bluuebunny/crossref_metadata_2025 huggingface dataset:
Recurrent Urinary Stone Formers: Imaging Assessment and Endoscopic Treatment Strategies: A Systematic Search and Review
Authors: Mavridis Charalampos , Bouchalakis Athanasios , Tsagkaraki Vasiliki , Somani Bhaskar Kumar , Mamoulakis Charalampos , Tokas Theodoros
Published: June 2024

Background/Objectives: Nephrolithiasis is a heterogeneous disease with a high prevalence and recurrence rate. Although there has been much progress regarding the surgical treatment of stones, a standardized follow-up, especially in recurrent stone formers (SFs), has yet to be decided. This fact leads to the overuse of computed tomography (CT) scans and many reoperations in patients, thus increasing their morbidity and the financial burden on the health systems. This review systematically searched the literature for original articles regarding imaging strategies and endoscopic treatment for patients with recurrent urolithiasis, aiming to identify optimal strategies to deal with these patients. Methods: We systematically searched the Medline database (accessed on 1 April 2024) for articles regarding imaging modalities and endoscopic treatment for patients with recurrent urinary tract lithiasis. Results: No specific follow-up or endoscopic treatment strategy exists for patients with recurrent urolithiasis. CT scan was the imaging modality most used in the studies, followed by X-ray, ultrasonography, and digital tomosynthesis. A transparent algorithm could not be identified. Percutaneous nephrolithotomy (PCNL), retrograde intrarenal surgery (RIRS), and ureteroscopy (URS) were used in the studies for endoscopic treatment. PCNL showed the best stone-free (SFr) rate and lowest hazard ratio (HR) for reoperation. RIRS showed superiority over extracorporeal shockwave lithotripsy for recurrent SFs, but fragments over 4 mm increased the recurrent rate. URS has an increased HR for reoperation for bilateral stones. Conclusions: The heterogeneity of urolithiasis leaves urologists without a standardized plan for recurrent SFs. Thus, each patient’s follow-up should be planned individually and holistically. Pre-stenting is not to be avoided, especially in high-risk patients, and SFr status needs to be the aim. Finally, CT scans should not be generally overused but should be part of a patient’s treatment plan. Prospective studies are required to define SFr status, the size of significant residual fragments, and the modalities of intervention and follow-up.
Additive Manufacturing of Ti3AlC2/TiC and Ti3AlC2/SiC Ceramics Using the Fused Granules Fabrication Technique
Authors: Krinitcyn Maksim , Kopytov Georgy , Ryumin Egor
Published: June 2024

In this work, SiC–Ti3AlC2 and TiC–Ti3AlC2 composites produced by additive manufacturing are investigated. The issue of obtaining ceramic materials using additive manufacturing technologies is currently relevant, since not many modern additive technologies are suitable for working with ceramic materials. The study is devoted to the optimization of additive manufacturing parameters, as well as the study of the structure and properties of the resulting objects. The fused granules fabrication (FGF) method as one kind of the material extrusion additive manufacturing (MEAM) technology is used to obtain composite samples. The main advantage of the FGF technology is the ability to obtain high-quality samples from ceramic materials by additive manufacturing. Composites with different ratios between components and different powder/polymer ratios are investigated. The technological features of the additive formation of composites are investigated, as well as their structure and properties. The optimal sintering temperature to form the best mechanical properties for both composites is 1300 °C. The composites have a regulatable porosity. Ti3AlC2 content, sintering temperature, and polymer content in the feedstock are the main parameters that regulate the porosity of FGF samples.
The Complexity in Bilingual Code-Switching Research: A Systematic Review
Authors: Rayo William , Barrita Aldo M. , Cabrera Martinez Lianelys , Carbajal Ivan
Published: June 2024

This systematic review explored how researchers operationalized bilingualism when investigating the relationship between bilingual code-switching experience and cognition. Through a PRISMA-guided systematic review of thirty-two studies with original data, published in English, focusing on adult non-clinical samples, with bilingualism as a key variable, we aimed to understand the prevalence of these issues. Criteria for inclusion required an assessment of bilingualism beyond language proficiency or age of acquisition, and consideration of naturalistic code-switching behaviors. We report our results through an analysis of themes that included aspects of language that are considered when measuring bilingualism and code-switching experience. We present our findings and offer insights for future research, advocating for the inclusion of sociocultural factors and more complex analytical modeling in bilingualism research to foster an evolution in the field.
Incipient Inter-Turn Short Circuit Detection in Induction Motors Using Cumulative Distribution Function and the EfficientNetv2 Model
Authors: Morales-Perez Carlos Javier , Perez-Enriquez Laritza , Amezquita-Sanchez Juan Pablo , de Jesus Rangel-Magdaleno Jose , Valtierra-Rodriguez Martin , Granados-Lieberman David
Published: June 2024

