Automation of production in the nurseries of flower producing companies using barcode scanners have been attempted but with little success.Stationary laser barcode scanners which have been used for automation have fai...Automation of production in the nurseries of flower producing companies using barcode scanners have been attempted but with little success.Stationary laser barcode scanners which have been used for automation have failed due to the close proximity between the barcode and the scanner,and factors such as speed,angle of inclination of the barcode,damage to the barcode and dirt on the barcode.Furthermore,laser barcode scanners are still being used manually in the nurseries making work laborious and time consuming,which leading to reduced productivity.Therefore,an automated image-based barcode detection system to help solve the aforementioned problems was proposed.Experiments were conducted under different situations with clean and artificially soiled Code 128 barcodes in both the laboratory and under real production conditions in a flower producing company.The images were analyzed with a specific algorithm developed with the software tool Halcon.Overall the results from the company showed that the image-based system has a future prospect for automation in the nursery.展开更多
China is in a dominant position in apple production globally with both the largest apple growing area and the largest export of fresh apple fruits. However, the annual productivity of China＇s apple is significantly l...China is in a dominant position in apple production globally with both the largest apple growing area and the largest export of fresh apple fruits. However, the annual productivity of China＇s apple is significantly lower than that of other dominant apple producing countries. In addition, apple production is based on excessive application of chemical fertilizers and the nutrient use efficiency （especially nitrogen） is therefore low and the nutrient emissions to the environment are high. Apple production in China is considerably contributes to farmers＇ incomes and is important as export product. There is an urgent need to enhance apple productivity and improve nutrient use efficiencies in intensive apple production systems in the country. These can be attained by improved understanding of production potential, yield gaps, nutrient use and best management in apple orchards. To the end, priorities in research on apple production systems and required political support are described which may lead to more sustainable and environmental-friendly intensification of apple production in China.展开更多
Data curation is vital for selecting effective demonstration examples in graph-to-text generation.However,evaluating the quality ofKnowledgeGraphs(KGs)remains challenging.Prior research exhibits a narrowfocus on struc...Data curation is vital for selecting effective demonstration examples in graph-to-text generation.However,evaluating the quality ofKnowledgeGraphs(KGs)remains challenging.Prior research exhibits a narrowfocus on structural statistics,such as the shortest path length,while the correctness of graphs in representing the associated text is rarely explored.To address this gap,we introduce a dual-perspective evaluation framework for KG-text data,based on the computation of structural adequacy and semantic alignment.Froma structural perspective,we propose the Weighted Incremental EdgeMethod(WIEM)to quantify graph completeness by leveraging agreement between relation models to predict possible edges between entities.WIEM targets to find increments from models on“unseen links”,whose presence is inversely proportional to the structural adequacy of the original KG in representing the text.From a semantic perspective,we evaluate how well a KG aligns with the text in capturing the intended meaning.To do so,we instruct a large language model to convert KGs into natural language andmeasure the similarity between generated and reference texts.Based on these computations,we apply a Top-K union method,integrating the structural and semantic modules,to rank and select high-quality KGs.We evaluate our framework against various approaches for selecting few-shot examples in graph-to-text generation.Experiments on theAssociation for Computational LinguisticsAbstract Graph Dataset(ACL-AGD)and Automatic Content Extraction 05(ACE05)dataset demonstrate the effectiveness of our approach in distinguishing KG-text data of different qualities,evidenced by the largest performance gap between top-and bottom-ranked examples.We also find that the top examples selected through our dual-perspective framework consistently yield better performance than those selected by traditional measures.These results highlight the importance of data curation in improving graph-to-text generation.展开更多
Knowledge graphs convey precise semantic information that can be effectively interpreted by neural networks,and generating descriptive text based on these graphs places significant emphasis on content consistency.Howe...Knowledge graphs convey precise semantic information that can be effectively interpreted by neural networks,and generating descriptive text based on these graphs places significant emphasis on content consistency.However,knowledge graphs are inadequate for providing additional linguistic features such as paragraph structure and expressive modes,making it challenging to ensure content coherence in generating text that spans multiple sentences.This lack of coherence can further compromise the overall consistency of the content within a paragraph.In this work,we present the generation of scientific abstracts by leveraging knowledge graphs,with a focus on enhancing both content consistency and coherence.In particular,we construct the ACL Abstract Graph Dataset(ACL-AGD)which pairs knowledge graphs with text,incorporating sentence labels to guide text structure and diverse expressions.We then implement a Siamese network to complement and concretize the entities and relations based on paragraph structure by accomplishing two tasks:graph-to-text generation and entity alignment.Extensive experiments demonstrate that the logical paragraphs generated by our method exhibit entities with a uniform position distribution and appropriate frequency.In terms of content,our method accurately represents the information encoded in the knowledge graph,prevents the generation of irrelevant content,and achieves coherent and non-redundant adjacent sentences,even with a shared knowledge graph.展开更多
Background GOSSYM is a mechanistic,process-based cotton model that can simulate cotton crop growth and development,yield,and fiber quality.Its fiber quality module was developed based on controlled experiments explici...Background GOSSYM is a mechanistic,process-based cotton model that can simulate cotton crop growth and development,yield,and fiber quality.Its fiber quality module was developed based on controlled experiments explicitly conducted on the Texas Marker^(-1)(TM1)variety,potentially making its functional equations more aligned with this cultivar.To assess the model’s broader applicability,this study analyzed fiber quality data from 40 upland cotton cultivars,including TM1.The measured fiber quality from all cultivars was then compared with the modelsimulated fiber quality.Results Among the 40 upland cultivars,fiber strength varied from 28.4 cN·tex^(-1) to 34.6 cN·tex^(-1),fiber length ranged from 27.1 mm to 33.3 mm,micronaire value ranged from 2.7 to 4.6,and length uniformity index varied from 82.3%to 85.5%.The model simulated fiber quality closely matched the measured values for TM1,with the absolute percentage error(APE)being less than 0.92%for fiber strength,fiber length,and length uniformity index and 4.7%for micronaire.However,significant differences were observed for the other cultivars.The Pearson correlation coefficient(r)between the measured and simulated values was negative for all fiber quality traits,and Wilmotts’s index of agreement(WIA)was below 0.45,indicating a strong model bias toward TM1 without incorporating cultivar-specific parameters.After incorporating cultivar-specific parameters,the model’s performance improved significantly,with an average r-value of 0.84 and WIA of 0.88.Conclusions The adopted methodology and estimated cultivar-specific parameters improved the model’s simulation accuracy.This approach can be applied to newer cotton cultivars,enhancing the GOSSYM model’s utility and its applicability for agricultural management and policy decisions.展开更多
