Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://gcris.khas.edu.tr/handle/20.500.12469/1248
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Article Investigation of the Potential Effect of Complement 5 on Transplantation Outcome by Bioinformatics Tools(Iranian Society of Nephrology, 2025) Oguz, S.R.; Izgi, D.K.; Ozdilli, K.; Karadeniz, S.; Gurer, E.E.; Ciftci, H.S.Introduction. Activation of the complement system following transplantation may result in allograft rejection. Our study aimed to evaluate the potential relationship between factors affecting kidney transplant success and complement 5 (C5) using bioinformatic tools. Methods. GenCards and Genemania were used to provide the genetic functional information belonging to the C5 gene, and genomic browsers of STRING, UCSC, KEGG were used to reveal interactions with other genes and various pathways. MiRDB was used to specify the miRNAs that were associated with the C5 gene. The UniProt database was used to determine the tissues that expressed the C5 gene using protein-protein interactions. Results. In the bioinformatic analyses performed, high levels of C5 gene expression were found in the naiive kidney. Twenty-five genes were found to be strongly associated with C5. Fifty-four miRNAs targeting the C5 gene were specified. The C5 gene was found to be involved in biologic processes such as complement activation (FDR = 6.46e-22), complement binding (FDR = 2.20e-06), cytolysis (FDR = 4.82e-14), regulation of complement activation (FDR = 4.08e-24), positive regulation of vascular endothelial growth factor production (FDR = 0.0430), regulation of macrophage chemotaxis (FDR = 0.0447), activation of the immune response (FDR = 1.26e-13), leukocyte-mediated immunity (FDR = 1.41e-09), innate immune response (FDR = 3.05e-09), allograft rejection (FDR = 2.40e-12), oxidative injury response (FDR = 0.00016), and trigerring of the beginning of the complement cascade (FDR = 0.0244). Conclusions. The data obtained in this study will be used to guide future experimental investigations in the field of transplantation, and these data will give physicians with insight into allograft status following transplantation. © 2025, Iranian Society of Nephrology. All rights reserved.Article A Hybrid Rough Aggregation Approach for the Selection of Artificial Intelligence-Based Industrial Cleaning Robots Used in Public Spaces From the Perspective of Urban Waste Management(Elsevier Ltd, 2025) Görçün, Ö.F.; Saha, A.; Ravi Kumar, P.V.; Debnath, B.K.Waste management is becoming increasingly complex and challenging, especially in megacities with large populations. Unlike the past, when urban waste was simply collected and disposed of, modern waste management requires careful planning and execution of collection, separation, recycling, and reuse processes. Effective management of this complex system now needs more than just human effort. Integrating artificial intelligence (AI)-based systems into waste management can enhance waste reduction, reuse, and recycling effectiveness and efficiency. Selecting suitable AI-based cleaning robots (AI-ICR) for crowded public spaces, such as stations, train stations, and airports, poses complex decision-making challenges. The primary challenge is the novelty of the technology, which leads to uncertainties in selecting AI-ICRs. To address this challenge, we have developed a decision-making approach based on rough Archimedean-Dombi partitioned aggregation. This approach, termed “rough Archimedean-Dombi partitioned aggregation,” combines the flexibility of Archimedean operators, the smoothness of Dombi operators, and the structured decomposition of Partitioned operators. This model is mainly chosen for its ability to handle the uncertainty and complexity inherent in multiple criteria decision-making (MCDM) processes. Leveraging rough numbers provides a robust framework for evaluating AI-ICRs under uncertain conditions. The main advantage of this model is its robustness, consistency, stability, and ability to handle complex uncertainties. We applied the proposed model to assess four AI-ICR alternatives identified through extensive research. We evaluated these alternatives using eighteen criteria established through comprehensive field studies. Based on the results, “Recycling cost (B12)” emerged as the most crucial criterion for selecting AI-ICRs. Additionally, the research identifies the SD45 manufactured by Peppermint Robotics Co. as the optimal AI-ICR candidate. Finally, the sensitivity and benchmark analyses to validate the proposed model confirm its robustness, consistency, and reliability. © 2024 Elsevier LtdArticle A Nano-Design of a Quantum-Based Arithmetic and Logic Unit for Enhancing the Efficiency of the Future Iot Applications(American Institute of Physics, 2025) Ahmadpour, S.S.; Zaker, M.; Navimipour, N.J.; Misra, N.K.; Zohaib, M.; Kassa, S.; Hakimi, M.The Internet of Things (IoT) is an infrastructure of interconnected devices that gather, monitor, analyze, and distribute data. IoT is an inevitable technology for smart city infrastructure