bluuebunny/crossref_metadata_2025 huggingface dataset:
Polycrystalline Diamond Composite Bit Technology for Sustainable Work
Authors: Liu Xiaoao , Ji Guodong , Yang Liyuan , Ren Haitao , Wu Qiang , Yu Jinping , Huang Kuilin
Published: February 2025

Reducing the auxiliary drilling time and improving the drilling efficiency are not only important technical means to enhance the development and deep exploration of oil and gas reserves, but also have significant implications for ensuring energy security. Bottom hole self-renewal drill bit technology is a new technology that does not require the retrieval of drills from the well bottom, instead directly updating worn drill bits in place. Through the self-renewing structure of the drill bit, the sustainability of the drill bit can be increased. Conducting research on this technology is expected to overcome the technical issues related to the short useable life of drill bits, thus promoting single-trip drilling technology. This article summarizes the scientific progress made by researchers in self-renewal Polycrystalline Diamond Composite (PDC) drill bit technology; for example, the American National Oilwell Varco (NOV) company has developed a mobile self-renewal cone bit technology and introduced the structural characteristics and working principles of three types of rotating self-renewal drill bits: rack-driven, worm-driven, and ratchet-driven. This study compares and analyzes the advantages and disadvantages of these three rotary types of PDC drill bits, providing a detailed introduction to the working principles and modes of the triggering, transmission, limit and locking, and renewal structure devices of the drill bit. Relevant suggestions are proposed for the development of bottom hole self-renewal PDC drill bit technology; namely, strengthening research efforts relating to the intelligent judgment and recognition of cutting tooth wear of the drill bit, as well as the integration of multiple technologies. The sustainability of these novel bits can provide technical support for the development of single-trip drilling technology for deep formations, improve the service life of bits in deep formations that are difficult to drill, and contribute to the efficient development of deep-sea energy resources worldwide.
Disruptions, Challenges and Opportunities in the Provision of In-Person Psychological Therapy During the Era of COVID-19: A Review of the Literature
Authors: Parpottas Panagiotis
Published: February 2025

The outbreak of COVID-19 signaled an unprecedented era of unforeseen events which, among others, affected in-person psychological therapy (IPT). On the one hand, it could be argued that psychological therapy had the foundations to make the transition to remote delivery, but on the other, it was unclear what consequences the pandemic held for therapists and clients. This paper reviews the existing literature and explores the impact of the pandemic’s outbreak on IPT. Several studies suggest that IPT was abruptly interrupted, with a number of challenges observed in clients’ attendance, the transition to remote delivery and in the therapeutic process and relationship. Conversely, positive experiences and opportunities in the provision of therapy were reported too, such as convenience and flexibility in the process, improved accessibility and the continuation of therapy during the crisis. Finally, a number of studies report positive shifts in therapists’ attitudes towards remote delivery, while others highlight the importance of preparedness and previous experience. Following a review of the available studies and according to the pandemic’s trajectory, the current paper attempted to conceptualize findings in the revolving phases of regression, transition and adaptation, ultimately providing a starting point for further discussions and research in exploring the provision of psychological therapies in the future.
Spatiotemporal Changes of Vegetation Growth and Its Influencing Factors in the Huojitu Mining Area from 1999 to 2023 Based on kNDVI
Authors: Chen Zhichao , Cheng Yiqiang , Zhang Xufei , Zhu Zhenyao , Wang Shidong , Zhang Hebing , Zou Youfeng , Hao Chengyuan
Published: February 2025

Vegetation indices are important representatives of plant growth. Climate change and human activities seriously affect vegetation. This study focuses on the Huojitu mining area in the Shendong region, utilizing the kNDVI index calculated via the Google Earth Engine (GEE) cloud platform. The Mann–Kendall mutation test and linear regression analysis were employed to examine the spatiotemporal changes in vegetation growth over a 25-year period from 1999 to 2023. Through correlation analysis, geographic detector models, and land use map fusion, combined with climate, topography, soil, mining, and land use data, this study investigates the influencing factors of vegetation growth evolution. The key findings are as follows: (1) kNDVI is more suitable for analyzing vegetation growth in this study compared to NDVI. (2) Over the past 25 years, vegetation growth has exhibited an overall fluctuating upward trend, with an annual growth rate of 0.0041/a. The annual average kNDVI value in the mining area is 0.121. Specifically, kNDVI initially increased gradually, then rapidly increased, and subsequently declined rapidly. (3) Vegetation growth in the study area has significantly improved, with areas of improved vegetation accounting for 89.08% of the total mining area, while degraded areas account for 11.02%. (4) Precipitation and air temperature are the primary natural factors influencing vegetation growth fluctuations in the mining area, with precipitation being the dominant factor (r = 0.81, p < 0.01). The spatial heterogeneity of vegetation growth is influenced by land use, topography, soil nutrients, and mining activities, with land use having the greatest impact (q = 0.43). Major land use changes contribute 46.45% to vegetation improvement and 13.43% to vegetation degradation. The findings of this study provide a scientific basis for ecological planning and the development of the Huojitu mining area.
A Physical-Based Semi-Automatic Algorithm for Post-Tropical Cyclone Identification and Tracking in Australia
Authors: Deng Difei
Published: February 2025

