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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Publication Metadata only Ethics of deep brain stimulation for neuropsychiatric disorders(Springer, 2024) Darko, K.; Detchou, D.; Barrie, U.; Aydın, Serhat; School of MedicineDeep Brain Stimulation (DBS) has emerged as a revolutionary neurosurgical technique with significant implications for the treatment of various neuropsychiatric disorders. Initially developed for movement disorders like Parkinson’s disease, DBS has expanded to psychiatric conditions such as obsessive-compulsive disorder, depression, anorexia nervosa, dystonia, essential tremor, and Tourette’s syndrome. This paper explores the clinical efficacy and ethical considerations of DBS in treating these disorders. While DBS has shown substantial promise in alleviating symptoms and improving quality of life, it raises ethical challenges, including issues of informed consent, patient selection, long-term management, and equitable access to treatment. The irreversible nature of DBS, potential adverse effects, and the high cost of the procedure necessitate a rigorous ethical framework to guide its application. The ongoing evolution of neuromodulation requires continuous ethical analysis and the development of guidelines to ensure that DBS is used responsibly and equitably across different patient populations. This paper underscores the need for a balanced approach that integrates clinical efficacy with ethical considerations to optimize patient outcomes and ensure sustainable practice.Publication Metadata only Endometriosis, staging, infertility and assisted reproductive technology: time for a rethink(Elsevier Inc., 2024) Somigliana, Edgardo; Ata, Mustafa Barış; School of MedicineHow endometriosis causes infertility, with the exception of tubal dysfunction caused by adhesions, is unclear. The inflammatory milieu in the pelvis and impaired receptivity of the eutopic endometrium are considered to be possible factors. Anatomical staging systems fail to predict the fertility status of endometriosis patients. Data from assisted reproductive technology cycles consistently suggest that oocytes from patients with endometriosis have a normal potential to develop into euploid blastocysts. Moreover, oocyte or embryo recipients with endometriosis seem to have similar or slightly lower pregnancy and live birth rates compared with recipients without endometriosis, suggesting that eutopic endometrium is not or is only minimally affected, which may be caused by undiagnosed adenomyosis. In-vivo observations from women with endometriomas provide evidence against a detrimental effect of endometriomas on oocytes. Combined with the absence of an obvious improvement in fertility following the surgical destruction or excision of peritoneal endometriosis or from temporary medical suppression of the disease and the associated inflammation, the available evidence makes endometriosis-associated infertility questionable in the absence of tubal dysfunction caused by adhesions. It is likely that no anatomical staging will correlate with fertility beyond assessing tubal function. In patients with endometriosis assisted reproductive technology is as effective as for other indications.Publication Metadata only The effect of adrenalectomy on overall survival in metastatic adrenocortical carcinoma(Endocrine Society, 2024) Assad, A.; Incesu, R.B.; Morra, S.; Scheipner, L.; Baudo, A.; Siech, C.; De Angelis, M.; Tian, Z.; Ahyai, S.; Longo, N.; Chun, F.K.H.; Shariat, S.F.; Briganti, A.; Saad, F.; Karakiewicz, P.I.; Tilki, Derya; Koç University HospitalContext: Although complete surgical resection provides the only means of cure in adrenocortical carcinoma (ACC), the magnitude of the survival benefit of adrenalectomy in metastatic ACC (mACC) is unknown. Objective: This work aimed to assess the effect of adrenalectomy on survival outcomes in patients with mACC in a real-world setting. Methods: Patients with mACC aged 18 years or older with metastatic ACC at initial presentation who were treated between 2004 and 2020 were identified within the Surveillance, Epidemiology, and End Results database (SEER 2004-2020), and we tested for differences according to adrenalectomy status. Intervention included primary tumor resection status (adrenalectomy vs no adrenalectomy). Kaplan-Meier plots, multivariable Cox regression models, and landmark analyses were used. Sensitivity analyses focused on use of systemic therapy, contemporary (2012-2020) vs historical (2004-2011), single vs multiple metastatic sites, and assessable specific solitary metastatic sites (lung only and liver only). Results: Of 543 patients with mACC, 194 (36%) underwent adrenalectomy. In multivariable analyses, adrenalectomy was associated with lower overall mortality without (hazard ratio [HR]: 0.39; P < .001), as well as with 3 months' landmark analyses (HR: 0.57; P = .002). The same association effect with 3 months' landmark analyses was recorded in patients exposed to systemic therapy (HR: 0.49; P < .001), contemporary patients (HR: 0.57; P = .004), historical patients (HR: 0.42; P < .001), and in those with lung-only solitary metastasis (HR: 0.50; P = .02). In contrast, no statistically significant association was recorded in patients naive to systemic therapy (HR: 0.68; P = .3), those with multiple metastatic sites (HR: 0.55; P = .07), and those with liver-only solitary metastasis (HR: 0.98; P = .9). Conclusion: The present results indicate a potential protective effect of adrenalectomy in mACC, particularly in patients exposed to systemic therapy and those with lung-only metastases.Publication Metadata only Exploring emotions through co-speech gestures: the caveats and new directions(SAGE Publications Ltd, 2024) Aslan, Zeynep; Özer, Demet; Department of Psychology; Göksun, Tilbe; Department of Psychology; College of Social Sciences and HumanitiesCo-speech hand gestures offer a rich avenue for research into studying emotion communication because they serve as both prominent expressive bodily cues and an integral part of language. Despite such a strategic relevance, gesture-speech integration and interaction have received less research focus on its emotional function compared to its cognitive function. This review aims to shed light on the current state of the field regarding the interplay between co-speech hand gestures and emotions, focusing specifically on the role of gestures in expressing and understanding both others’ and one's own emotions. The article concludes by addressing current limitations in the field and proposing future directions for researchers investigating gesture-emotion interaction. Our goal is to provide a roadmap to researchers in their exploration of the role of gestures in emotions, ultimately contributing to a more comprehensive understanding of how gestures and emotions intersect.Publication Metadata only Does the holy grail of the evidence pyramid vindicate the controversial practice of endometrial scratching or is there room for healthy skepticism?(Oxford University Press, 2024) N/A; Ata, Mustafa Barış; Kalafat, Erkan; School of MedicineN/APublication Metadata only Deep learning-augmented T-junction droplet generation(Elsevier Inc., 2024) N/A; Department of Mechanical Engineering; Ahmadpour, Abdollah; Shojaeian, Mostafa; Taşoğlu, Savaş; Department of Mechanical Engineering; KU Arçelik Research Center for Creative Industries (KUAR) / KU Arçelik Yaratıcı Endüstriler Uygulama ve Araştırma Merkezi (KUAR); Koç Üniversitesi İş Bankası Yapay Zeka Uygulama ve Araştırma Merkezi (KUIS AI)/ Koç University İş Bank Artificial Intelligence Center (KUIS AI); Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); College of EngineeringDroplet generation technology has become increasingly important in a wide range of applications, including biotechnology and chemical synthesis. T-junction channels are commonly used for droplet generation due to their integration capability of a larger number of droplet generators in a compact space. In this study, a finite element analysis (FEA) approach is employed to simulate droplet production and its dynamic regimes in a T-junction configuration and collect data for post-processing analysis. Next, image analysis was performed to calculate the droplet length and determine the droplet generation regime. Furthermore, machine learning (ML) and deep learning (DL) algorithms were applied to estimate outputs through examination of input parameters within the simulation range. At the end, a graphical user interface (GUI) was developed for estimation of the droplet characteristics based on inputs, enabling the users to preselect their designs with comparable microfluidic configurations within the studied range.Publication Metadata only Selection of ionic liquid electrolytes for high-performing lithium-sulfur batteries: an experiment-guided high-throughput machine learning analysis(Elsevier B.V., 2024) Kılıç, Ayşegül; Abdelaty, Omar; Yıldırım, Ramazan; Eroğlu, Damla; Department of Chemical and Biological Engineering; Zeeshan, Muhammad; Uzun, Alper; Department of Chemical and Biological Engineering; Koç University Tüpraş Energy Center (KUTEM) / Koç Üniversitesi Tüpraş Enerji Merkezi (KÜTEM); Koç University Surface Science and Technology Center (KUYTAM) / Koç Üniversitesi Yüzey Teknolojileri Araştırmaları Merkezi (KUYTAM); Graduate School of Sciences and Engineering; College of EngineeringThe polysulfide (PS) shuttle mechanism (PSM) is one of the most significant challenges of lithium-sulfur (Li-S) batteries in achieving high capacity and cyclability. One way to minimize the shuttle effect is to limit the PS solubilities in the battery electrolyte. Ionic liquids (IL) are particularly suited as electrolyte solvents because of their tunable physical and chemical properties. In