Robustness and discrimination are two of the most important objectives in image hashing. We incorporate ring partition and invariant vector distance to image hashing algorithm for enhancing rotation ...robustness and discriminative capability. As ring partition is unrelated to image rotation, the statistical features that are extracted from image rings in perceptually uniform color space, i.e., CIE L*a*b* color space, are rotation invariant and stable. In particular, the Euclidean distance between vectors of these perceptual features is invariant to commonly used digital operations to images (e.g., JPEG compression, gamma correction, and brightness/contrast adjustment), which helps in making image hash compact and discriminative. We conduct experiments to evaluate the efficiency with 250 color images, and demonstrate that the proposed hashing algorithm is robust at commonly used digital operations to images. In addition, with the receiver operating characteristics curve, we illustrate that our hashing is much better than the existing popular hashing algorithms at robustness and discrimination.
The chemical and pore structures of coal play a crucial role in determining the content of free gas in coal reservoirs. This study focuses on investigating the impact of acidification transformation ...on the micro-physical and chemical structure characteristics of coal samples collected from Wenjiaba No. 1 Mine in Guizhou. The research involves a semi-quantitative analysis of the chemical structure parameters and crystal structure of coal samples before and after acidification using Fourier Transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) experiments. Additionally, the evolution characteristics of the pore structure are characterized through high-pressure mercury injection (HP-MIP), low-temperature nitrogen adsorption (LT-N2A), and scanning electron microscopy (SEM). The experimental findings reveal that the acid solution modifies the structural features of coal samples, weakening certain vibrational structures and altering the chemical composition. Specifically, the asymmetric vibration structure of aliphatic CH2, the asymmetric vibration of aliphatic CH3, and the symmetric vibration of CH2 are affected. This leads to a decrease in the contents of -OH and -NH functional groups while increasing aromatic structures. The crystal structure of coal samples primarily dissolves transversely after acidification, affecting intergranular spacing and average height. Acid treatment corrodes mineral particles within coal sample cracks, augmenting porosity, average pore diameter, and the ratio of macro-pores to transitional pores. Moreover, acidification increases fracture width and texture, enhancing the connectivity of the fracture structure in coal samples. These findings provide theoretical insights for optimizing coalbed methane (CBM) extraction and gas control strategies.
Abstract As the mechanization of the CBM extraction process advances and geological conditions continuously evolve, the production data from CBM wells is deviating increasingly from linearity, ...thereby presenting a significant challenge in accurately predicting future gas production from these wells. When it comes to predicting the production of CBM, a single deep-learning model can face several drawbacks such as overfitting, gradient explosion, and gradient disappearance. These issues can ultimately result in insufficient prediction accuracy, making it important to carefully consider the limitations of any given model. It’s impressive to see how advanced technology can enhance the prediction accuracy of CBM. In this paper, the use of a CNN model to extract features from CBM well data and combine it with Bi-LSTM and a Multi-Head Attention mechanism to construct a production prediction model for CBM wells—the CNN-BL-MHA model—is fascinating. It is even more exciting that predictions of gas production for experimental wells can be conducted using production data from Wells W1 and W2 as the model’s database. We compared and analyzed the prediction results obtained from the CNN-BL-MHA model we constructed with those from single models like ARIMA, LSTM, MLP, and GRU. The results show that the CNN-BL-MHA model proposed in the study has shown promising results in improving the accuracy of gas production prediction for CBM wells. It’s also impressive that this model demonstrated super stability, which is essential for reliable predictions. Compared to the single deep learning model used in this study, its prediction accuracy can be improved up to 35%, and the prediction results match the actual yield data with lower error.
In distributed cross-domain recommendation systems, current privacy protection techniques are ineffective at verifying data correctness and existing authenticity techniques have limitations in ...privacy protection. This poses a conflict between security and credibility. This paper designs a trusted cross-domain recommendation model based on multi-feature knowledge graph (MuKG) and blockchain to boost recommendation accuracy, data credibility and security. To the best of our knowledge, MuKG is proposed, for the first time, to realize a unified representation of multi-source heterogeneous data in a secure manner. Under this model, federated learning integrated with blockchain is used to implement a co-trust mechanism for distributed learning while guaranteeing the credibility of data through blockchain traceability. Our model can guarantee both data security and authenticity with no need of generalization for privacy protection and coordination of centralized servers for distributed controls. Experiments are performed on the two classic datasets, MovieLens and Amazon, with different sparsity. The results have shown that MuKG improves the recommendation accuracy by 1.5 % and diversity by 18 % while ensuring data security and credibility in sparse data. We also verify that different data characteristics have different influence on the recommendation results.
NEAT1 is an important tumor oncogenic gene in various tumors. Nevertheless, its involvement remains poorly studied in cervical cancer. Our study explored the functional mechanism of NEAT1 in cervical ...cancer. NEAT1 level in several cervical cancer cells was quantified and we found NEAT1 was greatly upregulated in vitro. NEAT1 knockdown inhibited cervical cancer development through repressing cell proliferation, colony formation, capacity of migration, and invasion and also inducing the apoptosis. For another, microRNA (miR)‐133a was downregulated in cervical cancer cells and NEAT1 negatively modulated miR‐133a expression. Subsequently, we validated that miR‐133a functioned as a potential target of NEAT1. Meanwhile, SOX4 is abnormally expressed in various cancers. SOX4 was able to act as a downstream target of miR‐133a and silencing of SOX4 can restrain cervical cancer progression. In addition, in vivo assays were conducted to prove the role of NEAT1/miR‐133a/SOX4 axis in cervical cancer. These findings implied that NEAT1 served as a competing endogenous RNA to sponge miR‐133a and regulate SOX4 in cervical cancer pathogenesis. To sum up, it was implied that NEAT1/miR‐133a/SOX4 axis was involved in cervical cancer development.
