Effects of resistance exercise and fortified milk on skeletal muscle mass, muscle size, and functional performance in middle-aged and older men: an 18-mo randomized controlled trial

Limited data have suggested that the consumption of fluid milk after resistance training (RT) may promote skeletal muscle hypertrophy. The aim of this study was to assess whether a milk-based nutritional supplement could enhance the effects of RT on muscle mass, size, strength, and function in middle-aged and older men. This was an 18-mo factorial design (randomized control trial) in which 180 healthy men aged 50–79 yr were allocated to the following groups: 1) exercise + fortified milk, 2) exercise, 3) fortified milk, or 4) control. Exercise consisted of progressive RT with weight-bearing impact exercise. Men assigned to the fortified milk consumed 400 ml/day of low-fat milk, providing an additional 836 kJ, 1000 mg calcium, 800 IU vitamin D3, and 13.2 g protein per day. Total body lean mass (LM) and fat mass (FM) (dual-energy X-ray absorptiometry), midfemur muscle cross-sectional area (CSA) (quantitative computed tomography), muscle strength, and physical function were assessed. After 18 mo, there was no significant exercise by fortified milk interaction for total body LM, muscle CSA, or any functional measure. However, main effect analyses revealed that exercise significantly improved muscle strength (∼20–52%, P < 0.001), LM (0.6 kg, P < 0.05), FM (−1.1 kg, P < 0.001), muscle CSA (1.8%, P < 0.001), and gait speed (11%, P < 0.05) relative to no exercise. There were no effects of the fortified milk on muscle size, strength, or function. In conclusion, the daily consumption of low-fat fortified milk does not enhance the effects of RT on skeletal muscle size, strength, or function in healthy middle-aged and older men with adequate energy and nutrient intakes.

Effect of noise factors in energy management of series plug-in hybrid electric vehicles

It has been demonstrated that charge depletion (CD) energy management strategies are more efficient choices for energy management of plug-in hybrid electric vehicles (PHEVs). The knowledge of drive cycle as a priori can improve the performance of CD energy management in PHEVs. However, there are many noise factors which affect both drivetrain power demand and vehicle performance even in identical drive cycles. In this research, the effect of each noise factor is investigated by introducing the concept of power cycle instead of drive cycle for a journey. Based on the nature of the noise factors, a practical solution for developing a power-cycle library is introduced. Investigating the predicted power cycle, an energy management strategy is developed which considers the influence of temperature noise factor on engine performance. The effect of different environmental and geographic conditions, driver behavior, aging of battery and other components are considered. Simulation results for a modelled series PHEV similar to GM Volt show that the suggested energy management strategy based on the driver power cycle library improves both vehicle fuel economy and battery health by reducing battery load and temperature.

Electrophoretic deposition of YSZ thin-film electrolyte for SOFCs utilizing electrostatic-steric stabilized suspensions obtained via high energy ball milling

This manuscript describes a facile alternative route to make thin-film yttria-stabilized zirconia (YSZ) electrolyte by liquid-phase assisted electrophoretic deposition utilizing electrostatic-steric stabilized YSZ suspension followed by sintering. Very fine YSZ particles in ball-milled suspension facilitate their sustained dispersion through electrostatic mechanism as evidenced by their higher zeta potentials. Binder addition into the ball-milled suspension is also demonstrated to contribute complementary steric hindrance effects on suspension stability. As the consequence, the film quality and sinterability improve in the sequence of film made from non ball-milled suspension, film made from ball-milled suspension and film made from ball-milled suspension with binder addition. The specific deposition mechanisms pertaining to each suspension are also postulated and discussed below. A very thin dense electrolyte layer of ∼10 μm can be achieved via electrophoretic deposition route utilizing ball-milled suspension and binder addition. This in turn, makes the electrolyte resistance a more negligible part of the overall cell resistance. Further on, we also tested the performance of SOFC utilizing as-formed 10 μm YSZ electrolyte i.e. YSZ-NiO|YSZ|LSM (La0.8Sr0.2MnO3-δ), whereby a maximum power density of ∼850 mW cm−2 at 850 °C was demonstrated.

