The 2023 MDPI Annual Report has
been released!
 
13 pages, 768 KiB  
Article
From Connectivity to Controllability: Unraveling the Brain Biomarkers of Major Depressive Disorder
by Chunyu Pan, Ying Ma, Lifei Wang, Yan Zhang, Fei Wang and Xizhe Zhang
Brain Sci. 2024, 14(5), 509; https://doi.org/10.3390/brainsci14050509 (registering DOI) - 17 May 2024
Abstract
Major Depressive Disorder (MDD) is a significant neurological condition associated with aberrations in brain functional networks. Traditional studies have predominantly analyzed these from a network topology perspective. However, given the brain’s dynamic and complex nature, exploring its mechanisms from a network control standpoint [...] Read more.
Major Depressive Disorder (MDD) is a significant neurological condition associated with aberrations in brain functional networks. Traditional studies have predominantly analyzed these from a network topology perspective. However, given the brain’s dynamic and complex nature, exploring its mechanisms from a network control standpoint provides a fresh and insightful framework. This research investigates the integration of network controllability and machine learning to pinpoint essential biomarkers for MDD using functional magnetic resonance imaging (fMRI) data. By employing network controllability methods, we identify crucial brain regions that are instrumental in facilitating transitions between brain states. These regions demonstrate the brain’s ability to navigate various functional states, emphasizing the utility of network controllability metrics as potential biomarkers. Furthermore, these metrics elucidate the complex dynamics of MDD and support the development of precision medicine strategies that incorporate machine learning to improve the precision of diagnostics and the efficacy of treatments. This study underscores the value of merging machine learning with network neuroscience to craft personalized interventions that align with the unique pathological profiles of individuals, ultimately enhancing the management and treatment of MDD. Full article
(This article belongs to the Special Issue Brain Network Connectivity Analysis in Neuroscience)
14 pages, 1063 KiB  
Article
Assessment of Cognitive Function in Romanian Patients with Chronic Alcohol Consumption
by Shandiz Morega, Claudiu-Marinel Ionele, Mihaela-Andreea Podeanu, Dan-Nicolae Florescu and Ion Rogoveanu
Gastroenterol. Insights 2024, 15(2), 433-446; https://doi.org/10.3390/gastroent15020031 (registering DOI) - 17 May 2024
Abstract
Alcoholism presents a significant health concern with notable socioeconomic implications. Alcohol withdrawal syndrome (AWS) can manifest when individuals cease or drastically reduce their alcohol consumption after prolonged use. Non-alcoholic fatty liver disease (NAFLD) is characterized by substantial lipid accumulation in the liver cells [...] Read more.
Alcoholism presents a significant health concern with notable socioeconomic implications. Alcohol withdrawal syndrome (AWS) can manifest when individuals cease or drastically reduce their alcohol consumption after prolonged use. Non-alcoholic fatty liver disease (NAFLD) is characterized by substantial lipid accumulation in the liver cells of individuals with no history of alcohol consumption. There is evidence suggesting an association between cognitive impairment and both conditions. This study aimed to evaluate cognitive impairment in patients with NAFLD and AWS using the Mini-Mental State Examination (MMSE). This study involved 120 patients admitted to two hospitals in Craiova, Romania. Results indicated that patients with NAFLD did not exhibit cognitive impairment as measured by MMSE (Mean = 29.27, SD = 0.785). Conversely, patients with AWS showed more pronounced cognitive dysfunction, with a mean MMSE score at admission of 16.60 ± 4.097 and 24.60 ± 2.832 after 2 weeks under treatment with Vitamins B1 and B6 and Cerebrolysin. Additionally, our findings suggested that cognitive dysfunction among alcohol consumers was correlated with the severity of clinical symptoms, as demonstrated by the severity of tremors in our study. The two-week period under treatment and alcohol withdrawal was insufficient for cognitive function to return to normal levels. Observational studies on longer periods of time are advised. Full article
(This article belongs to the Special Issue Novelties in Diagnostics and Therapeutics in Hepatology: 2nd Edition)
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11 pages, 1490 KiB  
Article
The Relationship between the Ewing Test, Sudoscan Cardiovascular Autonomic Neuropathy Score and Cardiovascular Risk Score Calculated with SCORE2-Diabetes
by Andra-Elena Nica, Emilia Rusu, Carmen Dobjanschi, Florin Rusu, Claudia Sivu, Oana Andreea Parlițeanu and Gabriela Radulian
Medicina 2024, 60(5), 828; https://doi.org/10.3390/medicina60050828 (registering DOI) - 17 May 2024
Abstract
Background and Objectives: Cardiac autonomic neuropathy (CAN) is a severe complication of diabetes mellitus (DM) strongly linked to a nearly five-fold higher risk of cardiovascular mortality. Patients with Type 2 Diabetes Mellitus (T2DM) are a significant cohort in which these assessments have [...] Read more.
Background and Objectives: Cardiac autonomic neuropathy (CAN) is a severe complication of diabetes mellitus (DM) strongly linked to a nearly five-fold higher risk of cardiovascular mortality. Patients with Type 2 Diabetes Mellitus (T2DM) are a significant cohort in which these assessments have particular relevance to the increased cardiovascular risk inherent in the condition. Materials and Methods: This study aimed to explore the subtle correlation between the Ewing test, Sudoscan-cardiovascular autonomic neuropathy score, and cardiovascular risk calculated using SCORE 2 Diabetes in individuals with T2DM. The methodology involved detailed assessments including Sudoscan tests to evaluate sudomotor function and various cardiovascular reflex tests (CART). The cohort consisted of 211 patients diagnosed with T2DM with overweight or obesity without established ASCVD, aged between 40 to 69 years. Results: The prevalence of CAN in our group was 67.2%. In the study group, according SCORE2-Diabetes, four patients (1.9%) were classified with moderate cardiovascular risk, thirty-five (16.6%) with high risk, and one hundred seventy-two (81.5%) with very high cardiovascular risk. Conclusions: On multiple linear regression, the SCORE2-Diabetes algorithm remained significantly associated with Sudoscan CAN-score and Sudoscan Nephro-score and Ewing test score. Testing for the diagnosis of CAN in very high-risk patients should be performed because approximately 70% of them associate CAN. Increased cardiovascular risk is associated with sudomotor damage and that Sudoscan is an effective and non-invasive measure of identifying such risk. Full article
(This article belongs to the Special Issue Advances in Clinical Diabetes, Obesity, and Metabolic Diseases)
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28 pages, 3121 KiB  
Article
A Stochastic Decision-Making Tool Suite for Distributed Energy Resources Integration in Energy Markets
by Sergio Cantillo-Luna, Ricardo Moreno-Chuquen, David Celeita and George J. Anders
Energies 2024, 17(10), 2419; https://doi.org/10.3390/en17102419 (registering DOI) - 17 May 2024
Abstract
Energy markets are crucial for integrating Distributed Energy Resources (DER) into modern power grids. However, this integration presents challenges due to the inherent variability and decentralized nature of DERs, as well as poorly adapted regulatory environments. This paper proposes a medium-term decision-making approach [...] Read more.
