Fault diagnosis of rotor using EMD thresholding-based de-noising combined with probabilistic neural network

De-noising of signal processing is crucial for fault diagnosis in order to successfully conduct feature extraction and is an efficient method for accurate determination of cause. In this paper, the empirical mode decomposition (EMD) thresholding-based de-noising method and probabilistic neural network (PNN) are respectively used in the de-noising of the vibration signal and rotor fault diagnosis and compared with wavelet thresholding-based de-noising technology and back propagation neural network (BPNN). The results show that the clear iterative EMD interval thresholding performs better than wavelet thresholding in the de-noising of the vibration signal, and avoids the determination of wavelet basis and decomposition level. In addition, the PNN created by feature samples does not require training and has a higher accuracy than BPNN

Diversity and soil chemical properties jointly explained the basal area in karst forest

IntroductionPlant diversity and soil chemical properties are important factors affecting the plant growth. We sought to compare the explanatory rates of diversity and soil chemical properties in explaining the variation of basal area in karst forests, and also sought to compare the relative importance of the niche complementarity and mass ratio hypotheses.MethodsOn the basis of linear regression and structural equation modelling, we examined the correlation between the basal area of plant communities and species diversity, functional diversity, phylogenetic diversity, the community-weighted mean (CWM) of traits, and soil chemical properties, using data obtained from 35 monitoring plots in southwest China.ResultsSpecies, functional, and phylogenetic diversities were all significantly correlated with the basal area of the plant community, among the indices of which, Faith’s phylogenetic diversity was found to have the greatest explanatory power for basal area. These plant diversity indices can better explain the variation in basal area than the CWM of traits, suggesting the niche complementarity hypothesis is more applicable than the mass ratio hypothesis. Moreover, soil chemical properties also have an equal important impact. Different chemical properties were found to show significant positive correlations with basal area, and their total effects on basal area were shown to be greater than the CWM of traits.DiscussionAttention should be paid to diversity and soil chemical properties. This study provides theoretical guidance for understanding biodiversity maintenance mechanisms and protecting karst forests

LinkLouvain: Link-Aware A/B Testing and Its Application on Online Marketing Campaign

A lot of online marketing campaigns aim to promote user interaction. The average treatment effect (ATE) of campaign strategies need to be monitored throughout the campaign. A/B testing is usually conducted for such needs, whereas the existence of user interaction can introduce interference to normal A/B testing. With the help of link prediction, we design a network A/B testing method LinkLouvain to minimize graph interference and it gives an accurate and sound estimate of the campaign's ATE. In this paper, we analyze the network A/B testing problem under a real-world online marketing campaign, describe our proposed LinkLouvain method, and evaluate it on real-world data. Our method achieves significant performance compared with others and is deployed in the online marketing campaign.Comment: Accepted by the Industrial & Practitioner Track of the 26th International Conference on Database Systems for Advanced Applications (DASFAA 2021

The traditional Chinese medicine formulation Ruanjian Sanjie Decoction regulates the tumor matrix and improves the anti-tumor efficacy of TP-PEG-LPs

The Ruanjian Sanjie Decoction (RSD) is a traditional Chinese medicine (TCM) formulation consisting of Spica Prunellae, Pseudobulbus Cremastrae Seu Pleiones, Concha Ostreae and Semen Coicis, and widely used as an adjuvant in anti-cancer therapy. The aim of this study was to determine the effects of RSD on the extracellular matrix (ECM) of tumors, and on the efficacy of anti-cancer nano-formulations in a tumor-bearing mouse model. The mice were treated with triptolide encapsulated in PEG-modified liposomes (TP-PEG-LPs), either alone or in combination with RSD. The combination treatment significantly retarded tumor growth relative to the untreated controls, indicating the potent adjuvant effect of RSD in targeted anti-cancer therapy. In addition, RSD also reduced the amount of total collagen and collagen I and increased that of collagen III in the tumor ECM, along with decreasing the expression of the pro-angiogenic VEGF. Finally, even high doses of RSD did not significantly affect the liver and kidney function or body weight, indicating low toxicity

Marketing Budget Allocation with Offline Constrained Deep Reinforcement Learning

We study the budget allocation problem in online marketing campaigns that utilize previously collected offline data. We first discuss the long-term effect of optimizing marketing budget allocation decisions in the offline setting. To overcome the challenge, we propose a novel game-theoretic offline value-based reinforcement learning method using mixed policies. The proposed method reduces the need to store infinitely many policies in previous methods to only constantly many policies, which achieves nearly optimal policy efficiency, making it practical and favorable for industrial usage. We further show that this method is guaranteed to converge to the optimal policy, which cannot be achieved by previous value-based reinforcement learning methods for marketing budget allocation. Our experiments on a large-scale marketing campaign with tens-of-millions users and more than one billion budget verify the theoretical results and show that the proposed method outperforms various baseline methods. The proposed method has been successfully deployed to serve all the traffic of this marketing campaign.Comment: WSDM 23, Best Paper Candidat

