bluuebunny/crossref_metadata_2025 huggingface dataset:
Unveiling the Anatomical and Functional Attributes of Stipular Colleters in Palicourea tetraphylla Cham. & Schltdl. and Palicourea rudgeoides (Müll. Arg.) Standl. (Rubiaceae)
Authors: Bezerra Laís de Almeida , Miguel Emilio Castro , Alexandrino Camilla Ribeiro , de Azevedo Rangel Miguel Thaiz Batista , Gomes Valdirene Moreira , Da Cunha Maura
Published: April 2024

The characterization of colleters in Rubiaceae is crucial for understanding their role in plant function. Analyzing colleters in Palicourea tetraphylla and Palicourea rudgeoides aims to deepen the understanding of these structures morphoanatomical and functional characteristics. The study reveals colleters with palisade epidermis and a parenchymatic central axis, classified as standard type, featuring vascularization and crystals. Colleter secretion, abundant in acidic mucopolysaccharides, proteins, and phenolic compounds, protects against desiccation. The ontogenesis, development, and senescence of the colleters are quite rapid and fulfill their role well in biotic and abiotic protection because these structures are present at different stages of development in the same stipule. Pronounced protrusions on the colleters surface, coupled with the accumulation of secretion in the intercellular and subcuticular spaces, suggest that the secretory process occurs through the wall, driven by pressure resulting from the accumulation of secretion. The microorganisms in the colleters’ secretion, especially in microbiota-rich environments such as the Atlantic Forest, provide valuable information about plant–microorganism interactions, such as resistance to other pathogens and organisms and ecological balance. This enhanced understanding of colleters contributes to the role of these structures in the plant and enriches knowledge about biological interactions within specific ecosystems and the family taxonomy.
Unveiling the Synergistic Effects of Phosphorus Fertilization and Organic Amendments on Red Pepper Growth, Productivity and Physio-Biochemical Response under Saline Water Irrigation and Climate-Arid Stresses
Authors: Bouras Hamza , Devkota Krishna Prasad , Mamassi Achraf , Loudari Aicha , Choukr-Allah Redouane , El-Jarroudi Moussa
Published: April 2024

In regions facing water scarcity and soil salinity, mitigating these abiotic stresses is paramount for sustaining crop production. This study aimed to unravel the synergistic effects of organic matter and phosphorus management in reducing the adverse effect of saline water for irrigation on red pepper (Capsicum annuum L.) production, fruit quality, plant physiology, and stress tolerance indicators. The study was carried out in the arid Tadla region of Morocco and involved two key experiments: (i) a field experiment during the 2019 growing season, where red pepper plants were subjected to varying phosphorus fertilizer rates (120, 140, and 170 kg of P2O5.ha−1) and saline water irrigation levels (0.7; 1.5; 3; and 5 dS.m−1); and (ii) a controlled pot experiment in 2021 for examining the interaction of saline water irrigation levels (EC values of 0.7, 2, 5, and 9 dS.m−1), phosphorus rates (30, 36, and 42 kg of P2O5.ha−1), and the amount of organic matter (4, 8, 12, and 16 t.ha−1). The field study highlighted that saline irrigation significantly affected red pepper yields and fruit size, although phosphorus fertilization helped enhance productivity. Additionally, biochemical markers of stress tolerance, such as proline and glycine betaine, along with stomatal conductance, were impacted by increasing salinity levels. The pot experiment showed that combining organic amendments and phosphorus improved soil properties and stimulated red pepper growth and root weight across all salinity levels. The integration of phosphorus fertilization and organic amendments proved instrumental for counteracting salinity-induced constraints on red pepper growth and yield. Nonetheless, caution is necessary as high salinity can still negatively impact red pepper productivity, necessitating the establishment of an irrigation water salinity threshold, set at 5 dS.m−1.
Rubber-like PTFE Thin Coatings Deposited by Pulsed Electron Beam Deposition (PED) Method
Authors: Niemczyk Agata , Jędrzejewski Roman , Piwowarczyk Joanna , Baranowska Jolanta
Published: April 2024

PTFE coatings were manufactured using the pulsed electron beam deposition (PED) technique and deposited on Si substrates. The deposition was carried out at constant parameters: temperature 24 °C, discharge voltages 12 kV, and 5000 electron pulses with a pulse frequency of 5 Hz. Nitrogen was used as the background gas. The gas pressure varied from 3 to 11 mTorr. The coating adhesion was evaluated using micro scratch testing and the residual scratch morphology was characterized by atomic force microscopy. Detailed studies of the chemical and physical structure were conducted using infrared spectroscopy and X-ray diffraction. These analyses were then correlated with the mechanical response of the coatings observed during the scratch tests. Drawing upon a review of the literature concerning energetic beam interactions with PTFE material, hypotheses were posed to explain why only specific conditions of the PED process yielded PTFE coatings with rubber-like properties.
Injectable Thermo-Responsive Peptide Hydrogels and Its Enzyme Triggered Dynamic Self-Assembly
Authors: Yin Bowen , Wang Ruoxue , Guo Yu , Li Liuxuan , Hu Xiuli
Published: April 2024

