Applied Sciences

11 pages, 10669 KiB

Open AccessArticle

Feasibility of Osseous Landmarks for ACL Reconstruction—A Macroscopic Anatomical Study

by Lena Hirtler, Dominik Rieschl, Sam A. Kandathil and Patrick Weninger

Appl. Sci. 2023, 13(12), 7345; https://doi.org/10.3390/app13127345 - 20 Jun 2023

Viewed by 1340

During knee arthroscopy, easy orientation is important, and possible landmarks include the lateral intercondylar ridge (LIR) and the lateral bifurcate ridge (LBR). The objective was to show the feasibility of the LIR and the LBR as landmarks of the femoral attachment of the [...] Read more.

During knee arthroscopy, easy orientation is important, and possible landmarks include the lateral intercondylar ridge (LIR) and the lateral bifurcate ridge (LBR). The objective was to show the feasibility of the LIR and the LBR as landmarks of the femoral attachment of the anterior cruciate ligament (ACL) among subjects with different levels of training. Thirty-six formalin-phenol-fixed lower extremities were acquired for this prospective macroscopic anatomical study. All soft tissue apart from the ligaments was removed. The two bundles of the ACL and their origins were identified, marked and photographed. Photographs were taken in an arthroscopic setting. An orthopedic surgeon, an anatomist and a medical student identified the ridges. The LIR existed in 80.6% of samples, while the LBR existed in 13.8% of samples. A significant difference existed between the raters in correctly identifying the LIR (p < 0.01). Due to its high frequency, the LIR seems more reliable than the LBR, especially as the LBR has the potential for false positive identification. Nevertheless, as these ridges are not easily discernible, the surgeon has to know the anatomy of the intercondylar notch perfectly to stand even a small chance of correctly placing drill holes in ACL reconstruction. New guidelines for more easily recognizing LIR and LBR arthroscopically are proposed. Full article

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11 pages, 798 KiB

Open AccessArticle

The Presence of Aromatic Substances in Incense: Determining Indoor Air Quality and Its Impact on Human Health

by Cristina Di Fiore, Pietro Pandolfi, Fabiana Carriera, Alessia Iannone, Gaetano Settimo, Vincenzo Mattei and Pasquale Avino

Appl. Sci. 2023, 13(12), 7344; https://doi.org/10.3390/app13127344 - 20 Jun 2023

Cited by 5 | Viewed by 2206

Abstract

Indoor air quality has become a topic of great concern. Burning incense has recently been identified as one of the primary sources of volatile organic compounds, specifically benzene, in an indoor setting. The current paper aims to evaluate volatile organic compound (VOC) emissions, [...] Read more.

Indoor air quality has become a topic of great concern. Burning incense has recently been identified as one of the primary sources of volatile organic compounds, specifically benzene, in an indoor setting. The current paper aims to evaluate volatile organic compound (VOC) emissions, particularly benzene, within indoor environments through the utilization of an experimental clean room. Experimental findings showed that 10 types of incense sticks emitted benzene in concentrations between 11.1 and 66.5 μg m⁻³, which were 2.5 lower than the limit suggested for non-occupation indoor exposure (160 μg m⁻³), identified by the American Association of Industrial Hygienists (ACGIH). Furthermore, a correlation between the dimensions (diameter and length) of the combustible parts in an incense stick was investigated and indicated a slight influence on the release of benzene. Taking into consideration the substantial influence benzene has on human health, coupled with a lack of precise legislation regarding indoor air quality in residential settings, this research serves as an initial investigation into the noteworthy effects of burning incense in private and public indoor settings. Full article

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26 pages, 6894 KiB

Open AccessArticle

Performance of Solar Hybrid Cooling Operated by Solar Compound Parabolic Collectors under Weather Conditions in Riyadh, Kingdom of Saudi Arabia

by Zakariya Kaneesamkandi and Abdul Sayeed

Appl. Sci. 2023, 13(12), 7343; https://doi.org/10.3390/app13127343 - 20 Jun 2023

Cited by 1 | Viewed by 1895

Abstract

The scientific aim of this work is to encourage energy conservation. This article offers a fresh perspective on renewable energy in the air conditioning sector, the country’s economic growth, and environment-friendly techniques to overcome global warming challenges. In this research, a solar vapor [...] Read more.

The scientific aim of this work is to encourage energy conservation. This article offers a fresh perspective on renewable energy in the air conditioning sector, the country’s economic growth, and environment-friendly techniques to overcome global warming challenges. In this research, a solar vapor absorption refrigeration (SVAR) system was combined with a conventional vapor compression refrigeration (VCR) system to analyze their combined performance, employing a compound parabolic collector (CPC). The goal was to assess the performance of a solar hybrid cooling system using this non-tracking solar collector. CPC was validated for heat output with 2.9% uncertainty by utilizing an engineering equation solver (EES). Other system components were also validated with EES and then extended to a larger-capacity solar hybrid cooling system. The results of this research indicate that CPC is effective in providing the required heat to SVAR throughout the year without any tracking, and the integration of SVAR in series with the VCR condenser produces 83% higher COP than the system that integrates VCR with the condenser of the SVAR system for Riyadh. The configuration results in high values of exergy COP and an efficiency of 88% and 84%, respectively, increases the cooling capacity of the VCR by 68%, and decreases the carbon emission by 166.4%. Full article

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15 pages, 4328 KiB

Open AccessArticle

Investigating Mitochondrial Gene Expression Patterns in Drosophila melanogaster Using Network Analysis to Understand Aging Mechanisms

by Manuel Mangoni, Francesco Petrizzelli, Niccolò Liorni, Salvatore Daniele Bianco, Tommaso Biagini, Alessandro Napoli, Marta Adinolfi, Pietro Hiram Guzzi, Antonio Novelli, Viviana Caputo and Tommaso Mazza

Appl. Sci. 2023, 13(12), 7342; https://doi.org/10.3390/app13127342 - 20 Jun 2023

Cited by 1 | Viewed by 1728

Abstract

The process of aging is a complex phenomenon that involves a progressive decline in physiological functions required for survival and fertility. To better understand the mechanisms underlying this process, the scientific community has utilized several tools. Among them, mitochondrial DNA has emerged as [...] Read more.

The process of aging is a complex phenomenon that involves a progressive decline in physiological functions required for survival and fertility. To better understand the mechanisms underlying this process, the scientific community has utilized several tools. Among them, mitochondrial DNA has emerged as a crucial factor in biological aging, given that mitochondrial dysfunction is thought to significantly contribute to this phenomenon. Additionally, Drosophila melanogaster has proven to be a valuable model organism for studying aging due to its low cost, capacity to generate large populations, and ease of genetic manipulation and tissue dissection. Moreover, graph theory has been employed to understand the dynamic changes in gene expression patterns associated with aging and to investigate the interactions between aging and aging-related diseases. In this study, we have integrated these approaches to examine the patterns of gene co-expression in Drosophila melanogaster at various stages of development. By applying graph-theory techniques, we have identified modules of co-expressing genes, highlighting those that contain a significantly high number of mitochondrial genes. We found important mitochondrial genes involved in aging and age-related diseases in Drosophila melanogaster, including UQCR-C1, ND-B17.2, ND-20, and Pdhb. Our findings shed light on the role of mitochondrial genes in the aging process and demonstrate the utility of Drosophila melanogaster as a model organism and graph theory in aging research. Full article

(This article belongs to the Special Issue Network Medicine Approaches in Ageing Research)

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47 pages, 2822 KiB

Open AccessArticle

High Efficiency Third-Harmonic Generation in a Medium with Quadratic Susceptibility Due to Cubic-like Nonlinearity Caused by Cascaded Second-Harmonic Generation

by Vyacheslav A. Trofimov, Dmitry M. Kharitonov, Mikhail V. Fedotov, Yongqiang Yang, Di Wang and Zhiheng Tai

Appl. Sci. 2023, 13(12), 7341; https://doi.org/10.3390/app13127341 - 20 Jun 2023

Cited by 2 | Viewed by 1533

Abstract

Third-harmonic generation (THG) is of interest for its various applications. We propose using the cascaded second-harmonic generation (SHG) to implement the frequency conversion process, which is similar to that occurring in a medium with cubic susceptibility. Physically, the process is based on consecutive [...] Read more.

