bluuebunny/crossref_metadata_2025 huggingface dataset:
Mesoporous Silica Promotes Osteogenesis of Human Adipose-Derived Stem Cells Identified by a High-Throughput Microfluidic Chip Assay
Authors: Chen Xin , Wang Chao , Hao Min , Zhao Hang , Xia He , Yu Liyang , Li Dong , Qiu Jichuan , Li Haijun , Han Lin , Sang Yuanhua
Published: December 2022

Silicon-derived biomaterials are conducive to regulating the fate of osteo-related stem cells, while their effects on the osteogenic differentiation of human adipose-derived stem cells (hADSCs) remain inconclusive. Mesoporous silica (mSiO2) is synthesized in a facile route that exhibited the capability of promoting osteogenic differentiation of hADSCs. The metabolism of SiO2 in cells is proposed according to the colocalization fluorescence analysis between lysosomes and nanoparticles. The released silicon elements promote osteogenic differentiation. The detection of secretory proteins through numerous parallel experiments performed via a microfluidic chip confirms the positive effect of SiO2 on the osteogenic differentiation of hADSCs. Moreover, constructed with superparamagnetic iron oxide (Fe3O4), the magnetic nanoparticles (MNPs) of Fe3O4@mSiO2 endow the cells with magnetic resonance imaging (MRI) properties. The MNP-regulated osteogenic differentiation of autologous adipose-derived stem cells provides considerable clinical application prospects for stem cell therapy of bone tissue repair with an effective reduction in immune rejection.
CD44-Receptor Targeted Gold-Doxorubicin Nanocomposite for Pulsatile Chemo-Photothermal Therapy of Triple-Negative Breast Cancer Cells
Authors: Kalyane Dnyaneshwar , Polaka Suryanarayana , Vasdev Nupur , Tekade Rakesh Kumar
Published: December 2022

This study reports the CD44 receptor-targeted gold-doxorubicin nanocomposite (TGNC-DOX) for pulsatile chemo-photothermal therapy of triple-negative breast cancer (TNBC). The developed TGNC-DOX was nanometric, having a particle size of 71.34 ± 3.66 nm. The doxorubicin was loaded by electrostatic interaction with high entrapment and loading efficiency (>75%). TGNC-DOX showed potent photothermal response and reversible photothermal stability following irradiation with 808 nm NIR laser irradiation. Further, TGNC-DOX showed laser-responsive and pH-dependent drug release behavior suggesting its suitability for chemo-photothermal therapy, specifically at the tumor microenvironment site. Cellular viability, cellular uptake, ROS generation, and apoptosis assays suggested selective localization of TGNC-DOX in cancer cells that showed a significant cytotoxic effect against MDA-MB-231 breast cancer cells. Moreover, the developed TGNC-DOX showed ferroptosis in MDA-MB-231 cells. The event of TGNC-DOX-mediated thermal ablation is marked by a significant generation of reactive oxygen species (ROS) and apoptosis, as affirmed by flow cytometry. NIR-808 laser-responsive photothermal therapy of cancer cells was found to be more effective than without NIR-808 laser-treated cells, suggesting the fundamental role of photothermal ablation. The outcome concludes developed TGNC-DOX is a novel and potential tool to mediate laser-guided chemo-photothermal ablation treatment of cancer cells.
Exploring Freeze-Drying as Strategy to Enhance Viability of Faecalibacterium duncaniae DSM 17677 upon Aerobic Storage and Gastrointestinal Conditions
Authors: Machado Daniela , Domingos Melany , Barbosa Joana Cristina , Almeida Diana , Andrade José Carlos , Freitas Ana Cristina , Gomes Ana Maria
Published: December 2022

Faecalibacterium duncaniae is an intestinal commensal bacterium proposed as a next-generation probiotic due to its promising outcomes in the treatment and prevention of several human diseases, which demonstrate its multiple contributions to the host’s health. However, its strict anaerobic nature has created several hurdles in the development of functional foods, nutraceuticals, and biotherapeutic products. Herein, we explored freeze-dried formulations containing prebiotics, cryoprotectants, and antioxidant agents as a technological strategy to enhance the viability of F. duncaniae DSM 17677 upon aerobic storage and gastrointestinal tract conditions. Our results indicate that freeze-dried F. duncaniae in a matrix containing inulin, sucrose, cysteine, and riboflavin survived at levels higher than 106 CFU/g and around 105 CFU/g after 1 and 4 days of aerobic storage at room temperature, respectively. Thus, the freeze-dried formulation with inulin, sucrose, cysteine, and riboflavin presents as a protective strategy to improve F. duncaniae viability under aerobic environments. Nevertheless, incorporation of a suitable coating aimed at protecting F. duncaniae against the detrimental gastrointestinal passage effects is urgently required, given its high susceptibility to extreme acidic pH values and bile.
RNA-Sequencing Muscle Plasticity to Resistance Exercise Training and Disuse in Youth and Older Age
Authors: Fernandez-Gonzalo Rodrigo , Willis Craig R. G. , Etheridge Timothy , Deane Colleen S.
Published: December 2022

