A simple strategy for spirocyclopentannullation of cyclic ketones. Formal total synthesis of (+/-)-acorone

A general and simple methodology for spirocyclopentannulation of cyclic ketones (or 4,4-disubstituted cyclopentenones from acyclic ketones) and its application in the synthesis of the spirodienone 7 via a prochiral precursor constituting a formal total synthesis of (+/-)-acorone (6), are described.

Towards the total synthesis of tashironin related allo-cedrane natural products: further exploitation of the oxidative dearomatization-IMDA-RCM triad based strategy

Synthetic studies directed towards allo-cedrane based, tashironin sibling natural products, involving some deft functional group manipulations on a preformed tetracyclic scaffold, are delineated. (C) 2011 Elsevier Ltd. All rights reserved.

Towards building an intelligent decision support system for project management

Management of large projects, especially the ones in which a major component of R&D is involved and those requiring knowledge from diverse specialised and sophisticated fields, may be classified as semi-structured problems. In these problems, there is some knowledge about the nature of the work involved, but there are also uncertainties associated with emerging technologies. In order to draw up a plan and schedule of activities of such a large and complex project, the project manager is faced with a host of complex decisions that he has to take, such as, when to start an activity, for how long the activity is likely to continue, etc. An Intelligent Decision Support System (IDSS) which aids the manager in decision making and drawing up a feasible schedule of activities while taking into consideration the constraints of resources and time, will have a considerable impact on the efficient management of the project. This report discusses the design of an IDSS that helps in project planning phase through the scheduling phase. The IDSS uses a new project scheduling tool, the Project Influence Graph (PIG).

A new strategy for the alpha-vinylation of ketones: Application to an enantioselective synthesis of sesquiterpene (+)-alpha-elemene

A new, simple and preparatively useful protocol for the construction of a-vinyl ketones, particularly those bearing a quaternary carbon centre, from the corresponding alkenes has been devised. Our four-step strategy consists of dichloroketene addition, base catalysed ring contraction to 'push-pull' cyclopropane esters, reduction and eliminative cyclopropane fragmentation to unravel the a-vinyl ketone moiety. The generality of this approach has been demonstrated with a few representative olefins and good regio- and stereocontrol has been observed. As an application of this methodology, an enantioselective synthesis of sesquiterpene hydrocarbon (+)-alpha-elemene (42) from R-(+)-limonene (43) has been accomplished.

Counselling and predictive testing for familial adenomatous polyposis in a rural South Indian community

Background—Mutations of the APC gene cause familial adenomatous polyposis (FAP), a hereditary colorectal cancer predisposition syndrome.Aims—To conduct a cost comparison analysis of predictive genetic testing versus conventional clinical screening for individuals at risk of inheriting FAP, using the perspective of a third party payer. Methods—All direct health care costs for both screening strategies were measured according to time and motion, and the expected costs evaluated using a decision analysis model.Results—The baseline analysis predicted that screening a prototype FAP family would cost $4975/£3109 by molecular testingand $8031/£5019 by clinical screening strategy, when family members were monitored with the same frequency of clinical surveillance (every two to three years). Sensitivity analyses revealed that the genetic testing approach is cost saving for key variables including the kindred size, the age of screening onset, and the cost of mutation identification in a proband. However, if the APC mutation carriers were monitored at an increased (annual) frequency, the cost of the genetic screening strategy increased to $7483/ £4677 and was especially sensitive to variability in age of onset of screening, family size, and cost of genetic testing of at risk relatives. Conclusions—In FAP kindreds, a predictive genetic testing strategy costs less than conventional clinical screening, provided that the frequency of surveillance is identical using either strategy. An additional significant benefit is the elimination of unnecessary colonic examinations for those family members found to be noncarriers.

A reinforcement learning approach to automatic generation control

This paper formulates the automatic generation control (AGC) problem as a stochastic multistage decision problem. A strategy for solving this new AGC problem formulation is presented by using a reinforcement learning (RL) approach This method of obtaining an AGC controller does not depend on any knowledge of the system model and more importantly it admits considerable flexibility in defining the control objective. Two specific RL based AGC algorithms are presented. The first algorithm uses the traditional control objective of limiting area control error (ACE) excursions, where as, in the second algorithm, the controller can restore the load-generation balance by only monitoring deviation in tie line flows and system frequency and it does not need to know or estimate the composite ACE signal as is done by all current approaches. The effectiveness and versatility of the approaches has been demonstrated using a two area AGC model. (C) 2002 Elsevier Science B.V. All rights reserved.

