Search Results (65)

The rapid demographic transition in middle-income countries creates unprecedented challenges for age-friendly urban development, as cities experience compressed aging within severe resource constraints—a phenomenon termed “getting old before getting rich.” This study develops a preliminary Resource-Constrained Age-Friendly City (RC-AFC) framework through empirical analysis of Bangkok’s urban aging challenges, addressing the need for context-specific approaches in resource-constrained environments. Using convergent parallel mixed-methods design, the research analyzed data from 1000 older adults and 195 multi-sectoral stakeholders to examine age-friendly service gaps and collaboration potential within Bangkok’s rapidly aging context. Importance-Performance Analysis revealed significant service disparities (average gap: 1.34) with Communication and Information (2.03), Housing (1.93), and Outdoor Spaces (1.78) identified as priority areas in Bangkok’s setting. The study proposes three initial RC-AFC principles based on Bangkok findings: Priority Hierarchy Adaptation suggesting systematic resource allocation approaches; Multi-Sectoral Resource Optimization indicating collaboration as structural necessity; and Leapfrog Innovation Potential demonstrating potential for constraint-driven solutions. This proof-of-concept study provides initial conceptual foundation specifically developed from Bangkok’s context, though systematic validation across different urban environments remains essential before any broader consideration. The research offers a Bangkok-derived starting point for understanding resource-constrained age-friendly development that requires substantial further testing and adaptation for application in other contexts. Full article

The agri-food sector is undergoing profound transformations driven by ecological and digital transitions, as well as evolving consumer and nutritional choices. These shifts pose significant challenges but also open new opportunities for businesses to enhance sustainability and competitiveness through circular economy principles. In response, Spoke 9 of the National Agritech Center (PNRR) has launched a survey to analyze agri-food companies and sustainability practices and promote circular strategies. A large-scale survey conducted in early 2024 gathered data from 3002 agri-food companies, covering 20 Italian regions and six major supply chains (wine, olive oil, dairy, milk, fruit and vegetables, and beekeeping). The study is the first attempt in Italy to get metrics on these topics from agri-food companies, and it provides a comprehensive assessment of circular economy practices in the sector. The key objectives of the work are as follows: (1) developing integrated sustainability indicators; (2) sector-specific circular metrics; (3) identifying best practices and gaps; (4) supporting policy and decision-making; and (5) benchmarking and monitoring. Full article

Sensor-based surveillance technology (SST) is increasingly employed in the care of people with dementia (PwD) in hospitals, nursing homes, and home care. With improved functionality and availability of SST, there will likely be a growing utilization in clinical settings. In the context of staff shortage, the expected resource-efficient safety benefits are attractive but must be critically balanced against concerns that basic ethical principles are violated. In this discussion paper, we provide a brief overview of frequently used SST and discuss ethical issues associated with their use. We identify intrusion into privacy and the complex interaction between stakeholders as the biggest challenges. Moreover, the frequent lack of decision-making capacity in PwD poses particular ethical challenges. Evidence concerning safety benefits exists mostly for the detection of patients leaving the intended area (i.e., getting up, leaving the premises) or occurring falls. The level of privacy intrusion to detect occurring falls varies widely between different sensor systems. Finally, we propose best practice recommendations for the clinical implementation of SST in the care of PwD, and we address the circumstances under which the use of sensors can be ethically justified despite the absence of legally valid informed consent. Full article

To address the problem of UAV path planning in complex mountainous terrains, this paper comprehensively considers constraints such as natural mountain and obstacle collision threats, the shortest path, and flight altitude. We propose a more practical UAV path planning model that better reflects the actual UAV path planning situation in complex mountainous areas. In order to solve this model, this paper improves the traditional dung beetle optimization (DBO) algorithm and proposes an improved dung beetle optimization (IDBO) algorithm. The IDBO algorithm optimizes the population initialization method based on the concept of symmetry, ensuring that the population is more evenly distributed within the solution space. Additionally, the algorithm introduces a sine–cosine function-based movement strategy, inspired by the symmetry principle, to enhance the search efficiency of individual population members. Furthermore, a population evolution strategy is incorporated to prevent the algorithm from getting stuck in local optima. To demonstrate the algorithm’s performance, tests were conducted using 23 commonly used benchmark functions provided by the CEC 2005 competition and six commonly used engineering problem models provided by the CEC 2020 competition. The results indicate that IDBO significantly outperforms DBO in terms of convergence performance, effectively solving various engineering optimization problems. Finally, experimental tests under three different threat scenarios show that the proposed IDBO algorithm has scientific validity when applied to UAV path planning. This solution method effectively reduces UAV flight energy consumption costs and obstacle collision threats while improving the efficiency and accuracy of UAV path planning. Full article

