Electronic properties of 2D materials and their junctions

With an extensive range of distinctive features at nano meter-scale thicknesses,two-dimensional(2D)materials drawn the attention of the scientific community.Despite tremendous advancements in exploratory research on 2D materials,knowledge of 2D electrical transport and carrier dynamics still in its infancy.Thus,here we highlighted the electrical characteristics of 2D materials with electronic band structure,electronic transport,dielectric constant,carriers mobility.The atomic thinness of 2D materials makes substantially scaled field-effect transistors(FETs)with reduced short-channel effects conceivable,even though strong carrier mobility required for high performance,low-voltage device operations.We also discussed here about factors affecting 2D materials which easily enhanced the activity of those materials for various applications.Presently,Those 2D materials used in state-of-the-art electrical and optoelectronic devices because of the extensive nature of their electronic band structure.2D materials offer unprecedented freedom for the design of novel p-n junction device topologies in contrast to conventional bulk semiconductors.We also,describe the numerous 2D p-n junctions,such as homo junction and hetero junction including mixed dimensional junctions.Finally,we talked about the problems and potential for the future.

Protected simultaneous quantum remote state preparation scheme by weak and reversal measurements in noisy environments

We discuss a quantum remote state preparation protocol by which two parties, Alice and Candy, prepare a single-qubit and a two-qubit state, respectively, at the site of the receiver Bob. The single-qubit state is known to Alice while the two-qubit state which is a non-maximally entangled Bell state is known to Candy. The three parties are connected through a single entangled state which acts as a quantum channel. We first describe the protocol in the ideal case when the entangled channel under use is in a pure state. After that, we consider the effect of amplitude damping(AD) noise on the quantum channel and describe the protocol executed through the noisy channel. The decrement of the fidelity is shown to occur with the increment in the noise parameter. This is shown by numerical computation in specific examples of the states to be created. Finally, we show that it is possible to maintain the label of fidelity to some extent and hence to decrease the effect of noise by the application of weak and reversal measurements. We also present a scheme for the generation of the five-qubit entangled resource which we require as a quantum channel. The generation scheme is run on the IBMQ platform.

Motor Imagery and Error Related Potential Induced Position Control of a Robotic Arm

The paper introduces an electroencephalography(EEG) driven online position control scheme for a robot arm by utilizing motor imagery to activate and error related potential(ErrP) to stop the movement of the individual links, following a fixed(pre-defined) order of link selection. The right(left)hand motor imagery is used to turn a link clockwise(counterclockwise) and foot imagery is used to move a link forward. The occurrence of ErrP here indicates that the link under motion crosses the visually fixed target position, which usually is a plane/line/point depending on the desired transition of the link across 3D planes/around 2D lines/along 2D lines respectively. The imagined task about individual link's movement is decoded by a classifier into three possible class labels: clockwise, counterclockwise and no movement in case of rotational movements and forward, backward and no movement in case of translational movements. One additional classifier is required to detect the occurrence of the ErrP signal, elicited due to visually inspired positional link error with reference to a geometrically selected target position. Wavelet coefficients and adaptive autoregressive parameters are extracted as features for motor imagery and ErrP signals respectively. Support vector machine classifiers are used to decode motor imagination and ErrP with high classification accuracy above 80%. The average time taken by the proposed scheme to decode and execute control intentions for the complete movement of three links of a robot is approximately33 seconds. The steady-state error and peak overshoot of the proposed controller are experimentally obtained as 1.1% and4.6% respectively.

Scope for improved properties of dissimilar joints of ferrous and non-ferrous metals

Dissimilar joints(DSJs)of ferrous and non-ferrous metals have huge technological importance in the frontiers of newdesigns in new machineries and improved design of conventional systems.This investigation was undertaken to improve mechanicalproperties of joints of two dissimilar metals:one is Ti-based and the other is Fe-based.DSJs were processed using bonding pressurefrom1to9MPa in step of2MPa at750°C for60min.Properties of the DSJs of these two metals using different mechanisms andmethods were compared with the present research for verification.Experimental results from the diffusion bonding mechanism forjoining the dissimilar metals validated the improvement in properties.Superior mechanical properties of dissimilar-metals joints wereachieved mainly due to the third non-ferrous metallic foil,Ni of^200-?m thickness,which avoided the formation of brittleFe-Ti-based intermetallics in the diffusion zone.DSJs processed are able to achieve maximum strength of^560MPa along withsubstantial ductility of^11.9%,which is the best ever reported in the literatures so far.Work hardening effect was detected in theDSJs when the bonding was processed at5MPa and above.Bulging ratio of the non-ferrous metal(Ti-based)was much higher thanthat of the ferrous metal(SS)of the DSJs processed.SEM analysis was carried out to know the details of reaction zone,while XRDwas carried out to support the SEM results.Reasons for change in mechanical,physical,and fracture properties of the DSJs with theprocess parameter variations were clarified.

