Patrol missiles are a common type of unmanned aerial vehicle, which can be efficiently used for reconnaissance and sensing. In this work, target detection and the damage assessment of typical mobile ground targets by patrol missiles are studied, and a new method, combining the YOLO v3 with the VGG networks, is proposed for the problem. Specifically, with YOLO v3 as the precursor, the proposed method can detect, classify, and localize ground targets accurately and quickly. Then, the image blocks of detected targets are fed into the lightweight VGG networks, which can evaluate their damage level coarsely. Meanwhile, based on class activation mapping (CAM) and deconvolution, we further analyse the activation intensity of clustered convolution kernels, which helps determine whether the targets’ key components are destroyed. Unlike traditional image change detection methods, which require images before and after a strike for comparison, the proposed method learns the target model through extensive training and can assess the target’s damage status in a timely and online manner. Compared to previous learning-based methods, our detailed analysis with convolutional feature visualization of the damaged targets and their components gives a more interpretable perspective. Finally, Unity simulation experiments prove the proposed method’s effectiveness, which improves the accuracy of damage level assessment by 16.0% and 8.8% compared with traditional image-change-detection-based methods and the two-CNN learning-based method. The convolutional feature clustering method evaluates the status of the targets’ key components with an accuracy of 72%. Full article

The analysis of racket stiffness effect on muscle activity during movement associated with badminton is essential for a better understanding of which badminton racket is better for the athletes to use. The present study aimed to evaluate the effect of racket stiffness on muscle activity and activation time of the upper limb muscles—biceps (Bicp), lateral head (TLat) and long head (TLong) of the triceps—when performing the backhand smash (BH) movement using two rackets with different levels of stiffness. A group of 6 volunteers, with an average age of 21.8 (±4.5) years, and an average badminton practice time of 10.7 (±5.3) years, performed 10 valid repetitions of the movement with each racket, and the muscle activity was collected using surface electromyography. Observing the results shows that the most excited muscle in the BH smash, in terms of (%MVC), is the TLat, regardless of the stiffness of the racket, which shows 56.9% for the Duora 33 and about 68.9% for the Duora 88, comparing with the Bicp and the TLong, respectively. Also, it was observed that the more rigid racket (Duora 88) showed a higher muscular activity for the Bicp and TLat muscles. Full article

This study evaluates the antimicrobial and antioxidant activities of five essential oils (EO): pine oil, thyme oil, sage oil, fennel oil, and eucalyptus essential oils. To identify the chemical composition of the essential oils, we used gas chromatography coupled to a mass spectrometer (GC-MS). EO are predominantly characterized by the presence of monoterpene hydrocarbons and oxygenated monoterpenes, except in the case of fennel essential oil which contains phenylpropanoids as its main components. The antimicrobial activity of the EO was highlighted on four standard microbial strains (two Gram-negative strains-Escherichia coli ATCC 25922 and Pseudomonas aeruginosa ATCC 27853; one Gram-positive strain Staphylococcus aureus ATCC 25923, and one yeast strain-Candida albicans ATCC 10231). Antimicrobial activity was assessed by measuring the diameter of the inhibition zone, and by determining the values of the minimum inhibitory concentration (MIC) and minimum concentration of biofilm eradication (MCBE). Analyzing the diameter values of the inhibition zones we observed increased efficiency of thyme essential oil, which showed the highest values for all tested microbial species. The results of tests performed in a liquid confirm the high sensitivity of the standard strain Escherichia coli ATCC 25922 to the action of all essential oils, the lowest values of MIC being recorded for sage and thyme essential oils. For the most essential oils tested in this study, the MCBE values are close to the MIC values, except for the pine EO which seems to have stimulated the adhesion of the yeast strain at concentrations lower than 5%. The study highlights the antimicrobial activity of the tested essential oils on Gram-positive and Gram-negative strains. Full article

