bluuebunny/crossref_metadata_2025 huggingface dataset:
The rDNA Diversity, Interseasonal Dynamic, and Functional Role of Cyanobacteria Synechococcus in the Sub-Arctic White Sea
Authors: Belevich Tatiana A. , Milyutina Irina A. , Vorob’eva Olga V. , Troitsky Aleksey V.
Published: November 2024

Planktonic unicellular cyanobacteria are the dominant biomass producers and carbon fixers in the global ocean ecosystem, but they are not abundant in polar seawater. The interseasonal dynamics of picocyanobacterial (PC) abundance, picophytoplankton primary production, and phylogenetic diversity of PC Synechococcus were studied in the sub-Arctic White Sea. The PC abundance varied from 0.2–0.3 × 106 cells/L in February to 5.2–16.7 × 106 cells/L in July. Picophytoplankton primary production ranged from 0.22 mg C/m3 per day in winter to 11.32 mg C/m3 per day in summer. Synechococcus abundance positively correlated with water temperature and river discharge that increased in recent years in the White Sea. Phylogenetic analysis of the 16S rRNA gene and ITS region clone libraries from the White Sea and Barents Sea eDNA revealed picocyanobacterial sequences related to marine Synechococcus subclusters 5.1-I, 5.I-IV, 5.2, and 5.3. All Synechococcus S5.1-I were common in the White and Barents seas and were consistently present in the picophytoplankton composition throughout the year. Synechococcus S5.2 and S5.3 appear in the PC community in summer, suggesting their river origin, and Synechococcus S5.1-IV inhabits only the Barents Sea and was not detected in the White Sea. A unique Synechococcus phylotype was revealed. It is expected that the increase in the abundance of PC and their increasing role in ecosystem functioning, as well as the enrichment of the species composition with new phylotypes in the semi-enclosed sub-Arctic White Sea, which is vulnerable to the effects of climate change, will be characteristic of all Arctic seas in general.
Ecological Aspects of Distribution and Population Status Assessment of Rhamnus erythroxyloides subsp. sintenisii (Rich.f) Mabb., a Relict Species in the Kyzylkum Desert of Uzbekistan
Authors: Shomurodov Khabibullo , Adilov Bekhzod , Rudov Alexander , Sharipova Vasila , Abduraimov Ozodbek , Khayitov Rizamat , Khabibullaev Bekhruz
Published: November 2024

Rhamnus erythroxyloides subsp. sintenisii (Rech.f.) Mabb. is a relict species occurring on the remnant mountains of Kyzylkum (in Uzbekistan). Up until recently, its population status and exact distribution remained unassessed. The ecological distribution and population status of four populations of Rh. erythroxyloides subsp. sintenisii were studied. The study of its morpho-anatomical structure revealed that the studied taxon’s vegetative and generative organs demonstrate clear adaptive features to arid climate. We observed an absence of the young fraction (seedlings and juvenile plants) in the populations, which is related to irregularity of seed renewal. Furthermore, population fragmentation due to a high degree of soil salinity and the presence of organic matter has been noticed at the present stage. According to the combination of threatening factors, the current state of the population of Rh. erythroxyloides subsp. sintenisii in Uzbekistan has been estimated as disappearing (EN)—B2ab (ii, iii, iv) + C1 + E.
Essential Oil Composition and Physiology of Three Mentha Genotypes Under Shaded Field Conditions
Authors: Hubert-Schöler Charlotte , Tsiaparas Saskia , Luhmer Katharina , Moll Marcel Dieter , Passon Maike , Wüst Matthias , Schieber Andreas , Pude Ralf
Published: November 2024

Mentha spp. are commonly used for the production of tea and for the extraction of essential oils (EOs). The key factor of mint quality is the content and composition of the EO. Health-promoting compounds such as menthol are desirable, whereas the presence of potentially health-damaging compounds such as menthofuran should be avoided. This study examines the effect of shading on the EO content and composition of three Mentha genotypes (Mentha × piperita ‘Multimentha’, Mentha × piperita ‘Fränkische Blaue’ and Mentha rotundifolia ‘Apfelminze’). The Mentha genotypes were cultivated in field trials for two years (2022–2023). Each genotype was shaded with a shading net (50% photosynthetic active radiation (PAR) reduction), and a control without shading was prepared. EO content was determined by steam distillation and EO composition was characterized by GC-MS analysis. Furthermore, biomass, vegetation indices (VIs) and the electron transport rate (ETR) were analyzed. While shading led to higher plant heights, higher EO content and a slightly reduced amount of undesired EO compounds, the unshaded control yielded a higher biomass accumulation. Significant genotypic differences were determined. In conclusion, the benefits of shading depend on the intended use and genotype selection.
Resistance in Soybean Against Infection by Phakopsora pachyrhizi Is Induced by a Phosphite of Nickel and Potassium
Authors: Fontes Bianca Apolônio , Silva Leandro Castro , Picanço Bárbara Bezerra Menezes , Barros Aline Vieira , Leal Isabela Maria Grossi , Quadros Leonardo Packer , Rodrigues Fabrício Ávila
Published: November 2024

