Conceptual information processing: A robust approach to KBS-DBMS integration

Integrating the respective functionality and architectural features of knowledge base and data base management systems is a topic of considerable interest. Several aspects of this topic and associated issues are addressed. The significance of integration and the problems associated with accomplishing that integration are discussed. The shortcomings of current approaches to integration and the need to fuse the capabilities of both knowledge base and data base management systems motivates the investigation of information processing paradigms. One such paradigm is concept based processing, i.e., processing based on concepts and conceptual relations. An approach to robust knowledge and data base system integration is discussed by addressing progress made in the development of an experimental model for conceptual information processing

A comparative study of Gaussian Graphical Model approaches for genomic data

The inference of networks of dependencies by Gaussian Graphical models on high-throughput data is an open issue in modern molecular biology. In this paper we provide a comparative study of three methods to obtain small sample and high dimension estimates of partial correlation coefficients: the Moore-Penrose pseudoinverse (PINV), residual correlation (RCM) and covariance-regularized method $(\ell_{2C})$. We first compare them on simulated datasets and we find that PINV is less stable in terms of AUC performance when the number of variables changes. The two regularized methods have comparable performances but $\ell_{2C}$ is much faster than RCM. Finally, we present the results of an application of $\ell_{2C}$ for the inference of a gene network for isoprenoid biosynthesis pathways in Arabidopsis thaliana.Comment: 7 pages, 1 figure, RevTex4, version to appear in the proceedings of 1st International Workshop on Pattern Recognition, Proteomics, Structural Biology and Bioinformatics: PR PS BB 2011, Ravenna, Italy, 13 September 201

Continuous global optimization for protein structure analysis

Optimization methods are a powerful tool in protein structure analysis. In this paper we show that they can be profitably used to solve relevant problems in drug design such as the comparison and recognition of protein binding sites and the protein-peptide docking. Binding sites recognition is generally based on geometry often combined with physico-chemical properties of the site whereas the search for correct protein-peptide docking is often based on the minimization of an interaction energy model. We show that continuous global optimization methods can be used to solve the above problems and show some computational results

Improving P300 Speller performance by means of optimization and machine learning

Brain-Computer Interfaces (BCIs) are systems allowing people to interact with the environment bypassing the natural neuromuscular and hormonal outputs of the peripheral nervous system (PNS). These interfaces record a user’s brain activity and translate it into control commands for external devices, thus providing the PNS with additional artificial outputs. In this framework, the BCIs based on the P300 Event-Related Potentials (ERP), which represent the electrical responses recorded from the brain after specific events or stimuli, have proven to be particularly successful and robust. The presence or the absence of a P300 evoked potential within the EEG features is determined through a classification algorithm. Linear classifiers such as stepwise linear discriminant analysis and support vector machine (SVM) are the most used discriminant algorithms for ERPs’ classification. Due to the low signal-to-noise ratio of the EEG signals, multiple stimulation sequences (a.k.a. iterations) are carried out and then averaged before the signals being classified. However, while augmenting the number of iterations improves the Signal-to-Noise Ratio, it also slows down the process. In the early studies, the number of iterations was fixed (no stopping environment), but recently several early stopping strategies have been proposed in the literature to dynamically interrupt the stimulation sequence when a certain criterion is met in order to enhance the communication rate. In this work, we explore how to improve the classification performances in P300 based BCIs by combining optimization and machine learning. First, we propose a new decision function that aims at improving classification performances in terms of accuracy and Information Transfer Rate both in a no stopping and early stopping environment. Then, we propose a new SVM training problem that aims to facilitate the target-detection process. Our approach proves to be effective on several publicly available datasets

Assessing chronological age of unaccompanied minors in Southern Italy

The increasing volume of, and subsequent complexities resulting from, migratory flows in the broader context of globalization has led to a range of problems, not only the protection of human rights and disease control but also the identification of those with the right to apply for refugee status and the age assessment of unaccompanied minors. Italy is a magnet for immigration from other countries bordering the Mediterranean Sea because the Italian coasts are within easy reach. In Italy, as in other western countries, unaccompanied asylum seekers deemed to be younger than 18 years face a very different path through the immigration system from that experienced by adults. Generally, adults are subject to immediate deportation or detention in jail. Minors are processed through the juvenile system, where detection is not mandatory; they will often have access to educational programs and may be granted a residency permit. The Section of Legal Medicine of the University of Bari was approached by immigration police authorities and judges to explore the possibility of examining unaccompanied asylum seekers, who claim do be younger than 18 years, to assess their age. A group of forensic pathologists and odontologists performed this evaluation relying on the skeletal maturation as seen on radiographs of the wrist and the pelvis for iliac crests and on an orthopantomograph, together with background information and clinical examination of each individual. Case studies are presented. This article does not attempt to give a definitive account of the different scientific methods for the assessment of age. It is important to understand some of the methods that may be used in an attempt to assess developmental maturity and from which it may be possible to ''read off'' an approximate chronological age. © 2011 by Lippincott Williams & Wilkins

