Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on control method of upper limb exoskeleton based on mixed perception model

Abstract As one of the research hotspots in the field of rehabilitation robotics, the upper limb exoskeleton robot has been widely used in the field of rehabilitation. However, the existing methods cannot comprehensively and accurately reflect the motion state of patients, which may lead to overtraining and secondary injury of patients in the process of rehabilitation training. In this paper, an upper limb exoskeleton control method based on mixed perception model of motion intention and intensity is proposed, which is based on the 6 degree-of-freedom upper limb rehabilitation exoskeleton in the laboratory. First, the kinematic information and heart rate information in the rehabilitation process of patients are collected, corresponding to patients’ motion intention and motion intensity, and fused to obtain the mixed perception vector. Second, the motion perception model based on long short-term memory neural network is established to realize the prediction of upper limb motion trajectory of patients and compared with back-propagation neural network to prove its effectiveness. Finally, the control system is built, and both offline and online test of the control method proposed are implemented. The experimental results show that the method can achieve comprehensive motion state perception of patients, realize real-time and accurate prediction trajectory according to human motion intention and intensity. The average prediction accuracy is 95.3%, and predicted joint angle error is less than 5 degrees. Therefore, the control method based on mixed perception model has good robustness and universality, which provides a new method for the active control of upper limb exoskeleton.
Comparison Evaluation of the Biological Effects of Sterigmatocystin and Aflatoxin B1 Utilizing SOS-Chromotest and a Novel Zebrafish (Danio rerio) Embryo Microinjection Method

Aflatoxin B1 (AFB1) is a potent mycotoxin and natural carcinogen. The primary producers of AFB1 are Aspergillus flavus and A. parasiticus. Sterigmatocystin (STC), another mycotoxin, shares its biosynthetic pathway with aflatoxins. While there are abundant data on the biological effects of AFB1, STC is not well characterised. According to published data, AFB1 is more harmful to biological systems than STC. It has been suggested that STC is about one-tenth as potent a mutagen as AFB1 as measured by the Ames test. In this research, the biological effects of S9 rat liver homogenate-activated and non-activated STC and AFB1 were compared using two different biomonitoring systems, SOS-Chromotest and a recently developed microinjection zebrafish embryo method. When comparing the treatments, activated STC caused the highest mortality and number of DNA strand breaks across all injected volumes. Based on the E. coli SOS-Chromotest, the two toxins exerted the same genotoxicities. Moreover, according to the newly developed zebrafish microinjection method, STC appeared more toxic than AFB1. The scarce information correlating AFB1 and STC toxicity suggests that AFB1 is a more potent genotoxin than STC. Our findings contradict this assumption and illustrate the need for more complex biomonitoring systems for mycotoxin risk assessment.
Antiosteoporosis Studies of 20 Medicine Food Homology Plants Containing Quercetin, Rutin, and Kaempferol: TCM Characteristics, In Vivo and In Vitro Activities, Potential Mechanisms, and Food Functions

Dietary nutraceutical compounds have been evidenced as backbone for bone health in recent years. It is reported that medicine food homology (MFH) plants have multiple nutraceutical compounds. Based on our literature research, 20 MFH plants caught our attention because they contain three popular antiosteoporosis compounds simultaneously: quercetin, rutin, and kaempferol. According to traditional Chinese medicine (TCM), their characteristics including natures, flavors, attributive to meridian tropism, and efficacies were listed. The relationships between TCM efficacies, such as “heat clearing,” “tonic,” and “the interior warming,” and antiosteoporosis pharmacological actions such as antioxidant and immune regulation were discussed. The in vivo antiosteoporosis effects of the 20 MFH plants were summarized. The in vitro antiosteoporosis activities and related mechanisms of the 20 plants and quercetin, rutin, kaempferol were detailed. The TGF-β-Smad signaling, fibroblast growth factor, and Wnt/β-catenin signaling on bone formation and the RANKL signaling, NF-κB signaling, and macrophage-colony-stimulating factor on bone resorption were identified. From food point, these 20 MFH plants could be classified as condiment, vegetable, fruit, tea and related products, beverage, etc. Based on the above discussion, these 20 MFH plants could be used as daily food supplements for the prevention and treatment against osteoporosis.
Antimicrobial Analysis of Biosynthesized Lectin-Conjugated Gold Nanoparticles