There are few studies on optimizing the dynamic and static characteristics of direct-drive turntables. In terms of dynamic and static characteristic analysis, most studies only analyze the dynamic and static characteristics of direct-drive turntables in a single machining position and working condition. The optimization is mainly for individual parts without considering the overall structure of the turntable. A multi-objective optimization method based on the back-propagation neural network (BP) and the non-dominated sorting genetic algorithm is proposed to ensure the machining accuracy of the direct-drive turntable, reduce the total mass, and improve its dynamic and static characteristics. In this paper, the workpiece and direct-drive turntable are studied as a whole. Static and modal analyses determine the maximum deformation locations and vulnerable parts of the turntable. Topology optimization analysis was used to find the redundant mass parts. We determined the optimization objectives and dimensional parameters based on the direct-drive turntable’s structural and topology optimization results. Using a central composite experimental design, we obtained test points and fitted them to a response surface model using a BP neural network. A multi-objective genetic algorithm then obtained the optimal solution. After multi-objective optimization, we reduced the mass of the direct-drive turntable by 9.02% and 21.394% compared with the topologically optimized and original models, respectively. The dynamic and static characteristics of the direct-drive turntable increased, and a lightweight design was achieved. Full article

Compared with traditional liquid crystal and organic light emitting diode (OLED), micro light emitting diode (μLED) has advantages in brightness, power consumption, and response speed. It has important applications in microelectronics, micro-electro-mechanical systems, biomedicine, and sensor systems. μLED massive transfer method plays an important role in these applications. However, the existing μLED massive transfer method is faced with the problem of low yield. To better transfer the μLED, the force value detached from the substrate needs to be measured. Atomic force microscope (AFM) was used to measure the force of a single μLED when it detached from the substrate. The μLED was glued to the front of the cantilever. When a single μLED was in contact with or detached from the Polydimethylsiloxane (PDMS), the maximum pull-off force can be obtained. The force at different peel speeds and preload was measured, and the experimental results show that the separation force between a single μLED and PDMS substrate is not only related to the peel speeds, but also related to the preload. The force values under different peel speeds and preload were measured to lay a theoretical foundation for better design of μLED massive transfer system. Full article

The increase in cancer cases is undoubtedly affecting the development of new therapeutic approaches. Polymeric nanoparticles are of great interest. Due to their relatively small size, the possibility of incorporating into them medicinal substances and the ease with which their physicochemical properties may be manipulated, they are being used as anticancer drug delivery systems. The aim of this review is to focus on the use of nanoscale polymeric particles in the treatment of colorectal cancer, breast cancer, ovarian cancer and glioblastoma multiforme, and to consider their potential use in cancer gene therapy. According to several reports, the use of polymer nanoparticles as drug carriers is promising in solid tumors. With their application, it is possible to precisely deliver medicinal substances to the tumor structure, to overcome the blood–brain barrier in the case of brain tumors, to reduce the side effects of anticancer agents on normal cells and to achieve a therapeutic effect with a lower drug dose. Additionally, a number of reports indicate that they can also be used in combination with other methods of cancer treatment, mainly radiotherapy. Full article

It is now widely recognized that the masonry infill frame used in reinforced concrete structures (RC) greatly enhances both the rigidity and strength of the surrounding frame. The lateral loading behavior of this RC frame is different from the frame without infill, although the structural contribution of infill walls is discarded in many countries, including Algeria. This paper aims to focus on the effect of openings and the effect of changing the distribution of masonry panels on the global behavior of buildings. For this, a pushover analysis is carried out to evaluate the seismic performance and assess the behavior of infilled RC, and to study the results related to capacity curve, inter-story drift and energy. The results obtained show that the effect of the openings and changing of the distribution of masonry panels can drastically change the overall behavior of the structures regarding enhancing strength capacities and energy absorption. Noticeable remarks in terms of distributing masonry panels within a frame are observed and several recommendations concerning the present practice might be important to be considered. Full article

Since 2004, scientific research on the damaged Giant Buddha statues and Buddhist paintings in Bamiyan, Afghanistan, has been conducted at various laboratories and large-scale facilities using mass-spectrometry techniques (GC-MS, LC-MS, LC-MS/MS, nano-LC/ESI-MS/MS), ELISA, and synchrotron-based micro-analyses) in parallel to conservation intervention. Studies on samples from these cultural heritage objects have shown that each is composed of a polychromatic multilayered structure with sizing layers, ground layers, painted layers, and glaze. The carefully produced complex multilayered structures were examined using optical microscopy (visible and UV light) as well as synchrotron-based infrared microscopy, both of which revealed various organic and inorganic components in each layer. High sensitivity bulk MS and ELISA methods were used to further identify details regarding organic materials, such as fatty acids and collagens, and these results suggest different vegetable oils and animal species of glues. For example, cow milk casein and cow skin glue were identified in the Eastern Giant Buddha, suggesting that casein was used as a sizing agent and the cow skin glue as a binder for painting. The wall paintings from Cave N(a) (mid-7th century AD) were found to have horse glue used as sizing and drying oil (poppyseed/walnuts/perilla oils) as a binding media. The paintings’ complex structures and their organic and inorganic materials were fully understood using both imaging and bulk methods, and thus, these methods help to reconstruct historical wall painting techniques in full. Full article

