Morphological Classification of Infrared Galaxies Based on WISE

This study introduces a novel convolutional neural network,the WISE Galaxy Classification Network(WGC),for classifying spiral and elliptical galaxies using Wide-field Infrared Survey Explorer(WISE)images.WGC attains an accuracy of 89.03%,surpassing the combined use of K-means or SVM with the Color-Color method in more accurately identifying galaxy morphologies.The enhanced variant,WGC_mag,integrates magnitude parameters with image features,further boosting the accuracy to 89.89%.The research also delves into the criteria for galaxy classification,discovering that WGC primarily categorizes dust-rich images as elliptical galaxies,corresponding to their lower star formation rates,and classifies less dusty images as spiral galaxies.The paper explores the consistency and complementarity of WISE infrared images with SDSS optical images in galaxy morphology classification.The SDSS Galaxy Classification Network(SGC),trained on SDSS images,achieved an accuracy of 94.64%.The accuracy reached 99.30% when predictions from SGC and WGC were consistent.Leveraging the complementarity of features in WISE and SDSS images,a novel variant of a classifier,namely the Multi-band Galaxy Morphology Integrated Classifier,has been developed.This classifier elevates the overall prediction accuracy to 95.39%.Lastly,the versatility of WGC was validated in other data sets.On the HyperLEDA data set,the distinction between elliptical galaxies and Sc,Scd and Sd spiral galaxies was most pronounced,achieving an accuracy of 90%,surpassing the classification results of the Galaxy Zoo 2 labeled WISE data set.This research not only demonstrates the effectiveness of WISE images in galaxy morphology classification but also represents an attempt to integrate multi-band astronomical data to enhance understanding of galaxy structures and evolution.

Strong metal-support interactions between highly dispersed Cu^(+) species and ceria via mix-MOF pyrolysis toward promoted water-gas shift reaction

The modulation of metal-support interfacial interaction is significant but challenging in the design of high-efficiency and high-stability supported catalysts.Here,we report a synthetic strategy to upgrade Cu-CeO_(2)interfacial interaction by the pyrolysis of mixed metal-organic framework(MOF)structure.The obtained highly dispersed Cu/CeO_(2)-MOF catalyst via this strategy was used to catalyze water-gas shift reaction(WGSR),which exhibited high activity of 40.5μmolCOgcat^(-1).s^(-1)at 300℃and high stability of about 120 h.Based on comprehensive studies of electronic structure,pyrolysis strategy has significant effect on enhancing metal-support interaction and then stabilizing interfacial Cu^(+)species under reaction conditions.Abundant Cu^(+)species and generated oxygen vacancies over Cu/CeO_(2)-MOF catalyst played a key role in CO molecule activation and H2O molecule dissociation,respectively.Both collaborated closely and then promoted WGSR catalytic performance in comparison with traditio nal supported catalysts.This study shall offer a robust approach to harvest highly dispersed catalysts with finely-tuned metal-support interactions for stabilizing the most interfacial active metal species in diverse heterogeneous catalytic reactions.

Forced propagation method for Monte Carlo fission source convergence acceleration in the RMC

In loosely coupled or large-scale problems with high dominance ratios,slow fission source convergence can take extremely long time,reducing Monte Carlo(MC)criticality calculation efficiency.Although various acceleration methods have been developed,some methods cannot reduce convergence times,whereas others have been limited to specific problem geometries.In this study,a new fission source convergence acceleration(FSCA)method,the forced propagation(FP)method,has been proposed,which forces the fission source to propagate and accelerate fission source convergence.Additionally,some stabilization techniques have been designed to render the method more practical.The resulting stabilized method was then successfully implemented in the MC transport code,and its feasibility and effectiveness were tested using the modified OECD/NEA,one-dimensional slab benchmark,and the Hoogenboom full-core problem.The comparison results showed that the FP method was able to achieve efficient FSCA.

Hybrid windowed networks for on-the-fly Doppler broadening in RMC code

On-the-fly Doppler broadening of cross sections is important in Monte Carlo simulations,particularly in Monte Carlo neutronics-thermal hydraulics coupling simulations.Methods such as Target Motion Sampling(TMS)and windowed multipole as well as a method based on regression models have been developed to solve this problem.However,these methods have limitations such as the need for a cross section in an ACE format at a given temperature or a limited application energy range.In this study,a new on-the-fly Doppler broadening method based on a Back Propagation(BP)neural network,called hybrid windowed networks(HWN),is proposed to resolve the resonance energy range.In the HWN method,the resolved resonance energy range is divided into windows to guarantee an even distribution of resonance peaks.BP networks with specially designed structures and training parameters are trained to evaluate the cross section at a base temperature and the broadening coefficient.The HWN method is implemented in the Reactor Monte Carlo(RMC)code,and the microscopic cross sections and macroscopic results are compared.The results show that the HWN method can reduce the memory requirement for cross-sectional data by approximately 65%;moreover,it can generate keff,power distribution,and energy spectrum results with acceptable accuracy and a limited increase in the calculation time.The feasibility and effectiveness of the proposed HWN method are thus demonstrated.

