bluuebunny/crossref_metadata_2025 huggingface dataset:
Combining No-Tillage with Hairy Vetch Return Improves Production and Nitrogen Utilization in Silage Maize
Authors: Li Zhou , Sun Xingrong , Pan Jie , Wang Tao , Li Yuan , Li Xiuting , Hou Shuai
Published: July 2024

The combination of no-till farming and green manure is key to nourishing the soil and increasing crop yields. However, it remains unclear how to enhance the efficiency of green manure under no-till conditions. We conducted a two-factor field trial of silage maize rotated with hairy vetch to test the effects of tillage methods and returning. Factor 1 is the type of tillage, which is divided into conventional ploughing and no-tillage; factor 2 is the different ways of returning hairy vetch as green manure, which were also compared: no return (NM), stubble return (H), mulching (HM), turnover (HR, for CT only), and live coverage (LM, for NT only). Our findings indicate that different methods of returning hairy vetch to the field will improve maize yield and quality. The best results were obtained in CT and NT in HM and LM, respectively. Specifically, HM resulted in the highest dry matter quality and yield, with improvements of 35.4% and 31.9% over NM under CT, respectively. It also demonstrated the best economic and net energy performance. However, other treatments had no significant effect on the beneficial utilization and return of nutrients. The LM improved yields under NT by boosting soil enzyme activity, promoting nitrogen transformation and accumulation, and increasing nitrogen use efficiency for better kernel development. Overall, NTLM is best at utilizing and distributing soil nutrients and increasing silage maize yield. This finding supports the eco-efficient cultivation approach in silage maize production in the region.
Polyploids of Brassicaceae: Genomic Insights and Assembly Strategies
Authors: Jeon Donghyun , Kim Changsoo
Published: July 2024

The Brassicaceae family is distinguished by its inclusion of high-value crops such as cabbage, broccoli, mustard, and wasabi, all noted for their glucosinolates. In this family, many polyploidy species are distributed and shaped by numerous whole-genome duplications, independent genome doublings, and hybridization events. The evolutionary trajectory of the family is marked by enhanced diversification and lineage splitting after paleo- and meso-polyploidization, with discernible remnants of whole-genome duplications within their genomes. The recent neopolyploidization events notably increased the proportion of polyploid species within the family. Although sequencing efforts for the Brassicaceae genome have been robust, accurately distinguishing sub-genomes remains a significant challenge, frequently complicating the assembly process. Assembly strategies include comparative analyses with ancestral species and examining k-mers, long terminal repeat retrotransposons, and pollen sequencing. This review comprehensively explores the unique genomic characteristics of the Brassicaceae family, with a particular emphasis on polyploidization events and the latest strategies for sequencing and assembly. This review will significantly improve our understanding of polyploidy in the Brassicaceae family and assist in future genome assembly methods.
Involvement of Auxin, Flavonoids and Strigolactones in the Different Rooting Ability of European Chestnut (Castanea sativa) and Hybrids (Castanea crenata × Castanea sativa)
Authors: Kunc Petra , Medic Aljaz , Osterc Gregor
Published: July 2024

The aim of this study was to investigate the differences between Castanea sativa Mill. and Castanea crenata Siebold & Zucc. × Castanea sativa Mill. in rooting ability in relation to endogenous levels of auxin, auxin cofactors and inhibitors that influence rooting success. Leafy cuttings of the two commercial cultivars ‘Marsol’ and ‘Maraval’ (Castanea crenata × Castanea sativa) and the native accession ‘Kozjak’ (Castanea sativa) were analyzed. Endogenous indole-3-acetic acid (IAA) concentration was assessed at the beginning of propagation (day 0); in addition, strigolactones, flavonoids, rooting ability and quality were assessed 120 days after. The concentration of endogenous IAA in ‘Maraval’ (324.34 ± 28.66 ng g−1) and ‘Marsol’ (251.60 ± 35.44 ng g−1) was significantly higher than in ‘Kozjak’ (112.87 ± 35.44 ng g−1). The best rooting result was observed with the genotypes ‘Maraval’ (100.00 ± 0.00%) and ‘Marsol’ (90.48 ± 6.15%). A significantly lower strigol concentration was observed in the roots of ‘Maraval’ (75.54 ± 17.93 ng g−1) compared with other genotypes. The total flavonoid concentration in ‘Maraval’ was significantly higher (2794.99 ± 187.13 μg g−1) than in ‘Kozjak’ (1057.38 ± 61.05 μg g−1). Our results indicate that the concentration of endogenous IAA has a significant influence on rooting success. The results further indicate that in the case of flavonoids and strigolactones, not only the individual compounds but also their ratio is important for rooting success. Correlation coefficients calculated between analyzed compounds and rooting success point toward specific functions of flavonoids and strigolactones in the rooting of Castanea that need to be functionally analyzed.
Genetic Diversity Analysis and Prediction of Potential Suitable Areas for the Rare and Endangered Wild Plant Henckelia longisepala
Authors: Zhao Renfen , Huang Nian , Zhang Zhiyan , Luo Wei , Xiang Jianying , Xu Yuanjie , Wang Yizhi
Published: July 2024

