bluuebunny/crossref_metadata_2025 huggingface dataset:
Study of Volatility Spillover from Crude Oil Futures to Grain Futures Across Multiple Cycles Based on the EEMD-BEKK-GARCH Model
Authors: Wang Xizhao , Pu Mingzhe , Sun Shengxuan , Zhong Yu
Published: January 2025

Against the backdrop of increasing financialization of grain markets, the cross-cycle and cross-market contagion among commodities has been intensifying. To investigate the risk spillover among commodities across different cycles, this study selected UK WTI crude oil and soybean, corn, and wheat futures prices from the Chicago Board of Trade as research subjects. Using ensemble empirical mode decomposition (EEMD), the original sequences were decomposed into sub-sequences of different frequencies. Based on these frequency characteristics, long-term, medium-term, and short-term fluctuations were constructed. The BEKK-GARCH model was then applied to explore the volatility spillover across markets under different cycles. The results indicate that in terms of pricing mechanisms, crude oil futures dominate the price fluctuations of grain futures. In terms of risk spillover across different cycles, there is a bidirectional risk spillover effect between crude oil and grain futures in short-term and medium-term fluctuations, while in long-term fluctuations, there is only a unidirectional transmission from crude oil futures to grain futures. Based on the research findings, this paper proposes relevant policy recommendations, aiming to provide government regulatory authorities and futures investors with policy guidance and a theoretical foundation across different cycles.
Correction: Yang et al. Use Efficiency, Reduction Potential, and Effects of Fertilizers on Carbon Emissions in China’s Major Citrus Regions. Agriculture 2024, 14, 1971
Authors: Yang Yueyuan , Qi Chunjie , Gu Yumeng , Fang Guozhu
Published: January 2025

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Effects of Different Straw Return Methods on Farmland Carbon Footprint and Water Footprint
Authors: Hua Lu , Gao Yang , Li Dingyang , Yang Zhenxing , Liu Zhiping
Published: January 2025

Straw return is an effective agricultural measure that influences the ecological environment. In the context of global climate change and the need for sustainable development, it is essential to explore how straw return methods affect the environment. This study conducted a two-year field experiment comparing different straw return treatments: no straw return (CK), straw return directly (SR), and straw returned in deep ditches (ISR). The results showed that SR treatment increased soil dissolved organic carbon (DOC) (21.7~25.8%) and dissolved organic nitrogen (DON) (8.5~43.8%) compared to CK. The ISR treatment significantly enhanced DOC (13.1~33.0%) and DON (14.2~50.8%). Both SR and ISR treatments also improved maize growth indicators, such as leaf area index (LAI), stem biomass, leaf biomass, and grain biomass. In terms of environmental effects, the ISR measure reduced N2O emissions and significantly lowered the carbon footprint (CF) and water footprint (WF). Specifically, the yield-scale carbon footprint (CFy) and yield-scale water footprint (WFy) of ISR were reduced by 12.0% and 9.1%, respectively, in 2023. Correlation analysis revealed that soil DON and DOC were key factors in these environmental benefits. Furthermore, the reduction in WF and CF was closely linked to the increased SWC and higher biomass in all maize organs. Therefore, we demonstrated that the ISR measure not only promotes maize biomass accumulation but also effectively mitigates carbon emissions and water consumption on farmland. It may be related to the boosting soil DON and DOC levels. Overall, the ISR method holds promise for supporting sustainable farming practices.
Simulation Analysis of Energy Inputs Required by Agricultural Machines to Perform Field Operations
Authors: Paciolla Francesco , Łyp-Wrońska Katarzyna , Quartarella Tommaso , Pascuzzi Simone
Published: January 2025

The evaluation of direct energy inputs and the assessment of the carbon footprint of an agricultural tractor during the execution of an agricultural operation is a complex task. Methodological approaches such as field surveys and life cycle assessments can provide unreliable and non-repeatable results. This study exploits the use of numerical simulation to assess the fuel consumption of two agricultural tractors and their CO2 emissions during the execution of pesticide treatment and milling. The digital models of the Landini REX 4-120 GB and the Fendt 942 Vario were developed, starting from experimental data acquired during field tests in which the power required at the power take-off (PTO) by the respective operating machine was measured. Two custom working cycles, simulating the two agricultural operations, have been defined and simulated. The estimated fuel consumption was 7.8 L∙ha−1 and 23.2 L∙ha−1, respectively, for the Landini REX 4-120 GB during pesticide treatment and for the Fendt 942 Vario during milling. The corresponding direct energy inputs required for the two agricultural operations were equal to 300.3 MJ∙ha−1 and 893.2 MJ∙ha−1, respectively. The estimated carbon footprint was 26.5 kgCO2∙ha−1 and 68.4 kgCO2∙ha−1 for pesticide treatment and for milling, respectively. Moreover, considering the operational efficiency of the systems, an analysis of the available mechanical work supplied by the fuel was conducted.
The Nitrogen Fixation Characteristics of Terrestrial Nitrogen-Fixing Cyanobacteria and Their Role in Promoting Rice Growth
Authors: Wu Lei , Dong Ji , Song Jian , Zhu Yuan , Che Songhao , Qin Xueting , Xu Yufeng , Tian Shiqi , Wang Dongchao , Tian Ping , Wei Xiaoshuang , Yang Xue , Yang Meiying , Wu Zhihai
Published: January 2025

