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16 pages, 5656 KiB

Open AccessTechnical Note

The Possibility of Detrimental Effects on Soil–Structure Interaction in Seismic Design Due to a Shift in System Frequency

by Weifeng Tao, Jia Fu and Yugang Li

Appl. Sci. 2024, 14(17), 7519; https://doi.org/10.3390/app14177519 (registering DOI) - 26 Aug 2024

Abstract

Soil–structure interaction (SSI) leads to a modification in the dynamic properties of structure, but due to the complexity of analysis, it is traditionally assumed in seismic designs that the structure is fixed-supported on the ground, which brings about potential risks to the seismic [...] Read more.

Soil–structure interaction (SSI) leads to a modification in the dynamic properties of structure, but due to the complexity of analysis, it is traditionally assumed in seismic designs that the structure is fixed-supported on the ground, which brings about potential risks to the seismic performances of structure. The study works on the possibility of SSI having detrimental effects by comparing the dynamic responses of the SSI system to a fixed-base structure, and presents charts for an evaluation of the system frequency of SSI for the purpose of engineering practice. In order to reveal the physical nature, the SSI model is reduced to its simplest form, consisting of a SDOF oscillator, a three-dimensional rectangular foundation, and a multi-layered half-space. The energy dissipation in the soil is achieved by foundation impedances and the substructure method. Previously, the foundation impedances are usually acquired by two-dimensional or axisymmetric three-dimensional models in uniform half-space to avoid the high cost of the more realistic, fully 3D models, while a high-precision indirect boundary element method is employed, combined with the non-singular Green’s functions of distributed loads to calculate the foundation impedances. Although SSI dampens the peak amplitude of structure response in the frequency domain, case studies on four buildings’ responses to 42 earthquakes in the time history show a possibility of 15–20% that SSI amplifies the dynamic responses of structures, such as the maximum and the mean values in the time history, depending on the properties of the structures and the site, as well as the frequency component of incident waves. Full article

(This article belongs to the Special Issue Soil-Structure Interaction in Structural and Geotechnical Engineering)

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12 pages, 730 KiB

Open AccessArticle

EMG Activity of Lower Limb Muscles During Anti-Gravity Treadmill Running with Different Loads and Speeds

by Przemysław Pietraszewski, Artur Gołaś, Robert Roczniok, Mariola Gepfert and Adam Zając

Appl. Sci. 2024, 14(17), 7518; https://doi.org/10.3390/app14177518 (registering DOI) - 25 Aug 2024

Abstract

The study’s objective was to identify the features of internal movement structure that depend on speed and the importance of unloading when jogging on an anti-gravity treadmill. The aim was to investigate whether the internal structure of running changes under unloaded conditions, using [...] Read more.

The study’s objective was to identify the features of internal movement structure that depend on speed and the importance of unloading when jogging on an anti-gravity treadmill. The aim was to investigate whether the internal structure of running changes under unloaded conditions, using an anti-gravity treadmill. Twenty male competitive middle- and long-distance runners with the following characteristics participated in the study: age, 25 ± 5 years; body weight, 67.2 ± 8.9 kg; body height, 177 ± 11 cm; and training experience, 9 ± 5 years. The gastrocnemius (GC), tibialis anterior (T), quadriceps femoris (Q), biceps femoris (B), and gluteus (G) were the five lower limb muscles whose muscle activity was evaluated. Surface electromyography (sEMG) was used to measure muscle activation while jogging and running on the AlterG Anti-Gravity Treadmill. The study method involved capturing the examined muscular activity at four different speeds: 6, 10, 14, and 18 km/h. At each of these speeds, four two-minute measurements were taken with varying body weight relief: 100%, 75%, 50%, and 25% of body weight. Repeated measures multivariate analysis of variance (RM-MANOVA) [F = 3.4663 p = 0.0001] showed that as running speed increases, the muscular activity of each muscle, expressed as a percentage of maximum muscle tension (%MVIC), decreases significantly. Results indicate that running pace affects the dynamics of the reduction in muscle activity in every examined muscle. As one runs faster, the decline in dynamics becomes more intense. At the slowest jogging pace (6 km/h), the variations were almost negligible (±4 percentage points between 25% and 100% body weight relief) as unloading increased. However, the discrepancies reached up to 14 percentage points at the fastest running speed (18 km/h). In every muscle studied, distinctive patterns and significant dynamics at high speeds were observed. The study’s findings suggest that using an anti-gravity treadmill for training can be beneficial, yet it is important to consider the significant relationships between speed and relief, as these variables could impact maintaining a proper movement pattern and running style. This knowledge may be useful when choosing the right training regimens and loads for runners recovering from injuries. Full article

17 pages, 835 KiB

Open AccessArticle

Effects of Allium ursinum L. Leaves and Egg Amount on Quality Attributes, Polyphenol Content, and Antioxidant Capacity of Pasta

by Cristina Adriana Rosan, Mariana Florica Bei, Alexandra Cristina Tocai (Moţoc), Manuel Alexandru Gitea and Simona Ioana Vicas

Appl. Sci. 2024, 14(17), 7517; https://doi.org/10.3390/app14177517 (registering DOI) - 25 Aug 2024

Abstract

Pastas enriched with vegetables are premium nutritious products and their consumption can bring significant health benefits. Recent studies have reported a high content of bioavailable phytochemical compounds in Allium ursinum L.; as such, it can be used in the development of functional food [...] Read more.

