The electromagnetic wave absorption of silicon carbide nanowires is improved by their uniform and diverse cross-structures.This study introduces a sustainable and high value-added method for synthesizing silicon carbi...The electromagnetic wave absorption of silicon carbide nanowires is improved by their uniform and diverse cross-structures.This study introduces a sustainable and high value-added method for synthesizing silicon carbide nanowires using lignite and waste silicon powder as raw materials through carbothermal reduction.The staggered structure of nanowires promotes the creation of interfacial polarization,impedance matching,and multiple loss mechanisms,leading to enhanced electromagnetic absorption performance.The silicon carbide nanowires demonstrate outstanding electromagnetic absorption capabilities with the minimum reflection loss of-48.09 d B at10.08 GHz and an effective absorption bandwidth(the reflection loss less than-10 d B)ranging from 8.54 to 16.68 GHz with a thickness of 2.17 mm.This research presents an innovative approach for utilizing solid waste in an environmentally friendly manner to produce broadband silicon carbide composite absorbers.展开更多
1 General information Journal of Geographical Sciences is an international academic journal that publishes papers of the highest quality in physical geography, natural resources, environmental sciences, geographic inf...1 General information Journal of Geographical Sciences is an international academic journal that publishes papers of the highest quality in physical geography, natural resources, environmental sciences, geographic information sciences, remote sensing and cartography. Manuscripts come from different parts of the world.展开更多
With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State I...With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State Information(CSI)offers fine-grained temporal,frequency,and spatial insights into multipath propagation,making it a crucial data source for human-centric sensing.Recently,the integration of deep learning has significantly improved the robustness and automation of feature extraction from CSI in complex environments.This paper provides a comprehensive review of deep learning-enhanced human sensing based on CSI.We first outline mainstream CSI acquisition tools and their hardware specifications,then provide a detailed discussion of preprocessing methods such as denoising,time–frequency transformation,data segmentation,and augmentation.Subsequently,we categorize deep learning approaches according to sensing tasks—namely detection,localization,and recognition—and highlight representative models across application scenarios.Finally,we examine key challenges including domain generalization,multi-user interference,and limited data availability,and we propose future research directions involving lightweight model deployment,multimodal data fusion,and semantic-level sensing.展开更多
With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration wi...With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration within urban spaces and serve as testbeds for exploring smart city planning and governance models.Information models facilitate the effective integration of technology into space.Building Information Modeling(BIM)and City Information Modeling(CIM)have been widely used in urban construction.However,the existing information models have limitations in the application of the park,so it is necessary to develop an information model suitable for the park.This paper first traces the evolution of park smart transformation,reviews the global landscape of smart park development,and identifies key trends and persistent challenges.Addressing the particularities of parks,the concept of Park Information Modeling(PIM)is proposed.PIM leverages smart technologies such as artificial intelligence,digital twins,and collaborative sensing to help form a‘space-technology-system’smart structure,enabling systematic management of diverse park spaces,addressing the deficiency in park-level information models,and aiming to achieve scale articulation between BIM and CIM.Finally,through a detailed top-level design application case study of the Nanjing Smart Education Park in China,this paper illustrates the translation process of the PIM concept into practice,showcasing its potential to provide smart management tools for park managers and enhance services for park stakeholders,although further empirical validation is required.展开更多
Based on the educational evaluation reform,this study explores the construction of an evidence-based value-added evaluation system based on data-driven,aiming to solve the limitations of traditional evaluation methods...Based on the educational evaluation reform,this study explores the construction of an evidence-based value-added evaluation system based on data-driven,aiming to solve the limitations of traditional evaluation methods.The research adopts the method of combining theoretical analysis and practical application,and designs the evidence-based value-added evaluation framework,which includes the core elements of a multi-source heterogeneous data acquisition and processing system,a value-added evaluation agent based on a large model,and an evaluation implementation and application mechanism.Through empirical research verification,the evaluation system has remarkable effects in improving learning participation,promoting ability development,and supporting teaching decision-making,and provides a theoretical reference and practical path for educational evaluation reform in the new era.The research shows that the evidence-based value-added evaluation system based on data-driven can reflect students’actual progress more fairly and objectively by accurately measuring the difference in starting point and development range of students,and provide strong support for the realization of high-quality education development.展开更多
