Improving Five Grade Government Girls Primary School Students Reading Comprehension Skills in Sindh Pakistan

The design of this study was a quasi-experimental study. The study was conducted in GGPS Gul Mohmmad Parhyar. The population of this study included all the fifth grade students of GGPS Gul Mohmmad Parhyar in the academic year of 2019/2020. Two classes were selected from the population as the experimental and control groups, i.e. Class V A and Class V B. There were 15 students in Class A and 15 students in Class B. Class A was chosen as the experimental group while Class B was chosen as the control group. The experimental group was taught by using strategic reading-SQ3R whereas the control group was taught by using non-strategic reading-SQ3R. The data were collected by administering a pre-test and a post-test. The data were analyzed using independent P test.The results of the data analysis are as follows. First, the mean score of the post-test in the experimental group (29.67) is higher than that in the control group (27.33). Second, there is a significant difference in the reading comprehension ability between both groups indicated by the results, in which the significance level is 5% or 0.05 and p value 0.000 which is less then 0.05.Therefore, our result give the evidence in favor of research hypothesis that is“There is a significant difference in the reading comprehension ability between the 5th grade students GGps Gul Mohmmad Parhyar in the academic year of 2019-20. Keywords: SQ3R (Survey, Question, Read, Recall, Review). DOI: 10.7176/RHSS/11-4-03 Publication date: February 28th 202

The Effect of Shocks on the Current and Future Behavior of Sudan Economy: Autoregressive Moving-average Approach

This paper attempts to achieve two core objectives. Firstly, it aims to synthesize the information contained in the different expenditure components of GDP for developing a set of Autoregressive Moving-Average (ARMA) models to examine the effect of shocks on the current and subsequent cyclical deviations of Sudan real GDP from what is trending. Secondly, it aims to compare the intensity of those cyclical deviations within the reviewed period (1970-2010) and outside it. ARMA models of different orders are experimented to distinguish, empirically, whether the effect of shocks is transient or permanent and lasts for a long period of time. The major result is that the lingering effect of shocks is permanent causing intensified deviation from the trend outside the reviewed period

A reinforcement learning hyper-heuristic for the optimisation of flight connections

Many combinatorial computational problems have been effectively solved by means of hyper-heuristics. In this study, we focus on a problem proposed by Kiwi.com and solve this problem by implementing a Reinforcement Learning (RL) hyperheuristic algorithm. Kiwi.com proposed a real-world NP-hard minimisation problem associated with air travelling services. The problem shares some characteristics with several TSP variants, such as time-dependence and time-windows that make the problem more complex in comparison to the classical TSP. In this work, we evaluate our proposed RL method on kiwi.com problem and compare its results statistically with common random-based hyper-heuristic approaches. The empirical results show that RL method achieves the best performance between the tested selection hyper-heuristics. Another significant achievement of RL is that better solutions were found compared to the best known solutions in several problem instances

Assessment of the Self-medication with antibiotics behaviors At Khartoum Locality, Sudan,2021.