To enhance the bioactivity of molecules through nanoparticles is being tested which has potential use in sustained-release drug delivery systems and to enhance the therapeutic effectiveness of drugs. Our current investigation s is to conjugate lectin to that of a gold nanoparticle (GNP) surface without disturbing the bioactive properties and enhances the antibacterial activity of lectin. Au-lectin nanoparticles were checked for their hemagglutination activity, characterized by transmission electron microscopy (TEM) and UV-visible spectrophotometer. The antibacterial effect of nanoparticle lectin, Au salt nanoparticle, and conjugated Au-lectin was estimated by Kirby-Bauer disc method; MICs were determined by microbroth dilution and compared with ciprofloxacin. These tests were done using known species of bacterial strain of multidrug resistant. The hemagglutination activity of lectin was improved to fourfold after purification. Lectin and Au nanoparticles combined had a significant effect on the inhibition of bacterial growth. No significant differences were observed in the inhibition zone diameters from killed bacteria and its supernatant towards any of the tested organisms. Lectin-conjugated gold particles showed good efficacy as antimicrobial agents and the nanoparticle-killed bacteria to work against the viable population of the same bacterium and/or other bacterial species too.
Harmful Stress-Related Couple Processes During the COVID-19 Pandemic and Lockdown: A Longitudinal Dyadic Perspective

In March 2020, the World Health Organization declared the disease caused by SARS-CoV-2 coronavirus “pandemic. ” To reduce the risk of contamination, many countries have ordered a lockdown characterized by social distancing and restrictive isolation measures. While the lockdown has proven to be quite effective in terms of physical health, little is known about its impact on couple satisfaction in a dyadic perspective. The current research was a 4-waves longitudinal study (i.e., from March to July 2020) with the objective to examine the trajectory of couple satisfaction during the lockdown with a dyadic perspective (N = 108 couples), including the presence (or absence) of children at home, the number of hours spent together, and the duration of the relationship as time-invariant predictors and the partner’s couple satisfaction trajectory as a time-varying covariate. Results showed positive intraindividual changes in couple satisfaction during the lockdown, especially an increase in partners’ effectiveness for resolving couple conflicts and a decrease in partners’ aggressiveness. Partners had also perceived the influence of the lockdown as more and more positive over time on couple and family functioning. Finally, the couple satisfaction of both partners changed in tandem during the lockdown: The perception of the couple relationship seems to similarly evolve between partners.
Traffic Flow Prediction: An Intelligent Scheme for Forecasting Traffic Flow Using Air Pollution Data in Smart Cities with Bagging Ensemble

Traffic flow prediction is the most critical part of any traffic management system in a smart city. It can help a driver to pick the most optimized way to their target destination. Air pollution data are often connected with traffic congestion and there exists plenty of research on the connection between air pollution and traffic congestion using different machine learning approaches. A scheme for efficiently predicting traffic flow using ensemble techniques such as bagging and air pollution has not yet been introduced. Therefore, there is a need for a more accurate traffic flow prediction system for the smart cities. The aim of this research is to forecast traffic flow using pollution data. The contribution is twofold: Firstly, a comparison has been made using different simple regression techniques to find out the best-performing model. Secondly, bagging and stacking ensemble techniques have been used to find out the most accurate model of the two comparisons. The results show that the K-Nearest Neighbors (KNN) bagging ensemble provides far better results than all the other regression models used in this study. The experimental results show that the KNN bagging ensemble model reduces the error rate in predicting the traffic congestion by more than 30%.
Improved PMSM for Wind Turbine Applications with Multiple High-speed Generators : Invited paper from the International Conference on Optimization of Electrical and Electronic Equipment (OPTIM) [24], May 22-24, 2014, Brasov

