Search Results (21,237)

This study evaluates eight biodiesel blend types and determines the overall optimal blend by applying two established multi-criteria decision-making methods: the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The selected blends represent widely produced and utilized feedstocks that are reported in the previous literature. In the proposed methodology, AHP is employed to determine the weights for both emissions-related subcriteria, quantified through Global Warming Potential scores and property-related subcriteria, thereby reducing the subjectivity often encountered in earlier studies. Furthermore, two boundary alternatives, defined as the “Best” and “Worst” based on international standards, are introduced to enhance the robustness of the normalization procedure. The weights determined via AHP are subsequently integrated into the TOPSIS framework to rank the biodiesel alternatives. This combined AHP-TOPSIS approach addresses a gap in the literature, as no previous study has compared the best performing blends from different sources to identify a single optimal alternative. The results indicate that a 20% sunflower biodiesel blend (SN20) achieves the highest ranking. Sensitivity analyses, including the incorporation of an additional economic criterion, consistently reaffirm SN20’s superior performance. This study offers a transparent and reproducible method that can guide future biodiesel blend evaluations and reduce subjectivity in comparative assessment. Full article

Background: Dementia is a condition that affects the components of cognitive functions that are responsible for processing thought. There is no cure, but both pharmacological and non-pharmacological treatment helps to slow its progression. Presently, there is an increasing interest in non-pharmacological treatment, including cognitive stimulation, which aims to improve the person’s preserved abilities in order to slow down the progression of the disease while maintaining the current state for as long as possible. The aim of this systematic review is to analyse the effects of cognitive stimulation in older people with dementia. Methods: This systematic review was conducted in the Pubmed, OTSeeker, ScienceDirect, Dialnet, and Scopus databases. The inclusion criteria were controlled trials, randomised and non-randomised clinical trials, and pilot studies that applied cognitive stimulation to older people with dementia or compared this therapy with another type of non-pharmacological intervention. Results: Twenty-one studies were included in the review. Most of the articles showed that the intervention group achieved better cognitive performance than the control group after completing the cognitive stimulation intervention. Four of the studies assessed caregivers and, in two of the them, improvements in the caregiver’s relationship with the person with dementia were achieved and the caregivers also improved their health-related quality of life. Conclusions: According to the results, cognitive stimulation does influence older adults with dementia, especially on cognitive functions. The results also indicate that cognitive stimulation can be beneficial for the caregivers because this therapy has positive effects on their quality of life as related to both their health and their relationship with the person with the disease. However, more research is needed, especially regarding the quality of life of patients with the disease. Full article

This paper examines the relationship between weak orthogonality and almost orthogonality for complete non-algebraic 1-types in weakly ordered minimal theories. A central element of our approach is the concept of neighborhoods, which encapsulate local properties of type realizations. This work contributes to a deeper understanding of the geometry of types in weakly ordered minimal theories and provides tools that may be applied in related model-theoretic contexts. Full article

Background: Hydromorphone is a semi-synthetic opioid agonist and a hydrogenated ketone of morphine. This study examined hydromorphone use in the United States (US) using three databases. Methods: The distribution of hydromorphone in the US (in grams) was provided by the US Drug Enforcement Administration’s Automated Reports and Consolidated Orders System (ARCOS) by state, zip code, and business type (pharmacies, hospitals, providers, etc.). Hydromorphone prescription claims were also examined using the Medicaid and Medicare Part D programs from 2010 to 2023. Results: Hydromorphone increased by +30.6% by 2013, followed by a decrease of −55.9% by 2023 in ARCOS. Medicaid prescriptions increased by +39.6% by 2015 and decreased by −48.9% by 2023. Medicare Part D claims increased by +8.5% by 2015 and decreased by −31.9% by 2023. There were also pronounced regional disparities in hydromorphone use identified in ARCOS (158.7-fold), Medicaid (17.5-fold), and Medicare Part D (13.7-fold). Conclusions: Hydromorphone use in the US has decreased substantially from 2010 to 2023. Additionally, these findings highlight considerable regional disparities, which may inform targeted opioid stewardship initiatives and guide policymakers to ensure safe and equitable opioid prescribing practices. Full article

