bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of the Final Ratio on the Consumption of an Electric Vehicle under Conditions of Standardized Driving Cycles
Authors: Puma-Benavides David Sebastian , Izquierdo-Reyes Javier , Galluzzi Renato , Calderon-Najera Juan de Dios
Published: December 2021

Electric vehicles must improve their electric drive system efficiency and effectively use their limited energy to become a viable means of transportation. As such, these technologies have undergone substantial improvements from their initial conception. More efficient powertrains, together with improved storage technologies, have enabled more extended autonomy. However, from an engineering perspective, these systems are still a key area of research and optimization. This work presents a powertrain optimization methodology, developing energy savings and improving the performance of the electric vehicle by focusing on the differential. The proposed methodology includes a study of the dynamics of the electric vehicle and the generation of a mathematical model that represents it. By simulating the vehicle and varying the final ratio of the differential, a significant optimization for energy savings is obtained by developing a standardized driving cycle. In this case, NEDC, WLTC-2, and WLTC-3 test cycles are used. The results show that a short ratio improves performance, even if this implies a larger torque from the prime mover. Depending on the operating cycle used, an energy-saving between 3% and 8% was registered. An extended energy autonomy and an increment in the life-cycle of the batteries are expected in real driving scenarios.
Functional Outlier Detection by Means of h-Mode Depth and Dynamic Time Warping
Authors: Rollón de Pinedo Álvaro , Couplet Mathieu , Iooss Bertrand , Marie Nathalie , Marrel Amandine , Merle Elsa , Sueur Roman
Published: December 2021

Finding outliers in functional infinite-dimensional vector spaces is widely present in the industry for data that may originate from physical measurements or numerical simulations. An automatic and unsupervised process of outlier identification can help ensure the quality of a dataset (trimming), validate the results of industrial simulation codes, or detect specific phenomena or anomalies. This paper focuses on data originating from expensive simulation codes to take into account the realistic case where only a limited quantity of information about the studied process is available. A detection methodology based on different features, such as h-mode depth or the dynamic time warping, is proposed to evaluate the outlyingness both in the magnitude and shape senses. Theoretical examples are used to identify pertinent feature combinations and showcase the quality of the detection method with respect to state-of-the-art methodologies of detection. Finally, we show the practical interest of the method in an industrial context thanks to a nuclear thermal-hydraulic use case and how it can serve as a tool to perform sensitivity analysis on functional data.
Frequency Contour-Strip Method for Characterization of Damage in Structures under Noisy Conditions
Authors: Peng Jiayi , Xu Hao , Jia Hailei , Sumarac Dragoslav , Deng Tongfa , Zhang Xin , Cao Maosen
Published: December 2021

Eigen-frequency, compared with mode shape and damping, is a more practical and reliable dynamic feature to portray structural damage. The frequency contour-line method relying on this feature is a representative method to identify damage in beam-type structures. Although this method has been increasingly applied in the area of damage identification, it has two significant deficiencies: inefficiency in establishing the eigen-frequency panorama; and incompetence to identify cracks in noisy conditions, considerably impairing the effectiveness in identifying structural damage. To overcome these deficiencies, a novel method, termed the frequency contour-strip method, is developed for the first time. This method is derived by extending the frequency contour line of 1D to frequency contour strip of 2D. The advantages of the frequency contour-strip method are twofold: (i) it uses the isosurface function to instantly produce the eigen-frequency panorama with a computational efficiency several orders of magnitude higher than that of the frequency contour-line method; and (ii) it can accommodate the effect of random noise on damage identification, thereby thoroughly overcoming the deficiencies of the frequency contour-line method. With these merits, the frequency contour-strip method can characterize damage in beam-type structures with more efficiency, greater accuracy, and stronger robustness against noise. The proof of concept of the proposed method is performed on an analytical model of a Timoshenko beam bearing a crack and the effectiveness of the method is experimentally validated via crack identification in a steel beam.
A Data Augmentation Method for Skeleton-Based Action Recognition with Relative Features
Authors: Chen Junjie , Yang Wei , Liu Chenqi , Yao Leiyue
Published: December 2021

In recent years, skeleton-based human action recognition (HAR) approaches using convolutional neural network (CNN) models have made tremendous progress in computer vision applications. However, using relative features to depict human actions, in addition to preventing overfitting when the CNN model is trained on a few samples, is still a challenge. In this paper, a new motion image is introduced to transform spatial-temporal motion information into image-based representations. For each skeleton sequence, three relative features are extracted to describe human actions. The three relative features are consisted of relative coordinates, immediate displacement, and immediate motion orientation. In particular, the relative coordinates introduced in our paper not only depict the spatial relations of human skeleton joints but also provide long-term temporal information. To address the problem of small sample sizes, a data augmentation strategy consisting of three simple but effective data augmentation methods is proposed to expand the training samples. Because the generated color images are small in size, a shallow CNN model is suitable to extract the deep features of the generated motion images. Two small-scale but challenging skeleton datasets were used to evaluate the method, scoring 96.59% and 97.48% on the Florence 3D Actions dataset and UTkinect-Action 3D dataset, respectively. The results show that the proposed method achieved a competitive performance compared with the state-of-the-art methods. Furthermore, the augmentation strategy proposed in this paper effectively solves the overfitting problem and can be widely adopted in skeleton-based action recognition.
Special Issue on “Machine Learning/Deep Learning in Medical Image Processing”
Authors: Nishio Mizuho
Published: December 2021

