In the process industry, automation and process control systems are widely implemented, information integration is however far away from satisfactory. It remains a hard job for senior managers to make decisions based ...In the process industry, automation and process control systems are widely implemented, information integration is however far away from satisfactory. It remains a hard job for senior managers to make decisions based on the plant-wide real-time integrated information. This paper proposes a multi-layer information integration platform. In the data integration level, the standard for the exchange of product (STEP) and the extensible markup language (XML) are used to unify these data of the chemical process. In the model integration level, the models are integrated by using the neutral model repository and CAPE-OPEN. In the integration of process task, the common object request broker architecture (CORBA) is used as the communication mediator. The XML is taken as the data standard. A uniform information platform is thus constructed and realized. The proposed information integration platform is satisfactorily implemented to solve the Tennessee Eastman (TE) problem.展开更多
At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-laye...At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-layer multi-pass FRAM-deposited alumin-um alloy samples were successfully prepared using a non-shoulder tool head.The material flow behavior and microstructure of the over-lapped zone between adjacent layers and passes during multi-layer multi-pass FRAM deposition were studied using the hybrid 6061 and 5052 aluminum alloys.The results showed that a mechanical interlocking structure was formed between the adjacent layers and the adja-cent passes in the overlapped center area.Repeated friction and rolling of the tool head led to different degrees of lateral flow and plastic deformation of the materials in the overlapped zone,which made the recrystallization degree in the left and right edge zones of the over-lapped zone the highest,followed by the overlapped center zone and the non-overlapped zone.The tensile strength of the overlapped zone exceeded 90%of that of the single-pass deposition sample.It is proved that although there are uneven grooves on the surface of the over-lapping area during multi-layer and multi-pass deposition,they can be filled by the flow of materials during the deposition of the next lay-er,thus ensuring the dense microstructure and excellent mechanical properties of the overlapping area.The multi-layer multi-pass FRAM deposition overcomes the limitation of deposition width and lays the foundation for the future deposition of large-scale high-performance components.展开更多
Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environ...Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant challenge.To address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data registration.Specifically,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less efficient.Meanwhile,visual texture information complements LiDAR-Visual localization by providing additional contextual details.By incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of localization.This approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.展开更多
Objective: This study evaluates the impact of handshake and information support on patients’ outcomes during laparoscopic cholecystectomy. It examines the effects on their physiological and psychological responses an...Objective: This study evaluates the impact of handshake and information support on patients’ outcomes during laparoscopic cholecystectomy. It examines the effects on their physiological and psychological responses and overall satisfaction with nursing care. Methods: A total of 84 patients scheduled for laparoscopic cholecystectomy were selected through convenient sampling and randomly assigned to either the control group or the intervention group using a random number table. Each group consisted of 42 patients. The control group received standard surgical nursing care. In addition to standard care, the intervention group received handshake and information support from the circulating nurse before anesthesia induction. Vital signs were recorded before surgery and before anesthesia induction. Anxiety levels were measured using the State-Trait Anxiety Inventory (STAI) and the State-Anxiety Inventory (S-AI), while nursing satisfaction was assessed using a numerical rating scale. Results: No significant differences were found between the two groups in systolic and diastolic blood pressures before surgery and anesthesia induction (P > 0.05). However, there was a significant difference in heart rate before anesthesia induction (P Conclusion: Providing handshake and information support before anesthesia induction effectively reduces stress, alleviates anxiety, and enhances comfort and satisfaction among patients undergoing laparoscopic cholecystectomy.展开更多
This study analyzes the User Interface(UI)and User Experience(UX)of information systems that provide local government information.The systems analyzed are the Local Administrative Comprehensive Information Disclosure ...This study analyzes the User Interface(UI)and User Experience(UX)of information systems that provide local government information.The systems analyzed are the Local Administrative Comprehensive Information Disclosure System(Zheripan),the Integrated Local Financial Disclosure System(Qinching Online),and the Local Regulations Information System(12348 Zhejiang Legal Network).The Local Administrative Comprehensive Information Disclosure System offers public service and personnel information,while the Integrated Local Financial Disclosure System provides financial information,and the Local Regulations Information System offers legal information as its main content.The analysis framework utilized three elements:objective data,psychological factors,and heuristic evaluation.The results of the first objective data analysis show that approximately 70%of visits to Zheripan and Qinching Online are through search,and the time spent on the homepage is short.In contrast,about 70%of visits to the 12348 Zhejiang Legal Network are direct visits,with users browsing multiple pages with a clear purpose.In terms of data provision methods,Zheripan provides two types of data in three formats,Qinching Online offers 28 types of data in five formats,and 12348 Zhejiang Legal Network provides one type of information in a single format.The second psychological factor analysis found that all three websites had a number of menus suitable for short-term cognitive capacity.However,only one of the sites had a layout that considered the user’s eye movement.Finally,the heuristic evaluation revealed that most of the evaluation criteria were not met.While the design is relatively simple and follows standards,feedback for users,error prevention,and help options were lacking.Moreover,the user-specific usability was low,and the systems remained at the information-providing level.Based on these findings,both short-term and long-term improvement measures for creating an interactive system beyond simple information disclosure are proposed.展开更多
