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It is a universal phenomenon for patients who do not know which clinical department to register in large general hospitals. Although triage nurses can help patients, due to the larger number of patients, they have to stand in a queue for minutes to consult. Recently, there have already been some efforts to devote deep-learning techniques or pre-trained language models (PLMs) to triage recommendations. However, these methods may suffer two main limitations: (1) These methods typically require a certain amount of labeled or unlabeled data for model training, which are not always accessible and costly to acquire. (2) These methods have not taken into account the distortion of semantic feature structure and the loss of category discriminability in the model training. To overcome these limitations, in this study, we propose a cross-domain text classification method based on prompt-tuning, which can classify patients' questions or texts about their symptoms into several given categories to give suggestions on which kind of consulting room patients could choose. Specifically, first, different prompt templates are manually crafted based on various data contents, embedding source domain information into the prompt templates to generate another text with similar semantic feature structures for performing classification tasks. Then, five different strategies are employed to expand the label word space for modifying prompts, and the integration of these strategies is used as the final verbalizer. The extensive experiments on Chinese Triage datasets demonstrate that our method achieved state-of-the-art performance.

In the built environment (BE) of tourism-service-oriented villages, understanding visitor flow volumes and behaviours is crucial for guiding space revitalization and tourism management. This research uncovers quantitative relationships between visitor flow volume, spatial visual exposure, and visitors’ behaviour at 12 sites in the Tabian Rural Section of Qingshan Village, a typical tourism service-oriented village in Hangzhou. The methodologies employed in this study are based on two space syntax algorithms: 3-D isovist analysis and agent-based models (ABMs). Visual Exposure Rates (VERs) in 3-D isovists along visitors’ routes were calculated using parametric programming, and visitor flow simulation was conducted using two ABMs. Real-world visitor volumes (RWFVs) and visitors’ behaviors were also recorded during an in-situ survey. A comprehensive correlation analysis revealed multiple associations. The results demonstrated that combined simulations from ABM I, and VERs explained 50.5% of the overall variability in RWFVs. Notably, VERs were found to be associated with visitors’ behaviours of photography and seating, while the outputs from ABM I showed a moderate correlation with RWFVs. This study innovatively combines space syntax models for extended application in the research of rural BEs, providing guidance for optimizing strategies to improve spatial configuration in homogeneous villages.

ABSTRACT Infection with respiratory syncytial virus (RSV) is a major cause of acute lower respiratory tract disease in young children and older people. Despite intensive efforts over the past few decades, no direct-acting small-molecule agents against RSV are available. Most small-molecule candidates targeting the RSV fusion (F) protein pose a considerable risk of inducing drug-resistant mutations. Here, we explored the in vitro and in vivo virological properties of the K394R variant, a cross-resistant mutant capable of evading multiple RSV fusion inhibitors. Our results demonstrated that the K394R variant is highly fusogenic in vitro and more pathogenic than the parental strain in vivo. The small molecule (2E,2′E)-N,N′-((1R,2S,3S)−3-hydroxycyclohexane-1,2-diyl)bis(3-(2-bromo-4-fluorophenyl) acrylamide) (CL-A3-7), a structurally optimized compound derived from a natural caffeoylquinic acid derivative, substantially reduced in vitro and in vivo infections of both wild-type RSV and the K394R variant. Mechanistically, CL-A3-7 significantly inhibited virus–cell fusion during RSV entry by blocking the interaction between the viral F protein and the cellular insulin-like growth factor 1 receptor (IGF1R). Collectively, these results indicate severe disease risks caused by the K394R variant and reveal a new anti-RSV mechanism to overcome K394R-associated resistance.IMPORTANCERespiratory syncytial virus (RSV) infection is a major public health concern, and many small-molecule candidates targeting the viral fusion (F) protein are associated with a considerable risk of inducing drug-resistant mutations. This study investigated virological features of the K394R variant, a mutant strain conferring resistance to multiple RSV fusion inhibitors. Our results demonstrated that the K394R variant is highly fusogenic in cell cultures and more pathogenic than the parental strain in mice. The small-molecule inhibitor CL-A3-7 substantially reduced in vitro and in vivo infections of both wild-type RSV and the K394R variant by blocking the interaction of viral F protein with its cellular receptor, showing a new mechanism of action for small-molecules to inhibit RSV infection and overcome K394R-associated resistance.

