bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization of Key Phytoconstituents in Nigella Oil from Diverse Sources and Their Transfer Efficiency During Oil Processing
Authors: Thani Parbat Raj , Johnson Joel B. , Bhattarai Surya , Trotter Tieneke , Walsh Kerry , Broszczak Daniel , Naiker Mani
Published: November 2024

Nigella sativa L., which is commonly referred to as black cumin, is a globally recognized plant for the nutraceutical and pharmaceutical values of its seed oil. While numerous studies have investigated Nigella oil, there is a scarcity of information regarding the variation of key phytoconstituents in Nigella oil from diverse seed sources. It is also unclear whether the variation in phytoconstituents across different seed sources translates to variations in their respective oils, which is important for understanding their health benefits. Additionally, there is a gap in information on how specific phytochemicals transfer from seed to oil during the oil pressing. Therefore, this study investigated Nigella sourced from different genotypes and agricultural practices (planting densities and sowing times) to determine total phenolic content (TPC), antioxidant capacity (FRAP and CUPRAC), thymoquinone (TQ), and fatty acid composition. The results showed significant variation of TPC (87.4–144.1 mg gallic acid equivalents (GAE)/100 g), FRAP (454.1–560.9 mg Trolox equivalents (TE)/100 g), CUPRAC (356.3–482.5 mg TE/100 g), TQ (1493.5–2268.4 mg TQ/100 g), saturated fatty acid (SFA) (65.9–83.7 mg/g), monounsaturated fatty acid (MUFA) (42.5–67.8 mg/g), and polyunsaturated fatty acid (PUFA) (266.1–383.4 mg/g) in the oil derived from the seeds of different genotypes and agricultural practices. The total transfer of TPC, FRAP, and CUPRAC into the screw-pressed oil was relatively low, contributing only 2.3–3.7%, 7.1–11.7%, and 1.5–2.3%, respectively, of their total value in the respective seed. However, the transfer of TQ, SFA, MUFA, and PUFA was observed to be comparatively higher, contributing 32.8–48.5%, 60.8–84.2%, 45.6–74.4%, and 43.1–69.4%, respectively, of their total value in the respective seed. There was no strong correlation observed among TPC, FRAP, CUPRAC, and TQ, and none of the fatty acids showed a strong correlation with these variables.
Cooperative Path Planning for Multi-UAVs with Time-Varying Communication and Energy Consumption Constraints
Authors: Guo Jia , Gan Minggang , Hu Kang
Published: November 2024

In the field of Unmanned Aerial Vehicle (UAV) path planning, designing efficient, safe, and feasible trajectories in complex, dynamic environments poses substantial challenges. Traditional optimization methods often struggle to address the multidimensional nature of these problems, particularly when considering constraints like obstacle avoidance, energy efficiency, and real-time responsiveness. In this paper, we propose a novel algorithm, Dimensional Learning Strategy and Spherical Motion-based Particle Swarm Optimization (DLS-SMPSO), specifically designed to handle the unique constraints and requirements of cooperative path planning for Multiple UAVs (Multi-UAVs). By encoding particle positions as motion paths in spherical coordinates, the algorithm offers a natural and effective approach to navigating multidimensional search spaces. The incorporation of a Dimensional Learning Strategy (DLS) enhances performance by minimizing particle oscillations and allowing each particle to learn valuable information from the global best solution on a dimension-by-dimension basis. Extensive simulations validate the effectiveness of the DLS-SMPSO algorithm, demonstrating its capability to consistently generate optimal paths. The proposed algorithm outperforms other metaheuristic optimization algorithms, achieving a feasibility ratio as high as 97%. The proposed solution is scalable, adaptable, and suitable for real-time implementation, making it an excellent choice for a broad range of cooperative multi-UAV applications.
Modeling Critical Success Factors for Industrial Symbiosis
Authors: Chrysikopoulos Stamatios K. , Chountalas Panos T. , Georgakellos Dimitrios A. , Lagodimos Athanasios G.
Published: November 2024

The critical importance of effective industrial symbiosis is emphasized in the rapidly evolving landscape of manufacturing, energy, and environmental sustainability. This study employs the Decision Making Trial and Evaluation Laboratory (DEMATEL) methodology to examine and outline the complex interrelationships among critical success factors (CSFs) pivotal for the successful implementation of industrial symbiosis. Key findings indicate that leadership and technology are the most significant causal CSFs, driving positive outcomes in waste reduction, environmental impact, and economic growth, identified as primary effect factors. Leadership emerges as the predominant influence, guiding strategic alignment, fostering a collaborative and sustainable organizational culture, and affecting all other CSFs. Technological integration acts both as a direct driver of operational efficiency and as a mediator of leadership’s influence, enabling optimized resource flows and data-driven decision-making. Additional CSFs such as clear communication, enhanced training and education, and policy and regulatory support also serve as essential mediators connecting leadership to key outcomes. This research outlines an actionable pathway for stakeholders, including policymakers, engineers, and corporate executives, to strategically prioritize and utilize these CSFs to promote more resilient and sustainable industrial ecosystems.
The Spatiotemporal Dynamics of Vegetation Cover and Its Response to the Grain for Green Project in the Loess Plateau of China
Authors: Huang Yinlan , Jin Yunxiang , Chen Shi
Published: November 2024