Of all meteorological events, Tropical Cyclones (TCs) are by far the costliest of natural hazards around the globe. They typically lose their strength quite rapidly once making landfall. Recent studies have revealed that TCs, even degrading below TC strength after landfall, can survive for prolonged periods and still exert a significant impact as Post-Tropical Cyclones (PTCs). However, the widely used TC best track datasets, including the International Best Track Archive for Climate Stewardship, do not consistently track TCs for long enough following landfall to include complete PTC tracks. The absence of tracking limits our understanding of the overall TC-related impacts. In this study, we developed a semi-automatic tracking algorithm using satellite imagery and reanalysis data to extend TC tracks beyond the best track dataset until dissipation overland. Based on all landfalling TCs for the period 1990–2020 in Australia, these TCs can be further tracked overland for an additional 1.6 days on average, with a maximum of 15 days, since the last record in best track datasets. Although the intensity of Australian landfalling TCs has declined over the 30 years, they continue to linger over land for similar durations before dissipation, suggesting an increasing likelihood of favorable land conditions for TCs and PTCs.
Class-Incremental Semantic Segmentation for Mobile Laser Scanning Point Clouds Using Feature Representation Preservation and Loss Cross-Coupling
Authors: Chen Xucheng , Luo Haifeng , Huang Tianqiang , He Hanxian , Hu Wenyan
Published: February 2025

Significant progress has been made in the semantic segmentation of mobile laser scanning (MLS) point clouds based on deep learning. However, the segmentation classes of deep learning models depend on the label classes of the source point clouds used for training, which makes it difficult to generalize the models to target point clouds with novel classes. In addition, retraining models using complete class label datasets is time-consuming, and the source point clouds are often unavailable or occupy a large amount of storage space. In this paper, we propose a new class-incremental semantic segmentation framework for MLS point clouds. Firstly, to prevent catastrophic forgetting of original class knowledge when the model learns novel classes, we design a feature representation preservation-based knowledge distillation module to maintain the encoding ability of the target models for original classes. Then, to further separate novel classes from the original background classes, we introduce a background shift mechanism based on loss cross-coupling and pseudo-label collaborative training, which adaptively balances the model plasticity when learning novel class knowledge. Finally, we conducted extensive experiments on two benchmark datasets (Paris-Lille-3D and Toronto-3D), and our proposed method achieved impressive results, which indicate that the proposed framework could effectively achieve class-incremental semantic segmentation for MLS point clouds.
The Relationship Between Stature and Live Weight of Dairy Cows Between Birth and Maturity
Authors: Gibson Michaela J. , Sneddon Nick W. , Rogers Chris W. , Back Penny J. , Dittmer Keren E. , Martín Natalia P.
Published: February 2025

Lactational and reproductive performance are strongly associated with cow live weight and capacity. However, there are limited data published describing capacity (thoracic) growth and the prediction of final stature and capacity from measurements at birth. Therefore, the aim of this study was to examine the relationship between stature and live weight of female dairy cattle between birth and maturity. Forty dairy cows, with records of stature and capacity from birth up until two years of age, underwent follow-up measurements for live weight, height at withers, wither-rump length, girth circumference and leg length on four occasions between 42 and 52 months of age. Measures of wither height, leg length and wither rump length at fourth mating had the strongest association with measures at birth (R2 > 0.90) compared to girth and live weight (R2 = 0.88 and 0.82, respectively). The weaker association between birth and maturity measures for girth is likely a reflection of the stronger relationship with live weight resulting in a later maturity (approximately 810 days) compared to linear measures such as height (approximately 730 days). Therefore, to maximise capacity, adequate nutrition is required until approximately 810 days of age when capacity growth is most sensitive to environmental input.
Experimental Investigation of the Evaluation of the Cement Hydration Process in the Annular Space Using Distributed Fiber Optic Temperature Sensing
Authors: Li Zhong , Li Mengbo , Guo Huan , Wu Yi , Sheng Leixiang , Jiao Jingang , Li Zhenbo , Sui Weibo
Published: February 2025