Video coding mode decision as a classification problem

In this paper, we show that it is possible to reduce the complexity of Intra MB coding in H.264/AVC based on a novel chance constrained classifier. Using the pairs of simple mean-variances values, our technique is able to reduce the complexity of Intra MB coding process with a negligible loss in PSNR. We present an alternate approach to address the classification problem which is equivalent to machine learning. Implementation results show that the proposed method reduces encoding time to about 20% of the reference implementation with average loss of 0.05 dB in PSNR.

GyrI: a counter-defensive strategy against proteinaceous inhibitors of DNA gyrase

DNA gyrase is the target of two plasmid-encoded toxins CcdB and microcin B17, which ensure plasmid maintenance. These proteins stabilize gyrase-DNA covalent complexes leading to double-strand breaks in the genome. In contrast, the physiological role of chromosomally encoded inhibitor of DNA gyrase (Gyrl) in Escherichia coli is unclear and its mechanism of inhibition has not been established. We demonstrate that the mode of inhibition of GyrI is distinct from all other gyrase inhibitors. It inhibits DNA gyrase prior to, or at the step of, binding of DNA by the enzyme. Gyrl reduces intrinsic as well as toxin-stabilized gyrase-DNA covalent complexes. Furthermore, Gyri reduces microcin B17-mediated double-strand breaks in vivo, imparting protection to the cells against the toxin, substantiating the in vitro results. Thus, Gyrl is an antidote to DNA gyrase-specific proteinaceous poisons encoded by plasmid addiction systems.

Risk-sensitive optimal control for Markov decision processes with monotone cost

The existence of an optimal feedback law is established for the risk-sensitive optimal control problem with denumerable state space. The main assumptions imposed are irreducibility and a near monotonicity condition on the one-step cost function. A solution can be found constructively using either value iteration or policy iteration under suitable conditions on initial feedback law.

Use of climate information for farm-level decision making: rainfed groundnut in southern India

The production of rainfed crops in semi-arid tropics exhibits large variation in response to the variation in seasonal rainfall. There are several farm-level decisions such as the choice of cropping pattern, whether to invest in fertilizers, pesticides etc., the choice of the period for planting, plant population density etc. for which the appropriate choice (associated with maximum production or minimum risk) depends upon the nature of the rainfall variability or the prediction for a specific year. In this paper, we have addressed the problem of identifying the appropriate strategies for cultivation of rainfed groundnut in the Anantapur region in a semi-arid part of the Indian peninsula. The approach developed involves participatory research with active collaboration with farmers, so that the problems with perceived need are addressed with the modern tools and data sets available. Given the large spatial variation of climate and soil, the appropriate strategies are necessarily location specific. With the approach adopted, it is possible to tap the detailed location specific knowledge of the complex rainfed ecosystem and gain an insight into the variety of options of land use and management practices available to each category of stakeholders. We believe such a participatory approach is essential for identifying strategies that have a favourable cost-benefit ratio over the region considered and hence are associated with a high chance of acceptance by the stakeholders. (C) 2002 Elsevier Science Ltd. All rights reserved.

Role of Management Decision Variables in Determining Technology Progress and Technical Efficiency in Indian Electronic Industry

This paper analyses the influence of management on Technical Efficiency Change (TEC) and Technological Progress (TP) in the communication equipment and consumer electronics sub-sectors of Indian hardware electronics industry. Each sub-sector comprises 13 sample firms for two time periods.The primary objective is to determine the relative contribution of TP and TEC to TFP Growth (TFPG) and to establish the influence of firm specific operational management decision variables on these two components. The study finds that both the sub-sectors have strived and achieved steady TP but not TEC in the period of economic liberalisation to cope with the intensifying competition. The management decisions with respect to asset and profit utilization, vertical integration, among others, improved TP and TE in the sub-sectors. However, R&D investments and technology imports proved costly for TFP indicating inadequate efforts and/or poor resource utilisation by the management. Management was found to be complacent in terms of improving or developing their own technology as indicated by their higher dependence on import of raw materials and no influence of R&D on TP.

