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Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world.
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most exciting work published in the various research areas of the journal.
This paper provides an overview of fractal antennas and metasurfaces, exploring their design principles, performance, and applications. Fractal antennas, incorporating self-similar geometric shapes, offer several advantages, such as their multiband operation, compact size, and improved performance. Metasurfaces, on the other hand, are two-dimensional
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This paper provides an overview of fractal antennas and metasurfaces, exploring their design principles, performance, and applications. Fractal antennas, incorporating self-similar geometric shapes, offer several advantages, such as their multiband operation, compact size, and improved performance. Metasurfaces, on the other hand, are two-dimensional structures composed of subwavelength unit cells and are designed to achieve advantageous and unusual electromagnetic properties by enabling precise control over electromagnetic waves. This paper discusses the fundamental concepts of fractal antennas and metasurfaces, compares their characteristics, and presents the latest advances in research. Additionally, it highlights applications in wireless communications, energy harvesting, sensing, and beyond.
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Nonheading Chinese cabbage is an important leafy vegetable, and quantitative identification and automated analysis of nonheading Chinese cabbage leaves are crucial for cultivating new varieties with higher quality, yield, and resistance. Traditional leaf phenotypic analysis relies mainly on phenotypic observation and the practical
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Nonheading Chinese cabbage is an important leafy vegetable, and quantitative identification and automated analysis of nonheading Chinese cabbage leaves are crucial for cultivating new varieties with higher quality, yield, and resistance. Traditional leaf phenotypic analysis relies mainly on phenotypic observation and the practical experience of breeders, leading to issues such as time consumption, labor intensity, and low precision, which result in low breeding efficiency. Considering these issues, a method for the extraction and analysis of phenotypes of nonheading Chinese cabbage leaves is proposed, targeting four qualitative traits and ten quantitative traits from 1500 samples, by integrating deep learning and OpenCV image processing technology. First, a leaf classification model is trained using YOLOv8 to infer the qualitative traits of the leaves, followed by the extraction and calculation of the quantitative traits of the leaves using OpenCV image processing technology. The results indicate that the model achieved an average accuracy of 95.25%, an average precision of 96.09%, an average recall rate of 96.31%, and an average F1 score of 0.9620 for the four qualitative traits. From the ten quantitative traits, the OpenCV-calculated values for the whole leaf length, leaf width, and total leaf area were compared with manually measured values, showing RMSEs of 0.19 cm, 0.1762 cm, and 0.2161 cm2, respectively. Bland–Altman analysis indicated that the error values were all within the 95% confidence intervals, and the average detection time per image was 269 ms. This method achieved good results in the extraction of phenotypic traits from nonheading Chinese cabbage leaves, significantly reducing the personpower and time costs associated with genetic resource analysis. This approach provides a new technique for the analysis of nonheading Chinese cabbage genetic resources that is high-throughput, precise, and automated.
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Basudev Chowdhury, Swati Garg, Wei Ni, Martin Sattler, Dana Sanchez, Chengcheng Meng, Taisei Akatsu, Richard Stone, William Forrester, Edmund Harrington, Sara J. Buhrlage, James D. Griffin and Ellen Weisberg
Cancers2024, 16(7), 1319; https://doi.org/10.3390/cancers16071319 (registering DOI) - 28 Mar 2024
Progress in the treatment of multiple myeloma (MM) has resulted in improvement in the survival rate for younger patients but not for patients >65. Thus, there is a need for more efficacious therapies. We and others have shown that bromodomain-containing protein 9 (BRD9),
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Progress in the treatment of multiple myeloma (MM) has resulted in improvement in the survival rate for younger patients but not for patients >65. Thus, there is a need for more efficacious therapies. We and others have shown that bromodomain-containing protein 9 (BRD9), a member of the non-canonical SWI/SNF chromatin remodeling complex, plays a role in MM cell survival, and targeting BRD9 selectively blocks MM cell proliferation and synergizes with IMiDs. We found that synergy in vitro is associated with the downregulation of MYC and Ikaros proteins, including IKZF3, and overexpression of IKZF3 or MYC could partially reverse synergy. RNA-seq analysis revealed synergy to be associated with the suppression of pathways associated with MYC and E2F target genes and pathways, including cell cycle, cell division, and DNA replication. Stimulated pathways included cell adhesion and immune and inflammatory response. Importantly, combining IMiD treatment and BRD9 targeting, which leads to the downregulation of MYC protein and upregulation of CRBN protein, was able to override IMiD resistance of cells exposed to iberdomide in long-term culture. Taken together, our results support the notion that combination therapy based on agents targeting BRD9 and IKZF3, two established dependencies in MM, represents a promising novel therapeutic strategy for MM and IMiD-resistant disease.
