A classification and regression technique to handle heterogeneous and imperfect information

Imperfect information inevitably appears in real situations for a variety of reasons. Although efforts have been made to incorporate imperfect data into learning and inference methods, there are many limitations as to the type of data, uncertainty and imprecision that can be handled. In this paper, we propose a classification and regression technique to handle imperfect information. We incorporate the handling of imperfect information into both the learning phase, by building the model that represents the situation under examination, and the inference phase, by using such a model. The model obtained is global and is described by a Gaussian mixture. To show the efficiency of the proposed technique, we perform a comparative study with a broad baseline of techniques available in literature tested with several data sets.     

Erratum to: Reasoning with infinite stable models [Artificial Intelligence 156 (1) (2004) 75-111]

Theorem 16 in [Piero A. Bonatti, Reasoning with infinite stable models, Artificial Intelligence 156 (1) (2004) 75-111] states that ground skeptical and credulous inferences under the stable model semantics are decidable when the given normal logic program is finitary. Giovanni Criscuolo and Nicola Leone independently observed in personal communications that the proof of this theorem relies on an unproved assumption that—at the best of our current knowledge—might turn out to be false. In this note we correct Theorem 16 by adding the set of odd-cyclic atoms to the inputs of the computation, and argue that this change has no impact on the current applications of the theory of finitary programs.     

Apoptotic DNA fragmentation can be revealed in situ: An ultrastructural approach

A common pattern of apoptotic death is DNA cleavage, initially producing large fragments (50 kbp), followed by the production of nucleosomic/oligonucleosomic fragments. Nevertheless, apoptosis without DNA fragmentation, at least of the nucleosomic type, has been reported. To investigate the spatial relationship between DNA cleavage and chromatin condensation, we applied the TUNEL technique to the ultrastructural analysis of apoptotic cells. A modified method, utilizing a gold‐conjugated antidigoxigenin antibody, was carried out on U937 versus Molt‐4 cells, both exposed to UVB radiation or staurosporine treatment. Gold particle density in the different domains of apoptotic cells was evaluated by a four‐way ANOVA test. Gold labelling was more strongly localised in condensed chromatin than in the diffuse chromatin. U937 cells, which evidenced in vitro oligonucleosomic fragmentation after both UVB and staurosporine treatments, revealed a significantly higher gold particle density, when compared with Molt‐4, which did not show, on the other hand, oligonucleosomic cleavage even in the presence of ≤50 kbp cleavage. Thus, a correlation between DNA fragment sizes and gold particle density appears. TUNEL applied to electron microscopy is an effective approach to study the relationship between apoptotic chromatin condensation and DNA cleavage. Both these events indeed appear in the apoptotic nucleus, but their reciprocal correlation is still greatly unknown. Microsc. Res. Tech. 2009. © 2009 Wiley‐Liss, Inc.     

Formation versus Hydrolysis of the Peptide Bond from a Quantum-mechanical Viewpoint: The Role of Mineral Surfaces and Implications for the Origin of Life

The condensation (polymerization by water elimination) of molecular building blocks to yield the first active biopolymers (e.g. of amino acids to form peptides) during primitive Earth is an intriguing question that nowadays still remains open since these processes are thermodynamically disfavoured in highly dilute water solutions. In the present contribution, formation and hydrolysis of glycine oligopeptides occurring on a cluster model of sanidine feldspar (001) surface have been simulated by quantum mechanical methods. Results indicate that the catalytic interplay between Lewis and Brønsted sites both present at the sanidine surface, in cooperation with the London forces acting between the biomolecules and the inorganic surface, plays a crucial role to: i) favour the condensation of glycine to yield oligopeptides as reaction products; ii) inhibit the hydrolysis of the newly formed oligopeptides. Both facts suggest that mineral surfaces may have helped in catalyzing, stabilizing and protecting from hydration the oligopeptides formed in the prebiotic era.     

Time-constrained reasoning under uncertainty

Dynamic classification problems present unique challenges beyond those of more traditionalstatic knowledge-based systems. Uncertain and incomplete input data, unpredictable event sequences, and critical time and resource constraints require new approaches and techniques for automated reasoning. Our work toward addressing these complex requirements has concentrated on developing an integrated software architecture which supports the knowledge engineering process from development to deployment. The approach we are using to deal with real-time issues in the deployment environment involves the use of a fast knowledge representation scheme, efficient forward and backward chaining mechanisms, and a meta-controller which handles asynchronous inputs, prioritized task requests, and hard performance deadlines.     

The Release Rate of Indomethacin from Solid Dispersions with Eudragite

The coprecipitates were prepared by a solvent technique using Eudragit E as carrier and indomethacin as a model drug.

X-Ray diffractometry, differential scanning calorimetry (DSC) and wettability tests were employed to investigate the physical state of the studied formulations. Up to 50% of indomethacin can be dispersed in an amorphous state in Eudragit E.

The influence of the pH on the in vitro release of solid dispersions has been evaluated. Because of the good solubility of Eudragit E at pH 1.2 a fast dissolution rate of the drug was observed while a marked delay was noticed at pH 7.5 where the polymer is only permeable to water. At pH 5.8 the kinetics of drug release can be modulated by the drug/polymer ratio. The dissolution rate of the drug can be increased by decreasing its amount in the coevaporate.     

White Electroluminescence by Supramolecular Control of Energy Transfer in Blends of Organic‐Soluble Encapsulated Polyfluorenes

Here, it is demonstrated that energy transfer in a blend of semiconducting polymers can be strongly reduced by non‐covalent encapsulation of one constituent, ensured by threading of the conjugated strands into functionalized cyclodextrins. Such macrocycles control the minimum intermolecular distance of chromophores with similar alignment, at the nanoscale, and therefore the relevant energy transfer rates, thus enabling fabrication of white‐light‐emitting diodes (CIE coordinates: x = 0.282, y = 0.336). In particular, white electroluminescence in a binary blend of a blue‐emitting, organic‐soluble rotaxane based on a polyfluorene derivative and the green‐emitting poly(9,9‐dioctylfluorene‐alt‐benzothiadiazole ( F8BT ) is achieved. Morphological and structural analyses by atomic force microscopy, fluorescence mapping, µ‐Raman, and fluorescence lifetime microscopy are used to complement optical and electroluminescence characterization, and to enable a deeper insight into the properties of the novel blend.     

CFD simulations of segregating fluidized bidisperse mixtures of particles differing in size

In this work, we use a multifluid model to investigate numerically the dynamics of segregating fluidized bidisperse mixtures. The model uses the default multifluid equations of commercial computational fluid dynamics (CFD) codes, except for the fluid–particle drag force closure, which Mazzei and Lettieri [1] recently developed and extended to polydisperse systems. The study also comprises some preliminary simulations of collapsing monodisperse beds, focusing on the role of the plastic solid stress. This work tests whether the model is able to correctly predict not only the axial segregation profiles through the bed, but also the minimum fluid velocities at which a) the mixture, being no longer fixed, starts segregating and transient fluidization takes place, and b) the mixture becomes steadily fluidized and fully mixed. To validate the model predictions, we use the experimental findings of Marzocchella et al. [2]. The plastic stress results to play an important role, rendering the simulations more stable and allowing for larger time steps. The model well predicts the stationary axial segregation profiles, and for short computational times estimates correctly the onset of transient fluidization; for longer computational times, however, the system evolves towards a new steady state where, even if the powder is at maximum packing, it partly segregates. The model overestimates the velocity required to fully mix the suspension, probably because the simulated bubbling is not as vigorous as it is experimentally.