Search Results (20,794)

The formulation of construction material unit price policies in areas with limited accessibility is a critical issue in ensuring effective and accountable government infrastructure planning. In such regions, construction costs are often highly volatile and difficult to predict, primarily due to transportation constraints, logistical inefficiencies, and geographical challenges. These conditions frequently result in budget overruns and inconsistencies between planned and actual project expenditures. Therefore, a rational and context-sensitive policy framework is required to support accurate cost estimation and sustainable infrastructure development. This study aims to develop a policy-oriented model for determining construction material unit prices in areas with limited accessibility based on influencing factors. A quantitative research approach was employed through a questionnaire survey involving 235 respondents, consisting of contractors, government representatives, consultants, and academics with experience in infrastructure development in remote or access-constrained regions. The collected data were analysed using Partial Least Squares–Structural Equation Modelling (PLS-SEM) to identify and validate the dominant factors affecting construction material unit prices. The results of the PLS-SEM analysis identified 33 influential factors that significantly contribute to the unpredictability of construction material unit prices in limited-accessibility areas. These factors encompass logistical costs, material price dynamics, government policies, geographical conditions, and local cultural aspects. The proposed model demonstrates that government policy plays a central role, both directly and indirectly through local cultural mediation, in influencing project performance and cost reliability. The findings of this study provide a structured and empirically grounded framework that can be utilized by local governments as a policy reference in establishing construction material unit prices for remote and access-constrained areas. By incorporating the identified influencing factors into unit price formulation, cost prediction accuracy can be improved, thereby supporting more effective budget allocation and ensuring that infrastructure quality is maintained without compromise due to unanticipated cost escalation. These improvements contribute to more sustainable infrastructure development by enhancing resource efficiency, minimizing cost overruns, and supporting equitable infrastructure provision in remote areas. Full article

Taxanes, such as paclitaxel and docetaxel, are microtubule-stabilizing agents widely used in oncology, either as monotherapy or in combination regimens. While highly effective, these first-generation taxanes face important limitations, including significant toxicity, reduced water solubility, and the emergence of multidrug resistance. To address these challenges, semi-synthetic taxoids have been developed, aiming to improve pharmacological profiles and overcome therapeutic barriers. Central to these efforts is the understanding of structure-activity relationships, which guides the rational design of taxane analogues with enhanced efficacy and safety. This review explores recent advances in taxoid development, highlights findings from clinical trials, and evaluates how these new agents compare with traditional taxanes in terms of therapeutic potential and tolerability. While novel delivery systems offer improved outcomes with existing drugs, the development of new taxane analogues remains a promising approach to address drug resistance, albeit with challenges related to toxicity, high costs, and historically low success rates in drug development. Furthermore, taxanes are already used in certain cardiovascular conditions and show emerging potential in neurodegenerative diseases, although current evidence remains largely limited to preclinical or early-phase clinical studies. These developments mark an important evolution in the field and offer new opportunities for future therapeutic strategies. Full article

The transition toward capacity-based network tariffs shifts the primary role of battery energy storage systems (BESS) from traditional energy arbitrage to active peak shaving. This paper presents a mixed-integer linear programming (MILP) optimization model for the co-optimization of both BESS size and operation scheduling for multiple prosumers operating individually and within an energy community (EC). Battery aging is accounted for in the optimization model through the state of health (SOH). The framework is evaluated by a comprehensive techno-economic analysis of BESS integration under Slovenia’s multi-block tariff structure. The results demonstrate that while individual distributed BESS integration is highly profitable, centralized EC BESS financially underperforms. Because centralized BESS cannot directly reduce individual contracted power limits, its profitability relies on energy arbitrage, making the initial investment and double grid fees the primary barriers. Conversely, integrating distributed storage with peer-to-peer (P2P) trading minimizes the required BESS capacity while maintaining profitability. The evaluation also reveals that ECs do not automatically act as socio-economic equalizers, indicated by a stable Gini coefficient. However, a break-even analysis reveals the necessary reduction in capital costs to overcome these hurdles, confirming the strong future viability of centralized EC BESS. Full article

