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Recent Articles  

27 pages, 542 KiB  
Article
Unsupervised Learning for Lateral-Movement-Based Threat Mitigation in Active Directory Attack Graphs
by David Herranz-Oliveros, Marino Tejedor-Romero, Jose Manuel Gimenez-Guzman and Luis Cruz-Piris
Electronics 2024, 13(19), 3944; https://doi.org/10.3390/electronics13193944 (registering DOI) - 6 Oct 2024
Abstract
Cybersecurity threats, particularly those involving lateral movement within networks, pose significant risks to critical infrastructures such as Microsoft Active Directory. This study addresses the need for effective defense mechanisms that minimize network disruption while preventing attackers from reaching key assets. Modeling Active Directory [...] Read more.
Cybersecurity threats, particularly those involving lateral movement within networks, pose significant risks to critical infrastructures such as Microsoft Active Directory. This study addresses the need for effective defense mechanisms that minimize network disruption while preventing attackers from reaching key assets. Modeling Active Directory networks as a graph in which the nodes represent the network components and the edges represent the logical interactions between them, we use centrality metrics to derive the impact of hardening nodes in terms of constraining the progression of attacks. We propose using Unsupervised Learning techniques, specifically density-based clustering algorithms, to identify those nodes given the information provided by their metrics. Our approach includes simulating attack paths using a snowball model, enabling us to analytically evaluate the impact of hardening on delaying Domain Administration compromise. We tested our methodology on both real and synthetic Active Directory graphs, demonstrating that it can significantly slow down the propagation of threats from reaching the Domain Administration across the studied scenarios. Additionally, we explore the potential of these techniques to enable flexible selection of the number of nodes to secure. Our findings suggest that the proposed methods significantly enhance the resilience of Active Directory environments against targeted cyber-attacks. Full article
(This article belongs to the Special Issue Machine Learning for Cybersecurity: Threat Detection and Mitigation)
24 pages, 827 KiB  
Systematic Review
Measuring Instruments for Media Health Literacy: A Systematic Review of Psychometric Properties
by Noelia Navas-Echazarreta, Raúl Juárez-Vela, Antonio Martínez-Sabater, Emmanuel Echániz-Serrano, María Teresa Fernández-Rodrigo, Olga Navarro-Martínez, Consuelo Sancho-Sánchez, Ana Cobos-Rincón, Antonio Rodríguez-Calvo, Silvia González-Fernández, Elena Chover-Sierra and Pedro José Satústegui-Dordá
Nurs. Rep. 2024, 14(4), 2795-2818; https://doi.org/10.3390/nursrep14040206 (registering DOI) - 6 Oct 2024
Abstract
Background: Informational overload hinders the recognition of quality information and influences a population’s health-related decisions. In this context, media health literacy aims to promote citizens’ critical analysis skills, contributing to informed decision-making. This study aims to identify the instruments used to measure [...] Read more.
Background: Informational overload hinders the recognition of quality information and influences a population’s health-related decisions. In this context, media health literacy aims to promote citizens’ critical analysis skills, contributing to informed decision-making. This study aims to identify the instruments used to measure the level of media health literacy and their psychometric properties. Methods: A systematic review of the scientific literature was performed in 2023. The articles were extracted from the electronic databases “Pubmed”, “Web of Science”, “Dialnet”, and “Scopus”. The search languages were limited to English, Spanish, and Portuguese. Results: Twelve articles were selected for further analysis. The described measurement instruments included five original scales and seven cross-cultural adaptations of three of them. Four scales (the Sugar-Sweetened Beverages Media Literacy scale adapted to Turkish and Chinese, along with the Media Health Literacy (MeHLit) scale and its adaptation to the Chinese language) exhibited high quality in the assessment of psychometric properties. Conclusions: These instruments allow for the measurement of an individual’s level of skill when consuming specific health information, enabling an analysis to understand the risk they are exposed to. Further research is recommended to strengthen the existing evidence and apply these tools to broader and more diverse populations. Full article
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16 pages, 1890 KiB  
Article
Inductive Effect of Exogenous Abscisic Acid on the Weed-Suppressive Activity of Allelopathic and Non-Allelopathic Rice Accessions at the Root Level
by Jiayu Li, Ting Wang, Yuhui Fan, Shuyu Chen, Xinyi Ye, Yanping Wang and Chen Cheng
Agronomy 2024, 14(10), 2297; https://doi.org/10.3390/agronomy14102297 (registering DOI) - 6 Oct 2024
Abstract
Rice allelopathy is a natural method of weed control that is regarded as an eco-friendly practice in agroecology. The root growth of allelopathic rice at the seedling stage plays an important role in its weed control. Our study characterizes a plant hormone that [...] Read more.
Rice allelopathy is a natural method of weed control that is regarded as an eco-friendly practice in agroecology. The root growth of allelopathic rice at the seedling stage plays an important role in its weed control. Our study characterizes a plant hormone that promotes root growth, abscisic acid (ABA), to explore its role in the induction of rice allelopathy. Increasing the root morphology traits (root length, root tip number, and root biomass) in rice using different concentrations of exogenous ABA resulted in increased inhibitory ratios against barnyard grass (Echinochloa crus-galli), both in a hydroponic experiment and pot test. In particular, the relative proportion of induced allelopathy to total allelopathy in non-allelopathic rice Lemont (Le) was higher than that in allelopathic rice PI31277 (PI). The total content of phenolic acid, which is an important allelochemical in rice, as previously reported, was significantly elevated in the root exudates of both PI and LE. The gene expression levels of OsPAL, OsC4H, and OsCOL related to phenolic acid synthesis were also up-regulated, with a higher regulatory fold in PI. ABA also increased the expression of OsKSL4 and CYP75B4 involved in the biosynthesis of momilactone B and tricin. Moreover, low concentrations of exogenous ABA mainly positively regulate the expression of OsIAA11, an AUX/IAA transcription factor gene, in the root of PI and Le. These findings suggest that the application of ABA could significantly enhance the weed-suppressive activity of both rice cultivars through regulating root growth and the synthesis of allelochemicals secreted by rice roots, providing an option for the improvement of rice allelopathy through chemical induction. Full article
(This article belongs to the Special Issue Strategies for Sustainable Weed Control: Embracing Multi-tactic Solutions)
26 pages, 6450 KiB  
Article
High-Gain Multi-Band Koch Fractal FSS Antenna for Sub-6 GHz Applications
by Atul Varshney and Duygu Nazan Gençoğlan
Appl. Sci. 2024, 14(19), 9022; https://doi.org/10.3390/app14199022 (registering DOI) - 6 Oct 2024
Abstract
This study introduces a novel antenna based on the binary operation of a modified circular patch in conjunction with the Koch fractal. The antenna is intended for applications in the sub-6 GHz band, partial C-band, and X-band. The low-cost antenna is fabricated on [...] Read more.
