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Continuous versus low-intensity interval aerobic exercise in pulmonary rehabilitation after COVID-19
No full textObjectives: This study aimed to compare the effectiveness of mild-moderate intensity continuous training (CT) and low-intensity interval moderate-intensity training (LIIT) aerobic exercises in pulmonary rehabilitation after coronavirus disease 2019 (COVID-19). Patients and methods: This prospective study was conducted between January 2021 and January 2022. Sixty-three patients (47 males, 16 females; mean age: 54.3±11.3 years; range, 25 to 81 years) with one or more residual symptoms following COVID-19 infections were randomly included in the CT (n=33) or LIIT (n=30) groups. Fifteen sessions (60 min, 3-5/week) of aerobic exercise (20-min 40% of peak workload for CT; 40% peak workload with 3-min loaded and 1-min nonloaded intervals for LIIT, with 5 min warm-up and cool-down), breathing, and upper extremity strengthening exercises were applied. Outcome measures were symptom-limited submaximal exercise test, and six-minute walk test (6MWT), the modified Medical Research Council (mMRC) dyspnea scale, modified Borg dyspnea scale, and Borg 6-20 rate of perceived exertion scale, hand grip strength, fat-free mass, Hospital Anxiety and Depression Scale (HADS), and 36-item Short-Form Health Survey. Results: The maximum load and time reached during the exercise test, the 6MWT distance, hand grip strength, mMRC, HADS, and SF-36 scores significantly improved in both groups (p0.05). The changes in mMRC, resting heart rate, and 6MWT distance were significantly higher in the LIIT group compared to the CT group (p<0.05). Conclusion: Both CT and LIIT improved functional capacity, dyspnea, tachycardia, depression, and quality of life measures safely and effectively in COVID-19 survivors with residual symptoms. Patients with poor clinical status who cannot tolerate CT after an acute pulmonary condition such as COVID-19 may benefit from LIIT. © 2025 Elsevier B.V., All rights reserved
Comparison of endobutton and tendon graft techniques in acromioclavicular joint dislocation: Early treatment yields better outcomes
No full textBackground:This study aims to compare the clinical outcomes of coracoclavicular fixation using the endobutton (EB) technique versus tendon grafts (TGs) and examine the impact of early surgical intervention on functional outcomes in patients with acute Rockwood type III, IV, and V acromioclavicular joint dislocations.Methods:This retrospective study encompasses 35 patients with acute Rockwood type III, IV, and V acromioclavicular joint dislocations who underwent coracoclavicular fixation surgery employing either the EB or hamstring TG techniques between January 2016 and January 2020. Patients were classified into 2 groups: the EB group and the TG group. Clinical outcomes were measured using the Visual Analog Scale (VAS), Disabilities of the Arm, Shoulder, and Hand questionnaire, and Constant score preoperatively and postoperatively.Results:The Constant-subjective and Meler scores of the EB group were significantly higher than those of the TG group. Postoperative EB group VAS scores were significantly lower than those of the TG group (P = .029). Furthermore, the Constant-objective scores of patients who underwent surgery within 3 weeks were significantly higher (P = .010). Additionally, the VAS scores of patients whose surgery occurred within 3 weeks were significantly lower than those of patients who had surgery after 3 weeks (P = .048).Conclusion:Early surgical treatment of acromioclavicular joint separation leads to higher Constant scores. Moreover, irrespective of the surgical technique, patients who underwent surgery within the first 3 weeks post-injury had lower VAS scores.Level of evidence:Level III, retrospective
Critical Node Detection for Enhanced Network Reliability: A Comparative Analysis Across Real-World Complex Networks
