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In the Ethernet lossless Data Center Networks (DCNs) deployed with Priority-based Flow Control (PFC), the head-of-line blocking problem is still difficult to prevent due to PFC triggering under burst traffic scenarios even with the existing congestion control solutions. To address the head-of-line blocking problem of PFC, we propose a new congestion control mechanism. The key point of Congestion Control Using In-Network Telemetry for Lossless Datacenters (ICC) is to use In-Network Telemetry (INT) technology to obtain comprehensive congestion information, which is then fed back to the sender to adjust the sending rate timely and accurately. It is possible to control congestion in time, converge to the target rate quickly, and maintain a near-zero queue length at the switch when using ICC. We conducted Network Simulator-3 (NS-3) simulation experiments to test the ICC's performance. When compared to Congestion Control for Large-Scale RDMA Deployments (DCQCN), TIMELY: RTT-based Congestion Control for the Datacenter (TIMELY), and Re-architecting Congestion Management in Lossless Ethernet (PCN), ICC effectively reduces PFC pause messages and Flow Completion Time (FCT) by 47%, 56%, 34%, and 15.3×, 14.8×, and 11.2×, respectively.

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Purpose This paper aimed at providing evidence for developing countermeasures to improve patients’ quality of life by using the scale Quality of Life Instruments for Chronic Diseases-Schizophrenia (V2.0)(QLICD-SC)), which is modular and sensitivity. Methods 163 people who met the diagnostic criteria for schizophrenia of the International Classification of Diseases(10th Revision) and were hospitalized at the Affiliated Hospital of Guangdong Medical University from May 2014 to December, 2015 were selected. Patients' clinical objective indexes, including blood routine, urine routine, blood biochemical examination, blood gas analysis etc. were collected by reviewing the medical records. Patients were assessed by the QLICD-SC (V2.0), a quality of life measurement scale for Schizophrenia. Simple correlation analysis was used to explore the correlation between the QLICD-SC (V2.0) scores and various clinical objective indicators, and multiple linear regression was used to further screen for correlates. Results There were 163 participants, ranging in age from 16 to 69, with a 30.67 ± 11.44 average age. The majority of them were men(57.1%), had a high school diploma(77.9%), and were married (65.6%). According to multiple linear regression, the variables included in the model are education, sex, eosinophilic granulocyte, hematocrit, percentage of monocytes, phosphorus (R2 = 0.065 ~ 0.222, P < 0.05). Conclusion Some clinical indicators such as hematocrit and socio-demographic factors may reflect alterations in the quality of life of individuals with schizophrenia.

Background: Schizophrenia is a long course mental disease which poses heavy burdens to patients and quality of life can reflect treatment effect. But a small number of specificity scales have been developed. By using the scale Quality of Life Instruments for Chronic Diseases-Schizophrenia (V2.0)(QLICD-SC))(V2.0) which is modular and sensitivity integrating Chinese culture, this paper aims at providing evidence for developing countermeasures to improve patients’ quality of life. Methods: 163 people who met the diagnostic criteria for schizophrenia of the International Classification of Diseases(10th Revision)(ICD-10) and were hospitalized at the Affiliated Hospital of Guangdong Medical University from May 2014 to December, 2015 were selected. Paper-based questionnaires were administered to the patients to collect their basic information. Patients' clinical objective indexes, including blood routine, urine routine, blood biochemical examination, blood gas analysis etc. were collected by reviewing the medical records. Statistical description was applied to analyse the distribution of basic characteristics of depressed patients. Simple correlation analysis was used to explore the correlations between domains scores of the QLICD-SC(V2.0) and clinical objective indexes and multiple linear regression was used to further screen for correlates.Results: There were 163 participants, ranging in age from 16 to 69, with a 30.67±11.44 average age. The majority of them were men(57.1%), had a high school diploma(77.9%), and were married (65.6%). Physical function, psychological function, social function, specific module and total scale each had QOL ratings of 61.09, 48.02, 63.21, 33.01 and 49.09, respectively. According to multiple linear regression, the variables included in the model are education, sex, eosinophilic granulocyte, hematocrit, percentage of monocytes, phosphorus (R2=0.065~0.222, P<0.05).Conclusion: Some clinical indicators such as hematocrit and socio-demographic factors may reflect alterations in the quality of life of individuals with schizophrenia.