Miracle-dz/UniFAR-FTUs huggingface dataset:
Voluntary Hydration with Skimmed Lactose-Free Milk during Exercise in the Heat: Exploring Effectiveness and Tolerance

Replacement of fluid losses (dehydration) during sports activities in the heat has been investigated with different beverages. Bovine milk has been recommended for post-exercise rehydration, but its use during exercise may provoke gastrointestinal disorders. This study compared voluntary fluid intake, hydration, and incidence and severity of gastrointestinal (GI) disorders during exercise in the heat under three conditions: no drink (ND), water (W), and skimmed lactose-free milk (SM). Sixteen physically active university students exercised at 32 °C and 70% RH for 90 min at 60–75% HRmax while drinking W or SM ad libitum, or ND assigned at random. A questionnaire explored possible GI disorders. Ad libitum intake was higher (p < 0.05) for water (1206.2 mL) than milk (918.8 mL). Dehydration showed significant differences for SM versus W and ND (W = 0.28% BM; SM = −0.07% BM; ND = 1.38% BM, p < 0.05). Urine volume was significantly higher (p < 0.05) in the W condition (W = 220.4 mL; SM = 81.3 mL; ND = 86.1 mL). Thick saliva, belching, and abdominal pain were higher for SM, but scores were low. Skimmed lactose-free milk is a suitable, effective alternative to be consumed as a hydration beverage during moderate-intensity cycling in the heat for 90 min.
Remarques sur un théorème de J. Delsarte

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Movable Object Detection in Remote Sensing Images via Dynamic Automatic Learning

The performance of deep networks for object detection in remote sensing images (RSIs) largely depends on the availability of large-scale training images whose labels are given at the bounding-box level through a labor-intensive manual labeling process. To alleviate the huge burden of providing bounding-box annotations manually for movable objects, we propose a new approach, called dynamic automatic learning (DAL), to progressively learn object detectors. Specifically, a novel initial annotation generation (IAG) strategy is first designed to produce bounding-box annotations for movable objects in multitemporal RSIs. During this process, image-level labels need to be manually labeled for the generated candidates. Next, a detection network learns the detection knowledge from multitemporal RSIs with bounding-box annotations and then transfers the knowledge to generate pseudoboxes for the unlabeled data. Finally, with these pseudoboxes, the object detector can be optimized for generating accurate pseudoboxes iteratively. Furthermore, we introduce a pseudobox filtering (PBF) strategy to purify the quality of pseudoboxes to obtain accurate supervision. Our experiments on the challenging Northwestern Polytechnical University (NWPU) VHR-10.v2 and object detection in optical remote sensing images (DIOR) datasets have demonstrated that our DAL approach can achieve competitive results compared with state-of-the-art methods.
Crop Classification of Multitemporal PolSAR Based on 3-D Attention Module With ViT

Multitemporal polarimertic SAR is considered to be very effective in crop classification and cultivated land detection, which has received much attention from researchers. Currently, for most multitemporal polarimetric SAR data classification methods, the simultaneous temporal–polarimetric–spatial feature extraction capability has not been exploited sufficiently. Also, the diversity of different time and different polarimetric features has not been taken into account sufficiently. In this letter, we propose a classification model that combines a dual-stream network as a temporal–polarimetric–spatial feature extraction module with vision transformer (ViT) called temporal–polarimetric–spatial transformer (TPST) to address the above problems. Second, a 3-D convolutional attention module that enables the network to weight the temporal dimension, polarimetric feature dimension and spatial dimension is developed, according to their importance. Experimental results on both the UAVSAR and RADARSAT-2 datasets show that the proposed method outperforms ResNet.
Models for Interdependent Event-History Data: Specification and Estimation

The idea of interdependence between events over an individual's life course is widespread. For example, the amount of schooling a person obtains may depend on her family behavior, and vice versa the family behavior may depend on whether the person is in school or not. This paper proposes a framework for analyzing such interdependencies by means of hazard-rate models. First, I discuss two existing approaches to studying interdependencies, the coupled and the Kalbfleisch and Prentice approaches. Then, I propose a new approach
Do two negatives make a positive? Language and logic in language processing

ABSTRACT This study focuses on a factor known to increase sentence processing complexity – negation. We sought to distill out of negation a logical property – Inference Reversal – to see whether it, and not an actual negation word, determines this complexity. First, we tested a negation-less pair of polar operators (at most, at least) in Hebrew. We found that processing time for sentences containing the Inference Reversing at most lagged behind those with at least. Second, we compared the processing of sentences containing two Inference Reversing operators (not less) to sentences with zero (ø, more) and one (not more, less). Since two Inference Reversing Operators annul Inference Reversal (“two negatives make a positive”), we asked whether their processing cost is annulled, or rather cumulative. Surprisingly, RT not less was shorter than RT not more . These findings lead to the conclusion that even when covert, Inference Reversal is an important determinant of processing complexity.
A Calibration Method of Three-axis Magnetic Sensor Based on Ellipsoid Fitting

