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The glycocalyx is a proteoglycan–glycoprotein structure lining the luminal surface of the vascular endothelium and is susceptible to damage due to blast overpressure (BOP) exposure. The glycocalyx is essential in maintaining the structural and functional integrity of the vasculature and regulation of cerebral blood flow (CBF). Assessment of alterations in the density of the glycocalyx; its components (heparan sulphate proteoglycan (HSPG/syndecan-2), heparan sulphate (HS), and chondroitin sulphate (CS)); CBF; and the effect of hypercapnia on CBF was conducted at 2–3 h, 1, 3, 14, and 28 days after a high-intensity (18.9 PSI/131 kPa peak pressure, 10.95 ms duration, and 70.26 PSI·ms/484.42 kPa·ms impulse) BOP exposure in rats. A significant reduction in the density of the glycocalyx was observed 2–3 h, 1-, and 3 days after the blast exposure. The glycocalyx recovered by 28 days after exposure and was associated with an increase in HS (14 and 28 days) and in HSPG/syndecan-2 and CS (28 days) in the frontal cortex. In separate experiments, we observed significant decreases in CBF and a diminished response to hypercapnia at all time points with some recovery at 3 days. Given the role of the glycocalyx in regulating physiological function of the cerebral vasculature, damage to the glycocalyx after BOP exposure may result in the onset of pathogenesis and progression of cerebrovascular dysfunction leading to neuropathology. [ABSTRACT FROM AUTHOR]

Pressure sensing plays an important role in many industrial fields; conventional electronic pressure sensors struggle to survive in the harsh environment. Recently microelectromechanical systems (MEMS) fiber-optic Fabry–Perot (FP) pressure sensors have attracted great interest. Here we review the basic principles of MEMS fiber-optic FP pressure sensors and then discuss the sensors based on different materials and their industrial applications. We also introduce recent progress, such as two-photon polymerization-based 3D printing technology, and the state-of-the-art in this field, e.g., sapphire-based sensors that work up to 1200 °C. Finally, we discuss the limitations and opportunities for future development. [ABSTRACT FROM AUTHOR]

In this study, the refinement of two microstructures was controlled in medium carbon 25Cr2Ni3MoV steel via multi-step tempering and partition (MTP) to achieve high cryogenic strength–ductility combinations. Microstructure evolution, the distribution of stress concentration, and microcrack formation and propagation during cryogenic Charpy impact testing were investigated. Compared with their performance in the quenching and tempering states (QT), the MTP steels showed a significant improvement in yield strength (1300 MPa), total elongation (25%), and impact toughness (>25 J) at liquid nitrogen temperature (LNT). The strengthening contributions mainly originated from the high dislocation density and refinement cementite (size: 70 nm) in the martensite lath (width: 1.5 μm) introduced by refined reversed austenite and its latter decomposition. The instrumented Charpy impact results indicated that cracks nucleated in the primary austenite grain (PAG) boundary for two steels due to the strain concentration band preferring to appear near PAGs, while cracks in the QT and MTP samples propagated along the PAGs and high-angle grain boundary (HAGB), respectively. The crystallized plasticity finite element simulation revealed that the PAG boundary with cementite precipitates of large size (>200 nm) was less able to dissipate crack propagation energy than the HAGBs by continuously forming a high strain concentration area, thus leading to the low-impact toughness of the QT steel. [ABSTRACT FROM AUTHOR]

Osteoarthritis (OA) is a chronic, degenerative joint disease presenting a significant global health threat. While current therapeutic approaches primarily target symptom relief, their efficacy in repairing joint damage remains limited. Recent research has highlighted mesenchymal stem cells (MSCs) as potential contributors to cartilage repair, anti-inflammatory modulation, and immune regulation in OA patients. Notably, MSCs from different sources and their derivatives exhibit variations in their effectiveness in treating OA. Moreover, pretreatment and gene editing techniques of MSCs can enhance their therapeutic outcomes in OA. Additionally, the combination of novel biomaterials with MSCs has shown promise in facilitating the repair of damaged cartilage. This review summarizes recent studies on the role of MSCs in the treatment of OA, delving into their advantages and exploring potential directions for development, with the aim of providing fresh insights for future research in this critical field. [ABSTRACT FROM AUTHOR]

This paper mainly investigates the problem of direction of arrival (DOA) estimation for a monostatic MIMO radar. Specifically, the proposed array, which is called a nested–nested sparse array (NNSA), is structurally composed of two nested subarrays, a NA with N 1 + N 2 elements and a sparse NA, respectively, with N 3 + N 4 elements. The design process of NNSA is optimized into two steps and presented in detail. Setting NNSA as transmitter/receiver arrays, we derive the closed-form expression of consecutive DOFs and calculate the mutual coupling coefficient. Eventually, extensive simulations are carried out and the results verify the superiority of the proposed array over the previous arrays in terms of consecutive DOFs, array aperture and mutual coupling effect. [ABSTRACT FROM AUTHOR]

Metschnikowia bicuspidata causes a "milky disease" in Chinese mitten crab, Eriocheir sinensis, which inflicts significant damage on the breeding industry, but there are no effective drugs for this disease. Precise detection technologies and clarification of transmission routes are now essential to prevent its occurrence. A real-time fluorescent quantitative PCR (qPCR) detection method targeting the mitochondrial cytochrome c oxidase subunit VIA (COX6A) of M. bicuspidata was developed and its sensitivity, specificity, repeatability, and application effectiveness evaluated. There was a robust linear relationship between the qPCR threshold cycle value (Ct) and copy number of the standard with a wide dynamic range. The standard curve had a correlation coefficient (R2) of 0.996, amplification efficiency of 103.092%, and a lower limit of detection sensitivity of 7.6 × 101 copies/µL. The COX6A-qPCR method exhibited high specificity for the detection of M. bicuspidata, with no cross-reactivity. The intra- and inter-group variation coefficients were <1% and 2%, respectively. The qPCR exhibited superior sensitivity compared to existing detection methods, with a positivity rate of 76.67%. The M. bicuspidata content ranged from 1.0 × 101–2.7 × 106 copies/µL. The COX6A-qPCR detection technology exhibited high sensitivity, strong specificity, and excellent repeatability, enabling the accurate quantification of M. bicuspidata. [ABSTRACT FROM AUTHOR]

In aviation fire extinguishing systems, the extinguishing agent is stored in a bottle, which is pressurized by nitrogen. When fire occurs, the agent is discharged via pipe and nozzle to the target compartment. The geometry of the pipe has a significant impact on the discharge process, and merits study. In this study of the discharge process of halon1301 using pipes of different diameters, the pressure distribution was significantly influenced by varying pipe diameter. Contributions to pressure drops through the valve/pipe/nozzle were approximately 2%, 8%, and 90%, respectively, when the pipe diameter was larger than the nozzle diameter. The contribution through the pipe increased, and the contribution through the nozzle decreased, as the pipe diameter became smaller. When the pipe diameter was decreased to the nozzle diameter, pressure drops through the valve/pipe/nozzle were 10%, 45%, and 45%, respectively; there was an increased pressure drop through the pipe. Distinctions in pressure distribution led to temperature differences; when there were more pressure drops through the nozzle, the temperature in the pipe was lower. [ABSTRACT FROM AUTHOR]