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Yakun Guo, Conghao Song, Fan Gao, Yixin Zhi, Xianbo Zheng, Xiaobei Wang, Haipeng Zhang, Nan Hou, Jun Cheng, Wei Wang, Langlang Zhang, Xia Ye, Jidong Li, Bin Tan, Xiaodong Lian and Jiancan Feng
Horticulturae2024, 10(4), 332; https://doi.org/10.3390/horticulturae10040332 (registering DOI) - 28 Mar 2024
Expansins (EXPs) loosen plant cell walls and are involved in diverse developmental processes through modifying cell-walls; however, little is known about the role of PpEXPs in peach fruit. In this study, 26 PpEXP genes were identified in the peach genome and grouped into
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Expansins (EXPs) loosen plant cell walls and are involved in diverse developmental processes through modifying cell-walls; however, little is known about the role of PpEXPs in peach fruit. In this study, 26 PpEXP genes were identified in the peach genome and grouped into four subfamilies, with 20 PpEXPAs, three PpEXPBs, one PpEXPLA and two PpEXPLBs. The 26 PpEXPs were mapped on eight chromosomes. The primary mode of gene duplication of the PpEXPs was dispersed gene duplication (DSD, 50%). Notably, cis-elements involved in light responsiveness and MeJA-responsiveness were detected in the promoter regions of all PpEXPs, while ethylene responsive elements were observed in 12 PpEXPs. Transcript profiling of PpEXPs in the peach fruit varieties of MF (melting), NMF (non-melting) and SH (stony hard) at different stages showed that PpEXPs displayed distinct expression patterns. Among the 26 PpEXPs, 15 PpEXPs were expressed in the fruit. Combining the expressing patterns of PpEXPs in fruits with different flesh textures, PpEXPA7, PpEXPA13 and PpEXPA15 were selected as candidate genes, as they were highly consistent with the patterns of previous reported key genes (PpPGM, PpPGF and PpYUC11) in regard to peach fruit texture. The genes with different expression patterns between MF and NMF were divided into 16 modules, of which one module, with pink and midnightblue, negatively correlated with the phenotype of fruit firmness and was identified as PpEXPA1 and PpEXPA7, while the other module was identified as PpERF in the pink module, which might potentially effect fruit texture development by regulating PpEXPs. These results provide a foundation for the functional characterization of PpEXPs in peach.
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This research work arises from the need to design specific techniques for the characterisation of cultural sites. Assuming the increasing complexity of the protection typologies, the expansion of working scales gives thanks to technology and the pursuit of social sustainability objectives. Thus, its
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This research work arises from the need to design specific techniques for the characterisation of cultural sites. Assuming the increasing complexity of the protection typologies, the expansion of working scales gives thanks to technology and the pursuit of social sustainability objectives. Thus, its main objective is to search for innovative tools that other disciplines can contribute to the work of architects specialising in heritage studies. To this end, the research explores the main methodologies, maps, guides, and registers of landscape and historic landscape characterisation developed in Europe, particularly in Spain, over the last 40 years. Considering this intense and profound evolution of landscape analysis, useful strategies for the assessment of cultural sites from their conception in the 21st century arise. Nevertheless, landscape characterisation methods have been mainly developed and applied by geographers and are absent in many urban and territorial heritage studies. In response, this article proposes a new methodological approach focusing on contextual values to be used in the assessment of architectural heritage at the territorial scale.
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Alejandro Morales-Martín, Francisco-Javier Mesas-Carrascosa, Pedro Antonio Gutiérrez, Fernando-Juan Pérez-Porras, Víctor Manuel Vargas and César Hervás-Martínez
Sensors2024, 24(7), 2168; https://doi.org/10.3390/s24072168 (registering DOI) - 28 Mar 2024
Recent advances in Deep Learning and aerial Light Detection And Ranging (LiDAR) have offered the possibility of refining the classification and segmentation of 3D point clouds to contribute to the monitoring of complex environments. In this context, the present study focuses on developing
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Recent advances in Deep Learning and aerial Light Detection And Ranging (LiDAR) have offered the possibility of refining the classification and segmentation of 3D point clouds to contribute to the monitoring of complex environments. In this context, the present study focuses on developing an ordinal classification model in forest areas where LiDAR point clouds can be classified into four distinct ordinal classes: ground, low vegetation, medium vegetation, and high vegetation. To do so, an effective soft labeling technique based on a novel proposed generalized exponential function (CE-GE) is applied to the PointNet network architecture. Statistical analyses based on Kolmogorov–Smirnov and Student’s t-test reveal that the CE-GE method achieves the best results for all the evaluation metrics compared to other methodologies. Regarding the confusion matrices of the best alternative conceived and the standard categorical cross-entropy method, the smoothed ordinal classification obtains a more consistent classification compared to the nominal approach. Thus, the proposed methodology significantly improves the point-by-point classification of PointNet, reducing the errors in distinguishing between the middle classes (low vegetation and medium vegetation).