Many recent studies on medical image processing have involved the use of machine learning (ML) and deep learning (DL) [...]
Measurement and Analysis of Downhole Drill String Vibration Signal
Authors: Li Yafeng , Wang Jin , Shan Yonggang , Wang Chong , Hu Yuanbiao
Published: December 2021

Downhole drill string vibration data can provide an effective reference for research drill string vibration during drilling. In this paper, the research group used a storage-type downhole vibration measurement equipment equipped with an orthogonal, three-axis accelerometer to measure and collect drill string vibration signals during drilling in an oil well. Based on the installation characteristics of the sensor, the relationship between the acceleration measurement value of the sensor and the center acceleration value of the drill string is obtained. Then the time-domain signals representative of the vibration in igneous rock drilling is analyzed. It can be found that the occurrence of stick-slip vibration can be judged by the regular wave packets in the time-domain signal, while the time-domain signal of whirl is disorderly. The main frequency of stick-slip vibration in the low-frequency band is 0.1221 Hz and the period of stick-slip vibration is very close to 10 s through Fast Fourier (FFT) and Short-time Fourier transform (DTFT) methods. In the process of whirling, two frequencies, respectively, 0.05341 Hz and 155.5 Hz, play a major role. The frequency 0.05341 Hz is very close to the reciprocal of the period of 20 s when the peak energy spectrum density appears, indicating that the occurrence of whirl is very likely to be related to the natural frequency of the drilling tool. Through further time-frequency analysis, it also can be found that the occurrence of whirl and stick-slip is greatly related to the use of torsional impactors and jars.
Numerical Infeasibilities of Nanofibrous Mats Process Design
Authors: Drąg Marlena
Published: December 2021

A new computer-aided method to design electrospun, nanofibrous mats was implemented and tested. In this work, the standard nonlinear algebraic model led to the terminal fiber diameter FD being examined in detail. The analysis was performed in terms of numerical feasibility. The study specified the limit value of the axial length scale, parameter χ, that determined valid solutions. The presented approach has vast practical potential (i.e., biomedical applications, air/water purification systems, fire protection and solar industries).
A New Empirical Approach for Estimating Solar Insolation Using Air Temperature in Tropical and Mountainous Environments
Authors: Hoyos-Gomez Laura Sofía , Ruiz-Mendoza Belizza Janet
Published: December 2021

Solar irradiance is an available resource that could support electrification in regions that are low on socio-economic indices. Therefore, it is increasingly important to understand the behavior of solar irradiance. and data on solar irradiance. Some locations, especially those with a low socio-economic population, do not have measured solar irradiance data, and if such information exists, it is not complete. There are different approaches for estimating solar irradiance, from learning models to empirical models. The latter has the advantage of low computational costs, allowing its wide use. Researchers estimate solar energy resources using information from other meteorological variables, such as temperature. However, there is no broad analysis of these techniques in tropical and mountainous environments. Therefore, in order to address this gap, our research analyzes the performance of three well-known empirical temperature-based models—Hargreaves and Samani, Bristol and Campbell, and Okundamiya and Nzeako—and proposes a new one for tropical and mountainous environments. The new empirical technique models daily solar irradiance in some areas better than the other three models. Statistical error comparison allows us to select the best model for each location and determines the data imputation model. Hargreaves and Samani’s model had better results in the Pacific zone with an average RMSE of 936,195 Wh/m2 day, SD of 36,01%, MAE of 748,435 Wh/m2 day, and U95 of 1.836,325 Wh/m2 day. The new proposed model showed better results in the Andean and Amazon zones with an average RMSE of 1.032,99 Wh/m2 day, SD of 34,455 Wh/m2 day, MAE of 825,46 Wh/m2 day, and U95 of 2.025,84 Wh/m2 day. Another result was the linear relationship between the new empirical model constants and the altitude of 2500 MASL (mean above sea level).
Improvement of the Transglycosylation Efficiency of a Lacto-N-Biosidase from Bifidobacterium bifidum by Protein Engineering
Authors: Vuillemin Marlene , Holck Jesper , Matwiejuk Martin , Moreno Prieto Eduardo S. , Muschiol Jan , Molnar-Gabor Dora , Meyer Anne S. , Zeuner Birgitte
Published: December 2021

