Water resources utilization and eco-environmental safety in Northwest China

Northwest China includes Xinjiang Ugyur Autonomous Region, Qinghai Province, Gansu Province, Ningxia Hui Autonomous Region and Shaanxi Province, covering 308×10^4km^2. It is located in the warm-temperate zone and the climate is arid or semi-arid. Precipitation is very scarce but evaporation is extremely high. The climate is dry, the water resources are deficient, the ecoenvironment is fragile, and the distribution of water resources is uneven. In this region, precipitation is the only input, and evaporation is the only output in the inland rivers, and precipitation, surface water and groundwater change with each other for many times, which benefits the storage and utilization of water resources. The average precipitation in this region is 232 mm, the total precipitation amount is 7003×108m^3/a, the surface water resources are 1891×10^8m^3/a, the total natural groundwater resources are 1150×10^8m^3/a, the total available water resources are 438×10^8 m^3/a, and the total water resources are 1996×10^8m^3/a and per capita water resources are 2278 m^3/a. The water resources of the whole area are 5.94×10^4m^3/（a.km^2）, being only one-fifth of the mean value in China. Now, the available water resources are 876×10^8m^3/a, among which groundwater is proximate 130×10^8m^3/a.

Use of rural energy resources and eco-environmental degradation in Tibet

Cattle dung, firewood, and crop straw have being used as survival necessities by farmers and herdsmen for thousands of years in Tibet. Until recently such biotic energy source still constitutes more than 92 per cent of total rural energy consumption due to lack of petroleum, coal and new alternative energy sources. As a result, environmental degradation such as land desertification, soil erosion, grassland degradation and soil fertility reduction is increasingly aggravated, the area of desertified land has increased 1467.5 km2 from 1991 to 1997. Degraded area of grassland has reached 2.60×107hm2, increased by 116.1% from 1987 to 1996. To prevent further deterioration of eco-environment in Tibet great efforts should be made to make full use of ample solar energy, wind energy and other biotic energy of the Qinghai-Tibet Plateau. The solar cooking stoves and solar hothouse, expand forest area and replace existing abiotic energy sources with firewood forest should be popularized. This is an urgent task to protect the eco-environment of Tibet today.

Impact of coal resource development on eco-environment and its restoration in west of China

West China has rich mineral resources, especially in coal resources with very good mining conditions. Coal resource development is the one of important tasks in the Chinese “West Development”. Thus, the impact of coal resources development on eco-environment and its restoration is worth studying. This study shows that there are many environmental problems such as land damage, coal wastes, damage of hydro-geological condition and pollution of water resource, airborne effluents (industrial exhausts and methane emission from underground), dust, waste, water. Land damage and land desertification are the most important environmental issue in west China. Therefore, the stress of environmental restoration should be desert presentation and disturbed-land reclamation. To control environmental damages and rehabilitate the eco-environment, environmental restoration techniques are also discussed.

SAFETY ANALYSIS OF WATER RESOURCES AND ECO-ENVIRONMENT IN SHIYANG RIVER BASIN

The research on the present situation of soil and water development and utilization in Shiyang River Basin shows that water resources and eco-environment situation in this area are near the edge of collapse. Since the water crises occurred in the 1970s, problems caused by continuous decrease of water resources have been becoming serious year by year and eco-environment crisis occurred as a consequence. Up to now, 10 380ha of irrigated lands have been abandoned due to sand coverage and water shortage in the basin. Ground water was over exploded in Wuwei and Minqin because of water shortage. Ground water table in many places dropped under 5m （which is the ecology water table level）, thus about 3000ha ofElaeagnus angustifolia forest come to dead and another 5800ha become feeble, and wind-drift sand near the oasis become alive. According to the current situation, if water utilization scope was not enlarged, a water transfer volume of 600×10^6m^3/a from other areas will be suitable to keep water resources and eco-environment safety in the basin, and also 70×10^6m^3/a will be left as spare water. Under this condition the water resources and eco-environment of the basin can reach the critical safety line of 2.032×10^6m^3/a; or if 180×10^6m^3 of water can be transferred from other areas, the water resources can reach the safety warning line of 1.732×10^9m^3/a.

