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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]

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]

[Display omitted] • The FHUM coupling the pipe transport model with a shallow water model is proposed. • A quantitative evaluation of the underground pipe network's effect is studied. • The pipe network consistently plays an important and stable role in urban flood. • The pipe network may potentially lead to increased flood risk in localized areas. Rapid urbanization and climate change have heightened urban flood risks. An in-depth examination of the underground drainage pipe network's effect on urban flood inundation can enhance urban stormwater management and mitigate disaster risks. This study presents a full hydrodynamic urban flood model (FHUM) coupling the pipe transport module of the Storm Water Management Model (SWMM) with a shallow water model. Based on unstructured grid cells, runoff yield and confluence calculations are carried out to effectively separate the underground drainage pipe network from other factors. The model is applied to Minzhi Area and Haidian Island to quantitatively assess the influence of the underground drainage system on urban flooding. Results indicate that FHUM performs well, accurately reflecting the process from rainfall to inundation. The underground drainage pipe network reduces surface inundation in the study area and improves the city's stormwater drainage capacity. With increasing rainstorm intensity, the impact of the pipe network does not exhibit a consistent trend. During heavy rainstorms, the pipe network consistently plays a significant and stable role, particularly in reducing high inundation depths. However, attention should be paid to the potential flood risk transfer associated with using pipe networks in urban flood management. This work provides a scientific basis for urban stormwater management, holding significant importance in improving flood control and disaster reduction capabilities. [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]

Background: Our study aims to delineate the miRSNP–microRNA–gene–pathway interactions in the context of hypertrophic scars (HS) and keloids. Materials and Methods: We performed a computational biology study involving differential expression analysis to identify genes and their mRNAs in HS and keloid tissues compared to normal skin, identifying key hub genes and enriching their functional roles, comprehensively analyzing microRNA‐target genes and related signaling pathways through bioinformatics, identifying MiRSNPs, and constructing a pathway‐based network to illustrate miRSNP‐miRNA‐gene‐signaling pathway interactions. Results: Our results revealed a total of 429 hub genes, with a strong enrichment in signaling pathways related to proteoglycans in cancer, focal adhesion, TGF‐β, PI3K/Akt, and EGFR tyrosine kinase inhibitor resistance. Particularly noteworthy was the substantial crosstalk between the focal adhesion and PI3K/Akt signaling pathways, making them more susceptible to regulation by microRNAs. We also identified specific miRNAs, including miRNA‐1279, miRNA‐429, and miRNA‐302e, which harbored multiple SNP loci, with miRSNPs rs188493331 and rs78979933 exerting control over a significant number of miRNA target genes. Furthermore, we observed that miRSNP rs188493331 shared a location with microRNA302e, microRNA202a‐3p, and microRNA20b‐5p, and these three microRNAs collectively targeted the gene LAMA3, which is integral to the focal adhesion signaling pathway. Conclusions: The study successfully unveils the complex interactions between miRSNPs, miRNAs, genes, and signaling pathways, shedding light on the genetic factors contributing to HS and keloid formation. [ABSTRACT FROM AUTHOR]

IRAK4 is a critical mediator in NF-κB-regulated inflammatory signaling and has emerged as a promising therapeutic target for the treatment of autoimmune diseases; however, none of its inhibitors have received FDA approval. In this study, we identified a novel small-molecule IRAK4 kinase inhibitor, DW18134, with an IC50 value of 11.2 nM. DW18134 dose-dependently inhibited the phosphorylation of IRAK4 and IKK in primary peritoneal macrophages and RAW264.7 cells, inhibiting the secretion of TNF-α and IL-6 in both cell lines. The in vivo study demonstrated the efficacy of DW18134, significantly attenuating behavioral scores in an LPS-induced peritonitis model. Mechanistically, DW18134 reduced serum TNF-α and IL-6 levels and attenuated inflammatory tissue injury. By directly blocking IRAK4 activation, DW18134 diminished liver macrophage infiltration and the expression of related inflammatory cytokines in peritonitis mice. Additionally, in the DSS-induced colitis model, DW18134 significantly reduced the disease activity index (DAI) and normalized food and water intake and body weight. Furthermore, DW18134 restored intestinal damage and reduced inflammatory cytokine expression in mice by blocking the IRAK4 signaling pathway. Notably, DW18134 protected DSS-threatened intestinal barrier function by upregulating tight junction gene expression. In conclusion, our findings reported a novel IRAK4 inhibitor, DW18134, as a promising candidate for treating inflammatory diseases, including peritonitis and IBD. [ABSTRACT FROM AUTHOR]

