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We investigated the relationship between parental conflict and adolescent academic burnout, along with the mediating role of the parent–child relationship and the moderating role of teacher support. We surveyed 886 first-year secondary vocational school students in Foshan City using four scales: the Adolescent Student Burnout Inventory, the Children's Perception of Interparental Conflict Scale, the Parent–Child Closeness Scale, and the Students' Perception of Teachers' Supporting Behavior Questionnaire. The results showed that adolescent academic burnout was directly and positively associated with parental conflict, and that the parent–child relationship partially mediated this relationship. Teacher support moderated the effect of parental conflict and affected adolescent academic burnout indirectly through parent–child relationships. Thus, parents should try to create an emotionally secure family environment for children and cultivate high-quality parent–child relationships, to prevent or intervene in academic burnout among adolescents. Additionally, schools should consider the role of teacher support in the improvement of parent–child relationships among students. [ABSTRACT FROM AUTHOR]

FV (finger vein) identification is a biometric identification technology that extracts the features of FV images for identity authentication. To address the limitations of CNN-based FV identification, particularly the challenge of small receptive fields and difficulty in capturing long-range dependencies, an FV identification method named Let-Net (large kernel and attention mechanism network) was introduced, which combines local and global information. Firstly, Let-Net employs large kernels to capture a broader spectrum of spatial contextual information, utilizing deep convolution in conjunction with residual connections to curtail the volume of model parameters. Subsequently, an integrated attention mechanism is applied to augment information flow within the channel and spatial dimensions, effectively modeling global information for the extraction of crucial FV features. The experimental results on nine public datasets show that Let-Net has excellent identification performance, and the EER and accuracy rate on the FV_USM dataset can reach 0.04% and 99.77%. The parameter number and FLOPs of Let-Net are only 0.89M and 0.25G, which means that the time cost of training and reasoning of the model is low, and it is easier to deploy and integrate into various applications. [ABSTRACT FROM AUTHOR]

The detection of an infrared small target faces the problems of background interference and non-obvious target features, which have yet to be efficiently solved. By employing the non-local self-correlation characteristic of the infrared images, the principle component pursuit (PCP)-based methods are demonstrated to be applicable to infrared small target detection in a complex scene. However, existing PCP-based methods heavily depend on the uniform distribution of the background pixels and are prone to generating a high number of false alarms under strong clutter situations. In this paper, we propose a group low-rank regularized principle component pursuit model (GPCP) to solve this problem. First, the local image patches are clustered into several groups that correspond to different grayscale distributions. These patch groups are regularized with a group low-rank constraint, enabling an independent recovery of different background regions. Then, GPCP model integrates the group low-rank components with a global sparse component to extract small targets from the background. Different singular value thresholds can be exploited for image groups corresponding to different brightness and grayscale variance, boosting the recovery of background clutters and also enhancing the detection of small targets. Finally, a customized optimization approach based on alternating direction method of multipliers is proposed to solve this model. We set three representative detection scenes, including the ground background, sea background and sky background for experiment analysis and model comparison. The evaluation results show the proposed model has superiority in background suppression and achieves better adaptability for different scenes compared with various state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Human-caused nitrogen (N) deposition is a global environmental issue that can change community composition, functions, and ecosystem services. N deposition affects plants, soil, and microorganisms regionally and is linked to ecosystem, soil, and climate factors. We examined the effects of six N addition levels (0, 2.34 g, 4.67, 9.34,18.68, and 37.35 g N m−2 yr−1) on aboveground vegetation, surface soil properties, and microbial community. Alterations in microbial communities in response to N addition were monitored using 16S rRNA (16S ribosomal ribonucleic acid, where S donates a sedimentation coefficient) and ITS (internal transcribed spacer) regions for bacterial and fungal communities, respectively. N addition positively affected aboveground vegetation traits, such as biomass and community weighted mean of leaf nitrogen. N addition also limited phosphorus (P) availability and altered the microbial community assembly process from random processes to deterministic processes. The microbial community diversity and composition, however, were not sensitive to N addition. Partial least squares structural equation models showed that the composition of bacterial communities was mainly driven by the composition of plant communities and total nitrogen, while the composition of fungal communities was driven by soil pH and community weighted mean of leaf nitrogen. Taken together, the results of this research improved our understanding of the response of grassland ecosystems to N deposition and provided a theoretical basis for grassland utilization and management under N deposition. [ABSTRACT FROM AUTHOR]

Epidemiological studies have shown that patients with glaucoma are more prone to depression, but the mechanism of comorbid depression in patients with glaucoma remains unknown. Excessive neuroinflammation has been shown to participate in glaucoma-induced retinal degeneration and hippocampal neural apoptosis in depression. However, little research has been conducted to determine whether neuroinflammation contributes to glaucoma-induced depression. Since the degeneration of retinal ganglion cells is a hallmark of glaucoma, we investigated the role of microglia-induced neuroinflammation in retinal degeneration-induced depression and its potential mechanism. An N-methyl-D-aspartate (NMDA)-induced retinal degeneration model was established, and behavioral tests were conducted at 3, 7, 14, and 21 days after retinal degeneration. After tissue collection, we used immunohistochemistry to assess the activation of microglia and real-time polymerase chain reaction to measure the levels of pro-inflammatory cytokines and the NOD-, LRR-, and pyrin-domain containing protein 3 (NLRP3) inflammasome. The mice exhibited depressive-like behaviors 14 and 21 days after retinal degeneration, based on the open field test, tail suspension test, and forced swimming test. Mice also displayed a lower body weight gain than the control group. In addition, microglial activation was observed in the hippocampus. Microglial proliferation was first observed in the dentate gyrus on day 3, while the number of microglia in cornu ammonis 1 grew the most. Moreover, not only was the expression of pro-inflammatory cytokines, including interleukin-1β, interleukin-18, and interleukin-6 promoted, but the messenger ribonucleic acid levels of the NLRP3 inflammasome were also increased. In conclusion, our research shows that NMDA-induced retinal degeneration can induce depressive-like behaviors, which may be attributed to hippocampal neuroinflammation. • NMDA-induced retinal degeneration leads to depressive-like behaviors. • Microglia-mediated neuroinflammation contributes to depressive-like behaviors. • The NLRP3/IL-1β pathway participates in depressive-like behaviors. [ABSTRACT FROM AUTHOR]

Objective: Progesterone supplementation is recommended to prevent spontaneous preterm birth (sPTB) in clinical practice. However, the exact mechanism is still unclear. This study aims to better understand the mechanisms that progesterone can prevent PTB. Methods: Late pregnant mice were given various doses of progesterone receptor antagonist mifepristone, and pregnancy outcomes were observed. Then, non‐pregnant and pregnant mice were given a subcutaneous injection of 40 mg/kg progesterone and 5 mg/kg mifepristone, respectively. CD4+CD25+FoxP3+ Treg cells in peripheral blood and decidua basalis were detected by FACS. Expressions of FoxP3 and TGF‐β1 in the decidua basalis were detected. Results: Mifepristone induced preterm birth, and an obvious dose‐response was found. Proportions of CD4+CD25+FoxP3+ Treg cells in the peripheral blood of non‐pregnant mice increased significantly after progesterone injection. CD4+CD25+FoxP3+ Treg cells in the peripheral blood of pregnant mice increased significantly compared with those of non‐pregnant mice. In pregnant mice, mifepristone significantly decreased the proportions of CD4+CD25+FoxP3+ Treg cells in peripheral blood, and reduced proportions of Treg cells at the maternal‐fetal interface and expressions of FoxP3 and TGF‐β1 in the maternal‐fetal interface. Total 40 mg/kg of progesterone did not increase CD4+CD25+FoxP3+ Treg in the peripheral blood of pregnant mice, but increased proportions of Treg cells at the maternal‐fetal interface and up‐regulated FoxP3 and TGF‐β1 expressions in the maternal‐fetal interface. Conclusion: Progesterone promotes pregnancy immune homeostasis by up‐regulating Treg cells and TGF‐β1 expression in the maternal‐fetal interface. It may be one of the mechanisms of progesterone in preventing sPTB. [ABSTRACT FROM AUTHOR]