Information extraction(IE)aims to automatically identify and extract information about specific interests from raw texts.Despite the abundance of solutions based on fine-tuning pretrained language models,IE in the con...Information extraction(IE)aims to automatically identify and extract information about specific interests from raw texts.Despite the abundance of solutions based on fine-tuning pretrained language models,IE in the context of fewshot and zero-shot scenarios remains highly challenging due to the scarcity of training data.Large language models(LLMs),on the other hand,can generalize well to unseen tasks with few-shot demonstrations or even zero-shot instructions and have demonstrated impressive ability for a wide range of natural language understanding or generation tasks.Nevertheless,it is unclear,whether such effectiveness can be replicated in the task of IE,where the target tasks involve specialized schema and quite abstractive entity or relation concepts.In this paper,we first examine the validity of LLMs in executing IE tasks with an established prompting strategy and further propose multiple types of augmented prompting methods,including the structured fundamental prompt(SFP),the structured interactive reasoning prompt(SIRP),and the voting-enabled structured interactive reasoning prompt(VESIRP).The experimental results demonstrate that while directly promotes inferior performance,the proposed augmented prompt methods significantly improve the extraction accuracy,achieving comparable or even better performance(e.g.,zero-shot FewNERD,FewNERD-INTRA)than state-of-theart methods that require large-scale training samples.This study represents a systematic exploration of employing instruction-following LLM for the task of IE.It not only establishes a performance benchmark for this novel paradigm but,more importantly,validates a practical technical pathway through the proposed prompt enhancement method,offering a viable solution for efficient IE in low-resource settings.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
Advanced geological prediction is a crucial means to ensure safety and efficiency in tunnel construction.However,diff erent advanced geological forecasting methods have their own limitations,resulting in poor detectio...Advanced geological prediction is a crucial means to ensure safety and efficiency in tunnel construction.However,diff erent advanced geological forecasting methods have their own limitations,resulting in poor detection accuracy.Using multiple methods to carry out a comprehensive evaluation can eff ectively improve the accuracy of advanced geological prediction results.In this study,geological information is combined with the detection results of geophysical methods,including transient electromagnetic,induced polarization,and tunnel seismic prediction,to establish a comprehensive analysis method of adverse geology.First,the possible main adverse geological problems are determined according to the geological information.Subsequently,various physical parameters of the rock mass in front of the tunnel face can then be derived on the basis of multisource geophysical data.Finally,based on the analysis results of geological information,the multisource data fusion algorithm is used to determine the type,location,and scale of adverse geology.The advanced geological prediction results that can provide eff ective guidance for tunnel construction can then be obtained.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
Value-added evaluation focuses on individual student growth by tracking changes in academic performance,skills,literacy,etc.,at different time points.It weakens horizontal comparisons and emphasizes vertical progress ...Value-added evaluation focuses on individual student growth by tracking changes in academic performance,skills,literacy,etc.,at different time points.It weakens horizontal comparisons and emphasizes vertical progress to more fairly reflect educational effectiveness.This evaluation method is particularly suitable for vocational education,effectively motivating students’learning enthusiasm and enhancing their self-confidence.Foreign research is represented by the Tennessee Value-Added Assessment System(TVAAS),widely used in evaluating school quality and teacher performance.Domestic research currently focuses on the theoretical construction,model establishment,optimization,and practical application of value-added evaluation,still facing significant challenges in data collection comprehensiveness and model adaptability.Aiming at current issues,this study focuses on exploring the application of artificial intelligence large models in student value-added evaluation from an evidence-based perspective,committed to constructing an innovative evidence-based value-added evaluation system.It aims to achieve precise assessment of students’learning effect“net value-added”through multi-source data collection,intelligent analysis,and personalized feedback.The system integrates outcome evaluation,process evaluation,value-added evaluation,and comprehensive evaluation to form a“four-in-one”dynamic evaluation framework,considering students’starting points,process performance,and final achievements.In the future,value-added evaluation needs to further expand the assessment of non-academic dimensions(such as professional literacy and social-emotional skills)and explore the application of non-linear models to promote the deepening and innovation of educational evaluation reform.展开更多
As the enlightenment stage of students’Chinese learning,primary school Chinese education plays a key role in cultivating students’language ability,thinking development,and humanistic literacy.Value-added evaluation,...As the enlightenment stage of students’Chinese learning,primary school Chinese education plays a key role in cultivating students’language ability,thinking development,and humanistic literacy.Value-added evaluation,as an evaluation method that focuses on the changes in students’individual development and attaches importance to the learning process,has gradually attracted attention in the application of primary school Chinese education.This paper first analyzes the problems existing in the current implementation of value-added evaluation in primary school Chinese,and then explores the countermeasures to improve the effectiveness of value-added evaluation in primary school Chinese from the aspects of evaluation concept,evaluation content,evaluation method,evaluation subject,and application of evaluation results.The purpose is to provide strong support for the improvement of primary school Chinese teaching quality and the all-round development of students.展开更多
