bluuebunny/crossref_metadata_2025 huggingface dataset:
Abietane Diterpenes from Medusantha martiusii and Their Anti-Neuroinflammatory Activity
Authors: Assis Edileuza B. de , Andrade Rodrigo S. de , Silva Joanda P. R. e , Martorano Lucas H. , Amorim Geraldo M. W. , Loureiro Paulo B. A. , Abreu Lucas S. , Sobral Marianna V. , Scotti Marcus T. , Santos Junior Fernando M. dos , Agra Maria de Fátima , Tavares Josean F. , Silva Marcelo S. da
Published: June 2024

Seven new abietane diterpenoids, comprising medusanthol A–G (1–3, 5, 7–9) and two previously identified analogs (4 and 6), were isolated from the hexane extract of the aerial parts of Medusantha martiusii. The structures of the compounds were elucidated by HRESIMS, 1D/2D NMR spectroscopic data, IR spectroscopy, NMR calculations with DP4+ probability analysis, and ECD calculations. The anti-neuroinflammatory potential of compounds 1–7 was evaluated by determining their ability to inhibit the production of nitric oxide (NO) and the proinflammatory cytokine TNF-α in BV2 microglia stimulated with LPS and IFN-γ. Compounds 1–4 and 7 exhibited decreased NO levels at a concentration of 12.5 µM. Compound 1 demonstrated strong activity with an IC50 of 3.12 µM, and compound 2 had an IC50 of 15.53 µM; both compounds effectively reduced NO levels compared to the positive control quercetin (IC50 11.8 µM). Additionally, both compounds significantly decreased TNF-α levels, indicating their potential as promising anti-neuroinflammatory agents.
Investigation of Combustion and NO/SO2 Emission Characteristics during the Co-Combustion Process of Torrefied Biomass and Lignite
Authors: Yang Xu , Zhu Wenkun , Li Zhaoming , Xu Li , Zhu Shujun , Tian Jilin , Wang Zhuozhi , Shen Boxiong
Published: June 2024

This paper investigates the combustion characteristics and pollutant emission patterns of the mixed combustion of lignite (L) and torrefied pine wood (TPW) under different blending ratios. Isothermal combustion experiments were conducted in a fixed bed reaction system at 800 °C, and pollutant emission concentrations were measured using a flue gas analyzer. Using scanning electron microscopy (SEM) and BET (nitrogen adsorption) experiments, it was found that torrefied pine wood (TPW) has a larger specific surface area and a more developed pore structure, which can facilitate more complete combustion of the sample. The results of the non-isothermal thermogravimetric analysis show that with the TPW blending ratio increase, the entire combustion process advances, and the ignition temperature, maximum peak temperature, and burnout temperature all show a decreasing trend. The kinetic equations of the combustion reaction process of mixed gas were calculated by Flynn–Wall–Ozawa (FWO) and Kissinger–Akahira–Sunose (KAS) kinetic equations. The results show that the blending of TPW reduces the activation energy of the combustion reaction of the mixed fuel. When the TPW blending ratio is 80%, the activation energy values of the mixed fuel are the lowest at 111.32 kJ/mol and 104.87 kJ/mol. The abundant alkali metal ions and porous structure in TPW reduce the conversion rates of N and S elements in the fuel to NO and SO2, thus reducing the pollutant emissions from the mixed fuel.
Novel Histone Deacetylase (HDAC) Inhibitor Induces Apoptosis and Suppresses Invasion via E-Cadherin Upregulation in Pancreatic Ductal Adenocarcinoma (PDAC)
Authors: Schiedlauske Katja , Deipenbrock Alina , Pflieger Marc , Hamacher Alexandra , Hänsel Jan , Kassack Matthias U. , Kurz Thomas , Teusch Nicole E.
Published: June 2024

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal form of pancreatic cancer characterized by therapy resistance and early metastasis, resulting in a low survival rate. Histone deacetylase (HDAC) inhibitors showed potential for the treatment of hematological malignancies. In PDAC, the overexpression of HDAC 2 is associated with the epithelial–mesenchymal transition (EMT), principally accompanied by the downregulation of the epithelial marker E-cadherin and increased metastatic capacity. The effector cytokine transforming growth factor-β (TGF β) is known to be a major inducer of the EMT in PDAC, leading to high metastatic and invasive potential. In addition, the overexpression of HDAC 6 in PDAC is associated with reduced apoptosis. Here, we have demonstrated that a novel HDAC 2/6 inhibitor not only significantly increased E-cadherin expression in PANC-1 cells (5.5-fold) and in 3D PDAC co-culture spheroids (2.5-fold) but was also able to reverse the TGF-β-induced downregulation of E-cadherin expression. Moreover, our study indicates that the HDAC inhibitor mediated re-differentiation resulting in a significant inhibition of tumor cell invasion by approximately 60% compared to control. In particular, we have shown that the HDAC inhibitor induces both apoptosis (2-fold) and cell cycle arrest. In conclusion, the HDAC 2/6 inhibitor acts by suppressing invasion via upregulating E-cadherin mediated by HDAC 2 blockade and by inducing cell cycle arrest leading to apoptosis via HDAC 6 inhibition. These results suggest that the HDAC 2/6 inhibitor might represent a novel therapeutic strategy for the treatment of PDAC tumorigenesis and metastasis.
Intranasal Delivery of Cell-Penetrating Therapeutic Peptide Enhances Brain Delivery, Reduces Inflammation, and Improves Neurologic Function in Moderate Traumatic Brain Injury
Authors: Yanamadala Yaswanthi , Roy Ritika , Williams Afrika Alake , Uppu Navya , Kim Audrey Yoonsun , DeCoster Mark A. , Kim Paul , Murray Teresa Ann
Published: June 2024

