Applied Sciences

Extinction has been frequently studied by evolutionary biologists and is shown to play a significant role in evolution. The genetic algorithm (GA), one of popular evolutionary algorithms, has been based on key concepts in natural evolution such as selection, crossover, and mutation. Although GA has been widely studied and implemented in many fields, little work has been done to enhance the performance of GA through extinction. In this research, we propose stagnation-driven extinction protocol for genetic algorithm (SDEP-GA), a novel algorithm inspired by the extinction phenomenon in nature, to enhance the performance of classical GA. Experimental results on various benchmark test functions and their comparative analysis indicate the effectiveness of SDEP-GA in terms of avoiding stagnation in the evolution process. Full article

Taste function and condition may be a tool that exhibits a rapid deficit to impress the subject with an objectively measured effect of smoking on his/her own body, because smokers exhibit significantly lower taste sensitivity than non-smokers. This study proposed a visual method to measure capillaries of taste buds with capillaroscopy and classified the difference between smokers and non-smokers through convolutional neural networks (CNNs). The dataset was collected from 26 human subjects through the capillaroscopy with the low and high magnification directly; of which 13 were smokers, and the other 13 were non-smokers. The acquired dataset consisted of 2600 images. The results of gradient-weighted class activation mapping (grad-cam) enabled us to understand the difference in capillaries of taste buds between smokers and non-smokers. Through the results, it was found that CNNs gave us a good performance with 79% accuracy. It was discussed that there was a shortage of extracted features when the conventional methods such as structural similarity index (SSIM) and scale-invariant feature transform (SIFT) were used to classify. Full article

Based on the principal stress values generated by the bending beam, the material’s strength required at 10⁶ cycles is determined depending on time. To determine the stress/strength reliability (R(t)), the stress distribution is determined directly from the range of the principal stresses values, and the strength distribution is determined based on the reduced tensile strength (S'_e) and fatigue strength (S_e) range. Therefore, based on the time-dependent stress and the material’s strength, a step-by-step method to determine the reliability R(t) of the structural element at 10⁶ cycles is provided. The R(t) index is used to select the best among the feasible beam alternatives of the static/elastic and plastic methodologies. The method’s efficiency is based on the time-dependent stress analysis performed by using the elastic modulus, and corresponding strain as time dependence variables. Because the time-dependent stress is related to the changes of the bending deflection through time, it is determined based on the addressed equivalent stress at 10⁶ cycles. Full article

Flow duration curve (FDC) is a cumulative frequency curve that shows the percent of time a specific discharge has been equaled or exceeded during a particular period of time at a given river location, providing a comprehensive description of the hydrological regime of a catchment. Thus, relying on historical streamflow records, FDCs are typically constrained to gauged and updated ground stations. Earth Observations can support our monitoring capability and be considered as a valuable and additional source for the observation of the Earth’s physical parameters. Here, we investigated the potential of the surface reflectance in the Near Infrared (NIR) band of the MODIS 500 m and eight-day product, in providing reliable FDCs along the Mississippi River. Results highlight the capability of NIR bands to estimate the FDCs, enabling a realistic reconstruction of the flow regimes at different locations. Apart from a few exceptions, the relative Root Mean Square Error, rRMSE, of the discharge value in validation period ranges from 27–58% with higher error experienced for extremely high flows (low duration), mainly due to the limit of the sensor to penetrate the clouds during the flood events. Due to the spatial resolution of the satellite product higher errors are found at the stations where the river is narrow. In general, good performances are obtained for medium flows, encouraging the use of the satellite for the water resources management at ungauged river sites. Full article

This paper suggests an application of blockchain as an energy open data ledger, designed to save and track data regarding the energy footprint of public buildings and public energy communities. The developed platform permits writing energy production and consumption of public buildings using blockchain-enabled smart meters. Once authenticated on the blockchain, this data can be made available to the public domain for techno-economic analyses for either research studies and internal or third parties audits, increasing, in this way, the perceived transparency of the public institutions. A further feature of the platform, starting on the previously disclosed raw data, allows calculating, validating, and sharing sustainability indicators of public buildings and facilities, allowing the tracking of their improvements in sustainability goals. The paper also provides the preliminary results of a field-test experimentation of the proposed platform on a group of public buildings, highlighting the possible benefits of its widespread exploitation. Full article

