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13 pages, 3265 KiB  
Review
Pre-Treatment and Post-Treatment I-131 Imaging in Differentiated Thyroid Carcinoma
by Jasna Mihailovi?
J. Clin. Med. 2024, 13(7), 1984; https://doi.org/10.3390/jcm13071984 (registering DOI) - 29 Mar 2024
Abstract
Radioiodine imaging in initial perioperative settings, after the total thyroidectomy, includes pre-treatment and post-treatment radioiodine imaging. While the benefit of post-treatment whole-body imaging (PT-WBI) is well established, the role of diagnostic whole-body imaging (dx WBI), prior to radioiodine (I-131) ablative or therapeutic doses, [...] Read more.
Radioiodine imaging in initial perioperative settings, after the total thyroidectomy, includes pre-treatment and post-treatment radioiodine imaging. While the benefit of post-treatment whole-body imaging (PT-WBI) is well established, the role of diagnostic whole-body imaging (dx WBI), prior to radioiodine (I-131) ablative or therapeutic doses, is controversial. Dx WBI has been abandoned in most nuclear medicine centers long ago. Planar low-dose dxWBI provides the volume of postoperative thyroid remnants, but it cannot detect occult metastatic foci in the neck. The modern integrated multimodality, i.e., SPECT/CT imaging, provides three dimensional images and accurate anatomic/metabolic data. This hybrid technology offers better spatial resolution but not better sensitivity. Dx WBI has low theranostic power because of the radioiodine indifference and low detection sensitivity for small-volume nodal disease in the neck. Since dx WBI cannot clarify the paratracheal cervical uptake, thyroid remnants may be easily misinterpreted as nodal disease, leading to a false N upstaging (from N0 stage to N1 stage) in DTC patients. Post-ablation I-131 imaging has a significant role in the initial staging of radioiodine-avid DTC and in the identification of non-radioiodine avid tumors. Additionally, SPECT/CT in the post-treatment setting provides more accurate initial TNM staging and better risk stratification of DTC patients. Post-treatment I-131 imaging is obligatory and must be performed in all DTC patients who receive radioiodine treatment. Full article
(This article belongs to the Special Issue New Strategies in the Treatment of Thyroid Carcinoma)
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16 pages, 6432 KiB  
Article
Changes in Cortical Activation by Transcranial Magnetic Stimulation Due to Coil Rotation Are Not Attributable to Cranial Muscle Activation
by Marco Mancuso, Alessandro Cruciani, Valerio Sveva, Elias Casula, Katlyn E. Brown, Vincenzo Di Lazzaro, John C. Rothwell and Lorenzo Rocchi
Brain Sci. 2024, 14(4), 332; https://doi.org/10.3390/brainsci14040332 (registering DOI) - 29 Mar 2024
Abstract
Transcranial magnetic stimulation coupled with electroencephalography (TMS-EEG) allows for the study of brain dynamics in health and disease. Cranial muscle activation can decrease the interpretability of TMS-EEG signals by masking genuine EEG responses and increasing the reliance on preprocessing methods but can be [...] Read more.
Transcranial magnetic stimulation coupled with electroencephalography (TMS-EEG) allows for the study of brain dynamics in health and disease. Cranial muscle activation can decrease the interpretability of TMS-EEG signals by masking genuine EEG responses and increasing the reliance on preprocessing methods but can be at least partly prevented by coil rotation coupled with the online monitoring of signals; however, the extent to which changing coil rotation may affect TMS-EEG signals is not fully understood. Our objective was to compare TMS-EEG data obtained with an optimal coil rotation to induce motor evoked potentials (M1standard) while rotating the coil to minimize cranial muscle activation (M1emg). TMS-evoked potentials (TEPs), TMS-related spectral perturbation (TRSP), and intertrial phase clustering (ITPC) were calculated in both conditions using two different preprocessing pipelines based on independent component analysis (ICA) or signal-space projection with source-informed reconstruction (SSP-SIR). Comparisons were performed with cluster-based correction. The concordance correlation coefficient was computed to measure the similarity between M1standard and M1emg TMS-EEG signals. TEPs, TRSP, and ITPC were significantly larger in M1standard than in M1emg conditions; a lower CCC than expected was also found. These results were similar across the preprocessing pipelines. While rotating the coil may be advantageous to reduce cranial muscle activation, it may result in changes in TMS-EEG signals; therefore, this solution should be tailored to the specific experimental context. Full article
(This article belongs to the Section Neural Engineering, Neuroergonomics and Neurorobotics)
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13 pages, 983 KiB  
Article
Tradition and Innovation in the Italian Wine Industry: The Best Practices of Casa Paladin
by Daniele Grechi, Enrica Pavione, Patrizia Gazzola and Francesca Cardini
Sustainability 2024, 16(7), 2857; https://doi.org/10.3390/su16072857 (registering DOI) - 29 Mar 2024
Abstract
This study aims to make a significant contribution to the development of a model for integrating research in the wine sector, innovative knowledge, and family businesses with the traditional mode of production in the context of the introduction of modern production technologies with [...] Read more.
