An interpretative structural modeling based network reconfiguration strategy for power systems

The network reconfiguration is an important stage of restoring a power system after a complete blackout or a local outage. Reasonable planning of the network reconfiguration procedure is essential for rapidly restoring the power system concerned. An approach for evaluating the importance of a line is first proposed based on the line contraction concept. Then, the interpretative structural modeling (ISM) is employed to analyze the relationship among the factors having impacts on the network reconfiguration. The security and speediness of restoring generating units are considered with priority, and a method is next proposed to select the generating unit to be restored by maximizing the restoration benefit with both the generation capacity of the restored generating unit and the importance of the line in the restoration path considered. Both the start-up sequence of generating units and the related restoration paths are optimized together in the proposed method, and in this way the shortcomings of separately solving these two issues in the existing methods are avoided. Finally, the New England 10-unit 39-bus power system and the Guangdong power system in South China are employed to demonstrate the basic features of the proposed method.     

Hierarchical mesoporous silica microspheres as unique hard-template for preparation of hierarchical mesoporous TiO2 microspheres with trimodal mesoporosities via nanocasting

This work for the first time reported that hierarchical meso-mesoporous SBA-15 silica microspheres (HMM-SiO₂-MSs) can serve as a unique and suitable hard-template for the nanocasting preparation of mesoporous TiO₂ with both hierarchical mesostructures and well-preserved microsphere particle morphology. A two-step impregnation (TSI) method was developed and customized and its effectiveness was studied in comparison with the single-step impregnation method. Trimodal mesoporosities and their origin are newly recognized and analyzed. The materials were examined by various techniques, including the FE-SEM, N₂ sorption, TEM and XRD. Under optimized conditions, the hierarchical mesostructures and spherical particle morphology of HMM-SiO₂-MSs can be replicated for HMM-TiO₂-MSs. The high surface area and pore volume of HMM-TiO₂-MSs reach 194 m² g^-1 and 0.68 cm³ g^-1, respectively, with the latter more than twice those templated by conventional SBA-15s. Besides HMM-TiO₂-MSs, such HMM-SiO₂-MSs as hard-template might be extended to the preparation of other materials with hierarchical mesostructures.     

Which Chinese cities are more inclusive and why?

China's household registration system allows local governments to control migration by limiting migrants' eligibility to local public services. Many cities exclude migrant residents from important social benefits, which reduces labor mobility and contributes to the socioeconomic gap between migrants and urban natives. This study measures the extent of China's local migration restriction from the perspective of inclusive provision of public services and explains cross-city disparities. We define urban inclusiveness as the extent to which migrants can access social benefits provided locally and construct an urban inclusiveness index using factor analysis. We find significant cross-city differences in urban inclusiveness toward migrants. Statistical analyses suggest that local fiscal capacity and labor demand, instead of cultural tradition, are the major determinants of urban inclusiveness. We further use the gap between the inclusiveness toward high- and low-skilled migrants to measure local skill-based migration selectivity. We find that more developed cities, i.e., cities with larger populations, higher levels of gross regional product per capita, and greater shares of industrial sector, are more selective based on migrants' skills, while cultural openness does not help bring down skill-based selectivity. Our research suggests an instrumental view of migrants in China's urban policy that contributes to social inequality and the lack of labor mobility, which can restrict China's development in the long term.     

A further study on multiple attractors of mixed convection in confined spaces

By truncating the blended Fourier and Chebyshev expansion of the solution of the two-dimensional partial differential equations for viscously incompressible fluids, a simplified model on studying the mixed convection in an enclosure is developed. Dynamical behavior of the developed model while varying the system parameters is investigated numerically. Results seem to be helpful in explaining qualitatively the physical mechanism of the multiple mixed convection flows, and understanding the onset of chaotic mixed convection.     

