In April 2022,then-President of Mexico Andrés Manuel López Obrador officially implemented the lithium resources nationalization law and established the state-owned enterprise LitioMx to oversee their explora...In April 2022,then-President of Mexico Andrés Manuel López Obrador officially implemented the lithium resources nationalization law and established the state-owned enterprise LitioMx to oversee their exploration,extraction,and processing.His successor,Claudia Sheinbaum,reaffirmed this assertive resource governance policy in October 2024.As a direct consequence,the operations of the Chinese firm,Ganfeng Lithium in Mexico,experienced significant disruption.展开更多
State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.The la...State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.The laboratory was reconstructed based on former State Key Laboratory of Baiyun Obo Rare Earth Resources Researches and Comprehensive Utilization.展开更多
Efficient resource provisioning,allocation,and computation offloading are critical to realizing lowlatency,scalable,and energy-efficient applications in cloud,fog,and edge computing.Despite its importance,integrating ...Efficient resource provisioning,allocation,and computation offloading are critical to realizing lowlatency,scalable,and energy-efficient applications in cloud,fog,and edge computing.Despite its importance,integrating Software Defined Networks(SDN)for enhancing resource orchestration,task scheduling,and traffic management remains a relatively underexplored area with significant innovation potential.This paper provides a comprehensive review of existing mechanisms,categorizing resource provisioning approaches into static,dynamic,and user-centric models,while examining applications across domains such as IoT,healthcare,and autonomous systems.The survey highlights challenges such as scalability,interoperability,and security in managing dynamic and heterogeneous infrastructures.This exclusive research evaluates how SDN enables adaptive policy-based handling of distributed resources through advanced orchestration processes.Furthermore,proposes future directions,including AI-driven optimization techniques and hybrid orchestrationmodels.By addressing these emerging opportunities,thiswork serves as a foundational reference for advancing resource management strategies in next-generation cloud,fog,and edge computing ecosystems.This survey concludes that SDN-enabled computing environments find essential guidance in addressing upcoming management opportunities.展开更多
Efficient resource management within Internet of Things(IoT)environments remains a pressing challenge due to the increasing number of devices and their diverse functionalities.This study introduces a neural network-ba...Efficient resource management within Internet of Things(IoT)environments remains a pressing challenge due to the increasing number of devices and their diverse functionalities.This study introduces a neural network-based model that uses Long-Short-Term Memory(LSTM)to optimize resource allocation under dynam-ically changing conditions.Designed to monitor the workload on individual IoT nodes,the model incorporates long-term data dependencies,enabling adaptive resource distribution in real time.The training process utilizes Min-Max normalization and grid search for hyperparameter tuning,ensuring high resource utilization and consistent performance.The simulation results demonstrate the effectiveness of the proposed method,outperforming the state-of-the-art approaches,including Dynamic and Efficient Enhanced Load-Balancing(DEELB),Optimized Scheduling and Collaborative Active Resource-management(OSCAR),Convolutional Neural Network with Monarch Butterfly Optimization(CNN-MBO),and Autonomic Workload Prediction and Resource Allocation for Fog(AWPR-FOG).For example,in scenarios with low system utilization,the model achieved a resource utilization efficiency of 95%while maintaining a latency of just 15 ms,significantly exceeding the performance of comparative methods.展开更多
The ease of accessing a virtually unlimited pool of resources makes Infrastructure as a Service (IaaS) clouds an ideal platform for running data-intensive workflow applications comprising hundreds of computational tas...The ease of accessing a virtually unlimited pool of resources makes Infrastructure as a Service (IaaS) clouds an ideal platform for running data-intensive workflow applications comprising hundreds of computational tasks. However, executing scientific workflows in IaaS cloud environments poses significant challenges due to conflicting objectives, such as minimizing execution time (makespan) and reducing resource utilization costs. This study responds to the increasing need for efficient and adaptable optimization solutions in dynamic and complex environments, which are critical for meeting the evolving demands of modern users and applications. This study presents an innovative multi-objective approach for scheduling scientific workflows in IaaS cloud environments. The proposed algorithm, MOS-MWMC, aims to minimize total execution time (makespan) and resource utilization costs by leveraging key features of virtual machine instances, such as a high number of cores and fast local SSD storage. By integrating realistic simulations based on the WRENCH framework, the method effectively dimensions the cloud infrastructure and optimizes resource usage. Experimental results highlight the superiority of MOS-MWMC compared to benchmark algorithms HEFT and Max-Min. The Pareto fronts obtained for the CyberShake, Epigenomics, and Montage workflows demonstrate closer proximity to the optimal front, confirming the algorithm’s ability to balance conflicting objectives. This study contributes to optimizing scientific workflows in complex environments by providing solutions tailored to specific user needs while minimizing costs and execution times.展开更多
In 6th Generation Mobile Networks(6G),the Space-Integrated-Ground(SIG)Radio Access Network(RAN)promises seamless coverage and exceptionally high Quality of Service(QoS)for diverse services.However,achieving this neces...In 6th Generation Mobile Networks(6G),the Space-Integrated-Ground(SIG)Radio Access Network(RAN)promises seamless coverage and exceptionally high Quality of Service(QoS)for diverse services.However,achieving this necessitates effective management of computation and wireless resources tailored to the requirements of various services.The heterogeneity of computation resources and interference among shared wireless resources pose significant coordination and management challenges.To solve these problems,this work provides an overview of multi-dimensional resource management in 6G SIG RAN,including computation and wireless resource.Firstly it provides with a review of current investigations on computation and wireless resource management and an analysis of existing deficiencies and challenges.Then focusing on the provided challenges,the work proposes an MEC-based computation resource management scheme and a mixed numerology-based wireless resource management scheme.Furthermore,it outlines promising future technologies,including joint model-driven and data-driven resource management technology,and blockchain-based resource management technology within the 6G SIG network.The work also highlights remaining challenges,such as reducing communication costs associated with unstable ground-to-satellite links and overcoming barriers posed by spectrum isolation.Overall,this comprehensive approach aims to pave the way for efficient and effective resource management in future 6G networks.展开更多
Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the c...Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the current emergency resource allocation of chemical enterprises lacks scientific analysis of accident scenarios,and the individual allocation method of enterprises increases the cost of emergency resource allocation.Given the above problems,this paper proposes a regional collaborative allocation method of emergency resources for enterprises within the chemical industry park(CIP)based on the worst credible accident scenario(WCAS).Firstly,the concept and analysis method of the WCAS is proposed.Then,based on the characteristics and consequences of the accident,the mapping relationship between accident scenarios and emergency resources is established.Finally,an optimization model for regional collaborative allocation of emergency resources is constructed to determine the amount of emergency resource allocation for each enterprise.Through the case study,the emergency resource allocation method based on the WCAS analysis can better meet the demands of accident emergency rescue.Simultaneously,the regional collaborative allocation optimization model can strengthen the cooperation ability among enterprises,greatly reducing the cost of emergency resource allocation for each enterprise.展开更多
Resource allocation remains a challenging issue in communication networks,and its complexity is continuously increasing with the densification of the networks.With the evolution of new wireless technologies such as Fi...Resource allocation remains a challenging issue in communication networks,and its complexity is continuously increasing with the densification of the networks.With the evolution of new wireless technologies such as Fifth Generation(5G)and Sixth Generation(6G)mobile networks,the service level requirements have become stricter and more heterogeneous depending on the use case.In this paper,we review a large body of literature on various resource allocation schemes that are used in particular in mobile wireless communication networks and compare the proposed schemes in terms of performance indicators as well as techniques used.Our review shows that among the strategies proposed in the literature,there is a wide variety of optimization targets and combinations thereof,focusing mainly on performance indicators such as energy efficiency,spectral efficiency,and network capacity.In addition,in this paper,selected algorithms for resource allocation are numerically analyzed through simulations to compare and highlight the importance of how the resource algorithms are implemented to achieve efficient usage of the available spectrum.The performance of selected algorithms is evaluated in a multi-cell heterogeneous network and compared to proportional fair and eICIC,a widely-used combination of resource allocation and interferencemitigation techniques used by communication networks.The results show that one approach may performbetter when looking at the individual average user data rate but worse when looking at the overall spectral or energy efficiency,depending on the category of traffic.The results,therefore,confirm that theremay not be a single algorithmthat visibly outperforms other candidates in terms of all performance criteria.Instead,their efficiency is always a consequence of a strategic choice of goals,and the targeted parameters are optimized at a price.Thus,the development and implementation of resource allocation algorithms must follow concrete usage scenarios and network needs and be highly dependent on the requirements and criteria of network performance.展开更多
State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.
Accurate and effective assessment of hydrothermal resources is crucial in the geothermal industry,given that the global installed capacity for direct use(173303 MW)significantly exceeds that for geothermal power(16260...Accurate and effective assessment of hydrothermal resources is crucial in the geothermal industry,given that the global installed capacity for direct use(173303 MW)significantly exceeds that for geothermal power(16260 MW).Despite the widespread application of various geothermal resource assessment methods,including the volumetric method,Monte Carlo method,analogy,statistical analysis,and numerical methods,there are still limitations faced in terms of data precision and model uncertainty assessment,fracture heterogeneity,boundary conditions,renewable energy attributes,integration of geothermal compensation mechanisms under the“extraction-injection”balance,diversification of economic evaluation metrics,and the establishment of standardized assessment criteria.This review outlines the various methods suitable for different stages of the hydrothermal resource assessment process,and proposes future technical approaches for sustainable development,including improving the accuracy of assessments and establishing standards for geothermal resource evaluation methods,in order to enhance the efficiency of geothermal resource utilization.展开更多
Energy security is a crucial aspect of modern societies,as it directly impacts the availability,accessibility,and reliability of energy sources.The reliance on natural resources and geopolitical factors in shaping ene...Energy security is a crucial aspect of modern societies,as it directly impacts the availability,accessibility,and reliability of energy sources.The reliance on natural resources and geopolitical factors in shaping energy security has gained significant attention in recent years.Natural resources and geopolitical risk are examined in 38 countries at risk of geopolitical conflict between 1990 and 2021 by examining CO_(2) emissions,renewable energy consumption,and foreign direct investment as controlling variables.The long-run analysis conducted in this study focused on slope heterogeneity,Westerlund cointegration,and dynamic panel data estimation.The findings indicated that the energy security index is positively associated with various determinants,including natural resources,geopolitical risk,CO_(2) emissions,and renewable energy consumption.However,foreign direct investment was found to be negatively associated with the energy security index among the selected 38 geopolitical risk countries.The role of natural resources and geopolitical risk in energy security cannot be overlooked.Natural resources provide the raw materials for generating electricity and powering our societies,while geopolitical risks can disrupt energy supply chains and threaten stability.Achieving sustainable energy security requires a comprehensive approach that addresses both aspects of energy provision.Transitioning to renewable energy sources,improving energy efficiency,diversifying energy supplies,promoting international cooperation,and conserving natural resources are essential steps towards a more sustainable and resilient energy future.展开更多
The rich resources and unique environment of the Moon make it an ideal location for human expansion and the utilization of extraterrestrial resources.Oxygen,crucial for supporting human life on the Moon,can be extract...The rich resources and unique environment of the Moon make it an ideal location for human expansion and the utilization of extraterrestrial resources.Oxygen,crucial for supporting human life on the Moon,can be extracted from lunar regolith,which is highly rich in oxygen and contains polymetallic oxides.This oxygen and metal extraction can be achieved using existing metallurgical techniques.Furthermore,the ample reserves of water ice on the Moon offer another means for oxygen production.This paper offers a detailed overview of the leading technologies for achieving oxygen production on the Moon,drawing from an analysis of lunar resources and environmental conditions.It delves into the principles,processes,advantages,and drawbacks of water-ice electrolysis,two-step oxygen production from lunar regolith,and one-step oxygen production from lunar regolith.The two-step methods involve hydrogen reduction,carbothermal reduction,and hydrometallurgy,while the one-step methods encompass fluorination/chlorination,high-temperature decomposition,molten salt electrolysis,and molten regolith electrolysis(MOE).Following a thorough comparison of raw materials,equipment,technology,and economic viability,MOE is identified as the most promising approach for future in-situ oxygen production on the Moon.Considering the corrosion characteristics of molten lunar regolith at high temperatures,along with the Moon's low-gravity environment,the development of inexpensive and stable inert anodes and electrolysis devices that can easily collect oxygen is critical for promoting MOE technology on the Moon.This review significantly contributes to our understanding of in-situ oxygen production technologies on the Moon and supports upcoming lunar exploration initiatives.展开更多
