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Attributed graph clustering, the task of grouping nodes into communities using both graph structure and node attributes, is a fundamental problem in graph analysis. Recent approaches have utilized deep learning for node embedding followed by conventional clustering methods. However, these methods often suffer from the limitations of relying on the original network structure, which may be inadequate for clustering due to sparsity and noise, and using separate approaches that yield suboptimal embeddings for clustering. To address these limitations, we propose a novel method called Deep Attributed Clustering with High-order Proximity Preserve (DAC-HPP) for attributed graph clustering. DAC-HPP leverages an end-to-end deep clustering framework that integrates high-order proximities and fosters structural cohesiveness and attribute homogeneity. We introduce a modified Random Walk with Restart that captures k-order structural and attribute information, enabling the modelling of interactions between network structure and high-order proximities. A consensus matrix representation is constructed by combining diverse proximity measures, and a deep joint clustering approach is employed to leverage the complementary strengths of embedding and clustering. In summary, DAC-HPP offers a unique solution for attributed graph clustering by incorporating high-order proximities and employing an end-to-end deep clustering framework. Extensive experiments demonstrate its effectiveness, showcasing its superiority over existing methods. Evaluation on synthetic and real networks demonstrates that DAC-HPP outperforms seven state-of-the-art approaches, confirming its potential for advancing attributed graph clustering research. [ABSTRACT FROM AUTHOR]

Objective: The performance and stability of radiomics model caused by dimension reduction remain being confronted with major challenges. In this study, we aimed to propose a new scheme of global feature management independent of dimension reduction to improve it. Methods: The non-contrast computed tomography (NCCT) images of acute brainstem infarction (ABI) from two medical centers were used as test and validation sets. A new scheme was constructed based on global feature management, and the traditional scheme dependent on dimension reduction was used as control. The radiomic features of NCCT images were extracted in Matlab R2013a. The performance of prediction model was evaluated by the generalized linear model (GLM) and multivariate logistic regression. And, the stability of radiomics model was evaluated with the difference of area under curve (AUC) between the test and validation sets. Results: Compared with the traditional scheme, the new scheme presented a similar detection performance (AUC: 0.875 vs. 0.883), yet a better performance in predicting prognosis (AUC: 0.864, OR = 0.917, p = 0.021 vs. AUC:0.806, OR = 0.972, p = 0.007). All these results were well verified in an independent validation set. Moreover, the new scheme showed stronger stability in both the detection model (ΔAUC: 0.013 vs. 0.039) and prediction model (ΔAUC = 0.004 vs. 0.044). Conclusion: Although there might be several limitations, this study proved that the scheme of global feature management independent of dimension reduction could be a powerful supplement to the radiomics methodology. Key Points: • The new scheme (Swavelet) presented similar detection performances for ABI with the traditional scheme. • A better predictive performance for END was found in the new scheme (Swavelet) compared with the traditional scheme. • Stronger model stability was found in both the detection and prediction models based on the new scheme. [ABSTRACT FROM AUTHOR]

Activated carbon (AC) was treated with nitric acid, hydrogen peroxide, and urea. The obtained products were then used as supports for the preparation of palladium/activated carbon (Pd/AC) catalysts. The characterization results revealed that the AC textural structure and surface properties were selectively modified via different treatments, and the surface functional groups of the supports could affect the particle size, dispersion, and chemical states of the Pd nanoparticles. The surface of the urea-treated AC (AC-U) contained more carbonylic groups and nitrogenous species but fewer hydroxylic and carboxylic groups than the surfaces of the ACs subjected to other treatments. Consequently, in the hydrogenation synthesis of meropenem, the Pd/AC-U catalyst provided a higher meropenem yield and lower amounts of impurities in the meropenem product than the other catalysts. The nitrogenous groups not only provided efficient anchoring sites for Pd nanoparticles, improving the reaction activity, but also reduced the side reactions, decreasing the impurity content in the product. [ABSTRACT FROM AUTHOR]

The basis for the formation of spherical edge burrs during servo valve spool shoulder grinding and a method for eliminating these burrs were investigated. Based on the results of this investigation, a grinding and synchronous deburring device was designed. A geometric model of single abrasive grains was established and the formation mechanism of the valve spool edge burrs was evaluated. Subsequently, the deburring process was analyzed via dynamic simulations, and based on the results, the aforementioned device was designed for mounting on an S20 precision cylindrical grinder. The correctness of the simulation and the feasibility of the device were verified via experiments. The experimentally observed burr shape and size corresponded closely to the simulated features. Moreover, the test device was effective in removing the edge burrs of the valve spool, as evidenced by the lack of sharp edge burrs. Hence, this device could be helpful in grinding the valve spool shoulder for significant improvement in the processing quality and efficiency. [ABSTRACT FROM AUTHOR]