Henckelia longisepala (H. W. Li) D. J. Middleton & Mich. Möller is a rare and endangered plant species found only in Southeastern Yunnan, China, and Northern Vietnam. It is listed as a threatened species in China and recognized as a plant species with extremely small populations (PSESP), while also having high ornamental value and utilization potential. This study used ddRAD-seq technology to quantify genetic diversity and structure for 32 samples from three extant populations of H. longisepala. The H. longisepala populations were found to have low levels of genetic diversity (Ho = 0.1216, He = 0.1302, Pi = 0.1731, FIS = 0.1456), with greater genetic differentiation observed among populations (FST = 0.3225). As indicated by genetic structure and phylogenetic analyses, samples clustered into three distinct genetic groups that corresponded to geographically separate populations. MaxEnt modeling was used to identify suitable areas for H. longisepala across three time periods and two climate scenarios (SSP1-2.6, SSP5-8.5). High-suitability areas were identified in Southeastern Yunnan Province, Northern Vietnam, and Eastern Laos. Future H. longisepala distribution was predicted to remain centered in these areas, but with a decrease in the total amount of suitable habitat. The present study provides key data on H. longisepala genetic diversity, as well as a theoretical basis for the conservation, development, and utilization of its germplasm resources.
Vitis rotundifolia Genes Introgressed with RUN1 and RPV1: Poor Recombination and Impact on V. vinifera Berry Transcriptome
Authors: Shi Mengyao , Savoi Stefania , Sarah Gautier , Soriano Alexandre , Weber Audrey , Torregrosa Laurent , Romieu Charles
Published: July 2024

Thanks to several Vitis vinifera backcrosses with an initial V. vinifera L. × V. rotundifolia (previously Muscadinia rotundifolia) interspecific cross, the MrRUN1/MrRPV1 locus (resistance to downy and powdery mildews) was introgressed in genotypes phenotypically close to V. vinifera varieties. To check the consequences of introgressing parts of the V. rotundifolia genome on gene expression during fruit development, we conducted a comparative RNA-seq study on single berries from different V. vinifera cultivars and V. vinifera × V. rotundifolia hybrids, including ‘G5’ and two derivative microvine lines, ‘MV102’ (resistant) and ‘MV32’ (susceptible) segregating for the MrRUN1/RPV1 locus. RNA-Seq profiles were analyzed on a comprehensive set of single berries from the end of the herbaceous plateau to the ripe stage. Pair-end reads were aligned both on V. vinifera PN40024.V4 reference genome, V. rotundifolia cv ‘Trayshed’ and cv ‘Carlos’, and to the few resistance genes from the original V. rotundifolia cv ‘52’ parent available at NCBI. Weighted Gene Co-expression Network Analysis (WGCNA) led to classifying the differentially expressed genes into 15 modules either preferentially correlated with resistance or berry phenology and composition. Resistance positively correlated transcripts predominantly mapped on the 4–5 Mb distal region of V. rotundifolia chromosome 12 beginning with the MrRUN1/MrRPV1 locus, while the negatively correlated ones mapped on the orthologous V. vinifera region, showing this large extremity of LG12 remained recalcitrant to internal recombination during the successive backcrosses. Some constitutively expressed V. rotundifolia genes were also observed at lower densities outside this region. Genes overexpressed in developing berries from resistant accessions, either introgressed from V. rotundifolia or triggered by these in the vinifera genome, spanned various functional groups, encompassing calcium signal transduction, hormone signaling, transcription factors, plant–pathogen-associated interactions, disease resistance proteins, ROS and phenylpropanoid biosynthesis. This transcriptomic insight provides a foundation for understanding the disease resistance inherent in these hybrid cultivars and suggests a constitutive expression of NIR NBS LRR triggering calcium signaling. Moreover, these results illustrate the magnitude of transcriptomic changes caused by the introgressed V. rotundifolia background in backcrossed hybrids, on a large number of functions largely exceeding the ones constitutively expressed in single resistant gene transformants.
Development of a Rhizobium Seed Coating to Establish Lupine Species on Degraded Rangelands
Authors: Church Bridget M. , Geary Brad , Griffitts Joel , Drake Curtis L. , Ruebelmann Kate , Nelson Shannon V. , Madsen Matthew D.
Published: July 2024

Restoring native plant species on degraded landscapes is challenging. Symbiotic partners in the plant rhizosphere can aid in nutrient acquisition, pathogen protection, stress tolerance, and many other processes. However, these microbes are often absent in altered landscapes and need to be re-integrated to improve restoration efforts. We evaluated, within a laboratory setting, the ability of commercial and indigenous rhizobia strains to form nodules on lupine species used for rangeland seedings in the Great Basin region of the Western United States and ascertained if these strains could be applied through a seed coating. We also evaluated if a compost amendment applied via seed coating could further enhance the performance of the rhizobia strains. Our analysis showed that successful nodulation could occur using commercial and wildland-collected indigenous strains through either a liquid culture applied to seedlings or as a dry seed coating. However, the number of root nodules and the presence of a pink color (indicating nitrogen fixation) were typically higher in the commercial product than in the indigenous strains. Compost did not improve nodulation or the performance of the nodules; however, this treatment alone improved shoot growth. Overall, these results suggest that commercial rhizobium may be more effective in improving plant growth, and future research with native rhizobia may want to consider identifying strains compatible with seed-coating delivery. Longer-term studies are now merited for assessing how the rhizobia strains evaluated in this study influence plant growth, particularly in a field setting.
Assessment of Breeding Potential of Foxtail Millet Varieties Using a TOPSIS Model Constructed Based on Distinctness, Uniformity, and Stability Test Characteristics
Authors: Yu Jin , Bai Xionghui , Zhang Kaixi , Feng Leyong , Yu Zheng , Jiao Xiongfei , Guo Yaodong
Published: July 2024

