bluuebunny/crossref_metadata_2025 huggingface dataset:
Role of Multiple Intermolecular H-Bonding Interactions in Molecular Cluster of Hydroxyl-Functionalized Imidazolium Ionic Liquid: An Experimental, Topological, and Molecular Dynamics Study
Authors: Panja Sumit Kumar , Kumar Sumit , Haddad Boumediene , Patel Abhishek R. , Villemin Didier , Amine Hakkoum-Mohamed , Bera Sayantan , Debdab Mansour
Published: September 2024

Multiple intermolecular H-bonding interactions play a pivotal role in determining the macroscopic state of ionic liquids (ILs). Hence, the relationship between the microscopic and the macroscopic properties is key for a rational design of new imidazolium ILs. In the present work, we investigated how the physicochemical property of hydroxyl-functionalized imidazolium chloride is connected to the molecular structure and intermolecular interactions. In the isolated ion pair, strong N-H···Cl H-bonding interactions are observed rather than H-bonding interactions at the acidic C2-H site and alkyl-OH···Cl of the hydroxyl-functionalized imidazolium chloride. However, the N-H···Cl H-bonding interaction of the cation plays a significant role in ion-pair formations and polymeric clusters. For 3-(2-Hydroxy)-1H-imidazolium chloride (EtOHImCl), the oxygen atom (O) engages in two significant interactions within its homodimeric ion-pair cluster: N-H···O and alkyl OH···Cl. Vibrational spectroscopy and DFT calculations reveal that the chloride ion (Cl−) forms a hydrogen bond with the C2-H group via a C2-H···Cl interaction site. Natural Bond Orbital (NBO) analysis indicates that the O-H···Cl hydrogen-bonding interaction is crucial for the stability of the IL, with a second-order perturbation energy of approximately 133.8 kJ/mol. Additional computational studies using Atoms in Molecules (AIMs), non-covalent interaction (NCI) analysis, Electron Localization Function (ELF), and Localized Orbital Locator (LOL) provide significant insights into the properties and nature of non-covalent interactions in ILs. Ab initio molecular dynamics (AIMD) simulations of the IL demonstrate its stable states with relatively low energy values around −1680.6510 atomic units (a.u.) at both 100 fs and 400 fs due to O-H···Cl and C-H···Cl interactions.
Physiology of Marathon: A Narrative Review of Runners’ Profile and Predictors of Performance
Authors: Nikolaidis Pantelis T. , Knechtle Beat
Published: September 2024

Marathon sports events and those who participate in them have grown over the last years, reflecting notably an augmentation of women and master runners’ participation. The aim of the present narrative review was to briefly present the results of studies on anthropometric, physiological, and training characteristics, as well as predictors of performance, in marathon runners. It was observed that performance was better in runners with a small body weight, body mass index, body fat percentage, and rate of endomorphy. Regarding physiology, an increased maximal oxygen uptake, anaerobic threshold, and improved running economy could result in a faster race time. The training variables that could predict performance involved weekly training volume (distance) and intensity (running speed), as well as history of training (years). A combination of these three broad categories of characteristics may offer an approximate estimation of the race speed considering that other aspects (e.g., nutrition, biomechanics, and motivation) influence race performance, too. In summary, the findings of the present study provided an overview of the anthropometric, physiological, and training characteristics associated with marathon race times; thus, optimization of any of these characteristics would be expected to improve the race time.
The Role of Resistance and Plyometric Training in Firefighter Safety and Performance: A Narrative Review
Authors: Kohler Austin A. , Moore Andrew R. , Holland-Winkler Angelia M.
Published: September 2024

Firefighting is a physically demanding occupation that requires optimal fitness and coordination in addition to other physical and cognitive skills. When firefighters lack the physical fitness necessary to perform their duties, they put themselves and others in danger of injury and even death. The heavy, unbreathable personal protective equipment worn to shield firefighters from harmful conditions also promotes overall performance decrements via restricted range of motion as well as energy expenditure and heat-related fatigue. Firefighters are expected to carry other heavy loads, such as hose packs, tools, and victims, while working in hazardous environments. In addition to external load carriage, many firefighters also carry excess body fat that may contribute to poor physical fitness and performance. Therefore, it is imperative to incorporate training strategies to optimize load carriage and improve body composition for improved physical performance during emergencies. Thus, the aims of this narrative review are to (1) explore the impact of firefighter-specific issues on physical performance and safety and (2) identify strategies to assess and optimize occupational performance and safety. Plyometrics; resistance training; and exercise selection, volume, and intensity specifically for improving physical performance in firefighters will be discussed.
Metabolite and Transcriptomic Changes Reveal the Cold Stratification Process in Sinopodophyllum hexandrum Seeds
Authors: Ning Rongchun , Li Caixia , Fan Tingting , Ji Tingting , Xu Wenhua
Published: September 2024

