bluuebunny/crossref_metadata_2025 huggingface dataset:
Plant-Based Dairy Alternatives Contribute to a Healthy and Sustainable Diet
Authors: Craig Winston J. , Messina Virginia , Rowland Ian , Frankowska Angelina , Bradbury Jane , Smetana Sergiy , Medici Elphee
Published: July 2023

Plant-based foods are increasing in popularity as more and more people are concerned about personal and planetary health. The consumption of plant-based dairy alternatives (PBDAs) has assumed a more significant dietary role in populations shifting to more sustainable eating habits. Plant-based drinks (PBDs) made from soya and other legumes have ample protein levels. PBDs that are appropriately fortified have adequate levels of important vitamins and minerals comparable to dairy milk. For the PBDs examined, the greenhouse gas emissions were diminished by 59–71% per 250 mL, and the land use and eutrophication impact was markedly less than the levels displayed by dairy milk. The water usage for the oat and soya drinks, but not rice drinks, was substantially lower compared to dairy milk. When one substitutes the 250 mL serving of dairy milk allowed within the EAT Lancet Planetary Health Diet for a fortified plant-based drink, we found that the nutritional status is not compromised but the environmental footprint is reduced. Combining a nutrient density score with an environmental index can easily lead to a misclassification of food when the full nutrition profile is not utilized or only a selection of environmental factors is used. Many PBDAs have been categorized as ultra-processed foods (UPFs). Such a classification, with the implied adverse nutritional and health associations, is inconsistent with current findings regarding the nutritional quality of such products and may discourage people from transitioning to a plant-based diet with its health and environmental advantages.
Dietary Patterns and Circadian Syndrome among Adults Attending NHANES 2005–2016
Authors: Akbar Zoha , Shi Zumin
Published: July 2023

The study aimed to assess the associations of dietary patterns and circadian syndrome (CircS). Data from National Health and Nutrition Examination Survey (NHANES) 2005–2016 were analyzed (n = 10,486). Factor analysis was used to construct dietary patterns based on two 24 h food recalls. CircS was defined based on components of the metabolic syndrome, with the addition of short sleep and depression symptoms. Multivariable logistic regression was used to analyze the associations. Two major dietary patterns were identified. The Western dietary pattern had high loadings of refined grains, solid fats, added sugars, and red and cured meats, while the prudent pattern was characterized by a high intake of vegetables, whole grains, oils, nuts, and seeds. The prevalence of CircS was 41.3%. Comparing extreme quartiles of intake, the odds ratios (OR) for having CircS were 1.96 (95%CI 1.53–2.53) and 0.71 (95%CI 0.58–0.86) for the Western pattern and prudent pattern, respectively. The association between the Western dietary pattern and CircS was stronger among men (OR = 2.05; 95%CI 1.48–2.85) and those with low income (OR = 1.94; 95%CI 1.27–2.96) and high education (OR = 3.38; 95%CI 1.90–6.04). The Western dietary pattern was associated with a higher likelihood of having CircS, while the prudent pattern was inversely associated with CircS.
Mechanistic Action of Cell Cycle Arrest and Intrinsic Apoptosis via Inhibiting Akt/mTOR and Activation of p38-MAPK Signaling Pathways in Hep3B Liver Cancer Cells by Prunetrin—A Flavonoid with Therapeutic Potential
Authors: Abusaliya Abuyaseer , Jeong Se Hyo , Bhosale Pritam Bhagwan , Kim Hun Hwan , Park Min Yeong , Kim Eunhye , Won Chung Kil , Park Kwang Il , Heo Jeong Doo , Kim Hyun Wook , Ahn Meejung , Seong Je Kyung , Kim Gon Sup
Published: July 2023

Hepatocellular carcinoma (HCC) has a poor prognosis and a low survival rate. Drugs without side effects are desperately needed since chemotherapy has a negative effect on the host cells. Previous research has firmly established that plant-based compounds have significant bioactivities without a negative impact on the host. Flavonoids, in particular, are a class of compounds with both anti-inflammatory and anti-cancer properties. Prunetrin (PUR) is a glycosyloxyisoflavone (Prunetin 4′-O-glucoside) derived from Prunus sp., and its other form, called prunetin, showed optimistic results in an anti-cancerous study. Hence, we aimed to discover the anti-cancer ability of prunetrin in liver cancer Hep3B cells. Our cytotoxicity results showed that PUR can decrease cell viability. The colony formation assay confirms this strongly and correlates with cell cytotoxicity results. Prunetrin, in a dose-dependent manner, arrested the cell cycle in the G2/M phase and decreased the expression of cyclin proteins such as Cyclin B1, CDK1/CDC2, and CDC25c. Prunetrin treatment also promoted the strong cleavage of two important apoptotic hallmark proteins called PARP and caspase-3. It also confirms that apoptosis occurs through the mitochondrial pathway through increased expression of cleaved caspase-9 and increased levels of the pro-apoptotic protein Bak. Bak was significantly increased with the declining expression of the anti-apoptotic protein Bcl-xL. Next, it inhibits the mTOR/AKT signaling pathways, proving that prunetrin includes apoptosis and decreases cell viability by suppressing these pathways. Further, it was also observed that the activation of p38-MAPK was dose-dependent. Taken together, they provide evidence that prunetrin has an anti-cancerous ability in Hep3B liver cancer cells by arresting the cell cycle via p38 and inhibiting mTOR/AKT.
Associations between Delayed Introduction of Complementary Foods and Childhood Health Consequences in Exclusively Breastfed Children
Authors: Ha Eun Kyo , Lee Seung Won , Kim Ju Hee , Lee Eun , Cha Hye Ryeong , Han Bo Eun , Shin Jeewon , Han Man Yong
Published: July 2023