Energy markets are crucial for integrating Distributed Energy Resources (DER) into modern power grids. However, this integration presents challenges due to the inherent variability and decentralized nature of DERs, as well as poorly adapted regulatory environments. This paper proposes a medium-term decision-making approach based on a comprehensive suite of computational tools for integrating DERs into Colombian energy markets. The proposed framework consists of modular tools that are aligned with the operation of a Commercial Virtual Power Plant (CVPP). The tools aim to optimize participation in bilateral contracts and short-term energy markets. They use forecasting, uncertainty management, and decision-making modules to create an optimal portfolio of DER assets. The suite’s effectiveness and applicability are demonstrated and analyzed through its implementation with heterogeneous DER assets across various operational scenarios. Full article
(This article belongs to the Section C: Energy Economics and Policy)
27 pages, 11184 KiB  
Article
Exploring the Multi-Sensory Coupling Relationship of Open Space on a Winter Campus
by Shumin Li, Yijing Zhang, Qiqi Zhang, Pingting Xue, Hao Wu, Wenjian Xu, Jing Ye, Lingyan Chen, Tianyou He and Yushan Zheng
Forests 2024, 15(5), 876; https://doi.org/10.3390/f15050876 (registering DOI) - 17 May 2024
Abstract
Exploring the combined effects of multisensory interactions in open spaces can help improve the comfort of campus environments. Nine typical spaces on a university campus in Fuzhou were selected for this study. Subjects perceived the environment and then completed an on-site subjective questionnaire. [...] Read more.
Exploring the combined effects of multisensory interactions in open spaces can help improve the comfort of campus environments. Nine typical spaces on a university campus in Fuzhou were selected for this study. Subjects perceived the environment and then completed an on-site subjective questionnaire. At the same time, meteorological data (global radiation, air temperature, globe temperature, wind speed, relative humidity, and illumination intensity) were measured to determine the interactions between visual and acoustic and thermal perceptions. Differences in the meteorological parameters between the measuring points were described using a one-way ANOVA and Tukey’s post hoc test, and a chi-square test of independence was used to determine significant associations between thermal, acoustic, and visual comfort, which in turn led to the study of interactions between visual, acoustic, and thermal comfort using a two-way ANOVA. The following conclusions were drawn: (1) the Thermal Comfort Vote (TCV) increased with the increasing Acoustic Comfort Vote (ACV) at all levels of thermal stress. (2) The highest and lowest Acoustic Sensation Vote (ASV) values for each sound type were derived from either “slightly cold” or “warm” conditions. Both the Thermal Comfort Vote (TCV) and the Acoustic Comfort Vote (ACV) were positively correlated. (3) When “neutral”, the Thermal Sensation Vote (TSV) increased with increasing illumination intensity (LUX). (4) The Sunlight Sensation Vote (SSV) increased with the increasing Universal Thermal Climate Index (UTCI) when illumination intensity (LUX) was moderate and bright. (5) The highest and lowest Acoustic Sensation Vote (ASV) values for each sound type came from either “slightly cold” or “warm” conditions. Full article
(This article belongs to the Section Urban Forestry)
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13 pages, 2878 KiB  
Article
Changes in Collagen across Pork Tenderloin during Marination with Rosehip Nanocapsules
by Araceli Ulloa-Saavedra, Samantha Jardon-Xicotencatl, María L. Zambrano-Zaragoza, Sergio A. Ojeda-Piedra, María de los Angeles Cornejo-Villegas, Claudia I. García-Betanzos and Susana E. Mendoza-Elvira
Appl. Sci. 2024, 14(10), 4276; https://doi.org/10.3390/app14104276 (registering DOI) - 17 May 2024
Abstract
The objective of this study was to prepare zein–gum Arabic nanocapsules with rosehip oil (NC-RH), apply them to pork tenderloin, and analyze the changes in collagen structure under different conditions (pH 6.5 and 4.0) and temperatures (25 °C and 4 °C). NC-RHs were [...] Read more.
The objective of this study was to prepare zein–gum Arabic nanocapsules with rosehip oil (NC-RH), apply them to pork tenderloin, and analyze the changes in collagen structure under different conditions (pH 6.5 and 4.0) and temperatures (25 °C and 4 °C). NC-RHs were prepared using the nanoprecipitation method. Nanocapsules had a particle size of 423 ± 4.1 nm, a polydispersity index of 0.125 ± 3.1, a zeta potential value of −20.1 ± 0.41 mV, an encapsulation efficiency of 75.84 ± 3.1%, and backscattering (ΔBS = 10%); the antioxidant capacity of DPPH was 1052 ± 4.2 µM Eq Trolox and the radical scavenging capacity was 84 ± 0.4%. The dispersions exhibited Newtonian behavior at 25 °C and 4 °C. Incorporating NC-RH into acid marination benefited the tenderness, water-holding capacity, and collagen swelling, and favored changes in myofibrillar proteins corroborated with histological tests. The conditions with the best changes in pork tenderloin were a pH of 4.0 at 4 °C with an NC-RH-administered 11.47 ± 2.2% collagen area. Incorporating rosehip nanocapsules modifies collagen fibers and can be applied in pork marinades to increase the shelf life of a functional product. Full article
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14 pages, 530 KiB  
Article
Influence of Hf Doping on the Oxygen Behaviors on ZrCo(110) Surface Using First-Principles Calculation
by Ruijun Qian, Habibullah, Meitong Ye, Wanglai Cen and Chaoling Wu
Materials 2024, 17(10), 2424; https://doi.org/10.3390/ma17102424 (registering DOI) - 17 May 2024
Abstract
ZrCo alloy is easily poisoned by impurity gases such as O2, CO, and CO2, resulting in a deterioration in hydrogen storage performance. In this study, we conducted a comprehensive investigation into the adsorption and dissociation characteristics of oxygen on [...] Read more.
