bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Digital Agro-Technology Services on Technical Efficiency and Income of Small-Scale Farmers: Empirical Study from Mango Production in China
Authors: Xie Chongxin , Gao Yun , Zhong Yu , Zhao Zhijun
Published: November 2024

With the market-driven approach to agricultural technical services and the application of digital technology, digital agro-technical services have gradually emerged as a novel service model. However, there is a lack of empirical research on the effectiveness of this service in the academic literature. To address this research gap, this study measured the impact of this service on the technical efficiency and income levels of mango farmers, using data collected from 131 mango farmers in Hainan Province, China, from 2022 to 2024. This study employed the endogenous switching regression model (ESRM) and the inverse probability-weighted regression adjustment model (IPWRA) to analyze the data, addressing endogeneity through the instrumental variable method by replacing core explanatory variables and conducting sub-regional regression for robustness testing. The main research conclusions are as follows: Under the counterfactual assumption of ESRM, farmers who adopt this service would have experienced a decrease in technical efficiency by 0.025 (a decline of 3.6%) if they had not adopted the service. Conversely, farmers who did not adopt it would have seen an increase in technical efficiency by 0.047 (an increase of 7.3%) if they had chosen to do so. Additionally, under the post-treatment income effect estimation using IPWRA, compared to farmers who did not receive the service, those who did so saw an income increase of 15.6%. The analysis results from methods such as K-nearest neighbors matching also confirm this conclusion. Therefore, it is evident that digital agro-technology services play a significant role in improving the technical efficiency and income levels of small-scale farmers.
Enhancing Regional Topsoil Total Nitrogen Mapping Through Differentiated Fusion of Ground Hyperspectral Data and Satellite Images Under Low Vegetation Cover
Authors: He Rongpeng , Meng Jihua , Du Yanfei , Lin Zhenxin , You Xinyan , Gao Xinyu
Published: November 2024

Total nitrogen in soil (STN) serves as a crucial indicator of soil nutrient content and provides an essential nitrogen source necessary for crop growth. Precisely inversion of STN content is crucial for the sustainable management of soil resources and the advancement of agricultural development, particularly to achieve efficient fertilization—reduction in fertilizer usage without compromising yield or increase in yield while maintaining the total fertilization amount. Spectroscopy technology is regarded as an ideal non-destructive method for nutrient detection. However, due to the weak spectral signals of STN and its spatial heterogeneity, hyperspectral imaging technology presents significant potential for high-resolution measurements and precise characterization of STN heterogeneity. In this paper, the STN content was selected as the study subject, and three aspects of soil spectral feature enhancement, multi-source remote sensing data differentiated fusion, and STN content inversion model construction were studied. Therefore, a differentiated fusion of enhanced multispectral image bands (DFE_MSIBs) method combined with Random Forest (RF) algorithms was developed for spectral inversion of STN content. The findings demonstrate the following: 1. The enhanced spectral characteristics and differentiated fusion method not only strengthen the relationship between STN and Sentinel-2A MSI data but also enhance the precision of regional STN inversion models. 2. For the differentiated fusion of enhanced multispectral image bands (DFE_MSIBs) method combined with Random Forest (RF) algorithms, the R2 was 0.95, RMSE was 0.10 g/kg, and LCCC was 0.89. 3. Compared to the unfused model, the average R2 value was increased by 0.02, the average RMSE was decreased by 0.01 g/kg, and the average LCCC was increased by 0.03. These findings hold practical significance for utilizing multi-source remote sensing data in STN mapping and precision fertilization in agricultural fields.
Explicating the Role of Agricultural Socialized Services on Chemical Fertilizer Use Reduction: Evidence from China Using a Double Machine Learning Model
Authors: Wang Lulu , Lyu Jie , Zhang Junyan
Published: November 2024

Reducing chemical usage, particularly chemical fertilizers, is a crucial measure for advancing sustainable agricultural development. This study utilized field survey data from 894 maize farmers across three northeastern provinces of China. A double machine learning modeling framework was established to empirically examine the impact and mechanism of agricultural socialized services on chemical fertilizer use of farm households. The model addresses numerous stringent constraints of conventional causal inference models and effectively mitigates the “curse of dimensionality” issue. Current research indicates that agricultural socialized services can substantially decrease chemical fertilizer use among farmers. Further investigation reveals that these services facilitate this reduction by enhancing the mechanization level, promoting the use of organic fertilizers, and providing a labor substitution effect. The region heterogeneity test indicates that the impact of agricultural socialized services is more pronounced in Liaoning and Heilongjiang provinces geographically. Regarding the heterogeneity analysis of food crop income levels, agricultural socialized services can decrease chemical fertilizer use among farmers more effectively with elevated food crop income levels. Consequently, the findings imply that the socialization of agricultural services has substantial potential to be an effective chemical fertilizer reduction strategy to support the agricultural green transition, which can be enhanced through promoting the degree of mechanization, organic fertilizer application, and labor division and specialization.
Use of Drones for Trough Reading, Animal Counting, and Production Monitoring in Feedlot Systems
Authors: Bastos Kécia M. , Barcelos Jardel P. , Orioli Guilherme F. , Nascimento Sheila T.
Published: November 2024