Maize value-added products play a crucial role in reducing post-harvest losses, enhancing food security, and generating income. While extensive research has focused on maize production in Cameroon, the exploration of ...Maize value-added products play a crucial role in reducing post-harvest losses, enhancing food security, and generating income. While extensive research has focused on maize production in Cameroon, the exploration of its value-added products and their profitability in the North-West Region remains underexplored. This study examined the profitability of maize value-added products in Mezam Division, with the objectives to: 1) identify various maize-based products, 2) assess the diversity of these products, 3) conduct a cost-benefit analysis of selected products, 4) examine the relationship between profitability and product diversity, and 5) identify key constraints impacting profitability. To achieve these objectives, structured questionnaires were administered to 500 small-scale maize entrepreneurs randomly selected from five subdivisions. Descriptive statistics were used to analyze objective 1 and 5, while the Shannon Diversity Index was employed to assess product diversity. Additionally, a cost-benefit analysis was conducted on four selected products namely pap, parched corn, peeled parboiled corn, and corn beer, and a correlation analysis was used to examine objective 4. In total, 13 maize value-added products were identified, with a diversity index of 4.4. The total cost of processing the four selected products per entrepreneur using 18 kg of maize per product was FCFA 83631.5 (US $132.75), while the total revenue was FCFA 121864.5 (US $193.43), resulting in an economic profit of FCFA 38,233 (US $60.69). Pap emerged as the most profitable product, with an economic profit of FCFA 27,875 (US $44.24), while corn beer was the least profitable, with an economic profit of FCFA 2133.46 (US $3.39). The correlation analysis revealed a strong negative relationship between product diversity and profitability (r = −0.91), indicating that entrepreneurs can maximize profitability by focusing on a few high-demand products like pap and parched corn. Key constraints to profitability included fluctuating market prices, high production costs, limited access to finance, and inadequate storage facilities. Despite these challenges, our findings indicate that maize value addition is profitable in Mezam Division. Entrepreneurs can leverage this data for informed decision-making and future investments. It is recommended that the government promote maize value addition and provide financial support for modern processing equipment to boost profitability and income generation.展开更多
Electrochemical synthesis of value-added chemicals represents a promising approach to address multidisciplinary demands.This technology establishes direct pathways for electricity-to-chemical conversion while signific...Electrochemical synthesis of value-added chemicals represents a promising approach to address multidisciplinary demands.This technology establishes direct pathways for electricity-to-chemical conversion while significantly reducing the carbon footprint of chemical manufacturing.It simultaneously optimizes chemical energy storage and grid management,offering sustainable solutions for renewable energy utilization and overcoming geographical constraints in energy distribution.As a critical nexus between renewable energy and green chemistry,electrochemical synthesis serves dual roles in energy transformation and chemical production,emerging as a vital component in developing carbon-neutral circular economies.Focusing on key small molecules(H_(2)O,CO_(2),N_(2),O_(2)),this comment examines fundamental scientific challenges and practical barriers in electrocatalytic conversion processes,bridging laboratory innovations with industrial-scale implementation.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 visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions a...The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.展开更多
International trade research has long sought to investigate how manufacturers can upgrade within global value chains and escape the“low-end trap”.This paper examines how collaborative innovation can facilitate this ...International trade research has long sought to investigate how manufacturers can upgrade within global value chains and escape the“low-end trap”.This paper examines how collaborative innovation can facilitate this ascent,using an undirected weighted network of joint patent applications and firm-level data.By analyzing the network’s structural characteristics and its evolution,we explore the mechanisms through which collaboration drives the rise of manufacturing enterprises within global value chains.Our findings show that:(1)China’s rapidly expanding collaborative innovation network features a distinct“core-periphery”structure,with leading firms,universities,and government research institutions at its center.(2)By strengthening market power and enabling firms to take on more advanced production,collaborative innovation contributes to a higher domestic value-added rate in exports.(3)Heterogeneity analysis reveals that the impact of collaborative innovation on moving up the value chain is particularly evident for firms with strong production and technology absorption capabilities,those positioned lower in the value chain,and those facing fewer trade barriers.展开更多
基金supported by the National Natural Science Foundation of China(No.52436008)the Inner Mongolia Science and Technology Projects,China(Nos.JMRHZX20210003 and 2023YFCY0009)+3 种基金the Huaneng Group Co Ltd.,China(No.HNKJ23-H50)the National Natural Science Foundation of China(No.22408044)the China Postdoctoral Science Foundation(No.2024M761877)the National Key R&D Program of China(No.SQ2024YFD2200039)。
文摘The electromagnetic wave absorption of silicon carbide nanowires is improved by their uniform and diverse cross-structures.This study introduces a sustainable and high value-added method for synthesizing silicon carbide nanowires using lignite and waste silicon powder as raw materials through carbothermal reduction.The staggered structure of nanowires promotes the creation of interfacial polarization,impedance matching,and multiple loss mechanisms,leading to enhanced electromagnetic absorption performance.The silicon carbide nanowires demonstrate outstanding electromagnetic absorption capabilities with the minimum reflection loss of-48.09 d B at10.08 GHz and an effective absorption bandwidth(the reflection loss less than-10 d B)ranging from 8.54 to 16.68 GHz with a thickness of 2.17 mm.This research presents an innovative approach for utilizing solid waste in an environmentally friendly manner to produce broadband silicon carbide composite absorbers.
