bluuebunny/crossref_metadata_2025 huggingface dataset:
Acylation of Oleanolic Acid Oximes Effectively Improves Cytotoxic Activity in In Vitro Studies
Authors: Bednarczyk-Cwynar Barbara , Ruszkowski Piotr
Published: January 2024

(1) Background: The aim of the presented work was to obtain a set of oleanolic acid derivatives with a high level of anticancer activity and a low level of toxicity by applying an economic method. Three types of oleanolic acid derivatives were obtained: (i) derivatives of methyl oleanonate oxime, (ii) derivatives of methyl oleanonate oxime with an additional 11-oxo function, and (iii) derivatives of morpholide of oleanonic acid oxime. (2) Methods: The above oximes were acylated with aliphatic or aromatic carboxylic acid. The newly obtained compounds were subjected to ADMETox analysis and were also tested for cytotoxicity activity on the HeLa, KB, MCF-7, A-549, and HDF cell lines with the MTT assay. (3) Results: Among the tested acylated oximes of oleanolic acid, some derivatives, particularly those with two nitro groups attached to the aromatic ring, proved to be the most potent cytotoxic agents. These triterpene derivatives significantly inhibited the growth of the HeLa, KB, MCF-7, and A-549 cancer cell lines in micromolar concentrations. (4) Conclusions: The introduction of different moieties, particularly the 3,5-dinitro group, resulted in the synthesis of highly potent cytotoxic agents with favorable SI and ADMETox parameters.
Generalized One-Dimensional Periodic Potential Wells Tending to the Dirac Delta Potential
Authors: Mendoza-Villa F. , Ramos-Guivar Juan A. , Espinoza-Bernardo R. M.
Published: January 2024

The solution of a quantum periodic potential in solid state physics is relevant because one can understand how electrons behave in a corresponding crystal. In this paper, the analytical solution of the energy formulation for a one-dimensional periodic potential that meets certain boundary conditions is developed in a didactic and detailed way. In turn, the group speed and effective mass are also calculated from the transcendental energy equation of a potential V=V(x). From this, a comparison is made with periodic potentials with known analytical solutions, such as the Dirac delta, as well as rectangular and triangular potentials. Finally, some limits are proposed in which these periodic potentials of the form V=V(x) approach the periodic Dirac delta potential of positive intensity. Therefore, the calculations described in this paper can be used as the basis for more-complex one-dimensional potentials and related simulations.
Uncovering Novel QTLs and Candidate Genes for Salt Tolerance at the Bud Burst Stage in Rice through Genome-Wide Association Study
Authors: Li Caijing , Lu Changsheng , Yang Mengmeng , Wu Guangliang , Nyasulu Mvuyeni , He Haohua , He Xiaopeng , Bian Jianmin
Published: January 2024

Salt stress is one of the most important factors limiting rice growth and yield increase. Salt tolerance of rice at the bud burst (STB) stage determines whether germinated seeds can grow normally under salt stress, which is very important for direct seeding. However, reports on quantitative trait loci (QTLs) and candidate genes for STB in rice are very limited. In this study, a natural population of 130 indica and 81 japonica rice accessions was used to identify STB-related QTLs and candidate genes using a genome-wide association study (GWAS). Nine QTLs, including five for relative shoot length (RSL), two for relative root length (RRL), and two for relative root number (RRN), were identified. Five of these STB-related QTLs are located at the same site as the characterized salt tolerance genes, such as OsMDH1, OsSRFP1, and OsCDPK7. However, an important QTL related to RSL, qRSL1-2, has not been previously identified and was detected on chromosome 1. The candidate region for qRSL1-2 was identified by linkage disequilibrium analysis, 18 genes were found to have altered expression levels under salt stress through the RNA-seq database, and 10 of them were found to be highly expressed in the shoot. It was also found that, eight candidate genes (LOC_Os01g62980, LOC_Os01g63190, LOC_Os01g63230, LOC_Os01g63280, LOC_Os01g63400, LOC_Os01g63460, and LOC_Os01g63580) for qRSL1-2 carry different haplotypes between indica and japonica rice, which exactly corresponds to the significant difference in RSL values between indica and japonica rice in this study. Most of the accessions with elite haplotypes were indica rice, which had higher RSL values. These genes with indica-japonica specific haplotypes were identified as candidate genes. Rice accessions with elite haplotypes could be used as important resources for direct seeding. This study also provides new insights into the genetic mechanism of STB.
Juvenile Plant–Microbe Interactions Modulate the Adaptation and Response of Forest Seedlings to Rapid Climate Change
Authors: Sanhueza Tedy , Hernández Ionel , Sagredo-Sáez Cristiane , Villanueva-Guerrero Angela , Alvarado Roxana , Mujica Maria Isabel , Fuentes-Quiroz Alejandra , Menendez Esther , Jorquera-Fontena Emilio , Valadares Rafael Borges da Silva , Herrera Héctor
Published: January 2024