2,5-tetrahydrofurandimethanol (THFDM), which is an alicyclic diol in products of 5-hydroxymethylfurfural (HMF), is a sustainable monomer to protect environment for replacing the role of isophthalic acid (IPA) and 1,4-cyclohexanedimethanol (CHDM) which were optimized polyethylene terephthalate (PET) performance. By direct esterification method, poly (ethylene-co-tetrahydrofurandimethanol terephthalate) (PETT) was synthesized in 2.5 L reactor. The results showed that the contents of THFDM in copolyester were less than that feeding ratio attributed to its lower reaction reactivity. The color of PETT slightly turned yellow. PETT performed broader processing temperature window, while Tg maintained in good range because of the cyclic structure of THFDM. Especially, the cold crystallization occured in PETT but not in PET after finishing melt crystallization. Otherwise, the thermal stability and crystal structure of PETT remained the same as PET. The crystallization activity of PETT became significantly lower than PET. What proved THFDM was effective in reducing PET crystallinity was that crystallization kinetics using Jeziorny theory and the trend of activation energy of melt crystallization which was calculated by Friedman method. And PETT-2 fibre had comparable mechanical property to PET fibre. In the advancement of green chemistry, THFDM has added a choice of cyclic bio-based comonomers. [ABSTRACT FROM AUTHOR]

This work designed a mesoscale method of multi-step reduction of Fe 2 O 3 with H 2 based on Lattice Gas Cellular Automata (LGCA). Particles in the LGCA were marked to distinguish all the reactants, intermediates, products, and inert. A self-organized evolutionary mechanism is designed. The hydrogen reduction of Fe 2 O 3 in the temperature range of 460–550 °C and 650–800 °C was simulated. Results show that the intermediate product Fe 3 O 4 was found in both conditions, and its mass fraction quickly reach a peak at ∼0.8 and gradually decrease thereafter. An "induction period" can be identified in the initial stage of the reaction at 650–800 °C, where the reduction rate is slow due to the hindered formation of FeO. The porosity inside the Fe 2 O 3 particles increases continuously through the reduction process, resulting in significant changes in the flow field around the particles. Consequently, the wake vortex gradually decreases and disappears eventually. • The multiple step reduction of Fe 2 O 3 by hydrogen is investigated in mesoscale. • A mesoscale method with self-organized evolutionary mechanism is developed. • Three obvious reaction rate transitions can be identified at 650–800 °C by the method. • The flow field is altered from internal structural of Fe 2 O 3 changes during reduction. [ABSTRACT FROM AUTHOR]

• Vibro-electric coupling model of the VEH under square wave excitation is established. • The parameter adjusting priority of the VEH system is proposed. • The maximum output power of the proposed system is 2.7 W. • The proposed VEH is suitable for multi-vibration scenarios. Harvesting energy from surrounding vibrations is an effective method for powering various low-power electronic devices. The energy output performance of vibration energy harvesters under some special excitations remains to be investigated. In this paper, a vibration energy harvester (VEH) system based on a rack and pinion mechanism and a bevel gear set is proposed, and a detailed electromechanical coupling modeling of the system under general excitation and square wave excitation is carried out. The energy output characteristics of the proposed system under square wave excitation are explored through simulation and experiment. When the energy output is the target, the priority of adjusting the constituent parameters in the equivalent mass parameter, equivalent damping parameter and equivalent stiffness parameter of the system can be obtained based on the simulation results. The experimental results under periodic square wave excitation force show that the maximum output power of the proposed system is 2.7 W at an amplitude of 4 kN and a frequency of 3 Hz. This is a 55 % increase in the maximum power compared to the sinusoidal excitation under the same conditions. It is demonstrated that the proposed system has great potential to power various low-power electronic devices. [Display omitted] [ABSTRACT FROM AUTHOR]

The precise estimation of macroscopic traffic parameters, such as travel time and fuel consumption, is essential for the optimization of traffic management systems. Despite its importance, the comprehensive acquisition of vehicle trajectory data for the calculation of these macroscopic measures presents a challenge. To bridge this gap, this study aims to calibrate car-following models capable of predicting both microscopic measures and macroscopic measures. We conduct a numerical analysis to trace the cumulative process of model prediction errors across various measurements, and our findings indicate that macroscopic measures encapsulate the accumulation of model errors. By incorporating macroscopic measures into vehicle model calibration, we can mitigate the impact of noise on microscopic data measurements. We compare three car-following model calibration methods: MiC (using microscopic measurements), MaC (using macroscopic measurements), and BiC (using both microscopic and macroscopic measurements)—utilizing real-world trajectory data. The BiC method emerges as the most successful in reconstructing vehicle trajectories and accurately estimating travel time and fuel consumption, whereas the MiC method leads to overfitting and inaccurate macro-measurement predictions. This study underscores the importance of bi-scale calibration for precise traffic and energy consumption predictions, laying the groundwork for future research aimed at enhancing traffic management strategies. [ABSTRACT FROM AUTHOR]

