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Layered chiral magnets with broken spatial inversion symmetry (SIS) enable chiral spin textures to occur in atomically thin layers. However, most layered materials retain SIS during their crystallization. Here, we demonstrate that SIS can be broken in a layered transition metal dichalcogenide TaS2 by intercalating Mn atoms. A chiral magnetic phase in Mn1/3TaS2 has, thus, been realized. This phase enables a nonzero Dzyaloshinskii–Moriya interaction, which in turn gives rise to large topological Hall effects (THEs) below 50 K. Both the ferromagnetism and THE can be tuned at low temperatures by modulating the carrier density via a protonic gate. Measured at 20 K with Vg = −4.7 V applied to the gate and electron doping density of 1.7 × 1022 cm−3, the maximum THE was almost double that recorded with no gate voltage applied. By further reducing the sample thicknesses, both the Curie temperature Tc and the longitudinal magnetoresistance can be significantly modulated. This is consistent with the theory of critical behavior. Our work highlights the ability to control both magnetism and chiral spin textures in Mn1/3TaS2 nanoflakes. Applying this discovery may lead to a variety of practical van der Waals heterostructure devices. [ABSTRACT FROM AUTHOR]

Current maize (Zea mays L.) breeding methods and the limited germplasm infusion and mixing may slow the rate of genetic gain in the future. Using inter‐heterotic group composites for maize inbred development has been questioned because of the issue of choosing appropriate testers. However, three observations can be revisited to facilitate the exploration of alternative methods. First, since the adoption of single‐cross hybrids and the establishment of heterotic groups, the amount of heterosis has only been increasing slightly. Second, genomic analysis indicated the frequencies of the favorable alleles had significantly increased after a century's breeding. Third, the divergence of maize heterotic groups was preceded by the merging of landraces and diverse inbreds, after which three major heterotic groups were established. The objective of this study was to design different scenarios to generate inter‐heterotic group composites and evaluate their usefulness in the commercial breeding program. We investigated two methods: the inter‐heterotic group composite method (termed as super population [SupPop]) and the modified SupPop method (ModiSP, that is, backcrossing SupPop lines with elite inbreds). The results showed that the best scenario for the SupPop method was to use the SupPop inbreds to cross with a tester from the B14 group. When all four heterotic groups were mixed, the favored tester was from stiff stalk. However, ModiSP showed a higher chance of producing the best yield performance. These empirical results suggest that solutions can be proposed to identify the testers so that using inter‐heterotic group composites for inbred development can be considered. Core Ideas: Alternative maize inbred development methods may be tested to enhance genetic gain.A large‐scale, empirical study was conducted to develop inbreds from the inter‐heterotic group composites.With appropriate testers, inter‐heterotic group composites can be considered for inbred development. [ABSTRACT FROM AUTHOR]

Currently, the rockburst failure mode discrepancy is not taken into account in rockburst prediction, and some defects such as missing values, outlier samples and class imbalance are still present in the rockburst database. To solve the above problems, a three-step rockburst prediction model based on data preprocessing combined with clustering and classification algorithms (PCC) is proposed. The first step is data preprocessing for dealing with missing values and outlier samples. In the second step, the K-means algorithm is introduced to cluster the preprocessed data into two clusters for distinguishing the rockburst failure mode discrepancy. In the third step, Random Forest (RF), Gradient Boosting Decision Tree (GBDT) and Extreme Gradient Boosting (XGB) are employed to construct classification models, respectively, after class balancing. Finally, a comparative analysis between the PCC model and the rockburst prediction model based on data preprocessing and classification algorithms (PC) is conducted, and the analysis is based on 310 samples. Furthermore, the self-proposed metric and traditional metrics are employed to evaluate the model performance. The prediction results demonstrate that the performance of the PCC model is superior to the PC model, and the rockburst failure mode discrepancy should be considered in rockburst prediction. [ABSTRACT FROM AUTHOR]

In this study, the gas metal arc welding (GMAW) process was investigated for similar and dissimilar joints of A844 and A516 steel plates in different thicknesses. For welding, E 19-10H filler metal and category D joint design were used for joining nozzles to the cargo tank body. Also, the dependence of the microstructure, strength, and impact energy (cryogenic fracture toughness) on the cooling rate (∂T/∂t) was evaluated. Due to the effect of the square of thickness on the heat transfer rate, with the increase in thickness (8–10 mm), the cooling rate (∂T/∂t) increased by 57% for similar joints. According to this increase, the strength and cryogenic fracture toughness for the similar joints of A844 steel plates increased by 8 and 9%, respectively. For similar joints of A516 steel plates, it increased by 6 and 9%, respectively. The strength and cryogenic fracture toughness of dissimilar joints with different thicknesses depended on the type of base metals and the different cooling rates of each base metal. Continuous plastic deformation was observed in the weld zone during bending tests because E19-10H filler metal has more than 30% elongation. Also, the presence of any kind of cracks in the joints was ruled out by performing radiographic tests. [ABSTRACT FROM AUTHOR]

Glioma is the most common malignant tumor of the central nervous system, with EZH2 playing a crucial regulatory role. This study further explores the abnormal expression of EZH2 and its mechanisms in regulating glioma progression. Additionally, it was found that IHMT-337 can potentially be a therapeutic agent for glioma. The prognosis, expression, and localization of EZH2 were determined using bioinformatics, IHC staining, Western blot (WB) analysis, and immunofluorescence (IF) localization. The effects of EZH2 on cell function were assessed using CCK-8 assays, Transwell assays, and wound healing assays. Public databases and RT-qPCR were utilized to identify downstream targets. The mechanisms regulating these downstream targets were elucidated using MS-PCR and WB analysis. The efficacy of IHMT-337 was demonstrated through IC50 measurements, WB analysis, and RT-qPCR. The effects of IHMT-337 on glioma cells in vitro were evaluated using Transwell assays, EdU incorporation assays, and flow cytometry. The potential of IHMT-337 as a treatment for glioma was assessed using a blood–brain barrier (BBB) model and an orthotopic glioma model. Our research confirms significantly elevated EZH2 expression in gliomas, correlating with patient prognosis. EZH2 facilitates glioma proliferation, migration, and invasion alongside promoting SLC12A5 DNA methylation. By regulating SLC12A5 expression, EZH2 activates the WNK1-OSR1-NKCC1 pathway, enhancing its interaction with ERM to promote glioma migration. IHMT-337 targets EZH2 in vitro to inhibit WNK1 activation, thereby suppressing glioma cell migration. Additionally, it inhibits cell proliferation and arrests the cell cycle. IHMT-337 has the potential to cross the BBB and has successfully inhibited glioma progression in vivo. This study expands our understanding of the EZH2-SLC12A5 axis in gliomas, laying a new foundation for the clinical translation of IHMT-337 and offering new insights for precision glioma therapy. [ABSTRACT FROM AUTHOR]