The negative impacts of climate change on native forest ecosystems have created challenging conditions for the sustainability of natural forest regeneration. These challenges arise primarily from abiotic stresses that affect the early stages of forest tree development. While there is extensive evidence on the diversity of juvenile microbial symbioses in agricultural and fruit crops, there is a notable lack of reports on native forest plants. This review aims to summarize the critical studies conducted on the diversity of juvenile plant–microbe interactions in forest plants and to highlight the main benefits of beneficial microorganisms in overcoming environmental stresses such as drought, high and low temperatures, metal(loid) toxicity, nutrient deficiency, and salinity. The reviewed studies have consistently demonstrated the positive effects of juvenile plant–microbiota interactions and have highlighted the potential beneficial attributes to improve plantlet development. In addition, this review discusses the beneficial attributes of managing juvenile plant–microbiota symbiosis in the context of native forest restoration, including its impact on plant responses to phytopathogens, promotion of nutrient uptake, facilitation of seedling adaptation, resource exchange through shared hyphal networks, stimulation of native soil microbial communities, and modulation of gene and protein expression to enhance adaptation to adverse environmental conditions.
Determination of the Toxic Effects of Heavy Metals on the Morpho-Anatomical Responses of the Leaf of Typha latifolia as a Biomonitoring Tool
Authors: Mamine Nedjma , Grara Nedjoud , Khaldi Fadila , Maresca Viviana , Aouaichia Khaoula , Basile Adriana
Published: January 2024

Typha latifolia leaves act as sensitive barometers for trace heavy metal pollution, as revealed by their pronounced anatomical responses in a constructed wetland. Monthly water samples and Typha latifolia leaf tissue were collected over three consecutive months in 2018 from the Burgas Lake wetlands (Taoura), northeast Algeria. While physical and chemical parameters improved after treatment, atomic absorption spectrometry (Perkin Elmer A Analyst 800 AAS) detected persistent trace levels of cadmium, chromium, and lead in both the treated water and leaf tissue, highlighting the need for continued phytoremediation efforts. Microscopic examination of leaf tissue exposed to these metals revealed distinct anatomical adaptations, including shrunken vascular bundles, altered cell shapes, and stomatal closure. These findings underscore Typha latifolia’s effectiveness in accumulating heavy metals and its potential as a highly sensitive biomonitor for persistent pollution in lake ecosystems.
Sesquiterpene Lactones Isolated from Centaurea cineraria L. subsp. cineraria Inhibit the Radicle Growth of Broomrape Weeds
Authors: Zorrilla Jesús G. , Innangi Michele , Cala Peralta Antonio , Soriano Gabriele , Russo Maria Teresa , Masi Marco , Fernández-Aparicio Mónica , Cimmino Alessio
Published: January 2024

The plant Centaurea cineraria L. subsp. cineraria has been investigated as a potential source of inhibitors of broomrape radicle growth. The latter are weeds that pose a threat to agriculture and for which there are few methods available for the control of infestations. Four sesquiterpene lactones have been isolated from C. cineraria L. subsp. cineraria aerial parts and identified as isocnicin, cnicin, salonitenolide, and 11β,13-dihydrosalonitenolide using spectroscopic, spectrometric, and optical methods. Salonitenolide and 11β,13-dihydrosalonitenolide have been isolated for the first time from this plant. Tested at 1.0–0.1 mM against the broomrape species Phelipanche ramosa, Orobanche minor, Orobanche crenata, and Orobanche cumana, isocnicin, cnicin, and salonitenolide demonstrated remarkable inhibitory activity (over 80% in most of the cases) at the highest concentrations. Structure-activity relationship conclusions indicated the significance of the α,β-unsaturated lactone ring. In addition, the synthetic acetylated derivative of salonitenolide showed the strongest activity among all compounds tested, with inhibitions close to 100% at different concentrations, which has been related to a different lipophilicity and the absence of H-bond donor atoms in its structure. Neither the extracts nor the compounds exhibited the stimulating activity of broomrape germination (induction of suicidal germination). These findings highlight the potential of C. cineraria to produce bioactive compounds for managing parasitic weeds and prompt further studies on its sesquiterpene lactones as tools in developing natural product-based herbicides.
Effect of Collector Rotational Speed on the Morphology and Structure of Solution Blow Spun Polylactic Acid (PLA)
Authors: Nikolić Nataša , Olmos Dania , Kramar Ana , González-Benito Javier
Published: January 2024

Apart from structure and composition, morphology plays a significant role in influencing the performance of materials in terms of both bulk and surface behavior. In this work, polylactic acid (PLA) constituted by submicrometric fibers is prepared. Using a modified electrospinning (ES) device to carry out solution blow spinning (SBS), the fibrillar morphology is modified, with the aim to induce variations in the properties of the material. The modification of the ES device consists of the incorporation of a source of pressurized gas (air) and a 3D-printed nozzle of our own design. For this work, the morphology of the PLA submicrometric fibers is modified by varying the rotational speed of the collector in order to understand its influence on different properties and, consequently, on the performance of the material. The rotational speed of a cylindrical collector (250, 500, 1000 and 2000 rpm) is considered as variable for changing the morphology. Morphological study of the materials was performed using scanning electron microscopy and image analysis carried out with ImageJ 1.54f software. Besides a morphology study, structural characterization by Fourier transformed infrared spectroscopy using attenuated total reflectance of prepared materials is carried out. Finally, the morphology and structure of produced PLA fibrous mats were correlated with the analysis of mechanical properties, wettability behavior and adhesion of DH5-α E. coli bacteria. It is of interest to highlight how small morphological and chemical structure variations can lead to important changes in materials’ performance. These changes include, for example, those above 30% in some mechanical parameters and clear variations in bacterial adhesion capacity.
Phase Morphology and Mechanical Properties of Super-Tough PLLA/TPE/EMA-GMA Ternary Blends
Authors: Boruvka Martin , Base Roman , Novak Jan , Brdlik Pavel , Behalek Lubos , Ngaowthong Chakaphan
Published: January 2024

