Effects of chloroquine treatment on antioxidant enzymes in rat liver and kidney

The effect of chloroquine (CHQ) administration on antioxidant enzymes in rat liver and kidney was studied. Male Sprague-Dawley rats were administered 20 mg/kg CHQ once a week for 4 weeks (chronic treatment) or a single dose at 10 or 20 mg/kg (acute treatment). Antioxidant enzyme activities were determined in cytosolic fractions of liver and kidney, whereas reduced glutathione (GSH) and malondialdehyde (MDA) were determined in tissue samples. Results indicate minimal effects of acute CHQ treatment, whereas chronic treatment with CHQ differentially affected antioxidant enzymes in the two organs. Superoxide dismutase activity was increased nearly twofold, while activities of selenium glutathione peroxidase (GPX), catalase, and NAD (P) H: quinone oxidoreductase were decreased in livers of CHQ-treated rats compared to controls. No significant effects of CHQ on glutathione reductase, GSH, and MDA levels were seen in the liver. Fewer effects of CHQ were observed in the kidney where a decrease in GPX activity and an increase in MDA levels was seen. Lowering of antioxidant enzymes activities in the liver by CHQ could render the organ more susceptible to subsequent oxidative stress; while increased MDA production after CHQ treatment in the kidney indicate that the organ is being subjected to oxidative stress. This could have implications for prolonged chloroquine intake.     

Prediction of thermal expansion coefficients of plain weave fabric composites

Three plain weave fabric composite analysis models are presented for the prediction of the on-axes thermal expansion coefficients. These are two-dimensional models in the sense that the actual strand cross-sectional geometry, strand undulation and the presence of a gap between the adjacent strands are taken into account. In the first two models, termed refined models, the representative unit cell is discretised into slices and elements and analysed. In the third method, a closed-form solution is presented. In this case, the representative unit cell is idealised as a crossply laminate and analysed. The relative merits and demerits of the models are also discussed. The predicted results are compared with the experimental values. A good correlation is observed.     

Influence of additives on electrodeposition of bright Zn-Ni alloy on mild steel from acid sulphate bath

The influence of a condensation product (CP) of veratraldehyde (VRTD) and p-amino benzoic acid (PABA) on Zn-Ni alloy electrodeposited onto mild steel was studied in acidic sulphate solutions. Ethylenediaminetetraaceticacid (EDTA) and cetyltrimethylammoniumbromide (CTAB) were used as complexing and wetting agents, respectively. The effect of bath constituents, pH, current density and temperature on nature of deposit were studied through Hull cell experiments. The bath constituents and operating parameters were optimized. Deposit properties and corrosion resistance were discussed. Throwing power, current efficiency and polarization studies were carried out. SEM photomicrographs of the deposit obtained from optimum bath revealed fine-grained deposit of the alloy in the presence of condensation product and hence modified the morphology of zinc-nickel alloy deposit. IR spectrum of the scrapped deposit showed inclusion of addition agent.     

Efficient computation of unique input/output sequences in finitestate machines

This paper makes two contributions toward computing unique input/output (UIO) sequences in finite-state machines. Our first contribution is to compute all UIO sequences of minimal lengths in a finite-state machine. Our second contribution is to present a generally efficient algorithm to compute a UIO sequence for each state, if it exists. We begin by defining a path vector, vector perturbation, and UIO tree. The perturbation process allows us to construct the complete UIO tree for a machine. Each sequence of input/output from the initial vector of a UIO tree to a singleton vector represents a UIO sequence. Next, we define the idea of an inference rule that allows us to infer UIO sequences of a number of states from the UIO sequence of some state. That is, for a large class of machines, it is possible to compute UIO sequences for all possible states from a small set of initial UIOs. We give a modified depth-first algorithm, called the hybrid approach, that computes a partial UIO tree, called an essential subtree, from which UIO sequences of all possible states can be inferred. Using the concept of projection machines, we show that sometimes it is unnecessary to construct even a partial subtree. We prove that if a machine remains strongly connected after deleting all the converging transitions, then all of the states have UIO sequences. To demonstrate the effectiveness of our approach, we develop a tool to perform experiments using both small and large machines     

Gradient Boundary Detection for Time Series Snapshot Construction in Sensor Networks

