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To understand the tribocorrosion mechanism of TiB2–Ni coating doped with La2O3 in the deep ocean, the wear and corrosion test of La2O3–TiB2–Ni under various hydrostatic pressures was conducted and discussed in 3.5 wt % NaCl solution. The results indicate that the tribocorrosion mechanism of the La2O3–TiB2–Ni coating transitions from abrasive wear with corrosion under 0.1 MPa to abrasive wear with corrosion and adhesive wear under high hydrostatic pressure. The La2O3–TiB2–Ni coating shows significant enhancements in wear resistance and anti-friction properties compared to the TiB2–Ni coating. As the hydrostatic pressure increases from 0.1 MPa to 30 MPa, the self-corrosion current density experiences an approximate increase of 43.6 μA/cm2.

To enhance the tribocorrosion resistance of 7075-T6 aluminum alloy in deep sea environments, TiB2–Ni coatings with varying La2O3 content were deposited on 7075-T6 aluminum alloy substrates using plasma spray technology. The effects of different La2O3 contents on the organization, structure, and properties of the coatings were analyzed. The results indicated that La2O3 incorporation suppressed brittle phase formation such as Ni3B; 1.0 wt% La2O3 addition reduced Ni3B by 16.9%. The coating's corrosion resistance significantly improved with La2O3 doping - the self-corrosion current density of the 1.0 wt% La2O3-doped coating decreased from 71.2 nA/cm2 to 30.2 nA/cm2.

Abstract The human oral microbiome harbors one of the most diverse microbial communities in the human body, playing critical roles in oral and systemic health. Recent technological innovations are propelling the characterization and manipulation of oral microbiota. High-throughput sequencing enables comprehensive taxonomic and functional profiling of oral microbiomes. New long-read platforms improve genome assembly from complex samples. Single-cell genomics provides insights into uncultured taxa. Advanced imaging modalities including fluorescence, mass spectrometry, and Raman spectroscopy have enabled the visualization of the spatial organization and interactions of oral microbes with increasing resolution. Fluorescence techniques link phylogenetic identity with localization. Mass spectrometry imaging reveals metabolic niches and activities while Raman spectroscopy generates rapid biomolecular fingerprints for classification. Culturomics facilitates the isolation and cultivation of novel fastidious oral taxa using high-throughput approaches. Ongoing integration of these technologies holds the promise of transforming our understanding of oral microbiome assembly, gene expression, metabolites, microenvironments, virulence mechanisms, and microbe-host interfaces in the context of health and disease. However, significant knowledge gaps persist regarding community origins, developmental trajectories, homeostasis versus dysbiosis triggers, functional biomarkers, and strategies to deliberately reshape the oral microbiome for therapeutic benefit. The convergence of sequencing, imaging, cultureomics, synthetic systems, and biomimetic models will provide unprecedented insights into the oral microbiome and offer opportunities to predict, prevent, diagnose, and treat associated oral diseases.

The permeability, heat conductivity, and reaction rate will be varied with the change of natural gas hydrate saturation when thermal fluid is injected into the natural gas hydrate reservoirs. In order to characterize the variation of the physical field parameters with hydrate saturation, DDF-LBM was applied to simulate the hydrate dissociation process by thermal fluid injection under pore-scale modelling. Based on the forced conjugate heat transfer case, the relaxation frequency of the thermal lattice in the pores is corrected. Based on the P-T phase equilibrium relationship of hydrates and considering the heat absorbed by the hydrate reaction, the solid–liquid state of the hydrate lattice is judged in real time, and the dynamic simulation of the heat flow solidification multi-physics field is realized. The simulation results show that the dissociation rate of the hydrates by thermal fluid injection was higher than that by heating the hydrate surface alone and was positively correlated with the hydrate saturation. On the basis of the above results, this paper provided exponential fitting equations between different hydrate saturations and average permeability, effective thermal conductivity, and inherent reaction rate. The fitting results show that saturation has a negative correlation with relative permeability and effective thermal conductivity, and a positive correlation with the inherent reaction rate. The above results can provide a reference basis for accurately describing the heat and mass transfer of natural gas hydrate under the macroscale.

