Simone De Beauvoir’s tragic lesbian love story is finally published

By Agence France-Presse

Simone de Beauvoir STF AFP:File


A tragic love story that Simone de Beauvoir thought “too intimate” to publish during her lifetime will finally see the light of day Wednesday, 34 years after her death.

The great feminist writer recounts her teenage crush for another girl in “Les Inseparables”, the story of a “passionate and tragic friendship between two rebellious young girls.”

But de Beauvoir put the deeply autobiographical novel into a bottom drawer after her partner Jean-Paul Sartre “held his nose” when he read it.

The author of “The Second Sex” wrote how she became “instantly charmed by her new classmate”, Elisabeth “Zaza” Lacoin, who died of encephalitis at the age of 21.

“From the day I met you,” she wrote, “you were everything for me.”

In the novel, the de Beauvoir character does “her all in order to make Andree (a thinly-disguised Zaza) love her back,” said the 2Seas literary agency, who handled the foreign rights for the book.

Described as “moving, gripping coming-of-age novel” that “outlines Simone de Beauvoir’s personal battle against the conventional expectations”, de Beauvoir finished it in 1954, five years after her feminist masterpiece was published.

It’s theme of “the friendship between two young women struggling against conventional ideas of what a woman should be in early 20th-century Paris” echoed “The Second Sex”.

The book’s English publishers, Vintage, said the two girls were expected to be “devout, obedient and obliged from a young age to set aside her own interests and passions” for the men in their lives.

– Unrequited passion –

The writer went on to have several other relationships with women, some of whom were also Sartre’s lovers.

De Beauvoir first evoked her relationship with Zaza in her “Memoirs of a Dutiful Daughter”.

The two were so close during World War I and the 1920s that fellow students and teachers at their school called them the “inseparables”.

Zaza’s relationship with the communist philosopher Maurice Merleau-Ponty, whom she had met through de Beauvoir, scandalised her traditionalist Catholic family.

He appears as a charismatic student in the story, and one of his classmates was none other than Sartre.

The pair quarrelled and then permanently fell out over Soviet communism around the time the novel was written.

By then the object of de Beauvoir’s unrequited love was long dead.

Some have questioned whether Sartre’s rift with Merleau-Ponty may have also played a part in de Beauvoir putting the book to one side.

“It is said that it was Jean-Paul Sartre himself who advised De Beauvoir not to publish the novel, considering it of little interest,” the philosopher Paul B. Preciado wrote in the French daily Liberation.

But Sylvie Le Bon de Beauvoir, the writer’s adopted daughter, thinks that it was she herself who finally renounced it despite several rewrites.

In the preface to the book — which will be published in English next year — she argued that de Beauvoir found “the final fictional transcription of [her love for Zaza] unsatisfying”.

© 2020 AFP

AIR-Act2Act: A dataset for training social robots to interact with the elderly

by Ingrid Fadelli , Tech Xplore

Three of the interaction scenarios considered by the researchers, which were recorded using Kinect sensors and included in the AIR-Act2Act dataset. Fig. 2(b) Credit: Ko et al.

To interact with humans and assist them in their day-to-day life, robots should have both verbal and non-verbal communication capabilities. In other words, they should be able to understand both what a user is saying and what their behavior indicates, adapting their speech, behavior and actions accordingly.

To teach social robots to interact with humans, roboticists need to train them on datasets containing human-human verbal and non-verbal interactions. Compiling these datasets can be quite time consuming, hence are currently fairly scarce and are not always suitable for training robots to interact with specific segments of the population, such as children or the elderly.

To facilitate the development of robots that can best assist the elderly, researchers at the Electronics and Telecommunications Research Institute (ETRI) in South Korea recently created AIR-Act2Act, a dataset that can be used to teach robots non-verbal social behaviors. The new dataset was compiled as part of a broader project called AIR (AI for Robots), aimed at developing robots that can help older adults throughout their daily activities.

"Social robots can be great companions for lonely elderly people," Woo-Ri Ko, one of the researchers who carried out the study, told TechXplore. "To do this, however, robots should be able to understand the behavior of the elderly, infer their intentions, and respond appropriately. Machine learning is one way to implement this intelligence. Since it provides the ability to learn and improve automatically from experience, it can also allow robots to learn social skills by observing natural interactions between humans."

Ko and her colleagues were the first to record interactions between younger and older (i.e., senior) adults with the purpose of training social robots. The dataset they compiled contains over 5000 interactions, each with associated depth maps, body indexes and 3-D skeletal data of the interacting individuals.

One of the interaction scenarios considered by the researchers, which was recorded using Kinect sensors and included in the AIR-Act2Act dataset. Fig. 3. Credit: Ko et al.

