Miracle-dz/UniFAR-FTUs huggingface dataset:
Nitrogen Cycling and Biosignatures in a Hyperarid Mars Analog Environment

The hyperarid Atacama Desert is a unique Mars-analog environment with a large near-surface soil nitrate reservoir due to the lack of rainfall leaching for millennia. We investigated nitrogen (N) cycling and organic matter dynamics in this nitrate-rich terrestrial environment by analyzing the concentrations and isotopic compositions of nitrate, organic C, and organic N, coupled with microbial pathway-enzyme inferences, across a naturally occurring rainfall gradient. Nitrate deposits in sites with an annual precipitation of <10 mm carry atmospheric δ15N, δ18O, and Δ17O signatures, while these values are overprinted by biological cycling in sites with >15 mm annual precipitation. Metagenomic analyses suggest that the Atacama Desert harbors a unique biological nitrogen cycle driven by nitrifier denitrification, nitric oxide dioxygenase-driven alternative nitrification, and organic N loss pathways. Nitrate assimilation is the only nitrate consumption pathway available in the driest sites, although some hyperarid sites also support organisms with ammonia lyase- and nitric oxide synthase-driven organic N loss. Nitrifier denitrification is enhanced in the “transition zone” desert environments, which are generally hyperarid but see occasional large rainfall events, and shifts to nitric oxide dioxygenase-driven alternative nitrifications in wetter arid sites. Since extremophilic microorganisms tend to exploit all reachable nutrients, both N and O isotope fractionations during N transformations are reduced. These results suggest that N cycling on the more recent dry Mars might be dominated by nitrate assimilation that cycles atmospheric nitrate and exchanges water O during intermittent wetting, resulting stable isotope biosignatures could shift away from martian atmospheric nitrate endmember. Early wetter Mars could nurture putative life that metabolized nitrate with traceable paleoenvironmental isotopic markers similar to microbial denitrification and nitrification stored in deep subsurface.
Body composition changes during the lockdown-restart transition due to the SARS-CoV-2 pandemic in a group of professional football players.

BACKGROUND At the beginning of March 2020, because of the ongoing pandemic, all sport events were suspended in Italy. The Italian Serie A league abruptly interrupted all competitions and teams could not train in a group anymore. These containment measures were gradually eased in May. The aim of this study was to ascertain the impact of the lockdown-restart transition on the body composition of a group of Italian footballers of a Serie A team during the pandemic. METHODS The body composition of 18 male football players (age27.6 ± 4.5 yr.) from an Italian Serie A team was studied by bioelectrical impedance (BIA). Measures were conducted after lockdown, when they restarted to train in group with the ball (T0), and after the first regular match (T1). RESULTS Results show that there were no changes in body mass, body mass index, fat mass, fat-free mass, and total body water between T0 and T1. Differently, intracellular water, extracellular water, and phase angle were changed. CONCLUSIONS We concluded that the lockdown did not have any impact in athletes' body composition as they kept training at home. Moreover, the BIA method was able to detect subtle signals of shift in body water compartments (intra cellular and extra cellular water) likely due to the different kind of training conducted during and after the lockdown.
Biomarkers, Clinical Variables, and the CHA2DS2-VASc Score to Detect Silent Brain Infarcts in Atrial Fibrillation Patients