Abstract Acquisition of new stem cell fates relies on the dissolution of the prior regulatory network sustaining the existing cell fates. Currently, extensive insights have been revealed for the totipotency regulatory network around the zygotic genome activation (ZGA) period. However, how the dissolution of the totipotency network is triggered to ensure the timely embryonic development following ZGA is largely unknown. In this study, we identify the unexpected role of a highly expressed 2-cell (2C) embryo specific transcription factor, ZFP352, in facilitating the dissolution of the totipotency network. We find that ZFP352 has selective binding towards two different retrotransposon sub-families. ZFP352 coordinates with DUX to bind the 2C specific MT2_Mm sub-family. On the other hand, without DUX, ZFP352 switches affinity to bind extensively onto SINE_B1/Alu sub-family. This leads to the activation of later developmental programs like ubiquitination pathways, to facilitate the dissolution of the 2C state. Correspondingly, depleting ZFP352 in mouse embryos delays the 2C to morula transition process. Thus, through a shift of binding from MT2_Mm to SINE_B1/Alu, ZFP352 can trigger spontaneous dissolution of the totipotency network. Our study highlights the importance of different retrotransposons sub-families in facilitating the timely and programmed cell fates transition during early embryogenesis.

In this study, H _2 C _2 O _4 , H _2 SO _4 , HNO _3 , and HCl were used to etch the TA2 titanium matrix at the same concentration and temperature, and the effects of different acid etching methods on the properties of the titanium matrix and Ru-Ti electrode were investigated. The surface morphology of the titanium substrate and anode after acid etching was observed by scanning electron microscopy (SEM), while the electrochemical performance of the anode was determined by cyclic voltammetry (CV), linear sweep voltammetry (LSV), and tafel plots. SEM observations showed that H _2 C _2 O _4 had the best etching effect on the titanium substrate, as the scratches were uniform, and the surface cracks of the prepared anode reached 4–6 μ m; Analysis of the CV curves revealed that the Ti/RuO _2 -TiO _2 anode prepared by H _2 C _2 O _4 etching had the highest surface charge capacity (172 mC) compared to the anodes prepared by other acid etchings, while the LSV curves showed that the Ti/RuO _2 -TiO _2 anode after H _2 C _2 O _4 etching had the lowest polarization potential (1.232 V). Tafel curve analysis revealed that the corrosion potential of the Ti anode prepared by H _2 C _2 O _4 etching was 0.203 V, and the self-corrosion current density was −5.11 A cm ^−2 , indicating that the corrosion resistance of the Ti anode prepared by H _2 C _2 O _4 treatment is the weakest. X-ray photoelectron spectroscopy analysis showed that the electrode surface changed from Ru4+ to Ru3+ after corrosion, with the Ti2p spectra showing similar transition from Ti4+ to Ti3+.

The most commonly diagnosed and most lethal subtype of lung cancer is lung adenocarcinoma (LUAD). Therefore, more detailed understanding of the potential mechanism and identification of potential targets of lung adenocarcinoma is needed. A growing number of reports reveals that long non-coding RNAs (lncRNAs) play crucial roles in cancer progression. In present study, we found that lncRNA LINC00115 was upregulated in LUAD tissues and cells. Functional studies revealed that LINC00115 knockdown inhibits the proliferation, growth, invasion, and migration of LUAD cells. Mechanically, we indicated that miR-154-3p is target microRNA of LINC00115, and the effect of downregulated LINC00115 on LUAD cells was partially reversed by the miR-154-3p antisense oligonucleotide (ASO-miR-154-3p). Further investigation revealed that Specificity protein 3 (Sp3) directly interacted with miR-154-3p, and the Sp3 level was positively correlated with the LINC00115 expression. Rescue experiments further showed that Sp3 overexpression partially restored the effect of downregulated LINC00115 on LUAD cells. Similarly, in vivo experiments confirmed that downregulated LINC00115 inhibited xenograft growth and Sp3 expression. Our results demonstrated that LINC00115 knockdown inhibited LUAD progression via sponging miR-154-3p to modulate Sp3 expression. These data indicate that the LINC00115/miR-154-3p/Sp3 axis can be a potential therapeutic target of LUAD.

