Noise removing for Lamb wave signals by fractional differential

In the ultrasonic Lamb wave nondestructive testing and evaluation, the measured Lamb wave signals are often mixed with noises which affect their accuracy of measurement. In the present study, a fractional differential method is proposed to remove the noise for the Lamb wave signal. Firstly, the fractional differential of the amplitude spectrum of the received noisy signal at different orders is obtained with the fractional differential theory. Then, the characteristic parameters of the amplitude spectrum are extracted with the developed parameter estimation model. The Gaussian peak mode is used as a model to assign the amplitude spectrum of the original signal correctly. Finally, the waveform of the Lamb wave is restored by combining the amplitude and phase spectrums. Simulated and experimental data are used to evaluate the performance of the developed method. Results show that the developed method has effective noise removing performance for Lamb wave signals

Verification of DNA motifs in Arabidopsis using CRISPR/Cas9-mediated mutagenesis.

Transcription factors (TFs) and chromatin-modifying factors (CMFs) access chromatin by recognizing specific DNA motifs in their target genes. Chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq) has been widely used to discover the potential DNA-binding motifs for both TFs and CMFs. Yet, an in vivo method for verifying DNA motifs captured by ChIP-seq is lacking in plants. Here, we describe the use of clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated 9 (Cas9) to verify DNA motifs in their native genomic context in Arabidopsis. Using a single-guide RNA (sgRNA) targeting the DNA motif bound by REF6, a DNA sequence-specific H3K27 demethylase in plants, we generated stable transgenic plants where the motif was disrupted in a REF6 target gene. We also deleted a cluster of multiple motifs from another REF6 target gene using a pair of sgRNAs, targeting upstream and downstream regions of the cluster, respectively. We demonstrated that endogenous genes with motifs disrupted and/or deleted become inaccessible to REF6. This strategy should be widely applicable for in vivo verification of DNA motifs identified by ChIP-seq in plants

Fractional derivative method to reduce noise and improve SNR for lamb wave signals

Ultrasonic Lamb wave testing is one important nondestructive testing technology for the plate-like structural health monitoring. To improve the detection accuracy, a fractional derivative method is presented to reduce the noise of Lamb wave signals. First, the amplitude spectrum fractional derivative of the Lamb signal with noises at different orders is obtained. Next, the characteristic parameters of the amplitude spectrum are calculated according to the proposed relationship between the peak amplitude and the derivative order as well as that between the peak frequency and the derivative order. Finally, the Lamb wave signal is rebuilt by combining the amplitude and phase spectra. Both the simulated and experimental data are used to evaluate the developed method qualitatively and quantitatively. The results indicate that this method can effectively reduce the noise for Lamb wave signals

Shortcuts Arising from Contrast: Effective and Covert Clean-Label Attacks in Prompt-Based Learning

Prompt-based learning paradigm has demonstrated remarkable efficacy in enhancing the adaptability of pretrained language models (PLMs), particularly in few-shot scenarios. However, this learning paradigm has been shown to be vulnerable to backdoor attacks. The current clean-label attack, employing a specific prompt as a trigger, can achieve success without the need for external triggers and ensure correct labeling of poisoned samples, which is more stealthy compared to the poisoned-label attack, but on the other hand, it faces significant issues with false activations and poses greater challenges, necessitating a higher rate of poisoning. Using conventional negative data augmentation methods, we discovered that it is challenging to trade off between effectiveness and stealthiness in a clean-label setting. In addressing this issue, we are inspired by the notion that a backdoor acts as a shortcut and posit that this shortcut stems from the contrast between the trigger and the data utilized for poisoning. In this study, we propose a method named Contrastive Shortcut Injection (CSI), by leveraging activation values, integrates trigger design and data selection strategies to craft stronger shortcut features. With extensive experiments on full-shot and few-shot text classification tasks, we empirically validate CSI's high effectiveness and high stealthiness at low poisoning rates. Notably, we found that the two approaches play leading roles in full-shot and few-shot settings, respectively.Comment: 10 pages, 6 figures, conferenc

Study on the thin layer drying and diffusion mechanism of low rank coal in Inner Mongolia and Yunnan

