bluuebunny/crossref_metadata_2025 huggingface dataset:
Vegetal-Derived Bioactive Compounds as Multidrug Resistance Modulators in Colorectal Cancer
Authors: Quiñonero Francisco , Mesas Cristina , Peña Mercedes , Cabeza Laura , Perazzoli Gloria , Melguizo Consolación , Ortiz Raul , Prados Jose
Published: February 2023

Colorectal cancer is one of the leading causes of morbidity and mortality today. Knowledge of its pathogenesis has made it possible to advance the development of different therapeutic strategies. However, the appearance of drug resistance constitutes one of the main causes of treatment failure. Bioactive compounds of vegetable origin are being studied as a new strategy to improve antitumor treatment, due to their ability to regulate the pathways involved in the development of carcinogenesis or processes that are decisive in its evolution, including multidrug resistance. In vitro and in vivo studies of these substances in combination with cytotoxic drugs have shown that they reduce resistance and increase therapeutic efficacy. The objective of this review is to summarize the knowledge that is described in the scientific literature on the antitumor and chemo-sensitizing capacity of vegetable-derived biomolecules such as polyphenols, flavonoids, and terpenes. These compounds may hold a promising future in improving the treatment of colorectal cancer.
Restoration of a Textile Artefact: A Comparison of Cleaning Procedures Applied to a Historical Tapestry from the Quirinale Palace (Rome)
Authors: Guglielmi Vittoria , Comite Valeria , Lombardi Chiara Andrea , Bergomi Andrea , Boanini Elisabetta , Bonomi Roberto , Monfasani Elisa , Sassi Letizia , Borelli Mattia , Fermo Paola
Published: February 2023

The cleaning of textile artefacts and in particular historical tapestries is generally carried out using standard methods. Different cleaning procedures, including a new method based on a hydro-aspiration mechanism, recently developed by restorers with the aim of improving the efficiency of the cleaning system, were applied to a historical tapestry belonging to the lower edge of one of the tapestries of the “Ulysses Stories” series exhibited at the Quirinale Palace (Rome). The tapestry was made of wool and silk and has precious decorations made of metal yarns, which are particularly fragile. The new cleaning system was compared with the traditional methods commonly used by restorers for tapestry cleaning. For this purpose, the quantity and chemical composition of the particles removed and collected on quartz fibre filters by applying the different cleaning systems, were estimated by means of analytical techniques, such as IC (Ion Chromatography) for the quantification of the ionic species collected into the rinsing water, the TOT (Thermal Optical Transmittance) method for the quantification of the carbonaceous particles and SEM-EDX (Scanning Electron Microscopy coupled to Energy Dispersive X-ray Spectroscopy) for yarn morphological characterization and elemental analysis of the deposited particles. The objective of this study is to identify the correct cleaning method to apply to the polymaterial tapestry and, in particular, to the gilded silver and gold metallic yarns, whose conservation state requires the preservation of the “self-protection” patina necessary for the future exhibition inside the Quirinale Palace. The new hydro-aspiration method was found to be more efficient in removing dirt and preserving the structure of the metallic threads being in this way less invasive in detaching the fragile surface patina and at the same time more effective in removing dirt.
Research on Improved Retinex-Based Image Enhancement Method for Mine Monitoring
Authors: Tian Feng , Chen Tingting , Zhang Jing
Published: February 2023

An improved Retinex fusion image enhancement algorithm is proposed for the traditional image denoising methods and problems of halo enlargement and image overexposure after image enhancement caused by the existing Retinex algorithm. First, a homomorphic filtering algorithm is used to enhance each RGB component of the underground coal mine surveillance image and convert the image from RGB space to HSV space. Second, bilateral filtering and multi-scale retinex with color restoration (MSRCR) fusion algorithms are used to enhance the luminance V component while keeping the hue H component unchanged. Third, adaptive nonlinear stretching transform is used for the saturation S-component. Last, the three elements are combined and converted back to RGB space. MATLAB simulation experiments verify the superiority of the improved algorithm. Based on the same dataset and experimental environment, the improved algorithm has a more uniform histogram distribution than the multi-scale Retinex (msr) algorithm and MSRCR algorithm through comparative experiments. At the same time, the peak signal-to-noise ratio (PSNR), structural similarity (SSIM), standard deviation, average gradient, mean value, and colour picture information entropy of the images were improved by 8.28, 0.15, 4.39, 7.38, 52.92 and 2.04, respectively, compared to the MSR algorithm, and 3.97, 0.02, 34.33, 60.46, 26.21, and 1.33, respectively, compared to the MSRCR algorithm. The experimental results show that the image quality, brightness and contrast of the images enhanced by the improved Retinex algorithm are significantly enhanced, and the amount of information in the photos increases, the halo and overexposure in the images are considerably reduced, and the anti-distortion performance is also improved.
Fuzzy-PID-Based Atmosphere Packaging Gas Distribution System for Fresh Food
Authors: Zhang Haiyu , Zuo Xuanyi , Sun Boyu , Wei Bingqing , Fu Jiajie , Xiao Xinqing
Published: February 2023

