Holistic Schema Mappings for XML-on-RDBMS

When hosting XML information on relational backends, a mapping has to be established between the schemas of the information source and the target storage repositories. A rich body of recent literature exists for mapping isolated components of XML Schema to their relational counterparts, especially with regard to table configurations. In this paper, we present the Elixir system for designing industrial-strength mappings for real-world applications. Specifically, it produces an information-preserving holistic mapping that transforms the complete XML world-view (XML schema with constraints, XML documents XQuery queries including triggers and views) into a full-scale relational mapping (table definitions, integrity constraints, indices, triggers and views) that is tuned to the application workload. A key design feature of Elixir is that it performs all its mapping-related optimizations in the XML source space, rather than in the relational target space. Further, unlike the XML mapping tools of commercial database systems, which rely heavily on user inputs, Elixir takes a principled cost-based approach to automatically find an efficient relational mapping. A prototype of Elixir is operational and we quantitatively demonstrate its functionality and efficacy on a variety of real-life XML schemas.

Holistic Measures for Evaluating Prediction Models in Smart Grids

The performance of prediction models is often based on ``abstract metrics'' that estimate the model's ability to limit residual errors between the observed and predicted values. However, meaningful evaluation and selection of prediction models for end-user domains requires holistic and application-sensitive performance measures. Inspired by energy consumption prediction models used in the emerging ``big data'' domain of Smart Power Grids, we propose a suite of performance measures to rationally compare models along the dimensions of scale independence, reliability, volatility and cost. We include both application independent and dependent measures, the latter parameterized to allow customization by domain experts to fit their scenario. While our measures are generalizable to other domains, we offer an empirical analysis using real energy use data for three Smart Grid applications: planning, customer education and demand response, which are relevant for energy sustainability. Our results underscore the value of the proposed measures to offer a deeper insight into models' behavior and their impact on real applications, which benefit both data mining researchers and practitioners.

Computational systems approach for drug target discovery

Importance of the field: The shift in focus from ligand based design approaches to target based discovery over the last two to three decades has been a major milestone in drug discovery research. Currently, it is witnessing another major paradigm shift by leaning towards the holistic systems based approaches rather the reductionist single molecule based methods. The effect of this new trend is likely to be felt strongly in terms of new strategies for therapeutic intervention, new targets individually and in combinations, and design of specific and safer drugs. Computational modeling and simulation form important constituents of new-age biology because they are essential to comprehend the large-scale data generated by high-throughput experiments and to generate hypotheses, which are typically iterated with experimental validation. Areas covered in this review: This review focuses on the repertoire of systems-level computational approaches currently available for target identification. The review starts with a discussion on levels of abstraction of biological systems and describes different modeling methodologies that are available for this purpose. The review then focuses on how such modeling and simulations can be applied for drug target discovery. Finally, it discusses methods for studying other important issues such as understanding targetability, identifying target combinations and predicting drug resistance, and considering them during the target identification stage itself. What the reader will gain: The reader will get an account of the various approaches for target discovery and the need for systems approaches, followed by an overview of the different modeling and simulation approaches that have been developed. An idea of the promise and limitations of the various approaches and perspectives for future development will also be obtained. Take home message: Systems thinking has now come of age enabling a `bird's eye view' of the biological systems under study, at the same time allowing us to `zoom in', where necessary, for a detailed description of individual components. A number of different methods available for computational modeling and simulation of biological systems can be used effectively for drug target discovery.

Image fusion in GRDSS for Land use Mapping

Image fusion techniques are useful to integrate the geometric detail of a high-resolution panchromatic (PAN) image and the spectral information of a low-resolution multispectral (MSS) image, particularly important for understanding land use dynamics at larger scale (1:25000 or lower), which is required by the decision makers to adopt holistic approaches for regional planning. Fused images can extract features from source images and provide more information than one scene of MSS image. High spectral resolution aids in identification of objects more distinctly while high spatial resolution allows locating the objects more clearly. The geoinformatics technologies with an ability to provide high-spatial-spectral-resolution data helps in inventorying, mapping, monitoring and sustainable management of natural resources. Fusion module in GRDSS, taking into consideration the limitations in spatial resolution of MSS data and spectral resolution of PAN data, provide high-spatial-spectral-resolution remote sensing images required for land use mapping on regional scale. GRDSS is a freeware GIS Graphic User Interface (GUI) developed in Tcl/Tk is based on command line arguments of GRASS (Geographic Resources Analysis Support System) with the functionalities for raster analysis, vector analysis, site analysis, image processing, modeling and graphics visualization. It has the capabilities to capture, store, process, analyse, prioritize and display spatial and temporal data.