No full textIdentifying critical nodes in complex networks is crucial for assessing and improving the reliability and fault tolerance of systems across diverse domains, including communication, transportation, and infrastructure. While various critical node detection problems have been proposed, their practical implications for real-world reliability optimization still need to be explored. Most existing studies have focused on individual problems or specific types of networks, often lacking a comparative analysis across diverse real-world networks. This study conducts a comprehensive comparative analysis of three major problems: Maximizing the Number of Connected Components (MaxNum), Minimizing the size of the Largest Connected Component (MinMaxC), and the Critical Node Problem (CNP). Leveraging ten real-world networks from diverse domains, we investigate the similarities and differences between their optimal solution sets and evaluate how effectively common centrality metrics approximate them. Furthermore, a generalization of Isolating Centrality is proposed to overcome detected drawbacks. Our results reveal a high similarity (0.91) between the optimal node sets of MinMaxC and CNP, with PageRank centrality consistently showing strong alignment with these optimal critical node sets across a variety of network types. The study provides valuable insights for network reliability analysis, aiding the development of targeted strategies to enhance network stability and ensure reliable operation in crucial applications.TUBITAK (Scientific and Technical Research Council of Turkey) [121F092]This work was supported by the TUBITAK (Scientific and Technical Research Council of Turkey) under Grant 121F092
Evaluating the Accessibility, Usability, and Security of Corporate Investor Relations Web Pages: A Case Study of the Turkish Stock Market
No full textThis study investigates the accessibility, usability, and security of investor relations (IR) web pages of 53 companies listed on the Istanbul Stock Exchange (BIST), focusing on both BIST-30, representing the most liquid and highly capitalized companies, and BIST-2022, companies that had their initial public offerings (IPOs) in 2022. Using automated testing tools, the analysis examines adherence to the WCAG 2.1 guidelines, mobile responsiveness, and security measures. The findings reveal that accessibility issues, particularly related to the robust and perceivable principles, are prevalent across the assessed web pages, with BIST-30 companies showing a higher rate of errors. While BIST-2022 companies generally performed better in usability, with faster loading times and fewer broken links, security assessments indicated low to medium risks across both categories. This study contributes to the limited literature on the quality assessment of corporate IR web pages and highlights the necessity for enhancements in accessibility, usability and security, providing valuable insights for web administrators and developers to improve the quality of IR web pages
Q-öğrenme tabanlı bulanık C-ortalama yönlendirmeli hiper-sezgisel algoritma ile ısı eşanjörlerinin termo-ekonomik analizi
No full textBu çalışmada, mevcut araştırmalar üzerine inşa edilen yeni bir optimizasyon yaklaşımı geliştirmek amacıyla makine öğrenmesi temelleri ile meta-sezgisel algoritmalar bütünleştirilmiştir. Önerilen strateji, yerel arama işlemlerini özel optimizasyon ajanları aracılığıyla gerçekleştirmek için Bulanık C-Ortalamalar (Fuzzy C-means) kümeleme algoritmasını kullanırken, her iterasyonda en uygun optimizasyon algoritmasının seçilmesi için Q-öğrenme yönteminden yararlanmaktadır. Manta Ray Foraging Algorithm, African Vulture Algorithm ve Harris Hawks Optimization olmak üzere üç güncel meta-sezgisel algoritma, bu akıllı öğrenme teknikleriyle geliştirilerek çözüm doğruluğu ve dayanıklılığı artırılmıştır. Geliştirilen yöntem, CEC 2013 yarışmasından alınan zorlu test fonksiyonları üzerinde değerlendirilmiş; bu testler çok boyutlu, otuz boyutlu tek modlu, çok modlu ve birleşik benchmark problemlerini kapsamaktadır. Elde edilen sonuçlar, önerilen algoritmanın çoğu senaryoda güncel yöntemlere kıyasla daha başarılı olduğunu ve karmaşık problemlerin çözümünde yüksek etkinlik sağladığını ortaya koymaktadır. Ayrıca, çalışmada kabuk-boru tip ısı değiştirici tasarımında sıklıkla göz ardı edilen kritik bir konuya da değinilmiş; boru içi akışkanların genel verimlilik ve maliyet üzerindeki etkisi incelenmiştir. Altmıştan fazla soğutucu akışkanın değerlendirildiği çalışmada, toplam maliyeti minimize eden optimum konfigürasyonlar belirlenmiş ve NH? kullanılan sistemlerin, alternatif kurulumlara kıyasla en düşük toplam maliyeti sağladığı tespit edilmiştir.This study integrates machine learning fundamentals with metaheuristic optimizers to introduce a novel optimization approach that builds upon existing research. The proposed strategy employs the Fuzzy C-means clustering algorithm to facilitate local search operations through dedicated optimization agents, while Q-learning is utilized to select the most suitable optimization algorithm at each iteration. Three recent metaheuristic optimizers the Manta Ray Foraging Algorithm, African