bluuebunny/crossref_metadata_2025 huggingface dataset:
Nutrition, hydration and supplementation considerations for mountaineers in high-altitude conditions: a narrative review
Authors: Karpęcka-Gałka Ewa , Frączek Barbara
Published: November 2024

Staying and climbing in high mountains (>2,500 m) involves changes in diet due to poor access to fresh food, lack of appetite, food poisoning, environmental conditions and physiological changes. The purpose of this review is to summarize the current knowledge on the principles of nutrition, hydration and supplementation in high-altitude conditions and to propose practical recommendations/solutions based on scientific literature data. Databases such as Pubmed, Scopus, ScienceDirect and Google Scholar were searched to find studies published from 2000 to 2023 considering articles that were randomized, double-blind, placebo-controlled trials, narrative review articles, systematic reviews and meta-analyses. The manuscript provides recommendations for energy supply, dietary macronutrients and micronutrients, hydration, as well as supplementation recommendations and practical tips for mountaineers. In view of the difficulties of being in high mountains and practicing alpine climbing, as described in the review, it is important to increase athletes’ awareness of nutrition and supplementation in order to improve well-being, physical performance and increase the chance of achieving a mountain goal, and to provide the appropriate dietary care necessary to educate mountaineers and personalize recommendations to the needs of the individual.
Energy Drink Consumption Among Physically Active Polish Adolescents: Gender and Age-Specific Public Health Issue
Authors: Granda Dominika , Surała Olga , Malczewska-Lenczowska Jadwiga , Szczepańska Beata , Pastuszak Anna , Sarnecki Radosław
Published: November 2024

Objectives

To analyse the consumption of energy drinks (EDs) and the motives for their consumption among physically active adolescents in Poland.

Methods

A nationwide survey study was conducted in 1,530 adolescents (10–14 years old) participating in extracurricular, organised sports activities. A computer-assisted web interview method was applied.

Results

Nearly half (46.4%) of the respondents were ED consumers (significantly more boys than girls: 53.0% vs. 47.0%, p = 0.010). The percentage of ED consumers increased with age, from 27.2% in 10-year-olds to 65.4% in the group of 14-year-olds (p < 0.001). The motives and circumstances of ED consumption varied depending on gender: girls were more likely than boys to drink EDs to improve concentration during studying (17.1% vs. 8.8%, p < 0.001) and to stay awake (22.8% vs. 13.8%, p = 0.002), whereas boys more often than girls reported drinking EDs during physical activity (10.9% vs. 6.0%, p = 0.020).

Conclusion

It is necessary to implement gender-diversified educational campaigns on negative health effects of EDs, targeting children, parents and teachers, as consumption of EDs has been identified as a significant public health problem in Poland.
Values Are Not Taught, Values Are Built
Authors: Reyes-Sánchez Laura Bertha
Published: November 2024

Forming values to contribute to the complete formation of the human being as responsible citizens is an educational task that is indispensable to the construction of sustainability. Consequently, this document states that achieving a construction of values that leads to true development is not possible without a teaching and learning of science that, starting from an intersystemic and therefore complex vision of the world, allows us to build them. Answering the question How can interdisciplinary science teaching contribute to generating in today’s children a genuine interest in the study and knowledge of science in general, and in the conservation of natural resources in particular? Was the objective of the methodological proposal for interdisciplinary science teaching that was previously described in the article “Teaching soil science: a strategy and warranty towards the future” (Reyes-Sánchez, 2012). This second document addresses why, how and for what purpose the formation of values and principles accompanied this methodological proposal for interdisciplinary science teaching as a qualitative pedagogical approach that was applied within two schools with children in 5th and 6th grade of basic education −10 and 11 years of age-: by amalgamating the construction of knowledge with that of values to support the appropriation of both in a playful way, seeking and encouraging in children the congruence between knowledge, thought and action. The differences in children’s opinions regarding life problems that affect the social, political and economic order before and after the pedagogical intervention are presented in a comparative manner.
Analysis of Restrictions on Public Funding and Management of R&D Projects Arising from Legislation: The Case of the Spanish Context
Authors: Coca Pablo , García-Domínguez Amabel , Claver Juan
Published: November 2024

This article examines the challenges posed by national legislative frameworks in the European Union Member States regarding the management of publicly funded research and development (R&D) projects. Taking the case of Spain and its General Subsidies Act as an example, this study analyzes 55 R&D funding calls published by the Spanish Central Administration in 2021 and 2022. This research identifies key challenges associated with change management in these projects. This research performed a detailed review of relevant legislation and its application to R&D projects, alongside an analysis of regulatory bases making use of a flexibility index (FI) to assess the adaptability of grant conditions. Also, quantitative methodologies like Pearson’s correlation coefficient and principal component analysis were employed. The findings reveal that flexibility in project management, particularly concerning changes in scope, budget, and timeframes, is limited due to the rigidity of the legal framework. This lack of flexibility means a significant challenge for effective project execution, which inherently requires adaptability to manage uncertainty. This research suggests that future reforms should prioritize greater legal flexibility to improve the efficiency and success of publicly funded R&D initiatives. These findings contribute to the broader understanding of how regulatory constraints impact innovation management.
A Copula Function–Monte Carlo Method-Based Assessment of the Risk of Agricultural Water Demand in Xinjiang, China
Authors: Wang Xianli , Zhao Zhigang , Jie Feilong , Xu Jingjing , Li Sheng , Hao Kun , Peng Youliang
Published: November 2024

