Dense Platinum/Nickel Oxide Heterointerfaces with Abundant Oxygen Vacancies Enable Ampere-Level Current Density Ultrastable Hydrogen Evolution in Alkaline

Platinum (Pt) remains the benchmark electrocatalyst for alkaline hydrogen evolution reaction (HER), but its industry-scale hydrogen production is severely hampered by the lack of well-designed durable Pt-based materials that can operate at ampere-level current densities. Herein, based on the original oxide layer and parallel convex structure on the surface of nickel foam (NF), a 3D quasi-parallel architecture consisting of dense Pt nanoparticles (NPs) immobilized oxygen vacancy-rich NiO_x heterojunctions (Pt/NiO_x-O_V) as an alkaline HER catalyst is developed. A combined experimental and theoretical studies manifest that anchoring Pt NPs on NiO_x-O_V leads to electron-rich Pt species with altered density of states (DOS) distribution, which can efficiently optimize the d-band center and the adsorption of reaction intermediates as well as enhance the water dissociation ability. The as-prepared catalyst exhibits extraordinary HER performance with a low overpotential of 19.4 mV at 10 mA cm⁻², a mass activity 16.3-fold higher than that of 20% Pt/C, and a long durability of more than 100 h at 1000 mA cm⁻². Furthermore, the assembled alkaline electrolyzer combined with NiFe-layered double hydroxide requires extremely low voltage of 1.776 V to attain 1000 mA cm⁻², and can operate stably for more than 400 h, which is rarely achieved.     

Genetic-Chicken Swarm Algorithm for Minimizing Energy in Wireless Sensor Network

Wireless Sensor Network (WSN) technology is the real-time application that is growing rapidly as the result of smart environments. Battery power is one of the most significant resources in WSN. For enhancing a power factor, the clustering techniques are used. During the forward of data in WSN, more power is consumed. In the existing system, it works with Load Balanced Clustering Method (LBCM) and provides the lifespan of the network with scalability and reliability. In the existing system, it does not deal with end-to-end delay and delivery of packets. For overcoming these issues in WSN, the proposed Genetic Algorithm based on Chicken Swarm Optimization (GA-CSO) with Load Balanced Clustering Method (LBCM) is used. Genetic Algorithm generates chromosomes in an arbitrary method then the chromosomes values are calculated using Fitness Function. Chicken Swarm Optimization (CSO) helps to solve the complex optimization problems. Also, it consists of chickens, hens, and rooster. It divides the chicken into clusters. Load Balanced Clustering Method (LBCM) maintains the energy during communication among the sensor nodes and also it balances the load in the gateways. The proposed GA-CSO with LBCM improves the lifespan of the network. Moreover, it minimizes the energy consumption and also balances the load over the network. The proposed method outperforms by using the following metrics such as energy efficiency, ratio of packet delivery, throughput of the network, lifetime of the sensor nodes. Therefore, the evaluation result shows the energy efficiency that has achieved 83.56% and the delivery ratio of the packet has reached 99.12%. Also, it has attained linear standard deviation and reduced the end-to-end delay as 97.32 ms.     

Modeling and analysis for the development of Lightweight Piezoceramic Composite Actuators (LIPCA)

This paper focuses on the modeling and analysis of Lightweight Piezoceramic Composite Actuators (LIPCA) for developmental purposes. A simple analytical model and a numerical model for predicting the displacement of the actuators due to both an applied input voltage and transverse load to the piezoelectric ceramic layer are presented. The analytical model describing the laminated beam actuation results in two primary design parameters, an actuation coefficient of a laminated beam C_ulb and the bending stiffness of a laminated beam EI_lb. The C_ulb is a parameter when maximum displacement is required. The bending stiffness affects the displacement performance when a transverse load is applied to the actuators. An experiment was performed to verify the proposed laminated beam model. The numerical model, a NASTRAN finite element model, is used to assess the effect of initial dome heights of actuators on the displacement. An increase in the initial dome height produces a positive effect for the low anisotropic actuators and gives a negative effect for the high anisotropic actuators. In conclusion, the results indicate that designing to maximize the C_ulb, the EI_lb, and the initial dome height of the low anisotropic actuators could generate LIPCA-type actuators with larger displacement and higher force.     

Identification and validation of calmodulin as a binding protein of an anti-proliferative small molecule 3,4-dihydroisoquinolinium salt

IHY-153 (2-(2,5-difluorobenzyl)-3,4-dihydro-5-(10-hydroxydecyl)-6-methoxy-1-undecylisoquinolinium bromide) was recently discovered as a small molecule that potently inhibits proliferation of tumor cells by inducing cell-cycle arrest at G0-G1 phase. To investigate the basis of anti-proliferative activity of IHY-153, cellular binding proteins of biotinyl-IHY-153 were screened using T7 phage displayed human cDNA libraries. Calmodulin-expressing phage specifically bound to immobilized IHY-153 in a Ca(2+) -dependent manner. The interaction between IHY-153 and Ca(2+) /CaM was validated through phage competition binding assays, surface plasmon resonance analysis, and molecular modeling. IHY-153 induced sustained phosphorylation of extracellular signal-regulated kinase (ERK) 1/2 and subsequently increased p21(WAF1) expression in colon cancer cells. These results demonstrate that IHY-153, a novel small molecule, targets Ca(2+) /CaM and indicate that this compound functions as an anti-proliferative agent by influencing Ca(2+) /CaM-dependent signal transduction.     

