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The burgeoning field of image generation has captivated academia and industry with its potential to produce high-quality images, facilitating applications like text-to-image conversion, image translation, and recovery. These advancements have notably propelled the growth of the metaverse, where virtual environments constructed from generated images offer new interactive experiences, especially in conjunction with digital libraries. The technology creates detailed high-quality images, enabling immersive experiences. Despite diffusion models showing promise with superior image quality and mode coverage over GANs, their slow training and inference speeds have hindered broader adoption. To counter this, we introduce the Contour Wavelet Diffusion Model, which accelerates the process by decomposing features and employing multi-directional, anisotropic analysis. This model integrates an attention mechanism to focus on high-frequency details and a reconstruction loss function to ensure image consistency and accelerate convergence. The result is a significant reduction in training and inference times without sacrificing image quality, making diffusion models viable for large-scale applications and enhancing their practicality in the evolving digital landscape. • The Contour Wavelet Diffusion Model speeds up the original diffusion model while ensuring the quality of generated images. • The attention module enables effective focus on high-frequency information to improve the quality of image generation. • The model incorporates a reconstruction loss function to ensure the network learns variation consistency. [Display omitted] [ABSTRACT FROM AUTHOR]

• A transform-based feature reconstruction network is designed for missing modalities. • The model reconstructs missing element features to improve the robustness. • Modality-invariant representation is used in missing modalities. • Modality-invariant temporal representation is used to mitigate heterogeneity. • Experimental results show the superior performance of our proposed method. The investigation of missing modalities aims to extract valuable feature information from missing multi-modal data, it is a focal point in multi-modal learning. Existing missing modalities processing methods primarily focused on multi-modal fusion schemes to achieve optimal performance, but they faced the following two key challenges: (1) how to improve the robustness of incomplete multi-modal sequence representation, (2) how to effectively learn modality-invariant representations to mitigate heterogeneity between modalities. In this paper, we propose a m odality- i nvariant t emporal representation learning-based f eature r econstruction net work called MIT-FRNet for the missing modalities to tackle these challenges. In the MIT-FRNet, we first extract the latent features for each modality considering intra-modality and inter-modality, and then introduce an encoder-decoder framework to address the first challenge, it reconstructs missing element features via taking the incomplete modal sequences as input and implementing the inter-modal and cross-modal attention mechanisms for feature extraction. And then, through treating each timestamp as a single Gaussian distribution, we design a fine-grained similarity constraint based on distribution-level modality-invariant representations to learn effective modality-invariant representations, thereby addressing the second challenge. Finally, the efficiency of proposed model is validated through the classification results after multi-modal fusion that involves using a gate encoder to pass it and followed by a vector fusion to fuse it. Extensive experiments on public benchmark datasets demonstrate that the proposed MIT-FRNet method achieves promising results under varying missing rates while exhibiting good convergence. [ABSTRACT FROM AUTHOR]

This research investigated the enhancement of nutritional composition and physicochemical characteristics of highland barley through solid-state fermentation employing three bacterial strains: Lactobacillus acidophilus (LAC), Lactobacillus reuteri and Enterococcus faecalis. The results showed that solid-state fermentation significantly increased the contents of soluble dietary fiber (SDF) and total polyphenol, while decreased the contents of fat, starch and total dietary fiber (TDF) compared to the control (p < 0.05). Additionally, the fermented barley flour exhibited improved water and oil holding capacities. Solid-state fermentation altered the structural integrity of highland barley's whole grain and flour, resulting in finer particles. The physicochemical properties of the whole highland barley grain fermented with LAC showed marked improvement. Homemade highland barley cookies prepared with barley flour fermented by LAC , and enriched with ingredients homologous to both food and medicine, were favored by consumers. They also contained higher levels of protein, TDF and SDF compared to commercial cookies. The study indicated solid-state fermentation as a promising approach to enhance the nutritional value and overall quality of whole-grain foods, facilitating the development of products that were both nutritious and appealing to consumers. [ABSTRACT FROM AUTHOR]

