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Open AccessArticle
Testing the Wear Mechanisms of the Components of Machines Used in Fossil Energy Resource Extraction
Energies 2021, 14(8), 2125; https://doi.org/10.3390/en14082125 (registering DOI) - 10 Apr 2021
Abstract
The paper presents the results of tests of wear of hardened wear-resistant steels in the presence of quartz, coal and coal-mineral abrasives of a differentiated ratios of each component and in the case without abrasives. The tests were carried out on a ring-on-ring [...] Read more.
The paper presents the results of tests of wear of hardened wear-resistant steels in the presence of quartz, coal and coal-mineral abrasives of a differentiated ratios of each component and in the case without abrasives. The tests were carried out on a ring-on-ring test stand. Volume loss was the parameter used to characterize the wear level. Based on the Scanning Electron Microscopy (SEM) observations, different mechanisms of surface destruction depending on the type of abrasive were found. For the quartz abrasive, it was shown that the quartz grains cause micro-cutting, but surface cracks also appear that further transform into shallow holes. In the case of mixtures of quartz with coal, the surface was micro-scratched by quartz grains, but some of these grains were hammered into the surface, what was favoured by the presence of coal fractions. In the case of coal abrasive, traces of single cutting were observed, as well as unremoved scratches formed at the sample grinding stage. Based on the wear observation, two models of steel surface wear in the presence of coal and coal-mineral abrasives were determined. Full article
(This article belongs to the Special Issue The IMTech 2021 Innovative Mining Technologies)
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Open AccessReview
Enantioselective Mixed Matrix Membranes for Chiral Resolution
Membranes 2021, 11(4), 279; https://doi.org/10.3390/membranes11040279 (registering DOI) - 10 Apr 2021
Abstract
Most pharmaceuticals are stereoisomers that each enantiomer shows dramatically different biological activity. Therefore, the production of optically pure chemicals through sustainable and energy-efficient technology is one of the main objectives in the pharmaceutical industry. Membrane-based separation is a continuous process performed on a [...] Read more.
Most pharmaceuticals are stereoisomers that each enantiomer shows dramatically different biological activity. Therefore, the production of optically pure chemicals through sustainable and energy-efficient technology is one of the main objectives in the pharmaceutical industry. Membrane-based separation is a continuous process performed on a large scale that uses far less energy than the conventional thermal separation process. Enantioselective polymer membranes have been developed for chiral resolution of pharmaceuticals; however, it is difficult to generate sufficient enantiomeric excess (ee) with conventional polymers. This article describes a chiral resolution strategy using a composite structure of mixed matrix membrane that employs chiral fillers. We discuss several enantioselective fillers, including metal-organic frameworks (MOFs), covalent organic frameworks (COFs), zeolites, porous organic cages (POCs), and their potential use as chiral fillers in mixed matrix membranes. State-of-the-art enantioselective mixed matrix membranes (MMMs) and the future design consideration for highly efficient enantioselective MMMs are discussed. Full article
(This article belongs to the Special Issue Emerging Materials for Mixed-Matrix Membranes)
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Open AccessArticle
Simultaneous Identification of EGFR,KRAS,ERBB2, and TP53 Mutations in Patients with Non-Small Cell Lung Cancer by Machine Learning-Derived Three-Dimensional Radiomics
Cancers 2021, 13(8), 1814; https://doi.org/10.3390/cancers13081814 (registering DOI) - 10 Apr 2021
Abstract
Purpose: To develop a machine learning-derived radiomics approach to simultaneously discriminate epidermal growth factor receptor (EGFR), Kirsten rat sarcoma viral oncogene (KRAS), Erb-B2 receptor tyrosine kinase 2 (ERBB2), and tumor protein 53 (TP53) genetic mutations [...] Read more.
Purpose: To develop a machine learning-derived radiomics approach to simultaneously discriminate epidermal growth factor receptor (EGFR), Kirsten rat sarcoma viral oncogene (KRAS), Erb-B2 receptor tyrosine kinase 2 (ERBB2), and tumor protein 53 (TP53) genetic mutations in patients with non-small cell lung cancer (NSCLC). Methods: This study included consecutive patients from April 2018 to June 2020 who had histologically confirmed NSCLC, and underwent pre-surgical contrast-enhanced CT and post-surgical next-generation sequencing (NGS) tests to determine the presence of EGFR, KRAS, ERBB2, and TP53 mutations. A dedicated radiomics analysis package extracted 1672 radiomic features in three dimensions. Discriminative models were established using the least absolute shrinkage and selection operator to determine the presence of EGFR, KRAS, ERBB2, and TP53 mutations, based on radiomic features and relevant clinical factors. Results: In 134 patients (63.6 ± 8.9 years), the 20 most relevant radiomic features (13 for KRAS) to mutations were selected to construct models. The areas under the curve (AUCs) of the combined model (radiomic features and relevant clinical factors) for discriminating EGFR, KRAS, ERBB2, and TP53 mutations were 0.78 (95% CI: 0.70–0.86), 0.81 (0.69–0.93), 0.87 (0.78–0.95), and 0.84 (0.78–0.91), respectively. In particular, the specificity to exclude EGFR mutations was 0.96 (0.87–0.99). The sensitivity to determine KRAS, ERBB2, and TP53 mutations ranged from 0.82 (0.69–90) to 0.92 (0.62–0.99). Conclusions: Machine learning-derived 3D radiomics can simultaneously discriminate the presence of EGFR, KRAS, ERBB2, and TP53 mutations in patients with NSCLC. This noninvasive and low-cost approach may be helpful in screening patients before invasive sampling and NGS testing. Full article
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Open AccessArticle
Screening and Identification of Host Proteins Interacting with Iris lactea var. chinensis Metallothionein IlMT2a by Yeast Two-Hybrid Assay
Genes 2021, 12(4), 554; https://doi.org/10.3390/genes12040554 (registering DOI) - 10 Apr 2021
Abstract
Iris lactea var. chinensis (Fisch.) (I. lactea var. chinensis) is a well-known cadmium (Cd)-tolerant plant and we have previously shown that the metallothionein gene, IlMT2a, of the plant may be playing a key role in conferring the Cd tolerance. In [...] Read more.