Sustainability through remanufacturing in India: a case study on mobile handsets

Remanufacturing activities in India are still in nascent stages. However, the substantial growth of Indian economy, coupled with serious issues of population and environmental burden demands a radical shift in market strategies and legislations. The scattered and inefficient product recovery methods prevalent in India are unable to cope with increasing environmental and economic burden on the society - remanufacturing seems to be a promising strategy to explore for these. Our study investigated from a user's context the opportunity of establishing remanufacturing as a formal activity, answering the fundamental questions of whether remanufactured products would be accepted by Indian consumers and how these will fit into the Indian market. The study of the Indian mobile phone market eco-system showed how mobile phones currently move through the value chain, and the importance of the grey and used phone markets in this movement. A prescriptive model has been proposed which utilizes the usage patterns of different consumer groups to create a self-sustainable demand-supply system, potentially complementing frameworks such as the Automotive Remanufacturing Decision-Making Framework (RDMF). (C) 2011 Elsevier Ltd. All rights reserved.

Solar energy decision support system

Energy plays a prominent role in human society. As a result of technological and industrial development,the demand for energy is rapidly increasing. Existing power sources that are mainly fossil fuel based are leaving an unacceptable legacy of waste and pollution apart from diminishing stock of fuels.Hence, the focus is now shifted to large-scale propagation of renewable energy. Renewable energy technologies are clean sources of energy that have a much lower environmental impact than conventional energy technologies. Solar energy is one such renewable energy. Most renewable energy comes either directly or indirectly from the sun. Estimation of solar energy potential of a region requires detailed solar radiation climatology, and it is necessary to collect extensive radiation data of high accuracy covering all climatic zones of the region. In this regard, a decision support system (DSS)would help in estimating solar energy potential considering the region’s energy requirement.This article explains the design and implementation of DSS for assessment of solar energy. The DSS with executive information systems and reporting tools helps to tap vast data resources and deliver information. The main hypothesis is that this tool can be used to form a core of practical methodology that will result in more resilient in time and can be used by decision-making bodies to assess various scenarios. It also offers means of entering, accessing, and interpreting the information for the purpose of sound decision making.

Geographic Resources Decision Support System – an Open Source GIS

Fully structured and matured open source spatial and temporal analysis technology seems to be the official carrier of the future for planning of the natural resources especially in the developing nations. This technology has gained enormous momentum because of technical superiority, affordability and ability to join expertise from all sections of the society. Sustainable development of a region depends on the integrated planning approaches adopted in decision making which requires timely and accurate spatial data. With the increased developmental programmes, the need for appropriate decision support system has increased in order to analyse and visualise the decisions associated with spatial and temporal aspects of natural resources. In this regard Geographic Information System (GIS) along with remote sensing data support the applications that involve spatial and temporal analysis on digital thematic maps and the remotely sensed images. Open source GIS would help in wide scale applications involving decisions at various hierarchical levels (for example from village panchayat to planning commission) on economic viability, social acceptance apart from technical feasibility. GRASS (Geographic Resources Analysis Support System, http://wgbis.ces.iisc.ernet.in/grass) is an open source GIS that works on Linux platform (freeware), but most of the applications are in command line argument, necessitating a user friendly and cost effective graphical user interface (GUI). Keeping these aspects in mind, Geographic Resources Decision Support System (GRDSS) has been developed with functionality such as raster, topological vector, image processing, statistical analysis, geographical analysis, graphics production, etc. This operates through a GUI developed in Tcltk (Tool command language / Tool kit) under Linux as well as with a shell in X-Windows. GRDSS include options such as Import /Export of different data formats, Display, Digital Image processing, Map editing, Raster Analysis, Vector Analysis, Point Analysis, Spatial Query, which are required for regional planning such as watershed Analysis, Landscape Analysis etc. This is customised to Indian context with an option to extract individual band from the IRS (Indian Remote Sensing Satellites) data, which is in BIL (Band Interleaved by Lines) format. The integration of PostgreSQL (a freeware) in GRDSS aids as an efficient database management system.

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.