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Optimization of Regeneration and Transformation of Fagonia Indica

Thesis Info

Author

Maryam Naeem

Department

Department of Biochemistry, QAU

Program

Mphil

Institute

Quaid-i-Azam University

Institute Type

Public

City

Islamabad

Province

Islamabad

Country

Pakistan

Thesis Completing Year

2015

Thesis Completion Status

Completed

Page

ix,87

Subject

Biochemistry

Language

English

Other

Call No: Diss / M.Phil / BIO /3984

Added

2021-02-17 19:49:13

Modified

2023-02-19 12:33:56

ARI ID

1676716928415

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50. Qaf/Qaf

50. Qaf/Qaf

I/We begin by the Blessed Name of Allah

The Immensely Merciful to all, The Infinitely Compassionate to everyone.

50:01
a. Qaf.
b. By The Qur’an, The Majestic.

50:02
a. They consider it strange that a Warner has come to them from amongst themselves.
b. So the disbelievers say:
c. ‘This is certainly something strange!’

50:03
a. How can it be that when we will be dead and turned to mere dust in the grave that we will be brought back to another dimension of existence?
b. Such a return to another dimension of existence is far-fetched.

50:04
a. Thus do they reckon while WE Know well what the earth consumes of them,
b. and with US is a Record which keeps track of their deeds, dealings, speech and preserves everything.

50:05
a. Rather they denied and belied The Truth - The Qur’an - when it came to them,
b. so now they are in a state of confusion.

50:06
a. Would they never look up to the celestial realm, above them, and reflect,
- how WE built it without apparent supports, and
- how WE beautified it with planets, and
- how come it has no flaws in it?

50:07
a. And the earth – how did WE spread it out, and cast upon it firm mountains,
b. and made all kinds of splendid vegetation, in pairs, to grow upon it.

50:08
a. WE did all this as an evidence as well as a reminder for every person who turns to Allah in awe, reverence and piety.

50:09
a. And also WE...

Fasting Gastric Acidity Evidential Effect on Esophageal Mucosal Damage

Gastric substances that potentially increase the esophageal mucosal damage are: gastric acid, pepsin, bile salts, and pancreatic enzymes. From all of these substances, the highest potential for reflux damage is gastric acid. Although the main cause of clinical symptoms of GERD is acid reflux, it has been known that there are subgroups with typical reflux symptoms that do not provide sufficient response or not responsive to PPI treatment. Despite the improvement of esophagitis, there is no clinical improvements in reflux symptoms of 30% respondents. Therefore, this study was designed to determine fasting gastric acidity with endoscopic findings in patients with GERD. A comparative-analysis study, which determine the fasting gastric acidity from endoscopic findings in patients with GERD. Samples recruited using consecutives sampling technique and divided into groups of esophagitis and non-esophagitis reflux. A total of 40 samples involved in this study. The Mann-Whitney test, was used for analyzing the difference between fasting gastric acidity from endoscopic findings of esophagitis lesions in patient with GERD. The median value for fasting gastric acidity in the esophagitis reflux group was 1.88 (0.82-4.84), whereas the median value for fasting gastric acidity in the non-esophagitis reflux group was 2.49 (0.68-5.97). The Mann-Whitney test result was p=0.298 (p>0.05). This study shows that there is no significant difference of fasting gastric acidity from endoscopic findings between esophagitis and non esophagitis reflux groups in patients with gastroesophageal reflux disease (GERD). This study shows that esophagitis lesions are not affected by gastric acidity.

Mapping Simulated Bt Cotton Productivity in Punjab under Changing Climate Scenarios Using Modelling and Gis Tools

Cotton is very important cash crop of Pakistan and its yield and fiber quality is directly affected by future changing climate. Two-year experiment was conducted at Faisalabad, Sahiwal and Multan during summer season of 2014 and 2015 to estimate crop yield under changing climate scenarios and develop cotton productivity maps using modeling and GIS. The treatments were comprised of two sowing dates (1st May and 1st June), three cotton cultivars (FH-114, FH-142 and MNH-886) and three nitrogen rates (150, 200 and 250 kg ha-1). Experiment was planned in randomized complete block design with split-split plot. Statistical analysis of agronomic data collected from two-year experiment confirmed that cultivars FH-142 and MNH-886 sown with 200 kg N ha-1 on 1st May performed well under Faisalabad, Sahiwal and Multan. Crop model Decision Support System for Agro-Technology Transfer (DSSAT) simulated crop phenology, seasonal crop biomass, leaf area dynamics and seed cotton yield. The observed data was used for calibration and evaluation of CROPGRO-Cotton Model. Model calibrated well with the best treatment (1st May sown crop with 200 kg N ha-1) having Root Mean Square Error (RMSE) of 0.81 day, 407.28 kg ha-1, 448.40 kg ha-1, 0.23, 0 day for anthesis days, total dry matter, seed cotton yield, leaf area index and maturity days for cultivar FH-142, respectively. Simulation results from seasonal analysis depicted that under future climate, 16%, 34% and 45% yield loss at Faisalabad; 23%, 34% and 36% yield reduction at Sahiwal and 20%, 32% and 35% decrease in yield at Multan till end of early, mid and late century, respectively. Strategy analysis showed that timely sown cotton cultivar FH-142 at Faisalabad and Sahiwal and MNH-886 at Multan in month of May with 200 kg N ha-1 can be viable option to get maximum yield. Geographic Information System (GIS) maps of cotton productivity were generated by running model in R script with two methods. Spatial analysis with Weather generator showed that cotton yield will reduce in future all over Punjab and Dera Gazi Khan, Mianwali and Khushab districts have potential of higher seed cotton yield under 2°C rise in temperature in future. GIS maps with Metamodel showed similar results along with Sahiwal, Okara and Pakpatthan as potential districts for future cotton in Punjab. Crop Model and Geospatial maps based on simulation can be helpful tools to predict crop yield under future climate to develop site-specific adaptation strategies by adjustment of sowing dates and fertilizer with better management practices for different genotypes.