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Doktor İhsan Sami (Garan) Bey’in 1911 Bursa Kolerasına Dair Tespitleri ve Yansımaları
No full textAmaç: Bu çalışmada 1911 kolera salgını sırasında Bursa’ya gönderilen Dr. İhsan Sami Bey’i tanıtmak ve raporunda yer alan iddialar ile bu iddialara karşı yapılan inceleme hakkında bilgi vermek amaçlanmıştır. Yöntem: 1 Aralık 2024-3 Mart 2025 tarihleri arasında yapılan bu çalışmada tarih araştırmalarında kullanılan klasik yöntem kullanılmıştır. Bu çerçevede T.C. Cumhurbaşkanlığı Devlet Arşivleri Başkanlığı bünyesindeki Osmanlı ve Cumhuriyet Arşivi’nin farklı tasniflerindeki belgelerden ve konuyla ilgili mevcut literatürden yararlanılmıştır. Bulgular: Kolera Hindistan coğrafyasının yerli hastalığıdır. XIX. yüzyılda 6 büyük pandemi yapan kolera, Osmanlı Devleti’ndeki ilk salgınını 1822’de yapmıştır. Osmanlı idari teşkilatlanmasında Hüdavendigar Vilayetinin merkezi olan Bursa şehri de tarihsel süreç içerisinde kolera salgınlarına maruz kalmıştır. Bursa’da 1911 kolerası 27 Haziran’da başlamıştır. Salgın sırasında istilacı şekilde hüküm süren koleranın mahiyetini araştırmak ve sular hakkında bakteriyolojik incelemelerde bulunmak için bakteriyolog Dr. İhsan Sami Bey şehre gönderilmiştir. Onun tarafından kaleme alınan rapor koleranın bölgedeki etkisini artırmasına neden olabilecek önemli iddialara sahiptir. Merkezi hükümet bu iddiaları araştırmak için bölgeye Mülkiye Müfettişi Ali Seydi Bey’i göndermiştir. Sonuç: Bursa’da 1911 kolera salgınında 440 vaka görülmüş ve bunların 110’nu ölümle neticelenmiştir. Dr. İhsan Sami Bey’in raporunda yer alan valinin koleranın varlığına inanmaması, doktorları azarlaması, kordonlar, erzak dağıtımı, suların kirliliği, vaizlerin halka olumsuz telkinlerde bulunması, bazı doktorların kolera hastalarını hükümete haber vermemesi ve diğer iddialar oldukça önemlidir. Raporu dikkate alan merkezi hükümet bu iddiaları araştırması için Mülkiye Müfettişi Ali Seydi Bey’i Bursa’ya göndermiştir. Bu tavır devletin kamu sağlığı konusundaki hassasiyetini göstermesi bakımından önemlidir. Ancak Ali Seydi Bey’in iddialara ilişkin yapmış olduğu yazışmalarda rapor ile çelişen cevaplar bulunmaktadır
A Needs Analysis Study of Novice EFL Teachers’ Professional Development in Türkiye|Türkiye’de Mesleğe Yeni Başlayan İngilizce Öğretmenlerinin Mesleki Gelişim İhtiyaçları Üzerine Bir İhtiyaç Analizi Çalışması
No full textThis study investigates the professional development needs of novice EFL teachers in Türkiye, incorporating perspectives from multiple stakeholders. Additionally, it evaluates novice teachers’ perceptions of the induction program prepared for novice teachers by the Turkish Ministry of National Education (MoNE). Data collected from 109 participants (29 novice EFL teachers, 55 experienced EFL teachers, and 25 EFL teacher educators) through questionnaires suggest that while the program supports novice teachers in adapting to the profession, its overall effectiveness remains limited. The study identifies key areas for improvement, including the selection of mentors, the reduction of administrative workload, and the enhancement of practical training. The findings of the study, supported by the literature, emphasize the need for a more tailored professional development program that incorporates critical elements such as well-being, classroom management, technology-integrated materials development, diversity in EFL classrooms, and reflective practice. The implications of this study provide valuable insights for policymakers and teacher educators seeking to improve the induction process for novice teachers. © 2025 Elsevier B.V., All rights reserved
Clinical Failure of General-Purpose AI in Photographic Scoliosis Assessment: A Diagnostic Accuracy Study
No full textBackground and Objectives: General-purpose multimodal large language models (LLMs) are increasingly used for medical image interpretation despite lacking clinical validation. This study evaluates the diagnostic reliability of ChatGPT-4o and Claude 2 in photographic assessment of adolescent idiopathic scoliosis (AIS) against radiological standards. This study examines two critical questions: whether families can derive reliable preliminary assessments from LLMs through analysis of clinical photographs and whether LLMs exhibit cognitive fidelity in their visuospatial reasoning capabilities for AIS assessment. Materials and Methods: A prospective diagnostic accuracy study (STARD-compliant) analyzed 97 adolescents (74 with AIS and 23 with postural asymmetry). Standardized clinical photographs (nine views/patient) were assessed by two LLMs and two orthopedic residents against reference radiological measurements. Primary outcomes included diagnostic accuracy (sensitivity/specificity), Cobb angle concordance (Lin's CCC), inter-rater reliability (Cohen's kappa), and measurement agreement (Bland-Altman LoA). Results: The LLMs exhibited hazardous diagnostic inaccuracy: ChatGPT misclassified all non-AIS cases (specificity 0% [95% CI: 0.0-14.8]), while Claude 2 generated 78.3% false positives. Systematic measurement errors exceeded clinical tolerance: ChatGPT overestimated thoracic curves by +10.74 degrees (LoA: -21.45 degrees to +42.92 degrees), exceeding