bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of a Carvedilol Oral Liquid Formulation for Paediatric Use
Authors: Chiclana-Rodríguez Blanca , Garcia-Montoya Encarnacion , Rouaz-El Hajoui Khadija , Romero-Obon Miquel , Nardi-Ricart Anna , Suñé-Pou Marc , Suñé-Negre Josep M. , Pérez-Lozano Pilar
Published: September 2023

Carvedilol (CARV) is an ‘off-label’ β-blocker drug to treat cardiovascular diseases in children. Since CARV is nearly insoluble in water, only CARV solid forms are commercialized. Usually, CARV tablets are manipulated to prepare an extemporaneous liquid formulation for children in hospitals. We studied CARV to improve its aqueous solubility and develop an oral solution. In this study, we assessed the solubility and preliminary stability of CARV in different pH media. Using malic acid as a solubility enhancer had satisfactory results. We studied the chemical, physical, and microbiological stability of 1 mg/mL CARV–malic acid solution. A design of experiment (DoE) was used to optimize the CARV solution’s preparation parameters. A 1 mg/mL CARV solution containing malic acid was stable for up to 12 months at 25 °C and 30 °C and 6 months at 40 °C. An equation associating malic acid with CARV concentrations was obtained using DoE. Microbiological data showed that the use of methylparaben was not necessary for this period of time. We successfully developed an aqueous CARV solution suitable for paediatrics and proven to be stable over a 12-month period.
Kramers–Kronig Transmission with a Crosstalk-Dependent Step Multiple-Input Multiple-Output Volterra Equalizer in a Seven-Core Fiber
Authors: Tian Feng , Wu Tianze , Yu Chao , Wang Chuxuan , Yue Mohai , Gao Ran , Zhang Qi , Li Zhipei , Tian Qinghua , Wang Fu , Xin Xiangjun
Published: September 2023

In this paper, we experimentally demonstrate a net bit rate of 261.7 Gbit/s in a seven-core transmission system with a Kramers–Kronig (KK) receiver. The 10 GBaud 16-level quadrature amplitude modulation (QAM) signal is transmitted over a 2.5 km seven-core fiber, and the relationship between carrier-to-signal power ratio, signal power, frequency spacing, and optical power is analyzed. Moreover, a multiple-input multiple-output (MIMO) Volterra equalization algorithm with crosstalk-dependent steps is proposed to compensate for inter-core crosstalk and impairments induced by other devices. Compared to the single-input single-output (SISO) Volterra equalizer, the CSPR can be reduced by 1.3 dB, and the received power gain can reach up to 0.7 dB.
Syzygium cumini (L.) Extract-Derived Green Titanium Dioxide Nanoparticles Induce Caspase-Dependent Apoptosis in Hepatic Cancer Cells
Authors: Rayzah Musaed , Elderdery Abozer Y. , Alzerwi Nasser A. N. , Alzahrani Badr , Alsrhani Abdullah , Alsultan Afnan , Idrees Bandar , Rayzah Fares , Bakhsh Yaser , Alzahrani Ahmed M. , Subbiah Suresh K. , Mok Pooi Ling
Published: September 2023

An aqueous extract of Syzygium cumini seeds was utilized to green synthesize titanium dioxide nanoparticles (TiO2 NPs). UV-Visible, DLS, FTIR, XRD, FESEM, TEM, SAED, EDAX, and photoluminescence spectroscopy techniques were employed to characterize the prepared TiO2 nanoparticles. The rutile crystal structure of TiO2 NPs was revealed by XRD study. The TEM and FESEM images of the TiO2 NPs revealed an average particle size of 50–100 nm. We employed EDAX to investigate the elemental compositions of TiO2 NPs. The O-Ti-O stretching bands appeared in the FTIR spectrum of TiO2 NPs at wavenumbers of 495 cm−1. The absorption edge peaks of TiO2 NPs were found in the UV-vis spectra at 397 nm. The MTT study revealed that TiO2 NPs effectively inhibited the growth of liver cancer Hep3 and Hep-G2 cells. The results of the corresponding fluorescent staining assays showed that TiO2 NPs significantly increased ROS generation, decreased MMP, and induced apoptosis in both liver cancer Hep3 and Hep-G2 cells. TiO2 nanoparticles lessened SOD, CAT, and GSH levels while augmenting MDA contents in Hep3 and Hep-G2 cells. In both Hep3 and Hep-G2 cells treated with TiO2 NPs, the Bax, CytC, p53, caspase-3, -8, and -9 expressions were remarkably augmented, while Bcl-2 expression was reduced. Overall, these findings revealed that formulated TiO2 NPs treatment considerably inhibited growth and triggered apoptosis in Hep3 and HepG2 cells.
Genome-Wide Identification of Bilberry WRKY Transcription Factors: Go Wild and Duplicate
Authors: Felipez Winder , Villavicencio Jennifer , Nizolli Valeria Oliveira , Pegoraro Camila , da Maia Luciano , Costa de Oliveira Antonio
Published: September 2023

