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When granular assemblies are subject to external loads or displacements, particles interact with each other through contact and may exhibit translations and rotations. From a micromechanical perspective, particle rotations are an essential mechanism influencing the macroscopic behavior of granular materials. In this study, biaxial shearing tests were conducted on assemblies of dual-sized circular particles at different confining pressures. A high-precision image analysis method was developed to extract the particle-level motion of all the particles, including the rotational behavior. Experimental results showed that most of the particles exhibited rotations. Particles within the shear band exhibited more significant rotations and were characterized by low connectivity (number of contacts per particle). In contrast, the particles outside the shear band rotated lesser, only in the beginning stage of shearing. Every rotation in either direction is accompanied by an opposite rotation of almost the same magnitude in the neighboring region, and rotation clusters have been observed. Rotations in both directions are normally distributed within the assembly, and the average particle rotation is zero. The average rotations in both directions evolve symmetrically with major principal strain. Generally, the rotation rate (degrees per incremental strain) is observed to be maximum at the start of the shearing, and gradually it becomes constant toward the end of the shearing. The average value of the absolute cumulative rotation observed for whole particles is 18.6° at the end of shearing, i.e., 20% deviatoric strain. Smaller size particles tend to exhibit 67% higher rotations than bigger particles. Confining pressures have no significant effect on the rotational behavior of circular particles.

Background Being able to efficiently call variants from the increasing amount of sequencing data daily produced from multiple viral strains is of the utmost importance, as demonstrated during the COVID-19 pandemic, in order to track the spread of the viral strains across the globe. Results We present MALVIRUS , an easy-to-install and easy-to-use application that assists users in multiple tasks required for the analysis of a viral population, such as the SARS-CoV-2. MALVIRUS allows to: (1) construct a variant catalog consisting in a set of variations (SNPs/indels) from the population sequences, (2) efficiently genotype and annotate variants of the catalog supported by a read sample, and (3) when the considered viral species is the SARS-CoV-2, assign the input sample to the most likely Pango lineages using the genotyped variations. Conclusions Tests on Illumina and Nanopore samples proved the efficiency and the effectiveness of MALVIRUS in analyzing SARS-CoV-2 strain samples with respect to publicly available data provided by NCBI and the more complete dataset provided by GISAID. A comparison with state-of-the-art tools showed that MALVIRUS is always more precise and often have a better recall.

Background While the reconstruction of transcripts from a sample of RNA-Seq data is a computationally expensive and complicated task, the detection of splicing events from RNA-Seq data and a gene annotation is computationally feasible. This latter task, which is adequate for many transcriptome analyses, is usually achieved by aligning the reads to a reference genome, followed by comparing the alignments with a gene annotation, often implicitly represented by a graph: the splicing graph . Results We present ASGAL (Alternative Splicing Graph ALigner): a tool for mapping RNA-Seq data to the splicing graph, with the specific goal of detecting novel splicing events, involving either annotated or unannotated splice sites. ASGAL takes as input the annotated transcripts of a gene and a RNA-Seq sample, and computes (1) the spliced alignments of each read in input, and (2) a list of novel events with respect to the gene annotation. Conclusions An experimental analysis shows that ASGAL allows to enrich the annotation with novel alternative splicing events even when genes in an experiment express at most one isoform. Compared with other tools which use the spliced alignment of reads against a reference genome for differential analysis, ASGAL better predicts events that use splice sites which are novel with respect to a splicing graph, showing a higher accuracy. To the best of our knowledge, ASGAL is the first tool that detects novel alternative splicing events by directly aligning reads to a splicing graph. Availability Source code, documentation, and data are available for download at http://asgal.algolab.eu .

Particle rolling is an essential microscopic mechanism that governs macroscopic behavior. This study conducts biaxial shearing tests on bi-dispersed circular discs at different confining pressures. A novel 2D image analysis technique is employed to measure the rolling of all the particles. It is observed that most of the particles exhibit significant rolling during shearing. Rollings are normally distributed in clockwise and counterclockwise directions, and the net rolling of the granular assembly is almost zero. Generally, the rolling of a particle is accompanied by its neighboring particle’s opposite rolling in a similar magnitude. In some cases, a group of particles is observed to exhibit rolling in the same direction, accompanied by another opposite rolling group in the neighboring regions. Particles inside the shear band tend to show significant rolling. The rolling rate is prominent at the beginning of the shearing and gradually decreases towards the end. Small particles exhibit significantly higher rotations, while larger particles are relatively resistant to rolling. Small particles work as ball bearings between two big particles, reducing the shear strength of the granular materials. The experimental data obtained in this study can be used to perform detailed validation of numerical models to simulate realistic granular behavior such as DEM.