In this paper, both the buckling and material failure for ring-stiffened composite shells under hydrostatic pressure are studied by theoretical and finite element (FE) methods. Theoretical formulas to predict the critical buckling pressure and material failure load for ring-stiffened composite shells are proposed. To validate the proposed analytical solutions, FE models are built and the buckling and material failure analyses are performed. Moreover, two experimental tests on unstiffened and ring-stiffened composite shells were carried out. Analytical solutions, FE results and experimental tests were compared and it shows great accuracy of the proposed theoretical solution. Parametric studies are performed, the effects of rib height, width, and number on the stability as well as the effects of winding angle and thickness on the material failure are discussed. The buckling mode of a ring-stiffened composite shell will transform from overall to local buckling as the rib height, width, and number increase. The material failure pressures are mainly affected by winding angle and thickness. The composite shell with winding angles of [90/±40/90] or [±50/±50] have larger material failure pressure than other winding angles. [ABSTRACT FROM AUTHOR]

Background: Isolated microspore culture is a useful biotechnological technique applied in modern plant breeding programs as it can produce doubled haploid (DH) plants and accelerate the development of new varieties. Furthermore, as a single-cell culture technique, the isolated microspore culture provides an excellent platform for studying microspore embryogenesis. However, the reports on isolated microspore culture are rather limited in rice due to the low callus induction rate, poor regeneration capability, and high genotypic dependency. The present study developed an effective isolated microspore culture protocol for high-frequency androgenesis in four japonica rice genotypes. Several factors affecting the isolated microspore culture were studied to evaluate their effects on callus induction and plantlet regeneration. Results: Low-temperature pre-treatment at 4 ℃ for 10–15 days could effectively promote microspore embryogenesis in japonica rice. A simple and efficient method was proposed for identifying the microspore developmental stage. The anthers in yellow-green florets located on the second type of primary branch on the rice panicle were found to be the optimal stage for isolated microspore culture. The most effective induction media for callus induction were IM2 and IM3, depending on the genotype. The optimal concentration of 2, 4-D in the medium for callus induction was 1 mg/L. Callus induction was negatively affected by a high concentration of KT over 1.5 mg/L. The differentiation medium suitable for japonica rice microspore callus comprised 1/2 MS, 2 mg/L 6-BA, 0.5 mg/L NAA, 30 g/L sucrose, and 6 g/L agar. The regeneration frequency of the four genotypes ranged from 61–211 green plantlets per 100 mg calli, with Chongxiangjing showing the highest regeneration frequency. Conclusions: This study presented an efficient protocol for improved callus induction and green plantlet regeneration in japonica rice via isolated microspore culture, which could provide valuable support for rice breeding and genetic research. [ABSTRACT FROM AUTHOR]

Mitogen‐activated protein kinase (MAPK) signalling cascades are functionally important signalling modules in eukaryotes. Transcriptome reprogramming of immune‐related genes is a key process in plant immunity. Emerging evidence shows that plant MAPK cascade is associated with processing (P)‐body components and contributes to transcriptome reprogramming of immune‐related genes. However, it remains largely unknown how this process is regulated. Here, we show that OsMPK12, which is induced by Magnaporthe oryzae infection, positively regulates rice blast resistance. Further analysis revealed that OsMPK12 directly interacts with enhancer of mRNA decapping protein 4 (OsEDC4), a P‐body‐located protein, and recruits OsEDC4 to where OsMPK12 is enriched. Importantly, OsEDC4 directly interacts with two decapping complex members OsDCP1 and OsDCP2, indicating that OsEDC4 is a subunit of the mRNA decapping complex. Additionally, we found that OsEDC4 positively regulates rice blast resistance by regulating expression of immune‐related genes and maintaining proper mRNA levels of some negatively‐regulated genes. And OsMPK12 and OsEDC4 are also involved in rice growth and development regulation. Taken together, our data demonstrate that OsMPK12 positively regulates rice blast resistance via OsEDC4‐mediated mRNA decay of immune‐related genes, providing new insight into not only the new role of the MAPK signalling cascade, but also posttranscriptional regulation of immune‐related genes. [ABSTRACT FROM AUTHOR]

