Search Results (17,964)

Engineering programmes have been giving more weight to experiential learning, largely because many students still find it difficult to see how classroom theory connects to the work that engineers handle on the ground. With this in mind, a robotics-centred Project-based Learning (PBL) module was introduced to first-year general engineering students as part of the faculty’s engineering spine. The module asks students to design, build, and program small autonomous robots capable of navigating and competing in a set arena. Even a simple task of this kind draws together multiple strands of engineering. Students shift between sketching mechanical layouts, wiring basic circuits, writing code, testing prototypes, and negotiating the usual challenges that arise when several people share responsibility for the same piece of hardware. To explore how students learned through the module, a mixed-methods evaluation was carried out using survey responses alongside reflective pieces written by the students themselves. Certain patterns appeared repeatedly. Many students felt that their technical skills had grown, particularly in breaking down a messy problem into smaller, more workable components. Teamwork also surfaced as a prominent theme. Groups often had to sort out issues such as a robot veering off course due to a misaligned sensor or a block of code producing unpredictable behaviour. These issues were undoubtedly challenging for the students, but they also had a certain pedagogical flavour, with many students describing them as a source of frustration as well as a learning opportunity. Later iterations of the module may benefit from more targeted support at key stages. Despite the many challenges, robotics has been shown to be an attractive way for students to step into engineering practice. The project helped them build technical capability, but it also encouraged habits that matter just as much in real work, such as planning, communicating clearly, and returning to a problem until it behaves as expected. Taken together, the experience offers useful guidance for curriculum designers seeking to create early learning environments that feel authentic and manageable and for motivating students who are just beginning their engineering journey. Full article

In modern power systems, the implementation of load-frequency control (LFC) must reconcile continuous-time plant dynamics with discrete-time digital controllers operating under coarsely sampled communications. This paper develops a sampled-data $H_{\infty }$ framework for PI-type secondary LFC that explicitly accounts for aperiodic sampling and reduced inertia due to high wind penetration. Using a two-sided looped Lyapunov functional and free-matrix inequalities, sampling-interval-dependent linear matrix inequalities (LMIs) are derived for stability, $H_{\infty }$ performance and an exponential decay rate (EDR). The synthesis returns PI gains and the admissible maximum sampling period (MASP) via simple bisection. Numerical examples based on one-area, two-area, and three-area power systems demonstrate that the proposed stability conditions allow larger admissible sampling periods compared with existing approaches, while preserving satisfactory dynamic behaviour under different operating scenarios. Full article

Reducing urban–rural income inequality is a central objective of sustainable development and a critical challenge for inclusive growth in emerging economies. This study examines the impact of the digital economy on urban–rural income inequality in China. Using panel data across 279 cities in China and Chinese Household Income Project (CHIP) data, we find that the digital economy significantly widens urban–rural income inequality. Specifically, digital industries and innovations are the main drivers, contrasting with inclusive infrastructure. Although we observe a positive association between the digital economy and educational attainment among rural residents, such improvements do not appear to be fully translated into higher income. One possible explanation is that the digital economy is more effective in alleviating skill mismatch among urban residents than among their rural counterparts. Finally, our results suggest that Public Employment Services may help mitigate this negative effect through channels such as fiscal subsidies and improving skills training accessibility. Our findings highlight the need for caution regarding the inequality implications of digital economy development in emerging economies and underscore the crucial role of institutional arrangements in promoting socially sustainable and inclusive development. Full article

Over the past two decades, Light Detection and Ranging (LiDAR) technology has evolved from early National Aeronautics and Space Administration (NASA)-led airborne laser altimetry into commercially mature systems that now underpin vegetation remote sensing across scales. Continuous advancements in laser engineering, signal processing, and complementary technologies—such as Inertial Measurement Units (IMU) and Global Navigation Satellite Systems (GNSS)—have yielded compact, cost-effective, and highly sophisticated LiDAR sensors. Concurrently, innovations in carrier platforms, including uncrewed aerial systems (UAS), mobile laser scanning (MLS), Simultaneous Localization and Mapping (SLAM) frameworks, have expanded LiDAR’s observational capacity from plot- to global-scale applications in forestry, precision agriculture, ecological monitoring, Above Ground Biomass (AGB) modeling, and wildfire science. This review synthesizes LiDAR’s cross-domain capabilities for the following: (a) quantifying vegetation structure, function, and compositional dynamics; (b) recent sensor developments encompassing ALS discrete-return (ALS_D) and ALS full-waveform (ALS_FW), photon-counting LiDAR (PCL), emerging multispectral LiDAR (MSL), and hyperspectral LiDAR (HSL) systems; and (c) state-of-the-art data processing and fusion workflows integrating optical and radar datasets. The synthesis demonstrates that many LiDAR-derived vegetation metrics are inherently transferable across domains when interpreted within a unified structural framework. The review further highlights the growing role of artificial-intelligence (AI)-driven approaches for segmentation, classification, and multitemporal analysis, enabling scalable assessments of vegetation dynamics at unprecedented spatial and temporal extents. By consolidating historical developments, current methodological advances, and emerging research directions, this review establishes a comprehensive state-of-the-art perspective on LiDAR’s transformative role and future potential in monitoring and modeling Earth’s vegetated ecosystems. Full article

