Property Type, Size, and REIT Value

This study documents the wide deviation of securitized real estate assets in equity REITs from the value of the underlying commercial properties. A procedure for estimating the net asset value of REITs is developed and the estimates are used to investigate the sources of premiums/discounts from net asset value in a large sample of equity REITs. To avoid measurement error bias, two-way analysis of variance is used to test for differences among size and property-type categories. The results indicate that retail REITs trade at significant premiums relative to the average REIT while warehouse/industrial REITs trade at discounts and small REITs trade at significant discounts while large REITs trade at premiums. The discounts and premiums from net asset value do not translate into higher cash flow yields.

MrLazy: Lazy runtime label propagation for MapReduce

Organisations are starting to publish datasets containing potentially sensitive information in the Cloud; hence it is important there is a clear audit trail to show that involved parties are respecting data sharing laws and policies. Information Flow Control (IFC) has been proposed as a solution. However, fine-grained IFC has various deployment challenges and runtime overhead issues that have limited wide adoptation so far. In this paper we present MrLazy, a system that practically addresses some of these issues for MapReduce. Within one trust domain, we relax the need of continuously checking policies. We instead rely on lineage (information about the origin of a piece of data) as a mechanism to retrospectively apply policies on-demand. We show that MrLazy imposes manageable temporal and spatial overheads while enabling fine-grained data regulation

Shadow kernels: A general mechanism for kernel specialization in existing operating systems

Existing operating systems share a common kernel text section amongst all processes. It is not possible to perform kernel specialization or tuning such that different applications execute text optimized for their kernel use despite the benefits of kernel specialization for performance guided optimization, exokernels, kernel fastpaths, and cheaper hardware access. Current specialization primitives involve system wide changes to kernel text, which can have adverse effects on other processes sharing the kernel due to the global side-effects. We present shadow kernels: a primitive that allows multiple kernel text sections to coexist in a contemporary operating system. By remapping kernel virtual memory on a context-switch, or for individual system calls, we specialize the kernel on a fine-grained basis. Our implementation of shadow kernels uses the Xen hypervisor so can be applied to any operating system that runs on Xen.This work was principally supported by internal funds from the Computer Laboratory at the University of Cambridge; and also by the Engineering and Physical Sciences Research Council [grant number EP/K503009/1].This is the final version of the article. It first appeared from ACM via http://dx.doi.org/10.1145/2797022.279702

Number of Hours of Sleep with Changes in Blood Pressure Amongst Medical Students in Western Maharashtra

Introduction: Sleep has become one of the most ignored factors today. More sleep or less sleep does not matter it is just compensated the next day. Importance of regular and timely sleep amongst the students and their correlation with blood pressure is necessary to be found out so that the students can be made aware of and can be provided treatment to prevent further complications.  Method: Demographic profile was noted it includes name, age, gender, professional year of MBBS and residence. History of sleeping was noted and other factors which influences sleeping pattern (i.e, alcohol, smoking, an association of dreams with sleep, midnight awakenings with sleep, caffeine intake before bed and average stress levels) through a well-structured questionnaire. Blood pressures of all eligible students were recorded 3 times in a week at the same time by the principal investigator with the same instrument according to the JNC 7 classification for hypertension. Results: Amongst all the medical students, 6% had systolic hypertension and 22.50% had diastolic hypertension. Comparing blood pressures according to sleeping patterns, amongst cases (less than 5 hours of sleep) 20.8% had systolic hypertension and 56.30% had diastolic hypertension. Whereas in controls (more than 5 hours of sleep) 1.40% had systolic hypertension and 11.90% had diastolic hypertension. Factors such as alcohol consumption, smoking, caffeine consumption before sleep, dreams, midnight awakenings and stress were found to be associated with sleeping patterns and the results were found to be extremely significant (p<0.0001) statistically. Conclusion: Sleep duration of less than 5 hours was noted in 24% of the total population. The subjects with lesser number of sleeping hours had increased levels of blood pressure and a higher prevalence of hypertension. The average systolic blood pressure in subjects with less than 5 hours of sleep (cases) showed 48.50% pre-hypertensives and 20.80% hypertensives whereas in case of average diastolic blood pressure 18.50% were prehypertensive and 56.30% were hypertensive. Keywords: Blood pressures; Sleeping hours; Medical Students

