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Background: One of the most prevalent chronic illnesses in the nation and the world is diabetes. It remains as one of the leading cause of death so it's important to create cutting-edge, potentially cost-effective co-treatment techniques derived from plants that don't have any negative impacts. Previous research has shown that watercress (Nasturtium officinale) possesses anti-inflammatory, antioxidant, and anti-diabetic properties. Objectives: to investigate the effects of watercress aqueous extract on gene expression of glucose transporter 4 (GLUT4) and 5’ AMP-activated protein kinase (AMPK) in streptozotocin induced diabetic rats. Materials and methods: Sixty healthy male albino rats were used in this study. Animals were split into four equal groups, each of 15 rats. Group 1: (Negative Control), Group 2: (Diabetes Positive Control injected with (45mg/kg body weight) Streptozotocin intraperitoneally), Group 3 (diabetic rats received 100 mg of watercress aqueous extract /Kg body weight for 8 weeks, daily) and Group 4 (diabetic rats received 200 mg of watercress aqueous extract /Kg body weight for 8 weeks, daily). Blood was collected after scarification on weeks 2, 4, 6, and 8 of the experiment for serum separation and pancreatic tissues were collected on weeks 4 and 8 of the experiment. Fasting blood glucose as measured by glucometer, insulin hormone was measured by ELISA kit.Triglyceride, LDL, HDL, creatinine, urea, AST and ALT were measured by spectrophotometer. SYBR Green qPCR Master Mix was used for measurement of GLUT4, AMPK and Beta-actin. Results: The treated group exhibited a significant and progressive decrease in fasting blood glucose, triglycerides, total cholesterol, LDL, HDL, creatinine, urea, ALT, and AST and a significant and progressive increase in insulin hormone at all experiment times compared to the controls. The 4th group exhibited a significant and progressive up regulation gene expression of GLUT4 and AMPK genes at 4 and 8 weeks compared to the controls considering watercress as an alternative treatment for diabetes. Conclusion. Watercress aqueous extract had positive effects on lowering and maintaining normal glucose levels.

The significant losses that banks and other financial organizations suffered due to new bank account (NBA) fraud are alarming as the number of online banking service users increases. The inherent skewness and rarity of NBA fraud instances have been a major challenge to the machine learning (ML) models and happen when non-fraud instances outweigh the fraud instances, which leads the ML models to overlook and erroneously consider fraud as non-fraud instances. Such errors can erode the confidence and trust of customers. Existing studies consider fraud patterns instead of potential losses of NBA fraud risk features while addressing the skewness of fraud datasets. The detection of NBA fraud is proposed in this research within the context of value-at-risk as a risk measure that considers fraud instances as a worst-case scenario. Value-at-risk uses historical simulation to estimate potential losses of risk features and model them as a skewed tail distribution. The risk-return features obtained from value-at-risk were classified using ML on the bank account fraud (BAF) Dataset. The value-at-risk handles the fraud skewness using an adjustable threshold probability range to attach weight to the skewed NBA fraud instances. A novel detection rate (DT) metric that considers risk fraud features was used to measure the performance of the fraud detection model. An improved fraud detection model is achieved using a K-nearest neighbor with a true positive (TP) rate of 0.95 and a DT rate of 0.9406. Under an acceptable loss tolerance in the banking sector, value-at-risk presents an intelligent approach for establishing data-driven criteria for fraud risk management.

Background: Hypospadias is a wide-world congenital malformation that accounts for 1 of 300 live male births. Many procedures were considered for its management. As the tubularised incised plate (TIP) urethroplasty, the most prevalent technique, caused many complications, several modifications were applied to the original operation to improve the outcomes and alleviate complications. The aim of this study was to compare the outcome of the ordinary TIP urethroplasty with the technique modified without dissection of the glans penis. Materials and Methods: A total of 82 patients with a mean age of 18.8 (±14.8) months, were randomly assigned to undergo TIP with either complete glans wings mobilisation (Group A, n = 42 patients) or without glans dissection (Group B, n = 40 patients). To evaluate the effect of modified TIP urethroplasty without glanular dissection for treatment of distal hypospadias in contrast to classical TIP repair. Results: Both techniques showed similar outcomes regarding functional repair, with good to excellent results between 88% and 90% after 6 months of follow-up. Most confronted post-operative complications were wound infection, oedema, urethrocutaneous fistulas and meatal stenosis. Less frequently haematoma, post-operative bleeding and glans dehiscence were encountered. The differences in complication rates between the two studied groups were statistically insignificant except for oedema (P = 0.04), and need for urethral dilatation (P = 0.002) that were more prevalent among patients who were treated with classic TIP repair with complete glans wings mobilisation. Conclusion: From our point of view, it seems that TIP without glanular dissection technique does not outweigh TIP with complete glans wings mobilisation regarding functional outcomes and post-operative complications.

Background One of the most common conditions presenting to the oculoplastic clinic is congenital nasolacrimal duct obstruction (CNLDO), with an incidence of up to 20% in young children. Early probing as early as 18 months of age is usually associated with very good results. Conversely, the results of probing in older children and the need for intubation, either primary or secondary, are debatable in different studies. Purpose The aim of this study was to compare the outcome of probing versus primary intubation in children older than 2 years having CNLDO. Patients and methods This prospective cohort comparative study was carried out on 40 eyes of 36 children, aged 2–7 years of both sexes, with epiphora due to CNLDO. The eyes were divided into two groups: group A that included 20 eyes that underwent probing, and group B that included 20 eyes that underwent intubation in whom the tube was removed after 3 months. The enrolled children were subjected to local ophthalmological examination, eye lid examination, puncti evaluation, regurge test, nasal evaluation, lacrimal pathway evaluation, and computed tomography dacryocystography before the procedure and 3 months after the procedure. Results The intubation group (group B) was found to have a higher success rate (90%) compared to the probing group (group A) (80%), although the difference was statistically insignificant (P=0.661). On univariate regression analysis, age, contrast volume, and most dilated portion of the lacrimal sac before the procedure were significant predictors for the success rate (P

The effective usage of energy becomes crucial for the successful deployment and operation of unmanned aerial vehicles (UAVs) in different applications, such as surveillance, transportation, and communication networks. The increasing demand for UAVs in different industries such as agriculture, logistics, and emergency response has led to the development of more sophisticated and advanced UAVs. However, the limited onboard energy resource of UAVs poses a major problem for their long-term operation and endurance. In addition, artificial intelligence (AI) and machine learning (ML) could allow UAVs to make more informed and intelligent decisions regarding their operations, resulting in sustainable and more energy-efficient UAV deployment. This article designs a Hybrid Snake Optimizer-based Route Selection Approach for Unmanned Aerial Vehicles Communication (HSO-RSAUAVC) technique. The goal of the HSO-RSAUAVC technique is to explore and select optimal routes for UAV communication. In the presented HSO-RSAUAVC technique, the SO algorithm is integrated with Bernoulli Chaotic Mapping and Levy flight (LF) for enhanced performance. In addition, the HSO-RSAUAVC method derives a fitness function including residual energy (RE), distance, and UAV degree. By incorporating the HSO-RSAUAVC technique, we can dynamically adapt UAV paths to overcome obstacles, decrease communication interference, and optimize energy utilization. To validate the performance of the proposed model, a series of simulations were performed. The comparative result analysis illustrates the better performance of the HSO-RSAUAVC technique in improving the performance and reliability of UAV communication.