Pastas enriched with vegetables are premium nutritious products and their consumption can bring significant health benefits. Recent studies have reported a high content of bioavailable phytochemical compounds in Allium ursinum L.; as such, it can be used in the development of functional food products. This study involved the evaluation of 10 varieties of pasta. Five of these varieties were made from white flour and varying amounts of egg (Ctrl_1–Ctrl_5). The other five varieties (AU_1–AU_5) contained fresh shredded wild garlic leaves in equal proportions (20 g) in addition to the corresponding ingredients (white flour and egg). All pasta variants were investigated for their cooking properties and the presence of bioactive compounds and antioxidant capacity in the raw and cooked pasta. Sensory analysis was conducted on all types of cooked pasta, and results indicated that the pasta with the least quantity of eggs was the most favoured variant. Additionally, the pasta that was enhanced with wild garlic leaves received the highest rating for “overall quality”. According to our results, the optimal cooking time (OCT) increased when the quantity of eggs was raised, but when wild garlic leaves were present, OCT decreased in comparison to the control samples. A significant decrease (p < 0.05) in the cooking parameters, swelling index, and water absorption was observed in both egg pasta (Ctrl) and egg pasta enriched with A. ursinum L. (AU). However, compared to the corresponding egg pasta, the presence of wild garlic in pasta generally produced higher values in SI and WA. Pastas enriched with wild garlic are rich in polyphenols (TPh), with a content ranging from 82.44 to 94.62 µg GAE/g dw, and also exhibit antioxidant properties. The amount of total polyphenol significantly decreases (p < 0.05) during cooking varies depending on the composition of the pasta. The pasta with the highest egg content (AU_5) had the lowest loss of polyphenols, equivalent to 55.35%. Our investigations indicate that producing pasta with eggs and fresh wild garlic leaves results in a valuable food product with a good sensory score, enriched in bioactive components, with essential nutrients that maintains cooking qualities. Full article

(This article belongs to the Special Issue Advances in Bioactive Compounds from Plants and Their Applications)

20 pages, 2289 KiB

Open AccessArticle

Enhanced Coconut Yield Prediction Using Internet of Things and Deep Learning: A Bi-Directional Long Short-Term Memory Lévy Flight and Seagull Optimization Algorithm Approach

by Rami N. Alkhawaji, Suhail H. Serbaya, Siraj Zahran, Vasiliki Vita, Stylianos Pappas, Ali Rizwan and Georgios Fotis

Appl. Sci. 2024, 14(17), 7516; https://doi.org/10.3390/app14177516 (registering DOI) - 25 Aug 2024

Abstract

In coastal areas, coconuts are a common crop. Everyone from farmers to lawmakers and businesses would benefit from an accurate forecast of coconut production. Internet of Things (IoT) sensors are strategically positioned to continuously monitor the environment and gather production statistics to obtain [...] Read more.

In coastal areas, coconuts are a common crop. Everyone from farmers to lawmakers and businesses would benefit from an accurate forecast of coconut production. Internet of Things (IoT) sensors are strategically positioned to continuously monitor the environment and gather production statistics to obtain accurate agricultural output predictions. To effectively estimate coconut prediction, this study presents an enhanced deep learning classifier called Bi-directional Long Short-Term Memory (BILSTM) with the integrated Lévy Flight and Seagull Optimization Algorithm (LFSOA). LASSO feature selection is applied to eliminate the superfluous characteristics in the yield estimation. To further enhance the coconut yield estimate, the optimal set of hyperparameters for BILSTM is tuned by the LFSOA, which helps to avoid the overfitting issue. For the results, the BILSTM is compared against different classifiers such as Recurrent Neural Network (RNN), Random Forest Classifier (RFC), and LSTM. Similarly, LFSOA-based hyperparameter tuning is contrasted with different optimization algorithms. The outputs show that LFSOA-based hyperparameter tuning in BILSTM achieved accuracy, precision, recall, and f1-score of 98.963%, 99.026%, 99.155%, and 95.758%, respectively, which are higher when compared to existing methods. Similarly, the BILSTM-LFSOA accomplished better results in statistical measures, including the Root Mean Square Error (RMSE) of 0.105, Mean Squared Error (MSE) of 0.011, Mean Absolute Error (MAE) of 0.094, and coefficient of determination (R²) of 0.954, respectively. From the overall analysis, the proposed BILSTM-LFSOA improves coconut yield prediction by achieving better results in all the performance measures when compared with existing models. The results of this study are important to many stakeholders, including but not limited to policymakers, farmers, banks, and insurance companies. As coconuts are an important crop in developing countries, accurate coconut yield forecasting will lead to greater financial and food security in these regions. Full article

