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Glycyrrhiza is an important medicinal crop that has been extensively utilized in the food and medical sectors, yet studies on hyperspectral remote sensing monitoring of glycyrrhiza are currently scarce. This study analyzes glycyrrhiza hyperspectral images, extracts characteristic bands and vegetation indices, and constructs inversion models using different input features. The study obtained ground and unmanned aerial vehicle (UAV) hyperspectral images and chlorophyll content (called Soil and Plant Analyzer Development (SPAD) values) from sampling sites at three growth stages of glycyrrhiza (regreening, flowering, and maturity). Hyperspectral data were smoothed using the Savitzky–Golay filter, and the feature vegetation index was selected using the Pearson Correlation Coefficient (PCC) and Recursive Feature Elimination (RFE). Feature extraction was performed using Competitive Adaptive Reweighted Sampling (CARS), Genetic Algorithm (GA), and Successive Projections Algorithm (SPA). The SPAD values were then inverted using Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost), and the results were analyzed visually. The results indicate that in the ground glycyrrhiza inversion model, the GA-XGBoost model combination performed best during the regreening period, with R2, RMSE, and MAE values of 0.95, 0.967, and 0.825, respectively, showing improved model accuracy compared to full-spectrum methods. In the UAV glycyrrhiza inversion model, the CARS-PLSR combination algorithm yielded the best results during the maturity stage, with R2, RMSE, and MAE values of 0.83, 1.279, and 1.215, respectively. This study proposes a method combining feature selection techniques and machine learning algorithms that can provide a reference for rapid, nondestructive inversion of glycyrrhiza SPAD at different growth stages using hyperspectral sensors. This is significant for monitoring the growth of glycyrrhiza, managing fertilization, and advancing precision agriculture. [ABSTRACT FROM AUTHOR]

This research focuses on Scene Text Recognition (STR), a crucial component in various applications of artificial intelligence such as image retrieval, office automation, and intelligent traffic systems. Recent studies have shown that semantic-aware approaches significantly improve the performance of STR tasks, with context-aware STR methods becoming mainstream. Among these, the fusion of visual and language models has shown remarkable effectiveness. We propose a novel method (PABINet) that incorporates three key components: a Visual-Language Decoder, a Language Model, and a Fusion Model. First, during training, the Visual-Language Decoder masks the original labels in the Transformer decoder using permutation masks, with each mask being unique. This enhances word memorization and learning through contextual semantic information, resulting in robust semantic knowledge. During the inference stage, the Visual-Language Decoder employs autonomous Autoregressive model (AR) inference to generate results. Subsequently, the Language Model scrutinizes and corrects the output of the Visual-Language Encoder using a cloze mask approach, achieving context-aware, autonomous, bidirectional inference. Finally, the Fusion Model concatenates and refines the outputs of both models through iterative layers.Experimental results demonstrate that our PABINet performs exceptionally well when handling various quality images. When trained with synthetic data, PABINet achieves a new STR benchmark (average accuracy of 92.41%), and when trained with real data, it establishes new state-of-the-art results (average accuracy of 96.28%). [ABSTRACT FROM AUTHOR]

The photoluminescent properties of lanthanide complexes have been thoroughly investigated; however, there have been much fewer studies showcasing their potential use in ionizing radiation detection. In this work, we delve into the photo‐ and radio‐induced luminescence of a series of lanthanide‐bearing organic‐inorganic hybrids and their potential as a platform for X‐ray scintillation and imaging. The judicious synergy between lanthanide cations and 2,6‐di(1H‐pyrazol‐1‐yl)isonicotinate (bppCOO−) ligands affords six new materials with three distinct structures. Notably, Eu‐bppCOO‐1 and Tb‐bppCOO‐2 display sharp fingerprint X‐ray‐excited luminescence (XEL), the intensities of which can be linearly correlated with the X‐ray dose rates over a broad dynamic range (0.007–4.55 mGy s−1). Moreover, the X‐ray sensing efficacies of Eu‐bppCOO‐1 and Tb‐bppCOO‐2 were evaluated, showing that Tb‐bppCOO‐2 features a lower detection limit of 4.06 μGy s−1 compared to 14.55 μGy s−1 of Eu‐bppCOO‐1. Given the higher X‐ray sensitivity and excellent radiation stability of Tb‐bppCOO‐2, we fabricated a flexible scintillator film for X‐ray imaging by embedding finely ground Tb‐bppCOO‐2 in the polydimethylsiloxane (PDMS) polymer. The resulting scintillator film can be utilized for high‐resolution X‐ray imaging with a spatial resolution of approximately 7 lp mm−1. [ABSTRACT FROM AUTHOR]

Background: This study aimed to determine the factors that contribute to the failure of bowel preparation in patients undergoing colonoscopy and to develop a risk prediction model. Methods: A total of 1115 outpatients were included. Patients were randomly divided into two groups: the modeling group (669 patients) and the validation group (446 patients). In the modeling group, patients were further divided into two groups based on their success and failure in bowel preparation using the Boston Bowel Preparation Scale. A logistic regression analysis model was used to determine the risk factors of bowel preparation failure, which was subsequently visualized using an alignment diagram. Results: After controlling for relevant confounders, multifactorial logistic regression results showed that age ≥ 60 years (OR = 2.246), male (OR = 2.449), body mass index ≥ 24 (OR = 2.311), smoking (OR = 2.467), chronic constipation (OR = 5.199), diabetes mellitus (OR = 5.396) and history of colorectal surgery (OR = 5.170) were influencing factors of bowel preparation failure. The area under the ROC curve was 0.732 in the modeling group and 0.713 in the validation group. According to the calibration plot, the predictive effect of the model and the actual results were in good agreement. Conclusions: Age ≥ 60 years, male, body mass index ≥ 24, smoking, chronic constipation, diabetes mellitus, and history of colorectal surgery are independent risk factors for bowel preparation failure. The established prediction model has a good predictive efficacy and can be used as a simple and effective tool for screening patients at high risk for bowel preparation failure. [ABSTRACT FROM AUTHOR]

Developing new membranes with both high selectivity and permeability is critical in membrane science since conventional membranes are often limited by the trade-off between selectivity and permeability. In recent years, the emergence of advanced materials with accurate structures at atomic or molecular scale, such as metal organic framework, covalent organic framework, graphene, has accelerated the development of membranes, which benefits the precision of membrane structures. In this review, current state-of-the-art membranes are first reviewed and classified into three different types according to the structures of their building blocks, including laminar structured membranes, framework structured membranes and channel structured membranes, followed by the performance and applications for representative separations (liquid separation and gas separation) of these precisely designed membranes. Last, the challenges and opportunities of these advanced membranes are also discussed. [ABSTRACT FROM AUTHOR]

In order to solve the problem of large rotating missile surface infrared radiation interference during the dual-band infrared radiation attitude measurement and improve the infrared attitude measurement accuracy, the rotating missile self-infrared radiation compensation method is studied. Based on the six degree of freedom ballistic model, the surface temperature and infrared radiation characteristics of the missile are studied, and the surface temperature equation of the rotating missile is derived. According to the propagation law of dual-band infrared radiation in the atmosphere, the brightness of missile body dual-band infrared radiation is calculated, the mathematical model of dual-band infrared radiation compensation of the missile body is established, and the attitude compensation parameters of dual-band infrared radiation are simulated. The results of semi-physical experiments show that the error of attitude angle calculation after missile self-infrared radiation interference compensation is significantly reduced, and the attitude angle calculation accuracy is increased by more than 2.5 times. The compensation method provides an effective technical implementation method for the rotating missile self-infrared radiation interference compensation. [ABSTRACT FROM AUTHOR]

Synergistic assembly of uranyl centres and luminescent 2,6-bis(pyrazol-1-yl)pyridine-4-carboxylates (bppCOOH) gives rise to a uranyl coordination polymer, namely U-bppCOO, which exhibits a luminescence quenching response toward UV or X-ray irradiation doses. Notably, the photosensitivity of U-bppCOO has been significantly enhanced via metal–ligand assembly compared with that of the naked bppCOOH ligand. [ABSTRACT FROM AUTHOR]

