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Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration and Exploitation 被引量:2
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作者 Kang Yuan Yanjun Huang +4 位作者 Shuo Yang Zewei Zhou Yulei Wang Dongpu Cao Hong Chen 《Engineering》 SCIE EI CAS CSCD 2024年第2期108-120,共13页
Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning frame... Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data-and model-driven method.First,a data-driven decision-making module based on deep reinforcement learning(DRL)is developed to pursue a rational driving performance as much as possible.Then,model predictive control(MPC)is employed to execute both longitudinal and lateral motion planning tasks.Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements.Finally,two principles of safety and rationality for the self-evolution of autonomous driving are proposed.A motion envelope is established and embedded into a rational exploration and exploitation scheme,which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent.Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted,and the results show that the proposed online-evolution framework is able to generate safer,more rational,and more efficient driving action in a real-world environment. 展开更多
关键词 Autonomous driving decision-making Motion planning Deep reinforcement learning Model predictive control
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Toward Trustworthy Decision-Making for Autonomous Vehicles:A Robust Reinforcement Learning Approach with Safety Guarantees
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作者 Xiangkun He Wenhui Huang Chen Lv 《Engineering》 SCIE EI CAS CSCD 2024年第2期77-89,共13页
While autonomous vehicles are vital components of intelligent transportation systems,ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving.Therefore,we present... While autonomous vehicles are vital components of intelligent transportation systems,ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving.Therefore,we present a novel robust reinforcement learning approach with safety guarantees to attain trustworthy decision-making for autonomous vehicles.The proposed technique ensures decision trustworthiness in terms of policy robustness and collision safety.Specifically,an adversary model is learned online to simulate the worst-case uncertainty by approximating the optimal adversarial perturbations on the observed states and environmental dynamics.In addition,an adversarial robust actor-critic algorithm is developed to enable the agent to learn robust policies against perturbations in observations and dynamics.Moreover,we devise a safety mask to guarantee the collision safety of the autonomous driving agent during both the training and testing processes using an interpretable knowledge model known as the Responsibility-Sensitive Safety Model.Finally,the proposed approach is evaluated through both simulations and experiments.These results indicate that the autonomous driving agent can make trustworthy decisions and drastically reduce the number of collisions through robust safety policies. 展开更多
关键词 Autonomous vehicle decision-making Reinforcement learning Adversarial attack Safety guarantee
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Orientation and Decision-Making for Soccer Based on Sports Analytics and AI:A Systematic Review
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作者 Zhiqiang Pu Yi Pan +4 位作者 Shijie Wang Boyin Liu Min Chen Hao Ma Yixiong Cui 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第1期37-57,共21页
Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professio... Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) loop.In addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making. 展开更多
关键词 Artificial intelligence(AI) decision-making FOOTBALL review SOCCER sports analytics
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Tomato detection method using domain adaptive learning for dense planting environments
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作者 LI Yang HOU Wenhui +4 位作者 YANG Huihuang RAO Yuan WANG Tan JIN Xiu ZHU Jun 《农业工程学报》 EI CAS CSCD 北大核心 2024年第13期134-145,共12页
This study aimed to address the challenge of accurately and reliably detecting tomatoes in dense planting environments,a critical prerequisite for the automation implementation of robotic harvesting.However,the heavy ... This study aimed to address the challenge of accurately and reliably detecting tomatoes in dense planting environments,a critical prerequisite for the automation implementation of robotic harvesting.However,the heavy reliance on extensive manually annotated datasets for training deep learning models still poses significant limitations to their application in real-world agricultural production environments.To overcome these limitations,we employed domain adaptive learning approach combined with the YOLOv5 model to develop a novel tomato detection model called as TDA-YOLO(tomato detection domain adaptation).We designated the normal illumination scenes in dense planting environments as the source domain and utilized various other illumination scenes as the target domain.To construct bridge