The Mobile Edge Computing (MEC) system is crucial in modern networks, particularly for applications requiring low latency and high energy efficiency. Efficient task scheduling in MEC environments to balance these requirements is challenging. This paper presented a method that improves the Deep Deterministic Policy Gradient (DDPG) algorithm for better performance in MEC systems. Stability is enhanced through a soft update mechanism for target network parameters and an experience replay buffer to store past experiences, reducing sample correlation and improving training efficiency. It also proposed a reward function considering both latency and energy consumption, comparing the effects of linear and nonlinear reward functions on system performance. The task scheduling process includes state representation, action selection, environment feedback, network updates, and target network soft updates. The experimental results indicate that by analyzing the performance of different reward functions, a nonlinear reward function has been determined to achieve faster convergence. The improved DDPG algorithm outperforms traditional task scheduling algorithms in terms of latency and energy consumption under different task loads, and also has significant advantages in robustness. The ablation experiment further verified the positive contribution of each improved part to the overall performance. At Task load 10, the latency of DDPG, DDPG+Soft update, DDPG+Experience reply buffer, and this paper model were 267 ms, 263 ms, 260 ms, and 250 ms, respectively, with energy consumption of 988J, 974 J, 969 J, and 965 J. The improved DDPG algorithm in this paper not only effectively solves the task scheduling problem in MEC systems, but also provides important references for future research.

Objective Although mini‐plate fixation is an attractive treatment option for distal radius metaphyseal diaphysis junction (DRMDJ) fractures in children, the benefits of minimally invasive fixation (MIF) with pre‐bent elastic stable intramedullary nails (MIF) remain underexplored. Therefore, this study aimed to evaluate the clinical efficacy of MIF administration in children with DRMDJ fractures. Methods This retrospective study enrolled 40 patients with DRMDJ fractures who underwent MIF or mini‐plate fixation from January 2016 to January 2021. Radiographic parameters, such as palmar inclination and ulnar deflection angle, were examined postoperatively to assess the anatomical reduction of the wrist joint. Clinical outcomes, including the range of wrist flexion and back extension, were examined to analyze the recovery of the wrist range of motion. Additionally, the Gartland–Werley scoring system was used to assess the recovery status of wrist function and healing condition. The student t‐test and χ2 test were used to compare differences among groups. Results All included patients successfully underwent the operation and were followed up for 12–24 months. Patients in the MIF group had a smaller surgical incision length (0.49 ± 0.06 cm) compared to those in the mini‐plate fixation group (4.41 ± 0.73 cm) (t = 22.438, p = 0.000). Palmar inclination and ulnar deflection were within the normal range in patients of both groups, and the fractures were successfully anatomically reduced. Moreover, wrist flexion and back extension in the MIF group and mini‐plate group were (72.50° ± 0.64° vs. 70.18° ± 0.56°) and (59.55° ± 1.75° vs. 60.04° ± 1.37°), and differences were statistically significant (t = 2.708, p = 0.010 and t = 0.885, p = 0.382, respectively). Furthermore, MIF treatment resulted in a higher proportion of excellent Gartland–Werley scores (94.44%) than mini‐plate fixation (86.36%) (p = 0.390). In addition, one case in the mini‐plate fixation group experienced re‐fracture following the removal of the internal fixation, and the fracture healed after reduction and cast fixation. All patients achieved satisfactory bone healing without other complications. Conclusion Compared with mini‐plate fixation, MIF has the advantages of small incision length, superior range of motion of thr wrist joint, and better maintenance of the physiological radian, providing a promising approach for clinical and surgical treatment of DRMDJ fractures.

Background: Androgenetic alopecia (AGA) is the most common form of hair loss. Studies have suggested a potential link to metabolic disorders, but with conflicting results. To elucidate the lipidomics profile and sex-specific variations in AGA, while exploring correlation between AGA and metabolic syndrome (MetS). Methods: The AGA patients (n = 83) and healthy controls (n = 84) were collected in the study. The lipid profiles were analyzed using ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS). Serum levels of important factors associated with AGA, namely dihydrotestosterone (DHT), prostaglandin D2 (PGD2) and transforming growth factor-β1 (TGF-β1) were quantified using ELISA. Results: Compared with controls, AGA patients had a higher probability of MetS (26.51% vs 11.9%, P

