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13 pages, 1105 KiB  
Article
Route Planning Algorithms for Fleets of Connected Vehicles: State of the Art, Implementation, and Deployment
by Mattia D’Emidio, Esmaeil Delfaraz, Gabriele Di Stefano, Giannantonio Frittella and Edgardo Vittoria
Appl. Sci. 2024, 14(7), 2884; https://doi.org/10.3390/app14072884 (registering DOI) - 29 Mar 2024
Abstract
The introduction of 5G technologies has enabled the possibility of designing and building several new classes of networked information systems that were previously impossible to implement due to limitations on data throughput or the reliability of transmission channels. Among them, one of the [...] Read more.
The introduction of 5G technologies has enabled the possibility of designing and building several new classes of networked information systems that were previously impossible to implement due to limitations on data throughput or the reliability of transmission channels. Among them, one of the most interesting and successful examples with a highly positive impact in terms of the quality of urban environments and societal and economical welfare is a system of semi-autonomous connected vehicles, where IoT devices, data centers, and fleets of smart vehicles equipped with communication and computational resources are combined into a heterogeneous and distributed infrastructure, unifying hardware, networks, and software. In order to efficiently provide various services (e.g., patrolling, pickup and delivery, monitoring), these systems typically rely on collecting and broadcasting large amounts of data (e.g., sensor data, GPS traces, or maps), which need to be properly collected and processed in a timely manner. As is well documented in the literature, one of the most effective ways to achieve this purpose, especially in a real-time context, is to adopt a graph model of the data (e.g., to model communication networks, roads, or interactions between vehicles) and to employ suitable graph algorithms to solve properly defined computational problems of interest (e.g., shortest paths or distributed consensus). While research in this context has been extensive from a theoretical perspective, works that have focused on the implementation, deployment, and evaluation of the practical performance of graph algorithms for real-world systems of autonomous vehicles have been much rarer. In this paper, we present a study of this kind. Specifically, we first describe the main features of a real-world information system employing semi-autonomous connected vehicles that is currently being tested in the city of L’Aquila (Italy). Then, we present an overview of the computational challenges arising in the considered application domain and provide a systematic survey of known algorithmic results for one of the most relevant classes of computational problems that have to be addressed in said domain, namely, pickup and delivery problems. Finally, we discuss implementation issues, adopted software tools, and the deployment and testing phases concerning one of the algorithmic components of the mentioned real-world system dedicated to handling a specific problem of the above class, namely, the pickup and delivery multi-vehicle problem with time windows. Full article
(This article belongs to the Special Issue Advanced Technologies in Automated Driving)
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13 pages, 673 KiB  
Article
Pulmonary Hypertension and the Risk of 30-Day Postoperative Pulmonary Complications after Gastrointestinal Surgical or Endoscopic Procedures: A Retrospective Propensity Score-Weighted Cohort Analysis
by Yoshio Tatsuoka, Zyad J. Carr, Sachidhanand Jayakumar, Hung-Mo Lin, Zili He, Adham Farroukh and Paul Heerdt
J. Clin. Med. 2024, 13(7), 1996; https://doi.org/10.3390/jcm13071996 (registering DOI) - 29 Mar 2024
Abstract
Background: Pulmonary hypertension (PH) patients are at higher risk of postoperative complications. We analyzed the association of PH with 30-day postoperative pulmonary complications (PPCs). Methods: A single-center propensity score overlap weighting (OW) retrospective cohort study was conducted on 164 patients with [...] Read more.
Background: Pulmonary hypertension (PH) patients are at higher risk of postoperative complications. We analyzed the association of PH with 30-day postoperative pulmonary complications (PPCs). Methods: A single-center propensity score overlap weighting (OW) retrospective cohort study was conducted on 164 patients with a mean pulmonary artery pressure (mPAP) of >20 mmHg within 24 months of undergoing elective inpatient abdominal surgery or endoscopic procedures under general anesthesia and a control cohort (N = 1981). The primary outcome was PPCs, and the secondary outcomes were PPC sub-composites, namely respiratory failure (RF), pneumonia (PNA), aspiration pneumonia/pneumonitis (ASP), pulmonary embolism (PE), length of stay (LOS), and 30-day mortality. Results: PPCs were higher in the PH cohort (29.9% vs. 11.2%, p < 0.001). When sub-composites were analyzed, higher rates of RF (19.3% vs. 6.6%, p < 0.001) and PNA (11.2% vs. 5.7%, p = 0.01) were observed. After OW, PH was still associated with greater PPCs (RR 1.66, 95% CI (1.05–2.71), p = 0.036) and increased LOS (median 8.0 days vs. 4.9 days) but not 30-day mortality. Sub-cohort analysis showed no difference in PPCs between pre- and post-capillary PH patients. Conclusions: After covariate balancing, PH was associated with a higher risk for PPCs and prolonged LOS. This elevated PPC risk should be considered during preoperative risk assessment. Full article
(This article belongs to the Special Issue Advances in the Clinical Management of Perioperative Anesthesia)
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46 pages, 6832 KiB  
Review
A Comprehensive Review of Bimetallic Nanoparticle–Graphene Oxide and Bimetallic Nanoparticle–Metal–Organic Framework Nanocomposites as Photo-, Electro-, and Photoelectrocatalysts for Hydrogen Evolution Reaction
by Mogwasha Dapheny Makhafola, Sheriff Aweda Balogun and Kwena Desmond Modibane
Energies 2024, 17(7), 1646; https://doi.org/10.3390/en17071646 (registering DOI) - 29 Mar 2024
Abstract
This review extensively discusses current developments in bimetallic nanoparticle–GO and bimetallic nanoparticle–MOF nanocomposites as potential catalysts for HER, along with their different synthesis methodologies, structural characteristics, and catalytic mechanisms. The photoelectrocatalytic performance of these catalysts was also compared based on parameters such as [...] Read more.
