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Ali AlSahow,1 Bassam Bulbanat,2 Bassam Alhelal,3 Khaldoun Alhumoud,4 Ahmad Alkharaza,5 Torki Alotaibi,6 Heba Alrajab,7 Anas Alyousef,8 Fatimah Hadi9 1Nephrology division, Jahra Hospital, Al Jahra, Kuwait; 2Cardiac Center, Amiri Hospital, Kuwait City, Kuwait; 3Nephrology Division, Adan Hospital, Hadiya, Kuwait; 4Al salam International Hospital, Kuwait City, Kuwait; 5Cardiology Division, Adan Hospital, Hadiya, Kuwait; 6Hamad AlEssa Transplant Center, Ibn Sina Hospital, Kuwait City, Kuwait; 7Nephrology Division, Farwaniya Hospital, Sabah Al Nasser, Kuwait; 8Nephrology Division, Amiri Hospital, Kuwait City, Kuwait; 9Cardiology Division, Chest Diseases Hospital, Kuwait City, KuwaitCorrespondence: Ali AlSahow, Nephrology Division, Department of Medicine, Jahra Hospital, Bishr Bin Awana, Jahra, 00004, Kuwait, Email alsahow@hotmail.comIntroduction: Hyperkalemia is common in heart failure (HF) patients on renin angiotensin aldosterone inhibitors (RAASi), in chronic kidney disease (CKD), and in hemodialysis, and it negatively impacts their management. New potassium binders, such as sodium zirconium cyclosilicate (SZC), are effective in management of acute and chronic hyperkalemia. However, guidelines inconsistencies and lack of standardized treatment protocols are hindering proper and wider use of such agents. Therefore, an expert panel from Kuwait developed a consensus statement to address hyperkalemia management in acute settings, in HF, in CKD, and in hemodialysis.Methods: A three-step modified Delphi method was adopted to develop the present consensus, which consisted of two rounds of voting and in-between a virtual meeting. Twelve experts from Kuwait participated in this consensus. Statements were developed and shared with experts for voting. A meeting was held to discuss statements that did not reach consensus at the first round and then the remaining statements were shared for final voting.Results: The consensus consists of 44 statements involving an introduction to and the management of hyperkalemia in acute settings, HF, CKD, and hemodialysis. Thirty-six statements approved unanimously in the first vote. In the second vote, four statements were removed and four were approved after editing.Conclusion: Hyperkalemia management lacks standardized definitions, treatment thresholds and consistent guidelines and laboratory practices. This consensus is in response to lack of standardized treatment in the Arabian Gulf, and it aims to establish guidance on hyperkalemia management for healthcare practitioners in Kuwait and highlight future needs.Keywords: chronic kidney disease, heart failure, hemodialysis, hyperkalemia, potassium binders

Abstract Background The humanized monoclonal antibody galcanezumab is an anti-calcitonin-gene-related-peptide (CGRP) and frequently used for migraine prevention. However, the literature revealed limited data with conflicting results. This study aims to assess the safety and efficacy of galcanezumab in treating patients with episodic or chronic migraine. Methods We searched for randomized controlled trials till September 2022 from six databases (Cochrane library, Embase, PubMed, Web of Science, Scopus, and Clinicaltrials.gov registry). Our primary outcomes were the change in the number of monthly migraine headache days (MHDs) and adverse events. We extracted the data and analyzed it by RevMan (5.4) software. Results Eight studies with 4964 patients were included. Galcanezumab (≥ 120 mg) significantly reduced the MHDs for six months in migraine patients compared to placebo. The monthly risk ratio (RR) ranged from − 2.33 to − 1.62 for episodic migraine and − 2.86 to − 2.44 for chronic migraine. The response rate of ≥ 50%, ≥ 75% and 100% were higher with galcanezumab groups. The rate ranged from 1.72 to 4.19 for episodic migraine and 1.84 to 2.47 for chronic migraine. It is generally safe except for injection site safety outcomes (erythema, reaction, pruritis, and swelling), the results were significantly higher with galcanezumab groups. It appears dose independent except for injection site reaction, which showed higher with galcanezumab 120 mg only. Furthermore, any adverse events, serious adverse events (SAE) and that led to discontinuation were higher with galcanezumab 240 mg. Conclusion Galcanezumab is effective in patients with episodic or chronic migraine after one to six months use. It reduced MHDs and had an effective response rate. Moreover, it is generally safe except for injection site adverse events, and SAE, especially with galcanezumab 240mg.

