Discovering invariants via simple component analysis

We propose a new technique combining dynamic and static analysis of programs to find linear invariants. We use a statistical tool, called simple component analysis, to analyze partial execution traces of a given program. We get a new coordinate system in the vector space of program variables, which is used to specialize numerical abstract domains. As an application, we instantiate our technique to interval analysis of simple imperative programs and show some experimental evaluations.     

Leakage tests for Am solid sources used for liquid xenon detector monitoring

Experimental tests are described to check solid ²⁴¹Am radioactive sources used to monitor operation of liquid xenon detectors. In particular, radioactive leakage was tested in extreme temperature conditions following immersion in liquid nitrogen for different time periods. No radioactivity loss was detected from the sources considered. The paper describes the source characteristics, test methods and results obtained.     

Approximate similarity retrieval with M-trees

Motivated by the urgent need to improve the efficiency of similarity queries, approximate similarity retrieval is investigated in the environment of a metric tree index called the M-tree. Three different approximation techniques are proposed, which show how to forsake query precision for improved performance. Measures are defined that can quantify the improvements in performance efficiency and the quality of approximations. The proposed approximation techniques are then tested on various synthetic and real-life files. The evidence obtained from the experiments confirms our hypothesis that a high-quality approximated similarity search can be performed at a much lower cost than that needed to obtain the exact results. The proposed approximation techniques are scalable and appear to be independent of the metric used. Extensions of these techniques to the environments of other similarity search indexes are also discussed. Received July 7, 1998 / Accepted October 13, 1998     

Fighting the Huntington’s Disease with a G-Quadruplex-Forming Aptamer Specifically Binding to Mutant Huntingtin Protein: Biophysical Characterization,In Vitro and In Vivo Studies

A set of guanine-rich aptamers able to preferentially recognize full-length huntingtin with an expanded polyglutamine tract has been recently identified, showing high efficacy in modulating the functions of the mutated protein in a variety of cell experiments. We here report a detailed biophysical characterization of the best aptamer in the series, named MS3, proved to adopt a stable, parallel G-quadruplex structure and show high nuclease resistance in serum. Confocal microscopy experiments on HeLa and SH-SY5Y cells, as models of non-neuronal and neuronal cells, respectively, showed a rapid, dose-dependent uptake of fluorescein-labelled MS3, demonstrating its effective internalization, even in the absence of transfecting agents, with no general cytotoxicity. Then, using a well-established Drosophila melanogaster model for Huntington’s disease, which expresses the mutated form of human huntingtin, a significant improvement in the motor neuronal function in flies fed with MS3 was observed, proving the in vivo efficacy of this aptamer.     

A two-step,fourth-order method with energy preserving properties

We introduce a family of fourth-order two-step methods that preserve the energy function of canonical polynomial Hamiltonian systems. As is the case with linear mutistep and one-leg methods, a prerogative of the new formulae is that the associated nonlinear systems to be solved at each step of the integration procedure have the very same dimension of the underlying continuous problem.The key tools in the new methods are the line integral associated with a conservative vector field (such as the one defined by a Hamiltonian dynamical system) and its discretization obtained by the aid of a quadrature formula. Energy conservation is equivalent to the requirement that the quadrature is exact, which turns out to be always the case in the event that the Hamiltonian function is a polynomial and the degree of precision of the quadrature formula is high enough. The non-polynomial case is also discussed and a number of test problems are finally presented in order to compare the behavior of the new methods to the theoretical results.     

DEM modelling analysis of tree root growth in street pavements

The coexistence of urban green spaces and infrastructure is often difficult. Trees find inhospitable environments in urban areas, whereas tree root systems can damage sidewalk, street and parking lot. The main form of failure concerns the growing of tree roots beneath the pavements, which produce upheavals and displacements on wearing course. The main objective of this study was a distinct element method modelling analysis of the potential interactions between tree root systems and street pavements. This calculation code allowed us to simulate the dynamic behaviour of the ground-pavement system as result of the roots growth. The performed modelling, representative of various planting strategies commonly used in urban contexts, have highlighted the progressive reduction of deformations with the increase of the roots penetration depth. Such displacements were strongly influenced by other factors such as the porosity and the grain-size distribution of the soil and the type of pavement considered.     

Efficient energy-based embedding models for link prediction in knowledge graphs

We focus on the problem of link prediction in Knowledge Graphs, with the goal of discovering new facts. To this purpose, Energy-Based Models for Knowledge Graphs that embed entities and relations in continuous vector spaces have been largely used. The main limitation in their applicability lies in the parameter learning phase, which may require a large amount of time for converging to optimal solutions. In this article, we first propose an unified view on different Energy-Based Embedding Models. Hence, for improving the model training phase, we propose the adoption of adaptive learning rates. We show that, by adopting adaptive learning rates during training, we can improve the efficiency of the parameter learning process by an order of magnitude, while leading to more accurate link prediction models in a significantly lower number of iterations. We extensively evaluate the proposed learning procedure on a variety of new models: our result show a significant improvement over state-of-the-art link prediction methods on two large Knowledge Graphs, namely WordNet and Freebase.     