ZrCo alloy is easily poisoned by impurity gases such as O2, CO, and CO2, resulting in a deterioration in hydrogen storage performance. In this study, we conducted a comprehensive investigation into the adsorption and dissociation characteristics of oxygen on the ZrCo(110) surface using first-principles calculations. Previous studies indicated that the anti-disproportionation properties of ZrCo alloy can be significantly improved by Hf substitution, but the effect of Hf doping on the anti-poisoning properties has not been reported. We also examined the effect of Hf doping on the adsorption, dissociation, and diffusion characteristics of oxygen. It is found that on the ZrCo(110) surface, O2 molecules are easily dissociated and then stably adsorbed at the hollow site. Oxygen atoms will fill the surface preferentially and then diffuse inward. The doping of Hf has an insignificant impact on the adsorption or dissociation behavior of oxygen in comparison to the pure ZrCo surface. However, a notable observation is that the doping of Hf resulted in a reduction in the diffusion barrier for oxygen from the surface to the subsurface by 0.61 eV. Consequently, our study suggests that doping Hf is not an advisable strategy for improving the ZrCo(110) surface’s resistance to O2 poisoning because of improved oxygen permeability. Full article
(This article belongs to the Section Metals and Alloys)
17 pages, 4118 KiB  
Article
Transcriptome Analysis of Sesame (Sesamum indicum L.) Reveals the LncRNA and mRNA Regulatory Network Responding to Low Nitrogen Stress
by Pengyu Zhang, Feng Li, Yuan Tian, Dongyong Wang, Jinzhou Fu, Yasi Rong, Yin Wu, Tongmei Gao and Haiyang Zhang
Int. J. Mol. Sci. 2024, 25(10), 5501; https://doi.org/10.3390/ijms25105501 (registering DOI) - 17 May 2024
Abstract
Nitrogen is one of the important factors restricting the development of sesame planting and industry in China. Cultivating sesame varieties tolerant to low nitrogen is an effective way to solve the problem of crop nitrogen deficiency. To date, the mechanism of low nitrogen [...] Read more.
Nitrogen is one of the important factors restricting the development of sesame planting and industry in China. Cultivating sesame varieties tolerant to low nitrogen is an effective way to solve the problem of crop nitrogen deficiency. To date, the mechanism of low nitrogen tolerance in sesame has not been elucidated at the transcriptional level. In this study, two sesame varieties Zhengzhi HL05 (ZZ, nitrogen efficient) and Burmese prolific (MD, nitrogen inefficient) in low nitrogen were used for RNA-sequencing. A total of 3964 DEGs (differentially expressed genes) and 221 DELs (differentially expressed lncRNAs) were identified in two sesame varieties at 3d and 9d after low nitrogen stress. Among them, 1227 genes related to low nitrogen tolerance are mainly located in amino acid metabolism, starch and sucrose metabolism and secondary metabolism, and participate in the process of transporter activity and antioxidant activity. In addition, a total of 209 pairs of lncRNA-mRNA were detected, including 21 pairs of trans and 188 cis. WGCNA (weighted gene co-expression network analysis) analysis divided the obtained genes into 29 modules; phenotypic association analysis identified three low-nitrogen response modules; through lncRNA-mRNA co-expression network, a number of hub genes and cis/trans-regulatory factors were identified in response to low-nitrogen stress including GS1-2 (glutamine synthetase 1–2), PAL (phenylalanine ammonia-lyase), CHS (chalcone synthase, CHS), CAB21 (chlorophyll a-b binding protein 21) and transcription factors MYB54, MYB88 and NAC75 and so on. As a trans regulator, lncRNA MSTRG.13854.1 affects the expression of some genes related to low nitrogen response by regulating the expression of MYB54, thus responding to low nitrogen stress. Our research is the first to provide a more comprehensive understanding of DEGs involved in the low nitrogen stress of sesame at the transcriptome level. These results may reveal insights into the molecular mechanisms of low nitrogen tolerance in sesame and provide diverse genetic resources involved in low nitrogen tolerance research. Full article
(This article belongs to the Section Molecular Genetics and Genomics)
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15 pages, 5947 KiB  
Article
Pathogenicity Prediction of Gene Fusion in Structural Variations: A Knowledge Graph-Infused Explainable Artificial Intelligence (XAI) Framework
by Katsuhiko Murakami, Shin-ichiro Tago, Sho Takishita, Hiroaki Morikawa, Rikuhiro Kojima, Kazuaki Yokoyama, Miho Ogawa, Hidehito Fukushima, Hiroyuki Takamori, Yasuhito Nannya, Seiya Imoto and Masaru Fuji
Cancers 2024, 16(10), 1915; https://doi.org/10.3390/cancers16101915 (registering DOI) - 17 May 2024
Abstract
When analyzing cancer sample genomes in clinical practice, many structural variants (SVs), other than single nucleotide variants (SNVs), have been identified. To identify driver variants, the leading candidates must be narrowed down. When fusion genes are involved, selection is particularly difficult, and highly [...] Read more.
