Miracle-dz/UniFAR-FTUs huggingface dataset:
Repeatability and Reproducibility of in-vivo Brain Temperature Measurements

Background: Magnetic resonance spectroscopic imaging (MRSI) is a neuroimaging technique that may be useful for non-invasive mapping of brain temperature (i.e., thermometry) over a large brain volume. To date, intra-subject reproducibility of MRSI-based brain temperature (MRSI-t) has not been investigated. The objective of this repeated measures MRSI-t study was to establish intra-subject reproducibility and repeatability of brain temperature, as well as typical brain temperature range. Methods: Healthy participants aged 23–46 years (N = 18; 7 females) were scanned at two time points ~12-weeks apart. Volumetric MRSI data were processed by reconstructing metabolite and water images using parametric spectral analysis. Brain temperature was derived using the frequency difference between water and creatine (TCRE) for 47 regions of interest (ROIs) delineated by the modified Automated Anatomical Labeling (AAL) atlas. Reproducibility was measured using the coefficient of variation for repeated measures (COVrep), and repeatability was determined using the standard error of measurement (SEM). For each region, the upper and lower bounds of Minimal Detectable Change (MDC) were established to characterize the typical range of TCRE values. Results: The mean global brain temperature over all subjects was 37.2°C with spatial variations across ROIs. There was a significant main effect for time [F(1, 1,591) = 37.0, p < 0.0001] and for brain region [F(46, 1,591) = 2.66, p < 0.0001]. The time*brain region interaction was not significant [F(46, 1,591) = 0.80, p = 0.83]. Participants' TCRE was stable for each ROI across both time points, with ROIs' COVrep ranging from 0.81 to 3.08% (mean COVrep = 1.92%); majority of ROIs had a COVrep <2.0%. Conclusions: Brain temperature measurements were highly consistent between both time points, indicating high reproducibility and repeatability of MRSI-t. MRSI-t may be a promising diagnostic, prognostic, and therapeutic tool for non-invasively monitoring brain temperature changes in health and disease. However, further studies of healthy participants with larger sample size(s) and numerous repeated acquisitions are imperative for establishing a reference range of typical brain TCRE, as well as the threshold above which TCRE is likely pathological.
Can This Dog Be Rehomed to You? A Qualitative Analysis and Assessment of the Scientific Quality of the Potential Adopter Screening Policies and Procedures of Rehoming Organisations

Unwanted dogs are an international problem, and rehoming organisations are tasked with finding many of them appropriate homes. Whilst the processes involved in assessing dogs' suitability for rehoming have received considerable academic attention, the policies and procedures organisations employ for screening potential adopters, which are equally as important to dogs' outcomes, appear to be largely overlooked. Therefore, the aim of this study was to conduct a qualitative analysis of rehoming organisations' adopter screening processes in order to gain insight into what is being done, the extent to which this appears to have any scientific rationale, and what other factors might be driving the process. A written enquiry was sent to organisations in the UK; topics addressed included whether they use a standardised screening process, whether they interview potential adopters and what information is gathered during the interview, and how they score responses. Information was received from 82 respondents. Pre-adoption home visits were the most commonly used method. Self-administered questionnaires were the most standardised method. Using a thematic analysis, ten themes emerged from the types of information gathered during the screening process; 31 characteristics could lead an adopter being deemed unsuitable to adopt a dog. Evidence to potentially support these was found for only eight of them in the academic literature relating to risk factors for relinquishment and human safety risk. The inclusion of some of the characteristics considered important was thought to be for the purpose of ensuring a good quality of life for a dog, but there is a lack of relevant research investigating this. Organisations seem to invest considerable resources into screening potential adopters, but there is limited scientific, and sometimes logical, rationale for this. A further concern relates to the quality of the assessment processes, which show little evidence of quality control measures. Until the necessary research is conducted, it could be argued, from a pragmatic perspective, that organisations should relax their strict screening criteria, and focus their resources on ensuring owners are fully prepared for the changes in their life associated with the inclusion of a new dog in their home and supporting them as necessary.
Surfactant-Enhanced Carbon Regeneration in Liquid-Phase Application

Abstract In surfactant-enhanced carbon regeneration, a concentrated surfactant solution is passed over spent activated carbon to desorb the solutes in an in-sttu process. The solutes solubilize into micelles in the regenerate solution. Residual adsorbed surfactant can be removed by a water flush. In this study, phenol is the solute and sodium dodecyl sulfate is the anionic surfactant used. Previous studies have measured the ability of the regenerate to remove the solute from the carbon. This study presents the breakthrough curves for subsequent adsorption cycles following the regeneration. The reduction of the effective carbon adsorption capacity is less if a higher regenerate concentration of surfactant, more pore volumes of regenerate, or more pore volumes of water flush solution are used. Effective adsorption capacities of over 50% of that on. virgin carbon were observed on regenerated carbon.
Person-Independent Multimodal Emotion Detection for Children with High-Functioning Autism