In the current information era over the internet, social media has become one of the essential information sources for users. While the text is the primary information representation, finding relevant information is a challenging mission for researchers due to its nature (e.g., short length, sparseness). Acquiring high-quality search results from massive data, such as social media needs a set of representative query terms that are not always available. In this paper, we propose a novel query-based unsupervised learning model to represent the implicit relationships in the short text from social media. This bridges the gap of the lack of word co-occurrences without requiring many parameters to be estimated and external evidence to be collected. To confirm the proposed model effectiveness, we compare the proposed model with state-of-the-art lexical, topic model and temporal models on the large-scale TREC microblog 2011-2014 collections. The experimental results show that the proposed model significantly improved overall state-of-the-art lexical, topic model and temporal models with the maximum percentage of increase reaching 33.97% based on MAP value and 21.38% based on Precision at top 30 documents. The proposed model can improve the social media search effectiveness in potential closely retrieval tasks, such as question answering and timeline summarisation. [ABSTRACT FROM AUTHOR]

Objectives: The objective of this study was to evaluate whether baseline 18F-fluorodeoxyglucose (FDG) uptake is associated with carotid plaque progression.Methods: A total of 156 subjects with carotid plaque were enrolled and underwent carotid magnetic resonance imaging (MRI) (at baseline and the 12-month follow-up) and positron emission tomography-computed tomography (PET-CT) (baseline). Carotid plaque progression was evaluated by two indices (the incidence of plaque progression and percentage of plaque increase) with three-dimensional (3D) imaging, while the 18F-FDG uptake was evaluated by the 18F-FDG uptake levels and 18F-FDG uptake velocity. The association between plaque progression and 18F-FDG uptake was investigated by the trend test and multivariate logistic regression analysis.Results: Of the 156 subjects, 80 (51.3%) showed carotid plaque progression during the 12-month follow-up. Firstly, no association was found between 18F-FDG uptake levels and plaque progression. Secondly, significant differences in the incidence of plaque progression were observed among the groups with different uptake velocities, showing a significant decreasing trend ranging from high to intermediate to low (p = 0.002, trend test). After adjusting for covariates, an adequate prediction of the 18F-FDG uptake velocity for the incidence of plaque progression was revealed (OR = 0.682, p < 0.05). In addition, no association was found between the 18F-FDG uptake velocity and the percentage of plaque increase in the subjects with plaque progression (p = 0.757, trend test).Conclusions: Our findings suggest 18F-FDG uptake velocity is independently associated with the incidence of carotid plaque progression. Additionally, the 18F-FDG uptake velocity, as another important parameter of PET-CT, warrants further study in future clinical research.Key Points: • The18F-FDG uptake levels were not associated with the carotid plaque progression. • The18F-FDG uptake velocity could predict the incidence of carotid plaque progression. • The18F-FDG uptake velocity with related factors warrants more attention in future clinical research. [ABSTRACT FROM AUTHOR]

This study proposes a bi-level framework for real-time crash risk forecasting (RTCF) for signalised intersections, leveraging the temporal dependency among crash risks of contiguous time slices. At the first level of RTCF, a non-stationary generalised extreme value (GEV) model is developed to estimate the rear-end crash risk in real time (i.e., at a signal cycle level). Artificial intelligence techniques, like YOLO and DeepSort were used to extract traffic conflicts and time-varying covariates from traffic movement videos at three signalised intersections in Queensland, Australia. The estimated crash frequency from the non-stationary GEV model is compared against the historical crashes for the study locations (serving as ground truth), and the results indicate a close match between the estimated and observed crashes. Notably, the estimated mean crashes lie within the confidence intervals of observed crashes, further demonstrating the accuracy of the extreme value model. At the second level of RTCF, the estimated signal cycle crash risk is fed to a recurrent neural network to predict the crash risk of the subsequent signal cycles. Results reveal that the model can reasonably estimate crash risk for the next 20–25 min. The RTCF framework provides new pathways for proactive safety management at signalised intersections. [ABSTRACT FROM AUTHOR]