This review extensively discusses current developments in bimetallic nanoparticle–GO and bimetallic nanoparticle–MOF nanocomposites as potential catalysts for HER, along with their different synthesis methodologies, structural characteristics, and catalytic mechanisms. The photoelectrocatalytic performance of these catalysts was also compared based on parameters such as Tafel slope, current density, onset potential, turnover frequency, hydrogen yield, activation energy, stability, and durability. The review shows that the commonly used metal alloys in the bimetallic nanoparticle–GO-based catalysts for HERs include Pt-based alloys (e.g., PtNi, PtCo, PtCu, PtAu, PtSn), Pd-based alloys (e.g., PdAu, PdAg, PdPt) or other combinations, such as AuNi, AuRu, etc., while the most used electrolyte sources are H2SO4 and KOH. For the bimetallic nanoparticle MOF-based catalysts, Pt-based alloys (e.g., PtNi, PtCu), Pd-based alloys (e.g., PdAg, PdCu, PdCr), and Ni-based alloys (e.g., NiMo, NiTi, NiAg, NiCo) took the lead, with KOH being the most frequently used electrolyte source. Lastly, the review addresses challenges and prospects, highlighting opportunities for further optimization and technological integration of the catalysts as promising alternative photo/electrocatalysts for future hydrogen production and storage. Full article
(This article belongs to the Section A5: Hydrogen Energy)
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16 pages, 633 KiB  
Article
Influential Metrics Estimation and Dynamic Frequency Selection Based on Two-Dimensional Mapping for JPEG-Reversible Data Hiding
by Haiyong Wang and Chentao Lu
Entropy 2024, 26(4), 301; https://doi.org/10.3390/e26040301 (registering DOI) - 29 Mar 2024
Abstract
JPEG Reversible Data Hiding (RDH) is a method designed to extract hidden data from a marked image and perfectly restore the image to its original JPEG form. However, while existing RDH methods adaptively manage the visual distortion caused by embedded data, they often [...] Read more.
JPEG Reversible Data Hiding (RDH) is a method designed to extract hidden data from a marked image and perfectly restore the image to its original JPEG form. However, while existing RDH methods adaptively manage the visual distortion caused by embedded data, they often neglect the concurrent increase in file size. In rectifying this oversight, we have designed a new JPEG RDH scheme that addresses all influential metrics during the embedding phase and a dynamic frequency selection strategy with recoverable frequency order after data embedding. The process initiates with a pre-processing phase of blocks and the subsequent selection of frequencies. Utilizing a two-dimensional (2D) mapping strategy, we then compute the visual distortion and file size increment (FSI) for each image block by examining non-zero alternating current (AC) coefficient pairs (NZACPs) and their corresponding run lengths. Finally, we select appropriate block groups based on the influential metrics of each block group and proceed with data embedding by 2D histogram shifting (HS). Extensive experimentation demonstrates how our method’s efficiently and consistently outperformed existing techniques with a superior peak signal-to-noise Ratio (PSNR) and optimized FSI. Full article
(This article belongs to the Special Issue Information Theory and Coding for Image/Video Processing)
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17 pages, 3458 KiB  
Article
Straw Addition Enhances Crop Yield, Soil Aggregation, and Soil Microorganisms in a 14-Year Wheat–Rice Rotation System in Central China
by Bo Liu, Hao Xia, Chaoqiang Jiang, Cuncang Jiang, Muhammad Riaz, Li Yang, Yunfeng Chen, Xianpeng Fan, Zhiyi Zhang, Xiaoli Duan, Maoqian Wu and Xiange Xia
Plants 2024, 13(7), 985; https://doi.org/10.3390/plants13070985 (registering DOI) - 29 Mar 2024
Abstract
Straw return utilizes waste resources to reduce the use of chemical fertilizers worldwide. However, information is still lacking on the relative impact of straw return on soil fertility, the nutrient composition of different soil aggregates, and soil microbial communities. Therefore, this study aimed [...] Read more.
Straw return utilizes waste resources to reduce the use of chemical fertilizers worldwide. However, information is still lacking on the relative impact of straw return on soil fertility, the nutrient composition of different soil aggregates, and soil microbial communities. Therefore, this study aimed to understand the effects of different management practices on the crop yield, soil fertility, and soil community composition in a 14-year wheat–rice rotation system. The treatments included a control (without fertilizer and straw addition), chemical fertilization (NPK), straw return without fertilizer (S), and straw addition with chemical fertilizer (NPKS). The results showed that NPKS improved the wheat and rice yield by 185.12% and 88.02%, respectively, compared to the CK treatment. Additionally, compared to the CK treatment, the N, P, and K contents of the wheat stem were increased by 39.02%, 125%, and 20.23% under the NPKS treatment. Compared to the CK treatment, SOM, TN, TP, AN, AP, AK, CEC, AFe, AMn, ACu, and AZn were increased by 49.12%, 32.62%, 35.06%, 22.89%, 129.36%, 48.34%, 13.40%, 133.95%, 58.98%, 18.26% and 33.33% under the NPKS treatment, respectively. Moreover, straw addition promoted the creation and stabilization of macro-aggregates in crop soils. The relative abundance of macro-aggregates (0.25–2 mm) increased from 37.49% to 52.97%. Straw addition was associated with a higher proportion of aromatic and carbonyl carbon groups in the soil, which, in turn, promoted the formation of macro-aggregates. Redundancy analysis showed that straw return significantly increased the microbial community diversity. These findings demonstrate that straw addition together with chemical fertilizer could increase the crop yield by improving soil fertility, soil aggregate stability, and the diversity of fungi. Full article
(This article belongs to the Section Plant–Soil Interactions)
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21 pages, 12915 KiB  
Article
An Integrated Duranton and Overman Index and Local Duranton and Overman Index Framework for Industrial Spatial Agglomeration Pattern Analysis
by Yupu Huang, Li Zhuo and Jingjing Cao
ISPRS Int. J. Geo-Inf. 2024, 13(4), 116; https://doi.org/10.3390/ijgi13040116 (registering DOI) - 29 Mar 2024
Abstract
Accurately measuring industrial spatial agglomeration patterns is crucial for promoting regional economic development. However, few studies have considered both agglomeration degrees and cluster locations of industries. Moreover, the traditional multi-scale cluster location mining (MCLM) method still has limitations in terms of accuracy, parameter [...] Read more.
