Appl. Sci., Volume 13, Issue 2 (January-2 2023) – 552 articles

In order to improve the prediction accuracy of the machine learning model for concrete fatigue life using small datasets, a group calculation and random weight dynamic time warping barycentric averaging (GRW-DBA) data augmentation method is proposed. First, 27 sets of real experimental data were augmented by 10 times, 20 times, 50 times, 100 times, 200 times, 500 times, and 1000 times, respectively, using the GRW-DBA method, and the optimal factor was determined by comparing the model’s training time and prediction accuracy under different augmentation multiples. Then, a concrete fatigue life prediction model was established based on artificial neural network (ANN), and the hyperparameters of the model were determined through experiments. Finally, comparisons were made with data augmentation methods such as generative adversarial network (GAN) and regression prediction models such as support vector machine (SVM), and the generalization of the method was verified using another fatigue life dataset collected on the Internet. The result shows that the GRW-DBA algorithm can significantly improve the prediction accuracy of the ANN model when using small datasets (the R² index increased by 20.1% compared with the blank control, reaching 98.6%), and this accuracy improvement is also verified in different data distributions. Finally, a graphical user interface is created based on the developed model to facilitate application in engineering. Full article

Orthognathic surgery is a procedure used to correct intermaxillary discrepancies, thus promoting significant improvements in chewing and breathing. During the surgical planning stage, orthodontists often use two-dimensional imaging techniques. The assessment is based on CBCT images and dental cast models to overcome these limitations; however, the evaluation of soft tissues remains complex. The aim of the present study was to develop a co-registration method of CBCT and photo images that would result in realistic facial image reconstruction. CBCT images were three-dimensionally rendered, and the soft tissues were subsequently segmented resulting in the cranial external surface. A co-registration between the obtained surface and a frontal photo of the subject was then carried out. From this mapping, a photorealistic model capable of replicating the features of the face was generated. To assess the quality of this procedure, seven orthodontists were asked to fill in a survey on the models obtained. The survey results showed that orthodontists consider the three-dimensional model obtained to be realistic and of high quality. This process can automatically obtain a three-dimensional model from CBCT images, which in turn may enhance the predictability of surgical-orthognathic planning. Full article

Gas–liquid two-phase flow is very common in industrial pipelines. Flow regime identification is the first step to design, analyze, and operate the gas–liquid system successfully. The purpose of this study is to develop a methodology for identification of a two-phase flow regime using post signal processing techniques, namely Fast Fourier Transform (FFT) and Probabilistic Density Function (PDF). Three different flow regimes were simulated in a 6 m horizontal pipe with a 0.050 m inner diameter. A Level-Set (LS) method coupled with Volume of Fluid (VOF) method is used to model the air–water interface. After validation of the numerical method, dynamic pressure readings were collected with the intent to identify the associated flow regimes by post-processing of these signals. It was concluded that dynamic pressure signals of different flow regimes show different characteristics (like dominant frequency, FFT amplitude, PDF location and PDF magnitude) in the time and frequency domains. These characteristics can be potentially used as differentiating factors to distinguish different flow regimes. This research is limited to stratified, slug, and annular flow in the horizontal pipe. This paper uses a new approach to identify the flow regime in a horizontal pipe by Fast Fourier Transform and Probability Density Function of dynamic pressure readings obtained by using numerical simulation. Full article

To study the mechanical damage characteristics of rock under the effect of subversion, a series of mechanical experiments, including both uniaxial and triaxial mechanical compression experiments under various levels of water content were performed. In this study, researchers investigate the impact of water content on the mechanical characteristics of rock, based on the compliance of the rock damage variants to the Weibull statistic distribution, and Drucker–Prager strength rule, aiming to construct a constitutive model under the joint effect of load and moisture. In addition, the established constitutive model is tested in the experiment. According to the test results, during the initial phase of the submersion, the water content in the rock increases following the exponential function until reaching the threshold. The water content remains stable after the threshold. Under the uniaxial and triaxial loads, the damage detected in the rock and the elasticity modulus decreases linearly as the water content increases. The rock’s mechanical parameters and the damage evolution rate are significantly impacted by the surrounding pressure. As the surrounding pressure increases, the weakening effect of the water in the rock decreases. The theoretic curves developed to describe the rock damage under the joint effect of the water and load are consistent with the curves drafted based on the test, indicating that the constitutive model can accurately describe the stress and strain behaviors of rock under various water contents and loading conditions. Full article