Over the past decade, the association between oral health, intestinal microbiota, and systemic diseases has been further validated. Some oral microbial species have been isolated from pathological intestine mucosa or feces and identified as biomarkers for intestinal diseases. A small proportion of oral microbiome passes through or colonizes the lower gastrointestinal tract, even in healthy individuals. Opportunistic pathogens from the oral cavity may expand and participate in the occurrence and progression of intestinal diseases when the anatomical barrier is disrupted. These disruptors interact with the intestinal microbiota, disturbing indigenous microorganisms, and mucosal barriers through direct colonization, blood circulation, or derived metabolite pathways. While interacting with the host’s immune system, oral-derived pathogens stimulate inflammation responses and guide the transition of the intestinal microenvironment from a healthy state to a pre-disease state. Therefore, the oral-gut microbiome axis sheds light on new clinical therapy options, and gastrointestinal tract ecology balance necessitates simultaneous consideration of both oral and gut microbiomes. This review summarizes possible routes of oral microbes entering the intestine and the effects of certain oral bacteria on intestinal microbiota and the host’s immune responses.

ObjectivesGiven that the histological features of the thyroid parenchyma in patients with Hashimoto's thyroiditis (HT) differ from those of the normal thyroid gland, HT may affect the effectiveness of ultrasound-guided microwave ablation (MWA) for benign thyroid nodules (BTNs). The present study aimed to compare the effectiveness of MWA for the treatment of BTNs in patients with both BTNs and HT and those with BTNs and normal thyroid function, based on changes in the volume reduction ratio (VRR) of the BTNs.MethodsPatients who had achieved a VRR ≥50% after MWA for BTN (July 2020–June 2021), followed up for 12 months, and their data were retrospectively analyzed.ResultsA total of 213 nodules were identified in 185 patients, including 167 in the “BTN” group and 46 in the “BTN + HT” group. A comparison of the fitting curves for VRR–follow-up time revealed that the VRR increased with time after MWA, although the relationship was nonlinear. Piece-wise linear regression model analysis of the threshold effect of VRR and follow-up time in the two groups indicated that the inflection point of the “BTN” group occurred at 2.1 months: VRR increased fastest within 2.1 months of MWA (rate of change: 32.9% per month; P

Cleft lip and palate (CLP) is the most common congenital facial malformation and has a significant developmental, physical, and psychological impact on those with the deformity and their families. Risk factors contributing to CLP may conclude as genetic factors and environmental factors. The anatomical and morphological abnormalities related to CLP are favorable for dental plaque accumulation on the tooth surface. Therefore, patients with CLP undergo poorer oral hygiene and higher susceptibility to dental caries and periodontitis. In this review, we aim to conclude and update probable causes underlying the association between CLP and poor oral health and provide novel ideas of targeted early prevention for such oral diseases.

Oral streptococci are gram-positive facultative anaerobic bacteria that are normal inhabitants of the human oral cavity and play an important role in maintaining oral microecological balance and pathogenesis. Transposon mutagenesis is an effective genetic manipulation strategy for studying the function of genomic features. In order to study cariogenic related genes and crucial biological element genes of oral Streptococcus, transposon mutagenesis was widely used to identify functional genes. With the advent of next-generation sequencing (NGS) technology and the development of transposon random mutation library construction methods, transposon insertion sequencing (TIS) came into being. Benefiting from high-throughput advances in NGS, TIS was able to evaluate the fitness contribution and essentiality of genetic features in the bacterial genome. The application of transposon mutagenesis, including TIS, to oral streptococci provided a massive amount of valuable detailed linkage data between genetic fitness and genetic backgrounds, further clarify the processes of colonization, virulence, and persistence and provides a more reliable basis for investigating relationships with host ecology and disease status. This review focuses on transposon mutagenesis, including TIS, and its applicability in oral streptococci.

