bluuebunny/crossref_metadata_2025_split huggingface dataset:
A pilot study for self-guided, active robotic training of proprioception of the upper limb in chronic stroke
Authors: Tulimieri Duncan , Kim GilHwan , Hoh Joanna E. , Sergi Fabrizio , Semrau Jennifer A. 
Published: June 2024

Abstract

Background
Proprioceptive impairments of the upper limb are common after stroke. These impairments are not typically addressed during assessment or rehabilitation. Currently, most robotic paradigms for rehabilitative training of the upper limb have focused solely on improving motor function or have targeted proprioception in individuals with combined use of visual feedback. Our goal was to design a training paradigm that directly targets proprioception of the upper limb, while minimizing reliance on other sensory information to improve sensorimotor function after stroke.
Methods
In this pilot study, 5 stroke participants and 5 age-matched controls were tested on a single-day proprioceptive training paradigm. Here, participants used a joystick with their less-affected arm to send commands to a KINARM exoskeleton that would passively move their more-affected arm. To complete the passive reaching task, participants relied only on proprioceptive feedback from the more-affected arm and were only given knowledge of results information after each trial. Sensorimotor function of the upper limb was measured pre- and post-training via robotic measures of motor function (Visually Guided Reaching (VGR)) and position sense (Arm Position Matching (APM)). Sensorimotor function was quantified as a Task Score, which incorporated multiple task-relevant parameters for both VGR and APM. Changes in sensorimotor performance due to training were calculated as the pre- to post-training difference for VGR and APM within the control and stroke groups.
Results
We found significant improvements from pre-training to post-training for VGR in stroke participants (p < 0.001, CLES = 100) that were not observed in control participants (p = 0.87, CLES = 80). We observed significant changes from pre- to post-training in both VGR (Posture Speed, Reaction Time, Initial Direction Angle, Min-Max Speed Difference, and Movement Time) and APM (Contraction/Expansion Ratiox and Shifty) parameters.
Conclusions
Our novel proprioceptive training paradigm resulted in improvements in motor function and aspects of proprioceptive performance for individuals with chronic stroke. This pilot study demonstrates the feasibility of this training paradigm for targeted proprioceptive training to improve motor and sensory function in individuals with chronic stroke. Future studies aim to examine multi-day training to examine longer-term impacts on upper limb sensorimotor function.
Role of Edible Flowers on Reducing Lipid and Protein Oxidation in Ground Beef
Authors: Duggirala Krishna Brunda , Mohan Anand 
Published: June 2024

Abstract

This study examined the antioxidant, physicochemical, and sensory characteristics of raw ground beef patties, including those augmented with varying percentages of roselle (Hibiscus sabdariffa L.) and rose (Rosa canina L.) powders, and stored at 4°C for 7 days. The analysis encompassed parameters such as 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, 2-thiobarbituric acid reactive substances (TBARS), carbonyls, Schiff bases, free thiols, water holding capacity, pH, color, and texture. The incorporation of roselle and rose powders led to heightened scavenging activity, resulting in reduced oxidative activity, carbonyls, Schiff bases, and free thiols during storage. Enhanced water holding capacity and decreased pH were observed in raw ground beef patties treated with these powders. While minimal impact on texture was noted across all samples, color attributes of patties treated with roses remained acceptable by the 7th day. Overall, the inclusion of rose powder exhibited more favorable effects than untreated raw ground beef patties and those treated with roselle. Consequently, raw ground beef patties treated with rose powders demonstrated greater efficacy in enhancing the quality attributes under investigation.
Does workforce affect technical efficiency? A Stochastic Frontier Approach across industries
Authors: Pinheiro Carlos Manuel , Silva Paulo Pereira 
Published: June 2024