[Display omitted] • Novel multiscale variational autoencoder regressor is proposed. • The multiscale CNN module can extract multiscale information. • Establishing prediction models for ethylene and propylene production for energy structure optimization. • The prediction accuracy of the proposed model on ethylene and propylene data can reach around 95% and 96%, respectively. • The proposed model can effectively increase propylene and ethylene production and reduce carbon emissions. As modern industries increase in scale and integration, the industrial process data show more complex dynamic time variability. To solve the dynamic time-varying problem of industrial process data, a novel multiscale variational autoencoder (MSVAE) based Regressor (REG) (MSVAE-REG) is proposed for production prediction and energy saving. The encoder of the MSVAE is constructed by multiscale convolutional neural network (MSCNN) to extract the multiscale temporal dynamic features, including the overall and local trend features in the Gaussian latent space. Then, the decoder of the MSVAE recovers the input data to enhance the dynamic adaptability of multiscale features. Moreover, the REG utilizes the gated recurrent unit (GRU) to build a dynamic relationship between multiscale temporal dynamic features and the predicted output. Finally, the proposed model is verified on the propylene and ethylene production datasets. Compared with the back propagation (BP) network, the extreme learning machine (ELM), the radial basis function (RBF), the convolutional neural network (CNN) and the variational autoencoder (VAE), the MSVAE-REG achieves state-of-the-art results, with the prediction accuracy respectively reaching about 95% and 96%, providing a new judgment basis for optimizing the production process and saving energy. [ABSTRACT FROM AUTHOR]

The inner liners of reusable regeneratively-cooled thrust chambers endure significant thermal and mechanical loads, resulting in doghouse deformation and even cracks during cyclic operations. To correctly reveal the failure mechanism of the thrust chamber inner liner, this study investigates the material properties for CuZr alloy and develops a temperature-dependent material model spanning from cryogenic to elevated temperatures. Firstly, we experimentally obtain the thermal and mechanical properties of the material in the temperature range from 77 K to 900 K. The experimental data reveal that the material properties vary considerably with temperature. Then, to precisely characterize the mechanical behavior of CuZr alloy under cyclic loading across a wide temperature range, a material model that combines Voce nonlinear isotropic hardening model with Chaboche nonlinear kinematic hardening model is proposed, and temperature-dependent parameters of this model are calibrated and verified. Finally, the developed material model is applied to perform the thermal-structural analysis on a reusable thrust chamber, with the aim of investigating its failure mechanism. The results demonstrate the capability of the developed model to accurately replicate the doghouse deformation of the inner liner and quantitatively capture the ratcheting effect. [ABSTRACT FROM AUTHOR]

Background: To compare the clinical characteristics and prognoses of patients with isolated regional lymph node recurrent nasopharyngeal carcinoma (irrNPC) who underwent surgery or re-irradiation treatment. Methods: We retrospectively reviewed 124 irrNPC patients who underwent initial radiotherapy between January 2010 and December 2020. The staging of regional lymph node recurrence was as follows: 75.8% for rN1, 14.5% for rN2, and 9.7% for rN3. Fifty-five patients underwent regional lymph node surgery (Surgery group), and sixty-nine patients received salvage radiotherapy with or without chemotherapy (Re-irradiation group). The survival rate was compared using Kaplan‒Meier analysis and evaluated by the log-rank test. Cox proportional hazard models were used to analyze prognostic factors. Results: The median follow-up time was 70 months, the 5-year overall survival (OS) was 74%, and the median survival time was 60.8 months. There were no significant differences in 5-year OS (75.6% vs. 72.4%, P = 0.973), regional recurrence-free survival (RRFS, 62.7% vs. 71.1%, P = 0.330) or distant metastasis-free survival (DMFS, 4.2% vs.78.7%, P = 0.677) between the Surgery group and Re-irradiation group. Multivariate analysis revealed age at recurrence, radiologic extra-nodal extension (rENE) status, and recurrent lymph node (rN) classification as independent prognostic factors for OS. The rENE status was an independent prognostic factor for DMFS. Subgroup analysis of the Surgery group revealed that the rN3 classification was an adverse prognostic factor for OS. Age at recurrence ≥ 50 years, GTV-N dose, and induction chemotherapy were found to be independent prognostic factors for OS, RRFS, and DMFS, respectively, in the Re-irradiation group. Conclusions: For NPC patients with isolated regional lymph node recurrence after initial radiotherapy, those who underwent surgery had survival prognosis similar to those who underwent re-radiotherapy with or without chemotherapy. A prospective study is needed to validate these findings. [ABSTRACT FROM AUTHOR]

