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This study was designed to develop a sensitive and reliable RP-HPLC method for the separation of aerial parts ofJologbo. Different extraction methods were used and compared to obtain the maximum number of constituents. Different chromatographic conditions were optimized to achieve optimum separation. A total of 98 peaks were obtained in the optimized separation method. Seasonal variation and difference in chemical composition among aerial parts of the plant were evaluated. Significant difference in the chemical composition was observed and statistical data processing supported the results. The correlation coefficient and vector cosine were calculated by chemometric analysis to evaluate peak retention times, peak areas, and peak heights between various batches (using selected peaks) which showed good repeatability. Gallic and protocatechuic acids were identified from the plant and their intra-day and inter-day repeatability values were calculated and convincing results were obtained. [ABSTRACT FROM AUTHOR]

The traditional Langmuir equation displays drawback in accurately characterizing the methane adsorption behavior in coal, due to it assuming the uniform surface of coal pores. Additionally, the decay law of gas adsorption capacity with an increasing coal reservoir temperature remains unknown. In this study, the fractal adsorption model is proposed based on the fractal dimension (Df) of coal pores and the attenuation coefficient (n) of the adsorption capacity. The principles and methods of this fractal adsorption model are deduced and summarized in detail. The results show that the pore structures of the two coal samples exhibit obvious fractal characteristics, with the values of fractal dimensions (Df) being 2.6279 and 2.93. The values of adsorption capacity attenuation coefficients (n) are estimated as −0.006 and −0.004 by the adsorption experiments with different temperatures. The proposed fractal adsorption model presents a greater theoretical significance and higher accuracy than that of the Langmuir equation. The accuracy of the fractal adsorption model with temperature effect dependence is verified, establishing a prediction method for methane adsorption capacity in deep coal reservoirs. This study can serve as a theoretical foundation for coalbed methane exploration and development, as well as provide valuable insights for unconventional natural gas exploitation. [ABSTRACT FROM AUTHOR]

Zheng Guanying paid close attention to the issue of the spread of Christianity in China since his youth. Over a period of more than three decades, he produced five monographs specifically addressing Christianity, from unequivocally opposing the spread of Christianity in China in the mid-to-late 1870s, to advocating for the adoption of the preaching form of the Christian "gatherings every seven days" to disseminate the village covenants and sacred edicts among the Chinese people in the 1890s. He proposed that the Chinese people should hold the right to spread Christianity. In 1906, he advocated for the establishment of a "common religion" and proposed "one religion for all nations" to eliminate wars around the world. In his later years, he proposed the "Five great wishes" to integrate and govern the various religions of the world with Taoism as the core, attempting to reconstruct global order from the perspective of religious unity. He envisioned the establishment of a sacred Taoist monastery, the dissemination of religious concepts, and the cultivation of talents, which drew on the organizational structure and missionary methods of Christianity, reflecting the thinking and efforts of modern Chinese intellectuals to bridge the Chinese and Western civilizations, seek solutions for modern China, reconcile conflicts between China and the West, and pursue global unity. [ABSTRACT FROM AUTHOR]

Motivation There are many clustered transcriptionally active regions in the human genome, in which the transcription complex cannot immediately terminate transcription at the upstream gene termination site, but instead continues to transcribe intergenic regions and downstream genes, resulting in read-through transcripts. Several studies have demonstrated the regulatory roles of read-through transcripts in tumorigenesis and development. However, limited by the read length of next-generation sequencing, discovery of read-through transcripts has been slow. For long but also erroneous third-generation sequencing data, this study developed a novel minimizer sketch algorithm to accurately and quickly identify read-through transcripts. Results Readon initially splits the reference sequence into distinct active regions. It employs a sliding window approach within each region, calculates minimizers, and constructs the specialized structured arrays for query indexing. Following initial alignment anchor screening of candidate read-through transcripts, further confirmation steps are executed. Comparative assessments against existing software reveal Readon's superior performance on both simulated and validated real data. Additionally, two downstream tools are provided: one for predicting whether a read-through transcript is likely to undergo nonsense-mediated decay or encodes a protein, and another for visualizing splicing patterns. Availability and implementation Readon is freely available on GitHub (https://github.com/Bulabula45/Readon). [ABSTRACT FROM AUTHOR]

