sent by the originator of the connection after he has acknowledged the peer's PEER_INIT and by the peer as a reply to the originator's PEER_MSGINIT.
Parameters
| Data type | Content | Name | Description |
| BYTE | 03 | CMD | The command: the last connect package. |
| DWORD.L | 0a 00 00 00 | UNKNOWN | Unknown: 0xa = 10. |
| DWORD.L | 01 00 00 00 | UNKNOWN | Unknown: 0x1 = 1. Note: sometimes Windows ICQ sends a packet with rather strange values from here on; this seems to be to test the connection. If this value isn't 1, disconnect. |
| DWORD.L | xx xx xx xx | UNKNOWN | Unknown. Use 01 00 00 00 = 0x1 = 1 for incoming, 0 for outgoing connections. |
| DWORD.L | 00 00 00 00 | UNKNOWN | Unknown: empty. |
| DWORD.L | 00 00 00 00 | UNKNOWN | Unknown: empty. |
| DWORD.L | xx xx xx xx | UNKNOWN | Unknown. Use 01 00 04 00 = 0x40001 for incoming and 0 for outgoing connections. |
| DWORD.L | 00 00 00 00 | UNKNOWN | Unknown: empty. |
| DWORD.L | xx xx xx xx | UNKNOWN | Unknown. Use 0 on incoming, but 01 00 04 00 = 0x4001 for outgoing connections. |
Examples
01:48:41 Eingehendes TCP-Paket: 03 0a 00 00 00 01 00 00 - 00 01 00 00 00 00 00 00 .... .... .... .... 00 00 00 00 00 01 00 04 - 00 00 00 00 00 00 00 00 .... .... .... .... 00
23:20:56 Incoming TCP packet (6 - m:1126630): PEER_INIT2 03 0a 00 00 00 eb 03 00 - 00 00 00 00 00 a0 e9 3f .... .ë.. .... . é? 37 4f e9 d3 11 bc d2 00 - 04 ac 96 dd 96 01 00 04 7OéÓ .¼Ò. .¬.Ý .... 00 .
Attribution
Submitted by: tadu@gmx.de.


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addAttendance(HttpServletRequest, HttpServletResponse)
- Method in class com.sun.demo.personaladmin.servlet.
PersonAdminServlet
新增员工的考勤记录
addAttendanceRecord(AttendanceRecord)
- Method in class com.sun.demo.personaladmin.dao.impl.
PersonAdminDAO
addAttendanceRecord(AttendanceRecord)
- Method in interface com.sun.demo.personaladmin.dao.
IPersonAdminDAO
新增考勤记录
addAttendanceRecord(AttendanceRecord)
- Method in class com.sun.demo.personaladmin.service.impl.
PersonAdminService
addAttendanceRecord(AttendanceRecord)
- Method in interface com.sun.demo.personaladmin.service.
IPersonAdminService
新增一条考勤记录
addCar(Car)
- Method in class com.sun.demo.vehiclemanage.dao.impl.
VehicleManageDAO
addCar(Car)
- Method in interface com.sun.demo.vehiclemanage.dao.
IVehicleManageDAO
新增车辆信息
addCar(Car)
- Method in class com.sun.demo.vehiclemanage.service.impl.
VehicleManageService
addCar(Car)
- Method in interface com.sun.demo.vehiclemanage.service.
IVehicleManageService
新增车辆信息
addCar(HttpServletRequest, HttpServletResponse)
- Method in class com.sun.demo.vehiclemanage.servlet.
VehicleManageServlet
新增一个车辆信息
addCarUseInfo(HttpServletRequest, HttpServletResponse)
- Method in class com.sun.demo.vehiclemanage.servlet.
VehicleManageServlet
新增一条车辆使用信息
addCarUserInfo(CarUserInfo)
- Method in class com.sun.demo.vehiclemanage.service.impl.
VehicleManageService
addCarUserInfo(CarUserInfo)
- Method in interface com.sun.demo.vehiclemanage.service.
IVehicleManageService
新增一条车辆使用记录
addDepartment(Department)
- Method in class com.sun.demo.personaladmin.dao.impl.
PersonAdminDAO
addDepartment(Department)
- Method in interface com.sun.demo.personaladmin.dao.
IPersonAdminDAO
新增部门
addDepartment(Department)
- Method in class com.sun.demo.personaladmin.service.impl.
PersonAdminService
addDepartment(Department)
- Method in interface com.sun.demo.personaladmin.service.
IPersonAdminService
添加新的部门
addDepartment(HttpServletRequest, HttpServletResponse)
- Method in class com.sun.demo.personaladmin.servlet.
PersonAdminServlet
添加新的部门
addEmployee(Employee)
- Method in class com.sun.demo.personaladmin.dao.impl.
PersonAdminDAO
addEmployee(Employee)
- Method in interface com.sun.demo.personaladmin.dao.
IPersonAdminDAO
新增员工信息
addEmployee(Employee)
- Method in class com.sun.demo.personaladmin.service.impl.
PersonAdminService
addEmployee(Employee)
- Method in interface com.sun.demo.personaladmin.service.
IPersonAdminService
添加新员工
addEmployee(HttpServletRequest, HttpServletResponse)
- Method in class com.sun.demo.personaladmin.servlet.
PersonAdminServlet
增加新员工
addPark(Park)
- Method in class com.sun.demo.vehiclemanage.service.impl.
VehicleManageService
addPark(Park)
- Method in interface com.sun.demo.vehiclemanage.service.
IVehicleManageService
增加一个新的车位
addPark(HttpServletRequest, HttpServletResponse)
- Method in class com.sun.demo.vehiclemanage.servlet.
VehicleManageServlet
新增车位信息
AttendanceRecord
- Class in
com.sun.demo.bean
考勤记录
AttendanceRecord(String, String, String, String, String)
- Constructor for class com.sun.demo.bean.
AttendanceRecord
AttendanceRecord的构造方法， 实现全部的属性的初始化
AttendanceRecord()
- Constructor for class com.sun.demo.bean.
AttendanceRecord
AttendanceRecord的默认构造方法
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I recently was explaining to someone that as a coder, I do (or should do) a lot more than just code. I figured since I hadn’t written anything here in a while, I’d put my thoughts down here.
the tl;dr
Coders code. That much is obvious from the title, but there is much more that can and should be involved for anyone writing real code, at least for UNIX coders.
intro
So you’ve spent the last couple weeks / months / years writing some really brilliant bit of software that you think would benefit a lot of people. Or maybe, just a few, but you still are of the mindset that since you did the work to solve this problem, other people might have the same problem and if they had the solution, they could concentrate on other problems. Regardless of the quality of code and the development process you followed, which endless books have been written on the subject, there is still a lot more work to be done if you intend to make your software both useful and accessible to other people. You still need to make sure you have a reasonable portable (for the scope of the usefulness of your code) build system, good documentation, an easily accessible online place for people to get your code, and proper follow-through. Let’s talk through these bits.
the build system
No matter how wizard your code is, if it’s more work for other people to build
it than it’s worth, it won’t be used. That’s a simple fact. By now, users have
come to expect the proverbial ./configure && make && make install
(or
perhaps scons
or waf
or jam
or one of the other solutions). Regardless,
the build process should not require much work for end users, except in cases
where the code is a very purposeful bit of code that requires careful
configuration. I personally have begun making use of the autotools
suite
(my personal stance on the GPL notwithstanding, a rant for another day but
the curious can take a look at the license for most of my code on my
github page). This comprises
autoconf and
automake primarily. You will easily
spend many hours just writing out the configuration files on your end to
properly support and build the software, determining what needs to be checked
on the user’s system so that they can be sure the code will run on their node.
Once this is set up and functioning, for the most part and in theory, users
will be able to just do the typical configure-and-make pattern they have come
to know and love. The autotools are really designed for C and C++. For python,
there’s always the Python setuptools,
and of course for Perl there’s CPAN.
Of course, these tools are quite often in a different language than your code is. For example, the autotools use POSIX shell, M4, and POSIX Makefiles to generate the configure script and Makefiles for distribution. This takes time to learn, especially given some of the nuances involved. There is of course some debate (see “Stop the autoconf insanity! Why we need a new build system”[http://freshmeat.net/articles/stop-the-autoconf-insanity-why-we-need-a-new-build-system]) as to how useful these are, but for the most part the reward is worth the work. For the autotools suite, take a look at the No Starch Press book Autotools:A Practitioner’s Guide to GNU Autoconf, Automake, and Libtool. I found this book indispensable in learning the tool suite.
documentation
Documentation extends much further (or should) than the typical README and INSTALL files found in many distributions. Many developers learn the basics of TeX or LaTeX typesetting to produce aesthetically pleasing manuals; Texinfo is also quite common. Markdown is becoming popular as well and with the advent of tools like pandoc, even easier to convert from Markdown to other formats (pandoc supports html and LaTeX). Besides just the technical side of writing documentation and learning the typesetting language used, there’s the art of technical writing as well. Many companies have full-time technical writers whose sole purpose is writing documentation. This is because of another simple fact: your software is of no use if the users can’t figure out how to use it. While many users may be technically saavy enough to read the code to figure out how to use it, for your code to be truly useful, they should not have to resort to this. This is what I see as the Apple factor: many developers use Apple’s hardware and operating system because not only do things Just Work, but there is also excellent documentation available. Another operating system leading the way in documentation is my beloved OpenBSD. Users should have a clear set of instructions of not only how to use the software, but ways to extend it, what things it can do that they may not realise, and how to solve problems that may crop up. So a truly good coder is both at least a proficient typesetter but also a proficient writer of whatever human language the software is in (or aimed at).
Some projects go further and include a full copy of the license the software
is released under (which you should do for the safety / peace of mind /
convenience of your users - it took lteo constantly
reminding me of this for many of my projects before I started doing it out
of habit) which is most often in a file called LICENSE or COPYING; a copy of
the ChangeLog, which could also be gotten from source control such as
git log
; an AUTHORS file to list contributors; a README and INSTALL file to
give a quick usage and overview as well as installation instructions; and
perhaps a HACKING document to explain how to modify the code to be useful.
The README file is still rather useful; in fact, many times I will write the README first as part of my development process.
No matter how you approach it or what you use to write and format your user manuals, you should still have them included.
distribution
Today, distribution is one of the easiest aspects of coding. Numerous websites exist for the sole purpose of distributing your software, such as github, bitbucket, sourceforge, freshmeat, among others. Typically, such sites will also host a remote version of your version control system (you are version controlling, right?) in addition to supporting release downloads. A well-setup build system offers the ability to build a distribution release, often in tarball or tarred bzip2 format as well. Some sites still offer just a release tarball (for a while, this is how I released my libdaemon project, via my devio.us homepage. In fact, this is rapidly becoming one of the easiest pieces of the project lifecycle. If you haven’t already, take a look at one of the sites that works as a remote repo for whatever source control you are using. You will probably see that besides distribution, these sites are extremely useful for the last important additional part of coding I want to talk about.
support and maintenance
Once the user has a copy of your software and knows how to use it, they will inevitably encounter bugs or find that while they would really like to see a feature in the software, they don’t have the technical skills to implement it themselves (or perhaps the courage to look through your code…) Still other users might fix the bugs or add new features themselves, and would like to offer you those changes so you can incorporate them into the software. So the last important additional part of being a coder is support and maintenance.
Many of the sites that offer to host releases of your code provide additional tools, like wikis, bug reporting (aka trouble tickets), and feature requests. Users may also provide patchfiles or a git pull request to give you their contribition (and accordingly, you credit them in the documentation as well). A good coder needs to be able to support and maintain the software - users are more apt to use software if it gets patched or updated with new features (or if it just works and they don’t need new features or bugs patched, which is less likely but still possible).
conclusion
As I’ve explained, being a good coder and providing useful software encompasses so much more than just good technical skills or great development processes. There’s the administrative side (i.e. the build system, feature request and bug tracking) and the human side (i.e. documentation and responding to support requests). While it may not be as much fun as the actual coding, it is still integral to the development process.