Application of the DCT energy histogram for face recognition

In this paper, we investigate the face recognition problem via energy histogram of the DCT coefficients. Several issues related to the recognition performance are discussed, In particular the issue of histogram bin sizes and feature sets. In addition, we propose a technique for selecting the classification threshold incrementally. Experimentation was conducted on the Yale face database and results indicated that the threshold obtained via the proposed technique provides a balanced recognition in term of precision and recall. Furthermore, it demonstrated that the energy histogram algorithm outperformed the well-known Eigenface algorithm.

Face recognition via the overlapping energy histogram

In this paper we investigate the face recognition problem via the overlapping energy histogram of the DCT coefficients. Particularly, we investigate some important issues relating to the recognition performance, such as the issue of selecting threshold and the number of bins. These selection methods utilise information obtained from the training dataset. Experimentation is conducted on the Yale face database and results indicate that the proposed parameter selection methods perform well in selecting the threshold and number of bins. Furthermore, we show that the proposed overlapping energy histogram approach outperforms the Eigenfaces, 2DPCA and energy histogram significantly.

Progress on building energy labelling techniques

The building sector consumes around 30–40 per cent of the primary energy in most developed countries. The importance of labelling buildings as a national strategy for energy efficiency is well recognized worldwide. The last 10–15 years have seen an emergence of programmes in different parts of the world. As seen in the United States, European Union, South America and Asia, there is a collection of rating systems or tools internationally, designed with the intention of evaluating the design, construction and operation of buildings. This study presents an overview and critical reflection on the progress on building energy labelling techniques in recent years. The scope of labelling, methodology and methods of implementation are discussed in detail.

Intelligent energy management for plug-in hybrid electric vehicles : the role of ITS infrastructure in vehicle electrification

The desire to reduce carbon emissions due to transportation sources has led over the past decade to the development of new propulsion technologies, focused on vehicle electrification (including hybrid, plug-in hybrid and battery electric vehicles). These propulsion technologies, along with advances in telecommunication and computing power, have the potential of making passenger and commercial vehicles more energy efficient and environment friendly. In particular, energy management algorithms are an integral part of plug-in vehicles and are very important for achieving the performance benefits. The optimal performance of energy management algorithms depends strongly on the ability to forecast energy demand from the vehicle. Information available about environment (temperature, humidity, wind, road grade, etc.) and traffic (traffic density, traffic lights, etc.), is very important in operating a vehicle at optimal efficiency. This article outlines some current technologies that can help achieving this optimum efficiency goal. In addition to information available from telematic and geographical information systems, knowledge of projected vehicle charging demand on the power grid is necessary to build an intelligent energy management controller for future plug-in hybrid and electric vehicles. The impact of charging millions of vehicles from the power grid could be significant, in the form of increased loading of power plants, transmission and distribution lines, emissions and economics (information are given and discussed for the US case). Therefore, this effect should be considered in an intelligent way by controlling/scheduling the charging through a communication based distributed control.

Stochastic models of road geometry and wind condition for vehicle energy management and control

Modeling and simulation is commonly used to improve vehicle performance, to optimize vehicle system design, and to reduce vehicle development time. Vehicle performances can be affected by environmental conditions and driver behavior factors, which are often uncertain and immeasurable. To incorporate the role of environmental conditions in the modeling and simulation of vehicle systems, both real and artificial data are used. Often, real data are unavailable or inadequate for extensive investigations. Hence, it is important to be able to construct artificial environmental data whose characteristics resemble those of the real data for modeling and simulation purposes. However, to produce credible vehicle simulation results, the simulated environment must be realistic and validated using accepted practices. This paper proposes a stochastic model that is capable of creating artificial environmental factors such as road geometry and wind conditions. In addition, road geometric design principles are employed to modify the created road data, making it consistent with the real-road geometry. Two sets of real-road geometry and wind condition data are employed to propose probability models. To justify the distribution goodness of fit, Pearson's chi-square and correlation statistics have been used. Finally, the stochastic models of road geometry and wind conditions (SMRWs) are developed to produce realistic road and wind data. SMRW can be used to predict vehicle performance, energy management, and control strategies over multiple driving cycles and to assist in developing fuel-efficient vehicles.

