In recent years, the sample mining strategy has been integrated into the loss function of face recognition, significantly improving the performance of face recognition. But most of the work focuses ...on how to mine difficult samples during the training phase, without considering the potential unrecognized sample images in the difficult samples, resulting in poor recognition performance of the model for low-quality facial images. To solve this problem, this paper proposes a hybrid adaptive loss function MixFace that combines sample difficulty adaptation and image quality adaptation. The loss function combines the CurricularFace based on curriculum learning with the image adaptive loss function AdaFace. The feature norm is incorporated into the loss function as an image quality indicator. On the premise of focusing on image quality, this paper focuses on simple samples in the early training stage and difficult samples in the later training stage, reducing the network model’s attention to some low-quality unrecogn
With the growing shortage of fossil energy and the increasing of concerns over global climate changes and environmental problems have driven the development of alternative energy sources. Recently, ...great interest has been oriented towards the development of sustainable resources, especially the utilization of lignocellulosic biomass, a renewable and the most abundant source of biomass originating from plant photosynthesis in nature. Catalytic conversion of renewable cellulosic biomass can produce a series of compounds such as 5-hydroxymethylfurfural (HMF) and 2,5-dimethylfuran (DMF) which are important platform compounds and ideal renewable alternative to fossil fuels. To obtain the renowned bio-based platform molecules, various catalysts and reaction systems have been used in the past decade years. To fully understand current biomass to HMF and DMF development, it is necessary to have an overview and comparison of different homogeneous and heterogeneous catalysts. The reaction systems also exhibit a remarkable impact on the yield and distribution of products with different catalysts. General trends and future research directions of using biomass for HMF, DMF production are also discussed systematically.
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•Shifting from fossil resources to sustainable biomass for chemicals production is important in both academic and our society.•A comprehensive review about the catalytic conversion of biomass into HMF and DMF have been presented.•Catalysts, and reaction systems for the production of HMF and DMF developed in the last few years are discussed.•The scale-up conversion of biomass and the process economy analysis of HMF and DMF production are also discussed.
This paper introduces a novel algorithm for optimizing the coefficients of the digital filters used in incremental delta-sigma analog-to-digital converters (IDSC). This algorithm is modified from ...constrained linear least squares (LS) to improve the signal-to-noise-and-distortion ratio (SNDR) of IDSC and minimize the oversampling rate (OSR) of the modulator, which enhances system speed and reduces power consumption. In the case of the same SNDR, the first-order IDSC with the proposed filter can reduce the OSR of the modulator by 50%, at least compared to the IDSC with the conventional filter. The second-order IDSC with the proposed filter can reach a higher SNDR of 106 dB with an OSR of 64. Considering the nonlinearity of the integrator, the SNDR of IDSC with the proposed filter is also 10 dB greater than that of the conventional filters and 3dB greater than that of the IDSC using the near-optimal algorithm filter. The experimental results indicate that the proposed filter possesses an excellent figure of merit of 0.028
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Purpose
Non-small cell lung cancer (NSCLC) accounts for about 85% in all cases of lung cancer. In recent years, molecular targeting drugs for NSCLC have been developed rapidly. The epidermal growth ...factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) have changed the paradigm of cancer therapy from empirical cytotoxic chemotherapy to molecular-targeted cancer therapy. Currently, there are three generations of EGFR-TKIs, all of which have achieved good efficacy in clinical therapy. However, most patients developed drug resistance after 6–13 months EGFR-TKIs treatment. Therefore, a comprehensive understanding of EGFR-TKIs resistance mechanisms is of vital importance for clinical management of NSCLC.
Methods
Relevant data and information about the topic were obtained by searching PubMed (Medline), Web of Science and Google Scholar using the subject headings, such as “NSCLC”, “EGFR-TKIs resistance”, “EGFR mutations”, “human epidermal growth factor receptor-2 (HER2/erbB-2)”, “hepatocyte growth factor (HGF)”, “vascular endothelial growth factor (VEGF)”, “insulin-like growth factor 1 (IGF-1)”, “epithelial–mesenchymal transition (EMT)”, “phosphatase and tensin homolog (PTEN)”, “RAS mutation”, “BRAF mutation”, “signal transducer and activator of transcription 3 (STAT3)”, and “tumor microenvironment”, etc.
Results
The mechanisms for EGFR-TKIs resistance include EGFR mutations, upregulation of HER2, HGF/c-MET, VEGF IGF1, EMT and STAT3 pathways, mutations of PTEN, RAS and BRAF genes, and activation of other by-pass pathways. These mechanisms are interconnected and can be potential targets for the treatment of NSCLC.
Conclusion
In this review, we discuss the mechanisms of EGFR-TKIs drug resistance and the clinical strategies to overcome drug resistance from the perspective of EGFR-TKIs combined treatment.
JPEG Reversible Data Hiding (RDH) is a method designed to extract hidden data from a marked image and perfectly restore the image to its original JPEG form. However, while existing RDH methods ...adaptively manage the visual distortion caused by embedded data, they often neglect the concurrent increase in file size. In rectifying this oversight, we have designed a new JPEG RDH scheme that addresses all influential metrics during the embedding phase and a dynamic frequency selection strategy with recoverable frequency order after data embedding. The process initiates with a pre-processing phase of blocks and the subsequent selection of frequencies. Utilizing a two-dimensional (2D) mapping strategy, we then compute the visual distortion and file size increment (FSI) for each image block by examining non-zero alternating current (AC) coefficient pairs (NZACPs) and their corresponding run lengths. Finally, we select appropriate block groups based on the influential metrics of each block group and proceed with data embedding by 2D histogram shifting (HS). Extensive experimentation demonstrates how our method's efficiently and consistently outperformed existing techniques with a superior peak signal-to-noise Ratio (PSNR) and optimized FSI.
