IEU GCRIS Database (İzmir Ekonomi Üniversitesi)
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Erratum: Publisher Correction: a Mixed-Method Study on Physicians' Perceptions of Pay for Performance: Impact on Professionalism, Morality and Work-Life Balance (BMC Health Services Research (2025) 25 1 Doi: 10.1186/S12913-024-12148-9)
No full textEasy Prestressing of FRP for Strengthening RC Beams: Experimental Study With an Analytical Approach
No full textThis study investigates strengthening reinforced concrete (RC) beams using fiber-reinforced polymers (FRPs). Nine samples were cast and strengthened with varying parameters, including the width, number of laminates, use of anchors, and application of prestressing. A novel device-the easy prestressing machine (EPM)-was developed to apply prestress. The EPM is lightweight and operable manually, enabling up to 10% prestressing. All specimens were tested under three-point bending until failure, and load-displacement curves were recorded. An analytical method based on curvature increment and incorporating material nonlinearities is also proposed to estimate the load-displacement response of RC beams with and without FRP strengthening. Both experimental and analytical results are presented and compared. The analytical model strongly agreed with the experimental results, showing Pearson correlation coefficients exceeding 90% for most specimens. According to the experimental findings, applying FRP, particularly when combined with anchorage and prestressing, increased the load-bearing capacity by up to 45%. Anchorage and prestressing effectively mitigate premature debonding, with prestressing showing a more pronounced impact on enhancing bond performance and load capacity. Based on the results, conclusions regarding the analytical model, structural behavior, and optimal strengthening strategies are discussed
Determining the Factors Affecting the Satisfaction of Patient in Sedoanalgesia Due To Distal Radius Fracture in Emergency Department
No full textIntroduction: Patients with distal radius fractures (DRF) are frequently admitted to the emergency departments (EDs). Reduction with procedural sedation and analgesia (PSA) and followed by plaster/splint are the treatment of choice. We aimed to determine the factors affecting the satisfaction in patients with DRF undergoing PSA. Methods: This prospective, observational, cross-sectional study included 70 patients with DRF. The socio-demographic features, comorbidities, level of satisfaction with PSA procedure, physical factors of the environment, physician and patient satisfaction were evaluated. PSA satisfaction scores "1, 2 and, 3" were grouped as "dissatisfied group" and "4-5" points as "satisfied group" with the Likert scale. Patient satisfaction was compared between the groups according to the satisfaction levels. Results: The median satisfaction level was found 4 (interquartile range 4-5). Their satisfaction with the given information about the PSA procedure and the cleanliness of the area where the procedure was performed was higher in the satisfied group than the dissatisfied group (p=0.014 and p=0.007, respectively). Also, as the level of residents of emergency physicians, the satisfaction of the patients increased (p=0.025). There was no significant difference between the groups in terms of age, gender, educational status, comorbidities, fracture type, additional injury, selected sedo-analgesic drugs, Richmond Agitation Sedation Scale and, complications (p>0.05). Satisfaction was high in all physicians. Conclusion: PSA procedure was satisfactory by a majority and can be performed safely in the ED. The residency period of the physician who performed the PSA, satisfaction with the given information about PSA and the cleanliness of the area were affecting the patient satisfaction
Prospective Follow-Up of Neurological Findings and Recovery Tımes in Covid-19 Patients
No full textThis study aimed to evaluate the type, frequency, onset, and recovery duration of neurological symptoms caused by COVID-19, including newly emerging post-COVID-19 neurological findings, to contribute to improved prognosis and follow-up strategies. A total of 110 COVID-19 patients hospitalized with positive SARS-CoV-2 PCR tests (24 December 2021-10 March 2022) were prospectively assessed. Neurological symptoms during hospitalization and at 1, 3, and 6 months post-discharge were documented, with all findings confirmed by a neurologist. The time of symptom onset was recorded for each patient. Fatigue (75.5%) was the most common symptom, lasting 10.43 weeks on average, followed by myalgia (57.3%, 4.29 weeks) and headache (56.4%, 3.35 weeks). Forgetfulness persisted the longest (22.03 weeks). Headache and myalgia were more frequent in women, while symptoms like dizziness, insomnia, and nausea/vomiting were more common in patients aged = 50. No significant differences in symptom duration were observed based on age or gender. Neurological symptoms, such as fatigue, headache, myalgia, and forgetfulness, were prevalent in both the acute and post-COVID-19 phases. The study underscores the importance of systematic neurological monitoring and the development of individualized follow-up strategies to manage long-term neurological effects and improve patient outcomes
A Reinforcement Learning Based Approach To Solve Voltage Issues in Distribution Networks
