Miracle-dz/UniFAR-FTUs huggingface dataset:
Edinburgh Research Explorer Predictions, precision, and agentive attention

Ransom, Fazelpour, and Mole (this journal - 2017) raise an important puzzle for the ‘prediction error minimization’ account of cognitive processing. That account depicts all cognitive processing as fundamentally in the business of minimizing prediction errors concerning the evolving flow of sensory information. One of the cornerstones of these highly ambitious, would-be unifying accounts is their depiction of attention as nothing other than the process of optimizing the precision (inverse variance) of critical prediction error signals. But that story, Ransom et al suggest, cannot accommodate voluntary shifts of attention. In this paper, I show why this challenge to the grand unifying project fails. It fails because it locates the origins of voluntary attention in complexes of unanalyzed desire rather than in changing complexes of beliefs. Abstract Ransom, Fazelpour, and Mole (this journal - 2017) raise an important puzzle for the ‘prediction error minimization’ account of cognitive processing. That account depicts all cognitive processing as fundamentally in the business of minimizing prediction errors concerning the evolving flow of sensory information. One of the cornerstones of these highly ambitious, would-be unifying accounts is their depiction of attention as nothing other than the process of optimizing the precision (inverse variance) of critical prediction error signals. But that story, Ransom et al suggest, cannot accommodate voluntary shifts of attention. In this paper, I show why this challenge to the grand unifying project fails. It fails because it locates the origins of voluntary attention in complexes of unanalyzed desire rather than in changing complexes of beliefs.
Solanaceae: a model for linking genomics with biodiversity : Comparative and functional genomics

Recent progress in understanding the phylogeny of the economically important plant family Solanaceae makes this an ideal time to develop models for linking the new data on plant genomics with the huge diversity of naturally occurring species in the family. Phylogenetics provides the framework with which to investigate these linkages but, critically, good species-level descriptive resources for the Solanaceae community are currently missing. Phylogeny in the family as a whole is briefly reviewed, and the new NSF Planetary Biodiversity Inventories project 'PBI: Solanum - a worldwide treatment' is described. The aims of this project are to provide species-level information across the global scope of the genus Solanum and to make this available over the Internet. The project is in its infancy, but will make available nomenclatural information, descriptions, keys and illustrative material for all of the approximately 1500 species of Solanum. With this project, the opportunity of linking valid, up-to-date taxonomic information about wild species of Solanum with the genomic information being generated about the economically important species of the genus (potato, tomato and eggplant) can be realized. The phylogenetic framework in which the PBI project is set is also of enormous potential benefit to other workers on Solanum. The community of biologists working with Solanaceae has a unique opportunity to effectively link genomics and taxonomy for better understanding of this important family, taking plant biology to a new level for the next century.
Does Lidocaine Shorten Seizure Duration in Electroconvulsive Therapy?

Abstract Background Electroconvulsive therapy (ECT) is an effective short-term treatment for schizophrenia and depression, amongst other disorders. Lidocaine is typically added to reduce pain from intravenous propofol injection. However, depending on the dose used in the ECT setting, it can shorten seizure duration. The aim of this study was to investigate the effect of lidocaine dose on seizure duration. Methods This retrospective, naturalistic cohort study included 169 patients treated with ECT. We examined 4714 ECT sessions with propofol or propofol plus lidocaine. Ictal quality was manually rated by visual inspection. The main outcome of this study was the relation of lidocaine with seizure duration after controlling for socio-demographic, ECT, and other anesthetic variables. Results There was a significant negative association between lidocaine usage and seizure duration. Multivariate analyses showed that seizure duration was shortened by an average of 3.21 s in sessions with lidocaine. Moreover, in this subgroup, there was a significant negative dose-dependent association between lidocaine dose and seizure length. Complementarily, a significant positive association between preictal BIS and seizure length was found in the subgroup of sessions where preictal was used. Conclusions We provide additional evidence highlighting the importance of caution regarding lidocaine dosing due to the effect on seizure length in the ECT setting. It is advisable for clinicians to exercise caution when administering lidocaine regarding its dosing and seizure length in ECT settings. Future investigation is needed to assess causal relationships by studying certain vulnerable groups or employing other charge calculation techniques, such as the titration method.
Unistrand piRNA clusters are an evolutionarily conserved mechanism to suppress endogenous retroviruses across the Drosophila genus