Identification of immune-related biomarkers for glaucoma using gene expression profiling

Introduction: Glaucoma, a principal cause of irreversible vision loss, is characterized by intricate optic neuropathy involving significant immune mechanisms. This study seeks to elucidate the molecular and immune complexities of glaucoma, aiming to improve our understanding of its pathogenesis.Methods: Gene expression profiles from glaucoma patients were analyzed to identify immune-related differentially expressed genes (DEGs). Techniques used were weighted gene co-expression network analysis (WGCNA) for network building, machine learning algorithms for biomarker identification, establishment of subclusters related to immune reactions, and single-sample gene set enrichment analysis (ssGSEA) to explore hub genes’ relationships with immune cell infiltration and immune pathway activation. Validation was performed using an NMDA-induced excitotoxicity model and RT-qPCR for hub gene expression measurement.Results: The study identified 409 DEGs differentiating healthy individuals from glaucoma patients, highlighting the immune response’s significance in disease progression. Immune cell infiltration analysis revealed elevated levels of activated dendritic cells, natural killer cells, monocytes, and immature dendritic cells in glaucoma samples. Three hub genes, CD40LG, TEK, and MDK, were validated as potential diagnostic biomarkers for high-risk glaucoma patients, showing increased expression in the NMDA-induced excitotoxicity model.Discussion: The findings propose the three identified immune-related genes (IRGs) as novel diagnostic markers for glaucoma, offering new insights into the disease's pathogenesis and potential therapeutic targets. The strong correlation between these IRGs and immune responses underscores the intricate role of immunity in glaucoma, suggesting a shift in the approach to its diagnosis and treatment

Research Progress on the Application of Novel Non-thermal Sterilization Technologies in Fermented Fruit and Vegetable Products

Fermented fruit and vegetable products are an important part of traditional fermented food in China. During production, fresh vegetables and fruits are used as raw materials. The fermentation is conducted by the interactions between microorganisms including lactic acid bacteria and fungi which are naturally carried by raw materials. After fermentation, the composition and quantity of microorganisms in fruits and vegetables tend to become out of control, which often leads to post-acidification, softening, spoilage and other problems. Therefore, the development of sterilization technology suitable for fermented fruit and vegetable products has important industrial value. Compared with the destructive effect of traditional heat sterilization, the non-thermal sterilization technology without heating can not only kill the spoilage and pathogenic microorganisms, but also reduce the impact on probiotics, and greatly alleviate the deterioration of fermented fruit and vegetable products. Therefore, non-thermal sterilization technologies have gradually become one of the research hotspots in the field of fermented fruit and vegetable products sterilization. In this paper, the application progress of common non-thermal sterilization technologies in fermented fruit and vegetable products is reviewed. The sterile effect and influencing factors of non-thermal sterilization technologies in fermented fruit and vegetable products are summarized. Its influence on quality and safety attributes of products is discussed. The aim of this study is to provide a theoretical basis for the large-scale application of non-thermal sterilization technologies in the industrial production of fermented fruit and vegetable products

Global assessment of spatiotemporal changes of frequency of terrestrial wind speed

Wind energy, an important component of clean energy, is highly dictated by the disposable wind speed within the working regime of wind turbines (typically between 3 and 25 m s−1 at the hub height). Following a continuous reduction ('stilling') of global annual mean surface wind speed (SWS) since the 1960s, recently, researchers have reported a 'reversal' since 2011. However, little attention has been paid to the evolution of the effective wind speed for wind turbines. Since wind speed at hub height increases with SWS through power law, we focus on the wind speed frequency variations at various ranges of SWS through hourly in-situ observations and quantify their contributions to the average SWS changes over 1981–2021. We found that during the stilling period (here 1981–2010), the strong SWS (⩾ 5.0 m s−1, the 80th of global SWS) with decreasing frequency contributed 220.37% to the continuous weakening of mean SWS. During the reversal period of SWS (here 2011–2021), slight wind (0 m s−1 < SWS < 2.9 m s−1) contributed 64.07% to a strengthening of SWS. The strengthened strong wind (⩾ 5.0 m s−1) contributed 73.38% to the trend change of SWS from decrease to increase in 2010. Based on the synthetic capacity factor series calculated by considering commercial wind turbines (General Electric GE 2.5-120 model with rated power 2.5 MW) at the locations of the meteorological stations, the frequency changes resulted in a reduction of wind power energy (−10.02 TWh yr−1, p < 0.001) from 1981 to 2010 and relatively weak recovery (2.67 TWh yr−1, p < 0.05) during 2011–2021.This study was supported by the National Natural Science Foundation of China (Grant No. 42071022), Guangdong Basic and Applied Basic Research Fund (2022A1515240070) and the start-up fund provided by Southern University of Science and Technology (no. 29/Y01296122). C A-M was supported by the IBER-STILLING (RTI2018-095749-A-I00, MCIU/AEI/FEDER,UE); VENTS (GVA-AICO/2021/023); the CSIC Interdisciplinary Thematic Platform (PTI) Clima (PTI-CLIMA); and the 2021 Leonardo Grant for Researchers and Cultural Creators, BBVA Foundation. RJHD was supported by the Met Office Hadley Centre Climate Programme funded by BEIS and by the UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund. SJ was supported by the Ramon y Cajal program and the OPEN project (RYC2020-029993-I and TED2021-131074B-I00, MCIU/AEI/FEDER,UE)

