Fabrication of poly(ε‐caprolactone) (PCL)/poly(propylene carbonate) (PPC)/ethylene‐α‐octene block copolymer (OBC) triple shape memory blends with cycling performance by constructing a co‐continuous phase morphology

In this paper, a triple shape memory material was prepared by ultra‐simple melt blending from poly(ε‐caprolactone) (PCL), poly(propylene carbonate) (PPC) and ethylene‐α‐octene block copolymer (OBC). The obtained material possessed a co‐continuous phase morphology and presented an excellent triple shape memory effect (triple‐SME). Theoretical prediction demonstrated that a special continuous phase morphology could be constructed by adjusting the proportions of the blend. Moreover, the results indicated that a close relationship existed between the phase morphology and the triple‐SME of PCL/PPC/OBC. The sample with 35 vol% PPC content contributed to the formation of a continuous phase morphology and exhibited the optimal triple‐SME. Additionally, the sample PCL/PPC/OBC (32.5/35/32.5) showed outstanding structure and performance stability during cycle loading–unloading tests, which evidenced the prominent cycling shape memory property (nearly 100% shape fixing and recovery of temporary shape). Overall, this work could provide an efficient, convenient and recyclable method to obtain high‐performance shape memory materials. © 2020 Society of Chemical Industry     

基于FAHP的机械振动WSN均衡拓扑构建方法

针对机械振动无线传感器网络因拓扑不均衡导致传输时延和网络传输能耗增加的问题,提出了一种基于模糊层次分析(fuzzy analytic hierarchy process,简称FAHP)的均衡拓扑构建方法,该方法由构建模糊判断矩阵和计算权重向量组成。首先,传感器节点进行簇内通信获取信标广播信息,将信标节点网络决策因子统一量纲化,利用网络决策因子构建模糊判断矩阵;其次,检验模糊判断矩阵一致性,采用行和归一化处理或拉格朗日最小二乘法计算权重向量;最后,传感器节点通过权重向量计算出各个信标节点综合权值,关联最优信标节点为父节点加入网络,将提出的模糊层次分析拓扑构建方法与基于链路质量单准则构建网络拓扑机制进行对比。实验结果表明,该方法能有效改善传输时延和机械振动无线传感器节点网络寿命。     

Automated classification of simulated wind field patterns from multiphysics ensemble forecasts

In this study, we have proposed an automated classification approach to identify meaningful patterns in wind field data. Utilizing an extensive simulated wind database, we have demonstrated that the proposed approach can identify low‐level jets, near‐uniform profiles, and other patterns in a reliable manner. We have studied the dependence of these wind profile patterns on locations (eg, offshore vs onshore), seasons, and diurnal cycles. Furthermore, we have found that the probability distributions of some of the patterns depend on the underlying planetary boundary layer schemes in a significant way. The future potential of the proposed approach in wind resource assessment and, more generally, in mesoscale model parameterization improvement is touched upon in this paper.     

Compiler compatible 5.66 Mb/mm2 8T 1R1W register file in 14 nm FinFET technology

1-read/1-write (1R1W) register file (RF) is a popular memory configuration in modern feature rich SoCs requiring significant amount of embedded memory. A memory compiler is constructed using the 8T RF bitcell spanning a range of instances from 32 b to 72 Kb. An 8T low-leakage bitcell of 0.106 μm² is used in a 14 nm FinFET technology with a 70 nm contacted gate pitch for high-density (HD) two-port (TP) RF memory compiler which achieves 5.66 Mb/mm² array density for a 72 Kb array which is the highest reported density in 14 nm FinFET technology. The density improvement is achieved by using techniques such as leaf-cell optimization (eliminating transistors), better architectural planning, top level connectivity through leaf-cell abutment and minimizing the number of unique leaf-cells. These techniques are fully compatible with memory compiler usage over the required span. Leakage power is minimized by using power-switches without degrading the density mentioned above. Self-induced supply voltage collapse technique is applied for write and a four stack static keeper is used for read Vmin improvement. Fabricated test chips using 14 nm process have demonstrated 2.33 GHz performance at 1.1 V/25 °C operation. Overall V_min of 550 mV is achieved with this design at 25 °C. The inbuilt power-switch improves leakage power by 12x in simulation. Approximately 8% die area of a leading 14 nm SoC in commercialization is occupied by these compiled RF instances.     

