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Background: Nonsteroidal anti-inflammatory drugs (NSAIDs) and caffeine-containing beverages are widely consumed but their impact on gastrointestinal (GI) health requires further investigation. This cross-sectional study investigated the relationship between NSAIDs use, caffeinated drink consumption, and the prevalence of self-reported GI symptoms in a Jordanian subpopulation. Methods: An online survey was administered to 400 Jordanian individuals aged 18–65 years. Data on sociodemographics, NSAIDs use, caffeine consumption, peptic ulcer disease (PUD) history, and GI symptoms were collected. Contingency tables were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between exposures and outcomes. Results: The prevalence of self-reported PUD-related GI symptoms was 6.0%. NSAID users had higher odds of PUD (OR = 2.431) and related GI symptoms, including abdominal pain (OR = 4.688, p < 0.001) and discomfort (OR = 8.068, p < 0.001). Caffeine consumption was associated with self-reported burning stomach pain (OR = 14.104, p < 0.001), fullness (OR = 8.304, p = 0.010), and bloating (OR = 8.304, p = 0.010). Coffee, tea, soft drinks, and energy drinks were associated with increased odds of various GI symptoms (ORs 2.018-12.715, p < 0.05). Conclusions: NSAIDs use and caffeine consumption were independently associated with the increased prevalence of self-reported PUD and related GI symptoms. Despite the lack of adjustment for necessary confounders, our findings highlight the importance of considering the potential GI effects of NSAIDs and caffeine. Public health strategies promoting their safe use may help reduce the burden of GI disorders.

This research paper examines the digital infrastructure required to achieve project management success by analyzing the enabling elements of this digital infrastructure in terms of three pillars: digital readiness, digital fitness, and digital tools. A comprehensive literature review was conducted to identify these enabling elements and to develop a list of project management success indicators through which the success of project management can be measured. To evaluate and rank the digital infrastructure enabling elements, a Multi-Criteria Analysis (MCA) was implemented using a hybrid approach combining Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS). The study used the digital infrastructure enabling elements as MCA alternatives and the project management success indicators identified in the literature review as MCA criteria. The results indicated that the enabling elements associated with digital tools are the most significant for project management success, with a FTOPSIS closeness coefficient (CCi) of 0.8525, followed by those related to digital fitness (CCi = 0.6481) and digital readiness (CCi = 0.1602). These findings have proven to be robust, as they remained consistent even when weights of the MCA criteria were adjusted in three new scenarios proposed in a scenario analysis. This research highlights the critical role of digital enabling elements in enhancing project management practice and achieving project management success. It also offers a strategic framework for organizations to develop and strengthen their digital infrastructure.

The technique of multi-stage desalination with brine recirculation (MSF-BR) is characterized by its high energy demand, necessitating the exploration of efficient operational methods to minimize energy consumption and enhance plant performance. In this research study, Matlab R2021a software was used to apply a genetic algorithm with the aim of determining the optimal values of the operating variables of the MSF-BR system within certain limits, considering energy consumption and feed seawater temperature variation. The study included improving several operational factors, including top brine temperature, steam temperature, feed seawater temperature, cooling water flow rate and make up flow rate, number of station stages, and the stages of the heat rejection section. The optimal maintenance period during the operational year was also determined. The results of the analysis were based on data from the Al-Khafji desalination plant, which consists of 16 stages and has a production capacity of 7,053,393.8 gallons/day. The study aimed to achieve two main objectives: increasing the gain output ratio (GOR) and reducing the proportion of the recovery ratio. The results showed that the optimal period for maintenance is January, where the performance ratio ranges between 0.987 and 9.38, compared to the currently used month of December, where the performance ratio ranges between 1.096 and 9.56. Optimal target values were set at the following operating parameters: 33.3 °C for feed seawater temperature, 98.67 °C for steam temperature, 95.62 °C for brine temperature, 1571.18 kg/s for cooling water flow rate, 1624.24 kg/s for feed water flow rate, 21 stages for the station, and two stages for the heat rejection section. To achieve the highest GOR, the number of stages and heat rejection section should be more than 19 and 2, respectively. In general, to achieve improvements in GOR and reduce energy consumption, it is recommended to maintain Tf in the range of 33–34 °C and set Mcw between 1050 and 1800 kg/s.

