Daily Archives: 1. November 2020
Germany hopes to make Australia one of its hydrogen suppliers
This sounds every bit as inefficient as the UK importing wood pellets from North America on an industrial scale, to generate electricity. How the hydrogen might be sent across the world in a ‘green’ way is not mentioned.
– – –
A bilateral agreement aimed at increasing German imports of hydrogen produced from solar power plants in Australia could set a milestone in efforts to establish a global hydrogen market, says Euractiv.
Australia said it wants to become “a powerhouse in hydrogen production and exports” after signing what it described as “a landmark agreement” with Germany on 11 September.
The agreement initiated a joint feasibility study that will look into establishing a green hydrogen supply chain between the two countries.
Australia’s partnership with Germany came in addition to similar deals on green hydrogen made with other countries like Japan, South Korea and Singapore, the Australian trade minister said in a statement.
Addressing a webinar on the subject last month, moderated by EURACTIV, Lynette Wood, the Australian ambassador to Germany, said: “It is our ambition to become a global leader in hydrogen production”.
Over time, the European Union is expected to play its part by introducing a certification scheme that could serve as a basis for trading green hydrogen on a global scale.
“We want to work with Germany and the European Union” to develop a global hydrogen market, Wood told the webinar, organised on 14 September by the Australian embassy in Germany.
Germany is eyeing massive imports of green hydrogen produced from places like Australia, Africa or the Middle East.
Seen from Berlin, these countries have vast untapped potential for solar power which could be fed into electrolysers producing “green” hydrogen made from renewables.
“We are only at the beginning of a very long road,” said Dr Hinrich Thölken, deputy director-general for energy and climate policy at the German Federal Foreign Office, who spoke at the webinar.
Reaching climate neutrality by 2050 – the EU’s stated goal – requires decarbonising the entire economy, including sectors such as cement, chemicals and heavy-duty transport, which are hard to electrify and could use hydrogen as a clean alternative, Thölken pointed out.
This is why “we are convinced that green hydrogen will play a crucial role in achieving our goals,” he told participants at the webinar.
Full article here.
via Tallbloke’s Talkshop
November 1, 2020 at 01:42PM
44,000 SCIENTISTS, PUBLIC HEALTH EXPERTS, AND CLINICIANS SIGN A DECLARATION THAT STATES LOCKDOWNS DON’T WORK
“We’re following the scientific advice,” say western governments as they enforce these, their second nationwide lockdowns in fewer than 8 months. Well, the science has now definitely advised, but is anyone following…?
At the start of the year, if you asked members of the public “should we implement face masks/lockdowns to fight a particularly nasty strain of flu?”, their answers would generally be along the lines of “of course not” and “I’ll accept the risk”. Today, however, as the calendar flips to November, the results of a highly effective brainwashing campaign are on show, and a-scared-out-of-their-wits majority are now in full favor of such oppressive, economy-wrecking measures, believing them to be key to their survival despite there being ZERO scientific backing behind them.
These “useful idiots” are even calling for wider and stricter measures. In the UK, for example, school’s aren’t due to close in this latest round of restrictions –enforced on Nov 5– a decision the nation’s teaching unions have evocatively labeled a “deadly mistake”. Such useful idiots have merely been scared, not informed. How do people think the human race has survived thus far? We build immunity against a flu virus, by getting it, no profiteering vaccine required.
Of the 750million people the World Health Organisation says have been infected by the virus to date, almost none have been reinfected.
Furthermore, although COVID-19 is new, coronavirus strains are not. What is never pointed out is that many who have been infected by other coronaviruses in the past have successfully built an immunity to closely related ones, such as COVID-19. Multiple research groups in Europe and the US have shown that around 30% of the population was already immune to COVID-19 before the virus even arrived — a fact that government advisors continue to ignore. In the UK, that equates to more than 20million people. Adding to this, the latest data reveals that 33.5% of the population has already been infected by COVID-19. And once you then factor in that a tenth of the UK population is aged ten or under (and so therefore largely invulnerable), that leaves about 26.5% of people who are actually susceptible to being infected: “That’s a far cry from [the UK gov’s] current prediction of 93%,” writes Dr. Mike Yeadon, who has a degree in biochemistry and toxicology and a research-based PhD in respiratory pharmacology.
