Distributed Rate Allocation in Inter-Session Network Coding

In this work, we propose a distributed rate allocation algorithm that minimizes the average decoding delay for multimedia clients in inter-session network coding systems. We consider a scenario where the users are organized in a mesh network and each user requests the content of one of the available sources. We propose a novel distributed algorithm where network users determine the coding operations and the packet rates to be requested from the parent nodes, such that the decoding delay is minimized for all clients. A rate allocation problem is solved by every user, which seeks the rates that minimize the average decoding delay for its children and for itself. Since this optimization problem is a priori non-convex, we introduce the concept of equivalent packet flows, which permits to estimate the expected number of packets that every user needs to collect for decoding. We then decompose our original rate allocation problem into a set of convex subproblems, which are eventually combined to obtain an effective approximate solution to the delay minimization problem. The results demonstrate that the proposed scheme eliminates the bottlenecks and reduces the decoding delay experienced by users with limited bandwidth resources. We validate the performance of our distributed rate allocation algorithm in different video streaming scenarios using the NS-3 network simulator. We show that our system is able to take benefit of inter-session network coding for simultaneous delivery of video sessions in networks with path diversity.

SLA-Driven Simulation of Multi-Tenant Scalable Cloud-Distributed Enterprise Information Systems

Cloud Computing is an enabler for delivering large-scale, distributed enterprise applications with strict requirements in terms of performance. It is often the case that such applications have complex scaling and Service Level Agreement (SLA) management requirements. In this paper we present a simulation approach for validating and comparing SLA-aware scaling policies using the CloudSim simulator, using data from an actual Distributed Enterprise Information System (dEIS). We extend CloudSim with concurrent and multi-tenant task simulation capabilities. We then show how different scaling policies can be used for simulating multiple dEIS applications. We present multiple experiments depicting the impact of VM scaling on both datacenter energy consumption and dEIS performance indicators.

A web-based non-intrusive ambient system to measure and classify activities of daily living.

BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.

Simulation of SLA-based VM-scaling algorithms for cloud-distributed applications

Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.

Service Level Agreements-Driven Management of Distributed Applications in Cloud Computing Environments

Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure and distributed applications might lead to violations of SLAs and inefficient use of hardware and software resources. This dissertation focusses on how SLAs can be used as an input to the cloud management system, increasing the efficiency of allocating resources, as well as that of infrastructure scaling. First, we present an extended SLA semantic model for modelling complex service-dependencies in distributed applications, and for enabling automated cloud infrastructure management operations. Second, we describe a multi-objective VM allocation algorithm for optimised resource allocation in infrastructure clouds. Third, we describe a method of discovering relations between the performance indicators of services belonging to distributed applications and then using these relations for building scaling rules that a CMS can use for automated management of VMs. Fourth, we introduce two novel VM-scaling algorithms, which optimally scale systems composed of VMs, based on given SLA performance constraints. All presented research works were implemented and tested using enterprise distributed applications.

Positive and negative mutant selection in the human histone hairpin-binding protein using the yeast three-hybrid system.

We have used the yeast three-hybrid system in a positive selection for mutants of the human histone hairpin-binding protein (HBP) capable of interacting with non-canonical hairpins and in a negative selection for loss-of-binding mutants. Interestingly, all mutations from the positive selection are located in the N- and C-terminal regions flanking a minimal RNA-binding domain (RBD) previously defined between amino acids 126 and 198. Further, in vitro binding studies demonstrate that the RBD, which shows no obvious similarity to other RNA-binding motifs, has a relaxed sequence specificity compared to full-length HBP, allowing it to bind to mutant hairpin RNAs not normally found in histone genes. These findings indicate that the sequences flanking the RBD are important for restricting binding to the highly conserved histone hairpin structure. Among the loss-of-binding mutations, about half are nonsense mutations distributed throughout the N-terminal part and the RBD whereas the other half are missense mutations restricted to the RBD. Whereas the nonsense mutations permit a more precise definition of the C-terminal border of the RBD, the missense mutations identify critical residues for RNA binding within the RBD.

