Hakkari University

Solar irradiance is considered a fundamental parameter for photovoltaic systems. Stations established worldwide to measure solar irradiance are limited in terms of coverage. Therefore, many solar irradiance prediction models and techniques are being developed to obtain solar irradiance data. The influence of climatic factors on solar irradiance, its non-stationary nature, random variability, and complexity make prediction challenging. This study presents a short-term (minute) approach to predict global solar irradiance on a horizontal plane from satellite images, addressing all complexities and without relying on ground stations, providing broad coverage. In the proposed approach, convolutional neural network-based deep neural network architectures are employed to extract convolutional features from satellite images for the purpose of global solar irradiance on a horizontal plane prediction. Data obtained from satellite images were trained in an artificial neural network and tested and validated in regions of Turkey with different climatic conditions. Subsequently, the performance of the model is assessed and compared using common performance metrics in the literature, such as root mean square error and correlation coefficient (R), without considering the data of the predicted regions. The obtained results show that the proposed prediction model demonstrates high performance in some regions with an R value of over 97%. The prediction model may perform better if the larger training dataset is more similar to the test dataset. Indeed, successful prediction results have been obtained in regions located close to the training dataset in some areas. These results highlight that deep learning architectures can make significant contributions to research on renewable energy sources, such as solar energy.

Environmental barrier coatings (EBCs) were developed to protect SiC/SiC CMCs used in the hot sections of new-generation gas turbine engines from corrosion. Plasma-sprayed YbSi is deposited as an EBC top layer, mostly in the amorphous phase. Plasma spraying inherently creates cracks and porosity on the surface. These are disadvantages of coatings in hot corrosion and CMAS corrosion. To address these disadvantages, the presented study explored laser glazing as a solution. The surfaces of plasma-sprayed EBCs were modified with various laser processing parameters. The entire surface of the EBC was glazed using the determined optimum parameter. Hot corrosion and CMAS corrosion tests were conducted on laser-glazed EBCs. Laser glazing transformed the amorphous phase structure of the YbSi into a crystalline. It also created a smooth and dense layer on the surface. Characterizations after hot corrosion tests showed that the laser-modified sample did not show enhanced resistance. Structural deterioration, specifically an induced crack network and pits, facilitated increased penetration of corrosive salts. This led to a degradation of performance compared to the as-sprayed coating, which maintained partial resistance. Conversely, laser modification proved highly beneficial for CMAS corrosion of EBCs. The fully scanned surface’s crystallized structure effectively restricted the penetration of the corrosive glass phases. This structural integrity and the maintenance of the Yb2Si2O7 phase stability resulted in a 50

PurposeThis study aims to examine the influence of firm-specific characteristics and regional and industry-level factors on the survival of newly established small and medium-sized enterprises (SMEs) in Turkey. It also investigates whether these effects vary according to the initial scale of the firm.Design/methodology/approachThe data from over 100,000 newly established SMEs operating in Turkey between 2009 and 2020 was analyzed using the Cox regression model.FindingsSMEs that are larger, more productive and export more, and that operate in less economically developed cities and more innovative industries are more likely to survive. Moreover, these effects vary according to the initial scale of firms.Research limitations/implicationsThis study has several limitations that should be noted. First, register data improve reliability but lack information on many firm-level characteristics that may affect survival. Second, the results are based on post-2009 data and reflect economic and institutional conditions specific to that period, which may limit their applicability over time. Finally, firm exit is treated as failure, although the data do not distinguish between negative exits and positive exits such as mergers.Practical implicationsThe results suggest that policymakers should avoid a holistic approach when formulating policies for SMEs and develop separate approaches for micro, small and medium-sized firms. They also provide insights for owners and managers to help them ensure the survival of their firms.Originality/valueThe findings add to the existing understanding of the factors that contribute to the survival of start-up SMEs, particularly by examining the impact of factors such as the level of innovation and economic development of the environment in which the firm operates, which have been relatively little studied in the literature. More importantly, the results of the study underscore the importance of recognizing SMEs as a non-homogeneous group in research and policy formation.

In this study, the complete mitochondrial genome (mitogenome) of Saga hakkarica ,Sirin & Taylan, 2019, an Anatolian endemic species belonging to the order Orthoptera, family Tettigoniidae, subfamily Saginae, was characterized and genetically analysed. Next-generation sequencing technologies were employed to obtain the mitogenome sequences of S. hakkarica. With a total of 14,508,962 reads were generated, with an overall sequence length of approximately 2.19 Gbp. The mitogenome exhibited a GC content of 46.8% and an AT content of 53.2%. The analyses showed that the mitogenome of S. hakkarica is 15,755 bp in length and comprises 37 genes. These include 22 transfer RNA (tRNA) genes, two ribosomal RNA (rRNA) genes, 13 protein-coding genes (PCGs), along with a control region. Furthermore, it was determined that 23 of the 37 genes are located on the forward strand, while the remaining 14 genes are situated on the reverse strand. The mitogenome of S. hakkarica shows a high degree of similarity to Orthoptera mitogenomes reported in the literature with respect to the number of PCG, tRNA, and rRNA genes. Although the start and stop codons exhibit overall similarity, specific at the sequence-level differences were identified. In conclusion, this study presents, for the first time, the structural and functional characteristics of the complete mitogenome of S. hakkarica. As the second mitogenome dataset obtained from the subfamily Saginae, it provides an intrageneric evaluation and an important resource for future genetic and phylogenetic studies.

This qualitative study explored the experiences of and challenges faced by mothers raising a child with Down syndrome The study group consisted of mothers raising children with Down syndrome. The qualitative data were collected between July 30, 2025, and September 30, 2025. To identify these mothers' experiences and challenges, data were collected through a focus group interview with 15 participants using socio-demographic data collection and semi-structured interview forms. A descriptive thematic approach was used for data analysis, and coding and analysis were carried out using the MAXQDA qualitative data analysis program. Three main themes emerged from the analysis: emotional responsibility, social burden, and family responsibility. The findings suggest that mothers' experiences of and challenges in raising a child with Down syndrome affected their lives in several ways. Increasing the public awareness of the bio-psychosocial needs of mothers and their children and developing family-focused interventions and educational programs for children with Down syndrome could help reduce the difficulties these mothers face.