Cyanobacteria, ubiquitous phototrophic prokaryotes, can enhance soil fertility and crop productivity by promoting biological nitrogen fixation, phosphate dissolution, and mineral release. In this study, five nitrogen-fixing cyanobacteria were isolated and purified from paddy soil in Jilin Province. The effects of nitrogen-fixing cyanobacteria on soil fertility and rice seedling growth were examined through a pot experiment to clarify their growth and nitrogen-fixing characteristics. The results showed that the application of nitrogen-fixing cyanobacteria led to a significant increase in soil nitrogen content. GD2 and GD8 have the highest nitrogenase activity, at 75.33 U·mg−1 and 50.34 U·mg−1, respectively. It also enhanced the activities of urease, sucrase, phosphatase, and catalase in rice soil. In addition, it significantly promoted root development and plant height in rice plants. The total number of microorganisms in rice soil increased by 133–366%. Remarkably, the Desmonostoc muscorum GD2 strain was found to exhibit higher growth state indicators, including the growth curve, chlorophyll content, carbon and nitrogen content, and biomass accumulation, compared to other algae strains. The total nitrogen content of rice leaves treated with GD2 increased by 48.73%, and the soluble protein content increased by 52.89%. GD2 has great potential as an excellent nitrogen-fixing cyanobacteria inoculant for rice, suitable for agricultural production. In conclusion, the application of these nitrogen-fixing cyanobacteria significantly increased soil nitrogen levels and activated key enzyme activities involved in plant nitrogen metabolism. Moreover, it improved nitrogen utilization rates and promoted plant growth.
Response of Non-Irrigated Peanut to Multiple Rate Delayed Flumioxazin Applications
Authors: Hurdle Nicholas L. , Grey Timothy L. , Rodrigues Juliana de Souza , Monfort W. Scott
Published: January 2025

Flumioxazin is crucial for peanut weed management across the United States with over 75% of growers applying it to control troublesome weed species. For maximum peanut yield, it is essential that weed control is maintained during weeks three through eight after planting. Peanut injury due to flumioxazin PRE applied has been noted under unfavorable moisture or weather conditions, but also due to delays in application as growers plant hundreds of hectares on their farms. Research in Georgia (GA) investigated the response of non-irrigated peanut to flumioxazin PRE applied from 0 to 107 g ai/ha at 0 to 14 d after planting for cultivar Georgia-16HO. Trends during the 2020 through 2022 growing seasons indicated that as rate and time after planting of application increased, injury increased. Over 50% injury was noted in Tift County and 24% in Sumter County during the 2021 growing season. Peanut pod yield decreased while flumioxazin rate increased and time of application after planting was delayed in Tift County, but no differences were noted in Sumter County, potentially due to soil adsorption of the herbicide. Yield differences of up to 800 kg/ha were noted when comparing no herbicide being applied to the full application rate. The recorded injury coincided with large amounts of rainfall at both locations. It was also noted that peanut may be most sensitive to flumioxazin application injury between days seven and ten after planting.
Design and Optimization of a Lightweight and Simple Self-Propelled Crawler Potato Combine Harvester
Authors: Liu Caichao , Wu Ning , Cheng Guangseng , Wu Feng , Gu Fengwei , Shi Lili , Wang Bing
Published: January 2025

To address the inadequacies of mechanized potato-harvesting equipment on challenging terrains like hills, mountains, and small fields, a lightweight and simple self-propelled crawler potato combine harvester was developed based on the agronomic and harvesting requirements of potato cultivation. The machine consists of key components including a depth-limited soil-crushing device, an auxiliary feeding device, an excavation device, a rubber rod separation device, and a ton bag sorting device. It offers technical advantages such as a lightweight structure, auxiliary feeding and conveying, and manual assistance in sorting ton bags. The key components, such as the auxiliary feeding device, depth-limiting soil-crushing device, and rubber rod separation device, were analyzed theoretically to determine the relevant structures and parameters. Through initial harvesting performance tests, the separation screen line speed, vibration frequency, and device inclination angle were identified as the experimental factors. Evaluation indicators such as potato bruise rate, skin breakage rate, loss rate, and impurity content were chosen, and a three-factor, three-level Box–Behnken optimization test was conducted. The results indicated that with a separation screen line speed of 1 m/s, vibration frequency of 8 Hz, and device inclination angle of 30°, the potato damage rate during harvesting was 1.318%, the skin breakage rate was 1.825%, the loss rate was 2.815%, and the impurity rate was 2.736%. Field tests with the same parameters showed that the potato damage rate, skin breakage rate, loss rate, and impurity rate of the harvester were 1.357%, 1.853%, 2.86%, and 2.748%, respectively, meeting relevant industry technical standards. This research can serve as a reference for enhancing the harvesting performance of potato combine harvesters and ton bag sorting technology.
Effects of Furrow Corn Straw Mulch on Soil Erosion and Organic Carbon Loss in Sloping Farmland in the Black Soil Region
Authors: Shen Haiou , Li Hongli , Liu Hang , Wu Jialong , Li Chunli , Liang Yushi
Published: January 2025