Induction motors are one of the most used machines because they provide the necessary traction force for many industrial applications. Their easy operation, installation, maintenance, and reliability make them preferred over other electrical motors. Mechanical and electrical failures, as with other machines, can appear at any stage of their service life, making the stator intern-turn short-circuit fault (ITSC) stand out. Hence, its detection is necessary in order to extend and save useful life, avoiding a breakdown and unprogrammed maintenance processes as well as, in the worst circumstances, a total loss of the machine. Nonetheless, the challenge lies in detecting this type of fault, which has made the analysis and diagnosis processes easier. Such is the case with convolutional neural networks (CNNs), which facilitate the development of methodologies for pattern recognition in several areas of knowledge. Unfortunately, these techniques require a large amount of data for an adequate training process, which is not always available. In this sense, this paper presents a new methodology for the detection of incipient ITSC faults employing a modified cumulative distribution function (CDF) of the current stator signal. Then, these are converted to images and fed into a fast and compact CNN model, trained with a small data set, reaching up to 99.16% accuracy for seven conditions (0, 5, 10, 15, 20, 30, and 40 short-circuited turns) and four mechanical load conditions.
Experimental Evaluation of Mechanical Compression Properties of Aluminum Alloy Lattice Trusses for Anti-Ice System Applications
Authors: Ferro Carlo Giovanni , Varetti Sara , Maggiore Paolo
Published: June 2024

Lattice structures have emerged as promising materials for aerospace structure applications due to their high strength-to-weight ratios, customizable properties, and efficient use of materials. These properties make them attractive for use in anti-ice systems, where lightweight and heat exchange are essential. This paper presents an extensive experimental investigation into mechanical compression properties of lattice trusses fabricated from AlSi10Mg powder alloy, a material commonly used in casted aerospace parts. The truss structures were manufactured using the additive manufacturing selective laser melting technique and were subjected to uniaxial compressive loading to assess their performance. The results demonstrate that AlSi10Mg lattice trusses exhibit remarkable compressive strength with strong correlations depending upon both topology and cells’ parameters setup. The findings described highlight the potential of AlSi10Mg alloy as a promising material for custom truss fabrication, offering customizable cost-effective and lightweight solutions for the aerospace market. This study also emphasizes the role of additive manufacturing in producing complex structures with pointwise-tailored mechanical properties.
Experimental Evaluation of Flexible Fixture Stiffness for Steering Knuckles When Loading a Milling Machine Tool
Authors: Kolesnyk Vitalii , Kuruc Marcel , Dehtiarov Ivan , Neshta Anna , Avramenko Serhii , Kononovych Vitalii , Dynnyk Oksana , Dovhopolov Andrii , Lemekh Serhii , Titskyi Roman
Published: June 2024

In the conditions of the increase in the range of products in the automobile and aircraft industry, there is a tendency to increase the scope of application of flexible fixtures. Thus, in the current article, it was proposed to consider a new concept of a flexible fixture for location parts of a complex shape. The stress and deflection of the steering knuckle elements were calculated using finite element modeling. During the experiment on the static loading, the deflection of the steering knuckle elements was measured, and the results of finite element modeling were validated. It was determined that the stiffness of the proposed flexible fixture ensures compliance with the tolerances of the mutual location of the surfaces of the part, making it reasonable for feature research the novel flexible fixture design during milling.
Maintainability Analysis of Remotely Operated LNG Marine Loading Arms Based on UNE 151001 Standard
Authors: Orellana Fabian , Durán Orlando , Vergara José Ignacio , Arata Adolfo
Published: June 2024

The operation of liquefied natural gas (LNG) marine loading arms plays a pivotal role in the efficient transfer of LNG from maritime vessels to downstream facilities, underpinning the global LNG supply chain. Despite their criticality, these systems frequently encounter operational challenges, notably slow coupling speeds and increased downtimes driven by maintenance demands. Addressing these challenges, Physical Asset Management principles advocate for maximizing process availability by minimizing both planned and unplanned outages. Recognizing maintainability as a key equipment attribute, this document proposes a procedure that extends the use of the UNE 151001 standard to evaluate the maintainability of physical assets. This proposal incorporates into traditional RCM a step for the selection of maintenance levels proposed in the standard, as well as the use of the AHP technique for selecting the weights used during the analysis process. Finally, an aggregated maintainability indicator is presented, which will allow for better evaluation, comparison, and monitoring of this characteristic in one or more industrial assets. To demonstrate its feasibility and utility, the proposed procedure is applied to a set of LNG marine unloading arms. This study identifies pivotal areas for improvement and devises strategic action plans aimed at enhancing asset’s maintainability. The outcomes of this analysis not only provide a roadmap for augmenting operational efficiency but also furnish empirical justification for the requisite investments in maintainability enhancements, thereby contributing to the resilience and sustainability of LNG logistics infrastructure.
Advanced Waterjet Technology for Machining Beveled Structures of High-Strength and Thick Material
Authors: Du Mingming , Zhong Wei , Song Zhichao , Teng Jialin , Liang Wei , Wang Haijin
Published: June 2024

