Search Results (152,045)

Objectives—This study aimed to investigate the factors contributing to increased absenteeism among nurses in primary healthcare institutions in Oman. Methods—A quantitative descriptive cross-sectional design included a structured written questionnaire that uses a quantitative self-repot technique was used. The study was conducted between January 2022 to November 2022 on a random selection of 300 nurses working in the primary and secondary healthcare institutions and regional hospitals in the Muscat governorate. Results—A total of 229 questionnaire were returned with a response rate of 76%. Almost 97% (222) participants were females, and 7 (3.1%) were males. Almost 51% of nurses were 25–34 years old. The respondents considered minor physical alignments, chronic medical conditions, and stress-related factors to be the predominant factors contributing to absenteeism among nurses. In addition, the coercive attitude of the leader, nurses whose performance was always criticized by the leader, and the nurse leader having inadequate support and guidance in performing patient care were considered important factors contributing to absenteeism. Conclusions—Nurses’ absenteeism is considered a threat to the quality of services provided for society at the primary healthcare level. The most common factors leading to increased absenteeism among nurses were found to be linked with demographic, leadership, and work characteristics. The most significant factors were considered to be within work characteristics, specifically the shortage of staff leading to workload, shift duties with limited flexibility, extra tasks, and absence of supportive policies. Additionally, leadership factors such as involvement, regular feedback, respect, and active listening to concerns were among the contributing factors to increased nursing absenteeism. Full article

The Altay Mountains’ forests are vital to Xinjiang’s terrestrial ecosystem, especially water regulation and conservation. This study evaluates vegetation evapotranspiration (ET) from 2000 to 2017 using temperature, precipitation, and ET data from the China Meteorological Data Sharing Service. The dataset underwent quality control and was interpolated using the inverse distance weighted (IDW) method. Correlation analysis and climate trend methodologies were applied to assess the impacts of temperature, precipitation, drought, and extreme weather events on ET. The results indicate that air temperature had a minimal effect on ET, with 68.34% of the region showing weak correlations (coefficients between −0.2 and 0.2). Conversely, precipitation exhibited a strong positive correlation with ET across 98.91% of the area. Drought analysis, using the standardized precipitation evapotranspiration index (SPEI) and the Temperature Vegetation Dryness Index (TVDI), showed that ET was significantly correlated with the SPEI in 96.47% of the region, while the TVDI displayed both positive and negative correlations. Extreme weather events also significantly influenced ET, with reductions in the Simple Daily Intensity Index (SDII), heavy precipitation days (R95p, R10), and increases in indicators like growing season length (GSL) and warm spell duration index (WSDI) leading to variations in ET. Based on the correlation coefficients and their significance, it was confirmed that the SII (precipitation intensity) and R95p (heavy precipitation) are the main factors causing vegetation ET increases. These findings offer crucial insights into the interactions between meteorological variables and ET, essential information for sustainable forest management, by highlighting the importance of optimizing water regulation strategies, such as adjusting species composition and forest density to enhance resilience against drought and extreme weather, thereby ensuring long-term forest health and productivity in response to climate change. Full article

With the launch of OpenAI’s ChatGPT, large language models have garnered significant attention, and applications based on these models have proliferated. A critical challenge has emerged: how to rapidly enhance the capabilities of general LLMs in specialized domains. Compared to fine-tuning and other methods, prompt engineering has proven to be a cost-effective approach for improving the performance of LLMs on specific tasks, yielding remarkable results. However, current prompt example construction methods are numerous and lack a universally applicable approach that spans different models and tasks. Furthermore, existing research is predominantly tested and evaluated on a limited range of specific datasets, failing to explore the broader impact of these methods on a wider array of tasks. This paper proposes a prompt example construction method based on clustering and semantic similarity, which combines clustering algorithms with semantic similarity techniques to significantly improve the quality of prompt examples. In comparative tests conducted on six LLMs and seven datasets, the overall accuracy and stability of the proposed method significantly outperforms five other common methods, demonstrating broad applicability and the potential to enhance the output performance of all LLMs. Through comparative experiments, this paper also identifies that as the parameter scale of LLMs increases, the improvement effect of the prompt example construction method on LLM output performance tends to diminish. Additionally, diversified prompt example sets provide a more pronounced enhancement in LLM output performance. Full article

