Development of a simple low-cost solar simulator for indoor collector testing

Indoor test methods for solar collectors are widely accepted and recommended by ASHRAE. The development of a solar simulator for indoor testing and the certification procedure for photo-thermal solar devices is discussed in this paper. The system consists of 14 quartz halogen lamps and provides a testing area of about 1 × 1 m. The irradiance can be varied from 400 to 1500 W/m². This is achieved by varying the input power supplied to individual lamps. The radiation output characteristics of a single lamp have been studied. The distribution of intensity over the covered area of 1·20 × 1·20 m has been recorded using a precision Eppley pyranometer.A variety of collectors—evacuated tubular collectors and flat-plate collectors of both liquid and air heating types—has been tested under sufficiently stable insolation conditions. Results for a conventional solar air heater are presented together with suggestions for further improvements.     

A novel social deep autoencoder NMF incentive scheme to detect a selfish node in delay tolerant network

Detection of the selfish node in a delay tolerant network (DTN) can sharply reduce the loss incurred in a network. The algorithm's current pedigree mainly focuses on the rely on nodes, records, and delivery performance. The community structure and social aspects have been overlooked. Analysis of individual and social tie preferences results in an extensive detection time and increases communication overhead. In this article, a heterogeneous DTN topology with high-power stationary nodes and mobile nodes on Manhattan's accurate map is designed. With the increasing complexity of social ties and the diversified nature of topology structure, there need for a method that can effectively capture the essence within the speculated time. In this article, a novel deep autoencoder-based nonnegative matrix factorization (DANMF) is proposed for DTN topology. The topology of social ties projected onto low-dimensional space leads to effective cluster formation. DANMF automatically learns an appropriate nonlinear mapping function by utilizing the features of data. Also, the inherent structure of the deep autoencoder is nonlinear and has strong generalization. The membership matrices extracted from the DANMF are used to design the weighted cumulative social tie that eventually, along with the residual energy, is used to detect the network's selfish node. The testing of the designed model is carried out on the real dataset of MIT reality. The proficiency of the developed algorithm has been well tested and proved at every step. The methods employed for social tie extraction are NMF and DANMF. The methodology is rigorously experimented on various scenarios and has improved around 80% in the worst-case scenario of 40% nodes turning selfish. A comprehensive comparison is made with the other existing state-of-the-art methods which are also incentive-based approaches. The developed method has outperformed and has shown the supremacy of the current methods to capture the latent, hidden structure of the social tie.

     

Uncertain supply chain network design considering carbon footprint and social factors using two-stage approach

Sustainable development has become one of the leading global issues over the period of time. Currently, implementation of sustainability in supply chain has been continuously in center of attention due to introducing stringent legislations regarding environmental pollution by various governments and increasing stakeholders’ concerns toward social injustice. Unfortunately, literature is still scarce on studies considering all three dimensions (economical, environmental and social) of sustainability for the supply chain. An effective supply chain network design (SCND) is very important to implement sustainability in supply chain. This study proposes an uncertain SCND model that minimizes the total supply chain-oriented cost and determines the opening of plants, warehouses and flow of materials across the supply chain network by considering various carbon emissions and social factors. In this study, a new AHP and fuzzy TOPSIS-based methodology is proposed to transform qualitative social factors into quantitative social index, which is subsequently used in chance-constrained SCND model with an aim at reducing negative social impact. Further, the carbon emission of supply chain is estimated by considering a composite emission that consists of raw material, production, transportation and handling emissions. In the model, a carbon emission cap is imposed on total supply chain to reduce the carbon footprint of supply chain. To solve the proposed model, a code is developed in AMPL software using a nonlinear solver SNOPT. The applicability of the proposed model is illustrated with a numerical example. The sensitivity analysis examines the effects of reducing carbon footprint cap, negative social impacts and varying probability on the total cost of the supply chain. It is observed that a stricter carbon cap over supply chain network leads to opening of more plants across the supply chain. In addition, carbon footprint of supply chain is found to be decreased in certain extent with the reduction in negative social impacts from suppliers. The carbon footprint of the supply chain is found to be reduced with increasing certainty of material supply from the suppliers. The total supply chain cost is observed to be augmented with increasing probability.     

Ascorbic acid imprinted polymer-modified graphite electrode: A diagnostic sensor for hypovitaminosis C at ultra trace ascorbic acid level

A new kind of molecularly imprinted polymer-modified graphite electrode was fabricated by “grafting-to” approach, incorporating sol–gel technique, for the detection of acute deficiency in serum ascorbic acid level (SAAL), manifesting hypovitaminosis C. The modified electrode exhibited ascorbic acid (AA) oxidation at less positive potential (0.0 V) than the earlier reported methods, resulting in a limit of detection as low as 6.13 ng mL⁻¹ (RSD = 1.2%, S/N = 3). The diffusion coefficient (1.096 × 10⁻⁵ cm² s⁻¹), rate constant (7.308 s⁻¹), and Gibb's free energy change (−12.59 kJ mol⁻¹) due to analyte adsorption, were also calculated to explore the kinetics of AA oxidation. The proposed sensor was found to enhance sensitivity substantially so as to detect ultra trace level of AA in the presence of other biologically important compounds (dopamine, uric acid, etc.), without any cross interference and matrix complications from biological fluids and pharmaceutical samples.     