Accurately measuring industrial spatial agglomeration patterns is crucial for promoting regional economic development. However, few studies have considered both agglomeration degrees and cluster locations of industries. Moreover, the traditional multi-scale cluster location mining (MCLM) method still has limitations in terms of accuracy, parameter setting, calculation efficiency, etc. This study proposes a new framework for analyzing industrial spatial agglomeration patterns, which uses the Duranton and Overman (DO) index for estimating agglomeration degrees and a newly developed local DO (LDO) index for mining cluster locations. The MCLM-LDO method was proposed by incorporating the LDO index into the MCLM method, and it was validated via comparisons with three baseline methods based on two synthetic datasets. The results proved that the MCLM-LDO method can achieve accuracies of 0.945 and 1 with computational times of 0.15 s and 0.11 s on two datasets, which are superior to existing MCLM methods. The proposed framework was further applied to analyze the spatial agglomeration patterns of the industry of computer, communication, and other electronic equipment manufacturing in Guangdong Province, China. The results showed that the framework gives a more holistic perspective of spatial agglomeration patterns, which can serve as more meaningful references for industrial sustainable development. Full article
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17 pages, 595 KiB  
Article
A Content Analysis of Online Messages about Sugar-Sweetened Beverages
by Yingke Li, Lijiang Shen, James Price Dillard and Shu (Scott) Li
Nutrients 2024, 16(7), 1005; https://doi.org/10.3390/nu16071005 (registering DOI) - 29 Mar 2024
Abstract
Media campaigns can reduce or promote the consumption of sugar-sweetened beverages (SSBs). Brief, US-based English-language online messages were gathered from searchable media platforms, a process that yielded 112 anti-SSB videos and 29 pro-SSB commercials. Using a combination of inductive and deductive methods, a [...] Read more.
Media campaigns can reduce or promote the consumption of sugar-sweetened beverages (SSBs). Brief, US-based English-language online messages were gathered from searchable media platforms, a process that yielded 112 anti-SSB videos and 29 pro-SSB commercials. Using a combination of inductive and deductive methods, a content analysis of those messages was conducted to identify their properties. They were coded for the direction (pro vs. anti), target of the advocacy (e.g., consumption vs. policy), actor demographics (gender, age, and ethnicity), persuasive theme (e.g., excessive sugar, nurturing), and message sensation value. Anti-SSB appeals primarily targeted individual-level consumption behavior. They utilized six persuasive themes and often included more than one theme in a single message. Pro-SSB messages used feel-good themes and utilized only one theme per message. The proportions of adults, adolescents, and children differed by the direction of the advocacy. Black, Hispanic, and Asian actors were under-represented in the anti-SSB sample relative to Whites. Pro-SSB appeals were slightly higher than anti-SSB appeals in message sensation value (p = 0.09). The findings illuminate the message features that characterize the universe of brief anti-SSB appeals available online, highlight messaging disparities, and reveal the absence of certain common, effective persuasive themes. Full article
(This article belongs to the Section Nutrition and Public Health)
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12 pages, 3169 KiB  
Article
Phonon Pseudoangular Momentum in α-MoO3
by Meiqi Li, Zhibing Li, Huanjun Chen and Weiliang Wang
Nanomaterials 2024, 14(7), 607; https://doi.org/10.3390/nano14070607 (registering DOI) - 29 Mar 2024
Abstract
In recent studies, it has been discovered that phonons can carry angular momentum, leading to a series of investigations into systems with three-fold rotation symmetry. However, for systems with two-fold screw rotational symmetry, such as α-MoO3, there has been no relevant [...] Read more.
In recent studies, it has been discovered that phonons can carry angular momentum, leading to a series of investigations into systems with three-fold rotation symmetry. However, for systems with two-fold screw rotational symmetry, such as α-MoO3, there has been no relevant discussion. In this paper, we investigated the pseudoangular momentum of phonons in crystals with two-fold screw rotational symmetry. Taking α-MoO3 as an example, we explain the selection rules in circularly polarized Raman experiments resulting from pseudoangular momentum conservation, providing important guidance for experiments. This study of pseudoangular momentum in α-MoO3 opens up a new degree of freedom for its potential applications, expanding into new application domains. Full article
(This article belongs to the Section Nanophotonics Materials and Devices)
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15 pages, 845 KiB  
Review
Composition and Function of Neutrophil Extracellular Traps
by Yijie Wang, Chunjing Du, Yue Zhang and Liuluan Zhu
Biomolecules 2024, 14(4), 416; https://doi.org/10.3390/biom14040416 (registering DOI) - 29 Mar 2024
Abstract
Neutrophil extracellular traps (NETs) are intricate fibrous structures released by neutrophils in response to specific stimuli. These structures are composed of depolymerized chromatin adorned with histones, granule proteins, and cytosolic proteins. NETs are formed via two distinct pathways known as suicidal NETosis, which [...] Read more.