Automatic symbolic compositional verification by learning assumptions

Compositional reasoning aims to improve scalability of verification tools by reducing the original verification task into subproblems. The simplification is typically based on assume-guarantee reasoning principles, and requires user guidance to identify appropriate assumptions for components. In this paper, we propose a fully automated approach to compositional reasoning that consists of automated decomposition using a hypergraph partitioning algorithm for balanced clustering of variables, and discovering assumptions using the L ^* algorithm for active learning of regular languages. We present a symbolic implementation of the learning algorithm, and incorporate it in the model checker NuSmv. In some cases, our experiments demonstrate significant savings in the computational requirements of symbolic model checking. This research was partially supported by ARO grant DAAD19-01-1-0473, and NSF grants ITR/SY 0121431 and CCR0306382.     

Lossless video coding based on pixel-wise prediction

The state-of-the-art H.264/AVC was designed for lossy video coding in the beginning. Recently, the H.264/AVC FRExt was developed by removing transformation and quantization for lossless coding. In this paper, we propose an efficient intra lossless coding method based on a pixel-wise prediction. The proposed algorithm introduces an additional intra prediction mode that employs the LOCO-I predictor of JPEG LS. We found that the proposed lossless coding algorithm achieved approximately 22.0, 2.6, and 10.7% bit saving in terms of compression ratio, compared to the H.264/AVC FRExt, lossless intra 4:4:4, and Takamura’s lossless coding methods, respectively.     

Instability dependent upon bias and temperature stress in amorphous‐indium gallium zinc oxide (a‐IGZO) thin‐film transistors

Abstract— The effects of gate‐bias stress, drain‐bias stress, and temperature on the electrical parameters of amorphous‐indium gallium zinc oxide (a‐IGZO) thin‐film transistors have been investigated. Results demonstrate that the devices suffer from threshold‐voltage instabilities that are recovered at room temperature without any treatments. It is suggested that these instabilities result from the bias field and temperature‐assisted charging and discharging phenomenon of preexisting traps at the near‐interface and the a‐IGZO channel region. The experimental results show that applying a drain‐bias stress obviously impacts the instability of a‐IGZO TFTs; however, the instability caused by drain bias is not caused by hot‐electron generation as in conventional MOSFETs. And the degradation trend is affected by thermally activated carriers at high temperature.     

Shape sensitivity analysis with design-dependent loadings—equivalence between continuum and discrete derivatives

The purpose of this paper is twofold: (1) showing equivalence between continuum and discrete formulations in sensitivity analysis when a linear velocity field is used and (2) presenting shape sensitivity formulations for design-dependent loadings. The equations for structural analysis are often composed of the stiffness part and the applied loading part. The shape sensitivity formulations for the stiffness part were well-developed in the literature, but not for the loading part, especially for body forces and surface tractions. The applied loads are often assumed to be conservative or design-independent. In shape design problems, however, the applied loads are often functions of design variables. In this paper, shape sensitivity formulations are presented when the body forces and surface tractions depend on shape design variables. Especially, the continuum–discrete (C–D) and discrete–discrete (D–D) approaches are compared in detail. It is shown that the two methods are theoretically and numerically equivalent when the same discretization, numerical integration, and linear design velocity fields are used. The accuracy of sensitivity calculation is demonstrated using a cantilevered beam under uniform pressure and an arch dam crown cantilever under gravity and hydrostatic loading at the upstream face of the structure. It is shown that the sensitivity results are consistent with finite difference results, but different from the analytical sensitivity due to discretization and approximation errors of numerical analysis.     

Loss of Nckx3 Exacerbates Experimental DSS-Induced Colitis in Mice through p53/NF-κB Pathway

Inflammatory bowel diseases (IBDs) comprises a range of chronic inflammatory conditions of the intestinal tract. The incidence and prevalence of IBDs are increasing worldwide, but the precise etiology of these diseases is not completely understood. Calcium signaling plays a regulatory role in cellular proliferation. Nckx3, a potassium-dependent Na⁺/Ca²⁺ exchanger, is not only expressed in the brain but also in the aortic, uterine, and intestinal tissues, which contain abundant smooth muscle cells. This study investigated the role of Nckx3 in intestinal inflammation. Microarray analyses revealed the upregulation of the innate immune response-associated genes in the duodenum of Nckx3 knockout (KO) mice. The Nckx3 KO mice also showed an increase in IBD- and tumorigenesis-related genes. Using dextran sodium sulfate (DSS)-induced experimental colitis mice models, the Nckx3 KO mice showed severe colitis. Furthermore, the pathways involving p53 and NF-κB signaling were significantly upregulated by the absence of Nckx3. Overall, Nckx3 plays a critical role in the innate immune and immune response and may be central to the pathogenesis of IBD.     

Estimation of Mass Transport Parameters of Organic Compounds through High Density Polyethylene Geomembranes Using a Modifield Double-Compartment Apparatus

A modified double-compartment apparatus (MDCA) is used to estimate mass transport parameters of organic compounds through high density polyethylene (HDPE) geomembranes and to investigate the effects of aging and external tension of HDPE geomembranes on the mass transport of organic compounds. A developed one-dimensional partition–diffusion mass transport model successfully explains the mass transport of the organic compounds through the HDPE geomembranes in a dilute aqueous solution–geomembrane system. Similar to batch immersion tests, the HDPE–water partition coefficient (KHDPE–W) values of organic compounds are found to have close relationships with the octanol–water partition coefficient and the aqueous solubility; furthermore, the diffusion coefficient (D) values decrease with the increase of their molecular diameter. For HDPE geomembranes served in the landfill liner for 5 years and stretched by 8% of their initial length, KHDPE–W values for organic compounds increase by 5–58%, D values for organic compounds increase by 10–86%, and breakthrough times are faster, indicating more amounts of organic compounds may break through the HDPE geomembrane in fields than expected. The mass transport parameters from MDCA tests could be used with those from batch immersion tests interchangeably after mass loss and immobilization of organic compounds in MDCA tests are considered.