The inherent brittleness of poly(lactic acid) (PLA) limits its use in a wider range of applications that require plastic deformation at higher stress levels. To overcome this, a series of poly(l-lactic acid) (PLLA)/biodegradable thermoplastic polyester elastomer (TPE) blends and their ternary blends with an ethylene-methyl acrylate-glycidyl methacrylate (EMA-GMA) copolymer as a compatibilizer were prepared via melt blending to improve the poor impact strength and low ductility of PLAs. The thermal behavior, crystallinity, and miscibility of the binary and ternary blends were analyzed by differential scanning calorimetry (DSC). Tensile tests revealed a brittle–ductile transition when the binary PLLA/20TPE blend was compatibilized by 8.6 wt. % EMA-GMA, and the elongation at break increased from 10.9% to 227%. The “super tough” behavior of the PLLA/30TPE/12.9EMA-GMA ternary blend with the incomplete break and notched impact strength of 89.2 kJ∙m−2 was observed at an ambient temperature (23 °C). In addition, unnotched PLLA/40TPE samples showed a tremendous improvement in crack initiation resistance at sub-zero test conditions (−40 °C) with an impact strength of 178.1 kJ∙m−2. Morphological observation by scanning electron microscopy (SEM) indicates that EMA-GMA is preferentially located at the PLLA/TPE interphase, where it is partially incorporated into the matrix and partially encapsulates the TPE. The excellent combination of good interfacial adhesion, debonding cavitation, and subsequent matrix shear yielding worked synergistically with the phase transition from sea–island to co-continuous morphology to form an interesting super-toughening mechanism.
Enhanced Mechanical Properties of PUMA/SiO2 Ceramic Composites via Digital Light Processing
Authors: Kang Jiwan , Park Seong Hyeon , Park Keun
Published: January 2024

This study aims to enhance the mechanical properties of additively manufactured polymer parts by incorporating ceramic particles (SiO2) into diluted urethane methacrylate (UDMA) photopolymer resin using digital light processing (DLP) technology. The resulting PUMA/SiO2 composites, featuring varying SiO2 contents (16.7, 28.5, and 37.5 wt%) and processed under different conditions, underwent a comprehensive series of mechanical, thermal, and chemical tests. Hardness tests showed that composites with 37.5 wt% SiO2 demonstrated superior hardness with low sensitivity to processing conditions. Bending tests indicated that elevated vat temperatures tended to degrade flexural properties, yet this degradation was mitigated in the case of the 37.5 wt% SiO2 composition. Tensile tests revealed a transition from viscoelastic to linear elastic behaviors with increasing SiO2 content, with high tensile strength sustained at low vat temperatures (<35 °C) when the SiO2 content exceeded 28.5 wt%. Thermogravimetric analysis supported these findings, indicating that increased SiO2 content ensured a more uniform dispersion, enhancing mechanical properties consequently. Thermal tests showed augmented thermal conductivity and diffusivity with reduced specific heat in SiO2-inclusive composites. This study provides guidelines for optimal PUMA/SiO2 composite utilization that emphasizes high SiO2 content and low vat temperature, offering comprehensive insights for high-performance ceramic composite fabrication in functional applications.
Effect of Superabsorbent Polymer (SAP) Size on Microstructure and Compressive Strength of Concrete
Authors: Niu Xiaobo , Zhang Yile , Elakneswaran Yogarajah , Sasaki Miyu , Takayama Takeshi , Kawai Hajime
Published: January 2024

Superabsorbent polymers (SAPs) are hydrophilic, polymeric network materials renowned for their ability to enhance various properties of cementitious materials. This investigation examines the impact of SAP size on the hydration degree, porosity, and compressive strength of cement pastes and concrete under diverse curing conditions and ageing periods. The findings reveal that SAP addition stimulates the hydration of the C2S phase, particularly during the early curing stages, thereby favouring early strength development. However, the effect of SAPs on hydration promotion diminishes as their size increases. Conversely, the size of SAPs affects the hydration range of their action, and the 400 µm SAP demonstrates the most extensive range of hydration enhancement, reaching up to 105 µm. Additionally, SAPs effectively reduce porosity in small pores (4 nm–10 μm), with 200 μm and 400 μm SAPs exhibiting the highest efficacy. While analysing the effects of SAPs on larger pores (>10 μm), the results show that although larger SAPs result in larger average porosity, the total porosity is effectively reduced, particularly in samples incorporating 400 μm SAP. The compressive strength of cement paste, even after 28 days, is slightly reduced following the introduction of SAPs. However, the strength of concrete, due to the naturally occurring pores eliminating the negative effects of the pores produced by SAPs, is significantly increased following the introduction of SAPs, especially 400 µm SAP.
Magnesium Hydroxide as a Versatile Nanofiller for 3D-Printed PLA Bone Scaffolds
Authors: Guo Wang , Bu Wenlang , Mao Yufeng , Wang Enyu , Yang Yanjuan , Liu Chao , Guo Feng , Mai Huaming , You Hui , Long Yu
Published: January 2024