The timing of complementary food (CF) introduction is closely related to childhood health, and it may vary depending on the region, culture, feeding type, or health condition. Despite numerous studies on the benefits of breastfeeding and the optimal timing of CF introduction, there have been limited investigations regarding delayed CF introduction in exclusively breastfed children. We compared an exposed group (CF introduction ≥7 months) with a reference group (CF introduction at 4 –< 7 months) regarding hospital admission, disease burden, and growth until age 10. Data from a nationwide population-based cohort study involving children born between 2008 and 2012 in the South Korea were analyzed. The final cohort comprised 206,248 children (165,925 in the exposed group and 40,323 in the reference group). Inverse probability of treatment weighting with propensity score matching was used to balance baseline health characteristics in the comparison groups. We estimated the incident risk ratios (IRR) for outcomes using modified Poisson regression and weighted odds ratios (weighted ORs) and their 95% confidence intervals (CIs) using multinomial logistic regression. The exposed group was associated with low height-for-age z-score (HAZ) (IRR (95% CI) for −1.64 < HAZ ≤ −1.03: 1.11 (1.08 to 1.14); HAZ ≤ −1.64: 1.21 (1.14 to 1.27)) and frequent (≥6 events) hospitalizations (weighted OR 1.18 (1.09 to 1.29). The rates of hospital admission, death, and specific medical conditions did not differ between groups. However, delaying the introduction of CF until seven months in exclusively breastfed infants was associated with frequent hospitalization events and lower heights.
Bioreactor Production Process of Spodoptera frugiperda multiple nucleopolyhedrovirus Biopesticide
Authors: Klafke Karina , Sanches Marcio Martinello , Sihler William , Souza Marlinda Lobo de , Tonso Aldo
Published: July 2023

Spodoptera frugiperda (fall armyworm) is one of the most important maize pests in the world and the baculovirus Spodoptera frugiperda multiple nucleopolyhedrovirus (SfMNPV), a natural pathogen of this pest, has been used as a biopesticide for its control. At present, in vivo strategies at the commercial scale are employed by multiplying the virus in the host insect in biofactory facilities; however, in vitro large-scale production is an interesting alternative to overcome the limitations of baculoviruses massal production. This study aimed to develop the process of the SfMNPV in vitro production by evaluating the effects of different multiplicities of infection (MOI) and nutritional supplements, morphological and molecular analysis of the infection on the growth of Sf9 cells and virus production. The Bioreactor Stirred Tank Reactor (STR) approach with glutamine-supplemented Sf-900 III serum free culture medium, combined with the MOI of 1.0, showed the best viral production performance, with a specific productivity above 300 occlusion bodies (OBs)/cell and volumetric productivity of 9.0 × 1011 OBs/L.
Calcium Electrochemotherapy for Tumor Eradication and the Potential of High-Frequency Nanosecond Protocols
Authors: Radzevičiūtė-Valčiukė Eivina , Želvys Augustinas , Mickevičiūtė Eglė , Gečaitė Jovita , Zinkevičienė Auksė , Malyško-Ptašinskė Veronika , Kašėta Vytautas , Novickij Jurij , Ivaškienė Tatjana , Novickij Vitalij
Published: July 2023

Calcium electroporation (CaEP) is an innovative approach to treating cancer, involving the internalization of supraphysiological amounts of calcium through electroporation, which leads to cell death. CaEP enables the replacement of chemotherapeutics (e.g., bleomycin). Here, we present a standard microsecond (μsCaEP) and novel high-frequency nanosecond protocols for calcium electroporation (nsCaEP) for the elimination of carcinoma tumors in C57BL/6J mice. We show the efficacy of CaEP in eliminating tumors and increasing their survival rates in vivo. The antitumor immune response after the treatment was observed by investigating immune cell populations in tumors, spleens, lymph nodes, and blood, as well as assessing antitumor antibodies. CaEP treatment resulted in an increased percentage of CD4+ and CD8+ central memory T cells and decreased splenic myeloid-derived suppressor cells (MDSC). Moreover, increased levels of antitumor IgG antibodies after CaEP treatment were detected. The experimental results demonstrated that the administration of CaEP led to tumor growth delay, increased survival rates, and stimulated immune response, indicating a potential synergistic relationship between CaEP and immunotherapy.
Ferrocene-Based Drugs, Delivery Nanomaterials and Fenton Mechanism: State of the Art, Recent Developments and Prospects
Authors: Ornelas Catia , Astruc Didier
Published: July 2023