Abstract There is insufficient research on bioaerosols in hospital waste decontamination stations. This study aimed to investigate the effect of three-layer and N95 masks in reducing the inhalation risk of bacterial bioaerosols in a waste decontamination station at a teaching hospital. Active sampling was conducted on five different days at three locations: the yard, resting room, and autoclave room in three different modes: without a mask, with a three-layer mask, and with an N95 mask. Bacterial bioaerosols passing through the masks were identified using biochemical tests and polymerase chain reaction (PCR). The median concentration and interquartile range (IQR) of bacterial bioaerosols was 217.093 (230.174) colony-forming units per cubic meter (CFU/m3), which is higher than the recommended amount by Pan American Health Organization (PAHO). The resting room had high contamination levels, with a median (IQR) of 321.9 (793.529) CFU/m3 of bacterial bioaerosols. The maximum concentration of bioaerosols was also recorded in the same room (2443.282 CFU/m3). The concentration of bacterial bioaerosols differed significantly between using a three-layer or N95 mask and not using a mask (p-value

The broad negative effects of land-use conversion for agriculture on wildlife species are well known, but few studies have evaluated how different land-use types impact spatiotemporal patterns and trophic strategy of large carnivores. We conducted sign surveys for the Asiatic black bear, a critically endangered subspecies in southeastern Iran. We applied Bayesian occupancy modelling and quantified spatiotemporal determinants of black bear occurrence as a function of date palms, distance to agriculture, elevation, precipitation, and protected area (PA) size. We also investigated its diet composition based on scat (n = 150) analyses. Date palm area size (β = 2.07; 95 % Credible Interval = 0.67 to 3.89) and distance to croplands had a strong and significant (β = −1.06, 95 % CrI = −2.10 to −0.20) influence on the occupancy. Elevation, precipitation, village density, and PA size did not substantially influence occupancy. Black bear detection probability became 100 % only above 14 km survey effort, indicating its overall rarity, and bears were much more easily detected during and after rainfall. Bears mainly relied on date palms (41 %) followed by herbaceous plants (24.6 %), insects (15 %), wild mammals (6.4 %), wild fruits (5.6 %), livestock (4.9 %) and other vertebrates (2.5 %, e.g., birds). Most of the predicted bear occupancy was outside PAs and thus suggests a high likelihood of human-bear conflicts. Presumably, resource density is insufficient to support bears inside PAs, but information concerning resource density is currently lacking. Our results showed that the agricultural landscape provided an important feeding (46 %) area for bears. Consequently, effective conservation programs such as the protection of abandoned date palm groves as a conflict-free food source are necessary. Practical training such as protective measures against crop-raiding behavior of bears would be essential to foster the tolerance of people toward bears and thus can help facilitate coexistence.

Abstract Background Latinx children in the United States experience disparities in asthma control and asthma-related functional outcomes compared to non-Latinx White children, including more school absences, emergency department visits, and hospitalizations for asthma. Stress appears to play a role in asthma control, but interventions designed to address the role of stress in asthma control for Latinx children are limited. Method The current randomized controlled trial tests the effects of Adapt 2 Asthma (A2A), a family-based coping skills and asthma management intervention tailored to the stressors, strengths, and cultural beliefs of Latinx families, compared to an asthma self-management control arm (the Asthma Plan for Kids; APK). Latinx families of children ages 8 to 14 years old with asthma (target N = 280) are identified and enrolled from primary care clinics and randomly assigned to either A2A or APK. The intervention is delivered by lay health workers trained and receiving ongoing consultation from the study team. The primary outcome is child- and parent-reported asthma control, while secondary outcomes are child’s quality of life, lung function, school absences, and emergency department visits, and child and parent coping and family asthma management behaviors. Participants will be assessed at baseline, post-intervention, and at 6- and 12-month follow-up timepoints. Discussion This study has the potential to provide new evidence regarding the effects of culturally relevant coping and asthma management intervention strategies for Latinx children with asthma. Trial Registration Clinicaltrials.gov NCT05118282 . Registered on 11 November 2021.

