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Our study assesses the community-engaged research approach (CEnR) followed during the planning phase for a randomized controlled trial designed to assess how young adult Syrian refugees living in the Bekaa region of Lebanon implementing PM+ with adults in their community will be impacted themselves. We aim to describe the community-engaged research process implemented in our study, and the impact of community engagement on the process of adaptation of the intervention, and the design of the study. Methods: Community-engaged research (CEnR) was used to adapt this intervention to the context of the young adult Syrian refugee community in Lebanon by forming a community alliance committee (CAC). Twelve members from the Syrian refugee community in the Bekaa, Lebanon with different professional and socio-demographic characteristics who have lived experience or expertise related to mental health, education, health more generally, or young adults were invited to join a community alliance committee. Thematic analysis was conducted for two sources of data: (1) minutes of the CAC meetings; (2) in-depth interviews conducted with five CAC members. Findings demonstrate that community-engaged research increases rigor and relevance of the intervention and influenced outcomes, process, and context measures. Suggested modifications made by the CAC members enhanced the social and cultural relevance of the intervention, the measurement tools, and the study's approach. Conclusion: Our results showed that a CEnR process contributes to building trust with the community, creating a safe space for everyone to share their inputs, and when integrating those inputs into the adaptation of the intervention, results in a more contextualized intervention.

With the growing integration of IoT devices in critical infrastructure, cybersecurity threats such as Distributed Denial of Service (DDoS) attacks on Energy Hubs (EH) have become a significant concern. This study aims to address these challenges by evaluating the effectiveness of various supervised machine learning (ML) algorithms in predicting DDoS attacks targeting EH systems through IoT devices. Using the CICDDOS2019 and KDD-CUP datasets, a comprehensive analysis was conducted on several classifiers, including Decision Tree (DT), Gradient Boosting, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Random Forest. The results highlight Gradient Boosting as the most effective model, particularly for the CICDDOS2019 dataset, demonstrating superior accuracy and predictive capability. Additionally, hybrid models combining Gradient Boosting with SVM or DT showed strong performance, though with varying precision and recall. This study provides valuable insights into the selection and tailoring of ML models for specific security challenges, emphasizing the need for ongoing research to enhance the resilience of EH systems and IoT devices against evolving DDoS threats.

IntroductionThe COVID-19 pandemic had significant impacts on youth health and well-being. Youth with prior inequities, such as those exposed to child maltreatment, may have experienced greater psychosocial challenges and long-term difficulties than their peers, including sustained interpersonal relationships problems. Given the importance of healthy relationships during adolescence and early adulthood, the significant impact the pandemic had on youth, and the potential disproportionate challenges for youth with a child maltreatment history, the purpose of the present study was to better understand changes in relational conflict among youth with and without a child maltreatment history from the perspectives of youth themselves. Specifically, the aims were to examine if youth child maltreatment history was associated with an increased likelihood of reporting increased conflict with (a) parents, (b) siblings, or (c) intimate partners during the first three years of the COVID-19 pandemic.MethodsData were drawn from the Well-Being and Experiences (WE) Study; a longitudinal and intergenerational cohort study of 1,000 youth/parent dyads in Manitoba, Canada that began in 2017. WE study data were collected annually via self-reported youth surveys between 2017 and 2022 for a total of 5 waves of data collection, and COVID-19 questions were included in Waves 3 (2020), 4 (2021) and 5 (2022) (n = 586, 56.43% female, ages 18 to 21 at Wave 5). Multinomial regressions models were computed to examine whether a youth's child maltreatment history was associated with increased, decreased, or consistent levels of conflict with parents, siblings, and intimate partners in 2020, 2021, and 2022 compared to pre-pandemic levels.ResultsResults indicated that compared to youth with no child maltreatment history, youth with a child maltreatment history were more likely to report increased conflict across all three types of relationships during first three years of the pandemic.DiscussionFindings contribute to our understanding of the association between the COVID-19 pandemic and interpersonal relationships among youth who have a child maltreatment history compared to their peers without child maltreatment histories, signal potential long-term challenges or inequities for youth and families with a history of maltreatment, and may inform policy, programming, intervention, and recovery efforts in the post-COVID-19 period, and for future global emergencies.