Abstract

Sustainability has become the new normal for value creation in the long haul, and is on the top of every board’s agenda. We assess the relationship between the workforce and a firm’s output gap justified by systematic inefficiency. To do so we apply a stochastic frontier model to a large sample of U.S. listed firms, across industries, spanning 2005 to 2019, focusing on measures of companies’ management commitment and effectiveness in addressing their workforce job conditions and well-being. Our results reveal an economically sizable and statistically significant positive association between technical efficiency and workforce-wellbeing. Firm inefficiency is explained by firm specific factors and is a decreasing (increasing) function of size and external monitoring (leverage, blockholdings and foreign sales). It is mitigated by employee-oriented practices and external governance mechanisms, as well as market surveillance. The association between workforce and technical efficiency is non-linear and varies across industry sectors. Our results have policy implications and should interest managers and stakeholders in general.
JEL Classification: C73; G14, G23, G34
Assessing the relationship between canopy density and understory vegetation in planted forest by using constraint line methodology
Authors: Hao Ruifang , Shi Mingchang , Wang Bin , Sun Yun , Qiao Jianmin 
Published: June 2024

Abstract

Greater shrub and herb abundance and diversity under the forest would potentially benefit biodiversity and improve forest ecosystem stability. Therefore, determining whether a high canopy density results in reduced growth of understory vegetation and associated thresholds may guide the reasonable planting density of planted forest. In this study, we selected an artificial coniferous forest planting area in Hubei Province, China as the research area, and adopted a constraint line to explore the relationship between the canopy density of different species, including Chinese fir (Cunninghamia lanceolata), cypress (Cupressus funebris), and Masson pine (Pinus massoniana), and the height and coverage of shrubs and herbs in the forests. The upper constraint lines, lower constraint lines, and mean lines were extracted by segmented quantile regression derived from the maximums, means, and minimums in the scatter clounds, which represented the relationships under the best, worst, and general environmental conditions, respectively. The results showed that for different species, the upper constraint lines were almost hump-shaped with thresholds, indicating that regardless of how good the environmental conditions were, the indicators of understory shrubs and herbs first increased and then decreased with an increase in canopy density. The canopy density thresholds for Chinese fir, cypress, and Masson pine were approximately 50%, 30%~40%, and 50%~60%, respectively. Overall, the thresholds of canopy density for herb indicators were greater than those of shrubs. Planning reasonable canopy density may enhance the growth of understory vegetation.
Causal relationship between gut microbiota, circulating inflammatory proteins and IgA nephropathy: two-sample and mediated Mendelian randomisation analysis
Authors: Dong Pengtao , Li Xiaoyu , Feng Xue , Huang Siyu , Cui Bing , Zhang Qing , Zhao Ziran , Wang Zheng 
Published: June 2024

Abstract

Background：IgA nephropathy (IgAN) is an immune-inflammatory glomerulonephritis mediated by both genetic and environmental factors. Recent research indicates a close association between gut microbiota dysbiosis and IgAN development. Additionally, circulating inflammatory proteins also play a significant role in the progression of IgAN.However, the causal relationship among gut microbiota, circulating inflammatory proteins, and IgAN remains unclear.
Methods：This study utilized publicly available genome-wide association study (GWAS) data for Mendelian randomization (MR) analysis to investigate the causal relationship among gut microbiota circulating inflammatory proteins and IgAN, as well as to examine the mediating role of circulating inflammatory proteins in the association between gut microbiota and IgAN. The primary analytical method employed in this study was inverse variance-weighted (IVW) analysis with specific attention given to Bayesian-weighted MR results and supported by MR-Egger regression, weighted median, median model and simple model approaches. Several sensitivity analyses were performed to evaluate the robustness of MR analysis findings.
Results：(1)MR analysis of gut microbiota and IgAN indicates negative associations between g_Roseburia, g_Faecalibacterium, s_Odoribacter_splanchnicus, and s_Roseburia_unclassified with IgAN risk, while positive associations exist between s_Paraprevotella_unclassified and s_Lachnospiraceae_bacterium_7_1_58FAA with IgAN risk.(2) Circulating inflammatory proteins to IgAN in MR analysis showed that IL-10RA was negatively correlated with the risk of IgAN, while TSGP-CD5, FGF23, LIF, and TGF-α levels were positively correlated with the risk of IgAN.(3)Mediation analysis suggests that TGF-αserves as a mediator between s_Odoribacter_splanchnicus and the causality of IgAN. (4) The results of the reverse MR analysis suggest no significant causal effect of IgAN on gut flora and circulating inflammatory proteins.Sensitivity analyses consistently support the reliability of the study results.
Conclusion：Our research findings, obtained through genetic methods, substantiate the causal link between gut microbiota, circulating inflammatory proteins, and IgAN. The identification of biomarkers offers novel insights into the potential mechanisms underlying IgAN, which can be advantageous for early diagnosis and the development of more effective treatment strategies.
Zinc sulphate alleviates olanzapine-induced testicular oxidative stress and alters trace elements in male rats
Authors: Ebaid Hossam , Bashandy Samir , Hassan Iftekhar , Al-Tamimi Jameel , Haredy Shimaa , Imbabi Tharwat , Omara Enayat , Bashandy Yousef , Awad Ezzat 
Published: June 2024

