Fusion of Convolutional Self-Attention and Cross-Dimensional Feature Transformationfor Human Posture Estimation

Human posture estimation is a prominent research topic in the fields of human-com-puter interaction,motion recognition,and other intelligent applications.However,achieving highaccuracy in key point localization,which is crucial for intelligent applications,contradicts the lowdetection accuracy of human posture detection models in practical scenarios.To address this issue,a human pose estimation network called AT-HRNet has been proposed,which combines convolu-tional self-attention and cross-dimensional feature transformation.AT-HRNet captures significantfeature information from various regions in an adaptive manner,aggregating them through convolu-tional operations within the local receptive domain.The residual structures TripNeck and Trip-Block of the high-resolution network are designed to further refine the key point locations,wherethe attention weight is adjusted by a cross-dimensional interaction to obtain more features.To vali-date the effectiveness of this network,AT-HRNet was evaluated using the COCO2017 dataset.Theresults show that AT-HRNet outperforms HRNet by improving 3.2%in mAP,4.0%in AP75,and3.9%in AP^(M).This suggests that AT-HRNet can offer more beneficial solutions for human posture estimation.

Risk identification and safety assessment of human-computer interaction in integrated avionics based on STAMP

To solve the problem of risk identification and quantitative assessment for human-computer interaction(HCI)in complex avionics systems,an HCI safety analysis framework based on system-theoretical process analysis(STPA)and cognitive reliability and error analysis method(CREAM)is proposed.STPACREAM can identify unsafe control actions and find the causal path during the interaction of avionics systems and pilot with the help of formal verification tools automatically.The common performance conditions(CPC)of avionics systems in the aviation environment is established and a quantitative analysis of human failure is carried out.Taking the head-up display(HUD)system interaction process as an example,a case analysis is carried out,the layered safety control structure and formal model of the HUD interaction process are established.For the interactive behavior“Pilots approaching with HUD”,four unsafe control actions and35 causal scenarios are identified and the impact of common performance conditions at different levels on the pilot decision model are analyzed.The results show that HUD's HCI level gradually improves as the scores of CPC increase,and the quality of crew member cooperation and time sufficiency of the task is the key to its HCI.Through case analysis,it is shown that STPACREAM can quantitatively assess the hazards in HCI and identify the key factors that impact safety.

Identification and distribution of 13003 landslides in the northwest margin of Qinghai-Tibet Plateau based on human-computer interaction remote sensing interpretation

The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remains insufficiently explored concerning landslide occurrence and dispersion.With the planning and construction of the Xinjiang-Tibet Railway,a comprehensive investigation into disastrous landslides in this area is essential for effective disaster preparedness and mitigation strategies.By using the human-computer interaction interpretation approach,the authors established a landslide database encompassing 13003 landslides,collectively spanning an area of 3351.24 km^(2)(36°N-40°N,73°E-78°E).The database incorporates diverse topographical and environmental parameters,including regional elevation,slope angle,slope aspect,distance to faults,distance to roads,distance to rivers,annual precipitation,and stratum.The statistical characteristics of number and area of landslides,landslide number density(LND),and landslide area percentage(LAP)are analyzed.The authors found that a predominant concentration of landslide origins within high slope angle regions,with the highest incidence observed in intervals characterised by average slopes of 20°to 30°,maximum slope angle above 80°,along with orientations towards the north(N),northeast(NE),and southwest(SW).Additionally,elevations above 4.5 km,distance to rivers below 1 km,rainfall between 20-30 mm and 30-40 mm emerge as particularly susceptible to landslide development.The study area’s geological composition primarily comprises Mesozoic and Upper Paleozoic outcrops.Both fault and human engineering activities have different degrees of influence on landslide development.Furthermore,the significance of the landslide database,the relationship between landslide distribution and environmental factors,and the geometric and morphological characteristics of landslides are discussed.The landslide H/L ratios in the study area are mainly concentrated between 0.4 and 0.64.It means the landslides mobility in the region is relatively low,and the authors speculate that landslides in this region more possibly triggered by earthquakes or located in meizoseismal area.