Philipp Krisai, Ceylan Eken, Stefanie Aeschbacher, Michael Coslovsky, Vinzent Rolny, Desirée Carmine, Lorenzo Grazioli Gauthier, Jürg Beer, Laurent Roten, Oliver Baretella, Nicolas Rodondi, Leo H. Bonati, Christine S. Zuern, Christian Müller, David Conen, Michael Kühne, Stefan Osswald, for the Swiss-AF study investigators Cardiovascular Research Institute Basel, University Hospital Basel, Basel, Switzerland Electrophysiology and Ablation Unit and L’Institut de Rythmologie et Modélisation Cardiaque (LIRYC), University Hospital Bordeaux, BordeauxPessac, France Department of Cardiology, University Hospital Basel, Basel, Switzerland Roche Diagnostics GmbH, Penzberg, Germany Department of Internal Medicine, Regional Hospital Lugano, Ticino, Switzerland Department of Internal Medicine, Cantonal Hospital Baden, Baden, Switzerland Department of Cardiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland Department of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland Department of Neurology, University Hospital Basel, Basel, Switzerland Population Health Research Institute, McMaster University, Hamilton, ON, Canada Journal of Stroke 2021;23(3):449-452 https://doi.org/10.5853/jos.2021. 02068
High prevalence of HIV-1 transmitted drug resistance and factors associated with time to virological failure and viral suppression in Taiwan.

BACKGROUND Integrase strand transfer inhibitor (InSTI)-based regimens have become the major first-line treatment for HIV-1-infected patients in Taiwan. Transmitted drug resistance (TDR) and several clinical characteristics are associated with time to virological failure or viral suppression; however, these have not been investigated in Taiwan. OBJECTIVES To determine the impact of several factors on treatment outcomes in HIV-1-infected patients in Taiwan. METHODS The cohort included 164 HIV-1 treatment-naive patients in Taiwan from 2018 to 2020. Blood specimens were collected to determine the genotypic drug resistance using the Stanford University HIV drug resistance database. Cox proportional hazards models were used to identify factors associated with time to virological failure or viral suppression. RESULTS The prevalence of TDR in Taiwan was 27.4% and an increasing trend was seen from 2018 to 2020. TDR mutations related to NNRTIs were the most prevalent (21%) while TDR to InSTIs remained at a relatively low level (1.3%). A baseline HIV-1 viral load of ≥100 000 copies/mL was associated with a shorter time to virological failure [multivariate hazard ratio (mHR) 7.84; P = 0.018] and longer time to viral suppression (mHR 0.46; P < 0.001). Time to viral suppression was shorter in patients receiving InSTI-based regimens (mHR 2.18; P = 0.006). Different InSTI-based regimens as initial treatment did not affect the treatment outcomes. CONCLUSIONS This study found an increasing trend of HIV-1 TDR prevalence from 2018 to 2020 in Taiwan. Baseline HIV-1 viral load and receiving InSTI-based regimens are important factors associated with time to virological failure or viral suppression.
Overtrusting robots: Setting a research agenda to mitigate overtrust in automation

Abstract There is increasing attention given to the concept of trustworthiness for artificial intelligence and robotics. However, trust is highly context-dependent, varies among cultures, and requires reflection on others’ trustworthiness, appraising whether there is enough evidence to conclude that these agents deserve to be trusted. Moreover, little research exists on what happens when too much trust is placed in robots and autonomous systems. Conceptual clarity and a shared framework for approaching overtrust are missing. In this contribution, we offer an overview of pressing topics in the context of overtrust and robots and autonomous systems. Our review mobilizes insights solicited from in-depth conversations from a multidisciplinary workshop on the subject of trust in human–robot interaction (HRI), held at a leading robotics conference in 2020. A broad range of participants brought in their expertise, allowing the formulation of a forward-looking research agenda on overtrust and automation biases in robotics and autonomous systems. Key points include the need for multidisciplinary understandings that are situated in an eco-system perspective, the consideration of adjacent concepts such as deception and anthropomorphization, a connection to ongoing legal discussions through the topic of liability, and a socially embedded understanding of overtrust in education and literacy matters. The article integrates diverse literature and provides a ground for common understanding for overtrust in the context of HRI.
Psychological Adjustment, Quality of Life and Well-Being in a German and Portuguese Adult Population During COVID-19 Pandemics Crisis

