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Depression is associated with alterations in prosody when speaking (e.g., less variation in pitch, slowed speech rate), but less is known about its impact on emotional prosody. This is particularly important to investigate in parent–child contexts, as parental expression of emotion may contribute to the intergenerational transmission of depression risk. The current study asked mothers of preschool-aged children (with and without a history of major depressive disorder during their child's lifetime) to produce child-relevant sentences in neutral, angry, and happy tones of voice. We examined whether groups' portrayals were acoustically or perceptually different, in speech analyses and listener ratings. Mothers with a history of depression expressed happiness with less range in pitch and a slower speech rate (slower, more monotonous voice) than mothers with no history of depression. Across groups, happy exemplars with less range in pitch were rated as less emotionally intense, recognizable, and authentically happy by listeners; slower speech rate was associated with opposite perceptual ratings. However, listeners' ratings did not differ by depression group as a whole. Results suggest that a history of depression may influence maternal vocal expression of happiness, but that its impact on listeners' perceptions may depend on mothers' idiosyncratic use of acoustic cues. [ABSTRACT FROM AUTHOR]

ABSTRACT Objective Clinical Consideration Conclusion Clinical Significance The aim of this report is to present the workflow of a surgical procedure involving U‐shaped splitting in an envelope flap with simultaneous implant placement using two digital guides for patients with insufficient bone width and labial concavity.Two digital guides and an envelope flap are proposed in this report. An implant drilling guide and an osteotomy guide guarantee the precise execution of surgical procedures. Using an envelope flap enhances the integrity of the labial mucoperiosteum, minimizing surgical trauma and improving the effect of bone augmentation.With the assistance of two digital guides, precise U‐shaped splitting in an envelope flap can minimize surgical trauma and have a significant effect on horizontal bone augmentation.This workflow considers the implant positions, the scope of osteotomy, and the kind of flap. It ensures minimal surgical trauma and excellent bone augmentation effect, which means predictable esthetic outcomes and stability in oral implantology, and provides a considerable solution for patients with insufficient bone width and labial concavity. [ABSTRACT FROM AUTHOR]

ABSTRACT Blueberry flower buds cultivated in greenhouses develop during both autumn and spring, with floral induction being a critical process for flowering, influenced by environmental factors. This study aimed to clarify the regulatory mechanisms governing floral induction in greenhouse blueberries, focusing on the similarities and differences in flower bud differentiation between the spring and autumn seasons. Understanding these mechanisms is pivotal for enhancing blueberry production. In this study, we analysed the phenotypic characteristics associated with flower bud differentiation and observed that short photoperiods markedly affect the induction process. Transcriptomic analyses revealed distinct major metabolic pathways activated in autumn compared to spring. Seasonal variations in carbohydrate metabolism were also noted, with sucrose hydrolysis being prominent in autumn and sucrose synthesis prevailing in spring. The interplay between circadian rhythms and photosynthesis appeared to facilitate the allocation of sugars for bud development. Subsequent investigations underscored the sensitivity of VcCO3 to variations in photoperiod. Predominantly localised in the nucleus, VcCO3 facilitated floral induction in response to short photoperiods by activating the expression of downstream genes, including VcFT, VcLFY, VcAP3, and VcSOC1. Furthermore, VcCO3 exhibits a close association with the sugar metabolism gene VcSUS, promoting increased sucrose concentrations. [ABSTRACT FROM AUTHOR]

Correlation between echocardiographic and pathoanatomic variables and their prognostic value in murine cardiomyopathy models remain unknown. Using echocardiography, morphometrics, and survival monitoring, we characterized transgenic (TG) mice with dilated cardiomyopathy due to cardiac overexpression of β2‐adrenoceptors focusing on predicting heart failure (HF) risk and HF mortality. In 12‐month‐old non‐TG and TG mice, echocardiography was performed to determine left ventricular (LV) dimensions (d), wall thickness (h), and fractional shortening (FS). Animals were monitored for 3 months for survival. Organ weights and pathological events indicating left HF were determined. TG mice (n = 76) had reduced FS and enlarged LV, and 79% died of HF or likely arrhythmias during the follow‐up period while all non‐TG mice (n = 26) survived. These mice with left HF also had pulmonary congestion and hypertrophy/dilatation of the right ventricle (RV). Weights of lungs, RV, and atria were intercorrelated (r = 0.79–0.83) and also negatively correlated with FS × (h/d) index (r = −0.502 to −0.609). By FS × (h/d) tertiles, TG mice of low tertiles were identified with the highest mortality (96%) largely due to HF (76%). In conclusion, in aged cardiomyopathy mice a good correlation existed between echocardiographic and pathoanatomic variables. Echocardiography‐derived LV function and remodeling were useful in identifying a subgroup of TG mice with a high risk of HF and HF fatality. [ABSTRACT FROM AUTHOR]

AbstractThe concept of regions has long been crucial for understanding and managing Earth’s phenomena, leading to regionalization, aggregating smaller areas into larger, contiguous, and homogeneous regions to achieve specific goals. Open-source regionalization is gaining traction because it reduces dependence on commercial software and fosters wider adoption in analysis and decision-making. However, these packages, often designed by experts for specialized tasks, can be challenging to understand and utilize due to domain-specific jargon and functionalities, especially for unfamiliar users. A prevalent disconnect must be addressed: How can we make a complex optimization approach available to a broad audience with various backgrounds? This study introduces RegionDefiner, a Large Language Modeling (LLM)-powered conversational agent, to comprehensively understand the functionality, inputs, outputs, and potential applications of regionalization problems. We selected it as an illustrative example due to its wide-ranging potential for delineating study regions in various applications. RegionDefiner is designed to guide users in framing their problems, collecting necessary data, and implementing solution approaches in a straightforward and user-centric manner. The experiments demonstrate that RegionDefiner interprets and presents the results in an understandable way for all audiences, thus bridging the gap between intricate computations and practical problem-solving needs. [ABSTRACT FROM AUTHOR]

Key Clinical Message: Coronary artery aneurysm (CAA), marked by diffuse or localized dilation of artery, can cause life‐threatening complications in acute coronary syndrome. This report presents a case of CAA combined with acute ST‐segment elevation myocardial infarction, successfully treated with cardiac rehabilitation exercise therapy, offering insights for clinical practice. [ABSTRACT FROM AUTHOR]

This paper proposes a novel strategy to fabricate porous calcium hex-aluminate (CA 6) ceramics using CaCl 2 -KCl as reactive medium. Effects of CaCl 2 -KCl content and sintering temperature on microstructure and properties of porous CA 6 ceramics are systematically studied. CaCl 2 -KCl serves as both a pore former and an additional source of CaO, eliminating the need for additional salt-washing treatment. By optimizing CaCl 2 -KCl content to 20 wt%, porous CA 6 ceramics with well cross-interlocking plate-like structures, possessing low thermal conductivity of 0.32 W·(m·K)−1 (1000°C), high apparent porosity of 68.28%, and desirable compressive strength of 6.76 MPa, are fabricated at 1300°C. This work not only validates the promising applicability of porous CA 6 materials for thermal insulation, but also introduces an auspicious fabrication methodology for thermal insulation materials. [ABSTRACT FROM AUTHOR]