Abstract

Male infertility is a complex and multifactorial clinical condition affecting a large population attributed to various factors, including perturbation in oxidative stress and the level of essential trace elements. Oxidative insults exert multiple issues related to reproductive health, including male infertility, decreased sperm motility, sperm DNA damage, and an increased susceptibility to genetic disorders. Besides chemical toxins and food allergens in junk food items, many drugs can also lead to male fertility. Olanzapine, a general antipsychotic drug, has also been reported to induce male fertility. A great deal of literature entails that zinc can alleviate oxidative stress-related clinical complications including male fertility. This study investigates the potential protective effects of zinc sulphate on olanzapine-induced male infertility. In the present study, there were four treatment groups (n = 6) Group 1 as control (without any treatment); Group 2 treated with olanzapine (10 mg/kg) orally daily for six weeks; Group 3 and 4 treated with 50mg/kg and 100 mg/kg of zinc sulphate respectively in pre-exposed olanzapine (10mg/kg) orally daily for six weeks. After completion of the treatment, the biochemical analysis of serum and tissue samples demonstrated that group 2 had compromised levels of antioxidant parameters (SOD, CAT and GSH) as well as elevated levels of stress parameters (GSSG, MDA and NO). However, ZnSO4 corrected all these parameters in a dose-dependent way in groups 3 and 4. Other health indicators, like taurine, enzyme Q10, phosphatidylcholine, ascorbic acid, and vitamin E, were also observed to improve with the supplementation of ZnSO4. Intriguingly, all the fertility parameters (sperm motility, count and level of testosterone) were also found to significantly enhanced with decreased sperm abnormalities in both the combination groups. The histological evaluation of the testis section also agreed with the biochemical analysis. Therefore, the study strongly advocates that supplementation of Zn can ameliorate olanzapine-induced male infertility to a significant extent.
Salinity prediction in Qiantang Estuary based on Improved LSTM model
Authors: Zheng Rong , Sun Zhilin , Jiao Jiange , Ma Qianqian , Zhao Liqin 
Published: June 2024

Abstract

Investigating saltwater intrusion is vital for optimal use of estuarine water resources. Presently, diverse data-driven models, mainly neural network models, have been employed to predict tidal estuarine salinity. However, the high nonlinearity, randomness, and instability of salinity sequences pose challenges for accurate estuarine salinity forecasting. In this paper, a multi-factor salinity prediction model using an enhanced Long Short-Term Memory (LSTM) network was proposed, based on measured data from Cangqian and Qibao stations in the Qiantang Estuary during 2011-2012. To improve prediction accuracy, input variables of the model were determined through Grey Relational Analysis (GRA) combined with estuarine dynamic analysis, and hyperparameters were optimized using a multi-strategy Improved Sparrow Search Algorithm (ISSA). Additionally, the model was applied to forecast salinity under different runoff conditions, analyzing the sensitivity of salinity to upstream discharge. Experimental result shows that compared to other models (BP, GRU, LSTM, SSA-LSTM), the new proposed ISSA-LSTM model has smaller errors and higher prediction accuracy, with NSE improving over 5% and other metrics (MAP, MAPE, RMSE) improving over 10%. Thus, the model provides a practical solution for the rapid and precise prediction of estuarine salinity.
The impact of blastocyst grade on singleton birthweight in fresh IVF-ET cycles in ART: a retrospective study
Authors: Zhao Boya , Shi Qiongyao , Shi Senlin 
Published: June 2024

