IEU GCRIS Database (İzmir Ekonomi Üniversitesi)
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Navicular Tubercle Osteotomy for Mobilization of the Posterior Tibial Tendon: a Simple and Effective Technique for Visualization and Repair of the Spring Ligament
No full textRepair or reconstruction of spring ligament complex (SLC) is strongly recommended in the surgical treatment of flexible pes planovalgus, as this structure plays a major role in supplying the integrity of the medial longitudinal arch. The SLC is located underneath the terminal portion of the posterior tibial tendon (PTT) and the navicular tubercle, which makes visualization and repair grueling and often inadequate, unless the overlying structures are mobilized and removed temporarily out of its path. Previously defined techniques for mobilizing the terminal portion of the PTT include cutting the tendon body or detaching its distal end from the navicular bone. However, tendon-to-tendon and tendon-to-bone repairs inevitably heal with scar tissue, demonstrate inferior tissue strength and carry the risk of rupture, elongation and loss of function. Any technique that preserves the tendon and its bony attachment during mobilization of the PTT would definitely be more advantageous in terms of postoperative strength and function. This article defines a navicular tubercle osteotomy technique to mobilize the terminal portion of PTT without violating the tendon body or its bony insertion site. This technique provides perfect visualization and access to the SLC, talo-calcaneal joint and deep plantar structures of the foot. It also enables superior initial fixation of the detached fragment compared with tendon-to-tendon or tendon-to-bone fixation, allows scar-free healing at the osteotomy site and permits distalization of the insertion site of the PTT for retensioning. Level of Evidence: IV. Copyright © 2025 Wolters Kluwer Health, Inc. All rights reserved
Convivial Circularities for Degrowth: the Case of Upcycling
No full textThis study illustrates a critique of circular fashion practices using empirical insights from upcycling to highlight its potentials and limits for a degrowth transition in circular fashion. Acknowledging valuable marketing research on the motivations, benefits, and challenges of consumer upcycling, we investigate the often-overlooked domain of institutional upcycling practices, through interviews with diverse industry actors and secondary data analysis. Our analysis advances critical and theoretical debates on degrowth and circular fashion by examining how the socio-ecological value of upcycled waste is realized through institutional upcycling practices. Accordingly, we elucidate the emerging dynamics of degrowth circularity, demonstrating how these dynamics challenge and expand the degrowth principle of conviviality. Findings articulate the diverse convivialities necessary for a degrowth transition in circular fashion. Specifically, we highlight neo-material and more-than-human relationality as essential organizing principles of conviviality for degrowth circularity
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 T ; uuml;rkiye, 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
Audio-Based Anomaly Detection in Industrial Machines Using Deep One-Class Support Vector Data Description
No full textThe frequent breakdowns and malfunctions of industrial equipment have driven increasing interest in utilizing cost-effective and easy-to-deploy sensors, such as microphones, for effective condition monitoring of machinery. Microphones offer a low-cost alternative to widely used condition monitoring sensors with their high bandwidth and capability to detect subtle anomalies that other sensors might have less sensitivity. In this study, we investigate malfunctioning industrial machines to evaluate and compare anomaly detection performance across different machine types and fault conditions. Log-Mel spectrograms of machinery sound are used as input, and the performance is evaluated using the area under the curve (AUC) score for two different methods: baseline dense autoencoder (AE) and one-class deep Support Vector Data Description (deep SVDD) with different subspace dimensions. Our results over the MIMII sound dataset demonstrate that the deep SVDD method with a subspace dimension of 2 provides superior anomaly detection performance, achieving average AUC scores of 0.84, 0.80, and 0.69 for 6 dB, 0 dB, and -6 dB signal-to-noise ratios (SNRs), respectively, compared to 0.82, 0.72, and 0.64 for the baseline model. Moreover, deep SVDD requires 7.4 times fewer trainable parameters than the baseline dense AE, emphasizing its advantage in both effectiveness and computational efficiency. © 2025 IEEE.NSF-Business; Horizon Europe Framewor
Türkiye'deki Tüketici Satın Alma Eğilimine Dayalı Bira Ambalaj Tasarımı
