bluuebunny/crossref_metadata_2025 huggingface dataset:
Chemical Data and Relationships for a Scoring Algorithm of Extra Virgin Olive Oil’s Nutritional Value
Authors: Cecchi Lorenzo , Conticelli Filippo , Zanoni Bruno , Breschi Carlotta , Bellumori Maria , Mulinacci Nadia
Published: January 2024

Extra virgin olive oil (EVOO) is a valuable product and is highly appreciated by consumers for its great nutritional value. However, to date, there has been a lack of uniform systems capable of ranking the nutritional value of EVOO based on its chemical composition in terms of macro- and micronutrients (including phenolic compounds and tocopherols). The aim of this study was to propose a scoring algorithm to rank the nutritional value of EVOO samples, considering their chemical composition in macro- and micronutrients and their sensitivity to oxidation phenomena. Data from more than 1000 EVOO samples were used to assess the variability of the data, considering the selected negative parameters (free acidity, peroxide value, spectrophotometric indices) and positive components (composition in tocopherols via HPLC-DAD, phenolic compounds via HPLC-DAD, and fatty acids via GC-MS) so as to ensure the universal validity of the scoring algorithm. The dataset included samples from the main producing countries worldwide, in addition to Australia, across several production years; data were selected to represent different production realities. A mathematical model was set up for each chemical component, resulting in six variable values. By combining these values with a dimensionless constant value, the algorithm for computing the nutritional value score (NVS) was defined. It allows the nutritional value of an oil to be ranked on a scale of 0 to 100 based on its chemical composition. The algorithm was then successfully tested using chemical data from about 300 EVOO samples obtained from laboratories from different Italian regions. The proposed NVS is a simple and objective tool for scoring the nutritional value of an EVOO, easy to understand for both producers and consumers.
Development of Fluorescent Chemosensors for Calcium and Lead Detection
Authors: Gomes Liliana J. , Outis Mani , Gomes Clara S. B. , Tomé Augusto C. , Moro Artur J.
Published: January 2024

In the present work, several coumarin-3-carboxamides with different azacrown ether moieties were designed and tested as potential luminescent sensors for metal ions. The derivative containing a 1-aza-15-crown-5 as a metal chelating group was found to yield the strongest response for Ca2+ and Pb2+, exhibiting an eight- and nine-fold emission increase, respectively, while other cations induced no changes in the optical properties of the chemosensor molecule. Job’s plots revealed a 1:1 binding stoichiometry, with association constants of 4.8 × 104 and 8.7 × 104 M–1, and limits of detection of 1.21 and 8.04 µM, for Ca2+ and Pb2+, respectively. Computational studies suggest the existence of a PET quenching mechanism, which is inhibited after complexation with each of these two metals. Proton NMR experiments and X-ray crystallography suggest a contribution from the carbonyl groups in the coumarin-3-carboxamide fluorophore in the coordination sphere of the metal ion.
Anticancer Activity of Astaxanthin-Incorporated Chitosan Nanoparticles
Authors: Hwang Eun Ju , Jeong Young-IL , Lee Kyong-Je , Yu Young-Bob , Ohk Seung-Ho , Lee Sook-Young
Published: January 2024

Astaxanthin (AST)-encapsulated nanoparticles were fabricated using glycol chitosan (Chito) through electrostatic interaction (abbreviated as ChitoAST) to solve the aqueous solubility of astaxanthin and improve its biological activity. AST was dissolved in organic solvents and then mixed with chitosan solution, followed by a dialysis procedure. All formulations of ChitoAST nanoparticles showed small diameters (less than 400 nm) with monomodal distributions. Analysis with Fourier transform infrared (FT-IR) spectroscopy confirmed the specific peaks of AST and Chito. Furthermore, ChitoAST nanoparticles were formed through electrostatic interactions between Chito and AST. In addition, ChitoAST nanoparticles showed superior antioxidant activity, as good as AST itself; the half maximal radical scavenging concentrations (RC50) of AST and ChitoAST nanoparticles were 11.8 and 29.3 µg/mL, respectively. In vitro, AST and ChitoAST nanoparticles at 10 and 20 µg/mL properly inhibited the production of intracellular reactive oxygen species (ROSs), nitric oxide (NO), and inducible nitric oxide synthase (iNOS). ChitoAST nanoparticles had no significant cytotoxicity against RAW264.7 cells or B16F10 melanoma cells, whereas AST and ChitoAST nanoparticles inhibited the growth of cancer cells. Furthermore, AST itself and ChitoAST nanoparticles (20 µg/mL) efficiently inhibited the migration of cancer cells in a wound healing assay. An in vivo study using mice and a pulmonary metastasis model showed that ChitoAST nanoparticles were efficiently delivered to a lung with B16F10 cell metastasis; i.e., fluorescence intensity in the lung was significantly higher than in other organs. We suggest that ChitoAST nanoparticles are promising candidates for antioxidative and anticancer therapies of B16F10 cells.
Silver-Assisted Hydrogen Evolution from Aluminum Oxidation in Saline Media
Authors: Buryakovskaya Olesya A. , Maslakov Konstantin I. , Borshchev Nikita O. , Ambaryan Grayr N. , Butyrin Aleksey V. , Vlaskin Mikhail S.
Published: January 2024

