bluuebunny/crossref_metadata_2025 huggingface dataset:
Denoising Phase-Unwrapped Images in Laser Imaging via Statistical Analysis and DnCNN
Authors: Xie Yibo , Cheng Jin , Zhou Shun , Fan Qing , Jia Yue , Xiao Jingjin , Liu Weiguo
Published: November 2024

Three-dimensional imaging plays a crucial role at the micro-scale in fields such as precision manufacturing and materials science. However, image noise significantly impacts the accuracy of point cloud reconstruction, making image denoising techniques a widely discussed topic. Statistical analysis of laser imaging noise has led to the conclusion that logarithmically transformed noise follows a Gumbel distribution. A corresponding neural network training set was developed to address the challenges of difficult data collection and the scarcity of phase-unwrapped image datasets. Building on this foundation, a phase-unwrapped image denoising method based on the Denoising Convolutional Neural Network (DnCNN) is proposed. This method aims to achieve three-dimensional filtering by performing two-dimensional image denoising. Experimental results show a significant reduction in the Cloud-to-Mesh Distance (C2M) statistics of the corresponding point clouds before and after planar filtering. Specifically, the statistic at 97.5% of the 2σ principle decreases from 0.8782 mm to 0.3384 mm, highlighting the effectiveness of the filtering algorithm in improving the planar fit. Moreover, the DnCNN method exhibits exceptional denoising performance when applied to real-world target data, such as plaster statues with complex depth variations and PCBs made from different materials, thereby enhancing accuracy and reliability in point cloud reconstruction. This study provides valuable insights into phase-unwrapped image noise suppression in laser imaging, particularly in micro-scale applications where precision is critical.
Effect of Hot Junction Size on the Temperature Measurement of Proton Exchange Membrane Fuel Cells Using NiCr/NiSi Thin-Film Thermocouple Sensors
Authors: Guo Huijin , Liu Zhihui , Guo Tengda , Sun Yi , Shen Kai , Wang Bi , Cheng Yongjun , Wang Yuming , Ma Tiancai , Wang Zixi , Ding Wanyu
Published: November 2024

In the process of using thin-film thermocouples for contact measurement of the reaction temperature in proton exchange membrane fuel cells (PEMFC), the impact of thin-film thermocouple volume on the system’s reaction temperature field variation, reaction efficiency, and the lifespan of thermocouples under these conditions is not thoroughly studied. Using magnetron sputtering technology, NiCr/NiSi thin-film thermocouples (NiCr/NiSi TFTCs) with different junction sizes were fabricated on the proton exchange membrane (PEM). These NiCr/NiSi TFTCs exhibit excellent compactness, with thickness and planar dimensions in the micrometer range. When PEMFCs are equipped with built-in NiCr/NiSi TFTCs of different hot junction sizes, the time required for the system to reach a steady state varies with the size of the hot junction, with smaller hot junction sizes reaching a steady state more quickly. In a 500-h continuous operation test, the failure rates of NiCr/NiSi TFTCs also vary based on the hot junction size. Both smaller and larger hot junction sizes have relatively higher failure rates, whereas medium-sized junctions have a lower failure rate. These extensive and repetitive comparative experiments provide significant reference value for the size design of TFTCs operating inside PEMFCs, promoting both industrial production and scientific research.
An Image Processing Approach to Quality Control of Drop-on-Demand Electrohydrodynamic (EHD) Printing
Authors: Tawhari Yahya , Shukla Charchit , Ren Juan
Published: November 2024

Droplet quality in drop-on-demand (DoD) Electrohydrodynamic (EHD) inkjet printing plays a crucial role in influencing the overall performance and manufacturing quality of the operation. The current approach to droplet printing analysis involves manually outlining/labeling the printed dots on the substrate under a microscope and then using microscope software to estimate the dot sizes by assuming the dots have a standard circular shape. Therefore, it is prone to errors. Moreover, the dot spacing information is missing, which is also important for EHD DoD printing processes, such as manufacturing micro-arrays. In order to address these issues, the paper explores the application of feature extraction methods aimed at identifying characteristics of the printed droplets to enhance the detection, evaluation, and delineation of significant structures and edges in printed images. The proposed method involves three main stages: (1) image pre-processing, where edge detection techniques such as Canny filtering are applied for printed dot boundary detection; (2) contour detection, which is used to accurately quantify the dot sizes (such as dot perimeter and area); and (3) centroid detection and distance calculation, where the spacing between neighboring dots is quantified as the Euclidean distance of the dot geometric centers. These stages collectively improve the precision and efficiency of EHD DoD printing analysis in terms of dot size and spacing. Edge and contour detection strategies are implemented to minimize edge discrepancies and accurately delineate droplet perimeters for quality analysis, enhancing measurement precision. The proposed image processing approach was first tested using simulated EHD printed droplet arrays with specified dot sizes and spacing, and the achieved quantification accuracy was over 98% in analyzing dot size and spacing, highlighting the high precision of the proposed approach. This approach was further demonstrated through dot analysis of experimentally EHD-printed droplets, showing its superiority over conventional microscope-based measurements.
Bis(tricyclic) Aromatic Enes That Exhibit Efficient Fluorescence in the Solid State
Authors: Shimizu Masaki , Nishimura Kenta , Mineyama Mizuki , Terao Rin , Sakurai Tsuneaki , Sakaguchi Hiroshi
Published: November 2024