The rapid advent in artificial intelligence and big data has revolutionized the dynamic requirement in the demands of the computing resource for executing specific tasks in the cloud environment.The process of achievi...The rapid advent in artificial intelligence and big data has revolutionized the dynamic requirement in the demands of the computing resource for executing specific tasks in the cloud environment.The process of achieving autonomic resource management is identified to be a herculean task due to its huge distributed and heterogeneous environment.Moreover,the cloud network needs to provide autonomic resource management and deliver potential services to the clients by complying with the requirements of Quality-of-Service(QoS)without impacting the Service Level Agreements(SLAs).However,the existing autonomic cloud resource managing frameworks are not capable in handling the resources of the cloud with its dynamic requirements.In this paper,Coot Bird Behavior Model-based Workload Aware Autonomic Resource Management Scheme(CBBM-WARMS)is proposed for handling the dynamic requirements of cloud resources through the estimation of workload that need to be policed by the cloud environment.This CBBM-WARMS initially adopted the algorithm of adaptive density peak clustering for workloads clustering of the cloud.Then,it utilized the fuzzy logic during the process of workload scheduling for achieving the determining the availability of cloud resources.It further used CBBM for potential Virtual Machine(VM)deployment that attributes towards the provision of optimal resources.It is proposed with the capability of achieving optimal QoS with minimized time,energy consumption,SLA cost and SLA violation.The experimental validation of the proposed CBBMWARMS confirms minimized SLA cost of 19.21%and reduced SLA violation rate of 18.74%,better than the compared autonomic cloud resource managing frameworks.展开更多
Magnesium and magnesium alloys,serving as crucial lightweight structural materials and hydrogen storage elements,find extensive applications in space technology,aviation,automotive,and magnesium-based hydrogen industr...Magnesium and magnesium alloys,serving as crucial lightweight structural materials and hydrogen storage elements,find extensive applications in space technology,aviation,automotive,and magnesium-based hydrogen industries.The global production of primary magnesium has reached approximately 1.2 million tons per year,with anticipated diversification in future applications and significant market demand.Nevertheless,approximately 80%of the world’s primary magnesium is still manufactured through the Pidgeon process,grappling with formidable issues including high energy consumption,massive carbon emission,significant resource depletion,and environmental pollution.The implementation of the relative vacuum method shows potential in breaking through technological challenges in the Pidgeon process,facilitating clean,low-carbon continuous magnesium smelting.This paper begins by introducing the principles of the relative vacuum method.Subsequently,it elucidates various innovative process routes,including relative vacuum ferrosilicon reduction,aluminum thermal reduction co-production of spinel,and aluminum thermal reduction co-production of calcium aluminate.Finally,and thermodynamic foundations of the relative vacuum,a quantitative analysis of the material,energy flows,carbon emission,and production cost for several new processes is conducted,comparing and analyzing them against the Pidgeon process.The study findings reveal that,with identical raw materials,the relative vacuum silicon thermal reduction process significantly decreases raw material consumption,energy consumption,and carbon dioxide emissions by 15.86%,30.89%,and 26.27%,respectively,compared to the Pidgeon process.The relative vacuum process,using magnesite as the raw material and aluminum as the reducing agent,has the lowest magnesium-to-feed ratio,at only 3.385.Additionally,its energy consumption and carbon dioxide emissions are the lowest,at 1.817 tce/t Mg and 7.782 t CO_(2)/t Mg,respectively.The energy consumption and carbon emissions of the relative vacuum magnesium smelting process co-producing calcium aluminate(12CaO·7Al_(2)O_(3),3CaO·Al_(2)O_(3),and CaO·Al_(2)O_(3))are highly correlated with the consumption of dolomite in the raw materials.When the reduction temperature is around 1473.15 K,the critical volume fraction of magnesium vapor for different processes varies within the range of 5%–40%.Production cost analysis shows that the relative vacuum primary magnesium smelting process has significant economic benefits.This paper offers essential data support and theoretical guidance for achieving energy efficiency,carbon reduction in magnesium smelting,and the industrial adoption of innovative processes.展开更多
Energy poverty in developing countries is a critical issue characterized by the lack of access to modern energy services,such as electricity and clean cooking facilities,as marked in SDG 7.This study explores the corr...Energy poverty in developing countries is a critical issue characterized by the lack of access to modern energy services,such as electricity and clean cooking facilities,as marked in SDG 7.This study explores the correlations between energy poverty,energy intensity,resource abundance,and income inequality,as these factors have been theorized to play important roles in influencing energy poverty in developing countries.By observing that the dataset is heterogeneous across the countries and over the time frame,we use the Method of Moments Quantile Regression(MMQR)to analyze our developing countries’data from 2000 to 2019.Our findings indicate that energy intensity is a significant factor influencing energy poverty,suggesting that higher energy consumption relative to the sample countries can exacerbate this issue.Additionally,we observe that income inequality within the sample countries is a critical determinant of energy poverty levels,highlighting the dynamics between economic disparity and access to energy resources.Interestingly,our study reveals that resource abundance acts as a blessing rather than a curse in terms of energy poverty,implying that countries rich in natural resources may have better opportunities to combat energy deprivation.Finally,we emphasize the vital role of financial markets in addressing energy poverty on a global scale,suggesting that robust financial systems can facilitate investments and innovations aimed at improving energy access for vulnerable populations.The results from the robustness analysis support the empirical results obtained from the main estimation.The empirical findings of the present study advance important comprehensions for policymakers to adopt energy policies that address the complex challenges of energy poverty and promote inclusive energy access.展开更多