The regulation process of gas distribution systems for atmosphere packaging has the characteristics of being nonlinear time varying and having hysteric delay. When the conventional proportional-integral-derivative (PID) control algorithm is applied to this kind of system, it is difficult to set the parameters as the process is time consuming and has poor reliability. For these reasons, this paper designs a gas distribution system for fresh food atmosphere packaging based on a fuzzy PID controller. The step response method is used to construct the system’s mathematical model under the given conditions and to optimize the gas distribution control flow. A simulation experimental platform to compare between the fuzzy PID controller and a conventional PID controller is designed, and the effectiveness of the fuzzy PID control strategy is verified, which proves that it can improve the performance of the monitoring system. The system can realize the remote monitoring of the gas distribution processes through the use of a mobile phone communication network. The data transmission is reliable, the operation is convenient, and, at the same time, the overall efficiency is improved. The results of the system simulation and the gas distribution for atmosphere packaging show that the fuzzy PID algorithm has a faster gas distribution speed and good environmental adaptability as the controller of the gas distribution system. The results show that the stability time of the fuzzy PID controller is about 38 s, while the stability time of the conventional PID controller is about 85 s. The concentration error of fresh gases is ±0.25% floating, the accuracy is increased by 12 times, and the gas distribution speed is increased by about 50% when the system is stable.
Synthesis and Characterization of Cerium Oxide Nanoparticles: Effect of Cerium Precursor to Gelatin Ratio
Authors: Ioannou Maria Eleni , Pouroutzidou Georgia K. , Chatzimentor Iason , Tsamesidis Ioannis , Florini Nikoletta , Tsiaoussis Ioannis , Lymperaki Evgenia , Komninou Philomela , Kontonasaki Eleana
Published: February 2023

Hemocompatible nanoparticles with reactive oxygen species (ROS) scavenging properties for titanium implant surface coatings may eliminate implant failure related to inflammation and bacterial invasion. Cerium (Ce) is a rare earth element, that belongs to the lanthanide group. It exists in two oxidation states, Ce+3 and Ce+4, which contribute to antioxidant, catalytic, antibacterial, and ROS-scavenging properties. The purpose of the present study was to synthesize ceria nanoparticles and to evaluate their hemocompatibility and ROS scavenging properties. The synthesis of Ce-NPs was performed via the sol-gel method, and five different ratios of cerium precursors to gelatin were evaluated. Their characterization was achieved through FTIR, XRD, SEM, and TEM. Hemocompatibility and ROS analysis were evaluated at different concentrations with human erythrocytes. The morphology and size distribution were certified by TEM and the cubic CeO2 fluorite structure was identified by selected area electron diffraction and high-resolution TEM. The particle size of the lowest Ce concentration presented a mean diameter of 10 nm. At concentrations of <500 μg/mL, no hemolytic effect was observed. At the highest concentrations, no hemolytic behavior was recorded for samples with the highest Ce precursor, which also presented ROS scavenging properties (10–50% reduction in ROS). These properties make those CeO2 NPs unique candidates as nanofillers or nanocoatings with antibacterial properties.
EMG Signs of Motor Units’ Enlargement in Stroke Survivors
Authors: Pinto Talita P. , Turolla Andrea , Gazzoni Marco , Agostini Michela , Vieira Taian M.
Published: February 2023

The degeneration of lower motoneurons has often been reported in stroke survivors, with possible collateral reinnervation from the surviving motoneurons to the denervated muscle fibers. Under this assumption, a stroke would be expected to increase the size of motor units in paretic muscles. We indirectly address this issue with electrical stimulation and surface electromyography, asking whether stroke leads to greater variations in the amplitude of M waves elicited in paretic muscles than in contralateral, non-paretic muscles. Current pulses at progressively greater intensities were applied to the musculocutaneous nerve, stimulating motoneurons supplying the biceps brachii of eight stroke patients. The size of increases in the amplitude of M waves elicited consecutively, hereafter defined as increments, was considered to evaluate changes in the innervation ratio of biceps brachii motor units following stroke. Our findings showed that patients presented significantly (p = 0.016) greater increments in muscles of paretic than in non-paretic limbs. This result corroborates the notion that collateral reinnervation takes place after stroke, enlarging motor units’ size and the magnitude of the muscle responses. Therefore, the non-invasive analysis proposed here may be useful for health professionals to assess disease progression by tracking for neuromuscular changes likely associated with clinical outcomes in stroke survivors, such as in the muscles’ strength.
Improved Image Quality Assessment by Utilizing Pre-Trained Architecture Features with Unified Learning Mechanism
Authors: Ryu Jihyoung
Published: February 2023