Intercropping of upland rice with short-duration grain legumes has major advantages in increasing crop yields and soil productivity. However, the contribution of arbuscular mycorrhizas, the common mutualistic symbiosis between most crops and mycorrhizal fungi, is not fully understood in intercropping systems. We assayed the contribution of inoculation of the arbuscular mycorrhizal fungus (AMF) Glomus caledonium on nutrient acquisition and biomass yield. Using the method of plastic film and nylon net partition and tracing 15N transferred between the intercropped upland rice ( Oryza sativa ssp. Japonica Nipponbare) and mung bean ( Vigna radiata L. Chuanyuan), we compared the intercropping, with separation of the whole root systems by a plastic film, with and without a barrier of nylon net to allow penetration of the fungal hyphae. Intercropping significantly improved the formation of arbuscular mycorrhizas, particularly in the upland rice roots. The improved formation of mycorrhizas by the intercropping increased total P uptake by 57% in rice, total P and N acquisition by 65% and 64% respectively in mung bean, and nodulation by 54% in mung bean. The percentage of total 15N transfer from mung bean to rice leaves was increased from 5.4% to 15.7% by inoculation with AMF. In contrast, there was only 2.7% of 15N transfer from rice to mung bean and no AMF effect on N transfer. It is concluded that cereal and legume crop intercropping increase mycorrhiza formation, which in turn improves nodulation, N and P acquisition and N transfer in the legumes. [ABSTRACT FROM AUTHOR]

The single cleavage drilled compression specimens of sandstone were impacted by the large-diameter split Hopkinson pressure bar, during which the whole model-I dynamical fracture process was successfully observed. A crack propagation gauge is used to monitor the key time moment of dynamic initiation, propagation, arrest and re-initiation, respectively. The fractal crack extension model is used to analysis the propagation speed of the tortuous crack, and with further combination of the experimental–numerical-analytical method, to determine the dynamic initiation toughness, dynamic propagation toughness, dynamic arrest toughness, and dynamic re-initiation toughness of sandstone. The results show that in the process of crack propagation, the crack propagation path is torturous; and for this curved path, the value of the universal function, which is characterized by the crack's velocity, is smaller than that with a straight path. The dynamic propagation toughness thus obtained is closer to its real value by using the fractal model. Sandstone's dynamic initiation toughness is greater than the dynamic arrest toughness, and the dynamic initiation toughness is slightly bigger than the dynamic re-initiation toughness. [ABSTRACT FROM AUTHOR]

Some thiazolamide derivatives containing diphenyl ether moiety were designed, synthesized, and studied for their antifungal activity and cell cytotoxicity. Of these, several compounds II possessed excellent activity against Rhizoctonia solani, which was better than that of boscalid and comparable to thifluzamide. Besides, the cytotoxicity test showed that the optimal compound IIf had lower cytotoxicity than thifluzamide in general. Further, molecular docking could give a reasonable explanation for the high activity of the target compounds. The above results indicated that thiazolamide derivatives containing diphenyl ether moiety are valuable for in-depth study to obtain high-efficiency and low-toxicity green pesticides. A series of new thiazolamide derivatives containing diphenyl ether moiety were designed and synthesized. The biological evaluation indicated optimal compound IIf displayed not only high fungicidal activity but also lower cytotoxicity. Besides, molecular docking gave a reasonable explanation for the high activity of the target compounds. [ABSTRACT FROM AUTHOR]

Although the FDA already has approved two types of drug therapies for Alzheimer’s disease, in regard to moderate AD, there is no clear research to support the best choice of drug treatment. The goal of this study was to examine the levels of serum biomarkers in moderate-AD patients and to explore the value of these serum biomarkers for the diagnosis of memantine sensitivity in AD patients who are significantly affected by MEM. In our study, 177 patients with moderate AD were enrolled and divided into memantine-sensitive AD (n = 90) and memantine-insensitive AD (n = 87) groups. The sera from all patients were collected, and seven serum biomarkers were analysed. Then, 120 patients were used to establish a diagnostic model that was built with a binary logistic regression analysis, and 57 patients were used to validate our model. In addition, the area under the receiver operating characteristic (ROC) curve was established. From the seven serum biomarkers, the four serum biomarkers that were selected in to establish the regression model were VEGF, BDNF, IL-6 and IL-1β. The ROC curve of best combined detection was 0.899. The diagnostic ratio of the logistic model was 0.825. This study suggests that the logistic regression model (LRM) and the ROC curve based on patients’ serum levels of VEGF, BDNF, IL-6 and IL-1β is a promising research for diagnosing and choosing the best course of treatment for moderate AD. [ABSTRACT FROM AUTHOR]