tolerance by >800%. Both LLMs showed inverse biomechanical concordance in thoracolumbar curves (CCC <= -0.106). Inter-rater reliability fell below random chance (ChatGPT kappa = -0.039). Universal proportional bias (slopes approximate to -1.0) caused severe curve underestimation (e.g., 10-15 degrees error for 50 degrees deformities). Human evaluators demonstrated superior bias control (0.3-2.8 degrees vs. 2.6-10.7 degrees) but suboptimal specificity (21.7-26.1%) and hazardous lumbar concordance (CCC: -0.123). Conclusions: General-purpose LLMs demonstrate clinically unacceptable inaccuracy in photographic AIS assessment, contraindicating clinical deployment. Catastrophic false positives, systematic measurement errors exceeding tolerance by 480-1074%, and inverse diagnostic concordance necessitate urgent regulatory safeguards under frameworks like the EU AI Act. Neither LLMs nor photographic human assessment achieve reliability thresholds for standalone screening, mandating domain-specific algorithm development and integration of 3D modalities
Adaptive interoceptive sensibility and its predictive role in pain-related disability in people with chronic spinal pain
No full textBackground Identifying determinants of pain-related disability in chronic spinal pain (CSP) remains a major research focus, but the role of interoceptive sensibility is underexplored. Objective To determine whether adaptive interoceptive sensibility uniquely predicts pain-related disability and to compare its dimensions and cognitive factors across disability severity in people with CSP. Methods This cross-sectional study included 108 people with CSP. Pain intensity over the previous week and during activity, pain duration, and coexisting extremity pain were recorded. The Pain Disability Index, Pain Catastrophizing Scale, Pain Beliefs Questionnaire, and Multidimensional Assessment of Interoceptive Awareness (MAIA-2) were administered. A linear regression identified disability-related factors. Demographic-adjusted outcomes were compared across mild, moderate, and severe disability groups. Results Interoceptive sensibility explained an additional 17.70% of the variance in pain-related disability after adjusting for demographics, and among the eight dimensions measured by MAIA-2, not-distracting (B = -2.66, 95% CI = -5.13 to -0.18) and not-worrying (B = -6, 95% CI = -9.08 to -2.94) predicted pain-related disability (p < 0.05). Not-distracting remained a unique predictor when pain characteristics and catastrophizing were included in the model (B = -2.62, 95% CI = -4.41 to -0.83, p < 0.05). The mild disability group showed less catastrophizing and more not-worrying, and the severe disability group showed less not-distracting (p < 0.05, eta(2)p=0.06 to 0.19). Conclusion Adaptive interoceptive sensibility, especially not-worrying and not-distracting dimensions, were associated with spinal pain-related disability
Addition of antimicrobials to oral sprays containing nonsteroidal antiinflammatory drugs does not reduce the severity of postoperative sore throat: a prospective, randomized, placebo-controlled trial
No full textBackground/aim: Postoperative sore throat (POST) is a common complication following general anesthesia that significantly affects patient satisfaction, prolongs recovery, and increases treatment costs. This study aimed to evaluate whether the addition of antimicrobial agents to NSAID-based oral sprays could enhance the preventive efficacy against POST. Materials and methods: In this prospective, randomized, placebo-controlled trial, 105 patients (ASA I-II; age 18-65 years) scheduled for elective ear surgery under general orotracheal anesthesia were enrolled. Patients were randomly allocated into three groups: a placebo group; a flurbiprofen oral spray group; and a group receiving an oral spray containing benzydamine hydrochloride, chlorhexidine digluconate, and cetylpyridinium chloride. The sprays were administered under direct laryngoscopy before intubation and after the final oropharyngeal aspiration. POST severity was assessed using a 10mm Visual Analog Scale (VAS) at 1 h, 6 h, 24 h, and 1 week postoperatively. Patients were also subgrouped based on surgical duration (= 120 min). Results: Both NSAIDbased treatments significantly reduced VAS scores at early postoperative time points compared to the placebo. In subgroup analysis, patients undergoing surgeries lasting less than 120 min exhibited lower VAS scores with both active treatments, while in those with surgeries >= 120 min, significant differences were noted at 1 and 6 h. No significant difference was found between the flurbiprofen spray and the combination spray. Conclusion: NSAIDcontaining oral sprays effectively reduce the severity of postoperative sore throat. However, the addition of antimicrobial agents does not provide extra analgesic benefit, suggesting that simpler, costeffective NSAID formulations may be preferable in clinical practice
Photovoltaic System Performance Under Partial Shading Conditions: Insight into the Roles of Bypass Diode Numbers and Inverter Efficiency Curve