Lithium iron phosphate(LiFePO_(4),LFP)batteries have shown extensive adoption in power applications in recent years for their reliable safety,high theoretical capability and low cost.Nevertheless,the finite lifespan o...Lithium iron phosphate(LiFePO_(4),LFP)batteries have shown extensive adoption in power applications in recent years for their reliable safety,high theoretical capability and low cost.Nevertheless,the finite lifespan of these batteries necessitates the future processing of a significant number of spent LFP batteries,underscoring the urgent need for the development of both efficient and eco-friendly recycling methods.This study combines the advantages of wet leaching and direct regeneration methods,leveraging citric acid's multifaceted role to streamline the combined leaching and hydrothermal processes.Results indicate that citric acid efficiently leaches all elements from spent LFP batteries.Furthermore,through its unique structure,it enhances hydrothermal regeneration by stabilizing metal ions and controlling crystal growth,and also acts as a carbon source for the surface carbon coating of regenerated LFP(RLFP).The R-LFP shows outstanding electrochemical stability,achieving a discharge capacity of 155.1 mAh.g^(-1)at 0.1C,with a capacity retention rate of 93.2%after 300 cycles at 1C.Furthermore,economic and environmental analyses demonstrate this method's superior cost-effectiveness and sustainability.Therefore,the method proposed in this study is efficient,simple and avoids the complex process of element separation,innovatively using a single reagent to achieve closed-loop recycling of LFP batteries,providing a novel and effective solution for the resource sustainability application.展开更多
Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and ...Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.展开更多
[Objective]The channel straightening project of the Pinglu Canal has fragmented the river course,compromising the integrity of original river course and causing ecosystem patchiness.Understanding the current status of...[Objective]The channel straightening project of the Pinglu Canal has fragmented the river course,compromising the integrity of original river course and causing ecosystem patchiness.Understanding the current status of fish resources and the characteristics of their diversity is crucial for the ecological management of the Pinglu Canal.[Methods]During the spring and autumn in 2021 and 2022,a survey of fish resources and species diversity in the Pinglu Canal was conducted using multi-mesh gill nets.A total of 125 fish species were collected,belonging to 10 orders,34 families,and 89 genera.[Results]The result showed that the Pinglu Canal contained three nationally protected Class II species,two endemic species of the Qinjiang River,three anadromous/migratory species,and eight invasive species,accounting for 2.4%,1.6%,2.4%,and 6.4%of the total species,respectively.The fish community primarily consisted of mid-and bottom-dwelling,adhesive-egg-laying,and omnivorous species.The Shannon-Wiener,Simpson,Margalef,and Pielou indices of the fish community in the Pinglu Canal ranged from 2.347 to 2.757,0.081 to 0.151,3.493 to 4.382,and 0.812 to 0.892,respectively.These indices showed relatively uniform distribution across different river reaches.[Conclusion]The result indicate that the fish community structure in the Pinglu Canal is relatively uniform.The reach from the Yujiang River to the Shaping River shows higher stability,while other river reaches experience moderate or severe disturbances.This study provides supplementary baseline data on the fish community structure in the Pinglu Canal and explores the potential impact of inter-basin connectivity on fish resources,aiming to provide a scientific basis for habitat restoration assessments after the channel straightening project.展开更多
The Chinese tree shrew has gained prominence as a model organism due to its phylogenetic proximity to primates,offering distinct advantages over traditional rodent models in biomedical research.However,the neuroanatom...The Chinese tree shrew has gained prominence as a model organism due to its phylogenetic proximity to primates,offering distinct advantages over traditional rodent models in biomedical research.However,the neuroanatomy of this species remains insufficiently defined,limiting its utility in neurophysiological and neuropathological studies.In this study,immunofluorescence microscopy was employed to comprehensively map the distribution of three calciumbinding proteins,parvalbumin,calbindin D-28k,and calretinin,across the tree shrew cerebrum.Serial brain sections in sagittal,coronal,and horizontal planes from 12 individuals generated a dataset of 3638 cellular-resolution images.This dataset,accessible via Science Data Bank(https://doi.org/10.57760/sciencedb.23471),provides detailed region-and laminar-selective distributions of calcium-binding proteins valuable for the cyto-and chemoarchitectural characterization of the tree shrew cerebrum.This resource will not only advance our understanding of brain organization and facilitate basic and translational neuroscience research in tree shrews but also enhance comparative and evolutionary analyses across species.展开更多
BACKGROUND Cytomegalovirus(CMV)prophylaxis with valganciclovir and ganciclovir is associated with elevated neutropenia and leukopenia risk in kidney transplant recipients,although the impact of these events on healthc...BACKGROUND Cytomegalovirus(CMV)prophylaxis with valganciclovir and ganciclovir is associated with elevated neutropenia and leukopenia risk in kidney transplant recipients,although the impact of these events on healthcare resource utilization(HCRU)and clinical outcomes is unclear.AIM To quantify clinical events and HCRU associated with neutropenia and leukope-nia among adults receiving valganciclovir and/or ganciclovir post-kidney trans-plantation.METHODS Adult kidney transplant recipients receiving valganciclovir and/or ganciclovir prophylaxis were identified in the TriNetX database from 2012 to 2021.Patient characteristics were evaluated in the 1-year period pre-first transplant.HCRU and adjusted event rates per person-year were evaluated in follow-up year 1 and years 2-5 after first kidney transplantation among cohorts with vs without neutropenia and/or leukopenia.RESULTS Of 15398 identified patients,the average age was 52.39 years and 58.70%were male.Patients with neutropenia and/or leukopenia had greater risk of clinical events for CMV-related events,opportunistic infections,use of granulocyte colony stimulating factor,and hospitalizations(relative risk>1 in year 1 and years 2-5).Patients with vs without neutropenia and/or leukopenia had higher HCRU in year 1 and years 2-5 post kidney transplantation,including the mean number of inpatient admissions(year 1:3.47 vs 2.76;years 2-5:2.70 vs 2.29)and outpatient visits(48.97 vs 34.42;31.73 vs 15.59,respectively),as well as the mean number of labs(1654.55 vs 1182.27;622.37 vs 327.89).CONCLUSION Adults receiving valganciclovir and/or ganciclovir prophylaxis post-kidney transplantation had greater risk of neutropenia and/or leukopenia,which were associated with higher clinical event rates and HCRU up to 5 years post-transplantation.These findings suggest the need for alternative prophylaxis options with lower myelosup-pressive effects to improve patient outcomes.展开更多
文摘In April 2022,then-President of Mexico Andrés Manuel López Obrador officially implemented the lithium resources nationalization law and established the state-owned enterprise LitioMx to oversee their exploration,extraction,and processing.His successor,Claudia Sheinbaum,reaffirmed this assertive resource governance policy in October 2024.As a direct consequence,the operations of the Chinese firm,Ganfeng Lithium in Mexico,experienced significant disruption.
