Search Results (1,160)

Produce supply chains play a critical role in ensuring fruits and vegetables reach consumers efficiently, affordably, and at optimal freshness. In recent decades, hub-and-spoke network models have emerged as valuable tools for optimizing sustainable cold food supply chains. Traditional optimization efforts typically focus on removing inefficiencies, minimizing lead times, refining inventory management, strengthening supplier relationships, and leveraging technological advancements for better visibility and control. However, the majority of models rely on deterministic approaches that overlook the inherent uncertainties of crop yields, which are further intensified by climate variability. Rising atmospheric CO₂ concentrations, along with shifting temperature patterns and extreme weather events, have a substantial effect on crop productivity and availability. Such uncertainties can prompt distributors to seek alternative sources, increasing costs due to supply chain reconfiguration. This research introduces a stochastic hub-and-spoke network optimization model specifically designed to minimize transportation expenses by determining optimal distribution routes that explicitly account for climate variability effects on crop yields. A use case involving a cold food supply chain (CFSC) was carried out using several weather scenarios based on climate models and real soil data for California. Strawberries were selected as a representative crop, given California’s leading role in strawberry production. Simulation results show that scenarios characterized by increased rainfall during growing seasons result in increased yields, allowing distributors to reduce transportation costs by sourcing from nearby farms. Conversely, scenarios with reduced rainfall and lower yields require sourcing from more distant locations, thereby increasing transportation costs. Nonetheless, supply chain configurations may vary depending on the choice of climate models or weather prediction sources, highlighting the importance of regularly updating scenario inputs to ensure robust planning. This tool aids decision-making by planning climate-resilient supply chains, enhancing preparedness and responsiveness to future climate-related disruptions. Full article

Recent years have seen frequent heavy rainfall events in Japan, often linked to Baiu fronts and typhoons. These events are exacerbated by global warming, leading to an increased frequency and intensity. As floods represent a serious threat to sustainable urban development and community resilience, this study contributes to sustainability-focused risk reduction through integrated analysis. This study focuses on the 2 June 2023 heavy rain disaster in Toyohashi City, Japan, which caused extensive damage due to flooding from the Yagyu and Umeda Rivers. Using numerical models, this study accurately reproduces flooding patterns, revealing that high tides amplified the inundation area by 1.5 times at the Yagyu River. A resident questionnaire conducted in collaboration with Toyohashi City identifies key trends in evacuation behavior and disaster information usage. Traditional media such as TV remain dominant, but younger generations leverage electronic devices for disaster updates. These insights emphasize the need for targeted information dissemination and enhanced disaster preparedness strategies, including online materials and flexible training programs. The methods and findings presented in this study can inform local and regional governments in building adaptive disaster management policies, which contribute to a more sustainable society. Full article

Technological roadmaps are essential tools for managing and planning complex projects, especially in the rapidly evolving field of space exploration. Defined as dynamic schedules, they support strategic and long-term planning while coordinating current and future objectives with particular technology solutions. Currently, the available methodologies are mostly built on experts’ opinions and in just few cases, methodologies and tools have been developed to support the decision makers with a rational approach. In any case, all the available approaches are meant to draw “ideal” maturation plans. Therefore, it is deemed essential to develop an integrate new algorithms able to decision guidelines on “non-nominal” scenarios. In this context, Politecnico di Torino, in collaboration with the European Space Agency (ESA) and Thales Alenia Space–Italia, developed the Technology Roadmapping Strategy (TRIS), a multi-step process designed to create robust and data-driven roadmaps. However, one of the main concerns with its initial implementation was that TRIS did not account for time and budget estimates specific to the space exploration environment, nor was it capable of generating alternative development paths under constrained conditions. This paper discloses two main significant updates to TRIS methodology: (1) improved time and budget estimation to better reflect the specific challenges of space exploration scenarios and (2) the capability of generating alternative roadmaps, i.e., alternative technological maturation paths in resource-constrained scenarios, balancing financial and temporal limitations. The application of the developed routines to available case studies confirms the tool’s ability to provide consistent planning outputs across multiple scenarios without exceeding 20% deviation from expert-based judgements available as reference. The results demonstrate the potential of the enhanced methodology in supporting strategic decision making in early-phase mission planning, ensuring adaptability to changing conditions, optimized use of time and financial resources, as well as guaranteeing an improved flexibility of the tool. By integrating data-driven prioritization, uncertainty modeling, and resource-constrained planning, TRIS equips mission planners with reliable tools to navigate the complexities of space exploration projects. This methodology ensures that roadmaps remain adaptable to changing conditions and optimized for real-world challenges, supporting the sustainable advancement of space exploration initiatives. Full article