This study introduces a novel antenna based on the binary operation of a modified circular patch in conjunction with the Koch fractal. The antenna is intended for applications in the sub-6 GHz band, partial C-band, and X-band. The low-cost antenna is fabricated on a 1.6-mm-thick FR-4 substrate. A frequency-selective surface (FSS) is used to overcome the decreased values of the gain and bandwidth due to the fractal operations. The introduced split ring resonator (SRR) and the antenna substrate dimension reduction reduce the bandwidth and antenna gain. The air gap between the FSS and the antenna not only enhances the antenna gain but also controls the frequency tuning at the design frequency. The antenna size is miniaturized to 36.67%. A monopole antenna ground loaded with an SRR results in improved closest tuning (3.44 GHz) near the design frequency. The antenna achieves a peak gain of 9.37 dBi in this band. The FSS-based antenna results in a 4.65 dBi improvement in the gain value with the FSS. The measured and simulated plots exhibit an excellent match with each other in all three frequency bands at 2.96–4.72 GHz. These bands cover Wi-MAX (3.5 GHz), sub-6 GHz n77 (3300–3800 MHz), n78 (3300–4200 MHz), and approximately n79 (4400–4990 MHz), in addition to C-band applications. Full article
(This article belongs to the Special Issue Antenna Design and Microwave Engineering)
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14 pages, 2235 KiB  
Article
Exposure to Cyantraniliprole Adversely Impacts Fitness of Harmonia axyridis: Acute Toxicity and Sublethal Effects on Development, Fecundity and Antioxidant Responses
by Tianshu Zhang, Yongda Yuan, Haiyuan Teng, Dongsheng Wang and Haotian Gu
Insects 2024, 15(10), 773; https://doi.org/10.3390/insects15100773 (registering DOI) - 6 Oct 2024
Abstract
Extensive utilization of pesticides and their persistent residues inadvertently pose threats to the effectiveness and fitness of biocontrol agents in agroecosystems. However, these ecological consequences are generally disregarded when executing integrated pest management strategies (IPM). Cyantraniliprole (CNAP) serves as a wide-spectrum diamide insecticide [...] Read more.
Extensive utilization of pesticides and their persistent residues inadvertently pose threats to the effectiveness and fitness of biocontrol agents in agroecosystems. However, these ecological consequences are generally disregarded when executing integrated pest management strategies (IPM). Cyantraniliprole (CNAP) serves as a wide-spectrum diamide insecticide and its sublethal effects have been well characterized on multiple insect pests, whereas its impacts on beneficial natural enemies remain unfathomed. Herein we exposed Harmonia axyridis, a predacious generalist, to lethal and sublethal concentrations of CNAP via dipping treatment (egg stage) and topical applications (1st-instar stage + adult stage). The acute toxicity tests revealed that LC50 of CNAP were 90.11, 86.11 and 240.50 mg/L against embryos, 1st instar nymphs and female adults, respectively, with safety factors ranging from 1.14 to 5.34, suggesting its medium toxicity for H. axyridis and larval stage was the most susceptible. The embryonic, larval and pupal durations of coccinellids ecdysed from CNAP-treated eggs and 1st instars were all elongated under sublethal concentrations, of which LC30 triggered more pronounced and significant retardations relative to control. Besides, exposed coccinellids displayed substantially diminished pupal mass and pupation rate, most notably for insects molted from the 1st-instar stage upon CNAP sublethal treatments. With respect to reproductive performance, LC10 and LC30 of CNAP all significantly suppressed female fecundity, as evidenced by reduced vitellin content, a prolonged pre-oviposition period (POP), mitigated laid eggs and the egg hatching rate. Specifically, there existed positive correlations between vitellin level (Vn) and number of eggs deposited by per female, indicative of CNAP affecting fecundity by regulation of Vn. In addition, the antioxidant system was also profoundly disrupted by CNAP, with compromised POD activity at different concentrations over time and induced hormesis of SOD/CAT activities post LC10 exposure. Activities of SOD and TAC were enhanced to exert protective functions during the first 48 h, while defense collapsed at 72 h following LC30 treatments that depleted all enzymatic activities. We speculated that fitness trade-offs may occur between reproductive capacity and antioxidant defenses to sustain physiological homeostasis in response to CNAP stress. Collectively, this study evaluated the ecological risk of CNAP and unmasked its adverse implications for overall fitness of H. axyridis, which highlighted rational application of agrochemicals to conserve biocontrol agents when implementing IPM strategies for sustainable pest control. Full article
(This article belongs to the Section Insect Physiology, Reproduction and Development)
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15 pages, 1174 KiB  
Article
On the Use of the Multi-Site Langmuir Model for Predicting Methane Adsorption on Shale
by Zhe Wu, Yuan Ji, Ke Zhang, Li Jing and Tianyi Zhao
Energies 2024, 17(19), 4990; https://doi.org/10.3390/en17194990 (registering DOI) - 6 Oct 2024
Abstract
Shale gas, mainly consisting of adsorbed gas and free gas, has served a critical role of supplying the growing global natural gas demand in the past decades. Considering that the adsorbed methane has contributed up to 80% of the total gas in place [...] Read more.
Shale gas, mainly consisting of adsorbed gas and free gas, has served a critical role of supplying the growing global natural gas demand in the past decades. Considering that the adsorbed methane has contributed up to 80% of the total gas in place (GIP), understanding the methane adsorption behaviors is imperative to an accurate estimation of total GIP. Historically, the single-site Langmuir model, with the assumption of a homogeneous surface, is commonly applied to estimate the adsorbed gas amount. However, this assumption cannot depict the methane adsorption characteristics due to various compositions and pore sizes of shales. In this work, a multi-site model integrating the energetic heterogeneity in adsorption is derived to predict methane adsorption on shale. Our results show that the multi-site model is capable of addressing the heterogeneity of shales by a wide range of adsorption energy distributions (owing to the complex compositions and different pore sizes), which is different from the single-site model only characterized by single adsorption energy. Consequently, the multi-site model results have better accuracy against the experimental data. Therefore, applying the multi-site Langmuir model for estimating GIP in shales can achieve more accurate results compared with using the traditionally single-site model. Full article
(This article belongs to the Section H: Geo-Energy)
12 pages, 3861 KiB  
Article
Exploratory Investigation of Head Stability in Children with Cerebral Palsy and Typically Developing Children during a Targeted Stepping Task
by Harry G. B. Bailey, Thomas D. O’Brien, Gabor J. Barton, Alf Bass, David Wright, Ornella Pinzone, Henrike Greaves and Richard J. Foster
Appl. Sci. 2024, 14(19), 9008; https://doi.org/10.3390/app14199008 (registering DOI) - 6 Oct 2024
Abstract
Children with cerebral palsy (CP) exhibit head instability during simple overground walking, which may comprise sensory input and reduce stepping accuracy. Investigations of head stability during more challenging tasks, where fall risk may be increased, are limited. This study explored differences in head [...] Read more.
