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Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, and patients with HCC have a poor prognosis and low survival rates. Establishing a prognostic nomogram is important for predicting the survival of patients with HCC, as it helps to improve the patient’s prognosis. This study aimed to develop and evaluate nomograms and risk stratification to predict overall survival (OS) and cancer-specific survival (CSS) in HCC patients. Data from 10,302 patients with initially diagnosed HCC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2017. Patients were randomly divided into the training and validation set. Kaplan–Meier survival, LASSO regression, and Cox regression analysis were conducted to select the predictors of OS. Competing risk analysis, LASSO regression, and Cox regression analysis were conducted to select the predictors of CSS. The validation of the nomograms was performed using the concordance index (C-index), the Akaike information criterion (AIC), the Bayesian information criterion (BIC), Net Reclassification Index (NRI), Discrimination Improvement (IDI), the receiver operating characteristic (ROC) curve, calibration curves, and decision curve analyses (DCAs). The results indicated that factors including age, grade, T stage, N stage, M stage, surgery, surgery to lymph node (LN), Alpha-Fetal Protein (AFP), and tumor size were independent predictors of OS, whereas grade, T stage, surgery, AFP, tumor size, and distant lymph node metastasis were independent predictors of CSS. Based on these factors, predictive models were built and virtualized by nomograms. The C-index for predicting 1-, 3-, and 5-year OS were 0.788, 0.792, and 0.790. The C-index for predicting 1-, 3-, and 5-year CSS were 0.803, 0.808, and 0.806. AIC, BIC, NRI, and IDI suggested that nomograms had an excellent predictive performance with no significant overfitting. The calibration curves showed good consistency of OS and CSS between the actual observation and nomograms prediction, and the DCA showed great clinical usefulness of the nomograms. The risk stratification of OS and CSS was built that could perfectly classify HCC patients into three risk groups. Our study developed nomograms and a corresponding risk stratification system predicting the OS and CSS of HCC patients. These tools can assist in patient counseling and guiding treatment decision making. [ABSTRACT FROM AUTHOR]

Feature selection refers to a vital function in machine learning and data mining. The maximum weight minimum redundancy feature selection method not only considers the importance of features but also reduces the redundancy among features. However, the characteristics of various datasets are not identical, and thus the feature selection method should have different feature evaluation criteria for all datasets. Additionally, high-dimensional data analysis poses a challenge to enhancing the classification performance of the different feature selection methods. This study presents a kernel partial least squares feature selection method on the basis of the enhanced maximum weight minimum redundancy algorithm to simplify the calculation and improve the classification accuracy of high-dimensional datasets. By introducing a weight factor, the correlation between the maximum weight and the minimum redundancy in the evaluation criterion can be adjusted to develop an improved maximum weight minimum redundancy method. In this study, the proposed KPLS feature selection method considers the redundancy between the features and the feature weighting between any feature and a class label in different datasets. Moreover, the feature selection method proposed in this study has been tested regarding its classification accuracy on data containing noise and several datasets. The experimental findings achieved using different datasets explore the feasibility and effectiveness of the proposed method which can select an optimal feature subset and obtain great classification performance based on three different metrics when compared with other feature selection methods. [ABSTRACT FROM AUTHOR]

In this study, mode I fracture tests on cracked straight-through Brazilian disc (CSTBD) and notched semi-circular bend (NSCB) shale specimens with different sizes were conducted to investigate the difference between maximum tangential stress fracture criterion and the size effect law (SEL) model in predicting apparent fracture toughness (Ka) of shale. In addition, the effects of specimen size and geometry on the Ka and the selection of fracture criterion on the prediction of the inherent fracture toughness (KIc) were also studied. The results show that the Ka increases with the increase of specimen size, and the difference between KIc of shale specimens with different sizes predicted by the fracture process zone length determined by the further improved maximum tangential stress (FIMTS) criterion is the smallest. For the prediction of Ka of NSCB specimen, the results predicted by the FIMTS criterion are the closest to the tested fracture toughness. However, the effect of SEL model applied to the prediction of Ka of NSCB specimens is poor. The effective establishment of SEL model requires high accuracy for test data, especially for the configuration with large variation of the dimensionless stress intensity factor (Y*) with normalized crack length (α). Highlights: Fracture toughness is closely related to the size and configuration of the specimen, which is ultimately attributed to the inconsistent tangential stress distribution at the crack tip. The further improved maximum tangential stress criterion has the best effect on apparent fracture toughness prediction, and higher-order terms of the Williams expansion should be considered in apparent fracture toughness prediction of small-size specimens. The fracture criterion for determining the fracture process zone length should be consistent with the prediction criterion of apparent fracture toughness. The effective establishment of size effect law requires high accuracy tested data, especially for the configuration with large variation of the dimensionless stress intensity factor with normalized crack length. [ABSTRACT FROM AUTHOR]

In order to study the frequency-dependent attenuation characteristics of high-frequency elastic waves in rock-like materials, we conducted high-frequency elastic wave attenuation experiments on marble, granite, and red sandstone rods, and investigated the frequency dependence of the attenuation coefficient of high-frequency elastic waves and the frequency dependence of the attenuation of specific frequency components in elastic waves. The results show that, for the whole waveform packet of the elastic wave signal, the attenuation coefficient and the elastic wave frequency have an approximate power relationship, with the exponents of this power function being 0.408, 0.420, and 0.384 for marble, granite, and red sandstone, respectively, which are close to 1/2 the exponent value obtained theoretically by the Kelvin–Voigt viscoelastic model. However, when the specific frequency components are tracked during the elastic wave propagation, the exponents of the power relationship between the attenuation coefficient and frequency are 0.982, 1.523, and 0.860 for marble, granite, and red sandstone, respectively, which indicate that the relationship between the attenuation coefficient and frequency is rock-type dependent. Through the analysis of rock microstructure, we demonstrate that this rock-type-dependent relationship is mainly caused by the scattering attenuation component due to the small wavelength of the high-frequency elastic wave. Therefore, the scattering attenuation component may need to be considered when the Kelvin–Voigt model is used to describe high-frequency elastic wave attenuation in rock-like materials. The results of this research are of good help for further understanding the attenuation characteristics of high-frequency elastic waves in rock-like materials. [ABSTRACT FROM AUTHOR]

