The Exponentiated Generalized Power Generalized Weibull Distribution: Properties and Applications

This paper introduces a new flexible extension of power generalized Weibull distribution which contains many life-time distributions as sub-models. The hazard rate function of the proposed distribution is useful and suitable for monotone and non-monotone hazard behaviors that are more likely to be observed in real-life situations. Statistical properties of the new model are studied including; quantile, moment generating, reliability, hazard, and reverse hazard functions. Further, the moments, incomplete moments, mean deviations, Bonferroni and Lorenz curves, order statistics densities are derived. The maximum likelihood estimation method is used to estimate the distribution parameters. The effectiveness and usefulness of the new distribution are accomplished through four different real-life applications

Rapid mapping of digital integrated circuit logic gates via multi-spectral backside imaging

Modern semiconductor integrated circuits are increasingly fabricated at untrusted third party foundries. There now exist myriad security threats of malicious tampering at the hardware level and hence a clear and pressing need for new tools that enable rapid, robust and low-cost validation of circuit layouts. Optical backside imaging offers an attractive platform, but its limited resolution and throughput cannot cope with the nanoscale sizes of modern circuitry and the need to image over a large area. We propose and demonstrate a multi-spectral imaging approach to overcome these obstacles by identifying key circuit elements on the basis of their spectral response. This obviates the need to directly image the nanoscale components that define them, thereby relaxing resolution and spatial sampling requirements by 1 and 2 - 4 orders of magnitude respectively. Our results directly address critical security needs in the integrated circuit supply chain and highlight the potential of spectroscopic techniques to address fundamental resolution obstacles caused by the need to image ever shrinking feature sizes in semiconductor integrated circuits

Sunflower oil-based hyperbranched alkyd/spherical ZnO nanocomposite modeling for mechanical and anticorrosive applications

Approaches for designing advanced nanomaterials with hyperbranched architectures and lack of volatile organic content (VOC) have attracted considerable attention. In this study, eco-friendly hyperbranched alkyd resins for mechanical and anticorrosive coatings with high solid content were successfully synthesized based on sunflower oil (SFO) via a polyesterification approach. These resins are characterized by energy-efficient polymer synthesis, lack of gelation properties, high functionality, and low viscosity. A chemical precipitation process was used to fabricate zinc oxide (ZnO) spherical nanostructures with controlled diameters and morphologies. A series of conformal, novel, low-cost SFO-based hyperbranched alkyd/spherical ZnO nanocomposites were fabricated through an ex situ method. Various nanofiller concentrations were distributed to establish synergetic effects on the micro-nano binary scale performance of the materials. The features of the nanocomposites, including the molecular weight, acid and hydroxyl values of the prepared alkyd resins, were concomitantly assessed through various standard tests. The nanocomposites were also subjected to various tests to determine their surface adhesion and mechanical properties, such as impact, T-bending, crosscut, and abrasion resistance tests. Furthermore, the physico-mechanical properties, anticorrosive behavior, thermal stabilities and cellular cytotoxicities of the fabricated materials were assessed. The anticorrosive features of the nanocomposites were investigated through salt spray tests in 5 wt% NaCl. The results indicate that well-dispersed ZnO nanospheres (0.5%) in the interior of the hyperbranched alkyd matrix improve the durability and anticorrosive attributes of the composites; thus, they exhibit potential applications in eco-friendly surface coatings

BER and Capacity/Spectral Efficiency Enhancement of MIMO Systems Using Digital Antenna Arrays Beamforming

Multi-input Multi-output (MIMO) systems are of the most promising ones in the field of wireless communications as they provide high data rates and reduce the bit error rate (BER) using spatial multiplexing (SM) and diversity gain techniques, respectively. The deep review of MIMO systems shows that most of them are based on the utilization of uniform linear antennas (ULA) arrays. For further performance enhancement, a new digital array beamforming technique for linear antenna arrays optimization is introduced for both single-user and multi-user MIMO systems to achieve maximum gain. In our proposed technique, the antenna arrays are implemented for a higher gain by adjusting the feeding and the distance between the antenna elements. The modified mathematical model for our proposed digital array beamforming MIMO system has been derived and merged to the current linear detection techniques such as Maximum Likelihood (ML), Zero Forcing (ZF), and Minimum Mean Square Error (MMSE). The simulation results demonstrated the superiority of our proposed technique over the traditional MIMO systems in terms of BER and spectral efficiency (SE)