Agricultural water resources in Xinjiang, China, face significant supply and demand contradictions. Agricultural water demand risk is a key factor impacting water resource management. This study employs the copula function (CF) and Monte Carlo (MC) methods to evaluate agricultural water demand risk at 66 stations in Xinjiang. The evaluation is based on the marginal distributions of precipitation (PR) and reference evapotranspiration (RET). The findings classify Xinjiang’s precipitation–evapotranspiration relationship into three types: evapotranspiration, precipitation, and transition. Regions south of the Tianshan Mountains (TMs) primarily exhibit evapotranspiration characteristics. The Ili River Valley and areas north of the TMs display precipitation characteristics. Other areas north of the TMs have transitional characteristics. Both annual precipitation and RET in Xinjiang follow the Generalized Extreme Value (GEV) distribution. The Frank CF effectively describes the coupling relationship between precipitation and RET, revealing a negative correlation. This negative correlation is stronger north of the TMs and weaker to the south. The agricultural water demand risk in Xinjiang varies significantly across regions, with the precipitation–RET relationship being a crucial influencing factor. The demand index (DI) for agricultural water decreases as the risk probability (RP) increases. The stability of the DI is greatest in evapotranspiration-type regions, followed by transition-type, and weakest in precipitation-type regions. When the RP is constant, the DI decreases in the order of evapotranspiration, transition, and precipitation types. This study quantifies the spatial pattern of agricultural water demand risk in Xinjiang. The advantage of the CF–MC method lies in its ability to assess this risk without needing crop planting structures and its ability to evaluate spatial variations. However, it is less effective in areas with few meteorological stations or short monitoring periods. Future efforts should focus on accurately assessing water demand risk in data-deficient areas. The findings are crucial for guiding the regulation and efficient use of agricultural water resources in Xinjiang.
Fertilization with Olive Mill Pomace Compost Can Moderate Pest Damage in a Superintensive Olive Grove
Authors: González-Zamora José E. , Gamero-Monge José M. , Pérez-de la Luz Rosa
Published: November 2024

Olive cultivation is a key agricultural activity in Spain, primarily for producing oil. The extraction process of olive oil from the drupe yields a by-product known as ‘alperujo’, which can be composted and utilized as fertilizer. This research examines the impact of composted ‘alperujo’ on arthropod assemblages in the tree canopy, comparing it to mineral fertilization over the years 2021 and 2022. The study was conducted in two olive groves with different management systems (superintensive and traditional). Two types of sampling methods were used for the canopy: visual survey and sweep net. Under superintensive management, the presence and damage of Eriophyidae (Acari; Trombidiformes) in the shoots was significantly lower in the compost treatment in 2022 (20% of the shoots were occupied/damaged) compared to the mineral treatment (60% of the shoots were occupied/damaged). Araneae abundance was significantly higher (p = 0.033) in the compost treatment compared to the mineral treatment. However, under traditional management, no clear effect on arthropod assemblage was observed. In conclusion, the addition of compost to the superintensive grove helped to limit the presence of some arthropod pests compared to mineral treatment, contributing to a more sustainable crop. Grove type management appeared to play a significant role in the arthropod assemblages and effect of compost addition, but future research utilizing a greater number of groves (replicates) and an extended observation period should be performed to confirm these results.
Assessment of Sweet Sorghum Genotypes for Bioethanol Production Potential and Bagasse Combustion Characteristics in a Semi-Arid Mediterranean Climate
Authors: Nazli Recep Irfan , Aslankaciran Ceren , Yang Dongsheng , Liaqat Waqas , Polat Mihrab , Cavdar Asiye Sena , Tansi Veyis , Baloch Faheem Shehzad
Published: November 2024

