Miracle-dz/UniFAR-FTUs huggingface dataset:
Immediate Biomechanical Effects of Providing Adaptive Assistance with an Ankle Exoskeleton in Individuals After Stroke

Recent studies on ankle exoskeletons have shown the feasibility of this technology for post-stroke gait rehabilitation. The main contribution of the present work is a comprehensive experimental analysis and protocol that focused on evaluating a wide range of biomechanical, usability and users’ perception metrics under three different walking conditions: without exoskeleton, with an ankle exoskeleton unpowered, and with an ankle exoskeleton powered. To carry out this study, we developed the ABLE-S exoskeleton that can provide time-adapted ankle plantarflexion and dorsiflexion assistance. Tests with five participants with chronic stroke showed that walking with the ABLE-S exoskeleton significantly corrected foot drop by 25 % while reducing hip compensatory movements by 21 %. Furthermore, asymmetrical spatial gait patterns were significantly reduced by 51 % together with a significant increase in the average foot tilting angle at heel strike by 349 %. The total time to don, doff and set-up the device was of 7.86 ± 2.90 minutes. Finally, 80 % of the participants indicated that they were satisfied with their walking performance while wearing the exoskeleton, and 60 % would use the device for community ambulation. The results of this study add to the existing body of evidence supporting that ankle exoskeletons can improve gait biomechanics for post-stroke individuals.
Maternal Race and Stillbirth: Cohort Study and Systematic Review with Meta-Analysis

Accurate identification of independent predictors of stillbirth is needed to define preventive strategies. We aim to examine the independent contribution of maternal race in the risk of stillbirth after adjusting for maternal characteristics and medical history. There are two components to the study: first, prospective screening in 168,966 women with singleton pregnancies coordinated by the Fetal Medicine Foundation (FMF) and second, a systematic review and meta-analysis of studies reporting on race and stillbirth. In the FMF study, logistic regression analysis found that in black women, the risk of stillbirth, after adjustment for confounders, was higher than in white women (odds ratio 1.78, 95% confidence interval 1.50 to 2.11). The risk for other racial groups was not significantly different. The literature search identified 20 studies that provided data on over 6,500,000 pregnancies, but only 10 studies provided risks adjusted for some maternal characteristics; consequently, the majority of these studies did not provide accurate contribution of different racial groups to the prediction of stillbirth. It is concluded that in women of black origin, the risk of stillbirth, after adjustment for confounders, is about twofold higher than in white women. Consequently, closer surveillance should be granted for these women.
Parental Burnout in Hungary - Development and Psychometric Evaluation of the Hungarian Parental Burnout Assessment (PBA-HUN)

Introduction: Parental burnout might take place when excessive demands overwhelm the parents’ resources. Aims: To develop and validate the Hungarian version of the Parental Burnout Assessment (PBA-HUN), an instrument designed to measure parental burnout; and to determine the prevalence of parental burnout in Hungary. Methods: Data were collected via an online survey from parents with at least one child living in the household (N = 1215; 82.6% mothers; Mage = 38.68 years; SDage = 6.27 years). Confirmatory factor analysis was used to investigate the factor structure of the PBA-HUN. Results: The four-factor structure of the original PBA was replicated, confirming the following factors: exhaustion in one’s parental role, contrast with one’s parental role, feelings of being fed up, and emotional distancing from one’s children. A second-order model with a higher-order factor representing overall parental burnout also fit the data well. The internal consistency of both the subscale and total scores was excellent (α ≥ 0.84). Parental burnout had a moderately strong negative correlation with life satisfaction, and weak or moderate positive correlations with perceived stress, depression, vital exhaustion, and COVID-specific perceived stress supporting the construct validity of the PBA-HUN. The prevalence of parental burnout stood at 5.8% in this sample. The weak relationship between PBA-HUN scores and sociodemographic factors was also similar to those found in prior studies. Parental burnout correlated negatively with the number of hours spent sleeping and engaging in spare time activity, respectively. Conclusions: The PBA-HUN is a reliable and valid tool to assess parental burnout in Hungary.
Accounting for Lambertian reflection in the assimilation of microwave sounding radiances over snow and sea‐ice