Developing a facility for glass façade performance testing

This research aims to investigate whether real spaces can support legitimate measurements on glazing energy and thermal comfort analysis. This paper presents the development of a research facility for doing this. It will test simple to complex glazing and shading systems in a real (occupied) interior office environment. The purpose of this research project is to compare measured results with those being simulated with existing software and to discover discrepancies between simulation and real measured results. What parameters characterize a glazing system, whether simple or complex? Can these parameters be used to predict the energy transfer and comfort in the space? One must begin with simple glazing systems and verify measured with readily known simulated results. It is, at present, very difficult to use geometric based software with thermal based software to predict the performance of complex glazing systems. However, if we can characterize glazing systems with a set of reliable measurements, we can provide the data necessary for predicting performance in a live space. Specifically, the Solar Heat Gain Coefficient (SHGC) is a variable parameter based upon solar incident angle to a glazing system and is intended to be measured in its integral components: solar transmittance and inward-flowing fraction (radiative/convective) heat gain. A new instrumental approach through variable surface coated heat flux meters is being investigated to provide the measurement of interior glazing surface radiative and convective heat gain. The results suggest that this instrumentation may support be a viable method of testing inward-flowing heat gains from the interior glass surface. The test set-up also considers the application of a well-known B&K 1221 Comfort Meter for determining thermal comfort responses in the ‘perimeter zone’ on the interior side of a façade. This work requires further investigation, but is intended to be used in conjunction with solar pyranometers measuring transmittance as well as the heat flux meter and surface temperature instrumentation.

Combinational rate effects on the performance of nano-grained pseudoelastic Nitinols

Combinational loading-unloading rate effects were studied on the behavior of NiTi shape memory alloys (SMAs) under nanoindentation loads. While combinational loading rates showed negligible effects on the performance of NiTi SMAs, the combinational unloading rates did show significant effects on hysteresis energy. The heating-cooling phenomenon during the loading stage and the sole cooling during the unloading stage explain the effects. This study elucidates the nature of thermomechanical SMAs' behaviors during complex compressive loadings with the presence of solid-state phase transition.

Performance, personality, and energetics : correlation, causation, and mechanism

The study of phenotypic evolution should be an integrative endeavor that combines different approaches and crosses disciplinary and phylogenetic boundaries to consider complex traits and organisms that historically have been studied in isolation from each other. Analyses of individual variation within populations can act to bridge studies focused at the levels of morphology, physiology, biochemistry, organismal performance, behavior, and life history. For example, the study of individual variation recently facilitated the integration of behavior into the concept of a pace-of-life syndrome and effectively linked the field of energetics with research on animal personality. Here, we illustrate how studies on the pace-of-life syndrome and the energetics of personality can be integrated within a physiology-performance-behavior-fitness paradigm that includes consideration of ecological context. We first introduce key concepts and definitions and then review the rapidly expanding literature on the links between energy metabolism and personality traits commonly studied in nonhuman animals (activity, exploration, boldness, aggressiveness, sociability). We highlight some empirical literature involving mammals and squamates that demonstrates how emerging fields can develop in rather disparate ways because of historical accidents and/or particularities of different kinds of organisms. We then briefly discuss potentially interesting avenues for future conceptual and empirical research in relation to motivation, intraindividual variation, and mechanisms underlying trait correlations. The integration of performance traits within the pace-of-life-syndrome concept has the potential to fill a logical gap between the context dependency of selection and how energetics and personality are expected to interrelate. Studies of how performance abilities and/or aspects of Darwinian fitness relate to both metabolic rate and personality traits are particularly lacking.