Promoting cultivated land green utilization efficiency (CLGUE) through agricultural scale operation is critical for reconciling the conflict between food security and sustainable land use. Based on panel data from 30 provinces in China (2007–2022), this paper calculates CLGUE using the Super-efficiency SBM-Undesirable model and empirically examines the impact mechanisms and nonlinear characteristics of scale operation using Tobit and threshold models. The findings reveal that: (1) Agricultural scale operation has a significant positive impact on CLGUE, but this effect is non-linear and characterized by diminishing marginal returns, validating the “moderate scale” operation theory. (2) Substantial heterogeneity exists across different functional grain production zones and geographic regions. (3) Mechanism analysis identifies technological innovation as a key transmission channel through which scale operation boosts CLGUE. (4) A significant double-threshold effect is observed in fiscal support for agriculture; specifically, the positive enabling effect of scale operation is maximized only when fiscal support intensity is maintained within a specific rational range. Consequently, this study suggests that policymakers should prioritize “moderate scale” strategies, tailor policies to regional conditions, and optimize the allocation of fiscal funds to foster a transition toward green and sustainable agriculture. Full article

Japanese modern irrigation management is considered a successful model of water governance worldwide. However, debates continue over whether this success is due to natural water abundance or to water management practices. This study evaluates pre-modern water scarcity risk for six irrigation schemes, developed during that period in the Kinu River Basin (1603–1868); a period without large reservoirs, canal systems, or modern regulatory technologies. As the methodology, pre-modern river flows were reconstructed by removing the effects of four modern dams from the present-day river discharge, adjusting the conveyance efficiency, changes in paddy field area, rainfall input, and return flows. Water demand was assessed using Japanese irrigation standards of 5 mm/d (minimum water demand corresponding to evapotranspiration) and 20 mm/d (easy management), and risk was evaluated under both the prior appropriation and Equal Water Distribution rules. Results show that modern flow in the dry season is approximately 25 m³/s, whereas reconstructed natural flow during drought years declines to 10–18 m³/s, and about 15 m³/s after rainfall adjustment. Under the 20 mm/d demand scenario, scarcity occurred in four schemes (2 of 17 years in the third scheme and 7 of 17 years for the sixth scheme), while no scarcity occurred under the minimum-demand scenario (5 mm/d), even during low-flow conditions. This indicates that the available water in these schemes was at a level where drought damage could occur under extensive irrigation management, but could be avoided by intensive irrigation management to supply the minimum necessary water to all paddy fields. Full article

Background/Objectives: Alcohol-based handrub (ABHR) consumption is commonly used as an indirect proxy for hand hygiene practices. Hand hygiene compliance increased significantly during COVID-19, but sustainability remains uncertain. This study assessed ABHR consumption trends from 2022 to 2024 and compared them with pre-pandemic and pandemic-era rates. Methods: We conducted a follow-up observational study tracking quarterly ABHR consumption in a surgical department and hospital-wide (2022–2024). Consumption was normalized as mL per patient-day and compared with 2019–2020 data. Time-series regression with Newey–West standard errors assessed temporal trends. Results: Surgical department consumption declined 27.5% (55.9 to 40.5 mL/patient-day), returning to 2019 pre-pandemic levels. Hospital-wide consumption increased 36% (36.4 to 49.6 mL/patient-day). Neither trend reached statistical significance (p > 0.05). The 2024 surgical rate remained substantially below the 2020 pandemic peak (320 mL/patient-day). Conclusions: Pandemic-era ABHR consumption gains were not sustained in the surgical department despite maintained educational infrastructure, accessible dispensers, and consistent staffing. The critical missing element was systematic monitoring and feedback. Institutions relying solely on passive education may experience erosion of hand hygiene compliance post-crisis, highlighting the need for active surveillance programs to maintain behavioral gains. Full article

