Theoretical uncertainties of(d,^(3)He)and(^(3)He,d)reactions owing to the uncertainties of optical model potentials

The theoretical uncertainties of single proton transfer cross sections of the(^(3)He,d)and(d,^(3)He)reactions,owing to the uncertainties of the entrance-and exit-channel optical model potentials,are examined with the^(30)Si(^(3)He,d)^(31)P,^(13)B(d,^(3)He)^(12)Be,and^(34)S(^(3)He,d)^(35)Cl reactions at incident energies of 25,46,and 25 MeV,respectively,within the framework of the distorted wave Born approximation.The differential cross sections at the first peaks in the angular distributions of these reactions are found to have uncertainties of approximately 5%,owing to the uncertainties in the optical model potentials from 20,000 calculations of randomly sampled parameters.This amount of uncertainty is found to be nearly independent of the angular momentum transfer and the target masses within the studied range of incident energies.Uncertainties in the single proton spectroscopic factors obtained by matching the theoretical and experimental cross sections at different scattering angles are also discussed.

A Study of Compound Action Potentials in Current-Coupled Tracts: the General Case

In this paper, the authors investigate compound action potentials formed when the underlying tract's axons have current-mediated coupling amongst themselves, and no field-mediated coupling. The key finding of the paper is that, for the case of biophysically inhomogeneous axon tracts, the compound action potential is governed by a Hodgkin-Huxley like equation itself in certain cases. The paper extends an earlier result for the identical axon case.

基于LDA主题模型的GitHub Actions工作流项目推荐算法

在CI/CD实践中,自动化已成为软件开发实践中的一种规范。GitHub引入GitHub Actions为软件维护者提供自动化的持续集成工作流方案,尽管其为开发者提供了诸多便利,GitHub社区也提供了许多第三方的GitHub Actions服务,但仍然只有极少的项目在使用。为了满足开发人员对工作流自动化的需求,减少非开发任务工作量,提出一种基于隐含狄利克雷分布(LDA)主题模型和Jensen-Shannon距离的GitHub Actions工作流项目推荐算法。通过对GitHub Actions存储库的README文件进行主题建模,将GitHub的事件描述文本和用户输入作为模型输入,为正在开发的代码仓库推荐GitHub Actions服务。将该推荐模型与标准的基于余弦相似度的方法进行比较的实验结果表明,该方法能有效改善开源软件仓库的推荐精度。

Workout Action Recognition in Video Streams Using an Attention Driven Residual DC-GRU Network

Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions in videostreams holds significant importance in computer vision research, as it aims to enhance exercise adherence, enableinstant recognition, advance fitness tracking technologies, and optimize fitness routines. However, existing actiondatasets often lack diversity and specificity for workout actions, hindering the development of accurate recognitionmodels. To address this gap, the Workout Action Video dataset (WAVd) has been introduced as a significantcontribution. WAVd comprises a diverse collection of labeled workout action videos, meticulously curated toencompass various exercises performed by numerous individuals in different settings. This research proposes aninnovative framework based on the Attention driven Residual Deep Convolutional-Gated Recurrent Unit (ResDCGRU)network for workout action recognition in video streams. Unlike image-based action recognition, videoscontain spatio-temporal information, making the task more complex and challenging. While substantial progresshas been made in this area, challenges persist in detecting subtle and complex actions, handling occlusions,and managing the computational demands of deep learning approaches. The proposed ResDC-GRU Attentionmodel demonstrated exceptional classification performance with 95.81% accuracy in classifying workout actionvideos and also outperformed various state-of-the-art models. The method also yielded 81.6%, 97.2%, 95.6%, and93.2% accuracy on established benchmark datasets, namely HMDB51, Youtube Actions, UCF50, and UCF101,respectively, showcasing its superiority and robustness in action recognition. The findings suggest practicalimplications in real-world scenarios where precise video action recognition is paramount, addressing the persistingchallenges in the field. TheWAVd dataset serves as a catalyst for the development ofmore robust and effective fitnesstracking systems and ultimately promotes healthier lifestyles through improved exercise monitoring and analysis.