This study employed a full-scale cement sheath quality evaluation apparatus, along with a high-precision distributed fiber optic temperature sensing system, to perform real-time, continuous monitoring of the temperature change throughout the cement hydration process. The results of the cement annulus and cement bond defect monitoring during the hydration process indicated that the distributed fiber optic temperature data enabled centimeter-level resolution in defect identification. Defective regions exhibited significantly reduced temperature fluctuation amplitudes, and an inversion in temperature change at the early hydration stage, detected at the cement–defect boundary, facilitated the early detection of defect locations. The distributed fiber optic system was capable of conducting continuous and comprehensive monitoring of the sequential hydration temperature peaks of cement stages injected into the annulus. The results revealed the interdependence among different cement stages, as well as a phenomenon whereby an elevated annular temperature accelerates the progression of cement hydration. The experimental findings provide a reference for identifying the characteristic signals in distributed fiber optic monitoring of well-cementing operations, thereby establishing a foundation for the optimal and effective use of distributed fiber optics in assessing well-cementing quality.
Work–Family Interference as a Mediator Between Job Characteristics and Employee Well-Being During COVID-19 in China: A Job Demands–Resources Model
Authors: Chen Nan , Tsai Chiungtzu Lucetta
Published: February 2025

The COVID-19 pandemic has fundamentally transformed workplace dynamics worldwide. Within this context, emerging patterns in job demand and job resources necessitate a thorough examination of how these workplace changes affect work–family interference and employee well-being across diverse occupational categories. The current study investigates the differential impact of job characteristics on job satisfaction and work stress during the COVID-19 pandemic, comparing blue-collar and white-collar occupations in China. Drawing from the Chinese General Social Survey (CGSS) database, we conducted a cross-sectional analysis using data from two time periods, 2015 and 2021, encompassing 10,968 and 8148 valid samples, respectively. Through bootstrapping analysis, we tested the indirect effects of job characteristics on employee well-being, mediated by work–family interference. The results reveal distinct patterns across occupational categories. Blue-collar workers demonstrated increased susceptibility to work-related stress, primarily due to the compounding effects of dual workload demands that intensified their work–family interference. Conversely, white-collar employees maintained a positive relationship between job autonomy and job satisfaction, despite the negative mediating influence of work–family interference.
Xanthan- and Gelatine-Based Composites Used as Nursery Groundcovers: Assessment of Soil Microbiology and Seedling Performance
Authors: Valentini Francesco , Sorze Alessandro , Coello Jaime , Ros Laura , Chowdhury Atif Aziz , Piergiacomo Federica , Casapiccola Giulia , Brusetti Lorenzo , Bösing Janine , Hirschmüller Sebastian , Dorigato Andrea
Published: February 2025

In light of the significant impact of climate change, it is imperative to identify effective solutions to promote afforestation and reforestation operations, which are often constrained by a low survival rate. To mitigate the impact of weed competition and enhance water availability, biodegradable groundcovers comprising xanthan gum and gelatine were developed and evaluated over the course of the growing season in a nursery setting on narrow-leaved ash (Fraxinus angustifolia) and alder (Alnus glutinosa) in 3.5 L pots. The results demonstrated a beneficial impact of all groundcovers, particularly the gelatine-based ones, on both the aboveground and belowground growth rates. The efficacy of weed competition was controlled using gelatine-based groundcovers in the case of ash trees. Furthermore, the gelatine-based groundcover altered the soil physiochemical characteristics and affected the bacterial community while maintaining its role in increasing the soil nitrogen pool. In contrast, the xanthan gum-based groundcover was demonstrated to enhance microbial richness and diversity, with an augmented contribution to the soil nitrogen pool. However, further trials with diverse tree species and soil conditions are necessary to gain a more comprehensive understanding of these effects.
Developing a Sustainable Traffic Management Framework Using Machine Learning Models for Fuel Consumption Minimization at Closely Spaced Intersections
Authors: Politi Ruti R. , Tanyel Serhan
Published: February 2025

Closely spaced intersections can be specified as special types of intersections with short-distance characteristics that are generally located in urban areas. This study aimed to develop a sustainable transportation framework of machine learning algorithms to predict and minimize fuel consumption as a measure of environmental impact at closely spaced intersections. In the theoretical framework, this study incorporates key traffic parameters such as left-turn-lane length, cycle time, distance between intersections, left-turn movement ratio, and traffic volume fluctuations to model fuel consumption. In this context, different scenarios were modeled and compared with SIDRA Intersection (version 6.1), which is a well-known traffic analysis and intersection modeling software, by using partial least square regression (PLSR), polynomial support vector machine (PSVM), and artificial neural network (ANN) models to conduct a comparative analysis of their applicability. The results demonstrated that the ANN model best captured fuel consumption variations across different key influencing factors. Among all models, cycle time showed the highest sensitivity, highlighting its critical impact; the optimization of left-turn-lane length and cycle time is performed using Particle Swarm Optimization (PSO) to minimize the impact of left-turns on fuel consumption. These enhancements promote more efficient and environmentally friendly traffic management. The integration of the predictive and optimized PSO-ANN model establishes a foundation for optimizing intersection performance. The findings indicate that an overall improvement of 8.9% in fuel consumption is achieved by evaluating the optimized parameters under varying traffic volumes. The proposed framework supports sustainable signalized intersection management by improving fuel efficiency and reducing environmental impact.
Unveiling Regional Disparities in Unemployment: A Spatial Econometric Study of Spain
Authors: Cojocaru Ruxandra Maria , Bolboașă Maria Bianca , Agafiței Marina-Diana , Copcă Narcis , Grosu Florin Stelian
Published: February 2025