This article investigates two aspects aimed at an increased use of surface‐sensitive microwave sounding radiances for numerical weather prediction (NWP), namely the assimilation of humidity‐sounding radiances from the Advanced Technology Microwave Sounder (ATMS) over snow, as well as the use of Lambertian reflection in radiative‐transfer modelling over snow and sea‐ice surfaces for temperature‐ and humidity‐sounding radiances. The Lambertian characteristics are modelled through a parameterisation of the effective zenith angle used to calculate the downwelling radiation in the radiative‐transfer model. Using Lambertian rather than specular reflection improves the forward modelling significantly for 183‐GHz humidity‐sounding channels over snow and sea‐ice in comparisons with observations, including a reduction of significant zenith‐angle‐dependent biases. For temperature‐sounding channels in the 50‐GHz band, comparisons between observations and background equivalents also suggest improvements from treating snow and sea‐ice surfaces as Lambertian or semi‐Lambertian, but the characteristics appear more variable and there are indications of other sources of error, such as biases in the skin temperature. For both spectral regions, the improvement from using nonspecular reflection is clearest for snow‐covered land surfaces. Assimilation experiments show that the addition of 183‐GHz humidity‐sounding channels from ATMS over snow‐covered land leads to a slight positive impact over higher latitudes in winter. On top of this, replacing the specular surface assumption over snow and sea‐ice with a fully Lambertian one for 183‐GHz channels on ATMS and semi‐Lambertian one for 50‐GHz channels on ATMS and the Advanced Microwave Sounding Unit–A (AMSU‐A) means that more observations pass quality control, giving a neutral to slightly positive impact at higher latitudes in winter. Combining the two changes leads to small forecast benefits that are statistically significant up to day 3 at higher latitudes.
Variability in the Pre-Analytical Stages Influences Microbiome Laboratory Analyses

Introduction: There are numerous confounding variables in the pre-analytical steps in the analysis of gut microbial composition that affect data consistency and reproducibility. This study compared two DNA extraction methods from the same faecal samples to analyse differences in microbial composition. Methods: DNA was extracted from 20 faecal samples using either (A) chemical/enzymatic heat lysis (lysis buffer, proteinase K, 95 °C + 70 °C) or (B) mechanical and chemical/enzymatic heat lysis (bead-beating, lysis buffer, proteinase K, 65 °C). Gut microbiota was mapped through the 16S rRNA gene (V3–V9) using a set of pre-selected DNA probes targeting >300 bacteria on different taxonomic levels. Apart from the pre-analytical DNA extraction technique, all other parameters including microbial analysis remained the same. Bacterial abundance and deviations in the microbiome were compared between the two methods. Results: Significant variation in bacterial abundance was seen between the different DNA extraction techniques, with a higher yield of species noted in the combined mechanical and heat lysis technique (B). The five predominant bacteria seen in both (A) and (B) were Bacteroidota spp. and Prevotella spp. (p = NS), followed by Bacillota (p = 0.005), Lachhnospiraceae (p = 0.0001), Veillonella spp. (p < 0.0001) and Clostridioides (p < 0.0001). Conclusion: As microbial testing becomes more easily and commercially accessible, a unified international consensus for optimal sampling and DNA isolation procedures must be implemented for robustness and reproducibility of the results.
Targeting the very important buyers VIB: A cluster analysis approach

Abstract The Pareto Principle, known as the 80/20 rule, predicts that most sales generate from a minority of buyers. Further, consumer theory stipulates certain shoppers have a preference to consume experience versus tangible goods. Some people value the consumption of experience due to lifestyle and innate factors. Following a cluster analysis approach, this paper collected survey data from 700 consumers (adults that belonged to a consumer panel) to examine these propositions. The results support the propositions and show that the e-market comprises three segments: VIB of Experience, VIB of Material, and Normals. The discriminatory analysis shows that the affluent shoppers of experience diverge from the other segments on psychological and lifestyle factors. In addition, social class helps pinpoint these shoppers. Whereas VIB of Experience primarily belong to the Upper Uppers and the Upper Middles, VIB of Material belong to the Lower Uppers and the generic Middle Class. The results are of value to practitioners that aim to target affluent shoppers of experience versus affluent shoppers of material goods. The results suggest that the affluent e-shoppers are not homogeneous according to their shopping preference and highlight the relevance of the Pareto Principle to segment and target the e-shoppers.
Fisetin Attenuated Oxidative Stress-Induced Cellular Damage in ARPE-19 Human Retinal Pigment Epithelial Cells Through Nrf2-Mediated Activation of Heme Oxygenase-1