Present status of Gottigere Tank : Indicator of Decision maker’s apathy

Gottigere lake with a water spread area of about 14.98 ha is located in the Bellandur Lake catchment of the South Pennar River basin. In recent years, this lake catchment has been subjected to environmental stress mainly due to the rampant unplanned developmental activities in the catchment. The functional ability of the ecosystem is impaired due to structural changes in the ecosystem. This is evident from poor water quality, breeding of disease vectors, contamination of groundwater in the catchment, frequent flooding in the catchment due to topography alteration, decline in groundwater table, erosion in lake bed, etc. The development plans of the region (current as well as the proposed) ignore the integrated planning approaches considering all components of the ecosystem. Serious threats to the sustainability of the region due to lack of holistic approaches in aquatic resources management are land use changes (removal of vegetation cover, etc.), point and non-point sources of pollution impairing water quality, dumping of solid waste (building waste, etc.). Conservation of lake ecosystem is possible only when the physical and chemical integrity of its catchment is maintained. Alteration in the catchment either due to land use changes (leading to paved surface area from vegetation cover), alteration in topography, construction of roads in the immediate vicinity are detrimental to water yield in the catchment and hence, the sustenance of the lake. Open spaces in the form of lakes and parks aid as kidney and lung in an urban ecosystem, which maintain the health of the people residing in the locality. Identification of core buffer zones and conservation of buffer zones (500 to 1000 m from shore) is to be taken up on priority for conservation and sustainable management of Bangalore lakes. Bangalore is located over a ridge delineating four watersheds, viz. Hebbal, Koramangala, Challaghatta and Vrishabhavathi. Lakes and tanks are an integral part of natural drainage and help in retaining water during rainfall, which otherwise get drained off as flash floods. Each lake harvests rainwater from its catchment and surplus flows downstream spilling into the next lake in the chain. The topography of Bangalore has uniquely supported the creation of a large number of lakes. These lakes form chains, being a series of impoundments across streams. This emphasises the interconnectivity among Bangalore lakes, which has to be retained to prevent Bangalore from flooding or from water scarcity. The main source of replenishment of groundwater is the rainfall. The slope of the terrain allows most of the rainwater to flow as run-off. With the steep gradients available in the major valleys of Bangalore, the rainwater will flow out of the city within four to five hours. Only a small fraction of the rainwater infiltrates into the soil. The infiltration of water into the subsoil has declined with more and more buildings and paved road being constructed in the city. Thus the natural drainage of Bangalore is governed by flows from the central ridge to all lower contours and is connected with various tanks and ponds. There are no major rivers flowing in Bangalore and there is an urgent need to sustain these vital ecosystems through proper conservation and management measures. The proposed peripheral ring road connecting Hosur Road (NH 7) and Mysore Road (SH 17) at Gottigere lake falls within the buffer zone of the lake. This would alter the catchment integrity and hence water yield affecting flora, fauna and local people, and ultimately lead to the disappearance of Gottigere lake. Developmental activities in lake catchments, which has altered lake’s ecological integrity is in violation of the Indian Fisheries Act – 1857, the Indian Forest Act – 1927, Wildlife (Protection) Act – 1972, Water (Prevention and Control of Pollution) Act – 1974, Water (Prevention and Control of Pollution) Act – 1977, Forest (Conservation Act) – 1980, Environmental (Protection) Act – 1986, Wildlife (Protection) Amendment Act – 1991 and National Conservation Strategy and Policy Statement on Environment and Development – 1992. Considering 65% decline of waterbodies in Bangalore (during last three decades), decision makers should immediately take preventive measures to ensure that lake ecosystems are not affected. This report discusses the impacts due to the proposed infrastructure developmental activities in the vicinity of Gottigere tank.

