With the rapid development of electric vehicles,the requirements for charging stations are getting higher and higher.In this study,we constructed a charging station topology network inNanjing through the Space-L metho...With the rapid development of electric vehicles,the requirements for charging stations are getting higher and higher.In this study,we constructed a charging station topology network inNanjing through the Space-L method,mapping charging stations as network nodes and constructing edges through road relationships.The experiment introduced five EV charging recommendation strategies(based on distance,number of fast charging piles,user preference,price,and overall rating)used to simulate disordered charging caused by different user preferences,and the impact of the networkdynamic robustness in case of node failure is exploredby simulating the load-capacity cascade failure model.In this paper,two important metrics for evaluating network robustness are selected:the relative size of the maximum connected subgraph and the network efficiency.The experimental results point out that in the price recommendation strategy,the network stability significantly decreases when the node failure ratio reaches 75.4%,while the fast charging quantity recommendation strategy significantly decreases when the node failure ratio is 62.3%.Therefore,the robustness of the charging station network is best under the price recommendation,while the network robustness is poor under the fast charging quantity recommendation.While the network robustness is poor under preference recommendation.Based on this finding,this study particularly emphasizes that in the process of improving the robustness of the charging station network,it is necessary to comprehensively consider the market demand and guide users to charge in an orderly manner by reasonably adjusting the price strategy.This strategy not only effectively prevents network stability problems that may result fromdisorderly charging behavior,but also enhances the ability of the charging network to resist node failure and improves the overall dynamic robustness of the network.展开更多
The rapid development of short video platforms poses new challenges for traditional recommendation systems.Recommender systems typically depend on two types of user behavior feedback to construct user interest profile...The rapid development of short video platforms poses new challenges for traditional recommendation systems.Recommender systems typically depend on two types of user behavior feedback to construct user interest profiles:explicit feedback(interactive behavior),which significantly influences users’short-term interests,and implicit feedback(viewing time),which substantially affects their long-term interests.However,the previous model fails to distinguish between these two feedback methods,leading it to predict only the overall preferences of users based on extensive historical behavior sequences.Consequently,it cannot differentiate between users’long-term and shortterm interests,resulting in low accuracy in describing users’interest states and predicting the evolution of their interests.This paper introduces a video recommendationmodel calledCAT-MFRec(CrossAttention Transformer-Mixed Feedback Recommendation)designed to differentiate between explicit and implicit user feedback within the DIEN(Deep Interest Evolution Network)framework.This study emphasizes the separate learning of the two types of behavioral feedback,effectively integrating them through the cross-attention mechanism.Additionally,it leverages the long sequence dependence capabilities of Transformer technology to accurately construct user interest profiles and predict the evolution of user interests.Experimental results indicate that CAT-MF Rec significantly outperforms existing recommendation methods across various performance indicators.This advancement offers new theoretical and practical insights for the development of video recommendations,particularly in addressing complex and dynamic user behavior patterns.展开更多
In the Internet era,recommendation systems play a crucial role in helping users find relevant information from large datasets.Class imbalance is known to severely affect data quality,and therefore reduce the performan...In the Internet era,recommendation systems play a crucial role in helping users find relevant information from large datasets.Class imbalance is known to severely affect data quality,and therefore reduce the performance of recommendation systems.Due to the imbalance,machine learning algorithms tend to classify inputs into the positive(majority)class every time to achieve high prediction accuracy.Imbalance can be categorized such as by features and classes,but most studies consider only class imbalance.In this paper,we propose a recommendation system that can integrate multiple networks to adapt to a large number of imbalanced features and can deal with highly skewed and imbalanced datasets through a loss function.We propose a loss aware feature attention mechanism(LAFAM)to solve the issue of feature imbalance.The network incorporates an attention mechanism and uses multiple sub-networks to classify and learn features.For better results,the network can learn the weights of sub-networks and assign higher weights to important features.We propose suppression loss to address class imbalance,which favors negative loss by penalizing positive loss,and pays more attention to sample points near the decision boundary.Experiments on two large-scale datasets verify that the performance of the proposed system is greatly improved compared to baseline methods.展开更多