The widespread adoption of cloud computing has underscored the critical importance of efficient resource allocation and management, particularly in task scheduling, which involves assigning tasks to computing resource...The widespread adoption of cloud computing has underscored the critical importance of efficient resource allocation and management, particularly in task scheduling, which involves assigning tasks to computing resources for optimized resource utilization. Several meta-heuristic algorithms have shown effectiveness in task scheduling, among which the relatively recent Willow Catkin Optimization (WCO) algorithm has demonstrated potential, albeit with apparent needs for enhanced global search capability and convergence speed. To address these limitations of WCO in cloud computing task scheduling, this paper introduces an improved version termed the Advanced Willow Catkin Optimization (AWCO) algorithm. AWCO enhances the algorithm’s performance by augmenting its global search capability through a quasi-opposition-based learning strategy and accelerating its convergence speed via sinusoidal mapping. A comprehensive evaluation utilizing the CEC2014 benchmark suite, comprising 30 test functions, demonstrates that AWCO achieves superior optimization outcomes, surpassing conventional WCO and a range of established meta-heuristics. The proposed algorithm also considers trade-offs among the cost, makespan, and load balancing objectives. Experimental results of AWCO are compared with those obtained using the other meta-heuristics, illustrating that the proposed algorithm provides superior performance in task scheduling. The method offers a robust foundation for enhancing the utilization of cloud computing resources in the domain of task scheduling within a cloud computing environment.展开更多
An individual's mental health influences their capacity to think effectively,feel emotionally stable,and perform daily activities.As mental health concerns become more prevalent worldwide,new awareness and diagnos...An individual's mental health influences their capacity to think effectively,feel emotionally stable,and perform daily activities.As mental health concerns become more prevalent worldwide,new awareness and diagnostic and treatment tactics are needed.Digital tools and technology are helping solve these problems by providing scalable,tailored solutions for large populations.This detailed review examines mental health‐promoting internet tools.Smartphone applications,web‐based therapy systems,wearable tech,artificial intelligence‐powered resources,and virtual reality(VR)technologies were evaluated for efficacy and side effects.PubMed,PsycINFO,Scopus,IEEE Xplore,and Google Scholar were carefully searched.Search terms included“digital mental health tools,”“online therapy,”and“AI in mental health.”Randomized controlled trials,cohort studies,cross‐sectional studies,systematic reviews,and meta‐analyses of digital technology and mental health were included from among the literature published after 2010.Cognitive behavioral therapy methods,mood monitoring,and mindfulness exercises are among the numerous features of smartphone applications that have been demonstrated to mitigate symptoms of anxiety,depression,and tension.Online therapy platforms let marginalized individuals obtain therapy remotely.Wearable technology may detect heart rate,blood pressure,and sleep length,which may reveal mental health difficulties.Chatbots employ machine learning algorithms and natural language processing to deliver customized support and show promise for quick intervention.Exposure therapy for anxiety and trauma is increasingly using virtual reality environments.Although digital mental health therapies face challenges in relation to data privacy,limited long‐term efficacy,and technological inequality,digital technologies are modernizing mental healthcare.By offering inexpensive and effective alternatives to traditional therapies,digital technologies may help healthcare systems meet the growing demand for mental health services and overall well‐being.展开更多
A field experiment was conducted to evaluate the agronomic and physiological responses of rice under different water management systems, types of fertilizer and seedling age. This experiment was done at the farm of Ag...A field experiment was conducted to evaluate the agronomic and physiological responses of rice under different water management systems, types of fertilizer and seedling age. This experiment was done at the farm of Agri Park, College of Agriculture, Central Experimental Station (CES), Crop Science Cluster of the University of the Philippines Los Banos, College Laguna during 2013. The strip-split plot design with three replications was used with the two types of fertilizer (vermicompost and chemical fertilizer), water management (with and without standing water) and two seedling ages (10 and 14-d old) were the treatments in the experiment. Chemical fertilizer produced the highest grain yield, total dry matter (TDM), leaf area index (LAI), net assimilation rate (NAR) and crop growth rate (CGR). Most of these characters significantly increased in 10-d old seedlings with chemical fertilizer without standing water. The shorter phyllochron and higher root pulling resistance (RPR) were observed in 10-d old seedlings without standing water. For the variety NSIC Rc 216, the use of 10-d old seedlings grown without standing water with chemical fertilizer is the optimum conditions for the better growth and high productivity.展开更多
Two significant issues in Internet-based networked control systems （ INCSs）, transport performance of different protocols and security breach from Internet side, are investigated. First, for improving the performanc...Two significant issues in Internet-based networked control systems （ INCSs）, transport performance of different protocols and security breach from Internet side, are investigated. First, for improving the performance of data transmission, user datagram protocol （UDP） is adopted as the main stand for controllers and plants using INCSs. Second, a dual-channel secure transmission scheme （DCSTS）based on data transmission characteristics of INCSs is proposed, in which a raw UDP channel and a secure TCP （transmission control protocol） connection making use of SSL/TLS （secure sockets layer/transport layer security） are included. Further, a networked control protocol （NCP） at application layer for supporting DCSTS between the controllers and plants in INCSs is designed, and it also aims at providing a universal communication mechanism for interoperability of devices among the networked control laboratories in Beijing Institute of Technology of China, Central South University of China and Tokyo University of Technology of Japan. By means of a networked single-degree-of-free- dom robot arm, an INCS under the new protocol and security environment is created. Compared with systems such as IPSec or SSL/TLS, which may cause more than 91% network throughput deduction, the new DCSTS protocol may yield results ten times better, being just 5.67%.展开更多
