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World’s tallest wooden skyscraper planned in Tokyo



A Japanese company is planning to build the world’s tallest wooden skyscraper with 90 percent of the building made of wood.

Sumitomo Forestry says its wooden high-rise — dubbed the W350 — will be 350 meters tall and the planned structure will be a hybrid of mostly wood and steel.

The 70-storey building, expected to be built in Tokyo, will comprise of stores, offices, hotels and private homes, the company noted in plans released earlier in February.

Sumitomo Forestry, which notes on its website that “happiness grows from trees,” said it aimed to create environmentally-friendly, timber-utilizing cities which “become forests through increased use of wooden architecture for high-rise buildings.”

Building with wood is still not cheap, however.

Using 185,000 cubic meters of timber, the building is expected to cost around 600 billion Japanese yen ($5.6 billion) which is twice the amount of a conventional high-rise building constructed with current technology.

However, the company believed that those costs would come down as timber became a more-frequently used material: “Going forward, the economic feasibility of the project will be enhanced by reducing costs through technological development.”

Currently the tallest wooden building is 18-storeys high (53 meters) and serves as accommodation for students at the University of British Colombia.

Greenery will feature heavily in the building from Sumitomo Forestry with foliage connecting from the ground to top floors offering “a view of biodiversity in an urban setting.”

The building plans show balconies that continue around all four sides of the building, giving a space “in which people can enjoy fresh outside air, rich natural elements and sunshine filtering through foliage.”

With earthquakes not unusual in Japan, the building will incorporate a structural system composed of braced tubes made from columns, beams and braces “to prevent deformation of the building due to lateral forces such as earthquakes or wind.”

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WHO says Covid vaccines aren’t ‘silver bullets’ and relying entirely on them has hurt nations



Employees store coffins, some marked with “infection risk” as others have “corona” scrawled in chalk, in the mourning hall of the crematorium in Meissen, eastern Germany, on January 13, 2021, amid the new coronavirus COVID-19 pandemic. cremation.

Jens Schlueter | AFP | Getty Images

The World Health Organization said Friday that coronavirus vaccines aren’t “silver bullets” and relying solely on them to fight the pandemic has hurt nations.

Some countries in Europe, Africa and the Americas are seeing spikes in Covid-19 cases “because we are collectively not succeeding at breaking the chains of transmission at the community level or within households,” WHO Director-General Tedros Adhanom Ghebreyesus said during a news conference from the agency’s Geneva headquarters.

With global deaths reaching 2 million and new variants of the virus appearing in multiple countries, world leaders need to do all they can to curb infections “through tried and tested public health measures,” Tedros said. “There is only one way out of this storm and that is to share the tools we have and commit to using them together.”

The coronavirus has infected more than 93.3 million people worldwide and killed at least 2 million since the pandemic began about a year ago, according to data compiled by Johns Hopkins University. The virus continues to accelerate in some regions, with nations reporting that their supply of oxygen for Covid-19 patients is running “dangerously low,” the WHO said.

Some countries, including the U.S., have focused heavily on the use of vaccines to combat their outbreaks. While vaccines are a useful tool, they will not end the pandemic alone, Mike Ryan, executive director of the WHO’s health emergencies program, said at the news conference.

“We warned in 2020 that if we were to rely entirely on vaccines as the only solution, we could lose the very controlled measures that we had at our disposal at the time. And I think to some extent that has come true,” Ryan said, adding the colder seasons and the recent holidays also may have also played a role in the spread of the virus.

“A big portion of the transmission has occurred because we are reducing our physical distancing. … We are not breaking the chains of transmission. The virus is exploiting our lack of tactical commitment,” he added. “We are not doing as well as we could.”

Dr. Bruce Aylward, a senior advisor to the WHO’s director-general, echoed Ryan’s comments, saying, vaccines are not “silver bullets”

“Things can get worse, numbers can go up,” he said. We have vaccines, yes. But we have limited supplies of vaccines that will be rolled out slowly across the world. And vaccines are not perfect. They don’t protect everyone against every situation.”

In the U.S., the pace of vaccinations is going slower than officials had hoped. As of Friday at 6 a.m. ET, more than 31.1 million doses of vaccine had been distributed across the U.S., but just over 12.2 million shots have been administered, according to data compiled by the Centers for Disease Control and Prevention.

Meanwhile, cases are rapidly growing, with the U.S. recording at least 238,800 new Covid-19 cases and at least 3,310 virus-related deaths each day, based on a seven-day average calculated by CNBC using Johns Hopkins data.

On Thursday, President-elect Joe Biden unveiled a sweeping plan to combat the coronavirus pandemic in the United States. While his administration will invest billions in a vaccine campaign, it will also scale up testing, invest in new treatments and work to identify new strains, among other measures.

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Foreign Amazon sites named in U.S. ‘notorious markets’ list for counterfeit goods



Peter Endig | AFP | Getty Images

A handful of Amazon‘s foreign websites were included in the U.S. government’s annual “notorious markets” list due to concerns they host some counterfeit goods.

