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To solve the problem of high-precision and fast initial alignment for the Strapdown Inertial Navigation System (SINS) under both dynamic and static conditions, the high-precision attitude measured by the celestial navigation system (CNS) is used as the reference information for the initial alignment. The alignment algorithm is derived in the Earth-centered inertial (ECI) frame. Compared with the alignment algorithm in the navigation frame, it is independent of position parameters and avoids the influence of the approximate error caused by the dynamic deflection angle. In addition, hull deformation is considered in attitude optimal estimation, which can realize initial the alignment of the SINS installed in various parts of the carrier. On this basis, the velocity measurement information is added to the alignment process, which further improves the accuracy and speed of the initial alignment under static conditions. The experimental results show that the algorithms proposed in this paper have better performance in alignment accuracy, speed, and stability. The attitude and velocity matching algorithm in the ECI frame can achieve alignment accuracy better than 0.6′. The attitude matching algorithm in the ECI frame has better robustness and can be used for both dynamic and static conditions, which can achieve alignment accuracy better than 1.3′. [ABSTRACT FROM AUTHOR]

Available evidence suggests the involvement of microRNAs (miRNAs) in the pathological process of several diseases. Nonetheless, molecular mechanism underlying biological effects of miRNAs such as pacemaker exosome-derived miR-127-5p in embryonic-like stem cells (ESCs) differentiation into pacemaker cell is yet to be clarified. Through real time quantitative polymerase chain reaction (qPCR) or western blotting (WB) techniques, levels of miRNAs, miR-127-5p, and NKx2.5 expressions were quantitatively measured. Cellular differentiation (CD) was probed with flow cytometric (FC) and WB techniques. Prediction of miR-127-5p association with NKx2.5 was studied through bioinformatics tools before verification with luciferase assays. Promotion of ESCs differentiation to pacemaker through miR-127-5p was measured with qPCR and WB techniques. Through the same assaying methods, up-regulation of pace-making genes (Shox2, HCN4, Cx45, Tbx3 and Tbx18) expression was observed in Nkx2.5 knockdown group. However, Nkx2.5 expression was down-regulated during differentiation of pacemaker-like cells into ESCs. Furthermore, techniques (such as qPCR, WB, immunofluorescent staining and FC) were employed to demonstrate that overexpressed miR-127-5p could suppress NKx2.5 expression. Through NKx2.5 targeting, ESCs could be differentiated into pacemaker-like cells with miR-127-5p possibly serving as a crucial positive regulator. On the account of our findings, further researches are needed to unearth the possible underlying mechanism and role of exosome-derived miRNAs in cell signaling. • MiR-127-5p could act as a significant positive regulator in ESCs differentiated into pacemaker-like cells by targeting NKx2.5. • NKx2.5 expression was down-regulated during differentiation of pacemaker-like cells into ESCs. • This work is the first to describe the role of miR-127-5p in the regulation of NKx2.5 expression in cardiac development. [ABSTRACT FROM AUTHOR]

Goose is important meat poultry and its growth and development has always been the focus of attention, but the regulation mechanisms of genes and gene network underlying growth and development of goose are still unclear. Three males of large-size Shitou goose and three males of small size Wuzong goose at 5 weeks of age were used for transcriptome analysis with deep sequencing. After slaughter, their pituitary gland was taken for RNA-seq. A total of 290 DEGs were identified by fold change ≥2 and false discovery rate (FDR) <0.05, where there were 148 upregulated genes and 142 downregulated genes in Shitou goose compared to Wuzong goose. Results also showed that the DEGs related to insulin signaling pathway could increase protein synthesis and fat production, and the interaction network of DEGs was mainly related to development, endocrine system, inflammatory diseases, tissue damage and abnormality. The DEGs involved in the growth and function of the pituitary organs may regulate the growth and development of the body by affecting the synthesis and secretion of pituitary hormones. The results of this study will help to understand the regulatory mechanism of goose growth and development. [ABSTRACT FROM AUTHOR]

Background: Cleft lip and/or palate (CL/P) are congenital cleft facial deformities that are abnormal developments caused by errors in the fusion process of the embryo's face. Surgery is an important treatment, but postoperative scars will still cause psychological shadows to patients. This study aimed to systematically evaluate the efficacy of Botulinum toxin type A (BTXA) in preventing and treating postoperative CL/P scars and improving scar quality. Methods: A systematic review was performed by searching PubMed, EMBASE, the Cochrane Library, and Web of Science for relevant trials. All relevant trials were performed before June 30, 2021. The data were entered into Revman 5.3 software, and a meta‐analysis was conducted by using the random‐effects model or fixed‐effects model. Results: Four randomized controlled trials involving 161 cases were included. Through quantitative analysis, BTXA showed significant differences in preventing and treating postoperative CL/P scars in terms of scar width (MD: −0.20; [95% CI, −0.30, –0.10], p < 0.0001) and the Visual Analog Scale (VAS) (MD: 1.30; [95% CI, 1.06, 1.55], p < 0.0001), although no significant difference was noted on the Vancouver Scar Scale (VSS) (MD: −0.75; [95% CI, −1.68, 0.19], p = 0.12) between the two groups. Conclusion: In preventing and treating postoperative CL/P scar hypertrophy, we found that BTXA injection can show better results. There was no statistically significant difference between the results after omitting Navarro's study or Chang's study because of the time of injection—before/during surgery or adult CL/P scars. [ABSTRACT FROM AUTHOR]

Ionospheric forecasts are critical for space-weather anomaly detection. Forecasting ionospheric total electron content (TEC) from the global navigation satellite system (GNSS) is of great significance to near-earth space environment monitoring. In this study, we propose a novel ionospheric TEC forecasting model based on deep learning, which consists of a convolutional neural network (CNN), long-short term memory (LSTM) neural network, and attention mechanism. The attention mechanism is added to the pooling layer and the fully connected layer to assign weights to improve the model. We use observation data from 24 GNSS stations from the Crustal Movement Observation Network of China (CMONOC) to model and forecast ionospheric TEC. We drive the model with six parameters of the TEC time series, Bz, Kp, Dst, and F10.7 indices and hour of day (HD). The new model is compared with the empirical model and the traditional neural network model. Experimental results show the CNN-LSTM-Attention neural network model performs well when compared to NeQuick, LSTM, and CNN-LSTM forecast models with a root mean square error (RMSE) and R2 of 1.87 TECU and 0.90, respectively. The accuracy and correlation of the prediction results remained stable in different months and under different geomagnetic conditions. [ABSTRACT FROM AUTHOR]

We present the ionospheric disturbance responses over low-latitude regions by using total electron content from Geostationary Earth Orbit (GEO) satellites of the BeiDou Navigation Satellite System (BDS), ionosonde data and Swarm satellite data, during the geomagnetic storm in August 2018. The results show that a prominent total electron content (TEC) enhancement over low-latitude regions is observed during the main phase of the storm. There is a persistent TEC increase lasting for about 1–2 days and a moderately positive disturbance response during the recovery phase on 27–28 August, which distinguishes from the general performance of ionospheric TEC in the previous storms. We also find that this phenomenon is a unique local-area disturbance of the ionosphere during the recovery phase of the storm. The enhanced f o F 2 and h m F 2 of the ionospheric F2 layer is observed by SANYA and LEARMONTH ionosonde stations during the recovery phase. The electron density from Swarm satellites shows a strong equatorial ionization anomaly (EIA) crest over the low-latitude area during the main phase of storm, which is simultaneous with the uplift of the ionospheric F2 layer from the SANYA ionosonde. Meanwhile, the thermosphere O/N2 ratio shows a local increase on 27–28 August over low-latitude regions. From the above results, this study suggests that the uplift of F layer height and the enhanced O/N2 ratio are possibly main factors causing the local-area positive disturbance responses during the recovery phase of the storm in August 2018. [ABSTRACT FROM AUTHOR]