Iris lactea var. chinensis (Fisch.) (I. lactea var. chinensis) is a well-known cadmium (Cd)-tolerant plant and we have previously shown that the metallothionein gene, IlMT2a, of the plant may be playing a key role in conferring the Cd tolerance. In this study, we have identified several proteins interacting with the IlMT2a by screening yeast two-hybrid library constructed from cDNAs isolated from Cd-treated I. lacteal var. chinensis plants. Putative functions of these proteins include those involved in photosynthesis, ROS scavenge, nutrient transport, and transcriptional regulation, to name a few. In particular, another metallothionein, which we assigned the name of IlMT3, was identified as an interacting partner of the IlMT2a. Unlike IlMT2a, it did not provide any significant protection against Cd toxicity in transgenic Arabidopsis thaliana L. (A. thaliana). To our knowledge, this is the first time ever reporting the interaction of two metallothionein proteins in plants. Learning the biological significance of the interaction between IlMT2a and IlMT3 would be the focus of future study and would be able to provide valuable insights into the understanding plant metallothionein’s diverse and complex roles in coordinating many important cellular physiologies including stress responses, gene regulations, and energy metabolisms. Full article
(This article belongs to the Section Plant Genetics and Genomics)
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Open AccessArticle
Teaching Spatial Planning Using Elements of Design Thinking as an Example of Heuristic in Urban Planning
Sustainability 2021, 13(8), 4225; https://doi.org/10.3390/su13084225 (registering DOI) - 10 Apr 2021
Abstract
In modern urban analysis, line–nodal connections are often used as a model, diagram or matrix for describing space and its accompanying phenomena. In practice, the search for relationships in space is often nothing but the designation of lines reflecting their physical and nonphysical [...] Read more.
In modern urban analysis, line–nodal connections are often used as a model, diagram or matrix for describing space and its accompanying phenomena. In practice, the search for relationships in space is often nothing but the designation of lines reflecting their physical and nonphysical association by their geometry. Recording the spatial issues of a city constituting a very complex structure on the surface of paper, or on a computer monitor, is an extremely difficult conceptual task. At the heart of Design Thinking is a deep understanding of the relationship between different elements. It can therefore be concluded that heuristics are the basis for understanding the Design Thinking method. An attempt was made to check whether the Design Thinking method can restore the optimal balance between modern tools used to develop course projects, and the need to search for the best solution constituting the idea of the project. The article presents the results of two-year research on the use of the Design Thinking method in academic teaching of subjects related to the subject of spatial planning. Thanks to the use of the Design Thinking method in teaching spatial planning, it is often possible to discover design possibilities and proposals that surprise students. Full article
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Open AccessArticle
Material Selection and Characterization for a Novel Frame-Integrated Curtain Wall
Materials 2021, 14(8), 1896; https://doi.org/10.3390/ma14081896 (registering DOI) - 10 Apr 2021
Abstract
Curtain walls are the façade of choice in high-rise buildings and an indispensable element of architecture for a contemporary city. In conventional curtain walls, the glass panels are simply supported by the metal framing which transfers any imposed load to the building structure. [...] Read more.
Curtain walls are the façade of choice in high-rise buildings and an indispensable element of architecture for a contemporary city. In conventional curtain walls, the glass panels are simply supported by the metal framing which transfers any imposed load to the building structure. The absence of composite action between glass and metal results in deep frames, protruding to the inside, occupying valuable space and causing visual disruption. In response to the limited performance of conventional systems, an innovative frame-integrated unitized curtain wall is proposed to reduce structural depth to one fifth (80%) allowing an inside flush finish and gaining nettable space. The novel curtain wall is achieved by bonding a pultruded glass fiber reinforced polymer (GFRP) frame to the glass producing a composite insulated glass unit (IGU). This paper selects the candidate frame and adhesive materials performing mechanical tests on GFRP pultrusions to characterize strength and elasticity and on GFRP-glass connections to identify failure module and strength. The material test results are used in a computer-based numerical model of a GFRP-glass composite unitized panel to predict the structural performance when subjected to realistic wind loads. The results confirm the reduction to one fifth is possible since the allowable deflections are within limits. It also indicates that the GFRP areas adjacent to the support might require reinforcing to reduce shear stresses. Full article
(This article belongs to the Special Issue Advances in Construction and Building Materials)
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Open AccessArticle
Numerical Analysis of the Influence of Different Flow Patterns on Power and Reactant Transmission in Tubular-Shaped PEMFC
Energies 2021, 14(8), 2127; https://doi.org/10.3390/en14082127 (registering DOI) - 10 Apr 2021
Abstract
The influence of a tubular structure PEMFC (proton exchange membrane fuel cell) with different flow patterns is investigated in this study. A complete 3D non-isothermal model is constructed for square and circular tubular PEMFCs, and the distribution of oxygen and water concentration in [...] Read more.