Black soil with high fertility is a valuable soil resource, which plays an important role in guaranteeing regional food security and ecological security. Straw return is also a widely recognized way of straw resource utilization. However, it is still not clear which corn straw return method is more suitable for the Chinese black soil region with cold characteristics. The objectives of this study were to classify rainfall patterns (I—light rain with long duration, II—heavy rain with short duration, III—moderate rain with moderate duration; T1 and T2—special rains) and reveal the effects of furrow corn straw mulch—a new straw return—on soil erosion and organic carbon loss. Natural runoff plots (a planned size of 100 m2 and dimensions of 20 m × 5 m for each one) with or without the furrow corn straw mulch, which had slope gradients of 3°, 6° and 9°, were applied for natural rainfalls. Runoff and sediment samples were collected after each erosive rainfall to measure runoff, sediment, and organic carbon concentration. The results showed that when comparing treatments with the furrow corn straw mulch to control treatments, runoff coefficients, sediment concentration, and mean ratios of organic carbon loss in sediment to total carbon loss decreased by 48.0–97.7%, 45.6–99.7%, and 4.7–12.9%, respectively. Furthermore, the ratios of <0.053 mm sediment increased but the ratios of >0.25 mm sediment generally decreased. The mean organic carbon concentration both in runoff and sediment decreased in the following order: II > III > I > T1 > T2. Rainfall pattern II induced greater ratios of organic carbon loss. Therefore, the furrow corn straw mulch measure, which effectively decreased soil erosion and regulated organic carbon loss from the black soil, is suitable for the farmlands in the black soil regions.
Growth, Yield, and Water Productivity of Potato Genotypes Under Supplemental and Non-Supplemental Irrigation in Semi-Arid Areas of Northern Ethiopia
Authors: Misgina Niguse Abebe , Beshir Hussien Mohammed , Yohannes Derbew Belew , Gebreyohanes Gebre Hadgu
Published: January 2025

Potato is the dominant tuber and root crop grown in Tigray. However, the productivity is very low due to moisture stress, traditional production techniques, and low-yielding varieties. Hence, this study aimed to optimize potato yield by selecting suitable genotypes under both supplemental and non-supplemental irrigation conditions. The study involved five potato genotypes and two irrigation levels used as treatments arranged in a split plot using a randomized complete block design with three replications. Results revealed a significant difference in days to flowering and maturity, marketable and total tuber yield, and water productivity due to the main and interaction effect of genotype and irrigation. CIP-3960478.90 recorded significantly higher marketable yield (27.13 t ha−1), total tuber yield (28.71 t ha−1), and water productivity (7.59 kg m−3) under supplemental irrigation. Genotype CIP-394611.112 had achieved high marketable yield (24.45 t/ha), total yield (25.60 t/ha) and total water productivity (8.51 kg m−3) under non-irrigated treatment. Additionally, the potato water requirements in September and October exceeded the rainfall amounts, suggesting that supplemental irrigation is necessary during this period for optimal yields. Likewise, genotypes CIP-394611.112 and CIP-3960478.90, are recommended for semi-arid areas to enhance tuber yield with or without irrigation.
Study on the Synergistic Regulation Model for Lycium barbarum Berries Under Integrated Irrigation and Fertigation in Northwest Arid Regions
Authors: Ma Yanlin , Lv Huile , Wang Yanbiao , Wang Yayu , Yin Minhua , Kang Yanxia , Qi Guangping , Zhang Rong , Wang Jinwen , Chen Junxian
Published: January 2025

Water resources are fundamental to economic and social development. Improving agricultural water-use efficiency is essential for alleviating water scarcity, ensuring food security, and fostering sustainable growth. This study examines the effects of irrigation levels (severe water deficit, W0: 45–55% θFC; moderate water deficit, W1: 55–65% θFC; mild water deficit, W2: 65–75% θFC; full irrigation, W3: 75–85% θFC) and nitrogen application rates (N0: 0 kg·hm−2, N1: 150 kg·hm−2, N2: 300 kg·hm−2, N3: 450 kg·hm−2) on soil environment, crop yield, and water–nitrogen use efficiencies in Lycium barbarum under integrated water–fertilizer drip irrigation. The coordinated application of water and nitrogen significantly influenced yield and efficiencies (p < 0.05) by modifying rhizosphere conditions such as soil moisture, temperature, salinity, and enzyme activities. Soil temperature increased with nitrogen application (N1 > N2 > N0 > N3), with N1 raising soil temperature by 4.98–8.02% compared to N0, N2, and N3. Electrical conductivity was lowest under N0, showing a 7.53–18.74% reduction compared to N1, N2, and N3. Urease activity peaked under N3 (31.84–96.78% higher than other treatments), while alkaline phosphatase and catalase activities varied across treatments. The yield was highest under N2, at 6.79–41.31% higher than other nitrogen treatments. Water use efficiency (WUE), growth use efficiency (GUE), and nitrogen agronomic efficiency (NAE) peaked under N2, while nitrogen use efficiency (NUE) decreased with higher nitrogen rates. Among irrigation levels, W0 showed the highest soil temperature, while W3 exhibited the lowest conductivity in the 0–40 cm layer. W2 had the highest soil enzyme activities, yielding 4.41–42.86% more than other levels, with maximum efficiencies for WUE, GUE, NUE, and NAE. The combination of mild water deficit (65–75% θFC) and 300 kg·hm−2 nitrogen application (W2N2) resulted in the highest yield (2701.78 kg·hm−2). This study provides key insights for implementing integrated drip irrigation in northwest China’s arid regions.
The Occurrence and Diversity of Viruses Identified in Monocotyledonous Weeds
Authors: Agyemang Evans Duah , Ofosu Rita , Desiderio Francesco , Galbacs Zsuzsanna Nagyne , Takács András Péter , Várallyay Éva
Published: January 2025