The lacto-N-biosidase LnbB from Bifidobacterium bifidum JCM 1254 was engineered to improve its negligible transglycosylation efficiency with the purpose of enzymatically synthesizing lacto-N-tetraose (LNT; Gal-β1,3-GlcNAc-β1,3-Gal-β1,4-Glc) in one enzymatic step. LNT is a prebiotic human milk oligosaccharide in itself and constitutes the structural core of a range of more complex human milk oligosaccharides as well. Thirteen different LnbB variants were expressed and screened for transglycosylation activity by monitoring transglycosylation product formation using lacto-N-biose 1,2-oxazoline as donor substrate and lactose as acceptor substrate. LNT was the major reaction product, yet careful reaction analysis revealed the formation of three additional LNT isomers, which we identified to have a β1,2-linkage, a β1,6-linkage, and a 1,1-linkage, respectively, between lacto-N-biose (Gal-β1,3-GlcNAc) and lactose. Considering both maximal transglycosylation yield and regioselectivity as well as minimal product hydrolysis, the best variant was LnbB W394H, closely followed by W465H and Y419N. A high transglycosylation yield was also obtained with W394F, yet the substitution of W394 and W465 of the subsite −1 hydrophobic platform in the enzyme with His dramatically impaired the undesirable product hydrolysis as compared to substitution with Phe; the effect was most pronounced for W465. Using p-nitrophenyl-β-lacto-N-bioside as donor substrate manifested W394 as an important target position. The optimization of the substrate concentrations confirmed that high initial substrate concentration and high acceptor-to-donor ratio both favor transglycosylation.
A Novel Shadow Removal Method Based upon Color Transfer and Color Tuning in UAV Imaging
Authors: Alvarado-Robles Gilberto , Solís-Muñoz Francisco J. , Garduño-Ramón Marco A. , Osornio-Ríos Roque A. , Morales-Hernández Luis A.
Published: December 2021

Through the increasing use of unmanned aerial vehicles as remote sensing tools, shadows become evident in aerial imaging; this fact, alongside the higher spatial resolution obtained by high-resolution mounted cameras, presents a challenging issue when performing different image processing tasks related to urban areas monitoring. Accordingly, the state-of-the-art reported works can correct the shadow regions, but the heterogeneity between the corrected shadow and non-shadow areas is still evident and especially noticeable in concrete and asphalt regions. The present work introduces a local color transfer methodology to shadow removal which is based on the CIE L*a*b (Lightness, a and b) color space that considers chromatic differences in urban regions, and it is followed by a color tuning using the HSV color space. The quantitative comparison was executed by using the shadow standard deviation index (SSDI), where the proposed work provided low values that improve up to 19 units regarding other tested methods. The qualitative comparison was visually realized and proved that the proposed method enhances the color correspondence without losing texture information. Quantitative and qualitative results validate the results of color correction and texture preservation accuracy of the proposed method against other published methodologies.
High-Brightness Image Enhancement Algorithm
Authors: Wei Yifei , Jia Zhenhong , Yang Jie , Kasabov Nikola K.
Published: December 2021

In this paper, we introduce a tone mapping algorithm for processing high-brightness video images. This method can maximally recover the information of high-brightness areas and preserve detailed information. Along with benchmark data, real-life and practical application data were taken to test the proposed method. The experimental objects were license plates. We reconstructed the image in the RGB channel, and gamma correction was carried out. After that, local linear adjustment was completed through a tone mapping window to restore the detailed information of the high-brightness region. The experimental results showed that our algorithm could clearly restore the details of high-brightness local areas. The processed image conformed to the visual effect observed by human eyes but with higher definition. Compared with other algorithms, the proposed algorithm has advantages in terms of both subjective and objective evaluation. It can fully satisfy the needs in various practical applications.
A Randomized, Double-Blind, Placebo-Controlled Parallel Study on the Efficacy and Safety of Centella asiatica L. Extract for Reducing Alanine Transaminase (ALT) Level in Subjects with Elevated ALT
Authors: Jeong Yong Joon , Jeon Hyelin , Kang Se Chan
Published: December 2021

The liver is an important organ that detoxifies various metabolites, synthesizes proteins, and produces biochemicals necessary for life. There are many medications on the market to treat liver diseases, but these can be a strain on the liver due to the need for a detoxification process in the organ. Herbal medicines are replacing synthetic drugs. In the present study, we aimed to evaluate the efficacy and safety of Centella aisatica L. extract for reducing alanine transaminase (ALT) levels using a randomized, double-blind, placebo-controlled parallel study. Investigators performed a clinical trial in which an herbal treatment was administered every morning for 12 weeks to 80 patients in two groups. The study protocol number was SYN/RM/CA-008. The results demonstrated improved ALT levels with a positive change in the investigational product (IP) group (−19.9) compared to the placebo group (1.8) (p < 0.0001). In addition, IP treatment was safe and non-toxic. The current data indicate that CA-HE50 exhibits clinically significant changes for all hepatoprotective efficacy parameters, suggesting potential for development and applicability as a hepatoprotective substance.
Evaluation of a Novel Condition Indicator with Comparative Application to Hypoid Gear Failures
Authors: Surányi Marcell , Leighton Michael , Reinbrecht Christian , Bader Michael
Published: December 2021

This paper presents a condition monitoring methodology that uses a novel condition indicator (CI) algorithm, allowing for a confident assessment of system health and an advanced warning of failures. The CI is evaluated in the application of a specialized gear rig utilized for the high-cycle fatigue testing of hypoid gears. The CI is shown in this case study to ensure higher confidence in the prediction of failures than other algorithms, with variations in the results. In the comparison, consideration is given to the signal-to-noise ratio, the ability to differentiate between damages and/or damaged components and the sensitivity of the CI to the failure.
Comparative Evaluation on Combustion and Emission Characteristics of a Diesel Engine Fueled with Crude Palm Oil Blends
Authors: Ge Jun Cong , Yoon Sam Ki , Song Jun Hee
Published: December 2021