The nano-manipulation approach that combines Focused Ion Beam (FIB) milling and various imaging and probing techniques enables researchers to investigate the cellular structures in three dimensions. Such fusion approach, however, requires extensive effort on locating and examining randomly-distributed targets due to limited Field of View (FOV) when high magnification is desired. In the present study, we present the development that automates ‘pattern and probe’ particularly for single-cell analysis, achieved by computer aided tools including feature recognition and geometric planning algorithms. Scheduling of serial FOVs for imaging and probing of multiple cells was considered as a rectangle covering problem, and optimal or near-optimal solutions were obtained with the heuristics developed. FIB milling was then employed automatically followed by downstream analysis using Atomic Force Microscopy (AFM) to probe the cellular interior. Our strategy was applied to examine bacterial cells ( Klebsiella pneumoniae ) and achieved high efficiency with limited human interference. The developed algorithms can be easily adapted and integrated with different imaging platforms towards high-throughput imaging analysis of single cells. [ABSTRACT FROM AUTHOR]

Electrocatalytic conversion of methane (CH 4) into high-valued liquid products have been studied extensively, yet still limited by their low product yields. Herein, we report the electrocatalytic conversion of CH 4 into CH 3 COOH in HCO 3 --contained electrolyte. By optimizing the surface-active sites via defects engineering, a high CH 3 COOH yield of 347.31 mmol g cat −1 h−1, accompanied with a CH 3 COOH selectivity of 85.4 %, was obtained at 1.3 V vs RHE over the optimal catalyst. This CH 3 COOH yield is 2–5 orders of magnitude to previous reports so far as we know. Combinations of DFT theoretical simulation, defect sites characterization and control experiments of CH 4 electrochemical conversion confirmed the important roles of ample surface Zn/O defects. Our work provides a new insight into the design of highly active and selective catalysts toward CH 4 electrocatalytic conversion into CH 3 COOH. • ZnO nanosheets with plenty of atomic defects were synthesized. • They were used for highly efficient CH 4 conversion to acetic acid. • High yield rate and selectivity of 3473115 μmol (g cat h)−1 and 85.4 % are achieved. • The electrocatalytic performance outperforms the previous reports as we know. • Roles of Zn/O atom defects were studied in detail. [ABSTRACT FROM AUTHOR]

Economic resilience in California to destructive earthquakes is considered as an indicator of regional sustainability. We measure the abnormal volatility in stock markets, during the 1989 Loma Prieta Earthquake and the 1994 Northridge Earthquake as a series, by event study of statistical model, auto regressive moving average (ARMA) and generalized auto regressive conditional heteroscedasticity (GARCH) of economic model, and long short-term memory (LSTM) of deep learning model. The test results show there is no effect on the whole market; the sectors of Basic Industries Companies, Capital Goods Companies and Energy Companies are more sensitive to destructive earthquakes; on the level of stocks, the test result of the statistical model fit that of the economic model with percentage over 50%, and the result of the deep learning model is different. The relation between the company headquarters of the affected stocks with macroseismic intensity is unclear; those located around San Francisco Bay are sensitive to destructive earthquakes in California. [ABSTRACT FROM AUTHOR]

