Watch as brazen thieves jack up car and pinch catalytic converter in seconds
Police are urging drivers to protect their vehicles from catalytic converter thieves
by Sian FilcherTerrifying footage has shown just how quickly a catalytic converter can be stolen.
Two thieves were caught on CCTV jacking up a car in a car park, before pinching the converter in just seconds.
One of the men slides underneath the car and cuts the converter from the pipes before taking off in a silver Renault.
Catalytic converters are used to clean up harmful gases in a car's exhaust system.
Thieves target the devices for the precious metals inside the converter, including platinum, palladium and rhodium.
Palladium is currently worth around £1,347 per ounce, while rhodium is worth £4,463 per ounce.
The theft happened at Clifton Park and Ride on Clifton Lane, Nottingham at around 2:30pm on August 6.
Police are now urging drivers to protect their vehicles from catalytic converter thieves, by taking these precautions:
- If you can, park your vehicle in a locked garage when it is unattended.
- If it’s not possible to garage your vehicle, park it in a busy, well-lit area as close to your property as possible.
- Consider installing a Thatcham approved alarm to your vehicle. Ones that activate if your vehicle is lifted or tilted are particularly effective.
- Use a catalytic converter protection device or marking system.
Drivers will know if their catalytic converter has been stolen, as the engine will sound different.
Anyone with information on the theft should call 101, quoting incident number 470 of 6 August 2019.


UKCloud Limited (“UKC”) and Virtual Infrastructure Group Limited (“VIG”) (together “the Companies”) – in Compulsory Liquidation
On 25 October 2022, the Companies were placed into Liquidation with the Official Receiver appointed as Liquidator and J Robinson and A M Hudson simultaneously appointed as Special Managers to manage the liquidation process on behalf of the Official Receiver.
Further information regarding the Liquidations can be found here: https://www.gov.uk/government/news/virtual-infrastructure-group-limited-and-ukcloud-limited-information-for-creditors-and-interested-parties
Contact details:
For any general queries relating to the Liquidations please email<EMAIL_ADDRESS>For customer related queries please email<EMAIL_ADDRESS>For supplier related queries please email<EMAIL_ADDRESS>Janet connectivity FAQs
What is Janet?
Janet is the UK's research and education network. It's connected to all education organisations and research councils.
Janet is a free-of-charge network that eligible UKCloud customers can use; there are no ingress or egress charges for this network. It's presented from our Assured platform and has a current bandwidth capacity of 1Gbps.
Who is entitled to connect to the Janet network?
Any organisation that is either publicly funded or receives government or EU funding to drive digital initiatives is entitled to use the Janet network.
Can I use UKCloud's Janet connection without using cloud services provided by UKCloud?
No. We can only provide a Janet connection to customers who use our cloud services.
Does UKCloud provide local connections to the Janet network?
No. We can't arrange Janet connections to third-party offices. We only enable our customers and partners to provide services via the Janet network, using applications and solutions hosted on the UKCloud Assured OFFICIAL security domain.
Does UKCloud support dedicated Janet connections?
Yes. Our HybridConnect service option enables customers and partners to provide their own private circuits, including dedicated Janet connections. If you'd like a dedicated Janet connection to our cloud platform, we can arrange for the installation of dedicated Janet circuits to each of our UK data centres.
How do I get a Janet connection via the UKCloud Assured OFFICIAL security domain?
To place an order for a Janet connection, raise a Service Request via the My Calls section of the UKCloud Portal.
Can I get a Janet connection via the UKCloud Elevated OFFICIAL security domain?
No. Janet connections are available only in our Assured OFFICAL security domain.
I have multiple edges and need to configure a specific Janet route, how do I set this up?
To configure specific routing to allow access to each network, contact UKCloud support for a routing table.
If I already have a Janet connection, can I use cloud services provided by UKCloud?
Yes. A pre-existing connection to Janet will reduce the amount of time required to provision services via the Janet network based on the UKCloud Assured OFFICIAL security domain.
Is there an SLA on Janet connectivity?
We provide an SLA for availability of our core services such as UKCloud for VMware and UKCloud for OpenStack. We cannot provide an SLA on external services as they are outside of our control.
How can I create an allow-list of source Janet IP addresses on the edge gateway?
You can log in to VMware Cloud Director via the UKCloud Portal and edit the firewall settings to allow or deny incoming connections from external IP addresses. See How to create firewall rules for more details.
Can I use UKCloud as a transit or gateway between different connections?
No. Our cloud platform is designed so that all traffic either originates or terminates within our platform. We can't facilitate routing between connections. If your solution needs to service users on different networks, this will need to be implemented, managed and accredited within your application or through an authorised gateway service.
Is there a minimum commitment period?
There is no minimum commitment for Janet connectivity.
How will I be billed?
There is no charge for Janet connectivity or for the first IP address for each data centre you connect to the Janet network.
Additional IP addresses will need to be justified and an administration fee will apply of £20 per additional IP address that is set up.
There is no charge for bringing your own Janet IP addresses.
Will I incur an upfront cost (setup fee)?
UKCloud will set up new connections to the Janet network for you free of charge.
Feedback
If you find a problem with this article, click Improve this Doc to make the change yourself or raise an issue in GitHub. If you have an idea for how we could improve any of our services, send an email to feedback@ukcloud.com.


WITNESS LIST Pensions & Investments Committee (Subcommittee on Social Investing) February 23, 1998-10:30A Social Investing Against: Brown, Paul R. (FRRF, Chairman) Del Llano, Ann (ACLU of Texas) Forse, Don T. (American Family Assoc.) Kennedy, Peter (Atty (Brown v. Morales)) On: Beckett, Sheila (ERS) Doyle, Mike (Comptroller) Dunlap, Charles (TRS) Morgan, Todd (Tx. Tomorrow Fund) Murray, Dean (Perm School Fund) Ricks, Tom (UT Investment Mgt Co.) Registering, but not testifying: Against: Lolley, Diana (TEXPERS) Wilkison, Charlie (CLEAT) On: Reissman, Kathy-Ann (ERS (Resource Wns))


Institute of Health Systems (IHS) is a civil society institution established in 1990. The objectives of IHS are to promote and provide for study of health systems, health policy, health services management, health economics and medical sociology. The Institution has built up capacity in application of information technology to health care services.
The IHS has been contributing to the WSP(Water Safety Plan) by organizing expert group meetings and providing inputs for development of health based targets. The Director, IHS serves on the Steering Committee on Water Safety Plans and Saritha K, Head, WQTS, IHS serves on Task Force for Monitoring implementation of Water Safety Plans constituted by the HMWSSB.
To improve the efficacy, quality & equity of Health Systems.
Groom Skills, Gather Evidence and Generate Knowledge for people's health.
The IHS has been contributing to the WSP(Water Safety Plan) by organizing expert group meetings and providing inputs for development of health based targets. The Director, IHS serves on the Steering Committee on Water Safety Plans and Saritha K, Head, WQTS, IHS serves on Task Force for Monitoring implementation of Water Safety Plans constituted by the HMWSSB.
Protecting public health by easily accessible tests of water quality. Services include, basic & complete potability tests, bacteriological analysis, ground water potability & specified single or multiple parameter tests. The lab provides independent water quality monitoring of water in identified slum areas supplied by the Hyderabad Metro Water Supply & Sewerage Board.
Protecting public health by easily accessible tests of water quality. Services include, basic & complete potability tests, bacteriological analysis, ground water potability & specified single or multiple parameter tests. The lab provides independent water quality monitoring of water in identified slum areas supplied by the Hyderabad Metro Water Supply & Sewerage Board.


How well are Bristol City, Leeds United, Nottingham Forest and rest of the Championship backed in the promotion race
The latest Championship winner and promotion odds from The Pools
by Paul ClarkFulham host Queens Park Rangers this Friday as the seesaw nature of the Championship returns to our screens after 16 rounds of wild action already.
Just seven points separate seventh-place Fulham and league leaders West Bromwich Albion, while Birmingham City way down in 13th are only six points off the play-off spots.
With well over half of the league still dreaming of a push for the play-offs and potentially promotion, the latest odds on the Championship certainly make for interesting reading.
It's no surprise that West Brom are among the title favourites and they share the shortest odds with The Pools alongside Leeds United, who are currently third and two points adrift of the Baggies.
Fulham, meanwhile, are the third favourites to life the Championship trophy ahead of the likes of Preston North End and Brentford who round out the top five.
When it comes to promotion odds, the prices are a little shorter.
Leeds are priced at 1/4, West Brom 1/2, Fulham 11/8, Preston 14/5, while Brentford again round out the top five at 3/1.
Here are the Championship winner and promotion odds courtesy of The Pools.
Championship winner odds
Leeds United 21/20
West Bromwich Albion 21/10
Fulham 8/1
Preston North End 14/1
Brentford 18/1
Nottingham Forest 25/1
Swansea City 25/1
Bristol City 33/1
Sheffield Wednesday 50/1
Cardiff City 80/1
Queens Park Rangers 125/1
Hull City 125/1
Derby County 150/1
Millwall 200/1
Birmingham City 200/1
Blackburn Rovers 250/1
Reading 250/1
Charlton Athletic 250/1
Stoke City 500/1
Huddersfield Town 500/1
Middlesbrough 750/1
Barnsley 1000/1
Wigan Athletic 1000/1
Luton Town 1000/1
Championship promotion odds
Leeds United 1/4
West Bromwich Albion 1/2
Fulham 11/8
Preston North End 14/5
Brentford FC 3/1
Swansea City 11/2
Nottingham Forest 11/2
Bristol City 7/1
Sheffield Wednesday 15/2
Cardiff City 16/1
Queens Park Rangers 18/1
Hull City 25/1
Derby County 28/1
Blackburn Rovers 33/1
Millwall 33/1
Birmingham City 33/1
Reading 40/1
Charlton Athletic 40/1
Stoke City 40/1
Huddersfield Town 50/1
Middlesbrough 80/1
Wigan Athletic 125/1
Luton Town 150/1
Barnsley 250/1
Get lots more news, opinion and transfer updates on our Bristol City FC page and add a bookmark to find it quickly next time.