Relaxation time and frequency spectra are not directly available by measurement. To determine them, an ill-posed inverse problem must be solved based on relaxation stress or oscillatory shear relaxation data. Therefore, the quality of spectra models has only been assessed indirectly by examining the fit of the experiment data to the relaxation modulus or dynamic moduli models. As the measures of data fitting, the mean sum of the moduli square errors were usually used, the minimization of which was an essential step of the identification algorithms. The aim of this paper was to determine a relaxation spectrum model that best approximates the real unknown spectrum in a direct manner. It was assumed that discrete-time noise-corrupted measurements of a relaxation modulus obtained in the stress relaxation experiment are available for identification. A modified relaxation frequency spectrum was defined as a quotient of the real relaxation spectrum and relaxation frequency and expanded into a series of linearly independent exponential functions that are known to constitute a basis of the space of square-integrable functions. The spectrum model, given by a finite series of these basis functions, was assumed. An integral-square error between the real unknown modified spectrum and the spectrum model was taken as a measure of the model quality. This index was proved to be expressed in terms of the measurable relaxation modulus at uniquely defined sampling instants. Next, an empirical identification index was introduced in which the values of the real relaxation modulus are replaced by their noisy measurements. The identification consists of determining the spectrum model that minimizes this empirical index. Tikhonov regularization was applied to guarantee model smoothness and noise robustness. A simple analytical formula was derived to calculate the optimal model parameters and expressed in terms of the singular value decomposition. A complete identification algorithm was developed. The analysis of the model smoothness and model accuracy for noisy measurements was carried out. The equivalence of the direct identification of the relaxation frequency and time spectra has been demonstrated when the time spectrum is modeled by a series of functions given by the product of the relaxation frequency and its exponential function. The direct identification concept can be applied to both viscoelastic fluids and solids; however, some limitations to its applicability have been pointed out. Numerical studies have shown that the proposed identification algorithm can be successfully used to identify Gaussian-like and Kohlrausch–Williams–Watt relaxation spectra. The applicability of this approach to determining other commonly used classes of relaxation spectra was also examined. Full article

This analysis investigates the performance and underlying dynamics of the Fama–French Five-Factor Model (FF5M) in the context of the COVID-19 pandemic, exploring its implications on the U.S. stock market across 30 industries. Our findings reveal marked shifts in the significance of factors. The SMB (size) gained in strength, while the HML (value) factor rose and fell in response to shifting flight-to-quality, liquidity, and inflation concerns. Both the RMW (profitability) and CMA (investment) factors saw a decline in their overall significance during the pandemic. Our results illustrate the oscillation of investor preferences from 2018 to 2023, capturing three distinct periods: pre-COVID-19, COVID-19, and post-COVID-19. Full article

Background/Objectives: The Mediterranean Diet (MD) is a lifestyle offering numerous health benefits. Nevertheless, the adherence to the MD is moderate even in Mediterranean countries. While sociodemographic factors influence MD adherence, additional impacts occurred due to the COVID-19 pandemic. This cross-sectional longitudinal study with three cohorts of Portuguese adults analyzes MD adherence before, during, and after the COVID-19 pandemic, and explores the effect of sociodemographic variables. Methods: Sociodemographic factors, lifestyle habits, and MD adherence were assessed in the years 2019, 2021, and 2024 with an online self-filled questionnaire. MD adherence was measured with the Mediterranean Diet Adherence Screener (MEDAS). Results: MEDAS score increased significantly (p < 0.05) from 2019 to 2021 (6.2 ± 0.7 to 7.7 ± 0.1), followed by a significant (p < 0.05) decrease in 2024 (7.2 ± 0.1) relative to 2019, which was more pronounced in participants with higher income. Accordingly, a trend in healthier food choices was observed followed by a decline in 2024. Of note is the significant increase in red meat consumption (p < 0.05) in 2024 relative to 2021. Respondents who consumed more red meat were mostly men, employed, or in a stable relationship. Most respondents practiced sport “Never or occasionally” in 2019 and 2021 (59.4 and 55.2%, respectively); in 2024, this category was significantly (p < 0.05) reduced (40.9%); men or higher-income participants were more likely to meet the recommended activity levels. Conclusions: This study reveals that the improvements in MD lifestyle during the pandemic were not sustained in 2024, as healthier habits formed during confinement were not fully integrated into long-term behavior. These findings strengthen the need for targeted public health interventions to promote the MD. Full article

