Castelfranco Emilia, Italy
Castelfranco Emilia, Italy

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Malagoli C.,University of Modena and Reggio Emilia | Crespi C.M.,University of California at Los Angeles | Rodolfi R.,Local Health Unit of Reggio Emilia | Signorelli C.,University of Parma | And 9 more authors.
Bioelectromagnetics | Year: 2012

The issue of adverse human health effects due to exposure to electromagnetic fields is still unclear, and congenital anomalies are among the outcomes that have been inconsistently associated with such exposure. We conducted a population-based, case-control study to examine the risk of congenital anomalies associated with maternal exposure to magnetic fields (MF) from high-voltage power lines during pregnancy in a community in northern Italy. We identified 228 cases of congenital malformations diagnosed in live births, stillbirths, and induced abortions among women living in the municipality of Reggio Emilia during the period 1998-2006, and a reference group of healthy newborns was matched for year of birth, maternal age, and hospital of birth. We identified maternal residence during early pregnancy and used Geographic Information System to determine whether the residences were within geocoded corridors with MF ≥0.1μT near high-voltage power lines, then calculated the relative risk (RR) of congenital anomalies associated with maternal exposure. One case and 5 control mothers were classified as exposed, and the RR associated with MF ≥0.1μT was 0.2 (95% CI: 0.0-2.0) after adjusting for maternal education. While small or moderate effects may have gone undetected due to low statistical power, the results of this study overall do not provide support for major effects of a teratogenic risk due to exposure to MF during early pregnancy. © 2011 Wiley Periodicals, Inc.

Ahmed M.S.,University of Punjab | Shafiq K.,University of Punjab | Ali H.,GIS Laboratory | Ollevier F.,Charles University
Journal of Animal and Plant Sciences | Year: 2013

Morphological and morphometrical study was conducted on blood stream forms of Trypanosoma danilewskyi strain F Cc-1, isolated from laboratory-infected single breed juvenile common carp. A group of ten fish was intraperitoneally inoculated with 1000 live trypanosomes per fish. At the peak of parasitemia thin blood smears were prepared on precleaned glass slides on days 20, 30, 40 and 50 post infections (p.i). Blood smear was air dried, fixed with methanol and stained with May-Grünwald Giemsa stain. Stained trypanosomes were examined under light microscope at X 1000 magnification in the immersion oil. Morphology of trypanosome was recorded with a camera mounted on the microscope. From well stained slides 200 good specimens of T. danilewskyi FCc-1 were selected. For morphometric parameters, linear measurements in microns and nuclear area in square microns were taken by using Videoplan (Image Analysis System Kontron Bildanalyse, Germany). Morphometric measurements of T. danilewskyi strain FCc-1 were compared with reference strain of T. danilewskyi (Caa-1) already described earlier. The data revealed that T. danilewskyi strains FCc-1 and Caa-1 are the same.

Abbas S.,GIS Laboratory | Qamer F.M.,International Center for Integrated Mountain Development | Hussain N.,Helmholtz Center for Environmental Research | Saleem R.,GIS Laboratory | Nitin K.T.,Asian Institute of Technology
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | Year: 2012

