Miracle-dz/UniFAR-FTUs huggingface dataset:
Title Assessing functional connectivity differences and work-related fatigue in surviving COVID-negative patients . Running title Functional Alterations and Fatigue in COVID Author Names and Affiliations

1 The recent Coronavirus Disease 2019 (COVID-19) has affected all aspects of life around 2 the world. Neuroimaging evidence suggests the novel coronavirus can attack the central 3 nervous system (CNS), causing cerebro-vascular abnormalities in the brain. This can lead 4 to focal changes in cerebral blood flow and metabolic oxygen consumption rate in the 5 brain. However, the extent and spatial locations of brain alterations in COVID-19 survivors 6 are largely unknown. In this study, we have assessed brain functional connectivity (FC) 7 using resting-state functional MRI (RS-fMRI) in 38 (25 males) COVID patients two weeks 8 after hospital discharge, when PCR negative and 31 (24 males) healthy subjects. FC was 9 estimated using independent component analysis (ICA) and dual regression. The COVID 10 group demonstrated significantly enhanced FC in regions from the Occipital and Parietal 11 Lobes, comparing to the HC group. On the other hand, the COVID group exhibited 12 significantly reduced FC in several vermal layers of the cerebellum. More importantly, we 13 noticed negative correlation of FC with self-reported fatigue within regions from the 14 Parietal lobe, which are known to be associated with fatigue. 15
Preventing and Arresting Primary Tooth Enamel Lesions Using Self- Assembling Peptide P11-4 In Vitro

Objectives: To evaluate self-assembling peptides (SAP) for caries prevention and arrest in primary tooth enamel in vitro. Materials and Methods: Overall, 180 extracted primary teeth were used. In the prevention experiment (n = 20 samples per group), self-assembling peptide for prevention (SAPP), fluoride varnish/mouthwash (FV/FMW), casein-phosphopeptide amorphous-calcium phosphate (CPP-ACP), and nanohydroxyapatite (nHA) were applied. Samples were subjected to a demineralizing pH cycling for 14 days. In the arrest experiment (n = 15/group), 60 samples were pre-demineralized; induced lesions were treated using self-assembling peptide for repair (SAPR), FV, CPP-ACP plus fluoride, and resin infiltration (RI) and submitted to pH cycling. Mineral loss and its differences as well as lesion depth were determined using transversal microradiography. Numerical data were tested for normality using Shapiro–Wilk’s test and were compared using Kruskal–Wallis test followed by pairwise comparisons utilizing multiple Mann–Whitney U tests with Bonferroni correction. The significance level was set at P < 0.05 within all tests. Results: FV (median: −46.3 [interquartile range: 175.52] vol% × µm) and FMW (−33.35 [124.65] vol% × µm) prevented caries significantly more effectively than all other groups (P < 0.001), which did not show significant preventive effects. RI (median: 4949.70 [1637.20] vol% × µm) and FV (median = 6076.05 [5190.08] vol% × µm) arrested lesions, whereas SAPR and CPP-ACPF did not show such arrest. Conclusions: FV and FMW showed the largest caries-preventive effect, whereas RI and FV arrested lesion progression in primary tooth enamel in vitro.
Formula for cervical vertebral bone age of Vietnamese people from 7 to 18 years old