Endogenous stimuli-responsive injectable hydrogels hold significant promise for practical applications due to their spatio-temporal controllable drug delivery. Herein, we report a facile strategy to construct a series of in situ formation polypeptide hydrogels with thermal responsiveness and enzyme-triggered dynamic self-assembly. The thermo-responsive hydrogels are from the diblock random copolymer mPEG-b-P(Glu-co-Tyr). The L-glutamic acid (Glu) segments with different γ-alkyl groups, including methyl, ethyl, and n-butyl, offer specific secondary structure, facilitating the formation of hydrogel. The L-tyrosine (Tyr) residues not only provide hydrogen-bond interactions and thus adjust the sol–gel transition temperatures, but also endow polypeptide enzyme-responsive properties. The PTyr segments could be phosphorylated, and the phosphotyrosine copolymers were amphiphilies, which could readily self-assemble into spherical aggregates and transform into sheet-like structures upon dephosphorylation by alkaline phosphatase (ALP). P(MGlu-co-Tyr/P) and P(MGlu-co-Tyr) copolymers showed good compatibility with both MC3T3-E1 and Hela cells, with cell viability above 80% at concentrations up to 1000 μg/mL. The prepared injectable polypeptide hydrogel and its enzyme-triggered self-assemblies show particular potential for biomedical applications.
Correction: Meister et al. Assessing Long-Term Medical Remanufacturing Emissions with Life Cycle Analysis. Processes 2023, 11, 36
Authors: Meister Julia A. , Sharp Jack , Wang Yan , Nguyen Khuong An
Published: April 2024

In the original publication, ref [...]
New Insights in Prebiotic Utilization: A Systematic Review
Authors: Arapović Martina , Puljić Leona , Kajić Nikolina , Kartalović Brankica , Habschied Kristina , Mastanjević Krešimir
Published: April 2024

The hectic pace of modern life often leads to quick solutions, both in lifestyle and the choice of food we consume. The importance of the gut microbiome and its balance is being increasingly researched, with the prebiotic concept itself becoming a topic of scientific investigation. The aim of this paper is to analyze scientific studies on the understanding of prebiotics conducted between 2019 and 2024 in order to see what new knowledge, new sources, new ways of use, and newly established effects on certain disease states have been discovered during this period. The question that the authors are trying to answer is how specific prebiotics affect the growth and activity of selected probiotic strains in the human gut (have impact on gut microbiome) and what the implications of these interactions are. Four databases were searched: Pubmed/MEDLINE, Springerlink, Google Scholar, and Scopus. The keywords used were prebiotics, functional food, probiotics, gut microbiome, and trends. A systematic review of 30 scientific studies on the topic of prebiotics revealed significant advances in understanding and application. Research particularly indicates how prebiotics stimulate the growth of beneficial probiotic strains, such as Lacticaseibacillus rhamnosus, Lactiplantibacillus plantarum, and Bifidobacterium. In addition, innovative approaches in food production, including pasta rich in prebiotic fibers, chocolate with inulin and stevia, and the use of fruit by-products, show promising results in creating “healthier” food options. Although the papers had differing objectives and research methodologies, certain similarities were found. All papers emphasized the importance of using prebiotics, although it depended on the type they come from and their impact on the gut microbiome, i.e., the stimulation of probiotic action within the gut microbiome, which consequently has benefits on health. This review serves as a springboard for further research in this exciting field, with the ultimate goal of harnessing the power of prebiotics to improve health outcomes.
A Systematic Review of Multi-Objective Evolutionary Algorithms Optimization Frameworks
Authors: Pătrăușanu Andrei , Florea Adrian , Neghină Mihai , Dicoiu Alina , Chiș Radu
Published: April 2024

The study of evolutionary algorithms (EAs) has witnessed an impressive increase during the last decades. The need to explore this area is determined by the growing request for design and the optimization of more and more engineering problems in society, such as highway construction processes, food and agri-technologies processes, resource allocation problems, logistics and transportation systems, microarchitectures, suspension systems optimal design, etc. All of these matters refer to specific highly computational problems with a huge design space, hence the obvious need for evolutionary algorithms and frameworks, or platforms that allow for the implementing and testing of such algorithms and methods. This paper aims to comparatively analyze the existing software platforms and state-of-the-art multi-objective optimization algorithms and make a review of what features exist and what features might be included next as further developments in such tools, from a researcher’s perspective. Additionally, it is essential for a framework to be easily extendable with new types of problems and optimization algorithms, metrics and quality indicators, genetic operators or specific solution representations and results analysis and comparison features. After presenting the most relevant existing features in these types of platforms, we suggest some future steps and the developments we have been working on.
Numerical Study of Three-Dimensional Models of Single- and Two-Phase Nanofluid Flow through Corrugated Channels
Authors: Abugnah Elhadi Kh , Wan Salim Wan Saiful-Islam , Elfaghi Abdulhafid M. A. , Al-Alimi Sami , Saif Yazid , Zhou Wenbin
Published: April 2024