Introduction: The pandemics crisis had consequences in psychological adjustment of persons all over the world. The current study analyzes comparatively the topics of quality of life, and well-being, considering as predictors trait anxiety, feeling of threat, difficulty to relax, empathy and pro-social attitude, health care, sleep quality and optimism, in a population of German and Portuguese adults during the pandemics, in order to obtain a deeper understanding of the psychological reactions to crisis across countries and cultures. Methods: A sample of 470 adults divided in three age groups – —young adults (18—34 years), middle-age adults (34–54 years) and old adults (55 years and older)— completed a self-report questionnaire assessing socio-demographic data, quality of life, well-being, quality of sleep, trait anxiety, Coronavirus threat, optimism regarding the pandemics, difficulty to relax, empathy, and pro-social attitude during the pandemics period. Results: Portuguese participants expresses higher empathy and pro-social attitude and health care but in Germany people have higher quality of sleep. Young adults (a) rated their quality of life lower than middle-age adults and old adults, (b) showed also lower optimism than middle-age and old adults, and (c) showed lower well-being than middle-age,. Conclusions: Young adults rated their quality of life, optimism and well-being during pandemics lower than middle-age and old adults, and experienced higher levels of trait anxiety and difficulty to relax. It seems that young adults show a lower psychological adjustment than other age groups during COVID-19 crisis. It is concluded that quality of life, optimism, and well-being during the pandemics are affected differently according to country and group of age, suggesting individual differences across cultures and ages, and consequently the need of specific interventions to cope with the psychological reactions to pandemics crisis.
Voxel-Wise Quantitative Mapping of the Brain Association Ability

The association cortices of the brain are essential for integrating multimodal information that subserves complex and high-order cognitive functions. To delineate the changing pattern of associative cortices can provide critical insight into brain development, aging, plasticity, and disease-triggered functional abnormalities. However, how to quantitatively characterize the association capability of the brain is elusive. Here, we developed a new method of association index (Asso) at the voxel level to quantitatively characterize the brain association ability. Using the Asso method, we found high Asso values in association cortical networks, and low values in visual and limbic networks, suggesting a pattern of significant gradient distribution in neural functions. The spatial distribution patterns of Asso show high similarities across different thresholds suggesting that Asso mapping is a threshold-free method. In addition, compared with functional connectivity strength, i.e., degree centrality method, Asso mapping showed different patterns for association cortices and primary cortices. Finally, the Asso method was applied to investigate aging effects and identified similar findings with previous studies. All these results indicated that Asso can characterize the brain association patterns effectively and open a new avenue to reveal a neural basis for development, aging, and brain disorders.
Cyclical Patterns Affect Microbial Dynamics in the Water Basin of a Nuclear Research Reactor

The BR2 nuclear research reactor in Mol, Belgium, runs in successive phases of operation (cycles) and shutdown, whereby a water basin surrounding the reactor vessel undergoes periodic changes in physico-chemical parameters such as flow rate, temperature, and radiation. The aim of this study was to explore the microbial community in this unique environment and to investigate its long-term dynamics using a 16S rRNA amplicon sequencing approach. Results from two sampling campaigns spanning several months showed a clear shift in community profiles: cycles were mostly dominated by two Operational Taxonomic Units (OTUs) assigned to unclassified Gammaproteobacterium and Pelomonas, whereas shutdowns were dominated by an OTU assigned to Methylobacterium. Although 1 year apart, both campaigns showed similar results, indicating that the system remained stable over this 2-year period. The community shifts were linked with changes in physico-chemical parameters by Non-metric Multidimensional Scaling (NMDS) and correlation analyses. In addition, radiation was hypothesized to cause a decrease in cell number, whereas temperature had the opposite effect. Chemoautotrophic use of H2 and dead cell recycling are proposed to be used as a strategies for nutrient retrieval in this extremely oligotrophic environment.
How can we help? Towards a design framework for performance-accommodation mechanisms for users struggling with input