NATURAL RESOURCES AND ECO-ENVIRONMENT MAPPING IN HENAN,CHINA

The history is briefly looked back of natural resources and eec-environmental mapping in Henan Province. The main achievements are alsosummed up in following aspects: geographical mapping, soil mapping, land resource mapping, hydrothermal resource mapping, biological resource mapping, ecological mapping, design and compilation of natural resource and environment atlas, and study on cartographic theory and method. The basic characterristics are discussed, they include 1) extensive cartographic field and varied-type map; 2) resource and environment mapping being closely connected with resource investigation and environment research; 3) traditional cartographic method being dominant; 4) cooperation of cartographic researchers. Finally, the future tasks are proposed as follows: compiling a series of large-scale maps and renewing obsolete maps; dynamically monitoring and mapping of natural resource and environment system; mapping of eec-environment; and establishing information system of resource and environment.

Water resources optimization and eco-environmental protection in Qaidam Basin

In order to realize sustainable development of the arid area of Northwest China, rational water resources exploitation and optimization are primary prerequisites. Based on the essential principle of sustainable development, this paper puts forward a general idea on water resources optimization and eco-environmental protection in Qaidam Basin, and identifies the competitive multiple targets of water resources optimization. By some qualitative methods such as Input-output Model & AHP Model and some quantitative methods such as System Dynamics Model & Produce Function Model, some standard plans of water resources optimization come into being. According to the Multiple Targets Decision by the Closest Value Model, the best plan of water resources optimization, eco-environmental protection and sustainable development in Qaidam Basin is finally decided.

Structural properties of residual carbon in coal gasification fine slag and their influence on flotation separation and resource utilization:A review

Coal gasification fine slag(FS)is a typical solid waste generated in coal gasification.Its current disposal methods of stockpil-ing and landfilling have caused serious soil and ecological hazards.Separation recovery and the high-value utilization of residual carbon(RC)in FS are the keys to realizing the win-win situation of the coal chemical industry in terms of economic and environmental benefits.The structural properties,such as pore,surface functional group,and microcrystalline structures,of RC in FS(FS-RC)not only affect the flotation recovery efficiency of FS-RC but also form the basis for the high-value utilization of FS-RC.In this paper,the characteristics of FS-RC in terms of pore structure,surface functional groups,and microcrystalline structure are sorted out in accordance with gasification type and FS particle size.The reasons for the formation of the special structural properties of FS-RC are analyzed,and their influence on the flotation separation and high-value utilization of FS-RC is summarized.Separation methods based on the pore structural characterist-ics of FS-RC,such as ultrasonic pretreatment-pore-blocking flotation and pore breaking-flocculation flotation,are proposed to be the key development technologies for improving FS-RC recovery in the future.The design of low-cost,low-dose collectors containing polar bonds based on the surface and microcrystalline structures of FS-RC is proposed to be an important breakthrough point for strengthening the flotation efficiency of FS-RC in the future.The high-value utilization of FS should be based on the physicochemical structural proper-ties of FS-RC and should focus on the environmental impact of hazardous elements and the recyclability of chemical waste liquid to es-tablish an environmentally friendly utilization method.This review is of great theoretical importance for the comprehensive understand-ing of the unique structural properties of FS-RC,the breakthrough of the technological bottleneck in the efficient flotation separation of FS,and the expansion of the field of the high value-added utilization of FS-RC.

‘Partly'globalized networks and driving mechanism in resource-based state-owned enterprises:A case study of J Group

In the context of economic globalization,while multinational enterprises from developed countries occupy a high-end position in the global value chain,enterprises from developing countries are often marginalized in the world market.In China,resource-based state-owned enterprises(SOEs)are tasked with the mission of safeguarding resource security,and their internationalization development ideas and strategic deployment are significantly and fundamentally different from those of other non-state-owned enterprises and large multinational corporations.This study provides ideas for the globalization policies of enterprises in developing countries.We consider J Group in western China as a case and discuss its productive investment and global production network development from 2010 to 2019.We found that J Group was‘Partly'globalized,and there are multiple core nodes with the characteristics of centralized and decentralized coexistence in the production network;in addition,the overall layout centre shifted to Southeast Asia and China;however,its global production was restricted by the enterprise's investment security considerations,support and restrictions of the home country,political security risk of the host country,and sanctions from the West.These findings provide insights for future research:under the wave of anti-globalization and'internal circulation as the main body',resource SOEs should consider the potential risk of investment,especially keeping the middle and downstream industrial chain in China as much as possible.

