Text-Only Image Captioning with Multi-Context Data Generation

Text-only Image Captioning (TIC) is an approach that aims to construct a model solely based on text that can accurately describe images. Recently, diffusion models have demonstrated remarkable capabilities in generating high-quality images that are semantically coherent with given texts. This presents an opportunity to generate synthetic training images for TIC. However, we have identified a challenge that the images generated from simple descriptions typically exhibit a single perspective with one or limited contexts, which is not aligned with the complexity of real-world scenes in the image domain. In this paper, we propose a novel framework that addresses this issue by introducing multi-context data generation. Starting with an initial text corpus, our framework employs a large language model to select multiple sentences that describe the same scene from various perspectives. These sentences are then summarized into a single sentence with multiple contexts. We generate simple images using the straightforward sentences and complex images using the summarized sentences through diffusion models. Finally, we train the model exclusively using the synthetic image-text pairs obtained from this process. Experimental results demonstrate that our proposed framework effectively tackles the central challenge we have identified, achieving the state-of-the-art performance on popular datasets such as MSCOCO, Flickr30k, and SS1M

MiR-650 represses high-risk non-metastatic colorectal cancer progression via inhibition of AKT2/GSK3β/E-cadherin pathway

Although 5-year survival rate of non-metastatic colorectal cancer (CRC) is high, about 10% of patients in stage I and II still develop into metastatic CRC and eventually die after resection. Currently, there is no effective biomarker for predicting the prognosis of non-metastatic CRC in clinical practice. In this study, we identified miR-650 as a biomarker for prognosis prediction. We observed that the expression of miR-650 in tumor tissues had a positive association with overall survival. MiR-650 inhibited cell growth and invasion in vitro and in vivo. Furthermore, miR-650 targeted AKT2 and repressed the activation of the AKT pathway (AKT2/GSK3β/E-cadherin). Thus it induced the translocation of E-cadherin and β-catenin in cancer cells. Our results highlight the potential of miR-650 as a prognostic prediction biomarker and therapeutic target in non-metastatic CRC via inhibition of the AKT2/GSK3β/E-cadherin pathway

Application fruit tree hole storage brick fertilizer is beneficial to increase the nitrogen utilization of grape under subsurface drip irrigation

It is very important to promote plant growth and decrease the nitrogen leaching in soil, to improve nitrogen (N) utilization efficiency. In this experiment, we designed a new fertilization strategy, fruit tree hole storage brick (FTHSB) application under subsurface drip irrigation, to characterise the effects of FTHSB addition on N absorption and utilization in grapes. Three treatments were set in this study, including subsurface drip irrigation (CK) control, fruit tree hole storage brick A (T1) treatment, and fruit tree hole storage brick B (T2) treatment. Results showed that the pore number and size of FTHSB A were significantly higher than FTHSB B. Compared with CK, T1 and T2 treatments significantly increased the biomass of different organs of grape, N utilization and 15N content in the roots, stems and leaves, along with more prominent promotion at T1 treatment. When the soil depth was 15–30 cm, the FTHSB application significantly increased the soil 15N content. But when the soil depth was 30–45 cm, it reduced the soil 15N content greatly. T1 and T2 treatments obviously increased the activities of nitrite reductase (NR) and glutamine synthetase (GS) in grape leaves, also the urease activity(UR) in 30 cm of soil. Our findings suggest that FTHSB promoted plant N utilization by reducing N loss in soil and increasing the enzyme activity related to nitrogen metabolism. In addition, this study showed that FTHSB A application was more effective than FTHSB B in improving nitrogen utilization in grapes

Dynamical alterations of brain function and gut microbiome in weight loss

ObjectiveIntermittent energy restriction (IER) is an effective weight loss strategy. However, little is known about the dynamic effects of IER on the brain-gut-microbiome axis.MethodsIn this study, a total of 25 obese individuals successfully lost weight after a 2-month IER intervention. FMRI was used to determine the activity of brain regions. Metagenomic sequencing was performed to identify differentially abundant gut microbes and pathways in from fecal samples.ResultsOur results showed that IER longitudinally reduced the activity of obese-related brain regions at different timepoints, including the inferior frontal orbital gyrus in the cognitive control circuit, the putamen in the emotion and learning circuit, and the anterior cingulate cortex in the sensory circuit. IER longitudinally reduced E. coli abundance across multiple timepoints while elevating the abundance of obesity-related Faecalibacterium prausnitzii, Parabacteroides distasonis, and Bacterokles uniformis. Correlation analysis revealed longitudinally correlations between gut bacteria abundance alterations and brain activity changes.ConclusionsThere was dynamical alteration of BGM axis (the communication of E. coli with specific brain regions) during the weight loss under the IER

Parameter calibration of the discrete element simulation model for soaking paddy loam soil based on the slump test.