The Integrated Agricultural Systems workgroup is examining agricultural systems of the US to determine fundamental principles that underlie successful production systems. Our hypothesis is that principles are applicab...The Integrated Agricultural Systems workgroup is examining agricultural systems of the US to determine fundamental principles that underlie successful production systems. Our hypothesis is that principles are applicable across regions, but key drivers interact to influence producer decisions and create distinct production systems. We interviewed agricultural producers to examine the underlying rationale for producer decisions and discern primary factors influencing production and marketing practices. While drivers are common among regions, interactions between drivers and influences on decision-makers vary substantially to create unique production systems. The internal social driver that values farming lifestyle is the principal factor that leads people to farming. The type of farming is partly a lifestyle choice and is influenced by other factors. Economic drivers and marketing options are primary drivers influencing production systems and management choices, as farmers provide an economic foundation for their families. While all producers employed strategies to manage production and marketing risks, these varied with different marketing channels. Identification of key drivers and principles can be used by producers, scientists and policy makers to direct agricultural production and agricultural research. New management systems can be developed that are flexible enough to respond to changing societal demands, and are environmentally and economically sustainable.展开更多
Road traffic safety can decrease when drivers drive in a low-visibility environment.The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means...Road traffic safety can decrease when drivers drive in a low-visibility environment.The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of accidents.To tackle the challenges posed by the low recognition accuracy and the substan-tial computational burden associated with current infrared pedestrian-vehicle detection methods,an infrared pedestrian-vehicle detection method A proposal is presented,based on an enhanced version of You Only Look Once version 5(YOLOv5).First,A head specifically designed for detecting small targets has been integrated into the model to make full use of shallow feature information to enhance the accuracy in detecting small targets.Second,the Focal Generalized Intersection over Union(GIoU)is employed as an alternative to the original loss function to address issues related to target overlap and category imbalance.Third,the distribution shift convolution optimization feature extraction operator is used to alleviate the computational burden of the model without significantly compromising detection accuracy.The test results of the improved algorithm show that its average accuracy(mAP)reaches 90.1%.Specifically,the Giga Floating Point Operations Per second(GFLOPs)of the improved algorithm is only 9.1.In contrast,the improved algorithms outperformed the other algorithms on similar GFLOPs,such as YOLOv6n(11.9),YOLOv8n(8.7),YOLOv7t(13.2)and YOLOv5s(16.0).The mAPs that are 4.4%,3%,3.5%,and 1.7%greater than those of these algorithms show that the improved algorithm achieves higher accuracy in target detection tasks under similar computational resource overhead.On the other hand,compared with other algorithms such as YOLOv8l(91.1%),YOLOv6l(89.5%),YOLOv7(90.8%),and YOLOv3(90.1%),the improved algorithm needs only 5.5%,2.3%,8.6%,and 2.3%,respectively,of the GFLOPs.The improved algorithm has shown significant advancements in balancing accuracy and computational efficiency,making it promising for practical use in resource-limited scenarios.展开更多
This study reviews the recent advances in data-driven polarimetric imaging technologies based on a wide range of practical applications.The widespread international research and activity in polarimetric imaging techni...This study reviews the recent advances in data-driven polarimetric imaging technologies based on a wide range of practical applications.The widespread international research and activity in polarimetric imaging techniques demonstrate their broad applications and interest.Polarization information is increasingly incorporated into convolutional neural networks(CNN)as a supplemental feature of objects to improve performance in computer vision task applications.Polarimetric imaging and deep learning can extract abundant information to address various challenges.Therefore,this article briefly reviews recent developments in data-driven polarimetric imaging,including polarimetric descattering,3D imaging,reflection removal,target detection,and biomedical imaging.Furthermore,we synthetically analyze the input,datasets,and loss functions and list the existing datasets and loss functions with an evaluation of their advantages and disadvantages.We also highlight the significance of data-driven polarimetric imaging in future research and development.展开更多
In a post-disaster environment characterized by frequent interruptions in communication links,traditional wireless communication networks are ineffective.Although the“store-carry-forward”mechanism characteristic of ...In a post-disaster environment characterized by frequent interruptions in communication links,traditional wireless communication networks are ineffective.Although the“store-carry-forward”mechanism characteristic of Delay Tolerant Networks(DTNs)can transmit data from Internet of things devices to more reliable base stations or data centres,it also suffers from inefficient data transmission and excessive transmission delays.To address these challenges,we propose an intelligent routing strategy based on node sociability for post-disaster emergency network scenarios.First,we introduce an intelligent routing strategy based on node intimacy,which selects more suitable relay nodes and assigns the corresponding number of message copies based on comprehensive utility values.Second,we present an intelligent routing strategy based on geographical location of nodes to forward message replicas secondarily based on transmission utility values.Finally,experiments demonstrate the effectiveness of our proposed algorithm in terms of message delivery rate,network cost ratio and average transmission delay.展开更多
The growth optimizer(GO)is an innovative and robust metaheuristic optimization algorithm designed to simulate the learning and reflective processes experienced by individuals as they mature within the social environme...The growth optimizer(GO)is an innovative and robust metaheuristic optimization algorithm designed to simulate the learning and reflective processes experienced by individuals as they mature within the social environment.However,the original GO algorithm is constrained by two significant limitations:slow convergence and high mem-ory requirements.This restricts its application to large-scale and complex problems.To address these problems,this paper proposes an innovative enhanced growth optimizer(eGO).In contrast to conventional population-based optimization algorithms,the eGO algorithm utilizes a probabilistic model,designated as the virtual population,which is capable of accurately replicating the behavior of actual populations while simultaneously reducing memory consumption.Furthermore,this paper introduces the Lévy flight mechanism,which enhances the diversity and flexibility of the search process,thus further improving the algorithm’s global search capability and convergence speed.To verify the effectiveness of the eGO algorithm,a series of experiments were conducted using the CEC2014 and CEC2017 test sets.The results demonstrate that the eGO algorithm outperforms the original GO algorithm and other compact algorithms regarding memory usage and convergence speed,thus exhibiting powerful optimization capabilities.Finally,the eGO algorithm was applied to image fusion.Through a comparative analysis with the existing PSO and GO algorithms and other compact algorithms,the eGO algorithm demonstrates superior performance in image fusion.展开更多