Here to learn how to knit or crochet? Explore a bit to start absorbing info.If you've looked around and prefer a face-to-face lesson, send me a message and I'll see what I can do.


Although we can no longer hear these melodies, we can work out some aspects of how they sounded. One key element is the question of when you stop, take a breath, pause, and then start singing again. This happens at the end of a sentence, or at the end of a clause, or a shorter text unit. One place, of course, that there is always a stopping point is at the end of a chant.
Some of these combinations recur multiple times, as you can see. Here is a combination that appears on the words “veritas eius” (his truth). There is a unison, a two note rise, one single note, and then this three note neume: a note, a higher note, and then a lower note again. Can you spot this combination later on the same page of the manuscript? When you do, tap it with your finger on the screen.


The shortlist for The YA Book Prize was announced on Friday 1 March. This award “celebrates great books for teenagers and young adults and aims to get more teens reading.”
The One Memory of Flora Banks, by Emily Barr
“Flora has amnesia. She can’t remember anything day-to-day: the joke her friend made, the instructions her parents gave her, how old she is. Then she kisses someone she shouldn’t, and the next day she remembers it. It’s the first time she’s remembered anything since she was ten. But the boy is gone. She thinks he’s moved to the Arctic. Will following him be the key to unlocking her memory? Who can she trust?”
S.T.A.G.S. by M. A. Bennett
“It is the autumn term and Greer MacDonald is struggling to settle into the sixth form at the exclusive St Aidan the Great boarding school, known to its privileged pupils as S.T.A.G.S. Just when she despairs of making friends Greer receives a mysterious invitation with three words embossed upon on it: huntin’ shootin’ fishin’.
“When Greer learns that the invitation is to spend the half term weekend at the country manor of Henry de Warlencourt, the most popular and wealthy boy at S.T.A.G.S., she is as surprised as she is flattered. But when Greer joins the other chosen few at the ancient and sprawling Longcross Hall, she realises that Henry’s parents are not at home; the only adults present are a cohort of eerily compliant servants.”
It Only Happens in the Movies, by Holly Bourne
“Audrey is over romance. Since her parents’ relationship imploded her mother’s been catatonic, so she takes a cinema job to get out of the house. But there she meets wannabe film-maker Harry. Nobody expects Audrey and Harry to fall in love as hard and fast as they do. But that doesn’t mean things are easy. Because real love isn’t like the movies…”
Read Kate’s review of It Only Happens in the Movies →
Moonrise, by Sarah Crossan
“Joe hasn’t seen his brother for ten years, and it’s for the most brutal of reasons. Ed is on death row. But now Ed’s execution date has been set, and Joe is determined to spend those last weeks with him, no matter what other people think. What value do you place on life? What can you forgive? And just how do you say goodbye?”
Read Emily’s review of Moonrise
After the Fire, by Will Hill
“Father John controls everything inside The Fence. And Father John likes rules. Especially about never talking to Outsiders. Because Father John knows the truth. He knows what is right, and what is wrong. He knows what is coming. Moonbeam is starting to doubt, though. She’s starting to see the lies behind Father John’s words. She wants him to be found out. What if the only way out of the darkness is to light a fire?”
Indigo Donut, by Patrice Lawrence
“Bailey is 17, mixed race, lives with his mum and dad in Hackney and spends all his time playing guitar or tending to his luscious ginger afro. Indigo is 17 and new to London, having grown up in the care system after being found by her mum’s dead body as a toddler. All Indigo wants is to know who she really is.
“When Bailey and Indigo meet at sixth form, sparks fly. But when Bailey becomes the target of a homeless man who seems to know more about Indigo than is normal, Bailey is forced to make a choice he should never have to make.”
Release, by Patrick Ness
“Today will change Adam Thorn’s life.  And way across town, a ghost has risen from the lake. Is there time for Adam to find his release?”
Read Kate’s review of Release →
Things a Bright Girl Can Do, by Sally Nicholls
“Evelyn is 17, and though she is rich and clever, she may never be allowed to follow her older brother to university. Enraged that she is expected to marry her childhood sweetheart rather than be educated, she joins the Suffragettes, and vows to pay the ultimate price for women’s freedom.
“May is 15, and already sworn to the cause, though she and her fellow Suffragists refuse violence. When she meets Nell, a girl who’s grown up in hardship, she sees a kindred spirit. Together and in love, the two girls start to dream of a world where all kinds of women have their place.
“But the fight for freedom will challenge Evelyn, May and Nell more than they ever could believe. As war looms, just how much are they willing to sacrifice?”
Read Amélie’s review of Things a Bright Girl Can Do
The Book of Dust Volume 1: La Belle Sauvage, by Philip Pullman
“Eleven-year-old Malcolm Polstead and his dæmon, Asta, live with his parents at the Trout Inn near Oxford. Across the River Thames (which Malcolm navigates often using his beloved canoe, a boat by the name of La Belle Sauvage) is the Godstow Priory where the nuns live. Malcolm learns they have a guest with them; a baby by the name of Lyra Belacqua…”
Read Kate’s review of La Belle Sauvage →
Straight Outta Crongton, by Alex Wheatle
“Round these ends, it’s hard to hold on to your dreams. Life’s a constant hustle for Mo.  No wonder she’s vexed so much of the time. Thank god she has her sisters, Elaine and Naomi, on her side: if one of them falls then they all fall.
“But when badness goes down and a life is left hanging in the balance, Mo has to face her hot urge for revenge and she might end up losing more than she wins.”


“We are not a cheap country with crazy people that you can visit like a zoo”
Kyiv has a special vibe that is hard to find anywhere else, believes DJ Jana Woodstock. The frail platinum blonde with the penetrating look grew up in the German city of Hannover. When she moved back to Kyiv at the age of 14, she had a hard time adapting to the language and culture of her motherland. “Everything was different: the way of thinking and looking at things, the feeling of life, the humour. In Ukraine the jokes are darker, but that actually suits me”, Jana says while effortlessly climbing the steep mountain road at Andreevsky Descent, in the Old Town. On top of the hill, hidden between the trees, is a centuries-old pagan cemetery; one of her favorite spots in the city.
“When I am standing here, looking over the city, I really feel Kyiv. I find this a very inspirational place. Connecting with nature is very important to me. With my music I want to transmit the power that this place gives me to the people in the club.”
Every weekend, she’s playing dark techno - “I don’t do funny music” - at one of Kyiv’s many underground parties - Jana calls herself a “real Kyiv girl”. “Germany is still my home too, but I am aware of how little worries people have over there. They find themselves in such comfortable positions that they feel less of an urge to be truly inventive, it seems. In Kyiv the creative drive is bigger. Our government does not support us, so we do everything ourselves.”
“Most often a big electronic music scene develops itself in parallel to political events. Look at Berlin in the ‘90s: after the Wall fell, DJs from all over the world played at legendary clubs such as Tresor. I believe you can compare the current atmosphere of Kyiv’s club scene and how it has developed after Euromaidan with that period right after the Berlin Wall came down.Today DJs from all over the world are asking me to arrange a gig for them in Kyiv. It seems like everybody wants to play here now; it’s crazy.”
Having been a city with “only clubs for daddies and gangsters”, as Jana puts it, Kyiv is now hyped as Europe’s newest “rave capital”. Many hip online magazines have even declared that the Ukrainian capital has pushed Berlin off its throne. But according to Jana, that’s rather exaggerated. “Maybe in a year or five we will be a hotspot for party tourism like Berlin, but at the moment we are not being flooded by foreign ravers. That’s what I appreciate so much about the scene here; it is developing one step at a time, not rushing anything."
“The creative drive in Kyiv is bigger. Our government does not support us, so we do everything ourselves”
Jana’s own DJ career on the other hand, took off unexpectedly fast. Her friend and agent Masha (29) played an important role in this. Masha co-founded Club 56, a club where young, emerging DJs got a chance to build up some experience, contributing to “a new wave of Kyiv DJs”, as Masha calls it. “Four years ago Jana played her first set there. Since then she’s gotten quite popular.”
Jana: “It was crazy, because I actually played quite badly in the beginning. I had no idea what I was doing; I learned how to play while I was already behind my booth in the club. By day I was working in a bar, by night DJ’ing. It was a very nervous time for me.”
“We don’t need to fly in superstars for a successful party, our own music and DJs are more than good enough.”
Club 56 has now closed, but today Jana is DJ-in-residence at Osnova; a series of parties organized by her friend and agent Masha. Together with a few friends, Jana and Masha head for Otel’; the club where the Osnova parties mostly take place. Tonight, like most nights, there are only Ukrainian names on the bill. “Before this was mostly because of organisational problems: the weak hryvnia [the Ukrainian currency] and visa stress [travel between Ukraine and the EU was not visa-free until June 2017] made it impossible to invite a lot of foreign DJs,” Jana explains. “But in the meantime we transformed this limitation into an asset: we don’t need to fly in superstars for a successful party, our own music and DJs are more than good enough.”
Shortly after midnight, the industrial lot at Nyzhnoiurkivska Street slowly fills up with stylish youngsters who discuss where to spend their night, over a cigarette. The lot accommodates several clubs that didn’t exist five years ago. “It is hard to start a new club and keep it running. The government does not support it and raves are not very popular among private property owners,” Masha explains.
“But compared to Russia, where the police can shut a party down anytime they want, our government is quite tolerant towards ravers,” Jana adds. In Ukraine, president Poroshenko recently implemented a law that forbids such raids, as a reaction to an incident that took place last autumn. Special forces raided the now closed club Jugendhub, looking not only for drugs, but also for conscientious objectors to military service. Since the start of the war in 2014, all Ukrainian men over 18 who are not studying, are obliged to serve in the army. Masha: “The government understood that young people need raves to take off the pressure once in a while. And after all, they have bigger priorities at the moment.”
A seemingly lost Liverpool supporter taps her on the shoulder. The Champion’s League final brought him to Kyiv for the very first time, he explains, slurring his words. Where can he be entertained over here?, he asks. Masha kindly directs him to another club. “The rise in international interest in Ukraine is a good thing, I believe. Through this, our DJs get more followers, and I can get new clients.”
Masha thinks for a while, scratching her short bob with a long, black-painted nail. “But there’s also a downside to all this attention: Ukraine is often still perceived as a cheap country with crazy people. But we are no zoo that you can come visit.”


Download oculus-rest here: github.com/possan/oculus-rest.
Navigate to the directory containing the oculus-rest project.
Run the provided executable for your operating system. You must have the Oculus Rift™ connected to your computer via USB before running this application.
Run the intended application. Data will start to be send between the oculus rest application and your HMD to provide head tracking.
The GitHub repository also includes project files for Visual Studio(Windows) or XCode(OSX) so that you can build and run the files locally.


Hiking Trails Closing Ahead of Dangerous Weather Forecasts
by Hana Levi JulianThe Nature and Parks Authority has announced it is closing a significant number of hiking trails throughout the country as of Monday ahead of potentially dangerous weather conditions.
“Due to extreme weather warnings, it is forbidden to take walks in several sites in the north of Israel from Monday the 18th until Wednesday the 20th,” reads an alert on the Authority website. Hikers are directed to call the Authority’s call center at *3639.
High winds began entering the region over the weekend, with temperatures dropping on Sunday and continuing to drop further on Monday. Meteorologists say the incoming weather system is expected to further reduce humidity and bring stronger winds as well.
Brush fire warnings have been raised across the country as a result.
Israel is not the only country in the Mediterranean basin seeing strong weather patterns this week: in Italy, a record-high tide struck the city of Venice on Sunday for the third time in a week.
Tourists went wading through the flood-struck areas in Venice to photograph the sights, even though most of the stores and museums were closed, according to The Associated Press.
