Crystal structure of the heterotrimeric integrin-binding region of laminin-111

Laminins are cell - adhesive glycoproteins that are essential for basement membrane assembly and function. Integrins are important laminin receptors, but their binding site on the heterotrimeric laminin s is poorly defined structurally. We report the crystal structure at 2.13 Å resolution of a minimal integrin - binding fragment of mouse laminin - 111, consisting of ~50 resid ues of α 1 β 1 γ 1 coiled coil and the first three lam inin G - like (LG) domains of the α 1 chain . The LG domains adopt a triangular arrangem ent, with the C - terminus of the coiled coil situated between LG1 and LG2. The critical integrin - binding glutamic acid residue in the γ 1 chain tail is surface - exposed and predicted to bind to the metal ion - dependent adhesion site in the integrin β 1 subunit. Additional contacts to the integrin are likely to be made by the LG1 and LG2 surfaces adjacent to the γ 1 chain tail, which are notably conserved and free of obstructing glycans

The quarter-point quadratic isoparametric element as a singular element for crack problems

The quadratic isoparametric elements which embody the inverse square root singularity are used for calculating the stress intensity factors at tips of cracks. The strain singularity at a point or an edge is obtained in a simple manner by placing the mid-side nodes at quarter points in the vicinity of the crack tip or an edge. These elements are implemented in NASTRAN as dummy elements. The method eliminates the use of special crack tip elements and in addition, these elements satisfy the constant strain and rigid body modes required for convergence

Formulating and managing viable SLAs in cloud computing from a small to medium service provider's viewpoint: A state-of-the-art review

© 2017 Elsevier Ltd In today's competitive world, service providers need to be customer-focused and proactive in their marketing strategies to create consumer awareness of their services. Cloud computing provides an open and ubiquitous computing feature in which a large random number of consumers can interact with providers and request services. In such an environment, there is a need for intelligent and efficient methods that increase confidence in the successful achievement of business requirements. One such method is the Service Level Agreement (SLA), which is comprised of service objectives, business terms, service relations, obligations and the possible action to be taken in the case of SLA violation. Most of the emphasis in the literature has, until now, been on the formation of meaningful SLAs by service consumers, through which their requirements will be met. However, in an increasingly competitive market based on the cloud environment, service providers too need a framework that will form a viable SLA, predict possible SLA violations before they occur, and generate early warning alarms that flag a potential lack of resources. This is because when a provider and a consumer commit to an SLA, the service provider is bound to reserve the agreed amount of resources for the entire period of that agreement – whether the consumer uses them or not. It is therefore very important for cloud providers to accurately predict the likely resource usage for a particular consumer and to formulate an appropriate SLA before finalizing an agreement. This problem is more important for a small to medium cloud service provider which has limited resources that must be utilized in the best possible way to generate maximum revenue. A viable SLA in cloud computing is one that intelligently helps the service provider to determine the amount of resources to offer to a requesting consumer, and there are number of studies on SLA management in the literature. The aim of this paper is two-fold. First, it presents a comprehensive overview of existing state-of-the-art SLA management approaches in cloud computing, and their features and shortcomings in creating viable SLAs from the service provider's viewpoint. From a thorough analysis, we observe that the lack of a viable SLA management framework renders a service provider unable to make wise decisions in forming an SLA, which could lead to service violations and violation penalties. To fill this gap, our second contribution is the proposal of the Optimized Personalized Viable SLA (OPV-SLA) framework which assists a service provider to form a viable SLA and start managing SLA violation before an SLA is formed and executed. The framework also assists a service provider to make an optimal decision in service formation and allocate the appropriate amount of marginal resources. We demonstrate the applicability of our framework in forming viable SLAs through experiments. From the evaluative results, we observe that our framework helps a service provider to form viable SLAs and later to manage them to effectively minimize possible service violation and penalties

Qudit Colour Codes and Gauge Colour Codes in All Spatial Dimensions

Two-level quantum systems, qubits, are not the only basis for quantum computation. Advantages exist in using qudits, d-level quantum systems, as the basic carrier of quantum information. We show that color codes, a class of topological quantum codes with remarkable transversality properties, can be generalized to the qudit paradigm. In recent developments it was found that in three spatial dimensions a qubit color code can support a transversal non-Clifford gate, and that in higher spatial dimensions additional non-Clifford gates can be found, saturating Bravyi and K\"onig's bound [Phys. Rev. Lett. 110, 170503 (2013)]. Furthermore, by using gauge fixing techniques, an effective set of Clifford gates can be achieved, removing the need for state distillation. We show that the qudit color code can support the qudit analogues of these gates, and show that in higher spatial dimensions a color code can support a phase gate from higher levels of the Clifford hierarchy which can be proven to saturate Bravyi and K\"onig's bound in all but a finite number of special cases. The methodology used is a generalisation of Bravyi and Haah's method of triorthogonal matrices [Phys. Rev. A 86 052329 (2012)], which may be of independent interest. For completeness, we show explicitly that the qudit color codes generalize to gauge color codes, and share the many of the favorable properties of their qubit counterparts.Comment: Authors' final cop