• The MRT LB equations describing two-phase flows are modified to eliminate error terms. • Two wetting boundary schemes are developed for simulating contact-line motions of two-phase flows with large density ratios. • The requirement of virtual nodes in wetting boundary scheme is removed by a local scheme. • The developed wetting boundary schemes are validated by steady and dynamic simulations. • The contact angle hysteresis with large density and viscosity ratios can be successfully simulated. In this work, wetting boundary schemes in a modified phase-field lattice Boltzmann (LB) method are developed to simulate the contact-line motion and contact angle hysteresis of binary fluids with large density ratios. In the modified phase-field LB method, two multiple-relaxation-time (MRT) LB equations are utilized, one with a nondiagonal relaxation matrix used to solve the conserved Allen-Cahn (A-C) equation and the other with a modified discrete source term used to solve the incompressible Navier-Stokes (N-S) equations. Based on the idea of geometric formulation, two wetting boundary schemes corresponding to the modified phase-field LB model are proposed. In the first scheme, a layer of virtual nodes is utilized to realize the geometric formulation. The values of the order parameter at the virtual nodes are determined by the central difference method. In the second scheme, the geometric formulation is realized through a local scheme for the gradient terms of the order parameter where the nonequilibrium parts of the distribution function are utilized. Compared with the first wetting boundary scheme and some previous models, the second wetting boundary scheme does not require the virtual nodes and simplifies the numerical implementation. The developed two schemes are validated through a series of benchmark simulations, including droplet spreading on idea substrate, capillary intrusion and droplet shearing on nonideal substrate. It is found that satisfactory accuracy can be achieved by both two schemes, and the second scheme can obtain better stability while the first scheme shows better performance in simulating contact angle hysteresis. [ABSTRACT FROM AUTHOR]

Zoysiagrass (Zoysia japonica) is a popular turfgrass species and is widely used for sport turf and urban landscape. Zoysiagrass is often infected by Puccinia zoysiae, which causes a loss in turf quality. The physiological and molecular mechanisms of rust resistance are poorly understood in this species. In this study, the rust-resistant and susceptible lines of zoysiagrass were inoculated with P. zoysiae, and alterations of leaf cell structure, physiological indicators and transcriptomic response were investigated at the various stages of inoculation. After inoculation, the cell membranes, nucleus, mitochondria, and chloroplast were all impaired, followed by abnormal physiological metabolism. The damage occurred earlier and more severely in the susceptible line. Changes in electrolyte leakage and chlorophyll content varied with the genotype and the inoculation stages. The transcriptome analysis showed that plant hormones, MAPK signal transduction pathway, photosynthesis and energy generation pathways were significantly enriched in the early response, in both the resistant and susceptible lines. The results provided insights into the physiological and molecular mechanisms of rust disease resistance and would benefit the breeding of rust-resistant varieties in zoysiagrass and related turfgrass species. [ABSTRACT FROM AUTHOR]

Skeleton‐based action recognition is an inspired yet challenging task in computer vision. Recently, the latest graph convolutional network (GCN), which generalises well‐established convolutional neural networks to non‐Euclidean structures, is proven to be highly successful for action recognition from body skeleton data. However, the GCN architecture has not been fully studied. In this work, a Fisher vector (FV) encoding based GCN architecture (FV‐GCN) is proposed, which exceeds the limitations of existing GCN‐based methods by combining the GCN model with FV encoding. A channel‐wise spatial–temporal aggregation function to preserve spatial–temporal information in the whole action clip and integrate it into the FV‐GCN architecture is also presented. Since FV is different from the GCN structure, this hybrid architecture that incorporates the advantages of both algorithms can discover complementary information of feature representation effectively. On two challenging human action datasets, kinetics, and NTU‐RGBD, improved performance is demonstrated over the baseline method, and the FV‐GCN is better or comparable to some state‐of‐the‐art methods. [ABSTRACT FROM AUTHOR]

Accurate corrections for ionospheric total electron content (TEC) and early warning information are crucial for global navigation satellite system (GNSS) applications under the influence of space weather. In this study, we propose to use a new machine learning model—the Prophet model, to predict the global ionospheric TEC by establishing a short-term ionospheric prediction model. We use 15th-order spherical harmonic coefficients provided by the Center for Orbit Determination in Europe (CODE) as the training data set. Historical spherical harmonic coefficient data from 7 days, 15 days, and 30 days are used as the training set to model and predict 256 spherical harmonic coefficients. We use the predicted coefficients to generate a global ionospheric TEC forecast map based on the spherical harmonic function model and select a year with low solar activity (63.4 < F10.7 < 81.8) and a year with the high solar activity (79.5 < F10.7 < 255.0) to carry out a sliding 2-day forecast experiment. Meanwhile, we verify the model performance by comparing the forecasting results with the CODE forecast product (COPG) and final product (CODG). The results show that we obtain the best predictions by using 15 days of historical data as the training set. Compared with the results of CODE'S 1-Day (C1PG) and CODE'S 2-Day (C2PG). The number of days with RMSE better than COPG on the first and second day of the low-solar-activity year is 151 and 158 days, respectively. This statistic for high-solar-activity year is 183 days and 135 days. [ABSTRACT FROM AUTHOR]

Tobacco foreign material eliminating is an important step in the process of cigarette production. Through combing the research progress of tobacco foreign material eliminating technology in cigarette processing in China, it was pointed out that there were significant differences of tobacco foreign material in threshing and redrying, tobacco primary processing, rolling and wrapping process and waste cigarette treatment process. The tobacco foreign material eliminating methods in domestic cigarette processing included air purification removal, photoelectric impurity removal, laser impurity removal, etc. Different impurity removal methods had their advantages, disadvantages and applicable conditions. However, these impurity removal methods and technologies for tobacco were basically used alone, which made it difficult to meet the impurity removal efficiency while taking into account other index requirements. In the future, it should focus on in-depth research from three aspects: clarifying the characteristics and service conditions of various impurity removal methods, optimizing and upgrading the existing commonly used impurity removal methods, and carrying out research on multiple impurity removal and integrated composite impurity removal technologies. This would comprehensively improve the level of tobacco foreign material eliminating technology in the cigarette processing process, and then improve the cigarette product processing quality. [ABSTRACT FROM AUTHOR]

