A detailed study of Li-DNA fibres at various salt concentrations reveals a non-helical B-DNA and a possible similarity of solution and solid state structures

A thorough investigation of salt concentration dependence of lithium DNA fibres is made using X-ray diffraction. While for low salt the C-form pattern is obtained, crystalline B-type diffraction patterns result on increasing the salt concentration. The salt content in the gel (from which fibres are drawn) is estimated by equilibrium dialysis using the Donnan equilibrium principle. The salt range giving the best crystalline B pattern is determined. It is found that in this range meridional reflections occur on the fourth and sixth layer lines. In addition, the tenth layer meridian is absent at a particular salt concentration. These results strongly suggest the presence of non-helical features in the DNA molecule. Preliminary analysis of the diffraction patterns indicates a structural variability within the B-form itself. Further, the possibility of the structural parameters of DNA being similar in solid state and in solution is discussed.

A solution framework for scheduling a BPM with non-identical job dimensions

A Batch Processing Machine (BPM) is one which processes a number of jobs simultaneously as a batch with common beginning and ending times. Also, a BPM, once started cannot be interrupted in between (Pre-emption not allowed). This research is motivated by a BPM in steel casting industry. There are three main stages in any steel casting industry viz., pre-casting stage, casting stage and post-casting stage. A quick overview of the entire process, is shown in Figure 1. There are two BPMs : (1) Melting furnace in the pre-casting stage and (2) Heat Treatment Furnace (HTF) in the post casting stage of steel casting manufacturing process. This study focuses on scheduling the latter, namely HTF. Heat-treatment operation is one of the most important stages of steel casting industries. It determines the final properties that enable components to perform under demanding service conditions such as large mechanical load, high temperature and anti-corrosive processing. In general, different types of castings have to undergo more than one type of heat-treatment operations, where the total heat-treatment processing times change. To have a better control, castings are primarily classified into a number of job-families based on the alloy type such as low-alloy castings and high alloy castings. For technical reasons such as type of alloy, temperature level and the expected combination of heat-treatment operations, the castings from different families can not be processed together in the same batch.

Performance evaluation of elitist-mutated multi-objective particle swarm optimization for integrated water resources management

Optimal allocation of water resources for various stakeholders often involves considerable complexity with several conflicting goals, which often leads to multi-objective optimization. In aid of effective decision-making to the water managers, apart from developing effective multi-objective mathematical models, there is a greater necessity of providing efficient Pareto optimal solutions to the real world problems. This study proposes a swarm-intelligence-based multi-objective technique, namely the elitist-mutated multi-objective particle swarm optimization technique (EM-MOPSO), for arriving at efficient Pareto optimal solutions to the multi-objective water resource management problems. The EM-MOPSO technique is applied to a case study of the multi-objective reservoir operation problem. The model performance is evaluated by comparing with results of a non-dominated sorting genetic algorithm (NSGA-II) model, and it is found that the EM-MOPSO method results in better performance. The developed method can be used as an effective aid for multi-objective decision-making in integrated water resource management.

Minimizing total weighted tardiness on a batch-processing machine with non-agreeable release times and due dates

This study considers the scheduling problem observed in the burn-in operation of semiconductor final testing, where jobs are associated with release times, due dates, processing times, sizes, and non-agreeable release times and due dates. The burn-in oven is modeled as a batch-processing machine which can process a batch of several jobs as long as the total sizes of the jobs do not exceed the machine capacity and the processing time of a batch is equal to the longest time among all the jobs in the batch. Due to the importance of on-time delivery in semiconductor manufacturing, the objective measure of this problem is to minimize total weighted tardiness. We have formulated the scheduling problem into an integer linear programming model and empirically show its computational intractability. Due to the computational intractability, we propose a few simple greedy heuristic algorithms and meta-heuristic algorithm, simulated annealing (SA). A series of computational experiments are conducted to evaluate the performance of the proposed heuristic algorithms in comparison with exact solution on various small-size problem instances and in comparison with estimated optimal solution on various real-life large size problem instances. The computational results show that the SA algorithm, with initial solution obtained using our own proposed greedy heuristic algorithm, consistently finds a robust solution in a reasonable amount of computation time.

Scheduling a Burn-In Oven with Non-Agreeable Release Times and Due Dates

We consider the problem of scheduling semiconductor burn-in operations, where burn-in ovens are modelled as batch processing machines. Most of the studies assume that ready times and due dates of jobs are agreeable (i.e., ri < rj implies di ≤ dj). In many real world applications, the agreeable property assumption does not hold. Therefore, in this paper, scheduling of a single burn-in oven with non-agreeable release times and due dates along with non-identical job sizes as well as non-identical processing of time problem is formulated as a Non-Linear (0-1) Integer Programming optimisation problem. The objective measure of the problem is minimising the maximum completion time (makespan) of all jobs. Due to computational intractability, we have proposed four variants of a two-phase greedy heuristic algorithm. Computational experiments indicate that two out of four proposed algorithms have excellent average performance and also capable of solving any large-scale real life problems with a relatively low computational effort on a Pentium IV computer.