When analyzing cancer sample genomes in clinical practice, many structural variants (SVs), other than single nucleotide variants (SNVs), have been identified. To identify driver variants, the leading candidates must be narrowed down. When fusion genes are involved, selection is particularly difficult, and highly accurate predictions from AI is important. Furthermore, we also wanted to determine how the prediction can make more reliable diagnoses. Here, we developed an explainable AI (XAI) suitable for SVs with gene fusions, based on the XAI technology we previously developed for the prediction of SNV pathogenicity. To cope with gene fusion variants, we added new data to the previous knowledge graph for SVs and we improved the algorithm. Its prediction accuracy was as high as that of existing tools. Moreover, our XAI could explain the reasons for these predictions. We used some variant examples to demonstrate that the reasons are plausible in terms of pathogenic basic mechanisms. These results can be seen as a hopeful step toward the future of genomic medicine, where efficient and correct decisions can be made with the support of AI. Full article
(This article belongs to the Section Cancer Informatics and Big Data)
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28 pages, 4388 KiB  
Article
Regional Pulmonary Ventilation Assessment Method and System Based on Impedance Sensing Information from the Pentapulmonary Lobes
by Yapeng Zhang, Chengxin Song, Wei He, Qian Zhang, Pengcheng Zhao and Jingang Wang
Sensors 2024, 24(10), 3202; https://doi.org/10.3390/s24103202 (registering DOI) - 17 May 2024
Abstract
Regional lung ventilation assessment is a critical tool for the early detection of lung diseases and postoperative evaluation. Biosensor-based impedance measurements, known for their non-invasive nature, among other benefits, have garnered significant attention compared to traditional detection methods that utilize pressure sensors. However, [...] Read more.
Regional lung ventilation assessment is a critical tool for the early detection of lung diseases and postoperative evaluation. Biosensor-based impedance measurements, known for their non-invasive nature, among other benefits, have garnered significant attention compared to traditional detection methods that utilize pressure sensors. However, solely utilizing overall thoracic impedance fails to accurately capture changes in regional lung air volume. This study introduces an assessment method for lung ventilation that utilizes impedance data from the five lobes, develops a nonlinear model correlating regional impedance with lung air volume, and formulates an approach to identify regional ventilation obstructions based on impedance variations in affected areas. The electrode configuration for the five lung lobes was established through numerical simulations, revealing a power–function nonlinear relationship between regional impedance and air volume changes. An analysis of 389 pulmonary function tests refined the equations for calculating pulmonary function parameters, taking into account individual differences. Validation tests on 30 cases indicated maximum relative errors of 0.82% for FVC and 0.98% for FEV1, all within the 95% confidence intervals. The index for assessing regional ventilation impairment was corroborated by CT scans in 50 critical care cases, with 10 validation trials showing agreement with CT lesion localization results. Full article
15 pages, 637 KiB  
Article
Incorporating Symbolic Discrete Controller Synthesis into a Virtual Robot Experimental Platform: An Implementation with Collaborative Unmanned Aerial Vehicle Robots
by Mete Özbaltan and Serkan Çaşka
Drones 2024, 8(5), 206; https://doi.org/10.3390/drones8050206 (registering DOI) - 17 May 2024
Abstract
We introduce a modeling framework aimed at incorporating symbolic discrete controller synthesis (DCS) into a virtual robot experimental platform. This framework involves symbolically representing the behaviors of robotic systems along with their control objectives using synchronous programming techniques. We employed DCS algorithms through [...] Read more.
We introduce a modeling framework aimed at incorporating symbolic discrete controller synthesis (DCS) into a virtual robot experimental platform. This framework involves symbolically representing the behaviors of robotic systems along with their control objectives using synchronous programming techniques. We employed DCS algorithms through the reactive synchronous environment ReaX to generate controllers that fulfill specified objectives. These resulting controllers were subsequently deployed on the virtual robot experimental platform Simscape. To demonstrate and validate our approach, we provide an implementation example involving collaborative UAV robots. Full article
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22 pages, 3353 KiB  
Article
Enhancing Water Purification by Integrating Titanium Dioxide Nanotubes into Polyethersulfone Membranes for Improved Hydrophilicity and Anti-Fouling Performance
by Ayesha Bilal, Muhammad Yasin, Faheem Hassan Akhtar, Mazhar Amjad Gilani, Hamad Alhmohamadi, Mohammad Younas, Azeem Mushtaq, Muhammad Aslam, Mehdi Hassan, Rab Nawaz, Aqsha Aqsha, Jaka Sunarso, Muhammad Roil Bilad and Asim Laeeq Khan
Membranes 2024, 14(5), 116; https://doi.org/10.3390/membranes14050116 (registering DOI) - 17 May 2024
Abstract
Water pollution remains a critical concern, one necessitated by rapidly increasing industrialization and urbanization. Among the various strategies for water purification, membrane technology stands out, with polyethersulfone (PES) often being the material of choice due to its robust mechanical properties, thermal stability, and [...] Read more.