We have newly designed an electrostatic sensor,called an electric field mill(EFM),to simplify the estimation of the charge position and charge amount transferred by lightning discharges.It is necessary for this remote...We have newly designed an electrostatic sensor,called an electric field mill(EFM),to simplify the estimation of the charge position and charge amount transferred by lightning discharges.It is necessary for this remote estimation of the transferred charge to measure electric field changes caused by charge loss at the time of a lightning strike at multiple locations.For multiple-station measurement of electric field changes,not only speed but also phase for exposure and shielding of the sensing plates inside each EFM of the array should be synchronized to maintain the sensitivities of the deployed instruments.Currently,there is no such EFM with specified speed and phase control performance of the rotary part.Thus,we developed a new EFM in which the rotary mechanism was controlled consistently to within 3%error by a GPS module.Five EFMs had been distributed in the Hokuriku area of Japan during the winter season of 2022-2023 for a test observation.Here we describe the design and a simple calibration method for our new EFM array.Data analysis method based on the assumption of a simple monopole charge structure is also summarized.For validation,locations of assumed point charges were compared with three-dimensional lightning mapping data estimated by radio observations in the MF-HF bands.Initial results indicated the validity to estimate transferred charge amounts and positions of winter cloud-to-ground lightning discharges with our new EFM array.展开更多
Thermal processes are emerging as promising solutions to recovering phosphorus and other nutrient elements from anaerobic digestates.The feasibility of nutrient element recovery depends largely on the fates of nutrien...Thermal processes are emerging as promising solutions to recovering phosphorus and other nutrient elements from anaerobic digestates.The feasibility of nutrient element recovery depends largely on the fates of nutrient elements and heavy metals during thermal processing.This study assesses the partitioning of macronutrients(N,P,K,Na,Ca and Mg)and heavy metals(Zn,Cu,and Mn)between condensed and gaseous phases during thermal conversion of cattle slurry digestates in gas atmospheres of pyrolysis,combustion,and gasification processes.This study also assesses the chemical forms of macronutrients retained in combustion ashes.The partitioning of elements between condensed and gaseous phases was quantified by mass balances based on elemental analyses of char and ash residues.The char and ash residues were prepared in a fixed-bed,batch reactor at temperatures within the range 800-1000°C.Powder X-ray diffraction was used to identify the chemical forms of macronutrient elements in combustion ashes.Volatilisation of P was low(<20%)when the digestates were heated in inert and oxidising atmospheres,whereas a reducing atmosphere volatilized P to a major extent(~60%at 1000°C).Oxidising atmospheres increased volatilisation of N but suppressed volatilisation of K,Na,and Zn.Volatilisation of the following elements was low(<30%)in all investigated operating conditions:Ca,Mg,Mn,and Cu.The combustion ashes contained both high concentrations of P(around 7 w/w%)and acceptable concentrations of regulated heavy metals(Cu,and Zn)for application on agricultural and forest soils in Finland.Phosphorous was retained in the combustion ashes in the form of whitlockite.This form of P is expected to be available to plants when the ashes are added to soil.展开更多
Big data with its vast volume and complexity is increasingly concerned, developed and used for all professions and trades. Remote sensing, as one of the sources for big data, is generating earth-observation data and a...Big data with its vast volume and complexity is increasingly concerned, developed and used for all professions and trades. Remote sensing, as one of the sources for big data, is generating earth-observation data and analysis results daily from the platforms of satellites, manned/unmanned aircrafts, and ground-based structures. Agricultural remote sensing is one of the backbone technologies for precision agriculture, which considers within-field variability for site-specific management instead of uniform management as in traditional agriculture. The key of agricultural remote sensing is, with global positioning data and geographic information, to produce spatially-varied data for subsequent precision agricultural operations. Agricultural remote sensing data, as general remote sensing data, have all characteristics of big data. The acquisition, processing, storage, analysis and visualization of agricultural remote sensing big data are critical to the success of precision agriculture. This paper overviews available remote sensing data resources, recent development of technologies for remote sensing big data management, and remote sensing data processing and management for precision agriculture. A five-layer-fifteen- level （FLFL） satellite remote sensing data management structure is described and adapted to create a more appropriate four-layer-twelve-level （FLTL） remote sensing data management structure for management and applications of agricultural remote sensing big data for precision agriculture where the sensors are typically on high-resolution satellites, manned aircrafts, unmanned aerial vehicles and ground-based structures. The FLTL structure is the management and application framework of agricultural remote sensing big data for precision agriculture and local farm studies, which outlooks the future coordination of remote sensing big data management and applications at local regional and farm scale.展开更多
To investigate how the popular magnesium alloy AZ31 sheet(aluminum 3%,zinc 1%)behaves in cold working,deep drawing experiments at room temperature,along with finite element(FE)simulation,were performed on the cold for...To investigate how the popular magnesium alloy AZ31 sheet(aluminum 3%,zinc 1%)behaves in cold working,deep drawing experiments at room temperature,along with finite element(FE)simulation,were performed on the cold forming sheet of the AZ31 alloy after being annealed under various conditions.The activities were focused on the fracture pattern,limit drawing ratio(LDR),deformation load,thickness distribution,anisotropic effect,as well as the influences of the annealing conditions and tool configuration on them.The results display that punch shoulder radius instead of die clearance,has much influence on the thickness distribution.The anisotropy is remarkable in cold working,which adversely impacts the LDR.The fracture often happens on the side wall at an angle to axis of the deformed specimen.The results also imply that the LDR for the material under present experimental conditions is 1.72,and annealing the material at 450 ℃ for 1 h may be preferable for the cold deep drawing.展开更多
基金This project was part of the WeGa-Network(www.wega-online.org)funded by the German Federal Ministry of Education and Research.
