Search Results (11,407)

This paper considers the critical role of local markets in sustaining rural communities and forests through the trade of Boswellia serrata Roxb. gum-resin as a culturally significant non-timber forest product (NTFP). Despite its cultural significance in Hindu rituals, little is known about the market dynamics at the consumer end of the value chain. This is one of the first detailed studies on consumer behavior and seller economics of B. serrata gum-resin in temple contexts. Open-ended surveys with sellers and consumers reflect seller activities, incomes, and consumer perceptions within the markets, providing insights into the dynamics of the gum-resin value chain and the implications for sustainability. Challenges gum-resin sellers face are brought to light, with a notable struggle to secure a significant portion of the final product’s value. Consumer perceptions are identified as a pivotal aspect influencing this NTFP’s market dynamics. The study emphasizes the importance of understanding consumer demand and preferences in shaping market size and sustainability practices. The research advocates for establishing structured markets to enhance returns for harvesters and reduce costs for consumers. In providing insights into the socio-economic aspects of temple markets for B. serrata gum-resin, this study contributes to the understanding of NTFP value chains and their broader impact on the sustainability of forest-dwelling communities and forest ecosystems. The findings underscore the need for informed interventions and policy measures to address challenges, promote equitable practices, and ensure the long-term viability of NTFP-based economies. Full article

Triathlon is a multi-sport event that combines swimming, cycling and running. The distances vary and the physiological demands are high. Objectives: This review compiles information on nutritional strategies and ergogenic supplements for triathlon training, competition and recovery. It aims to provide an understanding of the specific challenges and needs of the sport to help triathletes and coaches optimise performance through effective training and nutrition plans. Methods: English-language publications were searched using the keywords triathlon, nutrition, recovery and ergogenic aids, alone or in combination, in databases. Results: Maintaining good glycogen levels, consuming enough carbohydrates and staying properly hydrated are key to athletic performance, especially for triathletes. Education regarding nutrition, the role of probiotics and supplements, and diet modification for the enhancement of performance and recovery are pivotal considerations. Conclusions: Triathletes are at risk of RED-S due to negative energy balance and high fibre/plant protein diets, especially women. Optimising muscle glycogen through tailored diet and training, especially pre- and in-race nutrition, including carbohydrate loading and hydration strategies, is critical. Education is needed to improve post-exercise nutrition, while probiotics and certain supplements may aid performance and recovery. Dietary support is important for resistance training to optimise performance and recovery. Full article

Accelerated life tests are vital in reliability studies, especially as new technologies create highly reliable products to meet market demand and competition. Progressive stress accelerated life test (PSALT) allows continual stress adjustments. For reliability and survival analysis in accelerated life studies, generalized progressive hybrid censoring (GPHC) is very important. The research on GPHC in PSALT models is lacking despite its growing importance. Binomial elimination and generalized progressive hybrid censoring augment PSALT in this investigation. This research examines PSALT under the Generalized Kavya–Manoharan exponential distribution based on the GPHC scheme. Using gamma prior, maximum likelihood, and Bayesian techniques, estimate model parameters. Squared error and entropy loss functions yield Bayesian estimators using informational priors in simulation and non-informative priors in application. Various censoring schemes are calculated using Monte Carlo simulation. The methodology is demonstrated using two real-world accelerated life test data sets. Full article

Background: Cervical degenerative disease is a common condition associated with significant morbidity, often presenting as neck pain, radiculopathy, or myelopathy. Its growing incidence, particularly in the aging population, has led to an increased demand for surgical interventions aimed at relieving neural compression and restoring spinal stability. Objective: This study aims to evaluate surgical outcomes in patients with degenerative cervical conditions, with a particular focus on the role of intraoperative neurophysiological monitoring (IONM) in preventing adverse neurological events both immediately postoperatively and at long-term follow-up. Methods: A retrospective analysis was performed on patients who underwent cervical spine surgery for degenerative conditions between January 2021 and June 2024. Data collected included demographics, comorbidities, surgical details, and intraoperative neurophysiological monitoring. Surgical outcomes were assessed using the modified Rankin Scale (mRS), Odom’s Criteria, and the modified Japanese Association (mJOA) score. Results: Key findings demonstrated that advanced age and the presence of preoperative myelopathy were significantly associated with poorer postoperative outcomes across all evaluated measures. Conversely, factors such as gender, surgical approach, and the number of treated levels did not significantly influence recovery. Although intraoperative neurophysiological monitoring (IONM) did not show an immediate effect on postoperative outcomes, it was linked to prognostic value for long-term neurological status, suggesting a potential protective role in preserving neurological function. Conclusions: This study identifies age, preoperative functional status, and myelopathy as crucial predictors of postoperative recovery in cervical spine surgery for degenerative disease. These findings underscore the importance of early intervention in patients with myelopathy and highlight the complex role of IONM in improving long-term neurological outcomes. IONM changes may help identify patients at higher risk of poor recovery who could benefit from intensive postoperative rehabilitation. Further prospective studies are warranted to elucidate the complex interactions between patient characteristics and surgical factors in optimizing postoperative recovery. Full article