Maintenance of skeletal muscle mass and function is critical to health and wellbeing throughout the lifespan. However, disuse through reduced physical activity (e.g., sedentarism), immobilisation, bed rest or microgravity has significant adverse effects on skeletal muscle health. Conversely, resistance exercise training (RET) induces positive muscle mass and strength adaptations. Several studies have employed microarray technology to understand the transcriptional basis of muscle atrophy and hypertrophy after disuse and RET, respectively, to devise fully effective therapeutic interventions. More recently, rapidly falling costs have seen RNA-sequencing (RNA-seq) increasingly applied in exploring muscle adaptations to RET and disuse. The aim of this review is to summarise the transcriptional responses to RET or disuse measured via RNA-seq in young and older adults. We also highlight analytical considerations to maximise the utility of RNA-seq in the context of skeletal muscle research. The limited number of muscle transcriptional signatures obtained thus far with RNA-seq are generally consistent with those obtained with microarrays. However, RNA-seq may provide additional molecular insight, particularly when combined with data-driven approaches such as correlation network analyses. In this context, it is essential to consider the most appropriate study design parameters as well as bioinformatic and statistical approaches. This will facilitate the use of RNA-seq to better understand the transcriptional regulators of skeletal muscle plasticity in response to increased or decreased use.
Influence of Bacteria of the Genus Pseudomonas on Leguminous Plants and Their Joint Application for Bioremediation of Oil Contaminated Soils
Authors: Kuzina Elena , Mukhamatdyarova Svetlana , Sharipova Yuliyana , Makhmutov Ainur , Belan Larisa , Korshunova Tatyana
Published: December 2022

The modern approach to the creation of biological products to stimulate plant growth is based on the study of specific inter-bacterial interactions. This study describes the impact that the introduction of strains of the genus Pseudomonas has on annual and perennial leguminous plants and the ecosystem of the leguminous plant—the indigenous microbial community. The objects of research under the conditions of vegetation experiments were plants of field peas (Pisum sativum L.), white lupine (Lupinus albus L.), chickpea (Cicer arietinum L.), alfalfa (Medicago sativa subsp. varia (Martyn) Arcang.), and white sweet clover (Melilotus albus Medik.). For the treatment of plant seeds, a liquid culture of strains of growth-stimulating bacteria Pseudomonas koreensis IB-4, and P. laurentiana ANT 17 was used. The positive effect of the studied strains on the germination, growth and development of plants was established. There was no inhibitory effect of inoculants on rhizobia; on the contrary, an increase in nodule formation was observed. The possibility of recultivation of oil-contaminated soil using chickpea and alfalfa as phytomeliorants and growth-stimulating strains P. koreensis IB-4, P. laurentiana ANT 17 as inoculants was evaluated. It is proved that seed treatment improved the morphological parameters of plants, as well as the efficiency of oil destruction.
Neutrophil Immunomodulatory Activity of Nerolidol, a Major Component of Essential Oils from Populus balsamifera Buds and Propolis
Authors: Schepetkin Igor A. , Özek Gulmira , Özek Temel , Kirpotina Liliya N. , Kokorina Polina I. , Khlebnikov Andrei I. , Quinn Mark T.
Published: December 2022

Propolis is a resinous mixture of substances collected and processed from various botanical sources by honeybees. Black poplar (Populus balsamifera L.) buds are one of the primary sources of propolis. Despite their reported therapeutic properties, little is known about the innate immunomodulatory activity of essential oils from P. balsamifera and propolis. In the present studies, essential oils were isolated from the buds of P. balsamifera and propolis collected in Montana. The main components of the essential oil from P. balsamifera were E-nerolidol (64.0%), 1,8-cineole (10.8%), benzyl benzoate (3.7%), α-terpinyl acetate (2.7%), α-pinene (1.8%), o-methyl anisol (1.8%), salicylaldehyde (1.8%), and benzyl salicylate (1.6%). Likewise, the essential oil from propolis was enriched with E-nerolidol (14.4%), cabreuva oxide-VI (7.9%), α-bisabolol (7.1%), benzyl benzoate (6.1%), β-eudesmol (3.6%), T-cadinol (3.1%), 2-methyl-3-buten-2-ol (3.1%), α-eudesmol (3.0%), fokienol (2.2%), nerolidol oxide derivative (1.9%), decanal (1.8%), 3-butenyl benzene (1.5%), 1,4-dihydronaphthalene (1.5%), selina-4,11-diene (1.5%), α-cadinol (1.5%), linalool (1.4%), γ-cadinene (1.4%), 2-phenylethyl-2-methyl butyrate (1.4%), 2-methyl-2-butenol (1.3%), octanal (1.1%), benzylacetone (1.1%), and eremoligenol (1.1%). A comparison between P. balsamifera and propolis essential oils demonstrated that 22 compounds were found in both essential oil samples. Both were enriched in E-nerolidol and its derivatives, including cabreuva oxide VI and nerolidol oxides. P. balsamifera and propolis essential oils and pure nerolidol activated Ca2+ influx in human neutrophils. Since these treatments activated neutrophils, the essential oil samples were also evaluated for their ability to down-regulate the neutrophil responses to subsequent agonist activation. Indeed, treatment with P. balsamifera and propolis essential oils inhibited subsequent activation of these cells by the N-formyl peptide receptor 1 (FPR1) agonist fMLF and the FPR2 agonist WKYMVM. Likewise, nerolidol inhibited human neutrophil activation induced by fMLF (IC50 = 4.0 μM) and WKYMVM (IC50 = 3.7 μM). Pretreatment with the essential oils and nerolidol also inhibited human neutrophil chemotaxis induced by fMLF, again suggesting that these treatments down-regulated human neutrophil responses to inflammatory chemoattractants. Finally, reverse pharmacophore mapping predicted several potential kinase targets for nerolidol. Thus, our studies have identified nerolidol as a potential anti-inflammatory modulator of human neutrophils.
The TaGSK1, TaSRG, TaPTF1, and TaP5CS Gene Transcripts Confirm Salinity Tolerance by Increasing Proline Production in Wheat (Triticum aestivum L.)
Authors: Aycan Murat , Baslam Marouane , Mitsui Toshiaki , Yildiz Mustafa
Published: December 2022