Sweetpotato (Ipomoea batatas [L.] Lam) is a widely cultivated food crop with generally good adaptability. However, drought stress can cause a significant decline in yield. To reveal the response mechanism of sweetpotato to drought stress, an integrated physiological, proteomic and metabolomic investigation was conducted in leaves of two sweetpotato varieties with differing responses to drought stress, drought-resistant Wanzishu56 (WZ56) and a more sensitive variety, Ningzishu2(NZ2). Physiological analysis showed that the variety with better drought tolerance had superior performance in water retention capacity and photosynthetic efficiency under drought stress. A total of 1140 proteins were identified within the two varieties. Among them, 192 differentially expressed proteins were detected under drought conditions, including 97 that were up-regulated. Functional analysis showed that these up-regulated proteins were primarily involved in photosynthesis, reactive oxygen species metabolism, organonitrogen compound metabolism, and precursor metabolite catabolism and energy generation. All differentially expressed proteins in WZ56 that were involved in photosynthetic and glutathione metabolic processes were up-regulated. Enzyme activity assays were carried out to validate the proteomics data. Moreover, 75 metabolites were found to have a higher expression level in WZ56 than NZ2 under drought stress. The higher concentration of carbohydrates, amino acids, flavonoids and organic acids found in drought-stressed leaves of WZ56 suggested that these metabolites may improve the drought resistance of sweetpotato. This study uncovered specific-proteins and metabolites associated with drought resistance, providing new insights into the molecular mechanisms of drought tolerance in sweetpotato. [ABSTRACT FROM AUTHOR]

Compressed ghost imaging method can effectively reduce the number of measurements required for ghost imaging reconstruction. The non-negative characteristics of measurement matrix in compressed ghost imaging method is inconsistent with the requirements of the measurement matrix in traditional compressed sensing theory, leading to low quality reconstruction. Aiming at the point, this paper proposes a singular value decomposition compressed ghost imaging method to improve the reconstruction quality of ghost imaging. First, the singular value decomposition is performed on the measurement matrix, and then the optimized measurement matrix and measurements are obtained, finally the reconstruction of the image is completed by the reconstruction algorithm. Numerical simulation experiments verify the superiority of our proposed singular value decomposition compressed ghost imaging method. [ABSTRACT FROM AUTHOR]

By utilising the mixed-ligand approach, a novel coordination polymer based on Zn(II) ions as nodes have been synthesised by the Zn(NO3)2 · 6H2O reacting with 1,4-H2NDC in the presence of a second N-donor ligand L, and its chemical formula is {[Zn(L)1.5(1,4-NDC)]·H2O}n (1, 1,4-H2NDC = 1,4-naphthalenedicarboxylic acid and L = N,N′-di(4-pyridyl)suberoamide). The as-synthesised complex 1 reveals outstanding water stability and it could be utilised as a platform of the multi-responsive recyclable luminescent sensor for the Al3+ and Fe3+ in water. The compound was synthesised in this research for the tuberculosis treatment. The biological function of the compound was assessed, and its detailed mechanism was explored. The Mycobacterium bacterial numbers in lung tissue was determined with spread plate method. In addition to this, the real-time reverse transcription-polymerase chain reaction (RT-PCR) method was conducted to determine the inhibition of compound against the ropA expression in Mycobacterium. [ABSTRACT FROM AUTHOR]

Smart energy plays an important role in alleviating energy poverty in China in the context of the new technological revolution and industrial change. This paper uses China's smart pilot policy as a quasi-natural experiment, employing China's provincial panel data from 2011 to 2022, measuring energy poverty indices based on a projection pursuit evaluation model, and conducting a quasi-natural experiment using a synthetic control method to assess the effect of smart energy on energy poverty and specific mechanisms of action. The study found that smart energy has a specific and significant impact on energy poverty, but the effect differs in different regions depending on the construction cycle and energy endowment. In the mechanism test, smart energy significantly alleviates energy poverty through the mechanisms of improving energy supply capacity, improving energy payment capacity, and improving energy cleanliness. The results of the study provide empirical references for regional solutions to energy poverty and the planning of smart energy construction. [ABSTRACT FROM AUTHOR]

Pseudo-halide substitution is an effective approach to enhance the performance and stability of perovskite optoelectronic devices. However, the role of pseudo-halide ions played in the perovskite light-emitting diodes (PeLEDs) is still rarely investigated. Herein, we have synthesized the organic salt PEABF 4 (PEA = phenylethylamine) as a pseudo halide substitute for surface halides in PEABr and fabricate quasi two-dimensional (quasi-2D) PeLEDs. The incorporation of BF 4 − anion improves the photoluminescence (PL) intensity and lifetime by taking advantage of improved crystallinity and enlarged grain size. The BF 4 − substituted PeLEDs shows great improvement of performance to the control devices. The optimized device with structure of indium tin oxide-coated glass (ITO(glass))/poly(3,4-ethylenedioxythiophene):poly(styrene-sulfonate)(PEDOT:PSS)/perovskite/4,7-Diphenyl-1,10-phenanthroline (Bphen)/Ag produces a maximum luminance at 44850 cd/m2, and an efficiency of 11.5 cd/A, respectively. Through further investigation by optical and electrical characterization, we find the substitution of BF 4 − anion has merits on the enhancement of exciton binding energy and suppression of non-radiative trap-assisted recombination on the surface. These results provide better understanding of pseudo-halide's benefits in perovskite light-emitting devices. By using the new designed organic salt PEABF 4 (PEA = phenylethylamine), we investigate the substitution effects of BF 4 − ion on quasi-2D perovskite light-emitting diode. Their influences on defect passivation and exciton binding energy are discussed in this work. [Display omitted] • We successful synthesis the large cation ligand PEABF 4 , and use solution method to partial substituted the Br− anion in qusi-2D perovskite. • The suitable substitution ratio of BF 4 − anion could improve the crystallinity and increase the exciton binding energy of the perovskite grains. • The surface defect induced non-radiative recombination has also suppressed by introduction of BF 4 − anions into the quasi-2D perovskites. • The best ratio of substituted PEABr with PEABF 4 to make highly efficient PeLED, which gives luminance at 44850 cd/m2 with a maximum current efficiency 11.5 cd/A in our testament. [ABSTRACT FROM AUTHOR]

[Display omitted] • CCL17/CCR4 axis has not been reported in CDR. • CCR4 on Th2 cells is activated by CCL17 during CDR, and CCL17/CCR4 axis-mediated CDR via the ERK/STAT3 pathway. • The results provide a new strategy for creating anti-CDR drugs that targeting CCL17/CCR4 axis. Cutaneous drug reactions (CDRs) are common drug-induced allergic reactions that cause severe consequences in HIV/AIDS patients. The CCL17/CCR4 axis is involved in the immune mechanism of allergic diseases, but its role in the CDRs has not been determined. Here, we aimed to determine the role of the CCL17/CCR4 axis and the underlying mechanism involved in CDRs. In this study, the serum cytokine levels in patients with CDR and healthy controls were measured. The CCL17-triggered allergic profile was screened via a PCR array. Apoptosis of keratinocytes cocultured with CCL17-stimulated Th2 cells was analyzed by flow cytometry. An NVP-induced rat CDR model was established, and dynamic inflammatory factor levels and Th2 cells in the peripheral blood of the rats were measured. Rat skin lesions and signaling pathways in Th2 cells were also analyzed. We showed that the serum CCL17 level was significantly upregulated in CDR patients (P = 0.0077), and the Th2 cell subgroup was also significantly elevated in the CDR rats. The CCL17/CCR4 axis induces Th2 cells to release IL-4 and IL-13 via the ERK/STAT3 pathway. The CCR4 antagonist compound 47 can alleviate rash symptoms resulting from NVP-induced drug eruption, Th2 cell subgroup, IL-4, and IL-13 and inhibit keratinocyte apoptosis. Taken together, these findings indicate that the CCL17/CCR4 axis mediates CDR via the ERK/STAT3 pathway in Th2 cells and type 2 cytokine-induced keratinocyte apoptosis. [ABSTRACT FROM AUTHOR]