The problem of the rate of convergence of Legendre approximation is considered. We first establish the decay rates of the coefficients in the Legendre series expansion and then derive error bounds of ...the truncated Legendre series in the uniform norm. In addition, we consider Legendre approximation with interpolation. In particular, we are interested in the barycentric Lagrange formula at the Gauss-Legendre points. Explicit barycentric weights, in terms of Gauss-Legendre points and corresponding quadrature weights, are presented that allow a fast evaluation of the Legendre interpolation formula. Error estimates for Legendre interpolation polynomials are also given.
Small cell lung cancer (SCLC) is a recalcitrant malignancy with elusive mechanism of pathogenesis and dismal prognosis. Over the past decades, platinum-based chemotherapy has been the backbone ...treatment for SCLC. However, subsequent chemoresistance after initial effectiveness urges researchers to explore novel therapeutic targets of SCLC. Recent years have witnessed significant improvements in targeted therapy in SCLC. New molecular candidates such as Ataxia telangiectasia and RAD3-related protein (ATR), WEE1, checkpoint kinase 1 (CHK1) and poly-ADP-ribose polymerase (PARP) have shown promising therapeutic utility in SCLC. While immune checkpoint inhibitor (ICI) has emerged as an indispensable treatment modality for SCLC, approaches to boost efficacy and reduce toxicity as well as selection of reliable biomarkers for ICI in SCLC have remained elusive and warrants our further investigation. Given the increasing importance of precision medicine in SCLC, optimal subtyping of SCLC using multi-omics have gradually applied into clinical practice, which may identify more drug targets and better tailor treatment strategies to each individual patient. The present review summarizes recent progress and future directions in SCLC. In addition to the emerging new therapeutics, we also focus on the establishment of predictive model for early detection of SCLC. More importantly, we also propose a multi-dimensional model in the prognosis of SCLC to ultimately attain the goal of accurate treatment of SCLC.
Background/Aims: An increasing number of studies have suggested that circular RNAs (circRNAs) have vital roles in carcinogenesis and tumor progression. However, the function of circRNAs in ...hepatocellular carcinoma (HCC) remains poorly characterized. Methods: We investigated the levels of circRNAs in patients with HCC to identify potential diagnostic biomarkers. We examined circRNA expression profiles in liver tumors and paired non-cancerous liver tissues from three HCC patients with cancer thrombus using a circRNA microarray. Bioinformatics analysis was performed to find circRNAs with significantly altered expression levels between tumors and their paired non-tumor tissues. We confirmed our initial findings by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Receiver operating characteristic (ROC) curves were also applied to identify a candidate circRNA with the optimal specificity and sensitivity. Finally, X-tile software was adopted to calculate the most efficient cut-off value for hsa_circ_0091579 expression. Results: Microarray analysis identified 20 unique circRNAs that were differentially expressed between tumor and non-tumor tissues (P < 0.05). The expression of these 20 circRNAs was verified by qRT-PCR. The expression of hsa_circ_16245-1 and hsa_circ_0091579 mRNA was consistent with their levels as tested by the microarray. The ROC curves showed that both hsa_circ_16245-1 and hsa_circ_0091579 had favorable specificity and sensitivity. We further confirmed that hsa_circ_0091579 was significantly upregulated in HCC and its high expression was intimately associated with a worse overall survival in patients with HCC. Conclusion: Hsa_circ_0091579 may play a critical role in HCC progression and serve as a potential biomarker for the prognosis of patients with HCC.
Additionally, there is a lack of detailed characterization of effects of neoadjuvant chemotherapy (NAC) on the tumor microenvironment (TME) in SCLC, especially in the clinical pre-treatment and ...post-treatment setting. ...in the present study, we explored the alterations in TME after NAC in SCLC by utilizing single-cell RNA sequencing analyses. ...our team has been conducting a phase 2 clinical trial exploring the role of neoadjuvant chemo-immunotherapy in patients with locally advanced SCLC, which might change the locally advanced SCLC as a potentially lethal malignancy into a curable disease in the clinical setting. Distinct immune gene programs associated with host tumor immunity, neoadjuvant chemotherapy, and chemoimmunotherapy in resectable NSCLC.
Metalloproteinases (MPs) is a large family of proteinases with metal ions in their active centers. According to the different domains metalloproteinases can be divided into a variety of subtypes ...mainly including Matrix Metalloproteinases (MMPs), A Disintegrin and Metalloproteases (ADAMs) and ADAMs with Thrombospondin Motifs (ADAMTS). They have various functions such as protein hydrolysis, cell adhesion and remodeling of extracellular matrix. Metalloproteinases expressed in multiple types of cancers and participate in many pathological processes involving tumor genesis and development, invasion and metastasis by regulating signal transduction and tumor microenvironment. In this review, based on the current research progress, we summarized the structure of MPs, their expression and especially immunomodulatory role and mechanisms in cancers. Additionally, a relevant and timely update of recent advances and future directions were provided for the diagnosis and immunotherapy targeting MPs in cancers.
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