Wind turbines (WTs) are energy conversion systems with a very complex electromechanical structure, consisting of highly interconnected subsystems, which are constantly exposed to dynamic electrical and mechanical stress. In order to improve their technical and economic efficiency, new alternative drive train concepts are being sought. This paper proposes a WT drive train with multiple high-speed generators. Different electrical machines are investigated analytically and the permanent magnet synchronous machine with V-shaped internal magnets (VI-PMSM) is chosen as the most suited topology for this application. A simple MATLAB Simulink model is developed to validate the proposed WT configuration in terms of efficiency gain. Furthermore, the operational behavior of the VI-PMSM is improved by means of sinusoidal rotor field poles.
Oxidative Stress and DNA Damage Effect of Dioscorea hispida Dennst. on Placental Tissues of Rats

Dioscorea hispida Dennst. locally known as “ubi gadung” has been used as a traditional remedy and source of carbohydrate among Malaysians. To assess the effect of Dioscorea hispida aqueous extract (DHAE) on the production of reactive oxygen species (ROS) and their effects on DNA damage in Sprague Dawley rat’s placental tissues, pregnant rats were randomly divided into four groups. The animals were orally treated with distilled water (negative control) and three different concentrations of DHAE (250, 500 and 1000 mg/kg body weight (BW)) from gestation day 6 until 20. The oxidative stress in placental tissues was evaluated at day 21 by measuring the level of ROS, superoxide dismutase (SOD) and lipid peroxidation biomarker, malondialdehyde (MDA) while comet assay was used for DNA damage. There was no significant production of ROS and SOD activities in all groups. Significant changes were observed in the MDA level at 1000 mg/kg BW DHAE. Comet assay revealed a significant increase (p < 0.05) of DNA damage on animals treated with 250 and 500 mg/kg BW DHAE but not at the highest concentration. It was postulated that the placental cells could have undergone necrosis which destroys all components including DNA. This occurrence simultaneously reduces the levels of DNA damage which can be represented by lower level of tail moments. This finding correlates with our histopathological examination where necrotic cells of spongiotrophoblast were observed in the basal zone of placental tissue. The high amount of hydrogen cyanide and other compounds in 1000 mg/kg BW DHAE could elevate the lipid peroxidation and directly induce cell necrosis which requires further investigation.
Angiotensin II Promotes Skeletal Muscle Angiogenesis Induced by Volume-Dependent Aerobic Exercise Training: Effects on miRNAs-27a/b and Oxidant–Antioxidant Balance

Aerobic exercise training (ET) produces beneficial adaptations in skeletal muscles, including angiogenesis. The renin–angiotensin system (RAS) is highly involved in angiogenesis stimuli. However, the molecular mechanisms underlying capillary growth in skeletal muscle induced by aerobic ET are not completely understood. This study aimed to investigate the effects of volume-dependent aerobic ET on skeletal muscle angiogenesis involving the expression of miRNAs-27a and 27b on RAS and oxidant–antioxidant balance. Eight-week-old female Wistar rats were divided into three groups: sedentary control (SC), trained protocol 1 (P1), and trained protocol 2 (P2). P1 consisted of 60 min/day of swimming, 5×/week, for 10 weeks. P2 consisted of the same protocol as P1 until the 8th week, but in the 9th week, rats trained 2×/day, and in the 10th week, trained 3×/day. Angiogenesis and molecular analyses were performed in soleus muscle samples. Furthermore, to establish ET-induced angiogenesis through RAS, animals were treated with an AT1 receptor blocker (losartan). Aerobic ET promoted higher VO2 peak and exercise tolerance values. In contrast, miRNA-27a and -27b levels were reduced in both trained groups, compared with the SC group. This was in parallel with an increase in the ACE1/Ang II/VEGF axis, which led to a higher capillary-to-fiber ratio. Moreover, aerobic ET induced an antioxidant profile increasing skeletal muscle SOD2 and catalase gene expression, which was accompanied by high nitrite levels and reduced nitrotyrosine concentrations in the circulation. Additionally, losartan treatment partially re-established the miRNAs expression and the capillary-to-fiber ratio in the trained groups. In summary, aerobic ET promoted angiogenesis through the miRNA-27a/b–ACE1/Ang II/VEGF axis and improved the redox balance. Losartan treatment demonstrates the participation of RAS in ET-induced vascular growth. miRNAs and RAS components are promising potential targets to modulate angiogenesis for combating vascular diseases, as well as potential biomarkers to monitor training interventions and physical performance.
Development of an Adaptive and Weighted Model Predictive Control Algorithm for Autonomous Driving With Disturbance Estimation and Grey Prediction

