Bilayer Graphene Conductance Analysis based on FET Channel

Graphene is considered as a famous nanomaterial because of some parameters such as its large surface–to–volume ratio, high conductivity, high mobility, and strong mechanical and elasticity properties. Therefore, in this work the conductance of two dimensional bilayer graphene (BG) is developed using the Fermi Dirac distribution function. For bilayer graphene two, various stacking structures (AA and AB) have been reported, which have armchair edge. Quantum gradient emerged between the channel and the gate and carrier movement of bilayer graphene is considered as FET channel, which is an important property of FET. Besides, band gap energy and resistance of BG have been modelled in this study. The impact of temperature on the resistance is extensively studied. It is demonstrated that the resistance of BG is the function of temperature and the conductance is increased at higher values of temperature

Synchronization in networked systems with large parameter heterogeneity

Systems that synchronize in nature are intrinsically different from one another, with possibly large differences from system to system. While a vast part of the literature has investigated the emergence of network synchronization for the case of small parametric mismatches, we consider the general case that parameter mismatches may be large. We present a unified stability analysis that predicts why the range of stability of the synchronous solution either increases or decreases with parameter heterogeneity for a given network. We introduce a parametric approach, based on the definition of a curvature contribution function, which allows us to estimate the effect of mismatches on the stability of the synchronous solution in terms of contributions of pairs of eigenvalues of the Laplacian. For cases in which synchronization occurs in a bounded interval of a parameter, we study the effects of parameter heterogeneity on both transitions (asynchronous to synchronous and synchronous to asynchronous.)Comment: Accepted for publication in Communications Physic

Improving the efficiency of photovoltaic cells embedded in floating buoys

Solar cells are used to power floating buoys, which is one of their applications. Floating buoys are devices that are placed on the sea and ocean surfaces to provide various information to the floats. Because these cells are subjected to varying environmental conditions, modeling and simulating photovoltaic cells enables us to install cells with higher efficiency and performance in them. The parameters of the single diode model are examined in this article so that the I-V, P-V diagrams, and characteristics of the cadmium telluride (CdTe) photovoltaic cell designed with three layers (CdTe, CdS, and SnOx) can be extracted using A solar cell capacitance simulator (SCAPS) software, and we obtain the parameters of the single diode model using the ant colony optimization (ACO) algorithm. In this paper, the objective function is root mean square error (RMSE), and the best value obtained after 30 runs is 5.2217×10-5 in 2.46 seconds per iteration, indicating a good agreement between the simulated model and the real model and outperforms many other algorithms that have been developed thus far. The above optimization with 200 iterations, a population of 30, and 84 points was completed on a server with 32 gigabytes of random-access memory (RAM) and 30 processing cores

Spiking ink drop spread clustering algorithm and its memristor crossbar conceptual hardware design

In this study, a novel neuro-fuzzy clustering algorithm is proposed based on spiking neural network and ink drop spread (IDS) concepts. The proposed structure is a one-layer artificial neural network with leaky integrate and fire (LIF) neurons. The structure implements the IDS algorithm as a fuzzy concept. Each training data will result in firing the corresponding input neuron and its neighboring neurons. A synchronous time coding algorithm is used to manage input and output neurons firing time. For an input data, one or several output neurons of the network will fire; confidence degree of the network to outputs is defined as the relative delay of the firing times with respect to the synchronous pulse. A memristor crossbar-based hardware is utilized for hardware implementation of the proposed algorithm. The simulation result corroborates that the proposed algorithm can be used as a neuro-fuzzy clustering and vector quantization algorithm

Utjecaj sadržaja nanočestica silicijeva dioksida (SiO2) na mehanička svojstva cementne ploče iverice proizvedene od lignoceluloznih materijala