Service level agreements-driven management of distributed applications in cloud computing environments

Advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing workload conditions, such as number of connected users, application performance might suffer, leading to violations of Service Level Agreements (SLA) and possible inefficient use of hardware resources. Combining dynamic application requirements with the increased use of virtualised computing resources creates a challenging resource Management context for application and cloud-infrastructure owners. In such complex environments, business entities use SLAs as a means for specifying quantitative and qualitative requirements of services. There are several challenges in running distributed enterprise applications in cloud environments, ranging from the instantiation of service VMs in the correct order using an adequate quantity of computing resources, to adapting the number of running services in response to varying external loads, such as number of users. The application owner is interested in finding the optimum amount of computing and network resources to use for ensuring that the performance requirements of all her/his applications are met. She/he is also interested in appropriately scaling the distributed services so that application performance guarantees are maintained even under dynamic workload conditions. Similarly, the infrastructure Providers are interested in optimally provisioning the virtual resources onto the available physical infrastructure so that her/his operational costs are minimized, while maximizing the performance of tenants’ applications. Motivated by the complexities associated with the management and scaling of distributed applications, while satisfying multiple objectives (related to both consumers and providers of cloud resources), this thesis proposes a cloud resource management platform able to dynamically provision and coordinate the various lifecycle actions on both virtual and physical cloud resources using semantically enriched SLAs. The system focuses on dynamic sizing (scaling) of virtual infrastructures composed of virtual machines (VM) bounded application services. We describe several algorithms for adapting the number of VMs allocated to the distributed application in response to changing workload conditions, based on SLA-defined performance guarantees. We also present a framework for dynamic composition of scaling rules for distributed service, which used benchmark-generated application Monitoring traces. We show how these scaling rules can be combined and included into semantic SLAs for controlling allocation of services. We also provide a detailed description of the multi-objective infrastructure resource allocation problem and various approaches to satisfying this problem. We present a resource management system based on a genetic algorithm, which performs allocation of virtual resources, while considering the optimization of multiple criteria. We prove that our approach significantly outperforms reactive VM-scaling algorithms as well as heuristic-based VM-allocation approaches.

Characterization of fetal antigen 1/delta-like 1 homologue expressing cells in the rat nigrostriatal system: effects of a unilateral 6-hydroxydopamine lesion.

Fetal antigen 1/delta-like 1 homologue (FA1/dlk1) belongs to the epidermal growth factor superfamily and is considered to be a non-canonical ligand for the Notch receptor. Interactions between Notch and its ligands are crucial for the development of various tissues. Moreover, FA1/dlk1 has been suggested as a potential supplementary marker of dopaminergic neurons. The present study aimed at investigating the distribution of FA1/dlk1-immunoreactive (-ir) cells in the early postnatal and adult midbrain as well as in the nigrostriatal system of 6-hydroxydopamine (6-OHDA)-lesioned hemiparkinsonian adult rats. FA1/dlk1-ir cells were predominantly distributed in the substantia nigra (SN) pars compacta (SNc) and in the ventral tegmental area. Interestingly, the expression of FA1/dlk1 significantly increased in tyrosine hydroxylase (TH)-ir cells during early postnatal development. Co-localization and tracing studies demonstrated that FA1/dlk1-ir cells in the SNc were nigrostriatal dopaminergic neurons, and unilateral 6-OHDA lesions resulted in loss of both FA1/dlk1-ir and TH-ir cells in the SNc. Surprisingly, increased numbers of FA1/dlk1-ir cells (by 70%) were detected in dopamine-depleted striata as compared to unlesioned controls. The higher number of FA1/dlk1-ir cells was likely not due to neurogenesis as colocalization studies for proliferation markers were negative. This suggests that FA1/dlk1 was up-regulated in intrinsic cells in response to the 6-OHDA-mediated loss of FA1/dlk1-expressing SNc dopaminergic neurons and/or due to the stab wound. Our findings hint to a significant role of FA1/dlk1 in the SNc during early postnatal development. The differential expression of FA1/dlk1 in the SNc and the striatum of dopamine-depleted rats could indicate a potential involvement of FA1/dlk1 in the cellular response to the degenerative processes.