Mangroves ecosystems consist of inter tidal flora and fauna found in the tropical and subtropical regions of the world. Mangroves forest is a collection of halophytic trees, shrubs, and other plants receiving inputs from regular tidal flushing and from freshwater streams and rivers. A global reduction of 25 % mangroves' area has been observed since 1980 and it is categorized as one of to the most threatened and vulnerable ecosystems of the world. Forest resources in Pakistan are being deteriorating both quantitatively and qualitatively due to anthropogenic activities, climatic v and loose institutional management. According to the FAO (2007), extent of forest cover of Pakistan in 2005 is 1,902,000 ha, which is 2.5% of its total land area. Annual change rate during 2000-2005 was -2.1% which is highest among all the countries in Asia. The Indus delta region contains the world's fifth-largest mangrove forest which provides a range of important ecosystem services, including coastal stabilisation, primary production and provision of nursery habitat for marine fish. Given their ecological importance in coastal settings, mangroves receive special attention in the assessment of conservation efforts and sustainable coastal developments. Coastline of Pakistan is 1050km long shared by the provinces, Sind (350km) and Baluchistan (700 km). The coastline, with typical arid subtropical climate, possesses five significant sites that are blessed with mangroves. In the Sindh province, mangroves are found in the Indus Delta and Sandspit. The Indus Delta is host to the most extensive mangroves areas and extends from Korangi Creek in the West to Sir Creek in the East, whereas Sandspit is a small locality in the West of Karachi city. In the Balochistan province, mangroves are located at three sites, Miani Hor, Kalmat Khor and Jiwani. Contemporary methods of Earth observation sciences are being incorporated as an integral part of environmental assessment related studies in coastal areas. GIS and Remote Sensing based technologies and methods are in use to map forest cover since the last two decades in Pakistan. The national level forest cover studies based upon satellite images include, Forestry Sector Master Plan (FSMP) and National Forest & Range Resources Assessment Study (NFRRAS). In FSMP, the mangrove forest extent was visually determined from Landsat images of 1988 - 1991, and was estimated to be 155,369 ha; whereas, in NFRRAS, Landsat images of 1997-2001 were automated processed and the mangroves areas was estimated to be 158,000 ha. To our knowledge, a comprehensive assessment of current mangroves cover of Pakistan has not been made over the last decade, although the mangroves ecosystems have become the focus of intention in context of recent climate change scenarios. This study was conducted to support the informed decision making for sustainable development in coastal areas of Pakistan by providing up-todate mangroves forest cover assessment of Pakistan. Various types of Earth Observation satellite images and processing methods have been tested in relation to mangroves mapping. Most of the studies have applied classical pixel - based approached, there are a few studies which used object - based methods of image analysis to map the mangroves ecosystems. Object - based methods have the advantage of incorporating spatial neighbourhood properties and hierarchical structures into the classification process to produce more accurate surface patterns recognition compared with classical pixel - based approaches. In this research, we applied multi-scale hierarchical approach of object-based methods of image analysis to ALOS - AVNIR-2 images of the year 2008-09 to map the land cover in the mangroves ecosystems of Pakistan. Considering the tide height and phonological effects of vegetation, particularly the algal mats, these data sets were meticulously chosen. Incorporation of multi-scale hierarchical structures made it easy to effectively discriminate among the land cover classes, particularly the mudflats from sparse mangroves, at their respective scales. Results of current image analysis deciphered that the overall mangroves cover of Pakistan is ~ 98,128 ha. Mangroves cover along the Indus Delta is estimated to be 92, 412 ha that is ~94.17 % of the total mangroves area of the country. 1,056 ha of the forest thrive in Sandspit, whilst the remainin 4,660 ha mangroves occurs along the Makran coast in 3 isolated pockets at Miani Hor (4,018 ha), Kalmat Khor (407 ha) and Jiwani (235 ha). Overall accuracy of land cover maps, from 250 ground reference points, was estimated to be 83.2% (kappa value .7301; kappa variance .0029) which was considered acceptable for optical data in a semi-aquatic environment.

Minhas R.A.,Jammu University | Ali U.,Jammu University | Awan M.S.,Jammu University | Ahmed K.B.,Jammu University | And 6 more authors.
Primates | Year: 2013

Grey langurs (Semnopithecus spp.) occupy a variety of habitats, ranging from lowland forests and semi-desert to alpine forests. Little is known about their foraging and ranging in alpine forests, which appear to contain less food than lowland forests. We conducted a 1-year study of Himalayan grey langurs (Semnopithecus ajax) in Machiara National Park, Pakistan, where they occur at relatively high altitudes (range 2000-4733 m). We followed three groups of different sizes and compositions and examined the effects of ecological and social factors on ranging and feeding. The home-range sizes of a small bisexual group (SBG), a large bisexual group (LBG), and an all-male group (AMG) were 2. 35 ± 0. 92 (mean ± SD; average of four seasons), 3. 28 ± 0. 55, and 3. 52 ± 1. 00 km2, respectively, and were largest in winter for all groups. The daily path lengths of the SBG, LBG, and AMG were 1. 23 ± 0. 28 (mean ± SD; average of four seasons), 1. 75 ± 0. 34, and 1. 84 ± 0. 70 km, respectively; that of the LBG was longer in winter, while that of the AMG was shorter in summer. Both the home-range size and daily path length of the AMG were larger than those of the other groups, even after partialling out the effect of group size differences. The mean altitude used by the langurs and the proportion of animals seen feeding did not differ among seasons or group types. As the mean temperature increased, the altitude used by langurs significantly increased for the SBG and LBG, but not for the AMG. On the other hand, as the temperature increased, the home-range sizes significantly decreased for the SBG and AMG, but not for the LBG. Rainfall did not show any correlation with ranging or feeding in any of the groups. Our results suggested that grey langurs in Machiara National Park employ a high-cost, high-return foraging strategy in winter, and that the ranging of the AMG also reflects its reproductive strategy. © 2013 Japan Monkey Centre and Springer Japan.