The purpose of the no-reference image quality assessment (NR-IQA) is to measure perceived image quality based on subjective judgments; however, due to the lack of a clean reference image, this is a complicated and unresolved challenge. Massive new IQA datasets have facilitated the creation of deep learning-based image quality measurements. We present a unique model to handle the NR-IQA challenge in this research by employing a hybrid strategy that leverages from pre-trained CNN model and the unified learning mechanism that extracts both local and non-local characteristics from the input patch. The deep analysis of the proposed framework shows that the model uses features and a mechanism that improves the monotonicity relationship between objective and subjective ratings. The intermediary goal was mapped to a quality score using a regression architecture. To extract various feature maps, a deep architecture with an adaptive receptive field was used. Analyses of this biggest NR-IQA benchmark datasets demonstrate that the suggested technique outperforms current state-of-the-art NR-IQA measures.
Hierarchical Tensor Decomposition of Module Partition for the Mechanical Simulation
Authors: Zhang Tao , Ai Yibo , Zhang Weidong
Published: February 2023

The mechanical simulation experiment can provide guidelines for the structural design of materials, but the module partition of mechanical simulation experiments is still in its infancy. A mechanical simulation contour, e.g., strain and stress contour, has hierarchical characteristics. By analyzing the contour at different layers, the physical properties of the structure material can be improved. Current state-of-the-art methods cannot distinguish between simulation strain contours, as well as sparsely distributed spots of strain (stress concentrations) from simulation strain contour images, resulting in simulation data that does not accurately reflect real strain contours. In this paper, a Hierarchical Tensor Decomposition (HTD) method is proposed to extract hierarchical contours and stress concentrations from the simulation strain contours and then improve the mechanical simulation. HTD decomposes a tensor into three classes of components: the multi-smooth layers, the sparse spots layer, and the noise layer. The number of multismooth layers is determined by the scree plot, which is the difference between the smooth layers and the sparse spots layer. The proposed method is validated by several numerical examples, which demonstrate its effectiveness and efficiency. A further benefit of the module partition is the improvement of the mechanical structural properties.
Dynamic Synthesis of Three−Point Circle Peripheral Docking Technology Pose
Authors: Xi Lin , Ni Huasheng , Wang Buyun , Li Zengchan , Zhang Chenghao
Published: February 2023

Research on space docking technology was first motivated by the application scenario of space station docking in the aviation field. Due to the maturity of this technology, its application field is expanding to other industries. To benefit the intelligent transportation field, this study uses space docking technology to realize combination and reconstruction between car bodies. Different spatial docking methods and structural characteristics are determined by different application scenarios. The docking of the space station is completed in the suspended state of the body in the outer space environment, which requires advanced technology, is high in hardware cost, and involves a small channel diameter. In this study, the docking of the reconstructed vehicle is completed on the ground; thus, it is low in hardware cost and involves a large channel diameter. Based on the above technical requirements, a three−point circular peripheral docking method is designed for the reconstructed vehicle. A visual positioning system is built, the mapping relationship between the camera coordinate system and the landmark coordinate system rotation matrix and translation vector is established, and the adaptive capture behavior is realized by path planning through the inverse pose solution model. Simulation experiments demonstrate that the active and passive vehicle bodies can achieve compliance capture with small collision force under the two conditions of forward collision and oblique collision, and the recovery coefficient after collision and docking is in the range of (0, 0.01). The acceleration decay process under two working conditions is measured in the crash test of a sample vehicle, which verifies the feasibility of the space reconstruction of the vehicle docking mechanism and the ability of this configuration to achieve tasks, providing a constructive idea for space docking technology with a large channel diameter.
Computer Percolation Models for Espresso Coffee: State of the Art, Results and Future Perspectives
Authors: Angeloni Simone , Giacomini Josephin , Maponi Pierluigi , Perticarini Alessia , Vittori Sauro , Cognigni Luca , Fioretti Lauro
Published: February 2023

Coffee is one of the most consumed beverages in the world. This has two main consequences: a high level of competitiveness among the players operating in the sector and an increasing pressure from the supply chain on the environment. These two aspects have to be supported by scientific research to foster innovation and reduce the negative impact of the coffee market on the environment. In this paper, we describe a mathematical model for espresso coffee extraction that is able to predict the chemical characterisation of the coffee in the cup. Such a model has been tested through a wide campaign of chemical laboratory analyses on espresso coffee samples extracted under different conditions. The results of such laboratory analyses are compared with the simulation results obtained using the aforementioned model. The comparison shows a close agreement between the real and in silico extractions, revealing that the model is a very promising scientific tool to take on the challenges of the coffee market.
Deep Parallel Optimizations on an LASG/IAP Climate System Ocean Model and Its Large-Scale Parallelization
Authors: Hao Huiqun , Jiang Jinrong , Wang Tianyi , Liu Hailong , Lin Pengfei , Zhang Ziyang , Niu Beifang
Published: February 2023