Formation of deformation bands and precipitation of Ni3Al(γ′) phase in NiAl(β)-based single crystals by thermomechanical processing

Microstructure and crystal orientation distribution of two-phase NiAl(β)/Ni₃Al(γ′) alloys obtained by thermomechanical processing were investigated. Cylindrical Ni-36 and 38 at.%Al alloy single crystals with various initial loading axes were hot-compressed at a high strain rate of 1.0 s⁻¹ and subsequently annealed in the (β/γ′) two-phase region. After the hot deformation, relatively uniform subgrain structures were formed in initial 〈111〉_β-oriented crystals, while a number of deformation bands perpendicular to the compressive axis developed in 〈100〉_β-, 〈110〉_β- and 〈123〉_β-oriented crystals. Two types of deformation bands with different crystal orientations were alternately arranged against the compressive axis. After annealing in the (β/γ′) two-phase region, a film-shaped γ′ phase with peculiar variants of the Kurdjumov–Sachs orientation relationship preferentially precipitated along the boundary between the deformation bands, resulting in the formation of a (β/γ′) two-phase lamellar structure. Formation process of the deformation bands in β phase and the crystallography of γ′ precipitates along deformation bands were discussed.     

How do we learn to get success together through crowdfunding platform? From the perspectives of system learning and multi-motivations

In recent years, crowdfunding has been widely applied as a new approach for solving the finance shortage problem of start-ups. The crowdfunding platform (CFP) has disseminating extensive knowledge of diverse fields and offers a channel for users who share the same interests to communicate with. However, relevant studies of CFP participant behavior overlook the knowledge value projected by CFP in the sense that CFP demo real cases for promoting the project success. Therefore, this study takes the ground of IS continuance theory and extends it by introducing the multi-motive theory (MISC) in investigating user CFP continuous behavior. In particular, this study examines the role of system learning (SL) on the association with CFP continuous-usage intentions. As Lowry et al. (2015) propose the SL concept as an intrinsic motivation and relevant to SL for adopting information system; there is no strong evidence confirmed their proposition yet. Results confirm that both intrinsic motivation perceived through the sense of perceived enjoyment and extrinsic motivation (CFP satisfaction) are associated with users' continuance intention. However, the intrinsic motivations of the system learning (knowledge sharing and stay informed) are partially associated with the perceived enjoyment and perceived usefulness. Discussions and implications for theory are given in the end.     

Structural,optical, and dielectric characteristics of copper oxide nanoparticles loaded CMC/PEO matrix

Journal of Materials Science - Polymer nanocomposite films were prepared using the casting method through filling a polymer mixture of carboxymethyl cellulose (CMC) and polyethylene oxide (PEO)...     

Animals and AI. The role of animals in AI research and application – An overview and ethical evaluation

Artificial intelligence (AI) technologies and their fields of application are among the most debated developments of recent times. Although being widely discussed academically, publicly and in policy debates, certain aspects of their research, development and application are completely ignored, namely the impact AI has on animals. Animals are affected by the research on and development of this technology since it partially relies on animal testing. In addition, AI is also being applied to improve monitoring and marketing of animals in an agricultural context. We argue that it is insufficient to exclude these aspects from debates around AI. In addition to the surveillance-applications on animals, which can be evaluated as impacting them negatively, AI applications, from which individual animals can benefit, do exist. These can primarily be found in nature and wildlife conservation, as we point out at the end of the paper. By providing an overview on how these technologies are applied to animals and how this affects them, this paper aims to fill a previously existing research gap.     

Electricity generation and economic growth in Indonesia

To cope with the increasing electricity demand and to overcome the supply shortage of electricity, it is imminent that investments be made on the electricity generation sector on a large scale in Indonesia. This paper attempts to investigate the causal relationship between electricity generation and economic growth in Indonesia, using time-series techniques for the period of 1971–2002. The results indicate that there is a uni-directional causality running from economic growth to electricity generation without any feedback effect. Thus, economic growth stimulates further electricity generation, and policies for reducing electricity generation can be initiated without deteriorating economic side effects in Indonesia.     

Combining task execution and background knowledge for the verification of medical guidelines

The use of a medical guideline can be seen as the execution of computational tasks, sequentially or in parallel, in the face of patient data. It has been shown that many of such guidelines can be represented as a ‘network of tasks’, i.e., as a number of steps that have a specific function or goal. To investigate the quality of such guidelines we propose a formalization of criteria for good practice medicine a guideline should comply to. We use this theory in conjunction with medical background knowledge to verify the quality of a guideline dealing with diabetes mellitus type 2 using the interactive theorem prover KIV. Verification using task execution and background knowledge is a novel approach to quality checking of medical guidelines.