文摘State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.The laboratory was reconstructed based on former State Key Laboratory of Baiyun Obo Rare Earth Resources Researches and Comprehensive Utilization.
文摘Efficient resource provisioning,allocation,and computation offloading are critical to realizing lowlatency,scalable,and energy-efficient applications in cloud,fog,and edge computing.Despite its importance,integrating Software Defined Networks(SDN)for enhancing resource orchestration,task scheduling,and traffic management remains a relatively underexplored area with significant innovation potential.This paper provides a comprehensive review of existing mechanisms,categorizing resource provisioning approaches into static,dynamic,and user-centric models,while examining applications across domains such as IoT,healthcare,and autonomous systems.The survey highlights challenges such as scalability,interoperability,and security in managing dynamic and heterogeneous infrastructures.This exclusive research evaluates how SDN enables adaptive policy-based handling of distributed resources through advanced orchestration processes.Furthermore,proposes future directions,including AI-driven optimization techniques and hybrid orchestrationmodels.By addressing these emerging opportunities,thiswork serves as a foundational reference for advancing resource management strategies in next-generation cloud,fog,and edge computing ecosystems.This survey concludes that SDN-enabled computing environments find essential guidance in addressing upcoming management opportunities.
基金funding of the Deanship of Graduate Studies and Scientific Research,Jazan University,Saudi Arabia,through Project Number:ISP-2024.
文摘Efficient resource management within Internet of Things(IoT)environments remains a pressing challenge due to the increasing number of devices and their diverse functionalities.This study introduces a neural network-based model that uses Long-Short-Term Memory(LSTM)to optimize resource allocation under dynam-ically changing conditions.Designed to monitor the workload on individual IoT nodes,the model incorporates long-term data dependencies,enabling adaptive resource distribution in real time.The training process utilizes Min-Max normalization and grid search for hyperparameter tuning,ensuring high resource utilization and consistent performance.The simulation results demonstrate the effectiveness of the proposed method,outperforming the state-of-the-art approaches,including Dynamic and Efficient Enhanced Load-Balancing(DEELB),Optimized Scheduling and Collaborative Active Resource-management(OSCAR),Convolutional Neural Network with Monarch Butterfly Optimization(CNN-MBO),and Autonomic Workload Prediction and Resource Allocation for Fog(AWPR-FOG).For example,in scenarios with low system utilization,the model achieved a resource utilization efficiency of 95%while maintaining a latency of just 15 ms,significantly exceeding the performance of comparative methods.
文摘The ease of accessing a virtually unlimited pool of resources makes Infrastructure as a Service (IaaS) clouds an ideal platform for running data-intensive workflow applications comprising hundreds of computational tasks. However, executing scientific workflows in IaaS cloud environments poses significant challenges due to conflicting objectives, such as minimizing execution time (makespan) and reducing resource utilization costs. This study responds to the increasing need for efficient and adaptable optimization solutions in dynamic and complex environments, which are critical for meeting the evolving demands of modern users and applications. This study presents an innovative multi-objective approach for scheduling scientific workflows in IaaS cloud environments. The proposed algorithm, MOS-MWMC, aims to minimize total execution time (makespan) and resource utilization costs by leveraging key features of virtual machine instances, such as a high number of cores and fast local SSD storage. By integrating realistic simulations based on the WRENCH framework, the method effectively dimensions the cloud infrastructure and optimizes resource usage. Experimental results highlight the superiority of MOS-MWMC compared to benchmark algorithms HEFT and Max-Min. The Pareto fronts obtained for the CyberShake, Epigenomics, and Montage workflows demonstrate closer proximity to the optimal front, confirming the algorithm’s ability to balance conflicting objectives. This study contributes to optimizing scientific workflows in complex environments by providing solutions tailored to specific user needs while minimizing costs and execution times.
基金supported by the National Key Research and Development Program of China(No.2021YFB2900504).
文摘In 6th Generation Mobile Networks(6G),the Space-Integrated-Ground(SIG)Radio Access Network(RAN)promises seamless coverage and exceptionally high Quality of Service(QoS)for diverse services.However,achieving this necessitates effective management of computation and wireless resources tailored to the requirements of various services.The heterogeneity of computation resources and interference among shared wireless resources pose significant coordination and management challenges.To solve these problems,this work provides an overview of multi-dimensional resource management in 6G SIG RAN,including computation and wireless resource.Firstly it provides with a review of current investigations on computation and wireless resource management and an analysis of existing deficiencies and challenges.Then focusing on the provided challenges,the work proposes an MEC-based computation resource management scheme and a mixed numerology-based wireless resource management scheme.Furthermore,it outlines promising future technologies,including joint model-driven and data-driven resource management technology,and blockchain-based resource management technology within the 6G SIG network.The work also highlights remaining challenges,such as reducing communication costs associated with unstable ground-to-satellite links and overcoming barriers posed by spectrum isolation.Overall,this comprehensive approach aims to pave the way for efficient and effective resource management in future 6G networks.
基金support provided by the Qingdao Science and Technology Benefits People Demonstration and Guidance Project(21-1-4-sf-4-nsh).