The rest of the country was likewise hit with similar severe weather ranging from an out-of-season avalanche to extremely high water levels in the rivers due to unusually heavy rain, and high winds.


--- title: nbds_colab keywords: fastai sidebar: home_sidebar summary: "Literate programming for data science using nbdev, Jupytemplate and Google Colaboratory" ---
nbds_colab is a template repository for small to medium sized data science projects which use the nbdev programming system from within Google Colaboratory. It combines the best features of the following to give quick project start-up followed by a complete low friction workflow, from first code to package release:
Fastai.nbdev - exploratory programming, automated documentation generation, integrated testing and easy PyPi package release nbdev
Google Colaboratory & Drive - low cost cloud computing with acceleration Colaboratory
Jupytemplate - standardized notebooks for data science xstreamsrl Jupytemplate
Full GitHub integration
The following assumes a working knowledge of the nbdev exploratory programming system, Jupiter notebooks, Google Colaboratory (Colab), Google Drive and GitHub. For more information on nbdev read the nbdev documentation and on how nbdev works with Google Colaboratory, the nbd_colab docs.
Make sure you are logged in to your GitHub account then click nbds_colab_template to go to the template repo on GitHub. Enter a name for your project and click 'Create repository from template'. A new repo based on the template will be created in your GitHUb.
From GitHub, edit the settings.ini
file of the new repo with your own personal and package information as described in the nbdev documentation and tutorial. Add any dependencies to the 'requirements' setting (requirements = dep1 dep2
etc) with multiple requirements separated by a single space. A set of test_flags have already been added (tst_flags = test_flag_colab|test_flag_deps|test_flag_GPU|test_flag_slow|test_flag_large|test_flag_other
). These can be customized if needed. Commit the new settings.ini
to save the changes.
Activate GitHub Pages to display automatic documentation: click on 'Settings', then scroll down to GitHub Pages and select 'master branch/docs folder'. Edit the repo description by adding the auto-generated GitHub Pages link to the box next to the repo description at the top of the page.
Finally, clone the new repo to your Google Drive. A detailed description of how, and helpful tools to accomplish this, are provided by nbds-colabs's sister library, nbd_colab. The nbd_colab documentation will guide you through installing nbd_colab and then cloning the new repo to your Google Drive as well as configuring it for GitHub integration.
Once cloned and configured on your Google Drive, the template repo now becomes the project template its own project directory and has full GitHub integration. Out of the box, the project notebooks are set up to support automatic documentation generation and integrated testing courtesy of nbdev. Every time you work with a notebook you just have to remember to run the cells at the top of the notebook to mount Google Drive, pip install nbdev and fastcore, and %cd
into the project directory. These cells are flagged #hide
, so they don't appear in the automated documentation.
The project template is structured to allow small to medium sized data science projects to be broken down into manageable units, each with its own notebook. You can put anything anywhere but if you are going to run with the already established project structure, our idea of what should go where is as follows:
00_core
: core functionality for the project (optional).
01_dstemplate1
- 03_
: data science templates to edit with the main project code.
04_
- 07_
add more notebooks as required!
08_ensemble1
- 09_
: code to create model ensembles from the output of 01_dstemplate
to 03_
.
10_final
: bring it all togather in the final project model or result.
11_common
: code, classes and functions shared between template files.
12_vis
: shared code for data visualization
13_dataproc
: shared data processing , preprocessing and feature engineering functionality
14_data
: data acquisition, initial processing and source description(s)
15_refs
: place all the project references and citations in one place for quick lookup
Before the first commit and push to GitHub is a good time to customize the template for your particular project.
Delete unwanted notebooks (simply remove them from Google Drive) and add new notebooks (see the nbd_colab documentation on how to do this) so that the repo has the desired project structure.
You can rename the 'dstemplate', 'ensemble' and 'final' notebooks to something more meaningful for your project but remember to keep the nbdev naming convention of progressive double digits following by the new name. If you work in a team, also including the authors initials - so something like, e.g. '00_AB_data_exploration.ipynb' or 'AB_00_data_exploration.ipynb'. Don't forget to ammend any associated import statements to the new name as well!
Update all #default_exp
flags with the new notebook name and don't forget to update all local imports similarly. Remove unwanted imports and add new ones as required.
Uncomment the %cd command
just below library installs and change the placeholder text to the name of the project directory. Run this cell every time you reload the notebook so that local imports work as expected.
Customize test_flags for development. As well as the built in all_flags
the template ships with the following custom test_flags: test_flag_colab
, test_flag_deps
, test_flag_GPU
, test_flag_slow
, test_flag_large
, and test_flag_other
. Use these or create your own by editing settings.ini.
Now you can build the project library with nbdev_build_lib
and documentation with nbdev_build_docs
as described in the nbdev documentation and nbd_colab docs. Don't forget to check for any diffs with nbdev_diffs_nbs
and run tests with nbdev_test_nbs
. If all is well, push the customized template with an 'init commit' message, or the like, to GitHub. After pushing, go to the remote repo's GitHub Pages and you should be able to view the starter documentation for you project!
The data science templates are adapted from xstreamsrl's jupytemplate project, where the aim is to provide a greater degree of structure and standardization to data science projects. Here we take the natural next step and place them into a literate programming environment. Dive in and edit them as needed for your project.
There is a certain life cycle to projects developed with nbdev and Google Colab.
Edit notebooks as required. Each Colab notebook must install and import all it's own dependencies.
Write tests and documentation straight into the notebook alongside (well above or below!) related code.
Consider which cells should be exported as .py scripts, which should be included in the documentation etc and add appropriate flags to the top of cells.
Review cell outputs - some you will want to show in the documentation and some you will want to hide by collapsing the output box in Colab.
When done, check the notebook can run independently top to toe.
Build the library, build the documentation and check for diffs
Run tests with nbdev_test_nbs
. Debug failing code and notebooks. Use test_flags to customizer testing where needed.
Push the new version to GitHub. Check the GitHub Actions panel for any problems during the push and review the rebuilt documentation on GitHub Pages.
Repeat the cycle until the project is finished.
New package versions can be released on PyPi with a few simple commands
This may seem complicated at first but very soon you get into the swing of it and most report greatly increased productivity after the initial learning curve. If anything is unclear the best place to go is the nbdev documentation and nbd_colab guide. Still stuck, try the nbdev threads on the fastai forum .
nbdev: use Jupyter Notebooks for everything, Jeremy Howard, Dec 02 2019.
Introducing jupytemplate: configurable templates for Jupyter, Emanuele Fabbiani, Feb 4th 2020.


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The end of Configuration Management
Thom May
Community Engineering at Chef
@thommay pretty much everywhere
With a hard coded file?
development:
url: postgresql://localhost/blog_development?pool=5
production:
url: postgresql://<IP_ADDRESS>/blog_development?pool=5
With a hard coded file that contains secrets?
development:
url: postgresql://localhost/blog_development?pool=5
user: blog
password: mypassword
production:
url: postgresql://<IP_ADDRESS>/blog_development?pool=5
user: blog
password: mysecurepassword
apiVersion: v1
kind: ReplicationController
metadata:
name: update-demo-kitten
spec:
selector:
name: update-demo
version: kitten
template:
spec:
containers:
- image: gcr.io/google_containers/update-demo:kitten
name: update-demo
ports:
- containerPort: 80
protocol: TCP
Configuration Management isn't just writing stuff to disk
Some quick sample code
package "sun-jdk" do
action :install
# node is populated at start up from information about the node,
# stored either locally or on a chef server
version node["java"]["version"]
end
Chef is data driven
applications = JSON.parse(Net::HTTP.get("https://config/applications"))
applications.each do |name, settings|
my_app name do
version settings["version"]
turbo :on
end
end
It's easy to extend
It's easy to ensure that actions are idempotent
How does this help?
Deploying a kubernetes master with chef is a little easier
kubernetes_master "master" do
cloud_provider "aws"
kubernetes_version "1.1.4"
end
Under the hood
docker_container "kubelet" do
repo kubernetes_repo
tag "v#{kubernetes_version}"
host docker_host
volumes ["/:/rootfs:ro", "/sys:/sys:ro", "/dev:/dev"]
network_mode "host"
privileged true
pid_mode "host"
command "/hyperkube kubelet"
end
Discovering services
db_ip = search(:node, "role:db_server AND chef_environment:production", {ip: [:ipaddress]})
kubernetes_service "master database" do
ip db_ip
port 5432
end
Secrets
vault = chef_vault_item(:credentials, "our_app_user")
kubernetes_secret "our_app_user" do
data({username: "our_app_user", password: vault["password"]})
end
Deployments
kubernetes_replication_controller "our_app" do
image "gcr.io/google_containers/update-demo"
version "kitten"
ports [80]
end


Welcome!
