Optimization of Power Consumption in 4G LTE Networks Using a Novel Barebones Self-adaptive Differential Evolution Algorithm

The power consumption of wireless access networks is an important issue. In this paper, the power consumption of Long Term Evolution (LTE) base stations is optimized. We consider the city of Ghent, Belgium with 75 possible LTE base station locations. We optimize the network towards two objectives: the coverage maximization and the power consumption minimization. We propose a new Barebones Self-adaptive Differential Evolution. The results of the proposed method indicate the advantages and applicability of our approach.     

Accelerated Mold Test on Dried Pine Sapwood Boards: Impact of Contact Heat Treatment

Abstract

We test the hypothesis that the combination of kiln drying of double-stacked boards and contact heat treatment will reduce the susceptibility of treated boards to colonization by mold fungi. Winter-felled Scots pine (Pinus sylvestris L.) sapwood boards were double-stacked in an industrial kiln in ‘‘sapwood out’’ and ‘‘sapwood in’’ positions. Dried samples were then contact heat-treated using a hot press at three different temperatures (140°C, 170°C, and 200°C) for three different periods (1, 3, and 10 min). An accelerated mold test was performed in a climate chamber where naturally mold-infected samples were used as a source of mold inocula. Contact heat treatment degraded the saccharides that accumulated at dried surfaces, and reduced the mold growth. The threshold temperature and time for inhibiting mold growth were 170°C for 10 min. However, for industrial application, the most feasible combination of temperature and time would be 200°C for 3 min. We concluded that double stacking/contact heat treatment used is an environmentally friendly alternative to chemicals for reducing mold on Scots pine sapwood boards.     

Mastering the structure of PLA foams made with extrusion assisted by supercritical CO2

In this study, the outcome of operating conditions of extrusion assisted by supercritical CO₂ for the manufacture of poly(lactic acid) foams was investigated. It was found that the temperature before and inside the die was the most prominent parameter to tune the foam properties. Foam porosity as high as 96% could be obtained (for die temperature between 109 and 112 °C), representing a total expansion exceeding 30. In this temperature range, low crystallinity (≈6%) was induced giving foams with high radial expansion i.e., large diameters and open porosity. At 112 °C, the CO₂ was able to greatly expand the foams, providing 73% of its potential blowing effect. On the other hand, a low die temperature (below a die temperature of 107 °C) induces a significantly higher level of crystallinity resulting in foams with closed‐porosity and a large longitudinal expansion due to higher strength of the polymer melt. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 45067.     

Development of a Method to Measure preβHDL and αHDL apoA-I Enrichment for Stable Isotopic Studies of HDL Kinetics

Our understanding of HDL metabolism would be enhanced by the measurement of the kinetics of preβHDL, the nascent form of HDL, since elevated levels have been reported in patients with coronary artery disease. Stable isotope methodology is an established technique that has enabled the determination of the kinetics (production and catabolism) of total HDL apoA-I in vivo. The development of separation procedures to obtain a preβHDL fraction, the isotopic enrichment of which could then be measured, would enable further understanding of the pathways in vivo for determining the fate of preβHDL and the formation of αHDL. A method was developed and optimised to separate and measure preβHDL and αHDL apoA-I enrichment. Agarose gel electrophoresis was first used to separate lipoprotein subclasses, and then a 4–10 % discontinuous SDS-PAGE used to isolate apoA-I. Measures of preβHDL enrichment in six healthy subjects were undertaken following an infusion of l-[1-¹³C-leucine]. After isolation of preβ and αHDL, the isotopic enrichment of apoA-I for each fraction was measured by gas chromatography–mass spectrometry. PreβHDL apoA-I enrichment was measured with a CV of 0.51 % and αHDL apoA-I with a CV of 0.34 %. The fractional catabolic rate (FCR) of preβHDL apoA-I was significantly higher than the FCR of αHDL apoA-I (p < 0.005). This methodology can be used to selectively isolate preβ and αHDL apoA-I for the measurement of apoA-I isotopic enrichment for kinetics studies of HDL subclass metabolism in a research setting.     

How light conditions influence theoretical pelagic to benthic primary production ratios in small lakes

Theoretical pelagic primary production of phytoplankton and benthic primary production of periphyton were modelled for two small lakes in Estonia (Northeast Europe). Although located only 500 m apart, the water colour and light attenuation of these two lakes differed markedly. The Secchi depth (SD) in the clear‐water lake was 4.5 m and only 0.47 m in the dark‐water lake. The total phosphorus (TP) concentrations were, respectively, 15 μg/l and 28 μg/l. An empirical model whose inputs were morphometric, light conditions and dissolved organic carbon parameters obtained from in situ measurements was employed for the present study. The model calculated primary production with a time‐step of 10 min, and a spatial resolution of 10 cm, from sunrise to sunset and from lake surface to lake bottom. The primary production of periphyton and phytoplankton was almost equal in the clear lake, whereas only phytoplankton contributed to whole‐lake primary production in the dark lake because of the stronger light attenuation in the water column. The results of the present study indicated the depth‐distribution profiles differed dramatically between the two lakes. The clear lake had a deep, U‐shaped curve, with the productive layer reaching considerable depth soon after sunrise and maintaining a similar profile throughout the light hours. In contrast, the dark lake production declined rapidly with increasing depth, whereas the profile changed over the day reaching the greatest depth at noon.     

Root cause analysis during process development using Joint-Y PLS

The original purpose of the JYPLS model was to aid product transfer and scale-up. This work demonstrates that the JYPLS model is also well suited to analyze data from a process in development where the number and type of sensors and sensor locations are also being decided. The specific application in this case was to determine the root cause for a bias found during the development of a multivariate calibration model for a Near Infrared (NIR) instrument. The calibration model was built in parallel with the development of the manufacturing process itself. Each time the calibration model was tested with data from a new batch run, a non-explained bias was observed. Laboratory results on samples gathered from the process show that the NIR signal itself was biased and not the actual concentration of the constituent. Data on the processing conditions were collected for all the batches and included in the JYPLS model along with NIR and lab results. The loadings and scores from the JYPLS model were interpreted to isolate the root cause of the observed drift in the calibration model. This work discusses the general approach and presents the sequence of diagnostics used to analyze the different campaigns during process development. This should be applicable to other scenarios in process development where the data has the same architecture.     

Understanding life cycle social impacts in manufacturing: A processed-based approach

Developing sustainable products and processes is growing in importance due to increasing regulation, consumer interest, access to information, and competitive forces. In order to adequately evaluate the sustainability of products and processes, there is a need to consider the impacts from all three pillars of sustainability – society, environment, and economics. There are substantial challenges to identifying and understanding the social impacts associated with manufacturing activities. This paper provides a framework for characterizing the social impacts of manufacturing throughout the life cycle of a product or process. Social impacts occur on various scales in manufacturing, from the level of a unit process to the level of the enterprise. Additionally, manufacturing activities impact consumers, communities, and larger political/spatial realms. This paper identifies key characteristics of social impacts associated with manufacturing that should be considered to more effectively address the social dimension of sustainability for products and processes. Examples involving a typical manufacturing process – welding – are presented to illustrate the utility of the framework.