Journal Description
Applied Sciences
Applied Sciences
is an international, peer-reviewed, open access journal on all aspects of applied natural sciences published semimonthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Inspec, CAPlus / SciFinder, and other databases.
- Journal Rank: JCR - Q2 (Engineering, Multidisciplinary) / CiteScore - Q1 (General Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.9 days after submission; acceptance to publication is undertaken in 2.6 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our authors say about Applied Sciences.
- Companion journals for Applied Sciences include: Applied Nano, AppliedChem, Applied Biosciences, Virtual Worlds, Spectroscopy Journal and JETA.
Impact Factor:
2.7 (2022);
5-Year Impact Factor:
2.9 (2022)
Latest Articles
The Derivation of Vertical Damping Reduction Factors for the Design and Analysis of Structures Using Acceleration, Velocity, and Displacement Spectra
Appl. Sci. 2024, 14(11), 4348; https://doi.org/10.3390/app14114348 (registering DOI) - 21 May 2024
Abstract
Damping reduction factors (DRFs) play a vital role in the seismic design of structures. DRFs have been widely studied due to their primary importance to the lateral resistance of structures subjected to earthquakes. On the other hand, devastating earthquakes have occurred all over
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Damping reduction factors (DRFs) play a vital role in the seismic design of structures. DRFs have been widely studied due to their primary importance to the lateral resistance of structures subjected to earthquakes. On the other hand, devastating earthquakes have occurred all over the world, and recently, the Kahramanmaraş earthquakes in Turkey revealed the import of the vertical component of earthquakes and their impact on structures and infrastructures. Considering the importance of this parameter, this paper aims to develop new damping reduction factor (DRF) equations for the acceleration (DRFa), velocity (DRFv), and displacement spectra (DRFd) of the vertical components of earthquakes. For this purpose, 775 real ground motion records were selected from the Pacific Earthquake Engineering Research (PEER) strong motion database, and the vertical elastic response spectra of selected records were computed according to linear dynamic analysis. Taking the 5%-damped vertical response spectra as the target, the vertical spectral damping reduction factors (DRFa, DRFv, and DRFd) were computed for 1%, 3%, 10%, 15%, 20%, 30%, and 40% damping ratios. The effect of the earthquake magnitude, distance, and soil types on the DRFs was investigated. The results indicated that magnitude, distance, and soil type had no particular effect on the trend in the DRFs. Based on the evaluations, extensive statistical analyses were carried out, and new prediction equations were developed according to the nonlinear regression method. The developed equations were then compared to those found in the literature and seismic design codes. The comparisons proved that the proposed DRFa, DRFd, and DRFv models are strongly compatible with real DRFs and show strong robustness compared to existing models.
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(This article belongs to the Section Civil Engineering)
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The Effects of Different Stretching Techniques Used in Warm-Up on the Triggering of Post-Activation Performance Enhancement in Soccer Players
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Kemal Kurak, İsmail İlbak, Stefan Stojanović, Ramazan Bayer, Tijana Purenović-Ivanović, Tomasz Pałka, Tadeusz Ambroży, Krzysztof Kasicki, Wojciech Czarny and Łukasz Rydzik
Appl. Sci. 2024, 14(11), 4347; https://doi.org/10.3390/app14114347 (registering DOI) - 21 May 2024
Abstract
The aim of this research was to investigate the effects of different stretching techniques used during warm-up exercises prior to post-activation performance enhancement (PAPE) on the explosive lower extremity strength performance of soccer players. This cross-sectional study involved the participation of 13 male
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The aim of this research was to investigate the effects of different stretching techniques used during warm-up exercises prior to post-activation performance enhancement (PAPE) on the explosive lower extremity strength performance of soccer players. This cross-sectional study involved the participation of 13 male soccer players with an average age of 22.38 ± 1.75, body height of 174.38 ± 3.94, and body mass of 72.30 ± 4.13. To determine the participants’ maximal strength performance, one repeated maximal strength (1-RM) squat exercise was applied. The PAPE protocol was then implemented with a squat exercise consisting of three repetitions at 80% of 1-RM. The warm-up protocols consisted of 5 min of cycling, followed by dynamic stretching, static stretching, or proprioceptive neuromuscular facilitation (PNF) stretching exercises. These protocols were applied on four different days with a 72 h interval. A vertical jump test was conducted to measure the participants’ explosive strength performance. The research data were analyzed using IBM Statistics (SPSS version 26.0, Armonk, NY, USA) software. The findings of this study revealed statistically significant differences in vertical jump performance values after PAPE among participants based on the different stretching techniques used during warm-up (p = 0.00). In this context, the research concluded that dynamic stretching is the optimal stretching technique during warm-up exercises before PAPE to maximize its effects. On the other hand, static stretching was found to negatively affect performance by absorbing the PAPE effect.