Roundness/angularity is a vital shape descriptor that significantly impacts the mechanical response of granular materials and is closely associated with many geotechnical problems, such as liquefaction, slope stability, and bearing capacity. In this study, a series of biaxial shearing tests are conducted on dual-size aluminum circular and hexagonal rod material. A novel image analysis technique is used to estimate particle kinematics. A discrete element model (DEM) of the biaxial shearing test is then developed and validated by comparing it with the complete experimental data set. To systematically investigate the effect of roundness/angularity on granular behavior, the DEM model is then used to simulate eight non-elongated convex polygonal-shaped particles. Macroscopically, it is observed that angular assemblies exhibit higher shear strengths and volumetric deformations, i.e., dilations. Moreover, a unique relationship is observed between the critical state stress ratio and particle roundness. Microscopically, the roundness shows a considerable effect on rotational behavior such that the absolute mean cumulative rotation at the same strain level increases with roundness. A decrease in roundness results in relatively stronger interlocking, restricting an individual particle’s free rotation. Furthermore, the particles inside the shear band exhibit significantly higher rotations and are always associated with low coordination numbers. Generally, the geometrical shape of a particle is found to have a dominant effect on rotational behavior than coordination number.

Flexible protection systems represent the most widespread and economic passive mitigation structure for rockfall hazard. Originally adapted from anti-torpedo meshes from World War 2, they have seen very little evolution in the past decades. The practical design and dimensioning for a given site are still based on arbitrary decisions and the experience of the engineer assigned to the job, while a series of guidelines for manufacturers to assess and compare barrier performance has only been released in recent years (ETAG027). However, this is only useful for comparison purposes, as the effective barrier capacity on the field appears to depend on a variety of parameters, not accounted for in the guidelines. While research on the topic is advancing, with innovative monitoring systems and sophisticated numerical models being developed, the procedures used to characterise barrier behaviour and the underlying constitutive laws for the numerical models stay the same. In this thesis, a combination of numerical modelling and laboratory testing is used to improve the current practices in the numerical simulation of double-twisted hexagonal meshes. First, a series of Discrete Element simulations is carried out to investigate the influence of the assumptions typically adopted in literature. The numerical model is then used to quantify the energy dissipation occurring during impact tests, the load on the structural elements and the effect of repeated loading cycles. It was found that the geometry discretisation approaches typically adopted in the literature produces an overestimation of the mechanical stiffness of the system, while the effect of multiple overlapping types of mesh designs changes according to the loading conditions and rates (i.e. quasi-static vs dynamic). Depending on the impact position, the percentage of energy dissipated through different processes changes (i.e. friction, mesh plasticisation, etc.), while the direction of the loads acting on the structural elements changes even within the same test, inducing bending, compressive and tensile actions. Next, the wire-scale barrier behaviour is characterised through a combination of laboratory testing and Finite Element modelling, in order to provide a more robust dataset for successive studies. An image analysis procedure was developed, calibrated and used to quantify wire slippage, correcting the experimental data. Overall, a much stiffer material behaviour, characterised by both necking and shearing failure modes, was observed (compared to the limited literature data available). The numerical model was validated against the experimental results, compared to analytical and semi-analytical solutions and used to carry out hybrid tensile/bending tests, difficult to reproduce experimentally. The data was summarised in a novel contact model for DEM, developed within a macro-element framework. The model is based on isotropic plastic hardening, with a non-associated flow rule. Non-linear plasticity is integrated by means of the third-order Runge-Kutta method. The model has been implemented in the commercial code PFC3D by means of a dynamic link library, compiled in C++. In order to aid model validation, an experimental procedure was developed to obtain continuous mesh deformation through low-cost, consumer grade instruments. The procedure was validated against LIDAR data and then used to record mesh-scale barrier impact tests. Finally, the data has been compared to the numerical results obtained using the contact models presented here and those available in the literature. While the latter were also able to capture the peak displacement at the barrier centre, i.e. what is typically used for validation, only the novel model was produced a realistic deformation field. This characteristic is important because it affects the energy repartition during the impact, changing the direction and modulus of the forces acting on the structural elements.

