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Upon rapid evolution, ChatGPT can now generate content that is linguistically accurate and logically sound, while sidestepping ethical, social and legal concerns. This research seeks to investigate whether ChatGPT will employ different pragmatic strategies in its responses to (im)polite questions. In our experiment, this AI-powered tool was instructed to answer 200 self-made questions over four (im)politeness levels, and the 200 responses were collected to go through linguistic and sentiment analysis. Triangulated data, together with typical examples, show that ChatGPT tends to give shorter and less positive answers to less polite questions, appearing to be less responsive when confronted with more blunt and offensive inquiries. This, to some extent, resembles how human beings react when treated impolitely. A tentative explanation may be that, given its nature as a large language model, ChatGPT mirrors human interaction in various scenarios, and draws on prevalent human communication tendencies. Thus, interacting with ChatGPT is more of a human-society interaction than human-machine communication in the real sense. Our research sheds light on the coined “human-machine pragmatics”, i.e. how humans can best communicate with computers for the best informative and affective outcomes. The implications for language education are also discussed in the end. [ABSTRACT FROM AUTHOR]

Barley is one of the most important cereal crops in the world, and its value as a food is constantly being revealed, so the research into and the use of barley germplasm are very important for global food security. Although a large number of barley germplasm samples have been collected globally, their specific genetic compositions are not well understood, and in many cases their origins are even disputed. In this study, 183 barley germplasm samples from the Shanghai Agricultural Gene Bank were genotyped using genotyping-by-sequencing (GBS) technology, SNPs were identified and their genetic parameters were estimated, principal component analysis (PCA) was preformed, and the phylogenetic tree and population structure of the samples were also analyzed. In addition, a genome-wide association study (GWAS) was carried out for the hulled/naked grain trait, and a KASP marker was developed using an associated SNP. The results showed that a total of 181,906 SNPs were identified, and these barley germplasm samples could be roughly divided into three categories according to the phylogenetic analysis, which was generally consistent with the classification of the traits of row type and hulled/naked grain. Population structure analysis showed that the whole barley population could be divided into four sub-populations (SPs), the main difference from previous classifications being that the two-rowed and the hulled genotypes were sub-divided into two SPs. The GWAS analysis of the hulled/naked trait showed that many associated loci were unrelated to the Nud/nud locus, indicating that there might be new loci controlling the trait. A KASP marker was developed for one exon-type SNP on chromosome 7. Genotyping based on the KASP assay was consistent with that based on SNPs, indicating that the gene of this locus might be associated with the hulled/naked trait. The above work not only lays a good foundation for the future utilization of this barley germplasm population but it provides new loci and candidate genes for the hulled/naked trait. [ABSTRACT FROM AUTHOR]

We propose a new method for estimating the distances of molecular clouds traced by CO line emission. Stars from 2MASS and Gaia EDR3 are selected as on-cloud stars when they are projected on a cloud. The background on-cloud stars have redder colors on average than the foreground stars. Instead of searching for stars projected away from the cloud, we employed the TRILEGA galaxy model to mimic the stellar population without cloud extinction along the sightline toward the cloud. Our method does not require an exact boundary of a cloud. The boundaries are highly variable and depend on the sensitivity of the molecular line data. For each cloud, we compared the distributions of on-cloud stars to the TRILEGAL stellar populations in the diagram of J−Ks color versus distance. The intrinsic J−Ks colors of main-sequence and evolved stars from TRILEGAL were considered separately, and they were used as the baseline for subtracting the observed J−Ks colors. The baseline-corrected J−Ks color was deployed with the Bayesian analysis and Markov chain Monte Carlo sampling to determine the distance at which the J−Ks color jump is largest. This method was successfully applied to measure the distances of 27 molecular clouds, which were selected from previously published cloud samples. By replacing TRILEGAL with the GALAXIA galaxy model, we were able to measure the distances for 21 of the 27 clouds. The distances of the 21 clouds based on the GALAXIA model agree well with those based on the TRILEGAL model. The distances of the 27 clouds estimated by this method are consistent with previous estimates. We will apply this new method to a larger region of the gaseous galactic plane, in particular, for the inner galactic region, where a region free of CO emission is hard to separate from the crowded field of clouds. [ABSTRACT FROM AUTHOR]

The utilization of ceramic aerogels is crucial in spacecraft thermal protection systems that necessitate exceptional high-temperature stability, mechanical robustness, and low thermal conductivity. The primary challenges hindering their implementation encompass inadequate mechanical robustness and high infrared radiation transparency. Herein, a biphasic nanorod encapsulation strategy is proposed to fabricate an Al 2 O 3 -TiO 2 nanorod aerogel (ATNA) with a hierarchical and anisotropic microstructure. The biphasic nanorod structure not only reduces the radiation heat transfer but also enhances the mechanical properties simultaneously. The primary compressive strain was borne by the intersecting Al 2 O 3 nanorods, while the interpenetrated TiO 2 nanorods served to reinforce and withstand partial stress at the joints. The ATNAs obtained exhibit an ultralow thermal conductivity (0.069 W·m−1·K−1 at 1100 °C), exceptional high stiffness (a specific compressive strength of 13.4 kN·m·kg−1), and remarkable thermal stability (1400 °C in air). The robust ATNAs can effectively meet the urgent demand for thermal insulation in high-temperature environments. • A biphasic nanorod encapsulation strategy is proposed to fabricate the Al2O3/ TiO2 ceramic aerogels. • Aerogels possessing the anisotropic and hierarchical structure. • The surface of Al2O3 nanorods is coated with TiO2 nanorods, which effectively absorb and reflect infrared heat radiation. • The derived aerogels exhibit high stiffness, low thermal conductivity and remarkable thermal stability. [ABSTRACT FROM AUTHOR]

Gelatin-based hydrogels with excellent mechanical properties and conductivities are desirable, but their fabrication is challenging. In this work, an innovative approach for the preparation of gelatin-based conductive hydrogels is presented that improves the mechanical and conductive properties of hydrogels by integrating Z–Gln–Gly into gelatin polymers via enzymatic crosslinking. In these hydrogels (Gel–TG–ZQG), dynamic π–π stacking interactions are created by the introduction of carbobenzoxy groups, which can increase the elasticity and toughness of the hydrogel and improve the conductivity sensitivity by forming effective electronic pathways. Moreover, the mechanical properties and conductivity of the obtained hydrogel can be controlled by tuning the molar ratio of Z–Gln–Gly to the primary amino groups in gelatin. The hydrogel with the optimal mechanical properties (Gel–TG–ZQG (0.25)) exhibits a high storage modulus, compressive strength, tensile strength, and elongation at break of 7.8 MPa at 10 °C, 0.15 MPa at 80% strain, 0.343 MPa, and 218.30%, respectively. The obtained Gel–TG–ZQG (0.25) strain sensor exhibits a short response/recovery time (260.37 ms/130.02 ms) and high sensitivity (0.138 kPa−1) in small pressure ranges (0–2.3 kPa). The Gel–TG–ZQG (0.25) hydrogel-based sensors can detect full-range human activities, such as swallowing, fist clenching, knee bending and finger pressing, with high sensitivity and stability, yielding highly reproducible and repeatable sensor responses. Additionally, the Gel–TG–ZQG hydrogels are noncytotoxic. All the results demonstrate that the Gel–TG–ZQG hydrogel has potential as a biosensor for wearable devices and health-monitoring systems. [ABSTRACT FROM AUTHOR]

The oxygen vacancies and surface oxygen species play pivotal roles in CO catalytic oxidation. In this study, Co3O4−CeO2 supported on resin based spherical activated carbon was fabricated and the effect of CeO2 on surface oxygen species was demonstrated through controlling various Ce contents. When Ce content was optimal (nCo : nCe=9), the maximum surface adsorbed oxygen content (60.3 %) is displayed and the catalyst achieved good CO conversion (T100=110 °C), water resistance and robust stability. DFT simulation calculation confirmed that the energy barriers of two transition states significantly decreased to 0.60 eV and 0.37 eV, respectively, with the addition of CeO2. The results indicate that the presence of CeO2 is conducive to the increasement of surface adsorbed oxygen content and optimal Co/Ce ratio is the most favorable for the CO oxidation. It is attributed to the visible decline of the energy barrier between oxygen vacancies and gas–phase oxygen at the Co3O4−CeO2 interface, and the process of oxygen vacancies replenishment could be more prone to occur at the interface. This study may provide a protocol for further improving surface species on supporting catalysts. [ABSTRACT FROM AUTHOR]

