Search Results (23)

This study presents a critical historical, bibliometric, and technological overview of the evolution of postharvest science, emphasizing the transition from classical physiology-based approaches to emerging predictive and technology-driven systems. Scientific production related to postharvest research was analyzed using the Scopus and Web of Science databases, while bibliometric mapping and co-occurrence networks were generated using VOSviewer to identify thematic trends, emerging research areas, and structural scientific clusters. In parallel, a technological foresight analysis was conducted through the Lens.org platform to investigate the temporal evolution of patent deposits, the geographical distribution of innovation, the leading institutional applicants, and the predominant technological domains according to the Cooperative Patent Classification (CPC). The results revealed a substantial global expansion of postharvest research over recent decades. This growth was accompanied by increasing technological diversification and stronger integration between scientific knowledge and intellectual property protection. The analysis also highlighted the progressive incorporation of advanced methodologies into postharvest science, including biochemical approaches, non-destructive technologies, artificial intelligence, predictive modeling, and digital tools for quality assessment and shelf-life management. Overall, the study demonstrates that postharvest science is undergoing a paradigmatic transition toward integrated, multidisciplinary, and data-driven systems aligned with current demands for sustainability, food security, innovation, and reduction of postharvest losses. Full article

Research Purpose: This study investigates the role of digital investor behavior, measured through Google Trends, alongside technical indicators such as RSI and Bollinger Bands, in forecasting volatility in the Dubai Financial Market. The aim is to develop a hybrid analytical framework that integrates behavioral and technical dimensions to enhance predictive accuracy in emerging markets. Study Methodology: Daily data from 2020 to 2025 were collected, covering both crisis and post-crisis periods. Digital attention was quantified using Google Trends search indices, while technical indicators included RSI and Bollinger Bands calculated over a 7-day horizon. Volatility was modeled using ARCH, GARCH, and EGARCH frameworks, with Max Drawdown employed as a complementary risk metric to capture extreme market movements. Findings: Digital investor attention shows a predictive association with volatility, particularly when combined with technical indicators. Models incorporating both behavioral and technical variables demonstrated superior predictive performance. The EGARCH model successfully captured the asymmetric impact of negative shocks (γ < 0, p < 0.05), while Max Drawdown provided additional insights into risk exposure during periods of heightened market stress, achieving an R² of 95.36%. Scientific value: This study positions digital attention as a complementary variable that improves forecasting, moving beyond conventional price-based models in volatility modeling; by integrating Google Trends with technical analysis, the research introduces a hybrid forecasting framework that can be adapted to other emerging markets. Practical Implications: The findings offer practical value for policymakers and investors. Regulators can use digital attention measures as early warning signals to anticipate volatility, while investors can integrate behavioral and technical indicators to improve risk management and trading strategies. From a foresight perspective, the study contributes to building more resilient financial systems by embedding behavioral data into predictive tools. Full article

Singular Design Foresight (SDF) is proposed as a foundational methodological framework for advancing Design Foresight (DF) toward a more explicit, traceable, and evaluable scientific discipline. The framework formalizes DF as a structured cycle in which qualitative foresight inputs—such as signals, trends, and expert interpretations—are progressively transformed into analyzable representations that support decision closure under conditions of structural uncertainty. SDF combines an expert-defined conceptual universe with semantic projections to relate textual and contextual evidence to anticipatory constructs, enabling the generation of traceable indicators and structured configurations of viable futures. Within this architecture, the Stakeholder Viability Principle (SVP) functions as a filtering mechanism that delimits relevant futures according to continuity, agency, and axiological coherence, while Social Singularity captures context-specific critical transitions that shape when and why decision closure becomes necessary. The framework is organized in alignment with Design Science Research (DSR), adopting an evaluation logic centered on validity, utility, and attribution. Rather than presenting conclusive system-level validation, the article synthesizes summative evidence from previously published studies on semantic projections, singularity detection, and mixed expert–corpus foresight applications to support the plausibility, internal coherence, and operational feasibility of the proposed framework, while delimiting full integrated validation as a future research objective. SDF does not aim to provide deterministic prediction; instead, it enables auditable anticipatory representations and justified closure under uncertainty. In this sense, the framework is compatible with forecasting understood as the production of evaluable anticipations under explicit assumptions, while preserving the interpretive and situated character of strategic decision-making. Full article