Foxtail millet (Setaria italica) is an important cereal crop with rich nutritional value. Distinctness, Uniformity, and Stability (DUS) are the prerequisites for the application of new variety rights for foxtail millet. In this study, we investigated 32 DUS test characteristics of 183 foxtail millet resources, studied their artificial selection trends, and identified the varieties that conform to breeding trends. The results indicated significant differences in terms of the means, ranges, and coefficients of variation for each characteristic. A correlation analysis was performed to determine the correlations between various DUS characteristics. A principal component analysis was conducted on 31 test characteristics to determine their primary characteristics. By plotting PC1 and PC2, all the germplasm resources could be clearly distinguished. The trends in foxtail millet breeding were identified through a differential analysis of the DUS test characteristics between the landrace and cultivated varieties. Based on these breeding trends, the optimal solution types for multiple evaluation indicators were determined; the weight allocation was calculated; and a specific TOPSIS algorithm was designed to establish a comprehensive multi-criteria decision-making model. Using this model, the breeding potential of foxtail millet germplasm resources were ranked. These findings provided important reference for foxtail millet breeding in the future.
Cultural Use and the Knowledge of Ethnomedicinal Plants in the Pülümür (Dersim-Tunceli) Region
Authors: Dogan Ahmet
Published: July 2024

Pülümür has been a refuge place for internal and external exiles several times throughout history, and today it is a district of the province of Tunceli (known as Dersim in the region), which differs significantly from many settlements around it in terms of biodiversity and social aspects. The aim of this study is to identify, catalog, and report the traditional medicinal uses of plants in this province, where every living thing and many natural objects around it are regarded as sacred, with a scientific ethnobotanical approach. The field study was completed between May 2016 and July 2023. The collection of plant excursion and plant usage information was implemented in two stages; in the first stage, a survey about the collection and the uses of medicinal plants was conducted. At this stage, plant samples were collected by visiting 49 villages of the district and performing face-to-face interviews with 112 participants (51 female and 61 male). In the second stage, the usage statistics related to the data obtained from the field studies were determined. For this reason, every informant was interviewed at least twice, people who were previously interviewed were included too. In the course of this study, interviews from 211 participants (95 female and 116 male) were analyzed. As a result of analysis, the traditional medicinal uses of 120 plants belonging to 48 families were identified. The most taxa are identified from the Asteraceae (15), Rosaceae (13), Fabaceae (8), Lamiaceae (8), and Apiaceae (6) families. In Pülümür, these medicinal plants are mostly used for the treatment of wounds, abdominal pain, constipation, and diabetes.
Ferrocene-Modified Polyacrylonitrile-Containing Block Copolymers as Preceramic Materials
Authors: Heinz Sebastian , Gemmer Lea , Janka Oliver , Gallei Markus
Published: July 2024

In the pursuit of fabricating functional ceramic nanostructures, the design of preceramic functional polymers has garnered significant interest. With their easily adaptable chemical composition, molecular structure, and processing versatility, these polymers hold immense potential in this field. Our study succeeded in focusing on synthesizing ferrocene-containing block copolymers (BCPs) based on polyacrylonitrile (PAN). The synthesis is accomplished via different poly(acrylonitrile-block-methacrylate)s via atom transfer radical polymerization (ATRP) and activators regenerated by electron transfer ATRP (ARGET ATRP) for the PAN macroinitiators. The molecular weights of the BCPs range from 44 to 82 kDa with dispersities between 1.19 and 1.5 as determined by SEC measurements. The volume fraction of the PMMA block ranges from 0.16 to 0.75 as determined by NMR. The post-modification of the BCPs using 3-ferrocenyl propylamine has led to the creation of redox-responsive preceramic polymers. The thermal stabilization of the polymer film has resulted in stabilized morphologies based on the oxidative PAN chemistry. The final pyrolysis of the sacrificial block segment and conversion of the metallopolymer has led to the formation of a porous carbon network with an iron oxide functionalized surface, investigated by scanning electron microscopy (SEM), energy dispersive X-ray mapping (EDX), and powder X-ray diffraction (PXRD). These findings could have significant implications in various applications, demonstrating the practical value of our research in convenient ceramic material design.
Correlating the Segmental Relaxation Time of Polystyrene
Authors: Hieber C. A.
Published: July 2024

A previous related paper dealing with the density relaxation of polystyrene (PS) has shown that the equilibrium relaxation time (τeq) has a purely exponential temperature dependence (ETD) below ≈100 °C. Such an ETD is now also confirmed based upon available dielectric spectra data for PS. By combining the ETD behavior of τeq (or aT) at low temperatures with a VFTH behavior at higher temperatures (based mainly on available recoverable shear compliance data), a composite correlation for τeq (or aT) is developed, which is continuous with continuous slope at a crossover temperature that is found to be 99.22 °C, where τeq = 92.15 s. This composite representation is shown to describe (without any adjustable parameters) available independent data for the segmental relaxation time over a finite range both above and below Tcrossover (i.e., the glass transition temperature).
Co-Cultivation between the Microalga Tetradesmus obliquus and Filamentous Fungus Cunninghamella echinulata Improves Tertiary Treatment of Cheese Whey Effluent in Semicontinuous Mode
Authors: Monteiro dos Santos Leandro , Barbosa da Silva Joyce Camila , de Farias Silva Carlos Eduardo , Villar da Gama Brígida Maria , Almeida Medeiros Josimayra , Markou Giorgos , Rosas Garcia Almeida Renata Maria , Abud Ana Karla de Souza
Published: July 2024