Citrus is an important commercial crop in Uganda, especially the Eastern region. However, in spite of the increasing regional demand, citrus productivity is still low, attributed to pest and diseases, soil moisture st...Citrus is an important commercial crop in Uganda, especially the Eastern region. However, in spite of the increasing regional demand, citrus productivity is still low, attributed to pest and diseases, soil moisture stress, and low soil fertility, among others. Efforts to improve soil fertility are limited by inadequate supply of organic fertilizers due to competing demands. In addition, there is inadequate information on inorganic fertilizer requirements for citrus production in Uganda. The objective of this study was to develop optimum fertilizer recommendations for citrus production for Eastern Uganda. The study was conducted in Teso region, Eastern Uganda. Fertilizer (NPK, 17:17:17) was randomly applied to Hamlin, Valencia and Washington varieties with fertilizer and variety factorially arranged for each farm and citrus age range, replicated three times. Fertilizer rates were 0, 139, 278 and 556 kg NPK/ha for the 4 - 7-year old trees, and 0, 278, 556 and 1111 kg NPK/ha for the mature (8 years and above) trees. For a given variety, each fertilizer rate was applied onto three representative trees per farmer, six farmers per district. Results showed that yields and net profits were highest for variety Hamlin, and nearly the same for varieties Washington and Valencia. Fertilizer application increased fruit yield and profits for both the 4 to 7-year and 8 and above-year-old trees, with highest yield and profitability values observed at 556 kg NPK/ha. These results suggest applying 556 kg NPK/ha to citrus per year as an optimum fertilizer rate for citrus production in Teso region. The fertilizer should be applied in smaller splits of 800, 600, and 600 grams per tree, applied in April, June, and August.展开更多
A survey conducted on the premature bolting of Huarong large leaf mustard from 2018 to 2024 revealed that Huarong large leaf mustard sown in middle August was associated with a higher propensity for premature bolting....A survey conducted on the premature bolting of Huarong large leaf mustard from 2018 to 2024 revealed that Huarong large leaf mustard sown in middle August was associated with a higher propensity for premature bolting. Furthermore, it was observed that the earlier being sown, the greater the rate of premature bolting when being sown prior to middle August. The rate of premature bolting observed in seedlings sown on August 8 was recorded at 35.6%. It was noted that as the age of the seedlings increased, the rate of premature bolting correspondingly increased. There were notable differences in the tolerance of various cultivars to elevated temperatures and prolonged sunlight exposure. For instance, cultivars such as Zhangjie 1 and Sichuan Shaguodi, which exhibit greater heat resistance, did not demonstrate premature bolting when sown in early August. The prolonged exposure to elevated temperatures, drought conditions, and extended periods of sunlight during the seedling stage of Huarong large leaf mustard, coupled with delayed irrigation and transplantation, contributed to the occurrence of premature bolting. The Huarong large leaf mustard, when been sown from late August to early September and transplanted at the appropriate time, exhibited normal growth and development, with no instances of premature bolting observed. It is advisable to select heat-resistant varieties, such as Zhangjie 1, prior to middle August. Huarong large leaf mustard should be sown in early to middle September. Additionally, it is essential to ensure centralized production and timely release of seeds, prompt transplantation and harvesting, and enhance the management of pests and diseases.展开更多
This study presents a new approach that advances the algorithm of similarity measures between generalized fuzzy numbers. Following a brief introduction to some properties of the proposed method, a comparative analysis...This study presents a new approach that advances the algorithm of similarity measures between generalized fuzzy numbers. Following a brief introduction to some properties of the proposed method, a comparative analysis based on 36 sets of generalized fuzzy numbers was performed, in which the degree of similarity of the fuzzy numbers was calculated with the proposed method and seven methods established by previous studies in the literature. The results of the analytical comparison show that the proposed similarity outperforms the existing methods by overcoming their drawbacks and yielding accurate outcomes in all calculations of similarity measures under consideration. Finally, in a numerical example that involves recommending cars to customers based on a nine-member linguistic term set, the proposed similarity measure proves to be competent in addressing fuzzy number recommendation problems.展开更多
This paper examines the impact of algorithmic recommendations and data-driven marketing on consumer engagement and business performance.By leveraging large volumes of user data,businesses can deliver personalized cont...This paper examines the impact of algorithmic recommendations and data-driven marketing on consumer engagement and business performance.By leveraging large volumes of user data,businesses can deliver personalized content that enhances user experiences and increases conversion rates.However,the growing reliance on these technologies introduces significant risks,including privacy violations,algorithmic bias,and ethical concerns.This paper explores these challenges and provides recommendations for businesses to mitigate associated risks while optimizing marketing strategies.It highlights the importance of transparency,fairness,and user control in ensuring responsible and effective data-driven marketing.展开更多