The study aimed to evaluate the genetic diversity of 41 sweet sorghum genotypes from seven countries for key biofuel-related traits over two sorghum growing seasons (2020 and 2021) in a semi-arid Mediterranean environment. Genotypes were assessed for key bioethanol production traits such as fresh stalk yield (FSY), juice yield (JY), Brix, dry biomass yield (DBY), theoretical juice ethanol yield (JEY), theoretical lignocellulosic ethanol yield (LEY), theoretical total ethanol yield (TEY), as well as their potential for solid biofuel production, measured through bagasse ash, nitrogen, and moisture content. Significant variations were observed among genotypes across most traits, analyzed using analysis of variance, principal component analysis, and hierarchical cluster analysis, identifying DBY, LEY, and TEY as the primary contributors to overall genetic variation. Cluster analysis grouped the genotypes into five distinct clusters, highlighting the diversity in biofuel-related traits. The correlation analysis revealed significant positive relationships between traits such as FSY, DBY, and TEY, indicating that higher biomass production directly enhances ethanol output. Strong positive correlations between FSY and TEY underscore the importance of biomass yield in maximizing ethanol production. However, traits like bagasse ash and nitrogen contents, which were negatively correlated with JEY, LEY, and TEY, present challenges in improving biomass combustion quality. The study concludes that certain genotypes, particularly ‘Yellow Bonnet’ and ‘IS 3556’, exhibited strong potential for biofuel production in semi-arid Mediterranean climates where water scarcity and high temperature favor genotypes with high biomass and sugar yields. These genotypes demonstrated high JEYs, LEYs, and TEYs, suggesting their adaptability to the unique environmental stresses of this region, making them good candidates for sustainable biofuel production in similar climates.
Multi-View Fusion-Based Automated Full-Posture Cattle Body Size Measurement
Authors: Wu Zhihua , Zhang Jikai , Li Jie , Zhao Wentao
Published: November 2024

Cattle farming is an important part of the global livestock industry, and cattle body size is the key indicator of livestock growth. However, traditional manual methods for measuring body sizes are not only time-consuming and labor-intensive but also incur significant costs. Meanwhile, automatic measurement techniques are prone to being affected by environmental conditions and the standing postures of livestock. To overcome these challenges, this study proposes a multi-view fusion-driven automatic measurement system for full-attitude cattle body measurements. Outdoors in natural light, three Zed2 cameras were installed covering different views of the channel. Multiple images, including RGB images, depth images, and point clouds, were automatically acquired from multiple views using the YOLOv8n algorithm. The point clouds from different views undergo multiple denoising to become local point clouds of the cattle body. The local point clouds are coarsely and finely aligned to become a complete point cloud of the cattle body. After detecting the 2D key points on the RGB image created by the YOLOv8x-pose algorithm, the 2D key points are mapped onto the 3D cattle body by combining the internal parameters of the camera and the depth values of the corresponding pixels of the depth map. Based on the mapped 3D key points, the body sizes of cows in different poses are automatically measured, including height, length, abdominal circumference, and chest circumference. In addition, support vector machines and Bézier curves are employed to rectify the missing and deformed circumference body sizes caused by environmental effects. The automatic body measurement system measured the height, length, abdominal circumference, and chest circumference of 47 Huaxi Beef Cattle, a breed native to China, and compared the results with manual measurements. The average relative errors were 2.32%, 2.27%, 3.67%, and 5.22%, respectively, when compared with manual measurements, demonstrating the feasibility and accuracy of the system.
Ensiling as a Conservation Technique for Opuntia ficus indica (L.) By-Products: Peel and Pastazzo
Authors: Gannuscio Riccardo , Cardamone Cinzia , Vastolo Alessandro , Lucia Caterina , D’Amico Angela , Maniaci Giuseppe , Todaro Massimo
Published: November 2024

Italy is the third largest producer of Opuntia fruits in the world after Mexico and the United States, and 97.72% of these fruits produced by Italy are grown in Sicily. The use of prickly pear fruits or juice leads to a high production of by-products. In this study, ensiling was chosen to preserve prickly pear peels (PPPs) and “pastazzo” (PPS) mixed with 12% wheat bran. PPP silage presented a lower DM than PPS silage (20.03 vs. 41.37%; p < 0.01), as well as aNDFom (25.31 vs. 66.66% DM; p < 0.01), but had the best protein content (12.02 vs. 9.55% DM; p < 0.01). For both by-products, fermentation proceeded rapidly with increasing temperature, with the temperature for PPS (38 °C) being higher than that for the PPP (30 °C). Mesophilic LAB (lactic acid bacteria) were detected at higher levels than thermophilic LAB, and rod counts were higher than cocci counts. The detected organic acids and silage pH indicate an optimal fermentation process for these by-products. PPP silage had a higher polyphenol content than PPS silage (30.24 vs. 24.22 mg GAE/g DM; p < 0.01) and, consequently, also higher antioxidant activity. The results of this study on the mineral composition and macro- and micro-nutrients in silage highlight that these by-products are sources of minerals, with high levels of potassium, calcium, and magnesium.
Innovation and Utilization of Functional Feed Additives from Maize By-Products in Broiler Chickens
Authors: Srinual Orranee , Kanmanee Chanidapha , Srinual Phatchari , Chaiyaso Thanongsak , Yachai Mongkol , Tapingkae Tanya , Tapingkae Wanaporn
Published: November 2024