It is very essential for a magnetic sensor to be calibrated before use because of various disturbances. However, Constrained by maneuverability of carriers, sample data distribute in a quite limited area, traditional calibration approach using ordinary least-square ellipsoid fitting algorithm makes large error or even cannot compensate properly. In this paper, a new onboard calibration method based on ellipsoid fitting is presented, without requiring external reference. Sample data are obtained in the restricted area by rotating carrier in three simple traces, ellipsoid coefficient are calculated using constrained least squares algorithm. The proposed method is contrasted with the traditional method via software simulation and experimental test; the results indicate that the new calibration method is stable and reliable, and superior to the traditional approach.
Machine vision defects classification methods based on 1-class SVM

A method based on 1-class classification is proposed for single class defects true/false judgments when training samples are less or sample numbers are different for different classes.First,the moment invariant feature which has scale and rotation invariance for training samples of every class is calculated.Then,the 1-class support vector machine(SVM) based on RBF kernel function is used to generate a hypersphere for every defects class.After that,a dual grids searching method is proposed to find parameters optimization of kernel function.Finally,the defects on the actual captured image are located and classified automatically.The results show that 1-class SVM method for defects classification can take advantages of unbalanced samples distribution between different classes,and it has high precision and is easy for on-line inspection.
Chitosan/PVA Nanofibers as Potential Material for the Development of Soft Actuators

Chitosan/PVA nanofibrous electroresponsive soft actuators were successfully obtained using an electrospinning process, which showed fast speed displacement under an acidic environment. Chitosan/PVA nanofibers were prepared and characterized, and their electroactive response was tested. Chitosan/PVA nanofibers were electrospun from a chitosan/PVA solution at different chitosan contents (2.5, 3, 3.5, and 4 wt.%). Nanofibers samples were characterized using Fourier transform infrared analyses, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), optical microscopy, and tensile test. The electroactive behavior of the nanofiber hydrogels was tested under different HCl pH (2–6) under a constant voltage (10 V). The electroactive response test showed a dependence between the nanofiber’s chitosan content and pH with the bending speed displacement, reaching a maximum speed displacement of 1.86 mm−1 in a pH 3 sample with a chitosan content of 4 wt. %. The results of the electroactive response were further supported by the determination of the proportion of free amine groups, though deconvoluting the FTIR spectra in the range of 3000–3700 cm−1. Deconvolution results showed that the proportion of free amine increased as the chitosan content was higher, being 3.6% and 4.59% for nanofibers with chitosan content of 2.5 and 4 wt. %, respectively.
Revealing the Second and the Third Causes of AgNPs Property to Restore the Bacterial Susceptibility to Antibiotics

The increase in bacterial resistance to antibiotics is a global problem for public health. In our previous works, it was shown that the application of AgNPs in cow mastitis treatment increased S. aureus and S. dysgalactiae susceptibility to 31 antibiotics due to a decrease in the bacterial efflux effect. The aim of the present work was to shed light on whether the change in adhesive and anti-lysozyme activities caused by AgNPs also contribute to the restoration of bacterial susceptibility to antibiotics. In vivo sampling was performed before and after cow mastitis treatments with antibiotics or AgNPs. The isolates were identified, and the adhesive and anti-lysozyme activities were assessed. These data were compared with the results obtained for in vitro pre-treatment of reference bacteria with AgNPs or antibiotics. The present study revealed that bacterial treatments in vitro and in vivo with AgNPs: (1) decrease the bacterial ability to adhere to cells to start an infection and (2) decrease bacterial anti-lysozyme activity, thereby enhancing the activity of lysozyme, a natural “antibiotic” present in living organisms. The obtained data contribute to the perspective of the future application of AgNPs for recovering the activity of antibiotics rapidly disappearing from the market.
Process Mining and Perceived Privacy Violations: A Pilot-Study

: Despite the existence of various methods and abstraction techniques to reduce the privacy risk of process models generated by process mining algorithms, it is unclear how process mining stakeholders perceive privacy violations. In this pilot-study various process model visualisations were shown to 6 stakeholders of a travel expense claim process. While changing the abstraction levels of these visualisations, the stakeholders were asked whether they perceived a violation of their privacy. The results show that there are differences in how individual stakeholders perceive privacy violations of process models generated via process mining algorithms. Results differ per type of visualization, type of privacy risk reducing methods, changes of abstraction level and stakeholder role. To reduce the privacy risk, the interviewees suggested to include an authorization table in the process mining tool, communicate the goal of the analysis with all stakeholders, and validate the analysis with a privacy officer. It is suggested that future research focuses on discussing and validating process visualisations and privacy risk reducing methods and techniques with various process mining stakeholders in organisations. This is expected to reduce perceived violations and prevents developing techniques that are aimed at reducing privacy risk but are not considered as such by stakeholders.
Efficacy and Safety Profile of Berberine Treatment in Improving Risk Factors for Cardiovascular Disease: A Systematic Review and Meta-analysis of Randomized, Double-blind Trials