Gaseous fire suppressants are usually stored in a vessel via pressurization, and then discharged out through pipelines. The flow behaviors of the agents in pipes greatly affect its dispersion in space, as well as the fire extinguishing results. Here, an experimental study was carried out on the transportation characteristics of perfluoro(2-methyl-3-pentanone) (C6F12O) in a horizontal straight pipe with the temperature and pressure recorded synchronously. At a filling pressure of 1800 kPa and a filling density of 517 kg·m−3, the agent release was completed in 2.0 s with the pipeline pressure peak of 1145 kPa and the pipeline temperature nadir of −10.6 °C. In comparison to that of bromotrifluoromethane (CF3Br) under the same conditions, the temperature and pressure curves of C6F12O exhibited similar varying trajectories but a much smaller amplitude, which could be ascribed to their different thermophysical properties. When keeping the other conditions unchanged, raising the filling pressure C6F12O reduces the discharge duration and the pipeline temperatures. Increasing the filling density extends the discharge duration, but shows little influence on the pipeline temperatures. The results were expected to provide useful information for the model validation and engineering design of a C6F12O fire-suppressing system with a predictable performance. [ABSTRACT FROM AUTHOR]

The characteristics of active sites on the surface of albite were theoretically analyzed by density functional theory, and the activation of the C-H bond of methane using an albite catalyst and the reaction mechanism of preparing C2 hydrocarbons by nonoxidative coupling were studied. There are two frustrated Lewis pairs (FLPs) on the (001) and (010) surfaces of albite; they can dissociate H2 under mild conditions and show high activity for the activation of methane C-H bonds. CH4 molecules can undergo direct dissociative adsorption on the (010) surface, whereas a 50.07 kJ/mol activation barrier is needed on the (001) surface. The prepared albite catalyst has a double combination function of the (001) and (010) surfaces; these surfaces produce a spillover phenomenon in the process of CH4 activation reactions, where CH3 overflows from the (001) surface with CH3 adsorbed on the (010) surface to achieve nonoxidative high efficiently C-C coupling with an activation energy of 18.51 kJ/mol. At the same time, this spillover phenomenon inhibits deep dehydrogenation, which is conducive to the selectivity of the C2 hydrocarbons. The experimental results confirm that the selectivity of the C2 hydrocarbons is maintained above 99% in the temperature range of 873 K to 1173 K. [ABSTRACT FROM AUTHOR]

The incidence of high-risk Human Papillomavirus (HR-HPV)-driven head and neck squamous cell carcinoma (HNSCC) is on the rise globally. HR-HPV-driven HNSCC displays molecular and clinical characteristics distinct from HPV-uninvolved cases. Therapeutic strategies for HR-HPV-driven HNSCC are under investigation. HR-HPVs encode the oncogenes E6 and E7, which are essential in tumorigenesis. Meanwhile, involvement of E6 and E7 provides attractive targets for developing new therapeutic regimen. Here we will review some of the recent advancements observed in preclinical studies and clinical trials on HR-HPV-driven HNSCC, focusing on nanotechnology related methods. Materials science innovation leads to great improvement for cancer therapeutics including HNSCC. This article discusses HPV-E6 or -E7- based vaccines, based on plasmid, messenger RNA or peptide, at their current stage of development and testing as well as how nanoparticles can be designed to target and access cancer cells and activate certain immunology pathways besides serving as a delivery vehicle. Nanotechnology was also used for chemotherapy and photothermal treatment. Short interference RNA targeting E6/E7 showed some potential in animal models. Gene editing by CRISPR-CAS9 combined with other treatments has also been assessed. These advancements have the potential to improve the outcome in HR-HPV-driven HNSCC, however breakthroughs are still to be awaited with nanomedicine playing an important role. [ABSTRACT FROM AUTHOR]

Hyperspectral remote sensing images (HRSI) have the characteristics of foreign objects with the same spectrum. As it is difficult to label samples manually, the hyperspectral remote sensing images are understood to be typical "small sample" datasets. Deep neural networks can effectively extract the deep features from the HRSI, but the classification accuracy mainly depends on the training label samples. Therefore, the stacked convolutional autoencoder network and transfer learning strategy are employed in order to design a new stacked convolutional autoencoder network model transfer (SCAE-MT) for the purposes of classifying the HRSI in this paper. In the proposed classification method, the stacked convolutional au-to-encoding network is employed in order to effectively extract the deep features from the HRSI. Then, the transfer learning strategy is applied to design a stacked convolutional autoencoder network model transfer under the small and limited training samples. The SCAE-MT model is used to propose a new HRSI classification method in order to solve the small samples of the HRSI. In this study, in order to prove the effectiveness of the proposed classification method, two HRSI datasets were chosen. In order to verify the effectiveness of the methods, the overall classification accuracy (OA) of the convolutional self-coding network classification method (CAE), the stack convolutional self-coding network classification method (SCAE), and the SCAE-MT method under 5%, 10%, and 15% training sets are calculated. When compared with the CAE and SCAE models in 5%, 10%, and 15% training datasets, the overall accuracy (OA) of the SCAE-MT method was improved by 2.71%, 3.33%, and 3.07% (on average), respectively. The SCAE-MT method is, thus, clearly superior to the other methods and also shows a good classification performance. [ABSTRACT FROM AUTHOR]

(1) Background: analyses of gene networks can elucidate hematopoietic differentiation from single-cell gene expression data, but most algorithms generate only a single, static network. Because gene interactions change over time, it is biologically meaningful to examine time-varying structures and to capture dynamic, even transient states, and cell-cell relationships. (2) Methods: a transcriptomic atlas of hematopoietic stem and progenitor cells was used for network analysis. After pseudo-time ordering with Monocle 2, LOGGLE was used to infer time-varying networks and to explore changes of differentiation gene networks over time. A range of network analysis tools were used to examine properties and genes in the inferred networks. (3) Results: shared characteristics of attributes during the evolution of differentiation gene networks showed a "U" shape of network density over time for all three branches for human and mouse. Differentiation appeared as a continuous process, originating from stem cells, through a brief transition state marked by fewer gene interactions, before stabilizing in a progenitor state. Human and mouse shared hub genes in evolutionary networks. (4) Conclusions: the conservation of network dynamics in the hematopoietic systems of mouse and human was reflected by shared hub genes and network topological changes during differentiation. [ABSTRACT FROM AUTHOR]

The electro-Fenton (EF) process is regarded as an efficient and promising sewage disposal technique for sustainable water environment protection. However, current developments in EF are largely restricted by cathode electrocatalysts. Herein, a supramolecular self-assembly strategy is adopted for synthetization, based on melamine–cyanuric acid (MCA) supramolecular aggregates integrated with carbon fixation using 5-aminosalicylic acid and zinc acetylacetonate hydrate. The prepared carbon materials characterize an ordered lamellar microstructure, high specific surface area (595 m2 g−1), broad mesoporous distribution (4~33 nm) and high N doping (19.62%). Such features result from the intrinsic superiority of hydrogen-bonded MCA supramolecular aggregates via the specific molecular assembly process. Accordingly, noteworthy activity and selectivity of H2O2 production (~190.0 mg L−1 with 2 h) are achieved. Excellent mineralization is declared for optimized carbon material in several organic pollutants, namely, basic fuchsin, chloramphenicol, phenol and several mixed triphenylmethane-type dyestuffs, with total organic carbon removal of 87.5%, 74.8%, 55.7% and 54.2% within 8 h, respectively. This work offers a valuable insight into facilitating the application of supramolecular-derived carbon materials for extensive EF degradation. [ABSTRACT FROM AUTHOR]