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(This article belongs to the Special Issue Performance Analysis in Sport and Exercise Ⅱ)
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Design of Non-Intrusive Online Monitoring System for Traction Elevators
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Zhixing Li, Jiahui Ning and Tianhao Li
Appl. Sci. 2024, 14(11), 4346; https://doi.org/10.3390/app14114346 (registering DOI) - 21 May 2024
Abstract
With the increase in elevator usage, more and more elevator real-time monitoring equipment is being applied to the operation of elevators. Traditional elevator monitoring equipment adopts a multi-sensor decentralized installation and layout, and the monitoring accuracy is low, which directly affects the effective
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With the increase in elevator usage, more and more elevator real-time monitoring equipment is being applied to the operation of elevators. Traditional elevator monitoring equipment adopts a multi-sensor decentralized installation and layout, and the monitoring accuracy is low, which directly affects the effective alarm of the monitoring system; however, existing online monitoring systems cannot quickly alarm for faults. Aiming to solve the above problems, an elevator online monitoring system based on narrow-band Internet of Things (NB-IoT) is designed. The system is highly integrated with an STM32 main control chip, a six-axis acceleration gyroscope sensor, and an air pressure sensor to realize the edge calculation of the monitoring system. At the same time, this paper eliminates the temperature drift of the pressure sensor by using a temperature compensation algorithm and inputs the extracted characteristic parameters into the BP neural network for training to eliminate the zero drift so as to obtain the real-time height data of the elevator. The six-axis acceleration gyroscope sensor is used to calculate the posture so as to avoid the problem that a three-axis acceleration sensor or a three-axis gyroscope sensor alone cannot obtain accurate posture data. In order to further improve the monitoring accuracy, the peak-to-peak value of the signal is calculated by using a 95% confidence interval algorithm to reduce the suppression of the high-frequency components of the signal by noise and ensure that the signal has a large signal-to-noise ratio so that the obtained elevator car posture and vibration operation data are more accurate. Finally, the effectiveness of the proposed method is verified by experiments.
Full article
(This article belongs to the Topic Multi-Energy Systems, 2nd Volume)
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The Stress State before the MS 6.8 Luding Earthquake on 5 September 2022 in Sichuan, China: A Retrospective View Based on the b-Value
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Liyuan Peng, Feng Long, Min Zhao, Xiyang Ran, Di Wang, Rui Wang, Weiwei Wu and Chang He
Appl. Sci. 2024, 14(11), 4345; https://doi.org/10.3390/app14114345 (registering DOI) - 21 May 2024
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On 5 September 2022 (BJT), Luding, located in southwestern Sichuan Province, China, experienced an MS 6.8 earthquake. This earthquake occurred within the historical rupture zone of the 1786 MS 7.75 event, part of the southern section of the Xianshui He Fault
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On 5 September 2022 (BJT), Luding, located in southwestern Sichuan Province, China, experienced an MS 6.8 earthquake. This earthquake occurred within the historical rupture zone of the 1786 MS 7.75 event, part of the southern section of the Xianshui He Fault belt. Given the average 155-year recurrence interval for strong earthquakes in this area, the 236 years since the last event made this earthquake somewhat expected. However, prior to this event, we did not detect any anomalies indicating low surface b-values, which are often indicative of a high-stress state in the source area before strong earthquakes, as highlighted by numerous studies. Our research focused on the northern section of the eastern boundary of the Sichuan–Yunnan sub-block, encompassing the Xianshui He, Anning He, Zemu He, and Daliang Shan fault belts. We meticulously located earthquakes of ML ≥ 1.5 from 2009 to May 2022. The catalog was divided into two periods: 2009–2014 and 2015–May 2022. Using an AIC-constraint method, we analyzed the changes in b-values (Δb) in the latter period compared to the former. Our findings revealed a significant abnormal Δb zone (Δb < −0.3), with a radius of approximately 50 km, when ΔAIC ≥ 2 was selected. Intriguingly, the epicenter of the recent Luding MS 6.8 earthquake fell within this abnormal zone. Furthermore, we calculated the b-value cross-section for the southern section of the Xianshui He fault belt using a directory of precisely located small earthquakes. This revealed that the location, scale, and shape of the abnormally low-b-value area corresponded with the large displacement co-seismic area of the main earthquake, affirming the b-value’s effectiveness in identifying asperities. The b-value’s temporal evolution prior to the mainshock exhibited a nearly decade-long continuous decrease, signifying a long-term stress-loading process akin to that observed before many strong earthquakes. The b-value anomalies observed from different profiles before the Luding earthquake underline the necessity of a comprehensive, multi-dimensional analysis of such anomalies. Finally, our analysis indicates that nine earthquakes with MS ≥ 6.5, including the Luding MS 6.8 event, have contributed to increased Coulomb Failure Stress change (ΔCFS) in the Daofu (DF)–Kangding (KD) section of the Xianshui He fault belt and the northern section of the Anning He fault belt south of Shimian (SM), with amplitudes surpassing the 0.01 MPa threshold. This suggests the potential for strong earthquakes in these zones.
