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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Publication 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 Discrete memories of a continuous world: a working memory perspective on event segmentation(Elsevier B.V., 2024) Güler, Berna; Uysal, Bilge; Günseli, Eren; Adıgüzel, Zeynep; Graduate School of Social Sciences and HumanitiesWe perceive the world in a continuum but remember our past as discrete episodic events. Dominant models of event segmentation suggest that prediction errors or contextual changes are the driving factors that parse continuous experiences into segmented events. These models propose working memory to hold a critical role in event segmentation, yet the particular functioning of working memory that underlies segmented episodic memories remains unclear. Here, we first review the literature regarding the factors that result in the segmentation of episodic memories. Next, we discuss the role of working memory under two possible models regarding how it represents information within each event and suggest experimental predictions. Clarifying the contributions of working memory to event segmentation is important to improve our understanding of the structure of episodic memories.Publication Metadata only Metric-bourbaki algebroids: cartan calculus for m-theory(Elsevier, 2024) Çatal-Özer, Aybike; Doğan, Keremcan; Department of Physics; Dereli, Tekin; Department of Physics; College of SciencesString and M theories seem to require generalizations of usual notions of differential geometry on smooth manifolds. Such generalizations usually involve extending the tangent bundle to larger vector bundles equipped with various algebroid structures such as Courant algebroids, higher Courant algebroids, metric algebroids, or G-algebroids. The most general geometric scheme is not well understood yet, and a unifying framework for such algebroid structures is needed. Our aim in this paper is to propose such a general framework. Our strategy is to follow the hierarchy of defining axioms for a Courant algebroid: almostCourant - metric - pre -Courant - Courant. In particular, we focus on the symmetric part of the bracket and the metric invariance property, and try to make sense of them in a manner as general as possible. These ideas lead us to define new algebroid structures which we dub Bourbaki and metric-Bourbaki algebroids, together with their almostand pre -versions. For a special case of metric-Bourbaki algebroids that we call exact, we construct a collection of maps which generalize the Cartan calculus of exterior derivative, Lie derivative and interior product. This is done by a kind of reverse -mathematical analysis of the Severa classification of exact Courant algebroids. By abstracting crucial properties of this collection of maps, we define the notion of Bourbaki calculus. Conversely, given an arbitrary Bourbaki calculus, we construct a metric-Bourbaki algebroid by building up a standard bracket that is analogous to the Dorfman bracket. Moreover, we prove that any exact metric-Bourbaki algebroid satisfying some further conditions has to have a bracket that is the twisted version of the standard bracket; a partly analogous result to Severa classification. We prove that many physically and mathematically motivated algebroids from the literature are examples of these new algebroids, and when possible we construct a Bourbaki calculus on them. In particular, we show that the Cartan calculus can be seen as the Bourbaki calculus corresponding to an exact higher Courant algebroid. We also point out examples of Bourbaki calculi including the generalization of the Cartan calculus on vector bundle valued forms. One straightforward generalization of our constructions might be done by replacing the tangent bundle with an arbitrary Lie algebroid A. This step allows us to define an extension of our results, A -version, and extend our main results for them while proving many other algebroids from the literature fit into this framework.Publication Metadata only Rethinking news trust in post-truth Turkey: immediacy as the imagined affordance of television and search engines(SAGE PUBLICATIONS INC, 2024) Department of Media and Visual Arts; Çamurdan, Suncem Koçer; Ünal, Nazlı Özkan; Department of Media and Visual Arts; College of Social Sciences and HumanitiesIn today's post-truth world, news users grapple with the tension between growing distrust in news institutions and the need for "true" information. Based on a mixed-methods study conducted in Turkey, this paper examines strategies developed by news users to establish trust in media tools in the context of the COVID-19 pandemic and populist polarization. We first collected data with a nationally representative survey (N = 1089). Then, 30 media users filled out media diaries for 1 week. We interviewed diary participants at the end of the week. We also conducted a four-week-long participant observation in three locations. Based on this data, we argue that users build trust in news stories by attributing a sense of immediacy to specific media, namely television and search engines. This immediacy arises from people's desire to scrutinize the accuracy of news stories in Turkey's highly polarized media environment. We term this ascribed meaning of transparency the imagined affordance of immediacy, asserting that immediacy is crucial for forming trust in the post-truth era. Contrary to suggestions that news trust is diminishing in the post-truth era, our paper highlights citizens' creative strategies to reestablish trust in contemporary news media.Publication Metadata only Objective-free ultrasensitive biosensing on large-area