Vegetable oil as an alternative fuel for diesel engine has attracted much attention all over the world, and it is also expected to achieve the goal of global carbon neutrality in the future. Although the product after transesterification, biodiesel, can greatly reduce the viscosity compared with vegetable oil, the high production cost is one of the reasons for restricting its extensive development. In addition, based on the current research on biodiesel in diesel engines, it has been almost thoroughly investigated. Therefore, in this study, crude palm oil (CPO) was directly used as an alternative fuel to be blended with commercial diesel. The combustion, engine performance and emissions were investigated on a 4-cylinder, turbocharged, common rail direct injection (CRDI) diesel engine fueled with different diesel-CPO blends according to various engine loads. The results show that adding CPO to diesel reduces the maximum in-cylinder pressure and maximum heat release rate to 30 Nm and 60 Nm. The most noteworthy finding is that the blend fuels reduce the emissions of hydrocarbons (HC), nitrogen oxides (NOx) and smoke, simultaneously. On the whole, diesel fuel blended with 30% CPO by volume is the best mixing ratio based on engine performance and emission characteristics.
Judgments of Object Size and Distance across Different Virtual Reality Environments: A Preliminary Study
Authors: Park Hannah , Faghihi Nafiseh , Dixit Manish , Vaid Jyotsna , McNamara Ann
Published: December 2021

Emerging technologies offer the potential to expand the domain of the future workforce to extreme environments, such as outer space and alien terrains. To understand how humans navigate in such environments that lack familiar spatial cues this study examined spatial perception in three types of environments. The environments were simulated using virtual reality. We examined participants’ ability to estimate the size and distance of stimuli under conditions of minimal, moderate, or maximum visual cues, corresponding to an environment simulating outer space, an alien terrain, or a typical cityscape, respectively. The findings show underestimation of distance in both the maximum and the minimum visual cue environment but a tendency for overestimation of distance in the moderate environment. We further observed that depth estimation was substantially better in the minimum environment than in the other two environments. However, estimation of height was more accurate in the environment with maximum cues (cityscape) than the environment with minimum cues (outer space). More generally, our results suggest that familiar visual cues facilitated better estimation of size and distance than unfamiliar cues. In fact, the presence of unfamiliar, and perhaps misleading visual cues (characterizing the alien terrain environment), was more disruptive than an environment with a total absence of visual cues for distance and size perception. The findings have implications for training workers to better adapt to extreme environments.
Mueller Matrix-Based Approach for the Ex Vivo Detection of Riboflavin-Treated Transparent Biotissue
Authors: Jütte Lennart , Sharma Gaurav , Fricke Dierk , Franke Maximilian , Wollweber Merve , Roth Bernhard
Published: December 2021

Corneal collagen cross-linking is an established procedure for the treatment of certain eye diseases which is applied to enhance the mechanical stability of such biotissue without deteriorating its functionality. However, being transparent, the optical analysis of the outcome of such treatments is cumbersome and relies on relatively expensive experimental equipment. We aim to apply the Mueller matrix polarimetry for the detection of photo-induced collagen cross-linking in transparent biotissue after treatment with riboflavin and UV irradiation. A simple Mueller matrix polarimetry setup could provide a fast and non-invasive analysis of transparent media to sensitively detect small photo-induced cross-linking effects in biotissue. We demonstrated the current capabilities of the approach on non-planar porcine cornea samples ex vivo. We reported the distinction between untreated and riboflavin-treated samples. The differences observed were correlated with the variation of certain Mueller matrix elements and parameters derived from the decomposition. The measurement data show variation in the cross-linked and non-cross-linked samples, although the effect of the UV treatment on the riboflavin-treated samples was not at the same level of significance yet and needs further investigation. The Mueller matrix measurement represents a promising approach for the detection of the effects of corneal collagen cross-linking. Further studies with a larger sample number are required to validate this approach. In the future, this could enable the reliable and non-invasive detection of photo-induced effects in biotissue and open the possibility for in vivo application, e.g., in eye disease treatment or the detection of scar collagen development.
RUL Prediction of Rolling Bearings Based on a DCAE and CNN
Authors: Wang Chenyang , Jiang Wanlu , Yang Xukang , Zhang Shuqing
Published: December 2021

Predicting the remaining useful life (RUL) of mechanical equipment can improve production efficiency while effectively reducing the life cycle cost and failure rate. This paper proposes a method for predicting the remaining service life of equipment through a combination of a deep convolutional autoencoder (DCAE) and a convolutional neural network (CNN). For rolling bearings, a health indicator (HI) could be built by combining DCAE and self-organizing map (SOM) networks, performing more advanced characterization against the original vibration data and modeling the degradation state of the rolling bearings. The HI serves as the label of the original vibration data, and the original data with such label is input into the prediction model of the RUL based on a one-dimensional convolutional neural network (1D-CNN). The model was trained for predicting the RUL of a rolling bearing. The bearing degradation dataset was evaluated to verify the method’s effectiveness. The results demonstrate that the constructed HI can characterize the bearing degradation state effectively and that the method of predicting the RUL can accurately predict the bearing degradation trend.
A Comparative Study on Teaching Methodologies Applied in Engineering and Manufacturing Process Subjects during the COVID-19 Pandemic in 2020 and 2021
Authors: López Óscar , González Alfonso , Álvarez Francisco J. , Rodríguez David
Published: December 2021