Salinity is an abiotic stress factor that reduces yield and threatens food security in the world’s arid and semi-arid regions. The development of salt-tolerant genotypes is critical for mitigating yield losses, and this journey begins with the identification of sensitive and tolerant plants. Numerous physiologic and molecular markers for detecting salt-tolerant wheat genotypes have been developed. One of them is proline, which has been used for a long time but has received little information about proline-related genes in wheat genotypes. In this study, proline content and the expression levels of proline-related genes (TaPTF1, TaDHN, TaSRG, TaSC, TaPIMP1, TaMIP, TaHKT1;4, TaGSK, TaP5CS, and TaMYB) were examined in sensitive, moderate, and tolerant genotypes under salt stress (0, 50, 150, and 250 mM NaCl) for 0, 12, and 24 h. Our results show that salt stress increased the proline content in all genotypes, but it was found higher in salt-tolerant genotypes than in moderate and sensitive genotypes. The salinity stress increased gene expression levels in salt-tolerant and moderate genotypes. While salt-stress exposure for 12 and 24 h had a substantial effect on gene expression in wheat, TaPTF1, TaPIMP1, TaMIP, TaHKT1;4, and TaMYB genes were considerably upregulated in 24 h. The salt-tolerant genotypes showed a higher positive interaction than a negative interaction. The TaPTF1, TaP5CS, TaGSK1, and TaSRG genes were found to be more selective than the other analyzed genes under salt-stress conditions. Despite each gene’s specific function, increasing proline biosynthesis functioned as a common mechanism for separating salt tolerance from sensitivity.
Classification and Prediction by Pigment Content in Lettuce (Lactuca sativa L.) Varieties Using Machine Learning and ATR-FTIR Spectroscopy
Authors: Falcioni Renan , Moriwaki Thaise , Gibin Mariana Sversut , Vollmann Alessandra , Pattaro Mariana Carmona , Giacomelli Marina Ellen , Sato Francielle , Nanni Marcos Rafael , Antunes Werner Camargos
Published: December 2022

Green or purple lettuce varieties produce many secondary metabolites, such as chlorophylls, carotenoids, anthocyanins, flavonoids, and phenolic compounds, which is an emergent search in the field of biomolecule research. The main objective of this study was to use multivariate and machine learning algorithms on Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR)-based spectra to classify, predict, and categorize chemometric attributes. The cluster heatmap showed the highest efficiency in grouping similar lettuce varieties based on pigment profiles. The relationship among pigments was more significant than the absolute contents. Other results allow classification based on ATR-FTIR fingerprints of inflections associated with structural and chemical components present in lettuce, obtaining high accuracy and precision (>97%) by using principal component analysis and discriminant analysis (PCA-LDA)-associated linear LDA and SVM machine learning algorithms. In addition, PLSR models were capable of predicting Chla, Chlb, Chla+b, Car, AnC, Flv, and Phe contents, with R2P and RPDP values considered very good (0.81–0.88) for Car, Anc, and Flv and excellent (0.91–0.93) for Phe. According to the RPDP metric, the models were considered excellent (>2.10) for all variables estimated. Thus, this research shows the potential of machine learning solutions for ATR-FTIR spectroscopy analysis to classify, estimate, and characterize the biomolecules associated with secondary metabolites in lettuce.
Relation of Chemical Composition and Colour of Spruce Wood
Authors: Kučerová Viera , Hrčka Richard , Hýrošová Tatiana
Published: December 2022

The visual inspection of fresh cut spruce wood (Picea abies, L. Karst.) showed the variability of its colour. Wood visual inspection is a part of wood quality assessment, for example, prior to or after its processing. The detail spruce wood colour analysis was performed using spectrophotometric data. The colour was measured by the bench-top spectrophotometer CM-5 Konica Minolta. The spectrophotometer was calibrated with a built-in white standard and on air. The whole analysis was performed in an xy chromaticity diagram supplemented with coordinate Y and CIE L*a*b* colour spaces. The ratio of the white chromophore amount to the amount of all achromatic chromophores is related to the Y coordinate. The ratio of the chromatic chromophore amount to all chromophores amount is saturation. The constructed model of the spruce wood colour is composed of four chromophores. The white chromophore belongs to holocellulose. The black chromophore belongs to lignin. The saturation is influenced by two chromophores. One of them belongs to extractives, another to lignin. The amounts of chromophores correlated with the spruce wood chemical composition. The chemical composition was measured using the procedures of Seifert, Wise, Sluiter, and ASTM. Moreover, the wood colour is affected by the moisture content.
Effect of Water Immersion on Compressive Properties of Coir Fiber Magnesium Phosphate Cement
Authors: Wang Shimin , Song Shaozhi , Huang Mingyu , Xie Zhujian , Zhang Liwen , Zheng Wenzhi
Published: December 2022