to ensure seamless communication across multiple nodes. IoT, with its ubiquitous application in every sector, ranging from health-care to transportation, energy, education, and agriculture, comes with serious challenges as well. Among the most significant ones is security since the majority of IoT devices do not encrypt normal data transmissions, making it easier for the network to breach and leak data. Traditional technologies such as CMOS and VLSI have the added disadvantage of consuming high energy, further creating avenues for security threats for IoT systems. To counter such problems, we require a new solution to replace traditional technologies with a secure IoT. In contrast to traditional solutions, quantum-based approaches offer promising solutions by significantly reducing the energy footprint of IoT systems. Quantum-dot Cellular Automata (QCA) is one such approach and is an advanced nano-technology that exploits quantum principles to achieve complex computations with the advantages of high speed, less occupied area, and low power consumption. By reducing the energy requirements to a minimum, QCA technology makes IoT devices secure. This paper presents a QCA-based Arithmetic Logic Unit (ALU) as a solution to IoT security problems. The proposed ALU includes more than 12 logical and arithmetic operations and is designed using majority gates, XOR gates, multiplexers, and full adders. The proposed architecture, simulated in QCADesigner 2.0.3, achieves an improvement of 60.45% and 66.66% in cell count and total occupied area, respectively, compared to the best of the existing designs, proving to be effective and efficient. © 2025 Author(s).Article Balancing Aspiration and Reality: Autarky in Turkish Defence Industrial Policy(Routledge, 2025) Kurç, Ç.; Güvenç, S.; Mevlütoğlu, A.; Egeli, S.Countries with limited financial resources, internal markets, and human resources, such as Turkey, face significant challenges in achieving defence autarky and competing with multinational corporations in the international arms market. Consequently, the literature suggests that these countries should adjust their defence industrialisation goals to match their financial capabilities. However, Turkish decision-makers maintain a public discourse emphasising the goal of defence autarky despite the defence industry’s financial crises and structural problems. Even though there is a growing recognition of the limits of the pursuit of defence autarky, Turkey still needs to devise a defence industrial policy focusing on niche markets. This paper argues that the persistent rhetoric of defence autarky enjoys very strong public appeal in domestic politics. Defence industrialisation, coupled with nationalism, creates a zone of impunity for the ruling party. This dynamic allows the ruling party to deflect criticism by highlighting successes in defence production, directly appealing to nationalist sentiments. Ultimately, the political gains for the ruling elites outweigh financial limitations, preventing an open shift toward a more moderate defence industrialisation goal. © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.Article Narratives of Preterm and Full-Term Preschool-Aged Children: Analyses of Different Narrative Dimensions(John Wiley and Sons Ltd, 2025) Akkan, İ.; Esmer, Ş.C.; Doğan, I.; Aktan Erciyes, A.; Demir-Lira, Ö.E.; Göksun, T.Preterm birth increases the likelihood of early language and cognitive delays, but less is known about later aspects of language development, such as narrative generation. Narrative skills involve dimensions, such as linguistic and narrative complexity, and preterm (PT) and full-term (FT) children's narrative performances may vary across these dimensions. We investigated the role of neonatal status on the total number of words produced, linguistic complexity, and narrative complexity across two presentation modes: narrative generation while seeing pictures and narrative generation after watching an animated video. Seventy-one Turkish-reared preschool-aged children (31 PT [Mage = 48.70, SD = 1.53] and 40 FT [Mage = 48.83, SD = 1.63]) participated in the study. Despite having lower expressive vocabulary skills (assessed by a standardized task) than full-term children, preterm children performed comparably in both picture and animated video-stories, except PT children tended to produce longer narratives in the picture story, possibly due to the different demand characteristics of the tasks. Overall, our findings support the possibility of interacting factors that may help PT children overcome challenges in narrative development. © 2025 The Author(s). British Journal of Developmental Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.Conference Object Enhancing Cybersecurity in Critical Infrastructure: Utilizing Random Forest Ai Model for Threat Detection(Springer Science and Business Media Deutschland GmbH, 2025) Jamil, M.; Creutzburg, R.Securing critical infrastructures is essential to reducing risks in the rapidly evolving digital world. Traditional manual techniques of threat identification