PubMed İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/397

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Citation - WoS: 2
Citation - Scopus: 6
Probabilistic Assessment of Wind Power Plant Energy Potential Through a Copula-Deep Learning Approach in Decision Trees
(Cell Press, 2024) Sahin, Kubra Nur; Sutcu, Muhammed
In the face of environmental degradation and diminished energy resources, there is an urgent need for clean, affordable, and sustainable energy solutions, which highlights the importance of wind energy. In the global transition to renewable energy sources, wind power has emerged as a key player that is in line with the Paris Agreement, the Net Zero Target by 2050, and the UN 2030 Goals, especially SDG-7. It is critical to consider the variable and intermittent nature of wind to efficiently harness wind energy and evaluate its potential. Nonetheless, since wind energy is inherently variable and intermittent, a comprehensive assessment of a prospective site's wind power generation potential is required. This analysis is crucial for stakeholders and policymakers to make well-informed decisions because it helps them assess financial risks and choose the best locations for wind power plant installations. In this study, we introduce a framework based on Copula-Deep Learning within the context of decision trees. The main objective is to enhance the assessment of the wind power potential of a site by exploiting the intricate and non-linear dependencies among meteorological variables through the fusion of copulas and deep learning techniques. An empirical study was carried out using wind power plant data from Turkey. This dataset includes hourly power output measurements as well as comprehensive meteorological data for 2021. The results show that acknowledging and addressing the non-independence of variables through innovative frameworks like the Copula-LSTM based decision tree approach can significantly improve the accuracy and reliability of wind power plant potential assessment and analysis in other real-world data scenarios. The implications of this research extend beyond wind energy to inform decision-making processes critical for a sustainable energy future.
Citation - WoS: 7
Citation - Scopus: 8
The Effect of Lockdown on Students' Performance: A Comparative Study Between Italy, Sweden and Turkey
(Cell Press, 2023) Casalone, Giorgia; Michelangeli, Alessandra; Osth, John; Turk, Umut
During the first months of the COVID-19 outbreak, countries adopted different strategies in order to mitigate the effects of the pandemic, ranging from recommendations to limit individual movement to severe lockdown measures. Regarding higher education, university studies were shifted to digital solutions in most countries. The sudden move to online teaching affected stu-dents differently, depending on the overall mitigation strategies applied. Severe lockdown and closure measures caused a disruption of their academic and social interactions. In contrast, rec-ommendations to limit activities probably did not change students' life to a great extent. The heterogeneity of the policies adopted in three countries (Italy, Sweden and Turkey) gives us an opportunity to assess the effects of lockdown measures due to the COVID-19 pandemic on uni-versity students' performance. We employ a difference-in-differences approach by exploiting the fact that Italy and Turkey experienced national lockdowns, while Sweden never applied nation-wide mandatory restrictive policies. We use administrative data from universities in the three countries to estimate the probability to pass exams after the spread of COVID-19 pandemic (and the shift to distance education), with respect to the previous comparable period. We find that the pass rate decreased with the shift to online teaching. However, lockdown measures, especially if very restrictive as those applied in Italy, helped to compensate such negative effect. A possible explanation is that students took advantage of the huge increase in the time available for their studies, given the impossibility to carry out any activity outside the home.
Citation - WoS: 2
Citation - Scopus: 2
ARL13B Regulates Juxtaposed Cilia-Cilia Elongation in BBSome Dependent Manner in Caenorhabditis Elegans
(Cell Press, 2025) Turan, Merve Gul; Kantarci, Hanife; Cevik, Sebiha; Kaplan, Oktay I.
The interaction of cilia with various cellular compartments, such as axons, has emerged as a new form of cellular communication. Cilia often extend in proximity to cilia from neighboring cells. However, the mechanisms driving this process termed juxtaposed cilia-cilia elongation (JCE) remain unclear. We use fluorescence-based visualization to study the mechanisms of coordinated cilia elongation in sensory neurons of Caenorhabditis elegans. Conducting a selective gene-based screening strategy reveals that ARL-13/ARL13B and MKS-5/RPGRIP1L are essential for JCE. We demonstrate that ARL-13 modulates JCE independently of cilia length. Loss of NPHP-2/inversin along with HDAC-6 enhances the cilia misdirection phenotype of arl-13 mutants, while disruption of the BBSome complex, but not microtubule components, partially suppresses the JCE defects in arl-13 mutants. We further show changes in the phospholipid compositions in arl-13 mutants. We suggest that ARL-13 contributes to JCE, in part, through the modulation of the ciliary membrane.

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