We explore the interaction between estrogen and PCSK9 and their collective impact on lipid metabolism, especially concerning the regulation of low-density lipoprotein receptor levels. Utilizing both animal and cellular models, including ovariectomized mice and HepG2 cell lines, we demonstrate that estrogen deficiency leads to a disruption in lipid metabolism, characterized by elevated levels of total cholesterol and LDL-C. The study commences with mice undergoing ovariectomy, followed by a diet regimen comprising either high-fat diet or normal feed for a four-week duration. Key assessments include analyzing lipid metabolism, measuring PCSK9 levels in the bloodstream, and evaluating hepatic low-density lipoprotein receptor expression. We will also conduct correlation analyses to understand the relationship between PCSK9 and various lipid profiles. Further, a subset of ovariectomized mice on high-fat diet will undergo treatment with either estrogen or PCSK9 inhibitor for two weeks, with a subsequent re-evaluation of the earlier mentioned parameters. Our findings reveal that estrogen inhibits PCSK9-mediated degradation of low-density lipoprotein receptor, a process crucial for maintaining lipid homeostasis. Through a series of experiments, including immunohistochemistry and western blot analysis, we establish that PCSK9 is involved in lipid metabolism disorders caused by estrogen deficiency and that estrogen regulates PCSK9 and low-density lipoprotein receptor at post-transcriptional level. The study provides a mechanism for the involvement of PCSK9 in elucidating the disorders of lipid metabolism caused by estrogen deficiency due to perimenopause and ovarian decline. [ABSTRACT FROM AUTHOR]

Background: The deposition of β-amyloid (Aβ) in the brain is a biomarker of Alzheimer's disease (AD). Highly sensitive Aβ positron emission tomography (PET) imaging plays an essential role in diagnosing and evaluating the therapeutic effects of AD. Aim: To synthesize a new Aβ tracer [18F]DRKXH1 (5-(4-(6-(2-[18]fluoroethoxy)ethoxy)imidazo[1,2-alpha]pyridin-2-yl)phenyl) and evaluate the tracer performance by biodistribution analysis, in vivo small-animal PET-CT dynamic scan, ex vivo and in vitro autoradiography, and PET in human subjects. Methods: [18F]DRKXH1 was synthesized automatically by the GE FN module. Log D (pH 7.4) and biodistribution of [18F]DRKXH1 were investigated. Small-animal-PET was used for [18F]DRKXH1 and [18F]AV45 imaging study in AD transgenic mice (APPswe/PSEN1dE9) and age-matched normal mice. The distribution volume ratios (DVR) and standardized uptake value ratios (SUVRs) were calculated with the cerebellum as the reference region. The deposition of Aβ plaques in the brain of AD transgenic mice was determined by ex vivo autoradiography and immunohistochemistry. In vitro autoradiography was performed in the postmortem brain sections of AD patients and healthy controls. Two healthy control subjects and one AD patient was subjected to in vivo PET study using [18F]DRKXH1. Results: The yield of [18F]DRKXH1 was 40%, and the specific activity was 156.64 ± 11.55 GBq/μmol. [18F]DRKXH1 was mainly excreted through the liver and kidney. The small-animal PET study showed high initial brain uptake and rapid washout of [18F]DRKXH1. The concentration of [18F]DRKXH1 was detected in the cortex and hippocampus of AD transgenic mice brain. The cortex DVR of AD transgenic mice was higher than that of WT mice (P < 0.0001). Moreover, the SUVRs of AD transgenic mice were higher than those of WT mice based on the 0–60-min dynamic scanning. In vitro autoradiography showed a significant concentration of tracer in the Aβ plaque-rich areas in the brain of AD transgenic mice. The DVR value of [18F]-DRKXH1 is higher than that of [18F]-AV45 (1.29 ± 0.05 vs. 1.05 ± 0.08; t = 5.33, P = 0.0003). Autoradiography of postmortem human brain sections showed [18F]DRKXH1-labeled Aβ plaques in the AD brain. The AD patients had high retention in cortical regions, while healthy control subjects had uniformly low radioactivity uptake. Conclusions: [18F]DRKXH1 is an Aβ tracer with high sensitivity in preclinical study and has the potential for in vivo detection of the human brain. [ABSTRACT FROM AUTHOR]

In order to further improve the performance of dual-band infrared and magnetic fusion attitude measurement method, an interactive multimodel extended Kalman filter (IMMEKF) attitude fusion algorithm is proposed to calculate the rotating missile's full attitude angle by using the data collected from dual-band two-axis infrared sensors and three-axis geomagnetic sensor. Four filtering models are used to solve the problem of inaccuracy in the single-model filtering process. The interactive multimodel and extended Kalman filter attitude estimation algorithms are combined by the probability density function and are used to update the model probability in real time. Each model's probability weights are modified to achieve the optimal attitude angle estimation according to the environment. The semiphysical experimental results show that the IMMEKF algorithm has higher accuracy and reliability compared with other latest state-of-the-art fusion estimation algorithms under normal infrared and geomagnetic conditions. In the case of infrared or geomagnetic anomalies, only the IMMEKF algorithm can avoid using the affected sensor data and calculate an accurate value of attitude angle. The reliability of the dual-band infrared and geomagnetic combined attitude estimation method is improved, which provides an effective technical implementation for the rotating missile attitude measurement. [ABSTRACT FROM AUTHOR]

Background and Purpose: In major depressive disorder (MDD), exploration of biomarkers will be helpful in diagnosing the disorder as well as in choosing a treatment and predicting the treatment response. Currently, tRNA‐derived small ribonucleic acids (tsRNAs) have been established as promising non‐invasive biomarker candidates that may enable a more reliable diagnosis or monitoring of various diseases. Herein, we aimed to explore tsRNA expression together with functional activities in MDD development. Experimental Approach: Serum samples were obtained from patients with MDD and healthy controls, and small RNA sequencing (RNA‐Seq) was used to profile tsRNA expression. Dysregulated tsRNAs in MDD were validated by quantitative real‐time polymerase chain reaction (qRT‐PCR). The diagnostic utility of specific tsRNAs and the expression of these tsRNAs after antidepressant treatment were analysed. Key Results: In total, 38 tsRNAs were significantly differentially expressed in MDD samples relative to healthy individuals (34 up‐regulated and 4 down‐regulated). qRT‐PCR was used to validate the expression of six tsRNAs that were up‐regulated in MDD (tiRNA‐1:20‐chrM.Ser‐GCT, tiRNA‐1:33‐Gly‐GCC‐1, tRF‐1:22‐chrM.Ser‐GCT, tRF‐1:31‐Ala‐AGC‐4‐M6, tRF‐1:31‐Pro‐TGG‐2 and tRF‐1:32‐chrM.Gln‐TTG). Interestingly, serum tiRNA‐Gly‐GCC‐001 levels exhibited an area under the ROC curve of 0.844. Moreover, tiRNA‐Gly‐GCC‐001 is predicted to suppress brain‐derived neurotrophic factor (BDNF) expression. Furthermore, significant tiRNA‐Gly‐GCC‐001 down‐regulation was evident following an 8‐week treatment course and served as a promising baseline predictor of patient response to antidepressant therapy. Conclusion and Implications: Our current work reports for the first time that tiRNA‐Gly‐GCC‐001 is a promising MDD biomarker candidate that can predict patient responses to antidepressant therapy. [ABSTRACT FROM AUTHOR]

Infrared radiation attitude measurement technology is a new, non-inertial, satellite independent and fast-responding attitude parameters testing method. However, the random occurrence of infrared radiation during missile flight, such as clouds or solar radiation, can cause significant interference in infrared radiation attitude measurement. To enhance the anti-interference capability of infrared radiation attitude measurement, the adaptive active differential (AAD) interference feature extraction algorithm and the four-axis error avoidance (FEA) attitude calculation algorithm with dual-band infrared radiation (DIR) are proposed. Initially, the long-wave and mid-wave infrared radiation laws of clouds and solar radiation are analyzed to identify their different characteristics in both wavebands. The interference type encountered by the rotating missile during flight is extracted by the designed AAD algorithm. Subsequently, based on the results of AAD algorithm, the adjacent axis long-wave or mid-wave infrared sensor data with less or no interference influence is selected. Finally, the attitude angle information is obtained by using two-axis or four-axis attitude calculation algorithm. The results of the semi-physical experiments indicate that the four-axis dual-band infrared attitude measurement device using the FEA algorithm can achieve RMSE about 1 even under the interference of solar or clouds cover. • Four-axis dual-band infrared attitude measurement. • Adaptive active differential (AAD) interference feature extraction algorithm. • Four-axis error avoidance (FEA) attitude calculation algorithm. • Interference from clouds and solar can be avoided. [ABSTRACT FROM AUTHOR]

