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Abstract Refactoring is a well-established topic in contemporary software engineering, focusing on enhancing software's structural design without altering its external behavior. Commit messages play a vital role in tracking changes to the codebase. However, determining the exact refactoring required in the code can be challenging due to various refactoring types. Prior studies have attempted to classify refactoring documentation by type, achieving acceptable results in accuracy, precision, recall, F1-Score, and other performance metrics. Nevertheless, there is room for improvement. To address this, we propose a novel approach using four ensemble Machine Learning algorithms to detect refactoring types. Our experimentation utilized a dataset containing 573 commits, with text cleaning and preprocessing applied to address data imbalances. Various techniques, including hyperparameter optimization, feature engineering with TF-IDF and bag-of-words, and binary transformation using one-vs-one and one-vs-rest classifiers, were employed to enhance accuracy. Results indicate that the experiment involving feature engineering using the TF-IDF technique outperformed other methods. Notably, the XGBoost algorithm with the same technique achieved superior performance across all metrics, attaining 100% accuracy. Moreover, our results surpass the current state-of-the-art performance using the same dataset. Our proposed approach bears significant implications for software engineering, particularly in enhancing the internal quality of software.

ObjectiveThis study investigated upper limb kinematics and muscle co-activation in wheelchair tennis players during the forehand stroke. By analyzing linear and angular kinematic variables alongside muscle co-activation patterns, the study aimed to provide insights into the biomechanical mechanisms supporting forehand stroke performance.MethodFifteen professional male wheelchair tennis players (height: 163.9 ± 2.05 cm; mass: 64.1 ± 3.07 kg; age: 32.2 ± 7.97 years) participated in this study. Electromyographic data from six muscles around the dominant arm joints were recorded using the Myon system. Four fixed GoPro Hero 8 cameras (120 Hz) captured 3D video, and kinematic analyses were performed using the APAS system. The forehand stroke was analyzed across three phases: (1) backswing, (2) forwardswing, and (3) follow-through.ResultsThe results showed significant phase-specific changes in muscle co-activation for the shoulder (p < 0.001), elbow (p < 0.005), and wrist (p < 0.01). Muscle co-activation was highest during the backswing phase, decreased during the forwardswing, and increased again during the follow-through phase. This pattern reflects the need for joint stability and control, particularly when changing stroke direction and slowing the arm after impact.ConclusionThese findings provide novel insights into the kinematic and neuromuscular mechanisms underlying the forehand stroke in wheelchair tennis. The data provide hypotheses about potential training and rehabilitation strategies that should be tested by prospective studies. The results also highlight the unique demands of wheelchair tennis, contributing to inclusive, evidence-based approaches to enhancing performance and safety in disability sports.

IntroductionGreater side-to-side asymmetry can indicate impaired skill, reduced power production, and an increased risk of injury. Bilateral differences highlight the presence of asymmetries that should be assessed to understand their impact on both injury risk and performance enhancement.ObjectiveThis study aimed to assessment muscle activation and bilateral asymmetry in major trunk and shoulder muscles during a two-armed kettlebell swing exercise.MethodsTwenty-seven participants (age: 24.2 ± 2.6 years; body mass: 82.9 ± 7.7 kg; height: 176.9 ± 7.0 cm) were included in the study. Electromyographic (EMG) data were collected bilaterally from twelve muscles (six muscles per side: anterior deltoid [AD], posterior deltoid [PD], erector spinae longissimus [ESL], erector spinae iliocostalis [ESI], external oblique [EO], and rectus abdominis [RA]).ResultsResults indicated that asymmetry indices for the AD, ESL, ESI, and RA muscles during the upward propulsion phase fell within the determined threshold of 15%. However, the asymmetry indices for the PD and EO muscles exceeded this threshold by 3.36% and 2.62%, respectively. The findings suggest that trunk muscle asymmetries during the kettlebell swing are generally less pronounced than those of the shoulder muscles, particularly during the float phase.ConclusionThese results provide valuable insights into bilateral muscle asymmetry during a two-armed kettlebell swing, which can inform the development of targeted training programs. The methods and findings of this study may further contribute to understanding the effects of muscle balance, symmetry, and injury mechanisms in dynamic movements.

Distributed agile software development (DASD) has become a prominent software development approach. Proper task allocation is crucial in DASD to avoid undesirable outcomes including project rejection by clients, unfavorable team attitudes, and project failure. Coordination and communication issues occur as businesses embrace the DASD environment more frequently to tap into global talent and knowledge while cutting development expenses. To overcome these challenges, efficient task allocation planning becomes a crucial success component in software project management. The purpose of this study is to utilize machine learning (ML) predictive algorithms to determine the most appropriate role for a given task, with the aim of assisting software managers in making task assignments more efficiently and effectively in DASD environment. Preprocessing steps applied to the dataset include data cleaning, normalization, and partitioning into training, validation, and test sets. Four model classifiers were used in the experiment: Random Forest, Decision Tree, K-Nearest Neighbors (K-NN), and AdaBoost. The results showed that Random Forest outperformed the other classifiers in task allocation prediction, achieving an accuracy of 96.7 %, followed by K-NN (94.2 %), Decision Tree (93.5 %), and AdaBoost (93 %). The study demonstrates that ML models are effective in tackling task allocation issues in DASD settings, and the outcomes are promising.

