The Swiss Board Directors Network in 2009

We study the networks formed by the directors of the most important Swiss boards and the boards themselves for the year 2009. The networks are obtained by projection from the original bipartite graph. We highlight a number of important statistical features of those networks such as degree distribution, weight distribution, and several centrality measures as well as their interrelationships. While similar statistics were already known for other board systems, and are comparable here, we have extended the study with a careful investigation of director and board centrality, a k-core analysis, and a simulation of the speed of information propagation and its relationships with the topological aspects of the network such as clustering and link weight and betweenness. The overall picture that emerges is one in which the topological structure of the Swiss board and director networks has evolved in such a way that special actors and links between actors play a fundamental role in the flow of information among distant parts of the network. This is shown in particular by the centrality measures and by the simulation of a simple epidemic process on the directors network.Comment: Submitted to The European Physical Journal

Production of 5-hydroxy-7-methoxy-4-methylphthalide in a culture of Penicillium crustosum.

The chemical reactions carried out by microorganisms have been used as a tool in modern chemistry. This paper reports the production of mycophenolic acid and a new phthalide by the endophytic fungus Penicillium crustosum obtained from coffee seeds. The fungus was cultivated in a liquid medium for a period of seven days and after that the culture medium was divided into four treatments: A, B, C and D, to which different organic substances were added. Treatment A was maintained as the control to evaluate the occurrence of biotransformation. Organic acids were added to the culture media of treatments B (ferulic and quinic acids) and C [cinnamic and 3,4-(methylenedioxy) cinnamic acids], and caffeine was added in the treatment D. All these organic compounds were dissolved in DMSO, and the fermentation was maintained for more 13 days, totalizing 20 days. Mycophenolic acid was isolated from the culture with no added acids (treatment A). Mycophenolic acid and a new phthalide, 5-hydroxy-7-methoxy-4-methylphthalide were isolated from treatments B and C, and mycophenolic acid and caffeine (added to the culture medium) were isolated from treatment D. The structures were determined by NMR techniques and confi rmed by MS and MS/MS technique

Pareto Local Optima of Multiobjective NK-Landscapes with Correlated Objectives

International audienceIn this paper, we conduct a fitness landscape analysis for multiobjective combinatorial optimization, based on the local optima of multiobjective NK-landscapes with objective correlation. In single-objective optimization, it has become clear that local optima have a strong impact on the performance of metaheuristics. Here, we propose an extension to the multiobjective case, based on the Pareto dominance. We study the co-influence of the problem dimension, the degree of non-linearity, the number of objectives and the correlation degree between objective functions on the number of Pareto local optima

The Local Optima Level in Chemotherapy Schedule Optimisation

In this paper a multi-drug Chemotherapy Schedule Optimisation Problem (CSOP) is subject to Local Optima Network (LON) analysis. LONs capture global patterns in fitness landscapes. CSOPs have not previously been subject to fitness landscape analysis. We fill this gap: LONs are constructed and studied for meaningful structure. The CSOP formulation presents novel challenges and questions for the LON model because there are infeasible regions in the fitness landscape and an unknown global optimum; it also brings a topic from healthcare to LON analysis. Two LON Construction algorithms are proposed for sampling CSOP fitness landscapes: a Markov-Chain Construction Algorithm and a Hybrid Construction Algorithm. The results provide new insight into LONs of highly-constrained spaces, and into the proficiency of search operators on the CSOP. Iterated Local Search and Memetic Search, which are the foundations for the LON algorithms, are found to markedly out-perform a Genetic Algorithm from the literature

The “Personal Health Budget” intervention model in early psychosis: Preliminary findings from the Parma experience

Objectives Personal Health Budget (PHB) has recently been provided to people with severe mental illness, reflecting a policy shift towards a personalized mental health care based on individual unmet needs. However, evidence on effectiveness of PHB initiatives is still limited. Aim of this research was to provide preliminary data about the beneficial effects of adding PHB to a multicomponent EIP intervention in patients with First-Episode Psychosis (FEP) along a 2-year follow-up period. Methods Participants (n = 49) were FEP patients, aged 18-50 years, entered the “Parma Early Psychosis” program and completing the Health of Nation Outcome Scale (HoNOS), the Brief Psychiatric Rating Scale (BPRS) and the Global Assessment of Functioning (GAF). Friedman test for repeated measure (with Wilcoxon test as post-hoc procedure) was performed to evaluate the longitudinal stability of functioning and clinical parameters. A linear regression analysis was also carried out. Results A significant effect of time on all HoNOS, BPRS and GAF scores along the 2 years of follow-up was found. Regression analysis results specifically showed a relevant association between a PHB multiaxial intervention and the longitudinal decrease in BPRS “Negative Symptoms” subscores, as well as in HoNOS “Behavioral Problems” and “Social Problems” scores. Conclusions Our results support the general applicability of a PHB approach within an “Early Intervention in Psychosis” program for help-seeking adults with FEP

Coarse-Grained Barrier Trees of Fitness Landscapes

Recent literature suggests that local optima in fitness landscapes are clustered, which offers an explanation of why perturbation-based metaheuristics often fail to find the global optimum: they become trapped in a sub-optimal cluster. We introduce a method to extract and visualize the global organization of these clusters in form of a barrier tree. Barrier trees have been used to visualize the barriers between local optima basins in fitness landscapes. Our method computes a more coarsely grained tree to reveal the barriers between clusters of local optima. The core element is a new variant of the flooding algorithm, applicable to local optima networks, a compressed representation of fitness landscapes. To identify the clusters, we apply a community detection algorithm. A sample of 200 NK fitness landscapes suggests that the depth of their coarse-grained barrier tree is related to their search difficulty

Understanding Phase Transitions with Local Optima Networks: Number Partitioning as a Case Study

Phase transitions play an important role in understanding search difficulty in combinatorial optimisation. However, previous attempts have not revealed a clear link between fitness landscape properties and the phase transition. We explore whether the global landscape structure of the number partitioning problem changes with the phase transition. Using the local optima network model, we analyse a number of instances before, during, and after the phase transition. We compute relevant network and neutrality metrics; and importantly, identify and visualise the funnel structure with an approach (monotonic sequences) inspired by theoretical chemistry. While most metrics remain oblivious to the phase transition, our results reveal that the funnel structure clearly changes. Easy instances feature a single or a small number of dominant funnels leading to global optima; hard instances have a large number of suboptimal funnels attracting the search. Our study brings new insights and tools to the study of phase transitions in combinatorial optimisation

Local Optima Networks of the Permutation Flow-Shop Problem

International audienceThis article extracts and analyzes local optima networks for the permutation flow-shop problem. Two widely used move operators for permutation representations, namely, swap and insertion, are incorporated into the network landscape model. The performance of a heuristic search algorithm on this problem is also analyzed. In particular, we study the correlation between local optima network features and the performance of an iterated local search heuristic. Our analysis reveals that network features can explain and predict problem difficulty. The evidence confirms the superiority of the insertion operator for this problem