Laryngopharyngeal reflux disease (LPRD) is a condition characterized by the regurgitation of stomach and duodenal contents into the laryngopharynx, with variable and non-specific symptoms. Therefore, developing an accurate symptom scale for different regions is essential. Notably, the symptoms of "dryness and burning sensation in the laryngopharynx or mouth" are prevalent among the Chinese population but are often omitted from conventional symptom assessment scales, such as the Reflux Symptom Index (RSI) and Reflux Symptom Score-12 (RSS-12) scales. To address this gap, our study incorporated the symptoms into the RSI and RSS-12 scales, developing the RSI-10/RSS-13 scales. Afterward, we assessed the role of the new scale's reliability (Cronbach's α and test–retest reliability), construct validity (confirmatory factor analysis and confirmatory factor analysis), and diagnostic efficiency. Our study encompassed 479 participants (average = 39.5 ± 13.4 years, 242 female) and 91 (average = 34.01 ± 13.50 years, 44 female) completed 24 h MII-pH monitoring. The Cronbach's α values of 0.80 and 0.82 for the RSI-10 and RSS-13 scales, respectively. RSI-10 and RSS-13 exhibited strong test–retest reliability (ICCs = 0.82–0.96) and diagnostic efficacy (AUC = 0.84–0.85). Furthermore, the factor analysis identified the RSS-13 and its three sub-scales (ear-nose-throat, digestive tract, respiratory tract) exhibited good to excellent structural validity (χ2/df = 1.95, P < 0.01; CFI = 0.95, RMSEA = 0.06, SRMR = 0.05). The AUC optimal thresholds for the RSI-10 and RSS-13 in the Chinese population were 13 and 36, respectively. Besides, the inclusion of the new item significantly improved the diagnostic efficiency of the RSI scale (P = 0.04), suggesting that RSI-10 holds promise as a more effective screening tool for LPRD, and global validation is needed to demonstrate the impact of this new symptom on the diagnosis of LPRD. [ABSTRACT FROM AUTHOR]

The charging coil plays an important role in the wireless charging system system. However, there are still some problems in the design of the wireless charging coil, such as the low coupling coefficient. In order to improve the coupling effect, this paper proposes an optimized design scheme for the metal shielding layer structure of DD coil. Firstly, the influence of the structure size of DD coil metal plate on the coupling coefficient is studied by the mathematical modeling analysis. Futhermore, the maxwell simulation is used to study the metal plate coupling coefficients with varying structure sizes, addressing receiving uniformity issues. The optimal size of the shielding layer is designed for optimal magnetic coupling in wireless charging. Finally, this paper validates the feasibility of the improved metal shielding layer through experiments. The research in this paper may have a reference role in the wireless charging system of electric vehicles. [ABSTRACT FROM AUTHOR]

More than 100 tidal disruption events (TDEs) have been detected at multiple bands, which can be viewed as extreme laboratories to investigate the accretion physics and gravity in the immediate vicinity of massive black holes. Future transient surveys are expected to detect several tens of thousands of TDEs, among which a small fraction may be strongly gravitationally lensed by intervening galaxies. In this paper, we statistically estimate the detection rate of lensed TDEs, with dependence on the limiting magnitude of the transient all-sky surveys searching for them. We find that the requisite limiting magnitude for an all-sky transient survey to observe at least 1 yr−1 is ≳21.3, 21.2, and 21.5 mag in the u, g, and z bands, respectively. If the limiting magnitude of the all-sky survey can reach ∼25–26 mag in the u, g, and z bands, the detection rate can be up to about several tens to hundreds per year. The discovery and identification of the first image of the lensed TDE can be taken as an early warning of the second and other subsequent images, which may enable detailed monitoring of the pre-peak photometry and spectroscopy evolution of the TDE. The additional early-stage information may help to constrain the dynamical and radiation processes involved in the TDEs. [ABSTRACT FROM AUTHOR]

Cloud medical treatment provides real-time data sharing in a cost-effective method, making it more practical to create, collect and manage vast amounts of personal health records (PHR) of patients. However, health information is considered highly sensitive. How to securely store and dynamically process massive patients' PHR data in a public cloud environment has become one of the most important challenges. Therefore, we introduce a novel solution to the problems of privacy exposure, data security and flexible access of storage modules in medical systems. In this paper, we present a privacy-preserving certificateless broadcast encryption with authorization for the PHR system, which is the best approach to effectively solve the above problems and avoid key escrow. In our work, users (patients) outsource their encrypted data to the cloud server and reallocate data accessing rights of recipients through an authorization set, sharing with a group of authorized receivers (doctors) in a secure and efficient manner. In addition, it is shown to be capable of achieving both plaintext confidentiality and receiver anonymity under the random oracle model. Moreover, the experimental evaluation shows that the proposed scheme enjoys low computational and communication overhead, indicating the feasibility and practicality of the scheme. [ABSTRACT FROM AUTHOR]

As the global human population continues to increase, the use of saline–alkali land for food production is an important consideration for food security. In addition to breeding or cultivating salt-tolerant crop varieties, microorganisms are increasingly being evaluated for their ability to improve plant salt tolerance. Barley is one of the most important and salt-tolerant cereal crops and is a model system for investigating the roles of microorganisms in improving plant salt tolerance. However, a comprehensive review of the mechanisms by which microorganisms improve barley salt tolerance remains lacking. In this review, the mechanisms of barley salt tolerance improvement by microorganisms are summarized, along with a discussion of existing problems in current research and areas of future research directions. In particular, with the development of sequencing technology and the great reduction of prices, the use of omics can not only comprehensively evaluate the role of microorganisms but also evaluate the impact of the microbiome on plants, which will provide us with many opportunities and challenges in this research area. [ABSTRACT FROM AUTHOR]

The prediction of surrounding agent trajectories in heterogeneous traffic environments remains a challenging task for autonomous driving due to several critical issues, such as understanding social interactions among agents and the environment, handling multiclass traffic movements, and generating feasible trajectories in accordance with real‐world rules, all of which hinder prediction accuracy. To address these issues, a new multimodal trajectory prediction framework based on the transformer network is presented in this study. A hierarchical‐structured context‐aware module, inspired by human perceptual logic, is proposed to capture contextual information within the scene. An efficient linear global attention mechanism is also proposed to reduce the computation and memory load of the transformer framework. Additionally, this study introduces a novel auxiliary loss to penalize infeasible off‐road predictions. Empirical results on the Lyft l5kit data set demonstrate the state‐of‐the‐art performance of the proposed model, which substantially enhances the accuracy and feasibility of prediction outcomes. The proposed model also possesses a unique feature, effectively dealing with missing input observations. This study underscores the importance of comprehending social interactions among agents and the environment, handling multiclass traffic movements, and generating feasible trajectories adhering to real‐world rules in autonomous driving. [ABSTRACT FROM AUTHOR]

Based on upconversion nanoparticles (UCNPs) as energy donor and herring sperm DNA (hsDNA) as molecular recognition element, an unlabelled upconversion luminescence (UCL) affinity biosensor was constructed for the detection of anthraquinone (AQ) anticancer drugs in biological fluids. AQ anticancer drugs can insert into the double helix structure of hsDNA on the surface of UCNPs, thereby shortening the distance from UCNPs. Therefore, the luminescence resonance energy transfer (LRET) phenomenon is effectively triggered between UCNPs and AQ anticancer drugs. Hence, AQ anticancer drugs can be quantitatively detected according to the UCL quenching rate. The biosensor showed good sensitivity and stability for the detection of daunorubicin (DNR) and doxorubicin (ADM). For the detection of DNR, the linear range is 1–100 μg·mL−1 with a limit of detection (LOD) of 0.60 μg·mL−1, and for ADM, the linear range is 0.5–100 μg·mL−1 with a LOD of 0.38 μg·mL−1. The proposed biosensor provides a convenient method for monitoring AQ anticancer drugs in clinical biological fluids in the future. [ABSTRACT FROM AUTHOR]

