bluuebunny/crossref_metadata_2025 huggingface dataset:
CMV Retinitis in the Context of SARS-CoV-2 Infection: A Case Study and Comprehensive Review of Viral Interactions
Authors: Stoicescu Emil Robert , Ghenciu Laura Andreea , Iacob Roxana , Ardelean Adina Iuliana , Dăescu Ecaterina , Hațegan Ovidiu Alin , Manolescu Diana , Tudorache Emanuela , Boru Casiana , Dima Mirabela
Published: October 2024

Purpose: Cytomegalovirus (CMV) retinitis is a sight-threatening condition predominantly affecting immunocompromised individuals, such as those with Human Immunodeficiency Virus (HIV)/Acquired Immunodeficiency Syndrome (AIDS). We aimed to present an observational case report on CMV retinitis following Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and to review the literature on the molecular and cellular changes in CMV and SARS-CoV-2 infections and how they may influence each other. Case Description: A 32-year-old man with a history of AIDS presented with decreased vision and ocular pain exacerbated by movement, beginning a day prior. Ocular examination revealed anterior uveitis, corneal endothelial edema, and retinal necrosis in the left eye. CMV retinitis was diagnosed based on positive serologic testing and a low cluster of differentiation 4 (CD4) count, with concurrent SARS-CoV-2 infection detected. Treatment included valganciclovir and topical agents, with a focus on managing CMV complications. This case highlights the potential role of SARS-CoV-2 in reactivating dormant CMV in severely immunocompromised individuals. We also discuss the implications of this interaction for immunocompromised patients, emphasizing the need for vigilant monitoring and personalized treatment strategies. Conclusions: Our case suggests that SARS-CoV-2 may trigger reactivation of CMV infection, leading to bilateral involvement in patients with low CD4 lymphocyte counts, which can result in severe visual impairment. The review discusses the molecular and cellular interactions between CMV and SARS-CoV-2, as well as risk factors, pathophysiology, and diagnostic methods for CMV retinitis, providing recommendations based on the literature findings.
Ceragenins Prevent the Development of Murine Vaginal Infection Caused by Gardnerella vaginalis
Authors: Wnorowska Urszula , Piktel Ewelina , Daniluk Tamara , Paprocka Paulina , Savage Paul B. , Durnaś Bonita , Bucki Robert
Published: October 2024

Background/Objectives: Bacterial vaginosis (BV), an infection caused primarily by Gardnerella vaginalis, is the most prevalent vaginal infection. Although BV is often characterized by an asymptomatic course, it can lead to considerable health complications. Currently, BV therapy choices are limited, and available treatments are complicated by concerns about antibiotic resistance. Ceragenins, which together comprise an innovative class of low molecular-weight, cholic acid-based antibacterial agents, have emerged as potential alternatives to conventional treatments. Methods: This study investigates (i) the antibacterial activity of ceragenins against G. vaginalis in in vitro experimental settings at varied pH, and (ii) the effectiveness and anti-inflammatory properties of CSA-13 in a G. vaginalis-induced bacterial vaginosis animal model. Results and Conclusions: We demonstrate that ceragenins, particularly CSA-13, maintain their antibacterial efficacy throughout pH range of 4.5–7, with the highest activity observed at neutral pH (7.0). Additionally, in an animal model, beneficial effects of ceragenins are attributed to anti-inflammatory properties of these compounds, making these compounds promising agents as potential new treatment options against G. vaginalis-associated vaginal infections.
Head-to-Head Comparison of UHPLC-MS/MS and Alinity C for Plasma Analysis of Risperidone and Paliperidone
Authors: Toja-Camba Francisco José , Hermelo-Vidal Gonzalo , Feitosa-Medeiros Carolina , Vidal-Millares María , Durán-Maseda María José , Fernández-Ferreiro Anxo , Mondelo-García Cristina
Published: October 2024

Background and objectives: Risperidone, a second-generation antipsychotic widely used in the treatment of schizophrenia, requires therapeutic drug monitoring due to its high interindividual variability. UHPLC-MS/MS is considered the gold standard for pharmacokinetic studies owing to its superior sensitivity and specificity, although it involves time-consuming manual sample preparation. In contrast, the Alinity C system, fully automated, simplifies sample processing, but only measures the active moiety (risperidone plus paliperidone). The aim of this study is to compare the performance of UHPLC-MS/MS and the Alinity C system for the determination of risperidone and paliperidone concentrations in plasma. Methods: A total of 115 plasma samples of 115 patients, 92 and 23 under risperidone and paliperidone long-acting treatment, respectively, were analyzed using both methods. Results: A strong correlation for the active moiety (risperidone plus 9-OH-Risperidone) (rs = 0.95) was observed. However, Bland–Altman analysis revealed a mean bias of 0.996 ng/mL, indicating that the Alinity C system slightly overestimates concentrations compared to UHPLC-MS/MS. While there was substantial agreement between methods (κ = 0.72), discrepancies were observed in 16.3% of cases, which could impact clinical decision-making. When analyzing paliperidone separately, the agreement was lower (κ = 0.63), with greater variability observed. Conclusions: These findings suggest that, while the Alinity C system is suitable for routine therapeutic monitoring, UHPLC-MS/MS remains the preferred method in clinical scenarios requiring higher precision, particularly for patients with concentrations near therapeutic thresholds.
Increased MAGE-C Family Gene Expression Levels as a Biomarker of Colon Cancer Through the Demethylation Mechanism
Authors: Almutairi Mikhlid H. , Alsoraie Waad A. , Alrubie Turki M. , Alkhaldi Ahmad S. , Alhajri Nada S. , Alaujan Monira A. , Almutairi Manar H. , Almutairi Bader O.
Published: October 2024