文摘1 General information Journal of Geographical Sciences is an international academic journal that publishes papers of the highest quality in physical geography, natural resources, environmental sciences, geographic information sciences, remote sensing and cartography. Manuscripts come from different parts of the world.
基金supported by National Natural Science Foundation of China(NSFC)under grant U23A20310.
文摘With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State Information(CSI)offers fine-grained temporal,frequency,and spatial insights into multipath propagation,making it a crucial data source for human-centric sensing.Recently,the integration of deep learning has significantly improved the robustness and automation of feature extraction from CSI in complex environments.This paper provides a comprehensive review of deep learning-enhanced human sensing based on CSI.We first outline mainstream CSI acquisition tools and their hardware specifications,then provide a detailed discussion of preprocessing methods such as denoising,time–frequency transformation,data segmentation,and augmentation.Subsequently,we categorize deep learning approaches according to sensing tasks—namely detection,localization,and recognition—and highlight representative models across application scenarios.Finally,we examine key challenges including domain generalization,multi-user interference,and limited data availability,and we propose future research directions involving lightweight model deployment,multimodal data fusion,and semantic-level sensing.
基金Under the auspices of National Natural Science Foundation of China(No.42330510)。
文摘With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration within urban spaces and serve as testbeds for exploring smart city planning and governance models.Information models facilitate the effective integration of technology into space.Building Information Modeling(BIM)and City Information Modeling(CIM)have been widely used in urban construction.However,the existing information models have limitations in the application of the park,so it is necessary to develop an information model suitable for the park.This paper first traces the evolution of park smart transformation,reviews the global landscape of smart park development,and identifies key trends and persistent challenges.Addressing the particularities of parks,the concept of Park Information Modeling(PIM)is proposed.PIM leverages smart technologies such as artificial intelligence,digital twins,and collaborative sensing to help form a‘space-technology-system’smart structure,enabling systematic management of diverse park spaces,addressing the deficiency in park-level information models,and aiming to achieve scale articulation between BIM and CIM.Finally,through a detailed top-level design application case study of the Nanjing Smart Education Park in China,this paper illustrates the translation process of the PIM concept into practice,showcasing its potential to provide smart management tools for park managers and enhance services for park stakeholders,although further empirical validation is required.
基金This paper is the research result of“Research on Innovation of Evidence-Based Teaching Paradigm in Vocational Education under the Background of New Quality Productivity”(2024JXQ176)the Shandong Province Artificial Intelligence Education Research Project(SDDJ202501035),which explores the application of artificial intelligence big models in student value-added evaluation from an evidence-based perspective。
文摘Based on the educational evaluation reform,this study explores the construction of an evidence-based value-added evaluation system based on data-driven,aiming to solve the limitations of traditional evaluation methods.The research adopts the method of combining theoretical analysis and practical application,and designs the evidence-based value-added evaluation framework,which includes the core elements of a multi-source heterogeneous data acquisition and processing system,a value-added evaluation agent based on a large model,and an evaluation implementation and application mechanism.Through empirical research verification,the evaluation system has remarkable effects in improving learning participation,promoting ability development,and supporting teaching decision-making,and provides a theoretical reference and practical path for educational evaluation reform in the new era.The research shows that the evidence-based value-added evaluation system based on data-driven can reflect students’actual progress more fairly and objectively by accurately measuring the difference in starting point and development range of students,and provide strong support for the realization of high-quality education development.
