A Statistical Model to Predict the Strength Development of Geopolymer Concrete Based on SiO2/Al2O3 Ratio Variation

Geopolymer Concrete (GPC) is a new class of concrete that presents a vital improvement in sustainability and the environment, particularly in recycling and alternative construction methods. Geopolymers offer a sustainable, low energy consumption, low carbon footprint, and a 100% substitute for the Portland cement binder for civil infrastructure applications. Furthermore, many aluminosilicate materials can be obtained as by-products of other processes, such as coal combustion or the thermal pulping of wood. In addition, slag and fly ash are necessary to source materials for geopolymer. Therefore, geopolymer is considered a solution for waste management that can minimize greenhouse gas emissions. In this statistical study, the present experimental work and found experimental data were collected from local and international literature and were used to build and validate the statistical models to predict the strength development of Geopolymer concrete with binary and ternary systems of source materials. The main independent variable was R, representing the ratio of SiO2/Al2O3by weight in the source material. The investigated range of R was 1.42–3.6. Nine concrete geopolymer mixes with R in the above range represent the experimental part carried out. The targeted properties were compressive, splitting, and flexural strengths. The experimental results showed that the R ratio significantly influences the mechanical performance of the final product. The compressive strength improved by 82, 86, 93, and 95%, when metakaolin content was partially replaced by fly ash and GGBS by percentages of 30, 70, 72, 90, and 95% for mixes 2, 3, 5, 7, and 8 respectively. Also, when GGBS partially replaced fly ash content by 36% and 100% for mixes 6 and 9, compressive strength improved by 10.6% and 41.8%, respectively, compared to mix4. Furthermore, the statistical study revealed that the R ratio might be utilized to determine geopolymer strength with reasonable accuracy. The built models were developed by linear and non-linear regression analysis using SPSS software, version 25. Doi: 10.28991/CEJ-2022-08-03-04 Full Text: PD

UK corporate data and future cash flows

This study examines the ability of current accounting data to explain future cash flows for UK firms, as disclosed under FRS I (1991, revised 1996). Rather than examining price data - from which cash flow implications have to be inferred -a more direct approach used in several recent US studies is adopted, in which actual future cash flow data are examined. Specifically, the methodology is a development of the OLS regression framework employed by Barth, et al. (2001). In the first stage of this study, a replication of their main OLS analysis is provided, and then extended to deal with fixed effects and time trends in the levels of cash flow data. The results show that (i) aggregate accruals have incremental information content beyond that already existing in aggregate earnings; (ii) the main components of aggregate accruals (depreciation and changes in accounts payable, accounts receivable, inventory) have incremental information content beyond that already existing in either earnings or aggregate accruals; and (iii) cash flows alone outperform earnings alone in explaining the variation in future cash flows. Furthermore, accruals (either aggregate or the individual components of accruals) have incremental information content beyond that already existing in cash flows. This evidence supports FRS I's assertion that accruals data should be used in conjunction with cash flow data in predicting future cash flows. The research design is then developed to examine the effect of firm characteristics on the association of earnings, cash flows and accruals with future cash flows. The results show that the decomposition of earnings into cash flows and accruals is more relevant and more value useful when: (i) the length of the operating cycle is short; (ii) the performance level is not extreme; (iii) the magnitude of total accruals is high; and (iii) the probability of default risk is high. The results also reveal that earnings outperform cash flows in explaining the variation in future cash flows when: (i) the magnitude of total accruals is low, and (ii) the probability of default risk is low.EThOS - Electronic Theses Online ServiceHashemite UniversityGBUnited Kingdo

Genetic-Moth Swarm Algorithm for Optimal Placement and Capacity of Renewable DG Sources in Distribution Systems

This paper presents a hybrid approach based on the Genetic Algorithm (GA) and Moth Swarm Algorithm (MSA), namely Genetic Moth Swarm Algorithm (GMSA), for determining the optimal location and sizing of renewable distributed generation (DG) sources on radial distribution networks (RDN). Minimizing the electrical power loss within the framework of system operation and under security constraints is the main objective of this study. In the proposed technique, the global search ability has been regulated by the incorporation of GA operations with adaptive mutation operator on the reconnaissance phase using genetic pathfinder moths. In addition, the selection of artificial light sources has been expanded over the swarm. The representation of individuals within the three phases of MSA has been modified in terms of quality and ratio. Elite individuals have been used to play different roles in order to reduce the design space and thus increase the exploitation ability. The developed GMSA has been applied on different scales of standard RDN of the (33 and 69-bus) power systems. Firstly, the most adequate buses for installing DGs are suggested using Voltage Stability Index (VSI). Then the proposed GMSA is applied to reduce real power generation, power loss, and total system cost, in addition, to improve the minimum bus voltage and the annual net saving by selecting the DGs size and their locations. Furthermore, GMSA is compared with other literature methods under several power system constraints and conditions, in single and multi-objective optimization space. The computational results prove the effectiveness and superiority of the GMSA with respect to power loss reduction and voltage profile enhancement using a minimum size of renewable DG units

