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PM2.5 poses a serious threat to human life and health, so the accurate prediction of PM2.5 concentration is essential for controlling air pollution. However, previous studies lacked the generalization ability to predict high-dimensional PM2.5 concentration time series. Therefore, a new model for predicting PM2.5 concentration was proposed to address this in this paper. Firstly, the linear rectification function with leakage (LeakyRelu) was used to replace the activation function in the Temporal Convolutional Network (TCN) to better capture the dependence of feature data over long distances. Next, the residual structure, dilated rate, and feature-matching convolution position of the TCN were adjusted to improve the performance of the improved TCN (LR-TCN) and reduce the amount of computation. Finally, a new prediction model (GRU-LR-TCN) was established, which adaptively integrated the prediction of the fused Gated Recurrent Unit (GRU) and LR-TCN based on the inverse ratio of root mean square error (RMSE) weighting. The experimental results show that, for monitoring station #1001, LR-TCN increased the RMSE, mean absolute error (MAE), and determination coefficient (R2) by 12.9%, 11.3%, and 3.8%, respectively, compared with baselines. Compared with LR-TCN, GRU-LR-TCN improved the index symmetric mean absolute percentage error (SMAPE) by 7.1%. In addition, by comparing the estimation results with other models on other air quality datasets, all the indicators have advantages, and it is further demonstrated that the GRU-LR-TCN model exhibits superior generalization across various datasets, proving to be more efficient and applicable in predicting urban PM2.5 concentration. This can contribute to enhancing air quality and safeguarding public health.

The most critical aspect of panorama generation is maintaining local semantic consistency. Objects may be projected from different depths in the captured image. When warping the image to a unified canvas, pixels at the semantic boundaries of the different views are significantly misaligned. We propose two lightweight strategies to address this challenge efficiently. First, the original image is segmented as superpixels rather than regular grids to preserve the structure of each cell. We propose effective cost functions to generate the warp matrix for each superpixel. The warp matrix varies progressively for smooth projection, which contributes to a more faithful reconstruction of object structures. Second, to deal with artifacts introduced by stitching, we use a seam line method tailored to superpixels. The algorithm takes into account the feature similarity of neighborhood superpixels, including color difference, structure and entropy. We also consider the semantic information to avoid semantic misalignment. The optimal solution constrained by the cost functions is obtained under a graph model. The resulting stitched images exhibit improved naturalness. Extensive testing on common panorama stitching datasets is performed on the algorithm. Experimental results show that the proposed algorithm effectively mitigates artifacts, preserves the completeness of semantics and produces panoramic images with a subjective quality that is superior to that of alternative methods.

With the gradual miniaturization of electronic devices, the thermal conductivity of electronic components is increasingly required. Epoxy (EP) resins are easy to process, exhibit excellent electrical insulation properties, and are light in weight and low in cost, making them the preferred material for thermal management applications. In order to endow EPs with better dielectric and thermal conductivity properties, bromo-oxygen-bismuth (BiOBr) prepared using the hydrothermal method was used as a filler to obtain BiOBr/EP composites, and the effect of BiOBr addition on the properties of the BiOBr/EP composites was also studied. The results showed that the addition of a small amount of BiOBr could greatly optimize the dielectric properties and thermal conductivity of EP resin, and when the content of BiOBr was 0.75 wt% and 1.00 wt%, the dielectric properties and thermal conductivity of the composite could reach the optimum, respectively. The high dielectric constant and excellent thermal conductivity of BiOBr/EP composites are mainly due to the good layered structure of BiOBr, which can provide good interfacial polarization and thermal conductivity.