We propose a dynamic monitoring and precision fertilization decision system for agricultural soil nutrients, integrating UAV remote sensing and GIS technologies to address the limitations of traditional soil nutrient assessment methods. The proposed method combines multi-source data fusion, including hyperspectral and multispectral UAV imagery with ground sensor data, to achieve high-resolution spatial and spectral analysis of soil nutrients. Real-time data processing algorithms enable rapid updates of soil nutrient status, while a time-series dynamic model captures seasonal variations and crop growth stage influences, improving prediction accuracy (RMSE reductions of 43–70% for nitrogen, phosphorus, and potassium compared to conventional laboratory-based methods and satellite NDVI approaches). The experimental validation compared the proposed system against two conventional approaches: (1) laboratory soil testing with standardized fertilization recommendations and (2) satellite NDVI-based fertilization. Field trials across three distinct agroecological zones demonstrated that the proposed system reduced fertilizer inputs by 18–27% while increasing crop yields by 4–11%, outperforming both conventional methods. Furthermore, an intelligent fertilization decision model generates tailored fertilization plans by analyzing real-time soil conditions, crop demands, and climate factors, with continuous learning enhancing its precision over time. The system also incorporates GIS-based visualization tools, providing intuitive spatial representations of nutrient distributions and interactive functionalities for detailed insights. Our approach significantly advances precision agriculture by automating the entire workflow from data collection to decision-making, reducing resource waste and optimizing crop yields. The integration of UAV remote sensing, dynamic modeling, and machine learning distinguishes this work from conventional static systems, offering a scalable and adaptive framework for sustainable farming practices. Full article

This study provides a detailed dataset from two modern homes constructed inside an environmentally controlled chamber. These data are used to carefully calibrate a dynamic thermal simulation model of these homes. The calibrated models show good agreement with measurements taken under controlled conditions. The two case study homes, “The Future Home” and “eHome2”, were constructed within the University of Salford’s Energy House 2.0, and high-quality data were collected over eight days. The calibration process involved updating U-values, air permeability rates, and modelling refinements, such as roof ventilation, ground temperatures, and sub-floor void exchange rates, set as boundary conditions. Results demonstrated a high level of accuracy, with performance gaps in whole-house heat transfer coefficient reduced to 0.5% for “The Future Home” and 0.6% for “eHome2”, falling within aggregate heat loss test uncertainty ranges by a significant amount. The study highlights the improved accuracy of calibrated dynamic thermal simulation models, compared to results from the steady-state Standard Assessment Procedure model. By providing openly accessible calibrated models and a clearly defined methodology, this research presents valuable resources for future building performance modelling studies. The findings support the UK’s transition to dynamic modelling approaches proposed in the recently introduced Home Energy Model approach, contributing to improved prediction of energy efficiency and aligning with goals for zero carbon ready and sustainable housing development. Full article

