Search Results (4,483)

Background/Objectives: Children and adolescents undergoing Haematopoietic Stem Cell Transplantation (HSCT) experience complex symptoms, often under-reported by patients and undetected by clinicians, which cause distress. Patient-Reported Outcome Measures (PROMs) offer a way to capture symptom experiences directly from patients, with the potential of supporting effective symptom assessment and management, yet their routine use in paediatric HSCT remains unclear. This systematic review synthesises evidence on PROMs used during inpatient paediatric HSCT care, examining their role in symptom monitoring and clinical decision-making, and identifying gaps to strengthen person-centred, developmentally appropriate care. Methods: We searched the MEDLINE, CINAHL, Embase, APA PsychINFO, and Cochrane Library in October 2024 for studies published in English between 2014 and 2025 describing the use of PROMs during inpatient paediatric (0–18 years) HSCT admission (up to Day +100 post HSCT). In March 2025, prior to data extraction, we added additional studies published by authors of included studies. Two-stage independent screening and data extraction were conducted, and the Quality Assessment with Diverse Studies (QuADS) tool was used to appraise each study. Narrative syntheses informed by Symptom Management Theory were used to compare PROM use, clinical integration, and reported impacts. Results: Seventeen studies met inclusion criteria, describing 20 PROMs used during paediatric HSCT hospitalisation. PROMs captured a wide range of physical and psychological symptoms, with pain and nausea most frequently reported. While PROMs reportedly improve symptom detection and communication, integration into routine paediatric HSCT clinical care was rare; and only two studies systematically used PROMs data to guide symptom management. Evidence of PROMs-driven improvements in HSCT clinical outcomes was scarce, and longitudinal data on symptom trajectories were limited. Conclusions: PROMs are not routinely used to inform clinical practice in paediatric HSCT, and current evidence provides only a partial understanding of symptom trajectories and lived symptom experiences during the paediatric acute transplant admission. To realise the full potential of PROMs in enhancing symptom assessment and management, systematic PROMs integration into clinical workflows is required, supported by electronic health record integration, clinician training, and longitudinal research designs that capture symptom evolution across the transplant continuum. Full article

Deep shale gas reservoirs in the southern Sichuan Basin (Weiyuan area) exhibit strong heterogeneity and complex pore-fracture networks. Traditional reservoir evaluation methods struggle to accurately capture their microscale pore characteristics and fracability, thereby restricting efficient development and precise sweet spot prediction. Therefore, integrating digital core technology with geological analysis is essential to systematically quantify key reservoir parameters, including microscale pore structure, mineral composition, and brittleness characteristics. To clarify the controlling factors of high-quality deep shale gas reservoirs in the Weiyuan area and assess their exploration and development potential, we performed digital core analysis at micron to nanometer scales. Three-dimensional digital core models of representative deep shale gas wells were constructed. Integrating mineral composition, geochemical characteristics, and pore space features, we discuss the geological conditions for deep shale gas accumulation and the fracability of horizontal wells, and we delineate favorable shale reservoir zones. The results show that digital core technology enables quantitative and visual characterization of each sublayer of the Longmaxi Formation shale reservoir, including mineral types, laminae types, pore-throat structures, and organic matter distribution. From the Long 11-1 sublayer to the Long 11-4 sublayer, the pore-throat radius, total pore volume, total throat volume, connected pore-throat percentage, and coordination number all gradually decrease. In the eastern Weiyuan area, the siliceous components in deep shale gas reservoirs at the base of the Longmaxi Formation are primarily of both biogenic and terrigenous origin. Due to local variations in the sedimentary environment, terrigenous input contributes significantly to the total siliceous content in this region. Although the Long 11-1 sublayer of the Longmaxi Formation is lithologically classified as mud shale, its particle size and mineral composition more closely resemble those of clayey siltstone or argillaceous sandstone, suggesting considerable potential for reservoir space development. Typical wells in the eastern Weiyuan area exhibit distinct lithological characteristics, including coarser grain sizes, stronger hydrodynamic conditions during deposition, and abundant terrigenous clastic supply. The rigid framework formed by silt- to sand-sized particles effectively mitigates compaction, thereby facilitating the preservation of intergranular pores and microfractures. High organic matter abundance, appropriate thermal maturity, and a considerable thickness of high-quality shale ensured sufficient hydrocarbon supply. The main types of natural fractures are intergranular and grain-edge fractures formed by differences in sedimentary grain size, and bedding-parallel fractures generated by hydrocarbon generation overpressure. Based on reservoir mineral composition, pore characteristics, areal porosity, and pore size distribution identified via digital core analysis, the bottom 0–3 m of the Long 11-1 sublayer is determined to be the optimal target interval. By delineating the microscopic characteristics of the shale reservoir and predicting rock mechanical parameters, a fracability evaluation index was established from digital core simulations. This guides the selection of target layers in deep shale gas reservoirs and optimizes hydraulic fracturing design. Full article