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Open AccessArticle
Cost-Effective Temperature Sensor for Monitoring the Setting Time of Concrete
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Leticia Presa Madrigal, Juan Antonio Rodríguez Rama, Domingo A. Martín Sánchez, Jorge L. Costafreda Mustelier, Miguel Ángel Sanjuán and José Luis Parra y Alfaro
Appl. Sci. 2024, 14(11), 4344; https://doi.org/10.3390/app14114344 (registering DOI) - 21 May 2024
Abstract
Concrete and Portland cement-based products are the most widely used materials in the construction industry. According to the Global Cement and Concrete Association (GCCA), 14 billion cubic meters of concrete are consumed worldwide every year. Knowledge of their properties is essential to ensure
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Concrete and Portland cement-based products are the most widely used materials in the construction industry. According to the Global Cement and Concrete Association (GCCA), 14 billion cubic meters of concrete are consumed worldwide every year. Knowledge of their properties is essential to ensure the quality of concrete products and structures. Knowing the evolution of certain parameters related to their durability makes it possible to prevent situations that affect compliance with quality requirements. Thanks to advances in IoT (Internet of Things) technologies, it is possible to know the evolution of these parameters in real time. The following work pursues the development and application of a prototype to monitor the setting time of concrete. This equipment provides real-time measurements, taking advantage of the Internet of Things (IoT) technology, allowing effective monitoring of the thermal behavior of concrete during its setting process. By measuring the temperature of the process and evaluating the resistance acquired during the setting time, we can correlate these two parameters, thus ensuring their correct evolution and allowing quick action to avoid future problems. For the development of this work, temperature measurements were made during the setting of 12 concrete specimens corresponding to four different mixtures (two types of cement with and without additives), assessed at three setting ages (28, 90, and 180 days). Through detailed experimental tests, the sensor was accurately and reliably validated, showing its ability to detect temperature changes, indicating the initial and final setting time. In addition, it was observed that the integration of the DS18B20 sensor does not compromise the structural properties of the concrete. The prototype’s cost-effectiveness, efficiency, and easy installation make it a valuable tool for construction professionals, offering an innovative solution to ensure the quality and durability of the concrete. This breakthrough could represent a significant step towards the digitalization and improvement of construction processes, with direct implications for the efficiency and sustainability of modern infrastructures.
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(This article belongs to the Special Issue Durability of Advanced Cement and Concrete Materials)
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Application Cluster Analysis as a Support form Modelling and Digitalizing the Logistics Processes in Warehousing
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Jana Kronova, Gabriela Izarikova, Peter Trebuna, Miriam Pekarcikova and Milan Filo
Appl. Sci. 2024, 14(11), 4343; https://doi.org/10.3390/app14114343 (registering DOI) - 21 May 2024
Abstract
The article deals with the application of cluster analysis in modeling in-house processes, specifically supply processes. An algorithm is designed on the theoretical basis of cluster analysis and according to the analysis of the supply processes in selected industrial companies. Specifically, the algorithm
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The article deals with the application of cluster analysis in modeling in-house processes, specifically supply processes. An algorithm is designed on the theoretical basis of cluster analysis and according to the analysis of the supply processes in selected industrial companies. Specifically, the algorithm is based on the hierarchical methods of cluster analysis, and the selected hierarchical clustering method is applicable in modeling storage systems under various production conditions in industrial companies. The methodology of clustering regarding the supply processes is subsequently experimentally verified. Based on the results of the cluster analysis, a system of organization was proposed for the analyzed warehouse in the form of 2D and 3D layout models of the warehouse.
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(This article belongs to the Special Issue Automation and Digitization in Industry: Advances and Applications)
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Simulation of a Radio-Frequency Wave Based Bacterial Biofilm Detection Method in Dairy Processing Facilities
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Ranajoy Bhattacharya, Ken Cornell and Jim Browning
Appl. Sci. 2024, 14(11), 4342; https://doi.org/10.3390/app14114342 (registering DOI) - 21 May 2024
Abstract
This paper describes the principles behind the radio-frequency (RF) sensing of bacterial biofilms in pipes and heat exchangers in a dairy processing plant using an electromagnetic simulation. Biofilm formation in dairy processing plants is a common issue where the absence of timely detection
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This paper describes the principles behind the radio-frequency (RF) sensing of bacterial biofilms in pipes and heat exchangers in a dairy processing plant using an electromagnetic simulation. Biofilm formation in dairy processing plants is a common issue where the absence of timely detection and subsequent cleaning can cause serious illness. Biofilms are known for causing health issues and cleaning requires a large volume of water and harsh chemicals. In this work, milk transportation pipes are considered circular waveguides, and pasteurizers/heat exchangers are considered resonant cavities. Simulations were carried out using the CST studio suite high-frequency solver to determine the effectiveness of the real-time RF sensing. The respective dielectric constants and loss tangents were applied to milk and biofilm. In our simulation, it was observed that a 1 µm thick layer of biofilm in a milk-filled pipe shifted the reflection coefficient of a 10.16 cm diameter stainless steel circular waveguide from 0.229 GHz to 0.19 GHz. Further sensitivity analysis revealed a shift in frequency from 0.8 GHz to 1.2 GHz for a film thickness of 5 µm to 10 µm with the highest wave reflection (S11) peak of ≈−120 dB for a 6 µm thick biofilm. A dielectric patch antenna to launch the waves into the waveguide through a dielectric window was also designed and simulated. Simulation using the antenna demonstrated a similar S11 response, where a shift in reflection coefficient from 0.229 GHz to 0.19 GHz was observed for a 1 µm thick biofilm. For the case of the resonant cavity, the same antenna approach was used to excite the modes in a 0.751 m × 0.321 m × 170 m rectangular cavity with heat exchange fins and filled with milk and biofilm. The simulated resonance frequency shifted from 1.52 GHz to 1.54 GHz, for a film thickness varying from 1 µm to 10 µm. This result demonstrated the sensitivity of the microwave detection method. Overall, these results suggest that microwave sensing has promise in the rapid, non-invasive, and real-time detection of biofilm formation in dairy processing plants.