This paper presents an adaptive and weighted model predictive control (MPC) algorithm for autonomous driving with disturbance estimation and prediction. Unexpected and unpredictable disturbances in the real world limit the performance of MPC. To overcome this limitation, this paper proposes adaptive and weighted prediction methods with a sliding mode observer and a weighting function with the grey prediction model. The sliding mode observer is designed for disturbance estimation with finite stability conditions, and the estimated disturbance is predicted using the grey prediction model. Based on the adaptive and weighted prediction method, the length of prediction horizon and cost value of each predicted state are adjusted in real time to eliminate any negative impact on future predicted states. Meanwhile, a variation in the cost value, which is caused by prediction horizon adaptation and weighted prediction, may harm the control performance as it can excessively increase or decrease the model uncertainty. Therefore, an input weighting factor is adapted in the MPC cost function based on an exponential weighting function. The performance of the proposed adaptive control algorithm is evaluated using CarMaker software under longitudinal and lateral autonomous driving scenarios.
Succession and Driving Factors of Periphytic Community in the Middle Route Project of South-to-North Water Division (Henan, China)

The Middle Route Project of the South-to-North Water Diversion is an artificially independent system that does not connect to other surface waters. Excessive periphyton proliferation causes a series of environmental problems in the canal. In this study, the periphyton community and environmental factors on the left and right banks of the canal in the algal growing area were investigated and sampled six times (June, September, and November of 2019 and 2020). The succession pattern of the attached organism community in the artificial canal was analyzed, and the key factors affecting the algal community were analyzed using RDA and GAM. The results showed that the seasonal variability of the environmental factors was more significant than the spatial variability. A total of 114 taxa of periphytic algae were found, belonging to seven phyla and 69 genera, and mainly composed of Bacillariophyta. Species richness was ranked as Bacillariophyta (60 taxa), Chlorophyta (31 taxa) and Cyanobacteria (15 taxa), and higher in autumn than in summer. The dominant taxa were Cymbella sp. , Fragilaria sp. , Navicula sp. and Diatoma sp. The abundance of periphytic algal varied from 0.07 × 105 to 8.99 × 105 ind. /cm2, with trends similar to that of species richness. The redundancy analysis and generalized additive model showed that water temperature and nutrient concentration were the key factors influencing the structure of the algal community, followed by discharge rate and velocity, which were the determinants of the spatial and temporal patterns of the algal community. In view of the influence of discharge and velocity on the structure of algal communities, it is suggested that ecological scheduling could be used to regulate the structure of the algal community on the canal wall in the operation of later water division projects to ensure the safety of water division.
Synthesis, antimicrobial, and antitubercular evaluation of new Schiff bases with in silico ADMET and molecular docking studies

Schiff bases are a proven moiety in antitubercular drug discovery and the antitubercular drug development. Drug discovery is a never-ending process due to evolving drug resistance by the bacteria, as a result, there is a need of developing new antitubercular drugs. In this continuous process of antitubercular drug discovery, new series of Schiff bases are synthesized using quinoline carbohydrazide upon coupling with different aldehydes in ethanolic media through multistep synthesis. These synthesized compounds were purified and characterized by different spectroscopic techniques. The molecules were in vitro screened for antifungal and antibacterial potential by Agar well diffusion assay, antitubercular activity by using microplate Alamar blue assay, and an attempt has been made to study the in-silico relationship between new Schiff base derivatives 4a-f and the crystal structure of M. tuberculosis (5V3Y) protein by molecular docking studies. Synthesized compounds 4a-f show good interaction with the crystal structure of M. tuberculosis protein (5V3Y) and fulfill ADMET characteristics in silico experiments. Among the compounds tested, compound 4d was found to be active against bacteria and fungi. Compound 4b was found to be sensitive against M. tuberculosis at 50 µg/mL concentration.
Numerical scrutinization of dropwise condensation heat transfer on an inclined surface