The traditional error model for strapdown inertial navigation system (SINS)/Doppler velocity log (DVL) integrated navigation is establish for special orthogonal group Kalman filter (SOKF), which is only suitable for the case of small misalignment angle. In this article, the Lie group based nonlinear error model is investigated for SINS/DVL in inertial frame, this model is no longer limited by the size of misalignment angle like traditional SOKF, so initial alignment and integrated navigation could be combined into one stage, and the navigation solution is more accurate and faster. First, a thorough theoretical analysis is presented for state transformation extended Kalman filter (STEKF) modeling in both special orthogonal group (SO(3)) and special euclidean group (SE(3)). Then, the nonlinear error models (both left and right invariant error models) in inertial frame are derived in extended special euclidean group (SE 2 (3)). On this basis, SINS/DVL is verified as a type of left invariant observation system which is more applicable to the left invariant error model. Finally, both simulation and field test for SINS/DVL are conducted to evaluate the actual performance of the investigated methods. The results show that the proposed left invariant error model in inertial frame performs better for SINS/DVL than right invariant error model, and it also has more excellent performance than other existing integrated navigation methods, such as SOKF and STEKF. Especially compared with the current advanced invariant error model defined in earth frame, the model we investigated is more concise, efficient and accurate. • A thorough theoretical analysis is presented for STEKF modeling in both special orthogonal group (SO(3)) and special euclidean group (SE(3)). The inherent defects of STEKF are discussed from linearized modeling and Lie group theory. • A new navigation state is defined in inertial frame extended special euclidean group (SE 2 (3)), which is proved to satisfy the group affine property. The left and right invariant error models corresponding to the aforementioned state are derived for SINS/DVL integrated navigation. SINS/DVL is discussed as a type of left invariant observation system based on the analysis of transition matrices. • The simulation and field test are conducted to evaluate the actual performance of the investigated nonlinear error models. The results are explicitly presented with thorough discussion, which are consistent with theoretical analysis. The proposed left invariant error model in inertial frame outperform the common models (such as SOKF and STEKF) on the state estimation. Especially compared with the current advanced invariant error model defined in earth frame, the model we investigated is more concise, efficient, and accurate. [ABSTRACT FROM AUTHOR]

• Self-assembled technology controls the thickness of MXene films. • Exploring the influence of thickness on the optoelectronic properties of MXene. • The discovery of transition states in MXene photoresponse. Due to its tunable interlayer chemistry, MXene shows great potential in various sensor applications, but the optoelectronic properties of MXene are greatly hindered by the slow photoresponsivity of the intercalation chemistry. The main challenge to MXene in photoelectric sensor applications arises from its composite resistive properties. This paper analyzes the photoelectric responses separately by constructing singlelayer and multilayer structures. Under light, the resistance of a monolayer of MXene increases to 100.1% and recovers in 1 s. When the number of layers increases, the resistance of MXene quickly drops to 99.6% under light and recovers slowly within 15 s. In summary, this study reveals how MXene's layered structure affects its photoresponsivity, offering insights for advancing MXene-based optoelectronic sensors. [ABSTRACT FROM AUTHOR]

[Display omitted] • Electrons are redistributed as Mg&MoP/CN loaded at a reverse interfacial position. • Interfacial MoP behaves as the electron collecting sites to improve the activity. • Exterior Mg functions as the catalyzing sites to tackle the selectivity challenge. • Selective and efficient CH 4 evolution are achieved by a Z-scheme reaction pathway. Constructing photocatalysts with dual-function active sites can coordinate the photogenerated electrons transfer and the adsorption energy of key intermediates, thereby converting CO 2 into valuable methane with high efficiency. However, the role that the interfacial position of functional catalysts played in determining the activity and selectivity of CO 2 photoreduction remains unclear. Herein, we regulated the action interface and synergistic effect of magnesium nitrate hydroxide and molybdenum phosphide (Mg & MoP) to modify polymeric carbon nitride (PCN), and found the function-oriented Mg-MoP/PCN exhibits superior performance for catalyzing CO 2 -to-CH 4 in pure water, with a rate of 24.45 μmol h−1 g−1 and 95.3 % selectivity. Theoretical and experimental studies reveal that interfacial layer of MoP promotes the evolutionary activity by facilitating the electron transfer while exterior layer of Mg functions as the catalyzing sites to tackle the selectivity challenge by promoting CO 2 adsorption and CO* stabilization. The synergistic interaction of function-oriented Mg&MoP realizes selective CH 4 evolution with high efficiency via a Z-scheme pathway. The interfacial position of bifunctional catalysts is vital for regulating CO 2 photoreduction activity and product selectivity. [ABSTRACT FROM AUTHOR]

The effect of composite additives on the pyrolysis characteristics of microalgae (Dunaliella salina) was studied by microwave-assisted pyrolysis system. The composite additive was blended by SiC and CaO. The three cases, i.e. different kinds of additives (single additive and composite additive), different addition amounts (5%, 10%, 15%, 20%, and 25%) of composite additives, and different blending ratios (SiC/CaO = 0:10, 3:7, 5:5, and 7:3) were investigated. The results show that when the composite additive was 15% and the blending ratio of SiC/CaO = 5:5, the average weight loss rate (Rv) and weight loss rate for the second peak (Rp2) were maximum, while the final time detected as weight stabilization (tf) and the time corresponding to second peak (tp2) were minimum. Besides, SiC and CaO had a synergistic effect in this experimental condition. When the additive was 7.5% SiC, the total weight loss (Mt) and the weight loss rate for the first peak (Rp1) were maximum and the time corresponding to first peak (tp1) was minimum. The minimum Rv and Mt occurred at 7.5% CaO group. [ABSTRACT FROM AUTHOR]

Ovarian cancer is the fifth leading cause of cancer-related mortality in women worldwide. Despite the development of technologies over decades to improve the diagnosis and treatment of patients with ovarian cancer, the survival rate remains dismal, mainly because most patients are diagnosed at a late stage. Traditional treatment methods and biomarkers such as cancer antigen-125 as a cancer screening tool lack specificity and cannot offer personalized combinatorial therapy schemes. Circulating tumor DNA (ctDNA) is a promising biomarker for ovarian cancer and can be detected using a noninvasive liquid biopsy. A wide variety of ctDNA applications are being elucidated in multiple studies for tracking ovarian carcinoma during diagnostic and prognostic evaluations of patients and are being integrated into clinical trials to evaluate the disease. Furthermore, ctDNA analysis may be used in combination with multiple "omic" techniques to analyze proteins, epigenetics, RNA, nucleosomes, exosomes, and associated immune markers to promote early detection. However, several technical and biological hurdles impede the application of ctDNA analysis. Certain intrinsic features of ctDNA that may enhance its utility as a biomarker are problematic for its detection, including ctDNA lengths, copy number variations, and methylation. Before the development of ctDNA assays for integration in the clinic, such issues are required to be resolved since these assays have substantial potential as a test for cancer screening. This review focuses on studies concerning the potential clinical applications of ctDNA in ovarian cancer diagnosis and discusses our perspective on the clinical research aimed to treat this daunting form of cancer. [ABSTRACT FROM AUTHOR]