文摘Automation of production in the nurseries of flower producing companies using barcode scanners have been attempted but with little success.Stationary laser barcode scanners which have been used for automation have failed due to the close proximity between the barcode and the scanner,and factors such as speed,angle of inclination of the barcode,damage to the barcode and dirt on the barcode.Furthermore,laser barcode scanners are still being used manually in the nurseries making work laborious and time consuming,which leading to reduced productivity.Therefore,an automated image-based barcode detection system to help solve the aforementioned problems was proposed.Experiments were conducted under different situations with clean and artificially soiled Code 128 barcodes in both the laboratory and under real production conditions in a flower producing company.The images were analyzed with a specific algorithm developed with the software tool Halcon.Overall the results from the company showed that the image-based system has a future prospect for automation in the nursery.
基金the project "Cash Crops Research Network of China" of the Center for Resources, Environment and Food Security, China Agricultural UniversityProfessor Oene Oenema from Alterra Wageningnen University, the Netherlands, for his financial support of the research
文摘China is in a dominant position in apple production globally with both the largest apple growing area and the largest export of fresh apple fruits. However, the annual productivity of China＇s apple is significantly lower than that of other dominant apple producing countries. In addition, apple production is based on excessive application of chemical fertilizers and the nutrient use efficiency （especially nitrogen） is therefore low and the nutrient emissions to the environment are high. Apple production in China is considerably contributes to farmers＇ incomes and is important as export product. There is an urgent need to enhance apple productivity and improve nutrient use efficiencies in intensive apple production systems in the country. These can be attained by improved understanding of production potential, yield gaps, nutrient use and best management in apple orchards. To the end, priorities in research on apple production systems and required political support are described which may lead to more sustainable and environmental-friendly intensification of apple production in China.
文摘Data curation is vital for selecting effective demonstration examples in graph-to-text generation.However,evaluating the quality ofKnowledgeGraphs(KGs)remains challenging.Prior research exhibits a narrowfocus on structural statistics,such as the shortest path length,while the correctness of graphs in representing the associated text is rarely explored.To address this gap,we introduce a dual-perspective evaluation framework for KG-text data,based on the computation of structural adequacy and semantic alignment.Froma structural perspective,we propose the Weighted Incremental EdgeMethod(WIEM)to quantify graph completeness by leveraging agreement between relation models to predict possible edges between entities.WIEM targets to find increments from models on“unseen links”,whose presence is inversely proportional to the structural adequacy of the original KG in representing the text.From a semantic perspective,we evaluate how well a KG aligns with the text in capturing the intended meaning.To do so,we instruct a large language model to convert KGs into natural language andmeasure the similarity between generated and reference texts.Based on these computations,we apply a Top-K union method,integrating the structural and semantic modules,to rank and select high-quality KGs.We evaluate our framework against various approaches for selecting few-shot examples in graph-to-text generation.Experiments on theAssociation for Computational LinguisticsAbstract Graph Dataset(ACL-AGD)and Automatic Content Extraction 05(ACE05)dataset demonstrate the effectiveness of our approach in distinguishing KG-text data of different qualities,evidenced by the largest performance gap between top-and bottom-ranked examples.We also find that the top examples selected through our dual-perspective framework consistently yield better performance than those selected by traditional measures.These results highlight the importance of data curation in improving graph-to-text generation.
文摘Knowledge graphs convey precise semantic information that can be effectively interpreted by neural networks,and generating descriptive text based on these graphs places significant emphasis on content consistency.However,knowledge graphs are inadequate for providing additional linguistic features such as paragraph structure and expressive modes,making it challenging to ensure content coherence in generating text that spans multiple sentences.This lack of coherence can further compromise the overall consistency of the content within a paragraph.In this work,we present the generation of scientific abstracts by leveraging knowledge graphs,with a focus on enhancing both content consistency and coherence.In particular,we construct the ACL Abstract Graph Dataset(ACL-AGD)which pairs knowledge graphs with text,incorporating sentence labels to guide text structure and diverse expressions.We then implement a Siamese network to complement and concretize the entities and relations based on paragraph structure by accomplishing two tasks:graph-to-text generation and entity alignment.Extensive experiments demonstrate that the logical paragraphs generated by our method exhibit entities with a uniform position distribution and appropriate frequency.In terms of content,our method accurately represents the information encoded in the knowledge graph,prevents the generation of irrelevant content,and achieves coherent and non-redundant adjacent sentences,even with a shared knowledge graph.
基金supported by United States Department of Agriculture,Agricultural Research Service(No.58-8042-9-072)United States Department of Agriculture-National Institute of Food and Agriculture(No.2019-34263-30552)+1 种基金Management Information System(No.043050)United States Department of Agriculture-Agricultural Research Service-Non-Assistance Cooperative Agreement(No.58-6066-2-030).