The deep learning method is widely used in remote sensing object detection on the premise that the training data have complete features. However, when data with a fixed class are added continuously, the trained detector is less able to adapt to new instances, impelling it to carry out incremental learning (IL). IL has two tasks with knowledge-related symmetry: continuing to learn unknown knowledge and maintaining existing knowledge. Unknown knowledge is more likely to exist in these new instances, which have features dissimilar from those of the old instances and cannot be well adapted by the detector before IL. Discarding all the old instances leads to the catastrophic forgetting of existing knowledge, which can be alleviated by relearning old instances, while different subsets represent different existing knowledge ranges and have different memory-retention effects on IL. Due to the different IL values of the data, the existing methods without appropriate distinguishing treatment preclude the efficient absorption of useful knowledge. Therefore, a rank-aware instance-incremental learning (RAIIL) method is proposed in this article, which pays attention to the difference in learning values from the aspects of the data-learning order and training loss weight. Specifically, RAIIL first designs the rank-score according to inference results and the true labels to determine the learning order and then weights the training loss according to the rank-score to balance the learning contribution. Comparative and analytical experiments conducted on two public remote sensing datasets for object detection, DOTA and DIOR, verified the superiority and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

An open-cell metal foam has excellent characteristics such as low density, high porosity, high specific surface area, high thermal conductivity, and low mass due to its unique internal three-dimensional network structure. It has gradually become a new material for enhanced heat transfer in industrial equipment, new compact heat exchangers, microelectronic device cooling, etc. This research established a comprehensive three-dimensional structural model of open-cell metal foams utilizing Laguerre–Voronoi tessellations and employed computational fluid dynamics to investigate its flow dynamics and coupled heat transfer performance. By exploring the impact of foam microstructure on flow resistance and heat transfer characteristics, the study provided insights into the overall convective heat transfer performance across a range of foam configurations with varying pore densities and porosities. The findings revealed a direct correlation between convective heat transfer coefficient (h) and pressure drop (ΔP) with increasing Reynolds number (Re), accompanied by notable changes in fluid turbulence kinetic energy (e) and temperature (T), ultimately influencing heat transfer efficiency. Furthermore, the analysis demonstrated that alterations in porosity (ε) and pore density significantly affected unit pressure drop (ΔP/L) and convective heat transfer coefficient (h). This study identified an optimal configuration, highlighting a metal foam with a pore density of 20 PPI and a porosity of 95% as exhibiting superior overall convective heat transfer performance. [ABSTRACT FROM AUTHOR]

As an important irritant trace gas in the atmosphere, ammonia (NH3) significantly impacts human health and environment. Bottom-up emission inventories are widely used to estimate ammonia emissions and their geographical distributions over China. However, high uncertainties are still associated with emission inventories due to inaccurate emission factors used. The Differential Evolution (DE) algorithm is a population-based stochastic optimization algorithm used to solve complicated optimization problems. We quantify NH3 emissions and lifetime from Infrared Atmospheric Sounding Interferometer (IASI) NH3 observations together with MERRA-2 wind fields based on the DE algorithm. Two inland cities, Urumchi and Golmud in China, are chosen to study of the NH3 emissions based on the distributions of NH3 total columns and wind fields. The NH3 emissions rate estimated is about 5.84 × 10−11 and 4.19 × 10−11 kg·m−2s−1 in Urumchi and in the Golmud area from May to September from 2008 to 2023, respectively. The lifetime of NH3 estimated in the two areas is 4.31 and 9.19 h, respectively. We compare the NH3 emissions and lifetime estimated in this study with the values in other studies, and the results show the reliability of the method used. This work is one of few quantitative studies of NH3 emissions from cities using satellite observations in China. [ABSTRACT FROM AUTHOR]

Flotation reagents are significant for modifying the interfacial characteristics of mineral grains to achieve the effective separation of minerals. Since the 1960s, when quantum chemistry was first introduced into the study of flotation reagents, many achievements have been made, although some controversial topics remain. The application of quantum chemistry in the research of flotation reagents for the separation of various minerals in the past decade is herein comprehensively and systematically reviewed. The main directions and gaps of current research are pointed out, the theoretical basis for the design and development of novel flotation reagents is summarized, and more importantly, the potential for the targeting design and development of efficient, selective, and environmentally friendly flotation reagent molecules by means of quantum chemistry is explored. [ABSTRACT FROM AUTHOR]

(1) Background: The imaging energy range of a typical Compton camera is limited due to the fact that scattered gamma photons are seldom fully absorbed when the incident energies are above 3 MeV. Further improving the upper energy limit of gamma-ray imaging has important application significance in the active interrogation of special nuclear materials and chemical warfare agents, as well as range verification of proton therapy. (2) Methods: To realize gamma-ray imaging in a wide energy range of 0.3~7 MeV, a principle prototype, named a portable three-layer Compton camera, is developed using the scintillation detector that consists of an silicon photomultiplier array coupled with a Gd3Al2Ga3O12:Ce pixelated scintillator array. Implemented in a list-mode maximum likelihood expectation maximization algorithm, a far-field energy-domain imaging method based on the two interaction events is applied to estimate the initial energy and spatial distribution of gamma-ray sources. The simulation model of the detectors is established based on the Monte Carlo simulation toolkit Geant4. The reconstructed images of a 133Ba, a 137Cs and a 60Co point-like sources have been successfully obtained with our prototype in laboratory tests and compared with simulation studies. (3) Results: The proportion of effective imaging events accounts for about 2%, which allows our prototype to realize the reconstruction of the distribution of a 0.05 μSv/h 137Cs source in 10 s. The angular resolution for resolving two 137Cs point-like sources is 15°. Additional simulated imaging of the 6.13 MeV gamma-rays from 14.1 MeV neutron scattering with water preliminarily demonstrates the imaging capability for high incident energy. (4) Conclusions: We conclude that the prototype has a good imaging performance in a wide energy range (0.3~7 MeV), which shows potential in several MeV gamma-ray imaging applications. [ABSTRACT FROM AUTHOR]

Material innovation plays a very important role in technological progress and industrial development. Traditional experimental exploration and numerical simulation often require considerable time and resources. A new approach is urgently needed to accelerate the discovery and exploration of new materials. Machine learning can greatly reduce computational costs, shorten the development cycle, and improve computational accuracy. It has become one of the most promising research approaches in the process of novel material screening and material property prediction. In recent years, machine learning has been widely used in many fields of research, such as superconductivity, thermoelectrics, photovoltaics, catalysis, and high-entropy alloys. In this review, the basic principles of machine learning are briefly outlined. Several commonly used algorithms in machine learning models and their primary applications are then introduced. The research progress of machine learning in predicting material properties and guiding material synthesis is discussed. Finally, a future outlook on machine learning in the materials science field is presented. [ABSTRACT FROM AUTHOR]

