5916 research outputs found
Sort by
Societal happiness and corporate cash holdings: The contingency role of climate policies
No full textAlthough prior research on the determinants of corporate cash holdings has highlighted the importance of institutional and societal characteristics, the role of several national-level factors and the boundaries of their influence remain underexplored. This paper aims to address this gap by examining the effects of societal happiness and climate policies on corporate cash holdings. It specifically argues that both societal happiness and climate policies reduce firms' cash holdings, and that climate policies weaken the negative effect of societal happiness on cash holdings. Using Multi-Way Fixed Effects (FE) models on an unbalanced panel dataset of non-financial firms from eight countries between 2013 and 2022, the findings support these arguments. This study extends the literature on corporate cash holdings by demonstrating how socio-emotional conditions and climate policies/environmental performance jointly shape firms’ cash holdings
Deep learning based classification and latency prediction in abr signals abr sinyallerinde derin grenme temelli siniflandirma ve latans tahmini
No full textThis paper proposes a CNN-based deep learning approach for detecting and identifying the fifth peak (Wave V) in Auditory Brainstem Response (ABR) signals. By performing two tasks: accurately predicting the peak location of wave V (R2 = 0.91) and classifying its presence (accuracy = 89.9%). These results demonstrate the potential of deep learning to enhance the precision and efficiency of auditory diagnostics while reducing manual interpretation efforts.TÜBİTA
Determination of integrated stem teacher competencies: A modified delphi method
No full textDetermination of integrated STEM teacher competencies for the effective use of STEM education is important in terms of managing the learning process and performing STEM integration effectively. More studies are needed to identify and describe STEM teacher competencies as a result of comprehensive research. The purpose of this research was to constitute integrated STEM teacher competencies for secondary education by taking the opinions of the STEM experts. The research was carried out via three-round modified Delphi method and validation stage. The following four competency areas were defined within the scope of integrated STEM teacher conceptual framework: Cognitive Characteristics in STEM Teaching, STEM Teaching Skills, Affective-Motivational Characteristics in STEM Teaching, and Collaboration and Engagement Skills. Under these competency areas, 14 competencies and 58 competence indicators were determined. This study would be a guiding framework for the development of STEM teacher education programs at the undergraduate or graduate levels.Publisher versio
Leveraging unlabeled data in federated learning: A review
No full textIn centralized machine learning, both the data and model to be trained reside on a single server, which may cause problems regarding data privacy as sensitive or personal data need to be transferred from clients to the server. Federated learning has been proposed to provide a solution to this problem by allowing the training of a model without the data leaving the clients. This training takes place between a coordinating server and the clients by continuously exchanging the model parameters instead of exchanging data. In real-life applications, the data on some of the clients or the server may be partially labeled or completely unlabeled, which poses a severe challenge to federated learning. In this paper, we present a survey of recently proposed methods that leverage unlabeled data in a federated learning setting to improve model performance. We also present a novel taxonomy of the methods that leverage unlabeled data based on whether the unlabeled data is assigned a pseudo-label during the process or not. We summarize the datasets, main data modalities, and application areas of federated learning with unlabeled data methods in the literature and highlight future research directions. We believe that this survey will be a useful guide for researchers planning to work on federated learning with partially labeled data.TÜBİTAKPublisher versio
Adaptive multi-uav coordination for heterogeneous target search and connect missions using proximal policy optimization
No full textA novel multi-agent reinforcement learning (MARL) technique utilizing Proximal Policy Optimization (PPO) is introduced to coordinate a drone team in search and rescue operations, where multiple targets with different connectivity requirements are present. The proposed approach integrates a dynamic reward system that effectively manages the trade-off between exploration, target identification, and network connectivity. The model is trained for a fixed target type and area size, but is evaluated for scenarios with different numbers of UAVs, diverse target configurations, and mission priorities, including target search and information updates, illustrating its adaptability and versatility in comparison to common methods.TÜBİTA
Geographical analysis of the european air cargo network: a comparative study from Pre-COVID-2019 to pandemic-impacted 2021
No full textThis study analyzes the structure of the European air cargo network by applying complex network analysis to Eurostat’s air cargo data from 291 airports in 2019 (pre-pandemic) and 260 airports in 2021 (pandemic-impacted), across 44 European countries. The results identify Leipzig, Cologne, and Paris Charles de Gaulle as key cargo hubs whose central roles strengthened during the pandemic. While the overall network structure remained stable, increased concentration around major hubs and fewer, more centralized clusters emerged in 2021. The findings highlight the resilience of Europe’s air cargo network and emphasize the significance of geographical factors in its evolution during crisis periods. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025
Seismic response assessment of topside equipment on fixed offshore platforms
No full textThe seismic performance of large equipment on offshore oil production platforms is vital for ensuring personnel safety and maintaining the structural integrity of the platform. Seismic failure of equipment can result in catastrophic hazards such as explosions, platform damage or collapse, significant economic losses, and environmental disasters. This paper evaluates the seismic performance of various types of commonly used equipment on offshore platforms in upstream operations. The seismic response of the equipment, modeled together with the platform, is assessed using nonlinear time-history analysis under three-component, 22 different high-magnitude recorded earthquake records, and analyzed through both coupled and uncoupled dynamic analyses. The findings reveal that offshore earthquakes significantly affect equipment on offshore platforms, with results indicating a positive correlation between peak ground acceleration (PGA) and material yielding in equipment supports, while peak ground velocity (PGV) and the PGA/PGV ratio significantly affect the seismic performance of the platform. Equipment that is horizontally positioned and supported is found to be more vulnerable than vertically positioned equipment, regardless of the first mode shape. The findings of this study establish seismic design recommendations for topside equipment, propose specific PGA thresholds for various types of equipment, and provide recommendations for enhanced equipment saddle designs to improve the seismic performance of topside equipment on offshore platforms