文摘Background GOSSYM is a mechanistic,process-based cotton model that can simulate cotton crop growth and development,yield,and fiber quality.Its fiber quality module was developed based on controlled experiments explicitly conducted on the Texas Marker^(-1)(TM1)variety,potentially making its functional equations more aligned with this cultivar.To assess the model’s broader applicability,this study analyzed fiber quality data from 40 upland cotton cultivars,including TM1.The measured fiber quality from all cultivars was then compared with the modelsimulated fiber quality.Results Among the 40 upland cultivars,fiber strength varied from 28.4 cN·tex^(-1) to 34.6 cN·tex^(-1),fiber length ranged from 27.1 mm to 33.3 mm,micronaire value ranged from 2.7 to 4.6,and length uniformity index varied from 82.3%to 85.5%.The model simulated fiber quality closely matched the measured values for TM1,with the absolute percentage error(APE)being less than 0.92%for fiber strength,fiber length,and length uniformity index and 4.7%for micronaire.However,significant differences were observed for the other cultivars.The Pearson correlation coefficient(r)between the measured and simulated values was negative for all fiber quality traits,and Wilmotts’s index of agreement(WIA)was below 0.45,indicating a strong model bias toward TM1 without incorporating cultivar-specific parameters.After incorporating cultivar-specific parameters,the model’s performance improved significantly,with an average r-value of 0.84 and WIA of 0.88.Conclusions The adopted methodology and estimated cultivar-specific parameters improved the model’s simulation accuracy.This approach can be applied to newer cotton cultivars,enhancing the GOSSYM model’s utility and its applicability for agricultural management and policy decisions.
文摘The widespread adoption of cloud computing has underscored the critical importance of efficient resource allocation and management, particularly in task scheduling, which involves assigning tasks to computing resources for optimized resource utilization. Several meta-heuristic algorithms have shown effectiveness in task scheduling, among which the relatively recent Willow Catkin Optimization (WCO) algorithm has demonstrated potential, albeit with apparent needs for enhanced global search capability and convergence speed. To address these limitations of WCO in cloud computing task scheduling, this paper introduces an improved version termed the Advanced Willow Catkin Optimization (AWCO) algorithm. AWCO enhances the algorithm’s performance by augmenting its global search capability through a quasi-opposition-based learning strategy and accelerating its convergence speed via sinusoidal mapping. A comprehensive evaluation utilizing the CEC2014 benchmark suite, comprising 30 test functions, demonstrates that AWCO achieves superior optimization outcomes, surpassing conventional WCO and a range of established meta-heuristics. The proposed algorithm also considers trade-offs among the cost, makespan, and load balancing objectives. Experimental results of AWCO are compared with those obtained using the other meta-heuristics, illustrating that the proposed algorithm provides superior performance in task scheduling. The method offers a robust foundation for enhancing the utilization of cloud computing resources in the domain of task scheduling within a cloud computing environment.
文摘An individual's mental health influences their capacity to think effectively,feel emotionally stable,and perform daily activities.As mental health concerns become more prevalent worldwide,new awareness and diagnostic and treatment tactics are needed.Digital tools and technology are helping solve these problems by providing scalable,tailored solutions for large populations.This detailed review examines mental health‐promoting internet tools.Smartphone applications,web‐based therapy systems,wearable tech,artificial intelligence‐powered resources,and virtual reality(VR)technologies were evaluated for efficacy and side effects.PubMed,PsycINFO,Scopus,IEEE Xplore,and Google Scholar were carefully searched.Search terms included“digital mental health tools,”“online therapy,”and“AI in mental health.”Randomized controlled trials,cohort studies,cross‐sectional studies,systematic reviews,and meta‐analyses of digital technology and mental health were included from among the literature published after 2010.Cognitive behavioral therapy methods,mood monitoring,and mindfulness exercises are among the numerous features of smartphone applications that have been demonstrated to mitigate symptoms of anxiety,depression,and tension.Online therapy platforms let marginalized individuals obtain therapy remotely.Wearable technology may detect heart rate,blood pressure,and sleep length,which may reveal mental health difficulties.Chatbots employ machine learning algorithms and natural language processing to deliver customized support and show promise for quick intervention.Exposure therapy for anxiety and trauma is increasingly using virtual reality environments.Although digital mental health therapies face challenges in relation to data privacy,limited long‐term efficacy,and technological inequality,digital technologies are modernizing mental healthcare.By offering inexpensive and effective alternatives to traditional therapies,digital technologies may help healthcare systems meet the growing demand for mental health services and overall well‐being.
文摘A field experiment was conducted to evaluate the agronomic and physiological responses of rice under different water management systems, types of fertilizer and seedling age. This experiment was done at the farm of Agri Park, College of Agriculture, Central Experimental Station (CES), Crop Science Cluster of the University of the Philippines Los Banos, College Laguna during 2013. The strip-split plot design with three replications was used with the two types of fertilizer (vermicompost and chemical fertilizer), water management (with and without standing water) and two seedling ages (10 and 14-d old) were the treatments in the experiment. Chemical fertilizer produced the highest grain yield, total dry matter (TDM), leaf area index (LAI), net assimilation rate (NAR) and crop growth rate (CGR). Most of these characters significantly increased in 10-d old seedlings with chemical fertilizer without standing water. The shorter phyllochron and higher root pulling resistance (RPR) were observed in 10-d old seedlings without standing water. For the variety NSIC Rc 216, the use of 10-d old seedlings grown without standing water with chemical fertilizer is the optimum conditions for the better growth and high productivity.
文摘Two significant issues in Internet-based networked control systems （ INCSs）, transport performance of different protocols and security breach from Internet side, are investigated. First, for improving the performance of data transmission, user datagram protocol （UDP） is adopted as the main stand for controllers and plants using INCSs. Second, a dual-channel secure transmission scheme （DCSTS）based on data transmission characteristics of INCSs is proposed, in which a raw UDP channel and a secure TCP （transmission control protocol） connection making use of SSL/TLS （secure sockets layer/transport layer security） are included. Further, a networked control protocol （NCP） at application layer for supporting DCSTS between the controllers and plants in INCSs is designed, and it also aims at providing a universal communication mechanism for interoperability of devices among the networked control laboratories in Beijing Institute of Technology of China, Central South University of China and Tokyo University of Technology of Japan. By means of a networked single-degree-of-free- dom robot arm, an INCS under the new protocol and security environment is created. Compared with systems such as IPSec or SSL/TLS, which may cause more than 91% network throughput deduction, the new DCSTS protocol may yield results ten times better, being just 5.67%.