Nowadays,spatiotemporal information,positioning,and navigation services have become critical components of new infrastructure.Precise positioning technology is indispensable for determining spatiotemporal information ...Nowadays,spatiotemporal information,positioning,and navigation services have become critical components of new infrastructure.Precise positioning technology is indispensable for determining spatiotemporal information and providing navigation services.展开更多
Background: For nursing students, gathering social information is essential for understanding healthcare and social issues and developing critical thinking and decision-making skills. However, the choice of informatio...Background: For nursing students, gathering social information is essential for understanding healthcare and social issues and developing critical thinking and decision-making skills. However, the choice of information sources varies by age and individual habits. With the widespread use of the internet, there are notable differences between younger and older generations in their reliance on the internet versus traditional media sources like newspapers and television. Given the wide age range and diverse backgrounds of nursing students, understanding generational differences in information-gathering methods is important for implementing effective education. Purpose: The purpose of this study is to identify how nursing students in different age groups obtain social information and to examine media usage trends by age group. Additionally, we aim to use the findings to provide insights into effective information dissemination methods in nursing education. Results: The results showed that nursing students in their teens to forties, regardless of gender, primarily relied on the internet as their main information source, with television playing a secondary role. In contrast, students in their fifties tended to obtain information more often from newspapers and television than from the internet. This highlights an age-related difference in preferred information sources, with older students showing a greater reliance on traditional media. Conclusions: This study demonstrates that nursing students use different information-gathering methods based on their age, suggesting a need to custo-mize information dissemination strategies in nursing education. Digital media may be more effective for younger students, while traditional media or printed materials might better serve older students. Educational institutions should consider these generational differences in media usage and adopt strategies that meet the diverse needs of their student populations.展开更多
Background: The availability of essential medicines and medical supplies is crucial for effectively delivering healthcare services. In Zambia, the Logistics Management Information System (LMIS) is a key tool for manag...Background: The availability of essential medicines and medical supplies is crucial for effectively delivering healthcare services. In Zambia, the Logistics Management Information System (LMIS) is a key tool for managing the supply chain of these commodities. This study aimed to evaluate the effectiveness of LMIS in ensuring the availability of essential medicines and medical supplies in public hospitals in the Copperbelt Province of Zambia. Materials and Methods: From February to April 2022, a cross-sectional study was conducted in 12 public hospitals across the Copperbelt Province. Data were collected using structured questionnaires, checklists, and stock control cards. The study assessed LMIS availability, training, and knowledge among pharmacy personnel, as well as data accuracy, product availability, and order fill rates. Descriptive statistics were used to analyse the data. Results: All surveyed hospitals had LMIS implemented and were using eLMIS as the primary LMIS. Only 47% and 48% of pharmacy personnel received training in eLMIS and Essential Medicines Logistics Improvement Program (EMLIP), respectively. Most personnel demonstrated good knowledge of LMIS, with 77.7% able to log in to eLMIS Facility Edition, 76.6% able to locate stock control cards in the system, and 78.7% able to perform transactions. However, data accuracy from physical and electronic records varied from 0% to 60%, and product availability ranged from 50% to 80%. Order fill rates from Zambia Medicines and Medical Supplies Agency (ZAMMSA) were consistently below 30%. Discrepancies were observed between physical stock counts and eLMIS records. Conclusion: This study found that most hospitals in the Copperbelt Province of Zambia have implemented LMIS use. While LMIS implementation is high in the Copperbelt Province of Zambia, challenges such as low training levels, data inaccuracies, low product availability, and order fill rates persist. Addressing these issues requires a comprehensive approach, including capacity building, data quality improvement, supply chain coordination, and investment in infrastructure and human resources. Strengthening LMIS effectiveness is crucial for improving healthcare delivery and patient outcomes in Zambia.展开更多
The growing incidence of cyberattacks necessitates a robust and effective Intrusion Detection Systems(IDS)for enhanced network security.While conventional IDSs can be unsuitable for detecting different and emerging at...The growing incidence of cyberattacks necessitates a robust and effective Intrusion Detection Systems(IDS)for enhanced network security.While conventional IDSs can be unsuitable for detecting different and emerging attacks,there is a demand for better techniques to improve detection reliability.This study introduces a new method,the Deep Adaptive Multi-Layer Attention Network(DAMLAN),to boost the result of intrusion detection on network data.Due to its multi-scale attention mechanisms and graph features,DAMLAN aims to address both known and unknown intrusions.The real-world NSL-KDD dataset,a popular choice among IDS researchers,is used to assess the proposed model.There are 67,343 normal samples and 58,630 intrusion attacks in the training set,12,833 normal samples,and 9711 intrusion attacks in the test set.Thus,the proposed DAMLAN method is more effective than the standard models due to the consideration of patterns by the attention layers.The experimental performance of the proposed model demonstrates that it achieves 99.26%training accuracy and 90.68%testing accuracy,with precision reaching 98.54%on the training set and 96.64%on the testing set.The recall and F1 scores again support the model with training set values of 99.90%and 99.21%and testing set values of 86.65%and 91.37%.These results provide a strong basis for the claims made regarding the model’s potential to identify intrusion attacks and affirm its relatively strong overall performance,irrespective of type.Future work would employ more attempts to extend the scalability and applicability of DAMLAN for real-time use in intrusion detection systems.展开更多
General Rules Journal of Polyphenols publishes research articles,reviews and short communications in English,on the fields of the science and technology of plant polyphenols.
