Modelling Cell Cycle using Different Levels of Representation

Understanding the behaviour of biological systems requires a complex setting of in vitro and in vivo experiments, which attracts high costs in terms of time and resources. The use of mathematical models allows researchers to perform computerised simulations of biological systems, which are called in silico experiments, to attain important insights and predictions about the system behaviour with a considerably lower cost. Computer visualisation is an important part of this approach, since it provides a realistic representation of the system behaviour. We define a formal methodology to model biological systems using different levels of representation: a purely formal representation, which we call molecular level, models the biochemical dynamics of the system; visualisation-oriented representations, which we call visual levels, provide views of the biological system at a higher level of organisation and are equipped with the necessary spatial information to generate the appropriate visualisation. We choose Spatial CLS, a formal language belonging to the class of Calculi of Looping Sequences, as the formalism for modelling all representation levels. We illustrate our approach using the budding yeast cell cycle as a case study

Enhancing low-rank solutions in semidefinite relaxations of Boolean quadratic problems

Boolean quadratic optimization problems occur in a number of applications. Their mixed integer-continuous nature is challenging, since it is inherently NP-hard. For this motivation, semidefinite programming relaxations (SDR's) are proposed in the literature to approximate the solution, which recasts the problem into convex optimization. Nevertheless, SDR's do not guarantee the extraction of the correct binary minimizer. In this paper, we present a novel approach to enhance the binary solution recovery. The key of the proposed method is the exploitation of known information on the eigenvalues of the desired solution. As the proposed approach yields a non-convex program, we develop and analyze an iterative descent strategy, whose practical effectiveness is shown via numerical results

Sparse linear regression from perturbed data

The problem of sparse linear regression is relevant in the context of linear system identification from large datasets. When data are collected from real-world experiments, measurements are always affected by perturbations or low-precision representations. However, the problem of sparse linear regression from fully-perturbed data is scarcely studied in the literature, due to its mathematical complexity. In this paper, we show that, by assuming bounded perturbations, this problem can be tackled by solving low-complex l2 and l1 minimization problems. Both theoretical guarantees and numerical results are illustrated in the paper

Sparse learning with concave regularization: relaxation of the irrepresentable condition

Learning sparse models from data is an important task in all those frameworks where relevant information should be identified within a large dataset. This can be achieved by formulating and solving suitable sparsity promoting optimization problems. As to linear regression models, Lasso is the most popular convex approach, based on an L1-norm regularization. In contrast, in this paper, we analyse a concave regularized approach, and we prove that it relaxes the irrepresentable condition, which is sufficient and essentially necessary for Lasso to select the right significant parameters. In practice, this has the benefit of reducing the number of necessary measurements with respect to Lasso. Since the proposed problem is nonconvex, we also discuss different algorithms to solve it, and we illustrate the obtained enhancement via numerical experiments

The platform switching approach to optimize split crest technique.

The split crest technique is a reliable procedure used simultaneously in the implant positioning. In the literature some authors describe a secondary bone resorption as postoperative complication. The authors show how platform switching can be able to avoid secondary resorption as complication of split crest technique

Multidisciplinary Approach to Fused Maxillary central Incisors: a Case Report

Introduction: The fusion of permanent teeth is a development anomaly of dental hard tissue. It may require a hard multidisciplinary approach with orthodontics, endodontics, surgery and prosthetics to solve aesthetic and functional problems. Case presentation: A 20-year-old Caucasian man presented to our Department to solve a dental anomaly of his upper central incisors. An oral investigation revealed the fusion of his maxillary central incisors and dyschromia of right central incisor. Vitality pulp tests were negative for lateral upper incisors and left central incisor. Radiographic examinations showed a fused tooth with two separate pulp chambers, two distinct roots and two separate root canals. There were also periapical lesions of central incisors and right lateral incisor, so he underwent endodontic treatment. Six months later, OPT examination revealed persistence of the periapical radiolucency, so endodontic surgery was performed, which included exeresis of the lesion, an apicoectomy and retrograde obturation with a reinforced zinc oxide-eugenol cement (SuperEBA) Complete healing of the lesion was obtained six months postoperatively. Fused teeth crowns were separated and orthodontic appliances were put in place. When correct teeth position was achieved (after nine months), the anterior teeth were prosthetically rehabilitated. Conclusion: Many treatment options have been proposed in the literature to solve cases of dental fusion. The best treatment plan depends on the nature of the anomaly, its location, the morphology of the pulp chamber and root canal system, the subgingival extent of the separation line, and the patient compliance. Following an analysis of radiographical and clinical data, it was possible to solve our patient’s dental anomaly with a multidisciplinary approach

Specifying and Verifying Concurrent Algorithms with Histories and Subjectivity

We present a lightweight approach to Hoare-style specifications for fine-grained concurrency, based on a notion of time-stamped histories that abstractly capture atomic changes in the program state. Our key observation is that histories form a partial commutative monoid, a structure fundamental for representation of concurrent resources. This insight provides us with a unifying mechanism that allows us to treat histories just like heaps in separation logic. For example, both are subject to the same assertion logic and inference rules (e.g., the frame rule). Moreover, the notion of ownership transfer, which usually applies to heaps, has an equivalent in histories. It can be used to formally represent helping---an important design pattern for concurrent algorithms whereby one thread can execute code on behalf of another. Specifications in terms of histories naturally abstract granularity, in the sense that sophisticated fine-grained algorithms can be given the same specifications as their simplified coarse-grained counterparts, making them equally convenient for client-side reasoning. We illustrate our approach on a number of examples and validate all of them in Coq.Comment: 17 page

Fixed-order FIR approximation of linear systems from quantized input and output data

Abstract The problem of identifying a fixed-order FIR approximation of linear systems with unknown structure, assuming that both input and output measurements are subjected to quantization, is dealt with in this paper. A fixed-order FIR model providing the best approximation of the input-output relationship is sought by minimizing the worst-case distance between the output of the true system and the modeled output, for all possible values of the input and output data consistent with their quantized measurements. The considered problem is firstly formulated in terms of robust optimization. Then, two different algorithms to compute the optimum of the formulated problem by means of linear programming techniques are presented. The effectiveness of the proposed approach is illustrated by means of a simulation example

Changes in the distribution of muscle activity when using a passive trunk exoskeleton depend on the type of working task: A high-density surface EMG study

Exoskeleton effectiveness in reducing muscle efforts has been usually assessed from surface electromyograms (EMGs) collected locally. It has been demonstrated, however, muscle activity redistributes within the low back muscles during static and dynamic contractions, suggesting the need of detecting surface EMGs from a large muscle region to reliably investigate changes in global muscle activation. This study used high-density surface EMG to assess the effects of a passive trunk exoskeleton on the distribution of low back muscles’ activity during different working tasks. Ten, male volunteers performed a static and a dynamic task with and without the exoskeleton. Multiple EMGs were sampled bilaterally from the lumbar erector spinae muscles while the hip and knee angles were measured unilaterally. Key results revealed for the static task exoskeleton led to a decrease in the average root mean square (RMS) amplitude (∼10%) concomitantly with a stable mean frequency and a redistribution of muscle activity (∼0.5 cm) in the caudal direction toward the end of the task. For the dynamic task, the exoskeleton reduced the RMS amplitude (∼5%) at the beginning of the task and the variability in the muscle activity distribution during the task. Moreover, a reduced range of motion in the lower limb was observed when using the exoskeleton during the dynamic task. Current results support the notion the passive exoskeleton has the potential to alleviate muscular loading at low back level especially for the static task