Copyright of Forensic Science & Technology is the property of Institute of Forensic Science, Ministry of Public Security and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A coupling mechanism between flicker noise and hot carrier degradation (HCD) is revealed in this work. Predicting the flicker noise properties of fresh and aged devices is becoming essential for circuit designs, requiring an understanding of the fundamental noise behaviors. While certain models for fresh devices have been proposed, those for aged devices have not been reported yet because of the lack of a clear mechanism. The flicker noise of aged FinFETs is characterized based on the measure-stress-measure (MSM) method and analyzed from the device physics. It is found that both the mean and deviations of the noise power spectral density increase compared with the fresh counterparts. A coupling mechanism is proposed to explain the trap time constants, leading to the trap characterizations in their energy profiles. The amplitude and number of contributing traps are also changing and are dependent on the mode of HCD and determined by the position of the induced traps. A microscopic picture is developed from the perspective of trap coupling, reproducing well the measured noise of advanced nanoscale FinFETs. The finding is important for accurate flicker noise calculations and aging-aware circuit designs. [ABSTRACT FROM AUTHOR]

There is a great threat to the production safety of coal mines caused by mine water disasters. Traditional identification methods are not adapted to the efficiency of today's coal mining and do not offer the advantage of accurate detection in real-time. In this study, the Mayfly Algorithm (MA) was used to optimize the Long Short-Term Memory (LSTM) network, combined with laser-induced fluorescence technology, to apply it to the identification of mine water sources for the prevention of mine water disasters and post-disaster relief work. Taking sandstone water and goaf water as the original samples, five mixed water samples were also prepared by mixing the sandstone water and goaf water in different proportions, giving a total of seven water samples to be tested. Laser-induced fluorescence technology was used to obtain the fluorescence spectral data of water samples, and then the Linear Discriminant Analysis (LDA) dimensionality reduction algorithm and the Principal Component Analysis (PCA) dimensionality reduction algorithm were used to reduce the dimensions of the original spectral data. Then, three architectures, including LSTM, GA-LSTM (optimization of the LSTM by genetic algorithm) and MA-LSTM were designed to identify mine water sources. Finally, from the results' analysis, MA-LSTM performs best in many aspects after PCA dimensionality reduction and has the best identification effect. These results supported the feasibility of the novel method. [ABSTRACT FROM AUTHOR]