Modeling the nonlinearity of a system is of primary importance both for optimizing its design and for controlling the behavior of physical systems operating with a wide dynamic range of input values, for which the linearity hypothesis may not be sufficient. To become of practical use, the identification of nonlinear models must be accurate and computationally efficient. For these reasons, in recent years, among the numerous models of nonlinear systems that have been proposed in the technical literature, the Hammerstein model has been widely applied as a consequence of the proposal of a new pattern identification technique based on pulse compression, which makes the identification of the model very accurate in numerous applications for which it has been adopted. Hammerstein model identification of a nonlinear system requires characterization of the linear filters present on the different branches of the model. These linear filters, which constitute the parameters of the model to be identified, must be considered with respect to their trends over time or, equivalently, in their frequency trends, as amplitude and phase responses. The identification can be considered accurate if the trends obtained for each filter adequately characterize it for the entire frequency range to which that specific filter is subjected in the normal operation of the system to be identified. This work focuses on this aspect, i.e., on the adequacy of the frequency range for which the filter is identified and on how to obtain correct identification in the entire frequency range of interest. The identification procedure based on exponential swept-sine signals defines these filters in the time domain by making use of intermediate functions that are related to the impulse responses of the model filters through a linear transformation. In this paper, we analyze, in detail, the roles of the bandwidths of both the excitation signal and the matched filter, which are the basis of the procedure, we verify the assumptions made about the amplitudes of their frequency bands, and we propose criteria for defining the bandwidths in order to maximize accuracy in model identification. The experiment performed makes it possible to verify that the proposed procedure avoids possible limitations and significantly improves the quality of the identification results, both if the description is made in the time domain and in the frequency domain. Full article

The monitoring and evaluation of air quality is a topic of great global interest as, with the decline of air quality, there are negative effects on human health and ecosystems. Thus, the purpose of this paper was to evaluate the air quality over 11 years, in the period 2011–2021, in four cities in Romania, reported as most polluted, namely, Brasov, Cluj-Napoca, Iasi, and Timisoara. Pollutants of interest included arsenic, carbon monoxide, and PM_2.5. The measured concentrations of the selected pollutants were collected from the National Environmental Protection Agency public reports. The database considered the daily measurements for the selected pollutants, from three monitoring stations in each city so that the air quality and trends for the last 11 years and impact assessment could be developed. Therefore, the input data were statistically analyzed to identify the trends of air quality, and then, on this basis, the environmental impacts and risks and health hazards were quantified. High concentrations of PM_2.5 were recorded for Iasi city, while for Timisoara city, significant concentrations of arsenic were reported. The results regarding the air quality aggregate index, air pollution index, and health hazard index were in the regular range, but in the case of sensitive, vulnerable targets such as children, they were triple compared to adults. The results show that the alert threshold value for PM_2.5 was exceeded every year in all four cities, while in the case of Timisoara city, the arsenic air pollution proved to be at a significant level with a major risk for human health. Full article

Cuffless blood pressure (BP) monitoring is crucial for patients with cardiovascular disease and hypertension. However, conventional BP monitors provide only single-point estimates without confidence intervals. Therefore, the statistical variability in the estimates is indistinguishable from the intrinsic variability caused by physiological processes. This study introduced a novel method for improving the reliability of BP and confidence intervals (CIs) estimations using a hybrid feature selection and decision method based on a Gaussian process. F-test and robust neighbor component analysis were applied as feature selection methods for obtaining a set of highly weighted features to estimate accurate BP and CIs. Akaike’s information criterion algorithm was used to select the best feature subset. The performance of the proposed algorithm was confirmed through experiments. Comparisons with conventional algorithms indicated that the proposed algorithm provided the most accurate BP and CIs estimates. To the best of the authors’ knowledge, the proposed method is currently the only one that provides highly reliable BP and CIs estimates. Therefore, the proposed algorithm may be robust for concurrently estimating BP and CIs. Full article

