Search Results (367)

This review investigates the latest advancements in Multi-Robot Systems (MRSs) and soft robotics, with a particular focus on their integration and emerging opportunities. An MRS extends principles from distributed artificial intelligence and coordination frameworks, enabling efficient collaboration in robotic applications such as object manipulation, navigation, and transportation. Soft robotics employs flexible materials and biomimetic designs to improve adaptability in unstructured environments, with applications in manufacturing, sensing, actuation, and modeling. Unlike previous reviews, which often address these fields independently, this work emphasizes their integration, identifying key challenges such as nonlinear dynamics, hyper-redundant configurations, and adaptive control. This review discusses recent advancements in locomotion, coordination, and simulation, offering insights into the development of adaptive and collaborative robotic systems across diverse applications. Full article

(1) Background: Microcracks and structural fragility in teeth, often undetected by traditional methods until severe complications like fractures or pulp exposure occur, are evaluated in this study using electrical impedance analysis (EIA) as a non-invasive tool for early detection and assessment. (2) Methods: A total of 57 patients were recruited, including individuals with bruxism (n = 20), dental restorations (n = 18), and no significant dental history (control group, n = 19). Electrical impedance measurements were performed on all teeth using a portable device, with data collected from occlusal and proximal surfaces. Patients with abnormal values underwent additional imaging (standard radiographs) to confirm the presence of microcracks. Statistical analyses included ANOVA to compare impedance values between groups and logistic regression to assess the predictors of structural fragility. (3) Results: Teeth with microcracks confirmed by standard radiographs exhibited significantly lower impedance values (mean 50 kΩ) compared to healthy teeth (mean 120 kΩ, p < 0.01). Patients with bruxism showed the highest proportion of teeth with abnormal impedance (45%). Logistic regression identified bruxism as a significant predictor of reduced impedance values (p < 0.05). (4) Conclusions: Electrical impedance analysis demonstrates promise as a non-invasive method for detecting microcracks and assessing structural fragility in teeth. Its application in routine dental check-ups could enable early interventions, particularly for high-risk patients with bruxism or restorations. Full article

This paper explores the intersection of tourism and environmental theories, highlighting how sustainability serves as a critical bridge between the two disciplines. Tourism theories such as Butler’s Tourism Area Life Cycle (TALC) and the Theory of Planned Behavior (TPB) provide insights into destination development and tourist behavior but often lack an ecological perspective. The environmental framework, including Ecological Modernization Theory (EMT) and Common-Pool Resource (CPR) Theory, emphasizes sustainable resource management and the interconnectedness of human activities and natural systems. This paper examines common concepts such as carrying capacity, sustainable development, and behavioral insights while also identifying tensions between economic growth and environmental preservation. Case studies from Costa Rica, Hawaii, and Thailand illustrate practical applications of these theories in real-world settings, revealing how tourism can be both a threat and a tool for conservation. My paper concludes that integrating environmental impact assessment (EIA) and community-based tourism (CBT) models into tourism planning can lead to better long-term resource management. It recommends the adoption of stricter regulations on tourism development in fragile ecosystems, the implementation of eco-certifications, and the promotion of locally governed tourism initiatives. These strategies will ensure the sustainability of both tourism activities and the ecosystems on which they depend. Full article

Background/Objectives: Accurate surveillance of recent HIV infections is crucial for effective epidemic control and timely intervention. The Limited Antigen Avidity Enzyme Immunoassay (LAg-EIA) allows precise differentiation between recent and long-term HIV infections. To enhance accessibility, it has been developted into a point-of-care test, the Asanté™ HIV-1 Rapid Recency^® Assay (ARRA), a rapid immunoassay. This study evaluated the performance and false recent rates (FRRs) of the ARRA, interpreted both visually and via a strip reader, in comparison with the LAg-EIA. Methods: Plasma samples were collected from two groups: 634 long-term HIV-infected individuals, identified through routine diagnostic testing, who had not received antiretroviral therapy for over one year, and 224 individuals from high-risk populations. High-risk individuals, including pregnant women, female sex workers, and men who have sex with men, were selected based on behavioral and demographic risk factors. Concordance between the ARRA and LAg-EIA was assessed, and FRRs were calculated for both assays. McNemar’s test was used to evaluate agreement, while Spearman’s rho was applied to assess correlation between the two methods. Results: Visual interpretation of ARRA demonstrated perfect agreement with LAg-Avidity EIA results (FRR = 0.00%), while the strip reader misclassified two specimens as recent infections (FRR = 0.32%). McNemar’s test indicated no significant differences between the methods (p > 0.05). Moderate agreement (Spearman’s rho = 0.434) was observed between ARRA strip reader results and LAg-Avidity EIA optical density values. Among high-risk populations, ARRA misclassified one sample as recent, resulting in an inconsistency rate of 0.45%. Conclusions: This study highlights ARRA’s reliability in identifying long-term infections and its potential as a point-of-care tool. Its rapid results and ease of use make it a valuable asset for effective HIV surveillance, facilitating targeted epidemic monitoring and enhancing public health interventions. Full article