mechanism between source and target domains,neural preset for color style transfer is introduced to generate a pseudo-dataset,which served to deal with domain discrepancy.Furthermore,this study combines the semi-supervised learning method to enable the model to extract domain-invariant features more fully,and uses knowledge distillation to improve the model's ability to adapt to the target domain.Additionally,for purpose of promoting inference speed and low computational demand,the lightweight FasterNet network was integrated into the YOLOv5's C3 module,creating a modified C3_Faster module.The experimental results demonstrated that the proposed TDA-YOLO model significantly outperformed original YOLOv5s model,achieving a mAP(mean average precision)of 96.80%for tomato detection across diverse scenarios in dense planting environments,increasing by 7.19 percentage points;Compared with the latest YOLOv8 and YOLOv9,it is also 2.17 and 1.19 percentage points higher,respectively.The model's average detection time per image was an impressive 15 milliseconds,with a FLOPs(floating point operations per second)count of 13.8 G.After acceleration processing,the detection accuracy of the TDA-YOLO model on the Jetson Xavier NX development board is 90.95%,the mAP value is 91.35%,and the detection time of each image is 21 ms,which can still meet the requirements of real-time detection of tomatoes in dense planting environment.The experimental results show that the proposed TDA-YOLO model can accurately and quickly detect tomatoes in dense planting environment,and at the same time avoid the use of a large number of annotated data,which provides technical support for the development of automatic harvesting systems for tomatoes and other fruits. 展开更多
关键词 plantS MODELS domain adaptive tomato detection illumination variation semi-supervised learning dense planting environments
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Ethical Decision-Making Framework Based on Incremental ILP Considering Conflicts
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作者 Xuemin Wang Qiaochen Li Xuguang Bao 《Computers, Materials & Continua》 SCIE EI 2024年第3期3619-3643,共25页
Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values... Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values or make ethical decisions,they may not meet the expectations of humans.Traditionally,an ethical decision-making framework is constructed by rule-based or statistical approaches.In this paper,we propose an ethical decision-making framework based on incremental ILP(Inductive Logic Programming),which can overcome the brittleness of rule-based approaches and little interpretability of statistical approaches.As the current incremental ILP makes it difficult to solve conflicts,we propose a novel ethical decision-making framework considering conflicts in this paper,which adopts our proposed incremental ILP system.The framework consists of two processes:the learning process and the deduction process.The first process records bottom clauses with their score functions and learns rules guided by the entailment and the score function.The second process obtains an ethical decision based on the rules.In an ethical scenario about chatbots for teenagers’mental health,we verify that our framework can learn ethical rules and make ethical decisions.Besides,we extract incremental ILP from the framework and compare it with the state-of-the-art ILP systems based on ASP(Answer Set Programming)focusing on conflict resolution.The results of comparisons show that our proposed system can generate better-quality rules than most other systems. 展开更多
关键词 Ethical decision-making inductive logic programming incremental learning conflicts
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Stroke Risk Assessment Decision-Making Using a Machine Learning Model:Logistic-AdaBoost
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作者 Congjun Rao Mengxi Li +1 位作者 Tingting Huang Feiyu Li 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第4期699-724,共26页
Stroke is a chronic cerebrovascular disease that carries a high risk.Stroke risk assessment is of great significance in preventing,reversing and reducing the spread and the health hazards caused by stroke.Aiming to ob... Stroke is a chronic cerebrovascular disease that carries a high risk.Stroke risk assessment is of great significance in preventing,reversing and reducing the spread and the health hazards caused by stroke.Aiming to objectively predict and identify strokes,this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost(Logistic-AB)based on machine learning.First,the categorical boosting(CatBoost)method is used to perform feature selection for all features of stroke,and 8 main features are selected to form a new index evaluation system to predict the risk of stroke.Second,the borderline synthetic minority oversampling technique(SMOTE)algorithm is applied to transform the unbalanced stroke dataset into a balanced dataset.Finally,the stroke risk assessment decision-makingmodel Logistic-AB is constructed,and the overall prediction performance of this new model is evaluated by comparing it with ten other similar models.The comparison results show that the new model proposed in this paper performs better than the two single algorithms(logistic regression and AdaBoost)on the four indicators of recall,precision,F1 score,and accuracy,and the overall performance of the proposed model is better than that of common machine learning algorithms.The Logistic-AB model presented in this paper can more accurately predict patients’stroke risk. 展开更多
