Miracle-dz/UniFAR-FTUs huggingface dataset:
Object detection and colour evaluation of multicoloured waste textiles using machine vision

Only 13% of the globally produced textile fibers are recycled, leading to fiber production having a large environmental impact. While many new technologies are emerging for the recycling of textiles, very little automated sorting capacity exists. This is a key problem, as fiber-to-fiber recycling requires material and colour sorting of the waste textiles. While textile material sorting has been done using NIR sensors, little literature exists on the subject of material sorting of waste textiles. Existing systems are experimental and based on fixed area sampling to determine the colours, which poses a limitation in performance for multi coloured textiles. This paper proposes a machine vision system for colour sorting of multicoloured waste textiles. The proposed system consists of three parts: (1) an object detection algorithm to define the boundary of the entire textile. (2) a discretization and colour determination algorithm which divides the textile area into a number of cells, and attributes a colour to each cell using colour descriptors. (3) a categorization algorithm which uses a descision tree to sort the textiles based on their colour distribution, using only a few sorting criteria. The proposed system was tested on a set of pre-sorted textiles and it was able to reach an accuracy of 88.3% with a mean computational time of 0.77 seconds for each textile. While a fixed area sampling method had an accuracy of 74.0%, it is concluded that the proposed system performs better, especially for multi coloured textiles.
Development of a Real-Time Stress Detection System for Older Adults with Heart Rate Data

Stress is one of the factors considerably contributing to older adult’s decreasing overall health. Detecting stress in real-time could aid family members to intervene more timely and keep older adults healthier. However, many stress detection systems are not detecting in real-time, depend on multiple devices, capture a plethora of inconveniently sampled data, or use data from younger adults. In this paper, we built a real-time stress detection system for older adults using only heart beats per minute (BPM), which can be easily obtained with most single, comfortable devices. We collected data from people over 60 (N=15), evaluating the Mannheim Multicomponent Stress Test (MMST) for older adults, then built a machine learning model with a classification performance of 76% (AUC) on BPM alone and tested it in real-time in another experiment, comparing the model’s effectiveness with four different heart rate devices. Detection performance decreased considerably (51%) when using the model in another experiment and could not be used successfully with other devices, while a reduced MMST induced stress comparable to the full test suite.
Efficient Data Sharing across Trust Domains

Cross-Trust-Domain Processing. Data is now a commodity. We know how to compute and store it efficiently and reliably at scale. We have, however, paid less attention to the notion of trust. Yet, data owners today are no longer the entities storing or processing their data (medical records are stored on the cloud, data is shared across banks, etc.). In fact, distributed systems today consist of many different parties, whether it is cloud providers, jurisdictions, organisations or humans. Modern data processing and storage always straddles trust domains.
Point-of-Care Verification of Blood Culture Volume in Neonates: A Feasibility Trial

Abstract Background Blood cultures remain the gold standard for the diagnosis of sepsis. However, volumes of blood submitted for cultures often do not match the recommended values. We propose a simple intervention aimed to verify the volume of blood sampled using a scale. This study was undertaken in preparation for a future, multicenter, pre- and post-intervention trial. Our primary objective was to test the feasibility (uptake and retention) of this future intervention. Materials and methods This study was conducted at a neonatal department in Warsaw, Poland, over a period of eight months (May to December 2020). Before starting the study, we undertook an educational intervention focused on obtaining adequate blood volumes for culture. The culture bottles that were weighed in advance were distributed in all blood collection areas. Blood volume was verified by weighing the bottle immediately after blood inoculation. The calculated value was communicated to the collecting clinician and recorded. The primary outcome measure was the percentage of blood culture submissions for which the blood volume inoculated into the bottles was determined by weighing. Results During the study period, 244 blood samples were collected for culture, out of which 205 samples were weighed (84.0%, CI95 [78.8% to 88.4%]). This high proportion remained stable throughout the study period. We have not observed any adverse events related to the study. Conclusions The point-of-care verification of blood culture volume using a scale was feasible to implement. Since we have met our pre-established criterion for success, a future, definitive trial is likely to proceed.
How Social Robots can Influence Motivation as Motivators in Learning: A Scoping Review

Earlier research has investigated how educational social robots can influence learner motivation and learning outcomes as motivators instead of learning materials. This paper presents a scoping literature review of this body of work, focusing on the educational strategies used, and describing the range of approaches used to influence motivation and learning through social robots, not as learning tools but as motivators. Nineteen advanced studies are identified and described according to the components of the ARCS model (a motivation model dominant in robotics research): Attention, Relevance, Confidence, and Satisfaction. We summarized the measures used for motivation in the studies and relate these measures to the four ARCS model components. Finally, we analyzed the studies from the perspectives of sample groups, study type, and domain or subject. Our analyses suggested that beyond focusing on persuasive (educational) strategies that educational social robots can use to keep learners’ attention, researchers should also focus on the satisfaction component of motivation. Furthermore, future studies should examine long-term interactions, apply more rigor in using validated questionnaires, and combine qualitative and quantitative methods to understand not only the effects of these different approaches but also the reasons behind them.
Mentoring, Life Purpose, and Well-Being in First-Generation College Students: Impact of Life Purpose Mentoring by Faculty