The use of affect-sensitive interfaces carries the promise of enhancing human-computer interaction by delivering a system capable of identifying a user’s emotions and adapt its content accordingly. Today’s technology shows great potential to support children with autism, for example by using computer systems to improve their social skills. Generally, however, this technology does not encompass the potential of affect-sensitive interfaces. This is mainly due to Emotion Detection (ED) models built for the general population usually not performing well when applied to children with autism, who express emotions differently. The aim of this project is therefore to build a person-independent Multimodal Emotion Detection system tailored for children with high-functioning autism for the ultimate goal of applying it to design affect-sensitive interfaces dedicated to children with autism. This is a work in progress and the project expects to build upon the current body of knowledge on methods to apply ED systems to this speciﬁc subset of the general population. We expect to apply the overall theoretical and practical design perspectives that arise from this research investigation (e.g. analysis of modalities and features extraction, behavioural cues based features, fusion layers and classiﬁer techniques) to propose a guiding framework for future studies.
The Interaction Between Microorganisms, Metabolites, and Immune System in the Female Genital Tract Microenvironment

The female reproductive tract microenvironment includes microorganisms, metabolites, and immune components, and the balance of the interactions among them plays an important role in maintaining female reproductive tract homeostasis and health. When any one of the reproductive tract microorganisms, metabolites, or immunity is out of balance, it will affect the other two, leading to the occurrence and development of diseases and the appearance of corresponding symptoms and signs, such as infertility, miscarriage, premature delivery, and gynecological tumors caused by infectious diseases of the reproductive tract. Nutrients in the female reproductive tract provide symbiotic and pathogenic microorganisms with a source of nutrients for their own reproduction and utilization. At the same time, this interaction with the host forms a variety of metabolites. Changes in metabolites in the host reproductive tract are related not only to the interaction between the host and microbiota under dysbiosis but also to changes in host immunity or the environment, all of which will participate in the pathogenesis of diseases and lead to disease-related phenotypes. Microorganisms and their metabolites can also interact with host immunity, activate host immunity, and change the host immune status and are closely related to persistent genital pathogen infections, aggravation of infectious diseases, severe pregnancy outcomes, and even gynecological cancers. Therefore, studying the interaction between microorganisms, metabolites, and immunity in the reproductive tract cannot only reveal the pathogenic mechanisms that lead to inflammation of the reproductive tract, adverse pregnancy outcomes and tumorigenesis but also provide a basis for further research on the diagnosis and treatment of targets.
Scenario forecasting information transparency of subjects' under uncertainty and development of the knowledge economy

Topicality of modeling information transparency is determined by the influence it has on the effectiveness of management decisions made by an economic entity in the context of uncertainty and information asymmetry. It has been found that information transparency is a poorly structured category which acts as a qualitative characteristic of information and at certain levels forms an additional spectrum of properties of the information that has been adequately perceived or processed. As a result of structuring knowledge about the factor environment, a fuzzy cognitive model of information transparency was constructed in the form of a weighted digraph. Structural analysis and scenario forecasting of optimal alternatives of the fuzzy cognitive model made it possible to evaluate the classes of factors, identify their limited relations, establish the centrality of the roles of information transparency and information and communication security in the system built and evaluate their importance when modeling the situation self-development. Information visibility, reliability and availability have been found to have the strongest impact on the system. Taking into account different initial weights of the key factors — information transparency and information and communication security — the study substantiates the strategic ways for economic entities to achieve their goals in the context of uncertainty and information asymmetry, which allows us to use this approach as a tool for strategic management in the information environment.
Use of Ionic Liquids in Protein and DNA Chemistry