Influence of Hall current and Joule heating on entropy generation during electrokinetically induced thermoradiative transport of nanofluids in a porous microchannel

A comprehensive theoretical study of entropy generation during electroki-netically driven transport of a nanofluid is of prime concern in the paper. The flow is considered to take place on a wavy channel under the action of an external transverse magnetic field and an external pressure gradient. Navier slips at the walls of the channel and thermal radiation have been taken into account in the study. The theoretical study has been carried out by developing a mathematical model by taking into account the effects of Joule heating, viscous dissipation, and the transverse magnetic field on heat transfer during the electrokinetic transport of the fluid. The derived analytical expres-sions have been computed numerically by considering the nanofluid as a mixture of blood and ferromagnetic nanoparticles. Variations in velocity, streaming potential, temperature distribution, Nusselt number, and Bejan number associated with the electrokinetic flow in capillaries have been investigated by the parametric variation method. The results have been presented graphically. The present investigation reveals that streaming potential decreases due to the Hall effect, while for the cooling capacity of the microsystem, we find an opposite behavior due to the Hall effect. The study further reveals that the fluidic temperature is reduced due to increase in the Hall current, and thereby thermal irreversibility of the system is reduced significantly. The results presented here can be considered as the approximate estimates of blood flow dynamics in capillaries during chemotherapy in cancer treatment.

Seismic fragility analysis of bridges by relevance vector machine based demand prediction model

A relevance vector machine(RVM)based demand prediction model is explored for efficient seismic fragility analysis(SFA)of a bridge structure.The proposed RVM model integrates both record-to-record variations of ground motions and uncertainties of parameters characterizing the bridge model.For efficient fragility computation,ground motion intensity is included as an added dimension to the demand prediction model.To incorporate different sources of uncertainty,random realizations of different structural parameters are generated using Latin hypercube sampling technique.Mean fragility,along with its dispersions,is estimated based on the log-normal fragility model for different critical components of a bridge.The effectiveness of the proposed RVM model-based SFA of a bridge structure is elucidated numerically by comparing it with fragility results obtained by the commonly used SFA approaches,while considering the most accurate direct Monte Carlo simulation-based fragility estimates as the benchmark.The proposed RVM model provides a more accurate estimate of fragility than conventional approaches,with significantly less computational effort.In addition,the proposed model provides a measure of uncertainty in fragility estimates by constructing confidence intervals for the fragility curves.

Influence of self-heating on the millimeter-wave and terahertz performance of MBE grown silicon IMPATT diodes

The influence of self-heating on the millimeter-wave(mm-wave)and terahertz(THz)performance of double-drift region(DDR)impact avalanche transit time(IMPATT)sources based on silicon(Si)has been investigated in this paper.The dependences of static and large-signal parameters on junction temperature are estimated using a non-sinusoidal voltage excited(NSVE)large-signal simulation technique developed by the authors,which is based on the quantum-corrected drift-diffusion(QCDD)model.Linear variations of static parameters and non-linear variations of large-signal parameters with temperature have been observed.Analytical expressions representing the temperature dependences of static and large-signal parameters of the diodes are developed using linear and 2nd degree polynomial curve fitting techniques,which will be highly useful for optimizing the thermal design of the oscillators.Finally,the simulated results are found to be in close agreement with the experimentally measured data.

Pressure Characteristics Study for the Configuration of Sudden Expansion with Central Restriction and Suction

In this paper, an extensive numerical study on pressure characteristics in the configuration of sudden expansion with central restriction and suction has been carried out. During study, Reynolds numbers (Re) are considered from 50 to 200, suction (S) from 2% to 10% of inlet mass flow, percentage of central restriction (CR) from 0% to 40% and aspect ratio (AR) from 2 to 6. The effects of each variable on average static pressure distribution and average stagnation pressure distribution have been studied in detail. The results have been compared with the configuration of plain sudden expansion, and sudden expansion with central restriction only. From the study, it is noted that maximum magnitude of average static pressure rise from throat increases with the increase in percentage of suction, flow Reynolds number and percentage of central restriction. This magnitude is higher at lower aspect ratio. Also, it is observed that maximum magnitude of average static pressure rise from throat is always more in case of suction configuration compared to the case of configuration of without suction. Average stagnation pressure drop at any section increases with the increase in percentage of suction and percentage of central restriction, but it decreases with the increase in Reynolds number. It is noted that higher pressure drop at any section occurs at higher aspect ratio. This pressure drop at a section is more in case of suction configuration compared to the case of without suction.

