Resilience effects for household food expenditure and dietary diversity in rural western China

A more resilient livelihood is increasingly recognized as an efficient way to improve vulnerable households’food security and optimize their dietary decisions.This study quantifies rural household resilience in western China,identifies the three pillars(absorptive capacity,adaptive capacity,and transformative capacity)contribution to resilience,and then establishes the estimated Resilience Capacity Index(RCI)linked with food security and dietary diversity supported by the multiple indicator multiple cause(MIMIC)model.Results show that,despite geographical heterogeneity,the RCI consistently increased from 2015 to 2021.Households with a higher RCI inheriting better capacity to deal with risk and shocks are significantly and positively correlated with increasing food expenditure and diversifying food choices.It can be because resilient households will allocate more money to food expenditure instead of saving for livelihood uncertainty.Thus,policymakers can provide more incentives for rural households to adopt more dynamic and effective risk management strategies.This,in turn,could yield positive spillover effects by preventing human capital loss associated with dietary-related chronic diseases and mortality.

Patient satisfaction and follow-up adherence to glaucoma case management clinic in China

AIM:To assess glaucoma patient satisfaction and follow-up adherence in case management and identify associated predictors to improve healthcare quality and patient outcomes.METHODS:In this cross-sectional study,a total of 119 patients completed a Patient Satisfaction Questionnaire-18 and a sociodemographic questionnaire.Clinical data was obtained from the case management system.Follow-up adherence was defined as completing each follow-up within±30d of the scheduled time set by ophthalmologists during the study period.RESULTS:Average satisfaction scored 78.65±7,with an average of 4.39±0.58 across the seven dimensions.Age negatively correlated with satisfaction(P=0.008),whilst patients with follow-up duration of 2 or more years reported higher satisfaction(P=0.045).Multivariate logistics regression analysis revealed that longer follow-up durations were associated with lower follow-up adherence(OR=0.97,95%CI,0.95-1.00,P=0.044).Additionally,patients with suspected glaucoma(OR=2.72,95%CI,1.03-7.20,P=0.044)and those with an annual income over 100000 Chinese yuan demonstrated higher adherence(OR=5.57,95%CI,1.00-30.89,P=0.049).CONCLUSION:The case management model proves effective for glaucoma patients,with positive adherence rates.The implementation of this model can be optimized in the future based on the identified factors and extended to glaucoma patients in more hospitals.

Advances in Zika virus vaccines and therapeutics:A systematic review

Zika virus(ZIKV)is the causative agent of a viral infection that causes neurological complications in newborns and adults worldwide.Its wide transmission route and alarming spread rates are of great concern to the scientific community.Numerous trials have been conducted to develop treatment options for ZIKV infection.This review highlights the latest developments in the fields of vaccinology and pharmaceuticals developments for ZIKV infection.A systematic and comprehensive approach was used to gather relevant and up-to-date data so that inferences could be made about the gaps in therapeutic development.The results indicate that several therapeutic interventions are being tested against ZIKV infection,such as DNA vaccines,subunit vaccines,live-attenuated vaccines,virus-vector-based vaccines,inactivated vaccines,virus-like particles,and mRNA-based vaccines.In addition,approved anti-ZIKV drugs that can reduce the global burden are discussed.Although many vaccine candidates for ZIKV are at different stages of development,none of them have received Food and Drug Authority approval for use up to now.The issue of side effects associated with these drugs in vulnerable newborns and pregnant women is a major obstacle in the therapeutic pathway.

Heat transfer enhanced inorganic phase change material compositing carbon nanotubes for battery thermal management and thermal runaway propagation mitigation

Developing technologies that can be applied simultaneously in battery thermal management(BTM)and thermal runaway(TR)mitigation is significant to improving the safety of lithium-ion battery systems.Inorganic phase change material(PCM)with nonflammability has the potential to achieve this dual function.This study proposed an encapsulated inorganic phase change material(EPCM)with a heat transfer enhancement for battery systems,where Na_(2)HPO_(4)·12H_(2)O was used as the core PCM encapsulated by silica and the additive of carbon nanotube(CNT)was applied to enhance the thermal conductivity.The microstructure and thermal properties of the EPCM/CNT were analyzed by a series of characterization tests.Two different incorporating methods of CNT were compared and the proper CNT adding amount was also studied.After preparation,the battery thermal management performance and TR propagation mitigation effects of EPCM/CNT were further investigated on the battery modules.The experimental results of thermal management tests showed that EPCM/CNT not only slowed down the temperature rising of the module but also improved the temperature uniformity during normal operation.The peak battery temperature decreased from 76℃to 61.2℃at 2 C discharge rate and the temperature difference was controlled below 3℃.Moreover,the results of TR propagation tests demonstrated that nonflammable EPCM/CNT with good heat absorption could work as a TR barrier,which exhibited effective mitigation on TR and TR propagation.The trigger time of three cells was successfully delayed by 129,474 and 551 s,respectively and the propagation intervals were greatly extended as well.