(This article belongs to the Special Issue Novel Research and Application on Swarm Optimization and Bioinspired Optimization Algorithms)

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16 pages, 4395 KiB

Open AccessArticle

Genesis of Low-Resistivity Shale Reservoirs and Its Influence on Gas-Bearing Property: A Case Study of the Longmaxi Formation in Southern Sichuan Basin

by Xi Hu, Anfu Zhou, Yading Li, Hongzong Jiang, Yonghong Fu, Yuqiang Jiang and Yifan Gu

Appl. Sci. 2024, 14(17), 7515; https://doi.org/10.3390/app14177515 (registering DOI) - 25 Aug 2024

Abstract

To mitigate the exploration and development risks, it is necessary to have a deeper understanding of the formation mechanism and gas-bearing control factors of low-resistance shale reservoirs. This study focuses on typical shale gas wells (including low-resistivity wells) in Luzhou area, and identification [...] Read more.

To mitigate the exploration and development risks, it is necessary to have a deeper understanding of the formation mechanism and gas-bearing control factors of low-resistance shale reservoirs. This study focuses on typical shale gas wells (including low-resistivity wells) in Luzhou area, and identification criteria for low-resistance shale reservoirs are redefined as resistivity less than 10 Ω·m and continuous formation thickness greater than 6 m. At the macro scale, low-resistivity shale reservoirs are characterized by high clay mineral content and high water saturation with low gas content. At the micro scale, the main pore size is less than 10 nm, with a small total pore volume but a large specific surface area. Shale reservoirs close to the Class II fault have high water saturation and strong compaction, which hinders the mutual transformation between minerals, resulting in low-resistivity shale with high clay mineral content, small pore volume, and pore size, which promotes the enhancement of reservoir conductivity. The gas content of low-resistivity shale reservoirs is lower, because the distance from the Class II fault is closer, resulting in high water saturation and strong diagenesis, which is not conducive to pore development and shale gas accumulation. When the water saturation exceeds 40%, the pore volume of shale reservoirs rapidly decreases to as low as 0.0074 cm³/g. In order to reduce the risk of exploration and development of the area, the well location deployment needs to be more than 2.8 km away from the Class II fault. Full article

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23 pages, 422 KiB

Open AccessArticle

On Beamforming with the Single-Sideband Transform

by Vitor Probst Curtarelli and Israel Cohen

Appl. Sci. 2024, 14(17), 7514; https://doi.org/10.3390/app14177514 (registering DOI) - 25 Aug 2024

Abstract

In this paper, we examine the use of the Single-Sideband Transform (SSBT) for convolutive beamformers. We explore its unique properties and implications for beamformer design. Our study sheds light on the tradeoffs involved in using the SSBT in beamforming applications, offering insights into [...] Read more.

In this paper, we examine the use of the Single-Sideband Transform (SSBT) for convolutive beamformers. We explore its unique properties and implications for beamformer design. Our study sheds light on the tradeoffs involved in using the SSBT in beamforming applications, offering insights into both its strengths and limitations. Despite the advantage of having real-valued coefficients, we show that the convolution handling of the transform presents challenges that impact fundamental beamforming principles. When compared to the Short-Time Fourier Transform (STFT), the SSBT displays lower robustness, especially in scenarios involving mismatch and modeling noise. Notably, we establish a direct equivalence between the SSBT and STFT when using identical transform parameters, enabling their seamless interchangeability and joint use in time–frequency signal enhancements. We validate our theoretical findings through realistic simulations using the Minimum-Power Distortionless Response beamformer. These simulations illustrate that although the STFT performs marginally better than the SSBT under optimal conditions, it outperforms significantly in non-ideal scenarios. Full article

(This article belongs to the Special Issue Advances and Applications of Audio and Speech Signal Processing)

18 pages, 1284 KiB

Open AccessArticle

Virtual Reality Immersive Simulations for a Forensic Molecular Biology Course—A Quantitative Comparative Study

by Ahmed Ewais, Stylianos Mystakidis, Walid Khalilia, Shadi Diab, Athanasios Christopoulos, Said Khasib, Baha Yahya and Ioannis Hatzilygeroudis

Appl. Sci. 2024, 14(17), 7513; https://doi.org/10.3390/app14177513 (registering DOI) - 25 Aug 2024

Abstract

Molecular biology is a complex, abstract, subject that can be challenging for higher education students to comprehend. The current manuscript describes the design, implementation, and evaluation of two immersive VR simulations of a DNA lab and a crime scene investigation (CSI) for a [...] Read more.