Generate API Keys
Your Admin Secret
Enter Application Name
Choose the APIs for the app
Grades API
Student Profile API
Courses List API
Student Registered Courses API
Student Daily Schedule API
Student Exam Schedule API
Generate the API Key:
Generating the API key


Javascript30
Homepage
About
Drum
Clock
CSS Var
Array Cardio Day 1
Flex Panel Gallery
Type Ahead
Array Cardio Day 2
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Age-specific survival rate ( l x) and fecundity ( m x) of ad ... |
| PMC6403357 |
Figure 1 |
Scenario 1: The coral community after 90 years of simulation ... |
| PMC6403357 |
Figure 2 |
Scenario 2: The surviving coral community after 90 years wit ... |
| PMC6403357 |
Figure 3 |
Scenario 3: The effect of gradually increasing temperatures ... |
| PMC6403357 |
Figure 4 |
Scenario 3: The relative coral cover in the year 2100 under ... |
| PMC6405940 |
Figure 1 |
Left: Pollutant patterns. Advection image of 17 pieces of in ... |
| PMC6405940 |
Figure 2 |
Time-dependence of the stretching rate in different climate ... |
| PMC6405940 |
Figure 3 |
Zonal dependence of the typical stretching rates. The ensemb ... |
| PMC6405940 |
Figure 4 |
Scatter plots. Diagrams for the areal-seasonal mean stretchi ... |
| PMC6405940 |
Figure 5 |
The prescribed CO 2 concentration (bottom) and the global me ... |
| PMC6406781 |
Figure 1 |
Marker of climate change: Trees die after salinity ingress i ... |
| PMC6407464 |
FIGURE 1 |
Interactions between human population and sustainable develo ... |
| PMC6407464 |
FIGURE 2 |
Methodological flow chart of this study. |
| PMC6407464 |
FIGURE 3 |
Population of Bangladesh (based on high, medium and low proj ... |
| PMC6407464 |
FIGURE 4 |
Average annual rate of change of total population and urbani ... |
| PMC6407464 |
FIGURE 5 |
Conceptualisation of implication of climate change on sustai ... |
| PMC6407465 |
FIGURE 1 |
Map of Zimbabwe showing Bikita District (indicated in red) w ... |
| PMC6407465 |
FIGURE 2 |
The location of Mazungunye Ward. |
| PMC6407507 |
Figure 1 |
Potential of invasive plant expansion in terrestrial (A) and ... |
| PMC6407507 |
Figure 2 |
Map showing the potential for invasive plant expansion in RC ... |
| PMC6407507 |
Figure 3 |
The average percent contribution of climatic variables to cl ... |
| PMC6407507 |
Figure 4 |
The changes in annual mean temperature (A and B) and tempera ... |
| PMC6409089 |
Figure 1 |
Distribution and images of the studied species. Limits of th ... |
| PMC6409089 |
Figure 2 |
Haplotype diversity of the studied species. Landscape distri ... |
| PMC6409089 |
Figure 3 |
Ecological niche models for every studied species. Geographi ... |
| PMC6409089 |
Figure 4 |
Environmental resistances for every species studied. Environ ... |
| PMC6409089 |
Figure 5 |
Reserves and haplotype diversity. Haplotype diversity of the ... |
| PMC6409995 |
Figure 1 |
Direct, indirect and socio-economic effects of climate chang ... |
| PMC6409995 |
Figure 2 |
Increasing number of extreme climate-related events occurred ... |
| PMC6409995 |
Figure 3 |
The number of publications per year related to abiotic and b ... |
| PMC6409995 |
Figure 4 |
Overall positive and negative effects of climate change and ... |
| PMC6409995 |
Figure 5 |
Hormonal crosstalk related to different stresses. |
| PMC6409995 |
Figure 6 |
A step-wise presentation of physiological, molecular breedin ... |
| PMC6409995 |
Figure 7 |
A model of CRISPR/Cas9 based genome engineering to develop t ... |
| PMC6411165 |
Fig. 1 |
a Global Precipitation Climatology Project (GPCP; version 2. ... |
| PMC6411165 |
Fig. 2 |
Vertically averaged annual- and zonal-mean meridional stream ... |
| PMC6411165 |
Fig. 3 |
Projected changes in ITCZ a location, b width, and c strengt ... |
| PMC6411165 |
Fig. 4 |
a Multimodel-median change at each latitude in (minus) annua ... |
| PMC6411204 |
Fig. 1 |
Indices of the Northern Annular Mode (left) and Southern Ann ... |
| PMC6414666 |
Figure 1 |
Exemplar thermal profiles used in studies of temperature-dep ... |
| PMC6414666 |
Figure 2 |
Thermal regimes used in this study to incubate eggs of Paint ... |
| PMC6414666 |
Figure 3 |
Components of the novel wCTU model of development and sex de ... |
| PMC6416275 |
Figure 1 |
Dynamic water level concept. Example from California for 1 m ... |
| PMC6416275 |
Figure 2 |
Coastal Storm Modeling System (CoSMoS) workflow. CoSMoS feat ... |
| PMC6416275 |
Figure 3 |
Study area and coastal flooding examples due to an extreme s ... |
| PMC6416275 |
Figure 4 |
Examples of coastal flooding with 0.25 m of sea level rise a ... |
| PMC6416275 |
Figure 5 |
Absolute changes in exposure to coastal-flooding hazards. Ab ... |
| PMC6416275 |
Figure 6 |
Relative changes in exposure to coastal-flooding hazards. Re ... |
| PMC6416299 |
Figure 1 |
Site location. ( a) Shaded elevation map of parts of Chile a ... |
| PMC6416299 |
Figure 2 |
Stratigraphic section of the west wall. ( a) West wall photo ... |
| PMC6416299 |
Figure 3 |
Bayesian age-height model based on 16 radiocarbon dates from ... |
| PMC6416299 |
Figure 4 |
Changes in impact-related and environmental proxies at the P ... |
| PMC6416299 |
Figure 5 |
Group 1 SEM Images: High-temperature Fe-rich impact-related ... |
| PMC6416299 |
Figure 6 |
SEM-EDS elemental map of YDB magnetic grain. Upper left, SEM ... |
| PMC6416299 |
Figure 7 |
Ternary diagrams comparing compositions of spherules from th ... |
| PMC6416299 |
Figure 8 |
Group 2: Cr-rich spherules from Pilauco. Micrographs ( a, b) ... |
| PMC6416299 |
Figure 9 |
Ca- and Si-rich basaltic volcanic spherules and basaltic gla ... |
| PMC6416299 |
Figure 10 |
Group 5: Anthropogenic spherules. ( a– d) SEM images of anth ... |
| PMC6416299 |
Figure 11 |
Group 4: Authigenic pyritic framboids and detrital magnetite ... |
| PMC6416299 |
Figure 12 |
Location map showing 53 YDB sites. Orange dots represent 28 ... |
| PMC6416299 |
Figure 13 |
Records of pollen, seeds, and charcoal. ( a) Pollen from gri ... |
| PMC6416299 |
Figure 14 |
Antarctic climate record exhibiting warming trend at ~12,800 ... |
| PMC6416299 |
Figure 15 |
Grid map of megafaunal (proboscidean) bone and human lithic ... |
| PMC6416299 |
Figure 16 |
Stratigraphic distribution of megafaunal bones and Sporormie ... |
| PMC6416299 |
Figure 17 |
Statistical analyses of megafaunal radiocarbon dates. ( a) S ... |
| PMC6418063 |
Fig. 1 |
Relative coverage of dimensions of adaptation (lower half of ... |
| PMC6418063 |
Fig. 2 |
The proportion of reviewed land and water sector models inco ... |
| PMC6423888 |
Fig. 1 |
PRISMA Flow Diagram for Review of health-related adaptation ... |
| PMC6426862 |
Fig. 1 |
Changes in temperature, moisture and population. Location of ... |
| PMC6426862 |
Fig. 2 |
Changes in functional composition. Changes in the community ... |
| PMC6426862 |
Fig. 3 |
Relationships between changes in functional composition and ... |
| PMC6426862 |
Fig. 4 |
Relationships between changes in different community indices ... |
| PMC6427016 |
Figure 1 |
Presentation of the Mont-Blanc Massif. ( a) The Mont-Blanc s ... |
| PMC6427016 |
Figure 2 |
Average frost occurrence (%, see colorbar) for Tn and Tx and ... |
| PMC6427016 |
Figure 3 |
Spatially-averaged temperature evolutions over the Mont-Blan ... |
| PMC6427016 |
Figure 4 |
Evolution of frost occurrence (percentage points) for the su ... |
| PMC6427016 |
Figure 5 |
Boxplot representation of the evolution of frost occurrence ... |
| PMC6427409 |
Figure 1 |
A systematic flow chart for estimating CH 4 under climate ch ... |
| PMC6427409 |
Figure 2 |
Study area and distribution of meteorological stations. |
| PMC6427409 |
Figure 3 |
Comparison of simulated and observed CH 4 fluxes in the vali ... |
| PMC6427409 |
Figure 4 |
Sensitive analysis of meteorological parameters on driving C ... |
| PMC6427409 |
Figure 5 |
Sensitive analysis of soil parameters on driving CH 4 flux i ... |
| PMC6427409 |
Figure 6 |
Sensitive analysis of crop parameters on driving CH 4 flux i ... |
| PMC6427409 |
Figure 7 |
Spatial distributions of CH 4 fluxes in ( a) 1970s, ( b) 199 ... |
| PMC6427409 |
Figure 8 |
Changing tendency of average CH 4 fluxes of meteorological s ... |
| PMC6427409 |
Figure 9 |
Spatial distributions of CH 4 fluxes in the ( a) 2030s, ( b) ... |
| PMC6427409 |
Figure 10 |
Spatial distributions of CH 4 fluxes in ( a) 2030s, ( b) 205 ... |
| PMC6427409 |
Figure 11 |
Simulated CH 4 fluxes of each global climate model (GCM) und ... |
| PMC6427409 |
Figure 12 |
Regression analysis between meteorological parameters and CH ... |
| PMC6427409 |
Figure 13 |
Response of SOC content between 0–20 cm, plant biomass, and ... |
| PMC6427774 |
Figure 1 |
Malaria cases in Russia. Source: Russian Federal Service for ... |
| PMC6427774 |
Figure 2 |
Dynamics of the average summer air temperature at the Mozhai ... |
| PMC6427774 |
Figure 3 |
Moscow region geographical position. |
| PMC6427774 |
Figure 4 |
Interrelation of the elements of malaria season (e.g., in Ce ... |
| PMC6427774 |
Figure 5 |
Sums of effective temperatures accumulated in Moscow city an ... |
| PMC6427774 |
Figure 6 |
Spatial distribution of changes in the sum of effective temp ... |
| PMC6427774 |
Figure 7 |
Change in the duration of season of effective infectivity (S ... |
| PMC6427774 |
Figure 8 |
Spatial distribution of changes in the duration of the SEI i ... |
| PMC6427774 |
Figure 9 |
Changes in the K f (index of favorability) in the Moscow reg ... |
| PMC6427774 |
Figure 10 |
Spatial distribution of changes in the K f (index of favorab ... |
| PMC6427774 |
Figure 11 |
Changes in the degree of favorability of thermal regime for ... |
| PMC6428232 |
Fig. 1 |
Example North Atlantic blocks. Snapshots of (colour shading) ... |
| PMC6428232 |
Fig. 2 |
Blocking climatology. (top) Winter and (bottom) summer block ... |
| PMC6428232 |
Fig. 3 |
Blocking biases. Multi-model mean (MMM) bias in (top) winter ... |
| PMC6428232 |
Fig. 4 |
Blocking projections. Multi-model mean (MMM) RCP8.5 projecti ... |
| PMC6428897 |
Figure 1 |
Overall monthly variations in the projected changes of preci ... |
| PMC6428897 |
Figure 2 |
Multi-GCM, multi-parameter, and multi-watershed projections ... |
| PMC6428897 |
Figure 3 |
Multi-GCM and multi-parameter ensemble predictions of change ... |
| PMC6428897 |
Figure 4 |
Watershed wise variations of uncertainty in the multi-parame ... |
| PMC6428897 |
Figure 5 |
Watershed wise variations of uncertainty in the multi-GCM hy ... |
| PMC6428897 |
Figure 6 |
Sensitivity of uncertainty quantified for multi-parameter hy ... |
| PMC6428897 |
Figure 7 |
GCM contributions to uncertainty in the multi-GCM ensemble p ... |
| PMC6428897 |
Figure 8 |
Correlation between the amount of uncertainty in the project ... |
| PMC6428897 |
Figure 9 |
Correlation between the amount of uncertainty in QQ (total r ... |
| PMC6428897 |
Figure 10 |