The novel coronavirus (COVID-19) has inundated the whole world by causing severe acute respiratory syndrome in humans, thus posing serious public health concerns. The oral and olfactory systems are significantly impacted by the COVID-19 condition, in addition to the respiratory and digestive systems. Oral symptoms of COVID-19 can be caused by a loss in oral hygiene, immune system suppression, a decline in general health, and candidiasis due to prolonged antibiotic use. Because many aerosols and droplets are produced during various dental operations, dental professionals and dentists are at a significant risk of contracting the COVID-19 infection. Few precautionary measures include performing a pre-appointment health screening for all patients, performing aerosol-producing procedures in a designated space or operatory, using proper personal protective equipment and disinfecting the operatory between patients, and limiting the number of dental procedures at one time. Against this background, the purposes of this article are to explore the oral presentations of COVID-19 infection and to emphasize the hazards to dental professionals during COVID-19 pandemic. Additionally, few preventive measures are also highlighted.

Background: Five-fifths of all incidents of blindness in Saudi Arabia may be attributed to cataracts. Cataracts are the second major cause of blindness, responsible for 35.5% of cases. Therefore, the purpose of the research was to measure the visual acuity improvement after cataract surgery in children. Materials and Methods: This systematic review followed PRISMA guidelines for reporting systematic reviews. All procedures followed the recommendations of the Cochrane handbook. Studies of varying study designs, both published and unpublished, are included. Retrospective studies with outcomes of pediatric cataract surgery were identified from various databases. Result: After an initial screening, 108 out of 167 items were deemed unsuitable for publication. There were 59 full-text papers assessed for inclusion, and only seven matched the criteria. All the articles included were of a very high standard. Both the duration of therapy and the target population varied widely between the studies. Conclusion: The results indicated that the majority of childhood cataracts are hereditary. Primary posterior capsulectomy and anterior vitrectomy combined with cataract extraction and intra-ocular lens implantation is the treatment of choice for pediatric cataracts. It is recommended that surgery be performed in a properly equipped facility staffed by trained, cooperative personnel and that different procedures be used to enhance post-operative follow-up.

The Single Instruction Multiple Data (SIMD) architecture, supported by various high-performance computing platforms, efficiently utilizes data-level parallelism. The SIMD model is used in traditional CPUs, dedicated vector systems, and accelerators such as GPUs, vector extensions, and Xeon Phi. It provides performance throughput in computation-intensive and data-parallel applications. Despite the similarity of data-processing principles between these architectures, porting various programming models between the reviewed platforms is challenging. Furthermore, enhancing the programmability of these architectures is an important feature for utilizing their emerging computing power and simplifying programming complexity. This paper reviews the basic principles of optimization techniques to run asynchronous Multiple Instruction Multiple Data (MIMD) on SIMD accelerators. It also surveys several GPU programming paradigms and application programming interfaces (APIs) and classifies these frameworks into different groups based on their criteria. In addition, a review of studies that performed a comparison of the collaborative execution of GPUs with CPUs and Xeon Phi is presented in this paper. This study will be beneficial for developers and researchers in the field of computer architecture and parallel computing of intensive scientific applications, specifically for early-stage high-performance computing researchers, to obtain a brief overview of performance optimization opportunities as well as the challenges of existing SIMD platforms.

Origami, the art of paper folding, addresses traditionally conflicting requirements for designing both powerful and low-cost haptic interfaces. As of today, there are no comprehensive reviews that cover origami-inspired haptic actuation, sensing, design processes, and fabrication. To fill this void, this paper summarizes existing origami-inspired haptic technologies in terms of workspace, degrees of freedom (DoF), power consumption, control methods, sensing, and actuation. The paper also presents an iterative design process for pattern generation and origami-inspired haptic characterization. Using this design process, we demonstrate a case study that involves the design, development, and evaluation of a novel syringe haptic interface for dental simulation. Our main findings suggest that origami-inspired haptics need more mathematically optimized and versatile design, as well as novel materials that offer a room for embedded sensing and actuation.

Abstract In the sugar industry, eliminating side impurities throughout the manufacturing process is the most significant obstacle to clarifying sugar solutions. Herein, magnetic chitosan (MCS) nanocomposite was Fabricated to be used as a biodegradable, environmentally friendly clarifying agent throughout the cane juice and sugar refining processes. Fe3O4 was synthesized using the coprecipitation procedure, and then MCS was combined using a cross-linking agent. Furthermore, 14.76 emu g−1 was the maximum saturation magnetization (Ms) value. Because MCS is magnetically saturated, it may be possible to employ an external magnetic field to separate the contaminant deposited on its surface. Additionally, zeta potential analysis showed outstanding findings for MCS with a maximum value of (+) 20.7 mV, with improvement in color removal % up to 44.8% using MCS with more than 24% in color removal % compared to the traditional clarification process. Moreover, utilizing MCS reduced turbidity from 167 to 1 IU. Overall, we determined that MCS nanocomposite exhibits considerable effectiveness in the clarifying process for different sugar solutions, performing as an eco-friendly bio-sorbent and flocculating material.

Abstract This study investigates using the phononic crystal with periodically closed resonators as a greenhouse gas sensor. The transfer matrix and green methods are used to investigate the dispersion relation theoretically and numerically. A linear acoustic design is proposed, and the waveguides are filled with gas samples. At the center of the structure, a defect resonator is used to excite an acoustic resonant peak inside the phononic bandgap. The localized acoustic peak is shifted to higher frequencies by increasing the acoustic speed and decreasing the density of gas samples. The sensitivity, transmittance of the resonant peak, bandwidth, and figure of merit are calculated at different geometrical conditions to select the optimum dimensions. The proposed closed resonator gas sensor records a sensitivity of 4.1 Hz m−1 s, a figure of merit of 332 m−1 s, a quality factor of 113,962, and a detection limit of 0.0003 m s−1. As a result of its high performance and simplicity, the proposed design can significantly contribute to gas sensors and bio-sensing applications.

BACKGROUND: The preparticipation physical evaluation (PPE) monograph is a vital resource for medical providers aimed at ensuring the safety and well-being of athletes during sports participation by screening for injuries and disease risk factors. However, the concept of PPE is relatively new in Saudi Arabia, where primary care physicians (PCPs) often lack the proper training for it. This study’s aim was to assess PCPs’ knowledge and practice of PPE and identify associated factors. MATERIALS AND METHODS: A self-administrated web-based questionnaire was distributed to PCPs in the Eastern Province of Saudi Arabia. The questionnaire covered the various aspects of PPE knowledge (including general principles, components, contraindications of sports participation, concerning history and physical findings, electrocardiography interpretations, and ethical considerations) as well as PPE practice. Initial treatment of data included descriptive statistics.; Chi-square tes or Fisher's exact test as, as appropriate, were used to determine association of knowledge and practices with various independent variables. RESULTS: Of the 240 contacted PCPs, 192 responded yielding a response rate of 80%; 50.5% had no prior PPE training. About 43% of the PCPs had not encountered PPE during their examination, but the remainder performed monthly PPE. Notably, 82.8% demonstrated a poor level of knowledge regarding PPE and only 43% had a satisfactory level of practice. CONCLUSION: This study revealed that a significant proportion of PCPs displayed poor knowledge of PPE and

Biomedical image segmentation is a vital task in the analysis of medical imaging, including the detection and delineation of pathological regions or anatomical structures within medical images. It has played a pivotal role in a variety of medical applications, involving diagnoses, monitoring of diseases, and treatment planning. Conventionally, clinicians or expert radiologists have manually conducted biomedical image segmentation, which is prone to human error, subjective, and time-consuming. With the advancement in computer vision and deep learning (DL) algorithms, automated and semi-automated segmentation techniques have attracted much research interest. DL approaches, particularly convolutional neural networks (CNN), have revolutionized biomedical image segmentation. With this motivation, we developed a novel equilibrium optimization algorithm with a deep learning-based biomedical image segmentation (EOADL-BIS) technique. The purpose of the EOADL-BIS technique is to integrate EOA with the Faster RCNN model for an accurate and efficient biomedical image segmentation process. To accomplish this, the EOADL-BIS technique involves Faster R-CNN architecture with ResNeXt as a backbone network for image segmentation. The region proposal network (RPN) proficiently creates a collection of a set of region proposals, which are then fed into the ResNeXt for classification and precise localization. During the training process of the Faster RCNN algorithm, the EOA was utilized to optimize the hyperparameter of the ResNeXt model which increased the segmentation results and reduced the loss function. The experimental outcome of the EOADL-BIS algorithm was tested on distinct benchmark medical image databases. The experimental results stated the greater efficiency of the EOADL-BIS algorithm compared to other DL-based segmentation approaches.