In line with the concept of precision agriculture, this study aimed to validate the use of digital aerial images captured using a remotely piloted aircraft (RPA) for collecting zootechnical data on cattle feedlot systems in a tropical environment. Images were captured on 21 non-consecutive days in 110 pens with up to 150 animals each. Conventional and RPA-based methods were adopted to determine animal behavior, feed trough levels, animal counts, and pen conditions. Data analysis revealed almost perfect agreement (kappa coefficient = 0.901) between trough readings taken by conventional and RPA methods as well as substantial agreement for fecal score (kappa coefficient = 0.785) and surface conditions (kappa coefficient = 0.737). However, animal counts and water quality scores showed only fair agreement, suggesting challenges in using RPA for these specific tasks. The results indicated that RPA represents a viable alternative to conventional methods for monitoring zootechnical indices in feedlots, offering benefits in terms of accuracy, efficiency, and cost-effectiveness. The implementation of RPA-based methods holds potential for improving animal management, welfare, and yield in feedlot systems.
Sustainable Disease Control of Phytophthora cactorum in a Strawberry Nursery by Adapting the Growing System
Authors: Evenhuis Albartus , Bac-Molenaar Johanna A. , Pham Khanh , Leiss Kirsten A.
Published: November 2024

The Netherlands is one of the most important countries for the production of strawberry transplants in Europe. Regulations for pesticide use and water quality become more strict each year, which is a challenge for this sector. Strawberry plants are grown from tips and raised in trays on a trayfield. One of the main plant diseases in strawberry is caused by Phytophthora cactorum. The dispersal of the disease is facilitated by sporangia and zoospores splashing from the surface of the trayfield onto the transplants in the trays. In this research, we compared, in three consecutive years, the traditional growing system with a new system in which the trays are elevated and splashes from the trayfield reaching the transplants are minimized. In two of the three years, we show that the new growing system without the use of any fungicide against P. cactorum performs as well as or even better than the traditional system with the use of the permitted pesticides. Data about Phytophthora occurring in air samples and in splash water collected at different heights support the hypothesis that the decrease in splash dispersal underlies the success of the elevated trayfield. This shows the potential of re-designing growing systems to become less dependent on pesticide use.
Spatio-Temporal Distribution of Stored Product Insects in a Feed Mill in Greece
Authors: Agrafioti Paraskevi , Lampiri Evagelia , Kaloudis Efstathios , Gourgouta Marina , Vassilakos Thomas N. , Ioannidis Philippos M. , Athanassiou Christos G.
Published: November 2024

Floor traps were placed in a feed mill in Greece for a period of approx. 13 months to illustrate the relative abundance and distribution of the stored product insects found. More than 20 taxa were found, with most of them belonging to Coleoptera. The most abundant species found were the rice weevil, Sitophilus oryzae (L.), and the granary weevil, Sitophilus granarius (L.), which are common primary colonizers of grains, and the confused flour beetle, Tribolium confusum Jacquelin du Val, and the red flour beetle, Tribolium castaneum (Herbst), which are secondary colonizers that usually occur in processed amylaceous commodities. Interestingly, the highest population densities of all four species were recorded during the same period, with the secondary colonizers slightly preceding the primary colonizers. Although competition among these species has been recorded in previous studies, we found that these four species could coexist during the entire trapping period in the same sampling units, which indicates possible spatial segregation and different colonization patterns in space and time. Our results demonstrate that trapping in storage and processing facilities is an essential component of decision-making regarding stored product pest management strategies in localized applications, and can drastically reduce the need for treating the entire facility.
Empirical Evaluation and Analysis of YOLO Models in Smart Transportation
Authors: Nguyen Lan Anh , Tran Manh Dat , Son Yongseok
Published: November 2024

You Only Look Once (YOLO) and its variants have emerged as the most popular real-time object detection algorithms. They have been widely used in real-time smart transportation applications due to their low-latency detection and high accuracy. However, because of the diverse characteristics of YOLO models, selecting the optimal model according to various applications and environments in smart transportation is critical. In this article, we conduct an empirical evaluation and analysis study for most YOLO versions to assess their performance in smart transportation. To achieve this, we first measure the average precision of YOLO models across multiple datasets (i.e., COCO and PASCAL VOC). Second, we analyze the performance of YOLO models on multiple object categories within each dataset, focusing on classes relevant to road transportation such as those commonly used in smart transportation applications. Third, multiple Intersection over Union (IoU) thresholds are considered in our performance measurement and analysis. By examining the performance of various YOLO models across datasets, IoU thresholds, and object classes, we make six observations on these three aspects while aiming to identify optimal models for road transportation scenarios. It was found that YOLOv5 and YOLOv8 outperform other models in all three aspects due to their novel performance features. For instance, YOLOv5 achieves stable performance thanks to its cross-stage partial darknet-53 (CSPDarknet53) backbone, auto-anchor mechanism, and efficient loss functions including IoU loss, complete IoU loss, focal loss, gradient harmonizing mechanism loss. Similarly, YOLOv8 outperforms others with its upgraded CSPDarknet53 backbone, anchor-free mechanism, and efficient loss functions like complete IoU loss and distribution focal loss.
Histological Analysis of the Effect of a Vector Potential Generator on the Femur of a Hindlimb-Suspended Rat
Authors: Minamizono Wataru , Yashima Nao , Matsunaga Hiroya , Fujikawa Kaoru , Suito Hirai , Okunuki Takumi , Ohsako Masafumi
Published: November 2024