文摘Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the current emergency resource allocation of chemical enterprises lacks scientific analysis of accident scenarios,and the individual allocation method of enterprises increases the cost of emergency resource allocation.Given the above problems,this paper proposes a regional collaborative allocation method of emergency resources for enterprises within the chemical industry park(CIP)based on the worst credible accident scenario(WCAS).Firstly,the concept and analysis method of the WCAS is proposed.Then,based on the characteristics and consequences of the accident,the mapping relationship between accident scenarios and emergency resources is established.Finally,an optimization model for regional collaborative allocation of emergency resources is constructed to determine the amount of emergency resource allocation for each enterprise.Through the case study,the emergency resource allocation method based on the WCAS analysis can better meet the demands of accident emergency rescue.Simultaneously,the regional collaborative allocation optimization model can strengthen the cooperation ability among enterprises,greatly reducing the cost of emergency resource allocation for each enterprise.
基金supported by the Slovenian Research and Innovation Agency(ARIS)within the Research Program P2-0425:“Decentralized Solutions for the Digitalization of Industry and Smart Cities and Communities”supported by the Ministry of Education,Science,Technology and Innovation of Republic of Kosovo through the annual small grant projects.
文摘Resource allocation remains a challenging issue in communication networks,and its complexity is continuously increasing with the densification of the networks.With the evolution of new wireless technologies such as Fifth Generation(5G)and Sixth Generation(6G)mobile networks,the service level requirements have become stricter and more heterogeneous depending on the use case.In this paper,we review a large body of literature on various resource allocation schemes that are used in particular in mobile wireless communication networks and compare the proposed schemes in terms of performance indicators as well as techniques used.Our review shows that among the strategies proposed in the literature,there is a wide variety of optimization targets and combinations thereof,focusing mainly on performance indicators such as energy efficiency,spectral efficiency,and network capacity.In addition,in this paper,selected algorithms for resource allocation are numerically analyzed through simulations to compare and highlight the importance of how the resource algorithms are implemented to achieve efficient usage of the available spectrum.The performance of selected algorithms is evaluated in a multi-cell heterogeneous network and compared to proportional fair and eICIC,a widely-used combination of resource allocation and interferencemitigation techniques used by communication networks.The results show that one approach may performbetter when looking at the individual average user data rate but worse when looking at the overall spectral or energy efficiency,depending on the category of traffic.The results,therefore,confirm that theremay not be a single algorithmthat visibly outperforms other candidates in terms of all performance criteria.Instead,their efficiency is always a consequence of a strategic choice of goals,and the targeted parameters are optimized at a price.Thus,the development and implementation of resource allocation algorithms must follow concrete usage scenarios and network needs and be highly dependent on the requirements and criteria of network performance.
文摘State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.
基金funded by the National Natural Science Foundation of China(No.42130809)the Science and Technology Project of China Petroleum and Chemical Corporation Limited(No.KLJP23009)。
文摘Accurate and effective assessment of hydrothermal resources is crucial in the geothermal industry,given that the global installed capacity for direct use(173303 MW)significantly exceeds that for geothermal power(16260 MW).Despite the widespread application of various geothermal resource assessment methods,including the volumetric method,Monte Carlo method,analogy,statistical analysis,and numerical methods,there are still limitations faced in terms of data precision and model uncertainty assessment,fracture heterogeneity,boundary conditions,renewable energy attributes,integration of geothermal compensation mechanisms under the“extraction-injection”balance,diversification of economic evaluation metrics,and the establishment of standardized assessment criteria.This review outlines the various methods suitable for different stages of the hydrothermal resource assessment process,and proposes future technical approaches for sustainable development,including improving the accuracy of assessments and establishing standards for geothermal resource evaluation methods,in order to enhance the efficiency of geothermal resource utilization.
基金funded by a grant from the Interdisciplinary Research Institute in New Finance and Economics,Hubei University of Economics(No.JXZD202403).
文摘Energy security is a crucial aspect of modern societies,as it directly impacts the availability,accessibility,and reliability of energy sources.The reliance on natural resources and geopolitical factors in shaping energy security has gained significant attention in recent years.Natural resources and geopolitical risk are examined in 38 countries at risk of geopolitical conflict between 1990 and 2021 by examining CO_(2) emissions,renewable energy consumption,and foreign direct investment as controlling variables.The long-run analysis conducted in this study focused on slope heterogeneity,Westerlund cointegration,and dynamic panel data estimation.The findings indicated that the energy security index is positively associated with various determinants,including natural resources,geopolitical risk,CO_(2) emissions,and renewable energy consumption.However,foreign direct investment was found to be negatively associated with the energy security index among the selected 38 geopolitical risk countries.The role of natural resources and geopolitical risk in energy security cannot be overlooked.Natural resources provide the raw materials for generating electricity and powering our societies,while geopolitical risks can disrupt energy supply chains and threaten stability.Achieving sustainable energy security requires a comprehensive approach that addresses both aspects of energy provision.Transitioning to renewable energy sources,improving energy efficiency,diversifying energy supplies,promoting international cooperation,and conserving natural resources are essential steps towards a more sustainable and resilient energy future.
基金financially supported by the National Natural Science Foundation of China(Nos.52404328,52274412,and 52374418)the China Postdoctoral Science Foundation(No.2024M753248)。
文摘The rich resources and unique environment of the Moon make it an ideal location for human expansion and the utilization of extraterrestrial resources.Oxygen,crucial for supporting human life on the Moon,can be extracted from lunar regolith,which is highly rich in oxygen and contains polymetallic oxides.This oxygen and metal extraction can be achieved using existing metallurgical techniques.Furthermore,the ample reserves of water ice on the Moon offer another means for oxygen production.This paper offers a detailed overview of the leading technologies for achieving oxygen production on the Moon,drawing from an analysis of lunar resources and environmental conditions.It delves into the principles,processes,advantages,and drawbacks of water-ice electrolysis,two-step oxygen production from lunar regolith,and one-step oxygen production from lunar regolith.The two-step methods involve hydrogen reduction,carbothermal reduction,and hydrometallurgy,while the one-step methods encompass fluorination/chlorination,high-temperature decomposition,molten salt electrolysis,and molten regolith electrolysis(MOE).Following a thorough comparison of raw materials,equipment,technology,and economic viability,MOE is identified as the most promising approach for future in-situ oxygen production on the Moon.Considering the corrosion characteristics of molten lunar regolith at high temperatures,along with the Moon's low-gravity environment,the development of inexpensive and stable inert anodes and electrolysis devices that can easily collect oxygen is critical for promoting MOE technology on the Moon.This review significantly contributes to our understanding of in-situ oxygen production technologies on the Moon and supports upcoming lunar exploration initiatives.
