درخت حوزه‌های تخصصی

Mild Cognitive Impairment (MCI) represents a transitional phase between normal aging and dementia, primarily affecting memory. It affects nearly one-fifth of adults over 50 worldwide, highlighting its growing clinical importance. Pharmacological treatments have shown limited efficacy, prompting interest in non-invasive interventions such as transcranial direct current stimulation (tDCS), which modulates cortical excitability through weak electrical currents. This systematic review aimed to evaluate the effects of tDCS on memory performance in older adults with MCI and to identify protocol-specific predictors of improvement. A systematic search was conducted in PubMed, Scopus, and Web of Science (up to April 2025) following PRISMA guidelines. Eligible studies included randomized and non-randomized trials examining tDCS alone or combined with cognitive training in adults aged 60 years and older with MCI. Ten studies (N = 428) met inclusion criteria. Due to heterogeneity, findings were synthesized narratively. Overall, tDCS significantly improved verbal and recognition memory, as well as spatial and episodic memory performance. Neurophysiological findings indicated enhanced neural activity and connectivity. Stimulation targeting the left dorsolateral prefrontal cortex produced the most consistent benefits, especially when applied for ten or more sessions at an intensity of 2 mA. Mild side effects, such as redness and tingling, occurred in approximately 20–30% of participants, with no serious adverse events reported. Preliminary evidence supports the effectiveness and safety of tDCS in improving memory among individuals with MCI. However, variability in protocols and small sample sizes underscore the need for standardized, biomarker-guided, and longitudinal research.

Based on conducted studies, lighting in Iranian architecture is one of the fundamental and essential features, with skylights playing a crucial role as a primary architectural element. Architecture in different regions is adjusted according to climatic conditions to maximize comfort while also considering the use of local materials. Given this, the design and placement of lighting elements can vary based on geographic location. The aim of this research is to examine the skylights in Qajar-era houses in Kerman and to explore the relationship between climate and regional architecture, considering both lighting and temperature factors simultaneously. Thus, the research questions are as follows: What are the characteristics of the windows in the historical houses of Kerman? Was natural light considered a key element in Kerman’s houses? Were the variety of windows in these historical homes adjusted based on climatic conditions? To achieve this goal, we studied four Qajar-era houses in Kerman: Azimi House, Kazemi House, Dinyar House, and Vaziri House. The research method is applied in nature and employs a descriptive and correlational approach for data collection, utilizing both field studies and library resources. By measuring the skylights and analyzing their design and positioning, we concluded that in desert regions, skylights are designed with small dimensions and colored glass to not only prevent direct sunlight but also regulate the lighting of the space. Additionally, these skylights are placed one meter above the floor and with a depth of less than 10 meters, providing both aesthetic appeal and environmental comfort.

This study explores whether combining Empirical Mode Decomposition (EMD) with machine learning models Artificial Neural Networks (ANN), Recurrent Neural Networks (RNN), and Long Short-Term Memory (LSTM)—can improve the accuracy of Bitcoin price volatility (VBTC) predictions. Utilizing daily Bitcoin price data from September 2011 to December 2024, the research, conducted using R software, compares the performance of hybrid models (EMD-ANN, EMD-RNN, EMD-LSTM) against standalone machine learning models and traditional time series methods like ARIMA. The results demonstrate that hybrid models significantly outperform their non-hybrid counterparts, with the EMD-RNN model achieving the highest accuracy, reducing Mean Absolute Error (MAE) by 95.76% and Root Mean Squared Error (RMSE) by 96.35%. The decomposition of VBTC into Intrinsic Mode Functions (IMFs) revealed distinct short-term and long-term volatility components, providing deeper insights into market behavior. The findings highlight the superiority of integrating EMD with machine learning for volatility forecasting, offering enhanced predictive accuracy and robustness. This research underscores the potential of advanced analytical techniques in improving risk management and investment strategies in highly volatile cryptocurrency markets.

This research discusses the pedagogical relevance of German idioms and Persian proverbs in language acquisition and intercultural communication. Idioms and proverbs are extremely useful in language competence and culture awareness development, but they are also very challenging for learners due to their non-literal nature and cultural boundness. This study uses a qualitative design to investigate how the use of idiomatic language in real communicative contexts improves comprehension, memorability, and intercultural competence in German language learners. Data were gathered based on semi-structured interviews with experienced teachers and advanced learners, and content analysis of idiomatic language selected from German and Persian texts. The findings show that the integration of cognitive and sociolinguistic approaches optimizes learners' ability to interpret idiomatic meaning and use them appropriately. Besides, computer-mediated resources and multimedia technology support memorization of idioms and their application in context. The instructional model in the research, by incorporating metaphorical comprehension with cultural contextualization, addresses knowledge gaps in traditional idiom instruction and emphasizes the necessity for contextualized learning environments. By enhancing both cultural sensitivity and language proficiency, this research has valuable pedagogical implications for language teachers and curriculum planners. Follow-up research should investigate the application of technology-assisted idiom learning in various linguistic and cultural contexts to validate the usefulness of the model suggested.

In recent years, many educational experts have concluded that game is one of the key elements in learning various skills in children, especially social skills. The aim of the present study was to identify the components of games based on social skill development for preschools in order to design a desirable model. The present study was conducted using a qualitative approach, specifically the grounded theory method. Data were collected through 25 semi-structured interviews with preschool teachers and educators who had valuable experiences related to the research topic using purposive sampling (snowball), and were analyzed in three main stages: open, axial, and selective coding. Interview data analysis revealed five main categories which affect educational games based on social skill development model; namely, causal factors, contextual factors, intervening factors, strategies, and advantages. It is concluded that proper implementation of a game-based social skills curriculum and paying attention to its various elements can lead to a child's physical, mental, and sensory development.