Water pollution remains a critical concern, one necessitated by rapidly increasing industrialization and urbanization. Among the various strategies for water purification, membrane technology stands out, with polyethersulfone (PES) often being the material of choice due to its robust mechanical properties, thermal stability, and chemical resistance. However, PES-based membranes tend to exhibit low hydrophilicity, leading to reduced flux and poor anti-fouling performance. This study addresses these limitations by incorporating titanium dioxide nanotubes (TiO2NTs) into PES nanofiltration membranes to enhance their hydrophilic properties. The TiO2NTs, characterized through FTIR, XRD, BET, and SEM, were embedded in PES at varying concentrations using a non-solvent induced phase inversion (NIPS) method. The fabricated mixed matrix membranes (MMMs) were subjected to testing for water permeability and solute rejection capabilities. Remarkably, membranes with a 1 wt.% TiO2NT loading displayed a significant increase in pure water flux, from 36 to 72 L m2 h−1 bar−1, a 300-fold increase in selectivity compared to the pristine sample, and a dye rejection of 99%. Furthermore, long-term stability tests showed only a slight reduction in permeate flux over a time of 36 h, while dye removal efficiency was maintained, thus confirming the membrane’s stability. Anti-fouling tests revealed a 93% flux recovery ratio, indicating excellent resistance to fouling. These results suggest that the inclusion of TiO2 NTs offers a promising avenue for the development of efficient and stable anti-fouling PES-based membranes for water purification. Full article
(This article belongs to the Special Issue Membrane-Based Technologies for Water/Wastewater Treatment)
13 pages, 573 KiB  
Review
Delayed Enhancement in Cardiac CT: A Potential Alternative to Cardiac MRI? Technical Updates and Clinical Considerations
by Domenico De Stefano, Federica Vaccarino, Domiziana Santucci, Marco Parillo, Antonio Nenna, Francesco Loreni, Chiara Ferrisi, Omar Giacinto, Raffaele Barbato, Ciro Mastroianni, Mario Lusini, Massimo Chello, Bruno Beomonte Zobel, Rosario Francesco Grasso and Eliodoro Faiella
Appl. Sci. 2024, 14(10), 4275; https://doi.org/10.3390/app14104275 (registering DOI) - 17 May 2024
Abstract
Despite cardiac magnetic resonance (CMR) with late gadolinium enhancement (LGE) being the current gold standard for non-invasive myocardial characterization and fibrosis quantification, its accessibility is limited, particularly in acute settings and in certain patient populations with contraindications to magnetic resonance imaging. Late iodine [...] Read more.
Despite cardiac magnetic resonance (CMR) with late gadolinium enhancement (LGE) being the current gold standard for non-invasive myocardial characterization and fibrosis quantification, its accessibility is limited, particularly in acute settings and in certain patient populations with contraindications to magnetic resonance imaging. Late iodine enhancement (LIE) in computed tomography (CT) imaging has emerged as a potential alternative, capitalizing on the similarities in the contrast kinetics between gadolinium and iodinated contrast agents. Studies have investigated LIE-CT’s effectiveness in myocardial infarction (MI) detection, revealing promising outcomes alongside some disparities compared to LGE-CMR. LIE-CT also proves beneficial in diagnosing non-ischemic heart diseases such as myocarditis, hypertrophic cardiomyopathy, and sarcoidosis. While LIE-CT demonstrates good accuracy in detecting certain myocardial pathologies, including acute MI and chronic fibrotic changes, it has limitations, such as the inability to detect diffuse myocardial enhancement. Nonetheless, thanks to the availability of optimized protocols with minimal radiation doses and contrast medium administration, integrating LIE-CT into cardiac CT protocols could enhance its clinical utility, particularly in acute settings, providing valuable prognostic and management insights across a spectrum of cardiac ischemic and non-ischemic conditions. Full article
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20 pages, 820 KiB  
Article
Electric Vehicle Supply Chain Risk Assessment Based on Combined Weights and an Improved Matter-Element Extension Model: The Chinese Case
by Huixin Liu and Xiang Hao
Sustainability 2024, 16(10), 4249; https://doi.org/10.3390/su16104249 (registering DOI) - 17 May 2024
Abstract
In order to meet energy and environmental challenges, many countries will implement the replacement of fuel vehicles for the future clean energy transition; so, the number of electric vehicles (EVs) operating in cities will grow significantly. It is crucial to assess the risks [...] Read more.
In order to meet energy and environmental challenges, many countries will implement the replacement of fuel vehicles for the future clean energy transition; so, the number of electric vehicles (EVs) operating in cities will grow significantly. It is crucial to assess the risks of the electric vehicle supply chain (EVSC) and prevent them. Based on this, this paper proposes an EVSC risk research framework with combined weights and an improved matter-element extension model: (i) Firstly, the EVSC evaluation index system is constructed from the six stages of supply chain planning, sales, procurement, manufacturing, distribution, after-sales, and external risks. (ii) The subjective and objective weights are calculated by the decision laboratory method and entropy weight method, respectively, and then the minimum deviation method is used for a combined design to overcome the defects of a single method. (iii) An improved matter-element extension model (MEEM) is constructed by introducing asymmetric proximity degree and risk bias. (iv) The model is applied to a case study and its feasibility and superiority are verified through sensitivity analysis and comparative analysis. The final results show that the method and framework proposed in this paper are in line with EVSC risk assessment standards and superior to other models, which can help EVSC managers to identify potential risks, formulate appropriate risk prevention measures, promote the stable development of electric vehicles, and provide a reference for the development of energy and environment. Full article
19 pages, 1561 KiB  
Article
Generic Carbon Budget Model for Assessing National Carbon Dynamics toward Carbon Neutrality: A Case Study of South Korea
by Youngjin Ko, Cholho Song, Max Fellows, Moonil Kim, Mina Hong, Werner A. Kurz, Juha Metsaranta, Jiwon Son and Woo-Kyun Lee
Forests 2024, 15(5), 877; https://doi.org/10.3390/f15050877 (registering DOI) - 17 May 2024
Abstract
Forests play a crucial role in South Korea’s carbon neutrality goal and require sustainable management strategies to overcome age-class imbalances. The Generic Carbon Budget Model (GCBM) offers a spatially explicit approach to simulate carbon dynamics at a regional scale. In this study, we [...] Read more.