In the context of intensifying climate and environmental changes, the high resilience of irrigation district infrastructure is of crucial importance for sustainable agriculture and water security. This paper proposes a resilience assessment indicator system for irrigation district infrastructure, comprising 23 indicators from the four dimensions of foresight capacity, absorption capacity, restoration capacity, and adaptive and learning capacity. This system is constructed by combining the research status quo at home and abroad with the change process of the resilience function. The model was constructed using the DEMATEL-ANP-Cloud method, and the Zhaokou Irrigation District in China was used as a case study to demonstrate the model’s application. The resilience analysis was conducted, and targeted strategies for enhancing resilience were proposed. The resilience assessment model constructed in this study provides a scientific basis for the resilience assessment of irrigation district infrastructure and a reference point for similar projects in terms of risk reduction and system resilience improvement. This is of great significance for guaranteeing sustainable agriculture and water security. Full article

In recent years, there have been frequent extreme weather events that defy traditional understanding. Specifically, mountain flood disasters can cause significant loss of life due to their sudden onset and destructive power. The 7.21 flood event in Xingyang, Zhengzhou, China, recorded a maximum 6 h precipitation of 240.5 mm in the Suo River basin, corresponding to a 500-year return period, and causing fatalities and substantial damage. The central government of China has launched supplementary mountain flood disaster surveys and evaluations involving key towns and villages, following an initial round of surveys in riverside villages, to improve foresight and response capabilities for mountain flood disaster risks under extreme conditions. This paper introduces the contents of the national mountain flood disaster surveys and evaluations of key towns and villages, elaborating on the principles, content, and rules for auditing the national survey and evaluation results. This paper innovatively proposes professional audit criteria, such as early warning indicators, monitoring facility correlations, and hazard zoning, based on a formal audit of the data quality. The implementation of professional audit criteria improved the data accuracy by 85% and reduced false alarms by 40%, enhancing the overall effectiveness of mountain flood disaster prevention. The analysis of the audit results suggests that the audit rules for the survey and evaluation results of key towns are scientific, reasonable, and effective, achieving the expected goals of data quality control. This approach can effectively enhance the practical value of the survey and evaluation outcomes for key towns, laying a solid data foundation for transforming flood disaster prevention from merely “existing” to “optimal”. Full article

The convergence of marine sciences and medical studies has the potential for substantial advances in healthcare. This study uses bibliometric and topic modeling studies to map the progression of research themes from 2000 to 2023, with an emphasis on the interdisciplinary subject of marine and medical sciences. Building on the global publication output at the interface between marine and medical sciences and using the Hierarchical Dirichlet Process, we discovered dominating research topics during three periods, emphasizing shifts in research focus and development trends. Our data show a significant rise in publication output, indicating a growing interest in using marine bioresources for medical applications. The paper identifies two main areas of active research, “natural product biochemistry” and “trace substance and genetics”, both with great therapeutic potential. We used social network analysis to map the collaborative networks and identify the prominent scholars and institutions driving this research and development progress. Our study indicates important paths for research policy and R&D management operating at the crossroads of healthcare innovation and marine sciences. It also underscores the significance of quantitative foresight methods and interdisciplinary teams in identifying and interpreting future scientific convergences and breakthroughs. Full article

Heilongjiang, located in the cold region, is China’s largest rice-producing and commercializing province. The variety selection of rice in cold regions (RCR) is indispensable in promoting the rice industry’s development, and technological innovation in breeding theory plays a significant role in breeding breakthrough. Based primarily on long-term research, contemplation, and breeding practices, the 4S (selected topic, selected breeding, selected progenies, and selected promotion) phenotypic-design breeding technical system for RCR, which has revolutionized the theoretical basis and deepened the conceptual model, has been developed through systematic analyses and generalization. The system covers several key aspects such as scientific question formulation, breeding objective optimization, parental taxa hybridization, progeny population selection, and innovation dissemination, aiming to improve the foresight, precision, and efficiency of breeding. Furthermore, the system has demonstrated successful cases of rice variety breeding over the past 20 years, such as for Suijing 3, Suijing 4, Suijing 18, and a series of other rice varieties, providing theoretical and technical supports for cold-region rice breeding. Full article

The article will contain a scientific analysis, showing thematic links between publications and consist of searching the data in the Scopus database. The timeframe of the searched publications will be 2010–2022. The parameters should also be narrowed down by selecting the following indexes: Science Citation Index Expanded (SCI-E), Social Science Citation Index (SSCI) and Emerging Sources Citation Index (ESCI), which was intended to eliminate abstracts of books and conference materials, leaving only reviewed works with the highest level of relevance for furthering knowledge. An additional limit of five minimum citations will be introduced. The analysis included 342 articles. Texts cited at least 100 times were highlighted. The research showed that authors focus piecemeal on selected aspects or problems, so an attempt was made to show thematic connections of keywords, illustrating the complexity of the transformations underway. The discussion identifies the most active authors and countries, especially exploring the topic of a transition to a sustainable energy system for smart cities. The authors have employed scientometric analysis to provide an objective and data-driven exploration of the transformation of sustainable energy systems for smart cities. This approach offers valuable insights into the research landscape, trends, and relationships within the field, which can guide future scientific research and contribute to a deeper understanding of the subject matter. As an additional element of this conclusion, the authors proposed supplementing the scientometric analysis with the foresight methodology. The authors’ research approach is distinguished by the following stages: problem formulation, data collection, choice of scientometric methodology, analysis of advantages and limitations of scientometrics, clustering analysis, data analysis, and presentation of results. Our systematic literature review systematizes the existing literature on the sustainable energy systems for smart cities, isolates main research interests, identifies future research avenues, and provides several important hints for researchers. Full article