Oleogels are a subclass of organogels that present a healthier alternative to traditional saturated and trans solid fats in food products. The unique structure and composition that oleogels possess make them able to provide desirable sensory and textural features to a range of food products, such as baked goods, processed meats, dairy products, and confectionery, while also improving the nutritional profiles of these food products. The fact that oleogels have the potential to bring about healthier food products, thereby contributing to a better diet, makes interest in the subject ever-increasing, especially due to the global issue of obesity and related health issues. Research studies have demonstrated that oleogels can effectively replace conventional fats without compromising flavor or texture. The use of plant-based gelators brings about a reduction in saturated fat content, as well as aligns with consumer demands for clean-label and sustainable food options. Oleogels minimize oil migration in foods due to their high oil-binding capacity, which in turn enhances food product shelf life and stability. Although oleogels are highly advantageous, their adoption in the food industry presents challenges, such as oil stability, sensory acceptance, and the scalability of production processes. Concerns such as mixed consumer perceptions of taste and mouthfeel and oxidative stability during processing and storage evidence the need for further research to optimize oleogel formulations. Addressing these limitations is fundamental for amplifying the use of oleogels and fulfilling their promise as a sustainable and healthier fat alternative in food products. As the oleogel industry continues to evolve, future research directions will focus on enhancing understanding of their properties, improving sensory evaluations, addressing regulatory challenges, and promoting sustainable production practices. The present report summarizes and updates the state-of-the-art about the structure, the properties, and the applications of oleogels in the food industry to highlight their full potential. Full article

The accelerated transformations in the education system marked by volatility, uncertainty, complexity, and ambiguity (VUCA) require a rethinking of pedagogical approaches. The VUCA environment requires a new educational management system in line with new technological trends in order to respond effectively to all the internal and external factors that may affect the quality of teaching. A particularly important course of action is updating teaching methods by combining traditional teaching methods with new interactive methods that promote the introduction of certain digital applications during the teaching of new topics. In this sense, the quantitative research carried out in the present study among second-year students from the psycho-pedagogical program organized by the Bucharest University of Economic Studies, Romania, has highlighted the fact that innovative teaching methods are more effective, contributing to the development of personality and communication skills among pupils and students. Also, the results obtained after applying the Mann–Whitney test showed that there is a significant difference between students involved in different educational activities and those who do not have contact with the educational environment in terms of perceiving the volatility, uncertainty, complexity and ambiguity of the educational environment. At the same time, in the context of the VUCA world, in order to ensure the effectiveness of the teaching–learning process, teachers need to develop new skills such as stress management, adaptability, creativity, technological skills, and time management. Addressing the specific competencies that teachers need to acquire in order to improve their teaching and to respond effectively to the volatility, uncertainty, complexity and ambiguity in education, this study contributes to the creation of a sustainable education system, which is able to cope with all transformations (technological, legislative, socio-economic, etc.). The article is based on the results obtained in the postdoctoral research conducted at the end of 2024. Full article

Pharmaceutical packaging materials play a crucial role in ensuring the safety and efficacy of medications. This mini-review examines the properties of common packaging materials (glass, plastics, metals, and rubber) and their implications for drug safety. By analyzing 127 research articles from PubMed, Web of Science, and CNKI databases (2000–2025), we also discuss recent regulatory updates in China and highlight emerging technologies, including nanomaterials, sustainable packaging solutions, and intelligent packaging systems that present new opportunities for the pharmaceutical industry. Key findings include the following: (1) The physicochemical properties of packaging materials and potential microbial contamination risks during production significantly impact drug quality and safety, underscoring the need for enhanced research and regulatory oversight. (2) Each material exhibits distinct advantages and limitations: glass demonstrates superior chemical stability but may leach ions; plastics offer versatility but risk plasticizer migration; metals provide exceptional strength yet have limited applications; rubber ensures effective sealing but may release additives compromising drug quality. (3) The pharmaceutical packaging sector is evolving toward intelligent systems and sustainable solutions to address contemporary healthcare challenges. This review can aid pharmaceutical companies in selecting drug packaging and guide manufacturers in developing innovative packaging solutions. Full article

Accurate and transparent Life Cycle Assessment (LCA) datasets are essential for reliable sustainability evaluations, particularly in the complex and varied textile industry. Historically, the ecoinvent database has been a foundational source for LCA studies in the textile sector. This paper critically examines the limitations of the ecoinvent v3.7 dataset, which is widely used in academic research, industry tools, and policymaking. While newer versions, such as v3.11, released in 2024, have addressed many issues, including enhanced geographical representation and updated emission profiles for chemicals, this study emphasises the historical implications of earlier data versions. By comparing the cradle-to-gate Global Warming Potential (GWP) of wool and polyester jumpers, this research reveals how aggregated and outdated data underestimated the polyester’s environmental impact while overestimating that of wool. These discrepancies have shaped fibre certification, eco-labelling, and consumer perceptions for years. Understanding the legacy of these datasets is vital for re-evaluating past LCA-based decisions and guiding future assessments toward greater regional relevance and transparency. Full article