Objective: This systematic review and meta-analysis aimed to evaluate the efficacy of berberine treatment in improving blood glucose, blood lipids, and blood pressure as well as the associated safety profile. Methods: PubMed, Embase, Cochrane Library, WanFang Data, and the China National Knowledge Infrastructure database were searched from the establishment of the database to December 31, 2021, to identify randomized, double-blind trials that examined the effect of berberine alone or as add-on treatment on blood glucose, blood lipids, and blood pressure with an intervention period of at least 3 months. Two researchers independently screened articles, extracted data, and assessed the quality of each study according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The efficacy outcomes included fasting blood glucose (FPG), 2-hour post-prandial glucose (2hPG), glycated hemoglobin (HbA1c), total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), and diastolic blood pressure (DBP). The safety outcome was the incidence of the total number of adverse events. Results: A total of 17 articles enrolling 1,485 participants were included in the meta-analysis. The intervention duration ranged from 12 to 24 weeks. Sixteen trials reported results for blood glucose, 14 trials reported results for blood lipids, and 7 reported results for blood pressure. Compared with placebo or baseline treatment, berberine alone or as add-on therapy significantly reduced FPG (by 0.35 mmol/L; 95% confidence interval (CI): 0.13–0.58 mmol/L; P = 0.002; I2 = 89.0%, n = 16), 2hPG (by 1.50 mmol/L; 95% CI: 0.50–2.49 mmol/L, P = 0.003, I2 = 84.1%, n = 4), HbA1c (by 0.45%, 95% CI: 0.24%–0.65%, P < 0.001, I2 = 82.8%, n = 9), TC (by 0.48 mmol/L; 95% CI: 0.36–0.60 mmol/L, P < 0.001, I2 = 72.3%, n = 13), TG (by 0.22 mmol/L; 95% CI: 0.13–0.31 mmol/L, P < 0.001, I2 = 57.1%, n = 14), and LDL-C (by 0.41 mmol/L; 95% CI: 0.34–0.48 mmol/L, P < 0.001, I2 = 35.0%, n = 12). The effect on blood glucose and blood lipids remained consistent when confined to high-quality trials. There is no significant effect of berberine treatment on HDL-C, SBP, and DBP. The incidence of the total number of adverse events was similar between the berberine group and the control group (risk ratio (RR) = 1.00, 95% CI: 0.84–1.19, P = 0.961). Gastrointestinal disorder was the most common adverse event in the berberine group and most adverse events were alleviated or disappeared as the dose was decreased or the intervention time was prolonged. Conclusions: Short-term berberine treatment significantly improved blood glucose and blood lipid profiles without raising safety concerns. A rigorously designed randomized controlled trial could be considered to examine the feasibility of the long-term application of berberine treatment in the prevention of cardiovascular disease.
Lipidome Analysis of Oropharyngeal Tumor Tissues Using Nanosecond Infrared Laser (NIRL) Tissue Sampling and Subsequent Mass Spectrometry

Ultrashort pulse infrared lasers can simultaneously sample and homogenize biological tissue using desorption by impulsive vibrational excitation (DIVE). With growing attention on alterations in lipid metabolism in malignant disease, mass spectrometry (MS)-based lipidomic analysis has become an emerging topic in cancer research. In this pilot study, we investigated the feasibility of tissue sampling with a nanosecond infrared laser (NIRL) for the subsequent lipidomic analysis of oropharyngeal tissues, and its potential to discriminate oropharyngeal squamous cell carcinoma (OPSCC) from non-tumorous oropharyngeal tissue. Eleven fresh frozen oropharyngeal tissue samples were ablated. The produced aerosols were collected by a glass fiber filter, and the lipidomes were analyzed with mass spectrometry. Data was evaluated by principal component analysis and Welch’s t-tests. Lipid profiles comprised 13 lipid classes and up to 755 lipid species. We found significant inter- and intrapatient alterations in lipid profiles for tumor and non-tumor samples (p-value < 0.05, two-fold difference). Thus, NIRL tissue sampling with consecutive MS lipidomic analysis is a feasible and promising approach for the differentiation of OPSCC and non-tumorous oropharyngeal tissue and may provide new insights into lipid composition alterations in OPSCC.
Experimental Models to Study the Functions of the Blood–Brain Barrier