The bevel cutting of large-thickness plates is a key process in modern industries. However, traditional processing method such as air-arc gouging bevel cutting or laser bevel cutting may cause serious deformation and rough surface quality due to the defects of the thermal cutting method. In order to improve the quality and efficiency of bevel processing, the abrasive waterjet cutting method is used in this research to overcome the challenge for bevel machining of high-strength DH40 steel plates with a large thickness. For different kinds of beveled structures, a 3D camera is used to measure the reference points defined on the workpiece and the SVD registration algorithm is adopted to transform the theoretical coordinate system to the actual coordinate system. Furthermore, the distance between the nozzle and the workpiece surface is also measured and compensated for to ensure the consistency of the bevel width. Finally, experiments are carried out for different kinds of bevels to verify the feasibility of the proposed method for high precision processing for beveled structures. The developed method has been effectively applied in the actual shipbuilding industry.
Convergence Result for Solving the Split Fixed Point Problem with Multiple Output Sets in Nonlinear Spaces
Authors: Rashid Maliha , Kalsoom Amna , Albargi Amer Hassan , Hussain Aftab , Sundas Hira
Published: June 2024

We study the split fixed point problem with multiple output sets in nonlinear spaces, particularly in CAT(0) spaces. We modify the existing self-adaptive algorithm for solving the split common fixed point problem with multiple output sets in the settings of generalized structures. We also present the consequences of our main theorem in terms of the split feasibility problem and the split common fixed point problem.
Modular Quasi-Pseudo Metrics and the Aggregation Problem
Authors: Bibiloni-Femenias Maria del Mar , Valero Oscar
Published: June 2024

The applicability of the distance aggregation problem has attracted the interest of many authors. Motivated by this fact, in this paper, we face the modular quasi-(pseudo-)metric aggregation problem, which consists of analyzing the properties that a function must have to fuse a collection of modular quasi-(pseudo-)metrics into a single one. In this paper, we characterize such functions as monotone, subadditive and vanishing at zero. Moreover, a description of such functions in terms of triangle triplets is given, and, in addition, the relationship between modular quasi-(pseudo-)metric aggregation functions and modular (pseudo-)metric aggregation functions is discussed. Specifically, we show that the class of modular (quasi-)(pseudo-)metric aggregation functions coincides with that of modular (pseudo-)metric aggregation functions. The characterizations are illustrated with appropriate examples. A few methods to construct modular quasi-(pseudo-)metrics are provided using the exposed theory. By exploring the existence of absorbent and neutral elements of modular quasi-(pseudo-)metric aggregation functions, we find that every modular quasi-pseudo-metric aggregation function with 0 as the neutral element is an Aumann function, is majored by the sum and satisfies the 1-Lipschitz condition. Moreover, a characterization of those modular quasi-(pseudo-)metric aggregation functions that preserve modular quasi-(pseudo-)metrics is also provided. Furthermore, the relationship between modular quasi-(pseudo-)metric aggregation functions and quasi-(pseudo-)metric aggregation functions is studied. Particularly, we have proven that they are the same only when the former functions are finite. Finally, the usefulness of modular quasi-(pseudo-)metric aggregation functions in multi-agent systems is analyzed.
Pre-Symmetric w-Cone Distances and Characterization of TVS-Cone Metric Completeness
Authors: Karimizad Seyedeh Sara , Soleimani Rad Ghasem
Published: June 2024

Motivated by two definitions of distance, “pre-symmetric w-distance” and “w-cone distance”, we define the concept of a pre-symmetric w-cone distance in a TVS-CMS and introduce its properties and examples. Also, we discuss the TVS-cone version of the recent results obtained by Romaguera and Tirado. Meanwhile, using Minkowski functionals, we show the equivalency between some consequences concerning a pre-symmetric w-distance in a usual metric space and a pre-symmetric w-cone distance in a TVS-CMS. Then, some types of various w-cone-contractions and the relations among them are investigated. Finally, as an application, a characterization of the completeness of TVS-cone metric regarding pre-symmetric concept is performed, which differentiates our results from former characterizations.
Identification of a Novel KPC Variant, KPC-204, Conferring Resistance to Both Carbapenems and Ceftazidime–Avibactam in an ST11 Klebsiella pneumoniae Strain
Authors: Gong Yanqiao , Feng Yu , Lv Xiaoju
Published: June 2024

This study describes KPC-204, a novel variant of Klebsiella pneumoniae carbapenemase, characterized by a Lys-Asp-Asp (KDD) amino acid insertion at Ambler position 269 deviates from KPC-2. This variant was identified in an ST11-type clinical isolate of carbapenem-resistant Klebsiella pneumoniae from China. Notably, KPC-204 exhibits resistance to both ceftazidime-avibactam and carbapenems. Genetic analysis revealed that blaKPC-204 was located on a highly mobile IncFII/IncR plasmid within a complex genetic structure that facilitates its spread. Functional analysis, achieved through cloning into E. coli DH5α, validates KPC-204’s contribution to increased resistance to ceftazidime-avibactam. The kinetic parameters showed that KPC-204 exhibited similar affinity to KPC-2 toward ceftazidime and reduced sensitivity to avibactam. Docking simulations revealed a weaker interaction between KPC-204 and avibactam compared to KPC-2. Mating experiments demonstrated the resistance’s transmissibility. This investigation underscores the evolving diversity of KPC variants affecting ceftazidime-avibactam resistance, highlighting the necessity for continuous monitoring.
Metabarcoding the Bacterial Assemblages Associated with Toxopneustes roseus in the Mexican Central Pacific
Authors: Hernández-Zulueta Joicye , Rubio-Bueno Sharix , Zamora-Tavares María del Pilar , Vargas-Ponce Ofelia , Rodríguez-Troncoso Alma Paola , Rodríguez-Zaragoza Fabián A.
Published: June 2024