Overview of the immunological mechanisms in hepatitis B virus reactivation:Implications for disease progression and management strategies

Hepatitis B virus(HBV)reactivation is a clinically significant challenge in disease management.This review explores the immunological mechanisms underlying HBV reactivation,emphasizing disease progression and management.It delves into host immune responses and reactivation’s delicate balance,spanning innate and adaptive immunity.Viral factors’disruption of this balance,as are interac-tions between viral antigens,immune cells,cytokine networks,and immune checkpoint pathways,are examined.Notably,the roles of T cells,natural killer cells,and antigen-presenting cells are discussed,highlighting their influence on disease progression.HBV reactivation’s impact on disease severity,hepatic flares,liver fibrosis progression,and hepatocellular carcinoma is detailed.Management strategies,including anti-viral and immunomodulatory approaches,are critically analyzed.The role of prophylactic anti-viral therapy during immunosuppressive treatments is explored alongside novel immunotherapeutic interventions to restore immune control and prevent reactivation.In conclusion,this compre-hensive review furnishes a holistic view of the immunological mechanisms that propel HBV reactivation.With a dedicated focus on understanding its implic-ations for disease progression and the prospects of efficient management stra-tegies,this article contributes significantly to the knowledge base.The more profound insights into the intricate interactions between viral elements and the immune system will inform evidence-based approaches,ultimately enhancing disease management and elevating patient outcomes.The dynamic landscape of management strategies is critically scrutinized,spanning anti-viral and immunomodulatory approaches.The role of prophylactic anti-viral therapy in preventing reactivation during immunosuppressive treatments and the potential of innovative immunotherapeutic interventions to restore immune control and proactively deter reactivation.

Whole-process case management effects on mental state and selfcare ability in patients with liver cancer

BACKGROUND Regarding the incidence of malignant tumors in China,the incidence of liver cancer ranks fourth,second only to lung,gastric,and esophageal cancers.The case fatality rate ranks third after lung and cervical cancer.In a previous study,the whole-process management model was applied to patients with breast cancer,which effectively reduced their negative emotions and improved treatment adherence and nursing satisfaction.METHODS In this single-center,randomized,controlled study,60 randomly selected patients with liver cancer who had been admitted to our hospital from January 2021 to January 2022 were randomly divided into an observation group(n=30),who received whole-process case management on the basis of routine nursing mea-sures,and a control group(n=30),who were given routine nursing measures.We compared differences between the two groups in terms of anxiety,depression,the level of hope,self-care ability,symptom distress,sleep quality,and quality of life.RESULTS Post-intervention,Hamilton anxiety scale,Hamilton depression scale,memory symptom assessment scale,and Pittsburgh sleep quality index scores in both groups were lower than those pre-intervention,and the observation group had lower scores than the control group(P<0.05).Herth hope index,self-care ability assessment scale-revision in Chinese,and quality of life measurement scale for patients with liver cancer scores in both groups were higher than those pre-intervention,with higher scores in the observation group compared with the control group(P<0.05).CONCLUSION Whole-process case management can effectively reduce anxiety and depression in patients with liver cancer,alleviate symptoms and problems,and improve the level of hope,self-care ability,sleep quality,and quality of life,as well as provide feasible nursing alternatives for patients with liver cancer.