In this study, an alkaline-catalyzed sulfolane/water solvent system was developed for isolating high-purity and antioxidative lignin from willow (Salix matsudana cv. Zhuliu). Optimization of the pretreatment conditions such as temperature, sulfolane/water ratio, and alkaline catalyst (NaOH) dosage were comprehensively investigated for effective lignin extraction from willow. The 44.4% of lignin was recovered from the biomass with 54% of delignification in 50/50 (w/w) sulfolane/water system at 170 °C. As the addition of the alkaline catalyst (NaOH) increased to 4%, the delignification yield was increased up to 94% with about 70% of lignin recovery yield. The recovered lignin was comparatively investigated with its control, milled wood lignin (MWL). The β- O -4 linkages and phenolic hydroxyl were well preserved in the extracted lignin fractions with the sulfolane/water system. Furthermore, excellent radical scavenging ability was observed with the extracted lignins by sulfolane/water pretreatments owing to rich phenolic hydroxyl groups in the lignins. Hence, systematical investigation on the lignin properties and potential applications under sulfolane organosolv pretreatment would promote the utilization of lignin in biorefinery processes. [ABSTRACT FROM AUTHOR]

Integrating gas as a main building block into nanomaterial construction is a challenging mission that remains elusive. Herein, we report a gas‐constructed vesicular system formed by CO2 gas and frustrated Lewis pairs (FLPs). Two molecular triads bearing three bulky borane and phosphine groups are designed as trivalent disc‐like FLP monomers. CO2, as a gas cross‐linker, can drive the two‐dimensional polymerization of these two FLP monomers, leading to the generation of planar FLP networks that further transform into a thermodynamically favored membranous vesicle structure. Gas‐guided vesicle formation is also applicable to other inert but FLP‐activatable gases. Different gas linkages can form vesicles with distinct architectures, sizes, and morphologies. We envisage that this study would suggest a new concept that exploits gases to fabricate tunable nanomaterials. [ABSTRACT FROM AUTHOR]

Integrating gas as a main building block into nanomaterial construction is a challenging mission that remains elusive. Herein, we report a gas‐constructed vesicular system formed by CO2 gas and frustrated Lewis pairs (FLPs). Two molecular triads bearing three bulky borane and phosphine groups are designed as trivalent disc‐like FLP monomers. CO2, as a gas cross‐linker, can drive the two‐dimensional polymerization of these two FLP monomers, leading to the generation of planar FLP networks that further transform into a thermodynamically favored membranous vesicle structure. Gas‐guided vesicle formation is also applicable to other inert but FLP‐activatable gases. Different gas linkages can form vesicles with distinct architectures, sizes, and morphologies. We envisage that this study would suggest a new concept that exploits gases to fabricate tunable nanomaterials. [ABSTRACT FROM AUTHOR]

Highlights • A new atmospheric turbulence interference compensation method for infrared attitude measurement. • The infrared radiation propagation path model and intensity weakening model are established. • The ability of the anti-aerodynamic turbulence interference is improved. • The estimation accuracy of roll angle can be kept within ±1°. Abstract In researching the disturbance of atmospheric turbulence in the infrared attitude measurement, a compensation model for atmospheric turbulence interference with missile-borne infrared radiation is established, which improves the solution accuracy of infrared attitude measurement method. Firstly, the influence of aerodynamic turbulence on the infrared radiation transmission direction received by the missile-borne infrared sensors is analysed. Meanwhile, a model of infrared radiation propagation path under the influence of turbulence is established. Then, the infrared radiation weakening degree received by infrared sensors is calculated, and the infrared radiation compensation model is designed with the earth infrared radiation model. Finally, through the curve fitting and derivation, the calculation formula of attitude angle compensation under the influence of atmospheric turbulence is established. The results from the experiments show that the roll angle calculation error is within ±1 degree, the ability of the anti-aerodynamic turbulence interference is improved and the problem of low accuracy of infrared radiation attitude measurement is solved. [ABSTRACT FROM AUTHOR]

With the further development of infrared radiation research in sea-sky background and the requirement of spinning projectile’s attitude measurement, the sea-sky infrared radiation field is used to carry out spinning projectile’s attitude angle instead of inertial sensors. Firstly, the generation mechanism of sea-sky infrared radiation is analysed. The mathematical model of sea-sky infrared radiation is deduced in LW (long wave) infrared 8 ∼ 14 µm band by calculating the sea surface and sky infrared radiation. Secondly, according to the movement characteristics of spinning projectile, the attitude measurement model of infrared sensors on projectile’s three axis is established. And the feasibility of the model is analysed by simulation. Finally, the projectile’s attitude calculation algorithm is designed to improve the attitude angle estimation accuracy. The results of semi-physical experiments show that the segmented interactive algorithm estimation error of pitch and roll angle is within ±1.5°. The attitude measurement method is effective and feasible, and provides accurate measurement basis for the guidance of spinning projectile. [ABSTRACT FROM AUTHOR]

Protein allostery, a chemical‐to‐mechanical effect that can precisely regulate protein structure, exists in many proteins. Herein, we demonstrate that protein allostery can be used to drive self‐assembly for the construction of tunable protein architectures. Calmodulin (CaM) was chosen as a model allosteric protein. Ca2+‐mediated contraction of CaM to a closed state can activate CaM and its ligand to self‐assemble into a 1D protein helical microfilament. Conversely, relaxation of CaM to the open state can unwind and further dissociate the helical assemblies. Fine regulation of the protein conformation by tuning the external Ca2+ level allows us to obtain various protein helical nanostructures with tunable helicity. This study offers a new approach toward chemomechanically controlled protein self‐assembly. [ABSTRACT FROM AUTHOR]

Abstract: Protein allostery, a chemical‐to‐mechanical effect that can precisely regulate protein structure, exists in many proteins. Herein, we demonstrate that protein allostery can be used to drive self‐assembly for the construction of tunable protein architectures. Calmodulin (CaM) was chosen as a model allosteric protein. Ca2+‐mediated contraction of CaM to a closed state can activate CaM and its ligand to self‐assemble into a 1D protein helical microfilament. Conversely, relaxation of CaM to the open state can unwind and further dissociate the helical assemblies. Fine regulation of the protein conformation by tuning the external Ca2+ level allows us to obtain various protein helical nanostructures with tunable helicity. This study offers a new approach toward chemomechanically controlled protein self‐assembly. [ABSTRACT FROM AUTHOR]

Aiming at the problems of Uyghur oblique deformation, character adhesion and character similarity in scene images, this paper proposes a scene Uyghur recognition model with enhanced visual prediction. First, the content-aware correction network TPS++ is used to perform feature-level correction for skewed text. Then, ABINet is used as the basic recognition network, and the U-Net structure in the vision model is improved to aggregate horizontal features, suppress multiple activation phenomena, better describe the spatial characteristics of character positions, and alleviate the problem of character adhesion. Finally, a visual masking semantic awareness (VMSA) module is added to guide the vision model to consider the language information in the visual space by masking the corresponding visual features on the attention map to obtain more accurate visual prediction. This module can not only alleviate the correction load of the language model, but also distinguish similar characters using the language information. The effectiveness of the improved method is verified by ablation experiments, and the model is compared with common scene text recognition methods and scene Uyghur recognition methods on the self-built scene Uyghur dataset. [ABSTRACT FROM AUTHOR]

