Quantitative pharmacophore models with inductive logic programming

Three-dimensional models, or pharmacophores, describing Euclidean constraints on the location on small molecules of functional groups (like hydrophobic groups, hydrogen acceptors and donors, etc.), are often used in drug design to describe the medicinal activity of potential drugs (or ‘ligands’). This medicinal activity is produced by interaction of the functional groups on the ligand with a binding site on a target protein. In identifying structure-activity relations of this kind there are three principal issues: (1) It is often difficult to “align” the ligands in order to identify common structural properties that may be responsible for activity; (2) Ligands in solution can adopt different shapes (or `conformations’) arising from torsional rotations about bonds. The 3-D molecular substructure is typically sought on one or more low-energy conformers; and (3) Pharmacophore models must, ideally, predict medicinal activity on some quantitative scale. It has been shown that the logical representation adopted by Inductive Logic Programming (ILP) naturally resolves many of the difficulties associated with the alignment and multi-conformation issues. However, the predictions of models constructed by ILP have hitherto only been nominal, predicting medicinal activity to be present or absent. In this paper, we investigate the construction of two kinds of quantitative pharmacophoric models with ILP: (a) Models that predict the probability that a ligand is “active”; and (b) Models that predict the actual medicinal activity of a ligand. Quantitative predictions are obtained by the utilising the following statistical procedures as background knowledge: logistic regression and naive Bayes, for probability prediction; linear and kernel regression, for activity prediction. The multi-conformation issue and, more generally, the relational representation used by ILP results in some special difficulties in the use of any statistical procedure. We present the principal issues and some solutions. Specifically, using data on the inhibition of the protease Thermolysin, we demonstrate that it is possible for an ILP program to construct good quantitative structure-activity models. We also comment on the relationship of this work to other recent developments in statistical relational learning. Editors: Tamás Horváth and Akihiro Yamamoto     

A shell for cooperating expert systems

Abstract: This paper describes a shell for cooperating expert systems that has been developed at the University of Porto. The main goal of this shell is two-fold: to generate a community of cooperative knowledge-based systems and to develop several special reasoning techniques which can be used under a distributed and cooperative paradigm. UPShell is able to convert a set of generated intelligent systems (ISs) into a community of cooperative ISs. In this first version it is already possible to generate different intelligent systems which are able to run 'simultaneously' as separate Unix processes and, using a message-passing mechanism, to communicate among themselves. They can be set to pursue an overall goal in a cooperative way. Moreover, several tasks can be given to each IS to be solved simultaneously, and the IS can switch from task to task according to dynamic priorities reflecting the urgency attached to the specific sub-tasks that emerge. The shell described here may also be used to test, within a distributed environment, some time-bounded reasoning techniques that are presently being developed. The paper has three main parts: a general overview of the UPShell (Section 1); a tutorial explaining, by means of examples, how to use the package (Section 2); and, finally, some considerations on the reasoning techniques used and future improvements (Sections 3–5).     

Wetting behaviour of silicon nitride ceramics by Ti–Cu alloys

The wetting of Ti–Cu alloys on Si₃N₄ was analyzed by the sessile drop method, using an imaging system with a CCD camera during the heating under argon flow. The contact angle was measured as a function of temperature and time. The samples were cut transversally and characterized by scanning electron microscopy and energy dispersive spectrometry (SEM/EDS). Wettability of the Ti–Cu alloy on Si₃N₄ is influenced by the reaction between the Ti and the ceramic. The TC1 and TC2 alloys presented low final contact angle values around 2° and 26°, respectively, indicating good wetting on Si₃N₄.     

Organic matter release in low temperature thermal treatment of biological sludge for reduction of excess sludge production.

Thermal treatment applied in association with a biological system allows for a significant reduction in excess sludge production (approximately 50%). In general, heat treatment is described as a sludge disintegration technique. This paper offers a thorough study on the impact of heat treatment, at temperatures below 100 degrees C, on the solubilisation of the sludge COD and its biodegradability. Discontinuous heating experiments were performed on activated and digested sludge. At all temperatures tested the released COD for digested sludge was systematically higher than that for activated sludge (15 and 40%, respectively, at 95 degrees C for 40 min of contact time). For the first 30 min, a 1st order kinetic, with respect to the residual COD, was systematically found. In the range of 40-95 degrees C, digested sludge had a lower activation energy than activated sludge (26 kcal/mol compared to 70-160 kcal/mol). COD solubilisation is thus more positively influenced by temperature in the case of activated sludge. This may be due to the significant difference in the ratio of protein/carbohydrate in digested and activated sludge (1-5 and 0.2-0.7, respectively). The increase in the COD/TKN ratio in the solubilised fraction after thermal treatment of activated sludge suggests a preferential solubilisation of proteins over carbohydrates. Respirometric tests performed on the solubilised COD showed that whatever the sludge origin, only 40-50% of released COD is biodegradable at a conventional hydraulic retention time (i.e., 24 h). Hence, heat treatment would act more through organic matter solubilisation rather than by a biodegradability increase.     