A swarf of aluminum alloy with high corrosion resistance and ductility was successfully converted into fine hydro reactive powders via ball milling with silver powder and either lithium chloride or gallium. The latter substances significantly intensified particle size reduction, while silver formed ‘cathodic’ sites (Ag, Ag2Al), promoting Al corrosion in aqueous saline solutions with hydrogen generation. The diffraction patterns, microphotographs, and elemental analysis results demonstrated partial aluminum oxidation in the samples and their contamination with tungsten carbide from milling balls. Those factors were responsible for obtaining lower hydrogen yields than expected. For AlCl3 solution at 60 °C, Al–LiCl–Ag, Al–LiCl, Al–Ga–Ag, and Al–Ga composites delivered (84.6 ± 0.2), (86.8 ± 1.4), (80.2 ± 0.5), and (76.7 ± 0.7)% of the expected hydrogen, respectively. Modification with Ag promoted Al oxidation, thus providing higher hydrogen evolution rates. The samples with Ag were tested in a CaCl2 solution as well, for which the reaction proceeded much more slowly. At a higher temperature (80 °C) after 3 h of experiment, the corresponding hydrogen yields for Al–LiCl–Ag and Al–Ga–Ag powders were (46.7 ± 2.1) and (31.8 ± 1.9)%. The tested Ag-modified composite powders were considered promising for hydrogen generation and had the potential for further improvement to deliver higher hydrogen yields.
Emerging Multiscale Biofabrication Approaches for Bacteriotherapy
Authors: Rovelli Roberta , Cecchini Beatrice , Zavagna Lorenzo , Azimi Bahareh , Ricci Claudio , Esin Semih , Milazzo Mario , Batoni Giovanna , Danti Serena
Published: January 2024

Bacteriotherapy is emerging as a strategic and effective approach to treat infections by providing putatively harmless bacteria (i.e., probiotics) as antagonists to pathogens. Proper delivery of probiotics or their metabolites (i.e., post-biotics) can facilitate their availing of biomaterial encapsulation via innovative manufacturing technologies. This review paper aims to provide the most recent biomaterial-assisted strategies proposed to treat infections or dysbiosis using bacteriotherapy. We revised the encapsulation processes across multiscale biomaterial approaches, which could be ideal for targeting different tissues and suit diverse therapeutic opportunities. Hydrogels, and specifically polysaccharides, are the focus of this review, as they have been reported to better sustain the vitality of the live cells incorporated. Specifically, the approaches used for fabricating hydrogel-based devices with increasing dimensionality (D)—namely, 0D (i.e., particles), 1D (i.e., fibers), 2D (i.e., fiber meshes), and 3D (i.e., scaffolds)—endowed with probiotics, were detailed by describing their advantages and challenges, along with a future overlook in the field. Electrospinning, electrospray, and 3D bioprinting were investigated as new biofabrication methods for probiotic encapsulation within multidimensional matrices. Finally, examples of biomaterial-based systems for cell and possibly post-biotic release were reported.
Design and Validation of a Short Novel Estradiol Aptamer and Exploration of Its Application in Sensor Technology
Authors: Jin Hongyan , Cheng Yan , Kong Fanli , Huang He , Yang Zhenjun , Wang Xinyi , Cai Xinxia , Luo Jinping , Ming Tao
Published: January 2024

The specific and sensitive detection of 17β-estradiol (E2) is critical for diagnosing and treating numerous diseases, and aptamers have emerged as promising recognition probes for developing detection platforms. However, traditional long-sequence E2 aptamers have demonstrated limited clinical performance due to redundant structures that can affect their stability and recognition ability. There is thus an urgent need to further optimize the structure of the aptamer to build an effective detection platform for E2. In this work, we have designed a novel short aptamer that retains the key binding structure of traditional aptamers to E2 while eliminating the redundant structures. The proposed aptamer was evaluated for its binding properties using microscale thermophoresis, a gold nanoparticle-based colorimetric method, and electrochemical assays. Our results demonstrate that the proposed aptamer has excellent specific recognition ability for E2 and a high affinity with a dissociation constant of 92 nM. Moreover, the aptamer shows great potential as a recognition probe for constructing a highly specific and sensitive clinical estradiol detection platform. The aptamer-based electrochemical sensor enabled the detection of E2 with a linear range between 5 pg mL–1 and 10 ng mL–1 (R2 = 0.973), and the detection capability of a definite low concentration level was 5 pg mL–1 (S/N = 3). Overall, this novel aptamer holds great promise as a valuable tool for future studies on the role of E2 in various physiological and pathological processes and for developing sensitive and specific diagnostic assays for E2 detection in clinical applications.
Regulating Microstructure and Macroscopic Properties in Saturated Salt Solutions Containing Disordered Anions and Cations by Magnetic Field
Authors: Wang Jihong , An Shasha , Ren Junchao
Published: January 2024