Geoinformatics for Urbanisation and Urban Sprawl Pattern Analysis

Urbanisation is the increase in the population of cities in proportion to the region's rural population. Urbanisation in India is very rapid with urban population growing at around 2.3 percent per annum. Urban sprawl refers to the dispersed development along highways or surrounding the city and in rural countryside with implications such as loss of agricultural land, open space and ecologically sensitive habitats. Sprawl is thus a pattern and pace of land use in which the rate of land consumed for urban purposes exceeds the rate of population growth resulting in an inefficient and consumptive use of land and its associated resources. This unprecedented urbanisation trend due to burgeoning population has posed serious challenges to the decision makers in the city planning and management process involving plethora of issues like infrastructure development, traffic congestion, and basic amenities (electricity, water, and sanitation), etc. In this context, to aid the decision makers in following the holistic approaches in the city and urban planning, the pattern, analysis, visualization of urban growth and its impact on natural resources has gained importance. This communication, analyses the urbanisation pattern and trends using temporal remote sensing data based on supervised learning using maximum likelihood estimation of multivariate normal density parameters and Bayesian classification approach. The technique is implemented for Greater Bangalore – one of the fastest growing city in the World, with Landsat data of 1973, 1992 and 2000, IRS LISS-3 data of 1999, 2006 and MODIS data of 2002 and 2007. The study shows that there has been a growth of 466% in urban areas of Greater Bangalore across 35 years (1973 to 2007). The study unravels the pattern of growth in Greater Bangalore and its implication on local climate and also on the natural resources, necessitating appropriate strategies for the sustainable management.

Tamarind orchards: Agroforestry for dry lands

Agroforestry has a potential for sequestering as much carbon if not more than forests. Massive benefits can be channeled to small farmers and landless labourers through cultivation of Tamarind and other fast growing and fruit yielding trees. This paper describes a project started by small farmers and landless labourers in a semiarid areas of south India. The aim is to upgrade dryland holdings of the member families through economically sound dry land horticulture, community woodlots, and planting of fast growing species along orchard and field boundaries. The small farmers invest massive labour inputs and project gives economic benefits to change their land use practices and improve environmental quality. This paper describes the planning. processes of the project, hurdles in finding AIJ partners, current monitoring procedures and costs of C sequestration. This shows this project is economically viable on its own, but initially needed, and continues to need Carbon credit investment in order to spread rapidly across the geopolitical region covered by the organization. It argues that economic gains to small farmers and landless labourers are the most certain way of achieving massive biomass increase and soil carbon replenishment, and that multiple holistic benefits are achieved through this kind of project.

Influence of the Blade Hub Geometry on the Performance of Low-Head Axial Flow Turbines

The influence of geometric parameters, such as blade profile and hub geometry on axial flow turbines for micro hydro application remains poorly characterized. This paper first introduces a holistic theoretical model for studying the hydraulic phenomenon resulting from geometric modification to the blades. It then describes modification carried out on two runner stages, of which one has untwisted blades and the other has twisted blades obtained by modifying the inlet hub. The experimental results showed that the performance of the untwisted blade runner was satisfactory with a maximum efficiency of 68%. However, positive effects of twisted blades were clearly evident with an efficiency rise of more than 2%. This study also looks into the possible limitations of the model and suggests the extension of the experimental work and the use of computational tools to conduct a progressive validation of all experimental findings, especially on the flow physics within the hub region and the slip phenomena. The paper finally underlines the importance of developing a standardization philosophy for axial flow turbines specific for micro hydro requirements. DOI:10.1061/(ASCE)EY.1943-7897.0000060. (C) 2012 American Society of Civil Engineers.

Current trends in modeling hostpathogen interactions

The rapid emergence of infectious diseases calls for immediate attention to determine practical solutions for intervention strategies. To this end, it becomes necessary to obtain a holistic view of the complex hostpathogen interactome. Advances in omics and related technology have resulted in massive generation of data for the interacting systems at unprecedented levels of detail. Systems-level studies with the aid of mathematical tools contribute to a deeper understanding of biological systems, where intuitive reasoning alone does not suffice. In this review, we discuss different aspects of hostpathogen interactions (HPIs) and the available data resources and tools used to study them. We discuss in detail models of HPIs at various levels of abstraction, along with their applications and limitations. We also enlist a few case studies, which incorporate different modeling approaches, providing significant insights into disease. (c) 2013 Wiley Periodicals, Inc.

