Please use the sharing tools found via the share button at the top or side of articles. Subscribers may share up to 10 or 20 articles per month using the gift article service. More information can be found here. The writer is professor of computer science and Smith-Zadeh professor in engineering, University of California, Berkeley The subject of autonomous killer robots exercises many technologists, politicians and human rights activists. Indeed, the Financial Times's advice page for would-be opinion writers complains that, in their pitches, "lots of people spin doomsday scenarios about robots".

What does it mean to be an inventor? In patent law, designed to protect the intellectual property of inventors, officials are used to thinking of inventors as humans, taking an "inventive step" – a new way of doing something -- not obvious to a person skilled in the same art. But last week -- in a judicial world first -- Australia's Federal Court ruled an artificial intelligence (AI) system can be named as an inventor. That judgement overturned a decision by the nation's Commissioner of Patents that meant US scientist Stephen Thaler could not patent inventions by his AI system, DABUS (Device for Autonomous Bootstrapping of Unified Sentience). Thaler says DABUS independently designed a fractal-shaped container for improved grip and heat transfer, and an emergency beacon that flashes more noticeably.

Extreme Learning Machine is a powerful classification method very competitive existing classification methods. It is extremely fast at training. Nevertheless, it cannot perform face verification tasks properly because face verification tasks require comparison of facial images of two individuals at the same time and decide whether the two faces identify the same person. The structure of Extreme Leaning Machine was not designed to feed two input data streams simultaneously, thus, in 2-input scenarios Extreme Learning Machine methods are normally applied using concatenated inputs. However, this setup consumes two times more computational resources and it is not optimized for recognition tasks where learning a separable distance metric is critical. For these reasons, we propose and develop a Siamese Extreme Learning Machine (SELM). SELM was designed to be fed with two data streams in parallel simultaneously. It utilizes a dual-stream Siamese condition in the extra Siamese layer to transform the data before passing it along to the hidden layer. Moreover, we propose a Gender-Ethnicity-Dependent triplet feature exclusively trained on a variety of specific demographic groups. This feature enables learning and extracting of useful facial features of each group. Experiments were conducted to evaluate and compare the performances of SELM, Extreme Learning Machine, and DCNN. The experimental results showed that the proposed feature was able to perform correct classification at 97.87% accuracy and 99.45% AUC. They also showed that using SELM in conjunction with the proposed feature provided 98.31% accuracy and 99.72% AUC. They outperformed the well-known DCNN and Extreme Leaning Machine methods by a wide margin.

Breast cancer is one of the factors that cause the increase of mortality of women. The most widely used method for diagnosing this geological disease i.e. breast cancer is the ultrasound scan. Several key features such as the smoothness and the texture of the tumor captured through ultrasound scans encode the abnormality of the breast tumors (malignant from benign). However, ultrasound scans are often noisy and include irrelevant parts of the breast that may bias the segmentation of eventual tumors. In this paper, we are going to extract the region of interest ( i.e, bounding boxes of the tumors) and feed-forward them to one semantic segmentation encoder-decoder structure based on its classification (i.e, malignant or benign). the whole process aims to build an instance-based segmenter from a semantic segmenter and an object detector.

Israel's defense minister warned Thursday that his country is prepared to strike Iran, issuing the threat against the Islamic Republic after a fatal drone strike on a oil tanker at sea that his nation blamed on Tehran. The comments by Benny Gantz come as Israel lobbies countries for action at the United Nations over last week's attack on the oil tanker Mercer Street that killed two people. The tanker, struck off Oman in the Arabian Sea, is managed by a firm owned by an Israeli billionaire. The U.S. and the United Kingdom also blamed Iran for the attack, but no country has offered evidence or intelligence to support the claim. Iran, which along with its regional militia allies has launched similar drone attacks, has denied being involved.

