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Magnetic Resonance Imaging (MRI) is increasingly becoming a cornerstone in modern diagnostic healthcare, offering unparalleled capabilities in stroke, dementia, and cancer screening. Therefore, this study aims to map medical MRI literature affiliated with Arab countries, focusing on publication trends, top journals, author affiliations, study countries, and authors' collaboration, and keyword analysis. The scientific database used is the Scopus database. Microsoft Excel, VOSviewer software, and Biblioshiny for the Bibliometrix R package are the bibliometric tools used in this analysis. A total of 2592 publications were published between 1988 and 2022, with total citations of 22,115. Most of them were original articles (91,7%) and 89.9% were published in traditional journals. The number of total publications exhibited a steady increase over time, whereas total citations showed fluctuations, peaking in 2015 with 1571 citations for publications from that year. The most cited article was authored by Yaseen M. Arabi, receiving 286 citations. Saudi Arabia was the top active country. In addition, the most prolific author was Maha S Zaki, and the most prolific source was the “Egyptian Journal of Radiology and Nuclear Medicine”. The most prolific affiliation was Cairo University. The “multiple sclerosis” and “case report” were the most trending keywords. The analysis revealed a significant growth in MRI research inside Arab countries, as shown by an increase in the total number of publications and international collaborations. Despite these developments, the results of this study suggest that there is still room for MRI research in the Arab region to advance. This can be achieved through increasing international collaboration and multidisciplinary work.

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Fine control over the graphitization level of carbonized nanostructures can play a strategic role in tuning the crystallization of supported nanocatalysts, thereby modulating the kinetics of catalysis. However, realizing the synergistic interplay of graphitization‐tunable support and supported catalysts poses a significant challenge. This study proposes a current pulse‐induced ultrafast strategy for developing MOF‐derived graphitic nano‐leaves (GNL) and supported ultrafine ruthenium nanoclusters exhibiting selective crystallization states depending on the tunable graphitization level of GNL. The resulting ultrafine (≈0.7 nm) amorphous‐ruthenium nanoclusters linked with GNL (a‐Ru@GNL500) exhibit state‐of‐the‐art performance in the hydrogen evolution reaction (HER), requiring very low overpotentials of only 23.0 and 285.0 mV to achieve current densities of 10 and 500 mA cm−2, respectively. Furthermore, a‐Ru@GNL500 demonstrates exceptional operational stability for 100 h under high HER currents of 200 and 400 mA cm−2. Density functional theory reveals that the unique electronic structure of a‐Ru and the cooperative effect of cobalt embedded in the graphitic layer lower the occupancy of the antibonding orbital, resulting in an accelerated HER process. Additionally, the unique electronic structure, highly conducting GNL, and efficient bubble release dynamics of super‐aerophobic a‐Ru@GNL500 contribute to reduced overpotentials, particularly at high HER current densities. [ABSTRACT FROM AUTHOR]

The elevated level of carbon dioxide (CO2) in the troposphere is playing a crucial role in changing the earth's climatic system. Excess CO2 concentration is trapping a substantial proportion of heat imparting adverse range of environmental effects like extreme weather events, agricultural impacts and disruption of the ecosystem. Strategies such as CO2 capturing and storage are being pursued using polyoxometalates (POMs) to mitigate the elevated level of CO2 and their efficient conversion into useful chemicals. This review outlines the importance of CO2 reduction by electrocatalytic and photocatalytic reduction of CO2. POMs have several advantages for CO2 activation because of their promising catalytic activity, high selectivity and versatility for incorporating different metal ions and ligands. The efficient redox active metal center facilitates the conversion of CO2 by providing sufficient activation energy. Their robust structure also enables them resist harsh conditions, including high temperature and acidic or basic conditions. Owing to these properties, POMs can be a catalyst, co‐catalyst, photosensitizer or multielectron donor for CO2 reduction. Finally, we stated the challenges and future insight for CO2 activation using POMs. [ABSTRACT FROM AUTHOR]