Neutrophil extracellular traps (NETs) are intricate fibrous structures released by neutrophils in response to specific stimuli. These structures are composed of depolymerized chromatin adorned with histones, granule proteins, and cytosolic proteins. NETs are formed via two distinct pathways known as suicidal NETosis, which involves NADPH oxidase (NOX), and vital NETosis, which is independent of NOX. Certain proteins found within NETs exhibit strong cytotoxic effects against both pathogens and nearby host cells. While NETs play a defensive role against pathogens, they can also contribute to tissue damage and worsen inflammation. Despite extensive research on the pathophysiological role of NETs, less attention has been paid to their components, which form a unique structure containing various proteins that have significant implications in a wide range of diseases. This review aims to elucidate the components of NETs and provide an overview of their impact on host defense against invasive pathogens, autoimmune diseases, and cancer. Full article
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17 pages, 1539 KiB  
Article
Comprehensive Genome-Wide Natural Variation and Expression Analysis of Tubby-like Proteins Gene Family in Brachypodium distachyon
by Sendi Mejia, Jose Lorenzo B. Santos and Christos Noutsos
Plants 2024, 13(7), 987; https://doi.org/10.3390/plants13070987 (registering DOI) - 29 Mar 2024
Abstract
The Tubby-like proteins (TLPs) gene family is a group of transcription factors found in both animals and plants. In this study, we identified twelve B. distachyon TLPs, divided into six groups based on conserved domains and evolutionary relationships. We predicted cis-regulatory elements involved [...] Read more.
The Tubby-like proteins (TLPs) gene family is a group of transcription factors found in both animals and plants. In this study, we identified twelve B. distachyon TLPs, divided into six groups based on conserved domains and evolutionary relationships. We predicted cis-regulatory elements involved in light, hormone, and biotic and abiotic stresses. The expression patterns in response to light and hormones revealed that BdTLP3, 4, 7, and 14 are involved in light responses, and BdTLP1 is involved in ABA responses. Furthermore, BdTLP2, 7, 9, and 13 are expressed throughout vegetative and reproductive stages, whereas BdTLP1, 3, 5, and 14 are expressed at germinating grains and early vegetative development, and BdTLP4, 6, 8, and 10 are expressed at the early reproduction stage. The natural variation in the eleven most diverged B. distachyon lines revealed high conservation levels of BdTLP1-6 to high variation in BdTLP7-14 proteins. Based on diversifying selection, we identified amino acids in BdTLP1, 3, 8, and 13, potentially substantially affecting protein functions. This analysis provided valuable information for further functional studies to understand the regulation, pathways involved, and mechanism of BdTLPs. Full article
(This article belongs to the Section Plant Genetics, Genomics and Biotechnology)
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14 pages, 301 KiB  
Review
Clinical Significance and Remaining Issues of Anti-HBc Antibody and HBV Core-Related Antigen
by Yoshihiko Yano, Itsuko Sato, Takamitsu Imanishi, Ryutaro Yoshida, Takanori Matsuura, Yoshihide Ueda and Yuzo Kodama
Diagnostics 2024, 14(7), 728; https://doi.org/10.3390/diagnostics14070728 (registering DOI) - 29 Mar 2024
Abstract
Currently, hepatitis B virus (HBV) core antibody (anti-HBc antibody) and HBV core-related antigen (HBcrAg) are widely used as serum markers for diagnosis based on the HBV core region. This review focused on anti-HBc antibodies and HBcrAg and aimed to summarize the clinical significance [...] Read more.
Currently, hepatitis B virus (HBV) core antibody (anti-HBc antibody) and HBV core-related antigen (HBcrAg) are widely used as serum markers for diagnosis based on the HBV core region. This review focused on anti-HBc antibodies and HBcrAg and aimed to summarize the clinical significance of currently used assay systems and the issues involved. While anti-HBc is very significant for clinical diagnosis, the clinical significance of quantitative assay of anti-HBc antibody has been reevaluated with improvements in diagnostic performance, including its association with clinical stage and prediction of carcinogenesis and reactivation. In addition, concerning the new HBcrAg, a high-sensitivity assay method has recently been established, and its diagnostic significance, including the prediction of reactivation, is being reevaluated. On the other hand, the quantitative level of anti-HBc antibody expressed in different units among assay systems complicates the interpretation of the results. However, it is difficult to standardize assay systems as they vary in advantages, and caution is needed in interpreting the assay results. In conclusion, with the development of highly sensitive HBcrAg and anti-HBc antibody, a rapid and sensitive detection assay system has been developed and used in clinical practice. In the future, it is hoped that a global standard will be created based on the many clinical findings. Full article
23 pages, 1640 KiB  
Review
Blue Biotechnology: Marine Bacteria Bioproducts
by Karina Maldonado-Ruiz, Ruth Pedroza-Islas and Lorena Pedraza-Segura
Microorganisms 2024, 12(4), 697; https://doi.org/10.3390/microorganisms12040697 (registering DOI) - 29 Mar 2024
Abstract
The ocean is the habitat of a great number of organisms with different characteristics. Compared to terrestrial microorganisms, marine microorganisms also represent a vast and largely unexplored reservoir of bioactive compounds with diverse industrial applications like terrestrial microorganisms. This review examines the properties [...] Read more.