This present work investigates the spatial distribution of the unemployment rate in Spain, one of the European countries with the highest recorded level of unemployment. The unemployment rate reached 16% during the pandemic. For this purpose, data from 2020 were used, such as the growth rate of the number of companies and entrepreneurs, the percentage of the workforce employed in the industrial sector, and the percentage of young people aged 16–25 years. All of these data were collected at the provincial level. The importance of spatiality in unemployment estimation is proven using regressions estimated in Geoda and GeodaSpace. The results support the introduction of the lag factor in regressions, improving the performance of the OLS model. However, the use of error models was found to be inefficient. Moreover, creating local estimates of coefficients can effectively adapt to the unique spatial characteristics of Spanish provinces. The research focuses on the sustainability challenges linked to regional inequalities in unemployment. It argues that these inequalities disrupt the balanced distribution of economic activities and hinder the achievement of long-term sustainable development across Spain’s regions. Resolving these inequalities is crucial for promoting regional competitiveness and overall economic growth.
Monitoring Eco-Efficiency and Its Convergence Towards Sustainability in the European Rubber and Plastics Industry Through Circular Economy Transition
Authors: Halkos George E. , Moll de Alba Jaime , Aslanidis Panagiotis-Stavros C. , Bampatsou Christina
Published: February 2025

Eco-efficiency is crucial for the European rubber and plastics industry to minimize production costs through effective resource management (e.g., energy management) and reduce environmental impacts like greenhouse gases (GHGs) emissions. Circular economy (CE) solutions can support the industry’s competitiveness while aligning with sustainability goals and regulatory requirements. In the present research, we employ a hybrid window data envelopment analysis (WDEA) methodology to measure panel data eco-efficiency via the application of the moving average principle. The examination of 27 European countries as decision-making units (DMUs), in the period 2014–2022, led to the conclusion that the average eco-efficiency is 70.33%, showing that most of the DMUs can ameliorate their performance regarding pollution control. The highest eco-efficiency in 2014 can be monitored in Ireland, Switzerland, Norway, and Poland, but in 2022, only Ireland and Switzerland kept their positions, whereas Norway dropped to the 16th position and Poland plummeted to the 24th hierarchical position. Geographical disparities can be spotted, as Northern and Western Europe have greater eco-efficiency than Eastern and Southern Europe. At a second level of analysis, the convergence between the 27 European countries in the period under consideration is examined using the log t regression test and club clustering. The analysis leads to three final clubs where conditional convergence dominates.
Spatiotemporal Analysis, Predictive Modeling, and Driving Mechanism Investigation of Carbon Storage Dynamics in Changde City Under the Framework of LUCC
Authors: Luo Ziyi , Chen Caihong , She Jiyun , Wang Yamin , Tong Wenfu , Guo Zexin
Published: February 2025

In the context of the worldwide attention on climate change, examining how land use relates to the carbon sink functions of regions is essential. This research innovatively utilizes the 2000–2020 land use data of Changde City, integrating the PLUS and InVEST models to analyze spatiotemporal changes and predict scenarios. It also combines the parameter geodetector and multiscale geographically weighted regression model to dissect driving factor distributions and mechanisms, capture interactions and multiscale impacts, uncover underlying laws, pioneer new paths for similar studies, and support regional ecological sustainability. The results show that from 2000–2020, forest and arable land areas declined while construction land expanded, leading to a yij1,172,200-ton carbon storage reduction in Changde City. Carbon storage decreased under natural development and arable land protection scenarios but increased in the ecological scenario. The main drivers of carbon storage in Changde City are the DEM, slope, and annual average temperature, with their interactions enhancing spatial heterogeneity. Human activities, especially in mountains and urbanizing regions, negatively impact carbon storage. This study aids in optimizing land resource allocation, improving land use efficiency, and promoting coordinated and sustainable development in Changde City’s ecological, economic, and social systems.
Advancing Sustainable Energy: Environmental and Economic Assessment of Plastic Waste Gasification for Syngas and Electricity Generation Using Life Cycle Modeling
Authors: Javed Muhammad Hassan , Ahmad Anees , Rehan Mohammad , Musharavati Farayi , Nizami Abdul-Sattar , Khan Mohammad Ilyas
Published: February 2025