Haiyang-2 (HY-2) missions have accumulated sea surface height (SSH) observations on a global scale for more than 10 years. Four satellites, HY-2A, HY-2B, HY-2C and HY-2D, provide even but differently distributed data, which play a complementary role in marine gravity studies with other missions. Therefore, this paper evaluates the performances of HY-2 altimetric data in marine gravity modeling from the following four perspectives: SSH accuracy, geoid signal resolution ability, vertical deflections and gravity anomaly. First, the centimeter-magnitude accuracy level of HY-2 data is proved by analyzing SSH discrepancies at crossover points within a certain time limit. Second, the spectral analysis of repetitive along-track data sequences in a time domain shows a geoid resolution range from 18 to 24 km. Taking HY-2 exact repeat missions (ERM), for example, the resolution could be remarkably enhanced by stacking repetitive cycles. Third, validation with an XGM2019 model showed that vertical deflections were reliably computed for all HY-2 missions, but HY-2A performed slightly worse than the other HY-2 missions. Meanwhile, HY-2C and HY-2D with a ~66° orbital inclination obviously had an improved ability to capture east–west signals compared to HY-2A and HY-2B. Finally, we constructed global marine gravity results based on three input datasets, HY-2 dataset only, multi-satellite dataset without HY-2 and multi-satellite dataset with HY-2. Validations were performed using published models and shipborne gravimetric data. The results showed that the HY-2 dataset is capable of improving marine gravity anomaly recoveries and that the accuracy of NSOAS22 with incorporated HY-2 data is comparable to DTU21 and SS V31.1. Furthermore, HY-2 observations should not be the only input dataset to construct a 1' × 1' resolution marine gravity model. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: This paper aims to summarize the influence law of hybrid deposited and micro-rolling (HDMR) technology on the bead morphology and overlapping coefficient. A better bead topology positively supports the overlapping deposited in multi-beads between layers while actively assisting the subsequent layer's deposition in the wire and arc additive manufacturing (WAAM). Hybrid-deposited and micro-rolling (HDMR) additive manufacturing (AM) technology can smooth the weld bead for improved surface quality. However, the micro-rolling process will change the weld bead profile fitting curve to affect the overlapping coefficient. Design/methodology/approach: Weld bead contours for WAAM and HDMR were extracted using line lasers. A comparison of bead profile curves was conducted to determine the influence law of micro-zone rolling on the welding bead contour and fitting curve. Aiming at the optimized overlapping coefficient of weld bead in HDMR AM, the optimal HDMR overlapping coefficient curve was proposed which varies with the reduction based on the best surface flatness. The mathematical model for overlapping in HDMR was checked by comparing the HDMR weld bead contours under different rolling reductions. Findings: A fitting function of the bead forming by HDMR AM was proposed based on the law of conservation of mass. The change rule of the HDMR weld bead overlapping spacing with the degree of weld bead rolling reduction was generated using the flat-top transition calculation for this model. Considering the damming-up impact of the first bead, the overlapping coefficient was examined for its effect on layer surface flatness. Originality/value: Using the predicted overlapping model, the optimal overlapping coefficients for different rolling reductions can be achieved without experiments. These conclusions can encourage the development of HDMR technology. [ABSTRACT FROM AUTHOR]

In this article, we exploit Semi-Supervised Learning (SSL) to increase the amount of training data to improve the performance of Fine-Grained Visual Categorization (FGVC). This problem has not been investigated in the past in spite of prohibitive annotation costs that FGVC requires. Our approach leverages unlabeled data with an adversarial optimization strategy in which the internal features representation is obtained with a second-order pooling model. This combination allows one to back-propagate the information of the parts, represented by second-order pooling, onto unlabeled data in an adversarial training setting. We demonstrate the effectiveness of the combined use by conducting experiments on six state-of-the-art finegrained datasets, which include Aircrafts, Stanford Cars, CUB-200-2011, Oxford Flowers, Stanford Dogs, and the recent Semi-Supervised iNaturalist-Aves. Experimental results clearly show that our proposed method has better performance than the only previous approach that examined this problem; it also obtained higher classification accuracy with respect to the supervised learning methods with which we compared. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to present a series of approaches for three-related issues in multiaxis in wire and arc additive manufacturing (WAAM) as follows: how to achieve a stable and robust deposition process and maintain uniform growth of the part; how to maintain consistent formation of a melt pool on the surface of the workpiece; and how to fabricate an overhanging structure without supports. Design/methodology/approach: The principal component analysis-based path planning approach is proposed to compute the best scanning directions of slicing contours for the generation of filling paths, including zigzag paths and parallel skeleton paths. These printing paths have been experimented with in WAAM. To maintain consistent formation of a melt pool at overhanging regions, the authors introduce definitions for the overhanging point, overhanging distance and overhanging vector, with which the authors can compute and optimize the multiaxis motion. A novel fabricating strategy of depositing the overhanging segments as a support for the deposition of filling paths is presented. Findings: The second principal component of a planar contour is a reasonable scanning direction to generate zigzag filling paths and parallel skeleton filling paths. The overhanging regions of a printing layer can be supported by pre-deposition of overhanging segments. Large overhangs can be successfully fabricated by the multiaxis WAAM process without supporting structures. Originality/value: An intelligent approach of generating zigzag printing paths and parallel skeleton printing paths. Optimizations of depositing zigzag paths and parallel skeleton paths. Applications of overhanging point overhanging distance and overhanging vector for multiaxis motion planning. A novel fabricating strategy of depositing the overhanging segments as a support for the deposition of filling paths. [ABSTRACT FROM AUTHOR]