No full textSon yıllarda, kraft bira dünya genelinde önemli bir popülerlik kazanmış ve öne çıkan bir içecek seçeneği haline gelmiştir. Bu çalışma, Türkiye bira pazarında, özellikle kraft bira sektöründe, paket tasarımı unsurlarının tüketici tercihleri üzerindeki etkisini araştırmaktadır. Kapsamlı bir araştırma çerçevesi kullanarak, çalışma, ambalaj tasarımı özelliklerinin Türkiye'nin kendine özgü sosyokültürel ve düzenleyici ortamı bağlamında tüketici algılarını ve satın alma kararlarını nasıl etkilediğini incelemektedir. Çalışma, tasarım çalışmaları, tüketici tercihleri ve pazar dinamiklerinden elde edilen iç görüleri birleştirerek, Türkiye'deki bira tüketicilerinin çeşitli demografik profillerini temsil eden 447 katılımcıdan nicel veri toplamak için yapılandırılmış bir anket kullanmıştır. Anket, demografik profilin, bira tüketim alışkanlıkları ve sıklığının ve paket tasarımı özelliklerinin etkisini değerlendirmiş, renk şemaları, tipografi, görseller, şişe şekilleri ve metin yerleşimi gibi anahtar unsurları analiz etmiştir. Toplanan veriler, tanımlayıcı istatistikler, frekans analizi ve keşifsel faktör analizi uygulanarak analiz edilmiş ve değerlendirilmiştir. Bulgular, vii altın paletler ve geleneksel tipografileri içeren geleneksel tasarımlara belirgin bir eğilim olduğunu göstermiştir. Aynı zamanda, tüketiciler, hikaye anlatımı, özgünlük ve görsel farklılıklarla karakterize edilen yenilikçi ve zanaatkar tasarımlara belirgin bir eğilim sergilemiştir. Ayrıca, çalışma, şişe boyutu ve şeklinin satın alma kararları üzerinde önemli bir etkiye sahip olduğunu belirlemiş, ana akım tüketicilerin standartlaştırılmış tasarımlara, kraft bira meraklılarının ise çağdaş ve yenilikçi paket tasarımlarına eğilim gösterdiğini ortaya koymuştur. Bu araştırma, paket tasarımı ve tüketici davranışı konusundaki mevcut literatüre, Türk bira pazarına özgü uygulanabilir iç görüler sunarak önemli bir katkı sağlamaktadır. Çalışma, ambalajın farklılaşma ve pazar konumlandırması için stratejik bir araç olarak önemini vurgulamaktadır.In recent years, craft beer has gained significant popularity worldwide, emerging as a prominent beverage option. This study investigates the influence of package design elements on consumer preferences within the Turkish beer market, with a specific emphasis on the craft beer sector. Utilizing a comprehensive research framework, the study explores how package design attributes influence consumer perceptions and purchasing decisions within the context of Turkey's distinctive sociocultural and regulatory environment. The study integrated insights from design studies, consumer preferences, employing a structured survey to collect quantitative data from 447 participants representing diverse demographic profiles of Turkish beer consumers. The survey assessed the impact of demographic profile, beer consumption habits and frequency, and package design attributes, analyzing key elements such as color schemes, typography, imagery, bottle shapes, and textual placement. The collected data was analyzed and evaluated by implementing descriptive statistics, frequency analysis, and exploratory factor analysis. The findings indicated a marked predilection v for conventional designs, encompassing gold palettes and traditional typographies. Concurrently, consumers exhibited a discernible inclination for innovative and artisanal designs, characterized by authenticity, and visual distinctiveness. The study ascertained that bottle size and shape exerted a substantial influence on purchasing decisions, with mainstream consumers demonstrating a predilection for standardized designs, while craft beer enthusiasts exhibited a propensity for contemporary and innovative packaging designs. This research makes a significant contribution to the existing literature on package design and consumer preferences in the Turkish beer market
From Refuse To Resource: Exploring Technological and Economic Dimensions of Waste-To
No full textWaste valorization offers a sustainable approach to waste management and the generation of biofuels and bioenergy, mitigating the environmental impact of fossil fuel production and use. Carbon emissions and food-source competition associated with first-generation biofuels production can be mitigated. Reports on thermochemical and biochemical pathways for generating bio-oil and syngas provide extensive coverage of production processes but lack recent insights into technological advances for upgrading these outputs into biodiesel, biomethanol, bioethanol, biogas, and biomethane. They also often omit information on commercial status, leading and prospective companies, market size, future market predictions, and associated challenges. The drawbacks of waste valorization do not appear to have been discussed widely in the literature – they include deforestation, land-use changes, soil texture changes, and biodiversity and social impacts. To address these gaps in the literature, this review examines the factors mentioned above, focusing on the drawbacks of waste-to-energy conversion and proposing solutions targeted at governments, policymakers, investors, entrepreneurs, and researchers seeking to understand and mitigate the challenges in this sector. © 2025 Society of Industrial Chemistry and John Wiley ; Sons Ltd
Pentraxin 3: a Marker for the Presence and Severity of Coronary Artery Disease
No full textObjective: Atherosclerosis, a major contributor to coronary artery disease (CAD), is characterized by chronic arterial inflammation. Pentraxin 3 (PTX-3), a biomarker of inflammation, serves as an indicator of both atherosclerosis and the progression of CAD. The aim of this study was to investigate the association between PTX-3 levels and the presence and severity of CAD, as determined by coronary computed tomography angiography (CCTA). Method: In this study, 94 participants (54 with CAD and 40 controls) underwent CCTA and coronary artery calcium scoring (CACS) using computed tomography. PTX-3 levels were measured using the enzyme-linked immunosorbent assay (ELISA) method. CAD patients were categorized based on CCTA findings and furthersubdivided into three groups according to their CACS: Group I (CACS 100), Group II (CACS 100-299), and Group III (CACS >= 300). Results: Serum PTX-3 levels were significantly higher in the CAD group. A PTX3 cut-off value of 5.80 ng/mL predicted CAD with 68% sensitivity and 66% specificity. A strong positive correlation was observed between CACS and PTX-3 levels (r = 0.521, P 0.001). In high-risk patients with a CACS >= 300, PTX-3 levels were significantly higher than those in low- and intermediate-risk groups a CACS 300. However, no significant difference in PTX-3 levels was observed between the normal coronary group and the low- and intermediate-risk groups. Furthermore, no correlation was found between the degree of coronary artery stenosis and PTX-3 levels. Conclusion: Pentraxin 3 might serve as a valuable biomarkerforthe diagnosis and severity of CAD