Traffic tunnels are important engineering structures in transportation, and their stability is critical to traffic safety. In particular, when these tunnels are in an earthquake-prone area, the rupture process under seismic excitation needs to be studied in depth for safer tunnel design. In this paper, based on a construction project on the Nairobi-Malaba railway in East Africa, a laboratory shaking table test with 24 working cases of seismic excitation on a mountain tunnel is designed, and the acoustic emission (AE) technique is employed to investigate the tunnel rupture process. The results show that the high frequency components between 20 and 30 kHz of AE signals are the tunnel rupturing signals under the seismic excitation under such conditions. The tunnel vault and the arch foot are prone to rupture during the seismic excitation, and the initial rupture in the arch foot and vault of the tunnel occur under the horizontal and vertical Kobe wave seismic excitation, respectively, with a maximum acceleration of 0.4 g. After the rupture initiation, the tunnel arch foot continues to rupture in the subsequent working cases regardless of whether the excitation direction is horizontal or vertical, while the tunnel vault does not rupture continuously with the implementation of the subsequent excitations. Moreover, the Kobe seismic wave has a higher degree of damage potential to underground structures than the El seismic wave. [ABSTRACT FROM AUTHOR]

The b value is a critical parameter that has been used to describe spatial and temporal size distribution characteristics in data from both natural seismicity and laboratory rock acoustic emission (AE) tests. However, unlike the magnitude used for b value estimation in earthquakes which corrects for hypocentral distance, the apparent amplitude of the AE, is most commonly used for b value estimation in the rock AE test. This ignores the effect of attenuation, which may modify the frequency–amplitude distribution and affect the b value results. Here, we investigate the attenuation effect on the estimate of b value from synthetic data generated by random sampling of a doubly truncated frequency–amplitude distribution and a known underlying b value from a statistical perspective. We generated AE source amplitudes that obey an exponential distribution with different theoretical b values and applied an attenuation operator to obtain apparent frequency–amplitude data for comparison with the true underlying distribution. The results show that the b value is unchanged within a specific interval of amplitude distribution after accounting for attenuation under the conditions examined here, and that data truncation is the primary cause of modification of the frequency–amplitude distribution in the presence of attenuation, rather than attenuation alone. In addition, we employed the same synthetic data simulation scheme to estimate the minimum data volume for accurate estimation of the underlying b value from the apparent amplitude distribution. We found that the determination of the minimum data volume is influenced by the theoretical b value of the underlying distribution: the higher the theoretical b value, the larger the minimum data volume required, varying from 200 events from b  < 1.5 to 300 for b  > 1.5. [ABSTRACT FROM AUTHOR]

The rock mode I fracture characteristics and the size effect are of great significance in understanding the crack initiation, nucleation, propagation, and characterizing the fracture toughness of rocks which is essential for predicting the behavior of rock masses and designing underground structures. In this paper, three-point bending fracture experiments were carried out using single-edge notched beam specimens of different sizes. The fracture characteristics of the entire loading stage, including the post peak stage, were analyzed using digital image correlation (DIC) technology and acoustic emission (AE) technology. Specifically, the calculation of the b value uses the Fisher optimal split and global search algorithm (FGS) method. The results show that both the Fracture process zone (FPZ) length and fracture toughness of granite are size-dependent parameters, and the FPZ length growth rate increases with increasing load level. The failure mode of the source during fracture is mainly tensile failure, and the proportion of tensile failure tends to increase with the increase of specimen size. The temporal b value, average AF value and RA value show corresponding stage changes with time, and the minimum b value, minimum AF value and maximum RA value can characterize the maximum of macroscopic growth rate. • Investigated the size-dependence of post-peak tensile fracture characteristics in granite. • Application of FGS method for calculating acoustic emission b value to analyze the failure scale of specimens. • Tensile failure dominated specimen fractures, with larger specimens showing more tensile failures. • Temporal variations of b value, average frequency, and rise time-to-amplitude ratio reflect changes in corresponding loading stages. [ABSTRACT FROM AUTHOR]

The Gutenberg‐Richter (G‐R) relationship has been regarded as the fundamental description of the size distribution from large‐scale‐earthquake to small‐scale‐laboratory rock ruptures. However, because deviation from the G‐R relationship has often been reported, especially when the amplitude distribution is used for b value estimation in rock acoustic emission testing, the effect of attenuation should be considered. Here, we perform a detailed analysis on the deviation of the size distribution from a G‐R law and discuss modification of the attenuation on the doubly truncated size distribution from a more general perspective. We find that the attenuation will not modify the size distribution, and the b value is theoretically verified to be unchanged within an interval specified by the minimum and maximum amount of attenuation. Based on these discussions, we propose a new b value estimation procedure for rock acoustic emission testing and apply it to a dilation rupturing test; the results confirm that b value depends on material heterogeneity and stress. Plain Language Summary: The Gutenberg‐Richter relationship is an intrinsic characteristic of the frequency‐size distribution of earthquake and laboratory rock ruptures, indicating that the number of small‐scale ruptures is much greater than the number of large‐scale ones. Nevertheless, due to many reasons such as the statistical methods, inadequate data acquisition, and data truncation in cumulative frequency distribution, deviation from a Gutenberg‐Richter relationship of the frequency‐size distribution is inevitable in practice. In order to understand the deviation of the frequency‐size distribution in the laboratory rock fracture testing, we perform a detailed analysis of the statistical methods and the attenuation effect on the Gutenberg‐Richter relationship of the frequency‐size distribution and propose a new procedure for scaling parameter estimation of Gutenberg‐Richter relationship. This newly proposed procedure shows its reliability in a dilation rupturing test and can well ensure the robustness of the scaling parameter estimation. Key Points: The inferred b value for acoustic emission apparent amplitude is equal to that at source irrespective of the form of attenuation lawThe finite size of the sample leads to a finite range of applicability of the Gutenberg‐Richter lawA new method is used to determine the finite range, and its application confirms that b depends on material heterogeneity and stress [ABSTRACT FROM AUTHOR]