The horizontal features of vehicle bottom and the vertical features of both sides of vehicle are selected, and the local features of gray scale and its gradient and variation, which are less affected by global gray scale, are extracted. The horizontal and vertical features of vehicle are fused respectively by applying weighted evidence theory, and the weight of each feature is adjusted according to different light intensity. For improving the realtimeness of identification, artificial fish swarm algorithm is applied, and a vehicle identification module is added to enhance the guiding ability of artificial fishes. Based on search results and further judgment by symmetric feature, the accurate positioning of front vehicle is realized. Experiment results show that the technique proposed can accurately identify front vehicles under different lighting conditions with good adaptability, accuracy and realtimeness. [ABSTRACT FROM AUTHOR]

Due to severer transistor aging at nanoscale, circuit design margin becomes extremely tight for advanced technology nodes. Thus, reliability-aware circuit design is urgently needed. In this article, a new framework to perform aging-aware static timing analysis (STA) is presented for reliability analysis. The key parts of aging-aware STA flows are workload analysis and aged delay/transition calculation. For the workload analysis, a new analytical stress probability (SP) calculation model is proposed, which considers the floating effect and signal correlations. For aged delay/transition calculation, a new aging-aware model is developed, which is accessible to large industrial libraries. The results show that the proposed model achieves high accuracy in the degradation estimation and aged-path-delay calculation. Due to its high accuracy and scalability, the proposed framework is a promising solution that is compatible with commercial Electronic Design Automation (EDA) tools. [ABSTRACT FROM AUTHOR]

The most common and challenging issues in image recognition are scene character recognition from the street view image, and the scene character consists of both text and number. Recently, the researchers were introduced a lot of scene character recognition methods, but the performance of the methods often degraded due to complexity. So, we proposed the improved firefly algorithm for local trapping problem (IFLT) utilizing convolutional neural network (CNN) for the extraction of features from the scene character. The IFLT approach is the improved version of the firefly optimization algorithm to solve local trapping problems. During feature extraction, the hyperparameters on CNN are tuned with the help of the IFLT approach. The alignment and multilayer perceptron layers are used on CNN. Subsequently, the support vector machine approach is used to classify the relevant class of scene characters from the street view image. Experimentally, we use six scene character dataset SVHN, ISN, IIIT5K-words, SVT, ICDAR 2003, and ICDAR 2013 dataset. The performance of the proposed IFLT approach is evaluated with standard deviation, mean, average computational time, and most excellent minimum (MEmin) parameters. The experimental results demonstrate that the proposed IFLT-CNN is well suitable for scene character recognition. [ABSTRACT FROM AUTHOR]