Freezing severely impacts potato production. Deciphering the pathways and metabolites that regulate the freezing tolerance of potato is useful in cultivation and breeding for hardiness. In the present study, Solanum acaule was identified to be more freezing tolerant than S. tuberosum. Furthermore, the two genotypes before/after exposure to 4 °C for 7 d with additional −1 °C for 12 h were analysed by RNA-seq and metabolomics, and the results were compared with the previous −1 °C for 12 h. The results showed that S. acaule activated numerous genes that differed from those of S. tuberosum. Among the genes, five pathways, such as the hormone signalling pathway, which includes salicylic acid, were enriched. Further metabolomics analysis showed that the content of salicylic acid was improved in S. acaule in response to −1 °C for 12 h. Moreover, exogenous application of 0.1 mM salicylic acid to potato was shown to improve constitutive freezing tolerance and increase the expression of HSFC1. Following transcriptome and metabolome analyses, it was documented that the content of SA that increased in freezing-tolerant S. acaule after exposure to cold condition, associated with the SA signalling pathway, enhanced potato freezing tolerance, probably through HSFC1. [ABSTRACT FROM AUTHOR]

Background: D-amino acid oxidase (DAAO) is a flavoenzyme that specifically catalyzes the deamination of many neutral and basic D-amino acids. This study aims to explore the pathological increment of hippocampal DAAO and its potential relationship with delayed hippocampal neuronal death. Methods: Ischemia–reperfusion was induced in mice through middle cerebral artery occlusion (MCAO). Neurological deficit scores and hippocampal neuronal death were assessed in MCAO mice. Immunofluorescent staining was applied to identify activated astrocytes and evaluate DAAO expression. TUNEL and Nissl staining were utilized to identify cell apoptosis of hippocampal neurons. Results: Hippocampal astrocytic DAAO was strikingly increased following ischemic stroke, with the greatest increase on day 5 after surgery, followed by the manifestation of neurobehavioral deficits. Astrocytic DAAO was found to be mainly expressed in the hippocampal CA2 region and linked with subsequent specific neural apoptosis. Thus, it is supposed that the activation of astrocytic DAAO in ischemic stroke might contribute to neuronal death. An intravenous, twice-daily administration of 4H-furo[3,2-b]pyrrole-5-carboxylic acid (SUN, 10 mg/kg) markedly relieved behavioral status and delayed hippocampal neuronal death by 38.0% and 41.5%, respectively, compared to the model group treated with saline. In transfected primary astrocytes, DAAO overexpression inhibits cell activity, induces cytotoxicity, and promotes hippocampal neuronal death at least partly by enhancing H2O2 levels with subsequent activation of TRP calcium channels in neurons. Conclusions: Our findings suggest that increased hippocampal DAAO is causally associated with the development of delayed neuronal death after MCAO onset via astrocyte–neuron interactions. Hence, targeting DAAO is a promising therapeutic strategy for the management of neurological disorders. [ABSTRACT FROM AUTHOR]

With the rapid development of remote sensing technology and the growing demand for applications, the classical deep learning-based object detection model is bottlenecked in processing incremental data, especially in the increasing classes of detected objects. It requires models to sequentially learn new classes of objects based on the current model, while preserving old categories-related knowledge. Existing class-incremental detection methods achieve this goal mainly by constraining the optimization trajectory in the feature of output space. However, these works neglect the case where the previously learned background is a new category to learn, resulting in performance degradation in the new category because of the conflict between remaining the background-related knowledge or updating the background-related knowledge. This paper proposes a novel class-incremental detection method incorporated with the teacher-student architecture and the selective distillation (SDCID) strategy. Specifically, it is the asymmetry architecture, i.e., the teacher network temporarily stores historical knowledge of previously learned objects, and the student network integrates historical knowledge from the teacher network with the newly learned object-related knowledge, respectively. This asymmetry architecture reveals the significance of the distinct representation of history knowledge and new knowledge in incremental detection. Furthermore, SDCID selectively masks the shared subobject of new images to learn and previously learned background, while learning new categories of images and then transfers the classification results of the student model to the background class following the judgment model of the teacher model. This manner avoids interferences between the background category-related knowledge from a teacher model and the learning of other new classes of objects. In addition, we proposed a new incremental learning evaluation metric, C-SP, to comprehensively evaluate the incremental learning stability and plasticity performance. We verified the proposed method on two object detection datasets of remote sensing images, i.e., DIOR and DOTA. The experience results in accuracy and C-SP suggest that the proposed method surpasses existing class-incremental detection methods. We further analyzed the influence of the mask component in our method and the hyper-parameters sensitive to our method. [ABSTRACT FROM AUTHOR]

Simple Summary: The Chalcididae are a moderate-sized family of the superfamily Chalcidoidea in Hymenoptera, comprising 1548 species in 87 genera worldwide. Some species are potential natural enemies of pests in agriculture and forestry. Currently, there are still some controversies about the monophyly of Chalcididae and the phylogenetic relationships between Chalcididae and other families in Chalcidoidea. Based on the fact that no mitogenomic phylogenetic analyses of all of the published mitogenomes of Chalcidoidea have been conducted and no complete mitogenome of Chalcididae species has been reported, two newly completed mitochondrial genomes of Chalcididae species (Brachymeria lasus and Haltichella nipponensis) were sequenced and analyzed. The results show that the two chalcidid mitogenomes have quite similar structures and features. In phylogenetic analyses based on 13 PCGs of mitogenomes, the basal position and monophyly of Chalcididae within Chalcidoidea were supported by all trees derived from maximum likelihood (ML) and Bayesian inference (BI) methods. The complete mitochondrial genomes of two species of Chalcididae were newly sequenced: Brachymeria lasus and Haltichella nipponensis. Both circular mitogenomes are 15,147 and 15,334 bp in total length, respectively, including 13 protein-coding genes (PCGs), two ribosomal RNA genes (rRNAs), and 22 transfer RNA genes (tRNAs) and an A+T-rich region. The nucleotide composition indicated a strong A/T bias. All PCGs of B. lasus and H. nipponensis began with the start codon ATD, except for B. lasus, which had an abnormal initiation codon TTG in ND1. Most PCGs of the two mitogenomes are terminated by a codon of TAR, and the remaining PCGs by the incomplete stop codon T or TA (ATP6, COX3, and ND4 in both species, with an extra CYTB in B. lasus). Except for trnS1 and trnF, all tRNAs can be folded into a typical clover structure. Both mitogenomes had similar control regions, and two repeat units of 135 bp were found in H. nipponensis. Phylogenetic analyses based on two datasets (PCG123 and PCG12) covering Chalcididae and nine families of Chalcidoidea were conducted using two methods (maximum likelihood and Bayesian inference); all the results support Mymaridae as the sister group of the remaining Chalcidoidea, with Chalcididae as the next successive group. Only analyses of PCG123 generated similar topologies of Mymaridae + (Chalcididae + (Agaonidae + remaining Chalcidoidea)) and provided one relative stable clade as Eulophidae + (Torymidae + (Aphelinidae + Trichogrammatidae)). Our mitogenomic phylogenetic results share one important similarity with earlier molecular phylogenetic efforts: strong support for the monophyly of many families, but a largely unresolved or unstable "backbone" of relationships among families. [ABSTRACT FROM AUTHOR]