Polylactic acid (PLA) has attracted much attention in bone tissue engineering due to its good biocompatibility and processability, but it still faces problems such as a slow degradation rate, acidic degradation product, weak biomineralization ability, and poor cell response, which limits its wider application in developing bone scaffolds. In this study, Mg(OH)2 nanoparticles were employed as a versatile nanofiller for developing PLA/Mg(OH)2 composite bone scaffolds using fused deposition modeling (FDM) 3D printing technology, and its mechanical, degradation, and biological properties were evaluated. The mechanical tests revealed that a 5 wt% addition of Mg(OH)2 improved the tensile and compressive strengths of the PLA scaffold by 20.50% and 63.97%, respectively. The soaking experiment in phosphate buffered solution (PBS) revealed that the alkaline degradation products of Mg(OH)2 neutralized the acidic degradation products of PLA, thus accelerating the degradation of PLA. The weight loss rate of the PLA/20Mg(OH)2 scaffold (15.40%) was significantly higher than that of PLA (0.15%) on day 28. Meanwhile, the composite scaffolds showed long-term Mg2+ release for more than 28 days. The simulated body fluid (SBF) immersion experiment indicated that Mg(OH)2 promoted the deposition of apatite and improved the biomineralization of PLA scaffolds. The cell culture of bone marrow mesenchymal stem cells (BMSCs) indicated that adding 5 wt% Mg(OH)2 effectively improved cell responses, including adhesion, proliferation, and osteogenic differentiation, due to the release of Mg2+. This study suggests that Mg(OH)2 can simultaneously address various issues related to polymer scaffolds, including degradation, mechanical properties, and cell interaction, having promising applications in tissue engineering.
Stochastic Modeling and Simulation of Filament Aggregation in Alzheimer’s Disease
Authors: Ojha Vaghawan Prasad , Yarahmadian Shantia , Om Madhav
Published: January 2024

Alzheimer’s disease has been a serious problem for humankind, one without a promising cure for a long time now, and researchers around the world have been working to better understand this disease mathematically, biologically and computationally so that a better cure can be developed and finally humanity can get some relief from this disease. In this study, we try to understand the progression of Alzheimer’s disease by modeling the progression of amyloid-beta aggregation, leading to the formation of filaments using the stochastic method. In a noble approach, we treat the progression of filaments as a random chemical reaction process and apply the Monte Carlo simulation of the kinetics to simulate the progression of filaments of lengths up to 8. By modeling the progression of disease as a progression of filaments and treating this process as a stochastic process, we aim to understand the inherent randomness and complex spatial–temporal features and the convergence of filament propagation process. We also analyze different reaction events and observe the events such as primary as well as secondary elongation, aggregations and fragmentation using different propensities for different possible reactions. We also introduce the random switching of the propensity at random time, which further changes the convergence of the overall dynamics. Our findings show that the stochastic modeling can be utilized to understand the progression of amyloid-beta aggregation, which eventually leads to larger plaques and the development of Alzheimer disease in the patients. This method can be generalized for protein aggregation in any disease, which includes both the primary and secondary aggregation and fragmentation of proteins.
ADAMS Simulation and HHT Feature Extraction Method for Bearing Faults of Coal Shearer
Authors: Qin Yi-Fan , Fu Xiang , Li Xiao-Kun , Li Hao-Jie
Published: January 2024

Aiming at the problem of difficult fault diagnosis work caused by the difficulty of data acquisition of the bearing in the traction part of a coal mining machine, a method of ADAMS simulation and HHT feature extraction of the bearing fault of a coal mining machine is proposed. First of all, take the traction section bearing as the research object, use the virtual prototype in the establishment of the healthy state of coal mining machine traction section model based on the establishment of the bearing inner ring fault, rolling body fault, outer ring fault of the coal mining machine traction section dynamics model, and then after the EMD decomposition, each IMF component of the Hilbert transform, to obtain the signal in the time-frequency plane of the time-frequency joint characteristics, to get the HHT marginal spectra and to different Under different working conditions, the bearing vibration signal features are mined by quantitative feature extraction. Finally, a variety of mainstream machine learning algorithms are introduced to classify the features, and the results show that the feature extraction method in this paper is universal and provides valuable theoretical support and technical guidance for the field application of coal mining machine-bearing fault diagnosis.
A Survey of Machine Learning Approaches for Mobile Robot Control
Authors: Rybczak Monika , Popowniak Natalia , Lazarowska Agnieszka
Published: January 2024