Saturated aqueous salt solutions have diverse applications in food production, mineral processing, pharmaceuticals, and environmental monitoring. However, the random and disordered arrangement of ions in these solutions poses limitations across different fields. In this study, we employ magnetic fields to regulate the disordered arrangement by a comprehensive methodology combining contact angle measurement, Raman spectroscopy, X-ray diffraction, and molecular dynamics simulations on saturated KCl solutions. Our findings reveal that weak magnetic fields impede the formation of K-Cl contact pairs and disrupt hydrogen bond networks, particularly DDAA and free OH types. However, they facilitate the interaction between water molecules and ions, leading to an increase in the number of K-O and Cl-H contact pairs, along with an expansion in ion hydration radius. These changes affect macroscopic properties, including the interaction with solid substrates and potential solubility increases. Our experimental and simulation results mutually validate each other, contributing to a theoretical framework for studying magnetic field–material interactions.
Effect of Hydroxytyrosol Derivatives of Donepezil on the Activity of Enzymes Involved in Neurodegenerative Diseases and Oxidative Damage
Authors: D’Errico Antonio , Nasso Rosarita , Rullo Rosario , Maiuolo Jessica , Costanzo Paola , Bonacci Sonia , Oliverio Manuela , De Vendittis Emmanuele , Masullo Mariorosario , Arcone Rosaria
Published: January 2024

Monoamine oxidase and xanthine oxidase inhibitors represent useful multi-target drugs for the prevention, attenuation, and treatment of oxidative damage and neurodegenerative disorders. Chimeric molecules, constituted by naturally derived compounds linked to drugs, represent lead compounds to be explored for the discovery of new synthetic drugs acting as enzyme inhibitors. We have previously reported that seven hydroxytyrosol-donepezil hybrid compounds play a protective role in an in vitro neuronal cell model of Alzheimer’s disease. In this work, we analyzed the effects exerted by the hybrid compounds on the activity of monoamine oxidase A (MAO-A) and B (MAO-B), as well as on xanthine oxidase (XO), enzymes involved in both neurodegenerative disorders and oxidative stress. The results pointed to the identification, among the compounds tested, of selective inhibitors between the two classes of enzymes. While the 4-hydroxy-3-methoxyphenethyl 1-benzylpiperidine-4-carboxylate- (HT3) and the 4-hydroxyphenethyl 1-benzylpiperidine-4-carboxylate- donepezil derivatives (HT4) represented the best inhibitors of MAO-A, with a scarce effect on MAO-B, they were almost ineffective on XO. On the other hand, the 4,5-dihydroxy-2-nitrophenethyl 1-benzylpiperidine-4-carboxylate donepezil derivative (HT2), the least efficient MAO inhibitor, acted like the best XO inhibitor. Therefore, the differential enzymatic targets identified among the hybrid compounds synthesized enhance the possible applications of these polyphenol-donepezil hybrids in neurodegenerative disorders and oxidative stress.
A Novel Label-Free Electrochemical Immunosensor for the Detection of Thyroid Transcription Factor 1 Using Ribbon-like Tungsten Disulfide-Reduced Graphene Oxide Nanohybrids and Gold Nanoparticles
Authors: Wang Wenjing , Tang Huabiao , Zhou Leiji , Li Zhaohui
Published: January 2024

Thyroid transcription factor 1 (TTF1) is an important cancer-related biomarker for clinical diagnosis, especially for carcinomas of lung and thyroid origin. Herein, a novel label-free electrochemical immunosensor was prepared for TTF1 detection based on nanohybrids of ribbon-like tungsten disulfide-reduced graphene oxide (WS2-rGO) and gold nanoparticles (AuNPs). The proposed immunosensor employed H2O2 as the electrochemical probe because of the excellent peroxidase-like activity of ribbon-like WS2-rGO. The introduction of AuNPs not only enhanced the electrocatalytic activity of the immunosensor, but also provided immobilization sites for binding TTF1 antibodies. The electrochemical signals can be greatly amplified due to their excellent electrochemical performance, which realized the sensitive determination of TTF1 with a wide linear range of 0.025–50 ng mL−1 and a lower detection limit of 0.016 ng mL−1 (S/N = 3). Moreover, the immunosensor exhibited high selectivity, good reproducibility, and robust stability, as well as the ability to detect TTF1 in human serum with satisfactory results. These observed properties of the immunosensor enhance its potential practicability in clinical applications. This method can also be used for the detection of other tumor biomarkers by using the corresponding antigen–antibody complex.
The Community Pharmacy as a Study Center for the Epidemiological Analysis of the Population Vaccination against SARS-CoV-2: Evaluation of Vaccine Safety and Pharmaceutical Service
Authors: Dibenedetto Jacopo Raffaele , Cetrone Michela , Antonacci Marina , Cannone Domenico Pio , Antonacci Stefania , Bratta Pasquale , Leonetti Francesco , Tricarico Domenico
Published: January 2024

We conducted a monocentric observational study aimed at evaluating the vaccine safety and the pharmaceutical service provided at a community pharmacy (C.PHARM) in the Puglia Region in the period from 29 December 2021 to 12 March 2022 using data from 550 patients of various ages and sexes and with concomitant diseases. We collected anamnestic data, the number of hospitalizations, and any post-vaccination adverse reactions. Interviews using the integrated EQ5 method were also performed to evaluate the quality of the service offered and any therapy preference. As expected, the vaccines were reactogenic after the first dose in the patients with mild–moderate reactions, with younger age and female gender as risk factors. Immune-allergic reactions of a moderate–severe degree were observed in adult females. In the elderly, the vaccination was well tolerated. Comirnaty® showed a favorable O.R. < 1 vs. other vaccines. No cardiovascular events or hospitalizations were observed up to May 2023. Regional data indicate that all treatments during May 2023 were correlated with the viremia. PaxlovidTM was prescribed in 3% of the patients in our center and in 1.46% in the region, and distributed/dispensed on behalf of third parties in accordance with a novel distribution/dispensation protocol of the C.PHARM that resulted in a safe vaccination center providing appropriate patient inclusion during vaccination.
Preparation of Crust Type Dust Suppression Gel Based on Plant Extraction Technology for Ginkgo biloba Leaves: Characterization, Properties, and Function Mechanism
Authors: Ren Bo , Zhou Gang , Song Mingkun , Jiang Bingyou , Zheng Yuannan , Fan Tao , Li Shuailong , Zhao Jing , Li Haoyang , Qu Hongrui
Published: January 2024