Dr. Yeadon goes on to contextualize the UK’s death toll, writing that the pandemic is being presented as “the biggest public health emergency in decades, when in fact mortality in 2020 so far ranks eighth out of the last 27 years. The death rate at present is also normal for the time of year — the number of respiratory deaths is actually low for late October,” he points out.
So, not only not only is this virus less dangerous than we are being led to believe, with almost three quarters of the population at no risk of infection, we’re actually very close to achieving herd immunity.
The science has spoken
Echoing this reality is the Great Barrington Declaration, co-authored by three professors from Oxford, Harvard and Stanford universities — dismissed as ‘emphatically false’ by UK politicians, yet signed by more then 44,000 scientists, public health experts, and clinicians so far, including Nobel Prize winner Dr Michael Levitt.
The declaration states: “Current lockdown policies are producing devastating effects on short and long-term public health. The results (to name a few) include lower childhood vaccination rates, worsening cardiovascular disease outcomes, fewer cancer screenings and deteriorating mental health – leading to greater excess mortality in years to come, with the working class and younger members of society carrying the heaviest burden. Keeping students out of school is a grave injustice. Keeping these measures in place until a vaccine is available will cause irreparable damage, with the underprivileged disproportionately harmed.“
The scientists point out that vulnerability to death from COVID-19 is more than a thousand-fold higher in the old and infirm than the young: “Indeed, for children, COVID-19 is less dangerous than many other harms, including influenza.
“As immunity builds in the population, the risk of infection to all – including the vulnerable – falls. We know that all populations will eventually reach herd immunity – i.e. the point at which the rate of new infections is stable – and that this can be assisted by (but is not dependent upon) a vaccine. Our goal should therefore be to minimize mortality and social harm until we reach herd immunity. The most compassionate approach that balances the risks and benefits of reaching herd immunity, is to allow those who are at minimal risk of death to live their lives normally to build up immunity to the virus through natural infection, while better protecting those who are at highest risk.”
The eminent scientists call this approach “Focused Protection”.
I urge you to read their declaration in full, here.
Governments are ignoring a formidable collective of respected scientific opinion and relying instead on their own deified, yet utterly incompetent advisers–advisers caught in the headlights, and too spineless to stand up for what’s right. In the words of Dr. Yeadon, “I have no confidence in Sage (the UK Gov’s advisory body) – and neither should you – and I fear that, yet again, they’re about to force further decisions that we will look back on with deep regret.”
The post 44,000 Scientists, Public Health Experts, and Clinicians sign a Declaration that states Lockdowns don’t work appeared first on Electroverse.
via ELECTROVERSE
Eta a Hurricane Threat to Central America
11/1/2020 South Haven 10-14 ft Waves Gale Warning
Trump leads Biden in Iowa 48% to 41%.
MSN headline downplays Trump’s 7-point lead, saying only that “Trump gains ground over Biden in Iowa.”
I’ll give MSN a small amount of credit, though, because the first paragraph in the article does admit that President Trump is “leading Democratic nominee Joe Biden by 7 points.”
The article refers to a new Iowa Poll released Saturday night by the Des Moines Register/Mediacom, saying that Trump leads Biden 48% to 41%.”
The poll also showed Sen. Joni Ernst leading her Democratic challenger 46% to 42%.
Perhaps common sense will triumph after all.