Machine learning (ML) is a branch of artificial intelligence that has been developing at a dynamic pace in recent years. ML is also linked with Big Data, which are huge datasets that need special tools and approaches to process them. ML algorithms make use of data to learn how to perform specific tasks or make appropriate decisions. This paper presents a comprehensive survey of recent ML approaches that have been applied to the task of mobile robot control, and they are divided into the following: supervised learning, unsupervised learning, and reinforcement learning. The distinction of ML methods applied to wheeled mobile robots and to walking robots is also presented in the paper. The strengths and weaknesses of the compared methods are formulated, and future prospects are proposed. The results of the carried out literature review enable one to state the ML methods that have been applied to different tasks, such as the following: position estimation, environment mapping, SLAM, terrain classification, obstacle avoidance, path following, learning to walk, and multirobot coordination. The survey allowed us to associate the most commonly used ML algorithms with mobile robotic tasks. There still exist many open questions and challenges such as the following: complex ML algorithms and limited computational resources on board a mobile robot; decision making and motion control in real time; the adaptability of the algorithms to changing environments; the acquisition of large volumes of valuable data; and the assurance of safety and reliability of a robot’s operation. The development of ML algorithms for nature-inspired walking robots also seems to be a challenging research issue as there exists a very limited amount of such solutions in the recent literature.
A Focusing Method of Buildings for Airborne Circular SAR
Authors: Feng Dong , An Daoxiang , Wang Jian , Chen Leping , Huang Xiaotao
Published: January 2024

Airborne circular synthetic aperture radar (CSAR) can realize high-resolution imaging of the scene over 360 degrees azimuth angle variation. Aiming at the problem of focusing of buildings for the airborne CSAR, this paper first analyzes the phase errors of CSAR buildings focusing in detail, and the analytic relationship between the scatterer height and azimuth focusing quality is deduced. Then, a focusing method of CSAR buildings based on the back projection algorithm is proposed. This method adopts the processing strategy of multi-layers imaging, and it is able to improve azimuth focusing quality of the buildings which have large height dimension. The proposed method is especially suitable for the high-resolution imaging and monitoring of the urban site with high-rise buildings in the airborne CSAR scenario. The correctness of the theoretical analysis and the validity of the proposed method are verified by using both simulation results and Ku-band airborne CSAR real data processing results.
Improved Main Lobe Cancellation Method for Suppression Directional Noise in HFSWR Systems
Authors: Xiao Dezhu , Zhang Xin , Yang Qiang , Li Jiaming
Published: January 2024

High frequency surface wave radar (HFSWR) has been successfully developed for early warning, especially for vessel target detection. However, the system’s performance is consistently constrained by external environmental noise, particularly directional noise, which presents a new problem for HFSWR. Anisotropic directional noise has complex behavior, and its noise level is generally increased by 10 to 15 dB compared to traditional noise floor level. Suppressing varying directional noise and exploring obscured targets are challenging tasks for HFSWR. In this paper, a novel algorithm based on angle-Doppler joint multi-eigenvector synthesis, which considers the angle-Doppler map of radar echoes, is adopted to analyze the characteristics of the directional noise. Given the measured data set, we first analyze the directional noise-spatial correlation. Then, an algorithm based on sliding main lobe cancellation (SL-MLC) based on a sliding single-notch space filter (SSNSF) is proposed to block target components and get training data that contains precise directional noise information. Finally, the method is examined by measured data, and the results indicate the method has better performance for directional noise than the compared method.
Mountain Vegetation Classification Method Based on Multi-Channel Semantic Segmentation Model
Authors: Wang Baoguo , Yao Yonghui
Published: January 2024

With the development of satellite remote sensing technology, a substantial quantity of remote sensing data can be obtained every day, but the ability to extract information from these data remains poor, especially regarding intelligent extraction models for vegetation information in mountainous areas. Because the features of remote sensing images (such as spectral, textural and geometric features) change with changes in illumination, viewing angle, scale and spectrum, it is difficult for a remote sensing intelligent interpretation model with a single data source as input to meet the requirements of engineering or large-scale vegetation information extraction and updating. The effective use multi-source, multi-resolution and multi-type data for remote sensing classification is still a challenge. The objective of this study is to develop a highly intelligent and generalizable classification model of mountain vegetation utilizing multi-source remote sensing data to achieve accurate vegetation extraction. Therefore, a multi-channel semantic segmentation model based on deep learning, FCN-ResNet, is proposed to integrate the features and textures of multi-source, multi-resolution and multi-temporal remote sensing data, thereby enhancing the differentiation of different mountain vegetation types by capturing their characteristics and dynamic changes. In addition, several sets of ablation experiments are designed to investigate the effectiveness of the model. The method is validated on Mt. Taibai (part of the Qinling-Daba Mountains), and the pixel accuracy (PA) of vegetation classification reaches 85.8%. The results show that the proposed multi-channel semantic segmentation model can effectively discriminate different vegetation types and has good intelligence and generalization ability in different mountainous areas with similar vegetation distributions. The multi-channel semantic segmentation model can be used for the rapid updating of vegetation type maps in mountainous areas.
Design of a Deployable Broadband Mesh Reflector Antenna for a SIGINT Satellite System Considering Surface Shape Deformation
Authors: Im Changhyeon , Seo Wongu , Park Seulgi , Kim Kihun , Park Sungkyun , Choo Hosung
Published: January 2024

