Fine-grained Affective Processing Capabilities Emerging from Large Language Models

Large language models, in particular generative pre-trained transformers (GPTs), show impressive results on a wide variety of language-related tasks. In this paper, we explore ChatGPT's zero-shot ability to perform affective computing tasks using prompting alone. We show that ChatGPT a) performs meaningful sentiment analysis in the Valence, Arousal and Dominance dimensions, b) has meaningful emotion representations in terms of emotion categories and these affective dimensions, and c) can perform basic appraisal-based emotion elicitation of situations based on a prompt-based computational implementation of the OCC appraisal model. These findings are highly relevant: First, they show that the ability to solve complex affect processing tasks emerges from language-based token prediction trained on extensive data sets. Second, they show the potential of large language models for simulating, processing and analyzing human emotions, which has important implications for various applications such as sentiment analysis, socially interactive agents, and social robotics

“Who’s a Good Robot?!” Designing Human-Robot Teaching Interactions Inspired by Dog Training

Recent work in Human-Robot Interaction (HRI) investigates the role of human users as teachers from which robots can flexibly learn new personalised skills through interaction. However, existing human-robot teaching methods remain largely unintuitive for the end user and require significant effort to adapt to the way the robot learns. This paper envisions the use of dog training methods as a starting point for HRI researchers to develop more intuitive interactions between human teachers and robot learners. We provide a design framework (called FETCH-R) aimed at guiding the conception of interactions between human teachers and robot learners inspired by dog training. This work paves the way towards the use of animal training as an inspiration to create human-robot teaching protocols that promote engagement, ease-of-use, and fosters human-robot relationships

A Survey of Automatic Protocol Reverse Engineering Approaches, Methods, and Tools on the Inputs and Outputs View

A network protocol defines rules that control communications between two or more machines on the Internet, whereas Automatic Protocol Reverse Engineering (APRE) defines the way of extracting the structure of a network protocol without accessing its specifications. Enough knowledge on undocumented protocols is essential for security purposes, network policy implementation, and management of network resources. This paper reviews and analyzes a total of 39 approaches, methods, and tools towards Protocol Reverse Engineering (PRE) and classifies them into four divisions, approaches that reverse engineer protocol finite state machines, protocol formats, and both protocol finite state machines and protocol formats to approaches that focus directly on neither reverse engineering protocol formats nor protocol finite state machines. The efficiency of all approaches’ outputs based on their selected inputs is analyzed in general along with appropriate reverse engineering inputs format. Additionally, we present discussion and extended classification in terms of automated to manual approaches, known and novel categories of reverse engineered protocols, and a literature of reverse engineered protocols in relation to the seven layers’ OSI (Open Systems Interconnection) model

Open Access and Open Data at CGIAR: Challenges and Solutions

CGIAR is a global research partnership of 15 geographically and scientifically diverse Centers dedicated to reducing poverty, enhancing food and nutrition security, and improving natural resource management. The Centers are charged with accelerating innovation to tackle challenges at a variety of scales from the local to the global. This requires data and other research outputs to be findable, accessible, interoperable, and reusable – that is, open via FAIR principles, and inter-linked where relevant. CGIAR Centers have made strong progress in implementing publication and data repositories; however, many of these still represent silos whose contents are not generally easily discoverable or inter-linked (e.g., agronomic trial data with socioeconomic or adoption data in the same geographies). In the absence of such interoperability-mediated discovery, “open” is of limited utility. The overall goal is for CGIAR’s trove of research data and associated information to be indexed and interlinked through a demand-driven cyberinfrastructure for agriculture, ensuring that research outputs are discoverable by humans and machines, and reusable via appropriate licensing to enhance innovation, uptake and impact. There are challenges to achieving this goal, not only across CGIAR, but for the agricultural domain in general. Among the foremost hurdles is that “open” tends to remain an unfunded mandate, making it difficult to operationalize effectively. Further, there is still significant concern on the part of scientists about making data open – largely centered around issues of trust, time, and quality – resulting in repositories frequently exposing metadata rather than the data sets themselves. While the ability to find metadata about resources qualifies as improvement, it continues to impose barriers to data access, discoverability, integration, and analysis, without which complex challenges to global agriculture development cannot be effectively addressed. CGIAR is addressing the urgent need to create a data sharing culture and enabling environment for Open Access and Open Data (OA/OD) that includes projects planning for OA/OD and allocating funds to support it, in parallel with the technical infrastructure mentioned above. While the technology necessary to enable FAIR outputs exists, achieving success implies data provider and consumer trust and buy-in, agreement and adherence to interoperability standards and/or mapping across varied approaches, and compliance with guidelines (including those on citation and licensing governing content reuse). Agricultural institutions, including CGIAR, are only now beginning to address these issues systematically, to agree on and adopt standards-based systems and processes, and to build cross-walks across differing schemas. Through its Open Access and Open Data initiative funded by the Bill and Melinda Gates Foundation, and via plans for an ambitious Big Data and ICT Platform , CGIAR is developing technical and cultural approaches that will enable research content to be consistently and seamlessly discovered, interlinked, and analyzed across its Centers. This paper describes the strategy used to identify the specific contexts and challenges faced by Centers in building an infrastructure and culture for OA/OD across CGIAR, with the ultimate goal of achieving greater impact in agricultural research for development