"AIR-Act2Act dataset is the only dataset up to date that specifically contains interactions with the elderly," Ko said. "We recruited 100 elderly people and two college students to perform 10 interactions in indoor environments and recorded data during these interactions. We also captured depth maps, body indexes and 3-D skeletal data of participants as they interacted with each other, using three Microsoft Kinect v2 cameras."

At a later stage, the researchers manually analyzed and refined the skeletal data they collected to identify instances in which the Kinect sensor did not track movements properly. This incorrect data was then adjusted or removed from the dataset.

Unlike other existing datasets for training social robots, AIR-Act2Act also contains representations of the movements that should be emulated or learned by a robot. More specifically, Ko and her colleagues calculated the actions that a humanoid robot called NAO would need to perform based on its joint angles to emulate the non-verbal behavior of human participants interacting in their data samples.

"Previous research used human-human interaction datasets to generate two social behaviors: handshakes and waiting," Ko said. "However, larger datasets were essential to generate more diverse behavior. We hope that our large-scale dataset will help advance this study further and promote related research."

Ko and her colleagues published AIR-Act2Act on GitHub, along with a series of useful python scripts, so it can now be easily accessed by other developers worldwide. In the future, their dataset could enable the development of more advanced and responsive humanoid robots for assisting the elderly that would be able to reproduce human non-verbal social behaviors.

"We are now conducting research exploring end-to-end learning-based social behavior generation using our dataset," Ko said. "We have already achieved promising results, which will be presented at the SMC 2020 conference. In the future, we plan to further expand on this research."

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Explore further

End-to-end learning of co-speech gesture generation for humanoid robots

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More information: Ko et. al., AIR-Act2Act: Human-human interaction dataset for teaching non-verbal social behaviors to robots. arXiv:2009.02041 [cs.RO]. arxiv.org/abs/2009.02041

© 2020 Science X Network

Can the voice of healthcare robots influence how they are perceived by humans?

by Ingrid Fadelli , Tech Xplore

Healthbot, a Healthcare robot developed at The University of Auckland. In the image a user is interacting with Healthbot using a touch screen. (Credit: Centre for Automation and Robotic Engineering Science, University of Auckland)

Robots are gradually making their way into hospitals and other clinical facilities, providing basic assistance to doctors and patients. To facilitate their widespread use in health care settings, however, robotics researchers need to ensure that users feel at ease with robots and accept the help they can offer. This could potentially be achieved by developing robots that communicate in empathetic and compassionate ways.


With this in mind, researchers at the University of Auckland and Singapore University of Technology & Design have been using speech synthesis techniques to create robots that sound more empathetic. In a recent paper published in the International Journal of Social Robotics, they presented the results of an experiment exploring the effects of using an empathetic synthesized voice on users' perception of robots.

"Our recent study is based on approximately three years of research aimed at developing a synthetic voice for health care robots," Jesin James, one of the researchers who carried out the study told TechXplore. "Past studies have shown that the type of synthesized voice used by robots can impact how users perceive them, which can encourage or discourage users from initiating interactions."

The speech research group at the University of Auckland and the Center for Automation and Robotic Engineering Science have been trying to develop health care robots that can assist people in care homes for several years now. Recently, they have been focusing their efforts on trying to identify voices that could make robots more acceptable in the eyes of humans they interact with.

"A lot of research and development efforts in robotics focus on broadening the capabilities of robots," James explained. "However, users may be entirely discouraged from using robots if they perceive a lack of reciprocal empathy. We felt that a robot's voice plays an important role in how people perceive it, which is what ultimately inspired us to carry out our recent study."

A participant taking part in the perception test carried out by the researchers. (Credit: James et al.)

First, James and her colleagues tested the hypothesis that a robot's voice can impact how users perceive it by conducting a simple experiment using a robot called Healthbot. The robot's voice was that of a professional voice artist, who was recorded while reading dialogs in two tone variations: a flat monotone and an empathetic voice.

The researchers recruited 120 participants and asked them to share their perceptions after they had watched videos of Healthbot talking with these two different voices. The vast majority of participants said that they perceived the robot as more empathetic when it spoke using the more empathetic voice. These initial results encouraged the researchers to explore the possibility of producing a synthetic voice that reproduced the empathetic tone used by the professional voice artist.


"Our study had two key objectives," James said. "One was to determine what type of synthesized voice is best for creating a health care robot that is perceived as empathetic. Once we identified it, we tried to use speech synthesis techniques to produce this voice."