Magnesium phosphate cement (MPC) is a new type of inorganic cementitious rapid repair material, but it has poor toughness and is easy to crack. According to our previous research, these problems can be ameliorated by adding natural coir fiber (CF) into MPC. As coir fiber magnesium phosphate cement (CF-MPC) may be used in humid or rainy areas, its water resistance is an important property in consideration. However, at present, little research has focused on this aspect to provide a good theoretical and experimental basis for the practical application of CF-MPC. In this paper, static compression test and solubility test were used to study the mechanical properties and solubility of CF-MPC under water. At the same time, X-ray diffraction (XRD) and scanning electron microscopy (SEM) were used to test the changes of hydration composition and microstructure of the test specimen, so as to understand the deterioration mechanism of CF-MPC in water. The results suggested that, when compared with CF-MPC cured in air, CF-MPC cured in water is more prone to encounter oblique cracks and through cracks in the compression process. Moreover, with the extension of curing time, the compressive strength and elastic modulus of CF-MPC cured in water will continue to decrease, the concentrations of PH, K+, and Mg2+ in the curing solution will change significantly, resulting in the gradual decrease in the mass ratio of MgO and MgKPO4·6H2O in CF-MPC matrix, cracks and pores, and looseness in the microstructure.
Maltol-Incorporated Acetylated Cassava Starch Films for Shelf-Life-Extension Packaging of Bakery Products
Authors: Promhuad Khwanchat , Bumbudsanpharoke Nattinee , Wadaugsorn Kiattichai , Sonchaeng Uruchaya , Harnkarnsujarit Nathdanai
Published: December 2022

Maltol is widely used as a flavor enhancer in baked goods and has an antimicrobial function. Maltol can also be incorporated into biopolymer films to produce active biodegradable packaging for bakery products. This research investigated the incorporation of 1–10% maltol into acetylated cassava starch films as functional packaging for shelf-life extension of butter cake. Films were determined for morphology, chemical interaction and packaging properties. Infrared absorption indicated H-bonding between starch and maltol, while plasticization effects decreased mechanical relaxation temperature. Microstructures showed enhanced smoothness at up to 3% maltol, while maltol crystallization occurred at higher concentrations, giving non-homogeneous matrices. Tensile strength and elongation at break reduced by 37% and 34%, respectively, with the addition of maltol up to 10%. Maltol concentration modified the hydrophilicity and molecular mobility of the matrices, impacting water vapor and oxygen permeability. Films incorporated with maltol were used as packaging for preservative-free butter cake and delayed visible mold growth at room temperature. Starch films with maltol at 1–5% delayed fungal growth by up to 2.7–times, while films containing 10% maltol inhibited mold growth by 6–times (up to 19 days of storage). Incorporating maltol into starch films produced bioactive materials, extending shelf-life while maintaining the aroma of bakery products.
Heat Transfer Model and Soft Sensing for Segmented Fluidized Bed Dryer
Authors: Lu Mengke , Kranz Patrick , Salmon Andrew , Wilkinson Sam , Sibanc Rok
Published: December 2022

The aim of this work is to evaluate thermal behaviors and develop a soft sensor for online prediction of LOD (loss-on-drying) in the segmented fluidized bed dryer (Seg-FBD) in the ConsiGma25 line, which is regarded as the intermediate critical quality attribute for the final drug product. Preheating and drying experiments are performed and heat transfers and conductions among the Seg-FBD are evaluated based on the temperature measurements from sensors and an infrared thermal camera. A temperature distribution in dryer cells and high heat conductions in walls are found. Considerable heat transfers between the neighboring dryer cells are determined, which equal approximately 7% of the energy provided from the heated air. The cell-to-cell heat transfers are implemented into the heat transfer and drying models of the Seg-FBD. The models are calibrated successively in gPROMS Formulated Products (gFP) and the temperature and LOD errors are less than 2 °C and 0.5 wt.%, respectively. Subsequently, a soft sensor is established by combining data sources, a real-time data communication method, and the developed drying model, and it shows the capability of predicting real-time LOD, where the error of end-point LOD is within 0.5 wt.%. The work provides detailed steps and applicable tools for developing a soft sensor, and the online deployment of the soft sensor could support continuous production in the Seg-FBD by enabling visualization of process status and determination of process end point.
Dust Explosion Risk Assessment for Dry Dust Collector Based on AHP-Fuzzy Comprehensive Evaluation
Authors: Sun Siheng , Mao Tingting , Lv Pengfei , Pang Lei
Published: December 2022

Dry dust collectors are a typical dust and gas coexistence space. Dust explosion risk assessments should be performed for effective prevention and control of dust explosion accidents. In this paper, a dust explosion risk assessment index system for dust removal systems was constructed following the dust characteristics and the actual operation of a dry dust collector. The proposed system consisted of three first-level indexes (dust explosion characteristic parameters, environmental parameters in the dust collector box, use state of explosion prevention and control device) and seven second-level indexes (dust explosion sensitivity, dust explosion severity, temperature in the dust collector box, pressure difference between inlet and outlet, operating state of spark detection, operating the explosion venting disc, and operating state of the lock gas ash discharge valve). The analytic hierarchy process was adapted to calculate the weight of each index. Additionally, a dust explosion risk assessment model for the dust removal system was constructed using the fuzzy comprehensive evaluation method to form a set of dust explosion risk assessment methods suitable for dry dust collectors. The risk of explosion was assessed at level II through the use of paper powder with a particle size of 75 μm, which means this method is reliable.
An Improved Adaptive Dynamic Programming Algorithm Based on Fuzzy Extended State Observer for Dissolved Oxygen Concentration Control
Authors: Chen Xueliang , Zhong Weimin , Peng Xin , Du Peihao , Li Zhongmei
Published: December 2022