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Zhengming Wang, Seongun Yang, Stephanie B. Lawson, V. Vinay K. Doddapaneni, Marc Albert, Benjamin Sutton, Chih-Hung Chang, Somayeh Pasebani and Donghua Xu
Materials2024, 17(7), 1543; https://doi.org/10.3390/ma17071543 (registering DOI) - 28 Mar 2024
Oxide-dispersion-strengthened (ODS) steels have long been viewed as a prime solution for harsh environments. However, conventional manufacturing of ODS steels limits the final product geometry, is difficult to scale up to large components, and is expensive due to multiple highly involved, solid-state processing
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Oxide-dispersion-strengthened (ODS) steels have long been viewed as a prime solution for harsh environments. However, conventional manufacturing of ODS steels limits the final product geometry, is difficult to scale up to large components, and is expensive due to multiple highly involved, solid-state processing steps required. Additive manufacturing (AM) can directly incorporate dispersion elements (e.g., Y, Ti and O) during component fabrication, thus bypassing the need for an ODS steel supply chain, the scale-up challenges of powder processing routes, the buoyancy challenges associated with casting ODS steels, and the joining issues for net-shape component fabrication. In the AM process, the diffusion of the dispersion elements in the molten steel plays a key role in the precipitation of the oxide particles, thereby influencing the microstructure, thermal stability and high-temperature mechanical properties of the resulting ODS steels. In this work, the atomic diffusivities of Y, Ti, and O in molten 316L stainless steel (SS) as functions of temperature are determined by ab initio molecular dynamics simulations. The latest Vienna Ab initio Simulation Package (VASP) package that incorporates an on-the-fly machine learning force field for accelerated computation is used. At a constant temperature, the time-dependent coordinates of the target atoms in the molten 316L SS were analyzed in the form of mean square displacement in order to obtain diffusivity. The values of the diffusivity at multiple temperatures are then fitted to the Arrhenius form to determine the activation energy and the pre-exponential factor. Given the challenges in experimental measurement of atomic diffusivity at such high temperatures and correspondingly the lack of experimental data, this study provides important physical parameters for future modeling of the oxide precipitation kinetics during AM process.
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In this study, the fabrication of microfluidic chips through the bonding of poly (methyl methacrylate) (PMMA) boards featuring designed patterns to create a three-dimensional sandwich structure with embedded microchannels was explored. A key focus was optimization of the interface quality of bonded PMMA
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In this study, the fabrication of microfluidic chips through the bonding of poly (methyl methacrylate) (PMMA) boards featuring designed patterns to create a three-dimensional sandwich structure with embedded microchannels was explored. A key focus was optimization of the interface quality of bonded PMMA pairs by adjusting the solvent, such as such as acetone, alcohol, and their mixture. Annealing was conducted below 50 °C to leverage the advantages of low-temperature bonding. Because of the differences in the chemical reactivity of PMMA toward acetone, alcohol, and their combinations, the resulting defect densities at the bonding interfaces differed significantly under low-temperature annealing conditions. To achieve the optimal sealing integrity, bonding pressures of 30 N, 40 N, and 50 N were evaluated. The interface was analyzed through microstructural examination via optical microscopy and stress measurements were determined using digital photoelasticity, while the bonding strength was assessed through tensile testing.