Software Bug Prediction (SBP) is an integral process to the software’s success that involves predicting software bugs before their occurrence. Detecting software bugs early in the development process enhances software quality, performance, and reduces software costs. The integration of Machine Learning (ML) algorithms has significantly improved software bug prediction accuracy and concurrently reduced costs and resource utilization. Numerous studies have explored the impact of Hyperparameter Optimization on single classifiers, enhancing these models’ overall performance in SBP analysis. Ensemble Learning (EL) approaches have also demonstrated increased model accuracy and performance on SBP datasets. This study proposes a novel learning model for predicting software bugs through the utilization of EL and tuning hyperparameters. The results are compared with single hypothesis learning models using the WEKA software. The dataset, collected by the National Aeronautics and Space Administration (NASA) U.S.A., comprises 10,885 instances with 20 attributes, including a classifier for defects in one of their coding projects. The findings indicate that EL models outperform single hypothesis learning models, and the proposed model’s accuracy increases after optimization. Furthermore, the accuracy of the proposed model demonstrates improvement following the optimization process. These results underscore the efficacy of ensemble learning, coupled with hyperparameter optimization, as a viable approach for enhancing the predictive capabilities of software bug prediction models.

Proximal sensing has become increasingly popular due to developments in soil observation technologies and the demands of timely information gathering through contemporary methods. By utilizing the morphological, physical, and chemical characteristics of representative pedogenetic profiles established in various soils of the Sohag governorate, Egypt, the current research addresses the characterization of surface reflectance spectra and links them with the corresponding soil classification. Three primary areas were identified: recently cultivated, old cultivated, and bare soils. For morphological analysis, a total of 25 soil profiles were chosen and made visible. In the dark room, an ASD Fieldspec portable spectroradiometer (350–2500 nm) was used to measure the spectrum. Based on how similar their surface spectra were, related soils were categorized. Ward’s method served as the basis for the grouping. Despite the fact that the VIS–NIR spectra of the surface soils from various land uses have a similar reflectance shape, it is still possible to compare the soil reflectance curves and the effects of the surface soils. As a result, three groups of soil curves representing various land uses were observed. Cluster analysis was performed on the reflectance data in four ranges (350–750, 751–1150, 1151–1850, and 1851–2500 nm). The groups derived from the soil surface ranges of 350–750 nm and 751–1150 nm were not the same as those derived from the ranges of 1151–1850 nm and 1851–2500 nm. The last two categories are strikingly comparable to various land uses with marginally similar features. Based on the ranges of 1151–1850 nm and 1851–2500 nm in surface spectral data, the dendrogram effectively separated and combined the profiles into two separate clusters. These clusters matched different land uses exactly. The results can be used to promote the widespread usage of in situ hyperspectral data sets for the investigation of various soil characteristics.

Abstract Refactoring tools have advanced greatly and are being used in many large projects. As a result, a great deal of information is now available about past refactoring and its effects on the source code. However, when multiple refactoring is performed at once, it becomes more difficult to analyze their impact. Refactoring visualization can help developers create more maintainable code that is easier to understand and modify over time. Although there is an increasing interest in visualizing code changes in software engineering research, there has been relatively little research on visualizing the process of refactoring. In this paper, we propose a Radar Chart Refactoring Visualization (RcRV) approach to visualize software refactoring of source code across multiple software releases. Radar charts are a form of 2D visualization that can show multiple variables on a single chart. The RcRv receives input from developers or through refactoring identification tools, such as Ref-Finder, to generate charts. The generated charts can show the changes made during the refactoring process, highlighting areas of the trend of refactoring over evolution for multiple refactoring, multiple methods, and multiple classes. The evaluation study conducted to assess the usefulness of the RcRV tool has shown that the proposed tool is useful to developers, appealing, and easy to use. The proposed method of visualization can be beneficial for developers and maintainers to detect design violations and potential bugs in the code, thus saving time and effort during the development and maintenance process. Therefore, this research presents a significant contribution to the software engineering field by providing developers with an efficient tool to enhance code quality and maintainability.