This study aims to make a significant contribution to the development of a model for integrating research in the wine sector, innovative knowledge, and family businesses with the traditional mode of production in the context of the introduction of modern production technologies with a view to sustainability and the improvement of services in tourism. From a methodological point of view, the research is based on the case study and, in particular, on Casa Paladin, a family business in the Italian wine sector, which bases its strategy on innovation in production processes and customer relations to obtain high product quality with the aim of meeting consumer needs. The findings underscore the crucial role of family businesses in preserving cultural and traditional elements in the wine sector, with technology and innovation serving as vital drivers for their development. Casa Paladin’s commitment to innovation in production processes and products is evident, emphasizing sustainability as a core element that impacts customer relationships and product quality. Enotourism, including tastings, festivals, and fairs, emerges as a significant aspect contributing to the promotion of the company’s history, culture, and traditions. This study posits Casa Paladin as a notable example in the Italian wine industry, offering transferable insights for other businesses. Its successful integration of culture, innovation, and sustainability contributes to a broader understanding of the contemporary role of family businesses in the Italian wine sector. Full article
(This article belongs to the Collection Sustainable Wine and Beverage Tourism)
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14 pages, 3623 KiB  
Article
Machine Learning-Based Predictions of Porosity during Cold Spray Deposition of High Entropy Alloy Coatings
by Deepak Sharma, Dibakor Boruah, Ali Alperen Bakir, Ahamed Ameen and Shiladitya Paul
Coatings 2024, 14(4), 404; https://doi.org/10.3390/coatings14040404 (registering DOI) - 29 Mar 2024
Abstract
Porosity poses a challenge to the mechanical properties of cold sprayed coatings, especially when it is open or surface-connected, limiting the coatings’ capabilities to act as a barrier. The porosity formation is dependent on the feedstock powder characteristics and the cold spray process [...] Read more.
Porosity poses a challenge to the mechanical properties of cold sprayed coatings, especially when it is open or surface-connected, limiting the coatings’ capabilities to act as a barrier. The porosity formation is dependent on the feedstock powder characteristics and the cold spray process parameters. We present a machine learning-based approach to predict porosity based on the above-mentioned factors. Nine different machine learning models based on linear regression (LR), decision trees, random forests, gradient boosting, support vector machine (SVM), and neural networks were explored. Considering the excellent properties of high entropy alloys, Cantor alloy was taken as the consumable. Our dataset, derived from the literature and experiments, identified SVM with a linear kernel and LR as the top-performing models based on the Pearson correlation coefficient (PCC) and root mean square error, where the PCC values exceeded 0.8. The SHapley Additive exPlanations method helped in identifying that the type of gas and powder are the top two factors in pore formation. Full article
(This article belongs to the Special Issue Compositionally Complex Coatings)
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16 pages, 3161 KiB  
Article
Multi-Objective Optimization Based on Simulation Integrated Pareto Analysis to Achieve Low-Carbon and Economical Operation of a Wastewater Treatment Plant
by Jianbo Liao, Shuang Li, Yihong Liu, Siyuan Mao, Tuo Tian, Xueyan Ma, Bing Li and Yong Qiu
Water 2024, 16(7), 995; https://doi.org/10.3390/w16070995 (registering DOI) - 29 Mar 2024
Abstract
It is essential to reduce carbon emissions in wastewater treatment plants (WWTPs) to achieve carbon neutrality in society. However, current optimization of WWTPs prioritizes the operation cost index (OCI) and effluent quality index (EQI) over greenhouse gas (GHG) emissions. This study aims to [...] Read more.
It is essential to reduce carbon emissions in wastewater treatment plants (WWTPs) to achieve carbon neutrality in society. However, current optimization of WWTPs prioritizes the operation cost index (OCI) and effluent quality index (EQI) over greenhouse gas (GHG) emissions. This study aims to conduct a multi-objective optimization of a WWTP, considering GHG emissions, EQI, and OCI. The anaerobic-anoxic-oxic integrated membrane bioreactor (AAO-MBR) process in an actual WWTP was selected as a typical case, tens of thousands of scenarios with combinations of six operational parameters (dissolved oxygen (DO), external carbon resource (ECR), poly aluminum chloride (PAC), internal reflux ratio (IRR), external reflux ratio (ERR), and sludge discharge (SD)) were simulated by GPS-X software (Hydromantics 8.0.1). It was shown that ECR has the greatest impact on optimization objectives. In the optimal scenario, the main parameters of ATDO, MTDO, IRR, and ERR were 0.1 mg/L, 4 mg/L, 50%, and 100%, respectively. The EQI, OCI, and GHG of the best scenario were 0.046 kg/m3, 0.27 ¥/m3, and 0.51 kgCO2/m3, which were 2.1%, 72.2%, and 34.6% better than the current situation of the case WWTP, respectively. This study provides an effective method for realizing low-carbon and economical operation of WWTPs. Full article
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21 pages, 3336 KiB  
Article
Green Hydrogen Production at the Gigawatt Scale in Portugal: A Technical and Economic Evaluation
by Rui P. Borges, Flávia Franco, Fátima N. Serralha and Isabel Cabrita
Energies 2024, 17(7), 1638; https://doi.org/10.3390/en17071638 (registering DOI) - 29 Mar 2024
Abstract
The European Union has committed to achieving carbon neutrality by 2050 and green hydrogen has been chosen as a priority vector for reaching that goal. Accordingly, Portugal has drafted a National Hydrogen Strategy laying out the various steps for the development of a [...] Read more.