As an extension of partial least squares (PLS), kernel partial least squares (KPLS) is an very important methods to find nonlinear patterns from data. However, the application of KPLS to large-scale problems remains a big challenge, due to storage and computation issues in the number of examples. To address this limitation, we utilize randomness to design scalable new variants of the kernel matrix to solve KPLS. Specifically, we consider the spectral properties of low-rank kernel matrices constructed as sums of random feature dot-products and present a new method called randomized kernel partial least squares (RKPLS) to approximate KPLS. RKPLS can alleviate the computation requirements of approximate KPLS with linear space and computation in the sample size. Theoretical analysis and experimental results show that the solution of our algorithm converges to exact kernel matrix in expectation. [ABSTRACT FROM AUTHOR]

• The size dependence of ECP length and apparent or equivalent fracture toughness is proved theoretically by Bažant's SEL. • The CSTBD sample with normalized crack length of 0.4 is recommended for testing rock fracture toughness. • Using FPZ length instead of ECP length will overestimate the equivalent fracture energy of the sample. • The ratio of ECP length to FPZ length decreases with the increase of sample size and converges to a fixed value. Purpose of this research is to apply the Bažant's size effect law to investigate the effects of material properties, specimen size, normalized crack length and loading span on the equivalent crack propagation (ECP) length and fracture energy test results of cracked straight through Brazilian disc (CSTBD) specimens and notch semi-circular bend (NSCB) specimens, and to clarify the relationship between ECP length and fracture process zone (FPZ) length. The results indicate that the ECP length is positively correlated with the specimen radius, c f (the ECP length of the infinite-size specimen) and the loading span, and the influence of the normalized crack length on the ECP length has the dependence of specimen configuration. Both the apparent fracture energy and the equivalent fracture energy have size effect, and the fracture energy tested by the specimen with smaller c f are more reliable. Based on the analysis of the influence of normalized crack length and loading span on fracture energy test results, CSTBD specimen with normalized crack length of 0.4 is recommended for rock fracture toughness test. In addition, the FPZ length determined by digital image correlation technique is more accurate than that determined by stress intensity factor method and finite element model method, and the ratio of ECP length to FPZ length decreases with the increase of specimen size. [ABSTRACT FROM AUTHOR]

Cognitive defects in autism spectrum disorder (ASD) include socialization and communication: key behavioral capacities that separate humans from other species. Here, we analyze gene expression in the prefrontal cortex of 63 autism patients and control individuals, as well as 62 chimpanzees and macaques, from natal to adult age. We show that among all aberrant expression changes seen in ASD brains, a single aberrant expression pattern overrepresented in genes involved synaptic-related pathways is enriched in nucleotide variants linked to autism. Furthermore, only this pattern contains an excess of developmental expression features unique to humans, thus resulting in the disruption of human-specific developmental programs in autism. Several members of the early growth response (EGR) transcription factor family can be implicated in regulation of this aberrant developmental change. Our study draws a connection between the genetic risk architecture of autism and molecular features of cortical development unique to humans. [ABSTRACT FROM AUTHOR]

What evolutionary events led to the emergence of human cognition? Although the genetic differences separating modern humans from both non-human primates (for example, chimpanzees) and archaic hominins (Neanderthals and Denisovans) are known, linking human-specific mutations to the cognitive phenotype remains a challenge. One strategy is to focus on human-specific changes at the level of intermediate phenotypes, such as gene expression and metabolism, in conjunction with evolutionary changes in gene regulation involving transcription factors, microRNA and proximal regulatory elements. In this Review we show how this strategy has yielded some of the first hints about the mechanisms of human cognition. [ABSTRACT FROM AUTHOR]

Abstract: Evolutionary conservation of neighbouring gene pairs has been widely explored in many species, but remains poorly understood in plants. The availability of several plant genome sequences allows for an in-depth investigation of this problem in plants. Here, we analyzed the phylogenetic conservation of physically linked gene pairs in nine plant genomes and compared the conservation in different orientations. We also examined several potential determinants to detect whether they affect the conservation of neighbouring gene pairs. Our results suggested that among the three types of neighbouring gene pairs, closely linked parallel pairs might be the least conserved. Intergenic distance was shown to be a major determinant of linkage conservation, suggesting that the conservation of gene order in plants was determined primarily by chance. The enrichment of housekeeping genes was identified to contribute to the conservation of all three types and the enrichment of genes involved in protein metabolism might contribute to the conservation of parallel pairs. Moreover, a co-expressed signal was detected in conserved divergent pairs, which might be determined by intergenic distance. [Copyright &y& Elsevier]

Monozygotic (MZ) twins are theoretically genetically identical. Although they are revealed to accumulate mutations after the zygote splits, discriminating between twin genomes remains a formidable challenge in the field of forensic genetics. Single-nucleotide variants (SNVs) are responsible for a substantial portion of genetic variation, thus potentially serving as promising biomarkers for the identification of MZ twins. In this study, we sequenced the whole genome of a pair of female MZ twins when they were 27 and 33 years old to approximately 30 × coverage using peripheral blood on an Illumina NovaSeq 6000 Sequencing System. Potentially discordant SNVs supported by whole-genome sequencing were validated extensively by amplicon-based targeted deep sequencing and Sanger sequencing. In total, we found nine bona fide post-twinning SNVs, all of which were identified in the younger genomes and found in the older genomes. None of the SNVs occurred within coding exons, three of which were observed in introns, supported by whole-exome sequencing results. A double-blind test was employed, and the reliability of MZ twin discrimination by discordant SNVs was endorsed. All SNVs were successfully detected when input DNA amounts decreased to 0.25 ng, and reliable detection was limited to seven SNVs below 0.075 ng input. This comprehensive analysis confirms that SNVs could serve as cost-effective biomarkers for MZ twin discrimination. [ABSTRACT FROM AUTHOR]