In this paper, we propose a deployable broadband mesh reflector antenna for use in signals intelligence (SIGINT) satellite systems, considering performance degradation due to shape deformation. To maximize gain by increasing the diameter of the reflector while reducing the weight of the antenna, the reflector of the antenna is designed using lightweight silver-coated Teflon mesh. The mesh reflectors are typically expanded by tension to maintain their parabolic structure; thus, shape deformation cannot be avoided. This shape deformation results in shape differences between the surface of the mesh reflector and the ideal parabolic reflector, thus resulting in the degradation of the performance of the mesh reflector antenna. To observe this degradation, we analyze antenna performance according to the number of arms, the number of joints, the feed distance, and the distance from the reflector center to each joint. The performance of the mesh reflector antenna is examined using an effective lossy conducting surface (ELCS) that has the same reflectivity as the silver-coated Teflon mesh to reduce simulation time and computing resources. The designed silver-coated Teflon mesh reflector and the double-ridged feed antenna are fabricated, and the bore-sight gain is measured using the three-antenna method. The measured bore-sight gain of the proposed antenna is 31.6 dBi at 10 GHz, and the measured and simulated results show an average difference of 3.28 dB from 2 GHz to 18 GHz. The proposed deployable mesh reflector antenna can be used in a variety of applications where small stowed volume is required for mobility, such as mobile high-gain antennas as well as satellite antenna systems. Through this study, we demonstrate that shape deformation of the mesh reflector surface significantly affects the performance of reflector antennas.
A Deep Learning Approach for Autonomous Compression Damage Identification in Fiber-Reinforced Concrete Using Piezoelectric Lead Zirconate Titanate Transducers
Authors: Sapidis George M. , Kansizoglou Ioannis , Naoum Maria C. , Papadopoulos Nikos A. , Chalioris Constantin E.
Published: January 2024

Effective damage identification is paramount to evaluating safety conditions and preventing catastrophic failures of concrete structures. Although various methods have been introduced in the literature, developing robust and reliable structural health monitoring (SHM) procedures remains an open research challenge. This study proposes a new approach utilizing a 1-D convolution neural network to identify the formation of cracks from the raw electromechanical impedance (EMI) signature of externally bonded piezoelectric lead zirconate titanate (PZT) transducers. Externally bonded PZT transducers were used to determine the EMI signature of fiber-reinforced concrete specimens subjected to monotonous and repeatable compression loading. A leave-one-specimen-out cross-validation scenario was adopted for the proposed SHM approach for a stricter and more realistic validation procedure. The experimental study and the obtained results clearly demonstrate the capacity of the introduced approach to provide autonomous and reliable damage identification in a PZT-enabled SHM system, with a mean accuracy of 95.24% and a standard deviation of 5.64%.
RFID Adaptive Parallel Response Collision Tree Algorithm Based on Lock-Bit
Authors: Luo Xuan , Jia Xiaolin , Gu Yajun
Published: January 2024

This paper proposes the Lock-Position-Based RFID Adaptive Parallel Collision Tree (LAPCT) algorithm to address the issues of excessive time slots required in the identification process of collision tree algorithms for multiple tags and the high communication complexity between the reader and multiple tags. The LAPCT algorithm adopts a single-query multiple-response mechanism and dynamically divides the response sub-cycle numbers in the identification cycle based on an adaptive strategy. It uses Manchester encoding to lock collision positions and generate a common query prefix, effectively reducing the number of reader queries. This reduction in queries decreases the total number of required time slots and transmitted bits during the reader–tag communication process, thereby improving the efficiency of multiple tag recognition. Theoretical and simulation experiments demonstrate that compared to similar algorithms, the LAPCT algorithm achieves a maximum reduction of 37% in total time slots required, a maximum improvement of 30% in recognition efficiency, and a maximum reduction of 90% in communication complexity. Furthermore, with an increase in the number of tags, the performance advantages of the LAPCT algorithm become more pronounced, making it suitable for large-scale tag scenarios.
Robust Cubature Kalman Filter for Moving-Target Tracking with Missing Measurements
Authors: Sahl Samer , Song Enbin , Niu Dunbiao
Published: January 2024

Handling the challenge of missing measurements in nonlinear systems is a difficult problem in various scientific and engineering fields. Missing measurements, which can arise from technical faults during observation, diffusion channel shrinking, or the loss of specific metrics, can bring many challenges when estimating the state of nonlinear systems. To tackle this issue, this paper proposes a technique that utilizes a robust cubature Kalman filter (RCKF) by integrating Huber’s M-estimation theory with the standard conventional cubature Kalman filter (CKF). Although a CKF is often used for solving nonlinear filtering problems, its effectiveness might be limited due to a lack of knowledge regarding the nonlinear model of the state and noise-related statistical information. In contrast, the RCKF demonstrates an ability to mitigate performance degradation and discretization issues related to track curves by leveraging covariance matrix predictions for state estimation and output control amidst dynamic disruption errors—even when noise statistics deviate from prior assumptions. The performance of extended Kalman filters (EKFs), unscented Kalman filters (UKFs), CKFs, and RCKFs was compared and evaluated using two numerical examples involving the Univariate Non-stationary Growth Model (UNGM) and bearing-only tracking (BOT). The numerical experiments demonstrated that the RCKF outperformed the EKF, EnKF, and CKF in effectively handling anomaly errors. Specifically, in the UNGM example, the RCKF achieved a significantly lower ARMSE (4.83) and ANCI (3.27)—similar outcomes were observed in the BOT example.
The Spectrum of Global Electron Content: A New Potential Indicator of Space Weather Activity
Authors: Aroca-Farrerons Josep Maria , Hernández-Pajares Manuel , Lyu Haixia , Roma-Dollase David , Orus-Perez Raul , García-Rigo Alberto , Graffigna Victoria , Olivares-Pulido Germán , Monte-Moreno Enric , Yang Heng , Liu Qi
Published: January 2024

