Miracle-dz/UniFAR-FTUs huggingface dataset:
Modifying International Classification of Functioning, Disability, and Health (ICF) to Guide Development of Environmental Interventions for Transfer Performance by Individuals with Disabilities and Their Caregivers

To improve ICF’s utility in guiding design decisions about physical environmental interventions forindividuals with activity limitations and their caregivers, a more robust approach is needed to classify, describe, and measure the task-relevant environmental characteristics that create demands on activity performance. The purpose of this paper is to demonstrate one possible approach, through examination of physical environmental influences that impact caregiver-assisted toilet transfer performance by older adults and their caregivers. By applying the Modified Dyadic ICF in our analysis of caregiver-assisted transfers, we make suggestions for conceptualization of physical environmental factors in the ICF. This work suggests that physical environmental influences in dyadic activity performance are highly dynamic, oftentimes reciprocal, and task-specific. The proposed approach appears to be a feasible method to reveal areas of suboptimal environmental interaction during activity performance, which can be remedied by future environmental design interventions. Future research is needed on additional activities to validate the generalizability of this approach.
Machine Learning Techniques for Prediction of Stress-Related Mental Disorders: A Scoping Review

The goal of this paper is to review the literature on machine learning (ML) and big data applications for mental health, emphasizing current research and practical implementations. To explore the field of ML in mental health, we used a scoping review process. The literature identified application domains of detection and prediction of stress as a contributor to mental health disorders. We evaluated the articles and data on the mental health application, machine learning approach, type of data (sensor, survey, etc.), and type of sensors. Most studies extracted features before developing AI-based stress detection algorithms. Findings revealed that heart rate, heart rate variability, and skin conductance features are the key indicators of stress. Moreover, among AI stress-detection methods, Random Forest and Neural Networks show promising results.
Success by Undesirable Means: Differences in Trust Following Successful (Yet Deviant) Flight Path Adherence

The success or failure of a system can impact one's trust in that system. User trust can also be affected by system behavior (e.g., type of movement, how social it is, human-likeness). However, there remains a gap in understanding the relationship between these two influences. Additionally, few studies have examined trust following differences in the behavior of systems with consistently successful results across behaviors. Therefore, the degree to which the behavior of a system in the pursuit of a successful outcome can influence user trust is unknown. In one experiment, participants were tasked with plotting a path for an Unmanned Aerial Vehicle (UAV) to fly. The UAV deviated from the path by different amounts, between subjects. Despite no differences in measures of performance (the success of the UAV reaching the end destination, time to complete the task, end score, or how far participants had to draw the routes), nor other cognitive constructs (i.e., workload), differences in trust were reported. These results indicate that it is not simply if a system accomplishes a task, but also the way it does that influences trust.
Examination of Within-Headset Sports Media Experiences

With the many varied options for media presentation available within virtual reality devices today, it is important to start comparing these different formats to determine how different they are from each other. This project examined the differences between 180-Degree and 2D presentations of sports media within virtual reality headsets (HMD). Additionally, it also examined how much including individual differences helped explain participant experiences of presence, suspense, and enjoyment. Participants were asked to watch a piece of sports media footage presented either in 180-Degree or 2D formats within their own headset and then complete surveys on presence, suspense, enjoyment, team disposition, and fanship post-watching the video clip. This data was analyzed using a MANOVA and hierarchical linear regression. Results showed that there were no differences between the two types of media presentation, but fanship did help to understand more of the variance within participants’ enjoyment.
Assessing Human Use of Partially-Automated Motor Vehicles: A Subjective Method for Use by Human Factors Experts

This paper describes a pilot test conducted of a quick assessment method in which experts evaluated the safety and usability of partially autonomous vehicles. Two PhD human factors experts drove 3 2018-model-year, partially-automated vehicles (Tesla Model X, Subaru Legacy, and Mazda CX5) and identified safety and usability problems related to the driver interface. From multiple drives of each vehicle over a well-defined course, comments were obtained, and they were classified into 5 safety/usability categories (e.g., not sure what the vehicle did, not sure why it did what it did) with 5 severity levels (cosmetic to catastrophic) in each category. The method was feasible. Planning the route and instrumenting the vehicles proceeded without difficulty, as did the coding of the data. Improvements such as using text-to-speech software (instead of time-consuming manual transcription) to support transcript generation, alternative problem categories, and revised problem severity scoring are described.
Databases for Estimating Task Element Times: An Overview