Sinopodophyllum hexandrum (Royle) Ying, an endangered perennial medicinal herb, exhibits morpho-physiological dormancy in its seeds, requiring cold stratification for germination. However, the precise molecular mechanisms underlying this transition from dormancy to germination remain unclear. This study integrates transcriptome and plant hormone-targeted metabolomics techniques to unravel these intricate molecular regulatory mechanisms during cold stratification in S. hexandrum seeds. Significant alterations in the physicochemical properties (starch, soluble sugars, soluble proteins) and enzyme activities (PK, SDH, G-6-PDH) within the seeds occur during stratification. To characterize and monitor the formation and transformation of plant hormones throughout this process, extracts from S. hexandrum seeds at five stratification stages of 0 days (S0), 30 days (S1), 60 days (S2), 90 days (S3), and 120 days (S4) were analyzed using UPLC-MS/MS, revealing a total of 37 differential metabolites belonging to seven major classes of plant hormones. To investigate the biosynthetic and conversion processes of plant hormones related to seed dormancy and germination, the transcriptome of S. hexandrum seeds was monitored via RNA-seq, revealing 65,372 differentially expressed genes associated with plant hormone synthesis and signaling. Notably, cytokinins (CKs) and gibberellins (GAs) exhibited synergistic effects, while abscisic acid (ABA) displayed antagonistic effects. Furthermore, key hub genes were identified through integrated network analysis. In this rigorous scientific study, we systematically elucidate the intricate dynamic molecular regulatory mechanisms that govern the transition from dormancy to germination in S. hexandrum seeds during stratification. By meticulously examining these mechanisms, we establish a solid foundation of knowledge that serves as a scientific basis for facilitating large-scale breeding programs and advancing the artificial cultivation of this highly valued medicinal plant.
Impact of Abiotic Stress on Rice and the Role of DNA Methylation in Stress Response Mechanisms
Authors: Yin Ming , Wang Shanwen , Wang Yanfang , Wei Ronghua , Liang Yawei , Zuo Liying , Huo Mingyue , Huang Zekai , Lang Jie , Zhao Xiuqin , Zhang Fan , Xu Jianlong , Fu Binying , Li Zichao , Wang Wensheng
Published: September 2024

With the intensification of global climate change and the increasing complexity of agricultural environments, the improvement of rice stress tolerance is an important focus of current breeding research. This review summarizes the current knowledge on the impact of various abiotic stresses on rice and the associated epigenetic responses (DNA methylation). Abiotic stress factors, including high temperature, drought, cold, heavy metal pollution, and high salinity, have a negative impact on crop productivity. Epigenetic changes are key regulatory factors in plant stress responses, and DNA methylation is one of the earliest discovered and thoroughly studied mechanisms in these epigenetic regulatory mechanisms. The normal growth of rice is highly dependent on the environment, and changes in the environment can lead to rice sterility and severe yield loss. Changes in the regulation of the DNA methylation pathway are involved in rice’s response to stress. Various DNA methylation-regulating protein complexes that function during rice development have been identified. Significant changes in DNA methylation occur in numerous stress-responsive genes, particularly those in the abscisic acid signaling pathway. These findings underscore the complex mechanisms of the abiotic stress response in rice. We propose the effective improvement of tolerance traits by regulating the epigenetic status of rice and emphasize the role of DNA methylation in abiotic stress tolerance, thereby addressing global climate change and ensuring food security.
Industry 4.0 and Sustainability: Empirical Validation of Constructs of Industry Technology and Sustainable Development
Authors: Melo Lucas da Silva , Fernandes Reimison Moreira , Nunes Denilson Ricardo de Lucena , Oliveira Renata Melo e Silva de , Silva Jonhatan Magno Norte da , Avila Lucas Veiga , Martins Vitor William Batista
Published: September 2024

The study has as purpose to identify, analyze, and validate challenge constructs of Industry 4.0, which can affect the promotion of sustainability within the industry. A systematic literature review was conducted to identify challenges to the promotion of Industry 4.0 sustainability. A set of seventy challenges were grouped into the following eight constructs: finances, technology, organizational, human resources, legislation, geopolitical and economic factors, and both internal and external factors. Subsequently, the same constructs were validated using a survey involving industry professionals. The data were analyzed using the Lawshe method. Five constructs within the eight constructs were considered relevant to industry sustainability according to the experts’ opinion. The validated set of constructs included: finance, technology, organizational, human resources, and internal factors. This study contributes to the literature in the field by addressing a research gap of constructs identification based on expert’s opinions that impact Industry 4.0 in promotion of sustainable development. This study delivers theoretical and practical implications. From a theoretical standpoint, it contributes to expanding knowledge by providing valuable insights into the adoption of Industry 4.0 and its specific challenges concerning the pursuit of more sustainable practices. These implications extend to diverse research areas given the multidisciplinary nature of Industry 4.0.
Delamination and Evaluation of Multilayer PE/Al/PET Packaging Waste Separated Using a Hydrophobic Deep Eutectic Solvent
Authors: Loukodimou Adamantini , Lovell Christopher , Theodosopoulos George , Maniam Kranthi Kumar , Paul Shiladitya
Published: September 2024