The monitoring and diagnostics of energy equipment aim to detect anomalies in time series data in order to support predictive maintenance and avoid unplanned shutdowns. Thus, the paper proposes a novel methodology that utilizes sequence-to-image transformation methods to feed Convolutional Neural Networks (CNNs) for diagnostic purposes. Multivariate time series taken from real gas turbines are transformed by using two methods. We study two CNN architectures, i.e., VGG-19 and SqueezeNet. The investigated anomaly is the spike fault. Spikes are implanted in field multivariate time series taken during normal operation of ten gas turbines and composed of twenty gas path measurements. Six fault scenarios are simulated. For each scenario, different combinations of fault parameters are considered. The main novel contribution of this study is the development of a comprehensive framework, which starts from time series transformation and ends up with a diagnostic response. The potential of CNNs for image recognition is applied to the gas path field measurements of a gas turbine. A hard-to-detect type of fault (i.e., random spikes of different magnitudes and frequencies of occurrence) was implanted in a seemingly real-world fashion. Since spike detection is highly challenging, the proposed framework has both scientific and industrial relevance. The extended and thorough analyses unequivocally prove that CNNs fed with images are remarkably more accurate than TCN models fed with raw time series data, with values higher than 93% if the number of implanted spikes is 10% of the total data and a gain in accuracy of up to 40% in the most realistic scenario. Full article

This work investigates the influence of chemical composition, grain boundary (GB) type, and atomic distribution on the thermal conductivity of Hf–Nb–Ta–Zr refractory high-entropy alloys (RHEAs) via atomistic simulations. Three compositions—equiatomic HfNbTaZr (M1), Hf₁₀Nb₄₀Ta₁₀Zr₄₀ (M2), and Hf₄₀Nb₁₀Ta₄₀Zr₁₀ (M3)—were studied in single-crystalline and bicrystalline models containing Σ3 or Σ5 GBs. The effect of chemical short-range order (SRO) and GB segregation was probed by comparing results for non-relaxed structures with those obtained for corresponding materials relaxed using combined Monte Carlo/molecular dynamics (MC/MD) simulation. Material relaxation is accompanied by the formation of coherent nanoclusters (NbTa in M1, Nb or Zr in M2, Hf or Ta in M3) and Hf/Zr segregation to GBs. In single crystals, SRO reduces thermal conductivity by up to ~2.7% (e.g., from 3.66 to 3.56 W/m·K in M1), which is explained by the phonon scattering effect from matrix–cluster interfaces, densely distributed in the structures. In contrast, in certain bicrystals, the combined effects of GB healing and intragranular cluster coarsening lead to a 6.9% increase in thermal conductivity (from 4.59 to 4.93 W/m·K), despite the presence of high-energy Σ5 GBs. These results demonstrate that the interplay between SRO, GB segregation, and microstructural evolution governs phonon transport in RHEAs, revealing a counterintuitive pathway to enhance thermal conductivity through controlled atomic redistribution. Full article

In recent years, there has been growing recognition that reducing environmental pollution, particularly from building emissions, is essential for improving residents’ well-being. Buildings contribute substantially to worldwide greenhouse gas and pollutant emissions, making effective mitigation strategies a priority in achieving Sustainable Development Goals (SDGs). Using data from the 2021 China General Social Survey (CGSS), this study examines the relationship between perceived building environmental pollution and residents’ well-being, as well as the mechanism underlying this relationship, through an ordered probit model. The results indicate that higher levels of building environmental pollution significantly reduce residents’ well-being. To explore heterogeneity, the sample was further divided by urban–rural differences, local environmental protection expenditure level, and geographic region. The research found that residents with lower environmental protection expenditures, residents in rural areas and those in the central region are more likely to be negatively affected by building environmental pollution, with the correlation coefficients being −0.111, −0.104 and −0.101 respectively. Furthermore, the analysis indicates that annual income, the number of children, and type of work have moderating effects on this relationship, with correlation coefficients of 0.047, −0.054, and −0.095 respectively. Overall, this study provides empirical evidence for perceiving the social impact of building pollution in the context of building-related emissions and offers policy-related insights for strengthening environmental protection measures in the construction industry to enhance residents’ well-being. Full article

Polycaprolactone (PCL) is one of the most widely used polymers in tissue engineering owing to its excellent biocompatibility, biodegradability, and processability. Nevertheless, most previous studies have primarily employed research-grade PCL, thereby limiting its clinical translation. In this study, four types of medical-grade PCL (RESOMER^® C203, C209, C212, and C217) were systematically evaluated for their applicability in three-dimensional (3D) printing, with respect to printability, mechanical characteristics, chemical stability, and biodegradation behavior. Among these, C209 and C212 exhibited superior printability and mechanical strength. FT-IR analysis showed that the chemical structure of PCL remained unchanged after both 3D printing and E-beam sterilization, while compressive testing demonstrated no significant differences in mechanical characteristics. In vitro degradation assessment revealed a time-dependent decrease in molecular weight. For kinetic analysis, both C209 and C212 were fitted using pseudo-first-order and pseudo-second-order models, which yielded comparable coefficients of determination (R²), suggesting that degradation may be governed by multiple factors rather than a single kinetic pathway. Taken together, these findings indicate that medical-grade PCL, particularly C209 and C212, is highly suitable for 3D printing. Furthermore, this study provides fundamental insights that may facilitate the clinical translation of PCL-based scaffolds for tissue engineering and biomedical implantation. Full article