Abstract In contemporary floriculture, particularly within the cut flower industry, there is a burgeoning interest in innovative methodologies aimed at enhancing the aesthetic appeal and prolonging the postharvest longevity of floral specimens. Within this context, the application of nanotechnology, specifically the utilization of silicon and selenium nanoparticles, has emerged as a promising approach for augmenting the qualitative attributes and extending the vase life of cut roses. This study evaluated the impact of silicon dioxide (SiO2-NPs) and selenium nanoparticles (Se-NPs) in preservative solutions on the physio-chemical properties of ‘Black Magic’ roses. Preservative solutions were formulated with varying concentrations of SiO2-NPs (25 and 50 mg L−1) and Se-NPs (10 and 20 mg L−1), supplemented with a continuous treatment of 3% sucrose. Roses treated with 20 mg L−1 Se-NPs exhibited the lowest relative water loss, highest solution uptake, maximum photochemical performance of PSII (Fv/Fm), and elevated antioxidative enzyme activities. The upward trajectory of hydrogen peroxide (H2O2) and malondialdehyde (MDA) levels in petals was mitigated by different levels of SiO2 and Se-NPs, with the lowest H2O2 and MDA observed in preservatives containing 50 mg L−1 SiO2- and 20 mg L−1 Se-NPs at the 15th day, surpassing controls and other treatments. Extended vase life and a substantial enhancement in antioxidative capacity were noted under Se and Si nanoparticles in preservatives. The levels of total phenols, flavonoids, and anthocyanin increased during the vase period, particularly in the 50 and 20 mg L−1 Se-NPs and SiO2-NPs. Petal carbohydrate exhibited a declining trend throughout the longevity, with reductions of 8% and 66% observed in 20 mg L−1 Se-NPs and controls, respectively. The longest vase life was achieved with Se-NPs (20 mg L−1), followed by SiO2-NPs (50 mg L−1) up to 16.6 and 15th days, respectively. These findings highlight the significant potential of SiO2- and Se-NPs in enhancing the vase life and physiological qualities of ‘Black Magic’ roses, with SiO2-NPs showing broad-spectrum efficacy.

Abstract Identifying influential nodes is one of the basic issues in managing large social networks. Identifying influence nodes in social networks and other networks, including transportation, can be effective in applications such as identifying the sources of spreading rumors, making advertisements more effective, predicting traffic, predicting diseases, etc. Therefore, it will be important to identify these people and nodes in social networks from different aspects. In this article, a new method is presented to identify influential nodes in the social network. The proposed method utilizes the combination of users’ social characteristics and their reaction information to identify influential users. Since the identification of these users in the large social network is a complex process and requires high processing power and time, clustering and identifying communities have been used in the proposed method to reduce the complexity of the problem. In the proposed method, the structure of the social network is divided into its constituent communities and thus the problem of identifying influential nodes (in the entire network) turns into several problems of identifying an influential node (in each community). The suggested method for predicting the nodes first predicts the links that may be created in the future and then identifies the influential nodes based on an iterative strategy. The proposed algorithm uses the criteria of centrality and influence domain to identify this category of users and performs the identification process both at the community and network levels. The efficiency of the method has been evaluated using real databases and the results have been compared with previous works. The results demonstrate that the proposed method provides a more suitable performance in detecting the influential nodes and is superior in terms of accuracy, recall and processing time.

The mining process involves several sequential stages, including drilling, blasting, loading, transportation, and mineral processing. Among these stages, blasting costs (BC) exhibit greater sensitivity compared to others. Inadequate blasting practices can lead to additional drilling, increased explosive consumption, and environmental consequences such as ground vibrations. The variability in blasting patterns and ore rock hardness results in variations in BC. Consequently, there's a need for a method that can establish a relationship between design, geotechnical parameters, and blasting costs while accounting for uncertainties in input parameters. In this study, the rock engineering system method (RES) was employed to construct a complex and non-linear model for predicting blasting costs, considering uncertainties in geotechnical parameters. Data from six limestone mines in Iran were utilized, incorporating 146 data points. The input parameters used for creating this relationship included hole diameter, burden, Emulsion, hole number, hole length, spacing, stemming, sub-drilling, rock hardness, ANFO, number of electric detonators, unia­xial compressive strength, and specific gravity. The model was built using 80% of the data (117 data points) to establish the RES-based method, with the remaining 20% (29 data points) dedicated to evaluating and validating the model. To assess its performance, the RES-based method was compared to other statistical regression techniques, utilizing statistical indicators such as root mean square error (RMSE), mean square error (MSE), and coefficient of determination (R2). The results demonstrated that the RES-based method significantly outperformed other statistical approaches, with impressive accuracy, as indicated by MSE=0.00608, RMSE=0.078, and R2=0.9518 in predicting explosion costs. Therefore, the model developed through this method can be effectively applied in mining and rock mechanics projects, providing a high level of accuracy.