The European Union has committed to achieving carbon neutrality by 2050 and green hydrogen has been chosen as a priority vector for reaching that goal. Accordingly, Portugal has drafted a National Hydrogen Strategy laying out the various steps for the development of a green hydrogen economy. One element of this strategy is the development of a gigawatt-scale hydrogen production facility powered by dedicated renewable electricity sources. This work presents an analysis of the technical and economic feasibility of a facility consisting of a gigawatt-scale polymer electrolyte membrane electrolyser powered by solar photovoltaic and wind electricity, using the energy analysis model EnergyPLAN. Different capacities and modes of operation of the electrolyser are considered, including the complementary use of grid electricity as well as different combinations of renewable power, resulting in a total of 72 different configurations. An economic analysis is conducted addressing the related annualised capital expenditures, maintenance, and variable costs, to allow for the determination of the levelised cost of hydrogen for the different configurations. This analysis shows the conditions required for maximising annual hydrogen production at the lowest levelised cost of hydrogen. The best options consist of an electrolyser powered by a combination of solar photovoltaic and wind, with limited exchanges with the electricity grid, and a levelised cost of hydrogen in the range 3.13–3.48 EUR/kg. Full article
(This article belongs to the Special Issue Hydrogen in the Energy Transition: From Production to End-Use)
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18 pages, 470 KiB  
Article
Comparing Hierarchical Approaches to Enhance Supervised Emotive Text Classification
by Lowri Williams, Eirini Anthi and Pete Burnap
Big Data Cogn. Comput. 2024, 8(4), 38; https://doi.org/10.3390/bdcc8040038 (registering DOI) - 29 Mar 2024
Abstract
The performance of emotive text classification using affective hierarchical schemes (e.g., WordNet-Affect) is often evaluated using the same traditional measures used to evaluate the performance of when a finite set of isolated classes are used. However, applying such measures means the full characteristics [...] Read more.
The performance of emotive text classification using affective hierarchical schemes (e.g., WordNet-Affect) is often evaluated using the same traditional measures used to evaluate the performance of when a finite set of isolated classes are used. However, applying such measures means the full characteristics and structure of the emotive hierarchical scheme are not considered. Thus, the overall performance of emotive text classification using emotion hierarchical schemes is often inaccurately reported and may lead to ineffective information retrieval and decision making. This paper provides a comparative investigation into how methods used in hierarchical classification problems in other domains, which extend traditional evaluation metrics to consider the characteristics of the hierarchical classification scheme, can be applied and subsequently improve the classification of emotive texts. This study investigates the classification performance of three widely used classifiers, Naive Bayes, J48 Decision Tree, and SVM, following the application of the aforementioned methods. The results demonstrated that all the methods improved the emotion classification. However, the most notable improvement was recorded when a depth-based method was applied to both the testing and validation data, where the precision, recall, and F1-score were significantly improved by around 70 percentage points for each classifier. Full article
(This article belongs to the Special Issue Advances in Natural Language Processing and Text Mining)
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12 pages, 5167 KiB  
Communication
Machine Learning-Assisted Prediction of Corrosion Behavior of 7XXX Aluminum Alloys
by Xilin Xiong, Na Zhang, Jingjing Yang, Tongqian Chen and Tong Niu
Metals 2024, 14(4), 401; https://doi.org/10.3390/met14040401 (registering DOI) - 29 Mar 2024
Abstract
High-strength and lightweight 7XXX Al alloys are widely applied in aerospace industries. Stress corrosion cracking (SCC) in these alloys has been extensively discussed, and electrochemical corrosion should be brought to the forefront when these materials are used in marine atmospheric environments. This work [...] Read more.
High-strength and lightweight 7XXX Al alloys are widely applied in aerospace industries. Stress corrosion cracking (SCC) in these alloys has been extensively discussed, and electrochemical corrosion should be brought to the forefront when these materials are used in marine atmospheric environments. This work obtained the corrosion potentials (Ecorr) and corrosion rates of 40 as-cast 7XXX Al alloys by potentiodynamic polarization tests and immersion tests, respectively; then, chemical compositions and physical features were used to build a machine learning model to predict these parameters. RFR was used for the prediction model of Ecorr with the features Cu, Ti, Al, and Zn, and GPR for that of the corrosion rate with the features of specific heat, latent heat of fusion, and proportion of p electrons. The physical meaning and reasonability were discussed based on the analysis of corrosion morphology and precipitated composition. This work provides a reference for the design of corrosion-resistant 7XXX Al alloys and shows a method of conducting corrosion mechanism evaluation by using machine learning. Full article
(This article belongs to the Section Corrosion and Protection)
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16 pages, 3117 KiB  
Article
A Parameter Reduction-Based Decision-Making Method with Interval-Valued Neutrosophic Soft Sets for the Selection of Bionic Thin-Wall Structures
by Honghao Zhang, Lingyu Wang, Danqi Wang, Zhongwei Huang, Dongtao Yu and Yong Peng
Biomimetics 2024, 9(4), 208; https://doi.org/10.3390/biomimetics9040208 (registering DOI) - 29 Mar 2024
Abstract
Bio-inspired thin-wall structures with excellent mechanical properties, high-energy absorption capabilities, and a desirable lightweight level have been extensively applied to the passive safety protection of transportation and aerospace. Collaboration matching and the selection of optional structures with different bionic principles considering the multiple [...] Read more.