The PIWI-interacting RNA (piRNA) pathway prevents endogenous genomic parasites, transposable elements, from damaging the genetic material of animal gonadal cells. Specific regions in the genome, called piRNA clusters, are thought to define each species’ piRNA repertoire and therefore its capacity to recognize and silence specific transposon families. The unistrand cluster flamenco (flam) is essential in the somatic compartment of the Drosophila ovary to restrict Gypsy-family transposons from infecting the neighbouring germ cells. Disruption of flam results in transposon derepression and sterility, yet it remains unknown whether this silencing mechanism is present more widely. Here, we systematically characterised 119 Drosophila species and identify five additional flam-like clusters separated by up to 45 million years. Small RNA-sequencing validated these as bona-fide unistrand piRNA clusters expressed in somatic cells of the ovary, where they selectively target transposons of the Gypsy family. Together, our study provides compelling evidence of a widely conserved transposon silencing mechanism that co-evolved with virus-like Gypsy-family transposons.
Measurement of stress-induced sympathetic nervous activity using multi-wavelength PPG

The onset of stress triggers sympathetic arousal (SA), which causes detectable changes to physiological parameters such as heart rate, blood pressure, dilation of the pupils and sweat release. The objective quantification of SA has tremendous potential to prevent and manage psychological disorders. Photoplethysmography (PPG), a non-invasive method to measure skin blood flow changes, has been used to estimate SA indirectly. However, the impact of various wavelengths of the PPG signal has not been investigated for estimating SA. In this study, we explore the feasibility of using various statistical and nonlinear features derived from peak-to-peak (AC) values of PPG signals of different wavelengths (green, blue, infrared and red) to estimate stress-induced changes in SA and compare their performances. The impact of two physical stressors: and Hand Grip are studied on 32 healthy individuals. Linear (Mean, s.d.) and nonlinear (Katz, Petrosian, Higuchi, SampEn, TotalSampEn) features are extracted from the PPG signal’s AC amplitudes to identify the onset, continuation and recovery phases of those stressors. The results show that the nonlinear features are the most promising in detecting stress-induced sympathetic activity. TotalSampEn feature was capable of detecting stress-induced changes in SA for all wavelengths, whereas other features (Petrosian, AvgSampEn) are significant (AUC ≥ 0.8) only for IR and Red wavelengths. The outcomes of this study can be used to make device design decisions as well as develop stress detection algorithms.
Infectious diseases may have arrested the southward advance of microblades in Upper Palaeolithic East Asia

An unsolved archaeological puzzle of the East Asian Upper Palaeolithic is why the southward expansion of an innovative lithic technology represented by microblades stalled at the Qinling–Huaihe Line. It has been suggested that the southward migration of foragers with microblades stopped there, which is consistent with ancient DNA studies showing that populations to the north and south of this line had differentiated genetically by 19 000 years ago. Many infectious pathogens are believed to have been associated with hominins since the Palaeolithic, and zoonotic pathogens in particular are prevalent at lower latitudes, which may have produced a disease barrier. We propose a mathematical model to argue that mortality due to infectious diseases may have arrested the wave-of-advance of the technologically advantaged foragers from the north.
Declining Unionization and the Despair of the Working Class

