SCI COMMUN### Astrophysics The team that in 2019 used a global network of radio telescopes to reveal the first image of a black hole has offered a new twist on that iconic view: the same black hole in polarized light. The thin lines spiraling in toward the black hole's shadow (above) show areas of light that differ in their polarization—the direction in which the light waves vibrate. The light, from plasma near the black hole's edge, was polarized by magnetic fields, and so the new image, described last week in The Astrophysical Journal by the Event Horizon Telescope team, indicates their structure. Researchers hope to learn how the fields help accreting black holes funnel matter and energy into jets emanating from their poles. 69% —Percentage of postdoctoral researchers surveyed in October 2020 by the U.S. National Institutes of Health who anticipate the COVID-19 pandemic will negatively affect their careers. For researchers at all levels, the figure was 55%. ### Conservation Despite the antienvironmental policies of its current leadership, Brazil has become the 130th country to ratify the Nagoya Protocol, a part of the Convention on Biological Diversity that lays out measures to protect countries' biodiversity claims, the CBD announced last week. The ratification, first proposed by a previous administration in 2012, had languished until 2019, when rampant deforestation led pro-environment leaders to push for approval. The current government is seen as having consented because the protocol allows nations to impose rules on the international trade in its plant and animal products; by legitimizing the sales, the regulations are expected to increase exports and tax revenues. For example, money from sales of native plants such as açai ( Euterpe oleracea ) and Brazil nut ( Bertholletia excelsa ) could be returned to help Indigenous communities that use and harvest them. Observers question whether the ratification alone will protect Brazil's biodiversity, perhaps the world's greatest—but hailed the step as helpful. ### Public health The United States and 13 other countries this week criticized a report by a World Health Organization panel that had visited China to investigate how the COVID-19 pandemic started. The 300-page document says the most likely cause was a bat coronavirus that infected another, unidentified animal and then moved to humans, but it recommends further research. The report's most definitive conclusion is also its most controversial: that it is “extremely unlikely” that SARS-CoV-2 came out of a Chinese laboratory. Scientists from China made up half of the 34-member international panel. A joint statement by other countries complained that the investigation was “significantly delayed and lacked access to complete, original data, and samples.” It called for a transparent, “rapid, independent, expert-led, and unimpeded evaluation of the origins.” ### Funding The science committee in the U.S. House of Representatives wants to more than double the budget of the National Science Foundation (NSF) in the next 5 years, from $8.5 billion to $18.3 billion. A sizable chunk of the extra money—$5 billion by 2026—would go to a new directorate, Science and Engineering Solutions, that would accelerate the conversion of basic research into new technologies and products. Last year, Senate Majority Leader Chuck Schumer (D–NY) proposed growing NSF to $100 billion over 5 years, with roughly one-third of that money going to a new technology directorate. Schumer's vision for NSF is part of still-evolving draft legislation affecting many federal agencies that pinpoints key technologies needed to address economic and security threats posed by China's growing technological prowess. In contrast, the House bill is limited to NSF's programs and is aimed at strengthening basic research across all disciplines that NSF supports. The House and Senate would need to agree on a vision for NSF, and other legislation would be needed to appropriate the money. ### Astronomy Light pollution from space junk and satellites may have already robbed the entire Earth of the dark skies best for sensitive astronomical observations, an analysis has found. Researchers estimated the size and shininess of tens of thousands of objects in orbit as of 2020, before an onslaught of thousands more satellites that companies plan to launch in the coming years. Even at Earth's darkest sites, the sky glows from natural sources such as ionized particles; but the existing orbiting objects reflect and scatter about 10% more of this diffuse light back into the atmosphere, the research team calculates in a paper accepted this week by the Monthly Notices of the Royal Astronomical Society . That extra amount violates an International Astronomical Union standard for observing sites and could compromise observations of the dimmest galaxies, which scientists study for clues about the physics of galaxy formation and the nature of dark matter. To gather such data, astronomers already need long exposures on the biggest telescopes at the darkest available sites. ### Ethics Harvard University last week penalized quantitative biologist Martin Nowak for his connections with disgraced financier Jeffrey Epstein. Epstein had donated $6.5 million for Nowak's research in 2003; after being convicted in 2008 of soliciting prostitution from a minor, Epstein introduced Nowak to donors who provided an additional $7.5 million. Nowak's actions after 2008—repeatedly hosting Epstein on campus, promoting Epstein on his program's web page, and providing false information about Epstein's support in a grant application—violated Harvard policies, and other actions showed “blameworthy negligence and unprofessional behavior,” Claudine Gay, dean of arts and sciences, wrote in an email last week to faculty members. Nowak will continue at Harvard as a math professor, but his Program for Evolutionary Dynamics will be shut down and he will be barred for at least 2 years from serving as a principal investigator on grants. “I regret the connection I was part of fostering between Harvard and Jeffrey Epstein,” Nowak said in a statement last week. Epstein died by suicide in 2019. ### Archaeology Chinese archaeologists last week reported unearthing more than 500 artifacts, including gold ornaments, bronze heads, ivory and jade tools, and a gold mask dating back about 3000 years at the Sanxingdui archaeological site in southwestern Sichuan province. Sanxingdui, then ruled by the Shu kingdom, has already yielded thousands of bronze relics unlike anything found elsewhere in China, including at sites of the contemporaneous Shang dynasty in the Yellow River region. The new finds, retrieved from what are thought to be sacrificial pits, may shed light on how the Shu kingdom contributed to Chinese civilization. VACCINE LEADER FIRED Moncef Slaoui, who headed COVID-19 vaccine development during the Trump administration, has been fired as chairman of a medical research firm controlled by manufacturer GlaxoSmithKline after he was accused of sexual harassment. The company said an outside investigation substantiated the allegation by a female employee about Slaoui's behavior several years ago when he worked there. Slaoui also stepped down from leadership roles at two other pharmaceutical companies and issued a statement in which he apologized to the woman and his family. RETURNING LOOTED ART Museums in Germany have pledged to return hundreds of artifacts, including bronze statues, looted during the colonial era from the kingdom of Benin in what is now Nigeria. The British Museum and others face growing pressure to join them. PARDON SOUGHT The Australian Academy of Science issued a statement saying a court ignored new genetic evidence when it denied last week an appeal by a woman convicted of killing her four young children. Tests point to a natural cause of the deaths: Two of the children carried a mutation in the CALM2 gene that is associated with sudden death by cardiac failure in infants and children. Prosecutors had accused Kathleen Folbigg of smothering the children but have not presented medical evidence that supports that position. Academy members have signed a petition asking New South Wales's governor to pardon her. AI IN MEDICINE The Broad Institute has received $300 million to study how machine learning can improve the prevention and treatment of disease. Half the sum is coming from a foundation of Wendy and Eric Schmidt, a member of Broad's board and former CEO of Google, and the rest from the Broad Foundation. R&D SPENDING RISE The United States spent more than 3% of gross domestic product on R&D in 2019 for the first time. The 3.07% share is a record and met a goal set by former President Barack Obama a decade ago. Israel led globally with 4.9%, the Organisation for Economic Co-operation and Development said. Total U.S. spending was more than any other country's.