This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi...This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi analytical solutions of temperature increment and displacement of multi-layered composite structures are obtained by using the Laplace transform method,upon which the effects of thermal resistance coefficient,partition coefficient,thermal conductivity ratio and heat capacity ratio on the responses are studied.The results show that the generalized imperfect thermal contact model can realistically describe the imperfect thermal contact problem.Accordingly,it may degenerate into other thermal contact models by adjusting the thermal resistance coefficient and partition coefficient.展开更多
Low Earth Orbit(LEO)mega-constellation networks,exemplified by Starlink,are poised to play a pivotal role in future mobile communication networks,due to their low latency and high capacity.With the massively deployed ...Low Earth Orbit(LEO)mega-constellation networks,exemplified by Starlink,are poised to play a pivotal role in future mobile communication networks,due to their low latency and high capacity.With the massively deployed satellites,ground users now can be covered by multiple visible satellites,but also face complex handover issues with such massive high-mobility satellites in multi-layer.The end-to-end routing is also affected by the handover behavior.In this paper,we propose an intelligent handover strategy dedicated to multi-layer LEO mega-constellation networks.Firstly,an analytic model is utilized to rapidly estimate the end-to-end propagation latency as a key handover factor to construct a multi-objective optimization model.Subsequently,an intelligent handover strategy is proposed by employing the Dueling Double Deep Q Network(D3QN)-based deep reinforcement learning algorithm for single-layer constellations.Moreover,an optimal crosslayer handover scheme is proposed by predicting the latency-jitter and minimizing the cross-layer overhead.Simulation results demonstrate the superior performance of the proposed method in the multi-layer LEO mega-constellation,showcasing reductions of up to 8.2%and 59.5%in end-to-end latency and jitter respectively,when compared to the existing handover strategies.展开更多
This article attempts to distinguish public relations(PRs)from propaganda,within the context of information management.Speedy dissemination of information is an important feature of contemporary communication practice...This article attempts to distinguish public relations(PRs)from propaganda,within the context of information management.Speedy dissemination of information is an important feature of contemporary communication practice globally.In this era,the information content of communication is an important element requiring critical evaluation.This is so,because of the need to safeguard the information ecosystem,considering the thin line between public relations and propaganda.While both propaganda and public relations aim to shape perceptions,influence attitudes,and sway opinions,one key distinction lies in their ethical considerations.Public relations emphasize honesty,accuracy,accountability,and a commitment to the truth.In contrast,propaganda may involve manipulation,distortion,or even fabrication of information to advance a particular agenda,often at the expense of truth and transparency.Hinged on The Excellence Theory and the Two-Way Symmetrical Model,the paper focuses on the meeting points and differences between public relations and propaganda,with a view to safeguarding the integrity of the information ecosystem.The study adopted the survey research method,with interview as research instrument.The study discovered that while propaganda is not entirely a bad practice,it has a heavy tilt towards bias.It therefore recommends that deliberate steps be taken by relevant professional organisations and other stakeholders towards educating the citizens on ways of distinguishing between public relations and propaganda contents.展开更多
Describe the content and current situation of maternal information needs and support,providing a basis for building maternal information needs assessment tools and improving information support systems.Retrieve articl...Describe the content and current situation of maternal information needs and support,providing a basis for building maternal information needs assessment tools and improving information support systems.Retrieve articles related to the topic from domestic and foreign databases,and ultimately include 54 articles.Summarize from the aspects of information demand content,influencing factors,evaluation tools,and information support channels.We found that the information needs of pregnant women are rich in content,but the existing information support content is limited and the form is single.There is an urgent need to establish scientific and effective information needs assessment tools,as well as diverse information support systems.展开更多
Ln-containing polyoxoniobates(PONbs)have appealing applications in luminescence,information encryption and magnetic fields,but the synthesis of PONbs containing high-nuclearity Ln-O clusters is challenging due to the ...Ln-containing polyoxoniobates(PONbs)have appealing applications in luminescence,information encryption and magnetic fields,but the synthesis of PONbs containing high-nuclearity Ln-O clusters is challenging due to the easy hydrolysis of Ln^(3+)ions in alkaline environments.In this paper,we are able to integrate CO_(3)^(2-)and high-nuclearity Ln-O clusters into PONb to construct an inorganic giant Eu_(19)-embedded PONb H_(49)K_(16)Na_(13)(H_(2)O)_(63)[Eu_(21)O_(2)(OH)_(7)(H_(2)O)_(5)(Nb_(7)O_(22))_(10)(Nb_(2)O_(6))_(2)(CO_(3))_(18)]·91H_(2)O(1),which contains the highest nuclearity Eu-O clusters and the largest number of Eu^(3+)ions among PONbs.In addition,the film that was prepared by mixing 1 with gelatin and glycerol,exhibits reversible luminescence switching behavior under acid/alkali stimulation and has been used to create a fluorescence-encoded information approach.This work paves a feasible strategy for the construction of high-nuclearity Ln-O cluster-containing PONbs and the expansion of the application of Ln-containing PONbs in information encryption.展开更多
With the continuous advancement of information technology,traditional teaching management models can no longer meet the demands of modern laboratory management.Information management,characterized by efficiency,conven...With the continuous advancement of information technology,traditional teaching management models can no longer meet the demands of modern laboratory management.Information management,characterized by efficiency,convenience,and intelligence,provides new ideas and directions for reforming laboratory teaching management models in higher education.Based on this,this paper explores reform strategies and practical approaches for laboratory teaching management models from the perspective of information management,aiming to offer references for enhancing the modernization and intelligentization of laboratory teaching management.展开更多