Ionic liquids (ILs) have been receiving much attention as solvents in various areas of biochemistry because of their various beneficial properties over the volatile solvents and ILs availability in myriad variants (perhaps as many as 108) owing to the possibility of paring one cation with several anions and vice-versa as well as formulations as zwitterions. Their potential as solvents lies in their tendency to offer both directional and non-directional forces toward a solute molecule. Because of these forces, ionic liquids easily undergo intermolecular interactions with a range of polar/non-polar solutes, including biomolecules such as proteins and DNA. The interaction of genomic species in aqueous/non-aqueous states assists in unraveling their structure and functioning, which have implications in various biomedical applications. The charge density of ionic liquids renders them hydrophilic and hydrophobic, which retain intact over long-range of temperatures. Their ability in stabilizing or destabilizing the 3D-structure of a protein or the double-helical structure of DNA has been assessed superior to the water and volatile organic solvents. The aptitude of an ion in influencing the structure and stability of a native protein depends on their ranking in the Hofmeister series. However, at several instances, a reverse Hofmeister ordering of ions and specific ion-solute interaction has been observed. The capability of an ionic liquid in terms of the tendency to promote the coiling/uncoiling of DNA structure is noted to rely on the basicity, electrostatic interaction, and hydrophobicity of the ionic liquid in question. Any change in the DNA's double-helical structure reflects a change in its melting temperature (Tm), compared to a standard buffer solution. These changes in DNA structure have implications in biosensor design and targeted drug-delivery in biomedical applications. In the current review, we have attempted to highlight various aspects of ionic liquids that influence the structure and properties of proteins and DNA. In short, the review will address the issues related to the origin and strength of intermolecular interactions, the effect of structural components, their nature, and the influence of temperature, pH, and additives on them.
Assessment of bank's financial security levels based on a comprehensive index using information technology

The article considers the issues of assessing the level of financial security of the bank. An analysis of existing approaches to solving this problem. A scientific and methodological approach based on the application of comprehensive assessment technology is proposed. The computational algorithm is presented in the form of a four-stage procedure, which contains the identification of the initial data set, their normalization, calculation of the partial composite indexes, and a comprehensive index of financial security. Results have interpretation. Determining the levels of financial security and the limits of the relevant integrated indicator is based on the analysis of the configuration of objects in the two-scale space of partial composite indexes, which is based on the division of the set of initial indicators by content characteristics. The results of the grouping generally coincided with the results of the banks ranking according to the rating assessment of their stability, presented in official statistics. The article presents the practical implementation of the proposed computational procedure. To automate calculations and the possibility of scenario modeling, an electronic form of a spreadsheet was created with the help of form controls. The obtained results allowed us to identify the number of levels of financial security and their boundaries.
Impact of Solids Formation and Gas Production on the Permeability of ZVI PRBs

The permeability of zero-valent iron permeable reactive barriers (ZVI PRBs) may be reduced by the production of gas and solid precipitates. The reduction in permeability was examined using column experiments, which showed that permeability loss was correlated with influent oxidant concentration. The column containing 100 mg/L nitrate experienced the greatest loss, approximately two orders of magnitude over the course of 200 pore volumes. However, the permeability loss owing to precipitated solids was largely independent of oxidant concentration, accounting for only 24% of the observed loss in the 100 mg/L nitrate column, suggesting that the majority of loss was attributable to gas, not precipitates. Geochemical modeling corroborated these findings, indicating that precipitation of solids in the 100 mg/L nitrate system does not account for more than a 10% permeability reduction. These findings suggest that in field PRBs in which a high reduction in permeability is observed, gas production may be implica.
Germanium diffusion and nanocrystal formation in silicon oxide on silicon substrate under rapid thermal annealing

The effect of rapid thermal annealing temperature on the diffusion of silicon (Si) and germanium (Ge) and the formation of Ge nanocrystals in a silicon oxide matrix was investigated. The formation of Ge nanocrystals was attributed mainly to the reduction of Ge suboxides by Si diffused from the Si substrate. For samples annealed at 800°C, the nanocrystals were uniform in size and distributed evenly in the bulk of the oxide but became denser nearer to the silicon–silicon oxide (Si–SiO2) interface. When the sample was annealed at 900°C, two regions with different nanocrystal densities and size distributions separated by a region void of nanocrystals were observed. The region of denser nanocrystals was located near the Si–SiO2 interface. For annealing at 1000°C, nanocrystals were only observed at the Si–SiO2 interface and these have significant size variation, with the rest of the oxide being void of nanocrystals. The nanocrystals formed at 900 and 1000°C were generally found to be defective.
Higher Education Polithecnic Students' Perspectives on the Transition to Emergency Remote Teaching

COVID-19 pandemic forced higher education institutions to make a sudden transition from face-to-face to distance learning, which involved a huge effort by all those involved in adapting to a new learning system The analysis of students' responses to questionnaires applied in a Portuguese higher education institution highlighted the main positive and negative aspects experienced, bringing contributions to a discussion on factors that determine the success of remote education and the preparation of the next semester © 2020 CEUR-WS All rights reserved
Performance and Sensitivity of Explosives

Experimental data from several performance and sensitivity tests have been combined after normalization to define a single performance and a security characteristic term, respectively. This allows to evaluate pure compounds and special formulations with regard to a well balanced ratio of performance and sensitivity. A graph shows an imaginary border line what has to be interpreted in the sense that–in the praxis of explosive charges–high performance is accompanied by an enhanced sensitivity and that an insensitive explosive will not exhibit a top performance. As this result cannot be proved by theory one should imagine that there are also exceptions, i.e. explosives which approach the ideal high explosive (with high performance and high security) what is exemplified.
High Adsorptive Property of Opened Carbon Nanotubes at 77 K

