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The relationships between parental involvement, teacher support, and mathematics performance: mediating roles of academic self-efficacy and academic buoyancy
Full text linkBackgroundThis study examined how parental involvement (PI) and perceived teacher support (TS) influence middle school students' mathematics performance (MP) through the mediating roles of academic self-efficacy (ASE) and academic buoyancy (AB). Unlike previous research, it simultaneously investigated these dual support systems and their indirect effects on math achievement, providing a comprehensive model that integrates both external support mechanisms with non-cognitive attributes affecting mathematics performance.MethodsParticipants were 363 sixth-grade students (51% boys, 49% girls) from middle schools in T & uuml;rkiye. Data were analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method.ResultsThe results revealed that PI had a significant positive effect on both ASE and AB, as well as a direct positive effect on MP. Similarly, perceived TS positively influenced both ASE and AB, and had both direct and indirect positive effects on MP. Both ASE and AB mediated the effects of PI and TS on MP.ConclusionsThis study reveals that students supported by teachers and parents tend to perform better in mathematics. This effect is related both directly and indirectly through increased ASE and AB. By identifying these dual pathways, the study deepens our understanding by providing important insights into the critical interaction between external supports and non-cognitive attributes in improving mathematics achievement
A Machine Learning Approach to Identify High-Risk Road Segments and Accident Severity Patterns Based on Categorical Data
No full textTraffic accidents remain a major public safety concern, particularly in regions where rapid motorization and limited infrastructure increase crash risk. This study proposes a machine learning-based framework to classify traffic accident severity and identify high-risk road segments using multidimensional crash data from Şırnak Province, Turkey. The dataset, obtained from the General Directorate of Security (EGM), contains 29 variables describing traffic, geometric, and operational roadway characteristics for crashes reported between 2018 and 2023. Due to the severe imbalance between injury and fatal crashes, the Synthetic Minority Oversampling Technique (SMOTE) was applied to enhance model sensitivity to the minority class. Five classifiers—Logistic Regression (LR), Support Vector Machines (SVM), Multilayer Perceptron (MLP), Random Forest (RF), and Extreme Gradient Boosting (XGBoost)—were trained and evaluated using accuracy, F1-score, ROC-AUC, and alarm metrics. Results from the original dataset showed that several models struggled to detect fatal crashes, while LR demonstrated moderate sensitivity. After SMOTE, performance improved across all models. XGBoost achieved the highest F1-score (0.61) with the lowest False Alarm rate (0.01), followed by RF and MLP, whereas SVM and LR yielded comparatively lower accuracy. Computation time analysis indicated that LR and SVM had the fastest runtimes, while MLP and XGBoost required longer training times. Overall, findings highlight the effectiveness of ensemble models—particularly XGBoost—in capturing critical crash patterns and supporting risk-based decision-making. Future work should incorporate time-series analysis and GIS-based spatial modeling to further enhance predictive capability and inform geographically targeted safety interventions
The use of artificial intelligence in damage assessment of historical buildings
Full text linkt Historical buildings are indispensable for maintaining cultural continuity. Proper restoration is the only way to preserve their original character. At this stage, early and accurate diagnosis of the damage to the historical building plays a vital role in the restoration process. Traditional damage assessment methods sometimes cause erroneous diagnoses and damage to the building. For this reason, non-destructive methods should be developed by utilizing the opportunities provided by technology. The research aims to develop an artificial intelligence-based damage detection model that can quickly and accurately detect deterioration in historical buildings. The study’s scope consists of traditional Gaziantep houses in the city’s historical center. The primary materials are high-resolution digital fac¸ade images, survey reports of these houses, and the findings obtained in the field research. The research reveals that deterioration maps, which are prepared with traditional methods by spending intensive labor and time, can be produced with an artificial intelligence-based system. Experts first documented the damages seen on the fac¸ades of historic stone buildings, and the model trained with these data was used as a supportive method to determine the types of deterioration. Integrating the system with expert opinions, field studies, and visual documents makes creating deterioration maps more efficient. ©2025 The Author(s). Publishing services by Elsevier B.V. on behalf of Higher Education Press and KeAi. This is an open access article under the CC BY-NC-ND license
A Comparative Evaluation of Deep Learning and Machine Learning Models for River Suspended Sediment Concentration Forecasting