The anticipated diagnosis of cancers and other fatal diseases from the simple analysis of the volatiles emitted by the body (volatolome) is getting closer and closer from becoming reality. The promises of vapour sensor arrays are to provide a rapid, reliable, non-invasive and ready-to-use method for clinical applications by making an olfactive fingerprint characteristic of people’s health state, to increase their chance of early recovery. However, the different steps of this complex and ambitious process are still paved with difficulties needing innovative answers. The purpose of this review is to provide a statement of the blocs composing the diagnostic chain to identify the improvements still needed. Nanocomposite chemo-resistive transducers have unique prospects to enhance both the selectivity and sensitivity to volatile biomarkers. The variety of their formulations offers multiple possibilities to chemical functionalization and conductive architectures that should provide solutions to discriminations and stability issues. A focus will be made on the protocols for the collection of organic volatile compounds (VOC) from the body, the choice of vapour sensors assembled into an array (e-nose), in particular, chemo-resistive vapour sensors, their principle, fabrication and characteristics, and the way to extract pertinent features and analyse them with suitable algorithms that are able to find and produce a health diagnosis. Full article

A multi-strategy improved honey badger algorithm (MIHBA) is proposed to address the problem that the honey badger algorithm may fall into local optimum and premature convergence when dealing with complex optimization problems. By introducing Halton sequences to initialize the population, the diversity of the population is enhanced, and premature convergence is effectively avoided. The dynamic density factor of water waves is added to improve the search efficiency of the algorithm in the solution space. Lens opposition learning based on the principle of lens imaging is also introduced to enhance the ability of the algorithm to get rid of local optimums. MIHBA achieves the best ranking in 23 test functions and 4 engineering design problems. The improvement of this paper improves the convergence speed and accuracy of the algorithm, enhances the adaptability and solving ability of the algorithm to complex functions, and provides new ideas for solving complex engineering design problems. Full article

Quantum game theory merges principles from quantum mechanics with game theory, exploring how quantum phenomena such as superposition and entanglement can influence strategic decision making. It offers a novel approach to analyzing and optimizing complex systems where traditional game theory may fall short. Congestion of passengers, if considered as a network, may fall into the categories of optimization cases of quantum games. This paper explores the application of quantum potential games to minimize congestion in common areas at airports. The players/passengers of the airport have identical interests and they share the same utility function. A metric is introduced that considers a passenger’s visit to a common area by setting their preferences, in order to avoid congestion. Passengers can decide whether to visit a specific common area or choose an alternative. This study demonstrates that the proposed game is a quantum potential game for tackling congestion, with identical interests, ensuring the existence of a Nash equilibrium. We consider passengers to be players that want to ensure their interests. Quantum entanglement is utilized to validate the concept, and the results highlight the effectiveness of this approach. The objective is to ensure that not all passengers select the same common place of the airport to reduce getting crowded; hence, the airborne disease infection probability increases due to overcrowding. Our findings provide a promising framework for optimizing passenger flow and reducing congestion in airport common areas through quantum game theory. We showed that the proposed system is stable by encapsulating the Lyapunov stability. We compared it to a simulated annealing approach to show the efficacy of the quantum game approach. We acknowledge that this framework can be utilized in other disciplines as well. For our future work, we will research different strategies than binary ones to investigate the efficacy of the approach. Full article

Greek wines excel in quality and exports, but the viticultural sector faces significant challenges from complex supply chains, shifting European policies, and the growing need for sustainability amidst climate change and economic pressures. External environmental costs could affect significantly the decision-making process of farmers, reflecting a broader evaluation of sustainability in viticulture. This study evaluates the economic and environmental impacts of organic, integrated, and conventional viticulture management systems in Drama, Greece using a life cycle (LC) approach and data envelopment analysis (DEA) to determine efficiency, quantify environmental impacts in monetary terms, and incorporate these costs into the analysis. Organic management systems have lower energy consumption and emissions compared to integrated and conventional systems, with organic systems ranging from 4546 to 6573 kWh/ha in energy use and 1358 to 1795 kg CO₂ eq./ha in emissions, while integrated and conventional systems range from 9157 to 12,109 kWh/ha and 2961 to 3661 kg CO₂ eq./ha. The DEA analysis reveals that most organic systems perform efficiently when accounting for environmental costs, whereas conventional systems face significant efficiency declines, with only a few maintaining optimal performance. Policy-supported transitions based on the provider gets principle are crucial for balancing economic and environmental goals in viticulture, as the integration of shadow prices significantly impacts efficiency. Full article