BER Performance Enhancement of MIMO Systems Using Hybrid Detection Techniques Based on Sphere Decoding

MIMO system is used in new communication systems to improve the bit error rate (BER), capacity, and the co-channel interference. In this paper, new hybrid detection techniques based on a combination between the sphere decoder (SD) and linear/non-linear detection techniques such as zero forcing (ZF), minimum mean square error (MMSE), Vertical Bell Lab Layered Space Time (V-BLAST), and lattice reduction are introduced. These hybrid techniques are intended to improve the BER performance of MIMO system. The proposed techniques are mainly based on dividing the received signal matrix into two equal size halves. The first half of the received symbols is detected using the selected linear or non-linear detector and the second half is detected using SD as the first scenario. For the second scenario, the first half of the received symbols is detected using SD and the second half is detected using the selected linear or non-linear detector. Several simulations are carried out to verify the efficiency of the proposed techniques. The simulations results show that the proposed techniques provide better performance than the traditional ones

Safe Reinforcement Learning using Data-Driven Predictive Control

Reinforcement learning (RL) algorithms can achieve state-of-the-art performance in decision-making and continuous control tasks. However, applying RL algorithms on safety-critical systems still needs to be well justified due to the exploration nature of many RL algorithms, especially when the model of the robot and the environment are unknown. To address this challenge, we propose a data-driven safety layer that acts as a filter for unsafe actions. The safety layer uses a data-driven predictive controller to enforce safety guarantees for RL policies during training and after deployment. The RL agent proposes an action that is verified by computing the data-driven reachability analysis. If there is an intersection between the reachable set of the robot using the proposed action, we call the data-driven predictive controller to find the closest safe action to the proposed unsafe action. The safety layer penalizes the RL agent if the proposed action is unsafe and replaces it with the closest safe one. In the simulation, we show that our method outperforms state-of-the-art safe RL methods on the robotics navigation problem for a Turtlebot 3 in Gazebo and a quadrotor in Unreal Engine 4 (UE4)

Theoretical and Experimental Sets of Choice Anode/Cathode Architectonics for High-Performance Full-Scale LIB Built-up Models

To control the power hierarchy design of lithium-ion battery (LIB) built-up sets for electric vehicles (EVs), we offer intensive theoretical and experimental sets of choice anode/cathode architectonics that can be modulated in full-scale LIB built-up models. As primary structural tectonics, heterogeneous composite superstructures of full-cell-LIB (anode//cathode) electrodes were designed in closely packed flower agave rosettes TiO2@C (FRTO@C anode) and vertical-star-tower LiFePO4@C (VST@C cathode) building blocks to regulate the electron/ion movement in the three-dimensional axes and orientation pathways. The superpower hierarchy surfaces and multi-directional orientation components may create isosurface potential electrodes with mobile electron movements, in-to-out interplay electron dominances, and electron/charge cloud distributions. This study is the first to evaluate the hotkeys of choice anode/cathode architectonics to assemble different LIB–electrode platforms with high-mobility electron/ion flows and high-performance capacity functionalities. Density functional theory calculation revealed that the FRTO@C anode and VST-(i)@C cathode architectonics are a superior choice for the configuration of full-scale LIB built-up models. The integrated FRTO@C//VST-(i)@C full-scale LIB retains a huge discharge capacity (~ 94.2%), an average Coulombic efficiency of 99.85% after 2000 cycles at 1 C, and a high energy density of 127 Wh kg−1, thereby satisfying scale-up commercial EV requirements

Will novel coronavirus (Covid-19) pandemic impact agriculture, food security and animal sectors?