In crop fields, weeds are perfect hosts for plant pathogenic viruses. The effects of these viruses can range from latent infection to plant death, affecting crop quality and yield and leading to economic loss in the world. Virus infection threatens cereals used as food for most of the world’s population. Weeds growing in cereal fields can compete for essential supply and act as virus reservoirs, strengthening their deteriorating effect. In this review, we collected the current information on viruses presenting in the most important monocotyledonous weeds: Echinocloa crus-galli, Setaria viridis, Cynodon dactylon, Sorghum halepense and millet species growing as weeds. Identifying plant viruses in monocotyledonous weed hosts provides more information about viral infection flow and guides the development of management strategies for safeguarding our field crops.
A Systematic Review of Opportunities and Limitations of Innovative Practices in Sustainable Agriculture
Authors: Boros Anita , Szólik Eszter , Desalegn Goshu , Tőzsér Dávid
Published: January 2025

A transformation is needed in agricultural production to satisfy the growing population-based increased food demands and overcome food safety challenges while supporting human health and the preservation of natural resources. Improving sustainable agricultural practices is essential for developing a long-term and resilient economy. This systematic review with meta-analyses aims to overview sustainable agriculture’s progress, trends, and future opportunities, focusing primarily on integrating novel technologies into recently prevailing agricultural operations. As a basis, an extensive literature search was conducted, identifying nearly 45,000 records related closely to various dimensions of sustainable agriculture. Out of these, based on a thorough selection process, 291 were included in further evaluations. The temporal distribution and content analyses indicated an improvement in the number of papers and the spectrum of addressed agricultural aspects. The analysis of the publications revealed that most traditional farming practices focus on mass food production and cannot deal with further interrelated sustainability challenges. On the other hand, sustainable agricultural practices consider sustainability’s environmental, economic, and social aspects, thereby preserving environmental health and supporting economic viability and social well-being. The integrative assessment in this study suggests that adopting novel, innovative practices can achieve the most significant progress toward agricultural sustainability. At the same time, a broad range of limitations and challenges are listed, which widely hinder the penetration of sustainability initiatives. To eliminate these barriers, consistent policy regulations are required, targeting specific agricultural problems, alongside a complex, education-based support system, further boosting initiatives related to the green transition in agriculture.
AI-Driven Plant Health Assessment: A Comparative Analysis of Inception V3, ResNet-50 and ViT with SHAP for Accurate Disease Identification in Taro
Authors: Maeda-Gutiérrez Valeria , Oropeza-Valdez Juan José , Reveles-Gómez Luis C. , Padron-Manrique Cristian , Resendis-Antonio Osbaldo , Solís-Sánchez Luis Octavio , Guerrero-Osuna Hector A. , Olvera Olvera Carlos Alberto
Published: January 2025

Early diagnosis and preventive measures are necessary to mitigate diseases’ impact on the yield of Colocasia esculenta (Taro). This study addresses the challenges of Taro disease identification by employing two key strategies: integrating explainable artificial intelligence techniques to interpret deep learning models and conducting a comparative analysis of advanced architectures Inception V3, ResNet-50, and Vision Transformers for classifying common Taro diseases, including leaf blight and mosaic virus, as well as identifying healthy leaves. The novelty of this work lies in the first-ever integration of SHapley Additive exPlanations (SHAP) with deep learning architectures to enhance model interpretability while providing a comprehensive comparison of state-of-the-art methods for this underexplored crop. The proposed models significantly improve the ability to recognize complex patterns and features, achieving high accuracy and robust performance in disease classification. The model’s efficacy was evaluated through multi-class statistical metrics, including accuracy, precision, F1 score, recall, specificity, Chohen’s kappa, and area under the curve. Among the architectures, Inception V3 exhibited superior performance in accuracy (0.9985), F1 score (0.9985), recall (0.9985), and specificity (0.9992). The explainability of Inception V3 was further enhanced using SHAP, which provides insights by dissecting the contributions of individual features in Taro leaves to the model’s predictions. This approach facilitates a deeper understanding of the disease classification process and supports the development of effective disease management strategies, ultimately contributing to improved Taro cultivation practices.
Double-Cropping Systems Based on Maize, Sorghum, and Alfalfa: Impact of Annual Combination on Biomass and Nutritional Yield
Authors: Ji Zhongya , Shi Yu , Jiang Liqiu , Wang Xiaoshan , Zhu Guanglong , Zhou Guisheng
Published: January 2025

