Studies on the interaction of concanavalin A with glycoproteins

Lectins (phytohaemagglutinin) are known to have the unique property of binding with certain specific sugars, polysaccharides and glycoproteins. Although the kinetics of interaction between lectins and sugar have been extensively studied, the binding characteristics of the lectins with various glycoproteins are not well understood. In this laboratory a systematic study has been initiated in relation to the interaction of lectins with glycoproteins. Concanavalin A is known to bind alpha-glucosides, mannosides and biopolymers having these sugar configurations. A galactose binding protein from caster bean has been purified to homogeneity and was found to contain mannose. This lectin was used as the source of glycoprotein for studying its interaction with concanavalin A. This study showed that the interaction is temperature dependent and the dissociation is time and alpha-methyl glucoside concentration dependent. This has led to speculate a model for cell-lectin interaction. Using concanavalin A it has been shown that all the lysosomal enzymes from brain studied were glycoprotein in nature. Moreover, using Sepharose-bound concanavalin A it has been possible to devise a method by which these lysosomal enzymes could be purified considerably. With the knowledge that the interaction between lectin and glycoprotein is not only dependent on the specific sugar present in the glycoprotein, but also on the nature of the glycoprotein it was possible to develop a novel method for immobilizing various glycoprotein enzymes, such as arylsulphatase A, hyaluronidase and glucose oxidase.

A questioning based method to automatically acquire expert assembly diagnostic knowledge

In the domain of manual mechanical assembly, expert knowledge is an important means of supporting assembly planning that leads to fewer issues during actual assembly. Knowledge based systems can be used to provide assembly planners with expert knowledge as advice. However, acquisition of knowledge remains a difficult task to automate, while manual acquisition is tedious, time-consuming, and requires engagement of knowledge engineers with specialist knowledge to understand and translate expert knowledge. This paper describes the development, implementation and preliminary evaluation of a method that asks a series of questions to an expert, so as to automatically acquire necessary diagnostic and remedial knowledge as rules for use in a knowledge based system for advising assembly planners diagnose and resolve issues. The method, called a questioning procedure, organizes its questions around an assembly situation which it presents to the expert as the context, and adapts its questions based on the answers it receives from the expert. (C) 2014 Elsevier Ltd. All rights reserved.

Preparative solid state chemistry. Recent developments

A survey of recent developments in preparative solid state chemistry shows that, with a knowledge of structural chemistry and reactivity patterns of solids, it is possible to synthesize a variety of new solids possessing novel structures. A distinction is made between synthesis ofnew solids and synthesis of solids bynew methods. Three new routes to solid state synthesis are recognized: the precursor method, and topochemical methods involving redox and ion-exchange reactions. The low-temperature topochemical methods enable synthesis of metastable phases that are inaccessible by the high temperature route. Several illustrative examples of solid state synthesis from the recent literature are presented.

WEPA: Wind energy potential assessment-spatial decision support system

Spatial Decision Support System (SDSS) assist in strategic decision-making activities considering spatial and temporal variables, which help in Regional planning. WEPA is a SDSS designed for assessment of wind potential spatially. A wind energy system transforms the kinetic energy of the wind into mechanical or electrical energy that can be harnessed for practical use. Wind energy can diversify the economies of rural communities, adding to the tax base and providing new types of income. Wind turbines can add a new source of property value in rural areas that have a hard time attracting new industry. Wind speed is extremely important parameter for assessing the amount of energy a wind turbine can convert to electricity: The energy content of the wind varies with the cube (the third power) of the average wind speed. Estimation of the wind power potential for a site is the most important requirement for selecting a site for the installation of a wind electric generator and evaluating projects in economic terms. It is based on data of the wind frequency distribution at the site, which are collected from a meteorological mast consisting of wind anemometer and a wind vane and spatial parameters (like area available for setting up wind farm, landscape, etc.). The wind resource is governed by the climatology of the region concerned and has large variability with reference to space (spatial expanse) and time (season) at any fixed location. Hence the need to conduct wind resource surveys and spatial analysis constitute vital components in programs for exploiting wind energy. SDSS for assessing wind potential of a region / location is designed with user friendly GUI’s (Graphic User Interface) using VB as front end with MS Access database (backend). Validation and pilot testing of WEPA SDSS has been done with the data collected for 45 locations in Karnataka based on primary data at selected locations and data collected from the meteorological observatories of the India Meteorological Department (IMD). Wind energy and its characteristics have been analysed for these locations to generate user-friendly reports and spatial maps. Energy Pattern Factor (EPF) and Power Densities are computed for sites with hourly wind data. With the knowledge of EPF and mean wind speed, mean power density is computed for the locations with only monthly data. Wind energy conversion systems would be most effective in these locations during May to August. The analyses show that coastal and dry arid zones in Karnataka have good wind potential, which if exploited would help local industries, coconut and areca plantations, and agriculture. Pre-monsoon availability of wind energy would help in irrigating these orchards, making wind energy a desirable alternative.