Minhas R.A.,Jammu University | Ahmed K.B.,Jammu University | Awan M.S.,Jammu University | Zaman Q.,Government of Pakistan | And 2 more authors.
Pakistan Journal of Zoology | Year: 2012

To determine the distribution patterns and population status of Himalayan Grey Langur (Semnopithecus ajax) in Machiara National Park (34o-31 N; 73o-37 E), Azad Jammu and Kashmir (Pakistan), surveys were conducted from April, 2006 to April, 2007 using 'All Count Method during transect walks. Langur troops were confined to about 4,890ha area, at 1,790-4,000m above mean sea level. Each langur troop maintained its area of distribution and movement with a little overlapping. Census revealed that the population of langur in the National Park was organized in seven uni-male bisexual troops, two multi-male bisexual troops and three all-male bands with a population density of 0.160 (individuals/ha) (n=783), comprising 10.22% adult males, 22.35% adult females, 7.28% sub-adult males, 15.96% sub-adult females, 7.79% juvenile males, 28.99% juvenile females and 7.41% infants. Copyright 2012 Zoological Society of Pakistan.

Abbas S.,GIS Laboratory | Qamer F.M.,GIS Laboratory | Rana A.D.,University of Punjab | Hussain N.,Photogrammetry and Geoinformatics | Saleem R.,GIS Laboratory
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | Year: 2010

The study aims at developing forest cover inventory from high resolution satellite imagery (0.6m) of Ayubia National Park, NWFP, Pakistan. The 3372 ha study area is one of the best examples of existing moist temperate Himalayan forest in Pakistan. Landscapes composed of large number of heterogeneous and complex elements, exhibit multi-scale hierarchical dependencies. A multi-scale object based image analysis has been carried out for the forest cover assessment of the park. Image objects representing homogenous landscape components were delineated using image segmentation routine. This approach allows efficient inclusion of spatial concepts by segmenting the digital image according to image resolution and scale of expected objects. Following the multiresolution segmentation a classification tree was developed that used a fuzzy nearest neighbor classifier to assign respective class to image segments at their respective scale. After manual classification of unclassified or misclassified objects, overall accuracy of the final out put was around 90%. Keeping in view the operational advantages and limitation of object based technique of Definiens, the proposed methodology can be easily replicated to other parts of moist temperate Himalayan forests in Pakistan. In order to meet growing needs of harmonized land cover system, class definition of FAO's Land Cover Classification System (LCCS) has been adopted.

Diaz J.A.,University of Costa Rica | Pieri D.,Jet Propulsion Laboratory | Arkin C.R.,ASRC Aerospace Corporation | Gore E.,NASA | And 8 more authors.
International Journal of Mass Spectrometry | Year: 2010

A small, 24V powered, portable mass spectrometer system, named ULISSES, for the study and visualization of gaseous volcanic emission is described. First deployments of the system have focused on both ground and airborne in situ measurement to monitor the awakening of the Turrialba Volcano in Costa Rica. Key gas measurements were acquired prior and after its eruption on 5 January 2010, confirming the presence of gas chemistry precursors typical of volcanic eruptions. Ground and airborne measurements were acquired to gain volcanological insight and as the first step towards the use of unmanned aerial vehicles (UAVs) as future airborne platforms and to confirm its unique capability to serve as a calibration/validation tool for satellite remote sensing data. Low parts per million (ppm) levels of helium and a large concentration of sulfur dioxide were measured in situ after the initial eruption. In particular, the SO2 data correlated with satellite remote sensing data. © 2010 Elsevier B.V.

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