The time evolution of the total number of free electrons in the Earth’s ionosphere, i.e., the Global Electron Content (GEC), during more than two solar cycles is analyzed in this work. The GEC time series has been extracted from the Global Ionospheric Maps (GIMs) of Vertical Total Electron Content (VTEC) estimated by UPC-IonSAT with TOMION-v1 software from global GPS measurements since the end of 1996. A dual-layer voxel-based tomographic model solved with a forward Kalman scalar filter, from dual-frequency carrier GPS data only, provides the so-called UQRG GIM after VTEC kriging interpolation, with a resolution of 15 min in time, 5° in longitude and 2.5° in latitude. UQRG is one of the best behaving GIMs in the International GNSS Service (IGS).In this context, the potential application of the GEC spectrum evolution as a potential space weather index is discussed and demonstrated.
Human Pose Estimation Based on Efficient and Lightweight High-Resolution Network (EL-HRNet)
Authors: Li Rui , Yan An , Yang Shiqiang , He Duo , Zeng Xin , Liu Hongyan
Published: January 2024

As an important direction in computer vision, human pose estimation has received extensive attention in recent years. A High-Resolution Network (HRNet) can achieve effective estimation results as a classical human pose estimation method. However, the complex structure of the model is not conducive to deployment under limited computer resources. Therefore, an improved Efficient and Lightweight HRNet (EL-HRNet) model is proposed. In detail, point-wise and grouped convolutions were used to construct a lightweight residual module, replacing the original 3 × 3 module to reduce the parameters. To compensate for the information loss caused by the network’s lightweight nature, the Convolutional Block Attention Module (CBAM) is introduced after the new lightweight residual module to construct the Lightweight Attention Basicblock (LA-Basicblock) module to achieve high-precision human pose estimation. To verify the effectiveness of the proposed EL-HRNet, experiments were carried out using the COCO2017 and MPII datasets. The experimental results show that the EL-HRNet model requires only 5 million parameters and 2.0 GFlops calculations and achieves an AP score of 67.1% on the COCO2017 validation set. In addition, PCKh@0.5mean is 87.7% on the MPII validation set, and EL-HRNet shows a good balance between model complexity and human pose estimation accuracy.
Quantitation of the Surface Shortwave and Longwave Radiative Effect of Dust with an Integrated System: A Case Study at Xianghe
Authors: Liu Mengqi , Shi Hongrong , Song Jingjing , Fu Disong
Published: January 2024

Aerosols play a crucial role in the surface radiative budget by absorbing and scattering both shortwave and longwave radiation. While most aerosol types exhibit a relatively minor longwave radiative forcing when compared to their shortwave counterparts, dust aerosols stand out for their substantial longwave radiative forcing. In this study, radiometers, a sun photometer, a microwave radiometer and the parameterization scheme for clear-sky radiation estimation were integrated to investigate the radiative properties of aerosols. During an event in Xianghe, North China Plain, from 25 April to 27 April 2018, both the composition (anthropogenic aerosol and dust) and the aerosol optical depth (AOD, ranging from 0.3 to 1.5) changed considerably. A notable shortwave aerosol radiative effect (SARE) was revealed by the integrated system (reaching its peak at −131.27 W·m−2 on 26 April 2018), which was primarily attributed to a reduction in direct irradiance caused by anthropogenic aerosols. The SARE became relatively consistent over the three days as the AODs approached similar levels. Conversely, the longwave aerosol radiative effect (LARE) on the dust days ranged from 8.94 to 32.93 W·m−2, significantly surpassing the values measured during the days of anthropogenic aerosol pollution, which ranged from 0.35 to 28.67 W·m−2, despite lower AOD values. The LARE increased with a higher AOD and a lower Ångström exponent (AE), with a lower AE having a more pronounced impact on the LARE than a higher AOD. It was estimated that, on a daily basis, the LARE will offset approximately 25% of the SARE during dust events and during periods of heavy anthropogenic pollution.
A Fault Diagnosis Method for 5G Cellular Networks Based on Knowledge and Data Fusion
Authors: Zhao Lingyu , He Chuhong , Zhu Xiaorong
Published: January 2024