Fisetin is a kind of bioactive flavonol, widely present in various fruits such as strawberries and apples, and is known to act as a potent free radical scavenger. However, the mechanism of action related to the antioxidant activity of this compound in human retinal pigment epithelial (RPE) cells is not precisely known. In this study, we aimed to investigate whether fisetin could attenuate oxidative stress-induced cytotoxicity on human RPE ARPE-19 cells. To mimic oxidative stress, ARPE-19 cells were treated with hydrogen peroxide (H2O2), and fisetin significantly inhibited H2O2-induced loss of cell viability and increase of intracellular reactive oxygen species (ROS) production. Fisetin also markedly attenuated DNA damage and apoptosis in H2O2-treated ARPE-19 cells. Moreover, mitochondrial dysfunction in H2O2-treated cells was alleviated in the presence of fisetin as indicated by preservation of mitochondrial membrane potential, increase of Bcl-2/Bax expression ratio, and suppression of cytochrome c release into the cytoplasm. In addition, fisetin enhanced phosphorylation and nuclear translocation of nuclear factor erythroid 2 related factor 2 (Nrf2), which was associated with increased expression and activity of heme oxygenase-1 (HO-1). However, the HO-1 inhibitor, zinc protoporphyrin, significantly reversed the protective effect of fisetin against H2O2-mediated ARPE-19 cell injury. Therefore, our results suggest that Nrf2-mediated activation of antioxidant enzyme HO-1 may play an important role in the ROS scavenging activity of fisetin in RPE cells, contributing to the amelioration of oxidative stress-induced ocular disorders.
Machine Learning Patient-Specific Prediction of Heart Failure Hospitalization Using Cardiac MRI-Based Phenotype and Electronic Health Information

Background Heart failure (HF) hospitalization is a dominant contributor of morbidity and healthcare expenditures in patients with systolic HF. Cardiovascular magnetic resonance (CMR) imaging is increasingly employed for the evaluation of HF given capacity to provide highly reproducible phenotypic markers of disease. The combined value of CMR phenotypic markers and patient health information to deliver predictions of future HF events has not been explored. We sought to develop and validate a novel risk model for the patient-specific prediction of time to HF hospitalization using routinely reported CMR variables, patient-reported health status, and electronic health information. Methods Standardized data capture was performed for 1,775 consecutive patients with chronic systolic HF referred for CMR imaging. Patient demographics, symptoms, Health-related Quality of Life, pharmacy, and routinely reported CMR features were provided to both machine learning (ML) and competing risk Fine-Gray-based models (FGM) for the prediction of time to HF hospitalization. Results The mean age was 59 years with a mean LVEF of 36 ± 11%. The population was evenly distributed between ischemic (52%) and idiopathic non-ischemic cardiomyopathy (48%). Over a median follow-up of 2.79 years (IQR: 1.59–4.04) 333 patients (19%) experienced HF related hospitalization. Both ML and competing risk FGM based models achieved robust performance for the prediction of time to HF hospitalization. Respective 90-day, 1 and 2-year AUC values were 0.87, 0.83, and 0.80 for the ML model, and 0.89, 0.84, and 0.80 for the competing risk FGM-based model in a holdout validation cohort. Patients classified as high-risk by the ML model experienced a 34-fold higher occurrence of HF hospitalization at 90 days vs. the low-risk group. Conclusion In this study we demonstrated capacity for routinely reported CMR phenotypic markers and patient health information to be combined for the delivery of patient-specific predictions of time to HF hospitalization. This work supports an evolving migration toward multi-domain data collection for the delivery of personalized risk prediction at time of diagnostic imaging.
Assessing the predictive validity of a risk assessment instrument for repeat victimization in the Netherlands using prior police contacts