The explosion of plastic waste generation, approaching 400 million tons per year, has created a worldwide environmental crisis that conventional waste management systems cannot handle. This problem can be solved through gasification, which converts nonrecyclable plastics to syngas with potential applications in electricity generation and synthetic fuel production. This study investigates whether syngas production from plastic waste by gasification is environmentally and economically feasible. Environmental impacts were assessed through a life cycle assessment framework using a life cycle impact assessment approach, ReCiPe 2016, with 10 midpoint/endpoint categories. Midpoint results of the baseline scenario with grid-mix electricity revealed climate change (GWP) of 775 kg CO2 equivalent and fossil depletion potential (FDP) of 311 kg oil equivalent per ton of plastic waste. Meanwhile, a solar scenario showed GWP as 435 kg CO2 equivalent and FDP as 166 kg oil equivalent per ton of plastic waste. Switching to solar energy cut GWP 44% and FDP 47%, respectively. However, the tradeoffs were higher human toxicity potential (HTP) and marine ecotoxicity potential (METP) due to upstream material extraction of renewable systems, respectively. Among environmental performance drivers, electricity inputs and operating materials were identified through sensitivity and uncertainty analyses. Syngas production from a plant of 50 tons per day can yield electricity sales revenue of USD 4.79 million, excluding USD 4.05 million in operational expenditures. Financial indicators like a 2.06-year payback period, USD 5.32 million net present value over a 20-year project life, and 38.2% internal rate of return indicate the profitability of the system. An external cost analysis showed emissions-related costs of USD 26.43 per ton of plastic waste processed, dominated by CO2 and NOx emissions. Despite these costs, the avoided impacts of less landfilling/incineration and electricity generation support gasification. Gasification should be promoted as a subsidy and incentive by policymakers for wider adoption and integration into municipal waste management systems. Findings show it can be adapted to global sustainability goals and circular economy principles while delivering strong economic returns. The study findings also contribute to several Sustainable Development Goals (SDGs), for instance, SDG 7 by promoting clean energy technologies, SDG 12 by implementing circular economy, and SDG 13 by reducing greenhouse gas (GHG) emissions.
Restoration of Ecological Connectivity in Zhaotong City Under the Interference of Human Activities
Authors: Wen Bo , Liu Chenxi , Cai Jingchao , Guo Jing , Ren Guoping
Published: February 2025

Plateau ecological vulnerability areas are experiencing substantial ecological challenges that threaten the integrity of ecological networks (ENs) due to irrational human activities, leading to habitat fragmentation and ecological connectivity degradation. The objectives of this study focus on understanding the structure, connectivity, and responses of ENs to construction land, crucial for maintaining ecological sustainability. Employing the circuit theory, the Minimum Cumulative Resistance (MCR) model, and complex network analysis methods, the ENs are constructed and the evolution characteristics are analyzed. The Geographically Weighted Regression (GWR) model is used to explore the correlation between construction land and ecological pinch points. The number of ecological corridors increased by 42, and the total length was reduced by 432.85 km, for a reduction of 15.25%. The proportion of highest-level ecological pinch points declined from 0.95% to 0.67%, indicating enhanced overall connectivity. Complex network analysis showed declining betweenness centrality in eight ecological sources over two periods, indicating reduced connectivity in partial northern and central regions. Correlation analysis showed the interaction of regional economic development policies and regional ecological restoration measures on the ecological networks. In areas with positive correlations, six ecological conservation areas were designated to maintain existing connectivity. In regions with negative correlations, seven ecological restoration areas were planned to improve ecological connectivity through scientific ecological restoration methods. This research provides a framework for optimizing regional ecological networks and enhancing ecological connectivity in plateau ecological vulnerability areas. It offers significant insights into the optimization of the ecological security pattern and practical guidance for policymakers and planners seeking to maintain ecological sustainability and resilience.
Changes in Farm Production in the Context of Overinvestment: A Case Study from Poland
Authors: Zmyślona Jagoda , Sadowski Arkadiusz , Kurzawa Izabela
Published: February 2025

Investments are the development core of every economic operator and the driving force for national economic development. While finding the optimal investment point is extremely difficult, every operator may seek to attain a level of fixed assets which allows them to maintain an increase in production and keep their income flowing. The difficulties in finding this optimum may lead to overinvestment. Hence, this paper estimates the parameters of the production function at various investment levels. Its purpose is to identify the relationship between the investment levels, the use of productive inputs, and growth or decline in production (output) levels. This study used microdata for 3273 Polish farms, as retrieved from the FADN (Farm Accountancy Data Network). The differences found at various farm investment levels allow for highlighting some problematic areas, e.g., in the context of excessive capital use relative to yearly increments in production values. The proposed method of analyzing overinvestment based on the production function can be extended to other countries. According to this paper, farms that invested too little or too much in relation to their production potential showed the worst economic performances, including the greatest declines in production.
Frictional Pressure Loss Prediction in Symmetrical Pipes During Drilling Using Soft Computing Algorithms
Authors: Agwu Okorie Ekwe , Wee Sia Chee , Akpabio Moses Gideon
Published: February 2025

