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Abstract Background High myopia represents a health issue and leads to the development of complications that threaten vision. The study of macular changes in high myopia patients has undergone great advances with updated technology via new spectral optical coherence tomography (OCT) and Optical coherence tomography angiography (OCTA). Most of related studies have focused on the adults and additional studies need to investigate macular changes in children and adolescents. This study aimed to evaluate the changes in the macular structure by OCT and the macular vessel density in high myopia in children and adolescents by OCTA. Methods A cross-sectional comparative study. The population was divided into two groups: group 1 (4–11 years) and group 2 (12–18 years). The results were comparable to those of control study of the same age group. The two high myopia groups and the control groups were examined by macular OCT and OCTA to evaluate macular thickness and vessel density in the superficial and deep capillary plexuses. Results OCT measurements of patients in group 1 revealed that central macular thickness was significantly lower in high myopia group than in the control group and measured 220.91 ± 27.87 μm and 258.23 ± 17.26 μm, respectively, (P

Chatbots are computer programs that mimic human conversation using text or voice or both. Users’ acceptance of chatbots is highly influenced by their persona. Users develop a sense of familiarity with chatbots as they use them, so they become more approachable, and this encourages them to interact with the chatbots more readily by fostering favorable opinions of the technology. In this study, we examine the moderating effects of persona traits on students’ acceptance and use of chatbot technology at higher educational institutions in the UK. We use an Extended Unified Theory of Acceptance and Use of Technology (Extended UTAUT2). Through a self-administrated survey using a questionnaire, data were collected from 431 undergraduate and postgraduate computer science students. This study employed a Likert scale to measure the variables associated with chatbot acceptance. To evaluate the gathered data, Structural Equation Modelling (SEM) coupled with multi-group analysis (MGA) using SmartPLS3 were used. The estimated Cronbach’s alpha highlighted the accuracy and legitimacy of the findings. The results showed that the emerging factors that influence students’ adoption and use of chatbot technology were habit, effort expectancy, and performance expectancy. Additionally, it was discovered that the Extended UTAUT2 model did not require grades or educational level to moderate the correlations. These results are important for improving user experience and they have implications for academics, researchers, and organizations, especially in the context of native chatbots.

Saffron (Crocus sativus L.) is the most expensive spice in the world and rich in a variety of bioactive compounds including phenolic acids, flavonoids, and vitamins. Saffron is used in food, cosmetics, perfumery, and dye industries due to its color, taste, aroma, and medicinal properties. The extraction of bioactive compounds imposes a constant search for economically and environmentally viable extraction strategies for higher yields including the solvent type. The research was carried out to evaluate total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activity of C. sativus L. anthers using different extraction solvents including ethanol, methanol, and distilled water. The results showed that ethanol was the most effective extraction solvent type exhibiting the highest TPC (7.29 mg GAE g-1 DW), TFC (3.77 mg QE g-1 DW), and antioxidant activity of flavonoids (88%) and ascorbic acid (76.07%). Flavonoids proved to be stronger antioxidants than ascorbic acid, irrespective of solvent type, however the ethanolic extracts showed significantly higher antioxidant activity. A Reverse Phase High-Performance Liquid Chromatography method revealed that gallic acid (3.1 mg g-1), syringic acid (0.2 mg g-1), and vanillic acid (0.13 mg g-1) were the main phenolic compounds detected in the dried anther ethanolic extracts, while quercetin (2.13 mg g-1), pyrogallol (1.73 mg g-1), kaempferol (1.2 mg g-1), rutin (0.2 mg g-1), and tricin (0.1 mg g-1) the main flavonoid compounds. Thus, apart from the spice, constituted by the red stigmas, the production of other flower parts such as the anthers, so far considered agricultural waste can constitute a rich source of bioactive compounds of high antioxidant potential by setting quality standards for new products’ development and ensuring better valorization of saffron’s bioresidues in Mashhad region of Iran.