As a pedagogical method to improve student recognition of Education for Sustainable Development (ESD) through scientific data reading, this study looked at the effects of learning in online academic discussions using data from global indicators. Students’ scholarly messages were coded and introduced into qualitative content analysis, sequential analysis, and social network analysis, which are emphasized, respectively, to investigate code co-occurrence, code sequence, and code distribution. In all, 307 messages appeared from 119 university students in the online community. The ESD competencies and collective intelligence (CI) are used as indicators for analyses. Qualitative content analysis, particularly addressing those sentences, proved that CI enhanced communication among students where they shared individual norms and values. Sequential analysis elucidated characteristics of discussion thread characteristics with CI, which induced further discussion with foresight views and questions. Social network analyses indicated students connected and showed the connection structure was meshed. Key student bridging messages were extracted. Whereas ESD competencies appeared effectively, the expansion of the current online environment must be regarded as including competency in participatory learning. After summarizing the effects of the online learning method in the Moodle forum environment, the method was proved to empower students to represent core competencies of ESD and to lead data-driven concept transformation. Full article

The study of a genesis is determined by the needs when designing the processes of high-tech development. This is performed taking the knowledge-intensive factors of a large knowledge economy into account under conditions of environmental uncertainty. An increase in the number of publications on the regulation of imbalances in the goals of innovation and efficiency that objectively arise in the processes of such development has been revealed. Therefore, the purpose of this study is to analyze models and socioeconomic approaches for the integration of mechanisms for foreseeing and controlling the development goals of enterprises in the processes of their genesis. This led to the improvement of the theory and the development of new methodologies, models, and methods for improving the quality of the management of the innovative development of enterprises according to sustainability criteria. Therefore, an analysis of textual sources was carried out, as it is crucial to understand various text-processing approaches to optimize the forecasting of long-term goals. An attempt was made to apply methods for assessing the quality of proposals available in the literature by a number of authors to summarize and discuss the current text-based socioeconomic advances in the aspect of forming a unified mechanism for improving the quality of governance. The properties of the monitoring of the factors of the knowledge economy and the strategic planning of development goals were analyzed. The quality of proposals was assessed in a procedure, and a discussion of the strengths and weaknesses of scientific approaches was conducted. This made it possible to determine the correspondence of approaches to the development of theories and new methodologies for the integration–balancing management of the integration and combination of resources by using a foresight-controlling mechanism. Moreover, this study also determines the prospects of the analyzed areas of socioeconomic research and project development. Full article

Scientific injection molding technologies involve the integration and collaboration of cyber-physical systems and smart manufacturing. In order to achieve adaptive process control and production optimization, injection molding systems with real-time sensing have gradually become the development- and application-trend of smart injection molding. At the same time, this technology is a highly non-linear process in which many factors affect the product quality during long-run fabrication processes. Therefore, in order to grasp changes in the characteristics of plastic materials and product quality monitoring, the injection process has become an important research topic. We installed sensors in the molding machine (injection barrel, nozzle, and mold-cavity) to collect the melting pressure and used different materials (semi-crystalline and amorphous polymer; the melting-fill-index (MFI) is unified to 14.5 ± 0.5 g/10 min) to explore the influences of melting pressure variation and its viscosity index on the quality characteristics of molded products. The experiment reveals that a combination of barrel, nozzle, and mold-cavity sensing on the melt-pressure trend-based injection process-control incorporated with viscosity index monitoring can confirm the weight and shrinkage variation of the injection product. At the same time, the pressure and viscosity index value measured and calculated during the melt-filling of two materials with similar MI resulted in significant variations in the amorphous polymer. This study showed the possibility of mastering and controlling the rheology (barrel position) and shrinkage properties of polymers and successful application in various product-quality monitoring platforms. Full article

