Assessment of roof water harvesting potential of Navsari city of Gujarat State, India by Remote sensing and Geographic information system (GIS)

Due to the water scarcity scenario in many parts of the Navsari city, Gujarat State in India, it is imperative to adopt cost-effective technologies that could harvest rainwater for satisfying drinking water requirements. The study was conducted with the aim of assessing the rainwater harvesting potential of Navsari city using remote sensing and Geographic Information System (GIS). The built-up areas of Navsari that could harness rainwater were identified by remote sensing and GIS. The effective built-up area contributing to rainwater harvesting was found to be 3.37 km2. The classification was carried out using “Remap” to assess the extent of the built-up area. The city was divided into equal grids and classification of each grid was implemented. The ground truth data was used for the evaluation of the built-up area. The roof water harvesting potential was estimated considering the average annual rainfall of 1621 mm and adopting suitable runoff coefficients. The rainwater harvesting potential of roofs for rainfall of different probabilities was estimated. For return periods of 10 years, 25 years, 50 years and 100 years, the roof water harvesting potentials were estimated to be 0.226, 0.261, 0.287 and 0.312 Million Cubic Metres (MCM), respectively. The estimated average roof water harvesting potential of Navsari city was 164 million litres per year, capable of satisfying the drinking water demand of approximately 1.12 lakh people annually. The rainwater harnessed from the rooftop could augment the current water supply and immensely help in fulfilling the drinking water demand of Navsari

BSRS: Best Stable Route Selection Algorithm for Wireless Sensor Network Applications

Topological changes in sensor networks frequently render routing paths unusable. Such recurrent path failures have detrimental effects on the network ability to support QoS-driven services. Because of connectivity richness in sensor networks, there often exist multiple paths between a source and a destination. Since many applications require uninterrupted connectivity of a session, the ability to find long-living paths can be very useful. In this paper, we propose Best Stable Route Selection (BSRS) approach based on Artificial Bee Colony based search algorithm, ensures that contributes stable quality performance of network and to calculate the best stable path services randomly based on QoS parameter requirements and existing circulation load; so that efficient route selection can easily capture by designing of proposed BSRS approach. The implementation of the proposed BSRS technique is implemented using NS2 simulation environment and the AODV routing protocol is used to incorporate the proposed algorithm. The experimental results are measured in terms of end to end delay, throughput, packet delivery ratio, and energy consumption and routing overhead. The results show the proposed BSRS algorithm improves the flexibility of network node and performance of network when multiple inefficient paths exist

Regulation of Translational Efficiency by Disparate 5′ UTRs of PPARγ Splice Variants

The PPAR-γ gene encodes for at least 7 unique transcripts due to alternative splicing of five exons in the 5′-untranslated region (UTR). The translated region is encoded by exons 1–6, which are identical in all isoforms. This study investigated the role of the 5′-UTR in regulating the efficiency with which the message is translated to protein. A coupled in vitro transcription-translation assay demonstrated that PPAR-γ1, -γ2, and -γ5 are efficiently translated, whereas PPAR-γ4 and -γ7 are poorly translated. An in vivo reporter gene assay using each 5′-UTR upstream of the firefly luciferase gene showed that the 5′-UTRs for PPAR-γ1, -γ2, and -γ4 enhanced translation, whereas the 5′-UTRs for PPAR-γ5 and -γ7 inhibited translation. Models of RNA secondary structure, obtained by the mfold software, were used to explain the mechanism of regulation by each 5′-UTR. In general, it was found that the translational efficiency was inversely correlated with the stability of the mRNA secondary structure, the presence of base-pairing in the consensus Kozak sequence, the number of start codons in the 5′-UTR, and the length of the 5′-UTR. A better understanding of posttranscriptional regulation of translation will allow modulation of protein levels without altering transcription

My grade, my right: linking academic entitlement to academic performance

The identifcation of determinants and correlates of academic entitlement is of particular interest for researchers and (academic) tutors alike. Whilst personality traits have been linked to academic entitlement in the past, the relative importance of familial influence remains unclear. Hence, to address this deficit, this study utilizes a sample of business and psychology undergraduates (N=170) in the United Arab Emirates. Additionally, the impact of academic entitlement on students’ misestimation of coursework grades was assessed in a subsample of psychology undergraduates (N=92). Multiple regression analyses revealed honesty–humility as the strongest predictor of academic entitlement, indicating lower entitlement of more honest students. In contrast, familial influences were unrelated to academic entitlement. Interestingly, higher entitled expectations were associated with larger overestimation of grades. Our findings indicate honesty–humility as an important driver of academic entitlement, whilst entitled expectations appear to be associated with misperceptions of students' own academic performance

Depth Customization of DSpace: Best Practices and Techniques of Institutional Repository at IIT Kanpur, India