基于深度学习的物流跟踪管理

利用先进的人工智能和计算机视觉技术,物流管理取得了重大进展。如何建立一套能够有效解决物体遮挡、运动模糊、目标相似等实际问题的检测技术,是一个重要的挑战。文章提出了一种基于YOLOv8和Deep-SORT的方法来跟踪货物位置。该系统可以有效地识别、定位、跟踪和计数镜头前的货物。称之为“warehouse management”,该算法基于示例跟踪范式,并将跟踪应用于检测对象的边界框。在此基础上,自动识别感兴趣区域(ROI),有效消除不需要物体。我们的F1的分数是0.816 7。

Symptom presentation and evolution in the first 48 hours after injury are associated with return to play after concussion in elite Rugby Union

Background:Return to play(RTP)in elite rugby is managed using a 6-stage graduated RTP protocol,which can result in clearance to play within 1 week of injury.We aimed to explore how symptom,cognitive,and balance presentation and evolution during concussion screens 2 h(head injury assessment(HIA2)and 48 h(HIA3)after injury were associated with time to RTP)to identify whether a more conservative graduated RTP may be appropriate.Methods:A retrospective cohort study was conducted in 380 concussed rugby players from elite men’s rugby over 3 consecutive seasons.Players were classified as shorter or longer returns,depending on whether RTP occurred within 7 days(allowing them to be considered to play the match 1 week after injury)or longer than 8 days,respectively.Symptom,cognitive,and balance performance during screens was assessed relative to baseline(normal or abnormal)and to the preceding screen(improving or worsening).Associations between sub-test abnormalities and RTP time were explored using odds ratios(OR,longer vs.shorter).Median day absence was compared between players with abnormal or worsening results and those whose results were normal or improving.Results:Abnormal symptom results during screens 2 h and 48 h after concussion were associated with longer return time(HIA2:OR=2.21,95%confidence interval(95%CI):1.39-3.50;HIA3:OR=3.30,95%CI:1.89-5.75).Worsening symptom number or severity from the time of injury to 2 h and 48 h post-injury was associated with longer return(HIA2:OR=2.49,95%CI:1.36-4.58;HIA3:OR=3.34,95%CI:1.10-10.15).Median days absence was greater in players with abnormal symptom results at both HIA2 and HIA3.Cognitive and balance performance were not associated with longer return and did not affect median days absence.Conclusion:Symptom presentation and evolution within 48 h of concussion were associated with longer RTP times.This may guide a more conservative approach to RTP,while still adhering to individualized concussion management principles.

Adaptive Integrated Coastal Zone Planning:History,Challenges,Advances,and Perspectives

Coastal zones are dynamic,rich environments,now densely populated,and increasingly challenged by human and climatechange pressures.Effective long-term integrated coastal zone planning is needed to ensure sustainable environmental protection and economic development.In this study,we reviewed the history of coastal zone planning since its birth in the 1950s based on the literature retrieved from the Web of Science(Core Collection)from 2000–2023,then summarized the tools and spatial allocation methods commonly used in the planning process,and finally proposed potential solutions to the challenges faced.The results show that after decades of development,coastal zone planning has changed from a decentralized activity to a targeted and integrated one,with an increasing emphasis on the ecosystem approach and the use of multiple planning tools.Spatial analysis techniques and environmental modelling software have become increasingly popular.Linear programming and overlay analysis are common approaches when performing spatial optimization,but land-sea interactions and planning in the marine parts still lack in-depth analysis and practical experience.We are also aware that the challenges posed by the integration of administrative hierarchies,scoping and conservation objectives,stakeholder participation,consideration of social dimensions,and climate change are pervasive throughout the planning process.There is an urgent need to develop more flexible and accurate spatial modelling tools,as well as more efficient participatory methods,and to focus on the holistic nature of the land-sea system to create more resilient and sustainable coastal zones.

Irrigation and nitrogen fertiliser optimisation in protected vegetable fields of northern China:Achieving environmental and agronomic sustainability

Globally,sub-optimal use of nitrogen (N) fertiliser and elevated N irrigation groundwater have led to high leached nitrate (NO_(3)^(–)) losses from protected vegetable field systems.Optimising fertiliser and irrigation management in different soil types is crucial to reduce future N loads from such systems.The present 4-year study examined leached N loads from lysimeter monitoring arrays set up across 18 protected vegetable system sites encompassing the dominant soil types of northern China.The treatments applied at each field site were:1) a high N and high irrigation input treatment (HNHI);2) a low N but high irrigation input treatment (LNHI) and 3) a low N with low irrigation input treatment (LNLI).Results showed that the mean annual leached total nitrogen loads from the HNHI,LNHI and LNLI treatments were 325,294 and 257 kg N ha^(–1) in the fluvo-aquic soil,114,100 and 78 kg N ha^(–1) in the cinnamon soil and 79,68 and 57 kg N ha^(–1) in the black soil,respectively.The N dissolved in irrigation water in the fluvo-aquic soil areas was 8.26-fold higher than in the cinnamon areas.A structural equation model showed that N fertiliser inputs and leaching water amounts explained 14.7 and 81.8%of the variation of leached N loads,respectively.Correspondingly,reducing irrigation water by 21.5%decreased leached N loads by 20.9%,while reducing manure N and chemical N inputs by 22 and 25%decreased leached N loads by only 9.5%. This study highlights that protected vegetable fields dominated by fluvo-aquic soil need management to curtail leached N losses in northern China.

