Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of home-based training and nutritional behavior on body composition and metabolic markers in cancer patients: data from the CRBP-TS study

Introduction Obesity and physical inactivity are known to affect cancer's development and prognosis. In this context, physical aerobic and resistance training as well as a Mediterranean nutrition have been proven to have many positive health effects. The aim of this study was therefore to investigate the effect of home-based training on body composition and certain metabolic laboratory parameters. Methods Patients with breast, colorectal and prostate cancer who underwent curative surgery at stages T1N0M0–T3N3M0 were eligible for this trial and randomized to an intervention and control group. In the intervention group the patients carried out online-based strength-endurance home training during the 6-month study period. Body composition was assessed via bioelectrical impedance analysis (baseline, 3 months and 6 months). Metabolic blood parameters were also analyzed and nutrition behavior determined using the Mediterranean Diet Adherence Screener (MEDAS). Results The intervention group's fat mass decreased while their lean body mass increased (time effect p = 0.001 and p = 0.001, respectively). We found no interaction effect in body weight (p = 0.19), fat mass [p = 0.06, 6-months estimates −0.9 (95% CI −1.8 to −0.1)] and lean body mass (p = 0.92). Blood samples also failed to show a statistically significant interaction effect between time × group for HbA1c% (p = 0.64), Insulin (p = 0.33), Adiponectin (p = 0.87), Leptin (p = 0.52) and Triglycerides (p = 0.43). Only Adiponectin revealed significance in the time effect (p < 0.001) and Leptin in the group effect (p = 0.03). Dietary behavior during the study period was similar in patients in the intervention and control groups (interaction p = 0.81; group p = 0.09 and time p = 0.03). Discussion Individualized online-based home training in postoperative cancer patients revealed only minor changes, with no group differences in body composition or metabolic laboratory parameters, which were predominantly in the reference range at baseline. More studies investigating effects of online-based home training on body composition and nutrition behavior are needed. Trial registration https://drks.de/search/en/trial/DRKS00020499, DRKS-ID: DRKS00020499.
Revascularization and Left Ventricular Dysfunction for ICD Eligibility

Common triggers for sudden cardiac death (SCD) are transient ischemia, hemodynamic fluctuations, neurocardiovascular influences, and environmental factors. SCD occurs rapidly when sinus rhythm degenerates into ventricular tachycardia (VT) and/or ventricular fibrillation (VF), followed by asystole. Such progressive worsening of the cardiac rhythm is in most cases observed in the setting of ischemic heart disease and often associated with advanced left ventricular (LV) impairment. Revascularization prevents negative outcomes including SCD and heart failure (HF) due to LV dysfunction (LVD). The implantable cardioverter–defibrillator (ICD) on top of medical therapy is superior to antiarrhythmic drugs for patients with LVD and VT/VF. The beneficial effects of ICD have been demonstrated in primary prevention of SCD as well. However, yet debated is the temporal management for patients with LVD who are eligible to ICD prior to revascularization, either through percutaneous or surgical approach. Restoration of coronary blood flow has a dramatic impact on adverse LV remodeling, while it requires aggressive long-term antiplatelet therapy, which might increase complication for eventual ICD procedure when percutaneous strategy is pursued; on the other hand, when LV and/or multiorgan dysfunction is present and coronary artery bypass grafting is chosen, the overall risk is augmented, mostly in HF patients. The aims of this review are to describe the pathophysiologic benefits of revascularization, the studies addressing percutaneous, surgical or no revascularization and ICD implantation, as well as emerging defibrillation strategies for patients deemed at transient risk of SCD and/or at higher risk for transvenous ICD implantation.
Exploring Community Perceptions of COVID-19 and Vaccine Hesitancy in Selected Cities of Ethiopia: A Qualitative Study

Even though the COVID-19 vaccine has been available and free of charge to the targeted population in Ethiopia, the vaccination rate was lower than needed to achieve herd immunity at community level. This study aimed to explore community perceptions of COVID-19 and vaccine hesitancy in selected cities of Ethiopia involving 70 in-depth interviews and 28 focused group discussions. The audio-taped data were transcribed verbatim, translated into English, and analyzed using a qualitative content analysis approach using the ATLAS.ti software version 8. The findings revealed that COVID-19 was perceived as evil and caused fear and frustration upon its emergence. The community initially used traditional remedies for its prevention but later transitioned to employing non-pharmaceutical interventions. The primary reasons for vaccine hesitancy were misinformation and misconceptions, such as connecting the vaccine with the mark of the beast, a lack of trust due to the multiple vaccine types, a shorter production timeline resulting in distrust of its effectiveness, and a fear of pain and side effects. Based on our findings, we recommend monitoring the use of social media and countering misinformation with the correct information and continuous public health campaigns. Further studies should be conducted to assess the types and magnitude of impacts from the myths and misconceptions on vaccination uptake.
CAMELLIA SINENSIS VAR. MADOENSIS (SECT. THEA, THEACEAE), A NEW TAXON FROM VIETNAM