Implementation of Level-3 Autonomous Patient-Specific Quality Assurance with Automated Human Interactive Devices

Purpose: Patient-specific quality assurance (PSQA) requires manual operation of different workstations, which is time-consuming and error-prone. Therefore, developing automated solutions to improve efficiency and accuracy is a priority. The purpose of this study was to develop a general software interface with scripting on a human interactive device (HID) for improving the efficiency and accuracy of manual quality assurance (QA) procedures. Methods: As an initial application, we aimed to automate our PSQA workflow that involves Varian Eclipse treatment planning system, Elekta MOSAIQ oncology information system and PTW Verisoft application. A general platform, the AutoFrame interface with two imbedded subsystems—the AutoFlow and the PyFlow, was developed with a scripting language for automating human operations of aforementioned systems. The interface included three functional modules: GUI module, UDF script interpreter and TCP/IP communication module. All workstations in the PSQA process were connected, and most manual operations were automated by AutoFrame sequentially or in parallel. Results: More than 20 PSQA tasks were performed both manually and using the developed AutoFrame interface. On average, 175 (±12) manual operations of the PSQA procedure were eliminated and performed by the automated process. The time to complete a PSQA task was 8.23 (±0.78) minutes for the automated workflow, in comparison to 13.91 (±3.01) minutes needed for manual operations. Conclusion: We have developed the AutoFrame interface framework that successfully automated our PSQA procedure, and significantly reduced the time, human (control/clicking/typing) errors, and operators’ stress. Future work will focus on improving the system’s flexibility and stability and extending its operations to other QA procedures.

Effect of a Thermal Spring Water on Carbohydrate-Protein Interactions in In-Vitro Models Implicating Normal Human Keratinocytes and Recombinant Lectins

Background: Sugar moiety of macromolecules is today very well known for its implications in many biological recognition mechanisms including cell-cell, extracellular matrix-cell and/or bacteria-cell interactions. In this context lectins, which are carbohydrate-binding proteins displaying a high affinity for sugar groups of other molecules, are of a great importance, notably in immune response involving bacteria, viruses and fungi. As protein-carbohydrate interactions are often mediated by ions such as calcium, zinc or magnesium, we were prompted to study the effect of a thermal spring water (which contains this type of component) on interactions existing between: 1) osidic receptors of human normal keratinocytes and 2) two lectins greatly implicated in the immune response mechanisms (i.e. the dectin-1 and the langerin), and their ligands. Materials and Methods: In a first series of experiments, we studied the effect of increasing concentrations of a thermal spring water on interactions existing between glycosylated molecules and the osidic receptors expressed at the normal human keratinocytes surface. In a second step, and in order to better understand the putative effect of our thermal spring water on the immune response, we analyzed its effect on the interactions existing between the dectin-1 (implicated in the recognition of bacteria, viruses and fungi) and the langerin (expressed by Langerhans cells, the immune cells of the cutaneous tissue), and their ligands in a model using recombinant human lectins and appropriate binding molecules. Results: We showed here that our thermal spring water was able to reinforce interactions between keratinocytes osidic receptors and some of their ligands, in a dose-related manner: From 8% to 55% of increase with 10% to 30% (v/v) of thermal spring water. In the second part of our studies, we also showed that our thermal spring water was able to modulate interactions between dectin-1 and langerin and their ligands through a biphasic effect: Interactions were enhanced by more than 40% and 20% respectively with 10% of thermal spring water, and return to their basal level or lower for higher concentrations. Conclusion: The tested thermal spring water, probably due to its ionic composition, could significantly affect interactions of osidic receptors with their ligands. This property could be of a great interest to help immune system to maintain an appropriate “vigilance state” by using the thermal water at up to a concentration of 10%, and by avoiding any runaway reaction in case of aggression, by using concentrations higher than 10%. .