Abstract Background The overuse of antibiotics leads to the emergence of antibiotic-resistant microbes which causes high mortality worldwide. Therefore, the synthesis of new active compounds has multifunctional activities are the main challenge. Nanotechnology provides a solution for this issue. Method The endophytic fungal strain Aspergillus terreus BR.1 was isolated from the healthy root of Allium sativum and identified using internal transcribed spacer (ITS) sequence analysis. The copper oxide nanoparticles (CuO-NPs) were synthesized by harnessing the metabolites of the endophytic fungal strain. The UV-Visble spectroscopy, Fourier-transform infrared spectroscopy (FT-IR), Transmission electron micrscopy (TEM), Energy dispersive X-ray (EDX), X-ray diffraction (XRD), Dynamic light scattering (DLS), and zeta potential (ζ) were used for the characterization of synthesized CuO-NPs. The activity against different pathogenic bacteria and Candida species were investigated by agar well-diffusion method. The biocombatibility and anticancer activity were assessed by MTT assay method. The scavenging of DPPH was used to investigate the antioxidant activity of synthesized CuO-NPs. Results Data showed the successful formation of crystalline nature and spherical shape CuO-NPs with sizes in the ranges of 15–55 nm. The EDX reveals that the as-formed sample contains ions of C, O, Cl, and Cu with weight percentages of 18.7, 23.82, 11.31, and 46.17%, respectively. The DLS and ζ-potential showed high homogeneity and high stability of synthesized CuO-NPs with a polydispersity index (PDI) of 0.362 and ζ-value of − 26.6 mV. The synthesized CuO-NPs exhibited promising antibacterial and anti-Candida activity (concentration-dependent) with minimum inhibitory concentration (MIC) values in the ranges of 25–50 µg mL–1. Moreover, the fungal mediated-CuO-NPs targeted cancer cells of MCF7 and PC3 at low IC50 concentrations of 159.2 ± 4.5 and 116.2 ± 3.6 µg mL–1, respectively as compared to normal cells (Vero and Wi38 with IC50 value of 220.6 ± 3.7 and 229.5 ± 2.1 µg mL–1, respectively). The biosynthesized CuO-NPs showed antioxidant activity as detected by the DPPH method with scavenging percentages of 80.5 ± 1.2% at a concentration of 1000 µg mL–1 and decreased to 20.4 ± 4.2% at 1.9 µg mL–1 as compared to ascorbic acid (control) with scavenging activity of 97.3 ± 0.2 and 37.5 ± 1.3% at the same concentrations, respectively. Conclusion The fungal mediated-CuO-NPs exhibited promising activity and can be integrated into various biomedical and theraputic applications.

Abstract The growth of cloud computing is hindered by concerns about privacy and security. Despite the widespread use of network intrusion detection systems (NIDS), the issue of false positives remains prevalent. Furthermore, few studies have approached the intrusion detection problem as a time series issue, requiring time series modeling. In this study, we propose a novel technique for the early detection of intrusions in cloud computing using time series data. Our approach involves a method for Feature Selection (FS) and a prediction model based on the Facebook Prophet model to assess its efficiency. The FS method we propose is a collaborative feature selection model that integrates time series analysis techniques with anomaly detection, stationary, and causality tests. This approach specifically addresses the challenge of misleading connections between time series anomalies and attacks. Our results demonstrate a significant reduction in predictors employed in our prediction model, from 70 to 10 predictors, while improving performance metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), Median Absolute Percentage Error (MdAPE), and Dynamic Time Warping (DTW). Furthermore, our approach has resulted in reduced training, prediction, and cross-validation times of approximately 85%, 15%, and 97%, respectively. Although memory consumption remains similar, the utilization time has been significantly reduced, resulting in substantial resource usage reduction. Overall, our study presents a comprehensive methodology for effective early detection of intrusions in cloud computing based on time series anomalies, employing a collaborative feature selection model and the Facebook Prophet prediction model. Our findings highlight the efficiency and performance improvements achieved through our approach, contributing to the advancement of intrusion detection techniques in the context of cloud computing security.

Abstract Herein, four endophytic fungal strains living in healthy roots of garlic were used to produce selenium nanoparticles (Se-NPs) via green synthesis. Penicillium verhagenii was found to be the most efficient Se-NPs producer with a ruby red color that showed maximum surface plasmon resonance at 270 nm. The as-formed Se-NPs were crystalline, spherical, and well-arranged without aggregation, and ranged from 25 to 75 nm in size with a zeta potential value of −32 mV, indicating high stability. Concentration-dependent biomedical activities of the P. verhagenii-based Se-NPs were observed, including promising antimicrobial activity against different pathogens (Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis, Staphylococcus aureus, Candida albicans, C. glabrata, C. tropicalis, and C. parapsilosis) with minimum inhibitory concentration (MIC) of 12.5–100 µg mL–1. The biosynthesized Se-NPs showed high antioxidant activity with DPPH-scavenging percentages of 86.8 ± 0.6% at a concentration of 1000 µg mL–1 and decreased to 19.3 ± 4.5% at 1.95 µg mL–1. Interestingly, the Se-NPs also showed anticancer activity against PC3 and MCF7 cell lines with IC50 of 225.7 ± 3.6 and 283.8 ± 7.5 µg mL–1, respectively while it is remaining biocompatible with normal WI38 and Vero cell lines. Additionally, the green synthesized Se-NPs were effective against instar larvae of a medical insect, Aedes albopictus with maximum mortality of 85.1 ± 3.1, 67.2 ± 1.2, 62.10 ± 1.4, and 51.0 ± 1.0% at a concentration of 50 µg mL–1 for I, II, III, and IV-instar larva, respectively. These data highlight the efficacy of endophytic fungal strains for cost-effective and eco-friendly Se-NPs synthesis with different applications.