No full textPartial shading is a common challenge influencing the performance of photovoltaic (PV) systems, particularly in urban and residential applications. A practical solution to mitigate hotspot formation due to shading is the use of bypass diodes. Increasing the number of bypass diodes further enhances PV system performance but alters the global maximum power points (MPPs), shifting their voltage locations and power magnitudes, consequently resulting in a change in the operating points in the efficiency curve of the inverters. This study investigates the impact of bypass diode numbers and inverter efficiency curves on PV system performance under various partial shading conditions. The analysis systematically deals with three inverters with different efficiency characteristics in terms of loading and input voltage, as well as module configurations with different numbers of bypass diodes. Additionally, three more factors-ambient temperature, inverter loading ratio by varying the number of series-connected PV modules, and shading intensity-are considered in the context of bypass diodes and inverter characteristics through the efficiency curve. The global MPPs of PV modules under different cases are simulated using a Simscape/Simulink-based circuit model with random irradiance samples. The results indicate the formation of bands according to the voltage that vary with bypass diode configurations. In this manner, utilizing the probabilities of these bands and inverter efficiency curves, the average PV system performance is determined for each case. The findings reveal the effects of the relationship between bypass diode configurations and inverter efficiency on PV system performance. As partial shading is especially common in dense urban areas, the results are of interest for the development of resilient and sustainable PV installations
Rethinking Digital Transformation of Manufacturing Through Platforms: A Critical Review and Integrative Framework
No full textThe digital transformation of manufacturing through platforms represents a paradigm shift in industrial operations, yet comprehensive frameworks for understanding and implementing these transformations remain fragmented. This study presents a systematic bibliometric analysis of 156 publications from Web of Science and Scopus databases (2011-2024), offering a critical review of digital manufacturing platform research. The analysis reveals three evolutionary phases: conceptual foundation (2011-2016), integration (2017-2020), and advanced implementation (2021-2024). While existing literature extensively addresses technical architectures and implementation methodologies, significant gaps remain in understanding the holistic integration of sustainability principles and standardization frameworks. This research contributes by proposing an integrative framework that synthesizes technological, organizational, and environmental dimensions of platform-based manufacturing transformation, encompassing five key elements: platform architecture, digital twin integration, interoperability standards, business model innovation, and sustainability integration. The findings indicate a shift from theoretical conceptualizations to practical implementation considerations, particularly for small and medium-sized enterprises. The study identifies emerging research directions, emphasizing standardized approaches to cross-platform interoperability and artificial intelligence integration in platform-based manufacturing systems, providing guidance for researchers and practitioners while considering sustainability imperatives
A preliminary study on the role of personal history of infectious and parasitic diseases on self-reported health across countries
No full textObjectives: Infectious diseases are often associated with decline in quality of life. The aim of this study is to analyze the relationship between personal history of communicable, i.e., infectious and parasitic diseases and self-rated health. Study design: Secondary analysis of a large dataset multi-country observational study. Methods: We used a four-pronged analysis approach to investigate whether personal history of infectious and parasitic diseases is related to self-reported health, measured with a single item. Results: Three of the four analyses found a small positive effect on self-reported health among those reporting a history of pathogen exposure. The meta-analysis found no support but large heterogeneity that was not reduced by two classifications of countries. Conclusion: Personal history of infectious and parasitic diseases does not reduce self-reported health across a global sample.Foundation for Polish Science (FNP) START scholarshipThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Marta Kowal was supported by the Foundation for Polish Science (FNP) START scholarship
A Machine Learning Analysis on Socioeconomic Determinants of Chronic Diseases