الخلفية: العلاج الذاتي هو أحد أشكال الاستخدام غير رشيد للمضادات الحيوية. المضادات الحيوية هي أكثر العقاقير التي يتم استخامها للعلاج ذاتي في العديد من أنحاء العالم . يتم الحصول على معظم المضادات الحيوية الفموية المستخدمة في جميع أنحاء العالم بدون وصفة طبية. الأهداف: لتقييم العلاج الذاتي والمعرفة السودانين تجاه فاعلية المضادات الحيوية ومقاومة المضادات الحيوية و سلوكيات المشتركين اتجاه استحدام المضادات الحيوية. الطريقة: في هذه الدراسة الوصفية والمقطعية ، تم جمع البيانات بشكل عشوائي من خلال المقابلات وجهًا لوجه باستخدام الاستبيان. أجريت هذه الدراسة بمحلية الخرطوم في 3 صيدليات تم الوصول اليها ، تم جمع البيانات عن الخصائص الاجتماعية ، والتزام المشاركين وموقفهم تجاه ممارسة العلاج الذاتي بالمضادات الحيوية ، ومعرفة المشاركين تجاه فعالية المضادات الحيوية ومقاومة المضادات الحيوية. تم تحليل البيانات باستخدام برنامج SPSS و و برنامج مايكروسفت اكسل, و كانت القيمة (p > 0.05) النتائج: من بين 50 من المشاركين ، (50٪) من المشتركين الذكور قالو أنهم استخدموا العلاج الذاتي بالمضادات الحيوية في اكثر من شهر سابق. 38٪ من المشاركين الذين تزيد أعمارهم عن 40 عامًا استخدموا المضادات الحيوية لعلاج التهاب الحلق وأعراض الأنفلونزا (القيمة الاحتمالية = 0.000). 50٪ من المشاركين الذين تتراوح أعمارهم بين (18-30) سنة (القيمة الاحتمالية = 0.000) و 35٪ من الطلاب الجامعيين المشاركين (القيمة الاحتمالية = 0.000) حصلوا على المضادات الحيوية من الصيدليات. فيما يتعلق بمعرفة المشاركين ، (62٪) من الذكور المشاركين قالو أن معلوماتهم ضعيفة عن مقاومة المضادات الحيوية. (80٪) منهم كانوا يعتقدون أن المضادات الحيوية تقتل الفيروسات. علي الرغم من ذلك 60٪ من المستجيبين عرفوا أن الاستخدام غير الحكيم للمضادات الحيوية يؤدي إلى مقاومة مضادات الميكروبات. 52٪ تتراوح أعمارهم بين (31-40) سنة استخدموا وسائل التواصل الاجتماعي كمصدر لمعلوماتهم حول العلاج الذاتي مع المضادات الحيوية ومقاومة المضادات الحيوية (القيمة الاحتمالية = 0.000). الخلاصة: كشفت النتائج عن مستوى الغير مرضي من المعرفة، واستخدام العلاج الذاتي للمضادات الحيوية ومقاومة المضادات الحيوية. ينتشر الاستخدام غير المناسب للمضادات الحيوية بشكل كبير ، على الرغم من وجود اتجاه إيجابي في المواقف والالتزام في الاستمرار في تناول الجرعة الدوائية في الوقت المحدد يوميًا. 62 ٪ من المشاركين الذكور العاطلين عن العمل أو المتقاعدين عندما شعروا بتحسن توقفوا عن تناول المضادات الحيوية (القيمة الاحتمالية = 0.000). توصي الدراسة بشدة وزارة الصحة بالاعتراف بالحملات التعليمية للجمهور السوداني لأنها مهمة في جوانب مختلفة. الكلمات الرئيسية: العلاج الذاتي بالمضادات الحيوية ، ومقاومة المضادات الحيوية ، ومستوى المعرفة

DETECTION OF GRANULATION TISSUE FOR HEALING ASSESSMENT OF CHRONIC ULCERS

Wounds that fail to heal within an expected period develop into ulcers that cause severe pain and expose patients to limb amputation. Ulcer appearance changes gradually as ulcer tissues evolve throughout the healing process. Dermatologists assess the progression of ulcer healing based on visual inspection of ulcer tissues, which is inconsistent and subjective. The ability to measure objectively early stages of ulcer healing is important to improve clinical decisions and enhance the effectiveness of the treatment. Ulcer healing is indicated by the growth of granulation tissue that contains pigment haemoglobin that causes the red colour of the tissue. An approach based on utilising haemoglobin content as an image marker to detect regions of granulation tissue on ulcers surface using colour images of chronic ulcers is investigated in this study. The approach is utilised to develop a system that is able to detect regions of granulation tissue on ulcers surface using colour images of chronic ulcers