Researchers are depending more than ever on remote sensing techniques to monitor and assess the agricultural water status, as well as to estimate crop water usage or crop actual evapotranspiration. In the current work, normal and stressed baselines for irrigated wheat genotypes were developed in an arid part of the Sohag governorate, Egypt, using infrared thermometry in conjunction with weather parameters. The experiment was carried out in a randomized complete block design in the normal and drought stress conditions based on three replicates using ten bread wheat genotypes (G1–G10), including five accessions, under drought stress. A standard Class-A-Pan in the experimental field provided the daily evaporation measurements (mm/day), which was multiplied by a pan factor of 0.8 and 0.4 for normal and stressed conditions, respectively. The relationship between the vapor pressure deficit (VPD) and canopy-air temperature differences (Tc − Ta) was plotted under upper (fully stressed) and lower baseline (normal) equations. Accordingly, the crop water stress indexes (CWSIs) for the stressed and normal baselines for wheat genotypes were developed. Additionally, the intercept (b) and the slope (a) of the lower baseline equation were computed for different genotypes. The results indicate that, before applying irrigation water, the CWSI values were high in both growing seasons and under all irrigation regimes. After that, the CWSI values declined. G10 underwent stress treatment, which produced the greatest CWSI (0.975). Conversely, the G6 condition that received well-watered irrigation yielded the lowest result (−0.007). When compared to a well-watered one, the CWSI values indicated a trend toward rising stress. There existed an inverse link between the CWSI and grain yield (GY); that is, a lower CWSI resulted in better plant water conditions and a higher GY. Under standard conditions, the wheat’s highest GY was recorded in G2, 8.36 Ton/ha and a WCSI of 0.481. In contrast, the CWSI result for the stress treatment was 0.883, indicating a minimum GY of 5.25 Ton/ha. The Water Use Efficiency (WUE) results demonstrated that the stress irrigation regime produced a greater WUE value than the usual one. This study makes a significant contribution by investigating the techniques that would allow CWSI to be used to estimate irrigation requirements, in addition to determining the irrigation time.

Gradable Epistemic Modals (GEMs) such as certain or likely have been analyzed to have the semantics of gradable adjectives, which constrain their epistemic modality. This squib analyzes the modal use of the sentential particle qad in Standard Arabic which has the following puzzling behavior: particle qad gives rise to the certainty/likelihood modality meaning only when it is composed with the tense expression of its propositional complement. Modal qad then manifests itself as an extreme, non-gradable modal with no lexically encoded but grammatically derived scale meaning. A probabilistic semantics is proposed to derive the truth conditions of the epistemic modal meaning of qad based on a monotonic, probabilistic time-world branching model. The analysis assigns maximum degree of likelihood to qad in the past tense which triggers certainty. It also assigns a minimum degree of likelihoods to qad in the present tense which triggers possibility.

One of the most important structural elements, the column is primarily intended to support compressive loads. The strengthening is carried out for existing reinforced concrete columns to increase the ductility of the column and to increase load capacity to sustain the applied load as sometimes there may be a use change, which leads to increased loads. This work aims to study the behavior and efficiency of RC columns strengthened with steel jackets and subjected to axial load. An experimental program was performed on columns specimen till failure. Aspect ratio (t is the long side of the cross-section /b is the short side of the cross-section), the volume of steel straps, and the spacing of steel straps at centers(S) were the primary research variables in this work. Ten specimens were rectangular concrete columns with aspect ratios equal to 1, 1.56, and 2.04. the cross sections of the column were (200*200mm), (160*250 mm) and (140*286 mm) respectively. the total height of the specimens was 1200 mm,960mm, and 840mm respectively. Under an axial load, three control columns and seven strengthened columns were tested. The results showed that using this method of strengthening is very effective and an increase in the axial load capacity of the strengthened columns is obtained. This increase was due to the confining effect of the steel jacket, and the ability of the steel angle to withstand a large part of the applied axial load.