This article summarizes several databases (aka predetermined time systems) that provide estimated times for task elements (e.g., reach, move a mouse, make a specific decision, make a specific movement) which can be summed to estimate total task time. Databases emphasized include Methods Time Measurement (MTM), Work Factor, the Keystroke-Level Model (KLM), MODAPTS, Society of Automotive Engineers (SAE) Recommended Practice J2365, and the Touchless Hand-Gesture-Level Model. Databases identified were drawn from industrial engineering, human-computer interaction, automotive interfaces, and other sources. In several cases, example element times and tables from these databases are provided to help readers appreciate and understand their content and structure. Also provided are 6 recommendations (e.g., choose the database that meets the analysis accuracy and time requirements; don’t mix databases with and without mental elements or those with different levels of resolution) to guide readers in database selection.
A unified valence scale based on diagnosis of facial expressions

Affect-adaptive systems detect the emotional user state, assess it against the current situation, and adjust interaction accordingly. Tools for real-time emotional state detection, like the Emotient FACET engine (Littlewort et al., 2011), are based on the analysis of facial expressions. When developing affect-adaptive systems, output from the diagnostic engine must be mapped onto theoretical models of emotion. The Circumplex Model of Affect (Russell, 1980) describes emotion on two dimensions: valence and arousal. However, FACET offers three classifiers for valence: positive, neutral, and negative valence. The present study aimed at developing an algorithm that converts these into a unified valence scale. We used FACET to analyze valence-labeled images from the AffectNet database. In a multiple regression analysis, FACET classifier values predicted database valence and explained 38% of the variance. By inserting classifier values into the regression equation, a unified valence scale can be calculated that matches dimensional models of emotion. This research forms the groundwork for adaptation of the emotional user state based on the FACET engine. A future affect-adaptive system can now use the FACET engine to detect the emotional user state on a unified valence dimension, which allows for distinct classification and interpretation of emotions.
Systematic Approach for Comparing Team-based Care Processes

Team-based care process modeling techniques have focused on understanding and designing solutions for a single site. Less is known about tailoring an effective team-based care process from one site to another, which is necessary for multi-site implementation efforts. We propose an approach for analyzing and comparing a team-based care process performed at two sites to inform redesign opportunities. Our approach includes abstracting the goals and strategies of each process by identifying whether sociotechnical system element differences exist. Element differences may exist for the phase, tasks, roles, information, and technology and tools. Differences in system elements may still support process goals and strategies and, thus, be irrelevant for redesign opportunities. We demonstrate the utility of the approach using an operating room to intensive care unit handoff protocol. This approach should be useful for researchers and practitioners that are tailoring and implementing a successful team-based care process at more than one site.
efecto de la atmósfera en la resolución óptica de la Z/I Digital Mapping Camera

Atmospheric influence on the Z/I Digital Mapping Camera optical resolution The Institut Cartografic de Catalunya (ICC) operates the airborne digital camera Z/I Digital Mapping Camera (DMC) for cartographic purposes. This imaging system suffers from certain resolution degradation due to both the optical system and the atmosphere. Therefore, real resolution of the camera is different from purely geometrical pixel size and the Ground Sampling Distance (GSD). In this work, camera resolution loss caused by the atmosphere as a function of the atmospheric radiative conditions is analysed. The resolution in pixel units is evaluated as the Full Width at Half Maximum (FWHM) of the Line Spread Function (LSF) computed from a reconstruction of the Edge Spread Function (ESF). The Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative transfer code is used to simulate the atmosphere. Atmosphere type, aerosol model and total load, illumination and observation geometries and spectral range are taken into account when computing simulations. The described methodology has been applied to an edge radiometric target at ICC test site on Banyoles (Spain) area. A synthetic image of the edge has been processed with the atmospheric simulations and then its resolution analysed to obtain the resolution loss caused by the atmosphere. The simulations results show a high correlation between resolution loss and aerosol model and total load. The results are also compatible with the resolution measures on the real image taken with the camera.
Recruitment, Admissions, Hiring, Retention, and Promotion: Mechanisms of Diversity, Equity, Inclusion (DEI) and Belonging in Higher Education

This panel session is for anyone in human factors and ergonomics (HFE) or related disciplines interested in recruiting, hiring, admitting, retaining, and promoting people within organizations from the perspective of pursuing authentic diversity. Applicants and hiring managers may also gain insight on what makes a meaningful diversity statement, a trending requirement in many degree programs and job applications. Although the panelists featured are from higher education, we welcome hearing from audience members in other industries (e.g., corporate, military, and consulting). Panelists will focus on our experiences crafting admissions or hiring criteria, recruiting and retaining Human Factors and Ergonomics Society (HFES) members, and evaluating the contributions of people in our field that go beyond the traditional bounds of science and engineering yet are central to the future of our profession. The goal of this panel is to foster community and discussion across people and organizations working to improve diversity, equity, inclusion, (DEI) and belonging in HFE.
Pesticide soil microbial toxicity: setting the scene for a new pesticide risk assessment for soil microorganisms (IUPAC Technical Report)