Background/Objectives: Colon cancer (CC) in Saudi Arabia is associated with a high death rate and is commonly identified at a more progressive stage. Therefore, it is critical to identify and characterize potential novel cancer-specific biomarkers to enhance early CC diagnosis. The goal was to assess their potential use as cancer biomarkers for the early detection and improvement of CC treatment. Methods: MAGE-C1, MAGE-C2, and MAGE-C3 family gene expression levels were examined using RT-PCR and qRT-PCR assays in 26 adjacent normal colon (NC) and CC tissue samples from male and female Saudi patients. Using several cell lines and the qRT-PCR technique, epigenetic control was also investigated to determine whether reduced treatment with 5-aza-2′-deoxycytidine, which reduces DNA methyltransferase, can increase the expression of the MAGE-C gene. The expression levels, promoter methylation, and prognostic significance of MAGE-C1, MAGE-C2, and MAGE-C3 genes across various cancers were analyzed using The Cancer Genome Atlas (TCGA) data. Additionally, the prognostic significance of these genes was assessed through Kaplan–Meier survival analysis. Results: The RT-PCR results showed that MAGE-C1, MAGE-C2, and MAGE-C3 gene expressions were significantly higher in the CC and NC tissues. The MAGE-C1 expression level was the highest in CC tissues (p < 0.0001), followed by MAGE-C3 (p = 0.0004) and MAGE-C2 (p = 0.0020) in descending order. The 5-aza-2′-deoxycytidine treatment significantly increased the mRNA expression levels of the MAGE-C1, MAGE-C2, and MAGE-C3 genes in HCT116, Caco-2, MCF-7, and MCF-10A cells. Expression analyses of TCGA samples revealed significant upregulation of these genes in several cancer types, with notable differences between normal, tumor, and metastatic tissues. Promoter methylation indicates hypomethylation in cancerous tissues. Survival analyses show that high expression levels of MAGE-C1 correlate with better prognosis, while MAGE-C3 is associated with poorer outcomes. Conclusions: These results demonstrate that MAGE-C genes are viable prospective biomarkers of CC controlled by hypomethylating drugs, consequently offering a possible treatment target for CC in a specific population.
Design of Experiments to Tailor the Potential of BSA-Coated Peptide Nanocomplexes for Temozolomide/p53 Gene Co-Delivery
Authors: Afonso Inês , Neves Ana R. , Eusébio Dalinda , Albuquerque Tânia , Vivès Eric , Boisguérin Prisca , Santos Adriana O. , Sousa Ângela , Costa Diana
Published: October 2024

Background: Gene therapy can be viewed as a promising/valuable therapeutic approach directed to cancer treatment, including glioblastoma. Concretely, the combination of gene therapy with chemotherapy could increase its therapeutic index due to a synergistic effect. In this context, bovine serum albumin (BSA)-coated temozolomide (TMZ)-peptide (WRAP5)/p53 gene-based plasmid DNA complexes were developed to promote payload co-delivery. Methods: Design of experiments (DoE) was employed to unravel the BSA-coated TMZ-WRAP5/p53 nanocomplexes with the highest potential by considering the nitrogen to phosphate groups ratio (N/P), and the BSA concentration as inputs and the size, polydispersity index, surface charge and p53-based plasmid complexation capacity (CC) as DoE outputs. Results: The obtained quadratic models were statistically significant (p-value < 0.05) with an adequate coefficient of determination, and the correspondent optimal points were successfully validated. The optimal complex formulation had N/P of 1.03, a BSA concentration of 0.08%, a size of approximately 182 nm, a zeta potential of +9.8 mV, and a pDNA CC of 96.5%. The optimal nanocomplexes are approximately spherical. A cytotoxicity assay showed that these BSA-coated TMZ-WRAP5/p53 complexes did not elicit toxicity in normal brain cells, and a hemolysis study demonstrated the hemocompatibility of the complexes. The complexes were stable in cell culture medium and fetal bovine serum and assured pDNA protection and release. Moreover, the optimal BSA-coated complexes were able of gene transcription and promoted a significant inhibition of glioblastoma cell viability. Conclusions: The reported findings instigate the development of future research to evaluate their potential utility to TMZ/p53 co-delivery. The DoE tool proved to be a powerful approach to explore and tailor the composition of BSA-coated TMZ-WRAP5/p53 complexes, which are expected to contribute to the progress toward a more efficient therapy against cancer and, more specifically, against glioblastoma.
Correction: Ibar, J.P. Raising Two More Fundamental Questions Regarding the Classical Views on the Rheology of Polymer Melts. Polymers 2024, 16, 2042
Authors: Ibar Jean Pierre
Published: October 2024

There was an error in the original publication [...]
Impact of Probiotic Fermentation on the Physicochemical Properties of Hemp Seed Protein Gels
Authors: Liu Yipeng , Fei Yingxue , Li Chen , Cheng Jianming , Xue Feng
Published: October 2024