The continuum macroscopic transport approach combined with a tabulated thermodynamic phase transformation path is established to predict the macrosegregation in Fe‐1.05 wt% C‐1.65 wt% Cr hypereutectoid steel castings. A combined partial‐equilibrium (PE) and para‐equilibrium (PA) thermodynamic approximation is developed to retrieve the phase transformation path in steels. PA routine is performed on both austenite to stoichiometric cementite transition and austenite to α‐ferrite transition in eutectoid transformation. The approach is also applied to a hypoeutectoid alloy to predict austenite to α‐ferrite transition as well as δ‐ferrite to austenite transition in mushy zone. Thermodynamic properties in macroscopic transport approach are updated by group interpolation from tabulated phase transformation path. Results show that the interaction between substitutional solute Cr and interstitial C weakens the segregation of C and the amount of cementite in the center of casting, making the C distribution more consistent with that obtained by original position statistical distribution analysis in GCr15SiMn alloy castings. This implies that including the contribution of more components can make the estimate more reasonable. The results indicate the potential of macroscopic transport prediction coupled with tabulated phase transformation path through PE + PA approximation. [ABSTRACT FROM AUTHOR]

Aircraft wake vortices are serious threats to aviation safety. The Pulsed Coherent Doppler Lidar (PCDL) has been widely used in the observation of aircraft wake vortices due to its advantages of high spatial-temporal resolution and high precision. However, the post-processing algorithms require significant computing resources, which cannot achieve the real-time detection of a wake vortex (WV). This paper presents an improved Convolutional Neural Network (CNN) method for WV locating and grading based on PCDL data to avoid the influence of unstable ambient wind fields on the localization and classification results of WV. Typical WV cases are selected for analysis, and the WV locating and grading models are validated on different test sets. The consistency of the analytical algorithm and the CNN algorithm is verified. The results indicate that the improved CNN method achieves satisfactory recognition accuracy with higher efficiency and better robustness, especially in the case of strong turbulence, where the CNN method recognizes the wake vortex while the analytical method cannot. The improved CNN method is expected to be applied to optimize the current aircraft spacing criteria, which is promising in terms of aviation safety and economic benefit improvement. [ABSTRACT FROM AUTHOR]

Objective: To compare the effect of fermentation on the chemical constituents of Gastrodia Tuder Halimasch Powder (GTHP), to establish its fingerprinting and multicomponent content determination, and to provide a basis for the processing, handling, and clinical application of this herb. Methods: Ultra-high-performance liquid chromatography-quadrupole-Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS) was used to conduct a preliminary analysis of the chemical constituents in GTHP before and after fermentation. High-performance liquid chromatography (HPLC) was used to determine some major differential components of GTHP and establish fingerprints. Cluster analysis (CA), and principal component analysis (PCA) were employed for comprehensive evaluation. Results: Seventy-nine compounds were identified, including flavonoids, organic acids, nucleosides, terpenoids, and others. The CA and PCA results showed that ten samples were divided into three groups. Through standard control and HPLC analysis, 10 compounds were identified from 22 peaks, namely uracil, guanosine, adenosine, 5-hydroxymethylfurfural (5-HMF), daidzin, genistin, glycitein, daidzein, genistein, and ergosterol. After fermentation, GTHP exhibited significantly higher contents of uracil, guanosine, adenosine, 5-hydroxymethylfurfural, and ergosterol and significantly lower genistein and daidzein contents. Conclusions: The UHPLC-Q-Orbitrap HRMS and HPLC methods can effectively identify a variety of chemical components before and after the fermentation of GTHP. This study provides a valuable reference for further research on the rational clinical application and quality control improvement of GTHP. [ABSTRACT FROM AUTHOR]

The scarcity of defect samples and the imbalance of defect types lead to the fact that achieving defect detection in color-patterned fabrics remains a challenge in the textile industry. Defect detection methods based on traditional auto-encoder are difficult to solve the problem of defect detection in complex color-patterned fabrics. In order to solve the problem of weak feature representation of traditional auto-encoders, this paper proposes an unsupervised method based on triplet attention multi-scale U-shape denoising convolutional auto-encoder (TA_MSUDCAE). The method further enhances the feature representation capability of the auto-encoder by introducing a triplet attention mechanism based on utilizing the multi-scale information of the image. Firstly, the defect-free samples that are added with Gaussian noise are used as inputs to the model in the training stage. The model is trained to reconstruct and repair the defective regions. Secondly, the test image is input to the trained model to obtain a normal reconstructed image, and the residual image is obtained by calculating the difference between the input image and the reconstructed image. Finally, the defect detection and localization results are obtained by threshold segmentation and mathematical morphology processing of the residual image. A large number of experiments have been carried out on a variety of representative color-patterned fabrics, and the results prove the effectiveness of the proposed method in fabric defect detection. [ABSTRACT FROM AUTHOR]

Bulimia, which means a person has episodes of eating a very large amount of food (bingeing) during which the person feels a loss of control over their eating, is the most primitive reason for being overweight and obese. The extended literature has indicated that childhood emotional abuse has a close relationship with adverse mood states, bulimia, and obesity. To comprehensively understand the potential links among these factors, we evaluated a multiple mediation model in which anxiety/depression and bulimia were mediators between childhood emotional abuse and body mass index (BMI). A set of self-report questionnaires, including the Childhood Trauma Questionnaire (CTQ), Beck Anxiety Inventory, Beck Depression Inventory (BDI), and Eating Disorder Inventory (EDI), was sent out. Clinical data from 37 obese patients (age: 29.65 ± 5.35, body mass index (BMI): 37.59 ± 6.34) and 37 demographically well-matched healthy people with normal body weight (age: 31.35 ± 10.84, BMI: 22.16 ± 3.69) were included in the investigation. We first performed an independent t-test to compare all scales or subscale scores between the two groups. Then, we conducted Pearson correlation analysis to test every two variables' pairwise correlation. Finally, multiple mediation analysis was performed with BMI as the outcome variable, and childhood emotional abuse as the predictive variable. Pairs of anxiety, bulimia, and depression, bulimia were selected as the mediating variables in different multiple mediation models separately. The results show that the obese group reported higher childhood emotional abuse (t = 2.157, p = 0.034), worse mood state (anxiety: t = 5.466, p < 0.001; depression: t = 2.220, p = 0.030), and higher bulimia (t = 3.400, p = 0.001) than the healthy control group. Positive correlations were found in every pairwise combination of BMI, childhood emotional abuse, anxiety, and bulimia. Multiple mediation analyses indicate that childhood emotional abuse is positively linked to BMI (β = 1.312, 95% CI = 0.482–2.141). The model using anxiety and bulimia as the multiple mediating variables is attested to play roles in the relationship between childhood emotional abuse and obesity (indirect effect = 0.739, 95% CI = 0.261–1.608, 56.33% of the total effect). These findings confirm that childhood emotional abuse contributes to adulthood obesity through the multiple mediating effects of anxiety and bulimia. The present study adds another potential model to facilitate our understanding of the eating psychopathology of obesity. [ABSTRACT FROM AUTHOR]

