The fundamentals of eye tracking part 3: How to choose an eye tracker.

There is an abundance of commercial and open-source eye trackers available for researchers interested in gaze and eye movements. Which aspects should be considered when choosing an eye tracker? The paper describes what distinguishes different types of eye trackers, their suitability for different types of research questions, and highlights questions researchers should ask themselves to make an informed choice.

Summon a demon and bind it: A grounded theory of LLM red teaming.

Engaging in the deliberate generation of abnormal outputs from Large Language Models (LLMs) by attacking them is a novel human activity. This paper presents a thorough exposition of how and why people perform such attacks, defining LLM red-teaming based on extensive and diverse evidence. Using a formal qualitative methodology, we interviewed dozens of practitioners from a broad range of backgrounds, all contributors to this novel work of attempting to cause LLMs to fail.

Prevalence of processed foods in major US grocery stores.

The offering of grocery stores is a strong driver of consumer decisions. While highly processed foods such as packaged products, processed meat and sweetened soft drinks have been increasingly associated with unhealthy diets, information on the degree of processing characterizing an item in a store is not straightforward to obtain, limiting the ability of individuals to make informed choices. GroceryDB, a database with over 50,000 food items sold by Walmart, Target and Whole Foods, shows the degree of processing of food items and potential alternatives in the surrounding food environment.

The fundamentals of eye tracking part 4: Tools for conducting an eye tracking study.

Researchers using eye tracking are heavily dependent on software and hardware tools to perform their studies, from recording eye tracking data and visualizing it, to processing and analyzing it. This article provides an overview of available tools for research using eye trackers and discusses considerations to make when choosing which tools to adopt for one's study.

Source-tracing of industrial and municipal wastewater effluent in river water via fluorescence fingerprinting.

Fluorescence fingerprinting is a technique to uniquely characterize water samples based on their distinct composition of dissolved organic matter (DOM) measured via 3D fluorescence spectroscopy. It is an effective tool for monitoring the chemical composition of various water systems. This study examines a river affected by several municipal and industrial wastewater treatment plant (WWTP) effluents and aims to source-tracing them via fluorescence fingerprints based on parallel factor analysis (PARAFAC) components.

Digital (mis)trust: ethnographic encounters with computational forms.

This special issue is driven by a curiosity about the role of computational forms - practices, logics, technologies, and infrastructures - in social life and how they mediate issues of trust and mistrust: designated . Through a series of ethnographic encounters, its contributors describe how (mis)trust is rendered as an issue of concern by various actors as it is problematized, conceptualized, narrated, and designed for. In doing so, the papers analyse the work (mis)trust does in these settings, with a focus on the role of computational thinking within public discourses on democratic elections, the use of computational technologies in establishing bureaucratic order, the computational practices at play in the production of coding subjectivities, and the computational artefacts that assure data circulations within digital infrastructures.

The crone and the hydra: Figuring temporal relations to aging code.

Managing older software code, often referred to as legacy code, entails a great deal of complexity, as the longer a software system has been around, the more likely it has been subjected to revisions and has grown in its interdependencies to other components written at different times by different people. This can lead to software being seen as aging and in decline as it becomes increasingly difficult to maintain. At the same time, writing new lines of code or updating to new platforms, languages, and software tools, can also be positioned as a means to rejuvenate organizational work, acting as a salve to overcome hardware limitations, or other forms of stagnation.

Mainland China's 2021 restrictions on under-18s' video game time were imposed when older 2019 restrictions already applied: Omitting the historical regulatory context is misleading.

Investigating the impacts of addiction policymaking following implementation is important. Effective policies should be considered for emulation elsewhere, whilst ineffective policies should be repealed. Zhou et al.

A grassroots approach to peer support by the Danish Reproducibility Network.

The Danish Reproducibility Network (DKRN) is a grassroots initiative for establishing a peer-supportive reproducibility-focused academic network in Denmark. We modelled our approach on already existing national Reproducibility Networks. We consulted with researchers and research support professionals to identify the needs of the research community.

Good deeds or exploitation?: Queer parents working for private assisted reproductive technologies companies in urban China.

This article examines the interplay of queer reproduction and private assisted reproductive technologies (ART) companies in urban China. While same-sex marriage has not gained legal recognition in mainland China and childbirth outside heterosexual marriage has been restricted, queer parents who have children through ART have gradually become visible. ART has emerged as an ideal way for Chinese queer citizens to have children, though they are not legally permitted to use ART services in domestic hospitals.

Disruption of outdoor activities caused by wildfires increases disease circulation.

Although climate change poses a well-established risk to human health, present-day health impacts, particularly those resulting from climate-induced behavioral changes, are under-quantified. Analyzing the U.S.

Evolutionary Implications of Self-Assembling Cybernetic Materials with Collective Problem-Solving Intelligence at Multiple Scales.

In recent years, the scientific community has increasingly recognized the complex multi-scale competency architecture (MCA) of biology, comprising nested layers of active homeostatic agents, each forming the self-orchestrated substrate for the layer above, and, in turn, relying on the structural and functional plasticity of the layer(s) below. The question of how natural selection could give rise to this MCA has been the focus of intense research. Here, we instead investigate the effects of such decision-making competencies of MCA agential components on the process of evolution itself, using in silico neuroevolution experiments of simulated, minimal developmental biology.