Camellia sinensis var. madoensis is described and illustrated as a new variety of Camellia sinensis (section Thea, Theaceae) from Xuan Loc Commune, Song Cau District, Phu Yen Province. The new variety is easily distinguishable from C. sinensis var. sinensis by style free ½ to the base. The ITS sequence of this variety is also different from that of Camellia sinensis and its other varieties, while the matK gene sequences are nearly identical among Camellia taxa.
A VALIDATION OF WAVE LOADS ON CREST WALLS ON TOP OF COMPOSITE BREAKWATERS USING OPENFOAM

The design of crest walls is often based on empirical formulations, physical model tests, numerical models and a fair amount of expert judgement. The present work validates the prediction of wave induced forces on the front face of crest walls on top of composite breakwaters in the numerical model OpenFOAM. The results show that OpenFOAM is able to capture the shape and order of magnitude of the force events caused by non-breaking and heavily breaking waves. In addition, a calibrated model predicts the highest wave induces forces caused by breaking waves with errors lower than 20percent.
Temperature and E-Poling Evolution of Structural, Vibrational, Dielectric, and Ferroelectric Properties of Ba1−xSrxTiO3 Ceramics (x = 0, 0.1, 0.2, 0.3, 0.4 and 0.45)

Lead-free Ba1−xSrxTiO3 (BST) (x = 0, 0.1, 0.2, 0.3, 0.4 and 0.45) ceramics were successfully prepared via the solid-state reaction route. A pure perovskite crystalline structure was identified for all compositions by X-ray diffraction analysis. The basic phase transition temperatures in these ceramics were studied over a wide temperature range. A change in symmetry from a tetragonal to cubic phase was detected, which was further proven by phonon anomalies in composition/temperature-dependent Raman spectra. The incorporation of Sr2+ into BaTiO3 (BT) lead to a shift in the phase transitions to lower temperatures, suppressing the ferroelectric properties and inducing relaxor-like behavior. Therefore, it was reasonable to suppose that the materials progressively lack long-range ordering. The initial second-harmonic generation (SHG) measurements demonstrated that the cubic phase of BST ceramics is not purely centrosymmetric over a wide temperature interval. We discussed the possible origin of the observed effects, and showed that electric field poling seems to reconstruct the structural ordering destroyed by the introduction of Sr2+ to BT. In the first approximation, substitution of Sr for larger Ba simply reduced the space for the off-central shift in Ti in the lattice and hence the domain polarization. A-site cation ordering in BST and its influence on the density of electronic states were also explored. The effect of doping with strontium ions in the BST compound on the density of electronic states was investigated using ab initio methods. As the calculations showed, doping BT with Sr2+ atoms led to an increase in the bandgap. The proposed calculations will also be used in the subsequent search for materials optimal for applications in photovoltaics.
Development of an artificial intelligence-based method for the diagnosis of the severity of myxomatous mitral valve disease from canine chest radiographs

An algorithm based on artificial intelligence (AI) was developed and tested to classify different stages of myxomatous mitral valve disease (MMVD) from canine thoracic radiographs. The radiographs were selected from the medical databases of two different institutions, considering dogs over 6 years of age that had undergone chest X-ray and echocardiographic examination. Only radiographs clearly showing the cardiac silhouette were considered. The convolutional neural network (CNN) was trained on both the right and left lateral and/or ventro-dorsal or dorso-ventral views. Each dog was classified according to the American College of Veterinary Internal Medicine (ACVIM) guidelines as stage B1, B2 or C + D. ResNet18 CNN was used as a classification network, and the results were evaluated using confusion matrices, receiver operating characteristic curves, and t-SNE and UMAP projections. The area under the curve (AUC) showed good heart-CNN performance in determining the MMVD stage from the lateral views with an AUC of 0.87, 0.77, and 0.88 for stages B1, B2, and C + D, respectively. The high accuracy of the algorithm in predicting the MMVD stage suggests that it could stand as a useful support tool in the interpretation of canine thoracic radiographs.
Editorial: Perspectives in brain-network dynamics in computational psychiatry

COPYRIGHT © 2023 Nobukawa and Takahashi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Editorial: Perspectives in brain-network dynamics in computational psychiatry
Clustering and Ensemble Based Approach for Securing Electricity Theft Detectors Against Evasion Attacks

