Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Validation of Virtual Reality Task for Neuro-Rehabilitation of Distal Upper Extremities

Stroke, affecting approximately 15 million people worldwide, has long been a global cause of death and disability. Virtual Reality (VR) has shown its potential as an assistive tool for post-stroke rehabilitation. The objective of this pilot study was to define the task-specific performance metrics of VR tasks to assess the performance level of healthy subjects and patients quantitatively and to obtain their feedback for improving the developed framework. A pilot prospective study was designed. We tested the designed VR tasks on forty healthy right-handed subjects to evaluate its potential. Qualitative trajectory plots and three quantitative performance metrics—time taken to complete the task, percentage relative error, and trajectory smoothness—were computed from the recorded data of forty healthy subjects. Two patients with stroke were also enrolled to compare their performance with healthy subjects. Each participant received one VR session of 90 min. No adverse effects were noticed throughout the study. Performance metrics obtained from healthy subjects were used as a reference for patients. Relatively higher values of task completion time and trajectory smoothness and lower values of relative % error was observed for the affected hands w.r. t the unaffected hands of both the patients. For the unaffected hands of both the patients, the performance levels were found objectively closer to that of healthy subjects. A library of VR tasks for wrist and fingers were designed, and task-specific performance metrics were defined in this study. The evaluation of the VR exercises using these performance metrics will help the clinicians to assess the patient’s progress quantitatively and to design the rehabilitation framework for a future clinical study.
New Evidence of Changes in Students’ Achievement Motivation in the Context of the COVID-19 Pandemic

In an article published early in 2021, we shared results indicating that expectancy (i.e., competence beliefs) and value (i.e., interest in learning, utility value, mastery and performance goals) perceptions among a sample of 90 French Canadian students (Mage = 14.81) in grades 9 and 10 remained at similar levels from few weeks before the first wave (January 2020) to the second wave (November 2020) of the COVID-19 pandemic. One perception (i.e., interest) even improved, suggesting that, after experiencing a confinement, students re-approached in-class activities with enthusiasm. To determine if this pattern of results remained the same as the pandemic persisted, an additional measurement has been performed during the third wave. Analysis with this additional data point revealed that interest, utility value and mastery goals ended up declining. These new data suggest that, ultimately, this pandemic has negative effects on students’ motivation, even if they keep benefiting from in-class activities.
Quantifying cerebral blood flow in the whole brain in a diffusion model with multiple sources from cerebrovascular structures

Various imaging techniques have been developed to visualize the three‐dimensional structures of the brain and cerebrovascular vessels. Recently, several imaging techniques have allowed the measurement of cerebral blood flow (CBF) in the whole brain. Despite the rapid development of imaging techniques, numerical methods of predicting CBF are still challenging, due to the complexity of cerebrovascular structure modeling at the clinical level. Additionally, simulation models for oxygen and mass transport from the vasculature to tissues are not available at the clinical level due to the lack of knowledge in the field of microvascular transport. In this study, we propose a computational method to quantify CBF in the whole brain, linking cerebrovascular transport, and brain tissue perfusion. To simplify the linking process, the microvascular transport of blood was treated as a diffusion process. The concentration of CBF was predicted using our novel computational method. Furthermore, we investigated changes in CBF in cases where the blood supply to specific areas of the brain were blocked by disrupted vessels.
Homeowner Willingness to Pay for a Pre-flood Agreement for a Post-flood Buyout

Homeowner buyout programs promote climate adaptation efforts by removing homes from floodplains. We estimate homeowner willingness to pay (WTP) for a novel agreement in which they precommit to relocating if a flood severely damages their home in exchange for an expedited buyout process. We find nearly all respondents identified positive WTP to enroll in this program, with average WTP about $600. Factors like flood risk and expectation of neighbors’ responses significantly affect WTP. If the pre-flood agreement is available only if the homeowner has flood insurance, only 68% of homeowners were willing to accept the agreement.
Towards automatic discovery and assessment of vulnerability severity in cyber-physical systems