基金supported by the National Natural Science Foundation of China(62222212).
文摘Information extraction(IE)aims to automatically identify and extract information about specific interests from raw texts.Despite the abundance of solutions based on fine-tuning pretrained language models,IE in the context of fewshot and zero-shot scenarios remains highly challenging due to the scarcity of training data.Large language models(LLMs),on the other hand,can generalize well to unseen tasks with few-shot demonstrations or even zero-shot instructions and have demonstrated impressive ability for a wide range of natural language understanding or generation tasks.Nevertheless,it is unclear,whether such effectiveness can be replicated in the task of IE,where the target tasks involve specialized schema and quite abstractive entity or relation concepts.In this paper,we first examine the validity of LLMs in executing IE tasks with an established prompting strategy and further propose multiple types of augmented prompting methods,including the structured fundamental prompt(SFP),the structured interactive reasoning prompt(SIRP),and the voting-enabled structured interactive reasoning prompt(VESIRP).The experimental results demonstrate that while directly promotes inferior performance,the proposed augmented prompt methods significantly improve the extraction accuracy,achieving comparable or even better performance(e.g.,zero-shot FewNERD,FewNERD-INTRA)than state-of-theart methods that require large-scale training samples.This study represents a systematic exploration of employing instruction-following LLM for the task of IE.It not only establishes a performance benchmark for this novel paradigm but,more importantly,validates a practical technical pathway through the proposed prompt enhancement method,offering a viable solution for efficient IE in low-resource settings.
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.
基金National Natural Science Foundation of China(grant numbers 42293351,41877239,51422904 and 51379112).
文摘Advanced geological prediction is a crucial means to ensure safety and efficiency in tunnel construction.However,diff erent advanced geological forecasting methods have their own limitations,resulting in poor detection accuracy.Using multiple methods to carry out a comprehensive evaluation can eff ectively improve the accuracy of advanced geological prediction results.In this study,geological information is combined with the detection results of geophysical methods,including transient electromagnetic,induced polarization,and tunnel seismic prediction,to establish a comprehensive analysis method of adverse geology.First,the possible main adverse geological problems are determined according to the geological information.Subsequently,various physical parameters of the rock mass in front of the tunnel face can then be derived on the basis of multisource geophysical data.Finally,based on the analysis results of geological information,the multisource data fusion algorithm is used to determine the type,location,and scale of adverse geology.The advanced geological prediction results that can provide eff ective guidance for tunnel construction can then be obtained.
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.
基金Artificial Intelligence Education Research Project of Shandong Provincial Audio-Visual Education Center“Exploration of the Application of Large-scale AI Models in Student Value-added Evaluation from an Evidence-based Perspective”(SDDJ202501035)。
文摘Value-added evaluation focuses on individual student growth by tracking changes in academic performance,skills,literacy,etc.,at different time points.It weakens horizontal comparisons and emphasizes vertical progress to more fairly reflect educational effectiveness.This evaluation method is particularly suitable for vocational education,effectively motivating students’learning enthusiasm and enhancing their self-confidence.Foreign research is represented by the Tennessee Value-Added Assessment System(TVAAS),widely used in evaluating school quality and teacher performance.Domestic research currently focuses on the theoretical construction,model establishment,optimization,and practical application of value-added evaluation,still facing significant challenges in data collection comprehensiveness and model adaptability.Aiming at current issues,this study focuses on exploring the application of artificial intelligence large models in student value-added evaluation from an evidence-based perspective,committed to constructing an innovative evidence-based value-added evaluation system.It aims to achieve precise assessment of students’learning effect“net value-added”through multi-source data collection,intelligent analysis,and personalized feedback.The system integrates outcome evaluation,process evaluation,value-added evaluation,and comprehensive evaluation to form a“four-in-one”dynamic evaluation framework,considering students’starting points,process performance,and final achievements.In the future,value-added evaluation needs to further expand the assessment of non-academic dimensions(such as professional literacy and social-emotional skills)and explore the application of non-linear models to promote the deepening and innovation of educational evaluation reform.
基金Shandong Provincial Education and Teaching Research Topic“Research on Student Value-Added Evaluation for Promoting Deep Learning”(2023JXY500)。
文摘As the enlightenment stage of students’Chinese learning,primary school Chinese education plays a key role in cultivating students’language ability,thinking development,and humanistic literacy.Value-added evaluation,as an evaluation method that focuses on the changes in students’individual development and attaches importance to the learning process,has gradually attracted attention in the application of primary school Chinese education.This paper first analyzes the problems existing in the current implementation of value-added evaluation in primary school Chinese,and then explores the countermeasures to improve the effectiveness of value-added evaluation in primary school Chinese from the aspects of evaluation concept,evaluation content,evaluation method,evaluation subject,and application of evaluation results.The purpose is to provide strong support for the improvement of primary school Chinese teaching quality and the all-round development of students.