As battles to contain the COVID-19 pandemic continue, attention is focused on emerging variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus that have been deemed variants of concern because they are resistant to antibodies elicited by infection or vaccination or they increase transmissibility or disease severity. Three papers used functional and structural studies to explore how mutations in the viral spike protein affect its ability to infect host cells and to evade host immunity. Gobeil et al. looked at a variant spike protein involved in transmission between minks and humans, as well as the B1.1.7 (alpha), B.1.351 (beta), and P1 (gamma) spike variants; Cai et al. focused on the alpha and beta variants; and McCallum et al. discuss the properties of the spike protein from the B1.1.427/B.1.429 (epsilon) variant. Together, these papers show a balance among mutations that enhance stability, those that increase binding to the human receptor ACE2, and those that confer resistance to neutralizing antibodies. Science , abi6226, abi9745, abi7994, this issue p. [eabi6226][1] , p. [642][2], p. [648][3] ### INTRODUCTION Variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been circulating worldwide since the beginning of the pandemic. Some are termed Variants of Concern (VOC) because they show evidence for increased transmissibility, higher disease severity, resistance to neutralizing antibodies elicited by current vaccines or from previous infection, reduced efficacy of treatments, or failure of diagnostic detection methods. VOCs accumulate mutations in the spike (S) glycoprotein. Some VOCs that arose independently in different geographical locations show identical changes, implying convergent evolution and selective advantages of the acquired variations. A set of three amino acid substitutions in the receptor-binding domain (RBD)—Lys417 → Asn (K417N), Glu484 → Lys (E484K), and Asn501 → Tyr (N501Y)—occurred in the B.1.1.28 and B.1.351 lineages that originated in Brazil and South Africa, respectively. The P.1 lineage that branched off B.1.1.28 harbored a Lys417 → Thr (K417T) substitution while retaining the E484K and N501Y changes. The E484K substitution has attracted attention as a result of its location within the epitope of many potent neutralizing antibodies. The N501Y substitution also occurred in the B.1.1.7 variant that originated in the UK and was implicated in increased receptor binding and higher transmissibility of the variant. The B.1.1.7 variant, in turn, shares the His69/Val70 spike deletion mutation with spike from a variant that was implicated in transmission between humans and minks (ΔFVI). ### RATIONALE Global sequencing initiatives and in vitro neutralization and antibody binding assays have rapidly provided critical and timely information on the VOCs. Here, by combining cryo–electron microscopy (cryo-EM) structural determination with binding assays and computational analyses on the variant spikes, we sought to visualize the impact of the amino acid substitutions on spike conformation to understand how these changes affect their biological function. ### RESULTS We measured angiotensin-converting enzyme 2 (ACE2) receptor and antibody binding for 19 SARS-CoV-2 S ectodomain constructs harboring amino acid changes found in circulating variants. These included a variant involved in interspecies SARS-CoV-2 transmission between humans and minks, as well as several VOCs including the B.1.1.7, B.1.1.28/P.1, and B.1.351 variants. Consistent with published neutralization data, B.1.1.7 showed decreased binding to N-terminal domain (NTD)–directed antibodies, whereas P.1 and B.1.351 showed reduced binding to both NTD- and RBD-directed antibodies. All variants showed increased binding to ACE2, which was mediated by higher propensity for RBD-up states, and affinity-enhancing mutations in the RBD. We observed spike instability in the mink-associated variant, highlighted by the presence of a population in the cryo-EM dataset with missing density for the S1 subunit of one protomer. Modulation of contacts between the SD1 and HR1 regions led to increased RBD-up states of the B.1.1.7 spike, with the protein stability maintained by a balance of stabilizing and destabilizing mutations. A local destabilizing effect of the RBD E484K mutation was implicated in resistance of the B.1.1.28/P.1 and B.1.351 variants to some potent RBD-directed neutralizing antibodies. ### CONCLUSION Our study revealed details of how amino acid substitutions affect spike conformation in circulating SARS-CoV-2 VOCs. We define communication networks that modulate spike allostery and show that the S protein uses different mechanisms to converge upon similar solutions for altering the RBD up/down positioning. ![Figure][4] Cryo-EM structures of SARS-CoV-2 spike ectodomains. Naturally occurring amino acid variations are represented by colored spheres. Spike mutations from a mink-associated (ΔFV) (top left), B.1.1.7 (top right), B.1.351 (bottom right), and a spike with three RBD mutations (bottom left) are shown. Relative proportions of the RBD down and up populations are indicated for each. The three amino acid substitutions in the RBD—K417N/T, E484K, and N501Y—were found in the B.1.1.28 variant and are shared with the P.1 and B.1.351 lineages. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with multiple spike mutations enable increased transmission and antibody resistance. We combined cryo–electron microscopy (cryo-EM), binding, and computational analyses to study variant spikes, including one that was involved in transmission between minks and humans, and others that originated and spread in human populations. All variants showed increased angiotensin-converting enzyme 2 (ACE2) receptor binding and increased propensity for receptor binding domain (RBD)–up states. While adaptation to mink resulted in spike destabilization, the B.1.1.7 (UK) spike balanced stabilizing and destabilizing mutations. A local destabilizing effect of the RBD E484K mutation was implicated in resistance of the B.1.1.28/P.1 (Brazil) and B.1.351 (South Africa) variants to neutralizing antibodies. Our studies revealed allosteric effects of mutations and mechanistic differences that drive either interspecies transmission or escape from antibody neutralization. [1]: /lookup/doi/10.1126/science.abi6226 [2]: /lookup/doi/10.1126/science.abi9745 [3]: /lookup/doi/10.1126/science.abi7994 [4]: pending:yes