Full article
(This article belongs to the Special Issue Design and Sensitivity Analysis for Biosensors: Latest Advances and Prospects)
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Enhancing Visual Data Security: A Novel FSM-Based Image Encryption and Decryption Methodology
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Gulmira Shakhmetova, Alibek Barlybayev, Zhanat Saukhanova, Altynbek Sharipbay, Sayat Raykul and Altay Khassenov
Appl. Sci. 2024, 14(11), 4341; https://doi.org/10.3390/app14114341 (registering DOI) - 21 May 2024
Abstract
The paper presents a comprehensive exploration of a novel image encryption and decryption methodology, leveraging finite state machines (FSM) for the secure transformation of visual data. The study meticulously evaluates the effectiveness of the proposed encryption algorithm using a diverse image dataset. The
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The paper presents a comprehensive exploration of a novel image encryption and decryption methodology, leveraging finite state machines (FSM) for the secure transformation of visual data. The study meticulously evaluates the effectiveness of the proposed encryption algorithm using a diverse image dataset. The encryption algorithm demonstrates high proficiency in obfuscating the original content of images, producing cipher images that resemble noise, thereby substantiating the encryption’s effectiveness. The robustness of the proposed methodology is further evidenced by its performance in the National Institute of Standards and Technology Statistical Test Suite (NIST STS). Such achievements highlight the algorithm’s capability to maintain the stochastic integrity of encrypted data, a critical aspect of data security and confidentiality. Histogram analysis revealed that the encryption process achieves a uniform distribution of pixel values across the encrypted images, masking any identifiable patterns and enhancing the security level. Correlation analysis corroborated the success of the encryption technique, showing a substantial reduction in the correlation among adjacent pixel values, thereby disrupting spatial relationships essential for deterring unauthorized data analysis. This improvement indicates the algorithm’s efficiency in altering pixel patterns to secure image data. Additionally, a comparative analysis of correlation coefficients using various encryption methods on the Lenna image offered insights into the relative effectiveness of different techniques, emphasizing the importance of method selection based on specific security requirements and data characteristics.
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(This article belongs to the Section Computing and Artificial Intelligence)
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Improving Anorexia Nervosa Treatment with Virtual Reality Body Exposure and Attentional Bias Modification: A Single Case Study
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Mariarca Ascione, Eduardo Serrano-Troncoso, Marta Carulla-Roig, Anna Blasco Martínez, Fernando Guerrero Álvarez, Franck-Alexandre Meschberger-Annweiler, Bruno Porras-Garcia, Marta Ferrer-Garcia and José Gutierrez-Maldonado
Appl. Sci. 2024, 14(11), 4340; https://doi.org/10.3390/app14114340 (registering DOI) - 21 May 2024
Abstract
This case study explores the potential of integrating attentional bias modification training (ABMT) with mirror exposure therapy (MET), utilizing virtual reality and eye-tracking, for a 14-year-old girl diagnosed with anorexia nervosa (AN). The ABMT-MET intervention was used alongside a standard treatment program called
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This case study explores the potential of integrating attentional bias modification training (ABMT) with mirror exposure therapy (MET), utilizing virtual reality and eye-tracking, for a 14-year-old girl diagnosed with anorexia nervosa (AN). The ABMT-MET intervention was used alongside a standard treatment program called Home Treatment (HoT), which combines cognitive behavioral therapy with family-based therapy. Though the patient began HoT with a 3-week inpatient phase, the ABMT-MET intervention specifically took place during the subsequent Home Treatment sessions. The experimental treatment, comprising five consecutive weekly sessions, was bookended by pre- and post-assessment sessions and included a six-month follow-up. During the sessions, the patient engaged in systematic and hierarchical exposure to a virtual representation of her silhouette, with gradual adjustments made to the avatar’s body mass index (BMI) toward a healthier range. ABMT sessions, conducted before each MET session, aimed to redistribute the patient’s focus evenly across her body, successfully neutralizing her initial attentional bias toward non-weight-related body parts. The patient demonstrated consistent decreases in anxiety and fear of weight gain, effectively progressing through the BMI hierarchy in the virtual setting. Post-treatment assessments indicated significant enhancements in body dissatisfaction, drive for thinness, body-checking behaviors, and body appreciation, with these gains preserved at the six-month follow-up, although the attentional bias returned to pre-treatment levels. Though the single-case design limits definitive conclusions, these findings suggest ABMT-MET may be a promising adjunct therapy for AN, requiring further research for confirmation.