文摘Maize value-added products play a crucial role in reducing post-harvest losses, enhancing food security, and generating income. While extensive research has focused on maize production in Cameroon, the exploration of its value-added products and their profitability in the North-West Region remains underexplored. This study examined the profitability of maize value-added products in Mezam Division, with the objectives to: 1) identify various maize-based products, 2) assess the diversity of these products, 3) conduct a cost-benefit analysis of selected products, 4) examine the relationship between profitability and product diversity, and 5) identify key constraints impacting profitability. To achieve these objectives, structured questionnaires were administered to 500 small-scale maize entrepreneurs randomly selected from five subdivisions. Descriptive statistics were used to analyze objective 1 and 5, while the Shannon Diversity Index was employed to assess product diversity. Additionally, a cost-benefit analysis was conducted on four selected products namely pap, parched corn, peeled parboiled corn, and corn beer, and a correlation analysis was used to examine objective 4. In total, 13 maize value-added products were identified, with a diversity index of 4.4. The total cost of processing the four selected products per entrepreneur using 18 kg of maize per product was FCFA 83631.5 (US $132.75), while the total revenue was FCFA 121864.5 (US $193.43), resulting in an economic profit of FCFA 38,233 (US $60.69). Pap emerged as the most profitable product, with an economic profit of FCFA 27,875 (US $44.24), while corn beer was the least profitable, with an economic profit of FCFA 2133.46 (US $3.39). The correlation analysis revealed a strong negative relationship between product diversity and profitability (r = −0.91), indicating that entrepreneurs can maximize profitability by focusing on a few high-demand products like pap and parched corn. Key constraints to profitability included fluctuating market prices, high production costs, limited access to finance, and inadequate storage facilities. Despite these challenges, our findings indicate that maize value addition is profitable in Mezam Division. Entrepreneurs can leverage this data for informed decision-making and future investments. It is recommended that the government promote maize value addition and provide financial support for modern processing equipment to boost profitability and income generation.
文摘Electrochemical synthesis of value-added chemicals represents a promising approach to address multidisciplinary demands.This technology establishes direct pathways for electricity-to-chemical conversion while significantly reducing the carbon footprint of chemical manufacturing.It simultaneously optimizes chemical energy storage and grid management,offering sustainable solutions for renewable energy utilization and overcoming geographical constraints in energy distribution.As a critical nexus between renewable energy and green chemistry,electrochemical synthesis serves dual roles in energy transformation and chemical production,emerging as a vital component in developing carbon-neutral circular economies.Focusing on key small molecules(H_(2)O,CO_(2),N_(2),O_(2)),this comment examines fundamental scientific challenges and practical barriers in electrocatalytic conversion processes,bridging laboratory innovations with industrial-scale implementation.
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supported by the National Natural Science(No.U19A2063)the Jilin Provincial Development Program of Science and Technology (No.20230201080GX)the Jilin Province Education Department Scientific Research Project (No.JJKH20230851KJ)。
文摘The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.
基金supported by the National Social Science Fund of China(NSSFC)“Research on Collaborative Innovation and Global Value Chain Upgrading in Manufacturing”(Grant No.23CJL019)“Research on the Advantages of Ultra-Large-Scale Market and the Construction of Modern Industrial System”(Grant No.23&ZD041).
文摘International trade research has long sought to investigate how manufacturers can upgrade within global value chains and escape the“low-end trap”.This paper examines how collaborative innovation can facilitate this ascent,using an undirected weighted network of joint patent applications and firm-level data.By analyzing the network’s structural characteristics and its evolution,we explore the mechanisms through which collaboration drives the rise of manufacturing enterprises within global value chains.Our findings show that:(1)China’s rapidly expanding collaborative innovation network features a distinct“core-periphery”structure,with leading firms,universities,and government research institutions at its center.(2)By strengthening market power and enabling firms to take on more advanced production,collaborative innovation contributes to a higher domestic value-added rate in exports.(3)Heterogeneity analysis reveals that the impact of collaborative innovation on moving up the value chain is particularly evident for firms with strong production and technology absorption capabilities,those positioned lower in the value chain,and those facing fewer trade barriers.