The Mexican Central Pacific (MCP) region has discontinuous coral ecosystems with different protection and anthropogenic disturbance. Characterizing the bacterial assemblage associated with the sea urchin Toxopneustes roseus and its relationship with environmental variables will contribute to understanding the species’ physiology and ecology. We collected sea urchins from coral ecosystems at six sites in the MCP during the summer and winter for two consecutive years. The spatial scale represented the most important variation in the T. roseus bacteriome, particularly because of Isla Isabel National Park (PNII). Likewise, spatial differences correlated with habitat structure variables, mainly the sponge and live coral cover. The PNII exhibited highly diverse bacterial assemblages compared to other sites, characterized by families associated with diseases and environmental stress (Saprospiraceae, Flammeovirgaceae, and Xanthobacteraceae). The remaining five sites presented a constant spatiotemporal pattern, where the predominance of the Campylobacteraceae and Helicobacteraceae families was key to T. roseus’ holobiont. However, the dominance of certain bacterial families, such as Enterobacteriaceae, in the second analyzed year suggests that Punto B and Islas e islotes de Bahía Chamela Sanctuary were exposed to sewage contamination. Overall, our results improve the understanding of host-associated bacterial assemblages in specific time and space and their relationship with the environmental condition.
The Use of Various Types of Waste Paper for the Removal of Anionic and Cationic Dyes from Aqueous Solutions
Authors: Jóźwiak Tomasz , Filipkowska Urszula , Bednarowicz Anna , Zielińska Dorota , Wiśniewska-Wrona Maria
Published: June 2024

This study examined the possibility of using various types of waste paper—used newsprint (NP), used lightweight coated paper (LWC), used office paper (OP), and used corrugated cardboard (CC)—for the removal of anionic dyes, Acid Red 18 (AR18) and Acid Yellow 23 (AY23), and cationic dyes, Basic Violet 10 (BV10) and Basic Red 46 (BR46), from aqueous solutions. The scope of this research included the characterization of sorbents (FTIR, SEM, BET surface area, porosity, pHPZC, effectiveness of water coloration), determination of pH effect on the effectiveness of dye sorption, sorption kinetics (pseudo-first-order model, second-order model, intraparticular diffusion model), and the maximum sorption capacity (Langmuir models and Freundlich model) of the tested sorbents. The use of waste paper materials as sorbents was found to not pose any severe risk of aquatic environment contamination. AR18, AY23, and BV10 sorption intensities were the highest at pH 2, and that of RB46 at pH 6. The waste paper sorbents proved particularly effective in removing cationic dyes, like in the case of, e.g., NP, which had a sorption capacity that reached 38.87 mg/g and 90.82 mg/g towards BV10 and BR46, respectively, and were comparable with that of selected activated carbons (literature data).
An Overview of the Sustainable Depolymerization/Degradation of Polypropylene Microplastics by Advanced Oxidation Technologies
Authors: García-López Elisa I. , Aoun Narimene , Marcì Giuseppe
Published: June 2024

Plastics have become indispensable in modern society; however, the proliferation of their waste has become a problem that can no longer be ignored as most plastics are not biodegradable. Depolymerization/degradation through sustainable processes in the context of the circular economy are urgent issues. The presence of multiple types of plastic materials makes it necessary to study the specific characteristics of each material. This mini-review aims to provide an overview of technological approaches and their performance for the depolymerization and/or degradation of one of the most widespread plastic materials, polypropylene (PP). The state of the art is presented, describing the most relevant technologies focusing on advanced oxidation technologies (AOT) and the results obtained so far for some of the approaches, such as ozonation, sonochemistry, or photocatalysis, with the final aim of making more sustainable the PP depolymerization/degradation process.
Heteroepitaxial Growth of InBi(001)
Authors: Rehaag Thomas J. , Bell Gavin R.
Published: June 2024

InBi is a topological nodal line semimetal with strong spin–orbit coupling. It is epitaxially compatible with III–V semiconductors and, hence, an attractive material for topological spintronics. However, growth by molecular beam epitaxy (MBE) is challenging owing to the low melting point of InBi and the tendency to form droplets. We investigate approaches for epitaxial growth of InBi films on InSb(001) substrates using MBE and periodic supply epitaxy (PSE). It was not possible to achieve planar, stoichiometric InBi heteroepitaxy using MBE growth over the parameter space explored. However, pseudomorphic growth of ultra-thin InBi(001) layers could be achieved by PSE on InSb(001). A remarkable change to the in-plane epitaxial orientation is observed.
The Phenotypic Variation in Moso Bamboo and the Selection of Key Traits
Authors: Zheng Shihui , Wei Songpo , Li Jiarui , Wang Jingsheng , Deng Ziyun , Gu Rui , Fan Shaohui , Liu Guanglu
Published: June 2024