Vulture Algorithm, and Harris Hawks Optimization are enhanced using these intelligent learning techniques to improve both solution accuracy and robustness. The new method is evaluated using challenging test functions from the CEC 2013 competition, which span multidimensional, thirty-dimensional unimodal, multimodal, and composite benchmarks. When compared to state-of-the-art optimizers, the proposed algorithm outperforms its competitors in most scenarios, highlighting its effectiveness in tackling complex problems. Moreover, the study addresses a critical yet often overlooked aspect of shell-and-tube heat exchanger design: the impact of in-tube refrigerants on overall efficiency and cost. By assessing over sixty refrigerants, the research identifies the optimal configurations for minimizing total expenditure, finding that systems operating with NH? yield the lowest overall cost compared to alternative setups
The effect of treatment duration on the prognosis of adhd: a multi-center naturalistic follow-up study
No full textObjective: This study aimed to evaluate the effect of medication duration over a 5-year period on the prognosis of Attention-Deficit/ Hyperactivity Disorder (ADHD) and the accompanying disruptive behavioral symptoms using a naturalistic methodology. Methods: The sample comprised 576 ADHD cases referred to 16 Child and Adolescent Psychiatry Clinics in 13 cities in Türkiye, aged between 7–12 five years ago and 12–18 currently. Baseline and current Turgay DSM-IV Disruptive Behavior Disorders Rating Scale (T-DSM-IV-S) scores completed by parents were compared. Sociodemographic data, treatment processes, life events, and habits were recorded. Disorder severity and recovery levels were determined using the Clinical Global Impression Scale (CGI). Results: All current T-DSM-IV-S scores were significantly lower than the baseline scores. Longer duration of medication use, receiving psychotherapy, and higher socioeconomic status were associated with better CGI scores in the present study. However, increased baseline conduct disorder symptoms, being bullied, longer duration of Internet usage, dropping out of school, smoking, and older age were associated with worse CGI scores. Conclusion: Our study indicates that a longer duration of medication use is associated with better global improvement in children with ADHD. Better identification of the factors that may directly or indirectly affect the general improvement in ADHD cases and changing these factors may enable a more positive prognosis. © 2025 Elsevier B.V., All rights reserved
Line balancing and ergonomic improvement approach with avix analysis in a line manufacturing environment
No full textBu tezde gerçekleştirilen çalışma ile bir beyaz eşya işletmesindeki üretim hattında iş istasyonları arasındaki dengesiz iş dağılımlarını ve ergonomi problemlerini ortadan kaldırmak amaçlanmaktadır. Üretim hattındaki mevcut durum, Avix analizi ve Muri analizi kullanılarak değerlendirilmiş, iyileştirme planları oluşturulmuştur. Avix analizi, iş süreçlerini video tabanlı olarak analiz ederek iş yükü dağılımını optimize etmeyi sağlayan bir yöntemdir. Muri analizi ise çalışanların ergonomik olmayan hareketlerini ve aşırı yüklenme durumlarını tespit ederek risk seviyelerini azaltmayı hedefler. Yapılan iyileştirmeler sonucunda, üretim hattındaki istasyon sayısı 45'ten 35'e düşürülmüş, üretim kapasitesi ise vardiya başına 600 adetten 700 adede çıkarılmıştır. Ayrıca, kırmızı ergonomik riskli iş adımları 87'den 22'ye düşürülerek çalışanların fiziksel ve ruhsal sağlıklarında iyileşme sağlanmıştır. Malzeme besleme tipleri değiştirilmiş, operatör hareketleri optimize edilerek verimlilik artırılmıştır. Çalışma, yalın üretim metodolojisi ile ergonomik iyileştirmelerin bir arada uygulanmasının üretim kapasitesine, çalışan memnuniyetine ve ürün kalitesine pozitif etkilerini ortaya koymuştur. Elde edilen sonuçlar, diğer üretim hatlarına uygulanabilir nitelikte olup, işletmenin genel verimliliğine katkı sağlamaktadır.The study in this thesis aims to eliminate unbalanced workload distribution among workstations and ergonomic problems in the production line of a white goods company. The current state of the production line was evaluated using Avix analysis and Muri analysis, and improvement plans were developed. Avix analysis is a method that uses video-based evaluation to optimize workload distribution across workstations. Muri analysis, on the other hand, identifies non-ergonomic movements and excessive workload situations to reduce risk levels. As a result of the