Background: SiNiSan, a Traditional Chinese Medicine containing Radix Bupleuri, Radix Paeoniae Alba, Fructus Aurantii Immaturus, and Radix Glycyrrhizae, has been shown to be clinically effective in treating liver damage, its underlying molecular mechanisms however remains unclear.Purpose: The aim of the current study was to understand the molecular mechanisms of SiNiSan in the treatment of liver damage utilizing mice and cell culture models.Methods: Here, mice were gavaged with 0.2% CCl4 to obtain acute liver injury model and with alcohol to obtain chronic liver injury model. H&E staining was performed to detect liver histomorphology. HPLC-MS was performed to analyze the composition of SiNiSan decoction and SiNiSan-medicated serum (SMS). In addition, western blots were done to analyze the representative protein expression in Wnt/β-catenin signaling. Immunofluorescence staining was done to analyze the protein levels in WB-F344 cells. Finally, in an attempt to measure the influence of SiNiSan on liver regeneration in rats, we constructed a rats partial hepatectomy models.Results: We demonstrated that SiNiSan treatment mitigated liver damage in mice, as evidenced by the decrease in serum AST and ALT levels, as well as improved liver tissue morphology. HPLC-MS results showed that SMS contained a variety of components from the SiNiSan decoction. Next, our results showed that SMS reduced the expression of α-fetoprotein (AFP) and enhanced the expression of albumin (ALB) and cytokeratin 19 (CK19) in WB-F344 cells. Further, SMS treatment induced the accumulation of β-catenin. After 14 days of SMS treatment, β-catenin protein underwent nuclear translocation and bound to the LEF1 receptor in the nucleus, which regulated c-Myc and Cyclin D1 factors to activate Wnt/β-catenin signaling and promoted differentiation of WB-F344 cells. In addition, we demonstrated that SiNiSan increased liver regeneration in rat hepatectomy.Conclusion: Collectively, the current study revealed that SiNiSan alleviated the acute liver injury induced by CCl4 as well as the chronic liver damage triggered by alcohol and sucrose in vitro. Concurrently, SMS treatment induced hepatic stem cell differentiation by activating Wnt/β-catenin signaling in vivo. Further study showed that SiNiSan promoted the regeneration of rats liver. The current study provides a theoretical basis for the clinical treatment of liver-related diseases with SiNiSan. [ABSTRACT FROM AUTHOR]

• The temperature-dependent fatigue crack growth behaviors are investigated. • The beneficial role of reinforcement diminishes with increasing temperature. • Micropores are formed ahead of crack tip and act as precursors for crack growth. • Fatigue promotes formation of interior micropores and degrades reinforcement layer. • Fatigue crack growth rates are well predicted by proposed Arrhenius-type expression. The fatigue crack growth behaviors of two fuel membranes are investigated at different temperatures. Fatigue crack growth rate increases with temperature, and Nafion XL membrane is more sensitive to temperature. An Arrhenius-type expression for fatigue crack growth rate is proposed and good prediction results are obtained. For Nafion XL composite membrane, fatigue crack grows by forming micropores ahead of crack tip. These micropore are formed due to the combined action of hygrothermal environment and mechanical stress, which increase with temperature. Besides, the interior micropores and microstructure changes in reinforcement layer also account for higher temperature sensitivity of Nafion XL membrane. [ABSTRACT FROM AUTHOR]

The high-frequency spectral-decay parameter κ has been used in the field of engineering seismology for several decades. The zero-distance κ value (κ 0) is a site parameter in ground motion models and strong motion synthesis. Using surface-borehole pairs of strong motion records from the strong-motion seismograph network KiK-net, we explored the effect of site soil on κ 0 , specifically the contribution from ground motion directionality. In the target area (138°E−143°E, 36°N–40°N), and records from earthquakes at 50 pairs of stations were collected. All horizontal orthogonal records were rotated from 0° to 180° with an increment of 10° to capture the difference between the average κ 0 on two horizontal components and the median value of the rotated κ 0 at surface and borehole stations. The same process was applied to Δκ 0 , the difference between surface station κ 0 and borehole station κ 0 , to measure the contribution by soil column. The nonlinear behavior of soils led to large shear strains, reduced stiffness, and decreased resonance frequency. Thus, the effect of soil nonlinearity on κ is investigated. In the same area, strong ground motion records with peak ground acceleration >100 cm/s2 were selected to identify the soil nonlinearity by the moving time window deconvolution method, and the temporal variation of time-average shear wave velocity and κ at the 50 surface stations were assessed. • The influence from ground motion directionality on κ 0 and Δκ 0 cannot be ignored. • An automated method to measure κ is proposed. • The temporal changes of V S and κ is observed by moving time window deconvolution. [ABSTRACT FROM AUTHOR]