Workout Action Recognition in Video Streams Using an Attention Driven Residual DC-GRU Network

Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions in videostreams holds significant importance in computer vision research, as it aims to enhance exercise adherence, enableinstant recognition, advance fitness tracking technologies, and optimize fitness routines. However, existing actiondatasets often lack diversity and specificity for workout actions, hindering the development of accurate recognitionmodels. To address this gap, the Workout Action Video dataset (WAVd) has been introduced as a significantcontribution. WAVd comprises a diverse collection of labeled workout action videos, meticulously curated toencompass various exercises performed by numerous individuals in different settings. This research proposes aninnovative framework based on the Attention driven Residual Deep Convolutional-Gated Recurrent Unit (ResDCGRU)network for workout action recognition in video streams. Unlike image-based action recognition, videoscontain spatio-temporal information, making the task more complex and challenging. While substantial progresshas been made in this area, challenges persist in detecting subtle and complex actions, handling occlusions,and managing the computational demands of deep learning approaches. The proposed ResDC-GRU Attentionmodel demonstrated exceptional classification performance with 95.81% accuracy in classifying workout actionvideos and also outperformed various state-of-the-art models. The method also yielded 81.6%, 97.2%, 95.6%, and93.2% accuracy on established benchmark datasets, namely HMDB51, Youtube Actions, UCF50, and UCF101,respectively, showcasing its superiority and robustness in action recognition. The findings suggest practicalimplications in real-world scenarios where precise video action recognition is paramount, addressing the persistingchallenges in the field. TheWAVd dataset serves as a catalyst for the development ofmore robust and effective fitnesstracking systems and ultimately promotes healthier lifestyles through improved exercise monitoring and analysis.

Hydrodynamic dispersion of reactive solute in a Hagen–Poiseuille flow of a layered liquid

An analysis of the solute dispersion in the liquid flowing through a pipe by means of Aris–Barton's ‘method of moments', under the joint effect of some finite yield stress and irreversible absorption into the wall is presented in this paper. The liquid is considered as a three-layer liquid where the center region is Casson liquid surrounded by Newtonian liquid layer. A significant change from previous modelling exercises in the study of hydrodynamic dispersion, different molecular diffusivity has been considered for the different region yet to be constant. For all time period, finite difference implicit scheme has been adopted to solve the integral moment equation arising from the unsteady convective diffusion equation. The purpose of the study is to find the dependency of solute transport coefficients on absorption parameter, yield stress, viscosity ratio, peripheral layer variation and in addition with various diffusivity coefficients in different liquid layers. This kind of study may be useful for understanding the dispersion process in the blood flow analysis.

A Cyclic Probabilistic C-Contraction Results using Hadzic and Lukasiewicz T-Norms in Menger Spaces

In this paper, we introduce generalized cyclic C-contractions through p number of subsets of a probabilistic metric space and establish two fixed point results for such contractions. In our first theorem we use the Hadzic type t-norm. In our next theorem we use Lukasiewicz t-norm. Our results generalize the results of Choudhury and Bhandari [11]. A control function [3] has been utilized in our second theorem. The results are illustrated with some examples.

Identification of Preferable Distributed Generators Locations for Congestion Relief in Multi-Bus Power Network

Installation of Distributed Generator (DG) is a well accepted method to improve power system operation from the point of reducing congestion and improving voltage profiles. For best results, Distributed Generators should be placed at strategic locations to exploit maximum benefits out of them. The (N-1) contingency criterion has been taken into account in this work. Most congested lines of the grids are ranked by congestion Index and considered to study the impact of DG penetration on congestion. The present paper proposes contribution factors of Distributed Generators for the placement of DG to keep the line flow within the capacity of each transmission line of the network. The results obtained from IEEE 30-bus test system indicate that the proposed methods are capable of identifying desirable DG location and its maximum allowable size. The influence of DG on bus voltage profile has also been demonstrated in this paper.