The present study aimed to investigate the influence of metacognitive beliefs on the relationship between the dark triad of personality and smartphone addiction among universities students. The research method was descriptive-correlational using structural equation modeling. The statistical population consisted of all universities students with the age range of 18-35 years in Tehran city in 2023. A sample of 457 students was selected using the voluntarily sampling method, and responded to the Dirty Dozen Scale, the Metacognitive Beliefs Questionnaire, and the Smartphone Addiction Scale. Pearson’s correlation method and structural equation modeling were used for the statistical data analysis. The results showed that the dark triad of personality had a positive and significant relationship with smartphone addiction, and metacognitive beliefs mediated this relationship significantly. The research findings emphasizing the importance of metacognition in conjunction with dark personality traits showed that metacognitive beliefs played a fundamental role in the tendency to become addicted to smartphones. Therefore, it is suggested that designing interventions based on metacognition should be considered in the treatment of smartphone addiction.

Abstract Background and objective(s) CRISPR-Cas is a prokaryotic adaptive immune system that protects bacteria and archaea against mobile genetic elements (MGEs) such as bacteriophages plasmids, and transposons. In this study, we aimed to assess the prevalence of the CRISPR-Cas systems and their association with antibiotic resistance in one of the most challenging bacterial pathogens, Klebsiella pneumoniae. Materials and methods A total of 105 K. pneumoniae isolates were collected from various clinical infections. Extended-spectrum β-lactamases (ESBLs) phenotypically were detected and the presence of ESBL, aminoglycoside-modifying enzymes (AME), and CRISPR-Cas system subtype genes were identified using PCR. Moreover, the diversity of the isolates was determined by enterobacterial repetitive intergenic consensus (ERIC)-PCR. Results Phenotypically, 41.9% (44/105) of the isolates were found to be ESBL producers. A significant inverse correlation existed between the subtype I-E CRISPR-Cas system’s presence and ESBL production in K. pneumoniae isolates. Additionally, the frequency of the ESBL genes bla CTX−M1 (3%), bla CTX−M9 (12.1%), bla SHV (51.5%), and bla TEM (33.3%), as well as some AME genes such as aac(3)-Iva (21.2%) and ant(2’’)-Ia (3%) was significantly lower in the isolates with the subtype I-E CRISPR-Cas system in comparison to CRISPR-negative isolates. There was a significant inverse correlation between the presence of ESBL and some AME genes with subtype I-E CRISPR-Cas system. Conclusion The presence of the subtype I-E CRISPR-Cas system was correlated with the antibiotic-resistant gene (ARGs). The isolates with subtype I-E CRISPR-Cas system had a lower frequency of ESBL genes and some AME genes than CRISPR-negative isolates.

Abstract Background Cancer patients are often treated with radiation, therefore increasing their exposure to high energy emissions. In such cases, medical errors may be threatening or fatal, inducing the need to innovate new methods for maximum reduction of irreversible events. Training is an efficient and methodical tool to subject professionals to the real world and heavily educate them on how to perform with minimal errors. An evolving technique for this is Serious Gaming that can fulfill this purpose, especially with the rise of COVID-19 and the shift to the online world, by realistic and visual simulations built to present engaging scenarios. This paper presents the first Serious Game for Lung Cancer Radiotherapy training that embodies Biomedical Engineering principles and clinical experience to create a realistic and precise platform for coherent training. Methods To develop the game, thorough 3D modeling, animation, and gaming fundamentals were utilized to represent the whole clinical process of treatment, along with the scores and progress of every player. The model’s goal is to output coherency and organization for students’ ease of use and progress tracking, and to provide a beneficial educational experience supplementary to the users’ training. It aims to also expand their knowledge and use of skills in critical cases where they must perform crucial decision-making and procedures on patients of different cases. Results At the end of this research, one of the accomplished goals consists of building a realistic model of the different equipment and tools accompanied with the radiotherapy process received by the patient on Maya 2018, including the true beam table, gantry, X-ray tube, CT Scanner, and so on. The serious game itself was then implemented on Unity Scenes with the built models to create a gamified authentic environment that incorporates the 5 main series of steps; Screening, Contouring, External Beam Planning, Plan Evaluation, Treatment, to simulate the practical workflow of an actual Oncology treatment delivery for lung cancer patients. Conclusion This serious game provides an educational and empirical space for training and practice that can be used by students, trainees, and professionals to expand their knowledge and skills in the aim of reducing potential errors.