during cyberattacks are becoming less and less effective due to the limitations of human labor and the necessity for prompt responses. AI-based threat detection is a powerful solution that uses AI to identify, classify, and mitigate the effects of cyberattacks. Over the past five years, selecting appropriate AI and machine learning algorithms to evaluate threats in critical infrastructure protection has grown to be a significant challenge. Moreover, AI-driven threat detection must be seamlessly integrated into critical infrastructure cybersecurity. This work proposes a Supervised Learning model, a type of machine learning where the algorithm is trained on a labeled dataset, called the Random Forest algorithm for threat detection. The procedure entails thorough preprocessing and data accumulation from the NSL-KDD vulnerabilities database. The Random Forest model, known for its reliability, analyzes refined data and is skilled in identifying current risks and forecasting future ones. The study showcases the high accuracy and reliability of the model, with an accuracy score of 99.90% and a false positive rate of less than 15% for every assault category. These results underscore the effectiveness of the research in producing a reliable and accurate cybersecurity model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.Article Design of Secure Multi-User Coded-Ssk With Index Selecting Capability(Institute of Electrical and Electronics Engineers Inc., 2025) Hassan, S.; Panayirci, E.; Helleseth, T.; Vincent Poor, H.We propose a new coded space shift keying (CSSK) signaling technique for multi-user (MU), multiple-input multiple-output (MIMO) communication systems incorporating physical layer security (PLS). Besides its error correction ability, the designed linear code is capable of choosing transmit antenna indices automatically and selecting the best set of antenna combinations that minimizes the bit error rate (BER). Results obtained for the single-user (SU) schemes are then extended to a general single-cell downlink MU CSSK setting. A precoder design is proposed with a maximum ratio combining (MRC) technique to eliminate the multi-user interference (MUI) entirely by taking advantage of channel state information (CSI) at the transmitter. It is shown that the same precoding provides a very effective jamming signal for the PLS against passive eavesdroppers, degrading their signal-to-interference-plus-noise ratio (SINR) severely. A closed-form expression for the achievable secrecy rates is derived and it is maximized by the proposed power allocation algorithm. Finally, it is shown analytically and by computer simulations that substantially better BER performance is achieved by each user over interference-free transmission compared to an SU transmission with a maximum likelihood (ML) detector. © 1972-2012 IEEE.Article Predicting User Purchases From Clickstream Data: a Comparative Analysis of Clickstream Data Representations and Machine Learning Models(Institute of Electrical and Electronics Engineers Inc., 2025) Aylin Tokuc, A.; Dag, T.Predicting purchase events from e-commerce clickstream data is a critical challenge with significant implications for optimizing marketing strategies and enhancing customer experience. This study addresses this challenge by systematically evaluating and comparing multiple data representations - aggregated session attributes, recent user actions, and hybrid combinations - which bridges gaps in the existing literature and demonstrates the superiority of hybrid approaches. Unlike prior research, which typically focuses on single representations, our approach combines aggregated session-level summaries with granular, sequential user actions to capture both long-term and short-term behavioral patterns. Through comprehensive experimentation, we compared multiple machine learning models, including LightGBM, decision trees, gradient boosting, SVC, and logistic regression, using real-world e-commerce clickstream data. Notably, the hybrid representation with LightGBM achieved superior predictive performance, significantly outperforming alternative methods. Feature importance analysis revealed key factors influencing purchase likelihood, such as time since the last event, session duration, and product interactions. This study provides actionable insights into real-time marketing interventions by demonstrating the practical utility of hybrid data representations and efficient tree-based models. Our findings offer a scalable and interpretable framework for e-commerce platforms to enhance purchase predictions and optimize marketing strategies. © 2013 IEEE.Conference Object Data-Driven Local Control Design for Dead Band Control of Load Tap Changers(Institute of Electrical and Electronics Engineers Inc., 2024) Savasci, A.; Ceylan, O.; Paudyal, S.This study presents an off-line optimization-guided machine learning approach for coordinating the local control rules of on-load tap changers (OLTCs) and step-voltage regula-tors (SVRs). Based on a bang-bang control rule, these legacy devices autonomously