A few production errors were found since the publication of the article. S SP T sp of key material parameters at different frequencies and times in the time-frequency model. [Extracted from the article]

The ultrasonic backscatter signal can be used to evaluate the grain size of polycrystalline media nondestructively. In this article, the joint time-frequency analysis is introduced into the ultrasonic backscatter model, with the independent scattering approximation. The time-frequency domain model is applied to predict the spatial variance surface (SVS) and fit the experimental results to evaluate the grain size with the approach giving a relative error of 2.26% in comparison with metallography. Moreover, it shows that the present method suppresses electrical noise better than either the time domain or the frequency domain models alone. Based on the global sensitivity analysis of Sobol's method, the sensitivities of transducer parameters and material parameters in the ultrasonic backscatter model are estimated. The sensitivity analysis shows that not all the transducer parameters in the model must be calibrated carefully. In addition, it is found that the grain size sensitivity index of the time-frequency backscatter model is higher than the time domain or the frequency-domain backscatter models. Overall, the backscatter model in the time-frequency domain can evaluate the microstructure more accurately. • Ultrasonic backscatter data are analyzed with the short-time Fourier transform. • Time-frequency backscatter model is developed for grain sizing. • The present model with Hanning window reduces the influence of electrical noise. • The parameter sensitivities in the model are quantified by Sobol's method. • The present method is more sensitive to the grain size than traditional methods. [ABSTRACT FROM AUTHOR]

To explore the variation in rock acoustic emission (AE) characteristics with strain rate, uniaxial compression tests at different loading rates and impact loading tests were conducted on granite using a MTS322 rock mechanical test system and split Hopkinson pressure bar (SHPB) system, respectively. The effect of the strain rate on the AE characteristic parameters, rock fracture properties, and destruction evolution were systematically analyzed. The results demonstrated that with increasing strain rate, the cumulative AE count decreases as a power function, and the variation between the cumulative AE count and strain rate can be fitted log-linearly with a slope of 0.48. The peak frequencies of the AE signals are mostly distributed in the zones of 0–100 kHz, 175–250 kHz, and 400–550 kHz. The signal proportion in the 0–100 kHz zone gradually increases with strain rate, while the signal proportions in the 175–250 kHz and 400–550 kHz zone exhibit decreasing trends. A transition of a sudden increase in the RA -value and decrease in the AF -value occurs when the stress reaches a certain level, and the stress level corresponding to this transition will increase with strain rate. Meanwhile, the RA–AF distribution is mostly concentrated on the abscissa in the low strain rate tests, but gradually concentrates on the longitudinal axis as the strain rate increases. This indicates that tensile cracking becomes the dominant fracture mode with increasing strain rate. The b -value decreases with increasing strain rate in the uniaxial compression tests; however, the b -value in the impact loading tests is higher than that in the uniaxial compression tests. Furthermore, to distinguish the signals generated by stress wave propagation from the signals generated by rock fracturing in the impact loading tests, a four-parameter k -means algorithm is used to conduct a clustering analysis. The results indicate that the signals can be classified into four clusters: tensile fracturing signals (cluster A), mixed stress wave and shear fracture signals (cluster B), mixed stress wave and tensile fracture signals (cluster C), and stress wave signals (cluster D). [ABSTRACT FROM AUTHOR]

There is increasing evidence that miRNAs play an important role in the prognosis of HCC. There is currently a lack of acknowledged models that accurately predict patient prognosis. The aim of this study is to create a miRNA-based model to precisely forecast a patient's prognosis and a miRNA–mRNA network to investigate the function of a targeted mRNA. TCGA miRNA dataset and survival data of HCC patients were downloaded for differential analysis. The outcomes of variance analysis were subjected to univariate and multivariate Cox regression analyses and LASSO analysis. We constructed and visualized prognosis-related models and subsequently used violin plots to probe the function of miRNAs in tumor cells. We predicted the target mRNAs added those to the String database, built PPI protein interaction networks, and screened those mRNA using Cytoscape. The hub mRNA was subjected to GO and KEGG analysis to determine its biological role. Six of them were associated with prognosis: hsa-miR-139-3p, hsa-miR-139-5p, hsa-miR-101-3p, hsa-miR-30d-5p, hsa-miR-5003-3p, and hsa-miR-6844. The prognostic model was highly predictive and consistently performs, with the C index exceeding 0.7 after 1, 3, and 5 years. The model estimated significant differences in the Kaplan–Meier plotter and the model could predict patient prognosis independently of clinical indicators. A relatively stable miRNA prognostic model for HCC patients was constructed, and the model was highly accurate in predicting patients with good stability over 5 years. The miRNA–mRNA network was constructed to explore the function of mRNA. [ABSTRACT FROM AUTHOR]

Investigations on flaw responses can benefit the nondestructive testing of cylinders using line-focused transducers. In this work, the system function, the wave beam model, and a flaw scattering model are combined to develop an ultrasonic measurement model for line-focused transducers to predict flaw responses in cylindrical components. The system function is characterized using reference signals by developing an acoustic transfer function for line-focused transducers, which works at different distances for both planar and curved surfaces. The wave beams in cylindrical components are modeled using a multi-Gaussian beam model, where the effects of wave mode conversion and curvatures of cylinders are considered. Simulation results of wave beams are provided to analyze their propagation behaviors. The proposed ultrasonic measurement model is certified from good agreement between the experimental and predicted signals of side-drilled holes. This work provides guidance for evaluating the detection ability of line-focused transducers in cylindrical component testing applications. [ABSTRACT FROM AUTHOR]