Considering the large number of individuals who have already been infected and may have reinfection, the post-infection effects of COVID-19 are of great importance for clinical practice and predicting disease trends. However, our understanding of the potential long-term effects, particularly on immunity, after recovering from COVID-19 remains limited. The aim of this study was to investigate the abnormal immunological factors that contribute to the prolonged immunological effects of COVID-19. Two groups of patients were enrolled in the study, including 11 individuals with various autoimmune diseases (AIDs) and 16 patients diagnosed with systemic lupus erythematosus (SLE). Detailed clinical symptoms were closely monitored, and peripheral mononuclear cells were analyzed using flow cytometry. The clinical status was evaluated using the SLE Disease Activity Index (SLEDAI) and the Clinical Global Impressions (CGI) index. The proportions of follicular T helper cells (Tfh) exhibited significant increases in both cohorts (AID: p = 0.03; SLE: p = 0.0008). Conversely, the percentages of Foxp3+ and CD4+ regulatory T cells (Treg) were reduced in patients following COVID-19 infection (AID: p = 0.009, 0.05, resp.; SLE: p = 0.02, 0.0009, resp.). The percentages of Th2 and Th17 cells were significantly increased in SLE patients (p < 0.05). Exacerbated conditions were observed in SLE patients two months after infection (SLEDAI, p < 0.05). Our findings show that COVID-19 infection increases Tfh cells and decreases Treg cells in patients of AIDs, worsening pathogenetic immune status in post-recovery populations.

Urban traffic prediction is essential for intelligent transportation systems. However, traffic data often exhibit highly complex spatio-temporal correlations, posing challenges for accurate forecasting. Graph neural networks have demonstrated an outstanding ability in capturing spatial correlations and are now extensively applied to traffic prediction. However, many graph-based methods neglect the dynamic spatial features between road segments and the continuity of spatial features across adjacent time steps, leading to subpar predictive performance. This paper proposes a Dynamic Spatio-Temporal Graph Fusion Convolutional Network (DSTGFCN) to enhance the accuracy of traffic prediction. Specifically, we designed a dynamic graph fusion module without prior road spatial information, which extracts dynamic spatial information among roads from observed data. Subsequently, we fused the dynamic spatial features of the current time step and adjacent time steps to generate a dynamic graph for each time step. The graph convolutional gated recurrent network was employed to model the spatio-temporal correlations jointly. Additionally, residual connections were added to the model to enhance the ability to extract long-term temporal relationships. Finally, we conducted experiments on six publicly available traffic datasets, and the results demonstrated that DSTGFCN outperforms the baseline models with state-of-the-art predictive performance.

The current investigation focuses on the stability of the magnesium oxide-based cementitious system under the action of sulfate attack and the dry-wet cycle. The phase change in the magnesium oxide-based cementitious system was quantitatively analyzed by X-ray diffraction, combined with thermogravimetry/derivative thermogravimetry and scanning electron microscope, to explore its erosion behavior under an erosion environment. The results revealed that, in the fully reactive magnesium oxide-based cementitious system under the environment of high concentration sulfate erosion, there was only magnesium silicate hydrate gel formation and no other phase; however, the reaction process of the incomplete magnesium oxide-based cementitious system was delayed, but not inhibited, by the environment of high-concentration sulfate, and it tended to turn completely into a magnesium silicate hydrate gel. The magnesium silicate hydrate sample outperformed the cement sample, in terms of stability in a high-concentration sulfate erosion environment, but it tended to degrade considerably more rapidly, and to a greater extent, than Portland cement, in both dry and wet sulfate cycle environments.