Hemp seed protein isolates (HPI) were used to produce a gel through probiotic fermentation. This study assessed how fermentation time (ranging from 0 to 16 h) affected the physicochemical properties of the HPI gel. The results indicated that gel formation began after 8 h of fermentation, as demonstrated by a pH decrease, an increase in particle size, and the development of aggregation observed through fluorescence and scanning electron microscopy. The gel produced after 16 h of fermentation showed the highest viscosity, storage modulus, and gel strength, attributed to stronger molecular interactions, including non-covalent and covalent crosslinking. However, the gel produced after 12 h of fermentation showed the highest water-holding capacity, and extending the fermentation beyond 12 h caused a decrease in water-holding capacity. Additionally, the subunits tended to form polymers after fermentation, suggesting that gel formation was influenced by both acidification and specific covalent crosslinking. These findings propose that HPI could serve as a viable alternative for developing plant-based gel products.
Enhanced Impact Resistance, Oxygen Barrier, and Thermal Dimensional Stability of Biaxially Processed Miscible Poly(Lactic Acid)/Poly(Butylene Succinate) Thin Films
Authors: Jariyasakoolroj Piyawanee , Kumsang Pramote , Phattarateera Supanut , Kerddonfag Noppadon
Published: October 2024

This study investigates the crystallization, microstructure, and performance of poly(lactic acid)/poly(butylene succinate) (PLA/PBS) thin films processed through blown film extrusion and biaxial orientation (BO) at various blend ratios. Succinic anhydride (SA) was used to enhance interfacial adhesion in PLA-rich blends, while blends near 50/50 formed co-continuous phases without SA. Biaxial stretching and annealing, adjusted according to the crystallization behavior of PLA and PBS, significantly influenced crystallinity, crystallite size, and molecular orientation. Biaxial stretching induced crystallization and ordered chain alignment, particularly at the cold crystallization temperature (Tcc), leading to a 70–80-fold increase in impact resistance compared to blown films. Annealing further enhanced crystallinity, especially at the Tcc of PLA, resulting in larger crystallite sizes. BO films demonstrated reduced thermal shrinkage due to improved PLA crystalline structure, whereas PLA-rich blown films showed higher shrinkage due to PLA’s lower thermal resistance. The SA-miscibilized phase reduced oxygen transmission in blown films, while BO films exhibited higher permeability due to anisotropic crystal orientation. However, the annealing of BO films, especially at high temperature (Tcc of PLA), further lowered oxygen permeability by promoting the crystallization of both PLA and PBS phases. Overall, the combination of SA compatibilization, biaxial stretching, and annealing resulted in substantial improvements in mechanical strength, dimensional stability, and oxygen barrier properties, highlighting the potential of these films for packaging applications.
Molecular Dynamics Simulation of the Viscosity Enhancement Mechanism of P-n Series Vinyl Acetate Polymer–CO2
Authors: Fu Hong , Pan Yiqi , Song Hanxuan , Xing Changtong , Bao Runfei , Song Kaoping , Fu Xindong
Published: October 2024

Carbon dioxide (CO2) drive is one of the effective methods to develop old oil fields with high water content for tertiary oil recovery and to improve the recovery rate. However, due to the low viscosity of pure CO2, it is not conducive to expanding the wave volume of the mixed phase, which leads to difficulty utilizing the residual oil in vertical distribution and a low degree of recovery in the reservoir. By introducing viscosity enhancers, it is possible to reduce the two-phase fluidity ratio, expanding the degree of longitudinal rippling and oil recovery efficiency. It has been proven that the acetate scCO2 tackifier PVE can effectively tackify CO2 systems. However, little research has been reported on the microscopic viscosity enhancement mechanism of scCO2 viscosity enhancers. To investigate the influence of a vinyl acetate (VAc) functional unit on the viscosity enhancement effect of the CO2 system, PVE (Polymer–Viscosity–Enhance, P-3) was used as the parent, the proportion of VAc was changed, and the molecules P-1 and P-2 were designed to establish a molecular dynamics simulation model for the P-n-CO2 system. The molecules in the system under the conditions of 70 °C-10 MPa, 80 °C-10 MPa, and 70 °C-20 MPa were simulated; the viscosity of the system was calculated; and the error between the theoretical and simulated values of the viscosity in the CO2 system was relatively small. The difference between P-n molecular structure and system viscosity was analyzed at multiple scales through polymer molecular dynamics simulations and used the molecular radial distribution function, system density, accessible surface area, radius of gyration, minimum intermolecular distance, and minimum number of intermolecular contacts as indicators. This study aimed to elucidate the viscosity enhancement mechanism, and the results showed that the higher the proportion of VAc introduced into the molecules of P-n-scCO2 viscosities, the larger the molecular amplitude, the larger the effective contact area, and the greater the viscosity of the system. Improvement in the contact efficiency between the ester group on the P-n molecule and CO2 promotes the onset of solvation behavior. This study on the microscopic mechanism of scCO2 tackifiers provides a theoretical approach for the design of new CO2 tackifiers.
Advanced Flexible Wearable Electronics from Hybrid Nanocomposites Based on Cellulose Nanofibers, PEDOT:PSS and Reduced Graphene Oxide
Authors: Carrascosa Ana , Sánchez Jaime S. , Morán-Aguilar María Guadalupe , Gabriel Gemma , Vilaseca Fabiola
Published: October 2024