Graphs have been widely applied in many real applications like knowledge mining of social networks, pattern recognition, biological analysis, etc. However, precise matching for large graphs has been proven to be a NP-hard problem. In the context, an efficient similarity join method is proposed to quickly seek similar candidate graph pairs from a large number of graphs in the paper. It is a new method, where local sensitive hash (LSH) and Minhash are used to sharply reduce the time needed to compare candidate graph pairs as well as improve the quality of similarity matching through graph associated vertex degree matrix. Furthermore, the bound filtering strategy is adopted to avoid invalid comparing between graph pairs, which can improve graph similarity join efficiency. To test the advantages of our method, various experiments on synthetic data and real data were conducted. The results of these experiments illustrate that the method in this paper has both good efficiency and effectiveness. In terms of the running time and the precision of the algorithm, the new method yields better results than the other similar methods. [ABSTRACT FROM AUTHOR]

Background: Changes in gene expression levels during brain development are thought to have played an important role in the evolution of human cognition. With the advent of high-throughput sequencing technologies, changes in brain developmental expression patterns, as well as human-specific brain gene expression, have been characterized. However, interpreting the origin of evolutionarily advanced cognition in human brains requires a deeper understanding of the regulation of gene expression, including the epigenomic context, along the primate genome. Here, we used chromatin immunoprecipitation sequencing (ChIP-seq) to measure the genome-wide profiles of histone H3 lysine 4 trimethylation (H3K4me3) and histone H3 lysine 27 acetylation (H3K27ac), both of which are associated with transcriptional activation in the prefrontal cortex of humans, chimpanzees, and rhesus macaques. Results: We found a discrete functional association, in which H3K4me3HP gain was significantly associated with myelination assembly and signaling transmission, while H3K4me3HP loss played a vital role in synaptic activity. Moreover, H3K27acHP gain was enriched in interneuron and oligodendrocyte markers, and H3K27acHP loss was enriched in CA1 pyramidal neuron markers. Using strand-specific RNA sequencing (ssRNA-seq), we first demonstrated that approximately 7 and 2% of human-specific expressed genes were epigenetically marked by H3K4me3HP and H3K27acHP, respectively, providing robust support for causal involvement of histones in gene expression. We also revealed the co-activation role of epigenetic modification and transcription factors in human-specific transcriptome evolution. Mechanistically, histone-modifying enzymes at least partially contribute to an epigenetic disturbance among primates, especially for the H3K27ac epigenomic marker. In line with this, peaks enriched in the macaque lineage were found to be driven by upregulated acetyl enzymes. Conclusions: Our results comprehensively elucidated a causal species-specific gene-histone-enzyme landscape in the prefrontal cortex and highlighted the regulatory interaction that drove transcriptional activation. [ABSTRACT FROM AUTHOR]

• The equivalent fracture toughness determined by the equivalent energy method has obvious rate dependency effect. • The change of the axial displacement of the specimen at high loading rate is more from the deformation caused by the mutual extrusion of materials. • There is a good linear relationship between b value estimated by using Fisher optimal split and Global Search algorithm and equivalent fracture toughness. The loading rate effect is an important mechanical property affecting the failure mechanism of rock materials. In this paper, the effect of loading rate on the mode I fracture characteristics of granite was studied by using Cracked Straight Through Brazilian Disc (CSTBD) specimen. The acoustic emission (AE) and Digital Image Correlation (DIC) techniques were used to monitor the fracture behavior of the specimen. Due to the nonlinearity of specimen deformation, the tested fracture toughness was corrected by equivalent energy method. The test results show that the equivalent fracture toughness has obvious rate dependency effect. Meanwhile, the crack tip opening displacement increases with the increase of the loading rate at low loading rate, and decreases with the increase of the loading rate when the loading rate reaches a certain value. The AE results show that the relationship between the cumulative energy of AE signals and the loading time can be well fitted by the power-law function, and the power exponent gradually decreases with the increase of loading rate. Moreover, b value decreases with the increase of loading rate, and there is a negative linear correlation between b value and fracture toughness. These indicate that with the increase of loading rate, the cracking process of the specimen gradually changes from that dominated by small-scale failure to that dominated by large-scale failure, and more fracture energy is needed for instability failure of specimens. In addition, the relationship between b value and fracture toughness can provide the possibility for estimating the equivalent fracture toughness of the material by the b value obtained from the AE test. [ABSTRACT FROM AUTHOR]

The accurate determination of fracture toughness (KIc) in rock is of great significance to the study of rock fracture characteristics. However, the effect of contact friction in the loading process on the test results of fracture toughness is rarely considered, and the tested KIc in previous studies is generally higher than the inherent KIc of the material. Based on the ABAQUS software, the influence of friction on the test results of KIc was investigated under different material elastic moduli, loading conditions and specimen sizes by the finite element analysis in this study. The results show that for the specimen with the notch semi-circular bend configuration, if the presence of friction is considered, the changes of load level, the span of roller support and the specimen size can significantly affect the test results of fracture toughness, except the elastic modulus of the material; if the influence of friction is not considered, there will be a large deviation in the research results of the size effect of fracture toughness in rock. As the friction coefficient increases, the estimated value of the fracture energy increases, while the fracture process zone length decreases for the specimen with an infinite size. [ABSTRACT FROM AUTHOR]

The rock acoustic emission (AE) technique has often been used to study rock destruction properties and has also been considered an important measure for simulating earthquake foreshock sequences. Among them, the AE b value is an essential parameter for the size distribution characteristics and probabilistic hazard analysis of rock fractures. Variations in b values obtained in rock AE tests and earthquakes are often compared to establish analogies in the damage process and precursory analysis. Nevertheless, because the amplitudes measured on the sample boundary by an acoustic sensor (apparent amplitude) are often used to estimate the b value, which cannot descript the source size distribution, it is necessary to develop a method to obtain the size distribution characteristics of the real source from the apparent amplitude in doubly truncated distribution. In this study, we obtain AE apparent amplitudes by applying an attenuation operator to source amplitudes generated by a computer with an underlying exponential distribution and then use these simulated apparent amplitudes to perform a comparative analysis of various b value estimation methods that are used in earthquakes and propose an optimal b value estimation procedure for rock AE tests through apparent amplitudes. To further verify the reliability of the newly proposed procedure, a b value characteristics analysis was carried out on a non-explosive expansion agent rock AE test and transparent refractive index experiment with red sandstone, marble, granite, and limestone. The results indicate that mineral grains of different sizes and compositions and different types of discontinuities of rock specimens determine the rock fracture characteristics, as well as the b value. The dynamic b values decreased linearly during the loading process, which confirms that variations in the b value also depend on the stress. These results indicate that the newly proposed procedure for estimating the b value in rock AE tests based on apparent amplitudes has high reliability. [ABSTRACT FROM AUTHOR]

