Dependence of Rydberg-atom-based sensor performance on different Rydberg atom populations in one atomic-vapor cell

The atomic-vapor cell is a vital component for Rydberg atomic microwave sensors,and impacts on overall capability of Rydberg sensors.However,the conventional analysis approach on effect of vapor-cell length contains two implicit assumptions,that is,the same atomic population density and buffer gas pressure,which make it unable to accurately capture actual response about effect of Rydberg-atom-based sensor performance on different Rydberg atom populations.Here,utilizing a stepped cesium atomic-vapor cell with five different dimensions at the same atomic population density and buffer gas pressure,the height and full width at half maximum of electromagnetically induced transparency(EIT)signal,and the sensitivity of the atomic superheterodyne sensor are comprehensively investigated under conditions of the same Rabi frequencies(saturated laser power).It is identified that EIT signal height is proportional to the cell length,full width at half maximum and sensitivity grow with the increment of cell length to a certain extent.Employing the coherent integration signal theory and atomic linear expansion coefficient method,theoretical analysis of the EIT height and sensitivity are further investigated.The results could shed new light on understanding and design of ultrahigh-sensitivity Rydberg atomic microwave sensors and find promising applications in quantum measurement,communication,and imaging.

Which Features of the SST Forcing Error Most Likely Disturb the Simulated Intensity of Tropical Cyclones?

Among all of the sources of tropical cyclone(TC) intensity forecast errors, the uncertainty of sea surface temperature(SST) has been shown to play a significant role. In the present study, we determine the SST forcing error that causes the largest simulation error of TC intensity during the entire simulation period by using the WRF model with time-dependent SST forcing. The SST forcing error is represented through the application of a nonlinear forcing singular vector(NFSV)structure. For the selected 12 TC cases, the NFSV-type SST forcing errors have a nearly coherent structure with positive(or negative) SST anomalies located along the track of TCs but are especially concentrated in a particular region. This particular region tends to occur during the specific period of the TCs life cycle when the TCs present relatively strong intensity, but are still intensifying just prior to the mature phase, especially within a TC state exhibiting a strong secondary circulation and very high inertial stability. The SST forcing errors located along the TC track during this time period are verified to have the strongest disturbing effect on TC intensity simulation. Physically, the strong inertial stability of TCs during this time period induces a strong response of the secondary circulation from diabatic heating errors induced by the SST forcing error. Consequently, this significantly influences the subsidence within the warm core in the eye region, which,in turn, leads to significant errors in TC intensity. This physical mechanism explains the formation of NSFV-type SST forcing errors. According to the sensitivity of the NFSV-type SST forcing errors, if one increases the density of SST observations along the TC track and assimilates them to the SST forcing field, the skill of TC intensity simulation generated by the WRF model could be greatly improved. However, this adjustment is most advantageous in improving simulation skill during the time period when TCs become strong but are still intensifying just prior to reaching full maturity. In light of this, the region along the TC track but in the time period of TC movement when the NFSV-type SST forcing errors occur may represent the sensitive area for targeting observation for SST forcing field associated with TC intensity simulation.

Exploration on Research Methods for Exploring Human Response to Luminous Environment with Chromogenic Windows Applied

Chromogenic windows enable both energy-saving and daylighting regulation.However,the human response to the luminous environment affected by them is difficult to test,since their features of dynamic change and tinting automatically.This study explores the research methods,including experimental design and statistical analysis,by literature review and an experiment demonstration.The results show that a proper size of the test room is significant to obtain desired data,and the advanced VR technologies have the potential to be applied for testing these dynamic variables.Bayesian approaches are recommended to be tried and get more accurate interference about the experimental results.