regulate the feeder voltage around the nominal level by varying the tap position in the lower or raise direction. The characterizing parameter of the local control rule is the dead band, which affects the number of tap switching in operation and is directly related to the economical use life of the equipment. The bandwidth is typically set within a standard voltage range and is generally kept constant in daily operation. However, adjusting the bandwidth dynamically can prevent excessive tap switching while maintaining satisfactory voltage regulation for varying loading and distributed generation conditions. Our approach aims to set the bandwidth parameter systematically and efficiently through a machine learning-based scheme, which is trained with a dataset formed by solving the distribution network optimal power flow (DOPF) problem. The performance of learning the bandwidth parameter is demonstrated on the modified 33-node feeder, which is promising for integrated voltage control schemes. © 2024 IEEE.Conference Object An Ant-Lion Optimization Based Approach To Solve Phase Balancing Problem in Distribution Networks(Institute of Electrical and Electronics Engineers Inc., 2024) Yesilyurt, G.; Ceylan, O.Phase unbalance is a significant issue for power distribution networks. It can lead to increased energy losses and voltage instability, undermining the electrical grid's reliability and efficiency. We propose an approach to minimize voltage unbalance through reactive power management from PV instal-lations and the optimization of charging/discharging of energy storage devices utilizing a control algorithm based on Ant-Lion Optimizer. We tested the approach on the IEEE 123-Bus Test System, incorporating PV generations by daily simulations. From the results, the combined operation of reactive power support from PVs and Storage Units with the help of the ALO algorithm offers a promising solution to the phase unbalance problem. © 2024 IEEE.Article Integration of Emerging Technologies in Tourism and Hospitality Curriculum: an International Perspective(Elsevier Sci Ltd, 2025) Baser, Mirac Yucel; Kozak, Metin; Buyukbes, TubaThis paper investigates the status of emerging technologies, how they can be integrated into the curriculum, the skills students can acquire through these technologies, and the employment opportunities they create in the tourism and hospitality industry. In the study, a content analysis was conducted on the curriculum of 65 undergraduate tourism and hospitality management programs, followed by an analysis of data from 28 academics to explore the role of emerging technologies in the curriculum. We have observed six core topics. Technology courses had the lowest proportion. We further observe four categories of skills that emerging technologies may provide students, highlighting their potential to shape future career opportunities. Building on these findings, the current study contributes to the literature by linking these skill sets - digital and technological, theoretical, operational, and managerial - to emerging job roles such as virtual reality tour designers, competent tourism developers, and AI-driven marketing specialists. Furthermore, the study identifies the domains where emerging technologies have the most relevance and outlines which purpose they may be included in the tourism and hospitality curriculum as a course. Thus, it forwards previous studies emphasizing the importance of emerging technologies. The study also suggests the implications for the literature, practice, and public policies.Book Part Cloud-Based Development Environments: Paas(Wiley, 2016) Aydin, M.N.; Perdahci, N.Z.; Odevci, B.In this chapter we elaborate the fundamentals of platform as a service (PaaS) and outline core components of a typical PaaS. We focus on a specific cloud-computing layer, which is called application platform as a service (aPaaS). Emergence of this layer raises several questions regarding the existence of traditional development environments, tools, and the viability of alternative ecosystems along with new positions in the market. It is this questioning that shows the need for making sense of what underpins the very idea of aPaaS and how the idea is manifested in the market, and finally what implications can be drawn for academics and practitioners We articulate basic approaches to aPaaS and discuss metadata aPaaS by using our industry experience as well as a review of recent studies on this subject. This leads to a concise comparison of leading PaaS solutions. © 2016 John Wiley & Sons, Ltd.Article Fictitious Conspiracy, Paranormal, and Pseudoscience Beliefs Are Closely Related To Their Regular Counterparts(Springer, 2025) Alper, Sinan; Elcil, Tugcenaz; Karaca, Nazif; Bayrak, Fatih; Yilmaz, OnurcanBelief in various types of Epistemically Suspect Beliefs (ESBs), such as conspiracy theories, paranormal phenomena, and pseudoscientific claims, tends to strongly correlate. However, the use of ESB scales in the literature, which often include phenomena frequently encountered in daily life with familiar