The b value deduced from the Gutenberg–Richter law is an important parameter for sequence and precursory analyses, both in laboratory acoustic emission tests and seismology. As the b value is a statistical value, the maximum likelihood estimation is mostly used to estimate the b value. However, traditional singly truncated maximum likelihood estimation in seismology only considers the minimum magnitude, while the acquisition device in rock acoustic emission tests will set the threshold value and maximum value of the amplitude; therefore, maximum likelihood estimation will estimate the b value in a doubly truncated size distribution, and its confidence limits need to be discussed. Here, in this study, we derive the calculation equations of the b value and the corresponding confidence limits for the maximum likelihood estimation with a narrow amplitude span in a doubly truncated frequency–amplitude distribution. The maximum likelihood b values estimated by the scheme of a singly and doubly truncated frequency–amplitude distribution are compared through acoustic emission data with the known underlying distribution. The results show that the maximum likelihood b value and confidence limits estimation scheme derived for rock acoustic emission tests with a narrow amplitude span is more reasonable. Then, the derived estimation scheme is applied to the rock dilation rupturing test; the results confirm its applicability. [ABSTRACT FROM AUTHOR]

The accurate determination of fracture toughness (KIc) in rock is of great significance to the study of rock fracture characteristics. However, the effect of contact friction in the loading process on the test results of fracture toughness is rarely considered, and the tested KIc in previous studies is generally higher than the inherent KIc of the material. Based on the ABAQUS software, the influence of friction on the test results of KIc was investigated under different material elastic moduli, loading conditions and specimen sizes by the finite element analysis in this study. The results show that for the specimen with the notch semi-circular bend configuration, if the presence of friction is considered, the changes of load level, the span of roller support and the specimen size can significantly affect the test results of fracture toughness, except the elastic modulus of the material; if the influence of friction is not considered, there will be a large deviation in the research results of the size effect of fracture toughness in rock. As the friction coefficient increases, the estimated value of the fracture energy increases, while the fracture process zone length decreases for the specimen with an infinite size. [ABSTRACT FROM AUTHOR]

• Five failure stages of rock were divided by accumulative AE hits line method, and crack closure stress (σ cc ), crack initiation stress (σ ci ) and crack damage stress (σ cd ) were determined. • A criterion for crack classification is proposed based on AE spectral parameters (Ad, FW), and a straight line dividing tensile and shear cracks was obtained in the density map of RA-AF.. • Based on the evolution characteristics of crack scale and type, the failure modes of different rocks were determined and verified by the failure images. This study aimed to investigate the crack evolution and failure mechanism of rocks by conducting uniaxial compression tests (UCT) and Brazilian indirect tension tests (BITT) using four categories of rock specimens. Real-time acoustic emission (AE) signals were detected and recorded during rock failure processes by an AE monitoring system. The study focused on the accumulative AE hits curves, stress–strain curves, and other AE energy characteristics to divide the failure process into five stages, and determine the stress thresholds. Furthermore, the transition trend of rock crack types was analyzed based on RA-AF data. A novel classification criterion of crack types based on clustering and statistical theory was proposed, and the crack boundaries of the four rocks were determined. Additionally, the tension to shear ratios of the rocks in descending order were fine-grained granite, granite, yellow sandstone, and white sandstone. Finally, the crack development trend and failure characteristics of the rock were analyzed using the crack scale and crack dividing line. The study found that the failure mode of the rock could be predicted accurately by AE parameter analysis at Unstable Crack Growth (Stage-IV). [ABSTRACT FROM AUTHOR]

Background. In this study, the whole exome sequencing in human aortic dissection, a highly lethal cardiovascular disease, was investigated to explore the aortic dissection-associated genes and variants in Chinese population. Methods. Whole exome sequencing was performed in 99 cases of aortic dissection. All single nucleotide polymorphisms (SNPs), insertions/deletions (InDels), and copy number variations (CNVs) were filtered to exclude the benign variants. Enrichment analysis and disease-gene correlation analysis were performed. Results. 3425873 SNPs, 685245 InDels, and 1177 CNVs were identified, and aortic dissection-associated SNPs, InDels, and CNVs were collected. After the disease correlation analysis, 20 candidate genes were identified. Part of these genes such as MYH11, FBN1, and ACTA2 were consistent with previous studies, while MLX, DAB2IP, EP300, ZFYVE9, PML, and PRKCD were newly identified as candidate aortic dissection-associated genes. Conclusion. The pathogenic and likely pathogenic variants in most of AD-associated genes (FBN1, MYH11, EFEMP2, TGFBR2, FBN2, COL3A1, and MYLK) were identified in our cohort study, and pathogenic CNVs involved in MYH11, COL family, and FBN were also identified which are not detectable by other NGS analysis. The correlation between MLX, DAB2IP, EP300, ZFYVE9, PML, PRKCD, and aortic dissection was identified, and EP300 may play a key role in AD. [ABSTRACT FROM AUTHOR]