When they analyzed the findings of a short pilot study, the researchers realized that the emotions that most influenced whether a human user perceived a voice as empathetic or not were not the primary emotions (i.e., anger, sadness, joy and fear), but more subtle, secondary emotions. These are complex emotions that are often conveyed by the tone of voice of human speakers, which could be, for instance, apologetic, anxious, confident, enthusiastic or worried. This realization inspired James and her colleagues to compile a new dataset of speech recordings conveying these secondary emotions, called JLCorpus.

By analyzing speech samples from this dataset, the team was able to produce a model that outlined the emotional qualities that a synthesized voice should have to be perceived as empathetic by human listeners. This model accounts for characteristics such as pitch, as well as speech rate and intensity. They then produced a synthesized voice that matched the emotional qualities they identified.

Mind map of reasons why participants did not prefer the robotic voice without empathetic emotions, based on the responses given by participants in the perception test. Credit: James et al.

Subsequently, James and her colleagues carried out a second perception test, during which users viewed videos of Healthbot speaking with the synthetized voice they had created and shared their perceptions of the robot.

"In this second perception test, participants saw a video of the health care robot speaking with the synthesized voice and rated the perceived empathy on a five-point scale based on the Motivational Interviewing Treatment Integrity (MITI) module," James said. "This is a five-point scale used to rate a clinician's empathy, and the same scale was used here with modifications done to suit the health care robot."

In the videos that the researchers showed participants, Healthbot had a neutral facial expression and its speech was not accompanied by any particular hand gestures. This means that it could only convey emotions and empathy via its voice. The vast majority of those who took part in the second test said that they perceived the robot as highly empathetic, rating it high on the five-point scale MITI module.

"Our findings suggest that people can perceive empathy from voice alone, without any supporting facial expressions or gestures," James said. "This implies that a robot's voice plays a key role in how humans perceive it. This voice is not just a medium of communicating with humans; it can actually impact their perceptions."

In addition to highlighting the important role that a robot's voice plays in how humans perceive it, the recent study carried out by James and her colleagues shows that subtle, secondary emotions are what ultimately make a voice sound more empathetic. These findings could pave the way towards new studies exploring secondary emotions, which have so far been seldomly investigated.

Mind map of reasons why participants did not prefer the robotic voice without empathetic emotions, based on the responses given by participants in the perception test. Credit: James et al.

"These emotions are subtle in nature, can be culture-specific and are sometimes difficult to define and reproduce, but this is the exciting part about analyzing them," James said. "We are not exactly sure about what we could find and that makes it all the more interesting. There is a lack of resources and databases to study secondary emotions, so developing these resources would be the next step forward."

In the future, the synthesized voice produced by this team of researchers could be used to create health care robots that sound more empathic and human-like. Meanwhile, the researchers plan to continue exploring how humans convey subtle secondary emotions in speech, so that they can synthesize robot voices that are increasingly convincing and empathetic. They would also like to develop emotion recognition models that can automatically detect these emotions in the voice of human speakers.

"So far, we carried out perception tests using a video of the robot speaking to participants," James said. "We are now conducting perception tests in such a way that participants can actually sit near a physical robot and interact with it. We expect that the presence of the robot near the participants will impact their perception of the robot further."


Explore further Robots could learn to recognise human emotions, study finds

More information: Empathetic speech synthesis and testing for healthcare robots. International Journal of Social Robotics(2020). DOI: 10.1007/s12369-020-00691-4.

Emotional speech corpus: github.com/tli725/JL-Corpus

© 2020 Science X Network

Crabs are key to ecology and economy in Oman

by Royal Netherlands Institute for Sea Research

The most abundant crab in Barr Al Hikman is the sentinel crab Macrophthalmus Sulcatus. Literally billions of these crabs live in the area. It is an essential food source for many shorebirds that winter in Barr Al Hikman. Credit: Jan van de Kam

The intertidal mudflats of Barr Al Hikman, a nature reserve at the south-east coast of the Sultanate of Oman, are crucial nursery grounds for numerous crab species. In return, these crabs are a vital element of the ecology, as well as the regional economy, a new publication in the scientific journal Hydrobiologia shows. "These important functions of the crabs should be considered when looking at the increasing human pressure on this nature reserve," first author and NIOZ-researcher Roeland Bom says.


Blue swimming crab

The mudflats of Barr Al Hikman are home to almost thirty crab species. For his research, Bom, together with colleagues in The Netherlands and at the Sultan Qaboos University in Oman, looked at the ecology of the two most abundant species. Bom notes, "Barr Al Hikman is also home to the blue swimming crab Portunus segnis. That is the species caught by local fishermen. This crab uses the mudflats of Barr Al Hikman as nursery grounds."

