Miracle-dz/UniFAR-FTUs huggingface dataset:
The Therapeutic Impact of Plant-Based and Nutritional Supplements on Anxiety, Depressive Symptoms and Sleep Quality among Adults and Elderly: A Systematic Review of the Literature

Background: The emerging research in the literature continues to forecast a drastic and alarming increase in negative mental health and sleep health outcomes among populations, especially after the COVID-19 pandemic, which significantly influenced people’s way of life. With mental health pharmaceutical interventions continuing to be stigmatized and inaccessible among populations, natural supplements provide an opportunity for intervention. Objective: This study sought to conduct a systematic review of the literature on the most recent comprehensive evidence for which nutritional supplements have the greatest therapeutic impact on symptoms of anxiety, depression, and insomnia. Methods: A systematic search of the literature, utilizing several databases, including PubMed and Web of Science, was conducted on 29 April 2022. We used developed keywords and MeSH terms for the search. The study eligibility criteria included (1) a randomized control trial; (2) investigating a plant-based therapeutic or natural supplement as the intervention; (3) measuring at least one health outcome of the following: anxiety symptoms, depressive symptoms, or sleep health outcomes; (4) utilizing validated measurement tools to measure the outcome of interest; (5) written in the English language; (6) peer reviewed; and (7) focused on adults and elderly populations. Main Results: Following the PRISMA guidelines, 76 studies were included in this review. We used the revised Risk of Bias tool (RoB2) to assess the quality of all included randomized control trials. A qualitative data synthesis was conducted. Overall, we found several valuable insights from the evidence in the literature, including evidence that demonstrates the benefits of probiotics and vitamin B complexes on anxiety symptoms, depressive symptoms, and sleep quality. Implication of Key Findings: This review provides the most updated findings in the literature on the topic, including an abundance of research that was published in the past 5 years. Given the expected rise in negative mental and sleep health outcomes following the pandemic, the supplements and therapeutics identified in this study should be the target of intervention measures to increase their accessibility and affordability and allow them to be incorporated into clinical guidelines of treatment. PROSPERO registration number: CRD42022361130.
Quantitative longitudinal measurement in a rat model of controlled burn severity using spatial frequency domain imaging

Background and Objective: Spatial Frequency Domain Imaging (SFDI) is a non-contact wide-field optical imaging technology currently being developed to investigate the feasibility of quantitative non-invasive evaluation of burn wound severity in a rat model. Our objective is to determine the potential of SFDI for mapping quantitative changes in spatially resolved tissue oxygen saturation and water concentration may be indicative of burn wound severity, healing, and further complications. In this portion of the investigation, we focus on the development of a rat burn model and the acute response of tissue to burn wounds. Study Design/Materials and Methods: A controlled burn protocol involving a heated brass comb was applied to 6 rats. Imaging was acquired at 17 evenly spaced wavelengths in the near-infrared from 650 to 970 nm. Over the course of the 3 hour post-burn period, we were able to map quantitative changes in spatially resolved chromophores. Burn severities were verified post-experiment using standard H and E histology and optical microscopy. Results/Conclusion: In total, we were able to induce 12 superficial-partial thickness burns, 8 deep-partial thickness burns, and 4 full thickness burns in our rat models. While several tissue chromophores were tracked, we found that changes in oxygen saturation and water concentration to be sensitive indicators of burn severity. Future work will include additional longitudinal studies over a period of days in order to investigate which parameters are correlated to tissue healing.
Free weight training vs. elastic band training

The aim of this study was to assess the effectiveness of two resistance training (RT) programs (free weight [FW] and elastic band [EB]) on velocity variables (handball throwing velocity [HTV] and maximal theoretical velocity [V0]) using load-velocity (L-V) relationship modelling. Both programs lasted 6 weeks and consisted of performing bench press and overarm dumbbell pull-over using free weights (FW group) or elastic bands (EB group). Nineteen male sports science students were randomly assigned to EB (n=10) or FW group (n=9). Both RT programs increased HTV and V0, although the increment was greater in the FW (>2 m·s-1) compared to the EB group (<1 m·s-1). RT programs had selective effects on the strength variables being FW more effective in increasing 1-repetition maximum, while EB in increasing maximal isometric force. Very large correlations were observed between two-point (L-V relationship modelled through two pairs of L and V data) and multiple-point methods (L-V relationship modelled through six pairs of L and V data) (V0: r=0.96; HTV: r=0.93). All coefficients of variation showed high validity both for V0 and HTV (≤6.2%). Altogether, FW training should be used for increasing the velocity of the throwing performance, while the two-point method for following training-induced changes.
Robust output feedback control of 2D discrete systems with actuator saturation and time-varying delay