This study employs causal inference methods to analyze user behavior on short-video platforms,examining how content characteristics,algorithmic recommendations,and social networks impact engagement.Using Propensity Sc...This study employs causal inference methods to analyze user behavior on short-video platforms,examining how content characteristics,algorithmic recommendations,and social networks impact engagement.Using Propensity Score Matching(PSM),Regression Discontinuity Design(RDD),and Instrumental Variables(IV),findings indicate that algorithmic promotion significantly boosts content diffusion,emotionally charged content is more shareable than neutral content,and influencer interactions increase visibility by 80%.The study shows that platform algorithms shape both information flow and group psychology.The results offer insights for social media marketing,public opinion management,and digital governance,with policy recommendations for content diversity,platform transparency,and algorithm fairness.展开更多
Current guidelines for treating asymptomatic common bile duct stones(CBDS)recommend stone removal,with endoscopic retrograde cholangiopan-creatography(ERCP)being the first treatment choice.When deciding on ERCP treatm...Current guidelines for treating asymptomatic common bile duct stones(CBDS)recommend stone removal,with endoscopic retrograde cholangiopan-creatography(ERCP)being the first treatment choice.When deciding on ERCP treatment for asymptomatic CBDS,the risk of ERCP-related complications and outcome of natural history of asymptomatic CBDS should be compared.The incidence rate of ERCP-related complications,particularly of post-ERCP pancreatitis for asymptomatic CBDS,was reportedly higher than that of symptomatic CBDS,increasing the risk of ERCP-related complications for asymptomatic CBDS compared with that previously reported for biliopancreatic diseases.Although studies have reported short-to middle-term outcomes of natural history of asymptomatic CBDS,its long-term natural history is not well known.Till date,there are no prospective studies that determined whether ERCP has a better outcome than no treatment in patients with asymptomatic CBDS or not.No randomized controlled trial has evaluated the risk of early and late ERCP-related complications vs the risk of biliary complications in the wait-and-see approach,suggesting that a change is needed in our perspective on endoscopic treatment for asymptomatic CBDS.Further studies examining long-term complication risks of ERCP and wait-and-see groups for asymptomatic CBDS are warranted to discuss whether routine endoscopic treatment for asymptomatic CBDS is justified or not.展开更多
From the view of both objective and subjective factors,the indoor air quality(IAQ)evaluation was considered.Carbon dioxide(CO2)and formaldehyde(HCHO)were selected as the typical contaminants of indoor air,and the eval...From the view of both objective and subjective factors,the indoor air quality(IAQ)evaluation was considered.Carbon dioxide(CO2)and formaldehyde(HCHO)were selected as the typical contaminants of indoor air,and the evaluation method of logarithmic index was adopted as the evaluation means of IAQ.Then the recommended limits(RL)of typical contaminants CO2 and HCHO were given through analysis and calculation.The limits of CO2 and HCHO in Indoor Air Quality Standard of China or other existing standards probably correspond to the level of PD=25(%).The result shows that the existing standards fail to meet the requirement of the definition of "acceptable indoor air quality",that is to say,less than 20% of the people express dissatisfaction.When PD=20%,RL of CO2 and HCHO are 728×10-6 and 0.068×10-6 respectively,which are stricter than the limits in the existing standards.The method proposed in this paper is applicable to 13.1%≤PD≤86.7%.展开更多
Objective To explore the possible preventive mechanism of Hunan expert group recommended Chinese medicine prescription of No.2(Pre-No.2)against coronavirus disease 2019(COVID-19)by network pharmacology method.Methods ...Objective To explore the possible preventive mechanism of Hunan expert group recommended Chinese medicine prescription of No.2(Pre-No.2)against coronavirus disease 2019(COVID-19)by network pharmacology method.Methods The target proteins of effective components and active compounds in Pre-No.2 were screened by searching the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP).A component-target-disease interaction network of Pre-No.2 was constructed by Cytoscape 3.7.2,gene ontology(GO)analysis,and Kyoto encyclopedia of genes and genomes(KEGG)analysis of target protein pathway by DAVID.Results A total of 163 compounds and 278 target protein targets in Pre-No.2 were collected from the TCMSP database.Kaempferol,wogonin,7-methoxy-2-methyl isoflavone,formononetin,isorhamnetin,and licochalcone A were the most frequent targets in the regulatory network.GO enrichment analysis showed that Pre-No.2 regulated response to virus,viral processes,humoral immune responses,defense responses to virus and viral entry into host cells.KEGG enrichment analysis showed that the formula regulated the NF-κB signaling pathway,B cell receptor signaling pathway,viral carcinogenesis,T cell signaling pathway and FcγR-mediated phagocytosis signaling pathway.Conclusions Pre-No.2 may play a preventive role against COVID-19 through regulation of the Toll-like signaling,T cell signaling,B cell signaling and other signaling pathways.It may regulate the immune system to protect against anti-influenza virus.展开更多
Book 1: (Editor-in-Chief: Shi Yafeng; Published by Elsevier and Science Press Beijing in 2008, 539 pages) Glaciers and Related Environments in China Since the professional institution for glaciology attached to the Ch...Book 1: (Editor-in-Chief: Shi Yafeng; Published by Elsevier and Science Press Beijing in 2008, 539 pages) Glaciers and Related Environments in China Since the professional institution for glaciology attached to the Chinese Academy of Sciences was established in 1958, studies of glaciers in alpine regions, and of Quaternary glaciations throughout展开更多
Closer sino-African relations have encouraged more Chinese enterprises to invest in African countries.Statistics show that more than 2,000 Chinese enterprises had invested in the continent by 2012.