Android malware recognition is the procedure of mitigating and identifying malicious software (malware) planned to target Android operating systems (OS) that are extremely utilized in smartphones and tablets. As the Android ecosystem endures to produce, therefore is the risk of malware attacks on these devices. Identifying Android malware is vital for keeping user data, privacy, and device integrity. Android malware detection utilizing deep learning (DL) signifies a cutting-edge system for the maintenance of mobile devices. DL approaches namely recurrent neural network (RNN) and convolutional neural network (CNN) are best in automatically removing intricate designs and behaviors in Android app data. By leveraging features such as application programming interface (API) call sequences, code patterns, and permissions, these approaches are efficiently differentiated between benign and malicious apps, even in the face of previous unseen attacks. This study presents an Intelligent Pattern Recognition using an Equilibrium Optimizer with Deep Learning (IPR-EODL) Approach for Android Malware Recognition. The purpose of the IPR-EODL approach is to properly identify and categorize the Android malware in such a way that security can be achieved. In the IPR-EODL technique, the data pre-processing step was applied to convert input data into a compatible setup. In addition, the IPR-EODL technique applies channel attention long short-term memory (CA-LSTM) methodology for the recognition of Android malware. To enhance the solution of the CA-LSTM algorithm, the IPR-EODL system employs the Equilibrium optimization (EO) algorithm for the hyperparameter tuning method. The experimentation evaluation of the IPR-EODL model can be verified on a benchmark Android malware database. The extensive results highlight the significant result of the IPR-EODL approach to the Android malware detection process.

Healthcare is an area of concern where the application of human-centred design practices and principles can enormously affect well-being and patient care. The provision of high-quality healthcare services requires a deep understanding of patients’ needs, experiences, and preferences. Human activity recognition (HAR) is paramount in healthcare monitoring by using machine learning (ML), sensor data, and artificial intelligence (AI) to track and discern individuals’ behaviours and physical movements. This technology allows healthcare professionals to remotely monitor patients, thereby ensuring they adhere to prescribed rehabilitation or exercise routines, and identify falls or anomalies, improving overall care and safety of the patient. HAR for healthcare monitoring, driven by deep learning (DL) algorithms, leverages neural networks and large quantities of sensor information to autonomously and accurately detect and track patients’ behaviors and physical activities. DL-based HAR provides a cutting-edge solution for healthcare professionals to provide precise and more proactive interventions, reducing the burden on healthcare systems and improving patient well-being while increasing the overall quality of care. Therefore, the study presents an improved coyote optimization algorithm with a deep learning-assisted HAR (ICOADL-HAR) approach for healthcare monitoring. The purpose of the ICOADL-HAR technique is to analyze the sensor information of the patients to determine the different kinds of activities. In the primary stage, the ICOADL-HAR model allows a data normalization process using the Z-score approach. For activity recognition, the ICOADL-HAR technique employs an attention-based long short-term memory (ALSTM) model. Finally, the hyperparameter tuning of the ALSTM model can be performed by using ICOA. The stimulation validation of the ICOADL-HAR model takes place using benchmark HAR datasets. The wide-ranging comparison analysis highlighted the improved recognition rate of the ICOADL-HAR method compared to other existing HAR approaches in terms of various measures.

The snow ablation optimization (SAO) is a new metaheuristic motivated by the melting and sublimation properties of snow. In this work, the economic load dispatch (ELD) problem, one of the key components of a power system, is solved using the SAO. There is one kind of ELD, that is focused on minimizing fuel usage costs. Assessing the reliability of the SAO, its performance is compared against some techniques. For the same case study, these techniques include the grey wolf optimization (GWO), the tunicate swarm algorithm (TSA), the monarch butterfly optimization (MBO), and the rime-ice algorithm (RIME). There are six cases used in this work: the first two cases are 6 generators at two loads 700 MW and 1000 MW for the ELD problem. The second two cases are 10 generators at two loads 1000 MW and 2000 MW for the ELD problem. The third two cases are 20 generators at two loads 2000 MW and 3000 MW for the ELD problem. The methods were assessed across 30 different runs using metrics for the maximum, mean, minimum objective function, and standard deviation. The primary component of ELD issues is the power mismatch element. This factor’s optimal value must approach zero. The optimal power mismatch values of 3.336E-13 and 1.57E-10 are obtained using the SAO method for six generator units at demand loads of 1000 MW and 700 MW, respectively. The optimal power mismatch values of 6.83E-6 and 1.65E-7 are obtained by the SAO method for ten generator units at demand loads of 1000 and 2000 MW, respectively. The optimal power mismatch values of 1.82E-4 and 7.91E-5 are obtained using the SAO method for 20 generator units at demand loads of 2000 and 3000 MW, respectively. The results produced for the six ELD case studies show that the SAO surpasses all competing algorithms, proving its superiority.

The Integrated Sensing and Communication (ISAC) system merged with Reconfigurable Intelligent Surface (RIS) has recently received much attention. This paper proposes an intelligent metaheuristic version of Enhanced Artificial Ecosystem Optimizer (EAEO) for a suggested beamforming optimization framework in ISAC systems with RIS. Two RIS are utilized in the presented model to enhance the received signal-to-noise ratio (SNR) for multiple-input multiple-output (MIMO) communication systems. Also, each element of each RIS scatters the incoming signal with a controllable phase-shift, without increasing its power. The signal is transmitted by a Dual-Function Base Station (DFBS) that is integrated with the RIS, which performs both communication and sensing functions simultaneously. The ISAC system is designed to optimize the signal transmission through the RIS by maximizing the SNR to increase the overall performance. In the proposed EAEO version, a Fitness-Distance-Balance Model (FDBM) is combined with the standard Artificial Ecosystem Optimizer (AEO) to improve the quality of the solutions in multidimensional and nonlinear optimization scenarios. The simulation results show that the proposed EAEO algorithm improves the SNR of different users for different numbers of RIS elements. The SNR reaches 25 dB when using 200 RIS elements. Moreover, the proposed EAEO is tested on the IEEE Congress on Evolutionary Computation 2017 (IEEE CEC’17) test suite. A comparative analysis is conducted compared to the standard AEO and several recent algorithms. The proposed EAEO derives great effectiveness and robustness over the others as it provides a higher rate of success in achieving the global optimum point.

Abstract For the treatment of rhinitis and asthma, a combination of Montelukast sodium and Bilastine has just been approved. Based on the first derivative of synchronous fluorescence, the current work developed a green, highly accurate, sensitive, and selective spectroscopic approach for estimating Montelukast sodium and Bilastine in pharmaceutical dosage form without previous separation. The selected technique focuses on measuring the synchronized fluorescence of the studied medications at a fixed wavelength range (Δλ) = 110 nm, and using the amplitude of the first derivative's peak at 381 and 324 nm, for quantitative estimation of Montelukast sodium and Bilastine, respectively. The impacts of different factors on the referred drugs' synchronized fluorescence intensity were investigated and adjusted. The calibration plots for were found to be linear over concentration ranges of 50–2000 ng mL−1 for Montelukast sodium and 50–1000 ng mL−1 for Bilastine. Montelukast sodium and Bilastine have LODs of 16.5 and 10.9 ng mL−1, respectively. In addition, LOQs were: 49.9 and 33.0 ng mL−1, for both drugs, respectively. The developed method was successfully employed to quantify the two drugs in synthetic tablets mixture and in laboratory prepared mixtures containing varied Montelukast and Bilastine ratios. To compare the results with the published analytical approach, a variance ratio F-test and a student t-test were used, which revealed no significant differences.

