The gear cracks of gear box are one of most common failure forms affecting gear shaft drive. It has become significant for practice and economy to diagnose the situation of gearbox rapidly and ...accurately. The extracted signal is filtered first to eliminate noise, which is pretreated for the diagnostic classification based on the particle filter of radial basis function. As traditional error back-propagation of wavelet neural network with falling into local minimum easily, slow convergence speed and other shortcomings, the particle swarm optimization algorithm is proposed in this paper. This particle swarm algorithm that optimizes the weight values of wavelet neural network (scale factor) and threshold value (the translation factor) was developed to reduce the iteration times and improve the convergence precision and rapidity so that the various parameters of wavelet neural network can be chosen adaptively. Experimental results demonstrate that the proposed method can accurately and quickly identify the damage situation of the gear crack, which is more robust than traditional back-propagation algorithm. It provides guidances and references for the maintenance of the gear drive system schemes.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, ODKLJ, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Disease Overview
Diffuse large B‐cell lymphoma (DLBCL) is the most common type of aggressive non‐Hodgkin lymphoma originating from the germinal center, and it represents a heterogeneous group of ...diseases with variable outcomes that are differentially characterized by clinical features, cell of origin (COO), molecular features, and most recently, frequently recurring mutations.
Diagnosis
DLBCL is ideally diagnosed from an excisional biopsy of a suspicious lymph node, which shows sheets of large cells that disrupt the underlying structural integrity of the follicle center and stain positive for pan‐B‐cell antigens, such as CD20 and CD79a. COO is determined by immunohistochemical stains, while molecular features such as double‐hit or triple‐hit disease are determined by fluorescent in situ hybridization analysis. Commercial tests for frequently recurring mutations are currently not routinely used to inform treatment.
Risk Stratification
Clinical prognostic systems for DLBCL, including the rituximab International Prognostic Index, age‐adjusted IPI, and NCCN‐IPI, use clinical factors for the risk stratification of patients, although this does not affect the treatment approach. Furthermore, DLBCL patients with non‐germinal center B‐cell (GCB)‐like DLBCL (activated B‐cell like and unclassifiable) have a poorer response to up‐front chemoimmunotherapy (CI) compared to patients with GCB‐like DLBCL. Those with c‐MYC‐altered disease alone and in combination with translocations in BCL2 and/or BCL6 (particularly when the MYC translocation partner is immunoglobulin) respond poorly to up‐front CI and salvage autologous stem cell transplant at relapse.
Risk‐Adapted Therapy
This review will focus on differential treatment of DLBCL up‐front and at the time of relapse by COO and molecular features.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
In the evolving landscape of Chinese education, understanding the factors that influence the emotional health and engagement of English language learners is increasingly vital. Against this backdrop, ...our study delves into how teachers' autonomy-supportive behavior, teachers' harmony, and peer support impact these key educational outcomes.
This study investigates the roles of teachers' autonomy-supportive behavior, teachers' harmony, and peer support in influencing the emotional health and engagement of English language learners in China.
Involving a diverse sample of 68 English Language Teachers and their 389 students from various Chinese universities, the study leverages a convenience sampling method.
Key findings indicate that students' emotional health is predominantly influenced by peer support, while student engagement is significantly affected by a combination of teachers' autonomy-supportive behavior, peer support, and teachers' harmony. These outcomes highlight the importance of both teacher behavior and peer relationships in educational settings, underscoring their crucial roles in enhancing student well-being and engagement. The study's methodology, incorporating a diverse sample from multiple educational institutions and a comprehensive analytical approach, offers robust insights. However, the limitations of convenience sampling and reliance on self-reported data necessitate a careful interpretation of the findings.
Implications from this research are vital for educational policy and practice, emphasizing the need for interventions that enhance teacher-student relationships and foster supportive peer environments. This study adds to the body of knowledge on factors influencing emotional health and engagement among English language learners, advocating for a comprehensive approach in educational strategies and interventions.
Well crystallized and interconnected SnO2 nanoparticles (<5 nm) were synthesized via oxidation of exfoliated SnS2 sheets. The SnO2 nanoparticles exhibit a high total faradaic efficiency (FE) of 97% ...towards electrochemical reduction of CO2 at −0.95 V vs. the reversible hydrogen electrode (RHE). The main product ratio of CO/HCOO− which intrinsically correlates to the surface SnOx/Sn ratio variation varies with the applied potential. Beyond CO and HCOO− products formed via the two-electron transfer pathway, hydrocarbons and oxygenates are produced. The formation of hydrocarbon (CH4) versus oxygenate (C2H5OH) depends on the choice of electrolyte (KOH vs. KHCO3), both of which can reach a maximal faradaic efficiency of 10%. The distinctive grain boundary and exposed corner/step sites in the interconnected SnO2 nanoparticles contribute to the high FE of CO2 reduction and unique selectivity.
