A competitive comparison of different types of evolutionary algorithms

This paper presents comparison of several stochastic optimization algorithms developed by authors in their previous works for the solution of some problems arising in Civil Engineering. The introduced optimization methods are: the integer augmented simulated annealing (IASA), the real-coded augmented simulated annealing (RASA), the differential evolution (DE) in its original fashion developed by R. Storn and K. Price and simplified real-coded differential genetic algorithm (SADE). Each of these methods was developed for some specific optimization problem; namely the Chebychev trial polynomial problem, the so called type 0 function and two engineering problems - the reinforced concrete beam layout and the periodic unit cell problem respectively. Detailed and extensive numerical tests were performed to examine the stability and efficiency of proposed algorithms. The results of our experiments suggest that the performance and robustness of RASA, IASA and SADE methods are comparable, while the DE algorithm performs slightly worse. This fact together with a small number of internal parameters promotes the SADE method as the most robust for practical use.Comment: 25 pages, 8 figures, 5 table

Bi-objective maritime route planning in pirate-infested waters

Contemporary maritime shipping is subject to a large number of constraints given by tight shipping schedules and very low margins. Additionally, problematic areas with increased security needs dynamically changing in time, combined with seasonal oceanographic and meteorological conditions pose a challenging voyage planning problem. In this work we present a risk-aware voyage planner taking into account spatio-temporal environmental conditions. The planner is based on a graph-based search algorithm A* . We discretize the required area into a graph, we store various layers of information into the edges of the graph (such as risk and weather conditions) in a form of numeric weights and we define a bi-objective planning problem with a tradeoff between security and duration of the voyage. The nature of the algorithm guarantees a complete and optimal solution in a form of an optimized voyage with respect to the criterion function composed of the two weighted components, i.e, duration and security of the voyage. We demonstrate the approach on our area of interest: Indian Ocean. We use NATO piracy activity risk surface as the risk layer and we compute all transit voyages between relevant routing points in the area. Finally, thanks to the discretization of the problem, we are able to integrate corridors imposed by the shipping authorities and evaluate additional what-if scenarios with extended corridor systems. The resulting planner is exposed to the public using a web service with an easy interface requiring start time of the voyage and the origin and the destination point of voyage. Combined with an expressive visualization, this tool demonstrates the capabilities of the proposed solution

Agent-based approach to illegal maritime behavior modeling

Maritime shipping is a set of complex activities with a large number of actors involved. We focus on a subset of illegal maritime activities, such as armed robberies, maritime piracy or contraband smuggling. To fight against them and minimize their negative impact naval authorities typically introduce a number of countermeasures, such as deployed patrols or surveillance agents. Due to very high costs of countermeasures it is often beneficial to evaluate their impact using a simulation, allowing what-if analysis and evaluation of a range of scenarios before actually deploying the countermeasures. We introduce BANDIT, an agent-based computational platform, which is designed to evaluate scenarios with an accent on the modeling of different types of illegal behavior and on the interaction between agents. The platform consists of an agent behavior modeling system and a multi-agent maritime simulator. The platform allows the definition of a number of scenarios through a simple configuration and it offers the means to run these scenarios in a single or a batch mode and evaluate the results as single or aggregate data sets respectively. We demonstrate the usefulness of the platform on the scenarios of the drug smuggling problem in the seas surrounding Central America. Senario outcomes (e.g., heatmaps of activities, set of trajectories etc.) are subsequently used to help with the design of effective countermeasures, i.e., allocating naval patrols and planning their patrol routes

Significant overexpression of Hsp110 gene during colorectal cancer progression

Colorectal cancer (CRC) is one of the most frequent malignant diseases in the world. Metastatic spread of the cancer to the lymph nodes is a crucial factor for progression and therapeutic management of the disease. We analysed gene expression profiles of CRC patiens by low-density cancer-focused oligonucleotide microarrays to identify new predictive markers of the extent of the disease and for better understanding of CRC progression. Relative expression levels of 440 genes known to be involved in cancer biology were obtained by low-density oligonucleotide microarrays from 20 tumor samples. Statistical analysis of gene expression data identified 3 genes (HSP110, HYOU1 and TCTP) significantly up-regulated in primary tumors of patients who developed lymph node metastasis. We have shown, for the first time, that up-regulation HSP110 and HYOU1 expression is associated with lymph node involvement in CRC. We validated the differences in HSP110 expression in an independent group of 30 patients of all clinical stages by real-time PCR. We identified significant up-regulation of HSP110 expression in colorectal tumors compared to adjacent non-tumoral tissue (p<0.0003). We observed significant differences of HSP110 gene expression between metastatic and localized disease (p=0.031) and negative trend of HSP110 gene expression and overall survival of CRC patients. We suggest that HSP110 gene is a promising molecular predictor in CRC

Control of anterior GRadient 2 (AGR2) dimerization links endoplasmic reticulum proteostasis to inflammation

Anterior gradient 2 (AGR2) is a dimeric protein disulfide isomerase family member involved in the regulation of protein quality control in the endoplasmic reticulum (ER). Mouse AGR2 deletion increases intestinal inflammation and promotes the development of inflammatory bowel disease (IBD). Although these biological effects are well established, the underlying molecular mechanisms of AGR2 function toward inflammation remain poorly defined. Here, using a protein–protein interaction screen to identify cellular regulators of AGR2 dimerization, we unveiled specific enhancers, including TMED2, and inhibitors of AGR2 dimerization, that control AGR2 functions. We demonstrate that modulation of AGR2 dimer formation, whether enhancing or inhibiting the process, yields pro‐inflammatory phenotypes, through either autophagy‐dependent processes or secretion of AGR2, respectively. We also demonstrate that in IBD and specifically in Crohn's disease, the levels of AGR2 dimerization modulators are selectively deregulated, and this correlates with severity of disease. Our study demonstrates that AGR2 dimers act as sensors of ER homeostasis which are disrupted upon ER stress and promote the secretion of AGR2 monomers. The latter might represent systemic alarm signals for pro‐inflammatory responses