Children with cerebral palsy (CP) exhibit head instability during simple overground walking, which may comprise sensory input and reduce stepping accuracy. Investigations of head stability during more challenging tasks, where fall risk may be increased, are limited. This study explored differences in head stability between ambulatory children with hemiplegic CP (N = 9) and diplegia (N = 9) (GMFCS I and II) and typically developing (TD) children (N = 8) during a targeted stepping task. All children completed five trials stepping into two successive rectangular floor-based targets whilst walking along an 8 m walkway. Three-dimensional motion capture enabled calculation of head stability and foot placement within and before each target. A two-way mixed-design ANOVA compared differences between all groups and target approach. Children with diplegic CP showed greater sagittal, frontal, and resultant head-to-laboratory and head-to-trunk head instability compared to children with hemiplegic CP and TD children. Anteroposterior foot placement error was significantly greater in children with hemiplegic CP (8.5 ± 5.0 cm) compared to TD children (3.8 ± 1.5 cm). Group differences in head instability were not consistent with group differences in foot placement error. To better understand how head instability might affect fall risk in children with CP, more challenging environments should be tested in future. Full article
(This article belongs to the Special Issue Advances in the Biomechanical Analysis of Human Movement)
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20 pages, 3646 KiB  
Article
Applying Deep Generative Neural Networks to Data Augmentation for Consumer Survey Data with a Small Sample Size
by Shinya Watanuki, Katsue Edo and Toshihiko Miura
Appl. Sci. 2024, 14(19), 9030; https://doi.org/10.3390/app14199030 (registering DOI) - 6 Oct 2024
Abstract
Questionnaire consumer survey research is primarily used for marketing research. To obtain credible results, collecting responses from numerous participants is necessary. However, two crucial challenges prevent marketers from conducting large-sample size surveys. The first is cost, as organizations with limited marketing budgets struggle [...] Read more.
Questionnaire consumer survey research is primarily used for marketing research. To obtain credible results, collecting responses from numerous participants is necessary. However, two crucial challenges prevent marketers from conducting large-sample size surveys. The first is cost, as organizations with limited marketing budgets struggle to gather sufficient data. The second involves rare population groups, where it is difficult to obtain representative samples. Furthermore, the increasing awareness of privacy and security concerns has made it challenging to ask sensitive and personal questions, further complicating respondent recruitment. To address these challenges, we augmented small-sized datawith synthesized data generated using deep generative neural networks (DGNNs). The synthesized data from three types of DGNNs (CTGAN, TVAE, and CopulaGAN) were based on seed data. For validation, 11 datasets were prepared: real data (original and seed), synthesized data (CTGAN, TVAE, and CopulaGAN), and augmented data (original + CTGAN, original + TVAE, original + CopulaGAN, seed + CTGAN, seed + TVAE, and seed + CopulaGAN). The large-sample-sized data, termed “original data”, served as the benchmark, whereas the small-sample-sized data acted as the foundation for synthesizing additional data. These datasets were evaluated using machine learning algorithms, particularly focusing on classification tasks. Conclusively, augmenting and synthesizing consumer survey data have shown potential in enhancing predictive performance, irrespective of the dataset’s size. Nonetheless, the challenge remains to minimize discrepancies between the original data and other datasets concerning the values and orders of feature importance. Although the efficacy of all three approaches should be improved in future work, CopulaGAN more accurately grasps the dependencies between the variables in table data compared with the other two DGNNs. The results provide cues for augmenting data with dependencies between variables in various fields. Full article
(This article belongs to the Special Issue Intelligent Data Mining, Analysis and Modeling Based on Machine Learning)
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28 pages, 454 KiB  
Article
Technological Innovation, Trade Openness, Natural Resources, and Environmental Sustainability in Egypt and Turkey: Evidence from Load Capacity Factor and Inverted Load Capacity Factor with Fourier Functions
by Zhu Yingjun, Sharmin Jahan and Md. Qamruzzaman
Sustainability 2024, 16(19), 8643; https://doi.org/10.3390/su16198643 (registering DOI) - 6 Oct 2024
Abstract
The environmental degradation in the Middle East and North Africa (MENA) region leads to significant challenges regarding economic sustainability and the attainment of sustainable development goals (SDGs). The extensive use of fossil fuels in the region, as well as rapid urbanization and economic [...] Read more.
The environmental degradation in the Middle East and North Africa (MENA) region leads to significant challenges regarding economic sustainability and the attainment of sustainable development goals (SDGs). The extensive use of fossil fuels in the region, as well as rapid urbanization and economic growth, has led to significant carbon emissions, together with unprecedented ecological footprints compromising environmental sustainability. The study aims to elucidate the influence exerted by technological innovation, trade openness, and natural resources on environmental sustainability in Turkey and Egypt for the period 1990–2022. In assessing the empirical relations, the study employed the Fourier function incorporate estimation techniques, that is, Fourier ADF for unit root test, Fourier ARDL, and Fourier NARDL for long-run and short-run elasticities of technological innovation (TI), trade openness (TO,) and natural resources rent (NRR) on load capacity factor (LCF) and inverted LCF (ILCF); finally, the directional causality evaluate through Fourier TY causality test. The results revealed that both Turkey and Egypt have severe environmental problems due to their high carbon emissions and ecological footprints. Technological change and international trade separately negatively affect environmental sustainability; however, these negative impacts have mixed character. On the one hand, technology can improve efficiency and reduce ecological footprints by obviating the use of high-impact processes or allowing cleaner production systems. In the same vein, trade openness helps transfer green technologies more quickly, but it can also lead to unsustainable resource extraction and pollution. The findings of the paper propose that in order to move forward, Turkey and Egypt need strategic policy shifts to ensure environmental sustainability, including transitioning towards renewable energy from fossil fuels while bolstering their capacity for energy efficiency. Policymakers must balance economic development with environmental conservation to reduce the harmful effects of climate degradation and help safeguard continued economic survival in the face of increasing climatic instability. This research helps to inform policy and investment decisions about how the SDGs can be achieved and how they are relevant for sustainable development in the MENA region. Full article
(This article belongs to the Section Environmental Sustainability and Applications)
16 pages, 1898 KiB  
Review
Pesticides Risk Assessment Review: Status, Modeling Approaches, and Future Perspectives
by Gamal El Afandi and Muhammad Irfan
Agronomy 2024, 14(10), 2299; https://doi.org/10.3390/agronomy14102299 (registering DOI) - 6 Oct 2024
Abstract
Pesticide exposure poses significant environmental and human health concerns, particularly given its extensive use in agricultural activities. The assessment of pesticide risks is a multifaceted and resource-intensive process, often requiring time-consuming toxicity studies. In response to this challenge, advanced computational models, remote sensing, [...] Read more.
