It has now been shown that an active and healthy lifestyle among university students helps to channel disruptive states arising from the academic environment. The objectives of this research are to describe the levels of anxiety, adherence to the Mediterranean diet, and motivational climate as a function of the type of physical activity, and to establish the relationship between adherence to the Mediterranean diet, motivational climate, and anxiety in university students. This objective is broken down into: (a) developing an explanatory model of the motivational climate towards sport and adherence to the Mediterranean diet on anxiety, and (b) contrasting the structural model by means of a multi-group analysis as a function of the type of physical activity. A descriptive, comparative, cross-sectional, and non-experimental study was proposed in a sample of 569 trainee teachers (M = 25.09; SD = 6.22). A sociodemographic questionnaire, the Beck Anxiety Inventory (BAI), the Perceived Motivational Climate in Sport Questionnaire (PMCSQ-2), the PREDIMED Questionnaire, and the International Physical Activity Questionnaire (IPAQ-SF) were used for data collection. The data show that subjects with higher weekly physical activity time show lower levels of anxiety, better adherence to the Mediterranean diet, and demonstrate task-oriented sport motivation. Full article

In the manufacture of steel and foundry coke, there are a series of circumstances inherent to the process which can affect the life of the refractory material with which the ovens of the batteries are built. This article will deal with the impact of aspects such as sticky ovens and hard pushes on the refractory. For this purpose, data will be obtained from a Didier design coke plant built in the 1970s. In particular, the data comes from two batteries or groups of ovens over a period of two years. Of the types of refractories of which coke batteries are composed, we will only deal with silica material. This is the type of refractory with which the combustion and coking chambers of the ovens are almost exclusively built. Its characteristics and behavior make silica a major player in the service life of a coke battery. Therefore, any aspect of the process that is susceptible to damage during this refractory will have a great impact on the life of the coke manufacturing equipment. The results show that hard pushes and especially sticky ovens damage the silica refractory of the furnaces. Therefore, the proper management of production, focused in minimizing these effects, can contribute to reduce the maintenance cost and prolong the service life of the coke ovens. Full article

Piston bowl geometry plays an important role in the fuel/air mixing quality which has a direct influence on the performance and emission characteristics of the engine. This work studied the effects of piston bowl geometry on the combustion and emissions of a four-stroke direct injection (DI) heavy-duty diesel marine engine. Three types of piston bowls with various parameters were numerically investigated, targeting to improve engine performance, fuel oil consumption, and emission characteristics. The results pointed out that the ω-type and re-entrant piston bowls enhanced cylinder power by 1.26% and 2.67% while reducing the indicated specific fuel oil consumption (ISFOC) of the engine by 1.06% and 1.60%, respectively, compared to the U-type bowl. Especially, the ω-type and re-entrant piston bowls reduced NO (nitric oxide) emission by up to 25.61% and 46.09%, respectively, owing to lower peak temperatures in comparison to the U-type piston bowl. The results also pointed out that changing the piston bowl type has negligible effects on the engine-out soot and CO₂ emission characteristics of the engine. Based on this study, it is highly recommended to utilize the re-entrant piston bowl for four-stroke DI diesel engines to improve both engine performance and fuel oil consumption while reducing NO emission simultaneously. Full article

The hollow structure of large-diameter ring piles (LDRPs) reduces the amount of concrete used, is economically efficient, and reduces the weight of the pile. However, its bearing characteristics and safety performance are still not fully known. In this study, to determine the properties of the LDRP structure, a combination of the indoor scale model test and numerical simulations was used, and a new parameter, K, which is the thickness-to-diameter ratio, was introduced. A comparative study of LDRPs with different hollow ranges was conducted. The results show that for a value of K in the range of 0.2–1, the ultimate bearing capacity of LDRPs is not significantly different from that of large-diameter solid piles (LDSPs), and they can ensure sufficient safety reserves. Under ultimate bearing capacity, the strain on an LDRP is large, but it does not exceed its own material strength, and the strain variation law is similar to that of a solid pile. LDRPs show the characteristics of end-bearing piles, and concrete savings can reach up to 50% for K in the range of 0.2–1. Full article