Photolithography is the mainstream technology used in micro/nanofabrication. While projection photolithography is widely used in production, with a resolution close to the wavelength of the light source, its processes are complicated and expensive. Moreover, in projection photolithography, scanning and splicing are required to achieve large-area exposure at the wafer level, which reduces throughput in production. Contact photolithography offers a cost-effective and parallel exposure solution, but achieving uniform resolution over large areas with micrometer or sub-micrometer resolution remains a challenge. In this study, we propose a conformal contact photolithography strategy based on a wafer-scale embedded elastomeric mask. By optimizing metal patterning and embedding transfer processes, we significantly improve the area (wafer-scale) and efficiency (lift-off and metal transfer process within seconds) of metal-embedded elastomeric mask fabrication. This method enables the rapid and cost-effective fabrication of large-area sub-micrometer-resolution structures, with broad applications in the production of sub-micrometer devices and academic research. Full article

Masonry buildings have shaped construction history since about 6500 BCE. They offer durability, strength, and cost effectiveness, especially in developing countries. Yet assessing compressive strength during construction remains challenging due to the constituent materials soil, cement, and stone, complicating standardization worldwide. In the present study, an innovative model based on a machine learning algorithm is put forth to predict the compressive strengths of prisms. Some important factors considered as input to the algorithm based on traditional methods are the brick and mortar strengths, prism geometry, mortar bed thickness, and empirically derived height-to-thickness (t) (h/t) ratios. Three different ANN algorithms are coded and trained on the input data, and they are based on the Levenberg–Marquardt algorithm, the resilient backpropagation algorithm, and the conjugate gradient algorithm. The optimal ANN model trained using the conjugate gradient Polak–Ribière algorithm (traincgp) achieves superior performance, with R² = 0.9881, R² = 0.9927, RMSE = 0.9914 MPa, MAE = 0.6039 MPa, MAPE = 20.9141%, VAF = 0.9881, and WI = 0.9970. Sensitivity analysis shows the height-to-thickness (h/t) ratio is the dominant influence on compressive strength, consistent with structural mechanics. The primary contributions are the systematically curated, richly parameterized dataset and its use to produce robust, physically interpretable predictions with established ANN methods. Full article

Understanding the spatial organization of environmental sounds is essential for linking acoustic patterns with landscape structure and ecological processes. While ecoacoustics has made substantial progress in the temporal and spectral analysis of soundscapes, their directional and spatial components remain comparatively underexplored, particularly through low-cost and scalable approaches. Here we introduce the Sonic Explorer, a lightweight rotational sonic device designed to explore the angular structure and the spatial dynamics of sonotopes, defined as homogeneous spatial sonic units within a soundscape. The system is based on two opposed supercardioid microphones mounted on a rotating platform, coupled with a custom signal-processing framework that analyzes directional variations in sound intensity across frequency classes. Rather than aiming at sound pressure level measurements or full-sphere sound field reconstruction, the Sonic Explorer focuses on detecting spatial contrasts, dominant sound directions, and angular sound patterns relevant to ecological interpretation. Field tests conducted in a human-modified environment demonstrate the ability of the device to identify coherent directional acoustic structures associated with landscape configuration and dominant sound sources. The proposed approach provides a new practical and exploratory tool for landscape and soundscape research, enabling spatially explicit interpretations of sonic environments while maintaining low cost, portability, and adaptability. Full article