Specific disciplines in engineering, such as manufacturing processes, require students in their academic stage to pay special attention, given the possible changes that may affect the acquisition of competencies. In an environment of uncertainty, such as a global pandemic, teaching must adapt without losing the effective delivery of content to students. The health and safety measures applied during the first months of the pandemic led to a different type of teaching to that which had customarily been applied, such as synchronous and asynchronous methodologies defined by the university’s governing bodies, where face-to-face and online methodologies coexisted in the same academic year. All of this avoided interrupting the academic year. This paper studies the results achieved in this uncertain environment, extends them and compares them with the following year, where only the face-to-face methodology was applied to the students enrolled in Manufacturing Processes 2 at the Centro Universitario de Mérida within the Bachelor’s Degree in Design Engineering and New Product Development (Grado en Ingeniería en Diseño y Desarrollo de Nuevos Productos -GIDIDP-). An analysis of variance (ANOVA) was applied to the data obtained to locate the significant differences between the samples taken in the first year with online and face-to-face teaching methodologies and those taken in the second year with an exclusively face-to-face methodology. When comparing the results, maintaining face-to-face teaching proved essential, as it contributes towards achieving better marks or maintaining the level. However, online methodologies also help as an additional tool to acquire other knowledge and specific skills in these technical engineering subjects, specifically those dealing with the manufacturing processes addressed in this study.
Dynamic Workpiece Modeling with Robotic Pick-Place Based on Stereo Vision Scanning Using Fast Point-Feature Histogram Algorithm
Authors: Do Quoc-Trung , Chang Wen-Yang , Chen Li-Wei
Published: December 2021

In the era of rapid development in industry, an automatic production line is the fundamental and crucial mission for robotic pick-place. However, most production works for picking and placing workpieces are still manual operations in the stamping industry. Therefore, an intelligent system that is fully automatic with robotic pick-place instead of human labor needs to be developed. This study proposes a dynamic workpiece modeling integrated with a robotic arm based on two stereo vision scans using the fast point-feature histogram algorithm for the stamping industry. The point cloud models of workpieces are acquired by leveraging two depth cameras, type Azure Kinect Microsoft, after stereo calibration. The 6D poses of workpieces, including three translations and three rotations, can be estimated by applying algorithms for point cloud processing. After modeling the workpiece, a conveyor controlled by a microcontroller will deliver the dynamic workpiece to the robot. In order to accomplish this dynamic task, a formula related to the velocity of the conveyor and the moving speed of the robot is implemented. The average error of 6D pose information between our system and the practical measurement is lower than 7%. The performance of the proposed method and algorithm has been appraised on real experiments of a specified stamping workpiece.
Numerical Simulation of Williamson Nanofluid Flow over an Inclined Surface: Keller Box Analysis
Authors: Rafique Khuram , Alotaibi Hammad
Published: December 2021

The study of nanofluids has become a key research area in mathematics, physics, engineering, and materials science. Nowadays, nanofluids are widely used in many industrial applications to improve thermophysical properties such as thermal conductivity, thermal diffusivity, convective heat transfer, and viscosity. This article discusses the effects of heat generation/absorption and chemical reaction on magnetohydrodynamics (MHD) flow of Williamson nanofluid over an inclined stretching surface. The impact of Williamson factor on velocity field is investigated numerically using Keller box analysis (KBA). Suitable similarity transformations are used to recover ordinary differential equations (ODEs) from the boundary flow equations. These ordinary differential equations are addressed numerically. The numerical computations revealed that energy and species exchange decrease with rising values of magnetic field. Moreover, it is found that increasing the chemical reaction parameter increases the Nusselt number and decreases skin friction. Further, the effect of Lewis parameter diminishes energy transport rate. In the same vein, it is also observed that increasing the inclination can enhance skin friction, while the opposite occurred for the energy and species transport rate. As given numerical computations demonstrate, our results are in reasonable agreement with the reported earlier studies.
Evaluation of In Vitro Wound-Healing Potential, Antioxidant Capacity, and Antimicrobial Activity of Stellaria media (L.) Vill
Authors: Miere (Groza) Florina , Teușdea Alin Cristian , Laslo Vasile , Cavalu Simona , Fritea Luminița , Dobjanschi Luciana , Zdrinca Mihaela , Zdrinca Marcel , Ganea Mariana , Pașc Priscilla , Memete Adriana Ramona , Antonescu Angela , Vlad Andreea Margareta , Vicas Simona Ioana
Published: December 2021