Aiming to aid Electric-Power Industry to accurately understand users, hybrid learning model based ensemble learning algorithms for recognizing user to be sensitive to electric charge is proposed in this paper. On the basis of big data presented by CCF competition sponsor in China, with some excellent technology or algorithm such as JieBa, SFFS, etc., we extract many key features from data set and successfully draw a portrait for users who pay close attention to electric charge. Furthermore, machine learning algorithms and the strategy selection model related to them are investigated. The feasibility that hybrid learning model combining several ensemble learning algorithms can substantially improve classification accuracy are proved from theoretical level. Then the details of implementing hybrid learning model are described in the paper. Lastly, the hybrid learning model named Stacking is achieved, which yields better performance in contrast to the state-of-the-art competitors. The experimental results indicate that Stacking has both high precision and recall with 0.8 and 0.85 respectively. Furthermore the F1 score of Stacking evaluation is 0.823. [ABSTRACT FROM AUTHOR]

Abstract This paper reports the further study carried out by the authors on the technique of long-hole raising in one blast. In the previous work reporting the results of preliminary study, method of vertical crater retreat (VCR) multiple-deck shots with different and smaller slice heights was used to excavate the raise in one blast. A 32-m raise in the cover of an abandoned cavity was successfully broken through. In this paper, an improved technique is suggested to overcome the overbreak and freezing in a long-hole raising blast. In the raising process, long-hole presplitting is first performed at the periphery of the blasting pattern, and then inner VCR multiple-deck shots with the same slice height are conducted according to a specific initiation sequence without in-slice delays. The previously calibrated numerical model is used to simulate the blasting process. The rock mass behaviours and the raising mechanisms are examined. It is shown that after the introduction of long-hole presplitting, the overbreak and freezing are greatly relieved, and the direction of advance and timing pattern are vitally responsible for the evolution of rock damage. This suggested technique was then applied to field raising blasts, and a 29-m raise and a 24-m raise under special cavity conditions were successfully developed. It demonstrates that, compared to the method of purely VCR multiple-deck shots, the design process can be greatly simplified and the present technique leads to better blasting performances. [ABSTRACT FROM AUTHOR]

We investigated the slow release of Zn ion (Zn2+) from nanocoatings and compared the in vitro response of osteoblasts (MC3T3-E1) and proosteoclasts (RAW 264.7) cultured on Ca2ZnSi2O7 nanocoated with different Zn/Ca molar ratios on a Ti-6Al-4V (i.e., Ti) substrate to optimize cell behaviors and molecule levels. Significant morphology differences were observed among samples. By comparing with pure Ti and CaSiO3 nanocoating, the morphology of Ca2ZnSi2O7 ceramic nanocoatings was rough and contained small nanoparticles or aggregations. Slow Zn2+ release from nanocoatings was observed and Zn2+ concentration was regulated by varying the Zn/Ca ratios. The cell-response results showed Ca2ZnSi2O7 nanocoating at different Zn/Ca molar ratios for osteoblasts and osteoclasts. Compared to other nanocoatings and Ti, sample Zn/Ca (0.3) showed the highest cell viability and upregulated expression of the osteogenic differentiation genes ALP, COL-1, and OCN. Additionally, sample Zn/Ca (0.3) showed the greatest inhibition of RAW 264.7 cell growth and decreased the mRNA levels of osteoclast-related genes OAR, TRAP, and HYA1. Therefore, the optimal Zn-Ca ratio of 0.3 in Ca2ZnSi2O7 ceramic nanocoating on Ti had a dual osteoblast-promoting and osteoclast-inhibiting effect to dynamically balance osteoblasts/osteoclasts. These optimal Zn-Ca ratios are valuable for Ca2ZnSi2O7 ceramic nanocoating on Ti-coated implants for potential applications in bone tissue regeneration. [ABSTRACT FROM AUTHOR]

• The effects of dry, natural, and water saturated conditions on the mechanical characteristics and crack propagation behaviour of red sandstone with different rock bridge lengths were investigated. • The water content and rock bridge length have conspicuous effects on the compressive strength, elastic modulus, temporal b value, P-wave velocity, and crack propagation model. • The weakening effect of water will promote the deterioration of the microstructure of rock. To comprehensively investigate the effect of water content on the crack propagation characteristics and fracture mechanism of jointed rock, uniaxial compression experiments were conducted on red sandstone specimens under different water content conditions and different bridge lengths. Acoustic emission (AE) techniques and digital image correlation (DIC) methods were applied to record the AE signals and deformation field of the specimens during the testing. The physical and mechanical properties, crack propagation characteristics and AE parameters of red sandstone under water–rock coupling were analysed. The results demonstrated that the water content and rock bridge length have conspicuous effects on the compressive strength, elastic modulus, temporal b value, P-wave velocity, and crack propagation model. The fracture initiates from the lowest pre-fabricated crack and the fracture mode gradually changes from shear to tensile fracture with the increase of the rock bridge length. Additionally, the micro-structure of the sandstone develops from a relatively dense pore cement structure to an irregular honeycomb structure. And the deterioration of the rock strength parameters could refer to the pore pressure generated by free water. [ABSTRACT FROM AUTHOR]

In this study, we investigated the failure process and evolution mechanisms in circular tunnels under a complex stress path of deep in-situ stress + excavation unloading + stress adjustment using a simulation test based on loading first and then drilling (LFTD) mode. This test was performed on cubic sandstone specimens using a true-triaxial testing system combined with a self-developed drilling unloading test device. For comparison, another set of sandstone specimens, similar to the original specimens but with Φ 25 mm circular through-holes, were processed to perform another set of simulation tests based on drilling first and then loading (DFTL) mode. Under constant lateral stress, compared with the DFTL test, the initial failure vertical stress was lower, and the surrounding rock was more prone to failure in the LFTD test, indicating that drilling unloading causes damage to the surrounding rock, thereby inducing a strength-weakening effect. Under constant lateral and vertical stresses, sidewall failure in the LFTD test was more severe. The sidewall's initial failure vertical stress difference between the LFTD and DFTL tests increases with increasing lateral stress or initial hydrostatic pressure. The effect of drilling unloading becomes more apparent under a higher initial stress state. Comparing the same types of simulation tests under different stress states, the initial failure vertical stress increases with the lateral stress or initial hydrostatic pressure, inducing a strength-strengthening effect in the surrounding rock. Comparing the strength-strengthening effect caused by increasing the lateral pressure or initial hydrostatic pressure and the strength-weakening effect caused by drilling unloading shows that the strength-strengthening effect is more evident. [ABSTRACT FROM AUTHOR]