Disuse osteoporosis occurs due to rest and reduced mechanical stimulation. Under these conditions, bone resorption exceeds bone formation, leading to a decrease in bone density. Vector potential (VP) generators have been developed, and their ability to maintain cartilage thickness has been reported. However, their effects on bone tissue remain unstudied. In this study, experiments were conducted to test the effects of VP on bones that had undergone weight reduction due to hindlimb suspension as a model of disuse osteoporosis. Methods: In this study, 7-week-old male Wistar rats (N = 6 each) were classified into control (CO), hindlimb suspension (HS), and VP energization intervention groups. The tail was used to suspend the HS and VP to remove the load applied to the hindlimbs. The VP conditions were as follows: voltage, 67 mV; frequency, 20 kHz, 0.12 mA; experimental intervention, 30 min/day, 5 days/week, for 3 weeks. At the end of the experimental period, the rats were euthanized with carbon dioxide gas, and histological specimens were fixed in 4% paraformaldehyde (PFA) in the femur and analyzed by electron microscopy, bone morphometry, immunohistology, bone fracture testing, and gene expression analysis. Results: HS decreased trabecular bone density and strength. However, VP maintained a significantly higher bone mass than HS, and VP did not differ from CO in bone strength; more osteoclasts were observed on the bone surface in HS, but they were suppressed in VP, and gene expression of CTSK and MMP-9 was decreased. Conclusions: VP suppressed bone resorption by osteoclasts, suggesting that VP is useful in the treatment of disuse osteoporosis.
Analyzing Targeted Muscle Strength: Impact on Speed, Endurance, and Performance in Female Volleyball
Authors: Martin Ștefan Adrian , Gavra Mihăiță George , Martin-Hadmaș Roxana Maria
Published: November 2024

This study examines the influence of muscle strength on performance metrics in volleyball, addressing the need to understand how specific and non-specific strength training impacts athletic capabilities. A cohort of athletes underwent various strength tests, including squats (SQs), bench presses (BPs), and deadlifts (DLs), to assess their force and power during various forms of test. Lactate thresholds (LT1 and LT2) were also measured to evaluate aerobic and anaerobic capacities. The median speed at LT1 was 1.80 m/s, and LT2 was determined at a mean velocity of 2.56 m/s. Notably, a correlation was found between SQ performance and total points scored (p = 0.040, r = 0.285), while upper body strength was strongly correlated with performance metrics, showing significant relationships with points scored (p = 0.0001, r = 0.690) and peak power during BPs (p = 0.0001, r = 0.587). The findings suggest that targeted strength training enhances physical capabilities and improves technical and tactical performance in volleyball, highlighting the critical role of muscle strength in athlete selection and training strategies.
Integrated Process for Ballot Bin Waste Valorization for High-Quality Cellulose Acetate Recovery
Authors: Lamanna Niccolò , Zuccante Giovanni , Rossetti Massimiliano , Franzetti Andrea , Santoro Carlo , Zoia Luca
Published: November 2024

Cigarette butt littering poses a significant environmental challenge, with billions of butts discarded each year, fouling ecosystems with slow-to-decompose cellulose acetate filters that absorb and release harmful compounds. In response, an innovative, sustainable approach for valorizing ballot bin waste (BBW) by extracting high-quality cellulose acetate from cigarette butts was investigated. This green approach eliminates the need for hazardous acids and toxic solvents, resulting in a yield of 30% (w/w) and a degree of substitution (DS) of 2.0–2.5, which is comparable to pure cellulose acetate. The following four essential processes are involved in this process: filter separation, water washing to remove impurities, ethanol purification, and acetone precipitation of the cellulose acetate. This approach not only mitigates environmental harm, but also supports circular economy goals by transforming waste into valuable resources.
Advanced Nested Coaxial Thin-Film ZnO Nanostructures Synthesized by Atomic Layer Deposition for Improved Sensing Performance
Authors: Lin Pengtao , Zhang Lari S. , Zhang Kai , Baumgart Helmut
Published: November 2024

We report a new synthesis method for multiple-walled nested thin-film nanostructures by combining hydrothermal growth methods with atomic layer deposition (ALD) thin-film technology and sacrificial films, thereby increasing the surface-to-volume ratio to improve the sensing performance of novel ZnO gas sensors. Single-crystal ZnO nanorods serve as the core of the nanostructure assembly and were synthesized hydrothermally on fine-grained ALD ZnO seed films. Subsequently, the ZnO core nanotubes were coated with alternating sacrificial coaxial 3D wrap-around ALD Al2O3 films and ALD ZnO films. Basically, the center nanorod was coated with an ALD 3D wrap-around Al2O3 sacrificial layer to realize a nested coaxial ZnO thin-film nanotube. To increase the surface-to-volume ratio of the nested multiple-film nanostructure, both the front and backside of the nested coaxial ZnO films must be exposed by selectively removing the intermittent Al2O3 sacrificial films. The selective removal of the sacrificial films exposes the front and backside of the free-standing ZnO films for interaction with target gases during sensing operation while steadily increasing the surface-to-volume ratio. The sensing response of the novel ZnO gas sensor architecture with nested nanotubes achieved a maximum 150% enhancement at low temperature compared to a conventional ZnO nanorod sensor.
Research on Nanoparticle-Enhanced Cooling Technology for Oil-Based Drilling Fluids
Authors: Wang Xudong , Wu Pengcheng , Chen Ye , Zhang Ergang , Ye Xiaoke , Huang Qi , Wang Ruolan , Wang Gui , Xie Gang
Published: November 2024