This study empirically investigates the relationship between Environmental, Social, and Governance (ESG) scores and the financial performance of Mexican companies traded at Bolsa Mexicana de Valores (BMV), based on firm value and profitability. The study used a quantitative method of correlational research. Using data from the Refinitiv, the study analyzes 103 companies operating in 37 different industries listed on the BMV over five years (2019–2023), excluding financial institutions. Ordinary least squares (OLS) regressions revealed a statistically significant, positive correlation between ESG scores associated with higher return on assets (ROA) and market value measured by Tobin’s Q). Stakeholder theory serves as the theoretical foundation, as ESG initiatives may enhance long-term value for stakeholders. The study found that ESG efforts contribute positively to ROA and Tobin’s Q of public companies in Mexico. This study focuses exclusively on Mexican companies, expanding the existing literature. Corporate decision makers and investors can gain insights into ESG’s role in Mexican companies’ financial strategy and stakeholder value creation. Full article

Floods are among the most catastrophic natural disasters, causing severe impact on human lives and ecosystems. The proposed methodology integrates Geographic Information Systems, 2D hydraulic modeling, and deep learning techniques to develop a computational simulation approach for flood extent prediction and was implemented in the Enipeas River basin, located within the Thessalia River Basin District, Greece. Hydrological analysis was performed using the HEC-HMS software (version 4.12), while hydraulic simulations were conducted with HEC-RAS 2D. The hydraulic modeling produced synthetic flood scenarios for a 1000-year return period, generating spatially distributed outputs of flood extents. The deep learning algorithm was based on a U-Net (CNN) architecture. The model was trained using multi-channel raster tiles, including open access geospatial data such as Digital Elevation Model, slope, flow direction, stream centerline, land use, and simulated flood extents. Model validation was carried out in two independent domains (TS1 and TS2) located within the same river basin. Model outputs are adequately compared with both 2D hydraulic simulations and official Flood Risk Management Plan maps, and the comparison indicates close spatial and quantitative agreement, with flood extent area differences below 8%. Based on the results, the proposed methodology presents a potential and efficient tool for rapid flood risk mapping. Full article

Ocular allergy (OA) is a subtype of seasonal allergy that causes symptoms of itchiness, redness, swelling and irritation of the ocular surface and eyelids, often triggering allergy-induced eye rubbing and sustained inflammation for up to six months of the year during peak allergy season. These symptoms, coupled with reduced sleep quality, impaired daily productivity and decreased mood, highlight a significant yet underrepresented disease burden. Recent advances in tear-based multi-omics have enabled detailed characterisation of OA-associated biochemical changes on the ocular surface, highlighting human tears as a promising biospecimen for diagnostic biomarker and therapeutic target research. This review discusses emerging proteomic, lipidomic, metabolomic and miRNA findings comparing OA sufferers with healthy controls, and, where relevant, with comorbid conditions such as dry eye disease and keratoconus. Differential expression patterns across these analytes implicate key pathways involved in immune response, wound healing, angiogenesis, inflammation, oxidative stress and return to homeostasis on the ocular surface. By integrating these data into a stepwise model of OA biopathway activation, this review outlines candidate biomarkers and highlights methodological advances that may support translation of tear multi-omics into clinical tools for OA management. Full article

Thyroid hormones (THs) regulate metabolism, proliferation, and genomic stability. Clinical studies have linked levothyroxine therapy with higher Oncotype DX Recurrence Scores in breast cancer (BC), suggesting a potential effect of thyroid hormone signaling on genomic risk. Here, we investigated the impact of triiodothyronine (T3) on DNA damage and repair pathways in estrogen receptor-positive T47D breast cancer and non-tumorigenic MCF10A cells. RNA sequencing revealed significant upregulation of RAD51 and enrichment of DNA repair pathways following 24 h T3 exposure. Consistently, T3 increased γH2AX and 53BP1 nuclear foci, indicating transient activation of the DNA damage response (DDR). These effects were transient, returning to baseline after 48 h, suggesting cellular adaptation. T3 also enhanced proliferation at 10 μM but inhibited growth at higher concentrations. Our findings indicate that acute exposure to T3 induces transient genomic stress, providing a potential mechanistic basis for the observed association between thyroid hormone therapy and increased BC recurrence risk. Full article

Background/Objectives: Low back pain (LBP) is the leading cause of disability in Saudi Arabia and contributes substantially to healthcare utilisation, reduced quality of life, and lost productivity. This guideline provides nationally standardised, evidence-based recommendations for the assessment and management of non-specific LBP and sciatica in adults, adapted to the clinical and health-system context in Saudi Arabia. Methods: A multidisciplinary Task Force developed the guideline using the GRADE ADOLOPMENT approach, using NICE guideline NG59 as the primary evidence source. One additional clinical question was formulated to address pain neuroscience education, informed by a relevant systematic review. Update literature searches were conducted in PubMed, Embase, and the Cochrane Library (2016–2022). The evidence was appraised using GRADE, and recommendations were formulated through structured Evidence-to-Decision deliberations and consensus voting. Results: The Task Force addressed eleven clinical questions in this guideline. Strong recommendations were provided for the use of validated risk assessment tools (very low certainty of evidence) and stratified management (moderate certainty of evidence). Conditional recommendations were made for indications for imaging, pharmacological treatment for sciatica, psychological interventions, multidisciplinary return to work programmes, epidural injections, prognostic value of image-concordant pathology, spinal decompression, radiofrequency denervation, and pain neuroscience education, with certainty of evidence ranging from very low to low. Conclusions: The findings indicate that management of non-specific LBP and sciatica in Saudi Arabia should be guided by clinical assessment, with restricted use of imaging, careful selection of pharmacological treatments, and appropriate use of psychological, multidisciplinary, and procedural interventions. Full article