The ocean is the habitat of a great number of organisms with different characteristics. Compared to terrestrial microorganisms, marine microorganisms also represent a vast and largely unexplored reservoir of bioactive compounds with diverse industrial applications like terrestrial microorganisms. This review examines the properties and potential applications of products derived from marine microorganisms, including bacteriocins, enzymes, exopolysaccharides, and pigments, juxtaposing them in some cases against their terrestrial counterparts. We discuss the distinct characteristics that set marine-derived products apart, including enhanced stability and unique structural features such as the amount of uronic acid and sulfate groups in exopolysaccharides. Further, we explore the uses of these marine-derived compounds across various industries, ranging from food and pharmaceuticals to cosmetics and biotechnology. This review also presents a broad description of biotechnologically important compounds produced by bacteria isolated from marine environments, some of them with different qualities compared to their terrestrial counterparts. Full article
(This article belongs to the Special Issue Bioactive Molecules from Microbial Sources)
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21 pages, 7653 KiB  
Article
The Use of Virtual Tissue Constructs That Include Morphological Variability to Assess the Potential of Electrical Impedance Spectroscopy to Differentiate between Thyroid and Parathyroid Tissues during Surgery
by Malwina Matella, Keith Hunter, Saba Balasubramanian and Dawn Walker
Sensors 2024, 24(7), 2198; https://doi.org/10.3390/s24072198 (registering DOI) - 29 Mar 2024
Abstract
Electrical impedance spectroscopy (EIS) has been proposed as a promising noninvasive method to differentiate healthy thyroid from parathyroid tissues during thyroidectomy. However, previously reported similarities in the in vivo measured spectra of these tissues during a pilot study suggest that this separation may [...] Read more.
Electrical impedance spectroscopy (EIS) has been proposed as a promising noninvasive method to differentiate healthy thyroid from parathyroid tissues during thyroidectomy. However, previously reported similarities in the in vivo measured spectra of these tissues during a pilot study suggest that this separation may not be straightforward. We utilise computational modelling as a method to elucidate the distinguishing characteristics in the EIS signal and explore the features of the tissue that contribute to the observed electrical behaviour. Firstly, multiscale finite element models (or ‘virtual tissue constructs’) of thyroid and parathyroid tissues were developed and verified against in vivo tissue measurements. A global sensitivity analysis was performed to investigate the impact of physiological micro-, meso- and macroscale tissue morphological features of both tissue types on the computed macroscale EIS spectra and explore the separability of the two tissue types. Our results suggest that the presence of a surface fascia layer could obstruct tissue differentiation, but an analysis of the separability of simulated spectra without the surface fascia layer suggests that differentiation of the two tissue types should be possible if this layer is completely removed by the surgeon. Comprehensive in vivo measurements are required to fully determine the potential for EIS as a method in distinguishing between thyroid and parathyroid tissues. Full article
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16 pages, 24589 KiB  
Article
Prediction of Sea Surface Temperature Using U-Net Based Model
by Jing Ren, Changying Wang, Ling Sun, Baoxiang Huang, Deyu Zhang, Jiadong Mu and Jianqiang Wu
Remote Sens. 2024, 16(7), 1205; https://doi.org/10.3390/rs16071205 (registering DOI) - 29 Mar 2024
Abstract
Sea surface temperature (SST) is a key parameter in ocean hydrology. Currently, existing SST prediction methods fail to fully utilize the potential spatial correlation between variables. To address this challenge, we propose a spatiotenporal UNet (ST-UNet) model based on the UNet model. In [...] Read more.
Sea surface temperature (SST) is a key parameter in ocean hydrology. Currently, existing SST prediction methods fail to fully utilize the potential spatial correlation between variables. To address this challenge, we propose a spatiotenporal UNet (ST-UNet) model based on the UNet model. In particular, in the encoding phase of ST-UNet, we use parallel convolution with different kernel sizes to efficiently extract spatial features, and use ConvLSTM to capture temporal features based on the utilization of spatial features. Atrous Spatial Pyramid Pooling (ASPP) module is placed at the bottleneck of the network to further incorporate the multi-scale features, allowing the spatial features to be fully utilized. The final prediction is then generated in the decoding stage using parallel convolution with different kernel sizes similar to the encoding stage. We conducted a series of experiments on the Bohai Sea and Yellow Sea SST data set, as well as the South China Sea SST data set, using SST data from the past 35 days to predict SST data for 1, 3, and 7 days in the future. The model was trained using data spanning from 2010 to 2021, with data from 2022 being utilized to assess the model’s predictive performance. The experimental results show that the model proposed in this research paper achieves excellent results at different prediction scales in both sea areas, and the model consistently outperforms other methods. Specifically, in the Bohai Sea and Yellow Sea sea areas, when the prediction scales are 1, 3, and 7 days, the MAE of ST-UNet outperforms the best results of the other three compared models by 17%, 12%, and 2%, and the MSE by 16%, 18%, and 9%, respectively. In the South China Sea, when the prediction ranges are 1, 3, and 7 days, the MAE of ST-UNet is 27%, 18%, and 3% higher than the best of the other three compared models, and the MSE is 46%, 39%, and 16% higher, respectively. Our results highlight the effectiveness of the ST-UNet model in capturing spatial correlations and accurately predicting SST. The proposed model is expected to improve marine hydrographic studies. Full article
(This article belongs to the Special Issue Artificial Intelligence and Big Data for Oceanography)
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19 pages, 5712 KiB  
Article
Soil Sampling Map Optimization with a Dual Deep Learning Framework
by Tan-Hanh Pham and Kim-Doang Nguyen
Mach. Learn. Knowl. Extr. 2024, 6(2), 751-769; https://doi.org/10.3390/make6020035 (registering DOI) - 29 Mar 2024
Abstract
Soil sampling constitutes a fundamental process in agriculture, enabling precise soil analysis and optimal fertilization. The automated selection of accurate soil sampling locations representative of a given field is critical for informed soil treatment decisions. This study leverages recent advancements in deep learning [...] Read more.