No full textAltera; EPRA Energy; et al.; IEEE Industrial Electronics Society (IES); IPEM Technologies; OPAL-RT TechnologiesThis paper proposes a Proximal Policy Optimization (PPO)-based reinforcement learning approach to solve overvoltage problem in power distribution networks. The approach aims to minimize the voltage deviations and to keep voltage magnitudes in the allowed ranges. The numerical simulations are performed on a modified unbalanced 123 node network. The modified test system includes a total number of 34 single phase Photovoltaics (200 kVA) connected to three phases. We modified the base case load profile based on real-world daily variations obtained from EPIAS. The PV generation profile was modeled according to a typical sunny day. Using OpenDSS and Python, we implemented PPO-based RL to optimize the setpoints of smart inverters and voltage regulators. The model was trained with load and solar profiles at 09:00, 12:00, and 16:00 to derive optimal voltage regulation strategies for these time points. From the simulation results, we observed that the proposed PPO-based RL approach significantly reduces voltage deviations across all phases, which may help efficient operation of the distribution networks. © 2025 IEEE
Nasal Septal Perforation in Adult Still's Disease
No full textBackground: Adult-onset Still's disease (AOSD) is a rare systemic inflammatory disorder characterized by fever, rash, arthritis, and pharyngitis. Ear, nose, and throat (ENT) complications beyond pharyngitis are uncommon. Case presentation: A 31-year-old female presented with fever, sore throat, maculopapular rash, and arthritis. Laboratory findings revealed elevated inflammatory markers, hyperferritinemia, and leukocytosis. After extensive exclusion of infectious and autoimmune causes, AOSD was diagnosed, and treatment with corticosteroids and methotrexate was initiated. Clinical symptoms improved within a week. However, one month later, the patient developed nasal bleeding and crusting. ENT examination revealed anterior nasal septal perforation. Known causes of septal perforation, including infection, trauma, intranasal drug use, and vasoconstrictor sprays, were excluded. Conclusion: This case highlights nasal septal perforation as a rare and possibly underrecognized complication of AOSD. Clinicians should consider ENT evaluation during both active disease and follow-up periods. © 2025 Société Française de Rhumatologi
Developing a Sustainable Traffic Management Framework Using Machine Learning Models for Fuel Consumption Minimization at Closely Spaced Intersections
No full textClosely spaced intersections can be specified as special types of intersections with short-distance characteristics that are generally located in urban areas. This study aimed to develop a sustainable transportation framework of machine learning algorithms to predict and minimize fuel consumption as a measure of environmental impact at closely spaced intersections. In the theoretical framework, this study incorporates key traffic parameters such as left-turn-lane length, cycle time, distance between intersections, left-turn movement ratio, and traffic volume fluctuations to model fuel consumption. In this context, different scenarios were modeled and compared with SIDRA Intersection (version 6.1), which is a well-known traffic analysis and intersection modeling software, by using partial least square regression (PLSR), polynomial support vector machine (PSVM), and artificial neural network (ANN) models to conduct a comparative analysis of their applicability. The results demonstrated that the ANN model best captured fuel consumption variations across different key influencing factors. Among all models, cycle time showed the highest sensitivity, highlighting its critical impact; the optimization of left-turn-lane length and cycle time is performed using Particle Swarm Optimization (PSO) to minimize the impact of left-turns on fuel consumption. These enhancements promote more efficient and environmentally friendly traffic management. The integration of the predictive and optimized PSO-ANN model establishes a foundation for optimizing intersection performance. The findings indicate that an overall improvement of 8.9% in fuel consumption is achieved by evaluating the optimized parameters under varying traffic volumes. The proposed framework supports sustainable signalized intersection management by improving fuel efficiency and reducing environmental impact. © 2025 by the authors
Life Cycle Assessment of White Meat Supply To Final Consumer: a Case Study From Türkiye
No full textThis study employs life cycle assessment (LCA) to analyze the environmental impact of white meat production in T ; uuml;rkiye, focusing on a major poultry producer. As far as the authors are concerned, it is the first ever study on the LCA of white meat production in the context of T ; uuml;rkiye. The LCA reveals significant environmental improvements compared to historical practices, with reductions of 75% in resource use, 36% in greenhouse gas emissions, 72% in land use, and 58% in water use. However, the analysis also identifies room for further progress, as the GWP score (4.21 kgCO2eq./kg chicken meat) remains slightly higher than the average reported in previous studies. To address this, the research proposes several strategies for the poultry industry, including sustainable feed production practices (reduced herbicide/pesticide use, renewable energy integration), optimized transport routes, and utilizing chicken waste for biofuel production. By implementing these strategies, the poultry sector can further minimize its environmental footprint. This research contributes to the understanding of the evolving environmental performance of the industry and offers practical approaches for achieving greater sustainability in white meat production
