Serious games (SG), (video games with an educational purpose), provide teachers with tools to strengthen their students’ knowledge. Developing a SG requires knowledge, time, and effort. As a result, specialized tools to aid in the development process are needed. This work presents a model for the development of SG in the platformer genre. A tool implementing the model is introduced as a proof of concept. A SG was generated using this tool, which in turn was evaluated in terms of gameplay, mechanics, story, and usability. The evaluation results show that the SG has the minimum elements requested by an audience of students, who were expecting a game with both entertaining and educational value. Furthermore, the results are satisfactory in three out of four areas, showing that there are opportunities for improvement regarding the game’s story. Our work intends to improve the development times of new SG, as well as to make them easier to develop by both software engineers and teachers who wish to implement them in their classrooms. Full article

The paper deals with long-term means of 557.7 nm atomic oxygen airglow intensity (OI) and air temperature within the mesopause over the southern regions of East Siberia. Data on temperature and emission parameters were obtained with a SABER radiometer, KEO Scientific “Arinae” Fabry–Pérot interferometer, SATI spectrometer and NRLMSIS model over the Tory Geophysical Observatory (52° N, 103° E). Annual variations of 557.7 nm emission intensity and temperature obtained in observations differ from model approximations. Potential reasons for the discrepancies revealed are discussed. Full article

A quantum computer capable of running the Grover search algorithm, which reduces the complexity of brute-force attacks by a square root, has the potential to undermine the security strength of symmetric-key cryptography and hash functions. Recently, studies on quantum approaches have proposed analyzing potential quantum attacks using the Grover search algorithm in conjunction with optimized quantum circuit implementations for symmetric-key cryptography and hash functions. Analyzing quantum attacks on a cipher (i.e., quantum cryptanalysis) and estimating the necessary quantum resources are related to evaluating post-quantum security for the target cryptography algorithms. In this paper, we revisit quantum implementations of CHAM block cipher, an ultra lightweight cipher, with a focus on optimizing the linear operations in its key schedule. We optimized the linear equations of CHAM as matrices by applying novel optimized decomposition techniques. Using the improved CHAM quantum circuits, we estimate the cost of Grover’s key search and evaluate the post-quantum security strength with further reduced costs. Full article

In the experiment, the roughness was measured on a machined surface with high gloss, which was also the main requirement for the test samples. For this reason, the samples made of stainless steel A304 and aluminum alloy AW 2017 were created by a progressive laser using material-cutting technology. This article explains a contact-free measurement method that uses the triangulation principle, which constitutes the basis on which the device used in the experiment, i.e., the laser profilometry, works. The surface roughness of the cut surfaces was examined on the manufactured samples through the selected roughness parameters of Ra and Rz. These parameters are commonly used in industry to quantify the roughness of a surface. The values measured in a contact-free manner were then compared with the reference values measured in a contact manner. Data from individual experimental measurements were graphed as dependencies based on which problem areas of measuring the roughness of glossy material surfaces with laser profilometry were described. Laser profilometry is a non-contact method for measuring the roughness of surfaces, and given the presented results of the experimental measurements and selected roughness parameters of the cut surface using a laser, we do not recommend using it for materials that have a glossy surface. Full article

A novel dynamic inverse control method based on a dynamical neural network (DNN) is proposed for the trajectory tracking control of a flexible air-breathing hypersonic vehicle (FAHV). Firstly, considering that the accurate model of FAHV is difficult to obtain, the FAHV is regarded as a completely unknown system, and a DNN is designed to identify its nonlinear model. On the basis of Lyapunov’s second law, the weight vectors of the DNN are adaptively updated. Then, a dynamic inverse controller is designed based on the identification model, which avoids the transformation of the nonlinear model of FAHV, thereby simplifying the controller design process. The simulation results verify that the DNN can identify FAHV accurately, and velocity and altitude can track the given reference signal accurately with the proposed dynamic inverse control method. Compared with the back-stepping control method, the proposed method has better tracking accuracy, and the amplitude of the initial control law is smaller. Full article

Climate change has increased the frequency of various types of meteorological disasters in recent years. Finding the primary factors that limit the emergency response capability of meteorological disasters through the evaluation of that capability and proposing corresponding improvement measures in order to increase that capability is of great practical importance. The evaluation of meteorological disaster emergency response capability still has some issues. The majority of research methods use qualitative analysis, which makes it challenging to deal with fuzzy factors, leading to conclusions that are subjective and insufficiently rigorous. The evaluation models themselves are also complex and challenging to simulate and analyze, making it challenging to promote and use them in practice. Deep learning techniques have made it easier to collect and process large amounts of data, which has opened new avenues for advancement in the emergency management of weather-related disasters. In this paper, we suggest a Recurrent Neural Network (RNN)-based dynamic capability feature extraction method. The process of evaluation content determination and index selection is used to build a meteorological disaster emergency response capability evaluation index system before an encoder, based on the encoder–decoder architecture, is built for dynamic feature extraction. The RNN autoencoder deep learning ability dynamic rating method used in this paper has been shown through a series of experiments to be able to not only efficiently extract ability features from time series data and reduce the dimensionality of ability features, but also to reduce the focus of the ability evaluation model on simple and abnormal samples, concentrate the model learning on difficult samples, and have a higher accuracy. As a result, it is more suitable for the problem situation at evaluation of the disaster capability. Full article