The counts of Bom and his colleagues show, that there are millions and millions of these crabs in Barr Al Hikman. They are food to hundreds of thousands of birds, both migrating species, as well as birds breeding in the area, such as crab plovers. The crabs live in holes in the ground. They forage on the seagrass beds that are still abundant in Barr Al Hikman. "Apart from the high primary production (algae) in Barr al Hikman, this reserve is also well suited for crabs because of the vastness of the area," Bom assumes. "The slopes of the mudflats are very gentle, so at low tide, the crabs have an immense area at their disposition."

Barr Al Hikman is an important nursery ground for Blue Swimming Crab Portunus segnis. This crab provides a major income for local fisheries. Credit: Jan van de Kam

Eco value

The value of the crabs is not just ecological, Bom stresses. "Local fishermen that catch the blue swimming crabs, distribute them not only through Oman, but also through the rest of the Arabian Peninsula and even to Japan. At approximately € 2,- per kilo, these crabs represent an important economic pillar, both under the region around Barr Al Hikman, as well as for the whole of Oman."

Reserve

The protection of the reserve of Barr Al Hikman is limited to national legislation. Efforts to acknowledge this reserve under the international Ramsar-convention were never effectuated. There is, however, increasing human pressure on the mudflats of Barr Al Hikman, the authors describe, that would justify further protection. For example, there are well-developed plans to start shrimp farming around this intertidal area. "When looking at the cost and benefits of these activities, it is important to look at the role of this reserve in the local ecology, as well as in the broader ecology of the many migratory birds that use the area," Bom says. "Moreover, our research shows that the unique ecosystem of Barr Al Hikman plays a key role in the economy as well."


Explore further Blue crab invasion spells doom for Albanian fishermen
More information: Roeland A. Bom et al, The intertidal mudflats of Barr Al Hikman, Sultanate of Oman, as feeding, reproduction and nursery grounds for brachyuran crabs, Hydrobiologia (2020). DOI: 10.1007/s10750-020-04418-4
Journal information: Hydrobiologia


Provided by Royal Netherlands Institute for Sea Research

A home energy management system to achieve optimal control of heat pumps and photovoltaics

by Ingrid Fadelli , Tech Xplore

A screenshot of the interactive JuMP Julia visualization produced by the researchers’ system. Credit: Langer & Volling.

Over the past few decades, researchers worldwide have developed a growing amount of systems that can produce renewable energy, such as solar, wind or hydroelectric energy. While some companies and individuals have already started adopting these technologies, a complete transition to more sustainable energy systems is yet to take place. Tools that simplify the implementation and management of renewable energy systems in both industrial and residential settings could ultimately aid this transition.


With this in mind, researchers at Technische Universität Berlin have recently created an energy management system that is specifically designed to modulate photovoltaic (PV) technology and heat pumps residential environments. This new system, presented in a paper published in Elsevier's Applied Energy journal, was developed using JuMP, a modeling framework for mathematical optimization that is embedded in a programming language called Julia.

"Our main goal was to model a comprehensive optimal home energy management system that does not only include PVs and batteries but also a heat pump and thermal storages, in order to capture the seasonal effects of sector coupling," Lissy Langer, one of the researchers who carried out the study, told TechXplore. "It was especially important for us to also publish the model code under an open license and use the open source optimization framework JuMP, in order to make our research reproducible."

As part of their study, Langer and her colleague Thomas Volling modeled a hypothetical building powered by a modulating air-sourced heat pump, a PV system, a battery and thermal storage systems for both floor heating and hot-water supply. Their model also includes a grid feed system that ensures that any surplus electricity produced by the PV technology is fed into the grid. The grid feed system implemented by the researchers takes the comfort of residents and fixed feed-in tariffs (i.e., financial incentives offered to renewable energy producers) into account.

"The home energy management system we proposed utilizes a classical model predictive control algorithm that derives optimal flows of a building under the assumption of perfect information," Langer said. "Due to the rolling horizon implementation of the system in Julia JuMP, we are able to analyze a whole year with a time resolution of 1h in just a couple of seconds."

The recent study carried out by Langer and her colleagues explores some of the common modeling effects associated with an optimization approach known as 'rolling horizon', which has the potential to improve modeling in energy management systems. In addition, the researchers calculated specific target states of charge that could be used as a reference to enhance rule-based energy management systems that are commonly used today.

In the future, the home energy management system devised by this team of researchers could simplify and promote the implementation of technology for the production of renewable energy in residential sites. The Julia JuMP-based model they developed is open-source and can be easily accessed online, thus it could also serve as a reference for other teams who are trying to develop sustainable energy management systems.