The relationship between obesity and the conformational structure of hemoglobin (Hb) has not been extensively investigated. This study aims to elucidate the dielectric parameters that distinguish the Hb molecule under obese conditions and following treatment with goldenberry (GB) extract, compared to a control group. The dielectric parameters analyzed include the loss factor (D), relaxation time (τ), dielectric increment (Δε), relative permittivity (έ), dielectric loss (ε''), conductivity (σ), and Cole-Cole parameters (α), measured across a frequency range of 20 Hz to 3 MHz. Significant differences in dielectric parameters were observed between obese rats and those treated with GB extract. Obese rats exhibited higher dielectric values compared to the control group, while rats treated with low and high doses of GB extract showed marked changes in Hb conformational structure. This study highlights the potential of dielectric parameters as biophysical markers for detecting hemoglobin conformational changes. Furthermore, it suggests that dielectric behavior could serve as an early indicator for assessing the severity of obesity and its related complications.

ABSTRACT This study aimed to determine the antimicrobial effects of ethanolic extracts of Ulva sp. and garlic (Allium sativum) powder ethanolic extracts against Vibrio harveyi in vitro. The stimulatory effects of Ulva sp. extract (UE) and garlic powder extract (GPE) on the growth performance and innate immune responses of white‐leg shrimp, Litopenaeus vannamei, and their challenge against V. harveyi infection were also investigated. A commercial shrimp diet (36.1% protein) was enriched with 0.5, 1.0 and 2.0 g UE/kg diet and 2, 4 and 6 g GPE/kg diet, whereas the control group was free of any supplement. Health juveniles of L. vannamei (average weight 2–3 g) were distributed in 21 fiberglass reinforced plastic (FRP) tanks (500‐L capacity) at a stocking density of 300 animals/tank to represent each treatment in triplicate. The animals were fed ad libitum on the experimental diets up to satiety four times daily for 60 days. The phytochemical analysis of ethanolic extracts of Ulva sp. and garlic powder evoked their richness of several bioactive compounds showing significant antibacterial activity against V. harveyi. The GPE exhibited a higher inhibition zone than that of the UE. The supplemented diets did not significantly affect weight gain %, final weight, feed conversion ratio, specific growth rate and survival rates of white shrimp compared to those fed on the control diet. Significant increases were observed in total haemocyte count, phagocytosis and phagocytic index of all treatments compared with the control group. There were significant increases in serum total protein, acid phosphatase activity, alkaline phosphatase, lysosomal enzyme activity, phenoloxidase activity and superoxide dismutase activity with offered diets with increasing the levels of ethanolic extracts of Ulva sp. and garlic powder up to 2.0 g UE/kg diet and 6 g GPE/kg diet, respectively. The ethanolic extraction of Ulva sp. and garlic powder‐supplemented diet groups, particularly at treatments of 2.0 and 6 g GPE/kg diet, respectively, significantly reduced the shrimp mortality induced by V. harveyi infection when compared with the control group. The net results evoked that ethanolic extraction of Ulva sp. (2.0 g UE/kg) and garlic powder (6 g GPE/kg diet) enhanced the immune response and disease resistance of the white‐leg shrimp, L. vannamei. It is also noted that the GPE is more efficient than the UE in vitro and in vivo investigations.