Teachers and Ai: Understanding the Factors Influencing Ai Integration in K-12 Education
No full textThis study investigates the psychological and pedagogical factors influencing K-12 teachers' readiness to integrate artificial intelligence (AI) into educational settings. An exploratory qualitative approach was employed, involving 66 teachers from 11 disciplines at a private school in T ; uuml;rkiye participating in a professional development program focused on AI-enhanced teaching. Data were collected through online discussion forums and AI-supported learning activity design tasks and analyzed using inductive thematic analysis. Findings reveal that teachers valued AI for its efficiency, interactivity, and adaptability, particularly in tools like ChatGPT and MagicSchool, which supported personalized learning and lesson planning. However, significant challenges emerged, including technical issues, curriculum misalignment, ethical concerns, and cultural barriers, such as difficulties adapting AI-generated content to local contexts. The study concludes that while AI offers significant potential to enhance education, successful integration requires addressing the identified barriers through targeted support, resources, and ethical guidelines. Implications for further research include exploring diverse educational settings to generalize findings, conducting longitudinal studies to assess long-term impacts, and investigating strategies to align AI tools with existing curricula and ethical standards.Scientific and Technological Research Council of Turkiye (TUBITAK)Open access funding provided by the Scientific and Technological Research Council of Turkiye (TUBITAK). This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors
Design and Implementation of CP Antennas for Automotive and Radar Applications at 76.5 Ghz
No full textAnritsu; Bosch; et al.; IHP Solutions; Keysight Technologies; Rohde and Schwarz (RS)This paper presents an antenna designed for autonomous vehicles and MIMO radar systems. MIMO radar enhances detection and resolution by using multiple antennas. The research covers the design and performance evaluation of MIMO radar antennas, aiming to advance radar technology. The antenna is made on Rogers RO4003C (dielectric constant 3.55, thickness 0.203 mm) and operates at 76.5 GHz with single and multiple circularly polarized configurations. One antenna was fabricated, showing a strong correlation between simulated and measured reflection coefficients. Key parameters like the 2D radiation pattern, realized gain, and axial ratio are discussed. Circularly polarized (CP) antennas are favored for their advantages: orientation independence, reduced multi-path fading, and compatibility with linear polarization systems. The gain of the four-element CP antenna at 76.5 GHz reaches 8.23 dB as an array, intended for future MIMO radar applications to enhance field of view and angle resolution. © 2025 Institut fur Mikrowellen und Antennentechnik - IMA
A Data-Driven Approach To Arsenic Classification in Groundwater in Geothermal Systems: Meta-Analysis and Machine Learning Applications in Western Anatolia, Turkiye
No full textWestern Anatolia, T ; uuml;rkiye, is renowned for its diverse geothermal resources, encompassing high, medium, and low enthalpy systems. While these systems are valuable for energy production and economic development, they are also associated with significant environmental challenges, particularly high concentration arsenic and boron contamination. This study highlights critical hotspots, including Sandikli (27 mg/L) and Banaz-Hamambogazi (95.64 mg/L), with arsenic levels far exceeding the World Health Organization's (WHO) maximum permissible limit of 10 ppb. Such contamination poses significant risks to water quality, agriculture, and public health, especially in major agricultural provinces like Aydin and Manisa. To address these challenges, machine learning models were applied to classify arsenic concentrations. Ensemble methods, including AdaBoost (ABC) and Extra Trees (ETC) classifiers, consistently outperformed others, showing high accuracy of about 97 % in distinguishing geochemical signatures and predicting arsenic levels. In contrast, the k-Nearest Neighbors Classifier (KNNC) proved less effective, with frequent misclassifications. The combination of machine learning and meta-analysis provided a robust framework for identifying spatial and temporal patterns of contamination, offering valuable insights for environmental monitoring. This approach not only enhanced the understanding of arsenic distribution in geothermal systems but also provided actionable insights for mitigating contamination risks. The findings underscore the importance of combining computational techniques with environmental geochemistry to improve the management of geothermal wastewater. Future research should expand these methodologies to other regions and contaminants, leveraging machine learning to develop more effective environmental protection strategies. This study demonstrates the potential of data-driven approaches to address critical environmental issues and supports sustainable development in geothermal-rich areas