This research aimed to explore the diverse phenotypic characteristics of moso bamboo in China and pinpoint essential characteristics of moso bamboo. In this study, 63 grids were selected using the grid method to investigate 28 phenotypic traits of moso bamboo across the entire distribution area of China. The results suggest that the phenotypic traits of moso bamboo exhibit rich diversity, with coefficients of variation ranging from 5.87% to 36.57%. The phenotypic traits of moso bamboo showed varying degrees of correlation. A principal component analysis was used to identify seven main phenotypic trait indicators: diameter at breast height (DBH), leaf area (LA), leaf weight (LW), branch-to-leaf ratio (BLr), leaf moisture content (Lmc), wall-to-cavity ratio (WCr), and node length at breast height (LN), which accounted for 81.64% of the total information. A random forest model was used, which gave good results to validate the results. The average combined phenotypic trait value (D-value) of most germplasm was 0.563. The highest D-value was found in Wuyi 1 moso in Fujian (0.803), while the lowest D-value was observed in Pingle 2 moso in Guangxi (0.317). The clustering analysis of phenotypic traits classified China’s moso bamboo germplasm into four groups. Group I had the highest D-value and is an important candidate germplasm for excellent germplasm screening.
A Transcriptomic and Metabolomic Study on the Biosynthesis of Iridoids in Phlomoides rotata from the Qinghai–Tibet Plateau
Authors: Wang Luhao , Geng Guigong , Xie Huichun , Zhou Lianyu , He Yujiao , Li Zuxia , Qiao Feng
Published: June 2024

Phlomoides rotata is a traditional Chinese herbal medicine that grows in the Qinghai–Tibet Plateau region at a 3100–5000 m altitude. Iridoid compounds are the main active compounds of the P. rotata used as medical ingredients and display anti-inflammatory, analgesic, and hepatoprotective properties. To better understand the biological mechanisms of iridoid compounds in this species, we performed a comprehensive analysis of the transcriptome and metabolome of P. rotata leaves from four different regions (3540–4270 m). Global metabolome profiling detected 575 metabolites, and 455 differentially accumulated metabolites (DAMs) were detected in P. rotata leaves from the four regions. Eight major DAMs related to iridoid metabolism in P. rotata leaves were investigated: shanzhiside methyl ester, 8-epideoxyloganic acid, barlerin, shanzhiside, geniposide, agnuside, feretoside, and catalpin. In addition, five soil physical and chemical indicators in P. rotata rhizosphere soils were analyzed. Four significant positive correlations were observed between alkaline nitrogen and geniposide, exchangeable calcium and geniposide, available potassium and shanzhiside, and available phosphorus and shanzhiside methyl ester. The transcriptome data showed 12 P. rotata cDNA libraries with 74.46 Gb of clean data, which formed 29,833 unigenes. Moreover, 78.91% of the unigenes were annotated using the eight public databases. Forty-one candidate genes representing 23 enzymes involved in the biosynthesis of iridoid compounds were identified in P. rotata leaves. Moreover, the DXS1, IDI1, 8-HGO1, and G10H2 genes associated with iridoid biosynthesis were specifically expressed in P. rotata. The integration of transcriptome and metabolome analyses highlights the crucial role of soil physical and chemical indicators and major gene expression related to iridoid metabolism pathways in P. rotata from different areas. Our findings provide a theoretical foundation for exploring the molecular mechanisms underlying iridoid compound accumulation in P. rotata.
Frequency Diversity Array Radar and Jammer Intelligent Frequency Domain Power Countermeasures Based on Multi-Agent Reinforcement Learning
Authors: Zhou Changlin , Wang Chunyang , Bao Lei , Gao Xianzhong , Gong Jian , Tan Ming
Published: June 2024

With the development of electronic warfare technology, the intelligent jammer dramatically reduces the performance of traditional radar anti-jamming methods. A key issue is how to actively adapt radar to complex electromagnetic environments and design anti-jamming strategies to deal with intelligent jammers. The space of the electromagnetic environment is dynamically changing, and the transmitting power of the jammer and frequency diversity array (FDA) radar in each frequency band is continuously adjustable. Both can learn the optimal strategy by interacting with the electromagnetic environment. Considering that the competition between the FDA radar and the jammer is a confrontation process of two agents, we find the optimal power allocation strategy for both sides by using the multi-agent deep deterministic policy gradient (MADDPG) algorithm based on multi-agent reinforcement learning (MARL). Finally, the simulation results show that the power allocation strategy of the FDA radar and the jammer can converge and effectively improve the performance of the FDA radar and the jammer in the intelligent countermeasure environment.
Variable Doppler Starting Point Keystone Transform for Radar Maneuvering Target Detection
Authors: Jia Wei , Feng Yuan , Qiao Xingshuai , Wang Tianrun , Shan Tao
Published: June 2024