It is well known that mono-sex culture has the advantages of a more rapid growth rate, more uniform size and lower energy consumption of gonadal development in fish. In production practice, male mandarin fish (Siniperca chuatsi) show great aquaculture value after the overwintering stage. As a species with an XY-type sex determination system, feminizing genetically male fish into physiological female fish and breeding YY supermales is a common method used to produce all-male populations. In this study, we systematically investigated feminization of mandarin fish by indirect feeding of 17β-estradiol (E 2) at different doses (200, 400 and 600 mg/kg). Neo-females were successfully yielded in all E 2 -treated concentrations. The sex-reversed ratios of the 200, 400 and 600 mg/kg E 2 -treated groups were 40%, 87% and 100%, respectively. From 45 to 135 dat (days after treatment), the gonads in the 600 mg/kg E 2 -treated group consisted of oogonium and previtellogenic oocytes. At 165 dat, early vitellogenic oocytes were observed in the gonads of the 600 mg/kg E 2 -treated group. Regarding the expression of sex-related genes, 600 mg/kg E 2 -treated mandarin fish presented a different gene expression pattern from that of normal males. Moreover, the growth and development status were also analysed in XY normal males and YY supermales at 360 dph, and YY supermales showed a higher number of lumina and significantly lower growth performance than XY normal males. In conclusion, we have established a technique for efficiently inducing male to female sex reversion and YY supermale breeding of mandarin fish, which provides a great foundation for the production of all-male mandarin fish. • Neo-females were successfully yielded in all three concentrations of E 2 (200, 400 and 600 mg/kg). • YY super-male mandarin fish was also obtained, which showed stronger reproductive capacity and slow growth speed. • Our study lays a great foundation for the production of all-male mandarin fish. [ABSTRACT FROM AUTHOR]

The copy number (CN) gain of protooncogenes is a frequent finding in gastric carcinoma (GC), but its prognostic implication remains elusive. The study aimed to characterize the clinicopathological features, including prognosis, of GCs with copy number gains in multiple protooncogenes. Three hundred thirty-three patients with advanced GC were analyzed for their gene ratios in EGFR, GATA6, IGF2, and SETDB1 using droplet dPCR (ddPCR) for an accurate assessment of CN changes in target genes. The number of GC patients with 3 or more genes with CN gain was 16 (4.8%). Compared with the GCs with 2 or less genes with CN gain, the GCs with 3 or more CN gains displayed more frequent venous invasion, a lower density of tumor-infiltrating lymphocytes, and lower methylation levels of L1 or SAT-alpha. Microsatellite instability-high tumors or Epstein–Barr virus-positive tumors were not found in the GCs with 3 or more genes with CN gain. Patients of this groups also showed the worst clinical outcomes for both overall survival and recurrence-free survival, which was persistent in the multivariate survival analyses. Our findings suggest that the ddPCR-based detection of multiple CN gain of protooncogenes might help to identify a subset of patients with poor prognosis. [ABSTRACT FROM AUTHOR]

The impact of external factors on the human gut microbiota and how gut microbes contribute to human health is an intriguing question. Here, the gut microbiome of 3,224 individuals (496 with serum metabolome) with 109 variables is studied. Multiple analyses reveal that geographic factors explain the greatest variance of the gut microbiome and the similarity of individuals' gut microbiome is negatively correlated with their geographic distance. Main food components are the most important factors that mediate the impact of host habitats on the gut microbiome. Diet and gut microbes collaboratively contribute to the variation of serum metabolites, and correlate to the increase or decrease of certain clinical indexes. Specifically, systolic blood pressure is lowered by vegetable oil through increasing the abundance of Blautia and reducing the serum level of 1‐palmitoyl‐2‐palmitoleoyl‐GPC (16:0/16:1), but it is reduced by fruit intake through increasing the serum level of Blautia improved threonate. Besides, aging‐related clinical indexes are also closely correlated with the variation of gut microbes and serum metabolites. In this study, the linkages of geographic locations, diet, the gut microbiome, serum metabolites, and physiological indexes in a Chinese population are characterized. It is proved again that gut microbes and their metabolites are important media for external factors to affect human health. [ABSTRACT FROM AUTHOR]

Background and Aims Compensatory base changes (CBCs) that occur in stems of ribosomal internal transcribed spacer 2 (ITS2) can have important phylogenetic implications because they are not expected to occur within a single species and also affect selection of appropriate DNA substitution models. These effects have been demonstrated when studying ancient lineages. Here we examine these effects to quantify their importance within a more recent lineage by using both DNA- and RNA-specific models. Methods We examined the phylogenetic implications of the CBC process by using a comprehensive sampling of ITS2 from ten closely related species of Corydalis. We predicted ITS2 secondary structures by using homology modelling, which was then used for a structure-based alignment. Paired and unpaired regions were analysed separately and in combination by using both RNA-specific substitution models and conventional DNA models. We mapped all base-pair states of CBCs on the phylogenetic tree to infer their evolution and relative timing. Key Results Our results indicate that selection acted to increase the thermodynamic stability of the secondary structure. Thus, the unpaired and paired regions did not evolve under a common substitution model. Only two CBCs occurred within the lineage sampled and no striking differences in topology or support for the shared clades were found between trees constructed using DNA- or RNA-specific substitution models. Conclusions Although application of RNA-specific substitution models remains preferred over more conventional DNA models, we infer that application of conventional DNA models is unlikely to be problematic when conducting phylogenetic analyses of ITS2 within closely related lineages wherein few CBCs are observed. Each of the two CBCs was found within the same lineages but was not observed within a given species, which supports application of the CBC species concept. [ABSTRACT FROM AUTHOR]

Highlights • A weighted reverse joint sparse model, considering the spatio-temporal characteristic of multiple templates, is proposed. • A binary indicator vector is employed to suppress the inaccurate results generated by the corrupted local image blocks. • An efficient solver, which is based on the smooth l 0, 2 norm, is proposed to solve the weighted joint sparse model. • The experimental results on OTB-100 show the proposed method outperforms other state-of-the-art tracking methods. Abstract In the particle filter framework, the sparse representation method models object tracking by predicting the likelihood of particles with respect to target templates. However, in most tracking methods, the spatio-temporal relationships of different templates have been neglected. This method applies the reverse sparse representation in multi-task learning, thus takes advantage of the temporal information and spatial continuity of a series of templates. Adding a predesigned weight matrix can reflect the temporal information, and make the new entrant templates have a greater influence on atoms' selection. To solve the locally weighted reverse joint sparse model (LWRJM), we design a modified smooth l 0, 2 algorithm which requires only a few iterations. The obtained sparse coding coefficients are mapped to a binary indicator vector by a statistic strategy, which is helpful to eliminate the contributions of the corrupted blocks and preserve the uncorrupted ones. Comparing with other state-of-the-art tracking methods on 100 challenging benchmark image sequences, the proposed tracker (LWRJM) outperforms other methods in both qualitative and quantitative evaluations. [ABSTRACT FROM AUTHOR]

The continuing dependence on fossil fuels and the rising energy use in the transport sector have resulted in increased research into viable transport biofuels to mitigate climate change and improve energy security. As transport biofuels now only have a small share of the transport sector energy supply and the complexity in providing the fuels because of issues related to available land and food security, this paper develops conversion path solutions for transport biofuel development based on a technological paradigm study. A data-driven approaches system (DAS) that combines visualization analyses with technological paradigm theory is proposed to reveal the key areas and trends in transport biofuels. Timeline, timezones, and cluster visualizations identified the transport biofuel technological paradigm (TBTP) from current transport biofuel developments; a pre-shift phase (including TBTP competition and TBTP diffusion) and a shift phase (TBTP shift), which respectively relate to conventional biofuels, advanced biofuels, and biofuel cells. However, from further DAS trend analyses and the practical findings, electric energy trends were revealed, indicating that there was a paradigm shift from the biofuel paradigm to a bio-electric energy paradigm. From the developed bio-electric energy framework, both indirect and direct methods were found to have led to an this electric energy conversion to an e-bio fuel cell vehicle for fuel cell electric vehicles (FCEV) and bioelectricity for electric vehicles (EV), both of which can contribute to a low-carbon, sustainable transportation future. [ABSTRACT FROM AUTHOR]