Coal is one of the world's most important energy substances. China is rich in coal resources, accounting for more than 90 % of all ascertained fossil energy reserves. The consumption share of coal energy reaches 56.5 % in 2021. Due to the high moisture content of low-rank coal, it is easy to cause equipment blockage in the dry sorting process. This paper considers low-rank coal coming from Inner Mongolia (NM samples) and Yunnan (YN samples). The weight loss performance of the samples was analyzed using thermogravimetric experiments to determine the appropriate temperature for drying experiments. Thin-layer drying experiments were carried out at different temperature conditions. The drying characteristics of low-rank coal were that the higher the drying temperature, the shorter the drying completion time; the smaller the particle size, the shorter the drying completion time. The effective moisture diffusion coefficient was fitted using the Arrhenius equation. The effective water diffusion coefficient of NM samples was 5.07·10–11 - 9.58·10–11 m2/s. The effective water diffusion coefficients of the three different particle sizes of YN samples were 1.89·10–11 - 4.92·10–11 (–1 mm), 1.38·10–10 - 4.13·10–10 (1-3 mm), 5.26·10–10 - 1.49·10–9 (3-6 mm). The activation energy of Inner Mongolia lignite was 10.97 kJ/mol (–1 mm). The activation energies of Yunnan lignite with different particle sizes were 17.97 kJ/mol (–1 mm), 33.52 kJ/mol (1-3 mm), and 38.64 kJ/mol (3-6 mm). The drying process was simulated using empirical and semi-empirical formulas. The optimal model for Inner Mongolia samples was the Two-term diffusion model, and Yunnan samples were the Hii equation was used

Large Language Models for Information Retrieval: A Survey

As a primary means of information acquisition, information retrieval (IR) systems, such as search engines, have integrated themselves into our daily lives. These systems also serve as components of dialogue, question-answering, and recommender systems. The trajectory of IR has evolved dynamically from its origins in term-based methods to its integration with advanced neural models. While the neural models excel at capturing complex contextual signals and semantic nuances, thereby reshaping the IR landscape, they still face challenges such as data scarcity, interpretability, and the generation of contextually plausible yet potentially inaccurate responses. This evolution requires a combination of both traditional methods (such as term-based sparse retrieval methods with rapid response) and modern neural architectures (such as language models with powerful language understanding capacity). Meanwhile, the emergence of large language models (LLMs), typified by ChatGPT and GPT-4, has revolutionized natural language processing due to their remarkable language understanding, generation, generalization, and reasoning abilities. Consequently, recent research has sought to leverage LLMs to improve IR systems. Given the rapid evolution of this research trajectory, it is necessary to consolidate existing methodologies and provide nuanced insights through a comprehensive overview. In this survey, we delve into the confluence of LLMs and IR systems, including crucial aspects such as query rewriters, retrievers, rerankers, and readers. Additionally, we explore promising directions within this expanding field

Cloning and characterization of two subunits of calcineurin cDNA in naked carp (Gymnocypris przewalskii) from Lake Qinghai, China

The naked carp (Gymnocypris przewalskii), a native teleost, plays an important role in maintenance of the ecological balance in the system of Lake Qinghai (altitude, 3.2 km) on the Qinghai-Tibet Plateau in China. Calcineurin (CN) is the only member of the serine/threonine phosphatase family that can be activated by both Ca2+ and calmodulin (CaM) and involved in many important physiological processes such as salt tolerance/adaption. In this report, cDNAs of CN catalytic subunit paralogue isoforms: GpCAα (GenBank accession no.JQ407043), GpCAγ (GenBank accession no. JQ407043), and CN regulatory subunit (GpCB) (GenBank accession no. JQ410473), were isolated from Gymnocypris przewalskii and their expression patterns in embryos developmentwere characterized. Gene expression profile demonstrated that GpCA and GpCB mRNA was distributed ubiquitously in all embryonic stages and showed decline until final stage of development. Immunohistologicalanalysis revealed CN localization in different tissues including kidney, heart, brain, spermary, and gill. Collectively, these results provide molecular basis and clues to further understand the role of CN during embryos development and its function in tissues for the adaptation mechanism of naked carp