No full textBu çalışmanın amacı sosyal, kültürel ve ekonomik değişkenlerle seçilmiş kronik hastalıklar (astım, kalp rahatsızlığı, hipertansiyon, şeker hastalığı, karaciğer yetmezliği, böbrek rahatsızlığı) arasındaki ilişkiyi analiz etmektir. Araştırmada kullanılan veri kümesinin büyük veri özelliğine sahip olması nedeniyle büyük veri tekniklerinden yararlanılmaktadır. Bu kapsamda, yapay zekanın bir alt dalı olan makine öğrenmesi yöntemi olan Derin öğrenme tekniği kullanılmaktadır. Çalışmada 2019 yılı Türkiye Sağlık Araştırması mikro veri seti kullanılmıştır. Derin öğrenme modelinden elde edilen sonuçlar, eğitim ve gelir düzeyindeki artışlar ile kronik rahatsızlıklar arasında negatif bir ilişkinin olduğunu göstermektedir. Modelde yer alan diğer değişkenlerden spor yapılan gün sayısı ile kronik hastalıklar arasında negatif bir ilişki görülürken, meyve yeme sıklığı ile kronik hastalıklar arasında hastalık türlerine göre pozitif (şeker hastalığı, böbrek rahatsızlığı) ve negatif (astım, kalp, hipertansiyon, karaciğer yetmezliği) bir ilişki görülmektedir. Bulgulardan hareketle, gelir düzeyi artan bireylerin yıpranan sağlık stoğunu telafi etmek amacıyla besin değeri yüksek gıdalara ve egzersiz gibi sportif faaliyetlere yöneleceği sonucuna ulaşılabilir. Öte yandan, eğitim düzeyindeki artış, bireylerin sağlığa yönelik riskleri daha iyi değerlendirmelerini sağlayarak, bireyleri koruyucu sağlık hizmetlerinden daha fazla yararlanmaları yönünde teşvik edebilir. Maliyet açısından ise diğer sağlık hizmetlerine göre daha uygun olan koruyucu sağlık hizmetlerine yönelik talebin artması sağlık sistemi üzerinde ortaya çıkan finansal yükü azaltabilir. Bu nedenle, koruyucu sağlık hizmetlerinin kullanımının artırılmasına yönelik politikalara önem verilmelidir.This study explores the relationship between various social, cultural, and economic variables and selected chronic diseases such as asthma, heart disease, hypertension, diabetes, liver failure, and nephropathy. Given that the dataset exhibits characteristics typical of big data, big data techniques have been applied. Specifically, deep learning - a sub-branch of artificial intelligence within machine learning - was utilized. The analysis used the Türkiye Health Survey (2019) microdata set. Findings from the deep learning model reveal a negative correlation between levels of education and income and the incidence of chronic diseases. While the model reveals a negative correlation between the number of days engaging in sports activities and chronic diseases, it also shows that the relationship between another variable - the frequency of eating fruit -and chronic diseases can be either positive (diabetes, nephropathy) or harmful (asthma, heart disease, hypertension, liver failure), depending on the type of disease. The findings suggest that individuals with increasing income levels are likely to choose foods with high nutritional value and engage in sports activities such as exercise to compensate for their deteriorating health. On the other hand, increasing education levels may encourage individuals to use preventive health services more by enabling them to assess health risks better. As preventive health services are generally more cost-effective than other health services, increasing their demand can alleviate the financial strain on the healthcare system. Consequently, policies that promote the use of preventive healthcare services should be prioritized.Bu çalışma İzmir Bakırçay Üniversitesi Bilimsel Araştırma Projeleri Koordinatörlüğü tarafından KBP.2021.004 nolu proje kapsamında desteklenmiştir
Alternative Surgical Technique for the Repair of Meniscus Root Tears Using Finite Element Analysis
No full textThis study investigates an alternative surgical approach for repairing meniscal root tears, a common knee injury that can significantly impact joint stability and function. Traditional repair methods often face challenges such as high rates of retear and persistent pain. To address these limitations, this research utilizes finite element analysis (FEA) to compare the biomechanical performance of an alternative technique against established surgical procedures. FEA models were carefully constructed to accurately represent the complex anatomy of the knee joint, including the medial meniscus, cartilage, ligaments, and surrounding bone structures. These models were then subjected to various loading conditions that simulated physiological activities such as walking, running, and squatting to assess the stress and strain experienced by the repaired tissue under realistic conditions. The results of the FEA simulations demonstrated a significant reduction in stress and strain on the repaired medial meniscus root when the alternative technique was employed compared to traditional methods. This reduction in biomechanical load is crucial for promoting tissue healing and minimizing the risk of retear. By reducing excessive stress on the repair site, the alternative surgical technique may enhance long-term patient outcomes, potentially improving knee function, reducing pain, and decreasing the likelihood of further surgical interventions such as meniscectomy or knee prosthesis replacement. In conclusion, this study provides strong evidence for the potential benefits of the alternative surgical technique in repairing meniscal root tears. The findings suggest that this approach may offer a promising alternative to traditional methods by optimizing biomechanical stability and promoting more favorable healing conditions. Further clinical studies are warranted to validate these findings and translate these promising results into improved patient care