Background: Diabetic foot ulcer (DFU) is a major complication of type 2 diabetes (T2D), frequently resulting in disability, lower-limb amputation, and substantial healthcare burden. Early identification of patients at high risk of progressing to severe DFU is essential for timely intervention, yet evidence on associated risk factors remains limited in Bangladesh. This study aims to identify demographic, clinical, and behavioral predictors of severe DFU to support early management strategies. Methods: A cross-sectional study was conducted among 159 DFU patients attending the Rajshahi Diabetic Association General Hospital, Bangladesh. Data on demographic characteristics, clinical variables, and behavioral factors were obtained through structured questionnaires and standardized examinations. Severe DFU was defined as Wagner grades 3–5, while grades 0–2 were considered non-severe. Firth’s penalized logistic regression was used to identify determinants of severe DFU. Model performance was assessed using ROC analysis, calibration belt analysis, and decision curve analysis (DCA). Results: Among the 159 participants, 101 (63.5%) presented with severe DFU. Patients with severe DFU had significantly higher BMI (26.1 vs. 23.7 kg/m²), treatment costs (50,000 vs. 20,000 BDT), and were older (57 vs. 54 years). Severe DFU was also associated with higher prevalence of peripheral arterial disease (PAD) (29.7% vs. 3.4%), prior amputation (31.7% vs. 3.4%), peripheral neuropathy (PN) (86.1% vs. 58.6%), and poor glycemic control (71.3% vs. 30.7%) (all p < 0.05). Firth’s regression identified older age (aOR 1.08), poor glycemic control (aOR 3.90), PN (aOR 3.41), PAD (aOR 7.54), and previous amputation (aOR 13.67) as independent predictors of severe DFU. Conclusions: Older age, uncontrolled glycemia, PN, PAD, and prior amputation were significantly associated with severe stages of DFU. Early detection and targeted management of these factors are critical to reducing complications and lowering the healthcare burden. Full article

Extra-virgin olive oil (EVOO) is a chemically complex lipid matrix whose minor constituents—especially phenolic secoiridoids—drive sensory quality, oxidative stability, and health benefits. However, these bioactives are vulnerable to heat, light, oxygen, and pro-oxidant metals during processing and distribution, while the high cost of EVOO often makes it a target for adulteration and mislabeling. This review critically assesses nano-enabled, food-grade strategies that (i) preserve phenolics and aroma compounds through nanoencapsulation, inclusion complexes, Pickering stabilization, and structured lipid systems; (ii) control their release and bioaccessibility during digestion; and (iii) enhance authenticity verification via sensor-ready packaging, spectroscopy/chemometrics, and digital traceability systems (IoT, machine learning, blockchain). We align these innovations with the “product identity constraints” of the EVOO category and with official quality standards used in routine control (IOC/EU). Finally, we explore circular valorization of olive-mill by-products within food-centered biorefineries, outlining pathways to convert biomass into ingredients, materials, and energy, thus reducing environmental impacts. Research priorities are proposed to develop scalable, regulation-compliant nanotechnologies that extend shelf life and increase consumer trust without compromising EVOO category standards. Full article

Electrocatalytic seawater splitting is an ideal strategy for the large-scale production of green hydrogen. Compared to scarce freshwater, oceanic seawater electrolysis represents a game-changer for the hydrogen economy. Herein, we report a cost-effective one-step synthesis of binder-free, self-supported 3D nickel–manganese–cobalt (NiMnCo) coatings on titanium (Ti) substrates and evaluated their electrocatalytic performance for the hydrogen evolution reactions (HERs) in alkaline media (1.0 M KOH), simulated seawater (SSW, 1.0 M KOH + 0.5 M NaCl) and alkaline natural seawater (ASW, 1.0 M KOH + natural seawater). These ternary coatings were electrodeposited on Ti substrates using an electrochemical deposition method via a dynamic hydrogen bubble template (DHBT) technique. The optimized ternary NiMnCo/Ti-2 electrocatalyst exhibited an enhanced HER activity in both alkaline and seawater media, achieving an ultra-low overpotential of 29, 59 and 66 mV to reach the benchmark current density of 10 mA cm⁻² in SSW, ASW and 1.0 M KOH, respectively. This efficient 3D ternary NiMnCo/Ti-2 electrocatalyst demonstrated stable long-term performance at a constant potential of −0.23 V (vs. RHE) and a constant current density of 10 mA cm⁻² for 50 h without any significant degradation. Furthermore, it exhibited long-term stability in alkaline electrolyte and simulated seawater during multi-step chronopotentiometric testing at variable current densities from 20 mA cm⁻² to 100 mA cm⁻² for 18 h. This superior performance can be attributed to its unique intermetallic structure and multi-component composition, which provides good Cl⁻ resistance, electrochemical stability and synergistic effects among its constituents. Therefore, the optimized NiMnCo/Ti-2 electrocatalyst is a promising candidate for practical seawater electrolysis aiming at green hydrogen production. Full article

