Comparison of performance of single-loop and current-injectioncontrol for PWM converters that operate in both continuous anddiscontinuous modes of operation

An analysis of current-injection-controlled (CIC) power converters operating in both the continuous and discontinuous modes is performed using the PWM switch model and a new, continuous-time model of CIC. The stability, output impedance, audio susceptibility, and transient response are compared with single-loop control. The control of an example buck converter is designed with CIC and single-loop control. It is shown how single-loop controlled power converters exhibit a large change in the dynamic performance when crossing the boundary between continuous mode and discontinuous mode. This is especially true for the output impedance and transient response. The dynamic performance of CIC power converters remains relatively fixed when crossing this boundary. A significant performance improvement can be realized when CIC is employed in converters that operate over a wide load range     

From an open-access to a state-controlled resource: the case of groundwater in the Kathmandu Valley,Nepal

Groundwater is no longer an open-access resource in Kathmandu. Perceptions of groundwater are changing from an “infinite” to a “finite” resource and the role of the government from supply developer to caretaker of the resource. In this context, this paper aims to unfold how perceptions of groundwater in Kathmandu Valley, Nepal, are changing from an open-access resource to an overexploited, depleted, degraded, vulnerable and state-controlled resource. In the process, it produces an aggregated picture of resource availability, development dynamics, impacts and responses in the area; suggests some “soft-path” approaches for groundwater management; and discusses implications of the experience for other areas.     

Dynamic Routing and Wavelength Assignment Using Cost Based Heuristics in WDM Optical Networks

Dynamic routing and wavelength assignment problem in optical networks is a two-step problem that is influenced by the choice of a successful optimal path selection and wavelength assignment. Proper selection techniques reduce the number of wavelengths required in the network and thereby improves traffic grooming. Heuristic algorithms and integer linear programming models help in selection of route and wavelength separately. Hence, the computation time is large which makes the system slow. A cost function is computed which uses independent parameters in the network for the selection of route and wavelength for a call. The heuristic reduces computation time by combining the search of route and wavelength to be assigned. In addition, the network performance is analyzed with and without alternate routing along with proposed heuristics. The selection of proper route and wavelength finding technique is very essential since it improves the grooming factor of the network thereby allowing more traffic support by the network. Our objective is to investigate and propose a cost based heuristics for dynamic traffic routing and wavelength Assignment in WDM optical networks. For this we plan to develop cost functions and heuristics to compute the route and wavelength assignment strategy. Here, our objective is to reduce the computation time for selection of route and wavelength assignment strategy by weighted cost function. The function has to include network parameters for its processing. Our work provides an overview about DRWA by applying cost based heuristics in WDM networks. This paper explains the proposed cost function and its applications in line with selection of independent parameters. The details of other functions like cost function formulation, hop-based route assignment, available wavelength based route assignment, mathematical analysis of proposed cost function are also explained. Results and discussions based on the findings are presented.

     

Atorvastatin-loaded lipid nanoparticles: antitumor activity studies on MCF-7 breast cancer cells

Atorvastatin is a synthetic statin commonly used in the treatment of hypercholesterolemia. Apart from this, statins appear to have pleiotropic effects, including modulation of cell growth, apoptosis. Through modulation of these pathways, statins have the potential to influence a wide range of disease processes, including cancer. However, poor aqueous solubility (0.1?mg/mL) and poor oral bioavailability has limited therapeutic application of atorvastatin. Present work is an attempt to improve tumor targeting of atorvastatin by incorporating in nanostructured lipid carriers (NLCs) and studying its anticancer activity on MCF-7 cell lines. NLCs of atorvastatin were formulated by high-speed homogenization followed by probe sonication method. The optimized batch of NLCs had a mean size of 130.02?±?3.1?nm and entrapment efficiency of 90.42?±?3.7%. The in vitro drug release study by dialysis method indicated that drug entrapped in the NLCs remains entrapped at acidic pH as well as in phosphate buffer of pH 7.4 for a prolonged period of time as compared to plain drug. In vitro cytotoxicity studies on MCF-7 (mammary adenocarcinoma human cell lines) cell lines showed that concentration of drug required for total growth inhibition (TGI) and 50% growth inhibition (GI50) of MCF-7 cells was found to be 27.4?µg/mL and <10?µg/mL respectively, in case of atorvastatin- NLCs which is less than that required in case of plain atorvastatin and almost similar to that of adriamycin. All these findings reinforce the fact that atorvastatin loaded NLCs are promising novel delivery system for treating breast cancer.     

Emotion recognition from geometric fuzzy membership functions

The posterity challenging task in the Machine Intelligence field is to design a smarter system to identify the human emotions. Facial Emotion Recognition (FER) is a significant visual based tool to construct a smarter system that can recognize human emotions. The existing methods in FER are based on Action Units (AU), appearance and geometrical parameters. Nearly 7000 different combinations of AUs are used in AU to discriminate the emotions, which can be very expensive and increase processing time. Generalize appearance features across the universe is another challenging task. In this paper, a novel geometrical fuzzy based approach is presented to accurately recognize the emotions. The four corner features from eyes and mouth regions are extracted without considering reference face. The extracted features are used to define the quadrilateral shape that failed to match with the shapes in geometry. The degree of impreciseness exists in the quadrilateral is measured by the proposed Mixed Quadratic Shape Model (MQSM) using fuzzy membership functions. Finally, twelve fuzzy features are extracted from the membership functions and used by the classifier for validation. The CK, JAFFE and ISED datasets are used in the experiment to evaluate the performance of the MSQM. It is observed the proposed method performed better than the contemporary methods using twelve fuzzy features without reference image.

     

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.     

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