Cheese whey (CW), a byproduct resulting from dairy processing, requires proper treatment and disposal. The use of microalgae during tertiary treatment emerges as a promising option due to its efficiency to remove chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) from effluents obtained after secondary treatment processes. The present study was focused on treating CW effluent at two organic loads (C1 and C2—with different concentrations of COD, TN, and TP) (550–2200 mg·L−1 of COD, 14–56 mg·L−1 of TN, and 4.5–18 mg·L−1 of TP) using the microalga Tetradesmus obliquus alone (CM1 and CM2) and in a consortium with the fungus Cuninghamella echinulata (CMF1 and CMF2), evaluating the residual values of COD, TN, and TP and removal efficiency. The experiments were carried out in an open system with a volumetric replacement ratio (VRR) of 40 and 60%. The CM treatment showed residual values of COD in the range of 190–410 mg·L−1 (removal efficiency: 57–68%), TN in the range of 6–24 mg·L−1 (removal efficiency: 29–35%), and TP in the range of 0.90–3.0 mg·L−1 (removal efficiency: 65–68%), after 7 days of volumetric replacement time (VRT) in a semicontinuous mode. In contrast, the consortium (CMF) showed greater stability and efficiency in contaminant removal compared to the treatment system containing only the microalga, showing residual values of COD in the range of 61–226 mg·L−1 (removal efficiency: 75–77%), TN in the range of 1.8–9.5 mg·L−1 (removal efficiency: 70–74%), and TP in the range of 0.6–3.5 mg·L−1 (removal efficiency: 66–70%), applying a lower VRT of 3 days and reaching the legislation standard for discharge to CMF1 (VRR: 40 and 60%) and CMF2 (VRR: 40%). The cell dry weight of 290–850 mg·L−1 was obtained (microalga and microalga–fungus cultivation), which can be a valuable biomass for biotechnological applications. Finally, during microalga–fungus co-cultivation, there was greater system buffering (with less pH variation), ensuring a better system stability.
Foreign Object Debris Detection on Wireless Electric Vehicle Charging Pad Using Machine Learning Approach
Authors: Rajamanickam Narayanamoorthi , Abraham Dominic Savio , Alroobaea Roobaea , Abdelfattah Waleed Mohammed
Published: July 2024

Foreign object debris (FOD) includes any unwanted and unintentional material lying on the charging lane or parking lots, posing a risk to the wireless charging system, the vehicle, or the people inside. FOD in an Electric Vehicle (EV) wireless charging system can cause problems, including decreased charging efficiency, safety risks, charging system damage, communication issues, and health risks. To address this problem, this paper proposes the deep learning object detection network approach of using YOLOv4 (You Only Look Once), which is a single-shot detector. Additionally, for real-time implementation, YOLOv4-Tiny is suggested, which is a compressed version of YOLOv4 designed for devices with low computational power. YOLOv4-Tiny enables faster inferences and facilitates the deployment of FOD detectors on edge devices. The algorithm is trained using the FOD dataset, consisting of images of common debris on runways or taxiways. Furthermore, utilizing the concept of transfer learning, the last few layers of the pre-trained YOLOv4 model are modified using the COCO (Common Objects in Context) dataset to transfer features to the new network and retrain the model on the FOD dataset. The results obtained using this YOLOv4 model yielded a precision rate of 99.05%, while the results from YOLOv4-Tiny achieved a precision rate of 97.74%, with an average inference time of 150 ms under the ambient light and weather conditions.
Economic and Environmental Optimization of a CCUS Supply Chain in Germany
Authors: Nguyen Tuan B. H. , Bahzad Husain Y. M. , Leonzio Grazia
Published: July 2024

Carbon capture, utilization, and storage supply chain is recently acknowledged as a crucial method to limit global warming. There is a notable desire to optimize supply chains simultaneously with respect to economic and environmental factors, and the development of a mathematical model integrating the life cycle assessment into source-sink matching is missing in the existing literature. The present work means to fill this gap by using a bi-objective mixed-integer linear programming problem. The case study for this research focuses on a real-life scenario in Germany where carbon dioxide is captured from flue gas and transported to be stored or/and used. The total profit and life cycle GHG reduction are maximized. The results show that the profit per unit of sequestered CO2 decreases from 2014 to −€332 as the rate of life cycle GHG reduction increases from −873 to 52 MtCO2eq/year. The findings from the model can provide valuable knowledge that can be utilized in various countries at different levels, such as at regional, state, and national levels. This knowledge can also assist decision-makers in selecting more sustainable solutions when designing carbon capture, utilization, and storage systems.
Efficient Enzymatic Hydrolysis and Polyhydroxybutyrate Production from Non-Recyclable Fiber Rejects from Paper Mills by Recombinant Escherichia coli
Authors: Jia Linjing , Juneja Ankita , Majumder Erica L.-W. , Ramarao Bandaru V. , Kumar Deepak
Published: July 2024