The ecological quality of freshwater ecosystems is endangered by various micropollutants released into the environment by human activities. The cumulative effects of these micropollutants can affect the fitness of organisms and populations and the functional diversity of stream ecosystems. In this study, we investigated the relationships between the joint toxicity of micropollutants and trait syndromes. A trait syndrome corresponds to a combination of traits that could occur together in communities due to the trait selection driven by exposure to these micropollutants. Our objectives were to (i) identify trait syndromes specific to diatom, macroinvertebrate, and fish assemblages and their responses to exposure, taking into account four micropollutant types (mineral micropollutants, pesticides, PAHs, and other organic micropollutants) and nine modes of action (only for pesticides), (ii) explore how these syndromes vary within and among the three biological compartments, (iii) investigate the trait categories driving the responses of syndromes to micropollutant exposure, and (iv) identify specific taxa, so-called paragons, which are highly representative of these syndromes. To achieve these objectives, we analyzed a dataset including the biological and physico-chemical results of 2007 sampling events from a large-scale monitoring survey routinely performed in French wadeable streams. We have identified five (diatoms), eight (macroinvertebrates), and eight (fishes) trait syndromes, either positively or negatively related to an increasing toxicity gradient of different clusters of micropollutant types or modes of action. Our analyses identified several key trait categories and sets of paragons, exhibiting good potential for highlighting exposure by specific micropollutant types and modes of action. Overall, trait syndromes might represent a novel and integrative bioassessment tool, driven by the diversity of trait-based responses to increasing gradients of micropollutant toxic cocktails. Full article

This article presents a bibliometric analysis of scientific publications investigating technological megatrends at the societal level, through the parallel analysis of 549 documents from Scopus and 291 documents in Web of Science (WoS) using the VOSviewer software and the Excel component of the MS Office 365 package. The main purpose of this study was to obtain an overview of the evolution of the research on the subject of technological megatrends from the perspective of interest, domains, geographical areas, sources, authors and cocitation networks, research clusters of countries, and cluster-related concepts. The results showed that publications on technological megatrends started in 1982, but from a scientific point of view they started in 1983 (Scopus) and 1984 (WoS), and that they display an increasing trend after 2010. Technological Forecasting and Social Change, Nature, SAE Technical Papers, VDI Berichte, Harvard Business Review, Advances in Intelligent Systems and Computing, and Sustainability represent the most important sources, and Gibbs, Kraemer, Dedrick, Kim, Chmiela, Sauceda, Müller, Tkatchenko, Pratt, Sarmiento, Montes, Ogilvie, Marcus, Perez, Brownson, D. Mourtzis, M. Doukas, and Bernidaki are the most notorious researchers in the field. At the societal level, technological megatrends are closely related to foresight, globalization, industry 4.0, the internet of things, digitalization, technology, artificial intelligence, innovation, the future, and sustainability. This study is original and useful for researchers in the context of the lack of similar studies on this subject. Full article

This article presents the research results related to the methodology of threat analysis to implement in energy security. In the conducted studies, the world’s output in scenario planning and the most famous cases of global security and technology scenarios were analysed. These projects were the Lisbon Group analysis, Shell’s scenario planning concepts, and the US National Intelligence Council’s long-term analysis. In this way, I demonstrated the limitations of a scenario-based view of the issues under study, resulting mainly from considering only one type of environment. The formulated conclusions made it possible to build the author’s model of the strategic analysis process for the energy security sector. It goes beyond scenario analysis, complementing it with the sector, portfolio, and integrated analysis methods. The strategic analysis built in this way takes into account the achievements of many scientific disciplines, namely, technology, security, strategic management, foresight, international relations, and military. The multidisciplinary knowledge used to build the proposed concept will allow one to consider the increasing complexity of the global environment. Only such a scientific approach nowadays allows practical analysis and planning in the long term. Areas of special attention in strategic analysis, which constitute directions for developing research methodology, are indicated. Full article

Moving from the scientific literature on the evaluation of environmental projects and programs, this study identifies how and under which conditions collaborations in environmentally sustainable projects are considered effective for the adaptive governance of SES. The method adopted is a systematic literature review based on the quantitative and qualitative analysis of 56 articles selected through specific queries on the SCOPUS database and published from 2004 to 2020. Results of the quantitative analysis identify conditions able to evaluate collaborations, highlighting the need to adopt a transdisciplinary approach analysing both social and ecological challenges and assessing both social and ecological results. Moreover, they suggest preferring using primary data involving multi-sector and multi-scale actors and enlarging the geographical context to the most vulnerable countries. The results of the qualitative analysis provide specific recommendations for collaborations being effective when related to communication, equity, foresight, and respect, which need to be further strengthened by all actors. Multiplicity in visions and approaches should be seen as a resource able to stimulate creativity in social arrangements and environmental practices, making collaborations in environmental projects instrumental for the effectiveness of adaptive governance of SES. Full article