Despite their wide proliferation, complex cyber–physical systems (CPSs) are subject to cybersecurity vulnerabilities and potential attacks. Vulnerability assessment for such complex systems are challenging, partly due to the discrepancy among mechanisms used to evaluate their cyber-security weakness levels. Several sources do report these weaknesses like the National Vulnerability Database (NVD), as well as manufacturer websites besides other security scanning advisories such as Cyber Emergency Response Team (CERT) and Shodan databases. However, these multiple sources are found to face inconsistency issues, especially in terms of vulnerability severity scores. We advocate an artificial intelligence based approach to streamline the computation of vulnerability severity magnitudes. This approach decreases the error rate induced by manual calculation processes, that are traditionally used in cybersecurity analysis. Popular repositories such as NVD and SecurityFocus are employed to validate the proposed approach, assisted with a query method to retrieve vulnerability instances. In doing so, we report discovered correlations among reported vulnerability scores to infer consistent magnitude values of vulnerability instances. The method is applied to a case study featuring a CPS application to illustrate the automation of the proposed vulnerability scoring mechanism, used to mitigate cybersecurity weaknesses.
Research on Quantitative Assessment Methods of Environmental Performance in Green Design

Life cycle assessment (LCA) plays more important roles in environmental impact assessment. While there are many kinds of LCA tools, quantitative assessment with good operability and pertinence for household appliance is few, therefore green design assessment for household appliances (GDAHA) software system is developed. Quantitative assessment methods are used separately in the 8 typical environmental indicators. Radar chart conducted by integrating the results of individual assessment items is used to show design limitations for environment. At last GDAHA software system developed by the author is introduced briefly, which shows that the quantitative assessment method is operable and reasonable through series of product experiments and improvements.
Detecting Elevated Pore Pressure due to Wastewater Injection Using Ambient Noise Monitoring

The injection of large volumes of wastewater has induced earthquakes from June 2010 to July 2011 along the Guy–Greenbrier fault in Arkansas. We measure time-dependent changes in seismic velocities underneath three temporary seismic stations, using the daily autocorrelations of ambient seismic noise. We do not find any effect of the pumping rate or volume injected in the changes in velocity. However, the induced earthquakes’ ground motions are associated with an extreme reduction in seismic velocities. The magnitude of the changes surpasses ten times the values typically found in other earthquake settings. Our full-waveform investigation suggests that the changes mainly occurred around the top of the Ozark aquifer. We interpret these extreme changes as a result of dynamic shaking in the elevated pore pressure system of the Ozark aquifer.
Targeted Deletion of Kindlin-2 in Mouse Mammary Glands Inhibits Tumor Growth, Invasion, and Metastasis Downstream of a TGF-β/EGF Oncogenic Signaling Pathway