Forests play a crucial role in South Korea’s carbon neutrality goal and require sustainable management strategies to overcome age-class imbalances. The Generic Carbon Budget Model (GCBM) offers a spatially explicit approach to simulate carbon dynamics at a regional scale. In this study, we utilized the GCBM to analyze the carbon budget of forests in South Korea and produce spatiotemporal maps for distribution of the forest biomass. The growth parameters of five representative tree species (Pinus densiflora Siebold & Zucc., Larix kaempferi Carr., Pinus koraiensis Siebold & Zucc., Quercus mongolica Fisch. ex Ledeb., Quercus variabilis Blume), which are the main species in South Korea, were used to operate the model. In addition, spatial data for harvest and thinning management activities were used to analyze the effects of anthropogenic activities. In 2020, the aboveground and belowground biomass were 112.98 and 22.84 tC ha−1, and the net primary productivity was 8.30 tC ha−1 year−1. These results were verified using comparison with statistics, a literature review, and MODIS NPP. In particular, broadleaf is higher than conifer forest in net primary production. The Canadian GCBM with Korean forest inventory data and yield curves successfully estimated the aboveground and belowground biomass of forests in South Korea. Our study demonstrates that these estimates can be mapped in detail, thereby supporting decision-makers and stakeholders in analyzing the carbon budget of the forests in South Korea and developing novel schemes that can serve regional and national aims related to forest management, wood utilization, and ecological preservation. Further studies are needed to improve the initialization of dead organic matter pools, given the large-scale afforestation efforts in recent decades that have established South Korea’s forests on predominantly non-forest sites. Full article
(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)
16 pages, 1544 KiB  
Article
Fractional-Order Least-Mean-Square-Based Active Control for an Electro–Hydraulic Composite Engine Mounts
by Lida Wang, Rongjun Ding, Kan Liu, Jun Yang, Xingwu Ding and Renping Li
Electronics 2024, 13(10), 1974; https://doi.org/10.3390/electronics13101974 (registering DOI) - 17 May 2024
Abstract
For the vibration of automobile powertrain, this paper designs electro–hydraulic composite engine mounts. Subsequently, the dynamic characteristics of the hydraulic mount and the electromagnetic actuator were analyzed and experimentally studied separately. Due to the strong nonlinearity of the hybrid electromechanical engine mount, a [...] Read more.
For the vibration of automobile powertrain, this paper designs electro–hydraulic composite engine mounts. Subsequently, the dynamic characteristics of the hydraulic mount and the electromagnetic actuator were analyzed and experimentally studied separately. Due to the strong nonlinearity of the hybrid electromechanical engine mount, a Fractional-Order Least-Mean-Square (FGO-LMS) algorithm was proposed to model its secondary path identification. To validate the vibration reduction effect, a rapid control prototype test platform was established, and vibration active control experiments were conducted based on the Multiple–Input Multiple–Output Filter-x Least-Mean-Square (MIMO-FxLMS) algorithm. The results indicate that, under various operating conditions, the vibration transmitted to the chassis from the powertrain was significantly suppressed. Full article
(This article belongs to the Special Issue Control and Optimization of Power Converters and Drives)
22 pages, 680 KiB  
Article
Application of Three-Dimensional Porous Aerogel as Adsorbent for Removal of Textile Dyes from Water
by Monika Liugė, Dainius Paliulis and Teresė Leonavičienė
Appl. Sci. 2024, 14(10), 4274; https://doi.org/10.3390/app14104274 (registering DOI) - 17 May 2024
Abstract
The textile industry is one of the most important industries in the European Union. The main environmental problems of the textile industry are the high water consumption, the generated pollution, the variety of chemicals used and the high energy demand. Recently, adsorbents with [...] Read more.
The textile industry is one of the most important industries in the European Union. The main environmental problems of the textile industry are the high water consumption, the generated pollution, the variety of chemicals used and the high energy demand. Recently, adsorbents with a large specific surface area and low weight, such as aerogels, have attracted great interest as promising materials for removing dyes from polluted water. Cellulose aerogels are inexpensive and non-toxic. Langmuir and Freundlich isotherms were chosen as the best method to describe the performance of the adsorbent. In this study, the adsorption efficiency of Congo red, Naphthol green B, Rhodamine B and Methylene blue were determined by using an adsorbent synthesized from paper and cardboard waste. The total organic carbon concentration was chosen as an indicator of the concentration of the dyes in the solutions. The aerogel capsules had 5% cellulose content. It was found that the adsorption capacity of the aerogel in the solutions of Congo red varied from 0.028 mg/g to 14.483 mg/g; in the solutions of Naphthol green B, from 0.013 mg/g to 7.698 mg/g; in the solutions of Rhodamine B, from 0.020 mg/g to 8.768 mg/g; and in the solutions of Methylene blue, from 0.024 mg/g to 13.538 mg/g. Full article
11 pages, 1960 KiB  
Article
Urethane Synthesis in the Presence of Organic Acid Catalysts—A Computational Study
by Hadeer Q. Waleed, Béla Viskolcz and Béla Fiser
Molecules 2024, 29(10), 2375; https://doi.org/10.3390/molecules29102375 (registering DOI) - 17 May 2024
Abstract
A general mechanism for catalytic urethane formation in the presence of acid catalysts, dimethyl hydrogen phosphate (DMHP), methanesulfonic acid (MSA), and trifluoromethanesulfonic acid (TFMSA), has been studied using theoretical methods. The reaction of phenyl isocyanate (PhNCO) and butan-1-ol (BuOH) has been selected to [...] Read more.
A general mechanism for catalytic urethane formation in the presence of acid catalysts, dimethyl hydrogen phosphate (DMHP), methanesulfonic acid (MSA), and trifluoromethanesulfonic acid (TFMSA), has been studied using theoretical methods. The reaction of phenyl isocyanate (PhNCO) and butan-1-ol (BuOH) has been selected to describe the energetic and structural features of the catalyst-free urethane formation. The catalytic activities of DMHP, MSA, and TFMSA have been compared by adding them to the PhNCO–BuOH model system. The thermodynamic properties of the reactions were computed by using the G3MP2BHandHLYP composite method. It was revealed that in the presence of trifluoromethanesulfonic acid, the activation energy was the lowest within the studied set of catalysts. The achieved results indicate that acids can be successfully employed in urethane synthesis and the mechanism was described. Full article
(This article belongs to the Special Issue Feature Papers in Computational and Theoretical Chemistry)
9 pages, 258 KiB  
Communication
Physiological and Biomechanical Characteristics of Olympic and World-Class Rowers—Case Study
by Ricardo Cardoso, Manoel Rios, Filipa Cardoso, Pedro Fonseca, Francisco A. Ferreira, Jose Arturo Abraldes, Beatriz B. Gomes, João Paulo Vilas-Boas and Ricardo J. Fernandes
Appl. Sci. 2024, 14(10), 4273; https://doi.org/10.3390/app14104273 (registering DOI) - 17 May 2024
Abstract
In this study, we quantified relevant biophysical characteristics of two elite rowers across a wide range of intensities. Two <40-year-old male and female Olympic and World Championship finalists performed a 7 × 3 min protocol plus 1 min maximal effort on a rowing [...] Read more.