Clostridium perfringens is one of the critical causative agents causing diarrhea in piglets, with significant economic losses to the pig industry. Under normal gut microbiota homeostasis and well-managed barns, diarrhea caused by C. perfringens could be controlled. Some reports show that probiotics, such as Bacillus subtilis, are beneficial in preventing necrotic enteritis (NE) in chickens, but few reports on piglets. Clostridium perfringens was found in the piglets’ diarrhea with intestinal microbiota dysbiosis in our survey. Bacillus subtilis G2B9-Q, which was isolated from the feces of healthy pigs, was found to have anti-Clostridium activity after screening. Clostridium perfringens was used to challenge mice by intraperitoneal injection for modeling to evaluate the anti-infective activity of cell-free supernatant (CFS) of B. subtilis G2B9-Q and different concentrations of B. subtilis G2B9-Q by oral administration. The results showed that G2B9-Q can mitigate intestinal lesions caused by C. perfringens infection, reduce inflammatory reactions, and modulate intestinal microbiota. The CFS of G2B9-Q can alleviate the pathological damage of intestinal tissues caused by C. perfringens infection, reduce the concentration of TNF-α and IL-10 in the sera of mice, as well as the relative expression levels of alpha toxin (CPA), perfringolysin O (PFO) toxin, IL-10, IL-22, and TNF-α in the jejunum and colon tissues, and alleviate the changes in gut microbiota structure caused by C. perfringens infection, which showed better therapeutic effects and indicated that the metabolites of G2B9-Q are essential mediators for their beneficial effects. Therefore, the CFS of G2B9-Q could potentially replace antibiotics in treating C. perfringens infection. [ABSTRACT FROM AUTHOR]

Spent galvanizing acid solution contains high concentrations of zinc salts, ferrous salts, and residual acids, exhibiting extremely high value-added recovery potential. However, achieving the efficient extraction and separation of Zn over Fe becomes particularly challenging under elevated Zn ion concentration. Here, the key extraction parameters, such as modifier ratio, Cyanex 923 concentration and ratio of organic phase to aqueous phase (O/A), are investigated. The stripping and regeneration of extractant, extraction mechanism, as well as high-value recovery of Zn and Fe resources are also comprehensively expounded. After the two-stage extraction, the extraction efficiency of Zn and Fe is 98.92 ​% and 2.09 ​%, respectively. Moreover, the stripping efficiency of Zn reaches 92.3 ​% with O/A ratio of 1 : 2, using oxalic acid as stripping agent. The predominant extracted species is confirmed to be Zn Cl 3 − , resulting in the formation of HZn Cl 3 ∙ R 3 PO complex. More importantly, the regenerated extractant can be recycled back into the extraction process, and the reproduced HCl, high-value recovered ZnO and Fe 2 O 3 can be used for different industrial fields. These findings lay a solid foundation for the efficient separation and comprehensive recovery of high-concentration spent galvanizing acid solution. The developed solvent extraction-stripping-calcination process has achieved the regeneration and recycling of extractant and HCl, as well as efficient recovery of high-value ZnO and Fe 2 O 3. [Display omitted] • Efficient extraction and separation of Zn over Fe from high-concentration spent galvanizing acid have been achieved. • The predominant species Zn Cl 3 − from spent galvanizing acid was extracted in the form of HZn Cl 3 ∙ R 3 PO complex. • Entire solvent extraction-stripping-calcination process realizes recovery of Zn, Fe and HCl, and recycling of extractant. [ABSTRACT FROM AUTHOR]

AbstractIn order to reach the fire protection standard for new energy vehicle battery packs, the incorporation of SiO2 aerogel particles as a functional filler in the nitrogen and phosphorus fire-retardant system is necessary due to the inadequate mechanical properties. The effects of SiO2 aerogel on the properties of the coatings for the electric car battery pack were investigated by fire protection test, thermogravimetric analysis, limited oxygen index, UL-94 vertical test, combustion test, mechanical properties test, and weathering resistance test. The backside temperature fireproof coatings containing 1.5% SiO2 aerogel was effectively reduced to 250.2 ± 0.1 °C and the residual weight of the coating reached 32.61 ± 0.01%. The composition and structure of the carbon layer were analyzed further. Especially, the weight loss percentage of the fireproof coating is only 5.87 ± 0.02% in the water resistance test. However, excessive SiO2 aerogel decreased the performances of fireproof coatings. [ABSTRACT FROM AUTHOR]

Recently, acoustic vortices with orbital angular momentum (OAM) have attracted great attention and interest owing to their extensive applications. Based on the generalized Snell's law (GSL), acoustic vortex beams can be observed by constructing different types of acoustic metasurfaces immersed into cylindrical waveguides. However, owing to the restrictions of the phase gradient of metasurface structures and the critical order of propagating vortex beams, there exist great challenges in realizing complex modulation of vortex beams and designing advanced multifunctional sound devices. Here, we theoretically study and experimentally demonstrate the extended GSL in designing a mode converter of vortex beams based on phase-gradient acoustic metagratings (AMs). We demonstrate that the extended GSL can not only accurately predict the transmitted or reflected orders of vortex beams created by a series of AMs with arbitrary phase gradient ξ, but also effectively overcome the limitations of both the phase gradient and the critical order. More importantly, we design a type of mode converter of vortex beams and realize the mode conversion of output vortex beams by simply modulating the orders of input vortex beams. To present it, we experimentally demonstrate the switch between the output vortex beams with the orders of −2 and 2 through the same phase-gradient AM by using the input vortex beams with the orders of 1 and −1, respectively, which can be separately predicted by the GSL and the extended GSL. Our work paves a way for the complex modulation of acoustic vortex beams and the design of multifunctional OAM-based sound devices with practical applications. [ABSTRACT FROM AUTHOR]

Fast radio bursts (FRBs) are cosmological radio transients with millisecond durations and extremely high brightness temperatures. One FRB repeater, FRB 180916.J0158+65 (FRB 180916B), was confirmed to appear 16.35-day periodic activities with 5-day activity window. Another FRB repeater, FRB 121102, and two soft gamma-ray repeaters (SGRs), SGR 1935+2154 and SGR 1806−20, also show possible periodic activities. These periodicities might originate from the precession process of young magnetars due to the anisotropic pressure from the inner magnetic fields as proposed in the literature. In this work, we analyse a self-consistent model for the rotation evolution of magnetars and obtain the evolutions of magnetar precession and obliquity. We find that if the FRB repeaters and the SGRs with (possible) periodic activities originate from the magnetar precession, their ages would be constrained to be hundreds to tens of thousands of years, which is consistent with the typical ages of magnetars. Assuming that the FRB emission is beaming in the magnetosphere as proposed in the literature, we calculate the evolution of the observable probability and the duty cycle of the active window period. We find that for a given magnetar the observable probability increases with the magnetar age in the early stage and decreases with the magnetar age in the later stage; meanwhile, there are one or two active windows in one precession period if the emission is not perfectly axisymmetric with respect to the deformation axis of a magnetar, which could be tested by the future observation for repeating FRB sources. [ABSTRACT FROM AUTHOR]

Piezoelectric quasicrystals have attracted the tremendous attention of researchers for their unique properties. In this paper, the semi-analysis solutions of the functionally graded multilayered two-dimensional decagonal piezoelectric quasicrystal plates are investigated for mixed boundary-value problems. Based on the quasicrystal linear elastic theory, the state-space method is employed to derive the state equations composed of partial differential along the thickness direction. The differential quadrature method is utilized to discretize state variables to satisfy the mixed boundary conditions in the horizontal plane. Different from the conventional propagator matrix, a new propagator relationship is proposed to study numerical instability caused by extensive discrete points. Comprehensive numerical results are shown for the sandwich quasicrystal plate with four different stacking sequences. The numerical results reveal the effect of the functional gradient index factors, and boundary conditions on the electric potential, electric displacements, stresses, and displacements under the mechanical/electric loadings. [ABSTRACT FROM AUTHOR]