The present study examines the negative ionospheric response over Europe during two geomagnetic storms on 10–13 May 2024, known as the Mother’s Day geomagnetic superstorm. The first storm, with a peak SYM-H value of −436 nT, occurred in the interval 10–11 May, while the second, less intense storm (SYM-H~−103 nT), followed in the interval 12–13 May. Using data from four European locations, temporal and spatial variations in ionospheric parameters (TEC, foF2, and hmF2) were analyzed to investigate the morphology of the strong negative response. Sharp electron density (Ne) depletion is associated with the equatorward displacement of the Midlatitude Ionospheric Trough (MIT), confirmed by Swarm satellite data. A key finding was the absence of foF2 and hmF2 values over all ionosonde stations during the recovery phase of the storms, likely due to the coupling between the Equatorial Ionization Anomaly (EIA) crests and the auroral ionosphere influenced by the intense uplift of the F layer. Relevant distinct features such as Large-scale Travelling Ionospheric Disturbance (LSTID) signatures and Spread F were also noted, particularly during the initial and main phase of the first storm over high midlatitude regions. Regional effects varied, with high European midlatitudes exhibiting different features compared to lower European latitude areas. Full article

Hepatitis C virus (HCV), a member of the Flaviviridae family, is an RNA virus enclosed in an envelope that infects approximately 50 million people worldwide. Despite its significant burden on public health, no vaccine is currently available, and many individuals remain unaware of their infection due to the often asymptomatic nature of the disease. Early detection of HCV is critical for initiating curative treatments, which can prevent long-term complications such as cirrhosis, liver cancer, and decompensated liver disease. However, conventional diagnostic approaches available, such as enzyme immunoassays (EIAs) and polymerase chain reaction (PCR)-based methods, are often costly, time-intensive, and challenging to be implemented in resource-limited settings. This review provides an overview of HCV disease and the structural components of the virus, illustrating how different diagnostic methods target various parts of the viral structure. It examines current diagnostic tests and assays, highlighting their mechanisms, applications, and limitations, which necessitates the development of improved detection methods. Additionally, the paper explores emerging technologies in HCV detection that could offer affordable, accessible, and easy-to-use diagnostic solutions, particularly for deployment in low-resource and point-of-care settings. These advancements have the potential to contribute significantly to achieving the World Health Organization’s (WHO) target of eliminating HCV as a public threat by 2030. Full article

The application of fuzzy logic to environmental impact assessment (EIA) provides a robust method to address uncertainties and subjectivities inherent in evaluating complex environmental systems. This is particularly relevant in ocean renewable energy projects, where predicting environmental impacts is challenging due to the dynamic nature of marine environments. We conducted a comprehensive literature review to identify the types of impacts currently being investigated, assessed, and monitored in existing marine energy conversion projects. Based on these foundations, we developed both traditional and fuzzy mythologies for EIA. The fuzzy logic methodology approach allows for the incorporation of uncertainties into the assessment process, converting qualitative assessments into quantifiable data and linguistic levels and enhancing decision-making accuracy. We tested this fuzzy methodology across four types of ocean energy devices: floating, submerged, fixed to the ocean floor, and onshore. Finally, we applied the methodology to the EIA of a marine energy project in the Cozumel Channel, Quintana Roo, Mexico. The results demonstrate that fuzzy logic provides a more flexible and reliable evaluation of environmental impacts, contributing to more effective environmental management and sustainable development in marine renewable energy contexts. Full article