Soil sampling constitutes a fundamental process in agriculture, enabling precise soil analysis and optimal fertilization. The automated selection of accurate soil sampling locations representative of a given field is critical for informed soil treatment decisions. This study leverages recent advancements in deep learning to develop efficient tools for generating soil sampling maps. We proposed two models, namely UDL and UFN, which are the results of innovations in machine learning architecture design and integration. The models are meticulously trained on a comprehensive soil sampling dataset collected from local farms in South Dakota. The data include five key attributes: aspect, flow accumulation, slope, normalized difference vegetation index, and yield. The inputs to the models consist of multispectral images, and the ground truths are highly unbalanced binary images. To address this challenge, we innovate a feature extraction technique to find patterns and characteristics from the data before using these refined features for further processing and generating soil sampling maps. Our approach is centered around building a refiner that extracts fine features and a selector that utilizes these features to produce prediction maps containing the selected optimal soil sampling locations. Our experimental results demonstrate the superiority of our tools compared to existing methods. During testing, our proposed models exhibit outstanding performance, achieving the highest mean Intersection over Union of 60.82% and mean Dice Coefficient of 73.74%. The research not only introduces an innovative tool for soil sampling but also lays the foundation for the integration of traditional and modern soil sampling methods. This work provides a promising solution for precision agriculture and soil management. Full article
(This article belongs to the Topic Applications in Image Analysis and Pattern Recognition)
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16 pages, 3300 KiB  
Article
Myocardial Expression of Pluripotency, Longevity, and Proinflammatory Genes in the Context of Hypercholesterolemia and Statin Treatment
by Konstantinos S. Mylonas, Michail Peroulis, Emmanouil I. Kapetanakis and Alkistis Kapelouzou
J. Clin. Med. 2024, 13(7), 1994; https://doi.org/10.3390/jcm13071994 (registering DOI) - 29 Mar 2024
Abstract
Background: This study sought to assess the effect of statin therapy on myocardial inflammation in a White New Zealand rabbit model of atherogenesis. Methods: The mRNA expression levels of pro-inflammatory, pluripotency, and aging-related markers were quantified following a controlled feeding protocol and statin [...] Read more.
Background: This study sought to assess the effect of statin therapy on myocardial inflammation in a White New Zealand rabbit model of atherogenesis. Methods: The mRNA expression levels of pro-inflammatory, pluripotency, and aging-related markers were quantified following a controlled feeding protocol and statin treatments. Results: Following high-cholesterol diet induction, we observed significant upregulation in the myocardial mRNA levels of MYD88, NF-κB, chemokines (CCL4, CCL20, and CCR2), IFN-γ, interleukins (IL-1β, IL-2, IL-4, IL-8, IL-10, and IL-18), and novel markers (klotho, KFL4, NANOG, and HIF1α). In contrast, HOXA5 expression was diminished following a hyperlipidemic diet. Both statin treatments significantly influenced the markers studied. Nevertheless, rosuvastatin administration resulted in a greater reduction in MYD88, NF-kB, chemokines (CCL4, CCL20, and CCR2), and interleukins IL-1β, IL-8, KLF4, NANOG, and HIF1α than fluvastatin. Fluvastatin, on the other hand, led to a stronger decrease in IL-4. Downregulation of IL-2 and IL-18 and upregulation of IFNβ and HOXA5 were comparable between the two statins. Notably, rosuvastatin had a stronger effect on the upregulation of klotho and IL-10. Conclusion: Overall, statin therapy significantly attenuated inflammatory, pluripotency, and klotho expression in myocardial tissue under atherogenic conditions. Our findings also highlight the differential efficacy of rosuvastatin over fluvastatin in curtailing proatherogenic inflammation, which could have profound implications for the clinical management of cardiovascular disease. Full article
(This article belongs to the Special Issue Clinical Advances in Diagnosis and Management of Atherosclerosis)
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11 pages, 5484 KiB  
Article
Optimizing the Structure and Optical Properties of Lanthanum Aluminate Perovskite through Nb5+ Doping
by Wei Liu, Yang Zou, Yuang Chen, Zijian Lei, Lili Zhao and Lixin Song
Nanomaterials 2024, 14(7), 608; https://doi.org/10.3390/nano14070608 (registering DOI) - 29 Mar 2024
Abstract
This work involves the introduction of niobium oxide into lanthanum aluminate (LaAlO3) via a conventional solid-state reaction technique to yield LaAlO3:Nb (LaNbxAl1−xO3+δ) samples with Nb5+ doping levels ranging from 0.00 to [...] Read more.
This work involves the introduction of niobium oxide into lanthanum aluminate (LaAlO3) via a conventional solid-state reaction technique to yield LaAlO3:Nb (LaNbxAl1−xO3+δ) samples with Nb5+ doping levels ranging from 0.00 to 0.25 mol%. This study presents a comprehensive investigation of the effects of niobium doping on the phase evolution, defect control, and reflectance of LaNbxAl1−xO3+δ powder. Powder X-ray diffraction (XRD) analysis confirms the perovskite structure in all powders, and XRD and transmission electron microscopy (TEM) reveal successful doping of Nb5+ into LaNbxAl1−xO3+δ. The surface morphology was analyzed by scanning electron microscopy (SEM), and the results show that increasing the doping concentration of niobium leads to fewer microstructural defects. Oxygen vacancy defects in different compositions are analyzed at 300 K, and as the doping level increases, a clear trend of defect reduction is observed. Notably, LaNbxAl1−xO3+δ with 0.15 mol% Nb5+ exhibits excellent reflectance properties, with a maximum infrared reflectance of 99.7%. This study shows that LaNbxAl1−xO3+δ powder materials have wide application potential in the field of high reflectivity coating materials due to their extremely low microstructural defects and oxygen vacancy defects. Full article
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12 pages, 271 KiB  
Article
Healthcare Utilization (HCU) Reduction with High-Frequency (10 kHz) Spinal Cord Stimulation (SCS) Therapy
by Vinicius Tieppo Francio, Logan Leavitt, John Alm, Daniel Mok, Byung-jo Victor Yoon, Niaman Nazir, Christopher M. Lam, Usman Latif, Timothy Sowder, Edward Braun, Andrew Sack, Talal W. Khan and Dawood Sayed
Healthcare 2024, 12(7), 745; https://doi.org/10.3390/healthcare12070745 (registering DOI) - 29 Mar 2024
Abstract
Spinal cord stimulation (SCS) is a well-established treatment for patients with chronic pain. With increasing healthcare costs, it is important to determine the benefits of SCS in healthcare utilization (HCU). This retrospective, single-center observational study involved 160 subjects who underwent implantation of a [...] Read more.