Background: With the increasing amount of elective spine fusion patients presenting with cardiac disease and congestive heart failure, it is becoming difficult to assess when it is safe to proceed with surgery. Assessing the severity of heart failure (HF) through ejection fraction may provide insight into patients' short- and long-term risks. Purpose: The purpose of this study was to assess the severity of HF on perioperative outcomes of spine fusion surgery patients. Study Design/Setting: This was a retrospective cohort study of the PearlDiver database. Patient Sample: We enrolled 670,526 patients undergoing spine fusion surgery. Outcome Measures: Thirty-day and 90-day complication rates, discharge destination, length of stay (LOS), physician reimbursement, and hospital costs. Methods: Patients undergoing elective spine fusion surgery were isolated and stratified by preoperative HF with preserved ejection fraction (P-EF) or reduced ejection fraction (R-EF) (International Classification of Diseases-9: 428.32 [chronic diastolic HF] and 428.22 [chronic systolic HF]). Means comparison tests (Chi-squared and independent samples t-tests, as appropriate) compared differences in demographics, diagnoses, comorbidities, procedural characteristics, LOS, 30-day and 90-day complication outcomes, and total hospital charges between those diagnosed with P-EF and those not R-EF. Binary logistic regression assessed the odds of complication associated with HF, controlling for levels fused (odds ratio [OR] [95% confidence interval]). Statistical significance was set at P < 0.05. Results: Totally 670,526 elective spine fusion patients were included. Four thousand and seventy-seven were diagnosed with P-EF and 2758 R-EF. Overall, P-EF patients presented with higher rates of morbid obesity, chronic kidney disease, chronic obstructive pulmonary disease, diabetes mellitus, and hypertension (all P < 0.001). In relation to No-HF, P-EF patients had higher rates of 30-day major complications including pulmonary embolism, pneumonia, cerebrovascular accident (CVA), myocardial infarctions (MI), sepsis, and death (all P < 0.001). Furthermore, P-EF was associated significantly with increased odds of pneumonia (OR: 2.07 [1.64–2.56], P < 0.001) and sepsis (OR: 2.09 [1.62–2.66], P < 0.001). Relative to No-HF, R-EF was associated with significantly higher odds of MI (OR: 3.66 [2.34–5.47]), CVA (OR: 2.70 [1.67–4.15]), and pneumonia (OR: 1.85 [1.40–2.40]) (all P < 0.001) postoperative within 30 days. Adjusting for prior history of MI, CAD, and the presence of a pacemaker R-EF was a significant predictor of an MI 30 days postoperatively (OR: 2.2 [1.14–4.32], P = 0.021). Further adjusting for history of CABG or stent placement, R-EF was associated with higher odds of CVA (OR: 2.11 [1.09–4.19], P = 0.028) and MI (OR: 2.27 [1.20–4.43], P = 0.013). Conclusions: When evaluating the severity of HF before spine surgery, R-EF was associated with a higher risk of major complications, especially the occurrence of a myocardial infarction 30 days postoperatively. During preoperative risk assessment, congestive HF should be considered thoroughly when thinking of postoperative outcomes with emphasis on R-EF. [ABSTRACT FROM AUTHOR]

Study Design: Retrospective review of Kids' Inpatient Database (KID). Purpose: Identify the risks and complications associated with surgery in adolescents diagnosed with Chiari and scoliosis. Overview of Literature: Scoliosis is frequently associated with Chiari malformation (CM). More specifically, reports have been made about this association with CM type I in the absence of syrinx status. Methods: The KID was used to identify all pediatric inpatients with CM and scoliosis. The patients were stratified into three groups: those with concomitant CM and scoliosis (CMS group), those with only CM (CM group), and those with only scoliosis (Sc group). Multivariate logistic regressions were used to assess association between surgical characteristics and diagnosis with complication rate. Results: A total of 90,707 spine patients were identified (61.8% Sc, 37% CM, 1.2% CMS). Sc patients were older, had a higher invasiveness score, and higher Charlson comorbidity index (all p <0.001). CMS patients had significantly higher rates of surgical decompression (36.7%). Sc patients had significantly higher rates of fusions (35.3%) and osteotomies (1.2%, all p <0.001). Controlling for age and invasiveness, postoperative complications were significantly associated with spine fusion surgery for Sc patients (odds ratio [OR], 1.8; p <0.05). Specifically, posterior spinal fusion in the thoracolumbar region had a greater risk of complications (OR, 4.9) than an anterior approach (OR, 3.6; all p <0.001). CM patients had a significant risk of complications when an osteotomy was performed as part of their surgery (OR, 2.9) and if a spinal fusion was concurrently performed (OR, 1.8; all p <0.05). Patients in the CMS cohort were significantly likely to develop postoperative complications if they underwent a spinal fusion from both anterior (OR, 2.5) and posterior approach (OR, 2.7; all p <0.001). Conclusions: Having concurrent scoliosis and CM increases operative risk for fusion surgeries despite approach. Being independently inflicted with scoliosis or Chiari leads to increased complication rate when paired with thoracolumbar fusion and osteotomies; respectively. [ABSTRACT FROM AUTHOR]