Drilling fluids are critical in oil and gas well drilling, particularly deep shale gas drilling. In recent years, applying nanoparticles as additives in drilling fluids has received widespread attention to address the various challenges associated with deep shale gas drilling. This study focused on the performance of three nanoparticle-enhanced oil-based drilling fluids (OBDFs), carbon nanotubes (CNTs), silicon dioxide (SiO2), and aluminums oxide (Al2O3) in terms of improving thermal capacity and cooling efficiency. The potential of the nanoparticles to improve the thermal management capability of the drilling fluids was evaluated by measuring specific heat capacity and thermal conductivity. The results showed that CNTs exhibited the most significant improvement, with thermal conductivity increasing by 7.97% and specific heat capacity by 19.38%. The rheological properties and high temperature and high pressure (HTHP) filtration performance of the nanoparticle-enhanced OBDFs were evaluated, demonstrating that CNTs and SiO2 significantly improved the rheological stability of the drilling fluids and reduced the filtration loss under high temperature conditions. When 3% CNTs were added, the HTHP filtration loss was reduced by 42.86%, exhibiting excellent sealing properties. The cooling effect of different nanoparticles was evaluated by calculating their effects on the bottomhole temperature. The results showed that CNTs performed the best in lowering the bottomhole temperature by 4.53 °C, followed by SiO2 by 1.47 °C and Al2O3 by only 0.88 °C. The results showed that CNTs were the most effective in lowering the bottomhole temperature. These results indicated that nanoparticles as additives to drilling fluids could significantly increase the thermal capacity and cooling efficiency of OBDFs, making them effective additives for high-temperature deep shale gas drilling applications.
Pupil Refinement Recognition Method Based on Deep Residual Network and Attention Mechanism
Authors: Chen Zehui , Wang Changyuan , Wu Gongpu
Published: November 2024

This study aims to capture subtle changes in the pupil, identify relatively weak inter-class changes, extract more abstract and discriminative pupil features, and study a pupil refinement recognition method based on attention mechanisms. Based on the deep learning framework and the ResNet101 deep residual network as the backbone network, a pupil refinement recognition model is established. Among them, the image preprocessing module is used to preprocess the pupil images captured by infrared spectroscopy, removing internal noise from the pupil images. By using the ResNet101 backbone network, subtle changes in the pupil are captured, weak inter-class changes are identified, and different features of the pupil image are extracted. The channel attention module is used to screen pupil features and obtain key pupil features. External attention modules are used to enhance the expression of key pupil feature information and extract more abstract and discriminative pupil features. The Softmax classifier is used to process the pupil features captured by infrared spectra and output refined pupil recognition results. Experimental results show that this method can effectively preprocess pupil images captured by infrared spectroscopy and extract pupil features. This method can effectively achieve fine pupil recognition, and the fine recognition effect is relatively good.
Pore Types and Dolomite Reservoir Genesis of the Fifth Member of the Ordovician Majiagou Formation in the Central and Eastern Ordos Basin
Authors: Chen Shilei , Dai Rong , Luo Shunshe
Published: November 2024

The Ordovician dolomite in the Ordos Basin is an important natural gas reservoir. Exploring dolomite genesis and the factors influencing reservoir characteristics is essential for deep carbonate rock exploration. This study offers a comprehensive analysis of dolomite evolution using methods such as thin-section petrography, isotope analysis, and trace and rare earth elements. The analysis shows that: Based on petrographic observations of the Majiagou Formation in the study area, the dolomite in the study area can be divided into residual oolitic dolomite of synsedimentary or metasomatic origin, micritic dolomite of secondary metasomatism or recrystallization origin, powder crystal dolomite, and fine crystal dolomite. Reservoir pores mainly develop intergranular pores, mold pores, dissolved pores, and fractures. Combined with the characteristics of major elements, trace elements, carbon and oxygen isotopes, rare earth elements, and inclusions in the study area, it can be concluded that the fifth member dolomite of the Majiagou Formation is of shallow–medium burial origin. The diagenetic evolution sequence from the penecontemporaneous period to the middle–deep burial period in the study area is penecontemporaneous dolomite, anhydrite dissolution → seepage silt filling, freshwater dolomite, calcite, and gypsum filling, pressure solution compaction, calcite partial dissolution → gypsum filling, karst cave, buried hydrothermal dolomite, dolomite partial dissolution → calcite complete dissolution, pore dissolution expansion, and quartz pyrite filling. In the early stage of compaction and pressure solution, the primary pores are rapidly reduced, and in the later stage, sutures are generated to provide channels for reservoir fluid migration. The recrystallization reduces the porosity during the middle–deep burial period.
Application of Microbial Antagonists in Combination with Sodium Bicarbonate to Control Post-Harvest Diseases of Sweet Cherry (Prunus avium L.) and Plums (Prunus salicina Lindl.)
Authors: Navajas-Preciado Bruno , Rocha-Pimienta Javier , Martillanes Sara , Galván Almudena , Izaguirre-Pérez Nuria , Delgado-Adámez Jonathan
Published: November 2024