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(This article belongs to the Section Computing and Artificial Intelligence)
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Exploring Vitamin D Synthesis and Function in Cardiovascular Health: A Narrative Review
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Gilda Aiello, Mauro Lombardo and Sara Baldelli
Appl. Sci. 2024, 14(11), 4339; https://doi.org/10.3390/app14114339 (registering DOI) - 21 May 2024
Abstract
Vitamin D plays a crucial role in the human body, influencing a wide range of physiological processes from bone health to immune function. The complex biochemical pathways involved in the synthesis, metabolism, and action of Vitamin D are explored, emphasizing its importance in
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Vitamin D plays a crucial role in the human body, influencing a wide range of physiological processes from bone health to immune function. The complex biochemical pathways involved in the synthesis, metabolism, and action of Vitamin D are explored, emphasizing its importance in nutrition and food technology. This review also investigates the regulatory mechanisms that control Vitamin D metabolism and its systemic effects on calcium homeostasis, cell proliferation, differentiation, and immune modulation. The role of Vitamin D3 in regulating blood pressure and atherosclerosis in the onset of cardiovascular disorders is discussed. Given the importance of Vitamin D in food science and technology, the regulatory mechanisms that control Vitamin D metabolism and its systemic effects on calcium homeostasis are also investigated, integrating innovative approaches and advanced technologies to improve human health through nutrition. Additionally, the review assesses the influence of food processing on Vitamin D levels and discusses cutting-edge technologies as innovative strategies to mitigate Vitamin D loss during food processing. This comprehensive exploration aims to improve our understanding of the biochemical pathways of Vitamin D and its relevance to food science, contributing to the development of new strategies for food fortification and the promotion of optimal health through diet.
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(This article belongs to the Special Issue Nutrient and Metabolite Profiling in Food Science)
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The Environmental Benefits of an Automatic Idling Control System of Connected and Autonomous Vehicles (CAVs)
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Hoe Kyoung Kim
Appl. Sci. 2024, 14(11), 4338; https://doi.org/10.3390/app14114338 (registering DOI) - 21 May 2024
Abstract
The transportation sector is regarded as the main culprit in greenhouse gas emission in the urban network, particularly idling vehicles waiting at signalized intersections. Although autonomous vehicles can be a promising technology to tackle vehicle idling, their environmental benefits receive little attention compared
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The transportation sector is regarded as the main culprit in greenhouse gas emission in the urban network, particularly idling vehicles waiting at signalized intersections. Although autonomous vehicles can be a promising technology to tackle vehicle idling, their environmental benefits receive little attention compared with their safety and mobility issues. This study investigated the environmental benefits of autonomous vehicles equipped with an automatic idling control function based on the queue discharge time and traffic signal information transmitted from the traffic signal controller via V2I communication using microscopic mobility and emission simulation models, VISSIM and MOVES, in Haeundae-gu in Busan, Korea. This study found that the function contributes to a significant reduction in CO2 emissions by 23.6% for all-inclusive emission and 94.3% for idling emission, respectively. Moreover, total reduced idling time accounts for 47.6% of the total travel time and 94.3% of the total idling time, respectively. Consequently, the autonomous vehicles equipped with automatic vehicle idling control function under C-ITS can play an important role in reducing greenhouse gas emissions and fuel consumption as well in the urban network.
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(This article belongs to the Special Issue Advances in Intelligent Transportation Systems)
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Analysis of Space Efficiency in High-Rise Timber Residential Towers
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Hüseyin Emre Ilgın and Özlem Nur Aslantamer
Appl. Sci. 2024, 14(11), 4337; https://doi.org/10.3390/app14114337 - 21 May 2024
Abstract
High-rise timber residential towers (≥eight-stories) represent a burgeoning and auspicious sector, predominantly due to their capability to provide significant ecological and financial advantages throughout their lifecycle. Like numerous other building types, spatial optimization in high-rise timber residential structures stands as a pivotal design
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High-rise timber residential towers (≥eight-stories) represent a burgeoning and auspicious sector, predominantly due to their capability to provide significant ecological and financial advantages throughout their lifecycle. Like numerous other building types, spatial optimization in high-rise timber residential structures stands as a pivotal design factor essential for project viability. Presently, there exists no comprehensive investigation on space efficiency in such towers. This study analyzed data from 51 case studies to enhance understanding of the design considerations influencing space efficiency in high-rise timber residential towers. Key findings included (1) the average space efficiency within the examined cases was recorded at 83%, exhibiting variances ranging from 70% to 93% across different cases, (2) the average percentage of core area to gross floor area (GFA) was calculated at 10%, demonstrating fluctuations within the range of 4% to 21% across diverse scenarios, and (3) no notable distinction was observed in the effect of various core planning strategies on spatial efficiency when properly designed, and similar conclusions were drawn regarding building forms and structural materials. This research will aid in formulating design guidelines tailored for various stakeholders such as architectural designers involved in high-rise residential timber building developments.