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1. The Polybius Square is essentially identical to the simple substitution cipher, except that each plaintext character is enciphered as 2 ciphertext characterss
2. each character in the plaintext is replaced with 2 characters in the cipher alphabet.
1. Enter the text to encrypt
2. Click on cipher button to encrypt the text.
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(.) hospitals EVD place healthcare patients workers survey cases needed Control suspected Ebola Infection care preparedness countries respondents PPE {border-style use available guidelines px;} #ffffff;} control Action action hand management staff support disease infectious outbreak %), %). IPC Africa admitting facilities hospital infection isolation medical training virus admit West ensure global majority provide regular Hospitals Table areas competency emerging equipment prevention rooms (would) EDV Significance aware cleaning clinical diseases hygiene need patient process professionals px; safe {font-family (Table African European Health addition, affected appropriate case compared font-size identified international members questionnaire suspect waste Disease World activities agents availability checklist cough countries. current double; etiquette half high hospitals, hospitals. measures national non-admitting plans prompt protocols related removal results risk services specialized surveillance systems teams test transfer transmission < accessible actions assess assessed better body border-color border-width concern data did disposal essential frontline health implementation laboratory level necessary notification plan point policy practices precautions procedures progress protective remaining renal reports resource respirator response safety solid; subsequently supplies supportive taken time timely travelers treatment version whilst working {font-style {font-weight Additional BA, Clinical Communication Compliance Education Essential Human ISC Infect International Isolation Preparedness Prevention Whilst, accordance alcohol analysis article audited bold centre. circulated correction courier; deaths detection developed disseminated em; exposed feedback fever general globe. handling human immediate implemented levels low manage new number order patients, performed probable provided providing pt;} public regularly replacement reported representative represented required respectively). returning rub sequence sick stakeholders therapeutics understand unexpected unexplained used work


I am a
"Every once in a while, a new technology, an old problem, and a big idea turn into an innovation."
I was born on a small island in the South Pacific and came to America to look for a better opportunity. I grew up in San Jose, CA and worked for my father’s videography company. My position in the family business was to work with computer programs such as Photoshop and Vegas pro. It is through this experience that I developed a passion for technology and aspire to become a Software Engineer. Some of my other passions include traveling with my family, creating and playing music, and playing and watching basketball.
I currently am in the process of completing my Computer Science degree at Utah Valley University. I returned to San Jose to attend Coding Dojo where I advanced my skills in the MEAN, Java, and Python stacks. I specialize in using these languages to create software that caters to individuals, small-businesses, and enterprise level corporations. Knowing that there is no limit to the things that I can create drives my passion for software engineering. I aspire to help bring other’s innovative ideas into reality, so let’s get to work.
Are you looking to start your next project with me? Go ahead and leave me a message and I will get back to you as soon as possible.


Educational background.
| Level |
years |
| Primary School |
2004-2011 |
| Secondary School |
2012-2016 |
| College education |
2016-2018 |
| Currently in Moringa School |
2020 jan-2020 july |
Job experience
Eugene has been equiped with different job skills that has enabled him acquire this skills
Being into different working sites below here are some of the jobs
After completion of my college education which i was persuing Financial sales i hapenned
to join ICEA and i worked there for an year.
Worked also as a handcraft guy in a local building site .
Involved in some mentor-community work projects that aparently was run quarterly
Involved in a community project that involved constructing fences garbage collection
Projects
Through Moringa school i was equiped with the different skills in the tech world and through this having made me become a world class develeper.
Here are some of the projects.
- My farm
This was a group project where I was a member. The project was aimed at improving farmers' progress in their work.
 It showed how the company tackled waste management.


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Detailed View and Generate Reports
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{{ det.member_id }}
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[foo](bar/{})
[dom](${name} was born in ${country}./{'country':'Antarctica','name':'Lomax'})
[default](hmm/{'age':25})


I moved this year to "Linux only" (Mint) and I have not yet had the occasion to setup the necessary tools to do AVR development on the PC. This is the occasion to start and document, so that I can do it the same way on all the PCs at home...
Presentation
Principle
I will go 2-flavor: the Arduino suite (for arduinos !) and the AVR toolchain (for all the other MCUs).
Arduino toolchain
Foreword
I'm using LInux Mint 19 (based on Ubuntu 18.04 LTS). **DO NOT USE THE PACKAGES THAT COME WITH MINT 19**, they are totally outdated. It's a shame but that's how it is.
We need to take a detour for doing the install the right way.
Install
That one is easy: go to the [[https://www.arduino.cc/en/main/software|arduino website]] and download the latest .tar.xz file. You can then //tar -zxf// it or just double click and put the insides somewhere. No need to run the installer unless you want to setup the icons. There, install completed!
**Nota bene:** regarding the //where// to install, I did in /usr/local/apps (which I created). Where to install software in Linux is an eternal debate, so I picked here, but it doesn't matter it will work anywhere.
Setup
AVR toolchain
Foreword
I'm using LInux Mint 19 (based on Ubuntu 18.04 LTS). **DO NOT USE THE PACKAGES THAT COME WITH MINT 19**, they are totally outdated. It's a shame but that's how it is.
We need to take a detour for doing the install the right way.
Install
I followed [[https://www.instructables.com/id/How-to-get-started-with-Eclipse-and-AVR/|this doc]] with minor editions/customizations. We'll use the [[http://avr-eclipse.sourceforge.net/wiki/index.php/The_AVR_Eclipse_Plugin|AVR Eclipse plugin]].
* Get Eclipse, download the **[[https://www.eclipse.org/downloads/packages/|Eclipse IDE for C/C++ Developers]]**, not the regular (Java).
* Get some packages while it downloads sudo apt-get install gcc-avr binutils-avr gdb-avr avr-libc avrdude
* Install Eclipse in your /opt folder, //tar zxvf// the file
* In Eclipse, Help > Install new software ... > add this source "http://avr-eclipse.sourceforge.net/updatesite/" and install
* Manual for a first build is [[http://avr-eclipse.sourceforge.net/user%20manual/gettingstarted/gs_newproj.html|here]]
* (note that on Linux Mint 19 I didn't have to do the operations I described [[linux mint|here]] to enable my mkII programmer, it worked out of the box)
Setup
Well it just works, that's great. As [[https://www.instructables.com/id/How-to-get-started-with-Eclipse-and-AVR/|this doc]] explains:
* File > New > Project ... > "C Project"
* Pick "AVR Cross Target Application"
* Choose the mCU and F_CPU
* Once project created, right-click > Properties
* AVR > AVRDude : pick your programmer
* C/C++ Build > Settings:
* * Optimization : set the optimization (default none)
* * Additional tools in the toolchain: make sure to check "generate the HEX for Flash" in your Release config (and check AVRDude for update on the fly if you want)
I tried 2 projects, one hello world and the [[USB without Arduino|USB keyboard]] sample: just worked like a breeze. No issue or none worth even mentionning. Linux rules! (^_^)b
Pictures
Links
Helpful sources
Inspiration


| DOSE: T+ 0:00 |
135 mg |
oral |
MDMA |
(capsule) |
| T+ 1:30 |
135 mg |
oral |
MDMA |
(capsule) |
here's a little bit of background that pertains to my tale... my dabbling in perception altering substances have been few & rather far between, consisting of 6 MDMA experiences & one rather unsettling LSD trip. i drink & smoke weed when the occasion permits, but not @ levels that seriously alter my reality. the main thing to bear in mind, dear reader, is that prior to the story that is about to unfold, i was a very depressed individual. i suffered from severe self esteem problems mostly centering around poor body image, & it had been interfering in my daily life for many years. w/ the aid of this wonderful empathogen, i was able to permanently change the way i perceive myself & the world, & consequently have been far happier in my life since this occurred. read on...
one night i had the wonderful good luck to run across 2 capsules of pure MDMA- 135 milligrams a piece of the good stuff, straight from the chemist, not cut w/ speed or anything else the way your average tablet of street E is. the two friends (D & J)i was w/ that night decided that it would be a good time for them to roll for the first time (D had a capsule of the same stuff i did, & J had a tablet of street E that was known to be strong but speedy) i agreed to roll w/ them, & sort of babysit them through the experience. in the past i'd never needed to take more than one tablet of E (approx. 125mgs of MDMA) to really feel it, so i thought that one of these capsules would work just fine. i passed out a multivitamin to my trip companions because i've found the magnesium in them stops jaw clench & eye jitters, & the vitamin C is good for you =) i took 400mg of advil for a headache, but i doubt that impacted my experience @ all.
9:30pm- down the hatch! we all down our respective pills w/ a grin & set off for a friend's house to relax & wait for them to hit.
10:00- J's E hits him suddenly, rocketing him to the peak almost instantly... his eyes are jittering around from the speediness of his tablet, but he's in heaven playing w/ ice cubes & hugging.
10:30- D & i are ~barely~ feeling the twinges of the come on, but he's feeling it more than i am
10:45- D beginning to come up noticeably, i'm still not really feeling it, & grow suspicious; was i cheated by the dealer? its NEVER taken this long for MDMA to affect me before!
11:00- i lose my patience & take the second capsule, wanting to be @ the same level as my companions.
11:15ish- time sort of gets lost around here... the come up i was feeling keeps growing & growing, sort of like a psychedelic snowball rolling down a mountain! i don't feel the sharp *peak* of street E, but rather this incredibly gentle but utterly irresistible wave of enhanced perception & sensation. i feel briefly guilty as i realize that D & J, who i'm supposed to be caring for, are supporting me between them as my head rolls around on my shoulders... they're engaged in deep conversation while i'm past the ability to verbalize & instead just lost in the tactile aspect of the drug.
i spend a good 3 hours floating in the grips of a ~VERY~ powerful plateau/peak, cuddling w/ my friends & silently absorbing their conversations, thrilled to know that they are getting something very meaningful out of this experience even if their 'trip-sitter' has melted into little more than a human pillow *grin*. by the time i'm 'down' enough to talk, they're both on the sleepy part of their come-downs, & so just sit smiling as i jabber & laugh to them about all the things that have occurred to me during the roll. after a lengthy & very uplifting conversation w/ them, we part ways & i return home, still WAY above baseline.
@ home i catch a glimpse of myself in my mirror, & this catalyzes some reaction deep inside of me. in my heightened state i see (for the first time) my own beauty! trivial though it sounds, it was a mind shattering realization for me, considering in the past mirrors had literally brought me to tears. in my previous experiences w/ MDMA i had always been struck w/ the exquisite beauty of my friends & surroundings, but i had never seen myself through that perceptual lens. i spend a good 2 hours writing down my personal revelations about myself while looking into a mirror, giggling & smiling ear to ear in sheer delight!
i finally fall asleep sometime before dawn, exhausted & ecstatic, & still nowhere near sober...
although my pupils had returned to their normal size (my pupils become EXTREMELY dilated while i'm under the influence of MDMA) & i wasn't feeling the physical 'roll' of the MDMA, i was still very affected by it until late afternoon/early evening the next day. i was quiet & subdued, but in the same state of heightened empathy i usually only experience during the peak of a roll. that night i finally returned to baseline, but w/ a wonderful feeling of peace w/ myself.
it has been over a week since this experience, & i still retain that wonderful sense of inner calm. my reflection greets me w/ a sly, almost mischievous smile now instead of a disparaging look of disgust, & the world seems a little brighter. i don't advocate looking for peace in a pill, & in fact i don't think that was where i ~really~ found it, but i do think everyone should be aware of the amazing effects that empathogens can have upon one's mind when the time is ripe for a change in how you view yourself & the world. blessed be.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


