A Novel Design of Multi-Chambered Biomass Battery

In this paper, a novel design of biomass battery has been introduced for providing electricity to meet the lighting requirements of rural household using biomass. A biomass battery is designed, developed and tested using cow dung as the raw material. This is done via anaerobic digestion of the cow dung, and power generation driven by the ions produced henceforth. The voltage and power output is estimated for the proposed system. It is for the first time that such a high voltage is obtained from cow dung fed biomass battery. The output characteristics of this novel battery design have also been compared with the previously designed battery

Simultaneously Sparse Solutions to Linear Inverse Problems with Multiple System Matrices and a Single Observation Vector

A linear inverse problem is proposed that requires the determination of multiple unknown signal vectors. Each unknown vector passes through a different system matrix and the results are added to yield a single observation vector. Given the matrices and lone observation, the objective is to find a simultaneously sparse set of unknown vectors that solves the system. We will refer to this as the multiple-system single-output (MSSO) simultaneous sparsity problem. This manuscript contrasts the MSSO problem with other simultaneous sparsity problems and conducts a thorough initial exploration of algorithms with which to solve it. Seven algorithms are formulated that approximately solve this NP-Hard problem. Three greedy techniques are developed (matching pursuit, orthogonal matching pursuit, and least squares matching pursuit) along with four methods based on a convex relaxation (iteratively reweighted least squares, two forms of iterative shrinkage, and formulation as a second-order cone program). The algorithms are evaluated across three experiments: the first and second involve sparsity profile recovery in noiseless and noisy scenarios, respectively, while the third deals with magnetic resonance imaging radio-frequency excitation pulse design.Comment: 36 pages; manuscript unchanged from July 21, 2008, except for updated references; content appears in September 2008 PhD thesi

Mixed Phase in Compact Starts : M-R relations and radial oscillations

It is believed that quark stars or neutron stars with mixed phase in the core have smaller radii compared to ordinary compact stars. With the recent observation of several low radius objects, typically a radius of $<10 Km.$ for star of mass $< 1M_0$ in low mass X-ray binaries (LMXB), it has become very important to understand the nature of these objects. An accurate determination of mass-radius relationship of these objects provide us with a physical laboratory to study the composition of high density matter and the nature of phase transition. We study the effect of quark and nuclear matter mixed phase on mass radius relationship and radial oscillations of neutron stars. We find that the effect of the mixed phase is to decrease the maximum mass of a stable neutron star and to decrease the radial frequencies .Comment: guest contribution at Int. Workshop on Astronomy & Relativistic Astrophysics (IWARA 03)held at Olinda-PE (Brazil) from Oct. 12-17,200

Young stellar population and ongoing star formation in the HII complex Sh2-252

In this paper an extensive survey of the star forming complex Sh2-252 has been undertaken with an aim to explore its hidden young stellar population as well as to understand the structure and star formation history. This complex is composed of five embedded clusters associated with the sub-regions A, C, E, NGC 2175s and Teu 136. Using 2MASS-NIR and Spitzer-IRAC, MIPS photometry we identified 577 young stellar objects (YSOs), of which, 163 are Class I, 400 are Class II and 14 are transition disk YSOs. Spatial distribution of the candidate YSOs shows that they are mostly clustered around the sub-regions in the western half of the complex, suggesting enhanced star formation activity towards its west. Using the spectral energy distribution and optical colour-magnitude diagram based age analyses, we derived probable evolutionary status of the sub-regions of Sh2-252. Our analysis shows that the region A is the youngest (~ 0.5 Myr), the regions B, C and E are of similar evolutionary stage (~ 1-2 Myr) and the clusters NGC 2175s and Teu 136 are slightly evolved (~ 2-3 Myr). Morphology of the region in the 1.1 mm map shows a semi-circular shaped molecular shell composed of several clumps and YSOs bordering the western ionization front of Sh2-252. Our analyses suggest that next generation star formation is currently under way along this border and that possibly fragmentation of the matter collected during the expansion of the HII region as one of the major processes responsible for such stars. We observed the densest concentration of YSOs (mostly Class I, ~ 0.5 Myr) at the western outskirts of the complex, within a molecular clump associated with water and methanol masers and we suggest that it is indeed a site of cluster formation at a very early evolutionary stage, sandwiched between the two relatively evolved CHII regions A and B.Comment: 19 pages, 13 figures, Accepted for publication in MNRA

