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Data centers aim at provisioning on-demand processing, storage and networking capabilities in a reliable and scalable way. In this context, proper maintenance of IT equipment within DC premises is crucial as it ensures prolonged lifetime of servers and uninterrupted availability of resources. DC management teams’ sustainable operation effort comprises various approaches to directly and indirectly reduce DC energy consumption. Thermal management aims to reduce excess energy consumption by air cooling and compute systems. This paper focuses on the analysis of the exact temperatures in a real DC cluster rather than considering device setpoints or guidelines. An extensive statistical analysis of available thermal data collected by server-level sensors, global and local thermal metrics evaluation is conducted. It enables isolating possible risks engendered by potential negative covert cooling-related factors. The ultimate outcome of this research is to bring about improvement of DC thermal management for sustainable operations.

Rationale & Objective: Approximately 11% of people with kidney failure worldwide are treated with peritoneal dialysis (PD). This study examined PD use and practice patterns across the globe. Study Design: A cross-sectional survey. Setting & Participants: Stakeholders including clinicians, policy makers, and patient representatives in 182 countries convened by the International Society of Nephrology between July and September 2018. Outcome(s): PD use, availability, accessibility, affordability, delivery, and reporting of quality outcome measures. Analytical Approach: Descriptive statistics. Result(s): Responses were received from 88% (n = 160) of countries and there were 313 participants (257 nephrologists [82%], 22 non-nephrologist physicians [7%], 6 other health professionals [2%], 17 administrators/policy makers/civil servants [5%], and 11 others [4%]). 85% (n = 156) of countries responded to questions about PD. Median PD use was 38.1 per million population. PD was not available in 30 of the 156 (19%) countries responding to PD-related questions, particularly in countries in Africa (20/41) and low-income countries (15/22). In 69% of countries, PD was the initial dialysis modality for <=10% of patients with newly diagnosed kidney failure. Patients receiving PD were expected to pay 1% to 25% of treatment costs, and higher (>75%) copayments (out-of-pocket expenses incurred by patients) were more common in South Asia and low-income countries. Average exchange volumes were adequate (defined as 3-4 exchanges per day or the equivalent for automated PD) in 72% of countries. PD quality outcome monitoring and reporting were variable. Most countries did not measure patient-reported PD outcomes. Limitation(s): Low responses from policy makers; limited ability to provide more in-depth explanations underpinning outcomes from each country due to lack of granular data; lack of objective data. Conclusion(s): Large inter- and intraregional disparities exist in PD availability, acce

The Global Kidney Health Atlas (GKHA) is a multinational, cross-sectional survey designed to assess the current capacity for kidney care across all world regions. The 2017 GKHA involved 125 countries and identified significant gaps in oversight, funding and infrastructure to support care for patients with kidney disease, especially in lower-middle-income countries. Here, we report results from the survey for the second iteration of the GKHA conducted in 2018, which included specific questions about health financing and oversight of end-stage kidney disease (ESKD) care worldwide. A cross-sectional global survey. Key stakeholders from 182 countries were invited to participate. Of those, stakeholders from 160 countries participated and were included. Primary outcomes included cost of kidney replacement therapy (KRT), funding for dialysis and transplantation, funding for conservative kidney management, extent of universal health coverage, out-of-pocket costs for KRT, within-country variability in ESKD care delivery and oversight systems for ESKD care. Outcomes were determined from a combination of desk research and input from key stakeholders in participating countries. 160 countries (covering 98% of the world's population) responded to the survey. Economic factors were identified as the top barrier to optimal ESKD care in 99 countries (64%). Full public funding for KRT was more common than for conservative kidney management (43% vs 28%). Among countries that provided at least some public coverage for KRT, 75% covered all citizens. Within-country variation in ESKD care delivery was reported in 40% of countries. Oversight of ESKD care was present in all high-income countries but was absent in 13% of low-income, 3% of lower-middle-income, and 10% of upper-middle-income countries. Significant gaps and variability exist in the public funding and oversight of ESKD care in many countries, particularly for those in low-income and lower-middle-income countries.Copyright © Autho