The response of rice to N fertilizer applicationhas shown that high rates of N application donot always ensure a proportional increase inyield due to high N losses. A model, ORYZA-0 was developed by ten Berge for desi...The response of rice to N fertilizer applicationhas shown that high rates of N application donot always ensure a proportional increase inyield due to high N losses. A model, ORYZA-0 was developed by ten Berge for designingoptimum N fertilizer management strategy inrice. We evaluated the performance ofORYZA-0 in Jinhua, Zhejiang Province. ORYZA-0 includes N uptakes, partition-ing of N among the organs, and utilization ofleaf N in converting solar energy to dry mat-ter. It can predict the amount and time of Nfertilizer application to achieve a maximumbiomass or yield combining with Price algo-rithm optimization procedure.展开更多
With the rapid growth of manuscript submissions,finding eligible reviewers for every submission has become a heavy task.Recommender systems are powerful tools developed in computer science and information science to d...With the rapid growth of manuscript submissions,finding eligible reviewers for every submission has become a heavy task.Recommender systems are powerful tools developed in computer science and information science to deal with this problem.However,most existing approaches resort to text mining techniques to match manuscripts with potential reviewers,which require high-quality textual information to perform well.In this paper,we propose a reviewer recommendation algorithm based on a network diffusion process on a scholar-paper multilayer network,with no requirement for textual information.The network incorporates the relationship of scholar-paper pairs,the collaboration among scholars,and the bibliographic coupling among papers.Experimental results show that our proposed algorithm outperforms other state-of-the-art recommendation methods that use graph random walk and matrix factorization and methods that use machine learning and natural language processing,with improvements of over 7.62%in recall,5.66%in hit rate,and 47.53%in ranking score.Our work sheds light on the effectiveness of multilayer network diffusion-based methods in the reviewer recommendation problem,which will help to facilitate the peer-review process and promote information retrieval research in other practical scenes.展开更多
Users’interests are often diverse and multi-grained,with their underlying intents even more so.Effectively captur-ing users’interests and uncovering the relationships between diverse interests are key to news recomm...Users’interests are often diverse and multi-grained,with their underlying intents even more so.Effectively captur-ing users’interests and uncovering the relationships between diverse interests are key to news recommendation.Meanwhile,diversity is an important metric for evaluating news recommendation algorithms,as users tend to reject excessive homogeneous information in their recommendation lists.However,recommendation models themselves lack diversity awareness,making it challenging to achieve a good balance between the accuracy and diversity of news recommendations.In this paper,we propose a news recommendation algorithm that achieves good performance in both accuracy and diversity.Unlike most existing works that solely optimize accuracy or employ more features to meet diversity,the proposed algorithm leverages the diversity-aware capability of the model.First,we introduce an augmented user model to fully capture user intent and the behavioral guidance they might undergo as a result.Specifically,we focus on the relationship between the original clicked news and the augmented clicked news.Moreover,we propose an effective adversarial training method for diversity(AT4D),which is a pluggable component that can enhance both the accuracy and diversity of news recommendation results.Extensive experiments on real-world datasets confirm the efficacy of the proposed algorithm in improving both the accuracy and diversity of news recommendations.展开更多
Background:The period following pregnancy is a critical time window when future habits with respect to physical activity(PA) and sedentary behavior(SB) are established;therefore,it warrants guidance.The purpose of thi...Background:The period following pregnancy is a critical time window when future habits with respect to physical activity(PA) and sedentary behavior(SB) are established;therefore,it warrants guidance.The purpose of this scoping review was to summarize public health-oriented country-specific postpartum PA and SB guidelines worldwide.Methods:To identity guidelines published since 2010,we performed a(a) systematic search of 4 databases(CINAHL,Global Health,PubMed,and SPORTDiscus),(b) structured repeatable web-based search separately for 194 countries,and(c) separate web-based search.Only the most recent guideline was included for each country.Results:We identified 22 countries with public health-oriented postpartum guidelines for PA and 11 countries with SB guidelines.The continents with guidelines included Europe(n=12),Asia(n=5),Oceania(n=2),Africa(n=1),North America(n=1),and South America(n=1).The most common benefits recorded for PA included weight control/management(n=10),reducing the risk of postpartum depression or depressive symptoms(n=9),and improving mood/well-being(n=8).Postpartum guidelines specified exercises to engage in,including pelvic floor exercises(n=17);muscle strengthening,weight training,or resistance exercises(n=13);aerobics/general aerobic activity(n=13);walking(n=11);cycling(n=9);and swimming(n=9).Eleven guidelines remarked on the interaction between PA and breastfeeding;several guidelines stated that PA did not impact breast milk quantity(n=7),breast milk quality(n=6),or infant growth(n=3).For SB,suggestions included limiting long-term sitting and interrupting sitting with PA.Conclusion:Country-specific postpartum guidelines for PA and SB can help promote healthy behaviors using a culturally appropriate context while providing specific guidance to public health practitioners.展开更多
More and more accounts or devices are shared by multiple users in video applications,which makes it difficult to provide recommendation service.Existing recommendation schemes overlook multiuser sharing scenarios,and ...More and more accounts or devices are shared by multiple users in video applications,which makes it difficult to provide recommendation service.Existing recommendation schemes overlook multiuser sharing scenarios,and they cannot make effective use of the mixed information generated by multi-user when exploring users’potential interests.To solve these problems,this paper proposes an adaptive program recommendation system for multi-user sharing environment.Specifically,we first design an offline periodic identification module by building multi-user features and periodically predicting target user in future sessions,which can separate the profile of target user from mixed log records.Subsequently,an online recommendation module with adaptive timevarying exploration strategy is constructed by jointly using personal information and multi-user social information provided by identification module.On one hand,to learn the dynamic changes in user-interest,a time-varying linear upper confidence bound(LinUCB)based on personal information is designed.On the other hand,to reduce the risk of exploration,a timeinvariant LinUCB based on separated multi-user social information from one account/device is proposed to compute the quality scores of programs for each user,which is integrated into the time-varying LinUCB by cross-weighting strategy.Finally,experimental results validate the efficiency of the proposed scheme.展开更多
Urban traffic control is a multifaceted and demanding task that necessitates extensive decision-making to ensure the safety and efficiency of urban transportation systems.Traditional approaches require traffic signal ...Urban traffic control is a multifaceted and demanding task that necessitates extensive decision-making to ensure the safety and efficiency of urban transportation systems.Traditional approaches require traffic signal professionals to manually intervene on traffic control devices at the intersection level,utilizing their knowledge and expertise.However,this process is cumbersome,labor-intensive,and cannot be applied on a large network scale.Recent studies have begun to explore the applicability of recommendation system for urban traffic control,which offer increased control efficiency and scalability.Such a decision recommendation system is complex,with various interdependent components,but a systematic literature review has not yet been conducted.In this work,we present an up-to-date survey that elucidates all the detailed components of a recommendation system for urban traffic control,demonstrates the utility and efficacy of such a system in the real world using data and knowledgedriven approaches,and discusses the current challenges and potential future directions of this field.展开更多
基金supported by the Jiangsu Science and Technology Think Tank Program(Youth)Project(JSKX24085)the Jiangsu Provincial College Students Innovation and Entrepreneurship Training Plan Project(202311276097Y).
