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Ultrasound Elastography is a late-model Ultrasound imaging technique mainly used to diagnose tumors and diffusion diseases that can't be detected by traditional Ultrasound imaging. However, artifact noise, speckle noise, low contrast and low signal-to-noise ratio in images make disease diagnosing a challenging task. Medical images denoising, as the first step in the follow-up processing of medical images, has been concerned by many people. With the widespread use of deep learning technique in the research field, dictionary learning method are once again receiving attention. Dictionary learning, as a traditional machine learning method, requires less sample size, has high training efficiency, and can describe images well. In this work, we present a novel strategy based on K-clustering with singular value decomposition (K-SVD) and principal component analysis (PCA) to reduce noise in Ultrasound Elastography images. At this stage of dictionary training, we implement a PCA method to transform the way dictionary atoms are updated in K-SVD. Finally, we reconstructed the image based on the dictionary atoms and sparse coefficients to obtain the denoised image. We applied the presented method on datasets of clinical Ultrasound Elastography images of lung cancer from Nanjing First Hospital, and compared the results of the presented method and the original method. The experimental results of subjective and objective evaluation demonstrated that presented approach reached a satisfactory denoising effect and this research provides a new technical reference for computer aided diagnosis.

A highly efficient hardware element capable of sensing and encoding multiple physical signals is still lacking. Here, the authors report a spike-based neuromorphic perception system consisting of tunable and highly uniform artificial sensory neurons based on epitaxial VO2 capable of hand gesture classification.

Industrial textile materials are a new type of functional or structural basic materials processed by weaving, knitting, or nonweaving of fibrous materials. They have been widely applied to aerospace, national defense, ocean engineering, energy, environmental protection, transportation, civil construction, and other fields. The vigorous development of industrial textile materials can significantly promote the manufacturing industry of China, transform and upgrade China’s textile industry into an emerging resource industry, and contribute to the international and domestic dual circulation of China’s textile industry. In this paper, the development status, application scenarios, industrial demand, and manufacturing technologies of industrial textile materials are analyzed, the development direction and focus of relevant technologies and equipment are clarified, and development countermeasures are proposed. Specifically, China needs to formulate special policies to coordinate the technological research, equipment development, production, and application of the industry, establish a standards system for industrial textile equipment, and build systems for innovative services and talent training.

Bioinspired neuromorphic vision components are highly desired for the emerging in-sensor computing technology. Here, Ge et al. develop an array of optoelectronic synapses capable of memorizing and processing ultraviolet images facilitated by photo-induced non-volatile phase transition in VO2 films.

Reconstructing the three-dimensional thermal structure of the ocean under typhoon conditions presents significant challenges due to the scarcity of observational data, particularly in subsurface regions, and the limitations of existing observation methods in terms of spatial and temporal resolution. Accurate reconstruction of these structures is crucial for understanding the energy exchange between the ocean and typhoons, as this exchange directly influences typhoon intensity and trajectory. To address these challenges, this study introduces a fully connected transformer network (FCT), which integrates fully connected layers with a transformer model. The FCT model leverages the attention mechanisms inherent in the transformer architecture to effectively extract and integrate multi-scale ocean dynamical features. Using data from Typhoon Lekima in 2019, this study reconstructs ocean thermal structures at various depths and achieves an RMSE of 1.03 °C and an MAE of 0.83 °C when validated against Argo data. Furthermore, the model's robustness was demonstrated through five-fold cross-validation, with the validation loss exhibiting minor fluctuations across folds but remaining stable overall, with an average validation loss of 0.986 °C, indicating the model's generalizability. Sensitivity analysis also revealed the model's resilience to variations in key input variables, showing minimal impact on output even with perturbations of up to 10% in input data. In addition, the study incorporates content analysis of typhoon-related news reports from 2011 to 2020, revealing a predominance of political topics, which underscores the central role of government in disaster response, with economic and ecological topics following. This integrated approach not only enhances our understanding of the interactions between ocean thermal structures and typhoon dynamics but also provides valuable insights into the societal impacts of typhoons, as reflected in media coverage, contributing to improved disaster management strategies. [ABSTRACT FROM AUTHOR]