Abnormal Action Recognition with Lightweight Pose Estimation Network in Electric Power Training Scene

Electric power training is essential for ensuring the safety and reliability of the system.In this study,we introduce a novel Abnormal Action Recognition(AAR)system that utilizes a Lightweight Pose Estimation Network(LPEN)to efficiently and effectively detect abnormal fall-down and trespass incidents in electric power training scenarios.The LPEN network,comprising three stages—MobileNet,Initial Stage,and Refinement Stage—is employed to swiftly extract image features,detect human key points,and refine them for accurate analysis.Subsequently,a Pose-aware Action Analysis Module(PAAM)captures the positional coordinates of human skeletal points in each frame.Finally,an Abnormal Action Inference Module(AAIM)evaluates whether abnormal fall-down or unauthorized trespass behavior is occurring.For fall-down recognition,three criteria—falling speed,main angles of skeletal points,and the person’s bounding box—are considered.To identify unauthorized trespass,emphasis is placed on the position of the ankles.Extensive experiments validate the effectiveness and efficiency of the proposed system in ensuring the safety and reliability of electric power training.

Unveiling health rights:A call to action for sex workers'HIV care in the Philippines

We are writing in response to the article titled“Addressing the needs and rights of sex workers for HIV healthcare services in the Philippines”[1].The article calls for attention on the significant challenges faced by sex workers in the Philippines in accessing HIV healthcare.We appreciate the article’s effort to examine these issues in depth.We would like to present a constant flow of thoughts in this letter while highlighting the positive aspects,potential obstacles,and additional points that contribute to this ongoing discussion.

Mass Increase with Strong and Gravitational Potentials, and Mass Defect with Electromagnetic Potential

The proposal is “mass increases due to strong and gravitational potentials, while it decreases due to Electromagnetic potential”. This proposal explains the big difference in mass between hadrons (protons, neutrons, & mesons) and their components (quarks), mass difference between nucleus and its individual components (protons and neutrons), massless of gamma photons, abnormal masses of mesons and bosons, and the excess in galaxy masses (dark matter). Also, this proposal shows the exact relation between mass and energy: Strong Potential=−3.04mc2| Electric Potential |=−5.57×10−3mc2Gravitational Potential=−1.22×10−7mc2where m represents the excess in mass due to strong potential, or gravitational potential and represents the decrease in mass due to electromagnetic potential. Released energy here equals potential energy and doesn’t equal decrease in mass using the formula E = mc2. Released energy is transferred to heat, photons, kinetic energy… Finally, proposal will try to describe the relation between photon energy and mass of its components using the general equation of kinetic energy: Photon Energy=1/2mc2m is the sum of the individual masses of its components, while the total mass of photon is zero.

Impact of Action Observation Therapy along with Usual Physiotherapy Intervention of Individual with Alzheimer’s Disease

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by cognitive impairments in the initial stage, which lead to severe cognitive dysfunction in the later stage. Action observation therapy (AOT) is a multisensory cognitive rehabilitation technique where the patient initially observes the actions and then tries to perform. The study aimed to examine the impact of AOT along with usual physiotherapy interventions to reduce depression, improve cognition and balance of a patient with AD. A 67 years old patient with AD was selected for this study because the patient has been suffering from depression, dementia, and physical dysfunction along with some other health conditions like diabetes and hypertension. Before starting intervention, a baseline assessment was done through the Beck Depression Inventory (BDI) tool, the Mini-Cog Scale, and the Berg Balance Scale (BBS). The patient received 12 sessions of AOT along with usual physiotherapy interventions thrice a week for four weeks, which included 45 minutes of each session. After four weeks of intervention, the patient demonstrated significant improvement in depression, cognition, and balance, whereas the BDI score declined from moderate 21/63 to mild 15/63 level of depression. The Mini-Cog score improved from 2/5 to 4/5, and the BBS score increased from 18/56 to 37/56. It is concluded that AOT along with usual physiotherapy intervention helps to reduce depression, improve cognition and balance of people with AD.