The influence of a tubular structure PEMFC (proton exchange membrane fuel cell) with different flow patterns is investigated in this study. A complete 3D non-isothermal model is constructed for square and circular tubular PEMFCs, and the distribution of oxygen and water concentration in cathode channels, current density, power density and cell net power are studied. To this end, the four arrangements of tubular PEMFC are square chordal (SC), square peripheral (SP), circular chordal (CC) and circular peripheral (CP). The calculation of the effective area and boundary conditions remains the same when performing all four configurations. The consequent results show that for the tubular structure PEMFC, compared with the co-flow mode, the counter-flow mode has better performance and provides more power. Using a counter-flow pattern, the permeability of the species increases, so a more uniform reaction occurs at the cell. The entire performance of the SP and CP model is not as good as that of the SC and CC models because the SP and CP models have a higher flow velocity. Moreover, the SC model using the counter-flow pattern has the maximum predicted net power among the other models. Full article
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Open AccessCommunication
Stable Coloured Micrometric Films from Highly Concentrated Nano-Silver Sols: The Role of the Stabilizing Agents
Nanomaterials 2021, 11(4), 980; https://doi.org/10.3390/nano11040980 (registering DOI) - 10 Apr 2021
Abstract
The synthesis of highly concentrated aqueous silver nanoparticles (NPs), exploiting different types of polymeric stabilizing agents, has been extensively investigated, especially for the stabilization of spherical yellow nanoparticles. In this context, here, a successful and easy wet chemical method was adopted to synthesize [...] Read more.
The synthesis of highly concentrated aqueous silver nanoparticles (NPs), exploiting different types of polymeric stabilizing agents, has been extensively investigated, especially for the stabilization of spherical yellow nanoparticles. In this context, here, a successful and easy wet chemical method was adopted to synthesize concentrated primary colored (yellow, red, blue and green) sols. The influence of polyvinylpyrrolidone (PVP) and polyvinyl alcohol (PVA) in affecting the final stability was finely investigating via UV/Vis spectroscopy, dynamic light scattering, TEM and colorimetric analysis. The next step consisted on the deposition of obtained sols onto a crown-treated polyethylene terephthalate (PET) support to obtain transparent colored micrometric homogeneous films. The fabricated PVP-based Ag films were revealed to be outstandingly UV-stable, contrarily to PVA-based films, probably due to the degradation of the polymer itself. Indeed, after UV aging tests, the PVA macromolecules could be broken and chemically modified (demonstrated by FT-IR analyses). This resulted in there being insufficient macromolecules to efficiently cover the surface of the nanoparticles, meaning that the nanoparticles tended to aggregate with each other, destabilizing the system itself. Hence, the obtained colored films described herein could represent a promising tool for different applications, from color shifting to optoelectronic devices. Full article
(This article belongs to the Special Issue Synthesis and Functionalization of Colloidal Nanoparticles)
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Open AccessArticle
Gene Module Analysis Reveals Cell-Type Specificity and Potential Target Genes in Autism’s Pathogenesis
Biomedicines 2021, 9(4), 410; https://doi.org/10.3390/biomedicines9040410 (registering DOI) - 10 Apr 2021
Abstract
Multiple genetic factors contribute to the pathogenesis of autism spectrum disorder (ASD), a kind of neurodevelopmental disorder. Genes were usually studied separately for their associations with ASD. However, genes associated with ASD do not act alone but interact with each other in a [...] Read more.
Multiple genetic factors contribute to the pathogenesis of autism spectrum disorder (ASD), a kind of neurodevelopmental disorder. Genes were usually studied separately for their associations with ASD. However, genes associated with ASD do not act alone but interact with each other in a network module. The identification of these modules is the basis for the systematic understanding of the pathogenesis of ASD. Moreover, ASD is characterized by highly pathogenic heterogeneity, and gene modules associated with ASD are cell-type-specific. In this study, based on the single-nucleus RNA sequencing data of 41 post-mortem tissue samples from the prefrontal cortex and anterior cingulate cortex of 19 ASD patients and 16 control individuals, we applied sparse module activity factorization, a matrix decomposition method consistent with the multi-factor and heterogeneous characteristics of ASD pathogenesis, to identify cell-type-specific gene modules. Then, statistical procedures were performed to detect highly reproducible cell-type-specific ASD-associated gene modules. Through the enrichment analysis of cell markers, 31 cell-type-specific gene modules related to ASD were further screened out. These 31 gene modules are all enriched with curated ASD risk genes. Finally, we utilized the expression patterns of these cell-type-specific ASD-associated gene modules to build predictive models for ASD. The excellent predictive performance also proved the associations between these gene modules and ASD. Our study confirmed the multifactorial and cell-type-specific characteristics of ASD pathogeneses. The results showed that excitatory neurons such as L2/3, L4, and L5/6-CC play essential roles in ASD’s pathogenic processes. We identified the potential ASD target genes that act together in cell-type-specific modules, such as NRG3, KCNIP4, BAI3, PTPRD, LRRTM4, and LINGO2 in the L2/3 gene modules. Our study offers new potential genomic targets for ASD and provides a novel method to study gene modules involved in the pathogenesis of ASD. Full article
(This article belongs to the Special Issue Bioinformatics and Its Application in Biomedicine)
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Open AccessArticle
PEA-OXA Mitigates Oxaliplatin-Induced Painful Neuropathy through NF-κB/Nrf-2 Axis
Int. J. Mol. Sci. 2021, 22(8), 3927; https://doi.org/10.3390/ijms22083927 (registering DOI) - 10 Apr 2021
Abstract
Chemotherapy-induced neuropathy is a common, dose-dependent adverse effect of several antineoplastics, such as oxaliplatin (L-OHP). The aim of the present work was to evaluate the potential beneficial effects of 2-pentadecyl-2-oxazoline (PEA-OXA) in a murine model of oxaliplatin-induced peripheral neuropathy (OIPN). OIPN was induced [...] Read more.