Ferulic acid (FA) and ferulic acid methyl ester (FAM) are important phenolic compounds in Baijiu. In this study, the interaction of FA and FAM with human serum albumin (HSA) and lysozyme (LZM) was investigated using multispectral methods and molecular dynamics simulation. FA and FAM could interact with HSA and LZM, changing the conformation and hydrophilicity of the protein. The quenching mechanisms of FA-HSA, FA-LZM, FAM-HSA, and FAM-LZM were all static-quenching. In the FA-HSA, FAM-HSA, and FA-LZM systems, the interaction forces were mainly hydrophobic interactions and hydrogen bonding. In the FAM-LZM system, the interaction forces were mainly hydrophobic interactions, hydrogen bonding, and van der Waals force. Common metal ions such as K+, Ca2+, Cu2+, Mg2+, and Mn2+ could affect the binding ability of FA and FAM to HSA and LZM. Moreover, FA and FAM could increase the stability of HSA and LZM, and the protein bound to FA/FAM was more stable than the free protein. FA and FAM had varying degrees of impact on the physiological activities of HSA and LZM. This study provides relevant information on the interactions and metabolic mechanisms of FA and its derivatives with endogenous proteins.

Multiple-thermal-fluid (MTF) stimulation technology has been successfully applied in heavy-oil reservoir development, resulting in the significant enhancement of oil production. However, the underlying mechanism of multi-component coupling remains unclear. This paper constructs a coupling model for MTF stimulation, investigates the coupling mechanism of different media in various zones during multiple-cycle stimulation operations, and compares the implementation effect with field results. The findings reveal that (1) based on media distribution, the area from near-wellbore to far well locations can be divided into four zones: high-temperature oil-viscosity-reduction zones, compound action zones, energy-replenishment zones, and unaffected zones. (2) In the high-temperature oil-viscosity-reduction zone, the latent heat of vaporization is released by steam, and ultra-heavy oil absorbs heat and reduces its viscosity, which plays a dominant role in the production of MTF. In the compound action zone, hot water, CO2, and N2 exhibit a synergistic effect which enhances overall performance. In the energy-replenishment zone, a small amount of N2 provides pressure maintenance and an additional energy supply. (3) As more cycles of stimulation are conducted, the compound action zone expands, while the energy-replenishment zone contracts. Simultaneously, there is a decrease in contribution rate from the high-temperature viscosity-reduction zone to oil production but an increase from both the compound action zone and energy-replenishment zone up to 30%. Based on the dynamic law of representative wells, this paper proposes a multi-media zonal coupling mechanism, providing a reference for subsequent research on MTF stimulation mechanisms and the adjustment of production measures.

Daqu is an important saccharifying starter in the fermentation of Nongxiangxing Baijiu in China. Vanillin is a health and flavor factor in Baijiu. However, only a few research studies on the vanillin content of Daqu are currently not systematic. In order to investigate the metabolic mechanism of vanillin in the fermentation process of Daqu, we analyzed the changes in microorganisms, influencing factors, and enzymes related to vanillin in Daqu. This research found that there were differences between bacterial and fungal genera in each sample, and the abundance of bacteria was greater than that of fungi. Among the microbial genera, Klebsiella, Escherichia, Acinetobacter, Saccharopolyspora, Aerococcus, and Puccinia were positively correlated with vanillin. Meanwhile, we also found that moisture and reducing sugar were the main physicochemical factors affecting the formation of vanillin. The functional annotation results indicate that carbohydrate metabolism and energy metabolism were important microbial metabolic pathways that impacted vanillin production in solid-state fermentation. The feruloyl-CoA hydratase/lyase (EC 4.1.2.61) and acylamidase (EC 3.5.1.4) were positively correlated with vanillin content (p ≤ 0.05) and promote the increase in vanillin content. These findings contribute to furthering our understanding of the functional microorganisms, physicochemical factors, and enzymes related to the change in vanillin content during the fermentation of Daqu and can help to further explore the flavor substances in Baijiu fermentation in the future.

Nasal bone is a long, paired series of small bones, which is narrow at the top and broad at the bottom, that forms the base of the nasal dorsum. Together with the nasal part of the frontal bone, the frontal process of the maxilla and the middle plate of the ethmoid bone constitute the bone scaffold of the external nose. In this paper, the DICOM image data file was imported into the Mimics software for 3D reconstruction. At the same time, the Geomagic software was used for relevant image processing, and the finite element software ANSYS was used to establish a finite element model to analyze the stress characteristics of the nasomaxillary complex. Results. The maximum principal stress and maximum strain force at the lower segment of nasal bone and the junction of nasal bone and maxilla were relatively large. When the same external force acts on the lower segment of the nasal bone and the angle is 0° (sagittal force), the maximum principal stress and maximum strain force are the smallest. When the angle continues to increase, the maximum principal stress and maximum strain force continue to increase.