The coal industry plays an essential role in China’s economic development, and issues such as occupational health and environmental pollution caused by coal dust have attracted a great deal of attention. In accordance with the principles of environmental protection and waste management, this study used carboxymethyl ginkgo cellulose (CL) extracted and modified from Ginkgo biloba leaves as a matrix, and a graft copolymerized with sodium 3-allyloxy-1-hydroxy-1-propanesulfonate (AHPS) and N-isopropylacrylamide (NIPAM) monomers to prepare low-cost, environmentally friendly, and high-performance coal dust suppression (C-A-N). By optimizing fitting experimental data through three factors and two response surface analyses, the optimal dust suppression efficiency ratio was determined to be 4:8:5, and its swelling and water retention properties were analyzed. The microstructure, chemical reaction process, combustion performance and crusting property of the dust suppression gel were analyzed using Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetry (TG), scanning electron microscopy (SEM), cone calorimetry, and consolidation layer strength tests. Relevant experiments show that the dust suppression gel prepared in this study has the characteristics of a strong wettability and minor impacts on the calorific value of coal, as well as green and environmental protection. When the wind speed is 10 m/s, the dust suppression effect reaches 93%, and the hardness of the solidified layer reaches 39.6 KPa. This study analyzed the migration and combination of functional groups in the interaction system using molecular dynamics simulation software. The microscopic effect and mechanism between dust suppression gel and coal are revealed from a molecular point of view. The feasibility and accuracy of the molecular dynamics simulation were verified by the consistency between simulation results and experimental data. Therefore, combining the utilization of waste resources with dust suppression can have important economic and social benefits.
Nonlinear Predictive Control of Diesel Engine DOC Outlet Temperature
Authors: Yu Xuan , Wang Yuhua , Wang Guiyong , Shen Qianqiao , Zeng Boshun , He Shuchao
Published: January 2024

In the regeneration mode, precise control of the Diesel Oxidation Catalyst (DOC) outlet temperature is crucial for the complete combustion of carbon Particulate Matter (PM) in the subsequent Diesel Particulate Filter (DPF) and the effective conversion of Nitrogen Oxides (NOx) in the Selective Catalytic Reduction (SCR). The temperature elevation process of the DOC involves a series of intricate physicochemical reactions characterized by high nonlinearity, substantial time delays, and uncertainties. These factors render effective and stable control of the DOC outlet temperature challenging. To address these issues, this study proposes an approach based on Long Short-Term Memory (LSTM) neural networks for Model Predictive Control (MPC), emphasizing precise control of the Diesel Oxidation Catalyst’s outlet temperature during the regeneration mode. To tackle the system’s nonlinear characteristics, LSTM is employed to construct a predictive model for the outlet temperature of the Diesel Oxidation Catalyst, thereby enhancing prediction accuracy. Simultaneously, model predictive control is applied to mitigate the significant time delays inherent in the system. The gradient descent algorithm is utilized within a rolling optimization cycle to optimize the objective function, enabling the rapid determination of the control law. To validate the performance of the proposed control strategy, tracking performance and disturbance rejection tests are conducted. Simulation results demonstrate that, compared to the traditional Proportional Integral Derivative (PID) controller, this control strategy exhibits superior tracking performance and disturbance rejection capabilities. In the regeneration mode, the adoption of this control strategy enables more effective and precise control of the Diesel Oxidation Catalyst’s outlet temperature.
Heat and Mass Transfer Characteristics of Oily Sludge Thermal Desorption
Authors: Li Kai , Cai Ao , Tang Yijun , Zhang Xianyong
Published: January 2024

Oily sludge is a loose material containing solid and multiple liquid components. Thermal desorption is an efficient method of disposing of liquids from oily sludge. Most existing studies have mainly discussed the effect of some external process parameters on thermal desorption, with little discussion on the heat transfer characteristics and the variation in the wet component mass of oily sludge under heating. Small-scale experiments have been performed to measure the rise in temperature and liquid phase content change of the sludge during heating. The temperature rise rate increases with material density and increases faster during the initial heating stage, while it slows down as the liquid phase evaporates. The adhesive shear stress is determined by measuring the pulling force of the test rod, which decreases with decreasing water content and increases significantly with decreasing oil phase content. Heat transfer and energy distribution models have been developed to calculate the rise in the temperature of materials and the evaporation of contained liquids. The heat and mass transfer processes are obtained from simulation calculations by taking the initial material with a mass content of 25% water and 10% oil under a heating temperature of 500 °C. When the heating time reaches 135 min, the drying region reaches the boundary of the test container, at which the material temperature exceeds 350 °C. During the evaporation of different liquid-phase components, there are multiple segments in the corresponding temperature curves. The processing time and heat source temperature can be reasonably determined by analyzing the temperature rise of the material, and the effect of the disposal of liquids from oily sludge can be predicted by analyzing the changes in liquid content. The results may guide the formulation of process parameters for engineering project schemes for oily sludge disposal.
The Nutritional Value of Plant Drink against Bovine Milk—Analysis of the Total Concentrations and the Bio-Accessible Fraction of Elements in Cow Milk and Plant-Based Beverages
Authors: Welna Maja , Szymczycha-Madeja Anna , Lesniewicz Anna , Pohl Pawel
Published: January 2024

