Modifications to the Machine Optics of BESSY II Necessitated by the EMIL Project

The Helmholtz Zentrum Berlin and the Max Planck Society are going to build a new dedicated X ray beam line at the synchrotron light source BESSY II which will be used for analyzing materials for renewable energy generation. The new large scale project has been dubbed EMIL. In this document we present the modifications to the machine optics and to what extent these changes affect the performance of BESSY I

Deception Detection: Using Eye-Tracking Technology to Measure Faking in a Simulated Applicant Setting

The impact of faking on selection assessments and the need for methods to detect such behavior has drawn increased attention of researchers in the selection field over the last quarter century. The overarching purpose of this study was to assess the validity of utilizing eye-tracking technology in the detection of applicant faking on personality measures. Specifically, this study examined the physiological cues of response latency, eye fixation, and pupil dilation and their association with deception in the context of personality assessment in a job seeking scenario. The results indicated that individuals engaged in faking behavior had significantly more eye fixations and recorded significantly higher scores on the paper and pencil measure of cognitive load. In addition, results suggest that the experimental conditions likely accounted for the alterations in cognitive load regardless of the level of social desirability of items

Category learning in a dynamic world

No description supplie

Moving from information and collaboration to action: report from the 3rd International Dog Health Workshop, Paris in April 2017

Abstract Background Breed-related health problems in dogs have received increased focus over the last decade. Responsibility for causing and/or solving these problems has been variously directed towards dog breeders and kennel clubs, the veterinary profession, welfare scientists, owners, regulators, insurance companies and the media. In reality, all these stakeholders are likely to share some responsibility and optimal progress on resolving these challenges requires all key stakeholders to work together. The International Partnership for Dogs (IPFD), together with an alternating host organization, holds biennial meetings called the International Dog Health Workshops (IDHW). The Société Centrale Canine (French Kennel Club) hosted the 3rd IDHW, in Paris, in April, 2017. These meetings bring together a wide range of stakeholders in dog health, science and welfare to improve international sharing of information and resources, to provide a forum for ongoing collaboration, and to identify specific needs and actions to improve health, well-being and welfare in dogs. Results The workshop included 140 participants from 23 countries and was structured around six important issues facing those who work to improve dog health. These included individualized breed-specific strategies for health and breeding, extreme conformations, education and communication in relation to antimicrobial resistance, behavior and welfare, genetic testing and population-based evidence. A number of exciting actions were agreed during the meeting. These included setting up working groups to create tools to help breed clubs accelerate the implementation of breed-health strategies, review aspects of extreme conformation and share useful information on behavior. The meeting also heralded the development of an online resource of relevant information describing quality measures for DNA testing. A demand for more and better data and evidence was a recurring message stressed across all themes. Conclusions The meeting confirmed the benefits from inclusion of a diverse range of stakeholders who all play relevant and collaborative parts to improve future canine health. Firm actions were set for progress towards improving breed-related welfare. The next international workshop will be in the UK in 2019 and will be organized by the UK Kennel Club

Large language models for aspect-based sentiment analysis

Large language models (LLMs) offer unprecedented text completion capabilities. As general models, they can fulfill a wide range of roles, including those of more specialized models. We assess the performance of GPT-4 and GPT-3.5 in zero shot, few shot and fine-tuned settings on the aspect-based sentiment analysis (ABSA) task. Fine-tuned GPT-3.5 achieves a state-of-the-art F1 score of 83.8 on the joint aspect term extraction and polarity classification task of the SemEval-2014 Task 4, improving upon InstructABSA [@scaria_instructabsa_2023] by 5.7%. However, this comes at the price of 1000 times more model parameters and thus increased inference cost. We discuss the the cost-performance trade-offs of different models, and analyze the typical errors that they make. Our results also indicate that detailed prompts improve performance in zero-shot and few-shot settings but are not necessary for fine-tuned models. This evidence is relevant for practioners that are faced with the choice of prompt engineering versus fine-tuning when using LLMs for ABSA

Modeling the Influence of Knowledge on Recognition: Connecting visualrecognition behavior across development to PDP computational models ofsemantic knowledge

Recent behavioral findings in children’s selection of a “real” versus “silly” animal demonstrated a developmentalchange wherein younger children select chimeric animals with regular forms (e.g., a seal with four legs, a camel with no hump)as real. To reduce verbal demands while maintaining the same stimuli, we developed a touch screen change-detection task inwhich children (4 – 7-years-old) were instructed to locate a single changing feature (e.g., a rhinoceros with and without a horn)as fast as possible. Children were faster to find changes when the feature appeared on animals with more prototypic animalforms (e.g., a donkey with and without a hump) when compared to animals with atypical forms (e.g., a camel with and withouta hump). Alongside exploration via computational models, these findings suggest that children’s real-world object recognitionis supported by the interplay of semantic knowledge, informed by covariation among visual features, and visual recognition

General Mechanisms Underlying Language and Spatial Cognitive Development

Previous research showed that children’s spatial language production predicts their spatial skills, but the mechanisms underlying this relation remain a source of debate. This study examined whether 4-year-olds’ spatial skills were predicted by their attention to task-relevant information—in tasks that emphasize either memory or language—above and beyond their spatial word production. Children completed three types of tasks: (1) a memory task assessing attention to task-relevant color, size, and location cues; (2) a production task assessing adaptive use of language to describe scenes, varying in color, size, and location; and (3) spatial tasks. After controlling for age, gender, and vocabulary, children’s spatial skills were significantly predicted by their memory for task-relevant cues, above and beyond their task-related language production and adaptive use of language. These findings suggest that attending to relevant information is a process supporting spatial skill acquisition and underlies the relation between language and spatial cognition