To solve the anti-disturbance control problem of dissolved oxygen concentration in the wastewater treatment plant (WWTP), an anti-disturbance control scheme based on reinforcement learning (RL) is proposed. An extended state observer (ESO) based on the Takagi–Sugeno (T-S) fuzzy model is first designed to estimate the the system state and total disturbance. The anti-disturbance controller compensates for the total disturbance based on the output of the observer in real time, online searches the optimal control policy using a neural-network-based adaptive dynamic programming (ADP) controller. For reducing the computational complexity and avoiding local optimal solutions, the echo state network (ESN) is used to approximate the optimal control policy and optimal value function in the ADP controller. Further analysis demonstrates the observer estimation errors for system state and total disturbance are bounded, and the weights of ESNs in the ADP controller are convergent. Finally, the effectiveness of the proposed ESO-based ADP control scheme is evaluated on a benchmark simulation model of the WWTP.
Elimination of PCDD/Fs over Commercial Honeycomb-Like Catalyst of V2O5-MoO3/TiO2 at Low Temperature: From Laboratory Experiments to Field Study
Authors: Lai Jianwen , Ma Yunfeng , Wu Jiayao , Yu Hong , Li Xiaodong , Lin Xiaoqing
Published: December 2022

With the need for ultra-low emissions and the strict regulation of PCDD/Fs from MSWI plants, traditional SCR catalysts have been applied to remove PCDD/Fs. In this study, we compared one typical commercial V2O5-MoO3/TiO2 catalyst’s performance in removing PCDD/Fs under laboratory and industrial conditions. Various characterization methods like XRF, XPS, BET, and H2-TPR were applied to analyze the catalyst’s properties. The laboratory results showed that the adsorption could significantly affect the removal at low temperatures. The RE on PCDD/Fs was 59.4% (55.0% for toxicity RE), 88.5% (90.3%), and 78.0% (76.0%) at 160 °C, 180 °C, and 200 °C, respectively, showing that 180 °C is the most suitable operation temperature for this V2O5-MoO3/TiO2 catalyst. The field study was conducted at 180 °C, and the results revealed that the competition between water vapor and the interaction of SO2 could lower the RE. However, comparisons between laboratory and field conditions showed that this V2O5-MoO3/TiO2 catalyst still showed good stability, with only a 6.8% drop.
Determination and Validation of Discrete Element Model Parameters of Soybeans with Various Moisture Content for the Discharge Simulation from a Cylindrical Model Silo
Authors: Jung Hwabin , Yoon Won Byong
Published: December 2022

This study investigates the physical parameters that affect the flow patterns of soybeans with various moisture content (12% to 60%) at varying orifice sizes (20, 40, and 60 mm) in a cylindrical silo. The flow conditions required to obtain a steady mass flow during discharge were evaluated via experiments and three-dimensional discrete element method (DEM) simulation. The discharged mass flow rates at different flow conditions provided the critical size of the orifice. If the reduced diameter (Dred) of an orifice is >5.59, the flow showed a steady state. Based on the mass flow index (MFI), the flow patterns at 40% and 60% moisture content at 40 and 60 mm orifice sizes, respectively, showed funnel flows. although these flow conditions were satisfied to maintain a steady flow. The maximum wall pressure for the funnel flow showed the location of the interlocking phenomenon where the stagnant zone began during discharging. DEM simulation was validated through the mass profiles using the parameters obtained by the experiments. This study demonstrates that the experimental and analytical results with DEM simulation predict the flow behaviors of soybeans well at various moisture contents. These results are useful for designing silos for continuous food processing.
Multiple Graph Adaptive Regularized Semi-Supervised Nonnegative Matrix Factorization with Sparse Constraint for Data Representation
Authors: Zhang Kexin , Li Lingling , Di Jinhong , Wang Yi , Zhao Xuezhuan , Zhang Ji
Published: December 2022

Multiple graph and semi-supervision techniques have been successfully introduced into the nonnegative matrix factorization (NMF) model for taking full advantage of the manifold structure and priori information of data to capture excellent low-dimensional data representation. However, the existing methods do not consider the sparse constraint, which can enhance the local learning ability and improve the performance in practical applications. To overcome this limitation, a novel NMF-based data representation method, namely, the multiple graph adaptive regularized semi-supervised nonnegative matrix factorization with sparse constraint (MSNMFSC) is developed in this paper for obtaining the sparse and discriminative data representation and increasing the quality of decomposition of NMF. Particularly, based on the standard NMF, the proposed MSNMFSC method combines the multiple graph adaptive regularization, the limited supervised information and the sparse constraint together to learn the more discriminative parts-based data representation. Moreover, the convergence analysis of MSNMFSC is studied. Experiments are conducted on several practical image datasets in clustering tasks, and the clustering results have shown that MSNMFSC achieves better performance than several most related NMF-based methods.
Mechanics Principle and Implementation Technology of Surrounding Rock Pressure Release in Gob-Side Entry Retaining by Roof Cutting
Authors: Zhu Zhen , Du Mingqing , Xi Chuanhao , Yuan Hongping , He Wenshuai
Published: December 2022