关键词 STROKE risk assessment decision-making CatBoost feature selection borderline SMOTE Logistic-AB
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Research on Maneuver Decision-Making of Multi-Agent Adversarial Game in a Random Interference Environment
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作者 Shiguang Hu Le Ru +4 位作者 Bo Lu Zhenhua Wang Xiaolin Zhao Wenfei Wang Hailong Xi 《Computers, Materials & Continua》 SCIE EI 2024年第10期1879-1903,共25页
The strategy evolution process of game players is highly uncertain due to random emergent situations and other external disturbances.This paper investigates the issue of strategy interaction and behavioral decision-ma... The strategy evolution process of game players is highly uncertain due to random emergent situations and other external disturbances.This paper investigates the issue of strategy interaction and behavioral decision-making among game players in simulated confrontation scenarios within a random interference environment.It considers the possible risks that random disturbances may pose to the autonomous decision-making of game players,as well as the impact of participants’manipulative behaviors on the state changes of the players.A nonlinear mathematical model is established to describe the strategy decision-making process of the participants in this scenario.Subsequently,the strategy selection interaction relationship,strategy evolution stability,and dynamic decision-making process of the game players are investigated and verified by simulation experiments.The results show that maneuver-related parameters and random environmental interference factors have different effects on the selection and evolutionary speed of the agent’s strategies.Especially in a highly uncertain environment,even small information asymmetry or miscalculation may have a significant impact on decision-making.This also confirms the feasibility and effectiveness of the method proposed in the paper,which can better explain the behavioral decision-making process of the agent in the interaction process.This study provides feasibility analysis ideas and theoretical references for improving multi-agent interactive decision-making and the interpretability of the game system model. 展开更多
关键词 Behavior decision-making stochastic evolutionary game nonlinear mathematical modeling MULTI-AGENT MANEUVER
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Determination of the best materials for development and designing product using a multi-criteria decision-making
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作者 Rabia Hassan Zeeshan Ahmad Arfeen +2 位作者 Mehreen Kausar Azam Zain ul Abiden Akhtar Abubakar Siddique 《Railway Sciences》 2024年第5期541-557,共17页
Purpose–Material selection,driven by wide and often conflicting objectives,is an important,sometimes difficult problem in material engineering.In this context,multi-criteria decision-making(MCDM)methodologies are eff... Purpose–Material selection,driven by wide and often conflicting objectives,is an important,sometimes difficult problem in material engineering.In this context,multi-criteria decision-making(MCDM)methodologies are effective.An approach of MCDM is needed to cater to criteria of material assortment simultaneously.More firms are now concerned about increasing their productivity using mathematical tools.To occupy a gap in the previous literature this research recommends an integrated MCDM and mathematical Bi-objective model for the selection of material.In addition,by using the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS),the inherent ambiguities of decision-makers in paired evaluations are considered in this research.It goes on to construct a mathematical bi-objective model for determining the best item to purchase.Design/methodology/approach–The entropy perspective is implemented in this paper to evaluate the weight parameters,while the TOPSIS technique is used to determine the best and worst intermediate pipe materials for automotive exhaust system.The intermediate pipes are used to join the components of the exhaust systems.The materials usually used to manufacture intermediate pipe are SUS 436LM,SUS 430,SUS 304,SUS 436L,SUH 409 L,SUS 441 L and SUS 439L.These seven materials are evaluated based on tensile strength(TS),hardness(H),elongation(E),yield strength(YS)and cost(C).A hybrid methodology combining entropy-based criteria weighting,with the TOPSIS for alternative ranking,is pursued to identify the optimal design material for an engineered application in this paper.This study aims to help while filling the information gap in selecting the most suitable material for use in the exhaust intermediate pipes.After that,the authors searched for and considered eight materials and evaluated them on the following five criteria:(1)TS,(2)YS,(3)H,(4)E