The Doppler band compensated by the keystone transform (KT) is limited. Therefore, it needs to be used in conjunction with the Doppler ambiguity compensation function to correct the range migration (RM) caused by maneuvering targets with Doppler ambiguity. However, the KT implemented by sinc interpolation suffers from significant performance loss at boundaries of compensation Doppler bands. Additionally, in a multi-target scenario, KT implementation methods occupy high complexity when the Doppler range of targets spans over two compensation Doppler bands. To address the aforementioned issues, this study presents a variable Doppler starting point keystone transform (VDSPKT) method, where a new form of ambiguity compensation function is constructed, turning the Doppler starting point of the compensation band in KT variable. Firstly, the position of the compensation Doppler band is changed from fixed to adjustable as needed, enhancing the flexibility of KT. Crucially, the connection points of the compensation Doppler bands in sinc interpolation are reset, avoiding performance loss at their boundaries. Also, the compensation band is adjusted to cover the narrow Doppler frequency range caused by targets, significantly improving computational efficiency. Finally, the simulation and real data experiments demonstrate that the proposed approach effectively addresses the performance degradation and high computational complexity of KT in the aforementioned scenarios, resulting in a computational load reduced by approximately 50% compared to traditional methods.
Scenario-Based Simulation of Impervious Surfaces for Detecting the Effects of Landscape Patterns on Urban Waterlogging
Authors: Li Jiahui , Hou Hao , Zhang Yindong , Huang Ruolin , Hu Tangao
Published: June 2024

With the increase in global extreme climate events, the frequency of urban waterlogging caused by extreme rainstorms is increasing, resulting in serious economic losses and risk to local residents. Understanding the influence of impervious surfaces on urban waterlogging is of great significance for reducing urban waterlogging disasters. Based on InfoWorks ICM, the urban waterlogging model of Lin’an City was established, and the multi-scenario design method was used to analyze the characteristics and causes of urban waterlogging under different designed rainfall return periods. The results show that the maximum stagnant water depth and area are positively correlated with the proportion of impervious surfaces and rainfall return periods. In addition, urban waterlogging is related to the fragmentation of impervious surfaces, pipeline network, and so on. Based on the findings, it is suggested that impervious surfaces should be placed upstream and along roads where feasible. It is also recommended that the aggregation of impervious surfaces is minimized to prevent urban waterlogging. The results provide technical support and reference for local governments to prevent waterlogging disasters.
Ground-Based Hyperspectral Estimation of Maize Leaf Chlorophyll Content Considering Phenological Characteristics
Authors: Guo Yiming , Jiang Shiyu , Miao Huiling , Song Zhenghua , Yu Junru , Guo Song , Chang Qingrui
Published: June 2024

Accurately measuring leaf chlorophyll content (LCC) is crucial for monitoring maize growth. This study aims to rapidly and non-destructively estimate the maize LCC during four critical growth stages and investigate the ability of phenological parameters (PPs) to estimate the LCC. First, four spectra were obtained by spectral denoising followed by spectral transformation. Next, sensitive bands (Rλ), spectral indices (SIs), and PPs were extracted from all four spectra at each growth stage. Then, univariate models were constructed to determine their potential for independent LCC estimation. The multivariate regression models for the LCC (LCC-MR) were built based on SIs, SIs + Rλ, and SIs + Rλ + PPs after feature variable selection. The results indicate that our machine-learning-based LCC-MR models demonstrated high overall accuracy. Notably, 83.33% and 58.33% of these models showed improved accuracy when the Rλ and PPs were successively introduced to the SIs. Additionally, the model accuracies of the milk-ripe and tasseling stages outperformed those of the flare–opening and jointing stages under identical conditions. The optimal model was created using XGBoost, incorporating the SI, Rλ, and PP variables at the R3 stage. These findings will provide guidance and support for maize growth monitoring and management.
Deep-Learning-Based Daytime COT Retrieval and Prediction Method Using FY4A AGRI Data
Authors: Xu Fanming , Song Biao , Chen Jianhua , Guan Runda , Zhu Rongjie , Liu Jiayu , Qiu Zhongfeng
Published: June 2024

The traditional method for retrieving cloud optical thickness (COT) is carried out through a Look-Up Table (LUT). Researchers must make a series of idealized assumptions and conduct extensive observations and record features in this scenario, consuming considerable resources. The emergence of deep learning effectively addresses the shortcomings of the traditional approach. In this paper, we first propose a daytime (SOZA < 70°) COT retrieval algorithm based on FY-4A AGRI. We establish and train a Convolutional Neural Network (CNN) model for COT retrieval, CM4CR, with the CALIPSO’s COT product spatially and temporally synchronized as the ground truth. Then, a deep learning method extended from video prediction models is adopted to predict COT values based on the retrieval results obtained from CM4CR. The COT prediction model (CPM) consists of an encoder, a predictor, and a decoder. On this basis, we further incorporated a time embedding module to enhance the model’s ability to learn from irregular time intervals in the input COT sequence. During the training phase, we employed Charbonnier Loss and Edge Loss to enhance the model’s capability to represent COT details. Experiments indicate that our CM4CR outperforms existing COT retrieval methods, with predictions showing better performance across several metrics than other benchmark prediction models. Additionally, this paper also investigates the impact of different lengths of COT input sequences and the time intervals between adjacent frames of COT on prediction performance.
Combined Coherent and Non-Coherent Long-Time Integration Method for High-Speed Target Detection Using High-Frequency Radar
Authors: Liu Gan , Tian Yingwei , Wen Biyang , Liu Chen
Published: June 2024