Bio-inspired thin-wall structures with excellent mechanical properties, high-energy absorption capabilities, and a desirable lightweight level have been extensively applied to the passive safety protection of transportation and aerospace. Collaboration matching and the selection of optional structures with different bionic principles considering the multiple attribute evaluation index and engineering preference information have become an urgent problem. This paper proposes a parameter reduction-based indifference threshold-based attribute ratio analysis method under an interval-valued neutrosophic soft set (IVNS-SOFT) to obtain the weight vector of an evaluation indicator system for the selection of bionic thin-wall structures, which can avoid the problem of an inadequate subjective evaluation and reduce redundant parameters. An IVNS-SOFT-based multi-attributive border approximation area comparison (MABAC) method is proposed to obtain an optimal alternative, which can quantify uncertainty explicitly and handle the uncertain and inconsistent information prevalent in the expert system. Subsequently, an application of five bio-inspired thin-wall structures is applied to demonstrate that this proposed method is valid and practical. Comparative analysis, sensitivity analysis, and discussion are conducted in this research. The results show that this study provides an effective tool for the selection of bionic thin-wall structures. Full article
(This article belongs to the Special Issue Computer-Aided Biomimetics)
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18 pages, 2455 KiB  
Article
Assessing Microplastic Contamination in Zooplanktonic Organisms from Two River Estuaries
by Francisca Espincho, Rúben Pereira, Sabrina M. Rodrigues, Diogo M. Silva, C. Marisa R. Almeida and Sandra Ramos
Water 2024, 16(7), 992; https://doi.org/10.3390/w16070992 (registering DOI) - 29 Mar 2024
Abstract
The present work aims to evaluate the MP contamination of zooplankton and its impact on MP trophic transfers at the lower levels of the food web in a field study. During 1 year, seasonal surveys were conducted to collect zooplankton and water samples [...] Read more.
The present work aims to evaluate the MP contamination of zooplankton and its impact on MP trophic transfers at the lower levels of the food web in a field study. During 1 year, seasonal surveys were conducted to collect zooplankton and water samples from different sites in two estuaries, the Douro and Lima estuaries (NW, Portugal). The zooplankton was quantified and identified into major zooplanktonic groups. Dedicated protocols that had been previously optimized were used to assess the MP presence in the water samples and in two of the most abundant zooplankton groups (copepods and chaetognaths). The results showed the presence of MPs in all water samples, with similar MP concentrations in both estuaries (Lima: 2.4 ± 2.0 MPs m−3; Douro: 2.3 ± 1.9 MPs m−3). In general, no temporal or spatial variations were observed. Fibres, blue and of a small size (<1 mm), were the most common characteristics of the MPs found in the water and zooplankton, indicating that water can be a source of MPs for zooplankton. Chaetognatha exhibited higher MP contamination in the Lima (2.9 ± 3.1 MPs ind−1) and Douro (2.0 ± 2.8 MPs ind−1) estuaries than Copepoda, which tended to have lower levels of MP contamination (Lima: 0.95 ± 1.12 MPs ind−1; Douro: 1.1 ± 1.2 MPs ind−1). Such differences in the MP concentrations between these two categories of zooplanktonic organisms indicate a possible MP trophic transfer at the lower levels of the food web. The results highlight the novel possibility of an MP trophic transfer in zooplankton and the need to fully assess the impacts of MPs in real scenarios. Full article
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14 pages, 1880 KiB  
Article
Forecasting Pitch Response of Floating Offshore Wind Turbines with a Deep Learning Model
by Mohammad Barooni and Deniz Velioglu Sogut
Clean Technol. 2024, 6(2), 418-431; https://doi.org/10.3390/cleantechnol6020021 (registering DOI) - 29 Mar 2024
Abstract
The design and optimization of floating offshore wind turbines (FOWTs) pose significant challenges, stemming from the complex interplay among aerodynamics, hydrodynamics, structural dynamics, and control systems. In this context, this study introduces an innovative method for forecasting the dynamic behavior of FOWTs under [...] Read more.
The design and optimization of floating offshore wind turbines (FOWTs) pose significant challenges, stemming from the complex interplay among aerodynamics, hydrodynamics, structural dynamics, and control systems. In this context, this study introduces an innovative method for forecasting the dynamic behavior of FOWTs under various conditions by merging Convolutional Neural Network (CNN) with a Gated Recurrent Unit (GRU) network. This model outperforms traditional numerical models by delivering precise and efficient predictions of dynamic FOWT responses. It adeptly handles computational complexities and reduces processing duration, while maintaining flexibility and effectively managing nonlinear dynamics. The model’s prowess is showcased through an analysis of a spar-type FOWT in a multivariate parallel time series dataset using the CNN–GRU structure. The outcomes are notably promising, underscoring the model’s proficiency in accurately forecasting the performance of FOWTs. Full article
(This article belongs to the Topic Advances in Wind Energy Technology)
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14 pages, 370 KiB  
Article
Leibniz’s Principle, (Non-)Entanglement, and Pauli Exclusion
by Cord Friebe
Philosophies 2024, 9(2), 45; https://doi.org/10.3390/philosophies9020045 (registering DOI) - 29 Mar 2024
Abstract
Both bosons and fermions satisfy a strong version of Leibniz’s Principle of the Identity of Indiscernibles (PII), and so are ontologically on par with respect to the PII. This holds for non-entangled, non-product states and for physically entangled states—as it has been established [...] Read more.
Both bosons and fermions satisfy a strong version of Leibniz’s Principle of the Identity of Indiscernibles (PII), and so are ontologically on par with respect to the PII. This holds for non-entangled, non-product states and for physically entangled states—as it has been established in previous work. In this paper, the Leibniz strategy is completed by including the (bosonic) symmetric product states. A new understanding of Pauli’s Exclusion Principle is provided, which distinguishes bosons from fermions in a peculiar ontological way. Finally, the program as a whole is defended against substantial objections. Full article
(This article belongs to the Special Issue Philosophy and Quantum Mechanics)
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23 pages, 12234 KiB  
Article
High-Precision Time Difference of Arrival Estimation Method Based on Phase Measurement
by Jihao Xin, Xuyang Ge, Yuan Zhang, Xingdong Liang, Hang Li, Linghao Wu, Jiashuo Wei and Xiangxi Bu
Remote Sens. 2024, 16(7), 1197; https://doi.org/10.3390/rs16071197 (registering DOI) - 29 Mar 2024
Abstract
In unmanned aerial vehicle (UAV)-based time difference of arrival (TDOA) positioning technique, baselines are limited due to communication constraints. In this case, the accuracy is highly sensitive to the TDOA measurements’ error. This article primarily addresses the problem of short-baseline high-precision time synchronization [...] Read more.