WRKY transcription factor genes compose an important family of transcriptional regulators that are present in several plant species. According to previous studies, these genes can also perform important roles in bilberry (Vaccinium myrtillus L.) metabolism, making it essential to deepen our understanding of fruit ripening regulation and anthocyanin biosynthesis. In this context, the detailed characterization of these proteins will provide a comprehensive view of the functional features of VmWRKY genes in different plant organs and in response to different intensities of light. In this study, the investigation of the complete genome of the bilberry identified 76 VmWRKY genes that were evaluated and distributed in all twelve chromosomes. The proteins encoded by these genes were classified into four groups (I, II, III, and IV) based on their conserved domains and zinc finger domain types. Fifteen pairs of VmWRKY genes in segmental duplication and four pairs in tandem duplication were detected. A cis element analysis showed that all promoters of the VmWRKY genes contain at least one potential cis stress-response element. Differential expression analysis of RNA-seq data revealed that VmWRKY genes from bilberry show preferential or specific expression in samples. These findings provide an overview of the functional characterization of these proteins in bilberry.
A Light-Thin Chitosan Nanofiber Separator for High-Performance Lithium-Ion Batteries
Authors: Song Yanghui , Zhao Guanglei , Zhang Sihan , Xie Chong , Li Xiaofeng
Published: September 2023

With the development of portable devices and wearable devices, there is a higher demand for high-energy density and light lithium-ion batteries (LIBs). The separator is a significant component directly affecting the performance of LIBs. In this paper, a thin and porous chitosan nanofiber separator was successfully fabricated using the simple ethanol displacement method. The thickness of the CME15 separator was about half that of mainstream commercial Celgard2325 separators. Owing to its inherent polarity and high porosity, the obtained CME15 separator achieved a small contact angle (18°) and excellent electrolyte wettability (324% uptake). The CME15 separator could maintain excellent thermal dimensional stability at 160 °C. Furthermore, the CME15 separator-based LIBs exhibited excellent cycling performance after 100 cycles (117 mAh g−1 at 1 C). The present work offers a perspective on applying a chitosan nanofiber separator in light and high-performance lithium-ion batteries (LIBs).
Effect of Octene Block Copolymer (OBC) and High-Density Polyethylene (HDPE) on Crystalline Morphology, Structure and Mechanical Properties of Octene Random Copolymer
Authors: Wang Yuan-Xia , Zou Cun-Ying , Bai Nan , Su Qun-Feng , Song Li-Xin , Li Xian-Liang
Published: September 2023

Blending octene random copolymer (ORC) with other polymers is a promising approach to improving ORC mechanical properties, such as tensile strength and elongation. In this study, octene block copolymer (OBC) with lower density than ORC and high-density polyethylene (HDPE) were used to blend with ORC. The effect of both OBC and HDPE on ORC was analyzed using scanning electron microscopy (SEM), differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA) and small-angle X-ray scattering (SAXS). For ORC/OBC blends, a small amount of OBC can improve the crystallization ability of ORC. Meanwhile, for ORC/HDPE blends, the crystallization ability of ORC was significantly suppressed, attributed to good compatibility between ORC and HDPE as indicated by the homogeneous morphology and the disappearance of the α transition peak of ORC in ORC/HDPE blends. Therefore, the tensile strength and elongation of ORC/HDPE blends are significantly higher than those of ORC/OBC blends. For ORC/OBC/HDPE ternary blends, we found that when ORC:OBC:HDPE are at a ratio of 70:15:15, cocrystallization is achieved. Although HDPE improves the compatibility of ORC and OBC, the three-phase structure of the ternary blends can be observed through SAXS when HDPE and OBC exceed 30 wt%. Blending HDPE and OBC (≤30 wt%) could improve the mechanical property of ORC.
Chitosan/Alginate Polymeric Nanoparticle-Loaded α-Mangostin: Characterization, Cytotoxicity, and In Vivo Evaluation against Breast Cancer Cells
Authors: Muchtaridi Muchtaridi , Suryani Ade Irma , Wathoni Nasrul , Herdiana Yedi , Mohammed Ahmed Fouad Abdelwahab , Gazzali Amirah Mohd , Lesmana Ronny , Joni I. Made
Published: September 2023

α-mangostin (Amg), a compound isolated from the mangosteen rind (Garcinia mangostana, L.), has demonstrated promising anticancer activity. However, its low solubility and selectivity against cancer cells limit its efficacy. To address this issue, researchers have developed chitosan/alginate polymeric nanoparticles (NANO-AMCAL) to enhance the effectiveness of Amg. In vitro studies have demonstrated that NANO-AMCAL is highly active against breast cancer cells. Therefore, an in vivo study was conducted to evaluate the efficacy of NANO-AMCAL in treating breast cancer in Wistar rats (Rattus norvegicus) and determine the effective dose. The rats were divided into seven treatment groups, including positive control, negative control, pure Amg, and NANO-AMCAL 5 mg, 10 mg, and 20 mg. The rats were injected subcutaneously with a carcinogenic agent, 7,12-dimethylbenz(a)anthracene (DMBA) and were evaluated for weight and tumor volume every three days during treatment. Surgery was performed on day 14, and histopathological studies were carried out on breast and lung cancer tissues. The results showed that NANO-AMCAL significantly enhanced the anticancer activity of Amg in treating breast cancer in Wistar rats. NANO-AMCAL containing 0.33 mg of Amg had a healing effect three times better than 20 mg pure Amg and was comparable to tamoxifen. The effective dose of NANO-AMCAL for anti-breast cancer treatment in Wistar rats was found to be 20 mg, which exhibited a good healing response, and the tumor volume continued to decrease up to 17.43% on the 14th day. Furthermore, histopathological tests showed tissue repair and no metastases. These findings suggest that NANO-AMCAL may be a promising therapeutic option for breast cancer treatment.
Effect of Selected Bio-Components on the Cell Structure and Properties of Rigid Polyurethane Foams
Authors: Prociak Aleksander , Kucała Michał , Kurańska Maria , Barczewski Mateusz
Published: September 2023