A novel kind of non-integer order bilinear filters, named double-order bilinear filters, is introduced in this work. They are based on the employment of two non-integer orders, offering the maximum design flexibility in comparison with their fractional-order and power-law counterparts. An attractive offered benefit is that this is achieved without increasing the circuit complexity, since the proposed structure is capable of realizing all non-integer kinds of filters. Two design examples are provided, where it is shown that lead/lag compensators utilized in control applications and low/high shelving filters employed in acoustic applications are actually bilinear filters with suitably selected pole/zero frequencies. Simulation and experimental results, using the OrCAD PSpice simulator and a Field Programmable Analog Array device, respectively, support the findings of this work.

Objective: To evaluate the perioperative as well as early oncological outcomes of patients undergoing robotic retroperitoneal lymph node dissection for treatment of testicular cancer. Methods: We conducted a prospective consecutive case series of patients undergoing robotic assisted retroperitoneal lymph node dissection for metastatic testicular cancer between May 2018 and July 2021 at our institution. Data were collected on patient and tumour characteristics, intraoperative and postoperative parameters, and functional and oncological outcomes. Descriptive statistics are presented. Results: Nineteen patients were identified; 18 (94.7%) completed the procedure robotically and one was converted to open surgery; 78.9% of patients had stage ≥IIB and 12 (63.2%) patients had undergone prior chemotherapy. The median operative time was 300 (interquartile range [IQR] 240–315) min. Median blood loss was 100 (IQR 50–175) mL. Median length of stay was 2 (range 1–11) days. All robotically completed patients commenced diet and passed flatus on Day 1 and were discharged by Day 3. The median lymph node yield was 40.5 (IQR 38–51) nodes. All patients undergoing nerve-sparing procedures recovered antegrade ejaculatory function. One patient had a Clavien-Dindo III complication (chylous ascites requiring drainage). At a median follow-up of 22.3 (IQR 16.3–24.9) months, one patient developed retroperitoneal recurrence, which was successfully treated with second-line chemotherapy; no other patients have had recurrences. Conclusion: Robotic retroperitoneal lymph node dissection is a safe and feasible alternative to open surgery in appropriately selected patients, offering low morbidity. Early oncological outcomes are promising. Larger cohorts and longer follow-ups are required to validate our institution's findings.

Currently, remote sensing images (RSIs) are often exploited in the explanation of urban and rural areas, change recognition, and other domains. As the majority of RSI is high-resolution and contains wide and varied data, proper interpretation of RSIs is most important. Land use and land cover (LULC) classification utilizing deep learning (DL) is a common and efficient manner in remote sensing and geospatial study. It is very important in land planning, environmental monitoring, mapping, and land management. But, one of the recent approaches is problems like vulnerability to noise interference, low classification accuracy, and worse generalization ability. DL approaches, mostly Convolutional Neural Networks (CNNs) revealed impressive performance in image recognition tasks, making them appropriate for LULC classification in RSIs. Therefore, this study introduces a novel Land Use and Land Cover Classification employing the River Formation Dynamics Algorithm with Deep Learning (LULCC-RFDADL) technique on RSIs. The main objective of the LULCC-RFDADL methodology is to recognize the diverse types of LC on RSIs. In the presented LULCC-RFDADL technique, the dense EfficientNet approach is applied for feature extraction. Furthermore, the hyperparameter tuning of the Dense EfficientNet method was implemented using the RFDA technique. For the classification process, the LULCC-RFDADL technique uses the Multi-Scale Convolutional Autoencoder (MSCAE) model. At last, the seeker optimization algorithm (SOA) has been exploited for the parameter choice of the MSCAE system. The achieved outcomes of the LULCC-RFDADL algorithm were examined on benchmark databases. The simulation values show the better result of the LULCC-RFDADL methods with other approaches in terms of different metrics.

Abstract Partial discharge (PD) could lead to the formation of small arcs or sparks within the insulating material, which can cause damage and degradation to the insulator over time. In ceramic insulators, there are several factors that can cause PD including manufacturing defects, aging, and exposure to environmental conditions such as moisture and temperature extremes. As a result, detecting and monitoring PD in ceramic insulators is important for ensuring the reliability and safety of electrical systems that rely on these insulators. In this study, acoustic emission technique is introduced for PD detection and condition monitoring of defective ceramic insulators. A sequence of data processing techniques is performed on the captured signals to extract and select the most significant signatures for classification of defects in insulator strings. Artificial neural network (ANN) has been used to build an intelligent classifier for easily and accurately classification of defective insulators. The overall recognition rate of the classifier was obtained at 96.03% from discrete wavelet transform analysis and 88.65% from fast Fourier transform analysis. This obtained result indicates high accuracy and performance classification. The outcomes of ANN were verified by SVM and KNN algorithms.

Abstract The advent of flow micro-power generation has resparked the interest in researching the galloping instability with the objective of determining the shape of the bluff body that is most prone to galloping. Such shape, which is sought to maximize the efficacy of galloping micro-power generators (GMPGs), must possess a very low cut-in flow speed while achieving large-amplitude steady-state oscillations beyond it. Additionally, since GMPGs can operate in environments with fluctuating flow conditions, the optimal shape must also have a very short rise time to its steady-state amplitude. In this work, we utilize computational fluid dynamics in conjunction with machine learning to optimize the shape of the bluff body of GMPGs for both steady-state and transient performance. We investigate a continuum shape description which encapsulates most of the cases studied earlier in the literature. The continuum has a straight frontal and dorsal faces with varying lengths, and side faces described by surfaces of different curvatures. The optimization study reveals that a curved-trapezoidal bluff body with the highest side surface curvature and frontal-to-dorsal ratio is the perfect shape for steady flow conditions. On the other hand, a square profile with the highest side surface curvature is the ideal choice for highly-fluctuating flow conditions because of its shortest rise time. The theoretical findings are replicated experimentally using wind tunnel tests.

Abstract Purpose To present the long-term results of redo-hypospadias at our tertiary referral center following a failed prior repair. Methods One hundred sixty-four individuals with a history of unsuccessful repairs qualified for our retrospective cohort study. Our inclusion criteria were as follows: pre-operative data that was accessible, redo-hypospadias that was successfully repaired, and at least three years of follow-up at the last hospital visit. Results The mean patient age was 91.3 ± 21.1 months. The mean follow-up after successful repair was 41.3 ± 3.1 months. Ninety-two (group A) had one prior repair, and 72 (group B) had 2 or 3 repairs. Group A underwent six primary techniques: 32 underwent Onlay Island Flap (OIF), 10 underwent Mathieu, 12 underwent Tubularized Incised Plate Urethroplasty (TIPU), 8 underwent Urethral Mobilization (UM), and 34 underwent Buccal Mucosal Graft (BMG) { dorsal inlay Graft Urethroplasty (DIGU) in 4 and staged BMG in 30 patients}. In group B, four procedures were used: TIPU in 4, UM in 6, and BMG in 62 (staged BMG in 50 cases and DIGU in 12). Conclusions The selected type of repair will depend on many factors, like residual healthy local skin and expertise. Safe techniques for repair of redo hypospadias after its 1st failure include TIPU, Mathieu, UM, OIF, and DIGU for distal varieties. After 2nd or 3rd repair DIGU, UM, and TIPU can be performed in distal types, while staged BMG can be applied for proximal ones.