Abstract The current study investigated the value of faculty mentoring among first-generation college students (FGCS). We examined mentored FGCS in general, and, more specifically, the impact of levels of quality of faculty mentoring on ratings of life purpose, perceived well-being, and perceived well-being subscales. We hypothesized that faculty-mentored FGCS would demonstrate greater perceived well-being and general life purpose than nonmentored FGCS. We also hypothesized that FGCS who reported high-quality faculty mentoring would demonstrate a greater sense of life purpose and perceived well-being than FGCS who received low-quality mentoring or no mentoring. Group comparisons based on mentoring quality indicated significant differences. Findings point to the value of programs that aim to increase the quality of faculty mentoring for FGCS, as well as the importance of future research examining specific subscales of well-being such as intellectual and spiritual well-being.
Gene-to-gene coordinated regulation of transcription and alternative splicing by 3D chromatin remodeling upon NF-κB activation

The p65/RelA factor of NF-κB plays a pivotal role in coordinating gene expression in response to diverse stimuli, including viral infections. At the chromatin level, p65/RelA regulates gene transcription and alternative splicing (AS) through promoter enrichment and genomic exon occupancy, respectively. However, the mechanisms underlying the coordination of these processes across distinct genes remain elusive. In this study, we employed the HTLV-1 Tax oncoprotein, a potent activator of NF-κB, to investigate the integrative relationship between 3D chromatin architecture, NF-κB-regulated transcription and AS. Our analysis revealed that Tax induces a pronounced reorganization of the 3D genome, resulting in the formation of multigene complexes that comprise genes regulated either transcriptionally or through AS. Notably, we found that the Tax-induced gene-gene contact between the two master genes NFKBIA and RELA is associated with their differential regulation in gene expression and AS, respectively. Through dCas9-mediated approaches, we demonstrated that NFKBIA-RELA interaction is required for AS regulation and is caused by an intragenic enrichment of p65/RelA on RELA. Our findings shed light on new regulatory mechanisms upon HTLV-1 Tax and underscore the integral role of p65/RelA in coordinated regulation of NF-κB-responsive genes at both transcriptional and AS levels in the context of the 3D genome.
Many morphs: parsing gesture signals from the noise

Parsing signals from noise is a general problem for signallers and recipients, as well as for researchers studying communicative systems. Substantial research efforts have been invested in comparing how other species encode information and meaning in their signals, and how signalling is structured. However, our ability to do so depends on identifying and discriminating signals that represent meaningful units of analysis. Early approaches to defining signal repertoires applied top- down approaches, classifying cases into predefined signal types. Recently, more labour-intensive methods have taken a bottom-up approach describing the features of each signal in detail and clustering cases into types based on patterns of similarity between them in multi-dimensional feature-space that were previously undetectable. Nevertheless, it remains essential to assess whether the resulting repertoires are composed of relevant units from the perspective of the species using them, and redefining repertoires when additional data makes more detailed analyses feasible. In this paper we provide a framework that takes data from the largest set of wild chimpanzee (Pan troglodytes) gestures currently available, splitting gesture types at a fine scale based on modifying features of gesture expression and then determining whether this splitting process increases the information content of the communication system. Our method allows different features of interest to be incorporated into the splitting process, providing substantial future flexibility across - for example - species, populations, and levels of signal granularity. In doing so we provide a powerful tool allowing researchers interested in gestural communication to establish repertoires of relevant units for subsequent analyses within and between systems of communication.
Insights into human outer kinetochore assembly and force transmission from a structure-function analysis of the KMN network

The biorientation of chromosomes during cell division is necessary for precise dispatching of a mother cell’s chromosomes into its two daughters. Kinetochores, large layered structures built on specialized chromosome loci named centromeres, promote biorientation by binding and sensing spindle microtubules. The kinetochore outer layer consists of a 10-subunit apparatus comprising Knl1C, Mis12C, and Ndc80C subcomplexes (KMN network). The KMN network is highly elongated and docks on kinetochores and microtubules using interfaces at its opposite extremes. Here, we combine cryo-EM reconstructions and AlphaFold2 predictions to generate a model of the KMN network that reveals all intra-KMN interfaces. We identify and functionally validate two interaction interfaces that link Mis12C to Ndc80C and Knl1C. Through targeted interference experiments and molecular dynamics simulations we demonstrate this mutual organization stabilizes the KMN network. Our work reports the first comprehensive structural and functional analysis of the microtubule binding machinery of kinetochores and elucidates a path of microtubule-generated force transmission
FRET-guided modeling of nucleic acids