See entire article:
https://www.msn.com/en-us/news/politics/trump-gains-ground-over-biden-in-iowa-poll-finds-ernst-leads-in-a-tight-senate-race/ar-BB1azYEw?li=BBnbfcL
The post Trump leads Biden in Iowa 48% to 41%. appeared first on Ice Age Now.
via Ice Age Now
November 1, 2020 at 01:26PM
Arctic Sea-Ice Extent Now Greater Than at Nearly Any Time in the Last 10,000 Years
Also, today’s sea surface temperatures are at least 4°C colder than they were just a few thousand years ago, when the Arctic was sea-ice free for all but a couple of months a year.
Three new studies expose the lie that today’s temperatures are the warmest on record.
For years scientists have been using biomarker evidence to reconstruct Arctic sea ice history. According to three new studies, modern (20th-21st century) Arctic sea ice is now at its greatest extent since the Holocene began.
Arctic was “nearly ice free throughout the year”
Scientists (Wu et al., 2020) have determined that from about 14,000 to 8,000 years ago, when CO2 lingered near 250 ppm, the Beaufort Sea (Arctic) was “nearly ice free throughout the year.” Not only was it nearly ice free, it was ~4°C warmer than today in winter.
With CO2 at ~400 ppm, this region is 70-100% ice-covered for all but 1-2 summer months in the modern era.
Glaciers had retreated many km (miles) from their modern positions
Another new study (Allaart et al., 2020) concludes that from around 10,000 to 5,000 years ago, Arctic Svalbard (Wijdefjorden) glaciers had retreated many km further back than their modern positions. And the smaller ice caps had “disappeared” from the region.
Today’s sea surface temperatures are at least 4°C colder than just a few thousand years ago
A third study involving a site northeast of Svalbard (Brice et al., 2020) reveals that today’s sea surface temperatures of “<0°C” are at least 4°C colder than they were just a few thousand years ago, when the Arctic was sea-ice free for all but “a couple of months” every year.
See entire comprehensive article:
https://www.climatedepot.com/2020/10/30/3-more-new-studies-show-modern-arctic-sea-ice-extent-is-greater-than-nearly-any-time-in-the-last-10000-years/
Thanks to Stephen Bird for this link
The post Arctic Sea-Ice Extent Now Greater Than at Nearly Any Time in the Last 10,000 Years appeared first on Ice Age Now.
via Ice Age Now
November 1, 2020 at 12:58PM
Claim: Disease-transmission model forecasts election outcomes
NEWS RELEASE 29-OCT-2020
Election model treats political influence like a contagion
NORTHWESTERN UNIVERSITY
[click view more link to watch video. ~cr]
VIDEO: TO VISUALIZE THE UNCERTAIN NATURE OF ELECTION FORECASTS, THIS VIDEO SHOWS A RANDOM SAMPLE OF 500 OF THE RESEARCHERS’ SIMULATED ELECTIONS. PAUSE THE VIDEO AT ANY TIME TO GET A… view more
CREDIT: NORTHWESTERN UNIVERSITY
- New model treats decided voters as ‘infected’ and undecided voters as ‘susceptible’ to infection
- Democratic and Republican ‘diseases’ propagate through a population, ‘infecting’ undecided voters
- Model introduces the possibility of asymmetric relationships, or influence, among states
- As of today (Oct. 29), the model forecasts a victory for Biden 89.03% of the time
EVANSTON, Ill. — A new election forecasting approach uses mathematical modeling to describe how voters in different states may influence each other during an election year.
To simulate how interactions between voters may play a role in the upcoming presidential, gubernatorial and senatorial elections, a Northwestern University research team is adapting a model that is commonly used to study infectious diseases.
The model treats decided voters as “infected” and undecided voters as “susceptible” to infection. Two “diseases” (namely, Democratic and Republican voting inclinations) propagate through a population, “infecting” (or influencing) undecided individuals.
“Experts like the team at FiveThirtyEight account for the fact that, if you misidentify how Pennsylvania will vote, then you might also misidentify how Ohio will vote because those states have some similar features,” said Northwestern’s Alexandria Volkening, who leads the research. “Such symmetric relationships between states are important. Using a disease-transmission model, we also introduce the possibility of asymmetric relationships, or influence. For example, a candidate campaigning in Florida might be featured in the news in Ohio and influence the voters there.”