and(5)C.The first two criteria have been chosen because they can have a lot of influence on the behavior of the exhaust intermediate pipes,on their performance and on the cost.In this structure,the weights of the criteria are calculated objectively through the entropy method in order to have an unbiased assessment.This essentially measures the quantity of information each criterion contribution,indicating the relative importance of these criteria better.Subsequently,the materials were ranked using the TOPSIS method in terms of their relative performance by measuring each material from an ideal solution to determine the best alternative.The results show that SUS 309,SUS 432L and SUS 436 LM are the first three materials that the exhaust intermediate pipe optimal design should consider.Findings–The material matrix of the decision presented in Table 3 was normalized through Equation 5,as shown in Table 5,and the matrix was multiplied with weighting criteriaß_j.The obtained weighted normalized matrix V_ij is presented in Table 6.However,the ideal,worst and best value was ascertained by employing Equation 7.This study is based on the selection of material for the development of intermediate pipe using MCDM,and it involves four basic stages,i.e.method of translation criteria,screening process,method of ranking and search for methods.The selection was done through the TOPSIS method,and the criteria weight was obtained by the entropy method.The result showed that the top three materials are SUS 309,SUS 432L and SUS 436 LM,respectively.For the future work,it is suggested to select more alternatives and criteria.The comparison can also be done by using different MCDM techniques like and Choice Expressing Reality(ELECTRE),Decision-Making Trial and Evaluation Laboratory(DEMATEL)and Preference Ranking Organization Method for Enrichment Evaluation(PROMETHEE).Originality/value–The results provide important conclusions for material selection in this targeted application,verifying the employment of mutual entropy-TOPSIS methodology for a series of difficult engineering decisions in material engineering concepts that combine superior capacity with better performance as well as cost-efficiency in various engineering design. 展开更多
关键词 TOPSIS Multi-criteria decision-making Entropy method Material selection
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The Spherical q-Linear Diophantine Fuzzy Multiple-Criteria Group Decision-Making Based on Differential Measure
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作者 Huzaira Razzaque Shahzaib Ashraf +1 位作者 Muhammad Naeem Yu-Ming Chu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第2期1925-1950,共26页
Spherical q-linearDiophantine fuzzy sets(Sq-LDFSs)provedmore effective for handling uncertainty and vagueness in multi-criteria decision-making(MADM).It does not only cover the data in two variable parameters but is a... Spherical q-linearDiophantine fuzzy sets(Sq-LDFSs)provedmore effective for handling uncertainty and vagueness in multi-criteria decision-making(MADM).It does not only cover the data in two variable parameters but is also beneficial for three parametric data.By Pythagorean fuzzy sets,the difference is calculated only between two parameters(membership and non-membership).According to human thoughts,fuzzy data can be found in three parameters(membership uncertainty,and non-membership).So,to make a compromise decision,comparing Sq-LDFSs is essential.Existing measures of different fuzzy sets do,however,can have several flaws that can lead to counterintuitive results.For instance,they treat any increase or decrease in the membership degree as the same as the non-membership degree because the uncertainty does not change,even though each parameter has a different implication.In the Sq-LDFSs comparison,this research develops the differentialmeasure(DFM).Themain goal of the DFM is to cover the unfair arguments that come from treating different types of FSs opposing criteria equally.Due to their relative positions in the attribute space and the similarity of their membership and non-membership degrees,two Sq-LDFSs formthis preference connectionwhen the uncertainty remains same in both sets.According to the degree of superiority or inferiority,two Sq-LDFSs are shown as identical,equivalent,superior,or inferior over one another.The suggested DFM’s fundamental characteristics are provided.Based on the newly developed DFM,a unique approach tomultiple criterion group decision-making is offered.Our suggestedmethod verifies the novel way of calculating the expert weights for Sq-LDFSS as in PFSs.Our proposed technique in three parameters is applied to evaluate solid-state drives and choose the optimum photovoltaic cell in two applications by taking uncertainty parameter zero.The method’s applicability and validity shown by the findings are contrasted with those obtained using various other existing approaches.To assess its stability and usefulness,a sensitivity analysis is done. 展开更多
关键词 Multi-criteria group decision-making spherical q-linear Diophantine fuzzy sets differencemeasures photovoltaic cells medical diagnosis