The efficient management of urban parking systems has emerged as a pivotal issue in today’s smart cities, where increasing vehicle populations strain limited parking infrastructure and challenge sustainable urban mobility. Aligned with the United Nations 2030 Agenda for Sustainable Development and the strategic goals of smart city planning, this study presents a sustainability-driven, multiagent simulation-based framework to model, analyze, and optimize smart parking dynamics in congested urban settings. The system architecture integrates ground-level IoT sensors installed in parking spaces, enabling real-time occupancy detection and communication with a centralized system using low-power wide-area communication protocols (LPWAN). This study introduces an intelligent parking guidance mechanism that dynamically directs drivers to the nearest available slots based on location, historical traffic flow, and predicted availability. To manage real-time data flow, the framework incorporates message queuing telemetry transport (MQTT) protocols and edge processing units for low-latency updates. A predictive algorithm, combining spatial data, usage patterns, and time-series forecasting, supports decision-making for future slot allocation and dynamic pricing policies. Field simulations, calibrated with sensor data in a representative high-density urban district, assess system performance under peak and off-peak conditions. A comparative evaluation against traditional first-come-first-served and static parking systems highlights significant gains: average parking search time is reduced by 42%, vehicular congestion near parking zones declines by 35%, and emissions from circling vehicles drop by 27%. The system also improves user satisfaction by enabling mobile app-based reservation and payment options. These findings contribute to broader sustainability goals by supporting efficient land use, reducing environmental impacts, and enhancing urban livability—key dimensions emphasized in sustainable smart city strategies. The proposed framework offers a scalable, interdisciplinary solution for urban planners and policymakers striving to design inclusive, resilient, and environmentally responsible urban mobility systems. Full article

Addressing resource depletion and minimizing construction waste requires closing the material loop through circular economy practices. However, the lack of comprehensive material information remains a significant barrier. The materials passport (MP) has become an essential tool for documenting material properties and dynamically updating information throughout its lifecycle. Despite recent advancements, existing MP frameworks remain static and lack a holistic approach, limiting their effectiveness in assessing material quality and supporting high-value recovery and reuse. As a result, the industry remains reluctant to adopt secondary materials due to concerns about their performance and quality in structural applications where assurance of reliability is essential. Therefore, this study aims to address this gap by (1) defining the conceptual boundary of the MP framework by examining current MP practices, key functions, and existing limitations and (2) developing a standardized framework using concrete as demonstration material. An extensive literature review was conducted to define the conceptual boundary. Literature and relevant standards were reviewed to identify essential attributes. The study identified three core MP functions, including material tracking and management, circularity assessment, and sustainability assessment, while proposing an additional function of quality assessment. These four functions collectively informed the development of a unique standardized and holistic MP framework. Thus, this study contributes by enabling practitioners to make quality-based, data-driven decisions that support the effective secondary use of materials. Full article

The increasing number of natural and man-made disasters registered at the global level is causing a significant amount of damage. This represents one of the main sustainability challenges at the global level. The collapse of the Twin Towers, Hurricane Katrina, and the nuclear accident at the Fukushima power plant are some of the most representative disaster events that occurred at the beginning of the third millennium. These relevant disasters need an enhanced level of preparedness to reduce the gaps between the plan and its implementation. Among these actions, training and exercises play a relevant role because they increase the capability of planners, managers, and the people involved. By focusing on the exposure risk component, the general objective of the research is to obtain quantitative evaluations of the exercise’s contribution to risk reduction through evacuation. The paper aims to analyze serious games using a set of methods and models that simulate an urban risk reduction plan. In particular, the paper proposes a transparent framework that merges transport risk analysis (TRA) and transport system models (TSMs), developing serious game activities with the support of emerging information and communication technologies (e-ICT). Transparency is possible through the explicitation of reproducible analytical formulations and linked parameters. The core framework of serious games is constituted by a set of models that reproduce the effects of players’ choices, including planned actions of decisionmakers and travel users’ choices. The framework constitutes the prototype of a digital platform in a “non-stressful” context aimed at providing more insights about the effects of planned actions. The proposed framework is characterized by transparency, a feature that allows other analysts and planners to reproduce each risk scenario, by applying TRA and relative effects simulations in territorial contexts by means of TSMs and parameters updated by e-ICT. A basic experimentation is performed by using a game, presenting the main results of a prototype test based on a reproducible exercise. The prototype experiment demonstrates the efficacy of increasing preparedness levels and reducing exposure by designing and implementing a serious game. The paper’s methodology and results are useful for policymakers, emergency managers, and the community for increasing the preparedness level. Full article