An observer-based dynamic output feedback H∞ controller is proposed for a class of two-dimensional (2D) uncertain discrete systems described by the Roesser model with actuator saturation, time-varying state delay and external disturbances. First, a delay-dependent Lyapunov stability condition is derived in linear matrix inequality (LMI) form which uses the reciprocal convex approach and H∞ disturbance attenuation performance is also analysed. Secondly, a convex hull is adopted to represent the saturation nonlinearity. The H∞ control synthesis for uncertain 2D discrete systems is described by a Roesser model subjected to actuator saturation and external disturbances using an observer-based dynamic output feedback approach. Some practical examples are provided to highlight the usefulness of the presented results.
An Improved Parallel Predictive Torque Control for Permanent Magnet Synchronous Motor

A predictive torque control strategy with parallel structure (P-PTC) was recently proposed to overcome the tedious tuning of weighting factor in the conventional predictive torque control (C-PTC). However, P-PTC still has some problems, such as the introduction of other parameters to be tuned and the lack of theoretical support, et al. To solve the above problems, an improved P-PTC without any extra parameters tuning (IP-PTC) is proposed for permanent magnet synchronous motor (PMSM). Firstly, two parallel cost functions are respectively constructed to select three voltage vectors that have the best control effect on electromagnetic torque and stator flux to form two new finite control sets (FCSs). Secondly, three different cases are divided according to the intersection number of these two FSCs. Finally, the corresponding optimal voltage vector selection scheme is proposed for these three cases. C-PTC, P-PTC and the proposed IP-PTC are studied through theory and experiments. The results show that when compared with C-PTC and P-PTC, the proposed IP-PTC has neither weighting factor nor any extra parameters, and it is well supported by theory. Furthermore, the proposed IP-PTC has the best static and dynamic performance among the three.
Safe and Efficient Dynamic Window Approach for Differential Mobile Robots With Stochastic Dynamics Using Deterministic Sampling

We propose an efficient and safe dynamic window approach (DWA) by using deterministic sampling. When the system dynamics have uncertainty, the control input includes errors, so that the DWA objective function becomes a random variable. When a random-choice algorithm with a finite number of samples is used to estimate the objective function, it may miss collisions during prediction. In this work, we approximate the end-state distribution as a one-dimensional distribution for each input candidate in advance and generate sample paths deterministically to eliminate the misses to achieve safe control. Numerical experiments have shown that this method is approximately three times as efficient as the Monte Carlo method in most indoor environments.
The Evaluation of Energy Availability and Dietary Nutrient Intake of Sport Climbers at Different Climbing Levels

Proper nutrition is the basis for athletes’ performances when competing or training. The increasing training volume accompanying the increase in advancement should go hand in hand with the appropriate supply of energy as well as macro and micronutrients. The diet of climbing representatives due to the desire to achieve a low body weight may be deficient in energy and micronutrients. Our study aimed to evaluate the differences in energy availability and nutrient intake of female and male sport climbers at different climbing levels. Anthropometric parameters and the resting metabolic rate were measured, the questionnaire about climbing grade and training hours was filled, and a 3-day food diary was fulfilled by 106 sport climbers. Based on the collected data, the energy availability as well as the macro- and micronutrient intake was calculated. Low energy availability (EA) was observed among both genders of sport climbing representatives. A significant difference between EA in various levels of advancement was found in the male group (p < 0.001). Differences in carbohydrate intake (g/kg/BW) between sexes were observed (p = 0.01). Differences in nutrients intake between climbing grade were found in both the female and male groups. In the group of female elite athletes, the adequate supply of most of the micronutrients can imply a high-quality diet despite the low calorie content. It is necessary to educate sport climbing representatives about the importance of proper nutrition as well as the consequences of insufficient energy intake.
Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects

Two general algorithms for solving constrained minimization problems are presented and discussed in the context of analysis and assimilation of meteorological observations. In both algorithms, the original constrained problem is transformed by appropriate modifications into one unconstrained problem, or into a sequence of unconstrained problems. The main advantage of proceeding in this way is that the new unconstrained problems can be solved by classical descent algorithms, thus avoiding the need of directly solving the Euler-Lagrange equations of the original constrained problem. The first algorithm presented in the augmented lagrangian algorithm. It generalizes the more classical penalty and duality algorithms. The second algorithm, inspired from optimal control techniques, is based on an appropriate use of an adjoint dynamical equation, and seems to be particularly well adapted to the assimilation of observations distributed in time. Simple numerical examples show the ability of these algorithms to solve non-linear minimization problems of the type encountered in meteorology. Their possible use in more complex situations is discussed, in particular in terms of their computational cost. DOI: 10.1111/j.1600-0870.1986. tb00459.x
A Conceptual Approach for Examining Effects of the Adolescent Bone Marrow Milieu on MSC Phenotype

