Investigation of Basic mechanical properties of Jute Reinforced polyster composites for Patellar Implant Application

n this study, Polyester resin matrix was reinforced with Jute fibers in different compositions and orientations. The polymer composites were prepared using Hand layup technique. Mechanical tests such as tensile test, compression test and bending test were conducted on the samples prepared to the standard dimensions. Also compared with the properties of UHMWPE, which is the presently used material.Thus it is concluded that Jute reinforced polymer composite is a low density material and the induced stresses are within the permissible range. So, existing implants can be replaced by polymer composite implants based on strength properties

Alvira : comparative genomics of viral strains

The Alvira tool is a general purpose multiple sequence alignment viewer with a special emphasis on the comparative analysis of viral genomes. This new tool has been devised specifically to address the problem of the simultaneous analysis of a large number of viral strains. The multiple alignment is embedded in a graph that can be explored at different levels of resolution

Closed-loop compensation of charge trapping induced by ionizing radiation in MOS capacitors

The objective of this work is to explore the capability of a charge trapping control loop to continuously compensate charge induced by ionizing radiation in the dielectric of MOS capacitors. To this effect, two devices made with silicon oxide have been simultaneously irradiated with gamma radiation: one with constant voltage bias, and the other working under a dielectric charge control. The experiment shows substantial charge trapping in the uncontrolled device whereas, at the same time, the control loop is able to compensate the charge induced by gamma radiation in the second device.Peer ReviewedPostprint (author's final draft

Applying a User-centred Approach to Interactive Visualization Design

Analysing users in their context of work and finding out how and why they use different information resources is essential to provide interactive visualisation systems that match their goals and needs. Designers should actively involve the intended users throughout the whole process. This chapter presents a user-centered approach for the design of interactive visualisation systems. We describe three phases of the iterative visualisation design process: the early envisioning phase, the global specification hase, and the detailed specification phase. The whole design cycle is repeated until some criterion of success is reached. We discuss different techniques for the analysis of users, their tasks and domain. Subsequently, the design of prototypes and evaluation methods in visualisation practice are presented. Finally, we discuss the practical challenges in design and evaluation of collaborative visualisation environments. Our own case studies and those of others are used throughout the whole chapter to illustrate various approaches

Fatigue-Induced Failure in Horizontal-Axis Wind-Turbine (HAWT) Blades and HAWT Drivetrain Gears

Wind energy is one of the most promising and the fastest growing installed alternative-energy production technologies. In fact, it is anticipated that by 2030, at least 20% of the U.S. energy needs will be met by various onshore and offshore wind-farms [a collection of wind-turbines (converters of wind energy into electrical energy) at the same location]. A majority of wind turbines nowadays fall into the class of the so-called Horizontal Axis Wind Turbines (HAWTs). Turbine blades and the gearbox are perhaps the most critical components/subsystems in the present designs of HAWTs. The combination of high failure rates (particularly those associated with turbine-blades and gear-boxes), long downtimes and the high cost of repair remains one of the major problems to the wind-energy industry today. In the case of HAWT blades, one is typically concerned about the following two quasi-static structural-performance requirements: (a) sufficient \u27flap-wise\u27 bending strength to withstand highly-rare extreme static-loading conditions (e.g., 50-year return-period gust, a short strong blast of wind); and (b) sufficient turbine blade \u27flap-wise\u27 bending stiffness in order to ensure that a minimal clearance is maintained between blade tip and the turbine tower at all times during wind turbine operation. If these two structural requirements are not met, HAWT blades typically fail prematurely. In addition to the aforementioned quasi-static structural-performance requirements, one is also concerned about the premature-failure caused by inadequate fatigue-based durability of the HAWT blades. The durability requirement for the turbine blades is typically defined as a minimum of 20-year fatigue life (which corresponds roughly to ca. 108 cycles) when subjected to stochastic wind-loading conditions and cyclic gravity-induced edge-wise bending loads in the presence of thermally-fluctuating and environmentally challenging conditions. In the present work, a computational framework has been developed to address: (a) structural response of HAWT blades subjected to extreme loading conditions; (b) high-cycle-fatigue-controlled durability of the HAWT blades; and (c) methodology for HAWT-blade material selection. To validate the computational approach used, key results are compared with their experimental counterparts available in the public-domain literature. As far as the HAWT gear-boxes are concerned, while they are designed for the entire life (ca. 20 years) of the HAWT, in practice, most gear-boxes have to be repaired or even overhauled considerably earlier (3-5 years). Typically, a HAWT gear-box fails either due to the bending-fatigue-induced failure of its gears, or by tribo-chemical degradation and failure of its bearings. In the present work, a computational framework has been developed to predict HAWT service-life under extreme loading and unfavorable kinematic conditions, for the case when the gear-box service-life is controlled by gear-tooth bending-fatigue failure. In addition, a preliminary investigation of gear-box bearing kinematics, which can result in undesirable rolling-element skidding conditions, is conducted

