INTEGRAL/XMM views on the MeV source GRO J1411-64

The COMPTEL unidentified source GRO J 1411-64 was observed by INTEGRAL and XMM-Newton in 2005. The Circinus Galaxy is the only source detected within the 4σ location error of GRO J1411-64, but in here excluded as the possible counterpart. At soft X-rays, 22 reliable and statistically significant sources (likelihood >10) were extracted and analyzed from XMM-Newton data. Only one of these sources, XMMU J141255.6-635932, is spectrally compatible with GRO J1411-64 although the fact the soft X-ray observations do not cover the full extent of the COMPTEL source position uncertainty make an association hard to quantify and thus risky. At the best location of the source, detections at hard X-rays show only upper limits, which, together with MeV results obtained by COMPTEL suggest the existence of a peak in power output located somewhere between 300–700 keV for the so-called low state. Such a spectrum resembles those in blazars or microquasars, and might suggest at work by the models accordingly. However, an analysis using a microquasar model consisting on a magnetized conical jet filled with relativistic electrons, shows that it is hard to comply with all observational constrains. This fact and the non-detection at hard X-rays introduce an a-posteriori question mark upon the physical reality of this source, what is discussed here.     

Application of global snow model for the estimation of snow depth in the UK

Microwave imagery can be used successfully for mapping of snow and estimation of snow pack characteristics under almost all weather conditions. This research is a contribution to the field of space borne remote sensing of snow by means of passive microwave data imagery. The satellite data are acquired from the Special Sensor Microwave Imager (SSM/I). The SSM/I is a four frequency seven channels dual polarization (except 22 GHz which is only vertically polarized) scanning radiometer with channels located at 19, 22, 37, and 85 GHz frequencies. A radiative transfer theory based model is used to estimate the snow cover characteristics of different snow pack types in the UK. A revised form of the Chang et al. (Nord Hydrol 16:57–66, 1987) model is used for this purpose. The revised Chang model was calibrated for global snow monitoring and takes into account forest fractional coverage effects. Snow cover characteristics have significant effects on up-welling naturally emitted microwave radiation through the processes of forward scattering. The up-welling signal is more complex for snow covers that consist of free liquid water content. The aim of this study is to test the global snow depth model for the UK snow cover. The Chang model predicted snow depth bias results for January, February, and March 1995 are ?1.26, ?0.35, and ?0.63 cm, respectively. Similarly, the Chang model Mean Absolute Error (MAE) for January, February, and March 1995 have values 2.88, 2.38, and 1.91 cm, respectively. These results show that the Chang model underestimates the snow depth prediction for all the case studies. The results of this study led us to the conclusion that the global snow models (Chang model) when applied for the retrieval of local snow depth estimation (UK snow cover) underestimate snow depth.     

Vulnerability and adaptability of wheat production in different climatic zones of Pakistan under climate change scenarios

Ten wheat production sites of Pakistan were categorized into four climatic zones i.e. arid, semi-arid, sub-humid and humid to explore the vulnerability of wheat production in these zones to climate change using CSM-Cropsim-CERES-Wheat model. The analysis was based on multi-year (1971–2000) crop model simulation runs using daily weather series under scenarios of increased temperature and atmospheric carbon dioxide concentration (CO₂) along with two scenarios of water management. Apart from this, sowing date as an adaptation option to offset the likely impacts of climate change was also considered. Increase in temperature resulted in yield declines in arid, semi-arid and sub-humid zone. But the humid zone followed a positive trend of gain in yield with rise in temperature up to 4°C. Within a water regime, increase in CO₂ concentration from 375 to 550 and 700 ppm will exert positive effect on gain in wheat yield but this positive effect is significantly variable in different climatic zones under rainfed conditions than the full irrigation. The highest response was shown by arid zone followed by semi-arid, sub-humid and humid zones. But if the current baseline water regimes (i.e. full irrigation in arid and semi-arid zones and rainfed in sub-humid and humid zones) persist in future, the sub-humid zone will be most benefited in terms of significantly higher percent gain in yield by increasing CO₂ level, mainly because of its rainfed water regime. Within a CO₂ level the changes in water supply from rainfed to full irrigation shows an intense degree of responsiveness in terms of yield gain at 375 ppm CO₂ level compared to 550 and 700 ppm. Arid and semi-arid zones were more responsive compared to sub-humid and humid zones. Rise in temperature reduced the length of crop life cycle in all areas, though at an accelerated rate in the humid zone. These results revealed that the climatic zones have shown a variable intensity of vulnerability to different scenarios of climate change and water management due to their inherent specific and spatial climatic features. In order to cope with the negative effects of climate change, alteration in sowing date towards cooler months will be an appropriate response by the farmers.     

