Three distinct optical-switching states in phase-change materials containing impurities:From physical origin to material design

Ge2Sb2Tes is the most widely utilized chalcogenide phase-change material for non-volatile photonic applications,which undergoes amorphous-cubic and cubic-hexagonal phase transition under external excitations.However,the cubic-hexagonal optical contrast is negligible,only the amorphous-cubic phase transition of Ge2Sb2Te5 is available.This limits the optical switching states of traditional active dis-plays and absorbers to two.We find that increasing structural disorder difference of cubic-hexagonal can increase optical contrast close to the level of amorphous-cubic.Therefore,an amorphous-cubic-hexagonal phase transition with high optical contrast is realized.Using this phase transition,we have developed display and absorber with three distinct switching states,improving the switching perfor-mance by 50％.Through the combination of first-principle calculations and experiments,we reveal that the key to increasing structural disorder difference of amorphous,cubic and hexagonal phases is to intro-duce small interstitial impurities(like N)in Ge2Sb2Tes,rather than large substitutional impurities(like Ag)previously thought.This is explained by the formation energy and lattice distortion.Based on the impurity atomic radius,interstitial site radius and formation energy,C and B are also potential suit-able impurities.In addition,introducing interstitial impurities into phase-change materials with van der Waals gaps in stable phase such as GeSb4Te7,GeSb2Te4,Ge3Sb2Te6,Sb2Te3 will produce high optical con-trast amorphous-metastable-stable phase transition.This research not only reveals the important role of interstitial impurities in increasing the optical contrast between metastable-stable phases,but also proposes varieties of candidate matrices and impurities.This provides new phase-change materials and design methods for non-volatile optical devices with multi-switching states.     

Role of the HSP70 Co-Chaperone SIL1 in Health and Disease

Cell surface and secreted proteins provide essential functions for multicellular life. They enter the endoplasmic reticulum (ER) lumen co-translationally, where they mature and fold into their complex three-dimensional structures. The ER is populated with a host of molecular chaperones, associated co-factors, and enzymes that assist and stabilize folded states. Together, they ensure that nascent proteins mature properly or, if this process fails, target them for degradation. BiP, the ER HSP70 chaperone, interacts with unfolded client proteins in a nucleotide-dependent manner, which is tightly regulated by eight DnaJ-type proteins and two nucleotide exchange factors (NEFs), SIL1 and GRP170. Loss of SIL1′s function is the leading cause of Marinesco-Sjögren syndrome (MSS), an autosomal recessive, multisystem disorder. The development of animal models has provided insights into SIL1′s functions and MSS-associated pathologies. This review provides an in-depth update on the current understanding of the molecular mechanisms underlying SIL1′s NEF activity and its role in maintaining ER homeostasis and normal physiology. A precise understanding of the underlying molecular mechanisms associated with the loss of SIL1 may allow for the development of new pharmacological approaches to treat MSS.     

Enhanced wide-activated residual network for efficient and accurate image deblocking

To save bandwidth and storage space as well as speed up data transmission, people usually perform lossy compression on images. Although the JPEG standard is a simple and effective compression method, it usually introduces various visually unpleasing artifacts, especially the notorious blocking artifacts. In recent years, deep convolutional neural networks (CNNs) have seen remarkable development in compression artifacts reduction. Despite the excellent performance, most deep CNNs suffer from heavy computation due to very deep and wide architectures. In this paper, we propose an enhanced wide-activated residual network (EWARN) for efficient and accurate image deblocking. Specifically, we propose an enhanced wide-activated residual block (EWARB) as basic construction module. Our EWARB gives rise to larger activation width, better use of interdependencies among channels, and more informative and discriminative non-linearity activation features without more parameters than residual block (RB) and wide-activated residual block (WARB). Furthermore, we introduce an overlapping patches extraction and combination (OPEC) strategy into our network in a full convolution way, leading to large receptive field, enforced compatibility among adjacent blocks, and efficient deblocking. Extensive experiments demonstrate that our EWARN outperforms several state-of-the-art methods quantitatively and qualitatively with relatively small model size and less running time, achieving a good trade-off between performance and complexity.     