Linguistic knowledge helps a lot in scene text recognition by providing semantic information to refine the character sequence. The visual model only focuses on the visual texture of characters without actively learning linguistic information, which leads to poor model recognition rates in some noisy (distorted and blurry, etc.) images. In order to address the aforementioned issues, this study builds upon the most recent findings of the Vision Transformer, and our approach (called Display-Semantic Transformer, or DST for short) constructs a masked language model and a semantic visual interaction module. The model can mine deep semantic information from images to assist scene text recognition and improve the robustness of the model. The semantic visual interaction module can better realize the interaction between semantic information and visual features. In this way, the visual features can be enhanced by the semantic information so that the model can achieve a better recognition effect. The experimental results show that our model improves the average recognition accuracy on six benchmark test sets by nearly 2% compared to the baseline. Our model retains the benefits of having a small number of parameters and allows for fast inference speed. Additionally, it attains a more optimal balance between accuracy and speed. [ABSTRACT FROM AUTHOR]

New strategies with the ability to enhance both the humoral and cellular immune responses remain a priority for the development of future therapeutic cancer vaccines. In this study, we took advantage of β-glucan particles (GPs) derived from Saccharomyces cerevisiae baker's yeast and a novel reverse micro-emulsion method to prepare an antigen-loaded GP carrier system for dendritic cell (DC) specific antigen delivery, followed by careful evaluation of the immune functions of the prepared particles in initiating both the humoral and cellular immune responses through in vitro and in vivo experiments. The prepared particles greatly promoted DC activation and cytokine production and cross presented the antigen to CD8 cells, inducing very strong OVA specific humoral and cellular immune responses. Treatment with these particles significantly prevented the growth of implanted EG7-OVA tumors in a prophylactic and pre-established tumor model. These results suggest that our strategy may be able to be utilized as a promising platform for cancer immunotherapy. [ABSTRACT FROM AUTHOR]

Scene text recognition (STR) has been a hot research field in computer vision, aiming to recognize text in natural scenes using computers. Currently, attention-based encoder–decoder frameworks struggle to precisely align feature regions with the target object when dealing with complex and low-quality images, a phenomenon known as attention drift. Additionally, with the rise of Transformer, the increasing size of parameters results in higher computational costs. In order to solve the above problems, based on the latest research results of Vision Transformer (ViT), we utilize an additional position-enhancement branch to alleviate attention drift and dynamically fused position information with visual information to achieve better recognition accuracy. The experimental results demonstrate that our model achieves a 3% higher average recognition accuracy on the test set compared to the baseline. Meanwhile, our model maintains the advantage of a small number of parameters and fast inference speed, achieving a good balance between accuracy, speed, and computational load. [ABSTRACT FROM AUTHOR]

• The dual-band solar infrared radiation is calculated and counted by MODTRAN. • The solar infrared radiation influence on attitude measurement is simulated and analyzed. • A four-axis long wave infrared sensor attitude compensation algorithm is designed. • The pitch angle error of the compensation algorithm can be kept within ±1 degree. Aiming at the problem that the dual-band infrared radiation attitude measurement cannot be used all day long, the dual-band solar infrared radiation interference analysis and compensation technology are studied. The proportion of solar direct and scattered infrared radiation in the total atmospheric radiation is counted by MODTRAN, and the influence of solar infrared radiation interference on dual-band attitude measurement is simulated. It shows that the medium wave infrared sensor cannot work normally under the influence of solar infrared radiation. When the long wave infrared sensor is facing the solar infrared radiation, it will produce an attitude angle error within 18 degrees, but when it is not facing the solar infrared radiation, the impact is small, and the attitude angle error is within 1 degree. Based on the solar infrared radiation interference law on long wave infrared radiation sensor, a four-axis attitude compensation algorithm with long wave infrared radiation sensor is designed. The semi-physical experimental results show that the attitude solution accuracy of the four-axis attitude compensation algorithm is within ±1 degree, which effectively improves the infrared radiation attitude test accuracy under the interference of solar infrared radiation. The algorithm is proved to be a solution with strong anti-interference ability for the dual-band infrared radiation attitude measurement of rotating projectile under all-day situation. [ABSTRACT FROM AUTHOR]

A vanillic acid imprinted mesoporous silica polymer (MIPs) was prepared by copolymerizing a modified mesoporous silica molecular sieve with template molecule, functional monomer and cross-linker in present work. Interaction between the template and functional monomer was investigated by ultraviolet/visible spectrophotometry. These MIPs were characterized by Fourier transmission infrared spectrometry (FTIR) and scanning electron microscopy (SEM). Adsorption dynamics and thermodynamic behavior of MIPs was explored and the selective recognition capability evaluated. Also, the applicability for the MIPs as solid phase extraction media was tested. Results indicated the 1:1 (mole ratio) complex of vanillic acid-4-vinylpyridine might predominate in the pre-polymerization mixture and the MIPs obtained possessed rapid binding dynamics and higher affinity toward template molecules, reaching adsorption equilibrium within 230 min with the highest adsorption amount of 50.7 mg g −1 . Freundlich model was shown best to describe isotherm adsorption for the MIPs. The MIPs could selectively bind template molecule with selectivity coefficients of 1.36–1.50. In addition, a higher enrichment capability when using it for gathering target compound from methanol extract of Artemisia stelleriana and a good reusability during adsorption–desorption recycling use could be observed. [ABSTRACT FROM AUTHOR]

By using femtosecond laser micromachining, optical wave guides in both depressed cladding and dual-line configurations have been produced in LiTaO3 crystal. The guiding properties and the thermal stability have been investigated for both geometries, which exhibit different performance. Depressed cladding waveguides support guidance along both extraordinary and ordinary index polarizations, while dual-line waveguides support only extraordinary index polarization. Thermal annealing has been proved to be an effective method to reduce the propagation losses. For the cladding waveguide, the lowest propagation loss was as low as 0.38 dB/cm after the annealing treatment at 400 °C. (© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [ABSTRACT FROM AUTHOR]

The complex heterogeneities of underground rocks will cause wave-induced fluid flows at different scales, which consequently leads to the wave velocity dispersion and energy loss. Mastering and modeling the frequency-dependent elastic and attenuation behaviors are of great significance to characterize underground rocks using multi-scale geophysical data. Following Biot's approach, the constitutive relationship, kinetic energy and dissipation functions in regard to wave induced global fluid flow, interlayer local fluid flow and squirt flow in the annular and penny-shaped cracks are established. From the Lagrange equations, the wave equations considering multi-scale wave induced fluid flow are further derived, which yields three P waves and one S wave. The frequency-dependent velocity and attenuation of fast P wave calculated by the multi-scale wave equations present nice match with that of the single-scale or dual-scale theories in the corresponding frequency bands. Besides, the multi-scale wave theory, under certain circumstance, can be degenerated to the widely known theories including Tang's pore-crack theory, the layered double-porosity theory and Biot's theory, which theoretically illustrates the rationality of the novel wave equation. In order to adjust the low-frequency velocity of the multi-scale wave equations to Gassmann velocity, the dynamic fluid modulus (DFM) is introduced into the multi-scale wave theory. However, the original multi-scale wave theory behaves better fit with the experimental data in comparison with the DFM multi-scale wave theory. The effect of micro-parameters on the dispersion and attenuation calculated by the multi-scale wave theory indicates that the annular crack deforms more with weaker stiffness than the penny-shaped cracks under the same aspect ratio. • We derive the wave equations in layered partially saturated pore-crack media considering multi-scale WIFF. • The frequency-dependent velocity and attenuation are analyzed in wide frequency bands based on the wave equations. • The dispersion and attenuation show fair correspondence with previously known theories and laboratory measurement data. [ABSTRACT FROM AUTHOR]