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•Proposed a three-dimensional convolutional neural network (3D-CNN) for heterogeneous composite material homogenization.•Network trained on labeled data generation by numerical ...simulation.•Tested uncertainty quantification ability and transferability of the trained model.•Demonstrated effectiveness and efficiency for predicting effective material properties.
Homogenization is a technique commonly used in multiscale computational science and engineering for predicting collective response of heterogeneous materials and extracting effective mechanical properties. In this paper, a three-dimensional deep convolutional neural network (3D-CNN) is proposed to predict the anisotropic effective material properties for representative volume elements (RVEs) with random inclusions. The high-fidelity dataset generated by a computational homogenization approach is used for training the 3D-CNN models. The inference results of the trained networks on unseen data indicate that the network is capable of capturing the microstructural features of RVEs and produces an accurate prediction of effective stiffness and Poisson’s ratio. The benefits of the 3D-CNN over conventional finite-element-based homogenization with regard to computational efficiency, uncertainty quantification and model’s transferability are discussed in sequence. We find the salient features of the 3D-CNN approach make it a potentially suitable alternative for facilitating material design with fast product design iteration and efficient uncertainty quantification.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Although the monolayers of most 2D materials are non‐ferroelectric with highly symmetric lattices, symmetry breaking may take place in their bilayers upon some stacking configuration, giving rise to ...so‐called sliding ferroelectricity where the vertical polarizations can be electrically reversed via interlayer translation. However, it is not supposed to appear in systems like graphene bilayer with centro‐symmetry at any stacking configuration, and the origin of the recently reported ferroelectricity (Nature 2020, 588, 71) in graphene bilayer intercalated between h‐BN remains mysterious. Here, a type of across‐layer sliding ferroelectricity that arises from the asymmetry of next‐neighbor interlayer couplings is proposed. The first‐principles evidence is shown that the vertical polarizations in intercalated centro‐symmetric 2D materials like graphene bilayer can be switched via multilayer sliding, which is likely to be the origin of the observed ferroelectric hysteresis. Moreover, such ferroelectricity may exist in a series of other heterolayers with quasi‐degenerate polar states, like graphene bilayer or trilayer on BN substrate, or even with a molecule layer on surface where each molecule can store 1‐bit data independently, resolving the bottleneck issue of sliding ferroelectricity for high‐density data storage.
Across‐layer sliding ferroelectricity that arises from the asymmetry of next‐neighbor interlayer couplings is proposed, where the vertical polarizations of intercalated centro‐symmetric 2D materials like graphene bilayer can be switched via multilayer sliding, which may exist in a series of other heterolayers, including molecular systems. It may clarify a previously unexplained phenomenon and be utilized for high‐density data storage.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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•Homogeneous and heterogeneous iron species activation of PS and PMS are presented.•Synthetic ways for heterogeneous iron catalysts for PS/PMS activation are reviewed.•Influencing ...factors and synergistic methods for PS/PMS activation are introduced.•Further efforts related to iron-mediated activation of PS and PMS are proposed.
Various organic contaminants accumulated in the environment pose great threat to ecosystems and human health. Sulfate radical-based advanced oxidation processes (SR-AOPs) have attracted increasing attention for the removal of these contaminants in recent years. Iron species, including ferrous and ferric iron, zero-valent iron, iron oxides and oxyhydroxides, iron sulfides and various supported iron catalysts, are known to be effective in activating persulfate (PS) or peroxymonosulfate (PMS) to generate sulfate radicals. This review is dedicated to summarize the up-to-date research progresses of iron-mediated activation of PS and PMS mediated by these iron-based species in both homogeneous and heterogeneous ways. The activators are categorized based on their chemistry, and the up-to-date knowledge regarding the activation mechanisms are summarized and discussed. Then, a summary of frequently-used synthesis methods of heterogeneous iron catalysts is presented. In addition, the effects of anions, solution pH, dissolved oxygen, and external energy on the activation processes are discussed. Finally, future research perspectives on the iron-based PS/PMS activation method are proposed and how to further improve such a technology for practical application are also discussed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The ADJUVANT study reported the comparative superiority of adjuvant gefitinib over chemotherapy in disease-free survival of resected EGFR-mutant stage II-IIIA non-small cell lung cancer (NSCLC). ...However, not all patients experienced favorable clinical outcomes with tyrosine kinase inhibitors (TKI), raising the necessity for further biomarker assessment. In this work, by comprehensive genomic profiling of 171 tumor tissues from the ADJUVANT trial, five predictive biomarkers are identified (TP53 exon4/5 mutations, RB1 alterations, and copy number gains of NKX2-1, CDK4, and MYC). Then we integrate them into the Multiple-gene INdex to Evaluate the Relative benefit of Various Adjuvant therapies (MINERVA) score, which categorizes patients into three subgroups with relative disease-free survival and overall survival benefits from either adjuvant gefitinib or chemotherapy (Highly TKI-Preferable, TKI-Preferable, and Chemotherapy-Preferable groups). This study demonstrates that predictive genomic signatures could potentially stratify resected EGFR-mutant NSCLC patients and provide precise guidance towards future personalized adjuvant therapy.