Rationale & Objective: Hemodialysis (HD) is the most common form of kidney replacement therapy. This study aimed to examine the use, availability, accessibility, affordability, and quality of HD care worldwide. Study Design: A cross-sectional survey. Setting & Participants: Stakeholders (clinicians, policy makers, and consumer representatives) in 182 countries were convened by the International Society of Nephrology from July to September 2018. Outcome(s): Use, availability, accessibility, affordability, and quality of HD care. Analytical Approach: Descriptive statistics. Result(s): Overall, representatives from 160 (88%) countries participated. Median country-specific use of maintenance HD was 298.4 (IQR, 80.5-599.4) per million population (pmp). Global median HD use among incident patients with kidney failure was 98.0 (IQR, 81.5-140.8) pmp and median number of HD centers was 4.5 (IQR, 1.2-9.9) pmp. Adequate HD services (3-4 hours 3 times weekly) were generally available in 27% of low-income countries. Home HD was generally available in 36% of high-income countries. 32% of countries performed monitoring of patient-reported outcomes; 61%, monitoring of small-solute clearance; 60%, monitoring of bone mineral markers; 51%, monitoring of technique survival; and 60%, monitoring of patient survival. At initiation of maintenance dialysis, only 5% of countries used an arteriovenous access in almost all patients. Vascular access education was suboptimal, funding for vascular access procedures was not uniform, and copayments were greater in countries with lower levels of income. Patients in 23% of the low-income countries had to pay >75% of HD costs compared with patients in only 4% of high-income countries. Limitation(s): A cross-sectional survey with possibility of response bias, social desirability bias, and limited data collection preventing in-depth analysis. Conclusion(s): In summary, findings reveal substantial variations in global HD use, availability, accessibility

BACKGROUND: Health information systems (HIS) are fundamental tools for the surveillance of health services, estimation of disease burden and prioritization of health resources. Several gaps in the availability of HIS for kidney disease were highlighted by the first iteration of the Global Kidney Health Atlas. METHOD(S): As part of its second iteration, the International Society of Nephrology conducted a cross-sectional global survey between July and October 2018 to explore the coverage and scope of HIS for kidney disease, with a focus on kidney replacement therapy (KRT). RESULT(S): Out of a total of 182 invited countries, 154 countries responded to questions on HIS (85% response rate). KRT registries were available in almost all high-income countries, but few low-income countries, while registries for non-dialysis chronic kidney disease (CKD) or acute kidney injury (AKI) were rare. Registries in high-income countries tended to be national, in contrast to registries in low-income countries, which often operated at local or regional levels. Although cause of end-stage kidney disease, modality of KRT and source of kidney transplant donors were frequently reported, few countries collected data on patient-reported outcome measures and only half of low-income countries recorded process-based measures. Almost no countries had programs to detect AKI and practices to identify CKD-targeted individuals with diabetes, hypertension and cardiovascular disease, rather than members of high-risk ethnic groups. CONCLUSION(S): These findings confirm significant heterogeneity in the global availability of HIS for kidney disease and highlight important gaps in their coverage and scope, especially in low-income countries and across the domains of AKI, non-dialysis CKD, patient-reported outcomes, process-based measures and quality indicators for KRT service delivery.Copyright © The Author(s) 2020. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

OBJECTIVES: The Global Kidney Health Atlas (GKHA) is a multinational, cross-sectional survey designed to assess the current capacity for kidney care across all world regions. The 2017 GKHA involved 125 countries and identified significant gaps in oversight, funding and infrastructure to support care for patients with kidney disease, especially in lower-middle-income countries. Here, we report results from the survey for the second iteration of the GKHA conducted in 2018, which included specific questions about health financing and oversight of end-stage kidney disease (ESKD) care worldwide. SETTING: A cross-sectional global survey. PARTICIPANTS: Key stakeholders from 182 countries were invited to participate. Of those, stakeholders from 160 countries participated and were included. PRIMARY OUTCOMES: Primary outcomes included cost of kidney replacement therapy (KRT), funding for dialysis and transplantation, funding for conservative kidney management, extent of universal health coverage, out-of-pocket costs for KRT, within-country variability in ESKD care delivery and oversight systems for ESKD care. Outcomes were determined from a combination of desk research and input from key stakeholders in participating countries. RESULTS: 160 countries (covering 98% of the world's population) responded to the survey. Economic factors were identified as the top barrier to optimal ESKD care in 99 countries (64%). Full public funding for KRT was more common than for conservative kidney management (43% vs 28%). Among countries that provided at least some public coverage for KRT, 75% covered all citizens. Within-country variation in ESKD care delivery was reported in 40% of countries. Oversight of ESKD care was present in all high-income countries but was absent in 13% of low-income, 3% of lower-middle-income, and 10% of upper-middle-income countries. CONCLUSION: Significant gaps and variability exist in the public funding and oversight of ESKD care in many countries, particularly f

