درخت حوزه‌های تخصصی

The Bayazid Bastami complex, located in Bastam, Semnan province, is considered one of the outstanding examples of the Iranian religious architecture during the Ilkhanid era. Due to the existence of a renowned Sufi’s shrine, Bayazid Bastami (161-234 AH), this complex has attracted the attention of different reigns and kings since the very early Islamic period, and numerous constructions have been performed in this monument during various periods from the Deylamiyān (Deylamites) dynasty to the Qajar period. Most of the constructions in this complex and also the restorations conducted here relate to the Ilkhanid era, and particularly to Sultan Muhammad Ghazan Khan’s reign (694-703 AH) and Sultan Mohammad Khodābandeh Öljaitü’s time (703-716 AH). Thanks to his high regard for Bayazid, Öljaitü even selected his own children’s names according to Bayazid’s name and titles: Bastam, Bayazid, and Ṭayfūr. In various Ilkhanid buildings and extensions in Bayazid Bastami’s complex, numerous inscriptions can be seen that have adorned the architectural elements of this complex. Due to the existence of multiple features and the religious importance of this part, inscriptions on the mihrab of this mosque, called Mardana or Bayazid, have been widely investigated and analyzed from different aspects, including ritual, artistic, and historical. In the present research, a descriptive-analytical methodology has been applied, and the data have been collected from documentary and field studies with a theoretical approach to study the cultural history.  

Examining administrative artefacts from the Proto-Elamite period in Susa through a phenomenological lens allows historians and archaeologists to contextualize these documents not only as dormant material culture but also as dynamic instruments in negotiating economic control, political authority, and institutional identity. This article draws on newly reevaluated evidence of clay sealing strips housed in the National Museum of Iran, interpreted initially as “wall sealings” by Holly Pittman. It reconsiders their function in light of comparative frameworks developed by Adelheid Otto for Middle Bronze Age Syria. By situating these items within the broader conceptual field of “administrative writing”, here extended to include physical sealing devices as protoarchival media, this study examines the thematic frameworks, authorial stances, and intended audiences embedded in both the ancient administrative practices and the modern scholarly discourse. Rather than occupying a marginal position in archaeological literature, these sealing strips emerge as powerful heuristic tools for understanding the evolution of bureaucratic management in early Iranian state formations.

Tourism is widely acknowledged as a potential engine of economic growth and poverty reduction, particularly in developing countries. This research investigates the impact of tourist growth on poverty reduction in Wukari Local Government Area, Taraba State, Nigeria. The study concentrated on its contributions, problems, and ideas for increasing its pro-poor effect. The questionnaire was applied to obtain data from 400 respondents. The data were examined descriptively. The findings show a clear consensus that tourism may greatly help to poverty reduction, with job creation and income generation highlighted as main advantages. However, fundamental constraints such as inadequate infrastructure, poor security, and little government backing impede tourist expansion. Respondents significantly approve policies such as government infrastructure investment, enhanced security measures, entrepreneurial training, awareness campaigns, and community participation in tourist planning. The study indicates that tourism has significant potential for poverty reduction in Wukari LGA, and that focused interventions are required to solve its obstacles for long-term and inclusive growth.

Objective : The global increase in the elderly population has heightened the need for coordinated, tailored healthcare services that address the complex needs of older adults. This study aims to conceptualize the elderly healthcare ecosystem by identifying its key actors, classifying their roles, and examining the nature of their interactions. Methodology: A multi-stage methodological approach was employed. First, an extensive literature review—focusing on healthcare ecosystems and ageing studies—was conducted to develop an initial analytical framework. Based on this, ecosystem actors were identified and categorized using Mitchell et al.’s Stakeholder Salience Model. An expert panel was then consulted to validate actor attributes and refine classifications. To analyze interdependencies and determine influential actors, a Fuzzy Cognitive Map was constructed, enabling the assessment of causal relationships and the dynamic positioning of stakeholders within the ecosystem. Results : The analysis identified seven groups of actors within the healthcare ecosystem. FCM findings reveal that the elderly, families, and medical centers are the most influential actors. At the same time, the Ministry of Health and Medical Education, insurance and pension funds, and the Ministry of Cooperatives, Labor, and Social Welfare emerge as the most influential and central stakeholders in advancing ecosystem objectives. Conclusion : The study demonstrates that the elderly healthcare ecosystem is inherently dynamic, and stakeholder classifications should not be viewed as static. Attributes such as power, legitimacy, and urgency are fluid and context-dependent. The FCM results further highlight this dynamism by illustrating how shifts in causal relationships can reposition actors across stakeholder categories, underscoring the need for adaptive policymaking.