this work, thousands of ILs are screened to narrow down potentially viable candidates to be used as electrolytes in Li-S batteries. To that end, the COnductor-like Screening Model for Realistic Solvents (COSMO-RS) calculations are performed over more than 36,000 ILs. An extensive database containing PS solubilities and other relevant properties is constructed at 25 °C. First, the effectiveness of the COSMO-RS calculations is experimentally tested with six different ILs having a wide range of solubility and viscosity values; a strong correlation between the PS solubility and battery performance is obtained. After specifying the target limits for promising ILs using the experimental battery performance data, machine learning (ML) tools are used to predict and identify the relationship between IL properties and PS solubilities and structural and molecular descriptors of ILs. The extreme gradient boosting (XGBoost) method successfully predicts the solubility and property values. Association rule mining (ARM) and the feature importance analysis show that anion descriptors are more dominant, whereas cations have less impact on the solubilities and properties of ILs. Finally, the imidazolium and pyridinium ILs with bis_imide and borate anion groups are identified as the most promising ones.Publication Metadata only Spatial and thermal aware methods for efficient workload management in distributed data centers(Elsevier B.V., 2024) N/A; Department of Computer Engineering; Ali, Ahsan; Özkasap, Öznur; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of EngineeringGeographically distributed data centers provide facilities for users to fulfill the demand of storage and computations, where most of the operational cost is due to electricity consumption. In this study, we address the problem of energy consumption of cloud data centers and identify key characteristics of techniques proposed for reducing operational costs, carbon emissions, and financial penalties due to service level agreement (SLA) violations. By considering computer room air condition (CRAC) units that utilize outside air for cooling purposes as well as temperature and space-varying properties, we propose the energy cost model which takes into account temperature ranges for cooling purposes and operations of CRAC units. Then, we propose spatio-thermal-aware algorithms to manage workload using the variation of electricity price, locational outside and within the data center temperature, where the aim is to schedule the incoming workload requests with minimum SLA violations, cooling cost, and energy consumption. We analyzed the performance of our proposed algorithms and compared the experimental results with the benchmark algorithms for metrics of interest including SLA violations, cooling cost, and overall operations cost. Modeling, experiments, and verification conducted on CloudSim with realistic data center scenarios and workload traces show that the proposed algorithms result in reduced SLA violations, save between 15% to 75% of cooling cost and between 3.89% to 39% of the overall operational cost compared to the existing solutions.Publication Metadata only Optimizing porosity of the catalyst for hydrogen peroxide based thrusters(Elsevier B.V., 2024) Kokal, U.; Yıldız, Y.; Baysal, M.; Department of Mechanical Engineering; Emerce, Nur Ber; Yıldız, Utku Can; Karabeyoğlu, Mustafa Arif; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; College of EngineeringThe texture of the catalyst support is a crucial factor for H2O2 decomposition due to the expansion of H2O2 in monopropellant thrusters, which can lead to overpressure and catalyst breakage. Therefore, alumina supports with 5 wt%, 10 wt%, and 15 wt% microcrystalline cellulose templates were studied to create macropores. MIP and SEM analysis showed that microcrystalline cellulose template increases the macropore fraction. Low-concentration H2O2 decomposition experiments revealed that over 10 wt% microcrystalline cellulose prevented catalyst breakage. Additionally, the thermal durability of the catalyst was studied at different calcination temperatures. Alumina with 15 wt% microcrystalline cellulose and a 900 °C calcination temperature exhibited the highest fracture strength and suitable reaction kinetics. The catalysts were tested in high-concentration H2O2 monopropellant thruster. The results demonstrated enhancement in catalyst size retention, pressure stability, and pressure drop. Introducing macropores through microcrystalline cellulose addition overcomes unstable thruster performance and it extends catalyst lifespan in H2O2 monopropellant thrusters’ applications. © 2023 Elsevier B.V.Publication Metadata only Perspective on smart materials for empowering small-scale manipulation(Elsevier B.V., 2024) Zhang, Mingchao; Department of Mechanical Engineering; Sitti, Metin; Department of Mechanical Engineering; College of Engineering