Maintaining balance between challenge and skills in games is critical for enjoyment, and can be applied to accommodate player performance as well as system performance for low accuracy input devices. Previous work has explored different performance-accommodation mechanisms (PAMs) for balancing, but studies have focused mainly on variables not directly related to how the PAMs lower challenge level. This paper identifies different levels of PAMs, then offers a first attempt at a coherent framework of action-level PAMs based on how they modify the mapping from player input to output.
The Impact of Social Proof on Moral Decision-Making in Video Games

When we make ethical decisions in everyday life, our choices are often influenced by what we see others doing around us. In psychology, this phenomenon is known as social proof. When we are uncertain about what to do, we are likely to follow the crowd, especially if we identify with them. In this study, we examine how this behaviour extends to video games, and how it is influenced by other design factors such as time-limited decisions. We present the results of a quantitative study of player behaviour in a visual-novel game The Great Fire. Before making a decision, players are presented with statistics showing what other players chose. We manipulated these figures to display different choices as popular, under timed and untimed conditions. We present preliminary work-in-progress results that suggest that players are indeed influenced to follow the crowd when facing an ambiguous moral decision, but can also show unexpected behaviour when faced with the non-moral choice of calling a coin flip.
Transfer Spatio-Temporal Knowledge from Emotion-Related Tasks for Facial Expression Spotting

Facial micro-expression computational analyses are becoming a prevalent research area, automatically micro-expression spotting as the first-in-the-pipeline problem has not been resolved yet. There are two main factors that confine the performance of current studies. 1) Subtle involuntary movements of micro-expression are hard to capture. 2) Micro-expression datasets are relatively small that can not fully support the training of deep neural networks. For the first problem, we propose modeling the expression movements from the view of consecutive frames in the wavelet space as temporal features. Combined with spatial features encoded by a convolutional neural network, temporal and spatial information can supplement each other in further analyses. For the second problem, we adopt transfer learning from other emotion-related tasks since the facial prior is homologous to our task. To train our model, we covert the spotting task to a frame-level classification task, meanwhile, weighted focal loss is used to deal with severe class imbalance. With leave-one-subject-out cross-validation, our method reports F1-score of 0.1763 and 0.1360 for CAS(ME)2 and SAMM-LV respectively. Code is available at https://github.com/guanjz20/MM21_FME_solution.
Inclusive Voice Interaction Techniques for Creative Object Positioning

People with physical impairments can experience challenges when using traditional input devices such as a mouse and keyboard for creative visual design work. Speech interaction is an alternative input method that can facilitate a more inclusive approach for supporting creative work. However, there has been a lack of work to date investigating how to position and move creative assets (e.g. images) around a digital workspace via speech interaction techniques. We present three multimodal speech interaction approaches to support the positioning of graphical objects around a design canvas via speech commands: Speed-based Control, Location Guides, and Positional Guides. A user evaluation with non-disabled participants (N=30) found that the Location Guides approach was significantly more efficient, accurate, and usable for the positioning of images when compared with the other methods. A follow-up study with physically impaired users (N=6) demonstrated they were able to effectively position images around a design canvas using the Location Guides technique with participants also rating this approach as exhibiting a high level of usability.
Towards Sonification in Multimodal and User-friendlyExplainable Artificial Intelligence