Third-harmonic generation (THG) is of interest for its various applications. We propose using the cascaded second-harmonic generation (SHG) to implement the frequency conversion process, which is similar to that occurring in a medium with cubic susceptibility. Physically, the process is based on consecutive generation of the second-harmonic and the sum frequency in the same crystal with quadratic susceptibility at large phase mismatching between the fundamental wave and the second-harmonic wave. In this case, at phase matching between the fundamental wave and the third-harmonic wave, THG occurs with high efficiency. To demonstrate such a possibility theoretically, we apply the multi-scale method to a set of Schrödinger equations, describing a three-wave interaction with the frequencies

ω, 2 ω

and

3 ω

in a medium with quadratic susceptibility, to derive modified equations describing the frequency tripling process. These equations are solved without using the fundamental wave energy non-depletion approximation. A THG efficiency equal to

94.5 %

is predicted theoretically. The analytical solution is confirmed by computer simulation results. We study how various factors, such as the incident pulse intensity, phase mismatching between interacting waves, group velocity mismatching of the pulses, and second-order dispersion of the wave packets influence the THG process. Full article

(This article belongs to the Section Optics and Lasers)

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11 pages, 1980 KiB

Open AccessArticle

Damage Characteristics and Energy Evolution of Bituminous Sandstones under Different Cyclic Amplitudes

by Xiaoyu Lu, Ruipeng Qin, Chunliang Dong and Chaotao Fan

Appl. Sci. 2023, 13(12), 7340; https://doi.org/10.3390/app13127340 - 20 Jun 2023

Cited by 1 | Viewed by 1125

Abstract

In many underground engineering projects, rocks are often subjected to cyclic loading and unloading, such as repeated excavation of roadway surrounding rock, which will lead to damage to underground rocks, and the energy of rocks also changes. Therefore, to study the energy evolution [...] Read more.

In many underground engineering projects, rocks are often subjected to cyclic loading and unloading, such as repeated excavation of roadway surrounding rock, which will lead to damage to underground rocks, and the energy of rocks also changes. Therefore, to study the energy evolution and damage characteristics of rocks under cyclic loading and unloading, different cyclic loading and unloading tests of bituminous sandstones under constant amplitude were conducted. Under cyclic loading and unloading, the lower limit stress was 40% of the rock peak intensity, the cyclic amplitude was 20–40% of the peak intensity, and the number of loading–unloading cycles was 10–30. The quantitative characterization of the damage degrees of bituminous sandstone was realized by the ultrasonic wave velocity and elasticity modulus methods. The energy evolution and damage characteristics of bituminous sandstone under different amplitudes and number of loading–unloading cycles were investigated through the energy dissipation method. Results showed that under cyclic loading and unloading, the ultrasonic wave velocity and elasticity modulus of bituminous sandstone decreased gradually; The damage variable shows a trend of rapid and then stable growth and has a power function relationship with the number of cycles; The input energy density and dissipation energy density curves were in L-shaped distribution, whereas the elastic energy density remained stable. The results of this study can provide some theoretical references to underground engineering construction. Full article

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24 pages, 919 KiB

Open AccessArticle

An Improvement to the 2-Opt Heuristic Algorithm for Approximation of Optimal TSP Tour

by Fakhar Uddin, Naveed Riaz, Abdul Manan, Imran Mahmood, Oh-Young Song, Arif Jamal Malik and Aaqif Afzaal Abbasi

Appl. Sci. 2023, 13(12), 7339; https://doi.org/10.3390/app13127339 - 20 Jun 2023

Cited by 10 | Viewed by 6593

Abstract

The travelling salesman problem (TSP) is perhaps the most researched problem in the field of Computer Science and Operations. It is a known NP-hard problem and has significant practical applications in a variety of areas, such as logistics, planning, and scheduling. Route optimisation [...] Read more.

The travelling salesman problem (TSP) is perhaps the most researched problem in the field of Computer Science and Operations. It is a known NP-hard problem and has significant practical applications in a variety of areas, such as logistics, planning, and scheduling. Route optimisation not only improves the overall profitability of a logistic centre but also reduces greenhouse gas emissions by minimising the distance travelled. In this article, we propose a simple and improved heuristic algorithm named 2-Opt++, which solves symmetric TSP problems using an enhanced 2-Opt local search technique, to generate better results. As with 2-Opt, our proposed method can also be applied to the Vehicle Routing Problem (VRP), with minor modifications. We have compared our technique with six existing algorithms, namely ruin and recreate, nearest neighbour, genetic algorithm, simulated annealing, Tabu search, and ant colony optimisation. Furthermore, to allow for the complexity of larger TSP instances, we have used a graph compression/candidate list technique that helps in reducing the computational complexity and time. The comprehensive empirical evaluation carried out for this research work shows the efficacy of the 2-Opt++ algorithm as it outperforms the other well-known algorithms in terms of the error margin, execution time, and time of convergence. Full article

(This article belongs to the Special Issue Technologies, Algorithms and Applications for Planning, Scheduling and Optimization)

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16 pages, 4818 KiB

Open AccessArticle

Concrete Composites Based on Quaternary Blended Cements with a Reduced Width of Initial Microcracks

by Grzegorz Ludwik Golewski

Appl. Sci. 2023, 13(12), 7338; https://doi.org/10.3390/app13127338 - 20 Jun 2023

Cited by 71 | Viewed by 2091

Abstract

This article is devoted to the study of the combined effect of siliceous fly ash (FA), silica fume (SF), and nanosilica (nS) on the cement matrix morphology and size of microcracks occurring in the Interfacial Transition Zone (ITZ) between the coarse aggregate and [...] Read more.