With the advancement of intelligent industrial equipment and the growing demand for system digitalization, parametric modeling of pump operational states has become increasingly important. This is especially true for large pumps, where real-time monitoring remains a major challenge. This paper proposes a pump characteristic curve prediction method based on transfer learning. By leveraging characteristic curve data from small, easily testable source domains for pre-training, the learned features are transferred as initial conditions for training performance models of other pump types. The test results show that neural network models pre-trained with transfer learning achieve faster prediction speeds and lower error rates. Transfer learning also demonstrates strong adaptability to characteristic curve data from various pump categories. Under varying volumes of target data, prediction accuracy improves significantly. Notably, when data are limited, the transfer learning approach achieves a prediction error of 5.2%, compared to 48.1% for direct deep learning modeling. Moreover, the proposed method effectively reduces prediction range beyond the scope of the original data. Full article

Given the growing global emphasis on inclusive education, it is critical to understand how diversity practices in schools influence middle school teachers’ job satisfaction and long-term retention. However, previous research has paid limited attention to cross-cultural differences and often overlooks how diversity-related demands interact with workplace resources. Grounded in the Job Demands–Resources (JD–R) framework, this comparative study conceptualizes perceived diversity practices as job demands that may place additional emotional and cognitive burdens on teachers, while teacher–student relationships are viewed as key social resources that can buffer these effects. Using data from the 2018 OECD Teaching and Learning International Survey (TALIS), we analyzed responses from over 6500 middle school teachers in the United States and China, employing regression analysis, Shapley value decomposition, and structural equation modeling (SEM) to examine direct and mediated pathways. The results reveal marked cultural variation: In the U.S., diversity practices as job demands are more likely to be associated with increased job satisfaction through direct institutional support—particularly for female and older teachers. In contrast, in China, the positive impact of diversity-related demands on job satisfaction is primarily achieved through strong teacher–student relationships, which serve as vital compensatory resources—especially for middle-aged educators. These findings underscore the importance of culturally responsive policy design; while individualistic educational systems may benefit from direct structural supports, collectivist systems may require relational strategies to foster sustainable teacher satisfaction and retention, ultimately advancing educational quality and equity. Full article

The Yellow River Basin in China is the region with the most severe agricultural non-point source pollution. The control of agricultural non-point source pollution is an important task for ecological protection and high-quality development in the Yellow River Basin at present and in the near future. This paper takes the eight provinces located along the Yellow River, except Sichuan, as the research object. This study estimates the total amount, intensity, and structure of agricultural non-point source pollution from 2014 to 2023 by adopting quantitative methods such as the pollutant discharge coefficient method, the equivalent pollution load method, and so on. The results reveal that the total amount of non-point source pollution of the Yellow River Basin has risen from approx. 4.94 million tons in 2014 to approx. 7.45 million tons in 2023. However, the growth rate has decelerated over the past five years, and the pollution intensity has decreased by 15~40% on average. The characteristics of agricultural non-point source pollution presents as follows: chemical oxygen demand (COD) emissions have become the most significant pollutant, accounting for 90% of the total pollution; livestock and poultry breeding has become the main source of pollution; and the key areas of pollution have shifted from the lower reaches to the middle and upper reaches, but the regional differences have been narrowing, as measured by the Gini coefficient. An analysis of the Kuznets curve indicates that most of the provinces in the Yellow River Basin still depend on an extensive growth model characterized by high input, high emission, and low output. Finally, this paper proposes a classified governance and measurement system for regions and sources, aiming to enhance the agricultural non-point source pollution prevention and control system. It also advocates for accelerating the green transformation of agricultural production in the Yellow River Basin to achieve the rapid decoupling of pollution emission from economic growth. Full article