Soybean (Glycine max (L.) Merr.) is one of the most profitable crops among the legumes grown worldwide. The occurrence of rust epidemics, caused by Phakopsora pachyrhizi, has greatly contributed to yield losses and an abusive use of fungicides. Within this context, this study investigated the potential of using a phosphite of nickel (Ni) and potassium (K) [referred to as induced resistance (IR) stimulus] to induce soybean resistance against infection by P. pachyrhizi. Plants were sprayed with water (control) or with IR stimulus and non-inoculated or inoculated with P. pachyrhizi. The germination of urediniospores was greatly reduced in vitro by 99% using IR stimulus rates ranging from 2 to 15 mL/L. Rust severity was significantly reduced from 68 to 78% from 7 to 15 days after inoculation (dai). The area under the disease progress curve significantly decreased by 74% for IR stimulus-sprayed plants compared to water-sprayed plants. For inoculated plants, foliar concentrations of K and Ni were significantly higher for IR stimulus treatment than for the control treatment. Infected and IR stimulus-sprayed plants had their photosynthetic apparatus (a great pool of photosynthetic pigments, and lower values for some chlorophyll a fluorescence parameters) preserved, associated with less cellular damage (lower concentrations of malondialdehyde, hydrogen peroxide, and anion superoxide) and a greater production of phenolics and lignin than plants from the control treatment. In response to infection by P. pachyrhizi, defense-related genes (PAL2.1, PAL3.1, CHIB1, LOX7, PR-1A, PR10, ICS1, ICS2, JAR, ETR1, ACS, ACO, and OPR3) were up-regulated from 7 to 15 dai for IR stimulus-sprayed plants in contrast to plants from the control treatment. Collectively, these findings provide a global picture of the enhanced capacity of IR stimulus-sprayed plants to efficiently cope with fungal infection at both biochemical and physiological levels. The direct effect of this IR stimulus against urediniospores’ germination over the leaf surface needs to be considered with the aim of reducing rust severity.
Understanding the Influence of Secondary Metabolites in Plant Invasion Strategies: A Comprehensive Review
Authors: Akbar Rasheed , Sun Jianfan , Bo Yanwen , Khattak Wajid , Khan Amir , Jin Cheng , Zeb Umar , Ullah Najeeb , Abbas Adeel , Liu Wei , Wang Xiaoyan , Khan Shah , Du Daolin
Published: November 2024

The invasion of non-native plant species presents a significant ecological challenge worldwide, impacting native ecosystems and biodiversity. These invasive plant species significantly affect the native ecosystem. The threat of invasive plant species having harmful effects on the natural ecosystem is a serious concern. Invasive plant species produce secondary metabolites, which not only help in growth and development but are also essential for the spread of these plant species. This review highlights the important functions of secondary metabolites in plant invasion, particularly their effect on allelopathy, defense system, interaction with micro soil biota, and competitive advantages. Secondary metabolites produced by invasive plant species play an important role by affecting allelopathic interactions and herbivory. They sometimes change the soil chemistry to make a viable condition for their proliferation. The secondary metabolites of invasive plant species inhibit the growth of native plant species by changing the resources available to them. Therefore, it is necessary to understand this complicated interaction between secondary metabolites and plant invasion. This review mainly summarizes all the known secondary metabolites of non-native plant species, emphasizing their significance for integrated weed management and research.
Parental Reconstruction from a Half-Sib Population of Stoneless Jujube Ziziphus jujuba Mill. Based on Individual Specific SNP Markers Using Multiplex PCR
Authors: Tahir Muhammad , Ren Yue , Wu Bo , Li Meiyu , Refaiy Mohamed , Cao Ming , Kong Decang , Pang Xiaoming
Published: November 2024

The selection of unique and individual-specific SNPs is important as compared with universal SNPs for individual identification. Therefore, the main significance of this research is the selection of specific SNPs in male parent and the identification of offspring with these specific SNPs in their genome by multiplex PCR, which is utilized for genotyping of 332 half-sib plants of Ziziphus jujuba.This cost-effective method makes as much as possible to utilize the same amount of each pair of various targeted loci primers. After PCR amplification of targeted genome parts, the mixed products can be directly used in a next-generation sequencing platform. We concomitantly amplified 10 unique SNP loci at 10 different chromosomes of male JingZao 39 plants in 332 half-sib plants and sequenced them on the Illumina Novaseq 6000 platform. Analysis of SNP genotyping accuracy of 332 half-sib plants showed that all 10 unique SNPs in all 332 plants were correctly amplified in this multiplex PCR method. Furthermore, based on Mendelian inheritance, we identified 124 full-sib plants that have 10 unique SNPs in their genomes. These results were further confirmed by whole genome resequencing of 82 randomly selected half-sib plants, and the identity-by-descent values of all full-sib plants were between 0.4399 to 0.5652. This study displayed a cost-effective multiplex PCR method and proper identification of pollen parent through specific SNPs in half-sib progenies and firstly obtained a full-sib population between ‘Wuhezao’ and ‘JingZao 39’, segregating for stone and stoneless fruit.
Characterization, Genome Sequencing, and Development of a Rapid PCR Identification Primer for Fusarium oxysporum f. sp. crocus, a New forma specialis Causing Saffron Corm Rot
Authors: Rong Zhenyu , Ren Tingdan , Yue Junji , Zhou Wei , Liang Dong , Zhang Chuanqing
Published: November 2024