Global economic burden of unmet surgical need for appendicitis

Background: There is a substantial gap in provision of adequate surgical care in many low-and middle-income countries. This study aimed to identify the economic burden of unmet surgical need for the common condition of appendicitis. Methods: Data on the incidence of appendicitis from 170 countries and two different approaches were used to estimate numbers of patients who do not receive surgery: as a fixed proportion of the total unmet surgical need per country (approach 1); and based on country income status (approach 2). Indirect costs with current levels of access and local quality, and those if quality were at the standards of high-income countries, were estimated. A human capital approach was applied, focusing on the economic burden resulting from premature death and absenteeism. Results: Excess mortality was 4185 per 100 000 cases of appendicitis using approach 1 and 3448 per 100 000 using approach 2. The economic burden of continuing current levels of access and local quality was US $92 492 million using approach 1 and$73 141 million using approach 2. The economic burden of not providing surgical care to the standards of high-income countries was $95 004 million using approach 1 and$75 666 million using approach 2. The largest share of these costs resulted from premature death (97.7 per cent) and lack of access (97.0 per cent) in contrast to lack of quality. Conclusion: For a comparatively non-complex emergency condition such as appendicitis, increasing access to care should be prioritized. Although improving quality of care should not be neglected, increasing provision of care at current standards could reduce societal costs substantially

Pooled analysis of WHO Surgical Safety Checklist use and mortality after emergency laparotomy

Background The World Health Organization (WHO) Surgical Safety Checklist has fostered safe practice for 10 years, yet its place in emergency surgery has not been assessed on a global scale. The aim of this study was to evaluate reported checklist use in emergency settings and examine the relationship with perioperative mortality in patients who had emergency laparotomy. Methods In two multinational cohort studies, adults undergoing emergency laparotomy were compared with those having elective gastrointestinal surgery. Relationships between reported checklist use and mortality were determined using multivariable logistic regression and bootstrapped simulation. Results Of 12 296 patients included from 76 countries, 4843 underwent emergency laparotomy. After adjusting for patient and disease factors, checklist use before emergency laparotomy was more common in countries with a high Human Development Index (HDI) (2455 of 2741, 89.6 per cent) compared with that in countries with a middle (753 of 1242, 60.6 per cent; odds ratio (OR) 0.17, 95 per cent c.i. 0.14 to 0.21, P <0001) or low (363 of 860, 422 per cent; OR 008, 007 to 010, P <0.001) HDI. Checklist use was less common in elective surgery than for emergency laparotomy in high-HDI countries (risk difference -94 (95 per cent c.i. -11.9 to -6.9) per cent; P <0001), but the relationship was reversed in low-HDI countries (+121 (+7.0 to +173) per cent; P <0001). In multivariable models, checklist use was associated with a lower 30-day perioperative mortality (OR 0.60, 0.50 to 073; P <0.001). The greatest absolute benefit was seen for emergency surgery in low- and middle-HDI countries. Conclusion Checklist use in emergency laparotomy was associated with a significantly lower perioperative mortality rate. Checklist use in low-HDI countries was half that in high-HDI countries.Peer reviewe

Annual cycles are the most common reproductive strategy in African tropical tree communities

We present the first cross continental comparison of the flowering and fruiting phenology of tropical forests across Africa. Flowering events of 5,446 trees from 196 species across 12 sites, and fruiting events of 4,595 trees from 191 species, across 11 sites were monitored over periods of 6 to 29 years, and analysed to describe phenology at the continental level. To study phenology we used Fourier analysis to identify the dominant cycles of flowering and fruiting for each individual tree and we identified the time of year African trees bloom and bear fruit and their relationship to local seasonality. Reproductive strategies were diverse and no single regular cycle was found in >50% of individuals across all 12 sites. Additionally, we found annual flowering and fruiting cycles to be the most common. Sub-annual cycles were the next most common for flowering whereas supra-annual patterns were the next most common for fruiting. We also identify variation in different subsets of species, with species exhibiting mainly annual cycles most common in West and West-Central African tropical forests, while more species at sites in East-Central and Eastern African forests showed cycles ranging from sub-annual to supra-annual. Despite many trees showing strong seasonality, at most sites some flowering and fruiting occurred all year round. Environmental factors with annual cycles are likely to be important drivers of seasonal periodicity in trees across Africa, but proximate triggers are unlikely to be constant across the continen

Pf7: an open dataset of Plasmodium falciparum genome variation in 20,000 worldwide samples

We describe the MalariaGEN Pf7 data resource, the seventh release of Plasmodium falciparum genome variation data from the MalariaGEN network.  It comprises over 20,000 samples from 82 partner studies in 33 countries, including several malaria endemic regions that were previously underrepresented.  For the first time we include dried blood spot samples that were sequenced after selective whole genome amplification, necessitating new methods to genotype copy number variations.  We identify a large number of newly emerging crt mutations in parts of Southeast Asia, and show examples of heterogeneities in patterns of drug resistance within Africa and within the Indian subcontinent.  We describe the profile of variations in the C-terminal of the csp gene and relate this to the sequence used in the RTS,S and R21 malaria vaccines.  Pf7 provides high-quality data on genotype calls for 6 million SNPs and short indels, analysis of large deletions that cause failure of rapid diagnostic tests, and systematic characterisation of six major drug resistance loci, all of which can be freely downloaded from the MalariaGEN website