Four types of non-dairy (plant) drinks—almond, oat, rice, and soy—as well as cow milk with varying fat contents (1.5%, 2.0%, and 3.2%), were examined and compared in terms of the total concentrations of Al, As, B, Ba, Ca, Cd, Cr, Cu, Fe, K, Mg, Na, Mn, Ni, P, Pb, Sb, Se, Sr, and Zn using inductively coupled optical emission spectrometry (ICP OES). Additionally, in vitro gastrointestinal digestion was used to determine the bio-accessible fraction of selected elements, evaluating the nutritional value and risk assessment involved with the consumption of these beverages. A significant difference in the mineral profile was observed depending on the type of plant drink, with the highest content of elements noted in the soy drink and the lowest in the rice drink. Except for Ca and P, the soy drink appears to be a much better source of essential nutrients, including Cu, Fe, and Mn, than cow’s milk. A similar Ca content in plant beverages can be obtained only by adding calcium salt at the stage of its production. Interestingly, by using the multivariate data analysis, the average content of the selected elements (Cu, K, Na, P, and Zn) can be used both to differentiate dairy and non-dairy milk samples according to their type and to distinguish plant drinks from milk of animal origin. The bio-accessibility of essential elements (Ca, Cu, Fe, Mg, Mn, P, Zn) in cow milk was within 8.37–98.2% and increased with an increase in its fat content. Accordingly, by drinking 1 L of this milk daily, it is possible to contribute to the recommended dietary intakes of Ca, P, Cu, Mg, and Zn between 5.6–68%. Although the bio-accessibility of elements in the rice drink was the highest (9.0–90.8%), the soy drink seems to be the best source of nutrients in bioavailable forms; its consumption (1 L/day) covers the requirements of Cu, Mn, Mg, Ca, P, and Zn in 7.0–67%. Unfortunately, both groups of beverages are not important sources of Fe (plant drink) and Mn or Fe (cow milk) in the human diet. On the other hand, potentially toxic elements (Al, B, Ba) were found in them in a relatively inert form.
Study on the Effectiveness of the Integral Emergency Response System for Coal Mine Water Hazard Accidents Based on Combination Weighting
Authors: Hao Yu , Yang Huanhuan , Zhang Lijun , Sun Chaolun
Published: January 2024

Improving the emergency response effectiveness of coal mines in response to water hazard accidents not only plays a vital part in minimizing the resultant losses, but also functions as an important index for evaluating the emergency response capability of coal mines. Therefore, it is of great necessity to test the emergency response capability of coal mines. In this study, an effectiveness measurement index system for the emergency response system that comprises two primary indexes (i.e., response capability and service capability) and six secondary indexes (i.e., accident information transmission, emergency command and control, emergency rescue and mitigation, emergency management, personnel team, and prevention and preparation) was constructed. Additionally, a technique for order preference by similarity to ideal solution (TOPSIS) model for evaluating the effectiveness of the integral emergency response system for coal mine water hazard accidents, based on combination weighting, was put forward. Both the empirical evaluation and model validation of the emergency response system for water hazard accidents were carried out by taking five coal mines attached to Henan Coking Coal Group as research objects. The findings suggest that the effectiveness of the emergency response system for water hazard accidents in the Guhanshan Coal Mine and the Zhongmachun Coal Mine is rated as “average”, while those in the Jiulishan Coal Mine, Zhaogu No. 1 Coal Mine, and Zhaogu No. 2 Coal Mine are graded as “good”. This result is consistent with the actual situation, which verifies the capacity of the proposed TOPSIS model to evaluate the emergency response system scientifically and efficiently for coal mine water hazard accidents. This study not only offers new ideas for how to enhance the comprehensive emergency response capability of coal mines with respect to water hazard accidents, but also provides support for making decisions concerning the upgrading of the emergency response capacity of coal mines.
Investigating the Influencing Factors of Imbibition of Fracturing Fluids in Tight Reservoirs
Authors: Liu Jian , Qu Xuefeng , Wang Jiwei , Liu Qiang , Zhang Lei , Huang Tao , Yu Haiyang
Published: January 2024

Tight reservoirs are the focus of unconventional oil and gas resource development, but most tight reservoirs exhibit complex pore structures, strong non-homogeneity, and limited water drive development. Fracturing fluid imbibition is a critically important way to improve the recovery of tight reservoirs. In this paper, an NMR experimental device was used to conduct imbibition experiments in tight reservoirs, and the relationship between temperature, pressure, matrix permeability, and imbibition recovery was investigated. Based on the fracturing fluid imbibition recovery curve, the imbibition process is divided into the fast imbibition stage, slow imbibition stage, and imbibition equilibrium. In addition, based on the pore structure division, the recovery changes of each pore under different experimental conditions were quantitatively analyzed. The results indicate that the highest imbibition recovery is achieved at an experimental pressure of 5 MPa within the range of 0 MPa to 15 MPa. Increasing the experimental pressure can increase the imbibition rate but will not increase imbibition recovery. Within the investigated range in this paper, fracturing fluid imbibition increases with rising temperature and matrix permeability. Moreover, the recovery of each pore gradually increases with the experimental pressure ranging from 0 MPa to 5 MPa. The recovery of each pore is positively correlated with matrix permeability and temperature. During the experiment, micropores contributed the most to the recovery, while macropores contributed the least. The study in this paper guides the efficient development of tight reservoirs.
The Contribution of Cornelian Cherry (Cornus mas L.) Alcoholic Beverages on the Sensory, Nutritional and Anti-Nutritional Characteristics—In Vitro and In Silico Approaches
Authors: Szczepaniak Oskar , Stachowiak Barbara , Jeleń Henryk , Stuper-Szablewska Kinga , Szambelan Katarzyna , Kobus-Cisowska Joanna
Published: January 2024

