Age‐Related Physiological Responses to Working in Deep Cold

Professional order‐picking in deep cold‐storage depots (i.e., storing, picking, and dispatching of frozen groceries) requires employees to remain working at temperatures of approximately ?24°C for a whole workday. Actually, a well‐regulated organization of working times and breaks has not been established, and no competent knowledge exists as to whether an additional age‐differentiated organization is necessary. To assess the physiological effects while working in deep cold, 30 male subjects (Ss) were classified into two age groups (20‐ to 35‐year‐olds and 40‐ to 65‐year‐olds). In whole workday tests, possible age‐dependent effects on the strain were measured to guarantee the preservation of the subjects' ability to work in the long run. For the objectification of the physiological strain, heart rate and skin surface temperature were registered continuously, and blood pressure and body core temperature were measured and recorded discretely during cold exposures of 80, 100, and 120 min, separated by 20‐min warming‐up breaks. Systematic differences of blood pressure could not be found. The heart rate values indicated a high physiological strain for both younger and older Ss, with work‐related increases above the resting level of 30 bpm and more. Due to increases over time, endurance level sometimes was exceeded. Age‐related differences in skin temperature could not be recorded, but the ability to generate heat deteriorated with advancing age, which is shown by more substantial decreases of body core temperature in the group of 40‐ to 65‐year‐olds taken at the tympanum. Regarding physiological strain brought about by maximum heart rate decreasing with age and declined heat generation, correspondingly adapted workday break regimes have to be provided for older employees to ensure their ability to work in the long run. © 2011 Wiley Periodicals, Inc.     

A metaheuristic-based downlink power allocation for LTE/LTE-A cellular deployments

The explosive growth of cellular networks makes their deployment and maintenance more and more complex, time consuming, and expensive. Self-Organizing Networks have been recognized as a promising way to alleviate this problem by minimizing human intervention in such processes. This paper introduces a novel multiobjective framework, based on evolutionary optimization, aiming at improving network performance and users Quality of Service. By tuning the transmitted power at each cell, average intercell interference levels are minimized. The design of the proposed scheme is feasible for distributed implementations in Long Term Evolution (LTE) and LTE-Advanced networks and its operation is compatible with current specifications. The framework is able to provide effective network-specific optimization and obtained results show that gains in terms of network capacity and cell edge performance are 5 and 10 %, respectively. Energy savings always accompanied such enhancements with reductions up to 35 %.     

Un-jamming due to energetic instability: statics to dynamics

Granular Matter - A method to identify the parameters of rolling resistance between particles in the discrete element method is proposed in this paper. Experiments revealed that a free rolling...     

A methodology for screening of microalgae as a decision making tool for energy and green chemical process applications

The increasing interest for biotechnological use of microalgae demands a methodology for selection of species suitable to support the development of technologies based on the use of such non-conventional renewable raw material, i.e., green industrial applications. The vast and expanding collection of experimental data on both cell growth and biomass composition available in the literature can be used to reduce the cost of the experimental investigations required to support process engineering and optimization. Selecting the appropriate organism requires extracting useful information from such data, a cumbersome task since various multidisciplinary factors must be considered. This paper presents a computer-aided methodology for selecting appropriate algal species given an energy or green chemical process application employing microalgae as a renewable raw material. The approach is “system oriented”, based on biomass composition and chemical processing of the biomass downstream of the CO₂ biofixation and harvesting operations. Quantitative performance results are supported by professional process simulation. Besides comparison of a set of species performances, the proposed methodology also allows the discrimination among distinct algal compositions resulting from different growth conditions for a given species. Furthermore, three categories of screening metrics are proposed to be maximized by the decision making procedure in order to elicit the relevant information. To demonstrate the potential of the proposed methodology, a databank of both biochemical and elemental compositions of microalgal biomass was used in three green applications: Assessment of biomass heating value; production of syngas by gasification of the biomass; and production of Bio-H₂. Within the accuracy of the databank employed to illustrate the procedure, the methodology selected Botryococcus braunii and Isochrysis galbana as potential promising candidates, for the three examined applications.     

Direct characterisation of phenolic antioxidants in infusions from four Mapuche medicinal plants by liquid chromatography with diode array detection (HPLC-DAD) and electrospray ionisation tandem mass spectrometry (HPLC-ESI-MS)

A simple, fast and direct method was developed for the qualitative analysis of phenolic constituents from infusions of Mapuche medicinal plants. Teas made of Linum chamissonis Schiede, Quinchamalium chilensis Mol., Adesmia emarginata Clos. and Escallonia illinita K. Presl. were analysed by high-performance liquid chromatography with diode array detector (HPLC-DAD) and electrospray mass spectrometry (ESI-MS). This technique allowed for the first time the tentative identification of 16 phenolic compounds in E. illinita, 27 in Q. chilensis, 10 in L. chamissonis and 19 in A. emarginata. The compounds were mainly phenolic acids, flavonoid glycosides, anthocyanins and tannins. The total phenolic and flavonoid content of the infusions was assessed as well as the free radical scavenging capacity measured by the bleaching of a solution of the 2,2-diphenyl-1-picrylhydrazyl (DPPH⁻) radical. From the four species, Q. chilensis exhibited the strongest antioxidant activity with highest total phenolic and flavonoid content.     