Graphene has been regarded as a potential application material in the field of new energy conversion and storage because of its unique two-dimensional structure and excellent physical and chemical properties. However, traditional graphene preparation methods are complicated in-process and difficult to form patterned structures. In recent years, laser-induced graphene (LIG) technology has received a large amount of attention from scholars and has a wide range of applications in supercapacitors, batteries, sensors, air filters, water treatment, etc. In this paper, we summarized a variety of preparation methods for graphene. The effects of laser processing parameters, laser type, precursor materials, and process atmosphere on the properties of the prepared LIG were reviewed. Then, two strategies for large-scale production of LIG were briefly described. We also discussed the wide applications of LIG in the fields of signal sensing, environmental protection, and energy storage. Finally, we briefly outlined the future trends of this research direction. [ABSTRACT FROM AUTHOR]

Salsola collina Pall has a long history of being used as a traditional medicine to treat hypertension, headache, insomnia, constipation and vertigo. However, only a few biologically active substances have been identified from S. collina. Here, the shoots and roots of S. collina, namely L-Sc and R-Sc, were studied. The primary and secondary metabolites were investigated using ultrahigh-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS). A total of 637 putative metabolites were identified and these metabolites were mainly classified into ten different categories. Correlation analysis, hierarchical clustering analysis, principal component analysis and orthogonal partial least squares discriminant analysis of metabolites showed that the L-Sc samples could be clearly separated from the R-Sc samples. Differential accumulated metabolite analysis revealed that most of differential primary metabolites were significantly lower in the L-Sc than in the R-Sc. Conversely, the major differential secondary metabolites had higher levels in the L-Sc than in the R-Sc. Further analysis indicated that the flavonoids were the major putative antioxidant components and most of putative antioxidant components exhibited higher relative concentrations in the L-Sc than the R-Sc. These results improve our understanding of metabolite accumulation and provide a reference for the study of medicinal value in S. collina. [ABSTRACT FROM AUTHOR]

A flexible wireless dielectric sensor is presented here for noninvasively monitoring the permittivity and conductivity of fluids, based on resistor–inductor–capacitor (RLC) resonant circuit and capacitively coupled contactless conductivity detection (C4D) technique. The RLC sensor consists of one single-turn inductor and one interdigital capacitor. The resonant frequency of the device is sensitive to the surrounding environment, thanks to the electric field leaked out between the interdigital capacitor electrodes. Through the high-frequency structure simulator (HFSS) simulation, and experiments on ethanol/water solutions and NaCl solutions, it was confirmed that a fluid's permittivity and conductivity could be detected by the return loss curve (S11). With great repeatability and stability, the proposed sensor has potential for broad applications, especially in wearable low-cost smart devices. [ABSTRACT FROM AUTHOR]

The identification of a new circovirus (Porcine Circovirus 3, PCV3) has raised concern because its impact on swine health is not fully known. In Fujian Province in eastern China, even its circulating status and genetic characteristics are unclear. Here, we tested 127 tissue samples from swine from Fujian Province that presented respiratory symptoms. All of the PCV3 positive samples were negative for many other pathogens involved in respiratory diseases like PCV2, PRRSV, and CSFV, suggesting that PCV3 is potentially pathogenic. From phylogenetic analysis, PCV3 strains are divided into two main clades and five sub-clades; PCV3a-1, PCV3a-2, PCV3a-3, PCV3b-1, and PCV3b-2. Our identified strains belong to genotypes PCV3a-1, PCV3a-2, PCV3a-3, and PCV3b-2, indicating a high degree of genetic diversity of PCV3 in Fujian province until 2019. Interestingly, we found the time of the most recent common ancestor (tMRCA) of PCV3 was dated to the 1950s, and PCV3 has a similar evolutionary rate as PCV2 (the main epidemic genotypes PCV2b and PCV2d). In addition, positive selection sites N56D/S and S77T/N on the capsid gene are located on the PCV3 antigen epitope, indicating that PCV3 is gradually adaptive in swine. In summary, our results provide important insights into the epidemiology of PCV3. [ABSTRACT FROM AUTHOR]

To develop implementation research on distributed optical fiber sensing technology, field tests were conducted on municipal roads and railways using a distributed acoustic sensor (DAS). Data were collected by the DAS during a field test for a long time period (more than 20 min), and we conducted short-term (<10 s) and long-term (≥10 s) analyses on these data separately. In the short-term data analysis, the vehicle type, vehicle length, and working status of the vehicle engine or the compressor were identified. In the long-term data analysis, the traffic flow was monitored, and the running distance, acceleration, speed, and braking distance of the vehicle were obtained. The characteristics of the vehicle operation data obtained in these field tests are important in developing the data processing method of DASs, which will help to promote the implementation of DASs. [ABSTRACT FROM AUTHOR]

Bifidobacterium longum subsp. longum XZ01 (BLSL1) is a new strain (isolated from the intestines of healthy people and deposited with the preservation number GDMCC 61618). An exopolysaccharide, S-EPS-1, was successfully isolated from the strain and then systematically investigated for the first time. Some structural features of S-EPS-1 were analyzed by chemical component, HPLC, ultraviolet, infrared, and nuclear magnetic resonance spectrum analyses. These analyses revealed that S-EPS-1 is a neutral heteropolysaccharide with an α-configuration. It contains mainly mannose and glucose, as well as small amounts of rhamnose and galactose. The molecular weight of S-EPS-1 was calculated to be 638 kDa. Several immunoregulatory activity assays indicated that S-EPS-1 could increase proliferation, phagocytosis, and NO production in vitro. In addition, S-EPS-1 could upregulate the expression of cytokines at the mRNA level through TLR4-mediated activation of the NF-κB signaling pathway in RAW 264.7 cells. Finally, S-EPS-1 was demonstrated to exhibit antioxidant activity by ABTS+• scavenging, DPPH• scavenging, and ferric-ion reducing power assays. Furthermore, S-EPS-1 can protect cells from oxidative stress and shows no cytotoxicity. These beneficial effects can be partly attributed to its antioxidant ability. Thus, the antioxidant S-EPS-1 may be applied as a functional food in the future. [ABSTRACT FROM AUTHOR]

Regulatory T cells (Tregs) are essential for maintaining immune tolerance and preventing autoimmune and inflammatory diseases. The activity and function of Tregs are in large part determined by various intracellular metabolic processes. Recent findings have focused on how intracellular metabolism can shape the development, trafficking, and function of Tregs. In this review, we summarize and discuss current research that reveals how distinct metabolic pathways modulate Tregs differentiation, phenotype stabilization, and function. These advances highlight numerous opportunities to alter Tregs frequency and function in physiopathologic conditions via metabolic manipulation and have important translational implications. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is one of the most common cancers that have high occurrence and death in both males and females. As various factors have been found to contribute to CRC development, personalized therapies are critical for efficient treatment. To achieve this purpose, the establishment of patient-derived tumor models is critical for diagnosis and drug test. The establishment of three-dimensional (3D) organoid cultures and two-dimensional (2D) monolayer cultures of patient-derived epithelial tissues is a breakthrough for expanding living materials for later use. This review provides an overview of the different types of 2D- and 3D-based intestinal stem cell cultures, their potential benefits, and the drawbacks in personalized medicine in treatment of the intestinal disorders. [ABSTRACT FROM AUTHOR]