The tail boom is a critical structural component of a helicopter, and accurately capturing its dynamic characteristics is essential; however, the inherent geometric and material complexity of the tail boom usually leads to large-scale finite element models whose system matrices are of very high order, and as the matrix order increases the computational effort grows exponentially. To further accelerate the condensation process for a truss-type tail-boom FE model, this paper presents a substructure-based secondary condensation method in which the global structure is partitioned into several substructures, each secondary substructure is first condensed onto its boundary nodes and then assembled into the primary structure, and the primary structure—now enriched with the condensed secondary substructures—is finally reduced to the target degrees of freedom, repeatedly operating on low-order matrices instead of a single high-order one to markedly shorten overall computation time. The proposed method is compared with both overall secondary IRS condensation and overall secondary SEREP condensation. All three secondary-condensation strategies yield six-degree-of-freedom coupled-spring equivalent models whose accuracy errors are very small in modal, frequency-domain, and time-domain analyses: frequency errors remain within 1%, and the goodness-of-fit of the time-history response curves exceeds 0.9, while the computational time is reduced by more than 70%, demonstrating that the substructure-based secondary condensation method is highly effective, delivering much higher computational efficiency without sacrificing accuracy. Full article

This paper investigated the tunnel slags generated from a specific tunnel project to systematically assess their environmental risk through phase composition, chemical composition, acidification potential, and heavy metal speciation. Leaching experiments were conducted under various influencing factors, including particle size, time, liquid-to-solid ratio, pH, temperature. The release concentration of heavy metals from the tunnel slag particles follows the following order: Zn > Cu > Cr. This is primarily attributed to the preferential release of Zn under acidic conditions due to its high acid-soluble state, while Cr, which is predominantly present in the residual state, exhibits very low mobility. Furthermore, decreased particle sizes, increased liquid-to-solid ratios, elevated leaching temperatures, extended leaching times, and lower pH values can effectively promote the dissolution of heavy metals from the tunnel slag. The cumulative leaching curves of Cr, Cu, and Zn from the three types of tunnel slags conform to the Elovich equation (R² > 0.88), indicating that the release process of heavy metals is primarily controlled by diffusion mechanisms. The S- and Fe/Mg-rich characteristics of D3 confers a high acidification risk, accompanied by a rapid and persistent heavy metal release rate. In contrast, D2, which is influenced by the neutralizing effect of carbonate dissolution, releases heavy metals at a steady rate, while D1, which is dominated by inert minerals like quartz and muscovite, exhibits the slowest release rate. It is recommended that waste management engineering prioritize controlling S- and Fe/Mg-rich tunnel slags (D3) and mitigating risks of elements like Zn and Cu under acidic conditions. This study provides a scientific basis and technical support for the environmentally safe disposal and resource utilization of tunnel slag. Full article

Recent trends in research on rotating machinery diagnosis focus on contactless diagnostic technologies. In this paper, novel higher order spectral technologies, based on spectral moduli, are proposed. The proposed technologies estimate statistical dependencies between moduli of harmonics of bearing defect frequencies. Moduli of harmonics of bearing defect frequencies, which appear due to bearing faults, are statistically dependent. The Third Order Modulus (TOM) is a novel higher order spectral signal processing technology developed for rotating machinery diagnostics. The paper presents mathematical expressions for new technologies as well as a detailed description of the signal processing algorithm of motor current for bearings diagnostics. The TOM technology is comprehensively validated via experimental trials for motor bearing diagnosis via motor current signature analysis. Results of experimental trials clearly show that the TOM technology is highly effective for diagnosis of bearing defects. Estimates of the total probabilities of correct diagnosis provided by the TOM technology are 100%. The TOM technology is experimentally compared with the classic bicoherence (CB) technology using eight bearings: four pristine bearings and four damaged bearings with two damage types. Comparison has shown that the TOM technology is more effective than the CB technology. Full article