As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limi...As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limits their ability to capture temporal differences between frames.Current methods also exhibit limited generalization capabilities,struggling to detect content generated by unknown forgery algorithms.Moreover,the diversity and complexity of forgery techniques introduced by Artificial Intelligence Generated Content(AIGC)present significant challenges for traditional detection frameworks,whichmust balance high detection accuracy with robust performance.To address these challenges,we propose a novel Deepfake detection framework that combines a two-stream convolutional network with a Vision Transformer(ViT)module to enhance spatio-temporal feature representation.The ViT model extracts spatial features from the forged video,while the 3D convolutional network captures temporal features.The 3D convolution enables cross-frame feature extraction,allowing the model to detect subtle facial changes between frames.The confidence scores from both the ViT and 3D convolution submodels are fused at the decision layer,enabling themodel to effectively handle unknown forgery techniques.Focusing on Deepfake videos and GAN-generated images,the proposed approach is evaluated on two widely used public face forgery datasets.Compared to existing state-of-theartmethods,it achieves higher detection accuracy and better generalization performance,offering a robust solution for deepfake detection in real-world scenarios.展开更多
Climate downscaling is used to transform large-scale meteorological data into small-scale data with enhanced detail,which finds wide applications in climate modeling,numerical weather forecasting,and renewable energy....Climate downscaling is used to transform large-scale meteorological data into small-scale data with enhanced detail,which finds wide applications in climate modeling,numerical weather forecasting,and renewable energy.Although deeplearning-based downscaling methods effectively capture the complex nonlinear mapping between meteorological data of varying scales,the supervised deep-learning-based downscaling methods suffer from insufficient high-resolution data in practice,and unsupervised methods struggle with accurately inferring small-scale specifics from limited large-scale inputs due to small-scale uncertainty.This article presents DualDS,a dual-learning framework utilizing a Generative Adversarial Network–based neural network and subgrid-scale auxiliary information for climate downscaling.Such a learning method is unified in a two-stream framework through up-and downsamplers,where the downsampler is used to simulate the information loss process during the upscaling,and the upsampler is used to reconstruct lost details and correct errors incurred during the upscaling.This dual learning strategy can eliminate the dependence on high-resolution ground truth data in the training process and refine the downscaling results by constraining the mapping process.Experimental findings demonstrate that DualDS is comparable to several state-of-the-art deep learning downscaling approaches,both qualitatively and quantitatively.Specifically,for a single surface-temperature data downscaling task,our method is comparable with other unsupervised algorithms with the same dataset,and we can achieve a 0.469 dB higher peak signal-to-noise ratio,0.017 higher structural similarity,0.08 lower RMSE,and the best correlation coefficient.In summary,this paper presents a novel approach to addressing small-scale uncertainty issues in unsupervised downscaling processes.展开更多
Online education has become a critical mode of instruction in Chinese universities,particularly during and after the COVID-19 pandemic.This study examines information management in online education through a triadic f...Online education has become a critical mode of instruction in Chinese universities,particularly during and after the COVID-19 pandemic.This study examines information management in online education through a triadic framework encompassing classroom information management,teaching effectiveness management,and teaching information management.Drawing on in-depth interviews with administrators,teachers,and students,the findings reveal three primary challenges in online education:the absence of embodied information,the uncontrollable nature of online platforms,and nonverbal overload caused by Zoom fatigue.Teachers face difficulties maintaining presence and interaction due to limited feedback from students and risks associated with class recordings.Students experience increased psychological and physical fatigue due to the overlap of learning and living spaces.Recommendations to address these issues include enhancing teacher-student interaction to foster a sense of presence,improving the transparency of course information to align expectations,and adopting user-friendly teaching platforms with privacy safeguards.These insights aim to improve the security,effectiveness,and experience of online education in higher education institutions.展开更多
This study focuses on the management of maintenance hemodialysis(MHD)patients,with a specific emphasis on the practical application effect of the network information management model including its impact on patients’...This study focuses on the management of maintenance hemodialysis(MHD)patients,with a specific emphasis on the practical application effect of the network information management model including its impact on patients’compliance.A network information management model for MHD patients was constructed around three management schemes:“software reminders+follow-up guidance”,“dietary records+self-management reminders”,and“dialysis plan+precise weight management”.These schemes were respectively used to optimize anemia management,control the risk of hyperphosphatemia,and improve toxin clearance efficiency.A controlled experiment was conducted,with an experimental group and a control group set up for comparative practice.The results showed that the network information management model can effectively improve patients’anemia,help alleviate mineral metabolism disorders and the accumulation of small-molecule toxins,and exert a positive impact on patients’treatment compliance.展开更多
文摘In the process industry, automation and process control systems are widely implemented, information integration is however far away from satisfactory. It remains a hard job for senior managers to make decisions based on the plant-wide real-time integrated information. This paper proposes a multi-layer information integration platform. In the data integration level, the standard for the exchange of product (STEP) and the extensible markup language (XML) are used to unify these data of the chemical process. In the model integration level, the models are integrated by using the neutral model repository and CAPE-OPEN. In the integration of process task, the common object request broker architecture (CORBA) is used as the communication mediator. The XML is taken as the data standard. A uniform information platform is thus constructed and realized. The proposed information integration platform is satisfactorily implemented to solve the Tennessee Eastman (TE) problem.