ZnO/Ecoflex自驱动柔性压电传感器及其人体姿态监测微系统设计

压力传感器是可穿戴电子设备的重要组成部分,但在能量供应、灵活性和皮肤适应性方面仍存在各种问题。研制了一种主要由ZnO/Ecoflex复合薄膜构成的自驱动柔性压力传感器,并构建了人体姿态监测系统,可用于动态监测人体姿态信号和其他运动参数。在外部压力应力的作用下,所制备的传感器表现出优异的灵敏度(0.068 V/N)、良好的线性度(约0.98)、宽的测量范围(5~80 N)以及卓越的耐久性(超过10000次循环)。此外,基于制备的传感器设计了硬件电路,建立了人机交互测试系统,实现了对人体姿态信号的远程传输功能。因此,这项工作不仅开发了一种新型的无铅化自驱动压力传感器,还设计了人体姿态监测微系统,为信号处理和智能传感提供了新思路,在医学研究、个性化识别和人机交互方面具有重要的应用潜力。

Modulatory role of plant-derived metabolites on host-microbiota interactions:personalized therapeutics outlook

A diverse array of microbes in and on the human body constitute the microbiota.These micro-residents continuously interact with the human host through the language of metabolites to dictate the host’s physiology in health and illnesses.Any biotic and abiotic component ensuring a balanced host-microbiota interaction are potential microbiome therapeutic agents to overcome human diseases.Plant metabolites are continually being used to treat various illnesses.These metabolites target the host’s metabolic machinery and host-gut microbiota interactions to overcome human diseases.Despite the paramount therapeutic significance of the factors affecting host-microbiota interactions,a comprehensive overview of the modulatory role of plant-derived metabolites in host-microbiota interactions is lacking.The current review puts an effort into comprehending the role of medicinal plants in gut microbiota modulation to mitigate various human illnesses.It would develop a holistic understanding of hostmicrobiota interactions and the role of effectors in health and diseases.

Human Interaction Recognition in Surveillance Videos Using Hybrid Deep Learning and Machine Learning Models

Human Interaction Recognition(HIR)was one of the challenging issues in computer vision research due to the involvement of multiple individuals and their mutual interactions within video frames generated from their movements.HIR requires more sophisticated analysis than Human Action Recognition(HAR)since HAR focuses solely on individual activities like walking or running,while HIR involves the interactions between people.This research aims to develop a robust system for recognizing five common human interactions,such as hugging,kicking,pushing,pointing,and no interaction,from video sequences using multiple cameras.In this study,a hybrid Deep Learning(DL)and Machine Learning(ML)model was employed to improve classification accuracy and generalizability.The dataset was collected in an indoor environment with four-channel cameras capturing the five types of interactions among 13 participants.The data was processed using a DL model with a fine-tuned ResNet(Residual Networks)architecture based on 2D Convolutional Neural Network(CNN)layers for feature extraction.Subsequently,machine learning models were trained and utilized for interaction classification using six commonly used ML algorithms,including SVM,KNN,RF,DT,NB,and XGBoost.The results demonstrate a high accuracy of 95.45%in classifying human interactions.The hybrid approach enabled effective learning,resulting in highly accurate performance across different interaction types.Future work will explore more complex scenarios involving multiple individuals based on the application of this architecture.

Home-based Detection and Prediction of Diabetic Foot Ulcers at Early Stage Using Sensor Technology and Supervised Learning

For years,foot ulcers linked with diabetes mellitus and neuropathy have significantly impacted diabetic patients’ health-related quality of life(HRQoL). Diabetes foot ulcers impact15% of all diabetic patients at some point in their lives. The facilities and resources used for DFU detection and treatment are only available at hospitals and clinics,which results in the unavailability of feasible and timely detection at an early stage. This necessitates the development of an at-home DFU detection system that enables timely predictions and seamless communication with users,thereby preventing amputations due to neglect and severity. This paper proposes a feasible system consisting of three major modules:an IoT device that works to sense foot nodes to send vibrations onto a foot sole,a machine learning model based on supervised learning which predicts the level of severity of the DFU using four different classification techniques including XGBoost,K-SVM,Random Forest,and Decision tree,and a mobile application that acts as an interface between the sensors and the patient. Based on the severity levels,necessary steps for prevention,treatment,and medications are recommended via the application.