Attainable moment sets (AMS) are a powerful method to assess aircraft controllability. However, as attainable moment sets only take into account the achievable moment set of the control effectors, they do not assess the required moment set to fulfill the aircraft mission requirements. This paper proposes to calculate a corresponding required moment set (RMS) which defines a set of moments sufficient for fulfilling aircraft controllability requirements in the mission flight envelope. The paper applies the required moment set approach to a nonlinear simulation model of an electric vertical take off vehicle (eVTOL) transition drone in hover. By comparing the required moment set to the AMS of the aircraft model, moment set margins are derived and used to assess the controllability of the considered aircraft. The results indicate that the combined evaluation directly identifies critical moment channels and margins, which is advantageous when compared to a pure AMS-based evaluation. The proposed approach enables the execution of simulation-based assessments in aircraft design and flight control development. In the early stages of aircraft design, required moment sets can support sizing, positioning and tilting of control effectors (e.g., propulsive elements) to fit the AMS to the actual required force and moment set for the specific system. Full article

Cold atmospheric pressure sterilization is one of the nominated and efficient techniques to prevent the spread of diseases. Reactive species such as O and OH and other radicals play a major role in the mechanism of plasma sterilization. Therefore, in this work, oxygen was mixed with different parentage from (0.2 to1.2%) to argon to enhance the generation of the reactive species and increase the argon atmospheric pressure plasma sterilization efficacy. The emission spectra from the jet increase the radicle line intensities by increasing the percentage admixture of O₂ with the argon gas to reach a maximum power at 0.8; then, it gradually decreases with a higher O² percentage. The OH band intensity decreases with increasing the admixture of O₂. The jet with different O₂ percentages was tested against Gram-positive S. epidermidis, which is the causal agent of nosocomial infections. The maximum reduction in colony-forming units (CFU) was observed at 0.2% O₂. No bacterial growth was observed at the later concentration applied for 8 min and the same case was detected at 0.4% O₂ applied to 16 min. Full article

The agro-industrial sector consumes a significant amount of natural resources for farming and meat production. By 2050, population growth is expected, generating more demand and, consequently, more consumption of scarce resources. This challenging scenario is a concern of the European Commission, revealed in the Green Deal commitment and by the United Nations’ 12th goal of sustainable development. Thus, organizations must increase productivity and be more sustainable as soon as possible. Internet of Things (IoT) is introduced as a solution to facilitate agro-food companies to be more eco-efficient, mainly facing difficulties on farms, such as food loss and waste, best efficiency in management of resources, and production. The deployment of this technology depends on the stage of maturity and potential of implementation. To assess and characterize companies, with respect of IoT implementation, a survey was applied in 21 micro, small and medium agro-food companies, belonging to milk, honey, olive oil, jams, fruticulture, bakery and pastry, meat, coffee, and wine sectors, in the central region of Portugal. As results, this paper reveals the stage of maturity, level of sophistication, potential, opportunities, solutions, and barriers for implementation of IoT. Additionally, suggestions and recommendations to improve practices are discussed. Full article

Resonance frequency analysis (RFA) is the most extended method for measuring implant stability. The implant stability quotient (ISQ) is the measure obtained by different RFA devices; however, inter- and intra-rater reliability and agreement of these instruments remain unknown. Thirty implants were placed in three different pig mandibles. ISQ was measured parallel and perpendicular (lingual) to the peg axis with Osstell^® Beacon, Penguin^® and MegaISQ^® by two different investigators and furthermore, one performed a test-retest. Intraclass correlation coefficient was calculated to assess the intra- and inter-rater reliability. Pearson correlation coefficient was used to assess the agreement. Intraclass correlation coefficients ranged from 0.20 to 0.65 for the Osstell^® Beacon; 0.57 to 0.86 for the Penguin^®; and −0.01 to 0.60 for the MegaISQ^®. The highest ISQ values were obtained using Penguin^® (66.3) in a parallel measurement; the lowest, using the MegaISQ^® (60.1) in a parallel measurement. The highest correlation values with the other devices were obtained by MegaISQ^® in a parallel measurement. Osstell^® Beacon and MegaISQ^® showed lower reliability than Penguin^®. Osstell^® had good agreement for measuring ISQ both in parallel and perpendicular, and MegaISQ^® had the best agreement for measuring ISQ in parallel. Full article