The detection of infrared dim and small targets in complex backgrounds is very challenging because of the low signal-to-noise ratio of targets and the drastic change in background. Low-rank sparse decomposition based on the structural characteristics of infrared images has attracted the attention of many scholars because of its good interpretability. In order to improve the sensitivity of sliding window size, insufficient utilization of time series information, and inaccurate tensor rank in existing methods, a four-dimensional tensor model based on superpixel segmentation and statistical clustering is proposed for infrared dim and small target detection (ISTD). First, the idea of superpixel segmentation is proposed to eliminate the dependence of the algorithm on selection of the sliding window size. Second, based on the improved structure tensor theory, the image pixels are statistically clustered into three types: corner region, flat region, and edge region, and are assigned different weights to reduce the influence of background edges. Next, in order to better use spatiotemporal correlation, a Four-Dimensional Fully-Connected Tensor Network (4D-FCTN) model is proposed in which 3D patches with the same feature types are rearranged into the same group to form a four-dimensional tensor. Finally, the FCTN decomposition method is used to decompose the clustered tensor into low-dimensional tensors, with the alternating direction multiplier method (ADMM) used to decompose the low-rank background part and sparse target part. We validated our model across various datasets, employing cutting-edge methodologies to assess its effectiveness in terms of detection precision and reduction of background interference. A comparative analysis corroborated the superiority of our proposed approach over prevailing techniques. [ABSTRACT FROM AUTHOR]

• ·T cells in pleural effusion have higher levels of STAT3 phosphorylation. • ·Multifunctional T cells of APTB patients have higher pSTAT3 levels. • ·The STAT3+ pSTAT3- phenotype of Mtb-specific T cells tended to be more anti-apoptotic. Tuberculosis (TB) remains one of the most serious infectious diseases in the world. Our aim was to investigate the regulatory role of STAT3 and pSTAT3 in the regulation of T cell immunophenotype and cell function. Twenty-five active pulmonary tuberculosis (APTB) patients, 18 latent tuberculosis infection (LTBI) patients, and 20 healthy controls (HCs) enrolled in this study. T cell phenotype and expression of STAT3 and pSTAT3 were detected by flow cytometry. Compared with HCs, the expression of pSTAT3 in CD4+ T and CD8+ T cells in peripheral blood of APTB patients was increased, and the expression was higher in pleural effusion. Multifunctional T cells that simultaneously secrete IFN-γ, TNF-α and IL-17A have higher pSTAT3 expression levels. Mtb-specific T cells from APTB patients had a higher cell frequency of the STAT3+ pSTAT3+ phenotype and a reduced cell frequency of the STAT3+ pSTAT3- phenotype compared with LTBI patients. Mtb-specific T cells with STAT3+ pSTAT3+ phenotype had higher expression of PD-1 and PD-L1, while cells with STAT3+ pSTAT3- phenotype had higher expression of Bcl-2. STAT3 and pSTAT3 in T cells of APTB patients feature in the process of anti-apoptosis and cytokine secretion. At the same time, the higher pSTAT3 may be related to the degree of cell functional exhaustion. The pSTAT3 level of T cells is related to the infection status and may indicate the clinical activity of the disease, which provides a new idea for the clinical identification and treatment of active pulmonary tuberculosis. [ABSTRACT FROM AUTHOR]

Convolutional neural networks (CNNs) have shown outstanding feature extraction capability and become a hot topic in the field of hyperspectral image (HSI) classification. However, most of the prior works usually focus on designing deeper or wider network architectures to extract spatial and spectral features, which give rise to difficulty for optimization and more parameters along with higher computation. Moreover, how to learn spatial and spectral information more effectively is still being researched. To tackle the aforementioned problems, a decompressed spectral-spatial multiscale semantic feature network (DSMSFNet) for HSI classification is proposed. This model is composed of a decompressed spectral-spatial feature extraction module (DSFEM) and a multiscale semantic feature extraction module (MSFEM). The former is devised to extract more discriminative and representative global decompressed spectral-spatial features in a lightweight extraction manner, while the latter is constructed to expand the range of available receptive fields and generate clean multiscale semantic features at a granular level to further enhance the classification performance. Compared with progressive classification approaches, abundant experimental results on three benchmark datasets prove the superiority of our developed DSMSFNet model. [ABSTRACT FROM AUTHOR]

Wood flour–poly(butylene succinate)–poly(lactic acid) biocomposite samples were prepared by fused-deposition-molding 3D-printing technology, and modifications with glycerol and a silane coupling agent (KH550) were carried out. The samples were then hydrothermally aged. Modification with glycerol and KH550 enhanced the hydrophilicity of the samples and increased their tensile strength. Hydrothermal aging clearly whitened the surfaces of all the samples and made them more hydrophobic. Meanwhile, their tensile properties and thermal stability became poor; a higher hydrothermal aging temperature affected the mechanical properties more negatively. The modified samples turned out to be more resistant to the hydrothermal aging, and modification with KH550 could improve the anti-hydrothermal aging properties of the samples better than that with glycerol, where the tensile properties and the cross-sectional morphologies of the fractured specimens were concerned. Generally, the effects of hydrothermal aging temperature on the physico-mechanical properties of the printed specimens were greater than those by hydrothermal aging time. [ABSTRACT FROM AUTHOR]

We developed a W/WO x -supported Ni catalyst for the diameter-controlled growth of single-walled carbon nanotubes (SWNTs) by chemical vapor deposition (CVD) valid for different substrates and broad growth conditions. The Ni nanoparticles anchored on W/WO x are well dispersed and show superior stability to high temperature. Under broad CVD windows of temperature and carbon feedstock supply conditions, SWNTs with narrow diameter distribution of ∼1.3 ± 0.1 nm can be steadily synthesized. This strategy also works well in the growth of surface lattice oriented SWNT arrays. The aligned SWNTs grown on ST-cut quartz show similar diameters to those obtained on silicon wafers. [ABSTRACT FROM AUTHOR]

Biofuels produced from renewable energy biomass are playing a more significant role because of the environmental problems resulting from the use of fossil fuels. However, a major problem with biofuel production is that despite the range of feedstock that can be used, raw material availability varies considerably. By combining a series of theories and methods, the research objective of this study is to determine the current developments and the future trends in biofuel feedstock. By combining technological paradigm theory with literature mining, it was found that biofuel feedstock production development followed a three-stage trajectory, which was in accordance with the traditional technological paradigm – the S-curve. This new curve can be divided into BFDP (biofuel feedstock development paradigm) competition, BFDP diffusion, and BFDP shift. The biofuel production diffusion velocity model showed that there has been constant growth from 2000, with the growth rate reaching a peak in 2008, after which time it began to drop. Biofuel production worldwide is expected to remain unchanged until 2030 when a paradigm shift is expected. This study also illustrates the results of our innovative procedure – a combination of the data analysis system and the technological paradigm theory – for the present biofuel feedstock soft path that will lead to this paradigm shift, with integrated biofuel production feedstock systems expected to be a significant new trend. [ABSTRACT FROM AUTHOR]

Lipophilic shellfish toxins (LSTs) produced by diverse microalgae have become a potential threat to the marine aquaculture industry in coastal regions throughout the world. In this study, phytoplankton, scallop, and seawater samples were collected and monitored in the aquaculture zone of Liuqing Bay located in the coast of Qingdao, Yellow Sea, in 2014 and 2015. Dissolved LSTs in seawater were adsorbed by solid phase adsorption toxin tracking (SPATT) bags and solid phase extraction (SPE) cartridges, respectively. PTX2 was found to be the predominant LSTs, while OA and DTX1 were detected at trace levels in the three species of Dinophysis and Phalacroma genera picked from the investigation zone. The highest quota of PTX2 occurred in D. fortii (0.28 pg cell −1 ), followed by D. acuminata complex (0.08 pg cell −1 ) and P. rotundatum (= D. rotundata ) (0.02 pg cell −1 ). PTX2 (nd∼5.7 μg kg −1 ), OA (nd∼2.8 μg kg −1 ) and DTX1 (nd∼1.6 μg kg −1 ) were also observed in cultivated scallops, but in addition to the former, PTX2sa, 7- epi -PTX2sa and an isobaric form of DTX1 suspected as DTX1b were also found in the SPATT bags. The isobaric compound of DTX1 only appeared in the SPATT bags deployed in field samples of seawater. A significant higher quantity of OA was adsorbed by SPATT bags compared to DTX1, although similar concentrations of both toxins were adsorbed by SPE cartridges from the aquaculture zone. AZA2 was also found in the concentrated phytoplankton cells, which demonstrated that AZA-producing microalgae were present in this investigated area. The variation in concentrations of PTX2 adsorbed by SPATT bags could reflect the change of Dinophysis density in seawater, but there was a time lag behind the peaks of Dinophysis density. Comparative results did not support the SPATT technology as a useful warning tool for toxic algal blooms and toxin accumulation in bivalves. The data suggest that the contamination of LSTs was prevalent in the coast of Qingdao and the environmental behavior of LSTs should be explored further. [ABSTRACT FROM AUTHOR]