Copyright of Forensic Science & Technology is the property of Institute of Forensic Science, Ministry of Public Security and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Prunella vulgaris, a traditional Chinese medicine, has been used to treat various benign and malignant tumours for centuries in China. In our previous studies, Prunella vulgaris extract (PVE) was shown to promote apoptosis in differentiated thyroid cancer (DTC) cells. However, whether other mechanisms are involved in the antitumour effect of PVE in thyroid cancer (TC) cells remains unclear. The present study aimed to investigate the antiproliferative and antimigratory effects of PVE on TC cell lines both in vitro and in vivo. First, the TPC-1 and SW579 human TC cell lines were screened by MTT assay for their high level of sensitivity to PVE. Then, the results of cell growth curve and colony formation assay and cell cycle analyses, wound healing, and migration assays demonstrated that PVE inhibited the proliferation and migration of TPC-1 and SW579 cells. Moreover, the antitumour effect of PVE was verified in a subcutaneous xenotransplanted tumour model. Next, MKI67, PCNA, CTNNB1, and CDH1 were screened by qRT-PCR for their significantly differential expression levels in xenograft tissue with and without PVE treatment, and expression of MKI67, PCNA, and CDH1 was verified by Western blot. Finally, an integrated bioinformatics analysis containing protein-protein interaction network, KEGG pathway, and GO analysis was conducted to explore more potential antitumour mechanisms of PVE. In summary, PVE could inhibit the proliferation and migration of TC cells both in vitro and in vivo, which may have been achieved by modulation of the expression of MKI67, PCNA, and CDH1. These data suggest that PVE has the potential to be developed into a new anticancer drug for the treatment of TC. [ABSTRACT FROM AUTHOR]

The gene-editing technique CRISPR—clustered regularly interspaced short palindromic repeats—is often depicted as a security threat because it could theoretically allow scientists or amateurs to edit the genome of a variety of organisms and potentially cause harm to humans, plants, and animals. The recent use of CRISPR by Chinese scientist He Jiankui to edit the genome of viable embryos, which resulted in the birth of twin girls, has exacerbated those fears. This article reviews the timeline of the CRISPR-babies experiment, highlights the challenges that contributed to the experiment's failure, and evaluates the risks of CRISPR's use for malevolent purposes. It concludes that although the potential for abuse is great, the technical obstacles are still too significant to allow successful modification that would threaten security. [ABSTRACT FROM AUTHOR]

Objective: Genome‐wide association studies have identified many susceptibility loci for systemic lupus erythematosus (SLE). However, most of these loci are located in noncoding regions of the genome. Long noncoding RNAs (lncRNAs) are pervasively expressed and have been reported to be involved in various diseases. This study aimed to explore the genetic significance of lncRNAs in SLE. Methods: A genome‐wide survey of SLE risk variants in lncRNA gene loci was performed in Han Chinese subjects (4,556 with SLE and 9,451 healthy controls). The functional relevance of an SLE risk variant in one of the lncRNA genes was explored using biochemical and molecular cell biology analyses. In vitro loss‐of‐function and gain‐of‐function strategies were used to clarify the functional and phenotypic relevance of this SLE susceptibility lncRNA. Moreover, correlation of this lncRNA with the degree of apoptosis in the peripheral blood of SLE patients was evaluated. Results: A novel SLE susceptibility locus in a lncRNA gene, designated SLEAR (for SLE‐associated RNA), was identified at the single‐nucleotide polymorphism rs13259960 (odds ratio 1.35, Pcombined = 1.03 × 10−11). The A>G variation at rs13259960, located in an intronic enhancer, was found to impair STAT1 recruitment to the enhancer that loops to the SLEAR promoter, resulting in decreased SLEAR production in peripheral blood mononuclear cells from patients with SLE (3 with the G/G genotype, 22 with A/G, and 103 with A/A at rs13259960; P = 0.0241). Moreover, SLEAR interacted with the RNA binding proteins interleukin enhancer binding factor 2, heterogeneous nuclear RNP F, and TATA‐binding protein–associated factor 15, to form a complex for transcriptional activation of the downstream antiapoptotic genes. In addition, SLEAR regulated apoptosis of Jurkat cells in vitro, and its expression level was correlated with the degree of cell death in the peripheral blood of patients with SLE (r = 0.824, P = 2.15 × 10−8; n = 30). Conclusion: These findings suggest a mechanism by which the risk variant at rs13259960 modulates SLEAR expression and confers a predisposition to SLE. Taken together, these results may give insights into the etiology of SLE. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Data Acquisition & Processing / Shu Ju Cai Ji Yu Chu Li is the property of Editorial Department of Journal of Nanjing University of Aeronautics & Astronautics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Forensic Science & Technology is the property of Institute of Forensic Science, Ministry of Public Security and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this letter, the lateral trap distributions in planar and FinFET devices are experimentally studied under various bias stress conditions of hot-carrier degradation (HCD). In contrast to the traditional understanding that the generated traps are crowded near the drain region during hot-carrier stress, it is found that the peak of the trap distribution profile will gradually move closer to the source region with the increase in ${V}_{\text {ds}}$ stress. The results suggest that the electron–electron scattering and multiple vibrational excitation are important mechanisms for the lateral trap distributions during HCD stress, which is helpful for the physical understanding of HCD. [ABSTRACT FROM AUTHOR]