Aiming at the operation and maintenance requirements of the fault location of high-temperature superconducting cables, a fault location method of high-temperature superconducting cables based on the improved time-frequency domain reflection method and EEMD noise reduction is proposed. Considering the cross-term interference problem in the traditional time-frequency domain reflection method, this paper introduces the affine transformation to project the time-frequency distribution of the self-term and the cross term and further highlights the characteristic differences between the two through coordinate transformation, and the particle swarm algorithm is employed to solve the optimal stagger angle of the affine transformation. The unscented particle filter is adopted to separate the cross term, and EEMD noise reduction is introduced to solve the signal noise problem. Finally, two software programs, PSCAD and MATLAB, are employed for joint simulation to build a model of high-temperature superconducting cable. The simulation example shows that the proposed method in this paper can eliminate the cross-term interference of the traditional time-frequency domain reflection method, effectively locate the fault of the high-temperature superconducting cable, and improve the positioning accuracy. [ABSTRACT FROM AUTHOR]

In this paper, based on two lattice models (D3Q19 and D3Q27), two three-dimensional weighted-orthogonal multiple-relaxation-time pseudopotential lattice Boltzmann (WMRT-PLB) models with tunable thermodynamic consistency and surface tension are developed in which the high-order terms of the equilibrium density distribution function and discrete forcing term in moment space are eliminated, and thus, the implementation of the collision process is simplified. The Chapman–Enskog analysis shows that the WMRT-PLB models can correctly recover the macroscopic Navier–Stokes equations in the low Mach number limit. Then, six classical multiphase flows benchmark cases are performed to validate the performance of the proposed model. The numerical results of the first three cases indicate that the developed WMRT-PLB models effectively weaken the non-physical coupling between kinetic viscosity and density, enhance the numerical stability because of the low spurious velocity, improve the computational efficiency by about 25% because of the simplification of the collision process, and increase the numerical accuracy in the dynamic problems. Meanwhile, the numerical results of the last three cases with the density ratio of 857.7 and the kinetic viscosity ratio of 1/15 agree well with the analytical solutions and experimental results reported in the literature. Note that it is also found that the simulation of droplet bouncing is still stable even when the Reynolds number is more than 3000, which shows the good numerical stability of the proposed model. It has the potential to be applied to the simulation of the complex multiphase flows with large density ratio and large Reynolds number. [ABSTRACT FROM AUTHOR]

The stability of the reservoir bank landslide is affected by a variety of external factors, and the fluctuation of reservoir water level is one of the important influencing factors. The Erdaohe landslide is a typically colluvial landslide in the Three Gorges Reservoir area with periodic reservoir water level fluctuations. According to landslide displacement data, the displacement of the Erdaohe landslide exhibits the significantly stepwise feature. Its failure mechanism was analyzed using strength reduction method by the FLAC3D package in the case of reservoir water level changes. The results indicate that the hydrodynamic pressure has an important impact on the initialization of the landslide failure. When reservoir water level rises rapidly or maintains constant at the lower level, the landslide stability would be higher. When the reservoir water level decreases rapidly or maintains constant at the higher level, the landslide stability will be smaller. When the reservoir water level was in the lowest elevation, the factor of safety (FS) reached the minimum value of 1.11. Findings in this paper can provide guidelines for the risk assessment of colluvial landslides. [ABSTRACT FROM AUTHOR]

The large-scale rectangular pipe jacking technology has attracted more and more attention in the construction of urban underground pipe galleries, especially the problem of prediction and control of the surface settlement. Taking the pipe gallery project of Chengbei Road in Suzhou as an example, the settlement values of three groups of monitoring sections under the conditions of natural settlement and synchronous grouting are monitored, and the measured settlement values are compared with Peck formula and random medium theory. The results show that the Peck formula is more accurate in predicting the natural settlement within 1.5 times the pipe jacking width, while the stochastic medium theory is more accurate in predicting the settlement beyond the width. By comparing the field test and theory, the suggestions on the prediction of ground settlement of rectangular pipe jacking of large scale are put forward. The results of this study provide a basis for subsequent related research work and engineering applications. [ABSTRACT FROM AUTHOR]

The total electron content (TEC) is a critical parameter of ionosphere morphology. Precise modeling and prediction of the TEC time series can significantly aid the functioning of the Global Navigation Satellite System (GNSS), satellite as well as shortwave communications. An improved Transformer-based TEC prediction model (ITM) is proposed in this study, in response to the high noise characteristics of the temporal data for TEC in the global ionosphere. The ITM model forecasts the global ionospheric TEC data provided by the Center for Orbit Determination in Europe (CODE) for the year 2018. Experimental results indicate that the model obtains an annual average root mean square error of 1.4 TECU, which represents a 6.67 % advancement over the daily forecast product C1PG published by the CODE center. The model also attains an annual average mean absolute error of 1 TECU, representing a 9.09 % improvement over the accuracy of C1PG. The annual average correlation coefficient is 0.98, which indicates a 0.62 % upgrade in C1PG's accuracy. Additionally, the model exhibits a maximum increase of 23.53 % in monthly average root mean square error over C1PG, a maximum increase of 25 % in monthly average mean absolute error, and a maximum increase of 1.55 % in monthly average correlation coefficient. During the more geomagnetically active phases of 2018, the ITM model's forecast accuracy exhibited an overall improvement of 5 % in RMSE, 7.14 % in MAE, and 0.83 % in correlation coefficient R compared to the C1PG product. [ABSTRACT FROM AUTHOR]

Identifying critical nodes in complex networks has gained increasing attention in recent years. However, how to design an algorithm that has low computational complexity but can accurately identify important network nodes is still a challenge. Considering the role of structural holes in shaping communication channels, this paper presents an effective method based on local characteristics to identify critical nodes that play important roles in maintaining network connectivity. Our method considers the connections of a node as well as the connectivity of the neighborhood of the node. Through numerical simulations on various real-world networks, we have demonstrated that the proposed approach outperforms some other well-known heuristic algorithms in identifying vital nodes and leads to faster network collapse in target destruction. [ABSTRACT FROM AUTHOR]

[Display omitted] • Bulk nanostructured ceramic was prepared by embedding CNTs in YSZ-MgO nanocrystals. • He ion irradiation response of CNT-reinforced ceramic at 500 °C was studied. • Management of defects/He atoms via constructed ternary nanostructures was realized. • High ability in keeping microstructure stability and resisting radiation hardening. Developing long-lifetime bulk-form ceramic-based materials with high irradiation resistance is crucial for advanced nuclear systems. Here, we incorporated carbon nanotubes (CNTs) into yttria-stabilized zirconia (YSZ) and magnesia (MgO) nanocrystals to fabricate bulk YSZ-MgO-CNT nanocomposites with abundant ternary nanostructures by spark plasma sintering. To understand the role of tailored ternary nanostructure on irradiation, we investigated the microstructure and mechanical properties evolutions of the YSZ-MgO-CNT nanocomposites irradiated by multi-energy He+ ions at high temperature to different fluences. Compared with the single-phase YSZ and ultrafine-grained YSZ-MgO composites, the YSZ-MgO-CNT nanocomposites possessed higher ability to manage irradiation-induced He bubbles/defects via the defect-interface interactions of proposed "loading-unloading" and "loading-transporting-unloading" mechanisms for controlling the dynamical behaviors of He atoms/defects in the CNT-doped ternary nanostructures, thereby presenting more stable microstructure and better performance in resisting irradiation hardening. This work provides insight into the design of advanced inert matrix nuclear fuel and new nuclear waste management materials. [ABSTRACT FROM AUTHOR]