Temporal and spatial variations hydrochemical components and driving factors in Baiyangdian Lake in the Northern Plain of China

Understanding the temporal and spatial variation of hydrochemical components in large freshwater lakes is crucial for effective management and conversation.In this study,we identify the temporalspatial characteristics and driving factors of the hydrochemical components in Baiyangdian Lake using geochemical methods(Gibbs diagram,Piper diagram and End-element diagram of ion ratio)and multivariate statistical techniques(Principal component analysis and Correlation analysis).16 sets of samples were collected from Baiyangdian Lake in May(normal season),July(flood season),and December(dry season)of 2022.Results indicate significant spatial variation in Nat,ci,SO and NO,,suggesting a strong influence of human activities.Cation concentrations exhibit greater seasonal variation in the dry season compared to the flood season,while the concentrations of the four anions show inconsistent seasonal changes due to the combined effects of river water chemical composition and human activities.The hydrochemical type of Baiyangdian Lake is primarily HCO,Cl-Na.Ca,Mg*and HCO,originate mainly from silicate and carbonate rock dissolution,while Kt,Nat and CI originate mainly from sewage and salt dissolution in sediments.SO42 may mainly stem from industrial wastewater,while NO,primarily originates from animal feces and domestic sewage.Through the use of Principal Component Analysis,it is identified that water-rock interaction(silicate and carbonate rocks dissolution,and dissolution of salt in sediments),carbonate sedimentation,sewage,agricultural fertilizer and manure,and nitrification are the main driving factors of the variation of hydrochemical components of Baiyangdian Lake across three hydrological seasons.These findings suggest the need for effective control of substandard domestic sewage discharge,optimization of agricultural fertilization strategies,and proper management of animal manure to comprehensively improve the water environment in Baiyangdian Lake.

Design and Implementation of the Image Interactive System Based on Human-Computer Interaction

Based on the traditional Human-Computer Interaction method which is mainly touch input system, the way of capturing the movement of people by using cameras is proposed. This is a convenient technique which can provide users more experience. In the article, a new way of detecting moving things is given on the basis of development of the image processing technique. The system architecture decides that the communication should be used between two different applications. After considered, named pipe is selected from many ways of communication to make sure that video is keeping in step with the movement from the analysis of the people moving. According to a large amount of data and principal knowledge, thinking of the need of actual project, a detailed system design and realization is finished. The system consists of three important modules: detecting of the people's movement, information transition between applications and video showing in step with people's movement. The article introduces the idea of each module and technique.

A Survey of Gesture Recognition Using Frequency Modulated Continuous Wave Radar

With technology advances and human requirements increasing, human-computer interaction plays an important role in our daily lives. Among these interactions, gesture-based recognition offers a natural and intuitive user experience that does not require physical contact and is becoming increasingly prevalent across various fields. Gesture recognition systems based on Frequency Modulated Continuous Wave (FMCW) millimeter-wave radar are receiving widespread attention due to their ability to operate without wearable sensors, their robustness to environmental factors, and the excellent penetrative ability of radar signals. This paper first reviews the current main gesture recognition applications. Subsequently, we introduce the system of gesture recognition based on FMCW radar and provide a general framework for gesture recognition, including gesture data acquisition, data preprocessing, and classification methods. We then discuss typical applications of gesture recognition systems and summarize the performance of these systems in terms of experimental environment, signal acquisition, signal processing, and classification methods. Specifically, we focus our study on four typical gesture recognition systems, including air-writing recognition, gesture command recognition, sign language recognition, and text input recognition. Finally, this paper addresses the challenges and unresolved problems in FMCW radar-based gesture recognition and provides insights into potential future research directions.

Gesture Recognition Based on Time-of-Flight Sensor and Residual Neural Network

With the advancement of technology and the increase in user demands, gesture recognition played a pivotal role in the field of human-computer interaction. Among various sensing devices, Time-of-Flight (ToF) sensors were widely applied due to their low cost. This paper explored the implementation of a human hand posture recognition system using ToF sensors and residual neural networks. Firstly, this paper reviewed the typical applications of human hand recognition. Secondly, this paper designed a hand gesture recognition system using a ToF sensor VL53L5. Subsequently, data preprocessing was conducted, followed by training the constructed residual neural network. Then, the recognition results were analyzed, indicating that gesture recognition based on the residual neural network achieved an accuracy of 98.5% in a 5-class classification scenario. Finally, the paper discussed existing issues and future research directions.

APPLICATION OF HUMAN COGNITIVE MODEL FOR TIME DEPENDENT OPERATOR BEHAVIOR IN CHINESE NPP

This paper discusses some issues on human reliability model of time dependent human behavior. Some results of the crew reliability experiment on Tsinghua training simulator in China are given, Meanwhile, a case of calculation for human error probability during anticipated transient without scram (ATWS) based on the data drew from the recent experiment is offered.