The combination of energy hubs with advanced information and communication technology has resulted in the creation of an intelligent system referred to as a smart energy hub (SEH). The implementation of the SEH has facilitated the enhancement of the entire energy distribution system by enabling a two-way exchange of energy and information between utility providers and consumers. This has resulted in a system that is secure, efficient, and dependable. The significance and visibility of big data in the SEH are evident as a result of the growing accumulation of data quantities. A wide range of equipment and software work together to collect and use energy data. This includes tools used by both energy providers and customers, like smart meters, software for billing, and various monitoring and control systems. Additionally, sensors, computers, and communication networks play a crucial role in collecting and transmitting this data across the energy grid. Hence, big data plays a crucial role in the development of an enhanced SEH. This paper presents an introduction to the notion of SEH and its associated concepts, as well as the function of big data in the context of SEH. It also discusses the obstacles that big data encounters in the SEH domain and explores the potential opportunities that big data offers for SEH.

This study investigates a novel approach to improve energy efficiency through a Demand Response (DR) program with a Game Theory (GT)-based Time-of-Use (ToU) pricing model. While traditional DR programs encourage consumption shifts towards off-peak periods, they utilize a flat pricing structure. This means all users pay the same regardless of their individual load contribution during peak times, where prices fluctuate based on demand exceeding generation capacity. The proposed GT-based ToU model addresses this by establishing dynamic on-peak and shoulder-peak hour rates tailored to each user’s consumption profile. This personalized pricing incentivizes a more targeted shift away from peak hours, potentially leading to further efficiency gains. The model’s effectiveness is evaluated against the existing ToU system and the current day-ahead real-time pricing scheme. Additionally, the study acknowledges the potential for increased demand during off-peak hours due to load shifting. To address this, the influence of two optimization algorithms, Genetic Algorithm (GA) and Archimedes Optimization Algorithm (AOA), on user electricity bills and peak-to-average ratio following load scheduling is examined. The research concludes by demonstrating the superiority of the GT-based ToU model and highlighting AOA’s superior performance compared to GA in optimizing these factors.

ObjectivesA prevalent symptom of many mental health issues, such as depression, is anhedonia, which is the inability to feel joy or pleasure. Tension-induced sensations, anxious thoughts, and bodily alterations are the hallmarks of anxiety. One known environmental factor that affects mental health is diet. In this implication, eating appetizing meals has been proposed to reduce unpleasant feelings like worry. This study aimed to indicate whether eating habits among postgraduate students are related to symptoms of anhedonia and/or anxiety.MethodsIn a cross-sectional study, responses were collected from a total of 393 postgraduate students. Each student self-answered the General Anxiety Disorder-7, Snaith-Hamilton Pleasure Scale for Anhedonia, and the Food Consumption Questionnaire and reported the body weight.ResultsThe prevalence of anhedonia was 28%, moderate anxiety and severe anxiety were 15.7 and 10.9%, respectively. In this research, results showed that sugary foods, fast food, and fried foods were positively associated with anxiety and anhedonia. However, fruits and vegetables were negatively associated with anxiety and anhedonia. Linear regression showed that fruit and drinking water consumption was significant with the number of meals/day. There was no significance between the number of meals per day and anhedonia; however, there was statistical significance with the total GAD-7 scale score regarding the number of meals/per day.ConclusionAnhedonia and anxiety are associated with food consumption, especially foods rich in sugars, fast and fried, which help to increase positive feelings. Future studies should focus on understanding the relationship between food consumption and following a healthy diet and improving and reducing symptoms of anxiety and anhedonia in those who suffer from a stressful or task-filled lifestyle, such as students, especially postgraduate students. In addition, it focuses on the importance of awareness of the symptoms of anhedonia, which is classified as a depressive disease, and how to control anxiety to maintain better mental health.