Background/Objectives: Previous studies show that allocating carbohydrates earlier and vegetables/protein later in late-evening meals improves glycemic control in both healthy individuals and those with type 2 diabetes. However, evidence remains insufficient regarding the effects of distributing carbohydrate intake across the day by dividing three regular meals into five smaller meals. Methods: We conducted a randomized, controlled, crossover trial to compare the effects of two dietary patterns: (1) a conventional three-meal pattern with simultaneous intake of all food components, and (2) a five-meal pattern incorporating divided carbohydrate portions and a fixed food order—vegetables first, followed by protein, and then carbohydrates. Eighteen healthy young women consumed the same test meals under both patterns. Glucose fluctuations were monitored using an intermittently continuous glucose monitoring system. Results: The five-meal pattern with food sequencing significantly improved the mean amplitude of glycemic excursions (MAGE; 2.56 ± 0.13 vs. 3.49 ± 0.32 mmol/L, p < 0.01), glucose peak, and incremental area under the glucose curve for breakfast, lunch, and dinner, and the time above the target glucose range [>7.8 mmol/L; 1.4 ± 0.6 vs. 4.2 ± 1.0%, p < 0.01] compared to the three-meal pattern. Conclusions: These findings suggest that divided carbohydrate intake and food order ameliorates the MAGE in healthy young women. Full article

The quality risks of land trusteeship services are increasingly prominent, leading to reduced crop yields for farmers and land degradation; however, relevant research remains insufficient. This paper aims to identify and evaluate the quality risk level of land trusteeship services. It comprehensively adopts a field survey, web crawler technology, and expert consultation methods to identify quality risk types, and then uses the fuzzy comprehensive evaluation method to assess the risk level based on survey data from Chinese farmers. The main conclusions are as follows: (1) Overall, the quality risk level of land trusteeship services is at a relatively high risk level. In terms of spatio-temporal patterns, the quality risk level shows an upward trend, and the quality risk level of mid-production services is increasing at the fastest rate. There are significant variations in service quality risk across prefecture-level cities in the Shandong Province of China. (2) In terms of risk heterogeneity, the quality risk level of small-scale pure farmers is higher than that of part-time farmers and large professional farmers, in that order. The quality risk level of the “farmer + service organization” model is higher than that of the “farmer + intermediary + service organization” model. According to the order of the quality risk level of different crops, the ranking (from highest to lowest) is cash crops, wheat, and corn. (3) The high quality risks of land trusteeship services will impact the multifunctionality of land systems. It exacerbates the land pollution and fertility degradation because of excessive application of chemical inputs like pesticides, fertilizers, and mulch by service organizations. It consequently destroys ecological systems, hinders sustainable agricultural development, and impacts farmers’ income and national food security by reducing yields. The research findings contribute to controlling the quality risks of land trusteeship services and protecting land. Full article

Analyzing the characteristics of soil salinization and conducting risk assessments are crucial for ensuring the sustainable development of agriculture and ecosystems. In order to analyze the characteristics of soil salinization and conduct a risk assessment in the Yellow River Delta region, 63 surface soil samples and 37 groundwater samples were collected from this area in August 2023. Based on the test results of the samples and using soil salt content as the criterion, the types, degrees, and risks of soil salinization in the Yellow River Delta region were analyzed separately. The results revealed a relatively high average soil salt content of 4.59 g/kg, with Na⁺ and Cl⁻ as the dominant ions. The primary salinization types were chloride and sulfate-chloride, covering 46.69% and 51.54% of the area, respectively. Moderate salinization was the most widespread, accounting for 45.35% of the region. Severe salinization, extremely severe salinization classes were mainly found in the coastal lowlands of the north and east, constituting 19.73% and 16.25% of the area, respectively. Groundwater exhibited transitional freshwater-saltwater characteristics, indicating widespread seawater intrusion across the region, which significantly contributed to soil salinity. Proximity to the Bohai Sea was the most critical factor influencing salinization, with areas closer to the sea showing a higher risk. High-risk zones, primarily along the coastline, covered 32.67% of the total area. The research findings can serve as valuable references for local wetland management and protection, the scientific enhancement of saline soils, rational soil utilization, effective prevention and control of soil salinization, and the sustainable development of water and soil resources. Full article

The disease COVID-19, which has befallen mankind in recent years, was a challenge that we had not faced for centuries. The first registered patient case was in China. This review is performed by the inspection of a large body of worldwide investigations conducted in the peak period of the disease’s progress. The disease is spread by airborne droplets and develops mainly with fever, cough, sputum, and shortness of breath. Laboratory tests show leukopenia, lymphopenia, a decrease in the levels of sodium, potassium, and calcium, and an increase in the levels of CRP, LDH, and D-dimer. Radiological changes in most cases are bilateral and of the “ground glass” type in the lower parts of the lungs. The most severe complication of COVID-19 pneumonia is ARDS. The risk groups are people with chronic lung diseases, the elderly, and those who are overweight. This article analyzes and summarizes the main characteristics of SARS-CoV-2 pneumonia in order to better understand and apply better clinical management of this condition. Full article