Interaction of β‐casein with (−)‐epigallocatechin‐3‐gallate assayed by fluorescence quenching: effect of thermal processing temperature

The interactions between the flavan‐3‐ol (?)‐epigallocatechin‐3‐gallate (EGCG) and bovine β‐casein in phosphate‐buffered saline (PBS) of pH 6.5 subjected to thermal processing at various temperatures (25–100 °C) were investigated using fluorescence quenching. The results indicated that different temperatures had different effects on the structural changes and EGCG‐binding ability of β‐casein. At temperatures below 60 °C, the β‐casein–EGCG interaction changed little (P > 0.05) with increasing temperature. At temperatures above 80 °C, native assemblies of β‐casein in solution dissociated into individual β‐casein molecules and unfolded, as demonstrated by a red shift of the maximum fluorescence emission wavelength (λ_max) of up to 8.8 nm. The highest quenching constant (K_q) and the number of binding sites (n) were 0.92 (±0.01) × 10¹³ m ^?1 s^?1 and 0.73 (±0.02) (100 °C), respectively. These results provide insight into the potential of interactions between β‐casein–EGCG that may modulate bioactivity or bioavailability to be altered during thermal process.     

Investigation on PEM water electrolysis cell design and components for a HyCon solar hydrogen generator

Hydrogen as a secondary energy carrier promises a large potential as a long term storage for fluctuating renewable energies. In this sense a highly efficient solar hydrogen generation is of great interest especially in southern countries having high solar irradiation. The patented Hydrogen Concentrator (HyCon) concept yields high efficiencies combining multi-junction solar cells with proton exchange (PEM) membrane water electrolysis. In this work, a special PEM electrolysis cell for the HyCon concept was developed and investigated. It is shown that the purpose-made PEM cell shows a high performance using a titanium hybrid fiber sinter function both as a porous transport layer and flow field. The electrolysis cell shows a high performance with 1.83 V at 1 A/cm² and 24 °C working under natural convection with a commercially available catalyst coated membrane. A theoretical examination predicts a total efficiency for the HyCon module from sunlight to hydrogen of approximately 19.5% according to the higher heating value.     

Detecting component changes at run time with behavior models

Modern software systems are composed of several services which may be developed and maintained by third parties and thus they can change independently and without notice during the system’s runtime execution. In such systems, changes may possibly be a threat to system functional correctness, and thus to its reliability. Hence, it is important to detect them as soon as they happen to enable proper reaction. Change detection can be done by monitoring system execution and comparing the observed execution traces against models of the services composing the application. Unfortunately, formal specifications for services are not usually provided and developers have to infer them. In this paper we propose a methodology which exactly addresses these issues by using software behavior models to monitor component execution and detect changes. In particular, we describe a technique to infer behavior model specifications with a dynamic black box approach, keep them up-to-date with run time observations and detect behavior changes. Finally, we present a case study to validate the effectiveness of the approach in component change detection for a component that implements a complex, real communication protocol.     

Complex and dynamic population structures: synthesis, open questions, and future directions

The population structure of an evolutionary algorithm influences the dissemination and mixing of advantageous alleles, and therefore affects search performance. Much recent attention has focused on the analysis of complex population structures, characterized by heterogeneous connectivity distributions, non-trivial clustering properties, and degree–degree correlations. Here, we synthesize the results of these recent studies, discuss their limitations, and highlight several open questions regarding (1) unsolved theoretical issues and (2) the practical utility of complex population structures for evolutionary search. In addition, we will discuss an alternative complex population structure that is known to significantly influence dynamical processes, but has yet to be explored for evolutionary optimization. We then shift our attention toward dynamic population structures, which have received markedly less attention than their static counterparts. We will discuss the strengths and limitations of extant techniques and present open theoretical and experimental questions and directions for future research. In particular, we will focus on the prospects of “active linking,” wherein edges are dynamically rewired according to the genotypic or phenotypic properties of individuals, or according to the success of prior inter-individual interactions.     

Extending the information delivery manual approach to identify information requirements for performance analysis of HVAC systems

Heating, Ventilation and Air-Conditioning (HVAC) systems account for more than 15% of the total energy consumption in the US. In order to improve the energy efficiency of HVAC systems, researchers have developed hundreds of algorithms to automatically analyze their performance. However, the complex information, such as configurations of HVAC systems, layouts and materials of building elements and dynamic data from the control systems, required by these algorithms inhibits the process of deploying them in real-world facilities. To address this challenge, we envision a framework that automatically integrates the required information items and provides them to the performance analysis algorithms for HVAC systems. This paper presents an approach to identify and document the information requirements from the publications that describe these algorithms. We extend the Information Delivery Manual (IDM) approach so that the identified information requirements can be mapped to multiple information sources that use various formats and schemas. This paper presents the extensions to the IDM approach and the results of using it to identify information requirements for performance analysis algorithms of HVAC systems.