Background: Post-COVID conditions (PCC), characterized by persistent symptoms following acute infection, represent an emerging chronic illness that potentially affects millions of people worldwide. SARS-CoV-2 infection has resulted in a PCC incidence ranging from 10 to 30 % in non-hospitalized individuals to 50–70 % in hospitalized patients. Most PCC patients experience mild symptoms, while a minority report severe manifestations. We aimed to estimate the prevalence of PCC among COVID-19 patients who attended three public hospitals in Alexandria, Egypt between June 2022 and February 2023, and to investigate its risk factors. Methods: All COVID-19-confirmed patients aged >18 years attended the selected hospitals, and their household contacts were contacted. Data were collected through telephone interviews using a questionnaire adapted from World Health Organization (WHO) and Penn Medicine tools, covering demographics, COVID-19 history, and PCC symptoms. PCC was defined as symptoms starting three months after the post-acute infection and lasting for at least two months beyond. Statistical analyses employed descriptive statistics, chi-square tests, and a logistic regression model, with a significance level of p

For a few decades, operators of energy systems have sought to achieve appropriate frameworks due to energy crises and rapid growth in energy requirements. In this regard, this study presents a multi-objective optimization model for an energy hub (EH) designed to manage a diverse energy portfolio. The EH receives electricity, natural gas, hydrogen, seawater, and solar energy as inputs, aiming to satisfy electricity, heating, and freshwater demands at the output port while considering a limited available area. The model incorporates the selection of the optimal solar energy technology (photovoltaics, parabolic dish, or parabolic trough collector) through a comprehensive evaluation encompassing technical, economic, and environmental aspects. To achieve optimal scheduling of the EH’s production units, the model factors in forecasts of solar energy availability alongside electrical, heat, and water load demands. The evaluation of the EH’s performance is conducted through a multi-objective framework considering social welfare, CO2 emissions, voltage stability margin (VSM), a newly proposed simplified fast temperature stability index (SFTSI), and a similarly novel simplified fast pressure stability index (SFPSI). The optimization problem is formulated within a MATLAB environment and solved using a multi-objective Archimedes optimization algorithm across five distinct case studies, each characterized by a varying designated area for solar energy generation. The effectiveness of the proposed model and optimization technique is validated through test systems, with the obtained results demonstrating significant improvements compared to a baseline scenario. These improvements include a 36.18% reduction in CO2 emissions, a 14.22% increase in total social welfare, and reductions in the average values of VSM, SFTSI, and SFPSI when incorporating all solar energy technologies.

Natural products have long been recognized as valuable sources of bioactive compounds in therapeutic agents. Thymus vulgaris, commonly known as thyme and belonging to the Lamiaceae family, is widely distributed and extensively used in Egyptian folk medicine for its antibroncholitic, antispasmodic, carminative, and diuretic properties. However, there is a lack of research on the effects of T. vulgaris seed extract in mitigating obesity-induced iron overload in rats. Given its potent bioactive constituents, this study aimed to investigate the impact of T. vulgaris seed extract on iron overload associated with obesity by evaluating lipid profiles, iron status parameters—including plasma ferritin, total iron-binding capacity (TIBC), plasma transferrin, transferrin saturation percentage (TS%), and hepcidin gene expression in adipose tissue. About 30 flavonoids were identified in T. vulgaris seed extract using LC-MS. Among these, methoxyflavonoids were the most abundant metabolites. The administration of T. vulgaris seed extract to obese rats resulted in significant reductions in anthropometric features, hepcidin gene expression, cholesterol, triglycerides, low-density lipoprotein (LDL), TIBC, plasma ferritin, leptin, and iron and copper content in adipose tissue. Moreover, treatment with T. vulgaris extract led to a notable decrease in interleukin-6 (IL-6) levels (76.33 ± 4.31 ng/L and 40.83 ± 1.82 ng/L for low and high doses, respectively) compared to the obese control group (110.83 ± 5.82 ng/L). Conversely, plasma adiponectin levels were significantly increased with T. vulgaris supplementation (123.6 ± 7.9 µg/L and 217.4 ± 6.1 µg/L for low and high doses, respectively) compared to the obese group (54.6 ± 4.9 µg/L). Additionally, adipose tissue zinc levels were significantly elevated in response to T. vulgaris supplementation (2.54 ± 0.20 µg/g and 3.75 ± 0.14 µg/g for low and high doses, respectively) compared to the obese group (1.45 ± 0.23 µg/g). Our findings suggest that T. vulgaris could be a promising novel therapeutic agent for managing obesity-induced iron overload.