In this work, an upconversion luminescence (UCL) nanosensor for fast detection of ferric ion (Fe3+) and phosphate ion (Pi) is developed based on the inner-filter effect (IFE) between NaYF4:Yb/Er upconversion nanoparticles (UCNPs) and Fe3+-hypocrellin B (HB) complex. Fe3+-HB complex has strong absorption band (450–650 nm), which overlaps with the green emission peak of UCNPs at 545 nm. By adding Fe3+ and Pi, the UCNPs-HB system produces the red-shift change of absorption spectrum, which leads to the "on–off-on" process of IFE. So, with the specific recognition ability of HB for Fe3+ and the competitive complexation of Pi for Fe3+, the proposed nanosensor utilizes the UCL change to achieve the detection of the targets. For the detections of Fe3+, the linear range is 10–600 μM with a limit of detection (LOD) of 2.62 μM, and for Pi, the linear range is 5–100 μM with a LOD of 1.25 μM. The results for selectivity, precision, and recovery test are also satisfactory. Furthermore, the real sample detection shows that the proposed nanaosensor has a great potential in environmental and biological systems. An upconversion luminescence (UCL) nanosensor based on the inner-filter effect (IFE) between upconversion nanoparticles (UCNPs) and Fe3+-hypocrellin B (HB) complex for the detection of Fe3+ and phosphate ion has been proposed, which is promising to be a convenient and sensitive assay for monitoring Fe3+ and phosphate ion in different environments and biological systems. [ABSTRACT FROM AUTHOR]

Autonomous driving systems rely on a comprehensive understanding of the surrounding environment, and trees, as important roadside features, have a significant impact on vehicle positioning and safety analysis. Existing methods use mobile LiDAR systems (MLS) to collect environmental information and automatically generate tree inventories based on dense point clouds, providing accurate geometric parameters. However, the use of MLS systems requires expensive survey-grade laser scanners and high-precision GNSS/IMU systems, which limits their large-scale deployment and results in poor real-time performance. Although LiDAR-based simultaneous localization and mapping (SLAM) techniques have been widely applied in the navigation field, to the best of my knowledge, there has been no research conducted on simultaneous real-time localization and roadside tree inventory. This paper proposes an innovative approach that uses LiDAR technology to achieve vehicle positioning and a roadside tree inventory. Firstly, a front-end odometry based on an error-state Kalman filter (ESKF) and a back-end optimization framework based on factor graphs are employed. The updated poses from the back-end are used for establishing point-to-plane residual constraints for the front-end in the local map. Secondly, a two-stage approach is adopted to minimize global mapping errors, refining accumulated mapping errors through GNSS-assisted registration to enhance system robustness. Additionally, a method is proposed for creating a tree inventory that extracts line features from real-time LiDAR point cloud data and projects them onto a global map, providing an initial estimation of possible tree locations for further tree detection. This method uses shared feature extraction results and data pre-processing results from SLAM to reduce the computational load of simultaneous vehicle positioning and roadside tree inventory. Compared to methods that directly search for trees in the global map, this approach benefits from fast perception of the initial tree position, meeting real-time requirements. Finally, our system is extensively evaluated on real datasets covering various road scenarios, including urban and suburban areas. The evaluation metrics are divided into two parts: the positioning accuracy of the vehicle during operation and the detection accuracy of trees. The results demonstrate centimeter-level positioning accuracy and real-time automatic creation of a roadside tree inventory. [ABSTRACT FROM AUTHOR]

The three‐component cyanoalkylsulfonylation cyclization reaction of N‐methacryloyl‐2‐phenylbenzimidazole, DABCO ⋅ (SO2)2 and cyclobutanone oxime ester regulated by different metals (iron and nickel) and the two‐component cyanoalkylation cyclization reaction of DABCO ⋅ (SO2)2 as oxidant were described. The tandem cyclization route allows different cyanoalkylsulfonylated benzimidazole [2,1‐a] iso‐quinoline‐6(5H)‐ones/cyanoalkylated benzimidazole [2,1‐a] iso‐quinoline‐6(5H)‐ones to be obtained in moderate to good yields under mild conditions, with good functional group tolerance, readily available starting materials, and simple operation. In addition, experiments show that the tandem cyclization reaction was a free radical reaction process. [ABSTRACT FROM AUTHOR]

Industrial production brings billions of tons of solid waste every year, which not only leads to resource waste, but also causes threat to the environment. Improving solid waste resource utilization can better meet the needs of environmental protection and sustainable development. Herein, steam activation method were used to transform the waste ion‐exchange resin (IER) into resin based spherical activated carbons (RSACs) with high adsorption properties and mechanical strength to realize the efficient use of waste resources. The porous structures and mechanical strength of RSACs can be adjusted by changing the reaction conditions including activation temperature, activation time and steam input. The largest specific surface area is up to 2047 m2/g with the pore volume of 1.56 cm3/g. The feasibility of utilizing RSACs to remove tetracycline (TC) from aqueous solution was evaluated, and the highest adsorption capacity is 701 mg/g. The pH variation shows some extent effect on the adsorption. The coexisting ions with higher valence state and concentration result in the decrease of the adsorption capacity to some extent. Additionally, the kinetics experimental data fit the pseudo‐second‐order model well, and the equilibrium data are more consistent with the Freundlich model. The adsorbent is promising in wastewater treatment. [ABSTRACT FROM AUTHOR]

NGDY has high‐N atom doping rate, many active sites, large pore size, outstanding thermal stability, and excellent lithium‐ion storage properties. The mixed adsorption of the Mn‐modified NGDY (Mn‐NGDY) system has been studied with the first principles approach, which shows the effects and the mechanism of action about the modified Mn atom and H2 molecules on the adsorption of CH4. From the results, more electrons are transferred from the Mn atom to the neighboring six‐membered ring, making the Mn atom positively charged and forming a strong Coulomb interaction with the substrate. There is Coulomb interaction between the first two methane molecules and Mn atoms, and CH4 molecules have strong polarization phenomenon under this interaction, which causes the surrounding CH4 molecules of the first layer (The CH4 molecules around the first two CH4 molecules) inducing polarization along the XY plane (parallel substrate), and the surrounding CH4 molecules of the second layer inducing polarization along the Z‐axis direction, which improve the adsorption properties of other CH4 molecules. In the first layer, the interaction forces of the adsorbed CH4 molecules region mainly come from the interaction forces between CH4 and the substrate, and the interaction forces between CH4 molecules dominate in the adsorption of second layer. Polarization of H2 molecules along the Z‐axis direction causes the formation of a weak negative center above it, which promotes the adsorption of CH4 molecules above it. For the 2Mn‐NGDY system, a maximum of 72 CH4 molecules and 4 H2 molecules can be adsorbed simultaneously on both sides, when the average adsorption energy and adsorption amount reach −0.169 eV and 73.41 wt%. [ABSTRACT FROM AUTHOR]

Background: Hepatitis C virus (HCV) infection remains a major public health problem in Chinese mainland. Investigation of the distribution of genotypes contributed to the prevention, diagnosis and treatment of HCV infection. Therefore, we conducted a study on the distribution of HCV genotypes and phylogenetic analysis to provide an up-to-date understanding of the molecular epidemiology of genotypes in Chinese mainland. Methods: Our retrospective multicenter study enrolled 11,008 samples collected between August 2018 and July 2019 from 29 provinces/municipalities (Beijing, Hebei, Inner Mongolia, Shanxi, Tianjin, Gansu, Ningxia, Shaanxi, Xinjiang, Heilongjiang, Jilin Liaoning, Henan, Hubei Hunan, Anhui, Fujian, Jiangsu, Jiangxi, Shandong, Shanghai Zhejiang, Guangdong, Guangxi, Hainan, Chongqing, Guizhou, Sichuan and Yunnan). Phylogenetic analysis of each subtype was performed to infer the evolutionary relationship of sequences from diverse regions. Two independent samples t tests were used for the comparison of continuous variables, and chi-square tests were used for the comparison of categorical variables. Results: Four genotypes (1, 2, 3 and 6) were found, including 14 subtypes. HCV genotype 1 was dominant, accounting for 49.2%, followed by genotypes 2, 3 and 6, accounting for 22.4%, 16.4%, and 11.9%, respectively. Additionally, the top five subtypes were 1b, 2a, 3b, 6a and 3a. Proportions of genotypes 1 and 2 decreased while genotypes 3 and 6 increased over past years (P < 0.001). Genotypes 3 and 6 were concentrated in the population aged 30 to 50 years, and male carriers had lower proportions of subtypes 1b and 2a than female carriers (P < 0.01). Genotypes 3 and 6 were more prevalent in southern parts of Chinese mainland. Nationwide spreads of subtypes 1b and 2a were associated with sequences from northern parts of Chinese mainland, while subtypes 3a, 3b and 6a were associated with sequences from southern parts of Chinese mainland. Conclusions: HCV subtypes 1b and 2a remained the most common subtypes in Chinese mainland, and their proportions decreased over the past years, while the proportions of genotypes 3 and 6 increased. Our investigation provided an accurate epidemiological picture of the circulating viral strains in Chinese mainland, contributing to the prevention, diagnosis and treatment of HCV infection. Trial registration: Not applicable. [ABSTRACT FROM AUTHOR]

