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Flexible and wearable electronics are attracting wide attention due to their potential applications in wearable human health monitoring and care systems. Carbon materials have combined superiorities such as good electrical conduct...
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Flexible and wearable electronics are attracting wide attention due to their potential applications in wearable human health monitoring and care systems. Carbon materials have combined superiorities such as good electrical conductivity, intrinsic and structural flexibility, light weight, high chemical and thermal stability, ease of chemical functionalization, as well as potential mass production, enabling them to be promising candidate materials for flexible and wearable electronics. Consequently, great efforts are devoted to the controlled fabrication of carbon materials with rationally designed structures for applications in next-generation electronics. Herein, the latest advances in the rational design and controlled fabrication of carbon materials toward applications in flexible and wearable electronics are reviewed. Various carbon materials (carbon nanotubes, graphene, natural-biomaterial-derived carbon, etc.) with controlled micro/nanostructures and designed macroscopic morphologies for high-performance flexible electronics are introduced. The fabrication strategies, working mechanism, performance, and applications of carbon-based flexible devices are reviewed and discussed, including strain/pressure sensors, temperature/humidity sensors, electrochemical sensors, flexible conductive electrodes/wires, and flexible power devices. Furthermore, the integration of multiple devices toward multifunctional wearable systems is briefly reviewed. Finally, the existing challenges and future opportunities in this field are summarized.
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We consider learning rates of kernel regularized regression (KRR) based on reproducing kernel Hilbert spaces (RKHSs) and differentiable strongly convex losses and provide some new strongly convex losses. We first show the robustne...
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We consider learning rates of kernel regularized regression (KRR) based on reproducing kernel Hilbert spaces (RKHSs) and differentiable strongly convex losses and provide some new strongly convex losses. We first show the robustness with the maximum mean discrepancy (MMD) and the Hutchinson metric respectively, and, along this line, bound the learning rate of the KRR. We first provide a capacity dependent learning rate and then give the learning rates for four concrete strongly convex losses respectively. In particular, we provide the learning rates when the hypothesis RKHS's logarithmic complexity exponent is arbitrarily small as well as sufficiently large.
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This paper proposes an optimal consensus model to derive weights for linguistic preference relations (LPRs). Two indexes, an individual-to-group consensus index (ICI) and a collective consensus index (CCI), are introduced. An iter...
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This paper proposes an optimal consensus model to derive weights for linguistic preference relations (LPRs). Two indexes, an individual-to-group consensus index (ICI) and a collective consensus index (CCI), are introduced. An iterative algorithm is presented to describe the consensus reaching process. By changing the weights and modifying a pair of individuals' comparison judgmentswhich have largest deviation value to the group judgmentsthe consensus reaching process can terminate, while both ICI and CCI are controlled with predefined thresholds. The algorithm aims to preserve the decision makers' original information as much as possible. The model and algorithm are then extended to handle the uncertain additive LPRs. Finally, two examples are given to show the effectiveness of the proposed methods.
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Excitatory (glutamatergic) synaptic transmission underlies many aspects of brain activity and the genesis of normal human behavior. The postsynaptic scaffolding proteins SAP90/PSD-95-associated proteins (SAPAPs), which are abundan...
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Excitatory (glutamatergic) synaptic transmission underlies many aspects of brain activity and the genesis of normal human behavior. The postsynaptic scaffolding proteins SAP90/PSD-95-associated proteins (SAPAPs), which are abundant components of the postsynaptic density (PSD) at excitatory synapses, play critical roles in synaptic structure, formation, development, plasticity, and signaling. The convergence of human genetic data with recent in vitro and in vivo animal model data indicates that mutations in the genes encoding SAPAP1–4 are associated with neurological and psychiatric disorders, and that dysfunction of SAPAP scaffolding proteins may contribute to the pathogenesis of various neuropsychiatric disorders, such as schizophrenia, autism spectrum disorders, obsessive compulsive disorders, Alzheimer’s disease, and bipolar disorder. Here, we review recent major genetic, epigenetic, molecular, behavioral, electrophysiological, and circuitry studies that have advanced our knowledge by clarifying the roles of SAPAP proteins at the synapses, providing new insights into the mechanistic links to neurodevelopmental and neuropsychiatric disorders.
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In this paper, we are concerned with a sixth-order nonlinear Schrodinger equation. By applying the factorization formula and an analytical method, we prove the existence and uniqueness of global solution for the Cauchy problem of ...
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In this paper, we are concerned with a sixth-order nonlinear Schrodinger equation. By applying the factorization formula and an analytical method, we prove the existence and uniqueness of global solution for the Cauchy problem of the sixth-order nonlinear Schrodinger equation. (C) 2020 Elsevier Inc. All rights reserved.
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This study uses panel data from the North China Water Resources Survey in 2004 and 2016 to update the status of groundwater. In the past two decades, groundwater irrigation has spread to more villages, but declining groundwater ta...