Our previous studies showed that S100A9 was overexpressed in glioma and promoted tumor growth. However, S100A9 can also be secreted by tumor cells to regulate the tumor microenvironment (TME). In this study, we aimed to explore the functions of glioma derived-S100A9 in microglial M2 polarization, resulting in inhibition of CD8+ T lymphocytes and promotion of immunosuppression. We first showed that glioma exhibited higher expression and secretion of S100A9 than astrocytes. After knocking down S100A9 in two glioma cell lines, the secretion of S100A9 was repressed. Then, the medium was collected and considered as conditioned medium (CM), which was incubated with microglia. We found that glioma-derived S100A9 drove microglial M2 polarization and increased TGFβ1 secretion. These molecular mechanisms were related to the interaction of S100A9 with αvβ3 integrin and the subsequent activation of AKT1 in microglia. Furthermore, we demonstrated that S100A9-induced M2 microglia negatively affected cell viability, IL-2 and IFN-γ secretion, together with increased early apoptosis in CD8+T lymphocytes via TGFβ1. Additionally, glioma cells were implanted into mouse brains, and we confirmed that S100A9 stimulated microglial M2 polarization, enhanced TGFβ1 levels and repressed CD8+ T lymphocytes in orthotopically transplanted tumors. In human glioma samples, S100A9 expression was positively associated with CD206 expression, but negatively correlated with CD8+T lymphocyte accumulation in the TME. Our data indicated that glioma-derived S100A9 has a promising ability to manipulate non-malignant cells and promote immune evasion in the TME, providing valuable insight into the mechanism by which S100A9 participates in the progression of glioma. • Glioma-derived S100A9 polarizes microglia toward M2 via αvβ3 integrin/AKT1. • M2 microglia secretes TGFβ1 to inhibit immunocompetence of CD8+T lymphocyte. • Crosstalk among glioma, M2 microglia and CD8+T lymphocytes for immunosuppression. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a complex neurodegenerative disease. Despite several decades of research, the development of effective treatments and responses for Alzheimer's disease remains elusive. The utilization of polysaccharides for Alzheimer's disease became more popular due to their beneficial characteristics, notably their multi-target activity and low toxicity. This review mainly focuses on the researches of recent 5 years in the regulation of AD by naturally derived polysaccharides, systematically lists the possible intervention pathways of polysaccharides from different mechanisms, and explores the structure-activity relationship between polysaccharide structural activities, so as to provide references for the intervention and treatment of AD by polysaccharides. [ABSTRACT FROM AUTHOR]

Nano-additives reinforced Inconel 625 alloys were manufactured by laser powder bed fusion (LPBF), consisting of titanium carbide nanoparticles (TiC) and/or nickel-coated multi-walled carbon nanotubes ((Ni)MWCNT). Microstructural characterization revealed that respective structures of TiC and (Ni)MWCNT nano-additives were retained, while the (Ni)MWCNT experienced fragmentation into shorter segments after ball milling and LPBF. Compared to LPBF In625, the reinforced samples showed enhanced ultimate tensile strength, yield strength, and hardness, despite decreased elongation to failure. Nano-additives exert varying effects on the properties of the alloys. Individually, (Ni)MWCNT strengthens the alloy, and TiC plays an insignificant role; collectively, they strengthen the material to a higher degree, via refining the cell size and probably increasing dislocation density. • Two nano-additives, (Ni)MWCNT and TiC, were incorporated into In625 alloy. • The nano-additives were found to be along the boundaries of cellular structures. • Individually, (Ni)MWCNT strengthens the alloy, and TiC plays an insignificant role. • Collectively, they strengthen the material to a higher degree, via refining the cell size. [ABSTRACT FROM AUTHOR]

In order to investigate the effects of different crosslinking agents on physicochemical properties and adsorption properties of porous starch. Native corn starch was hydrolyzed by maltase and crosslinked with different crosslinking agents. Sodium trimetaphosphate crosslinked porous starch (STMP-MPS), malic acid cross-linked porous starch (MA-MPS) and citric acid cross-linked porous starch (CA-MPS) were prepared. After crosslinking, MA-MPS and CA-MPS showed a new C O stretching absorption peak at 1738 cm−1, and the crosslinking degree was much higher than that of STMP-MPS. The surface area of MA-MPS was 36 % higher than that of STMP-MPS. Compared with the average pore size of 12.43 nm of STMP-MPS, CA-MPS (14.02 nm) and MA-MPS (14.79 nm) were increased more significantly. The degradation temperature of MA-MPS and CA-MPS was increased by the introduction of ester bond, which indicates that the organic acid cross-linking strengthens the starch granules and hence more energy is required for disruption. Compared with STMP-MPS, the water absorption of MA-MPS and CA-MPS increased by 64 % and 32 %, respectively. Furthermore, the adsorption capacity of MA-MPS to essential oil was the strongest, about 4 times that of STMP-MPS. Overall, it is feasible to modify porous starch by crosslinking reaction to improve its heat resistance and adsorption properties. • Porous starch was crosslinked by citric acid, malic acid and sodium trimetaphosphate. • Cross-linked porous starches had an obvious increment in surface area and pore size. • Malic acid cross-linked porous starch had the best thermal stability. • The adsorption capacity of MA-MPS for water, pigment, essential oil and soybean oil is the highest. [ABSTRACT FROM AUTHOR]

In order to investigate the effects of different crosslinking agents on physicochemical properties and adsorption properties of porous starch. Native corn starch was hydrolyzed by maltase and crosslinked with different crosslinking agents. Sodium trimetaphosphate crosslinked porous starch (STMP-MPS), malic acid cross-linked porous starch (MA-MPS) and citric acid cross-linked porous starch (CA-MPS) were prepared. After crosslinking, MA-MPS and CA-MPS showed a new C O stretching absorption peak at 1738 cm−1, and the crosslinking degree was much higher than that of STMP-MPS. The surface area of MA-MPS was 36 % higher than that of STMP-MPS. Compared with the average pore size of 12.43 nm of STMP-MPS, CA-MPS (14.02 nm) and MA-MPS (14.79 nm) were increased more significantly. The degradation temperature of MA-MPS and CA-MPS was increased by the introduction of ester bond, which indicates that the organic acid cross-linking strengthens the starch granules and hence more energy is required for disruption. Compared with STMP-MPS, the water absorption of MA-MPS and CA-MPS increased by 64 % and 32 %, respectively. Furthermore, the adsorption capacity of MA-MPS to essential oil was the strongest, about 4 times that of STMP-MPS. Overall, it is feasible to modify porous starch by crosslinking reaction to improve its heat resistance and adsorption properties. • Porous starch was crosslinked by citric acid, malic acid and sodium trimetaphosphate. • Cross-linked porous starches had an obvious increment in surface area and pore size. • Malic acid cross-linked porous starch had the best thermal stability. • The adsorption capacity of MA-MPS for water, pigment, essential oil and soybean oil is the highest. [ABSTRACT FROM AUTHOR]

