Using abstract interpretation to add type checking for interfaces in Java bytecode verification

Java interface types support multiple inheritance. Because of this, the standard bytecode verifier ignores them, since it is not able to model the class hierarchy as a lattice. Thus, type checks on interfaces are performed at run time. We propose a verification methodology that removes the need for run-time checks. The methodology consists of: (1) an augmented verifier that is very similar to the standard one, but is also able to check for interface types in most cases; (2) for all other cases, a set of additional simpler verifiers, each one specialized for a single interface type. We obtain these verifiers in a systematic way by using abstract interpretation techniques. Finally, we describe an implementation of the methodology and evaluate it on a large set of benchmarks.     

Robust embedded projective nonnegative matrix factorization for image analysis and feature extraction

Nonnegative matrix factorization (NMF) is an unsupervised learning method for decomposing high-dimensional nonnegative data matrices and extracting basic and intrinsic features. Since image data are described and stored as nonnegative matrices, the mining and analysis process usually involves the use of various NMF strategies. NMF methods have well-known applications in face recognition, image reconstruction, handwritten digit recognition, image denoising and feature extraction. Recently, several projective NMF (P-NMF) methods based on positively constrained projections have been proposed and were found to perform better than the standard NMF approach in some aspects. However, some drawbacks still affect the existing NMF and P-NMF algorithms; these include dense factors, slow convergence, learning poor local features, and low reconstruction accuracy. The aim of this paper is to design algorithms that address the aforementioned issues. In particular, we propose two embedded P-NMF algorithms: the first method combines the alternating least squares (ALS) algorithm with the P-NMF update rules of the Frobenius norm and the second one embeds ALS with the P-NMF update rule of the Kullback–Leibler divergence. To assess the performances of the proposed methods, we conducted various experiments on four well-known data sets of faces. The experimental results reveal that the proposed algorithms outperform other related methods by providing very sparse factors and extracting better localized features. In addition, the empirical studies show that the new methods provide highly orthogonal factors that possess small entropy values.     

Nitrous oxide mitigation potential of reduced tillage and N input in durum wheat in the Mediterranean

In Italy, managed soils account for about 50% of annual national emissions of nitrous oxide (N₂O), thus the effect of agricultural practices on N₂O emissions must be studied in order to develop mitigation strategies. Soil N₂O emissions were measured in two field campaigns (2013–2014 and 2014–2015) on durum wheat in a Mediterranean environment to test the mitigation potential of reduced tillage and nitrogen (N) fertilization rate. N₂O emissions were measured with a fully-transportable instrument developed during the project LIFE?+?IPNOA “Improved flux Prototypes for N₂O emission reduction from Agriculture” and equipped with an infrared laser detector. Reducing tillage from ploughing to minimum tillage had no effect on average daily N₂O flux, while decreasing the N rate from 170 to 110 kg N ha^?1 reduced the average daily N₂O flux, without negatively affecting the grain yield. Furthermore, N₂O daily flux were positively correlated with soil water filled pore space, NO₃-N, and NH₄-N concentrations, and they were largely variable between the two field campaigns as a result of different environmental and management conditions (i.e.: rainfall, different amount of crop residues incorporated in soil). Overall, the innovative fully-transportable instrument performed well in the field and allowed us to conclude that decreasing the N fertilizer rate was a valuable option to mitigate N₂O emissions without negative effects on wheat productivity.     

Exploring interoperability of language resources: the case of cross-lingual semi-automatic enrichment of wordnets

In this paper we present an application fostering the integration and interoperability of computational lexicons, focusing on the particular case of mutual linking and cross-lingual enrichment of two wordnets, the ItalWordNet and Sinica BOW lexicons. This is intended as a case-study investigating the needs and requirements of semi-automatic integration and interoperability of lexical resources, in the view of developing a prototype web application to support the GlobalWordNet Grid initiative.

Semantic technologies for open interaction systems

Open interaction systems play a crucial role in agreement technologies because they are software devised for enabling autonomous agents (software or human) to interact, negotiate, collaborate, and coordinate their activities in order to establish agreements and manage their execution. Following the approach proposed by the recent literature on agent environments those open distributed systems can be efficiently and effectively modeled as a set of correlated physical and institutional spaces of interaction where objects and agents are situated. In our view in distributed open systems, spaces are fundamental for modeling the fact that events, actions, and social concepts (like norms and institutional objects) should be perceivable only by the agents situated in the spaces where they happen or where they are situated. Institutional spaces are also crucial for their active functional role of keeping track of the state of the interaction, and for monitoring and enforcing norms. Given that in an open distributed and dynamic system it is fundamental to be able to create and destroy spaces of interaction at run-time, in this paper we propose to create them using Artificial Institutions (AIs) specified at design time. This dynamic creation is a complex task that deserves to be studied in all details. For doing that, in this paper, we will first define the various components of AIs and spaces using Semantic Web Technologies, then we will describe the mechanisms for using AIs specification for realizing spaces of interaction. We will exemplify this process by formalizing the components of the auction Artificial Institution and of the spaces created for running concrete auctions.     