We are largely used to hearing explanations. For example, if someone thinks you are sad today, they might reply to your “why? ” with “because you were so Hmmmmm-mmm-mmm”. Today’s Artificial Intelligence (AI), however, is – if at all – largely providing explanations of decisions in a visual or textual manner. While such approaches are good for communication via visual media such as in research papers or screens of intelligent devices, they may not always be the best way to explain; especially when the end user is not an expert. In particular, when the AI’s task is about Audio Intelligence, visual explanations appear less intuitive than audible, sonified ones. Sonification has also great potential for explainable AI (XAI) in systems that deal with non-audio data – for example, because it does not require visual contact or active attention of a user. Hence, sonified explanations of AI decisions face a challenging, yet highly promising and pioneering task. That involves incorporating innovative XAI algorithms to allow pointing back at the learning data responsible for decisions made by an AI, and to include decomposition of the data to identify salient aspects. It further aims to identify the components of the preprocessing, feature representation, and learnt attention patterns that are responsible for the decisions. Finally, it targets decision-making at the model-level, to provide a holistic explanation of the chain of processing in typical pattern recognition problems from end-to-end. Sonified AI explanations will need to unite methods for sonification of the identified aspects that benefit decisions, decomposition and recomposition of audio to sonify which parts in the audio were responsible for the decision, and rendering attention patterns and salient feature representations audible. Benchmarking sonified XAI is challenging, as it will require a comparison against a backdrop of existing, state-of-the-art visual and textual alternatives, as well as synergistic complementation of all modalities in user evaluations. Sonified AI explanations will need to target different user groups to allow personalisation of the sonification experience for different user needs, to lead to a major breakthrough in comprehensibility of AI via hearing how decisions are made, hence supporting tomorrow’s humane AI’s trustability. Here, we introduce and motivate the general idea, and provide accompanying considerations including milestones of realisation of sonifed XAI and foreseeable risks.
Enhancing Ultrasound Haptics with Parametric Audio Effects

Ultrasound haptic devices can create parametric audio as well as contactless haptic feedback. We investigate if multimodal output from these devices can influence the perception of haptic feedback. We used a magnitude estimation experiment to evaluate perceived roughness of an ultrasound haptic pattern. We found that white noise audio from the haptics device increased perceived roughness and pure tones did not, and that lower rendering frequencies may increase perceived roughness. Our results show that multimodal output has the potential to expand the range of sensations that can be presented by an ultrasound haptic device, paving the way to richer mid-air haptic interfaces.
Potentials of a web-based gamification guidance for knowledge transfer between research and industry

Research results show that gamification can influence emotions, motivation and behavior. However, in order to apply the results in the software development in industry, they need to be easily accessible. To enable a knowledge transfer, a concept and a prototype for an interactive web-based tool were designed to summarize and visualize existing research results and practical examples in a simplified way regarding the use of gamification elements. Step by step, the user defines parameters such as context of use, age, gender and user type for the target group. Based on this, effects in research results are presented simplified and sorted in four categories in pie charts. This is intended to provide users in the industry with the competence to select appropriate gamification elements for their usage. The approach was developed in a user-centered way, including pre-study interviews with seven participants from research and / or industry, and then evaluated using a clickable prototype and qualitative open interviews. Potentials for industry and research were examined. The approach was perceived as supportive in selecting appropriate gamification elements for use in industry. It may lead to faster finding of research results, promote networking and may generate a kind of meta review. The elaboration of such tools may support the interconnection between research and industry, as well as the transfer and applicability of knowledge in gamification.
Socially Informed AI for Healthcare: Understanding and Generating Multimodal Nonverbal Cues

Advances in the areas of face and gesture analysis, computational paralinguistics, multimodal interaction, and human-computer interaction have all played a major role in shaping research into assistive technologies over the last decade. This has resulted in a breadth of practical applications ranging from diagnosis and treatment tools to social companion technologies. From an analytical perspective, nonverbal cues provide understanding into the assessment of mental health and wellbeing (i.e., detecting depression and pain) and the detection of developmental and neurological conditions such as autism, dementia, and schizophrenia. From both a synthesis and generative perspective, it is necessary that assistive technologies, either disembodied or embodied, are capable of generating engaging, interactive behaviours and interventions that are personalised and adapted to user’s needs, profiles, and preferences. While nonverbal cues play an essential role, there are still many key issues to overcome, which affect both the development and the deployment of multimodal technologies in real-world settings. The key aim of this multidisciplinary workshop is to foster cross-pollination by bringing together computer scientists and social psychologists to discuss innovative ideas, challenges and opportunities for understanding and generating multimodal nonverbal cues within the scope of healthcare applications1.