Forage crops can be grown in mixed species cultivation to provide productivity and nutritional benefits. In a three-round field test, two double-cropping systems (DCSs) based on maize and sorghum as the summer forage crop and alfalfa as the preceding winter forage crop were compared. There were comparisons of harvesting and growing time, nutritive value, as well as biomass and nutritional yields. The superiority of the M–A (alfalfa following a preceding crop of maize) was identified as compared with the S–A (alfalfa following a preceding crop of sorghum). Within the M–A, the maize Dongdan 60 (M1)–alfalfa WL525 (A) combination under the late sowing condition (D3) achieved the highest annual biomass production (fresh weight and dry weight). The maize/alfalfa combination achieved significantly higher nutritional yields compared to those of the sorghum/alfalfa combination. The highest yield of crude protein was obtained in the late sowing (D3) condition for the maize Dongdan 60 (M1)–alfalfa WL525 (A) combination. The highest yield of starch was obtained in the earliest sowing date (D1) in the maize Dongdan 60 (M1)–alfalfa WL525 (A) combination. The highest yield of crude fat was obtained in the latest sowing date (D3) in the maize Dongdan 1331 (M2)–alfalfa WL525 (A) combination. The study indicated that the winter alfalfa and maize DCS could be a promising strategy to achieve high biomass and nutritional productivity.
Multispectral Inversion of Starch Content in Rice Grains from Yingjiang County Based on Feature Band Selection Algorithms
Authors: Su Xiaotong , Zhao Zhifang , Zeng Min , Zhao Fei , Li Ziyang , Zheng Yu
Published: January 2025

The starch content in rice grains is a key factor in determining their quality. An optimal starch level not only ensures grain fullness, improving storage stability, but also enhances the stickiness and viscosity of cooked rice, thereby boosting its palatability and nutritional value. However, traditional methods for monitoring starch content are expensive and lack the capability to provide rapid spatial distribution information across large areas. To address this limitation, this study focuses on mature rice grains in the Yingjiang region, leveraging multispectral data from the Sentinel-2 satellite. First and second derivative transformations were applied to the multispectral reflectance data, followed by the use of three feature selection algorithms to identify key spectral bands. BP neural networks and ELM neural network regression models were then integrated to quantitatively estimate starch content across the study area. As a result, high-precision spatial distribution maps of starch content were generated, providing a novel and efficient method for large-scale rapid monitoring. The results demonstrate that, compared to full-band data, the use of SPA feature selection significantly improved the predictive accuracy of both BP and ELM models, despite a slight increase in the models’ MSE. Similarly, CARS feature selection also contributed substantially to enhancing the accuracy of the BP and ELM models. In contrast, UVE feature selection significantly reduced the MSE of the BP model, improving predictive precision, with the model achieving an R2 of 0.8061 and an MSE of 0.3896. This study highlights that the inversion method, which combines feature selection algorithms with machine learning models, can effectively enhance the predictive accuracy of starch content estimation. Among the tested approaches, the combination of UVE feature selection and BP neural networks delivered the best performance. These findings confirm the feasibility of utilizing Sentinel-2 satellite multispectral data for the quantitative inversion of agronomic parameters across large agricultural areas, providing robust technical support for precision agriculture.
Efficient Hydrolysis of Sugar Beet Pulp Using Novel Enzyme Complexes
Authors: Komarova Maria I. , Semenova Margarita V. , Volkov Pavel V. , Shashkov Igor A. , Rozhkova Alexandra M. , Zorov Ivan N. , Kurzeev Sergei A. , Satrutdinov Aidar D. , Rubtsova Ekaterina A. , Sinitsyn Arkady P.
Published: January 2025

Sugar beet pulp is a byproduct of white sugar production, and it is quite significant in terms of volume. Every year, tens of millions of tons of beet pulp are produced around the world. However, only a fraction of it is currently used, mainly as animal feed. The composition of beet pulp includes plant polysaccharides, such as cellulose, arabinan, and pectin. Through the process of enzymatic hydrolysis, these polysaccharides are converted into technical C6/C5 sugars, which can be further used as a substrate for the microbial synthesis of various substances, including biofuels, organic acids, and other green chemistry molecules. The current study was designed with a primary objective that focused on the development of a strain that had the potential for enhanced productivity and the capacity to produce enzymes suitable for beet pulp hydrolysis. The pelA and abfA genes, which encode pectin lyase and arabinofuranosidase, respectively, in the fungus Penicillium canescens (VKPM F-178), were cloned and successfully expressed in the recipient strain Penicillium verruculosum B1-537 (VKPM F-3972D). New recombinant strains were created using the expression system of the mycelial fungus P. verruculosum B1-537, which is capable of simultaneously producing pectin lyase and arabinofuranosidase, as well as homologous cellulases. The screening of strains for increased enzymatic activity towards citrus pectin, sugar beet branched arabinan, and microcrystalline cellulose revealed that a B4 clone of P. verruculosum exhibited the greatest potential in sugar beet pulp cake hydrolysis. This clone was selected as the basis for the creation of a new enzyme preparation with enhanced pectin lyase, arabinase, and cellulase activities. The component composition of the enzyme preparation was determined, and the results indicated that the enzyme content comprised approximately 11% pectin lyase, 40% arabinofuranosidase, and 40% cellulases. The primary products of the enzymatic hydrolysis of the unpretreated beet pulp cake were arabinose and glucose. The degree of arabinan and cellulose conversion was observed to be up to 50% and 80%, respectively, after a period of 48 to 72 h of hydrolysis. The new B4 preparation was observed to be highly efficacious in the hydrolysis of beet cake at elevated concentrations of solids (up to 300 g/L) within the reaction mixture. The newly developed strain, as a producer of pectin lyase, arabinofuranosidase, and cellulase complexes, has the potential to be utilized for the bioconversion of sugar beet processing wastes and for the efficient generation of highly concentrated solutions of technical sugars for further implementation in processes of microbial synthesis.
The Impacts and Economic Analysis of Jack Mackerel Meal Inclusion in Low Fish Meal Diets on the Growth and Feed Availability of Juvenile Rockfish (Sebastes schlegeli)
Authors: Sim Yu Jin , Kim June , Cho Sung Hwoan
Published: January 2025