This article is devoted to the study of the combined effect of siliceous fly ash (FA), silica fume (SF), and nanosilica (nS) on the cement matrix morphology and size of microcracks occurring in the Interfacial Transition Zone (ITZ) between the coarse aggregate and the cement paste of concrete composites based on ordinary Portland cement (OPC). The manuscript contains analyses of width of microcracks (Wc) occurring in the ITZ area of concretes based on quaternary blended cements and changes in ITZ morphology in the concretes in question. Experiments were planned for four types of concrete. Three of them were composites based on quaternary blended cements (QBC), while the fourth was reference concrete (REF). Based on the observations of the matrices of individual composites, it was found that the REF concrete was characterized by the most heterogeneous structure. However, substitution of part of the cement binder with active pozzolanic additives resulted in a more compact and homogenous structure of the cement matrix in each of the QBC series concretes. Moreover, when analyzing the average Wc values, it should be stated that the modification of the basic structure of the cement matrix present in the REF concrete resulted in a significant reduction of the analyzed parameter in all concretes of the QBC series. For QBC-1, QBC-2, and QBC-3, the Wc values were 0.70 μm, 0.59 μm, and 0.79 μm, respectively, indicating a decrease of 38%, almost 48%, and 30%, respectively, compared with the working condition of concrete without additives. On the basis of the above results, it can therefore be concluded that the proposed modification of the binder composition in the analyzed materials clearly leads to homogenization of the composite structure and limitation of initial internal damages in concrete. Full article

(This article belongs to the Special Issue Improvement of Composite Components Performances according to Damage Tolerant Design Philosophies)

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14 pages, 25104 KiB

Open AccessFeature PaperArticle

Effect of Initial Grain Size on Microstructure and Mechanical Properties of In Situ Hybrid Aluminium Nanocomposites Fabricated by Friction Stir Processing

by Ghasem Azimiroeen, Seyed Farshid Kashani-Bozorg, Martin Nosko and Saeid Lotfian

Appl. Sci. 2023, 13(12), 7337; https://doi.org/10.3390/app13127337 - 20 Jun 2023

Cited by 2 | Viewed by 1293

Abstract

Friction stir processing (FSP) offers a unique opportunity to tailor the microstructure and improve the mechanical properties due to the combination of extensive strains, high temperatures, and high-strain rates inherent to the process. Reactive friction stir processing was carried out in order to [...] Read more.

Friction stir processing (FSP) offers a unique opportunity to tailor the microstructure and improve the mechanical properties due to the combination of extensive strains, high temperatures, and high-strain rates inherent to the process. Reactive friction stir processing was carried out in order to produce in situ Al/(Al₁₃Fe₄ + Al₂O₃) hybrid nanocomposites on wrought/as-annealed (673 K) AA1050 substrate. The active mixture of pre-ball milled Fe₂O₃ + Al powder was introduced into the stir zone by pre-placing it on the substrate. Microstructural characterisation showed that the Al₁₃Fe₄ and Al₂O₃ formed as the reaction products in a matrix of the dynamically restored aluminium matrix. The aluminium matrix means grain size was found to decrease markedly to 3.4 and 2 μm from ~55 μm and 40–50 μm after FSP using wrought and as-annealed substrates employing electron backscattered diffraction detectors, respectively. In addition, tensile testing results were indicative that the fabricated surface nanocomposite on the as-annealed substrate offered a greater ultimate tensile strength (~160 MPa) and hardness (73 HV) than those (146 MPa, and 60 HV) of the nanocomposite formed on the wrought substrate. Full article

(This article belongs to the Special Issue Deformation and Fracture Mechanics Analysis of Composite Materials)

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18 pages, 732 KiB

Open AccessArticle

A Decomposition Algorithm for Dynamic Car Sequencing Problems with Buffers

by Haida Zhang and Wensi Ding

Appl. Sci. 2023, 13(12), 7336; https://doi.org/10.3390/app13127336 - 20 Jun 2023

Cited by 2 | Viewed by 1392

Abstract

In this paper, we research the dynamic car sequencing problem with car body buffer (DCSPwB) in automotive mixed-flow assembly. The objective is to reorder the sequence of cars in the paint shop using the post-painted body buffers to minimize the violation of constraint [...] Read more.

In this paper, we research the dynamic car sequencing problem with car body buffer (DCSPwB) in automotive mixed-flow assembly. The objective is to reorder the sequence of cars in the paint shop using the post-painted body buffers to minimize the violation of constraint rules and the time cost of sequencing in the general assembly shop. We establish a mathematical model of DCSPwB and propose a decomposition-based algorithm based on the dynamic genetic algorithm (DGA) and greedy algorithm for delayed car release (PGDA). Experiments are conducted based on production orders from actual companies, and the results are compared with the solution results of the underlying genetic algorithm (GA) and greedy algorithm (GDA) to verify the effectiveness of the algorithm. In addition, the effect of buffer capacity on DCSPwB is investigated. Full article

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17 pages, 1553 KiB

Open AccessArticle

Detecting Underwater Concrete Cracks with Machine Learning: A Clear Vision of a Murky Problem

by Ugnė Orinaitė, Viltė Karaliūtė, Mayur Pal and Minvydas Ragulskis

Appl. Sci. 2023, 13(12), 7335; https://doi.org/10.3390/app13127335 - 20 Jun 2023

Cited by 5 | Viewed by 3116

Abstract

This paper presents the development of an underwater crack detection system for structural integrity assessment of submerged structures, such as offshore oil and gas installations, underwater pipelines, underwater foundations for bridges, dams, etc. Our focus is on the use of machine-learning-based approaches. First, [...] Read more.

This paper presents the development of an underwater crack detection system for structural integrity assessment of submerged structures, such as offshore oil and gas installations, underwater pipelines, underwater foundations for bridges, dams, etc. Our focus is on the use of machine-learning-based approaches. First, a detailed literature review of the state of the current methods for underwater surface crack detection is presented, highlighting challenges and opportunities. An overview of the image augmentation approach for the creation of underwater optical effects is also presented. Experimental results using a standard network-based machine learning approach, which is used for surface crack detection in onshore environments, are presented. A series of test cases is presented in which existing networks’ performance is improved using augmented images for underwater conditions. The effectiveness and accuracy of the proposed approach in detecting cracks in underwater concrete structures are demonstrated. The proposed approach has the potential to improve the safety and reliability of underwater structures and prevent catastrophic failures. Full article

(This article belongs to the Special Issue Visual Inspection Using Machine Learning and Artificial Intelligence)

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12 pages, 2437 KiB

Open AccessArticle

Clustering of LMS Use Strategies with Autoencoders

by María J. Verdú, Luisa M. Regueras, Juan P. de Castro and Elena Verdú

Appl. Sci. 2023, 13(12), 7334; https://doi.org/10.3390/app13127334 - 20 Jun 2023

Viewed by 2423

Abstract

Learning Management Systems provide teachers with many functionalities to offer materials to students, interact with them and manage their courses. Recognizing teachers’ instructing styles from their course designs would allow recommendations and best practices to be made. We propose a method that determines [...] Read more.

Learning Management Systems provide teachers with many functionalities to offer materials to students, interact with them and manage their courses. Recognizing teachers’ instructing styles from their course designs would allow recommendations and best practices to be made. We propose a method that determines teaching style in an unsupervised way from the course structure and use patterns. We define a course classification approach based on deep learning and clustering. We first use an autoencoder to reduce the dimensionality of the input data, while extracting the most important characteristics; thus, we obtain a latent representation of the courses. We then apply clustering techniques to the latent data to group courses based on their use patterns. The results show that this technique improves the clustering performance while avoiding the manual data pre-processing work. Furthermore, the obtained model defines seven course typologies that are clearly related to different use patterns of Learning Management Systems. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

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17 pages, 7032 KiB

Open AccessArticle

Evaluation of Dynamic Properties of Trees Subjected to Induced Vibrations

by Ernesto Grande, Ersilia Giordano and Francesco Clementi

Appl. Sci. 2023, 13(12), 7333; https://doi.org/10.3390/app13127333 - 20 Jun 2023

Cited by 3 | Viewed by 1184

Abstract

The preservation of trees in urban and archeological areas is a theme of particular relevance. Modern systems of monitoring, together with approaches for deriving the main characteristics of trees influencing their response toward extreme events, are nowadays at the basis of a growing [...] Read more.