A Comprehensive Survey on Joint Resource Allocation Strategies in Federated Edge Learning

Federated Edge Learning(FEL),an emerging distributed Machine Learning(ML)paradigm,enables model training in a distributed environment while ensuring user privacy by using physical separation for each user’s data.However,with the development of complex application scenarios such as the Internet of Things(IoT)and Smart Earth,the conventional resource allocation schemes can no longer effectively support these growing computational and communication demands.Therefore,joint resource optimization may be the key solution to the scaling problem.This paper simultaneously addresses the multifaceted challenges of computation and communication,with the growing multiple resource demands.We systematically review the joint allocation strategies for different resources(computation,data,communication,and network topology)in FEL,and summarize the advantages in improving system efficiency,reducing latency,enhancing resource utilization,and enhancing robustness.In addition,we present the potential ability of joint optimization to enhance privacy preservation by reducing communication requirements,indirectly.This work not only provides theoretical support for resource management in federated learning(FL)systems,but also provides ideas for potential optimal deployment in multiple real-world scenarios.By thoroughly discussing the current challenges and future research directions,it also provides some important insights into multi-resource optimization in complex application environments.

AMAD:Adaptive Mapping Approach for Datacenter Networks,an Energy-Friend Resource Allocation Framework via Repeated Leader Follower Game

Cloud Datacenter Network(CDN)providers usually have the option to scale their network structures to allow for far more resource capacities,though such scaling options may come with exponential costs that contradict their utility objectives.Yet,besides the cost of the physical assets and network resources,such scaling may also imposemore loads on the electricity power grids to feed the added nodes with the required energy to run and cool,which comes with extra costs too.Thus,those CDNproviders who utilize their resources better can certainly afford their services at lower price-units when compared to others who simply choose the scaling solutions.Resource utilization is a quite challenging process;indeed,clients of CDNs usually tend to exaggerate their true resource requirements when they lease their resources.Service providers are committed to their clients with Service Level Agreements(SLAs).Therefore,any amendment to the resource allocations needs to be approved by the clients first.In this work,we propose deploying a Stackelberg leadership framework to formulate a negotiation game between the cloud service providers and their client tenants.Through this,the providers seek to retrieve those leased unused resources from their clients.Cooperation is not expected from the clients,and they may ask high price units to return their extra resources to the provider’s premises.Hence,to motivate cooperation in such a non-cooperative game,as an extension to theVickery auctions,we developed an incentive-compatible pricingmodel for the returned resources.Moreover,we also proposed building a behavior belief function that shapes the way of negotiation and compensation for each client.Compared to other benchmark models,the assessment results showthat our proposed models provide for timely negotiation schemes,allowing for better resource utilization rates,higher utilities,and grid-friend CDNs.

Starlet:Network defense resource allocation with multi-armed bandits for cloud-edge crowd sensing in IoT

The cloud platform has limited defense resources to fully protect the edge servers used to process crowd sensing data in Internet of Things.To guarantee the network's overall security,we present a network defense resource allocation with multi-armed bandits to maximize the network's overall benefit.Firstly,we propose the method for dynamic setting of node defense resource thresholds to obtain the defender(attacker)benefit function of edge servers(nodes)and distribution.Secondly,we design a defense resource sharing mechanism for neighboring nodes to obtain the defense capability of nodes.Subsequently,we use the decomposability and Lipschitz conti-nuity of the defender's total expected utility to reduce the difference between the utility's discrete and continuous arms and analyze the difference theoretically.Finally,experimental results show that the method maximizes the defender's total expected utility and reduces the difference between the discrete and continuous arms of the utility.

Mapping and resource evaluation of deep high-temperature geothermal resources in the Jiyang Depression,China