文摘With the rapid development of electric vehicles,the requirements for charging stations are getting higher and higher.In this study,we constructed a charging station topology network inNanjing through the Space-L method,mapping charging stations as network nodes and constructing edges through road relationships.The experiment introduced five EV charging recommendation strategies(based on distance,number of fast charging piles,user preference,price,and overall rating)used to simulate disordered charging caused by different user preferences,and the impact of the networkdynamic robustness in case of node failure is exploredby simulating the load-capacity cascade failure model.In this paper,two important metrics for evaluating network robustness are selected:the relative size of the maximum connected subgraph and the network efficiency.The experimental results point out that in the price recommendation strategy,the network stability significantly decreases when the node failure ratio reaches 75.4%,while the fast charging quantity recommendation strategy significantly decreases when the node failure ratio is 62.3%.Therefore,the robustness of the charging station network is best under the price recommendation,while the network robustness is poor under the fast charging quantity recommendation.While the network robustness is poor under preference recommendation.Based on this finding,this study particularly emphasizes that in the process of improving the robustness of the charging station network,it is necessary to comprehensively consider the market demand and guide users to charge in an orderly manner by reasonably adjusting the price strategy.This strategy not only effectively prevents network stability problems that may result fromdisorderly charging behavior,but also enhances the ability of the charging network to resist node failure and improves the overall dynamic robustness of the network.
基金supported by National Natural Science Foundation of China(62072416)Key Research and Development Special Project of Henan Province(221111210500)Key TechnologiesR&DProgram of Henan rovince(232102211053,242102211071).
文摘The rapid development of short video platforms poses new challenges for traditional recommendation systems.Recommender systems typically depend on two types of user behavior feedback to construct user interest profiles:explicit feedback(interactive behavior),which significantly influences users’short-term interests,and implicit feedback(viewing time),which substantially affects their long-term interests.However,the previous model fails to distinguish between these two feedback methods,leading it to predict only the overall preferences of users based on extensive historical behavior sequences.Consequently,it cannot differentiate between users’long-term and shortterm interests,resulting in low accuracy in describing users’interest states and predicting the evolution of their interests.This paper introduces a video recommendationmodel calledCAT-MFRec(CrossAttention Transformer-Mixed Feedback Recommendation)designed to differentiate between explicit and implicit user feedback within the DIEN(Deep Interest Evolution Network)framework.This study emphasizes the separate learning of the two types of behavioral feedback,effectively integrating them through the cross-attention mechanism.Additionally,it leverages the long sequence dependence capabilities of Transformer technology to accurately construct user interest profiles and predict the evolution of user interests.Experimental results indicate that CAT-MF Rec significantly outperforms existing recommendation methods across various performance indicators.This advancement offers new theoretical and practical insights for the development of video recommendations,particularly in addressing complex and dynamic user behavior patterns.
基金supported by the National Key Research and Development Program of China(Grant numbers:2021YFF0901705,2021YFF0901700)the State Key Laboratory of Media Convergence and Communication,Communication University of China+1 种基金the Fundamental Research Funds for the Central Universitiesthe High-Quality and Cutting-Edge Disciplines Construction Project for Universities in Beijing(Internet Information,Communication University of China).
文摘In the Internet era,recommendation systems play a crucial role in helping users find relevant information from large datasets.Class imbalance is known to severely affect data quality,and therefore reduce the performance of recommendation systems.Due to the imbalance,machine learning algorithms tend to classify inputs into the positive(majority)class every time to achieve high prediction accuracy.Imbalance can be categorized such as by features and classes,but most studies consider only class imbalance.In this paper,we propose a recommendation system that can integrate multiple networks to adapt to a large number of imbalanced features and can deal with highly skewed and imbalanced datasets through a loss function.We propose a loss aware feature attention mechanism(LAFAM)to solve the issue of feature imbalance.The network incorporates an attention mechanism and uses multiple sub-networks to classify and learn features.For better results,the network can learn the weights of sub-networks and assign higher weights to important features.We propose suppression loss to address class imbalance,which favors negative loss by penalizing positive loss,and pays more attention to sample points near the decision boundary.Experiments on two large-scale datasets verify that the performance of the proposed system is greatly improved compared to baseline methods.