Histone deacetylases tuin (HDT) is a plant-specific protein subfamily of histone deacetylation enzymes (HDAC) which has a variety of functions in plant development, hormone signaling and stress response. Although the HDT family’s genes have been studied in many plant species, they have not been characterized in Brassicaceae. In this study, 14, 8 and 10 HDT genes were identified in Brassica napus, Brassica rapa and Brassica oleracea, respectively. According to phylogenetic analysis, the HDTs were divided into four groups: HDT1(HD2A), HDT2(HD2B), HDT3(HD2C) and HDT4(HD2D). There was an expansion of HDT2 orthologous genes in Brassicaceae. Most of the HDT genes were intron-rich and conserved in gene structure, and they coded for proteins with a nucleoplasmin-like (NPL) domain. Expression analysis showed that B. napus, B. rapa, and B. oleracea HDT genes were expressed in different organs at different developmental stages, while different HDT subgroups were specifically expressed in specific organs and tissues. Interestingly, most of the Bna/Br/BoHDT2 members were expressed in flowers, buds and siliques, suggesting they have an important role in the development of reproductive organs in Brassicaceae. Expression of BnaHDT was induced by various hormones, such as ABA and ethylene treatment, and some subgroups of genes were responsive to heat treatment. The expression of most HDT members was strongly induced by cold stress and freezing stress after non-cold acclimation, while it was slightly induced after cold acclimation. In this study, the HDT gene family of Brassicaceae was analyzed for the first time, which helps in understanding the function of BnaHDT in regulating plant responses to abiotic stresses, especially freezing stresses.

The self-perception or self-experience of patients with depersonalization/derealization disorder (DPD) is altered, leading to a profound disruption in self-awareness. The main aim of the study is to explore the characteristics of subliminal self-face processing in DPD patients. To our knowledge, this is the first experimental study that has measured and evaluated subliminal self-processing in DPD. To better understand this, we examined the ability of patients with DPD and healthy controls (HC) to identify pictures of faces using an experimental paradigm of breaking continuous flash suppression. There were 23 DPD outpatients from Beijing Anding Hospital, Capital Medical University and 23 matched HC who participated in this experiment. The time needed for a face to break into awareness was taken as the measure of participants’ subliminal processing of that face. The results indicated that there were significant differences between the DPD patients and HC in subliminal reaction times to different faces. Under experimental conditions, the average reaction response of self-face recognition in the HC group was significantly faster than for a famous face. However, this difference was not observed in DPD patients, which means that DPD patients did not show the processing advantage of their own faces as did the HC. The results suggest a deficit in subliminal self-face processing in DPD.

Rapeseed stores lipids in the form of oil bodies. Oil bodies in the seeds of higher plants are surrounded by oleosins. Adjusting oleosin protein levels can prevent the fusion of oil bodies and maintain oil body size during seed development. However, oil contents are affected by many factors, and studies on the complex molecular regulatory mechanisms underlying the variations in seed oil contents of B. napus are limited. In this study, a total of 53 BnOLEO (B. napus oleosin) genes were identified in the genome of B. napus through a genome-wide analysis. The promoter sequences of oleosin genes consisted of various light-, hormone-, and stress-related cis-acting elements, along with transcription factor (TF) binding sites, for 25 TF families in 53 BnOLEO genes. The differentially expressed oleosin genes between two high- and two low-oil-content accessions were explored. BnOLEO3-C09, BnOLEO4-A02, BnOLEO4-A09, BnOLEO2-C04, BnOLEO1-C01, and BnOLEO7-A03 showed higher expressions in the high-oil-content accessions than in low-oil-content accessions, at 25, 35, and 45 days after pollination (DAP) in two different environments. A regional association analysis of 50 re-sequenced rapeseed accessions was used to further analyze these six BnOLEO genes, and it revealed that the nucleotide variations in the BnOLEO1-C01 and BnOLEO7-A03 gene regions were related to the phenotypic variations in seed oil content. Moreover, a co-expression network analysis revealed that the BnOLEO genes were directly linked to lipid/fatty acid metabolism, TF, lipid transport, and carbohydrate genes, thus forming a molecular network involved in seed oil accumulation. These favorable haplotypes can be utilized in molecular marker-assisted selection in order to further improve seed oil contents in rapeseed.

