155199 research outputs found
Sort by
Independence Saturation and Strong Independent Saturation in Probabilistic Neural Networks
No full textThe independence saturation number IS(G) of a graph G = (V,E) is defined as min{IS(v): v V}, where IS(v) is the maximum cardinality of an independent set that contains v. The strong independent saturation number Is(G) of a graph G = (V,E) is defined as min{Is(v): v ∈ V}, where Is(v) is the maximum cardinality of a minimal strong independent dominating set of G that contains v. This paper is devoted to the computation of independence saturation and strong independent saturation numbers of 3- and 4-layered probabilistic neural networks
Challenging Symbolic Violence: Implementing Humanizing Multilingual Pedagogies in English Language Teacher Education in Türkiye
No full textThis study examines the implementation of humanizing equity and identity-oriented multilingual pedagogies (HEIMP) in a Turkish English Language Teacher Education program, focusing on how these pedagogies challenge the symbolic violence, or practices that reify the subordination of certain social groups, inherent in traditional educational structures (Bourdieu & Passeron, 1990). This paper draws from works that prioritize TC’s funds of knowledge and identities as well as their journeys of becoming multilingual (Gonzales et al, 2006; Esteban-Guitart & Moll, 2014; Canagarajah, 2019; Neville & Johnson, 2022). Through case studies of two teacher candidates (TCs), we explore divergent responses to a course designed to disrupt hierarchical power dynamics in linguistically diverse classrooms. Using narrative inquiry methods (Clandinin & Connelly, 2004), we thematically coded. and recursively analyzed language autobiographies and reflections to illuminate how participants negotiate the shift from teacher-centered, exam-focused norms to student-centered, participatory learning. Findings reveal a significant onto-epistemic shift in one participant, Murat, who deconstructs internalized educational paradigms and reimagines teaching practices. Conversely, Ali expresses discomfort with non-traditional participation modes and assessment practices, highlighting the deep-rooted nature of symbolic violence in educational contexts.The study demonstrates how HEIMP can challenge the reproduction of educational practices that perpetuate symbolic violence (Bourdieu & Passeron, 1990). By fostering open dialogue about cultural and linguistic backgrounds, the course encourages TCs to question established power dynamics and language ideologies. This approach, while transformative for some, proves "incompatible with the function of reproducing the intellectual and moral integration of the legitimate addressees" (Bourdieu & Passeron, 1990, p. 12) in the Turkish context.Our research highlights the potential for transformation and the resistance encountered when challenging deeply ingrained educational norms within language teacher education, offering insights into the complex process of disrupting symbolic violence in teacher preparation programs. </div
Menopoz Polikliniğine Başvuran Kadınlarda Postmenopozal Kanama Prevalansı ve Sağlık Arama Davranışlarının Belirlenmesi: Tanımlayıcı ve Kesitsel Çalışma
No full textChalcone-containing phthalocyanines: Determination of photophysical and photochemical properties and cytotoxicity on breast cancer cell models
No full textThe synthesis of new Zn(II), and Si(IV) phthalocyanine (Pc) derivatives containing chalcone group was successfully achieved and the compounds were characterized by MALDI-TOF mass spectroscopy, FT-IR, H-1 NMR, C-13 NMR, and UV-vis spectral data. The photophysical and photochemical properties of these novel Pcs were investigated in DMF. The in vitro cytotoxic effect of the compounds on mammary breast adenocarcinoma cell lines (MCF-7 and MDA-MB-231) and normal mammary breast epithelium (MCF-12A) were evaluated by using the WST assay. Based on the WST assay analysis, cytotoxicity of the Pc derivatives to mammary breast carcinoma cells was compared to normal mammary breast epithelium cells dependent on light illumination. The results of the present investigation demonstrate that all the Pc derivatives containing the chalcone group have a phototoxic effect on mammary breast cancer cells and could be promising photodynamic therapy (PDT) agents for further studies
Detection of Bipolar Disorder and Schizophrenia Employing Bayesian-Optimized Grad-CAM-Driven Deep Learning