Supplementation with spent mushroom substrate (SMS) as an exogenous enzyme in broiler diets represents a promising nutritional strategy to enhance production efficiency and reduce costs. To assess the effects of SMS enzyme products on various parameters, including growth performance, blood chemistry, carcass and meat quality, and gut health, a study was conducted with one-day-old broilers (n = 500). The broilers were separated into five groups: a control diet (CON) and an antibiotic group (AGP) which were added to the diet at 0.25 g kg−1, and SMS from Flammulina velutipes supplementation groups which were added to the diet at 0.5 g kg−1 (SMS0.5), 1.0 g kg−1 (SMS1.0), and 2.0 g kg−1 (SMS2.0). Final body weight and average daily gain in broilers which were fed the AGP diet were higher than in broilers which were fed the CON, SMS0.5, and SMS1.0 diets. Broilers in the CON group had a decreased average daily feed intake compared to other groups. The addition of AGP and SMS2.0 diets improved the feed conversion ratio and reduced the feed cost per gain in broilers. Broilers that were fed the CON diet had the highest serum cholesterol, while the AGP diet increased triglyceride. Dietary supplementation of SMS improved some carcass characteristics and ceacum microbial content in broilers, especially with the SMS2.0 diet. Broiler fed CON and SMS0.5 worsened the villus height/crypt depth ratio of duodenum histology. In conclusion, SMS supplementation at 1.0 and 2.0 g kg−1 can improve productive performance and health in broiler diets; however, SMS2.0 had the best efficiency.
Artificial Light at Night Advances the Onset of Vocal Activity in Both Male and Female Great Tits During the Breeding Season, While Noise Pollution Has Less Impact and Only in Females
Authors: Foppen Kim , Pinxten Rianne , Meijdam Marjolein , Eens Marcel
Published: November 2024

Artificial light at night (ALAN) and noise pollution are two important stressors associated with urbanisation that can have a profound impact on animal behaviour and physiology, potentially disrupting biological rhythms. Although the influence of ALAN and noise pollution on daily activity patterns of songbirds has been clearly demonstrated, studies often focus on males, and the few that examined females have not included the potential influence of males on female activity patterns. Using free-living pairs of great tits (Parus major) as a model, we examined for the first time the effects of ALAN and noise pollution and their interaction on the onset of (vocal) activity in both members of a pair. We focused on the egg-laying phase, when both sexes are most vocally active. The onset of male dawn song, female emergence time from the nest box and the onset of female calling in the nest box were measured and used as a proxy for the chronotype. The repeatabilities for all chronotype proxies were high, with higher repeatabilities for males. Consistent with previous studies, ALAN advanced the onset of male dawn song, while it did not elicit a strong response in female emergence time. Additionally, our results suggest an indirect effect of ALAN on the onset of female vocal activity via acoustic interaction with the male. Noise pollution advanced the emergence time in females, while an interaction between ALAN and noise pollution was found for the onset of female calling. In agreement with previous studies, several covariables were shown to have an influence on the activity onset. Taking several proxies for chronotype into account, this study has provided robust evidence of effects of ALAN on male and female cavity-nesting songbirds during the egg-laying period.
Automatic Reconstruction of Reservoir Geological Bodies Based on Improved Conditioning Spectral Normalization Generative Adversarial Network
Authors: Wang Sixuan , Liu Gang , Weng Zhengping , Chen Qiyu , Xiong Junping , Cui Zhesi , Fang Hongfeng
Published: November 2024

For reservoir structural models with obvious nonstationary and heterogeneous characteristics, traditional geostatistical simulation methods tend to produce suboptimal results. Additionally, these methods are computationally resource-intensive in consecutive simulation processes. Thanks to the feature extraction capability of deep learning, the generative adversarial network-based method can overcome the limitations of geostatistical simulation and effectively portray the structural attributes of the reservoir models. However, the fixed receptive fields may restrict the extraction of local geospatial multiscale features, while the gradient anomalies and mode collapse during the training process can cause poor reconstruction. Moreover, the sparsely distributed conditioning data lead to possible noise and artifacts in the simulation results due to its weak constraint ability. Therefore, this paper proposes an improved conditioning spectral normalization generation adversarial network framework (CSNGAN-ASPP) to achieve efficient and automatic reconstruction of reservoir geological bodies under sparse hard data constraints. Specifically, CSNGAN-ASPP features an encoder-decoder type generator with an atrous spatial pyramid pooling (ASPP) structure, which effectively identifies and extracts multi-scale geological features. A spectral normalization strategy is integrated into the discriminator to enhance the network stability. Attention mechanisms are incorporated to focus on the critical features. In addition, a joint loss function is defined to optimize the network parameters and thereby ensure the realism and accuracy of the simulation results. Three types of reservoir model were introduced to validate the reconstruction performance of CSNGAN-ASPP. The results show that they not only accurately conform to conditioning data constraints but also closely match the reference model in terms of spatial variance, channel connectivity, and facies attribute distribution. For the trained CSNGAN-ASPP, multiple corresponding simulation results can be obtained quickly through inputting conditioning data, thus achieving efficient and automatic reservoir geological model reconstruction.
Transient Stability Control Strategy Based on Uncertainty Quantification for Disturbances in Hybrid Energy Storage Microgrids
Authors: Wang Ce , Lei Zhengling , Huo Haibo , Yao Guoquan
Published: November 2024