While the effects of labor unions on objective conditions have been extensively studied, little is known about their role in individuals’ perceptions of economic circumstances. We investigate whether union density affects the subjective well-being of area residents by exploiting the staggered adoption of right-to-work laws in the United States through a border-county design. We find that unionization promotes happiness for those of low socioeconomic status, including non-college-educated residents and current or former blue-collar job holders, but has no discernible impact on their high-status counterparts. Of affected residents, workers stand to reap the most benefit. We also find that the favorable effect of unionization is transmitted through the assessment of improved financial situation, personal health, and workplace quality. This finding highlights the role of pecuniary and nonpecuniary benefits (for example, on-the-job safety, work-life balance, interpersonal trust, and workers’ autonomy) that unions afford to protect society’s most marginalized groups.
of Geophysical Research : Atmospheres Evaluating the advective Brewer-Dobson circulation in three reanalyses for the period 1979 – 2012

Most chemistry-climate models show an intensification of the Brewer-Dobson circulation (BDC) in the stratosphere associated with increasing greenhouse gas emissions and ozone depletion in the last decades, but this trend remains to be confirmed in observational data. In this work the evolution of the advective BDC for the period 1979–2012 is evaluated and compared in three modern reanalyses (ERA-Interim, MERRA, and JRA-55). Three different estimates of the BDC are computed for each reanalysis, one based on the definition of the residual circulation and two indirect estimates derived from momentum and thermodynamic balances. The comparison among the nine estimates shows substantial uncertainty in the mean magnitude (∼40%) but significant common variability. The tropical upwelling series show variability linked to the stratospheric quasi-biennial oscillation and to El Niño– Southern Oscillation (ENSO) and also reflect extreme events such as major sudden stratospheric warmings and volcanic eruptions. The trend analysis suggests a strengthening of tropical upwelling of around 2–5%/decade throughout the layer 100–10 hPa. The global spatial structure of the BDC trends provides evidence of an overall acceleration of the circulation in both hemispheres, with qualitative agreement among the estimates. The global BDC trends are mainly linked to changes in the boreal winter season and can be tracked to long-term increases in the resolved wave drag in both hemispheres.
MeLoDy: A Long-Term Dynamic Quality-Aware Incentive Mechanism for Crowdsourcing

Crowdsourcing allows requesters to allocate tasks to a group of workers on the Internet to make use of their collective intelligence. Quality control is a key design objective in incentive mechanisms for crowdsourcing as requesters aim at obtaining high-quality answers under a limited budget. However, when measuring workers’ long-term quality, existing mechanisms either fail to utilize workers’ historical information, or treat workers’ quality as stable and ignore its temporal characteristics, hence performing poorly in a long run. In this paper we propose <sc>MeLoDy</sc>, a long-term dynamic quality-aware incentive mechanism for crowdsourcing. <sc> MeLoDy</sc> models interaction between requesters and workers as reverse auctions that run continuously. In each run of <sc>MeLoDy</sc>, we design a truthful, individual rational, budget feasible and quality-aware algorithm for task allocation with polynomial-time computation complexity and <inline-formula><tex-math notation="LaTeX">$O(1)$</tex-math> <alternatives><inline-graphic xlink:href="wang-ieq1-2775232.gif"/></alternatives></inline-formula> performance ratio. Moreover, taking into consideration the long-term characteristics of workers’ quality, we propose a novel framework in <sc>MeLoDy</sc> for quality inference and parameters learning based on Linear Dynamical Systems at the end of each run, which takes full advantage of workers’ historical information and predicts their quality accurately. Through extensive simulations, we demonstrate that <sc>MeLoDy</sc> outperforms existing work in terms of both quality estimation (reducing estimation error by <inline-formula><tex-math notation="LaTeX">$17.6\% \sim 24.2\%$ </tex-math><alternatives><inline-graphic xlink:href="wang-ieq2-2775232.gif"/></alternatives></inline-formula>) and social performance (increasing requester's utility by <inline-formula><tex-math notation="LaTeX">$18.2\% \sim 46.6\%$</tex-math><alternatives><inline-graphic xlink:href="wang-ieq3-2775232.gif"/></alternatives></inline-formula>) in long-term scenarios.
GENESIS CGDYN: large-scale coarse-grained MD simulation with dynamic load balancing for heterogeneous biomolecular systems