Herein, an electrochemical trifluoromethylation/cyclization reaction of unactivated alkenes within benzimidazole molecules by direct cascade with C2–H has been developed. The protocol used the readily available CF3SO2Na as the trifluoromethylation reagent. A variety of polycyclic benzimidazoles were successfully synthesized under transition metal- and oxidant-free conditions in 34–78% yields. In addition, the reaction was characterized by good regioselectivity, a wide range of substrates and scalability. [ABSTRACT FROM AUTHOR]

The constitutive model serves as the foundation for executing structure analysis to obtain the deformation and stress/strain. In this paper, a neural network‐assisted Bayesian parameter identification framework is presented to calibrate parameters of the constitutive model while considering the unavoidable uncertainties. The low‐cycle fatigue test of the CuCrZr alloy at 700 K is first performed to provide realistic data. The posterior distributions are obtained by applying the transitional Markov Chain Monte Carlo method. To accelerate the identification, the neural network is adopted to directly predict the likelihood function value given material parameters. The effect of prior distributions on the identification parameters is also studied. The characteristic parameters of the normal distribution have almost no effect on the identification results. In the absence of prior information, uniform prior distributions can be used to perform Bayesian identification of material parameters, and satisfactory identification parameters can also be acquired. Highlights: A neural network‐assisted Bayesian parameter identification procedure is presented.Low‐cycle fatigue test for the rocket thrust chamber used CuCrZr is conducted.Two types of posterior distribution point estimators are investigated.The effect of the prior distribution on the parameter identification is studied. [ABSTRACT FROM AUTHOR]

The snow temperature above the ice sheet is one of the basic characteristic parameters of the ice sheet, which plays an important role in the study of the global climate. Because infrared and microwaves with different frequencies have different penetration depths in snow, it is possible to retrieve the snow temperature profiles by combining microwave and infrared brightness temperatures. This paper proposes a conjoint inversion algorithm to retrieve snow temperature profiles by combining multi-frequency microwave brightness temperature (BT) with infrared BT, in which different weight functions of microwave BT at different frequencies are adopted, and the atmosphere influence has also been corrected. The snow temperature profile data are retrieved based on AMSR2 microwave BT data and MODIS infrared BT data in 2017 and 2018, which are evaluated by comparing with the measured snow temperature at Dome-C station. The results confirm that the inverted snow temperature profiles are consistent with the field observation data from the Dome-C station. Multi-frequency microwave brightness temperature can be used to invert the snow temperature profiles; however, the inverted snow surface temperature is more accurate by combining the infrared BT with the microwave BT in the conjoint inversion algorithm. [ABSTRACT FROM AUTHOR]

Obtaining homozygous lines from transgenic plants is an important step for phenotypic evaluations, but the selection of homozygous plants is time-consuming and laborious. The process would be significantly shortened if anther or microspore culture could be completed in one generation. In this study, we obtained 24 homozygous doubled haploid (DH) transgenic plants entirely by microspore culture from one T0 transgenic plant overexpressing the gene HvPR1 (pathogenesis-related-1). Nine of the doubled haploids grew to maturity and produced seeds. qRCR (quantitative real-time PCR) validation showed that the HvPR1 gene was expressed differentially even among different DH1 plants (T2) from the same DH0 line (T1). Phenotyping analysis suggested that the overexpression of HvPR1 inhibited nitrogen use efficiency (NUE) only under low nitrogen treatment. The established method of producing homozygous transgenic lines will enable the rapid evaluation of transgenic lines for gene function studies and trait evaluation. As an example, the HvPR1 overexpression of DH lines also could be used for further analysis of NUE-related research in barley. [ABSTRACT FROM AUTHOR]

The tooth form is the most influential factor on the bearing capacity and operation performance of a gear drive. Tooth profiles of spur gears can be designed based on control of relative curvature of conjugate profiles, but how to conceive appropriate control strategies and appraise gear pairs accurately needs to be investigated in depth. This paper presents the control strategies through analysis of the effect mechanisms of relative curvature on the bearing capacity and lubrication performance. Evaluation approaches of the gear pairs are then proposed by establishing the analytical models (AMs). In case studies, gear pairs with optimal comprehensive performance are designed through five control strategies. The AMs for contact and bending capacity are validated with the finite element models. The effects of the control strategies are discussed through comparative analysis. Results reveal that the control strategies lead to remarkable enhancement of bearing capacity and lubrication performance. [ABSTRACT FROM AUTHOR]

Background: Hepatic fibrosis is characterized by the excessive deposition of extracellular matrix (ECM) which is mainly secreted by activated hepatic stellate cells (HSCs). Lamiophlomis rotata (L. rotata) was recorded to treat jaundice in the traditional Tibetan medical system with the potential of hepatoprotection. However, the bioactivities and the possible mechanism of L. rotata on hepatic fibrosis is still largely unknown. Aim of the study: To investigate the anti-hepatic fibrosis effects of bioactivities in L. rotata and the probable mechanism of action. Materials and methods: Herein, total polyphenolic glycosides of L. rotata (TPLR) was purified with the selectivity adsorption resin and was analyzed by ultrahigh-performance liquid chromatography coupled with time-of-flight mass spectrometry (UPLC-Q/TOF/MSn). The anti-hepatic fibrosis effect of TPLR was evaluated by carbon tetrachloride (CCl4)-induced liver fibrosis, and was evaluated with the apoptosis of activated HSCs. Results: In total, sixteen compounds, including nine phenylpropanoids and six flavonoids, were identified in the UPLC-TOF-MSn profile of the extracts. TPLR significantly ameliorated hepatic fibrosis in CCl4-induced mice and inhibited HSCs proliferation, Moreover, TPLR notably increased the apoptosis of activated HSCs along with up-regulated caspase-3, -8, -9, and -10. Furthermore, TPLR inhibited TGF-β/Smad pathway ameliorating hepatic fibrosis though downregulation the expression of Smad2/3, Smad4, and upregulation the expression of Smad7 in vivo and in vitro. Simultaneously, the expression of fibronectin (FN), α-smooth muscle actin (α-SMA), and Collagen I (Col1α1) were decreased in tissues and in cells with TPLR administration. Conclusion: These results initially demonstrated that TPLR has the potential to ameliorate hepatic fibrosis through an apoptosis mechanism via TGF-β/Smad signaling pathway. Highlights: Chemical composition of TPRL was identified by UPLC-Q/TOF/MSn in the profile of total ion current. TPRL was initially demostrated the effects of anti-hepatic fibrosis in vitro and in vivo. TPRL ameliorates hepatic fibrosis through apoptosis by TGF-β/Smad signaling pathway. [ABSTRACT FROM AUTHOR]

Vision-based modal analysis has gained popularity in the field of structural health monitoring due to significant advancements in optics and computer science. For long term monitoring, the structures are subjected to ambient excitation, so that their vibration amplitudes are quite small. Hence, although natural frequencies can be usually identified from the extracted displacements by vision-based techniques, it is still difficult to evaluate the corresponding mode shapes accurately due to limited resolution. In this study, a novel signal reconstruction algorithm is proposed to reconstruct the dynamic response extracted by the vision-based approach to identify the mode shapes of structures with low amplitude vibration due to environmental excitation. The experimental test of a cantilever beam shows that even if the vibration amplitude is as low as 0.01 mm, the first two mode shapes can be accurately identified if the proposed signal reconstruction algorithm is implemented, while without the proposed algorithm, they can only be identified when the vibration amplitude is at least 0.06 mm. The proposed algorithm can also perform well with various camera settings, indicating great potential to be used for vision-based structural health monitoring. [ABSTRACT FROM AUTHOR]

