A fast genetic algorithm for a critical protection problem in biomedical supply chain networks

In this paper, we present a new bilevel model for a biomedical supply chain network with capacity and budget constraint due to the protection and interdiction operations. The components considered in this model are biomedical devices, distribution centers (DCs), medical suppliers (MSs), and hospitals and patients as the demand points. On the other hand, two levels of decisions in the network planning is suggested: (1) the defender’s decision about protection operations of MSs and DCs, the assignment of clients to the DCs, and quantity of products shipped to DCs from MSs to minimize the demand-weighted traveling costs and transport costs and (2) the attacker’s decision about interdiction operations of MSs and DCs to maximize the capacity or service reduction and losses. Because of nondeterministic polynomial time (NP)-hardness of the problem under consideration, an efficient and fast approach based on a genetic algorithm and a fast branch and cut method (GA–FBC) was developed to solve the proposed model. Also, the efficiency via the comparison of results with the genetic algorithm based on CPLEX (GA-CPLEX) and decomposition method (DM) is investigated. In order to assess the performance of the presented GA–FBC, a set of 27 instances of the problem is used. Comprehensive analysis indicates that the proposed approach significantly solves the problem. In addition, the benefits and advantages of preference with running times and its accuracy is shown numerically. Simulation results clearly demonstrate that the defender’s objective effectively reduced and CPU time also within the large-sized instances of the problem in comparison with the GA-CPLEX and DM.     

Mimic Drug Dosage Modulation for Neuroplasticity Based on Charge-Trap Layered Electronics

The human brain is often likened to an incredibly complex and intricate computer, rather than electrical devices, consisting of billions of neuronal cells connected by synapses. Different brain circuits are responsible for coordinating and performing specific functions. The reward pathway of the synaptic plasticity in the brain is strongly related to the features of both drug addiction and relief. In the current study, a synaptic device based on layered hafnium disulfide (HfS₂) is developed for the first time, to emulate the behavioral mechanisms of drug dosage modulation for neuroplasticity. A strong gate-dependent persistent photocurrent is observed, arising from the modulation of substrate-trapping events. By controlling the polarity of gate voltage, the basic functions of biological synapses are realized under a range of light spiking conditions. Furthermore, under the control of detrapping/trapping events at the HfS₂/SiO₂ interface, positive/negative correlations of the A_n/A₁ index, which significantly reflected the weight change of synaptic plasticity, are realized under the same stimulation conditions for the emulation of the drug-related addition/relief behaviors in the brain. The findings provide a new advance for mimicking human brain plasticity.     

UMo/Zr单片式燃料板起泡行为数值模拟

燃料板的鼓泡临界温度是制定研究试验堆安全系数的标准之一，通常由鼓泡退火实验确定。针对鼓泡退火实验，本研究发展了一种对UMo/Zr单片式燃料板宏观起泡行为进行计算模拟的方法，并计算分析了气腔内裂变气体原子数对鼓泡高度的影响，获得了包壳内的Mises应力和等效塑性应变随温度升高而演化的规律。研究发现，气腔周围包壳产生塑性变形是起泡的一个关键原因。此研究为燃料板起泡机理和关键影响因素分析打下了基础。     

两类桡动脉压迫止血器临床应用效果分析

【摘要】目的比较旋钮式压迫止血器和气囊式压迫止血器在桡动脉途径介入治疗术中的临床应用效果。 方法回顾性分析2015年2月至9月接受冠状动脉介入治疗的186例患者临床资料。其中105例患者选用旋钮式压迫止血器，81例患者选用气囊式压迫止血器，比较两组患者术后临床特征及血管并发症发生情况。根据术后穿刺点出血情况将患者分为出血组和不出血组，比较两组患者临床特点。 结果使用气囊式压迫止血器患者术后手部肿胀率(P=0.001)、疼痛视觉模拟评分(VAS，P=0.02)均明显低于使用旋钮式压迫止血器患者；两者术后出血比例未见明显差异(17.3%对14.3%，P=0.55)。出血组患者活化部分凝血活酶时间(APTT，P=0.001)、国际标准化比值(INR，P=0.001)、术后使用低分子肝素或替罗非班比例(P=0.002)及疼痛VAS评分(P=0.001)均高于不出血组患者，诊断性造影比例低于不出血组患者(P=0.03)。 结论旋钮式压迫止血器和气囊式压迫止血器止血效果相当，气囊式压迫止血器在舒适度及肿胀率方面优于旋钮式压迫止血器。术后穿刺点是否出血与压迫止血器类型无关，与患者APTT、INR、术后抗凝药物使用情况及是否植入支架相关。


     

Optimizing inventory policies in process networks under uncertainty

We address the inventory planning problem in process networks under uncertainty through stochastic programming models. Inventory planning requires the formulation of multiperiod models to represent the time-varying conditions of industrial process, but multistage stochastic programming formulations are often too large to solve. We propose a policy-based approximation of the multistage stochastic model that avoids anticipativity by enforcing the same decision rule for all scenarios. The proposed formulation includes the logic that models inventory policies, and it is used to find the parameters that offer the best expected performance. We propose policies for inventory planning in process networks with arrangements of inventories in parallel and in series. We compare the inventory planning strategies obtained from the policy-based formulation and the analogous two-stage approximation of the multistage stochastic program. Sequential implementation of the planning strategies in receding horizon simulations shows the advantages of the policy-based model, despite the increase in computational complexity.     

