5916 research outputs found
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From hero to zero: Barriers to achieving IATA’s 2050 sustainability targets
No full textSustainable operations have become essential for mitigating the environmental impact of air transport and ensuring the long-term viability of the industry. Accordingly, achieving existing sustainability goals is crucial for reducing carbon emissions within the sector. This study presents an evaluation of the International Air Transport Association's (IATA) ambitious sustainability goals for 2050, focusing on the potential challenges and barriers that may impede their successful realization. Through a comprehensive survey circulated among carefully selected air transport sustainability researchers attending the Air Transport Research Society (ATRS) World Conference 2025, our study gathers independent academic expert perspectives on feasibility of IATA's commitments. The survey, structured around six categories, namely estimation of goal completion, economic barriers, technological challenges, policy issues, industry resistance, and public factors — elicits expert opinions on the likelihood of achieving the stated sustainability targets. The survey reveals significant skepticism about achieving net-zero carbon emissions by 2050, with economic barriers, technological challenges, and regulatory issues being major hurdles. High costs, slow tech adoption, and lack of global regulatory frameworks are other concerns. By leveraging the expertise of air transport researchers, this study offers a unique and authoritative perspective on the challenges facing the aviation industry's sustainability efforts.National Natural Science Foundation of China (NSFC
Sustainable development goals and energy: Progress and possibilities in nepal
No full textThis chapter discusses Nepal’s access to sustainable energy and its potential for future endeavors. Nepal heavily relies on India to meet its energy needs despite notable production of hydropower and biomass. The lack of political stability, inadequate storage capacity, and dependency on traditional sources of energy have hindered Nepal’s progress towards sustainable energy use. The chapter also considers the plans and policies made at the government level and analyzes their implementation. Effective utilization of renewable sources of energy should be ensured to protect nonrenewable sources and the environment. The sustainable use of energy will also be budget-friendly and reduce carbon emissions. © 2026 by Apple Academic Press, Inc
Beyond swiping through short-form videos
No full textShort-form videos have emerged as a dominant force in online media, and they have been characterized since the early 2010s by their bite-sized format, fast consumption and high engagement. Initially considered niche social media content, they now account for a substantial share of global media consumption. This paper begins by analyzing a dataset of short-form videos from a popular news application, which includes metrics related to videos consumed within the app in a format akin to YouTube Shorts or Instagram Reels. Building on these insights, the paper poses open questions and advocates for community-driven efforts to establish open protocols for short-form video content.Publisher versio
Diş problemleri tanısı için derin ögrenme tabanlı çoklu-hastalık tespiti
No full textThis work uses deep learning to automatically classify a set of dental pathologies from wide-field dental X-rays named panoramic radiographs. 9,573 adult and child patients' X-ray images form our dataset, each of which is manually annotated to 19 different dental pathologies. The proposed method leverages advanced deep learning models to diagnose a set of oral diseases and achieves state-of-the-art results. YOLO and DETR models are compared for their dental problem detection and classification accuracy. This complete AI-based method produces quick and ac-curate diagnoses of oral health, which allows dental practitioners to provide more informed decisions quickly and reliably. With evidence-based interpretation of AI results, we believe that the proposed method is a sensible way of supplementing dentists' diagnoses
GAT-HiC: Efficient reconstruction of 3D chromosome structure via residual graph attention neural networks
No full textHi-C is an experimental technique to measure the genome-wide topological dynamics and three-dimensional (3D) shape of chromosomes indirectly via counting the number of interactions between distinct sets of loci. One can estimate the 3D shape of a chromosome over these indirect interaction datasets. Here, we come up with graph attention and residual network-based GAT-HiC to predict three-dimensional chromosome structure from Hi-C interactions. GAT-HiC is distinct from the existing 3D chromosome shape prediction approaches in a way that it can generalize to data that is different than train data. So, we can train GAT-HiC on one type of Hi-C interaction matrix and infer on a completely dissimilar interaction matrix. GAT-HiC combines the unsupervised vertex embedding method Node2vec with an attention-based graph neural network when predicting each genomic loci's three-dimensional coordinates from Hi-C interaction matrix. We test the performance of our method across multiple Hi-C interaction datasets, where a trained model can be generalized across distinct cell populations, distinct restriction enzymes, and distinct Hi-C resolutions over human and mouse. GAT-HiC can reconstruct accurately in all these scenarios. Our method outperforms the existing approaches in terms of the accuracy of three-dimensional chromosome shape inference over interaction datasets. Code and datasets can be found at https://github.com/beyzoskaya/GAT-HiC. © 2025 IEEE