The development of the oil industry and the fossil fuel economy has historically improved the quality of life for many people, but it has also led to significant environmental degradation. As a response, the concept of ‘sustainable development’ has gained prominence recently, emphasizing the importance of balancing economic progress with environmental protection. Among the many environmental challenges we face today, preserving water resources is one of the most pressing. To tackle this issue, researchers are focusing on strategies to reduce water consumption and enhance the efficiency of wastewater treatment. In this context, the present review explores recent advancements in a novel coupled treatment process that integrates adsorption in activated carbon fiber (ACF) and photocatalytic oxidation using TiO₂ to remove micropollutants from wastewater. This innovative approach would allow for the in situ and continuous regeneration of ACF with TiO₂ photocatalysis, increasing the oxidative degradation efficiencies of the supported semiconductor thanks to the adsorbent material, all under the possibility of a durable and low-cost process using solar radiation. In addition, this is vital for meeting regulatory standards, protecting aquatic ecosystems, and safeguarding human health. Full article

A green, low-carbon concrete is a top way to recycle waste in construction. This study uses industrial solid waste slag powder (S95) and fly ash (FA) as binders to completely replace cement. This study used recycled coarse aggregate (RCA) instead of natural coarse aggregate (NCA). This is to prepare alkali-activated recycled concrete (AARC) with different cementitious material systems. Alkali-activated concrete (AAC) mixtures are modified for strength and performance based on the mechanical qualities and durability of AARC. Also, the time-varying effects of the environment on AARC properties are explored. The results show that with the performance enhancement of RCA, the mechanical performance of AARC is significantly improved. As RCA’s quality improves, so does AARC’s compressive strength. At a cementitious material content of 550 kg/m³, AARC’s 28d compressive strengths using I-, II-, and III-class RCA were reduced by 2.2%, 12.7%, and 21.8%, respectively. I-class AARC has characteristics similar to natural aggregate concrete (NAC) in terms of shrinkage, resistance to chloride penetration, carbonization, and frost resistance. AARC is a new type of green building material that uses industrial solid waste to prepare alkali-activated cementitious materials. It can effectively reduce the amount of cement and alleviate energy consumption. This is conducive to the reuse of resources, environmental protection, and sustainable development. Full article

The flexible piezoelectric pressure sensor is essential in areas such as machine sensing and human activity monitoring. Here, 0-dimensional PZT piezoelectric ceramic nanoparticles with carbon coating were synthesized by a surface-modified technique. The excellent electrical conductivity of the carbon shell causes redistribution and accumulation of mobile charges in the carbon layer, resulting in a greatly increased piezoelectric effect by inducing an enhanced electric field. A series of organic–inorganic composite films were prepared by the spin-coating method using polydimethylsiloxane (PDMS) as the matrix. The as-fabricated flexible PZT@C/PDMS composite film with 40 wt% PZT@C powder exhibits an excellent output voltage of ~74 V, a peak of output current ~295 nA, as well as a big sensitivity of 5.26 V N⁻¹. Moreover, the composite film can be used as a pressure sensor to detect changes in force as well as for monitoring limb movements such as finger flexion, wrist flexion, and pedaling. This study reveals the promising applications of flexible 40%PZT@C/PDMS composite film for limb motion monitoring and pressure sensing. Full article

