Track: Tracerouting in SDN networks with arbitrary network functions

The centralization of control plane in Software defined networking (SDN) creates a paramount challenge on troubleshooting the network as packets are ultimately forwarded by distributed data planes. Existing path tracing tools largely utilize packet tags to probe network paths among SDN-enabled switches. However, network functions (NFs) or middleboxes, whose presence is ubiquitous in today's networks, can drop packets or alter their tags - an action that can collapse the probing mechanism. In addition, sending probing packets through network functions could corrupt their internal states, risking of the correctness of servicing logic (e.g., incorrect load balancing decisions). In this paper, we present a novel troubleshooting tool, Track, for SDN-enabled network with arbitrary NFs. Track can discover the forwarding path including NFs taken by any packets, without changing the forwarding rules in switches and internal states of NFs. We have implemented Track on RYU controller. Our extensive experiment results show that Track can achieve 95.08% and 100% accuracy for discovering forwarding paths with and without NFs respectively, and can efficiently generate traces within 3 milliseconds per hop

Collective Description of Density Matrix of Identical Multi-level Atoms for Superradiance

A collective description of density matrix is presented for identical multi-level atoms, which are either excited initially, driven coherently or pumped incoherently. The density matrix is defined as expectation value of projection or transition operators in a basis of atom's product states. The identical matrix elements are identified with several integers, which specify uniquely the involved operators. To remove the redundancy, these identical elements are treated as single quantity and the equation for this quantity is dervied by mapping the transition or projection operators to a single vector specified with these integers. As a result, the number of computed elements increases polynomially rather than exponentially with the number of atoms. As an example, we carry out exact simulation of hundreds of two-level atoms and demonstrate the different conditions for observing superradiance and superfluorescence

Data_Sheet_1_Decomposing differences in the chronic disease condition between rural and urban older adults in China: a cross-sectional analysis.docx

BackgroundWith the increasing in aging in China, there has been an increase in older adults suffering from chronic diseases. However, little is known about the differences in chronic disease conditions between rural and urban older adults. The objective of this study is to identify chronic disease conditions and investigate the factors that cause differences in chronic disease conditions between urban and rural older adults.MethodsThe data are from the fourth wave of the China Health and Retirement Longitudinal Study. The coarsened exact matching (CEM) method was used to reduce the biases for a comparative study. After the CEM method, this study included 5,927 participants aged 60 and above. Chronic disease condition was used as the indicator to measure the health of older adults. Specifically, Fairlie's decomposition analysis was carried out to discover the differences in chronic disease conditions between urban and rural older adults.ResultsThe study showed that the proportion of those suffering from chronic diseases was significantly higher among urban older adults (51.26%) than rural older adults (46.56%). In those suffering from chronic diseases, there were significant differences in gender, education level, minorities, religiosities, duration of sleep, drinking alcohol, social activity, insurance, and socioeconomic status between rural and urban older adults, while in those not suffering from chronic diseases, there were significant differences in age, education level, marital status, drinking alcohol, social activity, insurance, region, and socioeconomic status between rural and urban older adults. For rural older adults, those who were widowers [Odds ratios (OR): 1.267], who drink alcohol (OR: 1.421), and having government medical insurance (OR: 4.869) had higher odds of having chronic diseases. However, those who were in high school and above (OR: 0.802), reporting a duration of sleep of 4–8 h (OR: 0.745) or above 8 h (OR: 0.649), having social activity (OR: 0.778), and having the most affluent socioeconomic status (OR: 0.778) had lower odds of having chronic diseases. As for urban older adults, those who were aged 65–74 years (OR: 1.246) and had government medical insurance (OR: 2.362) had higher odds of having chronic diseases. Fairlie's decomposition analysis indicated that 23.57% of the differences in chronic diseases conditions could be traced to duration of sleep, drinking alcohol, social activity, and region.ConclusionThis study illustrated that the proportion of chronic diseases was higher among urban older adults than rural older adults. Considering duration of sleep, drinking alcohol, region, social activity, and region, the study demonstrated health differences between urban and rural older adults and provided evidence for policy-making to narrow the health gap between urban and rural areas.</p

Additional file 1 of Methylated lncRNAs suppress apoptosis of gastric cancer stem cells via the lncRNA–miRNA/protein axis

Additional file 1: Table S1. Potential miRNAs targeted by lncRNAs. Fig S1. Detection of the predicted m6A sites of lncRNAs PSMA3-AS1 A and MIR22HG B in GCSCs using single-base elongation- and ligation-based qPCR amplification analysis. Total RNAs were extracted form GCSCS and then subjected to single-base elongation- and ligation-based qPCR amplification analysis to evaluate the predicted m6A sites on PSMA3-AS1 (A) or MIR22HG (B). The A232 site with no m6A motif RRACH (R=G/A; H=A/C/U) was used as an input control

