Energy optimization methods for Virtual Machine Placement in Cloud Data Center

The Information Technology industry has been upheaved by the influx of cloud computing. The extension of Cloud computing has resulted in the creation of huge data centers globally containing numbers of computers that consume large amounts of energy resulting in high operating costs. To reduce energy consumption providers must optimize resource usage by performing dynamic consolidation of virtual machines (VMs) in an efficient way. The problems of VM consolidation are host overload detection, host under-load detection, VM selection and VM placement. Each of the aforestated sub-problems must operate in an optimized manner to maintain the energy usage and performance. The process of VM placement has been focused in this work, and energy efficient, optimal virtual machine placement (E2OVMP) algorithm has been proposed. This minimizes the expenses for hosting virtual machines in a cloud provider environment in two different plans such as i) reservation and ii) on-demand plans, under future demand and price uncertainty. It also reduces energy consumption. E2OVMP algorithm makes a decision based on the gilt-edged solution of stochastic integer programming to lease resources from cloud IaaS providers. The performance of E2OVMP is evaluated by using CloudSim with inputs of planet lab workload. It minimized the user’s budget, number of VM migration resulting efficient energy consumption. It ensures a high level of constancy to the Service Level Agreements (SLA).Keywords: Cloud resource management; virtualization; dynamic consolidation; stochastic integer programming (SIP)*Cite as: Esha Barlaskar, N. Ajith Singh, Y. Jayanta Singh, “Energy optimization methods for Virtual Machine Placementin Cloud Data Center†ADBU J.Engg.Tech., 1(2014) 0011401(7pp

Enhancing photoacoustic visualization of medical devices with elastomeric nanocomposite coatings

Ultrasound (US) imaging is widely used for guiding minimally invasive procedures. However, with this modality, there can be poor visibility of interventional medical devices such as catheters and needles due to back-reflections outside the imaging aperture and low echogenicity. Photoacoustic (PA) imaging has shown promise with visualising bare metallic needles. In this study, we demonstrate the feasibility of a light emitting diode (LED)-based PA and US dual-modality imaging system for imaging metallic needles and polymeric medical catheters in biological tissue. Four medical devices were imaged with the system: two 20-gauge spinal needles with and without a multi-walled carbon nanotube / polydimethylsiloxane (MWCNT/PDMS) composite coating, and two 18-gauge epidural catheters with and without the MWCNT/PDMS composite coating. These devices were sequentially inserted into layers of chicken breast tissue within the US imaging plane. Interleaved PA and US imaging was performed during insertions of the needle and catheter. With US imaging, the uncoated needle had very poor visibility at an insertion angle of 45°. With PA imaging, the uncoated needle was not visible, but its coated counterpart was clearly visualised up to depths of 35 mm. Likewise, both catheters were not visible with US imaging. The uncoated catheter was not visible on PA images, but its coated counterpart was clearly visualised up to depths of 35 mm. We conclude that the highly absorbing CNT/PDMS composite coating conferred excellent visibility for medical devices with the LED-based PA imaging system and that it is promising for translation in minimally invasive procedures

Imaging of human peripheral blood vessels during cuff occlusion with a compact LED-based photoacoustic and ultrasound system

Non-invasive imaging plays an important role in diagnosing and monitoring peripheral artery disease (PAD). Doppler ultrasound imaging can be used for measuring blood flow in this context. However, this technique frequently provides low contrast for flow in small vessels. Photoacoustic imaging can allow for the visualization of blood in small vessels, with direct contrast from optical absorption of hemoglobin. In this work, we investigate the potential applications of a compact LED-based photoacoustic (850 nm) and ultrasound imaging system for visualizing human peripheral blood vessels during cuff occlusion. Each measurement comprised three stages. First, a baseline measurement of a digital artery of a human finger from a volunteer without a diagnosis of PAD was performed for several seconds. Second, arterial blood flow was stopped using an occlusion cuff, with a rapid increase of pressure up to 220 mm Hg. Third, the occlusion cuff was released rapidly. Raw photoacoustic and ultrasound image data (frame rate: 70 Hz) were recorded for the entire duration of the measurement (20 s). The average photoacoustic image amplitude over an image region that enclosed the digital artery was calculated. With this value, pulsations of image amplitudes from the arteries was clearly visualized. The average photoacoustic image amplitude decreased during the increase in cuff pressure and it was followed by a rapid recovery during cuff release. With real-time non-invasive measurements of peripheral blood vessel dynamics in vivo, the compact LED-based system could be valuable for point-of-care imaging to guide treatment of PAD

Photoacoustic imaging of the human placental vasculature

Minimally invasive fetal interventions require accurate imaging from inside the uterine cavity. Twin‐to‐twin transfusion syndrome (TTTS), a condition considered in this study, occurs from abnormal vascular anastomoses in the placenta that allow blood to flow unevenly between the fetuses. Currently, TTTS is treated fetoscopically by identifying the anastomosing vessels, and then performing laser photocoagulation. However, white light fetoscopy provides limited visibility of placental vasculature, which can lead to missed anastomoses or incomplete photocoagulation. Photoacoustic (PA) imaging is an alternative imaging method that provides contrast for hemoglobin, and in this study, two PA systems were used to visualize chorionic (fetal) superficial and subsurface vasculature in human placentas. The first system comprised an optical parametric oscillator for PA excitation and a 2D Fabry‐Pérot cavity ultrasound sensor; the second, light emitting diode arrays and a 1D clinical linear‐array ultrasound imaging probe. Volumetric photoacoustic images were acquired from ex vivo normal term and TTTS‐treated placentas. It was shown that superficial and subsurface branching blood vessels could be visualized to depths of approximately 7 mm, and that ablated tissue yielded negative image contrast. This study demonstrated the strong potential of PA imaging to guide minimally invasive fetal therapies

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Search for post-merger gravitational waves from the remnant of the binary neutron star merger GW170817

In Advanced LIGO, detection and astrophysical source parameter estimation of the binary black hole merger GW150914 requires a calibrated estimate of the gravitational-wave strain sensed by the detectors. Producing an estimate from each detector's differential arm length control loop readout signals requires applying time domain filters, which are designed from a frequency domain model of the detector's gravitational-wave response. The gravitational-wave response model is determined by the detector's opto-mechanical response and the properties of its feedback control system. The measurements used to validate the model and characterize its uncertainty are derived primarily from a dedicated photon radiation pressure actuator, with cross-checks provided by optical and radio frequency references. We describe how the gravitational-wave readout signal is calibrated into equivalent gravitational-wave-induced strain and how the statistical uncertainties and systematic errors are assessed. Detector data collected over 38 calendar days, from September 12 to October 20, 2015, contain the event GW150914 and approximately 16 of coincident data used to estimate the event false alarm probability. The calibration uncertainty is less than 10% in magnitude and 10 degrees in phase across the relevant frequency band 20 Hz to 1 kHz