As 5G networks become more complex and heterogeneous, the difficulty of network operation and maintenance forces mobile operators to find new strategies to stay competitive. However, most existing network fault diagnosis methods rely on manual testing and time stacking, which suffer from long optimization cycles and high resource consumption. Therefore, we herein propose a knowledge- and data-fusion-based fault diagnosis algorithm for 5G cellular networks from the perspective of big data and artificial intelligence. The algorithm uses a generative adversarial network (GAN) to expand the data set collected from real network scenarios to balance the number of samples under different network fault categories. In the process of fault diagnosis, a naive Bayesian model (NBM) combined with domain expert knowledge is firstly used to pre-diagnose the expanded data set and generate a topological association graph between the data with solid engineering significance and interpretability. Then, as the pre-diagnostic prior knowledge, the topological association graph is fed into the graph convolutional neural network (GCN) model simultaneously with the training data set for model training. We use a data set collected by Minimization of Drive Tests under real network scenarios in Lu’an City, Anhui Province, in August 2019. The simulation results demonstrate that the algorithm outperforms other traditional models in fault detection and diagnosis tasks, achieving an accuracy of 90.56% and a macro F1 score of 88.41%.
Tuning Nanopores in Tubular Ceramic Nanofiltration Membranes with Atmospheric-Pressure Atomic Layer Deposition: Prospects for Pressure-Based In-Line Monitoring of Pore Narrowing
Authors: Nijboer Michiel , Jan Asif , Chen Mingliang , Batenburg Kevin , Peper Julia , Aarnink Tom , Roozeboom Fred , Kovalgin Alexey , Nijmeijer Arian , Luiten-Olieman Mieke
Published: January 2024

Atomic layer deposition (ALD) is known for its unparalleled control over layer thickness and 3D conformality and could be the future technique of choice to tailor the pore size of ceramic nanofiltration membranes. However, a major challenge in tuning and functionalizing a multichannel ceramic membrane is posed by its large internal pore volume, which needs to be evacuated during ALD cycling. This may require significant energy and processing time. This study presents a new reactor design, operating at atmospheric pressure, that is able to deposit thin layers in the pores of ceramic membranes. In this design, the reactor wall is formed by the industrial tubular ceramic membrane itself, and carrier gas flows are employed to transport the precursor and co-reactant vapors to the reactive surface groups present on the membrane surface. The layer growth for atmospheric-pressure ALD in this case proceeds similarly to that for state-of-the-art vacuum-based ALD. Moreover, for membrane preparation, this new reactor design has three advantages: (i) monolayers are deposited only at the outer pore mouths rather than in the entire bulk of the porous membrane substrate, resulting in reduced flow resistances for liquid permeation; (ii) an in-line gas permeation method was developed to follow the layer growth in the pores during the deposition process, allowing more precise control over the finished membrane; and (iii) expensive vacuum components and cleanroom environment are eliminated. This opens up a new avenue for ceramic membrane development with nano-scale precision using ALD at atmospheric pressure.
Assessing the Conformity of Plasticizer-Free Polymers for Foodstuff Packaging Using Solid Phase Microextraction Coupled to Gas Chromatography/Mass Spectrometry
Authors: De Vietro Nicoletta , Aresta Antonella Maria , Gubitosa Jennifer , Rizzi Vito , Zambonin Carlo
Published: January 2024

Phthalates are the synthetic chemical plasticizers with the most varied uses and are a source of concern due to their toxicity and ubiquity, so much so that even plasticizer-free polymers can contain them as non-intentionally added substances (NIAS). Food packaging is among the materials with the greatest impact. In this study, a simple protocol is proposed for the location and identification of dimethyl phthalate, diethyl phthalate, dipropyl phthalate, and dibutyl phthalate which is applicable to compliance studies of food packaging materials and for the associated risk assessment. Solid phase microextraction gas chromatography/mass spectrometry was used to evaluate the migration of four NIAS from food packaging to release media simulating food substrates. Three plasticizer-free polymers were used: two that were lab-made and based on sodium alginate and a commercial polyethylene film. Linearity ranged from the LOQ to 10 µg/mL; within-day and between-day precision values were between 12.3–25.7% and 21.9–35.8%, respectively; the LOD and LOQ were in the range 0.029–0.073 µg/mL and 0.122–0.970 µg/mL. Migration tests were conducted for different periods of time at room temperature and at 8 °C. Exposure to microwaves (MW) was also evaluated. All packaging materials tested had global migration limits lower than 10 mg/dm2 of material surface.
Changes in the Well-Being of Foreign Language Speaking Migrant Mothers Living in Finland during the Initial Stage of the COVID-19 Pandemic
Authors: Heino Eveliina , Kara Hanna , Nordberg Camilla
Published: January 2024

This article examines changes in the well-being of foreign-language-speaking migrant mothers living in Finland during the initial stage of the COVID-19 pandemic in the spring of 2020. Our data consist of 73 mothers’ responses to a qualitative survey conducted between 18 April and 26 May 2020. In our analysis, we employ the division of well-being into three dimensions: having, loving, and being. According to our results, the participating mothers experienced dramatic changes, such as an increased burden of care and domestic work, difficulties helping children with remote studies, health concerns, a lack of free time, isolation from Finnish society and the inability to travel to their country of origin. Family-centered activities helped the mothers to cope in this situation but also caused strains. Based on our findings, we discuss the vulnerabilities these mothers experienced in relation to language, migration background and gender roles.