To identify an apoptosis-related gene (ARG) prediction model for oral squamous cell carcinoma (OSCC), we analyzed and validated the data from TCGA and GEO, respectively. Kaplan–Meier survival analysis and ROC curves showed a good prognostic ability of the model both in the internal training set and in the external testing set. Furthermore, we built a nomogram using these ARGs to forecast the survival probability of OSCC patients. Moreover, we evaluated the rate of immune cells infiltrating in the tumor samples and found obvious, different patterns between the high and low risk groups. GO and KEGG analyses demonstrated multiple molecular biological processes and signaling pathways connecting with this prognostic model in OSCC. The expression of these risk genes in clinical specimens was higher in the non-survival patients than in the well-survival patients by immunohistochemical staining analysis. In conclusion, we established a signature made up of six risk apoptosis-related genes to predict the survival rate of OSCC. These genes could also be targets for the treatment of OSCC.

Carboniferous carbonate reservoirs at the eastern edge of the Pre-Caspian Basin have undergone complex sedimentation, diagenesis and tectonism processes, and developed various reservoir space types of pores, cavities and fractures with complicated combination patterns which create intricate pore-throats structure. The complex pore-throat structure leads to the complex porosity-permeability relationship, bringing great challenges for classification and evaluation of reservoirs and efficient development. Based on the comprehensive analysis on cores, thin sections, SEM, mercury intrusion, routine core analysis and various tests, this paper systematically investigated the features and main controlling factors of pore-throats structure and its impact on the porosity-permeability relationship of the four reservoir types which were pore-cavity-fracture, pore-cavity, pore-fracture and pore, and three progresses are made. (1) A set of classification and descriptive approach for pore-throat structure of Carboniferous carbonate reservoirs applied to the eastern edge of the Pre-Caspian Basin was established. Four types of pore-throat structures were developed which were wide multimodal mode, wide bimodal mode, centralized unimodal mode and asymmetry bimodal mode, respectively. The discriminant index of pore-throat structure was proposed, realizing the quantitative characterization of pore-throat structure types. (2) The microscopic heterogeneity of pore reservoir was the strongest and four types of pore-throat structures were all developed. The pore-fracture and pore-cavity-fracture reservoirs took the second place, and the microscopic heterogeneity of pore-cavity reservoir was the weakest. It was revealed that the main controlling factor of pore-throat structure was the combination patterns of reservoir space types formed by sedimentation, diagenesis and tectonism. (3) It was revealed that the development of various pore-throat structure types was the important factor affecting poroperm relationship of reservoirs. The calculation accuracy of permeability of reservoirs can be improved remarkably by subdividing the pore-throat structure types. This study deepens the understanding of pore-throat structure of complicated carbonate reservoirs, and is conducive to classification and evaluation, establishment of precise porosity-permeability relationship and highly efficient development of carbonate reservoirs.

AbstractThe purpose of this study is to introduce a new three-linear flow model for capturing the dynamic behavior of water flooding with different fracture occurrences in carbonate reservoirs. Low-angle and high-angle fractures with different occurrences are usually developed in carbonate reservoirs. It is difficult to simulate the water injection development process and the law of water flooding is unclear, due to the large variation of the fracture dip. Based on the characteristics of water flooding displacement streamlines in fractured cores with different occurrences, the matrix is discretized into a number of one-dimensional linear subregions, and the channeling effect between each subregion is considered in this paper. The fractures are divided into the same number of fracture cells along with the matrix subregion, and the conduction effect between the fracture cells is considered. The fractured core injection-production system is divided into three areas of linear flow: The injected fluid flows horizontally and linearly from the matrix area at the inlet end of the core to the fracture and then linearly diverts from the fracture area. Finally, the matrix area at the outlet end of the core also presents a horizontal linear flow pattern. Thus, a trilinear flow model for water flooding oil in fractured cores with different occurrences is established. The modified BL equation is used to construct the matrix water-flooding analytical solution, and the fracture system establishes a finite-volume numerical solution, forming a high-efficiency semianalytical solution method for water-flooding BL-CVF. Compared with traditional numerical simulation methods, the accuracy is over 86%, the model is easy to construct, and the calculation efficiency is high. In addition, it can flexibly portray cracks at any dip angle, calculate various indicators of water flooding, and simulate the pressure field and saturation field, with great application effect. The research results show that the greater the fracture dip angle, the higher the oil displacement efficiency. When the fracture dip angle is above 45°, the fracture occurrence has almost no effect on the oil displacement efficiency. The water breakthrough time of through fractures is earlier than that of nonthrough fractures, and the oil displacement efficiency and injection pressure are more significantly affected by the fracture permeability. With the increase of fracture permeability, the oil displacement efficiency and the injection pressure of perforated fractured cores dropped drastically. The findings of this study can help for better understanding of the water drive law and optimizing its parameters in cores with different fracture occurrences. The three-linear flow model has strong adaptability and can accurately solve low-permeability reservoirs and high-angle fractures, but there are some errors for high-permeability reservoirs with long fractures.