(1) Background: Understanding vascular patterns is crucial for minimizing bleeding and operating time in colorectal surgeries. This study aimed to develop an anatomical atlas of the inferior mesenteric artery (IMA) and vein (IMV). (2) Methods: A total of 521 patients with left-sided colorectal cancer were included. IMA and IMV patterns were identified using maximum-intensity projection (MIP) and three-dimensional (3D) reconstruction techniques. The accuracy of these techniques was assessed by comparing them with surgical videos. We compared the amount of bleeding and operating time for IMA ligation across different IMA types. (3) Results: Most patients (45.7%) were classified as type I IMA, followed by type II (20.7%), type III (22.6%), and type IV (3.5%). Newly identified type V and type VI patterns were found in 6.5% and 1% of patients, respectively. Of the IMVs, 49.9% drained into the superior mesenteric vein (SMV), 38.4% drained into the splenic vein (SPV), 9.4% drained into the SMV–SPV junction, and only 2.3% drained into the first jejunal vein (J1V). Above the root of the left colic artery (LCA), 13.1% of IMVs had no branches, 50.1% had one, 30.1% had two, and 6.7% had three or more branches. Two patients had two main IMV branches, and ten had IMVs at the edge of the mesocolon with small branches. At the IMA root, 37.2% of LCAs overlapped with the IMV, with 34.0% being lateral, 16.9% distal, 8.7% medial, and both the marginal type of IMV and the persistent descending mesocolon (PDM) type represented 1.4%. MIP had an accuracy of 98.43%, and 3D reconstruction had an accuracy of 100%. Blood loss and operating time were significantly higher in the complex group compared to the simple group for IMA ligation (p < 0.001). (4) Conclusions: A comprehensive anatomical atlas of the IMA and IMV was provided. Complex IMA patterns were associated with increased bleeding and operating time. [ABSTRACT FROM AUTHOR]

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer with a low 5‐year survival rate. ANKRD22 is an ankyrin repeat protein capable of promoting tumor progression, and its mechanism in LUAD remains elusive. Our study aims to investigate the mechanisms underlying the involvement of ANKRD22 in the progression of LUAD. The expression of ANKRD22 in LUAD and its enriched pathway were analyzed by bioinformatics analysis. Meanwhile, the correlation between ANKRD22 and the expression of glycolysis‐related genes and M2 macrophage marker genes was analyzed. qRT‐PCR was used for determination of the expression of ANKRD22, IL‐10 and CCL17, CCK‐8 for cell viability, and western blot for expression of ANKRD22, LDHA, HK2, PGK1, and PKM2. Immunofluorescence and flow cytometry were utilized to examine the level of CD163, and kits were used to measure the contents of pyruvic acid, lactate, citrate, and malate. Seahorse XF96 analyzer was employed to determine extracellular acidification rate (ECAR) and oxygen consumption rate (OCR). Mitochondrial membrane potential was assessed using the JC‐1 probe. Bioinformatics analysis, qRT‐PCR, and western blot showed that ANKRD22 was highly expressed in LUAD, which had a positive connection with M2 marker genes. Knockdown of ANKRD22 considerably attenuated the expression of ANKRD22, IL‐10, and CCL17 in M2. ANKRD22 overexpression demonstrated the opposite results. Bioinformatics analysis uncovered that ANKRD22 was enriched in the glycolytic pathway and positively correlated with glycolysis‐related genes. The knockdown of ANKRD22 substantially attenuated pyruvic acid, lactate, citrate, malate, and ECAR levels and elevated OCR levels in cells. The knockdown of ANKRD22 also reduced mitochondrial membrane potential. Further, it was discovered that glycolysis‐related genes had a positive correlation with M2 marker genes. It was revealed by rescue experiments that the usage of 2‐DG, a glycolytic inhibitor, remarkably reversed the facilitating effect of overexpression of ANKRD22 on M2 polarization. This study demonstrates that ANKRD22 can facilitate LUAD M2 polarization through glycolysis, and targeting ANKRD22 to inhibit M2 polarization has the potential to be a new strategy for LUAD treatment. [ABSTRACT FROM AUTHOR]

Promoting green technology innovation is imperative for all nations seeking to attain sustainable development and foster green growth. China, as the largest developing country globally, stands at the forefront of rapid economic development. In this study, we delve into the influence of Taoism on green technology innovation within Chinese cities. Employing empirical analysis based on comprehensive Chinese city data, our findings substantiate that Taoism plays a constructive role in bolstering green technology innovation in these urban centers. Notably, a positive correlation emerges, demonstrating that a stronger presence of Taoist principles corresponds with heightened levels of green technology innovation. [ABSTRACT FROM AUTHOR]

The top oil temperature in ultra-high voltage (UHV) reactors has attracted enormous interest due to its wide applications in fault diagnosis and insulation evaluation. In this work, the precise prediction method based on the Seq2Seq module with the convolutional block attention mechanism is proposed for the UHV reactor. To reduce the influence of vibratility and improve computational efficiency, a combination of the encoding layer and decoding layer named Seq2Seq is performed to reconstruct the complex raw data. The convolutional block attention mechanism (CBAM), composed of spatial attention and channel attention, is utilized to maximize the use of information in data. The Seq2Seq-CBAM is established to forecast the variation tendency of the oil temperatures in the UHV reactor. The experimental results show that the proposed method achieves high prediction accuracy for the top oil temperature in both single-step and multi-step. [ABSTRACT FROM AUTHOR]

We investigate the quasi-synchronization of fractional-order complex networks (FCNs) with random coupling via quantized control. Firstly, based on the logarithmic quantizer theory and the Lyapunov stability theory, a new quantized feedback controller, which can make all nodes of complex networks quasi-synchronization and eliminate the disturbance of random coupling in the system state, is designed under non-delay conditions. Secondly, we extend the theoretical results under non-delay conditions to time-varying delay conditions and design another form of quantization feedback controller to ensure that the network achieves quasi-synchronization. Furthermore, the error bound of quasi-synchronization is obtained. Finally, we verify the accuracy of our results using two numerical simulation examples. [ABSTRACT FROM AUTHOR]

To improve the corrosion resistance of 6061 Al in electric vehicle battery packs, a composite coating of nano-SiO2/Micro-Arc oxidation (MAO) ceramic structure was prepared on its surface. Electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization curves (PDP) were used to evaluate the corrosion resistance of the specimens after 7 days immersion in a 3.5% NaCl solution. The corrosion resistance of the prefabricated coatings was measured via local electrochemical impedance spectroscopy (LEIS). Confocal microscopy, scanning electron microscopy (SEM), and X-ray diffraction (XRD) were used to characterize the microstructure and phase composition of the specimens. An energy dispersive spectrometer (EDS) was used to detect the elemental composition of the surface of the specimen. The results showed that the specimen with nano-SiO2/MAO composite coating had the least amount of micropores and superior corrosion resistance. The global electrochemical impedance of nano-SiO2/MAO composite coating was 1.1 times higher than that of the MAO coating and 8.4 times higher than that of the 6061 Al. When the coating was defective, the local electrochemical impedance of the nano-SiO2/MAO composite coating was still two times higher than that of the MAO coating. In the presence of scratches, the nano-SiO2/MAO composite coating still showed high corrosion resistance. The collapse corrosion mechanism of the nano-SiO2/MAO composite coating was proposed. [ABSTRACT FROM AUTHOR]