Little is still known about macro- and micronutrients in processed selected Brassica vegetables such as purple and green cauliflower, rutabaga and kale. This study evaluates the influence of different processing conditions (blanching and boiling) on the stability of selected macro- and micronutrients in the aforementioned vegetables. Results indicated that blanching and boiling affect the mineral content of Brassica vegetables. Of the examined Brassica vegetables, the largest losses were found for potassium and iron (on average by 39.72%). Full article

The Massachusetts Eye and Ear Infirmary (MEEI) database is an international-standard training database for voice pathology detection (VPD) systems. However, there is a class-imbalanced distribution in normal and pathological voice samples and different types of pathological voice samples in the MEEI database. This study aimed to develop a VPD system that uses the fuzzy clustering synthetic minority oversampling technique algorithm (FC-SMOTE) to automatically detect and classify four types of pathological voices in a multi-class imbalanced database. The proposed FC-SMOTE algorithm processes the initial class-imbalanced dataset. A set of machine learning models was evaluated and validated using the resulting class-balanced dataset as an input. The effectiveness of the VPD system with FC-SMOTE was further verified by an external validation set and another pathological voice database (Saarbruecken Voice Database (SVD)). The experimental results show that, in the multi-classification of pathological voice for the class-imbalanced dataset, the method we propose can significantly improve the diagnostic accuracy. Meanwhile, FC-SMOTE outperforms the traditional imbalanced data oversampling algorithms, and it is preferred for imbalanced voice diagnosis in practical applications. Full article

Both natural and anthropogenic coastal landforms characterize Penang Island. As years have passed it is a challenge to differentiate the genuineness of landmasses created by natural geological formations or by coastal reclamation projects. An account is given of the environmental impact of solid wastes used for reclaiming land in coastal areas of Penang and of the impact of a major sewage outfall in the western channel. Leaching of heavy metals was shown to be one of the main sources of contamination from solid wastes. This paper presents eight lines of ground penetrating radar (GPR) surveys and sediment analysis to identify the anthropogenic interventions that shaped the urban landscape of Penang Island by excavations, filling, and embankment construction along the coastline and differentiate it from the natural one. The surveys were implemented in two locations, the Batu Ferringhi area, representing the natural coastline, and Persiaran Bayan Indah (the Queensbay Mall area), representing the anthropogenic coastal landform. The apparent depth of penetration that was achieved using a 250-MHz antenna is limited (less than 5 m). The results show between natural and anthropogenic sediment recorded different radar facies. In complement mode, mean grain size distribution, sorting, skewness, and kurtosis graphics of sediment samples from both sites correspond with the GPR data. This technique can likely be applied to the developing coast, where natural and anthropogenic coastal landform data is incomplete, considering future coastline development. Full article

This paper proposes a complete-information-based principal component analysis (CIPCA)-back-propagation neural network (BPNN)_ fault prediction method using real unmanned aerial vehicle (UAV) flight data. Unmanned aerial vehicles are widely used in commercial and industrial fields. With the development of UAV technology, it is imperative to diagnose and predict UAV faults and improve their safety and reliability. The data-driven fault prediction method provides a basis for UAV fault prediction. A UAV is a typical complex system. Its flight data is a kind of typical high-dimensional large sample dataset, and traditional methods cannot meet the requirements of data compression and dimensionality reduction at the same time. The method used interval data to compress UAV flight data, used CIPCA to reduce the dimensionality of the compressed data, and then used a back propagation (BP) neural network to predict UAV failure. Experimental results show that the CIPCA-BPNN method had obvious advantages over the traditional principal component analysis (PCA)-BPNN method and could accurately predict a failure about 9 s before the UAV failure occurred. Full article

Anterior to posterior (AP) pinning is the recommended sagittal pin configuration in divergent lateral entry coronal pinning of pediatrics supracondylar fractures. However, there was still a lack of evidence regarding alternative sagittal pins configurations. We aimed to compare the construct stiffness of alternative sagittal pin configurations by using synthetic bone models. Sixty synthetic pediatric humeri were osteotomized to create a supracondylar fracture. After the fracture reduction, all specimens were fixed in the coronal plane with divergent lateral entry pin configurations in four different patterns in the sagittal plane: AP, crossed, divergent and parallel sagittal pin configuration. Each configuration was tested with five loading patterns. The AP sagittal pin had significantly lower construct stiffness than the divergent (p = 0.003) and the parallel sagittal pin configuration (p = 0.005) in external rotation loading tests. The divergent sagittal pin had the highest construct stiffness in extension, valgus, and external rotation loads, but the parallel sagittal pin had lower construct stiffness under extension load than the divergent and crossed sagittal pin configurations. The divergent sagittal pin configuration provides greater construct stiffness than other sagittal pin configurations due to the maximal pin spreading distance at the fracture site and the pin angle lock mechanism. Full article