• This study has positive significance for CO 2 geological storage, and the later the breakthrough time, the longer the CO 2 adsorption time. • The experimental study of CO 2 injection for CH 4 displacement in different coal ranks was studied. • Combined with the volume fraction of produced gas, permeability and flow rate, the effect of gas injection displacement is analyzed and discussed. • The gas production of CH 4 increases with the increase of coal rank. The dominant mechanism of CH 4 gas production was different before and after CO 2 breakthrough. Coal seam gas extraction is an important part of green mining. At the same time gas injection for enhanced coalbed methane recovery (ECBM) has been proposed as an environmentally friendly, low-carbon and effective technology to increase methane production. To study the influence of coal rank on carbon dioxide (CO 2)-ECBM efficiency, lignite, bituminous coal, and anthracite were tested using the Gas Flow and Displacement Testing Apparatus (GFDTA). Data indicated that: (1) in lignite and anthracite, outflow CO 2 and CH 4 fractions changed at higher rates as compared with bituminous coal. At the end of the experiments, lignite and anthracite displayed CH 4 outflow fractions of 0.19% and 7.73%, respectively; (2) at the initial stage of the experiments, permeability rapidly decreased. Later, a fast increase was followed by a stable phase. In lignite and anthracite, the increment in permeability during the rapid increase stage was significantly larger than that of bituminous coal. (3) The CH 4 flow rate of the three coal ranks showed a decreasing trend. Before the breakthrough, CH 4 flow rate decreased rapidly and slowed down. After the breakthrough, CO 2 flow displayed a linear increasing trend and later reached stability. (4) In general, CH 4 production increased with the increase in coal rank. The variation of CH 4 production is manifested in two phases with different dominant factors. In the first stage, CH 4 production was mainly affected by permeability, and followed the order lignite > anthracite > bituminous. In the second stage, CH 4 production was mainly controlled by the displacement effect, following the order anthracite > bituminous coal > lignite. [ABSTRACT FROM AUTHOR]

Recently, many weakly supervised video anomaly detection (WS-VAD) methods focus on generating reasonable pseudo-labels for frames by using video-level annotations. To achieve this goal, some existing label-noise cleaning techniques and pseudo-label generators are used by them, but their performance is limited. The main reason is that the useful prior knowledge, i.e., the graduality of anomaly events, is ignored. Here, we propose a Self-Training Framework, which assumes flexible soft boundaries between abnormal and normal clips. The framework consists of: (1) A prior knowledge guided pseudo-label generator that incorporates prior knowledge of video segment distributions into the MIL framework to generate high-confidence pseudo labels; (2) An improved self-guided attention encoder is developed to capture multiscale long-term spatiotemporal features, where dependencies among anomaly frames are preserved. Moreover, a pseudo-label based self-training scheme is adopted to supervise the encoder. Experimental results verify the superiority of our method over baseline approaches. • By taking the graduality of the anomaly events into account to generate pseudo labels. • Using one-dimensional median filter to constrain the anomaly scores of negative bags. • The network focuses on the most abnormal parts of the frame by the attention module. • The self-guided branch can capture the dependencies between video frames. [ABSTRACT FROM AUTHOR]

Mechanism of SO 2 effect on Cu 1-x Fe x CeZr catalysts for simultaneous removal of NO and toluene. [Display omitted] • The correlativity between the the reaction process and sulfur poisoning was studied. • The mechanism effect of SO 2 on the reaction process was studied. • A mechanism for simultaneous removal of NO and toluene was proposed. • The introduction of Fe enhanced oxygen vacancies formation and oxygen mobility. Developing non-vanadium-based SCR catalysts with high performances for simultaneous removal of NO and toluene at low-medium temperatures remains a challenge in addressing SO 2 poisoning. Herein, porous Fe-modified CuCeZr catalysts prepared via KIT-6 hard-templating method was conducted to investigate the simultaneous removal of NO and toluene at low-medium temperatures. A suite of experiments and characterizations was systematically used to probe into the effect of SO 2 on the reaction process. The results indicated that porous Fe-modified CuCeZr displayed excellent performance for simultaneous removal of NO and toluene. The introduction of Fe into CuCeZr enhances both acid sites and redox properties via the redox cycle between Cu2++Ce3+↔Cu++Ce4+ and Fe3++Ce3+↔Fe2++Ce4+ redox cycle. Importantly, Fe incorporation leads to the formation of lattice defects and oxygen vacancies, generating abundant active sites that mitigate the detrimental effects of SO 2 poisoning, and promote the efficient removal of NO and toluene simultaneously. Besides, a mechanism influence of SO 2 on the reaction process for simultaneous removal of NO and toluene at low-medium temperatures was proposed. This mechanism has the potential to provide an effective solution for developing non-vanadium-based SCR catalysts with sulfur resistance. [ABSTRACT FROM AUTHOR]

Graph convolutional network (GCN) has led to state-of-the-art performance for structured data. The superior performance would be partly due to the convolutional operations that operate over local neighborhoods. However, the distant long-range dependencies in data are still challenging to capture since it requires deep stacks of convolutional operations. Moreover, missing links in structured data might further hurt the performance. This paper introduces non-locality augmented graph convolution blocks into GCN to capture long-range or even disconnected dependencies. Specifically, we propose a dictionary-based non-locality encoding approach in which the non-local information is encoded by both graph convolution and dictionary-based implicit convolution. Unlike previous non-local approaches, our non-local block does not rely on the exhaustive computation of the relationship of data pairs. Thus, it is suitable for GCN, which typically models a large number of data samples. What's more, the proposed non-local blocks could be embedded into arbitrarily GCN architectures. We demonstrate the efficacy of our non-local block on four benchmark datasets. [ABSTRACT FROM AUTHOR]

Influence maximization (IM) has shown wide applicability in various fields over the past few decades, e.g., viral marketing, rumor control, and prevention of infectious diseases. Nevertheless, existing research on IM primarily focuses on ordinary networks with pairwise connections between nodes, which fall short in the representation of higher-order relations. Influence maximization on hypergraphs (HIM) has received limited research attention. A novel evaluation function, which aims to evaluate the spreading influence of selected nodes on hypergraphs, i.e., expected diffusion value on hypergraph (HEDV), is proposed in this work. Then, an advanced greedy-based algorithm, termed HEDV-greedy, is proposed to select seed nodes with maximum spreading influence on the hypergraph. We conduct extensive experiments on eight real-world hypergraph datasets, benchmarking HEDV-greedy against eight state-of-the-art methods for the HIM problem. Extensive experiments conducted on real-world datasets highlight the effectiveness and efficiency of our proposed methods. The HEDV-greedy algorithm demonstrates a marked reduction in time complexity by two orders of magnitude compared to the conventional greedy method. Moreover, HEDV-greedy outperforms other state-of-the-art algorithms across all datasets. Specifically, under conditions of lower propagation probability, HEDV-greedy exhibits an average improvement in solution accuracy of 25.76%. [ABSTRACT FROM AUTHOR]

Multi-timescale dynamics are common in chemical processes. These processes are often difficult to model and pose challenges in control system design. In this paper, we propose a data-based control approach for linear multi-timescale systems using a system behavioural framework. A data resampling method coupled with a novel data predictive control (DPC) design with multi-level optimisation horizons is developed to handle different timescales. To deal with the dynamics of different timescales, the optimisation horizons with small to large time intervals are used to predict and optimise control actions from near to distant future. Computational complexity wise, the multi-level structure allows horizon length to expand exponentially with optimisation steps. A trajectory-based dissipativity condition is also developed to ensure stability of the proposed DPC, while achieving disturbance rejection and tracking control. An example of controlling a multi-timescale reactive distillation column is presented to illustrate the proposed approach. • A novel multi-timescale Data-Predictive Control (DPC) approach is developed. • This approach is based on a system behavioural framework. • A data resampling approach is developed to capture multi-timescale dynamics. • A multi-level DPC approach is developed to control multi-timescale processes. • A trajectory-based dissipativity condition ensures stability of the proposed DPC. • Tracking control is achieved together with disturbance rejection. [ABSTRACT FROM AUTHOR]