Fucoidan, a polymer derived from seaweed, poses a broad range of biological applications, and its potential medicinal benefits have been widely studied over the past decade. In this study, fucoidan was extracted from marine macroalga Sargassum ilicifolium and its bioactive potential for in silico molecular docking was investigated. Additionally, the computational in silico docking studies were applied on the fucoidan against anticancer and antioxidant target proteins by using Glide ligand docking, Schrodinger software. The FT-IR analysis revealed that fucoidan mainly consisted of the fucose residues (59.1%) and a few monosaccharides, such as uronic acid (11.7%) and sulphate (18.3%). The in vitro tests revealed that fucoidan possessed various antioxidative properties and anticoagulant activities. Fucoidans played an inhibitory role in the colony formation of HepG2 cells. The NADPH oxidase (−7.169 Kcal/mol) and cellular tumor antigen p53 protein (−6.205 Kcal/mol) exhibited the highest antioxidant and anticancer proteins, respectively. Overall, the present study results provide a theoretical foundation for broadening the application of fucoidan from S. ilicifolium as a pharmaceutical ingredient. Full article

The ultrasonic transmission detection method is used to investigate the applicability for the second-harmonic generation (SHG) technology of longitudinal wave to quantitatively assess carbonated concrete. The principal of this method is to use the piezoelectric lead zirconate titanate (PZT) patch to detect the second-harmonic of longitudinal waves during the concrete carbonation process and extract non-linear parameters from observed signals. Non-linear parameters of concretes with two water–cement ratios (CI $(w/c=0.47)$, CII $(w/c=0.53)$), two moisture contents (CI $0\%$, CI-W $100\%$), and three ultrasonic incident frequencies (50 kHz, 75 kHz, 100 kHz) were measured in this study. Results of the experiment demonstrate that non-linear ultrasonic parameters of longitudinal ultrasonic waves with high frequencies (75 kHz, 100 kHz) exhibit a better resolution regarding changes in concrete microstructure. Moisture (CI $0\%$, CI-W $100\%$) has little effect on the rate (CI: 62.73%, CI-W: 60.25, carbonation depth: 15 mm) for the change in relative non-linear parameters in the same concrete. The carbonation depth of concrete (CI $(w/c=0.47)$, CI-W $(w/c=0.47)$, CII $(w/c=0.53)$) can be well reflected by the change in relative non-linear parameters. Furthermore, there exists a good fit between the relative non-linear parameters of longitudinal waves and the concrete carbonation process. The relative non-linear parameters of longitudinal waves demonstrate feasibility in the quantitative assessment of concrete carbonation. Full article

The existing block-based machine learning educational environments have a drawback in that they do not support model training based on large-scale data. This makes it difficult for young students to learn the importance of large amounts of data when creating machine learning models. In this paper, we present a novel programming environment in which students can easily train machine learning models based on large-scale data using a block-based programming language. We redefine the interfaces of existing machine learning blocks and also develop an effective model training algorithm suitable for block-based programming languages to enable “instant training” and “large-scale training”. As example educational applications based on this environment, we presented what is termed a “Question-Answering Chatbot” program trained on 11,822 text data instances with 7784 classes as well as a “Celebrity Look-Alike” program trained on 4431 image data instances with 7 classes. The experimental results show that teachers and pre-service teachers give high scores on all four evaluation measures for this environment. Full article

Representation of self-face is vulnerable to cognitive bias, and consequently, people often possess a distorted image of self-face. The present study sought to investigate the neural mechanism underlying distortion of self-face representation by measuring event-related potentials (ERPs) elicited by actual, aesthetically enhanced, and degraded images of self-face. In addition to conventional analysis of ERP amplitude and global field power, multivariate analysis based on machine learning of single trial data were integrated into the ERP analysis. The multivariate analysis revealed differential pattern of scalp ERPs at a long latency range to self and other familiar faces when they were original or aesthetically degraded. The analyses of ERP amplitude and global field power failed to find any effects of experimental manipulation during long-latency range. The present results indicate the susceptibility of neural correlates of self-face representation to aesthetical manipulation and the usefulness of the machine learning approach in clarifying the neural mechanism underlying self-face processing. Full article