The need for responsible electronics is leading to great interest in the development of new bio-based devices that are environmentally friendly. This work presents a simple and efficient process for the creation of conductive nanocomposites using renewable materials such as cellulose nanofibers (CNF) from enzymatic pretreatment, poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS), and/or reduced graphene oxide (rGO). Different combinations of CNF, rGo, and PEDOT:PSS were considered to generate homogeneous binary and ternary nanocomposite formulations. These formulations were characterized through SEM, Raman spectroscopy, mechanical, electrical, and electrochemical analysis. The binary formulation containing 40 wt% of PEDOT:PSS resulted in nanocomposite formulations with tensile strength, Young’s modulus, and a conductivity of 70.39 MPa, 3.87 GPa, and 0.35 S/cm, respectively. The binary formulation with 15 wt% of rGO reached 86.19 MPa, 4.41 GPa, and 13.88 S/cm of the same respective properties. A synergy effect was observed for the ternary formulations between both conductive elements; these nanocomposite formulations reached 42.11 S/cm of conductivity and kept their strength as nanocomposites. The 3D design strategy provided a highly conductive network maintaining the structural integrity of CNF, which generated homogenous nanocomposites with rGO and PEDOT:PSS. These formulations can be considered as greatly promising for the next generation of low-cost, eco-friendly, and energy storage devices, such as batteries or electrochemical capacitors.
Impact of Buriti Oil from Mauritia flexuosa Palm Tree on the Rheological, Thermal, and Mechanical Properties of Linear Low-Density Polyethylene for Improved Sustainability
Authors: Leite-Barbosa Odilon , Oliveira Marcelo Ferreira Leão de , Braga Fernanda Cristina Fernandes , Monteiro Sergio Neves , Oliveira Marcia Gomes de , Veiga-Junior Valdir Florêncio
Published: October 2024

Recent advancements highlight the utilization of vegetable oils as additives in polymeric materials, particularly for replacing conventional plasticizers. Buriti oil (BO), extracted from the Amazon’s Mauritia flexuosa palm tree fruit, boasts an impressive profile of vitamins, minerals, proteins, carotenoids, and tocopherol. This study investigates the impact of incorporating buriti oil as a plasticizer in linear low-density polyethylene (LLDPE) matrices. The aim of this research was to evaluate how buriti oil, a bioactive compound, influences the thermal and rheological properties of LLDPE. Buriti oil/LLDPE compositions were prepared via melt intercalation techniques, and the resulting materials were characterized through thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), Fourier-transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), mechanical property testing, and contact angle measurement. The addition of buriti oil was found to act as a processing aid and plasticizer, enhancing the fluidity of LLDPE polymer chains. TGA revealed distinct thermal stabilities for buriti oil/LLDPE under different degradation conditions. Notably, buriti oil exhibited an initial weight loss temperature of 402 °C, whereas that of LLDPE was 466.4 °C. This indicated a minor reduction in the thermal stability of buriti oil/LLDPE compositions. The thermal stability, as observed through DSC, displayed a nuanced response to the oil’s incorporation, suggesting a complex interaction between the oil and polymer matrix. Detailed mechanical testing indicated a marked increase in tensile strength and elongation at break, especially at optimal concentrations of buriti oil. SEM analysis showcased a more uniform and less brittle microstructure, correlating with the enhanced mechanical properties. Contact angle measurements revealed a notable shift in surface hydrophobicity, indicating a change in the surface chemistry. This study demonstrates that buriti oil can positively influence the processability and thermal properties of LLDPE, thus expanding its potential applications as an effective plasticizer.
Organic Bulk–Heterojunction Blends with Vertical Phase Separation for Enhanced Organic Photodetector Performance
Authors: Chen Chih-Ping , Peng Yan-Cheng , Jiang Bing-Huang , Hsu Ming-Wei , Chan Choon Kit , Du He-Yun , Yu Yang-Yen
Published: October 2024

The ternary blending strategy is a fundamental approach that is widely recognized in the field of organic optoelectronics. In our investigation, leveraging the inherent advantages of the ternary component blending methodology, we introduced an innovative design for organic photodetectors (OPDs) aimed at reducing the dark current density (Jd) under reverse bias. This pioneering effort involved combining two distinct conjugated molecules (IT-4F and IEICO-4F) with a conjugated polymer (PM7), resulting in a composite material characterized by a well-defined vertical phase separation. To thoroughly explore device performance variations, we utilized a comprehensive array of analytical techniques, including atomic force microscopy (AFM) cross-section methodologies and Kelvin probe force microscopy (KPFM). Through the optimization of the blend ratio (PM7:IT-4F: IEICO-4F at 1:0.8:0.2), we achieved significant advancements. The resulting OPD demonstrated an exceptional reduction in JD, reaching a remarkably low value of 4.95 × 10−10 A cm−2, coupled with an ultra-high detectivity of 4.95 × 1013 Jones and an outstanding linear dynamic range exceeding 100 dB at 780 nm under a bias of −1V. Furthermore, the attained cutoff frequency reached an impressive 220 kHz, highlighting substantial improvements in device performance metrics. Of particular significance is the successful translation of this technological breakthrough into real-world applications, such as in heart rate sensing, underscoring its tangible utility and expanding its potential across various fields. This demonstrates its practical relevance and underscores its versatility in diverse settings.
Study on a Pseudo-Elastic Model for High-Damping Rubber
Authors: Guo Zhihao , Peng Tianbo
Published: October 2024