Saffron corm rot (SCR), the most serious disease affecting saffron, has been confirmed to be caused by Fusarium oxysporum in previous studies. Compared to other fungal species, F. oxysporum exhibits host specialization, a special phenomenon associated with the secreted in xylem (SIX) genes. This study examined the pathogenicity specialization of F. oxysporum isolated from saffron corms with SCR disease. The results showed that this F. oxysporum strain was strongly pathogenic to saffron corms, causing SCR; weakly pathogenic to the corms of freesia, which is in the Iridaceae family along with saffron; and not pathogenic to watermelon, melon, and tomato. Other formae speciales of F. oxysporum were not pathogenic to saffron corms. This suggests that F. oxysporum saffron strains exhibit obvious pathogenicity specialization for Iridaceae spp. Subsequently, the F. oxysporum saffron strain (XHH35) genome was sequenced, and a comparative genomics study of XHH35 and three other formae speciales was conducted using OrthoVenn3. XHH35 contained 90 specific genes absent in the other three formae speciales. These genes are involved in certain key biological processes and molecular functions. Based on BLAST homology searching, the F. oxysporum saffron strain (XHH35) genome was predicted to contain seven SIX genes (SIX 4, SIX 6, SIX 7, SIX 10, SIX 11, SIX 12, and SIX 14) highly homologous to F. oxysporum f. sp. lycopersici, which was verified using polymerase chain reaction (PCR) amplification. The corresponding individual phylogenetic tree indicated that the F. oxysporum saffron strain (XHH35) showed a separate branch with different formae speciales. This study is the first-ever report of F. oxysporum f. sp. crocus, a new forma specialis. Based on the specificity of its SIX genes, the SIX 10 gene was selected to further establish a rapid identification technique for F. oxysporum f. sp. crocus, which will be useful in future research.
Effect of Compound Fertilizer on Foxtail Millet Productivity and Soil Environment
Authors: Duan Yanyan , Wang Chenyang , Li Lizhi , Han Ruihua , Shen Xiao , Han Genlan , Wang Jiang , Nie Mengen , Zhou Xinlei , Du Huiling , Yuan Xiangyang , Dong Shuqi
Published: November 2024

The effects of balanced fertilization with nitrogen, phosphorus, and potassium (NPK) on foxtail millet productivity and the soil environment under the same conditions of total nutrients have received limited research attention. Therefore, in this study, three balanced fertilization patterns of 27-14-10 (T1), 27-17-7 (T2), and 30-10-11 (T3), and one no fertilization treatment (CK), a total of four treatments, were set up through a two-year field experiment to study the effects of balanced fertilization patterns on foxtail millet yield and soil environment. Mantel analysis was conducted to reveal the correlation between soil environmental factors and the community and their contribution to productivity. The results showed that: (1) all balanced fertilization treatments significantly increased foxtail millet yield, with the highest yield in the T1 treatment. (2) The contents of EC, available K, available P, and alkaline-hydrolyzable nitrogen in the soil of the two-year TI treatments were higher than those of the other treatments and increased by 7.20–9.36%, 24.87–52.35%, 55.83–56.38%, and 21.05–43.95%, respectively, compared with CK. (3) Soil urease activity in the T1 treatment increased significantly by 26.67% and 9.00% compared with the control over the two years. Sucrase activity increased by 36.27% and 23.88% in the T1 treatment compared to CK, and glutaminase activity increased by 33.33% and 19.23% in the T1 treatment compared to CK. (4) T1 treatment significantly increased the OUT number and diversity index of the soil bacterial community. (5) Mantel analysis and principal component analysis showed that available soil nutrients and soil enzymes were positively correlated, and soil enzymes and soil nutrients contributed more to foxtail millet productivity. In this study, the 27-14-10 balanced fertilization pattern was more effective, providing a theoretical basis for the research and development of special fertilizers for foxtail millet and offering technical guidance for realizing the light simplified cultivation of foxtail millet and sustainable development of cost–saving and increased efficiency.
Influence of Microbial Treatments on Vine Growth and Must Quality: Preliminary Results
Authors: Mercanti Nicola , Macaluso Monica , Pieracci Ylenia , Bertonelli Leonardo , Flamini Guido , Zinnai Angela
Published: November 2024

Microorganisms play a crucial role in addressing the challenges related to the increasing detrimental effects of intensive agriculture in vineyards by contributing to various aspects, from maintaining soil health and vine vitality to influencing fermentation and the overall wine features. Among microorganisms, mycorrhizal fungi are widely distributed in both natural and agricultural ecosystems, and their mutually beneficial relationship with most terrestrial plants provides valuable ecological benefits. Nowadays, the wine industry is increasingly moving toward the production of organic wines, highlighting the need for novel and healthier strategies that prioritize both the consumer well-being and the quality of the final wine product. Following our previous study in collaboration with the Bioma SA Company (Quartino, Switzerland), the investigation was continued by extending the organic practice to the cultivation. The present work, indeed, aimed to evaluate the influence of the treatment with mycorrhizal fungi on the metabolism of “Sangiovese” grapevines. In particular, the chemical parameters, including alcohol content, pH, acidity, phenolic composition, and sulfur dioxide, were assessed on the must, while the analysis of the volatile emission was conducted both on whole and pressed grapes, on must, as well as on the grape skins. To the best of our knowledge, this is the first study investigating the mycorrhizal fungi association effect on the quality of “Sangiovese” grapes and, further, its effect on the VOCs emission.
Genetics and Distribution of the Italian Endemic Campanula fragilis Cirillo (Campanulaceae)
Authors: De Luca Daniele , Del Guacchio Emanuele , Cennamo Paola , Minutillo Francesco , Bernardo Liliana , Caputo Paolo
Published: November 2024

