Technical review: Improvement of mechanical properties and suitability towards armor applications – Alumina composites

Ceramic Matrix Composites (CMCs) have many interesting properties, mainly light weight, cost efficiency, low density, high compressive strength, high hardness and durability. Hence, they emerged as a boon to the development of personnel armors in the past. The current work aims to review various new methodologies adapted for the reinforcement of Alumina (Al₂O₃) CMCs in recent times, including some of the interesting results obtained with respect to mechanical properties, suitability of the synthesized composites for armor applications, and the upcoming reinforcement trends. Finally, studies related to reinforcement in Al₂O₃ CMCs, specifically towards armor applications have been consolidated to arrive at some of the important inferences for concluding reasonably.     

Electrocatalytic Reduction of CO2 to Ethylene by Molecular Cu‐Complex Immobilized on Graphitized Mesoporous Carbon

The electrochemical reduction of carbon dioxide (CO₂) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO₂ to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO₂ to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO₂ in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.     

Novel Short-chain Crosslinked Cationomeric Polyurethanes

Summary Novel PUs containing pyridinium moieties were synthesized by chain extending isocyanate endcapped prepolymers with N, N’-bis (2-hydroxyethyl) isonicotinamide. The pyridinium moieties in the PUs were chemically crosslinked using short-chain divalent quaternising agents. The polyurethane cationomers were characterized by spectral, thermal and mechanical analysis. Spectral results confirmed the quaternisation of tertiary nitrogen leading to crosslinking. Compared to conventional PUs, the crosslinked PU networks exhibited improved thermal stability. The damping value (i.e.) tan δ for cationomers were improved over a broad temperature range when compared to conventional PU.     

Cardiac disease in chronic uremia: management

Heart disease is a common cause of morbidity in end-stage renal disease (ESRD) patients. The management of heart disease in these patients requires a multidimensional approach to the management of heart failure, coronary disease, and arrhythmias, and to risk factors such as hypertension, anemia, secondary hyperparathyroidism, and electrolyte/acid-base disturbances. Coronary artery disease management includes use of antianginal drugs and revascularization of coronary arteries with angioplasty +/- stent placement or coronary artery bypass grafting. The long-term outcomes of these procedures need to be assessed and improved. Hypertension occupies a major role in the pathogenesis of heart disease in ESRD, and early and adequate control of hypertension is likely to have a major impact on the progression of cardiac disease. This entails the achievement of optimal volume status, combined with the appropriate use of antihypertensive agents such as calcium channel blockers, beta-blockers, angiotensin-converting enzyme (ACE) inhibitors, vasodilators, alpha-blockers, and central sympatholytic drugs. In ESRD patients, specific dialysis-related complications such as intradialytic hypotension and pericardial effusion may have additional effects on cardiac function and require attention. The choice of dialysate composition and membrane may influence clinical outcomes with specific effects on cardiac performance.     

Effect of temperature on recombinant protein production using the Bm5/Bm5.NPV expression system

A series of experiments have been conducted using a recombinant baculovirus/insect cell expression system (Bm5/Bm5.NPV.CAT) to establish the optimum temperature for both cell growth and virus infection. Bm5 cell growth was found to be limited at temperatures below 22°C and ceased completely at temperatures above 34°C. In the range between 24 and 28°C, final cell densities always reached 96% of the highest achievable viable cell density. The shortest population doubling time was obtained at 28°C. Overall, a consistent increase in metabolism with increasing temperatures was observed. During the infection/viral replication phase, an increase in the temperature from 25 to 31°C resulted in a faster decrease in viable cell density and an earlier production of chloramphenicol acetyltransferase (CAT). Furthermore, protein yield at temperatures above 28°C was significantly reduced. Overall, the best temperature for the infection phase for the Bm5/Bm5.NPV expression system was found to be 25°C when the cells are cultured in serum free media.     

SHARED: An information model for cooperative product development

One fundamental issue in developing collaborative engineering systems is the representation of product information which supports communication and coordination. This product information includes not only the geometric and physical properties of the product and its parts, but also information about functions, constraints and the design rationale. In this paper, we describe an information model, SHARED, which was developed for encoding product information in DICE, a distributed and integrated environment for computer-aided engineering. SHARED provides multiple levels of both functional and geometric abstractions, multiple views and techniques for maintaining consistency between the various abstractions and views. These elements are essential for a good representation model of product information. The use of the SHARED model is illustrated through an example, depicting the various representations of a product as it evolves through the design process. The SHARED model has been implemented over a distributed OODBMS as a toolkit/framework for developing environments which need to model, manipulate and communicate product information between distributed cooperating applications, while supporting coordination between them.     

A comparison of statistical relational learning and graph neural networks for aggregate graph queries

Statistical relational learning (SRL) and graph neural networks (GNNs) are two powerful approaches for learning and inference over graphs. Typically, they are evaluated in terms of simple metrics such as accuracy over individual node labels. Complex aggregate graph queries (AGQ) involving multiple nodes, edges, and labels are common in the graph mining community and are used to estimate important network properties such as social cohesion and influence. While graph mining algorithms support AGQs, they typically do not take into account uncertainty, or when they do, make simplifying assumptions and do not build full probabilistic models. In this paper, we examine the performance of SRL and GNNs on AGQs over graphs with partially observed node labels. We show that, not surprisingly, inferring the unobserved node labels as a first step and then evaluating the queries on the fully observed graph can lead to sub-optimal estimates, and that a better approach is to compute these queries as an expectation under the joint distribution. We propose a sampling framework to tractably compute the expected values of AGQs. Motivated by the analysis of subgroup cohesion in social networks, we propose a suite of AGQs that estimate the community structure in graphs. In our empirical evaluation, we show that by estimating these queries as an expectation, SRL-based approaches yield up to a 50-fold reduction in average error when compared to existing GNN-based approaches.

     

AHW-BGOA-DNN: a novel deep learning model for epileptic seizure detection

Neural Computing and Applications - “Brain–Computer Interface” (BCI)—a real-life support system provides a way for epileptic patients to improve their quality of life. In...     

Multipartite entangled magnon states as quantum communication channels

We investigate the entanglement properties of the two magnon states and explicate conditions under which, the two magnon state becomes useful for several quantum communication protocols. We systematically study the temporal behaviour of concurrence to find out the effect of exchange interaction on entanglement. The two magnon state, which is potentially realizable in quantum dots using Heisenberg exchange interaction, is found to be suitable for carrying out deterministic teleportation of an arbitrary two qubit composite system. Further, conditions for which the channel capacity reaches “Holevo bound”, allowing four classical bits to be transmitted through two qubits are derived. Later, an unconventional protocol is given to demonstrate that this state can be used for sharing of a two qubit entangled state among two parties.