Median Nerve Somatosensory Evoked Potentials in Patients with Chiari Malformation

Abnormal SEP reflects dysfunction of the medial lemniscus and posterior cervical cord. These structures are likely to be affected in Chiari malformation. Therefore, SEP abnormalities may provide valuable information in patients with CM. However, the consistency of SEP abnormality or normality with the damage is a matter of research. Knowing whether median nerve somatosensory evoked potential (SEP) is useful in revealing subclinical damage in patients with Chiari malformation is important in the treatment and follow-up plan of the disease. The aim of this study was to investigate the relationship between median nerve SEP values and the severity of cerebellar ectopia in patients with Chiari type 1 malformation. Median nerve SEP values were obtained from 30 healthy individuals and 146 individuals with Chiari malformation. The cerebellar ectopia degree and McRae line length were measured. SEP values were not significantly different between groups. The McRae line was found to be significantly shorter in the control group than in the Chiari malformation group (p = 0.031). There was no correlation between the degree of cerebellar ectopia and the length of the McRae line (r = 0.002, p = 0.979). Neither cerebellar ectopy degree nor McRae line length had a relationship with SEP values (r = -0.153, p = 0.066;r = -0.056, p = 0.500, respectively). There was no difference in cerebellar ectopy degree or SEP values between the groups with cerebellar ectopy with and without a syrinx (p = 0.899;p = 0.080, respectively). Likewise, McRae line length was not found to be related to the presence of a syrinx (p = 0.139). Median nerve SEP examination was not beneficial for diagnosing asymptomatic-oligosymptomatic Chiari malformation as a subclinical injury, whether accompanied by syringomyelia or not.

BCCLR:A Skeleton-Based Action Recognition with Graph Convolutional Network Combining Behavior Dependence and Context Clues

In recent years,skeleton-based action recognition has made great achievements in Computer Vision.A graph convolutional network(GCN)is effective for action recognition,modelling the human skeleton as a spatio-temporal graph.Most GCNs define the graph topology by physical relations of the human joints.However,this predefined graph ignores the spatial relationship between non-adjacent joint pairs in special actions and the behavior dependence between joint pairs,resulting in a low recognition rate for specific actions with implicit correlation between joint pairs.In addition,existing methods ignore the trend correlation between adjacent frames within an action and context clues,leading to erroneous action recognition with similar poses.Therefore,this study proposes a learnable GCN based on behavior dependence,which considers implicit joint correlation by constructing a dynamic learnable graph with extraction of specific behavior dependence of joint pairs.By using the weight relationship between the joint pairs,an adaptive model is constructed.It also designs a self-attention module to obtain their inter-frame topological relationship for exploring the context of actions.Combining the shared topology and the multi-head self-attention map,the module obtains the context-based clue topology to update the dynamic graph convolution,achieving accurate recognition of different actions with similar poses.Detailed experiments on public datasets demonstrate that the proposed method achieves better results and realizes higher quality representation of actions under various evaluation protocols compared to state-of-the-art methods.

General Optimal Trajectory Planning:Enabling Autonomous Vehicles with the Principle of Least Action

This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and efficiently.Firstly,we employ the fifth-order Bezier curve to generate and smooth the reference path along the road centerline.Cartesian coordinates are then transformed to achieve the curvature continuity of the generated curve.Considering the road constraints and vehicle dynamics,limited polynomial candidate trajectories are generated and smoothed in a curvilinear coordinate system.Furthermore,in selecting the optimal trajectory,we develop a unified and auto-tune objective function based on the principle of least action by employing AVs to simulate drivers’behavior and summarizing their manipulation characteristics of“seeking benefits and avoiding losses.”Finally,by integrating the idea of receding-horizon optimization,the proposed framework is achieved by considering dynamic multi-performance objectives and selecting trajectories that satisfy feasibility,optimality,and adaptability.Extensive simulations and experiments are performed,and the results demonstrate the framework’s feasibility and effectiveness,which avoids both dynamic and static obstacles and applies to various scenarios with multi-source interactive traffic participants.Moreover,we prove that the proposed method can guarantee real-time planning and safety requirements compared to drivers’manipulation.