Postharvest diseases cause considerable losses of fruits and vegetables during transportation and storage, and synthetic fungicides are the first option for their prevention. However, promising alternatives to chemical fungicides are currently available, and several post-harvest diseases can be controlled using microbial antagonists. This study utilised a comprehensive methodology to assess the antagonistic and synergistic interactions between four yeasts and two bacteria in conjunction with sodium bicarbonate (SB) during the treatment of sweet cherries and plums. The aim of this study was to evaluate the effects of microbial antagonists and sodium bicarbonate on fruits. The in situ treatments showed a protective effect exerted by the antagonists P. guillermondii and H. uvarum, and their combination with SB. However, in vivo studies did not indicate enhanced efficacy when combined with this compound. In conclusion, the use of microbial antagonists in conjunction with SB has been successful in preventing post-harvest rot of cherries and plums. Tests conducted on live organisms have shown that microbial antagonists are viable alternatives to synthetic fungicides for the control of stone fruit rot.
Dynamic Prediction of Shale Gas Drilling Costs Based on Machine Learning
Authors: Yang Tianxiang , Liang Yuan , Wang Zhong , Ji Qingyun
Published: November 2024

Shale gas, a significant recoverable natural gas resource trapped in shale formations, represents a significant energy reservoir. Although China has significant recoverable shale gas reserves, the challenge of controlling drilling costs remains a critical barrier to efficient development. This study presents a novel stacked ensemble learning model that integrates support vector machine (SVM) and long short-term memory (LSTM) networks to improve the accuracy of shale gas drilling cost prediction. The methodology consists of three main phases. First, we constructed a comprehensive, multidimensional spatiotemporal dataset of shale gas drilling costs. Second, we used Gradient Boosting Decision Tree (GBDT) modelling to rank the importance of various factors influencing drilling costs. Finally, we developed a stacked ensemble learning model combining SVM and LSTM architectures to achieve superior cost prediction accuracy. Experimental results demonstrate the effectiveness of the model, with the coefficient of determination (R2) improving from 0.25189/0.33834 (traditional SVM/LSTM models) to 0.55934. Model validation using selected well investment data from the Changning Block shows promising performance, achieving a Mean Absolute Percentage Error (MAPE) of 6.41%, with optimal prediction accuracy in the medium investment range (60–70 million yuan). This innovative approach provides a reliable tool for predicting shale gas drilling costs and offers new methodological perspectives for cost reduction strategies. The results contribute significantly to the sustainable development of shale gas resources and provide valuable insights for industry practitioners and researchers in the fields of energy economics and resource management.
Key Parameter Design and Experimental Analysis for Peelable Seedling Belts in Sweet Potato Transplanting Systems
Authors: Wei Youhao , Li Kun , Hu Minjuan , Qi Bing , Ji Yao , Zhang Wenyi , Yan Wei
Published: November 2024

Sweet potato is essential for food security, but its transplanting efficiency is currently low. To improve this, we developed a belt-type transplanter that uses seedling belt technology for automated feeding, increasing efficiency by over 25%. The use of the seedling belt is key to significantly enhancing the transplanter’s efficiency. Building on seedling belt feeding, we designed a “trumpet-shaped” staggered detachable seedling belt using LDPE film. Seedlings are fixed at intervals between two film layers via thermal bonding points. Mechanical analysis showed the optimal peeling strength is 13.2 N, ensuring smooth seedling transport during transplanting. Peeling strength depends on the heat sealing temperature, time, and pressure. To optimize these parameters, we designed an experimental device and conducted single-factor experiments to determine their effects on the peeling strength and establish reasonable ranges. Results show that, at a peeling strength of 13.2 N, the thermal bonds separate smoothly without tearing the film. A three-factor, three-level orthogonal experiment further optimized the heat sealing parameters, concluding that, at 140 °C, 1.2 s, and 0.4 MPa, the average peel force of the seedling tapes obtained from the experiments was 14.31 N, at which point the peeling effect was optimal.
Conserved Vectors, Analytic Solutions and Numerical Simulation of Soliton Collisions of the Modified Gardner Equation
Authors: Khalique Chaudry Masood , Olivier Carel , Sebogodi Boikanyo Pretty
Published: November 2024