ABSTRACT: Objectives: Plasmid genes, termed mobile colistin resistance-1 (mcr-1) and mobile colistin resistance-2 (mcr-2), are associated with resistance to colistin in Escherichia coli (E. coli). These mcr genes result in a range of protein modifications contributing to colistin resistance. This study aims to discern the proteomic characteristics of E. coli–carrying mcr-1 and mcr-2 genes. Furthermore, it evaluates the expression levels of various proteins under different conditions (with and without colistin). Methods: Plasmid extraction was performed using an alkaline lysis–based plasmid extraction kit, whereas polymerase chain reaction was used to detect the presence of mcr-1 and mcr-2 plasmids. The E. coli DH5α strain served as the competent cell for accepting and transforming mcr-1 and mcr-2 plasmids. We assessed proteomic alterations in the E. coli DH5α strain both with and without colistin in the growth medium. Proteomic data were analysed using mass spectrometry. Results: The findings revealed significant protein changes in the E. coli DH5α strain following cloning of mcr-1 and mcr-2 plasmids. Of the 20 proteins in the DH5α strain, expression in 8 was suppressed following transformation. In the presence of colistin in the culture medium, 39 new proteins were expressed following transformation with mcr-1 and mcr-2 plasmids. The proteins with altered expression play various roles. Conclusion: The results of this study highlight numerous protein alterations in E. coli resulting from mcr-1 and mcr-2–mediated resistance to colistin. This understanding can shed light on the resistance mechanism. Additionally, the proteomic variations observed in the presence and absence of colistin might indicate potential adverse effects of indiscriminate antibiotic exposure on treatment efficacy and heightened pathogenicity of microorganisms.

In this research, aligned with global policies aimed at reducing CO2 emissions from traditional power plants, we developed a holistic energy system utilizing solar, wind, and ocean thermal energy sources, tailored to regions optimal for ocean thermal energy conversion (OTEC). The selected site, characterized by favorable wind and solar conditions close to areas with high OTEC potential, is designed to meet the electricity needs of a coastal community. The system's core components include an Organic Rankine Cycle, turbines, thermoelectric elements, pumps, a heat exchanger, a wind turbine, and a solar collector. A detailed system analysis and thermodynamic evaluation based on thermodynamic principles were carried out using the Engineering Equation Solver (EES) software. Key factors such as wind speed, solar radiation, and collector area were critical in determining system performance. To enhance the system's effectiveness, we conducted a comprehensive comparison of optimization algorithms, incorporating the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and utilizing a Pareto front for value optimization. This approach significantly outperformed other algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Simulated Annealing (SA) in terms of system efficiency and cost-effectiveness. The developed system achieved an exergy efficiency of 14.46 % and a cost rate of $74.98 per hour, demonstrating its suitability for its intended functions. Moreover, exergoenvironmental evaluation was conducted for the proposed plant. The findings revealed that key component HEX has a high exergoenvironmental factor due to their use of hot water, which has zero unit exergoenvironmental impact. Additionally, pumps demonstrated a zero exergoenvironmental impact factor, indicating negligible component-related environmental impacts. Sensitivity analysis further evaluated critical performance parameters, revealing that increases in solar irradiation lead to decreased total system cost rates, while higher turbine temperatures resulted in a remarkable 14.08 % reduction in the system's cost rate. These results underscore the economic viability of operating the system at higher temperatures and strengthen the argument for its adoption from a financial perspective.