In this study, we have investigated the relationship between the plasma temperature in remote laser-induced breakdown spectroscopy (LIBS) experiments and the hydrophobic properties of silicone rubber insulators (SIRs). Contact angle and LIBS measurements were conducted on both artificially-aged (accelerated aging) and field-aged SIRs. This study reveals a clear connection between plasma temperature and the properties of aged SIRs on artificially-aged SIR specimens. Specifically, the plasma temperature exhibits a consistent increase with the duration of the accelerated aging test. The hydrophobicity of the artificially-aged SIRs was assessed by performing contact angle measurements, revealing a decrease in the hydrophobicity with increased aging test duration. Furthermore, we extended our investigation to the study of nine field-aged SIRs that had been in use on 150 kV overhead transmission lines for 0 to 21 years. We find that the laser absorption and hardness of the material do not relate to the plasma temperature. In summary, we observe a direct connection of plasma temperature to both contact-angle measurements and operation time of the in-service insulators. These results strongly suggest the potential use of LIBS for remotely evaluating the hydrophobicity and aging degree of silicone rubber insulators, thus assessing their real-time on-site operational quality. Full article

Fruit wine production is a practical approach for extending the shelf life and enhancing the value of strawberries (Fragaria × ananassa). Fruit cultivars and juices are important sources of volatile organic compounds (VOCs) that determine fruit wine sensory quality. In this study, VOCs in the juices and wines of four strawberry cultivars were identified using two-dimensional gas chromatography-time-of-flight mass spectrometry, and a sensory analysis of the wines was performed. A total of 1028 VOCs were detected. PCA and OPLS-DA distinguished the four cultivars from which the juices and wines were made. Six VOCs with variable importance in projection values greater than one were the main aroma and flavor components of strawberry wines. ZJ wine had the highest sensory scores for coordination (9.0) and overall evaluation (8.9) among the 18 descriptors of strawberry wine evaluated. Overall, the ZJ wine had the highest alcohol content (13.25 ± 0.59%, v/v) and sensory evaluation score, indicating that the ZJ cultivar is more suitable for fermentation. This study reflects the differences between wines made from four strawberry cultivars and provides a reference for brewing fruit wines. Full article

Psoriasis is an inflammatory skin disease with various symptoms of differing severities and with the reported prominent involvement of neutrophil extracellular traps (NETs). The excitation of neutrophils, e.g., by interleukin 8 (IL-8) or lipopolysaccharide (LPS), leads to the citrullination of histones and the release of protein–DNA complexes into the extracellular space, where they are digested by DNases. Our aim was to explore data on the levels of protein-complexed DNAs neutrophil elastase–DNA (NE-DNA) and myeloperoxidase–DNA (MPO-DNA), citrullinated histones (citH2, citH3, citH4), and NET-degrading enzyme DNase I in the serum of psoriatic patients with varying severities of clinical symptoms assessed with the Psoriasis Area Severity Index (PASI), Body Surface Area (BSA), and Dermatology Life Quality Index (DLQI) scores. The levels of factors were detected in 52 patients with psoriasis and 22 healthy volunteers by the enzyme-linked immunosorbent assay (ELISA). The results showed the elevated levels of NE-DNA, MPO-DNA, citH3, and DNase I in the patients with psoriasis compared to healthy volunteers (p < 0.05). Additionally, changes were noticed in the levels of NE-DNA, citH3, and DNase I, depending on the severity of symptoms (p < 0.05). In mild psoriasis (PASI < 10, BSA < 10, DLQI < 10), the suppressing activity of the enzyme caused the impaired ability to remove the physiological level of NETs, whereas in moderate to severe psoriasis (PASI ≥ 10, BSA ≥ 10, DLQI ≥ 10), the enhanced activity of DNase I failed to remove NETs due to the observed overexpression. It may, thus, be concluded that the mechanism of action of NETs, which play an undeniable role in psoriatic diseases, seem to follow two different paths depending on the severity of disease, which may be crucial in selecting potential anti-NET treatment methods. Full article