Ceftazidime/avibactam (CAZ-AVI) is FDA-approved for managing infections caused by resistant gram-negative bacilli, particularly infections via carbapenem-resistant Enterobacterales pathogens. The clinical data are still limited, particularly those in Saudi Arabia. The present study is a retrospective cohort study that was carried out at the Armed Forces Hospital in the southern region of Saudi Arabia to compare the clinical and microbiological outcomes for CAZ-AVI-treated patients as monotherapy and as an add-on to standard therapy for carbapenem-resistant Klebsiella pneumonia (CRKP) OXA-48 infections to those treated with standard drugs. The study included CRKP OXA-48-like infected patients who were administered antibiotics for more than seven days from 1 August 2018 to May 2023. Patients’ baseline characteristics and demography were extracted from the clinical records, and their clinical/microbiology efficiencies were assessed as per the corresponding definitions. Univariate and multivariate logistic regressions were conducted to identify the potential independent variable for CAZ-AVI efficiency. A total of 114 patient files were included for the evaluation. Among these patients, 64 used CAZ-AVI combined with standard therapy and were included in the intervention group, and 50 of them used standard therapy and were included in the comparative group. Following analysis, CAZ-AVI’s clinical success was 42.2% (p = 0.028), while the intervention versus comparative groups showed decreased 30-day all-cause mortality (50.0% versus 70.0%; p = 0.036) and infection recurrence (7.8% versus 24.0%; p = 0.019), as well as substantially increased rates of microbial eradication (68.8% versus 42.0%; p = 0.007). CAZ-AVI add-on therapy rather than monotherapy showed statistically significant favored clinical and microbial outcomes over the standard therapy. Furthermore, sex (female %), ICU admission, and fever were negatively associated with patients’ 30-day all-cause mortality, serving as independent negative factors. Only fever, CRP bio levels, inotropes, and ICU admissions were significant predictors influencing the CAZ-AVI’s clinical efficiency. The duration of CAZ-AVI therapy positively influenced CAZ-AVI’s microbial eradication, while both WBC counts and fever experiences were negative predictors. This study shows the effective usage of CAZ-AVI against CRKP OXA-48-like infections. The influencing independent variables depicted here should recommend that clinicians individualize the CAZ-AVI dose based on co-existing risk factors to achieve optimal survival and efficacy. Prospective multicenter and randomized control studies are recommended, with individualized CAZ-AVI precision administration implemented based on patients’ characteristics.

The objective of this research work is to evaluate the quality of central concrete plant of Al-Rasheed Company by using Six Sigma approach which is a measure of quality that strives for near elimination of defects using the statistical methods to improve outputs that are critical to customers. The fundamental objective of Six Sigma methodology is the implementation of a measurement-based strategy that focuses on process improvement and variation reduction to reach delighting customers, and then suggesting an improvement system to improve the production of concrete in Al-Rasheed State Contracting Construction Company. A field survey includes two parts (open and close questionnaire) that aimed to get the data and information required for achieving the research where the answers of questionnaire sample have led, during the application of DMAIC improvement cycle, to identifying the potential possible reasons that caused quality deviations in concrete works. Two programs have been used: First, ‘Sigma Level Calculator’ which is formulated by the researcher to measure the components of the processes performance. Second, ‘QI Macros Lean Six Sigma SPC Software 2011’ which uses the statistical tools of Six Sigma DMAIC methodology for: identifying the root causes of defects, analyzing the data, determining capability and stability of process. It is concluded that the processes sigma level for the concrete works quality is 2.41 σ and 181,070 DPMO which is considered too bad as compared with the current global competitio

Abstract Purpose To evaluate the surgical outcome of epicanthus and telecanthus correction by C-U medial canthoplasty with lateral canthoplasty in Blepharophimosis Syndrome. Patients and methods This was a retrospective single arm interventional study including 18 eyes of 9 patients with Blepharophimosis-ptosis-epicanthus inversus syndrome who presented to oculoplastic clinic, ophthalmology department, Qena university hospital in the period of between July 2020 to April 2021. All the patients had BPES with epicanthus and telecanthus. All cases were subjected to by C plasty with medial and lateral canthoplasty for correction of epicanthus and telecanthus correction followed by frontalis suspension surgery to correct the co-existing blepharoptosis. Results The study included 9 cases of BPES, 6 boys and 3 girls, the mean age was 5.4 ± 1.5 in the study group, all patients had a positive family history for BPES. After surgery, the mean IICD decreased from 38.44 mm preoperatively to 32.8 mm postoperatively, with a mean difference of 6.2 mm (P

Sepsis is characterized by multiple organ dysfunction, which is now accepted to be due to oxidative damage. The lung is the first organ exposed to this damage, and its injury is one of the leading causes of death. Therefore, many pharmacological strategies are employed to attenuate sepsis. This study aimed to evaluate the in silico and in vitro antibacterial activity of Cicer arietinum extract (CAE) against Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa and the in vivo modulatory effect of CAE against sepsis induced by cecal ligation and puncture (CLP) in rats. This study identified seven bioactive components in Cicer arietinum extract, revealing promising interactions between these components and Staphylococcus aureus-PBP2a and Pseudomonas aeruginosa-PBP3 proteins, highlighting their potential as novel antibacterial agents. After ensuring the bactericidal ability of CAE against Staphylococcus aureus and Pseudomonas aeruginosa, an in vivo study was performed. Twenty-four rats were divided into sham-operated rats, CLP-septic rats, CLP rats treated with CAE (500 mg/kg b.wt), and CLP rats treated with hydrocortisone (25 mg/ kg b.wt). CAE was administered orally for 3 days post-operation, and animals were euthanized on the fourth day. Another twenty-four rats were used to study survival for 5 days. This study revealed that CAE, like hydrocortisone, can rescue CLP rats from death by suppressing lung procalcitonin (PCT) and MDA and enhancing SOD, CAT, and GSH levels significantly, as compared with the CLP group. The histopathological results were parallel with the biochemical results since the CLP rats treated with CAE had lower histological/inflammatory scores in the lung like hydrocortisone. The beneficial role of CAE may result from its antibacterial and antioxidant activities, and CAE can be considered as a lung antiseptic extract. This study provides a novel treatment for sepsis-induced ALI. However, the beneficial impact of CAE needs extensive study to obtain evidence. [ABSTRACT FROM AUTHOR]