Pesticide exposure poses significant environmental and human health concerns, particularly given its extensive use in agricultural activities. The assessment of pesticide risks is a multifaceted and resource-intensive process, often requiring time-consuming toxicity studies. In response to this challenge, advanced computational models, remote sensing, and GIS (geographic information systems) have emerged as efficient and precise tools for evaluating pesticide exposure risks. This comprehensive review aims to provide an in-depth examination of the latest research methodologies for assessing the risks associated with pesticide exposure and their practical applications. These methodologies encompass the assessment of pesticide exposure in air, soil, and water, offering a comprehensive understanding of potential environmental pathways. The paper also delves into the effective utilization of these tools for pesticide risk assessment and examines the potential implications of their findings. The approaches outlined in this review hold promise for a thorough and insightful assessment of pesticide risks and are positioned to equip researchers and policymakers with valuable knowledge to mitigate the impacts of pesticide exposure on human health and the environment. Full article
(This article belongs to the Section Agroecology Innovation: Achieving System Resilience)
19 pages, 8988 KiB  
Article
CFD Analysis of the Effects of a Barrier in a Hydrogen Refueling Station Mock-Up Facility during a Vapor Cloud Explosion Using the radXiFoam v2.0 Code
by Hyung-Seok Kang, Keun-Sang Choi, Hyun-Woo Lee and Chul-Hee Yu
Processes 2024, 12(10), 2173; https://doi.org/10.3390/pr12102173 (registering DOI) - 6 Oct 2024
Abstract
A CFD (computational fluid dynamics) analysis to investigate the effects of the installation of a barrier in a hydrogen refueling station (HRS) mock-up facility, with a dummy vehicle and dispensers in the vapor cloud region, during a hydrogen-air explosion using a gas mixture [...] Read more.
A CFD (computational fluid dynamics) analysis to investigate the effects of the installation of a barrier in a hydrogen refueling station (HRS) mock-up facility, with a dummy vehicle and dispensers in the vapor cloud region, during a hydrogen-air explosion using a gas mixture volume of 70.16 m3 was conducted to determine whether the radXiFoam v2.0 code with the established analysis methodology to predict the peak overpressure can be utilized to evaluate the safety of a HRS with such a barrier installed in a large city in the Republic of Korea. The radXiFoam v2.0 code was developed on the basis of the XiFoam solver in the open-source CFD software OpenFOAM-v2112 by modifying C++ source codes in several libraries and governing equations so as to ensure effective calculations of the hydrogen-air chemical reaction and radiative heat transfer through water vapor in a humid air environment and to remove unnecessary warning messages that arise when using the radXiFoam v1.0 code. First, we conducted a validation analysis on the basis of measured overpressure datasets from a near field to a far field of a vapor cloud explosion (VCE) site in the HRS mock-up facility to evaluate the uncertainty in prediction datasets by radXiFoam v2.0. After this validation analysis, we undertook CFD sensitivity calculations by installing barriers with heights of 2.1 m and 4.2 m at a horizontal distance of 2.3 m from the VCE region in the grid model used for the validation analysis to assess the effects of these barriers on reducing the peak overpressure of the blast wave. From these calculations, we judged that the radXiFoam v2.0 code can accurately simulate the effects of the barrier during a VCE, as the calculated overpressure reduction values according to the barrier height are reasonable on the basis of previous validation results from Stanford Research Institute’s explosion test with such a barrier. The results herein imply that the radXiFoam v2.0 code is feasible for use in HRS safety when barrier installation must meet the technical regulations of the Korea Gas Safety Corporation in a large city. Full article
(This article belongs to the Special Issue Applications of Computational Fluid Dynamics (CFD) in Chemical Process Simulations)
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28 pages, 4231 KiB  
Article
On the Relationships between Clear-Sky Indices in Photosynthetically Active Radiation and Broadband Ranges in Overcast and Broken-Cloud Conditions
by William Wandji Nyamsi, Yves-Marie Saint-Drenan, John A. Augustine, Antti Arola and Lucien Wald
Remote Sens. 2024, 16(19), 3718; https://doi.org/10.3390/rs16193718 (registering DOI) - 6 Oct 2024
Abstract
Several studies proposed relationships linking irradiances in the photosynthetically active radiation (PAR) range and broadband irradiances. A previous study published in 2024 by the same authors proposes a linear model relating clear-sky indices in the PAR and broadband ranges that has been validated [...] Read more.
Several studies proposed relationships linking irradiances in the photosynthetically active radiation (PAR) range and broadband irradiances. A previous study published in 2024 by the same authors proposes a linear model relating clear-sky indices in the PAR and broadband ranges that has been validated in clear and overcast conditions only. The present work extends this study for broken-cloud conditions by using ground-based measurements obtained from the Surface Radiation Budget Network in the U.S.A. mainland. As expected, the clear-sky indices are highly correlated and are linked by affine functions whose parameters depend on the fractional sky cover (FSC), the year, and the site. The previous linear model is also efficient in broken-cloud conditions, with the same level of accuracy as in overcast conditions. When this model is combined with a PAR clear-sky model, the result tends to overestimate the PAR as the FSC decreases, i.e., when fewer and fewer scattered clouds are present. The bias is equal to 1 W m−2 in overcast conditions, up to 18 W m−2 when the FSC is small, and 6 W m−2 when all cloudy conditions are merged. The RMSEs are, respectively, 5, 24, and 15 W m−2. The linear and the clear-sky models can be combined with estimates of the broadband irradiance from satellites to yield estimates of PAR. Full article
13 pages, 1193 KiB  
Article
Effect of Er,Cr:YSGG Laser Irradiation on the Surface Modification and Cell Adhesion on Titanium Discs: An In Vitro Study
by Takahiko Shiba, Kailing Ho, Xuehao Ma, Ye Won Cho, Chia-Yu Chen and David M. Kim
Materials 2024, 17(19), 4899; https://doi.org/10.3390/ma17194899 (registering DOI) - 6 Oct 2024
Abstract
This study evaluates the potential of erbium, chromium-doped:yttrium, scandium, gallium, and garnet (Er,Cr:YSGG) laser irradiation to modify the titanium surface for optimal seeding of fibroblasts and osteoblasts in the treatment of peri-implantitis. Titanium discs were treated using the Er,Cr:YSGG laser, an ultrasonic device [...] Read more.