On Designs of Decentralized Reputation Management for Permissioned Blockchain Networks

In permissioned blockchain networks,the Proof of Authority(PoA)consensus,which uses the election of authorized nodes to validate transactions and blocks,has beenwidely advocated thanks to its high transaction throughput and fault tolerance.However,PoA suffers from the drawback of centralization dominated by a limited number of authorized nodes and the lack of anonymity due to the round-robin block proposal mechanism.As a result,traditional PoA is vulnerable to a single point of failure that compromises the security of the blockchain network.To address these issues,we propose a novel decentralized reputation management mechanism for permissioned blockchain networks to enhance security,promote liveness,and mitigate centralization while retaining the same throughput as traditional PoA.This paper aims to design an off-chain reputation evaluation and an on-chain reputation-aided consensus.First,we evaluate the nodes’reputation in the context of the blockchain networks and make the reputation globally verifiable through smart contracts.Second,building upon traditional PoA,we propose a reputation-aided PoA(rPoA)consensus to enhance securitywithout sacrificing throughput.In particular,rPoA can incentivize nodes to autonomously form committees based on reputation authority,which prevents block generation from being tracked through the randomness of reputation variation.Moreover,we develop a reputation-aided fork-choice rule for rPoA to promote the network’s liveness.Finally,experimental results show that the proposed rPoA achieves higher security performance while retaining transaction throughput compared to traditional PoA.

Role of outdoor trees on pedestrian wind and thermal conditions around a pre-education building for sustainable energy management

Finding sustainable energy resources is essential to face the increasing energy demand.Trees are an important part of ancient architecture but are becoming rare in urban areas.Trees can control and tune the pedestrian-level wind velocity and thermal condition.In this study,a numerical investigation is employed to assess the role of trees planted in the windward direction of the building complex on the thermal and pedestrian wind velocity conditions around/inside a pre-education building located in the center of the complex.Compared to the previous studies(which considered only outside buildings),this work considers the effects of trees on microclimate change both inside/outside buildings.Effects of different parameters including the leaf area density and number of trees,number of rows,far-field velocity magnitude,and thermal condition around the main building are assessed.The results show that the flow velocity in the spacing between the first-row buildings is reduced by 30%-40% when the one-row trees with 2 m height are planted 15 m farther than the buildings.Furthermore,two rows of trees are more effective in higher velocities and reduce the maximum velocity by about 50%.The investigation shows that trees also could reduce the temperature by about 1℃around the building.

Acaricidal effect of the antimicrobial metabolite xenocoumacin 1 on spider mite control

The two-spotted spider mite,Tetranychus urticae Koch,is one of the most harmful pests in many agroecosystems worldwide.To effectively manage this pest,there is an urgent need to develop novel bio-active acaricides that support integrated pest management strategies targeting T.urticae.In this study,we explored the acaricidal effects of xenocoumacin 1 (Xcn1) on T.urticae and its predator Neoseiulus californicus using the highly puri?ed compound.Xcn1 was extracted and purified from the cell-free supernatant of the Xenorhabdus nematophila CB6 mutant constructed by the easy promoter activated compound identi?cation (easyPACId) method.When the concentration of Xcn1 exceeded 100μg mL~(–1),the survival rate of spider mite adults declined to below 40%and the fecundity was decreased by 80%at six days post-application.At concentrations of 25 and 50μg mL~(–1),Xcn1 signi?cantly impeded spider mite development by inhibiting the molt.However,neither concentration had any adverse effects on the survival or reproduction of the predatory mite N.californicus.The results from laboratory and semi-?eld experiments consistently demonstrated the effectiveness of the antimicrobial metabolite Xcn1 in controlling pest mites at both the molecular and physiological levels.Our study offers a promising possibility that combines the compatible biocontrol agents of Xcn1 and predatory mites for integrated pest mite control.

