On the convergence of 3D free discontinuity models in variational fracture

Free discontinuity problems arising in the variational theory for fracture mechanics are considered. A Γ -convergence proof for an r-adaptive 3D finite element discretization is given in the case of a brittle material. The optimal displacement field, crack pattern and mesh geometry are obtained through a variational procedure that encompasses both mechanical and configurational forces. Possible extensions to cohesive fracture and quasi-static evolutions are discussed.     

A speed sensorless control based on a MRAS applied to a double fed induction machine drive

This paper proposes a new MRAS method to estimate the mechanical quantities in a double fed induction machine. In the traditional formulation the integral term, introduced by the PI MRAS regulator, is canceled in the transfer function between the estimated and the real speed. As a novelty, an additional term depending on the reference rotor flux through a constant gain g is introduced in the adjustable model of the MRAS. This innovation restores the integral term in the transfer function. As a consequence, during the closed loop operation, the estimated speed does not exhibit anymore a steady state error. The influence of the inverter non-linearities and of the non-linear rotor brush resistance on the speed estimation is also discussed. Some experimental tests validate the proposed method.     

Intrinsic Fluorescence of the Active and the Inactive Functional Forms of Human Thymidylate Synthase

The observables associated with protein intrinsic fluorescence – spectra, time decays, anisotropies – offer opportunities to monitor in real time and non-invasively a protein‘s functional form and its interchange with other forms with different functions. We employed these observables to sketch the fluorometric profiles of two functional forms of human thymidylate synthase (hTS), a homodimeric enzyme crucial for cell proliferation and thus targeted by anticancer drugs. The protein takes an active and an inactive form. Stabilization of the latter by peptides that, unlike classical hTS inhibitors, bind it at the monomer/monomer interface offers an alternative inhibition mechanism that promises to avoid the onset of drug resistance in anticancer therapy. The fluorescence features depicted herein can be used as tools to identify and quantify each of the two protein forms in solution, thus making it possible to investigate the kinetic and thermodynamic aspects of the active/inactive conformational interchange. Two examples of fluorometrically monitored interconversion kinetics are provided.     

Curcumin Prevents Cerebellar Hypoplasia and Restores the Behavior in Hyperbilirubinemic Gunn Rat by a Pleiotropic Effect on the Molecular Effectors of Brain Damage

Bilirubin toxicity to the central nervous system (CNS) is responsible for severe and permanent neurologic damage, resulting in hearing loss, cognitive, and movement impairment. Timely and effective management of severe neonatal hyperbilirubinemia by phototherapy or exchange transfusion is crucial for avoiding permanent neurological consequences, but these therapies are not always possible, particularly in low-income countries. To explore alternative options, we investigated a pharmaceutical approach focused on protecting the CNS from pigment toxicity, independently from serum bilirubin level. To this goal, we tested the ability of curcumin, a nutraceutical already used with relevant results in animal models as well as in clinics in other diseases, in the Gunn rat, the spontaneous model of neonatal hyperbilirubinemia. Curcumin treatment fully abolished the landmark cerebellar hypoplasia of Gunn rat, restoring the histological features, and reverting the behavioral abnormalities present in the hyperbilirubinemic rat. The protection was mediated by a multi-target action on the main bilirubin-induced pathological mechanism ongoing CNS damage (inflammation, redox imbalance, and glutamate neurotoxicity). If confirmed by independent studies, the result suggests the potential of curcumin as an alternative/complementary approach to bilirubin-induced brain damage in the clinical scenario.     

Anisotropic deformation for local shape control

Computational Visual Media - We present a novel approach to mesh deformation that enables simple context sensitive manipulation of 3D geometry. The method is based on locally anisotropic...     

How “Authentic Intentionality” can be Enabled: a Neurocomputational Hypothesis

According to John Haugeland, the capacity for “authentic intentionality” depends on a commitment to constitutive standards of objectivity. One of the consequences of Haugeland’s view is that a neurocomputational explanation cannot be adequate to understand “authentic intentionality”. This paper gives grounds to resist such a consequence. It provides the beginning of an account of authentic intentionality in terms of neurocomputational enabling conditions. It argues that the standards, which constitute the domain of objects that can be represented, reflect the statistical structure of the environments where brain sensory systems evolved and develop. The objection that I equivocate on what Haugeland means by “commitment to standards” is rebutted by introducing the notion of “florid, self-conscious representing”. Were the hypothesis presented plausible, computational neuroscience would offer a promising framework for a better understanding of the conditions for meaningful representation.     