Chemotherapy-induced neuropathy is a common, dose-dependent adverse effect of several antineoplastics, such as oxaliplatin (L-OHP). The aim of the present work was to evaluate the potential beneficial effects of 2-pentadecyl-2-oxazoline (PEA-OXA) in a murine model of oxaliplatin-induced peripheral neuropathy (OIPN). OIPN was induced by an intraperitoneally injection of L-OHP in rats on five consecutive days (D0–4) for a final cumulative dose of 10 mg/kg. PEA-OXA and ultramicronized palmitoylethanolamide (PEAum), both 10 mg/kg, were given orally 15–20 min prior (L-OHP) and sacrifice was made on day 25. Our results demonstrated that PEA-OXA, more than PEAum, reduced the development of hypersensitivity in rats; this was associated with the reduction in hyperactivation of glia cells and the increased production of proinflammatory cytokines in the dorsal horn of the spinal cord, accompanied by an upregulation of neurotrophic factors in the dorsal root ganglia (DRG). Moreover, we showed that PEA-OXA reduced L-OHP damage via a reduction in NF-κB pathway activation and a modulation of Nrf-2 pathways. Our findings identify PEA-OXA as a therapeutic target in chemotherapy-induced painful neuropathy, through the biomolecular signaling NF-κB/Nrf-2 axis, thanks to its abilities to counteract L-OHP damage. Therefore, we can consider PEA-OXA as a promising adjunct to chemotherapy to reduce chronic pain in patients. Full article
(This article belongs to the Special Issue Mechanisms of Chemotherapy-Induced Peripheral Neuropathy)
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Open AccessArticle
Melatonin Restores the Developmental Competence of Heat Stressed Porcine Oocytes, and Alters the Expression of Genes Related to Oocyte Maturation
Animals 2021, 11(4), 1086; https://doi.org/10.3390/ani11041086 (registering DOI) - 10 Apr 2021
Abstract
Melatonin enhances the quality and in vitro maturation (IVM) of oocytes under heat stress (HS), but the mechanism of melatonin in reducing HS injury on oocytes is not fully understood. In this study, porcine cumulus-oocyte complexes (COCs) were randomly divided into three groups. [...] Read more.
Melatonin enhances the quality and in vitro maturation (IVM) of oocytes under heat stress (HS), but the mechanism of melatonin in reducing HS injury on oocytes is not fully understood. In this study, porcine cumulus-oocyte complexes (COCs) were randomly divided into three groups. The COCs of the control group were cultured at 38.5 °C for 42 h, and the COCs of the HS group were cultured at 41.5 °C for 4 h, and then transferred into 38.5 °C for 38 h. The COCs of the HS + melatonin group were cultured with 10−9 M melatonin under the same conditions as the HS group. The survival rate, maturation rate, distribution of α-tubulin and F-actin of the oocytes were assessed. In addition, the expression profiles for genes related to the oocyte maturation, including heat shock protein 70 (HSP70), nuclear factor erythroid 2-related factor 2 (NRF2), cyclin-dependent kinase 1 (CDK1), growth differentiation factor 9 (GDF9) were analyzed by real-time quantitative PCR. The results showed that HS decreased the survival rate and maturation rate, distribution of α-tubulin and F-actin, but melatonin treatment could partly counteract these adverse effects. In addition, HS increased expression of HSP70 and NRF2 mRNA, and melatonin treatment had a similar effect on HSP70 expression, but had a contrary effect on NRF2 expression. Furthermore, HS inhibited expression of CDK1 and GDF9 mRNA, but melatonin treatment could weaken the effect on GDF9 expression induced by HS. In summary, melatonin treatment could attenuate the unfavorable effects induced by HS to enhance developmental competence of porcine oocytes during IVM. Full article
(This article belongs to the Section Animal Reproduction)
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Open AccessArticle
Effect of Silicon Nitride and Graphene Nanoplatelets on the Properties of Aluminum Metal Matrix Composites
Materials 2021, 14(8), 1898; https://doi.org/10.3390/ma14081898 (registering DOI) - 10 Apr 2021
Abstract
This research work aims at investigating the influence of a fixed content of silicon nitride (Si3N4) and varied contents of graphene nanoplatelets (GNPs) on the physical (density, structural, morphological) and mechanical properties (microhardness, nanoindentation) of Al-Si3N4 [...] Read more.