With advancements in seismic isolation and damping technology, high-damping rubber (HDR) bearings are now widely used. However, significant gaps remain in HDR-analysis model research, with few studies integrating multiple factors, the Mullins effect, and stiffness hardening for more accurate practical predictions. This study classifies the effective behavior of HDR and examines the stress–strain relationships of different behavioral types using more appropriate equations. Mathematical models were established based on pseudo-elasticity theory, which is an extension of continuum mechanics. Subsequently, parameter functions were developed through parameter determination tests and regression analysis, leading to the completion of the pseudo-elastic model for HDR. Finally, the model’s effectiveness was validated through validation tests. This study finds that behavior classification effectively examines phenomenological-based HDR stress–strain relationships, as distinct behavioral patterns are not adequately captured by a single approach. Incorporating tests to functionalize material parameters complements theoretical models. Additionally, accurately explaining HDR behavior requires considering the Mullins effect and stiffness hardening, influenced by the coupled effects of temperature, strain amplitude, and compressive stress. Consequently, this HDR pseudo-elastic model offers a comprehensive explanation of HDR behavior, including the Mullins effect and stiffness hardening, under various influencing factors based on clear mechanical principles and explicit computational procedures.
Macrophage Immunomodulation and Suppression of Bacterial Growth by Polydimethylsiloxane Surface-Interrupted Microlines’ Topography Targeting Breast Implant Applications
Authors: Negrescu Andreea Mariana , Nistorescu Simona , Bonciu Anca Florina , Rusen Laurentiu , Dumitrescu Luminita Nicoleta , Urzica Iuliana , Cimpean Anisoara , Dinca Valentina
Published: October 2024

Since breast cancer is one of the most common forms of cancer in women, silicone mammary implants have been extensively employed in numerous breast reconstruction procedures. However, despite the crucial role they play, their interaction with the host’s immune system and microbiome is poorly understood. Considering this, the present work investigates the immunomodulatory and bacterial mitigation potential of six textured surfaces, based on linear step-like features with various regular and irregular multiscaled arrangements, in comparison to a flat PDMS surface. We hypothesise that the chosen surface geometries are capable of modulating the cellular response through mechanical interdigitation within the multiscaled surface morphology, independent of the surface chemical properties. Each type of sample was characterised from a physico-chemical and biological points of view and by comparison to the flat PDMS surface. The overall results proved that the presence of linear multiscaled step-like features on the PDMS surface influenced both the surface’s characteristics (e.g., surface energy, wettability, and roughness parameters), as well as the cellular response. Thus, the biological evaluation revealed that, to different degrees, biomaterial-induced macrophage activation can be mitigated by the newly designed microtextured surfaces. Moreover, the reduction in bacteria adherence up to 90%, suggested that the topographical altered surfaces are capable of suppressing bacterial colonisation, therefore demonstrating that in a surgical environment at risk of bacterial contamination, they can be better tolerated.
On Astronomical Materials in Buddhist Scriptures
Authors: Niu Weixing
Published: October 2024

There are many foreign astronomical materials that were preserved in the Chinese translation of Buddhist canons. From the content, these astronomical materials include cosmology theories, lunar mansion systems, calendrical data, etc. These astronomical materials are important evidence for the exchange and dissemination of astronomy between ancient civilizations. This paper aims to sort out and analyze the astronomical materials preserved in the Chinese translation of Buddhist canons, classifying and differentiating the content of astronomy, which was foreign to China, tracing the origins of these astronomical knowledge, discussing their impact on local astronomy in China, and evaluating the preservation form, characteristics, reliability, functionality, and limitations of these astronomical materials. Through the above discussion, this paper will demonstrate the core meaning of the historical view of transcultural transmission of sciences and technology, which is ‘knowledge progresses through dissemination and civilization thrives through communication’.
Analysis of Multi-GNSS Multipath for Parameter-Unified Autocorrelation-Based Mitigation and the Impact of Constellation Shifts
Authors: Xiong Wenhao , Tian Yumiao , Dai Xiaolei , Zhang Qichao , Liang Yibing , Ruan Xiongwei
Published: October 2024