Abstract: Zn1− x Co x O nanocrystals with nominal Co doping concentrations of x =0–0.1 were synthesized through a simple solution route followed by a calcining process. The doping effects on the structural, morphological and optical properties were investigated by means of X-ray diffraction, scanning electron microscopy, transmission electron microscopy, Raman, absorption and luminescence spectroscopy. The results indicated that a small amount of Co ions were incorporated into ZnO lattice structure, whereas the secondary phase of Co3O4 was segregated and precipitated at high Co doping concentrations, the solid solubility of Co ions in ZnO nanocrystals could be lower than 0.05. The spectra related to transitions within the tetrahedral Co2+ ions in the ZnO host crystal were observed in absorption and luminescence spectra. [Copyright &y& Elsevier]

Negative emissions technologies (NETs), which remove and isolate carbon dioxide from the atmosphere, are expected to play a significant role in mitigating climate change. As one of the most promising NETs, bioenergy with carbon capture and storage (BECCS) methods, which captures carbon dioxide (CO 2) emissions from bioenergy plants and then stores them in geological reservoirs, are being widely used in climate change scenarios. With the increased focus on mitigating solutions, several concerns have been raised regarding the deployment of BECCS. As no science mapping analyses of evolutionary BECCS patterns have yet been made, this study sought to determine these evolution patterns using a systematic analysis approach based on science mapping and visualization analyses. Under a longitudinal framework, the conceptual BECCS evolutionary track was determined using SciMAT to elucidate the structure and dynamic aspects of the associated scientific research. The co-word network and thematic evolutionary analysis revealed five main BECCS related themes. While this study provides a systematic study of BECCS research and development, further research should continue to focus on techno-economic analyses and the ecological and environmental impacts (land-use, water, diversity, and bioenergy crops) of BECCS. An increased research focus on the emerging biochar and hydrogen production themes is expected. Unlabelled Image • Data analysis system (DAS) is developed based on science mapping towards evolution patterns analysis. • A conceptual evolution of BECCS is conducted by SciMAT under a longitudinal framework to show the structure and dynamic aspects. • Five main thematic areas have been revealed by thematic evolution analysis. • Further research should continue to focus on techno-economic analyses and the ecological and environmental impacts. • An increased research focus on the emerging biochar and hydrogen production themes is expected. [ABSTRACT FROM AUTHOR]

Increasing concerns about traffic congestion, road safety, greenhouse gas emissions and energy consumption have resulted in people making different transportation choices, which in turn are affecting future mobility patterns. As "sustainable mobility" has become an increasingly popular idea, the focus of recent transportation research has been to identify and build a sustainable transport future. With this in mind, this paper developed an evolutionary trajectory for car sharing developments based on the technological paradigm to achieve sustainable mobility. A data analysis system (DAS) was built to identify the car sharing developments and literature mining and science mapping conducted to develop a new definition for the car sharing technological paradigm (CSTP). In each CSTP phase, some representative car sharing technologies or modes are discussed: single mode in the first competition stage; fusion mode in the second diffusion stage; and the integration of different modes in the third shift stage. Disruption was observed to occur when the first two stages went to the shift stage-integration mode and four disruptive technology-driven trends were identified in the paradigm shift from the existing paradigm to the new paradigm-sustainable mobility. The tech-integrated analyses found that the connected, autonomous, shared, electric (CASE) integration framework was a possible future sustainable mobility trend. The market dynamics analysis found that along with the key technologies, consumers, regulations and economic considerations, CASE was being implemented and deployed in the market. As it was found that policy has the opportunity to affect the future path to be taken, policy implications are outlined for future tech-integrated developments. The results of this study provide the government, the market, and the public, with information and guidance on the application of the proposed framework to ensure a sustainable mobility future. • Data-driven approaches system is developed towards visualization analysis and technological paradigm theory. • Car sharing technological paradigm (CSTP) is proposed as existing paradigm. • Disruptive technologies in the shift phase lead to a paradigm shift to a new paradigm-sustainable mobility. • The connected, autonomous, shared, electric (CASE) integration is a possible future sustainable mobility trend. • Policy has the opportunity to affect the future path to be taken. [ABSTRACT FROM AUTHOR]

• Transcranial magnetic stimulation (TMS) has been widely applied to diagnose and treat intractable brain diseases. • Both 50 Hz LF-EMF and HF-EMF can promote the proliferation of NSCs in vitro. • LF-EMF can accelerate NSCs to differentiate into neurons. To compare the effects of high- (HF-EMF) and low-frequency electromagnetic fields (LF-EMF) on the proliferation and differentiation of neural stem cells (NSCs). NSCs were obtained from SD rat hippocampus and cultured in suspension and adherent differentiation media. NSCs were exposed to LF-EMF (5 m T, 50 Hz, 30 min daily), HF-EMF (maximum magnetic induction 2.5 T, 40 % MO, 50 Hz, 10 min daily) and no electromagnetic field. At 3 d, cell viability and quantity of NSCs in suspension were detected by CCK-8 assay and cell counting plate. Immunofluorescence staining and qRT-PCR were performed to detect the percentage of Tu j -1 and GFAP-positive NSCs and the expression of Tuj-1 and GFAP mRNA. The P3 NSCs were positive with Nestin and induced NSCs expressed Tuj-1, GFAP and oligodendrocyte markers (MBP). CCK-8 assay and cell counting showed that the OD value and quantity of LF-EMF group were significantly higher than those in other two groups (both P < 0.05). Compared with the control group, the OD value and quantity were significantly higher in the HF-EMF group (P < 0.05). Immunofluorescence staining and qRT-PCR revealed that the percentage of Tuj-1 positive cells and the expression of Tuj-1 mRNA of NSCs exposed to LF-EMF were the highest (both P < 0.05). The proportion of GFAP-positive NSCs and the expression of GFAP mRNA did not significantly differ among three groups (all P > 0.05). Both 50 Hz LF-EMF and HF-EMF can promote the proliferation of NSCs in vitro and LF-EMF can accelerate NSCs to differentiate into neurons. [ABSTRACT FROM AUTHOR]

We aimed to explore the effects of type-2 diabetes mellitus (T2DM) and hypoglycemic therapy on the salivary microbiome in periodontitis patients and identify the potential salivary micro-biomarker for the early warning of T2DM. Saliva samples were collected from healthy individuals (Health), periodontitis patients (P), T2DM patients, periodontitis patients with T2DM (DAP), and DAP patients treated with Metformin (Met). Samples were determined by16S rRNA gene sequencing. 29 phyla, 322 genera, and 333 species of salivary microbiome were annotated. Compared to the Health group, the P and DAP group showed a significantly higher diversity of saliva microbiota, while the T2DM and Met group had no significant difference in microbial abundance but showed a trend of increasing diversity. Other than well-known periodontitis-inducing pathogens, the proportion of Prevotella copri, Alloprevotella rava, and Ralstonia pickettii, etc. were also significantly increased in periodontitis patients with or without T2DM. After effective glycemic control, the abundance of Prevotella copri, Alloprevotella rava, Ralstonia pickettii, etc. decreased in periodontitis patients with companion T2DM. The accuracies of the classification models in differentiating Health-vs.-P, DAP-vs.-P, and T2DM-vs.-P were 100%, 96.3%, and 98.1%, respectively. Hypoglycemic therapy could reconstruct the saliva microbiota and hence improve the localized conditions of diabetes patients with periodontitis. [ABSTRACT FROM AUTHOR]