Simple Summary Studies from our group and others have established Kindlin-2 that is expressed in the cancer cells as a major driver of tumor progression and metastasis in breast cancer (BC). The role of Kindlin-2 that is expressed in the mammary glands (tumor microenvironment) in the pathogenesis of BC has, however, not been investigated. To this end, we generated a mouse strain that specifically lacks expression of Kindlin-2 in the basal cells within the mouse mammary glands. Loss of Kindlin-2 in this mammary gland compartment, while having no effect on mouse development, significantly inhibited BC tumors growth and metastasis when these Kindlin-2-deficient mice were challenged with mammary fat pad injection of cancer cells. At the molecular signaling level, we found that Kindlin-2 plays a significant role in regulating BC progression and metastasis in both the cancer cells and the tumor microenvironment (mammary epithelial cells) downstream of a TGF-β/EGF signaling axis. Abstract Breast cancer (BC) is one of the leading causes of cancer-related deaths due in part to its invasive and metastatic properties. Kindlin-2 (FERMT2) is associated with the pathogenesis of several cancers. Although the role of Kindlin-2 in regulating the invasion-metastasis cascade in BC is widely documented, its function in BC initiation and progression remains to be fully elucidated. Accordingly, we generated a floxed mouse strain by targeting the Fermt2 (K2lox/lox) locus, followed by tissue-specific deletion of Kindlin-2 in the myoepithelial compartment of the mammary glands by crossing the K2lox/lox mice with K14-Cre mice. Loss of Kindlin-2 in mammary epithelial cells (MECs) showed no deleterious effects on mammary gland development, fertility, and lactation in mice bearing Kindlin-2-deletion. However, in a syngeneic mouse model of BC, mammary gland, specific knockout of Kindlin-2 inhibited the growth and metastasis of murine E0771 BC cells inoculated into the mammary fat pads. However, injecting the E0771 cells into the lateral tail vein of Kindlin-2-deleted mice had no effect on tumor colonization in the lungs, thereby establishing a critical role of MEC Kindlin-2 in supporting BC tumor growth and metastasis. Mechanistically, we found the MEC Kindlin-2-mediated inhibition of tumor growth and metastasis is accomplished through its regulation of the TGF-β/ERK MAP kinase signaling axis. Thus, Kindlin-2 within the mammary gland microenvironment facilitates the progression and metastasis of BC.
Analyzing the career development barriers faced by rural women in India

In India, one of the most populous countries in the world, women make up approximately half of the country’s population. While most of Indian women hold the highest educational degrees and enter the workforce almost in every sector, rural women are lagging behind in their career development. The study was aimed at investigating the factors that inhibit and challenge rural women to progress in their career development. The study was conducted in two folds of data collection. The first fold is qualitative data using interviews with 10 rural women and their analysis using thematic analysis, and the second fold is quantitative research and data collection from 148 rural women using a semi-structured survey questionnaire based on the identified themes and analyzed using SPSS. The findings of the study illustrated various barriers related to personal, social, family, economic, and infrastructure issues. Respondents spoke about several challenges they face with not having support to continue their higher studies. Eighty-five percent of rural women demonstrated they are suppressed in society due to gender stereotypes and are predominantly overburdened with family responsibilities. Furthermore, the study recommends significant implications for Indian women and the government from a global perspective.
Biocomposite of Cassava Starch-Cymbopogan Citratus Fibre: Mechanical, Thermal and Biodegradation Properties

Increasing environmental awareness and concern have shifted the focus of research and development towards biodegradable materials development. In the current study, Cymbopogan citratus fibre (CCF) were incorporated into thermoplastic cassava starch (TPCS) with various content of CCF (10, 20, 30, 40, 50, 60 wt.%) via compression moulding. The determination of fundamental characteristics of TPCS/CCF biopolymer composites was conducted to assess their potential as biodegradable reinforcements. Characterization of the samples was conducted via Fourier-transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM), as well as mechanical, moisture absorption, and soil burial testings. The findings showed that the improved tensile and flexural features of the TPCS composites with CCF incorporation, with 50 wt. % CCF content yielded the maximum modulus and strength. The thermal properties of the biocomposite demonstrated that CCF addition improved the material’s thermal stability, as shown by a higher-onset decomposition temperature and ash content. Meanwhile, the CCF incorporation into TPCS slowed down the biodegradation of the composites. In term of morphological, homogeneous fibres and matrix dispersion with excellent adhesion was observed in morphological analyses using scanning electron microscopy (SEM), which is crucial for the enhancement of the mechanical performance of biocomposites.
An overview of SrRuO3-based heterostructures for spintronic and topological phenomena