This study aims to optimize an economic procedure to produce biogas and bio-ethanol from different organic wastes such as sewage sludge (SS) and/or cattle dung (CD) and/or poultry manure (PM). The experiment was carried out at a wastewater treatment plant in Egypt. Each waste type was mixed with the starter, CaCO3, and water then loaded in a fermenter and kept for 35 days at 35 °C under the anaerobic digestion. The evolved volume of the biogas and the content of methane CH4 were measured daily while the cellulase and protease enzymes were tested every four days. Results have indicated that the digester containing the SS has produced the greatest biogas volume (L) 27.45 Lb/D/d (liters biogas/digester/day), 0.61 Lb/D contents’ volume/d, and cumulative 606.30 Lb/D during the 16th day. Significant CH4 volume percentages produced during the 17th day were 72.07, 71.16, and 71.11% while the produced bio-ethanol alcohol was 2.47, 2.32, and 1.99% from the SS, CD, and PM, respectively. The procedure efficiency is prominent by the production of the biogases and in-situ activating enzymes all in one reactor that was periodically monitored for its reactants and product content. No need for the pre-treatment of wastes as raw materials or chemical additives and the fermented residue can be further tested for soil fertilization. These wastes can be promising for bio-energy production being economic and environment friendly.

Abstract Background Febrile neutropenia is a medical emergency and remains a significant cause of morbidity and mortality, it is defined as a temperature > 38.3 °C (101 °F), or a sustained temperature > 38.0 °C (100.4 °F) for more than 1 h in a neutropenic patient. Neutropenia is defined as a decrease in the absolute number of neutrophils in the blood

Abstract Background Despite their importance in reducing maternal mortality, information on access to Mifepristone, Misoprostol, and contraceptive medicines in the Eastern Mediterranean Region is limited. Methods A standardized assessment tool measuring access to Mifepristone, Misoprostol, and contraceptive medicines included in the WHO essential medicines list (EML) was implemented in eight countries in the Eastern Mediterranean Region (Afghanistan, Iraq, Lebanon, Libya, Morocco, Palestine, Pakistan, and Somalia) between 2020–2021. The assessment focused on five access measures: 1) the inclusion of medicines in national family planning guidelines; 2) inclusion of medicines in comprehensive abortion care guidelines; 3) inclusion of medicines on national essential medicines lists; 4) medicines registration; and 5) procurement and forecasting of Mifepristone, Misoprostol, and contraceptive medicines. A descriptive analysis of findings from these eight national assessments was conducted. Results Only Lebanon and Pakistan included all 12 contraceptives that are enlisted in the WHO-EML within their national family planning guidelines. Only Afghanistan and Lebanon included mifepristone and mifepristone-misoprostol combination in post-abortion care guidelines, but these medicines were not included in their national EMLs. Libya and Somalia lacked a national regulatory authority for medicines registration. Most contraceptives included on the national EMLs for Lebanon, Morocco and Pakistan were registered. Misoprostol was included on the EMLs—and registered—in six countries (Afghanistan, Iraq, Lebanon, Morocco, Palestine, and Pakistan). However, only three countries procured misoprostol (Iraq, Morocco, and Somalia). Conclusion These findings can guide efforts aimed at improving the availability of Mifepristone, Misoprostol, and contraceptive medicines in the Eastern Mediterranean Region. Opportunities include expanding national EMLs to include more options for Mifepristone, Misoprostol, and contraceptive medicines and strengthening the registration and procurement systems to ensure these medicines’ availability were permitted under national law and where culturally acceptable.

