Surface Tension Profiles under Various Microwave Radiation Modes

Surface tension of fluids is crucial for multiphase systems and is often controlled during industrial processes by introducing surfactants. In this study, effect of various microwave radiation modes on surface tension of water was investigated as an alternative physical method to manipulate the surface tension without using chemicals. It is found that surface tension decreased quickly while temperature increased during microwave. Once the radiation was turned off, the temperature returned rapidly as expected. However, surface tension did not recover so much. The minimum surface tension after microwave radiation depended on the power. Moreover, a second radiation can have additional reduction on surface tension.     

Clustering and selection of multiple criteria alternatives using unsupervised and supervised neural networks

There are decision-making problems that involve grouping and selecting a set of alternatives. Traditional decision-making approaches treat different sets of alternatives with the same method of analysis and selection. In this paper, we propose clustering alternatives into different sets so that different methods of analysis, selection, and implementation for each set can be applied. We consider multiple criteria decision-making alternatives where the decision-maker is faced with several conflicting and non-commensurate objectives (or criteria). For example, consider buying a set of computers for a company that vary in terms of their functions, prices, and computing powers. In this paper, we develop theories and procedures for clustering and selecting discrete multiple criteria alternatives. The sets of alternatives clustered are mutually exclusive and are based on (1) similar features among alternatives, and (2) preferential structure of the decision-maker. The decision-making process can be broken down into three steps: (1) generating alternatives; (2) grouping or clustering alternatives based on similarity of their features; and (3) choosing one or more alternatives from each cluster of alternatives. We utilize unsupervised learning clustering artificial neural networks (ANN) with variable weights for clustering of alternatives, and we use feedforward ANN for the selection of the best alternatives for each cluster of alternatives. The decision-maker is interactively involved by comparing and contrasting alternatives within each group so that the best alternative can be selected from each group. For the learning mechanism of ANN, we proposed using a generalized Euclidean distance where by changing its coefficients new formation of clusters of alternatives can be achieved. The algorithm is interactive and the results are independent of the initial set-up information. Some examples and computational results are presented.     

Viscous Potential Flow Analysis of Nonlinear Rayleigh–Taylor Instability with Heat and Mass Transfer

The nonlinear analysis of Rayleigh?CTaylor instability of two viscous fluids is studied when there is heat and mass transfer across the interface, using viscous potential flow theory. The fluids are considered to be viscous and incompressible with different kinematic viscosities. The analysis is based on the method of multiple scale perturbation and the nonlinear stability is governed by first-order nonlinear partial differential equation. The stability conditions are obtained and stability is discussed theoretically as well as numerically. Regions of stability and instability have been shown graphically indicating the effect of various parameters. It has been observed that the heat and mass transfer has stabilizing effect on the stability of the system in the nonlinear analysis.     

Broadening of Photonic Band Gap in a One—Dimensional Superconductor Star Waveguide Structure

The present paper describes the theoretical investigation of enlarged reflection bands (photonic band gaps) in a 1D star waveguide (SWG) structure consists of superconductor and dielectric as its constituent materials. For the present study, we take the different combinations of superconductor and dielectric materials as a backbone and side branches of the SWG structure. In order to obtain the dispersion relation, Interface Response Theory (IRT) has been employed. Photonic band gaps of SWG structure having superconductor?Csuperconductor, superconductor?Cdielectric, and dielectric?Csuperconductor materials are compared with the band gaps of the conventional photonic crystal (PC) structure having superconductor?Csuperconductor and dielectric?Csuperconductor materials. Analysis of the dispersion characteristics shows that there exists no band gaps for conventional PC when both layers are made of the same superconducting materials (as the usual case) while the SWG structure shows forbidden bands of finite width even the backbone and side branches are made of same materials. Also, the SWG structure having superconductor?Cdielectric shows the wider reflection bands in comparison with the structure having dielectric?Csuperconductor as its constituent materials, while for the conventional PC structure it is same in both the cases. Further, the effect of temperature and the effect of variation of number of grafted branches on the photonic bands of SWG structure have been studied.     

Magnetic-nanoparticle-doped carbogenic nanocomposite: an effective magnetic resonance/fluorescence multimodal imaging probe

A novel and facile approach is developed to synthesize a magnetic nanoparticle (iron oxide)-doped carbogenic nanocomposite (IO-CNC) for magnetic resonance (MR)/fluorescence imaging applications. IO-CNC is synthesized by thermal decomposition of organic precursors in the presence of Fe(3) O(4) nanoparticles with an average size of 6 nm. IO-CNC shows wavelength-tunable fluorescence properties with high quantum yield. Magnetic studies confirm the superparamagnetic nature of IO-CNC at room temperature. IO-CNC shows MR contrast behavior by affecting the proton relaxation phenomena. The measured longitudinal (r(1) ) and transverse (r(2) ) relaxivity values are 4.52 and 34.75 mM(-1) s(-1) , respectively. No apparent cytotoxicity is observed and the nanocomposite shows a biocompatible nature. In vivo MR studies show both T(1) and T(2) * contrast behavior of the nanocomposite. Fluorescence imaging indicates selective uptake of IO-CNC by macrophages in spleen.     