This paper proposes a series of parallel optimizations on a high-resolution ocean model, the LASG/IAP Climate System Ocean Model (LICOM), which was independently developed by the Institute of Atmospheric Physics of the Chinese Academy of Sciences. The version of LICOM that we used was LICOM 2.1. In order to improve the parallel performance of LICOM, a series of parallel optimization methods were applied. We optimized the parallelization scheme to tackle the problem of load imbalance. Some communication optimizations were implemented, including data packing, the application of the least communication algorithm, and the replacement of communications with calculations. Furthermore, for the calculation procedures, we implemented some mature optimizations and expanded functions in a loop. Additionally, a hybrid of MPI and OpenMP, as well as an asynchronous parallel IO, was used. In this work, the optimized version of LICOM 2.1 was able to achieve a speedup of more than two times compared with the original code. The parallelization scheme optimization and the communication optimization produced considerable improvement in performance in the large-scale parallelization. Meanwhile, the newly optimized LICOM could scale up to 245,760 processor cores. However, for the original version, there was no speedup when scaled up to over 10,000 processor cores. Additionally, the problem of jumpy wall time during the time integration process was also tackled with this optimization. Finally, we conducted a practical simulation from 1993 to 2007 by using the optimized version of LICOM 2.1. The results showed that the mesoscale vortex was well simulated by the model.
A Forecasting Approach to Cryptocurrency Price Index Using Reinforcement Learning
Authors: Mariappan L. , Pandian J. , Kumar V. , Geman Oana , Chiuchisan Iuliana , Năstase Carmen
Published: February 2023

Cryptocurrency has emerged as a well-known significant component with both economic and financial potential in recent years. Unfortunately, Bitcoin acquisition is not simple, due to uneven business and significant rate fluctuations. Traditional approaches to price forecasting have proven incapable of proving adequate data and solutions because prices can now be forecast in real time. We recommended a machine learning-based alternative for a mortgage lender based on highlighted problems in forecasting the price of Bitcoin. The proposed system included a reinforcement learning algorithm for price estimation and forecasting, as well as a blockchain framework for an efficient and secure environment. The proposed prediction, compared to other state-of-the-art strategies in this sector, demonstrated better performance. In this system, the proposed prediction reached improved consistency, in comparison to other systems, with respect to Monero (XMR), Litecoin (LTC), Oryen (ORY), and Bitcoin (BTC).
Static Bacterial Leakage in Different Conometric Connections: An In Vitro Study
Authors: D’Ercole Simonetta , Dotta Tatiane Cristina , Iezzi Giovanna , Cipollina Alessandro , Pedrazzi Vinicius , Piattelli Adriano , Petrini Morena
Published: February 2023

This in vitro study aims to evaluate the bacterial microleakage of three conometric connections. Sixty dental implants (3P implafavourite Scalenghe) were divided in groups (n = 20): Cone–Morse with passing screw (Group 1); Cone–Morse with solid abutment (Group 2); and Conometric connection with esthetic abutment (Group 3). The implants were fixed in resin bases. Then, 1.0 µL of Streptococcus oralis (SO) was inoculated in the internal platform in 10 fixtures for each group, and another 10 were inoculated with Pseudomonas aeruginosa (PA). The abutments were then screwed, and five implants from each subgroup were randomly selected for SEM inspection to ensure that the abutments were installed correctly. Data were submitted to statistical analysis, ANOVA and Fisher’s Least Significant Difference (p ≤ 0.05). The turbidity of the broth was monitored for 14 days of follow-up in order to determine the penetration of the bacterial suspension into the surrounding solution, but the observation of the samples lasted until the 90th day, in which there was no difference between the two. Microbial contamination was found in 30%, 20%, and 50% of Group 1, Group 2, and Group 3, respectively, but there were no statistically significant differences between the groups, and PA showed greater infiltration than SO. Although no statistically significant differences were found, cone morse connections showed lower infiltration percentages, respective to the conometric connection with 18° angle.
Sex-Based Differences in Bronchial Asthma: What Are the Mechanisms behind Them?
Authors: Mokra Daniela , Barosova Romana , Mokry Juraj
Published: February 2023

Sex-based differences in bronchial asthma can already be observed in childhood, at which time allergic atopic asthma is more frequently found in boys than in girls. In adulthood, higher prevalence of asthma is reported in women, especially for the more severe neutrophilic subtype associated with obesity, which responds poorly to corticosteroids. Sex-based differences seem to be attributable to changing levels of estrogens, progesterone, and testosterone, which may exert mainly pro-inflammatory (estrogens, progesterone) or anti-inflammatory effects (testosterone). Sex steroids differentially influence lung immune responses, airway reactivity, and pulmonary circulation and may thereby contribute to the higher susceptibility of females to more serious complications resulting from inflammatory lung diseases compared to males. However, other factors, such as anatomical and physiological differences in the lungs, differences in genetically conditioned factors, obesity and lifestyle, smoking, exposure to environmental and occupational factors, chronic stress, etc., may also contribute to the sex-based differences in asthma. Elucidation of the mechanisms behind these differences may contribute to more appropriate personalized therapy for asthma. For the review, articles in the English language from the PubMed database were used.
Comparative Study on the Total Phenolics, Total Flavonoids, and Biological Activities of Papaver rhoeas L. Extracts from Different Geographical Regions of Morocco
Authors: Hmamou Anouar , Kara Mohammed , Khomsi Mostafa El , Saleh Asmaa , Al Kamaly Omkulthom , Bendaoud Ahmed , El Ouadrhiri Faiçal , Adachi Abderrazzak , Tlemcani Sara , Eloutassi Noureddine , Lahkimi Amal
Published: February 2023