This study delves into computational fluid dynamics (CFDs) predictions for SiO2–water nanofluids, meticulously examining both single-phase and two-phase models. Employing the finite volume approach, we tackled the three-dimensional partial differential equations governing the turbulent mixed convection flow in a horizontally corrugated channel with uniform heat flux. The study encompasses two nanoparticle volume concentrations and five Reynolds numbers (10,000, 15,000, 20,000, 25,000, and 30,000) to unravel these intricate dynamics. Despite previous research on the mixed convection of nanofluids using both single-phase and two-phase models, our work stands out as the inaugural systematic comparison of their predictions for turbulent mixed convection flow through this corrugated channel, considering the influences of temperature-dependent properties and hydrodynamic characteristics. The results reveal distinct variations in thermal fields between the two-phase and single-phase models, with negligible differences in hydrodynamic fields. Notably, the forecasts generated by three two-phase models—Volume of Fluid (VOF), Eulerian Mixture Model (EMM), and Eulerian Eulerian Model (EEM)—demonstrate remarkable similarity in the average Nusselt number, which are 24% higher than the single-phase model (SPM). For low nanoparticle volume fractions, the average Nusselt number predicted by the two-phase models closely aligns with that of the single-phase model. However, as the volume fraction increases, differences emerge, especially at higher Reynolds numbers. In other words, as the volume fraction of the nanoparticles increases, the nanofluid flow becomes a multi-phase problem, as depicted by the findings of this study.
Flow Characterization in Fractured Shale Oil Matrices Using Advanced Nuclear Magnetic Resonance Techniques
Authors: Li Sichen , Sun Jing , Gao Yang , Liu Dehua , Zhang Zhengyang , Ma Pan
Published: April 2024

The evaluation of flow dynamics in fractured shale oil reservoirs presents significant challenges due to the complex pore configurations and high organic material concentration. Conventional methods for petrophysical and fluid dynamic evaluations are insufficient in addressing these complexities. However, nuclear magnetic resonance (NMR) technology is an effective technique for quantitatively delineating fluid micro-transport properties across the reservoir core. This study presents an experimental methodology rooted in NMR technology to quantify the flow capabilities within the shale oil matrix. This approach incorporates high-pressure saturation flow experiments across seven distinct core samples to gauge the micro-transport phenomena of fluids across various pore dimensions. The results revealed that under high-pressure saturation, shale cores devoid of fractures demonstrated an average crude oil saturation rate of merely 19.44%. Cores with evident stratification exhibited a 16.18% increase in flow capacity compared to their non-stratified counterparts. The flow dynamics within these shale reservoirs exhibited a range of behaviors, from non-linear to linear. In lower-permeability zones, non-linear patterns became increasingly apparent. An NMR T2 spectrum analysis was used to identify the minimum effective pore size conducive to shale oil flow within the matrix, which was between 8 and 10 nanometers. These insights provide a foundation for a deeper understanding of the mechanisms behind oil and gas migration in fractured shale oil matrices, offering valuable insight into their extractive potential.
Oil–Water Hydrodynamics Model during Oil Displacement by Water in Down-Hill Mobile Pipeline
Authors: Li Guang , Fang Gang , Kou Zhi , Chen Shiming , Duan Jimiao , Chen Yan
Published: April 2024

In the process of water displacing oil within mobile pipelines, it is common that the oil tends to accumulate at the elevated sections of inclined pipelines, leading to an issue of residual oil accumulation. In this paper, the mechanism of carrying accumulated oil out of the pipeline with water flow is discussed. Taking the residual oil layer in down-hill pipelines as a research object, a hydrodynamic model of the water-oil displacement process is established based on the theory of liquid–liquid two-phase flow and the application of the momentum transfer equation. It has been found that the use of this model can enhance the computational speed by 15% without affecting the accuracy of the calculations. Subsequently, the model is used to analyze the impact of different initial water-phase velocities, inclination angles, initial oil-phase heights, and pipeline diameters on the oil-carrying process of water flow. The results indicate that increasing the initial water-phase velocity, the angle of inclination, and the initial oil-phase height all enhance the fluctuation in the oil–water interface, making it easier for the oil phase to be carried away from the pipeline. Conversely, when all other parameters are held constant, an increase in the pipeline diameter tends to stabilize the oil–water interface, thereby making it more difficult for the residual oil to be carried away by the water flow.
Lessons from Master Hongyi’s Experiences with Impermanence for Death Education
Authors: Shi (Hsu-Feng Lee) Fazhao
Published: April 2024

This paper explores the life and teachings of the renowned Chinese Buddhist monk Master Hongyi (1880–1942), focusing on his transformative encounters with impermanence and their relevance for contemporary death education. Drawing upon historical records, personal writings, and the accounts of his contemporaries, this study traces Master Hongyi’s profound spiritual journey from intense grief and existential crisis to enlightened equanimity in the face of mortality. It examines how his skillful application of Buddhist practices enabled him to find meaning, purpose, and liberation amidst the challenges of aging, illness, and dying. Through an in-depth analysis of Master Hongyi’s wisdom and lived experience, this paper proposes the “Hongyi Model”, an innovative paradigm for integrating the spiritual, psychological, and artistic dimensions of his approach into modern death education. The findings underscore the transformative potential of Buddhist teachings for fostering a more authentic, meaningful, and spiritually grounded engagement with mortality, offering valuable insights for educators, counselors, and healthcare professionals working in end-of-life care.
Metaphorical Language and Function of the “Bridal Pick-Up” Ritual in Anatolian Traditional Weddings with Its Origin and Reflections
Authors: Kartal Atila , Şimşek Kemal , Atmaca Emine , Kaplan Haktan
Published: April 2024