Ferrocene has been the most used organometallic moiety introduced in organic and bioinorganic drugs to cure cancers and various other diseases. Following several pioneering studies, two real breakthroughs occurred in 1996 and 1997. In 1996, Jaouen et al. reported ferrocifens, ferrocene analogs of tamoxifen, the chemotherapeutic for hormone-dependent breast cancer. Several ferrocifens are now in preclinical evaluation. Independently, in 1997, ferroquine, an analog of the antimalarial drug chloroquine upon the introduction of a ferrocenyl substituent in the carbon chain, was reported by the Biot-Brocard group and found to be active against both chloroquine-sensitive and chloroquine-resistant strains of Plasmodium falciparum. Ferroquine, in combination with artefenomel, completed phase IIb clinical evaluation in 2019. More than 1000 studies have been published on ferrocenyl-containing pharmacophores against infectious diseases, including parasitic, bacterial, fungal, and viral infections, but the relationship between structure and biological activity has been scarcely demonstrated, unlike for ferrocifens and ferroquines. In a majority of ferrocene-containing drugs, however, the production of reactive oxygen species (ROS), in particular the OH. radical, produced by Fenton catalysis, plays a key role and is scrutinized in this mini-review, together with the supramolecular approach utilizing drug delivery nanosystems, such as micelles, metal–organic frameworks (MOFs), polymers, and dendrimers.
Cytotoxic Screening and Enhanced Anticancer Activity of Lippia alba and Clinopodium nepeta Essential Oils-Loaded Biocompatible Lipid Nanoparticles against Lung and Colon Cancer Cells
Authors: Rodenak-Kladniew Boris , Castro María Agustina , Gambaro Rocío Celeste , Girotti Juan , Cisneros José Sebastián , Viña Sonia , Padula Gisel , Crespo Rosana , Castro Guillermo Raúl , Gehring Stephan , Chain Cecilia Yamil , Islan Germán Abel
Published: July 2023

Plant and herbal essential oils (EOs) offer a wide range of pharmacological actions that include anticancer effects. Here, we evaluated the cytotoxic activity of EO from Lippia alba (chemotype linalool), L. alba (chemotype dihydrocarvone, LaDEO), Clinopodium nepeta (L.) Kuntze (CnEO), Eucalyptus globulus, Origanum × paniculatum, Mentha × piperita, Mentha arvensis L., and Rosmarinus officinalis L. against human lung (A549) and colon (HCT-116) cancer cells. The cells were treated with increasing EO concentrations (0–500 µL/L) for 24 h, and cytotoxic activity was assessed. LaDEO and CnEO were the most potent EOs evaluated (IC50 range, 145–275 µL/L). The gas chromatography–mass spectrometry method was used to determine their composition. Considering EO limitations as therapeutic agents (poor water solubility, volatilization, and oxidation), we evaluated whether LaDEO and CnEO encapsulation into solid lipid nanoparticles (SLN/EO) enhanced their anticancer activity. Highly stable spherical SLN/LaDEO and SLN/CnEO SLN/EO were obtained, with a mean diameter of 140–150 nm, narrow size dispersion, and Z potential around −5mV. EO encapsulation strongly increased their anticancer activity, particularly in A549 cells exposed to SLN/CnEO (IC50 = 66 µL/L CnEO). The physicochemical characterization, biosafety, and anticancer mechanisms of SLN/CnEO were also evaluated in A549 cells. SLN/CnEO containing 97 ± 1% CnEO was highly stable for up to 6 months. An increased in vitro CnEO release from SLN at an acidic pH (endolysosomal compartment) was observed. SLN/CnEO proved to be safe against blood components and non-toxic for normal WI-38 cells at therapeutic concentrations. SLN/CnEO substantially enhanced A549 cell death and cell migration inhibition compared with free CnEO.
Ballistic Performance, Thermal and Chemical Characterization of Ubim Fiber (Geonoma baculifera) Reinforced Epoxy Matrix Composites
Authors: Marchi Belayne Zanini , Silveira Pedro Henrique Poubel Mendonça da , Bezerra Wendell Bruno Almeida , Nascimento Lucio Fabio Cassiano , Lopes Felipe Perissé Duarte , Candido Verônica Scarpini , Silva Alisson Clay Rios da , Monteiro Sergio Neves
Published: July 2023

The search for unexplored natural materials as an alternative to synthetic components has driven the development of novel polymeric composites reinforced with environmentally-friendly materials. Natural lignocellulosic fibers (NLFs) have been highlighted as potential reinforcement in composite materials for engineering applications. In this work, a less known Amazonian fiber, the ubim fiber (Geonoma baculifera), is investigated as a possible reinforcement in epoxy composites and was, for the first time, thermally characterized by thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). Additionally, its chemical structure was elucidated by Fourier transform infrared spectroscopy (FTIR). Ballistic tests were also performed against the threat of a 7.62 mm high-speed lead projectile. The results were statistically analyzed by the Weibull statistical analysis method. FTIR analysis showed the functional groups normally found for NLFs highly rich in cellulose, hemicellulose, and lignin. The TGA/DTG results showed the onset of thermal degradation for the composites (325~335 °C), which represents better thermal stability than isolated ubim fiber (259 °C), but slightly lower than that of pure epoxy (352 °C). The DSC results of the composites indicate endothermic peaks between 54 and 56 °C, and for the ubim fibers, at 71 °C. Ballistic tests revealed higher energy absorption in composites with lower fiber content due to the more intense action of the brittle fracture mechanisms of the epoxy resin, which tended to dissipate more energy. These failure mechanisms revealed the presence of river marks, cracks, and broken fibers with a detachment interface. These results may contribute to the production of ubim fiber-reinforced composites in engineering applications, such as ballistic armors.
Mechanical Performances Analysis and Prediction of Short Plant Fiber-Reinforced PLA Composites
Authors: Mu Wenlong , Chen Xianglin , Li Shijie , Sun Yufeng , Wang Qingpeng , Na Jingxin
Published: July 2023