Non-recyclable fiber rejects from paper mills, particularly those from recycled linerboard mills, contain high levels of structural carbohydrates but are currently landfilled, causing financial and environmental burdens. The aim of this study was to develop efficient and sustainable bioprocess to upcycle these rejects into polyhydroxybutyrate (PHB), a biodegradable alternative to degradation-resistant petroleum-based plastics. To achieve high yields of PHB per unit biomass, the specific objective of the study was to investigate various approaches to enhance the hydrolysis yields of fiber rejects to maximize sugar recovery and evaluate the fermentation performance of these sugars using Escherichia coli LSBJ. The investigated approaches included size reduction, surfactant addition, and a chemical-free hydrothermal pretreatment process. A two-step hydrothermal pretreatment, involving a hot water pretreatment (150 °C and 15% solid loading for 10 min) followed by three cycles of disk refining, was found to be highly effective and resulted in an 83% cellulose conversion during hydrolysis. The hydrolysate obtained from pretreated biomass normally requires a detoxification step to enhance fermentation efficiency. However, the hydrolysate obtained from the pretreated biomass contained minimal to no inhibitory compounds, as indicated by the efficient sugar fermentation and high PHB yields, which were comparable to those from fermenting raw biomass hydrolysate. The structural and thermal properties of the extracted PHB were analyzed using various techniques and consistent with standard PHB.
Research on Real-Time Prediction Method of Photovoltaic Power Time Series Utilizing Improved Grey Wolf Optimization and Long Short-Term Memory Neural Network
Authors: Lu Xinyi , Guan Yan , Liu Junyu , Yang Wenye , Sun Jiayin , Dai Jing
Published: July 2024

This paper proposes a novel method for the real-time prediction of photovoltaic (PV) power output by integrating phase space reconstruction (PSR), improved grey wolf optimization (GWO), and long short-term memory (LSTM) neural networks. The proposed method consists of three main steps. First, historical data are denoised and features are extracted using singular spectrum analysis (SSA) and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Second, improved grey wolf optimization (GWO) is employed to optimize the key parameters of phase space reconstruction (PSR) and long short-term memory (LSTM) neural networks. Third, real-time predictions are made using LSTM neural networks, with dynamic updates of training data and model parameters. Experimental results demonstrate that the proposed method has significant advantages in both prediction accuracy and speed. Specifically, the proposed method achieves a mean absolute percentage error (MAPE) of 3.45%, significantly outperforming traditional machine learning models and other neural network-based approaches. Compared with seven alternative methods, our method improves prediction accuracy by 15% to 25% and computational speed by 20% to 30%. Additionally, the proposed method exhibits excellent prediction stability and adaptability, effectively handling the nonlinear and chaotic characteristics of PV power.
Exploring the Bioactive Properties of Hydroethanolic Cork Extracts of Quercus cerris and Quercus suber
Authors: Sen Umut , Almeida Daiana , da Silveira Tayse F. F. , Pires Tânia S. P. , Añibarro-Ortega Mikel , Mandim Filipa , Barros Lillian , Ferreira Isabel C. F. R. , Pereira Helena , Fernandes Ângela
Published: July 2024

The bioactive properties of underutilized corks such as Quercus cerris cork and planted Quercus suber cork in the Eastern Mediterranean are not well-known but are crucial in developing lignocellulosic biorefineries. To assess their biological potential, hydroethanolic cork extracts of Quercus cerris and Quercus suber were analyzed for phenolic composition, antioxidant, antiproliferative, antimicrobial activities, and hepatoxicity, as well as NO-production inhibition. Here, we show that a mild hydroethanolic extraction of Q. cerris and Q. suber corks yielded 3% phenolic extracts. The phenolic composition was similar in both cork extracts, with phenolic acids and ellagitannins as the primary compounds. The bioactivity of hydroethanolic cork extracts from Q. cerris surpassed that of Q. suber and showed effectiveness against all cancer cell lines tested. This first comprehensive study on the bioactivities of different corks involves detailed characterizations of phenolic compounds of cork extracts using UPLC-DAD-ESI/MSn, evaluations of the antioxidant properties with TBARS and OxHLIA methods, evaluation of antiproliferative activity against gastric (AGS), lung (NCI-H460), colon (CaCo2), and breast cancer (MCF7) cell lines, as well as evaluations of hepatotoxicity and NO-production inhibition. The findings from this study will help bolster the potential of using underutilized cork-rich barks as a valuable resource in bark-based biorefineries.
Heterogeneous Catalyst Characteristics of TiO2 Nanoparticles Impregnated with Alkaline CH3ONa for Use in Transesterification Process
Authors: Lin Cherng-Yuan , Tseng Shun-Lien
Published: July 2024