This research concerns the development and implementation of ground-breaking strategies for improving the sorting, separation, and recycling of common flexible laminate packaging materials. Such packaging laminates incorporate different functional materials in order to achieve the desired mechanical performance and barrier properties. Common components include poly(ethylene) (PE), poly(propylene) (PP), and poly(ethylene terephthalate) (PET), as well as valuable barrier materials such as poly(vinyl alcohol) (PVOH) and aluminium (Al) foils. Although widely used for the protection and preservation of food produce, such packaging materials present significant challenges for established recycling infrastructure and, therefore, to our future ambitions for a circular economy. Experience from the field of ionic liquids (ILs) and deep eutectic solvents (DESs) has been leveraged to develop novel green solvent systems that delaminate multilayer packaging materials to facilitate the separation and recovery of high-purity commodity plastics and aluminium. This research focuses on the development of a hydrophobic DES and the application of a Design of Experiments (DoE) methodology to investigate the effects of process parameters on the delamination of PE/Al/PET laminate packaging films. Key variables including temperature, time, loading, flake size, and perforations were assessed at laboratory scale using a 1 L filter reactor vessel. The results demonstrate that efficient separation of PE, Al, and PET can be achieved with high yields for material and solvent recovery. Recovered plastic films were subsequently characterised via Fourier-transform infra-red (FTIR) spectroscopy, Differential Scanning Calorimetry (DSC) and Thermogravimetric Analysis (TGA) to qualify the quality of plastics for reuse.
Magnetically Separable Chiral Poly(ionic liquid) Microcapsules Prepared Using Oil-in-Oil Emulsions
Authors: Siam Reema , Ali Abeer , Abu-Reziq Raed
Published: September 2024

This article presents a method for producing chiral ionic liquid-based polyurea microcapsules that can be magnetically separated. The method involves entrapping hydrophilic magnetic nanoparticles within chiral polyurea microspheres. The synthetic process for creating these magnetic polyurea particles involves oil-in-oil (o/o) nano-emulsification of an ionic liquid-modified magnetite nanoparticle (MNPs-IL) and an ionic liquid-based diamine monomer, which comprises a chiral bis(mandelato)borate anion, in a nonpolar organic solvent, toluene, and contains a suitable surfactant. This is followed by an interfacial polycondensation reaction between the isocyanate monomer, polymethylenepolyphenyl isocyanate (PAPI 27), and the chiral diamine monomer, which generates chiral polyurea microcapsules containing magnetic nanoparticles within their cores. The microcapsules generated from the process are then utilized to selectively adsorb either the R or S enantiomer of tryptophan (Trp) from a racemic mixture that is dissolved in water, in order to evaluate their chiral recognition capabilities. During the experiments, the magnetically separable chiral poly(ionic liquid) microcapsules, which incorporated either the R or S isomer of chiral bis(mandelato)borate, exhibited exceptional enantioselective adsorption performance. Thus, the chiral polymeric microcapsules embedded with the R-isomer of the bis(mandelato)borate anion demonstrated significant selectivity for adsorbing L-Trp, yielding a mixture with 70% enantiomeric excess after 96 h. In contrast, microcapsules containing the S-isomer of the bis(mandelato)borate anion preferentially adsorbed D-Trp, achieving an enantiomeric excess of 73% after 48 h.
Chemical Activation Boosted Interface Interaction between Poly(tetrafluoroethylene-co-hexafluoropropylene) Film and Silver Coating
Authors: Wang Hu , Guo Xiuqi , Li Xuelei , Gong Chenliang , Zhao Yongqing
Published: September 2024

To enhance the interfacial adhesion between poly(tetrafluoroethylene-co-hexafluoropropylene) (FEP) film and functional coatings, such as silver (Ag) coating, among others, the surface activation of FEP film has to be performed. Among various activation strategies, chemical activation, such as using naphthalene sodium system, is one of the most efficient methods. However, the effect of chemical activation on the interface interaction between the activated FEP and functional coating is rarely investigated. Herein, the FEP film was activated by naphthalene sodium solution under different conditions, and then the Ag layer was coated onto its surface by vacuum Ag deposition. Based on experimental results and density function theory (DFT) calculation, it is indicated that oxygen-containing functional groups (such as C=O and C–OH groups), introduced onto the surface of FEP by the chemical activation, play a key role in boosting the interface interaction, which is due to the strong interaction between the oxygen-containing functional groups and Ag atoms. In addition, the concentration of naphthalene sodium solution, activation time, and winding speed of Ag- deposition can have a significant impact on the microstructures of Ag coating and the interfacial adhesion between the activated FEP and Ag coating. Under the conditions of high concentration (0.9 M), medium activation time (15 min), and high winding speed (0.8 m min−1), there is the best interface adhesion.
Biopolymer from Annona muricata Residues as a Potential Sustainable Raw Material for Industrial Applications
Authors: Ramos Igor F. S. , Dias Samuel C. , Lopes Talissa B. C. , Silva Júnior Francisco T. dos S. , de Araújo Ricardo , Gutierrez Stanley J. C. , Pessoa Claudia , Osajima Josy A. , Rizzo Marcia S. , Silva-Filho Edson C. , Amorim Manuela , Ramos Óscar , Ribeiro Alessandra B. , Costa Marcilia P.
Published: September 2024