The growing energy demand has emphasized the importance of developing nuclear technologies and high-purity lithium isotopes (⁶Li and ⁷Li) as raw materials. This study investigates how voltage and migration time affect two types of low-density polyethylene membranes—one impregnated with ionic liquids and the other non-impregnated—for lithium isotope separation via electromigration from a lithium-loaded organic phase to an aqueous solution. We developed a laboratory-made setup for high-precision lithium isotope measurements (2RSD = ±0.30‰) of natural carbonate samples (LSVEC) and an optimized protocol for isotope ratio measurements using quadrupole ICP-MS with the sample-standard bracketing method (SSB). The results document that both impregnated and non-impregnated membranes can achieve promising ⁶Li enrichment under different environmental conditions, including ionic liquids and organic solutions in the cathode chamber. Lithium-ion mobility is influenced by voltage in an environment assisted by 0.1 mol/L tetrabutylammonium perchlorate and increases quasi-linearly from 5 to 15 V. Between 20 and 25 h, the lithium-ion concentration had the maximum value, after which the trend declined. In the BayesGLM model, we incorporated all data and systematically eliminated those with a low enrichment factor, either individually or in groups. Our findings indicated that the model was not significantly affected by the exclusion of measurements with low α. This suggests that voltage and migration time are crucial, and achieving a better enrichment factor depends on applying the optimal ratio of ionic liquids, crown ethers, and organic solvents. Ionic liquids used for impregnation sustain enrichment in the first hours, particularly for ⁷Li; however, after 25 h, ⁶Li demonstrated a higher enrichment capacity. The maximum single-stage separation factor for ⁶Li/⁷Li was achieved at 24 and 48 h for an impregnated membrane M2 (α = 1.021/1.029) and a non-impregnated membrane M5 (α = 1.031/1.038). Full article

Assessing nitrogen (N) status in potato (Solanum tuberosum L.) during the growing season is crucial for optimizing fertilizer application, aligning it with crop demand, and improving N use efficiency, particularly in Western Canada, where extensive potato cultivation supports the agricultural industry. This study evaluated the performance of three machine learning (ML) models—Random Forest (RF), Support Vector Machine (SVM), and Gradient Boosting Regression (GBR)—for predicting potato N status and examined the impact of feature selection techniques, including Partial Least Squares Regression (PLSR), Boruta, and Recursive Feature Elimination (RFE). A field experiment was conducted in 2023 and 2024 near Carberry, Manitoba, Canada, with plots receiving different N rates from various fertilizer sources. Multispectral drone imagery was collected throughout the growing seasons, and key vegetation indices (VIs) related to plant N concentration were extracted for model training. Among the VIs, Cl green exhibited the highest correlation with petiole NO₃-N concentration (PNC). The results indicate that RF outperformed SVM and GBR, achieving the highest coefficient of determination (R² = 0.571) and the lowest mean absolute error (MAE = 0.365%) using the RFE feature selection method. Feature selection enhanced model performance in specific cases, notably RF with RFE, and both SVM and GBR with Boruta. These findings highlight the potential of ML-based approaches for in-season potato N monitoring and emphasize the importance of feature selection in enhancing predictive accuracy. Full article

The objective of this study is to explore the cold chain system in a metropolitan area, focusing on the overall system cost encompassing both distribution centers and transportation. The research delves into the planning of urban cold chain systems, considering fluctuating minimum customer demands, the traffic conditions of potential new centers, and the variability in carbon-trading prices. To manage the complexity of these objectives and inherent uncertainties, we introduce a flexible chance-constrained programming model for the cold chain system (FCCP-CCS). An FCCP-CCS programming model is developed to address the multifaceted goals and various uncertainties. The effectiveness of this model is validated through experimental analysis using real-world data from a major city’s cold chain system. The findings of this study reveal several key insights: (1) The levels of confidence and satisfaction significantly impact system optimization, with higher levels leading to increased consumption. (2) Customer demand variations would determine the transportation and the potential new centers in the system. (3) The surroundings of a distribution center partly indicate its service quality. (4) Governmental adjustments in carbon-trading prices can effectively enhance the overall sustainability of the urban cold chain system. This research highlights the importance of optimization in designing and managing urban cold chain systems, particularly in environmental sustainability. Full article

As the frequency of extreme events keeps increasing, large-scale power system interruption is also increasing. Natural disasters cause more extensive damage than typical power outages or failures, and the system demands a longer recovery period. Accordingly, it is crucial and urgent for the power system to have resilience in addition to possessing strong robustness and reliability. For the power system resilience, time is a critical factor. The microgrid (MG) can be connected to the main grid or operate independently to significantly improve the flexibility of the system with great potential in enhancing the power system resilience. We summarize the important concepts of power system resilience and MGs to improve power system resilience. Useful references are provided in this article for power-related practitioners regarding efficient design schemes to improve the application of MGs in enhancing resilience. Full article

Eggs are good sources of animal proteins. Methods for creating designer eggs are attractive to scientists and producers of the eggs, in order to fulfill customers’ demands. We review and summarize the current understanding of how genetic and environmental factors influence chicken egg components, specifically, amino acid contents of yolk and albumen. Genetically diverse breeds of chicken enable us to obtain a wide variety of egg amino acids. Moreover, the use of fermented feed and different rearing systems (barn and deep litter) has impacts on egg amino acids, which may be mediated through changes in the intestinal environment, including the microbiota. To overcome the future food crisis, the combinations of breeds, feeds, and rearing systems will be important for producing designer eggs. In the future, not only long-term selected layer strains will be required, but also many kinds of indigenous chicken breeds, which have already adapted to each local environment in the world, should be investigated under the continental levels of climate environment using different fermented feed materials. To better understand the interplay between genetic and environmental factors, we will offer valuable insights for both egg producers and consumers, potentially guiding future efforts to optimize egg amino acid contents in chickens. Full article