文摘Citrus is an important commercial crop in Uganda, especially the Eastern region. However, in spite of the increasing regional demand, citrus productivity is still low, attributed to pest and diseases, soil moisture stress, and low soil fertility, among others. Efforts to improve soil fertility are limited by inadequate supply of organic fertilizers due to competing demands. In addition, there is inadequate information on inorganic fertilizer requirements for citrus production in Uganda. The objective of this study was to develop optimum fertilizer recommendations for citrus production for Eastern Uganda. The study was conducted in Teso region, Eastern Uganda. Fertilizer (NPK, 17:17:17) was randomly applied to Hamlin, Valencia and Washington varieties with fertilizer and variety factorially arranged for each farm and citrus age range, replicated three times. Fertilizer rates were 0, 139, 278 and 556 kg NPK/ha for the 4 - 7-year old trees, and 0, 278, 556 and 1111 kg NPK/ha for the mature (8 years and above) trees. For a given variety, each fertilizer rate was applied onto three representative trees per farmer, six farmers per district. Results showed that yields and net profits were highest for variety Hamlin, and nearly the same for varieties Washington and Valencia. Fertilizer application increased fruit yield and profits for both the 4 to 7-year and 8 and above-year-old trees, with highest yield and profitability values observed at 556 kg NPK/ha. These results suggest applying 556 kg NPK/ha to citrus per year as an optimum fertilizer rate for citrus production in Teso region. The fertilizer should be applied in smaller splits of 800, 600, and 600 grams per tree, applied in April, June, and August.
基金Supported by Key R&D Projects of Hunan Provincial Department of Science and Technology"Study on Key Modern Processing Techniques and Product Development of Huarong Mustard"(2023NK2039).
文摘A survey conducted on the premature bolting of Huarong large leaf mustard from 2018 to 2024 revealed that Huarong large leaf mustard sown in middle August was associated with a higher propensity for premature bolting. Furthermore, it was observed that the earlier being sown, the greater the rate of premature bolting when being sown prior to middle August. The rate of premature bolting observed in seedlings sown on August 8 was recorded at 35.6%. It was noted that as the age of the seedlings increased, the rate of premature bolting correspondingly increased. There were notable differences in the tolerance of various cultivars to elevated temperatures and prolonged sunlight exposure. For instance, cultivars such as Zhangjie 1 and Sichuan Shaguodi, which exhibit greater heat resistance, did not demonstrate premature bolting when sown in early August. The prolonged exposure to elevated temperatures, drought conditions, and extended periods of sunlight during the seedling stage of Huarong large leaf mustard, coupled with delayed irrigation and transplantation, contributed to the occurrence of premature bolting. The Huarong large leaf mustard, when been sown from late August to early September and transplanted at the appropriate time, exhibited normal growth and development, with no instances of premature bolting observed. It is advisable to select heat-resistant varieties, such as Zhangjie 1, prior to middle August. Huarong large leaf mustard should be sown in early to middle September. Additionally, it is essential to ensure centralized production and timely release of seeds, prompt transplantation and harvesting, and enhance the management of pests and diseases.
文摘This study presents a new approach that advances the algorithm of similarity measures between generalized fuzzy numbers. Following a brief introduction to some properties of the proposed method, a comparative analysis based on 36 sets of generalized fuzzy numbers was performed, in which the degree of similarity of the fuzzy numbers was calculated with the proposed method and seven methods established by previous studies in the literature. The results of the analytical comparison show that the proposed similarity outperforms the existing methods by overcoming their drawbacks and yielding accurate outcomes in all calculations of similarity measures under consideration. Finally, in a numerical example that involves recommending cars to customers based on a nine-member linguistic term set, the proposed similarity measure proves to be competent in addressing fuzzy number recommendation problems.
文摘This paper examines the impact of algorithmic recommendations and data-driven marketing on consumer engagement and business performance.By leveraging large volumes of user data,businesses can deliver personalized content that enhances user experiences and increases conversion rates.However,the growing reliance on these technologies introduces significant risks,including privacy violations,algorithmic bias,and ethical concerns.This paper explores these challenges and provides recommendations for businesses to mitigate associated risks while optimizing marketing strategies.It highlights the importance of transparency,fairness,and user control in ensuring responsible and effective data-driven marketing.
文摘This study employs causal inference methods to analyze user behavior on short-video platforms,examining how content characteristics,algorithmic recommendations,and social networks impact engagement.Using Propensity Score Matching(PSM),Regression Discontinuity Design(RDD),and Instrumental Variables(IV),findings indicate that algorithmic promotion significantly boosts content diffusion,emotionally charged content is more shareable than neutral content,and influencer interactions increase visibility by 80%.The study shows that platform algorithms shape both information flow and group psychology.The results offer insights for social media marketing,public opinion management,and digital governance,with policy recommendations for content diversity,platform transparency,and algorithm fairness.
文摘Current guidelines for treating asymptomatic common bile duct stones(CBDS)recommend stone removal,with endoscopic retrograde cholangiopan-creatography(ERCP)being the first treatment choice.When deciding on ERCP treatment for asymptomatic CBDS,the risk of ERCP-related complications and outcome of natural history of asymptomatic CBDS should be compared.The incidence rate of ERCP-related complications,particularly of post-ERCP pancreatitis for asymptomatic CBDS,was reportedly higher than that of symptomatic CBDS,increasing the risk of ERCP-related complications for asymptomatic CBDS compared with that previously reported for biliopancreatic diseases.Although studies have reported short-to middle-term outcomes of natural history of asymptomatic CBDS,its long-term natural history is not well known.Till date,there are no prospective studies that determined whether ERCP has a better outcome than no treatment in patients with asymptomatic CBDS or not.No randomized controlled trial has evaluated the risk of early and late ERCP-related complications vs the risk of biliary complications in the wait-and-see approach,suggesting that a change is needed in our perspective on endoscopic treatment for asymptomatic CBDS.Further studies examining long-term complication risks of ERCP and wait-and-see groups for asymptomatic CBDS are warranted to discuss whether routine endoscopic treatment for asymptomatic CBDS is justified or not.