A Robust System for Local Reuse Detection of Arabic Text on the Web

We developed techniques for finding local text reuse on the Web, with an emphasis on the Arabic language. That is, our objective is to develop text reuse detection methods that can detect alternative versions of the same information and focus on exploring the feasibility of employing text reuse detection methods on the Web. The results of this research can be thought of as rich tools to information analysts for corporate and intelligence applications. Such tools will become essential parts in validating and assessing information coming from uncertain origins. These tools will prove useful for detecting reuse in scientific literature too. It is also the time for ordinary Web users to become Fact Inspectors by providing a tool that allows people to quickly check the validity and originality of statements and their sources, so they will be given the opportunity to perform their own assessment of information quality. Local text reuse detection can be divided into two major subtasks: the first subtask is the retrieval of candidate documents that are likely to be the original sources of a given document in a collection of documents and then performing an extensive pairwise comparison between the given document and each of the possible sources of text reuse that have been retrieved. For this purpose, we develop a new technique to address the challenging problem of candidate documents retrieval from the Web. Given an input document d, the problem of local text reuse detection is to detect from a given documents collection, all the possible reused passages between d and the other documents. Comparing the passages of document d with the passages of every other document in the collection is obviously infeasible especially with large collections such as the Web. Therefore, selecting a subset of the documents that potentially contains reused text with d becomes a major step in the detection problem. In the setting of the Web, the search for such candidate source documents is usually performed through limited query interface. We developed a new efficient approach of query formulation to retrieve Arabic-based candidate source documents from the Web. The candidate documents are then fed to a local text reuse detection system for detailed similarity evaluation with d. We consider the candidate source document retrieval problem as an essential step in the detection of text reuse. Several techniques have been previously proposed for detecting text reuse, however, these techniques have been designed for relatively small and homogeneous collections. Furthermore, we are not aware of any actual previous work on Arabic text reuse detection on the Web. This is due to complexity of the Arabic language as well as the heterogeneity of the information contained on the Web and its large scale that makes the task of text reuse detection on the Web much more difficult than in relatively small and homogeneous collections. We evaluated the work using a collection of documents especially constructed and downloaded from the Web for the evaluation of Web documents retrieval in particular and the detailed text reuse detection in general. Our work to a certain degree is exploratory rather than definitive, in that this problem has not been investigated before for Arabic documents at the Web scale. However, our results show that the methods we described are applicable for Arabic-based reuse detection in practice. The experiments show that around 80% of the Web documents used in the reused cases were successfully retrieved. As for the detailed similarity analysis, the system achieved an overall score of 97.2% based on the precision and recall evaluation metrics

Hyper-heuristics for two complex vehicle routing problems: the urban transit routing problem, and a delivery and installation problem