Atherosclerosis (AS) is an inflammatory disease characterized by arterial inflammation. One important trigger for AS development is the excessive migration of vascular smooth muscle cells (VSMCs); however, the mechanism underlying this phenomenon remains unclear. Therefore, we investigated the role of DNA polymerase β (Pol β), a crucial enzyme involved in base excision repair, VSMC migration, and subsequent AS development. In this study, we revealed a significant increase in Pol β content within AS plaques in ApoE−/−Pol β+/+ mice. In vitro experiments demonstrated a significant decrease in hCASMC viability and migration ability upon Pol β knockdown, whereas the subsequent recovery of Pol β expression reversed this effect. Moreover, our investigations revealed that Pol β knockdown leads to the inhibition of the POSTN gene transcription by suppressing the YY1/TGF-β1 pathway, resulting in the decreased expression of the protein periostin during VSMC migration. Collectively, our findings provide insights into the role of Pol β in AS development, offering a novel approach for the clinical treatment of cardiovascular diseases. [ABSTRACT FROM AUTHOR]

High‐entropy spinel‐type oxides are synthesized by a modified Pechini process, wet chemistry approach, and solid‐state synthesis method and characterized as anode materials for Li‐ion batteries. The Pechini process that involves chelation and polyesterification reactions facilitates the formation of high‐entropy spinel‐type oxides without compositional segregation at ≈600 °C as confirmed by in situ and ex situ XRD. XAFS analysis and the Rietveld refinement of room‐temperature neutron diffraction data suggest the composition (Mn0.05Fe0.48Co0.47, tetrahedral)(Cr0.61Mn0.52Fe0.11Co0.09Ni0.68, octahedral)O4 for phase‐pure specimens. Compared to high‐entropy spinel‐type oxides synthesized by the solid‐state method, the precursor‐derived materials demonstrate higher specific capacity as anodes, in which the materials without citric acid addition exhibit low capacity fading at high current densities and maintained a capacity of ≈200 mAh g−1 after 1000 cycles. The generation of a rock‐salt‐type phase during cycling is confirmed for the first time by in situ charging–discharging XRD. The charging–discharging of this anode material is achieved mainly through the embedding–disembedding of lithium ions in the lattice of the generated rock‐salt‐type phase. [ABSTRACT FROM AUTHOR]

This article discusses a support vector regression-based interval power flow prediction method for distribution networks with distributed generators (DGs) integration. The method aims to address the challenges of uncertain power flow analysis in distribution networks, particularly as the size of the system increases. The proposed method utilizes intervals to describe system uncertainty and employs support vector regression for model training. Simulation results demonstrate that the method exhibits high prediction accuracy, adaptability, and computation efficiency, meeting the requirements for rapid and real-time power flow analysis in distribution networks with DGs integration. The text also discusses the construction of an Interval Power Flow (IPF) prediction model for distribution networks using Support Vector Regression (SVR). The model is a multi-output model that predicts the upper and lower bounds of power flow results, taking into account uncertainties in the distribution system. The model has been shown to have high prediction accuracy and computational efficiency in studies conducted on IEEE 33bw and IEEE 69 cases. The text concludes by stating that the claims expressed in the article are solely those of the authors and do not necessarily represent the views of their affiliated organizations or the publisher. The article titled "Distributionally robust multistage dispatch with discrete recourse of energy storage systems" by Zheng et al. explores the concept of distributionally robust multistage dispatch with discrete recourse of energy storage systems. The authors propose a mathematical model that considers uncertainties in renewable energy generation and electricity demand, and aims to optimize the dispatch of energy storage systems. The study highlights the importance of incorporating uncertainty [Extracted from the article]