In many applications of sensor networks, the sink needs to keep track of the history of sensed data of a monitored region for scientific analysis or supporting historical queries. We call these historical data a time series of value distributions or snapshots. Obviously, to build the time series snapshots by requiring all of the sensors to transmit their data to the sink periodically is not energy efficient. In this paper, we introduce the idea of gradient boundary and propose the gradient boundary detection (GBD) algorithm to construct these time series snapshots of a monitored region. In GBD, a monitored region is partitioned into a set of subregions and all sensed data in one subregion are within a predefined value range, namely, the gradient interval. Sensors located on the boundaries of the subregions are required to transmit the data to the sink and, then, the sink recovers all subregions to construct snapshots of the monitored area. In this process, only the boundary sensors transmit their data and, therefore, energy consumption is greatly reduced. The simulation results show that GBD is able to build snapshots with a comparable accuracy and has up to 40 percent energy savings compared with the existing approaches for large gradient intervals.     

Mesoporous silica with short-range MFI structure

A new type of mesoporous silica has been prepared which showed 780 m²/g of BET surface area and 0.6 ml/g of primary mesopores narrowly distributed around 4.2 nm. More importantly however, is that it showed short-range zeolite crystallinity as demonstrated by FTIR and XRD analysis, and hydrophobicity as demonstrated by water and n-hexane adsorption.

This material was synthesized via a dual-template, three-step hydrothermal–flocculation–steaming synthesis procedure developed by us recently. Briefly, MFI nanoprecursors (NPs) were first prepared by a low-temperature hydrothermal step using TPAOH as template for zeolite structure, and then flocculated using a surfactant that served as the template for the mesopores. The collected NPs are mesoporous silica exhibiting short-range MFI domains when directly calcined. However, the steaming step promoted the crystallization of the NPs and created uniform mesopores. It was found that almost every detail in these procedures affected the properties of the final product. The most important variables, however, were identified as the duration the flocculants were kept in contact with the liquid phase, and the humidity under which the steaming was conducted. By properly adjusting the procedures, the said mesoporous silica, as well as nanocrystals having high external surface area, could be produced at will.     

Biodiesel development from high acid value polanga seed oil and performance evaluation in a CI engine

Non-edible filtered high viscous (72 cSt at 40 °C) and high acid value (44 mg KOH/gm) polanga (Calophyllum inophyllum L.) oil based mono esters (biodiesel) produced by triple stage transesterification process and blended with high speed diesel (HSD) were tested for their use as a substitute fuel of diesel in a single cylinder diesel engine. HSD and polanga oil methyl ester (POME) fuel blends (20%, 40%, 60%, 80%, and 100%) were used for conducting the short-term engine performance tests at varying loads (0%, 20%, 40%, 60%, 80%, and 100%). Tests were carried out over entire range of engine operation at varying conditions of speed and load. The brake specific fuel consumption (BSFC) and brake thermal efficiency (BTE) were calculated from the recorded data. The engine performance parameters such as fuel consumption, thermal efficiency, exhaust gas temperature and exhaust emissions (CO, CO₂, HC, NO_x, and O₂) were recorded. The optimum engine operating condition based on lower brake specific fuel consumption and higher brake thermal efficiency was observed at 100% load for neat biodiesel. From emission point of view the neat POME was found to be the best fuel as it showed lesser exhaust emission as compared to HSD.     

Extreme learning machine and bayesian optimization-driven intelligent framework for IoMT cyber-attack detection

The Journal of Supercomputing - The Internet of Medical Things (IoMT) is a bionetwork of allied medical devices, sensors, wearable biosensor devices, etc. It is gradually reforming the healthcare...     

33.7 MHz heavy-ion radio frequency quadrupole linac at VECC Kolkata

A 33.7 MHz heavy-ion radio frequency quadrupole (RFQ) linear accelerator has been designed, built, and tested. It is a four-rod-type RFQ designed for acceleration of 1.38 keVu, qA> or =116 ions to about 29 keVu. Transmission efficiencies of about 85% and 80% have been measured for the unanalyzed and analyzed beams, respectively, of oxygen ((16)O(2+), (16)O(3+), (16)O(4+)), nitrogen ((14)N(3+), (14)N(4+)), and argon ((40)Ar(4+)). The system design and measurements along with results of beam acceleration test will be presented.