Neural Network Based Thermal Analysis of Ultradeep Submicron Digital Circuit Design

With a reduction in transistor dimensions to the nanoscale regime of 45 nm or less, quantum mechanical effects begin to reveal themselves and have an impact on key device performance parameters. As a result, in order to develop simulation tools that can be used for the design of nanoscale transistors in the future, new theories and modelling methodologies must be developed that properly and effectively capture the physics of quantum transport. An artificial neural network(ANN) is used in this paper to examine nanoscale CMOS circuits and predict the performance parameters of CMOS-based digital inverters for a temperature range of 300 K to 400 K. The training algorithm included three hidden layers with sizes of 20, 10, and 8, as well as a function fitting ANN with Bayesian Backpropagation Regularization. Further, simulation through HSPICE using Predictive Technology Model(PTM) nominal parameters has been done to compare with ANN(trained using an analytical model) results. The obtained results lie within the acceptable range of 1%-10%. Moreover, it has also been demonstrated that the ANN simulation provides a speed improvement of around 85 % over the HSPICE simulation, and that it can be easily integrated into software tools for designing and simulating complicated CMOS logic circuits.

Analyzing the Prebiotic Potential of Glucosamine for Targeting the Gut Microbiome Health

Recognizing the composition and modulation of the microbiome, a viable therapeutic tool for multi-targeted therapy is a new strategy that has recently been explored. Glucosamine (GS) is being studied for its prebiotic potential in addition to being the most abundant and naturally occurring amino monosaccharide. The current study focuses on glucosamine’s prebiotic potential by assessing the stability of various GS concentrations (1% - 5%) in the gastrointestinal tract (GIT) and its ability to be fermented by the gut microbiota. The results showed that GS stimulated the most growth in L. acidophilus even after a longer incubation time than B. bifidum and L. acidophilus growth was concentration-dependent, with maximum growth at 3% with a simultaneous decrease in pH (5.6 - 1.7). The decrease in GS concentration with time also represented the growth of bacterial species, demonstrating the species’ utilization of GS. Furthermore, at 3%, GS also represented the prebiotic index of 1.9. In addition, the concentration of GS in various simulated GIT fluids was estimated in both fast and fed conditions to examine GS stability at various levels in the gut. The results showed that GS remained unaffected and non-digestible in all of the simulated GIT fluids (salivary, gastric, intestinal, and colonic), but there was a slight decrease in GS concentration (2.8%) in the fasted state of gastric fluid due to low pH levels (1.6). As a result, the findings are conclusive and suggest that GS possesses prebiotic properties.

Paederia foetida- a promising ethno-medicinal tribal plant of northeastern India

The northeastern region of India constitutes one of the biodi- versity hotspots of the world. The ethnic groups inhabiting this region practice their distinctive traditional knowledge systems using biodiver- sity for food, shelter and healthcare. Among the less-studied plants, Paederia foetida has been used by various ethnic tribes as food and medicine. Many of its therapeutic properties relate to the gastrointestinal system and suggest its potential utility for gastrointestinal ailments. This is a review of the ethnobotanical uses, phytochemistry and therapeutic properties of P. foetida compiled from various reports. P. foetida is promising as a remedy for life-style related conditions, especially treat- ment of ulcers. Its utility highlights the need for proper evaluation of tribal plants as medicines and the species could be considered for devel- opment of new drugs.

Two-component modeling for non-Newtonian nanofluid slip flow and heat transfer over sheet: Lie group approach

The present paper deals with the multiple solutions and their stability analy- sis of non-Newtonian micropolar nanofluid slip flow past a shrinking sheet in the presence of a passively controlled nanoparticle boundary condition. The Lie group transformation is used to find the similarity transformations which transform the governing transport equations to a system of coupled ordinary differential equations with boundary condi- tions. These coupled set of ordinary differential equation is then solved using the Runge- Kutta-Fehlberg fourth-fifth order （RKF45） method and the ode15s solver in MATLAB. For stability analysis, the eigenvalue problem is solved to check the physically realizable solution. The upper branch is found to be stable, whereas the lower branch is unsta- ble. The critical values （turning points） for suction （0 〈 sc 〈 s） and the shrinking parameter （Xc 〈 X 〈 0） are also shown graphically for both no-slip and multiple-slip conditions. Multiple regression analysis for the stable solution is carried out to inves- tigate the impact of various pertinent parameters on heat transfer rates, The Nusselt number is found to be a decreasing function of the thermophoresis and Brownian motion parameters.