文摘The rapid advent in artificial intelligence and big data has revolutionized the dynamic requirement in the demands of the computing resource for executing specific tasks in the cloud environment.The process of achieving autonomic resource management is identified to be a herculean task due to its huge distributed and heterogeneous environment.Moreover,the cloud network needs to provide autonomic resource management and deliver potential services to the clients by complying with the requirements of Quality-of-Service(QoS)without impacting the Service Level Agreements(SLAs).However,the existing autonomic cloud resource managing frameworks are not capable in handling the resources of the cloud with its dynamic requirements.In this paper,Coot Bird Behavior Model-based Workload Aware Autonomic Resource Management Scheme(CBBM-WARMS)is proposed for handling the dynamic requirements of cloud resources through the estimation of workload that need to be policed by the cloud environment.This CBBM-WARMS initially adopted the algorithm of adaptive density peak clustering for workloads clustering of the cloud.Then,it utilized the fuzzy logic during the process of workload scheduling for achieving the determining the availability of cloud resources.It further used CBBM for potential Virtual Machine(VM)deployment that attributes towards the provision of optimal resources.It is proposed with the capability of achieving optimal QoS with minimized time,energy consumption,SLA cost and SLA violation.The experimental validation of the proposed CBBMWARMS confirms minimized SLA cost of 19.21%and reduced SLA violation rate of 18.74%,better than the compared autonomic cloud resource managing frameworks.
基金supported by the China Postdoctoral Science Foundation(No.2023T160088)the Youth Fund of the National Natural Science Foundation of China(No.52304324).
文摘Magnesium and magnesium alloys,serving as crucial lightweight structural materials and hydrogen storage elements,find extensive applications in space technology,aviation,automotive,and magnesium-based hydrogen industries.The global production of primary magnesium has reached approximately 1.2 million tons per year,with anticipated diversification in future applications and significant market demand.Nevertheless,approximately 80%of the world’s primary magnesium is still manufactured through the Pidgeon process,grappling with formidable issues including high energy consumption,massive carbon emission,significant resource depletion,and environmental pollution.The implementation of the relative vacuum method shows potential in breaking through technological challenges in the Pidgeon process,facilitating clean,low-carbon continuous magnesium smelting.This paper begins by introducing the principles of the relative vacuum method.Subsequently,it elucidates various innovative process routes,including relative vacuum ferrosilicon reduction,aluminum thermal reduction co-production of spinel,and aluminum thermal reduction co-production of calcium aluminate.Finally,and thermodynamic foundations of the relative vacuum,a quantitative analysis of the material,energy flows,carbon emission,and production cost for several new processes is conducted,comparing and analyzing them against the Pidgeon process.The study findings reveal that,with identical raw materials,the relative vacuum silicon thermal reduction process significantly decreases raw material consumption,energy consumption,and carbon dioxide emissions by 15.86%,30.89%,and 26.27%,respectively,compared to the Pidgeon process.The relative vacuum process,using magnesite as the raw material and aluminum as the reducing agent,has the lowest magnesium-to-feed ratio,at only 3.385.Additionally,its energy consumption and carbon dioxide emissions are the lowest,at 1.817 tce/t Mg and 7.782 t CO_(2)/t Mg,respectively.The energy consumption and carbon emissions of the relative vacuum magnesium smelting process co-producing calcium aluminate(12CaO·7Al_(2)O_(3),3CaO·Al_(2)O_(3),and CaO·Al_(2)O_(3))are highly correlated with the consumption of dolomite in the raw materials.When the reduction temperature is around 1473.15 K,the critical volume fraction of magnesium vapor for different processes varies within the range of 5%–40%.Production cost analysis shows that the relative vacuum primary magnesium smelting process has significant economic benefits.This paper offers essential data support and theoretical guidance for achieving energy efficiency,carbon reduction in magnesium smelting,and the industrial adoption of innovative processes.
文摘Energy poverty in developing countries is a critical issue characterized by the lack of access to modern energy services,such as electricity and clean cooking facilities,as marked in SDG 7.This study explores the correlations between energy poverty,energy intensity,resource abundance,and income inequality,as these factors have been theorized to play important roles in influencing energy poverty in developing countries.By observing that the dataset is heterogeneous across the countries and over the time frame,we use the Method of Moments Quantile Regression(MMQR)to analyze our developing countries’data from 2000 to 2019.Our findings indicate that energy intensity is a significant factor influencing energy poverty,suggesting that higher energy consumption relative to the sample countries can exacerbate this issue.Additionally,we observe that income inequality within the sample countries is a critical determinant of energy poverty levels,highlighting the dynamics between economic disparity and access to energy resources.Interestingly,our study reveals that resource abundance acts as a blessing rather than a curse in terms of energy poverty,implying that countries rich in natural resources may have better opportunities to combat energy deprivation.Finally,we emphasize the vital role of financial markets in addressing energy poverty on a global scale,suggesting that robust financial systems can facilitate investments and innovations aimed at improving energy access for vulnerable populations.The results from the robustness analysis support the empirical results obtained from the main estimation.The empirical findings of the present study advance important comprehensions for policymakers to adopt energy policies that address the complex challenges of energy poverty and promote inclusive energy access.