In wind turbine systems, bolted connections are frequently subjected to gravitational and centrifugal loads transmitted by the blades during operation. This can lead to the attenuation of bolt preloading, resulting in bolt loosening or uneven loading, which in turn affects the service life of the generator unit. Therefore, the study of bolt preloading variations is crucial. However, there are numerous factors influencing bolt preloading, and the existing techniques struggle to precisely assess bolt preloading. This paper proposed a bolt preloading evaluation technique based on the hammer modal method. Focusing on the 42CrMo4 bolted connection of a pitch bearing, a test platform for bolt preloading assessment is constructed. Hammer modal tests are conducted under various preloading forces. By combining finite element modal analysis, the correspondence between preloading changes and the bending frequencies and modes of the bolted connection is obtained. The research illustrated that with changes in bolt preloading, variations occur in coherence, phase, and natural frequencies of frequency response functions. The fundamental correlation between bolt preloading and the second-order bending frequency can be utilized to assess changes in preloading. Furthermore, the applicability of this method has been validated, offering a reference for evaluating bolt preloading. [ABSTRACT FROM AUTHOR]

We present a unified non-local damage model for modeling hydraulic fracture processes in porous media, in which damage evolves as a function of fluid pressure. This setup allows for a non-local damage model that resembles gradient-type models without the need for additional degrees of freedom. In other words, we propose a non-local damage formulation at the same cost of a local damage approach. Nonlinear anisotropic permeability is employed to distinguish between the fluid flow velocity in the damage zone and the intact porous media. The permeability evolves as a function of an equivalent strain measure, where its anisotropic evolution behavior is controlled by the direction of principle strain. The length scale of the proposed model is analytically derived as a function of material point variables and is shown to be dependent on the pressure rate. A mixed finite element method is proposed to monolithically solve the coupled displacement–pressure system. The nonlinear system is linearized and solved using Newton's method with analytically derived consistent Jacobian matrix and residual vector, and the evolution of the system in time is performed by a backward Euler scheme. Numerical examples of 1D and 2D hydraulic fracture problems are presented and discussed. The numerical results show that the proposed model is insensitive to the mesh size as well as the time step size and can well capture the features of hydraulic fracture in porous media. [ABSTRACT FROM AUTHOR]

Water vapor is a crucial component of the atmosphere. Its absorption significantly influences remote sensing by impacting radiation signals transmitted through the atmosphere. Determining columnar water vapor (CWV) from hyperspectral remote sensing data is essential during the imagery atmospheric correction process. Over the past 40 years, numerous CWV inversion algorithms have been developed, with refinements to enhance retrieval accuracy and reliability. In this study, we proposed an enhanced atmospheric pre-corrected differential absorption (APDA) algorithm. This enhancement was achieved by thoroughly analyzing water vapor absorption in relation to elevation and aerosol optical depth and extending look up tables (LUTs). The enhanced method utilizes a pre-built MODTRAN lookup table and is applied to ZY1-02D hyperspectral data from a satellite launched in 2020. We compared the inversion results of 10 ZY1-02D scenes obtained using the improved method with AERONET measurements and inversion results from commonly used atmospheric correction software, namely, FLAASH and ATCOR. The updated algorithm demonstrated a lower average error (0.0568 g·cm−2) and relative average error (10.49%) compared to the ATCOR software (0.17 g·cm−2 and 40.78%, respectively) and the FLAASH module (0.13 g·cm−2 and 30.82%, respectively). Consequently, the enhanced method outperforms traditional CWV inversion algorithms, especially at high altitudes. [ABSTRACT FROM AUTHOR]

Sparse-representation-based synthetic aperture radar (SAR) imaging technology has shown superior potential in the reconstruction of nonsparse scenes. However, many existing compressed sensing (CS) methods with sparse representation cannot obtain an optimal sparse basis and only apply to the sensing matrix obtained by exact observation, resulting in a low image quality occupying more storage space. To reduce the computational cost and improve the imaging performance of nonsparse scenes, we formulate a deep learning SAR imaging method based on sparse representation and approximated observation deduced from the chirp-scaling algorithm (CSA). First, we incorporate the CSA-derived approximated observation model and a nonlinear transform function within a sparse reconstruction framework. Second, an iterative shrinkage threshold algorithm is adopted to solve this framework, and the solving process is unfolded as a deep SAR imaging network. Third, a dual-path convolutional neural network (CNN) block is designed in the network to achieve the nonlinear transform, dramatically improving the sparse representation capability over conventional transform-domain-based CS methods. Last, we improve the CNN block to develop an enhanced version of the deep SAR imaging network, in which all the parameters are layer-varied and trained by supervised learning. The experiments demonstrate that our proposed two imaging networks outperform conventional CS-driven and deep-learning-based methods in terms of computing efficiency and reconstruction performance of nonsparse scenes. [ABSTRACT FROM AUTHOR]

Detecting acoustic signals in the ocean is crucial for port and coastal security, but existing methods often require informative priors. This paper introduces a new approach that transforms acoustic signal detection into network characterization using a MCN construction method. The method constructs a network representation of the acoustic signal by measuring pairwise correlations at different time scales. It proposes a network spectrum distance method that combines information geometry and graph signal processing theory to characterize these complex networks. By comparing the spectra of two networks, the method quantifies their similarity or dissimilarity, enabling comparisons of multi-scale correlation networks constructed from different time series data and tracking changes in nonlinear dynamics over time. The effectiveness of these methods is substantiated through comprehensive simulations and real-world data collected from the South China Sea. The results illustrate that the proposed approach attains a significant detection probability of over 90% when the signal-to-noise ratio exceeds −18 dB, whereas existing methods require a signal-to-noise ratio of at least −15 dB to achieve a comparable detection probability. This innovative approach holds promising applications in bolstering port security, facilitating coastal operations, and optimizing offshore activities by enabling more efficient detection of weak acoustic signals. [ABSTRACT FROM AUTHOR]

Summary: In this study, four kinds of sorghum starch gels containing different amylose were taken as the research objects and stored for 28 days. The parameter changes of gel properties during the retrogradation of different varieties of sorghum starches were observed using X‐ray diffraction, Low‐field nuclear magnetic resonance, textural, rheological and anti‐enzymatic hydrolysis capacity studies to construct kinetic models for the retrogradation. The results showed that the degree of retrogradation, crystallinity and anti‐enzymatic hydrolysis capacity of sorghum starch increased with the prolongation of storage time, and the crystal forms of H5 (Hongnuo No. 5 sorghum) and L13 (Longza No.13 sorghum) starch changed from type A to B. Among the four kinds of starch, L13 starch had the highest degree of retrogradation, and H5 starch had the strongest recrystallisation ability. The hardness of L13 retrograded starch gel grew fastest with increasing storage time, while the viscoelasticity of H1 (Hongnuo No.1 sorghum) retrograded starch showed a stable trend. Low‐field nuclear magnetic resonance was used to detect that the L1 (Longmiliang No.1 sorghum) retrograded starch gel had more free water. The crystallisation rate was positively correlated with hardness, resistant starch content and crystallinity and negatively correlated with springiness, gumminess and resilience. [ABSTRACT FROM AUTHOR]