On the Approximation of an Analytic Function Represented by Laplace-Stieltjes Transformation

In the present paper,we have considered the approximation of analytic functions represented by Laplace-Stieltjes transformations using sequence of definite integrals. We have characterized their order and type in terms of the rate of decrease of E;（F,β） where E;（F,β） is the error in approximating of the function F（s） by definite integral polynomials in the half plane Res≤β<α.

Identification of Sarcasm in Textual Data: A Comparative Study

Purpose:Ever increasing penetration of the Internet in our lives has led to an enormous amount of multimedia content generation on the internet.Textual data contributes a major share towards data generated on the world wide web.Understanding people’s sentiment is an important aspect of natural language processing,but this opinion can be biased and incorrect,if people use sarcasm while commenting,posting status updates or reviewing any product or a movie.Thus,it is of utmost importance to detect sarcasm correctly and make a correct prediction about the people’s intentions.Design/methodology/approach:This study tries to evaluate various machine learning models along with standard and hybrid deep learning models across various standardized datasets.We have performed vectorization of text using word embedding techniques.This has been done to convert the textual data into vectors for analytical purposes.We have used three standardized datasets available in public domain and used three word embeddings i.e Word2Vec,GloVe and fastText to validate the hypothesis.Findings:The results were analyzed and conclusions are drawn.The key finding is:the hybrid models that include Bidirectional LongTerm Short Memory(Bi-LSTM)and Convolutional Neural Network(CNN)outperform others conventional machine learning as well as deep learning models across all the datasets considered in this study,making our hypothesis valid.Research limitations:Using the data from different sources and customizing the models according to each dataset,slightly decreases the usability of the technique.But,overall this methodology provides effective measures to identify the presence of sarcasm with a minimum average accuracy of 80%or above for one dataset and better than the current baseline results for the other datasets.Practical implications:The results provide solid insights for the system developers to integrate this model into real-time analysis of any review or comment posted in the public domain.This study has various other practical implications for businesses that depend on user ratings and public opinions.This study also provides a launching platform for various researchers to work on the problem of sarcasm identification in textual data.Originality/value:This is a first of its kind study,to provide us the difference between conventional and the hybrid methods of prediction of sarcasm in textual data.The study also provides possible indicators that hybrid models are better when applied to textual data for analysis of sarcasm.

Analysis of periodic and aperiodic convective stability of double diffusive nanofluid convection in rotating porous layer

The onset of periodic and aperiodic convection in a binary nanofiuid satu- rated rotating porous layer is studied considering constant flux boundary conditions. The porous medium obeys Darcy＇s law, while the nanofluid envisages the effects of the Brow- nian motion and thermophoresis. The Rayleigh numbers for stationary and oscillatory convection are obtained in terms of various non-dimensional parameters. The effect of the involved physical parameters on the aperiodic convection is studied graphicMly. The results are validated in comparison with the published literature in limiting cases of the present study.

Controllable Transdermal Drug Delivery of Theobroma cacao Extract Based Polymeric Hydrogel against Dermal Microbial and Oxidative Damage

Human dermal layers are directly bared to the external environmental adversities like pollution, radiation, dust along with various chemical and mechanical stress conditions which constantly lead to the oxidative stress, eventually forming free radicals. These conditions also support the dermal microbial infections by invading the cutaneous layers. Therefore, the most efficient approach accepted globally to combat these complications is to opt for transdermal application of exogenous antioxidants which helps in reducing the ill effects of oxidative stress and promotes the DNA repair. However, many scientific findings exhibited the potential role of Theobroma cacao for providing efficient skin protection. Theobroma cacao known for its vital procyanidin flavonoids, phenolic compounds, methylxanthines, catechin and epicatechin phytoconstituents with numerous health benefits, besides helping in smoothening and softening the damaged skin. These therapeutic benefits of cocoa phytocompounds are attributed to its anti-inflammatory and antioxidative characteristics. This study addresses the fabrication and optimizations of Theobroma cacao extract loaded carbopol hydrogel system for increased antioxidative and antimicrobial effects. It was found in the studies that the hydrogel-based T. cacao extract (TCHG) has significantly improved the therapeutic index of the extract, making it more suitable for transdermal application. The optimized hydrogel was further characterized by physicochemical parameters, SEM analysis and in-vitro release kinetics. The reported findings showed the sustained compound release with comparatively significant antimicrobial activity of TCHG against microbial (Pseudomonas fluorescens, Bacillus licheniformis, Micrococcus luteus, Aspergillus niger, Trichoderma harzianum, Rhizopus oryzae) infections. Also, the higher ROS quenching ability of TCHG as compared to T. cacao extract promises to be an effective transdermal formulation.