Patient and health care professional decision-making to commence and withdraw from renal dialysis: A systematic review of qualitative research

Background and objectives. To ensure decisions to start and stop dialysis in end stage kidney disease are shared, the factors that affect patients and healthcare professionals in making such decisions need to be understood. This systematic review aims to explore how and why different factors mediate the choices about dialysis treatment. Design, setting, participants, and measurements. Medline, Embase, CINAHL and PsychINFO were searched for qualitative studies of factors that affect patients’ and/or healthcare professionals’ decisions to commence or withdraw from dialysis. A thematic synthesis was conducted. Results. Of 494 articles screened, 12 studies (conducted: 1985-2014) were included. These involved 206 predominantly haemodialysis patients and 64 healthcare professionals (age range: patients 26-93; professionals 26-61 years). (i) Commencing dialysis: patients based their choice on ‘gut-instinct’ as well as deliberating the impact of treatment on quality-of-life and survival. How individuals coped with decision-making was influential, some tried to take control of the problem of progressive renal failure, whilst others focussed on controlling their emotions. Healthcare professionals weighed-up biomedical factors and were led by an instinct to prolong life. Both patients and healthcare professionals described feeling powerless. (ii) Dialysis withdrawal: Only after prolonged periods of time on dialysis, were the realities of life on dialysis fully appreciated and past choice questioned. By this stage however patients were physically treatment dependent. Similar to commencing dialysis, individuals coped with treatment withdrawal in a problem or emotion-controlling way. Families struggled to differentiate choosing versus allowing death. Healthcare teams avoided and queried discussions regarding dialysis withdrawal. Patients however missed the dialogue they experienced during pre-dialysis education. Conclusions. Decision-making in end stage kidney disease is complex, dynamic, and evolves over time and towards death. The factors at work are multi-faceted and operate differently for patients and health professionals. More training and research on open-communication and shared decision-making is needed

Risk-based framework for SLA violation abatement from the cloud service provider's perspective

© The British Computer Society 2018. The constant increase in the growth of the cloud market creates new challenges for cloud service providers. One such challenge is the need to avoid possible service level agreement (SLA) violations and their consequences through good SLA management. Researchers have proposed various frameworks and have made significant advances in managing SLAs from the perspective of both cloud users and providers. However, none of these approaches guides the service provider on the necessary steps to take for SLA violation abatement; that is, the prediction of possible SLA violations, the process to follow when the system identifies the threat of SLA violation, and the recommended action to take to avoid SLA violation. In this paper, we approach this process of SLA violation detection and abatement from a risk management perspective. We propose a Risk Management-based Framework for SLA violation abatement (RMF-SLA) following the formation of an SLA which comprises SLA monitoring, violation prediction and decision recommendation. Through experiments, we validate and demonstrate the suitability of the proposed framework for assisting cloud providers to minimize possible service violations and penalties

Comparing time series with machine learning-based prediction approaches for violation management in cloud SLAs

© 2018 In cloud computing, service level agreements (SLAs) are legal agreements between a service provider and consumer that contain a list of obligations and commitments which need to be satisfied by both parties during the transaction. From a service provider's perspective, a violation of such a commitment leads to penalties in terms of money and reputation and thus has to be effectively managed. In the literature, this problem has been studied under the domain of cloud service management. One aspect required to manage cloud services after the formation of SLAs is to predict the future Quality of Service (QoS) of cloud parameters to ascertain if they lead to violations. Various approaches in the literature perform this task using different prediction approaches however none of them study the accuracy of each. However, it is important to do this as the results of each prediction approach vary according to the pattern of the input data and selecting an incorrect choice of a prediction algorithm could lead to service violation and penalties. In this paper, we test and report the accuracy of time series and machine learning-based prediction approaches. In each category, we test many different techniques and rank them according to their order of accuracy in predicting future QoS. Our analysis helps the cloud service provider to choose an appropriate prediction approach (whether time series or machine learning based) and further to utilize the best method depending on input data patterns to obtain an accurate prediction result and better manage their SLAs to avoid violation penalties