One of the significant challenges during wellbore drilling is accurately predicting frictional pressure losses in symmetrical drill pipes. In this work, a Bayesian regularized neural network (BRANN) and multivariate adaptive regression splines (MARS) are employed to develop accurate and interpretable models for predicting frictional pressure losses during drilling. Utilizing data of frictional pressure loss collected through experimentation, the models are created. The model inputs include mud flow rate, mud density, pipe diameter (inside and outside diameters), and viscometer dial readings, while pressure loss is the output. Statistical comparisons between the model predictions and the actual values demonstrate the models’ ability to reasonably forecast frictional pressure losses in wells. The performance of the models, as measured by error metrics, is as follows: BRANN (0.999, 0.076, 16.76, and 11.67) and MARS (0.998, 0.0989, 21.32, and 16.499) with respect to the coefficient of determination, average absolute percentage error, root mean square error, and mean absolute error, respectively. Additionally, a parametric importance study reveals that, among the input variables, internal and external pipe diameters are the top predictors, with a relevancy factor of −0.784 for each, followed by the mud flow rate, with a relevancy factor of 0.553. The trend analysis further confirms the physical validity of the proposed models. The explicit nature of the models, together with their physical validation through trend analysis and interpretability via a sensitivity analysis, adds to the novelty of this study. The precise and robust estimations provided by the models make them valuable virtual tools for the development of drilling hydraulics simulators for frictional pressure loss estimations in the field.
Measles Vaccination Coverage and Anti-Measles Herd Immunity Levels in the World and WHO Regions Worsened from 2019 to 2023
Authors: Plans-Rubió Pedro
Published: February 2025

Objectives: The objectives of this study were as follows: to determine mean percentages of measles vaccination coverage with zero, one and two doses of vaccine and anti-measles herd immunity levels in World Health Organization (WHO) regions in 2023; to assess variations in measles vaccination coverage and anti-measles herd immunity-related indicators from 2019 to 2023; and to assess whether zero-dose measles vaccination coverage indicators were on track to achieve the Immunization Agenda 2030 objective. Methods: Mean percentages of vaccination coverage with two, one and zero doses of measles vaccine in WHO regions in 2023 were calculated using data from the WHO/UNICEF global and regional immunization information system. Results: In 2023, the global mean two-dose measles vaccination coverage was 65.3%, and mean two-dose vaccination coverage was lower than 95% in all WHO regions; the mean prevalence of measles-protected individuals in the target vaccination population was 87.6%, and anti-measles herd immunity levels in the target vaccination population were sufficient to block the transmission of measles viruses with greater transmissibility (Ro ≥ 15) only in the Western Pacific and European WHO regions. The global mean two-dose measles vaccination coverage decreased by 3.7% from 2019 to 2023. In 2023, the mean zero-dose measles coverage and number of zero-dose measles children were, respectively, 36.7% and 40.6% greater than the values required to be on track to achieve the 2030 objective. Conclusion: This study found that all measles-vaccination-coverage-related indicators worsened from 2019 to 2023, and the zero-dose measles vaccination coverage and number of zero-dose measles children in 2023 were not on track to achieve the AI2030 objective. Interventions to increase routine two-dose measles vaccination coverage should be developed in all WHO regions.
Aflatoxin B1-Induced Apoptosis in Donkey Kidney via EndoG-Mediated Endoplasmic Reticulum Stress
Authors: Ji Yanfei , Zhang Yu , Si Wenxuan , Guo Jing , Liu Guiqin , Wang Changfa , Khan Muhammad Zahoor , Zhao Xia , Liu Wenqiang
Published: February 2025

Aflatoxin B1 (AFB1) is a prevalent environmental and forage contaminant that poses significant health risks to both humans and livestock due to its toxic effects on various organs and systems. Among its toxicological effects, nephrotoxicity is a hallmark of AFB1 exposure. However, the precise mechanisms underlying AFB1-induced kidney damage in donkeys remain poorly understood. To investigate this, we established a donkey model exposed to AFB1 by administering a diet supplemented with 1 mg AFB1/kg for 30 days. Kidney apoptosis was assessed using TUNEL staining, while gene expression and protein levels of Endonuclease G (EndoG), as well as genes related to endoplasmic reticulum (ER) stress and apoptosis, were quantified by RT-qPCR and Western blotting. Our findings indicate that AFB1 exposure resulted in significant kidney injury, apoptosis, and oxidative stress. Notably, AFB1 exposure upregulated the expression of EndoG and promoted its translocation to the ER, which subsequently induced ER stress and activated the mitochondrial apoptotic pathway. These results suggest that AFB1-induced kidney damage in donkeys is mediated through the oxidative stress and mitochondrial apoptosis pathways, primarily involving the EndoG-IRE1/ATF6-CHOP signaling axis.
A Community-Led Assessment to Identify Groundwater-Dependent Lakes in Parkland County (Alberta, Canada)
Authors: Smerdon Brian , Maccagno Jenna Bahija Tarrabain , Peter Bradley , Neilson Walter , Mussell Dave , Trew David
Published: February 2025