Molecular biology is a complex, abstract, subject that can be challenging for higher education students to comprehend. The current manuscript describes the design, implementation, and evaluation of two immersive VR simulations of a DNA lab and a crime scene investigation (CSI) for a forensic molecular biology course in the context of the “TESLA” Erasmus+ project. It illustrates the instructional design and technical aspects of the VR simulations’ development. The experimental study employed a comparative quantitative research design. The guiding research questions examined how instructional modalities (online vs. face-to-face) affect learners’ perceptions of VR-based training in higher education and the key factors influencing learners’ intention for their adoption. Forty-six (n = 46) undergraduate students completed a 17-item questionnaire, which served as the main data collection instrument. Results demonstrate that both online and face-to-face VR-based instruction can effectively convey core concepts, thus challenging the traditional notion that face-to-face interaction is inherently superior. Its implications underscore the potential of VR simulations to supplement or even substitute traditional teaching methods, particularly for complex science subjects. Full article

(This article belongs to the Special Issue Virtual and Augmented Reality Technology in Education and Entertainment)

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19 pages, 5810 KiB

Open AccessArticle

Influence of the Initial Prestress Level on the Distribution of Regions of Dynamic Instability of Geiger Domes

by Paulina Obara and Maryna Solovei

Appl. Sci. 2024, 14(17), 7512; https://doi.org/10.3390/app14177512 (registering DOI) - 25 Aug 2024

Abstract

This paper provides a parametric analysis of cable–strut tensegrity domes subjected to periodic loads. This analysis aims at determining the main regions of dynamic instability (unstable regions). From the point of view of the physical interpretation of the phenomenon, if the load occurs [...] Read more.

This paper provides a parametric analysis of cable–strut tensegrity domes subjected to periodic loads. This analysis aims at determining the main regions of dynamic instability (unstable regions). From the point of view of the physical interpretation of the phenomenon, if the load occurs in these regions, the amplitudes of the resulting vibrations increase, posing a risk to the durability of the structures. The consideration includes cable–strut structures called Geiger domes. Four dome design solutions known from the literature are compared, i.e., regular (patented by Geiger) and modified domes with a closed and an open upper section. In contrast to conventional cable–strut structures, Geiger domes are characterized by a self-equilibrated system of internal forces (initial prestress), which affects the shape and range of unstable regions. The main purpose is to answer the question as to which type of design solution is more sensitive to the risk of excitation vibrations. A nondimensional parameter

λ

is introduced for this quantitative assessment. This parameter reliably determines the change in the area of unstable regions as the initial prestress level increases. The range of the parameter

λ

is defined as a value between 1 and 0. In the case of

λ = 1

, there is potential for the excitation of unstable motion, whereas in the case of

λ = 0

, such a risk is absent. The analysis presented in this paper can be employed in the process of optimizing the initial prestress level, which will constitute the subsequent stage of this research. A geometrically non-linear model is used to evaluate the behavior of the considered structures. Full article

(This article belongs to the Section Mechanical Engineering)

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18 pages, 8150 KiB

Open AccessArticle

Flexural Fatigue Behavior of Prestressed High-Performance Concrete Bridges with Double Mineral Fine Powder Admixture: An Experimental Study

by Zhiguo Zhang and Haoran Li

Appl. Sci. 2024, 14(17), 7511; https://doi.org/10.3390/app14177511 (registering DOI) - 25 Aug 2024

Abstract

High-performance concrete (HPC) is commonly used in the main structures of bridges. HPC is widely applied in the main structures of bridges, yet some skepticism remains with integrating fly ash and mineral powder as admixtures into prestressed HPC bridges. To address this, this [...] Read more.

High-performance concrete (HPC) is commonly used in the main structures of bridges. HPC is widely applied in the main structures of bridges, yet some skepticism remains with integrating fly ash and mineral powder as admixtures into prestressed HPC bridges. To address this, this study conducted scaled-model experiments to analyze the flexural fatigue behavior of prestressed HPC bridges with double-mineral fine powder admixtures (PB-DA). This study derives the similarity criteria for a simply supported beam bridge under a concentrated load based on similarity theory. Subsequently, in following these criteria, a 30 m long actual bridge is scaled down to a 6 m PB-DA at a 1:5 scale. For this scaled PB-DA, the concentrated load is reduced to 1/25 of the actual bridge, while the strain remains the same as in the actual bridge. The double-mineral fine powder admixture (D-A) was produced and used to fabricate PB-DA by mixing fly ash and mineral powder. Five PB-DAs were constructed, with C50 and C80 concrete strength grades, and admixture ranges from 10% to 32%. Sinusoidal half-wave constant stress amplitude loading at 5 Hz frequency was applied, with 2 million fatigue loading cycles. After fatigue loading, a continuously increasing static load was applied until the PB-DA failed. The experimental results show that the upper part of the PB-DA is compressed, and the lower part is in tension. The PB-DA strain distribution from top to bottom generally conforms to the plane section assumption. During 2 million fatigue loading cycles, 200,000 cycles mark the beam strain and stiffness evolution boundary. Below 200,000 cycles, the PB-DA strain rapidly increases, and flexural stiffness quickly decreases. Beyond 200,000 cycles, the rate of increase in strain and the rate of decrease in flexural stiffness significantly slow down. After fatigue loading, the PB-DA displacement increases exponentially under a continuously increasing static load. The crack distribution is uniform across all PB-DA, with the cracks being sparsest at a 30% admixture. A comprehensive analysis shows that all PB-DAs demonstrate good flexural fatigue behavior. Notably, when D-A content reaches 30%, strain increases, but reductions in flexural stiffness and damage in PB-DA significantly decrease. This paper’s conclusions provide a reference for applying D-A at PB-DA. Full article