SrRuO3 (SRO)-based heterostructures have attracted much attention for potential applications such as electrodes, oxide spintronics, topological electronics and electrocatalytic function mainly due to the strong spin–orbit coupling, itinerant ferromagnetism with 4d electrons, high metallic conductivity, perpendicular magnetic anisotropy and rich oxygen octahedral distortion of SRO. Here, this work aims to offer a timely and systematic review on SRO-based heterostructures for its emerging opportunities in oxide spintronic and topological electronic applications. We first present a brief summary of the current status in SRO-based heterostructures and describe the motivations of this review. We then briefly review the surface and interface modulation in SRO-based heterostructures, including oxygen octahedral distortions (antiferrodistortive mode and ferroelectric mode) engineering and ion defect engineering. In the third part, we discuss the spin-charge interconversion phenomena in SRO-based heterostructures, covering the inverse spin Hall effect and current-induced spin-orbit torques. Particularly, in the fourth part, we discuss the emergent topological Hall effect and underlying mechanism in SRO-based heterostructures, including the two-channel anomalous Hall effect and Berry phase manipulation. The fifth part presents the magnetic Weyl fermions and its electric-field control of SRO films. We finally conclude with a discussion of challenges and prospects of SRO-based heterostructures, which provides a guidance for exploring novel physical properties and designing multifunctional devices based on SRO.
Phenotypic Variation in European Wild Pear (Pyrus pyraster (L.) Burgsd.) Populations in the North-Western Part of the Balkan Peninsula

Leaves play a central role in plant fitness, allowing efficient light capture, gas exchange and thermoregulation, ensuring optimal growing conditions for the plant. Phenotypic variability in leaf shape and size has been linked to environmental heterogeneity and habitat characteristics. Therefore, the study of foliar morphology in plant populations can help us to identify the environmental factors that may have influenced the process of species diversification. In this study, we used European wild pear (Pyrus pyraster (L.) Burgsd. , Rosaceae) as a model species to investigate the phenotypic variability of leaves under different environmental conditions. Using leaf morphometric data from 19 natural populations from the north-western part of the Balkan Peninsula, a high level of variability among and within populations were found. Leaf traits related to leaf size were more variable compared to leaf shape traits, with both influenced by geographic and environmental factors. Consequently, patterns of isolation by environment (IBE) and distance (IBD) were identified, with IBE showing a stronger influence on leaf variability. Multivariate statistical analysis revealed that European wild pear populations from the north-western part of the Balkan Peninsula can be divided into two morphological clusters, consistent with their geographical distance and environmental conditions. Our results confirm a high level of phenotypic variability in European wild pear populations, providing additional data on this poorly studied species, emphasizing phenotypic plasticity as a major driver in the adaptation of this noble hardwood species to rapid climate change.
Opioid Consumption in Chronic Pain Patients: Role of Perceived Injustice and Other Psychological and Socioeconomic Factors

Background: Chronic pain is a complex biopsychosocial phenomenon. Lifestyle, behavioral, socioeconomic, and psychosocial factors such as depression and perceived injustice are often associated with the development of chronic pain and vice versa. We sought to examine the interaction of these factors with opioid intake. Methods: At our institution, 164 patients with chronic pain undergoing an interdisciplinary assessment within a three-month period participated in the study and completed the Injustice Experience Questionnaire (IEQ). Data regarding opioid intake, pain levels, pain diagnosis, depression, anxiety, stress, quality of life, pain-related disability, habitual well-being, occupational status, and ongoing workers compensation litigation were extracted from the patients’ charts. Results: Approximately one-fourth of the patients used opioids. The IEQ total was significantly higher in patients using Schedule III opioids. Depression, but not the anxiety and stress scores, were significantly higher in patients using opioids. There were no significant differences regarding pain-related disability, habitual well-being, and the coded psychosocial diagnoses. In the patient group without opioids, the percentage of employed persons was significantly higher but there were no significant differences regarding work leave, pension application, or professional education. Conclusions: Opioid use appears to be more closely related to psychological factors and single social determinants of pain than to somatic factors.
Potential Differences in the Cardiometabolic Risk Profile of Patients with Psoriatic Disease according to Their HLA-C∗06 Status