The various industries, sectors, and citizens' daily lives have undergone significant changes after the outbreak of the COVID-19 pandemic. The researchers collected and analyzed PM2.5 samples including secondary inorganic ions (SO42−, NO3−, and NH4+, namely SNA), organic carbon (OC), elemental carbon (EC), and other 16 metal elements in Beijing in 2019 (before the pandemic) and 2020 (after the pandemic). The particulate matter (PM2.5) concentration in the autumn and winter of 2020 is 21.16 µg/m3 and 14.05 µg/m3 lower than in 2019, respectively. The contribution of six sources of pollution, including coal combustion, secondary sources, transportation-related sources, dust, Industrial I, and Industrial II, were analyzed using the Positive Matrix Factorization (PMF) model. Due to the impacts of the COVID-19 pandemic, more and more people are choosing private transportation, such as private cars, instead of public transportation. As a result, the contribution of PM2.5 pollution related to transportation increased after the pandemic. The metal elements measured during the sampling period represent only a very small fraction (1%) of PM2.5. However, their health risk to humans cannot be ignored because of the toxicity of some metallic elements, and the carcinogenic risks induced by metal elements in PM2.5 exceeded the safety threshold (>10−6) during the autumn and winter of 2019 and 2020. Arsenic (As) contributes the most to carcinogenic risk, so controlling arsenic emissions is the primary approach to reducing cancer risk in Beijing. Considering the contribution to the health risk from various sources obtained in PMF, coal combustion is the most significant contributor to cancer risk. Therefore, serious consideration should be given to controlling coal combustion at the local and regional levels to reduce health risks in Beijing. [ABSTRACT FROM AUTHOR]

Estimating the gamma dose rate at one meter above ground level and determining the distribution of radioactive pollution from aerial radiation monitoring data are the core technical issues of unmanned aerial vehicle nuclear radiation monitoring. In this paper, a reconstruction algorithm of the ground radioactivity distribution based on spectral deconvolution was proposed for the problem of regional surface source radioactivity distribution reconstruction and dose rate estimation. The algorithm estimates unknown radioactive nuclide types and their distributions using spectrum deconvolution and introduces energy windows to improve the accuracy of the deconvolution results, achieving accurate reconstruction of multiple continuous distribution radioactive nuclides and their distributions, as well as dose rate estimation of one meter above ground level. The feasibility and effectiveness of the method were verified through cases of single-nuclide (137Cs) and multi-nuclide (137Cs and 60Co) surface sources by modeling and solving them. The results showed that the cosine similarities between the estimated ground radioactivity distribution and dose rate distribution with the true value were 0.9950 and 0.9965, respectively, which could prove that the proposed reconstruction algorithm would effectively distinguish multiple radioactive nuclides and accurately restore their radioactivity distribution. Finally, the influences of statistical fluctuation levels and the number of energy windows on the deconvolution results were analyzed, showing that the lower the statistical fluctuation level and the more energy window divisions, the better the deconvolution results. [ABSTRACT FROM AUTHOR]

In recent years, three emerging cell deaths, ferroptosis, necroptosis and pyroptosis, have gradually attracted everyone's attention, and they also play an important role in the occurrence and development of various diseases. Ferroptosis is an idiographic iron-dependent form regulated cell death with the hallmark of accumulation of the intracellular reactive oxygen species (ROS). Necroptosis is a form of regulated necrotic cell death mediated by the receptor-interacting protein kinase 1(RIPK1) and receptor-interacting protein kinase 3RIPK3. Pyroptosis, also known as cell inflammatory necrosis, is a programmed cell necrosis mediated by Gasdermin D (GSDMD). It is manifested by the continuous swelling of the cells until the cell membrane ruptures, resulting in the release of the cell contents and the activation of a strong inflammatory response. Neurological disorders remain a clinical challenge and patients do not respond well to conventional treatments. Nerve cell death can aggravate the occurrence and development of neurological diseases. This article reviews the specific mechanisms of these three types of cell death and their relationship with neurological diseases and the evidence for the role of the three types of cell death in neurological diseases; understanding these pathways and their mechanisms is helpful for the treatment of neurological diseases. [ABSTRACT FROM AUTHOR]

Between 9 July and 19 August 2016, the air concentrations of 57 volatile organic compounds (VOCs) were measured in Shandong Province, eastern China. Seven sampling sites representing urban, coastal and background sites were selected for sampling. The measured data were employed to investigate the VOCs' characteristics, ozone formation potential, and main sources. During the sampling period, the concentrations of the VOCs ranged between 15.3 and 883 ppbv, with a mean of 139 ppbv. The most severely polluted city was Zibo (833 ppbv), followed by Jinan (33.5 ppbv) and Qingdao (32.8 ppbv). Propane was the most abundant species in all of the sampling sites, with a concentration range of 1.05–9.86 ppbv. Ethene, i-butane, 1-butene, cis-2-butene, n-butane, i-pentane, n-pentane, benzene and toluene were the predominant species in both the urban and coastal sites. Propylene equivalent concentrations (Pro-Equiv) and maximum incremental reactivity (MIR) were employed to assess the reactivity and contribution of each species to the photochemical ozone formation. The results showed that alkenes and aromatics were the most active species performing a key function in the ozone formation, accounting for 43.9–90.7% of the Pro-Equiv and 41.0–93% of the ozone formation potential (OFP). The ratios of ethylbenzene and m/p-xylene were calculated, and the results showed that local emissions were the main sources. Gasoline exhaust/fuel evaporation, industry process/solvent usage, diesel exhaust/petrochemical emission and coal burning were the dominant sources of VOCs in Shandong Province. [ABSTRACT FROM AUTHOR]

Cerebral ischemia/reperfusion (CI/R) injury causes high disability and mortality. Hydrogen (H2) enhances tolerance to an announced ischemic event; however, the therapeutic targets for the effective treatment of CI/R injury remain uncertain. Long non-coding RNA lincRNA-erythroid prosurvival (EPS) (lincRNA-EPS) regulate various biological processes, but their involvement in the effects of H2 and their associated underlying mechanisms still needs clarification. Herein, we examine the function of the lincRNA-EPS/Sirt1/autophagy pathway in the neuroprotection of H2 against CI/R injury. HT22 cells and an oxygen-glucose deprivation/reoxygenation (OGD/R) model were used to mimic CI/R injury in vitro. H2, 3-MA (an autophagy inhibitor), and RAPA (an autophagy agonist) were then administered, respectively. Autophagy, neuro-proinflammation, and apoptosis were evaluated by Western blot, enzyme-linked immunosorbent assay, immunofluorescence staining, real-time PCR, and flow cytometry. The results demonstrated that H2 attenuated HT22 cell injury, which would be confirmed by the improved cell survival rate and decreased levels of lactate dehydrogenase. Furthermore, H2 remarkably improved cell injury after OGD/R insult via decreasing pro-inflammatory factors, as well as suppressing apoptosis. Intriguingly, the protection of H2 against neuronal OGD/R injury was abolished by rapamycin. Importantly, the ability of H2 to promote lincRNA-EPS and Sirt1 expression and inhibit autophagy were abrogated by the siRNA-lincRNA-EPS. Taken together, the findings proved that neuronal cell injury caused by OGD/R is efficiently prevented by H2 via modulating lincRNA-EPS/Sirt1/autophagy-dependent pathway. It was hinted that lincRNA-EPS might be a potential target for the H2 treatment of CI/R injury. [ABSTRACT FROM AUTHOR]