Analysis of flamelet leading point dynamics in an inhomogeneous flow

Several studies have utilized “leading points” concepts to explain the augmentation of burning rates in turbulent flames by flow fluctuations. These ideas have been particularly utilized to explain the strong sensitivity of turbulent burning rates to fuel composition. Leading point concepts suggest that the burning velocity is controlled by the velocity of the points on the flame that propagate farthest out into the reactants – thus, they de-emphasize the classical idea that burning velocity enhancement is due to increases in flame surface area. Rather, within this interpretation, flame area creation is the effect, not the cause, of augmented turbulent burning velocities. However, the theory behind the implementation of leading point concepts in turbulent combustion modeling needs further development and the definition of “leading point” has not been fully clarified. For a certain class of steady shear flows, it is straightforward to demonstrate the leading point concept in an intuitive manner, but the problem becomes more complex when the leading points themselves evolve in time. In this paper, we use the G-equation to describe the flame dynamics and, utilizing results for Hamilton–Jacobi equations from the Aubry–Mather theory, demonstrate both the utility and limitations of leading points interpretations for front propagation, at least for deterministic problems. Specifically, we show how the large-time behavior of the solutions is controlled by discrete points on the flame under certain conditions and is, therefore, independent of the rest of the flow field details – a key hypothesis of leading points theories. However, it is possible to find other conditions where the large time behavior of the flame is not controlled by discrete points on the flame, but rather by the velocity field over its entire surface. Moreover, we also show that even in cases where the burning rate is controlled by discrete points, these points are not necessarily the most forward lying points in the flame front. Finally, we consider the case where the laminar flame speed is a function of flame front curvature and derive exact results for the sensitivity of the front speed to the Markstein length, ?, for ? > 0. These solutions explicitly illustrate how the reduction of front displacement speed for increasing ? can be interpreted in terms of leading points dynamics in some cases.     

Estimation of soil properties of shallow landslide source areas by dynamic penetration tests: first outcomes from Northern Tuscany (Italy)

In Northern Tuscany (Italy) rapid, shallow landslides often cause casualties and severe damage. Aimed at contributing to the characterisation of the source areas of rapid, shallow landslides, this paper deals with the geotechnical parameterisation of the mainly involved soil by means of dynamic penetration tests. The source areas are usually located in difficult access sites, where boring and undisturbed sampling are very hard and onerous. Therefore, the results of 177 dynamic penetration tests were analysed, including dynamic probing (DP) tests and standard penetration tests (SPT). The results of these tests were related to relative density D _r and friction angle Φ′ of the soil by means of empirical equations. The distribution and variability of these parameters were analysed and related to soil type, test type and probing depth. The D _r and Φ′ values coming from the DP and SPT tests were found to be comparable. The Φ′ values coming from DP tests and direct shear tests showed an acceptable correlation, confirming the utility of the DP tests. The DP test can thus be an effective tool in the estimation of the properties of potentially unstable soil slope covers.     

Novel Therapeutic Opportunities in Neoadjuvant Setting in Urothelial Cancers: A New Horizon Opened by Molecular Classification and Immune Checkpoint Inhibitors

Muscle invasive bladder cancer (MIBC) is a widespread malignancy with a worse prognosis often related to a late diagnosis. For early-stage MIBC pts, a multidisciplinary approach is mandatory to evaluate the timing of neoadjuvant chemotherapy (NAC) and surgery. The current standard therapy is platinum-based NAC (MVAC-methotrexate, vinblastine, doxorubicin, and cisplatin or Platinum–Gemcitabine regimens) followed by radical cystectomy (RC) with lymphadenectomy. However, preliminary data from Vesper trial highlighted that dose-dense NAC MVAC is endowed with a good pathological response but shows low tolerability. In the last few years, translational-based research approaches have identified several candidate biomarkers of NAC esponsiveness, such as ERCC2, ERBB2, or DNA damage response (DDR) gene alterations. Moreover, the recent consensus MIBC molecular classification identified six molecular subtypes, characterized by different sensitivity to chemo- or targeted or immunotherapy, that could open a novel procedure for patient selection and also for neoadjuvant therapies. The Italian PURE-01 phase II Trial extended data on efficacy and resistance to Immune Checkpoint Inhibitors (ICIs) in this setting. In this review, we summarize the most relevant literature data supporting NAC use in MIBC, focusing on novel therapeutic strategies such as immunotherapy, considering the better patient stratification and selection emerging from novel molecular classification.