Background: This study examines whether cognitive insight is impaired in high-risk individuals with attenuated psychotic symptoms (APS) and explores the relationship between cognitive and clinical insight at different durations of untreated attenuated psychotic symptoms (DUAPS).Methods: The Structured Interview for Psychosis high-risk Syndrome (SIPS) was used to identify APS individuals. APS (n = 121) and healthy control (HC, n = 87) subjects were asked to complete the Beck Cognitive Insight Scale (BCIS). Clinical insight of APS individuals was evaluated using the Schedule for Assessment of Insight (SAI). APS individuals were classified into four subgroups based on DUAPS, including 0–3, 4–6, 7–12, and >12 months. Power analysis for significant correlation was conducted using the WebPower package in R.Results: Compared with HC subjects, APS individuals showed poorer cognitive insight, with lower scores on BCIS self-reflectiveness and composite index (BCIS self-reflectiveness minus BCIS self-certainty). Only when DUAPS was longer than 12 months did the significant positive correlation between cognitive and clinical insight obtain the power about 0.8, including the associations between self-reflectiveness and awareness of illness, self-reflectiveness and the total clinical insight, and composite index and awareness of illness. The positive associations of composite index with awareness of illness within 0–3 months DUAPS and with the total score of SAI when DUAPS > 12 months were significant but failed to obtain satisfactory power.Conclusions: APS individuals may have impaired cognitive insight, demonstrating lower self-reflectiveness. The correlation between cognitive and clinical insight is associated with the duration of untreated attenuated psychotic symptoms.

Entomopathogenic fungi are promising biocontrol agents of insect-mediated crop damage. Microcycle conidiation has shown great potential in enhancing the conidial yield and quality of entomopathogenic fungi. Homologs of Cts1, an endochitinase of Saccharomyces cerevisiae, participate in cell separation in several fungal spp. and may contribute to the morphological differences that occur during the shift to microcycle conidiation. However, the precise functions of Cts1 in entomopathogenic fungi remain unclear. Herein, the endochitinase gene, MaCts1, was characterized in the model entomopathogen, Metarhizium acridum. A loss of function line for MaCts1 led to a delay of 1 h in the median germination time, a 28% reduction in conidial yield and significant defects in fungal resistances to UV-irradiation (18%) and heat-shock (15%), while fungal tolerances to cell wall stressors, oxidative and hyperosmotic stresses and virulence remained unchanged. The MaCts1-disruption strain displayed typical conidiation on the microcycle conidiation induction medium, SYA. In contrast, deletion of key genes in the morphogenesis-related NDR kinase network (MOR pathway)/regulation of Ace2 and morphogenesis (RAM pathway) did not affect the SYA-induction of microcycle conidiation. This indicates that MaCts1 makes contributions to the microcycle conidiation, which may not be dependent on the MOR/RAM pathway in M. acridum.

The prevalence of hypertension is increasing globally, while strategies for prevention and treatment of hypertension remain limited. FG-4592 (Roxadustat) is a potentially novel, orally active small-molecule hypoxia-inducible factor (HIF) stabilizer and is being used clinically to treat chronic kidney disease (CKD) anemia. In the present study, we evaluate the effects of FG-4592 on hypertension. In an angiotensin II (Ang II) hypertension model, FG-4592 abolished hypertensive responses; prevented vascular thickening, cardiac hypertrophy, and kidney injury; downregulated AGTR1 expression; and enhanced AGTR2, endothelial NO synthase (eNOS), and HIF1α protein levels in the aortas of mice. Additionally, the levels of thiobarbituric acid reactive substances (TBARs) in blood and urine were diminished by FG-4592 treatment. In vascular smooth muscle cells, FG-4592 treatment reduced angiotensin receptor type 1 (AGTR1) and increased AGTR2 levels, while preventing Ang II–induced oxidative stress. In vascular endothelial cells, FG-4592 upregulated total and phosphorylated eNOS. Moreover, FG-4592 treatment was hypotensive in L-NAME–induced hypertension. In summary, FG-4592 treatment remarkably ameliorated hypertension and organ injury, possibly through stabilizing HIF1α and subsequently targeting eNOS, AGTR1, AGTR2, and oxidative stress. Therefore, in addition to its role in treating CKD anemia, FG-4592 could be explored as a treatment for hypertension associated with high renin angiotensin system (RAS) activity or eNOS defects.

