Synergistic interaction of biocatalyst with bio-anode as a function of electrode materials

Comprehensive study was performed to understand the synergistic interaction between the biocatalyst and anode in terms of electron discharge (ED) pattern and microbial growth by varying electrode (bio-anode) materials viz., graphite, aluminum, brass, copper, nickel and stainless steel. Experiments were performed in bio-electrochemical cell consisting of three electrodes (bio-anode as working electrode, carbon rod as counter electrode and Ag/AgCl(S) as reference electrode) employing anaerobic mixed culture as anodic biocatalyst. Voltammetric and chronoamperometric analysis were used to enumerate the ED and redox reactions. Presence of higher microbial population and dominance of Gram positive bacteria with higher ED supported graphite function as a good bio-anode material. Nickel and stainless steel showed higher ED after graphite associated with dominance of Gram positive bacterial population. Although higher ED was noticed with brass, metal oxidation and decrement in ED with time doesn’t support its function as bio-anode. In spite of higher ED than nickel and stainless steel, aluminum and copper showed significant metal oxidation leading to change in both physical and electrochemical properties along with dominant growth of Gram negative bacteria. This study gives a comprehensive idea on biocatalyst interaction with anode in extracellular electron transfer which is important in improving the anode performance. Juxtaposing the results, it can be deduced that the outcome of the present study can be extended to all bio-electrochemical systems including microbial fuel cell (MFC).     

Adsorption and penetration of hydrogen in W: A first principles study

In BCC crystals, such as Tungsten (W), slippage has been observed on the (1 1 0) and (1 1 2) planes. In this work, hydrogen diffusion paths from three different W surfaces ((1 0 0), (1 1 0) and (1 1 2)) have been calculated using first principles density functional theory. Equilibrium sites for H at the surfaces are identified. The energetics for H penetration from the surfaces to the solute site in the bulk is calculated. It is found that for our low surface coverage of H (3.4 × 10¹⁴ H/cm²), approximately 2 eV is required for an H atom to penetrate any of the W surfaces considered in this study.     

Identification and extraction of brain tumor from MRI using local statistics of Zernike moments

In this article, a novel method is proposed for the detection of brain tumor in magnetic resonance images (MRIs). The features of Zernike moments are used to analyze the MRIs. The image is divided into two parts from the center of the image based on the average value of the pixel located at the center boundary, and new image vectors are formed to extract the tumor. The local statistics values obtained from the low and high order Zernike moments are used to calculate the appropriate threshold value for efficient tumor extraction. The proposed method successfully analyzes the tumor part of the image on testing with different MRIs.     

A theoretical study of the performance of sub-micron MOSFET devices in the presence of edge potential

In the present communication we have presented a detailed theoretical analysis of the performance of the sub-micron device in the presence of the discontinuity at the Si–SiO₂ interface. It is assumed that due to interface discontinuity a potential develops at the edges (Source/Drain) in addition to the built-in-potential. This potential, called Edge Potential, measures directly the extent of the interface roughness. The effect of this potential is more critical in the case of short channel device where drain and source are in close proximity. Our analysis shows that the discontinuity is dominant at the edges but not in the channel. Drive current as well as saturation transconductance decreases in the presence of edge potential. These results suggest that the performance of the device degrades due to the interface roughness. Effect of interface roughness near the edges can be reduced at high gate voltage but it will result more interface roughness scattering.     

Poly [2-(cinnamoyloxy)ethyl methacrylate-co-octamethacryl-POSS] nanocomposites: Synthesis and properties

Poly [2-(cinnamoyloxy)ethyl methacrylate-co-octamethacryl-POSS] nanocomposites were synthesized from octamethacryl-POSS and 2-(cinnamoyloxy)ethyl methacrylate (CEM) by free radical polymerization. The chemical structures and morphologies of these nanocomposites were determined by FTIR, ²⁹Si NMR, energy-dispersive spectroscopy (EDS), X-ray powder diffraction (XRD), and scanning electron microscopy (SEM) techniques. The XRD data showed that the materials were amorphous in nature, indicating that POSS formed an aggregate instead of a crystalline form in the polymer matrix. The POSS-CEM nanocomposites exhibited high thermal stability. Excitation and emission of the CEM-incorporated POSS nanocomposites, studied in the solid state, exhibited blue emission with CIE (x, 0.178; y, 0.137) coordinates, in addition to an emission intensity that increased with increasing CEM (monomer) concentration.     