This study evaluates the potential of erbium, chromium-doped:yttrium, scandium, gallium, and garnet (Er,Cr:YSGG) laser irradiation to modify the titanium surface for optimal seeding of fibroblasts and osteoblasts in the treatment of peri-implantitis. Titanium discs were treated using the Er,Cr:YSGG laser, an ultrasonic device with a stainless tip, or titanium scalers. Changes in surface properties were analyzed by profilometer and scanning electron microscopy (SEM). Murine fibroblast and osteoblast adhesion and proliferation were evaluated qualitatively and quantitatively at 24 and 72 h. Profilometric surface topography and SEM showed that titanium scalers and ultrasonic debridement techniques significantly changed the structure of the machined and rough titanium surfaces. The Er,Cr:YSGG laser irradiation, on the other hand, did not alter titanium microstructures. The Er,Cr:YSGG laser irradiation with the 40 Hz group showed a significantly higher attached fibroblast cell numbers than the titanium scaler group at 72 h after treatment (p = 0.023). Additionally, the number of the attached osteoblasts in the Er,Cr:YSGG laser irradiation with the 40 Hz group was significantly higher than that of the no-treatment groups 24 h after treatment (p = 0.045). The Er,Cr:YSGG laser effectively promoted adherence of fibroblasts and osteoblasts to the titanium surface without significantly altering the titanium surface, suggesting its superiority for treating peri-implantitis. Full article
(This article belongs to the Special Issue Advanced Dental Materials, Dental Technologies and Dental Care)
28 pages, 13775 KiB  
Article
Elderly Fall Detection in Complex Environment Based on Improved YOLOv5s and LSTM
by Thioanh Bui, Juncheng Liu, Jingyu Cao, Geng Wei and Qian Zeng
Appl. Sci. 2024, 14(19), 9028; https://doi.org/10.3390/app14199028 (registering DOI) - 6 Oct 2024
Abstract
This work was conducted mainly to provide a healthy and safe monitoring system for the elderly living in the home environment. In this paper, two different target fall detection schemes are proposed based on whether the target is visible or not. When the [...] Read more.
This work was conducted mainly to provide a healthy and safe monitoring system for the elderly living in the home environment. In this paper, two different target fall detection schemes are proposed based on whether the target is visible or not. When the target is visible, a vision-based fall detection algorithm is proposed, where an image of the target captured by a camera is transmitted to the improved You Only Look Once version 5s (YOLOv5s) model for posture detection. In contrast, when the target is invisible, a WiFi-based fall detection algorithm is proposed, where channel state information (CSI) signals are used to estimate the target’s posture with an improved long short-term memory (LSTM) model. In the improved YOLOv5s model, adaptive picture scaling technology named Letterbox is used to maintain consistency in the aspect ratio of images in the dataset, and the weighted bidirectional feature pyramid (BiFPN) and the attention mechanisms of squeeze-and-excitation (SE) and coordinate attention (CA) modules are added to the Backbone network and Neck network, respectively. In the improved LSTM model, the Hampel filter is used to eliminate the noise from CSI signals and the convolutional neural network (CNN) model is combined with the LSTM to process the image made from CSI signals, and thus the object of the improved LSTM model at a point in time is the analysis of the amplitude of 90 CSI signals. The final monitoring result of the health status of the target is the result of combining the fall detection of the improved YOLOv5s and LSTM models with the physiological information of the target. Experimental results show the following: (1) the detection precision, recall rate, and average precision of the improved YOLOv5s model are increased by 7.2%, 9%, and 7.6%, respectively, compared with the original model, and there is almost no missed detection of the target; (2) the detection accuracy of the improved LSTM model is improved by 15.61%, 29.36%, and 52.39% compared with the original LSTM, CNN, and neural network (NN) models, respectively, while the convergence speed is improved by 90% compared with the original LSTM model; and (3) the proposed algorithm can meet the requirements of accurate, real-time, and stable applications of health monitoring. Full article
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16 pages, 2197 KiB  
Review
Induced Necroptosis and Its Role in Cancer Immunotherapy
by Ziyao Zhang, Fangming Zhang, Wenjing Xie, Yubo Niu, Haonan Wang, Guofeng Li, Lingyun Zhao, Xing Wang and Wensheng Xie
Int. J. Mol. Sci. 2024, 25(19), 10760; https://doi.org/10.3390/ijms251910760 (registering DOI) - 6 Oct 2024
Abstract
Necroptosis is a type of regulated cell death (RCD) that is triggered by changes in the extracellular or intracellular milieu that are picked up by certain death receptors. Thanks to its potent capacity to induce immunological responses and overcome apoptotic resistance, it has [...] Read more.
Necroptosis is a type of regulated cell death (RCD) that is triggered by changes in the extracellular or intracellular milieu that are picked up by certain death receptors. Thanks to its potent capacity to induce immunological responses and overcome apoptotic resistance, it has garnered significant attention as a potential cancer treatment. Basic information for the creation of nano-biomedical treatments is provided by studies on the mechanisms underlying tumor necroptosis. Receptor-interacting protein kinase 1 (RIPK1)–RIPK3-mediated necroptosis, Toll-like receptor domain-containing adapter-inducing interferon (IFN)-β (TRIF)–RIPK3-mediated necroptosis, Z-DNA-binding protein 1 (ZBP1)–RIPK3-mediated necroptosis, and IFNR-mediated necroptosis are the four signaling pathways that collectively account for triggered necroptosis in this review. Necroptosis has garnered significant interest as a possible cancer treatment strategy because, in contrast to apoptosis, it elicits immunological responses that are relevant to therapy. Thus, a thorough discussion is held on the connections between tumor cell necroptosis and the immune environment, cancer immunosurveillance, and cells such as dendritic cells (DCs), cytotoxic T cells, natural killer (NK) cells, natural killer T (NKT) cells, and their respective cytokines. Lastly, a summary of the most recent nanomedicines that cause necroptosis in order to cause immunogenic cell death is provided in order to emphasize their promise for cancer immunotherapy. Full article
(This article belongs to the Section Molecular Immunology)
16 pages, 7440 KiB  
Article
Development of an Automatic Rock Mass Classification System Using Digital Tunnel Face Mapping
by Hyun-Koo Lee, Myung-Kyu Song, Young-Oh Jeong and Sean Seung-Won Lee
Appl. Sci. 2024, 14(19), 9024; https://doi.org/10.3390/app14199024 (registering DOI) - 6 Oct 2024
Abstract
To mitigate unforeseen incidents, such as key block failure or tunnel collapse during excavation, an appropriate support pattern that correlates with the geological conditions of the rock mass at the tunnel face should be designed. Rock mass evaluations should be conducted through geological [...] Read more.