We report herein that bis(tricyclic) aromatic enes (BAEs) consisting of 6-6-6-membered frameworks such as acridine, xanthene, thioxanthene, and thioxanthene-S,S-dioxide act as a new class of organic luminophores that exhibit blue-to-green fluorescence in the solid state and in polymer film with good to excellent quantum yields. The BAEs were prepared by the palladium-catalyzed double cross-coupling reaction of phenazastannines or 10,10-dimethyl-10H-phenothiastannin with 9-(dibromomethylene)xanthene, 9-(dibromomethylene)thioxanthene, or 9-(dibromomethylene)-9H-thioxanthene-10,10-dioxide. Microcrystals or powder samples of the BAEs exhibited brilliant fluorescence with good to high quantum yields (Φ = 0.45–0.88). Furthermore, more efficient emission of blue-to-green light (Φ = 0.59–0.91) was observed for the BAEs dispersed in the poly(methyl methacrylate) (PMMA) films. Density functional theory (DFT) calculations suggest that the photo-absorption of the (thio)xanthene moiety-containing BAEs proceeds via π–π* transitions, whereas the optical excitation of 10,10-dioxido-9H-thioxanthene moiety-containing BAEs involves an intramolecular charge transfer from the acridine/thioxanthene part to the electron-accepting 10,10-dioxido-9H-thioxanthene moiety.
Formononetin Exerts Neuroprotection in Parkinson’s Disease via the Activation of the Nrf2 Signaling Pathway
Authors: Wang Xiaotong , Kang Nianxin , Liu Ying , Xu Guojie
Published: November 2024

Parkinson’s disease (PD) is a prevalent neurodegenerative disease for which no effective treatment currently exists. In this study, we identified formononetin (FMN), a neuroprotective component found in herbal medicines such as Astragalus membranaceus and Glycyrrhiza uralensis, as a potential agent targeting multiple pathways involved in PD. To investigate the anti-PD effects of FMN, we employed Caenorhabditis elegans (C. elegans) PD models, specifically the transgenic strain NL5901 and the MPP(+)-induced strain BZ555, to investigate the effects of FMN on the key pathological features of PD, including dyskinesia, dopamine neuron damage, and reactive oxygen species (ROS) accumulation. The MPP(+)-induced SH-SY5Y cell PD model was utilized to evaluate the effects of FMN on cell viability, ROS accumulation, and mitochondrial dysfunction. The signaling pathway induced by FMN was analyzed using transcriptomic techniques and subsequently validated in vitro. Our results indicate that FMN significantly reduced ROS accumulation and improved both dopaminergic neuron vitality and dyskinesia in the C. elegans PD models. In the cell PD model, FMN significantly reduced ROS accumulation and enhanced mitochondrial membrane potential (MMP) and cell viability. A transcriptomic analysis suggested that the effects of FMN are associated with Nrf2 activation. Furthermore, ML385, a specific Nrf2 inhibitor, blocked the beneficial effects of FMN in vitro, indicating that FMN ameliorates dyskinesia and protects dopaminergic neurons through Nrf2 signaling pathway activation. In addition, the effects of FMN on ameliorating dyskinesia and protecting dopamine neurons were comparable to those of the Nrf2 agonist of sulforaphane (SFN) in vivo. The results of this study confirm that FMN exerts significant anti-PD effects primarily through the Nrf2 signaling pathway. These findings provide crucial insights for the development of anti-PD therapies.
Key Proteins in Rat Cerebral Cortex: Application of Cornu aspersum Extract as a Neuroprotective Agent in Alzheimer’s Type Dementia
Authors: Atanasov Ventseslav , Velkova Lyudmila , Tancheva Lyubka , Dolashki Aleksandar , Kalfin Reni , Dolashka Pavlina
Published: November 2024

Alzheimer’s disease (AD) is the most widespread neurodegenerative disorder. Recently, it was found that mucus extract from Cornu aspersum has beneficial effects on memory and cognitive processes in a rat scopolamine model of AD. The present study elucidated the mechanisms of action of standardized mucus snail extract (SE) enriched with a fraction above 20 kDa on Alzheimer-type dementia in rats. Using proteomic analysis on two-dimensional polyacrylamide gel electrophoresis (2D–PAGE) on rat cortex extracts, we compared protein expression in both groups: the first group was treated intraperitoneally with scopolamine (Sco, 2 mg/kg, 11 days) and the second (Sco + SE) group was treated intraperitoneally with Sco (Sco, 2 mg/kg) and protected by SE (0.5 mL/100 g bw) applied daily orally for 11 days. Brain cortex was separated and the expressions of various proteins related to memory and cognitive functions were identified. We found that the expression of Ubiquitin carboxyl-terminal hydrolase isozyme L1, Calbindin, Vacuolar ATP synthase catalytic subunit A, Tropomyosin beta chain, 14-3-3 zeta/delta, Kinesin-1 heavy chain, and Stathmin-4 significantly differs in SE-protected rats as compared to dement animals treated only by Sco, and these brain proteins might be potential therapeutic targets for Alzheimer’s-type dementia treatment.
Psychosocial Factors Influencing Breastmilk Production in Mothers After Preterm Birth: The Role of Social Support in Early Lactation Success—A Cross-Sectional Study
Authors: Krawczyk Aleksandra , Czerwińska-Osipiak Agnieszka , Szablewska Anna Weronika , Rozmarynowska Wiktoria
Published: November 2024

Background: Preterm birth is a major global health issue, associated with increased neonatal morbidity and mortality. Mothers of preterm infants face unique challenges, particularly with regard to lactation, due to the complexities of preterm neonatal care. Social support has been recognized as a factor in promoting successful breastfeeding, especially in vulnerable groups such as mothers of preterm infants. Objective: This study aimed to explore the psychosocial factors influencing breastfeeding in mothers following preterm birth, with a particular focus on the role of social support in early lactation success. Methods: A cross-sectional observational study was conducted between December 2022 and March 2023 at a tertiary referral hospital in Poland. The study included 130 women (71 mothers of preterm infants and 59 mothers of full-term infants) in the early postpartum period. Data were collected through a self-administered questionnaire and the Polish version of the Berlin Social Support Scales (BSSS). Lactation success was assessed based on the mother’s ability to initiate and maintain breastfeeding or expressed milk production. Statistical analyses included Mann–Whitney U tests, Pearson’s Chi-Square, and logistic regression to determine the association between social support and lactation outcomes. Results: The study revealed that mothers of preterm infants exhibited a greater need for social support compared with those who delivered at term. Social support, particularly perceived emotional and practical support, appeared to be significantly associated with successful early lactation. Women who received adequate social support were more likely to initiate breastfeeding early and maintain lactation. Conclusions: Psychosocial factors, particularly social support, play a critical role in the success of lactation among mothers of preterm infants. These findings underscore the need for comprehensive support systems for mothers of preterm infants to promote breastfeeding and improve neonatal health outcomes.
Propionic Acid Impact on Multiple Sclerosis: Evidence and Challenges
Authors: Lorefice Lorena , Zoledziewska Magdalena
Published: November 2024

Accumulating evidence suggests that multiple sclerosis (MS) is an environmentally influenced disorder with contributions from life-time exposure to factors including Epstein–Barr virus infection or shifts in microbiome, diet and lifestyle. One suggested factor is a deficiency in propionic acid, a short-chain fatty acid produced by gut bacteria that may contribute to the disease pathology both in animal models and in human cases of MS. Propionate appears to exert beneficial effects on the immune, peripheral and central nervous systems of people with MS (pwMS), showing immunoregulatory, neuroprotective and neurogenerative effects. These functions are crucial, given that MS is characterized by immune-mediated damage of myelin in the central nervous system. Accordingly, propionate supplementation or a modulated increase in its levels through the microbiome and diet may help counteract the pro-inflammatory state in MS by directly regulating immune system and/or by decreasing permeability of gut barrier and blood–brain barrier. This could potentially improve outcomes when used with immune-modulating therapy. However, while its broad effects are promising, further large clinical trials are necessary to evaluate its efficacy and safety in pwMS and clarify its role as a complementary therapeutic strategy. This review provides a comprehensive analysis of the evidence, challenges and limitations concerning propionic acid supplementation in MS.
Association of Low Protein-to-Carbohydrate Energy Ratio with Cognitive Impairment in Elderly Type 2 Diabetes Patients
Authors: Pujol Antelm , Sanchis Pilar , Tamayo María I. , Godoy Samantha , Andrés Pilar , Speranskaya Aleksandra , Espino Ana , Estremera Ana , Rigo Elena , Amengual Guillermo J. , Rodríguez Manuel , Ribes José Luis , Gomila Isabel , Grases Félix , González-Freire Marta , Masmiquel Lluís
Published: November 2024

Background/Objectives: The relationship between macronutrient intake and cognitive decline in older adults with type 2 diabetes mellitus (T2DM) remains underexplored. Methods: This cross-sectional study aimed to evaluate the association between the protein-to-carbohydrate energy ratio (%E:P) and cognitive impairment among 192 elderly T2DM patients. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) and the Self-Administered Gerocognitive Exam (SAGE), while dietary intake data, including (%E:P), was gathered using a validated semi-quantitative food frequency questionnaire. Results: Participants had a mean age of 71 ± 6 years, 46.4% were female, and the median BMI was 30 ± 4 kg/m2. After adjusting for confounding variables, patients in the highest (%E:P) tertile showed significantly higher MoCA and SAGE scores compared to those in the lowest tertile (p < 0.005). We identified an optimal (%E:P) threshold of 0.375 for predicting cognitive impairment, with a sensitivity of 53% and specificity of 64%. Conclusions: These findings suggest that a lower (%E:P) ratio may be a risk factor for cognitive impairment in elderly T2DM patients. Monitoring this ratio may serve as an early detection tool for cognitive deterioration. Moreover, current protein intake recommendations for older adults with T2DM may be insufficient to prevent cognitive impairment. Further research is needed to establish optimal dietary guidelines for this population.
The Relationship Between Dietary Patterns, Cognition, and Cardiometabolic Health in Healthy, Older Adults
Authors: Simpson Felicity M. , Wade Alexandra , Stanford Ty , Mellow Maddison L. , Collins Clare E. , Murphy Karen J. , Keage Hannah A. D. , Hunter Montana , Ware Nicholas , Barker Daniel , Smith Ashleigh E. , Karayanidis Frini
Published: November 2024

Background: Healthy dietary patterns can support the maintenance of cognition and brain health in older age and are negatively associated with cardiometabolic risk. Cardiometabolic risk factors are similarly important for cognition and may play an important role in linking diet to cognition. Aim: This study aimed to explore the relationship between dietary patterns and cognition and to determine whether cardiometabolic health markers moderate these relationships in older adulthood. Design: A cross-sectional analysis of observational data from the baseline of the ACTIVate study. Participants: The cohort included 426 cognitively normal adults aged 60–70 years. Methods: The Australian Eating Survey (AES) Food Frequency Questionnaire was used to collect data on usual dietary intake, along with additional questions assessing intake of dietary oils. Principal component analysis (PCA) was applied to reduce the dimensionality of dietary data. Cardiometabolic risk was quantified using the metabolic syndrome severity score (MetSSS). Tests from the Cambridge Neuropsychological Test Automated Battery (CANTAB) were used to derive composite scores on four cognitive domains: processing speed, executive function, short-term memory, and long-term memory. Results: Three dietary patterns were identified using PCA: a plant-dominant diet, a Western-style diet, and a meat-dominant diet. After controlling for age, sex, total years of education, energy intake, and moderate-to-vigorous physical activity (MVPA), there was a small, negative association between the meat-dominant diets and long-term memory. Subsequent moderation analysis indicated that MetSSS significantly moderated this relationship. Conclusions: Findings highlight the link between diet, cardiometabolic health, and cognitive function in older, cognitively healthy adults. However, longitudinal studies are needed to confirm observations and evaluate the dynamics of diet, cardiometabolic health, and cognitive function over time.
Interrelation Between Pathoadaptability Factors and Crispr-Element Patterns in the Genomes of Escherichia coli Isolates Collected from Healthy Puerperant Women in Ural Region, Russia
Authors: Mikhaylova Yulia , Tyumentseva Marina , Karbyshev Konstantin , Tyumentsev Aleksandr , Slavokhotova Anna , Smirnova Svetlana , Akinin Andrey , Shelenkov Andrey , Akimkin Vasiliy
Published: November 2024

Escherichia coli is a commensal and opportunistic bacterium widely distributed around the world in different niches including intestinal of humans and animals, and its extraordinary genome plasticity led to the emergence of pathogenic strains causing a wide range of diseases. E. coli is one of the monitored species in maternity hospitals, being the main etiological agent of urogenital infections, endometriosis, puerperal sepsis, and neonatal diseases. This study presents a comprehensive analysis of E. coli isolates obtained from the maternal birth canal of healthy puerperant women 3–4 days after labor. According to whole genome sequencing data, 31 sequence types and six phylogenetic groups characterized the collection containing 53 isolates. The majority of the isolates belonged to the B2 phylogroup. The data also includes phenotypic and genotypic antibiotic resistance profiles, virulence factors, and plasmid replicons. Phenotypic and genotypic antibiotic resistance testing did not demonstrate extensive drug resistance traits except for two multidrug-resistant E. coli isolates. The pathogenic factors revealed in silico were assessed with respect to CRISPR-element patterns. Multiparametric and correlation analyses were conducted to study the interrelation of different pathoadaptability factors, including antimicrobial resistance and virulence genomic determinants carried by the isolates under investigation. The data presented will serve as a valuable addition to further scientific investigations in the field of bacterial pathoadaptability, especially in studying the role of CRISPR/Cas systems in the E. coli genome plasticity and evolution.
Foodborne Pathogens Across Different Food Matrices in Sicily (Southern Italy)
Authors: Blanda Valeria , Giacchino Ilenia , Vaglica Valeria , Milioto Vanessa , Migliore Sergio , Di Bella Santina , Gucciardi Francesca , Bongiorno Carmelo , Chiarenza Giuseppina , Cardamone Cinzia , Mancuso Isabella , Scatassa Maria Luisa , Cannella Vincenza , Guercio Annalisa , Purpari Giuseppa , Grippi Francesca
Published: November 2024

Foodborne diseases result from the consumption of foods contaminated with pathogens or their toxins and represent a serious public health problem worldwide. This study aimed to assess the presence of Rotavirus (RoV), Adenovirus (AdV), Norovirus (NoV), Hepatitis A and Hepatitis E viruses (HAV and HEV, respectively), Toxoplasma gondii, Coxiella burnetii and Leptospira spp. across various food matrices in Sicily. The analysis concerned 504 samples, including mussels, farmed meat, game meat, vegetables and bulk milk. Following appropriate pre-treatment, acid nucleic extraction was carried out and amplification of pathogen nucleic acids was carried out by molecular methods. The mussels tested positive for NoVs (3/51, 5.9%) and farm meat resulted positive for T. gondii (1/34, 2.9%). The game offal samples tested positive for HEV, which was detected in 17 out of 222 samples (7.7%), and T. gondii (18/318, 5.7%) and Leptospira spp. (2/318, 0.6%). The milk samples tested positive for C. burnetii (15/85, 17.6%), T. gondii (2/85, 2.4%) and Leptospira spp. (1/85, 1.2%). This study highlights the variability in the risk of contamination of different food matrices, confirming the importance of vigilance in the consumption of potentially contaminated food products.
Discovery of Novel Thanatin-like Antimicrobial Peptides from Bean Bug Riptortus pedestris
Authors: Panteleev Pavel V. , Teplovodskaya Julia S. , Utkina Anastasia D. , Smolina Anastasia A. , Kruglikov Roman N. , Safronova Victoria N. , Bolosov Ilia A. , Korobova Olga V. , Borzilov Alexander I. , Ovchinnikova Tatiana V.
Published: November 2024

Background: Endogenous antimicrobial peptides (AMPs) are evolutionarily ancient molecular factors of innate immunity that play a key role in host defense. The study of the diversity of animal defense peptides has important applications in the context of the growing global antimicrobial resistance. Methods: In this study using a transcriptome mining approach, we found three novel thanatin-like β-hairpin AMPs in the bean bug Riptortus pedestris, named Rip-2, Rip-3, and Rip-4. The peptides were expressed in the bacterial system, and their antimicrobial activities were evaluated both in vitro and in vivo. Results: Homologs of the discovered AMPs are widely distributed among different members of the infraorder Pentatomomorpha. Rip-2 was shown to have the most similar structure and LptA-targeting mechanism of action to those of thanatin, but the former peptides demonstrated a higher activity against key Gram-negative ESKAPE pathogens and also displayed a significant efficacy in a lethal model of septicemia caused by E. coli in mice at daily doses greater than 5 mg/kg. In contrast, Rip-3 and Rip-4 peptides caused bacterial membrane damage, did not induce bacterial resistance, and exhibited a strong selectivity against Bacillus and Mycobacterium spp. Conclusions: This study extends the knowledge of the structure and functions of insect host defense AMPs. Each of the novel β-hairpin peptides has a potential to be a template for the development of selective antibiotic drugs.
MSANet: LiDAR-Camera Online Calibration with Multi-Scale Fusion and Attention Mechanisms
Authors: Xiong Fengguang , Zhang Zhiqiang , Kong Yu , Shen Chaofan , Hu Mingyue , Kuang Liqun , Han Xie
Published: November 2024

Sensor data fusion is increasingly crucial in the field of autonomous driving. In sensor fusion research, LiDAR and camera have become prevalent topics. However, accurate data calibration from different modalities is essential for effective fusion. Current calibration methods often depend on specific targets or manual intervention, which are time-consuming and have limited generalization capabilities. To address these issues, we introduce MSANet: LiDAR-Camera Online Calibration with Multi-Scale Fusion and Attention Mechanisms, an end-to-end deep learn-based online calibration network for inferring 6-degree of freedom (DOF) rigid body transformations between 2D images and 3D point clouds. By fusing multi-scale features, we obtain feature representations that contain a lot of detail and rich semantic information. The attention module is used to carry out feature correlation among different modes to complete feature matching. Rather than acquiring the precise parameters directly, MSANet online corrects deviations, aligning the initial calibration with the ground truth. We conducted extensive experiments on the KITTI datasets, demonstrating that our method performs well across various scenarios, the average error of translation prediction especially improves the accuracy by 2.03 cm compared with the best results in the comparison method.
Atmospheric Boundary Layer Stability in Urban Beijing: Insights from Meteorological Tower and Doppler Wind Lidar
Authors: Wang Linlin , Wan Bingcheng , Yang Yuanjian , Fan Sihui , Jing Yi , Cheng Xueling , Gao Zhiqiu , Miao Shiguang , Zou Han
Published: November 2024

The limited understanding of the structure of the urban surface atmospheric boundary layer can be attributed to its inherent complexity, as well as a deficiency in comprehensive measurements. We analyzed one year of meteorological data and Doppler wind lidar measurements in Beijing to explore how atmospheric stability is influenced by wind speed, radiation, turbulence, and pollution levels. Results indicate that the predominant state of the urban boundary layers in Beijing is an active condition (characterized by strong unstable and unstable stability regimes) throughout the day, attributed to the significant heat storage capacity of the urban canopy. Strong stable regimes are more frequently observed during winter and autumn, peaking during transitions from night to day. Furthermore, both strong unstable and strong stable regimes occur under very weak wind conditions (indicating weak dynamic instability), with strong instability associated with high net radiation levels while strong stability correlates with low net radiation conditions (indicative of robust thermal stability). The unstable regime manifests under strong winds (reflecting strong dynamic instability) alongside moderate net radiation environments, characterized by elevated values of turbulence kinetic energy and urban boundary height, highlighting the critical role of mechanical turbulence generation during periods of high wind activity. Additionally, six instances of pronounced stable conditions observed during daytime can be partially attributed to low radiation coupled with high pollutant concentrations near the surface, resulting from prolonged temperature inversions due to intense radiative cooling effects and weak dynamic forcing. Our findings presented herein are expected to have urban boundary layer climate and environment implications for other cities with high pollution and dense urban infrastructure all over the world.
Ensemble Network-Based Distillation for Hyperspectral Image Classification in the Presence of Label Noise
Authors: Zhang Youqiang , Ding Ruihui , Shi Hao , Liu Jiaxi , Yu Qiqiong , Cao Guo , Li Xuesong
Published: November 2024

Deep learning has made remarkable strides in hyperspectral image (HSI) classification, significantly improving classification performance. However, the challenge of obtaining accurately labeled training samples persists, primarily due to the subjectivity of human annotators and their limited domain knowledge. This often results in erroneous labels, commonly referred to as label noise. Such noisy labels can critically impair the performance of deep learning models, making it essential to address this issue. While previous studies focused on label noise filtering and label correction, these approaches often require estimating noise rates and may inadvertently propagate noisy labels to clean labels, especially in scenarios with high noise levels. In this study, we introduce an ensemble network-based distillation (END) method specifically designed to address the challenges posed by label noise in HSI classification. The core idea is to leverage multiple base neural networks to generate an estimated label distribution from the training data. This estimated distribution is then used alongside the ground-truth labels to train the target network effectively. Moreover, we propose a parameter-adaptive loss function that balances the impact of both the estimated and ground-truth label distributions during the training process. Our approach not only simplifies architectural requirements but also integrates seamlessly into existing deep learning frameworks. Comparative experiments on four hyperspectral datasets demonstrate the effectiveness of our method, highlighting its competitive performance in the presence of label noise.
DESAT: A Distance-Enhanced Strip Attention Transformer for Remote Sensing Image Super-Resolution
Authors: Mao Yujie , He Guojin , Wang Guizhou , Yin Ranyu , Peng Yan , Guan Bin
Published: November 2024

Transformer-based methods have demonstrated impressive performance in image super-resolution tasks. However, when applied to large-scale Earth observation images, the existing transformers encounter two significant challenges: (1) insufficient consideration of spatial correlation between adjacent ground objects; and (2) performance bottlenecks due to the underutilization of the upsample module. To address these issues, we propose a novel distance-enhanced strip attention transformer (DESAT). The DESAT integrates distance priors, easily obtainable from remote sensing images, into the strip window self-attention mechanism to capture spatial correlations more effectively. To further enhance the transfer of deep features into high-resolution outputs, we designed an attention-enhanced upsample block, which combines the pixel shuffle layer with an attention-based upsample branch implemented through the overlapping window self-attention mechanism. Additionally, to better simulate real-world scenarios, we constructed a new cross-sensor super-resolution dataset using Gaofen-6 satellite imagery. Extensive experiments on both simulated and real-world remote sensing datasets demonstrate that the DESAT outperforms state-of-the-art models by up to 1.17 dB along with superior qualitative results. Furthermore, the DESAT achieves more competitive performance in real-world tasks, effectively balancing spatial detail reconstruction and spectral transform, making it highly suitable for practical remote sensing super-resolution applications.
Multi-Maneuvering Target Tracking Based on a Gaussian Process
Authors: Zhao Ziwen , Chen Hui
Published: November 2024

Aiming at the uncertainty of target motion and observation models in multi-maneuvering target tracking (MMTT), this study presents an innovative data-driven approach based on a Gaussian process (GP). Traditional multi-model (MM) methods rely on a predefined set of motion models to describe target maneuvering. However, these methods are limited by the finite number of available models, making them unsuitable for handling highly complex and dynamic real-world scenarios, which, in turn, restricts the adaptability and flexibility of the filter. In addition, traditional methods often assume that observation models follow ideal linear or simple nonlinear relationships. However, these assumptions may be biased in actual application and so lead to degradation in tracking performance. To overcome these limitations, this study presents a learning-based algorithm-leveraging GP. This non-parametric GP approach enables learning an unlimited range of target motion and observation models, effectively mitigating the problems of model overload and mismatch. This improves the algorithm’s adaptability in complex environments. When the motion and observation models of multiple targets are unknown, the learned models are incorporated into the cubature Kalman probability hypothesis density (PHD) filter to achieve an accurate MMTT estimate. Our simulation results show that the presented approach delivers high-precision tracking of complex multi-maneuvering target scenarios, validating its effectiveness in addressing model uncertainty.
The Causal Nexus Between Different Feed Networks and Defected Ground Structures in Multi-Port MIMO Antennas
Authors: Yalcinkaya Merve Tascioglu , Kamal Shahanawaz , Sen Padmanava , Fettweis Gerhard P.
Published: November 2024

Multiple input multiple output (MIMO) antennas have recently received attention for improving wireless communication data rates in rich scattering environments. Despite this, the challenge of isolation persists prominently in compact MIMO-based electronics. Various techniques have recently emerged to address the isolation issues, among which the defected ground structure (DGS) stands out as a cost-effective solution. Additionally, selecting the appropriate feed mechanism is crucial for enhancing the key performance indicators of MIMO antennas. However, there has been minimal focus on how different feed methods impact the operation of MIMO antennas integrated with DGS. This paper begins with a comprehensive review of diverse antenna design, feeding strategies, and DGS architectures. Subsequently, the causal relationships between various feed networks and DGSs has been established through modeling, simulation, fabrication, and measurement of MIMO antennas operating within the sub-6 GHz spectrum. Particularly, dual elements of MIMO antennas grounded by a slotted complementary split ring resonator (SCSRR)-based DGS were excited using four standard feed methods: coaxial probe, microstrip line, proximity coupled, and aperture coupled feed. The influence of each feed network on the performance of MIMO antennas integrated with SCSRR-based DGSs has been thoroughly investigated and compared, leading to guidelines for feed network selection. The coaxial probe feed network provided improved isolation performance, ranging from 16.5 dB to 46 dB in experiments.The aperture and proximity-coupled feed network provided improvements in bandwidth of 38.7% and 15.6%, respectively. Furthermore, reasonable values for envelope correlation coefficient (ECC), diversity gain (DG), channel capacity loss (CCL), and mean effective gain (MEG) have been ascertained.
Recurrent Nasal Polyposis and Bifid Epiglottis in a Child with Bardet–Biedl Syndrome Ciliopathy
Authors: Fourla Natalia , Drimalas Nikolaos , Vlastos Ioannis Michael
Published: November 2024

Bardet–Biedl syndrome (BBS) is a genetic disease caused by mutations of the BBS genes that encode proteins involved in cilia functioning. It can present with major and/or minor clinical manifestations, such as rod–cone dystrophy, polydactyly, obesity, speech delay, anosmia, congenital heart disease and genital and renal abnormalities. Diagnosis of this rare disease is based on clinical criteria and can be confirmed with molecular genetic testing. Although BBS is a ciliopathy, nasal polyposis has never before been reported in patients with this condition. This article presents the case of a 12-year-old male patient admitted with symptoms of retinopathy, development delay, anosmia, bifid epiglottis and recurrent nasal polyposis. After several clinical, imaging and genetic examinations, the patient was diagnosed with BBS. His nasal symptoms were treated with functional endoscopic sinus surgery and long-term antibiotic therapy, whereas courses of topical antibiotics as well as topical and systemic corticosteroids had no effect. As a conclusion, it is a rare case that presents new clinical manifestations (nasal polyps) that can be related to BBS and possible effective treatments.
Correction: Gary et al. Dual-Credit Policy of New Energy Automobiles in China: Corporate Innovation Capability. Sustainability 2024, 16, 7504
Authors: Gary Joston , Zhao Pengfei , Bao Zhihao
Published: November 2024

The authors would like to make the correction outlined below to the published paper [...]
China’s Photovoltaic Development and Its Spillover Effects on Carbon Footprint at Cross-Regional Scale: Insights from the Largest Photovoltaic Industry in Northwest Arid Area
Authors: Qu Zhun , Jiang Chong , Wang Yixin , Wang Ran , Zhao Ying , Yang Suchang
Published: November 2024

Solar energy plays a crucial role in mitigating climate change and transitioning toward green energy. In China (particularly Northwest China), photovoltaic (PV) development is recognized as a co-benefit and nature-based solution for concurrently combating land degradation and producing clean energy. However, the existing literature on the subject is limited to the local effects of PV power station construction and ignores the spillover environmental effects in distant regions. Thus, a hotspot of PV development in Northwest China was selected as a case to quantify the spill-over impacts of PV development in Qinghai Province on cross-regional economy and the environment using an environmentally extended multi-regional input–output approach and related socioeconomic and environmental statistical data. A cross-regional carbon footprint analysis revealed that the eastern region of Qinghai Province had the highest carbon footprint, followed by the southwestern, central, southern, northwestern, northern, and northeastern regions; the production and supply sectors of electricity and heat were the primary sources of carbon emissions, followed by metal smelting and rolling processing products, non-metallic mineral products, and the transportation, warehousing, and postal sectors. In addition, the PV development in Qinghai Province strongly supports the electricity demand in the central and eastern coastal areas, while substantially reducing the carbon emissions in the eastern, southwestern, and central regions (through the distant supply of PV products). We quantified the spillover effects of PV development in Qinghai Province and address the challenges of PV development in the carbon emission reduction strategies implemented at the regional and cross-regional scales; our findings will support policymakers in developing plans that ensure sustainable energy supply and help China to achieve its carbon neutrality goals.
Synergistic Impacts of Clean Energy Demonstration Policy on Air Pollution and Carbon Reduction
Authors: Cui Lizhi , Sun Wang
Published: November 2024

The development of clean energy is of great significance for achieving air pollution and carbon reduction. China has launched clean energy demonstration province (CEDP) construction as a pilot program to accelerate cleaner alternatives and promote synergies between air pollution and carbon reduction. Existing studies have focused on the carbon abatement effects of this clean energy demonstration policy but are inconclusive as to whether the policy also reduces air pollution. In this paper, we empirically assess the synergistic impact of the CEDP policy on air pollution and carbon reduction using the difference-in-differences method by treating the CEDP pilot as a quasi-natural experiment using provincial-level panel data from 2005 to 2020 in China. We find that the PM2.5 and carbon intensity in the eastern and central regions show a tendency to move towards a lower gradient compared to the western region, and the CEDP pilot has a synergistic effect on air pollution and carbon reduction, as the implementation of the policy significantly increases synergy between air pollution and carbon reduction and reduces the intensity of PM2.5 and carbon emissions in the pilot provinces, which remains a robust finding after multiple tests. In terms of regional differences, the policy’s effects in the central and western regions are more significant than those in the eastern regions, which suggests that the central and western regions have made more progress in environmental improvement after the implementation of the relevant policies, and this finding provides new ideas and possibilities for reducing regional pollution. Further mechanism tests find that industrial upgrading and energy efficiency improvement are important channels for the CEDP policy to achieve the synergistic effects of air pollution and carbon reduction. Accordingly, we put forward policy recommendations to expand the coverage of CEDP pilots in an orderly manner, strengthen the transmission role of industrial upgrading and energy efficiency improvement, and improve the evaluation system of CEDP construction and operation.
The Impact of Digital Economy Policy on Mariculture Green Total Factor Productivity in China
Authors: Liu Sukun , Chen Fang , Cai Tiantian , Zhao Wanli , Hu Ying
Published: November 2024

Mariculture plays a crucial role in the marine industry, holding significant importance for global food provision, coastal economic growth, and marine ecological preservation. However, mariculture encounters challenges such as resource scarcity, environmental contamination, and market instabilities. The broad adoption of digital technology presents valuable growth prospects for mariculture. Employing the SBM-GML model, this study assesses the green total factor productivity of mariculture across ten coastal provinces in China from 2006 to 2022 and investigates the influence of digital economy policies on the sector’s green total factor productivity. The results reveal an overall fluctuating upward trend in the green total factor productivity of Chinese mariculture, ranging between 0.975 and 1.074, with variations in technical efficiency surpassing those in technological progress. This underscores that enhancing the green total factor productivity in China’s mariculture sector primarily hinges on technical efficiency. Noteworthy regional disparities point to an imbalance in regional mariculture advancement. Additionally, this study illustrates the favorable impact of digital economic strategies on the sector’s green total factor productivity, with varying effects observed across diverse regions. These findings provide empirical support and policy recommendations which will help government authorities formulate and implement effective policies, fostering the green transformation of mariculture amid the evolving digital economy landscape.
Numerical Investigation of Network-Based Shock Wave Propagation of Designated Methane Explosion Source in Subsurface Mine Ventilation System Using 1D FDM Code
Authors: Que Sisi , Zeng Jiaqin , Wang Liang
Published: November 2024

In coal mining operations, methane explosions constitute a severe safety risk, endangering miners’ lives and causing substantial economic losses, which, in turn, weaken the production efficiency and economic benefits of the mining industry and hinder the sustainable development of the industry. To address this challenge, this article explores the application of decoupling network-based methods in methane explosion simulation, aiming to optimize underground mine ventilation system design through scientific means and enhance safety protection for miners. We used the one-dimensional finite difference method (FDM) software Flowmaster to simulate the propagation process of shock waves from a gas explosion source in complex underground tunnel networks, covering a wide range of scenarios from laboratory-scale parallel network samples to full-scale experimental mine settings. During the simulation, we traced the pressure loss in the propagation of the shock wave in detail, taking into account the effects of pipeline friction, shock losses caused by bends and obstacles, T-joint branching connections, and cross-sectional changes. The results of these two case studies were presented, leading to the following insights: (1) geometric variations within airway networks exert a relatively minor influence on overpressure; (2) the positioning of the vent positively contributes to attenuation effects; (3) rarefaction waves propagate over greater distances than compression waves; and (4) oscillatory phenomena were detected in the conduits connecting to the surface. This research introduces a computationally efficient method for predicting methane explosions in complex underground ventilation networks, offering reasonable engineering accuracy. These research results provide valuable references for the safe design of underground mine ventilation systems, which can help to create a safer and more efficient mining environment and effectively protect the lives of miners.
Sustainable Use of By-Products (Okara and Linseed Cake) in Tempeh Fermentation: Effects on Isoflavones and Lignans
Authors: Kuligowski Maciej , Radziejewska-Kubzdela Elżbieta , Górna Oliwia , Jasińska-Kuligowska Iwona , Kidoń Marcin
Published: November 2024

Okara and linseed cake are nutrient-rich by-products containing phytoestrogens, which are underutilized in food production. The aim of this study was to optimize hydrothermal treatment and fermentation time using common starters for tempeh fermentation. Changes in isoflavones and secoisolariciresinol diglucoside (SDG) were analyzed using the HPLC-PDA method. Okara and linseed cake were steamed for 5 to 40 min, followed by fermentation with Rhizopus oligosporus at 30 °C for 48 h. The optimal steaming times were 10 min for okara and 20 min for linseed cake. Isoflavone analysis revealed a change in total levels depending on the microflora, with a significant increase in aglycones during fermentation. SDG levels did not show a significant reduction. In 24-h fermented tempeh, the isoflavone acetylglycosides content increased after frying. These results suggest that steam treatment is an effective hydrothermal method, offering energy and water savings. Additionally, the ability to modulate isoflavone composition through fermentation creates new opportunities for pro-healthy food development. This study concludes that okara and linseed cake can be successfully used for tempeh production, providing a sustainable alternative to conventional tempeh substrates. By utilizing these by-products, this research promotes the reduction of food waste and supports the development of environmentally friendly food production practices.