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A NovelMethod for Determining Tourism Carrying Capacity in a Decision-Making Context Using q−Rung Orthopair Fuzzy Hypersoft Environment
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作者 Salma Khan Muhammad Gulistan +2 位作者 NasreenKausar Seifedine Kadry Jungeun Kim 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第2期1951-1979,共29页
Tourism is a popular activity that allows individuals to escape their daily routines and explore new destinations for various reasons,including leisure,pleasure,or business.A recent study has proposed a unique mathema... Tourism is a popular activity that allows individuals to escape their daily routines and explore new destinations for various reasons,including leisure,pleasure,or business.A recent study has proposed a unique mathematical concept called a q−Rung orthopair fuzzy hypersoft set(q−ROFHS)to enhance the formal representation of human thought processes and evaluate tourism carrying capacity.This approach can capture the imprecision and ambiguity often present in human perception.With the advanced mathematical tools in this field,the study has also incorporated the Einstein aggregation operator and score function into the q−ROFHS values to supportmultiattribute decision-making algorithms.By implementing this technique,effective plans can be developed for social and economic development while avoiding detrimental effects such as overcrowding or environmental damage caused by tourism.A case study of selected tourism carrying capacity will demonstrate the proposed methodology. 展开更多
关键词 q−Rung orthopair fuzzy hypersoft set decision-making tourism carrying capacity aggregation operator
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UAV maneuvering decision-making algorithm based on deep reinforcement learning under the guidance of expert experience
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作者 ZHAN Guang ZHANG Kun +1 位作者 LI Ke PIAO Haiyin 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第3期644-665,共22页
Autonomous umanned aerial vehicle(UAV) manipulation is necessary for the defense department to execute tactical missions given by commanders in the future unmanned battlefield. A large amount of research has been devo... Autonomous umanned aerial vehicle(UAV) manipulation is necessary for the defense department to execute tactical missions given by commanders in the future unmanned battlefield. A large amount of research has been devoted to improving the autonomous decision-making ability of UAV in an interactive environment, where finding the optimal maneuvering decisionmaking policy became one of the key issues for enabling the intelligence of UAV. In this paper, we propose a maneuvering decision-making algorithm for autonomous air-delivery based on deep reinforcement learning under the guidance of expert experience. Specifically, we refine the guidance towards area and guidance towards specific point tasks for the air-delivery process based on the traditional air-to-surface fire control methods.Moreover, we construct the UAV maneuvering decision-making model based on Markov decision processes(MDPs). Specifically, we present a reward shaping method for the guidance towards area and guidance towards specific point tasks using potential-based function and expert-guided advice. The proposed algorithm could accelerate the convergence of the maneuvering decision-making policy and increase the stability of the policy in terms of the output during the later stage of training process. The effectiveness of the proposed maneuvering decision-making policy is illustrated by the curves of training parameters and extensive experimental results for testing the trained policy. 展开更多
关键词 unmanned aerial vehicle(UAV) maneuvering decision-making autonomous air-delivery deep reinforcement learning reward shaping expert experience
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Sorghum Productivity and Its Farming Feasibility in Dryland Agriculture:Genotypic and Planting Distance Insights
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作者 Kristamtini Sugeng Widodo +12 位作者 Heni Purwaningsih Arlyna Budi Pustika Setyorini Widyayanti Arif Muazam Arini Putri Hanifa Joko Triastono Dewi Sahara Heni Sulistyawati Purwaning Rahayu Pandu Laksono Diah Arina Fahmi Sutardi Joko Pramono Rachmiwati Yusuf 《Phyton-International Journal of Experimental Botany》 SCIE 2024年第5期1007-1021,共15页
Sorghum(Sorghum bicolor L.Moench)is an essential food crop for more than 750 million people in tropical and sub-tropical dry climates of Africa,India,and Latin America.The domestic sorghum market in Indonesia is still... Sorghum(Sorghum bicolor L.Moench)is an essential food crop for more than 750 million people in tropical and sub-tropical dry climates of Africa,India,and Latin America.The domestic sorghum market in Indonesia is still limited to the eastern region(East Nusa Tenggara,West Nusa Tenggara,Java,and South Sulawesi).Therefore,it is crucial to carry out sorghum research on drylands.This research aimed to investigate the effect of sorghum genotype and planting distance and their interaction toward growth and sorghum’s productivity in the Gunungkidul dryland,Yogyakarta,Indonesia.In addition,the farm business