This paper aims to study the modified Gardner (mG) equation that was proposed in the literature a short while ago. We first construct conserved vectors of the mG equation by invoking three different techniques; namely the method of multiplier, Noether’s theorem, and the conservation theorem owing to Ibragimov. Thereafter, we present exact solutions to the mG equation by invoking a complete discrimination system for the fifth degree polynomial. Finally, we simulate collisions of solitons for the mG equation.
Genotoxicity and Cytotoxicity Induced In Vitro by Airborne Particulate Matter (PM2.5) from an Open-Cast Coal Mining Area
Authors: Galeano-Páez Claudia , Brango Hugo , Pastor-Sierra Karina , Coneo-Pretelt Andrés , Arteaga-Arroyo Gean , Peñata-Taborda Ana , Espitia-Pérez Pedro , Ricardo-Caldera Dina , Humanez-Álvarez Alicia , Londoño-Velasco Elizabeth , Espinosa-Sáez Roger , Diaz-Ponguta Basilio , da Silva Juliana , Silva Corrêa Dione , Espitia-Pérez Lyda
Published: November 2024

This study evaluates the cytotoxic and genotoxic effects of PM2.5 collected from an open-cast coal mining area in northern Colombia. Cyclohexane (CH), dichloromethane (DCM), and acetone (ACE) extracts were obtained using Soxhlet extraction to isolate compounds of different polarities. Human lymphocytes were exposed to the extracted compounds, and cytotoxicity and genotoxicity were assessed using the cytokinesis block micronucleus (CBMN) and comet assays, incorporating FPG and ENDO III enzymes to detect oxidative DNA damage. Chemical analysis revealed that the organic fractions consisted mainly of modified hydrocarbons and volatile organic compounds. The CBMN assay showed a significant increase in micronuclei in binucleated (MNBN) and mononucleated (MNMONO) cells and nucleoplasmic bridges (NPB) in exposed lymphocytes. The comet assay revealed substantial oxidative DNA damage, particularly with the ACE extract, which significantly increased oxidized purines and pyrimidines. DCM induced similar effects, while CH showed moderate effects. CREST immunostaining revealed aneugenic activity, particularly in cells exposed to ACE and DCM extracts. These results suggest that polar fractions of PM2.5, likely containing metals and modified PAHs, contribute to DNA damage and chromosomal instability. The study highlights the need to monitor the composition of PM2.5 in mining regions to implement stricter environmental policies to reduce exposure and health risks.
Changes in the Profile of Phenolic Compounds and in the Antioxidant, Hypoglycemic, and Antidiabetic Activities of a Beverage Based on Sesame By-Product Caused by the Simulated Gastrointestinal Digestion Process
Authors: Carrasco-Chávez Jonhatan , Quintero-Soto María Fernanda , Velarde-Barraza Rosalio , Rivero-Espejel Ignacio Alfredo , Díaz-Peña Ismael , Vázquez-Ontiveros Martha Elena , Espinoza-Moreno Ramona Julieta , Ontiveros-García Luz Adriana , Amillano-Cisneros Jesús Mateo , Perales-Sánchez Janitzio Xiomara K. , Argüelles-López Oscar Daniel , Salas-López Fernando , Félix-Medina Jennifer Vianey
Published: November 2024

The by-product of extracting oil from sesame has good functional properties for use in the development of new food products. In this study, the effect of simulated gastrointestinal digestion on the bioaccessibility of phenolic compounds, as well as the antioxidant, antidiabetic, and hypoglycemic properties of a beverage from sesame by-products was analyzed. Oral digestion significantly decreased the total phenolic content of the beverage, while the total flavonoid content increased. Both phytochemicals increased after gastric and intestinal digestion. Twenty-five phenolic compounds were characterized in the sesame by-product beverage, including feruloylquinic acid, which was present in all the digestive fractions analyzed. The most abundant free phenolic was quercetin, which was also present in all the digested fractions. On the other hand, the most abundant phenolic in the digested fractions was isorhamnetin. During gastrointestinal digestion, the antioxidant activity and inhibitory effects on the α-glucosidase and DPP-IV of the beverage significantly improved, while the ability to inhibit the α-amylase significantly increased during oral digestion, remaining constant throughout digestion. Correlation analysis indicated that flavonoids, including quercetin, may be the compounds with the greatest effect on the evaluated activities. The results of this study not only improve the understanding of the impact of gastrointestinal digestion on the bioaccessibility of phenolic compounds but also suggest potential applications in formulating functional foods with enhanced antioxidant, hypoglycemic, and antidiabetic properties, contributing to the development of health-promoting food products.
Biofluid-Derived Exosomal LncRNAs: Their Potential in Obesity and Related Comorbidities
Authors: Ngowi Ebenezeri Erasto , Lu Tuyan , Liu Qing , Xie Xianghong , Wang Ning , Luo Liping , Deng Lijuan , Zhou Yinghua , Zhang Zhihong , Qiao Aijun
Published: November 2024

