A study of an environmental assessment of dust fall and the associated heavy metal contents was conducted during the period from the first of March 2011 to the end of February 2012 at adjoining area of a phosphate fertilizer plant. Around the industrial area 8 dust fall stations were established and one of them was built upwind far from pollution activities to be taken as a control sample. Dust fall samples collected monthly weighed and then prepared to be analyzed through Inductively Coupled Plasma-Mass Spectroscopy (ICP-MS) to obtain heavy metal concentration. Meteorological parameters influencing the distribution of dust fall such as wind speed and direction, temperature, humidity, rain fall and pressure were determined. Results showed that deposition flow rates were 38.2. 47.5, 57.7, 44.3, 39.4, 38.2, 42.7 and 5.9 g/m2·month for the sites No., 1, 2, 3, 4, 5, 6, 7 and 8 respectively, and were compared with the findings of other investigators of like industrial areas worldwide. Levels of heavy metal As, Cu, Pb, Zn, Cd, and Hg in the deposited dust fall were 3.30, 26.46, 22.33, 235.00, 4.53 and 3.80 μg/g respectively. Enrichment coefficients of the heavy metals in the dust fall were found to be significant and reached the values 1.81, 0.90, 0.85, 0.65, 0.41 and 0.35 for zinc, lead, cadmium, copper, mercury and arsenic respectively. The paper ends with results and recommendations suggesting a methodology to remediate the investigated area polluted with heavy metals and control measures for the fertilizer plant to reduce pollution into the surrounding environment.

تناقش الورقة البحثية معوقات تنمية السياحة الاستشفائية في محافظة حضرموت كأحد أهم أنواع السياحة بها تهدف الورقة البحثية إلى تحديد المتطلبات الأساسية التي تحتاجها هذه النوعية من السياحة من خلال دراسة مقومات تنمية السياحة الاستشفائية في مدينة الديس الشرقية )منطقةالدراسة (والتي تم اختيارها لما تشتهر به من مناطق عيون كبريتية ذات فوائد صحية.وتم من خلال الدراسة استخلاص الإمكانات المتوفرة )نقاط القوة (والمعوقات والمشاكل القائمة )نقاط الضعف (،ثم تم تحديد الفرص المتاحة والتهديدات المحتملة، وتم تحليل البيانات السابقة )نقاط القوة، نقاط الضعف، الفرص، التهديدات ) عن طريق التحليل الرباعي والتي تم من خلاله تحديد المتطلبات الأساسية التي تحتاجها تنمية مناطق السياحة الاستشفائية، وتخلص الورقة البحثية إلى وضع توجهات للحلول التي من خلالها يمكن رفع كفاءة هذه المناطق وزيادة أعداد السياح بما يتواكب مع طبيعة البيئة المحلية لمنطقة الدراسة .

تناقش الورقة البحثية معوقات تنمية السياحة الاستشفائية في محافظة حضرموت كأحد أهم أنواع السياحة بها تهدف الورقة البحثية إلى تحديد المتطلبات الأساسية التي تحتاجها هذه النوعية من السياحة من خلال دراسة مقومات تنمية السياحة الاستشفائية في مدينة الديس الشرقية )منطقةالدراسة (والتي تم اختيارها لما تشتهر به من مناطق عيون كبريتية ذات فوائد صحية.وتم من خلال الدراسة استخلاص الإمكانات المتوفرة )نقاط القوة (والمعوقات والمشاكل القائمة )نقاط الضعف (،ثم تم تحديد الفرص المتاحة والتهديدات المحتملة، وتم تحليل البيانات السابقة )نقاط القوة، نقاط الضعف، الفرص، التهديدات ) عن طريق التحليل الرباعي والتي تم من خلاله تحديد المتطلبات الأساسية التي تحتاجها تنمية مناطق السياحة الاستشفائية، وتخلص الورقة البحثية إلى وضع توجهات للحلول التي من خلالها يمكن رفع كفاءة هذه المناطق وزيادة أعداد السياح بما يتواكب مع طبيعة البيئة المحلية لمنطقة الدراسة .

Goslar district in Lower-Saxony, Germany, was one of the most important mining and metal production areas in the world. The long time of mining, mineral processing and smelting activities in the area have enriched the forest soil with many heavy metals. Spatial distribution of soil heavy metals Pb, Zn, and As was investigated using geostatistical methods and geographic information system (GIS). Geostatistical Analyst extension of ArcGIS was used to explore the raw data, transform to normality and calculate the experimental variogram and its fitted model. Ordinary Kriging was applied to predict the spatial distribution of soil heavy metals. A GIS model was built to optimize the spatial distribution of heavy metals by selecting new soil samples in sites of maximum Standard Prediction Error. Comparison between predicted surfaces before and after taking the new samples was studied. Hotspot locations of polluted soil were investigated by creating specific geostatistical structures for each intensive contaminated site. These specific predicted surfaces of hotspot locations are merged into the general predicted surface of the same soil heavy metal.