基金supported by the National Key Research and Development Program of China(No.2022YFB3404700)the National Natural Science Foundation of China(Nos.52105313 and 52275299)+2 种基金the Research and Development Program of Beijing Municipal Education Commission,China(No.KM202210005036)the Natural Science Foundation of Chongqing,China(No.CSTB2023NSCQ-MSX0701)the National Defense Basic Research Projects of China(No.JCKY2022405C002).
文摘At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-layer multi-pass FRAM-deposited alumin-um alloy samples were successfully prepared using a non-shoulder tool head.The material flow behavior and microstructure of the over-lapped zone between adjacent layers and passes during multi-layer multi-pass FRAM deposition were studied using the hybrid 6061 and 5052 aluminum alloys.The results showed that a mechanical interlocking structure was formed between the adjacent layers and the adja-cent passes in the overlapped center area.Repeated friction and rolling of the tool head led to different degrees of lateral flow and plastic deformation of the materials in the overlapped zone,which made the recrystallization degree in the left and right edge zones of the over-lapped zone the highest,followed by the overlapped center zone and the non-overlapped zone.The tensile strength of the overlapped zone exceeded 90%of that of the single-pass deposition sample.It is proved that although there are uneven grooves on the surface of the over-lapping area during multi-layer and multi-pass deposition,they can be filled by the flow of materials during the deposition of the next lay-er,thus ensuring the dense microstructure and excellent mechanical properties of the overlapping area.The multi-layer multi-pass FRAM deposition overcomes the limitation of deposition width and lays the foundation for the future deposition of large-scale high-performance components.
基金supported by the project“GEF9874:Strengthening Coordinated Approaches to Reduce Invasive Alien Species(lAS)Threats to Globally Significant Agrobiodiversity and Agroecosystems in China”funding from the Excellent Talent Training Funding Project in Dongcheng District,Beijing,with project number 2024-dchrcpyzz-9.
文摘Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant challenge.To address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data registration.Specifically,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less efficient.Meanwhile,visual texture information complements LiDAR-Visual localization by providing additional contextual details.By incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of localization.This approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.
文摘Objective: This study evaluates the impact of handshake and information support on patients’ outcomes during laparoscopic cholecystectomy. It examines the effects on their physiological and psychological responses and overall satisfaction with nursing care. Methods: A total of 84 patients scheduled for laparoscopic cholecystectomy were selected through convenient sampling and randomly assigned to either the control group or the intervention group using a random number table. Each group consisted of 42 patients. The control group received standard surgical nursing care. In addition to standard care, the intervention group received handshake and information support from the circulating nurse before anesthesia induction. Vital signs were recorded before surgery and before anesthesia induction. Anxiety levels were measured using the State-Trait Anxiety Inventory (STAI) and the State-Anxiety Inventory (S-AI), while nursing satisfaction was assessed using a numerical rating scale. Results: No significant differences were found between the two groups in systolic and diastolic blood pressures before surgery and anesthesia induction (P > 0.05). However, there was a significant difference in heart rate before anesthesia induction (P Conclusion: Providing handshake and information support before anesthesia induction effectively reduces stress, alleviates anxiety, and enhances comfort and satisfaction among patients undergoing laparoscopic cholecystectomy.
文摘This study analyzes the User Interface(UI)and User Experience(UX)of information systems that provide local government information.The systems analyzed are the Local Administrative Comprehensive Information Disclosure System(Zheripan),the Integrated Local Financial Disclosure System(Qinching Online),and the Local Regulations Information System(12348 Zhejiang Legal Network).The Local Administrative Comprehensive Information Disclosure System offers public service and personnel information,while the Integrated Local Financial Disclosure System provides financial information,and the Local Regulations Information System offers legal information as its main content.The analysis framework utilized three elements:objective data,psychological factors,and heuristic evaluation.The results of the first objective data analysis show that approximately 70%of visits to Zheripan and Qinching Online are through search,and the time spent on the homepage is short.In contrast,about 70%of visits to the 12348 Zhejiang Legal Network are direct visits,with users browsing multiple pages with a clear purpose.In terms of data provision methods,Zheripan provides two types of data in three formats,Qinching Online offers 28 types of data in five formats,and 12348 Zhejiang Legal Network provides one type of information in a single format.The second psychological factor analysis found that all three websites had a number of menus suitable for short-term cognitive capacity.However,only one of the sites had a layout that considered the user’s eye movement.Finally,the heuristic evaluation revealed that most of the evaluation criteria were not met.While the design is relatively simple and follows standards,feedback for users,error prevention,and help options were lacking.Moreover,the user-specific usability was low,and the systems remained at the information-providing level.Based on these findings,both short-term and long-term improvement measures for creating an interactive system beyond simple information disclosure are proposed.
文摘Nowadays,spatiotemporal information,positioning,and navigation services have become critical components of new infrastructure.Precise positioning technology is indispensable for determining spatiotemporal information and providing navigation services.