Annona muricata is a fruit species belonging to the Annonaceae family, which is native to the warmer tropical areas of North and South America. A large amount of discarded residue from A. muricata is of interest for obtaining new industrial inputs. To propose the applications of the biopolymer from A. muricata residues (Biop_AmRs), this study aimed to characterize this input chemically and functionally, as well as to evaluate its potential for hemocompatibility and cytotoxicity activity in vitro. Biop_AmRs is an anionic heteropolysaccharide composed of glucose, arabinose, xylose, galactose, mannose, uronic acid, and proteins. This biopolymer exhibited a semicrystalline structure and good thermal stability. Biop_AmRs exhibited excellent water holding capacity, emulsifying properties, and mucoadhesiviness and demonstrated hemocompatibility and cytocompatibility on the L929 cell line. These results indicate possible applications for this biopolymer as a potential environmentally friendly raw material in the food, pharmaceutical, biomedical, and cosmetic industries.
Sleep and Pregnancy: Future Perspectives from Circadian and Precision Medicine
Authors: Del Casale Antonio , Arena Jan Francesco , Girardi Paolo , Angeletti Gloria
Published: September 2024

Ten years ago, the Society for Women’s Health Research highlighted sleep as a significant area of interest in women’s health research [...]
Receptor-Based Strategies for Overcoming Resistance in Cancer Therapy
Authors: Sah Naresh , Shaik Abdul Althaf , Acharya Ganesh , Dunna Manikantha , Silwal Ashok , Sharma Sejal , Khan Sabiha , Bagchi Sounak
Published: September 2024

This review article explores the fundamental role of receptor targeting in overcoming drug resistance in cancer therapy, an area of critical concern given the persistently high rates of cancer morbidity and mortality globally. We highlight how receptor biology intersects with the development of therapeutic resistance with a specific focus on anti-angiogenic agents, immune checkpoint inhibitors, and monoclonal antibodies, which directly or indirectly influence receptor pathways. We also explore how other receptor tyrosine kinases can initially suppress tumor growth, yet often lead to resistance, underscoring the need for novel combinatorial approaches that incorporate advanced receptor modulation techniques. Further, the review delves into the mechanisms by which modulation of the tumor microenvironment and immune system via receptor pathways can overcome resistance to traditional immunotherapies. Additionally, emerging technologies in receptor-targeted nanomedicine are also highlighted, showcasing their potential to revolutionize drug delivery and improve therapeutic outcomes by targeting specific receptor interactions. Ultimately, this review calls for a deeper understanding of receptor dynamics to develop more precise interventions, including insights from various healthcare settings that can prevent or circumvent drug resistance, thus enhancing patient outcomes in oncology.
Exploring (Anti-)Radicalism on TikTok: German Islamic Content Creators between Advocacy and Activism
Authors: Hotait Nader , Ali Rami
Published: September 2024

This study explores the representation of radical and anti-radical ideologies among German Islamic TikTok creators, analyzing 2983 videos from 43 accounts through qualitative content analysis. The results reveal two main content clusters: religious practice involving social/lifestyle issues and political activism around Muslim grievances. Victimization, found in 150 videos, was the most common indicator associated with radicalization and emerged as a source of political activism and subversive discourse. Overall, indicators of radicalism were scarce, suggesting that visible mainstream Islamic creators do not exhibit high levels of radical ideology. However, this also reflects a selection bias in the design of this study, which systematically overlooks fringe actors. In addition, religious advocacy was the most common topic (1144 videos), serving as a source of guidance and motivation, but was occasionally linked to sectarianism and rigid religious interpretations. Male creators posted more religious/theological videos; female creators posted more lifestyle videos. However, gender distinctions are limited due to the low representation of female creators (6). Some topics, such as the hijab, served as an intersection between religious practice and politicized narratives. This study highlights TikTok’s role in promoting diverse ideological views and shaping community engagement, knowledge sharing, and political mobilization within Germany’s Muslim digital landscape.
Automatic Fine Co-Registration of Datasets from Extremely High Resolution Satellite Multispectral Scanners by Means of Injection of Residues of Multivariate Regression
Authors: Alparone Luciano , Arienzo Alberto , Garzelli Andrea
Published: September 2024

This work presents two pre-processing patches to automatically correct the residual local misalignment of datasets acquired by very/extremely high resolution (VHR/EHR) satellite multispectral (MS) scanners, one for, e.g., GeoEye-1 and Pléiades, featuring two separate instruments for MS and panchromatic (Pan) data, the other for WorldView-2/3 featuring three instruments, two of which are visible and near-infra-red (VNIR) MS scanners. The misalignment arises because the two/three instruments onboard GeoEye-1 / WorldView-2 (four onboard WorldView-3) share the same optics and, thus, cannot have parallel optical axes. Consequently, they image the same swath area from different positions along the orbit. Local height changes (hills, buildings, trees, etc.) originate local shifts among corresponding points in the datasets. The latter would be accurately aligned only if the digital elevation surface model were known with sufficient spatial resolution, which is hardly feasible everywhere because of the extremely high resolution, with Pan pixels of less than 0.5 m. The refined co-registration is achieved by injecting the residue of the multivariate linear regression of each scanner towards lowpass-filtered Pan. Experiments with two and three instruments show that an almost perfect alignment is achieved. MS pansharpening is also shown to greatly benefit from the improved alignment. The proposed alignment procedures are real-time, fully automated, and do not require any additional or ancillary information, but rely uniquely on the unimodality of the MS and Pan sensors.
Hydrological Cycle in the Arabian Sea Region from GRACE/GRACE-FO Missions and ERA5 Data
Authors: Boulahia Ahmed Kamel , García-García David , Trottini Mario , Sayol Juan-Manuel , Vigo M. Isabel
Published: September 2024