Protein lysine malonylation (Kmal) is a novel post-translational modification (PTM) that regulates various biological pathways such as energy metabolism and translation. Malonylation in prokaryotes, however, is still poorly understood. In this study, we performed a global Kmal analysis of the cariogenic organism Streptococcus mutans by combining antibody-based affinity enrichment and high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis. Altogether, 392 malonyllysine sites in 159 proteins were identified. Subsequent bioinformatic analysis revealed that Kmal occurs in proteins involved in various metabolic pathways including translation machinery, energy metabolism, RNA degradation, and biosynthesis of various secondary metabolites. Quantitative analysis demonstrated that Kmal substrates were globally altered in the biofilm growth state compared to the planktonic growth state. Furthermore, a comparative analysis of the lysine malonylome of our study with previously determined lysine acetylome in S. mutans revealed that a small proportion of Kmal sites overlapped with acetylated sites, whereby suggesting that these two acylations have distinct functional implications. These results expand our knowledge of Kmal in prokaryotes, providing a resource for researching metabolic regulation of bacterial virulence and physiological functions by PTM.

Cervical cancer is one of the most common cancers among women in the world, over 570,000 patients are affected annually. Pathological examination for patients using Pap Smear becomes the mainstream of cervical cancer diagnoses. Accurate diagnoses and analyses largely rely on 3 factors: cell segmentation, feature extraction and selection as well as classification. Firstly, a 2-layer segmentation algorithm based on block Maximum Between-Class Variance (Otsu) and Gradient Vector Flow (GVF) Snake model is applied to obtain regions of interest (ROI). Then the features of chroma, shape and texture are extracted and selected for a better classification performance. The random forest algorithm based on Artificial Fish Swarms Algorithm (AFSA) is used to recognize and classify cervical epithelial cells. The proposed methods were tested on 200 cervical Pap Smear images. Experimental results show that cervical cells can be segmented with an effective segmentation result. The proposed feature selection method achieved an accuracy of 81.31% with the minimum feature number. The improved random forest algorithm with 2 and 7 classification under fivefold cross-validation reaches the highest classification accuracy (96.86%). Experimental results showed that the proposed method has obvious recognition advantages, and thus provides a practical classification frame for the diagnoses of cervical cancer.

This paper considers an inventory system consisting of one supplier and one retailer, and studies a joint inventory policy and transport capacity decision for this inventory system with carbon emissions. The joint decision simultaneously determines the reorder interval of the retailer and the number of the vehicles used to transport the product from the supplier to the retailer while minimizing the inventory replenishment related cost and the carbon emission cost. This paper considers the carbon emissions from holding and replenishing inventory at the retailer, and calculates the carbon emissions based on the reorder interval of the retailer and the number of the vehicles used to transport the product. This problem is formulated as a nonlinear mixed integer programming, and an algorithm is designed to solve the nonlinear mixed integer programming to optimality. The computational results show that the integrated model proposed in this paper can reduce the system-wide cost and the carbon emissions by 5.6% and 14.42% in average, respectively. For the cases that the product with low fixed ordering cost and the vehicle with high fuel consumption, the superiority of the integrated model is more prominent. Besides, the computational results also provide some other management insights.