The generation of plausible and controllable 3D human motion animations is a long-standing problem that often requires a manual intervention of skilled artists. Existing machine learning approaches try to semi-automate this process by allowing the user to input partial information about the future movement. However, they are limited in two significant ways: they either base their pose prediction on past prior frames with no additional control over the future poses or allow the user to input only a single trajectory that precludes fine-grained control over the output. To mitigate these two issues, we reformulate the problem of future pose prediction into pose completion in space and time where trajectories are represented as poses with missing joints. We show that such a framework can generalize to other neural networks designed for future pose prediction. Once trained in this framework, a model is capable of predicting sequences from any number of trajectories. To leverage this notion, we propose a novel transformer-like architecture, TrajeVAE, that provides a versatile framework for 3D human animation. We demonstrate that TrajeVAE outperforms trajectory-based reference approaches and methods that base their predictions on past poses in terms of accuracy. We also show that it can predict reasonable future poses even if provided only with an initial pose.

Out of a hundred trials, how many errors does your speaker verifier make? For the user this is an important, practical question, but researchers and vendors typically sidestep it and supply instead the conditional error-rates that are given by the ROC/DET curve. We posit that the user's question is answered by the Bayes error-rate. We present a tutorial to show how to compute the error-rate that results when making Bayes decisions with calibrated likelihood ratios, supplied by the verifier, and an hypothesis prior, supplied by the user. For perfect calibration, the Bayes error-rate is upper bounded by min(EER,P,1-P), where EER is the equal-error-rate and P, 1-P are the prior probabilities of the competing hypotheses. The EER represents the accuracy of the verifier, while min(P,1-P) represents the hardness of the classification problem. We further show how the Bayes error-rate can be computed also for non-perfect calibration and how to generalize from error-rate to expected cost. We offer some criticism of decisions made by direct score thresholding. Finally, we demonstrate by analyzing error-rates of the recently published DCA-PLDA speaker verifier.