Multipath effects can significantly reduce the accuracy of GNSS precise positioning. Traditional methods, such as sidereal filtering and grid-based approaches, attempt to model and mitigate these errors by leveraging the spatial autocorrelation of multipath based on residuals. However, these methods can only approximately handle spatial autocorrelation data, limiting their effectiveness. This study investigates the spatial cross-correlation of residuals between various GNSS frequency bands, analyzes their covariance function parameters, and evaluates the impact of constellation shifts on long-term multipath mitigation. Based on this, a simplified autocorrelation-based approach utilizing unified covariance parameters for multipath mitigation is proposed, with its efficacy assessed for both short- and long-term applications. The study demonstrates the correlation of multipath effects across various GPS and Galileo frequencies, including GPS L1/L2/L5 and Galileo E1/E5a/E5b/E5ab/E6, by analyzing correlation coefficients. A strong correlation (greater than 0.8) is observed between residuals of closely spaced frequencies, such as E5b and E5ab, despite their frequency differences. Additionally, the covariance parameters of the residuals are found to be consistent across all frequencies for a baseline, suggesting that unified parameters can be applied effectively for spatial autocorrelation-based multipath mitigation without sacrificing performance. The orbit shifts of certain GPS satellites, particularly G02, G20, and G21, result in significant changes in orbital parameters and satellite tracks, reducing the effectiveness of long-term multipath mitigation. However, the impact of GPS orbit shifts can be minimized through periodic model updates or by integrating GPS and Galileo modeling. In experiments, the LSC correction strategy based on a GPS/Galileo combination, utilizing unified parameters, outperforms the grid method based on the GPS/Galileo combination, improving the mean residual variance elimination rate by 11.3% for GPS L1 and 11.4% for Galileo E1. These improvements remain consistent, with rates of 11.3% and 15.7%, respectively, even on DOY 365, which is 327 days after the modeling data were collected.
Hydraulics of Time-Variable Water Surface Slope in Rivers Observed by Satellite Altimetry
Authors: Bauer-Gottwein Peter , Christoffersen Linda , Musaeus Aske , Frías Monica Coppo , Nielsen Karina
Published: October 2024

The ICESat-2 and SWOT satellite earth observation missions have provided highly accurate water surface slope (WSS) observations in global rivers for the first time. While water surface slope is expected to remain constant in time for approximately uniform flow conditions, we observe time varying water surface slope in many river reaches around the globe in the ICESat-2 record. Here, we investigate the causes of time variability of WSSs using simplified river hydraulic models based on the theory of steady, gradually varied flow. We identify bed slope or cross section shape changes, river confluences, flood waves, and backwater effects from lakes, reservoirs, or the ocean as the main non-uniform hydraulic situations in natural rivers that cause time changes of WSSs. We illustrate these phenomena at selected river sites around the world, using ICESat-2 data and river discharge estimates. The analysis shows that WSS observations from space can provide new insights into river hydraulics and can enable the estimation of river discharge from combined observations of water surface elevation and WSSs at sites with complex hydraulic characteristics.
Efficient Semantic Segmentation for Large-Scale Agricultural Nursery Managements via Point Cloud-Based Neural Network
Authors: Liu Hui , Xu Jie , Chen Wen-Hua , Shen Yue , Kai Jinru
Published: October 2024

Remote sensing technology has found extensive application in agriculture, providing critical data for analysis. The advancement of semantic segmentation models significantly enhances the utilization of point cloud data, offering innovative technical support for modern horticulture in nursery environments, particularly in the area of plant cultivation. Semantic segmentation results aid in obtaining tree components, like canopies and trunks, and detailed data on tree growth environments. However, obtaining precise semantic segmentation results from large-scale areas can be challenging due to the vast number of points involved. Therefore, this paper introduces an improved model aimed at achieving superior performance for large-scale points. The model incorporates direction angles between points to improve local feature extraction and ensure rotational invariance. It also uses geometric and relative distance information for better adjustment of different neighboring point features. An external attention module extracts global spatial features, and an upsampling feature adjustment strategy integrates features from the encoder and decoder. A specialized dataset was created from real nursery environments for experiments. Results show that the improved model surpasses several point-based models, achieving a Mean Intersection over Union (mIoU) of 87.18%. This enhances the precision of nursery environment analysis and supports the advancement of autonomous nursery managements.
Severe Convection at Burgas Airport: Case Study 17 September 2022
Authors: Kostashki Bilyana , Penchev Rosen , Guerova Guergana
Published: October 2024

Convection monitoring and forecasting are crucial for air traffic management as they can lead to the development of intense thunderstorms and hazards such as severe turbulence and icing, lightning activity, microbursts and hail that affect aviation safety. The airport of Burgas is located in southeast Bulgaria on the Black Sea coast and occurrences of intense thunderstorms are mainly observed in the warm season between May and September. This work presents an analysis of severe convection over southeast Bulgaria on 17 September 2022. In the late afternoon, a gust front was formed that reached the Burgas airport with a wind speed exceeding 45 m/s, the record for the past 50 years, damaging the instrument landing system of the airport. To analyse the severe weather conditions, we combine state-of-the-art observations from satellite and radar with the upper-air sounding and surface. The studied period was dominated by the presence of a very unstable air mass over southeast Bulgaria ahead of the atmospheric front. As convection developed and moved east towards Burgas, it had four characteristics of severe deep convection, including gravitational waves at the overshooting cloud top, a cold U-shape, a flanking line and a cloud top temperature below −70 °C. The positive integrated water vapour (IWV) rate of change preceded the lightning activity peak by 30 min. Analysis of integrated vapour transport (IVT) gives higher values by a factor of two compared to climatology associated with the atmospheric river covering the eastern Mediterranean sea.
Predictive Modelling of Land Cover Changes in the Greater Amanzule Peatlands Using Multi-Source Remote Sensing and Machine Learning Techniques
Authors: Amoakoh Alex Owusu , Aplin Paul , Rodríguez-Veiga Pedro , Moses Cherith , Alonso Carolina Peña , Cortés Joaquín A. , Delgado-Fernandez Irene , Kankam Stephen , Mensah Justice Camillus , Nortey Daniel Doku Nii
Published: October 2024