Grain growth and grain boundary dynamics in colloidal polycrystals

Grain boundary dynamics and grain growth play a pivotal role in the fabrication of functional polycrystalline materials. However, not much is known about the delicate interplay between various microscopic processes that drive grain boundary motion which eventually culminates in the desired grain morphology. Colloidal systems are ideally suited to bridge the gap between the microscopic and macroscopic processes underlying grain growth, since their dynamics can be followed in real space and real time with single-particle resolution. The present review aims at highlighting contributions from colloid experiments that have led to a holistic understanding of grain growth in polycrystalline materials.

Experimental signatures of a nonequilibrium phase transition governing the yielding of a soft glass

We present direct experimental signatures of a nonequilibrium phase transition associated with the yield point of a prototypical soft solid-a binary colloidal glass. By simultaneously quantifying single-particle dynamics and bulk mechanical response, we identified the threshold for the onset of irreversibility with the yield strain. We extracted the relaxation time from the transient behavior of the loss modulus and found that it diverges in the vicinity of the yield strain. This critical slowing down is accompanied by a growing correlation length associated with the size of regions of high Debye-Waller factor, which are precursors to yield events in glasses. Our results affirm that the paradigm of nonequilibrium critical phenomena is instrumental in achieving a holistic understanding of yielding in soft solids.

CANDO and the infinite drug discovery frontier

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound-proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12-25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 `high value' predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering.

Cell (module) temperature regulated performance of a building integrated photovoltaic system in tropical conditions

The performance of a building integrated photovoltaic system (BIPV) has to be commendable, not only on the electrical front but also on the thermal comfort front, thereby fulfilling the true responsibility of an energy providing shelter. Given the low thermal mass of BIPV systems, unintended and undesired outcomes of harnessing solar energy - such as heat gain into the building, especially in tropical regions - have to be adequately addressed. Cell (module) temperature is one critical factor that affects both the electrical and the thermal performance of such installations. The current paper discusses the impact of cell (module) temperature on both the electrical efficiency and thermal comfort by investigating the holistic performance of one such system (5.25 kW(p)) installed at the Centre for Sustainable Technologies in the Indian Institute of Science, Bangalore. Some recommendations (passive techniques) for improving the performance and making BIPV structures thermally comfortable have been listed out. (C) 2014 Elsevier Ltd. All rights reserved.

Optimal Binary Power Control for Underlay CR With Different Interference Constraints and Impact of Channel Estimation Errors

Adapting the power of secondary users (SUs) while adhering to constraints on the interference caused to primary receivers (PRxs) is a critical issue in underlay cognitive radio (CR). This adaptation is driven by the interference and transmit power constraints imposed on the secondary transmitter (STx). Its performance also depends on the quality of channel state information (CSI) available at the STx of the links from the STx to the secondary receiver and to the PRxs. For a system in which an STx is subject to an average interference constraint or an interference outage probability constraint at each of the PRxs, we derive novel symbol error probability (SEP)-optimal, practically motivated binary transmit power control policies. As a reference, we also present the corresponding SEP-optimal continuous transmit power control policies for one PRx. We then analyze the robustness of the optimal policies when the STx knows noisy channel estimates of the links between the SU and the PRxs. Altogether, our work develops a holistic understanding of the critical role played by different transmit and interference constraints in driving power control in underlay CR and the impact of CSI on its performance.

Current trends in modeling hostpathogen interactions

The rapid emergence of infectious diseases calls for immediate attention to determine practical solutions for intervention strategies. To this end, it becomes necessary to obtain a holistic view of the complex hostpathogen interactome. Advances in omics and related technology have resulted in massive generation of data for the interacting systems at unprecedented levels of detail. Systems-level studies with the aid of mathematical tools contribute to a deeper understanding of biological systems, where intuitive reasoning alone does not suffice. In this review, we discuss different aspects of hostpathogen interactions (HPIs) and the available data resources and tools used to study them. We discuss in detail models of HPIs at various levels of abstraction, along with their applications and limitations. We also enlist a few case studies, which incorporate different modeling approaches, providing significant insights into disease. (c) 2013 Wiley Periodicals, Inc.