RMA-CNN:A Residual Mixed Domain Attention CNN for Bearings Fault Diagnosis and Its Time-Frequency Domain Interpretability

Early fault diagnosis of bearings is crucial for ensuring safe and reliable operations.Convolutional neural networks(CNNs)have achieved significant breakthroughs in machinery fault diagnosis.However,complex and varying working conditions can lead to inter-class similarity and intra-class variability in datasets,making it more challenging for CNNs to learn discriminative features.Furthermore,CNNs are often considered“black boxes”and lack sufficient interpretability in the fault diagnosis field.To address these issues,this paper introduces a residual mixed domain attention CNN method,referred to as RMA-CNN.This method comprises multiple residual mixed domain attention modules(RMAMs),each employing one attention mechanism to emphasize meaningful features in both time and channel domains.This significantly enhances the network’s ability to learn fault-related features.Moreover,we conduct an in-depth analysis of the inherent feature learning mechanism of the attention module RMAM to improve the interpretability of CNNs in fault diagnosis applications.Experiments conducted on two datasets—a high-speed aeronautical bearing dataset and a motor bearing dataset—demonstrate that the RMA-CNN achieves remarkable results in diagnostic tasks.

FogMed:A Fog-Based Framework for Disease Prognosis Based Medical Sensor

Recently,an increasing number of works start investigating the combination of fog computing and electronic health(ehealth)applications.However,there are still numerous unresolved issues worth to be explored.For instance,there is a lack of investigation on the disease prediction in fog environment and only limited studies show,how the Quality of Service(QoS)levels of fog services and the data stream mining techniques influence each other to improve the disease prediction performance(e.g.,accuracy and time efficiency).To address these issues,we propose a fog-based framework for disease prediction based on Medical sensor data streams,named FogMed.This framework aims to improve the disease prediction accuracy by achieving two objectives:QoS guarantee of fog services and anomaly prediction of Medical data streams.We build a virtual FogMed environment and conduct comprehensive experiments on the public ECG dataset to validate the performance of FogMed.The experiment results show that it performs better than the cloud computing model for processing tasks with different complexities in terms of time efficiency.

A Database-Driven Algorithm for Building Top-k Service-Based Systems

The purpose of this work aims is to automatically build top-k(the number of suggested results)light weight service based systems(LitSBSs)on the basis of user-given keywords.Compared with our previous work,we use a score(oscore)to evaluate the keyword matching degree and QoS performance of a service so that we could find top-k LitSBSs with both high keyword matching degree and great QoS performance at the same time.In addition,to guarantee the quality of found top-k LitSBSs and improve the time efficiency,we redesign the database-driven algorithm(LitDB).We add the step of referential services selecting into the process of the LitDB,which could prioritize services with high quality(high keyword matching degree and great QoS performance).We design comprehensive experiments to demonstrate the great time performance of LitDB.

Multifunctional regulatory protein connective tissue growth factor (CTGF):A potential therapeutic target for diverse diseases

Connective tissue growth factor(CTGF),a multifunctional protein of the CCN family,regulates cell proliferation,differentiation,adhesion,and a variety of other biological processes.It is involved in the disease-related pathways such as the Hippo pathway,p53 and nuclear factor kappa-B(NF-κB)pathways and thus contributes to the developments of inflammation,fibrosis,cancer and other diseases as a downstream effector.Therefore,CTGF might be a potential therapeutic target for treating various diseases.In recent years,the research on the potential of CTGF in the treatment of diseases has also been paid more attention.Several drugs targeting CTGF(monoclonal antibodies FG3149 and FG3019)are being assessed by clinical or preclinical trials and have shown promising outcomes.In this review,the cellular events regulated by CTGF,and the relationships between CTGF and pathogenesis of diseases are systematically summarized.In addition,we highlight the current researches,focusing on the preclinical and clinical trials concerned with CTGF as the therapeutic target.