The Grain for Green Project (GGP) is a major national initiative aimed at ecological improvement and vegetation restoration in China, achieving substantial ecological and socio-economic benefits. Nevertheless, research on vegetation cover trends and the long-term restoration efficacy of the GGP in the Loess Plateau remains limited. This study examines the temporal–spatial evolution and sustainability of vegetation cover in this region, using NDVI data from Landsat (2000–2022) with medium-high spatial resolution. The analytical methods involve Sen’s slope, Mann–Kendall non-parametric test, and Hurst exponent to assess trends and forecast sustainability. The findings reveal that between 2000 and 2022, vegetation coverage in the Loess Plateau increased by an average of 0.86% per year (p < 0.01), marked by high vegetation cover expansion (173 × 103 km2, 26.49%) and low vegetation cover reduction (149 × 103 km2, 22.83%). The spatial pattern exhibited a northwest-to-southeast gradient, with a transition from low to high coverage levels, reflecting a persistent increase in high vegetation cover and decrease in low vegetation cover. Approximately 93% of the vegetation cover in the Loess Plateau showed significant improvement, while 5% (approximately 31 × 103 km2) displayed a degradation trend, mainly in the urbanized and Yellow River Basin regions. Projections suggest that 90% of vegetation cover will continue to improve. In GGP-targeted areas, high and medium-high levels of vegetation cover increased significantly at rates of 0.456 ×103 km2/year and 0.304 × 103 km2/year, respectively, with approximately 75% of vegetation cover levels exhibiting positive trends. This study reveals the effectiveness of the GGP in promoting vegetation restoration in the Loess Plateau, offering valuable insights for vegetation recovery research and policy implementation in other ecologically fragile regions.
Ecological Stoichiometric Characteristics of C, N, and P in Pinus taiwanensis Hayata Needles, Leaf Litter, Soil, and Micro-Organisms at Different Forest Ages
Authors: Yuan Meng , Wang Yurong , Wang Yang , Wang Yi , Wang Shiwen , Pan Yang , Zhou Wangming , Xiang Xiaoyan , Tong Yuewei
Published: November 2024

The ecological stoichiometric characterization of plant and soil elements is essential for understanding the biogeochemical cycles of ecosystems. Based on three forest ages of Pinus taiwanensis Hayata (P. taiwanensis) plantations in the Gujingyuan National Nature Reserve (i.e., young (16 years), middle-aged (32 years), and mature forests (50 years)), we conducted a field experiment to analyzed C, N, and P stoichiometry and the relationships between needles, litter, soil, and micro-organisms in P. taiwanensis plantations. We intended to elucidate the nutritional characteristics and stability mechanisms of the artificial P. taiwanensis forest ecosystem. The results showed that the C contents of live needles, leaf litter, soil, and micro-organisms in P. taiwanensis plantation forests of the three forest ages were 504.17–547.05, 527.25–548.84, 23.40–35.85, and 0.33–0.54 g/kg, respectively; the respective N contents were 11.02–13.35, 10.71–11.76, 1.42–2.56, and 0.08–0.12 g/kg; and the respective P contents were 0.82–0.91, 0.60–0.74, 0.19–0.36, and 0.03–0.06 g/kg. Forest age significantly influenced both the C, N, and P contents in live needles, leaf litter, soil, and micro-organisms as well as stoichiometric characteristics (p < 0.05). Furthermore, although the litter N:P content was comparable to that of needles, the ratios of C:N and C:P in the litter were notably higher compared to those in needles. Soil C:P and N:P ratios were the highest in mature forests while microbial C:P and N:P ratios continuously decreased. Stoichiometric analyses of our findings suggest that forest stand age can influence divergent changes in element cycling among plants, soil, and micro-organisms. The presented results can aid in further understanding nutrient utilization strategies and regulatory mechanisms for P. taiwanensis plantation forest systems.
Forest Fire Burn Scar Mapping Based on Modified Image Super-Resolution Reconstruction via Sparse Representation
Authors: Zhang Juan , Zhang Gui , Xu Haizhou , Chu Rong , Yang Yongke , Wang Saizhuan
Published: November 2024