In this research, a comparative analysis was carried out to characterize the content of phenolics and biological activities of the whole plant of Papaver rhoeas L. (P. rhoeas) from different geographical regions of Morocco, as well as to determine the synergistic antimicrobial and antioxidant effects of all parts of P. rhoeas. The determination of total polyphenol content (TPC), total flavonoid content (TFC), and total anthocyanin content (TA) in extracts of whole plants of P. rhoeas from three different geographical regions: Taounate (P1E), Fez (P2E), and Sefrou (P3E) were estimated by the Folin–Ciocalteu reaction, the aluminum trichloride method and the differential pH absorption technique, respectively. Two tests were used to evaluate the antioxidant power of our samples: the DPPH test and the TAC test. Using two methods, disk diffusion and microdilution, antimicrobial activity was studied against four pathogenic bacteria and one yeast. The results of TPC, TFC, and TA show that the P3E sample is the richest in polyphenols, flavonoids, and anthocyanins, with values 37.33 ± 1.307 mg GAE/g, 4.72 ± 0.346 QE/g, and 1.77 ± 0.026 CGE/g, respectively. In addition, P3E showed the best antioxidant activity with an IC50 = 0.27 ± 0.001 mg/mL and TAC = 9.99 ± 0.768 mg AAE/g, respectively. The results of antimicrobial activity showed significant activity on almost all the tested strains. The lowest MIC was recorded for P3E against E. coli ATCC 25922 and E. coli CIP 53126 strains at 0.78 and 0.78 mg/mL, respectively. These results show that the geographical region can influence the plant’s phytochemistry and then these biological activities.
Carbonate Pore Shape Evaluation Using Digital Image Analysis, Tomography, and Effective Medium Theory
Authors: Ziganshin Eduard , Nourgaliev Danis , Bayuk Irina , Kadyrov Rail , Nguyen Thanh Hung
Published: February 2023

Carbonate rocks have a wide variety of pore shapes and different types of grains, which greatly affect the elastic properties and characteristics of the reservoir. This causes certain difficulties in petroelastic modeling. One of the problems is the scale of the input data, which is then used to build the rock physics model. The paper presents the results of studying three core samples of carbonate rocks of the Upper Devonian and Lower Carboniferous age, which are located in the South Tatar arch (Volga-Ural oil and gas basin (Russia)). To evaluate the structural characteristics of the pore space, the effective medium theory is used. The input data are the results of laboratory studies that include measurements of the velocities of longitudinal and transverse waves, porosity, and thin section and computed tomography analysis. When using the computed tomography, the core samples are analyzed at different resolution (12–37 µm/voxel). The tomography studies of pore space at different scales provide rather different values of porosity and pore aspect ratio. The tomography-based porosity estimations also differ from the experimentally measured porosity (up to 10%). The pore space characteristics provided by different datasets are used to build a rock physics model for the studied rocks that helps to estimate the elastic wave velocities with three different methods of effective medium theory (self-consistent approximation, differential effective medium (DEM), and the Kuster–Toksöz method). A comparison of the velocity estimations with their experimental analogs for dry rocks may indicate the presence of microcracks whose size is beyond the tomography resolution. Improved rock physics models incorporating both pores and microcracks are then used to predict the elastic wave velocities of fluid-saturated rock in a wide porosity range. It is demonstrated that the predicted values significantly differ (up to 30%) from those provided by the rock physics (RP) models constructed without the support of the tomography results. Moreover, other types of models are considered in which the difference in experimental and theoretical velocities is attributed to changes in the host matrix properties as compared to the calcite polycrystal, which are caused by various reasons.
Method and Experimental Study of Zeolite Crystal Manipulation Based in Hydrodynamic Forces for Single Crystal Assessment
Authors: De la Torre Dann , Garcés-Chávez Veneranda , Sanchez-Lopez Juan , O’Donnell Kevin , Nieto-Hipólito Juan , Yocupicio-Gaxiola Rosario
Published: February 2023