Campanula fragilis Cirillo is a species distributed in central and southern Italy and includes two subspecies with uncertain taxonomic position and distribution. By means of nuclear and chloroplast markers, we attempted at testing the genetic distinctness of the two subspecies, as well as their possible correspondence with geographical or ecological patterns. After a revision of geographic occurrences based on herbarium data, we carried out species distribution modeling to assess the present and future distribution of this species under different ecological variables, also for conservation purposes. Our findings support the recognition of two weakly differentiated taxa, here accepted at subspecific rank, in agreement with the current taxonomic treatment. We found that C. fragilis subsp. cavolinii is monophyletic and limited to mountains and hills of central Italy. On the contrary, C. fragilis subsp. fragilis shows a higher genetic variability and a broader distribution in central and southern Italy, with a wider altitudinal range from coasts to mountain cliffs. We confirmed that both subspecies are narrowly calcicolous and have similar ecological requirements, but C. fragilis subsp. cavolinii occurs in colder habitats. Our results forecast a significant distribution contraction in the long term.
Improvement in an Analytical Approach for Modeling the Melting Process in Single-Screw Extruders
Authors: Knaup Felix , Brüning Florian , Schöppner Volker
Published: November 2024

Most single-screw extruders used in the plastics processing industry are plasticizing extruders, designed to melt solid pellets or powders within the screw channel during processing. In many cases, the efficiency of the melting process acts as the primary throughput-limiting factor. If the material melts too late in the process, it may not be sufficiently mixed, resulting in substandard product quality. Accurate prediction of the melting process is therefore essential for efficient and cost-effective machine design. A practical method for engineers is the modeling of the melting process using mathematical–physical models that can be solved without complex numerical methods. These models enable rapid calculations while still providing sufficient predictive accuracy. This study revisits the modified Tadmor model by Potente, which describes the melting process and predicts the delay-zone length, extending from the hopper front edge to the point of melt pool formation. Based on extensive experimental investigations, this model is adapted by redefining the flow temperatures at the phase boundary and accounting for surface porosity at the beginning of the melting zone. Additionally, the effect of variable solid bed dynamics on model accuracy is examined. Significant model improvements were achieved by accounting for reduced heat flow into the solid bed due to the porous surface structure in the solid conveying zone, along with a new assumption for the flow temperature at the phase boundary between the solid bed and melt film.
Polymeric Materials in Energy Conversion and Storage
Authors: Kumar Vineet , Alam Md Najib
Published: November 2024

Energy conversion and storage devices based on polymeric materials are emerging as a promising avenue for renewable power sources [...]
Design and Optimization of PEDOT/Graphene Oxide and PEDOT/Reduced Graphene Oxide Electrodes to Improve the Performance of Microbial Fuel Cells, Accompanied by Comprehensive Electrochemical Analysis
Authors: Arteaga-Arroyo Gean , Ramos-Hernández Andrea , De Los Reyes-Rios Aldeir , Méndez-López Maximiliano , Pastor-Sierra Karina , Insuasty Daniel , Marquez Edgar , Fals Jayson
Published: November 2024

A comprehensive investigation into the design and electrochemical optimization of composite electrodes consisting of poly(3,4-ethylenedioxythiophene) (PEDOT)/graphene oxide (GO)/Methanococcus deltae and reduced graphene oxide (rGO)/Methanococcus deltae hybrids, anchored onto stainless-steel (SS) substrates, has been conducted. The GO and rGO materials were synthesized using a modified Hummer method. The resulting SS/PEDOT/GO and SS/PEDOT/rGO composite electrodes were subjected to systematic electrochemical characterization, focusing on the PEDOT p-type and n-type doping/undoping processes within diverse solvent environments (CH3CN and H2O) and electrolyte compositions (LiClO4 and KCl). Raman spectroscopy analysis confirmed the successful integration of graphene derivatives into the electrode structures, while field-emission scanning electron microscopy (FESEM) and atomic force microscopy (AFM) revealed increased surface roughness upon GO and rGO incorporation. This increase in surface roughness is believed to enhance the adhesion of Methanococcus deltae microorganisms and facilitate efficient electron transport. Electrochemical measurements showed that the resulting SS/PEDOT/GO and SS/PEDOT/rGO anodes exhibit remarkable electrocatalytic activity. The SS/PEDOT/GO electrode achieved a maximum power density of 1014.420 mW/cm2, while the SS/PEDOT/rGO electrode reached 632.019 mW/cm2.
Developing and Characterizing a Biocompatible Hydrogel Obtained by Cross-Linking Gelatin with Oxidized Sodium Alginate for Potential Biomedical Applications
Authors: Mahmoudi Chahrazed , Tahraoui Douma Naïma , Mahmoudi Hacene , Iurciuc (Tincu) Camelia Elena , Popa Marcel , Hamcerencu Mihaela , Andrițoiu Călin Vasile
Published: November 2024

The main goal of this research was to create biocompatible hydrogels using gelatin and a double cross-linking technique involving both covalent and ionic bonds to immobilize propolis. The covalent bonds were formed through Schiff base cross-links between protein-free amino groups (NH2) from the lysine residue and aldehyde groups (CHO) produced by oxidizing sodium alginate with NaIO4, while the ionic bonds were achieved using Mg2+ ions. Hydrogel films were obtained by varying the molar ratios of –CHO/–NH2 under different pH conditions (3.5 and 5.5). The presence of aldehyde groups in the oxidized sodium alginate (OSA) was confirmed using FTIR and NMR spectroscopy. The oxidation degree was monitored over 48 h, and the influence of temperature was examined. Results showed that higher –CHO/–NH2 molar ratios led to increased conversion index values of NH2 groups, and a decrease in swelling degree values was observed in mediums with pH values of 5.5 and 7.4. The encapsulation and release efficiency of propolis decreased with an increase in the hydrogel cross-linking degree. UV irradiation enhanced the antioxidant activity of both free and encapsulated propolis. These findings offer valuable insights for the biomedical and pharmaceutical fields into designing biocompatible hydrogels for propolis immobilization, with potential for controlled release.
Characteristics of Solid Mineral Phase Transitions During Sulfuric Acid Production from Gaseous-Sulphur-Reduced Gypsum
Authors: Wen Tianqi , Chen Yanxin , Zhao Bo
Published: November 2024