文摘Background: For nursing students, gathering social information is essential for understanding healthcare and social issues and developing critical thinking and decision-making skills. However, the choice of information sources varies by age and individual habits. With the widespread use of the internet, there are notable differences between younger and older generations in their reliance on the internet versus traditional media sources like newspapers and television. Given the wide age range and diverse backgrounds of nursing students, understanding generational differences in information-gathering methods is important for implementing effective education. Purpose: The purpose of this study is to identify how nursing students in different age groups obtain social information and to examine media usage trends by age group. Additionally, we aim to use the findings to provide insights into effective information dissemination methods in nursing education. Results: The results showed that nursing students in their teens to forties, regardless of gender, primarily relied on the internet as their main information source, with television playing a secondary role. In contrast, students in their fifties tended to obtain information more often from newspapers and television than from the internet. This highlights an age-related difference in preferred information sources, with older students showing a greater reliance on traditional media. Conclusions: This study demonstrates that nursing students use different information-gathering methods based on their age, suggesting a need to custo-mize information dissemination strategies in nursing education. Digital media may be more effective for younger students, while traditional media or printed materials might better serve older students. Educational institutions should consider these generational differences in media usage and adopt strategies that meet the diverse needs of their student populations.
文摘Background: The availability of essential medicines and medical supplies is crucial for effectively delivering healthcare services. In Zambia, the Logistics Management Information System (LMIS) is a key tool for managing the supply chain of these commodities. This study aimed to evaluate the effectiveness of LMIS in ensuring the availability of essential medicines and medical supplies in public hospitals in the Copperbelt Province of Zambia. Materials and Methods: From February to April 2022, a cross-sectional study was conducted in 12 public hospitals across the Copperbelt Province. Data were collected using structured questionnaires, checklists, and stock control cards. The study assessed LMIS availability, training, and knowledge among pharmacy personnel, as well as data accuracy, product availability, and order fill rates. Descriptive statistics were used to analyse the data. Results: All surveyed hospitals had LMIS implemented and were using eLMIS as the primary LMIS. Only 47% and 48% of pharmacy personnel received training in eLMIS and Essential Medicines Logistics Improvement Program (EMLIP), respectively. Most personnel demonstrated good knowledge of LMIS, with 77.7% able to log in to eLMIS Facility Edition, 76.6% able to locate stock control cards in the system, and 78.7% able to perform transactions. However, data accuracy from physical and electronic records varied from 0% to 60%, and product availability ranged from 50% to 80%. Order fill rates from Zambia Medicines and Medical Supplies Agency (ZAMMSA) were consistently below 30%. Discrepancies were observed between physical stock counts and eLMIS records. Conclusion: This study found that most hospitals in the Copperbelt Province of Zambia have implemented LMIS use. While LMIS implementation is high in the Copperbelt Province of Zambia, challenges such as low training levels, data inaccuracies, low product availability, and order fill rates persist. Addressing these issues requires a comprehensive approach, including capacity building, data quality improvement, supply chain coordination, and investment in infrastructure and human resources. Strengthening LMIS effectiveness is crucial for improving healthcare delivery and patient outcomes in Zambia.
基金Nourah bint Abdulrahman University for funding this project through the Researchers Supporting Project(PNURSP2025R319)Riyadh,Saudi Arabia and Prince Sultan University for covering the article processing charges(APC)associated with this publication.Special acknowledgement to Automated Systems&Soft Computing Lab(ASSCL),Prince Sultan University,Riyadh,Saudi Arabia.
文摘The growing incidence of cyberattacks necessitates a robust and effective Intrusion Detection Systems(IDS)for enhanced network security.While conventional IDSs can be unsuitable for detecting different and emerging attacks,there is a demand for better techniques to improve detection reliability.This study introduces a new method,the Deep Adaptive Multi-Layer Attention Network(DAMLAN),to boost the result of intrusion detection on network data.Due to its multi-scale attention mechanisms and graph features,DAMLAN aims to address both known and unknown intrusions.The real-world NSL-KDD dataset,a popular choice among IDS researchers,is used to assess the proposed model.There are 67,343 normal samples and 58,630 intrusion attacks in the training set,12,833 normal samples,and 9711 intrusion attacks in the test set.Thus,the proposed DAMLAN method is more effective than the standard models due to the consideration of patterns by the attention layers.The experimental performance of the proposed model demonstrates that it achieves 99.26%training accuracy and 90.68%testing accuracy,with precision reaching 98.54%on the training set and 96.64%on the testing set.The recall and F1 scores again support the model with training set values of 99.90%and 99.21%and testing set values of 86.65%and 91.37%.These results provide a strong basis for the claims made regarding the model’s potential to identify intrusion attacks and affirm its relatively strong overall performance,irrespective of type.Future work would employ more attempts to extend the scalability and applicability of DAMLAN for real-time use in intrusion detection systems.
文摘General Rules Journal of Polyphenols publishes research articles,reviews and short communications in English,on the fields of the science and technology of plant polyphenols.