Spinal cord stimulation (SCS) is a well-established treatment for patients with chronic pain. With increasing healthcare costs, it is important to determine the benefits of SCS in healthcare utilization (HCU). This retrospective, single-center observational study involved 160 subjects who underwent implantation of a high-frequency (10 kHz) SCS device. We focused on assessing trends in HCU by measuring opioid consumption in morphine milligram equivalents (MME), as well as monitoring emergency department (ED) and office visits for interventional pain procedures during the 12-month period preceding and following the SCS implant. Our results revealed a statistically significant reduction in HCU in all domains assessed. The mean MME was 51.05 and 26.52 pre- and post-implant, respectively. There was a 24.53 MME overall decrease and a mean of 78.2% statistically significant dose reduction (p < 0.0001). Of these, 91.5% reached a minimally clinically important difference (MCID) in opioid reduction. Similarly, we found a statistically significant (p < 0.01) decrease in ED visits, with a mean of 0.12 pre- and 0.03 post-implant, and a decrease in office visits for interventional pain procedures from a 1.39 pre- to 0.28 post-10 kHz SCS implant, representing a 1.11 statistically significant (p < 0.0001) mean reduction. Our study reports the largest cohort of real-world data published to date analyzing HCU trends with 10 kHz SCS for multiple pain etiologies. Furthermore, this is the first and only study evaluating HCU trends with 10 kHz SCS by assessing opioid use, ED visits, and outpatient visits for interventional pain procedures collectively. Preceding studies have individually investigated these outcomes, consistently yielding positive results comparable to our findings. Full article
(This article belongs to the Special Issue Pain Management in Healthcare Practice)
15 pages, 4400 KiB  
Article
Short Working Memory Impairment Associated with Hippocampal Microglia Activation in Chronic Hepatic Encephalopathy
by Bilal El-Mansoury, Kamal Smimih, Abdelaati El Khiat, Ahmed Draoui, Abdelmohcine Aimrane, Redouane Chatoui, Abdesslam Ferssiwi, Abdelali Bitar, Halima Gamrani, Arumugam R. Jayakumar and Omar El Hiba
Metabolites 2024, 14(4), 193; https://doi.org/10.3390/metabo14040193 (registering DOI) - 29 Mar 2024
Abstract
Hepatic encephalopathy (HE) is a major neuropsychological condition that occursas a result of impaired liver function. It is frequently observed in patients with advanced liver disease or cirrhosis. Memory impairment is among the symptoms of HE; the pathophysiologic mechanism for this enervating condition [...] Read more.
Hepatic encephalopathy (HE) is a major neuropsychological condition that occursas a result of impaired liver function. It is frequently observed in patients with advanced liver disease or cirrhosis. Memory impairment is among the symptoms of HE; the pathophysiologic mechanism for this enervating condition remains unclear. However, it is possible that neuroinflammation may be involved, as recent studies have emphasized such phenomena. Therefore, the aim of the present study is to assess short working memory (SWM) and examine the involvement of microglia in a chronic model of HE. The study was carried out with male Wistar rats that were induced by repeated thioacetamide (TAA) administration (100 mg/kg i.p injection for 10 days). SWM function was assessed through Y-maze, T-Maze, and novel object recognition (NOR) tests, together with an immunofluorescence study of microglia activation within the hippocampal areas. Our data showed impaired SWM in TAA-treated rats that was associated with microglial activation in the three hippocampal regions, and which contributed to cognitive impairment. Full article
(This article belongs to the Special Issue Metabolic Programming of Hepatic Organ Function)
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12 pages, 929 KiB  
Article
Optimal and Quasi-Optimal Automatic Tuning of Vibration Neutralizers
by Emiliano Rustighi
Vibration 2024, 7(2), 362-373; https://doi.org/10.3390/vibration7020018 (registering DOI) - 29 Mar 2024
Abstract
Vibration neutralizers are single-degree-of-freedom devices affixed to vibrating structures in order to reduce the response at a specific troublesome harmonic excitation frequency. As this frequency may vary over time, it becomes imperative to track and adjust the neutralizer to maintain the optimal performance. [...] Read more.
