Environmental economic impact assessment in China: Problems and prospects

The use of economic valuation methods to assess environmental impacts of projects and policies has grown considerably in recent years. However, environmental valuation appears to have developed independently of regulations and practice of environmental impact assessment (EIA), despite its potential benefits to the EIA process. Environmental valuation may be useful in judging significance of impacts, determining mitigation level, comparing alternatives and generally enabling a more objective analysis of tradeoffs. In China, laws and regulations require the use of environmental valuation in EIA, but current practice lags far behind. This paper assesses the problems and prospects of introducing environmental valuation into the EIA process in China. We conduct four case studies of environmental economic impact assessment (EEIA), three of which are based on environmental impact statements of construction projects (a power plant, a wastewater treatment plant and a road construction project) and one for a regional pollution problem (wastewater irrigation). The paper demonstrates the potential usefulness of environmental valuation but also discusses several challenges to the introduction and wider use of EEIA, many of which are likely to be of relevance far beyond the Chinese context. The paper closes with suggesting some initial core elements of an EEIA guidelineEnvironmental impact assessment; Environmental valuation; China; Economic analysis

Users Collaborative Mix-Zone to Resist the Query Content and Time Interval Correlation Attacks

In location-based services of continuous query, it is easier than snapshot to confirm whether a location belongs to a particular user, because sole location can be composed into a trajectory by profile correlation. In order to cut off the correlation and disturb the sub-trajectory, an un-detective region called mix-zone was proposed. However, at the time of this writing, the existing algorithms of this type mainly focus on the profiles of ID, passing time, transition probability, mobility patterns as well as road characteristics. In addition, there is still no standard way of coping with attacks of correlating each location by mining out query content and time interval from the sub-trajectory. To cope with such types of attack, users have to generalize their query contents and time intervals similarity. Hence, this paper first provided an attack model to simulate the adversary correlating the real location with a higher probability of query content and time interval similarity. Then a user collaboration mix-zone (CoMix) that can generalize these two types of profiles is proposed, so as to achieve location privacy. In CoMix, each user shares the common profile set to lowering the probability of success opponents to get the actual position through the correlation of location. Thirdly, entropy is utilized to measure the level of privacy preservation. At last, this paper further verifies the effectiveness and efficiency of the proposed algorithm by experimental evaluations

catena-Poly[[chloridomercury(II)]-μ-1,4-diaza­bicyclo­[2.2.2]octane-κ2 N:N′-[chlorido­mercury(II)]-di-μ-chlorido]

In the title coordination polymer, [Hg2Cl4(C6H12N2)]n, each HgII center within the chain is four-coordinated by one terminal Cl atom, two bridging μ2-Cl atoms, and one N-atom donor from a μ2-1,4-diaza­bicyclo­[2.2.2]octane (μ2-daco) ligand in a distorted tetra­hedral geometry. The daco ligand acts as an end-to-end bridging ligand and bridges adjacent HgII centers, forming a chain running along [001]. Weak C—H⋯Cl hydrogen-bonding inter­actions link the chains into a three-dimensional network. Comparison of the structural differences with previous findings suggests that the space between the two N donors, as well as the skeletal rigidity in N-heterocyclic linear ligands, may play an important role in the construction of such supra­molecular networks

Diaqua­bis[5-(2-pyrid­yl)tetra­zolato-κ2 N 1,N 5]iron(II)

The title complex, [Fe(C6H4N5)2(H2O)2], was synthesized by the reaction of ferrous sulfate with 5-(2-pyrid­yl)-2H-tetra­zole (HL). The FeII atom, located on a crystallographic center of inversion, is coordinated by four N-atom donors from two planar trans-related deprotonated L ligands and two O atoms from two axial water mol­ecules in a distorted octa­hedral geometry. The FeII mononuclear units are further connected by inter­molecular O—H⋯N and C—H⋯O hydrogen-bonding inter­actions, forming a three-dimensional framework

Protective effect of mulberry flavonoids on sciatic nerve in alloxan-induced diabetic rats

Folhas de amoreira (Morus alba L.) é um medicamento tradicional chinês para a redução da glicose no soro sanguíneo. Avaliaram-se, neste trabalho, os efeitos protetores dos flavonóides de amora no nervo ciático em ratos diabéticos aloxano-induzidos. Dividiram-se 80 ratos Sprague-Dawley em cinco grupos: A (controle), B (diabétidos tratados com solução salina), C-D (diabéticos tratados com 0,3, 0,1 g/kg) e E (diabéticos tratados com 0,3 mg de metilcobal).A diabetes foi induzida por injeção intraperitoneal de 200 mg/kg de aloxana dissolvida em solução salina. No final do período experimental, obtiveram-se amostras de sangue e de tecido para investigação bioquímica e histopatológica. O tratamento com 0,3 g/kg de flavonóides da amoreira inibiu, significativamente, a elevação de glicose no soro (pMulberry leaves (Morus alba L.) are a traditional Chinese medicine for blood serum glucose reduction. This study evaluated the protective effects of mulberry flavonoids on sciatic nerve in alloxan-induced diabetic rats. In this study, 80 Sprague-Dawley rats were divided into five groups: A (control), B (diabetic treated with saline), C-D (diabetic treated with 0.3, 0.1 g/kg mulberry flavonoids once a day for 8 weeks) and E (diabetic treated with 0.3 mg/kg methycobal). The diabetic condition was induced by intraperitoneal injection of 200 mg/kg alloxan dissolved in saline. At the end of the experimental period, blood, and tissue samples were obtained for biochemical and histopathological investigation. Treatment with 0.3 g/kg mulberry flavonoids significantly inhibited the elevated serum glucose (P< 0.01). The increased myelin sheath area (P< 0.01), myelinated fiber cross-sectional area and extramedullary fiber number (P< 0.05) were also reduced in alloxan-induced rats treated with 0.3 g/kg mulberry flavonoids. 0.3 g/kg mulberry flavonoids also markedly decreased onion-bulb type myelin destruction and degenerative changes of mitochondria and Schwann cells. These findings demonstrate that mulberry flavonoids may improve the recovery of a severe peripheral nerve injury in alloxan-induced diabetic rats and is likely to be useful as a potential treatment on peripheral neuropathy (PN) in diabetic rats