Due to the barely resonant earthed system used in the transmission line, it is more challenging to identify faults at a 66 kV voltage level because of insufficient fault identification techniques. In this paper, a 66 kV transmission line fault identification method based on a fault characteristic matrix and an improved particle swarm optimization (IPSO)-wavelet neural network (WNN) is proposed to address the difficulties in extracting and detecting characteristic parameters. The maximum matrix of the dbN wavelet was used to determine its decomposition scale and construct the fault characteristic matrix based on the energy values of frequency bands. The decomposition scale of the dbN wavelet was determined by the modulus maximum matrix to ensure the integrity of fault information. The fault feature matrix was then constructed based on the energy values of frequency bands and the fault feature was accurately extracted. In this research, aiming at the problems such as slow convergence speed and a tendency to fall into local minima, the WNN algorithm is enhanced with the IPSO algorithm. This significantly increased the convergence speed of the identification model and its ability to discover the global optimal solution. The simulation results demonstrate that this method can effectively and accurately identify the fault type with high identification accuracy, quick identification, and robust adaptability. Under challenging working conditions, it is capable of accurately identifying the fault type of 66 kV transmission lines. Full article

Carpal tunnel syndrome (CTS) is the most common pathology among disorders of the peripheral nervous system related to median nerve compression. To our knowledge, there are limited data on the effect of tendon movement on median nerve compression. This study focuses on the understanding of the carpal syndrome by simulating the impact of tendons movement caused by fingers flexion by Finite Element Analysis. Therefore, such modeling is the step toward the development of a personalized technique for value determining median nerve compression. Open-source MRI of the human right hand was used to build patient-specific phalanges of the fingers. Carpal tunnel soft tissues were considered as hyper-elastic materials, while bone structures were considered as elastic ones. The final finite-element model had 40 solid bodies which contacted the joint. Results were obtained for four cases of wrist movements: finger flexion, hand flexion/extension, and wrist extension with subsequent by finger flexion. Compression of the median nerve ranged from 129 Pa to 227 Pa. The results show that compression of the median nerve occurs faster during wrist flexion than during wrist extension or finger flexion. A decrease in compression during finger flexion was noticed with wrist extension followed by finger flexion. Full article

Due to recent advances in communication systems, dielectric and magnetic ceramics (ferrites) are attractive for use in devices. Spinel-type ferrites were the first material utilized in microwave devices; however, yttrium iron garnet (YIG) has low dielectric losses and is exploited in many applications. Owing to its high Faraday rotation, YIG films are utilized in magneto-optical applications. This study intends to examine the research trends and scientific research progress on highly cited papers discussing YIG films published between 2012 and 2022 using a bibliometric method. A comprehensive review of 100 scientific papers about YIG was performed from the Scopus database. The assessment of these highly cited papers was highlighted based on the following factors: publication trends and performance, limitations/research gaps, keywords, sub-fields, methodology journal evaluations, document type evaluation, issues, difficulties, solutions, and applications as well as guiding future YIG research. The majority of publications (99%) comprise experimental analysis, whereas 1% provide a based state-of-the-art overview. Ninety-one percent of articles focused on magnetization characterization. This bibliometric survey indicates that YIG film research is an expanding and developing field. The results of the data analysis can be utilized to improve the researchers’ understanding of YIG research and to encourage additional study in this area. Full article

Southern Romania is a geographic region with alluvial deposits. This soil type leads to rather long corner periods and provides as a particularity of the response spectrum an enlarged plateau. These conditions produce large displacement demands. Moreover, pulse-type ground acceleration records make this seismic area more unique. Research on the seismic behaviour of structures built under such unusual conditions is limited and Romanian engineers are not confident to apply alternative solutions such as base isolation. Although capacity design is still the regular design method applied in Romania, modern base isolation solutions may overcome the large displacement demand expectation produced by seismic events and fulfil immediate occupancy requirements. This study presents the seismic performance of an existing hospital from Bucharest, for which two seismic design solutions were applied: (i) classical approach based on capacity design and (ii) base isolation. Both approaches are compared in terms of drift, acceleration and base shear values. Static as well as non-linear dynamic analysis methods were applied. Full article