MSA for Optimal Reconfiguration and Capacitor Allocation in Radial/Ring Distribution Networks

This work presents a hybrid heuristic search algorithm called Moth Swarm Algorithm (MSA) in the context of power loss minimization of radial distribution networks (RDN) through optimal allocation and rating of shunt capacitors for enhancing the performance of distribution networks. With MSA, different optimization operators are used to mimic a set of behavioral patterns of moths in nature, which allows for flexible and powerful optimizer. Hence, a new dynamic selection strategy of crossover points is proposed based on population diversity to handle the difference vectors Lévy-mutation to force MSA jump out of stagnation and enhance its exploration ability. In addition, a spiral motion, adaptive Gaussian walks, and a novel associative learning mechanism with immediate memory are implemented to exploit the promising areas in the search space. In this article, the MSA is tested to adapt the objective function to reduce the system power losses, reduce total system cost and consequently increase the annual net saving with inequity constrains on capacitor size and voltage limits. The validation of the proposed algorithm has been tested and verified through small, medium and large scales of standard RDN of IEEE (33, 69, 85-bus) systems and also on ring main systems of 33 and 69-bus. In addition, the obtained results are compared with other algorithms to highlight the advantages of the proposed approach. Numerical results stated that the MSA can achieve optimal solutions for losses reduction and capacitor locations with finest performance compared with many existing algorithms

Protective effect of olive and juniper leaves extracts on nephrotoxicity induced by thioacetamide in male mice

AbstractThis study, for the first time, evaluates the effect of olive and juniper leaves extracts and their combination on thioacetamide (TAA)-induced nephrotoxicity in male mice. The experimental mice were divided into eight groups. Group 1 was served as control. Group 2 was exposed to TAA. Group 3 was treated with TAA and olive leaves extract. Group 4 was subjected to TAA and juniper leaves extract. Group 5 was exposed to TAA and olive and juniper leaves extracts. Groups 6, 7 and 8 were treated with olive, juniper, and olive and juniper leaves extracts respectively. In mice treated with only TAA, significant increases of blood urea nitrogen and uric acid were observed after six weeks. Moreover, levels of serum creatinine, blood urea nitrogen and uric acid were statistically increased in mice administrated with only TAA for twelve weeks. Insignificant alterations in levels of these haematobiochemical parameters were noted in other treated groups after six and twelve weeks. Histopathological evaluations of renal sections from mice treated with only TAA for twelve weeks showed severe damage of the renal corpuscles. Furthermore, the renal sections from mice treated with TAA and olive leaves extract, TAA and juniper leaves extract, TAA and olive and juniper leaves extracts, olive leaves extract, juniper leaves extract, and olive and juniper leaves extracts showed normal structures. In addition, it is conceivable therefore, that these extracts exhibit protective influences against TAA-induced nephrotoxicity, probably mediated through the antioxidative pathway roles

The Reality of organizational commitment in ministry of planning and international cooperation in Jordan: The employees perspective: Field study

هدفت الدراسة الى معرفة واقع الالتزام التنظيمي في وزارة التخطيط والتعاون الدولي،من وجهة نظر الموظفين، من خلال الابعاد التالية (الالتزام العاطفي،الالتزام المعياري،الالتزام الاستمراري) حيث تم توزيع (200) استبانة, وتم استرداد (155) استبانة واستبعاد (4) استبيانات بسبب عدم اكتمال إجابة المبحوثين عليها, حيث بلغت الاستبيانات الخاضعة للتحليل (151) استبانة, وبالتالي فان نسبة الاستبيانات المستخدمة في التحليل (75.5%) من مجموع الاستبيانات الموزعة، وبعد ان تم تحليلها احصائيا على نظام(spss) اظهرت النتائج بان مستوى الالتزام التنظيمي يعتبر مرتفعا بشكل عام في وزارة التخطيط والتعاون الدولي حيث يوجد مستوى من الالتزام التنظيمي بأبعاده (الالتزام العاطفي, الالتزام الاستمراري, الالتزام المعياري) في وزارة التخطيط والتعاون الدولي في الأردن وهذا يدل على ان الوزارة تهتم بموظفيها وتوفر لهم بيئة العمل المحفزة والداعمة حيث جاء مستوى الالتزام العاطفي كأعلى نسبة مرتفعة حيث بلغت  (80.8%) ثم يليها الالتزام المعياري بنسبة (74%) في حين جاء الالتزام الاستمراري كأقل نسبة حيث بلغت (69.6%)اوصت الدراسة بالاستمرار بتوفير البيئة المحفزة للمحافظة على مستويات الالتزام التنظيمي لدى موظفي وزارة التخطيط والتعاون الدولي كما اوصت بضرورة اجراء المزيد من الابحاث والدراسات حول موضوع الالتزام التنظيمي في القطاع العام.The study aims to specify the reality of organaizational commitment in minustry od planning and international cooperation in Jordan,through the following dimensions (emotional commitment, normative commitment, continuous commitment), where 200 questions were distributed, (151) questionnaires, and therefore the percentage of questionnaires used in the analysis (75.5%) of the total questionnaires distributed, The results showed that the level of organizational commitment is generally high in the Ministry of Planning and International Cooperation, where there is a level of organizational commitment in its dimensions (emotional commitment, continuous commitment, normative commitment) in the Ministry of Planning and International Cooperation in Jordan. Indicates that the ministry cares about its employees and provides them with a stimulating and supportive work environment. The level of emotional commitment reached the highest percentage (80.8%) followed by the standard commitment (74%) while the continuous commitment was the lowest percentage (69.6%) The study recommended to continue to provide incentive to maintain the organizational commitment of the Ministry of Planning and International Cooperation staff levels of the environment, also recommended the need for more research and studies on the subject of commitment Organizational structure in the public sector