This paper provides a synthetic and comprehensive overview on environmentally friendly anticorrosive polymeric coatings. Firstly, the economic and environmental impact of corrosion is presented to highlight the need of anticorrosive polymeric coatings as a flexible and effective solution to protect a metal. Secondly, the implementation of regulations together with the consumer awareness for environmental considerations and protection of health are the driving force for a progressive but significant change in the sector. Therefore, within the protective organic coatings market, this article provides a review of the most recent developments in environmentally friendly solutions, including bio-based and water-borne epoxy, hyperbranched polyester for low- volatile organic compounds (VOC) coatings, waterborne polyurethane and non-isocyanate polyurethanes (NIPUs), and graphene or bio-based fillers for acrylics. Moreover, this paper outlines new trends such as smart additives, bio-based corrosion inhibitors, and functional antibiocorrosive coatings as superhydrophobics. Finally, industrially relevant applications of environmentally friendly anticorrosive polymeric coatings including solutions for marine and off-shore industries are summarized. Full article

The application of solar energy as a renewable energy source has significantly escalated owing to its abundance and availability worldwide. However, the intermittent behavior of solar irradiance is a serious disadvantage for electricity grids using photovoltaic (PV) systems. Thus, reliable solar irradiance data are vital to achieve consistent energy production. Geostationary satellite images have become a solution to this issue, as they represent a database for solar irradiance on a massive spatiotemporal scale. The estimation of global horizontal irradiance (GHI) using satellite images has been developed based on physical and semi-empirical models, but only a few studies have been dedicated to modeling GHI using semi-empirical models in Korea. Therefore, this study conducted a comparative analysis to determine the most suitable semi-empirical model of GHI in Korea. Considering their applicability, the Beyer, Rigollier, Hammer, and Perez, models were selected to estimate the GHI over Seoul, Korea. After a comparative evaluation, the Hammer model was determined to be the best model. This study also introduced a hybrid model and applied a long short-term memory (LSTM) model in order to improve prediction accuracy. The hybrid model exhibited a smaller root-mean-square error (RMSE), 97.08 W/m², than that of the Hammer model, 103.92 W/m², while producing a comparable mean-bias error. Meanwhile, the LSTM model showed the potential to further reduce the RMSE by 11.2%, compared to the hybrid model. Full article

The authors focus on the process of potash ore production by a mechanized method. They show that currently there are no approved procedures for assessing the performance of heading-and-winning machines operating in the conditions of potash mines. This causes difficulties in determining the field of application of heading-and-winning machines, complicates the search for implicit technical solutions for the modernisation of existing models of mining units, prohibits real-time monitoring of the stability of stope-based technological processes and makes it difficult to assess the performance of the services concerning mining enterprises. The work represents an aggregate assessment of the performance of heading-and-winning machines for potash mines by determining complex indicators describing the technological and technical levels of organising the work in stopes. Such indicators are the coefficients of productivity and energy efficiency, respectively. Experimental studies have been carried out in the conditions of the potash mine of the Verkhnekamskoye potassium-magnesium salt deposit to assess the performance of the latest and most productive Ural-20R heading-and-winning machines manufactured in Russia. Using the above methodological approaches, this paper shows that the unsatisfactory technological performance of the studied machine is due to the low productivity of the mine district transport. The average productivity coefficient was 0.29. At the same time, high values of the energy efficiency coefficient show that the productivity of the machine is on par with design conditions. Full article

This study investigates the transient behavior of an electro-thermal drilling probe (ETDP) during a close-contact melting process within a glacier. In particular, the present work analyzes the effect of the tip temperature on the formation of molten thin liquid films and the subsequent rate of penetration (ROP) through numerical simulation. We used the commercial code of ANSYS Fluent (v.17.2) to solve the Reynolds-averaged Navier–Stokes equation, together with an energy equation considering the solidification and melting model. The ROP of the drilling probe is determined based on the energy balance between the heating power and melting rate of ice. As the results, the ETDP penetrates the ice through a close-contact melting process. The molten liquid layer with less than 1 mm of thickness forms near the heated probe tip. In addition, the ROP increases with the heated temperature of the probe tip. Full article