The transient stability control for disturbances in microgrids based on a lithium-ion battery–supercapacitor hybrid energy storage system (HESS) is a challenging problem, which not only involves needing to maintain stability under a dynamic load and changing external conditions but also involves dealing with the energy exchange between the battery and the supercapacitor, the dynamic change of the charging and discharging process and other factors. This paper focuses on the bus voltage control of HESS under load mutations and system uncertainty disturbances. A BP Neural Network-based Active Disturbance Rejection Controller (BP-ADRC) is proposed within the traditional voltage-current dual-loop control framework, leveraging uncertainty quantification. Firstly, system uncertainties are quantified using system-identification tools based on measurable information. Subsequently, an Extended State Observer (ESO) is designed to estimate the total system disturbance based on the quantified information. Thirdly, an adaptive BP Neural Network-based Active Disturbance Rejection Controller is studied to achieve transient stability control of disturbances. Robust controllers, PID controllers and second-order linear Active Disturbance Rejection Controllers are employed as benchmark strategies to design simulation experiments. Simulation results indicate that, compared to other benchmark strategies, the BP-ADRC controller based on uncertainty quantification exhibits superior tracking and disturbance-rejection performance in transient stability control within microgrids of hybrid energy storage systems.
Measurement Model of Full-Width Roughness Considering Longitudinal Profile Weighting
Authors: Luo Yingchao , An Huazhen , Li Xiaobing , Cao Jinjin , Miao Na , Wang Rui
Published: November 2024

This study proposes and establishes a roadway longitudinal profile weighting model and innovatively develops a process and method for evaluating road surface roughness. Initially, the Gaussian model is employed to accurately fit the distribution frequency of vehicle centerlines recorded in British Standard BS 5400-10, and a generalized lateral distribution model of wheel trajectories is further derived. Corresponding model parameters are suggested for different types of lanes in this study. Subsequently, based on the proposed distribution model, a longitudinal profile weighting model for lanes is constructed. After adjusting the elevation of the cross-section, the equivalent longitudinal elevation of the roadway is calculated. Furthermore, this study presents a new indicator and method for assessing the roughness of the entire road surface, which comprehensively considers the elevations of all longitudinal profiles within the lane. To validate the effectiveness of the proposed new method and indicator, a comparative test was conducted using a vehicle-mounted profiler and a three-dimensional measurement system. The experimental results demonstrate significant improvements in measurement repeatability and scientific rigor, offering a new perspective and evaluation strategy for road performance assessment.
Artificial Intelligence-Powered Recommender Systems for Promoting Healthy Habits and Active Aging: A Systematic Review
Authors: Lopez-Barreiro Juan , Garcia-Soidan Jose Luis , Alvarez-Sabucedo Luis , Santos-Gago Juan M.
Published: November 2024

(1) Background: Increasing life expectancy allows for more age-related health issues. Enhancing physical, cognitive, mental, and social health is crucial. Promoting healthy habits combats stress and diseases. Recommendation systems, like collaborative filtering, tailor suggestions but face challenges. Techniques such as artificial intelligence and machine learning are vital. Personalized health recommendations improve lifestyles and mitigate issues. (2) Methods: A systematic review adhering to the general principles of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses was conducted with the aim of identifying articles on innovative research about using recommendation algorithms, machine learning, or artificial intelligence to promote healthy habits and active aging. (3) Results: A total of 34 articles were included in this work. They address the topic of recommendation systems that use machine learning or artificial intelligence in the promotion of healthy habits. (4) Conclusions: This article reviews health-related activity recommendation techniques for the general population. With rising life expectancy and common health issues, effective recommendations are crucial for future public health. Limitations include excluding simpler models. Despite many proposals, systematic adherence mechanisms are lacking. Developing traceable, verifiable systems for healthy activity recommendations is vital for aging populations in developed countries.
Integrating Biofilm Growth and Degradation into a Model of Microplastic Transport in the Arctic Ocean
Authors: Golubeva Elena , Gradova Marina
Published: November 2024

The present study analyzes the potential propagation trajectories and fate of floating microplastic particles released on the Kara Sea shelf. The transport of microplastics is described using a Lagrangian model based on daily 2016–2020 data obtained from numerical modeling of Arctic Ocean dynamics. A particle biofouling model is used to simulate the submergence of floating microplastic particles in the water column. The model includes a parameterization of the processes of biofilm accumulation (via collision with algae in surrounding water, algae growth) and degradation (via respiration, mortality). The behavior of microplastic particles of different sizes (0.5 and 0.01 mm) during the sinking process and subsequent rising due to biofilm degradation is examined. The simulation results reveal that particles of 0.01 mm in size display a tendency to sink immediately during the process of biofouling. However, when the biofilm degraded, the particles exhibited a rising velocity, comparable to the current vertical velocity, and the particles remained submerged in the water for long periods. In contrast, the 0.5 mm particles remained at the surface for a longer period before sinking, accumulating biofilm. Subsequently, their behavior was oscillatory in response to changes in the biofilm, rising rapidly when the biofilm decayed and sinking rapidly again as a result of biomass accumulation. In winter, the 0.5 mm particles were mostly frozen into the ice. The phenomenon of biofouling, whereby microplastic particles of various sizes sink at different depths, results in considerable variation in the subsequent pathways of these particles in the Arctic Ocean.
Handwritten Signature Generation Using Denoising Diffusion Probabilistic Models with Auxiliary Classification Processes
Authors: Hong Dong-Jin , Chang Won-Du , Cha Eui-Young
Published: November 2024