Gender differences in the addiction to social networks in the Southern Spanish university students

Social networks sites have become the most popular instrument used to communicate and exchange information resulting in the addiction to this media. Previous studies suggested that personal characters play an essential role in addictive behavior and gender difference may be involved. Nevertheless, there are contradictions about the influence of gender. Some studies indicated higher addiction in men. Meanwhile, other researchers pointed out higher addiction among Spanish teenage female. Little studies in the Spanish context have analyzed the different socio-cultural and biological factors possibly related to this addiction and gender differences. With all being said, this study focused on determining the current incidence of social networks addiction in young college students, relating this social networking addiction with loneliness, prenatal testosterone (2D:4D ratio), self-esteem and personal satisfaction. A cross-sectional study focused on female and male college students aged 17–25 years (N = 278) was carried out. It was used several surveys, including the Social Network Addiction Questionnaire (SNA) and the 2D:4D ratio. The results showed difference among male and female about addiction (chi-square = 12.77, p-value = 0.002). Moreover, this addiction was linked with several factors, such as importance given to social networks by females (p-value < 0.001) and males (p-value < 0.001). Also, the findings showed that addiction to social networks might be influenced by gender, showing more importance sociopsychological factors in females and a combination of biological and social factors in the men. Moreover, Instagram has increased as the predominant social network for communication for college students (97.2% men and 93.7% women).     

基于降噪时序深度学习网络的风电功率短期预测方法

利用风电场历史功率数据预测未来一段时间内的风功率,对保障电网安全稳定运行具有重要的意义。本文提出一种基于奇异谱分析SSA(singular spectrum analysis)和长短时记忆LSTM(long-short term memory net⁃work)网络的时序特征预测框架用于短期风功率的预测。首先通过SSA对历史风功率原始数据进行降噪处理,然后经过数据转换之后,以LSTM网络为基础进行预测模型的训练,最后通过某风电场提供的两个风机的历史功率数据进行验证。实验结果表明,奇异谱分析对风电场的历史数据具有良好的降噪性,SSA+LSTM模型在测试数据上取得了较好的预测性能,能够有效进行短期风功率的预测。     

湖州南方中转仓储及输送工程建设特点

介绍了湖州南方物流有限公司中转仓储及输送工程项目的建设背景、建设条件,以及线路规划、主要技术方案,该项目是国内采用长距离越野曲线带式输送机系统运输熟料距离最长的绿色环保工程。项目以电力驱动运输替代汽车运输,日输送量达4.5~5万吨。采用密闭廊道输送,粉尘排放量低,噪声<50dB,日均减少汽车运输3000辆次,年节约燃油2000余吨,减少了尾气排放,缓解了沿线的交通拥堵,实现了良好的经济效益和社会效益。     

How Far Are We from Prescribing Fasting as Anticancer Medicine?

(1) Background: the present review provides a comprehensive and up-to date overview of the potential exploitation of fasting as an anticancer strategy. The rationale for this concept is that fasting elicits a differential stress response in the setting of unfavorable conditions, empowering the survival of normal cells, while killing cancer cells. (2) Methods: the present narrative review presents the basic aspects of the hormonal, molecular, and cellular response to fasting, focusing on the interrelationship of fasting with oxidative stress. It also presents nonclinical and clinical evidence concerning the implementation of fasting as adjuvant to chemotherapy, highlighting current challenges and future perspectives. (3) Results: there is ample nonclinical evidence indicating that fasting can mitigate the toxicity of chemotherapy and/or increase the efficacy of chemotherapy. The relevant clinical research is encouraging, albeit still in its infancy. The path forward for implementing fasting in oncology is a personalized approach, entailing counteraction of current challenges, including: (i) patient selection; (ii) fasting patterns; (iii) timeline of fasting and refeeding; (iv) validation of biomarkers for assessment of fasting; and (v) establishment of protocols for patients’ monitoring. (4) Conclusion: prescribing fasting as anticancer medicine may not be far away if large randomized clinical trials consolidate its safety and efficacy.     

Component spectroscopic properties of light-harvesting complexes with DFT calculations

Photosynthesis is a fundamental process in biosciences and biotechnology that influences profoundly the research in other disciplines. In this paper, we focus on the characterization of fundamental components, present in pigment-protein complexes, in terms of their spectroscopic properties such as infrared spectra, nuclear magnetic resonance, as well as nuclear quadrupole resonance, which are of critical importance for many applications. Such components include chlorophylls and bacteriochlorophylls. Based on the density functional theory method, we calculate the main spectroscopic characteristics of these components for the Fenna-Matthews-Olson light-harvesting complex, analyze them and compare them with available experimental results. Future outlook is discussed in the context of current and potential applications of the presented results.