Shigella species significantly impact global health due to their role in diarrheal diseases. A 2019–2022 cross-sectional study on 432 stool samples from pediatric patients in Mashhad, Iran, identified Shigella spp. and tested their susceptibility to 12 antimicrobials by the disk diffusion method. The presence of virulence factors, namely ipaH, virA, stx1, and stx2, as well as plasmid-mediated quinolone resistance (PMQR) genes, including qnrA, qnrB, qnrC, qnrD, and qnrS, were ascertained through the utilization of polymerase chain reaction techniques. Sequencing of 15 isolates detected mutations within quinolone resistance-determining regions (QRDRs) at the gyrA and parC genes, indicating fluoroquinolone (FQ) resistance. 19.2 % (83/432) of stool samples contained Shigella, primarily S. sonnei (77.1 %), followed by S. flexneri (21.6 %) and S. boydii (1.2 %). Most isolates were from children under five (55.4 %). All strains had the ipaH gene, lacked stx1 and stx2, and 86.7 % had virA. High resistance was noted for ampicillin and tetracycline (84.3 % each), trimethoprim-sulfamethoxazole (81.9 %), and azithromycin (60.2 %). 87.1 % of isolates were multidrug-resistant (MDR). The most common PMQR genes were qnrA and qnrS (41 % each). The qnrD gene, prevalent in 36.1 % of cases, is reported in Iran for the first time. The most common PMQR profile was qnrADS (15.7 %). Resistance to nalidixic acid and ciprofloxacin was 45.8 % and 12 %, respectively. The Shigella isolates exhibited mutations in the gyrA (at codons 83, 87, and 211) and parC (at codons 80, 84, 93, 126, 128, 129, and 132) genes. The D87Y mutation in the gyrA gene was the most common in Shigella isolates, occurring in 73 % of cases. The F93S and L132T mutations in the parC gene were unique to this study. Empirical FQ therapy in patients infected with MDR Shigella, possessing PMQR determinants and/or mutations in the QRDRs of gyrA and parC, may escalate the risks of secondary diseases, extended treatment duration, therapeutic failure, and resistance spread. Consequently, the necessity for continuous surveillance and genetic testing to detect FQ-resistant Shigella strains is of paramount importance.

The emergence and development of antibiotic resistance in bacteria is a serious threat to global public health. Antibiotic resistance genes (ARGs) are often located on mobile genetic elements (MGEs). They can be transferred among bacteria by horizontal gene transfer (HGT), leading to the spread of drug-resistant strains and antibiotic treatment failure. CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated genes) is one of the many strategies bacteria have developed under long-term selection pressure to restrict the HGT. CRISPR-Cas systems exist in about half of bacterial genomes and play a significant role in limiting the spread of antibiotic resistance. On the other hand, bacteriophages and other MGEs encode a wide range of anti-CRISPR proteins (Acrs) to counteract the immunity of the CRISPR-Cas system. The Acrs could decrease the CRISPR-Cas system's activity against phages and facilitate the acquisition of ARGs and virulence traits for bacteria. This review aimed to assess the relationship between the CRISPR-Cas systems and Acrs with bacterial antibiotic resistance. We also highlighted the CRISPR technology and Acrs to control and prevent antibacterial resistance. The CRISPR-Cas system can target nucleic acid sequences with high accuracy and reliability; therefore, it has become a novel gene editing and gene therapy tool to prevent the spread of antibiotic resistance. CRISPR-based approaches may pave the way for developing smart antibiotics, which could eliminate multidrug-resistant (MDR) bacteria and distinguish between pathogenic and beneficial microorganisms. Additionally, the engineered anti-CRISPR gene-containing phages in combination with antibiotics could be used as a cutting-edge treatment approach to reduce antibiotic resistance.