In this work, we propose a road pavement damage detection deep learning model based on feature points from a local minimum of grayscale. First, image blocks, consisting of the neighborhood of feature points, are cut from the image window to form an image block dataset. The image blocks are then input into a convolutional neural network (CNN) to train the model, extracting the image block features. In the testing process, the feature points as well as the image blocks are selected from a test image, and the trained CNN model can output the feature vectors for these feature image blocks. All the feature vectors will be combined to a composite feature vector as the feature descriptor of the test image. At last, the classifier of the model, constructed by a support vector machine (SVM), gives the classification as to whether the image window contains damaged areas or not. The experimental results suggest that the proposed pavement damage detection method based on feature-point image blocks and feature fusion is of high accuracy and efficiency. We believe that it has application potential in general road damage detection, and further investigation is desired in the future. Full article

The 2021 M_w 7.3 Maduo earthquake is one of the largest seismic events that has occurred in and around the Bayan Har block of Tibet. D-InSAR results and field surveys indicate that this earthquake resulted in more than 160 km of coseismic surface rupture along pre-existing fault traces. Based on the branching of the surface rupture, the fault of the Maduo earthquake can be roughly divided into four sections. Through detailed drone mapping, the fracture pattern and offset of the fault were counted and measured. The development of the peaty meadow layer on the ground determines the different combination modes of the fractures. The horizontal offset observed on the surface of this earthquake is generally less than 2 m and the vertical offset is less than 1 m, and the fault shows a primarily left-lateral strike-slip movement. In the desert-covered areas, there are long gaps between continuous rupture. Full article

The purpose of this study was to observe the effects of audible and inaudible binaural beat stimuli on alpha power elicitation and compare the differences in triggering effects depending on sound perception. Experiments were conducted on healthy male and female subjects (11 males and 10 females, mean age of 24.6 ± 1.8). To induce alpha waves, audible (250 Hz) or non-audible baseline sound frequencies (18,000 Hz) were presented to the left ear, and a frequency 10 Hz higher than the baseline was presented to the right ear. There were two experimental phases: a rest phase (5 min) in which no stimulus was presented and a stimulation phase (5 min) in which the binaural beat stimulus was presented. An electroencephalogram was measured at a sampling rate of 500 Hz, and relative alpha power values were calculated for each phase in each brain area. In the central regions, both baseline frequencies (audible and inaudible) increased the relative alpha power during the stimulation phase compared with the rest phase, and there were no differences between the two baseline frequencies. In the frontal and central regions, there was a greater increase in relative alpha power in the audible case compared with the inaudible case. Full article

The world is facing a great technological transformation towards fully autonomous vehicles, where optimists predict that by 2030 autonomous vehicles will be sufficiently reliable, affordable, and common to displace most human driving. To cope with these trends, reliable perception systems must enable vehicles to hear and see all their surroundings, with light detection and ranging (LiDAR) sensors being a key instrument for recreating a 3D visualization of the world in real time. However, perception systems must rely on accurate measurements of the environment. Thus, these intelligent sensors must be calibrated and benchmarked before being placed on the market or assembled in a car. This article presents an Evaluation and Testing Platform for Automotive LiDAR sensors, with the main goal of testing both commercially available sensors and new sensor prototypes currently under development in Bosch Car Multimedia Portugal. The testing system can benchmark any LiDAR sensor under different conditions, recreating the expected driving environment in which such devices normally operate. To characterize and validate the sensor under test, the platform evaluates several parameters, such as the field of view (FoV), angular resolution, sensor’s range, etc., based only on the point cloud output. This project is the result of a partnership between the University of Minho and Bosch Car Multimedia Portugal. Full article

Concrete structures are considered as durable construction material, but corrosion of the embedded steel reinforcement occurs under chloride exposure as concrete has porous properties. Herein, a cyclic drying–wetting test was performed for two years using saltwater to accelerate steel corrosion in a reinforced concrete (RC) member. The open-circuit potential (OCP) was measured using a newly developed and replaceable agar sensor. The corrosion potential was measured considering the chloride concentration, water-to-cement (w/c) ratio, and cover depth at three levels. Furthermore, its relationships with influential parameters were evaluated using averaged OCP results. The measured OCP showed a linear relationship with the cover depth, and this tendency was more distinct with increasing retention period and higher chloride concentration. For the highest w/c ratio (0.6), values below −100 mV were monitored after only six months regardless of the cover depth, and values below the critical potential level (−450 mV) were evaluated at lower cover depths (30 and 45 mm). The results of regression analysis considering the exposure environment showed a clear relationship in the case of high chloride concentration (7.0%). A linear relationship between cover depth and OCP was derived with a reasonable determination coefficient ranging from 0.614 to 0.771. Full article