Zwei neue Salices aus der Sammlung: "Plants of Southern Colorado collected and distributed by C. F. Baker, F. S. Earle and S. M. Tracy"

Von Otto v. Seemen

The design and evaluation of a 2D dose verification system for intensity modulated radiotherapy

The usage of intensity modulated radiotherapy (IMRT) treatments necessitates a significant amount of patient-specific quality assurance (QA). This research has investigated the precision and accuracy of Kodak EDR2 film measurements for IMRT verifications, the use of comparisons between 2D dose calculations and measurements to improve treatment plan beam models, and the dosimetric impact of delivery errors. New measurement techniques and software were developed and used clinically at M. D. Anderson Cancer Center. The software implemented two new dose comparison parameters, the 2D normalized agreement test (NAT) and the scalar NAT index. A single-film calibration technique using multileaf collimator (MLC) delivery was developed. EDR2 film's optical density response was found to be sensitive to several factors: radiation time, length of time between exposure and processing, and phantom material. Precision of EDR2 film measurements was found to be better than 1%. For IMRT verification, EDR2 film measurements agreed with ion chamber results to 2%/2mm accuracy for single-beam fluence map verifications and to 5%/2mm for transverse plane measurements of complete plan dose distributions. The same system was used to quantitatively optimize the radiation field offset and MLC transmission beam modeling parameters for Varian MLCs. While scalar dose comparison metrics can work well for optimization purposes, the influence of external parameters on the dose discrepancies must be minimized. The ability of 2D verifications to detect delivery errors was tested with simulated data. The dosimetric characteristics of delivery errors were compared to patient-specific clinical IMRT verifications. For the clinical verifications, the NAT index and percent of pixels failing the gamma index were exponentially distributed and dependent upon the measurement phantom but not the treatment site. Delivery errors affecting all beams in the treatment plan were flagged by the NAT index, although delivery errors impacting only one beam could not be differentiated from routine clinical verification discrepancies. Clinical use of this system will flag outliers, allow physicists to examine their causes, and perhaps improve the level of agreement between radiation dose distribution measurements and calculations. The principles used to design and evaluate this system are extensible to future multidimensional dose measurements and comparisons. ^

The Comprehensive Assessment of Leadership for Learning: A Next Generation Formative Evaluation and Feedback System

Recent developments in federal policy have prompted the creation of state evaluation frameworks for principals and teachers that hold educators accountable for effective practices and student outcomes. These changes have created a demand for formative evaluation instruments that reflect current accountability pressures and can be used by schools to focus school improvement and leadership development efforts. The Comprehensive Assessment of Leadership for Learning (CALL) is a next generation, 360-degree on-line assessment and feedback system that reflect best practices in feedback design. Some unique characteristics of CALL include a focus on: leadership distributed throughout the school rather than as carried out by an individual leader; assessment of leadership tasks rather than perceptions of leadership practice; a focus on larger complex systems of middle and high school; and transparency of assessment design. This paper describes research contributing to the design and validation of the CALL survey instrument.

Marine Isotope Stage (MIS) 11 results of model data with Community Climate System Model version 3 including the Dynamic Global Vegetation Model (CCSM3-DGVM) in NetCDF format at global and regional scale

The climate of Marine Isotope Stage (MIS) 11, the interglacial roughly 400,000 years ago, is investigated for four time slices, 416, 410, 400, and 394 ka. The overall picture is that MIS 11 was a relatively warm interglacial in comparison to preindustrial, with Northern Hemisphere (NH) summer temperatures early in MIS 11 (416-410 ka) warmer than preindustrial, though winters were cooler. Later in MIS 11, especially around 400 ka, conditions were cooler in the NH summer, mainly in the high latitudes. Climate changes simulated by the models were mainly driven by insolation changes, with the exception of two local feedbacks that amplify climate changes. Here, the NH high latitudes, where reductions in sea ice cover lead to a winter warming early in MIS 11, as well as the tropics, where monsoon changes lead to stronger climate variations than one would expect on the basis of latitudinal mean insolation change alone, are especially prominent. The results support a northward expansion of trees at the expense of grasses in the high northern latitudes early during MIS 11, especially in northern Asia and North America.