metamaterial surfaces in the near-IR(AMER CHEMICAL SOC, 2024) Department of Physics; Ramazanoğlu, Serap Aksu; Öktem, Evren; Department of Physics; College of Sciences; Graduate School of Sciences and EngineeringPlasmonic metamaterials have opened new avenues in medical diagnostics. However, the transfer of the technology to the markets has been delayed due to multiple challenges. The need of bulky optics for signal reading from nanostructures patterned on submillimeter area limits the miniaturization of the devices. The use of objective-free optics can solve this problem, which necessitates large area patterning of the nanostructures. In this work, we utilize laser interference lithography (LIL) to pattern nanodisc-shaped metamaterial absorber nanoantennas over a large area (4 cm(2)) within minutes. The introduction of a sacrificial layer during the fabrication process enables an inverted hole profile and a well-controlled liftoff, which ensures perfectly defined uniform nanopatterning almost with no defects. Furthermore, we use a macroscopic reflection probe for optical characterization in the near-IR, including the detection of the binding kinematics of immunologically relevant proteins. We show that the photonic quality of the plasmonic nanoantennas commensurates with electron-beam-lithography-fabricated ones over the whole area. The refractive index sensitivity of the LIL-fabricated metasurface is determined as 685 nm per refractive index unit, which demonstrates ultrasensitive detection. Moreover, the fabricated surfaces can be used multiple times for biosensing without losing their optical quality. The combination of rapid and large area nanofabrication with a simple optical reading not only simplifies the detection process but also makes the biosensors more environmentally friendly and cost-effective. Therefore, the improvements provided in this work will empower researchers and industries for accurate and real-time analysis of biological systems.Publication Metadata only On the past, present, and future of the Diebold-Yilmaz approach to dynamic network connectedness(Elsevier Science Sa, 2023) Diebold, Francis X.; Department of Economics; Yılmaz, Kamil; Department of Economics; College of Administrative Sciences and EconomicsWe offer retrospective and prospective assessments of the Diebold-Yilmaz connected-ness research program, combined with personal recollections of its development. Its centerpiece in many respects is Diebold and Yilmaz (2014), around which our discussion is organized.Publication Metadata only Solar-light-driven photocatalytic hydrogen evolution activity of gCN/WS2 heterojunctions incorporated with the first-row transition metals(Elsevier Science Sa, 2023) Acar, Eminegul Genc; Aslan, Emre; Patir, Imren Hatay; Department of Chemistry; Yılmaz, Seda; Eroğlu, Zafer; Metin, Önder; Department of Chemistry; 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 SciencesThe design of semiconductor-based heterojunctions is an effective strategy to build highly active photo-catalyst systems. In this study, tungsten disulfide (WS2) modified graphitic carbon nitride (gCN) hetero-junction (gCN/WS2) is incorporated with Co and Ni (gCN/WS2-Co and gCN/WS2-Ni) to enhance the photocatalytic hydrogen evolution reaction (HER) activity of gCN/WS2 via performing a chemical reduction method and characterized by advanced analytical techniques. The photocatalytic HER activities of gCN, gCN/ WS2, gCN/WS2-Ni and gCN/WS2-Co were measured as 0.126, 0.221, 0.237 and 0.249 mmol g-1h-1, respec-tively, under the visible light irradiation. The improvement of photocatalytic activity and stability of gCN/ WS2-Ni and gCN/WS2-Co nanocomposites could be attributed to the 2D/2D heterojunction structure, ex-tended light harvesting ability, increased electron-hole lifetime and decreased recombination rate of the charge carriers. Moreover, mechanistic studies revealed that a S-scheme heterojunction is attributed to the enhanced photocatalytic HER by the gCN/WS2-Ni and gCN/WS2-Co photocatalysts, which provides pro-moted efficiency by photocarrier transfer and separation.Publication Metadata only Endometriosis and adenomyosis: shared pathophysiology(Elsevier Science Inc, 2023) Bulun, Serdar E.; Adli, Mazhar; Chakravarti, Debabrata; Parker, James Brandon; Milad, Magdy; Yang, Linda; Chaudhari, Angela; Tsai, Susan; Wei, Jian Jun; Yin, Ping; Yıldız, Şule; School of MedicineEndometriosis and adenomyosis are closely related disorders. Their pathophysiologies are extremely similar. Both tissues originate from the eutopically located intracavitary endometrium. Oligoclones of endometrial glandular epithelial cells with somatic mutations and attached stromal cells may give rise to endometriosis if they travel to peritoneal surfaces or the ovary via retrograde menstruation and/or may be entrapped in the myometrium to give rise to adenomyosis. In both instances, the endometrial cell populations possess survival and growth capabilities conferred by somatic epithelial mutations and epigenetic abnormalities in stromal cells. Activating mutations of KRAS are the most commonly found genetic variant in endometriotic epithelial cells, whereas the adenomyotic epithelial cells almost exclusively bear KRAS mutations. Epigenetic abnormalities in the stromal cells of endometriosis and adenomyosis are very similar and involve an abnormal expression pattern of nuclear receptors, including the steroid receptors. These epigenetic defects give rise to excessive local estrogen biosynthesis by aromatase and abnormal estrogen action via estrogen receptor-b. Deficient progesterone receptor expression results in progesterone resistance in both endometriosis and adenomyosis.