New rigid polyurethane foams (RPURFs) modified with two types of bio-polyols based on rapeseed oil were elaborated and characterized. The effect of the bio-polyols with different functionality, synthesized by the epoxidation and oxirane ring-opening method, on the cell structure and selected properties of modified foams was evaluated. As oxirane ring-opening agents, 1-hexanol and 1.6-hexanediol were used to obtain bio-polyols with different functionality and hydroxyl numbers. Bio-polyols in different ratios were used to modify the polyurethane (PUR) composition, replacing 40 wt.% petrochemical polyol. The mass ratio of the used bio-polyols (1:0, 3:1, 1:1, 1:3, 0:1) affected the course of the foaming process of the PUR composition as well as the cellular structure and the physical and mechanical properties of the obtained foams. In general, the modification of the reference PUR system with the applied bio-polyols improved the cellular structure of the foam, reducing the size of the cells. Replacing the petrochemical polyol with the bio-polyols did not cause major differences in the apparent density (40–43 kg/m3), closed-cell content (87–89%), thermal conductivity (25–26 mW⋅(m⋅K)−1), brittleness (4.7–7.5%), or dimensional stability (<0.7%) of RPURFs. The compressive strength at 10% deformation was in the range of 190–260 and 120–190 kPa, respectively, for directions parallel and perpendicular to the direction of foam growth. DMA analysis confirmed that an increase in the bio-polyol of low functionality in the bio-polyol mixture reduced the compressive strength of the modified foams.
Properties of Cement Thermal Insulation Materials Containing Tailing Waste for Connecting Mines Assessed Using the Orthogonal Method with the Response Surface Method
Authors: Deng Hongwei , Ran Chunzhen , Liu Yao
Published: September 2023

High temperature in deep mines has become the main concern to limit the production capacity of mines. To mitigate the adverse impact of the underground high-temperature environment on mine production, an orthogonal test was used to design an experimental scheme, i.e., the contents of tailings, glass beads, and ordinary Portland cement PC32.5 (PC) were set as the main horizontal factors to prepare thermal insulation material samples with different combination ratios. Compressive strength and thermal conductivity were investigated, as well as the microstructure. Based on the response surface method (RSM), the interaction between the horizontal factors was explored and analyzed using Design Expert 12 software, and thus non-linear fitting equations were established with the volume fractions of the main horizontal factors as independent variables and compressive strength and thermal conductivity as dependent variables in the analysis parameters of thermal insulation materials. The results showed that errors between the fitted calculated values of compressive strength and thermal conductivity and the experimental results were only 0.42% and 1.2%, respectively, indicating that the process parameters obtained with the optimum fitting ratio under the established fitting equation are highly reliable and have excellent compressive strength and thermal insulation properties. The optimized results obtained by combining the orthogonal method and the RSM show accurate prediction and applicability in the field of thermal insulation materials in mines.
Prediction Model of the Remaining Useful Life of the Drill Bit during Micro-Drilling of the Packaging Substrate
Authors: Liu Xianwen , Tao Sha , Zhu Tao , Wang Zhaoguo , Shi Hongyan
Published: September 2023

The packaging substrate plays a significant role in electrical connection, heat dissipation, and protection for the chips. With the characteristics of high hardness and the complex material composition of packaging substrates, drill bit failure is an austere challenge in micro-drilling procedures. In order to monitor the health state of the drill bit and predict its remaining useful life (RUL) in micro-drilling of packaging substrate, an improved RUL prediction model is established based on the similarity principle, degradation rate, and offset coefficient. And then, a micro-drilling experiment on packaging substrate is carried out to collect the axial drilling force through the precision drilling force measurement platform. Axial drilling force signals, which are processed via the Wiener filtering method, are used to analyze the effectiveness of the improved RUL prediction model. The experiment results indicate that, compared to the curves of the traditional RUL prediction model, the curves of the improved RUL prediction model present a higher fitting degree with the actual RUL curves. The average relative errors of the improved RUL prediction model are small and stable in all groups; all of the values are less than 15%, while the fluctuation of the average relative errors of the traditional model is greatly large, and the maximum value even reaches 74.43%. Therefore, taking the degradation rate and offset coefficient into account is a proper method to enhance the accuracy of the RUL prediction model. Furthermore, the improved RUL prediction model is a reliable theoretical support for the health state monitoring of drill bits during the micro-drilling of packaging substrates, which also acts as a potential method to improve micro hole processing efficiency for packaging substrates.
Boosting CO2 Uptake from Waste Concrete Powder Using Artificial Intelligence and the Marine Predators Algorithm
Authors: Rezk Hegazy , Alahmer Ali , Ghoniem Rania M. , As’ad Samer
Published: September 2023