As an emerging flexible-scale energy storage technology, underwater compressed gas energy storage (UW-CGES) is regarded as a promising energy storage option for offshore platforms, offshore renewable energy farms, islands, coastal cities, etc. Liquid accumulation often occurs in underwater gas transmission pipelines, which is a challenge to overcome. In this study, an experimental investigation is carried out on the pressure distribution characteristics of liquid accumulation flow in hilly terrain under the condition of Zero Net Liquid Flow. A slug flow pressure model with different inclination angles at four times is established and verified, and its error range is within ±20%. Analysis revealed that reduction and growth in pressure difference are related to the outflow of slug in an inclined pipe. A high-speed camera is used to capture the movement of liquid accumulation under Zero Net Liquid Flow (ZNLF) and record the associated dynamic parameters. By imaging the motion of liquid accumulation and detecting the pressure changes in the pipeline at various times, the pressure fluctuation in the pipeline at the slug flow cause is studied. Outcomes from this work can be leveraged to help further the development of underwater compressed gas energy storage technology. Full article

The purpose of this study was to investigate the effects of oxygen tension on mouse induced pluripotent stem (iPS) cells by assessing differentiation in terms of embryoid body (EB) size and mRNA and protein expression levels of collagen type 1 and Runx2. EBs and outgrowth cells (OGCs) were cultured in conditions of hypoxia (2%), normoxia (21%) and hyperoxia (35%). Significantly larger EBs were observed in the hyperoxia and normoxia groups compared to the hypoxia group on Days 8 and 10. The hyperoxia group had significantly higher mRNA and protein expression levels of collagen type 1 and Runx2 compared to the hypoxia and normoxia groups on Days 10 and 26, and these expression levels in the hypoxia group were significantly lower than the normoxia group on Days 10 and 26. These results suggest that hyperoxia accelerates the enlargement in EBs and the differentiation of iPS cells. Full article

This paper investigates the dissipativity analysis of large-scale networked systems with linear time-invariant dynamics. The networked system is composed of a large number of subsystems whose connections are arbitrary, and each subsystem can have different dynamics. A sufficient and necessary condition for the strict dissipativity analysis of the networked system is derived, which takes advantage of the block-diagonal structure of the system parameter matrix and the sparseness characteristics of the subsystem interconnections. Then, a necessary condition and a sufficient condition that depend only on a single subsystem parameter are given separately. Numerical simulations illustrate that compared with the existing results, the conditions suggested in this paper have higher computational efficiency in the dissipative analysis of large-scale networked systems. Full article

Chia seed mucilage is a polysaccharide capable of forming hydrogels with excellent water-binding capacity due to its physical and chemical properties and favorable characteristics for encapsulating and protecting valuable hydrophilic molecules in the food, pharmaceutical, and cosmetic industries. This research aimed to show that mixtures of chia seed mucilage and sodium alginate used as wall materials to encapsulate hydrophilic molecules are suitable. We analyzed the relationship between the mucilage–alginate solution’s properties and the capsules obtained; we quantified the entrapment efficiency (EE%) and the release of rhodamine B; and we proposed a method to follow the rhodamine B release using confocal laser scanning microscopy (CLSM). We found that more viscous solutions are obtained when the mucilage concentration increases, making it difficult to produce capsules with less sphericity. The best entrapment efficiency was found when the proportion of the polymers was close to 1:1, based both on the properties of the capsules obtained and on the characterization of the release kinetics of rhodamine B; the analysis performed by fitting rhodamine B release data to theoretical models describe the diffusion process. Our results show that the use of chia seed mucilage as a wall material to trap and retain hydrophilic molecules is convenient. Full article

Aiming at the robotization of the grinding process in the steel bar finishing process, the steel bar grinding robot can achieve the goal of fast, efficient, and accurate online grinding operation, a multi-layer forward propagating deep neural network (DNN) method is proposed to efficiently predict the kinematic solution of grinding robot. The process and kinematics model of the grinding robot are introduced. Based on the proposed method, simulations of the end position and orientation, and joint angle of the grinding robot are given. Three different methods, including SGD + tanh, Nadam + tanh, Nadam + ELU, are used to test the DNN calculation process results show that the method combining Nadam with ELU function has the fastest solution speed and higher accuracy can be obtained with the increase in iteration times. Finally, the Nadam optimizer is used to optimize the calculation results of the example. The optimization results show that this method accelerates the convergence rate of trajectory prediction error and improves the accuracy of trajectory prediction. Thus, the proposed method in this paper is an effective method to predict the kinematic solution when the grinding robot works online. Full article