Varying contributions of GCMs to multi-GCM ensemble predicti ... |
| PMC6428897 |
Figure 11 |
Study watersheds in the Ohio River basin: ( A) the weather s ... |
| PMC6428897 |
Figure 12 |
Processes for quantifying uncertainty in multi-GCM and multi ... |
| PMC6432702 |
Figure 1 |
Location of Nyamakate Resettlement and Chundu Communal Area ... |
| PMC6432702 |
Figure 2 |
Household respondents' perceptions of rainfall and temperatu ... |
| PMC6432702 |
Figure 3 |
Household respondents' experiences of extreme events (1980–2 ... |
| PMC6432702 |
Figure 4 |
Mean monthly rainfall for Kariba (1967–2007) (source: Meteor ... |
| PMC6432702 |
Figure 5 |
Mean monthly temperature for Kariba (1967–2007) (source: Met ... |
| PMC6433898 |
Figure 1 |
Predicted impacts of climate change on the distribution of s ... |
| PMC6433898 |
Figure 2 |
Climate change impacts on species geographic distributions. ... |
| PMC6434555 |
Figure 1 |
Yellowhorn tree in bloom. (photograph credit: Dr. Wen‐Bin Gu ... |
| PMC6434555 |
Figure 2 |
Geographical distribution of cpDNA haplotypes in 38 wild yel ... |
| PMC6434555 |
Figure 3 |
(a) “Heatmap” representing the correlations among the 38 pop ... |
| PMC6434555 |
Figure 4 |
Phylogenetic tree obtained from posterior probabilities (>0. ... |
| PMC6434555 |
Figure 5 |
Network for 24 cpDNA microsatellite haplotypes (solid bars i ... |
| PMC6434555 |
Figure 6 |
Canonical correspondence analysis (CCA) for cpDNA microsatel ... |
| PMC6434555 |
Figure 7 |
Significant climate variables changing in recognized genetic ... |
| PMC6436735 |
Fig 1 |
A Framework to assess the vulnerability of agriculture and r ... |
| PMC6436735 |
Fig 2 |
Vulnerability of maize to climate change (2050) under a high ... |
| PMC6436735 |
Fig 3 |
Vulnerability to climate change (2050) under a high emission ... |
| PMC6438455 |
Fig 1 |
Mapping current temperature suitability for transmission. Ma ... |
| PMC6438455 |
Fig 2 |
Mapping future temperature suitability for transmission scen ... |
| PMC6438455 |
Fig 3 |
Projected net changes in population at risk. Projections are ... |
| PMC6445091 |
Fig. 1 |
Modeled CO 2 and N 2O effects of nitrogen-fixing trees relat ... |
| PMC6445091 |
Fig. 2 |
Mechanisms that drive the CO 2 and N 2O effects of nitrogen- ... |
| PMC6445091 |
Fig. 3 |
Modeled global CO 2 and N 2O effects of nitrogen-fixing tree ... |
| PMC6458158 |
Figure 1 |
Spatial change trends of Xinjiang grassland NPPA ( a) and (N ... |
| PMC6458158 |
Figure 2 |
Mann-Kendall mutation criterion curve of average NPPA (left ... |
| PMC6459508 |
Fig 1 |
Maps of projected species richness. Avian assemblage for cur ... |
| PMC6459508 |
Fig 2 |
Potential climate change effects on forecasted occurrence ar ... |
| PMC6459508 |
Fig 3 |
Potential change in mean area per trophic guild. Mean area f ... |
| PMC6459508 |
Fig 4 |
Percentage of species predicted to disappear in each protect ... |
| PMC6459508 |
Fig 5 |
Potential climatically stable areas for conservation actions ... |
| PMC6461033 |
Figure 1 |
Map of China, showing the observed species richness for vasc ... |
| PMC6461033 |
Figure 2 |
The biodiversity of vascular plant species in China. (A) Dar ... |
| PMC6461033 |
Figure 3 |
Variables importance derived from random forest models showe ... |
| PMC6461033 |
Figure 4 |
Predicted distribution of six dark species under current and ... |
| PMC6461246 |
Fig 1 |
Map of the global tropical cyclones tracks from Internationa ... |
| PMC6461246 |
Fig 2 |
Descriptive statistics for GTC data. Above: Frequency of tro ... |
| PMC6461246 |
Fig 3 |
Dynamics of the time-varying first-digit probability p t . T ... |
| PMC6461246 |
Fig 4 |
Dynamics of sum of squared deviations (SSD). The chart gives ... |
| PMC6461246 |
Fig 5 |
Dynamics of the time-varying second-digit probability p t ( ... |
| PMC6461246 |
Fig 6 |
Dynamics of the second-digit SSD. The chart presents the pos ... |
| PMC6465994 |
Figure 1 |
Loading ( a) and score ( b) plots from principal components ... |
| PMC6465994 |
Figure 2 |
The relative yield (as compared to mean values of the cultiv ... |
| PMC6465994 |
Figure 3 |
Loading ( a) and score ( b) plot from principal components a ... |
| PMC6468001 |
Fig. 1 |
Schematic of integrated modeling framework. a Full planning ... |
| PMC6468001 |
Fig. 2 |
Bayesian and democratic confidence intervals from GCM projec ... |
| PMC6468001 |
Fig. 3 |
Learning over time using virtual observations. a– d One samp ... |
| PMC6468001 |
Fig. 4 |
Optimal policies from SDP. a Threshold for initial decision ... |
| PMC6468001 |
Fig. 5 |
Simulated infrastructure decisions and costs. a, b Planning ... |
| PMC6468001 |
Fig. 6 |
Illustrative bottom-up regret analysis. a Total cost includi ... |
| PMC6468064 |
Figure 1 |
Species tested (a, b), experimental timeline (c, d), and exp ... |
| PMC6468064 |
Figure 2 |
Period (in days) until the first signs of necrosis (a) and u ... |
| PMC6468064 |
Figure 3 |
Species‐specific Kaplan–Meier estimated survival curves (ref ... |
| PMC6468064 |
Figure 4 |
Temporal development of the percentage of affected specimens ... |
| PMC6468064 |
Figure 5 |
Temporal development of the extent of tissue necrosis (mean ... |
| PMC6470110 |
Fig. 1 |
Overview of the City Blueprint Approach comprising three com ... |
| PMC6470110 |
Fig. 2 |
Map with eleven Asian cities included in the City Blueprint ... |
| PMC6470110 |
Fig. 3 |
Spider diagrams based on 25 performance indicators for Jakar ... |
| PMC6470110 |
Fig. 4 |
Correlation of the BCI with the TPI, climate readiness index ... |
| PMC6470110 |
Fig. 5 |
Population living in slums (%) for each country in relation ... |
| PMC6472565 |
Figure 1 |
Vulnerability is a function of exposure, sensitivity, and ad ... |
| PMC6474333 |
Figure 1 |
The processing method in the flowchart. The study mainly inc ... |
| PMC6474333 |
Figure 2 |
The original occurrence records. Red dots represented georef ... |
| PMC6474333 |
Figure 3 |
Present (A and F), and future (B–E and G–J) potential spatia ... |
| PMC6474333 |
Figure 4 |
The area of suitable habitats of N. jatamansi and N. chinens ... |
| PMC6474333 |
Figure 5 |
The Jackknife test for evaluating the relative importance of ... |
| PMC6474333 |
Figure 6 |
The response curves of precipitation of driest month under t ... |
| PMC6474857 |
Figure 1 |
Global distribution of phylogeographic Montivipera clades (P ... |
| PMC6474857 |
Figure 2 |
Values of the model’s accuracy based on AUC and TSS of the 1 ... |
| PMC6474857 |
Figure 3 |
Predicted climatically suitable areas for the Bornmuelleri c ... |
| PMC6474857 |
Figure 4 |
Predicted climatically suitable areas for the Raddei clade f ... |
| PMC6474857 |
Figure 5 |
Predicted climatically suitable areas for the Xanthina clade ... |
| PMC6474857 |
Figure 6 |
Boxplot of the comparison of percentage loss (red) and gain ... |
| PMC6474857 |
Figure 7 |
Projected changes in the landscape metrics number of patch ( ... |
| PMC6476759 |
Figure 1 |
Cumulative survival of bay scallop larvae within each treatm ... |
| PMC6476759 |
Figure 2 |
Differential expression (i.e., log fold change) by larvae wi ... |
| PMC6476759 |
Figure 3 |
Venn diagram depicting the number of unique and shared trans ... |
| PMC6476759 |
Figure 4 |
Hierarchically clustered heat map of normalized read counts ... |
| PMC6476759 |
Figure 5 |
The number of significantly ( padj < 0.05) and differentiall ... |
| PMC6476759 |
Figure 6 |
The number of significantly ( padj < 0.05) and differentiall ... |
| PMC6476759 |
Figure 7 |
The number of significantly ( padj < 0.05) and differentiall ... |
| PMC6476759 |
Figure 8 |
The number of significantly ( padj < 0.05) and differentiall ... |
| PMC6476779 |
Figure 1 |
Sites sampled for use in genetic analyses. Geographic map sh ... |
| PMC6476779 |
Figure 2 |
Species Distribution Modeling. Diagram showing the conceptua ... |
| PMC6476779 |
Figure 3 |
Distributional shifts and stability. Maps showing inferred d ... |
| PMC6476779 |
Figure 4 |
Identification of natural genetic populations based on mtDNA ... |
| PMC6476779 |
Figure 5 |
(a) Best‐fit phylogeographic scenario inferred using ABC. Th ... |
| PMC6477182 |
FIGURE 1 |
Meteorological data in May, June, July, August, and Septembe ... |
| PMC6477182 |
FIGURE 2 |
Number of tussocks for different size classes (diameters in ... |
| PMC6477182 |
FIGURE 3 |
Relationships between the number of annually established tus ... |
| PMC6477182 |
FIGURE 4 |
Historical spatial distribution of the hybrids Spartina mari ... |
| PMC6477182 |
FIGURE 5 |
Flowering periods of native Spartina maritima ( Sm) and inva ... |
| PMC6477659 |
FIGURE 1 |
Summary of changes in phenology and fruit quality in grapevi ... |
| PMC6483340 |
Fig 1 |
Study area. Sugar maple range (adapted from [ 18, 19]), mapl ... |
| PMC6483340 |
Fig 2 |
Belief in climate change. a) Responses of the survey partici ... |
| PMC6483340 |
Fig 3 |
Causes of climate change. a) Responses of the survey partici ... |
| PMC6483340 |
Fig 4 |
General impacts of climate change. a) Responses of the surve ... |
| PMC6483340 |
Fig 5 |
Exposure to past climatic events. Responses of the survey pa ... |
| PMC6483340 |
Fig 6 |
Climate change and tap yield. a) Responses of the survey par ... |
| PMC6483340 |
Fig 7 |
Climate change and maple syrup production. Responses of the ... |
| PMC6483340 |
Fig 8 |
General statements on adaptation to climate change for maple ... |
| PMC6483340 |
Fig 9 |
Specific adaptation measures. Responses of the survey partic ... |
| PMC6483340 |
Fig 10 |
Adaptability and constraints to adaptation. 12. Responses of ... |
| PMC6487044 |
Fig. 1 |
Steps in burden-of-disease estimates for outcomes of mortali ... |
| PMC6487044 |
Fig. 2 |
Annual heat-attributable mortality rate 1971–2000 ( a) and 2 ... |
| PMC6487044 |
Fig. 3 |
Percentage of heat-attributable deaths ( a) and heat-attribu ... |
| PMC6488096 |
Fig 1 |
Ecuador, situated on the northwestern coast of South America ... |
| PMC6488096 |
Fig 2 |
Agreement of best model subsets built with best-ranked suite ... |
| PMC6488096 |
Fig 3 |
Agreement of best model subsets built with best ranked suite ... |
| PMC6488096 |
Fig 4 |
Best model subsets for current and future climate (GCMs proj ... |
| PMC6494948 |
FIGURE 1 |
Map showing Zvimba District. |
| PMC6494948 |
FIGURE 2 |
Rain-fed maize crops in Tigere village. |
| PMC6507478 |
Fig. 1 |
Pathways of climate change and health (adapted from WHO Regi ... |
| PMC6507478 |
Fig. 2 |
Summary of WHO survey responses by topic in 2012 and 2017 (a ... |
| PMC6509208 |
Figure 1 |
Archaeological sites and radiocarbon data: ( a) Kernel-smoot ... |
| PMC6509208 |
Figure 2 |
Test of summed probability distribution of calibrated archae ... |
| PMC6509208 |
Figure 3 |
Permutation test of regional summed probability distribution ... |
| PMC6509208 |
Figure 4 |
Correlating variance in Austral Summer (December-January-Feb ... |