The purpose of this paper was to discuss the achievements of in vitro modeling in terms of the blood–brain barrier [BBB] and to create a clear overview of this research area, which is useful in research planning. The text was divided into three main parts. The first part describes the BBB as a functional structure, its constitution, cellular and noncellular components, mechanisms of functioning and importance for the central nervous system, in terms of both protection and nourishment. The second part is an overview of parameters important in terms of establishing and maintaining a barrier phenotype that allows for formulating criteria of evaluation of the BBB in vitro models. The third and last part discusses certain techniques for developing the BBB in vitro models. It describes subsequent research approaches and models, as they underwent change alongside technological advancement. On the one hand, we discuss possibilities and limitations of different research approaches: primary cultures vs. cell lines and monocultures vs. multicultures. On the other hand, we review advantages and disadvantages of specific models, such as models-on-a-chip, 3D models or microfluidic models. We not only attempt to state the usefulness of specific models in different kinds of research on the BBB but also emphasize the significance of this area of research for advancement of neuroscience and the pharmaceutical industry.
Management System for Integration of the Disabled on the Labour Market

People with mental disabilities (mental disorders, mild brain dysfunction) face barriers to employment, leading to higher unemployment rates and economic inactivity. Incorporating a workplace technology system may help create a disability-inclusive environment. The paper presents an ICT solution for social enterprises, focusing primarily on cafés or restaurants. It is designed to help reduce the need for supervision of employees with mental disabilities in order to increase their autonomy. The proposed system records activities and provides an employee with information on which action to perform and how. The primary goal of the proposal is the monitoring of activities and the interactive transmission of instructions. The presented system is based on the Internet of Things (IoT) and includes advanced information technologies – cloud messaging, mobile applications, web applications. The employee with a disability will be equipped with a smartphone using a specially designed application. By a notification sent to the mobile phone, the employee will be immediately informed about the task assigned. The mobile application will help an employee carry out the task visually (sequence of instructions expressed in text, pictograms). In order to confirm the completion of the task, a sensor is placed at the desk location, which, when the mobile device is attached, registers the employee's presence at the desk where the task is to be performed. The Unified Process (UP) methodology was used to design an information system. The context diagram describes the relationship between the proposed system and its environment, a data flow diagram shows the dynamics and control information. The system is designed to be universally applicable in other workplaces. It may be used to help people who cannot communicate with other employees due to a lack of knowledge of the local language at the workplace.
Stakeholder Engagement for Development Impact Evaluation and Evidence Synthesis

This paper investigates stakeholder engagement with decision-making and research for international aid and social development, to encourage decisions that are both evidence-informed and appropriate to their context. The vision is for policy makers, programme managers and practitioners making decisions to engage with formal research about causal relationships and contextual influences (such as impact evaluations or systematic reviews), and to combine this with the know-how and tacit knowledge from those most intimately involved in the issues at hand. The rationale is that: stakeholders make better decisions when they engage with research findings; stakeholder engagement with the research process leads to research that takes into account their interests and concerns; and, in the absence of research, stakeholders’ familiarity with the local context is the starting point for informing decisions and new research.
Catalytic Sabatier Process under Thermally and Magnetically Induced Heating: A Comparative Case Study for Titania-Supported Nickel Catalyst

In the present paper, we compare the activity, selectivity, and stability of a supported nickel catalyst in classical heating conditions and in magnetically activated catalysis by using iron wool as a heating agent. The catalyst, 5 wt% Ni supported on titania (Degussa P25), was prepared via an organometallic decomposition method and was thoroughly characterized by using elemental, microscopic, and diffraction techniques. In the event of magnetic induction heating, the % CO2 conversion reached a maximum of ~85% compared to ~78% for thermal conditions at a slightly lower temperature (~335 °C) than the thermal heating (380 °C). More importantly, both processes were found to be stable for 45 h on stream. Moreover, the effects of magnetic induction and classical heating over the catalyst evolution were discussed. This study demonstrated the potential of magnetic heating-mediated methanation, which is currently under investigation for the development of pilot-scale reactors.
An Experience in the Gather.town: Factors That Promote Immersion in Systems for the Metaverse

: As UX becomes important in future digital technologies, Immersion is considered an essential UX aspect in emerging technologies, including Metaverse. Big tech companies have been interested in Metaverse platforms and services. Because the Metaverse has only recently begun to be studied, We are still on the way to exploring it, although its concept has been proposed for more than 30 years. We present an investigation into the factors that promote Immersion in Metaverse platforms using Gather.town. We promote an immersive experience on the Gather.town platform and then conduct a focus group to capture participants’ perceptions. We performed a qualitative analysis to identify the factors that most contributed to the Immersion in the experience. Our findings provide implications for how the Metaverse platforms should be designed and what factors should be emphasized to promote a good user experience in terms of Immersion.