Moral value transfer from regulatory fit: What feels right is right and what feels wrong is wrong.

People experience regulatory fit (E. T. Higgins, 2000) when the strategic manner of their goal pursuit suits their regulatory orientation, and this regulatory fit feels right. Fit violation feels wrong. Four studies tested the proposal that experiences of fit can transfer to moral evaluations. The authors examined transfer of feeling wrong from fit violation by having participants in a promotion or prevention focus recall transgressions of commission or omission (Studies 1 and 2). Both studies found that when the type of transgression was a fit violation, participants expressed more guilt. Studies 3 and 4 examined transfer of feeling right from regulatory fit. Participants evaluated conflict resolutions (Study 3) and public policies (Study 4) as more right when the means pursued had fit. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Synthesis,characterization and properties of functionalized styrene–maleimide copolymers

New functionalized styrene–maleimide copolymers were prepared by free radical copolymerization of styrene (St) and N‐4‐carboxybutylmaleimide (NBMI) in chloroform, using 2,2′‐azobisisobutyronitrile (AIBN) as initiator. Monomer and copolymer characterization was carried out by ¹H‐ and ¹³C‐NMR. Copolymer composition was determined by elemental analysis and Fourier‐transform infrared (FTIR) spectroscopy. The glass transition temperature (from DSC) and the thermogravimetric analysis (TGA) of the copolymers were consistent with the thermal behavior and stability observed for alternating St–maleimide copolymers. St–NBMI copolymers crosslinked with divinylbenzene (DVB) were also synthesized and their cation exchange properties evaluated in order to assess the capacity of the new copolymers to bind metallic ions. Copyright © 2005 Society of Chemical Industry     

Influence de la concentration des agents tensio-actifs sur la vitesse terminale d'ascension des gouttes

The rising of droplets in water contaminated with two surfactants, sodium salt dodecylhydrogenosulphate (L.S.S.) and Teepol, in the range 200 < N_Rep < 1000 was studied. The dispersed phases used were cyclohexane, benzene, toluene, and n-heptane. Experiences were conducted at a constant temperature of 30°C. It was shown that the presence of the two agents decreases the final rising rate of the droplets with an increasing surfactant concentration and droplet diameter. For the same interfacial tension values, this phenomenon is enhanced in the case of Teepol. An equation is proposed for the computation of the critical droplet diameter as well as the droplet rising rate. These equations demonstrate the effect of the chemical nature of the surface agent and reproduce the experimental results with variations less than 10%.     

Superconductivity in a new quaternary phase with HgSm0.5In0.5Pb2 composition

This work reports a systematic study on the structural and superconducting properties in the Hg-Sm-In-Pb system. It is investigated how In and Sm dopings influence the superconducting properties of the HgPb₂ phase which was recently reported. Results for the HgSm_1 − xPb₂ system show that Sm atoms substitute Hg vacancies in the tetragonal phase which do not affect the onset critical temperature of the HgPb₂ compound. Simultaneous Sm and In doping effects on the properties of the HgPb₂ phase are also studied. Experimental and simulations of X-ray powder diffractograms suggest that the HgSm_1 − xIn_xPb₂ system (0.2 ≤ x ≤ 0.7) has a pseudo-cubic structure with lattice parameters near 4.88 Å. Superconducting properties measurements show that this system has an optimum doping at x ∼ 0.5 with the onset critical temperature close to 6.9 K. This is the highest superconducting critical temperature for the AuCu prototype so far reported.     

Min-Max MPC based on a computationally efficient upper bound of the worst case cost

Min-Max MPC (MMMPC) controllers [P.J. Campo, M. Morari, Robust model predictive control, in: Proc. American Control Conference, June 10–12, 1987, pp. 1021–1026] suffer from a great computational burden which limits their applicability in the industry. Sometimes upper bounds of the worst possible case of a performance index have been used to reduce the computational burden. This paper proposes a computationally efficient MMMPC control strategy in which the worst case cost is approximated by an upper bound based on a diagonalization scheme. The upper bound can be computed with O(n³) operations and using only simple matrix operations. This implies that the algorithm can be coded easily even in non-mathematical oriented programming languages such as those found in industrial embedded control hardware. A simulation example is given in the paper.