To mitigate unforeseen incidents, such as key block failure or tunnel collapse during excavation, an appropriate support pattern that correlates with the geological conditions of the rock mass at the tunnel face should be designed. Rock mass evaluations should be conducted through geological face mapping during the construction phase, alongside predictions based on field investigations during the design phase. When marked discrepancies are identified, it is customary to convene an on-site evaluation involving a committee of experts. This study develops a digital tunnel face mapping system that utilises mobile devices to facilitate online evaluations during the construction phase. This system effectively replaces the traditional on-site field evaluation method. Tunnel face mapping can be promptly accomplished using images captured at the excavation face, enabling rapid analysis. In conjunction with the mapping capabilities, the developed system was designed to digitally store geological information, which includes parameters such as rock strength distribution, the spacing and length of discontinuities observed during the mapping process, as well as data pertaining to weathering and the groundwater conditions of those discontinuities. This information was then correlated with the rock mass rating sheet to automate the determination of ratings for each parameter, ultimately leading to a conclusive classification of the rock mass quality. By employing this system for tunnel face mapping and rock quality evaluation, we significantly reduced the discrepancies in the evaluation results that often arise due to the subjective judgement of geologists, as well as human errors that can occur throughout the rating process. Full article
13 pages, 2886 KiB  
Article
Identification and Characterization of Four Novel Viruses in Balclutha incisa
by Jiajing Xiao, Guang Yang, Renyi Liu and Danfeng Ge
Insects 2024, 15(10), 772; https://doi.org/10.3390/insects15100772 (registering DOI) - 6 Oct 2024
Abstract
Balclutha incisa (Cicadellidae: Deltocephalinae), a leafhopper prevalent in tropical and temperate regions, is notably abundant in grasses and rice. The virome of B. incisa was investigated using deep transcriptome sequencing, leading to the first identification of four viruses belonging to the families Aliusviridae [...] Read more.
Balclutha incisa (Cicadellidae: Deltocephalinae), a leafhopper prevalent in tropical and temperate regions, is notably abundant in grasses and rice. The virome of B. incisa was investigated using deep transcriptome sequencing, leading to the first identification of four viruses belonging to the families Aliusviridae, Iflaviridae, and Totiviridae in B. incisa. These viruses have been provisionally named B. incisa ollusvirus 1 (BiOV1), B. incisa ollusvirus 2 (BiOV2), B. incisa iflavirus 1 (BiIV1), and B. incisa totivirus 1 (BiTV1). The complete genome sequences of these viruses were obtained through rapid amplification of cDNA ends (RACE). BiOV1 has a linear genome of 15,125 nucleotides (nt), while BiOV2 possesses a circular genome of 14,853 nt. The BiIV1 genome, excluding the poly(A) tail, is 10,903 nt in length and encodes a single open reading frame (ORF) for a polyprotein consisting of 3194 amino acids (aa). The BiTV1 genome is 4357 nt long and contains two overlapping ORFs, with the viral RNA-dependent RNA polymerase (RdRp) translated via a −1 ribosomal frameshift. Phylogenetic and sequence identity analyses suggest that all these viruses are novel members of their respective families. This study significantly expands our understanding of the virome associated with B. incisa by reporting and characterizing these novel viruses. Full article
(This article belongs to the Section Insect Behavior and Pathology)
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14 pages, 955 KiB  
Article
Desflurane Versus Sevoflurane and Postoperative Cardiac Biomarkers in Older Adults Undergoing Low- To Moderate-Risk Noncardiac Surgery—Secondary Analysis of a Prospective, Observer-Blinded, Randomized Clinical Trial
by Alexander Taschner, Christian Reiterer, Edith Fleischmann, Barbara Kabon, Katharina Horvath, Nikolas Adamowitsch, David Emler, Thomas Christian, Nicole Hantakova, Beatrix Hochreiter, Laura Höfer, Magdalena List, Barbara Rossi, Florian W. Zenz, Giulia Zanvettor, Oliver Zotti, Melanie Fraunschiel and Alexandra Graf
J. Clin. Med. 2024, 13(19), 5946; https://doi.org/10.3390/jcm13195946 (registering DOI) - 6 Oct 2024
Abstract
Background/Objectives: Previous preclinical studies have shown that desflurane might have the most significant cardioprotective effect of all volatile anesthetics. However, data regarding the cardioprotective effects of desflurane versus sevoflurane are lacking. Therefore, we evaluated the effect of the maintenance of anesthesia using [...] Read more.
Background/Objectives: Previous preclinical studies have shown that desflurane might have the most significant cardioprotective effect of all volatile anesthetics. However, data regarding the cardioprotective effects of desflurane versus sevoflurane are lacking. Therefore, we evaluated the effect of the maintenance of anesthesia using desflurane versus sevoflurane on the postoperative maximum concentrations of cardiac biomarkers in older adults undergoing low- to moderate-risk noncardiac surgery. Methods: In this secondary analysis of a prospective randomized trial, we included all 190 older adults undergoing low- to moderate-risk noncardiac surgery. Patients were randomized to receive desflurane or sevoflurane for the maintenance of anesthesia. We administered desflurane or sevoflurane, aiming at a BIS value of 50 ± 5. The cardiac-specific biomarkers included troponin T, NT-proBNP, and copeptin, which were measured preoperatively, within one hour after surgery, and on the second postoperative day. Results: There were no significant differences between the desflurane and sevoflurane groups in the postoperative maximum concentrations of troponin T (11 ng.L−1 [8; 16] versus 13 ng.L−1 [9; 18]; p = 0.595), NT-proBNP (196 pg.mL−1 [90; 686] versus 253 pg.mL−1 [134; 499]; p = 0.288), or copeptin (19 pmol.L−1 [7; 58] versus 12 pmol.L−1 [6; 41]; p = 0.096). We also observed no significant differences in the troponin T, NT-proBNP, or copeptin concentrations between the desflurane and sevoflurane groups at any measured timepoint (all p > 0.05). Conclusions: In contrast to preclinical studies, we did not observe a significant difference in the postoperative maximum concentrations of cardiac biomarkers. It seems likely that desflurane does not exert significant clinical meaningful cardioprotective effects in older adults. Thus, our results do not support the use of desflurane in patients undergoing low- to moderate-risk noncardiac surgery. Full article
(This article belongs to the Section Anesthesiology)
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15 pages, 28330 KiB  
Article
Assessment of the Spatiotemporal Dynamics of Suitable Habitats for Typical Halophytic Vegetation in China Based on Maxent Model and Landscape Ecology Theory
by Fuyin Guo, Xiaohuang Liu, Xuehua Chen, Hongyu Li, Zulpiya Mamat, Jiufen Liu, Run Liu, Ran Wang, Liyuan Xing and Junnan Li
Forests 2024, 15(10), 1757; https://doi.org/10.3390/f15101757 (registering DOI) - 6 Oct 2024
Abstract
The widespread and complex formation of saline soils in China significantly affects the sustainable development of regional ecosystems. Intense climate changes and regional land use further exacerbate the uncertainties faced by ecosystems in saline areas. Therefore, studying the distribution characteristics of typical halophytic [...] Read more.