In this study, we quantified relevant biophysical characteristics of two elite rowers across a wide range of intensities. Two <40-year-old male and female Olympic and World Championship finalists performed a 7 × 3 min protocol plus 1 min maximal effort on a rowing ergometer. The intensity increase resulted in maximum values of 79.4 ± 2.4 and 69.7 ± 1.5 mL/min/kg for oxygen uptake, 179.3 ± 5.7 and 152.5 ± 2.9 L/min for ventilation, 170 ± 1 and 173 ± 0 bpm for heart rate, 10.6 and 15.8 mmol/L for blood lactate concentration, and 38.1 ± 0.03 and 38.8 ± 0.03 °C for core temperature for the male and female rowers. The percentage of power corresponding to a previously conducted maximum 2000 m rowing ergometer test and the work at each step increased from 49 to 127 and 42 to 103% and from 226.8 to 398.9 J and 174.0 to 250.0 J, from low to extreme intensities, for the male and female. Concurrently, there was a decrease in cycle length and propulsive time, followed by an increase in maximal handle drive velocity, with the rise in rowing intensity. These world-class rowers seem capable of maintaining physiological and technical profiles (and a remarkable capacity to generate substantial power) at this phase of their careers possibly due to long-term engagement in elite-level training. Biophysical data provide valuable referential information for guiding rowers to improve their performance. Full article
(This article belongs to the Special Issue Advances in the Biomechanical Analysis of Human Movement)
26 pages, 1307 KiB  
Article
Incorporating Multi-Source Market Sentiment and Price Data for Stock Price Prediction
by Kui Fu and Yanbin Zhang
Mathematics 2024, 12(10), 1572; https://doi.org/10.3390/math12101572 (registering DOI) - 17 May 2024
Abstract
The problem of stock price prediction has been a hot research issue. Stock price is influenced by various factors at the same time, and market sentiment is one of the most critical factors. Financial texts such as news and investor comments reflect investor [...] Read more.
The problem of stock price prediction has been a hot research issue. Stock price is influenced by various factors at the same time, and market sentiment is one of the most critical factors. Financial texts such as news and investor comments reflect investor sentiment in the stock market and influence market movements. Previous research models have struggled to accurately mine multiple sources of market sentiment information originating from the Internet and traditional sentiment analysis models are challenging to quantify and combine indicator data from market data and multi-source sentiment data. Therefore, we propose a BERT-LLA stock price prediction model incorporating multi-source market sentiment and technical analysis. In the sentiment analysis module, we propose a semantic similarity and sector heat-based model to screen for related sectors and use fine-tuned BERT models to calculate the text sentiment index, transforming the text data into sentiment index time series data. In the technical indicator calculation module, technical indicator time series are calculated using market data. Finally, in the prediction module, we combine the sentiment index time series and technical indicator time series and employ a two-layer LSTM network prediction model with an integrated attention mechanism to predict stock close price. Our experiment results show that the BERT-LLA model can accurately capture market sentiment and has a strong practicality and forecasting ability in analyzing market sentiment and stock price prediction. Full article
28 pages, 8717 KiB  
Article
Determinants of Yearly CO2 Emission Fluctuations: A Machine Learning Perspective to Unveil Dynamics
by Christian Mulomba Mukendi, Hyebong Choi, Suhui Jung and Yun-Seon Kim
Sustainability 2024, 16(10), 4242; https://doi.org/10.3390/su16104242 (registering DOI) - 17 May 2024
Abstract
In order to understand the dynamics in climate change, inform policy decisions and prompt timely action to mitigate its impact, this study provides a comprehensive analysis of the short-term trend of the year-on-year CO2 emission changes across ten countries, considering a broad [...] Read more.
In order to understand the dynamics in climate change, inform policy decisions and prompt timely action to mitigate its impact, this study provides a comprehensive analysis of the short-term trend of the year-on-year CO2 emission changes across ten countries, considering a broad range of factors including socioeconomic factors, CO2-related industry, and education. This study uniquely goes beyond the common country-based analysis, offering a broader understanding of the interconnected impact of CO2 emissions across countries. Our preliminary regression analysis, using the ten most significant features, could only explain 66% of the variations in the target. To capture the emissions trend variation, we categorized countries by the change in CO2 emission volatility (high, moderate, low with upward or downward trends), assessed using standard deviation. We employed machine learning techniques, including feature importance analysis, Partial Dependence Plots (PDPs), sensitivity analysis, and Pearson and Canonical correlation analyses, to identify influential factors driving these short-term changes. The Decision Tree Classifier was the most accurate model, with an accuracy of 96%. It revealed population size, CO2 emissions from coal, the three-year average change in CO2 emissions, GDP, CO2 emissions from oil, education level (incomplete primary), and contribution to temperature rise as the most significant predictors, in order of importance. Furthermore, this study estimates the likelihood of a country transitioning to a higher emission category. Our findings provide valuable insights into the temporal dynamics of factors influencing CO2 emissions changes, contributing to the global efforts to address climate change. Full article
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18 pages, 1697 KiB  
Article
Detection and Analysis of Antidiarrheal Genes and Immune Factors in Various Shanghai Pig Breeds
by Jinyong Zhou, Fuqin Liu, Mengqian He, Jun Gao, Caifeng Wu, Yeqing Gan, Yi Bian, Jinliang Wei, Weijian Zhang, Wengang Zhang, Xuejun Han, Jianjun Dai and Lingwei Sun
Biomolecules 2024, 14(5), 595; https://doi.org/10.3390/biom14050595 (registering DOI) - 17 May 2024
Abstract
The aim of this study was to identify effective genetic markers for the Antigen Processing Associated Transporter 1 (TAP1), α (1,2) Fucosyltransferase 1 (FUT1), Natural Resistance Associated Macrophage Protein 1 (NRAMP1), Mucin 4 (MUC4) and [...] Read more.