Investigating the genetic diversity and population structure is important in conserving narrowly distributed plants. In this study, 90 Clematis acerifolia (C. acerifolia) plants belonging to nine populations were collected from the Taihang Mountains in Beijing, Hebei, and Henan. Twenty-nine simple sequence repeats (SSR) markers developed based on RAD-seq data were used to analyze the genetic diversity and population structure of C. acerifolia. The mean PIC value for all markers was 0.2910, indicating all SSR markers showed a moderate degree of polymorphism. The expected heterozygosity of the whole populations was 0.3483, indicating the genetic diversity of both C. acerifolia var. elobata and C. acerifolia were low. The expected heterozygosity of C. acerifolia var. elobata (He = 0.2800) was higher than that of C. acerifolia (He = 0.2614). Genetic structure analysis and principal coordinate analysis demonstrated that C. acerifolia and C. acerifolia var. elobata showed great genetic differences. Molecular variance analysis (AMOVA) demonstrated that within-population genetic variation (68.31%) was the main contributor to the variation of the C. acerifolia populations. Conclusively, C. acerifolia var. elobata had higher genetic diversity than C. acerifolia, and there are significant genetic differences between C. acerifolia and C. acerifolia var. elobata, and small genetic variations within the C. acerifolia populations. Our results provide a scientific and rational basis for the conservation of C. acerifolia and provide a reference for the conservation of other cliff plants. [ABSTRACT FROM AUTHOR]

Magnesium (Mg) and its compounds have been investigated as biodegradable metals for bone implants. However, high corrosion rates and low bioactivity that cause loss of mechanical properties are factors that have limited their biomedical applications. The purpose of this work is to remedy the weaknesses of the Mg–Zn (MZ) alloy matrix. For this purpose, we have synthesized Mg-based composites with different concentrations of bredigite (Br; Ca7MgSi4O16)–carbon nanotubes (CNTs) using mechanical alloying and semi-powder metallurgy processes with spark plasma sintering. Then, we studied the effect of the simultaneous addition of Br-CNTs on in vitro degradation, as well as its effect on the composites' mechanical and antibacterial properties. Increases of 57% and 72% respectively were observed in the microhardness and compressive strength of the MZ/Br-CNTs composite in comparison to the MZ alloy. In addition, the rate of degradation of Mg-based composites in simulated body fluids (SBF) was almost 2 times lower. An assessment of antibacterial behavior disclosed that the simultaneous adding of Br-CNTs to Mg can meaningfully prevent the growth and invasion of E. coli and S. aureus. These research findings demonstrate the potential application of MZ/Br-CNTs composites to implants and the treatment of bone infections. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the energy consumption of a continuous flow ohmic heater (CFOH) with advanced process controls for heating operations in the food and drinks industry. The study was carried out by using operational data collected from a CFOH pilot plant that was designed and constructed at the National Centre of Excellence for Food Engineering (NCEFE), Sheffield Hallam University. The CFOH is controlled by a PC and includes an onboard Programmable Logic Controller (PLC) and a Human Machine Interface (HMI) so that it can be operated as a stand-alone unit with basic on/off and power setting control but without any advanced control features. The technical solution presented in this paper for heating foods demonstrates significant energy saving compared with conventional heating methods. Using the CFOH, the electric current generated in the food products by the Joule effect produces a rapid temperature increase with very high energy efficiency. This technique eliminates the low efficiency of heat transfer from the surface of vessels typically used to heat and cook food products. The analysis presented in this paper describes the energy consumption of the CFOH and compares the efficiency of the CFOH when different advanced process control techniques are used. Experimental results and analysis have shown that the CFOH can achieve an energy efficiency conversion of at least 87.9%. It has also shown that the energy conversion percentage can be increased by applying advanced controllers such as model predictive control (MPC) or adaptive model predictive control (AMPC). [ABSTRACT FROM AUTHOR]

Multi‐passive‐sensor systems are a common means for the target tracking and their bearings processing is a prerequisite for stable control and nonlinear filtering. This study proposes a mathematical methodology that is based on the incorporating deterministic unscented transition rules into stochastic sequential importance sampling frame and makes use of soft spatiotemporal constraint comprise multiview epipolar geometry constraint and numerical regularization to solve the correspondence problem. A prototype measurement‐driven target tracking frame was developed that can work in real time and achieve filtering improvements of 41%–46% and 43%–48% in terms of root‐mean‐square error and root time‐averaged mean square error compared with the state‐of‐the‐art multiple model Rao–Blackwell particle filtering method, as proven by the simulation results. [ABSTRACT FROM AUTHOR]

This paper deals with the initial boundary value problem for the double dispersion equation with nonlinear damped term and exponential growth nonlinearity in two space dimensions. We first establish the local well-posedness in the natural energy space by the standard Galërkin method and contraction mapping principle. Then, we prove the solution is global in time by taking the initial data inside the potential well and the solution blows up in finite time as the initial data in the unstable set. Moreover, finite time blow-up results are provided for negative initial energy and for arbitrary positive initial energy respectively. [ABSTRACT FROM AUTHOR]

As a key intermediate in natural products and pharmaceutics, N-(R, R)-phenethyl-1-indane was directly prepared by one-pot reductive amination of 1-indanone and R-(+)-α-phenethylamine using abundant molecular hydrogen as a reductant. Compared with the traditional noble metal catalyst, the Co-VB1(1:2)/C-900 catalysts showed higher selectivity in this reaction, and generated the N-(R, R)-phenethyl-1-indane with high yield. The Co-VB1(1:2)/C-900 catalysts were prepared by the modification of thiamine hydrochloride (VB1) as nitrogen and sulfur sources. At the same time, the catalyst was reusable for several times. The synthesis of N-(R, R)-phenethyl-1-indane was cost-effective and atom-economical. The catalyst also presented moderate to good catalytic activities in reductive amination for a series substrate, ranging from aldehydes or ketones, to giving access to various valuable compounds. [ABSTRACT FROM AUTHOR]

In cutting, the mechanical impact caused by material mechanics, geometric discontinuity, and intermittent cutting process is the main factor that induces cutting tool fracture. Impact fracture and fatigue failure of cutting tools are sudden, which can be harmful to safe production and quality control. In this paper, the effect mechanism of shim stiffness on the impact fracture performance of a tool in a mechanically clamped cutting tool system is studied. Furthermore, the vibration model of the tool-shim system is established to analyze the impact loading response characteristics of the tool-shim system under different stiffness shims. Meanwhile, the effect of shim stiffness on the loading rate, peak value, high-level fluctuation, unloading rate, and elastic energy release of shim elastic reaction force is explored. Apart from that, theoretical analysis of the stress field change near the tool crack tip is carried out. Finally, intermittent turning experiments are performed, including carbide inserts with four shims of N8 aluminum alloy, TC4 titanium alloy, 08 steel, and YT14 cemented carbide. Moreover, the analysis of each stage of the vibration response is verified. According to the results, the stiffness of the shim affects both the impact fracture of the tool basal body and the coating peeling. Besides, appropriately weakening the shim stiffness can reduce the load peak value of the shim elastic reaction force on the tool, the high load fluctuation amplitude, the unloading rate, and the dynamic stress intensity factor (DSIF), which can be conductive to improving the impact damage resistance of the tool. [ABSTRACT FROM AUTHOR]