content, challenges the clarity of inferences about this relationship. To address this issue, we developed a scale for Fictitious Epistemically Suspect Beliefs (FESBs), composed entirely of novel and fabricated statements related to conspiracy, paranormal activity, and pseudoscience. In Study 1, with a Turkish sample of 448 participants, we found that FESBs positively correlated with ESBs, despite consisting of less familiar claims. Moreover, both FESBs and ESBs showed similar associations with individual differences in worldview and cognition. These findings were replicated in a larger Turkish sample (N = 786) in Study 2, and a UK sample (N = 746) in Study 3. The results indicate that individuals with higher ESBs are more likely to endorse FESBs, despite having never encountered these claims before.Article Cognitive Styles and Behavioral Systems: Linking Looming Cognitive Style and Reinforcement Sensitivity(Pergamon-elsevier Science Ltd, 2025) Altan-Atalay, Ayse; Gokdag, Ceren; King, NazBackground: Looming cognitive style, with its social and physical subtypes, is highly influential on how individuals perceive and respond to threats. Despite its robust relationship with anxiety, its relationship with other traits is underexplored. Revised reward sensitivity theory also addresses individual differences in approach, avoidance, and susceptibility to fear and anxiety. The current study examined associations of behavioral activation (BAS), inhibition (BIS), and fight-flight-freeze systems (FFFS) with social and physical looming. Method: Data were collected online from 401 adults (343 women) between the ages 18 and 65 (M = 22.78 (SD = 6.57) using measures of looming cognitive style, reinforcement sensitivity, anxiety, and depression. Results: The findings showed that social and physical looming were positively associated with BIS and FFFS, controlling for age, gender, and anxiety and depression symptoms. Additionally, social looming was negatively associated with BAS. Conclusions: The findings indicate that social and physical looming are linked to heightened sensitivity to threat and, in the case of social looming, reduced reward sensitivity. These results underscore the role of looming cognitive style in shaping anxiety-related behaviors and responses to environmental stimuli.Article Redistribution Trends in Turkey: Unintended Consequences Vs. Deliberate Policies(Wiley, 2025) Tekguc, Hasan; Eryar, DegerWe investigate the impact of taxes, transfers, and social spending on inequality in Turkey during the first two decades of the 21st century. We employ Household Budget Surveys from 2003, 2007, 2011, 2015, and 2019 to estimate market, pension as deferred income, gross, disposable, consumable, and final incomes following the framework developed by the Commitment to Equality Institute. We show that the equality-enhancing effect of total taxes and transfers became more noticeable, resulting in a larger decline in the Gini coefficient from 2003 (12 percentage points) to 2019 (17 percentage points). A large part of the higher equality-enhancing impact over time is accounted for by the unintended consequences of structural changes, past policies, and demographic trends. We focus on the forbearance of self-employment and capital income under-reporting, the endurance of past pension policies, the effect of the declining fertility rate, and explicit policy choices in the areas of health and social assistance. Compared to Latin American countries, the Turkish welfare system redistributes more, especially through the pension system, but also causes relatively higher fiscal impoverishment for low-income households due to the disproportionately high share of indirect taxes.Article Evaluation of the Sensitivity of Pbl and Sgs Treatments in Different Flow Fields Using the Wrf-Les at Perdigão(Mdpi, 2025) Yilmaz, Erkan; Mentes, Sukran Sibel; Kirkil, GokhanThis study investigates the effectiveness of the large eddy simulation version of the Weather Research and Forecasting model (WRF-LES) in reproducing the atmospheric conditions observed during a Perdig & atilde;o field experiment. When comparing the results of the WRF-LES with observations, using LES settings can accurately represent both large-scale events and the specific characteristics of atmospheric circulation at a small scale. Six sensitivity experiments are performed to evaluate the impact of different planetary boundary layer (PBL) schemes, including the MYNN, YSU, and Shin and Hong (SH) PBL models, as well as large eddy simulation (LES) with Smagorinsky (SMAG), a 1.5-order turbulence kinetic energy closure (TKE) model, and nonlinear backscatter and anisotropy (NBA) subgrid-scale (SGS) stress models. Two case studies are selected to be representative of flow conditions. In the northeastern flow, the MYNN NBA simulation yields the best result at a height of 100 m with an underestimation of 3.4%, despite SH generally producing better results than PBL schemes. In the southwestern flow, the MYNN TKE simulation at station Mast 29 is the best result, with an underestimation of 1.2%. The