In unmanned aerial vehicle (UAV)-based time difference of arrival (TDOA) positioning technique, baselines are limited due to communication constraints. In this case, the accuracy is highly sensitive to the TDOA measurements’ error. This article primarily addresses the problem of short-baseline high-precision time synchronization and TDOA measurement. We conducted a detailed analysis of error models in TDOA systems, considering both the time and phase measurement. We utilize the frequency division wireless phase synchronization technique in TDOA systems. Building upon this synchronization scheme, we propose a novel time delay estimation method that relies on phase measurements based on the integer least squares method. The performance of this method is demonstrated through Monte Carlo simulations and outdoor experiments. The standard deviations of synchronization and TDOA measurements in experiments are 1.12 ps and 1.66 ps, respectively. Furthermore, the circular error probable (CEP) accuracy is improved from 0.33%R to 0.02%R, offering support for the practical application of distributed short-baseline high-precision passive location techniques. Full article
(This article belongs to the Special Issue Unconventional Drone-Based Surveying 2nd Edition)
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11 pages, 3352 KiB  
Communication
Effects of Winter Warming on Alpine Permafrost Streamflow in Xinjiang China and Teleconnections with the Siberian High
by Jingshi Liu, Guligena Halimulati, Yuting Liu, Jianxin Mu and Namaiti Tuoheti
Water 2024, 16(7), 993; https://doi.org/10.3390/w16070993 (registering DOI) - 29 Mar 2024
Abstract
The climatic warming-induced shrinking of permafrost currently encompasses 65% of alpine areas in North China, where a large population relies on its water and land resources. With increasing recognition of the economic and ecological impacts of permafrost basins, forecasts of environmental vulnerability have [...] Read more.
The climatic warming-induced shrinking of permafrost currently encompasses 65% of alpine areas in North China, where a large population relies on its water and land resources. With increasing recognition of the economic and ecological impacts of permafrost basins, forecasts of environmental vulnerability have gained prominence. However, the links between permafrost and winter water resources remain inadequately explored, with most studies focusing on in-situ measurements related to snow cover and frozen layer thickness. Evaluating more complex phenomena, such as the magnitude and persistence of air temperature or low streamflow, depends on numerous climate-driven factors interacting through various subsurface flow mechanisms, basin drainage mechanics, and hydro-climatic correlations at a macroscale. The present study focuses on winter warming, flow increases, and their teleconnections in Xinjiang, China. The research analyzes their links to the atmospheric cycle of the Siberian High (SH) using long-term data spanning 55 years from two large alpine permafrost basins. Changes in variability and correlation persistence were explored for the past decades, and significant variability and connections were constructed using statistical correlation. The years 1980 and 1990 were a turning point when both winter temperatures and winter river flow began to exhibit a notable and consistent upward trend. Subsequently, the period from the mid-1990s to 2013 was characterized by high variability and persistence in these trends. The influence of the SH plays a dominant role in regard to both winter temperatures and river flow, and these variabilities and correlations can be utilized to estimate and predict winter flow in ungauged permafrost rivers in Xinjiang China. Full article
(This article belongs to the Special Issue Water Management in Arid and Semi-arid Regions)
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16 pages, 15639 KiB  
Article
Playing with Low Amounts of Expanded Graphite for Melt-Processed Polyamide and Copolyester Nanocomposites to Achieve Control of Mechanical, Tribological, Thermal and Dielectric Properties
by Ruben Vande Ryse, Michiel Van Osta, Mounia Gruyaert, Maarten Oosterlinck, ?dám Kalácska, Mariya Edeleva, Frederik Pille, Dagmar R. D’hooge, Ludwig Cardon and Patrick De Baets
Nanomaterials 2024, 14(7), 606; https://doi.org/10.3390/nano14070606 (registering DOI) - 29 Mar 2024
Abstract
Polyamide 11 (PA11) and copolyester (TPC-E) were compounded through melt extrusion with low levels (below 10%) of expanded graphite (EG), aiming at the manufacturing of a thermally and electrically conductive composite resistant to friction and with acceptable mechanical properties. Thermal characterisation showed that [...] Read more.