The Arabian Gulf, a semi-enclosed basin in the Middle East, connects to the Indian Ocean through the Strait of Hormuz and is surrounded by seven arid countries. This study examines the water cycle of the Gulf and its surrounding areas using data from the GRACE and GRACE Follow-On missions, along with ERA5 atmospheric reanalysis data, from 05/2002 to 05/2017 and from 07/2018 to 12/2023. Our findings reveal a persistent water deficit due to high evaporation rates, averaging 370 ± 3 km3/year, greatly surpassing precipitation, which accounts for only 15% of the evaporative loss. Continental runoff provides one-fifth of the needed water, while the remaining deficit, approximately 274 ± 10 km3/year, is balanced by net inflow of saltwater from the Indian Ocean. Seasonal variations show the lowest net inflow of 26 ± 49 km3/year in March and the highest of 586 ± 53 km3/year in November, driven by net evaporation, continental input, and changes in the Gulf’s water budget. This study highlights the complex hydrological dynamics influenced by climate patterns and provides a baseline for future research in the region, which will be needed to quantify the expected changes in the hydrological cycle due to climate change.
Disentangled Representation Learning for Robust Radar Inter-Pulse Modulation Feature Extraction and Recognition
Authors: Zhang Luyao , Zhu Mengtao , Zhang Ziwei , Li Yunjie
Published: September 2024

Modern Multi-Function Radars (MFRs) are sophisticated sensors that are capable of flexibly adapting their control parameters in transmitted pulse sequences. In complex electromagnetic environments, efficiently and accurately recognizing the inter-pulse modulations of non-cooperative radar pulse sequences is a key step for modern Electronic Support (ES) systems. Existing recognition methods focus more on algorithmic designs, such as neural network structure designs, to improve recognition performance. However, in open electromagnetic environments with increased flexibility in radar transmission, these methods would suffer performance degradation due to domain shifts between training and testing datasets. To address this issue, this study proposes a robust radar inter-pulse modulation feature extraction and recognition method based on disentangled representation learning. At first, inspired by the Representation Learning Theory (RLT), the received radar pulse sequences can be disentangled into three explanatory factors related to (i) modulation types, (ii) modulation parameters, and (iii) measurement characteristics, such as measurement noise. Then, an explainable radar pulse sequence disentanglement network is proposed based on auto-encoding variational Bayes. The features extracted through the proposed method can effectively represent the key latent factors related to recognition tasks and maintain performance under domain shift conditions. Experiments on both ideal and non-ideal situations demonstrate the effectiveness, robustness, and superiority of the proposed method in comparison with other methods.
Assessment of Spatial Characterization Metrics for On-Orbit Performance of Landsat 8 and 9 Thermal Infrared Sensors
Authors: Eftekharzadeh Kay S. , Wenny B. N. , Thome K. J. , Yarahmadi M. , Lampkin D. J. , Tahersima M. H. , Voskanian N.
Published: September 2024

The two near-identical pushbroom Thermal Infrared Sensors (TIRS) aboard Landsat 8 and 9 are currently imaging the Earth’s surface at 10.9 and 12 microns from similar 705 km altitude, sun-synchronous polar orbits. This work validates the consistency in the imaging data quality, which is vital for harmonization of the data from the two sensors needed for global mapping. The overlapping operation of these two near-identical sensors, launched eight years apart, provides a unique opportunity to assess the sensitivity of the conventionally used metrics to any unexpectedly found nuanced differences in their spatial performance caused by variety of factors. Our study evaluates spatial quality metrics for bands 10 and 11 from 2022, the first complete year during which both TIRS instruments have been operational. The assessment relies on the straight-knife-edge technique, also known as the Edge Method. The study focuses on comparing the consistency and stability of eight separate spatial metrics derived from four separate water–desert boundary scenes. Desert coastal scenes were selected for their high thermal contrast in both the along- and across-track directions with respect to the platforms ground tracks. The analysis makes use of the 30 m upsampled TIRS images. The results show that the Landsat 8 and Landsat 9 TIRS spatial performance are both meeting the spatial performance requirements of the Landsat program, and that the two sensors are consistent and nearly identical in both across- and along-track directions. Better agreement, both with time and in magnitude, is found for the edge slope and line spread function’s full-width at half maximum. The trend of averaged modulation transfer function at Nyquist shows that Landsat 8 TIRS MTF differs more between the along- and across-track scans than that for Landsat 9 TIRS. The across-track MTF is consistently lower than that for the along-track, though the differences are within the scatter seen in the results due to the use of the natural edges.
Multidirectional Attention Fusion Network for SAR Change Detection
Authors: Li Lingling , Liu Qiong , Cao Guojin , Jiao Licheng , Liu Fang , Liu Xu , Chen Puhua
Published: September 2024