Food producers have focused on novel and attractive raw materials with functional properties. Cornelian cherry (Cornus mas L.) fruits contain numerous compounds that may be beneficial for health. Objective: This study aimed to compare and assess the physicochemical properties and amygdalin levels in brandy and liquor prepared from frozen cornelian cherry fruits. Density functional theory-based B3LYP functionals were used to analyze the spectral and optical properties of amygdalin. The contents of the compounds and volatile products of amygdalin decay were found in two spirituose beverages of Cornus mas, using HPLC and GC-MS. Significant differences in their physicochemical properties were detected between the samples. Alcoholic beverages based on cornelian cherry fruits were rich in a wide range of functional ingredients with a low concentration of amygdalin. In silico analysis showed that orbital density diffusion has a major effect on the physical properties of amygdalin, while differences between the polarities of water and ethanol had no noticeable effect on the spectral properties of the compound. Cornelian cherry-based alcoholic drinks might be interesting functional products with rich aromatic bouquets. The amygdalin concentration is low enough to pose no toxicological threat, but rather shapes the tastory bouquet of the products. Levels of amygdalin may be controlled using the same analytical methods for solutions with different ethanol–water ratios.
Information Extraction and Three-Dimensional Contour Reconstruction of Vehicle Target Based on Multiple Different Pitch-Angle Observation Circular Synthetic Aperture Radar Data
Authors: Zhang Jian , Xie Hongtu , Zhang Lin , Lu Zheng
Published: January 2024

The circular synthetic aperture radar (CSAR) has the ability of all-round continuous observation and high-resolution imaging detection, and can obtain all-round scattering information and higher-resolution images of the observation scene, so as to realize the target information extraction and three-dimensional (3D) contour reconstruction of the observation targets. However, the existing methods are not accurate enough to extract the information of vehicle targets. Through the analysis of the vehicle target scattering model and CSAR image characteristics, this paper proposes a vehicle target information extraction and 3D contour reconstruction method based on multiple different pitch-angle observation CSAR data. The proposed method creatively utilizes the projection relationship of the vehicle in 2D CSAR imaging to reconstruct the 3D contour of the vehicle, without prior information. Firstly, the CSAR data obtained from multiple different pitch-angle observations are fully utilized, and the scattering points of odd-bounce reflection and even-bounce reflection echoes are extracted from the two-dimensional (2D) coherent CSAR images of the vehicle target. Secondly, the basic contour of the vehicle body is extracted from the scattering points of the even-bounce reflected echoes. Then, the geometric projection relationship of the “top–bottom shifting” effect of odd-bounce reflection is used to calculate the height and position information of the scattering points of odd-bounce reflection, so as to extract the multi-layer 3D contour of the vehicle target. Finally, the basic contour and the multi-layer 3D contour of the vehicle are fused to realize high-precision 3D contour reconstruction of the vehicle target. The correctness and effectiveness of the proposed method are verified by using the CVDomes simulation dataset of the American Air Force Research Laboratory (AFRL), and the experimental results show that the proposed method can achieve high-precision information extraction and realize distinct 3D contour reconstruction of the vehicle target.
Evaluating the Efficacy of Segment Anything Model for Delineating Agriculture and Urban Green Spaces in Multiresolution Aerial and Spaceborne Remote Sensing Images
Authors: Gui Baoling , Bhardwaj Anshuman , Sam Lydia
Published: January 2024