Against the dual backdrop of worsening air pollution and industrial intelligent transformation, industrial robot technology has become an important means to promote air pollution synergistic governance. This study innovatively incorporates public environmental satisfaction and industrial robot application as dynamic mechanism variables, constructing an evolutionary game model involving the government, industrial enterprises, and the public. Through theoretical analysis and numerical simulation, the study reveals the influence mechanism of key cost–benefit parameters on stakeholders’ strategic interaction and the system’s evolution path. The conclusions are as follows: (1) The government’s environmental supervision directly affects enterprises’ green transformation willingness, and enterprises’ behavior reversely impacts public satisfaction and supervision effectiveness, forming a “supervision–response–feedback” closed-loop. (2) The cost and benefit parameters related to industrial robots are crucial for the evolution of the game system, and there is significant heterogeneity in their impact on the strategic choices of the three parties. The robot adaptation transformation of enterprise industrial depends on the comprehensive consideration of the transformation cost and the green benefits. Public supervision is regulated by both the supervision cost and the incentive benefit. The government regulation takes into account both the regulatory cost and the loss of social reputation. Various parameters dynamically regulate the system’s equilibrium by altering the party’s cost–benefit structure. (3) The application of industrial robots and the feedback of public environmental satisfaction form a coupling effect, jointly determining the long-term evolution direction of the game system. When the cost benefit and supervision incentives are well-matched, enterprises will actively promote the green transformation of industrial robots in order to achieve intelligent pollution control. The effectiveness of public supervision has also been fully realized. The dynamic adaptation of the two components can lead the system towards an efficient and stable equilibrium in air pollution governance. Full article

Local antibiotic delivery has gained a central role as an adjunct to radical debridement in chronic osteomyelitis, allowing high antimicrobial concentrations at the infection site while reducing systemic toxicity. This narrative review summarizes the current clinical evidence on commercially available antibiotic-loadable bone substitutes, with particular focus on calcium sulfate (CaSO₄)-based systems and biphasic calcium sulfate/hydroxyapatite (CaS/HA) composites. Nineteen studies were included. Differences in formulation, resorption kinetics, antibiotic elution profile and osteoconductive behavior are discussed, alongside clinical outcomes including recurrence of infection, reoperation rates and complication patterns. Finally, based on the currently available evidence and expert recommendations, practical guidance is proposed to support carrier selection in different clinical scenarios (cavitary vs. corticomedullary defects; high-risk soft tissue; polymicrobial or resistant infections). Across published series, although heterogeneous, infection eradication rates are generally high when local carriers are integrated into structured surgical protocols. Calcium sulfate carriers provide rapid resorption and robust early antibiotic release but are associated with higher rates of sterile wound drainage. In contrast, CaS/HA biocomposites demonstrate more gradual remodeling and radiographic integration, potentially improving defect consolidation and reducing wound-related morbidity, although leakage and cost considerations remain relevant. Full article