<i>In-Silico</i>Validation and Development of Chlorogenic Acid (CGA) Loaded Polymeric Nanoparticle for Targeting Neurodegenerative Disorders

Background: Recent decades witnessed a significant growth in terms of phytocompounds based therapeutics, extensively explored for almost all types of existing disorders. They have also been widely investigated in Neurodegenerative disorders (NDDs) and Chlorogenic acid (CGA), a polyphenolic compound having potential anti-inflammatory and anti-oxidative properties, emerged as a promising compound in ameliorating NDDs. Owing to its poor stability, bioavailability and release kinetics, CGA needed a suitable nanocarrier based pharmaceutical design for targeting NDDs. Objective: The current study is aimed at the in-silico validation of CGA as an effective therapeutic agent targeting various NDDs followed by the fabrication of polymeric nanoparticles-based carrier system to overcome its pharmacological limitations and improve its stability. Methods: A successful in-silico validation using molecular docking techniques along with synthesis of CGA loaded polymeric nanoparticles (CGA-NPs) by ionic gelation method was performed. The statistical optimisation of the developed CGA-NPs was done by Box Behnken method and then the optimized formulation of CGA-NPs was characterised using particle size analysis (PSA), Transmission electron microscopy (TEM), Fourier Transform Infrared spectroscopy (FTIR) along with in-vitro release kinetics analysis. Results & Conclusion: The results attained exhibited average particle size of 101.9 ± 1.5 nm, Polydispersibility (PDI) score of 0.065 and a ZP of −17.4 mV. On a similar note, TEM results showed a size range of CGA-NPs between 90 - 110 nm with a spherical shape of NPs. Also, the data from in-vitro release kinetics showed a sustained release of CGA from the NPs following the first-order kinetics suggesting the appropriate designing of nanoformulation.

Synthesis and Characterization of <i>Citrus limonum</i>Essential Oil Based Nanoemulsion and Its Enhanced Antioxidant Activity with Stability for Transdermal Application

Lemon oil (LO), also known as Citrus limonum is a highly volatile essential oil (EO) with potential therapeutic properties like anti-oxidative, anti-proliferative, anti-fungal and anti-cancerous. However, the efficacy of LO is limited due to its physiological factors such as high volatility, poor stability (particularly sensitive to sunlight) and quick degradability upon exposure. To overcome these challenges, we formulated lemon oil loaded nanoemulsion system (LO-NE) (oil-in-water), using aqueous titration method. The formulation comprised of lemon oil (LO), Tween 80 and ethanol as oil, surfactant and co-surfactant phases respectively. The existence zone of NE was established by constructing pseudo-ternary phase diagrams using different concentrations of LO, surfactant and co-surfactant (Smix). The quantitative estimation of LO was performed using a high throughput gas chromatography, revealing the presence of various compounds like Limonene, Alpha-Pinene and Linalyl acetate followed by the estimation of total phenolics and flavonoid content. The characterization of LO-NE indicated the particle size of 60 ± 2.5 nm along with the polydispersity index of 0.125 and zeta potential of −14.9 mV. The size range of the NE particles dispersed in the colloidal system was further verified by TEM micrograph which shows size range between 46.2 - 104.7 nm. All the anti-oxidant assays outcomes exhibited the higher activity of LO-NE in comparison to LO alone with lower IC50 values. The release kinetics statistical data showed that LO-NE had a sustained release and followed the Higuchi’s model in comparison to burst release of LO alone. Lastly, the stability analysis of the optimised formulation (LO-NE) and LO was estimated through antioxidant assay and subjecting them for thermodynamic stability after 6 months. The results attained, showed higher stability and anti-oxidant capability of LO-NE than LO alone. The study suggested that formulated nanoemulsion can be effectively used as a highly efficacious biologically active alternative nanoformulation against many transdermal disorders.