Plant fiber-reinforced polylactic acid (PLA) exhibits excellent mechanical properties and environmental friendliness and, therefore, has a wide range of applications. This study investigated the mechanical properties of three short plant fiber-reinforced PLA composites (flax, jute, and ramie) using mechanical testing and material characterization techniques (SEM, FTIR, and DSC). Additionally, we propose a methodology for predicting the mechanical properties of high-content short plant fiber-reinforced composite materials. Results indicate that flax fibers provide the optimal reinforcement effect due to differences in fiber composition and microstructure. Surface pretreatment of the fibers using alkali and silane coupling agents increases the fiber–matrix interface contact area, improves interface performance, and effectively enhances the mechanical properties of the composite. The mechanical properties of the composites increase with increasing fiber content, reaching the highest value at 40%, which is 38.79% higher than pure PLA. However, further increases in content lead to fiber agglomeration and decreased composite properties. When the content is relatively low (10%), the mechanical properties are degraded because of internal defects in the material, which is 40.42% lower than pure PLA. Through Micro-CT technology, the fiber was reconstructed, and it was found that the fiber was distributed mainly along the direction of injection molding, and the twin-screw process changes the shape and length of the fiber. By introducing the fiber agglomeration factor function and correcting the Halpin-Tsai criterion, the mechanical properties of composite materials with different contents were successfully predicted. Considering the complex stress state of composite materials in actual service processes, a numerical simulation method was established based on transversely isotropic material using the finite element method combined with theoretical analysis. The mechanical properties of high-content short plant fiber-reinforced composite materials were successfully predicted, and the simulation results showed strong agreement with the experimental results.
Multicomponent Acrylic Formulation Design for Corrosion Casting with Controlled Mechanical Properties
Authors: Reyes Pablo , Edeleva Mariya , D’hooge Dagmar R. , Cardon Ludwig , Cornillie Pieter
Published: July 2023

Corrosion casting based on the curing of acrylic resins enables one to create casts as replicas of body systems, enhancing our knowledge of veterinary medicine. The identification of the optimal chemical formulations as well as the processing conditions, the delivery of good control during the liquid state and the excellent macroscopic properties during solidification and after use are remaining challenges. In the present work, based on the identification of more qualitative trends, it is demonstrated that multicomponent comonomer mixtures are interesting materials that can be used to expand the range of mechanical properties and can specifically result in a better balance between stiffness and flexibility while guaranteeing dimensional stability. Emphasis is put on a large pool of formulations in the testing phase to then perform a detailed mechanical flexural analysis for the most promising cases during a more rigorous testing phase, accounting for a new pragmatic protocol for the pot life. This protocol consists of a vial-based turning test and a measurement of the viscosity variation up to 1000 mPa∙s and highlights the complex interplay between the overall initial concentrations and the impact of the absence of mixing once the system is at rest. It is demonstrated that the use of only low-molar-mass crosslinkers should be avoided, and overall, an intermediate amount of crosslinkers is recommendable.
Size-Dependent Diffusion and Dispersion of Particles in Mucin
Authors: Kumar Parveen , Tamayo Joshua , Shiu Ruei-Feng , Chin Wei-Chun , Gopinath Arvind
Published: July 2023

Mucus, composed significantly of glycosylated mucins, is a soft and rheologically complex material that lines respiratory, reproductive, and gastrointestinal tracts in mammals. Mucus may present as a gel, as a highly viscous fluid, or as a viscoelastic fluid. Mucus acts as a barrier to the transport of harmful microbes and inhaled atmospheric pollutants to underlying cellular tissue. Studies on mucin gels have provided critical insights into the chemistry of the gels, their swelling kinetics, and the diffusion and permeability of molecular constituents such as water. The transport and dispersion of micron and sub-micron particles in mucin gels and solutions, however, differs from the motion of small molecules since the much larger tracers may interact with microstructure of the mucin network. Here, using brightfield and fluorescence microscopy, high-speed particle tracking, and passive microrheology, we study the thermally driven stochastic movement of 0.5–5.0 μm tracer particles in 10% mucin solutions at neutral pH, and in 10% mucin mixed with industrially relevant dust; specifically, unmodified limestone rock dust, modified limestone, and crystalline silica. Particle trajectories are used to calculate mean square displacements and the displacement probability distributions; these are then used to assess tracer diffusion and transport. Complex moduli are concomitantly extracted using established microrheology techniques. We find that under the conditions analyzed, the reconstituted mucin behaves as a weak viscoelastic fluid rather than as a viscoelastic gel. For small- to moderately sized tracers with a diameter of lessthan 2 μm, we find that effective diffusion coefficients follow the classical Stokes–Einstein relationship. Tracer diffusivity in dust-laden mucin is surprisingly larger than in bare mucin. Probability distributions of mean squared displacements suggest that heterogeneity, transient trapping, and electrostatic interactions impact dispersion and overall transport, especially for larger tracers. Our results motivate further exploration of physiochemical and rheological mechanisms mediating particle transport in mucin solutions and gels.
Novel Fucoidan Pharmaceutical Formulations and Their Potential Application in Oncology—A Review
Authors: Zahariev Nikolay , Katsarov Plamen , Lukova Paolina , Pilicheva Bissera
Published: July 2023