Steel corrosion is thought to be one of the primary causes of the inadequate durability of concrete buildings in the maritime environment. Because of this, adopting Fiber-Reinforced Polymer (FRP) bars in harsh settings has attracted a lot of attention for its appealing mechanical properties as well as to prevent corrosion issues. But because there hasn't been much research in this area, we don't fully understand how fiber-reinforced polymer (FRP) bars behave when they are compressed. This work's goal is to assess the expected axial compressive strength of columns when hybrid reinforcement is used in place of steel reinforcement. Hybrid bars are steel bars surrounded by a cover shell of Glass or Carbon FRP (hybrid-steel) for longitudinal reinforcement and/or transverse reinforcement. 17 column specimens were included in an experimental study program that was created.The specimens were tested to failure with an axial loading condition. The parameters studied were the type of fibers, the percentage of steel in the hybrid reinforcement for longitudinal main reinforcement ρL(0.96, 0.44, and 0.25), the ratio of the web reinforcement (internal ties), the proportion of fiber in the hybrid bars, as well as the columns' cross sections' rectangularity. Based on the data, mathematical models were devised and assessed to forecast the load bearing capability of the column. The findings indicate that hybrid reinforced concrete columns have acceptable levels of dependability index in general.

High feed prices and limited access to feed are two critical problems faced by fish producers. One approach that farmers may consider is using less expensive and locally available components. We conducted a 60-day feeding trial to investigate the consequences of the dietary addition of Hemicell® (HC) as exogenous β-mannanase and lavender flower meal (LFM) in low- protein diet (25 % CP) in Oreochromis niloticus. The investigation assessed growth, feed utilization, somatic, body composition and hemato-biochemical indices, and digestive enzyme activity. Fish (N = 180; average weight: 17.17 ± 0.72 g) were haphazardly organized into six groups in triplicates (10 fish/replicate) and stocked in 18 plastic tanks (60 L). For 60-days, fish groups were fed on six prepared experimental diets. The negative control group (NCG) and positive control group (PCG) were fed basal diets containing 30 % CP and 25 % CP, respectively. Groups (G1-G4) were fed on basal diets containing 25 % CP and supplemented with 0.25 g/kg HC, 0.5 g/kg HC, 0.25 g/kg HC+ 10 g/kg LFM, and 0.5 g/kg HC+ 10 g/kg LFM, respectively. The findings showed decreases in the growth, body composition (crude protein and lipids), and white blood cells count (WBCs) in PCG as compared with the control group (NCG); meanwhile, no significant alteration was recorded for other parameters. Dietary addition of HC alone or with LFM enhanced growth, feed utilization, digestive enzymes activity (trypsin, amylase, and lipase), serum total protein, and hematological indices (red blood cells count, WBCs, and Hb) as compared with PCG. The highest results were notable in G2. No marked impacts were observed on water quality parameters, fish survival, somatic index (hepato-somatic and visceral-somatic), and the level of cholesterol, glucose, and creatinine in fish serum by dietary HC or LFM. However, values of triglycerides, urea, hepatic enzymes (alanine and aminotransferases), and body crude lipids increased by supplementation of HC alone or with LFM. Our findings demonstrated that feeding O. niloticus a low-protein diet supplemented with HC (0.5 g/kg) could promote growth, digestive capability, and health status. This provides a platform for potential exogenous enzyme (HC) use in low-protein diets to reduce feed costs and support the aquaculture industry.

One of the construction industry’s main interest is using innovative materials to facilitate construction, extend service life, and minimize maintenance and rehabilitation costs. Recycling waste tire rubbers into conventional concrete materials constitutes one of the biggest challenging issues in modern concrete technology, which can significantly relieve critical environmental issues. However, the compressive strength reduction caused by the added rubber aggregates, albeit with significant ductility enhancement, has limited its application in concrete structures. The present study aimed at attaining the optimum ratio of crumb rubber ratio with minimal reduction in compressive strength to be used in large scale elements in which the ductility constitutes a critical design parameter. Different rubberized concrete mixes with different percentages of crumb rubber (CR) and different treatment were investigated. The main parameters were the type of crumb rubber (course or fine), the percentage of replacement (5%, 10%, 20%, and 30%), the treatment conditions (treated with NAOH, or without treatment), and using silica fume as partial replacement of cement. The test data were analyzed considering the workability, the compressive, tensile, and flexural strengths. The results revealed that the most appropriate concrete mix is using a 20% treated fine crumb rubber, with silica fume incorporation.

