A nonmonotone GRASP

A greedy randomized adaptive search procedure (GRASP) is an itera- tive multistart metaheuristic for difficult combinatorial optimization problems. Each GRASP iteration consists of two phases: a construction phase, in which a feasible solution is produced, and a local search phase, in which a local optimum in the neighborhood of the constructed solution is sought. Repeated applications of the con- struction procedure yields different starting solutions for the local search and the best overall solution is kept as the result. The GRASP local search applies iterative improvement until a locally optimal solution is found. During this phase, starting from the current solution an improving neighbor solution is accepted and considered as the new current solution. In this paper, we propose a variant of the GRASP framework that uses a new “nonmonotone” strategy to explore the neighborhood of the current solu- tion. We formally state the convergence of the nonmonotone local search to a locally optimal solution and illustrate the effectiveness of the resulting Nonmonotone GRASP on three classical hard combinatorial optimization problems: the maximum cut prob- lem (MAX-CUT), the weighted maximum satisfiability problem (MAX-SAT), and the quadratic assignment problem (QAP)

Hybridization of multi-objective deterministic particle swarm with derivative-free local searches

The paper presents a multi-objective derivative-free and deterministic global/local hybrid algorithm for the efficient and effective solution of simulation-based design optimization (SBDO) problems. The objective is to show how the hybridization of two multi-objective derivative-free global and local algorithms achieves better performance than the separate use of the two algorithms in solving specific SBDO problems for hull-form design. The proposed method belongs to the class of memetic algorithms, where the global exploration capability of multi-objective deterministic particle swarm optimization is enriched by exploiting the local search accuracy of a derivative-free multi-objective line-search method. To the authors best knowledge, studies are still limited on memetic, multi-objective, deterministic, derivative-free, and evolutionary algorithms for an effective and efficient solution of SBDO for hull-form design. The proposed formulation manages global and local searches based on the hypervolume metric. The hybridization scheme uses two parameters to control the local search activation and the number of function calls used by the local algorithm. The most promising values of these parameters were identified using forty analytical tests representative of the SBDO problem of interest. The resulting hybrid algorithm was finally applied to two SBDO problems for hull-form design. For both analytical tests and SBDO problems, the hybrid method achieves better performance than its global and local counterparts

OUTCOME OF A PILOT COURSE IN SCIENCE COMMUNICATION HIGHLIGHTS THE RELEVANCE OF STUDENT MOTIVATION

The authors devised a lecture series about the common principles making the core of Science Communication, irrespective of specialist disciplines. The aim of the initiative was to engage STEM students, curious about communication of science, into a mostly practical activity, evaluating their degree of satisfaction and the sustainability of the course schedule during the running semester. The course content was originally designed and advertised as an interactive living learning experience. It was then adapted last minute to remote teaching because of the Covid-19 semester, with a significant impact on both the actual interactions and the students’ satisfaction, with respect to expectations. Nonetheless, a follow-up analysis shows that 90% of students declared to have realized, in full or in part, their expected achievements. A high degree of global satisfaction (3.7/5) was acknowledged, despite 77% of students declared a Perceived Study Effort greater than expected. Final grades correlate positively with students Motivation, whereas they are not correlated with any specific Degree Course

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

A multi-objective DIRECT algorithm for ship hull optimization

The paper is concerned with black-box nonlinear constrained multi-objective optimization problems. Our interest is the definition of a multi-objective deterministic partition-based algorithm. The main target of the proposed algorithm is the solution of a real ship hull optimization problem. To this purpose and in pursuit of an efficient method, we develop an hybrid algorithm by coupling a multi-objective DIRECT-type algorithm with an efficient derivative-free local algorithm. The results obtained on a set of “hard” nonlinear constrained multi-objective test problems show viability of the proposed approach. Results on a hull-form optimization of a high-speed catamaran (sailing in head waves in the North Pacific Ocean) are also presented. In order to consider a real ocean environment, stochastic sea state and speed are taken into account. The problem is formulated as a multi-objective optimization aimed at (i) the reduction of the expected value of the mean total resistance in irregular head waves, at variable speed and (ii) the increase of the ship operability, with respect to a set of motion-related constraints. We show that the hybrid method performs well also on this industrial problem

Neuroprotective potential of isothiocyanates in an in vitro model of neuroinflammation

Isothiocyanates (ITCs), present as glucosinolate precursors in cruciferous vegetables, have shown anti-inflammatory, antioxidant and anticarcinogenic activities. Here, we compared the effects of three different ITCs on ROS production and on the expression of matrix metalloproteinase (MMP)-2 and -9, which represent important pathogenetic factors of various neurological diseases. Primary cultures of rat astrocytes were activated by LPS and simultaneously treated with different doses of Allyl isothiocyanate (AITC), 2-Phenethyl isothiocyanate (PEITC) and 2-Sulforaphane (SFN). Results showed that SFN and PEITC were able to counteract ROS production induced by H2O2. The zymographic analysis of cell culture supernatants evidenced that PEITC and SFN were the most effective inhibitors of MMP-9, whereas, only SFN significantly inhibited MMP-2 activity. PCR analysis showed that all the ITCs used significantly inhibited both MMP-2 and MMP-9 expression. The investigation on the mitogen-activated protein kinase (MAPK) signaling pathway demonstrated that ITCs modulate MMP transcription by inhibition of extracellular-regulated protein kinase (ERK) activity. Results of this study suggest that ITCs could be promising nutraceutical agents for the prevention and complementary treatment of neurological diseases associated with MMP involvement

GIADA performance during Rosetta mission scientific operations at comet 67P

The Grain Impact Analyser and Dust Accumulator (GIADA) instrument onboard Rosetta studied the dust environment of comet 67P/Churyumov–Gerasimenko from 3.7 au inbound, through perihelion, to 3.8 au outbound, measuring the dust flow and the dynamic properties of individual particles. GIADA is composed of three subsystems: 1) Grain Detection System (GDS); 2) Impact Sensor (IS); and 3) Micro-Balances System (MBS). Monitoring the subsystems’ performance during operations is an important element for the correct calibration of scientific measurements. In this paper, we analyse the GIADA inflight calibration data obtained by internal calibration devices for the three subsystems during the period from 1 August 2014 to 31 October 2015. The calibration data testify a nominal behaviour of the instrument during these fifteen months of mission; the only exception is a minor loss of sensitivity for one of the two GDS receivers, attributed to dust contamination