This research work aims at investigating the influence of a fixed content of silicon nitride (Si3N4) and varied contents of graphene nanoplatelets (GNPs) on the physical (density, structural, morphological) and mechanical properties (microhardness, nanoindentation) of Al-Si3N4-GNPs composites. The composites were fabricated by a microwave-assisted powder metallurgy route. The Si3N4 concentration was fixed at (5 wt.%) in Al-Si3N4-GNPs composites while the GNPs concentration was varied between (0 wt.%) to (1.5 wt.%) with an increment of (0.5 wt.%). The structural analysis indicates the formation of phase pure materials with high crystallinity. The microstructural analysis confirmed the presence of the Si3N4 and GNPs showing enhanced agglomeration with the increasing amount of GNPs. Moreover, the surface roughness of the synthesized composites increases with an increasing amount of GNPs reaching its maximum value (RMS = 65.32 nm) at 1.5 wt.% of GNPs. The Al-Si3N4-GNPs composites exhibit improved microhardness and promising load-indentation behavior during nanoindentation when compared to pure aluminum (Al). Moreover, Al-Si3N4-GNPs composites demonstrate higher values of compressive yield strength (CYS) and ultimate compressive strength (UCS) when compared to pure Al despite showing a declining trend with an increasing amount of GNPs in the matrix. Finally, a shear mode of fracture is prevalent in Al-Si3N4-GNPs composites under compression loading. Full article
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Open AccessArticle
Polyphenolic Compounds Extracted and Purified from Buddleja globosa Hope (Buddlejaceae) Leaves Using Natural Deep Eutectic Solvents and Centrifugal Partition Chromatography
Molecules 2021, 26(8), 2192; https://doi.org/10.3390/molecules26082192 (registering DOI) - 10 Apr 2021
Abstract
Chemical profiling of Buddleja globosa was performed by high-performance liquid chromatography coupled to electrospray ionization (HPLC-DAD-ESI-IT/MS) and quadrupole time-of-flight high-resolution mass spectrometry (HPLC-ESI-QTOF/MS). The identification of 17 main phenolic compounds in B. globosa leaf extracts was achieved. Along with caffeoyl glucoside isomers, caffeoylshikimic [...] Read more.
Chemical profiling of Buddleja globosa was performed by high-performance liquid chromatography coupled to electrospray ionization (HPLC-DAD-ESI-IT/MS) and quadrupole time-of-flight high-resolution mass spectrometry (HPLC-ESI-QTOF/MS). The identification of 17 main phenolic compounds in B. globosa leaf extracts was achieved. Along with caffeoyl glucoside isomers, caffeoylshikimic acid and several verbascoside derivatives (β-hydroxyverbascoside and β-hydroxyisoverbascoside) were identified. Among flavonoid compounds, the presence of 6-hydroxyluteolin-7-O-glucoside, quercetin-3-O-glucoside, luteolin 7-O-glucoside, apigenin 7-O-glucoside was confirmed. Campneoside I, forsythoside B, lipedoside A and forsythoside A were identified along with verbascoside, isoverbascoside, eukovoside and martynoside. The isolation of two bioactive phenolic compounds verbascoside and forsythoside B from Buddleja globosa (Buddlejaceae) was successfully achieved by centrifugal partition chromatography (CPC). Both compounds were obtained in one-step using optimized CPC methodology with the two-phase solvent system comprising ethyl acetate-n-butanol-ethanol-water (0.25: 0.75: 0.1: 1, v/v). Additionally, eight Natural Deep Eutectic Solvents (NADESs) were tested for the extraction of polyphenols and compared with 80% methanol. The contents of verbascoside and luteolin 7-O-glucoside after extraction with 80% methanol were 26.165 and 3.206 mg/g, respectively. Among the NADESs tested in this study, proline- citric acid (1:1) and choline chloride-1, 2- propanediol (1:2) were the most promising solvents. With these NADES, extraction yields for verbascoside and luteolin 7-O-glucoside were 51.045 and 4.387 mg/g, respectively. Taken together, the results of this study confirm that CPC enabled the fast isolation of bioactive polyphenols from B. globosa. NADESs displayed higher extraction efficiency of phenolic and therefore could be used as an ecofriendly alternative to classic organic solvents. Full article
Open AccessArticle
Remotely Piloted Aircraft and Random Forest in the Evaluation of the Spatial Variability of Foliar Nitrogen in Coffee Crop
Remote Sens. 2021, 13(8), 1471; https://doi.org/10.3390/rs13081471 (registering DOI) - 10 Apr 2021
Abstract
The development of approaches to determine the spatial variability of nitrogen (N) into coffee leaves is essential to increase productivity and reduce production costs and environmental impacts associated with excessive N applications. Thus, this study aimed to assess the potential of the Random [...] Read more.