A strong alkaline catalyst, sodium methoxide (CH3ONa), is commonly used to catalyze the transesterification reaction for biodiesel production. Meanwhile, titanium dioxide (TiO2) anatase with a bandgap of 3.2 eV is a highly competitive photocatalyst after the absorption of sufficient energy from ultraviolet light. There has been no published report on the synergistic catalyst effects of CH3ONa and TiO2 on further facilitating the transesterification reaction. Hence, an impregnating method was used in this study to prepare the heterogeneous photocatalyst comprising TiO2 nanoparticles embedded with a CH3ONa catalyst. The TiO2 nanoparticles were first immersed in an aqueous solution of CH3ONa so that CH3ONa could diffuse into the interior surfaces of the TiO2 porous structure. The mixture of TiO2 and CH3ONa was then calcined in the temperature range from 150 °C to 450 °C for 4 h to produce the TiO2/CH3ONa photocatalyst. Various characteristics of the catalyst were analyzed to determine the optimum preparation conditions. The Fourier transform infrared spectroscopy spectra revealed that the absorption peaks of CH3ONa appeared in the wavelength range of 600 cm−1 and 1500 cm−1. The X-ray diffractometer analysis showed that the calcined CH3ONa did not alter the crystal structure of the catalyst carrier TiO2. At the calcined temperatures between 100 °C and 800 °C, no intermediate or pyrolyzed product of CH3ONa was detected, as revealed by the thermogravimetric analyzer spectra. In addition, about 5~9 wt.% elemental calcium in the CH3ONa solution could be calcined onto the surface of TiO2. In addition, the FTIR spectra confirmed the successful sintering and bonding of CH3ONa onto the TiO2 nanoparticles. The energy dispersive spectrometry result revealed that the interior surface of the TiO2 nanoparticles was filled with the CH3ONa compound.
Numerical Simulations for the Mechanical Behavior of a Type-B Sleeve under Pipeline Suspension
Authors: Tang Haiping , Ding Yaping , Qiu Guangyou , Liu Ziguang , Deng Zhibin
Published: July 2024

The type-B sleeve is widely used for reinforcing defective pipelines. Due to the impact of suspension on pipeline safety, the behavior of the type-B sleeve structure has garnered increasing attention. In this study, we establish a numerical model of a defective pipeline reinforced with a type-B sleeve while accounting for the effects of the internal natural gas pressure and gravitational load. We investigate the influence of the sleeve length, suspended pipeline length, internal pressure, and sleeve position on the mechanical behavior of the type-B sleeve. The maximum values for Mises stress and axial strain were both observed near the edge of the suspended segment of the pipeline. For the type-B sleeve structure, the high Mises stress zone was at the bottom of the fillet weld; the axial strain near the fillet weld alternated between tension and compression along the axial direction. With an increase in internal pressure and suspended pipeline length, the Mises stress and axial strain of the type-B sleeve became more prominent. For sleeve length in the ranges of 1 to 3 m, the changes in the stress and strain did not exceed 10 MPa and 0.5 × 10−3, respectively. However, the Mises stress and axial strain on the type-B sleeve structure were independent of the position of the defect on the pipeline. This study provides an important reference for type-B sleeve protection during suspension and other similar practical engineering applications.
A TCN-BiGRU Density Logging Curve Reconstruction Method Based on Multi-Head Self-Attention Mechanism
Authors: Liao Wenlong , Gao Chuqiao , Fang Jiadi , Zhao Bin , Zhang Zhihu
Published: July 2024

In the process of oil and natural gas exploration and development, density logging curves play a crucial role, providing essential evidence for identifying lithology, calculating reservoir parameters, and analyzing fluid properties. Due to factors such as instrument failure and wellbore enlargement, logging data for some well segments may become distorted or missing during the actual logging process. To address this issue, this paper proposes a density logging curve reconstruction model that integrates the multi-head self-attention mechanism (MSA) with temporal convolutional networks (TCN) and bidirectional gated recurrent units (BiGRU). This model uses the distance correlation coefficient to determine curves with a strong correlation to density as a model input parameter and incorporates stratigraphic lithology indicators as physical constraints to enhance the model’s reconstruction accuracy and stability. This method was applied to reconstruct density logging curves in the X depression area, compared with several traditional reconstruction methods, and verified through core calibration experiments. The results show that the reconstruction method proposed in this paper exhibits high accuracy and generalizability.
Research on Gas Drainage Pipeline Leakage Detection and Localization Based on the Pressure Gradient Method
Authors: Zhang Huijie , Shen Maoliang , Huo Zhonggang , Zhang Yibin , Shu Longyong , Li Yang
Published: July 2024

Pipeline leakage seriously threatens the efficient and safe gas drainage in coal mines. To achieve the accurate detection and localization of gas drainage pipeline leakages, this study proposes a gas drainage pipeline leakage detection and localization approach based on the pressure gradient method. Firstly, the basic law of gas flow in the drainage pipeline was analyzed, and a pipeline network resistance correction formula was deduced based on the pressure gradient method. Then, a drainage pipeline model was established based on the realizable k-ε turbulence model, and the pressure and flow velocity distribution during pipeline leakage under different leakage degrees, leakage locations, and pipeline negative pressures were simulated and analyzed, thus verifying the feasibility of the pipeline leakage detection and localization method. It is concluded that the positioning errors of pipeline leakage points under different leakage degrees, different leakage positions, and different pipeline negative pressures were 0.88~1.08%, 0.88~1.49%, and 0.68~0.88%, respectively. Finally, field tests were conducted in the highly located drainage roadway 8421 of the Fifth Mine of Yangquan Coal Industry Group to verify the accuracy of the proposed pipeline leakage detection and localization method, and the relative error was about 8.2%. The results show that with increased pipeline leakage hole diameters, elevated pipeline negative pressures, and closer leakage positions to the pipeline center, the relative localization error was smaller, the localization accuracy was higher, and the stability was greater. The research results could lay the foundation for the fault diagnosis and localization of coal mine gas drainage pipeline networks and provide technical support for safe and efficient coal mine gas drainage.
Reinforcement Learning-Based Vibration Control for Half-Car Active Suspension Considering Unknown Dynamics and Preset Convergence Rate
Authors: Wang Gang , Deng Jiafan , Zhou Tingting , Liu Suqi
Published: July 2024