• In previous studies, deep learning methods were used for sound source localization using the frequency-domain features of array signals commonly. This paper proposes a time-domain signal feature for sound source localization for the first time and designs a novel method for constructing time-domain signal features. • A three-dimensional array formation suitable for this method has been designed, which, combined with the time-domain features, can achieve accurate localization in all directions. • This method directly uses time-domain signals as input features without performing any pre-processing on the signals, and does not rely on any basic signal processing methods. Combined with deep learning, once the network training is completed, rapid localization can be achieved. Deep learning, as the most commonly used machine learning algorithm, is widely used in various fields. In the field of acoustics, deep learning methods are combined with frequency-domain features of signals to locate sound sources. The commonly frequency domain features include microphones array Cross-spectral-Matrix(CSM) and Short Time Fourier Transform(STFT). However, the use of frequency-domain features often leads to the loss of partial signal information and increases the computational complexity. This paper proposed a novel sound source localization algorithm based on time-domain features, which uses convolutional neural network(CNN) as a medium to achieve mapping from time-domain features to sound source locations. This method does not rely on any basic signal processing algorithm, and directly uses time-domain sampling points as network inputs for sound source localization. The application simulation shows that the proposed method can achieve precise localization and low side-lobe effect under different testing conditions. Once the network training is completed, the testing accuracy under different conditions is above 95%, with a maximum of 100%. [ABSTRACT FROM AUTHOR]

In the context of COVID-19 pandemic prevention and control, it is of vital significance to realize accurate face mask detection via computer vision technique. In this paper, a novel attention improved Yolo (AI-Yolo) model is proposed, which can handle existing challenges in the complicated real-world scenarios with dense distribution, small-size object detection and interference of similar occlusions. In particular, a selective kernel (SK) module is set to achieve convolution domain soft attention mechanism with split, fusion and selection operations; a spatial pyramid pooling (SPP) module is applied to enhance the expression of local and global features, which enriches the receptive field information; and a feature fusion (FF) module is utilized to promote sufficient fusions of multi-scale features from each resolution branch, which adopts basic convolution operators without excessive computational complexity. In addition, the complete intersection over union (CIoU) loss function is adopted in the training stage for accurate positioning. Experiments are carried out on two challenging public face mask detection datasets, and the results demonstrate the superiority of the proposed AI-Yolo against other seven state-of-the-art object detection algorithms, which achieves the best results in terms of mean average precision and F1 score on both datasets. Furthermore, effectiveness of the meticulously designed modules in AI-Yolo is validated through extensive ablation studies. In a word, the proposed AI-Yolo is competent to accomplish face mask detection tasks under extremely complex situations with precise localization and accurate classification. • A novel attention-enhanced face mask detection framework is proposed. • Presentation ability of both local and global features is strengthened. • Information in multi-scale features is sufficiently fused. • CIoU loss function is applied to promote accurate localization. [ABSTRACT FROM AUTHOR]

Gold nanoparticles/785 porous silicon photonic crystals (Au NPs/785 PSi PhCs) were used as substrates in combination with a low-concentration serum surface-enhanced Raman spectroscopy (SERS) detection scheme to obtain spectral signals from healthy individuals and cervical cancer patients. The best principal component scores were selected by principal component analysis (PCA) combined with linear discriminant analysis (LDA) and support vector machine (SVM) to analyze the spectral differences distinguishing healthy and cervical cancer patients. The accuracy of the two models was 97.9% and 96.9%, respectively. SERS technique based on Au NPs/785 PSi PhCs has great potential to improve the screening of cervical cancer. [ABSTRACT FROM AUTHOR]

Lactobacillus delbrueckii is widely used in the fermentation industry. Previously, we identified Lactobacillus delbrueckii DMLD-H1, a strain of Lactobacillus delbrueckii subsp. bulgaricus , from traditional Chinese fermented milk. In this research, we sequenced the complete genome of DMLD-H1, which contains 1,836,627 bp in length with a total of 1947 genes and an average G + C content of 49.86%. In total, 103 carbohydrate metabolism genes are annotated in the KEGG database, and it is showed that DMLD-H1 has the ability to transport lactose, glucose, fructose, and mannose. Antibiotic resistance genes, genes encoding toxins and virulence factor genes are absent in risk-associated sequences of DMLD-H1. We also confirm its safety by indole assay, nitroreductase assay, and antibiotic resistance tests. A wide range of stress-related proteins may contribute to the survival of DMLD-H1 in the gastrointestinal environment, including oxidative stress, pH, bile salts, and temperature stress. The large number of adhesion proteins and stress response genes identified in DMLD-H1 in the genome-wide analysis, as well as phenotypic experiments including resistance to bile salts and acid, antioxidant, antimicrobial and self-cohesion activity, exhibited its excellent probiotic properties. This study demonstrates that DMLD-H1 can be a candidate fermentative agent in fermented dairy products. [Display omitted] • The entire genome of Lactobacillus delbrueckii DMLD-H1 was firstly sequenced. • The carbohydrate metabolic pathway is revealed in DMLD-H1. • The safety and probiotic properties of DMLD-H1 are described by genome analysis. • DMLD-H1 has a gene cluster for the generation of enterolysin A. [ABSTRACT FROM AUTHOR]

[Display omitted] • Probe is capable of detecting ONOO− with a longwave fluorescence emission. • TL could monitor high concentration of dexamethasone-induced an up-regulation of ONOO−. • Probe has mitochondrial targeting capability. • Probe have good selectivity and low detection limit. • The imaging demonstrated its value of practical application. Peroxynitrite (ONOO−), as a strong oxidizing reactive nitrogen substance (RNS), is generated endogenously by cells. Its visualization research is crucial to understand relevant disease processes. Herein, we reported a long-wavelength mitochondria-targeted fluorescence "turn on" probe TL. The probe TL could react with ONOO− by using 4-(Bromomethyl)benzeneboronic as a reactive site, which exhibited outstanding characteristics for detection of ONOO−, thus improving response time (about 50 s), sensitivity (DL, 10.1 nM), and emission wavelength (667 nm). Besides, TL displayed well mitochondria targeting and biological visualizing of exogenous and endogenous ONOO− in biological systems. Finally, TL was used to monitor high concentration of dexamethasone-induced an up-regulation of ONOO−. This indicated that TL has excellent potential to study the fluctuation of ONOO− in the physiological and pathological system. [ABSTRACT FROM AUTHOR]

As one of important indicators of atherosclerosis (AS), excess homocysteine (Hcy), could cause oxidation stress, thus leading to inflammation and tissue damage. Hypochlorous acid/hypochlorite (HOCl/OCl−), as an important reactive oxygen species, is speculated to be an indicator of AS caused by Hcy-inducated. Here, a fluorescence nanoprobe LR NPs based on the assembly of pluronic F-127 and probe TR was developed for ClO− detection and imaging during Hcy stress. As expected, LR NPs showed good selectivity and sensitivity for ClO− detection. LR NPs can visualize the fluxes of HClO/ClO− during the stimulation of Hcy induce AS in real time, which demonstrated HClO/ClO− could be performed as an indicator of AS. [Display omitted] • A nano-fluorescent probe (LR NPs) with high sensitivity and selectivity to ClO− was designed and synthesized. • LR NPs was applied to detect endogenous and exogenous ClO− in living cells. • The fluorescent imaging of ClO− caused by Hcy-induced was reported for the first time. [ABSTRACT FROM AUTHOR]