Existing end-to-end speech recognition methods typically employ hybrid decoders based on CTC and Transformer. However, the issue of error accumulation in these hybrid decoders hinders further improvements in accuracy. Additionally, most existing models are built upon Transformer architecture, which tends to be complex and unfriendly to small datasets. Hence, we propose a Nonlinear Regularization Decoding Method for Speech Recognition. Firstly, we introduce the nonlinear Transformer decoder, breaking away from traditional left-to-right or right-to-left decoding orders and enabling associations between any characters, mitigating the limitations of Transformer architectures on small datasets. Secondly, we propose a novel regularization attention module to optimize the attention score matrix, reducing the impact of early errors on later outputs. Finally, we introduce the tiny model to address the challenge of overly large model parameters. The experimental results indicate that our model demonstrates good performance. Compared to the baseline, our model achieves recognition improvements of 0.12%, 0.54%, 0.51%, and 1.2% on the Aishell1, Primewords, Free ST Chinese Corpus, and Common Voice 16.1 datasets of Uyghur, respectively. [ABSTRACT FROM AUTHOR]

Background: Numerous studies have developed or validated prediction models aimed at estimating the likelihood of amputation in diabetic foot (DF) patients. However, the quality and applicability of these models in clinical practice and future research remain uncertain. This study conducts a systematic review and assessment of the risk of bias and applicability of amputation prediction models among individuals with DF. Methods: A comprehensive search was conducted across multiple databases, including PubMed, Web of Science, EBSCO CINAHL Plus, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang, Chinese Biomedical Literature Database (CBM), and Weipu (VIP) from their inception to December 24, 2023. Two investigators independently screened the literature and extracted data using the checklist for critical appraisal and data extraction for systematic reviews of prediction modeling studies. The Prediction Model Risk of Bias Assessment Tool (PROBAST) checklist was employed to evaluate both the risk of bias and applicability. Results: A total of 20 studies were included in this analysis, comprising 17 development studies and three validation studies, encompassing 20 prediction models and 11 classification systems. The incidence of amputation in patients with DF ranged from 5.9 to 58.5%. Machine learning-based methods were employed in more than half of the studies. The reported area under the curve (AUC) varied from 0.560 to 0.939. Independent predictors consistently identified by multivariate models included age, gender, HbA1c, hemoglobin, white blood cell count, low-density lipoprotein cholesterol, diabetes duration, and Wagner's Classification. All studies were found to exhibit a high risk of bias, primarily attributed to inadequate handling of outcome events and missing data, lack of model performance assessment, and overfitting. Conclusions: The assessment using PROBAST revealed a notable risk of bias in the existing prediction models for amputation in patients with DF. It is imperative for future studies to concentrate on enhancing the robustness of current prediction models or constructing new models with stringent methodologies. [ABSTRACT FROM AUTHOR]

Left hemisphere injury can cause right spastic arm paralysis and aphasia, and recovery of both motor and language functions shares similar compensatory mechanisms and processes. Contralateral cervical seventh cross transfer (CC7) surgery can provide motor recovery for spastic arm paralysis by triggering interhemispheric plasticity, and self‐reports from patients indicate spontaneous improvement in language function but still need to be verified. To explore the improvements in motor and language function after CC7 surgery, we performed this prospective observational cohort study. The Upper Extremity part of Fugl‐Meyer scale (UEFM) and Modified Ashworth Scale were used to evaluate motor function, and Aphasia Quotient calculated by Mandarin version of the Western Aphasia Battery (WAB‐AQ, larger score indicates better language function) was assessed for language function. In 20 patients included, the average scores of UEFM increased by .40 and 3.70 points from baseline to 1‐week and 6‐month post‐surgery, respectively. The spasticity of the elbow and fingers decreased significantly at 1‐week post‐surgery, although partially recurred at 6‐month follow‐up. The average scores of WAB‐AQ were increased by 9.14 and 10.69 points at 1‐week and 6‐month post‐surgery (P < .001 for both), respectively. Post‐surgical fMRI scans revealed increased activity in the bilateral hemispheres related to language centrals, including the right precentral cortex and right gyrus rectus. These findings suggest that CC7 surgery not only enhances motor function but may also improve the aphasia quotient in patients with right arm paralysis and aphasia due to left hemisphere injuries. [ABSTRACT FROM AUTHOR]

SUMMARY: Mung bean (Vigna radiata) stands as a crucial legume crop in Asia, contributing to food security. However, our understanding of the underlying genetic foundation governing domesticated agronomic traits, especially those linked to pod architecture, remains largely unexplored. In this study, we delved into the genomic divergence between wild and domesticated mung bean varieties, leveraging germplasm obtained from diverse sources. Our findings unveiled pronounced variation in promoter regions (35%) between the two mung bean subpopulations, suggesting substantial changes in gene expression patterns during domestication. Leveraging transcriptome analysis using distinct reproductive stage pods and subpopulations, we identified candidate genes responsible for pod and seed architecture development, along with Genome‐Wide Association Studies (GWAS) and Quantitative Trait Locus (QTL) analysis. Notably, our research conclusively confirmed PDH1 as a parallel domesticated gene governing pod dehiscence in legumes. This study imparts valuable insights into the genetic underpinnings of domesticated agronomic traits in mung bean, and simultaneously highlighting the parallel domestication of pivotal traits within the realm of legume crops. Significance Statement: This study elucidates the genetic mechanisms underpinning pod development traits in mung bean, a key crop in Asian agriculture. By focusing on the PDH1 gene, our research reveals its pivotal role in pod dehiscence and contributes to the broader understanding of parallel domestication processes in legumes, providing valuable insights for future crop improvement strategies. [ABSTRACT FROM AUTHOR]

Background: Obesity, insulin resistance, and hyperandrogenemia are commonly seen in women with polycystic ovary syndrome (PCOS), and these three conditions form a vicious cycle leading to reproductive and metabolic abnormalities. Metformin improves the symptoms of PCOS by increasing insulin sensitivity but is not therapeutically optimal. Recent studies have reported that sodium-glucose co-transporter protein receptor inhibitors improve insulin resistance and reduce the weight of patients with PCOS. We performed a meta-analysis to assess the influence of sodium-glucose co-transporter protein-2 (SGLT2) inhibitors on anthropometric, glycolipid metabolism and reproductive outcomes after therapy of overweight/obese women with PCOS. Methods: We searched the relevant literature published up to April 2023. Information on the effect of SGLT2 inhibitors on overweight/obese patients with PCOS was extracted independently by two reviewers. Review Manager 5.3 was used for meta-analysis. Results: Five randomized controlled trials that met our criteria were retrieved. Our meta-analysis demonstrated that in overweight/obese patients with PCOS, SGLT2 inhibitors treatment was significantly superior to metformin treatment in terms of reducing body weight (P = 0.02, I2 = 36%), decreasing dehydroepiandrosterone sulfate concentrations [SMD = -0.42, 95% CI (-0.76, -0.07), I2 = 22%, P = 0.02], and reducing the incidence of nausea [RR = 0.35, 95% CI (0.21, 0.60), I2 = 71%, P = 0.0001]. Conclusions: SGLT2 inhibitors are a possible alternative therapy for treating overweight/obese women with PCOS who do not respond favorably to metformin treatment. However, further large randomized controlled trials and cost-effectiveness analyses are warranted to guide the implementation of SGLT2 inhibitors treatment in this population. [ABSTRACT FROM AUTHOR]

Sentiment analysis is the processing of textual data and giving positive or negative opinions to sentences. In the ABSA dataset, most sentences contain one aspect of sentiment polarity, or sentences of one aspect have multiple identical sentiment polarities, which weakens the sentiment polarity of the ABSA dataset. Therefore, this paper uses the SemEval 14 Restaurant Review dataset, in which each document is symmetrically divided into individual sentences, and two versions of the datasets ATSA and ACSA are created. ATSA: Aspect Term Sentiment Analysis Dataset. ACSA: Aspect Category Sentiment Analysis Dataset. In order to symmetrically simulate the complex relationship between aspect contexts and accurately extract the polarity of emotional features, this paper combines the latest development trend of NLP, combines capsule network and BRET, and proposes the baseline model CapsNet-BERT. The experimental results verify the effectiveness of the model. [ABSTRACT FROM AUTHOR]