Fucoidan belongs to the family of marine sulfated, L-fucose-rich polysaccharides found in the cell wall matrix of various brown algae species. In the last few years, sulfated polysaccharides have attracted the attention of researchers due to their broad biological activities such as anticoagulant, antithrombotic, antidiabetic, immunomodulatory, anticancer and antiproliferative effects. Recently the application of fucoidan in the field of pharmaceutical technology has been widely investigated. Due to its low toxicity, biocompatibility and biodegradability, fucoidan plays an important role as a drug carrier for the formulation of various drug delivery systems, especially as a biopolymer with anticancer activity, used for targeted delivery of chemotherapeutics in oncology. Furthermore, the presence of sulfate residues with negative charge in its structure enables fucoidan to form ionic complexes with oppositely charged molecules, providing relatively easy structure-forming properties in combination with other polymers. The aim of the present study was to overview essential fucoidan characteristics, related to its application in the development of pharmaceutical formulations as a single drug carrier or in combinations with other polymers. Special focus was placed on micro- and nanosized drug delivery systems with polysaccharides and their application in the field of oncology.
Investigation of the Mechanical Behavior of Acacia—Raffia Natural Fiber Composite
Authors: P Karthick , Vijaya Ramnath Bindu Madhavan , Palanikumar K.
Published: July 2023

Nowadays, industries place a strong emphasis on low-cost, biodegradable materials with long lifespans. As a result, businesses are concentrating on creating composite materials utilizing the world’s plentiful supply of natural fibers. In this study, acacia and raffia fibers are combined with epoxy resin and a hand layup method to create a biodegradable composite laminate. This article investigates the effect of fiber orientation on the mechanical and morphological evaluation of composite materials that have been manufactured. Three different kinds of composites were fabricated in this work: Composite 1, which contained acacia fiber; Composite 2, which was built of acacia and raffia fiber; and Composite 3, which was made of raffia fiber. While Composite 2 is a hybrid composite in this instance, Composites 1 and 3 are monofiber composites. In accordance with the ASTM standards, testing was performed to investigate the different mechanical behaviors, including tensile, flexural, double shear, delamination, hardness, and impact. The results demonstrate that Composite 1 has strong tensile strength, flexural strength, double shear, and hardness tests with a 45° fiber orientation. The 90° fiber orientation of Composite 1 performs well in the inter delamination test. The result demonstrates that composite 1 of type 0 absorbs greater energy. Additionally, Scanning electron microscopy was used to conduct morphological examinations in order to investigate the internal structural failure of the composites. It was found that the composite laminate has fiber cracks, pullouts, and voids, which were reduced with the right curing times and stress.
Hindu Civilization and Indian Nationalism: Conceptual Conflicts and Convergences in the Works of Romesh Chunder Dutt, c. 1870–1910
Authors: Mitra Arpita
Published: July 2023

This paper is about a particular construction of nationalism at the hands of Romesh Chunder Dutt (1848–1909), the well-known exponent of ‘economic nationalism’, in colonial Bengal from 1870 onwards till his death in 1909. In this construction of nationalism, which today scholars would best describe as ‘cultural nationalism’, the categories ‘Hindu’ and ‘national’ converged and became conflated. Through a discussion of Dutt’s ‘literary patriotism’, the paper seeks to answer why it was so in the case of someone like R C Dutt, and what implications we can draw from this regarding our understanding of colonial Indian nationalism and its origins. With reference to Dutt, Sudhir Chandra pointed out that the neat distinction that we draw between ‘economic nationalism’ and ‘cultural nationalism’ is fallacious. The paper reiterates and reinforces this argument by showing how cultural and political nationalisms were enmeshed together in the case of R C Dutt. Furthermore, the glorious past that Dutt reconstructed through his literary patriotism could not but be a Hindu past; he was not a vilifier of Muslims, but somehow he shelved the question of the place of Muslims in his construction of Indian nationhood.
Rethinking Eucharistic Communion: A Theology of Harmony—A Study of the Lima Document
Authors: Meng Xiangjiao
Published: July 2023

The mutual reception of the Eucharist is a key issue in contemporary Christian unity. As a landmark document in Christian unity, the Lima document provides a profound exposition of the Eucharist. According to this article, eucharistic communion in the Lima document is expressed in three themes: “Communion with Christ”, “Communion of the Faithful”, and “Meal of the Kingdom”. Within these three themes, there are three groups of relationships: the relationship of mutual participation between the faithful and Christ, and the relationship of “demonstrate” and “effect” between the Eucharist and the oneness of the Church. Moreover, in the connotation of the banquet, there is the relationship of “foretaste” between the Eucharist and the Kingdom of God. Further, in my opinion, the concept of “eucharistic communion” is developed into a “theology of harmony”, namely, “the harmony between heaven and humans”, “the harmony between people and people”, and “the harmony between heaven and earth” in the Lima document.
Airspace Contamination by Volcanic Ash from Sequences of Etna Paroxysms: Coupling the WRF-Chem Dispersion Model with Near-Source L-Band Radar Observations
Authors: Rizza Umberto , Donnadieu Franck , Morichetti Mauro , Avolio Elenio , Castorina Giuseppe , Semprebello Agostino , Magazu Salvatore , Passerini Giorgio , Mancinelli Enrico , Biensan Clothilde
Published: July 2023

