Multiobjective process line optimization under uncertainty applied to papermaking

Multiobjective optimization methodology for the development of the papermaking process is considered. The aim is to find efficient and reliable solution procedures for the process line model consisting of sequential unit-process models; some of them based on physics, whereas others on experimental data. By the consequence of modeling procedures, nonphysical states or inherited from modeling data in statistical case, the unit-process models may suffer from undesired unreliability. To control the uncertainty resulting from the unit-process models, a new multiobjective optimization approach is introduced where both the papermaking targets as well as the uncertainty related unit-process models are simultaneously taken into account. We illustrate the solution process by numerical examples related to the quality of the produced paper.     

Multi-objective Swarm Intelligence schedulers for online scientific Clouds

Cloud Computing is a promising paradigm for parallel computing. However, as Cloud-based services become more dynamic, resource provisioning in Clouds becomes more challenging. The paradigm, with its promise of virtually infinite resources, seems to suit well in solving resource greedy scientific computing problems. In a Cloud, an appropriate number of Virtual Machines (VM) is created and allocated in physical resources for executing jobs. This work focuses on the Infrastructure as a Service (IaaS) model where custom VMs are launched in appropriate hosts available in a Cloud to execute scientific experiments coming from multiple users. Finding optimal solutions to allocate VMs to physical resources is an NP-complete problem, and therefore many heuristics have been developed. In this work, we describe and evaluate two Cloud schedulers based on Swarm Intelligence (SI) techniques, particularly Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). The main performance metrics to study are the number of serviced users by the Cloud and the total number of created VMs in online (non-batch) scheduling scenarios. We also perform a sensitivity analysis by varying the specific-parameter values of each algorithm to evaluate the impact on the performance of the two objective metrics. The intra-Cloud network traffic is also measured. Simulated experiments performed using CloudSim and job data from real scientific problems show that the use of SI-based techniques succeeds in balancing the studied metrics compared to Genetic Algorithms.     

Issues related to the computer realization of a multidisciplinary and multiobjective optimization system

Issues and novel ideas to be considered when developing computer realizations of complex multidisciplinary and multiobjective optimization systems are introduced. The aim is to discuss computer realizations that make possible both computationally efficient multidisciplinary analysis and multiobjective optimization of real world problems. We introduce software tools that make typically very time-consuming simulation processes more effective and, thus, enable even interactive multiobjective optimization with a real decision maker. In this paper, we first define a multidisciplinary and multiobjective optimization system and after that present an implementation overview of such problems including basic components participating in the solution process. Furthermore, interfaces and data flows between the components are described. A couple of important features related to the implementation are discussed in detail, for example, the usage of automatic differentiation. Finally, the ideas presented are illustrated with an industrial multiobjective optimization problem, when we describe numerical experiments related to quality properties in paper making.     

Multifunctional carbon-nanotube cellular endoscopes

Glass micropipettes, atomic force microscope tips and nanoneedles can be used to interrogate cells, but these devices either have conical geometries that can damage cells during penetration or are incapable of continuous fluid handling. Here, we report a carbon-nanotube-based endoscope for interrogating cells, transporting fluids and performing optical and electrochemical diagnostics at the single organelle level. The endoscope, which is made by placing a multiwalled carbon nanotube (length, 50-60?μm) at the tip of a glass pipette, can probe the intracellular environment with a spatial resolution of ～100?nm and can also access organelles without disrupting the cell. When the nanotube is filled with magnetic nanoparticles, the endoscope can be remotely manoeuvered to transport nanoparticles and attolitre volumes of fluids to and from precise locations. Because they are mounted on conventional glass micropipettes, the endoscopes readily fit standard instruments, creating a broad range of opportunities for minimally invasive intracellular probing, drug delivery and single-cell surgery.     

HEXTRAN–SMABRE calculation of the VVER-1000 coolant transient-1 benchmark

The VVER-1000 coolant transient benchmark is intended for validation of couplings of the thermal hydraulic codes and three-dimensional neutron kinetic core models. It concerns switching on a main coolant pump when the other three main coolant pumps are in operation. The problem is based on an experiment performed in Kozloduy NPP in Bulgaria. In addition to the real plant transient, an extreme scenario concerning a control rod ejection after switching on a main coolant pump was calculated. At VTT the three-dimensional advanced nodal code HEXTRAN is used for the core dynamics, and the system code SMABRE as a thermal hydraulic model for the primary and secondary loop. The parallelly coupled HEXTRAN–SMABRE code has been in production use since early 1990s, and it has been extensively used for analyses of VVER NPPs. The SMABRE input model is based on the standard VVER-1000 input used at VTT. The whole core calculation is performed with HEXTRAN. Also the core model is based on earlier VVER-1000 models. Nuclear data for the calculation were specified in the benchmark. The paper outlines the input models used for both codes. Calculated results are introduced both for the coupled core system with inlet and outlet boundary conditions and for the whole plant model. Parametric studies have been performed for selected parameters.     

Probiotic and milk technological properties of Lactobacillus brevis

Two Lactobacillus brevis strains ATCC 8287 and ATCC 14869(T), were evaluated for their applicability as putative probiotics in dairy products. The strains expressed good in vitro adherence to human Caco-2 and Intestine 407 cells and tolerated well low pH, bile acids and pancreatic fluid under in vitro conditions. In antimicrobial activity assays, strain ATCC 8287 showed inhibitory properties toward selected potential harmful microorganisms, particularly against Bacillus cereus. Both L. brevis strains were resistant to vancomycin, which is typical for the genus Lactobacillus. The L. brevis strains were not able to acidify milk to yoghurt but were suitable as supplement strains in yoghurts. This was shown by producing a set of yoghurt products and analysing their rheological and sensory properties during a cold storage period of 28 days. Survival of the strains through human intestine was examined in 1-week feeding trials. Despite its human origin, L. brevis ATCC 14869(T) could not survive through the gastrointestinal (GI) tract, whereas L. brevis ATCC 8287 was detected in the faecal samples taken during and immediately after ingestion of the strain. In conclusion, L. brevis ATCC 8287 is a promising candidate as a probiotic supplement in dairy products.     

Insectivorous Birds Are Attracted by Plant Traits Induced by Insect Egg Deposition

Insectivorous birds feed upon all developmental stages of herbivorous insects, including insect eggs if larvae and adults are unavailable. Insect egg deposition on plants can induce plant traits that are subsequently exploited by egg parasitoids searching for hosts. However, it is unknown whether avian predators can also use egg-induced plant changes for prey localization. Here, we studied whether great tits (Parus major) and blue tits (Cyanistes caeruleus) are attracted by traits of the Scots pine (Pinus sylvestris) induced by pine sawfly (Diprion pini) egg deposition. We chose this plant – insect system because sawfly egg deposition on pine needles is known to locally and systemically induce a change in pine volatile organic compounds (VOCs), and tits are known to prey upon sawfly eggs. In dual choice laboratory experiments, we simultaneously offered the birds an egg-free control branch and a systemically egg-induced branch. Significantly more birds visited the egg-induced branch first. We confirmed by GC-MS analyses that systemically egg-induced branches released more (E)-β-farnesene compared to control branches. Spectrophotometric analyses showed that control branches reflected more light than egg-induced branches throughout the avian visual range. Although a discrimination threshold model for blue tits suggests that the birds are poor at discriminating this visual difference, the role of visual stimuli in attracting the birds to egg-induced pines cannot be discounted. Our study shows, for the first time, that egg-induced odorous and/or visual plant traits can help birds to locate insect eggs without smelling or seeing those eggs.