Cylindrical neutrosophic single-valued number and its application in networking problem, multi-criterion group decision-making problem and graph theory

In this study,the authors envisage the neutrosophic number from various distinct rational perspectives and viewpoints to give it a look of a conundrum.They focused and analysed neutrosophic fuzzy numbers when indeterminacy and falsity functions are dependent on each other,which serves an indispensable role for the uncertainty concept.Additionally,the idea of cylindrical neutrosophic single-valued number is focused here,when the indeterminacy and falsity functions are dependent to each other using an influx of different logical and innovative graphical representation.They also developed the score and accuracy function for this particular cylindrical neutrosophic single-valued number and analysed some real-life problems like networking critical path model problem and minimal spanning tree problem of operation research field when the numbers are in cylindrical neutrosophic ambiance.They also introduced a multi-criterion group decision-making problem in this cylindrical neutrosophic domain.This noble thought will help us to solve a plethora of daily life problems in the neutrosophic arena.

MCDA techniques used in optimization of weights and ratings of DRASTIC model for groundwater vulnerability assessment

DRASTIC is a very simple and common model used for the assessment of groundwater to contamination.This model is widely used across the world in various hydrogeological environments for groundwater vulnerability assessment.The Ohio Water Well Association(OWWA)developed DRASTIC model in 1987.Over the years,several modifications have been made in this model as per the need of the regional assessment of groundwater to contamination.This model has fixed weights for its parameters and fixed ratings for the sub-parameters under the main parameters.The weights and ratings of DRASTIC parameters were fixed on the basis of Delphi network technique,which is the best technique for the consensus-building of experts,but it lacks scientific explanations.Over the years,several optimization techniques have been used to optimize these weights and ratings.This work intends to present a critical analysis of decision optimization techniques used to get the optimum values of weights and ratings.The inherent pros and cons and the optimization challenges associated with these techniques have also been discussed.The finding of this study is that the application of MCDA optimization techniques used to optimize the weights and ratings of DRASTIC model to assess the vulnerability of groundwater depend on the availability of hydrogeological data,the pilot study area and the level of required accuracy for earmarking the vulnerable regions.It is recommended that one must choose the appropriate MCDA technique for the particular region because unnecessary complex structure for optimization process takes more time,efforts,resources,and implementation costs.

Bioprinting of radiopaque constructs for tissue engineering and understanding degradation behavior by use of Micro-CT

Bioprinting has emerged as a potential technique to fabricate tissue engineering constructs and in vitro models directly using living cells as a raw material for fabrication,conforming to the heterogeneity and architectural complexity of the tissues.In several of tissue engineering and in vitro disease modelling or surgical planning applications,it is desirable to have radiopaque constructs for monitoring and evaluation.In the present work,enhanced radiopaque constructs are generated by substituting Calcium ions with Barium ions for crosslinking of alginate hydrogels.The constructs are characterized for their structural integrity and followed by cell culture studies to evaluate their biocompatibility.This was followed by the radiopacity evaluation.The radiological images obtained by micro-CT technique was further applied to investigate the degradation behavior of the scaffolds.In conclusion,it is observed that barium crosslinking can provide a convenient means to obtain radiopaque constructs with potential for multi-faceted applications.

Cosmological test of dark energy parametrizations within the framework of Horava-Lifshitz gravity via baryon acoustic oscillation

We conduct an investigation to explore late-time cosmic acceleration through various dark energy parametrizations(Wettrich,Efstathiou,and Ma-Zhang)within the Horava-Lifshitz gravity framework.As an alternative to general relativity,this theory introduces anisotropic scaling at ultraviolet scales.Our primary objective is to constrain the key cosmic parameters and baryon acoustic oscillation(BAO)scale,specifically the sound horizon(rd),by utilizing 24 uncorrelated measurements of BAOs derived from recent galaxy surveys spanning a redshift range from z=0.106 to z=2.33.Additionally,we integrate the most recent Hubble constant measurement by Riess in 2022(denoted as R22)as an extra prior.For the parametrizations of Wettrich,Efstathiou,and Ma-Zhang,our analysis of BAO data yields sound horizon results of r_(d)=148.1560±2.7688 Mpc,r_(d)=148.6168±10.2469 Mpc,and r_(d)=147.9737±10.6096 Mpc,respectively.Incorporating the R22 prior into the BAO dataset results in r_(d)=139.5806±3.8522 Mpc,r_(d)=139.728025±2.7858 Mpc,and r_(d)=139.6001±2.7441 Mpc.These outcomes highlight a distinct inconsistency between early and late observational measurements,analogous to the H_(0) tension.A notable observation is that,when we do not include the R22 prior,the outcomes for rd tend to be in agreement with Planck and SDSS results.Following this,we conducted a cosmography test and comparative study of each parametrization within the Lambda Cold Dark Matter paradigm.Our diagnostic analyses demonstrate that all models fit seamlessly within the phantom region.All dark energy parametrizations predict an equation of state parameter close ω=-1,indicating a behavior similar to that of a cosmological constant.The statistical analysis indicates that neither of the two models can be ruled out based on the latest observational measurements.