This study examines the convergence of law, beauty standards, and feminist-Foucauldian theory, emphasising the influence of beauty myths on cultural norms and legal frameworks. Beauty standards, shaped by media, commercial, and legal structures, establish a restrictive and exclusive notion of beauty, frequently favouring lighter complexion, thinner physiques, and straight hair. These norms, devoid of a biological foundation, originate from social constructs that perpetuate patriarchal and capitalist ideologies. The law significantly reinforces these standars by normalizing certain physical traita and marginalising those who differ. Utilising Foucault’s notion of “disciplinary power,” the examination emphasises how individuals internalise societal norms and consciously modify their bodies to conform to these standards. It also attacks the legal system’s inadequacy in addressing body image discrimination, which exacerbates the marginalisation of individuals who diverge from conventional beauty standards. This study underscores the significance of intersectionality, asserting how beauty myths intersect with race, gender, and class, while urging legal frameworks that accommodate diverse body types to strengthen equality and protect against appearance-based discrimination.

This study examines Russia’s strategic culture in West Asia and its implications for bilateral relations with Iran from the post-Soviet period (1991) to recent developments in 2025. Employing a qualitative framework rooted in strategic culture analysis, the research demonstrates that Russia’s approach toward Iran is shaped by pragmatic opportunism, historical experience, and a desire to maintain regional influence without overcommitting militarily. Findings reveal that Moscow engages with Tehran episodically, balancing cooperation against shared threats with strategic caution to preserve flexibility in relations with other regional actors, including Israel, Saudi Arabia, and Turkey. Brief episodes such as the U.S. and Israeli strikes on Iranian nuclear facilities, the Syrian crisis, and the ongoing war in Ukraine illustrate how Russia mediates, condemns actions diplomatically, and selectively coordinates with Iran without offering binding security guarantees. The study identifies a persistent divergence in perceptions: Russia often views Iran as a secondary, conditional partner, whereas Tehran expects collaboration on an equal footing. Despite these differences, mutual interests in regional stability, energy cooperation, and strategic depth create occasions for tactical alignment, particularly under external pressures. Overall, the results demonstrate that the Russia–Iran relationship is conditional, adaptive, and strategically ambiguous, with cooperation shaped less by ideological convergence and more by pragmatic calculations. By situating these interactions within the framework of strategic culture, the study provides a nuanced understanding of the limits and possibilities of Russia–Iran engagement in West Asia, highlighting how historical legacies, geopolitical constraints, and contemporary crises collectively define a partnership that is influential yet inherently fragile.

Forecasting financial variables, especially the returns of debt instruments, plays a vital role in economic decision-making and risk management. Although the forecasting literature in financial markets is extensive, few studies have focused on predicting the returns of Islamic Treasury Bonds with unconventional structures. Moreover, despite the importance of these bonds, very limited work has been done using machine learning in the debt market. This study aims to predict the returns of Islamic Treasury Bonds using three models: Multiple Linear Regression (MLR), Multilayer Perceptron Neural Network (MLP), and Radial Basis Function Neural Network (RBF). Monthly data from 2018 to 2023 were collected using Excel and Python. The training and evaluation of the models were carried out in MATLAB. Eleven influential variables were selected based on previous studies and expert opinions. The models' performance was evaluated using Root Mean Square Error (RMSE) and the coefficient of determination (R²). The findings indicate that the Multilayer Perceptron Neural Network model has higher accuracy in predicting the returns of Islamic Treasury Bonds compared to Multiple Linear Regression and Radial Basis Function models. These results suggest that neural network models can serve as more effective tools in financial and economic analyses, significantly enhancing forecasting accuracy.

