Strategic leadership, strategic performance and core competencies in Lebanon’s education

The study examines a relationship among strategic leadership, strategic performance and core competence among teachers from Lebanon educational sector. Using sample size of 106 observations, with convenient sampling method, result showed that core competence has a direct effect on strategic performance and strategic leadership. Conversely, strategic leadership has not shown its significant mediation role in effecting strategic performance through the core competence. Examination of the data is performed using mediation regression model. Other implications, limitations, and future works are further discussed

Moral Identity as Moderator in the Relationship between Machiavellian Leadership perception and Employees’ Opportunistic Behaviors

This paper aims to examine the nature of the relationship between Machiavellian leadership perception and employees’ opportunistic behaviors, with the moderating role of moral identity. The study was conducted over a two years period, in which, a simple random sample was used with 295 questionnaires distributed on the employees of different service industries in Bahrain. Descriptive analysis, Simple and multiple regressions were used to analyze the data and test the hypotheses. The main results of the study indicate that there is a significant positive effect for Machiavellian leadership perception on employees’ opportunistic behaviors. They also indicate significant negative effects for both Internalization Moral Identity and Symbolization Moral Identity on employees’ opportunistic behaviors. Furthermore, the results show a partially moderating role for Internalization Moral Identity on the relationship between Machiavellian leadership perception and employees’ opportunistic behaviors. They also confirm a fully moderating role for Symbolization Moral Identity on the relationship between Machiavellian leadership perception and employees’ opportunistic behaviors

Use of steel slag in concrete mixtures

The recent unprecedented growth in the building industry in the State of Qatar has created a pressing demand for construction materials. Needs for concrete, being the major construction material has grown with the rapidly growing construction sector. Aggregate generally occupy about 70-80% of the volume of concrete used in buildings. The needs for alternative sources of aggregates are pressing. Steel slag, which is a by-product of steel manufacturing, could be an alternative solution. This paper presents the results from experimental works completed at Qatar University to check the applicability of using steel slag aggregates in concrete mixes in Qatar. Five trial concrete mixes were prepared.  One concrete mix composing of 100% gabbro coarse aggregates was designated as the control mix. Four other concrete mixes were prepared and they contained 100%, 75%, 50%, and 25% partial replacement of gabbro aggregates with slag aggregates, by weight. The concrete mix was proportioned to have a 28-day compressive strength of 35 MPa. The water-to-cement ratio was kept constant at 0.58 for all of the five mixes. All mixtures were cured for 7, 28, and 90 days.  No admixtures or additives were used in these mixes. The data indicate that steel slag has a promising potential to be used as a partial replacement for conventional aggregates in concrete. The emphasis of the work in the initial phase of this study was on the feasibility of utilizing steel slag aggregates in concrete, as a total or partial replacement of gabbro aggregate, used in construction in the State of Qatar by studying the properties of fresh and hardened concrete. Tests were conducted on concrete samples made of different aggregates to determine their acceptability for use in concrete. The different mixes were tested to determine compressive strength, splitting tensile strength, flexural strength, air content, and bulk density. Laboratory results, obtained in the six months research project, indicated that steel slag alone or in combination with other virgin raw materials such as gabbro, sand, and others could find uses in road construction applications in the State of Qatar

Acute effects of cigarette smoking in habitual smokers, a focus on endothelial function

AbstractBackgroundThe chronic effect of cigarette (cig.) smoking is well established. The acute effect of smoking abolishes the concept, argued by heavy smokers, to decrease the number of smoked cigarettes instead of quitting.AimTo detect the acute effects of cigarette smoking and the duration of these effects.Patients and methodsThirty four smokers (age 21–35years) were studied at 3 occasions; 9h after the last cig. smoking, 5min after one cig. smoking and 30min after 3 cig. smoking within 30min. They were subjected to measurement of both ventricular functions using standard and tissue Doppler imaging (TDI), aortic distensibility, stiffness and endothelial function assessment by endothelium-dependent flow-mediated dilatation (FMD) and maximum vasodilatation.ResultsAfter one cigarette smoking, we found a statistically significant effect on blood pressure, Heart Rate, FMD percent, Dilation Ratio, aortic distensibility (P=0.007), and aortic stiffness index (ASI) (P=0.01). Furthermore the LV diastolic function was significantly impaired after smoking. Despite disappearance of acute effect of 3 cig. smoking within 30min on blood pressure, Heart Rate and aortic distensibility, a significant difference was still found as regards FMD percent and dilation ratio denoting the extension of the endothelial dysfunction for more than 30min after the last cigarette.ConclusionMany acute changes occur following one cigarette smoking even in habitual smokers. Persistence of endothelial dysfunction parameters after smoking indicates the failure of circulation adaptation in response to such offense that might contribute to the precipitation of acute events in vulnerable patients