The influence mechanisms of the contact area on the sliding friction behavior are still not entirely clear, and determining the intrinsic correlation between friction and the contact area at the nanoscale remains a challenge. In this study, the area-dependent friction behavior is investigated based on the model of an annular graphene flake sliding on a supported graphene substrate via molecular dynamics simulations. The results demonstrate that the friction force decreases with the increasing flake area, i.e., the nanoscale friction is inversely correlated with the contact area. This contradicts the everyday experience, wherein an increase in the contact area leads to an increase in friction. The more pronounced edge effects and elastic deformation are considered the main reasons for the larger friction force of a smaller flake on the substrate. The study results are useful for comprehensively understanding the friction behavior of two-dimensional materials and extending their application fields. [ABSTRACT FROM AUTHOR]

Ti based composite coating with a micron-sized TiN and nano-sized TiB was successfully fabricated. During tribocorrosion, the corrosion rate due to stress (Δ C S ) of the 1600 W and 2400 W samples increased gradually to 304.42 μm/yr and 272.38 μm/yr, and the wear rate due to stress (Δ W S ) decreased gradually to −463.69 μm/yr and −794.84 μm/yr, respectively. The main reason is that a deeper deformation zone was formed at the subsurface of plastic 2400 W sample as stress increases to 300 MPa, which not only inhibits the local strain evolution to cracks but also accumulates dislocations and forms nanocrystals to maintain high-strain hardening. • Ti-based composite coating with a network structure was successfully fabricated. • The tribocorrosion behavior of the coating under different constant stress is quantitatively investigated. • The mechanisms of accelerated corrosion and inhibited wear under the coupled environment are analyzed. [ABSTRACT FROM AUTHOR]

Developing high-performance electromagnetic interference (EMI) shielding materials with robust microwave attenuation capabilities and structural stability remains a formidable challenge to enhance their practical adaptability in everyday scenarios. In this study, we have successfully fabricated a gradient structured MXene-based composite film tailored for high-performance EMI shielding. Initially, a hybrid MoS 2 @MXene material featuring heterointerfaces is synthesized, which exhibits exceptional electromagnetic wave (EMW) absorption capabilities. Subsequently, a gradient structured multi-layer film is engineered using a layer-by-layer casting approach, gradually increasing the MXene content in the MoS 2 @MXene/MXene/aramid nanofiber composite. This composite film is purposefully designed to employ an "absorb-reflect-reabsorb" EMI shielding mechanism, resulting in reduced reflection power. The resultant composite film achieves an impressive EMI SE of 50.9 dB, coupled with remarkable structural stability persisting through 500 folding cycles. This study presents a viable and potent strategy for developing flexible, absorption-dominant EMI shielding materials. [Display omitted] • MoS 2 @MXene has been synthesized for electromagnetic wave absorbing. • A gradient MoS 2 @MXene/MXene/ANF composite film is constructed. • The gradient film reaches 50.9 dB of SE T while SE R is only 8.0 dB. [ABSTRACT FROM AUTHOR]

The characteristic of joint consumption creates complex linkage between metal markets, which helps provide new insights into the energy-metal nexus relationship. To this end, this paper analyzes the price spillover effects between clean energy metals with joint consumption properties and further captures clean energy market's role in this dynamic connectedness. The results show that: (1) There are significant spillover effects within the clean energy metal markets, mainly dominant by short-term factors. The price fluctuation risk in the wind energy metal markets is more easily transmitted than the solar energy metal markets. (2) Copper and Tellurium markets are the main sources of risk in the spillover network of solar energy metal markets, while Copper and Aluminum act as the centers of risk transmission in the spillover network of wind energy metal markets. (3) Clean energy markets significantly impact the spillovers of metal markets, and exhibit non-linear movements, altering the spillover roles of some metal markets in the spillover network. Our findings reveal the system-wide price fluctuation patterns in clean energy metal markets, helping provide targeted recommendations in the risk management of energy-metal nexus system. • Significant short-term spillover effects exist within the clean energy metal markets. • The price fluctuation risk in the wind energy metal markets is more easily transmitted than the solar energy metal markets. • The spillover behaviours between clean energy metal markets exhibit less sensitivity to financial market fluctuations. • Clean energy markets strongly impact the spillover effects of joint-consumed metal markets in a non-linear way. [ABSTRACT FROM AUTHOR]

Support vector machine (SVM), being considered one of the most efficient tools for classification, has received widespread attention in various fields. However, its performance is hindered when dealing with large-scale pattern classification tasks due to high memory requirements and running very slow. To address this challenge, we construct a novel sparse and robust SVM based on our newly proposed capped squared loss (named as L c s l -SVM). To solve L c s l -SVM, we first focus on establishing optimality theory of L c s l -SVM via our defined proximal stationary point, which is convenient for us to efficiently characterize the L c s l support vectors of L c s l -SVM. We subsequently demonstrate that the L c s l support vectors comprise merely a minor fraction of entire training data. This observation leads us to introduce the concept of the working set. Furthermore, we design a novel subspace fast algorithm with working set (named as L c s l -ADMM) for solving L c s l -SVM, which is proven that L c s l -ADMM has both global convergence and relatively low computational complexity. Finally, numerical experiments show that L c s l -ADMM has excellent performances in terms of getting the best classification accuracy, using the shortest time and presenting the smallest numbers of support vectors when solving large-scale pattern classification problems. • We establish a novel SVM model called capped squared loss SVM. • We prove the optimality theory for capped squared loss SVM. • We propose a novel subspace fast algorithm with working set to address the capped squared loss SVM. • We demonstrate that our algorithm can efficiently solve the capped squared loss SVM. [ABSTRACT FROM AUTHOR]

The SWI/SNF2 chromatin remodeling factor decreased DNA methylation 1 (DDM1) is essential for the silencing of transposable elements (TEs) in both euchromatic and heterochromatic regions. Here, we determined the cryo-EM structures of DDM1-nucleosomeH2A and DDM1-nucleosomeH2A.W complexes at near-atomic resolution in the presence of the ATP analog ADP-BeFx. The structures show that nucleosomal DNA is unwrapped more on the surface of the histone octamer containing histone H2A than that containing histone H2A.W. DDM1 embraces one DNA gyre of the nucleosome and interacts with the N-terminal tails of histone H4. Although we did not observe DDM1-H2A.W interactions in our structures, the results of the pull-down experiments suggest a direct interaction between DDM1 and the core region of histone H2A.W. Our work provides mechanistic insights into the heterochromatin remodeling process driven by DDM1 in plants. [Display omitted] • NucleosomeH2A adopts a more unwrapped conformation compared with nucleosomeH2A.W • DDM1 embraces one DNA gyre of the bound nucleosome • DDM1 likely interacts with the core region of histone H2A.W Zhang et al. determined the cryo-EM structures of DDM1-nucleosmeH2A/H2A.W complexes. The structures reveal the conformational difference between DDM1-nucleosmeH2A and DDM1-nucleosmeH2A.W and provide insights into the interactions between DDM1 and the nucleosome. [ABSTRACT FROM AUTHOR]