The preservation of trees in urban and archeological areas is a theme of particular relevance. Modern systems of monitoring, together with approaches for deriving the main characteristics of trees influencing their response toward extreme events, are nowadays at the basis of a growing number of studies. The aim of the present paper is the dynamic identification of trees carried out by employing an approach which combines a simple data-acquisition system, direct and ambient sources of excitation, and different data-processing methods. In particular, using a single accelerometer placed at different sections of the trunk and considering excitations induced by either pulling tests or ambient vibrations, the derivation of the main frequencies and levels of modal damping characterizing the dynamic response of a sour cherry tree (Prunus cerasus) is carried out. A finite element model of the tree is also carried out to support the validation of the proposed approach and further analyze the derived outcomes. The obtained results underline the feasibility of the proposed approach in deriving information useful for assessing the behavior of trees toward dynamic actions and, consequently, of particular relevance for the identification of possible damages induced by variations in terms of dynamic characteristics (frequencies) and damping. Full article

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30 pages, 11851 KiB

Open AccessArticle

Load Forecasting Based on LVMD-DBFCM Load Curve Clustering and the CNN-IVIA-BLSTM Model

by Linjing Hu, Jiachen Wang, Zhaoze Guo and Tengda Zheng

Appl. Sci. 2023, 13(12), 7332; https://doi.org/10.3390/app13127332 - 20 Jun 2023

Cited by 3 | Viewed by 1643

Abstract

Power load forecasting plays an important role in power systems, and the accuracy of load forecasting is of vital importance to power system planning as well as economic efficiency. Power load data are nonsmooth, nonlinear time-series and “noisy” data. Traditional load forecasting has [...] Read more.

Power load forecasting plays an important role in power systems, and the accuracy of load forecasting is of vital importance to power system planning as well as economic efficiency. Power load data are nonsmooth, nonlinear time-series and “noisy” data. Traditional load forecasting has low accuracy and curves not fitting the load variation. It is not well predicted by a single forecasting model. In this paper, we propose a novel model based on the combination of data mining and deep learning to improve the prediction accuracy. First, data preprocessing is performed. Second, identification and correction of anomalous data, normalization of continuous sequences, and one-hot encoding of discrete sequences are performed. The load data are decomposed and denoised using the double decomposition modal (LVMD) strategy, the load curves are clustered using the double weighted fuzzy C-means (DBFCM) algorithm, and the typical curves obtained are used as load patterns. In addition, data feature analysis is performed. A convolutional neural network (CNN) is used to extract data features. A bidirectional long short-term memory (BLSTM) network is used for prediction, in which the number of hidden layer neurons, the number of training epochs, the learning rate, the regularization coefficient, and other relevant parameters in the BLSTM network are optimized using the influenza virus immunity optimization algorithm (IVIA). Finally, the historical data of City H from 1 January 2016 to 31 December 2018, are used for load forecasting. The experimental results show that the novel model based on LVMD-DBFCM load c1urve clustering combined with CNN-IVIA-BLSTM proposed in this paper has an error of only 2% for electric load forecasting. Full article

(This article belongs to the Topic Soft Computing)

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13 pages, 280 KiB

Open AccessReview

Diagnostic Protocol, Outcomes and Future Perspectives of the Vesical Imaging-Reporting and Data Systems (VI-RADS), a Narrative Review

by Luigi Napolitano, Simona Ippoliti, Peter Fletcher, Martina Caruso, Luigi Cirillo, Roberto Miano, Enrico Finazzi Agrò, Roberto La Rocca, Ferdinando Fusco, Davide Arcaniolo and Luca Orecchia

Appl. Sci. 2023, 13(12), 7331; https://doi.org/10.3390/app13127331 - 20 Jun 2023

Viewed by 1376

Abstract

Bladder cancer (BC) is common worldwide, and has aggressive features and high rates of relapse despite treatments. Approximately 30% of patients present with muscle invasive disease, and therefore, high risk of metastasis. This review provides an overview of the state of the art [...] Read more.

Bladder cancer (BC) is common worldwide, and has aggressive features and high rates of relapse despite treatments. Approximately 30% of patients present with muscle invasive disease, and therefore, high risk of metastasis. This review provides an overview of the state of the art for the ‘Vesical Imaging Reporting and Data System’ (VI-RADS). This scoring system presents a tool for the local staging of BC and has been validated across several institutions. We discuss the current application and the potential future clinical implications of VI-RADS in BC diagnosis, management and follow-up. Full article

(This article belongs to the Special Issue Novel Advances in the Diagnosis, Treatment and Prognosis of Urological Diseases)

15 pages, 3842 KiB

Open AccessArticle

Rail Surface Defect Detection Based on An Improved YOLOv5s

by Hui Luo, Lianming Cai and Chenbiao Li

Appl. Sci. 2023, 13(12), 7330; https://doi.org/10.3390/app13127330 - 20 Jun 2023

Cited by 11 | Viewed by 2266

Abstract

As the operational time of the railway increases, rail surfaces undergo irreversible defects. Once the defects occur, it is easy for them to develop rapidly, which seriously threatens the safe operation of trains. Therefore, the accurate and rapid detection of rail surface defects [...] Read more.

As the operational time of the railway increases, rail surfaces undergo irreversible defects. Once the defects occur, it is easy for them to develop rapidly, which seriously threatens the safe operation of trains. Therefore, the accurate and rapid detection of rail surface defects is very important. However, in the detection of rail surface defects, there are problems, such as low contrast between defects and the background, large scale differences, and insufficient training samples. Therefore, we propose a rail surface defect detection method based on an improved YOLOv5s in this paper. Firstly, the sample dataset of rail surface defect images was augmented with flip transformations, random cropping, and brightness transformations. Next, a Conv2D and Dilated Convolution(CDConv) module was designed to reduce the amount of network computation. In addition, the Swin Transformer was combined with the Backbone and Neck ends to improve the C3 module of the original network. Then, the global attention mechanism (GAM) was introduced into PANet to form a new prediction head, namely Swin transformer and GAM Prediction Head (SGPH). Finally, we used the Soft-SIoUNMS loss to replace the original CIoU loss, which accelerates the convergence speed of the algorithm and reduces regression errors. The experimental results show that the improved YOLOv5s detection algorithm reaches 96.9% in the average precision of rail surface defect detection, offering the accurate and rapid detection of rail surface defects, which has certain engineering application value. Full article

(This article belongs to the Special Issue Deep Learning for Object Detection)

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20 pages, 10282 KiB

Open AccessArticle

Experimental Investigation of the Effect of Delay Time on Rock Fragmentation in Multi-Hole Bench Blasting

by Hong-Liang Tang, Jun Yang and Qi Yu

Appl. Sci. 2023, 13(12), 7329; https://doi.org/10.3390/app13127329 - 20 Jun 2023

Cited by 2 | Viewed by 1880

Abstract

Rock fragmentation by blasting influences ore recovery and the cost of downstream operations. The development of electronic detonators makes it possible to improve fragmentation by controlling the initiation timing in blasting projects, and the effect of the mechanism of delay timing on rock [...] Read more.

