This article introduces an innovative fuzzy-based approach for developing a comprehensive portfolio optimization model that effectively accounts for inherent uncertainty while incorporating the investor's unique perspective on the dynamic stock market. The multi-objective optimization framework employs Conditional Drawdown at Risk to enhance investor flexibility in determining risk tolerance and optimal investment strategies tailored to specific needs. The research is notable for its pioneering use of intelligent methods to systematically collect valuable data from the Tehran Stock Exchange under fuzzy uncertainty. It incorporates important constraints such as cardinality and ceiling and floor limits for each investment period, allowing for a detailed analysis of various stock market scenarios and potential future outcomes. A case study is conducted with 25 diverse assets from the top five industry groups based on profit per share, from which five shares are thoughtfully selected to effectively demonstrate the model's unique effectiveness. The analysis rigorously assesses the model's performance in real-world conditions, highlighting the importance of accurately understanding the current stock market outlook and trends. To validate the model, the research compares results with a portfolio constructed under similar conditions of certainty and risk. The findings indicate that portfolios created under certainty yield significantly higher values, suggesting that successful portfolio construction is heavily influenced by the prevailing market conditions experienced by investors.

Portfolio optimization is a widely recognized strategy for investing that involves selecting a combination of assets that offers the optimal balance between potential gains and volatility. Traditional portfolio optimization typically focuses on a single period, considering only the current market conditions. However, multi-period portfolio optimization takes a more comprehensive approach by incorporating the dynamic nature of financial markets over multiple periods. Hence in this study, we focus on multi-period portfolio optimization. We conduct a bibliometric analysis of articles on multi-period portfolio optimization in the Web of Science (WoS) database. Through quantitative methods and the utilization of the Bibliometrix R package, we analyze publication trends, key research sites, and historical output in this field. Our findings provide valuable insights into the current state of research on multi-period portfolio optimization. This bibliometric analysis contributes to the existing literature on multi-period portfolio optimization and serves as a valuable resource for researchers, policymakers, and practitioners in the field of finance.

Portfolio optimization aims to minimize risk and maximize return on investment by determining the best combination of securities and proportions. The variance in portfolio optimization models is typically used for a measure of risk. Over the last few decades, portfolio optimization utilizing a variety of risk measures has grown significantly, and many studies have been conducted. Therefore, this paper provides a systematic review of risk measures for portfolio optimization using bibliometric analysis and maps to analyze the evolution and trends of 682 articles published between 2000 and 2022. Throughout this analysis, communication networks among articles, authors, sources, countries, and keywords are explored. Furthermore, a classification of risks and risk measures were presented to demonstrate a comprehensive overview of the field, and the top 50 papers were analyzed to determine which risk measures were most often used in recent studies.

The complexity and vulnerability of supply chains in today's globalized economy have heightened the significance of understanding and managing disruptions. Supply chain disruptions, ranging from natural disasters to pandemics, can lead to substantial delays, increased costs, and reduced quality, thereby impacting the operational performance and stability of businesses. Considering the theoretical sophistication and substantial relevance of the field, this research seeks to conduct an extensive bibliometric analysis of supply chain disruption. The goal is to offer a thorough summary of recent advancements and ongoing progress in this specific area. Additionally, it aims to pinpoint emerging research patterns that can guide future studies. We performed a bibliometric review of the structure and global trends of disruptions among supply chains, from 1996 to 2024 using techniques such as analysis of (1) the dataset, (2) sources, (3) authors, (4) countries and institutions, (5) documents, and (6) keywords. A total of 1356 bibliographic records from Web of Science databases were analyzed to generate the study’s research data through Scientometrics networks. The paper concludes by discussing the strengths and limitations of the study and suggesting potential avenues for future research, aiming to guide and inform future studies in this critical area of supply chain management. The findings of this study will enhance understanding of the prevailing patterns in this topic, thus laying the groundwork for future research initiatives in this field.