Objective: Although the guideline indicates that total kidney volume (TKV) is an important detection indicator in patients with autosomal dominant polycystic kidney disease (ADPKD), this study attempted to demonstrate that renal parenchymal information, combined with parenchymal volume and radiomics features, may have more valuable clinical guiding significance. Methods: A totals of 340 ADPKD patients with normal renal function were prospectively collected and followed-up for five years, with renal function tests and non-contrast computed tomography (CT) performed every six months. The relationship between renal function impairment and renal parenchymal volume (RPV) as along with radiomics features was explored using a multiple linear regression model and multiple logistic regression. Then, a combined model of RPV with radiomics features was constructed to comprehensively evaluate its predictive value. Results: Compared with TKV, decreased RPV presented a closer relationship with renal function impairment, namely, with the impairment rate (RPV: 82.3% vs. TVK: 67.1%) and eGFR (RPV: r = 0.614, p < 0.001 vs. TKV: r = -0.452, p < 0.001), and showed higher predictive power (RPV: AUC = 0.752 [95%CI 0.692–0.805], p < 0.001 vs. TKV: AUC = 0.711 [95%CI 0.649–0.768], p < 0.001). Correspondingly, the radiomics analysis that was derived from the renal parenchyma also showed a satisfactory result (AUC = 0.849 [95%Cl 0.797–0.892], p < 0.001). Importantly, the predictive power for renal function impairment was further improved in the combined model of RPV and radiomics features (AUC = 0.902 [95%Cl 0.857–0.937], p < 0.001). Conclusion: Renal parenchyma information may be a sensitive biomarker of renal function impairment in ADPKD, which can provide a new approach for clinically monitoring renal function, and may greatly improve the pre-hospital prevention and treatment effects. [ABSTRACT FROM AUTHOR]

Although topic detection and tracking techniques have made great progress, most of the researchers seldom pay more attention to the following two aspects. First, the construction of a topic model does not take the characteristics of different topics into consideration. Second, the factors that determine the formation and development of hot topics are not further analyzed. In order to correctly extract news blog hot topics, the paper views the above problems in a new perspective based on the W2T (Wisdom Web of Things) methodology, in which the characteristics of blog users, context of topic propagation and information granularity are investigated in a unified way. The motivations and features of blog users are first analyzed to understand the characteristics of news blog topics. Then the context of topic propagation is decomposed into the blog community, topic network and opinion network, respectively. Some important factors such as the user behavior pattern, opinion leader and network opinion are identified to track the development trends of news blog topics. Moreover, a blog hot topic detection algorithm is proposed, in which news blog hot topics are identified by measuring the duration, topic novelty, attention degree of users and topic growth. Experimental results show that the proposed method is feasible and effective. These results are also useful for further studying the formation mechanism of opinion leaders in blogspace. [ABSTRACT FROM AUTHOR]

Effect of bivalent cation Ca-doping on magnetic properties in multiferroic YMnO3 manganites was systemically studied by DC and AC magnetic measurements. Series of samples were prepared by solid-state reaction method with composition Y1− xCa xMnO3 ( x= i/8, i=2,3,...,7). The results show that each of the zero-field-cooling (ZFC) curves has a clear cusp and it shifts to higher temperature with increasing Ca-doping x. From the χ−1– T curve, the temperature of charge-ordering (CO) state TCO is given at about 244.0 K and this indicates that the CO state is dominated by the cooperative Jahn–Teller effect in Y1/2Ca1/2MnO3 with small A-site cation, for which there is a different behavior compared to the other manganites of larger 〈 r A〉. When x=2/8 and 7/8 for Y1− xCa xMnO3, the magnetization curve shows strong irreversibility between ZFC and FC data. The variation of AC susceptibility presents a maximum cusp at the beginning temperature of the bifurcation between ZFC and ZF curve and shifts to higher temperature with increasing measurement frequency for AC susceptibility. These results can be characterized by spin-glass, indicating that much more itinerant eg electrons are promoting the magnetic transition. [ABSTRACT FROM AUTHOR]