The acid co-production of cement is a prominent research focus for the large-scale, high-value utilization of phosphogypsum in the context of dual-carbon strategies. This paper builds on extensive research conducted by its authors on the co-production of sulphoaluminate cement clinker through acid production from gaseous-sulphur-reduced phosphogypsum. The solid mineral phase transformations occurring in the kiln during this process are systematically studied, and the effects of various calcination regimes (temperature, time, and atmosphere) on the evolution of clinker mineral phases are elucidated. This paper provides basic data support for the gas-sulfur-reduced phosphogypsum-acid cogeneration of sulfoaluminate cement clinker processes, and promotes the realization of the large-scale high-value utilization of phosphogypsum resources. The generation of the clinker mineral phase anhydrous calcium sulphoaluminate (C4A3S̅) begins at 1100 °C. Increasing the calcination temperature and extending the calcination time promote C4A3S̅ formation. However, when the calcination temperature exceeds 1350 °C, C4A3S̅ decomposes, leading to the formation of low-activity C2AS. In a CO atmosphere, the main mineral phases in the clinker transform into C2AS and 12CaO·7Al2O3, owing to the decomposition of CaSO4, which inhibits C4A3S̅ formation. At calcination temperatures exceeding 1300 °C, a significant amount of C2AS appears in the calcined material, and 12CaO·7Al2O3 begins to form.
Application of Machine Learning for the Prediction of Absorption, Distribution, Metabolism and Excretion (ADME) Properties from Cichorium intybus Plant Phytomolecules
Authors: Afzal Ayesha Hena , Alam Ozair , Zafar Sherin , Alam Mohammad Afshar , Ahmed Kahksha , Khan Jalaluddin , Khan Rahmuddin , Shahat Abdelaaty A. , Alhalmi Abdulsalam
Published: November 2024

Drug discovery is the process by which new drug candidates are discovered and drug development takes place. To enhance the efficiency, accuracy, and speed of the drug discovery process, machine learning (ML) could play a transformative role. For this research study, antidiabetic natural compounds from C. intybus, which is commonly known as chicory, were selected, as they have promising antidiabetic properties that can complement conventional diabetes treatments. A bioactive natural compound dataset was retrieved on the chicory plant using Indian Medicinal Plants, Phytochemistry, and Therapeutics (IMPPAT) public source information. This collected dataset was analyzed for its absorption, distribution, metabolism, and excretion (ADME) properties using the SwissADME online tool. Principal component analysis (PCA) and correlation analysis were performed using trial-version XLSTAT software 2014.5.03 and Python. The obtained dataset from SwissADME was subjected to cleaning, after that, it was used to develop machine learning models, such as support vacuum (SVM) ML, random forest (RF), Naive Bayes (NB), and decision tree (DT). The Lipinski rule of violation was chosen as the target variable. To improve the vitality of the created ADME dataset, PCA, a biplot graph, and correlation analysis were carried out. A large dataset of naturally occurring antidiabetic compounds was used to predict the drug-likeness of ML models that were effectively deployed on heterogeneous ADME datasets. Among all these ML models, DT performed better than the rest of the models.
Research on Reactivity-Equivalent Physical Transformation Method for Double Heterogeneity in Pressurized Water Reactors Based on Machine Learning
Authors: Li Song , Li Jiannan , Liu Lei , Huang Baocheng , Chen Ling , Zhang Yongfa , Hao Jianli , Zhang Yunfei
Published: November 2024

Traditional computational methods for pressurized water reactors are unable to handle dispersed fuel particles as the double heterogeneity and the direct volumetric homogenization can result in significant errors. In contrast, reactivity-equivalent physical transformation techniques offer high precision for addressing the double heterogeneity introduced by dispersed fuel particles. This approach converts the double heterogeneity problem into a single heterogeneity problem, which is then subsequently investigated by using the conventional pressurized water reactor computational procedure. However, it is currently empirical and takes a lot of time to obtain the right k∞. In this paper, we train the RPT model by using the existing dataset of plate-dispersed fuel and rod-dispersed fuel by a machine learning method based on a linear regression model, and we then use the new data to make predictions and derive the corresponding similarity ratios. The burnup verification, density verification, fission rate verification, and neutron energy spectrum analysis are calculated through the OpenMC program. For plate-type fuel elements, the method maintains an accuracy within 200 pcm during depletion, with deviations in the 235U density and 235U fission rate within 0.1% and neutron energy spectrum errors within 6%. For rod-type fuel elements, the method maintains an accuracy within 100 pcm during depletion, with deviations in 235U and 239Pu density within 1.5% and neutron energy spectrum errors within 1%. The numerical validation indicates that the reactivity-equivalent physical transformation method based on the linear regression model not only greatly improves the computational efficiency, but also ensures a very high accuracy to deal with double heterogeneity in nuclear reactors.
Real-Time Estimation of CO2 Absorption Capacity Using Ionic Conductivity of Protonated Di-Methyl-Ethanolamine (DMEA) and Electrical Conductivity in Low-Concentration DMEA Aqueous Solutions
Authors: Han Sang-Jun , Han Joo Young , Wee Jung-Ho
Published: November 2024