The estimation of cement compressive strength is of great significance in the quality inspections, technological designs, and engineering applications for cement. Compared to destructive methods, the nondestructive estimation approaches save the cost in the manpower and material. However, the existing nondestructive methods have the large error because the used influence factors are difficult to control and the used two-dimensional microstructure images can not reflect the specific spatial structure of the entire cement. In this paper, a novel model is proposed to estimate the cement compressive strength using three-dimensional microstructure images and deep belief network. To reduce the computation consumption induced by three-dimensional images with abundant information, this method extracts image features that reflect the cement hydration state to estimate cement compressive strength. Deep belief network is applied to build the estimation model. Its unique training pattern and flexibility of parameters improve the ability to learn nonlinear relationships between microstructure images and cement compressive strength. Furthermore, the training processes are accelerated on the graphics processing units. The experimental results prove that the proposed method estimates cement compressive strength nondestructively and improves the efficiency. [ABSTRACT FROM AUTHOR]

Thermal infrared (TIR) target tracking is a challenging task as it entails learning an effective model to identify the target in the situation of poor target visibility and clutter background. The sparse representation, as a typical appearance modeling approach, has been successfully exploited in the TIR target tracking. However, the discriminative information of the target and its surrounding background is usually neglected in the sparse coding process. To address this issue, we propose a mask sparse representation (MaskSR) model, which combines sparse coding together with high-level semantic features for TIR target tracking. We first obtain the pixel-wise labeling results of the target and its surrounding background in the last frame, and then use such results to train target-specific deep networks using a supervised manner. According to the output features of the deep networks, the high-level pixel-wise discriminative map of the target area is obtained. We introduce the binarized discriminative map as a mask template to the sparse representation and develop a novel algorithm to collaboratively represent the reliable target part and unreliable target part partitioned with the mask template, which explicitly indicates different discriminant capabilities by label 1 and 0. The proposed MaskSR model controls the superiority of the reliable target part in the reconstruction process via a weighted scheme. We solve this multi-parameter constrained problem by a customized alternating direction method of multipliers (ADMM) method. This model is applied to achieve TIR target tracking in the particle filter framework. To improve the sampling effectiveness and decrease the computation cost at the same time, a discriminative particle selection strategy based on kernelized correlation filter is proposed to replace the previous random sampling for searching useful candidates. Our proposed tracking method was tested on the VOT-TIR2016 benchmark. The experiment results show that the proposed method has a significant superiority compared with various state-of-the-art methods in TIR target tracking. [ABSTRACT FROM AUTHOR]

Individual cell types of human tissues have their own CpG site methylation profiles, which might be utilized for the development of methylation markers to denote tumor-infiltrating lymphocytes (TILs). We aimed to develop DNA methylation markers that recapitulate the densities of TILs in gastric carcinoma (GC). Through genome-wide methylation profiling, NCOR2, PARK2, and ZSCAN12 were found to be highly methylated in CD3-positive and CD8-positive cells and rarely methylated in tumor cells. Scores of the three methylation markers were analyzed for their relationship with the overall survival and recurrence-free survival of patients with advanced GC (n = 471). The scores of three methylation markers were closely associated with densities of CD3-positive or CD8-positive cells at the tumor center or invasive front of GCs and found to be a significant prognostic factor in univariate analysis of overall survival and recurrence-free survival. In multivariate analysis, the highest score showed hazard ratios of 0.513 (CI 0.306–0.857) and 0.434 (CI 0.261–0.720) for overall survival and recurrence-free survival, respectively. The findings suggest that methylation markers signifying TILs might be utilized for the recapitulation of TIL density in GCs and serve as biomarkers for predicting prognosis in patients with GC. [ABSTRACT FROM AUTHOR]

In the context of extensive disciplinary integration, researchers worldwide have increasingly focused on musical ability. However, despite the wide range of available music ability tests, there remains a dearth of validated tests applicable to China. The Music Ear Test (MET) is a validated scale that has been reported to be potentially suitable for cross-cultural distribution in a Chinese sample. However, no formal translation and cross-cultural reliability/validity tests have been conducted for the Chinese population in any of the studies using the Music Ear Test. This study aims to assess the factor structure, convergence, predictiveness, and validity of the Chinese version of the MET, based on a large sample of Chinese participants (n≥1235). Furthermore, we seek to determine whether variables such as music training level, response pattern, and demographic data such as gender and age have intervening effects on the results. In doing so, we aim to provide clear indications of musical aptitude and expertise by validating an existing instrument, the Music Ear Test, and provide a valid method for further understanding the musical abilities of the Chinese sample. [ABSTRACT FROM AUTHOR]

Granulite facies rocks provide important keys to evaluating collisional metamorphism in orogenic belts. The mafic granulites of Baoding in the Fuping Complex of the North China Craton occur within the Trans-North China Orogen (TNCO), a major Paleoproterozoic collisional orogen. Here, we present results from detailed investigations on newly discovered garnet pyroxenite, garnet two-pyroxene granulite, and garnet-bearing-plagioclase amphibolite using petrographic, mineralogical, geochemical, and zircon U-Pb dating methods. Our results show that the Fuping Complex metamorphic evolution in this study evolved in four stages: prograde (M1), high-pressure granulite facies (M2), granulite facies (M3), and retrograde (M4) stages. The mineral assemblage of the prograde stage (M1) consists of Amp + Pl + Q within garnet cores. The mineral assemblage of high-pressure granulite facies at the peak stage (M2) consists of Gt + Cpx + Pl + Q ± Amp, forming the garnet pyroxenite. The granulite facies stage M3 is characterized by the occurrence of orthopyroxene, with a mineral assemblage of Gt + Cpx + Opx + Amp+ Pl + Q. The early retrograde stage M4-1 includes clinopyroxenes scattered inside amphiboles, following the breakdown of garnet and clinopyroxene. The mineral assemblage of this stage comprises Amp + Pl + Q + Ilm ± Cpx. Later, in the late retrograde stage M4-2, the composition of amphiboles changed to actinolite, and epidote and chlorite started to appear in the matrix. Traditional geothermobarometry yielded P-T conditions of 700~706 °C and 6.0~6.2 kbar for prograde stage M1, 854~920 °C and 13.0~13.8 kbar for high-pressure granulite facies stage M2, 912~939 °C and 8.1~9.9 kbar for M3, 661~784 °C and 3.1~4.4 kbar for M4-1, and 637~638 °C, 1.1~1.3 kbar for M4-2, along a clockwise P-T path with a nearly isothermal decompression (ITD) and slight heating. Zircon LA-ICP-MS U-Pb dating constrains the timing of the high-pressure granulite facies metamorphic event to be between 1.83 and 1.86 Ga. Geochemical features suggest that the protoliths of the high-pressure granulites may have formed in an island arc environment within a convergent margin setting. Together with results from previous studies, our data suggest that the ~1.85 Ga metamorphic age recorded in the Fuping Complex represents a regional metamorphism in the TNCO, associated with the subduction–collision and assembly of the Eastern and Western Blocks of the NCC. [ABSTRACT FROM AUTHOR]

Due to their devastating ability to extract features, convolutional neural network (CNN)-based approaches have achieved tremendous success in hyperspectral image (HSI) classification. However, previous works have been dedicated to constructing deeper or wider deep learning networks to obtain exceptional classification performance, but as the layers get deeper, the gradient disappearance problem impedes the convergence stability of network models. Additionally, previous works usually focused on utilizing fixed-scale convolutional kernels or multiple available, receptive fields with varying scales to capture features, which leads to the underutilization of information and is vulnerable to feature learning. To remedy the above issues, we propose an innovative hybrid-scale feature enhancement network (HFENet) for HSI classification. Specifically, HFENet contains two key modules: a hybrid-scale feature extraction block (HFEB) and a shuffle attention enhancement block (SAEB). HFEB is designed to excavate spectral–spatial structure information of distinct scales, types, and branches, which can augment the multiplicity of spectral–spatial features while modeling the global long-range dependencies of spectral–spatial informative features. SAEB is devised to adaptively recalibrate spectral-wise and spatial-wise feature responses to generate the purified spectral–spatial information, which effectively filters redundant information and noisy pixels and is conducive to enhancing classification performance. Compared with several sophisticated baselines, a series of experiments conducted on three public hyperspectral datasets showed that the accuracies of OA, AA, and Kappa all exceed 99%, demonstrating that the presented HFENet achieves state-of-the-art performance. [ABSTRACT FROM AUTHOR]