Robotic Etiquette:Socially Acceptable Navigation of Service Robots with Human Motion Pattern Learning and Prediction

Nonverbal and noncontact behaviors play a significant role in allowing service robots to structure their interactions withhumans.In this paper, a novel human-mimic mechanism of robot’s navigational skills was proposed for developing sociallyacceptable robotic etiquette.Based on the sociological and physiological concerns of interpersonal interactions in movement,several criteria in navigation were represented by constraints and incorporated into a unified probabilistic cost grid for safemotion planning and control, followed by an emphasis on the prediction of the human’s movement for adjusting the robot’spre-collision navigational strategy.The human motion prediction utilizes a clustering-based algorithm for modeling humans’indoor motion patterns as well as the combination of the long-term and short-term tendency prediction that takes into accountthe uncertainties of both velocity and heading direction.Both simulation and real-world experiments verified the effectivenessand reliability of the method to ensure human’s safety and comfort in navigation.A statistical user trials study was also given tovalidate the users’favorable views of the human-friendly navigational behavior.

Fabrication of an electrochemical sensor for determination of doxorubicin in human plasma and its interaction with DNA

In this work, an electrochemical sensor was fabricated for determination of an anthracycline, doxorubicin(DOX) as a chemotherapy drug in plasma based on multi-walled carbon nanotubes modified platinum electrode(Pt/MWCNTs). DOX was effectively accumulated on the surface of modified electrode and generated a pair of redox peaks at around 0.522 and 0.647 V(vs. Ag/Ag Cl) in Britton Robinson(B-R) buffer(p H 4.0, 0.1 M). The electrochemical parameters including p H, type of buffer, accumulation time, amount of modifier and scan rate were optimized. Under the optimized conditions, there was a linear correlation between cathodic peak current and concentration of DOX in the range of 0.05–4.0 μg/m L with the detection limit of 0.002 μg/m L. The number of electron transfers(n) and electron transfer-coefficient(α) were estimated as 2.0 and 0.25, respectively. The constructed sensor displayed excellent precision, sensitivity, repeatability and selectivity in the determination of DOX in plasma. Moreover, cyclic voltammetry studies of DOX in the presence of DNA showed an intercalation mechanism with binding constant(K_b) of 1.12×10~5L/mol.

Structural analysis of tumor-relatedsingle amino acid mutations in human MxA protein

Background:Human myxovirus resistant protein A(MxA),encoded by the myxovirus resistance 1(Mx1) gene,is an interferon(IFN)-triggered dynamin-like multi-domain GTPase involved in innate immune responses against viral infections.Recent studies suggest that MxA is associated with several human cancers and may be a tumor suppressor and a promising biomarker for IFN therapy.Mxl gene mutations in the coding region for MxA have been discovered in many types of cancer,suggesting potential biological associations between mutations in MxA protein and corresponding cancers.In this study,we performed a systematic analysis based on the crystal structures of MxA and elucidated how these mutations specifically affect the structure and therefore the function of MxA protein.Methods:Cancer-associated Mxl mutations were collected and screened from the COSMIC database.Twenty-two unique mutations that cause single amino acid alterations in the MxA protein were chosen for the analysis.Amino acid sequence alignment was performed using Clustal W to check the conservation level of mutation sites in Mx proteins and dynamins.Structural analysis of the mutants was carried out with Coot.Structural models of selected mutants were generated by the SWISS-MODEL server for comparison with the corresponding non-mutated structures.All structural figures were generated using PyMOL.Results:We analyzed the conservation level of the single-point mutation sites and mapped them on different domains of MxA.Through individual structural analysis,we found that some mutations severely affect the stability and function of MxA either by disrupting the intraVinter-molecular interactions supported by the original residues or by incurring unfavorable configuration alterations,whereas other mutations lead to gentle or no interference to the protein stability and function because of positions or polarity features.The potential clinical value of the mutations that lead to drastic influence on MxA protein is also assessed.Conclusions:Among all of the reported tumor-associated single-point mutations,seven of them notably affect the structure and function of MxA and therefore deserve more attention with respect to potential clinical applications.Our research provides an example for systematic analysis and consequence evaluation of single-point mutations on a given cancer-related protein.