The present study investigates the real-time estimation of CO2 absorption capacity (CAC) based on the electrical conductivity (EC) of low-concentration di-methyl-ethanolamine (DMEA) solutions (0.1–0.5 M). CO2 absorption experiments are conducted to measure the variation in CAC and EC during CO2 absorption, revealing a strong correlation between the two properties. The ionic conductivity of DMEAH+ formed during absorption is calculated to be 53.1 S·cm2/(mol·z), which is found to be larger than that of TEAH+ and MDEAH+. This can be attributed to the smaller molar mass and higher ionic mobility of DMEAH+. A significant finding is that the measured EC (ECM) of the DMEA solutions consistently demonstrates a lower value than the theoretically predicted value. This discrepancy is due to the larger ionic size of DMEAH+, which results in a reduction in the real mean ionic activity coefficient. This effect becomes more pronounced with increasing DMEA concentration. Consequently, a higher CAC is required to produce the same change in EC at higher amine concentrations. Based on these findings, an empirical equation is devised to estimate CAC from ECM in solutions of constant DMEA concentration. This equation will be employed as a practical approach for the in situ monitoring of CO2 absorption using DMEA aqueous solution.
Optimization of Supercritical Extraction of Cannabidiol Using Response Surface Methodology
Authors: Hong Min , Kim Jong-Hui , Kim Chang-Hyeug , Lee Soo-Ung , Kwon Tae-Hyung
Published: November 2024

Hemp, also known as Cannabis sativa L., contains over 80 cannabinoids, with cannabidiol (CBD) being the primary neuroactive component. CBD possesses various pharmacological properties and is considered a non-psychoactive compound, making it a promising component for various applications, such as pharmaceuticals, cosmetics, and nutraceuticals. The aim of this study was to identify the optimal conditions for extracting CBD from hemp using supercritical fluid extraction (SFE). Response surface methodology (RSM) was employed to optimize the SFE conditions. The Box–Behnken design and the central composite design were utilized to refine the extraction parameters, including extraction time, temperature, and pressure. The statistical significance and reliability of the optimized conditions were confirmed by the significant influence of these independent variables on CBD yield. The extracted CBD was purified to a high level of purity and converted from cannabidiolic acid (CBDA) through heat treatment and then analyzed using high-performance liquid chromatography (HPLC). The following extraction conditions were considered optimal and led to a CBD yield of approximately 70.46 g/kg: pressure of 48.3 MPa, temperature of 60 °C, and extraction time of 109.2 min. Validation experiments confirmed the accuracy of the model, with experimental values closely matching the predicted values (69.93 ± 0.88 g/kg). This study demonstrates that SFE is an efficient method for obtaining high-purity CBD from hemp, highlighting its potential for industrial applications. The findings suggest that optimizing SFE conditions through RSM can significantly enhance the efficiency and yield of CBD extraction, providing a robust framework for industrial-scale production.
CFD Analysis of UV-C Intensity Radiation Distribution and Inactivation of Foodborne Pathogens on Whole and Minimally Processed Mango
Authors: Garzón-García Alba Mery , Largo-Ávila Esteban , Suárez-Rodríguez Carlos Hernán , Ruiz-Cruz Saul , Lobatón-García Hugo Fabián , Gómez-Daza Juan Carlos , Tapia-Hernández José Agustín
Published: November 2024

Ultraviolet shortwave (UV-C) is a technology for postharvest fruit disinfection. This study aimed to use computational fluid dynamics (CFD) based on the discrete ordinate (DO) radiation model to analyze the distribution of UV-C intensity on whole and minimally processed mangoes within a disinfection chamber and to predict treatments against foodborne pathogens. The mango spears were oriented both parallel and perpendicular to the lamp and positioned at varying distances from the radiation source (50, 75, and 100 mm for spears and 100 mm for whole fruit). CFD simulations integrated with in vitro kinetic parameters enabled predictions of the time and doses needed to inactivate one to three logarithmic units of pathogens on the fruit surface. The highest average radiation intensity values were recorded for the whole mango oriented parallel to the lamp at 100 mm and the spears oriented normally to the lamp at 50 mm. The estimated times to achieve inactivation of one to three logarithmic units of microorganisms ranged from approximately 15 to 6540 s, while the doses necessary for this inactivation were, on average, 1.854, 5.291, and 10.656 kJ/m2, respectively. CFD simulations are valuable for optimizing UV-C treatments in large-scale designing from both microbicide and sustainable perspectives.
Effect of UV-C Treatment on the Quality of Fresh-Cut Potatoes Obtained from Tubers of Different Ages
Authors: Pelaić Zdenka , Čošić Zrinka , Repajić Maja , Levaj Branka
Published: November 2024