The key challenge of image layer separation stems from recognizing different components in a single image. Typical methods optimize the modeling of different components by performing low-level supervision on the separated image to minimize its per-pixel difference from the groundtruth, which relies on substantial training samples to learn diverse components robustly and avoid overfitting spurious coupled patterns. In this work, we perform supervision on the contrastive distribution between the predicted separated images. Specifically, our proposed method separates components in parallel and seeks to maximize the distribution consistency between the separated components' contrast and their corresponding groundtruth contrast in the latent space. Such supervision pushes the model to focus on contrastive modeling between different components of the input image. Besides, the learned latent representations of different components directly guide the weight optimization of convolution kernels in the decoder, which achieves more comprehensive separation than traditional skip connection while reconstructing target images by the decoder. We validate the effectiveness and generalization of our CFDNet on two single image layer separation tasks, including image reflection separation and intrinsic image decomposition. Extensive experiments demonstrate that our CFDNet consistently outperforms other state-of-the-art methods specifically designed for either of image separation applications. [ABSTRACT FROM AUTHOR]

Congenital scoliosis (CS), affecting approximately 0.5 to 1 in 1,000 live births, is commonly caused by congenital vertebral malformations (CVMs) arising from aberrant somitogenesis or somite differentiation. While Wnt/ß- catenin signaling has been implicated in somite development, the function of Wnt/planar cell polarity (Wnt/PCP) signaling in this process remains unclear. Here, we investigated the role of Vangl1 and Vangl2 in vertebral development and found that their deletion causes vertebral anomalies resembling human CVMs. Analysis of exome sequencing data from multiethnic CS patients revealed a number of rare and deleterious variants in VANGL1 and VANGL2, many of which exhibited loss- of- function and dominant- negative effects. Zebrafish models confirmed the pathogenicity of these variants. Furthermore, we found that Vangl1 knock- in (p.R258H) mice exhibited vertebral malformations in a Vangl gene dose- and environment- dependent manner. Our findings highlight critical roles for PCP signaling in vertebral development and predisposition to CVMs in CS patients, providing insights into the molecular mechanisms underlying this disorder. [ABSTRACT FROM AUTHOR]

We study optimal information disclosure via an ambiguous persuasion approach in a two-player contest. The designer can precommit to an ambiguous device to influence the uninformed contestant's belief about his opponent's private type. We fully characterize the optimal ambiguous information structures when players are maxmin expected utility (MMEU) maximizers. Depending on the prior, it is optimal to either induce ambiguity or fully conceal information. We provide a necessary and sufficient condition under which an effort-maximizing organizer can benefit strictly more from using ambiguous persuasion than from using the optimal Bayesian device. [ABSTRACT FROM AUTHOR]

Few‐Shot Object Detection (FSOD) task involves accurately identifying target object classes using only a small set of labeled samples. Most of the current FSOD tasks independently predict class prototype features without considering class relationships and only rely on visual information. To address these challenges, we propose a novel Class‐relational Reasoning Method with Knowledge‐transfer (CRK‐Net), built on the meta‐learning‐based framework. Although data may be scarce, the semantic relationship between classes is invariant, Joint‐feature Fusion Module (JFM) are hence proposed to transfers the semantic information of different categories in the natural language world to integrate with visual information and produce multi‐modality embeddings. Some base classes and novel classes have similar features, so this can be borrowed by modeling the relationship between classes feature. Building upon the observation, we propose a Class‐relational Reasoning Module (CRM) to establish the correlations between categories and enhance prototype representations for each category. After passing through the JFM and CRM modules, a high‐quality class prototype is finally produced for subsequent regression and classification. Extensive experiments on PASCAL VOC demonstrate the effectiveness of our proposed method and provide a new scheme for fusing semantic and visual information. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The exact solutions for the propagation of Love waves in one-dimensional (1D) hexagonal piezoelectric quasicrystal (PQC) nanoplates with surface effects are derived. An electro-elastic model is developed to investigate the anti-plane strain problem of Love wave propagation. By introducing three shape functions, the wave equations and electric balance equations are decoupled into three uncorrelated problems. Satisfying the boundary conditions of the top surface on the covering layer, the interlayer interface, and the matrix, a dispersive equation with the influence of multi-physical field coupling is provided. A surface PQC model is developed to investigate the surface effects on the propagation behaviors of Love waves in quasicrystal (QC) multilayered structures with nanoscale thicknesses. A novel dispersion relation for the PQC structure is derived in an explicit closed form according to the non-classical mechanical and electric boundary conditions. Numerical examples are given to reveal the effects of the boundary conditions, stacking sequence, characteristic scale, and phason fluctuation characteristics on the dispersion curves of Love waves propagating in PQC nanoplates with surface effects. [ABSTRACT FROM AUTHOR]

Background: The NLRP3 inflammasome is a vital player in the emergence of inflammation. The priming and activation of the NLRP3 inflammasome is a major trigger for inflammation which is a defense response against adverse stimuli. However, the excessive activation of the NLRP3 inflammasome can lead to the development of various inflammatory diseases. Cannabidiol, as the second-most abundant component in cannabis, has a variety of pharmacological properties, particularly anti-inflammation. Unlike tetrahydrocannabinol, cannabidiol has a lower affinity for cannabinoid receptors, which may be the reason why it is not psychoactive. Notably, the mechanism by which cannabidiol exerts its anti-inflammatory effect is still unclear. Methods: We have performed a literature review based on published original and review articles encompassing the NLRP3 inflammasome and cannabidiol in inflammation from central databases, including PubMed and Web of Science. Results and conclusions: In this review, we first summarize the composition and activation process of the NLRP3 inflammasome. Then, we list possible molecular mechanisms of action of cannabidiol. Next, we explain the role of the NLRP3 inflammasome and the anti-inflammatory effect of cannabidiol in inflammatory disorders. Finally, we emphasize the capacity of cannabidiol to suppress inflammation by blocking the NLRP3 signaling pathway, which indicates that cannabidiol is a quite promising anti-inflammatory compound. [ABSTRACT FROM AUTHOR]

In recent years, various self-knowledge distillation approaches have been proposed to reduce the cost of training teacher networks. However, these methods often overlook the significance of deep features. To address this limitation and strengthen the capability of deep features while preserving the ability of shallow features, we propose performing Self-Knowledge Distillation via Pyramid Feature Refinement (PR-SKD). Inspired by the representation learning characteristics of deep neural networks, PR-SKD builds a cohort of sub-networks with a pyramid architecture to hierarchically transfer refined information to the target network. According to the different contributions and functions between deep and shallow feature maps, our PR-SKD fully utilizes feature information to improve deep feature representation ability without compromising the capability of shallow feature maps. Extensive experiments on various image classification datasets demonstrate the superiority of our proposed method over widely used state-of-the-art knowledge distillation methods. The code is available at: https://github.com/wo16pao/PR-SKD. • The method recognizes the variation contribution of different feature maps in self-distillation. • A new hierarchical refinement distillation technique via pyramid architecture. • The approach improves the deep feature representative capability of the target network. • The proposed technique achieves highly competitive performance on recent benchmarks by focusing on deep feature representation. [ABSTRACT FROM AUTHOR]

