Artificial Intelligence Technologies for COVID-19 De Novo Drug Design

The recent covid crisis has provided important lessons for academia and industry regarding digital reorganization. Among the fascinating lessons from these times is the huge potential of data analytics and artificial intelligence. The crisis exponentially accelerated the adoption of analytics and artificial intelligence, and this momentum is predicted to continue into the 2020s and beyond. Drug development is a costly and time-consuming business, and only a minority of approved drugs generate returns exceeding the research and development costs. As a result, there is a huge drive to make drug discovery cheaper and faster. With modern algorithms and hardware, it is not too surprising that the new technologies of artificial intelligence and other computational simulation tools can help drug developers. In only two years of covid research, many novel molecules have been designed/identified using artificial intelligence methods with astonishing results in terms of time and effectiveness. This paper reviews the most significant research on artificial intelligence in de novo drug design for COVID-19 pharmaceutical research.     

On the Spatial Distribution of Fingerprint Singularities

Fingerprint singularities play an important role in several fingerprint recognition and classification systems. Although some general relationships and constraints about the location of singularities in the different fingerprint classes are well known, to the best of our knowledge no statistical models have been developed until now. This paper studies the spatial distributions of singularity locations in nature and derives, from a representative dataset of labelled samples, the probability density functions of the four main fingerprint classes. The results obtained can be directly exploited to improve the accuracy of many techniques relying on the position of singularities, as confirmed by the results of two experiments on fingerprint classification and synthesis.     

Mitigation of Liquefaction-Induced Lateral Deformation in a Sloping Stratum: Three-dimensional Numerical Simulation

Finite-element (FE) simulations are increasingly providing a versatile environment for conducting lateral ground deformation studies. In this environment, mitigation strategies may be assessed in order to achieve economical and effective solutions. On the basis of a systematic parametric study, three-dimensional FE simulations are conducted to evaluate mitigation by the stone column (SC) and the pile-pinning approaches. Mildly sloping saturated cohesionless strata are investigated under the action of an applied earthquake excitation. For that purpose, the open-source computational platform OpenSees is employed, through a robust user interface that simplifies the effort-intensive pre- and postprocessing phases. The extent of deployed remediation and effect of the installed SC permeability are investigated. The influence of mesh resolution is also addressed. Generally, SC remediation was found to be effective in reducing the sand stratum lateral deformation. For a similar stratum with permeability in the silt range, SC remediation was highly ineffective. In contrast, pile pinning appeared to be equally effective for the sand and silt strata permeability scenarios. Overall, the conducted study highlights the potential of computations for providing insights toward the process of defining a reliable remediation solution.     

Reoptimization of the Shortest Common Superstring Problem

A reoptimization problem describes the following scenario: given an instance of an optimization problem together with an optimal solution for it, we want to find a good solution for a locally modified instance.     

Use of microfibrillated cellulose and dendritic copper for the elaboration of conductive films from water- and ethanol-based dispersions

In this study, microfibrillated cellulose (MFC) and dendritic copper were used as binder and conductive phase for the elaboration of self-standing conductive films and coatings. A filtration technique was used to prepare MFC/Cu films from particle dispersions in water and ethanol. In aqueous slurries copper oxidized and an additional corona treatment or the use of zinc particles as sacrificial anode were necessary to obtain films with conductivities ranging from 70 to 2500 S m^?1, respectively. In ethanol-based MFC/Cu slurries, copper was subjected to limited oxidation. However, the low packing density of conductive particles (below the percolation threshold) led to resistive films which, after densification by calendering, displayed extremely high conductivities, up to 70000 S m^?1. Aqueous MFC/Cu slurries were successfully used for the deposition of conductive coatings on copy paper by Mayer rod coating and screen printing, which were subsequently treated by corona discharge and calendering. The obtained coatings displayed intermediate conductivity (i.e. 95 and 570 S m^?1 for rod coating and screen printing, respectively), which can be further increased using zinc particles or ethanol-based formulations.     

Integration of acoustical information in the perception of impacted sound sources: The role of information accuracy and exploitability.

Sound sources are perceived by integrating information from multiple acoustical features. The factors influencing the integration of information are largely unknown. We measured how the perceptual weighting of different features varies with the accuracy of information and with a listener’s ability to exploit it. Participants judged the hardness of two objects whose interaction generates an impact sound: a hammer and a sounding object. In a first discrimination experiment, trained listeners focused on the most accurate information, although with greater difficulty when perceiving the hammer. We inferred a limited exploitability for the most accurate hammer-hardness information. In a second rating experiment, listeners focused on the most accurate information only when estimating sounding-object hardness. In a third rating experiment, we synthesized sounds by independently manipulating source properties that covaried in Experiments 1 and 2: sounding-object hardness and impact properties. Sounding-object hardness perception relied on the most accurate acoustical information, whereas impact-properties influenced more strongly hammer hardness perception. Overall, perceptual weight increased with the accuracy of acoustical information, although information that was not easily exploited was perceptually secondary, even if accurate. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Rawseeds ground truth collection systems for indoor self-localization and mapping

A trustable and accurate ground truth is a key requirement for benchmarking self-localization and mapping algorithms; on the other hand, collection of ground truth is a complex and daunting task, and its validation is a challenging issue. In this paper we propose two techniques for indoor ground truth collection, developed in the framework of the European project Rawseeds, which are mutually independent and also independent on the sensors onboard the robot. These techniques are based, respectively, on a network of fixed cameras, and on a network of fixed laser scanners. We show how these systems are implemented and deployed, and, most importantly, we evaluate their performance; moreover, we investigate the possible fusion of their outputs.     

Assessment of river Po sediment quality by micropollutant analysis

Trace metals, PCB congeners and DDT homologues were determined in composite sediment samples collected from 10 representative sites along the river Po in two separate seasons. The aim was to identify the most anthropogenically impacted areas for future monitoring programmes and to aid development of Italian sediment quality criteria. The surface samples were collected during low flow conditions. Trace metal concentrations were assayed by electrothermal (Cd, Co, Cr, Cu, Ni, Pb), flame (Fe, Mn, Zn) or hydride generation (As) atomic absorption spectrometry after microwave assisted acid digestion. Hg was determined on solid samples by automated analyser. Organic microcontaminants were determined by gas-chromatography with 63Ni electron capture detector after Soxhlet extraction. Concentrations of trace metals, total PCB and DDT homologues showed two distinct peaks at the sites immediately downstream of Turin and Milan, respectively, and in each case decreased progressively further downstream. Principal component analysis identified three major factors (from a multi-dimensional space of 35 variables) which explained 85-90% of the total observed variance. The first and second factors corresponded to anthropogenic inputs and geological factors on sediment quality; the third included seasonal processes of minor importance. Sediment quality assessment identified Cd, Cu, Hg, Pb, Zn and organic microcontaminants as posing the most serious threats to river sediment quality. A reference site within the Po basin provided useful background values. Moderate pollution by organochlorine compounds was ascribed both to local sources and to atmospheric deposition.