The physico-chemical properties of potato tubers change with age, which can affect not only the quality of the tubers but also the quality and shelf-life of fresh-cut potatoes (FCP) produced from older tubers. One of the methods that has proven useful for extending the shelf-life of some foods is ultraviolet-C (UV-C) irradiation. This study investigated whether UV-C irradiation can mitigate the negative effects of tuber age. FCP from tubers after storage (1 and 9 months), vacuum-packaged, were irradiated with UV-C (2.70 kJ m−2) and stored (6 °C/15 days). The total aerobic mesophilic bacteria count (TAMBC), total and soluble solids content, pH, firmness, color, chlorogenic acid, reducing sugars, sensory properties of raw FCP and subsequently boiled and fried FCP, and acrylamide content in fried FCP were monitored. UV-C irradiation of FCP does not affect all parameters equally for both tuber ages, but was generally effective in reducing TAMBC, and UV-C-treated samples reached a shelf-life of 15 days. UV-C irradiation improved the sensory properties of raw and thermally processed FCP at both ages. UV-C irradiation caused an increase in acrylamide content in fried FCP, regardless of. the tubers age, but all samples were safe in this respect.
Numerical Simulation of the Diffusion Characteristics of Odor Pollutants of Waste Bunkers in Waste Incineration Plant
Authors: Wu Hao , Zhu Lingxia , Cai Jianjun , Wei Qiuxia , Guo Minjia
Published: November 2024

This paper utilizes the waste bunker of a waste incineration plant as the analysis model. It analyzes the airflow characteristics under various unloading door opening states and the air flow velocity through CFD simulation. The simulation analysis results show that when one unloading door is opened, it is recommended to adjust the opening amplitude or set an air outlet to optimize the airflow distribution. If two unloading doors are opened, it is advised to prioritize the two middle unloading doors (M4, M5) or the two rightmost doors (M7, M8). Furthermore, the exhaust port located relatively far from the unloading door should be closed to reduce the turbulence of the airflow. When all unloading doors are opened, the air flow velocity at the unloading door needs to be increased to achieve an efficient exhaust effect and prevent negative pressure problems at low speed. The results offer theoretical support for odor control technologies and provide valuable design recommendations for air outlets and unloading doors in municipal waste incineration plants. Additionally, this study proposes optimization strategies and effective solutions for addressing odor pollutant diffusion in waste incineration facilities.
Decision Support System (DSS) for Improving Production Ergonomics in the Construction Sector
Authors: Sardinha Laura , Baleiras Joana Valente , Sousa Sofia , Lima Tânia M. , Gaspar Pedro D.
Published: November 2024

Ergonomics is essential to improving workplace safety and efficiency by reducing the risks associated with physical tasks. This study presents a decision support system (DSS) aimed at enhancing production ergonomics in the construction sector through an analysis of high-risk postures. Using the Ovako Work Posture Analysis System (OWAS), the Revised NIOSH Lifting Equation (NIOSH equation) and Rapid Entire Body Assessment (REBA), the DSS identifies ergonomic risks by assessing body postures across common construction tasks. Three specific postures—X, Y and Z—were selected to represent typical construction activities, including lifting, squatting and repetitive tool use. Posture X, involving a forward-leaning stance with arms above the shoulders and a 25 kg load, was identified as critical, yielding the highest OWAS and NIOSH values, thus indicating an immediate need for corrective action to mitigate risks of musculoskeletal injuries. The DSS provides recommendations for workplace adjustments and posture improvements, demonstrating a robust framework that can be adapted to other postures and industries. Future developments may include application to other postures and sectors, as well as the use of artificial intelligence to support ongoing ergonomic assessments, offering a promising solution to enhance Occupational Safety and Health policies.
Parameter Identification of Solid Oxide Fuel Cell Using Elman Neural Network and Dynamic Fitness Distance Balance-Manta Ray Foraging Optimization Algorithm
Authors: Li Hongbiao , Gao Dengke , Shi Linlong , Zheng Fei , Yang Bo
Published: November 2024

An accurate solid oxide fuel cell model is a prerequisite for optimizing the operation and state estimation of subsequent cell systems. Hence, this work aimed to utilize a vigoroso algorithmic tool, i.e., Elman neural network, for data prediction to enrich cell measurement data and employ the trained network model for noise reduction of voltage–current data. Furthermore, to obtain reliable cell parameters, a novel parameter identification model based on the dynamic fitness distance balance-manta ray foraging optimization (dFDB-MRFO) algorithm is proposed. Two datasets were applied to extract the electrochemical model and simple electrochemical model parameters of the solid oxide fuel cell model. To verify adequately the superiority of this method, which is compared with another seven conventional heuristic algorithms, four performance indicators were selected as evaluation criteria. Comprehensive case studies demonstrated that through data processing, the precision and robustness of identification could be effectively heightened. In general, the model fitting data obtained via parameter identification using dFDB-MRFO have excellent fitting precision contrast with the measured voltage–current data. Notably, the fitting degree obtained by dFDB-MRFO in the simple electrochemical model reached 99.95% and 99.91% under the two datasets, respectively.
Metal Acetate-Enhanced Microwave Pyrolysis of Waste Textiles for Efficient Syngas Production
Authors: Zhang Bo , Wu Lei , Li Fei , Xiong Wuwan , Yao Peiyu , Zhang Yang , Li Xiang
Published: November 2024