The current study examined to what extent a valid instrument that predicts repeat victimization can be based on a victim's prior police contacts. Police records between 2010 and 2017 were retrieved for a sample of 68,229 victims. The data was split into a training set (n = 34,224) and a test set (n = 34,005). Using logistic regression analyses in the training set, three models were developed linking prior police contacts to repeat victimization. The predictive validity was assessed in the test set. Results indicated that (a) prior police contacts as victims, suspects and witnesses were associated with an elevated risk of repeat victimization and (b) the model correctly classified a majority of both repeat victims and non-repeat victims across various cut-off points. Findings demonstrated moderate to acceptable predictive validity, thereby suggesting that there is considerable room for improvement.
Strategies and challenges in treatment of varicose veins and venous insufficiency

Patients with varicose veins can be treated with conservative or surgical approaches based on the clinical conditions and patient preferences. In the recent decade, the recommendations for managing symptomatic varicose veins have changed dramatically due to the rise of minimally invasive endovascular techniques. The literature was systematically searched on Medline without language restrictions. All papers on the treatment of varicose veins and venous insufficiency with different procedures were included and reviewed. Endovenous laser ablation (EVLA) and radiofrequency ablation (RFA) both are same safe and effective in terms of occlusion rate, and time to return to normal activity. In comparison with RFA or EVLT, Cure conservatrice et Hemodynamique de l'Insufficience Veineuse en Ambulatoire (CHIVA) may cause more bruising and make little or no difference to rates of limb infection, superficial vein thrombosis, nerve injury, or hematoma. In terms of recurrence of varicose veins, there is little or no difference between CHIVA and stripping, RFA, or EVLT. Great saphenous vein recanalization is highest in the ultrasound-guided foam sclerotherapy (FS) group (51%) during 1 year of follow-up. The 2013 National Institute for Health and Care Excellence clinical guidelines recommend surgery as a third-line therapeutic option after EVLA or RFA and sclerotherapy. Although the mechanochemical endovenous ablation (MOCA) is a non-thermal, non-tumescent option and appears to be of similar efficacy to stab avulsion with no potential risk of nerve damage, the overall success rate of MOCA is lower than those of other procedures such as EVLA, RFA, or high ligation and stripping. EVLA is the most cost-effective therapeutic option, with RFA being a close second for the treatment of patients with varicose veins. Endovenous thermal ablation (EVLA or RFA) is recommended as a first-line treatment for varicose veins and has substituted the high ligation of saphenofemoral junctional reflux and stripping of varicose veins. Ultrasound-guided FS is associated with a high recurrence rate and can be used in conjunction with other procedures. MOCA and cyanoacrylate embolization appear promising, but evidence of their effectiveness is required.
Developing a Validated Instrument to Measure Students’ Active Learning and Actual Use of Information and Communication Technologies for Learning in Saudi Arabia’s Higher Education

Higher education authorities have supplied information and communication technologies (ICTs) to guarantee that students use ICT to improve their learning and research outputs. ICT, on the other hand, has been proven to be underused, particularly by students. Therefore, we aimed to develop a new model to measure students’ active learning and actual use of ICT in higher education. To investigate this issue, the technology acceptance model and constructivism learning theory were verified and applied to evaluate university students’ use of ICT for active learning purposes. The participants in the study were 317 postgraduate and undergraduate students from four faculties at King Faisal University who consented to take part. The research data were analyzed using structural equation modeling (AMOS-SEM). Three specific components were used: the technology adoption model, constructivism learning, and active learning using ICT. The findings revealed that: (a) using ICTs for students’ interactivity, engagement, expected effort, subjective norm, and perceived ease of use has a direct positive impact on perceived enjoyment and usefulness; (b) perceived enjoyment and usefulness has a direct positive impact on active learning, attitude toward use, and behavioral intention to use ICTs; (c) active learning has a direct positive impact on attitude toward use, behavioral intention to use ICTs; and (d) active learning has a direct positive impact on attitude. Moreover, the results showed the mediator factors’ values positively “R square,” active learning (0.529), attitude toward use (0.572), behavioral intention to use (0.583), and actual ICT use (0.512) in higher education. Therefore, the results of the hypotheses developed a validated instrument to measure students’ active learning and actual use of ICTs in higher education in Saudi Arabia.
Developing and validating an affordable whole body vibration measurement device