Deep-water gas well testing is a key technology for obtaining reservoir production and physical property parameters. However, gas hydrates could easily form and cause blockage in the low-temperature and high-pressure environment on the seafloor. Therefore, it is extremely important to inhibit hydrate growth in deep-water operations. Ionic liquid is a type of hydrate inhibitor with both thermodynamic and kinetic effects. However, its intrinsic inhibiting mechanism is still unclear. By using molecular dynamics simulation, the growth process of methane hydrate in the 1-ethyl-3-methylimidazole chloride (EMIM-Cl)-containing system at the pressure of 15 MPa and temperature of 273.15 K was studied. The system energy and angular order parameters (AOP) were extracted as the evaluation indicators. It was found that the time for the complete growth of methane hydrate in the EMIM-Cl-containing system was about 10 ns, longer than that in the pure water, indicating that EMIM-Cl showed an obvious inhibition effect to hydrate growth. The results also implied that the joint action of hydrogen bond and steric hindrance might be the inhibition mechanism of EMIM-Cl. Some six-membered rings in hydrate crystal large cage structures evolved from five-membered rings under the effect of EMIM, which partly contributed to the delay of hydrate formation. [ABSTRACT FROM AUTHOR]

Silver nanowires (AgNWs) have received much attention and application in transparent electrodes, wearable electronic devices, and sensors. The hope is for these nanowires to eventually replace the most commonly used transparent electrode material—indium tin oxide (ITO). However, electrospinning used for the preparation of AgNWs on a large scale is limited by its low productivity and high electric field, while the alcohol-thermal method is limited to mixing by-product silver nanoparticles in silver nanowires. We demonstrate a novel and simple centrifugal spinning approach in order to successfully fabricate ultra-long silver microfibers based on AgNO3 and polyvinyl pyrrolidone (PVP). The centrifugal-spun precursor fiber and silver fiber can be prepared to as thin as 390 and 310 nm, respectively. Annealed fibers show typical nanostructures with grains down to a minimum size of 51 nm. Combinations of different parameters, including concentrations of PVP, needle size, and annealing temperature are also investigated, in order to optimize the spinning process of ultra-long silver microfibers. The feasibility of preparing silver microfibers by centrifugal spinning is preliminarily verified, examining prospects for mass production. Furthermore, numerous strategies related to assisting the creation of silver nanofibers using centrifugal spinning are presented as possibilities in future development. [ABSTRACT FROM AUTHOR]

The microstructure of asphalt affects the micro-mechanical properties. In this study, atomic force microscopy (AFM) was used to investigate the surface elastic modulus and nanohardness of asphalt binder. Relevant mechanical indexes were quantitatively evaluated by contact mechanical model. Five types of asphalts, including different grades, oil sources, and before and after modification, were selected as test objects, and the effects of asphalt binder type, aging, water, and anti-stripping agent on the asphalt micromechanics were explored. The results showed that the micromechanical properties of asphalt binder are affected by grade, oil source, and modification. The aging resistance of modified asphalt binder is better than that of unmodified asphalt binder. Water immersion reduces the surface micromechanical properties of the asphalt binder. The effect of the anti-stripping agent on the modified asphalt binder is greater than that of the unmodified asphalt binder. [ABSTRACT FROM AUTHOR]

Porcine circovirus-associated disease (PCVAD), caused by porcine circovirus type 2 (PCV2), has ravaged the pig industry, causing huge economic loss. At present, PCV2b and PCV2d are highly prevalent genotypes worldwide, while in China, in addition to PCV2b and PCV2d, a newly emerged PCV2e genotype detected in the Fujian province has attracted attention, indicating that PCV2 genotypes in China are more abundant. A preliminary study was conducted to better understand the genetic diversity and prevalence of PCV2 genotypes in southern China. We collected 79 random lung samples from pigs with respiratory signs, from 2018 to 2021. We found a PCV2-positivity rate of 29.1%, and frequent co-infections of PCV2 with PCV3, Streptococcus suis (S. suis), and other porcine pathogens. All PCV2-positive samples were sequenced and subjected to whole-genome analysis. Phylogenetic analysis, based on the PCV2 ORF2 gene and complete genomes, found that PCV2 strains identified in this study belonged to genotypes PCV2a (1), PCV2b (6), PCV2d (10), and PCV2e (6). Importantly, PCV2e was identified for the first time in some provinces, including Guangdong and Jiangxi. Additionally, we found two positively selected sites in the ORF2 region, located on the previously reported antigenic epitopes. Moreover, codon 63, one of the positively selected sites, has different types of amino acids in different genotypes. In conclusion, this study shows that PCV2e is an emerging genotype circulating in southern China, which warrants urgent, specific surveillance to aid the development of prevention and control strategies in China. [ABSTRACT FROM AUTHOR]

Purpose: Immune-related pneumonitis (IRP) has attracted extensive attention, owing to its increased mortality rate. Conventional chemotherapy (C) has been considered as an immunosuppressive agent and may thus reduce IRP's risk when used in combination with PD-1/L1 inhibitors. This study aimed to assess the risk of IRP with PD-1/L1 inhibitors plus chemotherapy (I+C) versus PD-1/L1 inhibitors alone (I) in solid cancer treatment. Method: Multiple databases were searched for RCTs before January 2021. This NMA was performed among I+C, I, and C to investigate IRP's risk. Subgroup analysis was carried out on the basis of different PD-1/L1 inhibitors and cancer types. Results: Thirty-one RCTs (19,624 patients) were included. The I+C group exhibited a lower risk of IRP in any grade (RR, 0.60; 95% CI, 0.38–0.95) and in grade 3–5 (RR, 0.44; 95% CI, 0.21–0.92) as opposed to the I group. The risk of any grade IRP with PD-1 plus chemotherapy was lower than that with PD-1 monotherapy (RR, 0.50; 95% CI, 0.28–0.89), although grade 3–5 IRP was similar. There was no statistically meaningful difference in the risk of any grade IRP between PD-L1 plus chemotherapy and PD-L1 inhibitors monotherapy (RR, 0.95; 95% CI, 0.43–2.09) or grade 3–5 IRP (RR, 0.71;95% CI, 0.24–2.07). In addition, compared with the I group, the I+C group was correlated with a decreased risk in IRP regardless of cancer type, while a substantial difference was only observed in NSCLC patients for grade 3–5 IRP (RR, 0.39; 95% CI, 0.15–0.98). Conclusion: In comparison to PD-1/L1 inhibitor treatment alone, combining chemotherapy with PD-1/L1 inhibitors might reduce the risk of IRP in the general population. Furthermore, PD-1 inhibitors in combination with chemotherapy were correlated with a decreased risk of IRP compared to PD-1 inhibitor treatment alone. In contrast to the I group, the I+C group exhibited a lower risk of IRP, especially for NSCLC patients. [ABSTRACT FROM AUTHOR]