Polyamide 11 (PA11) and copolyester (TPC-E) were compounded through melt extrusion with low levels (below 10%) of expanded graphite (EG), aiming at the manufacturing of a thermally and electrically conductive composite resistant to friction and with acceptable mechanical properties. Thermal characterisation showed that the EG presence had no influence on the onset degradation temperature or melting temperature. While the specific density of the produced composite materials increased linearly with increasing levels of EG, the tensile modulus and flexural modulus showed a significant increase already at the introduction of 1 wt% EG. However, the elongation at break decreased significantly for higher loadings, which is typical for composite materials. We observed the increase in the dielectric and thermal conductivity, and the dissipated power displayed a much larger increase where high frequencies (e.g., 10 GHz) were taken into account. The tribological results showed significant changes at 4 wt% for the PA11 composite and 6 wt% for the TPC-E composite. Morphological analysis of the wear surfaces indicated that the main wear mechanism changed from abrasive wear to adhesive wear, which contributes to the enhanced wear resistance of the developed materials. Overall, we manufactured new composite materials with enhanced dielectric properties and superior wear resistance while maintaining good processability, specifically upon using 4–6 wt% of EG. Full article
(This article belongs to the Special Issue Thermally Conductive Nanomaterials and Their Applications)
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16 pages, 2424 KiB  
Article
Serum Levels of Copper and Zinc and Survival in Breast Cancer Patients
by Marek Szwiec, Wojciech Marciniak, Ró?a Derkacz, Tomasz Huzarski, Jacek Gronwald, Cezary Cybulski, Tadeusz D?bniak, Anna Jakubowska, Marcin R. Lener, Micha? Falco, Józef K?adny, Piotr Baszuk, Joanne Kotsopoulos, Steven A. Narod and Jan Lubiński
Nutrients 2024, 16(7), 1000; https://doi.org/10.3390/nu16071000 (registering DOI) - 29 Mar 2024
Abstract
There is emerging interest in the relationship between several serum micronutrients and the prognosis of patients with breast cancer. The relationship between serum zinc and copper levels and breast cancer prognosis is unclear. In our study, we included 583 patients with breast cancer [...] Read more.
There is emerging interest in the relationship between several serum micronutrients and the prognosis of patients with breast cancer. The relationship between serum zinc and copper levels and breast cancer prognosis is unclear. In our study, we included 583 patients with breast cancer diagnosed between 2008 and 2015 in the region of Szczecin, Poland. In a blood sample obtained before treatment, serum zinc and copper levels were quantified by mass spectroscopy. Each patient was assigned to one of four categories (quartiles) based on the distribution of the elements in the entire cohort. Patients were followed from diagnosis to death over a mean of 10.0 years. The 10-year overall survival was 58.3% for women in the highest and 82.1% for those in the lowest quartile of serum copper/zinc ratio (p < 0.001). The multivariate hazard ratio (HR) for breast cancer death was 2.07 (95% CI 1.17–3.63; p = 0.01) for patients in the highest quartile of serum copper/zinc ratio compared to those in the lowest. There is evidence that the serum zinc level and copper/zinc ratio provide an independent predictive value for overall survival and breast cancer-specific survival after breast cancer diagnosis. Full article
(This article belongs to the Section Micronutrients and Human Health)
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15 pages, 613 KiB  
Article
Nutritional and Phytochemical Characterization of Freeze-Dried Raspberry (Rubus idaeus): A Comprehensive Analysis
by Mirko Marino, Claudio Gardana, Marco Rendine, Dorothy Klimis-Zacas, Patrizia Riso, Marisa Porrini and Cristian Del Bo’
Foods 2024, 13(7), 1051; https://doi.org/10.3390/foods13071051 (registering DOI) - 29 Mar 2024
Abstract
Several studies have highlighted the beneficial effects of consuming red raspberries on human health thanks to their high content of phytochemicals. However, the products used in these studies, both in the raw or freeze-dried form, were not fully characterized for nutrient and phytochemical [...] Read more.
Several studies have highlighted the beneficial effects of consuming red raspberries on human health thanks to their high content of phytochemicals. However, the products used in these studies, both in the raw or freeze-dried form, were not fully characterized for nutrient and phytochemical composition. In this study, we aimed to determine the nutrient and non-nutrient compounds present in a freeze-dried red raspberry powder widely used by the food industry and consumers. The main sugars identified were fructose (12%), glucose (11%), and sucrose (11%). Twelve fatty acids were detected, with linoleic acid (46%), α-linolenic acid (20%), and oleic acid (15%) being the most abundant. Regarding micronutrients, vitamin C was the main hydro-soluble vitamin, while minerals, potassium, phosphorous, copper and magnesium were the most abundant, with concentrations ranging from 9 up to 96 mg/100 g, followed by manganese, iron and zinc, detected in the range 0.1–0.9 mg/100 g. Phytochemical analysis using UHPLC-DAD-HR-MS detection revealed the presence of Sanguiin H6 (0.4%), Lambertianin C (0.05%), and Sanguiin H-10 isomers (0.9%) as the main compounds. Among anthocyanins, the most representative compounds were cyanidin-3-sophoroside, cyanidin-3-glucoside and cyanidin-3-sambubioside. Our findings can serve as a reliable resource for the food industry, nutraceutical applications and for future investigations in the context of human health. Full article
(This article belongs to the Special Issue Plant-Based Food:From Nutritional Value to Health Benefits)
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13 pages, 3227 KiB  
Article
EnvC Homolog Encoded by Xanthomonas citri subsp. citri Is Necessary for Cell Division and Virulence
by Michelle M. Pena, Thaisa Z. Martins, Doron Teper, Caio Zamuner, Helen A. Alves, Henrique Ferreira, Nian Wang, Maria Inês T. Ferro and Jesus A. Ferro
Microorganisms 2024, 12(4), 691; https://doi.org/10.3390/microorganisms12040691 (registering DOI) - 29 Mar 2024
Abstract
Peptidoglycan hydrolases are enzymes responsible for breaking the peptidoglycan present in the bacterial cell wall, facilitating cell growth, cell division and peptidoglycan turnover. Xanthomonas citri subsp. citri (X. citri), the causal agent of citrus canker, encodes an Escherichia coli M23 peptidase [...] Read more.