The calibration of cameras plays a critical role in close-range photogrammetry because the precision of calibration has a direct effect on the quality of results. When handling image capture using a camera, traditional swarm intelligence algorithms such as genetic algorithms and particle swarm optimization, in conjunction with Zhang’s calibration method, frequently face difficulties regarding local optima and sluggish convergence. This study presents an enhanced hybrid optimization approach utilizing both the principles of differential evolution and particle swarm optimization, which is then employed in the context of camera calibration. Initially, we establish a measurement model specific to the camera in close-range photogrammetry and determine its interior orientation parameters. Subsequently, employing these parameters as initial values, we perform global optimization and iteration using the improved hybrid optimization algorithm. The effectiveness of the proposed approach is subsequently validated through simulation and comparative experiments. Compared to alternative approaches, the proposed algorithm enhances both the accuracy of camera calibration and the convergence speed. It effectively addresses the issue of other algorithms getting trapped in local optima due to image distortion. These research findings provide theoretical support for practical engineering applications in the field of control theory and optimization to a certain extent. Full article

Three-dimensional (3D) printing in the pharmaceutical field allows rapid manufacturing of a diverse range of pharmaceutical dosage forms, including personalized items. The application of this technology in dosage form manufacturing requires the judicious selection of excipients because the selected materials must be appropriate to the working principle of each technique. Most techniques rely on the use of polymers as the main material. Among the pharmaceutically approved polymers, polyvinyl alcohol (PVA) is one of the most used, especially for fused deposition modeling (FDM) technology. This review summarizes the physical and chemical properties of pharmaceutical-grade PVA and its applications in the manufacturing of dosage forms, with a particular focus on those fabricated through FDM. The work provides evidence on the diversity of dosage forms created using this polymer, highlighting how formulation and processing difficulties may be overcome to get the dosage forms with a suitable design and release profile. Full article

Ground-based synthetic aperture radar (GBSAR) is widely used in mountains, mines, and other areas because it can get the sub-millimeter deformation information of monitoring scenes. This technology plays a vital role in safeguarding production operations, providing accurate disaster projections, and facilitating timely early warning dissemination. However, the moving target’s defocus/displaced signal will mask the image of GBSAR, which affects the accuracy of deformation inversion. Hence, the detection of moving targets in GBSAR imagery is essential. An algorithm for moving target detection based on refocusing is proposed in this paper to address this problem. The algorithm establishes a two-dimensional parameter search space for squint angle and relative speed. Based on the parameter searching, the improved Range Doppler (RD) algorithm is used for refocusing. The optimal 2D parameters are searched via an algorithm combining the entropy minimization principle and the enlightend search. The presence of a moving target in the observation area is determined based on whether there is an optimal parameter to minimize the entropy value of the refocused image. This approach enables the detection of moving targets in GBSAR imagery. The proposed method is verified by the synthetic data. Full article

As a power converter of battery energy storage, the multi-level converter and its battery balancing control have received much attention from scholars. This paper focuses on the modular multi-level half-bridge energy storage converter (MMH-ESC), including its topology, working principle, and pulse width modulation (PWM) methods. Under the battery balancing control strategy based on level-shifted carrier PWM (LS-PWM), formulas are derived and calculations are performed to get the charge or discharge of each submodule (SM), thereby obtaining the tolerance for capacity differences among these batteries. A range of battery capacity values that can maintain a balanced state is provided to enhance flexibility in battery configuration and utilization, avoiding the limitation of all batteries to the same capacity. Finally, a new bridge arm modulation wave allocation method is proposed. This method significantly expands the range of SM battery capacity selection and provides a high-tolerance modulation method for the converter under extreme or even fault conditions. Full article