A novel strategy based on salp swarm algorithm for extracting the maximum power of proton exchange membrane fuel cell

Cell temperature and water content of the membrane have a significant effect on the performance of fuel cells. The current-power curve of the fuel cell has a maximum power point (MPP) that is needed to be tracked. This study presents a novel strategy based on a salp swarm algorithm (SSA) for extracting the maximum power of proton-exchange membrane fuel cell (PEMFC). At first, a new formula is derived to estimate the optimal voltage of PEMFC corresponding to MPP. Then the error between the estimated voltage at MPP and the actual terminal voltage of the fuel cell is fed to a proportional-integral-derivative controller (PID). The output of the PID controller tunes the duty cycle of a boost converter to maximize the harvested power from the PEMFC. SSA determines the optimal gains of PID. Sensitivity analysis is performed with the operating fuel cell at different cell temperature and water content of the membrane. The obtained results through the proposed strategy are compared with other programmed approaches of incremental resistance method, Fuzzy-Logic, grey antlion optimizer, wolf optimizer, and mine-blast algorithm. The obtained results demonstrated high reliability and efficiency of the proposed strategy in extracting the maximum power of the PEMFC.     

宰前倒挂应激对鸭血凝胶特性的影响

宰前倒挂因能有效提高屠宰效率成为肉鸭宰杀前必经的一个工艺过程，但倒挂往往会加剧肉鸭的应激程度，影响其血液品质，已成为工厂生产中亟待解决的问题。因此，本实验旨在借助血液学与凝血相关指标探究宰前倒挂应激对鸭血凝胶特性的影响。在屠宰前，将40 只樱桃谷鸭随机分为2 个处理组：对照组和宰前倒挂组（宰前倒挂2.5 min），屠宰后采集血样并制备血凝块，随后分析血液指标（应激指标、血液学指标、凝血指标）以及鸭血凝胶特性。结果表明，宰前倒挂组鸭血中皮质酮激素及促肾上腺皮质激素的水平均高于对照组，说明实验所建立宰前倒挂模型成立。倒挂应激后，红细胞计数、血小板计数、血红蛋白质量浓度增加，红细胞比容、平均红细胞体积及平均血小板体积增大；凝血酶原的水平极显著上升（P＜0.01），组织因子的水平显著上升（P＜0.05）。宰前倒挂最终导致鸭血凝胶化加快，鸭血凝胶体系中水分迁移速率增大，结合水与自由水比例减少，不易流动水比例增大，质构特性和保水性变差。研究揭示了宰前倒挂应激通过影响鸭血的血液学指标和凝血系统从而改变其凝胶行为及凝胶特性，可为工厂改善应激对鸭血凝胶品质的影响提供理论依据。     

Development of surface reconstruction algorithms for optical interferometric measurement

Optical interferometry is a powerful tool for measuring and characterizing areal surface topography in precision manufacturing. A variety of instruments based on optical interferometry have been developed to meet the measurement needs in various applications, but the existing techniques are simply not enough to meet the ever-increasing requirements in terms of accuracy, speed, robustness, and dynamic range, especially in on-line or on-machine conditions. This paper provides an in-depth perspective of surface topography reconstruction for optical interferometric measurements. Principles, configurations, and applications of typical optical interferometers with different capabilities and limitations are presented. Theoretical background and recent advances of fringe analysis algorithms, including coherence peak sensing and phase-shifting algorithm, are summarized. The new developments in measurement accuracy and repeatability, noise resistance, self-calibration ability, and computational efficiency are discussed. This paper also presents the new challenges that optical interferometry techniques are facing in surface topography measurement. To address these challenges, advanced techniques in image stitching, on-machine measurement, intelligent sampling, parallel computing, and deep learning are explored to improve the functional performance of optical interferometry in future manufacturing metrology.