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Differential expression of VGLUT1, GAD65, GAD67, and MAP2 in the retina of hibernating Anatolian ground squirrel<i> (Spermophilus</i><i> xanthoprymnus)</i>
No full textThe Anatolian ground squirrel (Spermophilus xanthoprymnus) offers a valuable model for investigating neuroadaptive processes in the retina during hibernation. This study aimed to assess the expression of vesicular glutamate transporter 1 (VGLUT1), glutamic acid decarboxylase (GAD) isoforms GAD65 and GAD67, and microtubule-associated protein 2 (MAP2) in the retina during pre-hibernation and hibernation states. Retinal tissues were analyzed using immunohistochemistry and densitometric quantification. VGLUT1 expression remained stable in the outer plexiform layer (OPL) but was significantly reduced in the inner plexiform layer (IPL) during hibernation, indicating a selective downregulation of excitatory transmission between bipolar and ganglion cells. GAD65 showed widespread distribution across retinal synaptic layers and optic fibers in pre-hibernation but declined markedly during hibernation, consistent with reduced activity-dependent GABAergic signaling. In contrast, GAD67 immunoreactivity increased in the inner nuclear layer, suggesting a shift toward sustained basal inhibitory tone that may support synaptic stability during metabolic suppression. MAP2 immunoreactivity increased in the inner nuclear layer (INL) and outer plexiform layer (OPL) but decreased in the photoreceptor layer (PRL) during hibernation. This shift in distribution suggests cytoskeletal reorganization in second-order neurons and reduced physiological activity in photoreceptor terminals under metabolic suppression. Together, the modulation of excitatory (VGLUT1), inhibitory (GAD65/67), and cytoskeletal (MAP2) markers suggest that the hibernating retina undergoes structural and functional adaptations aimed at preserving neural circuitry under metabolic suppression
Kayseri Döner Kümbet'in Mimari Süslemelerinin Orta Asya Türk İkonografisi Açısından İncelenmesi
No full textKuşaklara GöreUltra İşlenmiş Gıda Tüketimi,Gıda Okuryazarlığı ve Kanserle İlişkili Yaşam Tarzı
No full textText Mining for Customer Feedback Analysis: Case Study of Furniture Companies
No full textIn this study, customer complaints from three different competing furniture companies were analyzed using text mining methods with Python programming. The aim of the study is to process unstructured linguistic data using natural language processing (NLP) techniques to correlate complaints with call types. In this context, a total of 9,930 complaints obtained from three different furniture companies between 2022 and 2023 underwent preprocessing, NLP, topic modeling, and classification processes. The data processed in preprocessing and NLP steps were grouped into four main topics using Non-Negative Matrix Factorization (NMF), an effective method for extracting meaningful topics from large and complex datasets. The results provided important insights into areas where furniture companies experience customer dissatisfaction and the specific issues that complaints focus on. Identified topics were evaluated for their alignment with call types identified by customer representatives using topic modeling techniques. Finally, the identified topics were designated as target variables for each complaint and classified using various classification algorithms to create a call assignment model. When comparing the performance of classification algorithms in this model, Support Vector Machine (SVM) was identified as the algorithm with the highest accuracy
The psychological foundations of moral disengagement: the dynamic relationships between state desperation, psychological flexibility, and mental well-being
No full textMXene (Ti3C2) an Effective Adsorbent for Micro Solid Phase Extraction of Trace Lead from Water and Tobacco Samples
No full textA micro-solid-phase extraction (μSPE) method has been proposed for the separation-preconcentration of lead on MXene (Ti3C2), prior to its high-resolution continuum source flame atomic absorption spectrometry (HR-CS-FAAS) detection. MXene was produced and characterized with a variety of methods, including Fourier-transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FE-SEM), scanning transmission electron microscopy (STEM), and X-ray diffraction. To optimize a variety of factors, including pH, eluent type, MXene quantity, and contact duration "one-factor-at-a-time" method was used. The MX-μSPE process included dispersing the MXene in the sample solution and then separating it from the matrix. The improved technique has limit of detection (LOD) of 0.5 µg L−1, and a preconcentration factor of 20. Two different certified reference materials were used to verify the accuracy of the proposed procedure. The procedure was applied to determination of lead contents of water and tobacco samples
Supportive Care Needs and Nursing Perceptions in Cancer Patients Receiving Targeted Immunotherapies: A Cross-Sectional Study
No full textAnalysis of Innovation Performance of South- Eastern European Countries in Transition Economies: An Application of the Entropy-Based ARTASI Method
No full textInnovation performance has emerged as a crucial policy concern for nations undergoing institutional change and economic restructuring. Using a novel hybrid multi-criteria decision-making (MCDM) framework, this study assesses the innovation capacities of five transition economies in South-Eastern Europe: Albania, Bosnia and Herzegovina, Montenegro, North Macedonia, and Serbia. Although the Global Innovation Index (GII) is widely regarded as a comprehensive benchmarking tool, its aggregated scoring system often obscures contextual subtleties, particularly in smaller or less-studied economies. To address these limitations, this study combines the ARTASI ranking model with objective weighting methods—Entropy and CRITIC—providing a transparent, flexible, and reproducible evaluation framework. The results indicate that output-oriented indicators—such as Knowledge and Technology Outputs, Market Sophistication, and Creative Outputs—are the most significant factors in differentiating national innovation performance. Among the analyzed countries, Serbia leads the regional ranking, followed by North Macedonia and Montenegro, while Albania and Bosnia and Herzegovina exhibit notable output-related deficiencies. Robustness checks—including sensitivity analysis and cross-validation with alternative MCDM techniques—confirm the model's stability and reliability. Beyond addressing a geographic gap in innovation literature, this study offers a methodologically refined approach to innovation evaluation. The proposed framework can serve as a foundation for comparative research in similar socioeconomic contexts and guide evidence-based policy-making in transition economies.</p
Navigating the triad: Economic growth, innovation, and aviation's role in shaping renewable energy transitions across G20 nations
No full textThis study explores how aviation, innovation, and GDP influence renewable energy consumption in G20 countries from 2001 to 2019. To analyze both short- and long-term relationships, the study applies panel data analysis, using the Panel ARDL/PMG and Panel Granger Causality (VECM) methods across four different models. The key variables included in the models are renewable energy consumption, air cargo volume, airline passenger numbers, flight landings, patent applications, and GDP. Findings from the Panel ARDL/PMG analysis reveal that air transportation consistently positively influence renewable energy consumption by 3.1 % while GDP influence renewable energy by -2.1 %. Meanwhile, innovation also has a significant long-term impact, except in Model 4. The VECM results show a one-way causal relationship between air cargo volume and flight landings and renewable energy consumption. However, a two-way relationship is observed between passenger numbers and renewable energy consumption, indicating that higher air passenger traffic contributes to renewable energy use, while renewable energy consumption, in turn, influences air travel demand. The findings provide significant policy insights, highlighting the necessity for cohesive strategies that synchronize innovation, air transport, and economic growth with renewable energy objectives, including enhanced investments in clean energy to facilitate the adoption of renewable resources in the aviation sector, such as advocating for sustainable fuels and implementing regulatory measures to mitigate carbon emissions