The widespread and complex formation of saline soils in China significantly affects the sustainable development of regional ecosystems. Intense climate changes and regional land use further exacerbate the uncertainties faced by ecosystems in saline areas. Therefore, studying the distribution characteristics of typical halophytic vegetation under the influence of climate change and human activities, and exploring their potential distribution areas, is crucial for maintaining ecological security in saline regions. This study focuses on Tamarix chinensis, Tamarix austromongolica, and Tamarix leptostachya, integrating geographic information systems, remote sensing, species distribution models, and landscape ecological risk (LER) theories and technologies. An optimized MaxEnt model was established using the ENMeval package, incorporating 143, 173, and 213 distribution records and 13 selected environmental variables to simulate the potential suitable habitats of these three Tamarix species. A quantitative assessment of the spatial characteristics and the area of their potential geographical distribution was conducted. Additionally, a landscape ecological risk assessment (LERA) of the highly suitable habitats of these three Tamarix species was performed using land use data from 1980 to 2020, and the results of the LERA were quantified using the Landscape Risk Index (LERI). The results showed that the suitable areas of Tamarix chinensis, Tamarix austromongolica, and Tamarix leptostachya were 9.09 × 105 km2, 6.03 × 105 km2, and 5.20 × 105 km2, respectively, and that the highly suitable habitats for the three species were concentrated in flat areas such as plains and basins. Tamarix austromongolica faced increasing ecological risk in 27.22% of its highly suitable habitat, concentrated in the northern region, followed by Tamarix chinensis in 16.70% of its area with increasing ecological risk, concentrated in the western and northern highly suitable habitats; Tamarix chinensis was the least affected, with an increase in ecological risk in only 1.38% of its area. This study provides valuable insights for the protection of halophytic vegetation, represented by Tamarix, in the context of China’s national land development. Full article
(This article belongs to the Topic Spatial Patterns of Disaster Risk Assessment via Remote Sensing)
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14 pages, 1838 KiB  
Article
Improved Discriminability of Severe Lung Injury and Atelectasis in Thoracic Trauma at Low keV Virtual Monoenergetic Images from Photon-Counting Detector CT
by Hanns Leonhard Kaatsch, Maximilian Franz Völlmecke, Benjamin V. Becker, Daniel Dillinger, Laura Kubitscheck, Aliona Wöhler, Sebastian Schaaf, Joel Piechotka, Christof Schreyer, Robert Schwab, Daniel Overhoff and Stephan Waldeck
Diagnostics 2024, 14(19), 2231; https://doi.org/10.3390/diagnostics14192231 (registering DOI) - 6 Oct 2024
Abstract
Objectives: To evaluate the value of virtual monoenergetic images (VMI) from photon-counting detector CT (PCD-CT) for discriminability of severe lung injury and atelectasis in polytraumatized patients. Materials & Methods: Contrast-enhanced PCD-CT examinations of 20 polytraumatized patients with severe thoracic trauma were [...] Read more.
Objectives: To evaluate the value of virtual monoenergetic images (VMI) from photon-counting detector CT (PCD-CT) for discriminability of severe lung injury and atelectasis in polytraumatized patients. Materials & Methods: Contrast-enhanced PCD-CT examinations of 20 polytraumatized patients with severe thoracic trauma were included in this retrospective study. Spectral PCD-CT data were reconstructed using a noise-optimized virtual monoenergetic imaging (VMI) algorithm with calculated VMIs ranging from 40 to 120 keV at 10 keV increments. Injury-to-atelectasis contrast-to-noise ratio (CNR) was calculated and compared at each energy level based on CT number measurements in severely injured as well as atelectatic lung areas. Three radiologists assessed subjective discriminability, noise perception, and overall image quality. Results: CT values for atelectasis decreased as photon energy increased from 40 keV to 120 keV (mean Hounsfield units (HU): 69 at 40 keV; 342 at 120 keV), whereas CT values for severe lung injury remained near-constant from 40 keV to 120 keV (mean HU: 42 at 40 keV; 44 at 120 keV) with significant differences at each keV level (p < 0.001). The optimal injury-to-atelectasis CNR was observed at 40 keV in comparison with the remaining energy levels (p < 0.001) except for 50 keV (p > 0.05). In line with this, VMIs at 40 keV were rated best regarding subjective discriminability. VMIs at 60–70 keV, however, provided the highest subjective observer parameters regarding subjective image noise as well as image quality. Conclusions: Discriminability between severely injured and atelectatic lung areas after thoracic trauma can be substantially improved by virtual monoenergetic imaging from PCD-CT with superior contrast and visual discriminability at 40–50 keV. Full article
(This article belongs to the Special Issue Cardiothoracic Imaging: Recent Techniques and Applications in Diagnostics, Second Edition)
18 pages, 4420 KiB  
Article
Machine Learning Approach for Arabic Handwritten Recognition
by A. M. Mutawa, Mohammad Y. Allaho and Monirah Al-Hajeri
Appl. Sci. 2024, 14(19), 9020; https://doi.org/10.3390/app14199020 (registering DOI) - 6 Oct 2024
Abstract
Text recognition is an important area of the pattern recognition field. Natural language processing (NLP) and pattern recognition have been utilized efficiently in script recognition. Much research has been conducted on handwritten script recognition. However, the research on the Arabic language for handwritten [...] Read more.
