Timing and distribution of protein ingestion during prolonged recovery from resistance exercise alters myofibrillar protein synthesis

Quantity and timing of protein ingestion are major factors regulating myofibrillar protein synthesis (MPS). However, the effect of specific ingestion patterns on MPS throughout a 12 h period is unknown. We determined how different distributions of protein feeding during 12 h recovery after resistance exercise affects anabolic responses in skeletal muscle. Twenty-four healthy trained males were assigned to three groups (n = 8/group) and undertook a bout of resistance exercise followed by ingestion of 80 g of whey protein throughout 12 h recovery in one of the following protocols: 8 × 10 g every 1.5 h (PULSE); 4 × 20 g every 3 h (intermediate: INT); or 2 × 40 g every 6 h (BOLUS). Muscle biopsies were obtained at rest and after 1, 4, 6, 7 and 12 h post exercise. Resting and post-exercise MPS (l-[ring-(13)C6] phenylalanine), and muscle mRNA abundance and cell signalling were assessed. All ingestion protocols increased MPS above rest throughout 1-12 h recovery (88-148%, P < 0.02), but INT elicited greater MPS than PULSE and BOLUS (31-48%, P < 0.02). In general signalling showed a BOLUS>INT>PULSE hierarchy in magnitude of phosphorylation. MuRF-1 and SLC38A2 mRNA were differentially expressed with BOLUS. In conclusion, 20 g of whey protein consumed every 3 h was superior to either PULSE or BOLUS feeding patterns for stimulating MPS throughout the day. This study provides novel information on the effect of modulating the distribution of protein intake on anabolic responses in skeletal muscle and has the potential to maximize outcomes of resistance training for attaining peak muscle mass.

Integrated Lean Six Sigma approach for patient flow improvement in hospital emergency department

Because of increased competition between healthcare providers, higher customer expectations, stringent checks on insurance payments and new government regulations, it has become vital for healthcare organisations to enhance the quality of the care they provide, to increase efficiency, and to improve the cost effectiveness of their services. Consequently, a number of quality management concepts and tools are employed in the healthcare domain to achieve the most efficient ways of using time, manpower, space and other resources. Emergency departments are designed to provide a high-quality medical service with immediate availability of resources to those in need of emergency care. The challenge of maintaining a smooth flow of patients in emergency departments is a global problem. This study attempts to improve the patient flow in emergency departments by considering Lean techniques and Six Sigma methodology in a comprehensive conceptual framework. The proposed research will develop a systematic approach through integration of Lean techniques with Six Sigma methodology to improve patient flow in emergency departments. The results reported in this paper are based on a standard questionnaire survey of 350 patients in the Emergency Department of Aseer Central Hospital in Saudi Arabia. The results of the study led us to determine the most significant variables affecting patient satisfaction with patient flow, including waiting time during patient treatment in the emergency department; effectiveness of the system when dealing with the patient’s complaints; and the layout of the emergency department. The proposed model will be developed within a performance evaluation metric based on these critical variables, to be evaluated in future work within fuzzy logic for continuous quality improvement.

Better understanding of food material on the basis of water distribution using Thermogravimetric analysis

The prime objective of drying is to enhance shelf life of perishable food materials. As the process is very energy intensive in nature, researchers are trying to minimise energy consumption in the drying process. In order to determine the exact amount of energy needed for drying a food product, understanding the physics of moisture distribution and bond strength of water within the food material is essential. In order understand the critical moisture content, moisture distribution and water bond strength in food material, Thermogravimetric analysis (TGA) can be properly utilised. This work has been conducted to investigate moisture distribution and water bond strength in selected food materials; apple, banana and potato. It was found that moisture distribution and water bond strength influence moisture migration from the food materials. In addition, proportion of different types of water (bound, free, surface water) has been simply identified using TGA. This study provides a better understanding of water contents and its role in drying rate and energy consumption.

Characteristics of nontuberculous mycobacteria from a municipal water distribution system and their relevance to human infections

This thesis documented pathogenic species of nontuberculous mycobacteria in the Brisbane water distribution system. When water and shower aerosol strains were compared with human strains of mycobacteria, the study found that the likelihood of acquiring infection from municipal water was specific for four main species. The method for isolation of mycobacteria from water was refined, followed by sampling from 220 sites across Brisbane. A variety of species (incl 15 pathogens) were identified and genotypically compared to human strains. For M. abscessus and M. lentiflavum, water strains clustered with human strains. Pathogenic strains of M. kansasii were found, though non-pathogenic strains dominated. Waterborne strains of M. fortuitum differed to human strains. Extensive home sampling of 20 patients with NTM disease, supported the theory that the risk of acquiring NTM from water or shower aerosols appears species specific for M. avium, M. kansasii, M. lentiflavum and M. abscessus.