Residue-level coarse-grained (CG) molecular dynamics (MD) simulation is widely used to investigate slow biological processes that involve multiple proteins, nucleic acids, and their complexes. Biomolecules in a large simulation system are distributed non-uniformly, limiting computational efficiency with conventional methods. Here, we develop a hierarchical domain decomposition scheme with dynamic load balancing for heterogeneous biomolecular systems to keep computational efficiency even after drastic changes in particle distribution. The new schemes are applied to intrinsically disordered protein (IDP) droplet fusions. The droplet shape changes correlate with mixing IDP chains from two droplets. We also simulate formations of large IDP droplets, whose sizes are almost equivalent to those observed in microscopy. The methods have been implemented in CGDYN of the GENESIS software, which provides a new tool for investigating mesoscopic biological phenomena using the residue-level CG models.
An index of river health for river plain network regions.

We propose a new concept ― "water health" ― based on ecological health to describe the degradation of aquatic ecosystems in relation to human-induced watershed alterations, and present a partial application of these ideas in a river plain network region. An indicator framework for the analysis and assessment of "water health" is presented which takes environmental, ecological, landscape and social service functions into consideration. The meaning and method of determination of each indicator is described. The entropy method was adopted to calculate the weight of index, applying the weighted sum model. These approaches were implemented to assess the four main functions of "water health" for Xinghua city, China. It was found that the water quality is inferred as being only lightly polluted ― "the general stage"; ecological and landscape functions were also in this category. In addition, large-scale exploitation of the social service function has also influenced the regional environment to some extent.
Clinical Study Heart Rate Variability Is Associated with Survival in Patients with Brain Metastasis : A Preliminary Report

1 Institute of Physiology, National Yang-Ming University, Beitou, Taipei 11221, Taiwan 2Department of Radiation Oncology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Niao-Sung, Kaohsiung 83306, Taiwan 3Department of Mathematics, Stanford University, Stanford, CA 94305, USA 4 School of Traditional Chinese Medicine, College of Medicine, Chang Gung University, Kwei-Shan, Taoyuan 33302, Taiwan 5Department of Anesthesiology, Taipei Veterans General Hospital, Beitou, Taipei 11217, Taiwan
Open Research Online Bias in data-driven artiﬁcial intelligence systems - An introductory survey

Artificial Intelligence (AI)-based systems are widely employed nowadays to make decisions that have far-reaching impact on individuals and society. Their decisions might affect everyone, everywhere, and anytime, entailing concerns about potential human rights issues. Therefore, it is necessary to move beyond tradi-tional AI algorithms optimized for predictive performance and embed ethical and legal principles in their design, training, and deployment to ensure social good while still benefiting from the huge potential of the AI technology. The goal of this survey is to provide a broad multidisciplinary overview of the area of bias in AI systems, focusing on technical challenges and solutions as well as to suggest new research directions towards approaches well-grounded in a legal frame. In this survey, we focus on data-driven AI, as a large part of AI is powered nowadays by (big) data and powerful machine learning algorithms. If otherwise not specified, we use the general term bias to describe problems related to the gather-ing or processing of data that might result in prejudiced decisions on the bases of demographic features such as race, sex, and so forth. This article is categorized under: and this paper, we survey recent technical approaches on bias and fairness in AI-based decision-making systems, we discuss their legal ground 2 as well as open challenges and directions towards AI-solutions for societal good. We divide the works into three broad categories:
Accessibility Research in Digital Audiovisual Media: What Has Been Achieved and What Should Be Done Next?