Portable Facial Expression System Based on EMG Sensors and Machine Learning Models.

One of the biggest challenges of computers is collecting data from human behavior, such as interpreting human emotions. Traditionally, this process is carried out by computer vision or multichannel electroencephalograms. However, they comprise heavy computational resources, far from final users or where the dataset was made.

GroceryDB: Prevalence of Processed Food in Grocery Stores.

The offering of grocery stores is a strong driver of consumer decisions, shaping their diet and long-term health. While highly processed food like packaged products, processed meat, and sweetened soft drinks have been increasingly associated with unhealthy diet, information on the degree of processing characterizing an item in a store is not straightforward to obtain, limiting the ability of individuals to make informed choices. Here we introduce GroceryDB, a database with over 50,000 food items sold by Walmart, Target, and Wholefoods, unveiling how big data can be harnessed to empower consumers and policymakers with systematic access to the degree of processing of the foods they select, and the potential alternatives in the surrounding food environment.

Development of the Saini-Hodgins Addiction Risk Potential of Games (SHARP-G) Scale: An International Delphi study.

Background And Objectives: As the gaming industry experiences exponential growth, concerns about gaming disorder (GD) also grow. It is crucial to understand the structural features of games that can interact with individual characteristics of gamers to promote GD. This research consolidates the views of an international body of panelists to create an assessment tool for gauging the addictive potential of distinct games.

The SCOPE framework - implementing ideals of responsible research assessment.

Background: Research and researchers are heavily evaluated, and over the past decade it has become widely acknowledged that the consequences of evaluating the research enterprise and particularly individual researchers are considerable. This has resulted in the publishing of several guidelines and principles to support moving towards more responsible research assessment (RRA). To ensure that research evaluation is meaningful, responsible, and effective the International Network of Research Management Societies (INORMS) Research Evaluation Group created the SCOPE framework enabling evaluators to deliver on existing principles of RRA.

Sparse Firing in a Hybrid Central Pattern Generator for Spinal Motor Circuits.

Central pattern generators are circuits generating rhythmic movements, such as walking. The majority of existing computational models of these circuits produce antagonistic output where all neurons within a population spike with a broad burst at about the same neuronal phase with respect to network output. However, experimental recordings reveal that many neurons within these circuits fire sparsely, sometimes as rarely as once within a cycle.

Urban form and COVID-19 cases and deaths in Greater London: An urban morphometric approach.

The COVID-19 pandemic generated a considerable debate in relation to urban density. This is an old debate, originated in mid 19th century's England with the emergence of public health and urban planning disciplines. While popularly linked, evidence suggests that such relationship cannot be generally assumed.

Development and validation of prognostic machine learning models for short- and long-term mortality among acutely admitted patients based on blood tests.

Unlabelled: Several scores predicting mortality at the emergency department have been developed. However, all with shortcomings either simple and applicable in a clinical setting, with poor performance, or advanced, with high performance, but clinically difficult to implement. This study aimed to explore if machine learning algorithms could predict all-cause short- and long-term mortality based on the routine blood test collected at admission.

Metrics reloaded: recommendations for image analysis validation.

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. In biomedical image analysis, chosen performance metrics often do not reflect the domain interest, and thus fail to adequately measure scientific progress and hinder translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics.

Understanding metric-related pitfalls in image analysis validation.

Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence research and its translation into practice. However, increasing evidence shows that, particularly in image analysis, metrics are often chosen inadequately. Although taking into account the individual strengths, weaknesses and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers.

Animal-robot interaction-an emerging field at the intersection of biology and robotics.

The field of animal-robot and organism-robot interaction systems (ARIS, ORIS) is a currently rapidly emerging field in biorobotics. In this special issue we aim for providing a comprehensive overview of the cutting-edge advancements and pioneering breakthroughs within this scientific and engineering discipline. Therefore, we collected scientific articles that delineate and expound upon the complexity of these remarkable biohybrid systems.

Future directions in human mobility science.

We provide a brief review of human mobility science and present three key areas where we expect to see substantial advancements. We start from the mind and discuss the need to better understand how spatial cognition shapes mobility patterns. We then move to societies and argue the importance of better understanding new forms of transportation.

Using sequences of life-events to predict human lives.

Here we represent human lives in a way that shares structural similarity to language, and we exploit this similarity to adapt natural language processing techniques to examine the evolution and predictability of human lives based on detailed event sequences. We do this by drawing on a comprehensive registry dataset, which is available for Denmark across several years, and that includes information about life-events related to health, education, occupation, income, address and working hours, recorded with day-to-day resolution. We create embeddings of life-events in a single vector space, showing that this embedding space is robust and highly structured.

[Digital health applications (DiGA) in the area of tension between progress and criticism : Discussion paper from the "Digital health" specialist group of the German Informatics Society].

Since December 2019, digital health applications (DiGA) have been included in standard care in Germany and are therefore reimbursed by the statutory health insurance funds to support patients in the treatment of diseases or impairments. There are 48 registered DiGA listed in the directory of the Federal Institute of Drugs and Medical Devices (BfArM), mainly in the areas of mental health; hormones and metabolism; and muscles, bones, and joints. In this article, the "Digital Health" specialist group of the German Informatics Society describes the current developments around DiGA as well as the current sentiment on topics such as user-centricity, patient and practitioner acceptance, and innovation potential.