Introduction: The purpose of this study was to establish a formula for cervical vertebral bone age (CVBA) based on the morphological changes of cervical vertebrae on cephalometric radiographs in Vietnamese subjects between 7 and 18 years of age. Materials and Methods: This study included 180 children and adolescents (92 boys, 88 girls), between 7 and 18 years of age, selected from the craniofacial morphology studies of the Faculty of Odonto-Stomatology, Ho Chi Minh University of Medicine and Pharmacy. The cephalometric and hand-wrist radiographs of each subject were taken simultaneously and evaluated. Eleven hand-wrist skeletal maturity indicators of Fishman were grouped into five stages: initiation and acceleration, transition, deceleration, maturation, and completion stage. A multivariate regression analysis was conducted to assess the correlation between the stages of hand-wrist BA and the morphological characteristics of the second, third, and fourth cervical vertebrae on the cephalometric radiographs. Results: A formula for CVBA was proposed as follows: CVBA = 1.92+ 0.04 FNx01 α2 + 0.03 FNx01 α4 –1.12FNx01AB3/BC3 + 3.17 FNx01 h4/w4, where α2 and α4 are anteroinferior border angles of C2 and C4; AB3/BC3 is the ratio of inferior to anterior dimension of C3; h4/w4 is the ratio of height to width of C4. The means and standard deviations of five stages of CVBA will be as follows: CVBA I= 1.527 ± 0.906; CVBA II= 2.732 ± 0.568; CVBA III= 3.762 ± 0.589; CVBA IV= 5.077 ± 0.840; and CVBA V= 5.820 ± 0.661. Conclusion: The quantitative CVBA method could be useful to assess the level of skeletal maturation in orthodontic and orthopedic treatments.
Association between family behaviors and self-care activities among type-II diabetes mellitus patients at a teaching hospital in Kathmandu, Nepal

BACKGROUND: Self-care activities are associated with prognosis of type-II diabetes mellitus patients and include medication adherence, dietary adherence, physical activity, self-monitoring of blood glucose (SMBG), and appropriate foot care. The behaviors of a patient's family members can influence the patient's self-care activities, but little data exist on this association. The objective of this study was to assess the extent of the association between behaviors of family members of Type-II diabetes patients and the patients' self-care activities. MATERIALS AND METHODS: We conducted a cross-sectional study at a teaching hospital in Kathmandu, Nepal, and interviewed 411 outpatients with Type-2 diabetes mellitus. We used exploratory factor analysis to group family members' behaviors into 3 domains (”authoritarian,” “supportive,” and “planning” behaviors) and graded the level of the behavior into 3 categories (”high” vs. “medium” vs. “low”) according to its ranking distribution in each domain. We assessed the association between domains of family behavior and self-care activities using multivariate logistic regression with Bonferroni correction. RESULTS: High (vs. low) level of supportive behavior was associated with compliance to SMBG (58% vs. 11%; adjusted odds ratio [OR] =7.44; 95% confidence interval [CI] =2.41, 23.01). High (vs. low) level of planning behavior was associated with high level of foot care adherence (64% vs. 21%; adjusted OR = 6.03; 95% CI = 3.01, 12.11). CONCLUSIONS: We found associations between behaviors of diabetes patients' family members and the patients' own self-care behaviors. However, the incongruence between the family behavior measurement questions and the self-care of interest limited the implications of the findings.
Reactive Power Capability of DFIG-based Wind Power Generator Considering Static Stability Constraint

For voltage issue caused by large-scale wind farm integration into grid,this paper introduces the power relationship of doubly-fed induction generator(DFIG) and summarizes the research results on the inherent reactive power capability of DFIG.The power-angle characteristic of DFIG and the impacts of static stability constraint and grid code on the reactive power regulation of DFIG are analyzed.Based on these,reactive power regulation capability of DFIG with constraints,such as operation limit,static stability,and grid code,is analyzed.By simulation of actual DFIG,it is shown that the reactive power regulation capability of DFIG considering multi-constraints is closer to the actual.Also,it can help DFIG take part in the grid voltage regulation in wind power integrated region according to accurate reactive power regulation capability of DFIG.
Deep Learning for Prediction of Non-Accidental Trauma from Electronic Health Records

Non-accidental traumas (NATs) are intentionally inflicted injuries that are deadly and challenging to predict. Anticipation of future NATs could inform clinical interventions to prevent harmful outcomes. Using a comprehensive electronic health record (EHR) database, we developed an embedding strategy to map patient trajectories to a shared latent space, containing information about diagnostic codes, procedural history, demographics, and visit timing. Using these embeddings, we developed two deep learning models for prediction of future NAT: a Long Short Term Memory (LSTM) model and a Bidirectional Encoder Representations from Transformers (BERT) model. Our best performing model was a pretrained and finetuned BERT model, which achieved an area under the ROC curve of 0.79, average precision of 0.78, and accuracy of 0.72.
Monitoring Sargassum Inundation on Beaches and Nearshore Waters Using PlanetScope/Dove Observations