For Mega-Constellations: Edge Computing and Safety Management Based on Blockchain Technology

In mega-constellation Communication Systems, efficient routing algorithms and data transmission technologies are employed to ensure fast and reliable data transfer. However, the limited computational resources of satellites necessitate the use of edge computing to enhance secure communication.While edge computing reduces the burden on cloud computing, it introduces security and reliability challenges in open satellite communication channels. To address these challenges, we propose a blockchain architecture specifically designed for edge computing in mega-constellation communication systems. This architecture narrows down the consensus scope of the blockchain to meet the requirements of edge computing while ensuring comprehensive log storage across the network. Additionally, we introduce a reputation management mechanism for nodes within the blockchain, evaluating their trustworthiness, workload, and efficiency. Nodes with higher reputation scores are selected to participate in tasks and are appropriately incentivized. Simulation results demonstrate that our approach achieves a task result reliability of 95% while improving computational speed.

An optimized strategy of nitrogen-split application based on the leaf positional differences in chlorophyll meter readings

Modern rice production faces the dual challenges of increasing grain yields while reducing inputs of chemical fertilizer.However,the disequilibrium between the nitrogen(N)supplement from the soil and the demand for N of plants is a serious obstacle to achieving these goals.Plant-based diagnosis can help farmers make better choices regarding the timing and amount of topdressing N fertilizer.Our objective was to evaluate a non-destructive assessment of rice N demands based on the relative SPAD value(RSPAD)due to leaf positional differences.In this study,two field experiments were conducted,including a field experiment of different N rates(Exp.I)and an experiment to evaluate the new strategy of nitrogen-split application based on RSPAD(Exp.II).The results showed that higher N inputs significantly increased grain yield in modern high yielding super rice,but at the expense of lower nitrogen use efficiency(NUE).The N nutrition index(NNI)can adequately differentiate situations of excessive,optimal,and insufficient N nutrition in rice,and the optimal N rate for modern high yielding rice is higher than conventional cultivars.The RSPAD is calculated as the SPAD value of the top fully expanded leaf vs.the value of the third leaf,which takes into account the non-uniform N distribution within a canopy.The RSPAD can be used as an indicator for higher yield and NUE,and guide better management of N fertilizer application.Furthermore,we developed a new strategy of nitrogen-split application based on RSPAD,in which the N rate was reduced by 18.7%,yield was increased by 1.7%,and the agronomic N use efficiency was increased by 27.8%,when compared with standard farmers'practices.This strategy of N fertilization shows great potential for ensuring high yielding and improving NUE at lower N inputs.

High performance wide bandgap perovskite solar cell with low V_(OC) deficit less than 0.4 V

Wide bandgap perovskite solar cells(PSCs)have attracted significant attention because they can be applied to the top cells of tandem solar cells.However,high open-circuit voltage(V_(OC))deficit(>0.4 V)result from poor crystallization and high non-radiative recombination losses become a serious limitation in the pursuit of high performance.Here,the relevance between different Pbl_(2)proportions and performance parameters are revealed through analysis of surface morphology,residual stress,and photostability.The increase of Pbl_(2)proportion promotes crystal growth and reduces the work function of the perovskite film surface and promotes the energy level alignment with the carrier transport layer,which decreased the V_(OC)deficit.However,residual PbI_(2)exacerbated the stress level of perovskite film,and the resulting lattice disorder deteriorated the photostability of the device.Ultimately,after the synergistic passivation of residual PbI_(2)and PEAI,the V_(OC)achieves 1.266 V and V_(OC)deficit is less than 0.4 V,the record value in wide bandgap PSCs.

面向工业化种植的光热管理农膜——机遇与挑战

As indispensable parts of greenhouses and plant factories,agricultural covering films play a prominent role in regulating microclimate environments.Polyethylene covering films directly transmit the full solar spectrum.However,this high level of sunlight transmission may be inappropriate or even harmful for crops with specific photothermal requirements.Modern greenhouses are integrated with agricultural covering materials,heating,ventilation,and air conditioning(HVAC)systems,and smart irrigation and communication technologies to maximize planting efficiency.This review provides insight into the photothermal requirements of crops and ways to meet these requirements,including new materials based on passive radiative cooling and light scattering,simulations to evaluate the energy consumption and environmental conditions in a greenhouse,and data mining to identify key biological growth factors and thereby improve new covering films.Finally,future challenges and directions for photothermalmanagement agricultural films are elaborated on to bridge the gap between lab-scale research and large-scale practical applications.