Too many input features in applications may lead to over-fitting and reduce the performance of the learning algorithm. Moreover, in most cases, each feature containing different information content has different effects on the prediction target. Therefore, a feature selection method for calculating the importance of each feature, called WKNNGAFS, is proposed in this paper. In this method, the genetic algorithm (GA) is adopted to search the optimal weight vector, the value of the ith component of which corresponds to the contribution degree of the ith feature to the classification from a global perspective. Besides, weighted K-nearest neighbors algorithm (WKNN), which takes both the different contributions of nearest neighbors and the different classification ability of each feature into account, is used to determine the target label. To evaluate the effectiveness of the proposed method, nine existing feature selection methods are compared with it on 13 real datasets, including 6 high dimensional microarray datasets. Experimental results demonstrate the method is more effective and can improve classification performance.

The carboniferous carbonate reservoirs in the North Truva Oilfield have undergone complex sedimentation, diagenesis and tectonic transformation. Various reservoir spaces of pores, caves and fractures, with strong reservoir heterogeneity and diverse pore structures, have been developed. As a result, a quantitative description of the pore structure is difficult, and the accuracy of logging identification and prediction is low. These pose a lot of challenges to reservoir classification and evaluation as well as efficient development of the reservoirs. This study is based on the analysis of core, thin section, scanning electron microscope, high-pressure mercury injection and other data. Six types of petrophysical facies, PG1, PG2, PG3, PG4, PG5, and PG6, were divided according to the displacement pressure, mercury removal efficiency, and median pore-throat radius isobaric mercury parameters, combined with the shape of the capillary pressure curve. The petrophysical facies of the wells with mercury injection data were divided accordingly, and then the machine learning method was applied. The petrophysical facies division results of two mercury injection wells were used as training samples. The artificial neural network (ANN) method was applied to establish a training model of petrophysical facies recognition. Subsequently, the prediction for the petrophysical facies of each well in the oilfield was carried out, and the petrophysical facies division results of other mercury injection wells were applied to verify the prediction. The results show that the overall coincidence rate for identifying petrophysical facies is as high as 89.3%, which can be used for high-precision identification and prediction of petrophysical facies in non-coring wells.

Multi-view clustering has been deeply explored since the compatible and complementary information among views can be well captured. Recently, the low-rank tensor representation-based methods have effectively improved the clustering performance by exploring high-order correlations between multiple views. However, most of them often express the low-rank structure of the self-representative tensor by the sum of unfolded matrix nuclear norms, which may cause the loss of information in the tensor structure. In addition, the amount of effective information in all views is not consistent, and it is unreasonable to treat their contribution to clustering equally. To address the above issues, we propose a novel weighted low-rank tensor representation (WLRTR) method for multi-view subspace clustering, which encodes the low-rank structure of the representation tensor through Tucker decomposition and weights the core tensor to retain the main information of the views. Under the augmented Lagrangian method framework, an iterative algorithm is designed to solve the WLRTR method. Numerical studies on four real databases have proved that WLRTR is superior to eight state-of-the-art clustering methods.

Computational methods that predict protein stability changes induced by missense mutations have made a lot of progress over the past decades. Most of the available methods however have very limited accuracy in predicting stabilizing mutations because existing experimental sets are dominated by mutations reducing protein stability. Moreover, few approaches could consistently perform well across different test cases. To address these issues, we developed a new computational method PremPS to more accurately evaluate the effects of missense mutations on protein stability. The PremPS method is composed of only ten evolutionary- and structure-based features and parameterized on a balanced dataset with an equal number of stabilizing and destabilizing mutations. A comprehensive comparison of the predictive performance of PremPS with other available methods on nine benchmark datasets confirms that our approach consistently outperforms other methods and shows considerable improvement in estimating the impacts of stabilizing mutations. A protein could have multiple structures available, and if another structure of the same protein is used, the predicted change in stability for structure-based methods might be different. Thus, we further estimated the impact of using different structures on prediction accuracy, and demonstrate that our method performs well across different types of structures except for low-resolution structures and models built based on templates with low sequence identity. PremPS can be used for finding functionally important variants, revealing the molecular mechanisms of functional influences and protein design. PremPS is freely available at https://lilab.jysw.suda.edu.cn/research/PremPS/, which allows to do large-scale mutational scanning and takes about four minutes to perform calculations for a single mutation per protein with ~ 300 residues and requires ~ 0.4 seconds for each additional mutation.