Synthetic Aperture Radar (SAR) imaging is essential for monitoring geomorphic changes, urban transformations, and natural disasters. However, the inherent complexities of SAR, particularly pronounced speckle noise, often lead to numerous false detections. To address these challenges, we propose the Multidirectional Attention Fusion Network (MDAF-Net), an advanced framework that significantly enhances image quality and detection accuracy. Firstly, we introduce the Multidirectional Filter (MF), which employs side-window filtering techniques and eight directional filters. This approach supports multidirectional image processing, effectively suppressing speckle noise and precisely preserving edge details. By utilizing deep neural network components, such as average pooling, the MF dynamically adapts to different noise patterns and textures, thereby enhancing image clarity and contrast. Building on this innovation, MDAF-Net integrates multidirectional feature learning with a multiscale self-attention mechanism. This design utilizes local edge information for robust noise suppression and combines global and local contextual data, enhancing the model’s contextual understanding and adaptability across various scenarios. Rigorous testing on six SAR datasets demonstrated that MDAF-Net achieves superior detection accuracy compared with other methods. On average, the Kappa coefficient improved by approximately 1.14%, substantially reducing errors and enhancing change detection precision.
Recent Patterns and Trends of Snow Cover (2000–2023) in the Cantabrian Mountains (Spain) from Satellite Imagery Using Google Earth Engine
Authors: Melón-Nava Adrián
Published: September 2024

Snow cover is a relevant component of the Earth’s climate system, influencing water supply, ecosystem health, and natural hazard management. This study aims to monitor daily snow cover in the Cantabrian Mountains using Sentinel-2, Landsat (5–8), and MODIS data processed in Google Earth Engine (GEE). The main purpose is to extract metrics on snow cover extent, duration, frequency, and trends. Key findings reveal significant spatial and temporal variability in Snow-Cover Days (SCDs) across the region. Over the past 23 years, there has been a notable overall decrease in snow-cover days (−0.26 days per year, and −0.92 days per year in areas with a significant trend). Altitudes between 1000–2000 m a.s.l. showed marked decreases. The analysis of Snow-Cover Fraction (SCF) indicates high interannual variability and records the highest values at the end of January and the beginning of February. The effectiveness of satellite data and GEE is highlighted in providing detailed, long-term snow cover analysis, despite some limitations in steep slopes, forests, and prolonged cloud-cover areas. These results underscore the capacity for continuous monitoring with satellite imagery, especially in areas with sparse snow observation networks, where studies could be enhanced with more localized studies or additional ground-based observations.
Multi-Scale Context Fusion Network for Urban Solid Waste Detection in Remote Sensing Images
Authors: Li Yangke , Zhang Xinman
Published: September 2024

Illegal waste dumping not only encroaches on land resources but also threatens the health of the surrounding residents. The traditional artificial waste monitoring solution requires professional workers to conduct field investigations. This solution not only requires high labor resources and economic costs but also demands a prolonged cycle for updating the monitoring status. Therefore, some scholars use deep learning to achieve automatic waste detection from satellite imagery. However, relevant models cannot effectively capture multi-scale features and enhance key information. To further bolster the monitoring efficiency of urban solid waste, we propose a novel multi-scale context fusion network for solid waste detection in remote sensing images, which can quickly collect waste distribution information in a large-scale range. Specifically, it introduces a new guidance fusion module that leverages spatial attention mechanisms alongside the use of large kernel convolutions. This module helps guide shallow features to retain useful details and adaptively adjust multi-scale spatial receptive fields. Meanwhile, it proposes a novel context awareness module based on heterogeneous convolutions and gating mechanisms. This module can effectively capture richer context information and provide anisotropic features for waste localization. In addition, it also designs an effective multi-scale interaction module based on cross-guidance and coordinate perception. This module not only enhances critical information but also fuses multi-scale semantic features. To substantiate the effectiveness of our approach, we conducted a series of comprehensive experiments on two representative urban waste detection datasets. The outcomes of relevant experiments indicate that our methodology surpasses other deep learning models. As plug-and-play components, these modules can be flexibly integrated into existing object detection frameworks, thereby delivering consistent enhancements in performance. Overall, we provide an efficient solution for monitoring illegal waste dumping, which contributes to promoting eco-friendly development.
MAFNet: Multimodal Asymmetric Fusion Network for Radar Echo Extrapolation
Authors: Pei Yanle , Li Qian , Wu Yayi , Peng Xuan , Guo Shiqing , Ye Chengzhi , Wang Tianying
Published: September 2024