Improving coal resource mining rates has long been a focus of coal industry research. The gob-side entry retaining by roof cutting (GERRC) is a new coal mining technology that has gained popularity in China due to its high mining rate and safety. Based on the GERRC technology, the precise technical procedure is elaborated, and the fundamental idea of pressure relief is explored through creating a structural mechanics model of the surrounding rock in this paper. The results of mechanical analysis show that the primary mechanism of roof pressure release is to weaken the integrity of the roof, thereby reducing the ultimate bending moment of the rock stratum. In addition, an additional strategy for pressure release is suggested in this research, involving the weakening of the roof rock by the creation of dense pressure-released holes. The results of the engineering field experimentation demonstrate that the dense pressure-released holes can completely replace the conventional blasting technology of the past to achieve the effect of releasing the roof pressure, thus avoiding the use of hazardous and challenging-to-obtain explosives and demonstrating safety, reliability, and feasibility.
Study on the Flow Pattern and Transition Criterion of Gas-Liquid Two-Phase Flow in the Annular of Shale Gas Fractured Horizontal Wells
Authors: Lei Yu , Wu Zhenghua , Wang Wei , Wu Jian , Ma Bin
Published: December 2022

Improving the accuracy of pressure prediction in the wellbore annular is of great importance for the design in oil and gas production. However, due to the existence of double-layer liquid membrane and the lack of relevant experiments, the existing correlations fail to the field application. In this study, a new model of flow pattern transition in inclined annulus pipe is proposed by using a mechanistic approach to classify the flow patterns. Firstly, a gas-liquid two-phase flow experiment in annulus pipe was carried out in a pipe with an outer diameter of 73.02 mm and an inner diameter of 121.36 mm, and then the influence of inclined angle on the transition boundary of flow pattern is discussed. Finally, a hydrodynamic transition criterion for the flow pattern model of inclined annulus pipe is established and verified in detail. The experimental results show that bubble flow, slug flow, churn flow and annular flow were observed under different inclination angles, and the results indicate that the slug flow will be shifted to the larger gas-liquid superficial flow rate region with the smaller inclination angle, and the annular flow will appear in the higher gas superficial flow rate region. Compared to the performance of the existing correlations (Kelessidis and Zhang) and the present model using the experimental data, the accuracy of the new model reached 83%, significantly higher than the other two models, and the new correlation was better in predicting the transition from slug flow to churn flow and churn flow to annular flow.
Training Machine Learning Algorithms Using Remote Sensing and Topographic Indices for Corn Yield Prediction
Authors: Oliveira Mailson Freire de , Ortiz Brenda Valeska , Morata Guilherme Trimer , Jiménez Andrés-F , Rolim Glauco de Souza , Silva Rouverson Pereira da
Published: December 2022

Methods using remote sensing associated with artificial intelligence to forecast corn yield at the management zone level can help farmers understand the spatial variability of yield before harvesting. Here, spectral bands, topographic wetness index, and topographic position index were integrated to predict corn yield at the management zone using machine learning approaches (e.g., extremely randomized trees, gradient boosting machine, XGBoost algorithms, and stacked ensemble models). We tested four approaches: only spectral bands, spectral bands + topographic position index, spectral bands + topographic wetness index, and spectral bands + topographic position index + topographic wetness index. We also explored two approaches for model calibration: the whole-field approach and the site-specific model at the management zone level. The model’s performance was evaluated in terms of accuracy (mean absolute error) and tendency (estimated mean error). The results showed that it is possible to predict corn yield with reasonable accuracy using spectral crop information associated with the topographic wetness index and topographic position index during the flowering growth stage. Site-specific models increase the accuracy and reduce the tendency of corn yield forecasting on management zones with high, low, and intermediate yields.
Long-Term Spatiotemporal Variability of Whitings in Lake Geneva from Multispectral Remote Sensing and Machine Learning
Authors: Many Gaël , Escoffier Nicolas , Ferrari Michele , Jacquet Philippe , Odermatt Daniel , Mariethoz Gregoire , Perolo Pascal , Perga Marie-Elodie
Published: December 2022

Whiting events are massive calcite precipitation events turning hardwater lake waters to a milky turquoise color. Herein, we use a multispectral remote sensing approach to describe the spatial and temporal occurrences of whitings in Lake Geneva from 2013 to 2021. Landsat-8, Sentinel-2, and Sentinel-3 sensors are combined to derive the AreaBGR index and identify whitings using appropriate filters. 95% of the detected whitings are located in the northeastern part of the lake and occur in a highly reproducible environmental setting. An extended time series of whitings in the last 60 years is reconstructed from a random forest algorithm and analyzed through a Bayesian decomposition for annual and seasonal trends. The annual number of whiting days between 1958 and 2021 does not follow any particular monotonic trend. The inter-annual changes of whiting occurrences significantly correlate to the Western Mediterranean Oscillation Index. Spring whitings have increased since 2000 and significantly follow the Atlantic Multidecadal Oscillation index. Future climate change in the Mediterranean Sea and the Atlantic Ocean could induce more variable and earlier whiting events in Lake Geneva.
Transmit Beampattern Design for Distributed Satellite Constellation Based on Space–Time–Frequency DoFs
Authors: Tan Xiaomin , Duan Chongdi , Li Yu , Chen Jinming , An Jianping
Published: December 2022