The use of games to help children eyes testing

A doctor cannot perform a good diagnosis without the patient collaboration. One of the major problem for ophthalmologists with children is to capture and maintain their attention while performing their tests. Sometimes children give wrong answers, or not accurate, since they are no longer interested in the task. In this paper we use the serious game paradigm to help children eyes testing. We ask the children to perform a vision acuity and a daltonism test using our game PlayWithEyes. Children have to recognize symbols projected on a wall and point them in a touch interface which displays all the possible answers. Tests performed in a kindergarten with 65 children have shown that the use of our game helps to obtain children cooperation because they have fun, so their attention may last longer, thus improving the possibility to perform a correct diagnosis especially for very young children. This is particular important for some sight defects like amblyopia (lazy eye). Moreover, the system allows us to identify visual acuity reduction in two children. Tests also highlight some limitations of the tool which have been promptly fixed.     

Flow-based local optimization for image-to-geometry projection

The projection of a photographic data set on a 3D model is a robust and widely applicable way to acquire appearance information of an object. The first step of this procedure is the alignment of the images on the 3D model. While any reconstruction pipeline aims at avoiding misregistration by improving camera calibrations and geometry, in practice a perfect alignment cannot always be reached. Depending on the way multiple camera images are fused on the object surface, remaining misregistrations show up either as ghosting or as discontinuities at transitions from one camera view to another. In this paper we propose a method, based on the computation of Optical Flow between overlapping images, to correct the local misalignment by determining the necessary displacement. The goal is to correct the symptoms of misregistration, instead of searching for a globally consistent mapping, which might not exist. The method scales up well with the size of the data set (both photographic and geometric) and is quite independent of the characteristics of the 3D model (topology cleanliness, parametrization, density). The method is robust and can handle real world cases that have different characteristics: low level geometric details and images that lack enough features for global optimization or manual methods. It can be applied to different mapping strategies, such as texture or per-vertex attribute encoding.     

SPIDER: An availability-aware framework for the service function chain placement in distributed scenarios

The network function virtualization (NFV) paradigm replaces hardware-dependent network functions by virtual network functions (VNFs) that can be deployed in commodity hardware, including legacy servers. Consequently, the use of NFV is expected to reduce operating and capital expenses, as well as improve service deployment operation and management flexibility. For many use cases, the VNFs must be visited and invoked following a specific order of execution in order to compose a complete network service, named service function chain (SFC). Nonetheless, despite the benefits from NFV and SFC virtualization technologies, their introduction must not harm network performance and service availability. On the one hand, redundancy is seen by network service planners as a mechanism well established to combat availability issues. At same time, there is a goal to optimize resource utilization in order to reduce operational expenditure. In this article, we share our experience in the design use of a framework, named SPIDER, focused on SFC placement that considers the network infrastructure condition and the required SFC availability to define the placement strategy. The SPIDER monitors the status of infrastructure nodes and links and defines which servers the VNFs should be placed on and the number of redundant replicas needed. We present a proof-of-concept of SPIDER using Kubernetes to launch the VNFs as containers. We also use Kubernetes to forward the traffic between the VNFs, composing the service chain. We perform experiments to evaluate the runtime of SPIDER and the SFC delay under different network conditions.     

Scientific workflows for process mining: building blocks,scenarios, and implementation

Over the past decade process mining has emerged as a new analytical discipline able to answer a variety of questions based on event data. Event logs have a very particular structure; events have timestamps, refer to activities and resources, and need to be correlated to form process instances. Process mining results tend to be very different from classical data mining results, e.g., process discovery may yield end-to-end process models capturing different perspectives rather than decision trees or frequent patterns. A process-mining tool like ProM provides hundreds of different process mining techniques ranging from discovery and conformance checking to filtering and prediction. Typically, a combination of techniques is needed and, for every step, there are different techniques that may be very sensitive to parameter settings. Moreover, event logs may be huge and may need to be decomposed and distributed for analysis. These aspects make it very cumbersome to analyze event logs manually. Process mining should be repeatable and automated. Therefore, we propose a framework to support the analysis of process mining workflows. Existing scientific workflow systems and data mining tools are not tailored towards process mining and the artifacts used for analysis (process models and event logs). This paper structures the basic building blocks needed for process mining and describes various analysis scenarios. Based on these requirements we implemented RapidProM, a tool supporting scientific workflows for process mining. Examples illustrating the different scenarios are provided to show the feasibility of the approach.