The United States Trade Representative (USTR) office released its 2020 review of notorious markets on Thursday. The list identifies e-commerce sites and companies that are believed to be facilitating the sale of counterfeit goods, engaging in intellectual property violations or piracy.

Amazon sites in the U.K., Germany, Spain, France and Italy were named in the report. Complainants against the foreign sites alleged that Amazon’s counterfeit removal process is slow, even for companies that are enrolled in its brand protection programs. They also argued that Amazon doesn’t thoroughly vet third-party sellers on its marketplace or make it clear to brands and consumers “who is selling the goods.”

Amazon disputed the trade representative’s report, which didn’t include Amazon’s U.S. site, and pointed to its extensive programs and tools that are designed to stop counterfeiters.

“Including Amazon in this report is the continuation of a personal vendetta against Amazon, and nothing more than a desperate stunt in the final days of this administration,” an Amazon spokesperson told CNBC in a statement. “Amazon does more to fight counterfeit than any other private entity we are aware of.”

Representatives from the USTR didn’t immediately respond to a request for comment.

President Donald Trump has repeatedly been critical of Amazon and its CEO Jeff Bezos during his four-year term. Bezos owns The Washington Post, which Trump has criticized for its unfavorable coverage of his administration. Amazon has also claimed it didn’t win a Pentagon cloud-computing contract, which could be worth as much as $10 billion, as a result of attacks from Trump against the company and Bezos.

Amazon sites were added to the USTR’s notorious markets list for the first time in 2019. The American Apparel & Footwear Association in 2018 urged the trade representative to include some Amazon sites on the list.

Beyond Amazon, other companies named on the list include Chinese e-commerce site Pinduoduo, South American e-commerce company Mercadolibre and file sharing site The Pirate Bay.

Amazon has stepped up its efforts to curtail counterfeits as the third-party marketplace has grown. The marketplace now accounts for more than half of the company’s overall sales and hosts millions of third-party merchants.

While it remains a critical component of Amazon’s business, the marketplace has also faced a number of issues related to the sale of counterfeitunsafe and expired goods. In 2019, Amazon began mentioning counterfeit products as a risk factor in its annual filing.

The company has pursued counterfeiters in court, rolled out various programs to seek and detect sales of counterfeit goods, and in June launched the Counterfeit Crimes Unit, made up of former federal prosecutors, investigators and data analysts, to mine the site for fraudulent activity.

As a result of these and other efforts, 99.9% of pages viewed by customers on the site have never had a valid report of counterfeit, the spokesperson said.

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Facebook builds A.I. to predict likelihood of worsening Covid symptoms



Dr. Dan Ponticiello, 43, and Dr. Gabriel Gomez, 40, intubate a coronavirus disease (COVID-19) patient in the COVID-19 ICU at Providence Mission Hospital in Mission Viejo, California, January 8, 2021.

Lucy Nicholson | Reuters

Artificial intelligence researchers at Facebook claim they have developed software that can predict the likelihood of a Covid patient deteriorating or needing oxygen based on their chest X-rays.

Facebook, which worked with academics at NYU Langone Health’s predictive analytics unit and department of radiology on the research, says that the software could help doctors avoid sending at-risk patients home too early, while also helping hospitals plan for oxygen demand.

The 10 researchers involved in the study — five from Facebook AI Research and five from the NYU School of Medicine — said they have developed three machine-learning “models” in total, that are all slightly different.

One tries to predict patient deterioration based on a single chest X-ray, another does the same with a sequence of X-rays, and a third uses a single X-ray to predict how much supplemental oxygen (if any) a patient might need.

“Our model using sequential chest X-rays can predict up to four days (96 hours) in advance if a patient may need more intensive care solutions, generally outperforming predictions by human experts,” the authors said in a blog post published Friday.

William Moore, a professor of radiology at NYU Langone Health, said in a statement: “We have been able to show that with the use of this AI algorithm, serial chest radiographs can predict the need for escalation of care in patients with Covid-19.”

He added: “As Covid-19 continues to be a major public health issue, the ability to predict a patient’s need for elevation of care — for example, ICU admission — will be essential for hospitals.”

In order to learn how to make predictions, the AI system was fed two datasets of non-Covid patient chest X-rays and a dataset of 26,838 chest X-rays from 4,914 Covid patients.

The researchers said they used an AI technique called “momentum contrast” to train a neural network to extract information from chest X-ray images. A neural network is a computing system vaguely inspired by the human brain that can spot patterns and recognize relationships between vast amounts of data.

The research was published by Facebook this week but experts have already questioned how effective the AI software can be in practice.

“From a machine learning perspective, one would need to study how well this translates to new, unseen data from different hospitals and patient populations,” said Ben Glocker, who researches machine learning for imaging at Imperial College London, via email. “From my skim reading, it appears that all data (training and testing) is coming from the same hospital.”

The Facebook and NYU researchers said: “These models are not products, but rather research solutions, intended to help hospitals in the days and months to come with resource planning. While hospitals have their own unique data sets, they often don’t have the computational power necessary to train deep learning models from scratch.”

“We are open-sourcing our pretrained models (and publishing our results) so that hospitals with limited computational resources can fine-tune the models using their own data,” they added.

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