The healing of skin wounds remains an important concern in medicine, especially in chronic wounds caused by various diseases such as diabetes. Using herbs or herbal products to heal skin wounds is a therapeutic challenge for traditional medicine. In this context, the main aim of our work was to highlight the in vitro healing potential of Stellaria media (L.) Vill. (SM) extract using the scratch assay on normal human dermal fibroblasts (NHDF). The ability to stimulate cell migration and proliferation under the influence of different concentrations of SM extract (range between 12.5 and 200 µg/mL) was determined compared to the control (untreated in vitro-simulated wound) and positive control (allantoin 50 µg/mL). Our results showed that the concentration of 100 µg/mL SM extract applied on the simulated wound recorded the strongest and fastest (24 h) migration (with wound closure) and proliferation of NHDF compared with the control. In addition, the SM extract was characterized in terms of bioactive compounds (total phenols and flavonoids content), antioxidant capacity (FRAP (The Ferric-Reducing Antioxidant Power) assay and electrochemical method), and antimicrobial activity. The results show that the SM extract contains a considerable amount of polyphenols (17.19 ± 1.32 mg GAE/g dw and 7.28 ± 1.18 mg QE/g dw for total phenol and flavonoid content, respectively) with antioxidant capacity. Antimicrobial activity against Gram-positive bacteria (S. aureus) is higher than E. coli at a dose of 15 µg/mL. This study showed that Stellaria media is a source of polyphenols compounds with antioxidant capacity, and for the first time, its wound healing potential was emphasized.
Concisely Indexed Multi-Keyword Rank Search on Encrypted Cloud Documents
Authors: Chin Tai-Lin , Shih Wan-Ni
Published: December 2021

With the advent of cloud computing, the low-cost and high-capacity cloud storages have attracted people to move their data from local computers to the remote facilities. People can access and share their data with others at anytime, from anywhere. However, the convenience of cloud storages also comes with new problems and challenges. This paper investigates the problem of secure document search on the cloud. Traditional search schemes use a long index for each document to facilitate keyword search in a large dataset, but long indexes can reduce the search efficiency and waste space. Another concern to prevent people from using cloud storages is the security and privacy problem. Since cloud services are usually run by third party providers, data owners desire to avoid the leakage of their confidential information, and data users desire to protect their privacy when performing search. A trivial solution is to encrypt the data before outsourcing the data to the cloud. However, the encryption could make the search difficult by plain keywords. This paper proposes a secure multi-keyword search scheme with condensed index for encrypted cloud documents. The proposed scheme resolves the issue of long document index and the problem of searching documents over encrypted data, simultaneously. Extended simulations are conducted to show the improvements in terms of time and space efficiency for cloud data search.
Short-Term Traffic State Prediction Based on Mobile Edge Computing in V2X Communication
Authors: Wang Pangwei , Liu Xiao , Wang Yunfeng , Wang Tianren , Zhang Juan
Published: December 2021

Real-time and reliable short-term traffic state prediction is one of the most critical technologies in intelligent transportation systems (ITS). However, the traffic state is generally perceived by single sensor in existing studies, which is difficult to satisfy the requirement of real-time prediction in complex traffic networks. In this paper, a short-term traffic prediction model based on complex neural network is proposed under the environment of vehicle-to-everything (V2X) communication systems. Firstly, a traffic perception system of multi-source sensors based on V2X communication is proposed and designed. A mobile edge computing (MEC)-assisted architecture is then introduced in a V2X network to facilitate perceptual and computational abilities of the system. Moreover, the graph convolutional network (GCN), the gated recurrent unit (GRU), and the soft-attention mechanism are combined to extract spatiotemporal features of traffic state and integrate them for future prediction. Finally, an intelligent roadside test platform is demonstrated for perception and computation of real-time traffic state. The comparison experiments show that the proposed method can significantly improve the prediction accuracy by comparing with the existing neural network models, which consider one of the spatiotemporal features. In particular, for comparison results of the traffic state prediction and the error value of root mean squared error (RMSE) is reduced by 39.53%, which is the greatest reduction in error occurrences by comparing with the GCN and GRU models in 5, 10, 15 and 30 min respectively.
Human Physiological Parameters Related to Solar and Geomagnetic Disturbances: Data from Different Geographic Regions
Authors: Mavromichalaki Helen , Papailiou Maria-Christina , Gerontidou Maria , Dimitrova Svetla , Kudela Karel
Published: December 2021

It is well known that the various manifestations of space weather can influence a wide range of human activities, from technological systems to human health. Various earlier, as well as more recent multi-disciplinary heliobiological and biometeorological studies have revealed that the human organism is sensitive to environmental physical activity changes and reacts to them through variations of the physiological parameters of the human body. This paper constitutes an overview of the National and Kapodistrian University of Athens investigations in regard to the possible effect of solar, geomagnetic, and cosmic ray activity on human physiological parameters. The Athens Cosmic Ray and Solar Physics Groups collaborated with scientific teams from different countries, statistically processing and analyzing data related to human physiological parameters (such as mean heart rate, arterial systolic, and diastolic pressure), or the number of incidents of different types of cardiac arrhythmias and so forth, in relation to data concerning and describing geomagnetic activity (geomagnetic indices Ap and Dst) and variations in cosmic ray intensity (Forbush decreases and cosmic ray intensity enhancements). In total, four projects were carried out concerning data from different geographical regions (Baku, Azerbaijan; Kosice, Slovakia; Tbilisi, Georgia; Piraeus, Greece), covering different time periods and time scales (daily data or yearly data), and referring to different groups of individuals (selected healthy persons or random persons). The studies concluded with interesting results concerning the possible influence of geomagnetic and cosmic ray activity on the human physiological state.
Energy Spectra of Atmospheric Turbulence for Calculating Cn2 Parameter. I. Maidanak and Suffa Observatories in Uzbekistan
Authors: Shikhovtsev Artem Yu. , Kovadlo Pavel G. , Kopylov Evgeniy A. , Ibrahimov Mansur A. , Ehgamberdiev Shuhrat A. , Tillayev Yusufjon A.
Published: December 2021