For distributed satellite constellations, detection performance can be equivalently regarded as a single large satellite by the cooperative operation of multiple small satellites, which is a promising research topic of the Next-Generation Radar (NGR) system. However, dense grating lobes inevitably occur in the synthetic transmit pattern due to its distributed configuration, as a result of which the detection performance of dynamic coherent radar is seriously weakened. In this paper, a novel transmit beampattern optimization method for dynamic coherent radar based on a distributed satellite constellation is presented. Firstly, the effective coherent detection range interval is determined by several influence factors, i.e., coherent detection, far-field, and system link constraints. Then, we discuss the quantitative evaluation method for coherent integration in terms of synchronization error, beam pointing error, and high-speed motion characteristics and we allocate the corresponding terms in a reasonable way from the perspective of engineering. Finally, the space–time–frequency degrees of freedom (DOFs), which can be collected from satellite spacing, carrier frequencies, and platform motion characteristics, are utilized to realize a robust transmit beampattern with low sidelobe by invoking a genetic algorithm (GA). Simulation results validate the effectiveness of our theoretic analysis, and unambiguous coherent transmit beamforming with a satellite constellation of limited scale is accomplished.
Time-Range Adaptive Focusing Method Based on APC and Iterative Adaptive Radon-Fourier Transform
Authors: Guan Jian , Pei Jiazheng , Huang Yong , Chen Xiaolong , Chen Baoxin
Published: December 2022

In conventional radar signal processing, the cascade of pulse compression (i.e., matched filter) and Radon-Fourier transform (RFT) can extract the estimated scattering coefficient of the target in the range-velocity dimension through long-time coherent integration (i.e., long-time focusing). However, matched filter has problems such as range sidelobes. RFT belongs to a standard time-dimension matched filter, which will cause velocity sidelobes of strong targets. The range-velocity sidelobes caused by matched filter and RFT will mask other weak targets and affect the subsequent signal processing processes such as target detection and tracking. To suppress range-velocity sidelobes and achieve better range-velocity focusing, this paper proposes a time-range adaptive focusing method named APC-IARFT for short, which is based on adaptive pulse compression (APC) and newly proposed iterative adaptive Radon-Fourier transform (IARFT). In the APC-IARFT method, the radar time-range adaptive focusing consists of two steps: range-dimension adaptive focusing and long-time adaptive focusing in the velocity dimension. The APC method can realize range-dimension adaptive focusing and suppress range sidelobes of strong targets. Then, based on the minimum variance distortionless response (MVDR) formulation, the proposed IARFT method iteratively designs time-dimension adaptive filter of each range-velocity grid according to the received signal processed by APC to suppress velocity sidelobes of strong targets and achieve long-time adaptive focusing. Compared with the conventional cascade of matched filter and RFT, the cascade of matched filter and adaptive Radon-Fourier transform (ARFT), the results show that the proposed time-range adaptive focusing method (i.e., APC-IARFT) is competent for a variety of scenarios.
Sentinel-1 InSAR and GPS-Integrated Long-Term and Seasonal Subsidence Monitoring in Houston, Texas, USA
Authors: Liu Yuhao , Wang Guoquan , Yu Xiao , Wang Kuan
Published: December 2022

For approximately 100 years, the Houston region has been adversely impacted by land subsidence associated with excessive groundwater withdrawals. The rapidly growing population in the Houston region means the ongoing subsidence must be vigilantly monitored. Interferometric synthetic aperture radar (InSAR) has become a powerful tool for remotely mapping land-surface deformation over time and space. However, the humid weather and the heavy vegetation have significantly degraded the performance of InSAR techniques in the Houston region. This study introduced an approach integrating GPS and Sentinel-1 InSAR datasets for mapping long-term (2015–2019) and short-term (inter-annual, seasonal) subsidence within the greater Houston region. The root-mean-square (RMS) of the detrended InSAR-displacement time series is able to achieve a subcentimeter level, and the uncertainty (95% confidence interval) of the InSAR-derived subsidence rates is able to achieve a couple of millimeters per year for 5-year or longer datasets. The InSAR mapping results suggest the occurrence of moderate ongoing subsidence (~1 cm/year) in nothwestern Austin County, northern Waller County, western Liberty County, and the city of Mont Belvieu in Champers County. Subsidence in these areas was not recognized in previous GPS-based investigations. The InSAR mapping results also suggest that previous GPS-based investigations overestimated the ongoing subsidence in southwestern Montgomery County, but underestimated the ongoing subsidence in the northeastern portion of the county. We also compared the InSAR- and GPS-derived seasonal ground movements (subsidence and heave). The amplitudes of the seasonal signals from both datasets are comparable, below 4 mm within non-subsiding areas and over 6 mm in subsiding (>1 cm/year) areas. This study indicates that groundwater-level changes in the Evangeline aquifer are the primary reason for ongoing long-term and seasonal subsidence in the Houston region. The former is dominated by inelastic deformation, and the latter is dominated by elastic deformation. Both could cause infrastructure damage. This study demonstrated the potential of employing the GPS- and InSAR-integrated method (GInSAR) for near-real-time subsidence monitoring in the greater Houston region. The near-real-time monitoring would also provide timely information for understanding the dynamic of groundwater storage and improving both long-term and short-term groundwater resource management.
Using UAV Photogrammetry and Automated Sensors to Assess Aquifer Recharge from a Coastal Wetland
Authors: García-López Santiago , Vélez-Nicolás Mercedes , Martínez-López Javier , Sánchez-Bellón Angel , Pacheco-Orellana María Jesús , Ruiz-Ortiz Verónica , Muñoz-Pérez Juan José , Barbero Luis
Published: December 2022