A variety of resources such as geothermal, mineral, groundwater, oil and gas, etc., are explored in the volcanic rock reservoirs, which has aroused widespread focus in the world. The researches on the relationship between macroscopic physical properties and microstructures are conducive to the resource exploration and development, in which the rock-physics model is an important and valid media. Taking the Junggar Basin in Western China as an example, a novel rock-physics model for volcanic rocks is proposed. The mineral contents are initially estimated with the proposed evolutionary complex algorithm based on a novel volume interpretation model suitable for the diversity of the minerals of different lithology. The simultaneous inversion of the porosity and aspect ratio of different kinds of pores constrained by the P-wave and S-wave velocities is further implemented and then the heterogeneity of the rock can be carved. In addition, to satisfy the hypothesis of the fluid saturation model, the disconnected pores including bound water and invalid pass are introduced by the acoustic porosity formula as a part of the matrix. Furthermore, due to the approximate aligned cracks, the volcanic rock reservoirs can be simplified as transversely isotropic media with horizontal symmetry axis. The Eshelby-Cheng model and Brown-Korringa theory are further utilized for the estimation of the elastic modulus of the anisotropic dry rock and saturated rock, respectively. The example demonstrates that the proposed rock-physics model is able to predict the elastic parameters of different lithology of volcanic rocks and the modelling method can give some enlightenment for the exploration of other volcanic resources. • Propose an evolutionary complex algorithm based on a novel volume interpretation model for different volcanic lithology. •The pore parameters such as the disconnected porosity, the porosities and aspect ratios of different pores are estimated. •A novel rock-physics model for volcanic rocks is proposed, in which the heterogeneity and anisotropy are considered. •The rock-physics model can be used to estimate the elastic modulus such as velocity with the relative error less than 10%. [ABSTRACT FROM AUTHOR]

Background: The novel distal radial artery (dRA) approach is a popular arterial access route for interventional cardiology and neurointerventions. We explored the dRA as an alternative site to the classic forearm radial artery (RA) for perioperative blood pressure monitoring. We hypothesized that dRA catheterization is noninferior to RA for the first attempt success rate. Methods: This was a single-center, prospective, randomized controlled, noninferiority study. Adult patients who underwent elective surgery at the Jinling Hospital from May 2021 to August 2021 were enrolled. The primary endpoint was to test the noninferiority of the first attempt success rate between the groups. Secondary endpoints included anatomical characteristics, catheterization time, arterial posterior wall puncture rate, postoperative compression time, dampened arterial pressure waveforms, and complications. Results: Totally, 161 patients who received either dRA (n = 81) or RA (n = 80) catheterization were analyzed. The first attempt success rates were 87.7 and 91.3% in the dRA and RA groups, respectively, with a mean difference of − 3.6% (95% CI, − 13.1 to 5.9%). The dRA diameter and cross-sectional area were significantly smaller than those of the RA (P < 0.001). The subcutaneous depth of dRA was significantly greater than that of the RA (P < 0.001). The dRA had a longer catheterization time (P = 0.008) but a shorter postoperative compression time (P < 0.001). The arterial posterior wall puncture rate of dRA was significantly higher than that of the RA (P = 0.006). The dRA had fewer dampened arterial waveforms than RA (P = 0.030) perioperatively. Conclusions: The dRA is a rational alternative approach to RA for perioperative arterial pressure monitoring and provides a noninferior first attempt success rate. Trial registration: This study is registered in the Chinese Clinical Trials Registry (registration number: ChiCTR2100043714, registration date: 27/02/2021). [ABSTRACT FROM AUTHOR]

• Ferrihydrite-Humic acid coprecipitate was prepared through coprecipitation method. • The coprecipitate exhibited good stabilization on cadmium and lead in the soil. • The effect of coprecipitate on soil enzyme activity was discussed. • Coprecipitate treatment has almost no effect on soil physicochemical properties. Heavy metals will accumulate continuously after entering the soil environment, which will adversely affect soil quality and harm to human health through the food chain. Among many soil remediation methods, stabilization methods for applying amendments to soil are widely used because of their higher cost-effectiveness and lower environmental impact. In order to evaluate the actual remediation effect of soil amendments, more means are needed to confirm. In this paper, the effects of Fh-HA (Ferrihydrite-Humic acid) coprecipitate as amendment on soil environmental quality of Cd- and Pb-contaminated soil was evaluated by combining the changes of heavy metals fractionation, TCLP-leachable concentration and soil enzyme activity. The experimental data showed that the Fh-HA coprecipitate could greatly enhance the stabilization of Cd and Pb, and promote its transformation from labile fractions to stable fractions. And coprecipitate could also reduce both the TCLP-leachable Cd and Pb, with the maximum reduction efficiencies of 50.7% and 74.8%, respectively. The activities of urease, catalase and alkaline phosphatase increased up to 62.7%, 50.8% and 38.5%, respectively, at a coprecipitate addition of 10%. At the same time, the soil pH was almost unchanged. The results indicated that the application of Fh-HA coprecipitate amendment has a positive effect on improving the quality of terrestrial environment, and no effect on soil physical and chemical properties. The Fh-HA coprecipitate can be further investigated as an economical and environmentally friendly amendment. [ABSTRACT FROM AUTHOR]

Xylose residue (XR), after diluted acid treatment of corncob, consists of cellulose and lignin. However, structural changes of XR lignin have not been investigated comprehensively, and this has seriously hindered the efficient utilization of lignin. In this study, corncob milled wood lignin (CC MWL), and xylose residue milled wood lignin (XR MWL) were isolated according to the modified milled wood lignin (MWL) method. The structural features of two lignin fractions were thoroughly investigated via fourier transform infrared spectroscopy (FTIR), gel permeation chromatography (GPC), thermogravimetric analysis (TGA) and two dimensional nuclear magnetic resonance (2D NMR) spectroscopy techniques. XR MWL with higher yield and lower bound carbohydrate contents presented more phenolic OH contents than CC MWL due to partial cleavage of β-O-4. Furthermore, the molecular weights of XR MWL were increased, possibly because of condensation of the lignin during the xylose production. A study on antioxidant activity showed that XR lignin had better radical scavenging ability than that of 2,6-Di-tert-butyl-4-methyl-phenol (BHT) and CC MWL. The results suggested that the lignin in xylose residue, showing great antioxidant properties, has potential applications in food additives. [ABSTRACT FROM AUTHOR]

• AEBP1 promotes growth, and migration of PTC cells in vitro and in vivo. • AEBP1 induces epithelial-mesenchymal transition in PTC progression. • BMP4 mediates the biological role of AEBP1 in PTC progression. Papillary thyroid cancer (PTC) is the most prevalent endocrine cancer worldwide. Approximately 30 % of PTC patients will progress into the advanced or metastatic stage and have a relatively poor prognosis. It is well known that epithelial-mesenchymal transition (EMT) plays a pivotal role in thyroid cancer metastasis, resistance to therapy, and recurrence. Clarifying the molecular mechanisms of EMT in PTC progression will help develop the targeted therapy of PTC. The aberrant expression of some transcription factors (TFs) participated in many pathological processes of cancers including EMT. In this study, by performing bioinformatics analysis, adipocyte enhancer-binding protein 1 (AEBP1) was screened as a pivotal TF that promoted EMT and tumor progression in PTC. In vitro experiments indicated that knockout of AEBP1 can inhibit the growth and invasion of PTC cells and reduce the expression of EMT markers including N-cadherin, TWIST1, and ZEB2. In the xenograft model, knockout of AEBP1 inhibited the growth and lung metastasis of PTC cells. By performing RNA-sequencing, dual-luciferase reporter assay, and chromatin immunoprecipitation assay, Bone morphogenetic protein 4 (BMP4) was identified as a downstream target of AEBP1. Over-expression of BMP4 can rescue the inhibitory effects of AEBP1 knockout on the growth, invasion, and EMT phenotype of PTC cells. In conclusion, these findings demonstrated that AEBP1 plays a critical role in PTC progression by regulating BMP4 expression and the AEBP1-BMP4 axis may present novel therapeutic targets for PTC treatment. [Display omitted] [ABSTRACT FROM AUTHOR]