Following traumatic brain injury (TBI), secondary brain damage due to chronic inflammation is the most predominant cause of the delayed onset of mood and memory disorders. Currently no therapeutic approach is available to effectively mitigate secondary brain injury after TBI. One reason is the blood–brain barrier (BBB), which prevents the passage of most therapeutic agents into the brain. Peptides have been among the leading candidates for CNS therapy due to their low immunogenicity and toxicity, bioavailability, and ease of modification. In this study, we demonstrated that non-invasive intranasal (IN) administration of KAFAK, a cell penetrating anti-inflammatory peptide, traversed the BBB in a murine model of diffuse, moderate TBI. Notably, KAFAK treatment reduced the production of proinflammatory cytokines that contribute to secondary injury. Furthermore, behavioral tests showed improved or restored neurological, memory, and locomotor performance after TBI in KAFAK-treated mice. This study demonstrates KAFAK’s ability to cross the blood–brain barrier, to lower proinflammatory cytokines in vivo, and to restore function after a moderate TBI.
Comparison of Lifetime-Based Pressure-Sensitive Paint Measurements in a Wind Tunnel Using Model Pitch–Traverse and Pitch–Pause Modes
Authors: Klein Christian , Yorita Daisuke , Henne Ulrich
Published: June 2024

In order to improve the data productivity of a wind tunnel test, the model under investigation in the wind tunnel is moved continuously with a predetermined constant angular speed in the so-called pitch–traverse mode. Alternatively, the wind tunnel model can be moved in the so-called pitch–pause mode, in which it keeps its position for a certain (measurement) time at a fixed pitch position, after which it is moved to the next pitch position. The latter procedure is more time-consuming, so, for the same time interval, the number of measured data points taken in the pitch–pause mode is less than that for the pitch–traverse mode. Since wind tunnel test time can be quite expensive, in most wind tunnel tests where only conventional forces and pressures are recorded with conventional measuring systems, the wind tunnel model is moved in the pitch–traverse mode in order to obtain as much aerodynamic data as possible during the tunnel runtime. The application of the Pressure-Sensitive Paint (PSP) technique has been widely used in wind tunnel testing for the purpose of providing pressure data on wind tunnel models with high spatial resolution. The lifetime-based PSP method has several advantages over the intensity-based method since it often has higher accuracy. Up until now, the lifetime-based PSP technique has mainly been used for wind tunnel testing, where the test model has been moved to the pitch–pause mode. The traditional lifetime method using on-chip accumulation requires multiple (~1000) excitation light pulses to accumulate enough luminescence (fluorescence or phosphorescence) photons on the camera sensor to provide acceptable signal-to-noise ratios and, therefore, it may seem to be not compatible with a continuously moving wind tunnel model. Nevertheless, the present study verifies the application of lifetime-based PSP utilizing on-chip accumulation with a continuously moving wind tunnel model which would make the entire PSP data acquisition compatible with that of the conventional measurements (forces and pressures), as mentioned above. In this paper, the applicability of the lifetime-based PSP technique to a continuously moving wind tunnel model (in pitch–traverse mode) is investigated with the help of measurements in the transonic wind tunnel in Göttingen (TWG). For this investigation, PSP was applied on the delta-wing model DLR-F22, which is to be tested in TWG. The pressure distribution on the wind tunnel model was measured using the PSP lifetime method for both model movement modes (pitch–pause and pitch–traverse mode) so that the corresponding PSP results could be directly compared with each other. In addition, an error analysis of the PSP results was carried out and compared with the conventional pressure measurement results, hence providing an assessment of the accuracy of the PSP results; finally, a recommendation for future PSP measurements could be given.
Weather Extremes Shock Maize Production: Current Approaches and Future Research Directions in Africa
Authors: Du Shaolong , Xiong Wei
Published: June 2024

Extreme weather events have led to widespread yield losses and significant global economic damage in recent decades. African agriculture is particularly vulnerable due to its harsh environments and limited adaptation capacity. This systematic review analyzes 96 articles from Web of Science, Science Direct, and Google Scholar, focusing on biophysical studies related to maize in Africa and worldwide. We investigated the observed and projected extreme weather events in Africa, their impacts on maize production, and the approaches used to assess these effects. Our analysis reveals that drought, heatwaves, and floods are major threats to African maize production, impacting yields, suitable cultivation areas, and farmers’ livelihoods. While studies have employed various methods, including field experiments, statistical models, and process-based modeling, African research is often limited by data gaps and technological constraints. We identify three main gaps: (i) lack of reliable long-term experimental and empirical data, (ii) limited access to advanced climate change adaptation technologies, and (iii) insufficient knowledge about specific extreme weather patterns and their interactions with management regimes. This review highlights the urgent need for targeted research in Africa to improve understanding of extreme weather impacts and formulate effective adaptation strategies. We advocate for focused research on data collection, technology transfer, and integration of local knowledge with new technologies to bolster maize resilience and food security in Africa.
Associations of the Seed Fatty Acid Composition of Sesame (Sesamum indicum L.) Germplasm with Agronomic Traits and FAD2 Variations
Authors: Kim Eun-Gyeong , Lee Sookyeong , Yang Tae-Jin , Lee Jae-Eun , Yoo Eunae , Lee Gi-An , Sung Jungsook
Published: June 2024