Prevention and management of fractured instruments in endodontic treatment

Intracanal instrument fracture is an unpredictable and problematic occurrence that can prevent adequatecleaning and shaping procedures and influence the prognosis of endodontic treatment. The prevalence of instrument fracture is reported to range between 0.28% and 16.2%. This article presents an overview of the prevention and management of instruments fractured during endodontic therapy on the basis of literature retrieved from Pub Med and selected journal searches. Instrument fracture occurs because of reduced metal fatigue and/or torsional resistance. The reasons include canal morphology and curvature, manufacturing processes and instrument design, instrument use times and technique, rotational speeds and operator experience. With the development of various equipment and techniques, most of the retained instrument separations can be removed safely. However, in canals without associated periapical disease not every fractured separation should be removed from difficult locations because of the increased risk for root perforation and fracture. In difficult cases, either retain or bypass the fragment in the root canal and ensure regular follow-up reviews. Fractured instruments retained in the presence of periapical disease reduce significantly the prognosis of endodontically treated teeth, indicating a greater need to attempt the removal or bypass of the file separations. Apical surgery might be required in some instances, emphasizing the importance of preventing instrument fracture.

Research progress of kynurenine pathway in Alzheimer's disease

The kynurenine pathway(KP)has been shown to be involved in the pathophysiology of dementia diseases.Among the dementia diseases,the neurodegenerative diseases Alzheimer's disease and cerebrovascular diseases are vascular.The highest incidence of dementia.KP activation results in the production of neuroactive metabolites,which may interfere with normal neuronal function,leading to the appearance of symptoms of cognitive impairment.This review investigated KP's involvement in the neurological diseases Alzheimer's disease and vascular dementia,suggesting that KP is a potential therapeutic target for both diseases.

Research progress of quinolinic acid in neuropsychiatric diseases

Quinolinic acid is a neurotoxic substance produced by tryptophan through the kynurenine metabolism pathway.Quinolinic acid is involved in the pathological processes of Alzheimer's disease,Parkinson's disease,Huntington's disease,amyotrophic lateral sclerosis,encephalitis,depression,and schizophrenia.The above process is realized through pathophysiological processes such as excitatory neurotoxicity,metabolic damage,free radical generation and oxidative stress,participation in inflammatory response,induction of neuron and astrocytic apoptosis.This article will explain the metabolic regulation,biological characteristics,and neurotoxicity of quinolinic acid.The research progress of quinolinic acid in Alzheimer's disease,Parkinson's disease,Huntington's disease,depression and subacute sclerosing panencephalitis is also described.

Rhodium-catalyzed Doyle-Kirmse rearrangement reactions of sulfoxoniun ylides

Doyle-Kirmse rearrangement reactions have received continuous attention as an important method for constructing complex chemical structures. Herein, we disclosed an efficient rhodium-catalyzed DoyleKirmse rearrangement reaction, which can simultaneously construct C–C bonds and C–X(X = S/Se) bonds using sulfoxonium ylides as starting materials to obtain sulfur-or selenium-containing compounds. This strategy is characterized by the safer and greener carbene precursor, high yields and broad substrate scope, possessing a wide range of application.

Assessment of circulating tumor DNA in cerebrospinal fluid by whole exome sequencing to detect genomic alterations of glioblastoma

Background:Cerebrospinal fluid(CSF)has been demonstrated as a better source of circulating tumor DNA(ctDNA)than plasma for brain tumors.However,it is unclear whether whole exome sequencing(WES)is qualified for detection of ctDNA in CSF.The aim of this study was to determine if assessment of ctDNA in CSF by WES is a feasible approach to detect genomic alterations of glioblastoma.Methods:CSFs of ten glioblastoma patients were collected pre-operatively at the Department of Neurosurgery,Sun Yat-sen University Cancer Center.ctDNA in CSF and genome DNA in the resected tumor were extracted and subjected to WES.The identified glioblastoma-associated mutations from ctDNA in CSF and genome DNA in the resected tumor were compared.Results:Due to the ctDNA in CSF was unqualified for exome sequencing for one patient,nine patients were included into the final analysis.More glioblastoma-associated mutations tended to be detected in CSF compared with the corresponding tumor tissue samples(3.56±0.75 vs.2.22±0.32,P=0.097),while the statistical significance was limited by the small sample size.The average mutation frequencies were similar in CSF and tumor tissue samples(74.1%±6.0%vs.73.8%±6.0%,P=0.924).The R132H mutation of isocitrate dehydrogenase 1 and the G34V mutation of H3 histone,family 3A(H3F3A)which had been reported in the pathological diagnoses were also detected from ctDNA in CSF by WES.Patients who received temozolomide chemotherapy previously or those whose tumor involved subventricular zone tended to harbor more mutations in their CSF.Conclusion:Assessment of ctDNA in CSF by WES is a feasible approach to detect genomic alterations of glioblastoma,which may provide useful information for the decision of treatment strategy.