No full textDiagnosing bipolar disorder (BD) and schizophrenia (SCH) presents significant challenges due to overlapping symptoms, reliance on subjective assessments, and the late-stage manifestation of many symptoms. Current methods using structural magnetic resonance imaging (sMRI) as input data often fail to provide the objectivity and sensitivity needed for early and accurate diagnosis. sMRI is well known to be capable of detecting anatomical changes, such as reduced gray matter volume in SCH or cortical thickness alterations in BD. However, advanced techniques are required to capture subtle neuroanatomical patterns critical for distinguishing these disorders in sMRI. Deep learning (DL) has emerged as a transformative tool in neuroimaging analysis, offering the ability to automatically extract intricate features from large datasets. Building on its success in other domains, including autism spectrum disorder and Alzheimer’s disease, DL models have demonstrated the potential to detect subtle structural changes in BD and SCH. Recent advancements suggest that DL can outperform traditional statistical methods, offering higher classification accuracy and enabling the differentiation of complex psychiatric disorders. In this context, this study introduces a novel deep learning framework for distinguishing BD and SCH using sMRI data. The model is specifically designed to address subtle neuroanatomical differences, offering three key contributions: (1) a tailored DL model that leverages explainability to extract features that boost psychiatric MRI analysis performance, (2) a comprehensive evaluation of the model’s performance in classifying BD and SCH using both spatial and morphological analysis together with classification metrics, and (3) detailed insights, which are derived from both quantitative (performance metrics) and qualitative analyses (visual observations), into key brain regions most relevant for differentiating these disorders. The results have achieved an accuracy of 78.84%, an area under the curve (AUC) of 83.35%, and a Matthews correlation coefficient (MCC) of 59.10% using the proposed framework. These metrics significantly outperform traditional machine learning models. Furthermore, the proposed method demonstrated superior precision and recall for both BD and SCH, with notable improvements in identifying subtle neuroanatomical patterns. Depending on the acquired result, it can be said that the proposed method enhances the application of DL in psychiatry, paving the way for more objective, non-invasive diagnostic tools with the potential to improve early detection and personalized treatment
Photoremoval of Dissolved Organic Waste and Dielectric-Energy Storage with SmCuO/ZnO/CuMn2O4 Tri-Composite
No full textQualitative and quantitative educational disparities and brain signatures in healthy aging and dementia across global settings
No full textBackground: While education is crucial for brain health, evidence mainly relies on individual measures of years of education (YoE), neglecting education quality (EQ). The effect of YoE and EQ on aging and dementia has not been compared. Methods: We conducted a cross-sectional assessment of the effect of EQ and YoE on brain health in 7533 subjects from 20 countries, including healthy controls (HCs), Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD). EQ was based on country-level quality indicators provided by the programme for international student assessment (PISA). After applying neuroimage harmonization, we examined its effect, along with YoE, on gray matter volume and functional connectivity. Regression models were adjusted for age, sex, and cognition, controlling for multiple comparisons. The influence of image quality was assessed through sensitivity analysis. Data collection was conducted between June 1 and October 30, 2024. Findings: Less EQ and YoE were associated with brain alterations across groups. However, EQ had a stronger influence, mainly targeting the critical areas of each condition. At the whole-brain level, EQ influenced volume (HCs: Δmean = 2·0 [1·9–2·0] × 10−2, p < 10−5; AD: Δmean = 0·1 [−0·0 to 0·3] × 10−2, p = 0·18; FTLD: Δmean = 3·5 [3·0–4·0] × 10−2, p < 10−5; all with 95% confidence intervals) and networks (HCs: Δmean = 13·5 [13·2–13·7] × 10−2, p < 10−5; AD: Δmean = 5·9 [5·2–6·7] × 10−2, p < 10−5; FTLD: Δmean = 13·2 [11·2–13·7] × 10−2, p < 10−5) 1·3 to 7·0 times more than YoE. These effects remain robust despite variations in income and socioeconomic factors at country and individual levels. Interpretation: The results support the need to incorporate education quality into studying and improving brain health, underscoring the importance of country-level measures. Funding: Multi-partner consortium to expand dementia research in Latin America (ReDLat)
DMN network and neurocognitive changes associated with dissociative symptoms in major depressive disorder: a research protocol
No full textIntroduction: Depression is a heterogeneous disorder with diverse clinical presentations and etiological underpinnings, necessitating the identification of distinct subtypes to enhance targeted interventions. Dissociative symptoms, commonly observed in major depressive disorder (MDD) and linked to early life trauma, may represent a unique clinical dimension associated with specific neurocognitive deficits. Although emerging research has begun to explore the role of dissociation in depression, most studies have provided only descriptive analyses, leaving the mechanistic interplay between these phenomena underexplored. The primary objective of this study is to determine whether MDD patients with prominent dissociative symptoms differ from those without such symptoms in clinical presentation, neurocognitive performance, and markers of functional connectivity. This investigation will be the first to integrate comprehensive