基金Projects(42477162,52108347,52178371,52168046,52178321,52308383)supported by the National Natural Science Foundation of ChinaProjects(2023C03143,2022C01099,2024C01219,2022C03151)supported by the Zhejiang Key Research and Development Plan,China+6 种基金Project(LQ22E080010)supported by the Exploring Youth Project of Zhejiang Natural Science Foundation,ChinaProject(LR21E080005)supported by the Outstanding Youth Project of Natural Science Foundation of Zhejiang Province,ChinaProject(2022M712964)supported by the Postdoctoral Science Foundation of ChinaProject(2023AFB008)supported by the Natural Science Foundation of Hubei Province for Youth,ChinaProject(202203)supported by Engineering Research Centre of Rock-Soil Drilling&Excavation and Protection,Ministry of Education,ChinaProject(202305-2)supported by the Science and Technology Project of Zhejiang Provincial Communication Department,ChinaProject(2021K256)supported by the Construction Research Founds of Department of Housing and Urban-Rural Development of Zhejiang Province,China。
文摘This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi analytical solutions of temperature increment and displacement of multi-layered composite structures are obtained by using the Laplace transform method,upon which the effects of thermal resistance coefficient,partition coefficient,thermal conductivity ratio and heat capacity ratio on the responses are studied.The results show that the generalized imperfect thermal contact model can realistically describe the imperfect thermal contact problem.Accordingly,it may degenerate into other thermal contact models by adjusting the thermal resistance coefficient and partition coefficient.
基金supported by the National Natural Science Foundation of China(No.62401597)Natural Science Foundation of Hunan Province,China(No.2024JJ6469)the Research Project of National University of Defense Technology,China(No.ZK22-02).
文摘Low Earth Orbit(LEO)mega-constellation networks,exemplified by Starlink,are poised to play a pivotal role in future mobile communication networks,due to their low latency and high capacity.With the massively deployed satellites,ground users now can be covered by multiple visible satellites,but also face complex handover issues with such massive high-mobility satellites in multi-layer.The end-to-end routing is also affected by the handover behavior.In this paper,we propose an intelligent handover strategy dedicated to multi-layer LEO mega-constellation networks.Firstly,an analytic model is utilized to rapidly estimate the end-to-end propagation latency as a key handover factor to construct a multi-objective optimization model.Subsequently,an intelligent handover strategy is proposed by employing the Dueling Double Deep Q Network(D3QN)-based deep reinforcement learning algorithm for single-layer constellations.Moreover,an optimal crosslayer handover scheme is proposed by predicting the latency-jitter and minimizing the cross-layer overhead.Simulation results demonstrate the superior performance of the proposed method in the multi-layer LEO mega-constellation,showcasing reductions of up to 8.2%and 59.5%in end-to-end latency and jitter respectively,when compared to the existing handover strategies.
文摘This article attempts to distinguish public relations(PRs)from propaganda,within the context of information management.Speedy dissemination of information is an important feature of contemporary communication practice globally.In this era,the information content of communication is an important element requiring critical evaluation.This is so,because of the need to safeguard the information ecosystem,considering the thin line between public relations and propaganda.While both propaganda and public relations aim to shape perceptions,influence attitudes,and sway opinions,one key distinction lies in their ethical considerations.Public relations emphasize honesty,accuracy,accountability,and a commitment to the truth.In contrast,propaganda may involve manipulation,distortion,or even fabrication of information to advance a particular agenda,often at the expense of truth and transparency.Hinged on The Excellence Theory and the Two-Way Symmetrical Model,the paper focuses on the meeting points and differences between public relations and propaganda,with a view to safeguarding the integrity of the information ecosystem.The study adopted the survey research method,with interview as research instrument.The study discovered that while propaganda is not entirely a bad practice,it has a heavy tilt towards bias.It therefore recommends that deliberate steps be taken by relevant professional organisations and other stakeholders towards educating the citizens on ways of distinguishing between public relations and propaganda contents.
文摘Describe the content and current situation of maternal information needs and support,providing a basis for building maternal information needs assessment tools and improving information support systems.Retrieve articles related to the topic from domestic and foreign databases,and ultimately include 54 articles.Summarize from the aspects of information demand content,influencing factors,evaluation tools,and information support channels.We found that the information needs of pregnant women are rich in content,but the existing information support content is limited and the form is single.There is an urgent need to establish scientific and effective information needs assessment tools,as well as diverse information support systems.
基金the financial support from the National Natural Science Foundation of China(Nos.21971040,22171045,and 22371046)。
文摘Ln-containing polyoxoniobates(PONbs)have appealing applications in luminescence,information encryption and magnetic fields,but the synthesis of PONbs containing high-nuclearity Ln-O clusters is challenging due to the easy hydrolysis of Ln^(3+)ions in alkaline environments.In this paper,we are able to integrate CO_(3)^(2-)and high-nuclearity Ln-O clusters into PONb to construct an inorganic giant Eu_(19)-embedded PONb H_(49)K_(16)Na_(13)(H_(2)O)_(63)[Eu_(21)O_(2)(OH)_(7)(H_(2)O)_(5)(Nb_(7)O_(22))_(10)(Nb_(2)O_(6))_(2)(CO_(3))_(18)]·91H_(2)O(1),which contains the highest nuclearity Eu-O clusters and the largest number of Eu^(3+)ions among PONbs.In addition,the film that was prepared by mixing 1 with gelatin and glycerol,exhibits reversible luminescence switching behavior under acid/alkali stimulation and has been used to create a fluorescence-encoded information approach.This work paves a feasible strategy for the construction of high-nuclearity Ln-O cluster-containing PONbs and the expansion of the application of Ln-containing PONbs in information encryption.