Segmentation of Agricultural Remote Sensing Images (ARSIs) stands as a pivotal component within the intelligent development path of agricultural information technology. Similarly, quick and effective delineation of urban green spaces (UGSs) in high-resolution images is also increasingly needed as input in various urban simulation models. Numerous segmentation algorithms exist for ARSIs and UGSs; however, a model with exceptional generalization capabilities and accuracy remains elusive. Notably, the newly released Segment Anything Model (SAM) by META AI is gaining significant recognition in various domains for segmenting conventional images, yielding commendable results. Nevertheless, SAM’s application in ARSI and UGS segmentation has been relatively limited. ARSIs and UGSs exhibit distinct image characteristics, such as prominent boundaries, larger frame sizes, and extensive data types and volumes. Presently, there is a dearth of research on how SAM can effectively handle various ARSI and UGS image types and deliver superior segmentation outcomes. Thus, as a novel attempt in this paper, we aim to evaluate SAM’s compatibility with a wide array of ARSI and UGS image types. The data acquisition platform comprises both aerial and spaceborne sensors, and the study sites encompass most regions of the United States, with images of varying resolutions and frame sizes. It is noteworthy that the segmentation effect of SAM is significantly influenced by the content of the image, as well as the stability and accuracy across images of different resolutions and sizes. However, in general, our findings indicate that resolution has a minimal impact on the effectiveness of conditional SAM-based segmentation, maintaining an overall segmentation accuracy above 90%. In contrast, the unsupervised segmentation approach, SAM, exhibits performance issues, with around 55% of images (3 m and coarser resolutions) experiencing lower accuracy on low-resolution images. Whereas frame size exerts a more substantial influence, as the image size increases, the accuracy of unsupervised segmentation methods decreases extremely fast, and conditional segmentation methods also show some degree of degradation. Additionally, SAM’s segmentation efficacy diminishes considerably in the case of images featuring unclear edges and minimal color distinctions. Consequently, we propose enhancing SAM’s capabilities by augmenting the training dataset and fine-tuning hyperparameters to align with the demands of ARSI and UGS image segmentation. Leveraging the multispectral nature and extensive data volumes of remote sensing images, the secondary development of SAM can harness its formidable segmentation potential to elevate the overall standard of ARSI and UGS image segmentation.
Preliminary Performance Assessment of the Wave Parameter Retrieval Algorithm from the Average Reflected Pulse
Authors: Titchenko Yuriy , Jie Guo , Karaev Vladimir , Ponur Kirill , Ryabkova Maria , Baranov Vladimir , Ocherednik Vladimir , He Yijun
Published: January 2024

To obtain new information about surface waves, it is proposed to use an underwater acoustic wave gauge, and an assessment of its effectiveness can be performed using a numerical simulation and field experiment. A new device, an underwater acoustic wave gauge named “Kalmar”, was developed by the Institute of Applied Physics of the Russian Academy of Sciences for long-term, all-weather monitoring of wind waves. The instrument uses ultrasound to probe the water surface from underwater and can be used to verify remote sensing data. In this work, the capabilities of the device are tested and compared with ADCP data. Two independent methods for processing underwater acoustic wave gauge data are discussed and compared. One of them is completely new for acoustic measurements and is based on the analysis of the shape of the reflected acoustic pulse averaged over space and time. The other allows processing individual reflected pulses and calculating the time implementation of the distance to the water surface. It is shown that two independent methods of significant wave height retrieval from the acoustic wave gauge measurements are highly correlated. The “Kalmar” acoustic wave gauge and the RDI WH-600 acoustic Doppler current profiler operated simultaneously at the test site in Gelendzhik from 1 February to 10 February 2020. The significant wave heights measured by the two instruments are in good agreement.
Unsupervised Domain-Adaptive SAR Ship Detection Based on Cross-Domain Feature Interaction and Data Contribution Balance
Authors: Yang Yanrui , Chen Jie , Sun Long , Zhou Zheng , Huang Zhixiang , Wu Bocai
Published: January 2024

Due to the complex imaging mechanism of SAR images and the lack of multi-angle and multi-parameter real scene SAR target data, the generalization performance of existing deep-learning-based synthetic aperture radar (SAR) image target detection methods are extremely limited. In this paper, we propose an unsupervised domain-adaptive SAR ship detection method based on cross-domain feature interaction and data contribution balance. First, we designed a new cross-domain image generation module called CycleGAN-SCA to narrow the gap between the source domain and the target domain. Second, to alleviate the influence of complex backgrounds on ship detection, a new backbone using a self-attention mechanism to tap the potential of feature representation was designed. Furthermore, aiming at the problems of low resolution, few features and easy information loss of small ships, a new lightweight feature fusion and feature enhancement neck was designed. Finally, to balance the influence of different quality samples on the model, a simple and efficient E12IoU Loss was constructed. Experimental results based on a self-built large-scale optical-SAR cross-domain target detection dataset show that compared with existing cross-domain methods, our method achieved optimal performance, with the mAP reaching 68.54%. Furthermore, our method achieved a 6.27% improvement compared to the baseline, even with only 5% of the target domain labeled data.
Retrieval of Tree Height Percentiles over Rugged Mountain Areas via Target Response Waveform of Satellite Lidar
Authors: Song Hao , Zhou Hui , Wang Heng , Ma Yue , Zhang Qianyin , Li Song
Published: January 2024

The retrieval of tree height percentiles from satellite lidar waveforms observed over mountainous areas is greatly challenging due to the broadening and overlapping of the ground return and vegetation return. To accurately represent the shape distributions of the vegetation and ground returns, the target response waveform (TRW) is resolved using a Richardson–Lucy deconvolution algorithm with adaptive iteration. Meanwhile, the ground return is identified as the TRW component within a 4.6 m ground signal extent above the end point of the TRW. Based on the cumulative TRW distribution, the height metrics of the energy percentiles of 25%, 50%, 75%, and 95% are determined using their vertical distances relative to the ground elevation in this study. To validate the proposed algorithm, we select the received waveforms of the Global Ecosystem Dynamics Investigation (GEDI) lidar over the Pahvant Mountains of central Utah, USA. The results reveal that the resolved TRWs closely resemble the actual target response waveforms from the coincident airborne lidar data, with the mean values of the coefficient of correlation, total bias, and root-mean-square error (RMSE) taking values of 0.92, 0.0813, and 0.0016, respectively. In addition, the accuracies of the derived height percentiles from the proposed algorithm are greatly improved compared with the conventional Gaussian decomposition method and the slope-adaptive waveform metrics method. The mean bias and RMSE values decrease by the mean values of 1.68 m and 2.32 m and 1.96 m and 2.72 m, respectively. This demonstrates that the proposed algorithm can eliminate the broadening and overlapping of the ground return and vegetation return and presents good potential in the extraction of forest structure parameters over rugged mountainous areas.
Detection of Benggang in Remote Sensing Imagery through Integration of Segmentation Anything Model with Object-Based Classification
Authors: Hu Yixin , Qi Zhixin , Zhou Zhexun , Qin Yan
Published: January 2024