SemiSphere rotates a semi-spherical "solid" body of revolution.
module modSemiSphere <src_file = "semisphr.cxx", cxx_hdr_files = "fld/Xfld.h"> { // Inputs int+IPort2 active = 1; int+IPort2 num_thetas = 10; float+IPort2 r_outside; float+IPort2 r_inside; float+IPort2 z_offset; float+IPort2 half_angle; float+IPort2 density = 1; // Outputs float+OPort2 mass; float+OPort2 zcg; float+OPort2 izz; Field+Space3+OPort2 out { ncell_sets = 2; // Polytri definition !cell_set[0] { cell_corner_nnodes => cell_nnodes; cell_nnodes = 3; cell_ndim = 2; cell_order = 1; poly_flag = 1; poly_type-opt = 2; /* to distinguish from Polyhedron */ poly_nnodes =>cache(init_array(npolys,2,2)); poly_connect_list[npolys*2]; /* node connectivity array */ ncells => cache(get_ncells_polytri(npolys, poly_connect_list)); node_connect_list => cache(get_connect_polytri(npolys, poly_connect_list)); int+virtual cell_type = 10; string+virtual cell_name = "Polytri"; float+virtual node_uvw[3][3] = {{1.0,0.0,0.0}, {0.0,1.0,0.0}, {0.0,0.0,0.0}}; }; // Polyline definition !cell_set[1] { cell_corner_nnodes => cell_nnodes; cell_nnodes = 2; cell_ndim = 1; cell_order = 1; poly_flag = 1; poly_nnodes =>cache(init_array(npolys,2,2)); poly_connect_list[npolys*2]; /* node connectivity array */ ncells => cache(get_ncells_polyline(npolys, poly_connect_list)); node_connect_list => cache(get_connect_polyline(npolys, poly_connect_list)); int+virtual cell_type = 3; string+virtual cell_name = "Polyline"; float+virtual node_uvw[2][3] = {{-1.0,0.0,0.0}, {1.0,0.0,0.0}}; }; // Normals node data nnode_data = 1; !node_data[0] { veclen = 3; id = 666; }; }; cxxmethod+notify_inst+req update( .active+read+notify+req, .num_thetas+read+notify+req, .r_outside+read+notify+req, .r_inside+read+notify, .z_offset+read+notify+req, .half_angle+read+notify+req, .density+read+notify+req, .volume+write, .mass+write, .cg+write, .izz+write, .out+write ); };
SemiSphere rotates a semi-spherical "solid" body of revolution. The routine creates surfaces and the appropriate normals for the inside, outside, and end cap (if required). The outside polyline line is required. The routine also calculates the mass properties for the body. The body is generated fo 360 degrees of revolution only.
active
Input to enable or disable the execution of this module.
num_thetas
Controls the resolution of the mesh/grid that makes up the semisphere surface.
r_outside
Set the radius of the outside of the semisphere surface.
r_inside
Set the radius of the inside of the semisphere surface.
z_offset
Offsets the z-axis coordinates of the surface.
half_angle
Set the angle at which the semisphere surface stops, e.g., 90 degrees will give a semisphere; 180 degrees is a normal sphere.
density
Provide a density setting for the mass calculations taken from the volume contained within the inner and outer semispheres.
mass
Mass parameter of the generated volume.
zcg
Mass parameter of the generated volume.
izz
Mass parameter of the generated volume.
out
Grid and mesh containing the semisphere surface. Contains both polytri (surface) and polyline (outline) cell sets.
n/a
SemiSphereEg is a simple example application showing the modSemiSphere module in use, with the output connected to a viewer.
xp_comm_proj/semisphr/smspmods.v contains the modSemiSphere module V definition. xp_comm_proj/semisphr/smspmacs.v contains the SemiSphereEg example application V definition.
The low-level SemiSphereMods library containing the module modSemiSphere does not specify a process. By default the express process will be used.
Brian Selle, Leon Thrane, Advanced Visual Systems Inc. Documentation - Ian Curington, Advanced Visual Systems Inc.
Paul G. Lever
n/a


{%load static%} {%load static%} {%load static%} {%load static%}
RepoPy is a self-hosted source code repository browser. It lets you browse your source code and do searching on your files. RepoPy is aware of classes inside your repository. You can find classes that are related using the integrated search engine.


Formula One and ESPN sign new deal
AUSTIN, Texas: ESPN and Formula One signed a new three-year deal to continue to broadcast races in the United States, the all-sport network said on Friday (Nov 1).
Formula One said the series had seen double-digit television viewership growth in the United States over the past two seasons since coverage returned to ESPN in 2018.
Even so Formula One remains a niche sport in the United States with this weekend's grand prix in Austin, Texas, the only US stop on the glamour circuit.
Through 18 races this season, Formula One is averaging 671,000 viewers on ESPN networks, an increase of 19 per cent on the average of 561,000 last year.
In comparison, this year's Super Bowl between the Los Angeles Rams and New England Patriots had the lowest audience in more than a decade while this year's Indianapolis 500 pulled in 5.4 million viewers.
The Women’s College Softball World Series two-game championship series in June between the UCLA Bruins and Oklahoma Sooners averaged 1.5 million viewers, more than double the viewership of any Formula One race in the United States.
"Our partnership with ESPN has delivered a 19 per cent increase in viewership across the US and we are delighted to extend our partnership through to 2022," said Sean Bratches, managing director, commercial partnerships, at Formula One in a statement.
"The US is one of our key focuses for growth and ESPN know and understand the US sports audience like no one else.
"The combination of their dedicated coverage and Formula One’s amazing racing spectacle is a perfect partnership for us to build on our recent success with US audiences."
The new deal will see all races continue to air live and free of commercials on either ESPN, ESPN2 or ABC.
All practice sessions, qualifying and races will air live and in replay across ESPN platforms.
While Formula One has long coveted the US market the sport has never caught on.
Until a state of the art track was constructed in Austin, the US grand prix had trouble finding a home with races in Indianapolis, Phoenix, Detroit and Las Vegas.
Formula One has tried for years to put a second race in the United States but all attempts have ended in disappointment.
Plans to stage a race in Miami in 2021 faced new obstacles this week when Miami-Dade County commissioners passed a resolution enabling them to prohibit road closures linked to racing events in or near residential areas.


In the previous chapter, we considered the case of fitness being independant of the distribution of the whole population (the rates of increase of 1 type just depended on the quantity of that type). That was a specific case of Evolutionary game theory which considers frequency dependent selection.
Consider. Let $x=(x_1, x_2)$ correspond to the population sizes of both types. The fitness functions are given by:
$$f_1(x)\qquad f_2(x)$$As before we ensure a constant population size: $x_1 + x_2 = 1$. We have:
$$ \frac{dx_1}{dt}=x_1(f_1(x)-\phi) \qquad \frac{dx_2}{dt}=x_2(f_2(x)-\phi) $$we again have:
$$ \frac{dx_1}{dt} + \frac{dx_2}{dt}=x_1(f_1(x)-\phi) + x_2(f_2(x)-\phi)=0 $$So $\phi=x_1f_1(x)+x_2f_2(x)$ (the average fitness).
We can substitute: $x_2=1-x_1$ to obtain:
$$ \frac{dx_1}{dt}=x_1(f_1(x)-x_1f_1(x)-x_2f_2(x))=x_1((1-x_1)f_1(x)-(1-x_1)f_2(x)) $$$$ \frac{dx_1}{dt}=x_1(1-x_1)(f_1(x)-f_2(x)) $$We see that we have 3 equilibria:
Now we will consider potential differences of these equilibria. First we will return to considering Normal form games:
$$ A = \begin{pmatrix} a & b\\ c & d \end{pmatrix} $$Evolutionary Game theory assigns strategies as types in a population, and indivividuals randomly encounter other individuals and play their corresponding strategy. The matrix $A$ correspods to the utility of a row player in a game where the row player is a given individual and the column player is the population.
This gives:
$$f_1=ax_1+bx_2\qquad f_2=cx_1+dx_2$$or equivalently:
$$f=Ax\qquad \phi=fx$$thus we have the same equation as before but in matrix notation:
$$\frac{dx}{dt}=x(f-\phi)$$In this case, the 3 stable distributions correspond to:
We now consider the utility of a stable population in a mutated population.
Given a strategy vector $x=(x_1, x_2)$, some $\epsilon>0$ and another strategy $y=(y_1, y_2)$, the post entry population $x_{\epsilon}$ is given by:
$$ x_{\epsilon} = (x_1 + \epsilon(y_1 - x_1), x_2 + \epsilon(y_2 - x_2)) $$Given a stable population distribution, $x$ it represents an Evolutionary Stable Strategy (ESS) if and only if there exists $\bar\epsilon>0$:
$$u(x, x_{\epsilon})>u(y, x_{\epsilon})\text{ for all }0<\epsilon<\bar\epsilon, y$$where $u(x, y)$ corresponds to the fitness of strategy $x$ in population $y$ which is given by:
$$xAy^T$$For the first type to be an ESS this corresponds to:
$$a(1-\epsilon)+b\epsilon > c(1-\epsilon) + d\epsilon$$For small values of $\epsilon$ this corresponds to:
$$a>c$$However if $a=c$, this corresponds to:
$$b>d$$Thus the first strategy is an ESS (ie resists invasion) iff one of the two hold:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from scipy.integrate import odeint
t = np.linspace(0, 10, 100) # Obtain 100 time points
def dx(x, t, A):
"""
Define the derivate of x.
"""
f = np.dot(A, x)
phi = np.dot(f, x)
return x * (f - phi)
The case of $a>c$:
A = np.array([[4, 3], [2, 1]])
epsilon = 10 ** -1
xs = odeint(func=dx, y0=[1 - epsilon, epsilon], t=t, args=(A,))
plt.plot(xs);
The case of $a=c$ and $b>d$:
A = np.array([[4, 3], [4, 1]])
epsilon = 10 ** -1
xs = odeint(func=dx, y0=[1 - epsilon, epsilon], t=t, args=(A,))
plt.plot(xs);
$a=c$ and $b < d$:
A = np.array([[4, 3], [4, 5]])
epsilon = 10 ** -1
xs = odeint(func=dx, y0=[1 - epsilon, epsilon], t=t, args=(A,))
plt.plot(xs);
$a < c$:
A = np.array([[1, 3], [4, 1]])
epsilon = 10 ** -1
xs = odeint(func=dx, y0=[1 - epsilon, epsilon], t=t, args=(A,))
plt.plot(xs);
We see in the above case that the population seems to stabilise at a mixed strategy. This leads to the general definition of the fitness of a mixed strategy: $x=(x_1, x_2)$:
$$u(x,x) = x_1f_1(x)+x_2f_2(x)$$If $x$ is an ESS, then for all $y\ne x$, either:
Conversely, if either (1) or (2) holds for all $y\ne x$ then $x$ is an ESS.
If $x$ is an ESS, then by definition:
$$u(x,x_{\epsilon})>u(y,x_{\epsilon})$$which corresponds to:
$$(1-\epsilon)u(x,x)+\epsilon u(x,y)>(1-\epsilon)u(y,x)+\epsilon u(y,y)$$Conversely:
If $u(x,x) < u(y,x)$ then we can find $\epsilon$ sufficiently small such that the inequality is violated.
If $u(x, x) = u(y,x)$ and $u(x,y) \leq u(y,y)$ then the inequality is violated.
This result gives us an efficient way of computing ESS. The first condition is in fact almost a condition for Nash Equilibrium (with a strict inequality), the second is thus a stronger condition that removes certain Nash equilibria from consideration. This becomes particularly relevant when considering Nash equilibrium in mixed strategies.
To find ESS in a pairwise context population game we:
Let us apply it to the one example that seemed to stabilise at a mixed strategy:
$$ A =\begin{pmatrix} 1 & 3\\ 4 & 1 \end{pmatrix} $$import nashpy as nash
game = nash.Game(A, A.transpose())
list(game.support_enumeration())
Looking at $x=(.4, .6)$ (which is the only symmetric nash equilibrium), we have
$$u(x, x)=u(y, x)$$and (recall $y_1 + y_2 = 1$):
$$ u(x, y)=2.8y_1 + 1.8y_2=2.8y_1 + 1.8(1-y_1)=y_1+1.8 $$\begin{align} u(y, y)&=y_1^2+3y_1y_2+4y_1y_2+y_2^2\\ &=y_1^2+7y_1-7y_1^2+1 - 2y_1 + y_1^2\\ &=5y_1-5y_1^2+1 \end{align}Thus:
$$u(x, y) - u(y, y) = -4y_1+5y_1^2+.8 = 5(y_1 - .4)^2$$however $y_1\ne.4$ thus $x=(.4, .6)$ is an ESS.
Here is some code to verify the above calculations:
import sympy as sym
sym.init_printing()
A = sym.Matrix(A)
y_1, y_2 = sym.symbols("y_1, y_2")
y = sym.Matrix([y_1, y_2])
A, y
rhs = sym.expand((y.transpose() * A * y)[0].subs({y_2: 1 - y_1}))
rhs
lhs = sym.expand((sym.Matrix([[.4, .6]]) * A * y)[0].subs({y_2: 1-y_1}))
lhs
sym.factor(lhs - rhs)
Source code: @drvinceknight Powered by: Python Mathjax Github pages Skeleton css