Background: Soft tissue defects reconstruction of the heel region represents a challenge for a plastic surgeon due to the limited availability of local soft tissue and the special structural and functional characteristics of this region.The aim of the work: The current study aimed to evaluate the versatility of different loco-regional flaps for heel reconstruction.Patients and Methods: This study included 20 patients with soft-tissue defects localized to the heel. Patients were divided into four groups according to type of flap used: medial plantar, reversed sural, V–Y advancement and lateral calcaneal flap. The main outcomes were donor site morbidity, flap sensation, stability and daily activities.Results: The age of studied patients ranged between 21 and 56 years, 14 patients were males and 6 were females, 13 patients were right sided and 7 were left sided. Thirteen defects were traumatic, 6 neuropathic and 1 post-burn unstable scar. In reversed sural group, excellent results in 2 patients [20%], good in 6 patients [60%] and fair in 2 patients [20%]. In medial plantar flap group, excellent results in 3 patients [60 %] and good in 2 patients [40%]. In V–Y advancement flap group, all 3 patients [100%] with excellent results. In lateral calcaneal flap group, one patient was excellent [50%] and good in another patient [50%].Conclusion: Loco-regional flaps were very useful to reconstruct soft-tissue defects in the heel defect. The flaps from plantar aspect [medial plantar and V-Y flap] were the best option for small and medium sized defects due to its minimal donor site morbidity, similar tissue to heel and protective sensation. Reversed sural and lateral calcaneal flap were another good option if the plantar flaps unavailable.

Objectives: Egypt incurred about 74 billion of Egyptian pounds in the last decade due to arbitration cases. This paper aims to find a solution for the Egyptian construction industry to avoid disputes among project parties, which convert the project from win-win situation to lose-lose situation and the project may not be completed.Methods/Analysis: This study uses the new approach of contracts administration of avoiding disputes from its inception represented in FIDIC 2017 and the approach of disputes settlement represented in FIDIC 1999 instead of the used ad-hoc construction contracts in Egypt.After analyzing the Egyptian construction field, it is found that each of badly written contract and poor contract administration are the main reasons for most of disputes among project parties.as a try to solve this issue, a case study been applied to use the standard contract of FIDIC 2017 to be the project’s contract instead of used regular ad-hoc contracts in Egyptian construction field, results confirmed that the new approach of disputes avoidance is in the line of the nature of Egyptian construction projects, in addition to FIDIC 2017 mentions more detailed conditions and scenarios which avoid almost all project disputes and deliver the project to the completion date with win–win situation for all project parties.Novelty/Improvement: the application of standard contract of FIDIC 2017 as the project contract in Egypt shall be a solution for the badly written contract and facilitate the contract administration for all project stages which shall be a great step to improve the Egyptian construction field and save billions of Egyptian pounds in arbitration courts.

Foot-and-mouth disease (FMD), a highly contagious viral disease caused by FMD virus (FMDV) that threatens Egypt's livestock industry. FMDV causes severe economic losses in the livestock, with restriction of international trade from endemic regions. Surveillance for FMDV serotypes circulating in Egypt is urgently needed to assess the epidemiological situation in the country. FMD outbreaks reported in Egypt in between December 2016 and January-March 2017. A cross-sectional study was conducted to identify the FMDV serotypes responsible for the outbreaks and to collect information on the virus's morphopathological effects. Postmortem tissue and clinical samples (oral swabs, vesicular fluids from ruptured vesicles, and blood) were collected from recently deceased and infected animals. Pathological examination revealed classical FMD lesions as vesicular and erosive lesions on epithelial tissues with non-suppurative lymphoplasmacytic myocarditis. Phylogenetic and sequencing analyses demonstrated that FMDV serotype O, EA-3 topotype, VP1 is the prevalent serotype responsible for the pathological alterations and the high mortality in young calves, adult cattle, and water buffalo. The outcomes indicate continuous mutations in the circulating FMDV, which result in the occasional failure of vaccination. Based on these findings, extensive continuous monitoring and serotyping of the existing circulating FMDV isolates and regular vaccination with reevaluation of the currently used vaccine in Egypt are recommended to prevent the recurrence of such outbreaks.

Background: Refractive outcome has become more relevant in myopic patients. Refractive surprises are mainly caused by errors in axial length (AL) measurement. Aim: This study aimed to evaluate the accuracy of intraocular lens (IOL) power calculation in myopic eyes using the AL measured by optical biometry versus an optimised AL calculated by the Wang-Koch method. Setting: Ophthalmology Department, Cairo University and Ophthalmic Diagnostic and Laser Unit, Cairo University Hospitals, both in Cairo, Egypt. Methods: A prospective study of 30 eyes of 23 patients with ALs greater than 25.0 mm that underwent phacoemulsification with IOL implantation in the capsular bag. The LENSTAR was used for preoperative IOL power calculation using the Holladay 1 formula and the LENSTAR AL (group 1), and for back-calculation of the prediction error (PE) for the same 30 eyes using the Holladay 1 formula and the optimised AL (group 2). Postoperative PEs and mean absolute errors (MAEs) were calculated six weeks after surgery. Results: The postoperative spherical equivalent was within ± 1.00 dioptre (D) of predicted in 86.7% and 90.0% of eyes, respectively, (p = 0.69). However, 66.7% of eyes had a hyperopic outcome in group 1, in comparison to 20.0% that would be left hyperopic using the optimised AL in group 2 (p 0.05). Conclusion: The Wang-Koch method of optimising the AL would have significantly reduced the percentage of eyes rendered hyperopic using the LENSTAR AL from 66.7% to 20.0%. This difference represents a clinically significant improvement in IOL power prediction in these eyes.