A review on anode materials for lithium/sodium-ion batteries

Since lithium-ion batteries(LIBs) have been substantially researched in recent years, they now possess exceptional energy and power densities, making them the most suited energy storage technology for use in developed and developing industries like stationary storage and electric cars, etc. Concerns about the cost and availability of lithium have prompted research into alternatives, such as sodium-ion batteries(SIBs), which use sodium instead of lithium as the charge carrier. This is especially relevant for stationary applications, where the size and weight of battery are less important. The working efficiency and capacity of these batteries are mainly dependent on the anode, cathode, and electrolyte. The anode,which is one of these components, is by far the most important part of the rechargeable battery.Because of its characteristics and its structure, the anode has a tremendous impact on the overall performance of the battery as a whole. Keeping the above in view, in this review we critically reviewed the different types of anodes and their performances studied to date in LIBs and SIBs. The review article is divided into three main sections, namely:(i) intercalation reaction-based anode materials;(ii) alloying reaction-based anode materials;and(iii) conversion reaction-based anode materials, which are further classified into a number of subsections based on the type of material used. In each main section, we have discussed the merits and challenges faced by their particular system. Afterward, a brief summary of the review has been discussed. Finally, the road ahead for better application of Li/Na-ion batteries is discussed, which seems to mainly depend on exploring the innovative materials as anode and on the inoperando characterization of the existing materials for making them more capable in terms of application in rechargeable batteries.

化学反应对粗糙边界和被动控制微极性纳米流体热稳定性的影响:神经网络

本文在无通量和粗糙边界的情况下演示了化学反应对微极性纳米流体中热对流初始状态的影响。本研究应用Saffman界面条件求解粗糙边界。考虑在许多工业应用中具有重要作用的微极性非牛顿纳米流体。对于线性稳定性,利用正态模态技术(NMT)将控制系统的偏微分方程(PDE)转化为特征值问题(EVP),并采用基于有限差分的三阶段LobattoⅢa方法进行数值求解。发现对流的主要模式是静止模式。增加纳米流体中热流通量与自旋霍尔效应的耦合系数(δ)、自旋霍尔效应与涡度的耦合系数(K)、粗糙度参数(λ_(1),λ_(2))、化学反应参数(Cr)、修正扩散比(NA)和微极性参数(A)的取值,可以降低对流,从而稳定系统。然后,在81个数据点的基础上,利用嵌入多人感知的人工神经网络(ANN)确定四个控制参数与Rayleigh临界数之间的关系。

Mathematical Insight into Moderate Inversion Gate Delay Variability for Ultradeep Submicron Digital Circuit Design

Voltage scaling has been extensively used in industry for decades to reduce power consumption.In recent years,exploring digital circuit operation in moderate inversion has created an interest among researchers due to its immense capability to provide a perfect tradeoff between high performance and low energy operation.But circuits operating in moderate inversion are susceptible to process variations and variability.To compute variability,statistical parameters such as the probability density function(PDF)and cumulative distribution function(CDF)are required.This paper presents an analytical model framework for delay calculations utilizing log skew normal distribution for ultradeep submicron technology nodes up to 22 nm.The CDF of the proposed model is utilized to calculate minimum and maximum delays with 3σ-accuracy providing better accuracy than the conventional methods.The obtained results are also compared with Monte Carlo simulations with errors lying within the acceptable range of 2%-4%.

Particle Swarm Optimization for Solving Sine-Gordan Equation

The term‘optimization’refers to the process of maximizing the beneficial attributes of a mathematical function or system while minimizing the unfavorable ones.The majority of real-world situations can be modelled as an optimization problem.The complex nature of models restricts traditional optimization techniques to obtain a global optimal solution and paves the path for global optimization methods.Particle Swarm Optimization is a potential global optimization technique that has been widely used to address problems in a variety of fields.The idea of this research is to use exponential basis functions and the particle swarm optimization technique to find a numerical solution for the Sine-Gordan equation,whose numerical solutions show the soliton form and has diverse applications.The implemented optimization technique is employed to determine the involved parameter in the basis functions,which was previously approximated as a random number in the work reported till now in the literature.The obtained results are comparable with the results obtained in the literature.The work is presented in the form of figures and tables and is found encouraging.