improvements, the number of workstations was reduced from 45 to 35, and production capacity increased from 600 units to 700 units per shift. Additionally, the number of high-risk ergonomic tasks (red risk) was reduced from 87 to 22, leading to significant improvements in the physical and mental well-being of employees. Material feeding methods were revised, and operator movements were optimized to enhance efficiency. This study demonstrates the positive impact of combining lean production methodologies with ergonomic improvements on production capacity, employee satisfaction, and product quality. The results are applicable to other production lines and contribute to the overall efficiency of the company
Staged Urethroplasty in a Patient with Urethral Stricture Following Female to Male Transgender Surgery
No full textComplications of urethral reconstruction are common in patients who have undergone female to male transgender surgery. Patients may develop urethral strictures and fistulas, which lead to repeated surgery. Our aim was to present a case of staged buccal mucosal graft urethroplasty in a patient who developed urethral stricture after gender-affirming surgery from female to male
From Shadows to Signatures: Interpreting Bypass Diode Faults in PV Modules Under Partial Shading Through Data-Driven Models
No full textBypass diode faults are among the most hard-to-detect but impactful anomalies in photovoltaic (PV) systems, especially under partial shading conditions, where their electrical signatures often resemble those caused by non-critical irradiance variations. This study presents a systematic simulation-based investigation into how different bypass diode fault types-short-circuited, open-circuited, and healthy-affect the electrical behavior of PV strings under diverse irradiance profiles. A high-resolution MATLAB/Simulink model is developed to simulate 27 unique diode fault configurations across multiple shading scenarios, enabling the extraction of key features from resulting I-V curves. These features include global and local maximum power point parameters, open-circuit voltage, and short-circuit current. To address the challenge of feature redundancy and classification ambiguity, a preprocessing step is applied to remove near-duplicate instances and improve model generalization. An artificial neural network (ANN) model is then trained to classify the number of faulty bypass diodes based on these features. Comparative evaluations are conducted with support vector machines and random forests. The results indicate that the ANN achieves the highest test accuracy (93.57%) and average AUC (0.9925), outperforming other classifiers in both robustness and discriminative power. These findings highlight the importance of feature-informed, data-driven approaches for fault detection in PV systems and demonstrate the feasibility of diode fault classification without precise fault localization
Three-Dimensional Deployment Optimization of UAVs Using Symbolic Control for Coverage Enhancement via UAV-Mounted 6G Mobile Base Stations
No full textWe propose a novel systematic approach for the deployment optimization of unmanned aerial vehicles (UAVs). In this context, this study focuses on enhancing the coverage of UAV-mounted 6G mobile base stations. The number and placement optimization of UAV-mounted 6G mobile base stations, deployed to support terrestrial base stations during periods of increased population density in a given area, are addressed using a symbolic limited optimal discrete controller synthesis technique. Within the scope of this study, the UAVs' altitude and attitude behaviors are optimized to ensure the most efficient trajectory toward the designated base station coordinates. Additionally, at their new locations, these behaviors are adjusted to facilitate accurate coverage estimation from the base stations they serve. In the deployment optimization of UAVs, the placement of base stations is determined using received signal strength data obtained through the ray-tracing-based channel modeling technique. The channel model considered critical parameters such as path loss, received power, weather loss, and foliage loss. Final average path loss values of 102.3 dB, 111.7 dB, and 127.4 dB were obtained at the carrier frequencies of 7 GHz, 26 GHz, and 140 GHz, respectively. These findings were confirmed with MATLAB-based ray tracing simulations. Our proposed approach is validated through experimental evaluations, demonstrating superior performance compared to existing methods reported in the literature