基金financially supported by the Natural Science Foundation of China(No.22162007)the Science and Technology Supporting Project of Guizhou Province(Nos.[2021]480 and[2023]379)+1 种基金Wengfu(Group)Co.,Ltd.Technology Development Project(No.WH-220787(YF))the project from Guizhou Institute of Innovation and development of dual-carbon and new energy technologies(No.DCRE-2023-05)。
文摘Lithium iron phosphate(LiFePO_(4),LFP)batteries have shown extensive adoption in power applications in recent years for their reliable safety,high theoretical capability and low cost.Nevertheless,the finite lifespan of these batteries necessitates the future processing of a significant number of spent LFP batteries,underscoring the urgent need for the development of both efficient and eco-friendly recycling methods.This study combines the advantages of wet leaching and direct regeneration methods,leveraging citric acid's multifaceted role to streamline the combined leaching and hydrothermal processes.Results indicate that citric acid efficiently leaches all elements from spent LFP batteries.Furthermore,through its unique structure,it enhances hydrothermal regeneration by stabilizing metal ions and controlling crystal growth,and also acts as a carbon source for the surface carbon coating of regenerated LFP(RLFP).The R-LFP shows outstanding electrochemical stability,achieving a discharge capacity of 155.1 mAh.g^(-1)at 0.1C,with a capacity retention rate of 93.2%after 300 cycles at 1C.Furthermore,economic and environmental analyses demonstrate this method's superior cost-effectiveness and sustainability.Therefore,the method proposed in this study is efficient,simple and avoids the complex process of element separation,innovatively using a single reagent to achieve closed-loop recycling of LFP batteries,providing a novel and effective solution for the resource sustainability application.
基金supported by the Deanship of Scientific Research and Graduate Studies at King Khalid University under research grant number(R.G.P.2/93/45).
文摘Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.
文摘[Objective]The channel straightening project of the Pinglu Canal has fragmented the river course,compromising the integrity of original river course and causing ecosystem patchiness.Understanding the current status of fish resources and the characteristics of their diversity is crucial for the ecological management of the Pinglu Canal.[Methods]During the spring and autumn in 2021 and 2022,a survey of fish resources and species diversity in the Pinglu Canal was conducted using multi-mesh gill nets.A total of 125 fish species were collected,belonging to 10 orders,34 families,and 89 genera.[Results]The result showed that the Pinglu Canal contained three nationally protected Class II species,two endemic species of the Qinjiang River,three anadromous/migratory species,and eight invasive species,accounting for 2.4%,1.6%,2.4%,and 6.4%of the total species,respectively.The fish community primarily consisted of mid-and bottom-dwelling,adhesive-egg-laying,and omnivorous species.The Shannon-Wiener,Simpson,Margalef,and Pielou indices of the fish community in the Pinglu Canal ranged from 2.347 to 2.757,0.081 to 0.151,3.493 to 4.382,and 0.812 to 0.892,respectively.These indices showed relatively uniform distribution across different river reaches.[Conclusion]The result indicate that the fish community structure in the Pinglu Canal is relatively uniform.The reach from the Yujiang River to the Shaping River shows higher stability,while other river reaches experience moderate or severe disturbances.This study provides supplementary baseline data on the fish community structure in the Pinglu Canal and explores the potential impact of inter-basin connectivity on fish resources,aiming to provide a scientific basis for habitat restoration assessments after the channel straightening project.
基金supported by the Science and Technology Innovation(STI)2030-Major Projects(2022ZD0205000 to L.L.)CAS“Light of West China”Program(xbzg-zdsys-202404 to L.L.)+1 种基金Yunnan Revitalization Talent Support Program Yunling Scholar Project(to L.L.)Yunnan Fundamental Research Projects(202305AH340006,202301AS070060 to L.L.,202401AT070206 to X.C.)。
文摘The Chinese tree shrew has gained prominence as a model organism due to its phylogenetic proximity to primates,offering distinct advantages over traditional rodent models in biomedical research.However,the neuroanatomy of this species remains insufficiently defined,limiting its utility in neurophysiological and neuropathological studies.In this study,immunofluorescence microscopy was employed to comprehensively map the distribution of three calciumbinding proteins,parvalbumin,calbindin D-28k,and calretinin,across the tree shrew cerebrum.Serial brain sections in sagittal,coronal,and horizontal planes from 12 individuals generated a dataset of 3638 cellular-resolution images.This dataset,accessible via Science Data Bank(https://doi.org/10.57760/sciencedb.23471),provides detailed region-and laminar-selective distributions of calcium-binding proteins valuable for the cyto-and chemoarchitectural characterization of the tree shrew cerebrum.This resource will not only advance our understanding of brain organization and facilitate basic and translational neuroscience research in tree shrews but also enhance comparative and evolutionary analyses across species.
文摘BACKGROUND Cytomegalovirus(CMV)prophylaxis with valganciclovir and ganciclovir is associated with elevated neutropenia and leukopenia risk in kidney transplant recipients,although the impact of these events on healthcare resource utilization(HCRU)and clinical outcomes is unclear.AIM To quantify clinical events and HCRU associated with neutropenia and leukope-nia among adults receiving valganciclovir and/or ganciclovir post-kidney trans-plantation.METHODS Adult kidney transplant recipients receiving valganciclovir and/or ganciclovir prophylaxis were identified in the TriNetX database from 2012 to 2021.Patient characteristics were evaluated in the 1-year period pre-first transplant.HCRU and adjusted event rates per person-year were evaluated in follow-up year 1 and years 2-5 after first kidney transplantation among cohorts with vs without neutropenia and/or leukopenia.RESULTS Of 15398 identified patients,the average age was 52.39 years and 58.70%were male.Patients with neutropenia and/or leukopenia had greater risk of clinical events for CMV-related events,opportunistic infections,use of granulocyte colony stimulating factor,and hospitalizations(relative risk>1 in year 1 and years 2-5).Patients with vs without neutropenia and/or leukopenia had higher HCRU in year 1 and years 2-5 post kidney transplantation,including the mean number of inpatient admissions(year 1:3.47 vs 2.76;years 2-5:2.70 vs 2.29)and outpatient visits(48.97 vs 34.42;31.73 vs 15.59,respectively),as well as the mean number of labs(1654.55 vs 1182.27;622.37 vs 327.89).CONCLUSION Adults receiving valganciclovir and/or ganciclovir prophylaxis post-kidney transplantation had greater risk of neutropenia and/or leukopenia,which were associated with higher clinical event rates and HCRU up to 5 years post-transplantation.These findings suggest the need for alternative prophylaxis options with lower myelosup-pressive effects to improve patient outcomes.