In the urban centers of Türkiye, where cultural changes are more widespread and effective, wedding processional is replaced by the solemnization of the marriage at indoor weddings, and the Kūdegū (old Turkic language; refers to bridegroom, son-in-law) awaiting the bride’s arrival at the boy’s house is replaced by differences in the way of the bride and groom’s entry together; moreover, while wedding rituals such as the bridal bath and groom’s hammam are being forgotten, bachelor/bachelorette parties are on the rise. The beliefs and practices related to the bride being taken out of the girl’s house with a special ceremony have deep meanings, such as blessing the bride who has just joined the family, acclimatizing the bride who feels like an outsider and avoiding her from these feelings, and protecting the bride and groom from the körmös (spirits in Turkic mythology, devilish entities living in the underworld), bad spirits, and the evil eye. In this paper, the structure, function, practices, and beliefs of the rituals surrounding the bride and groom on the last day of Anatolian Turkish weddings are analyzed using a qualitative research method. In addition, this study identified the betrothal, performance, beliefs, and practices surrounding the ritual of “bridal pick up” among Anatolian Turks and evaluated the symbols and signs in the ritual procedures in the functional context of the origins and reflections of traditional Turkish beliefs.
Between a Rock and a Hard Place: The Intersectional Experiences of Iranian Feminists from Minoritized Ethno-National Backgrounds
Authors: Ahmadi Donya
Published: April 2024

Over the past decades, Iran has been witnessing the growth of a burgeoning feminist movement. With its origins deeply rooted in the early 20th century, the Iranian feminist movement, as such, is not a uniform body: it embodies various, opposing even, political ideologies under the umbrella of feminism, reflecting the divergent social locations of its protagonists. While the movement has been criticized for its centralist, middle-class and at times apolitical tendencies, academic scholarship has yet to offer intersectional analyses that problematize historically rooted and daily materialized relations of power within the movement, particularly in relation to axes such as ethnicity (and race), religion, gender identity, sexuality, and (dis)ability. In light of this gap, the present article aims towards documenting and theorizing the intersectionality of the challenges facing Iranian feminist activists belonging to various ethnic nations and religious beliefs. Drawing on ethnographic research, it argues that minority feminists find themselves between a rock and a hard place: the rock being masculinist politics within their minoritized communities, which prioritize ethno-nationalist demands over gendered ones; the hard place being a centralist liberal feminist movement that fails to reflect the intersectionality of their experiences as non-Persian non-Shia women, thereby reproducing hierarchies of power in relation to ethnicity, religion, and class.
Group Formative Processes in 2 Cor 6:14–7:1
Authors: Appeldoorn Gijsbert van
Published: April 2024

This article offers a fresh interpretation of the intended impact of 2 Cor 6:14–7:1 on the group formation of the Corinthian Christ community. To achieve this interpretation, it will first determine the most likely social reference of the term οἱ ἄπιστοι. Secondly, it will describe a methodological tool from the Social Identity Approach that will help to visualise how groups are formed and reformed when the context changes. Finally, it will apply this tool to determine how 2 Cor 6:14–7:1 affected the boundaries of the Christ community in Corinth.
Capsule Broad Learning System Network for Robust Synthetic Aperture Radar Automatic Target Recognition with Small Samples
Authors: Yu Cuilin , Zhai Yikui , Huang Haifeng , Wang Qingsong , Zhou Wenlve
Published: April 2024

The utilization of deep learning in Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) has witnessed a recent surge owing to its remarkable feature extraction capabilities. Nonetheless, deep learning methodologies are often encumbered by inadequacies in labeled data and the protracted nature of training processes. To address these challenges and offer an alternative avenue for accurately extracting image features, this paper puts forth a novel and distinctive network dubbed the Capsule Broad Learning System Network for robust SAR ATR (CBLS-SARNET). This novel strategy is specifically tailored to cater to small-sample SAR ATR scenarios. On the one hand, we introduce a United Division Co-training (UDC) Framework as a feature filter, adeptly amalgamating CapsNet and the Broad Learning System (BLS) to enhance network efficiency and efficacy. On the other hand, we devise a Parameters Sharing (PS) network to facilitate secondary learning by sharing the weight and bias of BLS node layers, thereby augmenting the recognition capability of CBLS-SARNET. Experimental results unequivocally demonstrate that our proposed CBLS-SARNET outperforms other deep learning methods in terms of recognition accuracy and training time. Furthermore, experiments validate the generalization and robustness of our novel method under various conditions, including the addition of blur, Gaussian noise, noisy labels, and different depression angles. These findings underscore the superior generalization capabilities of CBLS-SARNET across diverse SAR ATR scenarios.
The Construction of a Crop Flood Damage Assessment Index to Rapidly Assess the Extent of Postdisaster Impact
Authors: Dang Yaoshuai , Yang Leiku , Song Jinling
Published: April 2024