The development of approaches to determine the spatial variability of nitrogen (N) into coffee leaves is essential to increase productivity and reduce production costs and environmental impacts associated with excessive N applications. Thus, this study aimed to assess the potential of the Random Forest (RF) machine learning method applied to vegetation indices (VI) obtained from Remotely Piloted Aircraft (RPA) images to measure the N content in coffee plants. A total of 10 VI were obtained from multispectral images by a camera attached to a rotary-wing RPA. The RGB orthomosaic was used to determine sampling points at the crop area, which were ranked by N levels in the plants as deficient, critical, or sufficient. The chemical analysis of N content in the coffee leaves, as well as the VI values in sample points, were used as input parameters for the image training and its classification by the RF. The suggested model has shown global accuracy and a kappa coefficient of up to 0.91 and 0.86, respectively. The best results were achieved using the Green Normalized Difference Vegetation (GNDVI) and Green Optimized Soil Adjusted Vegetation Index (GOSAVI). In addition, the model enabled the evaluation of the spatial distribution of N in the coffee trees, as well as quantification of N deficiency in the crop for the whole area. The GNDVI and GOSAVI allowed the verification that 22% of the entire crop area had plants with N deficiency symptoms, which would result in a reduction of 78% in the amount of N applied by the producer. Full article
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Open AccessReview
Security Challenges of Location Privacy in VANETs and State-of-The Art Solutions: A Survey
Future Internet 2021, 13(4), 96; https://doi.org/10.3390/fi13040096 (registering DOI) - 10 Apr 2021
Abstract
A Vehicular Ad-hoc Network (VANET) comprises a group of moving or stationary vehicles connected by a wireless network. VANETs play a vital role in providing safety and comfort to drivers in vehicular environments. They provide smart traffic control and real-time information, event allocation. [...] Read more.
A Vehicular Ad-hoc Network (VANET) comprises a group of moving or stationary vehicles connected by a wireless network. VANETs play a vital role in providing safety and comfort to drivers in vehicular environments. They provide smart traffic control and real-time information, event allocation. VANETs have received attention in support of safe driving, intelligent navigation, emergency and entertainment applications in vehicles. Nevertheless, these increasingly linked vehicles pose a range of new safety and security risks to both the host and its associated properties and may even have fatal consequences. Violations of national privacy and vehicle identities are a major obstacle to introducing forced contact protocols in vehicles. Location privacy refers to the privacy of the vehicle (driver) and the location of the vehicle. Whenever a vehicle sends a message, no one but authorized entities should know their real identity and location of the vehicle. All the messages sent by the vehicle must be authenticated before processing, hence location privacy is an important design aspect to be considered in VANETs operations. The novelty of this paper is that it specifically reviews location privacy in VANETs in terms of operational and safety concerns. Furthermore, it presents a critical analysis of various attacks, identity thefts, manipulation and other techniques in vogue for location privacy protection available in state-of-the-art solutions for VANETs. The efforts in this paper will help researchers to develop a great breadth of understanding pertaining to location privacy issues and various security threats encountered by VANETs and present the critical analysis of the available state-of-the- art solutions to maintain location privacy in VANETs. Full article
(This article belongs to the Collection Information Systems Security)
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Open AccessArticle
PISCO_HyM_GR2M: A Model of Monthly Water Balance in Peru (1981–2020)
Water 2021, 13(8), 1048; https://doi.org/10.3390/w13081048 (registering DOI) - 10 Apr 2021
Abstract
Quantification of the surface water offer is crucial for its management. In Peru, the low spatial density of hydrometric stations makes this task challenging. This work aims to evaluate the hydrological performance of a monthly water balance model in Peru using precipitation and [...] Read more.
Quantification of the surface water offer is crucial for its management. In Peru, the low spatial density of hydrometric stations makes this task challenging. This work aims to evaluate the hydrological performance of a monthly water balance model in Peru using precipitation and evapotranspiration data from the high-resolution meteorological PISCO dataset, which has been developed by the National Service of Meteorology and Hydrology of Peru (SENAMHI). A regionalization approach based on Fourier Amplitude Sensitivity Testing (FAST) of the rainfall-runoff (RR) and runoff variability (RV) indices defined 14 calibration regions nationwide. Next, the GR2M model was used at a semi-distributed scale in 3594 sub-basins and river streams to simulate monthly discharges from January 1981 to March 2020. Model performance was evaluated using the Kling–Gupta efficiency (KGE), square root transferred Nash–Sutcliffe efficiency (NSEsqrt), and water balance error (WBE) metrics. The results show a very well representation of monthly discharges for a large portion of Peruvian sub-basins (KGE ≥ 0.75, NSEsqrt ≥ 0.65, and −0.29 < WBE < 0.23). Finally, this study introduces a product of continuous monthly discharge rates in Peru, named PISCO_HyM_GR2M, to understand surface water balance in data-scarce sub-basins. Full article
(This article belongs to the Section Hydrology and Hydrogeology)
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Open AccessArticle
Radiomic Feature Reduction Approach to Predict Breast Cancer by Contrast-Enhanced Spectral Mammography Images
Diagnostics 2021, 11(4), 684; https://doi.org/10.3390/diagnostics11040684 (registering DOI) - 10 Apr 2021
Abstract
Contrast-enhanced spectral mammography (CESM) is an advanced instrument for breast care that is still operator dependent. The aim of this paper is the proposal of an automated system able to discriminate benign and malignant breast lesions based on radiomic analysis. We selected a [...] Read more.