The Greater Amanzule Peatlands (GAP) in Ghana is an important biodiversity hotspot facing increasing pressure from anthropogenic land-use activities driven by rapid agricultural plantation expansion, urbanisation, and the burgeoning oil and gas industry. Accurate measurement of how these pressures alter land cover over time, along with the projection of future changes, is crucial for sustainable management. This study aims to analyse these changes from 2010 to 2020 and predict future scenarios up to 2040 using multi-source remote sensing and machine learning techniques. Optical, radar, and topographical remote sensing data from Landsat-7, Landsat-8, ALOS/PALSAR, and Shuttle Radar Topography Mission derived digital elevation models (DEMs) were integrated to perform land cover change analysis using Random Forest (RF), while Cellular Automata Artificial Neural Networks (CA-ANNs) were employed for predictive modelling. The classification model achieved overall accuracies of 93% in 2010 and 94% in both 2015 and 2020, with weighted F1 scores of 80.0%, 75.8%, and 75.7%, respectively. Validation of the predictive model yielded a Kappa value of 0.70, with an overall accuracy rate of 80%, ensuring reliable spatial predictions of future land cover dynamics. Findings reveal a 12% expansion in peatland cover, equivalent to approximately 6570 ± 308.59 hectares, despite declines in specific peatland types. Concurrently, anthropogenic land uses have increased, evidenced by an 85% rise in rubber plantations (from 30,530 ± 110.96 hectares to 56,617 ± 220.90 hectares) and a 6% reduction in natural forest cover (5965 ± 353.72 hectares). Sparse vegetation, including smallholder farms, decreased by 35% from 45,064 ± 163.79 hectares to 29,424 ± 114.81 hectares. Projections for 2030 and 2040 indicate minimal changes based on current trends; however, they do not consider potential impacts from climate change, large-scale development projects, and demographic shifts, necessitating cautious interpretation. The results highlight areas of stability and vulnerability within the understudied GAP region, offering critical insights for developing targeted conservation strategies. Additionally, the methodological framework, which combines optical, radar, and topographical data with machine learning, provides a robust approach for accurate and detailed landscape-scale monitoring of tropical peatlands that is applicable to other regions facing similar environmental challenges.
CCE-OMBOC: A Simple and Efficient Constant-Envelope Technology for Multicarrier Navigation Modulation by Clipping
Authors: Deng Lingyu , Yang Yikang , Qian Xingyou , Ma Jiangang , Feng Yanxiang , Li Hengnian
Published: October 2024

Multicarrier navigation modulation is a trend within next-generation global navigation satellite systems (GNSS) aiming to enhance navigation performance, but it forces amplifiers to work in nonsaturation zones, resulting in low power efficiency. This paper presents constant-envelope multiplexing (CEM) based on clipping to overcome the low transmission efficiency of orthogonal multi-binary offset carriers (OMBOCs). The clip constant-envelope OMBOC (CCE-OMBOC) features a hard limit for the original OMBOC signal, and its cross-correlation function (CCF) has a fixed ratio with the CCF of the original OMBOC. Thus, the clipping process has no adverse effect on navigation performance. Additionally, the expression of transmission and multiplexing efficiency is presented according to OMBOC’s amplitude distribution. A low sampling rate is suggested for the CCE-OMBOC, which reduces the cost of signal generation. For OMBOC, the CCE-OMBOC provides multiplexing efficiency comparable to that of constant-envelope multiplexing via intermodulation construction (CEMIC). CCE-OMBOC has a straightforward generation process; in contrast, the complexity of CEMIC rises significantly with increasing subcarriers. Moreover, the CCE-OMBOC is a multicarrier CEM modulation tool that has good tracking performance and excellent compatibility. The greater the number of subcarriers, the more navigation services and the higher the navigation data rate. The CCE-OMBOC can be used in next-generation GNSS and integrated communication and navigation systems.
Recovering Bathymetry Using BP Neural Network Combined with Modified Gravity–Geologic Method: A Case Study in the South China Sea
Authors: Chen Xiaodong , Zhong Min , Sun Mingzhi , An Dechao , Feng Wei , Yang Meng
Published: October 2024

The gravity–geologic method (GGM) is widely used for bathymetric predictions. However, the conventional GGM cannot be applied in regions without actual bathymetric data. The modified gravity–geologic method (MGGM) enhances the accuracy of bathymetric models by supplementing short-wavelength gravity anomalies with an a priori bathymetric model, but it overlooks the significance of actual bathymetric data in the prediction process. In this study, we used the BP neural network (BPNN), incorporating shipborne depth soundings and coastline data as zero-depth estimates combined with the MGGM to produce a bathymetric model (BPGGM_BAT) for the South China Sea (105°E–122°E, 0°N–26°N). The results indicate that the BPGGM_BAT model decreases the root-mean-square (RMS) of bathymetry differences from 154.33 m to approximately 140.43 m relative to multibeam depth data. Additionally, the RMS differences between the BPGGM_BAT model and multibeam depth data show further improvements of 19.63%, 20.10%, and 19.54% when compared with the recently released SRTM15_V2.6, GEBCO_2022, and topo_V27.1 models, respectively. The precision of the BPGGM_BAT model is comparable to that of the SDUST2023BCO model, as verified using multibeam depth data in open sea regions. The BPGGM_BAT model outperforms existing models with RMS differences of 8.54% to 32.66%, as verified using Electronic Navigational Chart (ENC) bathymetric data in the regions around the Zhongsha and Nansha Islands. A power density analysis suggests that the BPGGM_BAT model is superior to the MGGM_BAT model for predicting seafloor topography within wavelengths shorter than 15 km, and its performance is closely consistent with that of the topo_V27.1 and SDUST2023BCO models. Overall, this integrated method demonstrates significant potential for improving the accuracy of bathymetric predictions.
A Static Sign Language Recognition Method Enhanced with Self-Attention Mechanisms
Authors: Wang Yongxin , Jiang He , Sun Yutong , Xu Longqi
Published: October 2024