Hydrogen adsorption in porous materials is one of the methods actively being studied to store hydrogen on board vehicles driven by fuel cells. Recent experiments and numerical simulations have shown that adsorbent materials appropriate to hydrogen storage could be made up of carbon nanotubes. In this work we study the properties of such materials. By Monte Carlo simulations, we compute the hydrogen adsorption in two arrangements of opened single-walled carbon nanotubes at a temperature of 77 K and pressures up to 15 MPa. A quantitative comparison is made between simulation data and experimental results. The studied nanotube arrangements seem able to adsorb hydrogen gas in amounts required for their use in fuel cell vehicles.
Microscopic study of crystal defects enriches our knowledge of materials chemistry

Electron microscopic study of crystal defects enables us not only to reveal various structural imperfections, but also to discover their formation mechanisms and to understand their effects on the properties of solid materials. This short article highlights some recent examples of defect investigation mainly performed at University of St Andrews, including defective pores in zeolite β, defects in single-crystal-like icositetrahedra of zeolite analcime, point defects in perovskite-type materials and in a new C60 phase, and defects in carbon–MnO2 composites.
Fog Transport Mode Detection

A user's transport mode can be detected automatically by using a smartphone. In fact, such devices exist in a great number and have many sensors. In addition, using a smartphone in a fog environment allows to extend its capabilities ensuring low latency and low battery usage with high accuracy. We present the main idea underlying a smartphone app we plan to develop that uses a local classifier, the GPS, the accelerometer, and the magnetometer. The novelty of this work is the use of the magnetometer data for classification improvement and the use of the fog approach.
Near‐infrared fourier transform Raman spectroscopy of indigoids

Near-infrared Fourier transform Raman spectra (3400 to — 20 cm−1) for the solid phases of indigo, thioindigo, selenoindigo and N,N'-dimethylindigo were recorded with excitation using Nd:YAG laser radiation at 1064 nm. A complete vibrational assignment is proposed supported by the results of ab initio calculations. The spectra are complementary to the IR spectra recorded earlier. They also complete earlier results of resonance Raman spectroscopy. The spectra support a molecular structure of the indigo chromophore with a cross-conjugated vinylogue amide system.
Micro-Doppler Signal Representation for Drone Classification by Deep Learning

There are numerous formats which represent the micro-Doppler signature. Our goal is to determine which one is the most adapted to classify small UAV (Unmanned Aerial Vehicules) with Deep Learning. To achieve this goal, we compare drone classification results with the different micro-Doppler signatures for a given neural network. This comparison has been performed on data obtained during a radar measurement campaign. We evaluate the classification performance in function of different use conditions we identified with a given neural network. According to the experiments conducted, the recommended format is a spectrum issued from long observations as its classification results are better for most criteria.
3D Point Cloud Denoising Using a Joint Geometry and Color k-NN Graph

Many point cloud acquisition methods, e.g. multi-viewpoint image stereo matching and acquisition of depth data from active light sensors, suffer from significant geometry noise in the data. In the existing literature, denoising of this geometry noise has been performed using only geometry information. In this paper, based on the notion that color attributes are correlated with the geometry, we propose a novel geometry denoising technique that takes advantage of this correlation via a graph-based optimization process. In particular, we construct a graph based on both color and geometry information, and use it for graph-based Tikhonov regularization. Results on synthetic and real-world point clouds show that the proposed denoising method significantly outperforms existing geometry-only techniques.
Loss Functions for CNN-based Biometric Vein Recognition

The recent progress in deep learning has led to a rapid change in the way biometric data can be handled, offering new opportunities for further research on physical, behavioral, and cognitive biometric recognition. In particular, conventional modalities for preprocessing, extracting features, and comparing templates derived from biometric traits have been swiftly altered, replacing the search for hand-crafted features with the ever-increasing use of generalized deep learning models and transfer learning, able to guarantee notably-high recognition performance. This study investigates the capabilities of deep learning approaches in performing vein pattern verification. Specifically, recent advances in the design of convolutional neural networks, introduced to increase the inter-class variability and decrease the intra-class variability of the generated representations, are here taken into account to speculate on the effects on recognition performance of the selection for the most suitable loss function. Experimental tests conducted on finger vein, palm vein, and hand dorsum vein patterns testify the effectiveness of the proposed frameworks, able to exceed current state-of-the-art performance on five different publicly available vein datasets.