The consumption of digital audiovisual media is a mainstay of many people’s lives. However, people with accessibility needs often have issues accessing this content. With a view to addressing this inequality, there exists a wide range of interventions that researchers have explored to bridge this accessibility gap. Despite this work, our understanding of the capability of these interventions is poor. In this paper, we address this through a systematic review of the literature, creating a dataset of and analysing N = 181 scientific papers. We have found that certain areas have accrued a disproportionate amount of attention from the research community – for example, blind and visually impaired and d/Deaf and hard of hearing people account for of papers (N = 170). We describe challenges researchers have addressed, end-user communities of focus, and interventions examined. We conclude by evaluating gaps in the literature and areas that could use more focus on in the future.
A Preliminary Study of the Eye Tracker in the Meta Quest Pro

This paper presents the preliminary results of an accuracy testing of the Meta Quest Pro’s eye tracker. We conducted user testing to evaluate the spatial accuracy, spatial precision and subjective performance under head-free and head-restrained conditions. Our measurements indicated an average accuracy of 1.652° with a precision of 0.699° (standard deviation) and 0.849° (root mean square) for a visual field spanning 15° during head-free. The signal quality of Quest Pro’s eye-tracker is comparable to existing AR/VR eye-tracking headsets. Notably, careful considerations are required when designing the size of scene objects, mapping areas of interest, and determining the interaction flow. Researchers should also be cautious about interpreting the fixation results when multiple targets are within close proximity. Further investigation and better specification information transparency are needed to establish its capabilities and limitations.
Towards User Guided Actionable Recourse

Machine Learning’s proliferation in critical fields such as healthcare, banking, and criminal justice has motivated the creation of tools which ensure trust and transparency in ML models. One such tool is Actionable Recourse (AR) for negatively impacted users. AR describes recommendations of cost-efficient changes to a user’s actionable features to help them obtain favorable outcomes. Existing approaches for providing recourse optimize for properties such as proximity, sparsity, validity, and distance-based costs. However, an often-overlooked but crucial requirement for actionability is a consideration of User Preference to guide the recourse generation process. In this work, we attempt to capture user preferences via soft constraints in three simple forms: i) scoring continuous features, ii) bounding feature values and iii) ranking categorical features. Finally, we propose a gradient-based approach to identify User Preferred Actionable Recourse (UP-AR). We carried out extensive experiments to verify the effectiveness of our approach.
A VR Intervention Based on Social Story™ to Develop Social Skills in Children with ASD

Social interactions and communication play a crucial role in people’s lives. Those with autism spectrum disorder (ASD), especially children, may have difficulties participating in social interactions. Such challenges can be characterised by displaying atypical behaviours and limited sharing intention in social settings. Sharing is an important part of social interaction, and a lack of awareness or limited willingness to share undermines the development of social skills. These characteristics may be related to the impaired theory of mind (ToM). This means that it is difficult to understand people’s wishes and feelings. A range of interventions have been created to help develop social communication skills. The Social Story™ intervention is one such example, and it provides clear visual narratives to explain social situations and concepts to help children with ASD. The narratives provide a mechanism to visually communicate typical communication behaviours. The social story intervention approach is book-based. As such, it is dependent on a reader to communicate well the concepts and demands a certain level with respect to the listener’s imagination capacity. With the limitation of the paper-based medium in mind, this work-in-progress paper outlines the steps, approach, and end application to translate the Social Story™ into a virtual reality (VR) experience. The Social Story™ experience in VR potentially offers a more interactive, immersive and flexible intervention.
Sputum-spotted solid matrix designed to release diagnostic-grade Mycobacterium tuberculosis DNA demonstrate optimal biocontainment property

Biosafety quotient of a reagent-coated cellulose matrix designed to release Mycobacterium tuberculosis (Mtb) DNA from sputum deposited onto it, was determined. Thirty-seven sputum samples infected with Mtb and 5 sputum samples from healthy individuals were processed and spotted onto the TBSend cards. Live Mtb bacilli were attempted for rescue from the spotted TBSend cards by washing them in phosphate buffer under mild shaking conditions. No live Mtb bacilli could be detected by the BACTEC™ MGIT 960™ TB System from both Mtb infected as well as non-infected, sample-spotted TBSend cards when they were washed at two different time-points, viz., 1 minute and 15 hours from the time of spotting of the cards with sputum mixed with the preprocessing “spotting” buffer. The study reiterated published finding that chaotropic agents, which is an active component of the TBSend card module, have cent per cent bactericidal properties with regard to Mtb.