In China,geothermal resource utilization has mainly focused on resources at shallow and medium depths.Yet,the exploration of deep,high-temperature geothermal resources holds significant importance for achieving the“dual carbon”goals and the transition of energy structure.The Jiyang Depression in the Bohai Bay Basin has vast potential for deep,high-temperature geothermal resources.By analyzing data from 2187 wells with temperature logs and 270 locations for temperature measurement in deep strata,we mapped the geothermal field of shallow to medium-deep layers in the Jiyang Depression using ArcGIS and predicted the temperatures of deep layers with a burial depth of 4000 m.Through stochastic modeling and numerical simulation,a reservoir attribute parameter database for favorable deep,high-temperature geothermal areas was developed,systematically characterizing the spatial distribution of geothermal resources within a play fairway of 139.5 km2 and estimating the exploitable deep geothermal resource potential by using the heat storage method and Monte Carlo data analysis.The study reveals that the Fan 54 well block in the Boxing-Jijia region is of prime significance to develop deep,high-temperature geothermal resources in the Jiyang Depression.Strata from the Cenozoic to the Upper Paleozoic are identified as effective cap layers for these deep geothermal resources.The Lower Paleozoic capable of effectively storing thermal energy and possessing an exploitable resource volume up to 127 million tons of standard coal,is identified as a target system for the development of deep high-temperature geothermal resources,providing significant insights for the efficient development of geothermal resources in the Jiyang Depression.

Optimization of resource allocation in FDD massive MIMO systems

The performance of massive MIMO systems relies heavily on the availability of Channel State Information at the Transmitter(CSIT).A large amount of work has been devoted to reducing the CSIT acquisition overhead at the pilot training and/or CsI feedback stage.In fact,the downlink communication generally includes three stages,i.e.,pilot training,CsI feedback,and data transmission.These three stages are mutually related and jointly determine the overall system performance.Unfortunately,there exist few studies on the reduction of csIT acquisition overhead from the global point of view.In this paper,we integrate the Minimum Mean Square Error(MMSE)channel estimation,Random Vector Quantization(RVQ)based limited feedback and Maximal Ratio Combining(MRC)precoding into a unified framework for investigating the resource allocation problem.In particular,we first approximate the covariance matrix of the quantization error with a simple expression and derive an analytical expression of the received Signal-to-Noise Ratio(SNR)based on the deterministic equivalence theory.Then the three performance metrics(the spectral efficiency,energy efficiency,and total energy consumption)oriented problems are formulated analytically.With practical system requirements,these three metrics can be collaboratively optimized.Finally,we propose an optimization solver to derive the optimal partition of channel coherence time.Experiment results verify the benefits of the proposed resource allocation schemes under three different scenarios and illustrate the tradeoff of resource allocation between three stages.

Resource utilization of hazardous gypsum sludge in oxidation smelting of lead concentrate

Gypsum sludge,a hazardous waste generated by the non-ferrous smelting industry,presents a significant challenge for disposal and utilization.To investigate the feasibility of substituting gypsum sludge for limestone as a flux for smelting,the effects of calcium sulfate(CaSO_(4))and smelting conditions on oxygen-rich smelting of lead concentrate were studied.The interaction between CaSO_(4)and sulfides facilitates the conversion of CaSO_(4)into CaO,which is crucial for slag formation.The order of the influence of sulfide minerals on the conversion of CaSO_(4)is pyrite>sphalerite>galena.When using gypsum sludge exclusively as the calcium source,under optimal conditions with a CaO/SiO_(2)mass ratio of 0.8,an FeO/SiO_(2)mass ratio of 1.2,a melting temperature of 1150℃,an oxygen flow rate of 1.3 L/min,the recovery rates of Pb and Zn in the lead-rich slag reached 85.01%and 95.69%,respectively,with a sulfur content of 2.65 wt%.The As content in the smelting slag obtained by reduction smelting was 0.02 wt%.Resource utilization of gypsum sludge in lead smelting is a feasible method.

An Adaptive Hybrid Optimization Strategy for Resource Allocation in Network Function Virtualization

With the rapid development of Network Function Virtualization(NFV),the problem of low resource utilizationin traditional data centers is gradually being addressed.However,existing research does not optimize both localand global allocation of resources in data centers.Hence,we propose an adaptive hybrid optimization strategy thatcombines dynamic programming and neural networks to improve resource utilization and service quality in datacenters.Our approach encompasses a service function chain simulation generator,a parallel architecture servicesystem,a dynamic programming strategy formaximizing the utilization of local server resources,a neural networkfor predicting the global utilization rate of resources and a global resource optimization strategy for bottleneck andredundant resources.With the implementation of our local and global resource allocation strategies,the systemperformance is significantly optimized through simulation.