Stable subphthalocyanine-type dyes with a high electron affinity attract much attention as potential substitutes for traditional fullerenes in molecular electronics devices. One possible way to enhance the acceptor properties of the subphthalocyanine core is by replacing the peripheral benzene fragments (C₆H₄) with 1,2,5-thiadiazole fragments (C₂N₂S₁). However, the resistance of these materials to light or atmospheric effect remains an open question, which limits their further application in device manufacturing. In this work, we compare vacuum-deposited films of three derivatives, SubPzS₃H₀ (all peripheral fragments are 1,2,5-thiadiazoles), SubPzS₂H₄ (two fragments are 1,2,5-thiadiazoles and one fragment is benzene), and SubPcS₀H₁₂ (all benzenes, i.e., parent subphthalocyanine). Practically relevant substrates were used for deposition, namely, bare glass, glass/ITO or FTO, and PET/ITO. Photobleaching of films under continuous 1 sun illumination was studied in laboratory air, synthetic air, and ultrapure argon. It is shown that the exclusion of near-UV photons from the incident light spectrum, which corresponds to the absorption of subphthalocyanines in the Soret-band, strongly inhibits degradation. Absorption in the Q-band range initiates soft annealing rather than photobleaching of films. The stability of the films deposited on glass decreases as SubPzS₃H₀ > SubPzS₂H₄ > SubPcS₀H₁₂ in air, and vice versa in argon. The substrate adds more complexity to this picture. In argon, the ITO coating reduces degradation of all of the compounds equally, in contrast to the glass samples, while in air, the SubPzS₃H₀ films discolor completely. The latter reaction proceeds due to the indium-containing species migrating from the conductive coating. Full article

Melanin skin lesions are most commonly spotted as small patches on the skin. It is nothing but overgrowth caused by melanocyte cells. Skin melanoma is caused due to the abnormal surge of melanocytes. The number of patients suffering from skin cancer is observably rising globally. Timely and precise identification of skin cancer is crucial for lowering mortality rates. An expert dermatologist is required to handle the cases of skin cancer using dermoscopy images. Improper diagnosis can cause fatality to the patient if it is not detected accurately. Some of the classes come under the category of benign while the rest are malignant, causing severe issues if not diagnosed at an early stage. To overcome these issues, Computer-Aided Design (CAD) systems are proposed which help to reduce the burden on the dermatologist by giving them accurate and precise diagnosis of skin images. There are several deep learning techniques that are implemented for cancer classification. In this experimental study, we have implemented a custom Convolution Neural Network (CNN) on a Human-against-Machine (HAM10000) database which is publicly accessible through the Kaggle website. The designed CNN model classifies the seven different classes present in HAM10000 database. The proposed experimental model achieves an accuracy metric of 98.77%, 98.36%, and 98.89% for protocol-I, protocol-II, and protocol-III, respectively, for skin cancer classification. Results of our proposed models are also assimilated with several different models in the literature and were found to be superior than most of them. To enhance the performance metrics, the database is initially pre-processed using an Enhanced Super Resolution Generative Adversarial Network (ESRGAN) which gives a better image resolution for images of smaller size. Full article

The novelty of this paper is to propose a numerical method for solving ordinary differential equations of the first order that include both linear and nonlinear terms (ODEs). The method is constructed in two stages, which may be called predictor and corrector stages. The predictor stage uses the dependent variable’s first- and second-order derivative in the given differential equation. In literature, most predictor–corrector schemes utilize the first-order derivative of the dependent variable. The stability region of the method is found for linear scalar first-order ODEs. In addition, a mathematical model for boundary layer flow over the sheet is modified with electrical and magnetic effects. The model’s governing equations are expressed in partial differential equations (PDEs), and their corresponding dimensionless ODE form is solved with the proposed scheme. A shooting method is adopted to overcome the deficiency of the scheme for solving only first-order boundary value ODEs. An iterative approach is also considered because the proposed scheme combines explicit and implicit concepts. The method is also compared with an existing method, producing faster convergence than an existing one. The obtained results show that the velocity profile escalates by rising electric variables. The findings provided in this study can serve as a helpful guide for investigations into fluid flow in closed-off industrial settings in the future. Full article