The cold metal transfer (CMT) process is widely used in thin plate welding because of its characteristics of low heat input and stable arc. In actual production, a larger weld gap, misalignment, or other problems due to assembly error lead to serious welding defects, such as burn-through and a lack of fusion. The arc sound contains a wealth of information related to the quality of the weld. This work analyzes the mechanism of CMT arc sound generation, as well as the correlation between the time–frequency spectrum of the arc sound signal and welding quality. This paper studies the extraction of the multi-channel time–frequency spectrum of an arc sound and inputs it to a custom convolutional neural network for the CMT welding defect identification of thin aluminum alloy plates. The experimental result shows that the average accuracy of the proposed model is 91.49% in the defect identification of a CMT arc-welded aluminum alloy sheet, which is higher than that of the single-channel time–frequency convolutional neural network and other traditional classification models. Full article

Climate change and urban heat island effects affect the energy consumption of buildings in urban heat islands. In order to meet the requirements of engineering applications for detailed daily design parameters for air conditioning, the 15-year summer meteorological data for Beijing and Shanghai and the corresponding average heat island intensity data were analyzed. Using the CRITIC objective weighting method and K-means clustering analysis, the hourly change coefficient, β, of dry bulb temperature was calculated, and the LSTM algorithm was used to predict the changing trends in β. Finally, the air conditioning load model for a hospital was established using DeST (version DeST3.0 1.0.2107.14 20220712) software, and the air conditioning cooling load in summer was calculated and predicted. The results show that, compared with the original design days, regional differences in the new design days are more obvious, the maximum temperature and time have changed, and the design days parameters are more consistent with the local meteorological conditions. Design day temperatures in Shanghai are expected to continue rising for some time to come, while those in Beijing are expected to gradually return to previous levels. Among hospital buildings, the cooling load of outpatient buildings in Beijing and Shanghai will decrease by 0.69% and increase by 12.61% and by 12.12% and 15.51%, respectively, under the influence of the heat island effect. It is predicted to decrease by 1.35% and increase by 29.75%, respectively, in future. The cooling load of inpatient buildings in Beijing and Shanghai increased by 0.27% and 6.71%, respectively, and increased by 7.13% and 8.09%, respectively, under the influence of the heat island effect, and is predicted to decrease by 0.93% and increase by 16.07%, respectively, in future. Full article

The scale-up and the economic feasibility of the synthesis of St-MMA-GMA-PEGMA particles biofunctionalized with HSA were studied. First, the geometrical similarity of laboratory and pilot plant reactors was checked to develop the scale up of the process according to a criterion of partial similarity. The selected criterion was constant Re number. Then, a reaction in the pilot plant scale was carried out, confirming the suitability of the scale-up criterion, since particles with similar characteristics (same particle size with a deviation of just 6%) and functional groups were obtained. Finally, the design of an industrial plant able to produce 581 Tm/year of HSA functionalized St-MMA-GMA-PEGMA particles was addressed. The economic feasibility of this plant was confirmed by a value of internal rate of return (IRR) of 14.8% and a net present value (NPV) of 5452 M€, with a payback time between six and seven years, for the price of a cartridge 25% lower than that from the current treatments for bilirubin removal from patients with liver failure. Full article

According to the seismic damage due to past events, buildings located on slopes can present a worse seismic performance. To explore this, this study established a finite element model based on a 6-story RC frame structure and soil models based on a practical slope using OpenSees software. Combining the superstructure model with the soil model through soil spring elements, three soil-structure interaction systems with different slope rates were set up. Twenty near-field seismic actions were used as input loads for dynamic time–history analysis. The analysis shows that in the process of seismic action, the deformation tendency of the structure is affected by the slope. There is a clear tendency for lateral displacement towards the slope, and it is more obvious with a greater slope ratio. Meanwhile, the slope has no impact on the shear force at the base of the structure or at the bottom of the column. In addition, there is no correlation between the degree of impact and the slope gradient on the peak value of internal forces and deformations of structure. Full article