To better understand the seepage field in tailings dam with a drainage structure that combines drainage mat, drainage tube, and geotextile, an equivalent seepage analysis method for the drainage structure is presented. In the method, an equivalent drainage structure is suggested to replace the original drainage. It has enough size to be easily presented in the three-dimensional (3d) model of a tailings dam. According to a back analysis procedure using the quasi-3d models of a tailings dam with original and equivalent drainage structures, the material properties of the equivalent drainage structure can be obtained under the principle of drainage capacity equivalence. It is demonstrated that the suggested method is accurate enough to capture the seepage field in a tailings dam based on comparing the calculated and measured phreatic lines in a tailings dam for verification. Then, the method is employed to investigate the seepage field in a tailings dam in China for a case study. The rise of water level, damage of drainage structure, or increase of tailings discharge speed and time will lift up phreatic line. After terminating tailings discharge, phreatic line will first rise and then fall. The effect of tailings discharge on phreatic line will almost disappear after terminating tailings discharge for 24 h. [ABSTRACT FROM AUTHOR]

In this paper, we consider a class of wave equations of Hartree type on a bounded smooth convex domain with Dirichlet boundary condition. By applying the standard semigroup theory, we get the local existence result. Using potential well theory, we derive the condition of global existence of weak solutions. With the help of potential well theory and convexity method, we give blowup results for solutions when the initial energy is nonnegative or negative. [ABSTRACT FROM AUTHOR]

Introduction: Pro-inflammatory cytokines are responsible for initiating an effective defense against exogenous pathogens, and their regulation has a vital role in maintaining physiological homeostasis. The involvement of pro-inflammatory cytokines in pathological conditions have been explored in great detail, however, studies investigating metabolic pathways associated with these cytokines under normal homeostatic conditions are scarce. Objectives: The aim of the current study was to identify metabolites and metabolic pathways associated with circulating pro-inflammatory cytokines under homeostatic conditions using a metabolomics approach. Methods: The study participants (n = 133) were derived from the Newfoundland Osteoarthritis Study (NFOAS) and the Complex Diseases in the Newfoundland population: Environment and Genetics (CODING) study. Plasma concentrations of cytokines including tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-1 beta (IL-1β), and macrophage migration inhibitory factor (MIF) were assessed by enzyme-linked immunosorbent assay. Targeted metabolomic profiling on fasting plasma samples was performed using Biocrates MxP® Quant 500 kit which measures a total of 630 metabolites. Associations between natural log-transformed metabolite concentrations and metabolite sums/ratios and cytokine levels were assessed using linear regression with adjustment for age, sex, body mass index (BMI), and osteoarthritis status. Results: Seven metabolites and 11 metabolite sums/ratios were found to be significantly associated with TNF-α, IL-1β, and MIF (all p ≤ 5.13 × 10− 5) after controlling multiple testing with Bonferroni method, indicating the association between glutathione (GSH), polyamine, and lysophosphatidylcholine (lysoPC) synthesis pathways and these pro-inflammatory cytokines. Conclusion: GSH, polyamine, and lysoPC synthesis pathways were positively associated with circulating TNF-α, IL-1β, and MIF levels under homeostatic conditions. [ABSTRACT FROM AUTHOR]

The finite-time synchronization of fractional-order multi-weighted complex networks (FMCNs) with uncertain parameters and external disturbances is studied. Firstly, based on fractional calculus characteristics and Lyapunov stability theory, quantized controllers are designed to guarantee that FMCNs can achieve synchronization in a limited time with and without coupling delay, respectively. Then, appropriate parameter update laws are obtained to identify the uncertain parameters in FMCNs. Finally, numerical simulation examples are given to validate the correctness of the theoretical results. [ABSTRACT FROM AUTHOR]

Recommender systems are the systems that take advantages of users' historical behavior data to model the users' behavior preferences to recommend things to users. However, recommender systems often suffer from data sparsity issues, due to a lack of adequate preference data, which degrades the overall recommendation performance. Cross-domain recommender systems were later developed to transfer knowledge from the auxiliary domain with rich user behavior data to help improve the recommendation performance of the target domain. Most of the existing cross-domain recommendation methods assume that overlapping entities are shared between domains, and then use them as a bridge for knowledge transfer across domains. However, this assumption does not universally hold. In this scenario, the existing cross-domain recommendation methods rarely consider the distribution inconsistency between domains, but directly transfer the cluster-level knowledge learned from the auxiliary domain to the target domain, which cannot ensure the consistency of knowledge transfer. Therefore, when overlapping entities are not shared between domains, how to effectively transfer knowledge is a key challenge for cross-domain recommender systems. Here, we propose a Cross-Domain Collaborative Recommendation without Overlapping Entities Based on Domain Adaptation, called CCR-DA. We find that CCR-DA can simultaneously achieve the consistency of knowledge transfer and avoid negative transfer in a unified framework. Specifically, we first seamlessly integrate the Maximum Mean Discrepancy (MMD) regularization constraints into the weighted collective matrix tri-factorization to reduce the distribution discrepancy between domains, so as to ensure the consistency of knowledge transfer. Then we further incorporate the graph regularization of user and item graphs from the two domains into the above framework to maintain the inherent geometric structure of each domain, thereby avoiding negative transfer. Experimental results on three categories of cross-domain recommendation tasks constructed from six real-world data sets show that our CCR-DA method outperforms. [ABSTRACT FROM AUTHOR]

During the construction of coal mine laneway, due to the particularity of the geographical location and structure of the laneway, its accidents often occur, causing great trouble to the personal and property safety of the construction personnel. Therefore, according to the environmental characteristics of the coal mine tunnel and the positive correlation between the phase envelope range and the wavelength, this paper proposes a structural design of the personnel positioning system of the coal mine tunnel based on the dual wavelength phase unwrapping, which combines the coherent detection structure with the dual wavelength phase measurement method in digital holography. In order to reduce false positives in the position information, the synthetic wavelength is used to increase the spread range of the phase. The experiment shows that this structure can reduce the false positioning without reducing the positioning accuracy, and the average double wavelength phase demodulation can reduce the positioning false alarm by 82.5%, which greatly improves the accuracy of the prediction of the tunnel construction safety, brings great protection to the personal and property safety of the tunnel construction personnel, and improves the mining efficiency of the coal mine. [ABSTRACT FROM AUTHOR]

Tripartite motif (TRIM) proteins are a multifunctional family of ubiquitin E3 ligases involved in multiple biological processes. Studies have shown that many TRIM proteins in mammals play vital roles in the host defense against viral pathogens. In the present study, we identified a novel TRIM gene (MnTrim-like) from the oriental river prawn, Macrobrachium nipponense. Predicted MnTrim-like protein contains the characteristic RING finger domain. MnTrim-like was abundantly distributed in hepatopancreas, intestine, stomach, and gills. Upon white spot syndrome virus (WSSV) challenge, transcripts of MnTrim-like in the stomach were significantly up-regulated. Knockdown of MnTrim-like increased the expression of VP28 and decreased the synthesis of several antimicrobial peptides, including two crustins and one anti-lipopolysaccharide factor. Besides, silencing of these three antimicrobial peptides (AMPs) led to an increase in the expression of VP28 and WSSV copies. Moreover, it was found that injection of recombinant MnTrim-like protein with WSSV could decrease the transcription of VP28 and the number of virus particles. These results suggest that this MnTrim-like may restrict WSSV infection by positively regulating the expression of AMPs with antiviral activities and directly interacting with viral components. This study will broaden our understanding about the function of TRIM in crustacean during viral infection. • The TRIM-like gene was induced by WSSV infection. • Knockdown of MnTrim-like increased the expression of VP28 and decreased the synthesis of several antimicrobial peptides. • Injection of recombinant MnTrim-like protein restricts the replication of WSSV in vivo. [ABSTRACT FROM AUTHOR]