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The effect of hydrogen content on the deformation and fracture behavior of 27Cr−4Mo−2Ni super ferritic stainless steel (SFSS) was investigated in this study. It was shown that the plasticity and yield strength of SFSS were very susceptible to hydrogen content. The introduction of
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The effect of hydrogen content on the deformation and fracture behavior of 27Cr−4Mo−2Ni super ferritic stainless steel (SFSS) was investigated in this study. It was shown that the plasticity and yield strength of SFSS were very susceptible to hydrogen content. The introduction of hydrogen led to a significant decrease in elongation and a concurrent increase in yield strength. Nevertheless, a critical threshold was identified in the elongation reduction, after which the elongation remained approximately constant even with more hydrogen introduced, while the yield strength exhibited a monotonic increase with increasing hydrogen content within the experimental range, attributed to the pinning effect of the hydrogen Cottrell atmosphere on dislocations. Furthermore, the hydrogen-charged SFSS shows an apparent drop in flow stress after upper yielding and a reduced work hardening rate during the subsequent plastic deformation. The more hydrogen is charged, the more the flow stress drops, and the lower the work hardening rate becomes.
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Helaina E. Huneault, Chih-Yu Chen, Catherine C. Cohen, Xueyun Liu, Zachery R. Jarrell, Zhulin He, Karla E. DeSantos, Jean A. Welsh, Kristal M. Maner-Smith, Eric A. Ortlund, Jeffrey B. Schwimmer and Miriam B. Vos
Metabolites2024, 14(4), 191; https://doi.org/10.3390/metabo14040191 (registering DOI) - 28 Mar 2024
Little is known about lipid changes that occur in the setting of metabolic-dysfunction-associated steatotic liver disease (MASLD) regression. We previously reported improvements in hepatic steatosis, de novo lipogenesis (DNL), and metabolomic profiles associated with oxidative stress, inflammation, and selected lipid metabolism in 40
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Little is known about lipid changes that occur in the setting of metabolic-dysfunction-associated steatotic liver disease (MASLD) regression. We previously reported improvements in hepatic steatosis, de novo lipogenesis (DNL), and metabolomic profiles associated with oxidative stress, inflammation, and selected lipid metabolism in 40 adolescent boys (11–16 y) with hepatic steatosis ≥5% (98% meeting the definition of MASLD). Participants were randomized to a low-free-sugar diet (LFSD) (n = 20) or usual diet (n = 20) for 8 weeks. Here, we employed untargeted/targeted lipidomics to examine lipid adaptations associated with the LFSD and improvement of hepatic steatosis. Our LC-MS/MS analysis revealed decreased triglycerides (TGs), diacylglycerols (DGs), cholesteryl esters (ChE), lysophosphatidylcholine (LPC), and phosphatidylcholine (PC) species with the diet intervention (p < 0.05). Network analysis demonstrated significantly lower levels of palmitate-enriched TG species post-intervention, mirroring the previously shown reduction in DNL in response to the LFSD. Targeted oxylipins analysis revealed a decrease in the abundance of 8-isoprostane and 14,15-DiHET and an increase in 8,9-DiHET (p < 0.05). Overall, we observed reductions in TGs, DGs, ChE, PC, and LPC species among participants in the LFSD group. These same lipids have been associated with MASLD progression; therefore, our findings may indicate normalization of key biological processes, including lipid metabolism, insulin resistance, and lipotoxicity. Additionally, our targeted oxylipins assay revealed novel changes in eicosanoids, suggesting improvements in oxidative stress. Future studies are needed to elucidate the mechanisms of these findings and prospects of these lipids as biomarkers of MASLD regression.
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In recent decades, batch hot-dip galvanized (HDG) steel has proven itself in practical applications due to the good corrosion resistance of its components. Despite the importance of the mechanical-load-bearing capacity of these coatings, the wear behavior has, so far, only been investigated very
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In recent decades, batch hot-dip galvanized (HDG) steel has proven itself in practical applications due to the good corrosion resistance of its components. Despite the importance of the mechanical-load-bearing capacity of these coatings, the wear behavior has, so far, only been investigated very sporadically and not systematically, so a quantification of the wear behavior and statements on the mechanisms are vague. Therefore, two body wear tests with bonded abrasive grain were carried out. Varying the friction rolls, load, and total number of cycles, the wear behavior was investigated. The mass loss and the layer thickness reduction were measured at different intervals. After the test, the microstructure in the cross-section and the hardness according to Vickers (0.01 HV) were evaluated. The results showed that the wear behavior of HDG coatings against abrasive loads can be characterized with the selected test conditions. Initially, the applied load removed the soft η-phase. As the total number of cycles increases, the η- and ζ-phases deform plastically, resulting in a lower mass reduction compared to that expected from the measured layer thickness. The characteristic structure of a batch HDG coating with hard intermetallic Zn-Fe phases and an outer pure zinc phase has demonstrated effective resistance to abrasion.