Systemic inflammatory load in humans is suppressed by consumption of two formulations of dried,encapsulated juice concentrate

Chronic inflammation contributes to an increased risk for developing chronic conditions such as cardiovascular disease, diabetes, and cancer. A high “inflammatory load” is defined as elevated inflammation markers in blood or other tissues. We evaluated several markers of systemic inflammation from healthy adults and tested the hypothesis that two formulations of encapsulated fruit and vegetable juice powder concentrate with added berry powders (FVB) or without (FV) could impact markers of inflammatory load. Using a double‐blind, placebo‐controlled approach, 117 subjects were randomly assigned to receive placebo, FV, or FVB capsules. Blood was drawn at baseline and after 60 d of capsule consumption. We measured inflammatory markers (high sensitivity C‐Reactive Protein, Monocyte Chemotactic Protein‐1, Macrophage Inflammatory Protein 1‐β, and Regulated upon Activation, Normal T cell Expressed and Secreted), superoxide dismutase, and micronutrients (β‐carotene, vitamin C, and vitamin E). Results showed Monocyte Chemotactic Protein‐1, Macrophage Inflammatory Protein 1‐β, and RANTES levels were significantly reduced and superoxide dismutase and micronutrient levels were significantly increased in subjects consuming both FV and FVB, relative to placebo. Data suggest a potential health benefit by consuming either formulation of the encapsulated juice concentrates through their anti‐inflammatory properties.     

Monthly Rainfall Prediction Using Wavelet Neural Network Analysis

Rainfall is one of the most significant parameters in a hydrological model. Several models have been developed to analyze and predict the rainfall forecast. In recent years, wavelet techniques have been widely applied to various water resources research because of their time-frequency representation. In this paper an attempt has been made to find an alternative method for rainfall prediction by combining the wavelet technique with Artificial Neural Network (ANN). The wavelet and ANN models have been applied to monthly rainfall data of Darjeeling rain gauge station. The calibration and validation performance of the models is evaluated with appropriate statistical methods. The results of monthly rainfall series modeling indicate that the performances of wavelet neural network models are more effective than the ANN models.     

A Physics-driven Neural Networks-based Simulation System (PhyNNeSS) for multimodal interactive virtual environments involving nonlinear deformable objects

BACKGROUND: While an update rate of 30 Hz is considered adequate for real time graphics, a much higher update rate of about 1 kHz is necessary for haptics. Physics-based modeling of deformable objects, especially when large nonlinear deformations and complex nonlinear material properties are involved, at these very high rates is one of the most challenging tasks in the development of real time simulation systems. While some specialized solutions exist, there is no general solution for arbitrary nonlinearities. METHODS: In this work we present PhyNNeSS - a Physics-driven Neural Networks-based Simulation System - to address this long-standing technical challenge. The first step is an off-line pre-computation step in which a database is generated by applying carefully prescribed displacements to each node of the finite element models of the deformable objects. In the next step, the data is condensed into a set of coefficients describing neurons of a Radial Basis Function network (RBFN). During real-time computation, these neural networks are used to reconstruct the deformation fields as well as the interaction forces. RESULTS: We present realistic simulation examples from interactive surgical simulation with real time force feedback. As an example, we have developed a deformable human stomach model and a Penrose-drain model used in the Fundamentals of Laparoscopic Surgery (FLS) training tool box. CONCLUSIONS: A unique computational modeling system has been developed that is capable of simulating the response of nonlinear deformable objects in real time. The method distinguishes itself from previous efforts in that a systematic physics-based pre-computational step allows training of neural networks which may be used in real time simulations. We show, through careful error analysis, that the scheme is scalable, with the accuracy being controlled by the number of neurons used in the simulation. PhyNNeSS has been integrated into SoFMIS (Software Framework for Multimodal Interactive Simulation) for general use.     

Microstructure and residual stress distribution of similar and dissimilar electron beam welds – Maraging steel to medium alloy medium carbon steel

The influence of parent metal heat treatment condition on the residual stress distribution in dissimilar metal welds of maraging steel to quenched and tempered medium alloy medium carbon steel has been investigated. It has been observed that the residual stress distribution would be more compressive if the maraging steel is in soft condition. This is attributed to stress absorbing nature of highly yielding soft maraging steel.     

A Technique for Optimal Sequential Maintenance Scheduling

This paper presents the mathematical development of, and a simple solution technique for, an optimal sequential maintenance scheduling problem. The model is shown to satisfy the Kuhn-Tucker conditions, the necessary and sufficient conditions for the existence of an optimal solution. Real-world systems consisting of mixtures of constant and increasing failure rate devices are considered in the model. Sequential preventive maintenance schedules are developed for groups of identical items with increasing failure rates. Provision is made for the corrective maintenance of these groups if failures occur in between the preventive maintenance schedules. Also, constant failure rate devices are accorded corrective maintenance when failures occur. Optimality is achieved by minimizing the total annual maintenance cost, subject to constraints on the system availability, number of maintenance personnel and intervals of preventive maintenance. The model is applied to a coal mine power system example.