文摘With the continuous advancement of information technology,traditional teaching management models can no longer meet the demands of modern laboratory management.Information management,characterized by efficiency,convenience,and intelligence,provides new ideas and directions for reforming laboratory teaching management models in higher education.Based on this,this paper explores reform strategies and practical approaches for laboratory teaching management models from the perspective of information management,aiming to offer references for enhancing the modernization and intelligentization of laboratory teaching management.
基金supported by National Natural Science Foundation of China(Nos.62477026,62177029,61807020)Humanities and Social Sciences Research Program of the Ministry of Education of China(No.23YJAZH047)the Startup Foundation for Introducing Talent of Nanjing University of Posts and Communications under Grant NY222034.
文摘As Deepfake technology continues to evolve,the distinction between real and fake content becomes increasingly blurred.Most existing Deepfake video detectionmethods rely on single-frame facial image features,which limits their ability to capture temporal differences between frames.Current methods also exhibit limited generalization capabilities,struggling to detect content generated by unknown forgery algorithms.Moreover,the diversity and complexity of forgery techniques introduced by Artificial Intelligence Generated Content(AIGC)present significant challenges for traditional detection frameworks,whichmust balance high detection accuracy with robust performance.To address these challenges,we propose a novel Deepfake detection framework that combines a two-stream convolutional network with a Vision Transformer(ViT)module to enhance spatio-temporal feature representation.The ViT model extracts spatial features from the forged video,while the 3D convolutional network captures temporal features.The 3D convolution enables cross-frame feature extraction,allowing the model to detect subtle facial changes between frames.The confidence scores from both the ViT and 3D convolution submodels are fused at the decision layer,enabling themodel to effectively handle unknown forgery techniques.Focusing on Deepfake videos and GAN-generated images,the proposed approach is evaluated on two widely used public face forgery datasets.Compared to existing state-of-theartmethods,it achieves higher detection accuracy and better generalization performance,offering a robust solution for deepfake detection in real-world scenarios.
基金supported by the following funding bodies:the National Key Research and Development Program of China(Grant No.2020YFA0608000)National Science Foundation of China(Grant Nos.42075142,42375148,42125503+2 种基金42130608)FY-APP-2022.0609,Sichuan Province Key Tech nology Research and Development project(Grant Nos.2024ZHCG0168,2024ZHCG0176,2023YFG0305,2023YFG-0124,and 23ZDYF0091)the CUIT Science and Technology Innovation Capacity Enhancement Program project(Grant No.KYQN202305)。
文摘Climate downscaling is used to transform large-scale meteorological data into small-scale data with enhanced detail,which finds wide applications in climate modeling,numerical weather forecasting,and renewable energy.Although deeplearning-based downscaling methods effectively capture the complex nonlinear mapping between meteorological data of varying scales,the supervised deep-learning-based downscaling methods suffer from insufficient high-resolution data in practice,and unsupervised methods struggle with accurately inferring small-scale specifics from limited large-scale inputs due to small-scale uncertainty.This article presents DualDS,a dual-learning framework utilizing a Generative Adversarial Network–based neural network and subgrid-scale auxiliary information for climate downscaling.Such a learning method is unified in a two-stream framework through up-and downsamplers,where the downsampler is used to simulate the information loss process during the upscaling,and the upsampler is used to reconstruct lost details and correct errors incurred during the upscaling.This dual learning strategy can eliminate the dependence on high-resolution ground truth data in the training process and refine the downscaling results by constraining the mapping process.Experimental findings demonstrate that DualDS is comparable to several state-of-the-art deep learning downscaling approaches,both qualitatively and quantitatively.Specifically,for a single surface-temperature data downscaling task,our method is comparable with other unsupervised algorithms with the same dataset,and we can achieve a 0.469 dB higher peak signal-to-noise ratio,0.017 higher structural similarity,0.08 lower RMSE,and the best correlation coefficient.In summary,this paper presents a novel approach to addressing small-scale uncertainty issues in unsupervised downscaling processes.
文摘Online education has become a critical mode of instruction in Chinese universities,particularly during and after the COVID-19 pandemic.This study examines information management in online education through a triadic framework encompassing classroom information management,teaching effectiveness management,and teaching information management.Drawing on in-depth interviews with administrators,teachers,and students,the findings reveal three primary challenges in online education:the absence of embodied information,the uncontrollable nature of online platforms,and nonverbal overload caused by Zoom fatigue.Teachers face difficulties maintaining presence and interaction due to limited feedback from students and risks associated with class recordings.Students experience increased psychological and physical fatigue due to the overlap of learning and living spaces.Recommendations to address these issues include enhancing teacher-student interaction to foster a sense of presence,improving the transparency of course information to align expectations,and adopting user-friendly teaching platforms with privacy safeguards.These insights aim to improve the security,effectiveness,and experience of online education in higher education institutions.
文摘This study focuses on the management of maintenance hemodialysis(MHD)patients,with a specific emphasis on the practical application effect of the network information management model including its impact on patients’compliance.A network information management model for MHD patients was constructed around three management schemes:“software reminders+follow-up guidance”,“dietary records+self-management reminders”,and“dialysis plan+precise weight management”.These schemes were respectively used to optimize anemia management,control the risk of hyperphosphatemia,and improve toxin clearance efficiency.A controlled experiment was conducted,with an experimental group and a control group set up for comparative practice.The results showed that the network information management model can effectively improve patients’anemia,help alleviate mineral metabolism disorders and the accumulation of small-molecule toxins,and exert a positive impact on patients’treatment compliance.