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Breast cancer (BCA) remains the leading cause of cancer-related mortality among women worldwide. This review delves into the therapeutic challenges of BCA, emphasizing the roles of interleukin-13 receptor α2 (IL-13Rα2) and erythropoietin-producing hepatocellular receptor A2 (EphA2) in tumor progression and resistance. Highlighting their
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Breast cancer (BCA) remains the leading cause of cancer-related mortality among women worldwide. This review delves into the therapeutic challenges of BCA, emphasizing the roles of interleukin-13 receptor α2 (IL-13Rα2) and erythropoietin-producing hepatocellular receptor A2 (EphA2) in tumor progression and resistance. Highlighting their overexpression in BCA, particularly in aggressive subtypes, such as Her-2-enriched and triple-negative breast cancer (TNBC), we discuss the potential of these receptors as targets for chimeric antigen receptor T-cell (CAR-T) therapies. We examine the structural and functional roles of IL-13Rα2 and EphA2, their pathological significance in BCA, and the promising therapeutic avenues their targeting presents. With an in-depth analysis of current immunotherapeutic strategies, including the limitations of existing treatments and the potential of dual antigen-targeting CAR T-cell therapies, this review aims to summarize potential future novel, more effective therapeutic interventions for BCA. Through a thorough examination of preclinical and clinical studies, it underlines the urgent need for targeted therapies in combating the high mortality rates associated with Her-2-enriched and TNBC subtypes and discusses the potential role of IL-13Rα2 and EphA2 as promising candidates for the development of CAR T-cell therapies.
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False codling moth (FCM) Thaumatotibia leucotreta Meyrick (Lepidoptera: Tortricidae) is currently the main pest of phytosanitary concern in international trade, causing rejection and decline of horticultural produce from Kenya exported to the European Union (EU). Overreliance on synthetic insecticides to control this pest
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False codling moth (FCM) Thaumatotibia leucotreta Meyrick (Lepidoptera: Tortricidae) is currently the main pest of phytosanitary concern in international trade, causing rejection and decline of horticultural produce from Kenya exported to the European Union (EU). Overreliance on synthetic insecticides to control this pest is ineffective and unsustainable in the long run, whereas continuous use of pesticides results in high levels of residues in the produce. To gather farmers’ knowledge, attitudes, and practices used by smallholder farmers to manage this pest, a field survey was carried out in 10 Capsicum sp. (Solanales: Solanaceae)-producing counties in Kenya. Data were collected using semi-structured questionnaires administered through face-to-face interviews and focus group discussions involving 108 individual farmers, 20 key informants, and 10 focus group discussions. The majority of the respondents (83.33%) were aware of the FCM infesting Capsicum sp. About three quarters of the farmers (76.85%) reported yield losses and unmarketable quality of FCM-infested Capsicum sp. Most farmers interviewed (99.07%) used insecticides as a management tool. In contrast, only 39.81% of the farmers applied integrated pest management strategies including use of biological control agents and intercropping with repellent plants to control this pest. The results show that FCM is perceived as a significant threat to the horticultural industry of Kenya. Training needs for smallholder farmers and key informants to avoid overreliance on synthetic chemical pesticides and to maintain export goals to the EU where identified.
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Fucoidan (FC) is known for its antioxidant properties, but it has unclear effects and mechanisms on weaned piglets. Two experiments were conducted to determine the optimal FC dosage in piglet diets and its protective effect against lipopolysaccharide (LPS)-induced oxidative stress. In experiment one,
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Fucoidan (FC) is known for its antioxidant properties, but it has unclear effects and mechanisms on weaned piglets. Two experiments were conducted to determine the optimal FC dosage in piglet diets and its protective effect against lipopolysaccharide (LPS)-induced oxidative stress. In experiment one, 24 low weight weaned piglets were randomly assigned to four dietary treatments: a basal diet (FC 0), or a diet supplemented with 150 (FC 150), 300 (FC 300), or 600 mg/kg FC (FC 600). In experiment two, 72 low-weaning weight piglets were randomly allocated into four treatments: a basal diet (CON), or 300 mg/kg of fucoidan added to a basal diet challenged with LPS (100 µg LPS/kg body weight) or not. The results showed that FC treatments increased the G:F ratio, and dietary FC 300 reduced the diarrhea incidence and increased the plasma IGF-1 concentrations. In addition, FC 300 and FC 600 supplementation increased the plasma SOD activity and reduced the plasma MDA concentration. LPS challenge triggered a strong systemic redox imbalance and mitochondrial dysfunction. However, dietary FC (300 mg/kg) supplementation increased the activity of antioxidant enzymes, including SOD, decreased the MDA concentration in the plasma and liver, down-regulated Keap1 gene expression, and up-regulated Nrf2, CAT, MFN2, SDHA, and UQCRB gene expression in the liver. These results indicated that dietary fucoidan (300 mg/kg) supplementation improved the growth performance and antioxidant capacity of low-weaning weight piglets, which might be attributed to the modulation of the Keap1/Nrf2 signaling pathway and the mitochondrial function in the liver.
