Analysis of power consumption in heterogeneous virtual machine environments

Reduction of energy consumption in Cloud computing datacenters today is a hot a research topic, as these consume large amounts of energy. Furthermore, most of the energy is used inefficiently because of the improper usage of computational resources such as CPU, storage and network. A good balance between the computing resources and performed workload is mandatory. In the context of data-intensive applications, a significant portion of energy is consumed just to keep alive virtual machines or to move data around without performing useful computation. Moreover, heterogeneity of resources increases the difficulty degree, when trying to achieve energy efficiency. Power consumption optimization requires identification of those inefficiencies in the underlying system and applications. Based on the relation between server load and energy consumption, we study the efficiency of data-intensive applications, and the penalties, in terms of power consumption, that are introduced by different degrees of heterogeneity of the virtual machines characteristics in a cluster

Analysis of power consumption in heterogeneous virtual machine environments

Reduction of energy consumption in Cloud computing datacenters today is a hot a research topic, as these consume large amounts of energy. Furthermore, most of the energy is used inefficiently because of the improper usage of computational resources such as CPU, storage and network. A good balance between the computing resources and performed workload is mandatory. In the context of data-intensive applications, a significant portion of energy is consumed just to keep alive virtual machines or to move data around without performing useful computation. Moreover, heterogeneity of resources increases the difficulty degree, when trying to achieve energy efficiency. Power consumption optimization requires identification of those inefficiencies in the underlying system and applications. Based on the relation between server load and energy consumption, we study the efficiency of data-intensive applications, and the penalties, in terms of power consumption, that are introduced by different degrees of heterogeneity of the virtual machines characteristics in a cluster

Evaluation of carbohydrate and lipid metabolism dynamics in chronic HCV diabetic patients treated with direct antiviral agents

Although Hepatitis C virus (HCV) infection has become a curable disease, the aftermath of the infection remains an important aspect to be evaluated. HCV infection is well known for its extrahepatic manifestations, mostly the tight relationship between HCV, type 2 diabetes mellitus (T2DM) and dyslipidemia. Not only HCV increases the risk of T2DM, but it also affects its control in diabetic patients, increasing the risk of diabetes related complications. Furthermore, HCV hijacks the lipid metabolism resulting in abnormalities in circulating lipids which can lead to multiple complications, such as increased atherosclerotic risk and hepatic steatosis. Objectives. The aim of this study was to evaluate the dynamics of the parameters of carbohydrate and lipid metabolism in HCV-infected diabetic patients compared to non-diabetic patients after viral eradication. Material and methods. This is a prospective study conducted on 100 patients with chronic HVC infection who obtained viral clearance after interferon-free treatment. 58 patients had type 2 diabetes mellitus and 42 were nondiabetic. We evaluated serum total cholesterol, triglycerides, blood glucose and glycosylated hemoglobin in both groups at treatment initiation and 1 year after. Continuous variables were expressed as mean values ± standard deviation or median, categorical variables were represented as relative or absolute frequencies. Characteristics were compared using the Mann-Whitney method or the two-sample Student's T-test method for continuous variables, Chi-square and Fischer's test for categorical variables. A p value < 0.05 was considered statistically significant. Outcomes. The study analyzed and compared lipid and glycemic profiles of diabetic and non-diabetic HVC patients before and after viral cure. Conclusions. 1 year after treatment initiation the changes in lipid metabolism seem to persist, carbohydrate metabolism seems to remain unchanged, with no differences between diabetic and non-diabetic patients

Catalin Negru's Quick Files

The Quick Files feature was discontinued and it’s files were migrated into this Project on March 11, 2022. The file URL’s will still resolve properly, and the Quick Files logs are available in the Project’s Recent Activity

Service level agreement characteristics of monitoring wireless sensor networks for water resource management (SLAs4Water)

One of the most important characteristics of a Service Level Agreement (SLA) when discussing about Monitoring Wireless Sensor Networks (MWSNs) is its effectiveness in assuring business success, a high provider profit, an increased level of client satisfaction and trust. In order to ensure that these goals will be achieved the provider of the MWSN must define some parameters that characterize the Service Level Agreement that occurs between MWSN provider and the MWSN customer. This paper addresses a solution behind an efficient and effective Service Level Agreement (SLA) design and implementation related to a Monitoring Wireless Sensor Network (MSN) and applies the SLA in the case of water resources management. The characteristics of the SLA in place between the MWSN provider and the MWSN customer must be defined by taking into consideration various parameters that are particular to the MWSN such as routing algorithms, recovery from failure, monitoring and reporting aspects. An appropriate definition of a SLA contract helps identify the responsibilities of both the provider and customer of the Monitoring Wireless Sensor Network (MSN) and makes the interaction between the provider and customer easier

The Unmet Diagnostic and Treatment Needs in Large Cell Neuroendocrine Carcinoma of the Lung

Large cell neuroendocrine carcinoma of the lung (LCNEC) is currently classified as a rare lung cancer subtype, but given the high incidence of lung cancer, the overall number of cases is considerable. The pathologic diagnosis of LCNEC is mainly based on the microscopic appearance of the tumor cells, the mitotic rate, the amount of intra-tumoral necrosis, and the presence of positive neuroendocrine markers identified by immunohistochemistry. Recently, a subdivision into two main categories was proposed based on mutation signatures involving the RB1, TP53, KRAS, and STK11/LKB1 genes, into SCLC-like (small cell lung cancer-like) and NSCLC-like (non-small cell lung cancer-like) LCNEC. In terms of treatment, surgery is still the best option for resectable, stage I–IIIA cases. Chemotherapy and radiotherapy have conflicting evidence. Etoposide/platinum remains the standard chemotherapy regimen. However, based on the newly proposed LCNEC subtypes, some retrospective series report better outcomes using a pathology-driven chemotherapy approach. Encouraging outcomes have also been reported for immunotherapy and targeted therapy, but the real impact of these strategies is still being determined in the absence of adequate prospective clinical trials. The current paper scrutinized the epidemiology, reviewed the reliability of pathologic diagnosis, discussed the need for molecular subtyping, and reviewed the heterogeneity of treatment algorithms in LCNEC