The Canyon System off Fimbulisen

In der vorliegenden Arbeit werden Daten einer systematischen Vermessung in der Lazarev Sea nahe des Fimbul-Ice-Shelfs (Fimbulisen) genutzt, die während der Expedition ANT XIX-2 mit dem Fächersonarsystem Hydrosweep DS-2 und dem Sedimentecholot Parasound erhoben wurden. Nach kurzer Darstellung der Hintergründe dieser durchgeführten Untersuchungen in dem Messgebiet wird allgemein auf wesentliche Aspekte der Hydroakustik hinsichtlich der Anwendung von Echolotsystemen eingegangen. Schwerpunktmäßig soll dabei der parametrischen Effekt, das Messprinzip parametrischer Sedimentecholote, behandelt werden. Nach anschließender Anführung zweier praktischer Anwendungen hydroakustischer Messverfahren anhand des Hydrosweep DS-2 und des Parasound-Systems wird eingehend deren Positionierung auf FS 'Polarstern' dargestellt, da sich bei der Aufbereitung der Messungen zeigte, dass sich das größte Problem der Daten beider Systeme in der minderwertigen Qualität der Navigationsdaten abzeichnete. Aus den bereinigten Tiefendaten der Fächersonarmessung wird ein digitales Geländemodell (DGM) mit einer Rasterweite von 100 m generiert. Dieses Modell liegt für die weitere Bearbeitung digital und in Form einer bathymetrischen Karte im Maßstab 1:250,000 vor, bei der die Topographie des Canyon-Systems nahe dem Fimbulisen durch Isolinien mit einer Aquidistanz von 50 m dargestellt wird. Die als Ergebnis der prozessierten Parasound-Daten erhaltenen Seismogramme, die gefiltert im digitalen Bildformat mit bekannter Start- und Endposition für einen definierten Tiefenbereich vorliegen, können zusammen mit dem DGM in einem dreidimensionalen Modell dargestellt werden. Dieses in digitaler Form vorliegende Modell kann durch den Nutzer interaktiv durchschritten und die darin enthaltenen Messergebnisse in ihrer Gesamtheit sowie in Detailansichten aus verschiedenen Perspektiven betrachtet werden, was das gegenseitige Verständnis und Einschätzung der Ergebnisse aus den beiden Messverfahren fördert. Diese gemeinsame Darstellungsweise eines digitalen Geländemodells in Kombination mit den Seismogramm-Bildern des Sedimentecholotes Parasound bietet sich auch hinsichtlich einer geologischen Klassifizierung der verschiedenen Echotypen und einer anschließenden Interpretation der Sedimentationsvorgänge in einem flächenhaft vermessenen Gebiet an.

Pigment data set from the SeaWiFS Bio-optical Archive and Storage System (1961-1996)

The oceans play a critical role in the Earth's climate, but unfortunately, the extent of this role is only partially understood. One major obstacle is the difficulty associated with making high-quality, globally distributed observations, a feat that is nearly impossible using only ships and other ocean-based platforms. The data collected by satellite-borne ocean color instruments, however, provide environmental scientists a synoptic look at the productivity and variability of the Earth's oceans and atmosphere, respectively, on high-resolution temporal and spatial scales. Three such instruments, the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) onboard ORBIMAGE's OrbView-2 satellite, and two Moderate Resolution Imaging Spectroradiometers (MODIS) onboard the National Aeronautic and Space Administration's (NASA) Terra and Aqua satellites, have been in continuous operation since September 1997, February 2000, and June 2002, respectively. To facilitate the assembly of a suitably accurate data set for climate research, members of the NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project and SeaWiFS Project Offices devote significant attention to the calibration and validation of these and other ocean color instruments. This article briefly presents results from the SIMBIOS and SeaWiFS Project Office's (SSPO) satellite ocean color validation activities and describes the SeaWiFS Bio-optical Archive and Storage System (SeaBASS), a state-of-the-art system for archiving, cataloging, and distributing the in situ data used in these activities.