High-frequency (HF) radar plays a crucial role in the detection of far-range, stealth, and high-speed targets. Nevertheless, the echo signal of such targets typically exhibits a low signal-to-noise ratio (SNR) and significant amplitude fluctuations because their radar cross-section (RCS) accounting for the HF band is in the resonance region. While enhancing detection performance often requires long-time integration, existing algorithms inadequately consider the impact of amplitude fluctuation. In response to this challenge, this article introduces an improved approach based on coherent and non-coherent integration. Initially, coherent integration, employing the generalized Radon Fourier transform (GRFT), is utilized to derive a candidate detection set of targets’ range–time trajectories. This involves a joint solution for range migration (RM) and Doppler frequency migration (DFM) through a multi-parameter motion model search. Subsequently, the removal of low SNR pulses, followed by non-coherent integration, is implemented to mitigate amplitude fluctuation, referred to as Amplitude Fluctuation Suppression (AFS), and refine the detection outcomes. Both simulation and experiment results are provided to prove the effectiveness of the proposed AFS-GRFT algorithm.
Response of the Normalized Difference Vegetation Index (NDVI) to Snow Cover Changes on the Qinghai–Tibet Plateau
Authors: Zhou Yuantao , Liu Fenggui , Zhang Guoming , Wang Jing’ai
Published: June 2024

The eco-hydrological process related to vegetation on the Qinghai–Tibet Plateau is special, and the impact of snow cover on the growth of vegetation is unique and important. In this study, we analyzed the multi-year variations in the normalized difference vegetation index (NDVI) and snow cover on the Qinghai–Tibet Plateau from spatial and temporal perspectives and determined the relationship between the changes in the NDVI and snow cover. Results showed that in the last 40 years, the rate of change in the snow depth on the plateau was −0.016 mm/a, and the NDVI changed by 0.0005/a. The correlations (|R| values) between the different factors and the NDVI followed the order of precipitation (0.77) > snow depth (0.76) > temperature (0.67) > solar radiation (0.21). The responses of the NDVI to changes in meteorological elements were synchronous, whereas the opposite was found for the snow cover. The snow cover had more significant impacts on vegetation at higher elevations. The NDVI had a lag of about 2 months from the onset of the snow cover, and heavy snow events had negative impacts on the NDVI for more than 3 years. Our findings will facilitate studies of ecological vulnerability and the predictions of changes in vegetation on the plateau.
Spaceborne HRWS-SAR-GMTI System Design Method with Optimal Configuration
Authors: Jiang Yan , Wang Lingyu , Ling Qing , Ma Jingtao , Huang Penghui , Liu Xingzhao , Fan Jixia
Published: June 2024

The spaceborne high-resolution and wide-swath synthetic aperture radar (HRWS-SAR) system combined with the ground moving target indication (GMTI) mode provides a promising prospect in the realization of wide-area target surveying and high-resolution target imaging. In this paper, a system design method is proposed for an HRWS-SAR-GMTI system with ideal reconstruction configuration. In the proposed method, the whole azimuth receiving channels are uniformly divided into multiple groups, where HRWS-SAR imaging is implemented in each sub-group and then GMTI processing is performed based on the reconstructed SAR images. Then, an optimal candidate PRF is properly selected with respect to the optimal reconstruction configuration. After that, the digital beam forming scanning on receive (DBF-SCORE) technique is applied to further enlarge the range swath and improve the noise equivalent scattering coefficient (NESZ). Based on the predesigned system, HRWS-SAR image-based GMTI processing can finally be accomplished. The effectiveness of the proposed method is validated by simulated experiments.
Imagery Time Series Cloud Removal and Classification Using Long Short Term Memory Neural Networks
Authors: Alonso-Sarria Francisco , Valdivieso-Ros Carmen , Gomariz-Castillo Francisco
Published: June 2024

The availability of high spatial and temporal resolution imagery, such as that provided by the Sentinel satellites, allows the use of image time series to classify land cover. Recurrent neural networks (RNNs) are a clear candidate for such an approach; however, the presence of clouds poses a difficulty. In this paper, random forest (RF) and RNNs are used to reconstruct cloud-covered pixels using data from other next in time images instead of pixels in the same image. Additionally, two RNN architectures are tested to classify land cover from the series, treating reflectivities as time series and also treating spectral signatures as time series. The results are compared with an RF classification. The results for cloud removal show a high accuracy with a maximum RMSE of 0.057 for RNN and 0.038 for RF over all images and bands analysed. In terms of classification, the RNN model obtained higher accuracy (over 0.92 in the test data for the best hyperparameter combinations) than the RF model (0.905). However, the temporal–spectral model accuracies did not reach 0.9 in any case.
Design of Evaluation Classification Algorithm for Identifying Conveyor Belt Mistracking in a Continuous Transport System’s Digital Twin
Authors: Fedorko Gabriel , Molnar Vieroslav , Stehlikova Beata , Michalik Peter , Saliga Jan
Published: June 2024