"A subsequent paper currently under review analyzes the effects of market and tariff design in a peer-to-peer market consisting of prosumagers, prosumers and consumers, in instances that involve the use of similar home energy management systems," Langer said. "In our next paper, we also plan to introduce uncertainty into our model and see if a close-to-optimal policy can be achieved using a reinforcement learning approach."


Explore further Intelligent software for district renewable energy management 

More information: An optimal home energy management system for modulating heat pumps and photovoltaic systems. Applied Energy (2020). DOI: 10.1016/j.apenergy.2020.115661.

© 2020 Science X Network

Data show big gains for offshore wind

by National Renewable Energy Laboratory

The U.S. offshore wind project pipeline grew more than 10% between 2018 and 2019. Credit: NREL

Global installed offshore wind capacity reached 27,064 MW in 2019—a 19% increase from the previous year. This and other trends can be found in the "2019 Offshore Wind Technology Data Update," released by NREL on behalf of the U.S. Department of Energy's Wind Energy Technologies Office.

Only one commercial offshore wind farm currently operates in the United States, but NREL's 2019 data show advancing technology, falling prices, and increased federal and state support for the U.S. offshore wind industry. The U.S. offshore wind project pipeline grew 10% by the end of 2019, while the amount of U.S. offshore wind capacity under federal and state permitting with a signed offtake agreement was 6,439 MW—a threefold increase from the previous year.

State investment has been a major driver of offshore wind's growth in the United States. State procurement commitments climbed nearly 10,000 MW between 2018 and 2019, exceeding the capacity potential of the current U.S. pipeline.

"It's stunning how fast state commitments have grown," said NREL Offshore Wind Lead Walt Musial. "These numbers show that the industry is progressing toward real projects that are likely to get built."

Wind Projects Proposed for Deeper Waters, Farther from Shore

Technological advancements helped offshore wind projects operate farther from shore in 2019. The average distance from shore was 47 kilometers (km) for installed projects, and project announcements indicate an increase to 70 km by 2025.

Projects are also being sited in deeper waters, with the capacity-weighted average depth of installed projects at 31 meters. Project announcements indicate that, over the next five years, offshore sites will increase to average depths to 43 meters for projects commencing operation in 2025.

Semisubmersible offshore wind platforms accounted for 89% of substructures in floating wind projects either installed or announced in 2019. Other projects may use spar or tension-leg platform substructures. Credit: Josh Bauer, NREL

"As the industry matures, projects are getting bigger, and they're being sited farther from shore," Musial said. "That means offshore wind projects become less visible from shore, which could make them more easily accepted by the communities they power."

NREL's research found that floating offshore wind—important for tapping deep-water offshore wind resources—has progressed as well, both in the United States and globally. In 2019, Maine's public utility commission approved an updated power purchase agreement (PPA) for the 12-MW Aqua Ventus floating demonstration project, which will help the state develop its predominantly deep-water offshore wind resource and could usher in U.S. commercial floating wind development.


Globally, up to 1,549 MW of floating offshore wind has reached the permitting stage, while the total global pipeline reached 7,663 MW at the end of 2019.

Falling Costs Drive Offshore Development

Industry analyst projections indicate that offshore wind costs will continue to decline globally over the next decade. Costs are anticipated to reach a levelized cost of energy (LCOE) range of $50 to $75 per megawatt-hour (MWh) for fixed-bottom systems by 2030. In the United States, PPAs and offshore renewable energy certificate prices have fallen 40% over the last two years, making offshore wind projects more competitive in these electricity markets.

The information in the "2019 Offshore Wind Technology Data Update" is intended to provide offshore wind policymakers, regulators, developers, researchers, engineers, financiers, supply chain participants, and other stakeholders with up-to-date quantitative information about the offshore wind market, technology, and cost trends in the United States and worldwide.


Explore further Floating wind turbines on the rise
More information: For more information, view slides that display and summarize the "2019 Offshore Wind Technology Data Update" or download a spreadsheet of the data.
Provided by National Renewable Energy Laboratory

Global Privacy Control initiative seeks to give users control over their Internet privacy wishes

by Bob Yirka , Tech Xplore

Credit: Pixabay/CC0 Public Domain

An ensemble of activist groups, tech companies and publishers has banded together to start a new initiative aimed at giving internet users more control over the way their data is used. The group has named the new initiative Global Privacy Control (GPC), and has announced its launch on their web page.


A decade ago, several entities in the tech and privacy sector proposed a feature for web browsers called Do Not Track. It was supposed to force websites to stop tracking user internet activities (which allows for creating targeted ads). Several browser companies implemented the feature, but it never caught on, mainly because website owners ignored it. That, proponents of the new initiative claim, was because they were not legally forced to do so. But that might be changing. Recently, the state of California passed legislation called the California Consumer Privacy Act (CCPA), which gives users in that state the right to demand that their data not be used unless they give their permission. Some European countries have passed similar legislation.