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This study uses panel data from the North China Water Resources Survey in 2004 and 2016 to update the status of groundwater. In the past two decades, groundwater irrigation has spread to more villages, but declining groundwater tables and deterioration in water quality have become more serious. Some policy measures (well-drilling permits, water quotas, water resources fees) have been implemented in an increasing number of villages, but they still only reached a small fraction of villages. Some of the responses by farmers to these challenges have accelerated groundwater extraction. Policy efforts are needed to improve the effectiveness of policy implementation and enhance sustainable groundwater use.
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In this paper, we propose some new aggregation operators which are based on the Choquet integral and Einstein operations. The operators not only consider the importance of the elements or their ordered positions, but also consider...
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In this paper, we propose some new aggregation operators which are based on the Choquet integral and Einstein operations. The operators not only consider the importance of the elements or their ordered positions, but also consider the interactions phenomena among the decision making criteria or their ordered positions. It is shown that the proposed operators generalize several intuitionistic fuzzy Einstein aggregation operators. Moreover, some of their properties are investigated. We also study the relationship between the proposed operators and the existing intuitionistic fuzzy Choquet aggregation operators. Furthermore, an approach based on intuitionistic fuzzy Einstein Choquet integral operators is presented for multiple attribute decision-making problem. Finally, a practical decision making problem involving the water resource management is given to illustrate the multiple attribute decision making process.
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Compared with the surface-mounted permanent magnet (SPM) motors, the consequent-pole permanent magnet (CPM) motors can obtain the approximate output torque on the basis of saving 30% PM material. However, due to the special arrang...
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Compared with the surface-mounted permanent magnet (SPM) motors, the consequent-pole permanent magnet (CPM) motors can obtain the approximate output torque on the basis of saving 30% PM material. However, due to the special arrangement of the CPM motor, its torque ripple is large, which will affect the smooth operation of this kind of motor. Therefore, this paper proposes a hybrid consequent-pole permanent magnet (HCPM) motor with an auxiliary PM on one side of the iron pole, which can reduce the torque ripple and ensure smooth operation effectively. In order to make the performances of proposed motor better, the Taguchi method is used to optimize the proposed HCPM motor. Furthermore, the influence rule and the relative importance of each optimization variable on the optimization goal are obtained by the average value analysis and the variance analysis, respectively. According to the above analysis results, the optimized hybrid consequent-pole permanent magnet (OHCPM) motor is obtained. Finally, the performances of SPM motor, CPM motor, and OHCPM motor are compared to verify the validity of the proposed structure.
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In the analytical hierarchy process (AHP), it needs the decision maker to establish a pairwise comparison matrix requires n(n-1)/2 judgments for a level with n criteria (or alternatives). In some instances, the decision maker may ...
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In the analytical hierarchy process (AHP), it needs the decision maker to establish a pairwise comparison matrix requires n(n-1)/2 judgments for a level with n criteria (or alternatives). In some instances, the decision maker may have to deal with the problems in which only partial information and uncertain preference relation is available. Consequently, the decision maker may provide interval fuzzy preference relation with incomplete information. In this paper, we focus our attention on the investigation of incomplete interval fuzzy preference relation. We first extend a characterization to the interval fuzzy preference relation which is based on the additive transitivity property. Using the characterization, we propose a method to construct interval additive consistent fuzzy preference relations from a set of n-1 preference data. The study reveals that the proposed method can not only alleviate the comparisons, but also ensure interval preference relations with the additive consistent property. We also develop a novel procedure to deal with the analytic hierarchy problem for group decision making with incomplete interval fuzzy preference relations. Finally, a numerical example is illustrated and a supplier selection case in supply chain management is investigated using the proposed method.
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We develop a newsvendor model to study the retailer's order quantity, the manufacturer's returns handling strategy, and channel coordination. The manufacturer chooses one of two returns handling strategies: manufacturer handling o...
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We develop a newsvendor model to study the retailer's order quantity, the manufacturer's returns handling strategy, and channel coordination. The manufacturer chooses one of two returns handling strategies: manufacturer handling or retailer handling under the coordinated and decentralized scenarios, respectively. Under the coordinated scenario, we find that when consumer's returns handling cost under manufacturer handling or the manufacturer's returns handling cost is small, consumer returns should be handled by the manufacturer. Under the decentralized scenario, when the retailer's returns handling cost or the consumer's returns handling cost under retailer handling is low, the manufacturer will choose manufacturer handling; both the manufacturer and the retailer may be better off using manufacturer handling (a win-win situation). The impact of the returns handling strategy on the retailer's ordering quantity largely depends on its effect on the consumer's returns handling cost. Finally, we also design buyback contracts to coordinate the supply chain and find that both wholesale price and buyback price under manufacturer handling are higher than those under retailer handling.
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