To enhance the propulsion efficiency of near-space high-altitude unmanned aerial vehicle under low-density conditions and to gain a deeper understanding of the aerodynamic characteristics of contra-rotating propellers under complex interference, this study focuses on a high-altitude contra-rotating propeller propulsion system. A systematic investigation is conducted on the influence of design variables and flow characteristics. Considering the distinctive features of high-altitude environments, including low Reynolds numbers, high induced velocity ratios, and strong mutual interference between front and rear rotors, a numerical simulation method for contra-rotating propellers is established. The aerodynamic performance and typical flow structures are analyzed and compared with conventional propeller configurations to elucidate the aerodynamic advantages of contra-rotating propellers. Furthermore, key design variables such as axial distance, pitch angles of the front and rear propellers, and rotational speed matching are systematically examined to assess their effects on aerodynamic characteristics. Comparative analysis of axial velocity distributions reveals the interaction mechanisms between front and rear rotors under different parameter combinations and identifies the dominant factors influencing aerodynamic performance. The results indicate that rational matching of geometric parameters between front and rear rotors can effectively mitigate adverse interference, optimize wake structures, and improve the overall aerodynamic performance of contra-rotating propellers at high altitudes. These findings provide theoretical guidance and engineering references for the aerodynamic design and parameter selection of high-altitude contra-rotating propeller systems. Full article

This study presents an analytical formulation for predicting the additional elastic deflection of tapered steel beams with variable-diameter circular web openings, a configuration that is not addressed by existing analytical models or current design codes. The proposed formulation accounts for the coupled effects of cross-section tapering, progressive variation in opening diameter along the span, and shear–bending interaction within perforated regions. To the best of the authors’ knowledge, this is the first analytical model addressing such complex non-prismatic cellular beam configurations. The formulation is implemented in MATLAB R2019a, enabling fast and automated deflection calculations over a wide parametric range, including various loading cases, tapering ratios, beam spans, web-post widths, and opening dimensions. For prismatic configurations, the analytical predictions are benchmarked against Eurocode 3 and the SCI P355 design guide, both originally developed for beams with constant cross-sections and regular openings. The results demonstrate the improved accuracy and broader applicability of the proposed approach. For tapered configurations with variable-diameter openings, the formulation is assessed against finite element simulations performed in Abaqus/CAE 2017, with the numerical model previously validated against experimental results available in the literature. The proposed method provides a reliable and practical analytical tool for the serviceability assessment of tapered perforated steel beams in structural engineering applications. Full article

Many wind farms currently host turbines approaching their designed lifespan, which need to be repowered. Using historical operational data for wind resource evaluation can not only reduce costs but also improve efficiency. However, nacelle wind speed deviates from actual inflow wind speed due to rotor disturbance, thus demanding correction prior to use. This paper innovatively proposes a piecewise inflow wind speed calculation (PMCP) method based on pitch angle and power fusion. This method divides the full wind speed range into low and high regions by taking the rated wind speed as the boundary. Inflow wind speed in the low region is calculated via the turbine’s theoretical power curve, while that in the high region is derived from the pitch angle curve, with statistical methods establishing the mathematical relationship between inflow and nacelle wind speeds. Two wind farms are selected as cases to verify the method’s applicability across different topographies. Results show that the PMCP method exhibits varying performance in different terrains. In flat terrain, the time-series wind speed RMSE is 15.7% lower than that of direct nacelle wind speed, with accuracy comparable to the IEC nacelle transfer function (NTF) method. Moreover, the Weibull distribution curve of the calculated wind speed agrees significantly better with the measured one. In complex terrain, while its error is slightly higher than the NTF method, the accuracy is still markedly improved compared to direct use of nacelle wind speed. The PMCP method can accurately calculate full-range time-series inflow wind speed and improve the accuracy of wind resource assessment at turbine sites, while boasting the prominent advantage of relying solely on historical turbine operation data with no need for measured inflow wind speed. Full article