In this work, we report an optofluidic system for manipulation of orientation of zeolite crystals near the bottom of a rectangular cross-sectional, straight, quartz microfluidic channel. Manipulation is accomplished by using two computer-controlled syringe pumps that generate adequate hydrodynamic forces for translation and rotation of crystals. Rotation of a crystal around its longitudinal axis allows us to inspect its four major faces for defects. Coffin-shaped zeolite crystals have been studied by several authors by fixing them to a substrate, using two different crystals to assess the roof and gable orientations. The proposed system permits complete assessment of a single crystal by shifting it between roof and gable orientations; moreover the medium can be controlled. Computational fluid dynamics simulations show that crystals in free motion near the bottom of the channel should move faster than the velocity estimated from video. An opposing force, which prevents the crystals from moving freely, has been calculated in order to match translation velocities from simulations and experiments for three given flow rates. The reported optofluidic system is proposed as a novel tool that we believe will open new possibilities for individual zeolite crystal assessment by manipulation of its orientation and medium control.
Human Pose Estimation Using MediaPipe Pose and Optimization Method Based on a Humanoid Model
Authors: Kim Jong-Wook , Choi Jin-Young , Ha Eun-Ju , Choi Jae-Ho
Published: February 2023

Seniors who live alone at home are at risk of falling and injuring themselves and, thus, may need a mobile robot that monitors and recognizes their poses automatically. Even though deep learning methods are actively evolving in this area, they have limitations in estimating poses that are absent or rare in training datasets. For a lightweight approach, an off-the-shelf 2D pose estimation method, a more sophisticated humanoid model, and a fast optimization method are combined to estimate joint angles for 3D pose estimation. As a novel idea, the depth ambiguity problem of 3D pose estimation is solved by adding a loss function deviation of the center of mass from the center of the supporting feet and penalty functions concerning appropriate joint angle rotation range. To verify the proposed pose estimation method, six daily poses were estimated with a mean joint coordinate difference of 0.097 m and an average angle difference per joint of 10.017 degrees. In addition, to confirm practicality, videos of exercise activities and a scene of a person falling were filmed, and the joint angle trajectories were produced as the 3D estimation results. The optimized execution time per frame was measured at 0.033 s on a single-board computer (SBC) without GPU, showing the feasibility of the proposed method as a real-time system.
Structure and Optical Properties of Transparent Cobalt-Doped ZnO Thin Layers
Authors: Potera Piotr , Virt Ihor S. , Cieniek Bogumił
Published: February 2023

Transparent thin layers of cobalt-doped ZnO were produced with the pulsed laser deposition method. The cobalt content of the original solid solution was 20% at. The crystallographic structure was examined by X-ray diffraction, which showed that the fabricated layers crystallized in the wurtzite phase and had a dominant orientation along the a-axis. The texture coefficient (increasing from F = 0.08 for the non-annealed layer to F = 0.94 for the annealed layer at 400 °C) and grain size (D = 110 ÷ 140 nm) were calculated. Optical constants, such as the refractive index n (1.62) and the extinction coefficient k (0.1 ÷ 0.4), were determined from the ultraviolet–visible–near-infrared transmission spectrum using the envelope method. The value of the optical band gap was determined, which is lower than for pure ZnO. Increasing the annealing temperature of the ZnO:Co layer increases the Urbach energy from 0.20 to 0.25 eV, which shows the difference in the type of growth defects in the ZnO matrix.
Classification of the Central Effects of Transcutaneous Electroacupuncture Stimulation (TEAS) at Different Frequencies: A Deep Learning Approach Using Wavelet Packet Decomposition with an Entropy Estimator
Authors: Uyulan Çağlar , Mayor David , Steffert Tony , Watson Tim , Banks Duncan
Published: February 2023

The field of signal processing using machine and deep learning algorithms has undergone significant growth in the last few years, with a wide scope of practical applications for electroencephalography (EEG). Transcutaneous electroacupuncture stimulation (TEAS) is a well-established variant of the traditional method of acupuncture that is also receiving increasing research attention. This paper presents the results of using deep learning algorithms on EEG data to investigate the effects on the brain of different frequencies of TEAS when applied to the hands in 66 participants, before, during and immediately after 20 min of stimulation. Wavelet packet decomposition (WPD) and a hybrid Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) model were used to examine the central effects of this peripheral stimulation. The classification results were analysed using confusion matrices, with kappa as a metric. Contrary to expectation, the greatest differences in EEG from baseline occurred during TEAS at 80 pulses per second (pps) or in the ‘sham’ (160 pps, zero amplitude), while the smallest differences occurred during 2.5 or 10 pps stimulation (mean kappa 0.414). The mean and CV for kappa were considerably higher for the CNN-LSTM than for the Multilayer Perceptron Neural Network (MLP-NN) model. As far as we are aware, from the published literature, no prior artificial intelligence (AI) research appears to have been conducted into the effects on EEG of different frequencies of electroacupuncture-type stimulation (whether EA or TEAS). This ground-breaking study thus offers a significant contribution to the literature. However, as with all (unsupervised) DL methods, a particular challenge is that the results are not easy to interpret, due to the complexity of the algorithms and the lack of a clear understanding of the underlying mechanisms. There is therefore scope for further research that explores the effects of the frequency of TEAS on EEG using AI methods, with the most obvious place to start being a hybrid CNN-LSTM model. This would allow for better extraction of information to understand the central effects of peripheral stimulation.
Learning and Compressing: Low-Rank Matrix Factorization for Deep Neural Network Compression
Authors: Cai Gaoyuan , Li Juhu , Liu Xuanxin , Chen Zhibo , Zhang Haiyan
Published: February 2023