A novel bond damage model is proposed to better replicate the behaviour of highly porous soft-rocks. The contact model employs an exponential damage law to describe the permanent deformation developing at the microscale. To i) reach a high porosity initial state, ii) reproduce complex contact configuration of irregular grains and iii) consider the physical existence of fractured bond fragments, a far-field interaction is introduced in this model, enabling non-overlapping particles to transmit forces. The model performance is validated by replicating the behaviour of Maastricht calcarenite. Finally, a 3D coupled DEM (Discrete Element Method) - FDM (Finite Difference Method) modelling is employed to simulate the penetration of a cone-end shaped pile in calcarenite. The good agreement between the experimental and numerical results suggests that the proposed model has the potential to reveal microscopic mechanism of soft-rock / structure interaction.

This study assesses the static stability of the artificial Sabereebi Cave Monastery southeast of Georgia's capital, Tbilisi. The cliff into which these Georgian-Orthodox caverns, chapels, and churches were carved consists of a five-layered sequence of weak sedimentary rock—all of which bear a considerable failure potential and, consequently, pose the challenge of preservation to geologists, engineers, and archaeologists. In the first part of this study, we present a strategy to process point cloud data from drone photogrammetry as well as from laser scanners acquired in- and outside the caves into high-resolution CAD objects that can be used for numerical modeling ranging from macro- to micro-scale. In the second part, we explore four distinct series of static elasto-plastic finite element stability models featuring different levels of detail, each of which focuses on specific geomechanical scenarios such as classic landsliding due to overburden, deformation of architectural features as a result of stress concentration, material response to weathering, and pillar failure due to vertical load. With this bipartite approach, the study serves as a comprehensive 3D stability assessment of the Sabereebi Cave Monastery on the one hand; on the other hand, the established procedure should serve as a pilot scheme, which could be adapted to different sites in the future combining non-invasive and relatively cost-efficient assessment methods, data processing and hazard estimation.HighlightsOne single high-resolution 3D FEM model allowing for failure zone identification on macro- to micro-scaleStrategy to process point cloud data from drone photogrammetry and laser scanners into composite FEM-suitable CAD objectsStrategy application to a real-life geoarchaeological case studyDemonstration of versatile FEM model usage for different geotechnical questionsFailure potential estimation across an underground compound consisting of seven caves and sub-caves

Abstract The amount of genetic variation discovered and characterized in human populations is huge, and is growing rapidly with the widespread availability of modern sequencing technologies. Such a great deal of variation data, that accounts for human diversity, leads to various challenging computational tasks, including variant calling and genotyping of newly sequenced individuals. The standard pipelines for addressing these problems include read mapping, which is a computationally expensive procedure. A few mapping-free tools were proposed in recent years to speed up the genotyping process. While such tools have highly efficient run-times, they focus on isolated, bi-allelic SNPs, providing limited support for multi-allelic SNPs, indels, and genomic regions with high variant density. To address these issues, we introduce MALVA, a fast and lightweight mapping-free method to genotype an individual directly from a sample of reads. MALVA is the first mapping-free tool that is able to genotype multi-allelic SNPs and indels, even in high density genomic regions, and to effectively handle a huge number of variants such as those provided by the 1000 Genome Project. An experimental evaluation on whole-genome data shows that MALVA requires one order of magnitude less time to genotype a donor than alignment-based pipelines, providing similar accuracy. Remarkably, on indels, MALVA provides even better results than the most widely adopted variant discovery tools. Footnotes * {giulia.bernardini{at}unimib.it, paola.bonizzoni{at}unimib.it, marco.previtali{at}unimib.it} l.denti{at}campus.unimib.it alexander.schoenhuth{at}cwi.nl

Indexing very large collections of strings, such as those produced by the widespread next generation sequencing technologies, heavily relies on multistring generalization of the Burrows-Wheeler Transform (BWT): large requirements of in-memory approaches have stimulated recent developments on external memory algorithms. The related problem of computing the Longest Common Prefix (LCP) array of a set of strings is instrumental to compute the suffix-prefix overlaps among strings, which is an essential step for many genome assembly algorithms. In a previous paper, we presented an in-memory divide-and-conquer method for building the BWT and LCP where we merge partial BWTs with a forward approach to sort suffixes. In this paper, we propose an alternative backward strategy to develop an external memory method to simultaneously build the BWT and the LCP array on a collection of m strings of different lengths. The algorithm over a set of strings having constant length k has O(mkl) time and I/O volume, using O(k + m) main memory, where l is the maximum value in the LCP array.