Floods are among the most serious natural disasters worldwide; they cause enormous crop losses every year and threaten world food security. Many studies have focused on flood impact assessments for administrative districts, but fewer have focused on postdisaster impact assessments for specific crops. Therefore, this study used remote sensing data, including the normalized difference vegetation index (NDVI), elevation data, slope data, and precipitation data, combined with crop growth period data to construct a crop flood damage assessment index (CFAI). First, the analytic hierarchy process (AHP) was used to assign weights to the impact parameters; then, the Weighted Composite Score Method was used to calculate the CFAI; and finally, the impact was classified as sub-slight, slight, moderate, sub-severe, or severe based on the magnitude of the CFAI. This method was used for the Missouri River floods of 2019 in the United States and the Henan flood of 2021 in China. Due to the lack of measured data, the disaster vegetation damage index (DVDI) was used to compare the results. Compared with the DVDI, the CFAI underestimated the evaluation results. The CFAI can respond well to the degree of crop impact after flooding, providing new ideas and reference standards for agriculture-related departments.
The ARGOS Instrument for Stratospheric Aerosol Measurements
Authors: DeLand Matthew T. , Kowalewski Matthew G. , Colarco Peter R. , Ramos-Izquierdo Luis
Published: April 2024

Atmospheric aerosols represent an important component of the Earth’s climate system because they can contribute both positive and negative forcing to the energy budget. We are developing the Aerosol Radiometer for Global Observations of the Stratosphere (ARGOS) instrument to provide improved measurements of stratospheric aerosols in a compact package. ARGOS makes limb scattering measurements from space in eight directions simultaneously, using two near-IR wavelengths for each viewing direction. The combination of forward and backward scattering views along the orbit track gives additional information to constrain the aerosol phase function and size distribution. Cross-track views provide expanded spatial coverage. ARGOS will have a demonstration flight through a hosted payload provider in the fall of 2024. The instrument has completed pre-launch environmental testing and radiometric characterization tests. The hosted payload approach offers advantages in size, weight, and power margins for instrument design compared to other approaches, with significant benefits in terms of reducing infrastructure requirements for the instrument team.
SAM-Induced Pseudo Fully Supervised Learning for Weakly Supervised Object Detection in Remote Sensing Images
Authors: Qian Xiaoliang , Lin Chenyang , Chen Zhiwu , Wang Wei
Published: April 2024

Weakly supervised object detection (WSOD) in remote sensing images (RSIs) aims to detect high-value targets by solely utilizing image-level category labels; however, two problems have not been well addressed by existing methods. Firstly, the seed instances (SIs) are mined solely relying on the category score (CS) of each proposal, which is inclined to concentrate on the most salient parts of the object; furthermore, they are unreliable because the robustness of the CS is not sufficient due to the fact that the inter-category similarity and intra-category diversity are more serious in RSIs. Secondly, the localization accuracy is limited by the proposals generated by the selective search or edge box algorithm. To address the first problem, a segment anything model (SAM)-induced seed instance-mining (SSIM) module is proposed, which mines the SIs according to the object quality score, which indicates the comprehensive characteristic of the category and the completeness of the object. To handle the second problem, a SAM-based pseudo-ground truth-mining (SPGTM) module is proposed to mine the pseudo-ground truth (PGT) instances, for which the localization is more accurate than traditional proposals by fully making use of the advantages of SAM, and the object-detection heads are trained by the PGT instances in a fully supervised manner. The ablation studies show the effectiveness of the SSIM and SPGTM modules. Comprehensive comparisons with 15 WSOD methods demonstrate the superiority of our method on two RSI datasets.
R-LRBPNet: A Lightweight SAR Image Oriented Ship Detection and Classification Method
Authors: Gao Gui , Chen Yuhao , Feng Zhuo , Zhang Chuan , Duan Dingfeng , Li Hengchao , Zhang Xi
Published: April 2024

Synthetic Aperture Radar (SAR) has the advantage of continuous observation throughout the day and in all weather conditions, and is used in a wide range of military and civil applications. Among these, the detection of ships at sea is an important research topic. Ships in SAR images are characterized by dense alignment, an arbitrary orientation and multiple scales. The existing detection algorithms are unable to solve these problems effectively. To address these issues, A YOLOV8-based oriented ship detection and classification method using SAR imaging with lightweight receptor field feature convolution, bottleneck transformers and a probabilistic intersection-over-union network (R-LRBPNet) is proposed in this paper. First, a CSP bottleneck with two bottleneck transformer (C2fBT) modules based on bottleneck transformers is proposed; this is an improved feature fusion module that integrates the global spatial features of bottleneck transformers and the rich channel features of C2f. This effectively reduces the negative impact of densely arranged scenarios. Second, we propose an angle decoupling module. This module uses probabilistic intersection-over-union (ProbIoU) and distribution focal loss (DFL) methods to compute the rotated intersection-over-union (RIoU), which effectively alleviates the problem of angle regression and the imbalance between angle regression and other regression tasks. Third, the lightweight receptive field feature convolution (LRFConv) is designed to replace the conventional convolution in the neck. This module can dynamically adjust the receptive field according to the target scale and calculate the feature pixel weights based on the input feature map. Through this module, the network can efficiently extract details and important information about ships to improve the classification performance of the ship. We conducted extensive experiments on the complex scene SAR dataset SRSDD and SSDD+. The experimental results show that R-LRBPNet has only 6.8 MB of model memory, which can achieve 78.2% detection accuracy, 64.2% recall, a 70.51 F1-Score and 71.85% mAP on the SRSDD dataset.
Identification of Rare Wildlife in the Field Environment Based on the Improved YOLOv5 Model
Authors: Su Xiaohui , Zhang Jiawei , Ma Zhibin , Dong Yanqi , Zi Jiali , Xu Nuo , Zhang Haiyan , Xu Fu , Chen Feixiang
Published: April 2024