We found that NEAT1 served as a competing endogenous RNA to sponge microRNA (miR)‐133a and regulate SOX4 in cervical cancer pathogenesis. To sum up, it was implied that NEAT1/miR‐133a/SOX4 axis was involved in cervical cancer development.
White button mushrooms (
Agaricus bisporus
) were treated with 5 μl L
−1
, 10 μl L
−1
, 20 μl L
−1
, and 50 μl L
−1
peppermint oil and then stored at 4 °C for 8 days to investigate with respect to ...browning and postharvest qualities. It was found that 20 μl L
−1
peppermint oil treatment could provide the best effect on inhibiting browning of fruit bodies. Our results indicated 20 μl L
−1
peppermint oil fumigation restrains browning development and alleviated membrane lipid peroxidation, as reflected by lower electrolyte leakage (17.42%), malondialdehyde (MDA) content (21.95%), and weight loss (1.69%) compared with those of the control mushrooms at 8 days, respectively. In addition, the 20 μl L
−1
peppermint oil fumigation had 1.49-fold and 1.24-fold higher phenolics and flavonoids accumulation respectively than those in control and retained high levels of soluble protein and total sugar at the end of the storage time. Furthermore, peppermint oil treatment significantly improved the antioxidant system, which increased the activity of superoxide dismutase (SOD) and phenylalnine ammonia lyase (PAL), and inhibited the activity of polyphenol oxidase (PPO) and peroxidase (POD), as well as regulated the relative expression levels of genes encoding polyphenol oxidase (
AbPPO1, AbPPO2, AbPPO5, AbPPO6
) and phenylalanine ammonia lyase (
AbPAL1, AbPAL2
) during the storage period. These findings suggest that peppermint oil fumigation is a promising method to control browning and improve the quality of button mushrooms.
Gold nanoparticle/graphene oxide hybrids (AuNP/GO) were easily fabricated by a redox reaction between GO and chloroauric acid without using any additional reductant and then used to stabilize ...Pickering emulsions. Factors affecting the properties of the emulsions were studied, including the HAuCl4/GO mass ratio used to prepare the AuNP/GO, the oil/water ratio, the AuNP/GO concentration, the pH value, and the type and concentration of electrolytes. The emulsions were more stable when stabilized by AuNP/GO made from HAuCl4/GO mass ratios of 0.375–0.5. High pH values and AuNP/GO concentrations that were too high or too low were unfavorable to the stability of the Pickering emulsions. Adding electrolytes to the systems improved the stability of the Pickering emulsions owing to the reduction of repulsive interactions between AuNP/GO sheets. The AuNP/GO stabilized Pickering emulsions were used to prepare AuNP/GO supported polystyrene (PS) microspheres (AuNP/GO@PS) by polymerizing the Pickering emulsion. The catalytic performance of AuNP/GO@PS for the reduction of 4-nitrophenol was then studied.
Decreased postharvest quality is one of the main reasons for the short shelf life of the white button mushroom. The effects of L-arginine on color, weight loss, firmness, electrolyte leakage rate, ...malondialdehyde (MDA) content, PPO activity, PAL activity, SOD activity, POD activity, total phenolic levels, flavonoid amounts, total sugar, and soluble protein amounts in white button mushrooms were assessed during storage at 4 °C for 8 days. The results showed that treatment with 10 mM L-arginine maintained tissue firmness, reduced electrolyte leakage, and delayed browning compared with the control treatment. In addition, 10 mM L-arginine treatment inhibited PPO and PAL activities, while inducing SOD and POD activities. Furthermore, L-arginine treatment increased the accumulation of phenolic substances and flavonoids, while total sugar and soluble protein contents were maintained at high levels throughout the storage period. These findings suggested that 10 mM L-arginine treatment may maintain the quality of the button mushrooms and extend their shelf life.
Numerous studies have demonstrated the impact of beverage consumption on overall health and oral health. Specifically, high consumption of sugar-sweetened beverages and coffee has been associated ...with an increased risk of metabolic disorders and periodontitis. Conversely, high intake of plain water has been linked to various health benefits, including weight management and reduced energy intake. However, no previous studies have explored the potential association between plain water intake and the risk of periodontitis.
Our objective was to investigate the relationship between plain water consumption and periodontitis in a middle-aged and elderly population.
The present cross-sectional study was conducted among participants aged ≥ 45 in the 2009-2014 National Health and Nutrition Examination Surveys. Multivariable regression analysis, subgroup analysis and smooth fitting tests were conducted to explore the independent relationship between plain water intake and periodontitis.
A total of 5,882 participants were enrolled,62.02% have periodontitis. Periodontitis patients have lower plain water intake. The multivariable regression tests showed that the risk of periodontitis decreased with increased plain water intake quartiles (Q4 OR = 0.78; 95%CI 0.62-0.96) after fully adjustment. Subgroup analysis and interaction tests showed that gender, age, smoking, diabetes, hypertension or BMI does not significantly interact with the association. However, the relation was significant in males (Q4 OR = 0.64; 95%CI 0.47-0.86) but not in females (Q4 OR = 0.97;95% CI 0.71-1.31). In the smoothed curve fits stratified by gender, the curve for male participants displayed as a U-shape, with an optimal plain water intake at 1200 ml/day. For males drinking plain water less than 1200 ml/day, the risk of periodontitis decreased by 24% with each increase of 500 ml plain water intake (OR = 0.76, 95%CI 0.66-0.87, p < 0.001).
Together, the results showed that plain water intake is negatively associated with periodontitis risk in US middle aged and elderly population. Further studies are needed to investigate the mechanism unites this association. Attention should be given to adequate plain water intake when considering dietary suggestions to the population at high risk of developing periodontitis, especially for men.