The new GPC initiative is backed and run by a diverse group, including the Washington Post, the Mozilla Foundation, and professors at Georgetown Law School. It is also still in its infancy, so the particulars of how users might go about exerting their possible new rights are still being worked out. On its website, the GPC group suggests that rather than set up a single feature, as was the case with Do Not Track, users should have multiple options. They can cease using Google or Microsoft Edge, for example, and switch to Mozilla or other browsers that offer privacy options. Or they can download and install browser add-ons.

Members of the GPC initiative are also working to pressure more states (and the federal government) to enact legislation similar to what is being done in California. For that to work, though, they will need broad support from the user and technology community. But for now, users who live in California can take advantage of the privacy tools now available and to start asking websites to stop tracking them—and if such sites refuse or ignore them, they can take legal action.


Explore further Firefox unveils major security upgrade: DoH protocol boosts user privacy

More information: Global Privacy Control: globalprivacycontrol.org/

Announcing Global Privacy Control: Making it Easy for Consumers to Exercise Their Privacy Rights: globalprivacycontrol.org/press … elease/20201007.html

© 2020 Science X Network

American duo win Nobel Economics Prize for work on auctions

by Johannes Ledel, With Marc Preel

Paul Milgrom and Robert Wilson have helped invent new auction formats

US economists Paul Milgrom and Robert Wilson won the Nobel Economics Prize on Monday for work on commercial auctions, including for goods and services difficult to sell in traditional ways such as radio frequencies, the Nobel Committee said.

The duo was honoured "for improvements to auction theory and inventions of new auction formats," the jury said.

The Royal Swedish Academy of Sciences noted that the discoveries by Milgrom, 72, and Wilson, 83, "have benefitted sellers, buyers and taxpayers around the world," it said in a statement.

Wilson, a professor at Stanford in the US, was spotlighted for developing a theory for auctions with a common value, "a value which is uncertain beforehand but, in the end, is the same for everyone," according to the academy.

Wilson's work showed why rational bidders tend to bid under their own estimate of the worth due to worries over the "winner's curse," or winning the auction but paying too much.

Milgrom, also at Stanford, then came up with a more general theory of auctions, by analysing bidding strategies in different auction forms.

The academy noted that while "people have always sold things to the highest bidder," societies have also had to allocate "ever more complex objects... such as landing slots and radio frequencies."

"In response, Milgrom and Wilson invented new formats for auctioning off many interrelated objects simultaneously, on behalf of a seller motivated by broad societal benefit rather than maximal revenue," the academy said.

The winners will share the prize sum of 10 million Swedish kronor (about $1.1 million, 950,000 euros).

Speaking to reporters in Stockholm via a telephone link, Wilson said the announcement had been "very happy news," conceding that despite his research focus he himself had "never participated in an auction."
The winners of the Nobel prize for economics, 2016-2020

However, he quickly had to retract his statement. "My wife is pointing out that we bought ski boots on eBay, I guess that was an auction," Wilson said.

Last year the honour went to French-American Esther Duflo, Indian-born Abhijit Banerjee of the US, and American Michael Kremer for their experimental work on alleviating poverty.

Not created by Alfred Nobel

Even if it might be the most prestigious prize an economist can hope to receive, the economics prize has not reached the same status as the awards originally chosen by Alfred Nobel in his 1895 will founding the awards, which included medicine, physics, chemistry, literature and peace.


It was instead created in 1968 through a donation from the Swedish central bank and detractors have thus dubbed it "a false Nobel."

The award closes the 2020 Nobel season, which saw the closely-watched peace prize awarded to the UN's World Food Programme.

Women have been more prevalent than usual this year, with American poet Louise Gluck winning the literature prize.

Frenchwoman Emmanuelle Charpentier and American Jennifer Doudna became the first all-female duo to win a scientific Nobel on Wednesday, clinching the chemistry award for their discovery of the CRISPR-Cas9 DNA snipping "scissors".

While the number of female winners has risen sharply since the turn of the century, they still represent only about one out of every 20 Nobel medals since 1901.

Winners would normally receive their Nobel from King Carl XVI Gustaf at a formal ceremony in Stockholm on December 10, but the pandemic means it has been replaced by a televised ceremony showing the laureates receiving their awards in their home countries.