Research on wildlife monitoring methods is a crucial tool for the conservation of rare wildlife in China. However, the fact that rare wildlife monitoring images in field scenes are easily affected by complex scene information, poorly illuminated, obscured, and blurred limits their use. This often results in unstable recognition and low accuracy levels. To address this issue, this paper proposes a novel wildlife identification model for rare animals in Giant Panda National Park (GPNP). We redesigned the C3 module of YOLOv5 using NAMAttention and the MemoryEfficientMish activation function to decrease the weight of field scene features. Additionally, we integrated the WIoU boundary loss function to mitigate the influence of low-quality images during training, resulting in the development of the NMW-YOLOv5 model. Our model achieved 97.3% for mAP50 and 83.3% for mAP50:95 in the LoTE-Animal dataset. When comparing the model with some classical YOLO models for the purpose of conducting comparison experiments, it surpasses the current best-performing model by 1.6% for mAP50:95, showcasing a high level of recognition accuracy. In the generalization ability test, the model has a low error rate for most rare wildlife species and is generally able to identify wildlife in the wild environment of the GPNP with greater accuracy. It has been demonstrated that NMW-YOLOv5 significantly enhances wildlife recognition accuracy in field environments by eliminating irrelevant features and extracting deep, effective features. Furthermore, it exhibits strong detection and recognition capabilities for rare wildlife in GPNP field environments. This could offer a new and effective tool for rare wildlife monitoring in GPNP.
Preflight Spectral Calibration of the Ozone Monitoring Suite-Nadir on FengYun 3F Satellite
Authors: Wang Qian , Wang Yongmei , Xu Na , Mao Jinghua , Sun Ling , Shi Entao , Hu Xiuqing , Chen Lin , Yang Zhongdong , Si Fuqi , Liu Jianguo , Zhang Peng
Published: April 2024

The Ozone Monitoring Suite-Nadir (OMS-N) instrument is the first hyperspectral remote sensor in the ultraviolet band of China’s Fengyun series satellites. It can be used to detect several kinds of atmospheric constituents. This paper describes the prelaunch spectral calibration of the OMS-N onboard FengYun 3F. Several critical spectral parameters including the spectral resolution, spectral dispersion, and the instrument spectral response function were determined through laser-based measurements. A secondary peak of the instrument spectral response function from the short wavelength side of the ultraviolet band was found, and the possible influence on data applications was analyzed using a reference solar model and radiative transfer model. The results indicate that the spectral resolution and spectral accuracy of OMS-N meet the mission requirements. However, the asymmetries in the instrument spectral response function in the ultraviolet band were found near nadir rows, which are expressed as the “asymmetric central peak” and “secondary peak”. The analysis results show that if the influences of the instrument spectral response function “asymmetric central peak” and “secondary peak” in the ultraviolet band are ignored, they will bring an error as large as 5% at the center of the absorption line.
Correcting the Location Error of Persistent Scatterers in an Urban Area Based on Adaptive Building Contours Matching: A Case Study of Changsha
Authors: Hu Miaowen , Xu Bing , Wei Jia , Zuo Bangwei , Su Yunce , Zeng Yirui
Published: April 2024

Persistent Scatterer InSAR (PS-InSAR) technology enables the monitoring of displacement in millimeters. However, without the use of external parameter correction, radar scatterers exhibit poor geopositioning precision in meters, limiting the correlation between observed deformation and the actual structure. The integration of PS-InSAR datasets and building databases is often overlooked in deformation research. This paper presents a novel strategy for matching between PS points and building contours based on spatial distribution characteristics. A convex hull is employed to simplify the building outline. Considering the influence of building height and incident angle on geometric distortion, an adaptive buffer zone is established. The PS points on a building are further identified through the nearest neighbor method. In this study, both ascending and descending TerraSAR-X orbit datasets acquired between 2016 and 2019 were utilized for PS-InSAR monitoring. The efficacy of the proposed method was evaluated by comparing the PS-InSAR results obtained from different orbits. Through a process of comparison and verification, it was demonstrated that the matching effect between PS points and building contours was significantly enhanced, resulting in an increase of 29.2% in the number of matching PS points. The results indicate that this novel strategy can be employed to associate PS points with building outlines without the need for complex calculations, thereby providing a robust foundation for subsequent building risk assessment.
Deep Learning Test Platform for Maritime Applications: Development of the eM/S Salama Unmanned Surface Vessel and Its Remote Operations Center for Sensor Data Collection and Algorithm Development
Authors: Kalliovaara Juha , Jokela Tero , Asadi Mehdi , Majd Amin , Hallio Juhani , Auranen Jani , Seppänen Mika , Putkonen Ari , Koskinen Juho , Tuomola Tommi , Mohammadi Moghaddam Reza , Paavola Jarkko
Published: April 2024