The capital market, as one of the main components of the financial markets, plays an important role in the economic development of countries. As financial markets become more globalized through the free flow of capital and international trade, price fluctuations in financial assets also affect other assets and markets. Due to the high impact of foreign exchange, gold, and oil markets on other financial markets, this study examined the impact of these markets on the Tehran Stock Exchange market from April 2015 to March 2021. In this regard, US dollar, ounces of gold, and crude oil are used as independent variables, and Tehran Price Index (TEPIX) is considered as a dependent variable. The results of the final model indicate that the prices of dollars, gold, and oil had significant effects on the total price index of the Tehran Stock Exchange.

The capital market is one of the most critical pillars of financial markets, which plays an important role in countries' economies. With the increasing development of international trade and the free flow of capital, financial asset prices spread to other assets. The extend is increasing with the expansion of communication networks as well as the close connection of financial markets to each other. Therefore, the state of a market is not only specific to itself but also affects other financial markets. Global oil, gold, and basic metal prices, including palladium, significantly influence the American financial markets. Due to the importance of the Nasdaq index for investors' investment decisions, this study analyzes the impact of oil, gold, and palladium metal prices on the Nasdaq index monthly between 2016 and 2021. Based on the final model, the oil and gold markets significantly impact the Nasdaq index, while palladium has a less significant impact.

In contemporary medicine, two trends are of particular significance: the establishment of Telehealth as a fundamental component of healthcare delivery, and the emergence of Large Language Models (LLMs) as a transformative category of artificial intelligence. The convergence of these domains has created a new, dynamic, and rapidly expanding research frontier. Despite this escalating interest, a comprehensive map of the field's intellectual foundations, key contributors, and thematic progression has yet to be established. This study addresses this critical knowledge gap by employing a quantitative scientometric methodology to systematically map the intellectual structure and evolutionary trajectory of research at the intersection of Telehealth and LLMs. We conducted a comprehensive bibliometric analysis of 670 scientific documents extracted from the Web of Science (WoS) Core Collection database, spanning the period from 1997 to Oct 2025. The analysis utilized performance metrics and network mapping tools to identify publication dynamics, influential actors, and core conceptual themes. The findings reveal a field in a state of “Hypergrowth“, characterized by an exponential increase in scientific production, particularly after 2021. The United States and China are identified as the dominant leaders in research output. Thematic analysis demonstrates a clear paradigm shift within the literature: an evolution from a broad focus on general artificial intelligence and machine learning applications toward a more specialized and intense concentration on the capabilities and implications of LLMs and Generative AI. This research provides the first large-scale quantitative map of the Telehealth and LLM landscape. It documents a field that is maturing at an accelerated rate, creating an urgent need for scholarly and practical frameworks that bridge the gap between rapid technological innovation and the slower-moving, yet critical, domains of clinical validation, regulatory oversight, and ethical considerations. The insights provided herein offer a data-driven foundation for researchers, policymakers, and practitioners to navigate and contribute to this critical and rapidly evolving field.

Semaglutide, which is a glucagon-like peptide-1 receptor agonist (GLP-1 RA), has shown significant effects for weight loss in RCTs. However, good results obtained during clinical trials are not necessarily reflected in everyday practice because of factors such as adherence, dosing, patient differences, and healthcare system limitations. In this review, we present the results of 67 studies as real-world evidence (RWE) that help to assess semaglutide's effectiveness in weight control. RWE gives a constant message that semaglutide does indeed cause weight loss that is clinically significant in varieties of patients including those with type 2 diabetes (T2D) and simply obesity. Although the reduction in weight in real clinical situations is generally somewhat less than in RCTs, the studies speak of weight losses of 4-6% over 6-7 months and 9-15% over 12 months, with even greater losses among the most compliant patients. Some of the main barriers are identified as high dropout rates, inadequate dose titration, and the effects of both access and cost. Nevertheless, semaglutide proves to be a very effective option in standard care, with its positive effects on glycemic control, cardiovascular risk factors, and patient-reported outcomes. This paper highlights the importance of RWE in confirming, and sometimes even augmenting, RCT outcomes, as well as in providing support for clinical decision making in weight loss therapy.