In recent years, hazardous wastewater treatment has been a complex and global problem. In this work, by considering the antimicrobial activity of Ag nanoparticles (AgNPs) and reduced graphene oxide (rGO), we constructed an antibacterial device (G-AgNP) with AgNPs conformably deposited onto a 3D scaffold of reduced graphene oxide in situ. The major limitation, which is difficult to recycle, of two-dimensional graphene-silver composite materials in previous studies is improved. Characterization techniques, SEM, TEM, XRD, and XPS, confirmed the synthesis of nanocomposites. Attributed to its larger specific area, more active sites, and synergistic enhancement, the G-AgNP device demonstrated the best bacterial removal capacity, with an antibacterial rate for both E. coli and S. aureus as high as 100% at quite low AgNP contents. The reported G-AgNP has potential application as a wearable sewage treatment device and for the protection of wearable sensors as a promising sterilizing candidate based on its high and stable antibacterial efficiency.

Resveratrol (RSV) is a natural extract that has been extensively studied for its significant anti-inflammatory and antioxidant effects, which are closely associated with a variety of injurious diseases and even cosmetic medicine. In this review, we have researched and summarized the role of resveratrol and its different forms of action in wound healing, exploring its role and mechanisms in promoting wound healing through different modes of action such as hydrogels, fibrous scaffolds and parallel ratio medical devices with their anti-inflammatory, antioxidant, antibacterial and anti-ageing properties and functions in various cells that may play a role in wound healing. This will provide a direction for further understanding of the mechanism of action of resveratrol in wound healing for future research.

Due to the increasing complexity of the entire satellite system and the deteriorating orbital environment, multiple independent single faults may occur simultaneously in the satellite power system. However, two stumbling blocks hinder the effective diagnosis of simultaneous-fault, namely, the difficulty of obtaining the simultaneous-fault data and the extremely complicated mapping of the simultaneous-fault modes to the sensor data. To tackle the challenges, a fault diagnosis strategy based on a novel rough set model is proposed. Specifically, a novel rough set model named FNζDTRS by introducing a concise loss function matrix and fuzzy neighborhood relationship is proposed to accurately mine and characterize the relationship between fault and data. Furthermore, an attribute rule-based fault matching strategy is designed without using simultaneous-fault data as training samples. The numerical experiments demonstrate the effectiveness of the FNζDTRS model, and the diagnosis experiments performed on a satellite power system illustrate the superiority of the proposed approach.

Introduction: Non-invasive brain stimulation seems to be beneficial for DPD patients. However, the sites used in previous studies were empirical. Exploring new stimulation locations via functional magnetic resonance imaging may improve the efficacy. Objectives: The objective was to find potential locations for non-invasive brain stimulation on the depersonalization-derealization disorder. Methods: We explored the potential brain surface regions from three pipelines: pipeline 1: activation likelihood estimation meta-analysis (five studies with 36 foci included); pipeline 2: functional connectivity analysis based on DPD-network (76 subjects included); and pipeline 3: functional connectivity analysis based on DPD regions of interest from the meta-analysis. Potential targets were the 10–20 system coordinates for brain surface regions. Results: We identified several potential brain surface regions, including the bilateral medial prefrontal cortex, dorsal lateral prefrontal cortex, superior parietal gyrus, superior temporal gyrus, and right ventrolateral prefrontal cortex as potential sites. Conclusion: Our findings of the potential stimulation targets might help clinicians optimize the application of non-invasive brain stimulation therapy in individuals with DPD.

Various ferulic acid (FA) dimers occurring in plant cell walls, such as 8-5-, 8-O-4-, 5-5-, and 8-8-coupled dimers, are effective antioxidants and potential antimicrobials. It is necessary to access these diferulates as reference compounds to validate those isolated from plants. 3,6-bis(4-hydroxy-3-methoxyphenyl)-tetrahydrofuro-[3,4-c]furan-1,4-dione, a 8-8-coupled FA dilactone generated from ferulic acid via radical coupling, has been used to synthesize 8-8-coupled FA dimers although few reports investigated the distribution of products and mechanisms involved in the transformation of FA dilactone. In this work, the FA dilactone, obtained from FA by a peroxidase-catalyzed radical coupling, was reacted under various base/acid conditions. Effects of reaction conditions and workup procedures on the distribution of products were investigated by GC-MS. The isolated products from such treatments of FA dilactone were characterized by NMR. New derivatives of FA dimer including 2-(4-hydroxy-3-methoxybenzylidene)-3-(hydroxyl-(4-hydroxy-3-methoxyphenyl)methyl)succinic acid and 2-(bis(4-hydroxy-3-methoxyphenyl)-methyl)-succinic acid were produced from NaOH treatment. Another novel 8-8-coupled cyclic FA dimer, diethyl 6-hydroxy-1-(4-hydroxy-3-methoxyphenyl)-7-methoxy-1,2-dihydronaphthalene-2,3-dicarboxylate was identified in products from FA dilactone treated by dry HCl in absolute ethanol. Mechanisms involved in such transformations were proposed.