Abstract Background This study aimed to evaluate the safety and efficacy of the endovascular deconstructive artery technique in the treatment of dissecting posterior cerebral artery (PCA) aneurysms (P1 and P2 segments). We retrospectively analyzed the angiographic characteristics, technical data, and clinical outcomes of nine consecutive patients with dissecting PCA aneurysms treated by our team using the endovascular deconstructive technique between January 2019 and December 2022. The patients consisted of six males and three females ranging in age from 36 to 63 years (mean: 48.1 ± 9). Four patients had a P1 segment dissecting aneurysm, and five patients had a P2 segment dissecting aneurysm. Five patients presented with a headache, one patient presented with epilepsy and headache, and three patients presented with subarachnoid hemorrhage. Results A balloon occlusion test (BOT) was performed for one patient. Eight patients were treated by parent artery occlusion (PAO) using micro-coils, whereas one patient was treated by occluding the P2 segment dissecting aneurysm using NBCA glue. There were no cortical infarctions following the occlusion of the parent artery. Two patients with P1 occlusion experienced post-procedural small thalamic infarctions that resolved to mRs:1 at three months of follow-up. P2 segment occlusion was asymptomatic in all patients. One patient showed partial aneurysmal recurrence. Conclusions Endovascular parent artery occlusion is an effective and safe treatment approach for the dissecting aneurysms of PCA, even without an occlusion test. In addition, the risk of perforator infarction must be considered in P1 occlusion. Level of evidence Level 4, Case Series.

Photovoltaic (PV) systems are prone to partial shading (PS) due to the environmental factors that they function in such as vegetation, nearby structures, and clouds. All types of PS scenarios can lead to power loss and hot spots in the PV system due to module mismatch and heating of shaded cells. To mitigate the power loss that occurs due to PS, it is imperative to detect PS and its characteristics, such as the number of shaded modules and the associated shading factor (SF), in a reliable manner. This paper proposes a three-step framework to detect and locate PS, the number of shaded modules, and the SF in the PV system using a random forest (RF)-based approach. The proposed approach utilizes independent string current and voltage measurements to distinguish different PS scenarios. This approach allows for a scalable data acquisition through an uncoupled modeling scheme. PS, the number of shaded modules and the SF are deduced with accuracies of 99.5%, 92.3%, 90.2%, respectively. Further, the proposed approach is validated through two testing tiers, and its ability to detect multiple PS scenarios in a PV system has been highlighted. The results observed through different PS scenarios confirm the high reliability and demonstrate the effectiveness and scalability of the proposed RF-based approach.

Lung and colon cancers are deadly diseases that can develop concurrently in organs and undesirably affect human life in some special cases. The detection of these cancers from histopathological images poses a complex challenge in medical diagnostics. Advanced image processing techniques, including deep learning algorithms, offer a solution by analyzing intricate patterns and structures in histopathological slides. The integration of artificial intelligence in histopathological analysis not only improves the proficiency of cancer detection but also holds the potential to increase prognostic assessments, eventually contributing to effective treatment strategies for patients with lung and colon cancers. This manuscript presents an Improved Water Strider Algorithm with Convolutional Autoencoder for Lung and Colon Cancer Detection (IWSACAE-LCCD) on HIs. The major aim of the IWSACAE-LCCD technique aims to detect lung and colon cancer. For noise removal process, median filtering (MF) approach can be used. Besides, deep convolutional neural network based MobileNetv2 model can be applied as a feature extractor with IWSA based hyperparameter optimizer. Finally, convolutional autoencoder (CAE) model can be applied to detect the presence of lung and colon cancer. To enhance the detection results of the IWSACAE-LCCD technique, a series of simulations were performed. The obtained results highlighted that the IWSACAE-LCCD technique outperforms other approaches in terms of different measures.

Mice are laboratory models used for evaluating anesthetic drugs; the combination of more than one drug to achieve general anesthesia was very common; orphenadrine considered as a special remedy because of its multiple pharmacodynamics properties in variant pathways and is use mainly as a muscle relaxant to treat muscle pain and muscle spasm. The purpose of our research was to appraise the effect of concomitant administration of orphenadrine and ketamine on the quality of general anesthesia in male albino mice. Male mice were used to assess the combination of orphenadrine and ketamine at the onset of anesthesia, duration, and recovery, as well as the presence or absence of notable reflex responses and the analgesic action of a mixture of ketamine and orphenadrine was evaluated by determining the median effective dose by using the up and down method in the tail immersion test. The combination of orphenadrine and ketamine formed a significant decrease in the onset of anesthesia compared with ketamine alone, a significant rise in the duration of anesthesia, and a significant decrease in the recovery time compared with ketamine alone; this mixture led to the disappearance of almost all reflex responses, which that presence in mice anesthetized, with ketamine alone. Our results showed a synergistic analgesic effect when orphenadrine and ketamine were administered together, depending on the calculated value of Y. We demonstrated the possibility of using orphenadrine as an alternative to xylazine when administered with ketamine to induce general anesthesia, and the analgesic action was synergistic when a combination of ketamine and orphenadrine was administered. Therefore, these results open new horizons for the use of orphenadrine in the field of anesthesia. Therefore, we recommended conducting more studies on this topic.

Orphenadrine is an anticholinergic drug used in clinics as a muscle relaxant. It acts on several receptors, including muscarinic, histaminic, and NMDA. This study aimed to evaluate the effect of pretreatment with orphenadrine on the anesthesia indices of two essential parenteral anesthetic drugs in mice. Three experiments were performed with 15 mice per experiment. All experiments used orphenadrine at 10 mg and 20 mg/kg/IP b.wt as a pretreatment drug. Propofol (100 mg/kg/IP), thiopental (50 mg/kg/IP), and their combinations were used in the first, second, and third experiments, respectively. The indices of anesthesia, represented by the latency to onset of anesthesia, duration of anesthesia, and recovery from anesthesia, were recorded. Orphenadrine at doses of 10 mg and 20 mg/kg/IP as a pretreatment drug showed a dose-dependent decrease in the latency to the onset of anesthesia and an increase in the duration of anesthesia compared to the control groups of all three experiments (propofol 100 mg/kg, thiopental 50 mg/kg, and combinations of propofol and thiopental) respectively. We conclude that orphenadrine affects anesthesia indices, which are recorded for the first time, laying the foundation for further studies and the possibility of using it as an anesthesia co-treatment.

2-Indolinone nucleus is considered one of a promising heterocyclic core in medicinal chemistry that showed numerous range of activity among which antimicrobial, antioxidant, antiviral, antitubercular and anticancer activities. Cancer targeting is still an issue so there is a need for developing new agents that inhibit cancer growth without or low effect on normal body cells. Some derivatives of indolin-2-one are known to be a critical structure in some inhibitors of receptor tyrosine kinases (RTKs); a cancer target therapy, for example, Sunitinib. Herein in this review we focus on 2-indolinone derivatives as RTKs inhibitors as cancer targeting therapy.

Most researchers have turned during the past period to study local history because of its importance and influence on the history of contemporary Iraq. The subject of the Al-Duleim brigade's acting commanders in the royal era is considered one of the important subjects that have not been studied previously and through which the personalities who reached the position of the acting commanders during the royal era, who were mostly from outside the brigadeMost researchers have turned during the past period to study local history because of its importance and influence on the history of contemporary Iraq. The subject of the Al-Duleim brigade's acting commanders in the royal era is considered one of the important subjects that have not been studied previously and through which the personalities who reached the position of the acting commanders during the royal era, who were mostly from outside the brigade

Abstract Metamaterial absorbers have diverse applications in the terahertz range. In this paper, a metallic metamaterial absorber is designed to work as a narrowband, wideband, or ultrawideband according to application. A systematic method with minimal computational requirements for the design is developed. The method is efficient since the only information required is the operating frequency and required bandwidth. A condition for zero reflection which ensures matching with free space is derived. The proposed design method is used for the design of narrowband, wideband, and ultrawideband absorbers. For each case the design parameters are different. The narrow bandwidth is less than 5%, while the wide band lies between 5 and 20%, and the ultrawideband is larger than 20%. The dimensions of the designed structure and material properties (εr″) are different for each case. The designed absorber is wide-angle and polarization-independent. The sensitivity of the designed material due to changes of physical dimensions and permittivity is studied. To validate results, reflectivity and absorptivity are calculated using CST package. The dimensions obtained from the developed method are a bit modified using trial and error. The results from the developed method and CST are in excellent agreement.