The human leukocyte antigen-C∗06 (HLA-C∗06, formerly HLA-Cw6) is the main genetic biomarker in psoriatic disease. It has been related to several phenotypic traits in psoriatic disease, but its role in relation to cardiometabolic comorbidities is unknown at present. Here, we analyze the potential connections between this biomarker and the cardiometabolic profile of these patients. We carried out a cross-sectional observational study including 400 patients recruited at a single university hospital. Clinical and classical cardiometabolic factors were compared between HLA-C∗06-positive and HLA-C∗06-negative individuals (OR with 95% CI). Multivariate regression analyses were carried out to check for disease traits associated with different cardiometabolic risk factors. The study population included 215 men (53.8%) and 185 women (46.2%), mean age of 46 ± 15 years, and an average disease evolution of 17 ± 12.6 years. Ninety-three (23.3%) patients met CASPAR criteria for psoriatic arthritis. HLA-C∗06 carriers (n: 160, 40%) showed an earlier age at disease onset, psoriasis family history, and more severe skin disease (type I disease). After correcting for age, sex, and disease duration, they also showed less hypertension (13.8% vs. 24.2%, OR 0.7 (95% CI: 0.42-0.78), p = 0.025), lower waist circumference (94.4 ± 13.7 vs. 98.3 ± 13.8 cm), and lower BMI (27 ± 4.4 vs. 28.1 ± 4.8, p < 0.05). We confirmed the well-known association between HLA-C∗06 and type I psoriatic disease. As a novel finding, patients carrying HLA-C∗06 showed a better cardiometabolic profile. In any case, these findings need further confirmation.
Attitude plus angular rate matching method for shipboard transfer alignment

The transfer alignment methods with measurement parameters are limited by sea condition,so an attitude plus angular rate matching method is put forward.In this paper,the deformation of ship's deck and the constant drift of gyros under three typical sea conditions is estimated using this method with Kalman filter,and the estimate precision is interpreted.The feasibility of the calibration of gyro drift is analyzed in detail as well.Study results show that higher precision and shorter response time with robust is obtained.The calibration of gyro drift is depended on the magnitude of dynamic deformation of ship's deck.
End-to-End Modeling and Transfer Learning for Audiovisual Emotion Recognition in-the-Wild

As emotions play a central role in human communication, automatic emotion recognition has attracted increasing attention in the last two decades. While multimodal systems enjoy high performances on lab-controlled data, they are still far from providing ecological validity on non-lab-controlled, namely “in-the-wild” data. This work investigates audiovisual deep learning approaches to emotion recognition in in-the-wild problem. Inspired by the outstanding performance of end-to-end and transfer learning techniques, we explored the effectiveness of architectures in which a modality-specific Convolutional Neural Network (CNN) is followed by a Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) using the AffWild2 dataset under the Affective Behavior Analysis in-the-Wild (ABAW) challenge protocol. We deployed unimodal end-to-end and transfer learning approaches within a multimodal fusion system, which generated final predictions using a weighted score fusion scheme. Exploiting the proposed deep-learning-based multimodal system, we reached a test set challenge performance measure of 48.1% on the ABAW 2020 Facial Expressions challenge, which advances the first-runner-up performance.
Antidiabetic Potential of Volatile Cinnamon Oil: A Review and Exploration of Mechanisms Using In Silico Molecular Docking Simulations

Cinnamon has been used as a flavoring and medicinal agent for centuries. Much research has focused on cinnamon bark powder, which contains antioxidants, flavonoids, carotenoids, vitamins, minerals, fiber, and small amounts of essential oil. However, isolated and concentrated cinnamon essential oil may also have important medicinal qualities, particularly in antidiabetic therapy. Some of the most common essential oil constituents identified in the literature include cinnamaldehyde, eugenol, and beta-caryophyllene. Due to their high concentration in cinnamon essential oil, these constituents are hypothesized to have the most significant physiological activity. Here, we present a brief review of literature on cinnamon oil and its constituents as they relate to glucose metabolism and diabetic pathogenesis. We also present molecular docking simulations of these cinnamon essential oil constituents (cinnamaldehyde, eugenol, beta-caryophyllene) that suggest interaction with several key enzymes in glucometabolic pathways.