Summary Lipids are prominent components of the nervous system. Here we performed a large-scale mass spectrometry-based analysis of the lipid composition of three brain regions as well as kidney and skeletal muscle of humans, chimpanzees, rhesus macaques, and mice. The human brain shows the most distinct lipid composition: 76% of 5,713 lipid compounds examined in our study are either enriched or depleted in the human brain. Concentration levels of lipids enriched in the brain evolve approximately four times faster among primates compared with lipids characteristic of non-neural tissues and show further acceleration of change in human neocortical regions but not in the cerebellum. Human-specific concentration changes are supported by human-specific expression changes for corresponding enzymes. These results provide the first insights into the role of lipids in human brain evolution. Video Abstract [ABSTRACT FROM AUTHOR]

The acoustic emission b value is an important and widely used parameter for the early prediction of rock fractures. In this study, five groups of true triaxial compression tests were conducted on granite specimens to analyze changes in b value during the process of rock failure, and to investigate the b value characteristics of acoustic emission events. First, the acoustic emission events that simultaneously triggered at least four sensors were located using P-wave arrivals and sensor coordinates. Then, considering various intervals of acoustic emission event counts, stress magnitude, and stress proportion, b values were calculated using the values of the maximum amplitude, average amplitude, maximum absolute energy, and average absolute energy of the acoustic emission events. In addition, the goodness of the fitting curves was used to evaluate the fitting reliability of the b values. The results indicated higher accuracy of b value when calculated using the average amplitude setting for intervals of acoustic emission event counts of 200 or greater, stress magnitude of 20 MPa or greater, and stress proportion of 10% or greater. Moreover, the interval of event counts of 200 is suggested as a window parameter for b value calculations, and the b values are observed to exhibit a decreasing trend before fracture for more than 80% of the specimens. Furthermore, the b value tends to decrease with an increase in confining pressure. Thus, the b value can be used as an indicator for validating the stress concentration area, including magnitudes and accumulative probability density distribution of events, which is a beneficial complement to clarifying precursor information of rock mass instability. [ABSTRACT FROM AUTHOR]

: Accelerated evolution of the human brain and muscle metabolomes reflects our unique cognitive and physical capacities. [ABSTRACT FROM AUTHOR]

• CNN investigation for subwavelength ultrasonic imaging at low SNR. • No flaw echoes are needed in training, only structural noise signals. • Distinguishing flaw echoes from the background of structural noise by CNN. • Imaging subwavelength flaws in complex structural materials. Subwavelength ultrasonic imaging (SUI) can detect subwavelength flaws beyond the diffraction limit, however, SUI sometimes fails to clearly reveal flaws in C-scans when the signal-to-noise ratio (SNR) is low. In this work, a convolutional neural network (CNN) that takes structural noise into account is developed for SUI to distinguish flaw echoes from structural noise. The network contains a regression CNN for learning features from the structural noise and a learnable soft thresholding layer for classification. Experiments show that the proposed method performs well for imaging subwavelength flaws at different depths and of different sizes. It achieved an F 1 score of 97.69 ± 1.56% in detecting flaws as compared to the enhanced ultrasonic flaw detection method with time-dependent threshold. As an example of general application of the method, we also performed SUI on natural flaws in a spheroidal graphite cast iron specimen. The results show that the method can achieve SUI without a theoretical backscattering model and is not limited by noise distribution, multiple scattering, or complex microstructures. Furthermore, the network does not need to prepare flaw echoes for training. [ABSTRACT FROM AUTHOR]

What evolutionary events led to the emergence of human cognition? Although the genetic differences separating modern humans from both non-human primates (for example, chimpanzees) and archaic hominins (Neanderthals and Denisovans) are known, linking human-specific mutations to the cognitive phenotype remains a challenge. One strategy is to focus on human-specific changes at the level of intermediate phenotypes, such as gene expression and metabolism, in conjunction with evolutionary changes in gene regulation involving transcription factors, microRNA and proximal regulatory elements. In this Review we show how this strategy has yielded some of the first hints about the mechanisms of human cognition. [ABSTRACT FROM AUTHOR]

The traditional heterogeneous embedding method based on a random walk strategy does not focus on the random walk fundamentally because of higher-order Markov chains. One of the important properties of Markov chains is stationary distributions (SDs). However, in large-scale network computation, SDs are not feasible and consume a lot of memory. So, we use a non-Markovian space strategy, i.e., a heterogeneous personalized spacey random walk strategy, to efficiently get SDs between nodes and skip some unimportant intermediate nodes, which allows for more accurate vector representation and memory savings. This heterogeneous personalized spacey random walk strategy was extended to heterogeneous space embedding methods in combination with vector learning, which is better than the traditional heterogeneous embedding methods for node classification tasks. As an excellent embedding method can obtain more accurate vector representations, it is important for the improvement of the recommendation model. In this article, recommendation algorithm research was carried out based on the heterogeneous personalized spacey embedding method. For the problem that the standard random walk strategy used to compute the stationary distribution consumes a large amount of memory, which may lead to inefficient node vector representation, we propose a meta-path-based heterogenous personalized spacey random walk for recommendation (MPHSRec). The meta-path-based heterogeneous personalized spacey random walk strategy is used to generate a meaningful sequence of nodes for network representation learning, and the learned embedded vectors of different meta-paths are transformed by a nonlinear fusion function and integrated into a matrix decomposition model for rating prediction. The experimental results demonstrate that MPHSRec not only improves the accuracy, but also reduces the memory cost compared with other excellent algorithms. [ABSTRACT FROM AUTHOR]