It is generally known that the two most crucial elements of concrete that depend on the slump value of the mixture are workability and compressive strength. In addition, slump retention is more delicate than the commonly used slump value since it reflects the concrete mixture’s durability for usage in civil engineering applications. In this study, the effect of three water-reducer additives was tested on concrete’s workability and compressive strength from 1 day to 28 days of curing. The slump of the concrete was measured at the time of adding water to the mix and after 30 min of adding water. This study employed 0–1.5% (%wt) water-reducer additives. The original ratio between water and cement (wc) was 0.65, 0.6, and 0.56 for mixtures incorporating 300, 350, and 400 kg of cement. It was lowered to 0.3 by adding water-reducer additives based on the additives type and cement content. Depending on the kind and amount of water-reducer additives, w/c, gravel content, sand content, crushed content, and curing age, adding water-reducer additives to the concrete increased its compressive strength by 8% to 186%. When polymers were added to the concrete, they formed a fiber net (netting) that reduced the space between the cement particles. As a result, joining the cement particles quickly enhanced the fresh concrete’s viscosity and the hardened concrete’s compressive strength. The study aims to establish mathematical models (nonlinear and M5P models) to predict the concrete compressive strength when containing water-reducer additives for construction projects without theoretical restrictions and investigate the impact of mix proportion on concrete compressive strength. A total of 483 concrete samples modified with 3 water-reducer additives were examined, evaluated, and modeled for this study. Full article

In this research series, several sugar beet molasses of different osmolalities were inoculated with a mix of the following microorganisms, Escherichia coli, Salmonella spp. and Listeria monocytogenes, to develop mathematical models and correlations of the effect of different levels of osmolality and different exposure time to the viability of the selected microorganisms. The respective enumerations of Escherichia coli, Salmonella spp., Listeria monocytogenes, Enterobacteriaceae, and total plate count were conducted on inoculated molasses samples of different osmolalities (from 5500 to 7000 mmol/kg) and at different exposure times (from 0 to 5 h). The results showed that by increasing molasses osmolalities, all the selected microorganisms’ exposure time viability measures statistically decreased significantly. Salmonella spp. showed the highest viability of all the tested microorganisms in a high osmotic environment. In contrast, Listeria monocytogenes showed the least resilience to osmotic stress, with a reduction in the numbers below the detection limit. The developed mathematical models of microorganisms’ viability exposed to molasses’s high-osmolality environment were statistically significant, allowing for the good prediction of a number of microorganisms based on exposure time and osmolality levels. The obtained results describe molasses’s excellent microbial load-reducing capability and provide the potential for applications in the production of safe foods. Full article

Counterbalanced forklift trucks (FLT) are frequently used in combination with interchangeable equipment in order to handle loads in different manners. The main risks which may arise after assembling interchangeable equipment to a FLT are related to the loss of stability of the assembly. Actually, the presence of interchangeable equipment and the associated payload may change in a significant way the overall centre of gravity with respect to the FLT in its basic configuration with forks. Therefore, the stability limits of the assembly, based on the same footprints on the ground of the FLT alone, are affected by the position of the overall centre of gravity. Thus, the presence of interchangeable equipment could reduce the functionality (e.g., lifting capability, lifting height, etc.) of the FLT in order to continue its stability during use. Often, interchangeable equipment is placed on the market by manufacturers other than the FLT manufacturer. In these cases, the correct and safe coupling of the interchangeable equipment with the FLT is the responsibility of the manufacturers of interchangeable equipment, including the stability risk assessment. Thus, the interchangeable equipment manufacturer should have access to the relevant information of the FLT concerning operative and structural features and its configuration as a procedure for assessing the correct and safe coupling. Otherwise, he should perform experimental stability tests for each model of FLT so that its interchangeable equipment can be fitted. Specific research activity is developed in order to define an analytical procedure to assess the stability of FLT when assembled with interchangeable equipment. Specific typologies of FLTs and interchangeable equipment have been selected in order to better characterise the case study. The analytical equations mimic the static stability tests. The results achieved have been compared to experimental data in order to optimise the procedure. The results attained by the application of the analytical procedure to all the combinations of main typologies of FLTs and the interchangeable equipment selected showed good agreement with experimental tests. Full article