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20 pages, 4654 KiB

Open AccessArticle

An Optimization Method for Location-Routing of Cruise Ship Cabin Materials Considering Obstacle Blocking Effects

by Jinghua Li, Wenhao Huang, Xiaoyuan Wu, Ruipu Dong and Pengfei Lin

Appl. Sci. 2024, 14(17), 7510; https://doi.org/10.3390/app14177510 (registering DOI) - 25 Aug 2024

Abstract

This study examines the challenges related to the storage and distribution of cabin materials on board during the construction of cruise ships. The construction process of cruise ships involves the assembly of various cabin materials, which are temporarily stored and transported in a [...] Read more.

This study examines the challenges related to the storage and distribution of cabin materials on board during the construction of cruise ships. The construction process of cruise ships involves the assembly of various cabin materials, which are temporarily stored and transported in a complex deck environment with multiple obstacles. These processes can be viewed as location-routing problems (LRPs). However, existing solutions for LRPs do not account for the obstacles commonly encountered in deck environments. Therefore, this paper introduces a new variant of LRPs, termed as the BE-LRP (blocking environment location-routing problem). Initially, by considering the optimization objectives of minimizing the distribution distance and the number of vehicles required, the paper develops an optimization model for the location-routing of on-board materials while taking obstacles into consideration. Subsequently, a method for estimating blocked distances is proposed. This method utilizes Gaussian process regression to predict blocked distances and enables the rapid estimation of distances obstructed by obstacles between different destinations. Lastly, a hybrid obstacle blocking distance processing HO-NSGAII algorithm is formulated to address the BE-LRP. Experimental comparisons demonstrate that the distribution scheme derived from this research method does not necessitate modifications to the delivery distance when compared to the traditional NSGAII algorithm, and better aligns with the actual deck conditions. With an equivalent number of delivery vehicles, the scheme results in shorter delivery distances. The delivery distance can be reduced by 3–17% under varying circumstances. These findings are advantageous for enhancing the efficiency of cruise ship construction and mitigating the impact of warehousing and distribution on construction progress. Full article

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18 pages, 6518 KiB

Open AccessArticle

The Lattice Boltzmann Method and Image Processing Techniques for Effective Parameter Estimation of Digital Rock

by Ardian Nurcahya, Aldenia Alexandra, Fadhillah Akmal and Irwan Ary Dharmawan

Appl. Sci. 2024, 14(17), 7509; https://doi.org/10.3390/app14177509 (registering DOI) - 25 Aug 2024

Abstract

Several numerical simulations of fluid flow were performed using the Lattice Boltzmann method and image processing techniques to estimate the effective properties of 2-D porous rocks. The effective properties evaluated were the physical characteristics that allow fluid flow including the effective porosity, permeability, [...] Read more.

Several numerical simulations of fluid flow were performed using the Lattice Boltzmann method and image processing techniques to estimate the effective properties of 2-D porous rocks. The effective properties evaluated were the physical characteristics that allow fluid flow including the effective porosity, permeability, tortuosity, and average throat size to determine the storage and transport of fluids in porous rocks. The permeability was compared using the Darcy model simulation and the empirical Kozeny–Carman Equation. The results showed that the Lattice Boltzmann method and image processing techniques can estimate the effective parameters of porous rocks. Furthermore, there was a good correlation between permeability and parameters such as effective porosity, tortuosity, and average throat size. The Darcy model simulation revealed a gamma distribution in the permeability, while the empirical Kozeny–Carman Equation showed a log-normal distribution. Full article

(This article belongs to the Section Fluid Science and Technology)

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26 pages, 11819 KiB

Open AccessArticle

CNN-Based Damage Identification of Submerged Structure-Foundation System Using Vibration Data

by Ngoc-Lan Pham, Quoc-Bao Ta and Jeong-Tae Kim

Appl. Sci. 2024, 14(17), 7508; https://doi.org/10.3390/app14177508 (registering DOI) - 25 Aug 2024

Abstract

This study presents a convolutional neural network (CNN) deep learning approach for identifying damage in submerged structure-foundation systems using vibration data. Firstly, foundation damage in a lab-scale caisson-foundation system is simulated to measure time-history responses. Singular value decomposition (SVD) responses are derived from [...] Read more.