Abstract Background The primary challenge in the cut flower industry, specifically in the postharvest phase, is the short vase life of flowers. This issue, along with early leaf yellowing and perianth abscission, significantly diminishes the economic value of flowers due to their accelerated senescence. To tackle this, we conducted a factorial experiment on Alstroemeria cv. Rebecca, utilizing a completely randomized design with three replications. In this experiment the effects of varying concentrations of Salicylic acid (SA) (0, 1.5, and 3 mM) and sucrose (SU) (0% and 3%) were investigated on the postharvest quality of leaves and florets, with systematic evaluations every three days throughout their vase life. Results This experiment revealed that the specific treatment combination of 1.5 mM SA + 3% SU (T5) markedly improved various parameters, such as vase life, total chlorophyll content, membrane stability index, relative fresh weight, and water uptake of cut flowers. In our analysis, we observed that this preservative solution not only extended the vase life and enhanced water uptake but also effectively preserved total chlorophyll, mitigated the loss of fresh weight, and reduced membrane deterioration in petals. Additionally, our results showed an increase in the activities of catalase (CAT) and peroxidase (POD) enzymes, as well as total protein content, alongside a decrease in malondialdehyde (MDA) and hydrogen peroxide (H2O2) levels. Moreover, this study noted a decrease in microbial populations in solutions containing different concentrations of salicylic acid. Conclusions Our research demonstrated that alstroemeria flowers maintained in a solution with 1.5 mM SA + 3% SU exhibited a significantly prolonged vase life of up to 21 days, in contrast to the 15 days observed in control flowers kept in water. These results are highly beneficial for manufacturers in the cut flower industry, as they provide a viable method to substantially extend the vase life of cut flowers. Such an enhancement in flower longevity can lead to increased market value and customer satisfaction. Furthermore, the reduction in flower senescence and decay rates can contribute to decreased waste and greater efficiency in cut flower distribution and sales, offering a substantial advantage to manufacturers in this competitive market. The extended vase life and reduced senescence observed in alstroemeria flowers treated with 1.5 mM SA and 3% SU are attributed to SA's role in enhancing endogenous defense responses and sucrose's function as an energy source, collectively improving water uptake, and delaying the natural decay process.

Aim and Background: One of the foremost challenges that women face in their lives is the issue of becoming a mother, which can influence their mental well-being. The present study aimed to Comparison of the Effectiveness of a Motherhood Role Acceptance Training Package with Group Positive Psychotherapy on the Social Competence of Married Women Childless. Methods and Materials: The research method was a quantitative and semi-experimental method with a pretest-posttest-follow-up design employed. Fifty-three women from the statistical population of all married women without children in Isfahan City who did not want to have children were selected by purposeful sampling and randomly assigned to two experimental groups and one control group. The experimental groups received a training package on the acceptance of the maternal role and positive psychotherapy. The participants were assessed using a social competence questionnaire. Findings: The findings indicate that the educational package of Motherhood Role Acceptance and positive psychotherapy both had an effect on the social competence of married women without children. However, based on the findings, the effectiveness of the training package Motherhood Role Acceptance was more than that of group-positive psychotherapy. Conclusions: The findings indicate that the educational package of Motherhood Role Acceptance and positive psychotherapy both had an effect on the social competence of married women without children. However, based on the findings, the effectiveness of the training package Motherhood Role Acceptance was more than that of group-positive psychotherapy.

This article, published in the Qatar Medical Journal, examines the characteristics and outcomes of intensive care unit (ICU) readmissions within the first year of lung transplantation. The study, conducted at a tertiary care center in Saudi Arabia, analyzed the electronic medical records of 20 adult patients who underwent lung transplantation and were readmitted to the ICU. The most common indication for transplantation in readmitted patients was chronic obstructive pulmonary disease (COPD), with pneumonia being the most common cause of readmission. The study found a mortality rate of 35% and identified the use of vasopressors and longer ICU stays as factors associated with higher mortality. [Extracted from the article]

This paper explores advanced machine learning approaches to enhance the prediction accuracy of compressive strength (CoS) in geopolymer composites (GePC). Geopolymers, as sustainable alternatives to Ordinary Portland Cement (OPC), offer significant environmental benefits by utilizing industrial by-products such as fly ash and ground granulated blast furnace slag (GGBS). The accurate prediction of their compressive strength is crucial for optimizing their mix design and reducing experimental efforts. We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). Using a comprehensive dataset derived from various scientific publications, we focus on key input variables including the fine aggregate, GGBS, fly ash, sodium hydroxide (NaOH) molarity, and others. Our results indicate that the SCA-RF model achieved a superior performance with a root mean square error (RMSE) of 1.562 and a coefficient of determination (R2) of 0.987, compared to the HHO-RF model, which obtained an RMSE of 1.742 and an R2 of 0.982. Both hybrid models significantly outperformed traditional methods, demonstrating their higher accuracy and reliability in predicting the compressive strength of GePC. This research underscores the potential of hybrid machine learning models in advancing sustainable construction materials through precise predictive modeling, paving the way for more environmentally friendly and efficient construction practices.