The phenotypic traits of Streptococcus mutans, such as fluoride tolerance, are usually associated with genotypic alterations. The aim of this study was to identify adaptive mutations of S. mutans to gradient fluoride concentrations and possible relationships between the mutations and fluoride tolerance. We identified a highly resistant S. mutans strain (FR1000) with a novel single nucleotide polymorphism (SNP, −36G→T) in the promoter region of F0F1-ATPase gene cluster (SMU_1527-SMU_1534) resistant to 1,000 ppm fluoride using the whole-genome Illumina PE250 sequencing. Thus, a −36G→T F0F1-ATPase promoter mutation from the parental strain S. mutans UA159 was constructed and named UA159-T. qRT-PCR showed that the F0F1-ATPase gene expression of both FR1000 and UA159-T was up-regulated, and fluoride tolerance of UA159-T was significantly improved. Complementation of Dicyclohexylcarbodiimide (DCCD), a specific inhibitor of F0F1-ATPase, increased fluoride susceptibility of FR1000 and UA159-T. Intracellular fluoride concentrations of fluoride tolerance strains were higher compared to UA159 strain as demonstrated by 18F analysis. Further validation with rat caries models showed that UA159-T caused more severe caries lesions under fluoride exposure compared with its parental UA159 strain. Overall, the identified −36G→T mutation in the promoter region of F0F1-ATPase gene drastically contributed to the fluoride tolerance and enhanced cariogenicity of S. mutans. These findings provided new insights into the mechanism of microbial fluoride tolerance, and suggested F0F1-ATPase as a potential target for suppressing fluoride resistant strains.

In this paper, a portable residual stress tester and synchrotron radiation diffraction technique were used to measure the residual stress distribution of thick 2A14 aluminum alloy plates under different aging conditions after solution treatment. The stress changes after solution and aging were analyzed using metallographic structure observation, electron backscattered diffraction (EBSD), X-ray diffraction (XRD), and other characterization methods. The results show that after solution treatment at 500 °C and aging at 170 °C, the second phase precipitates, lattice distortion is released, and the stress level gradually decreases with aging time. The residual stress of the plate comprises compressive stress; there is stress concentration in the central area. The stress distribution obtained by the two residual stress calculation methods, cosα and sin2ψ, under different process conditions was consistent.

In this paper, based on in situ synchrotron radiation SAXS technology, the effects of stress field, temperature field and thermo-mechanical coupling conditions on the evolution of residual stress are discussed, respectively. The results show that the continuous increase of the external load led to the increase of the residual stress perpendicular to the tensile direction of the 2A14 aluminum alloy, and when the external load closed to the yield strength, the change of the residual stress was no longer significant. Under the action of temperature, the residual stress of 2A14 aluminum alloy reduced after the process of heating–holding–cooling. Under the action of thermo-mechanical coupling, the recovery effect of aluminum alloy was triggered, the energy storage of deformation was released, the lattice strain was reduced and the residual stress introduced by external load was reduced.

In this paper, the tribocorrosion behavior and synergistic effect of 7075-T6 aluminum alloy under different applied loads (100, 150, and 200 N) and sliding velocities (100, 150, and 200 rpm) were studied in a 3.5 wt.% NaCl solution. Tribocorrosion experiments were conducted in a tribobocorrosion system with pin-on-disc testing. The results show that the interaction between applied load and sliding velocity significantly affects the mechanical and electrochemical properties of 7075-T6 aluminum alloy. Increases in sliding velocity and applied load will accelerate the corrosion. Due to the synergistic effect of corrosion and wear, the wear rate is almost unchanged as the sliding velocity increases. When the applied load increased from 100 to 200 N, the wear rate increased from 1.97 × 10−5 to 2.08 × 10−5 mm3/N·m, and the delamination wear phenomenon was aggravated.

Cellulose is the most abundant source of biomass, which can be converted into monosaccharide or other chemical platform molecules for the sustainable production of chemicals and fuels. Acid catalysts can promote hydrolytic degradation of cellulose into valuable platform molecules, which is of great significance in the development of chemicals and biofuels. However, there are still some shortcomings and limitations of the catalysts for the hydrolytic degradation of cellulosic biomass. Heteropoly acid (HPA), as a green catalyst, seems to be more conducive to the degradation of cellulosic biomass due to its extreme acidity. HPAs can be designed in homogeneous and heterogeneous systems. Moreover, they can be easily separated from the products in both systems by a simple extraction process. According to the unique properties of HPAs (e.g., good solubility, high thermal stability, and strong acidity), using heteropoly acid-based catalysts to depolymerize and convert cellulose into value-added chemicals and biofuels has become one of the most remarkable processes in chemistry for sustainability. In this review, the characteristics, advantages, and applications of HPAs in different categories for cellulose degradation, especially hydrolysis hydrolytic degradation, are summarized. Moreover, the mechanisms of HPAs catalysts in the effective degradation of cellulosic biomass are discussed. This review provides more avenues for the development of renewed and robust HPAs for cellulose degradation in the future.