SCI COMMUN### Space science The International Space Station (ISS) had a tense hour last week when thrusters on a newly arrived Russian laboratory module misfired and pushed the station 45° out of its normal orientation. The 20-ton, truck-size Nauka module—named for the Russian word for “science”—was delayed 15 years by funding and technical issues. The troubles continued after its 21 July liftoff on a Proton-M rocket, as controllers struggled to communicate with Nauka after it reached orbit and to fire up its main engine. Three hours after docking with the ISS on 29 July, Nauka's thrusters switched on unprompted—the result of a “short-term software failure,” according to the Russian space agency Roscosmos—and began to slowly turn the whole station. Russian controllers tried to counteract the turn by firing thrusters on an attached service module and later a cargo freighter. Nauka's thrusters eventually ran out of fuel and the station was righted. NASA says the ISS crew was never in any danger and could not feel the thruster tug-of-war going on in the station's Russian section. > “This pandemic was a big test for AI [artificial intelligence] and medicine. … But I don't think we passed that test.” > > University of Cambridge machine learning researcher Derek Driggs , to MIT Technology Review, on findings that none of hundreds of AI-based tools to diagnose or triage COVID-19 patients are fit for clinical use. ### Conservation The killing of adult female elephants reduces the survival chances of offspring even if they are already weaned—and the effect is large enough to slow population growth, researchers report this week. Maternal care is known to be important for long-lived mammals such as elephants, but its impact on population growth hadn't been directly measured for any wild species. By studying 19 years of data on 645 female elephants in a wild population in Samburu county in Kenya, scientists calculated annual survival probabilities for elephants of various ages. An orphaned juvenile—a weaned individual between the ages of 3 and 8 years—had an 86% chance of survival, compared with 96% for a juvenile with a living mother, the researchers report in Current Biology . The orphans were less likely to survive than the oldest adult females, which surprised the team, in part because poachers target adults for their large tusks. It's not known why orphaned juveniles are vulnerable, but they tend to face more aggression from their herd. ### COVID-19 In a dramatic reversal that concedes the power of the highly transmissible Delta variant, the U.S. Centers for Disease Control and Prevention (CDC) on 27 July revised its 13 May guidance on wearing masks, saying fully vaccinated people should again wear masks in public, indoor spaces in areas of substantial or high coronavirus transmission. Three days later, the agency published data from an outbreak in Barnstable county in Massachusetts that it called “pivotal” to its decision. Of 469 people infected there during the first half of July, a time of densely packed indoor and outdoor events, 74% were fully vaccinated. The Delta variant was identified in 89% of 133 sequenced cases. Furthermore, samples from the noses and throats of fully vaccinated people bore as much virus as those from the unvaccinated. That finding “raised concerns that, unlike with other variants, vaccinated people infected with Delta can transmit the virus,” CDC Director Rochelle Walensky said in a 30 July statement. She added that the masking recommendation was updated to ensure vaccinated individuals would “not unknowingly transmit virus to others.” Four of five people who were hospitalized in the Massachusetts outbreak were fully vaccinated. There were no deaths. ### Bioethics Relatives of Henrietta Lacks, whose cervical cancer cells were harvested without her knowledge at Johns Hopkins Hospital in 1951, plan to sue pharmaceutical companies that have profited from studying those cells. The self-renewing “HeLa” cell line has become a mainstay of basic and applied research in diverse fields including cancer biology and infectious disease. Lacks's family has hired trial lawyer Christopher Seeger and civil rights attorney Ben Crump, who has also represented families of Black men killed by the police, including George Floyd and Michael Brown, The Baltimore Sun reported last week. The lawyers have not disclosed any defendants, but said they plan to file the first lawsuits on the 70th anniversary of Lacks's death, on 4 October. ### COVID-19 The mysterious disappearance of coronavirus sequences from a U.S. database appears to have a mundane explanation: the accidental deletion of a data-sharing statement. In late June, evolutionary biologist Jesse Bloom of the Fred Hutchinson Cancer Research Center suggested in a preprint that Chinese scientists had deliberately hidden viral sequences from early COVID-19 patients in Wuhan, first adding them to a National Institutes of Health (NIH) database but then requesting they be removed. Using data in a paper the group published in the journal Small , Bloom was able to recover parts of the missing sequences in Google's Cloud. Last month, a Chinese health minister said editors at the journal had eliminated text that noted where the sequences were deposited, leading the scientists to think the data did not need to be public and to request their removal. Last week, the journal added a correction note to the paper confirming that a “Data Availability” paragraph had been mistakenly deleted during copy editing. The viral sequences have now