This study assesses the energy, economic, and environmental implications of switching Tanzania’s road transport sector to natural gas, which is slowly transitioning. In energy, the main goal is to identify the energy demand for petroleum fuel (diesel and petrol) and natural gas during the transition, while in the economy, the government revenue in the form of taxes for shifted and unshifted vehicles, as well as the loss in government revenue from petroleum fuel revenue post-transition, is assessed. In the environment, carbon emission in terms of carbon dioxide equivalent (CO_2e), carbon tax revenues, and carbon credit revenues post-transition is estimated. The shift involved 10, 20, and 30% of the road vehicle population. The 10, 20, and 30% shift targeted about 142,247, 183,893, and 225,540 vehicles, which in turn dropped diesel and petrol demand by 7 and 3.68%, 7 and 3.8%, and 15 and 7.5%, respectively. In natural gas, the demand started at 0.0916 billion kg and grew exponentially by 200% and later by 300%. The transition has consequences in government revenue, which takes the form of taxes on petroleum products. The shift from 10 to 30% could lead to foregone taxes amounting to Tanzania shilling TZS 0.09, 0.31, and 0.54 trillion (US$ 33,358,680, US$ 11,490,212, and US$ 20,015,208), indicating a tax loss of about 3, 9, and 15%. Contrary, the government may benefit from these losses by lowering the amount of foreign currency necessary for oil importation. In environmental benefits, the 10, 20, and 30% shift could offset approximately 8,959,198.92119, 8,438,863.65528, and 7,918,528.38937 tCO_2e, equivalent to 5.4, 10.97, and 16.47% of the road emissions. The post-transition road emissions might result in a carbon tax revenue of about US$ 71,673,591.37, 67,510,909.24, and 63,348,227.11 per year. The post-transition carbon credit revenue of about US$ 20,813,410.64, 41,626,821.27, and 62,440,231.91 is expected annually. The findings are critical for policy design and promoting a transition in the road transport sector. Full article

Natural gas consumption in Europe has undergone substantial changes in recent years, driven by geopolitical tensions, economic dynamics, and the continent’s ongoing transition towards cleaner energy sources. Furthermore, as noted in the International Energy Agency’s Gas Market Report 2025, natural gas demand is becoming increasingly sensitive to fluctuations in weather patterns, including cold snaps and heatwaves. These factors make the task of forecasting future annual consumption particularly challenging from a statistical perspective and underscore the importance of accurately quantifying the uncertainty surrounding predictions. In this paper, we propose a simple yet flexible approach to issuing dynamic probabilistic forecasts based on an additive time series model. To capture long-term trends, the model incorporates a deterministic component based on the Guseo–Guidolin innovation diffusion framework. In addition, a stochastic innovation term governed by an ARIMAX process is used to describe year-over-year fluctuations, helping to account for the potential presence of variance nonstationarity over time. The proposed methodology is applied to forecast future annual consumption in six key European countries: Austria, France, Germany, Italy, the Netherlands, and the United Kingdom. Full article

Energy-efficient and cost-effective water desalination systems can significantly replenish freshwater reserves without further stressing limited energy resources. Currently, the majority of the desalination systems are operated by non-renewable energy sources such as fossil fuel power plants. The viability of any desalination process depends primarily on the type and amount of energy it utilizes and on the product recovery. In recent years, membrane distillation (MD) and forward osmosis (FO) have drawn the attention of the scientific community because of FO’s low energy demand and the potential of MD operation with low-grade heat or a renewable source like geothermal, wind, or solar energy. Despite the numerous potential advantages of MD and FO, there are still some limitations that negatively affect their performance associated with the water–energy nexus. This critical review focuses on the hybrid forward osmosis–membrane distillation (FO-MD) processes, emphasizing energy demand and product quality. It starts with exploring the limitations of MD and FO as standalone processes and their performance. Based on this, the importance of combining these technologies into an FO-MD hybrid process and the resulting strengths of it will be demonstrated. The promising applications of this hybrid process and their advantages will be also explored. Furthermore, the performance of FO-MD processes will be compared with other hybrid processes like FO–nanofiltration (FO-NF) and FO–reverse osmosis (FO-RO). It will be outlined how the FO-MD hybrid process could outperform other hybrid processes when utilizing a low-grade heat source. In conclusion, it will be shown that the FO-MD hybrid process can offer a sustainable solution to address water scarcity and efficiently manage the water–energy nexus. Full article