文摘From the view of both objective and subjective factors,the indoor air quality(IAQ)evaluation was considered.Carbon dioxide(CO2)and formaldehyde(HCHO)were selected as the typical contaminants of indoor air,and the evaluation method of logarithmic index was adopted as the evaluation means of IAQ.Then the recommended limits(RL)of typical contaminants CO2 and HCHO were given through analysis and calculation.The limits of CO2 and HCHO in Indoor Air Quality Standard of China or other existing standards probably correspond to the level of PD=25(%).The result shows that the existing standards fail to meet the requirement of the definition of "acceptable indoor air quality",that is to say,less than 20% of the people express dissatisfaction.When PD=20%,RL of CO2 and HCHO are 728×10-6 and 0.068×10-6 respectively,which are stricter than the limits in the existing standards.The method proposed in this paper is applicable to 13.1%≤PD≤86.7%.
基金funding support from the Scientific Research Fund of Hunan Administration of TCM(No.KYGG06,No.KYGG07)。
文摘Objective To explore the possible preventive mechanism of Hunan expert group recommended Chinese medicine prescription of No.2(Pre-No.2)against coronavirus disease 2019(COVID-19)by network pharmacology method.Methods The target proteins of effective components and active compounds in Pre-No.2 were screened by searching the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP).A component-target-disease interaction network of Pre-No.2 was constructed by Cytoscape 3.7.2,gene ontology(GO)analysis,and Kyoto encyclopedia of genes and genomes(KEGG)analysis of target protein pathway by DAVID.Results A total of 163 compounds and 278 target protein targets in Pre-No.2 were collected from the TCMSP database.Kaempferol,wogonin,7-methoxy-2-methyl isoflavone,formononetin,isorhamnetin,and licochalcone A were the most frequent targets in the regulatory network.GO enrichment analysis showed that Pre-No.2 regulated response to virus,viral processes,humoral immune responses,defense responses to virus and viral entry into host cells.KEGG enrichment analysis showed that the formula regulated the NF-κB signaling pathway,B cell receptor signaling pathway,viral carcinogenesis,T cell signaling pathway and FcγR-mediated phagocytosis signaling pathway.Conclusions Pre-No.2 may play a preventive role against COVID-19 through regulation of the Toll-like signaling,T cell signaling,B cell signaling and other signaling pathways.It may regulate the immune system to protect against anti-influenza virus.
文摘Book 1: (Editor-in-Chief: Shi Yafeng; Published by Elsevier and Science Press Beijing in 2008, 539 pages) Glaciers and Related Environments in China Since the professional institution for glaciology attached to the Chinese Academy of Sciences was established in 1958, studies of glaciers in alpine regions, and of Quaternary glaciations throughout
文摘Closer sino-African relations have encouraged more Chinese enterprises to invest in African countries.Statistics show that more than 2,000 Chinese enterprises had invested in the continent by 2012.
文摘The response of rice to N fertilizer applicationhas shown that high rates of N application donot always ensure a proportional increase inyield due to high N losses. A model, ORYZA-0 was developed by ten Berge for designingoptimum N fertilizer management strategy inrice. We evaluated the performance ofORYZA-0 in Jinhua, Zhejiang Province. ORYZA-0 includes N uptakes, partition-ing of N among the organs, and utilization ofleaf N in converting solar energy to dry mat-ter. It can predict the amount and time of Nfertilizer application to achieve a maximumbiomass or yield combining with Price algo-rithm optimization procedure.
基金Project supported by the National Natural Science Foundation of China(Grant No.T2293771)the New Cornerstone Science Foundation through the XPLORER PRIZE.
文摘With the rapid growth of manuscript submissions,finding eligible reviewers for every submission has become a heavy task.Recommender systems are powerful tools developed in computer science and information science to deal with this problem.However,most existing approaches resort to text mining techniques to match manuscripts with potential reviewers,which require high-quality textual information to perform well.In this paper,we propose a reviewer recommendation algorithm based on a network diffusion process on a scholar-paper multilayer network,with no requirement for textual information.The network incorporates the relationship of scholar-paper pairs,the collaboration among scholars,and the bibliographic coupling among papers.Experimental results show that our proposed algorithm outperforms other state-of-the-art recommendation methods that use graph random walk and matrix factorization and methods that use machine learning and natural language processing,with improvements of over 7.62%in recall,5.66%in hit rate,and 47.53%in ranking score.Our work sheds light on the effectiveness of multilayer network diffusion-based methods in the reviewer recommendation problem,which will help to facilitate the peer-review process and promote information retrieval research in other practical scenes.
基金This research was funded by Beijing Municipal Social Science Foundation(23YTB031)the Fundamental Research Funds for the Central Universities(CUC23ZDTJ005).