Sulfatases are commonly divided into three classes: type I, type II, and type III sulfatases. The type III sulfatase, alkylsulfatase, could hydrolyze the primary alkyl sulfates, such as sodium dodecyl sulfate (SDS) and sodium octyl sulfate. Thus, it has the potential application of SDS biodegradation. However, the roles of alkylsulfatase in biological control fungus remain unclear. In this study, an alkylsulfatase gene MaAts was identified from Metarhizium acridum. The deletion strain (ΔMaAts) and the complemented strain (CP) were constructed to reveal their functions in M. acridum. The activity of alkylsulfatase in ΔMaAts was dramatically reduced compared to the wild-type (WT) strain. The loss of MaAts delayed conidial germination, conidiation, and significantly declined the fungal tolerances to UV-B irradiation and heat-shock, while the fungal conidial yield and virulence were unaffected in M. acridum. The transcription levels of stress resistance-related genes were significantly changed after MaAts inactivation. Furthermore, digital gene expression profiling showed that 512 differential expression genes (DEGs), including 177 up-regulated genes and 335 down-regulated genes in ΔMaAts, were identified. Of these DEGs, some genes were involved in melanin synthesis, cell wall integrity, and tolerances to various stresses. These results indicate that MaAts and the DEGs involved in fungal stress tolerances may be candidate genes to be adopted to improve the stress tolerances of mycopesticides.

Background/foreground separation has become an inevitable step in numerous image/video processing applications, such as image/video inpainting, anomaly detection, motion segmentation, augmented reality, and so on. Recent low-rank based approaches, such as robust principal component analysis separating a data matrix into a low-rank matrix with a sparse matrix, have achieved encouraging performance. However, these approaches usually need relatively high computation cost, mainly due to calculation of full or partial singular value decomposition of large matrices. On the other hand, the nuclear norm is widely exploited as a convex surrogate of the original rank function, while it is not a tighter envelope of the original rank function. To address these above-mentioned issues, this paper proposes a fast background/foreground separation algorithm in which the low-rank constraint is solved by a matrix factorization scheme, thus heavily reducing the computation cost. We further adopt two non-convex low-rank approximations to improve the robustness and flexibility of the traditional nuclear norm. In comparison with the state-of-the-art low-rank reconstruction methods, experimental results on challenging data sets, which contain different real data sets, show our superior performance in both image clarity and computation efficiency.

Citric acid-treated zeolite Y (CY) and zeolite beta were mechanically mixed to obtain composite zeolites (CY-Beta) with various zeolite beta contents. The composite zeolites were used as the acid components of hydrocracking catalyst supports. The physical and chemical properties of the supports and catalysts were analyzed by N2 adsorption-desorption, XRD, SEM, and NH3-TPD. The mechanical mixing of CY and zeolite beta does not destroy the textual properties of the original zeolites. However, the acidity of the composite zeolite does not fit the linearly calculated value of the two zeolites because some of the acid sites are covered or reacted with other acid sites during the mixing process. In addition, weak acid sites favor the high yield of tail oil with low BMCI value. Compared with the CY-based and beta-based catalysts, the conversion and light oil yield of the CY-Beta-based catalyst was increased. The conversion, light oil yield, and petrochemical yield of the Ni-W/20CY-Beta(20)/ASA catalyst are 78.15, 65.0, and 83.7%, respectively. The BMCI value of the tail oil is 4.7, and the aromatic potential content (APC) of heavy naphtha (boiling point 65–177°C) is 42%. The 1,500 h pilot plant test of Ni-W/20CY-Beta(20)/ASA at 350°C, 7.0 MPa, 2.0 h−1 LHSV, and 800 H2/oil (v/v) shows that the activity remains stable during the 1,500 h evaluation. The heavy naphtha (APC about 41.0) yield of 41.2 illustrates that the catalyst has the ability to aromatize and cyclize the light fractions. The yield of diesel is about 25% with a cetane index (CI) of 59.2; the frozen point is lower than −45°C, and the cold filter plugging point is −35°C, demonstrating the isomerization performance for middle distillations. The yield of tail oil is 14.9% with a BMCI of 4.4, showing the high hydrogenation performance of the catalyst to transform the un-cracked tail oil to saturated hydrocarbon in order to reduce the BMCI value.