The research published online yesterday in SIAM Review. Viewers can follow the 2020 forecast here.
Volkening is an NSF-Simons Fellow in Northwestern’s NSF-Simons Center for Quantitative Biology and in the McCormick School of Engineering’s Department of Engineering Sciences and Applied Mathematics. The paper’s coauthors are Daniel Linder of Augusta University, Mason Porter of UCLA and Grzegorz Rempala of The Ohio State University. Their 2020 forecasts are in collaboration with Volkening’s students (Samuel Chian, William He and Christopher Lee), who are undergraduates in the McCormick School of Engineering.
The project began when Volkening and her coauthors aimed to better understand election forecasting.
“My background is not in election forecasting,” said Volkening, who often applies math to biological questions. “But I’m interested in problems in complex systems, where individuals come together to create group dynamics. Mathematical models can be used to describe the behavior of cells in developmental-biology applications and the interactions of voters leading up to elections.”
Volkening and her team wanted to use a data-driven, mathematical modeling approach. They settled on adapting a so-called “susceptible-infected-susceptible” compartmental model that is typically used to study the propagation of illnesses such as the flu.
By adapting this model to account for two “diseases” (Democratic and Republican voting inclinations), the researchers simulated how decided voters may influence undecided voters. A Republican voter speaking to an undecided voter, for example, may influence them to become Republican. In another scenario, former Vice President Joe Biden could attend a campaign event that influences undecided voters.
“In the future, we may be able to tease out how states are influencing each other and pinpoint more influential states,” Volkening said. “We’d like to explore how interactions among states change over time.”
To generate each of their 2020 forecasts, the researchers use polling data from FiveThirtyEight to simulate 10,000 potential election outcomes. At the time of this article, the model forecasts a victory for Biden 89.03% of the time, and a victory for President Donald Trump 10.78% of the time.
“It’s been exciting to run the model continuously over time,” said He, a sophomore studying applied mathematics and statistics. “We don’t just have a single forecast. We update our website regularly, so we can track how opinions are changing.”
Although 89% may sound like Biden has a high chance of winning the election, Volkening is quick to point out that voter turnout and undecided voters could change this.
“In many states, the margin of victory that we are forecasting for Biden is lower than the percentage of undecided voters,” she said. “If undecided voters turn out strongly for Trump, we could certainly see a Republican outcome.”
###
The paper, “Forecasting elections using compartmental models of infection,” was supported by the Mathematical Biosciences Institute, the National Science Foundation (grant numbers DMS-1440386, DMS-1853587 and DMS-1764421) and the Simons Foundation (grant number 597491-RWC). The students’ research has been supported by Northwestern’s Office of Undergraduate Research and NSF DMS-1547394.
More news at Northwestern Now
Find experts on our Faculty Experts Hub
Follow @NUSources for expert perspectives
via Watts Up With That?
November 1, 2020 at 12:49PM
WHAT TIMES DO WE LIVE IN ? POLE SHIFT GRAND SOLAR MINIMUM CLIMATE CHANGE
Claim: Disease-transmission model forecasts election outcomes
Charles Rotter / 1 hour ago November 1, 2020
NEWS RELEASE 29-OCT-2020
Election model treats political influence like a contagion
NORTHWESTERN UNIVERSITY
[click view more link to watch video. ~cr]
VIDEO: TO VISUALIZE THE UNCERTAIN NATURE OF ELECTION FORECASTS, THIS VIDEO SHOWS A RANDOM SAMPLE OF 500 OF THE RESEARCHERS’ SIMULATED ELECTIONS. PAUSE THE VIDEO AT ANY TIME TO GET A… view more
CREDIT: NORTHWESTERN UNIVERSITY
- New model treats decided voters as ‘infected’ and undecided voters as ‘susceptible’ to infection
- Democratic and Republican ‘diseases’ propagate through a population, ‘infecting’ undecided voters
- Model introduces the possibility of asymmetric relationships, or influence, among states
- As of today (Oct. 29), the model forecasts a victory for Biden 89.03% of the time
EVANSTON, Ill. — A new election forecasting approach uses mathematical modeling to describe how voters in different states may influence each other during an election year.