CD36 is a transmembrane glycoprotein, located on surface of numerous cell types. This review is aimed to explore regulatory role of CD36 in hematopoiesis beyond fatty acid uptake. CD36 acts as a pattern recognition receptor, regulates cellular fatty acid homeostasis, and negatively monitors angiogenesis. CD36 also mediates free fatty acid transportation to hematopoietic stem cells in response to infections. During normal physiology and pathophysiology, CD36 significantly participates in the activation and metabolic needs of platelets, macrophages, monocytes, T cells, B cells, and dendritic cells. CD36 has shown a unique relationship with Plasmodium falciparum -infected erythrocytes (Pf IEs) as a beneficiary for both parasite and host. CD36 actively participates in pathogenesis of various hematological cancers as a significant prognostic biomarker including AML, HL, and NHL. CD36-targeting antibodies, CD36 antagonists (small molecules), and CD36 expression inhibitors/modulators are used to target CD36, depicting its therapeutic potential. Many preclinical studies or clinical trials were performed to assess CD36 as a therapeutic target; some are still under investigation. This review reflects the role of CD36 in hematopoiesis which requires more consideration in future research. [Display omitted] [ABSTRACT FROM AUTHOR]

• The proposed joint demand response and dynamic pricing strategies can make the net grid demand curve smoother and have practical significance. • The dynamic pricing strategy helps to realize the joint dispatch of multiple demand response resources in the region and alleviate the grid pressure during peak hours. • A two-layer optimization model is proposed to not only realize the economy of joint operation of multiple energy stations, but also make the net grid demand curve smoother through joint demand response. In recent years, countries around the world have made great efforts to coordinate energy green and low-carbon development and energy supply. In this context, it is of great significance to build energy stations that can greatly absorb renewable energy. The coordinated operation of multi-energy stations in the region can expand the role of energy stations and strengthen energy complementarity between regions. Aiming at the problem of energy interaction and coordinated operation of multi-energy stations in regional integrated energy system, this paper proposes a two-layer scheduling optimization model, which can effectively reduce the system operation cost and carbon emissions. At the same time, considering the joint demand response, it can effectively reduce the peak power supply pressure of the power grid. In addition, in order to ensure the accuracy and efficiency of the solution, this paper improves the traditional NSGA-II algorithm, greatly improving the overall performance of the algorithm. Finally, the simulation analysis is carried out through an example. The results show that the operation optimization model proposed in this paper can effectively reduce the total energy cost of the system, reduce carbon dioxide emissions, and reduce the peak pressure of the power grid. The coordinated operation optimization method is effective and feasible. [ABSTRACT FROM AUTHOR]

Applying a high-voltage electric field to waxy oil can significantly reduce its viscosity near the pour point, and the viscosity recovers gradually after the removal of the electric field. The impact of shear, which is an inevitable occurrence during oil pipeline transportation, on the durability of viscosity reduction remains inadequately explored. In this study, four waxy crude oils were subjected to electric fields with various strengths, and the effect of shear on the viscosity and impedance of treated oils was evaluated. The results revealed that a higher field strength promotes the accumulation of more colloidal particles (asphaltenes and resins) on wax particle surfaces, resulting in longer maintenance of viscosity reduction. Shear exhibited a contrasting impact on electrically-treated oils' viscosity: it hastened the disappearance of the modification effect of oils with low liquid phase viscosity and small colloidal particle size, but preserved the viscosity reduction of oils with high liquid phase viscosity and large colloidal particle size. Further investigation revealed that shear disrupted the interconnection between colloidal particles and wax particles, and promoted the collision and adhesion of free-moving colloidal particles with wax particles. The competition between these two effects determined the effect of shear on the viscosity of treated oils. • Higher field strength resulted in a longer maintenance of viscosity reduction. • Shear exhibited a contrasting impact on the viscosity of electrically-treated oils. • The state of charged colloidal particles under shear determined the shear effect. [ABSTRACT FROM AUTHOR]

Background: Systemic lupus erythematosus (SLE) is a complex systemic autoimmune disease characterized by the presence of numerous autoantibodies. The interaction of infectious agents (viruses, bacteria and parasites) and a genetically susceptible host may be a key mechanism for SLE. Toxoplasma gondii is a widespread intracellular parasite that has been implicated in the pathogenesis of autoimmune diseases. However, the relationship between T. gondii infection and the increased risk of SLE in Chinese populations remains unclear. Methods: The seroprevalence of T. gondii infection was assessed in 1771 serum samples collected from Chinese individuals (908 healthy controls and 863 SLE patients) from different regions of China using an enzyme-linked immunosorbent assay. Serum autoantibodies and clinical information were obtained and analysed. Results: Our observations revealed a higher prevalence of anti-T. gondii antibodies (ATxA) immunoglobulin G (IgG) in serum samples from SLE patients (144/863, 16.7%) than in those from the healthy controls (53/917, 5.8%; P < 0.0001), indicating a 2.48-fold increased risk of SLE in the ATxA-IgG+ population, after adjustment for age and sex (95% confidence interval [CI] 1.70–3.62, P < 0.0001). ATxA-IgG+ SLE patients also showed a 1.75-fold higher risk of developing moderate and severe lupus symptoms (95% CI 1.14–2.70, P = 0.011) compared to ATxA-IgG− patients. Relative to ATxA-IgG− patients, ATxA-IgG+ patients were more likely to develop specific clinical symptoms, including discoid rash, oral ulcer, myalgia and alopecia. Seven antibodies, namely anti-ribosomal RNA protein (rRNP), anti-double stranded DNA (dsDNA), anti-cell membrane DNA (cmDNA), anti-scleroderma-70 (Scl-70), anti-cardiolipin (CL), anti-beta2-glycoprotein-I (B2GPI) and rheumatoid factor (RF), occurred more frequently in ATxA-IgG+ patients. When combined with anti-dsDNA and RF/anti-rRNP/anti-cmDNA/ESR, ATxA-IgG significantly increased the risk for severe lupus. Conclusions: Our results suggest that ATxA-IgG may be a significant risk factor for SLE prevalence and severity in Chinese populations. [ABSTRACT FROM AUTHOR]

As a rare disease leading to male infertility, idiopathic hypogonadotropic hypogonadism (IHH) has strong heterogeneity of clinical phenotype and gene mutation. At present, there is no effective diagnosis and treatment method for this disease. This study is to explore the possible new pathogenic gene of idiopathic hypogonadotrophic hypogonadism and the pathological mechanism affecting its occurrence. We performed a whole-exome sequencing on 9 patients with normosmic idiopathic hypogonadotropic hypogonadism (nIHH), 19 varicocele patients with asthenospermia, oligospermia, or azoospermia, 5 patients with simple nonobstructive azoospermia, and 13 normal healthy adult males and carried out comparative analysis, channel analysis, etc. After preliminary sequencing screening, 309–431 genes harbouring variants, including SNPs and indels, were predicted to be harmful per single patient in each group. In genetic variations of nIHH patients' analysis, variants were detected in 10 loci and nine genes in nine patients. And in co-analysis of the three patient groups, nine nIHH patients, 19 VC patients, and five SN patients shared 116 variants, with 28 variant-harbouring genes detected in five or more patients. We found that the NEFH, CCDC177, and PCLO genes and the Gene Ontology pathways GO:0051301: cell division and GO:0090066: regulation of anatomical structure size may be key factors in the pathogenic mechanism of IHH. Our results suggest that the pathogenic mechanism of IHH is not limited to the central nervous system effects of GnRH but may involve other heterogeneous pathogenic genetic variants that affect peripheral organs. [ABSTRACT FROM AUTHOR]