Children with bone fragility often exhibit elevated bone marrow lipid levels, which may affect mesenchymal stem cell (MSC) differentiation potential and ultimately bone strength via cell‐autonomous and/or non‐cell‐autonomous factors. Here, we use standard co‐culture techniques to study biological effects of bone marrow cell‐derived secretome on MSC. Bone marrow was collected during routine orthopedic surgery, and the entire marrow cell preparation, with or without red blood cell (RBC) reduction, was plated at three different densities. Conditioned medium (secretome) was collected after 1, 3, and 7 days. ST2 cells, a murine MSC line, were then cultured in the secretomes. Exposure to the secretomes was associated with reductions of up to 62% in MSC MTT outcomes that depended on the duration of secretome development, as well as marrow cell plating density. Reduced MTT values were not associated with diminished cell number and viability assessed using Trypan Blue exclusion. Expression of pyruvate dehydrogenase kinase 4 was modestly elevated, and β‐actin levels were transiently reduced in ST2 cells exposed to secretome formulations that had elicited maximal reductions in MTT outcomes. The findings from this study can inform the design of future experimental studies to examine contributions of cell‐autonomous and non‐cell‐autonomous factors in the bone marrow to MSC differentiation potential, bone formation, and skeletal growth. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
A long-distance 3D face recognition architecture utilizing MEMS-based region-scanning LiDAR

In this paper, a novel 3D face recognition system utilizing the MEMS-based indirect Time-of-Flight (ToF) region-scanning LiDAR is proposed for long-distance person identification. Specifically, this face recognition system consists of two parts: (1) detection of the targeted face region by IR amplitude image and (2) 3D face recognition with the high-resolution face data of region-scanning. The proposed system is carried out on the self-collected dataset and gets maximum Rank-1 recognition rate of 95% in various distance and illumination conditions. Moreover, the proposed system outperformed the other 3D face recognition system with conventional ToF sensors in the aspect of the Rank-1 recognition rates at long distance of more than 3 meters.
Green innovation for the ecological footprints of tourism in China. Fresh evidence from ARDL approach

This study ’ s objective is to analyze ecological footprints that exist among China ’ s economic growth, energy consumption, carbon dioxide emissions, and the revenue that is generated from tourism in other countries. The years 1995 through 2020 are the focus of this particular research endeavor. The relationship between tourism and carbon emissions has been discovered by a large number of researchers; nevertheless, the findings have been inconsistent and do not give a clear picture of the situation. We can only hope that the results of the study will improve the existing body of knowledge on tourism and the quality of the surrounding environment. Throughout the whole of this investigation, the autoregressive distributed lagged (ARDL) model was used to explore both long-run and short-run estimations. A dynamic ordinary least squares (DOLS) model was used in the study to arrive at long-term estimations that could be relied upon. Even though money from tourism does not have a substantial influence on the quality of the environment in China, growth and increasing energy usage are primary donors to carbon emissions in the nation. ARDL model ’ s long-term projections were shown to be correct by the DOLS approach, which offered this validation. The results of the research provide fresh insights into the body of knowledge that has been accumulated on the subject of the linkage between tourism and the natural environment. Because the receipts from tourism do not have any significant negative exterior-ity toward the environment, energy usage is an important element of environmental degradation and policymakers should prioritize the development of the tourism sector over energy-focused manufacturing activities to maintain the growth of the nation in the upper quartiles. This is because tourism does not have any significant negative externalities on the environment. Sustainable tourism minimizes environmental and cultural damage while boosting profits. Developing the appropriate technology, physical infrastructure, and human capital requires money, time, and effort.
Teaching mathematics for social justice: The challenges and the prospects in the Ghanaian senior high schools

The study aimed to explore the prospects and challenges of teaching mathematics for social justice at Ghanaian senior high schools (SHSs). A non-random sample of seven respondents, including two experienced mathematics educators and five SHS students, were interviewed and analyzed qualitatively using thematic analysis. The analysis revealed seven themes: individual differences, students’ mathematics interests, participatory lessons, extracurriculars, non-interactive teaching, technology use, and cultural diversity. These thematic findings are related to technical, practical, and emancipatory knowledge constituent interests in schools and Ghanaian social, cultural, and historical settings. A teacher should utilize egalitarian pedagogy so that the students will gain practical and emancipatory skills.
Properties of a high-beta plasma produced by electron-cyclotron heating

The sequence of experiments resulting in the development of steady-state dense hot-electron plasmas is briefly described. These plasmas are produced in magnetic-mirror machines by radiation at the electron-cyclotron frequency. The electron-cyclotron plasma with the greatest stored energy to date has a volume of ∼ 50 liters, an electron “temperature” of 120 keV, a density of 4 — 7 × 1011/cm3, an d an average beta of ∼ 0.4. This plasma is created in the EPA Facility by a 50-kW c.w. 10.6-gHz microwave power source. The construction and operation of the machine are briefly discussed. The analysis and interpretation of the bremsstrahlung and diamagnetic measurements employed to determine these parameters are given. Diamagnetic and particle decay measurements on a smaller machine, the Physics Test Facility, are also described.
Retrospective analysis of quantitative electroencephalography changes in a dissimulating patient after dying by suicide: A single case report