Using species traits to guide conservation actions under climate change

Few assessments of species vulnerability to climate change used to inform conservation management consider the intrinsic traits that shape species’ capacity to respond to climate change. This omission is problematic as it may result in management actions that are not optimised for the long-term persistence of species as climates shift. We present a tool for explicitly linking data on plant species’ life history traits and range characteristics to appropriate management actions that maximise their capacity to respond to climate change. We deliberately target data on easily measured and widely available traits (e.g. dispersal syndrome, height, longevity) and range characteristics (e.g. range size, climatic/soil niche breadth), to allow for rapid comparison across many species. We test this framework on 1237 plants, categorising species on the basis of their potential climate change risk as related to four factors affecting their response capacity: reproduction, movement capability, abiotic niche specialisation and spatial coverage. Based on these four factors, species were allocated risk scores, and these were used to test the hypothesis that the current protection status under national legislation and related management actions capture species response capacity to climate change. Our results indicate that 20% of the plant species analysed (242 species) are likely to have a low capacity to respond to climate change based on the traits assessed, and are therefore at high risk. Of the 242 high risk species, only 10% (24 species) are currently listed for protection under conservation legislation. Importantly, many management plans for these listed species fail to address the capacity of species to respond to climate change with appropriate actions: 70% of approved management plans do not include crucial actions which may improve species’ ability to adapt to climate change. We illustrate how the use of easily attainable traits associated with ecological and evolutionary responses to changing environmental conditions can inform conservation actions for plant species globally.     

Biosynthesis and genetics of polyhydroxyalkanoates by newly isolated <Emphasis Type="Italic">Pseudomonas aeruginosa</Emphasis> IFS and 30N using inexpensive carbon sources

Poly(3-hydroxyalkanoates) (PHAs) are the bioplastics that are stored in many genera of bacteria as carbon and energy storage polyester granules. PHAs have established themselves as strong competitors to conventional plastics. This study reports the isolation of PHA-accumulating bacteria from local environment and their PHA characterization. Two potential strains identified as Pseudomonas aeruginosa strain IFS (Accession no. JQ041638) and P. aeruginosa strain 30N (Accession no. JQ041639) based on 16S rRNA gene sequence identity were cultivated under nitrogen limited conditions to study their PHA biosynthesis capabilities. The strain IFS and strain 30N produced 1.36 and 1.40 gl^?1 dry biomass with percentage PHA contents of 44.85 and 45.74%, respectively, when grown on glucose as carbon source. The PHA was identified as poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) by fourier transform infrared spectroscopy (FTIR) and gas chromatography coupled with mass spectrometry (GC–MS). The PHA synthase genes of these strains were isolated, sequenced and analyzed using bioinformatic tools that showed they belonging to type 2 PHA synthases and presented their evolutionary relationships with PHA synthases of other Pseudomonas species. The experimental results of this study highlight the importance of these strains for future use of bacterial biopolymer production growing on simple and inexpensive carbon sugars.     

Interacting modified Chaplygin gas in loop quantum cosmology

We investigate the background dynamics when dark energy is coupled to dark matter in the universe described by loop quantum cosmology. We consider dark energy of the form modified Chaplygin gas. The dynamical system of equations is solved numerically and a stable scaling solution is obtained. It henceforth resolves the famous cosmic coincidence problem in modern cosmology. The statefinder parameters are also calculated to classify this dark energy model.     

GPR Signatures of Pipes and Walls with Emphasis on the Effect of Inclined Scanning Trajectory

This study investigates the effects of some commonly encountered constraints such as inclined scanning trajectory, multiple targets in the vicinity and material variation on GPR responses of pipes and walls. Further, the effects of wall inclination and broken walls are also explored in GPR signatures. Interpretation of such signatures in GPR data for archaeological and geotechnical surveys has been a challenge. A physical model was created to simulate buried pipes and walls under controlled conditions by maintaining density and moisture content of the soil medium. The presence of PVC pipes, plastered brick and stone walls buried in the dry sand have been investigated and major observations have been reported. The inclined scanning trajectory on buried pipes shows a change in curvature of hyperbola-like signatures. Inclined transects near the ends of pipes and walls manifest single limb GPR signatures. The responses of multiple pipes and walls show dependence on separation of targets and footprint of an antenna. One can discern stone walls from brick walls by recognizing the diffraction of waves by irregular stones in GPR responses. The signatures of walls differ from pipes with respect to the width of the apex and variation in the intensity in the limb.     

Application of snowmelt runoff model for water resource management

Snow‐covered areas (SCAs) are the fundamental source of water for the hydrological cycle for some region. Accurate measurements of river discharge from snowmelt can help manage much needed water required for hydropower generation and irrigation purposes. This study aims to apply the snowmelt runoff model (SRM) in the Upper Indus basin by the Astore River in northern Pakistan for the years 2000 to 2006. The Shuttle Radar Topographic Mission (SRTM) data are used to generate the Digital Elevation Model (DEM) of the region. Various variables (snow cover depletion curves (SCDCs), temperature and precipitation) and parameters (degree‐day factor, recession coefficient, runoff coefficients, time lag, critical temperature and temperature lapse rate) are used as input in the SRM. However, snow cover data are direct and an important input to the SRM. Satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to estimate the SCA. Normalized difference snow index (NDSI) algorithm is applied for snow cover mapping and to differentiate snow from other land features. Nash–Sutcliffe coefficient of determination (R²) and volume difference (D_V) are used for quality assessment of the SRM. The results of the current research show that for the study years (2000–2006), the average value of R² is 0·87 and average volume difference D_V is 1·18%. The correlation coefficient between measured and computed runoff is 0·95. The results of the study further show that a high level of accuracy can be achieved during the snowmelt season. The simulation results endorse that the SRM in conjunction with MODIS snow cover product is very useful for water resource management in the Astore River and can be used for runoff forecasts in the Indus River basin in northern Pakistan. Copyright © 2011 John Wiley & Sons, Ltd.