In the context of accelerating digitalization, this study investigates how electronic commerce performance is influenced by Web 2.0 instruments in the 27 EU member states. Analyzing literature reviews and performing our own bibliometric review, we identified a gap related to the measurable economic results of e-commerce. The scope of this study was to analyze the relationship between Web 2.0 tools and the level of turnover generated by e-commerce, applying robust econometric models based on panel data regression with random effects and fixed effects (Arellano–Bond). The results highlight that the online paid advertisement and social media usage variables have significant, positive effects on e-commerce performance, confirming the first and second hypotheses. “Use the enterprise’s blog or microblogs” and “use of multimedia content sharing websites” do not influence enterprises’ total turnover from e-commerce sales to a valid and statistically significant extent. Thus, the third and fourth hypotheses are not confirmed by the results of the research conducted, possibly due to limited innovation and platform ownership in Europe. This study makes a notable empirical and methodological contribution, embedding digital sustainability in the analysis, which implies that the findings can be used for updating e-commerce policies. Full article

Technological advancement has radically transformed higher education, requiring faculty members to continually adapt to new tools and teaching methods. In this context, the phenomenon of fear of missing out (FoMO) has gained relevance, often manifesting through a range of negative emotional states, including technostress—stress associated with the use of technology. Objectives: This study aimed to map the available scientific evidence on technostress among nursing faculty in higher education, through a scoping review conducted according to the methodology proposed by the Joanna Briggs Institute (JBI). Methods: The literature search was performed across eight databases, including Medline (via PubMed), CINAHL Complete, Scopus, and the Teacher Reference Center. Results: Of the 266 studies identified, only 3 met the inclusion criteria. Conclusions: Findings reveal varying levels of technostress among nursing educators, with higher levels observed among older faculty members, frequently associated with limited technical and administrative support. Although the direct impact on job satisfaction was not significant, the anxiety induced by intensive technology use and the perceived necessity for constant professional updating—often driven by FoMO—was shown to affect daily academic life, highlighting the need for effective coping strategies. Understanding technostress within the context of nursing education is essential for addressing the challenges of pedagogical modernization. This review supports the need for future institutional interventions aimed at preventing technostress and fostering a more balanced, reflective, and sustainable relationship with technology in academic settings. Full article

Projected changes in outdoor environmental conditions are expected to significantly alter building energy demand across the United States. Yet, policymakers and designers lack typology and climate-zone-specific guidance to support long-term planning. We simulated 10 U.S. Department of Energy (DOE) prototype buildings across all 16 ASHRAE climate zones with EnergyPlus. Future weather files generated in Meteonorm from a CMIP6 ensemble reflected two emissions pathways (RCP 4.5 and RCP 8.5) and two planning horizons (2050 and 2080), producing 800 simulations. Envelope parameters and schedules were held at DOE reference values to isolate the pure climate signal. Results show that cooling energy use intensity (EUI) in very hot-humid Zones 1A–2A climbs by 12% for full-service restaurants and 21% for medium offices by 2080 under RCP 8.5, while heating EUI in sub-arctic Zone 8 falls by 14–20%. Hospitals and large hotels change by < 6%, showing resilience linked to high internal gains. A simple linear-regression meta-model (R² > 0.90) links baseline EUI to future percentage change, enabling rapid screening of vulnerable stock without further simulation. These high-resolution maps supply actionable targets for state code updates, retrofit prioritization, and long-term decarbonization planning to support climate adaptation and sustainable development. Full article