| Name | Model | Manufacturer | Cost in Credits | Length | Max Atmosphering Speed | Crew | Passengers | Cargo Capacity | Consumables | Vehicle Class |
|---|---|---|---|---|---|---|---|---|---|---|
| {{vd.name}} | {{vd.model}} | {{vd.manufacturer}} | {{vd.cost_in_credits}} | {{vd.length}} | {{vd.max_atmosphering_speed}} | {{vd.crew}} | {{vd.passengers}} | {{vd.cargo_capacity}} | {{vd.consumables}} | {{vd.vehicle_class}} |


People are an integral part of the California coastal ecosystem, and we stand to experience impacts and benefits from the newly implemented marine protected area (MPA) network. To understand the dynamic relationship between people and the environment through the lens of MPAs, we need to understand current and historical uses of coastal resources.
Focus on Human Uses
Humboldt State University (HSU) researchers, Ecotrust, and Strategic Earth Consulting are supporting the state to assess the baseline socioeconomic conditions of two human uses throughout the state of California and their relationship to the MPA network: commercial and commercial passenger fishing vessel (CPFV) fisheries. Our team will design an approach to monitor socioeconomic conditions related to fishing to inform long-term MPA monitoring. Results of this study will guide the 10-year management review of California’s MPA network.
Implementation
The socioeconomic status of California state fisheries is affected by the complex exchange between regulatory, environmental, and socioeconomic factors. MPAs are one of the many influences that could affect spatial fishing patterns and the economic health of California fisheries. Given this complexity, this project aims to assess commercial and CPFV fisheries across the state using temporal, spatial, and place-based approaches. Combined, these approaches will illustrate economic and spatial changes over time and provide insights on how place-based factors, including MPAs, have played a role in driving observed and experienced socioeconomic changes.
Temporal
We will analyze historical economic trends (e.g., participation rates, landings, revenue) in commercial and CPFV fisheries from 1992 to 2020 and use this time-series data to assess patterns and changes observed over time and to describe the current economic status of fisheries.
Spatial
We will integrate regional-level spatial data sets since the time of each region's implementation to develop a statewide understanding of spatial fishing patterns and evaluate how these have changed since MPA implementation.
Place-based
In Spring and Summer 2020, we will engage with the commercial and CPFV fishing communities in an on-the-ground focus group tour throughout 24 port complexes in California. To assist this effort, we are developing a ‘Port Community Well-being Assessment Tool’ (i.e., a questionnaire) that will be used to gather quantitative and qualitative information about the health and well-being of California fisheries in the context of MPAs. Questions from the Tool will guide focus group discussions, which will be used to gain a snapshot of the socioeconomic conditions of fisheries in California. The focus groups will provide information about fishermen’s perceptions of MPAs and the ways fishermen have been affected by the MPAs since implementation.


import numpy as np
import copy
from sklearn.decomposition import PCA
from sklearn import preprocessing
from umap import UMAP
[docs]class TDR():
"""TDR: Two-step dimensionality reduction (DR) to project a third-order
tensor onto a lower-dimensional space
Parameters
----------
first_learner: Class Object for DR, optional, (default=None)
Dimensionality reduction class object for the first DR step. Any class
object that has fit_transform as a class method (e.g., PCA in
scikit-learn). If None, sklearn's PCA is set as a learner (i.e.,
PCA(n_components=1)).
Also, to set a different DR for individual modes, you can input as a
dict. e.g., {'t': PCA(n_components=1), 'n': PCA(n_components=1), 'd':
PCA(n_components=1)}
second_learner: Class Object for DR, optional, (default=None)
Dimensionality reduction class object for the second DR step. Any class
object that has fit_transform as a class method (e.g., UMAP in
umap-learn). If None, UMAP is set as a learner (i.e.,
UMAP(n_components=2)).
Also, to set a different DR for individual modes, you can input as a
dict. e.g., {'t': UMAP(n_components=2), 'n': PCA(n_components=2), 'd':
TSNE(n_components=2)}
Attributes
----------
first_learner: the same with the input parameter one.
second_learner: the same with the input parameter one.
Y_tn: ndarray, shape (n_time_points, n_instances)
The matrix Y obtained by applying the first DR along a variable mode.
Rows and columns correspond to time points and intances, repectively.
Y_nd: ndarray, shape (n_instances, n_variables)
The matrix Y obtained by applying the first DR along a time mode.
Rows and columns correspond to intances and variables, repectively.
Y_dt: ndarray, shape (n_variables, n_time_points)
The matrix Y obtained by applying the first DR along an instance mode.
Rows and columns correspond to variables and time points, repectively.
Z_n_dt: ndarray, shape (n_instances, n_components_of_2nd_DR)
The matrix Z obtained by applying the first DR along a variable mode
and then the second DR along a time mode (1st DR : d, 2nd DR: t).
Z_n_td: ndarray, shape (n_instances, n_components_of_2nd_DR)
The matrix Z obtained by applying the first DR along a time mode
and then the second DR along a variable mode (1st DR: t, 2nd DR: d).
Z_d_nt: ndarray, shape (n_variables, n_components_of_2nd_DR)
The matrix Z obtained by applying the first DR along an instance mode
and then the second DR along a time mode (1st DR: n, 2nd DR: t).
Z_d_tn: ndarray, shape (n_variables, n_components_of_2nd_DR)
The matrix Z obtained by applying the first DR along a time mode
and then the second DR along an instance mode (1st DR: t, 2nd DR: n).
Z_t_dn: ndarray, shape (n_time_points, n_components_of_2nd_DR)
The matrix Z obtained by applying the first DR along a variable mode
and then the second DR along an instance mode (1st DR: d, 2nd DR: n).
Z_t_nd: ndarray, shape (n_time_points, n_components_of_2nd_DR)
The matrix Z obtained by applying the first DR along an instance mode
and then the second DR along a variable mode (1st DR: n, 2nd DR: d).
----------
Examples
--------
>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> from sklearn.decomposition import PCA
>>> from umap import UMAP
>>> from multidr.tdr import TDR
>>> def plot_results(results):
... plt.figure(figsize=(8, 6))
... for i, Z in enumerate(
...
Parameters
----------
X: array-like, shape(n_time_points, n_instances, n_variables)
Input third-order tensor.
scaling: boolean or dict of booleans, optional, default=True
If True, apply starndarziation before applying the first DR.
To set scaling for individual modes, you can input as a dict. e.g.,
{'t': False, 'n': False, 'd': True}
verbose: boolean, optional, default=False
If True, print the progress of two-step DR, etc.
Returns
-------
self
"""
T, N, D = X.shape
X_tn_d = np.zeros((T * N, D))
X_nd_t = np.zeros((N * D, T))
X_dt_n = np.zeros((D * T, N))
# unfolding
for t in range(T):
X_tn_d[t * N:(t + 1) * N, :] = X[t, :, :]
for n in range(N):
X_nd_t[n * D:(n + 1) * D, :] = X[:, n, :].transpose()
for d in range(D):
X_dt_n[d * T:(d + 1) * T, :] = X[:, :, d]
if verbose:
print("reshape done")
# set scaler
scl = {'t': lambda a: a, 'n': lambda a: a, 'd': lambda a: a}
if type(scaling) is dict:
scl['t'] = preprocessing.scale if scaling['t'] else lambda a: a
scl['n'] = preprocessing.scale if scaling['n'] else lambda a: a
scl['d'] = preprocessing.scale if scaling['d'] else lambda a: a
elif scaling:
scl['d'] = preprocessing.scale
scl['t'] = preprocessing.scale
scl['n'] = preprocessing.scale
# first DR
y_nd_t = self.first_learner['t'].fit_transform(scl['t'](X_nd_t))
y_dt_n = self.first_learner['n'].fit_transform(scl['n'](X_dt_n))
y_tn_d = self.first_learner['d'].fit_transform(scl['d'](X_tn_d))
if verbose:
if 'explained_variance_ratio_' in self.first_learner['t'].__dict__:
print("exp var ratio for compression of time ponts:",
self.first_learner['t'].explained_variance_ratio_)
if 'explained_variance_ratio_' in self.first_learner['n'].__dict__:
print("exp var ratio for compression of instances",
self.first_learner['n'].explained_variance_ratio_)
if 'explained_variance_ratio_' in self.first_learner['d'].__dict__:
print("exp var ratio for compression of variables:",
self.first_learner['d'].explained_variance_ratio_)
# sign flip if the weights tend to be negative
if 'components_' in self.first_learner['t'].__dict__:
if np.sum(self.first_learner['t'].components_) < 0:
self.first_learner['t'].components_ *= -1
y_nd_t *= -1
if 'components_' in self.first_learner['n'].__dict__:
if np.sum(self.first_learner['n'].components_) < 0:
self.first_learner['n'].components_ *= -1
y_dt_n *= -1
if 'components_' in self.first_learner['d'].__dict__:
if np.sum(self.first_learner['d'].components_) < 0:
self.first_learner['d'].components_ *= -1
y_tn_d *= -1
# folding
self.Y_tn = y_tn_d.reshape((T, N))
self.Y_nd = y_nd_t.reshape((N, D))
self.Y_dt = y_dt_n.reshape((D, T))
if verbose:
print("first repr done")
return self
[docs] def learn_second_repr(self, Y_tn, Y_nd, Y_dt, scaling=True, verbose=False):
"""Apply the first DR to learn Y_tn, Y_nd, Y_dt.
Parameters
----------
Y_tn: ndarray, shape (n_time_points, n_instances)
The matrix Y obtained by applying the first DR along a variable mode.
Rows and columns correspond to time points and intances, repectively.
Y_nd: ndarray, shape (n_instances, n_variables)
The matrix Y obtained by applying the first DR along a time mode.
Rows and columns correspond to intances and variables, repectively.
Y_dt: ndarray, shape (n_variables, n_time_points)
The matrix Y obtained by applying the first DR along an instance mode.
Rows and columns correspond to variables and time points, repectively.
scaling: boolean or dict of booleans, optional, default=True
If True, apply starndarziation before applying the second DR.
To set scaling for individual modes, you can input as a dict. e.g.,
{'t': False, 'n': False, 'd': True}
verbose: boolean, optional, default=False
If True, print the progress of two-step DR, etc.
Returns
-------
self
"""
# set scaler
scl = {'t': lambda a: a, 'n': lambda a: a, 'd': lambda a: a}
if type(scaling) is dict:
scl['t'] = preprocessing.scale if scaling['t'] else lambda a: a
scl['n'] = preprocessing.scale if scaling['n'] else lambda a: a
scl['d'] = preprocessing.scale if scaling['d'] else lambda a: a
elif scaling:
scl['d'] = preprocessing.scale
scl['t'] = preprocessing.scale
scl['n'] = preprocessing.scale
# second DR
self.Z_n_dt = self.second_learner['t'].fit_transform(scl['t'](
Y_tn.transpose()))
if verbose:
print("Z_n_dt done")
self.Z_d_nt = self.second_learner['t'].fit_transform(scl['t'](Y_dt))
if verbose:
print("Z_d_nt done")
self.Z_t_dn = self.second_learner['n'].fit_transform(scl['n'](Y_tn))
if verbose:
print("Z_t_dn done")
self.Z_d_tn = self.second_learner['n'].fit_transform(scl['n'](
Y_nd.transpose()))
if verbose:
print("Z_d_tn done")
self.Z_t_nd = self.second_learner['d'].fit_transform(scl['d'](
Y_dt.transpose()))
if verbose:
print("Z_t_nd done")
self.Z_n_td = self.second_learner['d'].fit_transform(scl['d'](Y_nd))
if verbose:
print("Z_n_td done")
if verbose:
print("second repr done")
return self
[docs] def set_first_learner(self, first_learner):
"""Set a method for the first DR.
Parameters
----------
first_learner: Class Object for DR
Dimensionality reduction class object for the first DR step. Any class
object that has fit_transform as a class method (e.g., PCA in
scikit-learn). If None, sklearn's PCA is set as a learner (i.e.,
PCA(n_components=1)).
Also, to set a different DR for individual modes, you can input as a
dict. e.g., {'t': PCA(n_components=1), 'n': PCA(n_components=1), 'd':
PCA(n_components=1)}
Returns
-------
self
"""
if first_learner is None:
self.first_learner = {
'n': PCA(n_components=1),
'd': PCA(n_components=1),
't': PCA(n_components=1)
}
elif type(first_learner) is not dict:
self.first_learner = {
'n': copy.deepcopy(first_learner),
'd': copy.deepcopy(first_learner),
't': copy.deepcopy(first_learner)
}
else:
self.first_learner = first_learner
return self
[docs] def set_second_learner(self, second_learner):
"""Set a method for the second DR.
Parameters
----------
second_learner: Class Object for DR, optional, (default=None)
Dimensionality reduction class object for the second DR step. Any class
object that has fit_transform as a class method (e.g., UMAP in
umap-learn). If None, UMAP is set as a learner (i.e.,
UMAP(n_components=2)).
Also, to set a different DR for individual modes, you can input as a
dict. e.g., {'t': UMAP(n_components=2), 'n': PCA(n_components=2), 'd':
TSNE(n_components=2)}
Returns
-------
self
"""
if second_learner is None:
self.second_learner = {'n': UMAP(), 'd': UMAP(), 't': UMAP()}
elif type(second_learner) is not dict:
self.second_learner = {
'n': copy.deepcopy(second_learner),
'd': copy.deepcopy(second_learner),
't': copy.deepcopy(second_learner)
}
else:
self.second_learner = second_learner
return self