Vibration neutralizers are single-degree-of-freedom devices affixed to vibrating structures in order to reduce the response at a specific troublesome harmonic excitation frequency. As this frequency may vary over time, it becomes imperative to track and adjust the neutralizer to maintain the optimal performance. Recent years have witnessed the emergence of adaptive tunable vibration neutralizers, offering real-time adjustment capabilities through external actions. Thanks to real-time control algorithms, these devices enable the automatic mitigation of vibration levels in mechanical structures. A particularly successful algorithm for the automatic tuning of these devices leverages the phase angle between the base acceleration and the neutralizer’s mass. This study critically examines the justification for employing such an algorithm and scrutinizes its optimal applicability limits, particularly in the context of viscous and structurally damped systems. The findings reveal that this algorithm accurately approximates optimum tuning for systems with low damping. Moreover, from an engineering perspective, the algorithm remains acceptable even for heavily damped structures. Through a focused and comprehensive analysis, this paper provides valuable insights into the efficacy and limitations of the phase-angle-based tuning algorithm, contributing to the advancement of adaptive vibration control strategies in smart structures. Full article
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19 pages, 9093 KiB  
Article
Route Risk Index for Autonomous Trucks
by Ryan Jones, Raj Bridgelall and Denver Tolliver
Appl. Sci. 2024, 14(7), 2892; https://doi.org/10.3390/app14072892 (registering DOI) - 29 Mar 2024
Abstract
The proliferation of autonomous trucking demands a sophisticated understanding of the risks associated with the diverse U.S. interstate system. Traditional risk assessment models, while beneficial, do not adequately address the state and regional variations in factors that significantly impact the safety and efficiency [...] Read more.
The proliferation of autonomous trucking demands a sophisticated understanding of the risks associated with the diverse U.S. interstate system. Traditional risk assessment models, while beneficial, do not adequately address the state and regional variations in factors that significantly impact the safety and efficiency of autonomous freight transport. This study addresses the problem by developing a composite risk index that evaluates the safety of U.S. interstate routes for autonomous trucking, considering both state and regional differences in traffic volumes, road conditions, safety records, and weather patterns. The potential for autonomous trucking to transform the freight industry necessitates a risk assessment model that is as dynamic and multifaceted as the system it aims to navigate. This work contributes a regionally sensitive risk index using GIS methodologies, integrating data from national databases, and applying statistical analysis to normalize risk factors. The findings reveal significant state and regional disparities in risk factors, such as the predominance of precipitation-related risks in the Southeast and traffic in the Far West. This work provides a targeted approach to risk assessment for policymakers and infrastructure planners and offers a strategic tool for logistics companies in optimizing autonomous trucking routes. The long-term benefit is a scalable model that can adapt to evolving data inputs and contribute to the broader application of risk assessment strategies in various domains. Full article
(This article belongs to the Special Issue Big Data Applications in Transportation)
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19 pages, 1712 KiB  
Article
Research on Joint Recommendation Algorithm for Knowledge Concepts and Learning Partners Based on Improved Multi-Gate Mixture-of-Experts
by Zhaoyu Shou, Yixin Chen, Hui Wen, Jinghua Liu, Jianwen Mo and Huibing Zhang
Electronics 2024, 13(7), 1272; https://doi.org/10.3390/electronics13071272 (registering DOI) - 29 Mar 2024
Abstract
The rise of Massive Open Online Courses (MOOCs) has increased the large audience for higher education. Different learners face different learning difficulties in the process of online learning. In order to ensure the quality of teaching, online learning resource recommendation services should be [...] Read more.
The rise of Massive Open Online Courses (MOOCs) has increased the large audience for higher education. Different learners face different learning difficulties in the process of online learning. In order to ensure the quality of teaching, online learning resource recommendation services should be more personalised and have more choices. In this paper, we propose a joint recommendation algorithm for knowledge concepts and learning partners based on improved MMoE (Multi-gate Mixture-of-Experts). Firstly, the heterogeneous information network (HIN) is constructed based on the MOOC platform and appropriate meta-paths are selected in order to extract the human–computer interaction information and student–student interaction information generated during the learners’ online learning processes more completely. Secondly, the temporal behavioural characteristics of students are obtained based on their learning paths as well as their knowledge of conceptual characteristics, and LSTM (Long Short-Term Memory) is used to mine students’ current learning interests. Finally, the gating network in MMoE is changed into an attention mechanism network, and for different tasks, multiple attention mechanism networks are used to fuse the learner’s human–computer interaction information, student–student interaction information, and interest characteristics to generate learner representations that are more in line with the respective task and to complete the tasks of knowledge conception and learning partner recommendation. Experiments on publicly available MOOC datasets show that the method proposed in this paper provides more accurate and varied personalization services to online learners compared to the latest proposed methods. Full article
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21 pages, 1347 KiB  
Review
Non-Coding RNAs: Regulators of Stress, Ageing, and Developmental Decisions in Yeast?
by Michal ?áp and Zdena Palková
Cells 2024, 13(7), 599; https://doi.org/10.3390/cells13070599 (registering DOI) - 29 Mar 2024
Abstract
Cells must change their properties in order to adapt to a constantly changing environment. Most of the cellular sensing and regulatory mechanisms described so far are based on proteins that serve as sensors, signal transducers, and effectors of signalling pathways, resulting in altered [...] Read more.
Cells must change their properties in order to adapt to a constantly changing environment. Most of the cellular sensing and regulatory mechanisms described so far are based on proteins that serve as sensors, signal transducers, and effectors of signalling pathways, resulting in altered cell physiology. In recent years, however, remarkable examples of the critical role of non-coding RNAs in some of these regulatory pathways have been described in various organisms. In this review, we focus on all classes of non-coding RNAs that play regulatory roles during stress response, starvation, and ageing in different yeast species as well as in structured yeast populations. Such regulation can occur, for example, by modulating the amount and functional state of tRNAs, rRNAs, or snRNAs that are directly involved in the processes of translation and splicing. In addition, long non-coding RNAs and microRNA-like molecules are bona fide regulators of the expression of their target genes. Non-coding RNAs thus represent an additional level of cellular regulation that is gradually being uncovered. Full article
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