Automatic signature verification has been widely studied for authentication purposes in real life, but limited data availability still poses a significant challenge. To address this issue, we propose a method with a denoising diffusion probabilistic model (DDPM) to generate artificial signatures that closely resemble authentic ones. In the proposed method, we modified the noise prediction process of the DDPM to allow the generation of signatures specific to certain classes. We also employed an auxiliary classification process to ensure that the generated signatures closely resemble the originals. The model was trained and evaluated using the CEDAR signature dataset, a widely used collection of offline handwritten signatures for signature verification research. The results indicate that the generated signatures exhibited a high similarity to the originals, with an average structural similarity index (SSIM) of 0.9806 and a root mean square error (RMSE) of 0.1819. Furthermore, when the generated signatures were added to the training data and the signature verification model was retrained and validated, the model achieved an accuracy of 94.87% on the test data, representing an improvement of 0.061 percentage points compared to training on only the original dataset. These results indicate that the generated signatures reflect the diversity that original signatures may exhibit and that the generated data can enhance the performance of verification systems. The proposed method introduces a novel approach to utilizing DDPM for signature data generation and demonstrates that the auxiliary classification process can reduce the likelihood of generated data being mistaken for forged signatures.
Numerical Methods Comparison of Shock-Induced Separation on Transonic Axisymmetric Hump
Authors: Zhang Miao , Tian Zhuoyue , Tang Songxiang , Wei Ziyan , Li Jie
Published: November 2024

A transonic hump with a Mach number (M∞) of 0.875 was utilized to compare the prediction capabilities of RANS, URANS, IDDES, and IDDES-SLA for shock-induced separation. The results matched the experimental data concerning pressure, friction coefficients, velocity distribution, and other parameters. The improved delayed detached eddy simulation with a modified sub-grid scale (IDDES-SLA) method performed the best amongst tested numerical methods, demonstrating differences of 1.3% and 4.1% from the experimental results for separation and reattachment locations, respectively. The primary difference between IDDES and IDDES-SLA is reflected in detailed data, such as velocity and high-frequency characteristics, although both methods exhibit similar simulation capabilities for the main structural features of the flow field. The POD and PSD analyses of the flow field results demonstrated that the IDDES-SLA method was more capable of resolving higher modes of flow field.
Application of Artificial Intelligence in Support of NAFLD Diagnosis
Authors: Płudowski Jakub , Mulawka Jan
Published: November 2024

A comprehensive system for automated medical data analysis and diagnosis of non-alcoholic fatty liver disease using artificial intelligence has been developed. The system consists of several modules: medical data aggregation, AI model training using advanced machine learning algorithms, Explainable AI generating reports, and patient diagnosis by ensemble model. Those models have achieved diagnostic accuracy higher than 95%, and the system is designed for continuous improvement by aggregating more data and automatically retraining models. It is a modern, flexible, and scalable tool designed to support medical diagnosis. It can make doctors’ work easier and faster, and the discovered biomarkers of a disease can increase the quality of its diagnosis. The ensemble model generating diagnoses achieved nearly perfect quality and, using explainable artificial intelligence, it was possible to determine attributes and their values that constitute non-alcoholic-fatty-liver-disease (NAFLD) biomarkers.
A Synchronous Tuning Control System for Very Low Frequency Communication Based on Real-Time Impedance Detection
Authors: Wei Shize , Xie Xu , Liu Yuqing , Zuo Hao
Published: November 2024

A Very Low Frequency (VLF) communication system is a communication system with limited transmit bandwidth, mainly because the VLF antenna is a high-Q electrically small antenna (ESA) with a narrow effective bandwidth, which limits the improvement of communication rate. To achieve broadband VLF communication, the commonly used method is synchronous tuning technology. In this paper, a synchronous control algorithm based on real-time impedance detection and a synchronous control system structure are proposed. Simulation results show that the method can improve the antenna matching performance, increase the effective bandwidth of the antenna feeder system, and improve the signaling rate.
A Review of Sustainability in Hot Asphalt Production: Greenhouse Gas Emissions and Energy Consumption
Authors: Liu Yancheng , Liu Zhengyi , Zhu Youwei , Zhang Haitao
Published: November 2024

