Rapid dewatering and thickening of whole-tailings with ultrafine particles is one of the most important processes for the whole-tailings paste preparation. Deep-cone thickener, a kind of such process for the flocculat...Rapid dewatering and thickening of whole-tailings with ultrafine particles is one of the most important processes for the whole-tailings paste preparation. Deep-cone thickener, a kind of such process for the flocculation and settling of whole-tailings, is particularly necessary to study. However, there exist many problems in observing the flocculation and settling process of whole-tailings, as well as the particle size distribution(PSD) of whole-tailings floccules in deep-cone thickener. Population balance model(PBM) is applied to predict the PSD in deep-cone thickener, and LUO model and GHADIRI model are employed to study the aggregation and fragmentation mechanism of the whole-tailings particles, respectively. Through three-dimensional numerical simulation on the whole-tailings flocculation and settling in deep-cone thickener using computational fluid dynamics(CFD)-PBM, the distribution of density and turbulent kinetic energy in deep-cone thickener were obtained, at the same time the spatio-temporal changes of whole-tailings floccules particle size distribution are analyzed. Finally, the major flocculation position in deep-cone thickener is found and the flocculation settling rules of whole-tailings are achieved.展开更多
Trawl is a main fishing gear in Chinese fishery,capturing large fish and letting small ones at large.However,long-term use of trawl would result in changes of phenotypic traits of the fish stocks,such as smaller size-...Trawl is a main fishing gear in Chinese fishery,capturing large fish and letting small ones at large.However,long-term use of trawl would result in changes of phenotypic traits of the fish stocks,such as smaller size-at-age and earlier age-at-maturation.In this study,we simulated a fish population with size characteristics of trawl fishing and the population produces one generation of offspring and lives for one year,used trawl to exploit the simulated fish population,and captured individuals by body size.We evaluated the impact of the changes on selectivity parameters,such as selective range and the length at 50% retention.Under fishing pressure,we specified the selectivity parameters,and determined that smaller selection rates and greater length at 50% retention were associated with an increased tendency towards miniaturization.展开更多
Quantitative characterization of complete canopy architecture is essential for accurate evaluation of crop photosynthesis and yield potential,thereby supporting crop ideotype design.Although various sensing technologi...Quantitative characterization of complete canopy architecture is essential for accurate evaluation of crop photosynthesis and yield potential,thereby supporting crop ideotype design.Although various sensing technologies enable three-dimensional(3D)reconstruction of individual plants and canopies,they often fail to describe canopy architecture accurately because of severe occlusion in dense populations.To address this limitation,we developed an effective framework for the 3D reconstruction of complex and dynamic population-scale canopy architecture in rapeseed using unmanned aerial vehicle multi-view imagery combined with a novel point cloud completion model.A complete point cloud generation pipeline was first established to enable automated training data annotation,allowing discrimination between surface points and occluded points within the canopy.The proposed crop population point cloud completion network(CP-PCN)integrates a multi-resolution dynamic graph convolutional encoder,a point pyramid decoder,a dynamic graph convolutional feature extractor,and a generative adversarial network-based loss function to predict occluded canopy points.CP-PCN achieved chamfer distance values of 3.35 to 4.51 cm across four growth stages,outperforming the state-of-the-art transformer-based method PoinTr.Ablation analyses confirmed that each of the four modules contributes to overall model accuracy.In addition,validation experiments showed that the improved architectural completeness achieved by CP-PCN resulted in more accurate yield estimation compared with incomplete and PoinTr-completed point clouds.CP-PCN also demonstrated strong cross-crop generalizability by successfully reconstructing mature rice canopies.Overall,this framework provides a scalable approach for quantitative analysis of complex canopy architectures in field-grown crops.展开更多
