Investigating the effect of silver nanorods embedded in polydimethylsiloxane matrix using nanoindentation and its use for flexible electronics

The stretchable electrodes with excellent flexibility, electrical conductivity, and mechanical durability are the most fundamental components in the emerging and exciting field of flexible electronics. This article proposes a method for fabrication of such a stretchable electrode by embedding silver nanorods (AgNRs) into a polydimethylsiloxane (PDMS) matrix that is grown by a unique glancing angle deposition technique. The surface, mechanical, and electrical properties of PDMS are significantly changed after embedding the AgNRs in it. The results show that surface roughness and polarity increase after AgNRs are embedded in the PDMS matrix. Elastic modulus (E) and hardness (H) decrease with an increase in the indentation load as a result of the indentation depth effect. Due to strong interfacial adhesion of AgNRs embedded in the PDMS matrix, the E and H of nanocomposite are increased by 167.6 and 93.3% compared with PDMS film, respectively. Furthermore, the AgNRs-PDMS film has an electrical resistivity value in the order of 10⁻⁷ Ωm. It remains conductive during various mechanical strains such as bending, twisting, and stretching, which is demonstrated using a light-emitting diode circuit. Simultaneously, the antimicrobial activity of silver could make it a promising candidate for wearable electronics.     

Escherichia coli,Salmonella spp., and Staphylococcus aureus susceptibility to antimicrobials of human and veterinary importance in poultry sector of India

In India, little attention has been paid on antimicrobial resistance (AMR) in the context of developing “One Health” approach. Hence, utilizing multi-disciplinary approach, we assess the AMR level and dynamics/pattern of multi-drug resistance (MDR) in Escherichia coli, Salmonella spp., and Staphylococcus aureus circulating over the different stages of poultry in India. A total of 342 isolates including E. coli (n = 143), Salmonella spp. (n = 104), and S. aureus (n = 95) were recovered from fecal (n = 80) and cecal (n = 80) samples of chicken, collected across the different poultry-retail shops and poultry-farms located at urban and rural areas of Rajasthan, India, respectively. High rates of AMR to drugs that are critically/highly important both in human and veterinary medicine were observed among all the isolates. Upward trends in AMR prevalence was observed in poultry-retail shops than in poultry-farms. Notably, >90% of all the isolates were MDR, of particular, pattern/prevalence of MDR was substantially varied across the poultry-farms vs. poultry-retail shops. Our results indicate AMR including MDR to be common in E. coli, Salmonella spp., and S. aureus distributed frequently in poultry. The study encourages the formulation of national policy, programmes and further research with a “One Health” approach that can benefits to the human/animal and the environment.     

Electrocatalytic Reduction of CO2 to Ethylene by Molecular Cu‐Complex Immobilized on Graphitized Mesoporous Carbon

The electrochemical reduction of carbon dioxide (CO₂) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO₂ to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO₂ to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO₂ in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.     

Bounds on the number of samples needed for neural learning.

The relationship between the number of hidden nodes in a neural network, the complexity of a multiclass discrimination problem, and the number of samples needed for effect learning are discussed. Bounds for the number of samples needed for effect learning are given. It is shown that Omega(min (d,n) M) boundary samples are required for successful classification of M clusters of samples using a two-hidden-layer neural network with d-dimensional inputs and n nodes in the first hidden layer.     

A VLSI architecture for a half-edge-based corner detector

Corner detection is a low-level feature detection operator that is of great use in image processing applications, for example, optical flow and structure from motion by image correspondence. The detection of corners is a computationally intensive operation. Past implementations of corner detection techniques have been restricted to software. In this paper we propose an efficient very large-scale integration (VLSI) architecture for detection of corners in images. The corner detection technique is based on the half-edge concept and the first directional derivative of Gaussian. Apart from the location of the corner points, the algorithm also computes the corner orientation and the corner angle and outputs the edge map of the image. The symmetrical properties of the masks are utilized to reduce the number of convolutions effectively, from eight to two. Therefore, the number of multiplications required per pixel is reduced from 1800 to 392. Thus, the proposed architecture yields a speed-up factor of 4.6 over conventional convolution architectures. The architecture uses the principles of pipelining and parallelism and can be implemented in VLSI.     

Performance of hashed cache data migration schemes on multicomputers

Many researchers approach the problem of programming distributed memory machines by assuming a global shared name space. Thus the user views the distributed memory of the machine as though it were shared. A major issue that arises at this point is how to manage the memory. When a processor accesses data stored on another processor's memory, data must be moved between the two processors. Once these data are retrieved from another processor's memory, several interesting issues are raised. Where should these data be stored locally? What transformations must be performed to the code to guarantee that the nonlocal accesses reference the correct memory location? What optimizations can be performed to reduce the time spent in accessing the nonlocal data? In this paper we examine various data migration mechanisms that allow an explicit and controlled mapping of data to memory. We describe, experimentally evaluate, and model a set of schemes for storing and retrieving off-processor array elements. The schemes are all based on using hash tables for efficient access of nonlocal data. The three different techniques evaluated are the basic hashed cache, partial enumeration, and full enumeration, the details of which are described in the paper. In all three schemes, nonlocal data are stored in hash tables—the difference is in the amount of memory used by the schemes and the retrieval mechanisms for nonlocal data.     

An inverse solution methodology for estimating the diffusion coefficient of gases in Athabasca bitumen from pressure-decay data

An inverse solution methodology is developed for the estimation of diffusion coefficient of gases in highly viscous, oil-sands bitumens from isothermal, pressure-decay measurements. The approach involves modeling the rate of change in pressure using the diffusion equation for the liquid phase coupled with a mass balance equation for the gas phase. The inverse solution framework is utilized to arrive at two graphical techniques for estimating the diffusion coefficient. Both techniques involve the determination of the slope of a straight line resulting from plotting the experimental data in accordance with the developed model. An advantage of the proposed techniques is that the diffusion coefficient is estimated directly, i.e. without making it an adjustable parameter. The novelty of the proposed method is in its simplicity as well as its ability to isolate portions of the pressure-decay data affected by experimental fluctuations. The effect of the initial pressure on the predicted diffusion coefficient and pressure-decay profile was also investigated. The diffusion coefficients of CO₂, CH₄, C₂H₆ and N₂ in Athabasca bitumen at 50–90 °C and about 8 MPa were estimated and compared with literature values.