This study conducted a thorough analysis of energy consumption and greenhouse gas (GHG) emissions in the production of hot mix asphalt. The primary sources of energy usage in asphalt mixes are the heating of aggregates, asphalt, and burners, with aggregate heating accounting for a remarkable 97% of the total energy consumption. The results indicate that low-temperature asphalt mixes offer significant benefits over conventional hot mix asphalt in terms of energy efficiency and GHG emissions, with reductions in carbon dioxide emissions ranging from 18% to 36% and energy savings between 15% and 87%. Additionally, the use of recycled asphalt pavement led to a 12% decrease in carbon dioxide emissions and a 15% reduction in energy consumption. The study further explored the effects of various fuel types on emissions, revealing that replacing fuel oil with natural gas can effectively diminish the carbon footprint of the production process. By optimizing production temperatures and selecting cleaner fuel alternatives, this research highlights the potential for considerable energy savings and emission reductions within the asphalt production sector. These strategies not only promote sustainable road construction practices but also play a vital role in environmental protection and climate change mitigation, advocating for the adoption of innovative technologies in asphalt pavement production.
A Hybrid JADE–Sine Cosine Approach for Advanced Metaheuristic Optimization
Authors: Ishtaiwi Abdelraouf , Al-Shamayleh Ahmad Sami , Fakhouri Hussam N.
Published: November 2024

This paper presents the development and application of the JADESCA optimization algorithm for solving complex engineering design problems, including the welded beam, pressure vessel, spring, and speed reducer design problems. JADESCA, a hybrid algorithm that combines elements of JADE (differential evolution with adaptive parameters) and the sine cosine algorithm (SCA), is evaluated against a range of benchmark functions from the CEC2022 competition as well as specific engineering problems. The algorithm’s performance is analyzed through convergence curves, search history diagrams, and statistical results. In engineering design problems, JADESCA consistently demonstrates superior performance by achieving optimal or near-optimal solutions with high precision and consistency. In particular, JADESCA outperforms 25 state-of-the-art optimizers over the CEC2022 benchmark functions, further proving its robustness and adaptability. Statistical comparisons and Wilcoxon rank-sum tests reinforce the superiority of JADESCA in achieving competitive results across various test cases, solidifying its effectiveness in handling complex, constrained optimization problems for engineering applications.
A Strong Noise Reduction Network for Seismic Records
Authors: Shen Tong , Jiang Xuan , Rong Wenzheng , Xu Lei , Tuo Xianguo , Peng Guili
Published: November 2024

Noise reduction is a critical step in seismic data processing. A novel strong noise reduction network is proposed in this study. The network enhances the U-Net architecture with an improved inception module and coordinate attention (CA) mechanism, suppressing noise and enhancing signal clarity. These enhancements improve the network’s capability to distinguish between signal and noise in the time–frequency domain. We trained and tested our model on the STEAD dataset, which eliminated noise across various frequency bands, improved the signal-to-noise ratio (SNR) of seismic records, and reduced the waveform distortion significantly. Comparative analyses against U-Net, DeepDenoiser, and DnRDB models, using signals with SNRs ranging from −14 dB to 0 dB, demonstrated our model’s superior performance. At the same time, we demonstrated that the Inception Conv Block has a significant impact on the denoising ability of the network. Furthermore, validation using the “Di Ting” dataset and real noisy signals confirmed the model’s generalizability. These results show that the proposed model significantly outperforms the comparative methods in terms of the SNR, correlation coefficient (r), and root mean square error (RMSE), delivering higher-quality seismograms. The enhanced phase-picking accuracy underscores the potential of our approach to advance in geophysics applications.
Effect of the Compounding Method on the Development of High-Performance Binary and Ternary Blends Based on PPE
Authors: López-Martínez Erika Ivonne , Zaragoza-Contreras Erasto Armando , Vega-Rios Alejandro , Flores-Gallardo Sergio Gabriel
Published: November 2024

The polymer blends are an effective strategy for materials design with new properties in the plastic industry; such features may depend on the blend components and the processing method. This study aimed to understand the effect of styrene-butadiene-styrene (SBS) content and its architecture on blends based on polyphenylene ether (PPE), high-impact polystyrene (HIPS), and SBS. In addition, this research compared and analyzed the blends formulated by different processing methods: twin-screw extrusion (TSE) and internal mixing (IM). Furthermore, three SBS copolymers, two radial and one linear (with different molecular weights), were used to produce PPE/HIPS/SBS blends, analyzing which SBS copolymer feature provides excellent viscoelasticity, thermomechanical properties, and impact resistance. The findings revealed that the melt processing method played a crucial role in Izod impact resistance of the PPE/HIPS/SBS blends, as well as the molecular architecture, molecular weight, and SBS content. The findings also demonstrated that the TSE process is more effective than the IM. Since the PPE/HIPS/SBS blends displayed higher Izod impact resistance than the PPE/HIPS or PPE/SBS binary blends, a synergistic effect of SBS and HIPS is suggested.
Impacts of Forecast Time and Verification Area Setting on the Targeted Observation of Typhoon
Authors: Kang Jiaqi , Guo Jianxia , Wang Jia , Zhang Chao
Published: November 2024