Rock fragmentation by blasting influences ore recovery and the cost of downstream operations. The development of electronic detonators makes it possible to improve fragmentation by controlling the initiation timing in blasting projects, and the effect of the mechanism of delay timing on rock fragmentation should be studied. Fragmentation of granite bench specimens with different initiation timing was investigated in blast experiments. Conclusions are obtained by studying the surface strain field and post-blast specimens. A total of six blasting tests were carried out on granite bench specimens with four boreholes each having a diameter of 10 mm and a length of 450 mm. Each borehole used pentaerythritol tetranitrate (PETN) as the explosive charge, which was approximately 4.84 g with a charge diameter of 5.5 mm. Delay times between adjacent boreholes in the same row were set as 0, 50, 100, 150, 200, and 250 µs. The surface strain field of the bench specimen under blast loading was analyzed using three-dimensional digital image correlation (3D-DIC) techniques based on two cameras that captured high-speed images. Additionally, the post-blast specimen was also observed and recorded. Fragments of each bench specimen were carefully collected, weighed, and sieved with a set of sieves, including very fine particles. According to the 3D-DIC analysis for bench specimens, the propagation pattern of the main strain concentration zone transformed from horizontal to vertical with the increase in inter-hole delay. The maximum blast excavation weight was obtained by the bench specimen with an inter-hole delay of 100 µs, while the bench specimen with the longest inter-hole delay (250 µs) obtained the minimum blast excavation weight. By combining the results for blast excavation weight with the results from fragment size distribution analysis of all specimens, the optimal inter-hole delay was 200 µs. Compared to simultaneous detonation, the median size was decreased by about 14.5% for the inter-hole delay of 200 µs. The results of experiments show that delay time significantly influences rock fragmentation, but the stress wave superposition in short delays cannot improve rock fragmentation. For long delays, the blast-induced crack propagation time should be regarded as an influential factor when choosing the proper delay time. The experimental findings of this study could provide a better understanding of the effect of the mechanism of delay time on rock fragmentation. Full article

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21 pages, 7485 KiB

Open AccessArticle

Machine Learning Algorithms for Raw and Unbalanced Intrusion Detection Data in a Multi-Class Classification Problem

by Mantas Bacevicius and Agne Paulauskaite-Taraseviciene

Appl. Sci. 2023, 13(12), 7328; https://doi.org/10.3390/app13127328 - 20 Jun 2023

Cited by 11 | Viewed by 2787

Abstract

Various machine learning algorithms have been applied to network intrusion classification problems, including both binary and multi-class classifications. Despite the existence of numerous studies involving unbalanced network intrusion datasets, such as CIC-IDS2017, a prevalent approach is to address the issue by either merging [...] Read more.

Various machine learning algorithms have been applied to network intrusion classification problems, including both binary and multi-class classifications. Despite the existence of numerous studies involving unbalanced network intrusion datasets, such as CIC-IDS2017, a prevalent approach is to address the issue by either merging the classes to optimize their numbers or retaining only the most dominant ones. However, there is no consistent trend showing that accuracy always decreases as the number of classes increases. Furthermore, it is essential for cybersecurity practitioners to recognize the specific type of attack and comprehend the causal factors that contribute to the resulting outcomes. This study focuses on tackling the challenges associated with evaluating the performance of multi-class classification for network intrusions using highly imbalanced raw data that encompasses the CIC-IDS2017 and CSE-CIC-IDS2018 datasets. The research concentrates on investigating diverse machine learning (ML) models, including Logistic Regression, Random Forest, Decision Trees, CNNs, and Artificial Neural Networks. Additionally, it explores the utilization of explainable AI (XAI) methods to interpret the obtained results. The results obtained indicated that decision trees using the CART algorithm performed best on the 28-class classification task, with an average macro F1-score of 0.96878. Full article

(This article belongs to the Special Issue Advances in Cybersecurity: Challenges and Solutions)

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12 pages, 1839 KiB

Open AccessArticle

In Vitro Comparison of the Fluoride Ion Release from the First- and Second-Generation Fluoride Varnishes

by Dagmara Piesiak-Panczyszyn, Adam Watras, Rafal J. Wiglusz and Maciej Dobrzynski

Appl. Sci. 2023, 13(12), 7327; https://doi.org/10.3390/app13127327 - 20 Jun 2023

Cited by 1 | Viewed by 1798

Abstract

Fluoride varnishes, both the first and the second generations, are effective in inhibiting caries, especially in children and adolescents, by reducing it on average by 43% for permanent teeth and 37% for deciduous teeth. The aim of this study was to evaluate the [...] Read more.

Fluoride varnishes, both the first and the second generations, are effective in inhibiting caries, especially in children and adolescents, by reducing it on average by 43% for permanent teeth and 37% for deciduous teeth. The aim of this study was to evaluate the dynamics of in vitro fluoride ion release from first- (Duraphat) and second-generation (MI Varnish and Embrace Varnish) fluoride varnishes and the impact of the type of varnish, the time from its application and the pH of the environment on this process. Materials and methods: The test material (90 specimens), prepared from extracted human teeth, were divided into nine groups of 10 specimens each. Measured amounts of the examined varnishes were applied onto specimens and the levels of fluoride release were assessed at the baseline and after 1, 2, 24, 48 and 168 h from the application with the use of an ion-specific electrode. The specimens were immersed into artificial saliva with pH adjusted to 4, 5 and 7. The highest cumulative release of fluoride was obtained by MI Varnish (11.52 ppm/mg), regardless of the pH of the environment, whereas the lowest released fluoride concentration was achieved by Embrace Varnish (4.82 ppm/mg). In the acidic environment, the release of fluoride was significantly higher than in the neutral environment for all investigated varnishes, with no change in the overall fluoride release profile and with maximum fluoride release in the first two hours after application. The findings of this study indicate that all examined fluoride varnishes released the maximum amount of fluoride within the first hours after application and that it was related to the acidity of the immersion medium. Full article

(This article belongs to the Section Materials Science and Engineering)

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22 pages, 3394 KiB

Open AccessArticle

Temporal Variations Dataset for Indoor Environmental Parameters in Northern Saudi Arabia

by Talal Alshammari, Rabie A. Ramadan and Aakash Ahmad

Appl. Sci. 2023, 13(12), 7326; https://doi.org/10.3390/app13127326 - 20 Jun 2023

Cited by 4 | Viewed by 1951

Abstract

The advancement of the Internet of Things applications (technologies and enabling platforms), consisting of software and hardware (e.g., sensors, actuators, etc.), allows healthcare providers and users to analyze and measure physical environments at home or hospital. The measured physical environment parameters contribute to [...] Read more.