analysis,including the feasibility of sorghum farming,was also examined.The research used a randomized complete block design(RCBD),arranged in a 5×4 factorial with 3 replicates.The first treatment consisted of 5 varieties(2 high-yielding varieties(Bioguma 1 and Kawali)and 3 local sorghum varieties(Plonco,Ketan Merah,and Hitam Wareng)).The second treatment consisted of 4 levels of planting distance,namely 50×20 cm,60×20 cm,70×15 cm,and 70×20×20 cm.Analysis of variance was used to analyze the data,where Duncan’s multiple range test(DMRT)was used post hoc.Plant height,panicle height,panicle width,panicle weight,stover weight,grains weight/plot,and productivity were significantly affected by sorghum varieties(p<0.05).However,there was no significant effect from the planting distance treatment and no interaction between planting distance and varietal treatments.Ketan Merah had the highest height,panicle length,and panicle width,while Bioguma 1 had the highest stover weight,panicle weight,grain weight/plot,and productivity.There was a significant linear regression equation,i.e.,productivity=0.0054–0.0003 panicle height+0.4163 grains weight/plot.Our findings on farm business analysis suggested that four out of five tested sorghum varieties were feasible to grow,except for the Ketan Merah variety.The most economically profitable sorghum variety to grow in Gunungkidul dryland was Bioguma 1. 展开更多
关键词 SORGHUM dryland agriculture planting space VARIETY local Gunungkidul
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Physiological and Biochemical Responses of Perennial Ryegrass Mixed Planting with Legumes under Heavy Metal Pollution
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作者 Yi Xi Li Zhang +2 位作者 Yanhong Xu Wei Cheng Chao Chen 《Phyton-International Journal of Experimental Botany》 SCIE 2024年第7期1749-1765,共17页
In artificially controlled pot experiments,perennial ryegrass was mixed with other leguminous plants(white clo-ver and alfalfa)and treated with lead,zinc and cadmium(337 mg·kg^(-1),648 mg·kg^(-1),and 9 mg... In artificially controlled pot experiments,perennial ryegrass was mixed with other leguminous plants(white clo-ver and alfalfa)and treated with lead,zinc and cadmium(337 mg·kg^(-1),648 mg·kg^(-1),and 9 mg·kg^(-1),respectively)to simulate compound pollution conditions.The results showed that the concentrations of heavy metals,trans-port factors,and bioconcentration factors in mixed planting of ryegrass decreased compared with those in mono-culture.Regardless of whether heavy metal pollution was introduced,mixed planting increased the aboveground and underground biomasses of ryegrass.The different mixed planting treatments had no significant impact on the chlorophyll concentration of ryegrass.The mowing time,mixed planting treatment,and heavy metal treatment had impacts on antioxidant and osmotic adjustment substances,and there were some interactions.The mixed planting treatment did not significantly affect glutathione concentration,cysteine concentration,or nonprotein thiol.Mixed planting generally increased the nitrogen and phosphorus concentrations of ryegrass while reducing the stoichiometric ratio of carbon,nitrogen,and phosphorus.These results suggest that the mixed planting of ryegrass with legumes promotes the growth of ryegrass in the presence of high concentrations of heavy metal pollution.However,it does not enhance the ability of ryegrass to remediate heavy metal pollution in the soil. 展开更多
关键词 Perennial ryegrass mixed planting PHYTOREMEDIATION LEAD ZINC and cadmium soil pollution
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Influence of social media on maternal decision-making and breastfeeding practices
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作者 Gowda Parameshwara Prashanth 《World Journal of Clinical Pediatrics》 2024年第4期109-111,共3页
Breastfeeding practices are influenced by multifactorial determinants including individual characteristics,external support systems,and media influences.This commentary emphasizes such complex factors influencing brea... Breastfeeding practices are influenced by multifactorial determinants including individual characteristics,external support systems,and media influences.This commentary emphasizes such complex factors influencing breastfeeding practices.Potential methodological limitations and the need for diverse sampling in studying breastfeeding practices are highlighted.Further research must explore the interplay between social influences,cultural norms,government policies,and individual factors in shaping maternal breastfeeding decisions. 展开更多
关键词 Exclusive breastfeeding Breastfeeding promotion Mass communication Maternal decision-making Social media
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Decision-Making and Management of Self-Care in Persons with Traumatic Spinal Cord Injuries: A Preliminary Study
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作者 Paul E. Plonski Jasmin Vassileva +5 位作者 Ryan Shahidi Paul B. Perrin William Carter Lance L. Goetz Amber Brochetti James M. Bjork 《Journal of Behavioral and Brain Science》 2024年第2期47-63,共17页