Remaining Useful Life (RUL) prediction is a key component of prognostics and health management for modern industrial systems. While deep learning methods have significantly improved prediction accuracy, many existing approaches rely on large neural networks that are difficult to deploy on resource-constrained edge devices. This study presents a deployment-oriented evaluation of compact neural networks for RUL prediction using the NASA C-MAPSS turbofan engine benchmark. Two lightweight hybrid architectures, CNN–GRU and CNN–TCN, were developed with approximately 28k–32k parameters to represent realistic models for CPU-based edge inference. A systematic experimental analysis was conducted across all four C-MAPSS subsets (FD001–FD004), which represent increasing levels of operational and fault complexity. In addition to baseline performance, two post-training compression techniques (i.e., global unstructured magnitude pruning and dynamic INT8 quantization) were evaluated. To assess real deployment behavior, inference latency was measured on both a high-performance Intel x86 workstation and a resource-constrained ARM platform. Results show that CNN–GRU generally achieves higher predictive accuracy, whereas CNN–TCN provides more consistent and lower inference latency due to its convolution-only temporal modeling. Unstructured pruning can yield modest improvements in prediction accuracy, suggesting a regularization effect, but it does not reliably reduce model size or latency on standard CPUs due to the overhead associated with pruning masks. Dynamic quantization substantially reduces model size (particularly for CNN–GRU) while preserving predictive accuracy; however, it increases runtime latency because of additional quantization and dequantization operations. These findings demonstrate that compression techniques commonly used for large models do not necessarily translate into deployment benefits for already compact RUL architectures and highlight the importance of hardware-aware evaluation when designing edge prognostics systems. Full article

Gas-cooled reactors are highly sophisticated energy systems in which numerous physical phenomena take place at the same time. Among these, the effective removal of heat from the reactor core is of great importance. In gas-cooled reactors, convective heat transfer and the conditions under which it occurs are critical to both the performance and safety of these reactors. Convective heat transfer in gas-cooled reactors is particularly complex due to the thermo-physical properties of gaseous coolants, high operating temperatures, and diverse flow regimes. It is commonly characterized using empirical and semi-empirical correlations. Each correlation is valid only within specific ranges of operating and geometric conditions, making the appropriate selection of correlations essential for accurate reactor design and reliable safety assessment. The aim of this review is to provide a comprehensive evaluation of the models and correlations applicable to the description and modeling of convective heat transfer in selected types of gas-cooled reactors. For each reactor type, the relevant correlations are categorized and summarized in tables, along with their ranges of applicability and inherent limitations. In total 154 correlations were reviewed. The findings highlight that convective heat transfer in different types of gas-cooled reactors is described differently. This article offer a consolidated reference of correlations useful for engineers and researchers working in the field of heat transfer and nuclear reactor engineering. In addition, remaining challenges are discussed and future research directions are proposed to support improved heat transfer modeling for current and next-generation gas-cooled reactor technologies. Full article

To address the limited in situ stress data and poor nonlinear fitting of existing methods, a Particle Swarm Optimization (PSO)–XGBoost inversion approach is proposed. XGBoost effectively models complex relationships between finite element results and measured stresses, leveraging its strong nonlinear mapping and suitability for small samples. PSO globally optimizes XGBoost hyperparameters, utilizing its fast convergence and global search capability. Combined with 5-fold cross-validation, this avoids empirical tuning errors and enhances generalization. The model uses finite-element-based stress-response values as inputs and calculates in situ stress data derived from hydraulic fracturing interpretations as targets. Engineering applications show that the PSO-XGBoost model outperforms common methods, achieving superior prediction accuracy and generalization with fast convergence. This offers a high-precision inversion approach for small-sample conditions, supporting engineering design and safety assessment. Full article

Groundwater contamination caused by dense non-aqueous phase liquid (DNAPL) has long been recognized as a persistent environmental challenge, particularly in fractured porous media. DNAPL migration is highly uncertain due to the heterogeneity and complexity of fracture networks, which complicates risk assessment and remediation design. This paper begins with an overview of mathematical models for multiphase flow migration in fractured media, followed by a systematic analysis and classification of DNAPL migration mechanisms based on laboratory experiments and numerical simulations. Subsequently, key challenges in current DNAPL remediation practices are discussed, including difficulties in monitoring and characterizing fractured aquifers, limited delivery and utilization efficiency of remedial agents, and the back-diffusion of DNAPL from low-permeability zones. Based on this analysis, three primary DNAPL remediation approaches—physical, chemical, and biological methods—are reviewed and evaluated. Finally, future research directions for understanding DNAPL migration and improving remediation strategies in fractured media are proposed. Overall, this review bridges mechanistic knowledge, simulation research, and remediation practice, providing insights that contribute to future technological progress and management decision-making in DNAPL-contaminated fractured aquifers. Full article