The advancement of the Internet of Things applications (technologies and enabling platforms), consisting of software and hardware (e.g., sensors, actuators, etc.), allows healthcare providers and users to analyze and measure physical environments at home or hospital. The measured physical environment parameters contribute to improving healthcare in real time. Researchers in this domain require existing representative datasets to develop machine-learning techniques to learn physical variables from the surrounding environments. The available environmental datasets are rare and need too much effort to be generated. To our knowledge, it has been noticed that no datasets are available for some countries, including Saudi Arabia. Therefore, this paper presents one of the first environmental data generated in Saudi Arabia’s environment. The advantage of this dataset is to encourage researchers to investigate the effectiveness of machine learning in such an environment. The collected data will also help utilize the machine learning and deep learning algorithms in smart home and health care applications based on the Saudi Arabia environment. Saudi Arabia has a special environment in each session, especially in the northern area where we work, where it is too hot in the summer and cold in the winter. Therefore, environmental data measurements in both sessions are important for the research community, especially those working in smart and healthcare environments. The dataset is generated based on the indoor environment from six sensors (timestamps, light, temperature, humidity, pressure, and altitude sensors). The room data were collected for 31 days in July 2022, acquiring 8910 records. The datasets include six columns of different data types that represent sensor values. During the experiment, the sensors captured the data every 5 min, storing them in a comma-separated value file. The data are already validated and publicly available at PLOMS Press and can be applied for training, testing, and validating machine learning algorithms. This is the first dataset developed by the authors for the research community for such an environment, and other datasets will follow it in different environments and places. Full article

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16 pages, 10378 KiB

Open AccessArticle

Aerodynamic Characteristics Analysis of Rectifier Drum of High-Speed Train Environmental Monitoring Devices

by Baowang Li, Xiaobing Wang, Junqiang Wu, Yang Tao and Neng Xiong

Appl. Sci. 2023, 13(12), 7325; https://doi.org/10.3390/app13127325 - 20 Jun 2023

Viewed by 1135

Abstract

To study the aerodynamic characteristics of the convex structure of a surface-monitoring device on a high-speed train and to evaluate its impact on the aerodynamic performance of the high-speed train, numerical simulation research was conducted on three different layouts of the monitoring device. [...] Read more.

To study the aerodynamic characteristics of the convex structure of a surface-monitoring device on a high-speed train and to evaluate its impact on the aerodynamic performance of the high-speed train, numerical simulation research was conducted on three different layouts of the monitoring device. The computational fluid dynamics (CFD) method was used for the simulation study, and the unsteady compressible NS equation was used as the control equation. Hexagonal grid technology was used to reduce the demand for the grid quantity. The rationality of the grid size and layout was verified through grid independence research. To increase the accuracy of the numerical simulation, the γ-Re_θ transition model and improved delayed detached eddy simulation (IDDES) method were coupled for the simulation research. The aerodynamic characteristics of the different operation directions and configurations were compared and analyzed. The research results showed that the windward side of the single pantograph detection device experienced positive pressure, and the sideline and leeward sides experienced negative pressure. Increasing the fillet radius of the sideline could appropriately reduce the aerodynamic resistance. When the speed was about 110 m/s, the drag force coefficient of the detection device was 210~410 N, and the lateral force was small, which means that it had little impact on the overall aerodynamic force of the train. According to the results of the unsteady analysis of the layout with a large space, the resistance during forward travel was greater than that during negative travel. The streamlined upwind surface was conducive to reducing the scope of the leeward separation zone and the amplitude of the pressure fluctuation in the leeward zone, and it thus reduced the resistance. For the running trains, a vortex was formed on their leeward surface. The pressure monitoring results showed that the separated airflow had no dominant frequency or energy peak. The possibility of the following train top and other components experiencing resonance damage is low. Full article

(This article belongs to the Topic Fluid Mechanics)

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22 pages, 5762 KiB

Open AccessArticle

Noncovalent Adsorption of Single-Stranded and Double-Stranded DNA on the Surface of Gold Nanoparticles

by Ekaterina A. Gorbunova, Anna V. Epanchintseva, Dmitrii V. Pyshnyi and Inna A. Pyshnaya

Appl. Sci. 2023, 13(12), 7324; https://doi.org/10.3390/app13127324 - 20 Jun 2023

Cited by 2 | Viewed by 1690

Abstract

Understanding the patterns of noncovalent adsorption of double-stranded nucleic acids (dsDNA) on gold nanoparticles (GNPs) was the aim of this study. It was found that the high-affinity motifs in DNA can and do act as an “anchor” for the fixation of the whole [...] Read more.

Understanding the patterns of noncovalent adsorption of double-stranded nucleic acids (dsDNA) on gold nanoparticles (GNPs) was the aim of this study. It was found that the high-affinity motifs in DNA can and do act as an “anchor” for the fixation of the whole molecule on the GNP (up to 98 ± 2 single-stranded (ss)DNA molecules per particle with diameter of 13 ± 2 nm). At the same time, the involvement of an “anchor” in the intramolecular DNA interaction can negatively affect the efficiency of the formation of ss(ds)DNA–GNP structures. It has been shown that the interaction of GNP with DNA duplexes is accompanied by their dissociation and competitive adsorption of ssDNAs on GNP, wherein the crucial factor of DNA adsorption efficiency is the intrinsic affinity of ssDNA to GNP. We propose a detailed scheme for the interaction of dsDNA with GNPs, which should be taken into account in studies of this type. Researchers focused on this field should accept the complicated nature of such objects and take into account the many competing processes, including the processes of adsorption and desorption of DNA on gold as well as the formation of secondary structures by individual DNA strands. Full article

(This article belongs to the Special Issue Novel Nanomaterials and Nanostructures)

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11 pages, 1247 KiB

Open AccessArticle

Kinetic and Kinematic Analysis of Gait Termination: A Comparison between Planned and Unplanned Conditions

by Chae-Won Kwon, Seong-Ho Yun, Dong-Kyun Koo and Jung-Won Kwon

Appl. Sci. 2023, 13(12), 7323; https://doi.org/10.3390/app13127323 - 20 Jun 2023

Cited by 3 | Viewed by 1600

Abstract

Purpose: Gait termination (GT) is the transition from steady-state walking to a complete stop, occurring under planned gait termination (PGT) or unplanned gait termination (UGT) conditions. This study aimed to investigate the biomechanical differences between PGT and UGT, which could help develop therapeutic [...] Read more.

Purpose: Gait termination (GT) is the transition from steady-state walking to a complete stop, occurring under planned gait termination (PGT) or unplanned gait termination (UGT) conditions. This study aimed to investigate the biomechanical differences between PGT and UGT, which could help develop therapeutic interventions for individuals experiencing difficulty with GT. Methods: Twenty healthy adults performed three walking trials, followed by PGT and UGT trials. Gait termination was analyzed in three phases as follows: Phase 1 (pre-stopping), Phase 2 (initial stopping phase), and Phase 3 (terminal stopping phase). Spatiotemporal, kinematic, and kinetic data during each phase were compared between conditions. Results: The GT time and GT step length were significantly different between the PGT and UGT trials. Ankle range of motion (ROM) demonstrated significant differences in Phase 1, with the PGT having a slightly lower ankle ROM than the UGT. In Phase 2, the hip, knee, and ankle ROM exhibited significant differences between the conditions. Finally, in Phase 3, UGT showed reduced hip ROM but increased knee ROM and kinetic parameters compared to PGT. Conclusion: Our results indicate that the ankle joint primarily contributes to deceleration during the initial preparation for generating braking force during PGT. Conversely, UGT reveals disrupted kinesthetic control due to instability, leading to a preference for a hip and knee strategy to absorb force and control the center of mass for a safe and rapid GT in response to unexpected stimuli. These findings provide valuable insights into the biomechanical mechanisms underlying body stability during GT and may contribute to the development of effective rehabilitation strategies for individuals with gait impairment. Full article

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29 pages, 3771 KiB

Open AccessArticle

Sample-Pair Envelope Diamond Autoencoder Ensemble Algorithm for Chronic Disease Recognition

by Yi Zhang, Jie Ma, Xiaolin Qin, Yongming Li and Zuwei Zhang

Appl. Sci. 2023, 13(12), 7322; https://doi.org/10.3390/app13127322 - 20 Jun 2023

Cited by 1 | Viewed by 1124

Abstract

Chronic diseases are severe and life-threatening, and their accurate early diagnosis is difficult. Machine-learning-based processes of data collected from the human body using wearable sensors are a valid method currently usable for diagnosis. However, it is difficult for wearable sensor systems to obtain [...] Read more.