Waste concrete powder (WCP) is emerging as a potential method of adoption for CO2 sequestration due to its ability to chemically react with carbon dioxide and trap it within its structure. This study explores the application of artificial intelligence (AI) and the Marine Predators Algorithm (MPA) to maximize the absorption of CO2 from waste concrete powder generated by recycling plants for building and demolition debris. Initially, a model is developed to assess CO2 uptake according to carbonation time (CT) and water-to-solid ratio (WSR), utilizing the adaptive neuro-fuzzy inference system (ANFIS) modeling approach. Subsequently, the MPA is employed to estimate the optimal values for CT and WSR, thereby maximizing CO2 uptake. A significant improvement in modeling accuracy is evident when the ANOVA method is replaced with ANFIS, leading to a substantial increase of approximately 19% in the coefficient of determination (R-squared) from 0.84, obtained through ANOVA, to an impressive 0.9999 obtained through the implementation of ANFIS; furthermore, the utilization of ANFIS yields a substantial reduction in the root mean square error (RMSE) from 1.96, as indicated by ANOVA, to an impressively low value of 0.0102 with ANFIS. The integration of ANFIS and MPA demonstrates impressive results, with a nearly 30% increase in the percentage value of CO2 uptake. The highest CO2 uptake of 3.86% was achieved when the carbonation time was 54.3 h, and the water-to-solid ratio was 0.27. This study highlights the potential of AI and the MPA as effective tools for optimizing CO2 absorption from waste concrete powder, contributing to sustainable waste management practices in the construction industry.
On the Origin of “Laozi Converting the Barbarians”: A Historical Background Analysis
Authors: Si Jiamin , Han Jishao , Zhang Yuan
Published: September 2023

This article examines the historical background of “Laozi huahu 老子化胡” (Laozi converting the barbarians) and investigates its generation mode and constituent elements. It also discusses and reflects on issues such as the origin of “huahu” and Laozi’s deification. The origin of “Laozi huahu” has little relationship to issues such as the divine system in the Han dynasty and Laozi’s deification. Its elements are rooted in Chinese secular ideological resources. The story of “heroes moving across borders” during the Spring and Autumn and Warring States periods, along with the notion of Laozi as the universal teacher for disciples of various schools, gave birth to the saying. An analysis of the historical background suggests that the origin of “huahu” had likely gone through a long evolutionary process, including an undocumented period where it was transmitted orally as a legend.
Fraud Detection in Healthcare Insurance Claims Using Machine Learning
Authors: Nabrawi Eman , Alanazi Abdullah
Published: September 2023

Healthcare fraud is intentionally submitting false claims or producing misinterpretation of facts to obtain entitlement payments. Thus, it wastes healthcare financial resources and increases healthcare costs. Subsequently, fraud poses a substantial financial challenge. Therefore, supervised machine and deep learning analytics such as random forest, logistic regression, and artificial neural networks are successfully used to detect healthcare insurance fraud. This study aims to develop a health model that automatically detects fraud from health insurance claims in Saudi Arabia. The model indicates the greatest contributing factor to fraud with optimal accuracy. The labeled imbalanced dataset used three supervised deep and machine learning methods. The dataset was obtained from three healthcare providers in Saudi Arabia. The applied models were random forest, logistic regression, and artificial neural networks. The SMOT technique was used to balance the dataset. Boruta object feature selection was applied to exclude insignificant features. Validation metrics were accuracy, precision, recall, specificity, F1 score, and area under the curve (AUC). Random forest classifiers indicated policy type, education, and age as the most significant features with an accuracy of 98.21%, 98.08% precision, 100% recall, an F1 score of 99.03%, specificity of 80%, and an AUC of 90.00%. Logistic regression resulted in an accuracy of 80.36%, 97.62% precision, 80.39% recall, an F1 score of 88.17%, specificity of 80%, and an AUC of 80.20%. ANN revealed an accuracy of 94.64%, 98.00% precision, 96.08% recall, an F1 score of 97.03%, a specificity of 80%, and an AUC of 88.04%. This predictive analytics study applied three successful models, each of which yielded acceptable accuracy and validation metrics; however, further research on a larger dataset is advised.
Siamese Multi-Scale Adaptive Search Network for Remote Sensing Single-Object Tracking
Authors: Hou Biao , Cui Yanyu , Ren Zhongle , Li Zhihao , Wang Shuang , Jiao Licheng
Published: September 2023

With the development of remote sensing earth observation technology, object tracking has gained attention for its broad application prospects in computer vision. However, object tracking is challenging owing to the background clutter, occlusion, and scale variation that often appear in remote sensing videos. Many existing trackers cannot accurately track the object for remote sensing videos with complex backgrounds. Several tracking methods can handle just one situation, such as occlusion. In this article, we propose a Siamese multi-scale adaptive search (SiamMAS) network framework to achieve object tracking for remote sensing videos. First, a multi-scale cross correlation is presented to obtain a more discriminative model and comprehensive feature representation, improving the performance of the model to handle complex backgrounds in remote sensing videos. Second, an adaptive search module is employed that augments the Kalman filter with a partition search strategy for object motion estimation. The Kalman filter is adopted to re-detect the object when the network cannot track the object in the current frame. Moreover, the partition search strategy can help the Kalman filter accomplish a more accurate region-proposal selection. Finally, extensive experiments on remote sensing videos taken from Jilin-1 commercial remote sensing satellites show that the proposed tracking algorithm achieves strong tracking performance with 0.913 precision while running at 37.528 frames per second (FPS), demonstrating its effectiveness and efficiency.
Improving the Estimation of Canopy Fluorescence Escape Probability in the Near-Infrared Band by Accounting for Soil Reflectance
Authors: Qi Mengjia , Liu Xinjie , Du Shanshan , Guan Linlin , Chen Ruonan , Liu Liangyun
Published: September 2023