文摘Users’interests are often diverse and multi-grained,with their underlying intents even more so.Effectively captur-ing users’interests and uncovering the relationships between diverse interests are key to news recommendation.Meanwhile,diversity is an important metric for evaluating news recommendation algorithms,as users tend to reject excessive homogeneous information in their recommendation lists.However,recommendation models themselves lack diversity awareness,making it challenging to achieve a good balance between the accuracy and diversity of news recommendations.In this paper,we propose a news recommendation algorithm that achieves good performance in both accuracy and diversity.Unlike most existing works that solely optimize accuracy or employ more features to meet diversity,the proposed algorithm leverages the diversity-aware capability of the model.First,we introduce an augmented user model to fully capture user intent and the behavioral guidance they might undergo as a result.Specifically,we focus on the relationship between the original clicked news and the augmented clicked news.Moreover,we propose an effective adversarial training method for diversity(AT4D),which is a pluggable component that can enhance both the accuracy and diversity of news recommendation results.Extensive experiments on real-world datasets confirm the efficacy of the proposed algorithm in improving both the accuracy and diversity of news recommendations.
基金support by the National Institutes of Health (NIH),National Institute of Child Health and Human Development,award number T32 HD091058
文摘Background:The period following pregnancy is a critical time window when future habits with respect to physical activity(PA) and sedentary behavior(SB) are established;therefore,it warrants guidance.The purpose of this scoping review was to summarize public health-oriented country-specific postpartum PA and SB guidelines worldwide.Methods:To identity guidelines published since 2010,we performed a(a) systematic search of 4 databases(CINAHL,Global Health,PubMed,and SPORTDiscus),(b) structured repeatable web-based search separately for 194 countries,and(c) separate web-based search.Only the most recent guideline was included for each country.Results:We identified 22 countries with public health-oriented postpartum guidelines for PA and 11 countries with SB guidelines.The continents with guidelines included Europe(n=12),Asia(n=5),Oceania(n=2),Africa(n=1),North America(n=1),and South America(n=1).The most common benefits recorded for PA included weight control/management(n=10),reducing the risk of postpartum depression or depressive symptoms(n=9),and improving mood/well-being(n=8).Postpartum guidelines specified exercises to engage in,including pelvic floor exercises(n=17);muscle strengthening,weight training,or resistance exercises(n=13);aerobics/general aerobic activity(n=13);walking(n=11);cycling(n=9);and swimming(n=9).Eleven guidelines remarked on the interaction between PA and breastfeeding;several guidelines stated that PA did not impact breast milk quantity(n=7),breast milk quality(n=6),or infant growth(n=3).For SB,suggestions included limiting long-term sitting and interrupting sitting with PA.Conclusion:Country-specific postpartum guidelines for PA and SB can help promote healthy behaviors using a culturally appropriate context while providing specific guidance to public health practitioners.
基金supported by the National Natural Science Foundation of China(Grant No.62277032,62231017,62071254)Education Scientific Planning Project of Jiangsu Province(Grant No.B/2022/01/150)Jiangsu Provincial Qinglan Project,the Special Fund for Urban and Rural Construction and Development in Jiangsu Province.
文摘More and more accounts or devices are shared by multiple users in video applications,which makes it difficult to provide recommendation service.Existing recommendation schemes overlook multiuser sharing scenarios,and they cannot make effective use of the mixed information generated by multi-user when exploring users’potential interests.To solve these problems,this paper proposes an adaptive program recommendation system for multi-user sharing environment.Specifically,we first design an offline periodic identification module by building multi-user features and periodically predicting target user in future sessions,which can separate the profile of target user from mixed log records.Subsequently,an online recommendation module with adaptive timevarying exploration strategy is constructed by jointly using personal information and multi-user social information provided by identification module.On one hand,to learn the dynamic changes in user-interest,a time-varying linear upper confidence bound(LinUCB)based on personal information is designed.On the other hand,to reduce the risk of exploration,a timeinvariant LinUCB based on separated multi-user social information from one account/device is proposed to compute the quality scores of programs for each user,which is integrated into the time-varying LinUCB by cross-weighting strategy.Finally,experimental results validate the efficiency of the proposed scheme.
基金supported by the National Key Research and Development Program of China(2021YFB2900200)the Key Research and Development Program of Science and Technology Department of Zhejiang Province(2022C01121)Zhejiang Provincial Department of Transport Research Project(ZJXL-JTT-202223).
文摘Urban traffic control is a multifaceted and demanding task that necessitates extensive decision-making to ensure the safety and efficiency of urban transportation systems.Traditional approaches require traffic signal professionals to manually intervene on traffic control devices at the intersection level,utilizing their knowledge and expertise.However,this process is cumbersome,labor-intensive,and cannot be applied on a large network scale.Recent studies have begun to explore the applicability of recommendation system for urban traffic control,which offer increased control efficiency and scalability.Such a decision recommendation system is complex,with various interdependent components,but a systematic literature review has not yet been conducted.In this work,we present an up-to-date survey that elucidates all the detailed components of a recommendation system for urban traffic control,demonstrates the utility and efficacy of such a system in the real world using data and knowledgedriven approaches,and discusses the current challenges and potential future directions of this field.