Novel data-acquisition technologies have revolutionized the study of natural systems, allowing the massive collection of information in situ and remotely. Merging these technologies improves the understanding of complex hydrological interactions, such as those of wetland–aquifer systems, and facilitates their conservation and management. This paper presents the combination of UAV technology with water level dataloggers for the study of a coastal temporary wetland linked to an underlying sandy aquifer and influenced by the tidal regime. Wetland morphology was defined using UAV imagery and SfM algorithms during the dry period. The DTM (6.9 cm resolution) was used to generate a flood model, which was subsequently validated with an orthophoto from a wet period. This information was combined with water stage records at 10-min intervals from a network of dataloggers to infer the water balance of the wetland and the transfers to the aquifer. Inflows into the pond were around 6200 m3 (40% direct precipitation over the pond, 60% surface runoff). Outputs equalled the inputs (41% direct evaporation from water surface, 59% transfers into the aquifer). The proposed methodology has demonstrated its suitability to unravel complex wetland–aquifer interactions and to provide reliable estimations of the elements of the water balance.
Precipitation Dominates the Distribution of Species Richness on the Kunlun–Pamir Plateau
Authors: Huang Xiaoran , Bao Anming , Zhang Junfeng , Yu Tao , Zheng Guoxiong , Yuan Ye , Wang Ting , Nzabarinda Vincent , De Maeyer Philippe , Van de Voorde Tim
Published: December 2022

The Kunlun–Pamir Plateau is a globally irreplaceable biodiversity reserve, yet it is still unclear what causes the distribution of species richness. Here, we relied on the productivity and the water–energy dynamics hypotheses to investigate the distribution pattern of species richness (and its determinants) in the Kunlun–Pamir Plateau. The productivity hypothesis is mainly based on five MODIS products (NDVI, EVI, FPAR, LAI and GPP), which were calculated for three Dynamic Habitat Indices (DHIs): (1) cumulative productivity (CumDHI), (2) minimum productivity (MinDHI) and (3) intra-annual variation productivity (VarDHI). The CumDHI was applied to assess whether or not more energy has a higher species richness value. The MinDHI was used to determine and evaluate the higher minimums, leading to a higher species richness. The VarDHI was the annual variation value in productivity and was utilized to assess if the reduced intra-annual variability triggers a higher species richness. We found that the DHIs based on the FPAR correlated slightly higher with the mammal, bird, breeding bird and non-breeding bird richness (than those based on the other four DHIs, and the values were 0.24, 0.25, 0.24 and 0.01, respectively). The correlation between the climate variables and the mammals, birds, breeding birds and non-breeding birds was bigger at 0.24, 0.54, 0.54 and 0.02, respectively, and was mainly dominated by the precipitation-related climatic factors. The water–energy dynamic hypothesis is better suited to the Kunlun–Pamir Plateau than the productivity hypothesis. Our results might provide valuable information regarding the biodiversity conservation in this region.
Carbon Air–Sea Flux in the Arctic Ocean from CALIPSO from 2007 to 2020
Authors: Zhang Siqi , Chen Peng , Zhang Zhenhua , Pan Delu
Published: December 2022

Quantified research on the Arctic Ocean carbon system is poorly understood, limited by the scarce available data. Measuring the associated phytoplankton responses to air–sea CO2 fluxes is challenging using traditional satellite passive ocean color measurements due to low solar elevation angles. We constructed a feedforward neural network light detection and ranging (LiDAR; FNN-LID) method to assess the Arctic diurnal partial pressure of carbon dioxide (pCO2) and formed a dataset of long-time-series variations in diurnal air–sea CO2 fluxes from 2001 to 2020; this study represents the first time spaceborne LiDAR data were employed in research on the Arctic air–sea carbon cycle, thus providing enlarged data coverage and diurnal pCO2 variations. Although some models replace Arctic winter Chl-a with the climatological average or interpolated Chl-a values, applying these statistical Chl-a values results in potential errors in the gap-filled wintertime pCO2 maps. The CALIPSO measurements obtained through active LiDAR sensing are not limited by solar radiation and can thus provide ‘fill-in’ data in the late autumn to early spring seasons, when ocean color sensors cannot record data; thus, we constructed the first complete record of polar pCO2. We obtained Arctic FFN-LID-fitted in situ measurements with an overall mean R2 of 0.75 and an average RMSE of 24.59 µatm and filled the wintertime observational gaps, thereby indicating that surface water pCO2 is higher in winter than in summer. The Arctic Ocean net CO2 sink has seasonal sources from some continental shelves. The growth rate of Arctic seawater pCO2 is becoming larger and more remarkable in sectors with significant sea ice retreat. The combination of sea surface partial pressure and wind speed impacts the diurnal carbon air–sea flux variability, which results in important differences between the Pacific and Atlantic Arctic Ocean. Our results show that the diurnal carbon sink is larger than the nocturnal carbon sink in the Atlantic Arctic Ocean, while the diurnal carbon sink is smaller than the nocturnal carbon sink in the Pacific Arctic Ocean.