The Jurassic coal-measure source rocks in the Junggar Basin have drawn considerable attention in recent years. In our hydrocarbon thermal simulation experiments of these rocks, we found that the dark mudstone evaluated as good source rock, had a much lower hydrocarbon generation capacity than the coal and carbonaceous mudstone, evaluated as poor source rock. Based on this background, we performed Fourier transform infrared spectroscopy (FTIR) and combined the results of semi-open thermal simulation experiments to explore the association between the molecular structure and hydrocarbon production capacity, with the aim of obtaining a new understanding of hydrocarbon potential of Jurassic coal-measure source rocks from the perspective of molecular structure. The results indicate that coals exhibit lower condensation of aromatic structures and higher relative abundance of aliphatic structures with a higher degree of branched chaining than mudstones and carbonaceous mudstones. Apparent aromaticity (fa), aromatic abundance parameter I, and degree of condensation (DOC) are negatively correlated with organic matter abundance. The aliphatic structural parameter H demonstrates a substantial positive correlation with organic matter abundance. Furthermore, aliphatic relative abundance factor A is associated with the type of organic matter; the better is the type of the organic matter, the larger is the A value. The combination of the molecular structures with the thermal simulation results shows that the aliphatic hydrogen enrichment of selected carbonaceous mudstone is similar to that of coal. However, the relative abundance of the aliphatic group of it is high, and the DOC of the aromatic structure is low, making the hydrocarbon generation base stronger and easier to crack. Thus, the hydrocarbon generation capacity of carbonaceous mudstone is slightly higher than that of coal. Mudstone has low H and I values, and the DOC is high, indicating that its hydrocarbon base is low, so it has low hydrocarbon generation capacity. Therefore, the molecular structure is closely associated with the hydrocarbon potential of coal-measure source rocks. When evaluating the qualities of coal-measure source rocks, the influence of molecular structure on these rocks should be considered. [ABSTRACT FROM AUTHOR]

Background In primary care, health professionals use blood tests to investigate nonspecific presentations to inform referral decisions. Reference ranges for the commonly used blood tests in western countries were developed in predominately White populations, and so may perform differently when applied to non-White populations. Knowledge of ethnic variation in blood test results in healthy/general populations could help address ethnic inequalities in cancer referral for diagnosis and outcomes. Objective This systematic review explored evidence of ethnic differences in the distribution of selected blood test results among healthy/general populations to inform future research aimed at addressing inequalities in cancer diagnosis. Methods We searched PubMed and EMBASE to identify studies reporting measures of haemoglobin, MCV, calcium, albumin, platelet count, and CRP in nondiseased adults from at least 2 different ethnic groups. Two reviewers independently screened studies, completed data extraction and quality assessment using an adapted Newcastle-Ottawa scale. Participants were stratified into White, Black, Asian, Mixed, and Other groups. Data were synthesised narratively and meta-analyses were conducted where possible. Results A total of 47 papers were included. Black men and women have lower average values of haemoglobin, MCV, and albumin, and higher average values of CRP relative to their White counterparts. Additionally, Black men have lower average haemoglobin than Asian men, whereas Asian women have lower average CRP values when compared with White women. Conclusions There is evidence of ethnic differences in average values of haemoglobin, MCV, CRP, and albumin in healthy/general populations. Further research is needed to explore the reasons for these differences. Systematic review registration: CRD42021274580 [ABSTRACT FROM AUTHOR]