The discrete element computer simulation method is an effective tool that enables the study of the interaction mechanism between the pulping components and the paddy soil during the paddy field pulping process. The findings are valuable in optimizing the parameters of the paddy beating device to improve its working quality and efficiency. However, the lack of accurate soil models for paddy soil has limited the application and development of the discrete element method in paddy pulping research. This study selected the Hertz-Mindlin with Johnson-Kendall-Roberts discrete element model for the pre-pulping paddy loam soil and used the slump error as the test index to select nine parameters, including soil Poisson's ratio and surface energy, as test factors to calibrate the model parameters. The Plackett-Burman test identified soil shear modulus, surface energy, and soil-iron plate static friction coefficient as significant factors affecting the test index. The steepest ascent test results determined the test range of the above parameters. The Box-Behnken test obtained the regression model between the significant factors and the test index, and the regression model was optimized using the slump error as the target. The optimal combination of parameters was surface energy of 3.257 J/m2, soil shear modulus of 0.709 MPa, and static friction coefficient between soil and iron plate of 0.701. The slump simulation test using this combination of parameters yielded an average slump error of 2.04%. The collective results indicate the accuracy of the calibrated discrete element simulation parameters for paddy loam soil. These parameters can be used for discrete element simulation analysis of the paddy pulping process after paddy field soaking

CNTR-YOLO: Improved YOLOv5 Based on ConvNext and Transformer for Aircraft Detection in Remote Sensing Images

Aircraft detection in remote sensing images is an important branch of target detection due to the military value of aircraft. However, the diverse categories of aircraft and the intricate background of remote sensing images often lead to insufficient detection accuracy. Here, we present the CNTR-YOLO algorithm based on YOLOv5 as a solution to this issue. The CNTR-YOLO algorithm improves detection accuracy through three primary strategies. (1) We deploy DenseNet in the backbone to address the vanishing gradient problem during training and enhance the extraction of fundamental information. (2) The CBAM attention mechanism is integrated into the neck to minimize background noise interference. (3) The C3CNTR module is designed based on ConvNext and Transformer to clarify the target’s position in the feature map from both local and global perspectives. This module is applied before the prediction head to optimize the accuracy of prediction results. Our proposed algorithm is validated on the MAR20 and DOTA datasets. The results on the MAR20 dataset show that the mean average precision (mAP) of CNTR-YOLO reached 70.1%, which is a 3.3% improvement compared with YOLOv5l. On the DOTA dataset, the results indicate that the mAP of CNTR-YOLO reached 63.7%, which is 2.5% higher than YOLOv5l

Assessing the Credit Risk of Corporate Bonds Based on Factor Analysis and Logistic Regress Analysis Techniques: Evidence from New Energy Enterprises in China

In recent years, new energy sources have ushered in tremendous opportunities for development. The difficulties to finance new energy enterprises (NEEs) can be estimated through issuing corporate bonds. However, there are few scientific and reasonable methods to assess the credit risk of NEE bonds, which is not conducive to the healthy development of NEEs. Based on this, this paper analyzes the advantages and risks of NEEs issuing bonds and the main factors affecting the credit risk of NEE bonds, constructs a hybrid model for assessing the credit risk of NEE bonds based on factor analysis and logistic regress analysis techniques, and verifies the applicability and effectiveness of the model employing relevant data from 46 Chinese NEEs. The results show that the main factors affecting the credit risk of NEE bonds are internal factors involving the company’s profitability, solvency, operational ability, growth potential, asset structure and viability, and external factors including macroeconomic environment and energy policy support. Based on the empirical results and the exact situation of China’s NEE bonds, this article finally puts forward several targeted recommendations

Dietary, Nutrient Patterns and Blood Essential Elements in Chinese Children with ADHD

Dietary or nutrient patterns represent the combined effects of foods or nutrients, and elucidate efficaciously the impact of diet on diseases. Because the pharmacotherapy on attention deficit hyperactivity disorder (ADHD) was reported be associated with certain side effects, and the etiology of ADHD is multifactorial, this study investigated the association of dietary and nutrient patterns with the risk of ADHD. We conducted a case-control study with 592 Chinese children including ADHD (n = 296) and non-ADHD (n = 296) aged 6–14 years old, matched by age and sex. Dietary and nutrient patterns were identified using factor analysis and a food frequency questionnaire. Blood essential elements levels were measured using atomic absorption spectrometry. A fish-white meat dietary pattern rich in shellfish, deep water fish, white meat, freshwater fish, organ meat and fungi and algae was inversely associated with ADHD (p = 0.006). Further analysis found that a mineral-protein nutrient pattern rich in zinc, protein, phosphorus, selenium, calcium and riboflavin was inversely associated with ADHD (p = 0.014). Additionally, the blood zinc was also negatively related to ADHD (p = 0.003). In conclusion, the fish-white meat dietary pattern and mineral-protein nutrient pattern may have beneficial effects on ADHD in Chinese children, and blood zinc may be helpful in distinguishing ADHD in Chinese children

Characterization of char from high temperature fluidized bed coal pyrolysis in complex atmospheres

The physiochemical properties of chars produced by coal pyrolysis in a laboratory-scale fluidized bed reactor with a continuous coal feed and char discharge at temperatures of 750 to 980 degrees C under N-2-based atmospheres containing O-2, H-2, CO, CH4, and CO2 were studied. The specific surface area of the char was found to decrease with increasing pyrolysis temperature. The interlayer spacing of the char also decreased, while the average stacking height and carbon crystal size increased at higher temperatures, suggesting that the char generated at high temperatures had a highly ordered structure. The char obtained using an ER value of 0.064 exhibited the highest specific surface area and oxidation reactivity. Relatively high O-2 concentrations degraded the pore structure of the char, decreasing the surface area. The char produced in an atmosphere incorporating H-2 showed a more condensed crystalline structure and consequently had lower oxidation reactivity. (C) 2015 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.orgilicenses/by-nc-nd/4.0/).</p