Computing Resource Allocation for Blockchain-Based Mobile Edge Computing

Users and edge servers are not fullymutually trusted inmobile edge computing(MEC),and hence blockchain can be introduced to provide trustableMEC.In blockchain-basedMEC,each edge server functions as a node in bothMEC and blockchain,processing users’tasks and then uploading the task related information to the blockchain.That is,each edge server runs both users’offloaded tasks and blockchain tasks simultaneously.Note that there is a trade-off between the resource allocation for MEC and blockchain tasks.Therefore,the allocation of the resources of edge servers to the blockchain and theMEC is crucial for the processing delay of blockchain-based MEC.Most of the existing research tackles the problem of resource allocation in either blockchain or MEC,which leads to unfavorable performance of the blockchain-based MEC system.In this paper,we study how to allocate the computing resources of edge servers to the MEC and blockchain tasks with the aimtominimize the total systemprocessing delay.For the problem,we propose a computing resource Allocation algorithmfor Blockchain-based MEC(ABM)which utilizes the Slater’s condition,Karush-Kuhn-Tucker(KKT)conditions,partial derivatives of the Lagrangian function and subgradient projection method to obtain the solution.Simulation results show that ABM converges and effectively reduces the processing delay of blockchain-based MEC.

Geological reservoir and resource potential(10^(13)m^(3))of gas hydrates in the South China Sea

A detailed understanding of the distribution and potential of natural gas hydrate(NGHs)resources is crucial to fostering the industrialization of those resources in the South China Sea,where NGHs are abundant.In this study,this study analyzed the applicability of resource evaluation methods,including the volumetric,genesis,and analogy methods,and estimated NGHs resource potential in the South China Sea by using scientific resource evaluation methods based on the factors controlling the geological accumulation and the reservoir characteristics of NGHs.Furthermore,this study compared the evaluation results of NGHs resource evaluations in representative worldwise sea areas via rational analysis.The results of this study are as follows:(1)The gas hydrate accumulation in the South China Sea is characterized by multiple sources of gas supply,multi-channel migration,and extensive accumulation,which are significantly different from those of oil and gas and other unconventional resources.(2)The evaluation of gas hydrate resources in the South China Sea is a highly targeted,stratified,and multidisciplinary evaluation of geological resources under the framework of a multi-type gas hydrate resource evaluation system and focuses on the comprehensive utilization of multi-source heterogeneous data.(3)Global NGHs resources is n×10^(15)m^(3),while the NGHs resources in the South China Sea are estimated to be 10^(13)m^(3),which is comparable to the abundance of typical marine NGHs deposits in other parts of the world.In the South China Sea,the NGHs resources have a broad prospect and provide a substantial resource base for production tests and industrialization of NGHs.

A Novel Predictive Model for Edge Computing Resource Scheduling Based on Deep Neural Network

Currently,applications accessing remote computing resources through cloud data centers is the main mode of operation,but this mode of operation greatly increases communication latency and reduces overall quality of service(QoS)and quality of experience(QoE).Edge computing technology extends cloud service functionality to the edge of the mobile network,closer to the task execution end,and can effectivelymitigate the communication latency problem.However,the massive and heterogeneous nature of servers in edge computing systems brings new challenges to task scheduling and resource management,and the booming development of artificial neural networks provides us withmore powerfulmethods to alleviate this limitation.Therefore,in this paper,we proposed a time series forecasting model incorporating Conv1D,LSTM and GRU for edge computing device resource scheduling,trained and tested the forecasting model using a small self-built dataset,and achieved competitive experimental results.

A Self-Attention Based Dynamic Resource Management for Satellite-Terrestrial Networks

The satellite-terrestrial networks possess the ability to transcend geographical constraints inherent in traditional communication networks,enabling global coverage and offering users ubiquitous computing power support,which is an important development direction of future communications.In this paper,we take into account a multi-scenario network model under the coverage of low earth orbit(LEO)satellite,which can provide computing resources to users in faraway areas to improve task processing efficiency.However,LEO satellites experience limitations in computing and communication resources and the channels are time-varying and complex,which makes the extraction of state information a daunting task.Therefore,we explore the dynamic resource management issue pertaining to joint computing,communication resource allocation and power control for multi-access edge computing(MEC).In order to tackle this formidable issue,we undertake the task of transforming the issue into a Markov decision process(MDP)problem and propose the self-attention based dynamic resource management(SABDRM)algorithm,which effectively extracts state information features to enhance the training process.Simulation results show that the proposed algorithm is capable of effectively reducing the long-term average delay and energy consumption of the tasks.