Serving hot oven-fresh pizza with its signature all-natural tomato sauce and using only the freshest ingredients,Supreme Pizzas has established itself at the top of the industry and is easily one of the first choices in quick service pizza in Africa.
At Supreme Pizzas, we offer the sweetest pizza one could ever think of. Pizzas are made with different toppings and crusts.We allow customers to choose their own toppings,crusts and sizes.
At Supreme Pizzas, we give out offers to our customers every Teusday.It is called the Terrific Tuesday where customers are given a free pizza for each purchase.This is a way to motivate customers.


In both 2008 and 2012, the Libertarian Party nominated former Republican office holders to be our presidential candidate. This time let us nominate a Libertarian officer holder.
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Lorem Ipsum is simply dummy text of the printing and typesetting industry when an unknown printer took a galley of type and scrambled it to make a type specimen book
Lorem Ipsum has been the industry's standard dummy text ever since the 1500s
Lorem Ipsum is simply dummy text of the printing and typesetting industry when an unknown printer took a galley of type and scrambled it to make a type specimen book
Not everyone like accordions and it's easier to play a kazoo
Lorem Ipsum is simply dummy text of the printing and typesetting industry when an unknown printer took a galley of type and scrambled it to make a type specimen book
Lorem Ipsum has been the industry's standard dummy text ever since the 1500s
Lorem Ipsum is simply dummy text of the printing and typesetting industry when an unknown printer took a galley of type and scrambled it to make a type specimen book
Help him decide to run!
Insert closing call to action here


|
My Project
|
Public Member Functions | |
| basic_parallel (Map &map, Allocate &alloc, Schedule &sched, volatile bool &exit_para) | |
| virtual void | start () |
Protected Attributes | |
| kernelkeeper & | source_kernels |
| kernelkeeper & | all_kernels |
| Allocate & | alloc |
| Schedule & | sched |
| volatile bool & | exit_para |
| basic_parallel::basic_parallel | ( | Map & | map, |
| Allocate & | alloc, | ||
| Schedule & | sched, | ||
| volatile bool & | exit_para | ||
| ) |
nothing to do here, move along
|
virtual |
since we have to have a lock on the ports for both BFS and duplication, we'll mark the kernels inside of BFS and duplicate outside of it.
start checking stats
input stats
apply criteria
FIXME, logic below only works for single input, single output..intended to get it working
clone
attach ports
connecting a.y -> b.x new_other_outprt == port y on a new_port_in == port x on b
connecting b.y -> c.x newoutport == port y on b new_other_inport == port x on c
schedule new kernel
|
protected |
both convenience structs, hold exactly what the names say


Deuteronomy 24:10
When thou dost lend thy brother any thing, thou shalt not go into his house to fetch his pledge.


public final class PatternAnalyzer extends ReusableAnalyzerBase
Reader
, that can flexibly separate text into terms via a regular expression
Pattern
(with behaviour identical to
String.split(String)
),
and that combines the functionality of
LetterTokenizer
,
LowerCaseTokenizer
,
WhitespaceTokenizer
,
StopFilter
into a single efficient
multi-purpose class.
If you are unsure how exactly a regular expression should look like, consider
prototyping by simply trying various expressions on some test texts via
String.split(String)
. Once you are satisfied, give that regex to
PatternAnalyzer. Also see
Java Regular Expression Tutorial
.
This class can be considerably faster than the "normal" Lucene tokenizers.
It can also serve as a building block in a compound Lucene
TokenFilter
chain. For example as in this
stemming example:
PatternAnalyzer pat = ... TokenStream tokenStream = new SnowballFilter( pat.tokenStream("content", "James is running round in the woods"), "English"));
ReusableAnalyzerBase.TokenStreamComponents
| Modifier and Type | Field and Description |
|---|---|
static
PatternAnalyzer
|
DEFAULT_ANALYZER
A lower-casing word analyzer with English stop words (can be shared
freely across threads without harm); global per class loader.
|
static
PatternAnalyzer
|
EXTENDED_ANALYZER
A lower-casing word analyzer with
extended
English stop words
(can be shared freely across threads without harm); global per class
loader.
|
static
Pattern
|
NON_WORD_PATTERN
"\\W+"
; Divides text at non-letters (NOT Character.isLetter(c))
|
static
Pattern
|
WHITESPACE_PATTERN
"\\s+"
; Divides text at whitespaces (Character.isWhitespace(c))
|
| Constructor and Description |
|---|
PatternAnalyzer
(
Version
matchVersion,
Pattern
pattern,
boolean toLowerCase,
Set
> stopWords)
Constructs a new instance with the given parameters.
|
| Modifier and Type | Method and Description |
|---|---|
ReusableAnalyzerBase.TokenStreamComponents
|
createComponents
(
String
fieldName,
Reader
reader)
Creates a token stream that tokenizes all the text in the given Reader;
This implementation forwards to
tokenStream(String, Reader, String)
and is
less efficient than
tokenStream(String, Reader, String)
.
|
ReusableAnalyzerBase.TokenStreamComponents
|
createComponents
(
String
fieldName,
Reader
reader,
String
text)
Creates a token stream that tokenizes the given string into token terms
(aka words).
|
boolean
|
equals
(
Object
other)
Indicates whether some other object is "equal to" this one.
|
int
|
hashCode
()
Returns a hash code value for the object.
|
initReader
,
reusableTokenStream
,
tokenStream
close
,
getOffsetGap
,
getPositionIncrementGap
,
getPreviousTokenStream
,
setPreviousTokenStream
public static final Pattern NON_WORD_PATTERN
"\\W+"
; Divides text at non-letters (NOT Character.isLetter(c))
public static final Pattern WHITESPACE_PATTERN
"\\s+"
; Divides text at whitespaces (Character.isWhitespace(c))
public static final PatternAnalyzer DEFAULT_ANALYZER
public static final PatternAnalyzer EXTENDED_ANALYZER
public PatternAnalyzer( Version matchVersion, Pattern pattern, boolean toLowerCase, Set > stopWords)
matchVersion
- currently does nothing
pattern
- a regular expression delimiting tokens
toLowerCase
- if
true
returns tokens after applying
String.toLowerCase()
stopWords
- if non-null, ignores all tokens that are contained in the
given stop set (after previously having applied toLowerCase()
if applicable). For example, created via
StopFilter.makeStopSet(Version, String[])
and/or
WordlistLoader
as in
WordlistLoader.getWordSet(new File("samples/fulltext/stopwords.txt")
or
other stop words
lists
.
public ReusableAnalyzerBase.TokenStreamComponents createComponents( String fieldName, Reader reader, String text)
fieldName
- the name of the field to tokenize (currently ignored).
reader
- reader (e.g. charfilter) of the original text. can be null.
text
- the string to tokenize
public ReusableAnalyzerBase.TokenStreamComponents createComponents( String fieldName, Reader reader)
tokenStream(String, Reader, String)
and is
less efficient than
tokenStream(String, Reader, String)
.
createComponents
in class
ReusableAnalyzerBase
fieldName
- the name of the field to tokenize (currently ignored).
reader
- the reader delivering the text
public boolean equals( Object other)