Hyper-heuristics have emerged as general purpose search techniques that explore the space of low-level heuristics to improve a given solution under an iterative framework. They were introduced to raise the level of generality of search techniques representing self-configuring and automated reusable heuristic approaches for solving combinatorial problems. There are two classes of hyper-heuristics identified in the literatire: generation and selection hyper-heuristics. In this thesis, we focus on the class of selection hyperheuristics and their efficient design and application on complex routing problems. We specifically focus on two routing problems: the Urban Transit Network design Problem (UTRP), and a rich vehicle routing problem for the delivery and installation of equipment which was the subject of the VeRoLog solver challenge 2019. The urban transit routing problem (UTRP) aims to find efficient travelling routes for vehicles in public transportation systems. It is one of the most significant problems faced by transit planners and city authorities throughout the world. This problem belongs to the class of combinatorial problems whose optimal solution is hard to find with the complexity that arises from the large search space, and the multiple constraints imposed in constructing the solution. Furthermore, realistic benchmark data sets are lacking, making it difficult for researchers to compare their problem solving techniques with those of other researchers. We evaluate and compare the performance of a set of selection hyperheuristics on the UTRP, with the goal of minimising the passengers’ travel time and the operators’ costs. Each selection hyper-heuristic is empirically tested on a set of known benchmark instances and statistically compared against all the other hyper-heuristics to determine the best approach. A sequence-based selection method utilising a hidden markov model achieved the best performance between the tested selection methods, and better solutions than the current known best solutions are achieved on benchmark instances. Then, we propose a hyper-heuristic algorithm specifically designed to solve the UTRP with defined terminal nodes that determine the start and end points of bus journeys. The algorithm is applied to a novel set of benchmark instances with real world size and characteristics representing the extended urban area of Nottingham city. We compare the hyper-heuristic performance on the data set with the NSGAII algorithm and real world bus routes, and prove that better solutions are found by hyper-heuristics. Due to the clear gap in research between the application of optimisation algorithms in public routes network optimisation and the real world planning processes, we implemented a hyper-heuristic algorithm that interactively work with interface procedures to optimise the public transport lines in Visum transportation modelling software. We adopt Selection Hyper-heuristics for two optimisation problems and the optimisation objectives include the passengers’ average travel time and operators’ costs. The results demonstrate the successful implementation of the applied optimisation methods for multi-modal public transport networks. Finally we introduce a population based hyperheuristic algorithm and apply it on a complex vehicle routing problem consisting of two stages: a Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) for the delivery of equipment, and the Service Technician Routing and Scheduling Problem (STRSP) for the installation of the delivered equipment. This problem was the subject of the VeRoLog solver challenge 2019. We apply the hyper-heuristic population-based algorithm on a small and large size data sets, and show that our approach performed better in terms of results and run time on small instances compared to the results of mathematical model implemented for this problem. We perform analysis of the new proposed algorithm and show that it finds better quality solutions compared to its constituent selection hyper-heuristics when applied individually. Finally we conclude the thesis with a summary of the work and future plans

Solving urban transit route design problem using selection hyper-heuristics

The urban transit routing problem (UTRP) focuses on finding efficient travelling routes for vehicles in a public transportation system. It is one of the most significant problems faced by transit planners and city authorities throughout the world. This problem belongs to the class of difficult combinatorial problems, whose optimal solution is hard to find with the complexity that arises from the large search space, and the number of constraints imposed in constructing the solution. Hyper-heuristics have emerged as general-purpose search techniques that explore the space of low level heuristics to improve a given solution under an iterative framework. In this work, we evaluate the performance of a set of selection hyper-heuristics on the route design problem of bus networks, with the goal of minimising the passengers’ travel time, and the operator’s costs. Each selection hyper-heuristic is empirically tested on a set of benchmark instances and statistically compared to the other selection hyper-heuristics to determine the best approach. A sequence-based selection method combined with the great deluge acceptance method achieved the best performance, succeeding in finding improved results in much faster run times over the current best known solutions

Probing Imidazotetrazine Prodrug Activation Mechanisms

yesThe archetypal prodrug of the imidazotetrazine class is the anticancer agent temozolomide (TMZ). The prodrug activation kinetics of TMZ show an unusual pH dependence: it is stable in acid and rapidly hydrolyses in alkali (Denny, B.J., et al. Biochemistry 1994, 33, 9045–9051). The incipient drug MTIC has the opposite properties—relatively stable in alkali but unstable in acid. In this study, the mechanism of prodrug activation was probed in greater detail to determine whether the reactions are specific or general acid or base catalysed. Three prodrugs and drugs were investigated, TMZ, MTIC and the novel dimeric imidazotetrazine EA27. Hydrolysis in a range of citrate-phosphate buffers (pH 8.0, 7.4, 4.0) was measured by UV spectrophotometry. Reaction of TMZ and MTIC obeyed single-phase, pseudo-first order kinetics (Figure 1). EA27 was more complex, showing biphasic but approximately pseudo-first order kinetics, Figure. General acid or base catalysis indicates that protonation or deprotonation is the rate-limiting step (rls). In biological milieu, the nature and concentration of other acidic or basic solutes may affect the prodrug activation reaction. In contrast, specific acid or base catalysis indicates that protonation or deprotonation occurs before the rls, so catalysis depends only on the local concentration of hydroxide or hydronium ion (i.e., pH) so the reaction kinetics are not expected to change appreciably in a biological medium