Microplastic (MP) pollution poses a huge threat to agroecosystems, but the distribution characteristics of MPs in different types of farmland are still largely unknown. In this work, samples from six land-use types were collected from Chinese farmlands in five provinces. It was found that MP abundances were in the range of 2783–6366 items/kg in all samples. MP distribution results showed that over 80% of particles were less than 1 mm, and that MP sizes ranging between 0.02 and 0.2 mm represented the greatest proportion. The particle shape classified as fragment (with edges and angular) was the most frequent shape, with an abundance of approximately 54.05%. Polyethylene (PE) and polyamides (PA) were the most abundant polymers in cropped lands; 20.88% and 20.31%, respectively. Statistical analyses showed that lands used for plastic mulching (mulch film and greenhouse crops) had a significantly higher particle abundance, hence identifying plastic mulching as a major contributor to MP pollution in agricultural lands. Furthermore, paddy lands had a significantly higher MP abundance than wheat lands. Variation analyses of MP characteristics revealed that cereal crop farmlands (wheat, paddy land) were more likely to contain fibrous shapes and large MP particles (1–5 mm). Economically important tree lands (orchards, woodlands) were likely to contain fragment shapes and pony-size MPs (0.02–0.2 mm). Discrepancies among farmlands may depend on various reasons, such as mulching plastic application, irrigation, atmospheric fallout, etc. This study provides firsthand evidences about the characteristics of MP pollution in farmlands and explores some predominant MP sources in agroecosystems. Image 1 • MPs pollution of different land-use types of farmland was studied. • The plastic mulching lands exhibited significantly higher particle abundances. • The MP abundances were significantly higher in paddy lands than wheat lands. • Fibers and large particle size (1–5 mm) dominated the MPs in cereal crops farmlands. • Fragment shapes and pony-size MPs (<0.2 mm) were abundant in economical tree lands. The MP distribution in six land-use types were distinctive, where cereal croplands were more fibers and large MPs, but economical tree lands were fragments and small MPs. [ABSTRACT FROM AUTHOR]

• The Di Wu Yang Gan (DWYG) had hepatoprotective effects. • DWYG reduced the levels of ALT and AST in vivo and in vitro. • DWYG decreased the expression of Bax, while increased the expression of Bcl-2. The development of functional foods based on medicinal food ingredients has become a hot topic in China. Di Wu Yang Gan (DWYG) is a Chinese medicinal food that contains five dietary plants. Various health benefits, including anti-inflammation, liver regeneration regulation, have been reported, though the mechanism is not clear. This study aimed to investigate the protective effect of DWYG on carbon tetrachloride-induced acute liver injury (ALI) in embryonic liver L-02 cells and mice model. DWYG-medicated serum protected L-02 cells from carbon tetrachloride-induced damage, reduced the levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in the culture medium, decreased the expression of Bax and increased the expression of Bcl-2. Mice study suggested that DWYG decreased the levels of malondialdehyde, ALT and AST. Together, these results suggest the hepatoprotective effects of DWYG against ALI and provide an experimental basis for the utilization of DWYG to treat liver damage. [ABSTRACT FROM AUTHOR]

The development of new nanomaterials for the highly efficient wastewater treatment has been one of the hot scientific researches. Herein, we report a novel 3D Fe3+-doped BiOBr-based magnetic Janus micromotors with superior solar photo-Fenton catalytic activity for organic pollutant degradation. Taking advantage of hydrogen peroxide as reagent and fuel, Fe3+-doped BiOBr based Janus micromotors exhibited extremely high efficiency for methylene blue degradation in a solar photo-Fenton system even at mild pH conditions, which was almost 4 times than BiOBr. The speed of the Janus micromotors could reach 214.7 ± 19.4 μm s−1 in a 5% H 2 O 2 solution. Factors influencing the solar photo-Fenton reaction including Fe3+-doping amount, pH, concentration of H 2 O 2 , self-propelled movement as well as mechanical stirring were investigated to clarify the degradation mechanism. Nearly 97% of methylene blue was degraded by Fe 0.11 Bi 0.89 OBr/Fe 3 O 4 /Mn 3 O 4 Janus micromotors in the presence of 3% H 2 O 2 solution at neutral environment within 50 min. This study provided a new insight into the preparation of Janus micromotors for water purification applications based on solar photo-Fenton reaction. [ABSTRACT FROM AUTHOR]