Volcanic emissions (ash, gas, aerosols) dispersed in the atmosphere during explosive eruptions generate hazards affecting aviation, human health, air quality, and the environment. We document for the first time the contamination of airspace by very fine volcanic ash due to sequences of transient ash plumes from Mount Etna. The atmospheric dispersal of sub-10 μm (PM10) ash is modelled using the WRF-Chem model, coupled online with meteorology and aerosols and offline with mass eruption rates (MERs) derived from near-vent Doppler radar measurements and inferred plume altitudes. We analyze two sequences of paroxysms with widely varied volcanological conditions and contrasted meteorological synoptic patterns in October–December 2013 and on 3–5 December 2015. We analyze the PM10 ash dispersal simulation maps in terms of time-averaged columnar ash density, concentration at specified flight levels averaged over the entire sequence interval, and daily average concentration during selected paroxysm days at these flight levels. The very fine ash from such eruption sequences is shown to easily contaminate the airspace around the volcano within a radius of about 1000 km in a matter of a few days. Synoptic patterns with relatively weak tropospheric currents lead to the accumulation of PM10 ash at a regional scale all around Etna. In this context, closely interspersed paroxysms tend to accumulate very fine ash more diffusively at a lower troposphere and in stretched ash clouds higher up in the troposphere. Low-pressure, high-winds weather systems tend to stretch ash clouds into ~100 km wide clouds, forming large-scale vortices 800–1600 km in diameter. Daily average PM10 ash concentrations commonly exceed the aviation hazard threshold, up to 1000 km downwind from the volcano and up to the upper troposphere for intense paroxysms. Vertical distributions show ash cloud thicknesses in the range 0.7–3 km, and PM10 sometimes stagnates at ground level, which represent a potential health hazard.
Coupled MOP and PLUS-SA Model Research on Land Use Scenario Simulations in Zhengzhou Metropolitan Area, Central China
Authors: Guo Pengfei , Wang Haiying , Qin Fen , Miao Changhong , Zhang Fangfang
Published: July 2023

Land use simulations are critical in predicting the impact of land use change (LUC) on the Earth. Various assumptions and policies influence land use structure and are a key factor in decisions made by policymakers. Meanwhile, the spatial autocorrelation effect between land use types has rarely been considered in existing land use spatial simulation models, and the simulation accuracy needs to be further improved. Thus, in this study, the driving mechanisms of LUC are analyzed. The quantity demand and spatial distribution of land use are predicted under natural development (ND), economic development (ED), ecological protection (EP), and sustainability development (SD) scenarios in Zhengzhou based on the coupled Multi-Objective Programming (MOP) model and the Patch-generating Land Use Simulation model (PLUS) considering Spatial Autocorrelation (PLUS-SA). We conclude the following. (1) The land use type in Zhengzhou was mainly cultivated land, and 83.85% of the land for urban expansion was cultivated land from 2000 to 2020. The reduction in forest from 2010 to 2020 was less than that from 2000 to 2010 due to the implementation of the policy in which farmland is transformed back into forests. (2) The accuracy of PLUS-SA was better than that of the traditional PLUS and Future Land Use Simulation (FLUS) models, and its Kappa coefficient, overall accuracy, and FOM were 0.91, 0.95, and 0.29, respectively. (3) Natural factors (temperature, precipitation, and DEM) contributed significantly to the expansion of cultivated land, and the increase in forest, grass, and construction land was greatly affected by socioeconomic factors (population, GDP, and proximity to town). (4) The land use structure will be more in line with the current requirements for sustainable urban development in the SD scenario, and the economic and ecological benefits will increase by 0.75 × 104 billion CNY and 1.71 billion CNY, respectively, in 2035 compared with those in 2020. The PLUS-SA model we proposed had higher simulation accuracy in Zhengzhou Compared with the traditional PLUS and FLUS models, and our research framework can provide a basis for decision-makers to formulate sustainable land use development policies to achieve high-quality and sustainable urban development.
Lithological Classification by Hyperspectral Images Based on a Two-Layer XGBoost Model, Combined with a Greedy Algorithm
Authors: Lin Nan , Fu Jiawei , Jiang Ranzhe , Li Genjun , Yang Qian
Published: July 2023