Identification of microRNAs and messenger RNAs involved in human umbilical cord mesenchymal stem cell treatment of ischemic cerebral infarction using integrated bioinformatics analysis

In recent years,a large number of differentially expressed genes have been identified in human umbilical cord mesenchymal stem cell(hUMSC)transplants for the treatment of ischemic cerebral infarction.These genes are involved in various biochemical processes,but the role of microRNAs(miRNAs)in this process is still unclear.From the Gene Expression Omnibus(GEO)database,we downloaded two microarray datasets for GSE78731(messenger RNA(mRNA)profile)and GSE97532(miRNA profile).The differentially expressed genes screened were compared between the hUMSC group and the middle cerebral artery occlusion group.Gene ontology enrichment and pathway enrichment analyses were subsequently conducted using the online Database for Annotation,Visualization,and Integrated Discovery.Identified genes were applied to perform weighted gene co-suppression analyses,to establish a weighted co-expression network model.Furthermore,the protein-protein interaction network for differentially expressed genes from turquoise modules was built using Cytoscape(version 3.40)and the most highly correlated subnetwork was extracted from the protein-protein interaction network using the MCODE plugin.The predicted target genes for differentially expressed miRNAs were also identified using the online database starBase v3.0.A total of 3698 differentially expressed genes were identified.Gene ontology analysis demonstrated that differentially expressed genes that are related to hUMSC treatment of ischemic cerebral infarction are involved in endocytosis and inflammatory responses.We identified 12 differentially expressed miRNAs in middle cerebral artery occlusion rats after hUMSC treatment,and these differentially expressed miRNAs were mainly involved in signaling in inflammatory pathways,such as in the regulation of neutrophil migration.In conclusion,we have identified a number of differentially expressed genes and differentially expressed mRNAs,miRNA-mRNAs,and signaling pathways involved in the hUMSC treatment of ischemic cerebral infarction.Bioinformatics and interaction analyses can provide novel clues for further research into hUMSC treatment of ischemic cerebral infarction.

BINDING AND INTERACTION OF TRANSCRIPTIONAL REGULATOR HUMAN DAXX WITH ADENOVIRUS12 E1B 55 KILODALTON ONCOPROTEIN

Objective: To study the disruption of co- localization of human Daxx(hDaxx) with promyelocytic leukemia protein(PML) at the PML oncogenic domains (PODs) by the interaction of hDaxx with adenovirus(Ad) 12 E1B 55 Kilodalton Oncoprotein (Ad12 E1B 55kD). Methods: The direct binding reaction of hDaxx and Ad12 E1B 55kD was analyzed by coimmunoprecipitation and Western blotting in vivo or in vitro. The interaction of hDaxx with Ad12 E1B 55kD was studied using yeast two-hybrid assay. Results: hDaxx bounded directly to Ad12 E1B 55kD in vivo and in vitro. hDaxx interacted with full length Ad12 E1B 55kD. Conclusion: Transcriptional regulator hDaxx directly binds to and interacts with Ad12 E1B 55kD.

Inhibition of mouse acrosome reaction and sperm-zona pellucida binding by anti-human sperm membrane protein 1 antibody

Aim： To investigate the possible functions of human sperm membrane protein （hSMP-1） in the process of fertilization. Methods： A 576-bp cDNA fragment of HSD-1 gene coding for the extracellular domain of hSMP-1 was cloned and expressed. The localization of this protein on human and mouse sperm was determined by indirect immunofluorescent staining by using anti-recombinant hSMP-1 （anti-rhSMP-1） antibodies. Sperm acrosome reaction and spermzona pellucida （ZP） binding assay were carried out in 10-week-old BALB/c mice. Results： Recombinant hSMP-1 was successfully cloned and expressed. The expression of the native protein was limited on the acrosome of human and mouse sperm. Treatment of anti-rhSMP-1 antibodies significantly decreased the average number of sperms bound to each egg. Meanwhile, the percentage of acrosome reaction was decreased in comparison to pre-immune control after treatment with anti-rhSMP-1 （P 〈 0.05）. Conclusion： The results suggest that anti-rhSMP-1 antibody inhibited mouse acrosome reaction and sperm-ZP binding.