Evaluating theory-of-mind in large language models through opponent modeling
No full textTheory-of-Mind (ToM), the ability to infer the mental states, goals, and preferences of others - is a core component of human social intelligence. In this work, we investigate whether Large Language Models (LLMs) exhibit ToM capabilities in the context of strategic interaction. We frame opponent modeling in negotiation as a grounded and interpretable ToM task, where a model must infer an agent's preferences by observing offer exchanges during the negotiation. We guide LLMs to interpret offer histories and infer latent utility representations, including issue and value weights. We conduct a comprehensive evaluation of state-of-the-art LLMs across multiple negotiation domains. Our results show that LLMs can successfully recover opponents unknown preferences and in some cases even outperform classical opponent modeling base-lines, even without task-specific training. These findings offer new evidence of LLMs' emerging capacity for social reasoning and position opponent modeling as a practical benchmark for evaluating Theory-of-Mind in foundation models.Publisher versio
Exploring cognitive and syntactic dimensions in a healthcare environment affecting the spatial perceptions of paediatric inpatients
No full textPurpose
The primary objective of this study is to investigate the cognitive aspects of spatial experiences of paediatric inpatients who receive long-term treatment in a healthcare setting in relation to the syntactic parameters of healthcare environment. It is aimed to investigate how the change in the child’s cognition caused by the environmental stress experienced by the child during his/her stay in the hospital is related to the physical parameters of the treatment space.
Design/methodology/approach
The methodology of the study is based on a correlational analysis to identify the cognitive and syntactic factors of the healthcare environment that contribute to changes in the perceptual processes of a sample group of thirty children. The study examined the relationships between the graph and isovist variables, and the cognitive parameters of paediatric inpatients. The two datasets were subjected to regression analyses in order to identify any significant findings, which allowed for a discussion of how the patients’ changing perceptual processes are influenced by the syntactic measures of the healthcare setting.
Findings
The study showed that a syntactically intelligible floor plan contributes significantly to reducing environmental stress among paediatric inpatients. The presence of shared spaces within the healthcare environment, where social interaction with peers is possible, emerges as a crucial factor influencing children’s spatial perception. Additionally, the visibility characteristics of shared spaces may also play a key role in enhancing children’s perceptions of safety.
Research limitations/implications
The limitations of the study include the fact that the study was conducted in an oncology and haematology inpatient unit with challenging conditions in terms of the mobility potentials of the children, which might have affected their perceptual processes. A further limitation is that the sample size comprised only 30 children, and the spatial configuration of the healthcare environment was linear and not particularly complex.
Social implications
By identifying the impact of spatial design on children’s well-being, the study informs the creation and improvement of healthcare environments. Enhanced understanding of factors like intelligible floor plans, shared spaces and isovist values can lead to more child-friendly facilities, potentially alleviating stress for young patients. Consequently, this research may contribute to improved healthcare outcomes, increased comfort for paediatric inpatients, and a more supportive environment for their families, fostering a holistic approach to paediatric care and positively influencing the overall quality of life for children undergoing long-term treatment.
Originality/value
This study contributes to the theoretical discourse on how the constrained physical conditions of a paediatric healthcare environment may influence the perceptual processes of paediatric inpatients. The results of this evidence-based study have the potential to inform the evaluation of design guidelines for healthcare settings, with the ultimate aim of enhancing therapeutic environments
Fertile debates, circumventive pursuits: Reproductive governance and gamete donation in Turkey
No full textThis article examines the transformations of reproductive politics in Turkey under the AKP governments since 2002, shaped by the intersection of neoconservatism, nationalism, familialism, and pronatalism. Focusing on public and media discourses surrounding assisted reproduction, it analyzes the controversy sparked by single celebrities' use of foreign sperm banks and the subsequent 2010 ban on transnational gamete donation. By linking the concept of reproductive governance with debates over a perceived crisis of masculinity, the article argues that this ban marks an early manifestation of a broader national masculinist restoration. It illustrates how gender, reproduction, and kinship have been reconfigured within increasingly religious, ethnonationalist and patriarchal frameworks. Through an analysis of media narratives, the article demonstrates how certain reproductive practices, particularly single women's pursuit of motherhood, are hypervisibilized and stigmatized, while other forms of assisted reproduction are obscured. These discursive strategies serve not only to discipline reproductive behaviors, but also to reinforce gendered hierarchies and normative family structures under the guise of moral, social, and national imperatives. Ultimately, the article reveals how reproductive politics in Turkey, and in similar contexts globally, are increasingly governed by authoritarian strategies of moralization, control, and criminalization. These strategies are mobilized in response to perceived threats to the national, moral, and social order, whether posed by shifting gender and familial norms, demographic anxieties, or assertions of reproductive autonomy.National Science Foun-dation Doctoral Dissertation Research Improvement Grant (in STS