In smart power grids, electricity theft causes huge economic losses to electrical utility companies. Machine learning (ML), especially deep neural network (DNN) models hold state-of-the-art performance in detecting electricity theft cyberattacks. However, DNN models are vulnerable to adversarial attacks, i.e., evasion attacks. In this work, we, first, study the vulnerability of the DNN-based electricity theft detectors against evasion attacks and the influence of the model’s regularization (generalization) and transferability on robustness. Then, we cluster the power consumers and train a detector for each cluster, and compare the performance and robustness of this detector to a global detector that is trained on all the consumers’ data. The results indicate that the cluster-based detector is not only more robust against evasion attacks but also enhances normal classification accuracy because its training data has more consumption pattern similarity compared to the training data of the global detector which requires higher level of regularization. Then, we develop a cluster-based parallel-ensemble electricity theft detector to achieve high robustness against evasion attacks and high detection accuracy. The proposed detector has two levels of defense, including clustering and ensemble, where clustering decreases regularization and improves robustness, and the ensemble of diverse decision models improves robustness against transferability. We evaluate the detector on different threat models, including Blackbox and Graybox with different knowledge about defense strategy, model architecture, and training dataset. The evaluation results indicate that unlike the existing solutions that sacrifice the normal accuracy of the model to improve the robustness against evasion attacks, the proposed detector outperforms the benchmark defenses in terms of robustness and normal classification accuracy.
Marginal Adaptation of In Vitro Class II Restorations Made Out of Bulk or Conventional Composite Using Single- or Multi-Layered Techniques

Objective: Testing the influence of various restorative materials (conventional or bulkfill composites) and filling techniques (single- or multi-layered techniques) on the in vitro marginal adaptation of large class II direct composites with supra and sub-gingival margins subjected to thermomechanical loading (TML). Methods: A total of 40 prepared teeth were attributed randomly to five experimental groups. In Group 1, restorations were made of multi-layered high-viscosity conventional composite (Tetric EvoCeram); in Groups 2 and 3, restorations were made of a high viscosity bulkfill composite (Tetric EvoCeram Bulk Fill) applied in one (Group 2) or three layers (Group 3); in Groups 4 and 5, restorations were made of a flowable bulkfill composite (SDR flow) applied in one (Group 4) or two layers (Group 5), covered with a layer of high-viscosity conventional composite (Ceram-X Universal). A single adhesive (OptiBond FL) was used in all groups. All specimens were submitted to a staged TML comprising three phases (2 × 500,000 and 1,000,000 cycles) at 50 N with 3350 thermal cycles (5 to 55 °C) every 500,000 cycles. The tooth–restoration interfaces on proximal surfaces were evaluated quantitatively by scanning electron microscopy, before and after each TML phase, hence at three timepoints (T0, T1, T2 and T3). The following segments were considered for evaluation: proximal, vertical enamel margins (assessed individually on both restoration sides), cervical enamel (restoration side above CEJ) and cervical dentin margin (restoration side below the CEJ). Results: TML induced a significant reduction in continuous adaptation at both enamel and dentin margins in all groups, with percentages of continuous margins ranging from 75.2 to 91.8% at T0, and decreasing to values ranging from 21.3 to 73.9% at T3. Both composite systems and layering protocols had a significant influence on marginal adaptation of the restorations, with statistical associations depending on the restoration group and the timepoint considered. Defective margins in enamel were all of a cohesive nature with micro-fractures, while in dentin, interfacial gaps were the main defect observed. Conclusions/Clinical significance: The present results highlighted significant degradation of marginal adaption after long-term in vitro fatigue test using materials even with high-viscosity conventional resin composites, applied with a proper layering approach in medium–large sub-gingival cavities. While no significant differences were observed at the dentin cervical margins, there was a tendency for better adaptation at the enamel margin when using a higher modulus material with a multi-layered technique.
The effects of a firefighting simulation on the vascular and autonomic functions and cognitive performance: a randomized crossover study