Radar echo extrapolation (REE) is a crucial method for convective nowcasting, and current deep learning (DL)-based methods for REE have shown significant potential in severe weather forecasting tasks. Existing DL-based REE methods use extensive historical radar data to learn the evolution patterns of echoes, they tend to suffer from low accuracy. This is because data of radar modality face difficulty adequately representing the state of weather systems. Inspired by multimodal learning and traditional numerical weather prediction (NWP) methods, we propose a Multimodal Asymmetric Fusion Network (MAFNet) for REE, which uses data from radar modality to model echo evolution, and data from satellite and ground observation modalities to model the background field of weather systems, collectively guiding echo extrapolation. In the MAFNet, we first extract overall convective features through a global shared encoder (GSE), followed by two branches of local modality encoder (LME) and local correlation encoders (LCEs) that extract convective features from radar, satellite, and ground observation modalities. We employ an multimodal asymmetric fusion module (MAFM) to fuse multimodal features at different scales and feature levels, enhancing radar echo extrapolation performance. Additionally, to address the temporal resolution differences in multimodal data, we design a time alignment module based on dynamic time warping (DTW), which aligns multimodal feature sequences temporally. Experimental results demonstrate that compared to state-of-the-art (SOTA) models, the MAFNet achieves average improvements of 1.86% in CSI and 3.18% in HSS on the MeteoNet dataset, and average improvements of 4.84% in CSI and 2.38% in HSS on the RAIN-F dataset.
Comparing Link Budget Requirements for Future Space-Based Interferometers
Authors: Sambridge Callum Scott , Valliyakalayil Jobin Thomas , McKenzie Kirk
Published: September 2024

Inter-satellite interferometric missions are critical in the ongoing monitoring of climate change. Next-generation Earth geodesy missions are opportunities to improve on mission cost and measurement sensitivity through revised design. To be considered feasible, mission architectures must meet an optical power requirement that factors in both shot noise and laser frequency noise. Reference-transponder mission configurations, like the Gravity Recovery and Climate Experiment-Follow On (GRACE-FO) mission, are designed for measurement down to a received carrier-to-noise density ratio of 70 dB-Hz—1.9 picowatts in shot-noise-limited detection. This work shows, through modeling and simulation, that the optical power level required to perform robust measurement varies significantly between mission configurations. Alternate configurations, such as retro-reflector-based schemes, can operate robustly down to much lower carrier-to-noise density ratios, with the example parameters considered here: down to 29 dB-Hz—150 attowatts in shot-noise-limited detection. These results motivate exploration of alternate missions configurations with revised optical power requirements, increasing the feasibility of new designs.
Design and Assembly of a Miniature Catheter Imaging System for In Vivo Heart Endoscopic Imaging
Authors: Messina Walter , Niemitz Lorenzo , Sorensen Simon , O’Dowling Claire , Buszman Piotr , Andersson-Engels Stefan , Burke Ray
Published: September 2024

In this paper, we present the design and fabrication of a novel chip-on-tip catheter, which uses a microcamera and optical fibres to capture in vivo images in a beating porcine heart thanks to a saline flush to clear the blood field. Here, we demonstrate the medical utility and mechanical robustness of this catheter platform system, which could be used for other optical diagnostic techniques, surgical guidance, and clinical navigation. We also discuss some of the challenges and system requirements associated with developing a miniature prototype for such a study and present assembly instructions. Methods of clearing the blood field are discussed, including an integrated flush channel at the distal end. This permits the capture of images of the endocardial walls. The device was navigated under fluoroscopic guiding, through a guiding catheter to various locations of the heart, where images were successfully acquired. Images were captured at the intra-atrial septum, in the left atrium after a trans-septal cross procedure, and in the left ventricle, which are, to the best of our knowledge, the first images captured in an in vivo beating heart using endoscopic techniques.
The Validity of Apple Watch Series 9 and Ultra 2 for Serial Measurements of Heart Rate Variability and Resting Heart Rate
Authors: O’Grady Ben , Lambe Rory , Baldwin Maximus , Acheson Tara , Doherty Cailbhe
Published: September 2024

The widespread use of wearable devices has enabled continuous monitoring of biometric data, including heart rate variability (HRV) and resting heart rate (RHR). However, the validity of these measurements, particularly from consumer devices like Apple Watch, remains underexplored. This study aimed to validate HRV measurements obtained from Apple Watch Series 9 and Ultra 2 against the Polar H10 chest strap paired with the Kubios HRV software, which together served as the reference standard. A prospective cohort of 39 healthy adults provided 316 HRV measurements over a 14-day period. Generalized Estimating Equations were used to assess the difference in HRV between devices, accounting for repeated measures. Apple Watch tended to underestimate HRV by an average of 8.31 ms compared to the Polar H10 (p = 0.025), with a mean absolute percentage error (MAPE) of 28.88% and a mean absolute error (MAE) of 20.46 ms. The study found no significant impact of RHR discrepancies on HRV differences (p = 0.156), with RHR showing a mean difference of −0.08 bpm, an MAPE of 5.91%, and an MAE of 3.73 bpm. Equivalence testing indicated that the HRV measurements from Apple Watch did not fall within the pre-specified equivalence margin of ±10 ms. Despite accurate RHR measurements, these findings underscore the need for improved HRV algorithms in consumer wearables and caution in interpreting HRV data for clinical or performance monitoring.
Fiber Bragg Grating Pulse and Systolic Blood Pressure Measurement System Based on Mach–Zehnder Interferometer
Authors: Li Yuanjun , Wang Bo , Liu Shanren , Gao Mengmeng , Li Qianhua , Chen Chao , Guo Qi , Yu Yongsen
Published: September 2024