Recently, achieving an ameliorated heat transfer rate in dropwise condensation (DWC) has attracted the attention of many researchers. Several parameters, including chemical and physical properties of the substrate, inclination, and interfacial characteristics influence DWC heat transfer rate. The variation of inclination angle is followed by the change in droplet shape and consequently, the heat transfer rate are changed. In this study, the effect of droplet shape variation on diverse inclined substrates is simulated. Moreover, three‐dimensional mass, momentum, and energy equations considering the desired boundary conditions on the unstructured grid are utilized for the scrutinization of flow behavior and heat transfer for static and sliding droplets. For the sake of validation, the outcomes obtained from the simulation were compared with existent data in the literature and a proper agreement was attained. Regarding the outcomes, it was of concern that the influence of inclination angle on the droplet shape is more distinct at higher droplet volume; while no considerable change was seen on heat flux of small droplets by increasing the inclination angle. Furthermore, a higher heat transfer rate was noted by exceeding the inclination angle beyond a definite angle. Additionally, the increased heat transfer rate was affirmed by increasing the Marangoni number ( Ma ) $({Ma})$ .
Translating social science for peace: Benefits, challenges, and recommendations.

translational science by conducting research that responds to pressing social challenges, and (b) to provide concrete recommendations on how to incorporate such practices into their research programs. To do this, we bring together perspectives of academicsand practitioners who have experience merging science with practice. We begin by de ﬁ ning what translational science is, describing the bene ﬁ ts of engaging in translational science for peace and con ﬂ ict studies, and highlighting past research that has done this successfully. Next, we describe various aspects of conducting translational science, such as how researchers can partner with nonacademic stakeholders to create social impact and advance scienti ﬁ c theory, and how they can disseminate ﬁ ndings for public impact. We also address key challenges researchers might face when conducting translational research andprovidepracticaltipsthatsocialscientistscanusetoeffectivelyengageinwhatwecoinedthe “ Bruneauian ” approach for how to address such challenges. Speci ﬁ cally, we focus on the skills needed for study design and deployment, how researchers can sensitively interact with vulnerable communities, statistical and methodological considerations, logistical challenges, and how to develop relationships with practitioners. Finally, we conclude with a practitioner ’ s perspective on how to foster these types of relationships. Here we make the case for translational science that not only advances theory but also achieves real world impact. We highlight the importance of using science to address pressing social challenges and offer guidance to those who are charged with addressing them.
Mouse brain extraction using 2-Stage CNNs

Magnetic resonance imaging of mice and other small animals plays an important role in translational medicine, where animal models are essential in the study of diseases and their potential treatments. While a large number of brain imaging studies using mice are conducted every year, there are few tools designed specifically for analyzing mouse MRI. Researchers often resort to adapting tools designed for processing MRI of human brains to work for the different structure, composition, and appearance of the mouse brain. While these methods may provide a reasonable initialization, researchers often have to perform extensive manual editing. In this work, we adapted a patch-based 2-Stage CNN Architecture to segment brain and non-brain in mouse MRI. We trained our model using brain MRI of healthy mice and mice with experimental autoimmune encephalomyelitis. These images had been previously acquired by our research team and processed to extract the brain using detailed manual editing. We compared our method with five existing tools, including BSE,1 rBET,2 AFNI,3 PCNN,4 and nnU-Net,5 using manually delineated mouse MRI. Both our method and nnU-Net achieved mean Dice scores on the order of 0.99 and HD95 measures on the order of one voxel, substantially outperforming the other methods. Our proposed method had slightly better Dice, HD99, and sensitivity measures than nnU-Net, while nnU-Net had slightly better HD95 scores. While these differences were small enough that further evaluation of the methods on a broader set of images would be warranted, they do suggest that our proposed method is competitive with a state-of-the-art deep learning method.