Sargassum beaching events have been reported in recent years around the Caribbean Sea and FL, USA, causing numerous environmental and economic problems. Satellite remote sensing has been widely used to monitor Sargassum blooms in open waters, yet due to either coarse spatial resolution or low-revisit frequency, it is difficult to provide timely information on Sargassum inundation from traditional satellite instruments. In this study, we demonstrate the capacity of 3-m resolution daily Dove imagery in monitoring Sargassum beaching events on Miami beach (FL, USA) and Cancun beach (Mexico). A U-net deep learning (DL) computer model is developed to extract Sargassum features from Dove imagery over beaches and nearshore waters. Application of the model to Dove image sequences between May and August 2019 shows two major inundation events on both Miami beach and Cancun beach, consistent with local reports. With the availability of 3-m resolution PlanetScope/Dove and PlanetScope/SuperDove data around the globe, the findings suggest that it is possible to monitor dynamic inundation events of not only Sargassum but also other macroalgae in many other regions.
Nonlinear control design for walking assistance training robotic systems

In this paper, the control problem for a novel walking assistance training robot is considered where the main objective is utilizing the robot to control the tilt angle and the position of a user. First, the novel walking assistance training robot together with a user is modeled as a nonlinear dynamical system in state space form with control input where the control input includes two elements standing for pulling forces on two straps which attach to the chest and back, respectively, of the user. Then, based on the nonlinear dynamical system and some results proposed in this paper, a feedback control system is developed, and a nonlinear state feedback control algorithm is designed where the control input includes two parts, namely, a dynamical part and a constant part. By doing this, it is ensured that the feedback control system is stable, and achieves the main objective under some limits for the control input. A simulation example is given to illustrate the effectiveness and performance of the proposed nonlinear state feedback control algorithm.
CU-Net: A New Improved Multi-Input Color U-Net Model for Skin Lesion Semantic Segmentation

Melanoma is considered one of the most dangerous skin cancer diseases that threaten human health and life. Early diagnosis of melanoma is a big challenge, especially with the presence of color variations across similar lesion types. Automatic skin lesion segmentation is an essential step to build a successful skin disease classification system. Recent deep learning architectures significantly improve the skin lesion segmentation results. Especially, U-Net deep convolutional neural network (CNN) is considered one of the state-of-the-art models with promising performance. Most deep CNNs and particularly U-Net model utilize a single input RGB color image for skin lesion semantic segmentation. However, RGB color space is not usually the best choice to represent the invariant characteristics of skin lesion chromatic information. The selection of the optimal color space significantly affects the performance of segmentation results. In this paper, three novel variants of U-Net model with single, dual, and triple inputs, namely, Single Input Color U-Net (SICU-Net), Dual Input Color U-Net (DICU-Net) and Triple Input Color U-Net (TICU-Net) are proposed. The structure of SICU-Net, DICU-Net, and TICU-Net contains single, dual, and triple encoder sub-networks connected with only a single decoder path. Each encoder sub-network is fed with different color space of the input image. A channel-wise attention module is utilized to fuse the contribution of the learned feature maps from each encoder sub-network which is fed to the decoder sub-network to generate segmented image map. Moreover, a composite loss function is designed to improve the performance of the proposed CU-Net models. Three public benchmark datasets, namely, International Skin Imaging Collaboration (ISIC 2017, ISIC 2018) and PH2 datasets, are utilized to evaluate the performance of the proposed models. Experimental results reveal that the proposed models significantly improve the performance of the original U-Net model and achieve comparable performance with other state-of-the-art methods.
Imaging the Kidney with an Unconventional Scanning Electron Microscopy Technique: Analysis of the Subpodocyte Space in Diabetic Mice