The article proposes a new approach to maximum power point tracking (MPPT) for photovoltaic (PV) systems operating under partial shading conditions (PSCs) that improves upon the limitations of traditional methods in identifying the global maximum power (GMP), resulting in reduced system efficiency. The proposed approach uses a two-stage MPPT method that employs machine learning (ML) and terminal sliding mode control (TSMC). In the first stage, a neuro fuzzy network (NFN) is used to improve the accuracy of the reference voltage generation for MPPT, while in the second stage, a TSMC is used to track the MPP voltage using a non-inverting DC—DC buck-boost converter. The proposed method has been validated through numerical simulations and experiments, demonstrating significant enhancements in MPPT performance even under challenging scenarios. A comprehensive comparison study was conducted with two traditional MPPT algorithms, PID and P&O, which demonstrated the superiority of the proposed method in generating higher power and less control time. The proposed method generates the least power loss in both steady and dynamic states and exhibits an 8.2% higher average power and 60% less control time compared to traditional methods, indicating its superior performance. The proposed method was also found to perform well under real-world conditions and load variations, resulting in 56.1% less variability and only 2–3 W standard deviation at the GMPP. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study of Convolutional Neural Networks (CNN) and transfer learning in the context of medical imaging. Medical imaging plays a critical role in the diagnosis and treatment of diseases, and CNN-based models have demonstrated significant improvements in image analysis and classification tasks. Transfer learning, which involves reusing pre-trained CNN models, has also shown promise in addressing challenges related to small datasets and limited computational resources. This paper reviews the advantages of CNN and transfer learning in medical imaging, including improved accuracy, reduced time and resource requirements, and the ability to address class imbalances. It also discusses challenges, such as the need for large and diverse datasets, and the limited interpretability of deep learning models. What factors contribute to the success of these networks? How are they fashioned, exactly? What motivated them to build the structures that they did? Finally, the paper presents current and future research directions and opportunities, including the development of specialized architectures and the exploration of new modalities and applications for medical imaging using CNN and transfer learning techniques. Overall, the paper highlights the significant potential of CNN and transfer learning in the field of medical imaging, while also acknowledging the need for continued research and development to overcome existing challenges and limitations. [ABSTRACT FROM AUTHOR]

Introduction: Fluorouracil (5-FU) pharmacokinetics are variable, leading to a risk of toxicity in some patients and underdosing in others. Therapeutic drug monitoring of 5-FU was shown to reduce toxicity and increase efficacy. This study assessed the clinical utility of starting treatment with 70–80% of BSA calculated dose and titrating according to 5-FU blood levels and toxicity. Methods: A retrospective analysis of a prospectively collected database of 126 patients treated with regimens containing 5-FU bolus and continuous infusion for 46 h for whom the 5-FU blood level was collected at least once. Response,and date of progression, and death were collected for patients with colon and pancreatic cancer. Results: In multivariate analysis, 5-FU blood levels were correlated with 5-FU dose and with age, albeit a small effect size (coefficient = 0.007). Of patients with colon cancer treated with an initial lower 5-FU dose, 18% had a therapeutic 5-FU blood level. The median survival was similar in patients with metastatic colon cancer treated with lower doses and those treated with a full dose. Of patients with pancreatic cancer treated with lower doses, 40% had therapeutic blood levels. The median survival was 13 months in patients with metastatic pancreatic cancer treated with lower 5-FU doses. Conclusion: Starting treatment with low 5-FU dose was associated with patient survival comparable to other published data, and a sizeable percentage of patients had therapeutic blood levels. This approach can be considered, especially in elderly and frail patients. [ABSTRACT FROM AUTHOR]

The search for sustainability and green energy, in electricity production, has lead many researchers to study and improve photovoltaic (PV) systems. The PV systems, being a combination of power electronic modules and PV array, have high tendency of faults in sensors, switches, and passive devices. Thus, a reliable fault diagnosis (FD) scheme plays a significant role in protecting PV systems. In this article, a sliding mode observer (SMO)-based FD scheme is presented to figure out the sensor faults in a standalone PV system. The proposed FD scheme makes use of residual formation which in turn helps in detection of faults on the basis of a defined threshold. In addition to the functionality of fault detection, the SMO provides the benefit of reduction in number of sensors required in the PV system. This feature can be utilized as software redundancy in fault-tolerant control (FTC). The test bench, standalone PV system, is equipped with a buck–boost converter for maximum power transfer (MPT) to the connected load. Moreover, the FD scheme is backed by a back-stepping (BS) analogy-based control scheme for extraction of maximum power from the PV panel. The simulations are performed in the MATLAB/Simulink platform under varying environmental conditions (temperature and irradiance) and resistive load. These simulations, subjected to varying operating conditions, confirm the efficacy, in terms of robustness, chattering (oscillations about the reference), and steady-state error, of the proposed scheme. [ABSTRACT FROM AUTHOR]