The increasing expression of GPX7 related to the malignant clinical features leading to poor prognosis of glioma patients

Background:Glioma is the most common malignant brain tumor in adults.The standard treatment scheme of glioma is surgical resection combined alternative radio-and chemotherapy.However,the outcome of glioma patients was unsatisfied.Here,we aimed to explore the molecular and biological function characteristics of GPX7 in glioma.Methods:The multidimensional data of glioma samples were downloaded from Chinese Glioma Genome Atlas(CGGA).RT-qPCR method was used to identify the expression status of GPX7.Kaplan–Meier curves and Cox regression analysis were used to explore the prognostic value of GPX7.Gene Set Enrichment Analysis(GSEA)was applied to investigate the GPX7-related functions in glioma.Results:The results indicated that the expression of GPX7 in glioma was higher compared to that in normal brain tissue.Univariate and multivariate Cox regression analyses confirmed that the expression value of GPX7 was an independent prognostic factor in glioma.The GSEA analysis showed that GPX7 was significantly enriched in the cell cycle pathway,ECM pathway,focal adhesion pathway,and toll-like receptor pathway.Conclusions:The GPX7 was recommended as an independent risk factor for patients diagnosed with glioma for the first time and GPX7 could be potentially used as the therapy target in future.Furthermore,we attempted to explore a potential biomarker for improving the diagnosis and prognosis of patients with glioma.

New biomarker:the gene HLA-DRA associated with low-grade glioma prognosis

Background:Low-grade gliomas(LGG)are WHO grade II tumors presenting as the most common primary malignant brain tumors in adults.Currently,LGG treatment involves either or a combination of surgery,radiation therapy,and chemotherapy.Despite the knowledge of constitutive genetic risk factors contributing to gliomas,the role of single genes as diagnostic and prognostic biomarkers is limited.The aim of the current study is to discover the predictive and prognostic genetic markers for LGG.Methods:Transcriptome data and clinical data were obtained from The Cancer Genome Atlas(TCGA)database.We first performed the tumor microenvironment(TME)survival analysis using the Kaplan-Meier method.An analysis was undertaken to screen for differentially expressed genes.The function of these genes was studied by Gene Ontology(GO)enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis.Following which a protein-protein interaction network(PPI)was constructed and visualized.Univariate and multivariate COX analyses were performed to obtain the probable prognostic genes.The key genes were selected by an intersection of core and prognostic genes.A clinical correlation analysis of single-gene expression was undertaken.GSEA enrichment analysis was performed to identify the function of key genes.Finally,a single gene-related correlation analysis was performed to identify the core immune cells involved in the development of LGG.Results:A total of 529 transcriptome data and 515 clinical samples were obtained from the TCGA.Immune cells and stromal cells were found to be significantly increased in the LGG microenvironment.The top five core genes intersected with the top 38 prognostically relevant genes and two key genes were identified.Our analysis revealed that a high expression of HLA-DRA was associated with a poor prognosis of LGG.Correlation analysis of immune cells showed that HLA-DRA expression level was related to immune infiltration,positively related to macrophage M1 phenotype,and negatively related to activation of NK cells.Conclusions:HLA-DRA may be an independent prognostic indicator and an important biomarker for diagnosing and predicting survival in LGG patients.It may also be associated with the immune infiltration phenotype in LGG.

Dynamic profiles of rose jam metabolomes reveal sugar-pickling impacts on their nutrient content

Rose jam is a Chinese traditional food,usually preserved from rose petals and sugar.There were few metabolomics studies on rose petals accompanying pickling.We conducted a LC-MS/MS based metabolomics study to feature the dynamics profiles of rose jam nutrients.The rose jams with 10-,20-and 30-days’sugar-pickling under different sun-exposure gradients were analyzed.Ultimately,there were 838 and 213 rose jam metabolites being identified in positive and negative ion mode,respectively.And a total of 492 differential metabolites accompanying pickling were detected.The dynamic temporal profiles of rose nutrients revealed that metabolites in rose jams showed directional distribution according to sugar-pickle times and parallel distribution according to sun exposure gradients.The temporal features of the nutrients suggested that the sugar pickling process could remain most of rose nutrients and expand the diversity of them.These results revealed the influence of sugar ratio and exposure time on rose jams nutrition composition and might be used as a theoretical guidance for the process optimization of rose jams industrial standardization production.