Recently, a multisource, raw material allocation form of Weber's classic single‐facility location problem was rediscovered and recognized for its significance in contemporary planning and decision‐making. This variation of the Weber problem investigates the location of a production plant while permitting the selection of each required raw material source. This article reviews the Weber problem with an emphasis on its extension to incorporate multiple facilities. The only formulated multiplant Weber problem involving resource allocation remains unsolved due to its complexity. An effective approach integrating GIS processing (i.e., the Voronoi diagram and vector‐based overlay) with the classic optimization algorithm (i.e., the Weiszfeld algorithm) is developed to address raw material sourcing in the process of siting facilities. The implementation relies entirely on open‐source Python packages, making the work reproducible, replicable, and expandable. Application findings demonstrate that the utility and computational efficiency of the proposed method to tackle this challenging problem are superior to those of the most advanced commercial optimization software. [ABSTRACT FROM AUTHOR]

Due to their excellent photoelectric conversion efficiency and low preparation cost, perovskite solar cells (PSCs) have attracted much attention from researchers and developed rapidly in the past decade. However, the stability and efficiency of perovskite photovoltaic devices still need to be improved for their practical applications. It is mainly because the perovskite thin films are inevitably defective to some extent (such as points defects and extrinsic defects), leading to the occurrence of non‐radiative recombination (NRR) inside the device and at the interface, which is closely related to the stability and efficiency of perovskite materials. Therefore, exploring reliable passivation strategies is essential to overcome the adverse effects of NRR losses of such point defects. Here, this article summarizes the perovskite solar cells, including the crystal structure and calculations of electronic properties of perovskites, composition, and principles of operation of perovskite solar cells, and more importantly, different passivation strategies, including Lewis acid‐base passivation, anionic and cationic passivation, polymer passivation, and alkyl halogen ammonium passivation for the defects involved in perovskite materials. The passivation effects of these strategies and their regulation mechanisms of point defects involving perovskite materials are also presented. We also discuss the intrinsic relationship between crystal defects and device stability and look forward to feasible defect passivation strategy options for future research. [ABSTRACT FROM AUTHOR]

This study was conducted to investigate the effects of dietary supplementation of active dry yeast (Saccharomyces cerevisiae) on growth performance, circulating ghrelin, fatty acid concentrations in the gastrointestinal tract, and trace mineral elements utilisation of finishing bulls. Twenty Yanbian cattle (bulls) [body weight (BW) 485 ± 38 kg] were randomly divided into two groups (control and treatment groups) and participated in a 100-day finishing trial. The control group (CON) was fed a basal diet (total mixed ration, TMR). The treatment group (active dry yeast, ADY) was fed a basal diet supplemented with ADY (Levucell SC, Saccharomyces cerevisiae CNCM I-1077, viable count ≥8.0 × 109 CFU/g, 1.0 g/bull/day). ADY supplementation significantly increased the dry matter intake (DMI) of bulls (p <.05); significantly increased the concentration of ghrelin O-acyl transferase (GOAT) (p <.05), significantly decreased the concentration of corticotropin-releasing hormone (CRH) (p <.05), tended to increase the concentration of acyl ghrelin (AG) (p =.053) in serum; significantly increased the content of C12:0 in duodenal digesta, the apparent digestibility of Zn, the concentrations Zn and Cu in serum and the deposition of Cu in the liver (p <.05), significantly decreased the deposition of Fe in muscle in finishing bulls (p <.05). In conclusion, ADY supplementation improved DMI of finishing bulls may be related to the change of AG, and a potential mechanism for the change of AG by ADY supplementation is via its effects on the metabolism of C12:0, Zn, and Cu in finishing bulls. Active dry yeast (ADY) supplementation increased the dry matter intake (DMI) and tended to increase the concentration of acyl ghrelin (AG) in the serum of finishing bulls. ADY supplementation increased the content of C12:0 in duodenal digesta and improved the bioavailability of Zn and Cu of finishing bulls. A potential mechanism for the change of AG by ADY supplementation is via its effects on the metabolism of C12:0, Zn, and Cu in finishing bulls. [ABSTRACT FROM AUTHOR]

Mass spectrometry technology can realize dynamic detection of many complex matrix samples in a simple, rapid, compassionate, precise, and high-throughput manner and has become an indispensable tool in accurate diagnosis. The mass spectrometry data analysis is mainly to analyze all metabolites in the organism quantitatively and to find the relative relationship between metabolites and physiological and pathological changes. A feature construction of mass spectrometry data (MSFS) method is proposed to construct the features of the original mass spectrometry data, so as to reduce the noise in the mass spectrometry data, reduce the redundancy of the original data and improve the information content of the data. Chi-square test is used to select the optimal non-redundant feature subset from high-dimensional features. And the optimal feature subset is visually analyzed and corresponds to the original mass spectrum interval. Training in 10 kinds of supervised learning models, and evaluating the classification effect of the models through various evaluation indexes. Taking two public mass spectrometry datasets as examples, the feasibility of the method proposed in this paper is verified. In the coronary heart disease dataset, during the identification process of mixed batch samples, the classification accuracy on the test set reached 1.000; During the recognition process, the classification accuracy on the test set advanced to 0.979. On the colorectal liver metastases data set, the classification accuracy on the test set reached 1.000. This paper attempts to use a new raw mass spectrometry data preprocessing method to realize the alignment operation of the raw mass spectrometry data, which significantly improves the classification accuracy and provides another new idea for mass spectrometry data analysis. Compared with MetaboAnalyst software and existing experimental results, the method proposed in this paper has obtained better classification results. [ABSTRACT FROM AUTHOR]

Background: Diabetes is a metabolic disorder usually caused by insufficient secretion of insulin from the pancreas or insensitivity of cells to insulin, resulting in long-term elevated blood sugar levels in patients. Patients usually present with frequent urination, thirst, and hunger. If left untreated, it can lead to various complications that can affect essential organs and even endanger life. Therefore, developing an intelligent diagnosis framework for diabetes is necessary. Result: This paper proposes a machine learning-based diabetes classification framework machine learning optimized GAN. The framework encompasses several methodological approaches to address the diverse challenges encountered during the analysis. These approaches encompass the implementation of the mean and median joint filling method for handling missing values, the application of the cap method for outlier processing, and the utilization of SMOTEENN to mitigate sample imbalance. Additionally, the framework incorporates the employment of the proposed Diabetes Classification Model based on Generative Adversarial Network and employs logistic regression for detailed feature analysis. The effectiveness of the framework is evaluated using both the PIMA dataset and the diabetes dataset obtained from the GEO database. The experimental findings showcase our model achieved exceptional results, including a binary classification accuracy of 96.27%, tertiary classification accuracy of 99.31%, precision and f1 score of 0.9698, recall of 0.9698, and an AUC of 0.9702. Conclusion: The experimental results show that the framework proposed in this paper can accurately classify diabetes and provide new ideas for intelligent diagnosis of diabetes. [ABSTRACT FROM AUTHOR]