| PMC6509381 |
Figure 1 |
Study area. (a) the northern Chinese coast (b) the southern ... |
| PMC6509381 |
Figure 2 |
The Venn's four‐set diagram. Based on the current habitats a ... |
| PMC6509381 |
Figure 3 |
AICc and smallest AICc values of ecology niche models with d ... |
| PMC6509381 |
Figure 4 |
Model evaluation metrics for ecology niche models at the nor ... |
| PMC6509381 |
Figure 5 |
The spatial distribution of the changed habitats of spartina ... |
| PMC6509395 |
Figure 1 |
Gymnocarpos przewalskii |
| PMC6509395 |
Figure 2 |
Geographical distributions in northwestern China for cpDNA a ... |
| PMC6509395 |
Figure 3 |
The haplotype networks in G. przewalskii. The red circle rep ... |
| PMC6509395 |
Figure 4 |
Above, UPGMA dendrogram between the 17 populations of G. prz ... |
| PMC6509395 |
Figure 5 |
The phylogenetic relationships among G. przewalskii species ... |
| PMC6509395 |
Figure 6 |
Divergence dating (Ma BP.) of both cpDNA and ITS haplotypes ... |
| PMC6509395 |
Figure 7 |
Mismatch distributions based on the cpDNA sequences and ITS ... |
| PMC6509395 |
Figure 8 |
Modeling distribution of G. przewalskii onto the LGM and cur ... |
| PMC6509607 |
Figure 1 |
Maximum monsoon season Standardized Precipitation and Evapot ... |
| PMC6509607 |
Figure 2 |
Effects of average Standardized Precipitation and Evapotrans ... |
| PMC6509607 |
Figure 3 |
Effects of floods during infancy on likelihood of stunting ( ... |
| PMC6509607 |
Figure 4 |
Effects of floods in the 3 months prior to measurement on li ... |
| PMC6514186 |
FIGURE 1 |
Multidimensional scaling analysis of participants, based on ... |
| PMC6514186 |
FIGURE 2 |
Cluster analyses of the sorting task for Audience conditions ... |
| PMC6514186 |
FIGURE 3 |
Cluster analyses of the sorting task for World View conditio ... |
| PMC6514186 |
FIGURE 4 |
Similarity of a retelling to the original story as a functio ... |
| PMC6514186 |
FIGURE 5 |
Similarity of a retelling to the original story as a functio ... |
| PMC6514186 |
FIGURE 6 |
Similarity of a retelling to each of the story characters as ... |
| PMC6514186 |
FIGURE 7 |
Similarity of a retelling to each of the story characters as ... |
| PMC6514186 |
FIGURE 8 |
Proportion of words from each category as a function of Term ... |
| PMC6516649 |
Fig 1 |
Study area. |
| PMC6516649 |
Fig 2 |
Methodology framework adopted in this study. |
| PMC6516649 |
Fig 3 |
Characteristics of the Adyar Sub-basin. (A) Digital elevatio ... |
| PMC6516649 |
Fig 4 |
Extremely heavy rainfall events based on the observed data ( ... |
| PMC6516649 |
Fig 5 |
Extremely heavy rainfall events based on the projected data ... |
| PMC6516649 |
Fig 6 |
IDF curves for Meenambakkam station rainfall for the period ... |
| PMC6516649 |
Fig 7 |
IDF curves for four GCMs used in this study for the period 2 ... |
| PMC6516649 |
Fig 8 |
Land use pattern for the year 2016. |
| PMC6516649 |
Fig 9 |
Comparison of peak discharge between observed and projected ... |
| PMC6516649 |
Fig 10 |
Comparison of the flooded area between observed and projecte ... |
| PMC6516649 |
Fig 11 |
Flood inundation map for 2, 5, 10, 50 and 100 year rainfall ... |
| PMC6516649 |
Fig 12 |
Flood inundation map for 2, 5, 10, 50 and 100 year rainfall ... |
| PMC6516649 |
Fig 13 |
Flood inundation map for 2, 5, 10, 50 and 100 year rainfall ... |
| PMC6516649 |
Fig 14 |
Flood inundation map for 2, 5, 10, 50 and 100 year rainfall ... |
| PMC6516649 |
Fig 15 |
Flood inundation map for 2, 5, 10, 50 and 100 year rainfall ... |
| PMC6519841 |
Fig 1 |
Historic and modern sampling localities. Tamias speciosus an ... |
| PMC6519841 |
Fig 2 |
Temporal and spatial population genetic structure. (A) Genet ... |
| PMC6519841 |
Fig 3 |
Population histories inferred with Approximate Bayesian Comp ... |
| PMC6519841 |
Fig 4 |
Derived alleles showing significant frequency shifts between ... |
| PMC6520021 |
Fig. 1 |
Climate warming across Europe and geographic locations of th ... |
| PMC6520021 |
Fig. 2 |
Plant species extinctions and subsequent coextinction cascad ... |
| PMC6520021 |
Fig. 3 |
Coextinctions may target different plant species than climat ... |
| PMC6520021 |
Fig. 4 |
The pruning of plants’ phylogenetic and functional trees thr ... |
| PMC6520021 |
Fig. 5 |
Plant vulnerability across orders and functional groups. The ... |
| PMC6525669 |
Fig. 1 |
Theoretical model for analyzing farmers’ individual percepti ... |
| PMC6527881 |
FIGURE 1 |
A schematic diagram illustrating the photosynthetic carbon a ... |
| PMC6527881 |
FIGURE 2 |
A simplified model for the processes involved in the convers ... |
| PMC6528024 |
Figure 1 |
Effects of acclimation temperature and test temperature on t ... |
| PMC6529159 |
Fig 1 |
Map of the study area and occurrence records. Study area, in ... |
| PMC6529159 |
Fig 2 |
Map of current potential habitat (CPH) of Mussismilia hartti ... |
| PMC6529159 |
Fig 3 |
Map of future potential habitat (FPH) of Mussismilia harttii ... |
| PMC6529159 |
Fig 4 |
Map of future potential habitat (FPH) of Mussismilia harttii ... |
| PMC6529159 |
Fig 5 |
Map of future potential habitat (FPH) of Mussismilia harttii ... |
| PMC6529642 |
Figure 1 |
Image-rating task screens. Participants were asked to rate t ... |
| PMC6529642 |
Figure 2 |
(A) There was a strong, positive correlation between images ... |
| PMC6529642 |
Figure 3 |
The 32 images rated highest in relevance to climate change, ... |
| PMC6529642 |
Figure 4 |
The 32 images rated lowest in relevance to climate change, r ... |
| PMC6529642 |
Figure 5 |
(A) There was a strong, positive relationship between the av ... |
| PMC6530845 |
Fig 1 |
The study area. (The GTOPO30 DEM data are from USGS, https:/ ... |
| PMC6530845 |
Fig 2 |
The spatial distribution of average SSM in the TRB from 1961 ... |
| PMC6530845 |
Fig 3 |
The interannual variation of the annual average SSM in the T ... |
| PMC6530845 |
Fig 4 |
The seasonal variation of SM at 0–10 cm in the TRB. |
| PMC6530845 |
Fig 5 |
The seasonal variation of SM at 10–40 cm in the TRB. |
| PMC6530845 |
Fig 6 |
The cross wavelet transform of precipitation and SM (0–10 cm ... |
| PMC6530845 |
Fig 7 |
The cross wavelet transform of precipitation and SM (10–40 c ... |
| PMC6530845 |
Fig 8 |
The cross wavelet transform of temperature and SM (0–10 cm). ... |
| PMC6530845 |
Fig 9 |
The cross wavelet transform of temperature and SM (10–40 cm) ... |
| PMC6531548 |
Figure 1 |
A 3-D model (built by meshing 10 aerial photographs taken by ... |
| PMC6531548 |
Figure 2 |
A graphical representation of the main vegetation detected i ... |
| PMC6531548 |
Figure 3 |
The behavior of allometric parameters (DBH = diameter at the ... |
| PMC6531548 |
Figure 4 |
The complete dendrochronological curve calculated as the mea ... |
| PMC6531548 |
Figure 5 |
The raw time-series (highest plot) is detrended and standard ... |
| PMC6531548 |
Figure 6 |
Scatter plots between basal area, mean annual growth, year o ... |
| PMC6531548 |
Figure 7 |
Left: a schematic representation of the distribution of ages ... |
| PMC6531548 |
Figure 8 |
The variation of mean annual temperature from [ref. 29 ] (le ... |
| PMC6531548 |
Figure 9 |
The autocorrelation function plotted against the different l ... |
| PMC6531548 |
Figure 10 |
The partial autocorrelation function plotted against the dif ... |
| PMC6531548 |
Figure 11 |
The histogram of the block bootstrapping method (left panel) ... |
| PMC6535848 |
Fig. 1 |
Map of Africa delineating drylands. This shows the geographi ... |
| PMC6535848 |
Fig. 2 |
The adaptive cycle showing how changes in social-ecological ... |
| PMC6535848 |
Fig. 3 |
Adaptive management of Vector-borne disease (VBD) risk in a ... |
| PMC6539038 |
Figure 1 |
The simulation domain settings in WRF-Chem, including ( a) t ... |
| PMC6539038 |
Figure 2 |
The spatial distribution of the monthly averaged differences ... |
| PMC6539038 |
Figure 3 |
The spatial distribution of the monthly averaged differences ... |
| PMC6539038 |
Figure 4 |
The spatial distribution of the monthly averaged differences ... |
| PMC6539038 |
Figure 5 |
The spatial distribution of the monthly averaged differences ... |
| PMC6539038 |
Figure 6 |
The spatial distribution of the monthly averaged differences ... |
| PMC6539038 |
Figure 7 |
The spatial distribution of monthly averaged differences of ... |
| PMC6539038 |
Figure 8 |
The vertical distribution along 32° N of monthly averaged di ... |
| PMC6539038 |
Figure 9 |
The spatial distribution of monthly averaged differences of ... |
| PMC6539038 |
Figure 10 |
The spatial distributions of monthly mean H 2O 2/HNO 3 durin ... |
| PMC6539075 |
Figure 1 |
Geographical location of the study area. |
| PMC6539075 |
Figure 2 |
Scatterplot of mean value ( a) and maximum value ( b) of NPP ... |
| PMC6539075 |
Figure 3 |
Local spatial agglomeration ( a, b) and significance ( c, d) ... |
| PMC6539075 |
Figure 4 |
Mean annual NPP from 2000 to 2015 ( a) and the spatial patte ... |
| PMC6539075 |
Figure 5 |
The NPP variation trends ( a), F significance test ( b), CV ... |
| PMC6539075 |
Figure 6 |
Spatial distribution and the T significance test of partial ... |
| PMC6539075 |
Figure 7 |
Future trend analysis of net primary productivity in the stu ... |
| PMC6539193 |
Figure 1 |
Geographical distribution of the 360 weather stations used i ... |
| PMC6539193 |
Figure 2 |
Linear trends and anomalies from annual means of S T max , S ... |
| PMC6539193 |
Figure 3 |
Spatial patterns of changes in soil surface temperatures ( S ... |
| PMC6539193 |
Figure 4 |
Spatial and seasonal patterns of changes in soil surface tem ... |
| PMC6539193 |
Figure 5 |
Partial correlation coefficients between S T max , S T min , ... |
| PMC6539193 |
Figure 6 |
Spatial patterns of changes in sunshine duration (SD) during ... |
| PMC6539193 |
Figure 7 |
( a) Precipitation (p) on annual and seasonal scales in Chin ... |
| PMC6539193 |
Figure 8 |
Linear trends from annual means of daily T D on annual and s ... |
| PMC6539193 |
Figure 9 |
Time series and linear trends from annual means of S T m e a ... |
| PMC6539282 |
Figure 1 |
Study hypotheses and conceptual framework. H1, attitude posi ... |
| PMC6539282 |
Figure 2 |
Results of structural equation modeling. * p < 0.05; *** p < ... |
| PMC6539500 |
Figure 1 |
Factors that influence the psychosocial health impacts of cl ... |
| PMC6541362 |
Fig 1 |
Location and geographic limits of the Caatinga. (A) Geograph ... |
| PMC6541362 |
Fig 2 |
Distribution of suitable habitats of plant species endemic t ... |
| PMC6541362 |
Fig 3 |
Reduction of suitable Caatinga habitat (probability of occur ... |
| PMC6541362 |
Fig 4 |
Distribution of suitable habitat for arboreous species (A, B ... |
| PMC6541362 |
Fig 5 |
Distribution of suitable habitat for plant species endemic t ... |
| PMC6541362 |
Fig 6 |
Distribution of suitable habitat for plants species endemic ... |