Sesame is an important oilseed crop grown for human consumption in many countries, with a high commercial value due to its high oleic/linoleic acid ratio (O/L ratio). However, its properties may vary among different accessions. In the current study, 282 sesame accessions were evaluated to determine the effects of agronomic traits and genotypes on the O/L ratio. The O/L ratio was positively correlated with the oleic acid (C18:1), stearic acid (C18:0), and myristic acid (C14:0) concentrations, as well as the capsule zone length (CZL), capsule width (CW), and capsule length (CL), and negatively correlated with the linoleic acid (C18:2) and linolenic acid (C18:3) concentrations, the days to maturity (DTM), days to flowering (DTF), and the height of the first capsule-bearing node (HFC) (p < 0.05). In addition, the O/L ratio was affected by the FAD2 haplotype, as the Hap2 and Hap3 sesame accessions had lower O/L ratios. Therefore, we suggest that the increase and decrease in the contents of C18:1 and C18:2 are associated with the FAD2 haplotype. A total of 25 agronomic traits and fatty acid compositions were compared via statistical analysis, and accessions with a high O/L ratio were selected. The results of this study can be used as a basis for further research on the development of new sesame varieties through enhancing nutritional functionality.
DEK219 and HSF17 Collaboratively Regulate the Kernel Length in Maize
Authors: Xie Sidi , Tian Ran , Liu Hanmei , Li Yangping , Hu Yufeng , Huang Yubi , Zhang Junjie , Liu Yinghong
Published: June 2024

The kernel length is a crucial determinant of maize (Zea mays L.) yield; however, only a limited number of genes regulating kernel length have been validated, thus leaving our understanding of the mechanisms governing kernel length incomplete. We previously identified a maize kernel mutant, defective kernel219 (dek219), which encodes the DICER-LIKE1 protein that is essential for miRNA biogenesis. The present study revealed that dek219 consistently exhibits a stable phenotype characterized by a reduced kernel length. Further analysis indicated that dek219 may reduce the kernel length by inhibiting the expression of genes involved in regulating kernel length. By employing miRNA-target gene prediction, expression analysis, and correlation analysis, we successfully identified nine transcription factors that potentially participate in the regulation of kernel length under the control of DEK219. Among them, the upregulation fold change of HEAT SHOCK TRANSCRIPTION FACTOR17 (HSF17) expression was the highest, and the difference was most significant. The results of transient expression analysis and electrophoretic mobility shift assay (EMSA) indicated that HSF17 can inhibit the expression of DEFECTIVE ENDOSPERM18 (DE18), a gene involved in regulating kernel length. Furthermore, the hsf17 mutant exhibited a significant increase in kernel length, suggesting that HSF17 functions as a negative regulator of kernel length. The results of this study provide crucial evidence for further elucidating the molecular regulatory mechanism underlying maize kernel length and also offer valuable genetic resources for breeding high-yielding maize varieties.
Controlling Oxidation of Kerf Loss Silicon Waste Enabling Stable Battery Anode
Authors: Jiang Yan , He Sitong , Ma Siqi , Xi Fengshuo , Gavrilin Ilya M. , Tong Zhongqiu , Lu Jijun , Wan Neng , Ma Wenhui , Zhu Yunpeng , Wu Pingkeng , Li Shaoyuan
Published: June 2024

The recovery of massive kerf loss silicon waste into silicon anodes is an attractive approach to efficiently utilizing resources and protect the environment. Tens-of-nanometers-scale-thickness Si waste particles enable the high feasibility of high-rate Li-ion storage, but continuous oxidation leads to a gradual loss of electrochemical activity. Understanding the relationship between this oxidation and Li-ion storage properties is key to efficiently recovering silicon wastes into silicon anodes. However, corresponding research is rare. Herein, a series of silicon waste samples with different oxidation states were synthesized and their Li-ion storage characters were investigated. By analyzing their Li-ion storage properties and kinetics, we found that oxidation has absolutely detrimental effects on Li-ion storage performance, which is different to previously reported results of nano-silicon materials. The 2.5 wt.% Si provides a substantial initial discharge capacity of 3519 mAh/g at 0.5 A/g. The capacity retention of 2.5 wt.% Si is almost 70% after 500 cycles at 1 A/g. However, the 35.8 wt.% Si presents a modest initial discharge capacity of merely 170 mAh/g. Additionally, oxidation leads the Li-ion storage kinetics to transform from Li-ion diffusion-controlled to charge transfer-controlled behaviors. For kerf loss silicon waste with an oxygen content over 35.8 wt.%, Li-ion storage capability is lost due to a high charge transfer resistance and a low Li-ion diffusion coefficient.
Identification and Absorption–Distribution–Metabolism–Excretion–Toxicity Prediction of Potential MTHFD2 Enzyme Inhibitors from Urtica dioica Ethanolic Leaf Extract
Authors: Alshammari Shifaa O.
Published: June 2024