Study on corrosion resistance of Portland cement-calcium sulphoaluminate cement binary system in a sodium chloride environment

Portland cement is widely used in civil engineering. However, Portland cement-based materials are easy to be corroded by seawater in marine environment. Many research show the corrosion resistance of Portland cement mortar can be improved by add appropriate amount of mineral admixture.Sulphoaluminate cement have high strength and good corrosion seawater resistance. However, the short setting time and high hydration heat of sulphoaluminate cement limit its application in civil engineering.Portland cement-sulphoaluminate cement (PC-CSA) not only have high strength and corrosion resistance but also long setting time.In this work, the sulphoaluminate cement was used to partially replace Portland cement. The replacement level of sulphoaluminate cement was 10 %, 20 % and 30 % by weight of Portland cement. Mortar specimens was soaked in sodium chloride solution under standard curing after 28 days. The concentration of sodium chloride solution was 3.5wt %. Mechanical properties , corrosion resistance and setting time of PC-CSA binary system were tested in the research. The hydration behavior of binary system was determined by isothermal calorimetry and X-ray diffraction methods. Microstructure of the binary system at different ages were analyzed by scanning electron microscope. The strength of PC-CSA binary system was tested at different curing ages up to 28 days.The results show when replacement level of sulphoaluminate cement is 20%, the comprehensive strength up to 50MPa and higher than other groups at 28 days soaked in corrosion solution.when replacement level of sulphoaluminate cement is 20%,the corrosion resistance is best,and penetration depth of chloride ions is the least

Chrion: Optimizing Recurrent Neural Network Inference by Collaboratively Utilizing CPUs and GPUs

Deploying deep learning models in cloud clusters provides efficient and prompt inference services to accommodate the widespread application of deep learning. These clusters are usually equipped with host CPUs and accelerators with distinct responsibilities to handle serving requests, i.e. generalpurpose CPUs for input preprocessing and domain-specific GPUs for forward computation. Recurrent neural networks play an essential role in handling temporal inputs and display distinctive computation characteristics because of their high inter-operator parallelism. Hence, we propose Chrion to optimize recurrent neural network inference by collaboratively utilizing CPUs and GPUs. We formulate the model deployment in the CPU-GPU cluster as an NP-hard scheduling problem of directed acyclic graphs on heterogeneous devices. Given an input model in the ONNX format and user-defined SLO requirement, Chrion firstly preprocesses the model by model parsing and profiling, and then partitions the graph to select execution devices for each operator. When an online request arrives, Chrion performs forward computation according to the graph partition by executing the operators on the CPU and GPU in parallel. Our experimental results show that the execution time can be reduced by 19.4% at most in the latency-optimal pattern and GPU memory footprint by 67.5% in the memory-optimal pattern compared with the execution on the GPU

KGExplainer: Towards Exploring Connected Subgraph Explanations for Knowledge Graph Completion

Knowledge graph completion (KGC) aims to alleviate the inherent incompleteness of knowledge graphs (KGs), which is a critical task for various applications, such as recommendations on the web. Although knowledge graph embedding (KGE) models have demonstrated superior predictive performance on KGC tasks, these models infer missing links in a black-box manner that lacks transparency and accountability, preventing researchers from developing accountable models. Existing KGE-based explanation methods focus on exploring key paths or isolated edges as explanations, which is information-less to reason target prediction. Additionally, the missing ground truth leads to these explanation methods being ineffective in quantitatively evaluating explored explanations. To overcome these limitations, we propose KGExplainer, a model-agnostic method that identifies connected subgraph explanations and distills an evaluator to assess them quantitatively. KGExplainer employs a perturbation-based greedy search algorithm to find key connected subgraphs as explanations within the local structure of target predictions. To evaluate the quality of the explored explanations, KGExplainer distills an evaluator from the target KGE model. By forwarding the explanations to the evaluator, our method can examine the fidelity of them. Extensive experiments on benchmark datasets demonstrate that KGExplainer yields promising improvement and achieves an optimal ratio of 83.3% in human evaluation.Comment: 13 pages, 7 figures, 11 tables. Under Revie