The influence of Nano-SiO2 (NS) content and lignocellulosic material addition on hydration behaviour of cement paste was studied through measurement of hydration temperature, initial and final setting time of cement paste and compressive strength of hardened cement paste. Besides, the amount of NS, particle size of reed and bagasse as lignocellulosic materials and bagasse to reed particles weight ratio were selected as manufacturing variables for cement-bonded particleboard (CBPB) each at five levels. The relationships between independent parameters and output variables (modulus of rupture (MOR), modulus of elasticity (MOE) and internal bonding (IB)) were modeled using response surface methodology (RSM) based on mathematical model equations (second-order multiple linear regression model) by computer simulation programming. The results indicated that cement pastes containing 3 wt.% Nano-SiO2 content mixed with milled reed or bagasse particles enhanced maximum hydration temperature; however, the time of reaching the main rate peak shortened. Besides, the increase of SiO2 replacement shortened the setting time. On the other hand, using reed particles, initial and final setting times of cement prolonged, while bagasse particles shortened initial and final setting times. Analysis of variance (ANOVA) was performed to determine the adequacy of the mathematical model and its respective variables. The interaction effect curves of the independent variables obtained from simulations showed a good agreement between the measured MOR, MOE and IB of CBPB and predicted values obtained by the developed models, and hence, the proposed concept was verified.Utjecaj sadržaja nanočestica silicijeva dioksida (NS) i dodatka lignoceluloznih tvari ispitivan je na temelju hidratacijskog ponašanja cementne paste uz pomoć mjerenja temperature hidratacije, početnoga i završnog vremena vezanja cementne paste te tlačne čvrstoće očvrsnute cementne paste. Od varijabli koje utječu na svojstva cementnih ploča iverica (CBPB) ispitivana je količina NS-a, veličina čestica lignoceluloznih materijala (trske i otpadaka u preradi šećerne trske) te težinski omjer različitih lignoceluloznih materijala. Za svaku varijablu odabrano je pet vrijednosti. Odnos između nezavisnih parametara i izlaznih varijabli – modula loma (MOR), modula elastičnosti (MOE) i čvrstoće raslojavanja (IB) – modeliran je s pomoću metodologije odziva površine (RSM-a) i računalnim simulacijskim programiranjem utemeljen na jednadžbama matematičkih modela (model višestruke linearne regresije drugoga reda). Rezultati su pokazali da cementne paste koje (težinski) sadržavaju 3 % čestica NS-a pomiješanih s mljevenim česticama trske ili otpadaka u preradi šećerne trske pokazuju povećanje maksimalne temperature hidratacije, no skraćeno je vrijeme postizanja maksimuma. Osim toga, s povećanjem udjela NS-a skraćeno je vrijeme vezanja cementne paste. Nasuprot tome, primjenom čestica trske produljeno je početno i završno vrijeme vezanja cementa, a primjenom čestica od otpadaka u preradi šećerne trske skraćuje se početno i završno vrijeme vezanja cementa. Kako bi se utvrdila adekvatnost matematičkog modela i njegovih odgovarajućih varijabli, provedena je analiza varijance (ANOVA). Krivulje interakcije nezavisnih varijabli dobivenih iz simulacija pokazale su dobru podudarnost izmjerenih vrijednosti MOR-a, MOE-a i IB-a cementnih ploča iverica s pretpostavljenim vrijednostima dobivenim razvijenim modelima, te je stoga predloženi koncept potvrđen

The Effect Of Physical Education Health-Related Program For Employees (PEHPE) On Exercise Behaviour And Quality Of Work Life Among Employees In Mobarakeh Steel Company, Iran

This study aims at examining the effects of the Physical Education Health-Related Programme for Employees (PEHPE) on exercise behaviour and quality of work life among employees in Mobarakeh Steel Company, Iran. The survey method was used at the first stage while quasi experimental research was used at the second stage of this study. The questionnaire of Sports Needs Assessment in terms of Interest (SNAI) with the high reliability coefficient of .977 alpha was used for data collection among the randomly selected sample of 376 employees from the population of 15000 male employees in Mobarakeh Steel Company

Single-Integrator Consensus Dynamics over Minimally Reactive Networks

The problem of achieving consensus in a network of connected systems arises in many science and engineering applications. In contrast to previous works, we focus on the system reactivity, i.e., the initial amplification of the norm of the system states. We identify a class of networks that we call minimally reactive, which are such that the indegree and the outdegree of each node of the network are the same. We propose several optimization procedures in which minimum perturbations (links or link weights) are imposed on a given network topology to make it minimally reactive. A new concept of structural reactivity is introduced which measures how much a given network is far from becoming minimally reactive by link perturbations. The structural reactivity of directed random graphs is studied

Synchronizing Chaos using Reservoir Computing

We attempt to achieve isochronal synchronization between a drive system unidirectionally coupled to a response system, under the assumption that limited knowledge on the states of the drive is available at the response. Machine learning techniques have been previously implemented to estimate the states of a dynamical system from limited measurements. We consider situations in which knowledge of the non-measurable states of the drive system is needed in order for the response system to synchronize with the drive. We use a reservoir computer to estimate the non-measurable states of the drive system from its measured states and then employ these measured states to synchronize the response system with the drive

Characterization of Pectobacterium carotovorum subsp. carotovorum as a new disease on lettuce in Malaysia.

Malaysia produces many varieties of vegetables. The Cameron Highland in the state of Pahang is the main area for lettuce (Lactuca sativa var. romana) production. A survey recently identified Pectobacterium spp. was responsible for more than 15 % damage to lettuce both in the field (including greenhouses) and storage. Isolates of Pectobacterium carotovorum were collected from different greenhouses and fields and analysed in the laboratory during 2010. Nine isolates were purified and charcterised by morphological, biochemical and molecular methods. Pathogenicity studies on lettuce using 4 strains showed there was a high susceptibility to the P. carotovorum. PCR amplification with Y1 and Y2 primers (specific for P. carotovorum subspecies) produced the expected band of 434 bp. PCR amplification of the intergenic transcribed spacer region (ITS) using G1 and L1 primers also resulted in the expected two bands (535 and 580 bp). Based on these biochemical and physiological characteristics, PCR based pel gene, characterisation of the ITS region and digestion of the ITS-PCR products with RsaI restriction enzyme, all isolates were identified as P. carotovorum subsp. carotovorum. This is the first record of the bacterial pathogen causing disease on lettuce in Malaysia