Long term exposure to whole-body vibration is a known cause of back pain and other adverse health effects. Exposure to vibration also contributes to operator fatigue and discomfort, and may interfere with task performance. Many operators of mobile plant and equipment used in surface and underground mines across the whole industry are exposed to signi@icant whole-body vibration for relatively long periods.The aim of the project is to develop and validate an iOS application to convert an iPod Touch into an affordable whole body vibration measurement tool which will enable surface coal mines to gather the data necessary to effectively manage this health hazard.
Little Impact of NaCl Reduction in Swiss-Type Cheese

Reducing salt intake can mitigate the prevalence of metabolic disorders. In fermented foods such as cheeses, however, salt can impact the activity of desirable and undesirable microorganisms and thus affect their properties. This study aimed to investigate the effect of salt level on Swiss-type cheese ripening. Since proteolysis is a major event in cheese ripening, three strains of Lactobacillus helveticus were selected on the cell-envelope proteinase (CEP) they harbor. Their proteolytic activity on caseins was studied at six salt levels (0–4.5%) at pH 7.5 and 5.2. Swiss-type cheeses were manufactured at regular, increased, and decreased salt concentrations, and characterized for their composition and techno-functional properties. L. helveticus strains possessed and expressed the expected CEPs, as shown by PCR and shaving experiments. The two strains of L. helveticus that possessed at least the CEP PrtH3 showed the greatest proteolytic activity. Casein hydrolysis in vitro was similar or higher at pH 5.2, i.e., cheese pH, compared to pH 7.5, and slightly decreased at the highest salt concentrations (3.0 and 4.4%). Similarly, in ripened cheeses, these L. helveticus strains showed 1.5–2.4 more proteolysis, compared to the cheeses manufactured without L. helveticus. Regarding the salt effect, the 30% salt-reduced cheeses showed the same proteolysis as regular cheeses, while the upper-salted cheeses showed a slight decrease (−14%) of the non-protein fraction. The microbial and biochemical composition remained unchanged in the 30%-reduced cheeses. In contrast, Propionibacterium freudenreichii, used as ripening bacteria in Swiss cheese, grew more slowly in upper-salted (1.14%, w/w) cheeses, which induced concomitant changes in the metabolites they consumed (−40% lactic acid) or produced (fivefold decrease in propionic acid). Some cheese techno-functional properties were slightly decreased by salt reduction, as extrusion (−17%) and oiling off (−4%) compared to regular cheeses. Overall, this study showed that a 30% salt reduction has little impact in the properties of Swiss-type cheeses, and that starters and ripening cultures strains could be chosen to compensate changes induced by salt modifications in Swiss-type and other hard cheeses.
RFID-Based Indoor Positioning Using Edge Machine Learning

Indoor positioning of objects and people is becoming of great importance in the Internet of Things (IoT), in-home automation, and navigation in malls, airports, or very large buildings. Positioning is determined by multiple distance measurements between reference points and sensors. Distance measurement uses the time of flight of an ultrasonic signal traveling from an emitter to receiving sensors. This requires close synchronization between the emitter and the sensors and a sharp time resolution of the time of arrival (TOA) of the ultrasonic signal. Usually, TOA is detected using cross-correlation processing requiring significant computational resources at the sensors level. In this work, the synchronization is done using the RFID standard protocol features. The TOA detection is performed firstly by training off-line a Machine Learning model using as input the peaks indexes of the ultrasonic signal received and the output of a cross-correlation based positioning system, as ground-truth. In a second phase, the positioning is evaluated and tested on-board using the previously trained model on a microcontroller. The system architecture is presented and experimental results on the positioning accuracy are shown accordingly. Results show a mean positioning error below 25 cm in 95% of the positionings in a typical room.