The mechanical properties of the Al-Mg alloy can be enhanced by adding metallic elements, but a continuous distribution of precipitates at grain boundaries leads to intergranular corrosion during sensitization treatment. In the present work, Mn, Zn additions, water cooling and furnace cooling were executed to investigate their effects on the mechanical and corrosion properties of the Al-4.6Mg alloy. Our results show that adding Mn to Al-4.6Mg alloys may produce grain refinement and dispersion strengthening, increasing tensile strength and hardness. The presence of Mn did not affect the corrosion resistance of Al-Mg alloys. Adding Zn to the Al-4.6Mg alloy increased tensile strength and hardness, but decreased corrosion resistance. Combined, the addition of Mn and Zn to the Al-4.6Mg alloy exhibited the highest tensile strength and hardness, but seriously reduced corrosion resistance. Furnace cooling substituted for water quenching could avoid intergranular corrosion, but slightly decreased the tensile strength and hardness by 7.0% and 6.8%, respectively. [ABSTRACT FROM AUTHOR]

Although many persons in the United States have acquired immunity to COVID-19, either through vaccination or infection with SARS-CoV-2, COVID-19 will pose an ongoing threat to non-immune persons so long as disease transmission continues. We can estimate when sustained disease transmission will end in a population by calculating the population-specific basic reproduction number ℛ 0 , the expected number of secondary cases generated by an infected person in the absence of any interventions. The value of ℛ 0 relates to a herd immunity threshold (HIT), which is given by 1 − 1 / ℛ 0 . When the immune fraction of a population exceeds this threshold, sustained disease transmission becomes exponentially unlikely (barring mutations allowing SARS-CoV-2 to escape immunity). Here, we report state-level ℛ 0 estimates obtained using Bayesian inference. Maximum a posteriori estimates range from 7.1 for New Jersey to 2.3 for Wyoming, indicating that disease transmission varies considerably across states and that reaching herd immunity will be more difficult in some states than others. ℛ 0 estimates were obtained from compartmental models via the next-generation matrix approach after each model was parameterized using regional daily confirmed case reports of COVID-19 from 21 January 2020 to 21 June 2020. Our ℛ 0 estimates characterize the infectiousness of ancestral strains, but they can be used to determine HITs for a distinct, currently dominant circulating strain, such as SARS-CoV-2 variant Delta (lineage B.1.617.2), if the relative infectiousness of the strain can be ascertained. On the basis of Delta-adjusted HITs, vaccination data, and seroprevalence survey data, we found that no state had achieved herd immunity as of 20 September 2021. [ABSTRACT FROM AUTHOR]

The phase transition, microscopic morphology and optical and ferroelectric properties are studied in a series of La- and Co-doped KNbO3-based ceramics. The results show that the doping induces the transformation from the orthorhombic to the cubic phase of KNbO3, significantly reduces the optical bandgap and simultaneously evidently improves the leakage, with a slight weakening of ferroelectric polarization. Further analysis reveals that (i) the Co doping is responsible for the obvious reduction of the bandgap, whereas it is reversed for the La doping; (ii) the slight deterioration of ferroelectricity is due to the doping-induced remarkable extrinsic defect levels and intrinsic oxygen vacancies; and (iii) the La doping can optimize the defect levels and inhibit the leakage. This investigation should both provide novel insight for exploring the bandgap engineering and ferroelectric properties of KNbO3, and suggest its potential applications, e.g., photovoltaic and multifunctional materials. [ABSTRACT FROM AUTHOR]

In view of the time-varying complexity of the heat source for the ball screw feed system, this paper proposes an adaptive inverse problem-solving method to estimate the time-varying heat source and temperature field of the feed system under working conditions. The feed system includes multiple heat sources, and the rapid change of the moving heat source increases the difficulty of its identification. This paper attempts to develop a numerical calculation method for identifying the heat source by combining the experiment with the optimization algorithm. Firstly, based on the theory of heat transfer, a new dynamic thermal network model was proposed. The temperature data signal and the position signal of the moving nut captured by the sensors are used as input to optimize the solution of the time-varying heat source. Then, based on the data obtained from the experiment, finite element software parametric programming was used to optimize the estimate of the heat source, and the results of the two heat source prediction methods are compared and verified. The other measured temperature points obtained by the experiment were used to compare and verify the inverse method of this numerical calculation, which illustrates the reliability and advantages of the dynamic thermal network combined with the genetic algorithm for the inverse method. The method based on the on-line monitoring of temperature sensors proposed in this paper has a strong application value for heat source and temperature field estimation of complex mechanical structures. [ABSTRACT FROM AUTHOR]

First-principle calculations were used to investigate the surface structure and electronic properties of sulfide (pyrite, galena, and sphalerite) and oxide minerals (hematite, cerussite, and smithsonite). Surface relaxation and Femi energy, as well as projected DOS, are considered. Results show that the surface atoms of the sulfide minerals are more susceptible and more easily affected by the fracture bonds. The sulfide surfaces possess higher chemical potential than the corresponding oxide surfaces, and are more likely to be electron donors in reactions. The S 3p states are the mainly contributing states in the sulfide surface, while that in the oxide surface are O 2p states. The bonds of the sulfide surface have more covalent features and that of the oxide surface are ionic interactions. The O–M (M represents Fe, Pb or Zn) bonds are more stable, as the DOS of the oxide surfaces distribute in the lower energy range. [ABSTRACT FROM AUTHOR]

With the development of urbanization, people's living standards have improved. Simultaneously, the growing aggravation of resource shortages and environmental pollution have also gradually attracted widespread attention. Low-carbon energy planning can effectively reduce dependence on fossil resources and carbon emissions to the atmosphere, as well as improve the utilization of resources. Therefore, the formulation and evaluation of low-carbon energy planning have become the focus of attention for related colleges and institutions. This paper puts forward a hybrid multi-criteria decision making(MCDM) method combining decision making trial and evaluation laboratory(DEMATEL), analytical network process(ANP), and VIKOR to obtain the weight of each criterion and evaluate each alternative about low-carbon energy planning for building. A hierarchy structure of criteria involving cost, safety, reliability, and environment protection is built. Afterwards, a case of four alternatives is applied for testifying this methodology. Lastly, a comparison with prior methodologies serves as proof of the raised ranking. The presentation has proved that this methodology offers a more precise and effective foundation for decisions about low-carbon energy planning evaluation. [ABSTRACT FROM AUTHOR]

For the first time, the power law characteristics of stock price jump intervals have been empirically found generally in stock markets. The classical jump-diffusion model is described as the jump-diffusion model with power law (JDMPL). An artificial stock market (ASM) is designed in which an agent’s investment strategies, risk appetite, learning ability, adaptability, and dynamic changes are considered to create a dynamically changing environment. An analysis of these data packets from the ASM simulation indicates that, with the learning mechanism, the ASM reflects the kurtosis, fat-tailed distribution characteristics commonly observed in real markets. Data packets obtained from simulating the ASM for 5010 periods are incorporated into a regression analysis. Analysis results indicate that the JDMPL effectively characterizes the stock price jumps in the market. The results also support the hypothesis that the time interval of stock price jumps is consistent with the power law and indicate that the diversity and dynamic changes of agents’ investment strategies are the reasons for the discontinuity in the changes of stock prices. [ABSTRACT FROM AUTHOR]