Soil resilience assessment using soil profile descriptions and Analytic Hierarchy Process in Mediterranean mountains considering diverse fire occurrences

Wildfires are complex natural phenomena that exert significant impacts on landscapes,societies,and economies.Understanding the concept of resilience is crucial in mitigating its possible negative impacts,as it involves preparing for,responding to,and recovering from wildfires.This research aims to demonstrate the utility of in situ soil profile description in assessing land use resilience using an Analytic Hierarchy Process(AHP)through an expert panel survey.The study examines a catchment located in the Balearic Islands,considering two fire occurrences(once and twice),comparing abandoned agricultural terraces and natural hillslopes.The results demonstrated that the priority ranking of variables to assess soil profile resilience against wildfires,determined by a panel of 10 experts,identified horizon depth(25.1%),slope inclination(21.5%),and hydrological connectivity(16.6%)as the most crucial factors.Other variables,such as number and size of roots,structure of pedal soil material,size class structure,and rock fragments,also contributed to resilience but to a lesser extent,with scores ranging from 5.7%to 9.6%.Analyzing the priorities established by the experts using AHP,the results showed that the least resilient soil horizon was H1 of the control hillslope,especially under high and low connectivity processes,which aligned with the loss of superficial soil horizons after one and two wildfires.Hillslopes showed greater changes in resilience after occurring wildfires compared to terraces,with the most significant alterations occurring after the second wildfire event.This study addresses a significant knowledge gap in the field by highlighting the interconnectedness of wildfires,resilience,and land use,providing insights into land management strategies for wildfire-prone regions.

Enhancing Secure Development in Globally Distributed Software Product Lines: A Machine Learning-Powered Framework for Cyber-Resilient Ecosystems

Embracing software product lines(SPLs)is pivotal in the dynamic landscape of contemporary software devel-opment.However,the flexibility and global distribution inherent in modern systems pose significant challenges to managing SPL variability,underscoring the critical importance of robust cybersecurity measures.This paper advocates for leveraging machine learning(ML)to address variability management issues and fortify the security of SPL.In the context of the broader special issue theme on innovative cybersecurity approaches,our proposed ML-based framework offers an interdisciplinary perspective,blending insights from computing,social sciences,and business.Specifically,it employs ML for demand analysis,dynamic feature extraction,and enhanced feature selection in distributed settings,contributing to cyber-resilient ecosystems.Our experiments demonstrate the framework’s superiority,emphasizing its potential to boost productivity and security in SPLs.As digital threats evolve,this research catalyzes interdisciplinary collaborations,aligning with the special issue’s goal of breaking down academic barriers to strengthen digital ecosystems against sophisticated attacks while upholding ethics,privacy,and human values.

Artificial Intelligence for Maximizing Agricultural Input Use Efficiency: Exploring Nutrient, Water and Weed Management Strategies

Agriculture plays a crucial role in the economy,and there is an increasing global emphasis on automating agri-cultural processes.With the tremendous increase in population,the demand for food and employment has also increased significantly.Agricultural methods traditionally used to meet these requirements are no longer ade-quate,requiring solutions to issues such as excessive herbicide use and the use of chemical fertilizers.Integration of technologies such as the Internet of Things,wireless communication,machine learning,artificial intelligence(AI),and deep learning shows promise in addressing these challenges.However,there is a lack of comprehensive documentation on the application and potential of AI in improving agricultural input efficiency.To address this gap,a desk research approach was used by utilizing peer-reviewed electronic databases like PubMed,Scopus,Goo-gle Scholar,Web of Science,and Science Direct for relevant articles.Out of 327 initially identified articles,180 were deemed pertinent,focusing primarily on AI’s potential in enhancing yield through better management of nutrients,water,and weeds.Taking into account researchfindings worldwide,we found that AI technologies could assist farmers by providing recommendations on the optimal nutrients to enhance soil quality and deter-mine the best time for irrigation or herbicide application.The present status of AI-driven automation in agricul-ture holds significant promise for optimizing agricultural input utilization and reducing resource waste,particularly in the context of three pillars of crop management,i.e.,nutrient,irrigation,and weed management.