Electromagnetic actuators, characterized by their lack of pneumatic or hydraulic circuits, rapid response, and ease of control, have the potential to significantly enhance the dynamic performance of automotive active suspensions. However, the complexity associated with their models and the calibration of control parameters hampers the efficiency of control design. To address this issue, this paper proposes a reinforcement learning vibration control strategy for electromagnetic active suspension. Firstly, a half-car dynamic model with electromagnetic active suspension is established. Considering the unknown dynamics of the actuator and its preset convergence performance, an optimal control method based on reinforcement learning is investigated. Secondly, a heuristic PI adaptive dynamic programming algorithm is presented. This method can update to the optimal control solution without requiring model parameters or initial design parameters. Finally, the energy consumption and dynamic performance of this method are analyzed through rapid prototyping control simulation. The results show that the ride comfort of the vehicle suspension can be improved with the given preset convergence rate.
Modern Geochemical and Tectonic Exploration—The Key Factor in Discovering the Northern Copper Belt, Poland
Authors: Speczik Stanisław , Zieliński Krzysztof , Pietrzela Alicja , Bieńko Tomasz
Published: July 2024

The discovery of the Northern Copper Belt in SW Poland is a result of an extensive exploration project with a key role played by various science-related methods. The project relied on mapping the distribution of mineral zones in the entire Fore-Sudetic Monocline, a unit known for its occurrences of Cu-Ag orebodies. This approach involved the examination of historical drill cores from over 400 oil and gas holes in this area, with the collection of samples for laboratory analyses. A close relationship was confirmed between the distribution of orebodies and the transformation of organic matter. Rock-Eval pyrolysis was also performed on selected samples. The tests of rock specimens were accompanied by the reprocessing of historical gravimetric and seismic surveying results. Field magnetotelluric surveying was also performed in certain areas. This phase resulted in the identification of areas with a high probability of finding the best ore, allowing for the initiation of the drilling stage. So far, 37 exploratory boreholes have been drilled in those locations, nearly all of them with highly positive results. The Northern Copper Belt consists of three deposits, Nowa Sól, Mozów, and Sulmierzyce North, along with numerous prognostic areas distributed therebetween. The future production of copper, silver, and the accompanying valuable elements presents a chance to provide the whole of Europe with a new plentiful supply of those critical raw materials.
Circular Economy in Practice: A Literature Review and Case Study of Phosphogypsum Use in Cement
Authors: Bumanis Girts , Vaičiukynienė Danutė , Tambovceva Tatjana , Puzule Liga , Sinka Maris , Nizevičienė Dalia , Fornés Ignacio , Bajare Diana
Published: July 2024

The utilization of waste generated from industrial production is a burden to overcome for society to reach a circular economy. Usually, production waste is associated with low-quality materials compared to its natural counterparts. In some cases, high-purity materials are generated, while different hazardous substances such as heavy metals, radioactive elements, or organic chemical substances are pollutants that often limit the materials’ further application. One such material that has accumulated for decades is phosphogypsum (PG). The extraction of fertilizers from metamorphous rocks results in large quantities of PG. Until now, PG has been deposited in large stockpiles near the production plant, causing problems for the environment in the surrounding area. However, the chemical composition of PG places it as a high-purity artificial gypsum material, which means that it could be used as a substitution or supplementary material in gypsum-based material production. The concerns, with respect to both legislation and prevailing prejudices in society, about its impurities strongly limit its application. This manuscript reviews current research practices for the effective use of PG and analyzes the importance of the circular economy. A life cycle assessment of current state-of-the-art technologies regarding PG application is proposed.
Association of SARS-CoV-2 Seropositivity with Persistent Immune Activation in HIV/Tuberculosis Co-Infected Patients
Authors: Shete Ashwini , Ghate Manisha , Iwasaki-Hozumi Hiroko , Patil Sandip , Shidhaye Pallavi , Matsuba Takashi , Bai Gaowa , Pharande Pratiksha , Hattori Toshio
Published: July 2024