Full text linkSuspended sediment concentration (SSC) in rivers is a crucial parameter required in hydrological studies, water resources management, and many other relevant applications. This study presents a comparative assessment of deep learning (DL) and machine learning (ML) methods in river SSC prediction of two river stations on the Mississippi River, United States. To that end, two single DL models, namely recurrent neural networks (RNN) and bidirectional RNN (BiRNN) were developed. Generally, the RNN was found to outperform the BiRNN for predicting SSC. Furthermore, a convolutional neural network (CNN) was coupled on the applied DL models to create the hybrid RNN-CNN and BiRNN-CNN models. The results denoted that the BiRNN-CNN models generally performed better compared with RNN-CNN ones. Besides the four types of DL models, three forms of ML models, including adaptive boosting (AdaBoost), natural gradient boosting (NGBoost), and gradient boosting regression trees (GBRT) were also established. As a general conclusion, NGBoost and GBRT demonstrated the highest and lowest level of accuracy in river SSC forecasting. Eventually, the influence of input predictors on the outputs of models was done considering local interpretable model-agnostic explanations (LIME). Assessing the LIME outcomes for the selected samples of the test data revealed that the current daily river streamflow and one daily lagged SSC data were the most effective inputs on SSC prediction results
Reconciling fiscal decentralization, environmental protection expenditures, and stringent regulations with the ecological priorities of the European Union
Full text linkThis study elucidates how fiscal decentralization affects environmental sustainability, moderating the role of environmental policy stringency in the selected European Union (EU) countries between 1995 and 2020. In addition, economic upturn, import diversification, and environmental protection expenditures are utilized as control variables. The empirical findings of the Method of the Moments Quantile Regression (MMQR) disclosed that the environmental policy stringency and environmental protection expenditures help the EU achieve ecological priorities. In addition, import diversification also spurs environmental sustainability, with more substantial impacts on less energy and carbon-efficient nations. Furthermore, the MMQR outcomes divulged that fiscal decentralization (all indicators) endorsed the environmental deterioration of EU members, undermining the achievement of ecological urgencies. Nonetheless, via the means of environmental policy stringency, fiscal decentralization positively influences environmental sustainability. These findings unveil that the harmful impact of fiscal decentralization on environmental sustainability can be curtailed if EU members impose more stringent environmental policies. Herein, to fulfil the targets of Sustainable Development Goals (SDGs), in particular, SDG7 and SDG13, EU members should consolidate fiscal decentralization initiatives and environmental policy stringency to ensure the achievement of ecological priorities
Generalizations Of 2-Absorbing Principally Right Primary Ideals In Non-Commutative Rings
No full textLet R be a non-commutative ring with 1 not equal 0 and S(R) be the set of all ideals of R. In this paper, we extend the concept of 2-absorbing principally right primary ideals to the context of phi-2-absorbing principally right primary ideals. Let phi : S(R)-* S(R) U {O} be a function. A proper ideal I of R is said to be a phi- 2-absorbing principally right primary ideal of R if whenever a, b, c E R with aRbRc C_ I and aRbRc not subset of phi(I) implies ab E I or ac E I or bc E I. A number of results and characterizations concerning phi-2-absorbing principally right primary ideals are given
The Relationship between Tourism Development and Economic Growth in Transition Economies: A Comparative Causality Analysis
Full text linkThe purpose of this study is to examine the relationship between tourism development
and economic growth in transition economies. For this objective, the symmetric
and asymmetric panel causality approach is employed to examine the relationship
between economic growth and tourism development in eight EU member transition
economies and six non-EU transition economies from 1995 to 2017. The symmetrical
causality test results show no evidence of a causal relationship between tourism
development and economic growth for both EU and non-EU country groups.
The asymmetric causality test did not reveal any evidence of a causal relationship in
non-EU transition economies. On the other hand, EU-member transition economies
have identified a bidirectional causal relationship between negative components of
tourism development and economic growth, and a unidirectional causal relationship
between positive components of tourism development. Asymmetric causality test
indicates a hidden cause-and-effect relationship for the EU member country group
but not for the non-EU country group. Determination of the hidden causality relationship
and measurement of positive and negative shocks between tourism development
and economic growth significantly contributes in the existing literature. We
also expect that the determination of this causality relationship enriches and expands
tourism policies in the face of the reactions of positive and negative shocks, and it
may guide the development of effective tourism policies that serve as a complement
to economic growth and tourism development
Evaluation of Factors Influencing the Quality of Life of Older Adult Earthquake Survivors in Türkiye: A Cross-Sectional Interview-Based Study
No full textObjective
Due to frailty, chronic health issues, limited mobility, dependence on assistive devices, and polypharmacy, the geriatric population is more susceptible to the adverse effects of earthquakes. The aim of this study was to determine the factors affecting the quality of life of older adults who experienced the Kahramanmaraş-centered earthquakes in Türkiye on February 6, 2023.
Methods
This cross-sectional interview-based study was conducted with 340 older adults who experienced the earthquakes on February 6, 2023, and visited outpatient departments in Gaziantep. Data were gathered using a demographic form, Modified Fried Frailty Index, and WHO Quality of Life Instrument for Older Adults.
Results
Participants’ average age was 71.37 ± 6.56 years, and 56.6% were women. Among them, 20.9% lost a first-degree relative, 15.3% were injured, and 45.3% were displaced. WHOQOL-OLD scores differed significantly by age, marital status, education, chronic illness, polypharmacy, living arrangements, and frailty.