Cholangiocarcinoma (CCA) is a hepatic malignancy that has a rapidly increasing incidence. CCA is anatomically classified into intrahepatic (iCCA) and extrahepatic (eCCA), which is further divided into perihilar (pCCA) and distal (dCCA) subtypes, with higher incidence rates in Asia. Despite its rarity, CCA has a low 5-year survival rate and remains the leading cause of primary liver tumor-related death over the past 10–20 years. The systemic therapy section discusses gemcitabine-based regimens as primary treatments, along with oxaliplatin-based options. Second-line therapy is limited but may include short-term infusional fluorouracil (FU) plus leucovorin (LV) and oxaliplatin. The adjuvant therapy section discusses approaches to improve overall survival (OS) post-surgery. However, only a minority of CCA patients qualify for surgical resection. In comparison to adjuvant therapies, neoadjuvant therapy for unresectable cases shows promise. Gemcitabine and cisplatin indicate potential benefits for patients awaiting liver transplantation. The addition of immunotherapies to chemotherapy in combination is discussed. Nivolumab and innovative approaches like CAR-T cells, TRBAs, and oncolytic viruses are explored. We aim in this review to provide a comprehensive report on the systemic and locoregional therapies for CCA.

The application of magnetic resonance imaging (MRI) in the classification of brain tumors is constrained by the complex and time-consuming characteristics of traditional diagnostics procedures, mainly because of the need for a thorough assessment across several regions. Nevertheless, advancements in deep learning (DL) have facilitated the development of an automated system that improves the identification and assessment of medical images, effectively addressing these difficulties. Convolutional neural networks (CNNs) have emerged as steadfast tools for image classification and visual perception. This study introduces an innovative approach that combines CNNs with a hybrid attention mechanism to classify primary brain tumors, including glioma, meningioma, pituitary, and no-tumor cases. The proposed algorithm was rigorously tested with benchmark data from well-documented sources in the literature. It was evaluated alongside established pre-trained models such as Xception, ResNet50V2, Densenet201, ResNet101V2, and DenseNet169. The performance metrics of the proposed method were remarkable, demonstrating classification accuracy of 98.33%, precision and recall of 98.30%, and F1-score of 98.20%. The experimental finding highlights the superior performance of the new approach in identifying the most frequent types of brain tumors. Furthermore, the method shows excellent generalization capabilities, making it an invaluable tool for healthcare in diagnosing brain conditions accurately and efficiently.

This paper provides an overview of the circular economy in Egypt. With the country facing significant environmental challenges, a circular economy approach can offer sustainable solutions to Egypt's environmental challenges by addressing issues like limited resources, waste generation, and a growing population in an eco-friendly and long-term perspective. This research employs a mixed-methods approach, including a literature review, surveys, and consultations with key stakeholders. The analysis reveals that although there are numerous challenges to establishing a circular economy in Egypt, such as limited understanding, insufficient government backing, and inadequate infrastructure, there are also opportunities, such as increasing demand for eco-friendly goods and services, as well as a receptive business environment. The paper recommends various policy and practical interventions to overcome these barriers and capitalize on these opportunities, including increasing awareness and understanding of the circular economy, developing supportive programs and regulations, investing in infrastructure and technology, and fostering stakeholder collaboration. This paper provides valuable insights into the potential for a circular economy in Egypt and the steps that can be taken to create a more sustainable future for the country. As such, it will interest policymakers, researchers, and practitioners working in the sustainability and environmental management field. The successful implementation of a circular economy in Egypt will require collective efforts from stakeholders to promote long-term sustainability and environmental stewardship.

Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lung infection has represented a global challenge. Intriguingly, it has been shown that the alveolar lung epithelium expresses little Angiotensin Converting Enzyme receptor protein (ACE2), the entry receptor for SARS-CoV-2. Upper airway establishment of infection and translocation to the lung is well documented but other anatomical niches may be relevant to potentially serious lung infection. ACE2 is heavily expressed in the gastrointestinal tract and gastrointestinal symptoms support a clinical diagnosis of Coronavirus disease 2019 (COVID-19). This suggests a research question and the need to gather patient data exploring potential aerodigestive links in SARS-CoV-2 tranlocation and infection which may be relevant in the peripheral lung. This recognizes anatomical proximity and concepts of bi-directional movement between the Gastrointestinal and lung systems in normal physiology and disease. We have therefore explored the potential for gastro oesophageal reflux disease (GORD) micro aspiration and aeorodigestive pathophysiology in a novel prospective investigation of patients hospitalized with COVID-19. Methods This is a prospective descriptive cohort study of 210 patients who were hospitalized with a confirmed diagnosis of COVID-19. The cohort was divided into three groups of patients based on symptom severity and radiological results. The Reflux Symptom Index (RSI) was used to evaluate the presence and severity of GOR. An RSI greater than 13 is considered to be abnormal. Patients’ saliva samples were tested using enzyme-linked immunosorbent assay (ELISA) to determine the level of salivary pepsin among the cohort of patients. Results A total of 210 patients with COVID-19 were enrolled in the study with 55.2% (116/210) classified as mildly ill, 31.9% (67/210) moderately ill and 12.9% (27/210) as severely ill. 34% (72/210) of the patients had an RSI score of over 13 and a median salivary pepsin value of 54 ± 29 ng/ml which suggested an incidence of extraesophageal reflux (EOR) in around a third of patients. The presence of respiratory comorbid conditions, an RSI score of over 13 and a salivary pepsin level of > 76ng/ml increased the risk of developing a more severe COVID-19 infection. Conclusion The study showed a high prevalence of EOR among the study cohort and provide the first prospective evidence suggesting the potential for aerodigestive pathophysiology including microaspiration in COVID-19 disease. We believe that the results of our study support the need for more extensive research.

Abstract This work presents the simple synthesis of a green and novel Palladium based magnetic nanocatalyst with effective catalytic properties and reusability. These heterogeneous catalysts were prepared by the anchoring of Pd(0) on the surface of ZrFe2O4 MNPs coated with a di-substituted adenine (Ade) compound as a green linker. The as-synthesized ZrFe2O4@SiO2@Ade-Pd MNPs were methodically characterized over different physicochemical measures like VSM, EDX, Map, SEM, TEM, ICP, and FT-IR analysis. The catalytic activity of ZrFe2O4@SiO2@Ade-Pd was carefully examined for the room-temperature Carbon–Carbon coupling reaction in acetonitrile as a solvent. It is worth noting that the synthesized solid catalyst can be easily recovered with a bar magnet and reused for five cycles without decrease of catalytic activity.

Abstract Recently, medical technologies have developed, and the diagnosis of diseases through medical images has become very important. Medical images often pass through the branches of the network from one end to the other. Hence, high‐level security is required. Problems arise due to unauthorized use of data in the image. One of the methods used to secure data in the image is encryption, which is one of the most effective techniques in this field. Confusion and diffusion are the two main steps addressed here. The contribution here is the adaptation of the deep neural network by the weight that has the highest impact on the output, whether it is an intermediate output or a semi‐final output in additional to a chaotic system that is not detectable using deep neural network algorithm. The colour and grayscale images were used in the proposed method by dividing the images according to the Region of Interest by the deep neural network algorithm. The algorithm was then used to generate random numbers to randomly create a chaotic system based on the replacement of columns and rows, and randomly distribute the pixels on the designated area. The proposed algorithm evaluated in several ways, and compared with the existing methods to prove the worth of the proposed method.