How Should Professional Psychiatric Associations Respond To a Large-Scale Disaster
No full textEsen, Emre Cem/0000-0003-4535-389X; Mutlu, Emre/0000-0001-6604-2105Disasters pose unique challenges, triggering significant psychological and social crises with both short- and long-term impacts. In this article, we address the critical role of professional psychiatric associations (PPAs) in responding to large-scale disasters, emphasizing the operational model connected with the Psychiatric Association of T ; uuml;rkiye's (PAT) response to the 2023 earthquakes in T ; uuml;rkiye and Northern Syria. We propose the SOLIDARITE model, a structured response framework, which incorporates sustained preparedness, organized networks, resource libraries, on-site and remote interventions, and comprehensive disaster planning across early, middle, and long-term phases. The model emphasizes a multidimensional approach integrating pre-disaster preparedness through training, various psychosocial support options, the establishment of networks, and the formulation of a master disaster response plan. The implementation of this model by PAT during the 2023 earthquakes facilitated an effective and prompt response, underlining the importance of PPAs' role in disaster preparedness and action. The SOLIDARITE model supports the need for deeper integration of disaster psychiatry into psychiatric training and calls for national and international collaboration to enhance the preparedness and response capacity of PPAs.The authors present their sincere gratitude to Disaster Preparedness and Intervention Unit, PAT Committees and Sections, and all members who made outstanding efforts through volunteer activities for the February 6, 2023, Earthquakes.PAT Committees and Section
Analysis of Inoculation Strategies During Covid-19 Pandemic With an Agent-Based Simulation Approach
No full textBackground: The severity of recent Coronavirus (COVID-19) pandemics has revealed the importance of development of inoculation strategies in case of limited vaccine availability. Authorities have implemented inoculation strategies based on perceived risk factors such as age and existence of other chronic health conditions for survivability from the disease. However, various other factors can be considered for identifying the preferred inoculation strategies depending on the vaccine availability and disease spread levels. This study explores the effectiveness of inoculating different groups of population in case of various vaccine availabilities and disease spread levels by means of some performance metrics namely: Attack Rate (AR), Death Rate (DR) and Hospitalization Rate (HR). Method: In this study we have implemented a highly detailed Agent-Based Simulation (ABS) model that extends classical SEIR Model by including five more additional states: Asymptomatic (A), Quarantine (Q), Hospitalized (H), Dead (D) and Immune (M) which can be used as a decision support tool to prioritize the groups of the population inoculated. The approach employs the modelling of daily mobility of individuals, their interactions and transmission of virus among individuals. The population is heterogeneously clustered according to age, family size, work status, transportation and leisure preferences with 17 different groups in order to find the most appropriate one to inoculate. Three different Disease Spread Levels (DSL) (low, mid, high) are experimented with four different Vaccine Available Percentages (VAP) (25%, 50%, 75% and 85%) with a total of 84 scenarios. Results: As the benchmark, under the No Vaccine case Attack Rate, Hospitalization Rate, and Death Rate goes as high as 99.53%, 16.96%, and 1.38%, respectively. Corresponding highest performance metrics (rates) are 72.33%, 15.95%, and 1.35% for VAP = 25%; 50.25%, 9.55%, and 0.94% for VAP = 50%; 24.53%, 2.62%, and 0.25% for VAP = 75%; and 11.51%, 0.002%, and 0.08% for VAP = 85%. The results of our study shows that the common practice of inoculation based on the age of individual does not yield the best outcome in terms of performance metrics across all DSL and VAP values. The groups containing workers and students that represent highly interactive individuals, i.e. Group (9, 10), Group (9, 11, 10‾) and Group (9, 10, 11, 12‾) emerge as a commonly recommended choice for inoculation in the majority of cases. As expected, we observe that the higher is the VAP levels the more is the number of alternative inoculation groups. Conclusions: Findings of this study present that: (i) inoculation considerably decreases the number of infected individuals, the number of deaths and the number of hospitalized individuals due to the disease, (ii) the best inoculation group/groups with respect to performance metrics varies depending on the vaccine availability percentages and disease spread levels, (iii) simultaneous implementation of both inoculation and precautions like lock-down, social distances and quarantines, yields a stronger impact on disease spread and its consequences. © 2024 Elsevier Lt