Background and Aims. Accurate prediction is essential for the survival of patients with nonmetastatic gastric signet ring cell carcinoma (GSRC) and medical decision-making. Current models rely on prespecified variables, limiting their performance and not being suitable for individual patients. Our study is aimed at developing a more precise model for predicting 1-, 3-, and 5-year overall survival (OS) in patients with nonmetastatic GSRC based on a machine learning approach. Methods. We selected 2127 GSRC patients diagnosed from 2004 to 2014 from the Surveillance, Epidemiology, and End Results (SEER) database and then randomly partitioned them into a training and validation cohort. We compared the performance of several machine learning-based models and finally chose the eXtreme gradient boosting (XGBoost) model as the optimal method to predict the OS in patients with nonmetastatic GSRC. The model was assessed using the receiver operating characteristic curve (ROC). Results. In the training cohort, for predicting OS rates at 1-, 3-, and 5-year, the AUCs of the XGBoost model were 0.842, 0.831, and 0.838, respectively, while in the testing cohort, the AUCs of 1-, 3-, and 5-year OS rates were 0.749, 0.823, and 0.829, respectively. Besides, the XGBoost model also performed better when compared with the American Joint Committee on Cancer (AJCC) stage. The performance for this model was stably maintained when stratified by age and ethnicity. Conclusion. The XGBoost-based model accurately predicts the 1-, 3-, and 5-year OS in patients with nonmetastatic GSRC. Machine learning is a promising way to predict the survival outcomes of tumor patients. [ABSTRACT FROM AUTHOR]

Objective: To establish a mini-pig model of ureteral stricture by using electrocoagulation under ureteroscopy.Methods: Twelve female mini-pigs were included. Their ureters on one side and contralateral side were randomly divided into electrocoagulation and control groups, respectively. In the electrocoagulation group, the middle ureter was circumferentially electrocoagulated by using a self-made electrocoagulation device with the ureteroscope under direct vision, while the control group underwent ureteroscopy only without electrocoagulation. At 30 and 90 days after electrocoagulation, the glomerular filtration rate (GFR), formation of ureteral stricture, and histomorphological changes of ureteral tissues of each group were detected.Results: At 90 days after surgery, ureteroscopy and retrograde urography revealed ureteral stricture formation in the middle ureter in the electrocoagulation group. GFR was gradually decreased over time with prolonged washout half-time in the electrocoagulation group. A compensatory increase in GFR was observed in the control group. Hematoxylin and eosin staining and Masson's Trichrome staining revealed fibroblast infiltration and fibrous tissue hyperplasia in the superficial muscular layers, and the muscular layers were arranged disorderly in the electrocoagulation group. Immunohistochemical staining showed accumulation and disorganization of ureteric epithelium in the narrow segment. In the control group, the epithelium was arranged neatly with normal structure.Conclusion: A mini-pig model of ureteral stricture was successfully established using electrocoagulation under ureteroscopy. This method has the advantages of being simple to implement, having high accuracy and high success rate, which can provide an ideal animal model for studying ureteral stricture. [ABSTRACT FROM AUTHOR]

Constructing layer-structured carbon/ceramic composites is promising for achieving high-performance and high-temperature electromagnetic interference (EMI) shielding materials, in which the rational composition and structural manipulation is critical. Here, a laminated SiBCN@CNTs/SiBCN film with a unique hierarchical structure is prepared using multi-layered carbon nanotubes (CNTs) films as the skeleton by alternatively stacking SiBCN@CNTs layers and SiBCN layers, and its thickness varies from 0.13 to 1.10 mm depending on the number of stacked layers (i.e. , 1 to 6 layers) and the concentration of polyborosilazane precursor for impregnation (i.e. , 10–70 wt%). Enlarging the thickness of the SiBCN@CNTs layers from 60 to 130 μm in the film or increasing their stacking numbers could both enhance the shielding effectiveness due to the introduction of additional interfacial and interlayer multi-reflection to extend the propagation path of electromagnetic waves for effective wave interference. Consequently, a high EMI shielding effectiveness of 49.4 dB has been achieved on SiBCN@CNTs/SiBCN-50-3, corresponding to a high specific shielding effectiveness (SE Total /d) of 182.9 dB mm−1, higher than previous pure ceramic shielding materials and carbon/ceramic composites. Moreover, because of the effective protection of SiBCN for CNTs, the SE Total of the film is still up to 23.9 dB after oxidation at 1000 °C for 2 h. Therefore, the laminated SiBCN@CNTs/SiBCN film represents an ideal candidate for high-efficiency EMI shielding material used in oxidation environments. A laminated SiBCN@CNTs/SiBCN film is successfully constructed by alternatively stacking SiBCN@CNTs layers and SiBCN layers for EMI shielding material, which provides interfacial and interlayer reflection for realizing high specific shielding effectiveness and good anti-oxidation up to 1000 °C, representing the best-reported values in ceramic-based shielding materials by far. [Display omitted] • Constructing a laminated SiBCN@CNTs/SiBCN composite film by multi-layered CNTs film. • Controlling layered structure stacked by SiBCN@CNTs layers and SiBCN layers. • Building interfacial and interlayer reflection for enhancing shielding performance. • Realizing high specific shielding effectiveness of 182.9 dB mm−1 • Achieving good anti-oxidation with SE of 23.9 dB after oxidation at 1000 °C. [ABSTRACT FROM AUTHOR]

Simple Summary: Immunity combined with ferroptosis is being considered as a new tumor treatment modality, and its regulation in head and neck squamous cell carcinoma is still unknown. The purpose of this study was to look into the potential molecular biological roles of immune ferroptosis genes in head and neck squamous cell carcinoma. The 12-IFRM signatures were successfully constructed and classified into high- and low-risk groups using the TCGA database and related data resources. In patients with head and neck squamous cell carcinoma, feature-based risk scores were more predictive of survival than traditional clinicopathological features. Furthermore, the expression of CD8+T cells and macrophage M0 differed significantly between the two groups. The expression of TNFSF9 and CD44 in the high-risk groups was significantly increased compared with the low-risk groups. Next, we found a higher proportion of high-risk mutations than in the low-risk group. In addition, the high-risk group was more sensitive to some chemotherapy drugs. Finally, we performed correlation analysis on the model genes. In this paper, the 12-IFRM signatures was developed with promising application prospects for predicting the clinical outcomes and treatment outcomes in head and neck squamous cell carcinoma. Ferroptosis is a new type of programmed cell death that plays a pivotal role in a variety of tumors. Moreover, immunity is closely related to ferroptosis. However, immune-ferroptosis-related mRNAs (IFRMs) are still not fully understood in the regulation of head and neck squamous cell carcinoma (HNSC). The purpose of this paper was to investigate the IFRMs prediction of HNSC and its possible molecular biological role. RNA-Seq and related clinical data were mined from the TCGA database, ImmPort database, GeneCards database, FerrDb database, and previous data. In R software, the "DESeq2" package was used to analyze the differential expression of IFRMs. We used univariate Cox analysis to judge the prognosis of the IFRMs. Using the least absolute shrinkage and selection operator (LASSO) and Cox regression, a prediction model for 12 IFRMs was established. In this study, the Kaplan–Meier survival curve and receiver operating characteristic (ROC) curve analysis were used to evaluate the prediction results. Moreover, factors such as immune landscape, somatic mutations, and drug susceptibility are also discussed. We successfully constructed the signature of 12-IFRMs. The two risk groups were classified according to the risk score obtained by this signature. Compared with conventional clinicopathological features, the characteristic-based risk score was more predictive of survival in patients with HNSC. Furthermore, the expression of CD8+T cells and macrophage M0 differed significantly between the two groups. Moreover, the expression of TNFSF9 and CD44 in high-risk groups was significantly increased compared with the low-risk groups. Then, we found a higher proportion of high-risk mutations than in the low-risk group. Next, the high-risk group was more sensitive to chemotherapy drugs such as bosutinib, docetaxel, erlotinib, gefitinib, imatinib, lapatinib, and sorafenib. Finally, an in-depth analysis of the association and potential value of the 12 genes was performed. In summary, the 12-IFRM signatures established in this paper had good application prospects and could be effectively used to predict the clinical outcome and treatment response of head and neck squamous cell carcinoma. [ABSTRACT FROM AUTHOR]