Abstract Pesticides constitute an integral part of modern agriculture. However, there are still concerns about their effects on non-target organisms. To address this the European Commission has imposed a stringent regulatory scheme for new pesticide compounds. Assessment of the aquatic toxicity of pesticides is based on a range of advanced tests. This does not apply to terrestrial ecosystems, where the toxicity of pesticides on soil microorganisms, is based on an outdated and crude test (N mineralization). This regulatory gap is reinforced by the recent methodological and standardization advances in soil microbial ecology. The inclusion of such standardized tools in a revised risk assessment scheme will enable the accurate estimation of the toxicity of pesticides on soil microorganisms and on associated ecosystem services. In this review we (i) summarize recent work in the assessment of the soil microbial toxicity of pesticides and point to ammonia-oxidizing microorganisms (AOM) and arbuscular mycorrhizal fungi (AMF) as most relevant bioindicator groups (ii) identify limitations in the experimental approaches used and propose mitigation solutions, (iii) identify scientific gaps and (iv) propose a new risk assessment procedure to assess the effects of pesticides on soil microorganisms.
Free and self-localized Wannier-Mott excitons in ionic crystals and activation energy of their mutual thermal conversion

The adiabatic approximation (strong-coupling limit) is used in a theoretical analysis of the coexistence of polarizing and nonpolarizing excitons in an ionic crystal. Calculations are made of their energies and of the height of a potential barrier which has to be overcome for conversion from the nonpolarizing to the polarizing exciton state. The difference between the energies of these excitons can change sign with the values of the crystal parameters. The barrier may ensure a long lifetime of the excitons with the higher energy.
Needing: an active inference process for physiological motivation

Need states are internal states that arise from deprivation of crucial biological stimuli. They direct motivation, independently of external learning. Despite their separate origin, they interact with reward processing systems that respond to external stimuli. This paper aims to illuminate the functioning of the needing system through the lens of active inference, a framework for understanding brain and cognition. We propose that need states exert a pervasive influence on the organism, which in active inference terms translates to a “pervasive surprise” - a measure of the distance from the organism’s preferred state. Crucially, we define needing as an active inference process that seeks to reduce this pervasive surprise. Through a series of simulations, we demonstrate that our proposal successfully captures key aspects of the phenomenology and neurobiology of needing. We show that as need states increase, the tendency to occupy preferred states strengthens, independently of external reward prediction. Furthermore, need states increase the precision of states (stimuli and actions) leading to preferred states, suggesting their ability to amplify the value of reward cues and rewards themselves. Collectively, our model and simulations provide valuable insights into the directional and underlying influence of need states, revealing how this influence amplifies the wanting or liking associated with relevant stimuli.
Trait-based predictors of genomic diversity within freshwater fish communities of the Ozarks

Phenotypic traits modulate the fate of species interactions with one another and the environment; thus, traits directly shape the past, present, and future evolutionary trajectories of populations. As such, distinct species-specific responses to a shifting environment are widely documented in the form of distinct genetic signatures, i.e., genetic diversity, reflecting differential responses over time. While the link between genetic diversity and phenotypic traits is seemingly fundamental, it has been challenging to establish unequivocally. Across an exemplar freshwater fish metacommunity, we employ phenotypic traits to test if they are significantly related to observed genetic patterns among species. Associated traits were then used to construct trait-based predictive models of genetic diversity. We collected representative constituents of a freshwater fish community (N=31 species) sampled across 75 sites within the White River Basin (Ozark Plateau, USA). For each species, we derived three genetic diversity indices (=HS/HT/G”ST) from SNP data (N=2,000 loci) and assessed 28 phenotypic traits related to morphology, life history, and ecology. We identified a series of traits (N=2–5, depending upon the index) strongly associated with facets of genetic diversity. These were subsequently applied in predictive models that explained 31–68% of the genetic variability across species, suggesting a potential utility as an imputation tactic for data-deficient species. Our approach effectively linked species-specific traits with genetic diversity within and among populations, thereby further clarifying correlations between contemporary ecological processes, as modulated by species traits, and long-term evolutionary trajectories.
Lmx1a is a master regulator of the cortical hem