A deeply branching thermophilic bacterium with an ancient acetyl-CoA pathway dominates a subsurface ecosystem

<div><p>A nearly complete genome sequence of <em>Candidatus</em> ‘Acetothermum autotrophicum’, a presently uncultivated bacterium in candidate division OP1, was revealed by metagenomic analysis of a subsurface thermophilic microbial mat community. Phylogenetic analysis based on the concatenated sequences of proteins common among 367 prokaryotes suggests that <em>Ca.</em> ‘A. autotrophicum’ is one of the earliest diverging bacterial lineages. It possesses a folate-dependent Wood-Ljungdahl (acetyl-CoA) pathway of CO₂ fixation, is predicted to have an acetogenic lifestyle, and possesses the newly discovered archaeal-autotrophic type of bifunctional fructose 1,6-bisphosphate aldolase/phosphatase. A phylogenetic analysis of the core gene cluster of the acethyl-CoA pathway, shared by acetogens, methanogens, some sulfur- and iron-reducers and dechlorinators, supports the hypothesis that the core gene cluster of <em>Ca.</em> ‘A. autotrophicum’ is a particularly ancient bacterial pathway. The habitat, physiology and phylogenetic position of <em>Ca.</em> ‘A. autotrophicum’ support the view that the first bacterial and archaeal lineages were H₂-dependent acetogens and methanogenes living in hydrothermal environments.</p> </div

Synthesis of boron nitride/vycor composite membrane structures by an optimized LPCVD process

Since the advent of the idea of ultrafiltration, microporous membranes have come through a long way in establishing a niche as an efficient technology for gas separation applications. More and more research is aimed at reducing pore size towards nanolevels, when separation factor is the criterion rather than the permeability. This work is focused at synthesizing and characterizing microporous inorganic membranes for gas separations by molecular sieving. BN was deposited on mesoporous vycor tubes using triethylamine borane complex (TEAB) and ammonia as precursors. Effect of temperature and deposition geometry on permeability of various gases has been studied. Very high selectivities have been achieved for separation of small inorganic gases such as He, H2 from N2. Activation energy study indicate that the permeability of He and H2 are thermally activated with activation energies of 39.7 kJ/mol and 5O kJ/mol respectively. XRD analysis indicate an amorphous BN deposit in the vycor tube

Evolution of Convolutional Neural Network (CNN): Compute vs Memory bandwidth for Edge AI

Convolutional Neural Networks (CNNs) have greatly influenced the field of Embedded Vision and Edge Artificial Intelligence (AI), enabling powerful machine learning capabilities on resource-constrained devices. This article explores the relationship between CNN compute requirements and memory bandwidth in the context of Edge AI. We delve into the historical progression of CNN architectures, from the early pioneering models to the current state-of-the-art designs, highlighting the advancements in compute-intensive operations. We examine the impact of increasing model complexity on both computational requirements and memory access patterns. The paper presents a comparison analysis of the evolving trade-off between compute demands and memory bandwidth requirements in CNNs. This analysis provides insights into designing efficient architectures and potential hardware accelerators in enhancing CNN performance on edge devices

Comparative Study of Dimension Reduction Approaches With Respect to Visualization in 3-Dimensional Space

In the present big data era, there is a need to process large amounts of unlabeled data and find some patterns in the data to use it further. If data has many dimensions, it is very hard to get any insight of it. It is possible to convert high-dimensional data to low-dimensional data using different techniques, this dimension reduction is important and makes tasks such as classification, visualization, communication and storage much easier. The loss of information should be less while mapping data from high-dimensional space to low-dimensional space. Dimension reduction has been a significant problem in many fields as it needs to discard features that are unimportant and discover only the representations that are needed, hence it gathers our interest in this problem and basis of the research. We consider different techniques prevailing for dimension reduction like PCA (Principal Component Analysis), SVD (Singular Value Decomposition), DBN (Deep Belief Networks) and Stacked Auto-encoders. This thesis is intended to ultimately show which technique performs best for dimension reduction with the help of studied experiments