Solar-induced chlorophyll fluorescence (SIF) has been found to be a useful indicator of vegetation’s gross primary productivity (GPP). However, the directional SIF observations obtained from a canopy only represent a portion of the total fluorescence emitted by all the leaf photosystems because of scattering and reabsorption effects inside the leaves and canopy. Hence, it is crucial to downscale the SIF from canopy level to leaf level by modeling fluorescence escape probability (fesc) for improved comprehension of the relationship between SIF and GPP. Most methods for estimating fesc rely on the assumption of a “black soil background,” ignoring soil reflectance and the effect of scattering between soils and leaves, which creates significant uncertainties for sparse canopies. In this study, we added a correction factor considering soil reflectance, which was modeled using the Gaussian process regression algorithm, to the semi-empirical NIRv/FAPAR model and obtained the improved fesc model accounting for soil reflectance (called the fesc_GPR-SR model), which is suitable for near-infrared SIF downscaling. The evaluation results using two simulation datasets from the Soil–Canopy–Observation of Photosynthesis and the Energy Balance (SCOPE) model and the Discrete Anisotropic Radiative Transfer (DART) model showed that the fesc_GPR-SR model outperformed the NIRv/FAPAR model, especially for sparse vegetation, with higher accuracy for estimating fesc (R2 = 0.954 and RMSE = 0.012 for SCOPE simulations; R2 = 0.982 and RMSE = 0.026 for DART simulations) compared with the NIRv/FAPAR model (R2 = 0.866 and RMSE = 0.100 for SCOPE simulations; R2 = 0.984 and RMSE = 0.070 for DART simulations). The evaluation results using in situ observation data from multi-species canopies also suggested that the leaf-level SIF calculated by the fesc_GPR-SR model tracked better with photosynthetic active radiation absorbed by green components (APARgreen) for sparse vegetation (R2 = 0.937, RMSE = 0.656 mW/m2/nm) compared with the NIRv/FAPAR model (R2 = 0.921, RMSE = 0.904 mW/m2/nm). The leaf-level SIF calculated by the fesc_GPR-SR model was less sensitive to observation angles and differences in canopy structure among multiple species. These results emphasize the significance of accounting for soil reflectance in the estimation of fesc and demonstrate that the fesc_GPR-SR model can contribute to further exploring the physiological mechanism between SIF and GPP.
Types of Coupling between the Stratospheric Polar Vortex and Tropospheric Polar Vortex, and Tropospheric Circulation Anomalies Associated with Each Type in Boreal Winter
Authors: Han Lixin , Shi Chunhua , Guo Dong
Published: September 2023

Fifty years of daily ERA5 reanalysis data are employed to investigate the linkages between the strength of the stratospheric polar vortex and the tropospheric polar vortex during the boreal winter. The strong coupling events, anomalies in both the stratospheric and tropospheric polar vortices, can be classified into four configurations, each representing the distinct characteristics of planetary wave vertical propagation and tropospheric circulation anomalies. The findings reveal the following patterns: (1) Strong stratospheric polar vortex and weak tropospheric polar vortex periods are associated with anomalous downward E-P flux from the stratosphere to the troposphere, predominantly induced by planetary waves 1 and 2. Warm anomalies occur along the North Atlantic coasts, while cold anomalies are evident over Eastern Europe and East Asia at the surface. (2) Weak stratospheric polar vortex and strong tropospheric polar vortex periods exhibit anomalous upward E-P flux in high latitudes, with dominant wave 1, and anomalous downward E-P flux in the middle latitudes, dominated by wave 2. Warm anomalies are observed over North America, Western Europe, and the northern side of the Gulf of Oman at the surface. (3) Strong stratospheric polar vortex and strong tropospheric polar vortex periods feature anomalous downward E-P flux in high latitudes, dominated by wave 1, and anomalous upward E-P flux in middle latitudes, with a wave 2 predominance. Warm anomalies prevail over Northeast Asia, Southern Europe, and North America at the surface. (4) Weak stratospheric polar vortex and weak tropospheric polar vortex periods display anomalous upward E-P flux in mid-to-high latitudes, predominantly with wave 1. In contrast to the tropospheric circulation anomalies observed in the third category, this pattern results in the presence of cold anomalies over Northeast Asia, Southern Europe, and North America.
Correction: Jiang et al. A Cloud Classification Method Based on a Convolutional Neural Network for FY-4A Satellites. Remote Sens. 2022, 14, 2314
Authors: Jiang Yuhang , Cheng Wei , Gao Feng , Zhang Shaoqing , Wang Shudong , Liu Chang , Liu Juanjuan
Published: September 2023

In the original publication [...]
Synthetic Aperture Anomaly Imaging for Through-Foliage Target Detection
Authors: Amala Arokia Nathan Rakesh John , Bimber Oliver
Published: September 2023