Development of the nervous system depends on signaling centers – specialized cellular populations that produce secreted molecules to regulate neurogenesis in the neighboring neuroepithelium. Some signaling centers also generate key types of neurons. The formation of a signaling center involves its induction, the maintenance of expression of its secreted molecules, and cell differentiation and migration events. How these distinct processes are coordinated during signaling center development remains unknown. Here we show that Lmx1a acts as a master regulator to orchestrate the formation and function of the cortical hem (CH), a critical signaling center that controls hippocampus development. Lmx1a co-regulates CH induction, its Wnt signaling, and the differentiation and migration of CH-derived Cajal-Retzius neurons. Combining RNAseq, genetic, and rescue experiments, we identified major downstream genes that mediate distinct Lmx1a-dependent processes. Our work revealed that signaling centers in the mammalian brain employ master regulatory genes and established a framework for analyzing signaling center development.
Dynamo theories

These lecture notes are based on a tutorial given in 2017 at a plasma physics winter school in Les Houches. Their aim is to provide a self-contained graduate-student level introduction to the theory and modelling of the dynamo effect in turbulent fluids and plasmas, blended with a review of current research in the field. The primary focus is on the physical and mathematical concepts underlying different (turbulent) branches of dynamo theory, with some astrophysical, geophysical and experimental contexts disseminated throughout the document. The text begins with an introduction to the rationale, observational and historical roots of the subject, and to the basic concepts of magnetohydrodynamics relevant to dynamo theory. The next two sections discuss the fundamental phenomenological and mathematical aspects of (linear and nonlinear) small- and large-scale magnetohydrodynamic (MHD) dynamos. These sections are complemented by an overview of a selection of current active research topics in the field, including the numerical modelling of the geo- and solar dynamos, shear dynamos driven by turbulence with zero net helicity and MHD-instability-driven dynamos such as the magnetorotational dynamo. The difficult problem of a unified, self-consistent statistical treatment of small- and large-scale dynamos at large magnetic Reynolds numbers is also discussed throughout the text. Finally, an excursion is made into the relatively new but increasingly popular realm of magnetic-field generation in weakly collisional plasmas. A short discussion of the outlook and challenges for the future of the field concludes the presentation.
Genome assembly of 3 Amazonian Morpho butterfly species reveals Z-chromosome rearrangements between closely related species living in sympatry

The genomic processes enabling speciation and the coexistence of species in sympatry are still largely unknown. Here we describe the whole genome sequencing and assembly of three closely-related species from the butterfly genus Morpho: Morpho achilles (Linnaeus, 1758), M. helenor (Cramer, 1776) and M. deidamia (Hübner, 1819). These large blue butterflies are emblematic species of the Amazonian rainforest. They live in sympatry in a wide range of their geographical distribution and display parallel diversification of dorsal wing colour pattern, suggesting local mimicry. By sequencing, assembling and annotating their genomes, we aim at uncovering pre-zygotic barriers preventing gene flow between these sympatric species. We found a genome size of 480 Mb for the three species and a chromosomal number ranging from 2n = 54 for M. deidamia to 2n = 56 for M. achilles and M. helenor. We also detected inversions on the sex chromosome Z that were differentially fixed between species, suggesting that chromosomal rearrangements may contribute to their reproductive isolation. The annotation of their genomes allowed us to recover in each species at least 12,000 protein-coding genes and to discover duplications of genes potentially involved in pre-zygotic isolation like genes controlling colour discrimination (L-opsin). Altogether, the assembly and the annotation of these three new reference genomes open new research avenues into the genomic architecture of speciation and reinforcement in sympatry, establishing Morpho butterflies as a new eco-evolutionary model.
Plasmaspheric plumes: Cluster, IMAGE and simulations

Plasmaspheric plumes have been routinely observed by the CLUSTER and IMAGE missions. CLUSTER provides high time resolution four-point measurements of the plasmasphere. Electron density is derived from the WHISPER sounder supplemented by data from the electric field instrument EFW. The EUV imager onboard IMAGE provides global images of the plasmasphere. We present coordinated observations of one plume event and numerical simulations for its formation based on the interchange instability mechanism. We compare several aspects of the plume motion as determined by different methods: (i) boundary velocity calculated from time delays of plume boundaries observed by WHISPER on all four spacecraft, (ii) ion velocity derived from the ion spectrometer CIS onboard CLUSTER, (iii) drift velocity measured by the electron drift instrument EDI onboard CLUSTER and (iv) global velocity determined from successive EUV images. These different methods consistently indicate that plasmaspheric plumes rotate around the Earth, with their foot fully co-rotating, but with their tip rotating slower and moving farther out.