Text recognition is an important area of the pattern recognition field. Natural language processing (NLP) and pattern recognition have been utilized efficiently in script recognition. Much research has been conducted on handwritten script recognition. However, the research on the Arabic language for handwritten text recognition received little attention compared with other languages. Therefore, it is crucial to develop a new model that can recognize Arabic handwritten text. Most of the existing models used to acknowledge Arabic text are based on traditional machine learning techniques. Therefore, we implemented a new model using deep machine learning techniques by integrating two deep neural networks. In the new model, the architecture of the Residual Network (ResNet) model is used to extract features from raw images. Then, the Bidirectional Long Short-Term Memory (BiLSTM) and connectionist temporal classification (CTC) are used for sequence modeling. Our system improved the recognition rate of Arabic handwritten text compared to other models of a similar type with a character error rate of 13.2% and word error rate of 27.31%. In conclusion, the domain of Arabic handwritten recognition is advancing swiftly with the use of sophisticated deep learning methods. Full article
(This article belongs to the Special Issue Applied Intelligence in Natural Language Processing)
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14 pages, 745 KiB  
Review
SGLT2 Inhibitors and the Risk of Contrast-Associated Nephropathy Following Angiographic Intervention: Contradictory Concepts and Clinical Outcomes
by Samuel N. Heyman, Doron Aronson and Zaid Abassi
Int. J. Mol. Sci. 2024, 25(19), 10759; https://doi.org/10.3390/ijms251910759 (registering DOI) - 6 Oct 2024
Abstract
The use of SGLT2 inhibitors (SGLT2is) has been found in large clinical studies to slow the progression of chronic kidney disease (CKD) and to lower the risk of acute kidney injury (AKI). Recent reports suggest that SGLT2is may also reduce the likelihood of [...] Read more.
The use of SGLT2 inhibitors (SGLT2is) has been found in large clinical studies to slow the progression of chronic kidney disease (CKD) and to lower the risk of acute kidney injury (AKI). Recent reports suggest that SGLT2is may also reduce the likelihood of developing radiocontrast-associated nephropathy (CAN) following contrast-enhanced imaging and intravascular interventions. This review underscores potential pitfalls and confounders in these studies and calls for caution in adopting their conclusions regarding the safety and renoprotective potency of SGLT2is, in particular in patients at high risk, with advanced CKD and hemodynamic instability undergoing coronary intervention. This caution is particularly warranted since both SGLT2is and contrast media intensify medullary hypoxia in the already hypoxic diabetic kidney and their combination may lead to medullary hypoxic damage, a principal component of CAN. Further studies are needed to evaluate this dispute, particularly in patients at high risk, and to reveal whether SGLT2is indeed provide renal protection or are hazardous during contrast-enhanced imaging and vascular interventions. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
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15 pages, 1257 KiB  
Article
Cobalt-Doped Hydrochar Derived from Microalgae as an Efficient Peroxymonosulfate Activator for Paraben Degradation
by Chenyan Hu, Suxin Wu, Jiali Wang and Lianguo Chen
Catalysts 2024, 14(10), 695; https://doi.org/10.3390/catal14100695 (registering DOI) - 6 Oct 2024
Abstract
Hydrochar, an attractive member of the carbonaceous materials, is derived from biomass and projects great potential in peroxymonosulfate (PMS) activation, but has not been studied much. Herein, by using the large-scale cultured Chlorella vulgaris and field-collected bloom algae, a series of porous hydrochar [...] Read more.
Hydrochar, an attractive member of the carbonaceous materials, is derived from biomass and projects great potential in peroxymonosulfate (PMS) activation, but has not been studied much. Herein, by using the large-scale cultured Chlorella vulgaris and field-collected bloom algae, a series of porous hydrochar was synthesized via a facile hydrothermal carbonization reaction, while Co doping significantly increased their specific surface areas, carbonization degree, and surface functional groups. These Co-doped hydrochar (xCo-HC, x: amount of the Co precursor) could efficiently activate the PMS, resulting in nearly 100% removal of five common paraben pollutants within 40 min. A dosage of 0.2Co-HC of 0.15 g/L, a PMS concentration of 0.6 g/L, and an unadjusted pH of 6.4 were verified more appropriately for paraben degradation. The coexistence of Cl−, SO42−, and humic acid inhibited the degradation, while HCO3− showed an enhancing effect. No observable change was found at the presence of NO3−. Quenching results illustrated that the produced •SO4− during the conversion of doped Co3+/Co2+ acted as the dominant active species for paraben degradation, while •O2−, 1O2, and •OH contributed relatively less. The algae-based hydrochar potentially facilitated the electron transfer in the xCo-HC/PMS system. Overall, this study develops a new strategy for resource utilization of the abundant algae. Full article
(This article belongs to the Special Issue Porous Materials as Efficient Catalysts: Synthesis, Characterization and Applications)
17 pages, 2422 KiB  
Article
A “Region-Specific Model Adaptation (RSMA)”-Based Training Data Method for Large-Scale Land Cover Mapping
by Congcong Li, George Xian and Suming Jin
Remote Sens. 2024, 16(19), 3717; https://doi.org/10.3390/rs16193717 (registering DOI) - 6 Oct 2024
Abstract
An accurate and historical land cover monitoring dataset for Alaska could provide fundamental information for a range of studies, such as conservation habitats, biogeochemical cycles, and climate systems, in this distinctive region. This research addresses challenges associated with the extraction of training data [...] Read more.
An accurate and historical land cover monitoring dataset for Alaska could provide fundamental information for a range of studies, such as conservation habitats, biogeochemical cycles, and climate systems, in this distinctive region. This research addresses challenges associated with the extraction of training data for timely and accurate land cover classifications in Alaska over longer time periods (e.g., greater than 10 years). Specifically, we designed the “Region-Specific Model Adaptation (RSMA)” method for training data. The method integrates land cover information from the National Land Cover Database (NLCD), LANDFIRE’s Existing Vegetation Type (EVT), and the National Wetlands Inventory (NWI) and machine learning techniques to generate robust training samples based on the Anderson Level II classification legend. The assumption of the method is that spectral signatures vary across regions because of diverse land surface compositions; however, despite these variations, there are consistent, collective land cover characteristics that span the entire region. Building upon this assumption, this research utilized the classification power of deep learning algorithms and the generalization ability of RSMA to construct a model for the RSMA method. Additionally, we interpreted existing vegetation plot information for land cover labels as validation data to reduce inconsistency in the human interpretation. Our validation results indicate that the RSMA method improved the quality of the training data derived solely from the NLCD by approximately 30% for the overall accuracy. The validation assessment also demonstrates that the RSMA method can generate reliable training data on large scales in regions that lack sufficient reliable data. Full article
(This article belongs to the Special Issue Advances of Remote Sensing in Land Cover and Land Use Mapping)
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