Methylaluminoxane: only a cocatalyst or something more?

Summary Methylaluminoxane (MAO) was used as a catalyst for the polymerization of several vinyl monomers. Polymer yields were found to decrease in the order styrene > isobutyl vinyl ether > methyl methacrylate ≈ acrylonitrile > α-methylstyrene > vinyl acetate = 0. The polymers exhibit low to moderate molar mass with broad distributions. NMR analysis were used to determine the polymers steric microstructure and the end groups. MAO was also able to produce styrene-methyl methacrylate, styrene-isobutyl vinyl ether and methyl methacrylate-isobutyl vinyl ether copolymers. Experimental evidences are against ionic polymerization mechanisms, whereas proofs for a radical mechanism are more controversial, but altogether against of it.     

Characterization of the nucleation and growth behavior of copper precipitates in low-carbon steels

The nucleation and growth behavior of copper precipitates in ferrite was investigated both theoretically and experimentally for two low-carbon steels with and without niobium additions in samples cooled directly to the desired aging temperature from the austenitizing temperature. Theoretical nucleation and growth rate models were constructed using calculated thermodynamic data in conjunction with classical theories. The maximum nucleation and growth rates for Cu were experimentally determined to be 8.0 × 10²¹ nuclei/m³ s at 612 °C and 0.12 nm/s at 682 °C, respectively. Using an experimentally determined “effective” activation energy for the diffusion of copper, the theoretical nucleation rate curve compared very well with the hardness data for the first 5 minutes of aging. The growth behavior of the Cu precipitates was investigated through use of a conventional transmission electron microscope (TEM) for samples directly aged at 550 °C. For aging times up to 21 hours, the average precipitate size scaled with a time dependence of t ^1/2.     

Using PIV to measure granular temperature in saturated unsteady polydisperse granular flows

The motion of debris flows, gravity-driven fast moving mixtures of rock, soil and water can be interpreted using the theories developed to describe the shearing motion of highly concentrated granular fluid flows. Frictional, collisional and viscous stress transfer between particles and fluid characterizes the mechanics of debris flows. To quantify the influence of collisional stress transfer, kinetic models have been proposed. Collisions among particles result in random fluctuations in their velocity that can be represented by their granular temperature, T. In this paper particle image velocimetry, PIV, is used to measure the instantaneous velocity field found internally to a physical model of an unsteady debris flow created by using “transparent soil”—i.e. a mixture of graded glass particles and a refractively matched fluid. The ensemble possesses bulk properties similar to that of real soil-pore fluid mixtures, but has the advantage of giving optical access to the interior of the flow by use of plane laser induced fluorescence, PLIF. The relationship between PIV patch size and particle size distribution for the front and tail of the flows is examined in order to assess their influences on the measured granular temperature of the system. We find that while PIV can be used to ascertain values of granular temperature in dense granular flows, due to increasing spatial correlation with widening gradation, a technique proposed to infer the true granular temperature may be limited to flows of relatively uniform particle size or large bulk.     

Integrin-targeting with peptide-bioconjugated semiconductor-magnetic nanocrystalline heterostructures

Binary asymmetric nanocrystals (BNCs), composed of a photoactive TiO₂ nanorod joined with a superparamagnetic γ-Fe₂O₃ spherical domain, were embedded in polyethylene glycol modified phospholipid micelle and successfully bioconjugated to a suitably designed peptide containing an RGD motif. BNCs represent a relevant multifunctional nanomaterial, owing to the coexistence of two distinct domains in one particle, characterized by high photoactivity and magnetic properties, that is particularly suited for use as a phototherapy and hyperthermia agent as well as a magnetic probe in biological imaging. We selected the RGD motif in order to target integrin expressed on activated endothelial cells and several types of cancer cells. The prepared RGD-peptide/BNC conjugates, comprehensively monitored by using complementary optical and structural techniques, demonstrated a high stability and uniform dispersibility in biological media. The cytotoxicity of the RGD-peptide/BNC conjugates was studied in vitro. The cellular uptake of RGD-peptide conjugates in the cells, assessed by means of two distinct approaches, namely confocal microscopy analysis and emission spectroscopy determination in cell lysates, displayed selectivity of the RGD-peptide-BNC conjugate for the αvβ3 integrin. These RGD-peptide-BNC conjugates have a high potential for theranostic treatment of cancer.

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