Measuring statistical isotropy of CMB anisotropy

The statistical expectation values of the temperature fluctuations and polarization of cosmic microwave background (CMB) are assumed to be preserved under rotations of the sky. We investigate the statistical isotropy (SI) of the CMB maps recently measured by the Wilkinson microwave anisotropy probe (WMAP) using the bipolar spherical harmonic formalism proposed in Hajian and Souradeep [Hajian, A., Souradeep, T. (2003) Astrophys. J. Lett. 597, L5] for CMB temperature anisotropy and extended to CMB polarization in Basak, Hajian and Souradeep [Basak, S., Hajian, A., Souradeep, T. (2006) Phys. Rev. D74, 02130(R)]. The Bipolar Power Spectrum (BiPS) had been measured for the full sky CMB anisotropy maps of the first year WMAP data and now for the recently released three years of WMAP data. We also introduce and measure directional sensitive reduced Bipolar coefficients on the three year WMAP ILC map. Consistent with our published results from first year WMAP data we have no evidence for violation of statistical isotropy on large angular scales. Preliminary analysis of the recently released first WMAP polarization maps, however, indicate significant violation of SI even when the foreground contaminated regions are masked out. Further work is required to confirm a possible cosmic origin and rule out the (more likely) origin in observational artifact such as foreground residuals at high galactic latitude.     

Continuum model and analysis of wick-drained systems

An equivalent homogeneous continuum theory is developed for modelling discretely drained soil stratum. The model accounts for the local horizontal flow to discrete vertical drains such as wick or sand or stone columns as well as direct vertical drainage of the soil and global horizontal flow due to non-uniform horizontal conditions. Calibration curves for the model are presented for the case of no soil smear due to the drain installation and for the case when smear exists. The model is implemented in both analytical and finite element analyses for those cases where no well resistance is present and when it is of importance. The accuracy and applicability of the model is demonstrated for simple one- and two- layered problems including smear and well resistance.     

Analysis of 2010-flood causes, nature and magnitude in the Khyber Pakhtunkhwa, Pakistan

This article attempts to analyse the nature, magnitude and causes of 2010 disastrous flood that seriously affected the province of Khyber Pakhtunkhwa (KPK), Pakistan. Pakistan is famous for its summer floods, but the flood of 2010 is considered to be the century’s worst. It has broken all the previous records in terms of discharge, damages and amount of rainfall occurred. Most of the meteorological stations have received rainfall above normal. Data for this study were collected both from primary and secondary sources. A total 150 questionnaires were filled in from the flood victims. However, secondary data were obtained from the Pakistan Meteorology Department, Flood Forecasting and Warning Centre, Federal Flood Commission, Provincial Disaster Management Authority, National Disaster Management Authority, Surface Water Hydrology Department and Provincial Irrigation and Drainage Authority. The analysis reveals that heavy and prolonged rainfall for four consecutive days (27–30 July) was the major cause of 2010-flood. In addition to this, the development of unusual low pressure zone over the northern Pakistan, aggradations of river bed, rapid deforestation, ponding back of river by motorway, blocking of bridges by tree trunks and subsequent bursting of temporary dams have played their role in causing the disastrous flood in almost all the rivers of KPK. This has inflicted terrible damages to human lives, standing crops, housing, infrastructure and other properties.     

Total load transport in gravel bed and sand bed rivers case study:Chelichay watershed

Field experiments were conducted on total load transport in the Chelichay River Basin,a mountainous catchment (1,400 km~2) located in north eastern of Iran,to evaluate total load formulas including four gravel bed rivers and a sand bed river(Qaresoo River).Gravel bed rivers in Chelichay River Basin can be grouped into two types;steep slope rivers with high shear values(Chehelchay River and Khormaloo River) and mild slope rivers with low shear values(Narmab River and Soosara River).Two depth integrating suspended load samplers(DH-48 and D-49),and two bed load samplers(Helley-Smith and BLSH) were used to measure total load.The performance is tested of 8 total load transport formulae including 4 macroscopic and 4 microscopic methods.A systematic and thorough analysis of 59 sets of data collected from sand bed river indicate that Yang and Engelund and Hansen reach to the better results, and from four gravel bed rivers confirmed that the methods of Karim and Kennedy and Engelund and Hansen yields the best results for steep slope rivers,and the methods of Einstein and Bijker are ranked highest in gradual slope rivers.     

A conceptual framework for quantitative estimation of physical vulnerability to landslides

The paper illustrates a method for scenario-based, quantitative estimation of physical vulnerability of the built environment to landslides. The rationale and main features of the procedure are presented in the context of quantitative risk estimation. Vulnerability is defined quantitatively as a function of landslide intensity and the susceptibility of vulnerable elements. Reference terminology is presented and discussed. Models for the quantification of intensity and susceptibility for some categories of elements at risk such as structures and persons are proposed. An example application is illustrated.     

Groundwater arsenic contamination in Manipur,one of the seven North-Eastern Hill states of India: a future danger

Manipur State, with a population of 2.29 million, is one of the seven North-Eastern Hill states in India, and is severely affected by groundwater arsenic contamination. Manipur has nine districts out of which four are in Manipur Valley where 59% of the people live on 10% of the land. These four districts are all arsenic contaminated. We analysed water samples from 628 tubewells for arsenic out of an expected total 2,014 tubewells in the Manipur Valley. Analyzed samples, 63.3%, contained >10 μg/l of arsenic, 23.2% between 10 and 50 μg/l, and 40% >50 μg/l. The percentages of contaminated wells above 10 and 50 μg/l are higher than in other arsenic affected states and countries of the Ganga–Meghna–Brahmaputra (GMB) Plain. Unlike on the GMB plains, in Manipur there is no systematic relation between arsenic concentration and the depth of tubewells. The source of arsenic in GMB Plain is sediments derived from the Himalaya and surrounding mountains. North-Eastern Hill states were formed at late phase of Himalaya orogeny, and so it will be found in the future that groundwater arsenic contamination in the valleys of other North-Eastern Hill states. Arsenic contaminated aquifers in Manipur Valley are mainly located within the Newer Alluvium. In Manipur, the high rainfall and abundant surface water resources can be exploited to avoid repeating the mass arsenic poisoning that has occurred on the GMB plains.     

Quality assessment of OpenStreetMap data using trajectory mining

OpenStreetMap (OSM) data are widely used but their reliability is still variable. Many contributors to OSM have not been trained in geography or surveying and consequently their contributions, including geometry and attribute data inserts, deletions, and updates, can be inaccurate, incomplete, inconsistent, or vague. There are some mechanisms and applications dedicated to discovering bugs and errors in OSM data. Such systems can remove errors through user-checks and applying predefined rules but they need an extra control process to check the real-world validity of suspected errors and bugs. This paper focuses on finding bugs and errors based on patterns and rules extracted from the tracking data of users. The underlying idea is that certain characteristics of user trajectories are directly linked to the type of feature. Using such rules, some sets of potential bugs and errors can be identified and stored for further investigations.