Knowledge of the turbulence spectra is of interest for describing atmospheric conditions as applied to astronomical observations. This article discusses the deformations of the turbulence spectra with heights in a wide range of scales at the sites of the Maidanak and Suffa observatories. It is shown that the energy of baroclinic instability is high at the sites of these observatories and should be taken into account in the calculations of the refractive index structure constant Cn2.
A Machine-Learning Approach Combining Wavelet Packet Denoising with Catboost for Weather Forecasting
Authors: Niu Dan , Diao Li , Zang Zengliang , Che Hongshu , Zhang Tianbao , Chen Xisong
Published: December 2021

Accurate forecasting of future meteorological elements is critical and has profoundly affected human life in many aspects from rainstorm warning to flight safety. The conventional numerical weather prediction (NWP) sometimes leads to unsatisfactory performance due to inappropriate initial state settings. In this paper, a short-term weather forecasting model based on wavelet packet denoising and Catboost is proposed, which takes advantage of the fusion information combining the historical observation data with the prior knowledge from NWP. The feature selection and spatiotemporal feather addition are also explored to further improve performance. The proposed method is evaluated on the datasets provided by Beijing weather stations. Experimental results demonstrate that compared with many deep-learning or machine-learning methods such as LSTM, Seq2Seq, and random forest, the proposed Catboost model incorporated with wavelet packet denoising can achieve shorter convergence time and higher prediction accuracy.
Soil Moisture-Boundary Layer Feedbacks on the Loess Plateau in China Using Radiosonde Data with 1-D Atmospheric Boundary Layer Model
Authors: Ma Yingsai , Meng Xianhong , Ao Yinhuan , Yu Ye , Li Guangwei , Lyu Shihua , Li Jianglin , Xu Jie
Published: December 2021

The Loess Plateau is one land-atmosphere coupling hotspot. Soil moisture has an influence on atmospheric boundary layer development under specific early-morning atmospheric thermodynamic structures. This paper investigates the sensitivity of atmospheric convection to soil moisture conditions over the Loess Plateau in China by using the convective triggering potential (CTP)—humidity index (HIlow) framework. The CTP indicates atmospheric stability and the HIlow indicates atmospheric humidity in the low-level atmosphere. By comparing the model outcomes with the observations, the one-dimensional model achieves realistic daily behavior of the radiation and surface heat fluxes and the mixed layer properties with appropriate modifications. New CTP-HIlow thresholds for soil moisture-atmosphere feedbacks are found in the Loess Plateau area. By applying the new thresholds with long-time scales sounding data, we conclude that negative feedback is dominant in the north and west portion of the Loess Plateau; positive feedback is predominant in the south and east portion. In general, this framework has predictive significance for the impact of soil moisture on precipitation. By using this new CTP-HIlow framework, we can determine under what atmospheric conditions soil moisture can affect the triggering of precipitation and under what atmospheric conditions soil moisture has no influence on the triggering of precipitation.
The LAI Coupling Associated with the M6 Luxian Earthquake in China on 16 September 2021
Authors: Chen Chieh-Hung , Sun Yang-Yi , Lin Kai , Liu Jing , Wang Yali , Gao Yongxin , Zhang Dixin , Xu Rui , Chen Cong
Published: December 2021

Periodic signals replaced noise that was found in continuous seismic data, particularly in the nighttime, from the broadband seismometer at the MVP-LAI (monitoring vibrations and perturbations in the lithosphere, atmosphere and ionosphere) system before the occurrence of the Luxian earthquake on 16 September 2021. A short distance of ~150 km between the MVP-LAI system and the epicenter of the Luxian earthquake suggests the periodic singles as promising seismo-phenomena, due to that the radius of the earthquake preparation zone is ~380 km for an M6 event. Integration of geophysical parameters, including atmospheric pressure, vertical electric field, radon concentration, groundwater level and precipitation, at the MVP-LAI system provides an excellent opportunity for studying the seismo-LAI coupling associated with the Luxian earthquake. Analytical results show that ground vibrations, atmospheric pressure and total electron content varied from ~10−3 to ~10−2 Hz before the Luxian earthquake. The seismo-LAI coupling in the relatively low frequency band (~10−3 Hz) can be referred to as the acoustic-gravity waves triggered by the amplified ground vibrations. In contrast, the seismo-LAI coupling in a relatively high frequency band (~10−2 Hz) would be caused by micro-cracks and/or the high-mode natural frequency that further drives changes of TEC due to the atmospheric resonance.
Syrah Grape Skin Residues Has Potential as Source of Antioxidant and Anti-Microbial Bioactive Compounds
Authors: de Andrade Roberta Barreto , Machado Bruna Aparecida Souza , Barreto Gabriele de Abreu , Nascimento Renata Quartieri , Corrêa Luiz Claudio , Leal Ingrid Lessa , Tavares Pedro Paulo Lordelo Guimarães , Ferreira Ederlan de Souza , Umsza-Guez Marcelo Andrés
Published: December 2021