Abstract Background We compare the outcome of microsurgical subinguinal varicocelectomy (MSV) using the pulling technique (P-MSV) compared to the standard technique (S-MSV). Methods A total of 60 patients were diagnosed with varicocele compounded with infertility and/or scrotal pain not responding to medical treatment. Twenty-nine patients were randomized to the P-MSV, while 31 were randomized to S-MSV. The number of ligated veins was counted intraoperative and compared. Follow-up was done at 1 and 3 months including clinical examination, scrotal duplex ultrasound scan, and semen analysis. Results A total of 85 sides were operated upon, 43 (50.5%) were done by the P-MSV technique while 42 (49.5%) were done by the S-MSV technique. The median gained cord length after using the P-MSV was [3 cm; IQR 2–5 cm]. For the P-MSV technique, the mean number of detected internal spermatic veins after cord pulling was (4 ± 1.3 SD) compared to (6 ± 1.4 SD) before pulling (P value

Abstract The potential dry reforming of methane technology allows for the synthesis of syngas from methane and carbon dioxide. Numerous investigations have been conducted on developing catalysts with exceptional activity and stability. Carbon deposition causes severe deactivation in typical nickel‐based catalysts, which is one of the most prevalent and important problems. In this study, methane was dry‐reformed over 5 wt.% Ni+xSr‐9La+Zr (x = 0–4 wt.%) catalysts for 7.5 h at 700°C and ambient pressure in a tubular fixed‐bed reactor. According to the weight percent of Sr loading, the features of the material's texture, morphology, and catalysis were investigated. N2‐physisorption, H2‐temperature programmed reduction, X‐ray diffraction, Raman, and TEM were used to evaluate the physicochemical characteristics of the catalysts. N2‐physisorption research revealed that changing the weight percentage loading of the Sr promoter had little effect on the textural qualities. The overall number of reducible NiO‐interacting species over the catalyst surface increased with increasing Sr loading. The 5Ni+2Sr‐9La+Zr catalyst exhibited the optimum CH4 and CO2 conversions of 62.9%–65.9% and 69.1%–70.3%, respectively, and the lowest deactivation factor of 4.7.

الملخص: أهداف البحث: هدفت هذه الدراسة إلى استكشاف وتحليل الملامح الوبائية ورصد واستجابة كوفيد-19، وديناميكيات انتقالها وتشكل المجموعات. طرق البحث: تحليل استرجاعي لبيانات الرصد، بما في ذلك تتبع الاتصال، وعوامل الخطر، والمعلومات السريرية. أجريت تحليلات الانحدار اللوجستية الثنائية لتقييم احتمالات القبول، وتشكل المجموعات، وكونه حالة رئيسية. تم توضيح المجموعات باستخدام أنظمة البيانات الجغرافية وتحليل الشبكات وبرامج التصور. النتائج: تم تشخيص ١١٠٠ حالة إصابة بفيروس كوفيد-١٩ في الفترة من ٢٠ مارس إلى ٧ يونيو ٢٠٢٠، وكانت ١٤٤ حالة منها (١٣,١٪) بدون أعراض. كانت المدة المتوسطة من بدء الأعراض حتى القبول في المستشفى ٧ أيام (٤,٥ - ١٠)، ومدة الأعراض نفسها كانت ٥ أيام (٣ - ٩). تم تحديد 89 مجموعة تحتوي على ٧٣٦ مريضا. وتم تمييز ثلاث مراحل توضح إجراءات الرصد والسيطرة. بدأت المجموعات في المرحلة الثانية وزادت وضوحا في المرحلة الثالثة. المرضى الذين تجاوزوا سن ٥٠ عاما وأولئك الذين يعانون من الحمى لديهم فرصة أكبر للقبول في المستشفى، بنسبة ١٢,٨٥ (٩٥٪ م.م. ٥,١٣ – ٣٢,١٩) و ٢,٥٣ (٩٥٪ م.م. ١,٢٤ – ٥,١٧) على التوالي. وقد لوحظ تشكل المجموعات بين الإناث والمرضى الذين لم يظهروا أعراضا وبين سكان ولاية عوابي، بنسب ٢,٣ (٩٥٪ م.م. ١,٧ – ٣,١) و ٦,٣٩ (٩٥٪ م.م. ٢,٣٣ – ١٧,٢) و ٣,٥٤ (٩٥٪ م.م. ٢,٠٦ – ٦,٠٧) على التوالي. وكان لدى المرضى العاملين في قطاعات الشرطة والدفاع فرصة أعلى لكونهم حالة رئيسية، بنسبة ٧,٨٨ (٩٥٪ م.م. ٣,٣٥ – ١٨,٥٢). الاستنتاجات: يجب دعم التدخلات القائمة على الحالات من خلال التدابير الموسعة على مستوى السكان - خاصة قيود الحركة. يعد إنشاء فرق الوقاية أو وحدات المنطقة، أو من خلال الرعاية الأولية أمرا حاسما للسيطرة على الأوبئة المستقبلية. يجب أن تكون الوقاية دائما أولوية للفئات السكانية الضعيفة. Abstract: Objectives: This study was aimed at exploring and analyzing the epidemiological profile, surveillance, and response to COVID-19, including transmission dynamics and cluster formation. Methodology: This was a retrospective analysis of surveillance data, including contact tracing, risk factors, and clinical information. Binary logistic regressions were used to assess the likelihood of admission, cluster formation, and of each individual being an index patient. Clusters were demonstrated through geographic data systems, network analysis, and visualization software. Results: A total of 1100 COVID-19 cases were diagnosed from 20 March to 7 June 2020, of which 144 (13.1%) were asymptomatic. The median time from symptom onset to admission was 7 days (IQR, 4.5–10), and the median symptom duration was 5 days (IQR, 3–9). Eighty-nine clusters containing 736 patients were identified. The surveillance and control actions were divided into three phases. Clusters began to form in phase 2 and became more pronounced in phase 3. Patients ≥50 years of age and patients presenting with fever had relatively higher odds of admission: OR = 12.85 (95% CI 5.13–32.19) and 2.53 (95% CI 1.24–5.17), respectively. Cluster formation was observed among females, asymptomatic patients, and people living in Awabi: OR = 2.3 (95% CI 1.7–3.1), 6.39 (95% CI 2.33–17.2), and 3.54 (95% CI 2.06–6.07), respectively. Patients working in the police and defense sectors had higher odds of being an index patient: OR = 7.88 (95% CI 3.35–18.52). Conclusion: Case-based interventions should be supported by population-wide measures, particularly movement restrictions. Establishing prevention teams or district units, or primary care will be crucial for the control of future pandemics. Prevention should always be prioritized for vulnerable populations.

