A Hybrid Strategy-Based Ultra-Narrow Stretchable Microelectrodes with Cell-Level Resolution

Stretchable ultra-narrow (e.g., 10 µm in width) microelectrodes are crucial for the electrophysiological monitoring of single cells providing the fundamental understanding to the working mechanism of neuro network or other electrically functional cells. Current fabrication strategies either focus on the preparation of normal stretchable electrodes with hundreds of micrometers or millimeters in width by using inorganic conductive materials or develop conductive organic polymer gel for ultra-narrow electrodes which suffer from low stretchability and instability for long-term implantation, therefore, it is still highly desirable to explore bio-interfacial ultra-narrow stretchable inorganic electrodes. Herein, a hybrid strategy is reported to prepare ultra-narrow multi-channel stretchable microelectrodes without using photolithography or laser-assisting etching. A 10 µm × 10 µm monitoring window is fabricated with enhanced interfacial impedance by the special rough surface. The stretchability achieves to 120% for this 10 µm-width stretchable electrode. Supported by these superior properties, it is demonstrated that the stretchable microelectrodes can detect electrophysiological signals of single cells in vitro and collect electrophysiological signals more precisely in vivo. The reported strategy will open up the accessible preparation of the fine-size stretchable microelectrode. It will significantly improve the resolution of monitoring and stimulation of inorganic stretchable electrodes.     

Secrecy Trade-off at the Physical Layer over Mixed Fading Multicast Channels Employing Antenna Diversity

This paper deals with the secrecy performance analysis of a multicast network over mixed fading scenarios in which a cluster of passive eavesdroppers is trying to overhear the secret transmission. Our key contribution is to prevent this malicious attack of the illegitimate receivers. Rayleigh/ Rician mixed fading channels are considered to model alternately the multicast/ eavesdropper and eavesdropper/ multicast channels as such mixed fading scenarios are often encountered in cellular communication where only one link (either multicast or eavesdropper) undergo a line-of-sight propagation path. At first, we derive the probability density functions for the single-input-multiple-output multicast scenarios and then the secrecy analysis is carried out by obtaining closed-form expressions for the performance matrices such as the probability of non-zero secrecy multicast capacity, ergodic secrecy multicast capacity, and secure outage probability for multicasting. The derived expressions are beneficial to investigate how the antenna diversity can combat the detrimental impact of fading as well as the number of multicast users and eavesdroppers, and improve the secrecy level to the acceptable limit. Moreover, the best secure scenario in terms of the secrecy parameters is obtained when the multicast channels undergo Rician fading whereas the eavesdropper channels experience Rayleigh fading. Finally, the analytical expressions are justified via the Monte-Carlo simulations.

     

Semi-Supervised Deep Learning for Multi-Tissue Segmentation from Multi-Contrast MRI

Journal of Signal Processing Systems - Segmentation of thigh tissues (muscle, fat, inter-muscular adipose tissue (IMAT), bone, and bone marrow) from magnetic resonance imaging (MRI) scans is useful...     

A hybrid method for variable-order fractional 2D optimal control problems on an unbounded domain

Engineering with Computers - In this study, the Caputo-Fabrizio fractional derivative is applied to generate a new category of variable-order fractional 2D optimization problems in an unbounded...     

Orthonormal Bernoulli polynomials for space–time fractal-fractional modified Benjamin–Bona–Mahony type equations

Engineering with Computers - In this study, a new fractal-fractional (FF) derivative is defined by coupling the local conformable derivative and non-local Caputo fractional derivative. Using the...     

Containerization technologies: taxonomies,applications and challenges

Modern scientific research challenges require new technologies, integrated tools, reusable and complex experiments in distributed computing infrastructures. But above all, computing power for efficient data processing and analyzing. Containers technologies have emerged as a new paradigm to address such intensive scientific applications problems. Their easy deployment in a reasonable amount of time and the few required computational resource make them more suitable. Containers are considered light virtualization solutions. They enable performance isolation and flexible deployment of complex, parallel, and high-performance systems. Moreover, they gained popularity to modernize and migrate scientific applications in computing infrastructure management. Additionally, they reduce computational time processing. In this paper, we first give an overview of virtualization and containerization technologies. We discuss the taxonomies of containerization technologies of the literature, and then we provide a new one that covers and completes those proposed in the literature. We identify the most important application domains of containerization and their technological progress. Furthermore, we discuss the performance metrics used in most containerization techniques. Finally, we point out research gaps in the related aspects of containerization technology that require more research.

     

Resource-constrained FPGA implementation of YOLOv2

Neural Computing and Applications - Progress is being made to deploy convolutional neural networks (CNNs) into the Internet of Things (IoT) edge devices for handling image analysis tasks locally....     

Creation and electrical properties of p-Cu2ZnSnS4/n-Si heterojunctions

Technical Physics Letters - Anisotype p-Cu2ZnSnS4/n-Si heterojunctions have been manufactured for the first type by sulfidation of base-metal layers predeposited onto polycrystalline silicon...     

The influence of particle geometry and the intermediate stress ratio on the shear behavior of granular materials

The behavior of granular materials is very complex in nature and depends on particle shape, stress path, fabric, density, particle size distribution, amongst others. This paper presents a study of the effect of particle geometry (aspect ratio) on the mechanical behaviour of granular materials using the discrete element method (DEM). This study discusses 3D DEM simulations of conventional triaxial and true triaxial tests. The numerical experiments employ samples with different particle aspect ratios and a unique particle size distribution (PSD). Test results show that both particle aspect ratio (AR) and intermediate stress ratio \((b=({\upsigma }_{2}'-{\upsigma }_{3}')/({\upsigma }_{1}'-{\upsigma }_{3}'))\) affect the macro- and micro-scale responses. At the macro-scale, the shear strength decreases with an increase in both aspect ratio and intermediate stress ratio b values. At the micro-scale level, the fabric evolution is also affected by both AR and b. The results from DEM analyses qualitatively agree with available experimental data. The critical state behaviour and failure states are also discussed. It is observed that the position of the critical state loci in the compression \((e-p')\) space is only slightly affected by aspect ratio (AR) while the critical stress ratio is dependent on both AR and b. It is also demonstrated that the influence of the aspect ratio and the intermediate stress can be captured by micro-scale fabric evolutions that can be well understood within the framework of existing critical state theories. It is also found that for a given stress path, a unique critical state fabric norm is dependent on the particle shape but is independent of critical state void ratio.