A type of carbonate-hosted lead-zinc (Pb-Zn) ore deposits, known as Mississippi Valley Type (MVT) deposits, constitutes an important category of lead-zinc ore deposits. Previous studies proposed a fluid-mixing model to account for metal precipitation mechanism of the MVT ore deposits, in which fluids with metal-chloride complexes happen to mix with fluids with reduced sulfur, producing metal sulfide deposition. In this hypothesis, however, the detailed chemical kinetic process of mixing reactions, and especially the controlling factors on the metal precipitation are not yet clearly stated. In this paper, a series of mixing experiments under ambient temperature and pressure conditions were conducted to simulate the fluid mixing process, by titrating the metal-chloride solutions, doping with or without dolomite, and using NaHS solution. Experimental results, combined with the thermodynamic calculations, suggest that H2S, rather than HS− or S2−, dominated the reactions of Pb and/or Zn precipitation during the fluid mixing process, in which metal precipitation was influenced by the stability of metal complexes and the pH. Given the constant concentrations of metal and total S in fluids, the pH was a primary factor controlling the Pb and/or Zn metal precipitation. This is because neutralizing or neutralized processes for the ore-forming fluids can cause instabilities of Pb and/or Zn chloride complexes and re-distribution of sulfur species, and thus can facilitate the hydrolysis of Pb and Zn ions and precipitation of sulfides. Therefore, a weakly acidic to neutral fluid environment is most favorable for the precipitation of Pb and Zn sulfides associated with the carbonate-hosted Pb-Zn deposits. [ABSTRACT FROM AUTHOR]

Background: Finding peptides with high binding affinity to Class I major histocompatibility complex (MHC-I) attracts intensive research, and it serves a crucial part of developing a better vaccine for precision medicine. Traditional methods cost highly for designing such peptides. The advancement of computational approaches reduces the cost of new drug discovery dramatically. Compared with flourishing computational drug discovery area, the immunology area lacks tools focused on in silico design for the peptides with high binding affinity. Attributed to the ever-expanding amount of MHC-peptides binding data, it enables the tremendous influx of deep learning techniques for modeling MHC-peptides binding. To leverage the availability of these data, it is of great significance to find MHC-peptides binding specificities. The binding motifs are one of the key components to decide the MHC-peptides combination, which generally refer to a combination of some certain amino acids at certain sites which highly contribute to the binding affinity. Result: In this work, we propose the Motif Activation Mapping (MAM) network for MHC-I and peptides binding to extract motifs from peptides. Then, we substitute amino acid randomly according to the motifs for generating peptides with high affinity. We demonstrated the MAM network could extract motifs which are the features of peptides of highly binding affinities, as well as generate peptides with high-affinities; that is, 0.859 for HLA-A*0201, 0.75 for HLA-A*0206, 0.92 for HLA-B*2702, 0.9 for HLA-A*6802 and 0.839 for Mamu-A1*001:01. Besides, its binding prediction result reaches the state of the art. The experiment also reveals the network is appropriate for most MHC-I with transfer learning. Conclusions: We design the MAM network to extract the motifs from MHC-peptides binding through prediction, which are proved to generate the peptides with high binding affinity successfully. The new peptides preserve the motifs but vary in sequences. [ABSTRACT FROM AUTHOR]