Purpose: The research on social media-based academic communication has made great progress with the development of the mobile Internet era, and while a large number of research results have emerged, clarifying the topology of the knowledge label network (KLN) in this field and showing the development of its knowledge labels and related concepts is one of the issues that must be faced. This study aims to discuss the aforementioned issue. Design/methodology/approach: From a bibliometric perspective, 5,217 research papers in this field from CNKI from 2011 to 2021 are selected, and the title and abstract of each paper are subjected to subword processing and topic model analysis, and the extended labels are obtained by taking the merged set with the original keywords, so as to construct a conceptually expanded KLN. At the same time, appropriate time window slicing is performed to observe the temporal evolution of the network topology. Specifically, the basic network topological parameters and the complex modal structure are analyzed empirically to explore the evolution pattern and inner mechanism of the KLN in this domain. In addition, the ARIMA time series prediction model is used to further predict and compare the changing trend of network structure among different disciplines, so as to compare the differences among different disciplines. Findings: The results show that the degree sequence distribution of the KLN is power-law distributed during the growth process, and it performs better in the mature stage of network development, and the network shows more stable scale-free characteristics. At the same time, the network has the characteristics of "short path and high clustering" throughout the time series, which is a typical small-world network. The KLN consists of a small number of hub nodes occupying the core position of the network, while a large number of label nodes are distributed at the periphery of the network and formed around these hub nodes, and its knowledge expansion pattern has a certain retrospective nature. More knowledge label nodes expand from the center to the periphery and have a gradual and stable trend. In addition, there are certain differences between different disciplines, and the research direction or topic of library and information science (LIS) is more refined and deeper than that of journalism and media and computer science. The LIS discipline has shown better development momentum in this field. Originality/value: KLN is constructed by using extended labels and empirically analyzed by using network frontier conceptual motifs, which reflects the innovation of the study to a certain extent. In future research, the influence of larger-scale network motifs on the structural features and evolutionary mechanisms of KLNs will be further explored. [ABSTRACT FROM AUTHOR]

Circular RNAs (circRNAs) are a class of covalently closed, endogenous ncRNAs. Most circRNAs are derived from exonic or intronic sequences by precursor RNA back-splicing. Advanced high-throughput RNA sequencing and experimental technologies have enabled the extensive identification and characterization of circRNAs, such as novel types of biogenesis, tissue-specific and cell-specific expression patterns, epigenetic regulation, translation potential, localization and metabolism. Increasing evidence has revealed that circRNAs participate in diverse cellular processes, and their dysregulation is involved in the pathogenesis of various diseases, particularly cancer. In this review, we systematically discuss the characterization of circRNAs, databases, challenges for circRNA discovery, new insight into strategies used in circRNA studies and biomedical applications. Although recent studies have advanced the understanding of circRNAs, advanced knowledge and approaches for circRNA annotation, functional characterization and biomedical applications are continuously needed to provide new insights into circRNAs. The emergence of circRNA-based protein translation strategy will be a promising direction in the field of biomedicine. [ABSTRACT FROM AUTHOR]

Phytochemical analyses of Swertia davidii Franch. extracts using column chromatography and semi-preparative HPLC were performed. Two novel phenolic glycosides named swertiosides A and B (compounds 1 and 2, respectively) were isolated and characterized. Four known phenolic glycosides were also extracted (compounds 3-6). The structural characteristics of these novel compounds were analyzed using 1D, 2D NMR, and HRMS. All six compounds have never been isolated from this particular plant species before this study. Subsequent assessment of bioactive properties suggested that compounds 1 and 2 exhibited moderate levels of cytotoxicity. [ABSTRACT FROM AUTHOR]

Mass spectrometry technology can realize dynamic detection of many complex matrix samples in a simple, rapid, compassionate, precise, and high-throughput manner and has become an indispensable tool in accurate diagnosis. The mass spectrometry data analysis is mainly to analyze all metabolites in the organism quantitatively and to find the relative relationship between metabolites and physiological and pathological changes. A feature construction of mass spectrometry data (MSFS) method is proposed to construct the features of the original mass spectrometry data, so as to reduce the noise in the mass spectrometry data, reduce the redundancy of the original data and improve the information content of the data. Chi-square test is used to select the optimal non-redundant feature subset from high-dimensional features. And the optimal feature subset is visually analyzed and corresponds to the original mass spectrum interval. Training in 10 kinds of supervised learning models, and evaluating the classification effect of the models through various evaluation indexes. Taking two public mass spectrometry datasets as examples, the feasibility of the method proposed in this paper is verified. In the coronary heart disease dataset, during the identification process of mixed batch samples, the classification accuracy on the test set reached 1.000; During the recognition process, the classification accuracy on the test set advanced to 0.979. On the colorectal liver metastases data set, the classification accuracy on the test set reached 1.000. This paper attempts to use a new raw mass spectrometry data preprocessing method to realize the alignment operation of the raw mass spectrometry data, which significantly improves the classification accuracy and provides another new idea for mass spectrometry data analysis. Compared with MetaboAnalyst software and existing experimental results, the method proposed in this paper has obtained better classification results. [ABSTRACT FROM AUTHOR]

Mass spectrometry technology can realize dynamic detection of many complex matrix samples in a simple, rapid, compassionate, precise, and high-throughput manner and has become an indispensable tool in accurate diagnosis. The mass spectrometry data analysis is mainly to analyze all metabolites in the organism quantitatively and to find the relative relationship between metabolites and physiological and pathological changes. A feature construction of mass spectrometry data (MSFS) method is proposed to construct the features of the original mass spectrometry data, so as to reduce the noise in the mass spectrometry data, reduce the redundancy of the original data and improve the information content of the data. Chi-square test is used to select the optimal non-redundant feature subset from high-dimensional features. And the optimal feature subset is visually analyzed and corresponds to the original mass spectrum interval. Training in 10 kinds of supervised learning models, and evaluating the classification effect of the models through various evaluation indexes. Taking two public mass spectrometry datasets as examples, the feasibility of the method proposed in this paper is verified. In the coronary heart disease dataset, during the identification process of mixed batch samples, the classification accuracy on the test set reached 1.000; During the recognition process, the classification accuracy on the test set advanced to 0.979. On the colorectal liver metastases data set, the classification accuracy on the test set reached 1.000. This paper attempts to use a new raw mass spectrometry data preprocessing method to realize the alignment operation of the raw mass spectrometry data, which significantly improves the classification accuracy and provides another new idea for mass spectrometry data analysis. Compared with MetaboAnalyst software and existing experimental results, the method proposed in this paper has obtained better classification results. [ABSTRACT FROM AUTHOR]

Purpose: The online Question and Answer community is full of a large number of science and technology topics, the discussion and dissemination of which play an important role in promoting the popularization of new technologies and cultivating public enthusiasm for science. However, the spread of false information and rumors weakens the community's positive effect, making the community more difficult for people to obtain useful information on such topics. Research on the influencing factors and governance of the spread of false information on science and technology topics has become the key to the spread of popular science. Design/methodology/approach: Therefore, this paper uses the Elaboration Likelihood Model as the theoretical framework to examine the role of the factors influencing the spread of false information on science and technology topics in Zhihu community on the information persuasion and the impact on public behavior attitude from the core path and the edge path. This paper compiles a crawler program to capture 12,893 response information under the "Metaverse" topic in Zhihu community as an empirical sample and uses text mining and conducts visual correlation analysis to explore the key factors affecting the persuasive transmission path of information on science and technology topics. Findings: The research finds that the content specialization, content consistency and content coherence of science and technology topics affect personal judgment from the aspect of information content through the core path and have a positive correlation with information persuasion; the number of comments, the length of the text and the publishing authors' influence from the edge image characteristics through the edge path are positively correlated with the information persuasion. Then, from the perspective of topic platform, government and topic participants, this paper puts forward a general plan to improve the information persuasion of science and technology topics so as to deal with false information. Originality/value: Compared with the small data set of the traditional questionnaire survey, the research based on community empirical big data is more reliable. The model takes into account the attitude and behavior of users and is more suitable for the research on the transmission path of scientific and technological information in the internet era. This research provides a direction for analyzing the text characteristics and development trends of information in the field of science and technology and is conducive to promoting the optimization of the network information environment and building a good ecology, with the spread of rumors about science and technology topics curbed and the governance of false information strengthened. [ABSTRACT FROM AUTHOR]