It is of great significance to map forest fire burn scars for post-disaster management and assessment of forest fires. Satellites can be utilized to acquire imagery even in primitive forests with steep mountainous terrain. However, forest fire burn scar mapping extracted by the Burned Area Index (BAI), differenced Normalized Burn Ratio (dNBR), and Feature Extraction Rule-Based (FERB) approaches directly at pixel level is limited by the satellite imagery spatial resolution. To further improve the spatial resolution of forest fire burn scar mapping, we improved the image super-resolution reconstruction via sparse representation (SCSR) and named it modified image super-resolution reconstruction via sparse representation (MSCSR). It was compared with the Burned Area Subpixel Mapping–Feature Extraction Rule-Based (BASM-FERB) method to screen a better approach. Based on the Sentinel-2 satellite imagery, the MSCSR and BASM-FERB approaches were used to map forest fire burn scars at the subpixel level, and the extraction result was validated using actual forest fire data. The results show that forest fire burn scar mapping at the subpixel level obtained by the MSCSR and BASM-FERB approaches has a higher spatial resolution; in particular, the MSCSR approach can more effectively reduce the noise effect on forest fire burn scar mapping at the subpixel level. Five accuracy indexes, the Overall Accuracy (OA), User’s Accuracy (UA), Producer’s Accuracy (PA), Intersection over Union (IoU), and Kappa Coefficient (Kappa), are used to assess the accuracy of forest fire burn scar mapping at the pixel/subpixel level based on the BAI, dNBR, FERB, MSCSR and BASM-FERB approaches. The average accuracy values of the OA, UA, PA, IoU, and Kappa of the forest fire burn scar mapping results at the subpixel level extracted by the MSCSR and BASM-FERB approaches are superior compared to the forest fire burn scar mapping results at the pixel level extracted by the BAI, dNBR and FERB approaches. In particular, the average accuracy values of the OA, UA, PA, IoU, and Kappa of the forest fire burn scar mapping at the subpixel level detected by the MSCSR approach are 98.49%, 99.13%, 92.31%, 95.83%, and 92.81%, respectively, which are 1.48%, 10.93%, 2.47%, 15.55%, and 5.90%, respectively, higher than the accuracy of that extracted by the BASM-FERB approach. It is concluded that the MSCSR approach extracts forest fire burn scar mapping at the subpixel level with higher accuracy and spatial resolution for post-disaster management and assessment of forest fires.
The Hydration-Dependent Dynamics of Greenhouse Gas Fluxes of Epiphytic Lichens in the Permafrost-Affected Region
Authors: Masyagina Oxana V. , Evgrafova Svetlana Yu. , Kovaleva Natalia M. , Detsura Anna E. , Porfirieva Elizaveta V. , Menyailo Oleg V. , Matvienko Anastasia I.
Published: November 2024

Recent studies actively debate oxic methane (CH4) production processes in water and terrestrial ecosystems. This previously unknown source of CH4 on a regional and global scale has the potential to alter our understanding of climate-driving processes in vulnerable ecosystems, particularly high-latitude ecosystems. Thus, the main objective of this study is to use the incubation approach to explore possible greenhouse gas (GHG) fluxes by the most widely distributed species of epiphytic lichens (ELs; Evernia mesomorpha Nyl. and Bryoria simplicior (Vain.) Brodo et D. Hawksw.) in the permafrost zone of Central Siberia. We observed CH4 production by hydrated (50%–400% of thallus water content) ELs during 2 h incubation under illumination. Moreover, in agreement with other studies, we found evidence that oxic CH4 production by Els is linked to the CO2 photoassimilation process, and the EL thallus water content regulates that relationship. Although the GHG fluxes presented here were obtained under a controlled environment and are probably not representative of actual emissions in the field, more research is needed to fully comprehend ELs’ function in the C cycle. This particular research provides a solid foundation for future studies into the role of ELs in the C cycle of permafrost forest ecosystems under ongoing climate change (as non-methanogenesis processes in oxic environments).
Optimizing Pinus tabuliformis Forest Spatial Structure and Function in Beijing, China
Authors: Zhang Yan , Qi Shi , Zhang Lin , Guo Yanrui , Zhang Dai , Liu Shaodong , Ma Luxiao , Hu Jun , Lu Jinsheng , Wang Xiangyu
Published: November 2024

Enhancing forest ecological functioning by optimizing stand structure is essential in high-quality, sustainable forests. We examined this in 38 plots (20 m × 20 m) of Pinus tabuliformis forests in the mountainous area of Beijing. We investigated and analyzed the spatial structure and functional characteristics of these plots. Structural equation modeling and response surface methodology were used to identify spatial structural stand factors affecting soil nutrient levels and understory biodiversity. We examined the pathways and strengths of the coupling relationships between structure and function and the ranges and thresholds of changes in these structural factors. Mingling degree, openness degree, competition index, and forest layer index substantially affected the understory herbaceous species diversity and soil nutrient levels. Mingling degree significantly impacted understory biodiversity and soil nutrient levels (direct path coefficient (DPC), 0.48 and 0.70, respectively). Openness degree significantly affected understory species diversity (DPC, 0.37). The competition index and forest layer index exerted less significant direct impacts on these functions; competition influenced herbaceous diversity primarily indirectly. The optimal features were as follows: mingling degree, 0.8; openness degree, 1.1; competition index, 0.3; and forest layer index, 0.5. Average understory herbaceous species diversity and soil nutrient levels are projected to increase by ca. 47.74% and 52.29%, respectively, post optimization. These findings provide a reference for precise regulated stand structures and establish multifunction management optimization objectives in Beijing’s mountainous Pinus tabuliformis forests.
Molecular Mechanisms of Poplar Adaptation to Water–Fertilizer Coupling: Insights from Transcriptomic and Metabolomic Analyses
Authors: Shen Jiajia , Li Xiao , Jiang Luping , Wang Hongxing , Pang Zhongyi , Peng Yanhui , Zhang Xinxin , Zhao Xiyang
Published: November 2024