The Convenient and accurate identification of the traffic load of passing vehicles is of great significance to bridge health monitoring. The existing identification approaches often require prior environment knowledge to determine the location of the vehicle load, i.e., prior information of the road, which is inconvenient in practice and therefore limits its application. Moreover, camera disturbance usually reduces the measurement accuracy in case of long-term monitoring. In this study, a novel approach to identify the spatiotemporal information of passing vehicles is proposed based on computer vision. The position relationship between the camera and the passing vehicle is established, and then the location of the passing vehicle can be calculated by setting the camera shooting point as the origin. Since the angle information of the camera is pre-determined, the identification result is robust to camera disturbance. Lab-scale test and field measurement have been conducted to validate the reliability and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

Quantitative ultrasound (QUS) is a promising screening method for osteoporosis. In this study, a new method to improve the diagnostic accuracy of QUS was established in which a multichannel convolutional neural network (MCNN) processes the raw radiofrequency (RF) signal of QUS. The improvement in the diagnostic accuracy of osteoporosis using this new method was evaluated by comparison with the conventional speed of sound (SOS) method. Dual-energy X-ray absorptiometry was used as the diagnostic standard. After being trained, validated and tested in a data set consisting of 274 participants, the MCNN model could significantly raise the accuracy of osteoporosis diagnosis compared with the SOS method. The adjusted MCNN model performed even better when adjusted by age, height and weight data. The sensitivity, specificity and accuracy of the adjusted MCNN method for osteoporosis diagnosis were 80.86%, 84.23% and 83.05%, respectively; the corresponding values for SOS were 50.60%, 73.68% and 66.67%. The area under the receiver operating characteristic curve of the adjusted MCNN method was also higher than that of SOS (0.846 vs. 0.679). In conclusion, our study indicates that the MCNN method may be more accurate than the conventional SOS method. The MCNN tool and ultrasound RF signal analysis are promising future developmental directions for QUS in screening for osteoporosis. [ABSTRACT FROM AUTHOR]

There is a certain amount of current harmonics in interior permanent magnet synchronous motor. In order to accurately control the current harmonic, this article focuses on three aspects: establishing current harmonic calculation model, extracting current harmonic, and designing current harmonic regulator. A current harmonic calculation model, which considers the effect of voltage harmonics induced by current controllers and digital control delay on the initial phase angle of voltage harmonics, is established for the first time. With the help of multiple synchronous rotating frame transformation, a current harmonic extraction method more suitable for motor drive field, which aims to extract the current harmonic characteristics of d-axis and q-axis currents, is proposed. On this basis, the controlled quantity and control quantity are unified in d–q coordinate frame for analyzing the coupling relationship of current harmonic characteristics. And then a PI current harmonic regulator, including current harmonic decoupling and voltage harmonic initial phase angle compensation, is constructed, so as to realize the effective control of current harmonics. Finally, the effectiveness and superiority of the proposed method are verified by simulation and experiments. [ABSTRACT FROM AUTHOR]

Crop breeding for high nitrogen use efficiency (NUE) or tolerance to low nitrogen fertilization is thought to be an ideal solution to reduce the cost, carbon footprint, and other environmental problems caused by the excess use of nitrogen fertilizers. As a model plant for cereal crops, barley has many advantages, including good adaptability, a short growth period, and high natural stress resistance or tolerance. Therefore, research on improving NUE in barley is not only beneficial for nitrogen-efficient barley breeding but will also inform NUE improvement in other cereal crops. In this review, recent progress in understanding barley's response to nitrogen nutrition, evaluation of NUE or low-nitrogen tolerance, quantitative trait loci (QTL) mapping and gene cloning associated with improving NUE, and breeding of nitrogen-efficient barley is summarized. Furthermore, several biotechnological tools that could be used for revealing the molecular mechanisms of NUE or breeding for improving NUE in barley are introduced, including GWAS, omics, and gene editing. The latest research ideas in unraveling the molecular mechanisms of improving NUE in other crops are also discussed. Thus, this review provides a better understanding of improving the NUE of barley and some directions for future research in this area. [ABSTRACT FROM AUTHOR]

With the development of virtual reality and digital reconstruction technology, digital museums have been widely promoted in various cities. Digital museums offer new ways to display and disseminate cultural heritage. It allows remote users to autonomously browse displays in a physical museum environment in a digital space. It is also possible to reproduce the lost heritage through digital reconstruction and restoration, so as to digitally present tangible cultural heritage and intangible cultural heritage to the public. However, the user's experience of using digital museums has not been fully and deeply studied at present. In this study, the user's experience evaluation data of digital museum are classified and processed, so as to analyze the user's emotional trend towards the museum. Considering that the user's evaluation data are unbalanced data, this study uses an unbalanced support vector machine (USVM) in the classification of user evaluation data. The main idea of this method is that the boundary of the support vector is continuously shifted to the majority class by repeatedly oversampling some support vectors until the real support vector samples are found. The experimental results show that the classification obtained by the used USVM has a good practical reference value. Based on the classification results of the evaluation data, the construction of the digital museum can be further guided and maintained, thereby improving the user experience satisfaction of the museum. This research will make an important contribution to the construction of the museum and the inheritance of culture. [ABSTRACT FROM AUTHOR]

In order to propose more reasonable protection measures of transformers, the electromagnetic transient of distribution transformers under the lightning strike fault should be given enough attention. In this article, a 35-kV distribution transformer under the lightning strike is taken as the research object. First, the lightning overvoltage model of the transformer is established utilizing the double exponential model. The electromagnetic transient change of the transformer under the rated voltage superposed the lightning overvoltage is analyzed. Second, the magnetic flux distortion of the transformer core and the current distribution law of the transformer windings during the lightning invasion are calculated and summarized, respectively. Finally, on the basis of revealing the whole process that the lightning wave invades the transformer windings, a new type design scheme of transformer lightning protection is proposed. The results show that the additional windings of the lightning protection scheme can greatly reduce the positive and negative overvoltage of lightning wave acting on the transformer. The feasibility of the proposed protective measures is verified, which can provide some scientific references for improving and perfecting the lightning protection measures of the distribution network. [ABSTRACT FROM AUTHOR]

Torque ripple reduction for permanent magnet assisted reluctance (PMAREL) machine has always been concerned by designers. In order to seek the internal factors of torque ripple for PMAREL, this article proposes an effective torque calculation model considering air-gap field time-space harmonics using finite element method (FEM) combined with two-dimensional fast Fourier transform (2D-FFT). It can be used to investigate the contribution of air-gap field time-space harmonics to average torque and torque ripple, and precisely extract the characteristic components of the air-gap field time-space harmonics that contribute to the torque. Besides, the details of time-space harmonic order, movement form, magnitude and initial phase will be obtained from the characteristic components. Hence, the time-space harmonics of air-gap field that mainly contribute to the torque ripple can be found through this model and suppressed by adjusting the angles of the flux-barrier ends for making torque smooth. According to the optimized design, a 36-slot 4-pole PMAREL is manufactured and tested. Both finite element analysis and experimental results confirm the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

• The closed form of bridge displacement induced by heavy vehicle is derived via frequency modulation technique. • Nonlinear frequency modulation signal reconstruction technique is adopted to separate the static and dynamic components. • Error analysis by theoretical derivation shows the effectiveness of simplifying the multi-axle heavy inspection vehicle. • Numerical simulations, laboratory tests and field measurements are presented to validate the proposed method. Bridge influence line plays an important role in evaluating bridge condition, which are usually identified by either time domain or frequency domain methods. Time domain approaches, while prevalent, encounter significant challenges in minimizing inspection durations and enhancing operational efficiency. Frequency domain methods often struggle with the accurate detection of signal peaks. Addressing these limitations, this study introduces an innovative time–frequency analysis technique, specifically, the application of nonlinear frequency modulation signal decomposition, to reconstruct bridge influence line from displacement induced by a heavy inspection vehicle. A comprehensive theoretical analysis is presented to derive the displacement response of a bridge subjected to a heavy inspection vehicle, as opposed to the conventional moving load paradigm. This displacement comprises two distinct components: a dynamic component, characterized as a typical frequency modulation signal, and a static component, which is directly proportional to the bridge influence line. Then the nonlinear frequency modulation signal reconstruction technique is proposed to separate the static and dynamic components and therefore extract bridge influence line. Moreover, error analysis is carried out through theoretical derivation to show the effectiveness of simplifying multi-axle inspection vehicle into a single-axle inspection vehicle. The study also incorporates numerical simulations to validate the derived bridge displacement, characterized by time-varying instantaneous frequency. These simulations confirm the feasibility of the proposed method in extracting the bridge influence line and enable a parametric analysis considering variables such as vehicle speed, type of inspection vehicle, and road surface roughness. To corroborate the theoretical and numerical findings, the study includes both laboratory experiments and field measurements. These validations highlight the efficiency and practicality of the proposed method. Notably, the method allows for inspection speeds of up to 60 km/h, significantly surpassing existing bridge influence line identification techniques, and obviates the need for constructing a vehicle information matrix. This study, therefore, presents a significant advancement in the field of bridge condition evaluation, offering a more efficient and practical approach to bridge influence line identification. [ABSTRACT FROM AUTHOR]

