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Uncovering the Nexus between ESG Reports and ESG Scores across Various Liquidity Levels: Evidence from Publicly Traded Turkish Companies by Machine Learning Algorithms
No full textAccessible Hyperlinks and Search Engine Rankings: An Empirical Investigation Erisilebilir Ba?glantilar ve Arama Motoru Siralamalari: Ampirik Bir Inceleme
No full textThis study investigates the impact of accessibility features of internal links on a website's Search Engine Results Page (SERP) ranking. To test the hypothesis that accessibility influences SERP ranking, a labeled dataset was created to measure internal link accessibility. In creating this dataset, internal links on websites were matched with their corresponding subpages listed by search engines to complete the labeling process. Accessibility metrics such as "is_unique", "contrast_ratio", and "text_clarity"were extracted for the internal links using machine learning techniques. Analysis of the data suggests that accessibility features may indeed influence SERP rankings. The labeled dataset created in this study will serve as a resource for future research on internal link accessibility and SERP ranking
F-wave motor unit numbers do not change in diabetic polyneuropathy: does it indicate a pathophysiologic mechanism for generating F-waves?
No full textObjectives: Motor unit number estimation (MUNE) methods including the one using F-waves (F-MUNE) are used to detect axonal loss in polyneuropathies. The aim of this study is to evaluate the amount of axonal loss by repeater F-wave parameters and F-MUNE in patients with type 2 diabetes mellitus (DM). Methods: In 24 controls and 49 patients with diabetic polyneuropathy, 90 F-waves elicited with supramaximal and 300 F-waves with submaximal stimulation of the ulnar nerve were recorded from the abductor digiti minimi muscle. F-MUNE values were calculated using the automated software with the repeater F-waves elicited using submaximal stimulation. Results: Ulnar repeater F-wave index and repeater neuron index were found to be significantly higher in patients with DM compared with the control group. The amplitudes of F-waves elicited using both sub- and supramaximal stimulus intensities were reduced in patients with polyneuropathy when compared with controls. The F-MUNE values were found to be similar between the two groups. Discussion: Repeater F-wave parameters recorded from the upper extremity might indicate the presence of axon loss in DM-related polyneuropathy. However, F-MUNE failed to reveal axonal loss in diabetic polyneuropathy probably because of its length-dependent nature and the dominance of low-amplitude F-waves, which might be secondary to several yet unknown mechanisms, mainly related to sensory fiber dysfunction
Introducing MOSAIC-SEN2-CC: A Multispectral Dataset and Adaptation Framework for Remote Sensing Change Captioning
No full textRemote Sensing Image Change Captioning (RSICC) aims to generate descriptive sentences that effectively characterize the changes between bitemporal images. Although the state-of-the-art methods focus on predicting captions from RGB image pairs, change captioning in multispectral images has not been investigated yet. For this purpose, we created a new MOSAIC-SEN2-CC dataset, which contains 5232 pairs of multispectral (MS) images captured from Sentinel-2 satellites and 26 160 change captions over a 12-month period. Our dataset consists of a total of eight categories, namely Wildfire (WF), Flood (FL), Wetland (WET), Green Field (GF), Glacier (GL), Urban (UR), Agriculture (AG), along with a No-Change (NO) category. In this article, we propose a Multispectral Image Change Captioning framework that consists of BigEarthNet Feature Extractor, Feature Enhancement, and Transformer-Based Decoder modules to effectively benefit from spectral band information. Specifically, the state-of-the-art methods, such as RSICCformer, Chg2Cap, and PSNet, are adapted to work with BigEarthNet models using ten spectral band images. Detailed comparisons that include attention visualizations, RGB versus MS tradeoffs, change captions, and performance metrics further demonstrate its effectiveness and ability to address RSICC challenges
COMPARATIVE ANALYSIS of INSTITUTIONAL CONTEXT: Different Institutional Dynamics in Turkish Shipbreaking and ELV Dismantling Industries
No full textThere is a growing consensus among scholars that institutions play a critical role in urban and regional development (Acemoglu et al., 2005; Gertler, 2010; Rodriguez-Pose, 2013; Storper, 2013). However, although numerous studies have been conducted in economic geography on the analysis of the ways institutions operate in different contexts, the definition of institutions and the explanation of institutional change are still highly ambiguous (Gertler, 2018; Rodriguez-Pose, 2020). With that being said, a new research line has recently emerged that develops a discipline-specific definition of institutions from a relational perspective (Bathelt and Glückler, 2014) and conceptualizes institutional change through the relationships among the building blocks (regulations-organizations-institutions) of the institutional context (Glückler and Lenz, 2016). Based on this new line, this study aims to explain the impact of organizational field-specific dynamics on the differentiation of interactions between institutions and the other dimensions of the institutional context. In this respect, the institutional contexts of the OSTİM end-of-life vehicle dismantling industry and the Aliağa shipbreaking industry, which were moved from the center of the Ankara and Istanbul metropolises to the peripheral regions in the 1980s, respectively, have been analyzed comparatively. For this, 42 interviews were conducted with actors from within and outside industry-specific organizational fields. According to the findings, the institutional patterns of forgery in car/ship purchasing, disinterest about recycling and waste disposal, disinterest in complaying with environmental and occupational health&safety measures and disbelief in meeting technical conditions have been observed in the development processes of both industries. Additionally, OSTİM represents a case study where the regulations cannot compete with existing institutions and are ineffective, thus the dominant institutional patterns continue to exist unchanged for many years. However, Aliağa represents a case study where regulations developed for the same purposes as in OSTİM circumvent these patterns. In Aliağa, the organizational field allows social practice to reorganize around costs and benefits, while in OSTİM, it causes social practice to show great resistance to change to maintain existing benefits and avoid new costs. In conclusion, this study will contribute in terms of the use of a comparative methodology to the new research line initiated by Bathelt and Glückler (2014) and continues to develop with both conceptual and empirical contributions. Keywords: Institutional context, comparative analysis, shipbreaking, end-of-Life vehicles (ELVs) dismantling, Turkey.</p
Detection of Overlapping Cells in Histopathological Images with Deep Sparse Learning Derin Seyrek ?grenme ile Histopatolojik G r nt lerde rt sen H crelerin Tespiti
No full textNowadays, artificial intelligence is rapidly developing, and with increasing data volumes, the learning capacity of models is expanding. However, this also increases training costs and processing times. In this study, deep sparse learning (DSL) methods are evaluated for the classification of cancer cells and tissues. The Ocelot dataset was used to analyze cell and tissue images. While the highest F1 Score reported in the literature is 75.58%, the proposed method improved the initial F1 Score from 69.45% to 73.12%. Additionally, the DSL model, supported by data augmentation techniques, achieved a 20% improvement in processing time. The findings demonstrate that DSL not only improves accuracy but also reduces processing time, providing more efficient and cost-effective solutions in the field of medical image processing