Conclusions
This study highlights the factors influencing the quality of life of older adults in Türkiye after an earthquake. Living with a spouse and having primary or secondary education improved quality of life, while chronic illnesses and displacement had negative impacts. These findings emphasize the importance of considering the specific needs of older adults in disaster preparedness and response
Turkish Russian relations 1600-2024, an analysis based on expert opinions & perceptions
Full text linkThe research critically analyzes Turkish-Russian relations between 1600 and 2024 on the basis of expert views regarding historical, geopolitical, security, ideological, economic, and contemporary factors influencing the bilateral relationship. A quantitative research method involved a structured survey of 88 respondents, including media professionals, political analysts, and specialists with either direct or indirect exposure to Turkish-Russian relations. The data collected through the survey were used to identify key determinants influencing policy formation and bilateral relations. The findings indicate that geopolitical and national security concerns are perceived as major drivers of the relationship, followed by economic interdependence in trade and energy sectors. Historical legacies, and also ideological trends such as nationalism and religion, are perceived to be moderate drivers. The analysis also reveals that the perceptions are shaped by respondents' nationality, academic background, and cultural exposure. Although the study references theoretical paradigms like realism, liberalism, and constructivism in placing the findings, the focus is primarily on mapping and examining perceptions from experts. The study ends by offering practitioner suggestions for enhancing cooperative endeavors through realistic diplomacy, economic engagement, and strategic balance, thereby furthering the understanding of this complex and dynamic bilateral relationship. The recommendations and practical implications include the development of confidence-building measures, strengthening cooperative economic activities, and promoting exchanges on the cultural and academic levels for strengthening bilateral relations.Bu araştırma, Türk-Rus ilişkilerini 1600 ile 2024 yılları arasında etkileyen tarihî, jeopolitik, güvenlik, ideolojik, ekonomik ve çağdaş faktörler bağlamında uzman görüşlerine dayanarak eleştirel bir şekilde analiz etmektedir. Nicel bir araştırma yöntemi kapsamında, Türk-Rus ilişkileriyle doğrudan ya da dolaylı temas hâlinde olan medya mensupları, siyasi analistler ve uzmanlardan oluşan 88 katılımcıyla yapılandırılmış bir anket uygulanmıştır. Anket yoluyla toplanan veriler, politika oluşturma sürecini ve ikili ilişkileri etkileyen temel belirleyicileri ortaya koymak amacıyla kullanılmıştır. Elde edilen bulgular, ilişkilerin en önemli itici güçleri olarak jeopolitik ve ulusal güvenlik kaygılarının öne çıktığını; bunu ticaret ve enerji sektörlerindeki ekonomik karşılıklı bağımlılığın izlediğini göstermektedir. Tarihsel miraslar ile milliyetçilik ve din gibi ideolojik eğilimler ise orta düzeyde etkili faktörler olarak değerlendirilmektedir. Analiz ayrıca, algıların katılımcıların milliyeti, akademik geçmişi ve kültürel birikimi doğrultusunda şekillendiğini ortaya koymaktadır. Araştırma, bulgularını yerleştirirken realizm, liberalizm ve inşacılık gibi kuramsal paradigmaları referans alsa da, esas odak uzmanların algılarını haritalandırmak ve incelemek üzerinedir. Çalışma, gerçekçi diplomasi, ekonomik iş birliği ve stratejik denge yoluyla iş birliğini artırmaya yönelik uygulayıcılara yönelik öneriler sunarak bu karmaşık ve dinamik ikili ilişkiye dair anlayışı derinleştirmeyi amaçlamaktadır. Son olarak, öneriler ve pratik sonuçlar arasında güven artırıcı önlemlerin geliştirilmesi, ekonomik iş birliğinin güçlendirilmesi ve kültürel ile akademik düzeyde karşılıklı değişimlerin teşvik edilmesi yer almaktadır. Bu öneriler, Türk-Rus ilişkilerinin daha sağlam temeller üzerinde ilerlemesine katkı sağlamayı hedeflemektedir
The phenomenological examination of Turkish mothers who have hemophilic sons
Full text linkHemophilia is a coagulation disorder characterized by bleeding episodes that are genetically transmitted from mothers to sons. The
disease affects the family psychologically and socially, especially the mothers, who are closely involved in the care of the affected child. We aimed
to question the experiences of Turkish mothers with children diagnosed with hemophilia.
Method: The study is based on phenomenology, one of the qualitative research designs. We conducted and recorded face-to-face interviews with
nine mothers of patients with severe hemophilia A. Each of the semi-structured interviews, in which the interview form consisting of 23 questions
was used, lasted approximately 40 minutes. After the recorded data were deciphered, the interviews were analyzed using qualitative analysis
methods and presented under six themes.
Results: There is long-term anxiety in the daily life of mothers. Fatalism in Islam and the presence of a hemophilic individual in the family were the
most important factors in accepting the disease. However, the mothers have the potential to live an uneasy and anxious life. It limits the social life of
both the hemophilic son and the mother. Children are placed in a “glass bell” like a lonely fish during early childhood. The glass bell suddenly breaks
at the beginning of school, and children face various social-emotional risks. In the adolescent period, children’s social life expands, and mothers’
anxiety about the future of their children begins to increase.
Conclusion: As we know, treatment compliance can improve the quality of life in children with hemophilia. To ensure this compliance, knowing
and identifying the psychosocial burden of the disease on the mother and finding solutions will increase her child’s compliance with hemophilia
treatment and life expectancy