The radionuclide cesium (Cs) was solidified using magnesium silicate hydrate (M−S−H) cement. The influence of Cs+ on the reaction of the M−S−H gel system was evaluated by measuring the compressive strength and microscopic properties of the solidified body. By testing the impact resistance, leaching resistance and freeze−thaw resistance of the solidified body, the immobilizing ability of Cs+ by the M−S−H cement was analyzed. Results indicate that Cs+ only slightly affects the reaction process of the M−S−H gel system, and only slows down the transformation rate of Mg(OH)2 into the M−S−H gel to a certain extent. The M−S−H cement exhibits superior performance in solidifying Cs+. Both the leaching rate and cumulative leach fraction at 42 d were considerably lower than the national requirements and better than the ordinary Portland cement-solidified body. The curing effect of the M−S−H cement on Cs+ is mainly physical encapsulation and chemisorption of hydration products.

Chinese Angelica is a significant medical plant due to the various therapeutic constituents in its root; whereas the aerial part is considered worthless and often discarded as agricultural waste. In this work, phytochemicals from the stem were first systematically analyzed by means of GC⁻MS after derivatization and HPLC⁻MS/MS in multiple reaction monitoring (MRM) mode. Phthalides, ferulic acid, and coniferyl ferulate were detected in the stem; although their content is relatively low in comparison with the root. Some specific compounds, such as p-hydroxybenzoic acid, vanillic acid, protocatechuic acid, caffeic acid, 4-hydroxyphenyl-1, 2-ethanediol, thymol-β-d-glucopyranoside, etc. and a significant amount of phytosterols (1.36 mg/g stem, mainly β-sitosterol) were detected in the stem. The extracted oil from the stem contained a considerable amount of phthalides (48.5 mg/g), β-sitosterol (56.21 mg/g), and stigmasterol (14.03 mg/g); no other bioactive compounds were found that could be potentially used as pharmaceuticals or additives to healthcare food.

Poly(lactic acid) (PLA)/lignin-containing cellulose nanofibrils (L-CNFs) composite films with different lignin contents were produced bythe solution casting method. The effect of the lignin content on the mechanical, thermal, and crystallinity properties, and PLA/LCNFs interfacial adhesion wereinvestigated by tensile tests, thermogravimetric analysis, differential scanning calorimetry (DSC), dynamic mechanical analysis, Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The tensile strength and modulus of the PLA/9-LCNFs (9 wt % lignin LCNFs) composites are 37% and 61% higher than those of pure PLA, respectively. The glass transition temperature (Tg) decreases from 61.2 for pure PLA to 52.6 °C for the PLA/14-LCNFs (14 wt % lignin LCNFs) composite, and the composites have higher thermal stability below 380 °C than pure PLA. The DSC results indicate that the LCNFs, containing different lignin contents, act as a nucleating agent to increase the degree of crystallinity of PLA. The effect of the LCNFs lignin content on the PLA/LCNFs compatibility/adhesion was confirmed by the FTIR, SEM, and Tg results. Increasing the LCNFs lignin content increases the storage modulus of the PLA/LCNFs composites to a maximum for the PLA/9-LCNFs composite. This study shows that the lignin content has a considerable effect on the strength and flexibility of PLA/LCNFs composites.