Assessment of the environmental kuznets curve within EU-27:Steps toward environmental sustainability(1990-2019)

Reducing environmental pollution is a critical goal in global environmental economics and economic development.The European Union(EU)faces environmental challenges due to its development activities.Here we present a comprehensive approach to assess the impact of carbon dioxide(CO_(2))emissions,energy consumption(EC),population structure(POP),economy(GDP),and policies on the environment within the EU using the environmental Kuznets curve(EKC).Our research reveals that between 1990 and 2019,the EU-27 experienced an increase of t1.18 million tonnes of oil equivalent(Mtoe)per year in energy consumption(p<0.05),while CO_(2)emissions decreased by 24.25 million tonnes(Mt)per year(p<0.05).The highest reduction in CO_(2)emissions occurred in Germany(7.52 Mt CO_(2)annually),and the lowest in Latvia(0.087 Mt CO_(2)annually).The empirical EKC analysis shows an inverted-U shaped relationship between GDP and CO_(2)emissions in the EU-27.Specifically,a 1%increase in GDP results in a 0.705%increase in carbon emission,while a 1%increase in GDP2 leads to a 0.062%reduction in environmental pollution in the long run(p<0.01).These findings indicate that economic development within the EU has reached a stage where economic growth positively impacts the environment.Overall,this study provides insights into the effectiveness of environmental policies in mitigating degradation and promoting green growth in the EU 27 countries.

Analysis of a predator-prey model with herd behavior and disease in prey incorporating prey refuge

In this work,we have introduced an eco-epidemiological model of an infected predator prey system.Incorporation of prey refuge gives that a fraction of the infected prey is available to the predator for consumption.Moreover,to make the model more realistic to the environment,we have introduced strong Allee effect in the susceptible population.Boundedness and positivity of the solution have been established.Local stability conditions of the equilibrium points have been found with the help of Routh-Hurwitz criterion and it has been observed that if a prey population is infected with a lethal disease,then both the prey(susceptible and infected)and predator cannot survive simultaneously in the system for any parametric values.The disease transmission rate and the attack rate on the susceptible have an important role to control the system dynamics.For different values of these two key parameters,we have got only healthy or disease-free or predation-free or a fluctuating disease-free or even a fluctuating predator-free system with some certain parametric conditions.

Heat Transfer and Thermal Characteristics Effects on Moving Plate Impinging from Cu-Water Nanofluid Jet

The present article is focused on modelling of flow and heat transfer behaviour of Cu-water nanofluid in a confined slot jet impingement on hot moving plate.Different parameters such as various moving plate velocities,nanoparticles at various concentrations,variation in turbulent Reynolds number and jet nozzle to plate distance have been considered to study the flow field and convective heat transfer performance of the system.Results of distribution of local and average Nusselt number and skin friction coefficients at the plate surface are shown to elucidate the heat transfer and fluid flow process.Qualitative analysis of both stream function and isotherm contours are carried out to perceive the flow pattern and heat transfer mechanism due to moving plate.The results revealed that average Nusselt number significantly rises with plate velocity in addition with jet inlet Reynolds number.Correlations of the average Nusselt numbers are presented.

Kernel fuzzy c-means clustering on energy detection based cooperative spectrum sensing

Cooperation in spectral sensing （SS） offers a fast and reliable detection of primary user （PU） transmission over a frequency spectrum at the expense of increased energy consumption. Since the fusion center （FC） has to handle a large set of data, a duster based approach, specifically fuzzy c-means clustering （FCM）, has been extensively used in energy detection based cooperative spectrum sensing （CSS）. However, the performance of FCM degrades at low signal-to-noise ratios （SNR） and in the presence of multiple PUs as energy data patterns at the FC are often found to be non-spherical i.e. overlapping. To address the problem, this work explores the scope of kernel fuzzy c-means （KFCM） on energy detection based CSS through the projection of non-linear input data to a high dimensional feature space. Extensive simulation results are shown to highlight the improved detection of multiple PUs at low SNR with low energy consumption. An improvement in the detection probability by ～6.78% and ～6.96% at -15 dBW and -20 dBW, respectively, is achieved over the existing FCM method.