choice of SGS models over complex terrain affects wind field features in the boundary layer more than above the boundary layer. The NBA model generally produces better results in complex terrain when compared to other SGS models. In general, the WRF-LES can model the observed flow with high-resolution topographic maps in complex terrain with different SGS models for both flow regimes.Article Influence of a Perspective Oriented Task, Executive Function, and Trait Perspective Taking on Efl Writing(Pergamon-elsevier Science Ltd, 2025) Coskun, Turgut; Aptoula, Nur YigitogluThis study adopted a cognitive approach and investigated the effect of a writing task on the passages composed by B2-level EFL learners by considering their executive function and trait perspective-taking capabilities. The experimental group was exposed to a perspective-oriented writing task. Most importantly, they were asked to read three short messages shared by their audience, then take their perspective and write down whatever came to their minds. A perspective-neutral control group was also asked to read the messages but was not encouraged to take the audience's perspective. They were just asked to write down whatever came to their minds. Then, both groups tried to write a convincing passage and completed four executive function tasks and a trait perspective-taking scale. The results revealed that exposing B2-level EFL learners to a perspective-oriented task increased the overall writing quality of the participants if they have high executive function or trait perspective-taking capabilities. These findings confirm the importance of a task for directing and managing cognitive resources and show the executive function's central role and trait perspective-taking's importance in writing. The tasks that encourage employing these individual resources may enrich the instructor toolboxes.Article Green Transition for Turkey: Growth, Employment, and Trade Deficit Effects(Elsevier Sci Ltd, 2025) Gozkun, Kubra Atik; Orhangazi, OzgurThis study examines the potential economic impacts of Turkey's energy transition by focusing on the effects of solar and wind energy investments. With Turkey aiming for "net zero" emissions by 2053, this research evaluates the impacts on total emissions, economic growth, employment, and the trade deficit under various scenarios. Utilizing input-output analysis and the employment factor approach, we analyze the macroeconomic and emission outcomes of a 10-year clean energy investment project targeting the transformation of the energy sector. Our findings indicate that investing in solar and wind energy could reduce Turkey's greenhouse gas emissions by 28-77 percent of 2020 emission levels. These investments are projected to enhance economic growth, contributing an additional 0.6%-1.8% of 2020 GDP annually on average. The employment effects are also significant, with total potential job creation amounting to a total of 1.3%-3.4% of Turkey's labor force in 2020. Furthermore, the investments are expected to improve the trade balance by 6.9-14.6 billion dollars over 10 years. The results suggest that green energy investments can simultaneously achieve environmental goals and promote economic stability through job creation and improve trade balances.Editorial Revitalizing Tourism Research(Pergamon-elsevier Science Ltd, 2025) Buckley, Ralf; Kozak, Metin; Wen, Jun; Cooper, Mary-AnnArticle Exploring Women's Visceral Engagement With Electric Appliances in Turkish Kitchens(Springernature, 2025) Karaosmanoglu, Defne; Ata, Leyla Bektas; Emgin, BaharThis paper investigates the narratives and experiences of women regarding cooking with small electric appliances. It intends to offer a novel perspective on gender and technology studies by foregrounding the visceral dimensions of these encounters. Drawing from a larger project on the historical representations and lived experiences of domestic technologies in Turkey, it highlights how the embodied dimensions of cooking shape the ways women perceive, adapt, and integrate technology into their daily lives. This study is based on interviews with twenty-seven women across five cities in Turkey conducted between 2022 and 2024. While small electric appliances are often marketed for convenience and efficiency, we argue that focusing solely on their instrumental benefits neglects the complex and visceral ways women engage with technology. A visceral approach remains an undervalued lens for understanding these interactions, particularly as women's embodied knowledge and relationships to kitchen appliances challenge scholarship that prioritizes progress and efficiency. As active agents, many women resist these technologies, viewing them as misaligned with the embodied knowledge and practices integral to cooking. By reevaluating the relationship between food, gender, and technology, we propose that such disengagement challenges the positivist reliance on science and technology, emphasizing the importance of embodied knowledge and everyday practices in shaping women's interactions with technology.