The aim of this paper was to investigate the transcriptomic and metabolomic differences in Populus cathayana × canadasis ‘Xinlin1’ (P. cathayana × canadasis ‘Xinlin 1’) under varying irrigation and fertilization conditions. Ten-year-old P. cathayana × canadasis ‘Xinlin 1’ was selected as the test subject in this study; different irrigation and fertilization treatments were set up, and DEGs and DAMs in response to water and fertilizer regulation were identified. Transcriptomic and metabolomic profiles were analyzed from both leaves and roots. A total of 22,870 DEGs were identified in response to water and fertilizer treatments, predominantly belonging to 48 transcription factor families, including MYB, ERF, and MYB-related ones. Additionally, 2432 DAMs were detected and categorized into 18 metabolite classes, with flavonoids being the most abundant (342 metabolites), followed by terpenoids, lipids, and others. KEGG enrichment analysis revealed that DEGs and DAMs were significantly associated with pathways such as plant hormone signal transduction and starch and sucrose metabolism pathways. The levels of ABA exhibited an initial decrease followed by an increase, with several key genes, including PYR/PYL, PP2C, SnRK2, and ABF, also differentially expressed in the plant hormone signal transduction pathway. In the starch and sucrose metabolic pathways, sucrose was more hydrolyzed into D-fructose, which gradually translocated from roots to leaves. DEGs were significantly involved in sucrose synthesis and decomposition into D-fructose and 1,3-β-glucose, as well as starch synthesis and starch decomposition into cellulose dextrin, which underwent complete hydrolysis to glucose. In the starch hydrolysis process, 29 DEGs were involved, with 12 down-regulated and 17 up-regulated.
Anti-Inflammatory and Osteogenic Effects of Vitamin K from Sargassum fulvellum Fermented by Lactococcus lactis KCCM12759P and Leuconostoc mesenteroides KCCM12756P
Authors: Sim Yejin , Jo Hyun-Sol , Kim Choong-Gon , Cho Young-Eun , Yang Jungwoo , Hong Sun-Mee
Published: November 2024

Vitamin K (VitK) is a vital nutrient that is newly recognized to support bone and cardiovascular health. As a nutraceutical, VitK is produced via plant extraction and bacterial fermentation. This study examined the potential anti-inflammatory and osteogenic benefits of VitK, i.e., VitK1 (phylloquinone; PK) and VitK2 (menaquinone; MKs), derived from Sargassum fulvellum fermented by Lactococcus lactis and Leuconostoc mesenteroides (SfLlLm) using lipopolysaccharide (LPS)-induced Raw264.7, MC3T3-E1 cells, and ovariectomized (OVX) mice. MK4, MK7, and MK9, as well as PK, were effectively acquired from SfLlLm and analyzed. SfLlLm_VitK reduced levels of proinflammatory cytokine in LPS-induced Raw264.7 cells and induced an osteogenesis regulating factor in MC3T3-E1 cells. In OVX mice, SfLlLm feeding reduced plasma levels of alkaline phosphatase, phosphate, and the pro-collagen type I alpha 2 gene (pro-Col1a2) while elevating cancellous bone volume and trabecular numbers. Accordingly, SfLlLm, comprising MKs, may be a candidate for preventing and treating immune and bone diseases.
Coating of Hemp Fibres with Hydrophobic Compounds Extracted from Pine Bark
Authors: Abbel Robert , Risani Regis , Nourtier Maxime , Donaldson Lloyd , Brunschwig Christel , Mayer-Laigle Claire , Bridson James , Thumm Armin , Dickson Alan , Murray Rachel , Harris Jessica , Beaugrand Johnny , Hill Stefan
Published: November 2024

Applying coatings of paraffins and other synthetic waxes is a common approach to impart hydrophobic properties to fibres and thus control their surface characteristics. Replacing these fossil-based products with alternatives derived from renewable resources can contribute to humankind’s transition to a sustainable bioeconomy. This study presents the coating of hemp fibres with waxes extracted from pine bark as an exemplar application. Two bio-based emulsifiers were used to prepare wax emulsions suitable for a dry blending process. The coatings on the fibres were characterised, quantified, and visualised using a combination of spectroscopic and microscopic techniques. Confocal fluorescence microscopy was an excellent tool to investigate the spatial distribution of the pine bark waxes on the fibre surfaces. While successful deposition was demonstrated for all tested formulations, coating homogeneity varied for different emulsifiers. Compounding the hemp fibres with a bio-based polyester resulted in the substantial improvement of the mechanical behaviour. However, the presence of a wax coating on the fibres did not lead to a significant change in mechanical properties compared to the controls with uncoated fibres. Optimising the composite chemistry or adjusting the processing conditions might improve the compatibility of the hemp fibres with the matrix material, resulting in enhanced mechanical performance.
Artificial Induction of Spawning in Threeline Grunt, Parapristipoma trilineatum Under Controlled Environmental Conditions
Authors: Park Jin Woo , Cho Jeong-Hyeon , Baek Seong Il , Im Kang-Hee , Ryu Yong-Woon
Published: November 2024

The threeline grunt (Parapristipoma trilineatum) is a recently introduced aquaculture species that has attracted considerable interest in Korea. However, research on its aquaculture potential and reproductive biology remains limited. This study aimed to investigate the natural reproductive cycle and the feasibility of manipulating the spawning period of the threeline grunt through environmental control. We designed an environmental changes protocol involving a gradual increase in water temperature (16 °C → 21 °C) and extension of photoperiod (10 L → 14 L) from January to April and compared the group exposed to these conditions to those maintained under natural conditions. The experimental group exhibited significantly higher plasma sex steroid hormone levels at 60 and 90 days and significantly higher gonadosomatic index at 100 days. In addition, the experimental group spawned between April and June, approximately 2 months earlier than that of the control group. Despite earlier spawning, no significant differences were found in egg diameter, hatching rate, and larval notochord length. These findings suggest that spawning can be accelerated through photothermal changes without negatively impacting egg and larval quality. This study provides valuable insights into the reproductive biology of the threeline grunt and highlights the potential of utilizing photothermal control to enhance its aquaculture production.
Detection of Apple Sucrose Concentration Based on Fluorescence Hyperspectral Image System and Machine Learning
Authors: Zhan Chunyi , Mao Hongyi , Fan Rongsheng , He Tanggui , Qing Rui , Zhang Wenliang , Lin Yi , Li Kunyu , Wang Lei , Xia Tie’en , Wu Youli , Kang Zhiliang
Published: November 2024