A two-way {dietary substitution source [chicken by-product meal (CBM), meat meal (MM), and tuna by-product meal (TBM)] × substitution level (25% and 50%)} ANOVA experimental design was adopted. The control (Con) diet included 55% FM. In the Con diet, 25% and 50% of FM were substituted with CBM, MM, and TBM, with the inclusion of 22% JMM exhibiting strong attractiveness for rockfish, named CBM25J, CBM50J, MM25J, MM50J, TBM25J, and TBM50J diets, respectively. All experimental diets were assigned to triplicate groups of fish. A total of 525 juvenile fish were distributed into 21 flow-through tanks. The CBM- and TBM-substituted diets achieved greater weight gain and specific growth rates (SGRs) of rockfish than the MM-substituted diets. Moreover, dietary 25% FM substitutions achieved greater weight gain and SGRs of rockfish than dietary 50% FM substitutions. Weight gain and SGRs of rockfish fed the Con, CBM25J, and TBM25J diets were superior to those of rockfish fed the CBM50J, MM50J, and TBM50J diets. Dietary 25% FM substitutions exhibited higher rockfish feed consumption than dietary 50% FM substitutions. None of the proximate compositions, amino and fatty acid profiles, or blood chemistry of the fish were significantly different among dietary treatments. The highest EPI was observed in the CBM25J diet. Conclusively, a 25% FM substitution with CBM, MM, and TBM with the inclusion of 22% JMM in the 55% FM-based diet could be made without reducing the growth and feed consumption of rockfish. Finally, the CBM25J diet produced the highest weight gain and SGRs of rockfish, as well as the highest economic return to farmers.
Detection and Molecular Characterization of Gyrovirus Galga 1 in Chickens in Northern Vietnam Reveals Evidence of Recombination
Authors: Tran Giang Thi Huong , Huynh Le Thi My , Dong Hieu Van , Rattanasrisomporn Amonpun , Kayan Autchara , Bui Dao Anh Tran , Rattanasrisomporn Jatuporn
Published: January 2025

In total, 126 tissue-pooled samples were collected from suspected sick chickens showing signs of stunted growth, weakness, and diarrhea in five provinces/cities in Northern Vietnam. The Gyrovirus gala 1 (GyVg1) genome was detected in 26 (20.63%) of the 126 chicken samples based on a polymerase chain reaction assay. The five Vietnamese GyVg1 genomes obtained were all 2.375 nucleotides in length. Among them, the nucleotide identical rates ranged from 94.01% to 100%. Phylogenetic analysis of the complete genomes revealed that the current five GyVg1 strains belonged to different branches at two levels: GyVg1 II (two of five strains) and GyVg1 III (three of five strains). The Vietnamese GyVg1 strains were generically clustered with the Japanese and Chinese strains. Some amino acid substitutions were found in VPs 1, 2, and 3 of the Vietnamese GyVg1 strains. In addition, three and two positive selection sites of VPs 1 and 3 were detected, respectively. A recombination event occurred and generated a recombination Chicken/Vietnam/AGV/VNUA-TN12/2023 strain. These findings indicate the first evidence of GyVg1 viruses circulating in commercial chicken flocks in Vietnam.
The Application of Structural Reliability and Sensitivity Analysis in Engineering Practice
Authors: Radoń Urszula , Zabojszcza Paweł
Published: January 2025

Standard safety assessments of civil engineering systems are conducted using safety factors. An alternative method to this approach is the assessment of the engineering system using reliability analysis of the structure. In reliability analysis of the structure, both the uncertainty of the load and the properties of the materials or geometry are explicitly taken into account. The uncertainties are described in a probabilistic manner. After defining the ultimate and serviceability limit state functions, we can calculate the failure probability for each state. When assessing structural reliability, it is useful to calculate measures that provide information about the influence of random parameters on the failure probability. Classical measures are vectors, whose coordinates are the first partial derivatives of reliability indices evaluated in the design point. These values are obtained as a by-product of the First-Order Reliability Method. Furthermore, we use Sobol indices to describe the sensitivity of the failure probability to input random variables. Computations of the Sobol indices are carried out using the classic Monte Carlo method. The aim of this article is not to define new sensitivity measures, but to show the advantages of using structural reliability and sensitivity analysis in everyday design practice. Using a simple cantilever beam as an example, we will present calculations of probability failure and local and global sensitivity measures. The calculations will be performed using COMREL modules of the STRUREL computing environment. Based on the results obtained from the sensitivity analysis, we can conclude that in the case of the serviceability limit state, the most significant influence on the results is exerted by variables related to the geometry of the beam under consideration. The influence of changes in Young’s modulus and load on the probability of failure is minimal. In further calculations, these quantities can be treated as deterministic. In the case of the ultimate limit state, the influence of changes in the yield strength is significant. The influence of changes in the load and length of the beam is significantly smaller. The authors present two alternative ways of designing with a probabilistic approach, using the FORM (SORM) and Monte Carlo simulation. The approximation FORM cannot be used in every case in connection with gradient determination problems. In such cases, it is worth using the Monte Carlo simulation method. The results of both methods are comparable.
Analysis of the Performance of Different Types of PV Panels in Spring and Summer Using Regression Methods
Authors: Kılıç Salim , Adıgüzel Ertuğrul , Atmaca Erkan
Published: January 2025