This study aimed to explore the potential of Urtica dioica (U. dioica) ethanolic leaf extract for cancer treatment by identifying its components, evaluating its effects on cancer cell lines, and analyzing its molecular docking. The objective of this study was to investigate the anticancer properties of U. dioica ethanolic leaf extract and assess its potential as a therapeutic strategy for cancer treatment. This study utilized high-performance liquid chromatography (HPLC) to analyze the chemical composition of U. dioica ethanolic leaf extract. The anticancer effects of the extract were evaluated by assessing cell viability, determining IC50 values, and conducting ADMET analysis after oral administration. U. dioica ethanolic leaf extract was found to contain methyl hexadecanoate as its primary component, along with flavonoids and polyphenols. It effectively reduced cell viability in various tested cancer cell lines, with IC50 values varying for each cell line. The duration of treatment significantly influenced cell viability, with the most significant reduction observed after 48 h. Molecular docking studies suggested that catechin, kaempferol, and quercetin-3-O-rutinoside may have potential as inhibitors of the MTHFD2 enzyme. This study revealed the potential of U. dioica and its compounds in cancer treatment. Ethanolic leaf extract has been shown to have anticancer effects on various cancer cell lines, with catechin and kaempferol showing promise as inhibitors of the MTHFD2 enzyme. Further research is warranted to explore the therapeutic implications of U. dioica in cancer treatment.
A Land-Corrected ASCAT Coastal Wind Product
Authors: Vogelzang Jur , Stoffelen Ad
Published: June 2024

A new ASCAT coastal wind product based on a 12.5 km grid size is presented. The new product contains winds up to the coast line and is identical to the current operational coastal product over the open ocean. It is based on the assumption that within a wind vector cell land and sea have constant radar cross section. With an accurate land fraction calculated from ASCAT’s spatial response function and a detailed land mask, the land correction can be obtained with a simple linear regression. The coastal winds stretch all the way to the coast, filling the coastal gap in the operational coastal ASCAT product, resulting in three times more winds within a distance of 20 km from the coast. The Quality Control (QC), based on the regression error and the regression bias error, reduces this abundance somewhat. A comparison of wind speed pdfs with those from NWP forecasts shows that the influence of land in the land-corrected scatterometer product appears more reasonable and starts not as far offshore as that in the NWP forecasts. The VRMS difference with moored buoys increases slightly from about 2.4 m/s at 20 km or more from the coast to 4.2 m/s at less than 5 km, where coastal wind effects clearly contribute to the latter difference. While the QC based on the regression bias error flags many WVCs that compare well with buoys, the land-corrected coastal product with more abundant coastal winds appears useful for nowcasting and other coastal wind applications.
Retrieval of Crop Canopy Chlorophyll: Machine Learning vs. Radiative Transfer Model
Authors: Alam Mir Md Tasnim , Simic Milas Anita , Gašparović Mateo , Osei Henry Poku
Published: June 2024

In recent years, the utilization of machine learning algorithms and advancements in unmanned aerial vehicle (UAV) technology have caused significant shifts in remote sensing practices. In particular, the integration of machine learning with physical models and their application in UAV–satellite data fusion have emerged as two prominent approaches for the estimation of vegetation biochemistry. This study evaluates the performance of five machine learning regression algorithms (MLRAs) for the mapping of crop canopy chlorophyll at the Kellogg Biological Station (KBS) in Michigan, USA, across three scenarios: (1) application to Landsat 7, RapidEye, and PlanetScope satellite images; (2) application to UAV–satellite data fusion; and (3) integration with the PROSAIL radiative transfer model (hybrid methods PROSAIL + MLRAs). The results indicate that the majority of the five MLRAs utilized in UAV–satellite data fusion perform better than the five PROSAIL + MLRAs. The general trend suggests that the integration of satellite data with UAV-derived information, including the normalized difference red-edge index (NDRE), canopy height model, and leaf area index (LAI), significantly enhances the performance of MLRAs. The UAV–RapidEye dataset exhibits the highest coefficient of determination (R2) and the lowest root mean square errors (RMSE) when employing kernel ridge regression (KRR) and Gaussian process regression (GPR) (R2 = 0.89 and 0.89 and RMSE = 8.99 µg/cm2 and 9.65 µg/cm2, respectively). Similar performance is observed for the UAV–Landsat and UAV–PlanetScope datasets (R2 = 0.86 and 0.87 for KRR, respectively). For the hybrid models, the maximum performance is attained with the Landsat data using KRR and GPR (R2 = 0.77 and 0.51 and RMSE = 33.10 µg/cm2 and 42.91 µg/cm2, respectively), followed by R2 = 0.75 and RMSE = 39.78 µg/cm2 for the PlanetScope data upon integrating partial least squares regression (PLSR) into the hybrid model. Across all hybrid models, the RapidEye data yield the most stable performance, with the R2 ranging from 0.45 to 0.71 and RMSE ranging from 19.16 µg/cm2 to 33.07 µg/cm2. The study highlights the importance of synergizing UAV and satellite data, which enables the effective monitoring of canopy chlorophyll in small agricultural lands.
Mapping Debris-Covered Glaciers Using High-Resolution Imagery (GF-2) and Deep Learning Algorithms
Authors: Yang Xin , Xie Fuming , Liu Shiyin , Zhu Yu , Fan Jinghui , Zhao Hongli , Fu Yuying , Duan Yunpeng , Fu Rong , Guo Siyang
Published: June 2024