Patients and physicians understand the importance of self-care following spinal cord injury (SCI), yet many individuals with SCI do not adhere to recommended self-care activities despite logistical supports. Neurobeha... Patients and physicians understand the importance of self-care following spinal cord injury (SCI), yet many individuals with SCI do not adhere to recommended self-care activities despite logistical supports. Neurobehavioral determinants of SCI self-care behavior, such as impulsivity, are not widely studied, yet understanding them could inform efforts to improve SCI self-care. We explored associations between impulsivity and self-care in an observational study of 35 US adults age 18 - 50 who had traumatic SCI with paraplegia at least six months before assessment. The primary outcome measure was self-reported self-care. In LASSO regression models that included all neurobehavioral measures and demographics as predictors of self-care, dispositional measures of greater impulsivity (negative urgency, lack of premeditation, lack of perseverance), and reduced mindfulness were associated with reduced self-care. Outcome (magnitude) sensitivity, a latent decision-making parameter derived from computationally modeling successive choices in a gambling task, was also associated with self-care behavior. These results are preliminary;more research is needed to demonstrate the utility of these findings in clinical settings. Information about associations between impulsivity and poor self-care in people with SCI could guide the development of interventions to improve SCI self-care and help patients with elevated risks related to self-care and secondary health conditions. 展开更多
关键词 Spinal Cord Injury SELF-CARE decision-making PARAPLEGIA Impulsive Behavior Health Care
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Study on Planting Techniques of Medicinal Plant Anchusa italica Retz
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作者 Nurbolat Aidarhan Sawle Abaihan +2 位作者 Geyu LIU Chunfang LU Haji Akber Aisa 《Agricultural Biotechnology》 2024年第5期14-15,18,共3页
Anchusa italica Retz.,a perennial herb,has the effects of clearing away heat and toxic materials,and killing parasites to relieve itching.It is mainly used for breast abscess,sore swollen poison,scabies and so on,and ... Anchusa italica Retz.,a perennial herb,has the effects of clearing away heat and toxic materials,and killing parasites to relieve itching.It is mainly used for breast abscess,sore swollen poison,scabies and so on,and serves as one of the commonly used medicinal materials in Uygur medicine.A.italica is distributed in Iran,Europe,Afghanistan and Kazakhstan.It is cultivated in China,and Xinjiang mostly imports it from Pakistan.This study belongs to the technical field of traditional Chinese medicine planting.The planting method solves the technical problems of sowing,field management,harvesting and processing of A.italica. 展开更多
关键词 Biological characteristic planting technique Medicinal value Chemical composition
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Exploring the impact of high density planting system and deficit irrigation in cotton(Gossypium hirsutum L.):a comprehensive review
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作者 MANIBHARATHI Sekar SOMASUNDARAM Selvaraj +3 位作者 PARASURAMAN Panneerselvam SUBRAMANIAN Alagesan RAVICHANDRAN Veerasamy MANIKANDA BOOPATHI Narayanan 《Journal of Cotton Research》 CAS 2024年第3期302-317,共16页
Lessons learned from past experiences push for an alternate way of crop production.In India,adopting high density planting system(HDPS)to boost cotton yield is becoming a growing trend.HDPS has recently been considere... Lessons learned from past experiences push for an alternate way of crop production.In India,adopting high density planting system(HDPS)to boost cotton yield is becoming a growing trend.HDPS has recently been considered a replacement for the current Indian production system.It is also suitable for mechanical harvesting,which reducing labour costs,increasing input use efficiency,timely harvesting timely,maintaining cotton quality,and offering the potential to increase productivity and profitability.This technology has become widespread in globally cotton growing regions.Water management is critical for the success of high density cotton planting.Due to the problem of freshwater availability,more crops should be produced per drop of water.In the high-density planting system,optimum water application is essential to control excessive vegetative growth and improve the translocation of photoassimilates to reproductive organs.Deficit irrigation is a tool to save water without compromising yield.At the same time,it consumes less water than the normal evapotranspiration of crops.This review comprehensively documents the importance of growing cotton under a high-density planting system with deficit irrigation.Based on the current research and combined with cotton production reality,this review discusses the application and future development of deficit irrigation,which may provide theoretical guidance for the sustainable advancement of cotton planting systems. 展开更多
关键词 Deficit irrigation High density planting system Ultra narrow row Cost saving Mechanical harvesting Yield optimization