Sample request:
https://timeserviceapi.herokuapp.com/December%2015,%202015 https://timeserviceapi.herokuapp.com/1450137600


What is Ember?
MVC Javascript Framework
Ember vs Other JS frameworks
React => Library for creating components
Vue => The Progressive Javascript Framework
Frameworks vs Libraries
A framework calls your code. Your code calls a library.
So Ember.js is a Framework
and React is a Library
Ember == Angular
Why Ember?
Ruby on Rails
Strong conventions
Developer Productivity
Single Page Application
Components of SPA
Routing in the browser
Client-side Routing
Hash-based routing
https://support.freshdesk.com/#tickets
https://support.freshdesk.com/#contacts
Fragment Identifiers
Part of the URL beginning with and following the # symbol
URL = http://google.com#cool-feature
Fragment Id = #cool-feature
Downsides of Hash-based routing
URL-based routing
https://support.freshdesk.com/tickets
https://support.freshdesk.com/contacts
History API
Manipulate the user's browsing history
window.history
| back() | Goes to the previous page in the history. |
| forward() | Goes to the next page in the history. |
| go(index) | Goes to a specific page in the history. |
| pushState(state, title, URL) | Pushes the data in the history stack and navigate to the provided URL. |
| replaceState(state, title, URL) | Replaces the most recent data in the history stack and navigates to the provided URL. |
Routing in Ember
// Hash based routing
ENV.locationType = "hash";
// URL based routing
ENV.locationType = "history";
Automatic routing
// Modern Browsers => History API
// Older Browsers => Hash based routing
ENV.locationType = "auto";
State management
Internal State
External State
Internal State
State within the context of a single component
Computed Properties
import EmberObject, { computed } from '@ember/object';
const Image = EmberObject.extend({
aspectRatio: computed('width', 'height', function() {
return this.width / this.height;
}),
});
Tracked Properties
import { tracked } from '@glimmer/tracking';
class Image {
@tracked width;
@tracked height;
get aspectRatio() {
return this.width / this.height;
}
}
External State
State within the context of whole application
involving multiple components
In React, we use Redux, MobX
In Ember, we use Services, Utils, Mixins along with Ember Data
API & Data
Ember Data
a powerful set of tools for formatting requests, normalizing responses, and efficiently managing a local cache of data.
Ember works with any type of backend
Models
import Model, { attr } from '@ember-data/model';
export default class PersonModel extends Model {
@attr('string') name;
@attr('date') birthday;
}
Relationships
import Model, { hasMany } from '@ember-data/model';
export default class OrderModel extends Model {
@hasMany('line-item') lineItems;
}
import Model, { belongsTo } from '@ember-data/model';
export default class LineItemModel extends Model {
@belongsTo('order') order;
}
Single Source of Truth
Records
an instance of model that contains data loaded from server.
this.store.findRecord('person', 1);
// => { id: 1, name: 'tony-stark' }
Finding a record
Finding a record (response)
Peek record
Templating
Dynamic value interpolation in your HTML
HTMLBars
Based on the Handlebars templating language
Template helpers
Helper functions are JavaScript functions that you can call from your template.
Given Name: {{capitalize this.person.givenName}}
Family Name: {{capitalize this.person.familyName}}
{{yield}}
denotes an area of a template that will be rendered inside of another template.
{{outlet}}
lets you specify where a child route will render in your template.
Styling
CSS
CSS Precompilers
Build Pipeline
Module Bundlers
Creating Ember projects
Official CLI for creating & managing Ember.js apps
npm install --global ember-cli
ember new
ember new [project-name]
ember new my-project
ember new my-project --yarn
Package Managers
Skip npm install
ember new my-project --skip-npm
Skip git init
ember new my-project --skip-git
More options
ember help
ember help new
How do I distribute reusable code with Ember?
Ember Addons
Ember Addons
Ember CLI provides a common format called Ember Addons for distributing reusable libraries.
Addons are JavaScript packages that integrate with Ember.
ember install ember-cli-sass
Generating new Ember addon
ember addon [addon-name]
Addon structure
Ember Observer
One place to find awesome ember addons
Zero config import from npm packages
ember-new-output
To quickly setup up projects with different Ember versions
degit ember-cli/ember-new-output#v2.18 [project-name]
Code splitting
Performance
Shipping unused code in the browser
Ember Engines
Composable applications for ambitious user experiences.
Engines are just glorified Ember addons


This is an example of using the pdf-viewer directive from the angular-pdfjs library to view PDFs rendered using PDFJS inside of an angular application.


{{ subsError }}
Fetching user subscriptions. Please Wait...
Rating: {{ blog.rating }} / 5 ({{ blog.ratingCount }} ratings)
{{ blog.commentCount }} comments
{{ blogsError }}
Fetching user blogs. Please wait...
We could not fetch the profile you requested. Sorry about that.
Error: {{ userError }}
We are fetching the user profile you requested. We'll have it for you shortly...


EXPERIENCE
Sales Consultant – Christian Dior Couture March 2018 - Present
- Location: London, United Kingdom
- Currently based in New Bond Street office
Student Ambassador – Royal Holloway, University of LondonOctober 2015 - Present
- Location: London, United Kingdom
- led a group of 20 students on campus tours and provided insights on university life on open days and applicant visit days
- Inspired students in admission; increased admission to the university by 20%
Executive Admin Assistant to CEO – Tanjai Limited March 2018 - April 2018
- Location: London, United Kingdom
- Organised weekly appointments with external clients; provided timely reminders
- Produced and collated project reports using Microsoft Word and Excel
Brand Ambassador – British American Group February 2018 - March 2018
- Location: London, United Kingdom
Sales Representative – Jo Malone London October 2017 - March 2018
- Location: London, United Kingdom
- Contributed around £1500 worth of cologne to the overall sales target per day
- Commended for excellent customer service and achieved a consistent 98% customer service satisfaction
- Exceeded daily sales target (£14k) and earned managers’ praise by hitting £28k


Gecode::Int::Extensional::Compact< View >::LostSupports Class Reference
Iterator over lost supports. More...
#include <extensional.hh>
Public Member Functions | |
| LostSupports (const Compact< View > &p, CTAdvisor &a, int l, int h) | |
| Initialize iterator for values between l and h. | |
| void | operator++ (void) |
| Move iterator to next value. | |
| bool | operator() (void) const |
| Whether iterator is done. | |
| const BitSetData * | supports (void) const |
| Provide access to corresponding supports. | |
Protected Attributes | |
| const unsigned int | n_words |
| Number of words. | |
| const Range * | r |
| Range information. | |
| int | l |
| Low value. | |
| int | h |
| High value. | |
| const BitSetData * | s |
| The lost value's support. |
Detailed Description
template<class View>
class Gecode::Int::Extensional::Compact< View >::LostSupports
Iterator over lost supports.
Definition at line 441 of file extensional.hh.
Constructor & Destructor Documentation
| Gecode::Int::Extensional::Compact< View >::LostSupports::LostSupports | ( | const Compact< View > & | p, | |
| CTAdvisor & | a, | |||
| int | l, | |||
| int | h | |||
| ) | [inline] |
Initialize iterator for values between l and h.
Definition at line 248 of file compact.hpp.
Member Function Documentation
| void Gecode::Int::Extensional::Compact< View >::LostSupports::operator++ | ( | void | ) | [inline] |
Move iterator to next value.
Definition at line 258 of file compact.hpp.
| bool Gecode::Int::Extensional::Compact< View >::LostSupports::operator() | ( | void | ) | const [inline] |
Whether iterator is done.
Definition at line 266 of file compact.hpp.
| const TupleSet::BitSetData * Gecode::Int::Extensional::Compact< View >::LostSupports::supports | ( | void | ) | const [inline] |
Provide access to corresponding supports.
Definition at line 271 of file compact.hpp.
Member Data Documentation
const unsigned int Gecode::Int::Extensional::Compact< View >::LostSupports::n_words [protected] |
Number of words.
Definition at line 444 of file extensional.hh.
const Range* Gecode::Int::Extensional::Compact< View >::LostSupports::r [protected] |
Range information.
Definition at line 446 of file extensional.hh.
int Gecode::Int::Extensional::Compact< View >::LostSupports::l [protected] |
Low value.
Definition at line 448 of file extensional.hh.
int Gecode::Int::Extensional::Compact< View >::LostSupports::h [protected] |
High value.
Definition at line 450 of file extensional.hh.
const BitSetData* Gecode::Int::Extensional::Compact< View >::LostSupports::s [protected] |
The lost value's support.
Definition at line 452 of file extensional.hh.
The documentation for this class was generated from the following files:
- gecode/int/extensional.hh
- gecode/int/extensional/compact.hpp


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MRF Challenge to kick-start on Thursday
Chetan Korada is the lone Indian on the grid
by Sports BureauDUBAIThe MRF Challenge will kick-start here at the Dubai Autodrome on Thursday.
Chennai-based 33-year-old Chetan Korada is the lone Indian on the grid that includes teenagers from Europe and Australian veteran Dylan Young, who has been a regular fixture in MRF Challenge.
Looking ahead to the season, Korada said: “This will be my second international season, also with MRF Challenge. My approach this year would be completely different. Last year was all about learning the car. I didn’t take part in the National championship this year, but did four days of testing in Malaysia in the summer.
“I have been studying the data as to where I can improve. I am continuing with MRF Challenge as they have been very supportive. So, overall, I am feeling good and hope to put in much better performances this season.”
The MRF Challenge will comprise 15 races spread over three rounds to be run in Dubai (November 21-23), Bahrain International Circuit, Bahrain (Dec. 12-14) and MMRT, Chennai (Feb. 14-16, 2020).


Disclaimer: The views expressed in this article are those of the authors and do not represent the official policy or position of the U.S. Department of the Army, Department of Defense, or U.S. Government.
Zika virus (ZIKV) is an emerging mosquito-borne pathogen with reported cases in Africa, Asia, and large outbreaks in the Pacific. No autochthonous ZIKV infections have been confirmed in Thailand. However, there have been several cases reported in travelers returning from Thailand. Here we report seven cases of acute ZIKV infection in Thai residents across the country confirmed by molecular or serological testing including sequence data. These endemic cases, combined with previous reports in travelers, provide evidence that ZIKV is widespread throughout Thailand.
Zika virus (ZIKV) is an emerging mosquito-borne pathogen first described in 1952 1 after being isolated from a sentinel rhesus macaque monkey in 1947 and a pool of Aedes africanus mosquitoes in 1948 from the Zika forest in Uganda. Since it was first reported, only a small number of cases had been described in Africa and Asia until 2007 when there was a large outbreak on Yap Island in the Federated States of Micronesia. 2 , 3 In October 2013, ZIKV was detected in French Polynesia where at least 396 laboratory-confirmed cases have occurred and an estimated 29,000 people (∼10% of the total population) have sought medical care for suspected Zika illness. 4 The affected areas in the Pacific have expanded to include the Cook Islands, New Caledonia, and Easter Island. 5
ZIKV is an approximately 11-kb single-stranded, positive-sense ribonucleic acid (RNA) virus from the Flaviviridae family, most closely related to the Spondweni virus. Two major lineages, African and Asian, have been identified through phylogenetic analyses. 2 , 6 , 7 Transmission likely occurs via mosquito vectors from the Aedes genus of the Culicidae family in a sylvatic cycle involving nonhuman primates, 8 although antibodies have been detected in a number of other mammals (i.e., water buffalo, elephants, zebras). 4 Humans have been suggested as primary amplification hosts in areas where there are no nonhuman primates. 3
A substantial proportion of ZIKV infections are subclinical, 3 , 9 but patients may also present with clinical symptoms similar to other arboviral infections (e.g., dengue and chikungunya). Commonly reported symptoms in the Yap Island and French Polynesian outbreaks included rash (90–95%), fever (65–73%), arthralgia (65–70%), and non-purulent conjunctivitis (55–63%). 3 , 9 Symptoms tend to be mild with no reported deaths. However, there is a concern that ZIKV infection may be related to an increase in cases of Guillain–Barre syndrome seen during the French Polynesian outbreak. 10
Diagnosis of ZIKV infection is hampered by serological cross-reactivity with other flaviviruses, and relies on the detection of ZIKV RNA in blood through ZIKV-specific reverse transcription polymerase chain reaction (RT-PCR) or pan-flavivirus PCR amplification followed by sequencing or viral isolation. The U.S. Centers for Disease Control and Prevention (CDC) proposed a case classification scheme during the epidemic in Yap in 2007, which combines molecular and serological methods. 3
In Thailand, no autochthonous ZIKV infections have been confirmed in Thai residents. However, several Zika cases have been reported in travelers returning from Thailand. In early 2013, ZIKV RNA was detected in the blood of a 45-year-old Canadian woman who had recently returned from a vacation in southern Thailand. 11 Another case of ZIKV infection was reported in an adult male from Germany who had developed symptoms 12 days after arrival in Thailand while visiting a number of islands in southern Thailand. 12 Most recently, a suspected case of ZIKV infection was reported in a 41-year-old Japanese male traveler to southern Thailand who had serological evidence of ZIKV infection in an acute blood sample. 13 Acute ZIKV infections in southeast Asia have also been reported from Indonesia 14 and Cambodia. 15 Indirect serological evidence of ZIKV infection has been documented in the past in non-acute blood samples from Thailand, Vietnam, Malaysia, Indonesia, and the Philippines. 8
The Thailand Ministry of Public Health (MOPH) collects and tests samples during outbreak investigations for public health. Full ethical review was not required; however, the purpose of the investigation was provided and verbal consent from the patient was obtained. The MOPH routinely tests samples from patients presenting with a maculopapular rash and/or fever for immunoglobulin M (IgM) antibodies by enzyme-linked immunosorbent assay (ELISA) to measles, rubella, chikungunya, and dengue viruses in convalescent serum samples. Acute samples (collected within 7 days of symptom onset) are also tested by RT-PCR for detection of dengue virus (DENV) 16 and chikungunya virus (CHIKV) 17 RNA.
In May 2013, the Thai MOPH was notified that ZIKV infection had been confirmed in a Canadian traveler to Thailand 11 prompting the MOPH to further evaluate a number of acute illness samples from outbreak investigations for evidence of ZIKV infection. A review of outbreak investigations conducted by the Thai MOPH throughout Thailand from January 2012 to December 2014 was undertaken. An outbreak was considered for further evaluation when individuals in the cluster had two of the following symptoms: 1) rash, 2) conjunctivitis, or 3) arthralgia, and the acute serum sample was negative for DENV and CHIKV and the IgM antibodies to rubella and measles were not detected in the convalescent sera. Four clusters out of 175 were identified for further evaluation for ZIKV infection.
Here, we report seven cases of acute ZIKV infection in Thai residents from different regions of the country confirmed by molecular or serological testing including one viral isolate with sequence data. These endemic cases, combined with previous ZIKV infection reported in travelers, provide evidence that ZIKV is widespread throughout Thailand.
Table 1 provides the characteristics of the samples and the results of the diagnostic assays. A total of 61 samples representing 38 subjects from the four outbreak clusters were available for further testing. Of the samples obtained before 2014, 54 were sent to the U.S. CDC in Fort Collins, CO, for in-house ZIKV serologic testing including IgM ELISA and plaque reduction neutralization test (PRNT) 3 while seven samples (obtained in 2014) were tested by the Thai CDC once ZIKV diagnostic PCR testing was available. PRNT testing was not completed on these samples. Acute samples were tested by real-time RT-PCR targeting the premembrane (prM)/envelope gene at the Armed Forces Research Institute of Medical Sciences (AFRIMS). 2
Three samples taken from Ratchaburi province, Thailand, were positive for ZIKV infection based on serologic studies whereas ZIKV RNA was detected in the other four samples. The 77 base pair RT-PCR amplicon, used for ZIKV diagnosis from a sample from Sisaket province, was sequenced and found to have high nucleotide identity (between 90% and 100%) to the prM/E region of ZIKV sequences reported in GenBank. Subsequently, three serum samples collected in Phetchabun province that were positive or equivocal for ZIKV by PCR were sent for virus isolation by intrathoracic inoculation of Toxorhynchites splendens mosquitoes followed by inoculation of mosquito-derived C6/36 cells. Typing ELISA using the universal flavivirus (4G2 monoclonal) antibody and DENV serotypes 1, 2, 3, and 4 specific monoclonal antibodies was also completed on the supernatants from the C6/36 cells. 18 , 19 One supernatant sample positive for 4G2 antibody, but negative for DENV antibodies, underwent next-generation sequencing (Illumina MiSeq Platform, Illumina, Hayward, CA). De novo assembly produced a 10,685 nucleotide (nt) consensus sequence (depth of coverage greater than 10,000). Maximum likelihood (ML) phylogenetic analysis of a 789-bp partial sequence of ZIKV nonstructural protein 5 (ZIKV NS5) (GenBank accession no. KM851039) indicated that the isolate belonged to the ZIKV Asian lineage, which includes strains from the Canadian traveler to Thailand (2013) 11 and strains from Cambodia (2010), 15 Micronesia (2007), 2 and French Polynesia (2013) 20 ( Figure 1). Pairwise genetic distance calculation illustrated that the isolate was most closely related to the French Polynesia 2013 strain ( p-distance = 0.009) with approximately 99% nucleotide identity (782/789).
Maximum likelihood phylogenetic trees of fragments of Zika virus nonstructural protein 5 (ZIKV NS5) utilizing GTR+G+I model with 14 reference ZIKV strains from GenBank. The contig sequences, obtained from de novo assembly and BLASTn, of KM851039/Thailand/2014 were analyzed against eight references from the African lineage (Accession numbers: KF268948, KF268950, KF268949, LC002520, AY632535, NC012532, HQ234500, and HQ234501) and six references from the Asian lineage (Accession numbers: KJ776791, JN860885, EU545988, HQ234499, KF993678, and KM851038). The scale of genetic distance equal to 0.02 is indicated in the bottom left of the panel. Bootstrap ≥ 70 is demonstrated next to the node of the tree. The year of collection is unknown for a number of African strains. Drawing is not to scale.
Full clinical information was available for five cases. There were four female patients and one male patient with an average age of 25 years (range: 12–39 years). Clinical presentation was mild and nonspecific. All subjects presented with fever and maculopapular rash. Other symptoms included sore throat (2), arthralgia (2), myalgia (1), rhinorhea (1), and headache (1). Of note, only two patients complained of conjunctivitis, which was less than previously reported in ZIKV cases outside Africa 3 , 4 , 9 including the travelers to Thailand with ZIKV infection. 11 , 12
Despite the isolate from Phetchabun (2014) having a closer relationship to the French Polynesian strain (2013) than the strain from the Canadian traveler (2013) or the strain from Cambodia (2010), these three ZIKV isolates are all part of the ZIKV Asian lineage with Micronesia (2007) and Philippines (2012). The phylogenetic analysis suggests that strains collected in Asia and the Pacific are all closely related. It is possible that these strains may have been co-circulating in this region for several years, but remained undetected as symptoms may have been attributed to other known endemic arboviruses with similar presentations, such as DENV and CHIKV. Alternatively, ZIKV may have been spread to each location successively as samples were collected at different time points.
Our report identifies a number of cases of confirmed ZIKV infection from different provinces across Thailand in patients with no recently reported travel outside their home province. When combined with previous reports of ZIKV infection in travelers to Thailand, it was clear that ZIKV has a widespread distribution across the country ( Figure 2). In future, increased surveillance using pan-flavivirus or ZIKV-specific molecular testing may lead to more frequent identification of ZIKV infections, which will help better describe the clinical spectrum of ZIKV infection, the distribution in Thailand, and the potential effects of co-circulation with other endemic flaviviruses.
Map of Thailand showing locations of confirmed Zika virus (ZIKV) infections. 1 ZIKV infection in Canadian traveler to Bangkok and Phuket provinces. 11 2 ZIKV infection in German traveler to Phuket and Krabi provinces. 12
We thank the patients who provided samples to the Thai Ministry of Public Health for testing during the investigations; the clinicians and investigation teams in Ratchaburi, Sisaket, Lamphun, and Phetchabun provinces; laboratory and administrative personnel at the Thailand National Institute of Health and the Armed Forces Research Institute of Medical Sciences, especially, Winai Kaneechit for mosquito inoculation and Prapapun Ong-Ajchaowlerd for C6/36 culture and typing ELISA; Richard Brown who helped coordinate the teleconference between Canadian and Thai public health personnel; Kip Baggett and Toni Whistler for their consultation; the CDC (Fort Collins, CO), particularly, Erin Staples and her colleagues, for their assistance with the ZIKV IgM ELISA and neutralization assays.
Financial support: Laura Hermann was supported by a Canadian Institutes of Health Research Fellowship.
Authors' addresses: Rome Buathong, Passakorn Akrasewi, and Tanarak Plipat, Department of Disease Control, Bureau of Epidemiology, Ministry of Public Health, Nonthaburi, Thailand, E-mails:
Summary of sample testing
| Date | Province | Age | Gender | DOI (days) | DENV RT-PCR | ZIKV RT-PCR | DENV IgM | DENV IgG | ZIKV IgM | DENV PRNT | ZIKV PRNT | Interpretation * |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| March 2012 | Ratchaburi | 18 | M | 7 | ND | Negative | Positive | Negative | Positive | 160 | 1,280 | ZIKV |
| March 2012 | Ratchaburi | 12 | F | 9 | ND | ND | Negative | Negative | Positive | 20 | 1,024 | ZIKV |
| March 2012 | Ratchaburi | 32 | F | 16 | ND | ND | Negative | Negative | Positive | 80 | 10,240 | ZIKV |
| September 2013 | Lamphun | 9 | F | 1 | Negative | Positive | Negative | Negative | Negative | ND | ND | ZIKV |
| September 2013 | Sisaket | 53 | F | 3 | Negative | Positive | Negative | Negative | ND | ND | ND | ZIKV |
| July 2014 | Phetchabun | 39 | F | 1 | Negative | Positive | ND † | ND † | ND | ND | ND | ZIKV ‡ |
| July 2014 | Phetchabun | 24 | F | 3 | Negative | Positive | ND † | ND † | ND | ND | ND | ZIKV |
DENV = dengue virus; DOI = date of illness; ND = not determined; PRNT = plaque reduction neutralization test; RT-PCR = reverse transcription polymerase chain reaction; ZIKV = Zika virus.
Interpretation: a sample was considered positive if ZIKV RNA was detected (positive PCR) or immunoglobulin M (IgM) antibody was present against ZIKV, and ZIKV PRNT was ≥ 20 with ZIKV PRNT:DENV PRNT ratio ≥ 4.
Both samples collected from Phetchabun province were also negative for dengue virus nonstructural protein 1 (DENV NS1) antigen testing.
Virus for sequencing was isolated from this sample by intrathoracic inoculation of Toxorhynchites splendens mosquitoes from the serum followed by inoculation of C6/36 cells.


Background
This is the first of many posts where I lay out my fundamental thesis for altcoins. Investing in these altcoins coins is riskier than $BTC and $ETH as they have higher betas, but the upside is enormous. The return profile is similar to VC who investing in tech startups: most of the projects go bust, but a few of the winners can pay for all the losers and more. Unlike in traditional startups who adjusts valuations between rounds, crypto altcoins have constant price feedback, creating a lot of volatility especially at the lower market caps.
Altcoins
The altcoins can be split into various sections similar to how MSCI splits up the S&P 500 into 11 different sub-sectors like financials, energy, and utilities. Looking through the top projects, there are a few groupings that jump out:
- Layer 1's ($ETH, $DOT, $ADA, $SOL)
- Stable Coins ($USDT, $USDC, $DAI, $SUSD)
- Exchange Coins ($BNB, $FTT, $KCS)
- Privacy Coins ($XMR, $ZEC, $\SCRT, $PRIV)
- DeFi ($LINK, $UNI, $AAVE, $SNX)
FTX
In this article, I focus on $FTT, the native token for the cryptocurrency exchange FTX . FTX is one of the top cryptocurrency exchanges by trading volume with lots of innovative features that make it stand out:
- They were the first exchange to create 3x and -3x levered tokens12.
- Tokenized stock trading including pre-ipo stocks which trade 24/7. FTX participates in the IPO process of certain companies and receive shares from underwriters. They then use those shares to create markets before official IPO date. 3
- They are often the first exchange to list new tokens. Examples include $USDT and $SUSHI futures.
- Consistently have quality IEOs (initial exchange listings). Like IPOs in the traditional market or ICOs from 2017, nowdays many protocols directly list on exchanges. FTX vets these protocols and allows exposure from day one.
- There is a world class risk management system with minimal claw-backs, unlike some of their competitors. This allows them to capture more volume in times of high volatility.
$FTT
In summer 2019, FTX launched their exchange token $FTT which provides trading discounts and other airdrops to holders of the token. Staking $FTT tokens can give maker rebates up to .3 bps and FTX is one of the few large exchanges with maker rebates often leading to deeper liquidity on the exchange. In addition there are weekly buyback and burns of the tokens until half of the supply is destroyed. These burns equate to
- 33% of all fees generated from the exchange
- 10% of net additions to the insurance fund
- 5% of fees from other uses of the platform
ICO
There were 3 ICO rounds which sold a total of 59.3 million $FTT tokens sold. The breakdowns are as follows:
- 50 million tokens between $0.1 and $0.2. These linearly vest over first 3 months.
- 6.5 million tokens between $0.2 and $0.6. These linearly vest over first 1.5 months.
- 2.8 million tokens between $0.6 and $0.8. These linearly vest over first month.
Token Emission and Vesting Schedule
There is a 350 million supply cap of $FTT according the the whitepaper4. Currently there are around 100 million $FTT circulating, so it is important to learn the emission schedule as a lot of these tokens could be coming on the market creating dilution and sell pressure. Apart from the ICO tokens described above, there are around 115 million tokens to be sold for future rounds and 175 million tokens for other tasks like insurance fund insurance, safety fund, liquidity fund, and team tokens. These are all locked up over 3 years with a linear vesting schedule.
Circulating Supply
Here is the genesis wallet which held 350 million $FTT. Since then, 273 million has exited leaving the wallet with 77 million $FTT. Those 77 million tokens are presumably part of the 115 million tokens to be sold for future rounds. On Crunchbase, we can see that FTX raised two additional rounds, in December 2019 and March 2020. I believe that 38 million tokens were sold already with a three year daily unlock. Another large wallet has over 170 million $FTT and it is the companies wallet. This leaves a total of around 100 million circulating tokens.
Inflation and Deflation Modeling
Weekly Unlocks
On the transparency page, there is a link to the breakdown of team tokens. The team has around 31.25 million tokens locked over 3 years translating to about 200k tokens unlocked a week. The other two rounds of investors who sold on Crunchbase have around 38 million tokens locked over 3 years translating to about 240k tokens unlocked per week. Summing those two together, there are around 440k tokens unlocked each week.
Token Burns
The opposite of the inflation schedule is the weekly token burn. At the time of this article, there have been almost 10 million tokens burned which equates to around 100 million dollars. The best proxy for the tokens burned is trading volume and we can create a model predicting the amount of tokens burned to the volume traded. Around 100k-200k tokens were burned per week in 2020, so this would lead to anywhere from 200k-300k new tokens introduced per week or around 10 million to 15 million per year akin to 10% to 15% of the circulating supply.
Pricing
One of the more fundamental ways to see if the price of a specific cryptocurrency will go up is to look at the supply increase and see if the underlying fundamentals will increase more or less than the specific supply. We see that there will be 10-15% of token dilution so we should see if the fundamental metrics will increase more of less than this number as this would keep some of the fundamental ratios in line. For example, if we were valuing the company like a traditional stock on P/E ratio in order for the price to go up over the 10-15% dilution, the earnings must also go up 10-15%. This leads us to the next section which we can project the fundamentals of FTX which is again (inherentely) how much volume will trade on FTX.
Crypto Volume
At the heart of the future valuation is the projected future volume. Cryptocurrencies are a growing industry and volume have slowly increased throughout the years. The exchange pie is getting bigger and FTX is being a larger player relative to other exchanges. Below we a picture of aggregated futures crypto traded volume from 2020. Specifically the blue line is the volume traded5, which went from around $20 billion a day to the current $160 billion a day an 8x increase in a year. In addition, the red line is the plot of futures volume6 traded on FTX. This started at 2\% and has since gone up to close to 4\% of total derivatives volume 7. I expect both the volume of crypto currencies traded and the percent traded on FTX to continue to increase in the foreseeable future.
So this past year FTX almost doubled its volume in relation to its peers and crypto itself did an 8x in volume. If 2021 is even remotely close to 2020, $FTT is extremely undervalued.
Conclusion
FTX has consistently made strides to capture the most crypto volume. In August 2020, FTX bought Blockfolio, one of the leading portfolio tracking apps with over 6 million users at the time of purchase. Then just yesterday, on the heels of Robinhood and other US brokerages limiting stock trading in select names, Blockfolio adds zero fee stock and crypto trading.
With innovative features along with a history of growth, I believe that FTX will continue on its path to becoming the largest exchanges in the world. I own $FTT both as a beta play on crypto exchange volume increasing as well as an alpha play on FTX continuing to eat market share from other participants. The pie is growing and the share of the pie is growing.
- This is similar to the levered ETFs in traditional finance. ↩
- These have the advantage of having fixed borrow compared to futures and there are no liquidations on the levered tokens. ↩
- Airbnb was the first pre-IPO market and Coinbase is the second. These provide a unique way to get exposure to an unlisted but popular stock. ↩
- Etherscan says there is 340 million but I will lean on the whitepaper number. ↩
- Rolling 30 days ↩
- Also rolling 30 days ↩
- The reason why there is the spike in February and March is because that time was very high volatility and FTX was one of the exchanges that was still functioning properly with the least amount of clawbacks. ↩


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Nov 22, 2008 Shaun White Snowboarding. Platform: Xbox 360, PlayStation 3, Wii Publisher:. Ubisoft UK Price (as reviewed):£38 00 (inc. VAT) US Price (as
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South Florida runner wins Keys half-marathon title
KEY LARGO, Fla. (AP) - A South Florida runner has won the overall men’s half-marathon title at the Key Largo Bridge Run in the Florida Keys.
Derek Morgan, 34, of Fort Lauderdale posted a time of one hour, 31 minutes and 35 seconds Saturday.
Miami resident Caroline Klosowski, 25, ran 01:53:10 to win the women’s division.
In the event’s 4-Mile division, the overall men’s winner was 15-year-old Colin Chivers of Davenport, Florida, with a time of 26:26. Julie Kellett, 35, of Belmont, Massachusetts, placed first in the women’s division with 28:36.
Organizers said the event attracted 499 participants to traverse roadbed and the Jewfish Creek Bridge at the top of the Florida Keys Overseas Highway.
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