HgaNets:Fusion of Visual Data and Skeletal Heatmap for Human Gesture Action Recognition

Recognition of human gesture actions is a challenging issue due to the complex patterns in both visual andskeletal features. Existing gesture action recognition (GAR) methods typically analyze visual and skeletal data,failing to meet the demands of various scenarios. Furthermore, multi-modal approaches lack the versatility toefficiently process both uniformand disparate input patterns.Thus, in this paper, an attention-enhanced pseudo-3Dresidual model is proposed to address the GAR problem, called HgaNets. This model comprises two independentcomponents designed formodeling visual RGB (red, green and blue) images and 3Dskeletal heatmaps, respectively.More specifically, each component consists of two main parts: 1) a multi-dimensional attention module forcapturing important spatial, temporal and feature information in human gestures;2) a spatiotemporal convolutionmodule that utilizes pseudo-3D residual convolution to characterize spatiotemporal features of gestures. Then,the output weights of the two components are fused to generate the recognition results. Finally, we conductedexperiments on four datasets to assess the efficiency of the proposed model. The results show that the accuracy onfour datasets reaches 85.40%, 91.91%, 94.70%, and 95.30%, respectively, as well as the inference time is 0.54 s andthe parameters is 2.74M. These findings highlight that the proposed model outperforms other existing approachesin terms of recognition accuracy.

Thermal conductivity of GeTe crystals based on machine learning potentials

GeTe has attracted extensive research interest for thermoelectric applications.In this paper,we first train a neuroevolution potential(NEP)based on a dataset constructed by ab initio molecular dynamics,with the Gaussian approximation potential(GAP)as a reference.The phonon density of states is then calculated by two machine learning potentials and compared with density functional theory results,with the GAP potential having higher accuracy.Next,the thermal conductivity of a GeTe crystal at 300 K is calculated by the equilibrium molecular dynamics method using both machine learning potentials,and both of them are in good agreement with the experimental results;however,the calculation speed when using the NEP potential is about 500 times faster than when using the GAP potential.Finally,the lattice thermal conductivity in the range of 300 K-600 K is calculated using the NEP potential.The lattice thermal conductivity decreases as the temperature increases due to the phonon anharmonic effect.This study provides a theoretical tool for the study of the thermal conductivity of GeTe.

Adjustment mechanism of blasting dynamic-static action in the water decoupling charge

Water decoupling charge blasting excels in rock breaking,relying on its uniform pressure transmission and low energy dissipation.The water decoupling coefficients can adjust the contributions of the stress wave and quasi-static pressure.However,the quantitative relationship between the two contributions is unclear,and it is difficult to provide reasonable theoretical support for the design of water decoupling blasting.In this study,a theoretical model of blasting fracturing partitioning is established.The mechanical mechanism and determination method of the optimal decoupling coefficient are obtained.The reliability is verified through model experiments and a field test.The results show that with the increasing of decoupling coefficient,the rock breaking ability of blasting dynamic action decreases,while quasi-static action increases and then decreases.The ability of quasi-static action to wedge into cracks changes due to the spatial adjustment of the blast hole and crushed zone.The quasi-static action plays a leading role in the fracturing range,determining an optimal decoupling coefficient.The optimal water decoupling coefficient is not a fixed value,which can be obtained by the proposed theoretical model.Compared with the theoretical results,the maximum error in the model experiment results is 8.03%,and the error in the field test result is 3.04%.