Human resource management practices and employee engagement

BACKGROUND AND OBJECTIVES: Employee engagement has emerged as a critical factor for organizations seeking to enhance productivity, foster employee well-being, and gain a competitive advantage. Human resource management practices are vital to driving employee engagement. Therefore, based on the social exchange theory, the current study explores the interaction between human resource management practices and employee engagement. and evaluates the level of engagement (i.e., High, medium, low) of employees. Also, finds an association between engagement levels and the age group of employees.METHODS:  The study administered the standardized questionnaire to employees (n= 187) working in information technology companies. A purposive random sampling research design was adopted for data collection. Confirmatory factor analysis was performed to ensure the validity of the adapted questionnaire, then simple linear regression was run in AMOS v24 software for finding the variance between human resource management practices and employee engagement. Further, chi-square and analysis of variance tests were also used in SPSS v22.FINDINGS: Human Resource Management practices such as recruiting and selection, continuous training and development opportunities, competitive rewards, career advancement, and employee involvement together explained 33 percent variance based on the coefficient of determination (R2) value, where (Beta= 0.57,

From Neural Tube Formation Through the Differentiation of Spinal Cord Neurons: Ion Channels in Action During Neural Development.

Ion channels are expressed throughout nervous system development. The type and diversity of conductances and gating mechanisms vary at different developmental stages and with the progressive maturational status of neural cells. The variety of ion channels allows for distinct signaling mechanisms in developing neural cells that in turn regulate the needed cellular processes taking place during each developmental period. These include neural cell proliferation and neuronal differentiation, which are crucial for developmental events ranging from the earliest steps of morphogenesis of the neural tube through the establishment of neuronal circuits. Here, we compile studies assessing the ontogeny of ionic currents in the developing nervous system. We then review work demonstrating a role for ion channels in neural tube formation, to underscore the necessity of the signaling downstream ion channels even at the earliest stages of neural development. We discuss the function of ion channels in neural cell proliferation and neuronal differentiation and conclude with how the regulation of all these morphogenetic and cellular processes by electrical activity enables the appropriate development of the nervous system and the establishment of functional circuits adapted to respond to a changing environment

Secure and energy-efficient smart building architecture with emerging technology IoT

With the advent of the Internet-of-Things (IoT), it is considered to be one of the latest innovations that offer interesting opportunities for different vertical industries. One of the most relevant IoT technology areas is smart construction. IoT operates in several sectors on a daily basis; implementation includes smart building, smart grids, smart cities, smart houses, physical defense, e-health, asset, and transportation management, but it is not restricted to this. Support from smart IoT buildings is an IoT-level, connected, and cost-effective system. Commercial space has major requirements in terms of comfort, accessibility, security, and energy management. Such requirements can be served organically by IoT-based systems. As the supply of energy has been exhausted and energy demand has risen, there has been a growing focus on energy usage and the maintenance of buildings.With the use of evolving IoT technology, we present a secure and energy-efficient smart building architecture.Every device is known by its unique address, and one of the key web transfer protocols is the Constrained Application Protocol (CoAP). It’s an application layer protocol that doesn’t use protected channels for data transfer. Automatic key management, confidentiality, authentication, and data integrity are all features of the Datagram Transport Layer Protection (DTLS).To achieve energy efficiency, we propose a smart construction architecture that, through IoT, manages the performance of all technological systems. The results of the simulation show that the energy consumption is lowered by about 30.86% with the use of the CoAP in the smart building, which is less than the Message Queuing Telemetry Transport case (MQTT). This paper also aims to observe how to integrate the DTLS protocol with the Secure Hash Algorithm (SHA-256) using optimizations from the Certificate Authority (CA) to improve security

Smoothed Analysis of Tensor Decompositions

Low rank tensor decompositions are a powerful tool for learning generative models, and uniqueness results give them a significant advantage over matrix decomposition methods. However, tensors pose significant algorithmic challenges and tensors analogs of much of the matrix algebra toolkit are unlikely to exist because of hardness results. Efficient decomposition in the overcomplete case (where rank exceeds dimension) is particularly challenging. We introduce a smoothed analysis model for studying these questions and develop an efficient algorithm for tensor decomposition in the highly overcomplete case (rank polynomial in the dimension). In this setting, we show that our algorithm is robust to inverse polynomial error -- a crucial property for applications in learning since we are only allowed a polynomial number of samples. While algorithms are known for exact tensor decomposition in some overcomplete settings, our main contribution is in analyzing their stability in the framework of smoothed analysis. Our main technical contribution is to show that tensor products of perturbed vectors are linearly independent in a robust sense (i.e. the associated matrix has singular values that are at least an inverse polynomial). This key result paves the way for applying tensor methods to learning problems in the smoothed setting. In particular, we use it to obtain results for learning multi-view models and mixtures of axis-aligned Gaussians where there are many more "components" than dimensions. The assumption here is that the model is not adversarially chosen, formalized by a perturbation of model parameters. We believe this an appealing way to analyze realistic instances of learning problems, since this framework allows us to overcome many of the usual limitations of using tensor methods.Comment: 32 pages (including appendix