Mechanical methods of tunnel excavation are widely used because of their high excavation output, and the selection of appropriate technology depends on ground composition and project-related features. Compared with tunnel boring machines (TBMs) and roadheaders, mechanical pre-cutting machines are used in tunnel widening and have proven to be reliable in tunnel capacity expansion. Compared to other machines, the excavation characteristics of pre-cutting machines are not systematically analyzed because of their rare use. In this study, the excavation characteristics of a pre-cutting machine are analyzed in a laboratory based on linear cutting tests performed on four rock specimens with different uniaxial compressive strengths. During testing, changes in tool forces, cutting volume, and specific energy are determined while maintaining different penetration depths, spacings, and rock strengths. The variations in these variables are selected accordingly. The results showed high similarity with the case of TBMs and roadheaders. However, in the excavation by the pre-cutting machine, the ratios of the peak-to-mean cutting forces and cutting-to-normal forces reached a maximum value at a specific s/p (spacing and penetration ratio), which is related to the optimal cutting conditions. This study can provide useful information for the operation and design of pre-cutting machines. Full article

Congenital muscular dystrophies (CMDs) are a heterogeneous group of genetic neuromuscular disorders. They usually occur at birth or in early childhood, with delayed acquisition of motor milestones, and diffuse muscle weakness. A dystrophic pattern is evident on the muscle biopsy. They are highly variable both in terms of severity and clinical evolution and in terms of pathogenetic biochemical mechanisms. The aim of this review is to collect and summarize the current knowledge of motor function in pediatric patients with congenital muscular dystrophies and the instruments used to assess it. This scoping review was conducted using the methodology of PRISMA (extension for Scoping Reviews, PRISMA-ScR). Two databases were queried from January 2002 to November 2022. Articles were identified based on title and abstract. Full-text papers published in peer-reviewed English-language journals were selected. It emerged that motor functional aspects are still underinvestigated in CMD patients, probably due to the rarity of these conditions and the phenotypic variability. The scales used to assess motor function are heterogeneous, as are the age groups considered. Finally, the predominant type of research design is cross-sectional; few studies analyze the progression of motor function over time. All these factors make it difficult to correlate the results of different publications and stress the need for more accurate and shared protocols for assessing motor function in these patients. Full article

Microalgae harvesting by coagulation can use coagulant agents such as alum, synthetic polymers or biocoagulants. Biocoagulants have attracted the attention of researchers because they are natural, biodegradable, and promote high microalgal harvesting efficiencies. This study aims to optimize the harvesting of Chlorella vulgaris based on the dosage of the Opuntia cochenillifera extract and the choice of eluent for biopolymer extraction. The outdoor cultivation of C. vulgaris achieved a specific growth rate of 0.455 d⁻¹ and a maximum biomass concentration of 1.28 g_DW L⁻¹. In order to harvest the microalgal biomass, the polymer present in the mucilage of O. cochenillifera was extracted using NaOH and HCl. Coagulation and sedimentation assays were performed with different coagulant dosages: 3.5, 5.9, and 8.2 g L⁻¹. The maximum harvesting efficiencies using the acid and alkaline extract coagulant solutions were 80.8% and 99.5%, respectively, with a dosage of 3.5 g L⁻¹. According to the results, the C. vulgaris biomass can be harvested with the mucilage from O. cochenillifera in acid and alkaline eluents. The application of this biocoagulant constitutes a sustainable solution for microalgal harvesting. Full article

Domain-generalized few-shot text classification (DG-FSTC) is a new setting for few-shot text classification (FSTC). In DG-FSTC, the model is meta-trained on a multi-domain dataset, and meta-tested on unseen datasets with different domains. However, previous methods mostly construct semantic representations by learning from words directly, which is limited in domain adaptability. In this study, we enhance the domain adaptability of the model by utilizing the distributional signatures of texts that indicate domain-related features in specific domains. We propose a Multi-level Distributional Signatures based model, namely MultiDS. Firstly, inspired by pretrained language models, we compute distributional signatures from an extra large news corpus, and we denote these as domain-agnostic features. Then we calculate the distributional signatures from texts in the same domain and texts from the same class, respectively. These two kinds of information are regarded as domain-specific and class-specific features, respectively. After that, we fuse and translate these three distributional signatures into word-level attention values, which enables the model to capture informative features as domain changes. In addition, we utilize domain-specific distributional signatures for the calibration of feature representations in specific domains. The calibration vectors produced by the domain-specific distributional signatures and word embeddings help the model adapt to various domains. Extensive experiments are performed on four benchmarks. The results demonstrate that our proposed method beats the state-of-the-art method with an average improvement of 1.41% on four datasets. Compared with five competitive baselines, our method achieves the best average performance. The ablation studies prove the effectiveness of each proposed module. Full article