Benggang is a type of erosion landform that commonly occurs in the southern regions of China, posing significant threats to local farmland and human safety. Object-based classification (OBC) can be applied with high-resolution (HR) remote sensing images for detecting Benggang areas on a large spatial scale, offering essential data for aiding in the remediation efforts for these areas. Nevertheless, traditional image segmentation methods may face challenges in accurately delineating Benggang areas. Consequently, the extraction of spatial and textural features from these areas can be susceptible to inaccuracies, potentially compromising the detection accuracy of Benggang areas. To address this issue, this study proposed a novel approach that integrates Segment Anything Model (SAM) and OBC for Benggang detection. The SAM was used to segment HR remote sensing imagery to delineate the boundaries of Benggang areas. After that, the OBC was employed to identify Benggang areas based on spectral, geometrical, and textural features. In comparison to traditional pixel-based classification using the random forest classifier (RFC-PBC) and OBC based on the multi-resolution segmentation (MRS-OBC), the proposed SAM-OBC exhibited superior performance, achieving a detection accuracy of 85.46%, a false alarm rate of 2.19%, and an overall accuracy of 96.48%. The feature importance analysis conducted with random forests highlighted the GLDV Entropy, GLDV Angular Second Moment (ASM), and GLCM ASM as the most pivotal features for the identification of Benggang areas. Due to its inability to extract and utilize these textural features, the PBC yielded suboptimal results compared to both the SAM-OBC and MRS-OBC. In contrast to the MRS, the SAM demonstrated superior capabilities in the precise delineation of Benggang areas, ensuring the extraction of accurate textural and spatial features. As a result, the SAM-OBC significantly enhanced detection accuracy by 34.12% and reduced the false alarm rate by 2.06% compared to the MRS-OBC. The results indicate that the SAM-OBC performs well in Benggang detection, holding significant implications for the monitoring and remediation of Benggang areas.
Efficient Human Violence Recognition for Surveillance in Real Time
Authors: Huillcen Baca Herwin Alayn , Palomino Valdivia Flor de Luz , Gutierrez Caceres Juan Carlos
Published: January 2024

Human violence recognition is an area of great interest in the scientific community due to its broad spectrum of applications, especially in video surveillance systems, because detecting violence in real time can prevent criminal acts and save lives. The majority of existing proposals and studies focus on result precision, neglecting efficiency and practical implementations. Thus, in this work, we propose a model that is effective and efficient in recognizing human violence in real time. The proposed model consists of three modules: the Spatial Motion Extractor (SME) module, which extracts regions of interest from a frame; the Short Temporal Extractor (STE) module, which extracts temporal characteristics of rapid movements; and the Global Temporal Extractor (GTE) module, which is responsible for identifying long-lasting temporal features and fine-tuning the model. The proposal was evaluated for its efficiency, effectiveness, and ability to operate in real time. The results obtained on the Hockey, Movies, and RWF-2000 datasets demonstrated that this approach is highly efficient compared to various alternatives. In addition, the VioPeru dataset was created, which contains violent and non-violent videos captured by real video surveillance cameras in Peru, to validate the real-time applicability of the model. When tested on this dataset, the effectiveness of our model was superior to the best existing models.
Optimal Control for a Superconducting Hybrid MagLev Transport System with Multirate Multisensors in a Smart Factory
Authors: Kim Changhyun
Published: January 2024

Recently, magnetic levitation systems have been applied and studied in various industrial fields. In particular, in-tracktype magnetic levitation conveyor systems are actively studied since they can effectively minimize electromagnetic effects in processes that require a highly clean environment. In this type of system, diverse and multiple sensors are structurally required so that the control performance of an integrated system is primarily governed by the slowest measuring sensor. This paper proposes a multisensor fusion compensator to integrate the outputs obtained from various sensors into one output with the single fastest time rate. Since the state of the system is estimated at a fast time rate, the optimal controller also guarantees fast performance and stability. The computation of electromagnetic fields and the control performance of the considered superconducting hybrid system were analyzed using a computer simulation based on finite element methods.
A Label-Free Optical Biosensor Based on an Array of Microring Resonators for the Detection of Human Serum Albumin
Authors: Chen Xin , Li Mingyu , Wang Zhaoyu , Zhao Kaihao , Gu Jiamei , Li Qiushun , He Jian-Jun
Published: January 2024

We introduced a label-free sensing system based on an array of microring resonators (MRRs) which was successfully employed for human serum albumin (HSA) detection. The sensing-ring surface was functionalized to immobilize anti-HSA, facilitating HSA binding. Our refractive index sensing system demonstrates high sensitivity at 168 nm/RIU and a low limit of detection (LOD) of 63.54 ng/mL, closely comparable to current HSA detection methods. These findings confirm the potential of MRRs as biocompatible sensors for HSA detection. This system holds great promise as an innovative platform for the detection of HSA, carrying significant importance in medical diagnostics.