Poly(lactic acid) (PLA) and Poly(butylene succinate) (PBS) were chosen as raw materials and melt blended by a twin screw extruder and pelletized; then, the pellets were extruded into filaments; after that, various PBS/PLA blending samples were prepared by Fused Deposition Molding (FDM) 3D printing technology using the filaments obtained and the effect of the dosage of PBS on technological properties of 3D-printed specimens was investigated. For comparison, the PLA specimen was also prepared by FDM printing. The tensile strength, tensile modulus, thermal stability, and hydrophilicity became poorer with increasing the dosage of PBS, while the flexural strength, flexural modulus, impact strength, and crystallinity increased first and then decreased. The blend containing 10% PBS (10% PBS/PLA) had the greatest flexural strength of 60.12 MPa, tensile modulus of 2360.04 MPa, impact strength of 89.39 kJ/m2, and crystallinity of 7.4%, which were increased by 54.65%, 61.04%, 14.78%, and 51.02% compared to those of printed PLA, respectively; this blend also absorbed the least water than any other specimen when immersed in water. Different from the transparent PLA filament, 10% PBS/PLA filament presented a milky white appearance. The printed 10% PBS/PLA specimen had a smooth surface, while the surface of the printed PLA was rough. All the results indicated that the printed 10% PBS/PLA specimen had good comprehensive properties, including improved mechanical properties, crystallization performance, and surface quality than PLA, as well as proper wettability and water absorption. The prominent conclusion achieved in this work was that 10% PBS/PLA should be an ideal candidate for biodegradable feedstock among all the PBS/PLA blends for FDM 3D printing. [ABSTRACT FROM AUTHOR]

In recent years, detection of trace amounts of dissolved lipophilic phycotoxins in coastal waters has been possible using solid phase adsorption toxin tracking (SPATT) samplers. To explore the contribution of dissolved diarrhetic shellfish toxins (DST) to the accumulation of toxins by cultivated bivalves, mussels (Mytilus galloprovincialis) were exposed to different concentrations of purified okadaic acid (OA) and dinophysistoxin-1 (DTX1) in filtered (0.45 µm) seawater for 96 h. Accumulation and esterification of DST by mussels under different experimental conditions, including with and without the addition of the food microalga Isochrysis galbana, and with the addition of different size-fractions of suspended particulate matter (SPM) (<75 µm, 75–150 µm, 150–250 µm) were compared. Results showed that mussels accumulated similar amounts of OA and DTX1 from seawater with or without food microalgae present, and slightly lower amounts when SPM particles were added. Mussels preferentially accumulated OA over DTX1 in all treatments. The efficiency of the mussel’s accumulation of OA and DTX1 from seawater spiked with low concentrations of toxins was higher than that in seawater with high toxin levels. A large proportion of OA (86–94%) and DTX1 (65–82%) was esterified to DTX3 by mussels in all treatments. The proportion of I. galbana cells cleared by mussels was markedly inhibited by dissolved OA and DTX1 (OA 9.2 µg L−1, DTX1 13.2 µg L−1) in seawater. Distribution of total OA and DTX1 accumulated in the mussel tissues ranked in all treatments as follows: digestive gland > gills > mantle > residual tissues. However, the percentage of total DST in the digestive gland of mussels in filtered seawater (67%) was higher than with the addition of SPM particles (75–150 µm) (51%), whereas the gills showed the opposite trend in filtered seawater with (27%) and without (14.4%) SPM particles. Results presented here will improve our understanding of the mechanisms of DST accumulation by bivalves in marine aquaculture environments. [ABSTRACT FROM AUTHOR]

Many species of Corydalis (Papaveraceae) have been used as medicinal plants in East Asia, and the most well-known species are Corydalis yanhusuo and C. decumbens in the Pharmacopoeia of China. However, authentication of these species remains problematic because of their high morphological variation. Here, we selected 14 closely related species and five genomic regions (chloroplast: matK, trnG, rbcL, psbA-trnH; nuclear: ITS) to explore the utility of DNA barcoding for authenticating these herbs. In addition, the Poisson tree process (PTP) and automatic barcode gap discovery (ABGD) were also used and compared with DNA barcoding. Our results showed that the ITS region was not suitable for molecular analysis because of its heterogeneous nature in Corydalis. In contrast, matK was an ideal region for species identification because all species could be resolved when matK was used along with the other three chloroplast regions. We found that at least five traditional identified species were lumped into one genetic species by ABGD and PTP methods; thus, highlighting the overestimation of species diversity using the morphological approach. In conclusion, our first attempt of molecular analysis of Corydalis herbs presented here successfully resolved the identification of medicinal species and encouraged their taxonomic re-assessment. [ABSTRACT FROM AUTHOR]

In the field of landmark detection based on deep learning, most of the research utilise convolutional neural networks to represent landmarks, and rarely adopt Transformer to represent and encode landmarks. Meanwhile, many works focus on modifying the network structure to improve network performance, and there is little research on the distribution of landmarks. In this article,the authors propose an unsupervised model to extract landmarks of objects in images. First, Transformer structure is combined with the convolutional neural network structure to represent and encode the landmarks; next, positive and negative sample pairs between landmarks are constructed, so that the semantically consistent landmarks on the image are pulled closer in the feature space and the semantically inconsistent landmarks are pushed farther in the feature space; then the authors concentrate their attention on the most active points to distinguish the landmarks of an object from the background; finally, based on the new contrastive loss, the network reconstructs the image by the landmarks of the object that are continuously learnt during training. Experiments show that the proposed model achieves better performance than other unsupervised methods on the CelebA, Annotated Facial Landmarks in the Wild, 300W datasets. [ABSTRACT FROM AUTHOR]

In the face of climate change and possible future energy shortages, the installed capacity of clean energy natural gas (NG) and renewable energy (RE) for power generation has gradually increased. However, in the traditional electricity market, there is significant competition between NG and RE as gas prices tend to be volatile, and RE power generation from wind and solar can be intermittent and somewhat unreliable, indicating that these power sources have some drawbacks if used to independently generate electricity; therefore, determining the balance of NG and RE to ensure are resilient, reliable, flexible and affordable power generation system is an important goal. Based on the data analysis system (DAS) combined with paradigm theory, this paper examines the possibility of hybrid power generation in the future. The results of literature analysis visualization show that NG or RE has its own power generation paradigm, and a paradigm shift towards hybrid NG-RE power generation was found, so NG-RE power generation paradigm (NGREP) was proposed. To determine whether these NG-RE hybrid energy developments could be more competitive than separate developments, a comparative analysis was conducted, from which it was found that hybrid NG-RE systems are more attractive in some cases. However, as there are still challenges in the developments of these systems, a driving force is needed to promote further hybrid developments. Using hybrid power generation in areas with plentiful wind, solar and gas can maximize energy use efficiency and significantly reduce carbon emissions and other pollutants. [ABSTRACT FROM AUTHOR]

Ginsenoside Rc is one of the active components used in traditional Chinese medicine. We aim to explore how ginsenoside Rc can be used in the treatment of osteoporosis. Micro-CT demonstrated that the treatment of ovariectomized (OVX) mice with ginsenoside Rc significantly inhibited the decrease in bone mineral density, bone volumetric fraction, and trabecular number, and the increase in trabecular separation. Histological staining, qRT-PCR, and Western blot demonstrated that ginsenoside Rc enhances the microstructure of trabecular bone, and promotes the expression of bone formation-related genes. Alkaline phosphatase (ALP) staining, Alizarin Red staining, qRT-PCR, and Western blotting demonstrated that ginsenoside Rc dose-dependently promoted the osteogenic differentiation of MC3T3-E1 cells. A ginsenoside Rc-induced increase in the expression of β-catenin, p-GSK-3β, collagen-1, ALP, and RUNX-2 family transcription factor-2 was significantly attenuated upon 10 μM XAV-939 treatment, while the decrease in the expression of GSK-3β and p-β-catenin was significantly enhanced. Ginsenoside Rc promotes bone formation in ovariectomy-induced osteoporosis in vivo and promotes osteogenic differentiation in vitro via the Wnt/β-catenin signaling pathway. [ABSTRACT FROM AUTHOR]

