صحیح بخاری کی کتاب التفسیر کے فنی مباحث کا اختصاصی مطالعہ

The book of tafseer of Sahi Bukhari is most comprehensive book among the books of Hadith and on the basis of many features, it is considered superior to many other books of Hadith. Imam Bukhari annotates each surah one by one in his book of tafseer and constructs 114 chapters equal to the number of surah and these chapters carry 548 hadith of Zikr in which 465 are Mosool and remaining are mualaq and 100 hadith are not described before and remaining are repetitive. Imam Bukhari implements both style of description that is tafseer bil masaur and tafseer bil rai which proves the fact that Imam Bukhari supports the style of tafseer bil rai mehmood. Many Quranic information can be collected from book of tafseer for example: sabub nazool, makki & madni, ilmul qirat, ghareebul quran etc. The derivation of these features the book of tafseer of Sahi Bukhari is not the end but it is a starting point for new study.

Acoustic Zoning Mapping and Prediction Modeling of Urban Zones of Peshawar

Noise is a well-known source of pollution in urban areas and recognized as one of the main and significant environmental problems and considered as the most pervasive hazardous pollution. It has detrimental effects on the health of people and becoming imposition upon human health and unjustifiable interference in the comfort and quality of modern life. Peshawar is one such area, located at the north-west of Pakistan that is experiencing high noise levels due to structural changes, extension of road networks, incessant increase in the number of vehicles and unbalanced urban development at both ends of the city. In order to check the severity of the mentioned issue, this study was carried out to quantify the noise pollution levels, effects on the health of the exposed population and effectiveness of the legislation to deal with it. The 24h acoustic survey was conducted with the Extech’s Datalogging Sound Level Meter at residential, commercial and silence zone and results were compared with the Pak-NEQS (2010) for noise. From the collected data different noise descriptors such as Leq, L1, L10, L50, L90, L99, LNP, NC, NEI and TNI both for day and nighttime were computed for all zones. Noise levels were measured at 30 residential locations, 23 commercial locations and 6 silence zone of the study area. The highest values of Leq dB (A) for daytime and nighttime for residential areas were recorded as 77.9 dB (A) and 70.9 dB (A), respectively. Similarly, for commercial areas the highest Leq for daytime was recorded as 87.2 dB (A) and for nighttime was recorded as 70.7 dB (A). Highest and lowest Leq dB (A) recorded at silence zone for daytime and nighttime were 72.3 dB (A) and 64.1 dB (A), respectively. The result showed that 90 % of residential sites, both for daytime and nighttime, 91% of commercial locations for daytime, 87% of commercial locations for nighttime, 100% silence zone for daytime and 83% for nighttime showed the values of Leq dB (A), beyond the permissible limit set out by NEQS-Pak (2010). The results of the noise indices for commercial and residential areas showed that noise fluctuates broadly and extreme fluctuations was encountered for 50% locations where, Leq values exceeded L90 by 10 dB(A) and same results were also witnessed for nighttime. However, for silence zone noise fluctuations were very little. The hourly Leq and noise indices for all residential, commercial and silence zone showed that Leq values were close to L10 values, which showed that fluctuations were broad and only at few locations extreme and little fluctuations were observed. Values of LNP and NC showed that fluctuations were high in commercial areas followed by residential and then silence zone both for day and nighttime. . Similarly, the NEI calculated for all the areas showed that maximum sites showed a value greater than 1. Similarly, high values of TNI were also recorded for all areas. Comparing Leq between different times of the day for commercial, residential and silence zones using ANOVA and Tukey statistical test at P<0.05 level a significance difference has been reported between different hours during daytime. Pearson correlation was performed and a strong positive correlation was found between Leq and L10, L50 Leq, L90, L1, L99, Max and Min noise levels for all zones. Significant effects of areas on the values of Ld, L10, L50, LNP were observed. Post hoc comparisons for Ld, L10, L50 and NC using the Tukey HSD test indicated that the mean score for the commercial areas during daytime for Ld was significantly different than residential areas but for nighttime no significant difference was found for all noise indices for any other area. From the collected data noise maps were also generated for daytime and nighttime using ArcGIS 9.3. Different acoustic zones were identified in the project area and the acoustic classification of the study area was used to classify the territory into six zones depending on the activities taking place in the areas. The HUD classification was used to identify the areas falling under different zones. The map showed that most of the areas fell under the normally unacceptable zone for daytime and normally acceptable zone for nighttime. A representative sample of population was interviewed using a questionnaire survey technique. Stakeholders such as policemen, shopkeepers, students, and drivers were selected as a target community. The results were analyzed through SEM and it indicates that exposure to noise for longer duration may cause headache, exhaustion, frustration and anxiety. However, person sensitive to noise may also experience difficulty in understanding speech and night awakenings in addition to the above mentioned diseases. These problems give rise to secondary issues like dizziness and ringing in ears. It is concluded that noise levels were quite high in urban zones of Peshawar owing to number of problems. One such problem is the lack of proper and comprehensive legislations for noise. Based on the data collected, a model to predict equivalent noise levels was proposed using SPSS version 18. For the development of the multiple linear regression model, the parameters used were two wheelers, three wheelers, four wheelers, van/Suzuki, bus/truck, carts and road width. A very low percentage of error for the data was exhibited by the proposed model. The main factor responsible for high noise levels was found to be traffic and its intensity. Ill planned fast growing traffic especially 3 wheelers and 2 wheelers were the main sources of traffic noise. In order to reduce the ill-effects of noise on the urban residents of Peshawar concrete actions from all the relevant agencies are needed to address the growing problem of noise pollution.