Parallel robots are widely applied in many fields because of their unique advantages. To ensure their operational safety and reduce maintenance costs, designing an accurate and reliable fault diagnosis method is essential. Focusing on the 2RRU-RRS parallel robot, this paper proposes an intelligent fault diagnosis method based on a multi-scale convolutional residual network integrated with an Efficient Channel Attention mechanism (MS-ECA-ResNet). Firstly, to fully retain the time-frequency features of the signals, the one-dimensional vibration signals are converted into two-dimensional images using the Continuous Wavelet Transform (CWT). Secondly, a multi-scale convolutional feature extraction structure is designed to enhance the model’s feature extraction ability at different time scales. Furthermore, the ECA mechanism is introduced into the residual network to reinforce important feature channels and suppress noise interference. Comparative experiments, noise environment experiments, and ablation experiments were conducted on a 2RRU-RRS parallel robot experimental platform with a vibration signal dataset. The results demonstrate that the proposed method achieves superior diagnostic accuracy and robustness compared to typical deep learning models, particularly in maintaining high performance under simulated noise conditions. This provides a preliminary validation of the method’s effectiveness in capturing fault-related impacts, offering a potential technical reference for the health monitoring of parallel robots in real-world scenarios. Full article

High-speed operation is a key pathway to higher power density in modern EV traction systems, and multi-parameter optimization is essential for enhancing its high-speed performance. This study investigates a 20,000 r/min interior double-V permanent-magnet flat-wire motor via finite-element simulations to systematically examine the effects of multiple interacting parameters—including flat-wire layer number, stator slot geometry, magnet grade, and rotor magnetic barrier angle—on the electromagnetic performance under high-speed operating conditions. The results indicate that increasing winding layers significantly reduces high-speed torque; an eight-layer design decreases torque by about 50% compared to a four-layer one, while a six-layer arrangement offers a favorable torque-loss trade-off. Wider slots lower the average torque but reduce torque ripple by approximately 27%, whereas deeper slots increase tooth flux density and reduce efficiency. Higher-grade magnets enhance air-gap flux and torque at elevated cost. Rotor magnet angle optimization reveals a trade-off between peak torque and ripple, with a symmetric 100°/100° design achieving balanced performance. These findings clarify structural–control interactions and support the multi-objective design of high-speed flat-wire permanent-magnet motors. Full article

Ionizing radiation therapy has undergone a clear paradigm shift in veterinary oncology and inflammatory disease management, moving from mainly palliative use toward structured, curative treatment programs. This review synthesizes current evidence on key modalities used in veterinary practice, including external beam radiotherapy, brachytherapy, systemic targeted radionuclide therapy, stereotactic radiosurgery, stereotactic body radiotherapy, radiosynoviorthesis, and low-dose radiotherapy. Each modality is discussed in relation to its physical and biological basis, major isotopes or beam types, routes of delivery, target species such as dogs, cats, and horses, clinical indications, and global availability. Comparative analysis highlights differences in clinical acceptance, evidence strength, access, and cost. External beam radiotherapy and stereotactic techniques support curative tumor management, whereas radiosynoviorthesis and low-dose radiotherapy are effective for inflammatory and degenerative disorders. Despite ongoing progress, challenges remain in access, dosimetry standardization, and prospective evidence. Companion animals are also emphasized as valuable translational models, guiding future innovation and collaboration internationally. Full article

The cascaded H-bridge static synchronous compensator (STATCOM) has been widely employed in medium- and high-voltage reactive power compensation applications due to its high modularity, fast response speed, and direct grid connection capability. However, the DC-link voltage exhibits an inherent double-frequency ripple, which poses a serious challenge to power quality. Therefore, numerous Active Power Decoupling (APD) techniques have been proposed. However, existing schemes still exhibit certain limitations: independent APD topologies are associated with higher costs, whereas single bridge-arm multiplexed APD topologies are confronted with issues such as elevated DC-side voltage and increased current stress on the multiplexed arm. Consequently, comprehensive optimization is difficult to achieve in terms of the number of power devices, decoupling accuracy, level of capacitor multiplexing, and device stress. To address the above issues, this paper proposes a DC split capacitor (DC-SC)-based dual bridge-arm multiplexed cascaded H-bridge STATCOM with active power decoupling capability, along with its corresponding control method. By constructing a fundamental-frequency common-mode voltage on the decoupling capacitor, this method effectively suppresses the double-frequency ripple in the DC-side voltage and reduces the current stress on the switching devices. The simulation and experimental results have verified the correctness and effectiveness of the proposed topological structure and control method. Full article