Transmission electron microscopy (TEM) remains the gold standard for renal histopathological diagnoses, given its higher resolving power, compared with light microscopy. However, it imposes several limitations on pathologists, including longer sample preparation time and a small observation area. To overcome these, we introduced a scanning electron microscopy (SEM) technique for imaging resin-embedded semi-thin sections of renal tissue. We developed a rapid tissue preparation protocol for experimental models and human biopsies which, alongside SEM digital imaging acquisition of secondary electrons (SE–SEM), enables fast electron microscopy examination, with a resolution similar to that achieved by TEM. We used this unconventional SEM imaging approach to investigate the subpodocyte space (SPS) in BTBR ob/ob mice with type 2 diabetes. Analysis of semi-thin sections with secondary electrons revealed that the SPS had expanded in volume and covered large areas of the glomerular basement membrane, forming wide spaces between the podocyte body and the underlying filtering membrane. Our results show that SE–SEM is a valuable tool for imaging the kidney at the ultrastructural level, filling the magnification gap between light microscopy and TEM, and reveal that in diabetic mice, the SPS is larger than in normal controls, which is associated with podocyte damage and impaired kidney function.
The heterogeneous effects of trade agreements with labor provisions

Do trade agreements with labor provisions affect trade differently from those without such provisions? Are their effects heterogeneous with respect to the level of development of the countries involved and the labor intensity of goods traded? In this paper we implement a state-of-the-art structural gravity model with intra-national trade and allow for heterogeneous effects depending on the level of enforceability of labor provisions (weak vs. strong provisions), sector (labor vs. non-labor intensive goods), members’ development level (North vs. South), and combinations of the three dimensions. We show that, overall, the trade effects of trade agreements with labor provisions are larger than those without. However, we also ﬁ nd that while exports from the South to the North display a signi ﬁ cant increase after a signature of a trade agreements with no or weak labor provisions, this is not the case if strong labor provisions are included in the agreement, and that such difference tend to be larger for labor-intensive goods.
Maneuver and formation control of a pair of soft pneumatic bending fingers by a cooperative strategy for planar in-hand object manipulation

In this paper, we seek performing dynamic in-hand object manipulation with two-segmented soft fingers in 2-D plane. Thereby, after the dynamic behavior of the soft fingers was defined, we evaluate the influence of external tip force on the finger. It is shown that the tip position error, under the effect of tip force, can be represented by uncertainties in kinematic parameters of the finger. As a result, we design a sliding-adaptive controller with compensation of kinematic uncertainties to fulfill our expectation that is controlling the tip position of the finger in vertical plane while interacting with the environment. Finally, inspired by the way that human fingers manipulate an object, a cooperative control system for manipulation is proposed which incorporates the states and tip positions of the fingers in its feedback signal. Combination of this controller with the adaptive control system yields more promising results than does the PID controller. In order to evaluate performance of the proposed controller, Simulation results for manipulation of a cubic rigid object are demonstrated.
Integrating neuroscientific knowledge into psychotherapy amongst Japanese psychotherapists: presence, benefits, needs and cultural barriers

ABSTRACT The practice of neuroscience-informed psychotherapy (NIP) that aims to refine the existing practice of psychotherapy is a recent topic in psychotherapy research. The researcher interviewed 25 Japanese psychotherapists and investigated the presence, benefits and needs of NIP and the potential barriers that may hinder the learning of NIP. A thematic analysis identified that the practice of NIP is currently limited in Japan due to limited learning opportunities. However, a minor proportion of Japanese psychotherapists practice NIP and experienced benefits, such as developing confidence in performing psychotherapy and effectively guiding clients to normalize problems. NIP may benefit psychotherapists in Japan and other Asian countries as psychotherapy in Japan and other Asian countries share many characteristics influenced by Confucianism, Buddhism and Westernization.
Numerical study on the aerodynamic performance and safe running of high-speed trains in sandstorms