The interaction of a tank impacting a water surface is an extremely complex nonlinear multiphase flow phenomenon. In this study, experiments and numerical simulations are used to systematically investigate the flow physics and load characteristics of a tank corner impacting a water surface. Free surface flow at different fall heights (200–800 mm) and inclination angles (0°–15°) was obtained through free fall experiments. The volume of fluids method and overset grid technology were used to simulate the water impact process of a three-dimensional structure accurately. For typical bubble flows, the numerical and experimental results agree well. On the basis of the three-dimensional flow characteristics and pressure distribution, flow behaviors, such as fluid climbing, corrugation disturbances, and air cavity effects, are analyzed. Bubble flow has a significant effect on the behavior mode of the impact load. In particular, the bubbles at the upper wall play a key role in the load characteristics at different locations. In addition, the influences of corrugations inside the tank's corner and the impact velocity on fluid flow were investigated. These results provide beneficial references for an in-depth understanding of the fluid flow and load characteristics between a tank and fluid. [ABSTRACT FROM AUTHOR]

The ability of conventional enzyme-linked immunosorbent assays to satisfy the increasing demand for advanced immunoassays is limited by their reliance on natural enzymes, low sensitivity, and narrow detection range. The development of nanozyme-assisted immunoassays is a viable approach to overcoming these constraints. Here, we report a one-step bimetallic nanozyme-assisted indirect competitive immunoassay to detect the pesticide acetamiprid in vegetables. Litchi-like bimetallic gold and platinum (Au@Pt) nanozymes with high catalytic properties and excellent biocompatibility were synthesized for this assay. The Au@Pt nanozymes were simple and inexpensive to prepare, exhibited stability and adjustable catalytic activity, and were directly conjugated with antibodies as signal probes, without the use of horseradish peroxidase-conjugated Affinipure goat antimouse IgG (IgG-HRP). Acetamiprid was shown to compete with the antigen to bind the Au@Pt probes. Subsequently, Au@Pt probes, which exhibited peroxidase-like activity, were used to catalyze the oxidation of colorless 3,3′,5,5′-tetramethylbenzidine, demonstrating the easy detection of acetamiprid through colorimetric signal monitoring. The linear range, sensitivity, relative standard deviation range, and limit of detection of the immunoassay were 1.85–327.19 μg/L, 25.58 μg/L, 0.46–10.35%, and 0.78 μg/L, respectively, satisfying the detection requirements. In conclusion, the method exhibited high sensitivity, reproducibility, and a wide linear range for the detection of acetamiprid, while eliminating the need for IgG and simplifying the experimental procedure. This new indirect competitive immunoassay has great potential value for on-site sensitive detection of acetamiprid in vegetables. [ABSTRACT FROM AUTHOR]

Ensuring rice (Oryza sativa) self-sufficiency in China relies significantly on achieving high grain yields in hybrid rice production. This study conducted field experiments across two site-years, comparing grain yield per unit of land area, grain yield generated per seedling, and associated yield traits for a hybrid rice variety under two combinations of hill spacing and the number of seedlings per hill. The combinations included a hill spacing of 30 cm × 14 cm with one seedling per hill (H14S1) and a hill spacing of 30 cm × 24 cm with three seedlings per hill (H24S3). The results revealed that H14S1 consistently outperformed H24S3, demonstrating a 7%–16% increase in grain yield per unit of land area and an impressive 88%–104% higher grain yield generated per seedling. H14S1 exhibited 56%–77% more panicles formed per seedling and 10%–15% more spikelets per panicle compared to H24S3. H14S1 produced 78%–115% higher biomass at heading and maturity per seedling and 8%–25% higher biomass at heading and maturity per tiller than H24S3. This study underscores the importance of promoting the individual growth and development of seedlings as a crucial strategy for achieving higher grain yield in hybrid rice production. [ABSTRACT FROM AUTHOR]

Studies of perceptual learning have revealed a great deal of plasticity in adult humans. In this study, we systematically investigated the effects and mechanisms of several forms (trial-by-trial, block, and session rewards) and levels (no, low, high, subliminal) of monetary reward on the rate, magnitude, and generalizability of perceptual learning. We found that high monetary reward can greatly promote the rate and boost the magnitude of learning and enhance performance in untrained spatial frequencies and eye without changing interocular, interlocation, and interdirection transfer indices. High reward per se made unique contributions to the enhanced learning through improved internal noise reduction. Furthermore, the effects of high reward on perceptual learning occurred in a range of perceptual tasks. The results may have major implications for the understanding of the nature of the learning rule in perceptual learning and for the use of reward to enhance perceptual learning in practical applications.