Obesity has escalated into a critical global health crisis, tripling in prevalence since the mid-1970s. This increase mirrors the rise in metabolic-associated diseases such as type 2 diabetes (T2D) and its complications, certain cancers, and cardiovascular conditions. While substantial research efforts have enriched our understanding and led to the development of innovative management strategies for these diseases, the suboptimal response rates of existing therapies remain a major obstacle to effectively managing obesity and its associated conditions. Over the years, inter-organ communication (IOC) has emerged as a crucial factor in the development and progression of metabolic disorders. Exosomes, which are nano-sized vesicular couriers released by cells, play a significant role in this communication by transporting proteins, lipids, and nucleic acids across cellular landscapes. The available evidence indicates that exosomal RNAs present in biofluids such as blood, urine, milk, vitreous humor (VH), and cerebrospinal fluid (CSF) are altered in numerous diseases, suggesting their diagnostic and therapeutic potential. Long non-coding RNAs contained in exosomes (exo-lncRNAs) have attracted considerable interest, owing to their ability to interact with critical components involved in a multitude of metabolic pathways. Recent studies have found that alterations in exo-lncRNAs in biofluids correlate with several metabolic parameters in patients with metabolic-associated conditions; however, their exact roles remain largely unclear. This review highlights the diagnostic and therapeutic potential of exosomal lncRNAs in obesity and its associated conditions, emphasizing their role in IOC and disease progression, aiming to pave the way for further research in this promising domain.
CircRNA: Functions, Applications and Prospects
Authors: Xu Fei , Xiao Qing , Du William W. , Wang Sheng , Yang Burton B.
Published: November 2024

Circular RNAs (circRNAs) represent a distinct class of covalently closed non-coding RNA molecules characterized by the absence of free 5′ and 3′ ends [...]
Contributions of the Primary Sensorimotor Cortex and Posterior Parietal Cortex to Motor Learning and Transfer
Authors: Wang Chenyu , Yu Yinghua , Yang Jiajia
Published: November 2024

Background: Transferring learned manipulations to new manipulation tasks has enabled humans to realize thousands of dexterous object manipulations in daily life. Two-digit grasp and three-digit grasp manipulations require different fingertip forces, and our brain can switch grasp types to ensure good performance according to motor memory. We hypothesized that several brain areas contribute to the execution of the new type of motor according to the motor memory. However, the motor memory mechanisms during this transfer period are still unclear. In the present functional magnetic resonance imaging (fMRI) study, we aimed to investigate the cortical mechanisms involved in motor memory during the transfer phase of learned manipulation tasks. Methods: Using a custom-built T-shaped object with an adjustable weight distribution, the participants performed grasp and lift manipulation tasks under different conditions to simulate the learning and transfer phases. The learning phase consisted of four grasp-and-lift repetitions with one motor type, followed by a transfer phase with four repetitions involving different motors (adding or removing a digit). Results: By comparing brain activity in the learning and transfer phases, we identified three regions (the superior frontal gyrus, supramarginal gyrus, and postcentral gyrus) associated with motor memory during the transfer of learned manipulations. Conclusions: Our findings improve the understanding of the role of the posterior parietal cortex in motor memory, highlighting how sensory information from memory and real-time input is integrated to generate novel motor control signals that guide the precise reapplication of control strategies. Furthermore, we believe that these areas contribute to motor learning from motor memory and may serve as key regions of interest for investigating neurodegenerative diseases.
Tower Crane Layout Planning: Multi-Optimal Solutions Algorithm
Authors: Huang Xiaokang , Chen Huazhou , Wang Rui , Wang Heng , Li Shuai , Zhang Pengfei , Yang Zhen
Published: November 2024

Effective tower crane layout planning is essential for the success of construction projects. Traditional optimization algorithms, which often provide a single optimal solution, may not always reveal the global optimum, leaving room for doubt. This paper introduces the competitor algorithm, a novel multi-optimal solution approach inspired by the competitive learning paradigm within classroom settings. This algorithm is designed to provide users with a diverse set of competitive solutions, while avoiding falling into local optima. This strategic diversification ensures that users are equipped with a comprehensive range of options, empowering them to make confident, informed decisions. Furthermore, we have streamlined the positioning range for tower cranes, transitioning from a two-dimensional plane to a one-dimensional segmented line, thus eliminating the need to explore extensive, non-competitive regions. The competitor algorithm’s performance was validated through practical application, showcasing both its stability and optimization prowess, thereby confirming its reliable utility in real-world scenarios.
Development and Characterization of Alkali-Activated Lithium Slag-Fly Ash Composite Cement
Authors: Dong Jingliang , Tu Zhen , Shang Xiaopeng , Wu Hao , Li Zhiping , Ding Haibin
Published: November 2024

As the demand for environmental sustainability grows in the global construction industry, traditional cement production faces significant challenges due to high energy consumption and substantial CO2 emissions. Therefore, developing low-carbon, high-performance alternative cementitious materials has become a research focus. This paper proposes a new low-carbon cement (alkali-activated lithium slag-fly ash composite cement, ALFC) as a substitute for traditional cement. First, the alkali activation reactivity of lithium slag (LS) is enhanced through calcination and grinding, revealing the reasons behind its improved reactivity. Then, alkali-activated LS and fly ash were partially used to replace cement to prepare ALFC, and the effects of the water-to-binder ratio (W/B), LS content, and NaOH addition on the flowability and mechanical properties of ALFC were investigated. XRD, SEM/EDS, and TG/DTG analyses were conducted to examine its hydration products and microstructure, revealing the hydration mechanism. The results show that the flowability of ALFC increases with W/B but decreases with a higher LS content. When W/B is 0.325 and the LS content is 25 wt.%, flowability reaches 200 mm, meeting construction requirements. LS calcined at 700 °C for 1 h significantly enhanced ALFC’s 90-day flexural and compressive strengths by 39.73% and 58.47%, respectively. The primary hydration products of ALFC are C-S-H, N-A-S-H, and C-A-S-H gels, with their content increasing as the NaOH concentration rises. The optimal NaOH concentration and LS content for ALFC are 2 mol/L and 25 wt.%, respectively.
Compressive Behaviour of Circular High-Strength Self-Compacting Concrete-Filled Steel Tubular (CFST) Stub Columns Under Chloride Corrosion: Numerical Simulation
Authors: Zheng Jun , Xu Qian , Wang Weiwei , Zheng Zhiyuan , Hou Mingxun , Lyu Xuetao
Published: November 2024