Image_2_Focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer.tif

In 2011, J. Hoffman, and B. Beutler won the Nobel Prize of medicine for the fact that they discovered the pattern recognition receptors (PRRs) and meanwhile described their effect on cell activation from the innate and adaptive immune systems. There are more and more evidences that have proved the obvious effect of PRRs on tumorigenesis progression. Nevertheless, the overall impact of PRR genes on prognosis, tumor microenvironmental characteristics and treatment response in patients with colon adenocarcinoma (COAD) remains unclear. In this research, we systematically assessed 20 PRR genes and comprehensively identified the prognostic value and enrichment degree of PRRs. The unsupervised clustering approach was employed for dividing COAD into 4 PRR subtypes, namely cluster A, cluster B, cluster C and cluster D, which were significantly different in terms of the clinical features, the immune infiltrations, and the functions. Among them, cluster B has better immune activities and functions. Cox and LASSO regression analysis was further applied to identify a prognostic five-PRR-based risk signature. Such signature can well predict patients’ overall survival (OS), together with a good robustness. Confounding parameters were controlled, with results indicating the ability of risk score to independently predict COAD patients’ OS. Besides, a nomogram with a strong reliability was created for enhancing the viability exhibited by the risk score in clinical practice. Also, patients who were classified based on the risk score owned distinguishable immune status and tumor mutation status, response to immunotherapy, as well as sensitivity to chemotherapy. A low risk score, featuring increased tumor stemness index (TSI), human leukocyte antigen (HLA), immune checkpoints, and immune activation, demonstrated a superior immunotherapeutic response. According to the study results, the prognostic PRR-based risk signature could serve as a robust biomarker for predicting the clinical outcomes as well as evaluating therapeutic response for COAD patients.</p

Amplified emission and lasing in a plasmonic nano-laser with many three-level molecules

Steady-state plasmonic lasing is studied theoretically for a system consisting of many dye molecules arranged regularly around a gold nano-sphere. A three-level model with realistic molecular dissipation is employed to analyze the performance as function of the pump field amplitude and number of molecules. Few molecules and moderate pumping produce a single narrow emission peak because the excited molecules transfer energy to a single dipole plasmon mode by amplified spontaneous emission. Under strong pumping, the single peak splits into broader and weaker emission peaks because two molecular excited levels interfere with each other through coherent coupling with the pump field and with the dipole plasmon field. A large number of molecules gives rise to a Poisson-like distribution of plasmon number states with a large mean number characteristic of lasing action. These characteristics of lasing, however, deteriorate under strong pumping because of the molecular interference effect

Image_3_Focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer.tif

In 2011, J. Hoffman, and B. Beutler won the Nobel Prize of medicine for the fact that they discovered the pattern recognition receptors (PRRs) and meanwhile described their effect on cell activation from the innate and adaptive immune systems. There are more and more evidences that have proved the obvious effect of PRRs on tumorigenesis progression. Nevertheless, the overall impact of PRR genes on prognosis, tumor microenvironmental characteristics and treatment response in patients with colon adenocarcinoma (COAD) remains unclear. In this research, we systematically assessed 20 PRR genes and comprehensively identified the prognostic value and enrichment degree of PRRs. The unsupervised clustering approach was employed for dividing COAD into 4 PRR subtypes, namely cluster A, cluster B, cluster C and cluster D, which were significantly different in terms of the clinical features, the immune infiltrations, and the functions. Among them, cluster B has better immune activities and functions. Cox and LASSO regression analysis was further applied to identify a prognostic five-PRR-based risk signature. Such signature can well predict patients’ overall survival (OS), together with a good robustness. Confounding parameters were controlled, with results indicating the ability of risk score to independently predict COAD patients’ OS. Besides, a nomogram with a strong reliability was created for enhancing the viability exhibited by the risk score in clinical practice. Also, patients who were classified based on the risk score owned distinguishable immune status and tumor mutation status, response to immunotherapy, as well as sensitivity to chemotherapy. A low risk score, featuring increased tumor stemness index (TSI), human leukocyte antigen (HLA), immune checkpoints, and immune activation, demonstrated a superior immunotherapeutic response. According to the study results, the prognostic PRR-based risk signature could serve as a robust biomarker for predicting the clinical outcomes as well as evaluating therapeutic response for COAD patients.</p

Image_1_Focus on pattern recognition receptors to identify prognosis and immune microenvironment in colon cancer.tif

In 2011, J. Hoffman, and B. Beutler won the Nobel Prize of medicine for the fact that they discovered the pattern recognition receptors (PRRs) and meanwhile described their effect on cell activation from the innate and adaptive immune systems. There are more and more evidences that have proved the obvious effect of PRRs on tumorigenesis progression. Nevertheless, the overall impact of PRR genes on prognosis, tumor microenvironmental characteristics and treatment response in patients with colon adenocarcinoma (COAD) remains unclear. In this research, we systematically assessed 20 PRR genes and comprehensively identified the prognostic value and enrichment degree of PRRs. The unsupervised clustering approach was employed for dividing COAD into 4 PRR subtypes, namely cluster A, cluster B, cluster C and cluster D, which were significantly different in terms of the clinical features, the immune infiltrations, and the functions. Among them, cluster B has better immune activities and functions. Cox and LASSO regression analysis was further applied to identify a prognostic five-PRR-based risk signature. Such signature can well predict patients’ overall survival (OS), together with a good robustness. Confounding parameters were controlled, with results indicating the ability of risk score to independently predict COAD patients’ OS. Besides, a nomogram with a strong reliability was created for enhancing the viability exhibited by the risk score in clinical practice. Also, patients who were classified based on the risk score owned distinguishable immune status and tumor mutation status, response to immunotherapy, as well as sensitivity to chemotherapy. A low risk score, featuring increased tumor stemness index (TSI), human leukocyte antigen (HLA), immune checkpoints, and immune activation, demonstrated a superior immunotherapeutic response. According to the study results, the prognostic PRR-based risk signature could serve as a robust biomarker for predicting the clinical outcomes as well as evaluating therapeutic response for COAD patients.</p

sj-docx-1-usj-10.1177_00420980211064136 – Supplemental material for Urban epidemic governance:An event system analysisof the outbreak and controlof COVID-19 in Wuhan, China

Supplemental material, sj-docx-1-usj-10.1177_00420980211064136 for Urban epidemic governance:An event system analysisof the outbreak and controlof COVID-19 in Wuhan, China by Jinliao He and Yuan Zhang in Urban Studies</p