Synthesis of Mg-based composite material with in-situ formed LaH_3 and its hydrogen storage characteristics

In this work,a Mg-based composite material with in-situ formed LaH3, Mg2 NiH4-LiBH4 ＋ 20 wt% LaH3,was prepared by ball milling LiBH4 and hydrogenated LaMg2 Ni and Mg2 Ni powder mixture, followed by heat treatment at 573 K. The onset dehydrogenation temperature of the composite is reduced by 50 K compared with that of Mg2 NiH4-LiBH4. The LaH3-doped composite shows faster kinetics,absorbing1.43 wt% hydrogen within 100 s at 423 K,which is 6.5 times faster than Mg2 NiH4-LiBH4. Moreover,the composite releases 1.24 wt% hydrogen within 500 s at 573 K,0.69 wt% higher than Mg2 NiH4-LiBH4. The activation energy of the composite is reduced by 8.2 and 80 kJ/mol compared with that of Mg2 NiH4-LiBH4 and commercial MgH2, respectively. The improvement in hydrogen storage properties is attributed to the fact that LaH3 promotes the generation of nano-sized spongy Mg structure, which has good catalytic activity during the subsequent hydrogenation/dehydrogenation process.

Author correction to‘Multifunctional regulatory protein connective tissue growth factor(CTGF):A potential therapeutic target for diverse diseases’[Acta pharmaceutica sinica B 12(2022)1740-1760]

The authors regret that there was an error in 7.Conclusion and prospect section of the article.The last paragraph of this section‘Under particular external…integrins interact with CT domain’is supposed to be the content of the figure legend(Fig.1).It is superfluous in this part and should be deleted.The revision does not affect any conclusions of this work.

Investigation of typical residential block typologies and their impact on pedestrianlevel microclimate in summers in Nanjing, China

The morphology of urban residential blocks in China,which is strictly affected by regulations,can potentially improve or deteriorate microclimates.This paper first proposes a framework for identifying typical residential block typologies using Nanjing as an example.A thorough investigation,consisting of 114 samples,was conducted,and 18 typical residential block typologies were summarized.Second,3D non-isothermal numerical simulations were performed on the hottest days of summer using the ENVI-met.The effect of morphological indices on the microclimate at the pedestrian level was explored using statistical methods and a novel graphic method named m-SpaceMate.The results revealed a strong correlation between the urban heat island intensity(UHII),mean radiation temperature,and universal thermal climate index(UTCI)and floor area ratio(FAR),as well as between wind velocity(U)and building coverage ratio(BCR).A significant increase in FAR(by approximately 1.0)can result in a low UTCI that was driven by MRT and shading conditions.Six-floor blocks,with FAR between 1.8 and 2.1,had a better overall thermal environment(except for lower U)than that of 11-floor blocks.When considering a similar BCR,blocks with slab-type buildings tended to have a U that was higher by approximately 30%.

Intranasal boosting with RBD-HR protein vaccine elicits robust mucosal and systemic immune responses

The emergence of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)variants has decreased the efficacy of SARs-CoV-2 vaccines in containing coronavirus disease 2019(CoVID-19)over time,and booster vaccination strategies are urgently necessitated to achieve sufficient protection.Intranasal immunization can improvemucosal immunity,offer-ing protection against the infection and sustaining the spread of SARS-CoV-2.In this study,an intranasal booster of the RBD-HR vaccine after two doses of the mRNA vaccine significantly increased the levels of specific binding antibodies in serum,nasal lavage fluid,and bronchoal-veolar lavage fluid compared with only two doses of mRNA vaccine.After intranasal boosting with the RBD-HR vaccine,the levels of serum neutralizing antibodies against prototype and variant strains of SARS-Cov-2 pseudoviruses weremarkedly higher than those in mice receiving mRNA vaccine alone,and intranasal boosting with the RBD-HR vaccine also inhibited the bind-ing of RBD to hACE2 receptors.Furthermore,the heterologous intranasal immunization regimen promoted extensive memory T cell responses and activated CD103+dendritic cells in the respiratory mucosa,and potently enhanced the formation of T follicular helper cells and germinal center B cells in vital immune organs,including mediastinal lymph nodes,inguinal lymph nodes,and spleen.Collectively,these data infer that heterologous intranasal boosting with the RBD-HR vaccine elicited broad protective immunity against SARS-CoV-2 both locallyandsystemically.