In this study, the contents and associated soil properties of 6 metal elements (Pb, As, Cu, Zn, Ni, Cr) were measured in 63 topsoil samples in the affected areas of a typical non-ferrous metal slag field in Huili City, Sichuan Province, China. The associated soil properties of the 6 metals include Ammonium Nitrogen (${\mathrm{NH}}_4^{+}$-N), Nitrate (${\mathrm{NO}}_3^{-}$-N), Available Phosphorus (AP), Available Potassium (AK), Electrical Conductivity (EC), Cation Exchange Capacity (CEC), Soil Water Content (SWC), and pH. Multivariate statistics-spatial analysis-soil pollution comprehensive evaluation method was used to quantify the environmental pollution degree of heavy metals in the topsoil and divided (zone) the slag field based on the degree of pollution. Pearson correlation analysis and positive matrix factorization (PMF) were used to identify and quantitatively analyze pollution sources and their contributions. The results show that the average contents of Pb, As, Cu, Zn, Ni, and Cr were 13.27, 19.87, 6.91, 50.55, 25.06, and 77.71 mg·kg⁻¹, respectively. Nemerow comprehensive evaluation results showed that the sites with Slight Pollution and Mild Pollution accounted for 26.98% and 3.17% of the total sampling sites, respectively. Approximately 70% of the sampling sites in the study area had no heavy metal pollution in the soil. Sites with No Pollution or Slight Pollution were mainly distributed in the forest areas with vegetation coverage, while sites with Moderate Pollution or Heavy Pollution were mainly distributed in crop planting areas and areas near slag fields. PMF model revealed four pollution sources: natural sources, mixed industrial and transportation sources, agricultural sources, and industrial river water. These results will provide theoretical references for the utilization and treatment of heavy metal-contaminated soil around the slag field in the dry-hot valley. Full article

Purpose: Using a data and machine learning approach, from classical to complex, we aim to approximate the relationship between factors such as behavioral, social or comorbidity and the ejection fraction for hospitalized patients. To measure how much the independent variables influence the left ventricular ejection fraction (LVEF), classification models will be made and the influences of the independent variables will be interpreted. Through the data obtained, it is desired to improve the management of patients with heart failure (treatment, monitoring in primary medicine) in order to reduce morbidity and mortality. Patients and Methods: In this study, we enrolled 201 patients hospitalized with decompensated chronic heart failure. The models used are extreme gradient boosting (XGB) and logistic regression (LR). To have a deeper analysis of the independent variables, their influences will be analyzed in two ways. The first is a modern technique, Shapley values, from game theory, adapted in the context of Machine Learning for XGB; and the second, the classical approach, is by analysis of Logistic Regression coefficients. Results: The importance of several factors related to behavior, social and diabetes are measured. Smoking, low education and obesity are the most harmful factors, while diabetes controlled by diet or medication does not significantly affect LVEF, indeed, there is a tendency to increase the LVEF. Conclusions: Using machine learning techniques, we can better understand to what extent certain factors affect LVEF in this sample. Following further studies on larger groups and from different regions, prevention could be better understood and applied. Full article

The vehicle driving simulator (VDS) is a virtual reality-based system that provides drivers and passengers with a driving feeling similar to the actual vehicle. However, the motion system of the VDS has limitations in providing the same driving feeling as the actual driving due to its limited kinematics and dynamic characteristics. In order to solve these problems and limit the motion of the VDS to the kinematic workspace, a washout algorithm is needed. However, since the classical washout algorithm causes simulator sickness due to time delay and signal distortion caused by using the signal filters, various washout algorithms have been proposed, such as a new tilt coordination algorithm and method of directly reflecting subregions of vehicle tilt angle. However, the new tilt coordination washout algorithm has the disadvantage of extremely degrading the rotational motion sensation, and the subregions scale method has the disadvantage of ambiguous criteria for selecting scale parameters. In this paper, we propose a novel washout algorithm that improves the motion sensation of the driver and passengers by an enhanced tilt coordination and subregion scale washout algorithm and evaluate it through a simulation based on the human sensation model. The proposed washout algorithm has the advantage of maintaining enhanced translational motion sensation by the new tilt coordination algorithm while complementing deteriorated rotational motion sensation. In addition, the structure of the algorithm is simple and gain tunning is intuitive, making it easy for the user to apply to the motion system of the VDS. Full article