The present study employs machine learning regression analyses to investigate the efficiency of photovoltaic (PV) panels utilizing solar energy under the influence of environmental factors. The experimental study was conducted on two 100-watt monocrystalline and two polycrystalline PV panels, which were divided into clean and dirty groups. The following variables were monitored and recorded for a period of six months: radiation, panel temperature, air temperature, wind speed, humidity, pressure, and ultraviolet (UV) radiation. Additionally, current, voltage, and power were recorded. These measurements were taken during the production of energy by PV panels. Monocrystalline PV panels exhibited an 8.6% increase in energy efficiency, while polycrystalline PV panels demonstrated a 6.2% increase, following the collection and cleaning of data in accordance with the IEC 61724 standard. Six distinct machine learning regression analyses were conducted on the dataset. The results were compared using the Root Mean Square Error (RMSE) and the coefficient of determination (R2). The Random Forest model demonstrated the greatest predictive success, while the Support Vector Regression (SVR) model exhibited the lowest performance.
Air Pollution and COPD: Unveiling Hidden Risks of Mortality, Mechanical Ventilation, and Prolonged Hospitalization
Authors: Javorac Jovan , Živanović Dejan , Ilić Miroslav , Milenković Ana , Vujičić Emilija , Kovačević Dragica , Zvekić-Svorcan Jelena , Mikić Darko , Stojkov Svetlana , Bačevac Eminović Jasminka , Jevtić Marija
Published: January 2025

While the impact of air pollution on acute exacerbations of chronic obstructive pulmonary disease (AECOPD) has been widely studied, its effect on hospitalization outcomes remains less explored. This study examines the influence of short-term air pollution exposure on adverse hospitalization outcomes—mortality, mechanical ventilation use, and prolonged hospitalization—in patients with non-infectious severe AECOPD in Novi Sad, Serbia. Using a five-year time-series analysis, concentrations of selected air pollutants (PM10, PM2.5, SO2, and NO2) and meteorological data were integrated with hospitalization outcomes. Distributed lag non-linear models (DLNMs) revealed significant associations between rising air pollutant levels and some unfavorable outcomes. Exposure to rising PM2.5 (urban background) and SO2 (urban traffic) concentrations were linked to higher risks of mechanical ventilation (cumulative OR 21.95 (95% CI 1.07–449.45) and 11.37 (95% CI 1.25–103.27), respectively) and prolonged non-infectious AECOPD hospitalization (cumulative RR 2.27 (95% CI 1.14–4.52) and 2.24 (95% CI 1.38–3.64), respectively). No cumulative lag effects on mortality were observed, though specific patterns emerged in individual lag models. These findings highlight the critical role of improving air quality in reducing some COPD-related hospitalization risks.
Analytical Relations and Statistical Estimations for Sums of Powered Integers
Authors: Lipovetsky Stan
Published: January 2025

Finding analytical closed-form solutions for the sums of powers of the first n positive integers is a classical problem of number theory. Analytical methods of constructing such sums produce complicated formulae of polynomials of a higher order, but they can be presented via the first two power sums. The current paper describes new presentations of the power sums and their extensions from polynomial to algebraic functions. Particularly, it shows that power sums of any higher order can be expressed just by a value of the arithmetic progression of the first power sum, or by the second power sum, or approximately by any another power sum. Regression modeling for the estimation of the powered sums is also considered, which is helpful for finding approximate values of long sums for big powers. Several problems based on the relations between sums of different powers in explicit forms are suggested for educational purposes.
Group-Valued Multisets
Authors: Alexandru Andrei , Ciobanu Gabriel
Published: January 2025

Hybrid sets are defined as multisets having also negative multiplicities, i.e. as functions from a crisp set to the group of all integers. In this article, we introduce a significant advancement in hybrid sets through the concept of group-valued multisets. These multisets map elements of a set X to an arbitrary group, ensuring that each multiplicity has an inverse. This framework allows us to explore deeper relationships and correlations among the multiplicities of the elements within X. By involving the finitely supported sets, we study the new defined group-valued multisets over infinite universes of discourse in a finitary manner. After presenting the algebraic groups in the framework of finitely supported sets, we study the finitely supported group-valued multisets. We provide a finitary characterization of group-valued multisets over infinite universes of discourse, and obtain new results that generalize the properties of hybrid sets obtained in the Zermelo–Fraenkel framework.
Acoustic Emission Technique for Battery Health Monitoring: Comprehensive Literature Review
Authors: Sedláčková Eliška , Pražanová Anna , Plachý Zbyněk , Klusoňová Nikola , Knap Vaclav , Dušek Karel
Published: January 2025