S-glutathionylation is an important post-translational modification (PTM) process that targets protein cysteine thiols by the addition of glutathione (GSH). This modification can prevent proteolysis caused by the excessive oxidation of protein cysteine residues under oxidative or nitrosative stress conditions. Recent studies have suggested that protein S-glutathionylation plays an essential role in the control of cell-signaling pathways by affecting the protein function in bacteria and even humans. In this study, we investigated the effects of S-glutathionylation on physiological regulation within Streptococcus mutans, the primary etiological agent of human dental caries. To determine the S-glutathionylated proteins in bacteria, the Cys reactive isobaric reagent iodoacetyl Tandem Mass Tag (iodoTMT) was used to label the S-glutathionylated Cys site, and an anti-TMT antibody-conjugated resin was used to enrich the modified peptides. Proteome profiling identified a total of 357 glutathionylated cysteine residues on 239 proteins. Functional enrichment analysis indicated that these S-glutathionylated proteins were involved in diverse important biological processes, such as pyruvate metabolism and glycolysis. Furthermore, we studied a thioredoxin-like protein (Tlp) to explore the effect of S-glutathionylation on interspecies competition between oral streptococcal biofilms. Through site mutagenesis, it was proved that glutathionylation on Cys41 residue of Tlp is crucial to protect S. mutans from oxidative stress and compete with S. sanguinis and S. gordonii. An addition rat caries model showed that the loss of S-glutathionylation attenuated the cariogenicity of S. mutans. Taken together, our study provides an insight into the S-glutathionylation of bacterial proteins and the regulation of oxidative stress resistance and interspecies competition.

The Nelson-Seiberg theorem relates R-symmetries to F-term supersymmetry breaking and provides a guiding rule for new physics model building beyond the Standard Model. A revision of the theorem gives a necessary and sufficient condition to supersymmetry breaking in models with polynomial superpotentials. This work revisits the theorem to include models with nonpolynomial superpotentials. With a generic R-symmetric superpotential, a singularity at the origin of the field space implies both R-symmetry breaking and supersymmetry breaking. We give a generalized necessary and sufficient condition for supersymmetry breaking which applies to both perturbative and nonperturbative models.

L-theanine is a nonprotein amino acid found in tea leaves and has been widely used as a safe food additive in beverages or foods because of its varied bioactivities. The aim of this study was to reveal the in vitro gastrointestinal protective effects of L-theanine in DSS-induced intestinal porcine enterocyte (IPEC-J2) cell models using molecular and metabolic methods. Results showed that 2.5% dextran sulfate sodium (DSS) treatment inhibited the cell proliferation of IPEC-J2 and blocked the normal operation of the cell cycle, while L-theanine pretreatment significantly preserved these trends to exert protective effects. L-theanine pre-treatment also up-regulated the EGF, CDC2, FGF2, Rb genes and down-regulated p53, p21 proliferation-related mRNA expression in DSS-treated cells, in accompany with p53 signaling pathway inhibition. Meanwhile, metabolomics analysis revealed that L-theanine and DSS treated IPEC-J2 cells have different metabolomic profiles, with significant changes in the key metabolites involved in pyrimidine metabolism and amino acid metabolism, which play an important role in nucleotide metabolism. In summary, L-theanine has a beneficial protection in DSS-induced IPEC-J2 cells via promoting proliferation and regulating metabolism disorders.