The new σ-IASI code for all sky radiative transfer calculations in the spectral range 10 to 2760 cm-1: σ-IASI/F2N

The paper describes a recently developed forward model (σ-IASI/F2N) to produce spectral radiances from the far to near-infrared spectrum (100 to 2760 cm-1). The model is a pseudo-monochromatic radiative transfer tool that exploits lookup tables to compute the optical depths of atmospheric gas and clouds. Multiple scattering effects are accurately included in both the Far IR and Thermal IR by using a scaling method for cloud and aerosol radiative properties parameterized in terms of their effective radius, which allows them to be handled adopting the same formalism used in the clear sky. In this paper we apply a novel approach to a classical scaling method in the thermal IR relying on our improved parametrization of backscattering parameter over that used by Chou (Martinazzo et al., 2021), while in the Far IR a corrective term is introduced. The code is written in Fortran and runs on Unix-based (Linux and macOS) or MS Windows operating systems. σ-IASI/F2N can be used to develop custom versions of fast-forward modules for satellite instruments working in the infrared spectral range, such as the Far-Infrared Outgoing Radiation Understanding and Monitoring (FORUM) and the Polar Radiant Energy in the Far-InfraRed Experiment (PREFIRE) missions. We discuss the σ-IASI/F2N performance in simulating a set of ECMWF analyses at the global scale. For this purpose, we compare observations from the Infrared Atmospheric Sounding Interferometer (IASI) flying on MetOp B, and C. Results show that σ-IASI/F2N can easily ingest ECMWF analyses data and accurately reproduce cloud patterns. We also show that the difference between σ-IASI/F2N simulations and corresponding IASI observations is below 1 K in the 8–12 um window region, which is mainly affected by the water vapor continuum absorption and weak lines, while for night-time clear sky, the differences are below 0.3 K. again within the same window region

Innovative approach for a classic target: fragment screening on trypanothione reductase reveals new opportunities for drug design

Trypanothione reductase (TR) is a key factor in the redox homeostasis of trypanosomatid parasites, critical for survival in the hostile oxidative environment generated by the host to fight infection. TR is considered an attractive target for the development of new trypanocidal agents as it is essential for parasite survival but has no close homolog in humans. However, the high efficiency and turnover of TR challenging targets since only potent inhibitors, with nanomolar IC50, can significantly affect parasite redox state and viability. To aid the design of effective compounds targeting TR, we performed a fragment-based crystal screening at the Diamond Light Source XChem facility using a library optimized for follow-up synthesis steps. The experiment, allowing for testing over 300 compounds, resulted in the identification of 12 new ligands binding five different sites. Interestingly, the screening revealed the existence of an allosteric pocket close to the NADPH binding site, named the "doorstop pocket" since ligands binding at this site interfere with TR activity by hampering the "opening movement" needed to allow cofactor binding. The second remarkable site, known as the Z-site, identified by the screening, is located within the large trypanothione cavity but corresponds to a region not yet exploited for inhibition. The fragments binding to this site are close to each other and have some remarkable features making them ideal for follow-up optimization as a piperazine moiety in three out of five fragments

Swelling-induced structural changes and microparticle uptake of gelatin gels probed by NMR and CLSM

Gelatin gels are increasingly involved in many industrial applications due to several advantages including cost efficiency and biocompatibility. Generally, their production requires the use of aqueous solvents, which cause significant swelling, due to the ability of solvent molecules to penetrate through the gel microstructure and increase its volume. Since swelling mechanisms and their effect on the gel structure are not fully understood, further investigations are required. In this work, we combine macroscopic measurements of the swelling ratio (SR) with Nuclear Magnetic Resonance (NMR) and Confocal Laser Scanning Microscopy (CLSM) to investigate changes in the gelatin structure as a function of both polymer concentration and swelling time. SR values increase as a function of time until a maximum is reached and then show a slight drop for all the gelatin concentrations after 24 h swelling time, probably due to a network relaxation process. NMR allows determination of mass transport and molecular dynamics of water inside the gelatin pores, while CLSM is used to visualize the penetration of tracers (polystyrene microbeads) with a diameter much larger than the gel pores. Structural parameters, such as average pore size and tortuosity, are estimated. In particular, the pore size decreases for higher polymer concentration and increases during swelling, until reaching a maximum, and then dropping at longer times. The penetration of tracers provides evidence of the heterogeneity of the gel structure and shows that single microcarriers can be loaded in gelatin gels upon swelling.Wolfson College, Cambridg