Glacier inventories are fundamental in understanding glacier dynamics and glacier-related environmental processes. High-resolution mapping of glacier outlines is lacking, although high-resolution satellite images have become available in recent decades. Challenges in development of glacier inventories have always included accurate delineation of boundaries of debris-covered glaciers, which is particularly true for high-resolution satellite images due to their limited spectral bands. To address this issue, we introduced an automated, high-precision method in this study for mapping debris-covered glaciers based on 1 m resolution Gaofen-2 (GF-2) imagery. By integrating GF-2 reflectance, topographic features, and land surface temperature (LST), we used an attention mechanism to improve the performance of several deep learning network models (the U-Net network, a fully convolutional neural network (FCNN), and DeepLabV3+). The trained models were then applied to map the outlines of debris-covered glaciers, at 1 m resolution, in the central Karakoram regions. The results indicated that the U-Net model enhanced with the Convolutional Block Attention Module (CBAM) outperforms other deep learning models (e.g., FCNN, DeepLabV3+, and U-Net model without CBAM) in terms of precision for supraglacial debris identification. On the testing dataset, the CBAM-enhanced U-Net model achieved notable performance metrics, with its accuracy, F1 score, mean intersection over union (MIoU), and kappa coefficient reaching 0.93, 0.74, 0.79, and 0.88. When applied at the regional scale, the model even exhibits heightened precision (accuracies = 0.94, F1 = 0.94, MIoU = 0.86, kappa = 0.91) in mapping debris-covered glaciers. The experimental glacier outlines were accurately extracted, enabling the distinction of supraglacial debris, clean ice, and other features on glaciers in central Karakoram using this trained model. The results for our method revealed differences of 0.14% for bare ice and 10.36% against the manually interpreted glacier boundary for supraglacial debris. Comparison with previous glacier inventories revealed raised precisions of 8.74% and 4.78% in extracting clean ice and with supraglacial debris, respectively. Additionally, our model demonstrates exceptionally high exclusion for bare rock outside glaciers and could reduce the influence of non-glacial snow on glacier delineation, showing substantial promise in mapping debris-covered glaciers.
The Time Lag Effects and Interaction among Climate, Soil Moisture, and Vegetation from In Situ Monitoring Measurements across China
Authors: Wang Jie , Bao Zhenxin , Wang Guoqing , Liu Cuishan , Xie Mingming , Wang Bin , Zhang Jianyun
Published: June 2024

The interaction between soil moisture (SM) and vegetation dynamics has been proven in previous studies. In situ measurements have provided reliable data to investigate and validate the time effect in different zones, which is important in the hydrology and agriculture fields. There were 845 SM in situ monitoring measurements utilized with the correlation between SM and vegetation across various soil depths and climate zones in China. The impact of climate and teleconnection factors on SM and the leaf area index (LAI) are also discussed. The results indicate that SM increases from northwest to southeast in China. The time lag responses of SM to temperature, precipitation, relative humidity, and sunshine duration are 0–3 days, 3–7 days, 1–3 days, and 3–15 days, respectively. The LAI is most strongly correlated with the climate of the current month. When the LAI leads SM, a negative correlation is observed, whereas a positive correlation is observed when SM leads the LAI. This proves that vegetation growth restricts the increase in SM, and soil drying further restricts the growth of vegetation. There was a response time of 2–4 months between the LAI and SM. The effect of vegetation and deeper SM was significant in the arid zone, while they were coupled with shallow SM in the humid zone. Additionally, the El Niño–Southern Oscillation (ENSO) showed a significant positive correlation with SM in 2015–2016 with signals of 9–14 months. The results provide support for balancing the contradiction between future vegetation restoration and water resource scarcity.
Transfer Learning-Based Specific Emitter Identification for ADS-B over Satellite System
Authors: Liu Mingqian , Chai Yae , Li Ming , Wang Jiakun , Zhao Nan
Published: June 2024

In future aviation surveillance, the demand for higher real-time updates for global flights can be met by deploying automatic dependent surveillance–broadcast (ADS-B) receivers on low Earth orbit satellites, capitalizing on their global coverage and terrain-independent capabilities for seamless monitoring. Specific emitter identification (SEI) leverages the distinctive features of ADS-B data. High data collection and annotation costs, along with limited dataset size, can lead to overfitting during training and low model recognition accuracy. Transfer learning, which does not require source and target domain data to share the same distribution, significantly reduces the sensitivity of traditional models to data volume and distribution. It can also address issues related to the incompleteness and inadequacy of communication emitter datasets. This paper proposes a distributed sensor system based on transfer learning to address the specific emitter identification. Firstly, signal fingerprint features are extracted using a bispectrum transform (BST) to train a convolutional neural network (CNN) preliminarily. Decision fusion is employed to tackle the challenges of the distributed system. Subsequently, a transfer learning strategy is employed, incorporating frozen model parameters, maximum mean discrepancy (MMD), and classification error measures to reduce the disparity between the target and source domains. A hyperbolic space module is introduced before the output layer to enhance the expressive capacity and data information extraction. After iterative training, the transfer learning model is obtained. Simulation results confirm that this method enhances model generalization, addresses the issue of slow convergence, and leads to improved training accuracy.
DAENet: Deformable Attention Edge Network for Automatic Coastline Extraction from Satellite Imagery
Authors: Kang Buyun , Wu Jian , Xu Jinyong , Wu Changshang
Published: June 2024