Responding to a growing concern about impacts from anthropogenic activity on several dozen lakes, a group of citizens initiated and led a water quality sampling program that included characterizing groundwater dependence. The small lakes are located on hummocky glacial terrain near Edmonton, Alberta, Canada. A team of volunteers collected lake samples for a variety of limnological and ecological analyses to document lake health and trophic state, and collaborated with a university research group to identify groundwater dependence using specific environmental tracers (δ2H, δ18O, and 222Rn). Water chemistry and isotopic measurements are largely explained by the position of a lake within the local groundwater flow system. A simple metric to express the likelihood of groundwater dependence was calculated using the total dissolved solids (TDS), δ18O, and 222Rn values. Across the relatively small study area, a greater likelihood of groundwater dependence was determined for lakes located downgradient from an elevated recharge area. In contrast, where the water table was relatively flat, a lower likelihood of groundwater dependence was found. These results were similar to the spatial pattern of a trophic state, indicating that groundwater dependence may be one of the factors responsible for lake ecological status. The data generated by citizens and the knowledge gained about the hydrology of this area will help discussions between landowners and decision makers on how to best manage land use in this diverse landscape.
Numerical Simulation and Optimization Study on the Flow Field Characteristics of a Double-Slot Spillway
Authors: Shuai Shijie , Zhang Yanxia , Yang Huixia , Wang Shun
Published: February 2025

To investigate the flow characteristics of a novel dual-slot overflow channel, a research approach integrating physical experiments and numerical simulations was adopted. A three-dimensional model of the overflow channel was developed, employing the RNG k-ε turbulence model and the VOF two-phase flow model to optimize the numerical simulation of the high-low dual-slot flow field. Physical experiments were conducted to verify and analyze the hydraulic characteristics of the high-low overflow channel, including the longitudinal water surface profile and flow patterns. The numerical simulation results aligned well with the physical model test results. By analyzing the flow field of the dual-slot counterflow spillway, the flow characteristics at both the spillway and outlet sections were identified. This study focused on the water surface profile along the spillway, the pressure distribution, and the counterflow characteristics of the protruding water tongue, and explored optimization strategies for the WES surface and spillway design. Physical model tests were conducted on the final optimized design, yielding good agreement between the theoretical predictions and experimental results, thereby confirming the feasibility of the energy dissipation methods for both high and low spillways. The research outcomes offer valuable references for related engineering applications.
Decarbonization of Long-Haul Heavy-Duty Truck Transport: Technologies, Life Cycle Emissions, and Costs
Authors: Syré Anne Magdalene , Göhlich Dietmar
Published: February 2025

Decarbonizing long-haul, heavy-duty transport in Europe focuses on battery-electric trucks with high-power chargers or electric road systems and fuel-cell-electric vehicles with hydrogen refueling stations. We present a comparative life cycle assessment and total cost of ownership analysis of these technologies for 20% of Germany’s heavy-duty, long-haul transport alongside internal combustion engine vehicles. The results show that fuel cell vehicles with on-site hydrogen have the highest life cycle emissions (65 Mt CO2e), followed by internal combustion engine vehicles (55 Mt CO2e). Battery-electric vehicles using electric road systems achieve the lowest emissions (21 Mt CO2e) and the lowest costs (EUR 45 billion). In contrast, fuel cell vehicles with on-site hydrogen have the highest costs (EUR 69 billion). Operational costs dominate total expenses, making them a compelling target for subsidies. The choice between battery and fuel cell technologies depends on the ratio of vehicles to infrastructure, transport performance, and range. Fuel cell trucks are better suited for remote areas due to their longer range, while integrating electric road systems with high-power charging could offer synergies. Recent advancements in battery and fuel cell durability further highlight the potential of both technologies in heavy-duty transport. This study provides insights for policymakers and industry stakeholders in the shift towards sustainable transport. The greenhouse gas emission savings from adopting battery-electric trucks are 54% in our high-power charging scenario and 62% in the electric road system scenario in comparison to the reference scenario with diesel trucks.
Charting the Path to Electrification: Analyzing the Economic and Technological Potential of Advanced Vehicle Powertrains
Authors: Islam Ehsan Sabri , Vijayagopal Ram , Rousseau Aymeric
Published: February 2025