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(This article belongs to the Special Issue Advances in Engineered Wood Products and Timber Structures)
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Investigating Acceleration and Deceleration Patterns in Elite Youth Football: The Interplay of Ball Possession and Tactical Behavior
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Javier Conde-Pipó, Guilherme de Sousa Pinheiro, David Fombella Pombal, Luis Mosquera Toscano, Juan Esteban Gomez Llamas, Jose Maria Cruz Gallardo, Bernardo Requena and Miguel Mariscal-Arcas
Appl. Sci. 2024, 14(10), 4336; https://doi.org/10.3390/app14104336 - 20 May 2024
Abstract
The main objective of this study was (1) to analyze the patterns of acceleration (Ac) and deceleration (Dec) during football matches in elite youth football, both within and between different segments of the match; and (2) to investigate the impact of ball possession
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The main objective of this study was (1) to analyze the patterns of acceleration (Ac) and deceleration (Dec) during football matches in elite youth football, both within and between different segments of the match; and (2) to investigate the impact of ball possession and various playing positions on these acceleration and deceleration patterns. To provide a broader explanatory context, the influence of tactical space management was assessed in terms of depth and width. A descriptive comparative design was used, and data were collected during two friendly matches. Player and ball tracking data were collected using a local positioning system. In the attack phase, differences were obtained in the average Ac (first half: 0.42 ± 0.06 m·s−2, second half: 0.38 ± 0.07 m·s−2; p = 0.021, d = 0.50) and average Dec (first half: −0.44 ± 0.09 m·s−2, second half: −0.36 ± 0.08 m·s−2; p = 0.001, d = 0.84). Wingers in the attack phase obtained higher values in maximum Ac (1.65 ± 0.65 m·s−2; p = 0.007, η2 = 0.03), and in the total number of both Ac (68.7 ± 45.22; p = 0.001, η2 = 0.10) and Dec (70.6 ± 45.70; p = 0.001, η2 = 0.10). In the defense phase, full-backs obtained higher values in average Ac (0.53 ± 0.17 m·s−2; p = 0.001, η2 = 0.07) and average Dec (−0.49 ± 0.18 m·s−2; p = 0.001, η2 = 0.05) and wingers in the total number of Ac (43.9 ± 27.30; p = 0.001, η2 = 0.11) and Dec (43.8 ± 28.60; p = 0.001, η2 = 0.10). In young football players, Ac and Dec do not follow a decreasing end throughout the match, and their behavior is uneven depending on ball possession and the position assigned to the player, with the highest demands on Ac/Dec in winger and full-back positions.
Full article
(This article belongs to the Special Issue Sports Medicine: Latest Advances and Prospects)
Open AccessArticle
Three-Dimensional Upper Bound Solution to Estimate Soil Thrust of a Track System on Saturated Clay Slopes under Undrained Conditions
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Sehee Shin and Sang Inn Woo
Appl. Sci. 2024, 14(10), 4335; https://doi.org/10.3390/app14104335 - 20 May 2024
Abstract
This study proposes a three-dimensional upper bound solution for estimating the soil thrust of tracked vehicles on saturated clay slopes. The present study considered block, triangular wedge, and trapezoidal wedge failure modes to formulate an upper bound solution for each. The analytical solution
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This study proposes a three-dimensional upper bound solution for estimating the soil thrust of tracked vehicles on saturated clay slopes. The present study considered block, triangular wedge, and trapezoidal wedge failure modes to formulate an upper bound solution for each. The analytical solution for soil thrust was determined as the minimum upper bound solution among those for each failure mode. This analytical solution was validated through numerical simulations that modeled track-ground interactions. Parametric studies, based on the upper bound solution, assessed the impact of track system shape, vehicle weight, undrained shear strength, and ground slope on soil thrust. The analytical solutions and parametric studies provide a rapid method for assessing vehicle operability on clay slopes and offer references for designing tracked vehicles suitable for site conditions.
Full article
(This article belongs to the Special Issue Advances in Failure Mechanism and Numerical Methods for Geomaterials)
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Investigation into the Impact of Piston Bowl Size on Diesel Engine Characteristics with Changes in Fuel Injection Pressure and Boost Pressure
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Thin Quynh Nguyen and Andrey Y. Dunin
Appl. Sci. 2024, 14(10), 4334; https://doi.org/10.3390/app14104334 - 20 May 2024
Abstract
This study presents the effects of piston bowl size on the characteristics of a four-stroke single-cylinder diesel engine, which is considered in relation to changes in factors such as fuel injection pressure and turbocharger pressure. The study was carried out by 3D modeling
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This study presents the effects of piston bowl size on the characteristics of a four-stroke single-cylinder diesel engine, which is considered in relation to changes in factors such as fuel injection pressure and turbocharger pressure. The study was carried out by 3D modeling using AVL Fire with an omega combustion chamber size and dimensions determined by the ratio between the diameter and depth of the piston bowl, which varies from 3.4 to 10.0. Additionally, the turbocharger pressure varies from 0.15 to 0.45 MPa at an engine speed of 1400 rpm and fuel injection pressure up to 300 MPa. The results show that the engine reaches the best values of indicated power, fuel efficiency, and a substantial decrease in emissions of nitrogen oxides at a turbocharger pressure from 0.25 to 0.35 MPa and with a ratio of the diameter to the depth from 7.8 to 10. However, the injection angle changes slightly, and the penetration depth and the tip velocity decrease with increasing boost pressure. While the piston bowl parameters only impact significantly on the tip velocity, the penetration and the spray angle are almost unchanged. In addition, the variation in the diameter of the combustion chamber has an influence on the fluctuation of the spray tip velocity and penetration.