The intensification of extreme rainfall events under changing climate regimes has heightened concerns over nutrient losses from paddy agriculture, particularly nitrogen (N), a primary contributor to non-point source pollution. Despite advances in drainage management, limited studies have integrated probabilistic rainfall modeling with N transport simulation to evaluate mitigation strategies in rice-based systems. This study addresses this critical gap by coupling the Log-Pearson Type III (LP-III) distribution with the DRAINMOD-N II model to simulate N dynamics under varying rainfall exceedance probabilities and drainage design configurations in the Kunshan region of eastern China. The DRAINMOD-N II showed good performance, with R² values of 0.70 and 0.69, AAD of 0.05 and 0.39 mg L⁻¹, and RMSE of 0.14 and 0.91 mg L⁻¹ for NO₃⁻-N and NH₄⁺-N during calibration, and R² values of 0.88 and 0.72, AAD of 0.06 and 0.21 mg L⁻¹, and RMSE of 0.10 and 0.34 mg L⁻¹ during validation. Using around 50 years of historical precipitation data, we developed intensity–duration–frequency (IDF) curves via LP-III to derive return-period rainfall scenarios (2%, 5%, 10%, and 20%). These scenarios were then input into a validated DRAINMOD-N II model to assess nitrate-nitrogen (NO₃⁻-N) and ammonium-nitrogen (NH₄⁺-N) losses across multiple drain spacing (1000–2000 cm) and depth (80–120 cm) treatments. Results demonstrated that NO₃⁻-N and NH₄⁺-N losses increase with rainfall intensity, with up to 57.9% and 45.1% greater leaching, respectively, under 2% exceedance events compared to 20%. However, wider drain spacing substantially mitigated N losses, reducing NO₃⁻-N and NH₄⁺-N loads by up to 18% and 12%, respectively, across extreme rainfall scenarios. The integrated framework developed in this study highlights the efficacy of drainage design optimization in reducing nutrient losses while maintaining hydrological resilience under extreme weather conditions. Full article

Reusable launch vehicles are a key category of next-gen European launchers, as multiple companies are in advanced stages of study and are shifting towards the development of first demonstrators. A worldwide tendency to reduce the costs associated with satellite insertion into low Earth orbits can be observed, together with the existence of a niche in the future European launcher family for reusable small launch vehicles, known as microlaunchers. Multiple recovery methods exist for space launch vehicles; in this study, a return to launch site (RTLS) vertical-landing approach is being prioritized for the recovery of the first stage of a two-stage LOX/methane microlauncher. In 2023, INCAS, with support from the Romanian Nucleu Program, initiated a large study to address the prospect of developing a partially reusable microlauncher. A multidisciplinary optimization (MDO) environment has been developed, which is used in this paper to assess the implications of stage recovery versus the landing location (return to launch site versus downrange recovery) and state whether an RTLS can be feasible for small launchers. The paper will also present some key results from previous studies, such that a clear solution trade-off can be made, together with the quantitative assessment of how different vertical-landing techniques affect the microlauncher specifications. Full article

Turkey is located on an active seismic belt, making the accurate determination of soil properties and earthquake effects essential for safe and reliable structural design. This study investigates the influence of ground improvement on the dynamic behavior of the soil at the construction site of the 950-bed Aydın City Hospital. Evaluations were carried out in terms of the dominant period, local site class and spectral characteristics to assess the effectiveness of the improvement applications. For this purpose, field tests conducted before the improvement were repeated afterward and the obtained data were compared. Local site classes were determined for both unimproved and improved soil conditions based on the relevant seismic code provisions. Furthermore, using site-specific data, nonlinear time-history analyses were performed and site-specific response spectra were obtained for 11 earthquake records at DD-1 and DD-2 seismic hazard levels (return periods of 475 and 2475 years). These spectra were then compared with the corresponding design spectra. The analyses revealed that ground improvement significantly affects not only the bearing capacity and liquefaction potential but also the dynamic behavior, dominant period and local site class of the soil. Full article