2,351 research outputs found

    Can Environmental Regulations Promote Corporate Environmental Responsibility? Evidence from the Moderated Mediating Effect Model and an Empirical Study in China

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    Based on the Stakeholder theory, a moderated mediating effect model is developed to reach the study objective, revealing an important connection that suggests environmental regulations (ERs) influence corporate environmental responsibility (CER) (Porter Hypothesis). In building the model, the validity of the questionnaire data was analyzed with factor analysis. By employing a two-step approach, a regression analysis is utilized to discuss the mediating effect of altruistic motivation and moderating effect of green innovation, and a structural equation model is used to explore the interactive mechanism of different variables. It is found that altruistic motivation plays a medium role in the relationship between ERs and CER, and green innovation engages a positive coordination in the relationship. The empirical study identifies factors affecting enterprises’ willingness to undertake environmental responsibility, including environment policies, corporate culture, and personal characters among others. It is also revealed that altruistic motivation is conducive to forming a community interests among enterprises and enhancing their resistance to market risks, which explains and corroborates the Stakeholder theory; and the higher the level of green innovation, the more willing enterprises are to implement environmentally friendly operations

    On the amount of counterpart assistance to be provided after natural disasters: from the perspective of indirect economic loss assessment

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    China’s counterpart assistance policy is of vital importance in providing guidance for emergency management and post-disaster reconstruction. However, the amount of assistance that partner provinces should provide as well as the criteria that partners should abide by in offering counterpart assistance remain a main challenge. The goal of this research is to fill this gap by proposing a new framework consisting of an interregional input–output (IRIO) model and a resilience index. Subsequently, the indirect economic loss is obtained by utilizing the index system of provincial economic resilience assessments, with measures of indirect economic loss developed from the IRIO. Furthermore, to examine the internal validity and systematic error, the reliability of the adopted models, the calculation methods, and the index systems are investigated. To assess the external validity of the proposed measures and resilience index of the framework, data from the 2008 Wenchuan Earthquake are applied for estimating parameter values of the framework, and a follow-up investigation was conducted for examining the fairness and enhanced effectiveness of the new counterpart assistance criteria. In summary, this paper attempts to present some new ideas about the analysis of economic motivations of mutual aid and the improvement of the counterpart assistance policy

    A Comprehensive Estimation of the Economic Effects of Meteorological Services Based on the Input-Output Method

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    Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete) economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency) in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27-1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30-1 : 51). Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries

    The Entropy of Co-Compact Open Covers

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    Co-compact entropy is introduced as an invariant of topological conjugation for perfect mappings defined on any Hausdorff space(compactness and metrizability not necessarily required). This is achieved through the consideration of co-compact covers of the space. The advantages of co-compact entropy include: 1) it does not require the space to be compact, and thus generalizes Adler, Konheim and McAndrew's topological entropy of continuous mappings on compact dynamical systems, and 2) it is an invariant of topological conjugation, compared to Bowen's entropy that is metric-dependent. Other properties of co-compact entropy are investigated, e.g., the co-compact entropy of a subsystem does not exceed that of the whole system. For the linear system (R, f) defined by f(x) = 2x, the co-compact entropy is zero, while Bowen's entropy for this system is at least log 2. More general, it is found that co-compact entropy is a lower bound of Bowen's entropies, and the proof of this result generates the Lebesgue Covering Theorem to co-compact open covers of non-compact metric spaces, too

    Novel role for dual-specificity phosphatase 4 in adipocytes

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    The growing prevalence of obesity has resulted in a huge impact on global health. Obesity contributes to the development of cardiovascular diseases, insulin resistance (IR) and other comorbidities. Research over the past few decades has revealed important roles for adipose tissue (AT) in regulating whole-body metabolism under normal physiological and pathological states. It is well accepted that obesity-mediated chronic, low-grade inflammation contributes to the development of metabolic dysfunctions via the mitogen-activated protein kinase (MAPK) signaling pathways. While the upstream activation of MAPKs has been extensively investigated, how MAPK deactivation modulates cellular responses remains largely unsolved. In recent years, increasing attention has been given to the MAPK-specific, dual-specificity phosphatases (DUSPs) as key regulators that negatively control MAPK activity, potentially provide treatment against obesity-induced AT inflammation and IR. Early evidence has suggested a role for DUSP4 towards MAPKs signaling in other cell types. However, no study has addressed the role of DUSP4 in 3T3-L1 adipocytes under any condition. Data presented in this dissertation demonstrate that DUSP4 was induced via the MEK/ERK signaling pathway while JNK or p38 did not affect DUSP4 expression. Subsequently, we show that DUSP4 protein was also stabilized by ERK activation and proteasomal activity was partially involved in its protein degradation. Moreover, accumulation of DUSP4 correlated with the suppression of nuclear ERK signal and protein-protein interactions were observed between DUSP4 and ERK, suggesting a role for this phosphatase in spatiotemporal regulation of ERK activity in adipocytes. We further demonstrate that DUSP4 is suppressed in AT under conditions of genetic and diet-induced obesity that is associated with increased inflammation and IR. We report biphasic inductions of DUSP4 during adipocyte differentiation, with the early phase induction being ERK-dependent and the later phase induction being ERK-independent and differentiation-specific. Moreover, DUSP4 was suppressed in preadipocytes and adipocytes exposed to tumor necrosis factor-a. Additionally, DUSP4 knockdown did not inhibit adipocyte differentiation, suggesting a role for this phosphatase that is independent from adipogenesis. Collectively, data presented in this dissertation provide new insights into regulation and potential function of DUSP4 in adipocytes, highlighting new therapeutic targets for the treatment of obesity-mediated inflammation and metabolic disorders