Background:Advances in artificial intelligence have enabled the simulation of human-like behaviors,raising the possibility of using large language models(LLMs)to generate synthetic population samples for research purp...Background:Advances in artificial intelligence have enabled the simulation of human-like behaviors,raising the possibility of using large language models(LLMs)to generate synthetic population samples for research purposes,which may be particularly useful in health and social sciences.Methods:This paper explores the potential of LLMs to simulate population samples mirroring real ones,as well as the feasibility of using personality questionnaires to assess the personality of LLMs.To advance in that direction,2 experiments were conducted with GPT-4o using the Eysenck Personality Questionnaire Revised-Abbreviated(EPQR-A)in 6 languages:Spanish,English,Slovak,Hebrew,Portuguese,and Turkish.Results:We find that GPT-4o exhibits distinct personality traits,which vary based on parameter settings and the language of the questionnaire.While the model shows promising trends in reflecting certain personality traits and differences across gender and academic fields,discrepancies between the synthetic populations’responses and those from real populations remain.Conclusions:These inconsistencies suggest that creating fully reliable synthetic population samples for questionnaire testing is still an open challenge.Further research is required to better align synthetic and real population behaviors.展开更多
The purpose of stock assessment is to support managers to provide intelligent decisions regarding removal from fish populations.Errors in assessment models may have devastating impacts on the population fitness and ne...The purpose of stock assessment is to support managers to provide intelligent decisions regarding removal from fish populations.Errors in assessment models may have devastating impacts on the population fitness and negative impacts on the economy of the resource users.Thus,accuracte estimations of population size,growth rates are critical for success.Evaluating and testing the behavior and performance of stock assessment models and assessing the consequences of model mis-specification and the impact of management strategies requires an operating model that accurately describe the dynamics of the target species,and can resolve spatial and seasonal changes.In addition,the most thorough evaluations of assessment models use an operating model that takes a different form than the assessment model.This paper presents an individual-based probabilistic model used to simulate the complex dynamics of populations and their associated fisheries.Various components of population dynamics are expressed as random Bernoulli trials in the model and detailed life and fishery histories of each individual are tracked over their life span.The simulation model is designed to be flexible so it can be used for different species and fisheries.It can simulate mixing among multiple stocks and link stock-recruit relationships to environmental factors.Furthermore,the model allows for flexibility in sub-models(e.g.,growth and recruitment)and model assumptions(e.g.,age-or size-dependent selectivity).This model enables the user to conduct various simulation studies,including testing the performance of assessment models under different assumptions,assessing the impacts of model mis-specification and evaluating management strategies.展开更多
基金Project(51174032)supported by the National Natural Science Foundation of ChinaProject(NCET-10-0225)supported by the Program for New Century Excellent Talents in University,ChinaProject(FRF-TP-09-001A)supported by the Fundamental Research Funds for the Central Universities,China
文摘Rapid dewatering and thickening of whole-tailings with ultrafine particles is one of the most important processes for the whole-tailings paste preparation. Deep-cone thickener, a kind of such process for the flocculation and settling of whole-tailings, is particularly necessary to study. However, there exist many problems in observing the flocculation and settling process of whole-tailings, as well as the particle size distribution(PSD) of whole-tailings floccules in deep-cone thickener. Population balance model(PBM) is applied to predict the PSD in deep-cone thickener, and LUO model and GHADIRI model are employed to study the aggregation and fragmentation mechanism of the whole-tailings particles, respectively. Through three-dimensional numerical simulation on the whole-tailings flocculation and settling in deep-cone thickener using computational fluid dynamics(CFD)-PBM, the distribution of density and turbulent kinetic energy in deep-cone thickener were obtained, at the same time the spatio-temporal changes of whole-tailings floccules particle size distribution are analyzed. Finally, the major flocculation position in deep-cone thickener is found and the flocculation settling rules of whole-tailings are achieved.
基金Supported by the Special Fund for Agro-scientific Research in the Public Interest of China(No.201203018)the National Key Technology Research and Development Program of China(No.2006BAD09A05)
文摘Trawl is a main fishing gear in Chinese fishery,capturing large fish and letting small ones at large.However,long-term use of trawl would result in changes of phenotypic traits of the fish stocks,such as smaller size-at-age and earlier age-at-maturation.In this study,we simulated a fish population with size characteristics of trawl fishing and the population produces one generation of offspring and lives for one year,used trawl to exploit the simulated fish population,and captured individuals by body size.We evaluated the impact of the changes on selectivity parameters,such as selective range and the length at 50% retention.Under fishing pressure,we specified the selectivity parameters,and determined that smaller selection rates and greater length at 50% retention were associated with an increased tendency towards miniaturization.