A newly discovered Elamite rock relief in the Alhak region of central Izeh in southwestern Iran contributes significantly to the corpus of commemorative Elamite art. Unlike other well-known reliefs from the area—such as those at Kūl-i Farah, Shahsavar, and Khung-i Azhdar—this composition was carved onto a conglomerate rock surface, a medium both unique and inherently fragile, leading to its accelerated erosion and delayed recognition. The relief depicts a male figure seated in profile on a simple throne, raising his right hand in a gesture of reverence or supplication. A stepped platform lies before him, while a prominent solar disc hovers above his head—features resonant with iconographic motifs found on contemporaneous cylinder seals from Elam and Mesopotamia. Iconographic and stylistic parallels suggest that the Alhak relief belongs to the Shimashki cultural horizon (ca. 2000–1970 BCE). The absence of divine attributes—such as horned crowns or zoomorphic insignia—indicates that the figure is more plausibly interpreted as a royal personage engaged in ritual devotion rather than a deity. The rightward orientation of the seated figure, in contrast to the left-facing postures of most Izeh reliefs, further underscores its distinctiveness. This discovery broadens our understanding of regional variability within Elamite rock art. It highlights the cultural resilience of Elamite traditions in the highlands following the collapse of lowland power centers such as Susa. Future investigations employing advanced imaging technologies (e.g., 3D scanning and photogrammetry) are essential for recovering lost details and refining our interpretation of the relief’s symbolic schema.

In data-driven marketing, customer behavior analysis plays a crucial role in developing targeted marketing strategies aimed at increasing return on investment, enhancing profitability, and gaining a larger market share. In this study, four clustering methods- including K-means, density-based clustering, principal component analysis, and hierarchical clustering- as well as four classification methods- including Support Vector Machine, XGBoost, Random Forest, and Gradient Boosting- are examined for customer behavior analysis. The data for this study was extracted from the "Amazon Customer Behavior Survey" dataset, which includes 23 features from 602 customers. Initially, the data was preprocessed, and then, using clustering methods, customers were divided into different groups. The performance of these methods was evaluated based on criteria such as the silhouette index, and ultimately, appropriate marketing strategies for each cluster were proposed. Additionally, to examine the possibility of predicting customer membership in the extracted clusters, the aforementioned classification models were implemented and compared. The results indicate that the K-means method performed the best in clustering, while the XGBoost model performed the best in classification. The innovation of this research lies in combining clustering and classification methods to provide targeted marketing strategies and comprehensively comparing these methods on real customer data. This study demonstrates that combining clustering and classification methods can help businesses better understand customer behavior and make more optimal marketing decisions.

As a trigger to communication, motivation still includes undiscovered aspects which require further investigation. Hence, considering the newly proposed dual continuum model of motivation, this study investigated the relationships among willingness to communicate (WTC), active/passive motivation, and foreign language achievement (FLA) among 216 high school English as a foreign language (EFL) learners. The modified version of the active/passive motivation scale (APMS) was revalidated using confirmatory factor analysis (CFA). Structural equation modeling (SEM) revealed significant relationships among active/passive motivation, L2WTC, and FLA. Additionally, six models were proposed for the prediction of learners’ L2WTC and FLA. The findings indicated that socio-cultural and sensory-perceptual active motivation as well as cognitive and sensory-perceptual passive motivation significantly predict learners’ L2WTC, while only cognitive active motivation predicts FLA. Furthermore, passive motivation predicts FLA in all sub-constructs. Finally, active motivation is a negative predictor of FLA if mediated by L2WTC. Overall, the study highlights the importance of passive as well as active motivation in promoting WTC and improving FLA among EFL learners.

English Medium Instruction (EMI) is increasingly adopted in higher education worldwide, yet its application in music education within non-English-speaking contexts remains underexplored. The application of EMI plays a crucial role in improving learners' English skills and subject matter, which can also affect learners' achievement. The most important predictor of learners' performance and success is self-efficacy, which is also a relevant concept in the area of music performance. This Review investigates the role of self-efficacy in shaping music students' academic achievement in EMI settings, where language and performance intersect. The study aims to identify how learners' self-efficacy in their musical and linguistic abilities influences their success and motivation. It contributes to EMI literature by highlighting self-efficacy as a mediating factor between language proficiency and academic performance in music education. The findings offer practical implications for curriculum design, instructional strategies, and learner support. Specifically, the study emphasizes the need to integrate self-efficacy-building practices—such as performance feedback, peer collaboration, and goal-setting—into EMI-based music instruction to enhance both linguistic and artistic development.