Recently, the deep neural network (DNN) has become one of the most advanced and powerful methods used in classification tasks. However, the cost of DNN models is sometimes considerable due to the huge sets of parameters. Therefore, it is necessary to compress these models in order to reduce the parameters in weight matrices and decrease computational consumption, while maintaining the same level of accuracy. In this paper, in order to deal with the compression problem, we first combine the loss function and the compression cost function into a joint function, and optimize it as an optimization framework. Then we combine the CUR decomposition method with this joint optimization framework to obtain the low-rank approximation matrices. Finally, we narrow the gap between the weight matrices and the low-rank approximations to compress the DNN models on the image classification task. In this algorithm, we not only solve the optimal ranks by enumeration, but also obtain the compression result with low-rank characteristics iteratively. Experiments were carried out on three public datasets under classification tasks. Comparisons with baselines and current state-of-the-art results can conclude that our proposed low-rank joint optimization compression algorithm can achieve higher accuracy and compression ratios.
Improving User Experience with Recommender Systems by Informing the Design of Recommendation Messages
Authors: Falconnet Antoine , Coursaris Constantinos K. , Beringer Joerg , Van Osch Wietske , Sénécal Sylvain , Léger Pierre-Majorique
Published: February 2023

Advice-giving systems such as decision support systems and recommender systems (RS) utilize algorithms to provide users with decision support by generating ‘advice’ ranging from tailored alerts for situational exception events to product recommendations based on preferences. Related extant research of user perceptions and behaviors has predominantly taken a system-level view, whereas limited attention has been given to the impact of message design on recommendation acceptance and system use intentions. Here, a comprehensive model was developed and tested to explore the presentation choices (i.e., recommendation message characteristics) that influenced users’ confidence in—and likely acceptance of—recommendations generated by the RS. Our findings indicate that the problem and solution-related information specificity of the recommendation increase both user intention and the actual acceptance of recommendations while decreasing the decision-making time; a shorter decision-making time was also observed when the recommendation was structured in a problem-to-solution sequence. Finally, information specificity was correlated with information sufficiency and transparency, confirming prior research with support for the links between user beliefs, user attitudes, and behavioral intentions. Implications for theory and practice are also discussed.
Multi-Scale Aggregation Residual Channel Attention Fusion Network for Single Image Deraining
Authors: Wang Jyun-Guo , Wu Cheng-Shiuan
Published: February 2023

Images captured on rainy days are prone to rain streaking on various scales. These images taken on a rainy day will be disturbed by rain streaks of varying degrees, resulting in degradation of image quality. This study sought to eliminate rain streaks from images using a two-stage network architecture involving progressive multi-scale recovery and aggregation. The proposed multi-scale aggregation residual channel attention fusion network (MARCAFNet) uses kernels of various scales to recover details at various levels of granularity to enhance the robustness of the model to streaks of various sizes, densities, and shapes. When applied to benchmark datasets, the proposed method outperformed other state-of-the-art schemes in the restoration of image details without distorting the image structure.
Study on Stiffness Parameters of the Hardening Soil Model in Sandy Gravel Stratum
Authors: Shi Xiaomeng , Sun Jinglai , Qi Yi , Zhu Xiangyang , Zhang Xueming , Liang Ruisong , Chen Hongjiang
Published: February 2023

Sandy gravel stratum is very common in tunnels and underground engineering projects. The accurate determination of mechanical parameters is crucial for engineering design and construction. The Hardening Soil (HS) Model, which accounts for both shear hardening and compression hardening, has demonstrated advantages in numerical simulations. This study conducts large-scale mechanical experiments, including triaxial drained shear tests, loading-unloading tests, and standard consolidation tests, on sandy gravel specimens. The results reveal that the ratio of the three stiffness parameters in the HS Model, namely Young’s modulus under triaxial loading (E50), oedometric loading (Eoed), and unloading-reloading (Eur) is 1:1:4.3. The validity of the established stiffness ratio relationship is verified through numerical simulations of a foundation pit project and comparison with field monitoring data, demonstrating a consistent agreement between the simulation results and actual monitoring values.
An Improved Visual SLAM Based on Map Point Reliability under Dynamic Environments
Authors: Ni Jianjun , Wang Li , Wang Xiaotian , Tang Guangyi
Published: February 2023