Deciphering the linear relationship in the activity of the oxygen reduction reaction on Pt electrodes:A decisive role of adsorbates

Despite substantial efforts in developing high-performance catalysts for the oxygen reduction reaction(ORR),the persistent challenge lies in the high onset overpotential of the ORR,and the effect of the elec-trolyte solution cannot be ignored.Consequently,we have systematically investigated the impact of adsorbate species and concentration,as well as solution pH,on the ORR activity on Pt(111)and Pt(poly)electrodes.The results all tend to establish a linear quantitative relationship between the onset potential for ORR and the adsorption equilibrium potential of the adsorbate.This finding indicates the decisive role of adsorbates in the onset potential for ORR,suggesting that the adsorption potential of adsorbates can serve as an intuitive criterion for ORR activity.Additional support for this conclusion is derived from experimental results obtained from the oxygen evolution reaction on Pt(poly)with different adsorbate species and from the hydrogen evolution reaction on Pt(111)with iodine adsorption.We further propose both an empirical equation for the onset potential for ORR and the concept of a potential-regulated adsor-bate shielding effect to elucidate the influence of adsorbates on ORR activity.This study provides new insights into the high onset overpotential of the ORR and offers potential strategies for predicting and enhancingORRactivity inthefuture.

Experimental study on the movement of oil spill under freeze-thaw action

Oil leakages cause environmental pollution,economic losses,and even engineering safety accidents.In cold regions,researchers urgently investigate the movement of oil spill in soils exposed to freeze-thaw cycles.In this study,a series of laboratory model experiments were carried out on the migration of oil leakage under freeze-thaw action,and the distributions of the soil temperature,unfrozen water content,and displacement were analyzed.The results showed that under freeze-thaw action,liquid water in soils migrated to the freezing front and accumulated.After the pipe cracked,oil pollutants first gathered at one side of the leak hole,and then moved around.The pipe wall temperature affected the soil temperature field,and the thermal influence range below and transverse the pipe wall(35–40 cm)was larger than that above the pipe wall(8 cm)owing to the soil surface temperature.The leaked oil's temperature would make the temperature of the surrounding soil rise.Oil would inhibit the cooling of the soils.Besides,oil migration was significantly affected by the gravity and water flow patterns.The freeze-thaw action would affect the migration of the oil,which was mainly manifested as inhibiting the diffusion and movement of oil when soils were frozen.Unfrozen water transport caused by freeze-thaw cycles would also inhibit oil migration.The research results would provide a scientific reference for understanding the relationship between the movement of oil pollutants,water,and soil temperature,and for establishing a waterheat-mass transport model in frozen soils.

Research Progress on Purification Process, Content Determination and Pharmacological Action of Atractylodin

Atractylodis Rhizoma comes from the dry rhizome of Atractylis lancea or Atractylodes chinensis in the Compositae family,and it is suitable for preventing and treating diseases such as cold,edema,night blindness and rheumatic arthralgia.Atractylodin is the main active component extracted and isolated from Atractylodis Rhizoma.A large number of studies have found that atractylodin has excellent drug activity in improving gastrointestinal emptying,anti-inflammation,inhibiting malignant tumor and reducing blood lipid.In this paper,the purification process and pharmacological activity of Atractylodin were summarized to provide a theoretical basis for basic research,clinical application and further development and utilization of atractylodin.

Clinical characteristics and analysis of vestibular-evoked myogenic potentials in patients with sudden sensorineural hearing loss in different ages