Explore furtherNobel awards season comes to an end with economics prize

Ancient tiny teeth reveal first mammals lived more like reptiles

by University of Bristol
Long: Scientists countfossilised growthrings in teeth liketree-rings to findout how long theearliest mammalslived.From left to right:reconstruction ofMorganucodon;Morganucodontooth withcementum, thestructure thatlocks tooth rootsto the gum,highlighted ingreen; as it growsnon-stopthroughout life,cementumdeposits everyyear like treerings, highlightedusing colouredarrows; Thesewere turned into3D models tocount 14 years oflife in the shrew-sizedMorganucodon.Short: Scientistscountfossilisedgrowth ringsin teeth liketree-rings tofind out howlong theearliestmammalslived. Credit: Nuria MelisaMoralesGarcia. Morganucodon based on BobNicholls/Palaeocreations 2018 model

Pioneering analysis of 200 million-year-old teeth belonging to the earliest mammals suggests they functioned like their cold-blooded counterparts—reptiles, leading less active but much longer lives.


The research, led by the University of Bristol, UK and University of Helsinki, Finland, published today in Nature Communications, is the first time palaeontologists have been able to study the physiologies of early fossil mammals directly, and turns on its head what was previously believed about our earliest ancestors.

Fossils of teeth, the size of a pinhead, from two of the earliest mammals, Morganucodon and Kuehneotherium, were scanned for the first time using powerful X-rays, shedding new light on the lifespan and evolution of these small mammals, which roamed the earth alongside early dinosaurs and were believed to be warm-blooded by many scientists. This allowed the team to study growth rings in their tooth sockets, deposited every year like tree rings, which could be counted to tell us how long these animals lived. The results indicated a maximum lifespan of up to 14 years—much older than their similarly sized furry successors such as mice and shrews, which tend to only survive a year or two in the wild.

"We made some amazing and very surprising discoveries. It was thought the key characteristics of mammals, including their warm-bloodedness, evolved at around the same time," said lead author Dr. Elis Newham, Research Associate at the University of Bristol, and previously Ph.D. student at the University of Southampton during the time when this study was conducted.

"By contrast, our findings clearly show that, although they had bigger brains and more advanced behaviour, they didn't live fast and die young but led a slower-paced, longer life akin to those of small reptiles, like lizards."

Using advanced imaging technology in this way was the brainchild of Dr. Newham's supervisor Dr. Pam Gill, Senior Research Associate at the University of Bristol and Scientific Associate at the Natural History Museum London, who was determined to get to the root of its potential.

"A colleague, one of the co-authors, had a tooth removed and told me they wanted to get it X-rayed, because it can tell all sorts of things about your life history. That got me wondering whether we could do the same to learn more about ancient mammals," Dr. Gill said.


By scanning the fossilised cementum, the material which locks the tooth roots into their socket in the gum and continues growing throughout life, Dr. Gill hoped the preservation would be clear enough to determine the mammal's lifespan.

To test the theory, an ancient tooth specimen belonging to Morganucodon was sent to Dr. Ian Corfe, from the University of Helsinki and the Geological Survey of Finland, who scanned it using high-powered Synchrotron X-ray radiation.

"To our delight, although the cementum is only a fraction of a millimetre thick, the image from the scan was so clear the rings could literally be counted," Dr. Corfe said.

It marked the start of a six-year international study, which focused on these first mammals, Morganucodon and Kuehneotherium, known from Jurassic rocks in South Wales, UK, dating back nearly 200 million years.

"The little mammals fell into caves and holes in the rock, where their skeletons, including their teeth, fossilised. Thanks to the incredible preservation of these tiny fragments, we were able to examine hundreds of individuals of a species, giving greater confidence in the results than might be expected from fossils so old," Dr. Corfe added.

The journey saw the researchers take some 200 teeth specimens, provided by the Natural History Museum London and University Museum of Zoology Cambridge, to be scanned at the European Synchrotron Radiation Facility and the Swiss Light Source, among the world's brightest X-ray light sources, in France and Switzerland, respectively.

In search of an exciting project, Dr. Newham took this up for the MSc in Palaeobiology at the University of Bristol, and then a Ph.D. at the University of Southampton.

"I was looking for something big to get my teeth into and this more than fitted the bill. The scanning alone took over a week and we ran 24-hour shifts to get it all done. It was an extraordinary experience, and when the images started coming through, we knew we were onto something," Dr. Newham said.

Dr. Newham was the first to analyse the cementum layers and pick up on their huge significance.

"We digitally reconstructed the tooth roots in 3-D and these showed that Morganucodon lived for up to 14 years, and Kuehneotherium for up to nine years. I was dumbfounded as these lifespans were much longer than the one to three years we anticipated for tiny mammals of the same size," Dr. Newham said.