This paper investigates the strength and behaviour of high-strength self-compacting concrete-filled steel tubular (HSSC-CFST) stub columns under axial compression. HSSC-CFST columns are high-performance structural members with wide applications in engineering structures. Nevertheless, relevant studies have commonly focused on the mechanical performance of HSSC-CFST in indoor environments. A finite element (FE) model was developed to predict the axial load capacity of HSSC-CFST stub columns subjected to chloride corrosion. According to this, several crucial geometric and material parameters were designed to investigate the influences on strength, initial stiffness, and ductile performance. Moreover, the analysis on failure mechanisms was investigated by N-ε curves and stress development in the whole loading process. The impacts of key parameters on the reduction factor of axial load capacity were also identified. The numerical analysis results indicate that the axial strength of HSSC-CFST stub columns under chloride corrosion was significantly heightened by increasing the strength of core self-compacting concrete, while contrary results were found with the increase in the steel ratio and yield strength of the steel tube. Lastly, design recommendations for the axially loaded HSSC-CFST were presented by modifying the design codes in CECS104-99. The proposed model is shown to be able to estimate the axial load-bearing capacity of HSSC-CFST stub columns more accurately.
Research and Application of YOLOv11-Based Object Segmentation in Intelligent Recognition at Construction Sites
Authors: He Luhao , Zhou Yongzhang , Liu Lei , Ma Jianhua
Published: November 2024

With the increasing complexity of construction site environments, robust object detection and segmentation technologies are essential for enhancing intelligent monitoring and ensuring safety. This study investigates the application of YOLOv11-Seg, an advanced target segmentation technology, for intelligent recognition on construction sites. The research focuses on improving the detection and segmentation of 13 object categories, including excavators, bulldozers, cranes, workers, and other equipment. The methodology involves preparing a high-quality dataset through cleaning, annotation, and augmentation, followed by training the YOLOv11-Seg model over 351 epochs. The loss function analysis indicates stable convergence, demonstrating the model’s effective learning capabilities. The evaluation results show an mAP@0.5 average of 0.808, F1 Score(B) of 0.8212, and F1 Score(M) of 0.8382, with 81.56% of test samples achieving confidence scores above 90%. The model performs effectively in static scenarios, such as equipment detection in Xiong’an New District, and dynamic scenarios, including real-time monitoring of workers and vehicles, maintaining stable performance even at 1080P resolution. Furthermore, it demonstrates robustness under challenging conditions, including nighttime, non-construction scenes, and incomplete images. The study concludes that YOLOv11-Seg exhibits strong generalization capability and practical utility, providing a reliable foundation for enhancing safety and intelligent monitoring at construction sites. Future work may integrate edge computing and UAV technologies to support the digital transformation of construction management.
Ultra-Processed Food and Prostate Cancer Risk: A Systemic Review and Meta-Analysis
Authors: Fichtel-Epstein Cayla , Huang Janice , Rich Benjamin James , Taswell Crystal Seldon , Isrow Derek , Jin William
Published: November 2024

Background/Objectives: Prostate cancer is the second leading cause of cancer death among American men, following lung cancer. While diet and exercise have been extensively studied in relation to prostate cancer prevention, the evidence remains inconclusive. Methods: A comprehensive literature search was performed to identify observational studies investigating the association between ultra-processed food (UPF) consumption and prostate cancer risk and mortality, determined by the NOVA classification system. In addition, we conducted subgroup analyses to assess the association based on study design, age, and data collection methods. Results: Six studies were identified, including four cohort studies and two case–control studies. No significant association was found between high UPF consumption and increased risk of prostate cancer [RR = 1.02, 95% confidence interval (CI) = 0.96–1.08, n = 5]. However, there was a slight increase in mortality (RR = 1.15, 95% CI = 0.99–1.35, n = 2). A subgroup analysis by the dietary assessment method revealed an RR of 1.01 (95% CI = 0.93–1.09) for studies using the food frequency questionnaire (FFQ) and 1.04 (95% CI = 0.93–1.16) for studies using 24-h recalls. There was no significant heterogeneity among the studies (I2 = 0, p = 0.82). Conclusions: This meta-analysis suggests no significant association between high UPF consumption and prostate cancer risk. Given the known associations with other chronic diseases, the potential public health implications of reducing UPF consumption remain important. Further research with the use of more robust food assignment systems and more precise dietary assessments is needed to clarify the role of UPF in prostate cancer development.