4th International Conference on Open RepositoriesThis presentation was part of the session : DSpace User Group PresentationsDate: 2009-05-21 08:30 AM – 10:00 AMRealizing the importance and magnitude of Institutional Repository and global visibility and further research scope, Indian Institute of Technology Kanpur, India has intensively planned and designed a full fledged IR project started in mid 2005. Considering the various characteristics and strategies we have designed a well defined and distinct roadmap for establishing our IR in two phases. In the first phase we have planned the mass digitization of entire theses collection of Masters and Doctoral Dissertations produced from 1963 spanning one million pages with their complex content. The content management and uploading to the content server with extracted metadata encoded in XML from our existing server by an in-house developed script is being organised effectively ensuring adequate quality checking of these pages. Initially manual submission for theses was in place. Now a provision has been made available to researchers to submit their theses online even without submitting any hardcopy in the library. The second phase is conceived of digitizing scholarly publications other than theses from our academic community. Its coverage is extremely appreciable in number and strategy we are using for our IR. Excellent feature of our system is the depth customization of DSpace at several places incorporating enhanced features. We discovered that default features offered by even the latest version of DSpace are not sufficient and adequate for academic community to establish their IR system in its full functionality so as to deliver the right information to the right user at the time it is needed. After a detailed study and research we have incorporated significant features like workflow, additional browse and search options, cross-collection search, linking to keywords/subject/homepage/citation, total count of items in respect of supervisor/subject/citation. Additionally, login user authentication from central database, IP based access restrictions, embargo and encryption on the bit stream are also provided. Redesigned feedback form has also been provided to improve its scope and functionalities of our system. These are unique features of our IR system and these enhanced features may be useful to any system in identical academic environment using DSpace to power their Institutional Repositories.Indian Institute of Technology Kanpur, Indi

A comparative study of early and delayed cord clamping in term deliveries

Background: Timing of clamping of the umbilical cord has always been a debatable issue. Early cord clamping (ECC) is defined as clamping of the cord within 30 seconds of delivery of the baby and delayed cord clamping (DCC) is defined as clamping of the cord between 30 to 120 seconds of delivery. Delayed cord clamping, despite some limitations, is said to be beneficial to the neonate.  A comparative study between ECC and DCC was carried out on a select group of term pregnant women without any high-risk factor and delivering at term. Aim of the study was to compare the effects of early versus delayed cord clamping on neonates and mothers. The focus was on the neonatal haemoglobin levels and adverse effects, if any on neonates and mothers in the two groups.Methods: 100 women satisfying the inclusion/exclusion criteria were recruited for the study. They were randomly divided into two groups of 50 each. Group A underwent early cord clamping and Group B delayed cord clamping. Mothers were observed for 1 hour post-delivery for any evidence of post-partum haemorrhage. Neonates were observed for any sign of tachypnea and blood sample was sent after 72 hours of delivery for analyzing Hb, hematocrit and bilirubin of the neonate.Results: The results revealed that neonates with DCC had a higher mean Hb level of 15.02 vis-à-vis the ECC group Hb of 11.69G/dl and the difference was statistically significant. Similarly mean hematocrit of DCC group was 48.67 while the ECC group mean was 42.36, the difference again was statistically significant. There was no significant side effects or complications in both mother and newborn babies.Conclusions: It was concluded that delayed cord clamping should be practiced in otherwise non high-risk deliveries

Impact of different cropping systems on properties of soil and water in different micro watersheds

Studies on soils of Navsari Agricultural University (NAU) having different cropping system were carried out in the four micro watersheds that exist in the 400 ha University campus. Soil samples from 0-15 cm depth and water samples from adjacent bore wells were collected and analyzed from different locations of micro watersheds. Soils of watersheds showed that soils texture was clay in nature, having more than 65 % clay, whereas silt was more in watershed ‘A’. Soil organic carbon content (SOC) was 0.32 %, found in the field near University play ground and the highest 0.88 %, in Forestry farm, thus underlining the need of forest species in agricultural farms. SOC levels have reduced significantly due to intensive cultivation in all the watersheds. The result of exchangeable sodium percent (ESP) is supported by the topographic features, as, ESP was more in watershed ‘B’ (5.15) than C (2.95), this showed that infiltration rate was lesser in ‘B’ as compared to ‘C’ due to availability of more sodium (Na). Available N was highest in watershed ‘A’ (246 kg/ha) followed by ‘C’ (225 kg/ha) than ‘B’ (203 kg/ha), the reason was watershed ‘A’ had only horticulture crops whereas B and C had different crops of the region. Electrical conductivity (EC) of ground water collected from wells in watershed ‘C’ was found to be very high both before (3.44 dS/m) and after monsoon (2.95 dS/m), showing that water is highly saline and not fit for surface irrigation and there is need of ground water recharging

CANDLE: Decomposing Conditional and Conjunctive Queries for Task-Oriented Dialogue Systems

Domain-specific dialogue systems generally determine user intents by relying on sentence-level classifiers which mainly focus on single action sentences. Such classifiers are not designed to effectively handle complex queries composed of conditional and sequential clauses that represent multiple actions. We attempt to decompose such queries into smaller single-action sub-queries that are reasonable for intent classifiers to understand in a dialogue pipeline. We release CANDLE (Conditional & AND type Expressions), a dataset consisting of 3124 utterances manually tagged with conditional and sequential labels and demonstrates this decomposition by training two baseline taggers