Aliphatic and aromatic polyesters of hydroxycarboxylic acids are characterized not only by biodegradability, but also by biocompatibility and inertness, which makes them suitable for use in different applications. Polyesters with high enzymatic hydrolysis capacity include poly(lactic acid), poly(ε-caprolactone), poly(butylene succinate) and poly(butylene adipate-co-terephthalate), poly(butylene succinate-co-adipate). At the same time, poly(lactic acid) is the most durable, widespread, and cheap polyester from this series. However, it has a number of drawbacks, such as high brittleness, narrow temperature-viscosity processing range, and limited biodegradability. Three main approaches are known for poly(lactic acid) modification: incorporation of dispersed particles or low molecular weight and oligomeric substances, copolymerization with other polymers, and blending with other polymers. The review includes an analysis of experimental works devoted to developing mixtures based on poly(lactic acid) and other polymers. Regularities in the formation of the structure of such systems and the possibility of controlling the properties of poly(lactic acid) are considered. Full article

App-based ride-hailing mobility services are becoming increasingly popular in cities worldwide. However, key drivers explaining the balance between supply and demand to set final prices remain to a considerable extent unknown. This research intends to understand and predict the behavior of ride-hailing fares by employing statistical and supervised machine learning approaches (such as Linear Regression, Decision Tree, and Random Forest). The data used for model calibration correspond to a ten-month period and were downloaded from the Uber Application Programming Interface for the city of Madrid. The findings reveal that the Random Forest model is the most appropriate for this type of prediction, having the best performance metrics. To further understand the patterns of the prediction errors, the unsupervised technique of cluster analysis (using the k-means clustering method) was applied to explore the variation of the discrepancy between Uber fares predictions and observed values. The analysis identified a small share of observations with high prediction errors (only 1.96%), which are caused by unexpected surges due to imbalances between supply and demand (usually occurring at major events, peak times, weekends, holidays, or when there is a taxi strike). This study helps policymakers understand pricing, demand for services, and pricing schemes in the ride-hailing market. Full article

Landslide susceptibility maps are widely used in land management and urban planning to delimit potentially problematic areas. In this article we improve their reliability by acting on the frequency ratio method and map classification systems. For the frequency ratio method, we have worked with continuous variables and established intervals grouped by probability according to the landslide inventory and based on the characteristics of the data rather than on standard divisions. For map classification systems, we have compared the efficacy of conventional classifications and those based on the concepts of sensitivity and specificity, with the specificity classifications being supported by the information offered by available comparative data. Both strategies make it possible to avoid subjective and repetitive procedures that are alien to the nature of the data being assessed. We present a case study in the 23,000 km² Region of Valencia where a total of 48 different susceptibility maps were generated. We demonstrate that the methods applied in this study to calculate the frequency ratio provide an improvement in specificity in areas of high susceptibility while maintaining good sensitivity. In particular, the Area Under Curve (AUC) values increase from 0.67 for the conventional methods to 0.76 with the methods proposed in this work. This improvement is transferred to susceptibility mapping much more clearly when classifications that incorporate sensitivity, and especially specificity parameters, are used. Full article

Automatic modulation classification (AMC) is a vital process in wireless communication systems that is fundamentally a classification problem. It is employed to automatically determine the type of modulation of a received signal. Deep learning (DL) methods have gained popularity in addressing the problem of modulation classification, as they automatically learn the features without needing technical expertise. However, their efficacy depends on the complexity of the algorithm, which can be characterized by the number of parameters. In this research, we presented a deep learning algorithm for AMC, inspired by residual learning, which has remarkable accuracy and great representational ability. We also employed a squeeze-and-excitation network that is capable of exploiting modeling interconnections between channels and adaptively re-calibrates the channel-wise feature response to improve performance. The proposed network was designed to meet the accuracy requirements with a reduced number of parameters for efficiency. The proposed model was evaluated on two benchmark datasets and compared with existing methods. The results show that the proposed model outperforms existing methods in terms of accuracy and has up to $72.5\%$ fewer parameters than convolutional neural network designs. Full article

The known amplitude-sensitive eddy-current method for measuring the thickness of non-conductive coatings on conductive non-magnetic base metals does not satisfy the accuracy requirements. A primary consideration is the significant influence of a change in the specific electrical conductivity of the base metals on results of measurements. In this study, we developed a technique for measuring the thickness of non-conductive coatings on non-magnetic conductive base metals by using the eddy-current amplitude-phase method and implemented algorithms to process obtained information. Our method considered the influence of the specific electrical conductivity of the base metals by forming a two-dimensional graduation characteristic of the thickness gauge by using several base metals with different specific electrical conductivity. The algorithm for point-in-polygon determination was applied, which allowed us to measure the thickness of the coatings and the specific electrical conductivity of the base metals as independent values. The equipment necessary to construct the two-dimensional graduation characteristic and the algorithm for calculation of the thickness are described in detail. Full article