This study aims to investigate the impact of ionospheric models on Global Navigation Satellite System (GNSS) positioning and proposes an ionospheric prediction method based on a Transformer deep learning model. We construct a Transformer-based deep learning model that utilizes global ionospheric maps as input to achieve spatiotemporal prediction of Total Electron Content (TEC). To gain a deeper understanding of the model’s prediction mechanism, we employ integrated gradients for explainability analysis. The results reveal the key ionospheric features that the model focuses on during prediction, providing guidance for further model optimization. This study demonstrates the efficacy of a Transformer-based model in predicting Vertical Total Electron Content (VTEC), achieving comparable accuracy to traditional methods while offering enhanced adaptability to spatial and temporal variations in ionospheric behavior. Furthermore, the application of advanced explainability techniques, particularly the Integrated Decision Gradient (IDG) method, provides unprecedented insights into the model’s decision-making process, revealing complex feature interactions and spatial dependencies in VTEC prediction, thus bridging the gap between deep learning capabilities and explainable scientific modeling in geophysical applications. The model achieved positioning accuracies of −1.775 m, −2.5720 m, and 2.6240 m in the East, North, and Up directions respectively, with standard deviations of 0.3399 m, 0.2971 m, and 1.3876 m. For VTEC prediction, the model successfully captured the diurnal variations of the Equatorial Ionization Anomaly (EIA), with differences between predicted and CORG VTEC values typically ranging from −6 to 6 TECU across the study region. The gradient score analysis revealed that solar activity indicators (F10.7 and sunspot number) showed the strongest correlations (0.7–0.8) with VTEC variations, while geomagnetic indices exhibited more localized impacts. The IDG method effectively identified feature importance variations across different spatial locations, demonstrating the model’s ability to adapt to regional ionospheric characteristics. Full article

Due to significant political and environmental decisions regarding clean energy, rapid adoption of solar photovoltaic (PV), wind power, and hydropower is taking place. In China, policy environmental impact assessment (EIA) plays an important role in pollution prevention, while its practice is relatively limited due to insufficient methodologies and weak legislative enforcement. Taking the clean energy action plan (CEAP) in the Qinghai region as a case study, this study explored the application of life cycle assessment (LCA) to evaluate the potential environmental impacts imposed by the installment capability of 70,000 MW solar PV in pristine areas. It was found that the CO₂ emissions of solar PV are less than 3% of that of clean coal-fired power, while the emissions of pollutants such as sulfur dioxide, nitrogen oxides, and particulate matter only account for about 18~27% of coal-fired power. Meanwhile, from the full life cycle perspective, 4.61 million tons of solar PV panel waste will be generated, and 4172 square kilometers of land surface area will be occupied. Herein, implications for policy are proposed, including (1) advance planning of local waste disposal capacity and processing facilities, (2) the integration of clean energy planning with legal ecological environment protection schemes, and (3) rational planning of upstream and downstream solar PV industries. Full article

The Asia-Pacific region has gradually become a driver of global economic growth, with economic integration agreements (EIAs) and climate distance playing increasingly important roles in the agri-food trade in the 21st century. The recent signing and implementation of the Regional Comprehensive Economic Partnership (RCEP) and the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) have garnered global attention. This study examines the roles of different types of regional trade agreements and climate distance in the agri-food trade in the Asia-Pacific region and constructs a trade system involving 19 member countries of the RCEP and the CPTPP by analyzing panel data from 2003 to 2022. The Poisson pseudo-maximum likelihood estimator is employed to estimate an augmented gravity model that considers domestic trade flows, endogeneity issues, reverse causality, globalization effects, long-term effects, and overlapping membership. The empirical findings demonstrate that partial scope agreements and EIAs significantly promote bilateral agri-food trade, whereas temperature distance acts as a barrier and precipitation distance has a negligible effect. Overlapping members of the RCEP and CPTPP exhibit cumulative positive effects three years after the implementation of EIAs, resulting in an approximately 52.1% increase in the bilateral agri-food trade after ten years. Additionally, overlapping membership mitigates the long-term negative impact of temperature distance. This study reveals that the seven overlapping members of the RCEP and CPTPP in the Asia-Pacific region achieve greater benefits more quickly through EIAs, suggesting that overlapping membership can be an effective adaptive strategy for dealing with climate change. Full article

This paper presents the development of an Active Disturbance Rejection Controller (ADRC) to address the trajectory tracking problem of a 2DOF (Degrees of Freedom) Serial Flexible Robot. The proposed approach leverages differential flatness theory to determine the system’s flat output, simplifying the trajectory tracking problem into a linear state feedback control with disturbance rejection. A set of a Generalized Proportional Integral Observer (GPIO) and Luenberger observers is employed to estimate the derivatives of the flat output and both internal and external disturbances in real time. The control law is experimentally validated on a 2DOF Serial Flexible Robot prototype developed by Quanser. Quantitative results demonstrate that the ADRC achieves superior performance compared to a partial state feedback control scheme, with a Mean Squared Error (MSE) as low as 1.0651 × 10⁻⁵ rad² for trajectory tracking. The ADRC effectively suppresses oscillations, minimizes high-frequency noise and reduces saturation effects, even under external disturbances. These findings underscore the robustness and efficiency of the proposed method for underactuated flexible systems. Full article