In this paper, we consider a distribution system consisting of one distribution center (DC), a set of ports, and a set of retailers, in which the product is distributed to the retailers from the DC through the ports by the water transport, and study inventory management for the distribution system with considering the effect of the free storage periods provided by the ports. Inventory management for the distribution system is to determine the order intervals of the DC and the retailers while minimizing the inventory ordering and holding costs. Focusing on stationary and integer-ratio policies, we formulate this inventory management problem as an optimization problem with a convex objective function and a set of integer-ratio constraints and present O(Nlog⁡N) time algorithm to solve the relaxed problem (relaxing the integer-ratio constraints) to optimality, where N is the number of the retailers. We prove that the relaxed problem provides a lower bound on average cost for all the feasible policies (containing dynamic policies) for this inventory management problem. By using the optimal solution of the relaxed problem, we build a stationary integer-ratio policy (a power-of-two policy) for this inventory management problem and prove that the power-of-two policy can approximate the optimal inventory policy to 83% accuracy.

In this paper, we consider an integrated supply chain network design problem, which incorporates inventory and pricing decisions into the capacitated facility location model. We assume that each warehouse has a capacity limitation that limits the average demand flowing through the warehouse and that the supplier can choose whether to satisfy each potential retailer’s demand. We formulate the problem as a nonlinear integer programming model and solve the model via a Lagrangian relaxation based approach. We develop an efficient algorithm to solve the subproblem that arises from the Lagrangian relaxation procedure. Finally, we conduct extensive computational experiments to test the performance of the algorithms proposed in this paper and provide the managerial insights based on the computational results.

Gait phase detection on different terrains is an essential procedure for amputees with a lower limb assistive device to restore walking ability. In the present study, the intent recognition of gait events on three terrains based on sEMG was presented. The class separability and robustness of time, frequency, and time-frequency domain features of sEMG signals from five leg and back muscles were quantitatively evaluated by statistical analysis to select the best features set. Then, ensemble learning method that combines the outputs of multiple classifiers into a single fusion-produced output was implemented. The results obtained from data collected from four human participants revealed that the light gradient boosting machine (LightGBM) algorithm has an average accuracy of 93.1%, a macro-F1 score of 0.929, and a calculation time of prediction of 15 ms in discriminating 12 different gait phases on three terrains. This was better than traditional voting-based multiple classifier fusion methods. LightGBM is a perfect choice for gait phase detection on different terrains in daily life.

The characteristics of soil moisture content (SMC) distribution in an area are necessarily analyzed for the design and construction of sponge cities. Combining remote sensing data with experimental data, this paper establishes a machine learning model to reveal the characteristics of SMC. Taking Beijing as an example, the SMC distribution was obtained and the characteristics were analyzed after training and validating. When comparing different machine learning methods, it can be concluded that the support vector classifier (SVC) method trained with remote sensing and grayscale data can achieve the highest accuracy (76.69%). The calculation results show that the districts with the highest and lowest SMC value are Xicheng District (19.94%) and Daxing District (11.04%), respectively, in Beijing. The mean SMC value of Beijing is 15.65%. The SMC distribution characteristic in Beijing shows that the soil in the west and north are relatively wet, while the soil in the east and south are relatively dry. Therefore, it is suggested that the timely monitoring of the SMC of vegetation covered areas at the north and west should be carried out. Water conservation facilities also need to be established with the development of city constructions in the south and east areas.

The title compound, C17H17NO3, prepared by the condensation reaction of 2-(1,3-dioxan-2-yl)aniline and salicylaldehyde, has an E conformation about the C=N bond. The six-membered O-heterocycle adopts a chair conformation, with the bond to the aromatic ring located at its equatorial position. The dihedral angle between the aromatic rings is 36.54 (9)°. There is an intramolecular N—H...O hydrogen bond forming an S(6) ring motif. In the crystal, molecules are linked by C—H...O hydrogen bonds, forming chains along the a-axis direction. Within the chains, there are C—H...π interactions involving adjacent molecules.

The title compound, C19H16F4O4, was prepared by the condensation reaction of 2,6-difluorobenzaldehyde and pentaerythritol. The whole molecule is generated by twofold rotational symmetry. The two six-membered O-heterocycles adopt chair conformations through a shared spiro-carbon atom that is located on the crystallographic twofold rotation axis. In this conformation, the two aromatic rings are located at the equatorial positions of the O-heterocycles. The conformation of this doubly substituted tetraoxaspiro system is chiral. In the crystal, molecules are linked by C—H...O hydrogen bonds, forming layers parallel to (100). These layers are linked by C—H...F hydrogen bonds into a three-dimensional structure.