The influence of sandstorms on train aerodynamic performance and safe running was studied in response to the frequent occurrence of sandstorm weather in north China.An Eulerian two-phase model in the computational fluid dynamic (CFD) software FLUENT,validated with published data,was used to solve the gas-solid multiphase flow of a sandstorm around a train.The train aerodynamic performance under different sandstorm levels and no sand conditions was then simulated.Results showed that in sandstorm weather,the drag,lift,side forces and overturning moment increase by variable degrees.Based on a numerical analysis of aerodynamic characteristics,an equation of train stability was also derived using the theory of moment balance from the view of dynamics.A recommended speed limit of a train under different sandstorm levels was calculated based on the stability analysis.
Mindfulness mediates relations between anxiety with problematic smartphone use severity

A growing body of literature has demonstrated relations between mood- and anxiety-related psychopathology with problematic smartphone use (PSU) symptom severity. However, there has been little empirical inquiry of potential mediators of these relationships. The current study examined trait mindfulness and smartphone use expectancies as mediators of the relation between depression/anxiety and PSU severity in 352 undergraduate students. Participants completed an online survey that measured depression, anxiety, smartphone use expectancies, and PSU severity. Structural equation modeling demonstrated that trait mindfulness was inversely associated, and smartphone use expectancies were positively associated, with PSU severity. Trait mindfulness significantly mediated relations between anxiety and PSU severity. Results provide implications for understanding PSU within the context of theoretical models of PSU’s development, and highlight the role of mindfulness as an emotion regulation strategy and potential treatment for PSU.
Changes in physical performance characteristics of female volleyball players during regional division competitions

This study aims to examine the seasonal changes in the physical performance of female volleyball players competing in the regional division. Forty-three volunteer female players (age: 22 ± 2.1 years, height: 172.9 ± 4 cm, weight: 61.5 ± 6 kg, experience: 8.8 years) competing in the same group of the regional division of the Turkish volleyball league participated in this study. Players participated in a series of test protocols including the 20m shuttle-run, T-run, 20m sprint, vertical jump, and running anaerobic sprint (RAST) in the beginning, mid, and ending of the 16-week competition season. The results showed that all tested physical performance characteristics of the players improved significantly in both the first and second periods of the competition season. However, the improvements in the first period were significantly higher than in the second period for VO2max (4.7 vs 1.5%, p<0.05), anaerobic power (6.6 vs 1.9%, p<0.05), vertical jump height (3.46 vs 1.54%, p<0.05), explosive power (4.48 vs 3.72%, p<0.05), 20-m sprint (2.4 vs 0.98%, p<0.05) and change of direction abilities (0.9 vs 0.7%, p<0.05). This study indicated that the prolonged competition season might induce significant functional improvements in the physical fitness profile of female volleyball players competing in the regional division. Este estudio tiene como objetivo examinar los cambios estacionales en el rendimiento físico de las jugadoras de voleibol que compiten en la división regional. En este estudio participaron 43 jugadoras voluntarias (edad: 22 ± 2,1 años, altura: 172,9 ± 4 cm, peso: 61,5 ± 6 kg, experiencia: 8,8 ± 1,8 años) que competían en el mismo grupo de la división regional de la liga turca de voleibol. Las jugadoras participaron en una serie de pruebas que incluían el test de ida y vuelta de 20 metros, T-test de agilidad, sprint de 20 m, salto vertical y carrera de sprint anaeróbico (RAST) al principio, a la mitad y al final de la temporada de competición de 16 semanas. Los resultados mostraron que todas las características de rendimiento físico evaluadas de las jugadoras mejoraron significativamente tanto en el primer como en el segundo período de la temporada de competición. Sin embargo, las mejoras en el primer período fueron significativamente más altas que en el segundo período para el VO2máx (4,7 vs 1,5%, p <0,05), potencia anaeróbica (6.6 vs 1,9%, p <0,05), altura del salto vertical (3,46 vs 1,54%, p <0,05), potencia explosiva (4,48 vs 3,72%, p <0,05), sprint de 20 m (2,4 vs 0,98%, p <0,05) y habilidades de cambio de dirección (0,9 vs 0,7%, p <0,05). Este estudio indicó que la temporada de competición prolongada podría inducir mejoras funcionales significativas en el perfil de condición física de las jugadoras de voleibol que compiten en la división regional.