Reverse electrodialysis (RED) is a promising method for harvesting the salinity gradient energy (SGE) between the brine and river water. Many investigations are carried out by using the artificially brine and fresh water, bringing difficulties in reflecting the practical RED performance under the complex influences of feed solutions. This work explores the performance of the RED system for hydrogen and electricity co-generation that is driven by salinity gradient between the actual concentrated brine and natural river water, and compared with the simulative brines and river waters under six testing schemes. The results show both the working current and solutions influence the system performances, including the output voltage, power density, hydrogen production, and energy conversion efficiency. Besides, the effects of salinity gradient of feed solutions are greater than that of the presence of trace multivalent ions and anionic radical in brine. The effective monovalent ion ionic strength is vital. The experimental maximum hydrogen production and power density are 82.12 mL·h−1 and 0.124 W·m−2 respectively at the current is 0.2 A, and the total power reached 0.32 W with the energy conversion efficiency of 25%. The research offers recommendations for harnessing SGE from actual brines and freshwater to produce hydrogen. • An innovative process of energy recovery from the actual brines and freshwater was presented. • A reverse electrodialysis stack was built to produce H 2 driven by actual brine and river water. • Feasibility is analyzed based on the comparation testes by 3 brines and 3 fresh waters schemes. • Maintaining a suitable working current heightens H 2 production and total power output. • Power density is 0.149 W·m−2 and H 2 production is 82.12 ml·h−1, at the current is 0.2 A. [ABSTRACT FROM AUTHOR]

In friction stir welding (FSW) of dissimilar Al/Mg alloys, inevitable formation of intermetallic compounds (IMCs) has deleterious effect on the performance of joints. Although ultrasonic vibration enhanced FSW (UVeFSW) was invented to suppress the IMCs formation, the mitigating mechanism is not elucidated. In this work, the measured maximum temperature in weld nugget zone (WNZ) confirmed that in butt FSW of Al/Mg alloys the IMCs are generated by diffusion of solid atoms. The acoustic softening and antifriction effects were taken into account for computation of temperature, strain rate and dislocation density which are main factors affecting the inter-diffusion coefficients of Mg and Al atoms. An atom-diffusion based model was developed, and the formation and growth of the IMCs were quantitatively analyzed in FSW/UVeFSW of Al/Mg alloys. It was found that as the checking point flows toward to the tool, Al 12 Mg 17 layer is first formed at the bonding interface, and then Al 3 Mg 2 is formed at the Al side and grows rapidly. Under the conditions used in this study, the predicted values of IMCs thickness at the WNZ center in FSW and UVeFSW are 3.9 µm and 1.8 µm, respectively. The calculated IMCs thicknesses at the selected locations on the transverse cross-section and horizontal cross-section agree well with the measured ones. Ultrasonic induced dislocation-annihilation and associated decreasing of dislocation density in UVeFSW cause declining of the atomic diffusion coefficients, so that the formation and growth of IMCs are inhibited with ultrasonic action. • The measured temperature confirmed that in butt FSW the IMCs are generated by diffusion of solid atoms. • The IMCs thickness are quantitatively analyzed in FSW/UVeFSW of Al/Mg alloys. • The calculated IMCs thicknesses at selected locations on different cross-sections agree well with the measured ones. • The reason why ultrasonic vibration has an inhibition influence on IMCs thickness is explained. [ABSTRACT FROM AUTHOR]

• A novel W-DATA method for mechanical degradation performance description and reliability estimation. • ApEn and P-EMD are introduced for degradation feature extraction and quantification. • An ApEn -based Wiener degradation model with a pseudo failure threshold is employed to estimate the reliability. • W-DATA can be effectively used for lubricating oil pump reducer reliability estimation. The Wiener-process-based Degradation Approach with Two-phase Algorithm (W-DATA) is introduced as a multi-dimensional framework explicitly designed for modeling mechanical system reliability. This approach leverages an enhanced Empirical Mode Decomposition, known as P-EMD, for degradation feature extraction, and utilizes Approximate Entropy (ApEn) for quantifying feature complexities. W-DATA seamlessly integrates these components into a time-resolved degradation model. To enhance its robustness, the proposed reliability model synergizes with a Box-Cox transformed Wiener model, allowing for improved adaptability to non-Gaussian data landscapes. The paper outlines a strategy for establishing a reliable threshold for this data-driven degradation model based on non-Gaussian data, a critical aspect for reliability modeling using the Wiener process. This strategy addresses the challenge of Wiener process verification through normality and independent testing of data increments. The integrative methodology is recommended for application in machinery reliability analytics and has undergone rigorous validation through a 770 h real-world test on a marine lubricating oil pump reducer. The results affirm its efficacy and feasibility in accurately estimating mechanical system reliability. [ABSTRACT FROM AUTHOR]

• Propose a new reliability model by determining the optimal redundant number. • Incorporate satellite operating environment into the reliability model. • Model the satellite communication system using a Markov Bayesian network. • Give a new importance measure to identify the critical satellite communication. • Use MOPSO algorithm to solve the redundancy design of satellite propulsion system. Satellite communication system holds a crucial role in modern society, so it is significant to improve its reliability and stability. Optimizing reliability and designing redundancy become imperative methods to ensure continuous and efficient operation of the system in the intricate space environment. In this paper, we initially model the satellite communication system using a Markov Bayesian Network in conjunction with a non-working reserve system, facilitating a systematic analysis of its reliability. Secondly, we propose a novel Bayesian environmental importance measure by considering the unique attributes of the space environment. This importance measure verifies the contributions and significance of the individual subsystems within the satellite communication system. Subsequently, we formulate a redundancy design strategy for critical subsystems to maximize reliability while minimizing costs. To solve the optimal number of redundancies of components in the subsystem, we employ the multi-objective particle swarm optimization algorithm. Finally, the effectiveness of the proposed method is demonstrated by a satellite communication system. [ABSTRACT FROM AUTHOR]