The results of the identification of sensitive areas are affected by the forecast time and verification area settings in targeted observations. Understanding this setting issue is important for improving the effectiveness of the identification of sensitive areas in real-time field campaigns. To determine this, a series of experiments were carried out based on the Ensemble Transform Sensitivity (ETS) method, and the results are as follows: (1) First, Observation System Simulation Experiments (OSSEs) were conducted to assimilate simulated dropsondes in sensitive areas (SENS) or non-sensitive areas (OTHR). The results showed that the SENS experiment improved forecasts of typhoon intensity, track, precipitation score, and RMSE of forecast elements. However, the OTHR experiment only improved the forecast in some aspects and even had negative effects on other aspects. This indicates that the sensitive areas identified by the ETS method are effective. (2) Different forecast time experiments were carried out. There were significant differences between the sensitive areas of fixed verification times and variable targeted observation times, indicating that the sensitive areas changed greatly with time. In the field campaign, it was necessary to calculate the sensitive area for multiple times in advance and to design or adjust the observation scheme according to the time. (3) Finally, comparative experiments of position deviation and size change in the verification area were carried out. It was found that for a big deviation, too large or too small a verification area will result in significant differences in the sensitive areas. Based on the study in this article, a verification area size of about 6° × 6° is recommended; this can not only accommodate the position deviation of the verification area from the typhoon center caused by forecast errors, but also does not contain too much noise unrelated to typhoons, which may affect the accuracy of identification of sensitive areas.
How Does Physical Activity Modulate Hormone Responses?
Authors: Mennitti Cristina , Farina Gabriele , Imperatore Antonio , De Fonzo Giulia , Gentile Alessandro , La Civita Evelina , Carbone Gianluigi , De Simone Rosa Redenta , Di Iorio Maria Rosaria , Tinto Nadia , Frisso Giulia , D’Argenio Valeria , Lombardo Barbara , Terracciano Daniela , Crescioli Clara , Scudiero Olga
Published: November 2024

Physical activity highly impacts the neuroendocrine system and hormonal secretion. Numerous variables, both those related to the individual, including genetics, age, sex, biological rhythms, nutritional status, level of training, intake of drugs or supplements, and previous or current pathologies, and those related to the physical activity in terms of type, intensity, and duration of exercise, or environmental conditions can shape the hormonal response to physical exercise. The aim of this review is to provide an overview of the effects of physical exercise on hormonal levels in the human body, focusing on changes in concentrations of hormones such as cortisol, testosterone, and insulin in response to different types and intensities of physical activity. Regular monitoring of hormonal responses in athletes could be a potential tool to design individual training programs and prevent overtraining syndrome.
Recapitulating Glioma Stem Cell Niches Using 3D Spheroid Models for Glioblastoma Research
Authors: Jo Hyunji , Lee Seulgi , Kim Min-Hyeok , Park Sungsu , Lee Seo-Yeon
Published: November 2024

Glioblastoma multiforme (GBM) is among the most aggressive brain cancers, and it contains glioma stem cells (GSCs) that drive tumor initiation, progression, and recurrence. These cells resist conventional therapies, contributing to high recurrence rates in GBM patients. Developing in vitro models that mimic the tumor microenvironment (TME), particularly the GSC niche, is crucial for understanding GBM growth and therapeutic resistance. Three-dimensional (3D) spheroid models provide a more physiologically relevant approach than traditional two-dimensional (2D) cultures, recapitulating key tumor features like hypoxia, cell heterogeneity, and drug resistance. This review examines scaffold-free and scaffold-based methods for generating 3D GBM spheroids, focusing on their applications in studying the cancer stem cell niche. The discussion encompasses methods such as the hanging drop, low-adhesion plates, and magnetic levitation, alongside advancements in embedding spheroids within extracellular matrix-based hydrogels and employing 3D bioprinting to fabricate more intricate tumor models. These 3D culture systems offer substantial potential for enhancing our understanding of GBM biology and devising more effective targeted therapies.
Recent Advance in Single-Molecule Fluorescent Biosensors for Tumor Biomarker Detection
Authors: Zhang Jie , Liu Jiawen , Qiao Lixue , Zhang Qian , Hu Juan , Zhang Chun-yang
Published: November 2024

The construction of biosensors for specific, sensitive, and rapid detection of tumor biomarkers significantly contributes to biomedical research and early cancer diagnosis. However, conventional assays often involve large sample consumption and poor sensitivity, limiting their further application in real samples. In recent years, single-molecule biosensing has emerged as a robust tool for detecting and characterizing biomarkers due to its unique advantages including simplicity, low sample consumption, ultra-high sensitivity, and rapid assay time. This review summarizes the recent advances in the construction of single-molecule biosensors for the measurement of various tumor biomarkers, including DNAs, DNA modifications, RNAs, and enzymes. We give a comprehensive review about the working principles and practical applications of these single-molecule biosensors. Additionally, we discuss the challenges and limitations of current single-molecule biosensors, and highlight the future directions.