The U.S. Department of Energy’s Vehicle Technologies Office (DOE-VTO) is driving advancements in highway transportation by targeting energy efficiency, environmental sustainability, and cost reductions. This study investigates the fuel economy potential and cost implications of advanced powertrain technologies using comprehensive system simulations. Leveraging tools such as Autonomie and TechScape, developed by Argonne National Laboratory, this study evaluates multiple timeframes (2023–2050) and powertrain types, including conventional internal combustion engines, hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs). Simulations conducted across standard regulatory driving cycles provide detailed insights into fuel economy improvements, cost trajectories, and total cost of ownership. The findings highlight key innovations in battery energy density, lightweighting, and powertrain optimization, demonstrating the growing viability of BEVs and their projected economic competitiveness with conventional vehicles by 2050. This work delivers actionable insights for policymakers and industry stakeholders, underscoring the transformative potential of vehicle electrification in achieving sustainable transportation goals.
Comparative Analysis of Neural Network Models for Predicting Battery Pack Safety in Frontal Collisions
Authors: Wang Jun , Chen Ouyang , Zhan Zhenfei , Zhao Zhiwei , Bao Huanhuan
Published: February 2025

Amid concerns about environmental degradation and the consumption of non-renewable energy, the development of electric vehicles (EVs) has accelerated, with increasing focus on safety. On the road, battery packs are exposed to potential risks from unforeseen objects that may collide with or scratch the system, which may lead to damage or even explosions, thus endangering the safety of transportation participants. In this study, several predictive models aimed at assessing the safety performances of battery packs are proposed to provide a basis for data-driven structural optimization by numerically simulating the deformation of the battery base plate. Initially, a finite element model of the battery pack was developed, and the accuracy of the model was verified by performing modal analysis with various commercial software tools. Then, representative samples were collected using optimal Latin hypercube sampling, followed by collision simulations to gather data under different collision conditions. Next, the prediction accuracy of three models—PSO-BP neural network, RIME-BP neural network, and RBF neural network—was compared for predicting battery pack bottom shell deformation. Finally, the prediction accuracy of the models was compared based on error functions. The results indicate that these neural network models can accurately predict deformation under frontal collision conditions within the specified limits, with the RIME-BP model yielding the best performance beyond those limits. The developed neural network prediction model is able to accurately assess the mechanical response of battery packs under frontal collision, providing support for data-driven structural optimization. It also provides an important reference for improving the safety and durability of battery pack design.
Oligopeptides and the process of lipid peroxidation: molecular mechanisms of interaction
Authors:   Federal State Budgetary Educational Institution of Higher Education «Tyumen State Medical University», Boldyreva Yu.V
Published: February 2025

As a result of numerous studies, the role of free radical reactions was postulated,
the development of which was associated with the possibility of oxidative modification of the
primary structure of the most important biomolecules and their macromolecular complexes.
It was found that oxidation of lipids of biological membranes leads to disorganization of the
bilayer of biological membranes, disruption of the integrity and death of cells. Along with
the lipids of biological membranes, DNA molecules were also considered as a target for the
action of free radicals, primarily hydroxyl radicals, formed in large quantities from water
molecules during radiation exposure of humans and animals. It was shown that changes in
the structure of nucleic acids can lead to mutations, disturbances in the native structure of
proteins, enzymes, which excludes the performance of their biological functions. It was also
found that during the oxidation of proteins, disturbances in the tertiary and quaternary structure accumulated, leading to «cross-linking» of macromolecules, complicating proteolytic processes.
Foreigners and the labor market
Authors:   St Petersburg, Skachkova G.S.
Published: February 2025

The article discusses issues related to attracting foreign labor to Russia. Some features of the personnel policy of the Russian state are shown, taking into account the changing demographic situation in the country, attention is drawn to new requirements in the legislation of the Russian Federation — both for foreigners when they formalize
employment relations in Russia and for employers who employ them. There are also innovations in the Administrative Code of the Russian Federation in cases of violations of the legislation of the Russian Federation in attracting foreigners to work in Russia.
On the issue of the economic and legal content of the minimum wage
Authors:   Ural State University named after V. I. Yakovlev, Yekaterinburg, Kuchina Ju.A.
Published: February 2025

With the principle of respect for human labor enshrined in the Constitution of the Russian Federation, the minimum wage proclaimed as a state guarantee is becoming the main indicator of the implementation of one of Russia’s national development goals — improving human well-being. The author analyzes the minimum wage as an economic
and legal category, emphasizes the role of the Constitutional Court of the Russian Federation in filling this state guarantee of remuneration with essential characteristics in the absence of an appropriate legislative definition.
Improvement of statistical monitoring of personal subsidiary farms
Authors:   Russian State Agrarian University — Moscow Timiryazev Agricultural Academy, Institute of Economics and Management of Agroindustrial Complex, Moscow, Russia, Ukolova A. V. , Kozlov K. A. ,   Russian State Agrarian University — Moscow Timiryazev Agricultural Academy, Institute of Economics and Management of Agroindustrial Complex, Moscow, Russia
Published: February 2025

The article presents proposals to supplement the cost indicators of the
agricultural census program for large personal subsidiary farms of a commodity type.
In particular, it is proposed to add indicators characterizing the receipt of income from
the sale of own-made products, the receipt of credit and borrowed funds, as well as
expenses for agricultural activities. It is proposed to identify the category of personal
auxiliary workers to be examined under the expanded program based on the typology and criteria developed.