The integrated energy system plays an important role in the energy conservation, emission reduction and the resource-efficient utilization. Accurate load forecasting is a significant basis for the optimal scheduling of the integrated energy system. The integrated energy system has coupling interaction between different energy sources in production, distribution and storage. However, the traditional method cannot effectively extract multi-scale features and utilize the coupling information between the multivariate energy sources. In this paper, a novel multi-scale fusion convolutional neural network integrating the bi-directional long short-term memory network and multi-domains hierarchical decoding is proposed to extract and analyze multivariate load data coupling in the integrated energy system data. The multi-scale fusion convolutional neural network is constructed by the multi-dimension convolution layer to obtain multi-scale feature of the integrated energy system data. Meanwhile, the bi-directional long short-term memory network is applied to extract the time dependencies of the integrated energy system data. Finally, the multi-domains hierarchical decoding extracts the coupling characteristics of different domains to predict multiple domains values. Compared with the backpropagation neural network, the support vector machine, the short and long-time memory network, the bi-directional long short-term memory network, and the convolutional neural network - bi-directional long short-term memory network, the proposed method achieves state-of-the-art results in terms of the mean absolute percentage error with 0.365 %, the explained variance score with 99.987 % and the R2-score with 99.984 %, which proves the effectiveness of the proposed model in the load prediction of the integrated energy system. In addition, the proposed method can provide operational guidance for energy production and storage. Through the operation guidance of the proposed method, the carbon emissions are reduced by 238791.58 kg every week. [Display omitted] • Novel multi-scale fusion convolutional neural network is proposed. • Load prediction of integrated energy systems for energy saving and carbon emission is built. • The proposed method achieves state-of-the-art results in terms of the MAPE, the EV and the R2-score. • The proposed method can provide operational guidance for energy production and storage. • The carbon emission is reduced by 238791.58 kg every week. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel kinetic modeling strategy combining the moments method with an improved multi-objective mayfly algorithm is proposed. • The improved multi-objective mayfly algorithm is proposed. • Industrial-scale propylene polymerization model based on the proposed method is established. • The proposed algorithm presents the state-of-art ability on prediction results of the PR and the MI. • This proposed algorithm has a good prospect for the PP industrial application. Polypropylene (PP) is a synthetic resin with exceptional physical and chemical properties, making it suitable for various household and industrial applications. However, as the demand for PP continues to rise, the polypropylene industry faces challenges in improving its quality and efficiency. Developing an accurate mathematical model that describes the continuous polymerization process is crucial for enhancing PP production, as it is useful for controlling product quality and improving production efficiency. While previous studies have focused on modeling propylene polymerization using laboratory-scale and pilot-scale reactors, these models do not effectively apply to industrial-scale processes due to the complexity of the industrial environment. Therefore, a novel kinetic modeling method combining the modeling of the kinetic mechanism of the polymerization reaction with an intelligent optimization algorithm for the industrial-scale continuous gas-phase fluidized bed propylene polymerization process is proposed. To establish the kinetic mechanism model, the improved moments (MOM) method is utilized to derive a set of mass balance equations that account for various fundamental processes such as catalyst activation, chain initiation, chain growth, chain transfer to hydrogen, chain transfer to monomers, chain transfer to co-catalysts, and spontaneous deactivation. However, kinetic parameters serve as the link between the theoretical model and the actual production process, so the kinetic parameters estimation problem need to be transformed into a multi-objective problem by minimizing the least squares difference between the measurement data of the actual industry process and the predicted result of the kinetic model. Therefore, an improved multi-objective mayfly algorithm (IMOMA) is introduced to estimate the polymerization kinetic parameters, which incorporates the simulated binary crossover (SBX) operator and the polynomial mutation (PM) operator into the basic multi-objective mayfly algorithm (MOMA). Finally, by fitting industrial measurement data of the melt index (MI) and the polymerization rate (PR) of an actual polypropylene industrial case study, the proposed algorithm accurately determines the polymerization kinetic parameters. The results demonstrate that the MOM-IMOMA modeling approach outperforms other methods and holds significant promise for industrial-scale polypropylene production. [ABSTRACT FROM AUTHOR]

[Display omitted] Designing high-efficiency heterojunction photocatalysts for water splitting is an intriguing prospect in energy conversion. Herein, we successfully fabricated a CdS/ZIF-8 heterojunction system through a facile wet-chemically method, in which ZIF-8 nanoparticles were in-situ adhered on hollow CdS nanotubes. Due to the well-matched band structure and intimate interface contact in CdS/ZIF-8 hybrid structure, the interfacial charge separation in the established system was tremendously boosted. As a consequence, the established CdS/ZIF-8 heterojunction exhibited the optimal photocatalytic hydrogen production performance (2.10 mmol·g−1 L−1), which was 35 times higher than pristine CdS (0.06 mmol·g−1·L−1). We believe this strategy will endow new insights for the development of novel photocatalysts. [ABSTRACT FROM AUTHOR]

The "asymmetry" between spatiotemporally varying passenger demand and fixed-capacity transportation supply has been a long-standing problem in urban mass transportation (UMT) systems around the world. The emerging modular autonomous vehicle (MAV) technology offers us an opportunity to close the substantial gap between passenger demand and vehicle capacity through station-wise docking and undocking operations. However, there still lacks an appropriate approach that can solve the operational design problem for UMT corridor systems with MAVs efficiently. To bridge this methodological gap, this paper proposes a continuum approximation (CA) model that can offer near-optimal solutions to the operational design for MAV-based transit corridors very efficiently. We investigate the theoretical properties of the optimal solutions to the investigated problem in a certain (yet not uncommon) case. These theoretical properties allow us to estimate the seat demand of each time neighborhood with the arrival demand curves, which recover the "local impact" property of the investigated problem. With the property, a CA model is properly formulated to decompose the original problem into a finite number of subproblems that can be analytically solved. A discretization heuristic is then proposed to convert the analytical solution from the CA model to feasible solutions to the original problem. With two sets of numerical experiments, we show that the proposed CA model can achieve near-optimal solutions (with gaps less than 4% for most cases) to the investigated problem in almost no time (less than 10 ms) for large-scale instances with a wide range of parameter settings (a commercial solver may even not obtain a feasible solution in several hours). The theoretical properties are verified, and managerial insights regarding how input parameters affect system performance are provided through these numerical results. Additionally, results also reveal that, although the CA model does not incorporate vehicle repositioning decisions, the timetabling decisions obtained by solving the CA model can be easily applied to obtain near-optimal repositioning decisions (with gaps less than 5% in most instances) very efficiently (within 10 ms). Thus, the proposed CA model provides a foundation for developing solution approaches for other problems (e.g., MAV repositioning) with more complex system operation constraints whose exact optimal solution can hardly be found with discrete modeling methods. [ABSTRACT FROM AUTHOR]

Background: Software for nuclear magnetic resonance (NMR) spectrometers offer general functionality of instrument control and data processing; these applications are often developed with non-scripting languages. NMR users need to flexibly integrate rapidly developing NMR applications with emerging technologies. Scripting systems offer open environments for NMR users to write custom programs. However, existing scripting systems have limited capabilities for both extending the functionality of NMR software's non-script main program and using advanced native script libraries to support specialized application domains (e.g., biomacromolecules and metabolomics). Therefore, it is essential to design a novel scripting system to address both of these needs. Result: Here, a novel NMR scripting system named SpinSPJ is proposed. It works as a plug-in in the Java based NMR spectrometer software SpinStudioJ. In the scripting system, both Java based NMR methods and original CPython based libraries are supported. A module has been developed as a bridge to integrate the runtime environments of Java and CPython. The module works as an extension in the CPython environment and interacts with Java via the Java Native Interface. Leveraging this bridge, Java based instrument control and data processing methods of SpinStudioJ can be called with the CPython style. Compared with traditional scripting systems, SpinSPJ better supports both extending the non-script main program and implementing advanced NMR applications with a rich variety of script libraries. NMR researchers can easily call functions of instrument control and data processing as well as developing complex functionality (such as multivariate statistical analysis, deep learning, etc.) with CPython native libraries. Conclusion: SpinSPJ offers a user-friendly environment to implement custom functionality leveraging its powerful basic NMR and rich CPython libraries. NMR applications with emerging technologies can be easily integrated. The scripting system is free of charge and can be downloaded by visiting http://www.spinstudioj.net/spinspj. [ABSTRACT FROM AUTHOR]

To overcome nitrogen deficiency, legume roots establish symbiotic interactions with nitrogen-fixing rhizobia that are fostered in specialized organs (nodules). Similar to other organs, nodule formation is determined by a local maximum of the phytohormone auxin at the primordium site. However, how auxin regulates nodule development remains poorly understood. Here, we found that in soybean, (Glycine max), dynamic auxin transport driven by PIN-FORMED (PIN) transporter GmPIN1 is involved in nodule primordium formation. GmPIN1 was specifically expressed in nodule primordium cells and GmPIN1 was polarly localized in these cells. Two nodulation regulators, (iso)flavonoids trigger expanded distribution of GmPIN1b to root cortical cells, and cytokinin rearranges GmPIN1b polarity. Gmpin1abc triple mutants generated with CRISPR-Cas9 showed the impaired establishment of auxin maxima in nodule meristems and aberrant divisions in the nodule primordium cells. Moreover, overexpression of GmPIN1 suppressed nodule primordium initiation. GmPIN9d, an ortholog of Arabidopsis thaliana PIN2, acts together with GmPIN1 later in nodule development to acropetally transport auxin in vascular bundles, fine-tuning the auxin supply for nodule enlargement. Our findings reveal how PIN-dependent auxin transport modulates different aspects of soybean nodule development and suggest that the establishment of auxin gradient is a prerequisite for the proper interaction between legumes and rhizobia. [ABSTRACT FROM AUTHOR]