This study presents a convolutional neural network (CNN) deep learning approach for identifying damage in submerged structure-foundation systems using vibration data. Firstly, foundation damage in a lab-scale caisson-foundation system is simulated to measure time-history responses. Singular value decomposition (SVD) responses are derived from the time-history responses. Secondly, the 1-D CNN deep learning model is trained using both the time-history responses and SVD responses. Finally, the trained CNN models are implemented to evaluate the foundation damage under conditions of noise contamination and partially untrained data. The experimental results demonstrate the effectiveness of CNN models for damage identification and highlight the comparative strengths of time-history and SVD data. The CNN model trained using SVD data outperforms the other model when under noise contamination conditions, while the CNN model trained using time-history data maintains better accuracy in partially untrained data conditions. Integrating both types of data enhances the accuracy of damage classification. Full article

(This article belongs to the Special Issue Artificial Intelligence in Fault Diagnosis and Signal Processing)

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22 pages, 2133 KiB

Open AccessArticle

Degradation and Migration in Olive Oil Packaged in Polyethylene Terephthalate under Thermal Treatment and Storage Conditions

by Pablo González-Torres, Ángeles García-Ruiz and M. Dolores La Rubia

Appl. Sci. 2024, 14(17), 7507; https://doi.org/10.3390/app14177507 (registering DOI) - 25 Aug 2024

Abstract

The research addresses challenges in food safety related to the migration of contaminants from plastics to food. It focused on the physicochemical and sensory degradation of olive oils packaged in polyethylene terephthalate (PET) and subjected to thermal exposure at 40 °C and 60 [...] Read more.

The research addresses challenges in food safety related to the migration of contaminants from plastics to food. It focused on the physicochemical and sensory degradation of olive oils packaged in polyethylene terephthalate (PET) and subjected to thermal exposure at 40 °C and 60 °C for several weeks and a subsequent 12 months of storage, as well as the stability and migration of compounds from the PET packaging itself. Olive oils (OO) from Spanish supermarkets (a mixture of refined and virgin, with commercial identifications of mild and intense) were selected and subjected to thermal treatments at 40 °C and 60 °C for 1, 2, and 3 weeks, followed by 12 months of storage. The treatments were conducted through the following two independent experiments: Experiment A focused on immediate analysis post-thermal treatment, while Experiment B included a 12-month storage period post-thermal treatment. The presence of antimony (Sb) was analyzed using acid digestion with nitric acid (HNO₃) and high-resolution inductively coupled plasma mass spectrometry (HR-ICP-MS), while the metals cadmium (Cd), copper (Cu), lead (Pb), and iron (Fe) were analyzed using inductively coupled plasma mass spectrometry (ICP-MS). The PET characterization was assessed using Fourier transform infrared spectroscopy in the mid-infrared range (FT-IR/MIR), carbonyl index, and differential scanning calorimetry (DSC). The results showed increases in the acidity index by 0.29%, the peroxide value by 25.92%, and the K₂₆₈ coefficient by 51.22% between the control sample and the most severe treatments, with more pronounced effects observed after 12 months. Sensory quality declined, with reduced intensity of the “fruity” attribute and increased presence of the “rancid” defect. PET degradation was reflected in an increase in the carbonyl index and greater structural amorphization. Fe was the predominant metal, and Sb concentration increased after thermal treatments. The lack of studies on the raw consumption of oils packaged in PET and the concerns about the migration of compounds from the packaging to the food highlight the relevance of this research. This study provides new insights into the effects of thermal exposure and storage on the migration of PET contaminants into oils, contributing to the development of strategies to ensure food safety and product quality. Full article

(This article belongs to the Section Green Sustainable Science and Technology)

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11 pages, 2736 KiB

Open AccessArticle

Identification of Topographic Seismic Site Periods in Sloping Terrains

by Edgar Giovanny Diaz-Segura and Jorge Eduardo Oviedo-Veas

Appl. Sci. 2024, 14(17), 7506; https://doi.org/10.3390/app14177506 (registering DOI) - 25 Aug 2024

Abstract

The fundamental period of a terrain is a key parameter for characterizing the maximum soil amplification. Since the 1960s, research has been conducted for sloping terrains with a focus on evaluating topographic effects. However, few studies have focused on identifying whether the site [...] Read more.