Magnesium silicate hydrate (MSH) gel was formed by reacting magnesium oxide (MgO) with silica fume (SF) in distilled water. The MSH was prepared using a MgO/SF molar ratio of 1.0 (40:60 weight ratio). Samples were analyzed during hydration process up to 300 days at room temperature. The MSH characterization has been carried out using a range of analytical techniques. Quantitative analysis was achieved using thermogravimetric analysis (TG/DTG) with a de-convolution technology. The structure of MSH gel was characterized using solid state nuclear magnetic resonance (29Si NMR) and Fourier transform infrared (FT-IR) spectroscopy. Transmission electron microscopy (TEM) was used to investigate MSH microstructure. Compared with natural magnesium silicate hydrate minerals, the structure of MSH gel is highly disordered and generates on the surface of particles, producing a shell structure with cavity. The molecular structure of MSH phase is layered. The results also show that the extent of polymerization of MSH gel is related to the solution pH during hydration.

A compound control scheme is proposed to achieve high control performance for a two-axis inertially stabilized platform (ISP) with multi-sensors applied to an unmanned helicopter (UH)-based airborne power line inspection (APLI) system. Compared with the traditional two closed-loop control scheme that is composed of a high-bandwidth rate loop and a lower bandwidth position loop, a new current loop inside rate loop is particularly designed to suppress the influences of voltage fluctuation from power supply and motor back electromotive force (BEMF) on control precision. In this way, the stabilization accuracy of the ISP is greatly improved. The rate loop, which is the middle one, is used to improve sensor’s stability precision through compensating for various disturbances. To ensure the pointing accuracy of the line of sight (LOS) of multi-sensors, the position loop is designed to be the outer one and acts as the main feedback path, by which the accurate pointing angular position is achieved. To validate the scheme, a series of experiments were carried out. The results show that the proposed compound control scheme can achieve reliable control precision and satisfy the requirements of real APLI tasks.

Underground coal gasification (UCG) is an efficient method for the conversion of deep coal resources into energy. The scope of this work is to model the subsidence of four gasification cavities with a size of 30 m × 30 m × 15 m, separated by 15 m wide pillars. Two scenarios of gasification sequence are modelled, one with the gasification of cavities 1 and 2 followed by 3 and 4, and the other one with the sequence of cavities 1 and 3, followed by 2 and 4. The results show that the final surface subsidence after gasification of four cavities is 9.8 mm and the gasification sequence has an impact only on the subsidence at the intermediate stage but has no impact on the final subsidence after all four cavities are formed, when only the elasticity regime is considered. Additionally, the maximum surface subsidence for the studied cavities of different sizes ranges from 0.016 mm to 7.14 mm, and the relationship between the subsidence and the cavity volume is approximately linear. Finally, a prediction model of surface subsidence deformation is built up using the elastic plate theory, and the formula of surface deformation at a random point is given. The maximum difference between measured and calculated deformation is 4.6%, demonstrating that the proposed method can be used to predict the ground subsidence induced by UCG.

Aspergillus flavus is notorious for contaminating food with its secondary metabolite—highly carcinogenic aflatoxins. In this study, we found that exogenous nitric oxide (NO) donor could influence aflatoxin production in A. flavus. Flavohemoglobins (FHbs) are vital functional units in maintaining nitric oxide (NO) homeostasis and are crucial for normal cell function. To investigate whether endogenous NO changes affect aflatoxin biosynthesis, two FHbs, FHbA and FHbB, were identified in this study. FHbA was confirmed as the main protein to maintain NO homeostasis, as its absence led to a significant increase in intracellular NO levels and heightened sensitivity to SNP stress. Dramatically, FHbA deletion retarded aflatoxin production. In addition, FHbA played important roles in mycelial growth, conidial germination, and sclerotial development, and response to oxidative stress and high-temperature stress. Although FHbB did not significantly impact the cellular NO level, it was also involved in sclerotial development, aflatoxin synthesis, and stress response. Our findings provide a new perspective for studying the regulatory mechanism of the development and secondary mechanism in A. flavus.