Dynamical Evolution of Anisotropic Response in Black Phosphorus under Ultrafast Photoexcitation

Black phosphorus has recently emerged as a promising material for high performance electronic and optoelectronic device for its high mobility, tunable mid-infrared bandgap and anisotropic electronic properties. Dynamical evolution of photo excited carriers and its induced change of transient electronic properties are critical for materials' high field performance, but remains to be explored for black phosphorus. In this work, we perform angle resolved transient reflection spectroscopy to study the dynamical evolution of anisotropic properties of black phosphorus under photo excitation. We find that the anisotropy of reflectivity is enhanced in the pump induced quasi-equilibrium state, suggesting an extraordinary enhancement of the anisotropy in dynamical conductivity in hot carrier dominated regime. These results raise enormous possibilities of creating high field, angle sensitive electronic, optoelectronic and remote sensing devices exploiting the dynamical electronic anisotropic with black phosphorus.Comment: 22 pages,10 figure

Identification of a cellular senescence-related-lncRNA (SRlncRNA) signature to predict the overall survival of glioma patients and the tumor immune microenvironment

Background: Gliomas are brain tumors that arise from glial cells, and they are the most common primary intracranial tumors with a poor prognosis. Cellular senescence plays a critical role in cancer, especially in glioma. In this study, we constructed a senescence-related lncRNA (SRlncRNA) signature to assess the prognosis of glioma.Methods: The Cancer Genome Atlas was used to collect SRlncRNA transcriptome profiles and clinical data about glioma. Patients were randomized to training, testing, and whole cohorts. LASSO and Cox regression analyses were employed to construct the SRlncRNA signature, and Kaplan–Meier (K-M) analysis was performed to determine each cohort’s survival. Receiver operating characteristic (ROC) curves were applied to verify the accuracy of this signature. Gene set enrichment analysis was used to visualize functional enrichment (GSEA). The CIBERSORT algorithm, ESTIMATE and TIMER databases were utilized to evaluate the differences in the infiltration of 22 types of immune cells and their association with the signature. RT–qPCR and IHC were used to identify the consistency of the signature in tumor tissue.Results: An SRlncRNA signature consisting of six long non-coding RNAs (lncRNAs) was constructed, and patients were divided into high-risk and low-risk groups by the median of their riskscore. The KM analysis showed that the high-risk group had worse overall survival, and the ROC curve confirmed that the riskscore had more accurate predictive power. A multivariate Cox analysis and its scatter plot with clinical characteristics confirmed the riskscore as an independent risk factor for overall survival. GSEA showed that the GO and KEGG pathways were mainly enriched in the immune response to tumor cells, p53 signaling pathway, mTOR signaling pathway, and Wnt signaling pathway. Further validation also yielded significant differences in the risk signature in terms of immune cell infiltration, which may be closely related to prognostic differences, and qRT–PCR and IHC confirmed the consistency of the expression differences in the major lncRNAs with those in the prediction model.Conclusion Our findings indicated that the SRlncRNA signature might be used as a predictive biomarker and that there is a link between it and immune infiltration. This discovery is consistent with the present categorization system and may open new avenues for research and personalized therapy

Nodal s± pairing symmetry in an iron-based superconductor with only hole pockets

The origin of high-temperature superconductivity in iron-based superconductors is still not understood; determination of the pairing symmetry is essential for understanding the superconductivity mechanism. In the iron-based superconductors that have hole pockets around the Brillouin zone centre and electron pockets around the zone corners, the pairing symmetry is generally considered to be s±, which indicates a sign change in the superconducting gap between the hole and electron pockets. For the iron-based superconductors with only hole pockets, however, a couple of pairing scenarios have been proposed, but the exact symmetry is still controversial. Here we determine that the pairing symmetry in KFe2As2—which is a prototypical iron-based superconductor with hole pockets both around the zone centre and around the zone corners—is also of the s± type. Our laser-based angle-resolved photoemission measurements have determined the superconducting gap distribution and identified the locations of the gap nodes on all the Fermi surfaces around the zone centres and the zone corners. These results unify the pairing symmetry in hole-doped iron-based superconductors and point to spin fluctuation as the pairing glue in generating superconductivity