• Cytotoxic cells decreased but activation increased in septic shock patients. • The function of toxic cells 2–3 days after admission indicated the clinical outcome. • Dynamic monitoring of cytotoxic cells in patients with septic shock was key. : Septic shock is a great threat to human life. Our aim is to explore the immune status and dynamic changes of circulating cytotoxic cells in septic shock patients. : Forty-eight septic shock patients (9 non-survivors and 39 survivors) and 30 healthy controls (HCs) were enroled in our study. The function of cytotoxic cells was dynamically monitored by flow cytometry. : The number of circulating CD8+ T and NK cells decreased significantly in septic shock patients, while the number of CD8+ T cells rose in survivors 5 days after admission. The frequency of HLA-DR+CD8+ T / NK cells increased in both groups after admission but decreased in non-survivors on day 3. Moreover, the frequency of GrA+/GrB+/perforin+NK and GrB+CD8+ T cells decreased to varying degrees in both groups, and the frequency of GrB+/perforin+CD8+ T cells on the second day of non-survivors was significantly lower than that of survival patients. Besides, the frequency of CXCR3+CD8+ T / NK cells was decreased in both groups and remained low in non-survivors, but remarkably increased in survivors after day 3. And the concentrations of cytokines IL-6, IL-10, TNF-α and IFN-γ were significantly increased in septic shock patients. : Circulating CD8+ T and NK cells reduced but activation function was compensatory enhanced in septic shock patients. The frequency of GrB+/PFP+CD8+ T and CXCR3+CD8+ T / NK cells may predict the progression of septic shock patients 2–3 days after admission. [ABSTRACT FROM AUTHOR]

[Display omitted] • Single-atom Cu anchored on algal-based carbon was prepared by one-step pyrolysis. • Single atom Cu was successfully loaded and coordinated with two N and two C. • TC was almost completely removed when the Cu–N/C-SAC(S) dosage was 0.1 g/L. • Cu–N/C-SAC(S) has a wide pH adaptation range and strong anti-interference ability. • Activation process of Cu–N/C-SAC(S) producing SO4•− was easier by DFT calculation. Single-atom catalysts have wide application prospects in peroxydisulfate (PDS)-based advanced oxidation process to degrade organic pollutants, but its catalytic performance is limited due to its cost, Metal-N coordination number, and single-atom loading amount. Herein, a novel nitrogen doped algal-based carbon confined single-atom copper catalyst (Cu–N/C-SAC (S)) was synthesized using molten salt assisted pyrolysis and coupling with PDS to degrade tetracycline (TC). AC-HAADF-STEM and XAFS analysis proved that single atom Cu was loaded (Content 1.9 %) successfully and coordinated with two N and two C. XPS and XANES spectra analysis suggested that Cu atoms mainly existed in a positive divalent state in Cu–N/C-SAC (S). When the catalyst dosage of Cu–N/C-SAC (S) was 0.1 g/L, TC was almost completely removed. Moreover, Cu–N/C-SAC (S) had a broad pH adaptation range and strong ability against interference. Singlet oxygen (1O 2), superoxide radicals (•O 2 −), and electron transfer had an important contribution for TC removal. DFT calculations confirmed that the activation process of Cu–N/C-SAC (S) producing SO 4 •− was easier than the nitrogen doped blue-green algal-based carbon (N-BGAC). In addition, Cu–N/C-SAC (S) possessed good recyclability and stability. The main degradation pathways of TC were analyzed, and the toxicity of the intermediates was calculated. This study provides a new solution strategy for the resource utilization of waste biomass, and provides technical support and theoretical guidance for the efficient application of single-atom catalysts in organic wastewater. [ABSTRACT FROM AUTHOR]

The order of the affiliations is incorrect. Please view the correct affiliation order below:Xiaoyu Wang2, Xiubo Ren2, Shidan Wang 2, Dan Yang2, Shilin Liu2, Meihui Li2, Mingyi Yang2, Yintong Liu2, Qiujian Xu1,2*1 School of Arts and Design, Yanshan University, 066000, Qinhuangdao, China, 2 Music College, Catholic University of Daegu, 13–13 Hayang-ro, Hayang-eup, Gyeongsan-si, Gyeongsangbuk-do, Republic of Korea.By Xiaoyu Wang; Xiubo Ren; Shidan Wang; Dan Yang; Shilin Liu; Meihui Li; Mingyi Yang; Yintong Liu and Qiujian XuReported by Author; Author; Author; Author; Author; Author; Author; Author; Author [Extracted from the article]

Background: Gastric cancer (GC) is a leading cause of cancer morbidity and mortality worldwide. This is due to the heterogeneous features of GC, which consist of a diverse molecular phenotype. Epstein–Barr virus (EBV)-positive GC and microsatellite instability (MSI)-high GC encompass similar epigenetic traits, including high levels of DNA methylation in CpG islands; however, EBV-positive and MSI-high GCs are mutually exclusive. We aimed to elucidate the underlying mechanism of this exclusivity. Methods: We knocked out MLH1 in EBV-positive GC cell lines SNU-719 and NCC24 via CRISPR-Cas9, and evaluated the modified cellular properties in vitro and in vivo. The MSI status of each cell line was screened with two marker capillary electrophoresis, and further diagnosed with five marker capillary electrophoresis and parallel sequencing using 21 markers. Results: Initial evaluation showed that cell growth, migration, invasion, and MSI status were not affected by MLH1 silencing. However, with prolonged passage, GC cell lines gradually gained MSI and NCC24 cells were transformed to EBV-positive/MSI-high GC cells after 12 months. Furthermore, MLH1 silencing reduced tumor stemness in SNU-719 and NCC24 regardless of the MSI status in vitro and in vivo. Conclusions: Our findings suggest that EBV-positivity and MSI-high status are mutually exclusive due to the immediate disadvantage in tumor stemness when MLH1 is silenced, whereas the establishment of MSI-high status in EBV-positive GCs required a longer period. [ABSTRACT FROM AUTHOR]

Background: Intrahepatic cholangiocarcinoma (iCCA) is the second most common malignant hepatic tumor and has a high postoperative recurrence rate and a poor prognosis. The key roles of most tumor recurrence-associated molecules in iCCA remain unclear. This study aimed to explore hub genes related to the postsurgical recurrence of iCCA. Method: Differentially expressed genes (DEGs) between iCCA samples and normal liver samples were screened from The Cancer Genome Atlas (TCGA) database and used to construct a weighted gene coexpression network. Module-trait correlations were calculated to identify the key module related to recurrence in iCCA patients. Genes in the key module were subjected to functional enrichment analysis, and candidate hub genes were filtered through coexpression and protein–protein interaction (PPI) network analysis. Validation studies were conducted to detect the "real" hub gene. Furthermore, the biological functions and the underlying mechanism of the real hub gene in iCCA tumorigenesis and progression were determined via in vitro experiments. Results: A total of 1019 DEGs were filtered and used to construct four coexpression modules. The red module, which showed the highest correlations with the recurrence status, family history, and day to death of patients, was identified as the key module. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses demonstrated that genes in the red module were enriched in genes and pathways related to tumorigenesis and tumor progression. We performed validation studies and identified estrogen receptor 1 (ESR1), which significantly impacted the prognosis of iCCA patients, as the real hub gene related to the recurrence of iCCA. The in vitro experiments demonstrated that ESR1 overexpression significantly suppressed cell proliferation, migration, and invasion, whereas ESR1 knockdown elicited opposite effects. Further investigation into the mechanism demonstrated that ESR1 acts as a tumor suppressor by inhibiting the JAK/STAT3 signaling pathway. Conclusions: ESR1 was identified as the real hub gene related to the recurrence of iCCA that plays a critical tumor suppressor role in iCCA progression. ESR1 significantly impacts the prognosis of iCCA patients and markedly suppresses cholangiocarcinoma cell proliferation, migration and invasion by inhibiting JAK/STAT3 signaling pathway. [ABSTRACT FROM AUTHOR]