Cross-modal pedestrian re-identification is a key technology to realize all-weather intelligent video surveillance system. This technology is designed to match the visible light image and infrared image of a pedestrian with a specific identity in a non-overlapping camera scene, so it faces huge intra-class changes and modal differences. Existing methods are difficult to solve these two difficulties, which is largely due to the lack of effective mining of feature discrimination and the full use of multi-source heterogeneous information. In view of the above shortcomings, a refined multi-source feature collaborative network is designed by the collaborative learning method, and multiple complementary features are extracted for information fusion, the learning ability of the network is improved. Multi-scale and multi-level features are extracted from the backbone convolutional network, and the refined feature collaborative learning is realized; the discriminative ability of features is enhanced to deal with intra-class changes. A modal sharing and unique feature collaboration module and a cross-modal human semantic self-supervision module are designed to achieve the purpose of multi-source feature collaborative learning, so as to improve the utilization of multi-source heterogeneous image information, and then modal differences are resolved. The validity and advancement of this method are verified on the SYSU-MM01 and RegDB data sets. [ABSTRACT FROM AUTHOR]

Aristolochic acids are widely distributed in the plants of Aristolochiaceae family and Asarum species. Aristolochic acid I (AAI) is the most frequent compound of aristolochic acids, which can accumulate in the soil, and then contaminates crops and water and enters the human body. Research has shown that AAI affects the reproductive system. However, the mechanism of AAI's effects on the ovaries at the tissue level still needs to be clarified. In this research, we found AAI exposure reduced the body and ovarian growth in mice, decreased the ovarian coefficient, prevented follicular development, and increased atretic follicles. Further experiments showed that AAI upregulated nuclear factor-κB and tumor necrosis factor-α expression, activated the NOD-like receptor protein 3 inflammasome, and led to ovarian inflammation and fibrosis. AAI also affected mitochondrial complex function and the balance between mitochondrial fusion and division. Metabolomic results also showed ovarian inflammation and mitochondrial dysfunction due to AAI exposure. These disruptions reduced the oocyte developmental potential by forming abnormal microtubule organizing centers and expressing abnormal BubR1 to destroy spindle assembly. In summary, AAI exposure triggers ovarian inflammation and fibrosis, affecting the oocyte developmental potential. [Display omitted] • Aristolochic acid I exposure triggers ovarian inflammation and fibrosis. • Aristolochic acid I exposure activates NLRP3 inflammasome. • Ovarian metabolomics uncovers mechanisms of aristolochic acid I toxicity. • Aristolochic acid I exposure reduces oocyte developmental potential. [ABSTRACT FROM AUTHOR]

Eshelby tensors serve as the basis of micromechanics which should be explored first to study the effective mechanical behavior of heterogeneous materials. In this paper, Eshelby tensors are extended from isotropic materials to quasicrystals. By utilizing Green's functions and Cauchy's residue theorem, simple and unified expressions of Eshelby tensors for one-dimensional (1D) orthorhombic quasicrystal are derived. Specifically, the closed-form Eshelby tensors are given when the shapes of the inclusions are spheroid, elliptic cylinder, rod-shaped, penny-shaped, and ribbon-like, respectively. Furthermore, the effective stiffnesses of 1D orthorhombic quasicrystal are obtained in view of the received Eshelby tensors and the Mori–Tanaka mean theory. Finally, parameter studies are carried out, and the effect of material properties and volume fraction on the effective overall material properties are investigated. [ABSTRACT FROM AUTHOR]

Background: Magnetic nanoparticles (MNPs) are used as tracers without ionizing radiation in vascular imaging, molecular imaging, and neuroimaging. The relaxation mechanisms of magnetization in response to excitation magnetic fields are important features of MNPs. The basic relaxation mechanisms include internal rotation (Néel relaxation) and external physical rotation (Brownian relaxation). Accurate measurement of these relaxation times may provide high sensitivity for predicting MNP types and viscosity‐based hydrodynamic states. It is challenging to separately measure the Néel and Brownian relaxation components using sinusoidal excitation in conventional MPI. Purpose: We developed a multi‐exponential relaxation spectral analysis method to separately measure the Néel and Brownian relaxation times in the magnetization recovery process in pulsed vascular MPI. Methods: Synomag‐D samples with different viscosities were excited using pulsed excitation in a trapezoidal‐waveform relaxometer. The samples were excited at different field amplitudes ranging from 0.5 to 10 mT at intervals of 0.5 mT. The inverse Laplace transform‐based spectral analysis of the relaxation‐induced decay signal in the field‐flat phase was performed by using PDCO, a primal‐dual interior method for convex objectives. Néel and Brownian relaxation peaks were elucidated and measured on samples with various glycerol and gelatin concentrations. The sensitivity of viscosity prediction of the decoupled relaxation times was evaluated. A digital vascular phantom was designed to mimic a plaque with viscous MNPs and a catheter with immobilized MNPs. Spectral imaging of the digital vascular phantom was simulated by combining a field‐free point with homogeneous pulsed excitation. The relationship between the Brownian relaxation time from different tissues and the number of periods for signal averages was evaluated for a scan time estimation in the simulation. Results: The relaxation spectra of synomag‐D samples with different viscosity levels exhibited two relaxation time peaks. The Brownian relaxation time had a positive linear relationship with the viscosity in the range 0.9 to 3.2 mPa · s. When the viscosity was >3.2 mPa · s, the Brownian relaxation time saturated and did not change with increasing viscosity. The Néel relaxation time decreased slightly with an increase in the viscosity. The Néel relaxation time exhibited a similar saturation effect when the viscosity level was >3.2 mPa · s for all field amplitudes. The sensitivity of the Brownian relaxation time increased with the field amplitude and was maximized at approximately 4.5 mT. The plaque and catheter regions were differentiated from the vessel region in the simulated Brownian relaxation time map. The simulation results show that the Néel relaxation time was 8.33±0.09 μs in the plaque region, 8.30±0.08 μs in the catheter region, and 8.46±0.11 μs in the vessel region. The Brownian relaxation time was 36.60±2.31 μs in the plaque region, 30.17±1.24 μs in the catheter region, and 31.21±1.53 μs in the vessel region. If we used 20 excitation periods for image acquisition in the simulation, the total scan time of the digital phantom was approximately 100 s. Conclusion: Quantitative assessment of the Néel and Brownian relaxation times through inverse Laplace transform‐based spectral analysis in pulsed excitation, highlighting their potential for use in multi‐contrast vascular MPI. [ABSTRACT FROM AUTHOR]

Maize is one of the most important economic crops in the world. The integrity of maize grains directly affects the economic value of the maize as a main commodity that depends on the percentage of grains broken (POGB) in mechanized harvesting. Decreasing grain processing breakage is key to achieving mechanical harvesting with high quality. It is difficult to ensure a low POGB, because it depends on different maize varieties, their moisture contents, threshing devices and harvester working speeds. In this paper, the effects of these factors on the POGB are investigated when the working speed of the harvester is 1.0 m·s−1, 1.5 m·s−1 and 2.0 m·s−1, respectively. The different threshing forms, including tangential-axial-flow (TAF), axial-flow with nail-tooth (AFN), axial-flow with rasp bar in big space (AFRBBS) and axial-flow with rasp bar in small space (AFRBSS), are summarized. The POGB of TAF was 5.4% and it was the lowest of four threshing devices when the working speed of the harvester was 1.0 m·s−1, which was suitable to thresh maize at a low working speed. Maize Demeiya No. 1 (DMYN1), XianDa205 (XD205), Demeiya No. 3 (DMYN3) and Hayu189 (HY189) were harvested at different harvester working speeds, and the POGB of maize DMYN1 was the lowest among the four maize varieties. The POGB increased with increases in the working speed of the harvester and the moisture content of the maize grains. The POGB reached a minimum value of 3.5% when maize XD205 with the lowest moisture content was harvested. The results can provide a reference for choosing the maize variety, its moisture content, the threshing device and the working speed of the harvester for decreasing grain processing breakage. [ABSTRACT FROM AUTHOR]