The presence of foliage is a serious problem for target detection with drones in application fields such as search and rescue, surveillance, early wildfire detection, or wildlife observation. Visual as well as automatic computational methods, such as classification and anomaly detection, fail in the presence of strong occlusion. Previous research has shown that both benefit from integrating multi-perspective images recorded over a wide synthetic aperture to suppress occlusion. In particular, commonly applied anomaly detection methods can be improved by the more uniform background statistics of integral images. In this article, we demonstrate that integrating the results of anomaly detection applied to single aerial images instead of applying anomaly detection to integral images is significantly more effective and increases target visibility as well as precision by an additional 20% on average in our experiments. This results in enhanced occlusion removal and outlier suppression, and consequently, in higher chances of detecting targets that remain otherwise occluded. We present results from simulations and field experiments, as well as a real-time application that makes our findings available to blue-light organizations and others using commercial drone platforms. Furthermore, we outline that our method is applicable for 2D images as well as for 3D volumes.
Multiband Image Fusion via Regularization on a Riemannian Submanifold
Authors: Pan Han , Jing Zhongliang , Leung Henry , Peng Pai , Zhang Hao
Published: September 2023

Multiband image fusion aims to generate high spatial resolution hyperspectral images by combining hyperspectral, multispectral or panchromatic images. However, fusing multiband images remains a challenge due to the identifiability and tracking of the underlying subspace across varying modalities and resolutions. In this paper, an efficient multiband image fusion model is proposed to investigate the latent structures and intrinsic physical properties of a multiband image, which is characterized by the Riemannian submanifold regularization method, nonnegativity and sum-to-one constraints. An alternating minimization scheme is proposed to recover the latent structures of the subspace via the manifold alternating direction method of multipliers (MADMM). The subproblem with Riemannian submanifold regularization is tackled by the projected Riemannian trust-region method with guaranteed convergence. The effectiveness of the proposed method is demonstrated on two multiband image fusion problems: (1) hyperspectral and panchromatic image fusion and (2) hyperspectral, multispectral and panchromatic image fusion. The experimental results confirm that our method demonstrates superior fusion performance with respect to competitive state-of-the-art fusion methods.
Decentralized Approach for Translational Motion Estimation with Multistatic Inverse Synthetic Aperture Radar Systems
Authors: Testa Alejandro , Pastina Debora , Santi Fabrizio
Published: September 2023

This paper addresses the estimation of the target translational motion by using a multistatic Inverse Synthetic Aperture Radar (ISAR) system composed of an active radar sensor and multiple receiving-only devices. Particularly, a two-step decentralized technique is derived: the first step estimates specific signal parameters (i.e., Doppler frequency and Doppler rate) at the single-sensor level, while the second step exploits these estimated parameters to derive the target velocity and acceleration components. Specifically, the second step is organized in two stages: the former is for velocity estimation, while the latter is devoted to velocity estimation refinement if a constant velocity model motion can be regarded as acceptable, or to acceleration estimation if a constant velocity assumption does not apply. A proper decision criterion to select between the two motion models is also provided. A closed-form theoretical performance analysis is provided for the overall technique, which is then used to assess the achievable performance under different distributions of the radar sensors. Additionally, a comparison with a state-of-the-art centralized approach has been carried out considering computational burden and robustness. Finally, results obtained against experimental multisensory data are shown confirming the effectiveness of the proposed technique and supporting its practical application.
Development of a Deep Learning-Based Epiglottis Obstruction Ratio Calculation System
Authors: Su Hsing-Hao , Lu Chuan-Pin
Published: September 2023

Surgeons determine the treatment method for patients with epiglottis obstruction based on its severity, often by estimating the obstruction severity (using three obstruction degrees) from the examination of drug-induced sleep endoscopy images. However, the use of obstruction degrees is inadequate and fails to correspond to changes in respiratory airflow. Current artificial intelligence image technologies can effectively address this issue. To enhance the accuracy of epiglottis obstruction assessment and replace obstruction degrees with obstruction ratios, this study developed a computer vision system with a deep learning-based method for calculating epiglottis obstruction ratios. The system employs a convolutional neural network, the YOLOv4 model, for epiglottis cartilage localization, a color quantization method to transform pixels into regions, and a region puzzle algorithm to calculate the range of a patient’s epiglottis airway. This information is then utilized to compute the obstruction ratio of the patient’s epiglottis site. Additionally, this system integrates web-based and PC-based programming technologies to realize its functionalities. Through experimental validation, this system was found to autonomously calculate obstruction ratios with a precision of 0.1% (ranging from 0% to 100%). It presents epiglottis obstruction levels as continuous data, providing crucial diagnostic insight for surgeons to assess the severity of epiglottis obstruction in patients.
Anthropometric Profiling and Changes in Segmental Body Composition of Professional Football Players in Relation to Age over the Training Macrocycle
Authors: Staśkiewicz-Bartecka Wiktoria , Grochowska-Niedworok Elżbieta , Zydek Grzegorz , Grajek Mateusz , Kiciak Agata , Białek-Dratwa Agnieszka , Niewiadomska Ewa , Kowalski Oskar , Kardas Marek
Published: September 2023