Abstract

Background:
The positive correlation between embryo quality and pregnancy outcomes has been well confirmed in many studies, but few studies have investigated the impact of embryo quality on neonatal weight, especially among neonates from fresh IVF-ET cycles in ART. So the objective of the article was to compare the birth weights of infants from different blastocyst grades in fresh IVF-ET cycles and to explore related factors affecting birth weight.
Methods:
A retrospectively cohort study was performed to compare the birth weight of different blastocyst grades in fresh transplantation cycle and explore the related factors affecting the birth weight. A total of 1301 fresh cycles of single blastocyst transplantation and single live birth profile were retrospectively analyzed and were grouped into four groups depending on the blastocyst quality: excellent group(grade AA) 170 cycles, good group༈grade AB/BA༉312 cycles, average group༈grade BB/CA/AC༉ 559 cycles and poor group༈grade BC/CB༉260 cycles. Comparison among four groups of patients by birth weight and general conditions, fertilization rate, embryo rate, cleavage rate and D5、D6 blastocyst formation rate and other laboratory indicators were made. And then compare the birth weight of different groups which were divided by the degree of blastocyst expansion, and the classification of intracellular mass(ICM) and extracellular trophoblastic(TE).
Results:
The study showed that birth weight of excellent group was significantly higher than that of the other three groups (P < 0.05). And the high quality embryo rate and blastocyst rate of excellent group were significantly higher than those of the other three groups (P < 0.05). What’s more, the clinical pregnancy rate, implantation rate and live birth rate of high grade blastocyst were higher, but there was no significant difference in abortion rate. The birth weight of blastocyst of grade 3 and below was significantly lower than that of those with grade 3 and above (P < 0.05).The birth weight of grade A intracellular mass was significantly higher than that of B intracellular mass of blastocyst(P < 0.05). Babies born with grade B ectotrophoblast cells were significantly heavier than those born with grade C ectotrophoblast cells(P < 0.05).
Conclusion:
The authors conclude that high grade blastocyst transplantation can achieve better pregnancy outcome. Different blastocyst grades affect birth weight, and low grade blastocyst transplantation was associated with a single birth weight loss.
MopIR: a machine-learning-oriented data preprocessing pipeline for precise analysis of infrared spectroscopy
Authors: Huang Ziwei , Gu Xingxin , Shi Suwen , Meng Xiangyi , Hang Junjie , Lin Jianli , Zhong Claire Chenwen , Li Yu , Huang Junjie 
Published: June 2024

Abstract

The application of infrared (IR) spectroscopy is limited due to intrinsically theoretical constraints. Machine learning offers a route for overcoming these limitations. Nevertheless, its efficacy significantly relies on the quality of data because irrelevant and/or redundant information hinders the success of learning the true signal. In this study, we introduced an intuitive multivariate method tailored for assessing the quality of spectra obtained from experimental replicates of identical samples. Additionally, we developed an analytical tool named "MopIR" (Machine-learning-Oriented Pipeline for InfraRed spectroscopy) designed to enhance the quality of IR spectra and therefore boost the performance in downstream machine learning tasks. The application of MopIR on simulated IR spectra yielded a substantial improvement in the quality of processed spectra. Furthermore, we extended the application of MopIR by combining it with machine learning algorithms on labeled IR spectra obtained from soil samples to predict carbon concentration within the samples. Our findings revealed a remarkable reduction in predictive errors and an enhancement in stability when comparing MopIR-processed data to raw data. In addition, we applied MopIR to IR spectra obtained from wood samples subjected to thermal-hydro-mechanical (THM) modifications, resulting in the reduction of background effect, signal amplification, and a boost in classification accuracy. Our results demonstrated an enhancement in machine learning tasks achieved through the improvement of data quality in the context of IR spectra analysis.
A rigidity theorem for compact gradient Einstein-type manifolds with boundary
Authors: Chen Xiaomin 
Published: June 2024

Abstract

Inspired by the recent paper of Baltazar and Queiroz (Rigidity Theorem for Integral Pinched Static Manifolds and Related Critical Spaces, J. Geom. Anal. 2024), in this article, we prove the rigidity for compact gradient Einstein-type manifolds with nonempty boundary and constant scalar curvature under a pinching condition, which is independent on the potential function. As a special case of gradient Einstein-type manifold, we also give a rigidity result of (m, ρ)-quasi-Einstein manifold with boundary.
2020 Mathematics Subject Classification. 53C25; 53C20; 53C21.
Research on Visual Recognition Method for Defect Detection in Photovoltaic Cells Based on Deep Learning
Authors: Wang Xueguang , Yin Hengbin , Wang Meng 
Published: June 2024