Understanding the change dynamics of land use and land cover (LULC) is critical for efficient ecological management modification and sustainable land-use planning. This work aimed to identify, simulate, and predict historical and future LULC changes in the Sohag Governorate, Egypt, as an arid region. In the present study, the detection of historical LULC change dynamics for time series 1984–2002, 2002–2013, and 2013–2022 was performed, as well as CA-Markov hybrid model was employed to project the future LULC trends for 2030, 2040, and 2050. Four Landsat images acquired by different sensors were used as spatial–temporal data sources for the study region, including TM for 1984, ETM+ for 2002, and OLI for 2013 and 2022. Furthermore, a supervised classification technique was implemented in the image classification process. All remote sensing data was processed and modeled using IDRISI 7.02 software. Four main LULC categories were recognized in the study region: urban areas, cultivated lands, desert lands, and water bodies. The precision of LULC categorization analysis was high, with Kappa coefficients above 0.7 and overall accuracy above 87.5% for all classifications. The results obtained from estimating LULC change in the period from 1984 to 2022 indicated that built-up areas expanded to cover 12.5% of the study area in 2022 instead of 5.5% in 1984. This urban sprawl occurred at the cost of reducing old farmlands in old towns and villages and building new settlements on bare lands. Furthermore, cultivated lands increased from 45.5% of the total area in 1984 to 60.7% in 2022 due to ongoing soil reclamation projects in desert areas outside the Nile Valley. Moreover, between 1984 and 2022, desert lands lost around half of their area, while water bodies gained a very slight increase. According to the simulation and projection of the future LULC trends for 2030, 2040, and 2050, similar trends to historical LULC changes were detected. These trends are represented by decreasing desert lands and increasing urban and cultivated newly reclaimed areas. Concerning CA-Markov model validation, Kappa indices ranged across actual and simulated maps from 0.84 to 0.93, suggesting that this model was reasonably excellent at projecting future LULC trends. Therefore, using the CA-Markov hybrid model as a prediction and modeling approach for future LULC trends provides a good vision for monitoring and reducing the negative impacts of LULC changes, supporting land use policy-makers, and developing land management.

The aim of this study was to determine the muscle activations of the dominant arm during the forehand stroke of wheelchair tennis. Five players participated in the present study (age: 32.6 ± 9.9 years; body mass: 63.8 ± 3.12 kg; height: 164.4 ± 1.7 cm). The electrical muscle activity of six dominant arm muscles was recorded using an sEMG system. A significant effect of the muscle’s activity was observed, and it was shown that the muscle activation was significantly higher in the execution phase compared to the preparation phase in the anterior deltoid and biceps brachii (34.98 ± 10.23% and 29.13 ± 8.27%, p < 0.001); the posterior deltoid, triceps brachii, flexor carpi radialis, and extensor carpi radialis were higher in the follow-through phase than in the execution phase (16.43 ± 11.72%, 16.96 ± 12.19%, 36.23 ± 21.47% and 19.13 ± 12.55%, p < 0.01). In conclusion, it was determined that the muscle activations of the dominant arm muscles demonstrate variances throughout the phases of the forehand stroke. Furthermore, the application of electromyographic analysis to the primary arm muscles has been beneficial in understanding the muscular activity of the shoulder, elbow, and wrist throughout the various phases of the forehand stroke in wheelchair tennis.

This paper addresses a puzzle involving two modes of superlative modification in definite relatives in Jordanian Arabic1: the so-called (A)ttributive and (G)enitive superlatives.2 We show that under the low interpretation of the definite relative clause, both modes of superlative modification exhibit an asymmetrical behavior: while the A-superlative is ambiguous between the absolute and relative readings, the relative reading is blocked in G-superlatives. To resolve the puzzle, we propose a compositional analysis based on the late merger of the definite relative which generates the absolute/relative ambiguity in A-superlatives and at the same time it blocks the relative reading in G-superlatives.

External confinement of reinforced concrete columns using fiber-reinforced polymer (FRP) sheets can significantly enhance their seismic behavior. This research presents a numerical investigation to evaluate the seismic performance of RC rectangular columns with limited cross-sections' aspect ratios (1, 1.5, and 2) strengthened with a fully wrapped CFRP jacket under constant axial and pushover lateral loads. Therefore, a three-dimensional finite element model was implemented via ABAQUS software, which has been adopted in this study, where the proposed model showed a reliable agreement with the previous experimental work. The studied parameters are: longitudinal steel reinforcement ratio, CFRP confinement ratio, and axial load/capacity ratio for each cross-section aspect ratio. The obtained numerical results have proved that the external wrapping of RC rectangular columns with CFRP sheets has effectively increased drift capacity ratios for cross-sections aspect ratios 1, 1.5, and 2. Moreover, the strengthening of RC rectangular columns using external CFRP wrapping increases the nominal shear and flexural strengths of the strengthened columns. Also, the effect of increasing the longitudinal steel reinforcement ratio can significantly decrease the ultimate lateral displacement and drift capacity ratios. Besides, with the increase of the axial load/capacity ratios, the drift capacity ratios significantly decrease for the strengthened RC rectangular columns.