been added to a public Chinese database, the health minister noted. Bloom says that appears true, but adds the explanation given is “completely inconsistent” with the emailed data removal request sent to NIH last year, which said the sequences had already been deposited elsewhere. ### Research collaboration The U.S. government wants to retry a former faculty member at the University of Tennessee, Knoxville, it had previously charged with concealing his ties to Chinese entities. On 16 June, a federal judge declared a mistrial in the case against Anming Hu, the first to go before a jury under the government's 3-year-old China Initiative, which has led to the prosecution of several scientists of Chinese heritage. But on 30 July the Department of Justice filed “a notice of intent” to retry Hu, who lost his job after his arrest in February 2020 and has remained under house arrest. Civil rights groups that have accused the government of racial profiling condemned the move. On 29 July, nearly 100 Democratic members of Congress complained to U.S. Attorney General Merrick Garland that Hu has been one of “many people of Asian descent … falsely accused of espionage” under the initiative. ### Biotechnology A genetic engineering technique called gene drive successfully collapsed captive populations of the malaria-spreading mosquito Anopheles gambiae in the largest test yet of the strategy. Researchers inserted a mutation that renders females unable to reproduce, along with another genetic element that spreads that mutation quickly through a population. A 2018 study showed the approach could suppress populations of mosquitoes housed in small cages (about .016 cubic meters). The new study tested the strategy in larger cages (nearly 5 cubic meters), where multiple generations of mosquitoes could mate, forage, and lay eggs more like they would in the wild. Introducing the engineered mosquitoes crashed the caged populations within 1 year, the researchers reported last week in Nature Communications , and the insects did not develop resistance to the sterilizing effects of the mutation. Experimental releases of the insects in the wild face regulatory hurdles and are likely still years away. ### Conservation The International Union for Conservation of Nature (IUCN) last week announced that its long-running “Red List of Threatened Species” will be joined by a new measure, “Green Status of Species,” that looks beyond the Red List's ratings of extinction risk to measure recovery and the impact of conservation efforts. Species currently on the Red List will now also get a green score that puts them into one of several categories ranging from “extinct in the wild” to “fully recovered.” Researchers will also estimate the impact of past, current, and future conservation efforts on a species. They hope this metric, which is more success-oriented and sensitive to change than Red List status, will provide a road map for future protective measures. The first batch of roughly 50 assessments is slated to go live on the IUCN website this fall. $33.5 billion —Anticipated 2021 revenue from Pfizer's COVID-19 vaccine, according to an updated projection the company released last week. 40% —Proportion of wild white-tailed deer tested in four U.S. states between January and March that had SARS-CoV-2 antibodies, suggesting they had been infected with the virus. (bioRxiv) ### A test for anonymous hiring In a bid to reduce bias during faculty hiring, Yale University's molecular biophysics and biochemistry department conducted an experiment last year: Scientists applying for a tenure-track position were asked to submit anonymized materials—omitting their names and the names of institutions they'd trained at and journals they'd published in. Science spoke with the department chair, Enrique De La Cruz, to find out how the search—which was ultimately successful—went. (A longer version of this interview is at .) > Q: Was there any pushback to the idea? > A: No. There was skepticism. I think there was concern that we would de-emphasize the significance of scholarship for other things. But the fact that it was an experiment helped. We're scientists, so if you phrase it that way everyone's on board. “OK, it's an experiment? Sure, sounds good. That's what we do.” > Q: How did it work? > A: We asked applicants to make their applications anonymous. It required them to think deeply about what they've done and articulate their contributions without relying on the shorthand—for example, I worked for this Nobel laureate at this prestigious institution, and I published in these fantastic journals. The hiring committee made a first cut based only on anonymized statements about the applicants' past and future research, and then another based on teaching and diversity, equity, inclusion statements, which were also anonymized. After all that was done, they looked at CVs and letters of recommendation, which were not anonymous. … It was a lot of work, but I do think it'll be easier next time. > Q: After the initial selection, you ended up with a larger percentage of women and members of underrepresented racial and ethnic groups compared with the applicant pool. Why do you think that is? > A: I'm not going to draw any firm conclusions based on an experiment I've done once. But I can imagine that it is possible that people from underrepresented groups were energized and motivated by being evaluated without identifying information. Maybe they took it a little more seriously because they saw it as an opportunity as opposed to an obstacle.