Human motion retrieval and analysis is a useful means of activity recognition to 3D human bodies. An efficient method is proposed to estimate human motion by using symmetric joint points and limb features of various limb parts based on regression task. We primarily obtain the 3D coordinates of symmetric joint points based on the located waist and hip points. By introducing three critical feature points on torso and symmetric joint points’ matching on motion video sequences, the 3D coordinates of symmetric joint points and its asymmetric limb features will not be affected by shading and interference of limb on different postures. With the asymmetric limb features of various human parts, a dynamic regulated Fuzzy neural network (DRFNN) is proposed to estimate human motion for different asymmetric postures using learning algorithm of network parameters and weights. Finally, human sequential actions corresponding to different asymmetric postures are presented according to the best retrieval results by DRFNN based on 3D human action database. Experiments show that compared with the traditional adaptive self-organizing fuzzy neural network (SOFNN) model, the proposed algorithm has higher estimation accuracy and better presentation results compared with the existing human motion analysis algorithms.

A fracture-pore carbonate reservoir in eastern Pre-Caspian basin was taken as an example to analyze the oil phase behavior change and seepage physical characteristics change of weakly volatile oil reservoirs with the decrease of formation pressure. Based on the analysis, the water-flooding development technique policy of the reservoir under different formation pressure was presented. Experiments show that the weakly volatile crude oil degasifies as the formation pressure decreases, with methane and intermediate hydrocarbons separated out successively, and the crude oil gradually transforms into ordinary black oil. With the separation of light hydrocarbons, the saturation of in-place oil drops rapidly, the viscosity increases, and the oil permeability reduces, leading to lower well productivity. Retention of formation pressure is a vital factor controlling the reservoir development effect. The lower the formation pressure, the lower the ultimate recovery. Given low formation pressure, water-flooding is required to recover the formation pressure. In water-flooding, the lower level the formation pressure is retained at, the lower the reasonable pressure to be recovered is, and the lower the ultimate recovery is. Compared with zones without fractures, the zone with fractures provides lower injection-production ratio when water-flooding is conducted under the same formation pressure, and its water-flooding time has more impact on oilfield recovery. Therefore, it is recommended to develop weakly volatile oil reservoir by early water-flooding in a moderate way. Key words: carbonate reservoir, weakly volatile oil, phase behavior change, seepage characteristics, formation pressure, water-flooding time

To measure the photocatalytic performance of N-doped TiO2-pillared clay nanocomposites (N-TiO2-PILC) for Cr(VI) removal under visible light, this paper prepares N-TiO2-PILC samples by sol-gel method and characterized them by scanning electron microscopy (SEM), X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) analysis and energy-dispersive X-ray spectroscopy (EDS). The author also explored the preparation conditions, settleability and reusability of the samples. The results show that N-TiO2-PILC had uniform pore size distribution, a large specific surface area (SSA) and an anatase crystal structure. The pillaring successfully introduces TiO2 particles into the clay, giving the composites a uniform interlayer structure. In addition, the optimal acid-base ratio and Ti/ clay ratio were determined as 3:1mL/mL and 15:1mmol/g, respectively; the optimal calcination temperature was proved to be 500 °C. The research findings shed new light on the removal of Cr(VI) in water under visible light.

In recent years, detection of trace amounts of dissolved lipophilic phycotoxins in coastal waters has been possible using solid phase adsorption toxin tracking (SPATT) samplers. To explore the contribution of dissolved diarrhetic shellfish toxins (DST) to the accumulation of toxins by cultivated bivalves, mussels (Mytilus galloprovincialis) were exposed to different concentrations of purified okadaic acid (OA) and dinophysistoxin-1 (DTX1) in filtered (0.45 µm) seawater for 96 h. Accumulation and esterification of DST by mussels under different experimental conditions, including with and without the addition of the food microalga Isochrysis galbana, and with the addition of different size-fractions of suspended particulate matter (SPM) ( gills > mantle > residual tissues. However, the percentage of total DST in the digestive gland of mussels in filtered seawater (67%) was higher than with the addition of SPM particles (75–150 µm) (51%), whereas the gills showed the opposite trend in filtered seawater with (27%) and without (14.4%) SPM particles. Results presented here will improve our understanding of the mechanisms of DST accumulation by bivalves in marine aquaculture environments.

Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs), for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs) and long short-term memory (LSTM) neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction.