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Science с факт-чек на вирусната конспирация Фалшиви и абсурдни твърдения на Джуди Миковиц опровергани от престижно научно издание

Post Syndicated from Екип на Биволъ original https://bivol.bg/mikovits-fakes-debunk-science.html

неделя 10 май 2020


Във видеофилм, който през последните няколко дни разтърси социалните медии, вирусологът Джуди Миковиц твърди, че новият коронавирус е погрешно обвинен за многото смъртни случаи. Тя прави абсурдни твърдения за вируса, при които се почесваш по главата – например, че той се “активира” от маските за лице.

Миковиц обвинява Антъни Фаучи, ръководител на Американския Национален институт по алергии и инфекциозни болести (NIAID) и ключов член на щаба за борба с коронавируса при Белия дом – тя смята, че той е отговорен за смъртта на милиони в първите години на пандемията на ХИВ/СПИН. Във видеото Миковиц твърди, че е била част от екипа, който открива ХИВ, че прави революция в лечението на ХИВ и че е била в затвора без повдигнато обвинение за научните си позиции.

Изданието „Наука“ /Science/ изследва видеото и подчертава, че нито едно от тези твърдения не е вярно. Видеото е откъс от предстоящия филм „Plandemic“, който обещава да “изложи научния и политически елит, който управлява измамата, каквато е нашата глобална здравна система”. YouTube, Facebook и други платформи са свалили видеоклипа поради неточности. Той продължава да се разпространява, включително на уебсайта на „Plandemic“, който в “опит да заобиколи преградите за свободното слово”, кани хората да изтеглят видеото и да го репостват.

Но първо, коя е Джуди Миковиц?

Миковиц започва кариерата си като лаборант в Националния онкологичен институт (NCI) през 1988 г. Тя става учен и получава докторска степен по биохимия и молекулярна биология от Университета Джордж Вашингтон през 1991. До 2009 г. е директор на института Уитмор Питърсън (WPI), частен изследователски център в Рино, Невада, но остава до голяма степен непозната на научната общност. Същата година, обаче, тя става съавтор на научен доклад, който разкрива неясен агент, наречен свързан вирус на ксенотропна миша левкемия (XMRV), причинен от синдрома на хроничната умора (CFS).

Причината за CFS, наричан още миалгичен енцефаломиелит, отдавна остава неуловима, а болестта е пренебрегвана от науката. Проучването създаде надежда, че CFS може да стане лечим с антивирусни средства. Някои пациенти дори започнаха да приемат антиретровирусни лекарства, използвани от заразени с ХИВ хора. Но документът също създаде притеснения, че XMRV може да се разпространи чрез кръвоснабдяването.

Други изследователи скоро подлагат на съмнения констатациите и през следващите 2 години твърденията на доклада се разпаднаха. Изследователите показват, че XMRV е създаден случайно в лабораторията по време на експерименти с мишки и може никога да не е инфектирал хора. Авторите първо са изтеглили две цифри и таблица от доклада през октомври 2011 г. По същото време, едно изследване от няколко лаборатории, включително и тази в института Уитмор Питърсън, показват, че констатациите не могат да бъдат потвърдени.

Два месеца по-късно целият научен доклад е отстранен. Миковиц отказва да подпише известието за отписването, но тя участва в още едно голяма разработка. Това проучване за $2.3 милиона, водено от Иън Липкин от Колумбийския университет и финансирано от Националните институти по здравеопазване, е “окончателният отговор”, заяви Миковиц на пресконференция през септември 2012 г., на която резултатите бяха обявени. В задълбоченото проучване се търси XMRV в кръв от почти 300 души, половината от които са имали болестта, и нито един от тях не е имал вирус. “Няма доказателства, че XMRV е човешки патоген”, призна Миковиц.

Отделът за научни новини на Scienc, който работи независимо от редакцията, следва отблизо сагата и публикува подробна реконструкция на фиаското през септември 2011. (Историята печели награда за комуникации от Американското дружество за микробиология.)

По същото време Миковиц преживя взривоопасна раздяла с WPI – института Уитмор Питърсън. Институтът заведе дело срещу нея през ноември 2011г. за предполагаемо премахване на лабораторни дневници и съхраняване на друга патентована информация на личния лаптоп, на флашки и в личен имейл акаунт. Арестувана е в Калифорния по обвинение в престъпление като беглец от правосъдието и е била в затвора няколко дни. Прокурорите в Невада в крайна сметка свалиха наказателните обвинения срещу нея през юни 2012 г.

Миковиц не е публикувала нищо в научната литература от 2012 г. Но скоро отново започва да популяризира хипотезата за ХMRV и атакува изследването на Липкин, че се е съгласил да остави въпроса на пауза. Тя се включва в дебата за аутизма с противоречиви теории за причините и леченията. Нейната дискредитирана работа и правните й патила я направиха мъченик в очите на някои.

Сега идва нова книга с нейно съавторство „Чумата на корупцията: Възстановяване на вярата в обещанието на науката“, таксувана като “задкулисието на въпросите и егото, които ще определят бъдещото здраве на човечеството”, и видеото за вируса, което е разширено интервю с Миковиц.

Изданието Science поиска разговор с Миковиц за тази статия. Тя отговори с празен имейл с прикачен файл копие от новата си книга и PowerPoint на презентация от 2019 г., озаглавена “Преследване и прикриване”.

По-долу са представени някои от основните твърдения във видеоклипа, заедно с проверените факти:

Интервюиращ: Д-р Джуди Миковиц е определена като един от най-изявените учени от нейното поколение.

Тя е автор на 40 научни статии и не е широко известна в научната общност, преди да публикува научния доклад от 2009 г., в който се твърди, че има връзка между новия ретровирус и CFS (синдром на хроничната умора). По-късно докладът е посочен като погрешен и е отречен.

Интервюиращ: Нейната докторска теза от 1991 г. прави революция в лечението на ХИВ/СПИН.

Тезата в доктората на Миковиц “Негативна регулация на ХИВ експресия в моноцитите” видимо не оказа осезаемо влияние върху лечението на ХИВ/СПИН.

Интервюиращ: В разгара на кариерата си д-р Миковиц публикува блокбъстър в списание Science. Спорната статия предизвиква шокови вълни сред научната общност, тъй като тя разкрива, че общата употреба на животински и човешки тъкани е причина за разгръщане на унищожителни язви от хронични заболявания.

Докладът й не разкрива нищо от това, тя само е твърдяла, че показва връзка между едно условие, CFS, и миши ретровирус.

Миковиц: Бях въдворена в затвора, без да имам подвигнати обвинения.

Окръжният прокурор в Невада подаде наказателна жалба срещу Миковиц, като я обвини в незаконно вземане на компютърни данни от WPI – института Уитмор Питърсън. Обвиненията бяха отпаднали, отчасти поради правни проблеми, пред които е бил изправен бившият й работодател.

Миковиц: Ръководителите на целия ни HHS (Департамент по здравеопазване и човешки услуги) забъркаха и унищожиха репутацията ми, и Министерството на правосъдието и ФБР държаха това дело запечатано.

Миковиц не е представила преки доказателства, че ръководителите на HHS са заговорничили срещу нея.

Миковиц: (Фаучи) режисира прикриването. И всъщност, всички останали бяха платени и се платиха много пари, милиони долари се финансираха от Тони Фаучи и … Националния институт по алергии и инфекциозни болести. И до ден днешен тези изследователи, извършили измамата, продължават да получават много от NIAID.

Не е ясно за кои измами и за какво точно говори Миковиц. Няма доказателства, че Фаучи е замесен в прикриване, или че някой е заплатен с финансиране от него или от института му. Никой не е обвинен в измама във връзка с твърденията на Миковиц.

Миковиц: Започна реално, когато бях на 25 години, и бях част от екипа, който изолира ХИВ от слюнката и кръвта на пациентите от Франция, където вирусологът Люк Монтание първоначално изолира вируса. … Фаучи публикува доклада си в продължение на няколко месеца, докато Робърт Гало пише свой собствен и взима всички кредити, и разбира се, с включени патенти. Това забавяне на потвърждението буквално доведе до разпространение на вируса, както знаете, до убийството на милиони.

По време на откриването на ХИВ Миковиц е лабораторен техник в лабораторията на Франсис Русцети в NCI и все още не е получила докторската си титла. Няма доказателства, че е била част от екипа, който е изолирал вируса. Първата й публикация, съавторска с Русцети, е за ХИВ и е публикувана през май 1986 г., 2 години след като Science публикува четири статии, които свързват ХИВ (след това наречен HTLV-III от лабораторията на Гало) със СПИН. Първият доклад на Русцети за ХИВ се появява през август 1985 г. Няма доказателства, че Фаучи е задържал доклада или че това е довело до смъртта на милиони.

Интервюиращ: Ако се наложат задължителни ваксини в световен мащаб, предполагам, че тези хора, които ги притежават, ще направят станат стотици милиарди долари.

Миковиц: И те ще убият милиони, които вече са ваксинирани. Понастоящем няма ваксина по схема за който и да е РНК вирус, която действа.

Ваксините не са убили милиони; те са спасили милиони животи. Много ваксини, които работят срещу РНК вируси, са на пазара, включително за грип, морбили, паротит, рубеола, бяс, жълта треска и ебола.

Интервюиращ: Трябва да те питам, да не си антиваксър?
Миковиц: О, абсолютно не. Всъщност ваксината е имунна терапия, както интерферон алфа е имунна терапия, така че аз не съм антиваксър. Работата ми е да развивам имунни терапии. Това са ваксините.

В друг видеоклип Миковиц носи шапка с надпис VAXXED II, което е продължение на филм, който свързва ваксина срещу морбили, паротит и рубеола с аутизъм, развенчаващо теорията й. Тя също така повтаря няколко твърдения, направени от хора, които ръководят движението срещу ваксините. В презентацията на PowerPoint, която тя изпрати на Science, тя призовава за “незабавен мораториум” на всички ваксини.

Интервюиращ: Смятате ли, че този вирус (SARS-CoV-2) е създаден в лаборатория?
Миковиц: Не бих използвала думата създадена. Но не може да се каже, че е естествено срещнат, ако е било чрез лабораторията. Значи, много е ясно, че вирусът е манипулиран. Това семейство вируси е манипулирано и проучено в лаборатория, където животните са били поставени в лабораторията, и това е това, което е било освободено, независимо дали умишлено или не. Това не може да е естествено. Не някой е бил на пазар и си е купил прилеп, не е било на пазара, вирусът не скача директно върху хората. Не става така. Това е ускорена вирусна еволюция. Ако е било естествено явление, би отнело до 800 години, за да се случи.

Научните оценки показват, че най-близкият вирус до SARS-CoV-2, този, който причинява COVID-19, е прилепов коронавирус, идентифициран от Института по вирусология в Ухан (WIV). “Разстоянието” в еволюционното време до SARS-CoV-2 е около 20 до 80 години. Няма доказателства, че вирусът на прилепа е бил манипулиран.

Интервюиращ: А имате ли някакви идеи за това къде е станало?
Миковиц: О, да, сигурна съм, че е станало между лабораториите на Северна Каролина Форт Детрик, Медицинския институт по инфекциозни болести на армията на САЩ и лабораторията в Ухан.

Няма доказателства, че SARS-CoV-2 е с произход от WIV (Wuhan Institute of Virology). Институтът на Фаучи спря финансирането на американските екипи, които работят с лабораторията на Ухан, това възмути много учени.

Миковиц: Италия има много старо население. Тези хора са много болни от възпалителни заболявания. В началото на 2019 г. те получиха неизпитана нова форма на грипна ваксина, която има четири различни щама грип, включително високо патогенния H1N1. Ваксината е била отгледана в клетъчна линия, в кучешка клетъчна линия. Кучетата имат много коронавируси.

Няма доказателства, че всяка ваксина срещу грип, или кучешки коронавирус са свързани с епидемията от Covid-19 в Италия.

Миковиц: Носенето на маската буквално активира собствения ти вирус. И ако се случи да е SARS-CoV-2, тогава имаш голям проблем.

Не е ясно какво Миковиц обозначава с “коронавирусни изрази”. Няма доказателства, че носенето на маска може да активира вируси и да разболее хората.

Миковиц: Защо ще затваряте плажа? Имате последователности в почвата, в пясъка. Имате лечебни микроби в океана, в солената вода. Това е лудост.
Не е ясно какво означава за Миковиц „последователности“ в пясъка или почвата. Няма доказателства, че микробите в океана могат да лекуват пациенти с COVID-19.

Автори: Мартин Енсеринк, Джон Коен, Science

Превод: Екип на Биволъ

FluSense takes on COVID-19 with Raspberry Pi

Post Syndicated from Ashley Whittaker original https://www.raspberrypi.org/blog/flusense-takes-on-covid-19-with-raspberry-pi/

Raspberry Pi devices are often used by scientists, especially in biology to capture and analyse data, and a particularly striking – and sobering – project has made the news this week. Researchers at UMass Amherst have created FluSense, a dictionary-sized piece of equipment comprising a cheap microphone array, a thermal sensor, an Intel Movidius 2 neural computing engine, and a Raspberry Pi. FluSense monitors crowd sounds to forecast outbreaks of viral respiratory disease like seasonal flu; naturally, the headlines about their work have focused on its potential relevance to the COVID-19 pandemic.

A photo of Forsad Al Hossain and Tauhidur Rahman with the FluSense device alongside a logo from the Amherst University of Massachusetts

Forsad Al Hossain and Tauhidur Rahman with the FluSense device. Image courtesy of the University of Massachusetts Amherst

The device can distinguish coughing from other sounds. When cough data is combined with information about the size of the crowd in a location, it can provide an index predicting how many people are likely to be experiencing flu symptoms.

It was successfully tested in in four health clinic waiting rooms, and now, PhD student Forsad Al Hossain and his adviser, assistant professor Tauhidur Rahman, plan to roll FluSense out in other large spaces to capture data on a larger scale and strengthen the device’s capabilities. Privacy concerns are mitigated by heavy encryption, and Al Hossain and Rahman explain that the emphasis is on aggregating data, not identifying sickness in any single patient.

The researchers believe the secret to FluSense’s success lies in how much of the processing work is done locally, via the neural computing engine and Raspberry Pi: “Symptom information is sent wirelessly to the lab for collation, of course, but the heavy lifting is accomplished at the edge.”

A bird's-eye view of the components inside the Flu Sense device

Image courtesy of the University of Massachusetts Amherst

FluSense offers a different set of advantages to other tools, such as the extremely popular self-reporting app developed by researchers at Kings College Hospital in London, UK, together with startup Zoe. Approaches like this rely on the public to sign up, and that’s likely to skew the data they gather, because people in some demographic groups are more likely than others to be motivated and able to participate. FluSense can be installed to capture data passively from groups across the entire population. This could be particularly helpful to underprivileged groups who are less likely to have access to healthcare.

Makers, engineers, and scientists across the world are rising to the challenge of tackling COVID-19. One notable initiative is the Montreal General Hospital Foundation’s challenge to quickly design a low-cost, easy to use ventilator which can be built locally to serve patients, with a prize of CAD $200,000 on offer. The winning designs will be made available to download for free.

There is, of course, loads of chatter on the Raspberry Pi forum about the role computing has in beating the virus. We particularly liked this PSA letting you know how to free up some of your unused processing power for those researching treatments.

screenshot of the hand washer being built from a video on instagram

Screenshot via @deeplocal on Instagram

And to end on a cheering note, we *heart* this project from @deeplocal on Instagram. They’ve created a Raspberry Pi-powered soap dispenser which will play 20 seconds of your favourite song to keep you at the sink and make sure you’re washing your hands for long enough to properly protect yourself.

The post FluSense takes on COVID-19 with Raspberry Pi appeared first on Raspberry Pi.

Raspberry Pi vs antibiotic resistance: microbiology imaging with open source hardware

Post Syndicated from Helen Lynn original https://www.raspberrypi.org/blog/raspberry-pi-vs-antibiotic-resistance-microbiology-imaging-with-open-source-hardware/

The Edwards Lab at the University of Reading has developed a flexible, low-cost, open source lab robot for capturing images of microbiology samples with a Raspberry Pi camera module. It’s called POLIR, for Raspberry Pi camera Open-source Laboratory Imaging Robot. Here’s a timelapse video of them assembling it.

Measuring antibiotic resistance with colour-changing dye

The robot is useful for all kinds of microbiology imaging, but at the moment the lab is using it to measure antimicrobial resistance in bacteria. They’re doing this by detecting the colour change in a dye called resazurin, which changes from blue to pink in the presence of metabolically active cells: if bacteria incubated with antibiotics grow, their metabolic activity causes the dye to turn pink. However, if the antibiotics stop or impede the growth of the bacteria, their lower levels of metabolic activity will cause less colour change, or none at all. In the photo below, the colourful microtitre plate holds bacterial samples with and without resistance to the antibiotics against which they’re being tested.

POLIR, an open source 3D printer-based Raspberry Pi lab imaging robot

An imaging system based on 3D-printer designs

The researchers adapted existing open source 3D printer designs and used v-slot aluminium extrusion (this stuff) with custom 3D-printed joints to make a frame. Instead of a printer extrusion head, a Raspberry Pi and camera module are mounted on the frame. An Arduino running open-source Repetier software controls x-y-z stepper motors to adjust the position of the computer and camera.

Front and top views of POLIR

Open-source OctoPrint software controls the camera position by supplying scripts from the Raspberry Pi to the Arduino. OctoPrint also allows remote access and control, which gives researchers flexibility in when they run experiments and check progress. Images are acquired using a Python script configured with the appropriate settings (eg image exposure), and are stored on the Raspberry Pi’s SD card. From there, they can be accessed via FTP.

More flexibility, lower cost

Off-the-shelf lab automation systems are extremely expensive and remain out of the reach of most research groups. POLIR cost just £600.

The system has a number of advantages over higher-cost off-the-shelf imaging systems. One is its flexibility: the robot can image a range of sample formats, including agar plates like those in the video above, microtitre plates like the one in the first photograph, and microfluidic “lab-on-a-comb” devices. A comb looks much like a small, narrow rectangle of clear plastic with striations running down its length; each striation is a microcapillary with capacity for a 1μl sample, and each comb has ten microcapillaries. These microfluidic devices let scientists run experiments on a large number of samples at once, while using a minimum of space on a lab bench, in an incubator, or in an imaging robot like POLIR.

POLIR accommodates 2160 individual capillaries and a 96 well plate, with room to spare

High spatial and temporal resolution

For lab-on-a-comb images, POLIR gives the Reading team four times the spatial resolution they get with a static camera. The moveable Raspberry Pi camera with a short focus yields images with 6 pixels per capillary, compared to 1.5 pixels per capillary using a $700 static Canon camera with a macro lens.

Because POLIR is automated, it brings higher temporal resolution within reach, too. A non-automated system, by contrast, can only be used for timelapse imaging if a researcher repeatedly intervenes at fixed time intervals. Capturing kinetic data with timelapse imaging is valuable because it can be significant if different samples reach the same endpoint but at different rates, and because some dyes can give a transient signal that would be missed by an endpoint measurement alone.

Dr Alexander Edwards of the University of Reading comments:

We built the robot with a simple purpose, to make antimicrobial resistance testing more robust without resorting to expensive and highly specialised lab equipment […] The beauty of the POLIR kit is that it’s based on open source designs and we have likewise published our own designs and modifications, allowing everyone and anyone to benefit from the original design and the modifications in other contexts. We believe that open source hardware is a game changer that will revolutionise microbiological and other life science lab work by increasing data production whilst reducing hands-on labour time in the lab.

You can find POLIR on GitLab here. You can also read more, and browse more figures, in the team’s open-access paper, Exploiting open source 3D printer architecture for laboratory robotics to automate high-throughput time-lapse imaging for analytical microbiology.

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Chinese bioweapon II: Electric Boogaloo

Post Syndicated from esr original http://esr.ibiblio.org/?p=8587

Yikes. Despite the withdrawal of the Indian paper arguing that the Wuhan virus showed signs of engineering, the hypothesis that that it’s an escaped bioweapon looks stronger than ever.

Why do I say this? Because it looks like my previous inclination to believe the rough correctness of the official statistics – as conveyed by the Johns Hopkins tracker – was wrong. I now think the Chinese are in way deeper shit than they’re admitting.

My willingness to believe the official line didn’t stem from any credulity about what the Chinese government would do if it believed the truth wouldn’t serve. As Communists they are lying evil scum pretty much by definition, and denial would have been politically attractive for as long as they thought they could nip the pandemic in the bud. I thought their incentives had flipped and they would now be honest as a way of assisting their own countermeasures and seeking international help.

My first clue that I was wrong about that came from a friend who is plugged into the diaspora Chinese community. According to him, there is terrifying video being sent from Chinese clans to the overseas branches they planted in the West to prepare a soft landing in case they have to bail out of China. Video of streets littered with corpses. And of living victims exhibiting symptoms like St. Vitus’s Dance (aka Sydenham’a chorea), which means the virus is attacking central nervous systems.

My second clue was the Tencent leak. Read about it here; the takeaway is that there is now reason to believe that as of Feb 1st the actual coronavirus toll looked like this: confirmed cases 154023, suspected cases 79808, cured 269, deaths 24589.

Compare that with the Johns Hopkins tracker numbers for today, a week later: Confirmed cases 31207, cured 1733, deaths 638. Allowing for the Tencent leak being roughly one doubling period earlier, the official statistics have been lowballing the confirmed case number by a factor of about 8 and the deaths by a factor of about 80. And then inflating cures by a factor of about 12.

Even given what I’d heard about the video, I might have remained skeptical about the leak numbers if someone (don’t remember who or where) hadn’t pointed out that the ratio between reported cases and deaths has been suspiciously constant in the official Chinese statistics. In uncooked statistics one would expect more noise in that ratio, if only because of reporting problems.

So my present judgment, subject to change on further evidence, is that the Tencent-leak numbers are the PRC’s actual statistics. And that has a lot of grim implications.

One is that the Wuhan virus has at least a 15% fatality rate in confirmed cases – and most ways the PRC’s own statistics could be off due to reporting problems would drive it higher. Another is that containment in China has failed. Even in the cooked official statistics first derivative has not fallen; the doubling time is on the close order of five days now and may decrease.

We are already well past any even theoretical coping capability of China’s medical infrastructure. For that matter, it isn’t likely that there are enough trained medical personnel on the entire planet to get on top of a pandemic this size with a 5-day doubling time.

Which means this thing is probably not going to top out in China until it saturates the percentage of the population without natural immunity and kills at least 15% of them. The big, grim question is how many natural immunes there are. The history of past natural pandemics does not conduce to any optimism at all about that.

A very safe prediction is that a whole lot of elderly Chinese people are going to die because their immune systems are pre-compromised.

China’s population is about 1.4 billion. Conservatively, therefore, we can already expect this plague to kill more people in China than the Black Death did in Europe. At its present velocity we can expect that in about 12 doubling periods, or approximately 60 days.

Meanwhile, coronavirus spread outside China enters a critical time.

Based on what we think we know about the incubation period (about 14 days), if there’s going to be a pandemic breakout outside of China due to asymptomatic carriers, we should start to see a slope change in the overseas incidence curve during the next week. It’s been long enough for that now.

If that doesn’t happen, either the rest of the world dodged the pandemic bullet (optimistic) or the low end of the incubation period is longer than has been thought (pessimistic). On the basis of previous experience with SARS and MERS, I think the optimistic read is more likely to be correct.

Now back to the bioweapon hypothesis. Does recent data strengthen or weaken it? Consider:

* 645 Indian evacuees from Wuhan all tested negative.

* The only death outside China has been an ethnic-Chinese traveler from Wuhan.

The evidence that this virus likes to eat Han Chinese and almost ignores everybody else is mounting. That’s bioweapon-like selectivity.

One of my previous objections to the bioweapon hypothesis was that the Wuhan virus’s lethality wasn’t high enough. At 15% or higher I withdraw that objection.

And that St. Vitus’s Dance thing – coronaviruses don’t do that. But it’s exactly the kind of thing you’d engineer into a terror weapon intended not just to kill a chunk of your target population but break the morale of the rest.

Finally, my friend Phil Salkie tells me that on Google Maps the reported location of the Wuhan Institute of Virology has been jumping around like a Mexican flea. That’s guilty behavior, that is.

Three reasons to believe the Wuhan virus is a bioweapon

Post Syndicated from esr original http://esr.ibiblio.org/?p=8566

I know it sounds like tinfoil-hat territory, but there are now three pieces of evidence pointing at the conclusion that the Wuhan coronavirus is an accidentally released bioweapon.

First point: The propagation statistics of this virus have looked deeply weird from the get-go. In particular, the differential in spread and mortality rates between China and the rest of the world.

This map and accompanying statistics story the story. Inside China, the disease is propagating like crazy and has 2.3% mortality among those showing overt symptoms (which sounds low, but it’s about the same as the devastating 1918 flu virus). Outside of China, the disease has spread very very slowly and there have been zero deaths. If it had comparable lethality among overseas populations to what it has exhibited in China we should have seen approximately 4 overseas deaths by now.

In general, infectious diseases only have this kind of behavioral split when for whatever reason you’re looking at two populations with greatly differing vulnerability to the pathogen. The classic example is Hansen’s disease – leprosy – which is nearly asymptomatic in most of the population but has horrifying symptoms if you are in a minority with exactly the wrong alleles at six identified genetic loci.

In the case of the Wuhan virus, infectivity and lethality may be related to a particular protein called ACE II which, when present in lung cells, acts as a receptor for the virus. This receptor is, apparently, common in East Asians but not in other populations.

If you were designing a targeted bioweapon, this is exactly the kind of discriminator you’d look for – a way to make it highly lethal to a specific target population and relatively harmless to others.

Second point: The Wuhan virus shows signs of having been engineered. This paper says there are four sequences in the Wuhan virus’s spike protein that are suspiciously similar to those of the AIDS virus. The abstract observes the similarities are “unlikely to be fortuitous in nature”.

Third point: Laboratory facilities that are graded for the most dangerous category of research into infectious diseases are called P4 or BSL4 labs. If you are doing research into biological warfare, a P4 lab is where you are doing it, because it’s too dangerous to pursue anywhere else.

Worldwide, there are approximately 55 such laboratories. The U.S. has 15 of them. The People’s Republic of China has one. It’s the Wuhan Institute of Virology and yes, it’s located at geographical ground zero of the outbreak.

Awfully damn coincidental, isn’t that?

Let’s review. Virus shows signs of engineering. There’s a P4 lab dealing in virus research at ground zero of the epidemic. And the virus exhibits weirdly sharp selectivity about who it will infect and kill.

There are problems with the bioweapon theory. One is the obvious question of why the PRC would design a bioweapon genetically targeted at its own people. Another is that the Wuhan virus is missing some traits you’d want in a production bioweapon, like much higher lethality and a reliable vaccine. If the PRC had one they would surely have deployed it by now.

But there is a plausible theory that fits all these facts. It’s this: the Wuhan virus was not a deliberate release of a production bioweapon, it was an accidental release of research in progress – the kind of nasty “Ooops!” that P4 containment is designed to prevent. Someone screwed up big time.

And why targeted on East Asians? Possibly no reason at all other than they were experimenting with genetic targeting and it was intended as a step towards a virus that could selectively target gweilos. Or Japanese. Or Indians.

But I can think of a blood-chillingly good reason for the Communists to keep a shot like this in their locker. And that reason is the island of Taiwan. Release the virus there, wait for it to do its thing, then when the Taiwanese are screaming for help offer humanitarian aid. Delivered by the Peoples’ Liberation Army.

No, I do not think this was intended for Hong Kong. The PRC leadership are not gamblers; I don’t think they’d be down with releasing a bioweapon in a city that has close overland links with the Chinese industrial heartland. But Taiwan is an island; if the plague got too hot for available countermeasures you could just interdict the island until it cooled down.

A final note: if the Chinese people become convinced that the PRC government brewed up this virus, it’s done. Kaput. Serious plagues are historically considered a sign that a dynasty has lost the Mandate of Heaven anyway, and the self-infliction of the wound would make the legitimacy collapse harder. Every couple of centuries there are popular revolts severe enough to topple dynasties; we could see one over this.

Growth Monitor pi: an open monitoring system for plant science

Post Syndicated from Helen Lynn original https://www.raspberrypi.org/blog/growth-monitor-pi-an-open-monitoring-system-for-plant-science/

Plant scientists and agronomists use growth chambers to provide consistent growing conditions for the plants they study. This reduces confounding variables – inconsistent temperature or light levels, for example – that could render the results of their experiments less meaningful. To make sure that conditions really are consistent both within and between growth chambers, which minimises experimental bias and ensures that experiments are reproducible, it’s helpful to monitor and record environmental variables in the chambers.

A neat grid of small leafy plants on a black plastic tray. Metal housing and tubing is visible to the sides.

Arabidopsis thaliana in a growth chamber on the International Space Station. Many experimental plants are less well monitored than these ones.
(“Arabidopsis thaliana plants […]” by Rawpixel Ltd (original by NASA) / CC BY 2.0)

In a recent paper in Applications in Plant Sciences, Brandin Grindstaff and colleagues at the universities of Missouri and Arizona describe how they developed Growth Monitor pi, or GMpi: an affordable growth chamber monitor that provides wider functionality than other devices. As well as sensing growth conditions, it sends the gathered data to cloud storage, captures images, and generates alerts to inform scientists when conditions drift outside of an acceptable range.

The authors emphasise – and we heartily agree – that you don’t need expertise with software and computing to build, use, and adapt a system like this. They’ve written a detailed protocol and made available all the necessary software for any researcher to build GMpi, and they note that commercial solutions with similar functionality range in price from $10,000 to $1,000,000 – something of an incentive to give the DIY approach a go.

GMpi uses a Raspberry Pi Model 3B+, to which are connected temperature-humidity and light sensors from our friends at Adafruit, as well as a Raspberry Pi Camera Module.

The team used open-source app Rclone to upload sensor data to a cloud service, choosing Google Drive since it’s available for free. To alert users when growing conditions fall outside of a set range, they use the incoming webhooks app to generate notifications in a Slack channel. Sensor operation, data gathering, and remote monitoring are supported by a combination of software that’s available for free from the open-source community and software the authors developed themselves. Their package GMPi_Pack is available on GitHub.

With a bill of materials amounting to something in the region of $200, GMpi is another excellent example of affordable, accessible, customisable open labware that’s available to researchers and students. If you want to find out how to build GMpi for your lab, or just for your greenhouse, Affordable remote monitoring of plant growth in facilities using Raspberry Pi computers by Brandin et al. is available on PubMed Central, and it includes appendices with clear and detailed set-up instructions for the whole system.

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A low-cost, open-source, computer-assisted microscope

Post Syndicated from Helen Lynn original https://www.raspberrypi.org/blog/a-low-cost-open-source-computer-assisted-microscope/

Low-cost open labware is a good thing in the world, and I was particularly pleased when micropalaeontologist Martin Tetard got in touch about the Raspberry Pi-based microscope he is developing. The project is called microscoPI (what else?), and it can capture, process, and store images and image analysis results. Martin is engaged in climate research: he uses microscopy to study tiny fossil remains, from which he gleans information about the environmental conditions that prevailed in the far-distant past.

microscoPI: a microcomputer-assisted microscope

microscoPI a project that aims to design a multipurpose, open-source and inexpensive micro-computer-assisted microscope (Raspberry PI 3). This microscope can automatically take images, process them, and save them altogether with the results of image analyses on a flash drive. It it multipurpose as it can be used on various kinds of images (e.g.

Martin repurposed an old microscope with a Z-axis adjustable stage for accurate focusing, and sourced an inexpensive X/Y movable stage to allow more accurate horizontal positioning of samples under the camera. He emptied the head of the scope to install a Raspberry Pi Camera Module, and he uses an M12 lens adapter to attach lenses suitable for single-specimen close-ups or for imaging several specimens at once. A Raspberry Pi 3B sits above the head of the microscope, and a 3.5-inch TFT touchscreen mounted on top of the Raspberry Pi allows the user to check images as they are captured and processed.

The Raspberry Pi runs our free operating system, Raspbian, and free image-processing software ImageJ. Martin and his colleagues use a number of plugins, some developed themselves and some by others, to support the specific requirements of their research. With this software, microscoPI can capture and analyse microfossil images automatically: it can count particles, including tiny specimens that are touching, analyse their shape and size, and save images and results before prompting the user for the name of the next sample.

microscoPI is compact – less than 30cm in height – and it’s powered by a battery bank secured under the base of the microscope, so it’s easily portable. The entire build comes in at under 160 Euros. You can find out more, and get in touch with Martin, on the microscoPI website.

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The dream is real

Post Syndicated from esr original http://esr.ibiblio.org/?p=8473

So, I just listened to an elaborate economic and engineering rationale for why Elon Musk’s new Starship is not the tall skinny pressurized-aluminum cylinder we’re used to thinking of a real rocket, but a fat cigar-shaped thing made of stainless steel, with tail fins.

And I don’t believe a word of it.

It had to be that way because Elon Musk grew up on the same Golden Age science fiction magazine cover illustrations I did, and it looks exactly like those.

Has tailfins. Freaking tailfins. And lands on a pillar of fire just like God and Robert Heinlein (PBUH) intended.

The dream is real.

Contra Gelernter on Darwin

Post Syndicated from esr original http://esr.ibiblio.org/?p=8422

David Gelernter recently wrote an essay on Giving Up Darwin that is not obviously stupid. Dr. Gelernter, in many ways an astute thinker, does not commit obvious stupidities – but I have had to call him out before for allowing himself to be blinded by a hunger for epistemic gaps that fit the shape of religion. Apparently it is, alas, time to do that again.

The central argument of Gelernter’s essay is that random chance is not good enough, even at geologic timescales, to produce the ratchet of escalating complexity we see when we look at living organisms and the fossil record. Most mutations are deleterious and degrade the functioning of the organism; few are useful enough to build on. There hasn’t been enough time for the results we see.

Before getting to that one I want to deal with a subsidiary argument in the essay, that Darwinism is somehow falsified because we don’t observe the the slow and uniform evolution that Darwin posited. But we have actually observed evolution (all the way up to speciation) in bacteria and other organisms with rapid lifespans, and we know the answer to this one.

The rate of evolutionary change varies; it increases when environmental changes increase selective pressures on a species and decreases when their environment is stable. You can watch this happen in a Petri dish, even trigger episodes of rapid evolution in bacteria by introducing novel environmental stressors.

Rate of evolution can also increase when a species enters a new, unexploited environment and promptly radiates into subspecies all expressing slightly different modes of exploitation. Darwin himself spotted this happening among Galapagos finches. An excellent recent book, The 10,000 Year Explosion, observes the same acceleration in humans since the invention of agriculture.

Thus, when we observe punctuated equilibrium (long stretches of stable morphology in species punctuated by rapid changes that are hard to spot in the fossil record) we shouldn’t see this as the kind of ineffable mystery that Gelernter and other opponents of Darwinism want to make of it. Rather, it is a signal about the shape of variability in the adaptive environment – also punctuated.

Even huge punctuation marks like the Cambrian explosion, which Gelernter spends a lot of rhetorical energy trying to make into an insuperable puzzle, fall to this analysis. The fossil record is telling us that something happened at the dawn of the Cambrian that let loose a huge fan of possibilities; adaptive radiation, a period of rapid evolution, promptly followed just as it did for the Galapagos finches.

We don’t know what happened, exactly. It could have been something as simple as the oxygen level in seawater going up. Or maybe there was some key biological invention – better structural material for forming hard body parts with would be one obvious one. Both these things, or several other things, might have happened near enough together in time that the effects can’t be disentangled in the fossil record.

The real point here is that there is nothing special about the Cambrian explosion that demands mechanisms we haven’t observed (not just theorized about, but observed) on much faster timescales. It takes an ignotum per æque ignotum kind of mistake to erect a mystery here, and it’s difficult to imagine a thinker as bright as Dr. Gelernter falling into such a trap…unless he wants to.

But Dr. Gelernter makes an even more basic error when he says “The engine that powers Neo-Darwinian evolution is pure chance and lots of time.” That is wrong, or at any rate leaves out an important co-factor and leads to badly wrong intuitions about the scope of the problem. Down that road one ends up doing silly thought experiments like “How often would a hurricane assemble a 747 from a pile of parts?”

To get a better handle on the problem, it helps to ask the kind of question D’Arcy Thompson did in his monumental 1917 book “On Growth and Form”: why is a hen’s egg round?

The shape of an egg can be neatly described by a parametric equation in three variables, but neither that formula nor those parameters are encoded in the chicken genome. The chicken genome describes a relative simple production rule about the timed release of various egg-component chemicals; that rule doesn’t know anything about the spatial organization of the result.

What happens instead is a dance between the construction steps and the diffusion physics of the chemicals. The egg shape is supplied by the principle of least action. The chicken genome’s recipe captures – incorporates – this physics without actually coding it.

Thus, if you derange the egg-formation recipe with point mutations, the outcomes are limited by the physics. You may abort egg formation entirely, or you may get ellipsoids with differing sizes or shapes. What you won’t get is cubes or Klein bottles. Random variation in the egg-production genome doesn’t produce random variation in the shapes of eggs – it produces sharply constrained variation. The design space that mutations of the recipe are exploring is many orders of magnitude smaller and more continuous than you’d expect from a “pure chance” account.

Gelernter makes a similar mistake when he asks “Starting with 150 links of gibberish, what are the chances that we can mutate our way to a useful new shape of protein?” But this is never a question evolution has to answer. The nearest correct question would be “Starting from 150 links of a protein we know is already selected for usefulness because it’s already expressed in an organism, what are the chances we can mutate to something else useful?”

Again…the physics of van der Waals forces mean that a small change in coding for a protein is likely to produce a small change in its folding. As with eggs, point mutations are highly unlikely to jump a large distance in expressed phenotypic design. And – this is the point – they are thus unlikely to jump far away from a design that is productive for something.

The question Gelernter actually asked is a silly straw man that depends for its apparent force on the reader having no intuitions about the effects of a history of successful adaptation – or of the constraining role of extragenetic natural laws – at all.

Gelernter himself is definitely not stupid or ignorant enough to fall into this kind of error when he’s thinking clearly. From which we can only conclude that, on this subject, he refuses to think clearly.

Saving biologists’ time with Raspberry Pi

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/saving-biologists-time-with-raspberry-pi/

In an effort to save themselves and fellow biologists hours of time each week, Team IoHeat are currently prototyping a device that allows solutions to be heated while they are still in cold storage.

The IoHeat team didn’t provide any photos with their project writeup, so here’s a picture of a bored biologist that I found online

Saving time in the lab

As they explain in their prototype write-up:

As scientists working with living organisms (from single cells to tissue samples), we are often required to return to work outside of normal hours to maintain our specimens. In many cases, the compounds and solutions we are using in our line of work are stored at 4°C and need to reach 37°C before they can be used. So far, in order to do this we need to return to our workplace early, incubate our solutions at 37°C for 1–2h, depending on the required volume, and then use them in processes that often take a few minutes. It is clear that there is a lot of room here to improve our efficiency.

Controlling temperatures with Raspberry Pi

These hours wasted on waiting for solutions to heat up could be better spent elsewhere, so the team is building a Raspberry Pi–powered device that will allow them to control the heating process remotely.

We are aiming to built a small incubator that we can store in a cold room/fridge, and that can be activated remotely to warm up to a defined temperature. This incubator will enable us to safely store our reagents at low temperature and warm them up remotely before we need to use them, saving an estimate of 12h per week per user.

This is a great project idea, and they’ve already prototyped it using a Raspberry Pi, heating element, and fan. Temperature and humidity sensors connected to the Raspberry Pi monitor conditions inside the incubator, and the prototype can be controlled via Telegram.

Find out more about the project on Hackster.

We’ve got more than one biologist on the Raspberry Pi staff, so we have a personal appreciation for the effort behind this project, and we look forward to seeing how IoHeat progresses in the future.

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Raspberry Pi-monitored chemical reactor 💥

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/raspberry-pi-monitored-chemical-reactor/

In Hello World issue 7, Steven Weir introduces a Raspberry Pi into the classroom to monitor a classic science experiment.

A Raspberry Pi can be used to monitor the reaction between hydrochloric acid and sodium thiosulphate to complement a popular GCSE Chemistry practical.

The rate of reaction between hydrochloric acid and sodium thiosulphate is typically studied as part of GCSE Chemistry. The experiment involves measuring the time required for the reaction mixture to turn cloudy, due to the formation of sulphur as a precipitate. Students can then change the temperature or concentration of the reactants to study their effect on the rate of reaction. The time for the reaction mixture to turn cloudy is normally facilitated by recording the time a hand-drawn cross takes to become obscured when placed underneath a glass vessel holding the reaction mixture. This timing is prone to variability due to operator judgement of when the cross first becomes obscured. This variability can legitimately be discussed as part of the lesson. However, the element of operator judgement can be avoided using a Raspberry Pi-monitored chemical reactor.

The chemical reactor

Attached to a glass jar of approximate 80ml volume (the size is not critical) are two drinking straws, of which one houses a white LED (light-emitting diode) and the other a LDR (light-dependent resistor). The jar is covered in black tape to minimise intrusion of ambient light. The reactor is shown in Figure 1, along with details of other electrical components and connection instructions to a Raspberry Pi.

Figure 1
A: Reactor covered in black tape
B: Drinking straw attached to the reactor, with a further straw inserted housing a white LED
C: Drinking straw attached to the reactor, with a further straw inserted housing a LDR
D: 220Ω resistor to connect to the LED and GPIO 23
E: Wire to connect to ground
F: Wire to connect to 3.3v supply
G: 1µF capacitor to connect to ground
H: Crocodile clip to connect to GPIO 27 (NB: the other end of the wire is situated in between the capacitor and the LDR)

Results

The Python code shown in Figure 2 should be run prior to addition of chemicals to the reactor. Instructions appear on the screen to prompt chemical additions and to start data collection.

Figure 2: Python code for the chemical reactor

Figure 3 shows the results from the experiment when 25ml 0.1M hydrochloric acid is reacted with 25ml 0.15M sodium thiosulphate at 20°C. The reaction is complete at the time the light transmission first reads 0, (i.e. complete obscuration of the light by the precipitate formation) — in this example, that time is 45.4s. For more advanced students, tangents can be drawn at various points on the curve, and gradients calculated to determine the maximum rate of reaction from various reaction conditions.

Figure 3: Graph showing the change in light transmission with time

Download Hello World for free

Download your free copy of Hello World issue 7 today from the Hello World website, where you’ll also find all previous issues. And if you’re an educator in the UK, you’ll have the chance sign up to receive free hard copies to your door!

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HackSpace magazine 10: build a drone

Post Syndicated from Andrew Gregory original https://www.raspberrypi.org/blog/hackspace-magazine-10-build-a-drone/

If you’re a subscriber to HackSpace magazine you’ll already know all about issue 10. For the rest of you who’ve yet to subscribe, issue 10 is out today!

HackSpace magazine 10 Raspberry Pi Press

Build a drone

Ever since Icarus flew too close to the sun, man has dreamed of flight. Thanks to brushless motors, cheaper batteries than ever before, and smaller, more powerful microcontrollers, pretty much anyone with the right know-how can build their own drone. Discover the crucial steps you need to get right; find the right motors, propellers, and chassis; then get out there while the weather is still good and soar like a PCB eagle.

HackSpace magazine 10 Raspberry Pi Press

Rocket-launching robot

If you prefer to keep your remote-controlled vehicles on the ground, we have an inspiring tale of how one maker combined a miniature strandbeest with our other great obsession (fire, obviously) to create a unique firework launcher. Guy Fawkes would surely be pleased.

HackSpace magazine 10 Raspberry Pi Press

Hardware hacking for the environment

In less frivolous project news, we’re reporting from the Okavango Delta in Botswana, where open hardware, open data, and the hard work of volunteers are giving ecologists more information about this essential wetland region. Makers are bringing science out of labs and classrooms, and putting it into the hands of citizen scientists who want to understand and protect their local environment – that’s something we should be proud of.

HackSpace magazine 10 Raspberry Pi Press

PCBs win prizes

The Hackaday Prize: the Academy Awards of open hardware. Enter your project today and you stand a chance of winning $50,000. The competition is fierce, so before you do, read our interview with Stephen Tranovich. Stephen is the Technical Community Lead at the Hackaday Prize and decides who gets the chance to win the glittering prizes. Learn from their words!

HackSpace magazine 10 Raspberry Pi Press

Food

Our editor Ben loves to eat, so this month he’s been eating lamb kebabs cooked in his home-made tandoor. This ancient cooking method is used all over the Indian subcontinent, and imparts a unique flavour with its combination of heat and steam. Best of all, you can make your own tandoor oven with a Dremel and a few plant pots.

HackSpace magazine 10 Raspberry Pi Press

Tutorials



Add push notifications to your letterbox (so your dog doesn’t eat your new passport), write a game for an Arduino, add a recharging pocket to a bag so you can Instagram on the go, and learn everything there is to know about capacitors. All this and more, in HackSpace magazine issue 10!

Get your copy of HackSpace magazine

If you like the sound of this month’s content, you can find HackSpace magazine in WHSmith, Tesco, Sainsbury’s, and independent newsagents in the UK. If you live in the US, check out your local Barnes & Noble, Fry’s, or Micro Center next week. We’re also shipping to stores in Australia, Hong Kong, Canada, Singapore, Belgium, and Brazil, so be sure to ask your local newsagent whether they’ll be getting HackSpace magazine. And if you’d rather try before you buy, you can always download the free PDF.

Subscribe now

Subscribe now” may not be subtle as a marketing message, but we really think you should. You’ll get the magazine early, plus a lovely physical paper copy, which has really good battery life.

HackSpace magazine 10 Raspberry Pi Press

Oh, and twelve-month print subscribers get an Adafruit Circuit Playground Express loaded with inputs and sensors and ready for your next project. Tempted?

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HackSpace magazine 8: Raspberry Pi <3 Arduino

Post Syndicated from Andrew Gregory original https://www.raspberrypi.org/blog/hackspace-magazine-8/

Arduino is officially brilliant. It’s the perfect companion for your Raspberry Pi, opening up new possibilities for robotics, drones and all sorts of physical computing projects. In HackSpace magazine issue 8  we’re taking a look at what’s going on on planet Arduino, and how it can make our world better.

HackSpace magazine

This little board and its ecosystem are hugely important to the world of digital making. It’s affordable, it’s powerful, and it’s open hardware so you know that if you embed one of these in a project and the company goes bust tomorrow, the hardware will always be viable.

Arduino has helped power a new generation of digital makers, and now with a new team in charge, new boards and new software, it’s ready for the next generation.

Noisy toys

We get to speak to loads of fascinating people, but this month marks the first time we’ve ever met a science busker. Meet Stephen Summers, a former teacher who makes a mess with cornflour, water, and sound waves, all in the name of sharing the joy of physics.

HackSpace magazine

Glass-blowing

While we love messing about with digital technologies, we’re also a big fan of good old-fashioned craft skills. And you can’t get much more old-fashioned than traditional glass-blowing. Join us as we attempt to turn red hot molten glass into a multicoloured object without burning ourselves or setting anything on fire.

Guitar synth

People are endlessly clever, inventive, and all-round brilliant. A fantastic example is Björk, the Icelandic musician whose work defies categorisation. Another is Matt Bradshaw, who has made a synthesiser that you play by strumming six metal strings with a plectrum to complete a circuit. Oh, and named it after Björk. Read all about it and get inspired to do something equally bonkers.

HackSpace magazine

Machine learning

Do you have children? Do they leave the lights on all the time, causing you to shout, “THIS ISN’T BLACKPOOL FLAMING ILLUMINATIONS, YOU KNOW!” Well, now you can replace those children with an Arduino. With a bit of machine learning, the Arduino can train itself to turn the lights on and off at the right time, all the time. Plus they don’t cost as much as human children, so it’s a double win!

Dry ice cream

When the sun comes out in Blighty, it doesn’t hang around for long. So why wait for your domestic fridge to freeze your tasty dairy-based desserts, when you can add some solid carbon dioxide and freeze it in a flash? Follow our tutorial and you too can have tasty treats with the ironically warm glow that comes from using chemicals at -78°C.

HackSpace magazine

And there’s more

We’ve filled the rest of the magazine with a robot orchestra, watch restoration, audio boards for Raspberry Pi, magical colour-changing wearables, and more. Get stuck in!



Get your copy of HackSpace magazine

If you like the sound of this month’s content, you can find HackSpace magazine in WHSmith, Tesco, Sainsbury’s, and independent newsagents in the UK. If you live in the US, check out your local Barnes & Noble, Fry’s, or Micro Center next week. We’re also shipping to stores in Australia, Hong Kong, Canada, Singapore, Belgium, and Brazil, so be sure to ask your local newsagent whether they’ll be getting HackSpace magazine.

And if you can’t get to the shops, fear not: you can subscribe from £4 an issue from our online shop. And if you’d rather try before you buy, you can always download the free PDF. Happy reading, and happy making!

The post HackSpace magazine 8: Raspberry Pi <3 Arduino appeared first on Raspberry Pi.

The Benefits of Side Projects

Post Syndicated from Bozho original https://techblog.bozho.net/the-benefits-of-side-projects/

Side projects are the things you do at home, after work, for your own “entertainment”, or to satisfy your desire to learn new stuff, in case your workplace doesn’t give you that opportunity (or at least not enough of it). Side projects are also a way to build stuff that you think is valuable but not necessarily “commercialisable”. Many side projects are open-sourced sooner or later and some of them contribute to the pool of tools at other people’s disposal.

I’ve outlined one recommendation about side projects before – do them with technologies that are new to you, so that you learn important things that will keep you better positioned in the software world.

But there are more benefits than that – serendipitous benefits, for example. And I’d like to tell some personal stories about that. I’ll focus on a few examples from my list of side projects to show how, through a sort-of butterfly effect, they helped shape my career.

The computoser project, no matter how cool algorithmic music composition, didn’t manage to have much of a long term impact. But it did teach me something apart from niche musical theory – how to read a bulk of scientific papers (mostly computer science) and understand them without being formally trained in the particular field. We’ll see how that was useful later.

Then there was the “State alerts” project – a website that scraped content from public institutions in my country (legislation, legislation proposals, decisions by regulators, new tenders, etc.), made them searchable, and “subscribable” – so that you get notified when a keyword of interest is mentioned in newly proposed legislation, for example. (I obviously subscribed for “information technologies” and “electronic”).

And that project turned out to have a significant impact on the following years. First, I chose a new technology to write it with – Scala. Which turned out to be of great use when I started working at TomTom, and on the 3rd day I was transferred to a Scala project, which was way cooler and much more complex than the original one I was hired for. It was a bit ironic, as my colleagues had just read that “I don’t like Scala” a few weeks earlier, but nevertheless, that was one of the most interesting projects I’ve worked on, and it went on for two years. Had I not known Scala, I’d probably be gone from TomTom much earlier (as the other project was restructured a few times), and I would not have learned many of the scalability, architecture and AWS lessons that I did learn there.

But the very same project had an even more important follow-up. Because if its “civic hacking” flavour, I was invited to join an informal group of developers (later officiated as an NGO) who create tools that are useful for society (something like MySociety.org). That group gathered regularly, discussed both tools and policies, and at some point we put up a list of policy priorities that we wanted to lobby policy makers. One of them was open source for the government, the other one was open data. As a result of our interaction with an interim government, we donated the official open data portal of my country, functioning to this day.

As a result of that, a few months later we got a proposal from the deputy prime minister’s office to “elect” one of the group for an advisor to the cabinet. And we decided that could be me. So I went for it and became advisor to the deputy prime minister. The job has nothing to do with anything one could imagine, and it was challenging and fascinating. We managed to pass legislation, including one that requires open source for custom projects, eID and open data. And all of that would not have been possible without my little side project.

As for my latest side project, LogSentinel – it became my current startup company. And not without help from the previous two mentioned above – the computer science paper reading was of great use when I was navigating the crypto papers landscape, and from the government job I not only gained invaluable legal knowledge, but I also “got” a co-founder.

Some other side projects died without much fanfare, and that’s fine. But the ones above shaped my “story” in a way that would not have been possible otherwise.

And I agree that such serendipitous chain of events could have happened without side projects – I could’ve gotten these opportunities by meeting someone at a bar (unlikely, but who knows). But we, as software engineers, are capable of tilting chance towards us by utilizing our skills. Side projects are our “extracurricular activities”, and they often lead to unpredictable, but rather positive chains of events. They would rarely be the only factor, but they are certainly great at unlocking potential.

The post The Benefits of Side Projects appeared first on Bozho's tech blog.

Puerto Rico’s First Raspberry Pi Educator Workshop

Post Syndicated from Dana Augustin original https://www.raspberrypi.org/blog/puerto-rico-raspberry-pi-workshop/

Earlier this spring, an excited group of STEM educators came together to participate in the first ever Raspberry Pi and Arduino workshop in Puerto Rico.

Their three-day digital making adventure was led by MakerTechPR’s José Rullán and Raspberry Pi Certified Educator Alex Martínez. They ran the event as part of the Robot Makers challenge organized by Yees! and sponsored by Puerto Rico’s Department of Economic Development and Trade to promote entrepreneurial skills within Puerto Rico’s education system.

Over 30 educators attended the workshop, which covered the use of the Raspberry Pi 3 as a computer and digital making resource. The educators received a kit consisting of a Raspberry Pi 3 with an Explorer HAT Pro and an Arduino Uno. At the end of the workshop, the educators were able to keep the kit as a demonstration unit for their classrooms. They were enthusiastic to learn new concepts and immerse themselves in the world of physical computing.

In their first session, the educators were introduced to the Raspberry Pi as an affordable technology for robotic clubs. In their second session, they explored physical computing and the coding languages needed to control the Explorer HAT Pro. They started off coding with Scratch, with which some educators had experience, and ended with controlling the GPIO pins with Python. In the final session, they learned how to develop applications using the powerful combination of Arduino and Raspberry Pi for robotics projects. This gave them a better understanding of how they could engage their students in physical computing.

“The Raspberry Pi ecosystem is the perfect solution in the classroom because to us it is very resourceful and accessible.” – Alex Martínez

Computer science and robotics courses are important for many schools and teachers in Puerto Rico. The simple idea of programming a microcontroller from a $35 computer increases the chances of more students having access to more technology to create things.

Puerto Rico’s education system has faced enormous challenges after Hurricane Maria, including economic collapse and the government’s closure of many schools due to the exodus of families from the island. By attending training like this workshop, educators in Puerto Rico are becoming more experienced in fields like robotics in particular, which are key for 21st-century skills and learning. This, in turn, can lead to more educational opportunities, and hopefully the reopening of more schools on the island.

“We find it imperative that our children be taught STEM disciplines and skills. Our goal is to continue this work of spreading digital making and computer science using the Raspberry Pi around Puerto Rico. We want our children to have the best education possible.” – Alex Martínez

After attending Picademy in 2016, Alex has integrated the Raspberry Pi Foundation’s online resources into his classroom. He has also taught small workshops around the island and in the local Puerto Rican makerspace community. José is an electrical engineer, entrepreneur, educator and hobbyist who enjoys learning to use technology and sharing his knowledge through projects and challenges.

The post Puerto Rico’s First Raspberry Pi Educator Workshop appeared first on Raspberry Pi.

Introducing the AWS Machine Learning Competency for Consulting Partners

Post Syndicated from Randall Hunt original https://aws.amazon.com/blogs/aws/introducing-the-aws-machine-learning-competency-for-consulting-partners/

Today I’m excited to announce a new Machine Learning Competency for Consulting Partners in the Amazon Partner Network (APN). This AWS Competency program allows APN Consulting Partners to demonstrate a deep expertise in machine learning on AWS by providing solutions that enable machine learning and data science workflows for their customers. This new AWS Competency is in addition to the Machine Learning comptency for our APN Technology Partners, that we launched at the re:Invent 2017 partner summit.

These APN Consulting Partners help organizations solve their machine learning and data challenges through:

  • Providing data services that help data scientists and machine learning practitioners prepare their enterprise data for training.
  • Platform solutions that provide data scientists and machine learning practitioners with tools to take their data, train models, and make predictions on new data.
  • SaaS and API solutions to enable predictive capabilities within customer applications.

Why work with an AWS Machine Learning Competency Partner?

The AWS Competency Program helps customers find the most qualified partners with deep expertise. AWS Machine Learning Competency Partners undergo a strict validation of their capabilities to demonstrate technical proficiency and proven customer success with AWS machine learning tools.

If you’re an AWS customer interested in machine learning workloads on AWS, check out our AWS Machine Learning launch partners below:

 

Interested in becoming an AWS Machine Learning Competency Partner?

APN Partners with experience in Machine Learning can learn more about becoming an AWS Machine Learning Competency Partner here. To learn more about the benefits of joining the AWS Partner Network, see our APN Partner website.

Thanks to the AWS Partner Team for their help with this post!
Randall

AWS Online Tech Talks – May and Early June 2018

Post Syndicated from Devin Watson original https://aws.amazon.com/blogs/aws/aws-online-tech-talks-may-and-early-june-2018/

AWS Online Tech Talks – May and Early June 2018  

Join us this month to learn about some of the exciting new services and solution best practices at AWS. We also have our first re:Invent 2018 webinar series, “How to re:Invent”. Sign up now to learn more, we look forward to seeing you.

Note – All sessions are free and in Pacific Time.

Tech talks featured this month:

Analytics & Big Data

May 21, 2018 | 11:00 AM – 11:45 AM PT Integrating Amazon Elasticsearch with your DevOps Tooling – Learn how you can easily integrate Amazon Elasticsearch Service into your DevOps tooling and gain valuable insight from your log data.

May 23, 2018 | 11:00 AM – 11:45 AM PTData Warehousing and Data Lake Analytics, Together – Learn how to query data across your data warehouse and data lake without moving data.

May 24, 2018 | 11:00 AM – 11:45 AM PTData Transformation Patterns in AWS – Discover how to perform common data transformations on the AWS Data Lake.

Compute

May 29, 2018 | 01:00 PM – 01:45 PM PT – Creating and Managing a WordPress Website with Amazon Lightsail – Learn about Amazon Lightsail and how you can create, run and manage your WordPress websites with Amazon’s simple compute platform.

May 30, 2018 | 01:00 PM – 01:45 PM PTAccelerating Life Sciences with HPC on AWS – Learn how you can accelerate your Life Sciences research workloads by harnessing the power of high performance computing on AWS.

Containers

May 24, 2018 | 01:00 PM – 01:45 PM PT – Building Microservices with the 12 Factor App Pattern on AWS – Learn best practices for building containerized microservices on AWS, and how traditional software design patterns evolve in the context of containers.

Databases

May 21, 2018 | 01:00 PM – 01:45 PM PTHow to Migrate from Cassandra to Amazon DynamoDB – Get the benefits, best practices and guides on how to migrate your Cassandra databases to Amazon DynamoDB.

May 23, 2018 | 01:00 PM – 01:45 PM PT5 Hacks for Optimizing MySQL in the Cloud – Learn how to optimize your MySQL databases for high availability, performance, and disaster resilience using RDS.

DevOps

May 23, 2018 | 09:00 AM – 09:45 AM PT.NET Serverless Development on AWS – Learn how to build a modern serverless application in .NET Core 2.0.

Enterprise & Hybrid

May 22, 2018 | 11:00 AM – 11:45 AM PTHybrid Cloud Customer Use Cases on AWS – Learn how customers are leveraging AWS hybrid cloud capabilities to easily extend their datacenter capacity, deliver new services and applications, and ensure business continuity and disaster recovery.

IoT

May 31, 2018 | 11:00 AM – 11:45 AM PTUsing AWS IoT for Industrial Applications – Discover how you can quickly onboard your fleet of connected devices, keep them secure, and build predictive analytics with AWS IoT.

Machine Learning

May 22, 2018 | 09:00 AM – 09:45 AM PTUsing Apache Spark with Amazon SageMaker – Discover how to use Apache Spark with Amazon SageMaker for training jobs and application integration.

May 24, 2018 | 09:00 AM – 09:45 AM PTIntroducing AWS DeepLens – Learn how AWS DeepLens provides a new way for developers to learn machine learning by pairing the physical device with a broad set of tutorials, examples, source code, and integration with familiar AWS services.

Management Tools

May 21, 2018 | 09:00 AM – 09:45 AM PTGaining Better Observability of Your VMs with Amazon CloudWatch – Learn how CloudWatch Agent makes it easy for customers like Rackspace to monitor their VMs.

Mobile

May 29, 2018 | 11:00 AM – 11:45 AM PT – Deep Dive on Amazon Pinpoint Segmentation and Endpoint Management – See how segmentation and endpoint management with Amazon Pinpoint can help you target the right audience.

Networking

May 31, 2018 | 09:00 AM – 09:45 AM PTMaking Private Connectivity the New Norm via AWS PrivateLink – See how PrivateLink enables service owners to offer private endpoints to customers outside their company.

Security, Identity, & Compliance

May 30, 2018 | 09:00 AM – 09:45 AM PT – Introducing AWS Certificate Manager Private Certificate Authority (CA) – Learn how AWS Certificate Manager (ACM) Private Certificate Authority (CA), a managed private CA service, helps you easily and securely manage the lifecycle of your private certificates.

June 1, 2018 | 09:00 AM – 09:45 AM PTIntroducing AWS Firewall Manager – Centrally configure and manage AWS WAF rules across your accounts and applications.

Serverless

May 22, 2018 | 01:00 PM – 01:45 PM PTBuilding API-Driven Microservices with Amazon API Gateway – Learn how to build a secure, scalable API for your application in our tech talk about API-driven microservices.

Storage

May 30, 2018 | 11:00 AM – 11:45 AM PTAccelerate Productivity by Computing at the Edge – Learn how AWS Snowball Edge support for compute instances helps accelerate data transfers, execute custom applications, and reduce overall storage costs.

June 1, 2018 | 11:00 AM – 11:45 AM PTLearn to Build a Cloud-Scale Website Powered by Amazon EFS – Technical deep dive where you’ll learn tips and tricks for integrating WordPress, Drupal and Magento with Amazon EFS.

 

 

 

 

Hello World Issue 5: Engineering

Post Syndicated from Russell Barnes original https://www.raspberrypi.org/blog/hello-world-issue-5/

Join us as we celebrate the Year of Engineering in the newest issue of Hello World, our magazine for computing and digital making educators.

 

Inspiring future engineers

We’ve brought together a wide range of experts to share their ideas and advice on how to bring engineering to your classroom — read issue 5 to find out the best ways to inspire the next generation.



Plus we’ve got plenty on GP and Scratch, we answer your latest questions, and we bring you our usual collection of useful features, guides, and lesson plans.

Highlights of issue 5 include:

  • The bluffers’ guide to putting together a tech-themed school trip
  • Inclusion, and coding for the visually impaired
  • Getting students interested in databases
  • Why copying may not always be a bad thing

How to get Hello World #5

Hello World is available as a free download under a Creative Commons license for everyone in world who is interested in computer science and digital making education. Get the latest issue as a PDF file straight from the Hello World website.

We’re currently offering free print copies of the magazine to serving educators in the UK. This offer is open to teachers, Code Club and CoderDojo volunteers, teaching assistants, teacher trainers, and others who help children and young people learn about computing and digital making. Subscribe to have your free print magazine posted directly to your home, or subscribe digitally — 20000 educators have already signed up to receive theirs!

Get in touch!

You could write for us about your experiences as an educator, and share your advice with the community. Wherever you are in the world, get in touch by emailing our editorial team about your article idea — we would love to hear from you!

Hello World magazine is a collaboration between the Raspberry Pi Foundation and Computing At School, which is part of the British Computing Society.

The post Hello World Issue 5: Engineering appeared first on Raspberry Pi.

The intersection of Customer Engagement and Data Science

Post Syndicated from Brent Meyer original https://aws.amazon.com/blogs/messaging-and-targeting/the-intersection-of-customer-engagement-and-data-science/

On the Messaging and Targeting team, we’re constantly inspired by the new and novel ways that customers use our services. For example, last year we took an in-depth look at a customer who built a fully featured email marketing platform based on Amazon SES and other AWS Services.

This week, our friends on the AWS Machine Learning team published a blog post that brings together the worlds of data science and customer engagement. Their solution uses Amazon SageMaker (a platform for building and deploying machine learning models) to create a system that makes purchasing predictions based on customers’ past behaviors. It then uses Amazon Pinpoint to send campaigns to customers based on these predictions.

The blog post is an interesting read that includes a primer on the process of creating a useful Machine Learning solution. It then goes in-depth, discussing the real-world considerations that are involved in implementing the solution.

Take a look at their post, Amazon Pinpoint campaigns driven by machine learning on Amazon SageMaker, on the AWS Machine Learning Blog.