Microbial communities can undergo significant successional changes during decay and decomposition, potentially providing valuable insights for determining the postmortem interval (PMI). The microbiota produce various gases that cause cadaver bloating, and rupture releases nutrient-rich bodily fluids into the environment, altering the soil microbiota around the carcasses. In this study, we aimed to investigate the underlying principles governing the succession of microbial communities during the decomposition of pig carcasses and the soil beneath the carcasses. At early decay, the phylum Firmicutes and Bacteroidota were the most abundant in both the winter and summer pig rectum. However, Proteobacteria became the most abundant in the winter pig rectum in late decay. Using genus as a biomarker to estimate the PMI could get the MAE from 1.375 days to 2.478 days based on the RF model. The abundance of bacterial communities showed a decreasing trend with prolonged decomposition time. There were statistically significant differences in microbial diversity in the two periods (pre-rupture and post-rupture) of the four groups (WPG 0–8Dvs. WPG 16–40D, p < 0.0001; WPS 0–16Dvs. WPS 24–40D, p = 0.003; SPG 0D vs. SPG 8–40D, p = 0.0005; and SPS 0D vs. SPS 8–40D, p = 0.0208). Most of the biomarkers in the pre-rupture period belong to obligate anaerobes. In contrast, the biomarkers in the post-rupture period belong to aerobic bacteria. Furthermore, the genus Vagococcus shows a similar increase trend, whether in winter or summer. Together, these results suggest that microbial succession was predictable and can be developed into a forensic tool for estimating the PMI. Full article

The field of human–computer interaction is constantly evolving and facing new challenges. In this study, we propose an experimental method for designing e-commerce user interfaces with varying levels of aesthetics and usability while maintaining a similar level of user experience. The method is based on the Deming Cycle and Nielsen’s framework for design principles. Four e-commerce websites were designed with low/high levels of aesthetics and usability. Based on 160 surveys, the experimental results demonstrated that it is possible to design user interfaces with varying levels of aesthetics and usability while maintaining a similar level of user design perception. Our findings suggest that usability is more crucial than aesthetics in enhancing user experience, which aligns with previous studies. We also emphasize considering aesthetics and usability in UI design and propose the principle “What You Design Is What You Get” (WYDISWYG) as a foundation for future research. Among the evaluated websites, Website1 (the best design) achieved the highest UI quality, with users perceiving it positively at an impressive rate of almost 0.91 percent. In contrast, Website4 (the worst design) had the lowest UI quality, receiving a perception score of only 0.38 percent. The websites designed with a combination of aesthetics and usability, Website2 and Website3, garnered different perception values of 0.79 and 0.51, respectively. While this study has some limitations, such as the subjective selection of features and the focus on e-commerce websites only, it provides a starting point for further investigation into the selection of design principles, consideration of other website domains, and clarification of users’ perception of UI elements to align with Nielsen’s principles. Full article

Optimizing nitrogen (N) availability to plants is crucial for achieving maximum crop yield and quality. However, ensuring the appropriate supply of N to crops is challenging due to the various pathways through which N can be lost, such as ammonia (NH₃) volatilization, nitrous oxide emissions, denitrification, nitrate (NO₃⁻) leaching, and runoff. Additionally, N can become immobilized by soil minerals when ammonium (NH₄⁺) gets trapped in the interlayers of clay minerals. Although synchronizing N availability with plant uptake could potentially reduce N loss, this approach is hindered by the fact that N loss from crop fields is typically influenced by a combination of management practices (which can be controlled) and weather dynamics, particularly precipitation, temperature fluctuations, and wind (which are beyond our control). In recent years, the use of urease and nitrification inhibitors has emerged as a strategy to temporarily delay the microbiological transformations of N-based fertilizers, thereby synchronizing N availability with plant uptake and mitigating N loss. Urease inhibitors slow down the hydrolysis of urea to NH₄⁺ and reduce nitrogen loss through NH₃ volatilization. Nitrification inhibitors temporarily inhibit soil bacteria (Nitrosomonas spp.) that convert NH₄⁺ to nitrite (NO₂⁻), thereby slowing down the first and rate-determining step of the nitrification process and reducing nitrogen loss as NO₃⁻ or through denitrification. This review aims to provide a comprehensive understanding of urease and nitrification inhibitor technologies and their profound implications for plants and root nitrogen uptake. It underscores the critical need to develop design principles for inhibitors with enhanced efficiency, highlighting their potential to revolutionize agricultural practices. Furthermore, this review offers valuable insights into future directions for inhibitor usage and emphasizes the essential traits that superior inhibitors should possess, thereby paving the way for innovative advancements in optimizing nitrogen management and ensuring sustainable crop production. Full article