Novelty detection is usually defined as the identification of new or abnormal objects (outliers) from the normal ones (inliers), which has wide potential applications in the real world. Recently, an effective algorithm called Deep Support Vector Data Description (Deep SVDD) has been proposed for novelty detection, which jointly trains a deep neural network while optimizing a data-enclosing hypersphere in output space. However, some constraints such as hypersphere collapse, limit the adaptability of the model and may affect the model performance. Moreover, most of the existing studies concerning Deep SVDD focus on the novelty detection for single-view data, which may fail to provide an accurate and reliable decision because the single-view data sometimes cannot fully reflect the actual condition of the problem. In this study, we developed an end-to-end deep learning method of novelty detection for multi-view data, i.e., the Deep Multi-View SVDD (DMVSVDD). To fully preserve the correlative and complementary information of multi-view data, we jointly trained multiple deep autoencoding neural networks for multiple views while adaptively optimizing the data-enclosing hypersphere of each view in latent space. A global objective function was proposed, which takes both of the sample reconstruction error minimization and the hypersphere volume minimization into consideration simultaneously to prevent hypersphere collapse in the model. In the global objective function, the hypersphere centers and view weights of different views were designed to adaptively select the better representative features after each epoch during the training process by embedding multi-view target samples into multiple data-enclosing hyperspheres with minimum volumes. The experimental results on the MNIST-USPS and NUS-WIDE-OBJECT datasets reveal that our proposed method learns the target class effectively and is superior to some state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Dempster–Shafer evidence theory can combine multiple sources of uncertain information to form a consistent basic probability assignment (BPA). How to transform BPA into decision probability is still an open issue. To solve this problem, an importance-based Decision Probability Transformation (DPT) method is proposed in this paper. In this method, the importance weight is introduced into the belief interval for the first time, and then the importance is used to define the information volume and superiority degree, so that more reliable decisions can be achieved through the trade-off between conservative and aggressive. Comparative experiments on numerical examples and applications show that the proposed DPT method can weigh the aggressiveness of decisions, and its decision probability transformation behavior is the most rational and its application performance is the most reliable. Especially, the accuracy rate of classification application is 95.31%, which is at least 0.54% higher than other compared methods. • Importance is introduced for the first time to weigh the aggressive of decision. • The information volume and superiority degree are defined with importance weights. • Weighing the importance of beliefs yields the most reliable decision probabilities. • The proposed method performs best in target recognition and classification. [ABSTRACT FROM AUTHOR]

The chemical composition of EPS (Extracellular Polymeric Substances) produced by Bacillus vallismortis sp. and its adsorption performance on typical heavy metal were studied under Na 2 S stress/induction at different concentrations. Its structure was characterized by three-dimensional fluorescence spectrogram (3D-EEM), infrared spectrum (FTIR) and X-ray photoelectron spectroscopy (XPS). The results showed that, when the Na 2 S stress/induction intensity was 20 mg/L, the protein concentration was nearly doubled compared with Control-EPS (EPS produced by Bacillus vallismortis sp. without exogenous sulfur stress); furthermore, the 3D-EEM results also demonstrated that there was an increase in the protein content, with the –SH content reaching 154.36 μmol/L, which was 48.2% higher than before stress (104.15 μmol/L). Under this condition, S-EPS (EPS produced by Bacillus vallismortis sp. stressed by exogenous sulfur) exhibited the best adsorption effect on Cu(II), with the theoretical maximum adsorption capacity reaching 1428.57 mg/g EPS. FTIR and XPS analyses revealed that the –SH, C O, N–H played a major role in the adsorption of Cu(II); among those, –SH played a key role. Moreover, the adsorption capacity of Cu(II) by S-EPS was correlated with the content of sulfhydryl protein; indeed, the exogenous sulfur stress/induction can effectively regulate the chemical composition of EPS and improve its adsorption performance, which can be crucial in the prevention and control of heavy metal pollution. • The directional regulation of EPS components and properties was achieved. • The content of sulfhydryl protein was increased, it was 48.2% higher than that before stress. • The removal efficiency of Cu(II) is improved, equilibrium adsorption capacity of Cu(II) reached 1428.57 mg/g EPS. • The analysis method is simple and effective. [ABSTRACT FROM AUTHOR]