文摘The Integrated Agricultural Systems workgroup is examining agricultural systems of the US to determine fundamental principles that underlie successful production systems. Our hypothesis is that principles are applicable across regions, but key drivers interact to influence producer decisions and create distinct production systems. We interviewed agricultural producers to examine the underlying rationale for producer decisions and discern primary factors influencing production and marketing practices. While drivers are common among regions, interactions between drivers and influences on decision-makers vary substantially to create unique production systems. The internal social driver that values farming lifestyle is the principal factor that leads people to farming. The type of farming is partly a lifestyle choice and is influenced by other factors. Economic drivers and marketing options are primary drivers influencing production systems and management choices, as farmers provide an economic foundation for their families. While all producers employed strategies to manage production and marketing risks, these varied with different marketing channels. Identification of key drivers and principles can be used by producers, scientists and policy makers to direct agricultural production and agricultural research. New management systems can be developed that are flexible enough to respond to changing societal demands, and are environmentally and economically sustainable.
文摘Road traffic safety can decrease when drivers drive in a low-visibility environment.The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of accidents.To tackle the challenges posed by the low recognition accuracy and the substan-tial computational burden associated with current infrared pedestrian-vehicle detection methods,an infrared pedestrian-vehicle detection method A proposal is presented,based on an enhanced version of You Only Look Once version 5(YOLOv5).First,A head specifically designed for detecting small targets has been integrated into the model to make full use of shallow feature information to enhance the accuracy in detecting small targets.Second,the Focal Generalized Intersection over Union(GIoU)is employed as an alternative to the original loss function to address issues related to target overlap and category imbalance.Third,the distribution shift convolution optimization feature extraction operator is used to alleviate the computational burden of the model without significantly compromising detection accuracy.The test results of the improved algorithm show that its average accuracy(mAP)reaches 90.1%.Specifically,the Giga Floating Point Operations Per second(GFLOPs)of the improved algorithm is only 9.1.In contrast,the improved algorithms outperformed the other algorithms on similar GFLOPs,such as YOLOv6n(11.9),YOLOv8n(8.7),YOLOv7t(13.2)and YOLOv5s(16.0).The mAPs that are 4.4%,3%,3.5%,and 1.7%greater than those of these algorithms show that the improved algorithm achieves higher accuracy in target detection tasks under similar computational resource overhead.On the other hand,compared with other algorithms such as YOLOv8l(91.1%),YOLOv6l(89.5%),YOLOv7(90.8%),and YOLOv3(90.1%),the improved algorithm needs only 5.5%,2.3%,8.6%,and 2.3%,respectively,of the GFLOPs.The improved algorithm has shown significant advancements in balancing accuracy and computational efficiency,making it promising for practical use in resource-limited scenarios.
基金support from the National Natural Science Foundation of China(Nos.62205259,62075175,61975254,62375212,62005203 and 62105254)the Open Research Fund of CAS Key Laboratory of Space Precision Measurement Technology(No.B022420004)the Fundamental Research Funds for the Central Universities(No.ZYTS23125).
文摘This study reviews the recent advances in data-driven polarimetric imaging technologies based on a wide range of practical applications.The widespread international research and activity in polarimetric imaging techniques demonstrate their broad applications and interest.Polarization information is increasingly incorporated into convolutional neural networks(CNN)as a supplemental feature of objects to improve performance in computer vision task applications.Polarimetric imaging and deep learning can extract abundant information to address various challenges.Therefore,this article briefly reviews recent developments in data-driven polarimetric imaging,including polarimetric descattering,3D imaging,reflection removal,target detection,and biomedical imaging.Furthermore,we synthetically analyze the input,datasets,and loss functions and list the existing datasets and loss functions with an evaluation of their advantages and disadvantages.We also highlight the significance of data-driven polarimetric imaging in future research and development.
基金funded by the Researchers Supporting Project Number RSPD2024R681,King Saud University,Riyadh,Saudi Arabia.
文摘In a post-disaster environment characterized by frequent interruptions in communication links,traditional wireless communication networks are ineffective.Although the“store-carry-forward”mechanism characteristic of Delay Tolerant Networks(DTNs)can transmit data from Internet of things devices to more reliable base stations or data centres,it also suffers from inefficient data transmission and excessive transmission delays.To address these challenges,we propose an intelligent routing strategy based on node sociability for post-disaster emergency network scenarios.First,we introduce an intelligent routing strategy based on node intimacy,which selects more suitable relay nodes and assigns the corresponding number of message copies based on comprehensive utility values.Second,we present an intelligent routing strategy based on geographical location of nodes to forward message replicas secondarily based on transmission utility values.Finally,experiments demonstrate the effectiveness of our proposed algorithm in terms of message delivery rate,network cost ratio and average transmission delay.
文摘The growth optimizer(GO)is an innovative and robust metaheuristic optimization algorithm designed to simulate the learning and reflective processes experienced by individuals as they mature within the social environment.However,the original GO algorithm is constrained by two significant limitations:slow convergence and high mem-ory requirements.This restricts its application to large-scale and complex problems.To address these problems,this paper proposes an innovative enhanced growth optimizer(eGO).In contrast to conventional population-based optimization algorithms,the eGO algorithm utilizes a probabilistic model,designated as the virtual population,which is capable of accurately replicating the behavior of actual populations while simultaneously reducing memory consumption.Furthermore,this paper introduces the Lévy flight mechanism,which enhances the diversity and flexibility of the search process,thus further improving the algorithm’s global search capability and convergence speed.To verify the effectiveness of the eGO algorithm,a series of experiments were conducted using the CEC2014 and CEC2017 test sets.The results demonstrate that the eGO algorithm outperforms the original GO algorithm and other compact algorithms regarding memory usage and convergence speed,thus exhibiting powerful optimization capabilities.Finally,the eGO algorithm was applied to image fusion.Through a comparative analysis with the existing PSO and GO algorithms and other compact algorithms,the eGO algorithm demonstrates superior performance in image fusion.