The influence of compression molding techniques on thermal conductivity of UHMWPE/BN and UHMWPE/(BN + MWCNT) hybrid composites with segregated structure

Various ultra-high-molecular-weight polyethylene (UHMWPE)/boron nitride (BN) and UHMWPE/(BN + multi-wall carbon nanotube (MWCNT)) composites with segregated structure were prepared by using the compression molding process. The dispersion of fillers under different compression molding were observed by optical microscopy and scanning electron microscopy. The results showed that integrated thermal conductive networks were formed after cold-pressing sintering. However, these networks would be destroyed by middle-high pressure/high temperature treatment. Although the treatment of high pressure/high temperature can effectively improve the crystallinity and crystal size of UHMWPE, the thermal conductivity of composite dramatically decreased due to the replacement of filler-filler by filler-polymer-filler interface. The 1D-MWCNT is liable to entangle with 2D-BNs and formed MWCNT-BN networks even at high pressure/high temperature, leading to a nearly constant thermal conductivity (reached 1.794 W/m·K with the addition of 50% (BNs + MWCNT) hybrid fillers). Besides, the dispersion of the fillers have a great influence on thermal stability of the composites.     

Stability and nonlinear controller analysis of wind energy conversion system with random wind speed

In the recent years, globally wind energy has played a vital role in renewable sources in order to minimize the environmental consequence on power generation, As a result of this, computer models of wind turbines for power system stability studies have been developed and supplied to the consumer. Therefore, the development of such models is of particular consequence for stability of power system, which has been studied and can be structured and integrated into network simulation software are needed. However, in this contribution a nonlinear control design modeling is required to stabilize and analyze wind energy conversion system (WECS) by regulating the electrical frequency and stator voltage amplitude of the squirrel-cage induction generator (SCIG) at random wind speed approach is presented. A design scheme consists of dynamic wind turbine system and 3-phase SCIG unit. In this research study, we employ a unique technique based on feedback linearization technique through field oriented control concepts. The controllers were designed in simulated software Matlab in order to regulate the SCIG constraints. The validation of the developing system models will be appropriate to provide for large system stability and control.     

Electron correlation effects on polarons recombination in coupled polymer chains

The recombination dynamics of singlet and triplet oppositely charged polarons under the influence of electron–electron (e–e) interactions in coupled polymer chains are investigated using a multi-configurational time-dependent Hartree–Fock (MCTDHF) method. During recombination processes, singlet and triplet intrachain excitons are important products. By calculating the yields of the singlet and triplet intrachain excitons as a function of the on-site and long-range e–e interactions, it is found that the yields of the singlet and triplet intrachain excitons both decrease with increasing on-site e–e interactions. On the other hand, as the long-range e–e interactions increase, the yields of singlet intrachain excitons initially increase and then maintain a constant value, while the yields of the triplet intrachain excitons decrease. Our results show that the long-range e–e interaction is of fundamental importance and improves the luminescence efficiency in coupled polymer chains. Finally, the influence of the polymer chain length on the yields of singlet and triplet intrachain excitons is discussed.     

Ultrathin MoSSe alloy nanosheets anchored on carbon nanotubes as advanced catalysts for hydrogen evolution

The activity of transition metal dichalcogenides (TMD) toward hydrogen evolution reaction (HER) derives from the active sites at the edges, but the basal surface still remain catalytic insert. Herein, ultrathin MoSSe alloy nanosheets array on multiwalled carbon nanotubes (MWCNTs) to form a core shell structure via a simple solvothermal process. These three-dimensional (3D) MoSSe hybrids show a high activity in hydrogen evolution reaction (HER) with a small Tafel slope of 38 mV dec⁻¹ and a low overpotential of 102 mV at 10 mA cm⁻². In addition, their HER activity remains remarkably stable without significant decay after 100 h polarization. Such superior catalytic HER activity springs from the 3D hierarchical heterostructure, which is abundant of catalytic edge sites, and the alloy effect between S and Se, which will create huge defects and strain to form vacancy sites on the basal plane. This strategy may open a new avenue toward the development of nonprecious high-performance HER catalysts.