A prerequisite for continuous transport systems’ operation is their digital transformation, which interprets operating conditions based on the availability of a wide range of data and information in the form of measured quantities that can be obtained, for example, by experimental measurement. To implement digital transformation in continuous transport systems, it is necessary to examine and analyze the informative value of individual measured quantities in detail. Research in this area must focus on identifying addressable quantities with a clear, informative value. Such an approach enables the monitoring of continuous transport systems operation and performance of operational diagnostics, the objective of which should be identifying undesirable operating conditions. Within this paper, research will be presented aiming to verify the hypothesis that, based on a measurement of selected parameters, it is possible to identify belt mistracking in a continuous transport system. Belt mistracking is an undesirable condition that can cause a conveyor belt to converge and thus seriously turn off an entire transport system. The research results confirmed the established hypothesis. Based on this, an evaluation algorithm was created for on-time evaluation. The proposed algorithm is also suitable for the needs of a digital twin of a continuous transport system.
Comparing the Drop Vertical Jump Tracking Performance of the Azure Kinect to the Kinect V2
Authors: Abdelnour Patrik , Zhao Kevin Y. , Babouras Athanasios , Corban Jason Philip Aaron Hiro , Karatzas Nicolaos , Fevens Thomas , Martineau Paul Andre
Published: June 2024

Traditional motion analysis systems are impractical for widespread screening of non-contact anterior cruciate ligament (ACL) injury risk. The Kinect V2 has been identified as a portable and reliable alternative but was replaced by the Azure Kinect. We hypothesize that the Azure Kinect will assess drop vertical jump (DVJ) parameters associated with ACL injury risk with similar accuracy to its predecessor, the Kinect V2. Sixty-nine participants performed DVJs while being recorded by both the Azure Kinect and the Kinect V2 simultaneously. Our software analyzed the data to identify initial coronal, peak coronal, and peak sagittal knee angles. Agreement between the two systems was evaluated using the intraclass correlation coefficient (ICC). There was poor agreement between the Azure Kinect and the Kinect V2 for initial and peak coronal angles (ICC values ranging from 0.135 to 0.446), and moderate agreement for peak sagittal angles (ICC = 0.608, 0.655 for left and right knees, respectively). At this point in time, the Azure Kinect system is not a reliable successor to the Kinect V2 system for assessment of initial coronal, peak coronal, and peak sagittal angles during a DVJ, despite demonstrating superior tracking of continuous knee angles. Alternative motion analysis systems should be explored.
Security Control of Cyber–Physical Systems under Cyber Attacks: A Survey
Authors: Xing Wei , Shen Jun
Published: June 2024

Cyber–physical systems (CPSs), which combine computer science, control systems, and physical elements, have become essential in modern industrial and societal contexts. However, their extensive integration presents increasing security challenges, particularly due to recurring cyber attacks. Therefore, it is crucial to explore CPS security control. In this review, we systematically examine the prevalent cyber attacks affecting CPSs, such as denial of service, false data injection, and replay attacks, explaining their impacts on CPSs’ operation and integrity, as well as summarizing classic attack detection methods. Regarding CPSs’ security control approaches, we comprehensively outline protective strategies and technologies, including event-triggered control, switching control, predictive control, and optimal control. These approaches aim to effectively counter various cyber threats and strengthen CPSs’ security and resilience. Lastly, we anticipate future advancements in CPS security control, envisioning strategies to address emerging cyber risks and innovations in intelligent security control techniques.
Anatomical Registration of Implanted Sensors Improves Accuracy of Trunk Tilt Estimates with a Networked Neuroprosthesis
Authors: Morrison Matthew W. , Miller Michael E. , Lombardo Lisa M. , Triolo Ronald J. , Audu Musa L.
Published: June 2024

For individuals with spinal cord injuries (SCIs) above the midthoracic level, a common complication is the partial or complete loss of trunk stability in the seated position. Functional neuromuscular stimulation (FNS) can restore seated posture and other motor functions after paralysis by applying small electrical currents to the peripheral motor nerves. In particular, the Networked Neuroprosthesis (NNP) is a fully implanted, modular FNS system that is also capable of capturing information from embedded accelerometers for measuring trunk tilt for feedback control of stimulation. The NNP modules containing the accelerometers are located in the body based on surgical constraints. As such, their exact orientations are generally unknown and cannot be easily assessed. In this study, a method for estimating trunk tilt that employed the Gram–Schmidt method to reorient acceleration signals to the anatomical axes of the body was developed and deployed in individuals with SCI using the implanted NNP system. An anatomically realistic model of a human trunk and five accelerometer sensors was developed to verify the accuracy of the reorientation algorithm. Correlation coefficients and root mean square errors (RMSEs) were calculated to compare target trunk tilt estimates and tilt estimates derived from simulated accelerometer signals under a variety of conditions. Simulated trunk tilt estimates with correlation coefficients above 0.92 and RMSEs below 5° were achieved. The algorithm was then applied to accelerometer signals from implanted sensors installed in three NNP recipients. Error analysis was performed by comparing the correlation coefficients and RMSEs derived from trunk tilt estimates calculated from implanted sensor signals to those calculated via motion capture data, which served as the gold standard. NNP-derived trunk tilt estimates exhibited correlation coefficients between 0.80 and 0.95 and RMSEs below 13° for both pitch and roll in most cases. These findings suggest that the algorithm is effective at estimating trunk tilt with the implanted sensors of the NNP system, which implies that the method may be appropriate for extracting feedback signals for control systems for seated stability with NNP technology for individuals who have reduced control of their trunk due to paralysis.