Background & Aims: Following the classification of metabolic dysfunction‐associated fatty liver disease (MAFLD), non‐alcoholic fatty liver disease (NAFLD) has recently been redefined again as metabolic dysfunction‐associated steatotic liver disease (MASLD). However, the distinctions in characteristics and mortality outcomes between NAFLD, MAFLD and MASLD remain unclear. Methods: We analysed data from 7519 participants in the third National Health and Nutrition Examination Surveys of United States (US) and their linked mortality until 2019. Survey weight‐adjusted multivariable Cox proportional model was used to study the mortality over three terms. Results: The prevalence of NAFLD, MAFLD and MASLD was 18.5%, 19.3% and 20.8%, respectively. Most individuals with NAFLD (94.5%) or MAFLD (100%) can be classified as MASLD, while a relatively low percentage of those with MASLD were also diagnosed with either NAFLD (84.1%) or MAFLD (92.7%). During a median follow‐up of 26.9 years, both MAFLD and MASLD were associated with increased risk of all‐cause mortality (adjusted hazard ratio [aHR] 1.18, 95% CI 1.04–1.33 and 1.19, 1.06–1.34, respectively), this association was mainly observed in NAFLD−/MASLD+ subgroups. NAFLD was not associated with all‐cause mortality. However, all three terms were associated with an increased risk of all‐cause mortality in individuals with advanced fibrosis (aHR: 1.71–1.81). Subgroup analyses showed that higher risk of all‐cause mortality for both MAFLD and MASLD were observed among older adults (≥65 year), non‐Hispanic whites and those without diabetes. Conclusions: Both MASLD and MALFD were linked to higher all‐cause mortality risk, but MASLD identified a greater number of individuals compared to MAFLD. [ABSTRACT FROM AUTHOR]

In the present study, a series of shaking table model tests were performed on a slope with a gabion reinforced retaining wall. Transfer functions were employed to compute the inherent frequencies of the slope. Furthermore, the investigation examined various aspects of the slope, including the peak acceleration amplification factor, incremental dynamic stresses, displacements, and tensile forces. Additionally, the study employed the Hilbert Huang transform (HHT) to analyze the slope's time-frequency characteristics and energy distribution. The findings of the study revealed that there is an inverse relationship between the amplitude of the input seismic wave and the natural frequency of the top of the gabion reinforced retaining wall slope. As the amplitude of the seismic wave increases, the natural frequency of the slope decreases. The amplification factors for peak acceleration were all found to be less than 1.9, suggesting a notable dissipation of seismic energy in comparison to typical slopes. The response of incremental dynamic stress was most pronounced in the middle section of the slope, followed by the top of the slope. The magnitude of the incremental displacement was found to be highest at layer 4, whereas the incremental tensile force exhibited its maximum value at layer 5. The dynamic response exhibited the least pronounced characteristics at the lower portion of the slope, demonstrating the most stable behavior. The peak frequencies observed in the Hilbert marginal spectrum displayed comparable characteristics to the natural frequencies. • Large-scale shaking table tests were conducted on the stepped gabion reinforced retaining wall slope. • The natural frequency, damping ratio, and dynamic shear modulus were used to analyze the dynamic characteristics of the gabion reinforced retaining wall slope under seismic action. • The energy dissipation mechanism of the gabion reinforced retaining wall slope was investigated by peak acceleration amplification factor, dynamic stress increment, displacement increment and tension increment. • The time-frequency domain and energy perspective of the gabion reinforced retaining wall slope under seismic action was analyzed by using HHT, and the damage evolution mechanism inside the slope when the amplitude of input seismic wave increases is revealed. [ABSTRACT FROM AUTHOR]

In our relentless pursuit of improving healthcare and elevating wellness standards, we have unveiled a groundbreaking approach that amalgamates the cutting-edge realms of quantum optics, Channel coding, artificial intelligence (AI), and Advanced Optical Systems (optical IoT). This innovative collaboration is meticulously designed to fortify healthcare systems while enhancing cybersecurity protocols in the healthcare imaging sector. At the heart of this transformative initiative lies the cyber security threat and detecting analysis (CYSTDA), a groundbreaking framework that seamlessly integrates the strengths of AI, quantum optics, and advanced optical IoT to secure sensitive imaging data and systems. Quantum optics, known for its precision and sensitivity, offers a robust foundation for safeguarding imaging data. By leveraging quantum principles, it becomes possible to encode and protect visual information in an exceptionally secure manner. Channel coding techniques, initially designed for communication systems, are adapted to ensure the integrity and confidentiality of imaging data transmission, mitigating the risks of cyberattacks. On the other hand, AI plays a crucial role in CYSTDA by providing advanced threat detection techniques using deep learning models such as neural networks, enabling real-time monitoring and analysis of imaging data, and detecting anomalies and potential security breaches. This approach enhances the cybersecurity posture of imaging systems and safeguards the confidentiality of the visual information. Integration of advanced optical IoT is the other advantage of CYSTDA for improving cybersecurity in imaging; by deploying interconnected security devices and sensors, CYSTDA establishes a dynamic and secured ecosystem. Overall, the CYSTDA, which leverages the advanced technologies discussed earlier, was used to elevate cybersecurity protocols for imaging. This framework has the potential to significantly enhance the security of visual data, imaging devices, and infrastructure, safeguarding the confidentiality and integrity of imaging information in an increasingly digital and interconnected world. [ABSTRACT FROM AUTHOR]