"They were otherwise quite mammal-like in their skeletons, skulls and teeth. They had specialised chewing teeth, relatively large brains and probably had hair, but their long lifespan shows they were living life at more of a reptilian pace than a mammalian one. There is good evidence that the ancestors of mammals began to become increasingly warm-blooded from the Late Permian, more than 270 million years ago, but, even 70 million years later, our ancestors were still functioning more like modern reptiles than mammals"

While their pace-of-life remained reptilian, evidence for an intermediate ability for sustained exercise was found in the bone tissue of these early mammals. As a living tissue, bone contains fat and blood vessels. The diameter of these blood vessels can reveal the maximum possible blood flow available to an animal, critical for activities such as foraging and hunting.

Dr. Newham said: "We found that in the thigh bones of Morganucodon, the blood vessels had flow rates a little higher than in lizards of the same size, but much lower than in modern mammals. This suggests these early mammals were active for longer than small reptiles but could not live the energetic lifestyles of living mammals."


Explore further Jurassic Welsh mammals were picky eaters, study finds

More information: Nature Communications (2020). 

 DOI: 10.1038/s41467-020-18898-4

Journal information: Nature Communications


Provided by University of Bristol

An open access software-based tool for predicting COVID-19 susceptibility in animals

October 12, 2020 by Ashutosh Kumar, Ravi K. Narayan

Figure 1 Predicting susceptibility for SARS-CoV-2 infection using NCBI protein blast tool. Credit: Kumar et al., 2020. Zoo Biology.

The world is currently in the grip of the COVID-19 pandemic. Preventing the spread of COVID-19 from human to wildlife and domestic animals is an immediate concern of medical scientists worldwide. Recently, there have been reports of cats, ferrets, dogs, minks, golden hamsters, rhesus monkeys, tigers and lions testing positive for SARS-CoV-2 RNA. Preventing the spread of COVID-19 in the zoo and wildlife sanctuaries where chances of animal-human contact are higher should be a priority, as disease may threaten many rare and near-extinct animal species. Additionally, the continued presence of the virus in animals can work as a reservoir that can be a potential reason for failure in containment and recurrence of the pandemic.

SARS-CoV-2 infects humans using a cell-surface protein—angiotensin converting enzyme-2 (ACE2). The receptor binding domain (RBD) of SARS-CoV-2 binds to N-terminal end of ACE2, which is a key step for host cell entry of the virus. The animals that have the ACE2 protein sequence similar to humans, specifically for the segment of protein which binds to SARS-CoV-2 RBD, may also become infected with this virus.

Using the open-access NCBI protein database and protein blast tools, our research group, the Etiologically Elusive Disorders Research Network (EEDRN), has devised a two-step bioinformatics-based method for comparing the homology of human ACE2 with that of animal species-specific ACE2 protein sequence. First, we performed a comparative analysis of the variability of hACE2 with that of wildlife and domestic animal species in complete protein sequences. The species that showed significant homology for the complete sequence were selected for further analysis for the second step.

In the second step, we narrowed down our homology search to a sub-range of amino acid residues of human ACE2, which contain conserved hotspots for binding of SARS‐CoV‐2 RBD. The susceptibility for contracting SARS-CoV-2, and the degree of risk of infection for any animal species for which the ACE2 protein sequence is available at NCBI database can be easily calculated online in these two simple steps using open access NCBI protein blast tools.

On the basis of the sequence homology, we predicted the highest susceptibility for hominids (such as chimpanzee, gorilla, and rhesus monkey) and other primates, followed by carnivores, rodents and artiodactyles (ungulates). The risk for contracting the virus showed a distinct evolutionary trend—the closer to humans in evolution, the higher is the risk of infection. We tested our predictions against PCR‐based laboratory testing results for SARS‐CoV‐2 RNA reported in recent literature for animals such as cats, dogs, golden hamster, rhesus monkey, tigers and lions, which showed our results were highly accurate. Our proposed method can be used as a no-cost screening tool for guiding viral RNA testing for domestic and wildlife animals at risk of getting COVID-19, especially at the settings where immediate availability of PCR-based testing facility cannot be assured.

This story is part of Science X Dialog, where researchers can report findings from their published research articles. Visit this page for information about ScienceX Dialog and how to participate.

More information: Kumar A, Pandey SN, Pareek V, Narayan RK, Faiq MA, Kumari C. Predicting susceptibility for SARS‐CoV‐2 infection in domestic and wildlife animals using ACE2 protein sequence homology. Zoo Biology. 2020;1–7. doi.org/10.1002/zoo.21576.

Bio:
Dr. Ashutosh Kumar is an assistant professor and Dr. Ravi K. Narayan is a senior resident doctor, at Department of Anatomy, All India Institute of Medical Sciences (AIIMS), Patna, India.