Due to the significant increase in heavy feedstocks being transported to refineries and the hydrocracking process, the significance of adopting an ebullated bed reactor has been reemphasized in recent years. The predictive modelling of gas hold-up in an ebullated two-phase reactor was performed using 10 machine learning methods based on support vector machine (SVM) and Gaussian process regression (GPR) in this study. In an ebullated bed reactor, the impacts of three features, namely liquid velocity, gas velocity, and recycling ratio, on the gas hold-up were examined. The liquid velocity has the most impact on the predicted gas hold-up, according to the feature significance analysis. The rotational-quadratic, squared-exponential, Matern 5/2, and exponential kernel functions integrated with the GPR models and the linear, quadratic, cubic, fine, medium, and coarse kernel functions integrated with the SVM model performed well during training and testing, with the exception of the fine SVM model, whose R2 is very low. According to the R2 > 0.9 and low RMSE and MAE values, the rotational-quadratic, squared-exponential, and Matern 5/2 GPR models performed the best.

This study introduces the global-local least-squares support vector machine (GLocal-LS-SVM), a novel machine learning algorithm that combines the strengths of localised and global learning. GLocal-LS-SVM addresses the challenges associated with decentralised data sources, large datasets, and input-space-related issues. The algorithm is a double-layer learning approach that employs multiple local LS-SVM models in the first layer and one global LS-SVM model in the second layer. The key idea behind GLocal-LS-SVM is to extract the most informative data points, known as support vectors, from each local region in the input space. Local LS-SVM models are developed for each region to identify the most contributing data points with the highest support values. The local support vectors are then merged at the final layer to form a reduced training set used to train the global model. We evaluated the performance of GLocal-LS-SVM using both synthetic and real-world datasets. Our results demonstrate that GLocal-LS-SVM achieves comparable or superior classification performance compared to standard LS-SVM and state-of-the-art models. In addition, our experiments show that GLocal-LS-SVM outperforms standard LS-SVM in terms of computational efficiency. For instance, on a training dataset of 9, 000 instances, the average training time for GLocal-LS-SVM was only 2% of the time required to train the LS-SVM model while maintaining classification performance. In summary, the GLocal-LS-SVM algorithm offers a promising solution to address the challenges associated with decentralised data sources and large datasets while maintaining high classification performance. Furthermore, its computational efficiency makes it a valuable tool for practical applications in various domains.

Context The computerization of both fetal heart rate (FHR) and intelligent classification modeling of the cardiotocograph (CTG) is one of the approaches that are utilized in assisting obstetricians in conducting initial interpretation based on (CTG) analysis. CTG tracing interpretation is crucial for the monitoring of the fetal status during weeks into the pregnancy and childbirth. Most contemporary studies rely on computer-assisted fetal heart rate (FHR) feature extraction and CTG categorization to determine the best precise diagnosis for tracking fetal health during pregnancy. Furthermore, through the utilization of a computer-assisted fetal monitoring system, the FHR patterns can be precisely detected and categorized. Objective The goal of this project is to create a reliable feature extraction algorithm for the FHR as well as a systematic and viable classifier for the CTG through the utilization of the MATLAB platform, all the while adhering to the recognized Royal College of Obstetricians and Gynecologists (RCOG) recommendations. Method The compiled CTG data from spiky artifacts were cleaned by a specifically created application and compensated for missing data using the guidelines provided by RCOG and the MATLAB toolbox after the implemented data has been processed and the FHR fundamental features have been extracted, for example, the baseline, acceleration, deceleration, and baseline variability. This is followed by the classification phase based on the MATLAB environment. Next, using the guideline provided by the RCOG, the signals patterns of CTG were classified into three categories specifically as normal, abnormal (suspicious), or pathological. Furthermore, to ensure the effectiveness of the created computerized procedure and confirm the robustness of the method, the visual interpretation performed by five obstetricians is compared with the results utilizing the computerized version for the 150 CTG signals. Results The attained CTG signal categorization results revealed that there is variability, particularly a trivial dissimilarity of approximately (+/−4 and 6) beats per minute (b.p.m.). It was demonstrated that obstetricians’ observations coincide with algorithms based on deceleration type and number, except for acceleration values that differ by up to (+/−4). Discussion The results obtained based on CTG interpretation showed that the utilization of the computerized approach employed in infirmaries and home care services for pregnant women is indeed suitable. Conclusions The classification based on CTG that was used for the interpretation of the FHR attribute as discussed in this study is based on the RCOG guidelines. The system is evaluated and validated by experts based on their expert opinions and was compared with the CTG feature extraction and classification algorithms developed using MATLAB.