clinical evaluations, advanced neurocognitive testing, and high-resolution brain imaging to delineate the contribution of dissociative symptoms in MDD. Methods: We will recruit fifty participants for each of three groups: (1) depressive patients with dissociative symptoms, (2) depressive patients without dissociative symptoms, and (3) healthy controls. Diagnostic assessments will be performed using the Structured Clinical Interview for DSM-5 (SCID) alongside standardized scales for depression severity, dissociation, and childhood trauma. Neurocognitive performance will be evaluated through a battery of tests assessing memory, attention, executive function, and processing speed. Structural and functional magnetic resonance imaging (MRI) will be conducted on a 3 Tesla scanner, focusing on the connectivity of the Default Mode Network with key regions such as the orbitofrontal cortex, insula, and posterior cingulate cortex. Data analyses will employ SPM-12 and Matlab-based CONN and PRONTO tools, with multiclass Gaussian process classification applied to differentiate the three groups based on clinical, cognitive, and imaging data. Discussion: The results of this study will introduce a novel perspective on understanding the connection between major depressive disorder and dissociation. It could also aid in pinpointing a distinct form of depression associated with dissociative symptoms and early childhood stressors. Conclusion: Future research, aiming to forecast the response to biological and psychological interventions for depression, anticipates this subtype and provides insights
PATLATMALI KAZI ÇALIŞMALARINDA TİTREŞİM YAYILIM EŞİTLİKLERİNİN SAHA ÖLÇÜMLERİYLE KARŞILAŞTIRILMASI, BİR İNŞAAT PROJESİ ÖRNEĞİ
No full textGünümüzde kaya kütlelerinin parçalanarak taşınabilir duruma getirilmesinde mekanik kazının uzun süreler alması bu sebeple ekonomik olmaması, maruz kalınan gürültü süresinin artması, sert kayaçlarda kırıcı makinalarıın parçalama başarısının düşük olması gibi sebeplerden dolayı patlayıcı maddeler ve patlatma teknolojisi kaçınılmaz olarak uygulanmaktadır. Madencilik faaliyetlerinde yaygın olarak kullanılan patlatma teknolojisi aynı zamanda inşaat projelerinde temel kazısı ve alan düzeltme amacıyla sıklıkla kullanılmaktadır. İnşaat projelerinin çoğunlukla yerleşim yerlerine yakın alanlarda olması patlatmalı kazı çalışmalarının çevresel etkileri açısından problem yaratabilmektedir. Özellikle patlatma kaynaklı titreşimlerin Çevresel Gürültü Kontrol Yönetmeliği’nde izin verilen titreşim seviyesi limit değerlerine göre, proje alanına yakın yapılar üzerindeki etkisi titreşim yayılım denklemleri kullanılarak değerlendirilmelidir. Bu amaçla Muğla ili, Bodrum ilçesinde bir inşaat projesi alanında gerçekleştirilen patlatmalı kazı çalışmalarının çevre binalara ekisini değerlendirebilmek amacıyla titreşim ölçümleri gerçekleştirilerek titreşim yayılma eşitliği oluşturulmuştur. Saha özelinde elde edilen yayılım eşitliği ile Çevre Şehircilik ve İlkim Değişikliği Bakanlığı tarafından yayımlanan Patlatma Tasarımları ve Patlatma Kaynaklı Çevresel Etkiler Kılavuzu’nda patlatma türü olarak inşaat alanı için verilen eşitlikler kullanılarak titreşim hızı tahminleri yapılmış ve karşılaştırmalı olarak sunulmuştur. Yapılan çalışma sonucunda inşaat alanlarında kılavuzda verilen tahmin modellerinin kullanılarak çevresel etki değerlendirmesi yapılmasının uygun olmadığı, mutlaka sahada titreşim ölçümleri gerçekleştirilerek saha özelinde bir titreşim yayılım eşitliği elde edilmesinin çevre yapılara olası bir zararı önlemek için gerekli olduğu görülmüştür.Explosive materials and blasting technology are inevitably employed in the fragmentation of rock masses to make them transportable. Blasting technology, widely used in mining activities, is also frequently utilized in construction projects for foundation excavation and site leveling. The proximity of construction projects to residential areas often creates challenges regarding the environmental impacts of blasting operations. In particular, the effects of blast-induced vibrations on structures near the project site should be evaluated using vibration propagation equations, by the vibration level limits permitted by the Environmental Noise Control Regulation. For this purpose, blast-induced vibration measurements were conducted at a construction project site in Bodrum to assess the impact of blasting activities on nearby buildings, and a site-specific vibration propagation equation was established. Using the propagation equation obtained specifically for the site, vibration velocity predictions were made and comparatively presented based on the equations provided for construction site blasting in the "Blasting Designs and Environmental Effects of Blasting Guide" published by the Ministry of Environment, Urbanization, and Climate Change. The study's results indicate that using the prediction models provided in the guide for environmental impact assessment at construction sites is inappropriate. Instead, conducting on-site vibration measurements to derive a site-specific vibration propagation equation is essential to prevent potential damage to nearby structures.</p