In this study, we evaluated the effects of ultrasound-assisted extraction (UAE) under different time-temperature conditions on the content of bioactive compounds, antioxidant and antimicrobial activities of Syrah grape skin residue. The application of UAE showed a positive effect on the extraction of total flavonoids, and a negative effect on total polyphenols. The temperature of 40 °C and 60 °C without the UAE caused an increase of 260% and 287% of the total polyphenols, respectively. Nineteen individually bioactive compounds were quantified. The anthocyanin concentration (malvidin-3,5-di-O-glucoside 118.8–324.5 mg/100 g) showed high variation, to a lesser extent for phenolic acids, flavonoids, flavonols, procyanidins and stilbenes due to the UAE process. The Syrah grape skin residue has a high concentration of total phenolic compounds of 196–733.7 mg·GAE/100 g and a total flavonoid content of 9.8–40.0 mg·QE/100 g. The results of free radical scavenging activity (16.0–48.7 mg/100 mL, as EC50) and its inhibition of microbial growth (0.16 mg/mL, as EC50 for S. aureus, and 0.04 mg/mL, as EC50 for E. coli) by grape skin extract (UAE 40:20) indicate high antioxidant and antibacterial activity. It was concluded that the use of ultrasound needs further analysis for its application in this context, as it has shown deleterious effects on some compounds of interest. Syrah grape skin residue has potential as a source of bioactive antioxidants, antimicrobial activity and for use as a functional food ingredient.
Shoulder Positioning during Superior Capsular Reconstruction: Computational Analysis of Graft Integrity and Shoulder Stability
Authors: Antunes Madalena , Quental Carlos , Folgado João , de Campos Azevedo Clara , Ângelo Ana Catarina
Published: December 2021

The shoulder position during fixation of the graft may be a key factor impacting the outcome of arthroscopic superior capsular reconstruction (ASCR) in irreparable rotator cuff tears (IRCTs). However, biomechanical evidence regarding this effect is lacking. The aim of this study was to evaluate the influence of the shoulder position during fixation of the graft on shoulder stability and graft tear risk in ASCR. A 3-D musculoskeletal model of the upper limb was modified to account for the fixation of the graft in ASCR, assuming a full-thickness tear of the supraspinatus tendon. The concomitant tenotomy of the long head of the biceps (LHB) tendon was also studied. The biomechanical parameters evaluated included the strain of the graft and the glenohumeral joint reaction force (GH JRF), which were used to evaluate graft integrity and shoulder stability, respectively. Fixation of the graft considering abduction angles greater than 15° resulted in a high risk for graft tearing when the arm was adducted to the side of the trunk. For abduction angles below 15°, the mean shoulder stability improved significantly, ranging between 6% and 20% (p < 0.001), compared with that in the preoperative condition. The concomitant tenotomy of the LHB tendon resulted in loss of stability when compared to ASCR with an intact LHB tendon. The position of the shoulder during fixation of the graft has a significant effect on shoulder stability and graft tear risk after ASCR in IRCTs. This study provides new and important information regarding the role of shoulder positioning during fixation of the graft.
A Review of the Unintentional Release of Feral Genetically Modified Rapeseed into the Environment
Authors: Sohn Soo-In , Pandian Subramani , Oh Young-Ju , Kang Hyeon-Jung , Ryu Tae-Hun , Cho Woo-Suk , Shin Eun-Kyoung , Shin Kong-Sik
Published: December 2021

Globally, the cultivation area of genetically modified (GM) crops is increasing dramatically. Despite their well-known benefits, they may also pose many risks to agriculture and the environment. Among the various GM crops, GM rapeseed (Brassica napus L.) is widely cultivated, mainly for oil production. At the same time, B. napus possesses a number of characteristics, including the ability to form feral populations and act as small-seeded weeds, and has a high potential for hybridization with other species. In this review, we provide an overview of the commercialization, approval status, and cultivation of GM rapeseed, as well as the status of the feral rapeseed populations. In addition, we highlight the case studies on the unintentional environmental release of GM rapeseed during transportation in several countries. Previous studies suggest that the main reason for the unintentional release is seed spillage during transport/importing of rapeseed in both GM rapeseed-cultivating and -non-cultivating countries. Despite the fact that incidents of unintentional release have been recorded often, there have been no reports of serious detrimental consequences. However, since rapeseed has a high potential for hybridization, the possibilities of gene flow within the genus, especially with B. rapa, are relatively significant, and considering their weedy properties, effective management methods are needed. Hence, we recommend that specific programs be used for the effective monitoring of environmental releases of GM rapeseed as well as management to avoid environmental and agricultural perturbations.