To simulate how interactions between voters may play a role in the upcoming presidential, gubernatorial and senatorial elections, a Northwestern University research team is adapting a model that is commonly used to study infectious diseases.
The model treats decided voters as “infected” and undecided voters as “susceptible” to infection. Two “diseases” (namely, Democratic and Republican voting inclinations) propagate through a population, “infecting” (or influencing) undecided individuals.
“Experts like the team at FiveThirtyEight account for the fact that, if you misidentify how Pennsylvania will vote, then you might also misidentify how Ohio will vote because those states have some similar features,” said Northwestern’s Alexandria Volkening, who leads the research. “Such symmetric relationships between states are important. Using a disease-transmission model, we also introduce the possibility of asymmetric relationships, or influence. For example, a candidate campaigning in Florida might be featured in the news in Ohio and influence the voters there.”
The research published online yesterday in SIAM Review. Viewers can follow the 2020 forecast here.
Volkening is an NSF-Simons Fellow in Northwestern’s NSF-Simons Center for Quantitative Biology and in the McCormick School of Engineering’s Department of Engineering Sciences and Applied Mathematics. The paper’s coauthors are Daniel Linder of Augusta University, Mason Porter of UCLA and Grzegorz Rempala of The Ohio State University. Their 2020 forecasts are in collaboration with Volkening’s students (Samuel Chian, William He and Christopher Lee), who are undergraduates in the McCormick School of Engineering.
The project began when Volkening and her coauthors aimed to better understand election forecasting.
“My background is not in election forecasting,” said Volkening, who often applies math to biological questions. “But I’m interested in problems in complex systems, where individuals come together to create group dynamics. Mathematical models can be used to describe the behavior of cells in developmental-biology applications and the interactions of voters leading up to elections.”
Volkening and her team wanted to use a data-driven, mathematical modeling approach. They settled on adapting a so-called “susceptible-infected-susceptible” compartmental model that is typically used to study the propagation of illnesses such as the flu.
By adapting this model to account for two “diseases” (Democratic and Republican voting inclinations), the researchers simulated how decided voters may influence undecided voters. A Republican voter speaking to an undecided voter, for example, may influence them to become Republican. In another scenario, former Vice President Joe Biden could attend a campaign event that influences undecided voters.
“In the future, we may be able to tease out how states are influencing each other and pinpoint more influential states,” Volkening said. “We’d like to explore how interactions among states change over time.”
To generate each of their 2020 forecasts, the researchers use polling data from FiveThirtyEight to simulate 10,000 potential election outcomes. At the time of this article, the model forecasts a victory for Biden 89.03% of the time, and a victory for President Donald Trump 10.78% of the time.
“It’s been exciting to run the model continuously over time,” said He, a sophomore studying applied mathematics and statistics. “We don’t just have a single forecast. We update our website regularly, so we can track how opinions are changing.”
Although 89% may sound like Biden has a high chance of winning the election, Volkening is quick to point out that voter turnout and undecided voters could change this.
“In many states, the margin of victory that we are forecasting for Biden is lower than the percentage of undecided voters,” she said. “If undecided voters turn out strongly for Trump, we could certainly see a Republican outcome.”
###
The paper, “Forecasting elections using compartmental models of infection,” was supported by the Mathematical Biosciences Institute, the National Science Foundation (grant numbers DMS-1440386, DMS-1853587 and DMS-1764421) and the Simons Foundation (grant number 597491-RWC). The students’ research has been supported by Northwestern’s Office of Undergraduate Research and NSF DMS-1547394.
More news at Northwestern Now
Find experts on our Faculty Experts Hub
Follow @NUSources for expert perspectives
Charles Rotter / November 1, 2020