BackgroundMost patients with osteoporotic vertebral compression fracture (OVCF) obtain pain relief after vertebral augmentation, but some will experience residual back pain (RBP) after surgery. Although several risk factors of RBP have been reported, it is still difficult to estimate the risk of RBP preoperatively. Radiomics is helpful for disease diagnosis and outcome prediction by establishing complementary relationships between human-recognizable and computer-extracted features. However, musculoskeletal radiomics investigations are less frequently reported.ObjectiveThis study aims to establish a radiomics score (rad-score) based nomogram for the preoperative prediction of RBP in OVCF patients.MethodsThe training cohort of 731 OVCF patients was used for nomogram development, and the validation cohort was utilized for performance test. RBP was determined as the score of visual analogue scale ≥ 4 at both 3 and 30 days following surgery. After normalization, the RBP-related radiomics features were selected to create rad-scores. These rad-scores, along with the RBP predictors initially identified by univariate analyses, were included in the multivariate analysis to establish a nomogram for the assessment of the RBP risk in OVCF patients preoperatively.ResultsA total of 81 patients (11.2%) developed RBP postoperatively. We finally selected 8 radiomics features from 1316 features extracted from each segmented image to determine the rad-score. Multivariate analysis revealed that the rad-score plus bone mineral density, intravertebral cleft, and thoracolumbar fascia injury were independent factors of RBP. Our nomograms based on these factors demonstrated good discrimination, calibration, and clinical utility in both training and validation cohorts. Furthermore, it achieved better performance than the rad-score itself, as well as the nomogram only incorporating regular features.ConclusionWe developed and validated a nomogram incorporating the rad-score and regular features for preoperative prediction of the RBP risk in OVCF patients, which contributed to improved surgical outcomes and patient satisfaction.

Abstract Doxorubicin hydrochloride (DOX) is one of the widely used antineoplastic agents in treating various cancers, yet it is always associated with the occurrence of adverse reactions that limit its clinical use. Currently, encapsulating DOX in micelles may represent a promising strategy to reduce toxicity and side effects of the drug. This study aimed to explore a novel acitretin-based surfactant (ACMeNa) with good solid stability to encapsulate DOX to form micelles (ACM-DOX). In this work, ACM-DOX micelles were prepared by a microfluidic method free of organic solvents. The characteristics of ACM-DOX micelles were assessed, including morphology, particle size, stability, entrapment efficiency, and drug loading. An in vitro cytotoxicity experiment of the micelles on MDA-MB-231 (a human breast cancer cell line) was also performed. The micelle formation mechanism suggested that the insoluble ACMeNa/DOX complex was formed by electrostatic interaction, and subsequently encapsulated by self-assembly into micelles. The designed ACM-DOX micelles had an average particle size of 19.4 ± 0.2 nm and a zeta potential of −43.7 ± 2.4 mV, with entrapment efficiency and drug loading efficiency of 92.4 ± 0.5% and 33.4 ± 0.3%, respectively. The ACM-DOX micelles had worm-like structures under a Cryo-transmission electron microscope and exhibited good stability within 8 hours after reconstitution and 4- to 32-fold dilution of its reconstituted solution. ACM-DOX micelles released 80% of DOX within 24 hours in a medium of pH = 5.0, and its drug profile can be described by a first-order model. Moreover, ACM-DOX micelles showed cytotoxicity against MDA-MB-231 in a dose-dependent manner, and displayed a higher antitumor activity as compared with free DOX, with IC50 values of DOX and ACM-DOX micelles being 6.80 ± 0.50 and 4.64 ± 0.32 μg/mL, respectively. Given above, ACMeNa has great application potential as a DOX carrier for the treatment of cancers.