In recent years, scheduling optimization has been utilized in production systems. To construct a suitable mathematical model of a production scheduling problem, modeling techniques that can automatically select an appropriate objective function from historical data are necessary. This paper presents two methods to estimate weighting factors of the objective function in the scheduling problem from historical data, given the information of operation time and setup costs. We propose a machine learning-based method, and an inverse optimization-based method using the input/output data of the scheduling problems when the weighting factors of the objective function are unknown. These two methods are applied to a multi-objective parallel machine scheduling problem and a real-world chemical batch plant scheduling problem. The results of the estimation accuracy evaluation show that the proposed methods for estimating the weighting factors of the objective function are effective. Full article

Metal matrix nanocomposites (MMNCs) reinforced by carbon nanotubes (CNTs) are good candidates to produce structural components in the mobility industry, given their unique properties. The manufacture of these components can involve plastic deformation. Therefore, it is crucial to understand whether reinforcement can influence the deformation behaviour of these nanocomposites. Thus, this work aims to study the deformation behaviour of MMNCs, given their importance and the lack of studies on this topic. Although nickel is not the most widely used metal as a matrix of nanocomposites, it presents mechanical properties superior to other matrices, such as aluminium. In addition, this metal has proven to establish a strong interface and integration of carbon nanotubes, making it an exciting material for the production and study of these nanocomposites. In that sense, nickel matrix nanocomposites are reinforced by 1.00 %vol. CNTs were produced by powder metallurgy using ultrasonication as a dispersion/mixture method. For comparison purposes, a nickel matrix was produced under the same conditions. Samples with and without CNTs were cold-rolled with thickness reductions between 10 and 60% (logarithmic strains between 0.11 and 0.92) to investigate the deformation behaviour. Microstructural characterization was performed using scanning electron microscopy (SEM) and electron backscattered diffraction (EBSD). Microhardness tests were applied to evaluate their mechanical properties. The results revealed that the nanocomposites exhibited a softening for small strains (0.11 and 0.22). This decrease in hardness was attributed to the decline in dislocation density observed by EBSD, due to the rearrangement and annihilation of pre-existing dislocations that originated during production. A possible inversion can explain the decrease in dislocation density when minor strains are applied in the dislocation or deformation trajectory, known as the Bauschinger effect. The difference in the texture evolution of the nanocomposites can be explained by the initial crystallographic orientations, which are influenced by the presence of CNTs. Full article

Numerous studies have been done to determine the hydrocarbon potential of Malaysia’s formations and basins due to the need to identify more conventional or unconventional hydrocarbon resources. Due to the fact that none of these investigations were carried out with any prior knowledge in the relevant regions with hydrocarbon potential, some of them did not, however, yield the expected results. This study aims to provide researchers with all the necessary information about potential hydrocarbon-producing areas in Malaysia and the various lithologies connected to them by analyzing all earlier studies carried out in Malaysia. This was accomplished by determining patterns in the distribution of organic matter and characteristics of the formations in Malaysia. Total Organic Carbon (TOC), Generic Potential (GP), Vitrinite Reflectance (R_o), and Hydrocarbon Yield (S2) were the most important hydrocarbon generation potential indicators discussed. A heat map was created using a statistical weight ranking with a weight of 45% for the TOC value and 30%, 15%, and 10% for the GP, S2, and R_o values, respectively. According to the data, the Bintulu, Pinangah, Begrih, Liang, and Tanjong formations have the highest potential to generate hydrocarbons in Malaysia, while the Kroh, Setap, Kalabakan, Temburong, and Belaga have the least potential. Majority of formations with high hydrocarbon potential are tertiary in age and consist primarily of coal and carbonaceous shale formations. The most promising formations are mostly immature, with type II or type III kerogen quality. It is recommended that critical exploration activities be focused on the tertiary-aged formations, particularly those in East Malaysia, in order to increase Malaysia’s hydrocarbon production. Full article