Mathematical Analysis of Sensor Fusion for Intrusion Detection Systems

Fusion of multiple intrusion detection systems results in a more reliable and accurate detection for a wider class of intrusions. The paper presented here introduces the mathematical basis for sensor fusion and provides enough support for the acceptability of sensor fusion in performance enhancement of intrusion detection systems. The sensor fusion system is characterized and modeled with no knowledge of the intrusion detection systems and the intrusion detection data. The theoretical analysis is supported with an experimental illustration with three of the available intrusion detection systems using the DARPA 1999 evaluation data set.

On guessing the realization of an arbitrarily varying source

We present a method to guess the realization of an arbitrarily varying source. Let TU be the type of the unknown state sequence. Our method results in a guessing moment that is within Kn (TU) + O(log n=n) of the minimum attainable guessing moment with full knowledge of source statistics, i.e., with knowledge of the sequence of states sn. The quantity Kn (TU) + O(log n=n) can be interpreted as the penalty one pays for not knowing the sequence of states sn of the source. Kn (TU) by itself is the penalty one pays for guessing with the additional knowledge that the state sequence belongs to type TU. Conversely, given any guessing strategy, for every type TU, there is a state sequence belonging to this type whose corresponding source forces a guessing moment penalty of at least Kn (TU) ¡ O(log n=n).

Synthesis of pure iron magnetic nanoparticles in large quantity

Free nanoparticles of iron (Fe) and their colloids with high saturation magnetization are in demand for medical and microfluidic applications. However, the oxide layer that forms during processing has made such synthesis a formidable challenge. Lowering the synthesis temperature decreases rate of oxidation and hence provides a new way of producing pure metallic nanoparticles prone to oxidation in bulk amount (large quantity). In this paper we have proposed a methodology that is designed with the knowledge of thermodynamic imperatives of oxidation to obtain almost oxygen-free iron nanoparticles, with or without any organic capping by controlled milling at low temperatures in a specially designed high-energy ball mill with the possibility of bulk production. The particles can be ultrasonicated to produce colloids and can be bio-capped to produce transparent solution. The magnetic properties of these nanoparticles confirm their superiority for possible biomedical and other applications.

PMV model is insufficient to capture subjective thermal response from Indians

A controlled laboratory experiment was carried out on forty Indian male college students for evaluating the effect of indoor thermal environment on occupants' response and thermal comfort. During experiment, indoor temperature varied from 21 degrees C to 33 degrees C, and the variables like relative humidity, airflow, air temperature and radiant temperature were recorded along with subject's physiological parameters (skin (T-sk) and oral temperature (T-c)) and subjective thermal sensation responses (TSV). From T-sk and T-c, body temperature (T-b) was evaluated. Subjective Thermal Sensation Vote (TSV) was recorded using ASHRAE 7-point scale. In PMV model, Fanger's T-sk equation was used to accommodate adaptive response. Step-wise regression analysis result showed T-b was better predictor of TSV than T-sk and T-c. Regional skin temperature response, suppressed sweating without dipping, lower sweating threshold temperature and higher cutaneous threshold for sweating were observed as thermal adaptive responses. These adaptive responses cannot be considered in PMV model. To incorporate subjective adaptive response, mean skin temperature (T-sk) is considered in dry heat loss calculation. Along with these, PMV-model and other two methodologies are adopted to calculate PMV values and results are compared. However, recent literature is limited to measure the sweat rate in Indians and consideration of constant Ersw in PMV model needs to be corrected. Using measured T-sk in PMV model (Method(1)), thermal comfort zone corresponding to 0.5 <= PMV <= 0.5 was evaluated as (22.46-25.41) degrees C with neutral temperature of 23.91 degrees C, similarly while using TSV response, wider comfort zone was estimated as (23.25-26.32) degrees C with neutral temperature at 24.83 degrees C, which was further increased to with TSV-PPDnew, relation. It was observed that PMV-model overestimated the actual thermal response. Interestingly, these subjects were found to be less sensitive to hot but more sensitive to cold. A new TSV-PPD relation (PPDnew) was obtained from the population distribution of TSV response with an asymmetric distribution of hot-cold thermal sensation response from Indians. The calculations of human thermal stress according to steady state energy balance models used on PMV model seem to be inadequate to evaluate human thermal sensation of Indians. Relevance to industry: The purpose of this paper is to estimate thermal comfort zone and optimum temperature for Indians. It also highlights that PMV model seems to be inadequate to evaluate subjective thermal perception in Indians. These results can be used in feedback control of HVAC systems in residential and industrial buildings. (C) 2014 Elsevier B.V. All rights reserved.