Body composition is an important indicator of the overall health and fitness of team sports athletes, including in football, and therefore, anthropometric profiling of elite football players is useful as part of determining their skills, strengths, and weaknesses to develop effective strength and conditioning programs. One of the tools available to coaches to track correlates of performance and health is routine body composition assessment. The purpose of this study is to describe and compare the body composition and anthropometric profiles of players using the Direct Segmental Multi-Frequency Bio-Electrical Impedance Analysis method, and to manage body composition throughout the round in the 2020–2021 season. The investigation was carried out during the Polish football league, PKO BP Ekstraklasa, spring round of the football season 2020–2021, in which male football players participated. Athletes between the ages of 18 and 25 (n = 16) made up the younger age group, while those between the ages of 26 and 31 (n = 22) made up the older age group. This manuscript is a continuation of the presentation of the results of the study, which was conducted between 7 January and 23 July 2021. At different stages of the macrocycle, participants underwent six different body composition analyses. The younger and older groups of athletes were compared, as well as measurements of time points 1–6. The dominant extremities, assisting extremities, and trunk had larger fat-free mass contents in the older age group. In the study groups, there was a difference in the fat-free mass content between measures 1–6 that was statistically significant. In the younger group, there was a statistically significant difference in the amount of fat mass content between measurements 1–6. In the older age group, no statistically significant changes were found. The study showed changes in fat-free mass and fat mass in body segments; differences were observed between age groups and between different moments of measurement. Age is an important factor in determining body composition and is also related to an athlete’s experience and seniority. Anthropometric profiling and comprehensive body composition analysis are important tools used in preparing athletes for competition.
Macro- and Micro-Characteristics and Mechanical Properties of Xigeda Formation Claystone in Luding County, Western Sichuan, China
Authors: Wu Ruian , Li Xiang , Guo Changbao , Ni Jiawei , Wang Yang , Song Deguang , Qi Chang
Published: September 2023

Claystone is actually a type of hard soil or soft rock. To reveal the engineering geological characteristics of the Xigeda formation claystone in Luding County (Western Sichuan, China), some experiments, including X-ray diffraction (XRD), scanning electron microscopy (SEM), and geotechnical tests, are performed. The testing results indicate that the Xigeda formation claystone primarily consists of silt, clay, and other fine-grained materials. It is characterized by interbedded yellow and gray thin layers with a horizontal lamination structure. The yellow and gray claystones are made of the same materials but differ in their proportions. Additionally, yellow claystone is characterized by a higher density, resulting in enhanced cementation among clay particles. The permeability coefficient of Xigeda formation claystones ranges from 3.62 × 10−4~7.34 × 10−4 cm/s. The cohesion of yellow and gray claystones decreases with increasing moisture content, and the decline is greater at higher moisture contents. However, the relationship between internal friction angle and moisture content is different. The mechanical properties of the Xigeda formation exhibit significant differences in sensitivity to changes in moisture content across various regions. Notably, the claystone within the study region experiences a particularly pronounced weakening of its mechanical properties when exposed to water.
Effects of Hydraulic Erosion on the Spatial Redistribution Characteristics of Soil Aggregates and SOC on Pisha Sandstone Slope
Authors: Zhang Peng , Li Long , Wang Jing , Zhang Shangxuan , Zhu Zhizhuo
Published: September 2023

Under the long-term effects of hydraulic erosion, soil particles and nutrients are continuously lost and enriched in the process of runoff and sediment movement, leading to a change in soil organic carbon (SOC) in different spatial positions on the slope, which is closely related to the carbon balance of the ecosystem. Therefore, the changes in slope erosion intensity and the spatial redistribution characteristics of soil aggregates and SOC under water erosion conditions were quantitatively analyzed by combining field runoff plots with three-dimensional (3D) laser scanning technology. The results showed that: (1) After rainfall, the slope erosion intensity successively declined from the upper to the lower parts of the slope, and the content of soil aggregates in each soil layer changed obviously. The loss of 1–2 mm soil aggregates was the largest in the sedimentary area of the 2–4 cm soil layer, at 0.38 g/kg. The concentration of 0.5–1 mm soil aggregates was the largest in the micro-erosion area of the 2–4 cm soil layer, at 0.36 g/kg. (2) After rainfall, the overall SOC on the slope showed a loss state in the 0–2 cm soil layer and an enrichment state in the 2–4 cm soil layer. Among them, the loss of SOC in the medium erosion area of the 0–1 cm soil layer was the largest, and its content decreased by 57.58%. The enrichment in the 2–4 cm soil layer was the maximum in the micro-eroded area, with a content increase of 79.23%. (3) Before and after rainfall, the SOC of each soil layer was positively correlated with small aggregates, and the correlation gradually tended to be negative with the increase in the particle size of soil aggregates, and the SOC showed a negative correlation with large aggregates (>2 mm).
Giant Trevally Optimization Approach for Probabilistic Optimal Power Flow of Power Systems Including Renewable Energy Systems Uncertainty
Authors: Hashish Mohamed S. , Hasanien Hany M. , Ullah Zia , Alkuhayli Abdulaziz , Badr Ahmed O.
Published: September 2023