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Surface modification of membranes is essential for improving flux and resistance to contamination for membranes. This is of great significance for membrane distillation, which relies on the vapor pressure difference across the membrane as the driving force. In recent years, biomimetic mussel-inspired substances
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Surface modification of membranes is essential for improving flux and resistance to contamination for membranes. This is of great significance for membrane distillation, which relies on the vapor pressure difference across the membrane as the driving force. In recent years, biomimetic mussel-inspired substances have become the research hotspots. Among them, dopamine serves as surface modifiers that would achieve highly desirable and effective membrane applications owing to their unique physicochemical properties, such as universal adhesion, enhanced hydrophilicity, tunable reducibility, and excellent thermal conductivity. The incorporation of a hydrophilic layer, along with the utilization of photothermal properties and post-functionalization capabilities in modified membranes, effectively addresses challenges such as low flux, contamination susceptibility, and temperature polarization during membrane distillation. However, to the best of our knowledge, there is still a lack of comprehensive and in-depth discussions. Therefore, this paper systematically compiles the modification method of dopamine on the membrane surface and summarizes its application and mechanism in membrane distillation for the first time. It is believed that this paper would provide a reference for dopamine-assisted membrane separation during production, and further promote its practical application.
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In order to study the underground coal-gasification process, Aspen Plus software was used to simulate the lignite underground gasification process, and a variety of unit operation modules were selected and combined with the kinetic equations of coal underground gasification. The model can reflect
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In order to study the underground coal-gasification process, Aspen Plus software was used to simulate the lignite underground gasification process, and a variety of unit operation modules were selected and combined with the kinetic equations of coal underground gasification. The model can reflect the complete gasification process of the coal underground gasifier well, and the simulation results are more in line with the experimental results of the lignite underground gasification model test. The changes in the temperature and pressure of oxygen, gasification water, spray water, and syngas in pipelines were studied, and the effects of pipe diameters on pipeline conveying performance were investigated as well. The effects of the oxygen/water ratio, processing capacity, and spray-water volume on the components of syngas and components in different reaction zones were studied. In addition, the change tendency of gasification products under different conditions was researched. The results indicate that: (1) The depth of injection and the formation pressure at that depth need to be taken into account to determine a reasonable injection pressure. (2) The liquid-water injection process should select a lower injection pressure. (3) Increasing the oxygen/water ratio favors H2 production and decreasing the oxygen/water ratio favors CH4 production. (4) The content of CO2 is the highest in the oxidation zone, the lowest in the reduction zone, and then increases a little in the methanation reaction zone for the transform reaction. The content of CO is the lowest in the oxidation zone and the highest in the reduction zone. In the methanation reaction zone, CO partially converts into H2 and CO2, and the content of CO is reduced. (5) The injection of spray water does not affect the components of the gas but will increase the water vapor content in the gas; thus, this changes the molar fraction of the wet gas.
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DC microgrids have gained significant attention in recent years due to their potential to enhance energy efficiency, integrate renewable energy sources, and improve the resilience of power distribution systems. However, the reliable operation of DC microgrids relies on the early detection and location
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DC microgrids have gained significant attention in recent years due to their potential to enhance energy efficiency, integrate renewable energy sources, and improve the resilience of power distribution systems. However, the reliable operation of DC microgrids relies on the early detection and location of faults to ensure an uninterrupted power supply. This paper aims to develop fast and reliable fault detection and location mechanisms for DC microgrids, thereby enhancing operational efficiency, minimizing environmental impact, and contributing to resource conservation and sustainability goals. The fault detection method is based on compressed sensing (CS) and Regression Tree (RT) techniques. Besides, an accurate fault location method using the feature matrix and long short-term memory (LSTM) model combination has been provided. To implement the proposed fault detection and location method, a DC microgrid equipped with photovoltaic (PV) panels, the vehicle-to-grid (V2G) charging station, and a hybrid energy storage system (ESS) are used. The simulation results represent the proposed methods’ superiority over the recent studies. The fault occurrence in the studied DC microgrid is detected in 1 ms, and the proposed fault location method locates the fault with an accuracy of more than 93%. The presented techniques enhance DC microgrid reliability while conserving renewable resources, vital to promoting a greener and more sustainable power grid.