    Typical lignocellulosic wastes and by-products for biosorption process in water and wastewater treatment: A critical review

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    Biosorption on lignocellulosic wastes and by-products has been identified as a proper alternative to the existing technologies applied for toxic metal ion and dye removal from wastewater streams. This paper deals with utilization of typical low cost wastes and by-products produced in different food agricultural and agro-industries as biosorbent and reviews the current state of studies on a wide variety of cheap biosorbents in natural and modified forms. The efficiency of each biosorbent has been also discussed with respect to the operating conditions (e.g. temperature, hydraulic residence time, initial metal concentration, biosorbent particle size and its dosage), chemical modification on sorption capacity and preparation methods, as well as thermodynamics and kinetics. © 2013 Elsevier Ltd

    RANDOMIZATION BASED PRIVACY PRESERVING CATEGORICAL DATA ANALYSIS

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    The success of data mining relies on the availability of high quality data. To ensure quality data mining, effective information sharing between organizations becomes a vital requirement in today’s society. Since data mining often involves sensitive infor- mation of individuals, the public has expressed a deep concern about their privacy. Privacy-preserving data mining is a study of eliminating privacy threats while, at the same time, preserving useful information in the released data for data mining. This dissertation investigates data utility and privacy of randomization-based mod- els in privacy preserving data mining for categorical data. For the analysis of data utility in randomization model, we first investigate the accuracy analysis for associ- ation rule mining in market basket data. Then we propose a general framework to conduct theoretical analysis on how the randomization process affects the accuracy of various measures adopted in categorical data analysis. We also examine data utility when randomization mechanisms are not provided to data miners to achieve better privacy. We investigate how various objective associ- ation measures between two variables may be affected by randomization. We then extend it to multiple variables by examining the feasibility of hierarchical loglinear modeling. Our results provide a reference to data miners about what they can do and what they can not do with certainty upon randomized data directly without the knowledge about the original distribution of data and distortion information. Data privacy and data utility are commonly considered as a pair of conflicting re- quirements in privacy preserving data mining applications. In this dissertation, we investigate privacy issues in randomization models. In particular, we focus on the attribute disclosure under linking attack in data publishing. We propose efficient so- lutions to determine optimal distortion parameters such that we can maximize utility preservation while still satisfying privacy requirements. We compare our randomiza- tion approach with l-diversity and anatomy in terms of utility preservation (under the same privacy requirements) from three aspects (reconstructed distributions, accuracy of answering queries, and preservation of correlations). Our empirical results show that randomization incurs significantly smaller utility loss

    Impact of political dispute on international trade based on an international trade Inoperability Input-Output Model: A case study of the 2012 Diaoyu Islands Dispute

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    While political disputes occur frequently and widely among many countries, their impact on the international trade is unclear and less systematically investigated. Considering the 2012 Diaoyu Islands Dispute, under several premised assumptions, this paper applies the international trade Inoperability Input-Output Model to determine the indirect economic loss and to screen out Chinese industries that are sensitive to the dispute. Results based on Leontief's technical coefficients matrix show that the total indirect economic loss of China's gross trade is between RMB 540.4226 billion and RMB 1023.3068 billion. Industries that are sensitive to the dispute include electrical equipment and machinery, general special equipment manufacturing, metal smelting and rolling processing, manufacture and processing of metals and metal products, and chemical. The empirical findings suggest that China establish an early-warning mechanism and trade assistance system, so that key industries that were damaged could be properly compensated

    A Tri-Modality Image Fusion Method for Target Delineation of Brain Tumors in Radiotherapy

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    Purpose To develop a tri-modality image fusion method for better target delineation in image-guided radiotherapy for patients with brain tumors. Methods A new method of tri-modality image fusion was developed, which can fuse and display all image sets in one panel and one operation. And a feasibility study in gross tumor volume (GTV) delineation using data from three patients with brain tumors was conducted, which included images of simulation CT, MRI, and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) examinations before radiotherapy. Tri-modality image fusion was implemented after image registrations of CT+PET and CT+MRI, and the transparency weight of each modality could be adjusted and set by users. Three radiation oncologists delineated GTVs for all patients using dual-modality (MRI/CT) and tri-modality (MRI/CT/PET) image fusion respectively. Inter-observer variation was assessed by the coefficient of variation (COV), the average distance between surface and centroid (ADSC), and the local standard deviation (SDlocal). Analysis of COV was also performed to evaluate intra-observer volume variation. Results The inter-observer variation analysis showed that, the mean COV was 0.14(±0.09) and 0.07(±0.01) for dual-modality and tri-modality respectively; the standard deviation of ADSC was significantly reduced (p<0.05) with tri-modality; SDlocal averaged over median GTV surface was reduced in patient 2 (from 0.57 cm to 0.39 cm) and patient 3 (from 0.42 cm to 0.36 cm) with the new method. The intra-observer volume variation was also significantly reduced (p = 0.00) with the tri-modality method as compared with using the dual-modality method. Conclusion With the new tri-modality image fusion method smaller inter- and intra-observer variation in GTV definition for the brain tumors can be achieved, which improves the consistency and accuracy for target delineation in individualized radiotherapy
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