The residential sector accounts for 30% of the total green house gas emissions in Europe, which can be reduced either by switching to low-carbon technologies or reducing the amount of fossil fuel energy consumed. In this work, a new greenhouse gas emission (GHGE) reduction system at the house (nanogrid) level is investigated. The originality of the proposed system and underlying algorithm lies in the fact that it acts in a proactive manner, by continuously controlling and optimizing energy flows between on-site local power production systems (photovoltaics - PV - array in our case), loads, and storage units (combining battery and thermal storage reservoirs). This system/algorithm is evaluated based on real-life input datasets from the United Kingdom (UK) and France, and compared with traditional house energy infrastructures, namely (i) a house not fitted with battery, and (ii) a house fitted with battery but without additional “smart” software layer. Results show that it performs better in terms of CO2 (capacity of the algorithm to reduce the amount of non carbon-free energy consumed from the grid), Power to Grid (capacity to maximize the use of local green energy), and financial cost (capacity to reduce the overall electricity bill), respectively improving performance by up to 8%, 10% and 37%.

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Internet of Things (IoT) coupled with big data analytics is emerging as the core of smart and sustainable systems which bolsters economic, environmental and social sustainability. Cloud-based data centers provide high performance computing power to analyze voluminous IoT data to provide invaluable insights to support decision making. However, multifarious servers in data centers appear to be the black hole of superfluous energy consumption that contributes to 23% of the global carbon dioxide (CO2) emissions in ICT (Information and Communication Technology) industry. IoT-related energy research focuses on low-power sensors and enhanced machine-to-machine communication performance. To date, cloud-based data centers still face energy-related challenges which are detrimental to the environment. Virtual machine (VM) consolidation is a well-known approach to affect energy-efficient cloud infrastructures. Although several research works demonstrate positive results for VM consolidation in simulated environments, there is a gap for investigations on real, physical cloud infrastructure for big data workloads. This research work addresses the gap of conducting real physical cloud infrastructure-based experiments. The primary goal of setting up a real physical cloud infrastructure is for the evaluation of dynamic VM consolidation approaches which include integrated algorithms from existing relevant research. An open source VM consolidation framework, Openstack NEAT is adopted and experiments are conducted on a Multi-node Openstack Cloud with Apache Spark as the big data platform. Open sourced Openstack has been deployed because it enables rapid innovation, and boosts scalability as well as resource utilization. Additionally, this research work investigates the performance based on service level agreement (SLA) metrics and energy usage of compute hosts. Relevant results concerning the best performing combination of algor

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). The energy efficiency of Data Center (DC) operations heavily relies on a DC ambient temperature as well as its IT and cooling systems performance. A reliable and efficient cooling system is necessary to produce a persistent flow of cold air to cool servers that are subjected to constantly increasing computational load due to the advent of smart cloud-based applications. Consequently, the increased demand for computing power will inadvertently increase server waste heat creation in data centers. To improve a DC thermal profile which could undeniably influence energy efficiency and reliability of IT equipment, it is imperative to explore the thermal characteristics analysis of an IT room. This work encompasses the employment of an unsupervised machine learning technique for uncovering weaknesses of a DC cooling system based on real DC monitoring thermal data. The findings of the analysis result in the identification of areas for thermal management and cooling improvement that further feeds into DC recommendations. With the aim to identify overheated zones in a DC IT room and corresponding servers, we applied analyzed thermal characteristics of the IT room. Experimental dataset includes measurements of ambient air temperature in the hot aisle of the IT room in ENEA Portici research center hosting the CRESCO6 computing cluster. We use machine learning clustering techniques to identify overheated locations and categorize computing nodes based on surrounding air temperature ranges abstracted from the data. This work employs the principles and approaches replicable for the analysis of thermal characteristics of any DC, thereby fostering transferability. This paper demonstrates how best practices and guidelines could be applied for thermal