South Africa recently became what is believed to be the first country in the world to award a patent to an invention by an Artificial Intelligence (AI). An interlocking food and beverage container based on fractal geometry has been awarded a patent by South Africa's Companies and Intellectual Property Commission (CIPC). Confirmation of the patent was published in the commission's journal on 28 July. But unlike the hundreds of patents listed in the CIPC's latest journal, this container was not conceptualised by a human. The patent identifies Dabus – the Device for the Autonomous Bootstrapping of Unified Sentience – as the inventor.

Hate speech is a specific type of controversial content that is widely legislated as a crime that must be identified and blocked. However, due to the sheer volume and velocity of the Twitter data stream, hate speech detection cannot be performed manually. To address this issue, several studies have been conducted for hate speech detection in European languages, whereas little attention has been paid to low-resource South Asian languages, making the social media vulnerable for millions of users. In particular, to the best of our knowledge, no study has been conducted for hate speech detection in Roman Urdu text, which is widely used in the sub-continent. In this study, we have scrapped more than 90,000 tweets and manually parsed them to identify 5,000 Roman Urdu tweets. Subsequently, we have employed an iterative approach to develop guidelines and used them for generating the Hate Speech Roman Urdu 2020 corpus. The tweets in the this corpus are classified at three levels: Neutral-Hostile, Simple-Complex, and Offensive-Hate speech. As another contribution, we have used five supervised learning techniques, including a deep learning technique, to evaluate and compare their effectiveness for hate speech detection. The results show that Logistic Regression outperformed all other techniques, including deep learning techniques for the two levels of classification, by achieved an F1 score of 0.906 for distinguishing between Neutral-Hostile tweets, and 0.756 for distinguishing between Offensive-Hate speech tweets.

For easier communication, posting, or commenting on each others posts, people use their dialects. In Africa, various languages and dialects exist. However, they are still underrepresented and not fully exploited for analytical studies and research purposes. In order to perform approaches like Machine Learning and Deep Learning, datasets are required. One of the African languages is Bambara, used by citizens in different countries. However, no previous work on datasets for this language was performed for Sentiment Analysis. In this paper, we present the first common-crawl-based Bambara dialectal dataset dedicated for Sentiment Analysis, available freely for Natural Language Processing research purposes.