Assessment of estrus cyclicity in the Asian elephant (Elephas maximus) by measurement of fecal progesterone metabolite 5 alpha-P-3OH, using a non-invasive assay

Reproductive management of the Asian elephant (Elephas maximus) is important for its conservation. To monitor its estrous cyclicity, we earlier used an indirect ELISA to show that levels of fecal progesterone (P(4))-metabolite (allopregnanolone: 5 alpha-P-3OH) in semi-captive females sampled randomly positively correlated with serum P(4) levels [12]. In this longitudinal study (51 weeks), we measured levels of fecal 5 alpha-P-3OH and serum P(4) in seven semi-captive female elephants. Females exhibited three types of hormonal profiles. Four females showed cyclical patterns of fecal 5 alpha-P-3OH and serum P(4) typical of normal estrous cycles, two showed acyclic pattern while one showed high values indicative of a pregnant animal. Values for anestrous or follicular phases were <= 0.3 mu g g(-1), (5 alpha-P-3OH) and <= 0.3 ng mL(-1) (P(4)); for luteal phase 0.32-11.09 mu g g(-1) (5 alpha-P-3OH) and 0.32-1.48 ng mL(-1) (P(4)); for pregnancy 1.41-7.38 mu g g(-1) (5 alpha-P-3OH) and 0.39-1.6 ng mL(-1) (R(4)). A positive correlation (t = 8.8, p < 0.01, n = 321) between levels of fecal 5 alpha-P-3OH and serum P4 was observed. A random sample of 30 free-ranging female elephants showed fecal 5 alpha-P-3OH values of 0.06-23.4 mu g g(-1), indicating them to be in different stages of estrous cyclicity. This study is the first to assess the reproductive phases of female Asian elephants based on the correlative-patterns of both the fecal 5 alpha-P-3OH and serum P(4) values over multiple estrous cycles. This has a potential application in the reproductive management and conservation of Asian elephants. (C) 2011 Elsevier Inc. All rights reserved.

Thermal management using the bi-disperse porous medium approach

Thermal management of distributed electronics similar to data centers is studied using a bi-disperse porous medium (BDPM) approach. The BDPM channel comprises heat generating micro-porous square blocks, separated by macro-pores. Laminar forced convection cooling fluid of Pr = 0.7 saturates both the micro- and macro-pores. Bi-dispersion effect is induced by varying the macro-pore volume fraction phi(E), and by changing the number of porous blocks N-2, both representing re-distribution of the electronics. When 0.2 <= phi(E) <= 0.86, the heat transfer No is enhanced twice (from similar to 550 to similar to 1100) while the pressure drop Delta p* reduces almost eightfold. For phi(E) < 0.5, No reduces quickly to reach a minimum at the mono -disperse porous medium (MDPM) limit (phi(E) -> 0). Compared to N-2 = 1 case, No for BDPM configuration is high when N-2 >> 1, i.e., the micro-porous blocks are many and well distributed. The Nu increase with Re changes from non-linear to linear as N-2 increases from 1 to 81, with corresponding insignificant pumping power increase. (C) 2011 Elsevier Ltd. All rights reserved.

A non-syntactic approach for text sentiment classification with stopwords

The present approach uses stopwords and the gaps that oc- cur between successive stopwords –formed by contentwords– as features for sentiment classification.

Forest area estimation and reporting: implications for conservation, management and REDD

Periodic estimation, monitoring and reporting on area under forest and plantation types and afforestation rates are critical to forest and biodiversity conservation, sustainable forest management and for meeting international commitments. This article is aimed at assessing the adequacy of the current monitoring and reporting approach adopted in India in the context of new challenges of conservation and reporting to international conventions and agencies. The analysis shows that the current mode of monitoring and reporting of forest area is inadequate to meet the national and international requirements. India could be potentially over-reporting the area under forests by including many non-forest tree categories such as commercial plantations of coconut, cashew, coffee and rubber, and fruit orchards. India may also be under-reporting deforestation by reporting only gross forest area at the state and national levels. There is a need for monitoring and reporting of forest cover, deforestation and afforestation rates according to categories such as (i) natural/primary forest, (ii) secondary/degraded forests, (iii) forest plantations, (iv) commercial plantations, (v) fruit orchards and (vi) scattered trees.

What Drives Venture Capital Fundraising in India: An Empirical Analysis of Systematic and Non-Systematic Factors

In this paper, we develop a consolidated Supply-Demand framework of the Venture Capital (VC) ecosystem for India. Further, we empirically analyze the supply side of this ecosystem to ascertain the influence of systematic (macro) and non-systematic (micro) factors on VC fundraising. At the macro level, our results indicate that relatively strong fundamentals of the Indian economy in the past decade as compared with the severe recessionary tendencies in the developed economies have been critical in determining the aggregate volume of VC fundraising. Among the micro factors, past performance and reputation of the individual fund managers have been instrumental in determining their fund raising potential.

Design and Testing of a Control System for Supply Side Electrical Load Management

India's energy demand is increasing rapidly with the intensive growth of economy. The electricity demand in India exceeded the availability, both in terms of base load energy and peak availability. The efficient use of energy source and its conversion and utilizations are the viable alternatives available to the utilities or industry. There are essentially two approaches to electrical energy management. First at the supply / utility end (Supply Side Management or SSM) and the other at the consumer end (Demand Side Management or DSM). This work is based on Supply Side Management (SSM) protocol and consists of design, fabrication and testing of a control device that will be able to automatically regulate the power flow to an individual consumer's premise. This control device can monitor the overuse of electricity (above the connected load or contracted demand) by the individual consumers. The present project work specially emphasizes on contract demand of every consumer and tries to reduce the use beyond the contract demand. This control unit design includes both software and hardware work and designed for 0.5 kW contract demand. The device is tested in laboratory and reveals its potential use in the field.