The title compound, C26H22N4O5 (systematic name: methyl 2-ethoxy-1-{4-[2-(5-oxo-4,5-dihydro-1,2,4-oxadiazol-3-yl)phenyl]benzyl}-1H-1,3-benzodiazole-7-carboxylate ethyl acetate hemisolvate), was obtained via cyclization of methyl (Z)-2-ethoxy-1-{(2′-(N′-hydroxycarbamimidoyl)-[1,1′-biphenyl]-4-yl)methyl}-1H-benzo[d]imidazole-7-carboxylate with diphenyl carbonate. There are two independent molecules (A and B) with different conformations and an ethyl acetate solvent molecule in the asymmetric unit. In molecule A, the dihedral angle between the benzene ring and its attached oxadiazole ring is 59.36 (17); the dihedral angle between the benzene rings is 43.89 (15) and that between the benzene ring and its attached imidazole ring system is 80.06 (11)°. The corresponding dihedral angles in molecule B are 58.45 (18), 50.73 (16) and 85.37 (10)°, respectively. The C—O—C—Cm (m = methyl) torsion angles for the ethoxy side chains attached to the imidazole rings in molecules A and B are 93.9 (3) and −174.6 (3)°, respectively. In the crystal, the components are linked by N—H...N and C—H...O hydrogen bonds, generating a three-dimensional network. Aromatic π–π stacking interactions [shortest centroid–centroid separation = 3.536 (3)Å] are also observed.

Scanning electron microscopy (SEM) is a crucial tool in the field of materials science, providing valuable insights into the microstructural characteristics of materials. Unfortunately, SEM images often suffer from blurriness caused by improper hardware calibration or imaging automation errors, which present challenges in analyzing and interpretingmaterial characteristics. Consequently, rectifying the blurring of these images assumes paramount significance to enable subsequent analysis. To address this issue, we introduce a Material Images Deblurring Network (MIDNet) built upon the foundation of the Nonlinear Activation Free Network (NAFNet). MIDNet is meticulously tailored to address the blurring in images capturing the microstructure of materials. The key contributions include enhancing the NAFNet architecture for better feature extraction and representation, integrating a novel soft attention mechanism to uncover important correlations between encoder and decoder, and introducing newmulti-loss functions to improve training effectiveness and overallmodel performance. We conduct a comprehensive set of experiments utilizing the material blurry dataset and compare them to several state-of-theart deblurring methods. The experimental results demonstrate the applicability and effectiveness of MIDNet in the domain of deblurring material microstructure images, with a PSNR (Peak Signal-to-Noise Ratio) reaching 35.26 dB and an SSIM (Structural Similarity) of 0.946. Our dataset is available at: https://github.com/woshigui/MIDNet. [ABSTRACT FROM AUTHOR]

We consider the neural sparse representation to solve the Boltzmann equation with BGK and quadratic collision models, where a network-based ansatz that can approximate the distribution function with extremely high efficiency is proposed. Precisely, fully connected neural networks are employed in the time and physical space so as to avoid the discretization in space and time. Different low-rank representations are utilized in the microscopic velocity for the BGK and quadratic collision models, resulting in a significant reduction in the degree of freedom. We approximate the discrete velocity distribution in the BGK model using the canonical polyadic decomposition. For the quadratic collision model, a data-driven, SVD-based linear basis is built based on the BGK solution. All of these will significantly improve the efficiency of the network when solving the Boltzmann equation. Moreover, the specially designed adaptive-weight loss function is proposed with the strategies as multiscale input and Maxwellian splitting applied to further enhance the approximation efficiency and speed up the learning process. Several numerical experiments, including 1D wave and Sod tube problems and a 2D wave problem, demonstrate the effectiveness of these neural sparse representation methods. [ABSTRACT FROM AUTHOR]