A fiber Bragg grating (FBG) pulse and systolic blood pressure (SBP) measurement system based on the edge-filtering method is proposed. The edge filter is the Mach–Zehnder interferometer (MZI) fabricated by two fiber couplers with a linear slope of 52.45 dBm/nm. The developed system consists of a broadband light source, an edge filter, fiber Bragg gratings (FBGs), a coarse wavelength-division multiplexer (CWDM), and signal-processing circuits based on a field-programmable gate array (FPGA). It can simultaneously measure pulse pulsations of the radial artery in the wrist at three positions: Cun, Guan and Chi. The SBP can be calculated based on the pulse transit time (PTT) principle. The measurement results compared to a standard blood pressure monitor showed the mean absolute error (MAE) and standard deviation (STD) of the SBP were 0.93 ± 3.13 mmHg. The system meets the requirements of the Association for the Advancement of Medical Instrumentation (AAMI) equipment standards. The proposed system can achieve continuous real-time measurement of pulse and SBP and has the advantages of fast detection speed, stable performance, and no compression sensation for subjects. The system has important application value in the fields of human health monitoring and medical device development.
Applying Ant Colony Optimization to Reduce Tram Journey Times
Authors: Korzeń Mariusz , Gisterek Igor
Published: September 2024

Nature-inspired algorithms allow us to solve many problems related to the search for optimal solutions. One such issue is the problem of searching for optimal routes. In this paper, ant colony optimization is used to search for optimal tram routes. Ant colony optimization is a method inspired by the behavior of ants in nature, which as a group are able to successfully find optimal routes from the nest to food. The aim of this paper is to present a practical application of the algorithm as a tool for public transport network planning. In urban public transport, travel time is crucial. It is a major factor in passengers’ choice of transport mode. Therefore, in this paper, the objective function determining the operation of the algorithm is driving time. Scheduled time, real time and theoretical time are analyzed and compared. The routes are then compared with each other in order to select the optimal solution. A case study involving one of the largest tramway networks in Poland demonstrates the effectiveness of the nature-inspired algorithm. The obtained results allow route optimization by selecting the route with the shortest travel time. Thus, the development of the entire network is also possible. In addition, due to its versatility, the method can be applied to various modes of transport.
A Universal Model for Ultrasonic Energy Transmission in Various Media
Authors: Ma Yufei , Jiang Yunan , Li Chong
Published: September 2024

This study presents a comprehensive model for ultrasonic energy transfer (UET) using a 33-mode piezoelectric transducer to advance wireless sensor powering in challenging environments. One of the advantages of UET is that it is not stoppable by electromagnetic shielding and can penetrate metal. Existing models focus on feasibility and numerical analysis but lack an effective link between input and output power in different media applications. The proposed model fills this gap by incorporating key factors of link loss, including resonant frequency, impedance matching, acoustic coupling, and boundary conditions, to predict energy transfer efficiency more accurately. The model is validated through numerical simulations and experimental tests in air, metal, and underwater environments. An error analysis has shown that the maximum error between theoretical and experimental responses is 3.11% (air), 27.37% (water), and 1.76% (aluminum). This research provides valuable insights into UET dynamics and offers practical guidelines for developing efficient wireless powering solutions for sensors in difficult-to-access or electromagnetically shielded conditions.
Design and Development of Miniature Measuring Instrument for Parachute Cords Dynamic Load for Stepless Parachute Opening
Authors: Liang Wei , Zhao Xin , Wu Pengpeng , Li Yuxin , Lv Shuai
Published: September 2024

Spacecraft recovery technology is crucial in the field of aerospace, in which the parachute plays a key role in slowing down the descent speed of the spacecraft and realizing a smooth landing. In order to construct a dynamically adjustable parachute deployment strategy, it is necessary to measure the parachute dynamic load accurately in real-time. However, the existing sensor measurement scheme makes it difficult to meet the measurement requirements due to its large structure and complex wiring. In order to meet the current demand for real-time measurement of parachute cords dynamic load, a miniature measuring instrument is designed. According to the function and technical requirements of the miniature measuring instrument, the hardware modules of the acquisition system are selected and designed, and the integration debugging and performance optimization of the microcontroller module, A/D sampling module, signal acquisition circuit, and power supply module are carried out. The software of the parachute cords tension acquisition system based on the miniature measuring instrument is developed. The Load Cell is modeled by using SolidWorks 2022 and statically analyzed by using Ansys 2022 R1 Workbench finite element analysis software. Then the final structure of the Load Cell and the pasting position of the strain gauge are determined through the results analysis as well as experimental verification. The hardware module of the signal acquisition system for the miniature measuring instrument is then encapsulated. The force value of the miniature measuring instrument is calibrated and tested many times by using the microcomputer-controlled electronic universal testing machine. The experimental results show that the designed miniature measuring instrument has accurate data, strong stability, and good real-time performance, which meets the demand for real-time accurate measurement of miniature measuring instruments, and can provide reliable data for parachute cords parameter validation and stepless unfolding design.