Use of local discarded materials in concrete

Steel slag, a by-product of steel manufacturing, is generated in large quantities in Qatar. In fact, it is estimated that more than 400,000tons of steel slag are generated annually in the country. Gravel, resulting from washing sand, is also produced at more than 500,000tons/year in Qatar. Both materials are not efficiently used in the country and most of its aggregate (gabbro) needs are imported from neighboring countries. This paper presents the results obtained on the use of steel slag, gravel and gabbro in concrete. A total of nine concrete mixtures were prepared. One concrete mixture that contained 100% gabbro aggregate was considered as the control mix. Four concrete blends containing 100%, 75%, 50%, and 25% steel slag (by weight) were prepared as partial replacements of gabbro aggregates. Another four concrete mixtures containing 100%, 75%, 50%, and 25% gravel (by weight) were cast as partial replacements of gabbro aggregates. All samples were cured in a water tank for 7, 28 and 90days and then subjected to compressive, flexural and splitting tensile strength tests. All concrete mixtures prepared easily met the 28-day compressive strength design requirement of 28MPa. Best results were obtained for concrete prepared using 100% steel slag aggregates. Concrete cast using 100% gravel yielded lower strength results than the control mixture (100% gabbro). However, there was an increase in strength values with an increase in gabbro content in gravel/gabbro mixtures. Additional work is necessary to establish long-term performance, especially concerning what is reported in the literature about the expansive characteristics of steel slag aggregates when used in concrete. It should be noted that concrete cured for 90days in the water tank did not exhibit any reversal in strength.Slag Aggregate Producer, under Qatar University (QU) Research Grant No. QUEX-CENG-SAP-12/13-1. The Gulf Organisation for Research and Developmen

The development of machine learning in bariatric surgery

BackgroundMachine learning (ML), is an approach to data analysis that makes the process of analytical model building automatic. The significance of ML stems from its potential to evaluate big data and achieve quicker and more accurate outcomes. ML has recently witnessed increased adoption in the medical domain. Bariatric surgery, otherwise referred to as weight loss surgery, reflects the series of procedures performed on people demonstrating obesity. This systematic scoping review aims to explore the development of ML in bariatric surgery.MethodsThe study used the Preferred Reporting Items for Systematic and Meta-analyses for Scoping Review (PRISMA-ScR). A comprehensive literature search was performed of several databases including PubMed, Cochrane, and IEEE, and search engines namely Google Scholar. Eligible studies included journals published from 2016 to the current date. The PRESS checklist was used to evaluate the consistency demonstrated during the process.ResultsA total of seventeen articles qualified for inclusion in the study. Out of the included studies, sixteen concentrated on the role of ML algorithms in prediction, while one addressed ML's diagnostic capacity. Most articles (n = 15) were journal publications, whereas the rest (n = 2) were papers from conference proceedings. Most included reports were from the United States (n = 6). Most studies addressed neural networks, with convolutional neural networks as the most prevalent. Also, the data type used in most articles (n = 13) was derived from hospital databases, with very few articles (n = 4) collecting original data via observation.ConclusionsThis study indicates that ML has numerous benefits in bariatric surgery, however its current application is limited. The evidence suggests that bariatric surgeons can benefit from ML algorithms since they will facilitate the prediction and evaluation of patient outcomes. Also, ML approaches to enhance work processes by making data categorization and analysis easier. However, further large multicenter studies are required to validate results internally and externally as well as explore and address limitations of ML application in bariatric surgery

Carbon nanotube effect on the ductility, flexural strength, and permeability of concrete

Recently, remarkable types of carbon nanofilaments called carbon nanotubes (CNTs) have raised the interest of many concrete and cementitious composite researchers due to their significant mechanical, electrical, thermal, kinetic, and chemical properties. These nanofilaments are considered promising applicants to use in producing high-performance cement-based composite materials. In this research, the effect of CNT use on the flexural strength, strain capacity, permeability, and microstructure of concrete was investigated. Concrete batches of 0, 0.03, 0.08, 0.15, and 0.25 wt.% CNTs were prepared using a mixing method that consisted of a 30-minute solution sonication and a 60-minute batch mixing. On the 28th day, the mechanical properties were determined. The results indicated that concrete prepared using high CNT contents of 0.15 and 0.25 wt.% increased the flexural strength by more than 100% in comparison with 0% CNT concrete. Furthermore, the results showed that CNTs would increase the ductility of concrete beams by about 150%. The permeability test results showed the benefits of CNT inclusion in reducing the permeability of concrete. The permeability coefficient (kT) decreased by at least 45% when CNTs were added to concrete. A qualitative microstructural analysis illustrated the uniform dispersion of CNT filaments within the concrete hydration products in all batches.Scopu

Intelligent interaction tests suite generator for iot testing

Typical Internet of Things (IOT) applications consist of large heterogeneous components. In order to ensure free-of-bug integration, there is need for testing all possible combinations (i.e., causing combinatorial explosion problem). Testing all possibilities is practically impossible owing to resource and time constraints. In order to address these issues, t-way testing approach has been adopted to minimize the tests systematically

ABC Algorithm for Combinatorial Testing Problem

Computer software is in high demand everywhere in the world. The high dependence on software makes software requirements more complicated. As a result, software testing tasks get costlier and challenging due to a large number of test cases, coupled with the vast number of the system requirements. This challenge presents the need for reduction of the system redundant test cases. A combinatorial testing approach gives an intended result from the optimization of the system test cases. Hence, this study implements a combinatorial testing strategy called Artificial Bee Colony Test Generation (ABC-TG) that helps to get rid of some of the current combinatorial testing strategies. Results obtained from the ABC-TG were benchmarked with the results obtained from existing strategies in order to determine the efficiency of the ABC-TG. Finally, ABC-TG shows the efficiency and effectiveness in terms of generating optimum test cases size of some of the case studies and a comparable result with the existing combinatorial testing strategies