High Incidence and Endemic Spread of NDM-1-Positive Enterobacteriaceae in Henan Province, China

The emergence and spread of New Delhi metallo-β-lactamase 1 (NDM-1)-producing carbapenem-resistant Enterobacteriaceae (CRE) present an urgent threat to human health. In China, the blaNDM-1 gene has been reported mostly in Acinetobacter spp. but is rarely found in Enterobacteriaceae. Here, we report a high incidence and endemic spread of NDM-1-producing CRE in Henan Province in China. Sixteen (33.3%) of the 48 CRE isolates obtained from patients during June 2011 to July 2012 were positive for blaNDM-1, and the gene was found to be carried on plasmids of various sizes (∼55 to ∼360 kb). These plasmids were readily transferrable to recipient Escherichia coli by conjugation, conferred resistance to multiple antibiotics, and belonged to multiple replicon types. The blaNDM-1-positive CRE isolates were genetically diverse, and six new multilocus sequence typing (MLST) sequence types were linked to the carriage of NDM-1. Five of the isolates were classified as extensively drug-resistant (XDR) isolates, four of which also carried the fosA3 gene conferring resistance to fosfomycin, an alternative drug for treating infections by CRE. In each blaNDM-1-positive CRE isolate, the blaNDM-1 gene was downstream of an intact ISAba125 element and upstream of the bleMBL gene. Furthermore, gene environment analysis suggested the possible transmission of blaNDM-1-containing sequences from Acinetobacter spp. to Klebsiella pneumoniae and Klebsiella oxytoca. These findings reveal the emergence and active transmission of NDM-1-positive CRE in China and underscore the need for heightened measures to control their further spread

Early detection of lung cancer in a real-world cohort via tumor-associated immune autoantibody and imaging combination

BackgroundEfficient early detection methods for lung cancer can significantly decrease patient mortality. One promising approach is the use of tumor-associated autoantibodies (TAABs) as a diagnostic tool. In this study, the researchers aimed to evaluate the potential of seven TAABs in detecting lung cancer within a population undergoing routine health examinations. The results of this study could provide valuable insights into the utility of TAABs for lung cancer screening and diagnosis.MethodsIn this study, the serum concentrations of specific antibodies were measured using enzyme-linked immunosorbent assay (ELISA) in a cohort of 15,430 subjects. The efficacy of both a 7-TAAB panel and LDCT for lung cancer detection were evaluated through receiver operating characteristic (ROC) analyses, with sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) being assessed and compared. These results could have significant implications for the development of improved screening methods for lung cancer.ResultsOver the 12-month observation period, 26 individuals were diagnosed with lung cancer. The 7-TAAB panel demonstrated promising sensitivity (61.5%) and a high degree of specificity (88.5%). The panel’s area under the receiver operating characteristic (ROC) curve was 0.8062, which was superior to that of any individual TAAB. In stage I patients, the sensitivity of the panel was 50%. In our cohort, there was no gender or age bias observed. This 7-TAAB panel showed a sensitivity of approximately 60% in detecting lung cancer, regardless of histological subtype or lesion size. Notably, ground-glass nodules had a higher diagnostic rate than solid nodules (83.3% vs. 36.4%, P = 0.021). The ROC analyses further revealed that the combination of LDCT with the 7-TAAB assay exhibited a significantly superior diagnostic efficacy than LDCT alone.ConclusionIn the context of the study, it was demonstrated that the 7-TAAB panel showed improved detective efficacy of LDCT, thus serving as an effective aid for the detection of lung cancer in real-world scenarios