The Effect of Addition of CeO2 Nanoparticles on the Microstructure and Mechanical Properties of Ti-Al-Mg Compact Samples

In this research, Ti-15Al-5Mg alloy with different amount of CeO2 nanoparticles was prepared by powder metallurgy method, the powders of these materials were mixed together by ball mill then the mixed powders were pressed under high pressure, the compacted samples were sintered in electron furnace under argon gas. The density and porosity measured using Archimedes method, XRD and SEM images were used to detect phase's peaks and microstructure of all alloy sets. Vickers micro-hardness measured and Brazilian compressive tests, the results of these tests were drawing in charts with porosity and CeO2 nanoparticles percentage. From these results the best amount of CeO2 is 7 vol.% which give best mechanical and physical properties, because of created of (Ti-CeO2)

Synthetic generation of multidimensional data to improve classification model validity

This article aims to compare Generative Adversarial Network (GAN) models and feature selection methods for generating synthetic data in order to improve the validity of a classification model. The synthetic data generation technique involves generating new data samples from existing data to increase the diversity of the data and help the model generalize better. The multidimensional aspect of the data refers to the fact that it can have multiple features or variables that describe it. The GAN models have proven to be effective in preserving the statistical properties of the original data. However, the order of data augmentation and feature selection is crucial to build robust and accurate predictive models. By comparing the different GAN models with feature selection methods on multidimensional datasets, this article aims to determine the best combination to support the validity of a classification model in multidimensional data.</p

Short Term Effectiveness of Gamma Knife Radiosurgery in the Management of Brain Arteriovenous Malformation

AIM: To evaluate the short-term effectiveness of Gamma knife radiosurgery as a modality of treatment of brain arteriovenous malformation. METHODS: Sixty-three patients with arteriovenous brain malformations underwent Gamma knife radiosurgery included in this prospective study between April 2017 and September 2018 with clinical and radiological with MRI follow up was done at three months and six months post-Gamma knife radiosurgery. By the end of the 12th-month post-Gamma knife radiosurgery, the patients were re-evaluated using digital subtraction angiography co-registered with M.R.I. During the 12 months follow up, CT scan or MRI was done at any time if any one of the patients᾽ condition deteriorated or developed signs and symptoms of complications. The mean volume of the arteriovenous malformations treated was 26.0 ± 5 cm3 (range 12.5–39.5 cm3) in The Neurosciences Hospital, Baghdad/Iraq. RESULTS: By the end of the 12th month of follow up, the overall obliteration of the arteriovenous malformations was seen in six patients only (9.5%), while shrinkage was noticed in 57 patients (90.5%). Improvement or clinical stability was found in 24 out of 39 patients (61.5%) presented with epilepsy as a chief complaint before Gamma knife radiosurgery and 21 out of 24 patients (87.0%) complained of a headache before Gamma knife radiosurgery. Post-Gamma knife radiosurgery bleeding was found in only three patients (5.0%). CONCLUSION: Even with the short term follow up, Gamma knife radiosurgery has an excellent clinical outcome in most patients with arteriovenous brain malformations. The clinical symptoms like headache and seizure were either diminished or controlled with the same medical treatment dose before Gamma knife radiosurgery. Long term clinical and radiological follow up is recommended

TREATMENT OF DEPLETED URANIUMCONTAMINATION IN SOIL BY USING SODIUMBICARBONATE SOLUTION

The Depleted Uranium contamination in soil was treated with chemical leaching method by using sodium bicarbonate with respect to the effect of several variables (Time, Temperature, Bicarbonate Concentration, Carbonate/Bicarbonate Ratio, Oxidative Reagent Effect, pH, Soil/Solution Ratio and Rinsing Effect after treatment) in order to decontaminate or remove Depleted Uranium to acceptable regulatory levels. The objective is to reach a selectively extracted Depleted Uranium by using a soil washing/extraction without generating a secondary waste which would be difficult to manage and/or dispose off. Results of Depleted Uranium removal efficiency were ranged from (35.4-88.25) %