In response to the global megatrends of digitalization and transportation automation, Turku University of Applied Sciences has developed a test platform to advance autonomous maritime operations. This platform includes the unmanned surface vessel eM/S Salama and a remote operations center, both of which are detailed in this article. The article highlights the importance of collecting and annotating multi-modal sensor data from the vessel. These data are vital for developing deep learning algorithms that enhance situational awareness and guide autonomous navigation. By securing relevant data from maritime environments, we aim to enhance the autonomous features of unmanned surface vessels using deep learning techniques. The annotated sensor data will be made available for further research through open access. An image dataset, which includes synthetically generated weather conditions, is published alongside this article. While existing maritime datasets predominantly rely on RGB cameras, our work underscores the need for multi-modal data to advance autonomous capabilities in maritime applications.
Maritime Moving Target Reconstruction via MBLCFD in Staggered SAR System
Authors: Qi Xin , Zhang Yun , Jiang Yicheng , Liu Zitao , Ma Xinyue , Liu Xuan
Published: April 2024

Imaging maritime targets requires a high resolution and wide swath (HWRS) in a synthetic aperture radar (SAR). When operated with a variable pulse repetition interval (PRI), a staggered SAR can realize HRWS imaging, which needs to be reconstructed due to echo pulse loss and a nonuniformly sampled signal along the azimuth. The existing reconstruction algorithms are designed for stationary scenes in a staggered SAR mode, and thus, produce evident image defocusing caused by complex target motion for moving targets. Typically, the nonuniform sampling and complex motion of maritime targets aggravate the spectrum aliasing in a staggered SAR mode, causing inevitable ambiguity and degradation in its reconstruction performance. To this end, this study analyzed the spectrum of maritime targets in a staggered SAR system through theoretical derivation. After this, a reconstruction method named MBLCFD (Modified Best Linear Unbaised and Complex-Lag Time-Frequency Distribution) is proposed to refocus the blurred maritime target. First, the signal model of the maritime target with 3D rotation accompanying roll–pitch–yaw movement was established under the curved orbit of the satellite. The best linear unbiased (BLU) method was modified to alleviate the coupling of nonuniform sampling and target motion. A precise SAR algorithm was performed based on the method of inverse reversion to counteract the effect of a curved orbit and wide swath. Based on the hybrid SAR/ISAR technique, the complex-lag time-frequency distribution was exploited to refocus the maritime target images. Simulations and experiments were carried out to verify the effectiveness of the proposed method, providing precise refocusing performance in staggered mode.
Variable Universe Fuzzy–Proportional-Integral-Differential-Based Braking Force Control of Electro-Mechanical Brakes for Mine Underground Electric Trackless Rubber-Tired Vehicles
Authors: Li Jian , Jiang Yuqiang
Published: April 2024

Currently, the main solution for braking systems for underground electric trackless rubber-tired vehicles (UETRVs) is traditional hydraulic braking systems, which have the disadvantages of hydraulic pressure crawling, the risk of oil leakage and a high maintenance cost. An electro-mechanical-braking (EMB) system, as a type of novel brake-by-wire (BBW) system, can eliminate the above shortcomings and play a significant role in enhancing the intelligence level of the braking system in order to meet the motion control requirements of unmanned UETRVs. Among these requirements, the accurate control of clamping force is a key technology in controlling performance and the practical implementation of EMB systems. In order to achieve an adaptive clamping force control performance of an EMB system, an optimized fuzzy proportional-integral-differential (PID) controller is proposed, where the improved fuzzy algorithm is utilized to adaptively adjust the gain parameters of classic PID. In order to compensate for the deficiency of single-close-loop control and adjusting the brake gap automatically, a cascaded three-closed-loop control architecture with force/position switch technology is established, where a contact point detection method utilizing motor rotor angle displacement is proposed via experiments. The results of the simulation and experiments indicate that the clamping force response of the proposed multi-close-loop Variable Universe Fuzzy–PID (VUF-PID) controller is faster than the multi-closed-loop Fuzzy–PID and cascaded three-close-loop PID controllers. In addition, the chattering of braking force can be suppressed by 17%. This EMB system may rapidly and automatically finish the operation of the overall braking process, including gap elimination, clamping force tracking and gap recovery, which can obviously enhance the precision of the longitudinal motion control of UETRVs. It can thus serve as a BBW actuator of mine autonomous driving electric vehicles, especially in the stage of braking control.
Study of the Possibility of Using Virtual Reality Application in Rehabilitation among Elderly Post-Stroke Patients
Authors: Matys-Popielska Katarzyna , Popielski Krzysztof , Sibilska-Mroziewicz Anna
Published: April 2024