The rapid adoption of electric vehicles (EVs) has increased the demand for efficient methods to assess the state of health (SoH) of lithium-ion batteries (LIBs). Accurate and prompt evaluations are essential for safety, battery life extension, and performance optimization. While traditional techniques such as electrochemical impedance spectroscopy (EIS) are commonly used to monitor battery degradation, acoustic emission (AE) analysis is emerging as a promising complementary method. AE’s sensitivity to mechanical changes within the battery structure offers significant advantages, including speed and non-destructive assessment, enabling evaluations without disassembly. This capability is particularly beneficial for diagnosing second-life batteries and streamlining decision-making regarding the management of used batteries. Moreover, AE enhances diagnostics by facilitating early detection of potential issues, optimizing maintenance, and improving the reliability and longevity of battery systems. Importantly, AE is a non-destructive technique and belongs to the passive method category, as it does not introduce any external energy into the system but instead detects naturally occurring acoustic signals during the battery’s operation. Integrating AE with other analytical techniques can create a comprehensive tool for continuous battery condition monitoring and predictive maintenance, which is crucial in applications where battery reliability is vital, such as in EVs and energy storage systems. This review not only examines the potential of AE techniques in battery health monitoring but also underscores the need for further research and adoption of these techniques, encouraging the academic community and industry professionals to explore and implement these methods.
Antioxidant, Antiproliferative, Antibacterial, and Antimalarial Effects of Phenolic-Rich Green Tea Kombucha
Authors: Lacerda Udielle Vermelho , da Costa Carolina Vargas Pereira , Cardoso Rodrigo Rezende , D’Almeida Carolina Thomaz dos Santos , do Carmo Mariana Araújo Vieira , Lima Amanda dos Santos , Cruz Laura da Silva , de Souza Amanda Bubula , Fernandes Philipe Oliveira , Maltarollo Vinícius Gonçalves , Ferreira Mariana Simões Larraz , Azevedo Luciana , Eller Monique Renon , Corich Viviana , Giacomini Alessio , Barros Frederico Augusto Ribeiro de
Published: January 2025

Green tea kombucha, produced using a green tea (Camellia sinensis) grown in Brazil, was characterized and its in vitro bioactive properties were evaluated. Overall, 92 phenolic compounds were identified (70.7% flavonoids, 25% phenolic acids, 2.2% lignans, and 1.1% other polyphenols), contributing to the observed high antioxidant capacity. The major phenolics identified were gallocatechin, catechin 5-O-gallate, and epicatechin. Green tea kombucha exhibited antibacterial activity against all tested bacteria, being more effective against Salmonella spp. In addition, green tea kombucha demonstrated antimalarial activity against both chloroquine-sensitive and chloroquine-resistant strains of Plasmodium falciparum, and antiproliferative activity against cancer cell lines A549, HCT8, HepG2, and HUVEC. Additionally, it presented antioxidant properties by effectively reducing the generation of reactive oxygen species (ROS) and provided protection to erythrocytes against AAPH-induced oxidative stress. Thus, green tea kombucha is abundant in antioxidants and possesses intriguing bioactive properties that can be investigated by both the food and pharmaceutical sectors.
Role of B-Cell Lymphoma/Leukemia 11A in Normal and Malignant Hematopoiesis
Authors: Zhang Haihang , Zeng Junhao , Zhang Fangling , Liu Jing , Liang Long
Published: January 2025

B-cell lymphoma/leukemia 11A (BCL11A) is a crucial transcriptional regulator, widely recognized for its role in controlling fetal hemoglobin and its potential as a gene therapy target for inherited hemoglobinopathies. Beyond this, recent studies have also highlighted its key role in the maturation and function of immune cells and erythrocytes, mediated through the regulation of various molecules during hematopoietic development. The dysregulation of BCL11A disrupts downstream molecular pathways, contributing to the development of several hematological malignancies, particularly leukemias. This review provides a comprehensive overview of the role of BCL11A in normal and malignant hematopoiesis, details the hematological disorders associated with its dysregulation and explores the current therapeutic strategies targeting this transcription factor.
Persistent Health and Cognitive Impairments up to Four Years Post-COVID-19 in Young Students: The Impact of Virus Variants and Vaccination Timing
Authors: Latifi Ashkan , Flegr Jaroslav
Published: January 2025

Background: The long-term consequences of COVID-19 infection are becoming increasingly evident in recent studies. This repeated cross-sectional study aimed to explore the long-term health and cognitive effects of COVID-19, focusing on how virus variants, vaccination, illness severity, and time since infection impact post-COVID-19 outcomes. Methods: We examined three cohorts of university students (N = 584) and used non-parametric methods to assess correlations of various health and cognitive variables with SARS-CoV-2 infection, COVID-19 severity, vaccination status, time since infection, time since vaccination, and virus variants. Results: Our results suggest that some health and cognitive impairments may persist, with some even appearing to progressively worsen—particularly fatigue in women and memory in men—up to four years post-infection. The data further indicate that the ancestral SARS-CoV-2 variant may have the most significant long-term impact, while the Omicron variant appears to have the least. Interestingly, the severity of the acute illness was not correlated with the variant of SARS-CoV-2. The analysis also revealed that individuals who contracted COVID-19 after vaccination had better health and cognitive outcomes compared to those infected before vaccination. Conclusions: Overall, our results indicate that even in young individuals who predominantly experienced only mild forms of the infection, a gradual decline in health and fitness can occur over a span of four years post-infection. Notably, some negative trends—at least in men—only began to stabilize or even reverse during the fourth year, whereas in women, these trends showed no such improvement. These findings suggest that the long-term public health impacts of COVID-19 may be more severe and affect a much broader population than is commonly assumed.