The present investigation aims to study the role of Pr2O3 on the structural, physical, and radiation shielding properties of a dense cadmium lead borate glass. The XRD was used to affirm the glassy amorphous structure of fabricated sample materials. Moreover, the FTIR was used to record the change in the FT-IR spectra due to the addition of Pr2O3 in the wavenumber interval between 400 and 4000 cm−1. The features of glass surfaces and the elemental analyses for the synthesized Pr2O3-reinforced cadmium lead borate glasses were performed using a SEM, supported by an energy-dispersive spectrometer. The γ-ray protection capacity was evaluated using the Monte Carlo method in a wide energy interval ranging between 0.015 and 15 MeV. The linear attenuation coefficient (LAC) at 1 MeV was reduced by a factor of 10 % from 0.372 cm−1 to 0.340 cm−1. The decrease in the LAC values negatively affected the other shielding properties such as half-value thickness and the transmission factor. Although the linear attenuation coefficient is decreased slightly with the partial substitution of CdO by Pr2O3 compound, the fabricated glass samples still have a high shielding capacity compared to the traditional commercial glasses as well as previous similar reported glasses.

The structural integrity of the skin, which acts as a barrier to keep harmful external substances out of the body, is compromised by wounds. The process of wound healing is a multifaceted and ever-changing phenomenon that entails the replacement of bodily tissues or damaged skin. It has been demonstrated that nanoparticles, especially silver nanoparticles, have anti-microbial and anti-inflammatory qualities that encourage cell migration and proliferation. Low level laser therapy has the potential to accelerate wound healing by stimulating cell regeneration after injury, reducing pain, and modulating the immune system. The aim of our study is to evaluate the healing process after treatment with silver nanoparticle and/or low level laser by measuring the serum levels of some pro-inflammatory cytokines (IL1b, IL6, and TNF-α), wound healing rate and histological analysis. Wounds were inflicted into 63 adult male albino mice (Mus musculus) and randomly divided into nine groups (7 per each). Control was left to normal healing. Other groups received a different treatment with laser, silver nanoparticle or both for 21 days. Injured skin was sampled for histopathological examination. Quantitative determination of TNFα, IL1 beta and IL6 were carried out using the sandwich enzyme-linked immunosorbent assay (ELISA) twice (day 2 and day 21). One-way and two-way analysis of variance (ANOVA) was used for statistical analysis. The results showed that the groups treated with silver nanoparticles and / or low-level laser promoted wound healing by reducing pro- inflammatory cytokines (IL1β, IL6 and TNFα) and showed significantly better wound closure with a significant reduction in wound size. At day 2 histopathological changes were very similar in different groups. When silver nanoparticles were applied, either alone or in combination with laser exposure, better granulation tissue and fibrosis also necrosis in the canter of the lesion and high score of re-epithelialization with less inflammation observed gradually till day 21. The results of this study suggested that silver nanoparticles and low-level laser have a wound healing potential, since topical treatment with silver nanoparticles and low-level leasers has effectively improved the wound healing process.

Abstract Background The biosynthesis of zinc oxide nanoparticles (ZnO NPs) using Enterobacter sp. and the evaluation of their antimicrobial and copper stress (Cu+ 2)-reducing capabilities in Vicia faba (L.) plants. The green-synthesized ZnO NPs were validated using X-ray powder diffraction (XRD); Fourier transformed infrared (FTIR), Ultraviolet-Visible spectroscopy (UV-Vis), Transmission electron microscope (TEM) and scanning electron microscopy (SEM) techniques. ZnO NPs could serve as an improved bactericidal agent for various biological applications. as well as these nanoparticles used in alleviating the hazardous effects of copper stress on the morphological and physiological traits of 21-day-old Vicia faba (L.) plants. Results The results revealed that different concentrations of ZnO NPs (250, 500, or 1000 mg L-1) significantly alleviated the toxic effects of copper stress (100 mM CuSO4) and increased the growth parameters, photosynthetic efficiency (Fv/Fm), and pigments (Chlorophyll a and b) contents in Cu-stressed Vicia faba (L.) seedlings. Furthermore, applying high concentration of ZnO NPs (1000 mg L-1) was the best dose in maintaining the levels of antioxidant enzymes (CAT, SOD, and POX), total soluble carbohydrates, total soluble proteins, phenolic and flavonoid in all Cu-stressed Vicia faba (L.) seedlings. Additionally, contents of Malondialdehyde (MDA) and hydrogen peroxide (H2O2) were significantly suppressed in response to high concentrations of ZnO NPs (1000 mg L-1) in all Cu-stressed Vicia faba (L.) seedlings. Also, it demonstrates strong antibacterial action (0.9 mg/ml) against various pathogenic microorganisms. Conclusions The ZnO NPs produced in this study demonstrated the potential to enhance plant detoxification and tolerance mechanisms, enabling plants to better cope with environmental stress. Furthermore, these nanoparticles could serve as an improved bactericidal agent for various biological applications.