The functional diversity of RNA is encoded in their innate conformational heterogeneity. The combination of single-molecule spectroscopy and computational modeling offers new, attractive opportunities to map structural transitions within nucleic acid ensembles. Here, we describe a framework to harmonize single-molecule FRET measurements with molecular dynamics simulations and de novo structure prediction. Using either all-atom or implicit fluorophore modeling we recreate FRET experiments in silico, visualize the underlying structural dynamics and quantify the simulated reaction coordinates. Using multiple accessible-contact volumes (multi-ACV) as a post-hoc scoring method for fragment-assembly in Rosetta, we demonstrate that FRET effectively refines de novo RNA structure prediction without the need of explicit dye labeling. We benchmark our FRET-assisted modeling approach on double-labeled DNA strands and validate it against an intrinsically dynamic manganese(II)-binding riboswitch. We show that a FRET coordinate describing the assembly of a four-way junction allows our pipeline to recapitulate the global fold of the riboswitch with sub-helical accuracy to the crystal structure. We conclude that computational fluorescence spectroscopy facilitates the interpretability of dynamic structural ensembles and improves the mechanistic understanding of nucleic acid interactions. Graphical abstract Schematic workflow of integrative FRET modeling using all-atom fluorophores or an accessible-contact volume dye model. All-atom molecular dynamics track the dye coordinate explicitly as part of the simulation while multi-ACV infer mean dye positions post hoc.
VmPFC supports persistence during goal pursuit through selective attention

Striking the balance between persistence with a goal and flexibility in the face of better options is critical for effectively organizing behaviour across time. While people are often biased towards completing their current goal (e.g. ‘sunk cost’ biases), it is unclear how these biases occur at a mechanistic level, still allowing for some flexibility for goal abandonment. We propose that ventromedial prefrontal cortex (vmPFC) plays a critical role in orienting attention towards a current goal, prioritising goal completion but allowing for abandonment, particularly when the current goal fails. We developed a novel incremental goal pursuit task to study goal-directed attention and action in healthy individuals with functional magnetic resonance imaging (fMRI), and in an independent group of individuals with brain lesions. The task required participants to make sequential decisions between continuing to persist with a current goal (commitment), versus abandoning progress for a better alternative goal (flexibility). We show that individuals who persist more show greater goal-oriented attention outside the decision period. Increasing attentional capture by the current goal is also revealed in decision-making: people remain more likely to abandon from ‘frustration’ (collapse of value of the current goal) than from ‘temptation’ (attraction from valuable alternative goals). Strikingly, we find that our stable inter-individual metrics of persistence and goal-oriented attention were both predicted by baseline activity in vmPFC, tracking goal progress. We present converging evidence from an independent lesion patient study demonstrating the causal involvement of vmPFC in goal persistence: damage to the vmPFC reduces biases to over-persist with the current goal, leading to a performance benefit in our task.
osl-dynamics: A toolbox for modelling fast dynamic brain activity

Neural activity contains rich spatio-temporal structure that corresponds to cognition. This includes oscillatory bursting and dynamic activity that span across networks of brain regions, all of which can occur on timescales of a tens of milliseconds. While these processes can be accessed through brain recordings and imaging, modelling them presents methodological challenges due to their fast and transient nature. Furthermore, the exact timing and duration of interesting cognitive events is often a priori unknown. Here we present the OHBA Software Library Dynamics Toolbox (osl-dynamics), a Python-based package that can identify and describe recurrent dynamics in functional neuroimaging data on timescales as fast as tens of milliseconds. At its core are machine learning generative models that are able to adapt to the data and learn the timing, as well as the spatial and spectral characteristics, of brain activity with few assumptions. osl-dynamics incorporates state-of-the-art approaches that can be, and have been, used to elucidate brain dynamics in a wide range of data types, including magneto/electroencephalography, functional magnetic resonance imaging, invasive local field potential recordings and electrocorticography. It also provides novel summary measures of brain dynamics that can be used to inform our understanding of cognition, behaviour and disease. We hope osl-dynamics will further our understanding of brain function, through its ability to enhance the modelling of fast dynamic processes. Highlights An open-source toolbox for identifying and describing brain dynamics in neuroimaging data on fast timescales. Includes visualisation and quantification of oscillatory bursting and network dynamics. Provides novel summary measures and group analysis tools of brain dynamics that can be used to inform our understanding of cognition, behaviour and disease. Implemented in Python and makes use of TensorFlow. Includes comprehensive documentation and tutorials.
Tissue-specific increases in hypoxia-inducible factor 1 alpha protein are independent of mRNA levels during acute hypoxic exposure of the Gulf killifish, Fundulus grandis