Abstract

The quality and efficiency of photovoltaic power generation are closely related to the excellent performance of solar panels.Using defective panels may reduce power generation efficiency and product lifespan, and even lead to serious safety accidents .Therefore, strict defect detection is necessary before the photovoltaic panels leave the factory.This paper proposes a detection algorithm based YOLOv5 for Photovoltaic panel inspection.By combining a linear bottleneck inverted residual structure with an efficient pyramid split attention module called EPSA, the computational and parameter requirements are reduced. Additionally, by enhancing the optimization of Ghost convolution and deep convolution, the computational load is further reduced. The balanced cross-entropy loss function and non-maximum suppression method are combined to investigate multiple small target defect detections. Comparison experiment results on the defect dataset of photovoltaic cells demonstrate that the accuracy (P) of the enhanced algorithm has increased by 6.30%, and the average accuracy (mAP) has increased by 9.40%.The proposed model effectively identifies photovoltaic cell defects, fulfilling the criteria for photovoltaic panel inspection, and showing promising application prospects.
A novel distance measure for probabilistic linguistic term sets with application to emergency decision-making
Authors: Liu Hanjie , Wang Zhiying , Jia Hongmei 
Published: June 2024

Abstract

The probabilistic linguistic term sets (PLTSs), as a form of fuzzy language, is capable of effectively expressing the evaluation information of decision-makers (DMs) in emergency decision-making (EDM). In response to the uncertainty of decision-making information and the non-complete rationality of DMs in EDM, a method for EDM based on PLTSs and regret theory has been developed. Firstly, a novel distance measure model based on the Euclidean distance, Jensen-Shannon (JS) divergence, and Jousselme distance is established for the PLTSs. Secondly, the expert weight is calculated based on both the degree of trust in the expert and the degree of similarity in viewpoints. In the process of consensus reaching, a feedback adjustment coefficient is introduced to reasonably retain the original evaluation information provided by experts. Then, a combined weighting model is established based on both objective attribute weight and subjective attribute weight in order to solve the comprehensive attribute weight. It is important to consider that DMs are often not entirely rational; therefore, an EDM method is constructed using PLTSs and regret theory to prioritize alternatives. Finally, the effectiveness and feasibility of the proposed method are validated through the selection of a transportation scheme for earthquake relief materials.
Muscle-targeted Klotho Gene Therapy Ameliorates ALS Hallmarks by Addressing Multiple Disease Mechanisms in SOD1G93A Mice
Authors: Bosch Assumpció , Verdés Sergi , Guerrero-Yagüe Rubén , Gaja-Capdevila Núria , Sauleda Judith , Rey Javier Rel , Roig-Soriano Joan , Chillon Guillem , Leal-Julià Marc , Rodríguez-Estévez Laura , Chillón Miguel , Herrando-Grabulosa Mireia , Navarro Xavier 
Published: June 2024

Abstract

The antiaging protein a-Klotho (KL) exhibits neuroprotective and myoregenerative properties, mitigating age-related neurodegeneration and promoting muscle regeneration. This study harnesses its pleiotropic properties in the context of Amyotrophic Lateral Sclerosis (ALS), a motoneuron disease lacking effective treatments due to its diverse pathophysiological mechanisms. By overexpressing secreted KL in skeletal muscles of SOD1G93A mice with myotropic viral vectors we aimed to directly protect muscles and exert a paracrine effect on motoneuron (MN) terminals. Secreted KL preserved MNs and neuromuscular junctions, and mitigated glial reactivity, resulting in maintained muscle mass, improved neuromuscular function, delayed disease onset, and extended survival. Even when administered during symptomatic stages, KL slowed down ALS progression. Transcriptomic and proteomic studies in muscles revealed significant correction of pathophysiological mechanisms involved in ALS disease, unveiling novel roles for KL. These findings highlight the potential application of muscle-secreted KL in ALS regardless of its origin and suggest broader therapeutic implications.