The fundamental period of a terrain is a key parameter for characterizing the maximum soil amplification. Since the 1960s, research has been conducted for sloping terrains with a focus on evaluating topographic effects. However, few studies have focused on identifying whether the site topography induces an amplification peak that is associated with a characteristic period of sloping terrain. This study conducts a parametric analysis to identify a potential amplification pattern attributable to terrain geometry, using two-dimensional finite element models subjected to the action of a dynamic signal. The periods in which amplification peaks are generated are evaluated and compared with the amplification response recorded in the free field on horizontal terrain. The results reveal that the dynamic response of sloping terrain is a combination of the response from the surrounding terrain to the sloping zone and vice versa, and a distinctive amplification peak linked to the topography is identified. A new expression is proposed to define a topographic seismic site period in terms of shear wave velocity and the total soil thickness from the bedrock to the crest of sloping terrain. This study advances the processes of characterizing the seismic response of sloping terrains by demonstrating that the topographic seismic site period is consistent regardless of the slope angle. This provides engineers with a new dimension of analysis for the practical definition of criteria to determine topographic effects in design spectra. Full article

(This article belongs to the Special Issue Geotechnical Earthquake Engineering: Current Progress and Road Ahead)

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21 pages, 9294 KiB

Open AccessArticle

Influence of Fractal Disc Filter Flow Channel Parameters on Filtration Performance

by Jiefeng Zeng, Peiling Yang, Weijie Liu and Xudong Xiang

Appl. Sci. 2024, 14(17), 7505; https://doi.org/10.3390/app14177505 (registering DOI) - 25 Aug 2024

Abstract

The research and development of a new disc filter is a key link in intelligent irrigation systems, the core of efficient and water-saving irrigation development, and also an important joint effort to ensure a clean water source in micro-irrigation systems. In this paper, [...] Read more.

The research and development of a new disc filter is a key link in intelligent irrigation systems, the core of efficient and water-saving irrigation development, and also an important joint effort to ensure a clean water source in micro-irrigation systems. In this paper, the independent research and development of the fractal flow passage disc filter was taken as the research object, and the disc filter numerical simulation cell (FLUENT) and artificial intelligence technology (Back Propagation Neural Network) were combined to optimize the filter flow channel parameters, including the tilt angle, the length and height of the bottom of the internal section triangle, the taper, the position and number of buffer slots, etc. A new type of disc filter with lower head loss, larger flow capacity, higher filtration efficiency, and longer running time is proposed. It has certain reference value and promotion significance for the future development and design of high-performance disc filters and their wide use. Full article

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17 pages, 11033 KiB

Open AccessArticle

Logging Identification Method for Reservoir Facies in Fractured-Vuggy Dolomite Reservoirs Based on AI: A Case Study of Ediacaran Dengying Formation, Sichuan Basin, China

by Yu Ye, Zengzheng Jiang, Xiangjun Liu, Zhanlei Wang and Yifan Gu

Appl. Sci. 2024, 14(17), 7504; https://doi.org/10.3390/app14177504 (registering DOI) - 25 Aug 2024

Abstract

As an important target for deep to ultra-deep carbonate oil and gas exploration, Fractured-Vuggy dolomite reservoirs have strong heterogeneity. Accurate characterization of reservoir facies is crucial for their exploration and exploitation. Three methods, including the unsupervised intelligent clustering method of improved Fuzzy C-means [...] Read more.

As an important target for deep to ultra-deep carbonate oil and gas exploration, Fractured-Vuggy dolomite reservoirs have strong heterogeneity. Accurate characterization of reservoir facies is crucial for their exploration and exploitation. Three methods, including the unsupervised intelligent clustering method of improved Fuzzy C-means clustering Algorithm Based on Density Sensitive Distance and Fuzzy Partrition (FCM-DSDFP), the fusion method of Principal Components Analysis (PCA) dimensionality reduction and noise reduction, and the principle of clustering feature analysis are applied to identify reservoir facies based on logging data. Based on the PCA method, the logging response characteristics of the reservoir facies are excavated, and the fusion characterization data of dimensionality reduction and noise reduction are extracted. The FCM-DSDFP unsupervised intelligent clustering method, a model that approximates the subsurface conditions is established, and the reliability of the model is tested according to the elbow rule and silhouette coefficient. Combining drilling core observation, Fractured-Vuggy type, partially cemented Fractured-Vuggy type, Pore-Vuggy type, Pore Type I, Pore Type II, Tight Type I, and Tight Type II are divided in the Dengying Formation 4th Member. Fractured-Vuggy type, partially cemented Fractured-Vuggy type, Pore-Vuggy Type I, Pore-Vuggy Type II, Pore Type I, Pore Type II, and Tight Type are divided in the Dengying Formation 2nd Member, respectively. Two methods were applied to verify the reservoir facies identification results based on intelligent algorithms. The first method is to compare the identification results with the reservoir facies types identified by core observations (Well PT103 and PS13). The second method is to verify the recognition results of intelligent algorithms by utilizing the relationship between reservoir facies types and bitumen. The test results show that the accuracy of the reservoir level identification is higher than 0.9, and the applicability is better than the commonly used algorithms such as FCM and K-means. Full article

(This article belongs to the Topic Geomechanics and Engineering Evaluation of Fractured Oil and Gas Reservoirs)

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13 pages, 7337 KiB

Open AccessArticle

Natural Lime–Cork Mortar for the Seismic and Energetic Retrofit of Infill Walls: Design, Materials, and Method

by Rocco Buda and Raffaele Pucinotti

Appl. Sci. 2024, 14(17), 7503; https://doi.org/10.3390/app14177503 (registering DOI) - 25 Aug 2024

Abstract

Recent seismic events have prompted research into innovative and sustainable materials for strengthening and repairing obsolete and vulnerable buildings. These earthquakes have exposed the high seismic vulnerability of existing reinforced concrete (RC) buildings, particularly in secondary structural elements like infill walls. In addition [...] Read more.