This study examined the prospective associations among the trajectories of maternal depressive symptoms, maternal sensitivity, and child executive function (EF) across early and middle childhood, and tested the mediating role of maternal sensitivity in the links between change in maternal depressive symptoms and the growth of child EF. Participants included 1,364 children and mothers from the National Institute of Child Health and Human Development (NICHD) Study of Early Child Care and Youth Development (NICHD SECCYD). We found that maternal depressive symptoms (from 6 months to Grade 5) and sensitivity (from 36 months to Grade 5) decreased, whereas child EF (planning skills; from Grade 1 to 5) increased over time. We also found several direct associations: (a) lower maternal depressive symptoms at 36 months predicted higher sensitivity at 54 months; (b) higher sensitivity at 54 months and a faster decrease in sensitivity from 36 months to Grade 5 predicted higher child EF in Grade 1; and (c) higher sensitivity at 54 months predicted greater growth of EF from Grade 1 to 5. In addition, two mediation effects were found as follows: Lower levels of maternal depressive symptoms at 36 months predicted both higher levels of child EF in Grade 1 and greater growth of EF from Grade 1 to 5 through higher levels of maternal sensitivity at 54 months. The results suggest that early maternal depressive symptoms may have long-term effects on the growth of EF, especially planning skills, during middle childhood, and that one important pathway that maternal depressive symptoms affect child EF outcomes through maternal sensitivity. [ABSTRACT FROM AUTHOR]

In this paper, we accommodate the costly entry of contestants and examine an information design problem when the organizer can decide how to generate contestants' private information. The information designer should take into account both ex ante entry incentives and post-entry effort elicitation. We show that no transparency (full transparency) induces greater expected aggregate effort if the entry cost is lower (higher) than a threshold. We further consider randomized disclosure policies and identify the optimal degree of transparency, which increases with the entry cost to attract entry. In particular, depending on the entry cost, diverse randomized disclosure policies could be optimal. Our results indicate that endogenous participation plays a crucial role in the design of information revelation. [ABSTRACT FROM AUTHOR]

The synaptic devices based on various electronic materials have been widely investigated to realize functions of artificial information processing with low power consumption. In this work, a novel CVD graphene field-effect transistor is fabricated with ionic liquid gate to study the synaptic behaviors based on the electrical-double-layer mechanism. It is found that the excitative current is enhanced with the pulse width, voltage amplitude and frequency. With different situations of the applied pulse voltage, the inhibitory and excitatory behaviors are successfully simulated, at the same time the short-term memory is also realized. The corresponding ions migration and charge density variation are analyzed in the different time segments. This work provides the guidance for the design of artificial synaptic electronics with ionic liquid gate for low-power computing application. [ABSTRACT FROM AUTHOR]

As a model of the combination of nostalgia and creative products, ethnic cultural heritage carry the function of shaping and spreading geo-culture. Its unique geo-cultural context, as a link, shows the historical inheritance of local culture. The deep deconstruction of its emotional identity helps to strengthen this identity and stimulate more cultural and creative designs with national and local characteristics. While culture prospers, the local cultural and creative economy is strengthened and cultural confidence and national self-confidence are further enhanced. Based on the New Year paintings of Wuqiang in Hebei, which have a strong folk vernacular and geo-cultural character in northern China, in the process of using the reconstructed pattern elements for clothing design, 156 questionnaires were collected through questionnaire interviews and fsQCA was used to analyze the emotional identity of products with high geo-cultural recognition. The study finds that while the injection of regional culture plays a role in the development of products, people's emotional identification with vernacular cultural and creative products actually depends on a combination of causal paths, with beauty and elegance more important than place and humanity as commonly believed to reflect geographic cultural identity. fsQCA was used to analyze the emotional identity of products with high geo-cultural recognition. And understand the emotional components of vernacular cultural products and how emotional factors influence people's identities. [ABSTRACT FROM AUTHOR]

Although spinal gas is common and can be found in various sites and lesions, it should prompt a search for the underlying cause, given that the clinical significance of ectopic gas varies from benign to scary. Spinal gas can occur in the traumatic, iatrogenic, degenerative, osteoporotic, infectious, or neoplastic lesions. The imaging similarity may cause the misdiagnosis or delayed diagnosis which sometimes requires immediate attention. The pattern of gas distribution, detailed appearance, clinical history, and findings on examination can provide clues to diagnosis. Computed tomography is the best method for sensitive detection of gas. [ABSTRACT FROM AUTHOR]

An 86-year-old diabetic man presented with persistent back pain and tenderness at the thoracolumbar junction. His glycemic control was poor, but inflammatory markers were normal. Imaging revealed multiple gas foci in the T12-L1 intervertebral space, a collapsed vertebral body, and a swollen psoas muscle. A communication was visible between the collapsed vertebral body and the superior disc. The most possible diagnosis is not stated in the summary. The authors of the study had access to the data and contributed to writing the manuscript. The data used in the study are available upon request. The study had ethics approval and the patient provided written consent for publication. The authors declare no competing interests. [Extracted from the article]

In this study, one-step molten salt method followed by low-temperature sintering is employed for fabricating porous calcium hexaluminate (CA 6) ceramics with ideal plate-like structure and low thermal conductivity via the assistance of CaCl 2. The porous CA 6 ceramic containing 15 wt% CaCl 2 sintered at 1400 °C for 3 h exhibits desirable compressive strength (7.14 MPa), low bulk density (1.47 g/cm3), high porosity (61.12%), and low conductivity (0.439 W/(m·K)). The results imply that CaCl 2 , as a pore-forming agent and an additional source of CaO, provides a large number of liquid phases and resulting in quantities of closed pores. Moreover, the reactions between molten Al 2 O 3 and CaCl 2 alter the mass transfer modes of Al 2 O 3 and accelerate its phase transition to α-Al 2 O 3 in addition to contributing to the conversion of CaCl 2 to CaO and the subsequent formation of CA 6 , which results in the entire synthesis of low-temperature CA 6 at around 1400 °C. Therefore, there is no need for extra salt washing treatment owing to the consumption and evaporation of CaCl 2 , which makes this one-step molten salt method much more advantageous in terms of its economical and highly efficient. [ABSTRACT FROM AUTHOR]

MXenes have shown great potential application in new electronic devices owing to the unique surface properties and 2D structure, especially in the popular memory storage. In this work, Ti 3 C 2 T x , one of the MXenes, is partially oxidized and used as the resistance layer to fabricate memristors with resistance switching characteristics and synapse characteristics. The device exhibits excellent bipolar resistance switching property based on the gradual formation and annihilation of the conductive filaments of oxygen vacancy cation, including enough on/off ratio (≈102), long cyclic endurance (>103 cycles) and retention time (>104 s). Furthermore, since oxygen vacancy cation migration is similar to the Ca2+ ion dynamics of biological synapses, the device successfully mimics biological synaptic functions such as paired-pulse facilitation (PPF), long-term potentiation (LTP) and long-term depression (LTD). This work provides the experimental and theoretical foundation for MXenes in memristor and artificial synapse filed, pushes the development of MXenes in neurocomputing application. A novel nonvolatile memory device based on oxidized Ti 3 C 2 T x MXene with threshold resistance switching characteristics and synapse characteristics is demonstrated to realize the function of computing in memory in neurocomputing application. [Display omitted] [ABSTRACT FROM AUTHOR]