The visual simultaneous localization and mapping (SLAM) method under dynamic environments is a hot and challenging issue in the robotic field. The oriented FAST and Rotated BRIEF (ORB) SLAM algorithm is one of the most effective methods. However, the traditional ORB-SLAM algorithm cannot perform well in dynamic environments due to the feature points of dynamic map points at different timestamps being incorrectly matched. To deal with this problem, an improved visual SLAM method built on ORB-SLAM3 is proposed in this paper. In the proposed method, an improved new map points screening strategy and the repeated exiting map points elimination strategy are presented and combined to identify obvious dynamic map points. Then, a concept of map point reliability is introduced in the ORB-SLAM3 framework. Based on the proposed reliability calculation of the map points, a multi-period check strategy is used to identify the unobvious dynamic map points, which can further deal with the dynamic problem in visual SLAM, for those unobvious dynamic objects. Finally, various experiments are conducted on the challenging dynamic sequences of the TUM RGB-D dataset to evaluate the performance of our visual SLAM method. The experimental results demonstrate that our SLAM method can run at an average time of 17.51 ms per frame. Compared with ORB-SLAM3, the average RMSE of the absolute trajectory error (ATE) of the proposed method in nine dynamic sequences of the TUM RGB-D dataset can be reduced by 63.31%. Compared with the real-time dynamic SLAM methods, the proposed method can obtain state-of-the-art performance. The results prove that the proposed method is a real-time visual SLAM, which is effective in dynamic environments.
Development of a Digital Well Management System
Authors: Pavel Yurievich Ilyushin , Kirill Andreevich Vyatkin , Anton Vadimovich Kozlov
Published: February 2023

The modern oil industry is characterized by a strong trend towards the digitalization of all technological processes. At the same time, during the transition of oil fields to the later stages of development, the issues of optimizing the consumed electricity become relevant. The purpose of this work is to develop a digital automated system for distributed control of production wells using elements of machine learning. The structure of information exchange within the framework of the automated system being created, consisting of three levels of automation, is proposed. Management of the extractive fund is supposed to be based on the work of four modules. The “Complications” module analyzes the operation of oil wells and peripheral equipment and, according to the embedded algorithms, evaluates the cause of the deviation, ways to eliminate it and the effectiveness of each method based on historical data. The “Power Consumption Optimization” module allows integrating algorithms into the well control system to reduce energy consumption by maintaining the most energy-efficient operation of pumping equipment or optimizing its operation time. The module “Ensuring the well flow rate” allows you to analyze and determine the reasons for the decrease in production rate, taking into account the parameters of the operation of adjacent wells. The Equipment Anomaly Prediction module is based on machine learning and helps reduce equipment downtime by predicting and automatically responding to potential deviations. As a result of using the proposed system, many goals of the oil company are achieved: specific energy consumption, oil shortages, and accident rate are reduced, while reducing the labor costs of engineering and technological personnel for processing the operation parameters of all process equipment.
Indices of Pacific Walker Circulation Strength
Authors: Kosovelj Katarina , Zaplotnik Žiga
Published: February 2023

The Pacific Walker circulation (PWC) significantly affects the global weather patterns, the distribution of mean precipitation, and modulates the rate of global warming. In this study, we review and compare 10 different indices measuring the strength of the PWC using data from the ERA5 reanalyses for the period 1951–2020. We propose a revised velocity potential index, while we also discuss two streamfunction indices. We show that the normalized PWC indices largely agree on the annual-mean strength of the PWC, with the highest correlations observed between indices that measure closely linked physical processes. The indices tend to disagree the most during the periods of strong El Niño. Therefore, the trends in PWC strength vary depending on the chosen time frame. While trends for 1981–2010 show PWC strengthening, trends for 1951–2020 are mostly neutral, and the recent trends (2000–2020) show (insignificant) weakening of the PWC. The results hint at the multidecadal variability in the PWC strength with a period of approximately 35 years, which would result in continued weakening of the PWC in the coming decade.
Race and Street-Level Firework Legalization as Primary Determinants of July 4th Air Pollution across Southern California
Authors: Masri Shahir , Flores Leonel , Rea Jose , Wu Jun
Published: February 2023

Air pollution is a major public health threat that is associated with asthma, cardiovascular disease, respiratory disease and all-cause mortality. Among the most important acute air pollution events occurring each year are celebrations involving fireworks, such as the 4th of July holiday in the United States. In this community-engaged study, academic partners and residents collaborated to collect indoor and outdoor PM2.5 concentration measurements in the disadvantaged city of Santa Ana, California, using low-cost AtmoTube sensor devices before, during and after the July 4th firework celebration, while also examining July 4th data extracted from the PurpleAir sensor network across over a hundred other cities in southern California. Average outdoor PM2.5 concentrations on July 4th were found to be three-to-five times higher than baseline, with hourly concentrations exceeding 160 μg/m3. Outdoor averages were roughly 30% to 100% higher than indoor levels. The most polluted cities exhibited 15-times higher PM2.5 levels compared with the least contaminated cities and were often those where household-level fireworks were legal for sale and use. Race/ethnicity was found to be the leading predictor of July 4th-related air pollution across three counties in southern California, with greater PM2.5 being associated with higher proportions of Hispanic residents and lower proportions of White residents. The findings from this study underscore the importance of environmental justice as it relates to firework-related air pollution exposure, and the critical role city- and county-level firework policies play in determining exposure.