Hepatocellular carcinoma (HCC) is the most common malignant liver tumor with poor clinical outcomes. Increasing amount of long non-coding RNAs (lncRNAs) have been revealed to be implicated in the ...carcinogenesis and progression of HCC. However, the expressions, clinical significances, and roles of most lncRNAs in HCC are still unknown.
The expression of lncRNA MCM3AP antisense RNA 1 (MCM3AP-AS1) in HCC tissues and cell lines was detected by qRT-PCR and fluorescence in situ hybridization. Immunoblotting, CCK-8, EdU, colony formation and flow cytometry were performed to investigate the role of MCM3AP-AS1 in HCC cell proliferation, cell cycle and apoptosis in vitro. A subcutaneous tumor mouse model was constructed to analyze in vivo growth of HCC cells after MCM3AP-AS1 knockdown. The interactions among MCM3AP-AS1, miR-194-5p and FOXA1 were measured by RNA pull-down, RNA immunoprecipitation and luciferase reporter assay.
We revealed a novel oncogenic lncRNA MCM3AP-AS1, which is overexpressed in HCC and positively correlated with large tumor size, high tumor grade, advanced tumor stage and poor prognosis of HCC patients. MCM3AP-AS1 knockdown suppressed HCC cell proliferation, colony formation and cell cycle progression, and induced apoptosis in vitro, and depletion of MCM3AP-AS1 inhibited tumor growth of HCC in vivo. Mechanistically, MCM3AP-AS1 directly bound to miR-194-5p and acted as competing endogenous RNA (ceRNA), and subsequently facilitated miR-194-5p's target gene forkhead box A1 (FOXA1) expression in HCC cells. Interestingly, FOXA1 restoration rescued MCM3AP-AS1 knockdown induced proliferation inhibition, G1 arrest and apoptosis of HCC cells.
Our results recognized MCM3AP-AS1 as a novel oncogenic lncRNA, which indicated poor clinical outcomes in patients with HCC. MCM3AP-AS1 exerted an oncogenic role in HCC via targeting miR-194-5p and subsequently promoted FOXA1 expression. Our findings suggested that MCM3AP-AS1 could be a potential prognostic biomarker and therapeutic target for HCC.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
ADJUVANT-CTONG1104 (ClinicalTrials.gov identifier: NCT01405079), a randomized phase III trial, showed that adjuvant gefitinib treatment significantly improved disease-free survival (DFS) versus ...vinorelbine plus cisplatin (VP) in patients with epidermal growth factor receptor (
) mutation-positive resected stage II-IIIA (N1-N2) non-small-cell lung cancer (NSCLC). Here, we report the final overall survival (OS) results.
From September 2011 to April 2014, 222 patients from 27 sites were randomly assigned 1:1 to adjuvant gefitinib (n = 111) or VP (n = 111). Patients with resected stage II-IIIA (N1-N2) NSCLC and
-activating mutation were enrolled, receiving gefitinib for 24 months or VP every 3 weeks for four cycles. The primary end point was DFS (intention-to-treat ITT population). Secondary end points included OS, 3-, 5-year (y) DFS rates, and 5-year OS rate. Post hoc analysis was conducted for subsequent therapy data.
Median follow-up was 80.0 months. Median OS (ITT) was 75.5 and 62.8 months with gefitinib and VP, respectively (hazard ratio HR, 0.92; 95% CI, 0.62 to 1.36;
= .674); respective 5-year OS rates were 53.2% and 51.2% (
= .784). Subsequent therapy was administered upon progression in 68.4% and 73.6% of patients receiving gefitinib and VP, respectively. Subsequent targeted therapy contributed most to OS (HR, 0.23; 95% CI, 0.14 to 0.38) compared with no subsequent therapy. Updated 3y DFS rates were 39.6% and 32. 5% with gefitinib and VP (
= .316) and 5y DFS rates were 22. 6% and 23.2% (
= .928), respectively.
Adjuvant therapy with gefitinib in patients with early-stage NSCLC and
mutation demonstrated improved DFS over standard of care chemotherapy. Although this DFS advantage did not translate to a significant OS difference, OS with adjuvant gefitinib was one of the longest observed in this patient group compared with historic data.
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