Number of Hours of Sleep with Changes in Blood Pressure Amongst Medical Students in Western Maharashtra

Introduction: Sleep has become one of the most ignored factors today. More sleep or less sleep does not matter it is just compensated the next day. Importance of regular and timely sleep amongst the students and their correlation with blood pressure is necessary to be found out so that the students can be made aware of and can be provided treatment to prevent further complications.  Method: Demographic profile was noted it includes name, age, gender, professional year of MBBS and residence. History of sleeping was noted and other factors which influences sleeping pattern (i.e, alcohol, smoking, an association of dreams with sleep, midnight awakenings with sleep, caffeine intake before bed and average stress levels) through a well-structured questionnaire. Blood pressures of all eligible students were recorded 3 times in a week at the same time by the principal investigator with the same instrument according to the JNC 7 classification for hypertension. Results: Amongst all the medical students, 6% had systolic hypertension and 22.50% had diastolic hypertension. Comparing blood pressures according to sleeping patterns, amongst cases (less than 5 hours of sleep) 20.8% had systolic hypertension and 56.30% had diastolic hypertension. Whereas in controls (more than 5 hours of sleep) 1.40% had systolic hypertension and 11.90% had diastolic hypertension. Factors such as alcohol consumption, smoking, caffeine consumption before sleep, dreams, midnight awakenings and stress were found to be associated with sleeping patterns and the results were found to be extremely significant (p<0.0001) statistically. Conclusion: Sleep duration of less than 5 hours was noted in 24% of the total population. The subjects with lesser number of sleeping hours had increased levels of blood pressure and a higher prevalence of hypertension. The average systolic blood pressure in subjects with less than 5 hours of sleep (cases) showed 48.50% pre-hypertensives and 20.80% hypertensives whereas in case of average diastolic blood pressure 18.50% were prehypertensive and 56.30% were hypertensive. Keywords: Blood pressures; Sleeping hours; Medical Students

Structural analysis of whole-system provenance graphs

System based provenance generates traces captured from various systems, a representation method for inferring these traces is a graph. These graphs are not well understood, and current work focuses on their extraction and processing, without a thorough characterization being in place. This paper studies the topology of such graphs. We an- alyze multiple Whole-system-Provenance graphs and present that they have hubs-and-authorities model of graphs as well as a power law distri- bution. Our observations allow for a novel understanding of the structure of Whole-system-Provenance graphs.DARP

Soroban: Attributing latency in virtualized environments

Applications running in the cloud have highly-variable response times due to the lack of perfect performance isolation from other services served by common infrastructure. In particular, response latency when executing on a loaded hypervisor or in a container is substantially higher than uncontested bare-metal performance. Whilst efforts to increase performance isolation continue, we present Soroban, a framework for attributing latency to either the cloud provider or their customer. Soroban allows cloud providers to instrument commonly used programs, such as a web server to determine, for each request, how much of the latency is due to the cloud provider, or the consumer. We apply Soroban to a HTTP server and show that it identifies when the cause of latency is due to a provider-induced activity, such as underprovisioning a host, or due to the software run by the customer.This is the author accepted manuscript. The final version is available from USENIX. via https://www.usenix.org/conference/hotcloud15/workshop-program/presentation/sne

Turning down the lamp: Software specialisation for the cloud

© USENIX Workshop on Hot Topics in Cloud Computing, HotCloud 2010.All right reserved. The wide availability of cloud computing offers an unprecedented opportunity to rethink how we construct applications. The cloud is currently mostly used to package up existing software stacks and operating systems (e.g. LAMP) for scaling out websites. We instead view the cloud as a stable hardware platform, and present a programming framework which permits applications to be constructed to run directly on top of it without intervening software layers. Our prototype (dubbed Mirage) is unashamedly academic; it extends the Objective Caml language with storage extensions and a custom run-time to emit binaries that execute as a guest operating system under Xen. Mirage applications exhibit significant performance speedups for I/O and memory handling versus the same code running under Linux/Xen. Our results can be generalised to offer insight into improving more commonly used languages such as PHP, Python and Ruby, and we discuss lessons learnt and future directions

A primer on provenance

Better understanding data requires tracking its history and context.</jats:p