Design and analysis of RF MEMS shunt switch for V-band applications

Microsystem Technologies - In this paper, we have designed and simulations of RF MEMS shunt switch. The electro-mechanical and electromagnetic analysis of the switch have been done using COMSOL...     

Docosahexaenoic Acid and Eicosapentaenoic Acid Did not Alter <Emphasis Type="Italic">trans</Emphasis>-10,<Emphasis Type="Italic">cis</Emphasis>-12 Conjugated Linoleic Acid Incorporation into Mice Brain and Eye Lipids

trans 10,cis 12‐CLA has been reported to alter fatty acid composition in several non‐neurological tissues, but its effects are less known in neurological tissues. Therefore, the purpose of this study was to determine if CLA supplementation would alter brain and eye fatty acid composition and if those changes could be prevented by concomitant supplementation with docosahexaenoic acid (DHA; 22:6n3) or eicosapentaenoic acid (EPA; 20:5n3). Eight‐week‐old, pathogen‐free C57BL/6N female mice (n = 6/group) were fed either the control diet or diets containing 0.5% (w/w) t10,c12‐CLA in the presence or absence of either 1.5% DHA or 1.5% EPA for 8 weeks. CLA concentration was significantly (P < 0.05) greater in the eye but not in the brain lipids of the CLA group when compared with the control group. The sums of saturated, monounsaturated, polyunsaturated fatty acids, and n3:n6 ratio did not differ between these two groups for both tissues. The n3:n6 ratio and concentrations of 20:5n3 and 22:5n3 were significantly greater, and those of 20:4n6, 22:4n6, and 22:5n6 were lesser in the CLA + DHA and CLA + EPA groups than in the control and CLA groups for either tissue. DHA concentration was higher in the CLA + DHA group only but not in the CLA + EPA group when compared with the CLA group for both tissues. The dietary fatty acids generally induced similar changes in brain and eye fatty acid concentration and at the concentrations used both DHA and EPA fed individually with CLA were more potent than CLA alone in altering the tissue fatty acid concentration.     

An in-Depth Analysis of the Swelling,Mechanical, Electrical,and Drug Release Properties of Agar–Gelatin Co-Hydrogels

Agar–gelatin-based co-hydrogels were prepared with different compositions of the agar and the gelatin fractions. The intermolecular hydrogen bonding was higher in the co-hydrogels as compared to the gelatin hydrogel. Swelling studies indicated diffusion-mediated swelling. The electrical stability of the co-hydrogels was higher as compared to the gelatin hydrogel. Though the firmness of the co-hydrogels was higher, Weichert model of viscoelasticity indicated that the inherent mechanical stability of the gelatin hydrogel was superior. The release of ciprofloxacin hydrochloride was predominately Fickian diffusion-mediated. In gist, the co-hydrogels can be tried as polymeric constructs for controlled drug delivery applications.     

Impact of hydrogen generated by splitting water with nano-silicon and nano-aluminum on diesel engine performance

Efficient utilization of hydrogen generated during the reactions of nano-silicon/water and nano-aluminum/water in internal combustion engine has been investigated in the current work. Engine performance and emission studies of formulated and stabilized nanoemulsion fuels (water in diesel W/D), nano-aluminum in water/diesel (W/DA) and water in nano-silicon/diesel (W/DS) have been compared with those of diesel. Experimental investigations showed reduction in brake specific fuel consumption (BSFC) by 21% and 37%; rise in brake thermal efficiency (BTE) by 16% and 14% when engine was fueled with W/DA and W/DS respectively. For nanoemulsion fuels an increase in induced power was also recorded. Brake mean effective pressure, BTE and NOx emission dropped for W/D due to reduced exhaust gas temperatures. Nevertheless due to elevated peak cylinder pressures and exhaust gas temperatures a marginal rise in NOx, CO, HC and radiative heat emissions was observed with W/DA and W/DS.     

Gold nanorods mediated controlled release of doxorubicin: nano-needles for efficient drug delivery

Use of cysteamine hydrochloride (Cys-HCl) protected gold nanorods (GNRs) as efficient carrier of widely used anti-cancer drug doxorubicin using folic acid as navigational molecule is presented in this work. GNRs were found to have excellent drug loading capacity of >97 %. A detailed comprehension of in vitro drug release profile under ideal physiological condition was found to obey 1st order kinetics at pH 6.8, 5.3 and 7.2, an ideal milieu for drug delivery to solid tumours.     

Effect of Transition Metals on Polysialic Acid Structure and Functions

Polysialic acid (PSA) is one of the most abundant glycopolymer present in embryonic brain, and it is known to be involved in key roles such as plasticity in the central nervous system, cell adhesion, migration and localization of neurotrophins. However, in adult brain, its expression is quite low. The exception to this is in Alzheimer′s disease (AD) brain, where significantly increased levels of polysilylated neural cell adhesion molecule (PSA‐NCAM) have been reported. Here, we confirm the role of PSA as a metal chelator, allowing it to decrease cytotoxicity caused by high levels of transition metals, commonly found in AD brain, and as a regulator of cell behavior. UV‐visible (UV‐vis) and circular dichroism (CD) spectroscopy, atomic force microscopy (AFM), and isothermal titration calorimetry (ITC) techniques were used to investigate the assembly of PSA–metals complexes. These PSA–metal complexes exhibited less toxicity compared to free metal ions, and in particular, the PSA–Cu²⁺ complex synergistically promoted neurite outgrowth in PC12 cells.