China ranks first in apple production worldwide, making the assessment of apple quality a critical factor in agriculture. Sucrose concentration (SC) is a key factor influencing the flavor and ripeness of apples, serving as an important quality indicator. Nondestructive SC detection has significant practical value. Currently, SC is mainly measured using handheld refractometers, hydrometers, electronic tongues, and saccharimeter analyses, which are not only time-consuming and labor-intensive but also destructive to the sample. Therefore, a rapid nondestructive method is essential. The fluorescence hyperspectral imaging system (FHIS) is a tool for nondestructive detection. Upon excitation by the fluorescent light source, apples displayed distinct fluorescence characteristics within the 440–530 nm and 680–780 nm wavelength ranges, enabling the FHIS to detect SC. This study used FHIS combined with machine learning (ML) to predict SC at the apple’s equatorial position. Primary features were extracted using variable importance projection (VIP), the successive projection algorithm (SPA), and extreme gradient boosting (XGBoost). Secondary feature extraction was also conducted. Models like gradient boosting decision tree (GBDT), random forest (RF), and LightGBM were used to predict SC. VN-SPA + VIP-LightGBM achieved the highest accuracy, with Rp2, RMSEp, and RPD reaching 0.9074, 0.4656, and 3.2877, respectively. These results underscore the efficacy of FHIS in predicting apple SC, highlighting its potential for application in nondestructive quality assessment within the agricultural sector.
Evaluating the Greenness of Wine Analytical Chemistry: A New Metric Approach
Authors: Thanasi Vasiliki , Lopes Ana Beatriz , Barros Paulo , Ribeiro Natalia , Ricardo-da-Silva Jorge M. , Catarino Sofia
Published: November 2024

While the wine industry has already adopted some sustainable and environmentally friendly practices, special attention should be paid to the greenness of the analytical methodologies used. In this study, a new tool called “Green Wine Analytical Procedure Evaluation” (GWAPE) was developed to fulfill these “green” requirements. This framework offers a structured approach to evaluating the environmental impact of wine analysis processes, covering all the analytical steps from sample collection to the final results. GWAPE provides quantitative information, uses schematic representations, assigns varying levels of importance to green chemistry principles, and conducts detailed evaluations of hazard structures. Since wine analytical methods typically involve fewer highly hazardous reagents, certain criteria previously applied in green analytical chemistry should be integrated or omitted. In summary, GWAPE offers a customized and precise solution to help the laboratories of enology and the wineries assess their analytical methodologies’ environmental impact. As an example of application, the proposed metric was used to evaluate the greenness of three different standard analytical methodologies to determine sugars in wine, showing good discrimination ability.
Preparation, Characterization, Stability and In Vitro Release of a Pea Protein Fibril-Based Iron Fortificant via Self-Assembly
Authors: Chen Xiaoting , Yi Jiang , Wen Zhen , Fan Yuting
Published: November 2024

It is assumed that the stability and bioaccessibility of iron ions in iron–pea protein fibril (Fe-Fib PP) nanocomposite can be remarkably enhanced, and Fe-Fib PP exhibits great potential as an effective iron fortificant. Fe-Fib PP, a stable and effective iron supplement, was fabricated based on the reducing property of pea protein fibrils, derived from pea protein through thermal treatment at pH 2.0. The results demonstrated that the reducing power of iron was remarkably affected by fibril concentration and fibrillization degree. The reducing power of pea protein fibrils gradually enhanced from 0.31 to 0.92 with the increase in incubation time from 0 to 48 h. Compared with iron nanoparticles (Fe–Nano), Fe-Fib PP possessed much higher dispersibility. Additionally, the stability of iron in Fe-Fib PP was significantly higher than that in Fe–Nano under different storage conditions. X-ray photoelectron spectroscopy (XPS) outcomes revealed Fe (II) content in Fe-Fib PP (70.75 ± 0.65%) was remarkably higher than that of Fe–Nano (56.05 ± 0.50%). In addition, the bioaccessibility of Fe (II) dramatically improved from 42.7% to 62.8% using PP fibrils as carriers. The findings suggest that Fe-Fib PP is an effective iron nutrition enhancer.
Synergy of Modern Analytics and Innovative Managerial Decision-Making in the Turbulent and Uncertain New Normal
Authors: Kovacova Maria , Kalinova Eva , Durana Pavol , Frajtova Michalikova Katarina
Published: November 2024