Lithology classification is important in mineral resource exploration, engineering geological exploration, and disaster monitoring. Traditional laboratory methods for the qualitative analysis of rocks are limited by sampling conditions and analytical techniques, resulting in high costs, low efficiency, and the inability to quickly obtain large-scale geological information. Hyperspectral remote sensing technology can classify and identify lithology using the spectral characteristics of rock, and is characterized by fast detection, large coverage area, and environmental friendliness, which provide the application potential for lithological mapping at a large regional scale. In this study, ZY1-02D hyperspectral images were used as data sources to construct a new two-layer extreme gradient boosting (XGBoost) lithology classification model based on the XGBoost decision tree and an improved greedy search algorithm. A total of 153 spectral bands of the preprocessed hyperspectral images were input into the first layer of the XGBoost model. Based on the tree traversal structural characteristics of the leaf nodes in the XGBoost model, three built-in XGBoost importance indexes were split and combined. The improved greedy search algorithm was used to extract the spectral band variables, which were imported into the second layer of the XGBoost model, and the bat algorithm was used to optimize the modeling parameters of XGBoost. The extraction model of rock classification information was constructed, and the classification map of regional surface rock types was drawn. Field verification was performed for the two-layer XGBoost rock classification model, and its accuracy and reliability were evaluated based on four indexes, namely, accuracy, precision, recall, and F1 score. The results showed that the two-layer XGBoost model had a good lithological classification effect, robustness, and adaptability to small sample datasets. Compared with the traditional machine learning model, the two-layer XGBoost model shows superior performance. The accuracy, precision, recall, and F1 score of the verification set were 0.8343, 0.8406, 0.8350, and 0.8157, respectively. The variable extraction ability of the constructed two-layer XGBoost model was significantly improved. Compared with traditional feature selection methods, the GREED-GFC method, when applied to the two-layer XGBoost model, contributes to more stable rock classification performance and higher lithology prediction accuracy, and the smallest number of extracted features. The lithological distribution information identified by the model was in good agreement with the lithology information verified in the field.
YOLO-Lite: An Efficient Lightweight Network for SAR Ship Detection
Authors: Ren Xiaozhen , Bai Yanwen , Liu Gang , Zhang Ping
Published: July 2023

Automatic ship detection in SAR images plays an essential role in both military and civilian fields. However, most of the existing deep learning detection methods introduce complex models and huge calculations while improving the detection accuracy, which is not conducive to the application of real-time ship detection. To solve this problem, an efficient lightweight network YOLO-Lite is proposed for SAR ship detection in this paper. First, a lightweight feature enhancement backbone (LFEBNet) is designed to reduce the amount of calculation. Additionally, a channel and position enhancement attention (CPEA) module is constructed and embedded into the backbone network to more accurately locate the target location by capturing the positional information. Second, an enhanced spatial pyramid pooling (EnSPP) module is customized to enhance the expression ability of features and address the position information loss of small SAR ships in high-level features. Third, we construct an effective multi-scale feature fusion network (MFFNet) with two feature fusion channels to obtain feature maps with more position and semantic information. Furthermore, a novel confidence loss function is proposed to effectively improve the SAR ship target detection accuracy. Extensive experiments on SSDD and SAR ship datasets verify the effectiveness of our YOLO-Lite, which can not only accurately detect SAR ships in different backgrounds but can also realize a lightweight architecture with low computation cost.
A Clustering Approach for the Analysis of InSAR Time Series: Application to the Bandung Basin (Indonesia)
Authors: Rygus Michelle , Novellino Alessandro , Hussain Ekbal , Syafiudin Fifik , Andreas Heri , Meisina Claudia
Published: July 2023

Interferometric Synthetic Aperture (InSAR) time series measurements are widely used to monitor a variety of processes including subsidence, landslides, and volcanic activity. However, interpreting large InSAR datasets can be difficult due to the volume of data generated, requiring sophisticated signal-processing techniques to extract meaningful information. We propose a novel framework for interpreting the large number of ground displacement measurements derived from InSAR time series techniques using a three-step process: (1) dimensionality reduction of the displacement time series from an InSAR data stack; (2) clustering of the reduced dataset; and (3) detecting and quantifying accelerations and decelerations of deforming areas using a change detection method. The displacement rates, spatial variation, and the spatio-temporal nature of displacement accelerations and decelerations are used to investigate the physical behaviour of the deforming ground by linking the timing and location of changes in displacement rates to potential causal and triggering factors. We tested the method over the Bandung Basin in Indonesia using Sentinel-1 data processed with the small baseline subset InSAR time series technique. The results showed widespread subsidence in the central basin with rates up to 18.7 cm/yr. We identified 12 main clusters of subsidence, of which three covering a total area of 22 km2 show accelerating subsidence, four clusters over 52 km2 show a linear trend, and five show decelerating subsidence over an area of 22 km2. This approach provides an objective way to monitor and interpret ground movements, and is a valuable tool for understanding the physical behaviour of large deforming areas.
YOLO-ViT-Based Method for Unmanned Aerial Vehicle Infrared Vehicle Target Detection
Authors: Zhao Xiaofeng , Xia Yuting , Zhang Wenwen , Zheng Chao , Zhang Zhili
Published: July 2023

The detection of infrared vehicle targets by UAVs poses significant challenges in the presence of complex ground backgrounds, high target density, and a large proportion of small targets, which result in high false alarm rates. To alleviate these deficiencies, a novel YOLOv7-based, multi-scale target detection method for infrared vehicle targets is proposed, which is termed YOLO-ViT. Firstly, within the YOLOV7-based framework, the lightweight MobileViT network is incorporated as the feature extraction backbone network to fully extract the local and global features of the object and reduce the complexity of the model. Secondly, an innovative C3-PANet neural network structure is delicately designed, which adopts the CARAFE upsampling method to utilize the semantic information in the feature map and improve the model’s recognition accuracy of the target region. In conjunction with the C3 structure, the receptive field will be increased to enhance the network’s accuracy in recognizing small targets and model generalization ability. Finally, the K-means++ clustering method is utilized to optimize the anchor box size, leading to the design of anchor boxes better suited for detecting small infrared targets from UAVs, thereby improving detection efficiency. The present article showcases experimental findings attained through the use of the HIT-UAV public dataset. The results demonstrate that the enhanced YOLO-ViT approach, in comparison to the original method, achieves a reduction in the number of parameters by 49.9% and floating-point operations by 67.9%. Furthermore, the mean average precision (mAP) exhibits an improvement of 0.9% over the existing algorithm, reaching a value of 94.5%, which validates the effectiveness of the method for UAV infrared vehicle target detection.
The Sensitivity of Large Eddy Simulations to Grid Resolution in Tropical Cyclone High Wind Area Applications
Authors: Jing Yi , Wang Hong , Zhu Ping , Li Yubin , Ye Lei , Jiang Lifeng , Wang Anting
Published: July 2023