High-performance operation of permanent magnet synchronous motors (PMSMs) strongly depends on the reliable availability of rotor position and speed information. Although this information is commonly obtained using physical position sensors, such sensors increase system cost and structural complexity and may reduce long-term reliability, particularly in demanding operating environments. In this study, a model-based, discrete-time, nonlinear gradient observer is adapted for the sensorless estimation of rotor speed and position in PMSMs. The developed Runge–Kutta model-based gradient observer (RKGO) utilizes stator voltage inputs and measured stator currents within a mathematical motor model to estimate the system states. In contrast to conventional sensorless estimation approaches, the adopted observer framework exploits discretization-based gradient dynamics to enhance numerical robustness and convergence behavior under nonlinear operating conditions. The observer design specifically targets stable and accurate state estimation in discrete-time implementations, with a particular focus on low-speed operating conditions. The performance of the adapted method is experimentally evaluated under low-speed operating conditions, including transient and steady-state operation. Real-time implementation is carried out on a dSPACE DS1104 control platform, including loaded acceleration scenarios to assess practical robustness. In addition, a comparative analysis with the Extended Kalman Filter (EKF) and the Runge–Kutta Extended Kalman Filter (RKEKF) is conducted at 60 rad/s under identical experimental conditions. Experimental results show that the RKGO method achieves accurate steady-state speed and position estimation with acceptable transient performance. The findings demonstrate that RKGO can be considered a viable alternative for low-speed sensorless PMSM drive applications. Full article

In the context of digitalization and growing demands for environmental responsibility, creative industries are seeking ways to reduce their material footprint. The purpose of this study is to evaluate the role of digital technologies, such as virtual prototyping and digital fashion, in shaping new sustainability standards. To achieve this, a systemic multidisciplinary approach was applied, combining comparative analysis, quantitative assessment of key indicators (MIRR, CFCI, VSR), and the calculation of the Integral Sustainability Index (ISI).The results show that virtual prototyping reduces material costs by 45–65% and the number of physical prototypes by 3–5 times; however, its energy efficiency depends on project complexity and is achieved only after the ‘energy break-even point.’ Digital fashion practices demonstrate the potential to reduce the carbon footprint, but only when utilizing energy-efficient digital infrastructure. The integrated assessment revealed an increase in the overall level of sustainability (with $ISI$ rising from 0.52 to 0.71) during the transition to digital processes. The main conclusion is that digital technologies establish new sustainability standards, yet their positive impact is realized only through the conscious design of technological systems, business models, and institutional environments focused on balancing environmental, economic, and social goals. Full article

The increasing global demand for sustainable water purification technologies has accelerated research on catalytic degradation and advanced oxidation processes for the removal of refractory pollutants. This study provides a comprehensive bibliometric analysis of global research trends in catalytic water and wastewater treatment from 2010 to 2025, combining quantitative mapping with a qualitative synthesis of emerging technological directions. Bibliographic data were retrieved from the Scopus database and screened using the PRISMA framework, followed by analysis using VOSviewer (v1.6.20) and OriginPro (version 2023, OriginLab Corporation, Northampton, MA, USA) to examine publication growth, citation patterns, international collaboration networks, and thematic evolution. A total of 1550 publications, including 1265 research articles and 285 review papers, were analyzed. The results show a significant increase in research output after 2015, reflecting growing global attention to water sustainability and environmental remediation. China, the United States, and India were identified as the leading contributors, with strong international collaboration networks. Keyword co-occurrence analysis revealed three dominant research themes: photocatalytic degradation and semiconductor engineering, Fenton and Fenton-like advanced oxidation processes, and emerging hybrid catalytic systems involving carbon-based materials and metal–organic frameworks. The analysis also indicates a recent shift toward multifunctional hybrid catalysts designed to improve efficiency, stability, and performance in complex wastewater systems. These findings highlight key scientific developments and suggest future research priorities, including green catalyst synthesis, reactor and process scale-up, AI-assisted catalyst design, and life-cycle sustainability assessment to support the transition from laboratory research to practical water treatment applications. Full article