This paper focuses on analyzing the relationship between the financial performance of companies and their ability to utilize modern business methods. Financial analysis was conducted using the example of the automobile manufacturer Škoda Auto, with the results providing deeper insights into the company’s financial situation. The companies examined in this study were scored and underwent regression and cluster analyses. A questionnaire focusing on the modernity of advertising in selected companies was answered by 276 respondents. Based on the findings, a model for evaluating the modernity and stability of companies was developed, combining various factors including financial indicators and the adoption of modern technologies. The results indicate that there is a relationship between financial performance and the modernization of companies, although this relationship is not always straightforward. In particular, the operating profit and current ratio emerged as important factors influencing modernization. Overall, it can be concluded that the financial performance and modernization of companies are interconnected, but their relationship is complex and requires further investigation. This paper is an important contribution to understanding company modernization and sets the stage for further studies on this issue.
Nerve Signal Transferring Mechanism and Mathematical Modeling of Artificial Biological System Design
Authors: Park Jeongseop , Yoo Sehwan , Jeong Taikyeong
Published: November 2024

Our investigation demonstrates the necessity of mathematical modeling and design methodologies for nerve signals in the creation of artificial arms. Nerve impulses vary widely in speed; for example, unmyelinated nerves transmit impulses at around one mile per hour, while myelinated nerves conduct impulses at around 200 miles per hour. The electrical signals originating from the brain, such as those measured by electroencephalography, are translated into chemical reactions in each organ to produce energy. In this paper, we describe the mechanism by which nerve signals are transferred to various organs, not just the brain or spinal cord, as these signals account for the measured amounts of physical force—i.e., energy—as nerve signals. Since these frequency signals follow no fixed pattern, we consider wavelength and amplitude over a particular time frame. Our simulation results begin with the mechanical distinction that occurs throughout the entire process of nerve signal transmission in the artificial arm as an artificial biological system, and show numerical approaches and algebraic equations as a matrix in mathematical modeling. As a result, the mathematical modeling of nerve signals accurately reflects actual human nerve signals. These chemical changes, involving K (potassium), Na (sodium), and Cl (chloride), are linked to muscle states as they are converted into electrical signals. Investigating and identifying the neurotransmitter signal transmission system through theoretical approaches, mechanical analysis, and mathematical modeling reveals a strong relationship between mathematical simulation and algebraic matrix analysis.
Revolutionary ZVI-Entrapped Sol–Gel Silica Matrices: Efficient Catalytic Reduction of High-Concentration Halo-Organic Compounds—Addressing Bromoacetic Acid Contamination in Industrial Wastewaters
Authors: Rolly Gifty Sara , Meyerstein Dan , Burg Ariela , Shamir Dror , Albo Yael
Published: November 2024

The de-halogenation of highly concentrated halo-organic compounds using Zero Valent Iron entrapped in silica matrices as a catalyst was investigated. This study aimed to evaluate the effectiveness of the Zero Valent Iron-entrapped organically modified silica matrices in transforming highly concentrated hazardous halogenated compounds into environmentally benign materials in the presence of BH4−. The Zero Valent Iron-entrapped silica gel matrices were synthesized using the sol–gel method. The de-halogenation products were analyzed using high-performance liquid chromatography. The results suggest that the Zero Valent Iron-entrapped silica matrices are effective catalysts in the de-halogenation reaction of halo-organics by BH4− with 100% efficiency. The current work also highlights the complete de-bromination of harmful wastewater generated by the bromoacetic acid manufacturing industry using Zero Valent Iron-entrapped silica matrices. Therefore, Zero Valent Iron-entrapped silica matrices can be considered potential candidates for the catalytic removal of highly concentrated halo-organic compounds from contaminated water. This technology can play a crucial role in reducing the environmental impact of hazardous substances.
Navigating the Spectrum: Assessing the Concordance of ML-Based AI Findings with Radiology in Chest X-Rays in Clinical Settings
Authors: Kromrey Marie-Luise , Steiner Laura , Schön Felix , Gamain Julie , Roller Christian , Malsch Carolin
Published: November 2024

Background: The integration of artificial intelligence (AI) into radiology aims to improve diagnostic accuracy and efficiency, particularly in settings with limited access to expert radiologists and in times of personnel shortage. However, challenges such as insufficient validation in actual real-world settings or automation bias should be addressed before implementing AI software in clinical routine. Methods: This cross-sectional study in a maximum care hospital assesses the concordance between diagnoses made by a commercial AI-based software and conventional radiological methods augmented by AI for four major thoracic pathologies in chest X-ray: fracture, pleural effusion, pulmonary nodule and pneumonia. Chest radiographs of 1506 patients (median age 66 years, 56.5% men) consecutively obtained between January and August 2023 were re-evaluated by the AI software InferRead DR Chest®. Results: Overall, AI software detected thoracic pathologies more often than radiologists (18.5% vs. 11.1%). In detail, it detected fractures, pneumonia, and nodules more frequently than radiologists, while radiologists identified pleural effusions more often. Reliability was highest for pleural effusions (0.63, 95%-CI 0.58–0.69), indicating good agreement, and lowest for fractures (0.39, 95%-CI 0.32–0.45), indicating moderate agreement. Conclusions: The tested software shows a high detection rate, particularly for fractures, pneumonia, and nodules, but hereby produces a nonnegligible number of false positives. Thus, AI-based software shows promise in enhancing diagnostic accuracy; however, cautious interpretation and human oversight remain crucial.
The Importance of Interprofessional Collaboration (IPC) Guidelines in Stunting Management in Indonesia: A Systematic Review
Authors: Sentika Rachmat , Setiawan Trisna , Kusnadi Kusnadi , Rattu Deborah Johana , Yunita Irma , Masita Bertri Maulidya , Basrowi Ray Wagiu
Published: November 2024