Construction is a hazardous industry with a high number of injuries. Prior research found that many industry injuries can be prevented by implementing an effective safety plan if prepared and maintained by qualified safety personnel. However, there are no specific guidelines on how to select qualified construction safety personnel and what criteria should be used to select an individual for a safety position in the United States (US) construction industry. To fill this gap in knowledge, the study goal was to identify the desired qualifications of safety personnel in the US construction industry. To achieve the study goal, the Delphi technique was used as the main methodology for determining the desired qualifications for construction safety personnel. As a result, a panel of 15 subject-matter experts was selected, and 4 rounds of surveys were carried out. The findings of the study led to the identification of the desired qualifications for three construction safety positions (safety entry, safety professional, and safety manager). The present study contributes to the body of theoretical knowledge on construction safety and presents practical guidelines to assist industry stakeholders select qualified safety personnel for their projects. The selection of qualified safety personnel is expected to improve workplace safety performance and positively reflect on other project outcomes. Construction stakeholders should pay attention to three key aspects (namely, education, experience, and certification) when determining the qualifications for a safety leadership position and take into consideration the type of position intended to be filled. This study fills the gap in knowledge by identifying the desired qualifications and criteria on how to select safety personnel in the US construction industry.

The construction industry, characterized by unique challenges such as working at heights and using heavy equipment, has turned to unmanned aerial systems (UASs), frequently known as drones, to mitigate workplace hazards, improve safety, and enhance productivity. While numerous benefits claimed, application UASs in construction introduces unique safety challenges. The objectives of the present study are (1) to identify risks associated with the use of UASs for construction operations based on a review of existing literature, and (2) to present the identified risks to industry professionals and practitioners using hypothetical case study examples. The study findings indicate that risks associated with the use of UASs in construction can be classified into four categories: operational errors and safety hazards, privacy intrusions and security risks, mechanical and technical failures, and regulatory and legal considerations. After identifying the risks, three hypothetical examples are carefully developed and presented in collaboration with aviation safety experts to help industry people better comprehend risks associated with the use of UASs in construction. Each case study delineates hazards that could emerge on a construction site and explains the connection between these hazards and the utilization of UASs. The presented case studies also recommend risk mitigation strategies and best practices for using UASs for construction operations. The present study contributes to practice by aiding construction companies in risk awareness, safety training, and risk mitigation for UAS applications in construction. [ABSTRACT FROM AUTHOR]

The construction industry is essential for the economic prosperity of any nation. However, the construction workforce encounters numerous challenges stemming from various factors, including the dynamic and cyclical nature of construction operations. These challenges have led to undesired outcomes such as shortage of skilled employees and increased employee turnover rates. To overcome these undesired outcomes, construction companies have started to look for innovative strategies aimed at empowering their employees. The goal of the present study was to identify and statistically examine the most effective strategies for achieving employee empowerment, focusing specifically on the perspective of employees themselves. To achieve the study goal, a list of strategies from prior studies believed to be desired for empowering construction employees were identified from existing literature. A survey questionnaire was developed and sent to frontline construction employees, and 114 responses were collected. After collecting the responses, descriptive and inferential statistical analyses were performed. The findings identified 12 strategies perceived to be effective for empowering construction employees and provided statistical evidence to support the effectiveness of these strategies. In particular, equitable payment, nondiscrimination policy, transparency, and professional development/training were identified as particularly impactful in advancing employee empowerment in construction. By implementing the identified strategies, construction companies are expected to cultivate a positive work environment that fosters employee engagement, improves productivity, and ultimately contributes to overall organizational success. Future research and industry initiatives can build upon these findings to further enhance employee empowerment and well-being in the construction industry and facilitate the implementation of these strategies throughout the industry. The present study contributes to the understanding of employee empowerment in construction by highlighting the strategies perceived as highly effective by construction employees. [ABSTRACT FROM AUTHOR]