Follicle-stimulating hormone (FSH) has been newly demonstrated to play a great role in promoting fat accumulation, providing a potential to target FSH for controlling fat accumulation and treating obesity. A short, 13-amino acid of FSHβ (FSHβ13AA) was indentified to be the FSH receptor-binding epitope in both humans and mice. By conservation analysis, we found such FSHβ13AA is highly conserved across species. Accordingly, we designed a new FSH antigen by synthesizing a tandem of FSHβ13AA (LVYKDPARPNIQK) and then conjugating it to ovalbumin (FSHβ13AA-T-OVA). Then, we tested its efficacy in suppressing fat accumulation in both ovariectomized and intact mouse models. Vaccination with this novel antigen emulsified in mild adjuvant, Specol, was highly effective in preventing ovariectomy-induced body weight gain and fat accumulation in mice (P < 0.01). Mechanistically, FSH vaccination treatment inhibited lipid biosynthesis by inactivating PPARγ adipogenic signaling pathway and simultaneously enhanced adipocyte themogenesis via upregulating UCP1 expression in both visceral and subcutaneous adipose tissues. Moreover, injection of this novel FSH vaccine also substantially reduced (P < 0.05) fat accumulation in both intact male and female mice. These actions result from the specific binding of the generated antibody to the β-subunit to block its action, rather than lowering the circulating levels of FSH, as evidenced by nearly no alterations in serum FSH levels in mice following FSH vaccination. Overall, we developed a novel FSH antigen and vaccine, and demonstrated it is highly efficacious in suppressing fat accumulation. • A novel FSH vaccine was developed based on the FSH receptor-binding epitope of FSH β-subunit. • Vaccination with this vaccine was highly effective in preventing ovariectomy-induced fat accumulation in mice. • Vaccination with this vaccine was also highly effective in preventing fat accumulation in intact mice fed on normal chow. • FSH vaccination suppresses fat accumulation through inactivating PPARγ and upregulating UCP1 signaling in adipose tissues. [ABSTRACT FROM AUTHOR]

Simple Summary: Depression is a significant public health problem, and its pathogenesis is associated with inflammation in the central nervous system. In this study, we investigated the effects of H2S donor NaHS treatment on depression-like behavior caused by lipopolysaccharide (LPS) and its potential mechanisms. It was found that H2S treatment prevented LPS-induced depression-like behavior. LPS resulted in NF-κB and NLRP3 inflammasome activation and pyroptosis in the hippocampus and led to hippocampal mitochondrial dysfunction, which could be reversed with H2S treatment. Our data indicate that H2S prevents LPS-induced depression-like behaviors via the inhibition of neuroinflammation and pyroptosis and improving mitochondrial function. H2S could be a promising therapeutic reagent for depression. Hydrogen sulfide (H2S) has been implicated to have antidepressive effects. We sought to investigate the prevention effects of H2S donor NaHS on depression-like behavior induced by lipopolysaccharide (LPS) in mice and its potential mechanisms. Sucrose preference, force swimming, open field, and elevate zero maze were used to evaluate depression-like behavior. NF-κB and NLRP3 inflammasome activation and mitochondrial function in the hippocampus were determined. It was found that depression-like behavior induced by LPS was prevented by NaHS pretreatment. LPS caused NF-κB and NLRP3 inflammasome activation in the hippocampus as evidenced by increased phosphorylated-p65 levels and increased NLRP3, ASC, caspase-1, and mature IL-1β levels in the hippocampus, which were also blocked by NaHS. LPS increased GSDMD-N levels and TUNEL-positive cells in the hippocampus, which was prevented by NaHS. Abnormal mitochondrial morphology in the hippocampus was found in LPS-treated mice. Mitochondrial membrane potential and ATP production were reduced, and ROS production was increased in the hippocampus of LPS-treated mice. NaHS pretreatment improved impaired mitochondrial morphology and increased membrane potential and ATP production and reduced ROS production in the hippocampus of LPS-treated mice. Our data indicate that H2S prevents LPS-induced depression-like behaviors by inhibiting NLRP3 inflammasome activation and pyroptosis and improving mitochondrial function in the hippocampus. [ABSTRACT FROM AUTHOR]

[Display omitted] Wax molecules crystallize at ambient temperature, causing the crude oil to become a dispersed system, which poses challenges in the flow assurance of pipelines. Improving the cold flowability of crude oil is the fundamental solution to tackle these problems. Applying an electric field to waxy oil may markedly improve its cold flowability. The adhesion of charged particles on wax particles' surface under the electric field has been demonstrated as the essential mechanism of the electrorheological effect. However, the correlation between the accumulated charged particles and the induced viscosity reduction has not been explored quantitatively. In this study, the viscosity and impedance of four crude oils before and after electric treatment were measured. The conductivity changes of the oils' continuous phase were obtained by an equivalent circuit model. And then, the charged particles' concentration before and after electric treatment was calculated by the Stokes equation. The results showed there is a positive correlation between viscosity reduction and charged particle concentration reduction in the continuous phase. Importantly, this correlation is also quantitatively applicable to the results of ten different waxy oils which has been published. This study provides a quantitative basis for the mechanism of electrorheological behavior of waxy oils. [ABSTRACT FROM AUTHOR]

The antibacterial activity and mechanism of monolauroyl-galactosylglycerol (MLGG) against Bacillus cereus were investigated. The minimum inhibitory concentration of MLGG against B. cereus was 0.156 mg/ml. The inhibition growth curve assay also revealed that MLGG presented good antibacterial activity against B. cereus. Alkaline phosphatase activity assay, nucleotide leakage and cell viability analysis demonstrated that MLGG disrupted the integrity of cell wall and cell membrane of B. cereu s. Scanning electron microscopy and transmission electron microscopy results showed obvious morphological and ultrastructural changes of B. cereu s membrane, further confirming the damage of cell membrane integrity caused by MLGG. In summary, MLGG might exerted its antibacterial activity mainly by an action mode of membrane disruption, and it was expected to be an alternative for the development of new food preservatives. [ABSTRACT FROM AUTHOR]

There is a growing interest in scene text detection for arbitrary shapes. The effectiveness of text detection has also evolved from horizontal text detection to the ability to perform text detection in multiple directions and arbitrary shapes. However, scene text detection is still a challenging task due to significant differences in size and aspect ratio and diversity in shape, as well as orientation, coarse annotations, and other factors. Regression-based methods are inspired by object detection and have limitations in fitting the edges of arbitrarily shaped text due to the characteristics of their methods. Segmentation-based methods, on the other hand, perform prediction at the pixel level and thus can fit arbitrarily shaped text better. However, the inaccuracy of image text annotations and the distribution characteristics of text pixels, which contain a large number of background pixels and misclassified pixels, degrades the performance of segmentation-based text detection methods to some extent. Usually, considering whether a pixel belongs to a text region is highly dependent on the strength of the semantic information it has and the position of the pixel in the text area. Based on the above two points, we propose an innovative and robust method for scene text detection combining position and semantic information. First, we add position information to the images using a position encoding module (PosEM) to help the model learn the implicit feature relationships associated with the position. Second, we use the semantic enhancement module (SEM) to enhance the model's focus on the semantic information in the image during feature extraction. Then, to minimize the effect of noise due to inaccurate image text annotations and the distribution characteristics of text pixels, we convert the detection results into a probability map that can more reasonably represent the text distribution. Finally, we reconstruct and filter the text instances using a post-processing algorithm to reduce false positives. The experimental results show that our model improves significantly on the Total-Text, MSRA-TD500, and CTW1500 datasets, outperforming most previous advanced algorithms. [ABSTRACT FROM AUTHOR]

The segmentation-based scene text detection algorithm has advantages in scene text detection scenarios with arbitrary shape and extreme aspect ratio, depending on its pixel-level description and fine post-processing. However, the insufficient use of semantic and spatial information in the network limits the classification and positioning capabilities of the network. Existing scene text detection methods have the problem of losing important feature information in the process of extracting features from each network layer. To solve this problem, the Attention-based Dual Feature Fusion Model (ADFM) is proposed. The Bi-directional Feature Fusion Pyramid Module (BFM) first adds stronger semantic information to the higher-resolution feature maps through a top-down process and then reduces the aliasing effects generated by the previous process through a bottom-up process to enhance the representation of multi-scale text semantic information. Meanwhile, a position-sensitive Spatial Attention Module (SAM) is introduced in the intermediate process of two-stage feature fusion. It focuses on the one feature map with the highest resolution and strongest semantic features generated in the top-down process and weighs the spatial position weight by the relevance of text features, thus improving the sensitivity of the text detection network to text regions. The effectiveness of each module of ADFM was verified by ablation experiments and the model was compared with recent scene text detection methods on several publicly available datasets. [ABSTRACT FROM AUTHOR]