In this study, the Giant Trevally Optimizer (GTO) is employed to solve the probabilistic optimum power flow (P-OPF) issue, considering Renewable Energy Source (RES) uncertainties, achieving notable cost reduction. The objective function is established to minimize the overall generation cost, including the RES cost, which significantly surpassing existing solutions. The uncertain nature of the RES is represented through the employment of a Monte Carlo Simulation (MCS), strengthened by the K-means Clustering approach and the Elbow technique. Various cases are investigated, including various combinations of PV systems, WE systems, and both fixed and fluctuating loads. The study demonstrates that while considering the costs of solar, wind, or both might slightly increase the total generation cost, the cumulative generation cost remains significantly less than the scenario that does not consider the cost of RESs. The superior outcomes presented in this research underline the importance of considering RES costs, providing a more accurate representation of real-world system dynamics and enabling more effective decision making.
Sustainable Assessment of the Environmental Activities of Major Cosmetics and Personal Care Companies
Authors: Lim Hea Young , Kwon Ki Han
Published: September 2023

The cosmetics and personal care industry has, by its nature, contributed to global environmental issues such as climate change, waste, water scarcity, habitat destruction, and water and air pollution. Therefore, it is more important than ever for the cosmetics and personal care companies to be responsible and proactive in addressing environmental issues. Meanwhile, the complexity of the cosmetics and personal care industry has never been greater. The roles of not only brand companies but also OEM/ODM and retail companies are becoming increasingly important, and the boundaries are also collapsing. Despite the urgency of environmental issues, there has been a lack of research on specific and practical environmental activities of cosmetics and personal care companies, and the environmental responsibilities of OEM/ODM companies and retailers have been overlooked. Therefore, the need for this study was recognized. The purpose of this study was to expand the scope of assessment to include not only cosmetics brand companies but also OEM/ODM companies and retailers in general to identify the actual and concrete environmental activities being carried out. Therefore, in this study, the keywords cosmetics, environmental, eco-friendly, and sustainable, which have recently become the topics of discussion, were empirically analyzed. This study selected and analyzed 18 out of 28 annual reports, nonfinancial statements, and sustainability reports of 16 cosmetics- and personal-care-related companies. In addition, 456 articles were found through PubMed, Google Scholar, Google, and Scopus, and the final 108 articles were referenced using the PRISMA flow chart. The novelty of this study is, first, in the fact that it identified the actual and specific strategies and practices of cosmetics and personal care companies with respect to environmental issues. Second, it established common standards for environmental issues and compared corporate environmental activities. Third, this study included OEM/ODM companies and retailers, whose influence has been increasing in recent years, to understand the status of eco-friendly activities across the industry. This study makes a practical contribution by encouraging environmental activities in the cosmetics industry through comparing and evaluating the specific and practical environmental activities of not only brand companies but also OEM/ODM companies and retailers and laying the foundation for the development of a framework for environmental assessment. In addition, this study recognizes the need to study the environmental activity behavior of the cosmetics industry as a whole and contributes to the study of cosmetics companies’ environmental activities by suggesting how to use companies’ nonfinancial performance reports as materials to assess their actual environmental activities.
Comparing Darcy’s Law and the Brinkman Equation for Numerical Simulations of Saltwater Intrusion
Authors: Yao Jingwei , Zhang Hong
Published: September 2023

Saltwater intrusion into coastal aquifers presents a significant global challenge to fresh groundwater resources. Numerical modelling represents a valuable tool to study this phenomenon. Darcy’s Law is widely applied to groundwater studies and is extended into the Brinkman Equation to account for kinetic dissipations due to viscous shear. However, their comparative performance and accuracy in density-driven flows remain unclear. To determine the circumstances where the Brinkman Equation is required, numerical simulations with both models were implemented in hypothetical coastal aquifer scenarios. The results revealed that the largest discrepancies between the two models occur inside the dispersion zone during the break-through period, with concentration differences of up to 2.5%. The mixing of freshwater and saltwater induces rapid density and velocity variations. Brinkman’s viscous term moderates the rate of change and decreases the intrusion length by up to 6.1 m in a 180 m intrusion case. Furthermore, higher permeability and a lower recharge rate both strengthen the viscous effects in most sandy coastal aquifers. The Brinkman Equation excels at capturing intricate flow patterns with large variations. Therefore, it is necessary to be employed for studies on freshwater–saltwater interfaces and other similar conditions including groundwater–surface water interfaces, non-isothermal flows, and complex geological conditions.
Sustainable Approach Development for Education of Electrical Engineers in Long-Term Online Education Conditions
Authors: Trunova Iryna , Arhun Shchasiana , Hnatov Andrii , Apse-Apsitis Peteris , Kunicina Nadezhda , Myhal Vasiliy
Published: September 2023

The prolongation of the online education period is a significant challenge nowadays in Ukraine. Due to the ongoing war in Ukraine, educational institutions have been destroyed, leading to a significant movement of students both within the country and abroad. Consequently, the quality of educational services has suffered, particularly in technical specialties that require hands-on and laboratory work. The objective of this article is to explore solutions for training Ukrainian students in technical fields under the circumstances of war, with a focus on ensuring their safety and improving the overall quality of education. This article analyzes the existing methods of conducting laboratory work in remote settings. It identifies that distance learning at foreign universities, without the necessity of physical relocation, holds the most promising potential. Moreover, it recommends leveraging the “My Digital Electrical Engineering” (MDEE) laboratory, developed at RTU, for conducting remote laboratory work. A comprehensive examination of the MDEE laboratory is presented, along with a step-by-step algorithm for integrating it into the educational process at KhNAHU. The findings of this study can be utilized to enhance distance learning practices in Ukrainian technical universities. This, in turn, will enable students to continue their education during the war while ensuring their safety and facilitating the acquisition of knowledge at a high standard.