The hypoxia inducible factor 1 (HIF1) is a central regulator of the molecular responses to low oxygen in animals. It has been extensively studied in mammals, where its tissue levels are regulated by stabilization of the alpha subunit (HIF1α) when oxygen levels decrease. Consistent with this, the initial characterization of HIF1α in fish cells in culture indicated that protein abundance increased during hypoxia even when transcription was blocked. Subsequent studies, however, have reported an increase in HIF1α mRNA levels during hypoxia in certain tissues of selected species, raising the question whether hypoxic exposure brings about coordinated changes in HIF1α mRNA and protein in tissues when measured in the same fish. We have directly addressed this question by determining levels of HIF1α protein and mRNA in the tissues of Gulf killifish, Fundulus grandis, exposed to short-term hypoxia (24 h at 1 mg O2 l−1). HIF1α protein was higher in brain, ovary, and skeletal muscle from fish exposed to hypoxia compared with normoxic controls by 6 h, and it remained elevated in brain and ovary at 24 h. In contrast, HIF1α mRNA levels were unaffected by hypoxia in any tissue. Moreover, levels of HIF1α protein and mRNA in the same tissues were not correlated with one another, during either normoxia or hypoxia. These results suggest that, during the initial response to low oxygen, HIF1α protein levels increase as the result of post-translational protein stabilization, rather than new transcription, as predicted from studies in mammalian and fish cells in culture. Summary Statement Parallel measurements of protein and mRNA of the hypoxia inducible factor support post-translational protein stabilization rather than new transcription in the initial response of fish to low oxygen
Single-cell transcriptome landscape of developing fetal gonads defines somatic cell lineage specification in humans

Gonad development is an exciting model to study cell fate commitment. However, the specification and differentiation of somatic cell lineages within the testis and the ovary are incompletely characterized, especially in humans. In fact, a better understanding of sex determination first requires the identification of all the cell types involved and of their dynamic expression programs. Here we present a comprehensive analysis of approximately 128,000 single cells collected from 33 fetal testes and ovaries between 5 and 12 postconceptional weeks. In particular, a focused analysis of somatic cells allowed us to identify a common population of bipotential progenitors derived from the coelomic epithelium of both male and female gonads and capable of committing to either a steroidogenic or a supporting fate. Moreover, we have shown that early supporting cells, prior to further differentiation into Sertoli or granulosa cells, also give rise to the rete testis/ovarii lineage. Finally, we found that the ovary retains the capacity to feed the supporting cell pool for an extended period of time, directly from the surface epithelial cells and, bypassing the bipotential progenitor step. Altogether, our results provide an unprecedented revisiting of the human gonadal sex determination process.
Synchrony and amplitude modulation of cortical activity in humans performing manipulative visuomotor tasks

Synchrony of oscillatory brain activity has been postulated to be a binding mechanism for cognitive and motor functions. Spectral analysis of human electrocorticogram (ECoG) in sensorimotor cortex has shown that power density of gamma band activity (30-60 Hz) increased and that of alpha-beta band activity (10-20 Hz) decreased during performance of manipulative visuomotor tasks, indicating that amplitude modulation of the gamma band activity occurred in relation to the task performance. Amplitude modulation may provide evidence for synchrony of local neuronal assembly. However, it does not implement the binding mechanisms for distributed networks that are necessary for cognitive and motor functions. To prove that oscillatory activity mediates a binding mechanism, phase modulation of oscillatory activity in a wide range area should be shown. We performed coherence analysis of the ECoG signals in sensorimotor cortex to study if synchrony of the gamma band activity between these areas occurs in relation to manipulative task performance. The ECoGs were recorded from 14 sites in sensorimotor cortex including hand-arm areas with subdural grid electrodes in four subjects. Coherence estimates in all pair-wise sites were calculated in different frequency bands with 10 Hz widths from 10 to 80 Hz. In all subjects, coherence estimates increased in the lower gamma band (20-50 Hz) during the performance of the manipulative tasks. But coherence in the alpha-beta band (10-20 Hz) also increased even though amplitude modulation did not occur in this frequency band. Coherence estimates increased in site pairs within and between sensory and motor areas, many separated by intervening sites. This interregional synchrony of the alpha-beta and the lower gamma activities may play a role in integration of sensorimotor information. Task-dependent increases in coherence estimates, i.e., greater increases during performance of the manipulative tasks than during the simple tasks, suggest another role of synchrony in attention mechanism. Time-series coherence analysis showed that phase modulation occurred in different timings for activities in the alpha-beta and the lower gamma bands. For the activity in higher gamma band (50-80 Hz), power density increased but coherence estimates decreased. Thus, only amplitude modulation occurred in this frequency band. Altogether these results suggest that oscillatory activities in different frequency bands may reflect different functional roles by modulating neural activity in different ways.