Similarity-based approaches have made significant progress in visual object tracking (VOT). Although these methods work well in simple scenes, they ignore the continuous spatio-temporal connection of the object in the video sequence. For this reason, tracking by spatial matching solely can lead to tracking failures because of distractors and occlusion. In this paper, we propose a spatio-temporal joint-modeling tracker named STTrack which implicitly builds continuous connections between the temporal and spatial aspects of the sequence. Specifically, we first design a time-sequence iteration strategy (TSIS) to concentrate on the temporal connection of the object in the video sequence. Then, we propose a novel spatial temporal interaction Transformer network (STIN) to capture the spatio-temporal correlation of the object between frames. The proposed STIN module is robust in object occlusion because it explores the dynamic state change dependencies of the object. Finally, we introduce a spatio-temporal query to suppress distractors by iteratively propagating the target prior. Extensive experiments on six tracking benchmark datasets demonstrate that the proposed STTrack achieves excellent performance while operating in real-time. The code is publicly available at https://github.com/nubsym/STTrack. [ABSTRACT FROM AUTHOR]

Members of the transforming growth factor β (TGF-β) signaling pathway regulate diverse cellular biological processes in embryonic and tissue development. We took mandarin fish (Siniperca chuatsi) as the research object to identify all members of the TGF-β signaling pathway, measure their expression pattern in the key period post hatching, and further explore their possible role in the process of sex regulation. Herein, we identified eighty-three TGF-β signaling pathway members and located them on chromosomes based on the genome of mandarin fish. TGF-β signaling pathway members were highly conserved since each TGF-β subfamily clustered with orthologs from other species. Transcriptome analysis, qRT–PCR and in situ hybridization demonstrated that most mandarin fish TGF-β signaling pathway members presented stage-specific and/or sex-dimorphic expression during gonadal development, and different members of the TGF-β signaling pathway participated in different stages of gonadal development. Taken together, our results provide new insight into the role of TGF-β signaling pathway members in the sex regulation of mandarin fish. [ABSTRACT FROM AUTHOR]

Aiming at the application requirements of infrared detection, the influence of earth background interference on plume radiation detection is investigated and discussed in this article. The infrared image of the earth's atmospheric background radiation is simulated by the spectral correlation based on the conversion model of the surface radiation with different bands. The infrared radiation image of the jet flame and the background is generated by overlapping the infrared radiation of the engine flame and the background radiation according to the detection angle of view. Through the image quality evaluation model, the detectability of the flame is analyzed. The simulating results show that the comprehensive statistical features such as image information entropy, variance and signal-to-clutter ratio can be used to evaluate the detectability of the engine flame. [ABSTRACT FROM AUTHOR]

Objective: To investigate the effect and mechanism of SB525334 on self-renewal, migration and invasion of ovarian cancer stem cells. Methods: ALDHhigh-expressing cancer stem cells (CSCs) were isolated from human ovarian cancer cell line SKOV-3 by flow cytometry and treated with 2μg/mL SB525334 for 6h. The sphere forming assay was used to detect the ability of self-renewal of CSCs and the colony formation assay was used to detect the tumorigenicity in vitro. Transwell migration and invasion assay were used to detect the migration and invasion ability of CSCs. To further explore the mechanism, real-time quantitative PCR and flow cytometry were used to detect the mRNA and protein expression of TGF-β, Smad2, Smad3, phosphorylated Smad2, phosphorylated Smad3 and Smad4, respectively. Expressions of epithelial-mesenchymal transition (EMT)-related genes E-cadherin, Snail, Vimentin were also assessed. Results: The self-renewal ability, tumorigenicity in vitro, migration and invasion ability of CSCs were significantly attenuated after SB525334 treatment. The expressions of TGF-β, phosphorylated Smad2, phosphorylated Smad3, Snail, and Vimentin were decreased, while Smad4 and E-cadherin expressions were increased. Conclusion: SB525334 may inhibit the self-renewal, invasion and migration of ovarian CSCs by blocking the TGF-β/Smad/EMT pathway. [ABSTRACT FROM AUTHOR]

Patterned materials on substrates are of great importance for a wide variety of applications. In solution-based approaches to material patterning, fluidic flow is inevitable. Here we demonstrate not only the importance of fluidic behavior but also the methodology of engineering the flow pattern to guide the material crystallization and assembly. We show by both experiment and simulation that substrate heating, which is generally used to accelerate evaporation, produces irregular complex vortexes. Instead, a top-heating–bottom-cooling (THBC) set-up offers an inverse temperature gradient and results in a single Marangoni vortex, which is desired for ordered nanomaterial patterning near the contact line. We then realize the fabrication of large-scale patterns of iodide perovskite crystals on different substrates under THBC conditions. We further demonstrate that harnessing the flow behavior is a general strategy with great feasibility to pattern various functional materials ranging from inorganic, organic, hybrid to biological categories on different substrates, presenting great potential for practical applications. [ABSTRACT FROM AUTHOR]

Coal mining technology directly affects coal production quantity and quality, which in turn affects global energy supplies, especially in rapidly urbanizing, industrializing economies. In this research, a coal production technological diffusion mathematical model is proposed, the results from which indicated that while total coal production is expected to decline in the following decades, coal will continue to provide a sizable share of global prime energy to meet the expected energy demands. A general data analysis was conducted to fully understand coal mining technological paradigmatic development and future necessary improvements to ensure more efficient, environmentally-friendly coal production. It was found that the coal mining technological paradigm followed a three-stage trajectory; competition, diffusion, and shift; in accordance with the traditional technological paradigm S-curve, and underground coal gasification (UCG) related technologies were identified as the main development direction for coal mining technologies. An integrated energy exploitation approach for ecological coal mining was then designed to deal with current environmental and energy returns on investment problems, to improve performance, and to act as a foundation for future UCG technological developments. Some policy recommendations are given to guide the implementation of the proposed ecologically oriented integrated coal mining system. [ABSTRACT FROM AUTHOR]

The nearest neighbor partitioning (NNP) method is a high performance approach which is used for improving traditional neural network classifiers. However, the construction process of NNP model is very time-consuming, particularly for large data sets, thus limiting its range of application. In this study, a parallel NNP method is proposed to accelerate NNP based on Compute Unified Device Architecture(CUDA). In this method, blocks and threads are used to evaluate potential neural networks and to perform parallel subtasks, respectively. Experimental results manifest that the proposed parallel method improves performance of NNP neural network classifier. Furthermore, the application of parallel NNP in performance evaluation of cement microstructure indicates that the proposed approach has favorable performance. [ABSTRACT FROM AUTHOR]

Proponents of distributive justice with regard to energy hold that every household has the right to affordable access to energy. However, when passively participating in clean energy reform policies, households, and especially low-income households, are often forced to use energy beyond the scope of affordability, resulting in distributive injustice. However, research on the quantitative estimation of injustice in energy distribution is still rare. In this paper, an evaluation model of energy vulnerability and distributive justice is established through the "reverse deduction method," and the change value of energy vulnerability before and after energy reform is used to calculate the loss value of distributive justice, which is used as the basis for energy policy evaluation. Taking the policy of replacing coal with natural gas for rural heating in Gaocheng District, Hebei Province, China as a case study, the value of lost distributive justice is calculated. The results show that 34.51% of households experienced distributive injustice after the energy reform, while 19.34% of households improved their energy vulnerability and achieved energy justice through energy subsidy policies. However, 46.15% of households were able to adapt to the energy reform independently without subsidies, which indicates a waste of resources in the energy subsidy policy. The policy implication of these results is that differentiated energy subsidy policies should be implemented according to household energy vulnerability, so as to maximize the policy benefits on the premise of ensuring justice in household energy distribution and minimizing injustice. The empirical study proves that the method of assessing injustice in energy distribution based on the "reverse deduction method" of energy vulnerability is feasible and a new attempt. • The passive participation of low-income households in clean energy reform policies results in distributive injustice. • Apply the vulnerability framework to calculate energy distribution injustice. • The implementation of differentiated subsidies can effectively improve the vulnerability of rural households energy poverty. • It is feasible and a new attempt to measure energy distributive injustice by using the "reverse deduction method". [ABSTRACT FROM AUTHOR]