Application of Response Surface Methodology for Analysing and Optimizing the Finned Solar Air Heater

In this research paper,a solar air heater with triangular fins has been experimentally analysed and optimized.Initially,an experimental set-up of a solar air heater having triangular fins has been developed at the location of 28.10°N,78.23°E.The heat transfer rate through fins and fins efficiency has been determined by the Finite Difference Method model equations.The experimental data and modeled data of response parameters have been optimized in MINITAB-17 software by the Response Surface Methodology tool.For creating the response surface design,three input parameters have been selected namely solar intensity,Reynolds number,and fin base-to-height ratio.The range of solar intensity,Reynolds number,and fin base-to-height ratio is 600 to 1000W/m^(2),4000 to 6000,and 0.4 to 0.8 respectively.The response surface design has been analyzed by calculating the outlet temperature,friction factor,Nusselt number,fin efficiency,thermal performance factor,and exergy efficiency.The optimum settings of input parameters:solar intensity is 1000 W/m^(2);Reynolds number is 4969.7,and the fin base to height ratio is 0.6060,on which these response:namely outlet temperature of 92.531℃,friction factor of 0.2350,Nusselt number of 127.761,thermal efficiency of 50.836%,thermal performance factor of 1.4947,and exergy efficiency of 8.762%.

VDTA Based Electronically Tunable Voltage-Mode and Trans-Admittance Biquad Filter

In this paper, a biquad filter configuration based on two voltage differencing transconductance amplifiers (VDTAs) as newly active elements and only two capacitors as passive elements is proposed which can realize voltage-mode low pass (LP), band pass (BP), high pass (HP), band reject (BR) and all pass (AP) filtering responses using three voltage inputs. Simultaneously, the same configuration can also be used to obtain LP, BP and HP filtering responses in transadmittance-mode. The proposed biquad is capable of providing electronic control of quality factor independent of pole frequency through single transconductance parameter (biasing current). It also offers the advantage of low active and passive sensitivity. To support the theoretical analysis, the PSPICE simulation of the proposed circuit is done using 0.18 μm CMOS technology from TSMC.

Gompertz PSO variants for Knapsack and Multi-Knapsack Problems

Particle Swarm Optimization,a potential swarm intelligence heuristic,has been recognized as a global optimizer for solving various continuous as well as discrete optimization problems.Encourged by the performance of Gompertz PSO on a set of continuous problems,this works extends the application of Gompertz PSO for solving binary optimization problems.Moreover,a new chaotic variant of Gompertz PSO namely Chaotic Gompertz Binary Particle Swarm Optimization(CGBPSO)has also been proposed.The new variant is further analysed for solving binary optimization problems.The new chaotic variant embeds the notion of chaos into GBPSO in later stages of searching process to avoid stagnation phenomena.The efficiency of both the Binary PSO variants has been tested on different sets of Knapsack Problems(KPs):0-1 Knapsack Problem(0-1 KP)and Multidimensional Knapsack Problems(MKP).The concluding remarks have made on the basis of detailed analysis of results,which comprises the comparison of results for Knapsack and Multidimensional Knapsack problems obtained using BPSO,GBPSO and CGBPSO.

Analytical Modeling for Translating Statistical Changes to Circuit Variability by Ultra⁃Deep Submicron Digital Circuit Design

This paper presents a physics⁃based compact gate delay model that includes all short⁃channel phenomena prevalent at the ultra⁃deep submicron technology node of 32 nm.To simplify calculations,the proposed model is connected to a compactα⁃power law⁃based(Sakurai⁃Newton)model.The model has been tested on a wide range of supply voltages.The model accurately predicts nominal delays and the delays under process variations.It has been shown that at lower technology nodes,the delay is more sensitive to threshold voltage variations,specifically at the sub⁃threshold operating region as compared with effective channel length variations above the threshold region.

Wavelet Optimized Adaptive Mesh for MHD Flow Problems

There are many problems in science and engineering where the solution shows a boundary layer character. Near the boundary the gradient is large in contrast with the smooth behaviour in the central core. A uniform grid is, therefore, not suitable for a numerical solution. MHD flow problems belong to this category where a velocity and induced magnetic field profiles get flattened in a transverse flow. In the present paper an optimized grid has been generated using interpo-lating wavelets. The results are compared with those obtained using uniform grid, the finite element method and also from the analytical solution.