Recent seismic events have prompted research into innovative and sustainable materials for strengthening and repairing obsolete and vulnerable buildings. These earthquakes have exposed the high seismic vulnerability of existing reinforced concrete (RC) buildings, particularly in secondary structural elements like infill walls. In addition to structural issues, these buildings often face significant energy deficiencies, such as thermal bridges, due to inadequate insulation. Traditionally, structural and energy improvements for residential buildings are addressed separately with different methods and protocols. This preliminary study is part of a broader research initiative at the University of Reggio Calabria (Italy), aiming to design an innovative fiber-reinforced plaster using natural, sustainable, and locally produced materials to enhance the energy and structural performance of existing wall infills. The study investigates two plaster matrices made of natural hydraulic lime and silica sand, with 15% and 30% cork granules added. Mechanical and thermophysical tests on multiple specimens were conducted to evaluate their suitability for seismic and energy retrofitting of infill walls. Results indicate that adding cork reduces mechanical strength by approximately 42% at a 30% cork content without compromising its use in seismic retrofitting. Thermophysical tests show improved thermal performance with a higher cork content. These findings suggest that the lime–cork mixture at 30% is effective, offering excellent ductility and serving as a promising alternative to traditional cementitious plaster systems. The next experimental phase will test matrices with varying percentages of gorse fiber. Full article

(This article belongs to the Special Issue High Reliability Building Structures: Retrofits, Designs and Applications, 2nd Edition)

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11 pages, 1003 KiB

Open AccessArticle

Physicochemical Characterization of Carao Honey Flour (Cassia grandis) and Its Effects on the Sensory Attributes in a Cookie

by Jhunior Marcía Fuentes, Manuel de Jesús Álvarez Gil, Héctor Zumbado Fernández, Ismael Montero-Fernández, Daniel Martín-Vertedor, Ajitesh Yadav and Ricardo S. Aleman

Appl. Sci. 2024, 14(17), 7502; https://doi.org/10.3390/app14177502 (registering DOI) - 25 Aug 2024

Abstract

Carao honey is a potential functional ingredient that can generate added value to food products enriched by reducing waste. In many countries, carao has been utilized for therapeutic purposes since this type of plant extract can inhibit the growth against the most common [...] Read more.

Carao honey is a potential functional ingredient that can generate added value to food products enriched by reducing waste. In many countries, carao has been utilized for therapeutic purposes since this type of plant extract can inhibit the growth against the most common dermatophytes, a pathogenic fungus that grows on the skin, mucous membranes, hair, nails, feathers, and other body surfaces, causing ringworm and related diseases. The physicochemical characteristics of the cookies were also investigated, which included aW, proximate analysis, hardness, and color. A sensory study was carried out to determine the rejection threshold, acceptability, purchase intent, and general taste of 90 consumers. The gluten-free cookies were prepared with carao honey as a partial substitute for rice flour in different percentages (0%, 2.5%, 5%, and 10%). The carao honey proximate composition, rheological properties, and pasting properties were analyzed. It was emphasized that incorporating carao honey into cookies improves the ingredient’s sustainability. The impact of carao on the physicochemical and sensory properties of cookies was evident in color, flavor, and smell. According to the results, only samples with 2.5% carao were accepted regarding flavor and smell. Overall, liking scores, age, and flavor were the most significant predictors of purchase intent. The information given to panelists did not significantly (p < 0.05) influence liking scores only for cookies. According to physicochemical analysis, carao honey flour was high in carbohydrates (88%). The incorporation of carao produced cookies with darker colors and a softer texture. The study demonstrated that carao flour could be included to produce sensorial accepted cookies at a 2.5% addition level as an alternative in the food industry that benefits from environmental sustainability and, at the nutritional level, improves the availability of nutrients, mainly sugars and proteins. Full article

(This article belongs to the Special Issue Topical Advisory Panel Members’ Collection Series: Functional Foods)

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4 pages, 168 KiB

Open AccessEditorial

Decision Support Systems for Disease Detection and Diagnosis

by Maria Rizzi

Appl. Sci. 2024, 14(17), 7501; https://doi.org/10.3390/app14177501 (registering DOI) - 25 Aug 2024

Abstract

The last few years have been characterized by a large amount of research activity in the field of healthcare for both the improvement of diagnostic treatments and the development of simple, efficient, and multi-tasking applications [...] Full article

(This article belongs to the Special Issue Decision Support Systems for Disease Detection and Diagnosis)

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