Skeletal muscle fibers are mainly categorized into red and white fiber types, and the ratio of red/white fibers within muscle mass plays a crucial role in meat quality such as tenderness and flavor. To better understand the molecular difference between the two muscle fibers, this study takes advantage of RNA-seq to compare differences in the transcriptome between extensor digitorum longus (EDL; white fiber) and soleus (Sol; red fiber) muscles of large white pigs. In total, 89,658,562 and 46,723,568 raw reads from EDL and Sol were generated, respectively. Comparison between the two transcriptomes revealed 561 differentially expressed genes, with 408 displaying higher and 153 lower levels of expression in Sol. Quantitative real-time polymerase chain reaction validated the differential expression of nine genes. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis discovered several differentially enriched biological functions and processes of the two muscles. Moreover, transcriptome comparison between EDL and Sol identified many muscle-related genes (CSRP3, ACTN2, MYL1, and MYH6) and pathways related to myofiber formation, such as focal adhesion, tight junction formation, extracellular matrix (ECM)-receptor pathway, calcium signaling, and Wnt signaling. In addition, 58,362 and 58,359 single nucleotide polymorphisms were identified in EDL and Sol, respectively, and the sequence of 9069 genes was refined at the 5′, 3′ or both ends. Numerous novel transcripts and alternatively spliced RNAs were also identified. Our transcriptome analysis constitutes valuable sequence resource for uncovering important genes and pathways involved in muscle fiber type determination, and might help further our understanding of the molecular mechanisms in different types of muscle. [ABSTRACT FROM AUTHOR]

GaN thin films and multi-quantum wells (MQWs) were grown on the c-axis patterned sapphire substrates and c-axis flat sapphire substrates by metal organic chemical vapor deposition, respectively. The surface morphology of patterned sapphire substrate and flat sapphire substrate were measured by scanning electron microscopy. The crystal structure of GaN thin films and MQWs were measured by X-ray. The optical performance of MQWs was measured by photoluminescence spectra. The residual stress of GaN thin films was studied. GaN thin films on patterned sapphire substrate has a better crystalline quality in the [102] direction than that on flat sapphire substrate. The residual stress in MQWs on PSS is δ = 1.10 GPa, δ = 0.13 GPa, while the residual stress of films on FSS is δ = 0.83 GPa, δ = 0.10 GPa. It is found that the wavelength becomes shorter and the emission intensity becomes stronger on patterned sapphire substrate. [ABSTRACT FROM AUTHOR]

This paper provides a review of paleoclimate modeling activities in China. Rather than attempt to cover all topics, we have chosen a few climatic intervals and events judged to be particularly informative to the international community. In historical climate simulations, changes in solar radiation and volcanic activity explain most parts of reconstructions over the last millennium prior to the industrial era, while atmospheric greenhouse gas concentrations play the most important role in the 20th century warming over China. There is a considerable model-data mismatch in the annual and boreal winter temperature change over China during the mid-Holocene [6000 years before present (ka BP)], while coupled models with an interactive ocean generally perform better than atmospheric models. For the Last Glacial Maximum (21 ka BP), climate models successfully reproduce the surface cooling trend over China but fail to reproduce its magnitude, with a better performance for coupled models. At that time, reconstructed vegetation and western Pacific sea surface temperatures could have significantly affected the East Asian climate, and environmental conditions on the Qinghai-Tibetan Plateau were most likely very different to the present day. During the late Marine Isotope Stage 3 (30-40 ka BP), orbital forcing and Northern Hemisphere glaciation, as well as vegetation change in China, were likely responsible for East Asian climate change. On the tectonic scale, the Qinghai-Tibetan Plateau uplift, the Tethys Sea retreat, and the South China Sea expansion played important roles in the formation of the East Asian monsoon-dominant environment pattern during the late Cenozoic. [ABSTRACT FROM AUTHOR]

The reduction of hippocampal volume remains controversial in depression because of the variability among individuals in clinical studies. Here, a reliable experimental rat model of depression, established by chronic unpredictable mild stress (CUMS), was used. Thirty rats were randomly divided into two groups (CUMS group and control group). Hippocampal volume was dynamically measured every 2 weeks in a 56-day chronic stress procedure using structural magnetic resonance imaging, and the correlation between the hippocampal volume and the learning and memory changes was investigated. Our results demonstrated that CUMS rats showed significantly smaller volumes of the bilateral hippocampus compared to that of the controls, changing dramatically with the development of CUMS procedure. The left hippocampal volume was reduced earlier and more markedly than the right one from the 2nd week to the 8th week of the CUMS procedure (on the 8th week: left: approximately 15.3 %; right: approximately 8.4 % reduction). Additionally, the hippocampal volume of CUMS rats was significantly negatively correlated with the learning and memory changes. Of note, it showed that the more obviously the hippocampal volume reduced, the more severely the learning and memory damaged. In conclusion, the hippocampal volume decreased gradually and dynamically and was correlated with the impairment of the learning and memory in depression. [ABSTRACT FROM AUTHOR]