Sea–land segmentation (SLS) is a crucial step in coastline extraction. In CNN-based approaches for coastline feature extraction, downsampling is commonly used to reduce computational demands. However, this method may unintentionally discard small-scale features, hindering the capture of essential global contextual information and clear edge information necessary for SLS. To solve this problem, we propose a novel U-Net structure called Deformable Attention Edge Network (DAENet), which integrates edge enhancement algorithms and a deformable self-attention mechanism. First of all, we designed a multi-scale transformation (MST) to enhance edge feature extraction and model convergence through multi-scale transformation and edge detection, enabling the network to capture spatial–spectral changes more effectively. This is crucial because the deformability of the Deformable Attention Transformer (DAT) modules increases training costs for model convergence. Moreover, we introduced DAT, which leverages its powerful global modeling capabilities and deformability to enhance the model’s recognition of irregular coastlines. Finally, we integrated the Local Adaptive Multi-Head Attention-based Edge Detection (LAMBA) module to enhance the spatial differentiation of edge features. We designed each module to address the complexity of SLS. Experiments on benchmark datasets demonstrate the superiority of the proposed DAENet over state-of-the-art methods. Additionally, we conducted ablation experiments to evaluate the effectiveness of each module.
Fluorescent Probe-Based Fiber Optic Sensor for Real-Time Monitoring of Chloride Ions in Coastal Concrete Structures
Authors: Lin Zhen , Ouyang Quanfeng , Guo Chuanrui , Ni Yiqing
Published: June 2024

Coastal concrete structures, such as cross-sea bridges and tunnels, are susceptible to the penetration of chloride ions, which can lead to the deterioration of the passive film on the rebar surface, consequently accelerating the corrosion process. Conventional methods for monitoring chloride ions typically require in situ drilling for sample collection, thereby compromising efficiency and accuracy. Additionally, real-time monitoring and early warning cannot be achieved. To address these challenges, this work introduces a fluorescent-probe-based fiber optic sensor for monitoring chloride levels in concrete structures. Quinine sulfate was chosen as the fluorescent material due to its exceptional sensitivity to chloride ions and its stability in concrete environments. The proposed sensor was manufactured using sol–gel and 3D-printing techniques. Tests were conducted using concrete simulation fluid and cement mortar specimens. The results demonstrate that the sensitivity of the proposed sensor is greater than 0.01 M, and its accuracy in penetration depth measurement is better than 3 mm. The findings confirm that the designed fiber optic sensor based on quinine sulfate enables real-time monitoring of chloride ions in concrete structures, offering high sensitivity (0.1% in concentration and 2.7 mm in terms of penetration depth), unique selectivity (as it is immune to other ions whose concentrations are 10 times higher than those of Cl−), and a compact size (10 × 20 mm). These attributes render it promising for practical engineering applications.
Exploring Piezoelectric Actuation towards Its Applications in Laser Powder Bed Fusion Additive Manufacturing
Authors: Griffin Connor , Mei Hanfei , Karna Sivaji , Zhang Tianyu , Giurgiutiu Victor , Yuan Lang
Published: June 2024

Piezoelectric materials, which exhibit a charge distribution across the surfaces in reaction to mechanical strain, find significant utility in actuation and sensing applications. Apart from actuation applications like acoustic devices, motors, and vibration damping, an emerging domain for ultrasonic actuators lies in additive manufacturing processes. Ultrasonic waves applied during solidification aim to modulate grain structure and minimize defects. This research focuses on a fixture designed to facilitate and optimize ultrasonic wave propagation through the build plate in laser powder bed fusion additive manufacturing by utilizing a piezoelectric transducer. Three implementations of piezoelectric transducers were evaluated based on their out-of-plane ultrasonic velocity transmissions. It was determined that a thin plate adhered to the surface of the piezoelectric transducer yielded the most favorable outcomes for implementation, achieving 100% transmission of velocity and energy. Preliminary analysis of melt pool morphology and defects in single-track laser scanning experiments demonstrated the impact of ultrasound on solidification, hinting at a novel approach to enhancing the printability of alloys in laser powder bed fusion additive manufacturing processes. The optimal fixture and the explored transducing efficiency could further guide advanced ultrasound testing to enable in situ defect and texture detection during the additive manufacturing processes.
A Staggered Vane-Shaped Slot-Line Slow-Wave Structure for W-Band Dual-Sheet Electron-Beam-Traveling Wave Tubes
Authors: Wang Yuxin , Guo Jingyu , Dong Yang , Xu Duo , Zheng Yuan , Lu Zhigang , Wang Zhanliang , Wang Shaomeng
Published: June 2024

A staggered vane-shaped slot-line slow-wave structure (SV-SL SWS) for application in W-band traveling wave tubes (TWTs) is proposed in this article. In contrast to the conventional slot-line SWSs with dielectric substrates, the proposed SWS consists only of a thin metal sheet inscribed with periodic grooves and two half-metal enclosures, which means it can be easily manufactured and assembled and has the potential for mass production. This SWS not only solves the problem of the dielectric loading effect but also improves the heat dissipation capability of such structures. Meanwhile, the SWS design presented here covers a −15 dB S11 frequency range from 87.5 to 95 GHz. The 3-D simulation for a TWT based on the suggested SWS is also investigated. Under dual-electron injection conditions with a total voltage of 17.2 kV and a total current of 0.3 A, the maximum output power at 90 GHz is 200 W, with a 3 dB bandwidth up to 4 GHz. With a good potential for fabrication using microfabrication techniques, this structure can be a good candidate for millimeter-wave TWT applications.
Charge-Coupled Frequency Response Multispectral Inversion Network-Based Detection Method of Oil Contamination on Airport Runway
Authors: Zhao Shuanfeng , Luo Zhijian , Wang Li , Li Xiaoyu , Xing Zhizhong
Published: June 2024

Aircraft failures can result in the leakage of fuel, hydraulic oil, or other lubricants onto the runway during landing or taxiing. Damage to fuel tanks or oil lines during hard landings or accidents can also contribute to these spills. Further, improper maintenance or operational errors may leave oil traces on the runway before take-off or after landing. Identifying oil spills in airport runway videos is crucial to flight safety and accident investigation. Advanced image processing techniques can overcome the limitations of conventional RGB-based detection, which struggles to differentiate between oil spills and sewage due to similar coloration; given that oil and sewage have distinct spectral absorption patterns, precise detection can be performed based on multispectral images. In this study, we developed a method for spectrally enhancing RGB images of oil spills on airport runways to generate HSI images, facilitating oil spill detection in conventional RGB imagery. To this end, we employed the MST++ spectral reconstruction network model to effectively reconstruct RGB images into multispectral images, yielding improved accuracy in oil detection compared with other models. Additionally, we utilized the Fast R-CNN oil spill detection model, resulting in a 5% increase in Intersection over Union (IOU) for HSI images. Moreover, compared with RGB images, this approach significantly enhanced detection accuracy and completeness by 25.3% and 26.5%, respectively. These findings clearly demonstrate the superior precision and accuracy of HSI images based on spectral reconstruction in oil spill detection compared with traditional RGB images. With the spectral reconstruction technique, we can effectively make use of the spectral information inherent in oil spills, thereby enhancing detection accuracy. Future research could delve deeper into optimization techniques and conduct extensive validation in real airport environments. In conclusion, this spectral reconstruction-based technique for detecting oil spills on airport runways offers a novel and efficient approach that upholds both efficacy and accuracy. Its wide-scale implementation in airport operations holds great potential for improving aviation safety and environmental protection.
Adaptive Fuzzy Integral Sliding Mode Cooperative Control Based on Time-Delay Estimation for Free-Floating Close-Chain Manipulators
Authors: Li Zhongcan , Zhou Yufei , Zhu Mingchao , Wu Qingwen
Published: June 2024

Space manipulators are expected to perform more challenging missions in on-orbit service (OOS) systems, but there are some unique characteristics that are not found on ground-based robots, such as dynamic coupling between space bases and manipulators, limited fuel supply, and working with unfixed bases. This paper focuses on trajectory-tracking control and internal force control for free-floating close-chain manipulators. First, the kinematics and dynamics of free-floating close-chain manipulators are given using the momentum conservation and spatial operator algebra (SOA) methodologies, respectively. Furthermore, an adaptive fuzzy integral sliding mode controller (AFISMC) based on time delay estimation (TDE) was designed for trajectory-tracking control, and a proportional-integral (PI) control strategy was adopted for internal force control. The global asymptotic stability of the proposed controller was proven by using the Lyapunov methodology. Three cases were conducted to verify the efficiency of the controller by using numerical simulations on two six-link manipulators with a free-floating base. The controller presents the desired tracking capability.
Sensor Data Fusion Analysis for Broad Applications
Authors: Duro Natividad
Published: June 2024

Sensor data fusion analysis plays a pivotal role in a variety of fields by integrating data from multiple sensors to produce more accurate, reliable, and comprehensive information than that achieved by individual sensors alone [...]
Evidence of Hyperglycemic Levels Improving the Binding Capacity between Human Serum Albumin and the Antihypertensive Drug Hydrochlorothiazide
Authors: Soares Marilia Amável Gomes , Souza-Silva Franklin , Alves Carlos Roberto , Vazquez Leonardo , de Araujo Talita Stelling , Serpa Carlos , Chaves Otávio Augusto
Published: June 2024

Cardiovascular diseases (CVDs), especially arterial hypertension, stand as prominent contributors to global mortality. Regrettably, individuals with diabetes encounter a two-fold increase in the risk of mortality associated with CVDs. Hydrochlorothiazide (HCTZ) represents a primary intervention for hypertension, particularly in diabetic patients. Nevertheless, there has not yet been a comprehensive assessment of the biophysical characteristics regarding the impact of glucose levels on its binding affinity with human serum albumin (HSA). Thus, the present work reports the interactive profile of HSA/HCTZ in nonglycemic, normoglycemic (80 mg/dL), and hyperglycemic (320 mg/dL) conditions by time-resolved fluorescence, saturation transfer difference–nuclear magnetic resonance (STD-NMR), and surface plasmon resonance (SPR). There was a moderate ground state association of HSA/HCTZ with subdomain IIA that was affected in the presence of different glucose levels. The hyperglycemic condition decreased the binding affinity of HCTZ to subdomain IIA and increased the possibility of subdomain IB also being considered as a secondary binding site due to cooperativity and/or alterations in the protein’s structure. Overall, the glucose level under hyperglycemic conditions led to the cavities being more likely to receive more ligands, offering insights into the necessity of glucose control in the human bloodstream to not impact the residence time (pharmacokinetic profile) and pharmacotherapeutic potential of HCTZ.
How Do Eco-Labels for Everyday Products Made of Recycled Plastic Affect Consumer Behavior?
Authors: Tanaka Daisuke , Dente Sébastien M. R. , Hashimoto Seiji
Published: June 2024

Eco-labels promote environmentally conscious behavior through logos and accompanying information. However, research on the optimal combinations of this information is limited. This study examines the impact of the Japanese Eco Mark logo and recycled plastic input information on consumers’ willingness to pay (WTP) for mugs and pens. The survey results show that both elements positively influence WTP, though logos have a greater impact than recycled plastic information. The analysis of personal attributes revealed that females have a higher WTP than males, with no significant differences across age groups. Consistent with behavioral theories, WTP for mugs increased with environmental awareness towards the 3Rs (Reduce, Reuse, Recycle), while trends for pens were less distinct. This indicates that the effectiveness of eco-labels and recycling information varies by product, highlighting the need for further research to explore these differences.
An Integrated Approach to the Spanish Driving Behavior Questionnaire (SDBQ) in the City of Cuenca, Ecuador
Authors: Espinoza-Molina Fabricio Esteban , Ortega Martin , Sandoval Escobar Katherine Elizabeth , Vazquez Salazar Javier Stalin
Published: June 2024

Traffic collisions are the seventh leading cause of death in Ecuador, with reckless driving being one of the main causes. Although there are statistical data on traffic crashes, there has not yet been a comprehensive investigation of the causes. Therefore, the main objective of this study is to investigate unsafe driving behavior using a modified version of the Spanish Driving Behavior Questionnaire (SDBQ) adapted for Ecuador. The 34-item SDBQ we used has four main dimensions: lapses, errors, violations, and aggressive driving. To apply the SDBQ, a stratified random probability sample of 470 drivers with valid driver’s licenses aged 18–69 was used. Of the drivers, 68.8% were male, while 33.2% were female. We used a chi-square test and descriptive statistics to analyze the data for the SDBQ application items. Finally, four generalized linear Poisson models were used. The results show that taxi drivers have the highest scores on three of the four main dimensions of the SDBQ and male drivers are more likely than female drivers to cause traffic accidents. Drivers are also more likely to cause traffic accidents if they drive more hours per day. This research is the first of its kind to analyze driver behavior-based solutions in Ecuador to reduce traffic accidents. The error factor is the most critical outcome of dangerous behavior in the city of Cuenca. The SDBQ aims to foster a culture of safety and sustainability by promoting road safety measures through legislation and traffic regulations.
Alternative Heating, Ventilation, and Air Conditioning (HVAC) System Considerations for Reducing Energy Use and Emissions in Egg Industries in Temperate and Continental Climates: A Systematic Review of Current Systems, Insights, and Future Directions
Authors: Vanbaelinghem Leandra , Costantino Andrea , Grassauer Florian , Pelletier Nathan
Published: June 2024

Egg production is amongst the most rapidly expanding livestock sectors worldwide. A large share of non-renewable energy use in egg production is due to the operation of heating, ventilation, and air conditioning (HVAC) systems. Reducing energy use, therefore, is essential to decreasing the environmental impacts of intensive egg production. This review identifies market-ready alternatives (such as heat pumps and earth–air heat exchangers) to traditional HVAC systems that could be applied in the industrial egg sector, specifically focusing on their use in temperate and continental climates. For this analysis, energy simulations were run to estimate the typical thermal loads of caged and free-run poultry housing systems in various Canadian locations, which were used as examples of temperate and continental climates. These estimations were then used to evaluate alternative HVAC systems for (1) their capability to meet the energy demands of egg production facilities, (2) their environmental impact mitigation potential, and (3) their relative affordability by considering the insights from a systematic review of 225 relevant papers. The results highlighted that future research should prioritize earth–air heat exchangers as a complementary system and ground source heat pumps as a stand-alone system to reduce the impacts associated with conventional HVAC system operation in egg production.
Research on Fuzzy Evaluation of Land Environmental Security in Three Provinces of Northeast China
Authors: Wang Yu , Zhou Hanru , Guo Yanlong , Zhang Linfu
Published: June 2024

Among the world’s most important three chief black lands, China’s northeast region is a vital hub for the commercial extraction of grain, undertaking the task of grain reserves and special transfers. Utilizing the provincial data of the three northeastern provinces from 2010 to 2021, and using existing documents and records as essential elements, we structured a land security appraisal system with five criterion layers and 21 indicator layers of pressure, state, impact, response, and management. The three provinces in the northeast were evaluated for the security of their land resources using the entropy-dependent weight-TOPSIS pattern. The study findings indicate that: (1) In general, land resource security of the three northeastern provinces shows a pattern of decline followed by a gradual increase from 2012 to 2021, and there is a steady improvement in the level of land’s ecological stability; (2) There are differences in the ecological stability of the soil across cities and provinces, with Heilongjiang Province having the best land security status and Liaoning Province having the worst; (3) The amount of soil erosion in tiny watersheds is the indicator that has the biggest influence on land ecological stability in the three provinces in the northeast; (4) The response layer is the criterion layer that has the strongest correlation with land ecological safety.