BACKGROUND Numerous studies have found that patients experiencing sudden sensorineural hearing loss(SSHL),with or without accompanying vertigo,often show impaired vestibular function.However,there is a dearth of studies analyzing vestibularevoked myogenic potentials(VEMPs)in SSHL patients across various age groups.AIM To investigate vestibular condition in SSHL patients across various age demographics.METHODS Clinical data of 84 SSHL patients were investigated retrospectively.Audiometry,cervical vestibular evoked myogenic potentials(c-VEMPs),and ocular vestibular evoked myogenic potentials(o-VEMPs)were conducted on these patients.Parameters assessed included the latencies of P1 and N1 waves,as well as the amplitudes of P1–N1 waves.Moreover,the study evaluated the influence of factors such as sex,affected side,configuration of hearing loss,and presence of accompanying vertigo.RESULTS Among the 84 SSHL patients,no significant differences were observed among the three groups in terms of gender,affected side,and the presence or absence of vertigo.Group II(aged 41–60 years)had the highest number of SSHL cases.The rates of absent o-VEMPs in the affected ears were 20.83%,31.58%,and 22.72%for the three age groups,respectively,with no statistically significant difference among them.The rates of absent c-VEMPs in the affected ears were 8.3%,34.21%,and 18.18%for the three age groups,respectively,with significant differences.In the unaffected ears,there were differences observed in the extraction rates of o-VEMPs in the unaffected ears among the age groups.In the three age groups,no significant differences were noted in the three age groups in the latencies of P1 and N1 waves or in the amplitude of N1–P1 waves for c-VEMPs and o-VEMPs,either on the affected side or on the unaffected side,across the three age groups.CONCLUSION The extraction rate of VEMPs is more valuable than parameters.Regardless of the presence of vertigo,vestibular organs are involved in SSHL.Notably,SSHL patients aged 41–60 appear more susceptible to damage to the inferior vestibular nerve and saccule.

Tetrathiafulvalene esters with high redox potentials and improved solubilities for non-aqueous redox flow battery applications

The exploitation of high performance redox-active substances is critically important for the development of non-aqueous redoxflow batteries.Herein,three tetrathiofulvalene(TTF)derivatives with different substitution groups,namely TTF diethyl ester(TTFDE),TTF tetramethyl ester(TTFTM),and TTF tetraethyl ester(TTFTE),are prepared and their energy storage properties are evaluated.It has been found that the redox potential and solubility of these TTF derivatives in conventional carbonate electrolytes increases with the number of ester groups.The battery with a catholyte of 0.2 mol L^(-1) of TTFTE delivers a specific capacity of more than 10 Ah L^(-1) at the current density of 0.5 C with two discharge voltage platforms locating at as high as 3.85 and 3.60 V vs.Li/Liþ.Its capacity retention can be improved from 2.34 Ah L^(-1) to 3.60 Ah L^(-1) after 100 cycles by the use of an anion exchange membrane to block the crossover of TTF species.The excellent cycling stability of the TIF esters is supported by their well-delocalized electrons,as revealed by the density function theory calculations.Therefore,the introduction of more and larger electron-withdrawing groups is a promising strategy to simultaneously increase the redox-potential and solubility of redox-active ma-terials for non-aqueous redoxflow batteries.

Study on the Mechanism of Action of Glyasperin A in the Treatment of Atherosclerosis Based on Network Pharmacology and Molecular Docking

[Objectives] This study was conducted to investigate the mechanism of action of glyasperin A in the treatment of atherosclerosis using a network pharmacology approach. [Methods] Targets related to atherosclerosis were searched in GeneCards database. An active ingredient-disease-target network was constructed by Cytoscape 3.7.1. A target protein interaction network was constructed by String database. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the DAVID database. [Results] Glyasperin A acted on 36 atherosclerosis-related targets, and the biofunctional and pathway enrichment analyses showed that it was mainly involved in response to xenobiotic stimulus, drug transport across blood-brain barrier, lipid oxidation, barrier, and lipid oxidation, etc. The results showed that glyasperin A acted on 36 atherosclerosis-related targets. The biofunctional and pathway enrichment analyses showed that it was mainly involved in response to xenobiotic stimulus, drug transport across blood-brain barrier, lipid oxidation, positive regulation of protein localization to nucleus, and hepoxilin biosynthetic process, and it played an anti-fatigue role through signal pathways such as serotonergic synapse, efferocytosis, arachidonic acid metabolism, chemical carcinogenesis-receptor activation and platelet activation. [Conclusions] Glyasperin A has multi-target and multi-pathway effects in the treatment of atherosclerosis. This study provides reference for further research on glyasperin A in the treatment of atherosclerosis.