Diffusio-osmosis is the interfacial transport induced by solute density gradient and plays an essential role in many micro/nanofluidic systems. Here, we report the molecular dynamics simulations of the diffusio-osmosis of oil–CO2 mixture in silica and calcite nanopores. We show that, under the high solute (CO2) density considered, although the enrichment of CO2 near calcite walls is substantially higher than that near silica walls, the diffusio-osmosis in calcite pores is only marginally stronger. This phenomenon is attributed to the significantly different molecular structures and hydrodynamic properties of interfacial fluids in the two pores caused by the CO2 adsorption on their walls, which is in turn traced to the different physical chemistry of the silica and calcite walls. Using continuum simulations parameterized by the diffusio-osmosis characteristics obtained in our molecular modeling, we show that, for the oil transport through slit pores driven by pressurized CO2, the diffusio-osmosis becomes important compared to the Poiseuille flow when the pore width decreases below a few tens of nanometers and its significance compared to the Poiseuille flow increases quadratically as the pore width decreases. [ABSTRACT FROM AUTHOR]

Representation learning over dynamic graphs has attracted much attention because of its wide applications. Recently, sequential probabilistic generative models have achieved impressive results because they can model data distributions. However, modeling the distribution of dynamic graphs is still extremely challenging. Existing methods usually ignore the mutual interference of stochastic states and deterministic states. Besides, the assumption that latent variables follow Gaussian distributions is usually inappropriate. To address these problems, we propose stochastic graph recurrent neural network (SGRNN), a sequential generative model for the representation learning over dynamic graphs. It separates stochastic states and deterministic states in the iterative process. To improve the flexibility of latent variables, we set the prior distribution and posterior distribution as semi-implicit distributions and propose DSI-SGRNN. In addition, to alleviate the KL-vanishing problem in SGRNN, a simple and interpretable structure is proposed based on the lower bound of KL-divergence. The proposed structure introduces a few extra parameters and can be implemented with a few lines of code modification. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

With the development of multisource satellite platforms and the deepening of remote sensing applications, the growing demand for high-spatial resolution and high-temporal resolution remote sensing images has aroused extensive interest in spatiotemporal fusion research. However, reducing the uncertainty of fusion results caused by sensor inconsistencies and input data preprocessing is one of the challenges in spatiotemporal fusion algorithms. Here, we propose a novel sensor bias correction method to correct the input data of the spatiotemporal fusion model through a machine learning technique learning the bias between different sensors. Taking the normalized difference vegetation index (NDVI) images with low-spatial resolution (MODIS) and high-spatial resolution (Landsat) as the basic data, we generated the neighborhood gray matrices from the MODIS image and established the image bias pairs of MODIS and Landsat. The light gradient boosting machine (LGBM) regression model was used for the nonlinear fitting of the bias pairs to correct MODIS NDVI images. For three different landscape areas with various spatial heterogeneities, the fusion of the bias-corrected MODIS NDVI and Landsat NDVI was conducted by using the spatiotemporal adaptive reflection fusion model (STARFM) and the flexible spatiotemporal data fusion method (FSDAF), respectively. The results show that the sensor bias correction method can enhance the spatially detailed information in the input data, significantly improve the accuracy and robustness of the spatiotemporal fusion technology, and extend the applicability of the spatiotemporal fusion models. [ABSTRACT FROM AUTHOR]

[Display omitted] • Nematode-infected wild house mice reflect type-1 vs type-2 immune bias seen in experimental whip- and pinworm infections. • Th1 expansion is accompanied by a rise in IL-10+ Th1 cells irrespective of infection status. • Elevated type-2 activity in pinworm infection is paired with expanded regulatory T cells. Infections with high doses of intestinal nematodes result in protective immunity based on robust type 2 responses in most mouse lines under laboratory conditions. Here, we report on cellular responses of wild house mice from northern Germany. We detected robust Th1 responses in wild house mice naturally infected with the whipworm Trichuris muris. In contrast, mice infected with pinworms (Syphacia, Aspiculuris) reported type-2 activity by elevated IgG1 levels and eosinophil counts, but also harbored high frequencies of Foxp3+ regulatory T cells, suggesting that natural whip- and pinworm infections induce distinct immunoregulatory as well as effector profiles. [ABSTRACT FROM AUTHOR]

Contraindications for surgery: Surgery is contraindicated in patients to whom general contraindications for surgery apply, inactive asymptomatic cysts, difficult to access cysts, and very small cysts. Inclusion criteria: (1) patients with hepatic cystic echinococcosis who are able to tolerate surgery and routinely undergo open abdomen surgical treatment;(2) the case data is complete, and no important data is missing. Exclusion criteria: (1) patients with hepatic cystic echinococcosis who underwent emergency surgery (most of whom had hydatid complications, such as rupture);(2) patients who underwent surgery at other sites except for liver hydatid;(3) Laparoscopic treatment cases; (4) abnormal discharge patients. [Extracted from the article]

This work is devoted to studying a wave equation with degenerate nonlocal nonlinear damping and source terms. By potential well theory, we show the asymptotic stability of energy in the presence of a degenerate damping of polynomial type when the initial energy is small. Also, we firstly derive some sufficient conditions on initial data which lead to finite time blow-up. [ABSTRACT FROM AUTHOR]

Smart Float is a new multi-modal underwater vehicle, a tool for ocean observation and detection, whose performance is limited by its underwater voyage distance and endurance like most underwater vehicles. The utilization of marine energy provides an ideal way to overcome these limitations. In this paper, an external ocean thermal energy power generation module is developed for Smart Float, which can be used for multiple times of energy storage and power generation and is expected to be further applied to small and medium-sized underwater vehicles. The integration of the proposed device will cause changes in the counterweight characteristic, hydrodynamic characteristic, and heat transfer characteristic of the vehicle, which are deeply analyzed in this study, and adaptive modification solutions are proposed according to the analysis results. Finally, a prototype of Smart Float integrating the proposed device was deployed in the South China Sea to perform a sea trial, to test its performance in thermal energy utilization. According to the results, the device generates 1.341 Wh in a profile diving to 700 m, with the maximum single-profile generation of 1.487 Wh, the average electrical energy of 1.368 Wh, and the hydraulic-to-electric efficiency of about 60% in the power generation stage, which verifies its excellent performance in thermal energy utilization. This study realizes the integration of thermal energy power generation modules into an underwater vehicle for the first time, exploring a new way to improve the endurance and self-sustainability of commercial underwater vehicles. [ABSTRACT FROM AUTHOR]