5,176 research outputs found

    Minimum impact and immediacy of citations to physics open archives of arXiv.org: Science Citation Index based reports

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    The present work has calculated the minimum Open Archive Impact Factors and Open Archive Immediacy Index for the Physics Classes of arXiv.org as calculated for traditional journals in Journal Citation Reports of the Institute of Scientific Information using Science Citation Index without the citation by the classes itself. The calculated Impact Factors reveal that High-Energy Physics classes of arXiv.org (‘hep-th’, ‘hep-lat’, ‘hep-ex’, and ‘hep-ph’) have made more impact on the scientific community than any other classes except ‘nucl-ex’. The Impact Factors for the year 2003 are: ‘hep-th’ (0.999), ‘nucl-ex’ (0.806), ‘hep-lat’ (0.766), ‘hep-ex’ (0.73), ‘hep-ph’ (0.719), ‘nucl-th’ (0.338), ‘quant-ph’ (0.334), ‘cond-mat’ (0.313), ‘astro-ph’ (0.195), ‘math-ph’ (0.162), ‘physics’ (0.061), and ‘gr-qc’ (0.002). If the period for getting the citations to the open archive classes is considered one year as against two years for journal articles, the rank of the classes is the same. The immediacy of citing the Open Archives is also high for the High-Energy Physics classes. The Immediacy Indexes for the year 2003 are: ‘hep-ex’ (0.619), ‘hep-th’ (0.454), ‘hep-ph’ (0.44), ‘hep-lat’ (0.263), ‘nucl-ex’ (0.238), ‘quant-ph’ (0.202), ‘nucl-th’ (0.185), ‘cond-mat’ (0.168), ‘astro-ph’ (0.094), ‘math-ph’ (0.075), ‘physics’ (0.03), and ‘gr-qc’ (0.002). The impact is definitely much higher than what is concluded from the calculated factors because self-citations are not reckoned in the study. Use of web-tools like ‘Citebase’, ‘Citeseer’ etc. may strengthen the above argument

    Some Plane Symmetric Inhomogeneous Cosmological Models in the Scalar-Tensor Theory of Gravitation

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    The present study deals with the inhomogeneous plane symmetric models in scalar - tensor theory of gravitation. We used symmetry group analysis method to solve the field equations analytically. A new class of similarity solutions have been obtained by considering the inhomogeneous nature of metric potential. The physical behavior and geometrical aspects of the derived models are also discussed.Comment: 12 pages, 1 figure

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    Crab Farmin

    Effect of sowing dates and varieties on soybean performance in Vidarbha region of Maharashtra, India

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    oybean production is widely fluctuating in response to agro-environmental conditions year to year in Vidarbha region. Weather variations are the major determinants of soybean growth and yield. It is also important to study the response of suitable soybean varieties to varying weather parameters. So a field investigation was carried out to study the crop weather relationship of soybean and to optimize the sowing date with different soybean varie-ties. The results revealed that soybean crop sown up to 27th MW accumulated higher growing degree days (1640.5 0C day), photothermal units (20498.1 0C day hour) and recorded significantly higher seed yield (839 kg ha-1) and biological yield (2773 kg ha-1) with maximum heat use efficiency (0.51 kg ha-1°C day-1) and water productivity (2.49 kg ha-mm-1). Later sowings i.e. 30th MW sowing caused decreased amount of rainfall and increased maximum temperature regime across the total growing period with consequently lower seed yield (530 kg ha-1), GDD (1539.2 0C day), PTU (18689.9 0C day hour), heat use efficiency (0.34kg ha-1 °Cday-1) and water productivity (2.05kg ha-mm-1). Soybean variety TAMS 98-21 recorded significantly higher seed yield (734 kg ha-1) and highest biological yield (2649 kg ha-1) with maximum heat use efficiency (0.44 kg ha-1 °C day-1), GDD (1650.5 0C day ) and water productivity (2.41 kg ha-mm-1). Thus, the results of this study illustrated the importance of early sowing with suitable variety of soybean and indicates that sowing upto 27th MW with variety TAMS 98-21 is optimum for maximizing the yield in the Akola region of Vidarbha

    Combining ability and heterosis analysis for fibre yield and quality parameters in roselle (Hibiscus sabdariffa L.)