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Dry Breeding and Dry Planting Techniques for Indica Hybrid Rice in Karst Mountain Areas of Gejiu City
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作者 Guifen WANG Wei SHI 《Plant Diseases and Pests》 2024年第2期34-36,共3页
Based on the arable land situation in Gejiu City,upland dry planting of indica hybrid rice is being expanded in Karst mountain areas with a rainfall of over 1400 mm and an altitude of 1100-1600 m to develop grain prod... Based on the arable land situation in Gejiu City,upland dry planting of indica hybrid rice is being expanded in Karst mountain areas with a rainfall of over 1400 mm and an altitude of 1100-1600 m to develop grain production.This paper gives a specific description of hybrid rice upland dry seedling technology,upland transplanting technology,fertilization technology,field management,weed prevention and control technology,and disease and pest control. 展开更多
关键词 Karst mountain area Hybrid rice Dry breeding Dry planting
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Research on Public Engineering Emergency Decision-Making Based on Multi-Granularity Language Information
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作者 Huajun Liu Zengqiang Wang 《Journal of Architectural Research and Development》 2024年第1期32-37,共6页
To effectively deal with fuzzy and uncertain information in public engineering emergencies,an emergency decision-making method based on multi-granularity language information is proposed.Firstly,decision makers select... To effectively deal with fuzzy and uncertain information in public engineering emergencies,an emergency decision-making method based on multi-granularity language information is proposed.Firstly,decision makers select the appropriate language phrase set according to their own situation,give the preference information of the weight of each key indicator,and then transform the multi-granularity language information through consistency.On this basis,the sequential optimization technology of the approximately ideal scheme is introduced to obtain the weight coefficient of each key indicator.Subsequently,the weighted average operator is used to aggregate the preference information of each alternative scheme with the relative importance of decision-makers and the weight of key indicators in sequence,and the comprehensive evaluation value of each scheme is obtained to determine the optimal scheme.Lastly,the effectiveness and practicability of the method are verified by taking the earthwork collapse accident in the construction of a reservoir as an example. 展开更多
关键词 Public engineering EMERGENCY Multi-granularity language decision-making
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A Blind Spot in the Reframing of a Universe of Possibles: Towards a Suitable Model for Decision-Making Theory and A.I.
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作者 Gilbert Giacomoni 《Journal of Applied Mathematics and Physics》 2024年第6期2172-2189,共18页
Bayesian inference model is an optimal processing of incomplete information that, more than other models, better captures the way in which any decision-maker learns and updates his degree of rational beliefs about pos... Bayesian inference model is an optimal processing of incomplete information that, more than other models, better captures the way in which any decision-maker learns and updates his degree of rational beliefs about possible states of nature, in order to make a better judgment while taking new evidence into account. Such a scientific model proposed for the general theory of decision-making, like all others in general, whether in statistics, economics, operations research, A.I., data science or applied mathematics, regardless of whether they are time-dependent, have in common a theoretical basis that is axiomatized by relying on related concepts of a universe of possibles, especially the so-called universe (or the world), the state of nature (or the state of the world), when formulated explicitly. The issue of where to stand as an observer or a decision-maker to reframe such a universe of possibles together with a partition structure of knowledge (i.e. semantic formalisms), including a copy of itself as it was initially while generalizing it, is not addressed. Memory being the substratum, whether human or artificial, wherein everything stands, to date, even the theoretical possibility of such an operation of self-inclusion is prohibited by pure mathematics. We make this blind spot come to light through a counter-example (namely Archimedes’ Eureka experiment) and explore novel theoretical foundations, fitting better with a quantum form than with fuzzy modeling, to deal with more than a reference universe of possibles. This could open up a new path of investigation for the general theory of decision-making, as well as for Artificial Intelligence, often considered as the science of the imitation of human abilities, while being also the science of knowledge representation and the science of concept formation and reasoning. 展开更多
关键词 decision-making INNOVATION Universe of Possibles A.I. Quantum Form Fuzzy Modeling
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