This work supports further development of language technology for the languages of Africa by providing a Wikidata-derived resource of name lists corresponding to common entity types (person, location, and organization). While we are not the first to mine Wikidata for name lists, our approach emphasizes scalability and replicability and addresses data quality issues for languages that do not use Latin scripts. We produce lists containing approximately 1.9 million names across 28 African languages. We describe the data, the process used to produce it, and its limitations, and provide the software and data for public use. Finally, we discuss the ethical considerations of producing this resource and others of its kind.

Deep generative models, such as Variational Autoencoders (VAEs), have been employed widely in computational creativity research. However, such models discourage out-of-distribution generation to avoid spurious sample generation, limiting their creativity. Thus, incorporating research on human creativity into generative deep learning techniques presents an opportunity to make their outputs more compelling and human-like. As we see the emergence of generative models directed to creativity research, a need for machine learning-based surrogate metrics to characterize creative output from these models is imperative. We propose group-based subset scanning to quantify, detect, and characterize creative processes by detecting a subset of anomalous node-activations in the hidden layers of generative models. Our experiments on original, typically decoded, and "creatively decoded" (Das et al 2020) image datasets reveal that the proposed subset scores distribution is more useful for detecting creative processes in the activation space rather than the pixel space. Further, we found that creative samples generate larger subsets of anomalies than normal or non-creative samples across datasets. The node activations highlighted during the creative decoding process are different from those responsible for normal sample generation.

We present a parallel machine translation training corpus for English and Akuapem Twi of 25,421 sentence pairs. We used a transformer-based translator to generate initial translations in Akuapem Twi, which were later verified and corrected where necessary by native speakers to eliminate any occurrence of translationese. In addition, 697 higher quality crowd-sourced sentences are provided for use as an evaluation set for downstream Natural Language Processing (NLP) tasks. The typical use case for the larger human-verified dataset is for further training of machine translation models in Akuapem Twi. The higher quality 697 crowd-sourced dataset is recommended as a testing dataset for machine translation of English to Twi and Twi to English models. Furthermore, the Twi part of the crowd-sourced data may also be used for other tasks, such as representation learning, classification, etc. We fine-tune the transformer translation model on the training corpus and report benchmarks on the crowd-sourced test set.

In the much-applauded interventions by Google The advancement in machine learning computational and Microsoft through their translation services, power coupled with the recent investment quite a number of African languages have been within the domain by technological companies integrated, but Ghanaian languages are excluded has stimulated considerable interest and (Google, 2020; Microsoft, 2021). A historic move brought about a legion of applications in natural worth mentioning is Baidu Translate's incorporation language digitisation in developed countries, of the Twi language in their translation service.

The role of artificial intelligence in vaccine distribution will be very critical in vaccinating the global population against COVID-19. Vaccine distribution is one of the biggest logistical challenges humanity has faced so far and I think AI can be leveraged to help us with the equitable distribution of the vaccine. In the United States, as of now the rollout of the vaccine has been painfully slow with a lot of logistical issues from distribution to inoculations. Worldwide, the progress is even more sluggish, with some countries yet to start the journey of inoculations. The role of artificial intelligence in vaccine distribution involves the following challenges that AI can help with provided we have quality and accurate data.

Supply chains have taken a battering this year from the coronavirus pandemic and other extreme events--and artificial intelligence has emerged as a critical tool for navigating everyday business in this environment. The use of AI and its various subsets, such as machine learning, is enabling these companies to forecast demand with increasing accuracy and to optimize their supply chains, executives say. "As a supply-chain provider, as a logistics provider, we are very much in the data business," said Mario Harik, chief information officer at XPO Logistics Inc., while speaking Wednesday on a virtual panel at the WSJ Pro AI Executive Forum Mr. Harik said that events such as the accidental blocking of the Suez Canal by a shipping vessel this week demonstrate how supply-chain optimization and diversification have become essential. AI is a useful tool to quickly figure out how to reroute shipments and plan for extreme events by building redundancy into operations through multiple distribution facilities, he said. AI can help optimize the placement of these facilities, he said, as well as the "intake flow and the outbound flow at facilities as well."

Its widely accepted that artificial intelligence (AI) technologies will add trillions to global GDP in the next 20 years, making it the one of the world's most powerful technology trends on par with the disruption and opportunities being created by cloud computing and blockchain. So is Africa getting a slice of the lucrative artificial intelligence pie and what are the current AI adoption trends in the region? Although Africa's AI industry is still relatively small compared to the US, Europe and Asia, this has not stopped some of the continent's most innovative start-ups from developing solutions that demonstrate how promising the technology can be for the African economy. However, AI innovation in Africa is often ignored or overlooked because the number of patents applied for and the amount of research funding available is not well aligned with local contexts, data is missing, and the map still looks essentially bleak. That said, the prospects for AI in Africa are positive, as the potential for innovation and growth in artificial intelligence (AI) adoption is increasing.