| PMC6541362 |
Fig 7 |
Distribution of suitable habitat for plant species endemic t ... |
| PMC6544233 |
Fig 1 |
Impact of mean climate change on crop yield (tons/ha/year). ... |
| PMC6544233 |
Fig 2 |
Six examples showing construction of the regression model re ... |
| PMC6545231 |
Figure 1 |
Procedures for the assessment and methodology for data colle ... |
| PMC6545231 |
Figure 2 |
AHP framework for measuring urban sensibility for the threat ... |
| PMC6545231 |
Figure 3 |
Priority climatic threats in Beijing. The priority climatic ... |
| PMC6545231 |
Figure 4 |
Vulnerability in the climatic thread of drainage floods. The ... |
| PMC6545231 |
Figure 5 |
Vulnerability in the climatic thread of high temperature and ... |
| PMC6545231 |
Figure 6 |
Vulnerability in the climatic thread of drought. The vulnera ... |
| PMC6545231 |
Figure 7 |
Integrated vulnerability to climate change in Beijing. The i ... |
| PMC6547698 |
Figure 1 |
Calculating safety margin at the continental scale. For this ... |
| PMC6547698 |
Figure 2 |
Risk to Australian vegetation from change in mean annual tem ... |
| PMC6547698 |
Figure 3 |
Standardised scores of the safety margins of Australian vege ... |
| PMC6547698 |
Figure 4 |
Relationship between risk and adaptive capacity to climate c ... |
| PMC6547698 |
Figure 5 |
Twenty-two Australian Major Vegetation Groups (MVGs). MVGs h ... |
| PMC6553685 |
Fig 1 |
Endogenous social dynamics influence climate trajectories. S ... |
| PMC6553685 |
Fig 2 |
Peak temperature anomaly strongly depends on individual time ... |
| PMC6553685 |
Fig 3 |
Optimal pathways to mitigation via increasing social learnin ... |
| PMC6553685 |
Fig 4 |
Peak temperature anomaly is sensitive to both social and cli ... |
| PMC6559216 |
Fig. 1 |
Location of study sites across the United Kingdom (UK) and N ... |
| PMC6559216 |
Fig. 2 |
Simulated grain yield and harvest index (HI) of local winter ... |
| PMC6559216 |
Fig. 3 |
Simulated leaf area index ( LAI) at anthesis, grain filling ... |
| PMC6559268 |
Figure 1 |
Locations and county representation of the U.S. Forest Servi ... |
| PMC6559268 |
Figure 2 |
Average annual N deposition from 2005 to 2100, according to ... |
| PMC6559268 |
Figure 3 |
County‐level differences in average annual N deposition, rel ... |
| PMC6559268 |
Figure 4 |
Average annual (a) temperature and (b) precipitation from 20 ... |
| PMC6559268 |
Figure 5 |
County‐level differences in 2100 for average annual temperat ... |
| PMC6559268 |
Figure 6 |
Species‐specific biomass in 2005 and predicted maximum poten ... |
| PMC6559268 |
Figure 7 |
Species composition, as a percentage of total biomass of the ... |
| PMC6559268 |
Figure 8 |
Carbon sequestration (in Tg per 5 yr) in each 5‐yr period fr ... |
| PMC6559268 |
Figure 9 |
Present value (in 2015) of C sequestration in each 5‐yr peri ... |
| PMC6559268 |
Figure 10 |
Percent difference in total merchantable value (TMV) and tot ... |
| PMC6559268 |
Figure 11 |
Variation in county‐level tree species diversity relative to ... |
| PMC6559268 |
Figure 12 |
County‐level change in relative abundance (left column) and ... |
| PMC6560471 |
Fig. 1 |
Temporal coverage trends |
| PMC6561535 |
Fig 1 |
Model schema. Land-use change and climate change affect kit ... |
| PMC6561535 |
Fig 2 |
Modeled population size of female kit foxes under six scenar ... |
| PMC6561535 |
Fig 3 |
Loss of suitable kit fox habitat in the area to the east of ... |
| PMC6561535 |
Fig 4 |
Increased variability in precipitation increases population ... |
| PMC6561978 |
Figure 1 |
Species richness of snakes distributed in the Atlantic Fores ... |
| PMC6561978 |
Figure 2 |
Species richness and turnover patters of snake species acros ... |
| PMC6561978 |
Figure 3 |
Expected changes in the range size of the snakes in the Atla ... |
| PMC6561978 |
Figure 4 |
Range loss projected to 2080. I. species whose loss is estim ... |
| PMC6561978 |
Figure 5 |
Effectiveness of the protected areas of Atlantic Forest in s ... |
| PMC6561978 |
Figure 6 |
Relationship of the mean percentage overlap (MPO, percentage ... |
| PMC6561978 |
Figure 7 |
Brazilian Atlantic Forest Biodiversity Hotspot. Original ext ... |
| PMC6563998 |
Fig 1 |
Maps of cumulative number of species for both Islands. Curre ... |
| PMC6563998 |
Fig 2 |
Projections for locations of Protected Areas calculated with ... |
| PMC6563998 |
Fig 3 |
Projections for locations of protected areas calculated with ... |
| PMC6563998 |
Fig 4 |
Projections for locations of protected areas calculated with ... |
| PMC6563998 |
Fig 5 |
Projections for locations of protected areas calculated with ... |
| PMC6564006 |
Fig 1 |
Appearance of G. bermejoi (A). Maps of the Iberian Peninsula ... |
| PMC6564006 |
Fig 2 |
Habitat suitability predicted by the MaxEnt models for G. be ... |
| PMC6564006 |
Fig 3 |
Habitat suitability predicted by the MaxEnt models for G. be ... |
| PMC6564006 |
Fig 4 |
Habitat suitability predicted by the MaxEnt models for G. be ... |
| PMC6564006 |
Fig 5 |
Habitat suitability predicted by the MaxEnt models for G. be ... |
| PMC6564006 |
Fig 6 |
Bioclimatic niches of G. bermejoi and its parental species ( ... |
| PMC6564006 |
Fig 7 |
Occurrence density curves for specific bioclimatic variables ... |
| PMC6565733 |
Fig. 1 |
The diagram illustrates the four phases to develop the ACCVI ... |
| PMC6565733 |
Fig. 2 |
The top map shows the Inuit Nunangat region—which includes f ... |
| PMC6565733 |
Fig. 3 |
Exposure maps. a Rain exposure maps. Rain exposure model fo ... |
| PMC6565733 |
Fig. 4 |
Rain vulnerability maps. a, b Rain model for airport and ma ... |
| PMC6565733 |
Fig. 5 |
Rain increment maps. a, b Increment percentage/anomalies fo ... |
| PMC6565733 |
Fig. 6 |
Development of the Arctic Climate Change Vulnerability Index ... |
| PMC6565733 |
Fig. 7 |
Normalized climate variables, extreme indices and physical f ... |
| PMC6565733 |
Fig. 8 |
Vulnerability model type I was calculated for all 50 communi ... |
| PMC6571686 |
Figure 1 |
Sketch map of the Heihe River basin and gauging meteorologic ... |
| PMC6571686 |
Figure 2 |
Performances of 23 GCMs for the precipitation, T mean, T max ... |
| PMC6571686 |
Figure 3 |
Spatial variation patterns of the mean annual precipitation ... |
| PMC6571686 |
Figure 4 |
Spatial variation patterns of the T mean under ( a) RCP2.6; ... |
| PMC6571686 |
Figure 5 |
Spatial variation patterns of the T max under ( a) RCP2.6; ( ... |
| PMC6571686 |
Figure 6 |
Spatial variation patterns of the T min under ( a) RCP2.6; ( ... |
| PMC6571686 |
Figure 7 |
Changes of the mean annual ( a) maize yield and ( b) CWC in ... |
| PMC6571686 |
Figure 8 |
Changes of the mean annual ( a) maize yield and ( b) CWC in ... |
| PMC6571686 |
Figure 9 |
Decadal changes of the maize WP in the ( a) Gaotai area and ... |
| PMC6571897 |
Figure 1 |
Umbria region (central Italy) and the study grape-wine growi ... |
| PMC6571897 |
Figure 2 |
Annual average temperature (°C) in the grape-wine growing ar ... |
| PMC6571897 |
Figure 3 |
Precipitation in the grape-wine growing area PDO ‘Orvieto’. ... |
| PMC6571897 |
Figure 4 |
Growing Season average Temperature (GST) (°C) trend in the w ... |
| PMC6571897 |
Figure 5 |
( a) Number of days with daily maximum air temperature (Tmax ... |
| PMC6571897 |
Figure 6 |
Ripening dates (technological ripening, harvest) and trend l ... |
| PMC6571897 |
Figure 7 |
Berry quality and extreme temperature events; ( a) titratabl ... |
| PMC6571897 |
Figure 8 |
Total disease control treatments (continued black trend line ... |
| PMC6571897 |
Figure 9 |
Biplots of the climate indices and berry quality traits alon ... |
| PMC6580281 |
Figure 1 |
Geographic distribution of sampling sites in China. Temperat ... |
| PMC6580281 |
Figure 2 |
Structural equation models (SEMs) accounting for the direct ... |
| PMC6580281 |
Figure 3 |
Relative contribution of the different predictors used to mo ... |
| PMC6580281 |
Figure 4 |
Structural equation models (SEMs) accounting for the direct ... |
| PMC6582658 |
Figure 1 |
Potential for global distribution and abundance of female Ae ... |
| PMC6582658 |
Figure 2 |
Change in the potential abundance of Aedes aegypti (per larv ... |
| PMC6582658 |
Figure 3 |
Change in the potential abundance of Aedes aegypti (per larv ... |
| PMC6582658 |
Figure 4 |
Relative changes (%) in the global potential abundance of Ae ... |
| PMC6582658 |
Figure 5 |
Model comparison of different drivers on the global distribu ... |
| PMC6582658 |
Figure 6 |
Comparison two-decades averaged global distribution of femal ... |
| PMC6583992 |
Fig 1 |
Map of Nigeria with georeferenced sampling points of Anophel ... |
| PMC6583992 |
Fig 2 |
Prevalence of An. gambiae species under low and high emissio ... |
| PMC6583992 |
Fig 3 |
Potential occurrence and distribution of An. gambiae s.l. in ... |
| PMC6583992 |
Fig 4 |
Mean distribution density of An. gambiae species in each Nig ... |
| PMC6583992 |
Fig 5 |
Potential occurrence and distribution of An. gambiae s.s. in ... |
| PMC6583992 |
Fig 6 |
Potential occurrence and distribution of An. arabiensis in N ... |
| PMC6586318 |
Fig 1 |
Kanakaleonui Bird Corridor (KBC) on Hawai‘i Island. Seedling ... |
| PMC6586318 |
Fig 2 |
Survival (±SE) of 896 seedlings over a 20 week period. Seedl ... |
| PMC6586318 |
Fig 3 |
Average growth (±SE) of 744 seedlings over a 20 week period. ... |
| PMC6586835 |
Figure 1 |
Nesting beaches for loggerhead turtles in Brazil. From north ... |
| PMC6586835 |
Figure 2 |
Monthly averages for hatching success (bars) at ( a, b) Bahi ... |
| PMC6586835 |
Figure 3 |
Monthly averages for emergence rate (bars) at ( a, b) Bahia, ... |
| PMC6586835 |
Figure 4 |
Monthly climatic conditions for each state (line) and propor ... |
| PMC6586835 |
Figure 5 |
Best fit models descibing ( a– c) hatching success and ( d– ... |
| PMC6586835 |
Figure 6 |
Historic averages (solid points) and projected values of air ... |
| PMC6586835 |
Figure 7 |
Historic averages (solid points) and projected values of pre ... |
| PMC6586835 |
Figure 8 |
Historic average (solid point) and projected hatching succes ... |
| PMC6587073 |
Fig. 1 |
Framework on climate change and its impact on health (adapte ... |
| PMC6589993 |
Figure 1 |
Locations of the 12 collection sites in West Bengal, India, ... |
| PMC6589993 |
Figure 2 |
Graphical outline of Experiment 1 showing the origin of the ... |
| PMC6589993 |
Figure 3 |
Graphical outline of Experiment 2 showing the origin of the ... |
| PMC6589993 |
Figure 4 |
The effect of laboratory acclimation and short- and long-ter ... |
| PMC6589993 |
Figure 5 |
The relationship between site/acclimation temperature and ( ... |
| PMC6589993 |
Figure 6 |
The relationship between thermal tolerance (CT max) and cond ... |
| PMC6591298 |
Fig. 1 |
Changes in the main drivers of energy demand between 2010 an ... |
| PMC6591298 |