Properties of scaffolds based on chitosan and collagen with bioglass 45S5

Scaffolds based on chitosan (CTS), collagen (Coll) and glycosaminoglycans (GAG) mixtures cross‐linked by tannic acid (TA) with bioglass 45S5 addition were obtained with the use of the freeze‐drying method. The prepared scaffolds were characterised for morphology, mechanical strength and degradation rate. Moreover, cell viability on the obtained scaffolds was measured with and without the presence of ascorbic acid and dexamethasone. The main purpose of the research was to compare the effectiveness of bioglass 45S5 influence on the physicochemical and biological properties of scaffolds. The results demonstrated that the scaffolds based on the blends of biopolymers cross‐linked by TA are stable in an aqueous environment. Scanning electron microscope images allowed the observation of a porous scaffold structure with interconnected pores. The addition of bioglass nanoparticles improved the mechanical properties and decreased the degradation rate of composite materials. The biological properties were improved for 20% tannic acid addition compared to 5%. However, the addition of bioglass 45S5 did not change to cells response significantly.Inspec keywords: biomedical materials, drying, porous materials, freezing, tissue engineering, proteins, nanofabrication, bone, scanning electron microscopy, polymers, molecular biophysics, cellular biophysics, nanoparticles, porosityOther keywords: chitosan, collagen, glycosaminoglycans, bioglass 45S5 addition, freeze‐drying method, degradation rate, ascorbic acid, dexamethasone, physicochemical properties, biological properties, porous scaffold structure, bioglass nanoparticles, mechanical properties, tannic acid addition, scanning electron microscopy     

Thermal decomposition of Co-Al layered double hydroxide: Identification of precursor to oxide with spinel structure

The layered double hydroxide (LDH) of Co with Al decomposes to yield an oxide residue with the spinel structure below 250°C. The decomposition reaction is preceded by the formation of an intermediate hydroxide in which the metal hydroxide layers are regularly stacked about the c-crystallographic axis, but the layers themselves are aperiodic. Aperiodicity is modeled by locating randomly chosen Co²⁺ ions in tetrahedral sites in the interlayer region. This phase is characterized by a single strong basal reflection in its powder diffraction pattern. All other reflections are extinguished on account of (i) turbostratic disorder which destroys all hkl reflections and (ii) layer aperiodicity, which destroys all two dimensional hk reflections. Given its topochemical relationship with the spinel structure, such an intermediate is a necessary precursor to spinel formation.     

Evaluation of carsharing network’s growth strategies through discrete event simulation

Carsharing organizations are nowadays faced with the emergence of new markets due to the growing popularity of their services. To keep up with the growing demand, they have to constantly adapt their network and balance their stations’ capacities by implementing new strategies. These strategies involve creation of new carsharing stations, increasing the capacity of stations, merging or demerging carsharing stations etc. Currently, the decision makers rely on an intuitive strategy selection process which often results in inadequate decisions being made representing an immediate loss in resources, time and market penetration. This paper presents a discrete event simulation based decision support tool that assists the decision makers in selecting best network growth strategies to implement for meeting adequately the demand growth while maximizing the members’ satisfaction level and minimizing the number of vehicles used. Our discrete event simulation model allows modeling the activities at any given set of carsharing stations, regardless of their number and capacities. A benchmarking comparison of different potential strategies is done. An application of the proposed model on a region of Communauto’s Montréal (Québec, Canada) carsharing network is provided.     

Observational study of cloud base height and its frequency over a tropical station,Thiruvananthapuram, using a ceilometer

This study aims to investigate the characteristic features of cloud base height (CBH) over Thiruvananthapuram during different seasons. CBH data were used for the present work derived from the Vaisala Laser Ceilometer, CL31 (VLC) installed at the campus of the Centre for Earth Science Studies, Akkulam (8.29° N, 76.59° E, 15 m above sea level). The VLC was in operation from the second week of July 2006 onwards. From the study, we found that CBH shows distinct diurnal and seasonal variations during all the seasons (except on rainy days). The diurnal variation for low-level clouds was different from that for the mid-level clouds. A cloud-free layer is evident in the region between 2.5 and 4 km. This cloud-free zone is more prominent during the southwest monsoon period compared to other seasons. Moreover, the monthly variations of cloud frequency and CBH were also described in addition to the different periodicities in cloud frequency. The periodicities found in the cloud frequency were 8 days and 30 days and these are significant at the 5% level. Thermodynamic parameters from the radiosonde were also related to the cloud frequency for various seasons and they were in good agreement.     

Do drivers change their manual car-following behaviour after automated car-following?

There is evidence that drivers’ behaviour adapts after using different advanced driving assistance systems. For instance, drivers’ headway during car-following reduces after using adaptive cruise control. However, little is known about whether, and how, drivers’ behaviour will change if they experience automated car-following, and how this is affected by engagement in non-driving-related tasks (NDRT). The aim of this driving simulator study, conducted as part of the H2020 L3Pilot project, was to address this topic. We also investigated the effect of the presence of a lead vehicle during the resumption of control, on subsequent manual driving behaviour. Thirty-two participants were divided into two experimental groups. During automated car-following, one group was engaged in an NDRT (SAE Level 3), while the other group was free to look around the road environment (SAE Level 2). Both groups were exposed to Long (1.5 s) and Short (.5 s) Time Headway (THW) conditions during automated car-following, and resumed control both with and without a lead vehicle. All post-automation manual drives were compared to a Baseline Manual Drive, which was recorded at the start of the experiment. Drivers in both groups significantly reduced their time headway in all post-automation drives, compared to a Baseline Manual Drive. There was a greater reduction in THW after drivers resumed control in the presence of a lead vehicle, and also after they had experienced a shorter THW during automated car-following. However, whether drivers were in L2 or L3 did not appear to influence the change in mean THW. Subjective feedback suggests that drivers appeared not to be aware of the changes to their driving behaviour, but preferred longer THWs in automation. Our results suggest that automated driving systems should adopt longer THWs in car-following situations, since drivers’ behavioural adaptation may lead to adoption of unsafe headways after resumption of control.