Abstract Background Chronic kidney disease has a detrimental impact on the overall quality of life (QoL) in children. The regular visits to doctors, prolonged reliance on medication, frequent hospital stays, and changes in their physical appearance increase their vulnerability to developing psychiatric problems and hinder their daily activities and social interactions, resulting in isolation, poor peer relations, and low self-esteem. These factors may compel these children to depend on digital media to find connections, regulate emotions, and cope with their illnesses. The study aims to determine the prevalence of electronic addiction among minors undergoing regular hemodialysis for end-stage kidney disease (ESKD) while simultaneously assessing their parental styles and psychological adaptation. A total of 60 subjects were enrolled in the study and divided into two groups. Group A: Thirty patients undergoing regular hemodialysis for ESKD. Group B: Thirty healthy subjects of matching age and sex. All the recruited participants were subjected to semi-structured clinical interviews according to our institute’s sheets, Child Behavior Checklist (CBCL), Digital Addiction Scale for Children (DASC), Parent Authority Questionnaire (PAQ), and Psychological Adaptation Scale. Results Patients patients had a significantly higher prevalence of digital addiction compared to healthy subjects, with an average score of (87.00 ± 21.23) in dialysis patients against (53.00 ± 25.20) in normal participants, demonstrating significant differences (p< 0.001). There was a significant correlation between the duration of dialysis treatment and the prevalence of digital addiction (r = -0.415, p-value = 0.023). A significant inverse correlation was found between digital addiction and the emotional subtype of the psychological adaption rating (r= -0.375, p= 0.041). Conclusion The findings revealed that dialysis patients have a higher incidence of digital addiction. Prolonged dialysis duration was significantly associated with increased digital addiction among patients.

The Al–Zn–Mg–Cu 7055 aluminum alloy was meticulously fabricated through spray forming (SF) technology, followed by hot extrusion and T76 treatment. This comprehensive process allowed for a thorough investigation of its microstructural characteristics, mechanical properties, and fatigue behavior. Post-treatment analysis revealed that the SF-7055 aluminum alloy exhibited no notable segregation or porosity defects, ensuring its exceptional quality and reliability. The microstructural analysis revealed a uniform distribution of refined grains and dispersed precipitates, contributing to the material's strength. Mechanical testing demonstrated that the hot extruded SF-7055 aluminum alloy exhibits superior tensile strength and elongation, with significant anisotropy in mechanical properties favoring the extrusion direction (ED) over the transverse direction (TD). Fatigue testing under varying cyclic stresses revealed an extended fatigue life in the ED-oriented specimens, attributed to the texture-induced resistance to crack initiation and propagation. The study underscores the effectiveness of SF and hot extrusion in enhancing the SF-7055 aluminum alloy's performance, making it a viable candidate for critical aerospace applications. The findings provide valuable insights into the relationship between processing, microstructure, and properties, offering a pathway to the design and fabrication of high-performance aluminum alloys.