Background: Severe jaw atrophy limits traditional endosseous implantation, often necessitating complex regenerative procedures. Advances in digital planning and 3D printing have reintroduced custom-made subperiosteal (juxta-osseous) implants as a viable alternative. This study evaluates the clinical reliability and advantages of next-generation juxta-osseous implants. Materials and Methods: A systematic review was conducted in accordance with PRISMA guidelines across the PubMed, Scopus, and Web of Science databases. The search focused on English-language studies reporting on custom-made titanium juxta-osseous implants in patients with severe maxillary or mandibular atrophy. Methodological quality was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist. Additionally, a representative clinical case of a 60-year-old female treated via a fully digital workflow is presented to illustrate the protocol. Results: Twenty-six articles were included, accounting for 147 clinical cases. Most patients exhibited Cawood and Howell Class V–VI atrophy. All identified treatments utilized integrated digital workflows, including CBCT imaging, CAD/CAM design, and additive manufacturing (SLM/DMLS) of medical-grade titanium alloy. Reported success rates exceeded 90%, with high primary stability enabling immediate or early loading protocols and high patient satisfaction. Complications were primarily limited to manageable soft-tissue dehiscence. Conclusions: Modern juxta-osseous implants represent a promising, minimally invasive alternative to bone grafting for severe atrophy, enabling rapid functional restoration in the short-to-medium-term. However, because current evidence is limited to clinical studies, these findings should be interpreted with caution. Long-term prospective trials are essential to establish definitive clinical predictability and standardized protocols. Full article

Biomass combustion, as a key technology for achieving a low-carbon transformation of the energy system, faces multiple challenges in its efficient and clean utilization, including the high heterogeneity of fuels, the complex multi-scale coupling of the combustion process, and the attainment of ultra-low emissions. Traditional research methods have significant disconnections between microscopic mechanism understanding, macroscopic performance prediction of reactors, and end-of-pipe pollution control, which restricts the improvement of system performance. This review presents recent advances in advanced numerical simulation, pollutant control strategies, and bioenergy with carbon capture and storage (BECCS) pathways targeting ultra-low emissions in biomass combustion. This work synthesizes progress across three interconnected domains. First, methodologies are examined for integrating detailed chemical kinetics, particle-scale models, and reactor-scale simulations to develop high-fidelity predictive tools. Second, low-nitrogen combustion and synergistic pollutant control strategies for primary furnace types (e.g., grate, fluidized bed) are evaluated, alongside process optimization from fuel pretreatment to flue gas purification. Third, the potential for integrated design of biomass energy systems with carbon capture is assessed, emphasizing that system efficiency hinges on holistic “fuel-combustion-capture” chain optimization rather than isolated unit improvements. Future research directions are highlighted, including the development of physics-informed AI modeling paradigms, deeper co-design of multiple processes, and the establishment of robust life-cycle assessment frameworks. This review aims to provide a structured reference to inform both fundamental research and the practical development of next-generation clean biomass combustion technologies. Full article

Dispersed archaeological landscapes are often rich in heritage value but weakly integrated into regional tourism systems. This creates difficulties in visitor orientation, interpretive continuity, and conservation-sensitive tourism planning. In response to this problem, this study examines the Adana–Kozan–Anavarza axis in southern Türkiye and proposes a spatial corridor framework for organising tourism development within a dispersed archaeological landscape. The research integrates spatial accessibility assessment, service-capacity evaluation, field observation, and sequential route design in order to establish a hierarchical gateway–transition–anchor configuration. Anavarza, one of the largest archaeological complexes of Cilicia, represents a monumental urban heritage site and a biocultural landscape situated within a Mediterranean ecological zone historically associated with Pedanius Dioscorides. Although current visitor volumes remain moderate, official statistics indicate a substantial increase in annual entries between 2022 and 2024, reflecting rising destination visibility. This emerging growth trajectory underscores the need for proactive spatial governance mechanisms prior to the onset of congestion and environmental degradation pressures. The findings suggest that Adana can function as a metropolitan gateway, Kozan as an intermediate staging node, and Anavarza as the archaeological anchor within a realistic multi-day visitor sequence. In this configuration, visitor functions are distributed across multiple nodes, while the ecological and archaeological sensitivity of the anchor landscape is more cautiously managed through spatial sequencing. Rather than proposing a predictive model, the study develops and assesses a context-responsive spatial planning framework grounded in accessibility, infrastructural feasibility, and conservation-sensitive visitor distribution. Beyond the local case, the study offers a transferable hierarchical staging logic for corridor-based heritage planning. Full article