Education as a determinant of fertility: a case study of Kullu Town

Using a sample of 885 females (1/2 of all married women of reproductive age), this study examines the role of education as a determinant of fertility among couples in Kullu town of Himachol Pradesh, India. Of the 885 respondents, only 149 were illiterate. The average family size was 2.88. Findings reveal that 1) the average family size was largest for illiterate respondents (3.57) and for illiterate males (3.76); 2) average family size declined consistently after the middle level of education to 1.29 for post graduate respondents and 2.33 for post graduate males; 3) a negative correlation exists between fertility and education of both husband and wife, with the wife's education having a stronger negative correlation with fertility; and 4) couples with an educational level of matriculation and above have a distinctly smaller family size than those less educated.     

Spatial and temporal patterns of dry spell lengths in the Iberian Peninsula for the second half of the twentieth century

Summary Daily pluviometric records of 43 meteorological stations across the Iberian Peninsula have permitted a detailed analysis of dry spell patterns for the period 1951–2000 by distinguishing daily amount thresholds of 0.1, 1.0, 5.0 and 10.0 mm/day. The analyses are based on three annual series, namely the number of dry spells, N, the average dry spell length, L, and the extreme dry spell length, L _max. First, the statistical significance of local trends for the annual series of N, L and L _max has been investigated by means of the Mann-Kendall test and significant field trends have been established by means of Monte Carlo simulations. Clear signs of negative field trends are detected for N (1.0 and 10.0 mm/day) and L (0.1 mm/day). Second, the Weibull model fits well the empirical distributions of dry spell lengths for all the rain gauges, whatever the daily amount threshold, with a well ranged spatial distribution of their parameters u and k. On the basis of the Weibull distribution, return period maps for 2, 5, 10, 25 and 50 years have been obtained for dry spell lengths with respect to the four daily threshold levels. While for 0.1 and 1.0 mm/day the longest dry spells are expected at the south of the Iberian Peninsula, for 5.0 and 10.0 mm/day they are mostly detected at the southeast. Finally, the elapsed time between consecutive dry spells has been analysed by considering the same rain amount thresholds and different dry spell lengths at increasing intervals of 10 days. This analysis makes evident a significant negative field trend of the elapsed time between consecutive dry spells of lengths ranging from 10 to 20 days for daily amount thresholds of 1.0, 5.0 and 10.0 mm/day. Authors’ addresses: X. Lana, C. Serra, Departament de Física i Enginyeria Nuclear, ETSEIB, Universitat Politècnica de Catalunya, Av. Diagonal 647 planta 11, 08028 Barcelona, Spain; M. D. Marínez, Departament de Física Aplicada, Universitat Politècnica de Catalunya, 08028 Barcelona, Spain; A. Burgue?o, Departament de Meteorologia i Astronomia, Universitat de Barcelona, 08028 Barcelona, Spain; J. Martín-Vide, L. Gómez, Grup de Climatologia, Universitat de Barcelona, 08028 Barcelona, Spain.     

A distributed approach for calculating inundation height based on Dijkstra's algorithm

This research proposed a parallelized approach to scaling up the calculation of inundation height, the minimum sea‐level rise required to inundate a cell on a digital elevation model, which is based on Dijkstra's algorithm for shortest‐path calculations on a graph. Our approach is based on the concepts of spatial decomposition, calculate‐and‐correct, and a master/worker parallelization paradigm. The approach was tested using the U.S. Coastal Relief Model (CRM) dataset from the National Geophysical Data Center on a multicore desktop computer and various supercomputing resources through the U.S. Extreme Science and Engineering Discovery Environment (XSEDE) program. Our parallel implementation not only enables computations that were larger than previously possible, but also significantly outperforms serial implementations with respect to running time and memory footprint as the number of processing cores increases. The efficiency of the scalability seemed to be tied to tile size and flattened out at a certain number of workers.     

Comparison of Vegetation Indices from Two Ground Based Sensors

The best and commonly used ground-based sensor to monitor crop growth, ASD FieldSpecPro Spectroradiometer (Analytical Spectral Devices, Boulder, CO, USA) is a passive sensor, which can be used under adequate light condition. However, now-a-days active sensors such as GreenSeeker? (GS) handheld crop response (Trimble Agriculture division, USA) are used for monitoring crop growth and are flexible in terms of timeliness and illumination conditions besides being cheaper than the ASD. Before its wide use, the suitability and accuracy of GS should be assessed by comparing the NDVI measured by this instrument with that by ASD, under diverse wheat growing conditions of India. Keeping this in view, the present experiment was undertaken with the following objectives: (1) to find out the temporal variation of NDVI measured both by ASD and GS treatments, (2) to find out relationship between the NDVI measured through ASD and GS and, (3) to evaluate the suitability of GS for NDVI measurements. It was observed that the numerical value of NDVI as measured by GS was always significantly (P < 0.05) lower than that measured by ASD for all the experiments under study. The NDVI-ASD and NDVI-GS were significantly positively correlated (P < 0.01) with the correlation coefficients being +0.94, +0.88 and +0.87 for irrigation and nitrogen experiment, irrigation and cultivars experiment, and tillage, residue and nitrogen experiments, respectively. Further, the regression equation developed between the NDVI-ASD and NDVI-GS: [NDVI-GS = 1.070 × (NDVI-ASD ? 0.292] can be successfully used to compute the NDVI of ASD from that computed by GS.     

Estimation of Partial Pressure of Carbon Dioxide and Air-Sea Fluxes in Hooghly Estuary Based on In Situ and Satellite Observations

An empirical model is developed and used with remotely sensed predictors: sea surface temperature (SST) and chlorophyll-a concentration (Chl-a), to compute surface water partial pressure of carbon dioxide (pCO_2w) and air-sea fluxes of CO₂ in the Hooghly estuary and its adjacent coastal oceans. In situ observations used here were based on measurements carried out in this region during winter and summer periods in 2008. The estimated pCO_2w compares well with the in situ observations at root mean square error ±18 μatm. In winter, estimated pCO_2w ranges between 320 and 500 μatm with large values (>400 μatm) on the south-western and south-eastern flanks of the coastal domain and lower values (340–375 μatm) on the main-channel. In summer, it remained spatially uniform at 450 μatm. Extrapolation of the results over the study region based on the Moderate Imaging Specroradiometer (MODIS) measured SST and Chl-a suggests that the region is a strong source of atmospheric CO₂ during the summer with net release of 0.095 Tg C year^?1 (equivalent to mean flux of 90 molC m^?2 year^?1) and is a weak source during the winter with net release of 0.006 Tg C yr^?1 (0.5 molC m^?2 year^?1) from the geographical extent of 6000 Km² area.