An efficient and mild multicomponent reaction (MCR) for the preparation of vinyl sulfone is reported, which is achieved by the hydrogenation/difunctional sulfonylation of an alkynyl ester with the corresponding N-allyl bromodifluoroacetamide, DABSO and H2O under visible light conditions without the need for any metal catalysts or additives. This transformation is the first example of a conversion using H2O as the hydrogen source to interact with DABCO to form [DABCO-H]+, which ultimately reacts with the vinyl group, with the advantage of high chemoselectivity and step economy. Notably, the method produces different sulfonylation products with the same substrate regulated by the presence or absence of H2O, which greatly reduces the cost of the chemical reaction and exhibits good functional group tolerance and substrate range. In addition, gram-scale experiments proceeded smoothly, proving the practicality of the methodology. [ABSTRACT FROM AUTHOR]

Highlights: The innovation of this work mainly lies in the auto-regulation of reactive oxygen species (ROS) balance effective by combination of ROS antibacterial and ROS scavenging anti-inflammatory functions with a core–shell nanoplatform (CeO2@ZIF-8/Au), which can not only achieve high antibacterial efficiency, but also promote wound healing, and provide a new idea for the nano-catalytic system in the field of wound healing of bacterial infection. Reactive oxygen species (ROS) plays important roles in living organisms. While ROS is a double-edged sword, which can eliminate drug-resistant bacteria, but excessive levels can cause oxidative damage to cells. A core–shell nanozyme, CeO2@ZIF-8/Au, has been crafted, spontaneously activating both ROS generating and scavenging functions, achieving the multi-faceted functions of eliminating bacteria, reducing inflammation, and promoting wound healing. The Au Nanoparticles (NPs) on the shell exhibit high-efficiency peroxidase-like activity, producing ROS to kill bacteria. Meanwhile, the encapsulation of CeO2 core within ZIF-8 provides a seal for temporarily limiting the superoxide dismutase and catalase-like activities of CeO2 nanoparticles. Subsequently, as the ZIF-8 structure decomposes in the acidic microenvironment, the CeO2 core is gradually released, exerting its ROS scavenging activity to eliminate excess ROS produced by the Au NPs. These two functions automatically and continuously regulate the balance of ROS levels, ultimately achieving the function of killing bacteria, reducing inflammation, and promoting wound healing. Such innovative ROS spontaneous regulators hold immense potential for revolutionizing the field of antibacterial agents and therapies. [ABSTRACT FROM AUTHOR]

Osteoarthritis (OA) is a chronic joint disease characterized by synovitis and joint cartilage destruction. The severity of OA is highly associated with the imbalance between M1 and M2 synovial macrophages. In this study, a novel strategy is designed to modulate macrophage polarization by reducing intracellular reactive oxygen species (ROS) levels and regulating mitochondrial function. A ROS‐responsive polymer is synthesized to self‐assemble with astaxanthin and autophagy activator rapamycin to form nanoparticles (NP@PolyRHAPM). In vitro experiments show that NP@PolyRHAPM significantly reduced intracellular ROS levels. Furthermore, NP@PolyRHAPM restored mitochondrial membrane potential, increased glutathione (GSH) levels, and promoted intracellular autophagy, hence successfully repolarizing M1 macrophages into the M2 phenotype. This repolarization enhanced chondrocyte proliferation and vitality while inhibiting apoptosis. In vivo experiments utilizing an anterior cruciate ligament transection (ACLT)‐induced OA mouse model revealed the anti‐inflammatory and cartilage‐protective effects of NP@PolyRHAPM, effectively mitigating OA progression. Consequently, the findings suggest that intra‐articular delivery of ROS‐responsive nanocarrier systems holds significant promise as a potential and effective therapeutic strategy for OA treatment. [ABSTRACT FROM AUTHOR]

Aiming at low permeability, high water content light reservoir with a recovery rate higher than 20%, an improved air injection enhanced heat flooding technology is applied by combining the combustion reaction flow and flue gas flooding mechanism. The method involves the injection of air into the reservoir, which reacts with the crude oil at temperatures ranging from 220 to 300 °C. This reaction consumes part of the oil, enabling effective evaporation and flow of the remaining oil. This process combines combustion reaction flow with flue gas flooding, using high-temperature oxidation reactions to mobilize residual oil. Experimental results from combustion tube tests demonstrate stable reaction fronts, peak temperatures reaching up to 550 °C, and a significant increase in recovery rates, reaching 73.8% in some cases. Field applications of this technology require maintaining high air flux and burning rates in low-permeability zones to ensure effective heat-driven evaporation. The geological model of the well group shows that the recovery factor of the target block can be increased by more than 20% by air injection based on the water drive recovery factor of 28%–30%. The oil exchange ratio can be less than 4000 sm3/m3 by optimizing the air injection rate and oxygen content. The research results provide technical feasibility for heat flooding to significantly improve oil flow and recovery in low-permeability light oil reservoirs. [ABSTRACT FROM AUTHOR]