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    Roselle (Hibiscus sabdariffa L.) is second important bast fibre crop after jute in India. With an aim to ex-ploit non-additive genetic variance present experiment was designed to identify good general combining parents and specific cross combination for fibre yield and fibre quality parameters (fibre fineness, fibre tenacity) in roselle. A total of 11 parents were crossed in complete diallel fashion which resulted 55 F1, 55 RF1 (reciprocal F1). Parents, F1s and RF1s were grown in randomized block design. Analysis of variance revealed significant differences (P< 0.01, P<0.05) among the parents and their hybrids. The parents AMV 1, AMV 5, GR 27 and AHS 160 were identified as good combiners since they recorded significant general combining ability (GCA) effects for fibre yield and quality parameters. Further, For fibre yield only three crosses (AMV 1 × AMV 4, AMV 1 × GR 27, HS 4288 × JRR 07) showed significant specific combining ability (SCA) effects from them hybrid AMV 1 × GR 27 (fibre yield=27.37g/ plant) exhibited positively significant best parent (Non bris 4, Mean fibre yield=21.16g/plant) heterosis (29.35%). Similarly, for fibre tenacity, hybrid GR 27 × JRR 07 (fibre tenacity=23.47g/tex) exhibited positively significant best parent (HS 4288; fibre tenacity=20.35g/tex) heterosis (15.30%)

    The colour of life: interacting with SenseCam images on large multi-touch display walls

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    A SenseCam can provide a detailed visual archive of a person’s life, activities and experiences. However, as the number of images captured per year can extend beyond one million, gaining an insight into an individual’s lifestyle in a fast, effective and intuitive manner is a challenging prospect. In this work, we develop an interactive image browsing tool, which incorporates visualisation techniques that can capture not only a snapshot of an individual’s lifestyle over long periods of time, but also how that lifestyle varies with changing days, weeks, or years. The image retrieval tool incorporates the Colour of Life algorithms [1], which can represent an overview of millions of images with a single visualisation. The Colour of Life algorithms focus on the relationship between lifestyle and colour, by capturing the colours to which we are exposed in our lives (and therefore captured by SenseCam images), collating similar colours for specific time periods and depicting how those colours change over time with a flowing time-line – see Figure 1 which depicts the life of a SenseCam user over the period of 8 days. In this figure, time is orientated along the horizontal axis and larger vertical peaks indicate higher user activity for a given period of time. In Figure 1, the normal working week consists of the rhythmical blue, pink (work) and yellow (home) peaks and troughs for each day (with less activity at the start and end of the days), whereas time outdoors increases at the weekend, especially during the night (and hence the darker colours on the left hand side of the figure). The Colour of Life visualisation, while providing information on changes in lifestyle, does not provide sufficient context to understand the exact activities of a user for a given time period. For example, on the left of Figure 1 there is a peak of purple, that does not occur anywhere else during the 8 days of activities images – where was the user at this point in time and what was he doing? In this work, we build an interactive image browsing tool based around the Colour of Life visualisation. We exploit the use of high resolution multi-touch display walls, where we extend the Colour of Life algorithms to produce an intuitive visualisation, which incorporates image mosaicing (see Figure 2). Through this we incorporate coarse lifestyle data with more fine detailed contextual information on human activities into one interactive visualisation tool. As an additional feature, we have investigated the use of image classification within the framework of the Colour of Life. One such example is the categorisation of images as being as social (i.e. interacting with other people) or non-social. Using such a classification, we can depict a person’s social lifestyle, and how that varies over time
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