Ultra-high-strength steels have been considered an essential material for aviation components owing to their excellent mechanical properties and superior fatigue resistance. When machining these steels, severe tool wear frequently results in poor surface quality and low machining efficiency, which is intimately linked to the friction behavior at the tool–workpiece interface. To enhance the service life of tools, the adoption of efficient cooling methods is paramount. However, the understanding of friction behavior at the tool–workpiece interface under varying cooling conditions remains limited. In this work, both air atomization of cutting fluid (AACF) and ultrasonic atomization of cutting fluid (UACF) were employed, and their spray characteristic parameters, including droplet size distribution, droplet number density, and droplet velocity, were evaluated under different air pressures. Discontinuous sliding tests were conducted on the ultra-high-strength steel against cemented carbide and the effect of spray characteristic parameters on the adhesion friction coefficient was studied. The results reveal that ultrasonic atomization significantly improved the uniformity of droplet size distribution. An increase in air pressure resulted in an increase in both droplet number density and droplet velocity under both AACF and UACF conditions. Furthermore, the thickness of the liquid film was strongly dependent on the spray characteristic parameters. Additionally, UACF exhibited a reduction of 4.7% to 9.8% in adhesion friction coefficient compared to AACF. UACF provided the appropriate combination of spray characteristic parameters, causing an increased thickness of the liquid film, which subsequently exerted a positive impact on reducing the adhesion friction coefficient. Full article

Understanding the effects of bacteria and enzyme addition on mixed crop silage is imperative for dairy producers to make informed decisions. The current study evaluated the chemical changes in silage prepared from different ramie and elephant grass ratios (30:70, 50:50, 70:30, and 100:0) in response to bacteria (0, 100, 200, and 300 mg/kg) and enzyme addition (0, 10, 20, and 30 mg/kg) in a complete randomized design. The results indicated that the proportion of ramie in silage (p < 0.01), level of bacteria (p < 0.05), and level of enzyme added (p = 0.05) affected the CP, fiber, volatile fatty acids, and lactic acid contents and pH of silage. By comprehensive analysis, low lignin content and pH of silage with high lactic acid content was observed with a 30% ramie proportion. High CP and lactic acid contents with low ADF, lignin, and pH values were observed with the addition of bacteria (p < 0.05). High lactic acid with low ADF content was observed with the addition of enzyme in silage (p ≤ 0.05). The optimum quality of silage was observed when the ramie, bacteria, and enzymes were added at the levels of 30%, 200 mg/kg, and 20 mg/kg, respectively, in ramie and elephant grass mixed silage. Full article

Oilseed by-products (Cynara cardunculus and Camelina sativa) (CCCS) are rich in bioactive compounds. This study aimed to evaluate the health effects of consuming yogurt made from goat milk fed with CCCS industrial residues in adults. In this randomized, crossover clinical trial, 20 healthy adults (14F; 37.7 ± 14.2 years) consumed either yogurt made from goat milk fed with CCCS or regular goat yogurt (C) daily for 1 month in each phase. Anthropometric parameters and blood samples were collected at the beginning and end of each phase. CCCS yogurt consumption resulted in a significant fat mass reduction (−1.8% and −1.1 kg) and fat-free mass increase (+1.5% and +0.9 kg). Regarding blood parameters, a non-significant decrease in triglycerides, total cholesterol, and LDL cholesterol was observed, particularly after the CCCS intervention. Moreover, creatinine levels exhibited an opposite trend (p = 0.023) after CCCS, decreasing in subjects aged ≤30 years (−0.03 mg/dL) and increasing in older subjects (+0.05 mg/dL). Regarding inflammatory parameters, a non-significant trend in increased IL-1ra levels was observed especially after CCCS yogurt consumption compared to the C yogurt (+56.9 vs. +19.1 pg/mL, respectively). The use of unconventional feed derived from oilseed by-products for dairy goat feeding may have potential possible beneficial effects on human health. Full article