Knowledge graph (KG) has been fully considered in natural language generation (NLG) tasks. A KG can help models generate controllable text and achieve better performance. However, most existing related approaches still lack explainability and scalability in large‐scale knowledge reasoning. In this work, we propose a novel CogNLG framework for KG‐to‐text generation tasks. Our CogNLG is implemented based on the dual‐process theory in cognitive science. It consists of two systems: one system acts as the analytic system for knowledge extraction, and another is the perceptual system for text generation by using existing knowledge. During text generation, CogNLG provides a visible and explainable reasoning path. Our framework shows excellent performance on all datasets and achieves a BLEU score of 36.7, which increases by 6.7 compared to the best competitor. [ABSTRACT FROM AUTHOR]

Single-mode linear ultrasonic motors (SMLUMs) have the advantages of excellent accuracy, long travel distance, single vibration mode and simple driving scheme, which have been applied in precision positioning and micro/nano manipulation actuators. However, it is still challenging to accurately and efficiently analyze such motors due to their complicated electro-mechanical coupling behaviors under contact-based operating conditions. This paper proposed an improved equivalent circuit model for a single-mode linear ultrasonic motor considering the real contact-based operating conditions, where a new actuation mode of the V-shape transducer is adopted. The electro-mechanical coupling characteristics of the stator under contact-based boundary condition is modeled by a modified admittance-type equivalent circuit, where the variable contact stiffness and loss are characterized between the stator and the mover. The friction drive mechanism is modeled by a thyristor rectifying circuit to characterize the intermittent actuation characteristics, and the nonlinear relationship between the motor characteristics and the contact-based operating conditions is initially characterized from the circuit viewpoint. The merits and the applications of the circuit-based model are exemplified by parameter identification and modification, losses segregation, admittance characteristics analysis and output and control characteristics evaluation for such SMLUMs. [Display omitted] • The real contact-based operating conditions are considered in equivalent circuit modeling. • The friction drive mechanism is initially characterized and clarified from circuit viewpoint. • A circuit-based method is proposed to conduct segregation and evaluation of various losses. • The motor output and control characteristics can be evaluated by the proposed model. [ABSTRACT FROM AUTHOR]

[Display omitted] • BiOI/CdWO 4 with large specific surface area was synthesized by hydrothermal method. • The combination of aptamers and new materials improves the performance of aptamer-based sensors significantly. • A novel label- free PEC aptamer sensor for the detection of ochratoxin A was developed. • The photocurrent signal of BiOI/CdWO 4 could be effectively enhanced by in-situ growth of Ag 2 S quantum dots. • The photoelectrochemistry aptamer sensor has the advantages of high sensitivity, strong stability, strong selectivity, low detection limit and wide detection range. Ochratoxin A (OTA) is a kind of mycotoxin. It widely exists in all kinds of mammals and has teratogenicity and cytotoxicity. In this paper, a label-free photoelectrochemical (PEC) aptamer sensor based on bismuth oxyiodide/cadmium tungstate (BiOI/CdWO 4) was designed to detect OTA. The BiOI/CdWO 4 heterojunction is an excellent optoelectronic active material with remarkable chemical stability. AgNO 3 and Na 2 S were selected to grow in situ to form Ag 2 S quantum dots, which were sensitized to enhance the absorption of visible light and promote the generation of photocurrent. In this system, with the increasing of OTA concentration, the photoelectric signal intensity reduces as the specific binding with aptamer. When the concentration of OTA is between 0.01 ng/mL and 50.00 ng/mL, the linear equation is I (μA) = 48.95 – 10.276 lg c (c OTA , ng/mL), R2 = 99.281, and the detection limit is 0.823 pg/mL. The newly designed PEC aptamer sensor has exceptional stability, sensitivity, and reproducibility, making it capable of detecting OTA effectively and sensitively. [ABSTRACT FROM AUTHOR]

In this work, P-MIG is used as additive process, a new low-cost Co-free maraging steel wire is used as raw material to additive manufacturing block component, and the microstructure and mechanical properties of the component is investigated. The microstructure of the component is composed of martensite and austenite, and the closer to the bottom, the more serious the elemental segregation and the more austenite content. From the top to the bottom the high-angle grain boundaries increase and the grain size decrease, the difference of the heat dissipation condition and the thermal cycle are the reasons for this phenomenon. The texture of austenite is mainly Cube texture, and the texture of martensite is Rotated Cube texture and Goss texture. The tensile strength of XD, YD, ZD three directions is 1172 ± 15 MPa, 1021 ± 7 MPa, 1139 ± 16 MPa, respectively, impact toughness is 64.7 ± 1.6 J/cm2, 51.1 ± 5.6 J/cm2, 51.4 ± 3.1 J/cm2, respectively, TRIP effect occurs in the process of tensile, the main mode of fracture in tensile and impact is toughness fracture. The microhardness decreases gradually from bottom to top, which is due to the short-lived aging strengthening by thermal cycle, the change of grain size and GND density. The results of the work reveal the successful application of the new low-cost Co-free maraging steel wire in WAAM and provide an important reference for the adjustment of additive process, subsequent heat treatment and the adjustment of wire composition. [ABSTRACT FROM AUTHOR]