Peptidoglycan hydrolases are enzymes responsible for breaking the peptidoglycan present in the bacterial cell wall, facilitating cell growth, cell division and peptidoglycan turnover. Xanthomonas citri subsp. citri (X. citri), the causal agent of citrus canker, encodes an Escherichia coli M23 peptidase EnvC homolog. EnvC is a LytM factor essential for cleaving the septal peptidoglycan, thereby facilitating the separation of daughter cells. In this study, the investigation focused on EnvC contribution to the virulence and cell separation of X. citri. It was observed that disruption of the X. citri envC gene (ΔenvC) led to a reduction in virulence. Upon inoculation into leaves of Rangpur lime (Citrus limonia Osbeck), the X. citri ΔenvC exhibited a delayed onset of citrus canker symptoms compared with the wild-type X. citri. Mutant complementation restored the wild-type phenotype. Sub-cellular localization confirmed that X. citri EnvC is a periplasmic protein. Moreover, the X. citri ΔenvC mutant exhibited elongated cells, indicating a defect in cell division. These findings support the role of EnvC in the regulation of cell wall organization, cell division, and they clarify the role of this peptidase in X. citri virulence. Full article
(This article belongs to the Section Plant Microbe Interactions)
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16 pages, 3397 KiB  
Article
The Impact of Canopy on Nutrient Fluxes through Rainfall Partitioning in a Mixed Broadleaf and Coniferous Forest
by Junhui Yang, Anzhi Wang, Lidu Shen, Guanhua Dai, Yage Liu, Yuan Zhang, Wenli Fei and Jiabing Wu
Forests 2024, 15(4), 623; https://doi.org/10.3390/f15040623 (registering DOI) - 29 Mar 2024
Abstract
Rainfall constitutes the primary input in the nutrient flux within forest ecosystems. The forest canopy modulates this flux by partitioning rainfall and selectively absorbing or adding nutrients. In mixed forests, variation in tree species composition regulates rainwater chemical composition, potentially leading to spatial [...] Read more.
Rainfall constitutes the primary input in the nutrient flux within forest ecosystems. The forest canopy modulates this flux by partitioning rainfall and selectively absorbing or adding nutrients. In mixed forests, variation in tree species composition regulates rainwater chemical composition, potentially leading to spatial heterogeneity in nutrient distribution and influencing nutrient cycling processes. This study examined the partitioning of rainfall into throughfall and stemflow, as well as their associated nutrient concentrations and fluxes, in a mixed broadleaf and coniferous forest on Changbai Mountain in Northeast China. We observed a rising trend in nutrient contents from rainfall to throughfall and then stemflow. The nutrient contents of stemflow varied largely with tree species due to the differences in canopy structure and bark morphological characteristics. The nutrient input contributed by throughfall and stemflow was 92.30 kg ha−1 during the observation period, and most elements underwent passive leaching through washout except for F and Na+. We note that the nutrient fluxes in stemflow differed among tree species, with Pinus koraiensis (PK) delivering more acid group anions and Quercus mongolica (QM) providing more cations. Our research provides new insights into nutrient cycling within mixed forest canopies, sparking a transformative advancement in forest management and protection strategies through hydrochemistry-driven solutions. Full article
(This article belongs to the Section Forest Hydrology)
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19 pages, 4750 KiB  
Article
Unveiling Torrential Flood Dynamics: A Comprehensive Study of Spatio-Temporal Patterns in the Šumadija Region, Serbia
by Ana M. Petrovi?, Igor Le??e?en and Ivan Radevski
Water 2024, 16(7), 991; https://doi.org/10.3390/w16070991 (registering DOI) - 29 Mar 2024
Abstract
This paper presents a comprehensive analysis of flood frequency and a spatio-temporal characterization of historical torrential floods in the Šumadija region using water discharge datasets and documented events. A chronology of 344 recorded torrential flood events, spanning from 1929 to 2020, illustrates the [...] Read more.
This paper presents a comprehensive analysis of flood frequency and a spatio-temporal characterization of historical torrential floods in the Šumadija region using water discharge datasets and documented events. A chronology of 344 recorded torrential flood events, spanning from 1929 to 2020, illustrates the region’s vulnerability, with a death toll exceeding 43. The study defines the intra-annual primary and secondary peaks of torrential flood occurrences and explains their spatial distribution. Furthermore, the identification of suitable probability distribution functions underscores the necessity of tailored approaches for effective flood risk management in this diverse geographical environment. The study employed Flood Frequency Analysis (FFA) and goodness-of-fit tests, including the Kolmogorov–Smirnov (K-S) and Cramér–von Mises (CvM) tests, to assess the frequency and magnitude of flood events and evaluate diverse distribution functions. The main results include the identification of suitable probability distribution functions for each river within the region, emphasizing the need for tailored approaches in flood risk management. Additionally, discharge values for various return periods offer crucial insights for informed decision-making in flood risk management and infrastructure planning. Full article
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15 pages, 7082 KiB  
Article
Machine Learning Phase Prediction of Light-Weight High-Entropy Alloys Containing Aluminum, Magnesium, and Lithium
by Shenglong Li, Rui Liu, Hongwei Yan, Zhihui Li, Yanan Li, Xiwu Li, Yongan Zhang and Baiqing Xiong
Metals 2024, 14(4), 400; https://doi.org/10.3390/met14040400 (registering DOI) - 29 Mar 2024
Abstract
With the development of society, there is an increasingly urgent demand for light-weight, high-strength, and high-temperature-resistant structural materials. High-entropy alloys (HEAs) owe much of their unusual properties to the selection among three phases: solid solution (SS), intermetallic compound (IM), and mixed SS and [...] Read more.