Contrast-enhanced spectral mammography (CESM) is an advanced instrument for breast care that is still operator dependent. The aim of this paper is the proposal of an automated system able to discriminate benign and malignant breast lesions based on radiomic analysis. We selected a set of 58 regions of interest (ROIs) extracted from 53 patients referred to Istituto Tumori “Giovanni Paolo II” of Bari (Italy) for the breast cancer screening phase between March 2017 and June 2018. We extracted 464 features of different kinds, such as points and corners of interest, textural and statistical features from both the original ROIs and the ones obtained by a Haar decomposition and a gradient image implementation. The features data had a large dimension that can affect the process and accuracy of cancer classification. Therefore, a classification scheme for dimension reduction was needed. Specifically, a principal component analysis (PCA) dimension reduction technique that includes the calculation of variance proportion for eigenvector selection was used. For the classification method, we trained three different classifiers, that is a random forest, a naïve Bayes and a logistic regression, on each sub-set of principal components (PC) selected by a sequential forward algorithm. Moreover, we focused on the starting features that contributed most to the calculation of the related PCs, which returned the best classification models. The method obtained with the aid of the random forest classifier resulted in the best prediction of benign/malignant ROIs with median values for sensitivity and specificity of 88.37% and 100%, respectively, by using only three PCs. The features that had shown the greatest contribution to the definition of the same were almost all extracted from the LE images. Our system could represent a valid support tool for radiologists for interpreting CESM images. Full article
(This article belongs to the Special Issue Advancement in Breast Diagnostic and Interventional Radiology)
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Open AccessReview
Mechanisms of Antibiotic Resistance in Important Gram-Positive and Gram-Negative Pathogens and Novel Antibiotic Solutions
Antibiotics 2021, 10(4), 415; https://doi.org/10.3390/antibiotics10040415 (registering DOI) - 10 Apr 2021
Abstract
Multidrug-resistant bacteria have on overwhelming impact on human health, as they cause over 670,000 infections and 33,000 deaths annually in the European Union alone. Of these, the vast majority of infections and deaths are caused by only a handful of species—multi-drug resistant Escherichia [...] Read more.
Multidrug-resistant bacteria have on overwhelming impact on human health, as they cause over 670,000 infections and 33,000 deaths annually in the European Union alone. Of these, the vast majority of infections and deaths are caused by only a handful of species—multi-drug resistant Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Enterococcus spp., Acinetobacter spp. and Klebsiella pneumoniae. These pathogens employ a multitude of antibiotic resistance mechanisms, such as the production of antibiotic deactivating enzymes, changes in antibiotic targets, or a reduction of intracellular antibiotic concentration, which render them insusceptible to multiple antibiotics. The purpose of this review is to summarize in a clinical manner the resistance mechanisms of each of these 6 pathogens, as well as the mechanisms of recently developed antibiotics designed to overcome them. Through a basic understanding of the mechanisms of antibiotic resistance, the clinician can better comprehend and predict resistance patterns even to antibiotics not reported on the antibiogram and can subsequently select the most appropriate antibiotic for the pathogen in question. Full article
(This article belongs to the Special Issue Clinical Approach to Antibiotic Resistance: The Definitive Issue)
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Open AccessArticle
A Tree Ring Measurement Method Based on Error Correction in Digital Image of Stem Analysis Disk
Forests 2021, 12(4), 464; https://doi.org/10.3390/f12040464 (registering DOI) - 10 Apr 2021
Abstract
Stem analysis is an essential aspect in forestry investigation and forest management, as it is a primary method to study the growth law of trees. Stem analysis requires measuring the width and number of tree rings to ensure the accurate measurement, expand applicable [...] Read more.
Stem analysis is an essential aspect in forestry investigation and forest management, as it is a primary method to study the growth law of trees. Stem analysis requires measuring the width and number of tree rings to ensure the accurate measurement, expand applicable tree species, and reduce operation cost. This study explores the use of Open Source Computer Vision Library (Open CV) to measure the ring radius of analytic wood disk digital images, and establish a regression equation of ring radius based on image geometric distortion correction. Here, a digital camera was used to photograph the stem disks’ tree rings to obtain digital images. The images were preprocessed with Open CV to measure the disk’s annual ring radius. The error correction model based on the least-square polynomial fitting method was established for digital image geometric distortion correction. Finally, a regression equation for tree ring radius based on the error correction model was established. Through the above steps, click the intersection point between the radius line and each ring to get the pixel distance from the ring to the pith, then the size of ring radius can be calculated by the regression equation of ring radius. The study’s method was used to measure the digital image of the Chinese fir stem disk and compare it with the actual value. The results showed that the maximum error of this method was 0.15 cm, the average error was 0.04 cm, and the average detection accuracy reached 99.34%, which met the requirements for measuring the tree ring radius by stem disk analysis. This method is simple, accurate, and suitable for coniferous and broad-leaved species, which allows researchers to analyze tree ring radius measurement, and is of great significance for analyzing the tree growth process. Full article
(This article belongs to the Special Issue Modelling of Forests Structure and Biomass Distribution)
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Open AccessReview
Radical Resection for Locally Advanced Pancreatic Cancers in the Era of New Neoadjuvant Therapy—Arterial Resection, Arterial Divestment and Total Pancreatectomy
Cancers 2021, 13(8), 1818; https://doi.org/10.3390/cancers13081818 (registering DOI) - 10 Apr 2021
Abstract
Aggressive arterial resection (AR) or total pancreatectomy (TP) in surgical treatment for locally advanced pancreatic cancer (LAPC) had long been discouraged because of their high mortality rate and unsatisfactory long-term outcomes. Recently, new chemotherapy regimens such as FOLFIRINOX or Gemcitabine and nab-paclitaxel have [...] Read more.