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Ariane Cavalcante dos Santos Sousa, Bruno Leonardo Nascimento Correa Fernandes, Jeronimo Paulo Assis da Silva, Paulo Roberto Stevanato Filho, Luiza Bitencourt de Carvalho Terci Coimbra, Adriano de Oliveira Beserra, Ana Luiza Alvarenga, Giovanna Maida, Camila Tokumoto Guimaraes, Ingrid Martinez Nakamuta, Fabio Albuquerque Marchi, Camila Alves, Martina Lichtenfels, Caroline Brunetto de Farias, Bruna Elisa Catin Kupper, Felipe D’Almeida Costa, Celso Abdon Lopes de Mello, Dirce Maria Carraro, Giovana Tardin Torrezan, Ademar Lopes and Tiago Goss dos Santosadd
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Genes2024, 15(4), 424; https://doi.org/10.3390/genes15040424 (registering DOI) - 28 Mar 2024
Rare sarcomas present significant treatment challenges compared to more prevalent soft tissue sarcomas due to limited treatment options and a poor understanding of their biology. This study investigates a unique case of penile sarcoma, providing a comprehensive morphological and molecular analysis. Through the
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Rare sarcomas present significant treatment challenges compared to more prevalent soft tissue sarcomas due to limited treatment options and a poor understanding of their biology. This study investigates a unique case of penile sarcoma, providing a comprehensive morphological and molecular analysis. Through the creation of experimental patient-derived models—including patient-derived xenograft (PDX), 3D, and monolayer primary cultures—we successfully replicated crucial molecular traits observed in the patient’s tumor, such as smooth muscle actin and CD99 expression, along with specific mutations in genes like TSC2 and FGFR4. These models are helpful in assessing the potential for an in-depth exploration of this tumor’s biology. This comprehensive approach holds promise in identifying potential therapeutic avenues for managing this exceedingly rare soft tissue sarcoma.
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COVID-19 remains a communicable disease with the capacity to cause substantial damage to health and health systems. Enhanced health screening at points of entry (POEs) is a public health measure implemented to support early detection, prevention and response to communicable diseases, such as
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COVID-19 remains a communicable disease with the capacity to cause substantial damage to health and health systems. Enhanced health screening at points of entry (POEs) is a public health measure implemented to support early detection, prevention and response to communicable diseases, such as COVID-19. The purpose of this study was to review the available evidence on the effectiveness of POE health screening in the detection and containment of the COVID-19 pandemic. This study was registered under PROSPERO and followed PRISMA guidelines in which the literature between 2019 and 2022 was retrieved from Scopus, PubMed, Web of Science, Global Health, CINAHL, Embase, Google Scholar and international organizations. A total of 33,744 articles were screened for eligibility, from which 43 met the inclusion criteria. The modeling studies predicted POE screening able to detect COVID-19 in a range of 8.8% to 99.6%, while observational studies indicated a detection rate of 2% to 77.9%, including variants of concern depending on the screening method employed. The literature also indicated these measures can delay onset of the epidemic by 7 to 32 days. Based on our review findings, if POE screening measures are implemented in combination with other public health interventions such as rapid tests, they may help detect and reduce the spread of COVID-19.
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The classification of nasolabial folds into three types, each with distinct causative factors and mechanisms, is explored. Age-related changes in facial skin and connective tissues are examined in detail, revealing variations across different facial regions due to variances in tissue firmness and thickness.
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The classification of nasolabial folds into three types, each with distinct causative factors and mechanisms, is explored. Age-related changes in facial skin and connective tissues are examined in detail, revealing variations across different facial regions due to variances in tissue firmness and thickness. The innovative ‘Reverse Technique,’ involving cog threads to enhance tissue traction and effectiveness in thread-lifting procedures, is introduced. Detailed technical guidelines, anatomical considerations, and safety measures are provided, emphasizing the importance of identifying optimal vectors and fixing points to achieve maximum lifting effects while minimizing potential risks, particularly those associated with vascular structures. Additionally, the ‘Cross Technique using volumizing thread’ is discussed, designed to smooth tissue boundaries and rejuvenate sagging areas. Facial anatomy, including the positioning of arteries and ligaments, is underscored as essential for ensuring the safety and efficacy of procedures. In conclusion, this review stands as a comprehensive guide for practitioners, offering insights into innovative thread-lifting methods and their applications in addressing nasolabial folds. The primary focus is on achieving optimal aesthetic results while prioritizing patient safety.