Marsdenia tenacissima is a traditional Chinese medicine that has been used since the Ming dynasty. It is famous for its apoptotic effects on lung cancer. However, limited information is available about the underlying mechanisms. We aimed to determine the mechanisms by which different organic M. tenacissima extracts induce apoptosis in lung cancer cells. PubMed and CNKI databases were screened for M. tenacissima components that may targets lung cancer; 223 components were selected for drug-like and pharmacokinetic analysis. Moreover, the inhibitory effect of different extracts of M. tenacissima on tumor cells was illustrated using CCK-8 and apoptosis assays, and intracellular [Ca2+] was measured. The in vivo effects were examined by body weight, tumor pathology, and TUNEL staining analysis in a Lewis lung carcinoma mouse model. In vivo levels of the Ca2+ signaling-related proteins Calmodulin, CaMKⅡ, p-CaMKⅡ, MEK1/2, p-MEK1/2, ERK, and p-ERK were measured by Western blot. Petroleum ether and ethyl acetate extracts of M. tenacissima have stronger inhibitory effects than other extracts on lung cancer cells, with IC 50 values of 0.35 ± 0.04 mg/ml and 0.29 ± 0.02 mg/ml for LLC cells and 0.56 ± 0.05 mg/ml and 0.85 ± 0.04 mg/ml for A549 cells, respectively. Compared with the normal control group, A549 and LLC cells of treatment groups exhibited morphological changes typical of apoptosis, and the apoptosis rate was significantly higher, as determined by flow cytometry. Furthermore, the i[Ca2+] changed accordingly, causing a decrease in vivo in Calmodulin, CaMKⅡ, p-CaMKⅡ, p-MEK1/2 and p-ERK levels. M. tenacissima induces apoptosis, both in vitro and in vivo. Hydrophobic extracts are most effective; they increase i[Ca2+], decrease intracellular Calmodulin, CaMKⅡ, p-CaMKⅡ, p-MEK1/2 and p-ERK levels, and activate the apoptotic cascade. Image 1 [ABSTRACT FROM AUTHOR]

Impressed current technique is a widely adopted method for accelerating corrosion of steel reinforcement. The mass loss of steel can be theoretically estimated by Faraday's law with the assumption that all of the impressed current participated in the corrosion reaction. In the present study, accelerated corrosion process of reinforcing steel with impressed current was non-destructively traced by X-ray micro-computed tomography (μCT) with high accuracy. The mass loss of steel at different accelerated corrosion periods was analyzed and the efficiency of impressed current was calculated. It was found that the mass loss of steel did not always follow Faraday's law, and impressed current efficiencies varied with different corrosion periods. In the early corrosion periods, the water electrolysis occurred and lowered the current efficiency due to the high anode potential. While in the late corrosion periods, the natural corrosion caused the current efficiency to exceed 100%. [ABSTRACT FROM AUTHOR]

Chemical and mechanical degradations of perfluorosulfonic-acid membranes are two factors contributing to the reduced durability of fuel cells. While the mechanisms of isolated chemical or mechanical degradation are extensively investigated, the impact of chemical degradation on mechanical degradation is not fully understood. In this paper, the fracture behavior of Nafion 212 membranes with different chemical degradation levels are investigated. To characterize the degradation level and probe the molecular origins of chemical degradation, fluoride release, Fourier-transformer infrared spectra, conductivity and swelling behavior are measured. It is found that chemical degradation causes predominant loss of side-chains. A transition from ductile to brittle fracture is observed with increasing degradation level. In addition, the cross-sections are examined to link fracture behavior with microstructure changes. While the decreased fracture toughness is attributed to reduced mechanical properties such as Young's modulus and break strain, the decreased crack propagation resistance is ascribed to reduced plastic zone size ahead of crack tip, which reduces the plastic energy dissipation. These findings not only provide new mechanical dataset of degraded membranes for performance and durability modelling to take into account of chemical degradation effect but also improve the understanding of membrane durability. Image 1 • Fracture behavior of Nafion membranes are explored after chemical degradation. • Chemical degradation causes predominant loss of side chains. • Crack transforms from ductile to brittle fracture with increasing degradation level. • Stretch zone size from cross-section observation is related to crack propagation. • Reduced crack propagation resistance is ascribed to decreased plastic zone size. [ABSTRACT FROM AUTHOR]