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(This article belongs to the Section Applied Thermal Engineering)
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Theoretical and Experimental Analysis of the Effect of Vaporization Heat on the Interaction between Laser and Biological Tissue
by
Yuru Cheng, Yu Shen, Yuxia Gao, Ya Wen, Ze Lv, Erpeng Wang, Mingli Wang, Shenjin Zhang, Yong Bo and Qinjun Peng
Appl. Sci. 2024, 14(10), 4333; https://doi.org/10.3390/app14104333 - 20 May 2024
Abstract
A theoretical model, based on the classical Pennes’ bioheat theory, incorporating various boundary conditions, was established and compared to analyze the influence of the latent heat of vaporization via simulation. The aim was to elucidate the extent of its influence. The thermal damage
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A theoretical model, based on the classical Pennes’ bioheat theory, incorporating various boundary conditions, was established and compared to analyze the influence of the latent heat of vaporization via simulation. The aim was to elucidate the extent of its influence. The thermal damage rate, governed by the vaporization heat of biological tissue, is introduced as a key factor. Functional relationships between temperature and incident laser power, spatial position, and time are derived from the classical Pennes’ bioheat equation. According to the theoretical model, numerical simulations and experimental validations are conducted using Comsol Multiphysics 6.0, considering the tissue latent heat of vaporization. The model incorporating the latent heat of vaporization proved more suitable for analyzing the interactions between laser and biological tissue, evident from the degree of fit between simulated and experimental data. The minimum deviations between theoretical and experimental observations were determined to be 2.43% and 5.11% in temperature and thermal damage, respectively. Furthermore, this model can be extended to facilitate the theoretical analysis of the impact of vaporization heat from different primary tissue components on laser-tissue interaction.
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(This article belongs to the Section Optics and Lasers)
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Open AccessArticle
A One-Step Methodology for Identifying Concrete Pathologies Using Neural Networks—Using YOLO v8 and Dataset Review
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Joel de Conceição Nogueira Diniz, Anselmo Cardoso de Paiva, Geraldo Braz Junior, João Dallyson Sousa de Almeida, Aristófanes Corrêa Silva, António Manuel Trigueiros da Silva Cunha and Sandra Cristina Alves Pereira da Silva Cunha
Appl. Sci. 2024, 14(10), 4332; https://doi.org/10.3390/app14104332 - 20 May 2024
Abstract
Pathologies in concrete structures can be visually evidenced on the concrete surface, such as by fissures or cracks, fragmentation of part of the concrete, concrete efflorescence, corrosion stains on the concrete surface, or exposed steel bars, the latter two occurring in reinforced concrete.
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Pathologies in concrete structures can be visually evidenced on the concrete surface, such as by fissures or cracks, fragmentation of part of the concrete, concrete efflorescence, corrosion stains on the concrete surface, or exposed steel bars, the latter two occurring in reinforced concrete. Therefore, these pathologies can be analyzed via the images of concrete structures. This article proposes a methodology for visually inspecting concrete structures using deep neural networks. This method makes it possible to speed up the detection task and increase its effectiveness by saving time in preparing the identifications to be analyzed and eliminating or reducing errors, such as those resulting from human errors caused by the execution of tedious, repetitive analysis tasks. The methodology was tested to analyze its accuracy. The neural network architecture used for detection was YOLO, versions 4 and 8, which was tested to analyze the gain with migration to a more recent version. The dataset for classification was Ozgnel, which was trained with YOLO version 8, and the detection dataset was CODEBRIM. The use of a dedicated classification dataset allows for a better-trained network for this function and results in the elimination of false positives in the detection stage. The classification achieved 99.65% accuracy.
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(This article belongs to the Special Issue Intelligent Construction: Advancements in Civil Engineering and Building Structures)
Open AccessArticle
Investigation of Carbon Fiber Reinforced Polymer Concrete Reinforcement Ageing Using Microwave Infrared Thermography Method
by
Barbara Szymanik, Sam Ang Keo, Franck Brachelet and Didier Defer
Appl. Sci. 2024, 14(10), 4331; https://doi.org/10.3390/app14104331 - 20 May 2024
Abstract
This study presents the utilization of the microwave infrared thermography (MIRT) technique to identify and analyze the defects in the carbon-fiber-reinforced polymer (CFRP) composite reinforcement of concrete specimens. At first, a set of numerical models was created, comprising the broadband pyramidal horn antenna
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This study presents the utilization of the microwave infrared thermography (MIRT) technique to identify and analyze the defects in the carbon-fiber-reinforced polymer (CFRP) composite reinforcement of concrete specimens. At first, a set of numerical models was created, comprising the broadband pyramidal horn antenna and the analyzed specimen. The utilization of the system operating at a power of 1000 W in a continuous mode, operating at frequency of 2.45 GHz, was analyzed. The specimen under examination comprised a compact concrete slab that was covered with an adhesive layer and, thereafter, topped with a layer of CFRP. An air gap represented a defect at the interface between the concrete and the CFRP within the adhesive layer. In the modeling stage, the study investigated three separate scenarios—a sample with no defects, a sample with a defect located at the center, and a sample with a numerous additional random defects located at the rim of the CFRP matte—to analyze the effect of the natural reinforcement degradation in this area. The next phase of the study involved conducting experiments to confirm the results obtained from numerical modeling. In the experiments, the concrete sample aged for 10 years with the defect in the center and naturally developed defects at the CFRP rim was used. The study employed numerical modeling to explore the phenomenon of microwave heating in complex structures. The aim was to assess the chosen antenna design and identify the most effective experimental setup. These conclusions were subsequently confirmed through experimentation. The observations made during the heating process were particularly remarkable since they deviated from earlier studies that solely conducted measurements of the sample post-heating phase. The findings demonstrate that MIRT has the capacity to be employed as a technique for detecting flaws in concrete structures reinforced with CFRP.