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Unsupervised Domain Adaptative Object Detection (UDAOD) aims to alleviate the gap between the source domain and the target domain. Previous methods sought to plainly align global and local features across domains but adapted numerous pooled features and overlooked contextual information, which caused incorrect
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Unsupervised Domain Adaptative Object Detection (UDAOD) aims to alleviate the gap between the source domain and the target domain. Previous methods sought to plainly align global and local features across domains but adapted numerous pooled features and overlooked contextual information, which caused incorrect perceptions of foreground information. To tackle these problems, we propose Diverse Feature-level Guidance Adjustments (DFGAs) for two-stage object detection frameworks, including Pixel-wise Multi-scale Alignment (PMA) and Adaptative Threshold Confidence Adjustment (ATCA). Specifically, PMA adapts features within diverse hierarchical levels to capture sufficient contextual information. Through a customized PMA loss, features from different stages of a network facilitate information interaction across domains. Training with this loss function contributes to the generation of more domain-agnostic features. To better recognize foreground and background samples, ATCA employs adaptative thresholds to divide the foreground and background samples. This strategy flexibly instructs the classifier to perceive the significance of box candidates. Comprehensive experiments are conducted on Cityscapes, Foggy Cityscapes, KITTI, and Sim10k datasets to further demonstrate the superior performance of our method compared to the baseline method.
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Electric, dielectric, and optical (band gap) properties of pure multiferroic as well as La- and Ni-doped (SFO) (at different sites) are investigated using a microscopic model and Green’s function technique. The concentration dependence of the polarization P is considered
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Electric, dielectric, and optical (band gap) properties of pure multiferroic as well as La- and Ni-doped (SFO) (at different sites) are investigated using a microscopic model and Green’s function technique. The concentration dependence of the polarization P is considered for substitution of rare earths ions on the Sr sites. For a small La ion doping concentration, x = 0.1, La-doped SFO is ferroelectric, whereas for a larger doping concentration, for example x = 0.5, it is antiferroelectric. The real part of the dielectric constant increases with an increasing magnetic field h. decreases with an increasing frequency and La dopants. Therefore, La-doped SFO is suitable for microwave application with a low dielectric constant. The magnetic properties of pure SFO NPs are also studied. Ni doping at the Fe site of SFO leads to enhanced ferroelectric polarization and dielectric constant. The band gap decreases or increases by substitution of Ni or In ions on the Fe site, respectively. The results reveal that the tuned band gap of Ni-doped SFO makes it a crucial candidate for optoelectronic and solid oxide fuel cell applications.
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Face recognition techniques have been widely employed in real-world biomimetics applications. However, traditional approaches have limitations in recognizing faces correctly with large age differences because of significant changes over age in the same person, leading to unsatisfactory recognition performance. To address this, previous
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Face recognition techniques have been widely employed in real-world biomimetics applications. However, traditional approaches have limitations in recognizing faces correctly with large age differences because of significant changes over age in the same person, leading to unsatisfactory recognition performance. To address this, previous studies propose to decompose and identify age and identity features independently in facial images across diverse age groups when optimizing the discriminative model so as to improve the age-invariant face recognition accuracy. Nevertheless, the interrelationships between these features make it difficult for the decomposition to disentangle them properly, thus compromising the recognition accuracy due to the interactive impacts on both features. To this end, this paper proposes a novel deep framework that incorporates a novel Hybrid Spatial-Channel Attention Module to facilitate the cross-age face recognition task. Particularly, the proposed module enables better decomposition of the facial features in both spatial and channel dimensions with attention mechanisms simultaneously while mitigating the impact of age variation on the recognition performance. Beyond this, diverse pooling strategies are also combined when applying those spatial and channel attention mechanisms, which allows the module to generate discriminative face representations while preserving complete information within the original features, further yielding sounder recognition accuracy. The proposed model is extensively validated through experiments on public face datasets such as CACD-VS, AgeDB-30, and FGNET, where the results show significant performance improvements compared to competitive baselines.
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