Thanks to medical advances, life expectancy is increasing. With it comes an increased incidence of diseases, of which age is a risk factor. Stroke is among these diseases, and is one of the causes of long-term disability. The opportunity to treat these patients is via rehabilitation. A promising new technology that can enhance rehabilitation is virtual reality (VR). However, this technology is not widely used by elderly patients, and, moreover, the elderly often do not use modern technology at all. It therefore becomes a legitimate question whether elderly people will be able to use virtual reality in rehabilitation. This article presents a rehabilitation application dedicated to patients with upper limb paresis and unilateral spatial neglect (USN). The application was tested on a group of 60 individuals including 30 post-stroke patients with an average age of 72.83 years. The results of the conducted study include a self-assessment by the patients, the physiotherapist’s evaluation, as well as the patients’ performance of the exercise in VR. The study showed that elderly post-stroke patients are able to use virtual reality applications, but the ability to correctly and fully perform an exercise in VR depends on several factors. One of them is the ability to make logical contact (p = 0.0001 < 0.05). However, the study presented here shows that the ability to use VR applications does not depend on age but on mental and physical condition, which gives hope that virtual reality applications can be used in post-stroke rehabilitation among patients of all ages.
Automated Generation of Clinical Reports Using Sensing Technologies with Deep Learning Techniques
Authors: Cabello-Collado Celia , Rodriguez-Juan Javier , Ortiz-Perez David , Garcia-Rodriguez Jose , Tomás David , Vizcaya-Moreno Maria Flores
Published: April 2024

This study presents a pioneering approach that leverages advanced sensing technologies and data processing techniques to enhance the process of clinical documentation generation during medical consultations. By employing sophisticated sensors to capture and interpret various cues such as speech patterns, intonations, or pauses, the system aims to accurately perceive and understand patient–doctor interactions in real time. This sensing capability allows for the automation of transcription and summarization tasks, facilitating the creation of concise and informative clinical documents. Through the integration of automatic speech recognition sensors, spoken dialogue is seamlessly converted into text, enabling efficient data capture. Additionally, deep models such as Transformer models are utilized to extract and analyze crucial information from the dialogue, ensuring that the generated summaries encapsulate the essence of the consultations accurately. Despite encountering challenges during development, experimentation with these sensing technologies has yielded promising results. The system achieved a maximum ROUGE-1 metric score of 0.57, demonstrating its effectiveness in summarizing complex medical discussions. This sensor-based approach aims to alleviate the administrative burden on healthcare professionals by automating documentation tasks and safeguarding important patient information. Ultimately, by enhancing the efficiency and reliability of clinical documentation, this innovative method contributes to improving overall healthcare outcomes.
Tuning the Proportional–Integral–Derivative Control Parameters of Unmanned Aerial Vehicles Using Artificial Neural Networks for Point-to-Point Trajectory Approach
Authors: Ulu Burak , Savaş Sertaç , Ergin Ömer Faruk , Ulu Banu , Kırnap Ahmet , Bingöl Mehmet Safa , Yıldırım Şahin
Published: April 2024

Nowadays, trajectory control is a significant issue for unmanned micro aerial vehicles (MAVs) due to large disturbances such as wind and storms. Trajectory control is typically implemented using a proportional–integral–derivative (PID) controller. In order to achieve high accuracy in trajectory tracking, it is essential to set the PID gain parameters to optimum values. For this reason, separate gain values are set for roll, pitch and yaw movements before autonomous flight in quadrotor systems. Traditionally, this adjustment is performed manually or automatically in autotune mode. Given the constraints of narrow orchard corridors, the use of manual or autotune mode is neither practical nor effective, as the quadrotor system has to fly in narrow apple orchard corridors covered with hail nets. These reasons require the development of an innovative solution specific to quadrotor vehicles designed for constrained areas such as apple orchards. This paper recognizes the need for effective trajectory control in quadrotors and proposes a novel neural network-based approach to tuning the optimal PID control parameters. This new approach not only improves trajectory control efficiency but also addresses the unique challenges posed by environments with constrained locational characteristics. Flight simulations using the proposed neural network models have demonstrated successful trajectory tracking performance and highlighted the superiority of the feed-forward back propagation network (FFBPN), especially in latitude tracking within 7.52745 × 10−5 RMSE trajectory error. Simulation results support the high performance of the proposed approach for the development of automatic flight capabilities in challenging environments.
An Online Monitoring System for In Situ and Real-Time Analyzing of Inclusions within the Molten Metal
Authors: Wu Yunfei , Yan Hao , Wang Jiahao , Na Xianzhao , Wang Xiaodong , Zheng Jincan
Published: April 2024

Traditional methods for assessing the cleanliness of liquid metal are characterized by prolonged detection times, delays, and susceptibility to variations in sampling conditions. To address these limitations, an online cleanliness-analyzing system grounded in the method of the electrical sensing zone has been developed. This system facilitates real-time, in situ, and quantitative analysis of inclusion size and amount in liquid metal. Comprising pneumatic, embedded, and host computer modules, the system supports the continuous, online evaluation of metal cleanliness across various metallurgical processes in high-temperature environments. Tests conducted with gallium liquid at 90 °C and aluminum melt at 800 °C have validated the system’s ability to precisely and quantitatively detect inclusions in molten metal in real time. The detection procedure is stable and reliable, offering immediate data feedback that effectively captures fluctuations in inclusion amount, thereby meeting the metallurgical industry’s demand for real-time analyzing and control of inclusion cleanliness in liquid metal. Additionally, the system was used to analyze inclusion size distribution during the hot-dip galvanizing process. At a zinc melt temperature of 500 °C, it achieved a detection limit of 21 μm, simultaneously providing real-time data on the size and amount distribution of inclusions. This represents a novel strategy for the online monitoring and quality control of zinc slag throughout the hot-dip galvanizing process.