Background: Indonesia’s stunting prevention programs have shown limited effectiveness and scalability. Interprofessional collaboration (IPC) is crucial for preventing and treating pediatric stunting. This study aimed to investigate the roles of primary health centers and IPC in addressing stunting in Indonesia. Methods: A systematic review was conducted, searching PubMed, EMBASE, Web of Science, ProQuest, and Google Scholar for studies up to November 2023. Two reviewers independently screened and included full-text articles that examined IPC and stunting, focusing on prevalence, policy implications, healthcare roles, community roles, preventive measures, and challenges. Results: The review included 52 articles. IPC was found to be critical in reducing stunting prevalence. Training improved the knowledge of health cadres, aiding in the early detection and prevention of stunting. The studies emphasized IPC’s positive impact on stunting reduction across various regions. Policymakers are encouraged to adopt a comprehensive strategy involving collaboration, financial support, and effective program implementation. Conclusions: This study highlights IPC as essential in reducing stunting in Indonesia. Integrating stunting management into primary healthcare is recommended, with a call for developing guidelines to standardize and optimize the approach to this public health issue.
Implementation of Integrated Pest Management Measures in Vegetable Cropping Systems
Authors: Ramasamy Srinivasan
Published: November 2024

Vegetable crops play an important role in diversifying cropping systems and improving nutrition [...]
An Evaluation of Organic Biostimulants as a Tool for the Sustainable Management of Viral Infections in Zucchini Plants
Authors: Corrado Carla Libia , Donati Livia , Taglienti Anna , Ferretti Luca , Faggioli Francesco , Reverberi Massimo , Bertin Sabrina
Published: November 2024

In agriculture, new and sustainable strategies are increasingly demanded to integrate the traditional management of viral diseases based on the use of virus-free propagation materials and resistant or tolerant cultivars and on the control of insect vectors. Among the possible Integrated Pest Management (IPM) approaches, organic biostimulants have shown promising results in enhancing plant tolerance to virus infections by improving plant fitness and productivity and modulating metabolic functions. In this study, the combination of two organic biostimulants, Alert D-Max and Resil EVO Q, composed of seaweed and alfalfa extracts, enzymatic hydrolysates, and micronized zeolite, was applied on the leaves and roots of zucchini squashes, both healthy and infected by zucchini yellow mosaic virus (ZYMV). Four applications were scheduled based on ZYMV inoculation timing, and plant vegetative and reproductive parameters were recorded along with the virus titre and symptom severity. The modulation of the expression of specific genes potentially involved in pattern-triggered immunity (PTI), systemic acquired resistance (SAR), and oxidative stress defence pathways was also investigated. Besides increasing the general fitness of the healthy plants, the biostimulants significantly improved the production of flowers and fruits of the infected plants, with a potential positive impact on their productivity. The repeated biostimulant applications also led to a one-tenth reduction in ZYMV titre over time and induced a progressive slowdown of symptom severity. Genes associated with SAR and PTI were up-regulated after biostimulant applications, suggesting the biostimulant-based priming of plant defence mechanisms. Due to the observed beneficial effects, the tested biostimulant mix can be an effective component of the IPM of cucurbit crops, acting as a sustainable practice for enhancing plant fitness and tolerance to potyviruses.
Deciphering Fire Blight: From Erwinia amylovora Ecology to Genomics and Sustainable Control
Authors: Mendes Rafael J. , Regalado Laura , Rezzonico Fabio , Tavares Fernando , Santos Conceição
Published: November 2024

Fire blight is a highly destructive plant disease that affects the pome fruit value chain, with high economic impacts. Its etiological agent is the Gram-negative bacterium Erwinia amylovora. The origin of fire blight goes back to the late 1700s in North America, and the disease since then has spread to New Zealand, Europe, North Africa, the Middle East, and Asia. Due to its worldwide dissemination, advances have been made to identify and characterize E. amylovora strains from different regions and understand their evolutionary adaptation. Additionally, many efforts have been made in recent decades to stop the occurrence and impacts of fire blight, but in many countries, only preventive measures have been applied, as the application of antibiotics and copper-based compounds has become more restricted. Thus, new sustainable methods to control the pathogen are constantly required. This article presents a comprehensive review of the pathogen, from the phenotypic and molecular characterization methods applied to advances in comparative genomics and the development of new compounds for sustainable control of E. amylovora.
Modeling of Dry Reforming of Methane Using Artificial Neural Networks
Authors: Rahman Mohammod Hafizur , Biswas Mohammad
Published: November 2024