For the current wearable devices in the application of cross-diversified user groups, it is common to face the technical difficulties of static sign language recognition accuracy attenuation, weak anti-noise ability, and insufficient system robustness due to the differences in the use of users. This paper proposes a novel static sign language recognition method enhanced by a self-attention mechanism. The key features of sign language gesture classification are highlighted by the weight function, and then the self-attention mechanism is combined to pay more attention to the key features, and the convolutional neural network is used to extract the features and classify them, which realizes the accurate recognition of different types of static sign language under standard gestures and non-standard gestures. Experimental results reveal that the proposed method achieves an average accuracy of 99.52% in the standard static sign language recognition task when tested against the standard 36 static gestures selected within the reference American Sign Language dataset. By imposing random angular bias conditions of ±(0°–9°] and ±(9°–18°], the average recognition rates in this range were 98.63% and 86.33%. These findings indicate that, compared to existing methods, the proposed method not only maintains a high recognition rate for standard static gestures but also exhibits superior noise resistance and robustness, rendering it suitable for static sign language recognition among diverse user populations.
Localized Bearing Fault Analysis for Different Induction Machine Start-Up Modes via Vibration Time–Frequency Envelope Spectrum
Authors: Ruiz-Sarrio Jose E. , Antonino-Daviu Jose A. , Martis Claudia
Published: October 2024

Bearings are the most vulnerable component in low-voltage induction motors from a maintenance standpoint. Vibration monitoring is the benchmark technique for identifying mechanical faults in rotating machinery, including the diagnosis of bearing defects. The study of different bearing fault phenomena under induction motor transient conditions offers interesting capabilities to enhance classic fault detection techniques. This study analyzes the low-frequency localized bearing fault signatures in both the inner and outer races during the start-up and steady-state operation of inverter-fed and line-started induction motors. For this aim, the classic vibration envelope spectrum technique is explored in the time–frequency domain by using a simple, resampling-free, Short Time Fourier Transform (STFT) and a band-pass filtering stage. The vibration data are acquired in the motor housing in the radial direction for different load points. In addition, two different localized defect sizes are considered to explore the influence of the defect width. The analysis of extracted low-frequency characteristic frequencies conducted in this study demonstrates the feasibility of detecting early-stage localized bearing defects in induction motors across various operating conditions and actuation modes.
A Nonlinear Suspension Road Roughness Recognition Method Based on NARX-PASCKF
Authors: Qian Jiahao , Li Yinong , Zheng Ling , Wu Huan , Jin Yanlin , Yu Linhong
Published: October 2024

Road roughness significantly impacts vehicle safety and dynamic responses. For nonlinear suspension systems, the nonlinear characteristics often make it challenging for estimators to identify the actual road roughness accurately. This paper proposes a hybrid road roughness identification algorithm based on nonlinear auto-regressive with exogenous inputs (NARX) and a process noise adaptive square root cubature Kalman filter (PASCKF) to address this issue. Driven by vehicle acceleration data, an NARX-based road roughness identification system is constructed to mitigate the model uncertainties. Furthermore, a hybrid strategy is proposed. On the one hand, the accurate road roughness estimated by the NARX is converted into process noise covariance, enhancing the estimator’s accuracy and convergence rate. Another switching strategy is proposed to optimize the non-convergence issues of the PASCKF. Finally, simulation and actual vehicle experiment data demonstrate that this approach offers superior identification accuracy and adaptability compared to the standalone SCKF algorithm.
Neural Network Adaptive Inverse Control of Flexible Joint Space Manipulator Considering the Influence of Gravity
Authors: Li Shaoqing , Meng Lingcong , Fang Kai , Liu Fucai
Published: October 2024

With the aim of correcting the problem of trajectory tracking control of a flexible joint space manipulator in environments with different gravity, a neural network adaptive inverse control algorithm based on singular perturbation theory is proposed to resist the disturbance caused by system uncertainty. Firstly, the dynamic model of a flexible joint space manipulator with the influence of gravity is established, and then the system is divided into a fast subsystem and a slow subsystem using singular perturbation theory. The velocity feedback control rate is designed for the fast subsystem to suppress the elastic vibration caused by the joint flexibility. For the slow subsystem, the uncertain term and known term are separated by the inverse control algorithm, where the uncertain term is approximated online by the RBF neural network, and the robust control rate is designed to compensate for the approximation error. The simulation results show that the control method can not only effectively reduce the high-frequency vibration caused by the flexible joint but also resist the system disturbance so that a good track control effect is achieved.