The question of at what resolution the large eddy simulations (LESs) of a tropical cyclone (TC) high wind area may converge largely remains unanswered. To address this issue, LESs with five resolutions of 300 m, 100 m, 60 m, 33 m, and 20 m are performed in this study to simulate a high wind area near the radius of maximum wind of Typhoon Chanthu (2021) using the Weather Research and Forecasting (WRF) model. The results show that, for a limited area LES, model grid resolution may alter the local turbulence structure to generate significantly different extreme values of temperature, moisture, and winds, but it only has a marginal impact on the median values of these variables throughout the vertical column. All simulations are able to capture the turbulent roll vortices in the TC boundary layer, but the structure and intensity of the rolls vary substantially in different resolution simulations. Local hectometer-scale eddies with vertical velocities exceeding 10 m s−1 are only observed in the 20 m resolution simulation but not in the coarser resolution simulations. The ratio of the resolved turbulent momentum fluxes and turbulent kinetic energies (TKEs) to the total momentum fluxes and TKEs appears to show some convergence of LESs when the grid resolution reaches 100 m or finer, suggesting that it is an acceptable grid resolution for LES applications in TC simulations.
Comparison of Data Fusion Methods in Fusing Satellite Products and Model Simulations for Estimating Soil Moisture on Semi-Arid Grasslands
Authors: Zhu Yi , Zhang Lanhui , Li Feng , Xu Jiaxin , He Chansheng
Published: July 2023

In arid and semi-arid areas, soil moisture (SM) plays a crucial role in land-atmosphere interactions, hydrological processes, and ecosystem sustainability. SM data at large scales are critical for related climatic, hydrological, and ecohydrological research. Data fusion based on satellite products and model simulations is an important way to obtain SM data at large scales; however, little has been reported on the comparison of the data fusion methods in different categories. Here, we compared the performance of two widely used data fusion methods, the Ensemble Kalman Filter (EnKF) and the Back-Propagation Artificial Neural Network (BPANN), in the degraded grassland site (DGS) and the alpine grassland site (AGS). The SM data from the Community Land Model 5.0 (CLM5.0) and the Soil Moisture Active and Passive (SMAP) were fused and validated against the observations of the Cosmic-Ray Neutron Sensor (CRNS) to avoid the impacts of scale-mismatch. Results show that compared with the original data sets at both sites, the RMSE of the fused data by BPANN (FD-BPANN) and EnKF (FD-EnKF) had improved by more than 50% and 31%, respectively. Overall, the FD-BPANN performs better than the FD-EnKF because the BPANN method assigned higher weights to input data with better performance and the EnKF method is affected by the strong variabilities of both the fused CLM5.0 and SMAP data and the CRNS data. However, in terms of the percentile range, the FD-BPANN showed the worst performance, with overestimations in the low SM range of 25th percentile (<Q25), because the BPANN method tends to be trapped in a local minimum. The BPANN method performed better in humid areas, then followed by semi-humid areas, and finally arid and semi-arid areas. Moreover, compared with the previous studies in arid and semi-arid areas, the BPANN method in this study performed better.
Crop-Planting Area Prediction from Multi-Source Gaofen Satellite Images Using a Novel Deep Learning Model: A Case Study of Yangling District
Authors: Kuang Xiaofei , Guo Jiao , Bai Jingyuan , Geng Hongsuo , Wang Hui
Published: July 2023

Neural network models play an important role in crop extraction based on remote sensing data. However, when dealing with high-dimensional remote sensing data, these models are susceptible to performance degradation. In order to address the challenges associated with multi-source Gaofen satellite data, a novel method is proposed for dimension reduction and crop classification. This method combines the benefits of the stacked autoencoder network for data dimensionality reduction, and the convolutional neural network for classification. By leveraging the advantages of multi-dimensional remote sensing information, and mitigating the impact of dimensionality on the classification accuracy, this method aims to improve the effectiveness of crop classification. The proposed method was applied to the extraction of crop-planting areas in the Yangling Agricultural Demonstration Zone, using multi-temporal spectral data collected from the Gaofen satellites. The results demonstrate that the fusion network, which extracts low-dimensional characteristics, offers advantages in classification accuracy. At the same time, the proposed model is compared with methods such as the decision tree (DT), random forest (RF), support vector machine (SVM), hyperspectral image classification based on a convolutional neural network (HICCNN), and a characteristic selection classification method based on a convolutional neural network (CSCNN). The overall accuracy of the proposed method can reach 98.57%, which is 7.95%, 4.69%, 5.68%, 1.21%, and 1.10% higher than the above methods, respectively. The effectiveness of the proposed model was verified through experiments. Additionally, the model demonstrates a strong robustness when classifying based on new data. When extracting the crop area of the entire Yangling District, the errors for wheat and corn are only 9.6% and 6.3%, respectively, and the extraction results accurately reflect the actual planting situation of crops.