基金supported by the National Natural Science Foundation of China(Grant No.32371985)the International S&T Cooperation Program of China(Grant No.2024YFE0115000).
文摘Quantitative characterization of complete canopy architecture is essential for accurate evaluation of crop photosynthesis and yield potential,thereby supporting crop ideotype design.Although various sensing technologies enable three-dimensional(3D)reconstruction of individual plants and canopies,they often fail to describe canopy architecture accurately because of severe occlusion in dense populations.To address this limitation,we developed an effective framework for the 3D reconstruction of complex and dynamic population-scale canopy architecture in rapeseed using unmanned aerial vehicle multi-view imagery combined with a novel point cloud completion model.A complete point cloud generation pipeline was first established to enable automated training data annotation,allowing discrimination between surface points and occluded points within the canopy.The proposed crop population point cloud completion network(CP-PCN)integrates a multi-resolution dynamic graph convolutional encoder,a point pyramid decoder,a dynamic graph convolutional feature extractor,and a generative adversarial network-based loss function to predict occluded canopy points.CP-PCN achieved chamfer distance values of 3.35 to 4.51 cm across four growth stages,outperforming the state-of-the-art transformer-based method PoinTr.Ablation analyses confirmed that each of the four modules contributes to overall model accuracy.In addition,validation experiments showed that the improved architectural completeness achieved by CP-PCN resulted in more accurate yield estimation compared with incomplete and PoinTr-completed point clouds.CP-PCN also demonstrated strong cross-crop generalizability by successfully reconstructing mature rice canopies.Overall,this framework provides a scalable approach for quantitative analysis of complex canopy architectures in field-grown crops.
文摘Background:Advances in artificial intelligence have enabled the simulation of human-like behaviors,raising the possibility of using large language models(LLMs)to generate synthetic population samples for research purposes,which may be particularly useful in health and social sciences.Methods:This paper explores the potential of LLMs to simulate population samples mirroring real ones,as well as the feasibility of using personality questionnaires to assess the personality of LLMs.To advance in that direction,2 experiments were conducted with GPT-4o using the Eysenck Personality Questionnaire Revised-Abbreviated(EPQR-A)in 6 languages:Spanish,English,Slovak,Hebrew,Portuguese,and Turkish.Results:We find that GPT-4o exhibits distinct personality traits,which vary based on parameter settings and the language of the questionnaire.While the model shows promising trends in reflecting certain personality traits and differences across gender and academic fields,discrepancies between the synthetic populations’responses and those from real populations remain.Conclusions:These inconsistencies suggest that creating fully reliable synthetic population samples for questionnaire testing is still an open challenge.Further research is required to better align synthetic and real population behaviors.
基金Financial support for this project was provided by Shanghai Ocean University International Center for Marine Sciences.
文摘The purpose of stock assessment is to support managers to provide intelligent decisions regarding removal from fish populations.Errors in assessment models may have devastating impacts on the population fitness and negative impacts on the economy of the resource users.Thus,accuracte estimations of population size,growth rates are critical for success.Evaluating and testing the behavior and performance of stock assessment models and assessing the consequences of model mis-specification and the impact of management strategies requires an operating model that accurately describe the dynamics of the target species,and can resolve spatial and seasonal changes.In addition,the most thorough evaluations of assessment models use an operating model that takes a different form than the assessment model.This paper presents an individual-based probabilistic model used to simulate the complex dynamics of populations and their associated fisheries.Various components of population dynamics are expressed as random Bernoulli trials in the model and detailed life and fishery histories of each individual are tracked over their life span.The simulation model is designed to be flexible so it can be used for different species and fisheries.It can simulate mixing among multiple stocks and link stock-recruit relationships to environmental factors.Furthermore,the model allows for flexibility in sub-models(e.g.,growth and recruitment)and model assumptions(e.g.,age-or size-dependent selectivity).This model enables the user to conduct various simulation studies,including testing the performance of assessment models under different assumptions,assessing the impacts of model mis-specification and evaluating management strategies.