The production of waste textiles has increased rapidly in the past two decades along with the rapid development of the economy, the majority of which has been either landfilled or incinerated, resulting in energy loss and environmental pollution. Microwave pyrolysis, which can transform heterogeneous and complex waste feedstocks into value-added products, is considered one of the most competitive technologies for processing waste textiles. However, achieving selective product formation during the microwave pyrolysis of waste textiles remains a significant challenge. Herein, sodium acetate, potassium acetate, and nickel acetate were introduced into waste textiles through an impregnation method as raw materials to improve the pyrolysis efficiency. The optimized process parameters indicated that nickel acetate had the most favorable promotional effect of the three acetates. Notably, the waste textiles containing 1.0% Ni exhibited the highest gas production rate, with the hydrogen-containing combustible gas reaching 81.1% and 61.0%, respectively. Using X-ray diffraction (XRD), transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIR), and Raman spectroscopy to characterize the waste textiles before and after pyrolysis, it was found that nickel acetate was converted into metallic nickel (Ni0) during microwave pyrolysis. This active site significantly enhanced the pyrolysis process, and as the gas yield increased, the disorder of the resulting pyrolytic carbon also rose. The proposed Ni0-enhanced microwave pyrolysis mediated by nickel acetate offers a novel method for the efficient disposal and simultaneous resource recovery of waste textiles.
Preparation and Characterization of Lithraea molleoides Gum Flour and Its Blend Films
Authors: Becerra Federico , Garro Maria F. , Melo Gisela , Masuelli Martin
Published: November 2024

Lithraea molleoides fruit gum (LMFG) is a valuable product obtained from the total hydrolysis of the fruit. The hydrolysis process involves three methods: thermal (LMFGT), alkaline (LMFGB), and acid (LMFGA). Through these methods, the aim is to break bonds and de-esterify polysaccharides, resulting in increased solubility and decreased molecular weight. The resulting hydrolysates are then combined with pectins in a 1:2 ratio to form films. In this study, the focus is on utilizing the hydrolysates of Lithraea molleoides gums for film applications, with an evaluation of their structural and physicochemical characteristics. The films produced exhibit excellent mechanical properties and low water vapor permeability, as well as exceptional thermal stability. These properties make them highly suitable for industrial films in pharmaceutical and food applications. This research highlights the potential of LMFG-based films as a viable solution for various industrial needs due to their outstanding performance across multiple parameters.
Artificial Neural Network Modeling to Predict Electrical Conductivity and Moisture Content of Milk During Non-Thermal Pasteurization: New Application of Artificial Intelligence (AI) in Food Processing
Authors: Alsaedi Ali Wali M. , Al-Hilphy Asaad R. , Al-Mousawi Azhar J. , Gavahian Mohsen
Published: November 2024

This study proposed applying artificial intelligence (AI) to predict the actual electrical conductivity (EC) of raw and pasteurized milk using moderate electric field (MEF) based on the electric field strength (EFS) and mass flow rate (MFR) along with modeling moisture content (MC) based on the EC. To this end, an artificial neural network (ANN) was implemented for conventionally (CP) and non-thermally (NP) pasteurized milk. The findings indicated no significant difference (p > 0.05) between the experimental and predicted data for EC and MC. The MFR and EFS affected the actual EC. The raw milk samples had an EC of 0.468812–0.46913 S/m and MC of 87.3218–87.35941%, while these values in NP pasteurized milk were 0.457441–0.638224 S/m and 87.33986–87.40851%. With correlation coefficients (R) of 0.736478106–0.951840323 and mean square errors (MSE) of 0.005539–0.0064, the ANN accurately predicted the raw and pasteurized milk MC based on the EC using the sixth-order polynomial model and the EC based on the EFS and MFR using a quadratic model. The EC of pasteurized milk by NP was significantly (p < 0.05) lower than that of CP and raw milk by 15.44% and 11.30%, respectively. The results show that the EFS and MFR might be used for the online assessment of milk’s physical attributes (e.g., EC), followed by using the assessed parameter to determine other properties (e.g., MC) by developing AI approaches based on optimized models. These observations showcase the innovative use of ANN-based AI to predict milk’s EC and MC accurately. Integrating such AI platforms into non-thermal food processing could eventually develop more sustainable food production and enhance food security and quality through process innovation and sustainable manufacturing, contributing to the industrial revolution and sustainable development goals.
Effect of Microwave–Vacuum Drying and Pea Protein Fortification on Pasta Characteristics
Authors: Nguyen Nam Phuong Michalina , Marzec Agata
Published: November 2024

The widespread popularity of pasta has driven innovations in formulations and production technologies to enhance its versatility. Techniques such as alternative drying methods and fortification of wheat pasta seek to improve the nutritional value and functional properties of pasta products, thereby increasing their attractiveness to consumers. This study aimed to evaluate the effects of microwave–vacuum drying versus conventional drying on the characteristics of durum wheat semolina pasta, including moisture content, water activity, microstructure, colour, texture, weight gain factor, and cooking loss. Three types of pea protein concentrates (80, 84, and 88% dry matter) were used at levels of 3, 6, and 9% (g/100 g flour). Results indicated that microwave–vacuum drying had a significant impact on the physical properties and cooking quality of pasta. Microwave–vacuum drying caused material puffing, resulting in microstructure with high open porosity (64.1%) and minimal closed porosity (0.1%). This has likely contributed to the short rehydration time (2 min in boiling water) of produced pasta, effectively transforming it into an instant food product. All pasta samples had low water content (<9%) and water activity (<0.4), which ensure food safety. The microwave–vacuum-dried pasta weight gain factor (2.2) was lower than in the conventionally dried pasta (2.8). The firmness of microwave–vacuum-dried pasta was significantly higher (135 g) than that of conventional pasta (16 g). Fortification with pea protein enhanced porosity but did not affect pasta’s culinary parameters, such as weight gain or cooking loss, although it resulted in darker pasta (p = 0.001), especially notable with a 9% pea protein addition.