We asked if SARS-CoV-2 seropositivity in HIV/TB co-infected patients plays a role in precipitating active tuberculosis in HIV-infected individuals and alters inflammatory status. A prospective study was conducted on HIV/TB co-infected patients presenting with pulmonary (n = 20) or extrapulmonary (n = 12) tuberculosis. Abbott SARS-CoV-2 IgG kits assessed the presence of anti-nucleoprotein antibodies. Inflammatory markers viz. osteopontin, total and full-length galectin-9, and C-reactive protein were tested at baseline and the end of antituberculosis treatment. The inflammatory score (INS) was assessed based on the percentage of reduction in the inflammatory markers’ levels at the end of the treatment. Anti-SARS-CoV-2 antibodies were detected in five male patients diagnosed with pulmonary (n = 2) and extrapulmonary (n = 3) TB. None of them reported symptomatic COVID-19. Inflammatory marker levels did not differ significantly at baseline compared to those in seronegative patients. However, the INS correlated negatively with SARS-CoV-2 seropositivity (r = −0.386, p = 0.039), indicating persistently raised inflammatory markers in these patients at the end of the treatment compared to seronegative individuals. Among the four markers studied, total galectin-9 levels failed to decrease significantly in these patients (p = 0.030). The majority of HIV/TB co-infected patients enrolled in our study (84.5%) were SARS-CoV-2-seronegative, indicating that SARS-CoV-2 infection might not have played a role in precipitating TB reactivation.
Enhanced Design of an Adaptive Anthropomorphic Finger through Integration of Modular Soft Actuators and Kinematic Modeling
Authors: Lin Sheng-Guan , Chang Jen-Yuan (James)
Published: July 2024

This study introduces a novel modular soft actuator designed for an anthropomorphic robotic finger that addresses the need for adaptive behavior and precise joint-angle control. The key innovation is its modular design, which enables independent pressure regulation in each air chamber, thus achieving superior precision compared to traditional PneuNets soft actuators. A rigid skeleton is integrated to enhance force transmission and measurement capabilities and thus ensure effective force handling and transmission within each module. The versatility of the actuator is demonstrated through its adaptability in various scenarios, and its features include adaptive positional control achieved by modulating the inflation in each air chamber. This research includes kinematic and kinetostatic analyses to ensure precise control of joint angles and forces at the finger’s endpoint. Experimental results confirm the actuator’s excellent performance and adaptability, providing valuable insights for advancing soft-actuator technology. The findings suggest significant potential for this actuator in diverse applications, emphasizing its role in the future development of precise and adaptable robotic systems.
CPROS: A Multimodal Decision-Level Fusion Detection Method Based on Category Probability Sets
Authors: Li Can , Zuo Zhen , Tong Xiaozhong , Huang Honghe , Yuan Shudong , Dang Zhaoyang
Published: July 2024

Images acquired by different sensors exhibit different characteristics because of the varied imaging mechanisms of sensors. The fusion of visible and infrared images is valuable for specific image applications. While infrared images provide stronger object features under poor illumination and smoke interference, visible images have rich texture features and color information about the target. This study uses dual optical fusion as an example to explore fusion detection methods at different levels and proposes a multimodal decision-level fusion detection method based on category probability sets (CPROS). YOLOv8—a single-mode detector with good detection performance—was chosen as the benchmark. Next, we innovatively introduced the improved Yager formula and proposed a simple non-learning fusion strategy based on CPROS, which can combine the detection results of multiple modes and effectively improve target confidence. We validated the proposed algorithm using the VEDAI public dataset, which was captured from a drone perspective. The results showed that the mean average precision (mAP) of YOLOv8 using the CPROS method was 8.6% and 16.4% higher than that of the YOLOv8 detection single-mode dataset. The proposed method significantly reduces the missed detection rate (MR) and number of false detections per image (FPPI), and it can be generalized.
Multiple Land-Use Simulations and Driving Factor Analysis by Integrating a Deep Cascade Forest Model and Cellular Automata: A Case Study in the Pearl River Delta, China
Authors: Zhuang Haoming , Liu Xiaoping , Yan Yuchao , Li Bingjie , Wu Changjiang , Liu Wenkai
Published: July 2024

Cellular automata (CA) models have been extensively employed to predict and understand the spatiotemporal dynamics of land use. Driving factors play a significant role in shaping and driving land-use changes. Mining land-use transition rules from driving factors and quantifying the contribution of driving factors to land-use dynamics are fundamental aspects of CA simulation. However, existing CA models have limitations in obtaining accurate transition rules and reliable interpretations simultaneously for multiple land-use simulations. In this study, we constructed a CA model based on a tree-based deep learning algorithm, deep cascade forest (DCF), to improve multiple land-use simulations and driving factors analysis. The DCF algorithm was utilized to mine accurate multiple land-use transition rules without overfitting to improve CA simulation accuracy. Additionally, a novel ensemble mean decrease of impurity (MDI) factor importance analysis method (DCF-MDI), which leverages the cascade structure of the DCF model, was proposed to qualify the contribution of each driving factor to land-use dynamics stably and efficiently. To evaluate the effectiveness of the proposed DCF-CA, we applied the model to simulate land-use distributions and explore the driving mechanisms of land-use dynamics in the Pearl River Delta (PRD), China, from 2000 to 2010. Compared to existing models, the proposed DCF-CA model exhibits the highest accuracy (FoM = 23.79%, PA = 39.77%, UA = 36.35%, OA = 91.50%), which demonstrates its superiority in mining accurate transition rules for capturing multiple land-use dynamics. Factor importance analysis reveals that the proposed DCF-MDI method yields more stable ranking orders and lower standard deviation of contribution weights (<0.10%) compared to the traditional method, indicating its robustness to random disturbances and effectiveness in elucidating the driving mechanisms of land-use dynamics. The DCF-CA model proposed in this study, demonstrating high simulation accuracy and reliable interpretability simultaneously, can provide substantial support for sustainable land use management.