[Display omitted] • The integration of vibration reduction and energy harvesting for space vehicles is studied. • An electromagnetic-pneumatic regenerative shock absorber is proposed for the first time. • The coupling model of friction-electromagnetic-pneumatic damping is established. • The proposed new regenerative shock absorber has excellent damping smoothness. In recent years, the development of space exploration has attracted much attention. In order to save energy for lunar/mars rover, an electromagnetic-pneumatic regenerative shock absorber (EP-RSA) is proposed in this paper, which can harvest the vibration energy of rovers traveling on rough roads. Structurally, the design of the hybrid regenerative shock absorber includes three modules: vibration input, transmission, and generator. It is worth emphasizing that the transmission module involves pneumatic damping to provide enough damping force and improve the driving comfort for the rover. Mathematical modeling and simulation analysis of the dynamics and energy harvesting characteristics of the EP-RSA are carried out. Finally, the system prototype is manufactured and the dynamic and energy output performance are tested in the bench test environment. The experimental results show that the introduction of pneumatic damping makes the force–displacement curve smoother, and the damping force is increased by nearly 50 times. Meanwhile, the power output results of the system match the simulation results, and the average power can reach 1.26 W, indicating that the proposed EP-RSA is promising for the energy saving and dynamics improvement of the space exploration rover. [ABSTRACT FROM AUTHOR]

• AS-IV impedes macrophage senescence and promotes osteogenic differentiation of BMSCs through the modulation of STING/NF-κB. • AS-IV treatment ameliorated macrophage senescence, abnormal bone microstructure, and bone mass loss in a mouse model of SOP. Senile osteoporosis (SOP) is an age-related metabolic bone disease that currently lacks specific therapeutic interventions. Thus, this study aimed to investigate the effect of Astragaloside IV (AS-IV) on macrophage senescence, bone marrow mesenchymal stem cell (BMSC) osteogenesis, and SOP progression. A senescent macrophage model was established and treated with varying concentrations of AS-IV. Cell activity was measured using the CCK8 assay. The senescence levels of macrophages were evaluated through β-galactosidase staining, PCR, and immunofluorescence. Macrophage mitochondrial function was assessed using ROS and JC-1 staining. Macrophage polarization was evaluated through PCR, Western blot, and immunofluorescence. The inhibitory effects of AS-IV on macrophage senescence were investigated using Western blot analysis. Furthermore, the effects of macrophage conditioned medium (CM) on BMSCs osteogenic were detected using ALP, alizarin red, and PCR. AS-IV inhibited macrophage senescence and M1 polarization, alleviated mitochondrial dysfunction, and promoted M2 polarization. Mechanistically, it suppressed the STING/NF-κB pathway in H2O2-activated macrophages. Conversely, the STING agonist c-di-GMP reversed the effects of AS-IV on macrophage senescence. Additionally, AS-IV-induced macrophage CM promoted BMSC osteogenic differentiation. In vivo, AS-IV treatment ameliorated aberrant bone microstructure and bone mass loss in the SOP mouse model, inhibited macrophage senescence, and promoted M2 polarization. By modulating the STING/NF-κB signaling pathway, AS-IV potentially inhibited macrophage senescence and stimulated osteogenic differentiation of BMSCs, thus exerting an anti-osteoporotic effect. Consequently, AS-IV may serve as an effective therapeutic candidate for the treatment of osteoporosis. [ABSTRACT FROM AUTHOR]

Short answer scoring is a significant task in natural language processing. On datasets comprising numerous explicit or implicit symbols and quantization entities, the existing approaches continue to perform poorly. Additionally, the majority of relevant datasets contain few-shot samples, reducing model efficacy in low-resource scenarios. To solve the above issues, we propose a Multi-level Semantic Inference Model (M-Sim), which obtains features at multiple scales to fully consider the explicit or implicit entity information contained in the data. We then design a prompt-based data augmentation to construct the simulated datasets, which effectively enhance model performance in low-resource scenarios. Our M-Sim outperforms the best competitor models by an average of 1.48 percent in the F1 score. The data augmentation significantly increases all approaches' performance by an average of 0.036 in correlation coefficient scores. • M-Sim improves Chinese few-shot SAS with multi-scale similarity calculation. • New prompt-based data augmentation enhances SAS models low-resource performance. • New Chinese SAS dataset released to promote further study. [ABSTRACT FROM AUTHOR]