基金This research is based on results obtained from Project JPNP07015the New Energy and Industrial Technology Development Organization(NEDO)and is also partly supported by the Japan Society for the Promotion of Science KAKENHI Program(Grant No.21K18795)。
文摘We have newly designed an electrostatic sensor,called an electric field mill(EFM),to simplify the estimation of the charge position and charge amount transferred by lightning discharges.It is necessary for this remote estimation of the transferred charge to measure electric field changes caused by charge loss at the time of a lightning strike at multiple locations.For multiple-station measurement of electric field changes,not only speed but also phase for exposure and shielding of the sensing plates inside each EFM of the array should be synchronized to maintain the sensitivities of the deployed instruments.Currently,there is no such EFM with specified speed and phase control performance of the rotary part.Thus,we developed a new EFM in which the rotary mechanism was controlled consistently to within 3%error by a GPS module.Five EFMs had been distributed in the Hokuriku area of Japan during the winter season of 2022-2023 for a test observation.Here we describe the design and a simple calibration method for our new EFM array.Data analysis method based on the assumption of a simple monopole charge structure is also summarized.For validation,locations of assumed point charges were compared with three-dimensional lightning mapping data estimated by radio observations in the MF-HF bands.Initial results indicated the validity to estimate transferred charge amounts and positions of winter cloud-to-ground lightning discharges with our new EFM array.
基金financially supported by the Research Council of Finland grant to NJS(grant#311970)the Finnish Ministry of Agriculture and Forestry(VN/28562/2020-MMM-2).
文摘Thermal processes are emerging as promising solutions to recovering phosphorus and other nutrient elements from anaerobic digestates.The feasibility of nutrient element recovery depends largely on the fates of nutrient elements and heavy metals during thermal processing.This study assesses the partitioning of macronutrients(N,P,K,Na,Ca and Mg)and heavy metals(Zn,Cu,and Mn)between condensed and gaseous phases during thermal conversion of cattle slurry digestates in gas atmospheres of pyrolysis,combustion,and gasification processes.This study also assesses the chemical forms of macronutrients retained in combustion ashes.The partitioning of elements between condensed and gaseous phases was quantified by mass balances based on elemental analyses of char and ash residues.The char and ash residues were prepared in a fixed-bed,batch reactor at temperatures within the range 800-1000°C.Powder X-ray diffraction was used to identify the chemical forms of macronutrient elements in combustion ashes.Volatilisation of P was low(<20%)when the digestates were heated in inert and oxidising atmospheres,whereas a reducing atmosphere volatilized P to a major extent(~60%at 1000°C).Oxidising atmospheres increased volatilisation of N but suppressed volatilisation of K,Na,and Zn.Volatilisation of the following elements was low(<30%)in all investigated operating conditions:Ca,Mg,Mn,and Cu.The combustion ashes contained both high concentrations of P(around 7 w/w%)and acceptable concentrations of regulated heavy metals(Cu,and Zn)for application on agricultural and forest soils in Finland.Phosphorous was retained in the combustion ashes in the form of whitlockite.This form of P is expected to be available to plants when the ashes are added to soil.
基金financially supported by the funding appropriated from USDA-ARS National Program 305 Crop Productionthe 948 Program of Ministry of Agriculture of China (2016-X38)
文摘Big data with its vast volume and complexity is increasingly concerned, developed and used for all professions and trades. Remote sensing, as one of the sources for big data, is generating earth-observation data and analysis results daily from the platforms of satellites, manned/unmanned aircrafts, and ground-based structures. Agricultural remote sensing is one of the backbone technologies for precision agriculture, which considers within-field variability for site-specific management instead of uniform management as in traditional agriculture. The key of agricultural remote sensing is, with global positioning data and geographic information, to produce spatially-varied data for subsequent precision agricultural operations. Agricultural remote sensing data, as general remote sensing data, have all characteristics of big data. The acquisition, processing, storage, analysis and visualization of agricultural remote sensing big data are critical to the success of precision agriculture. This paper overviews available remote sensing data resources, recent development of technologies for remote sensing big data management, and remote sensing data processing and management for precision agriculture. A five-layer-fifteen- level （FLFL） satellite remote sensing data management structure is described and adapted to create a more appropriate four-layer-twelve-level （FLTL） remote sensing data management structure for management and applications of agricultural remote sensing big data for precision agriculture where the sensors are typically on high-resolution satellites, manned aircrafts, unmanned aerial vehicles and ground-based structures. The FLTL structure is the management and application framework of agricultural remote sensing big data for precision agriculture and local farm studies, which outlooks the future coordination of remote sensing big data management and applications at local regional and farm scale.
文摘To investigate how the popular magnesium alloy AZ31 sheet(aluminum 3%,zinc 1%)behaves in cold working,deep drawing experiments at room temperature,along with finite element(FE)simulation,were performed on the cold forming sheet of the AZ31 alloy after being annealed under various conditions.The activities were focused on the fracture pattern,limit drawing ratio(LDR),deformation load,thickness distribution,anisotropic effect,as well as the influences of the annealing conditions and tool configuration on them.The results display that punch shoulder radius instead of die clearance,has much influence on the thickness distribution.The anisotropy is remarkable in cold working,which adversely impacts the LDR.The fracture often happens on the side wall at an angle to axis of the deformed specimen.The results also imply that the LDR for the material under present experimental conditions is 1.72,and annealing the material at 450 ℃ for 1 h may be preferable for the cold deep drawing.