The whole world is in a great danger due to the novel coronavirus (COVID-19) pandemic. In December 2019, the outbreak of COVID-19 took place in Wuhan, China and then rapidly spread all over the world. The current study provides potential expectations for the adverse impact of (COVID-19). The global infection affected globe on agricultural level such as agriculture, food supplies and animal production sectors. Till today, 29th April 2020, there is no vaccine available for treating novel coronavirus, consequently, the outbreak resulted in closing borders and reducing production following social distancing measures. This short communication illustrates the possible implications and expected outcomes of the outbreak of coronavirus (COVID-19) on agricultural, food security, integrated pest management (IPM), animal productivity; and it predicts, as well, the possible adverse impacts on the economy worldwide. Brazil has one of the most important tropical agriculture in the world, being a leader in soybean production in the world. This chain impacts others such as meat and eggs. The impact of COVID-19 will be positive, encouraging the country to consolidate its leadership in the world market, stimulating exports, the machinery, inputs and fertilizers market, as well as generating employment and income in the country

Nitrogen-doped carbon hollow trunk-like structure as a portable electrochemical sensor for noradrenaline detection in neuronal cells

To date, the production and development of portable analytical devices for environmental and healthcare applications are rapidly growing. Herein, a portable electrochemical sensor for monitoring of noradrenaline (NA) secreted from living cells using mesoporous carbon-based materials was fabricated. The modification of the interdigitated electrode array (IDA) by nitrogen-doped mesoporous carbon spheres (N-doped MCS) and nitrogen-doped carbon hollow trunk-like structure (N-doped CHT) was used to fabricate the NA sensor. The N-doped CHT surface shows multiple holes distributed with micrometer-sized open holes (1–2 μm) and nanometer-sized thin walls (∼98 nm). The N-doped CHT surface heterogeneity of wrinkled and twisted hollow trunk structures improve the diffusion pathway and the NA molecules loading. The N-doped CHT/IDA showed a highly selective assay for monitoring of NA with high sensitivity (1770 μA/μM × cm2), a low detection limit (0.005 μM), and a wide linear range (0.01–0.3 μM). The N-doped CHT/IDA monitored the NA secreted from PC12 cells under various concentrations of simulation agents (KCl). The designed N-doped CHT/IDA provides a portable NA-sensor assay with facile signaling, good stability, high biocompatibility, in-vitro assay compatibility, and good reproducibility. Therefore, the designed sensor can be used as a portable sensor for NA detection in live cells and can be matched with portable smartphones after further developments

Three-Dimensional Circular Surface Curvature of a Spherule-Based Electrode for Selective Signaling and Dynamic Mobility of Norepinephrine in Living Cells

A highly sensitive protocol for signaling norepinephrine (NEP) in human fluids and neuronal cell line models should be established for clinical investigation of some neuronal diseases. A metal-free electrode catalyst was designed based on a sulfur-doped carbon spheroidal surface (S-CSN) and employed as a transducing element for selective signaling of NEP in biological samples. The designed electrode of S-CSN features a spherical construct and curvature surface to form a spheroidal nanolayer with an average layer size of <2 nm. S-CSN shows surface topography of a circular surface curvature with a rugged surface texture, ridge ends, and free open spaces between interlayers. The rich-space diversity surfaces offer highly active surface with facile molecular/electron diffusion, multi-diffusive centers, and high target loading along with in-/out-of-plane circular spheres of the S-CSN surface. The active doping of S atoms onto the carbon-based electrode creates an active transducing element with many active sites, strong binding to targeted molecules, facile diffusion of charges/molecules, long-term durability, and dense reactive exposure sites for signaling NEP at ultratrace levels. S-CSN could be a sensitive and selective nanosensor for signaling NEP and establishing a sensing protocol with high stability and reproducibility. The sensory protocol based on S-CSN exhibits high sensitivity and selectivity with a low detection limit of 0.001 μM and a wide linear range of 0.01–0.8 μM. The in vitro sensory protocol for NEP secreted from living cells (neuronal cell line model) under stimulated agents possesses high sensitivity, low cytotoxicity, and high biocompatibility. These results confirm the successful establishment of NEP sensor in human blood samples and neuronal cells for clinical investigation