This study focuses on the collection and UV characterization of the bio-oil phase from primary aerosols ejected from the liquid intermediate phase during the fast pyrolysis of biomass in a hot plate reactor. The effects of the reactor pressure and aerosol-collecting surface temperature on the bio-oil yield and characteristics were evaluated. The study found that lower reactor pressures and a lower temperature of the collecting surface significantly enhanced the aerosol yield (up to 85%). UV-fluorescence was employed to assess the influence of these parameters on the light-to-heavy compound ratio (monomers vs. oligomers). The heavy fraction of bio-oil from the hot plate reactor was predominantly composed of dimers and trimers (340–370 nm), similar to pyrolytic lignin and the heavy fraction of the bio-oil, which also showed peaks in this range. In contrast, pyrolysis oils from auger and fluidized bed reactors displayed two peaks in the UV spectrum, with a maximum around 300 nm, indicating that they are mainly composed of light monomeric compounds. The UV characterization of the primary aerosols and the comparison with the UV spectra of the bio-oil and its fractions (light and heavy fraction and pyrolignin) revealed similar UV prints, highlighting the importance of aerosol ejection in the final composition of bio-oil. Full article

Recently, groove gap waveguides (GGWs) have shown significant potential in power handling and bandwidth enhancement compared to conventional waveguides. In this research work, we designed and developed an innovative mushroom-unit-cell-based groove gap waveguide (MGGW) that has shown improved bandwidth compared to conventional GGW structures. The dispersion characteristics of the MGGW were analyzed through the eigenmode solver feature of Microwave Studio CST, which showed that the bandwidth was improved by 8% compared to conventional unit cells in the microwave spectrum. To validate our proposed method for the physical dimensions of unit cell structures, we developed an MGGW structure for the S band, which shows similar trends aligning with the simulation results. The measurement results are promising as a reflection coefficient of less than −20 dB was achieved over the entire band for the WR284 Electronic Industries Alliance (EIA) standard waveguide adapter. The proposed MGGW structure with improved bandwidth will open new doors for researchers to develop ultra-wide bandwidth microwave applications, i.e., filters, transmission lines, resonators, attenuators, etc. Full article

Objectives: This study aims to evaluate the technical and clinical outcomes of the E-nside stent graft for thoraco-abdominal aortic aneurysm (TAAA) and pararenal abdominal aortic aneurysm (PAAA) endovascular treatment at our University Hospital Center. Methods: We conducted a retrospective analysis of patients electively treated by inner branched EVAR (iBEVAR) between 05/2021 and 03/2023. Demographic, procedural, and clinical data were analyzed. The technical success and clinical outcomes, such as access-site-related complications were reported. The perioperative and early mortality rate, freedom from aortic reintervention, target vessels’ (TVs) patency, and the endoleak rate were evaluated during the follow-up. The technical aspects (external iliac artery diameter, iliac tortuosity, extent of aortic coverage) were retrospectively analyzed. Results: Twenty-two patients were included (age 75.9 ± 5.5; 72.7% male). The aneurism extent was Crawford I = 4 (18.2%), III = 8 (36.4%), IV = 5 (22.7%), V = 1 (4.5%), and PAAA = 4 (18.2%). The mean aortic diameter was 63.5 ± 9.9 mm. The technical success was 95.5% (assisted primary success 100%). The clinical success was 86.4%. The perioperative and early freedom from all-cause mortality rates were 90.9% and 90%, respectively. No case of inter-stage aortic-related mortality was reported, and there was no permanent/temporary spinal cord ischemia (SCI). Seventy-eight out of 81 patent TVs were incorporated through a bridging stent (96.3%). The TV success was 95.1%. The mean external iliac artery (EIA) diameter was 7.5 ± 1.1 mm. Twelve patients (54.5%, including all female patients) were considered outside the instructions for use (IFU) due to narrow iliac arteries. One access-site-related complication was reported. Conclusions: Our experience confirms that E-nside has promising technical and clinical success rates, as well as a low reintervention rate, but it requires a significant compromise of the healthy aortic tissue and adequate iliac arteries that still represents a limitation, especially among women. Mid- to long-term studies and prospective registries are mandatory to evaluate the long-term efficacy and safety, as a comparison between E-nside and other alternative off-the-shelf solutions. Full article