Pollution indices were used to investigate the levels of heavy metal concentrations in a polluted area under the effect of fertilizer plant emissions at Manqabad, Assiut. Huge amounts of dusts, fumes and gases containing heavy metals which are released from the industrial processing activities, precipitated in the neighbouring area by the effect of meteorological factors causing soil pollution. Soil samples were taken from the area downwind of the factory and analyzed to detect concentration of heavy metals in the study area. Results of soil analysis showed that the area has been harmfully affected by the heavy metals: Cd, Cu, Pb and Zn and their average concentrations are 0.3 mg/kg, 57.0 mg/kg, 94.7 mg/kg and 80.7 mg/kg respectively. These values exceeded the concentrations in soil background (0.013 mg/kg for Cd, 9.62 mg/kg for Cu, 5.17 mg/kg for Pb and 11.56 mg/kg for Zn) obtained from unpolluted area far from industrial activities and also exceeded the international standards for soil pollution stated by WHO. Pollution indices were developed to evaluate the levels of soil pollution with heavy metals. Index of geo-accumulation (Igeo), Enrichment Factor (EF), Pollution Index (PI), and Load Pollution Index (LPI), were estimated. The calculated results of contamination degree showed that the investigated area lies under the class of high pollution. In final conclusion, the investigated area is highly affected by emissions from the fertilizer plant. So control measures should be applied to the fertilizer plant and the polluted soil area adjacent to the factory should be remediate.

Pollution indices were used to investigate the levels of heavy metal concentrations in a polluted area under the effect of fertilizer plant emissions at Manqabad, Assiut. Huge amounts of dusts, fumes and gases containing heavy metals which are released from the industrial processing activities, precipitated in the neighbouring area by the effect of meteorological factors causing soil pollution. Soil samples were taken from the area downwind of the factory and analyzed to detect concentration of heavy metals in the study area. Results of soil analysis showed that the area has been harmfully affected by the heavy metals: Cd, Cu, Pb and Zn and their average concentrations are 0.3 mg/kg, 57.0 mg/kg, 94.7 mg/kg and 80.7 mg/kg respectively. These values exceeded the concentrations in soil background (0.013 mg/kg for Cd, 9.62 mg/kg for Cu, 5.17 mg/kg for Pb and 11.56 mg/kg for Zn) obtained from unpolluted area far from industrial activities and also exceeded the international standards for soil pollution stated by WHO. Pollution indices were developed to evaluate the levels of soil pollution with heavy metals. Index of geo-accumulation (Igeo), Enrichment Factor (EF), Pollution Index (PI), and Load Pollution Index (LPI), were estimated. The calculated results of contamination degree showed that the investigated area lies under the class of high pollution. In final conclusion, the investigated area is highly affected by emissions from the fertilizer plant. So control measures should be applied to the fertilizer plant and the polluted soil area adjacent to the factory should be remediate.

In this paper, a new approach for human recognition using heart sounds is proposed. The new approach is based mainly on extracting features from heart sounds using wavelet packet decomposition. Different linear and non-linear filter banks at different decomposition levels are designed using wavelet packet decomposition to select the appropriate bases for extracting discriminant features. Automatic wavelet de-noising and linear discriminant analysis are adopted for pre-processing and classification stages, respectively. The proposed system is tested using an open database for heart sounds known as HSCT-11 which contains data collected from 206 subjects. Based on the achieved results, the proposed system can identify subjects with best accuracy of 91.05% and verify them with an equal error rate of 3.2%. The obtained results in this paper show that wavelet packet based features are appropriate for human recognition task using heart sounds.

In this paper, a new approach for human recognition using heart sounds is proposed. The new approach is based mainly on extracting features from heart sounds using wavelet packet decomposition. Different linear and non-linear filter banks at different decomposition levels are designed using wavelet packet decomposition to select the appropriate bases for extracting discriminant features. Automatic wavelet de-noising and linear discriminant analysis are adopted for pre-processing and classification stages, respectively. The proposed system is tested using an open database for heart sounds known as HSCT-11 which contains data collected from 206 subjects. Based on the achieved results, the proposed system can identify subjects with best accuracy of 91.05% and verify them with an equal error rate of 3.2%. The obtained results in this paper show that wavelet packet based features are appropriate for human recognition task using heart sounds.

In this paper, a new approach for human recognition using heart sounds is proposed. The new approach is based mainly on extracting features from heart sounds using wavelet packet decomposition. Different linear and non-linear filter banks at different decomposition levels are designed using wavelet packet decomposition to select the appropriate bases for extracting discriminant features. Automatic wavelet de-noising and linear discriminant analysis are adopted for pre-processing and classification stages, respectively. The proposed system is tested using an open database for heart sounds known as HSCT-11 which contains data collected from 206 subjects. Based on the achieved results, the proposed system can identify subjects with best accuracy of 91.05% and verify them with an equal error rate of 3.2%. The obtained results in this paper show that wavelet packet based features are appropriate for human recognition task using heart sounds.

This paper aims to turn complex groundwater data into comprehensible information by indexing the different factors numerically comparative to the standards of World Health Organization (WHO) to produce Water Quality Index (WQI). Water Quality Index (WQI) has been used to assess groundwater quality and Geographic Information Systems (GIS) has been used to create maps representing the spatial distribution of groundwater categories in Assiut governorate, Egypt. Water Quality Index has been computed by Un-weighted Arithmetic Water Quality Index (WQIUA) method and applied on 796 wells over eight years from 2006 to 2013. The results showed that WQIUA values for drinking purposes were high and most of them reached higher or close to 100, which indicated that the groundwater was polluted and unsafe for drinking. On the other hand, the quality index of groundwater for irrigation purposes in most of the study area ranges between 55.78 and 78.38 (poor and very poor category); this means that groundwater is moderately polluted and rather suitable for irrigation.