Hepatic lipidosis (HL) is a serious metabolic disorder that affects transient high-producing dairy cows. However, there are many laboratory methods could help in the assessment of HL in dairy cows, the definite diagnosis of the disease under field conditions remains a challenge because of the non-specificity of clinical parameters. The aim of the study was to investigate the utility of serum biomarkers, and ultrasonography (US) measurement to diagnose HL in dairy cows. Forty Holstein dairy cows underwent physical examination and were divided into three groups: non-HL, mild HL, and severe HL groups based on US findings, and the concentrations of beta-hydroxybutyric acid (BHBA) and nonesterified fatty acids (NEFAs). Ultrasound images showed hyperechoic lesions and increased pixel intensity (PI) values of liver echotexture in the HL groups. A significant increase was observed in mild and severe HL groups in the activity of serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT), BHBA, NEFAs, malondialdehyde (MDA), and nitric oxide (NO) while the concentrations of triglyceride (TG), glutathione (GSH), and total antioxidant capacity (TAC) were significantly decreased. The classification accuracy was in the interest of NEFAs (cut off 0.62 mmol/L, sensitivity 82.6%, specificity 91.7%, and an AUC of 0.913) and BHBA (cut off 1.35 mmol/L, sensitivity 91.31%, specificity of 86.4%, and an AUC 0.812) as important diagnostic parameters. This study offers new insights into the importance of serum biochemical parameters and oxidative stress biomarkers especially, AST, NEFAs, BHBA, and GSH with the digital values of US images for prompt use of minimally invasive techniques to diagnose HL under farm conditions.HIGHLIGHTS Serum metabolites and oxidative stress indices could diagnose hepatic lipidosis in dairy cows NEFA and BHBA concentrations and ultrasound digital values can use as a non-invasive way to the classification of hepatic lipidosis degrees in cows under farm condition.

Aim: To assess the feasibility of video game-based trunk exercises using the Valedo® system in a chronic stroke population. Method: Ten chronic stroke survivors (eight males and two females, mean age 63 ± 15 years) were asked to complete 18 intervention sessions, each lasting 45 min., over 6–8 weeks. Feasibility was evaluated quantitatively using the Psychosocial Impact of Assistive Devices Scale (PIADS) as well as through recruitment, retention, adherence, and safety measures. Qualitative data on feasibility were collected through post-intervention semi-structured interviews. Descriptive analysis was used to summarize participant characteristics, recruitment, retention, and adherence. Qualitative data were analyzed using thematic analysis of the interviews. Results: Twelve stroke survivors were recruited from Southampton (United Kingdom) and Riyadh (Kingdom of Saudi Arabia), with two participants dropping out after the baseline assessment session. The remaining ten participants completed the study with a mean adherence of 96.11% to the planned sessions. No serious adverse effects were reported, however, four participants did experience trunk muscle tightness and fatigue. Post-intervention interviews revealed that participants encountered some physical and cognitive challenges while playing the Valedo video games. However, they felt that the implementation of trunk exercises using video games was safe, as the exercises were performed in a secure environment and in safe positions. Conclusions: The findings suggest that the Valedo system is feasible for delivering trunk exercises to chronic stroke survivors. Several factors should be considered when implementing this type of intervention in the future.

Carbon dots (CDs) derived from mandarin peel biochar (MBC) at different pyrolysis temperatures (200, 400, 600, and 800 °C) have been synthesized and characterized. This high-value transformation of waste materials into fluorescent nanoprobes for environmental monitoring represents a step forward towards a circular economy. In this itinerary, CDs produced via one-pot hydrothermal synthesis were utilized for the detection of copper (II) ions. The study looked at the spectroscopic features of biochar-derived CDs. The selectivity of CDs obtained from biochar following carbonization at 400 °C (MBC400-CDs towards various heavy metal ions resulted in considerable fluorescence quenching with copper (II) ions, showcasing their potential as selective detectors. Transmission electron microscopic (TEM) analysis validated the MBC-CDs’ consistent spherical shape, with a particle size of 0/F ratio, with the best ratio obtained with a pH of 10, for 10 min, and an aqueous reaction medium. Cu (II) was detected over a dynamic range of 4.9–197.5 μM and limit of detection (LOD) of 0.01 μM. Validation testing proved the accuracy and precision for evaluating tap and mountain waters with great selectivity and no interference from coexisting metal ions.

This research aims to support the goals of Oman Vision 2040 by reducing the dependency on non-renewable energy resources and increasing the utilization of the national natural renewable energy resources. Selecting appropriate energy storage systems (ESSs) will play a key role in achieving this vision by enabling a greater integration of solar and other renewable energy. ESSs allow for solar power generated during daylight hours to be stored for use during peak demand periods. Additionally, the proposed framework provides guidance for large-scale ESS infrastructure planning and investments to support Oman’s renewable energy goals. As the global renewable energy market grows rapidly and Oman implements economic reforms, the ESS market is expected to flourish in Oman. In the near future, ESS is expected to contribute to lower electricity costs and enhance stability compared to traditional energy systems. While ESS technologies have been studied broadly, there is a lack of comprehensive analysis for optimal ESS selection tailored to Oman’s unique geographical, technical, and policy context. The main objective of this study is to provide a comprehensive evaluation of ESS options and identify the type(s) most suitable for integration with Oman’s national grid using a multi-criteria decision-making (MCDM) methodology. This study addresses this gap by applying the Hesitate Fuzzy Analytic Hierarchy Process (HF-AHP) and Hesitate Fuzzy VIKOR methods to assess alternative ESS technologies based on technical, economic, environmental, and social criteria specifically for Oman’s context. The analysis reveals pumped hydro energy storage (PHES) and compressed air energy storage (CAES) as the most appropriate solutions. The tailored selection framework aims to guide policy and infrastructure planning to determine investments for large-scale ESSs and provide a model for comprehensive ESS assessment in energy transition planning for countries with similar challenges.

Indole derivatives have become an important class of compounds in medicinal chemistry, recognized for their wide-ranging biological activities and therapeutic potential. This review provides a comprehensive overview of recent advances in the evaluation of indole-based compounds in the last five years, highlighting their roles in cancer treatment, infectious disease management, anti-inflammatory therapies, metabolic disorder interventions, and neurodegenerative disease management. Indole derivatives have shown significant efficacy in targeting diverse biological pathways, making them valuable scaffolds in designing new drugs. Notably, these compounds have demonstrated the ability to combat drug-resistant cancer cells and pathogens, a significant breakthrough in the field, and offer promising therapeutic options for chronic diseases such as diabetes and hypertension. By summarizing recent key findings and exploring the underlying biological mechanisms, this review underscores the potential of indole derivatives in addressing major healthcare challenges, thereby instilling hope and optimism in the field of modern medicine.

Background and Objectives: Our objectives were to examine the association between balance confidence, functional mobility measures, and the presence of disability in older adults in Saudi Arabia and to identify the optimal cutoff scores for these measures that predict disability. Materials and Methods: A cross-sectional study was conducted among 324 community-dwelling older adults (65 ± 7 years, 59% women). Disability was assessed using the Arabic version of the basic activities of daily living (ADLs) scale. Balance confidence was evaluated using the Arabic version of the Activities -Specific Balance Confidence (ABC) scale, and functional mobility was assessed using the 30-Second Chair Stand Test (30s-CST). Results: The prevalence of disability was 33.6% among the participants. Logistic regression revealed a 6% increase in disability odds for each one-unit decrease in the 30s-CST (OR: 0.94) and a 3% increase per one-point decrease in the ABC score (OR: 0.97). The optimal cutoff scores were ≤5 repetitions for the 30s-CST (sensitivity: 74.4%; specificity: 51.4%; AUC: 0.64) and ≤40 for the ABC scale (sensitivity: 80.8%; specificity: 61.4%; AUC: 0.75). Conclusions: Impaired balance and functional mobility are significantly associated with disability among older adults. The 30s-CST and the ABC scale can be used as effective screening tools, but the cross-sectional design of the current study limits its generalizability. Longitudinal research is needed to validate these findings.

In the original publication [...]