Fig. 2 |
The total energy demand exposed to changes in cold and hot d ... |
| PMC6591298 |
Fig. 3 |
Global total energy demand amplification from climate change ... |
| PMC6591298 |
Fig. 4 |
Agreement across ESMs on changes in final energy demand. Map ... |
| PMC6591298 |
Fig. 5 |
Exposure of people with different adaptation challenges to c ... |
| PMC6591298 |
Fig. 6 |
Brief overview of the methodology of this study and its rela ... |
| PMC6591433 |
FIGURE 1 |
Participant responses to the survey questions designed to ca ... |
| PMC6591433 |
FIGURE 2 |
Regression plots showing the significance of cultural values ... |
| PMC6592885 |
Figure 1 |
Sites involved in the study, marked according to their compl ... |
| PMC6592885 |
Figure 2 |
Climate change impact on rice yields (% compared to the base ... |
| PMC6592885 |
Figure 3 |
Agreement between generated and reference baselines. Line co ... |
| PMC6592885 |
Figure 4 |
p-values for sources of variation affecting the difference b ... |
| PMC6592885 |
Figure 5 |
Probability to have the same density distribution for differ ... |
| PMC6592885 |
Figure 6 |
p-value for factors affecting the indices (described in Supp ... |
| PMC6592904 |
Figure 1 |
( a) Map of the Pearl River basin including elevation, tribu ... |
| PMC6592904 |
Figure 2 |
The spatio-temporal evolution of fluvial sediment loads alon ... |
| PMC6592904 |
Figure 3 |
Comparison between sediment loads predicted using the Phase ... |
| PMC6592904 |
Figure 4 |
The fluvial sediment supply to the coast over the period 195 ... |
| PMC6592904 |
Figure 5 |
Computational procedure followed to calculate fluvial sedime ... |
| PMC6597063 |
Fig 1 |
Conceptual model to prepare the maps of land suitability for ... |
| PMC6597063 |
Fig 2 |
The map of land suitability of walnut cultivation in Iran fo ... |
| PMC6597063 |
Fig 3 |
Classification of Iran for walnut cultivation regarding maxi ... |
| PMC6597063 |
Fig 4 |
Classification of Iran’s land for walnut cultivation regardi ... |
| PMC6597063 |
Fig 5 |
The map of land suitability for walnut cultivation in Iran ( ... |
| PMC6597076 |
Fig 1 |
Set-up of the model chain. Box 1–2 show the two models that ... |
| PMC6597076 |
Fig 2 |
Maps of predicted mean aflatoxin (AfB1) concentration (μg/kg ... |
| PMC6597871 |
Figure 1 |
Melipona subnitida sampling locations across northeastern Br ... |
| PMC6597871 |
Figure 2 |
Map showing Melipona subnitida assignments to four genetic c ... |
| PMC6597871 |
Figure 3 |
Spatial autocorrelation in genetic relatedness. The black so ... |
| PMC6597871 |
Figure 4 |
Isolation‐by‐resistance effects across the entire distributi ... |
| PMC6597871 |
Figure 5 |
Venn diagram showing the intersection of sequences (contigs) ... |
| PMC6597871 |
Figure 6 |
Spatial distribution of adaptive genetic variability in Meli ... |
| PMC6603027 |
Figure 1 |
Study area corresponding to the historical centre of the cit ... |
| PMC6603027 |
Figure 2 |
Comparison of floristic data reported in the two reference s ... |
| PMC6603027 |
Figure 3 |
Comparison of chorotypes between “Gabelli, 1894” 18 and “Sal ... |
| PMC6603027 |
Figure 4 |
Ellenberg indicator values for “Gabelli, 1894” 18 and “Salin ... |
| PMC6603027 |
Figure 5 |
Floristic richness variation in the different building areas ... |
| PMC6603027 |
Figure 6 |
Species richness in Bologna’s different urban areas and corr ... |
| PMC6605068 |
Figure 1 |
Empirical orthogonal function (EOF), correlation, and regres ... |
| PMC6605068 |
Figure 2 |
As in Figure 1 but for coarse dust (CD). |
| PMC6605068 |
Figure 3 |
Projected changes in annual mean (a) fine dust and (b) coars ... |
| PMC6605068 |
Figure 4 |
Total annual incidence (sum of reference and excess burdens) ... |
| PMC6605068 |
Figure 5 |
As in Figure 4 but for coarse dust. The health endpoints sho ... |
| PMC6605068 |
Figure 6 |
Total annual economic damages of health impacts related to f ... |
| PMC6606593 |
Figure 1 |
Hydropower exploitation in ( a) and geology of the Alpine Rh ... |
| PMC6606593 |
Figure 2 |
Lake Geneva showing the sites of sample cores ( a) and the 1 ... |
| PMC6606593 |
Figure 3 |
Time series of annual data for basin-averaged mean annual te ... |
| PMC6606593 |
Figure 4 |
Mean annual suspended sediment concentration ( a) and annual ... |
| PMC6614032 |
Figure 1 |
Geographical distribution of SHUE cities and their classific ... |
| PMC6614032 |
Figure 2 |
Increase in T mean in the hottest month vs. in the coldest m ... |
| PMC6614032 |
Figure 3 |
Increase in T mean under RCP2.6 (open triangles) and RCP8.5 ... |
| PMC6614032 |
Figure 4 |
Increases in T mean in the hottest month under RCP2.6 (blue) ... |
| PMC6614032 |
Figure 5 |
Increases in T mean for the hottest month relative to 2017: ... |
| PMC6614032 |
Figure 6 |
Increase in T mean in the hottest month by 2100 (relative to ... |
| PMC6615616 |
Fig 1 |
Map of the Dinki watershed, central highlands of Ethiopia. |
| PMC6615616 |
Fig 2 |
The core-resilience capacities (a) and resilience status of ... |
| PMC6615616 |
Fig 3 |
Resilience typologies by households’ monthly income. |
| PMC6619606 |
Fig 1 |
Distribution of current and future cities along the first 4 ... |
| PMC6619606 |
Fig 2 |
Extent of climate changes in major cities of the world by 20 ... |
| PMC6619606 |
Fig 3 |
Future cities and similar current climate counterpart. Diffe ... |
| PMC6619606 |
Fig 4 |
Latitudinal shift of cities relative to their distance to th ... |
| PMC6619692 |
Fig 1 |
Summary of projections of rainfall extremes for the Caribbea ... |
| PMC6619692 |
Fig 2 |
Vulnerability rank of some Caribbean countries. EcVI is the ... |
| PMC6619692 |
Fig 3 |
Schematic on approaches used in study. |
| PMC6619692 |
Fig 4 |
Spatial distribution of ranking of countries based on each s ... |
| PMC6619692 |
Fig 5 |
Ranking of stations using CVS. Calculated from historical da ... |
| PMC6619692 |
Fig 6 |
Annual extreme rainfall averages calculated over 1985 to 200 ... |
| PMC6619692 |
Fig 7 |
Future scenarios of RX1, RX5 and R10 for the 2050s under the ... |
| PMC6619692 |
Fig 8 |
Ranking of countries based on Caribbean vulnerability scores ... |
| PMC6619692 |
Fig 9 |
Ranking of countries based on Caribbean vulnerability scores ... |
| PMC6619988 |
Fig 1 |
Should increased exploration and drilling for oil, or increa ... |
| PMC6619988 |
Fig 2 |
Is climate change happening now, caused mainly by human acti ... |
| PMC6619988 |
Fig 3 |
Weighted percentages for “renewable energy higher priority” ... |
| PMC6619988 |
Fig 4 |
Weighted percentages for “climate change happening now, caus ... |
| PMC6619988 |
Fig 5 |
Weighted percentages and 95 percent confidence intervals for ... |
| PMC6619988 |
Fig 6 |
Weighted percentages and 95 percent confidence intervals for ... |
| PMC6619988 |
Fig 7 |
Weighted percentages “climate change happening now, caused m ... |
| PMC6619988 |
Fig 8 |
Linear (ordinary least squares) trends by age group on state ... |
| PMC6619988 |
Fig 9 |
Linear (ordinary least squares) trends by age group on north ... |
| PMC6619988 |
Fig 10 |
Probability of prioritizing renewable energy, or recognizing ... |
| PMC6620267 |
Figure 1 |
Seasonality in ( a) the average potable water quality, and ( ... |
| PMC6620267 |
Figure 2 |
Average trihalomethanes formation potential (THMFP) in ( a) ... |
| PMC6620267 |
Figure 3 |
( a) Temperature and ( b) DOC concentration effect on the tr ... |
| PMC6620486 |
FIGURE 1 |
Maps for Zimbabwe, Mashonaland Central province and Mount Da ... |
| PMC6620486 |
FIGURE 2 |
Respondents’ perceptions of the health hazards experienced b ... |
| PMC6620488 |
FIGURE 1 |
A conceptual framework for studying climate change and rural ... |
| PMC6620488 |
FIGURE 2 |
Schematic illustration of the rural transport adaptation opt ... |
| PMC6620496 |
FIGURE 1 |
Cape Town Metropolitan Municipality. |
| PMC6620496 |
FIGURE 2 |
Trends in dam water levels for six largest dams supplying Ca ... |
| PMC6620496 |
FIGURE 3 |
Using 50 L of water per day ‘wisely’. |
| PMC6620496 |
FIGURE 4 |
Key state institutions involved in Day Zero. |
| PMC6620500 |
FIGURE 1 |
Conceptual framework. |
| PMC6620500 |
FIGURE 2 |
Map of study area (GIS generated). |
| PMC6620506 |
FIGURE 1 |
Location of study area. |
| PMC6620506 |
FIGURE 2 |
Responses on observed river levels. |
| PMC6620506 |
FIGURE 3 |
Farm operational cost structure. |


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Fig. 1
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Growth of research output and media production relating to c ... |
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Fig. 2
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Prominent climate change contrarians (CCCs) and scientists ( ... |
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Fig. 3
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Discrepancy in scientific authority and media visibility—gro ... |
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Fig. 4
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Discrepancy in scientific authority and media visibility—ind ... |
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Fig. 5
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How climate change contrarians (CCCs) and climate change sci ... |
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Fig. 6
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Media article co-visibility network—individual level. Cluste ... |
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Fig. 7
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Research article citation network—group and individual level ... |


cooking spray
2 tablespoons butter
3 cloves garlic, minced
2 tablespoons all-purpose flour
¾ cup milk
½ cup freshly grated Parmesan cheese
salt and ground black pepper to taste
2 large potatoes, peeled and thinly sliced
Instructions Checklist
Preheat oven to 400 degrees F (200 degrees C). Spray 12 muffin cups with cooking spray or grease with butter.
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Heat butter in a saucepan over medium heat. Cook and stir garlic in the melted butter until fragrant, about 1 minute. Add flour to garlic mixture; cook and stir until mixture is smooth and thickened, about 2 minutes.
Slowly pour milk into flour-butter mixture while continuously stirring with a whisk until sauce is smooth and thickened, about 5 minutes. Remove saucepan from heat and stir Parmesan cheese into sauce until cheese melts from the heat of the sauce; season with salt and pepper.
Divide the potatoes among the 12 prepared muffin cups and spoon cheese sauce over potatoes.
Bake in the preheated oven until potatoes are tender, about 25 minutes.
92.4 calories; protein 3.2g 7% DV; carbohydrates 12.8g 4% DV; fat 3.3g 5% DV; cholesterol 9.2mg 3% DV; sodium 87.6mg 4% DV. Full Nutrition


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