Incentivizing group investments: Surplus sharing agreements in theory and experiment
No full textA better understanding of surplus sharing is crucial for improving collective action outcomes in investment contexts where individual decisions yield group-level results. This study explores how surplus sharing agreements affect total contribution levels in such environments. We first develop a theoretical framework and then examine its implications through an incentivized laboratory experiment. Our main result shows that a pre-commitment to allocating positive surpluses proportionally and negative surpluses according to a fixed ratio leads to significantly higher total contributions than allocating surpluses solely either proportionally or by a fixed ratio. Furthermore, total contributions under the purely proportional and the purely fixed sharing agreements do not differ significantly. Finally, the degree of inequality embedded in a fixed share allocation does not significantly affect total contribution levels.TÜBİTA
Does geopolitical risk drive earnings management? Evidence from low- and middle-income countries
No full textWe examine the impact of geopolitical risk (GPR) on earnings management (EM) in low- and middle-income countries (LMICs). Using 257,659 firm-year observations from 16 LMICs (2002-2022) and System Generalized Method of Moments (System-GMM) estimations, we find that GPR significantly increases EM, especially under weak audit quality, low development, and high taxation. While EM buffers short-term shocks, it undermines transparency, underscoring the need for stronger institutions.Publisher versio
A dual-input deep learning architecture for classification and latency estimation in ABR signals
No full textIntroduction Auditory brainstem response (ABR) is an objective neurophysiological evaluation designed to measure the electrical activity originating from the auditory nerve and brainstem in response to auditory stimulation. This assessment objectively records synchronous neural activity as it propagates along the auditory pathway. It is characterized by several distinct waves, most notably waves I, III, and V. Wave V plays a central clinical role since its presence and latency are routinely used to assess a patient's hearing status. However, manual identification and localization of wave V are time consuming and subjective. Previous work has explored automated detection methods to reduce this burden.Methods In this paper, we make two primary contributions. First, we propose a multi-task deep learning pipeline that simultaneously (i) detects the presence of wave V and (ii) predicts its latency, thus eliminating the need for separate manual interpretation steps and enhancing clinical usability. Second, inspired by the audiologist's practice of comparing responses at multiple click sound intensities-specifically, using responses at high intensities, where waves are more prominent, as reference-we introduce a paired-signal approach. Each input to our deep learning model consists of the test signal together with its corresponding 80 dB reference from the same recording session. This provides the model with richer contextual information, and we show that the paired-signal approach improves over the single input approach. For multi-task learning, we design a network that consists of a backbone and two branches, one for latency prediction and the other for classification of whether wave V exists or not. We first train a latency-prediction network and then freeze its feature extraction layers to initialize a classification branch. Finally, we fine-tune the entire network using a joint loss function that balances classification and regression objectives.Results Experimental results demonstrate that our joint model1 outperforms conventional single-task approaches. For classification, it achieves an F1-score of 0.92; for latency regression, it attains an R2 of 0.90.Discussion Our findings highlight the promise of convolutional neural networks for enhancing ABR analysis and underscore their potential to streamline clinical workflows in the diagnosis of auditory disorders.TÜBİTAKPublisher versio
Cultural instruments of legitimacy in constitutionalization: Constituent power through ceremony, ritual, and symbol
No full textThis study explores how ceremonies, rituals, and symbols function in constitution-making as instruments through which constituent power gains legitimacy and social acceptance. While constituent power is often seen as an extra-legal force, its endurance depends not only on legal norms but also on cultural performance. Practices such as public oaths, anthems, and ceremonial readings consecrate the new order, making visible the link between popular will and political authority. Far from mere spectacle, these acts inscribe constitutional moments into collective memory and shape future political belonging. Drawing on law, political science, and cultural anthropology, the study highlights the constitutive role of symbolic practices in producing constitutional order