This continuation reports the thermal consequences of couple stress nanofluid containing gyrotactic microorganisms model in presence of novel features like nonlinear thermal, temperature dependent viscosity and uniform magnetic force. The generalized expressions of diffusion theory are entertained for the modeling of energy and concentration equations. The thermal radiative flow is addressed by using nonlinear thermal radiation instead of traditional linear thermal expressions. The effective Brownian motion and thermophoresis mechanisms are focused in view of Buongiorno's nano-material model. The current nanofluid model with couple stress nonlinear model is the most improved thermal model which preserves many results as a limiting case. The flow is persuaded by periodically accelerated and stretching surface. The resulted equations based on various elementary laws are formulated in partial differential form. The most convergent technique homotopy analysis method is proposed to discuss the solution procedure. The convergence analysis is performed and later on a comprehensive graphical observation with interesting physical justifications is presented. Various physical quantities are graphically entertained. The results show that the velocity profile oscillates periodically and magnitude of oscillation increases with couple stress parameter. The temperature of nanoparticles boosted with the viscosity parameter while a declining pattern of temperature is noted for the thermal Biot number. The skin friction coefficient periodically increases with the viscosity vector and couple stress parameter.

In recent years, the nanofluids are assumed to be most effective source of energy and reflect many applications in various industrial and engineering processes. With effective thermal properties, the nano-materials convey exclusive beneficial applications in heat exchanges, coolant processes, medical treatment, electronic cooling systems, energy production etc. The prime objective of current analysis is to scrutinize the three-dimensional double stratification flow of Burgers fluid containing microorganisms. The thermal radiation with nonlinear relations and heat absorption and generation applications are also endorsed. The modified forms of heat and mass diffusions are utilized to modify the analysis. The flow expressions for modeled problem are numerically evaluated by employing the shooting scheme. Physical features for various parameters against velocity of fluid, temperature distribution, volumetric concentration of nanoparticles and rescaled density of nanoparticles is deliberated with the help of several graphs. The observations reveal that heat and mass transfer mechanism decline with Deborah number. The concentration field rise up with concentration stratified Biot number while reduces with concentration relaxation constant. The presence of buoyancy parameters enhanced nanofluid temperature, concentration and microorganisms profiles. The obtained theoretical observation reveal applications in industrial, engineering and thermal processes which heat transfer involved. The claimed results are useful to improve the cooling and heating processes, energy generation, thermal devices, solar systems, manufacturing processes etc.

Air conditioning systems accountable a huge amount of energy consumption, the purpose of this work is to inspect the energy efficiency and the economic impact for air-conditioners using Wireless Sensing and Actuator Networks. Different methods are explored. Referring to ASHRAE Standard 62.1-2007 specified by manufacturers, the real case study tested for all rooms in the MUAB and using Wireless Sensor and Actuator Networks (WSAN) for detecting and assessing diverse technique of the conditioners in order to compare them with the existing on the market, the main results mention that the old conditioners should be replaced. Power parameters analysis proves that substituting actions applied in the main building enhance a preserving of 10% in the regular consumption of energy. Furthermore an investigation implemented to enclosure Stirling engine in air conditioning cycle demonstrate that can be a promoted solution and lessen meaningfully energy consumption, the novel numerical thermal model based on second order integrating irreversibility and energy losses tested on an alpha Stirling engine for the identical temperature and pressure governed in the refrigeration cycle show that it can be worked with energy efficiency around 42%. Keywords: Energy efficiency, WSAN, Air-conditioners, Thermal engine, Energy efficiency, Performance, Economic impact

Linguistic categories can impact visual perception. For instance, learning that two objects have different names can enhance their discriminability. Previous studies have identified a typical pattern of categorical perception, characterized by faster discrimination of stimuli from different categories, a neural mismatch response during early visual processing (100-200 ms), and effects restricted to the right visual field. However, it remains unclear whether language affects perception online or through long-term changes to mental representations in memory. To address this, we tested the impact of newly learned object categories with and without memory consolidation during sleep. We replicated the canonical pattern of categorical perception for categories that underwent consolidation. Without consolidation, linguistic categories still influenced early visual processing but with distinct neural dynamics. Therefore, we found evidence of both transient and long-term effects of language on perception and conclude that memory consolidation plays a crucial role in shaping how linguistic categories modulate perception.