Despite the many proposals to solve the neural machine translation (NMT) problem of low-resource languages, it continues to be difficult. The issue becomes even more complicated when few resources cover only a single domain. In this paper, we discuss the applicability of a source-side monolingual dataset of low-resource languages to improve the NMT system for such languages. In our experiments, we used Wolaytta–English translation as a low-resource language. We discuss the use of self-learning and fine-tuning approaches to improve the NMT system for Wolaytta–English translation using both authentic and synthetic datasets. The self-learning approach showed +2.7 and +2.4 BLEU score improvements for Wolaytta–English and English–Wolaytta translations, respectively, over the best-performing baseline model. Further fine-tuning the best-performing self-learning model showed +1.2 and +0.6 BLEU score improvements for Wolaytta–English and English–Wolaytta translations, respectively. We reflect on our contributions and plan for the future of this difficult field of study. Full article

Driver fatigue can be further categorized into passive fatigue and active fatigue based on the task-induced fatigue perspective, with its categorization necessary from a theoretical basis and practical needs. Passive fatigue is caused by mental underload and inactive task engagement, which is considered more hazardous. To facilitate the construction of the driver monitoring system (DMS), the current study aims to investigate the physiological and behavioral changes of passive fatigue. A total of thirty-six participants completed a 90 min driving task on a monotonous highway, during which subjective fatigue level, eye tracking indicators, and driving dynamics were recorded using the Stanford Sleepiness Scale, Smart Eye Pro, and CAN Bus system. Results showed that drivers reported higher levels of fatigue as driving duration increased. An increase in pupil diameters and gaze dispersions were observed during the task. Drivers gradually reduced the control of the vehicle, in which faster speed and lower speed compliance were witnessed. In addition, a compensatory process was found as passive fatigue increased. Drivers tended to lower their standards to maintain the lateral position but recovered their lateral control when they lost control of the car speed. The current study emphasizes the importance of investigating active and passive fatigue of drivers independently, and the unique physiological and behavioral changes accompanied by passive fatigue should be considered in designing driver monitoring systems. Full article

Natural gas is cheaper than fuel on an energy basis, making it an alternative ship fuel which leads to a reduced operating cost and clean gas environmental conditions. The current study analyses the retrofit of an ageing multi-purpose ship to use liquefied natural gas as a primary ship fuel in the context of a short-ship sea operation. The objective is to transform an existing commercial ageing ship propulsion system into a green energy propulsion one and to analyse the economic feasibility considering the high volatility and increased LNG price. Four scenarios were analysed based on the net present value representing Denying, Disinterested, Good and Acceptable financial cash outflow. It was concluded that in the present economic instability and price of LNG fuel and CO₂ taxes, the ship owner needs to rely on the long-term contract of buying LNG fuel to implement measures to reduce greenhouse gas emissions and keep good benefits in shipping. Full article

Software design patterns have a proven impact on the quality of software applications and the development process of an application. The success of design patterns in the software industry has attracted mobile game developers and researchers to apply patterns in the context of mobile games. Researchers have already proposed different frameworks and design patterns, but they are not truly beneficial for game developers. The high-level taxonomies can be adjuvant while proposing useful design patterns. The existing taxonomies for mobile games do not consider different parts of a game that outline top-level structure. In this paper, we propose a new taxonomy that emphasizes the top-level structure for identifying new design patterns for mobile games. We propose five novel generic design patterns that might be applied to the development of mobile games and other software applications. The presented design patterns are, in a true sense, programming patterns that outline top-level generic classes and interfaces, and that could be the basis for the development of new games. We developed four demo games by using these patterns for the realization of taxonomy and design patterns. Full article