BACKGROUND: The incidence rate for migraine is 12% worldwide, and recurrence is common, which seriously affects the physical and mental health of patients. OBJECTIVE: To observe the clinical effect of Shallow Puncture and More Twirling method of acupuncture in treating migraine and its impact on serum 5-HT and β -EP. METHODS: A total of 76 patients with migraine were randomized into a control group and acupuncture group with 38 cases in each. In the control group, patients were orally administered flunarizine hydrochloride before sleep, 2 capsules once daily for 4 weeks. In the acupuncture group, Shallow Puncture and More Twirling method was adopted for the acupoints of Sizhukong (SJ 23), Toulinqi (GB 15) Shuaigu (GB 8), Xuanlu (GB 5), Fengchi (GB 20), Waiguan (SJ 5), Zulinqi (GB 41). Patients were given acupuncture 3 times per week for 4 weeks. Then, the total VAS (Visual Analogue Scale) scores, composite score of migraine, serum level of 5-HT and β -EP, and the clinical efficacy differences were observed before and after treatment and the side-effects were recorded among the two groups. RESULTS: The total VAS scores and composite score of migraine were significantly reduced among both groups after the treatment (P < 0.05), and the serum level of 5-HT and β -EP was significantly improved (P < 0.05). Compared with control group, the acupuncture group reported lower results in VAS score and migraine composite score (P < 0.05), and higher results in serum 5-HT and β -EP level (P < 0.05). The acupuncture group with shallow puncture and more twirling method showed a total effective rate of 86.5%, which is higher than the control group (78.4%). The difference is statistically significant (P < 0.05). CONCLUSION: Shallow Puncture and More Twirling method was superior to flunarizine hydrochloride in the treatment of clinical symptoms of migraine. Acupuncture also increases the serum level of 5-HT and β -EP in migraine. [ABSTRACT FROM AUTHOR]

The unique intermolecular van der Waals force in emerging two‐dimensional inorganic molecular crystals (2DIMCs) endows them with highly tunable structures and properties upon applying external stimuli. Using high pressure to modulate the intermolecular bonding, here we reveal the highly tunable charge transport behavior in 2DIMCs for the first time, from an insulator to a semiconductor. As pressure increases, 2D α‐Sb2O3 molecular crystal undergoes three isostructural transitions, and the intermolecular bonding enhances gradually, which results in a considerably decreased band gap by 25 % and a greatly enhanced charge transport. Impressively, the in situ resistivity measurement of the α‐Sb2O3 flake shows a sharp drop by 5 orders of magnitude in 0–3.2 GPa. This work sheds new light on the manipulation of charge transport in 2DIMCs and is of great significance for promoting the fundamental understanding and potential applications of 2DIMCs in advanced modern technologies. [ABSTRACT FROM AUTHOR]

The unique intermolecular van der Waals force in emerging two‐dimensional inorganic molecular crystals (2DIMCs) endows them with highly tunable structures and properties upon applying external stimuli. Using high pressure to modulate the intermolecular bonding, here we reveal the highly tunable charge transport behavior in 2DIMCs for the first time, from an insulator to a semiconductor. As pressure increases, 2D α‐Sb2O3 molecular crystal undergoes three isostructural transitions, and the intermolecular bonding enhances gradually, which results in a considerably decreased band gap by 25 % and a greatly enhanced charge transport. Impressively, the in situ resistivity measurement of the α‐Sb2O3 flake shows a sharp drop by 5 orders of magnitude in 0–3.2 GPa. This work sheds new light on the manipulation of charge transport in 2DIMCs and is of great significance for promoting the fundamental understanding and potential applications of 2DIMCs in advanced modern technologies. [ABSTRACT FROM AUTHOR]

Iris recognition has been considered as one of the most accurate and reliable biometric technologies, and it is widely used in security applications. Iris segmentation and iris localization, as important preprocessing tasks for iris biometrics, jointly determine the valid iris part of the input eye image; however, iris images that have been captured in user non-cooperative and visible illumination environments often suffer from adverse noise (e.g., light reflection, blurring, and glasses occlusion), which challenges many existing segmentation-based parameter-fitting localization methods. To address this problem, we propose a novel double-center-based end-to-end iris localization and segmentation network. Different from many previous iris localization methods, which use massive post-process methods (e.g., integro-differential operator-based or circular Hough transforms-based) on iris or contour mask to fit the inner and outer circles, our method directly predicts the inner and outer circles of the iris on the feature map. In our method, an anchor-free center-based double-circle iris-localization network and an iris mask segmentation module are designed to directly detect the circle boundary of the pupil and iris, and segment the iris region in an end-to-end framework. To facilitate efficient training, we propose a concentric sampling strategy according to the center distribution of the inner and outer iris circles. Extensive experiments on the four challenging iris data sets show that our method achieves excellent iris-localization performance; in particular, it achieves 84.02% box IoU and 89.15% mask IoU on NICE-II. On the three sub-datasets of MICHE, our method achieves 74.06% average box IoU, surpassing the existing methods by 4.64%. [ABSTRACT FROM AUTHOR]

The uvula flapping is one of the most distinctive features of snoring and is critical in affecting airway aerodynamics and vibrations. This study aimed to elucidate the mechanism of pharyngeal vibration and pressure fluctuation due to uvula flapping employing fluid–structure interaction simulations. The followings are the methodology part: we constructed an anatomically accurate pediatric pharynx model and put attention on the oropharynx region where the greatest level of upper airway compliance was reported to occur. The uvula was assumed to be a rigid body with specific flapping frequencies to guarantee proper boundary conditions with as little complexity as possible. The airway tissue was considered to have a uniform thickness. It was found that the flapping frequency had a more significant effect on the airway vibration than the flapping amplitude, as the flapping uvula influenced the pharyngeal aerodynamics by altering the jet flow from the mouth. Breathing only through the mouth could amplify the effect of flapping uvula on aerodynamic changes and result in more significant oropharynx vibration. [ABSTRACT FROM AUTHOR]

The tremendous attention of researchers has been attracted to the unusual properties of quasicrystals (QCs). In this article, the thermo-elastic problems of imperfectly bonded, multilayered, two-dimensional decagonal QC plates with mixed boundary conditions are investigated based on the QC linear elasticity theory. The temperature, heat flux, displacement, and stress components are expressed in terms of differential quadrature regional discrete point expansions in any rectangular plate, from which the state equations with thermomechanical coupling effects in a concise and compact matrix form is obtained. The different imperfect interface conditions are introduced to characterize specific structural and thermal contact properties at the interfaces and are further converted into the interface propagator matrix. Different from the conventional propagator matrix method, the new global propagator relation for the composite laminate with the presence of perfect/imperfect interfaces is recursively obtained by means of the reduced propagator distance and the exponential term between the layer to layer propagator matrix. The numerical examples indicate that numerical results are stability and precision, different boundary conditions have hardly influenced temperature and heat fluxes, and interlaminar thermal stresses strengthen with increasing interface coefficients. The methods and results can also serve as a reference for verifying existing or future QC laminate theories. [ABSTRACT FROM AUTHOR]