We present the case of a 49-year-old man who was diagnosed with depressive disorder, with the first episode having a strong reactive factor. He was involuntarily admitted to a psychiatric hospital after a failed attempt at taking his own life, where he responded to psychotherapy and antidepressant therapy, as evidenced by a >60% reduction in his MADRS total score. He was discharged after 10 days of treatment, denied having suicidal ideations, and was motivated to follow the recommended outpatient care. The risk for suicide during hospitalization was also assessed using suicide risk assessment tools and psychological assessments, including projective tests. The patient underwent a follow-up examination with an outpatient psychiatrist on the 7th day after discharge, during which the suicide risk assessment tool was administered. The results indicated no acute suicide risk or worsening of depressive symptoms. On the 10th day after discharge, the patient took his own life by jumping out of the window of his flat. We believe that the patient had dissimulated his symptoms and possessed suicidal ideations, which were not detected despite repeated examinations specifically designed to assess suicidality and depression symptoms. We retrospectively analyzed his quantitative electroencephalography (QEEG) records to evaluate the change in prefrontal theta cordance as a potentially promising biomarker of suicidality, given the inconclusive results of studies published to date. An increase in prefrontal theta cordance value was found after the first week of antidepressant therapy and psychotherapy in contrast to the expected decrease due to the fading of depressive symptoms. As demonstrated by the provided case study, we hypothesized that prefrontal theta cordance may be an EEG indicator of a higher risk of non-responsive depression and suicidality despite therapeutic improvement.
Accelerating Graph Convolutional Networks Through a PIM-Accelerated Approach

Graph convolutional networks (GCNs) are promising to enable machine learning on graph data. GCNs show potential vertex-level and intra-vertex parallelism for GPU acceleration, but their irregular memory accesses arising in aggregation operations and the inherent sparsity for vertex features of graphs cause inefficiencies on the GPU. In this paper, we present gPIM, which aims to accelerate GCNs inference through a processing-in-memory (PIM) enabled architecture. gPIM is expected to perform compute-intensive combination on the GPU while aggregation and memory-bound combination are offloaded to the PIM-featured hybrid memory cubes (HMCs). To maximize the efficiency of such GPU-HMC architecture, gPIM is novel with two key designs: 1) A GCN-induced graph partitioning that minimizes communication overheads between cubes, 2) A programmer-transparent performance estimation mechanism that predicts the performance bound of operations accurately for workload offloading. Experimental results show that gPIM significantly outperforms Intel Xeon E5-2680v3 CPU (8,979.52×), NVIDIA Tesla V100 GPU (96.01×), and a state-of-the-art GCN accelerator AWB-GCN (4.18×).
Threshold Autoregressions for Strongly Autocorrelated Time Series

In some cases the unit root or near unit root behavior of linear autoregressive models fitted to economic time series is not in accordance with the underlying economic theory. To accommodate this feature we consider a threshold autoregressive (TAR) process with the threshold effect only in the intercept term. Although these processes are stationary, their realizations switch between different regimes and can therefore closely resemble those of (near) integrated processes for sample sizes relevant in many economic applications. Estimation and inference of these TAR models are discussed, and a specification test for testing their stability is derived. Testing is based on the idea that if (near) integratedness is really caused by level shifts, the series purged of these shifts should be stable so that known stationarity tests can be applied to this series. Simulation results indicate that in certain cases these tests, like several linearity tests, can have low power. The proposed model is applied to interest rate data.
A tangentially viewing visible TV system for the DIII-D divertor

A video camera system has been installed on the DIII-D tokamak for 2-D spatial studies of line emission in the lower divertor region. The system views the divertor tangentially from an outer port at approximately the height of the X-point. At the tangency plane the entire divertor from inner wall to outside the DIII-D bias ring is viewed with spatial resolution of approximately 1 cm. The image contains information from approximately 90 degrees of toroidal angle. In a recent upgrade, remotely controllable filter changers were added which have produced images from nominally identical shots using a series of spectral lines. Software was developed to calculate the response function matrix using distributed computing techniques and assuming toroidal symmetry. Standard sparse matrix algorithms are then used to invert the 3-D images onto a poloidal plane. Spatial resolution of the inverted images is 2 cm; higher resolution simply increases the size of the response function matrix. Initial results from a series of experiments with multiple identical shots show that the emission from CII and CIII, which appears along the inner scrape-off layer above and below the X-point during ELMing H-mode, moves outward and becomes localized near the X-point in Partially Detached Divertor (PDD) operation.