The aim of this study was to identify effective genetic markers for the Antigen Processing Associated Transporter 1 (TAP1), α (1,2) Fucosyltransferase 1 (FUT1), Natural Resistance Associated Macrophage Protein 1 (NRAMP1), Mucin 4 (MUC4) and Mucin 13 (MUC13) diarrhea-resistance genes in the local pig breeds, namely Shanghai white pigs, Fengjing pigs, Shawutou pigs, Meishan pigs and Pudong white pigs, to provide a reference for the characterization of local pig breed resources in Shanghai. Polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLR) and sequence sequencing were applied to analyze the polymorphisms of the above genes and to explore the effects on the immunity of Shanghai local pig breeds in conjunction with some immunity factors. The results showed that both TAP1 and MUC4 genes had antidiarrheal genotype GG in the five pig breeds, AG and GG genotypes of the FUT1 gene were detected in Pudong white pigs, AA antidiarrheal genes of the NRAMP1 gene were detected in Meishan pigs, the AB type of the NRAMP1 gene was detected in Pudong white pigs, and antidiarrheal genotype GG of the MUC13 gene was only detected in Shanghai white pigs. The MUC13 antidiarrhea genotype GG was only detected in Shanghai white pigs. The TAP1 gene was moderately polymorphic in Shanghai white pigs, Fengjing pigs, Shawutou pigs, Meishan pigs and Pudong white pigs, among which TAP1 in Shanghai white pigs and Shawutou pigs did not satisfy the Hardy–Weinberg equilibrium. The FUT1 gene of Pudong white pigs was in a state of low polymorphism. NRAMP1 of Meishan pigs and Pudong white pigs was in a state of moderate polymorphism, which did not satisfy the Hardy–Weinberg equilibrium. The MUC4 genes of Shanghai white pigs and Pudong white pigs were in a state of low polymorphism, and the MUC4 genes of Fengjing pigs and Shawutou pigs were in a state of moderate polymorphism, and the MUC4 genes of Fengjing pigs and Pudong white pigs did not satisfy the Hardy–Weinberg equilibrium. The MUC13 gene of Shanghai white pigs and Pudong white pigs was in a state of moderate polymorphism. Meishan pigs had higher levels of IL-2, IL-10, IgG and TNF-α, and Pudong white pigs had higher levels of IL-12 than the other pigs. The level of interleukin 12 (IL-12) was significantly higher in the AA genotype of the MUC13 gene of Shanghai white pigs than in the AG genotype. The indicator of tumor necrosis factor alpha (TNF-α) in the AA genotype of the TAP1 gene of Fengjing pigs was significantly higher than that of the GG and AG genotypes. The indicator of IL-12 in the AG genotype of the Shawutou pig TAP1 gene was significantly higher than that of the GG genotype. The level of TNF-α in the AA genotype of the NRAMP1 gene of Meishan pigs was markedly higher than that of the AB genotype. The IL-2 level of the AG type of the FUT1 gene was obviously higher than that of the GG type of Pudong white pigs, the IL-2 level of the AA type of the MUC4 gene was dramatically higher than that of the AG type, and the IgG level of the GG type of the MUC13 gene was apparently higher than that of the AG type. The results of this study are of great significance in guiding the antidiarrhea breeding and molecular selection of Shanghai white pigs, Fengjing pigs, Shawutou pigs, Meishan pigs and Pudong white pigs and laying the foundation for future antidiarrhea breeding of various local pig breeds in Shanghai. Full article
(This article belongs to the Section Molecular Genetics)
18 pages, 587 KiB  
Article
Bio-Priming with Bacillus Isolates Suppresses Seed Infection and Improves the Germination of Garden Peas in the Presence of Fusarium Strains
by Dragana Miljaković, Jelena Marinković, Gordana Tamindžić, Dragana Milošević, Maja Ignjatov, Vasiljka Karačić and Snežana Jakšić
J. Fungi 2024, 10(5), 358; https://doi.org/10.3390/jof10050358 (registering DOI) - 17 May 2024
Abstract
Seed infection caused by Fusarium spp. is one of the major threats to the seed quality and yield of agricultural crops, including garden peas. The use of Bacillus spp. with multiple antagonistic and plant growth-promoting (PGP) abilities represents a potential disease control strategy. [...] Read more.
Seed infection caused by Fusarium spp. is one of the major threats to the seed quality and yield of agricultural crops, including garden peas. The use of Bacillus spp. with multiple antagonistic and plant growth-promoting (PGP) abilities represents a potential disease control strategy. This study was performed to evaluate the biocontrol potential of new Bacillus spp. rhizosphere isolates against two Fusarium strains affecting garden peas. Six Bacillus isolates identified by 16S rDNA sequencing as B. velezensis (B42), B. subtilis (B43), B. mojavensis (B44, B46), B. amyloliquefaciens (B50), and B. halotolerans (B66) showed the highest in vitro inhibition of F. proliferatum PS1 and F. equiseti PS18 growth (over 40%). The selected Bacillus isolates possessed biosynthetic genes for endoglucanase (B42, B43, B50), surfactin (B43, B44, B46), fengycin (B44, B46), bacillomycin D (B42, B50), and iturin (B42), and were able to produce indole-3-acetic acid (IAA), siderophores, and cellulase. Two isolates, B. subtilis B43 and B. amyloliquefaciens B50, had the highest effect on final germination, shoot length, root length, shoot dry weight, root dry weight, and seedling vigor index of garden peas as compared to the control. Their individual or combined application reduced seed infection and increased seed germination in the presence of F. proliferatum PS1 and F. equiseti PS18, both after seed inoculation and seed bio-priming. The most promising results were obtained in the cases of the bacterial consortium, seed bio-priming, and the more pathogenic strain PS18. The novel Bacillus isolates may be potential biocontrol agents intended for the management of Fusarium seed-borne diseases. Full article
(This article belongs to the Special Issue Fusarium, Alternaria and Rhizoctonia: A Spotlight on Fungal Pathogens)

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