Smart contracts are programs that reside and execute on a blockchain, like any transaction. They are automatically executed when preprogrammed terms and conditions are met. Although the smart contract (SC) must be presented in the blockchain for the integrity of data and transactions stored within it, it is highly exposed to several vulnerabilities attackers exploit to access the data. In this paper, classification and detection of vulnerabilities targeting smart contracts are performed using deep learning algorithms over two datasets containing 12,253 smart contracts. These contracts are converted into RGB and Grayscale images and then inserted into Residual Network (ResNet50), Visual Geometry Group-19 (VGG19), Dense Convolutional Network (DenseNet201), k-nearest Neighbors (KNN), and Random Forest (RF) algorithms for binary and multi-label classification. A comprehensive analysis is conducted to detect and classify vulnerabilities using different performance metrics. The performance of these algorithms was outstanding, accurately classifying vulnerabilities with high F1 scores and accuracy rates. For binary classification, RF emerged in RGB images as the best algorithm based on the highest F1 score of 86.66% and accuracy of 86.66%. Moving on to multi-label classification, VGG19 stood out in RGB images as the standout algorithm, achieving an impressive accuracy of 89.14% and an F1 score of 85.87%. To the best of our knowledge, and according to the available literature, this study is the first to investigate binary classification of vulnerabilities targeting Ethereum smart contracts, and the experimental results of the proposed methodology for multi-label vulnerability classification outperform existing literature.

This paper presents a conductive component tailored to a flexible substrate using Al-doped CoxCa(0.90−x)Ni0.10Fe2O4 (x = 0.25, 0.50, and 0.75) for visible to near-infrared (NIR) spectra in magneto-optical applications. The developed nanoparticles show uniformity, nanosized grains, and capillary nanopore fusion characteristics, which are confirmed by x-ray diffraction (XRD), field emission scanning electron microscopy, and energy-dispersive x-ray spectroscopy analyses, respectively. The XRD analysis revealed crystallite sizes of 33.36, 37.08, and 44.25 nm and particle sizes of 45.6, 34.6, and 31.5 nm for the compositions x = 0.25, 0.50, and 0.75, respectively. The Al-doped nanoparticles are converted to a flexible solid substrate utilizing a polyvinyl alcohol matrix, facilitating conformality to build complex shapes and broadening their application scope. The structure shows higher absorption across 450–720 nm, 480–720 nm, and 200–850 nm spectra for x = 0.25, 0.50, and 0.75, respectively. The distinctive magnetic and electrical properties are also evaluated through magnetic force microscopy and conductive atomic force microscopy, culminating in a substrate with exceptional control over light–matter interactions with smooth surfaces with lower surface roughness. The vibrating sample magnetometer analysis of the substrate shows how varying cobalt content affects magnetic properties relevant for visible to near-infrared (NIR) applications, offering insights into coercivity, magnetization, and retentivity changes at different x values. The perceptible novelties of this work are advancements in material sciences aimed at enhancing light manipulation and flexibility for electronic devices.

The objective of this study was to explore a novel methodology for the synthesis of nanocoated probiotics following their collection and cultivation under optimized conditions, in light of their significant contribution to human health. Probiotics are instrumental in sustaining immune health by modulating the gastrointestinal microbiota and facilitating digestion. However, the equilibrium they maintain can be adversely affected by antibiotic treatments. It is critical to investigate the vulnerability of probiotics to antibiotics, considering the potential implications. This research aimed to assess whether nanoparticle coating could augment the probiotics' resistance to antibiotic influence. A strain of Lactococcus lactis (L. lactis) was isolated, cultured, and comprehensively characterized utilizing state-of-the-art methodologies, including the VITEK® 2 compact system, VITEK® MS, and 16S rRNA gene sequencing. The nanoparticle coating was performed using iron (III) chloride hexahydrate and tannic acid, followed by an evaluation of the probiotics' resistance to a range of antibiotics. The analysis through scanning electron microscopy (SEM) and atomic force microscopy (AFM) demonstrated a partial nanoparticle coating of the probiotics, which was further supported by UV/Vis spectroscopy findings, suggesting enhanced resistance to standard antibiotics. The results revealed that this strain possesses a unique protein profile and is genetically similar to strains identified in various other countries. Moreover, nano-encapsulation notably increased the strain's resistance to a spectrum of standard antibiotics, including Benzylpenicillin, Teicoplanin, Oxacillin, Vancomycin, Tetracycline, Rifampicin, Erythromycin, and Clindamycin. These findings imply that nanoparticle-coated probiotics may effectively counteract the detrimental effects of extended antibiotic therapy, thus preserving their viability and beneficial influence on gastrointestinal health.

Our objective in this paper is to investigate the sinh-Gordon equation’s generalization using a q-calculus. This equation explains systems with broken symmetries. The q-deformed sinh-Gordon equation adds noncommutativity and non-linearity, expanding on its original form. We compare two methods for solving this equation: RqDTM and VIM. RqDTM is a modified differential transform technique for q-deformed equations, whereas VIM utilizes an iterative approach. We give numerical results and compare the accuracy and efficiency of the solutions achieved using these approaches. This analysis evaluates the merits and disadvantages of each strategy for solving the q-deformed sinh-Gordon equation, offering insights into their applicability and performance.

Nitrate leaching from soil is a major environmental issue in modern agriculture as it can contaminate groundwater and degrade soil quality. Both nitrogen fertilization practices and irrigation methods contribute greatly to increased nitrate leaching. Researchers have developed quantitative models to predict nitrate leaching based on these farming techniques. This article examines new literature focusing on such models, particularly regarding salty soils used for maize cultivation. The study investigated the effects of nitrogen application rates and irrigation intervals on soil and groundwater properties in clay soils in Egypt. Results showed that nitrogen fertilization and irrigation frequency significantly impacted the water table depth, groundwater salt content, soil moisture levels, soil nitrogen availability, and groundwater nitrate levels. Correlations were discovered between nitrogen application, irrigation schedules, and various soil and groundwater parameters. The research emphasizes managing nitrogen rates and irrigation timings to maximize soil moisture while minimizing nitrate leaching during maize production. Proper agricultural management techniques are needed to reduce groundwater nitrate pollution risks. The review contributes to more sustainable farming practices.

Concrete Filled Tube (CFT) columns represent an effective alternative to conventional reinforced concrete columns. Recently, there have been trials to replace steel encasing tubes with Polyvinyl-Chloride (PVC) tubes for the enhancement of columns performance. The use of fibrous concrete as the core of such columns still needs more focus. In this study, glass fibrous concrete was used to fabricate PVC CFT (PCFT) short columns. PVC tubes thickness, tube roughness and lateral PVC supporting ties were the adopted parameters herein. These columns were tested in compression and their vertical and lateral deformations were monitored during loading. It was concluded that PCFT columns have generally shown higher axial capacity and ductility in comparison to concrete core. The best performance was related to PCFT columns with rough interface which showed axial capacity of about two thirds and ductility of about three folds higher than concrete core. Also, the use of lateral ties along the column height showed reasonable results, but the installation method of these ties needs to be modified to reach better results. Based on the experimental program, a design formula was deduced to predict short PCFT columns capacity with an error of about 8%.

Background: Drug hypersensitivity reactions (DHRs) are immune-mediated responses triggered by exposure to a drug. DHRs are responsible for serious adverse drug reactions (ADRs) and are considered the fifth leading cause of death. This study aims to assess and evaluate the knowledge, practice, and attitudes of healthcare providers (HCPs) towards DHRs. Methods: A cross-sectional survey was conducted at King Abdulaziz Medical City (KAMC) in Riyadh, Saudi Arabia. Healthcare providers, including pharmacists, physicians, and nurses, were recruited using a convenience sampling method to complete the survey. The survey comprised three domains: knowledge (14 items), attitudes (5 items), and practices (6 items), utilizing a standardized self-administered questionnaire. Results: The survey was completed by 373 healthcare providers. The respondents were predominantly female (72.1 %) with a mean age of 33.8 ± 7.8 years. Of the respondents, 64 % were nurses, 25 % pharmacists, and 11.3 % physicians. Educational levels varied, with 53 % holding a bachelor's degree, 22 % an associate degree, and 25 % a master's degree or higher. The median knowledge score was 48. Female healthcare providers, those with advanced levels of education, and physicians had higher knowledge scores compared to male and nurse participants (p