With the development of society, there is an increasingly urgent demand for light-weight, high-strength, and high-temperature-resistant structural materials. High-entropy alloys (HEAs) owe much of their unusual properties to the selection among three phases: solid solution (SS), intermetallic compound (IM), and mixed SS and IM (SS and IM). Therefore, accurate phase prediction is crucial for guiding the selection of element combinations to form HEAs with desired properties. Light high-entropy alloys (LHEAs), as a significant branch of HEAs, exhibit excellent performance in terms of specific strength. In this study, we employ a machine learning (ML) method to realize the design of light-weight high-entropy alloys based on solid solutions. We determined the Gradient Boosting Classifier model as the best machine learning model through a two-step feature and model selection, in which its accuracy and F1_Score achieve 0.9166 and 0.8923. According to the predicted results, we obtained Al28Li35Mg15Zn10Cu12 LHEAs, which are mainly composed of 90% solid solution. This alloy accords with the prediction results of machine learning. But it is made up of a two-phase solid solution. In order to obtain a light-weight high-entropy alloy dominated by a single solid solution, we designed Al24Li15Mg26Zn9Cu26 LHEAs on the basis of machine learning prediction results accompanied by expert experience. Its main structure includes a single-phase solid solution. Our work provides an alternative approach to the computational design of HEAs and provides a direction for future exploration of light-weight high-entropy alloys. Full article
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20 pages, 1949 KiB  
Article
Long-Term Region-Specific Mitochondrial Functionality Changes in Both Cerebral Hemispheres after fMCAo Model of Ischemic Stroke
by Ksenija Lūcija Bahire, Reinis Ma?uhins, Fiona Bello, Jolanta Upīte, Aleksandrs Makarovs and Baiba Jansone
Antioxidants 2024, 13(4), 416; https://doi.org/10.3390/antiox13040416 (registering DOI) - 29 Mar 2024
Abstract
Cerebral ischemia/reperfusion (I/R) refers to a secondary brain injury that results in mitochondrial dysfunction of variable extent, leading to neuronal cell damage. The impact of this process has mainly been studied in the short term, from the early hours up to one week [...] Read more.
Cerebral ischemia/reperfusion (I/R) refers to a secondary brain injury that results in mitochondrial dysfunction of variable extent, leading to neuronal cell damage. The impact of this process has mainly been studied in the short term, from the early hours up to one week after blood flow reperfusion, and in the ischemic hemisphere only. The focus of this study was to assess the long-term impacts of I/R on mitochondrial functionality using high-resolution fluorespirometry to evaluate state-dependent activities in both ischemic (ipsilateral) and non-ischemic (contralateral) hemispheres of male mice 60, 90, 120, and 180 days after I/R caused by 60-min-long filament-induced middle cerebral artery occlusion (fMCAo). Our results indicate that in cortical tissues, succinate-supported oxygen flux (Complex I&II OXPHOS state) and H2O2 production (Complex II LEAK state) were significantly decreased in the fMCAo (stroke) group ipsilateral hemisphere compared to measurements in the contralateral hemisphere 60 and 90 days after stroke. In hippocampal tissues, during the Complex I&II ET state, mitochondrial respiration was generally lower in the ipsilateral compared to the contralateral hemisphere 90 days following stroke. An aging-dependent impact on mitochondria oxygen consumption following I/R injury was observed 180 days after surgery, wherein Complex I&II activities were lowest in both hemispheres. The obtained results highlight the importance of long-term studies in the field of ischemic stroke, particularly when evaluating mitochondrial bioenergetics in specific brain regions within and between separately affected cerebral hemispheres. Full article
(This article belongs to the Special Issue Oxidative Stress and Pathophysiology of Stroke)
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13 pages, 3938 KiB  
Article
Surface Quality Related to Face Milling Parameters in 3D Printed Carbon Fiber-Reinforced PETG
by Mohamad El Mehtedi, Pasquale Buonadonna, Gabriela Loi, Rayane El Mohtadi, Mauro Carta and Francesco Aymerich
J. Compos. Sci. 2024, 8(4), 128; https://doi.org/10.3390/jcs8040128 (registering DOI) - 29 Mar 2024
Abstract
Three-dimensional printing technology holds significant potential for enhancing the flexibility and cost-efficiency of producing carbon fiber-reinforced polymer composites (CFRPs). However, it faces limitations such as challenges in achieving high surface qualityand precise dimensional accuracy and managing the distinctive anisotropic mechanical properties that it [...] Read more.
Three-dimensional printing technology holds significant potential for enhancing the flexibility and cost-efficiency of producing carbon fiber-reinforced polymer composites (CFRPs). However, it faces limitations such as challenges in achieving high surface qualityand precise dimensional accuracy and managing the distinctive anisotropic mechanical properties that it demonstrates. This study aims to explore the machinability of 3D printed PETG infused with 20% short carbon fiber and to assess the resulting surface roughness and burr formation. Employing a Design of Experiments (DoE) approach, three factors were considered: rotational speed, feed rate, and depth of cut. These factors were tested at varying levels—rotational speeds of 3000, 5500, and 8000 rpm; feed rates of 400, 600, and 800 mm/min; and depth of cut values of 0.2, 0.4, 0.6, and 0.8 mm. The evaluation of machinability relied on two key response parameters: surface roughness (Sa) determined from the milled surface and burr height measured on both sides using a roughness meter. The findings revealed a significant influence of milling parameters on both roughness and burr formation. However, the ideal conditions for minimizing roughness and reducing burr formation did not align. Furthermore, a comparative analysis was conducted between these results and the machinability of PETG under similar conditions. Full article
(This article belongs to the Special Issue Carbon Fiber Composites, Volume III)
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