The process of dry reforming methane (DRM) is seen as a viable approach for producing hydrogen and lowering the atmospheric concentration of carbon dioxide. Recent times have witnessed notable advancements in the development of catalysts that enable this pathway. Numerous experiments have been conducted to investigate the use of nickel-based catalysts in the dry reforming of methane. All these reported experiments showed that variations in the catalyst property, namely pore size, pore volume, and surface area, affect the hydrogen production in DRM. None of the previous studies has modeled the surface nickel-incorporated catalyst activity based on its properties. In this research, DRM’s hydrogen yield is predicted using three different artificial neural network-learning algorithms as a function of the physical properties of Ni-based catalyst along with two reaction inputs. The geometric properties as an input set are a different approach to developing such empirical models. The best-fitting models are the artificial neural network model using the Levenberg–Marquardt algorithm and ten hidden neurons, which gave a coefficient of determination of 0.9931 and an MSE of 7.51, and the artificial neural network model using the scaled conjugate gradient algorithm and eight hidden layer neurons, which had a coefficient of determination of 0.9951 and an MSE of 4.29. This study offers useful knowledge on how to improve the DRM processes.
Quantification of Visual Attention by Using Eye-Tracking Technology for Soundscape Assessment Through Physiological Response
Authors: Jo Hyun In , Jeon Jin Yong
Published: November 2024

Because soundscapes affect human health and comfort, methodologies for evaluating them through physiological responses have attracted considerable attention. In this study, we proposed a novel method for evaluating visual attention by using eye-tracking technology to objectively assess soundscape perception. The study incorporated questionnaire surveys and physiological measurements focusing on visual attention responses. Results from the questionnaire indicated that perceptions of vehicles and the sky were 6% and 26% more sensitive, respectively, whereas perceptions of vegetation, based on physiological responses, were approximately 3% to 50% more sensitive. The soundscape quality prediction model indicates that the proposed methodology can complement conventional questionnaire-based models and provide a nuanced interpretation of eventfulness relationships. Additionally, the visual attention quantification technique enhanced the restoration responses of questionnaire-based methods by 1–2%. The results of this study are significant because the study introduces a novel methodology for quantifying visual attention, which can be used as a supplementary tool for physiological responses in soundscape research. The proposed method can uncover novel mechanisms of human perception of soundscapes that may not be captured by questionnaires, providing insights for future research in soundscape evaluation through physiological measurements.
Heat Index: An Alternative Indicator for Measuring the Impacts of Meteorological Factors on Diarrhoea in the Climate Change Era: A Time Series Study in Dhaka, Bangladesh
Authors: Haque Farhana , Lampe Fiona C. , Hajat Shakoor , Stavrianaki Katerina , Hasan S. M. Tafsir , Faruque A. S. G. , Ahmed Tahmeed , Jubayer Shamim , Kelman Ilan
Published: November 2024

Heat index (HI) is a biometeorological indicator that combines temperature and relative humidity. This study aimed to investigate the relationship between the Heat Index and daily counts of diarrhoea hospitalisation in Dhaka, Bangladesh. Data on daily diarrhoea hospitalisations and meteorological variables from 1981 to 2010 were collected. We categorised the Heat Index of >94.3 °F (>34.6 °C), >100.7 °F (>38.2 °C) and >105 °F (>40.6 °C) as high, very high and extremely high Heat Index, respectively. We applied a time series adjusted generalised linear model (GLM) with negative binomial distribution to investigate the effects of the Heat Index and extreme Heat Index on hospitalisations for diarrhoea. Effects were assessed for all ages, children under 5 years old and by gender. A unit higher HI and high, very high and extremely high HI were associated with 0.8%, 8%, 7% and 9% increase in diarrhoea hospitalisations in all ages, respectively. The effects varied slightly by gender and were most pronounced in children under 5 years old with a rise of 1°F in high, very high and extremely high HI associated with a 14.1% (95% CI: 11.3–17.0%), 18.3% (95% CI: 13.4–23.5%) and 18.1% (95% CI: 8.4–28.6%) increase of diarrhoea, respectively. This suggests that the Heat Index may serve as an alternative indicator for measuring the combined effects of temperature and humidity on diarrhoea.
BRAF-Mutated Melanoma Cell Lines Develop Distinct Molecular Signatures After Prolonged Exposure to AZ628 or Dabrafenib: Potential Benefits of the Antiretroviral Treatments Cabotegravir or Doravirine on BRAF-Inhibitor-Resistant Cells
Authors: Zanrè Valentina , Bellinato Francesco , Cardile Alessia , Passarini Carlotta , Di Bella Stefano , Menegazzi Marta
Published: November 2024

Melanoma is an aggressive cancer characterized by rapid growth, early metastasis, and poor prognosis, with resistance to current therapies being a significant issue. BRAF mutations drive uncontrolled cell division by activating the MAPK pathway. In this study, A375 and FO-1, BRAF-mutated melanoma cell lines, were treated for 4–5 months with RAF inhibitor dabrafenib or AZ628, leading to drug resistance over time. The resistant cells showed altered molecular signatures, with differences in cell cycle regulation and the propensity of cell death. Dabrafenib-resistant cells maintained high proliferative activity, while AZ628-resistant cells, especially A375 cells, exhibited slow-cycling, and a senescent-like phenotype with high susceptibility to ferroptosis, a form of cell death driven by iron. Antiretroviral drugs doravirine and cabotegravir, known for their effects on human endogenous retroviruses, were tested for their impact on these resistant melanoma cells. Both drugs reduced cell viability and colony formation in resistant cell lines. Doravirine was particularly effective in reactivating apoptosis and reducing cell growth in highly proliferative resistant cells by increasing tumor-suppressor proteins p16Ink4a and p27Kip1. These findings suggest that antiretroviral drugs can influence apoptosis and cell proliferation in RAF-inhibitor-resistant melanoma cells, offering potential therapeutic strategies for overcoming drug resistance.