Chronic diseases are severe and life-threatening, and their accurate early diagnosis is difficult. Machine-learning-based processes of data collected from the human body using wearable sensors are a valid method currently usable for diagnosis. However, it is difficult for wearable sensor systems to obtain high-quality and large amounts of data to meet the demands of diagnostic accuracy. Furthermore, existing feature-learning methods do not deal with this problem well. To address the above issues, a sample-pair envelope diamond autoencoder ensemble algorithm (SP_DFsaeLA) is proposed. The proposed algorithm has four main components. Firstly, sample-pair envelope manifold neighborhood concatenation mechanism (SP_EMNCM) is designed to find pairs of samples that are close to each other in a manifold neighborhood. Secondly, the feature-embedding stacked sparse autoencoder (FESSAE) is designed to extend features. Thirdly, a staged feature reduction mechanism is designed to reduce redundancy in the extended features. Fourthly, the sample-pair-based model and single-sample-based model are combined by weighted fusion. The proposed algorithm was experimentally validated on nine datasets and compared with the latest algorithm. The experimental results show that the algorithm is significantly better than existing representative algorithms and it achieves the highest improvement of 22.77%, 21.03%, 24.5%, 27.89%, and 10.65% on five criteria over the state-of-the-art methods. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Visual Signal Processing)

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18 pages, 2194 KiB

Open AccessArticle

Capture of CO₂ Using Mixed Amines and Solvent Regeneration in a Lab-Scale Continuous Bubble-Column Scrubber

by Pao-Chi Chen, Jyun-Hong Jhuang, Ting-Wei Wu, Chen-Yu Yang, Kuo-Yu Wang and Chang-Ming Chen

Appl. Sci. 2023, 13(12), 7321; https://doi.org/10.3390/app13127321 - 20 Jun 2023

Cited by 1 | Viewed by 1695

Abstract

This study used monoethanolamine (MEA) as an amine-based solvent, which was blended with secondary amines (DIPA), tertiary amines, stereo amines, and piperazine (PZ) to prepare mixed amines at the required concentrations, which were used as the test solvents. To search for the best-mixed [...] Read more.

This study used monoethanolamine (MEA) as an amine-based solvent, which was blended with secondary amines (DIPA), tertiary amines, stereo amines, and piperazine (PZ) to prepare mixed amines at the required concentrations, which were used as the test solvents. To search for the best-mixed amines, a continuous bubble-column scrubber was adopted to explore the performance of mixed solvents presented in this study. The solvent regeneration test was also carried out at different temperatures. The selected factors included the type of mixed amine (A), the ratio of mixed amines (B), the liquid feed flow (C), the gas flow rate (D), the concentration of mixed amines (E), and the liquid temperature (F), each having five levels. Using the Taguchi experimental design, the conventional experimental number could be reduced from 15,625 to 25, saving much time and cost. The absorption efficiency (E_F), absorption rate (R_A), overall mass-transfer coefficient (K_Ga), and absorption factor (ϕ) were estimated as the indicators. After the Taguchi analysis, E, D, and C were found to play important roles in the capture of CO₂ gas. Verifications of optimum conditions were found to be 100%, 19.96 × 10⁻⁴ mole/s·L, 1.2312 1/s, and 0.6891 mol-CO₂/L·mol-solvent for E_F, R_A, K_Ga, and ϕ, respectively. The evaluated indexes suggested that MEA + PZ was the best-mixed amine, followed by MEA and MEA + DIPA. The solvent regeneration tests for the scrubbed solutions performed at different optimum conditions showed that the heat of the regeneration sequence was in the order of MEA > MEA + PZ > MEA + DIPA with minimum energy required at 110 °C. The individual energy required was also analyzed here. Full article

(This article belongs to the Special Issue Applications and Challenges in Carbon Capture, Utilization and Storage)

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16 pages, 766 KiB

Open AccessArticle

A Comprehensive Framework for Industrial Sticker Information Recognition Using Advanced OCR and Object Detection Techniques

by Gabriella Monteiro, Leonardo Camelo, Gustavo Aquino, Rubens de A. Fernandes, Raimundo Gomes, André Printes, Israel Torné, Heitor Silva, Jozias Oliveira and Carlos Figueiredo

Appl. Sci. 2023, 13(12), 7320; https://doi.org/10.3390/app13127320 - 20 Jun 2023

Cited by 8 | Viewed by 2922

Abstract

Recent advancements in Artificial Intelligence (AI), deep learning (DL), and computer vision have revolutionized various industrial processes through image classification and object detection. State-of-the-art Optical Character Recognition (OCR) and object detection (OD) technologies, such as YOLO and PaddleOCR, have emerged as powerful solutions [...] Read more.

Recent advancements in Artificial Intelligence (AI), deep learning (DL), and computer vision have revolutionized various industrial processes through image classification and object detection. State-of-the-art Optical Character Recognition (OCR) and object detection (OD) technologies, such as YOLO and PaddleOCR, have emerged as powerful solutions for addressing challenges in recognizing textual and non-textual information on printed stickers. However, a well-established framework integrating these cutting-edge technologies for industrial applications still needs to be discovered. In this paper, we propose an innovative framework that combines advanced OCR and OD techniques to automate visual inspection processes in an industrial context. Our primary contribution is a comprehensive framework adept at detecting and recognizing textual and non-textual information on printed stickers within a company, harnessing the latest AI tools and technologies for sticker information recognition. Our experiments reveal an overall macro accuracy of 0.88 for sticker OCR across three distinct patterns. Furthermore, the proposed system goes beyond traditional Printed Character Recognition (PCR) by extracting supplementary information, such as barcodes and QR codes present in the image, significantly streamlining industrial workflows and minimizing manual labor demands. Full article

(This article belongs to the Special Issue Computer Vision and Pattern Recognition Based on Deep Learning)

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20 pages, 340 KiB

Open AccessReview

Exploring the Advantages and Disadvantages of a Whole Foods Approach for Elevating Dietary Nitrate Intake: Have Researchers Concentrated Too Much on Beetroot Juice?

by Alex Griffiths, Shatha Alhulaefi, Eleanor J. Hayes, Jamie Matu, Kirsten Brandt, Anthony Watson, Mario Siervo and Oliver M. Shannon

Appl. Sci. 2023, 13(12), 7319; https://doi.org/10.3390/app13127319 - 20 Jun 2023

Cited by 6 | Viewed by 2719

Abstract

In recent years, a number of studies have explored the potential salutary effects of dietary nitrate, with promising findings emerging. Indeed, numerous investigations have now demonstrated that increasing intake of dietary nitrate can reduce blood pressure, improve endothelial function, decrease platelet aggregation, increase [...] Read more.