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(This article belongs to the Special Issue Advanced Diagnostics and Nondestructive Testing Technologies for Civil Structures)
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Open AccessArticle
Limitations of Large Language Models in Propaganda Detection Task
by
Joanna Szwoch, Mateusz Staszkow, Rafal Rzepka and Kenji Araki
Appl. Sci. 2024, 14(10), 4330; https://doi.org/10.3390/app14104330 - 20 May 2024
Abstract
Propaganda in the digital era is often associated with online news. In this study, we focused on the use of large language models and their detection of propaganda techniques in the electronic press to investigate whether it is a noteworthy replacement for human
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Propaganda in the digital era is often associated with online news. In this study, we focused on the use of large language models and their detection of propaganda techniques in the electronic press to investigate whether it is a noteworthy replacement for human annotators. We prepared prompts for generative pre-trained transformer models to find spans in news articles where propaganda techniques appear and name them. Our study was divided into three experiments on different datasets—two based on an annotated SemEval2020 Task 11 corpora and one on an unannotated subset of the Polish Online News Corpus, which we claim to be an even bigger challenge as an example of an under-resourced language. Reproduction of the results of the first experiment resulted in a higher recall of 64.53% than the original run, and the highest precision of 81.82% was achieved for gpt-4-1106-preview CoT. None of our attempts outperformed the baseline F1 score. One of the attempts with gpt-4-0125-preview on original SemEval2020 Task 11 achieved an almost 20% F1 score, but it was below the baseline, which oscillated around 50%. Part of our work that was dedicated to Polish articles showed that gpt-4-0125-preview had a 74% accuracy in the binary detection of propaganda techniques and 69% in propaganda technique classification. The results for SemEval2020 show that the outputs of generative models tend to be unpredictable and are hardly reproducible for propaganda detection. For the time being, these are unreliable methods for this task, but we believe they can help to generate more training data.
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(This article belongs to the Section Computing and Artificial Intelligence)
Open AccessArticle
The total Phenolic Content and Antioxidant Activity of Nine Monofloral Honey Types
by
Chrysoula Tananaki, Maria-Anna Rodopoulou, Maria Dimou, Dimitrios Kanelis and Vasilios Liolios
Appl. Sci. 2024, 14(10), 4329; https://doi.org/10.3390/app14104329 - 20 May 2024
Abstract
Honey is well known for its antioxidant and antimicrobial properties, which significantly contribute to its high demand among consumers. While there is plenty of information available about the antioxidant potential of honey, there is still a lack of research specifically focused on monofloral
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Honey is well known for its antioxidant and antimicrobial properties, which significantly contribute to its high demand among consumers. While there is plenty of information available about the antioxidant potential of honey, there is still a lack of research specifically focused on monofloral honeys, as most studies have been based on market samples. To address this issue, in the present study we analyzed the total phenolic content and antioxidant activity of nine monofloral honey types produced in Greece: fir, chestnut, citrus, erica, cotton, Jerusalem thorn, pine, oak and thyme, in comparison with manuka honey. The samples were collected from beekeepers applying the appropriate beekeeping practices. In total, ninety-six representative monofloral honey samples meeting the microscopic, physicochemical, and sensory characteristics were analyzed. Oak honey stood out as the darkest type (L* = 33.67) with the highest total phenolic content (203.75 mg GAE/100 g) and antioxidant activity (106.2 mg AAE/100 g). Chestnut honey closely followed, having also the highest electrical conductivity (1.679 mS/cm). Although manuka honey had a high total phenolic content, its total antioxidant activity was found to be medium-low compared to fir, pine, and erica honeys. Citrus honey, being the lightest in color (L* = 37.2), exhibited the lowest total antioxidant activity (6.36 mg AAE/100 g). Statistical analysis revealed significant positive correlation between total antioxidant activity and electrical conductivity (ra-e =0.587, pa-e =0.000), and negative correlation between total antioxidant activity and L* parameter (ra-L = −0.424, pa-L = 0.000). Similar correlations were also observed regarding total phenolic content (rp-e = 0.457, pp-e = 0.000, rp-L = −0.455, pp-L = 0.000). In conclusion, oak and chestnut honeys seem to have a high antioxidant potential, that should be further explored, to highlight their value and help promote them worldwide.
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(This article belongs to the Special Issue Analysis, Characterization and Antioxidant Activity of Natural Products)
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