Introduction: During firefighting, physical and cognitive demands increase. However, the stress inherent to these events can decrease cognitive performance and increase the risk of cardiovascular events in firefighters. Thus, this crossover study aimed to evaluate the effects of a firefighting Simulation on cognitive performance and vascular and autonomic functions in military firefighters. Methods: Sixteen firefighters (37.8 ± 5.6 years) underwent anthropometry, mental health status, and sleep quality assessments. They randomly performed two interventions, Simulation (Firefighting tasks; 10.0 ± 1.1 min) and Control (rest for 10 min), on different days. After both interventions, cognitive performance was assessed using the Stroop Test, Paced Auditory Serial Addition Test, and Trail Making Test. Then, the vascular function was assessed using ultrasonography through the carotid artery reactivity to the cold pressor test. The arterial pressure, heart rate, and cardiac intervals were recorded before interventions. The cardiac intervals were also measured during the cold pressor test. Student’s t-test and Wilcoxon were used for comparisons between Control and Simulation and the analysis of variance for repeated measures was used for comparison over time during the cold pressor test. A significance level of p < 0.05 was adopted. Results: Although the mean and maximum heart rate were higher before the Simulation (p < 0.0001), all the heart rate variability parameters (p > 0.05) and mean arterial pressure (p > 0.3795) were similar before the interventions. After Simulation, the cognitive performance was similar to Control (p > 0.05), except for the improvement in Stroop Test part B (p < 0.0001). After Simulation, carotid artery reactivity was attenuated (p < 0.0010). During the cold pressor test, the high-frequency band of the heart rate variability was lower after the Simulation (p < 0.0104). Discussion: Although firefighting Simulation did not substantially change cognitive performance, the lower carotid artery reactivity and parasympathetic modulation to the heart during the cold pressor test may contribute to greater vulnerability to cardiovascular events in firefighters on duty.
A Novel Common-Ground Multisource Inverter

This letter proposes a novel switched-capacitor (SC) multisource boosting multilevel inverter featuring common ground connection for photovoltaic (PV)-dominated high-frequency ac applications. The proposed topology requires only eight switches, two diodes, and two SCs for generating a nine-level output voltage. The proposed topology has the ability to accommodate two PV sources while ensuring near zero ground leakage current. With the series/parallel technique, the SCs are self-voltage balanced, achieving sensor-less operation. The devised structure has the lowest conduction losses due to reduced number of conducting devices at each level. Furthermore, switching losses are reduced since fewer devices transit at any level as compared to the state-of-the-art topologies. A comprehensive comparative assessment of the proposed topology is carried out and included to highlight its beneficial features against the counterparts. The experimental evaluation of the proposed inverter topology is carried out and the results are presented to validate its feasibility and operability.
Organizational citizenship behavior among prison managers: An empirical study in Indonesian Nusakambangan correctional institutions

Abstract This study examines the influence of perceived organizational support on middle manager perceptions by demonstrating that the organization values their well-being, causing them to contribute to organizational growth. This study also tries to explain how psychological capital mediates the impact of perceived organizational support on organizational citizenship behavior among middle managers at the Indonesian Nusakambangan correctional institution. Data is collected from 76 middle managers and analyzed using Partial Least Square—Structural Equation Modeling. The test results indicate a significant influence between perceived organizational support on organizational citizenship behavior and psychological capital and psychological capital on organizational citizenship behavior. The test results also show that psychological capital can mediate perceived organizational support for organizational citizenship behavior. Correctional institutions should be prepared for a variety of situations that are prone to security disruptions. The middle managers and all other team members must be confident that all work activities will go according to plan. This study implies that belief or trust may develop effectively when an organization recognizes employees’ contributions to long-term difficulties to achieve all necessary alternative answers. The study highlights the importance of psychological capital as a direct effect or mediator that drives middle managers towards positive and better mental health, specifically in a volatile organization like a correctional institution.
Deep Learning-Based Recognition of Unsafe Acts in Manufacturing Industry

Despite technological progress and the tendency for automation, the majority of manufacturing workplaces still rely on human labor. Although industrial tasks are frequently composed of simple operator actions, non-ergonomic execution of such repetitive tasks has been reported as the primary cause of musculoskeletal disorders. Considering the sizes of manufacturing halls and large numbers of employees, there is an increasing need for tools that can improve the recognition of unsafe acts. Herein, a deep learning-based procedure for pose safety assessment is proposed and validated using monocular videos captured with a conventional IP camera. The two key composing components of the proposed pipeline are the three-dimensional (3D) pose estimator and mesh classifier. The proposed method was validated experimentally by considering three different methodologically selected industrial tasks: a laborious task that requires all-body effort (pushing and pulling), a task that requires an upper-limb action comprising intensive interaction and motion control (drilling), and a typical collaborative task (polishing with a collaborative robot with variable mechanical impedance). Accuracies of 84.67%, 92%, and 98%, respectively, were achieved. Besides higher accuracy, the proposed method has shown practical advantages over existing alternatives based on analyzing the parameters derived from the human poses. Particularly, we report that the proposed procedure is generic, and it works directly with 3D human body poses, which significantly increases applicability while reducing the complexity and effort needed for data annotation and output interpretation by non-experts.