Aggressive arterial resection (AR) or total pancreatectomy (TP) in surgical treatment for locally advanced pancreatic cancer (LAPC) had long been discouraged because of their high mortality rate and unsatisfactory long-term outcomes. Recently, new chemotherapy regimens such as FOLFIRINOX or Gemcitabine and nab-paclitaxel have provided more adequate patient selection and local tumor suppression, justifying aggressive local resection. In this review, we investigate the recent reports focusing on arterial resection and total pancreatectomy for LAPC and discuss the rationale of such an aggressive approach in the treatment of PC. AR for LAPCs is divided into three, according to the target vessel. The hepatic artery resection is the simplest one, and the reconstruction methods comprise end-to-end, graft or transposition, and no reconstruction. Celiac axis resection is mainly done with distal pancreatectomy, which allows collateral arterial supply to the liver via the pancreas head. Resection of the superior mesenteric artery is increasingly reported, though its rationale is still controversial. Total pancreatectomy has been re-evaluated as an effective option to balance both the local control and postoperative safety. In conclusion, more and more aggressive pancreatectomy has become justified by the principle of total neoadjuvant therapy. Further technical standardization and optimal neoadjuvant strategy are mandatory for the global dissemination of aggressive pancreatectomies. Full article
(This article belongs to the Special Issue Surgical Treatment of Pancreatic Ductal Adenocarcinoma)
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Open AccessArticle
Regulation of Flowering Timing by ABA-NnSnRK1 Signaling Pathway in Lotus
Int. J. Mol. Sci. 2021, 22(8), 3932; https://doi.org/10.3390/ijms22083932 (registering DOI) - 10 Apr 2021
Abstract
The lotus produces flower buds at each node, yet most of them are aborted because of unfavorable environmental changes and the mechanism remains unclear. In this work, we proposed a potential novel pathway for ABA-mediated flower timing control in the lotus, which was [...] Read more.
The lotus produces flower buds at each node, yet most of them are aborted because of unfavorable environmental changes and the mechanism remains unclear. In this work, we proposed a potential novel pathway for ABA-mediated flower timing control in the lotus, which was explored by combining molecular, genetic, transcriptomic, biochemical, and pharmacologic approaches. We found that the aborting flower buds experienced extensive programmed cell death (PCD). The hormonal changes between the normal and aborting flower buds were dominated by abscisic acid (ABA). Seedlings treated with increasing concentrations of ABA exhibited a differential alleviating effect on flower bud abortion, with a maximal response at 80 μM. Transcriptome analysis further confirmed the changes of ABA content and the occurrence of PCD, and indicated the importance of PCD-related SNF1-related protein kinase 1 (NnSnRK1). The NnSnRK1-silenced lotus seedlings showed stronger flowering ability, with their flower:leaf ratio increased by 40%. When seedlings were treated with ABA, the expression level and protein kinase activity of NnSnRK1 significantly decreased. The phenotype of NnSnRK1-silenced seedlings could also be enhanced by ABA treatment and reversed by tungstate treatment. These results suggested that the decline of ABA content in lotus flower buds released its repression of NnSnRK1, which then initiated flower bud abortion. Full article
(This article belongs to the Section Molecular Plant Sciences)
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Open AccessArticle
To What Extent Can a Sediment Yield Model Be Trusted? A Case Study from the Passaúna Catchment, Brazil
Water 2021, 13(8), 1045; https://doi.org/10.3390/w13081045 (registering DOI) - 10 Apr 2021
Abstract
Soil degradation and reservoir siltation are two of the major actual environmental, scientific, and engineering challenges. With the actual trend of world population increase, further pressure is expected on both water and soil systems around the world. Soil degradation and reservoir siltation are, [...] Read more.
Soil degradation and reservoir siltation are two of the major actual environmental, scientific, and engineering challenges. With the actual trend of world population increase, further pressure is expected on both water and soil systems around the world. Soil degradation and reservoir siltation are, however, strongly interlinked with the erosion processes that take place in the hydrological catchments, as both are consequences of these processes. Due to the spatial scale and duration of erosion events, the installation and operation of monitoring systems are rather cost- and time-consuming. Modeling is a feasible alternative for assessing the soil loss adequately. In this study, the possibility of adopting reservoir sediment stock as a validation measure for a monthly time-step sediment input model was investigated. For the assessment of sediment stock in the reservoir, the commercial free-fall penetrometer GraviProbe (GP) was used, while the calculation of sediment yield was calculated by combining a revised universal soil loss equation (RUSLE)-based model with a sediment delivery ratio model based on the connectivity approach. For the RUSLE factors, a combination of remote sensing, literature review, and conventional sampling was used. For calculation of the C Factor, satellite imagery from the Sentinel-2 platform was used. The C Factor was derived from an empirical approach by combining the normalized difference vegetation index (NDVI), the degree of soil sealing, and land-use/land-cover data. The key research objective of this study was to examine to what extent a reservoir can be used to validate a long-term erosion model, and to find out the limiting factors in this regard. Another focus was to assess the potential improvements in erosion modeling from the use of Sentinel-2 data. The use of such data showed good potential to improve the overall spatial and temporal performance of the model and also dictated further opportunities for using such types of model as reliable decision support systems for sustainable catchment management and reservoir protection measures. Full article
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