In recent years, a number of studies have explored the potential salutary effects of dietary nitrate, with promising findings emerging. Indeed, numerous investigations have now demonstrated that increasing intake of dietary nitrate can reduce blood pressure, improve endothelial function, decrease platelet aggregation, increase cognitive function and brain perfusion, and enhance exercise performance. Most researchers have explored the health and/or performance effects of dietary nitrate by providing participants with concentrated beetroot juice, which is rich in this compound. Another strategy for increasing/optimising dietary nitrate intake, which could be embraced alongside or instead of nitrate-rich supplements in research and non-research settings, is the consumption of whole nitrate-rich vegetables. In this review, we explore the potential advantages and disadvantages of increasing consumption of various whole nitrate-rich vegetables to augment dietary nitrate intake. We compare the cost, convenience, availability, feasibility/acceptability, and efficacy of consumption of nitrate via whole nitrate-rich vegetables against concentrated beetroot juice ‘shots’ as defined supplements. We also discuss possible strategies that could be used to help individuals maximise their intake of nitrate via whole vegetables, and outline potential avenues for future research. Full article

(This article belongs to the Special Issue Potential Health Benefits of Fruits and Vegetables III)

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9 pages, 206 KiB

Open AccessConference Report

The 2nd International Symposium on New Frontiers in Reef Coral Biotechnology (12 May 2023, Taiwan)

by Chiahsin Lin

Appl. Sci. 2023, 13(12), 7318; https://doi.org/10.3390/app13127318 - 20 Jun 2023

Cited by 1 | Viewed by 1505

Abstract

For the second year in a row, the theme is “reef coral biotechnology”, specifically the interface between basic science and conservation. It has never been more important to attempt to leverage what we know about these beautiful, albeit highly imperiled and fragile, ecosystems [...] Read more.

For the second year in a row, the theme is “reef coral biotechnology”, specifically the interface between basic science and conservation. It has never been more important to attempt to leverage what we know about these beautiful, albeit highly imperiled and fragile, ecosystems towards conserving them. Our invited speakers’ areas of expertise span all levels of biological organization: from molecules within coral cells, to coral tissues, to entire coral colonies, and then up to reef-scale processes. Our goal is to promote communication not only among local Taiwanese marine biologists, but also those within Southeast Asia and farther afield; we especially encourage participation from early-career researchers, including Master’s students, PhD candidates, and post-doctoral researchers. It is our hope that the presentations (and the discussions that follow) will encourage collaboration. As importantly, we envision that the tools and approaches shared amongst us can be tapped into to expedite our collective efforts to better understand, manage, and conserve coral reefs. Full article

(This article belongs to the Special Issue New Frontiers in Reef Coral Biotechnology)

14 pages, 5038 KiB

Open AccessArticle

Temperature-Controlled Hyperthermia with Non-Invasive Temperature Monitoring through Speed of Sound Imaging

by Haoyang Wang, Yuchen Sun, Yuxin Wang, Ying Chen, Yun Ge, Jie Yuan and Paul Carson

Appl. Sci. 2023, 13(12), 7317; https://doi.org/10.3390/app13127317 - 20 Jun 2023

Cited by 2 | Viewed by 1680

Abstract

Hyperthermia therapy (HT) is used to treat diseases through heating of high temperature usually in conjunction with some other medical therapeutics such as chemotherapy and radiotherapy. In this study, we propose a promising temperature-controlled hyperthermia method that uses high-intensity focused ultrasound (HIFU) for [...] Read more.

Hyperthermia therapy (HT) is used to treat diseases through heating of high temperature usually in conjunction with some other medical therapeutics such as chemotherapy and radiotherapy. In this study, we propose a promising temperature-controlled hyperthermia method that uses high-intensity focused ultrasound (HIFU) for clinical tumor treatment combined with diagnostic ultrasound image guidance and non-invasive temperature monitoring through speed of sound (SOS) imaging. HIFU heating is realized by a ring ultrasound transducer array with 256 elements. In this study, tumors in the human thigh were set as heating targets. The inner structure information of thigh tissue is obtained by B-mode ultrasound imaging. Since the relationship between temperature and SOS in different human tissue is available, the temperature detection is converted to the SOS detection obtained by the full-wave inversion (FWI) method. Simulation results show that our model can achieve expected hyperthermia of constant temperature on tumor target with 0.2 °C maximum temperature fluctuation for 5 h. Through simulation, our proposed thermal therapy model achieves accurate temperature control of ±0.2 °C in human thigh tumors, which verifies the feasibility of the proposed temperature-controlled hyperthermia model. Furthermore, the temperature measurement can share the same ring ultrasound transducer array for HIFU heating and B-mode ultrasound imaging, which provides a guiding significance for clinical application. Full article

(This article belongs to the Section Biomedical Engineering)

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12 pages, 2322 KiB

Open AccessArticle

Study on Changes in Physical and Mechanical Properties and Integrity Decay of Sandstone Subjected to Freeze–Thaw Cycling

by Liping Wang, Xiaotong Chen, Wan Zhang, Yanzhe Tian and Shuanhai Xu

Appl. Sci. 2023, 13(12), 7316; https://doi.org/10.3390/app13127316 - 20 Jun 2023

Viewed by 1028

Abstract

To investigate the effects of long-term freeze–thaw cycles on the physical and mechanical properties as well as the attenuation trend of rocks, this study conducted saturated freeze–thaw tests on coarse sandstone and fine sandstone samples collected from the slopes of Muli Coal Mine [...] Read more.

To investigate the effects of long-term freeze–thaw cycles on the physical and mechanical properties as well as the attenuation trend of rocks, this study conducted saturated freeze–thaw tests on coarse sandstone and fine sandstone samples collected from the slopes of Muli Coal Mine in Qinghai Province. The samples underwent different numbers of freeze–thaw cycles, and their porosity, longitudinal wave velocity, and uniaxial compression strength were studied. The variations in the physical and mechanical properties of the two types of sandstone with respect to the number of freeze–thaw cycles were analyzed. Take uniaxial compressive strength (UCS) as the integrity index, and decay laws of rock integrity were analyzed based on the decay equation suggested in previous studies. We found that the decay index λ, which is commonly assumed to be constant, varies with the number of freeze–thaw cycles. Furthermore, the λ values varied between different rock types. For fine sandstone, the λ decreases with an increase in the number of freeze–thaw cycles, ranging from 0.00385 to 0.005. However, for coarse sandstone, the λ initially decreases and then increases with an increase in the number of freeze–thaw cycles. The range of λ for coarse sandstone is between 0.00376 and 0.00481. Finally, we established a relationship between the decay index, porosity, and longitudinal wave velocity in the fine sandstones. This relationship provides a more straightforward way to evaluate the integrity of fine sandstones subjected to different numbers of freeze–thaw cycles. Full article

(This article belongs to the Section Earth Sciences)

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