Changes in the site distribution of common melanoma subtypes in Queensland, Australia over time: implications for public health campaigns

Abstract BACKGROUND: An examination of melanoma incidence according to anatomical region may be one method of monitoring the impact of public health initiatives. OBJECTIVES:   To examine melanoma incidence trends by body site, sex and age at diagnosis or body site and morphology in a population at high risk. MATERIALS AND METHODS:   Population-based data on invasive melanoma cases (n = 51473) diagnosed between 1982 and 2008 were extracted from the Queensland Cancer Registry. Age-standardized incidence rates were calculated using the direct method (2000 world standard population) and joinpoint regression models were used to fit trend lines. RESULTS:   Significantly decreasing trends for melanomas on the trunk and upper limbs/shoulders were observed during recent years for both sexes under the age of 40 years and among males aged 40-59years. However, in the 60 and over age group, the incidence of melanoma is continuing to increase at all sites (apart from the trunk) for males and on the scalp/neck and upper limbs/shoulders for females. Rates of nodular melanoma are currently decreasing on the trunk and lower limbs. In contrast, superficial spreading melanoma is significantly increasing on the scalp/neck and lower limbs, along with substantial increases in lentigo maligna melanoma since the late 1990s at all sites apart from the lower limbs. CONCLUSIONS:   In this large study we have observed significant decreases in rates of invasive melanoma in the younger age groups on less frequently exposed body sites. These results may provide some indirect evidence of the impact of long-running primary prevention campaigns.

A novel real time pricing scheme for demand response in residential distribution systems

Price based technique is one way to handle increase in peak demand and deal with voltage violations in residential distribution systems. This paper proposes an improved real time pricing scheme for residential customers with demand response option. Smart meters and in-home display units are used to broadcast the price and appropriate load adjustment signals. Customers are given an opportunity to respond to the signals and adjust the loads. This scheme helps distribution companies to deal with overloading problems and voltage issues in a more efficient way. Also, variations in wholesale electricity prices are passed on to electricity customers to take collective measure to reduce network peak demand. It is ensured that both customers and utility are benefitted by this scheme.

Mathematical modelling of counter flow v-grove solar air collector

Double-pass counter flow v-grove collector is considered one of the most efficient solar air-collectors. In this design of the collector, the inlet air initially flows at the top part of the collector and changes direction once it reaches the end of the collector and flows below the collector to the outlet. A mathematical model is developed for this type of collector and simulation is carried out using MATLAB programme. The simulation results were verified with three distinguished research results and it was found that the simulation has the ability to predict the performance of the air collector accurately as proven by the comparison of experimental data with simulation. The difference between the predicted and experimental results is, at maximum, approximately 7% which is within the acceptable limit considering some uncertainties in the input parameter values to allow comparison. A parametric study was performed and it was found that solar radiation, inlet air temperature, flow rate and length have a significant effect on the efficiency of the air collector. Additionally, the results are compared with single flow V-groove collector.

Local stress-strain distribution and load transfer across cartilage matrix at micro-scale using combined microscopy-based finite element method

Articular cartilage is the load-bearing tissue that consists of proteoglycan macromolecules entrapped between collagen fibrils in a three-dimensional architecture. To date, the drudgery of searching for mathematical models to represent the biomechanics of such a system continues without providing a fitting description of its functional response to load at micro-scale level. We believe that the major complication arose when cartilage was first envisaged as a multiphasic model with distinguishable components and that quantifying those and searching for the laws that govern their interaction is inadequate. To the thesis of this paper, cartilage as a bulk is as much continuum as is the response of its components to the external stimuli. For this reason, we framed the fundamental question as to what would be the mechano-structural functionality of such a system in the total absence of one of its key constituents-proteoglycans. To answer this, hydrated normal and proteoglycan depleted samples were tested under confined compression while finite element models were reproduced, for the first time, based on the structural microarchitecture of the cross-sectional profile of the matrices. These micro-porous in silico models served as virtual transducers to produce an internal noninvasive probing mechanism beyond experimental capabilities to render the matrices micromechanics and several others properties like permeability, orientation etc. The results demonstrated that load transfer was closely related to the microarchitecture of the hyperelastic models that represent solid skeleton stress and fluid response based on the state of the collagen network with and without the swollen proteoglycans. In other words, the stress gradient during deformation was a function of the structural pattern of the network and acted in concert with the position-dependent compositional state of the matrix. This reveals that the interaction between indistinguishable components in real cartilage is superimposed by its microarchitectural state which directly influences macromechanical behavior.

A coordinated voltage control approach for coordination of OLTC, voltage regulator and DG to regulate voltage in a distribution feeder

Integration of small-scale electricity generators, known as Distributed Generation (DG), into the distribution networks has become increasingly popular at the present. This tendency together with the falling price of synchronous-type generator has potential to give the DG a better chance in participating in the voltage regulation process together with other devices already available in the system. The voltage control issue turns out to be a very challenging problem for the distribution engineers since existing control coordination schemes would need to be reconsidered to take into account the DG operation. In this paper, we propose a control coordination technique, which is able to utilize the ability of the DG as a voltage regulator, and at the same time minimizes interaction with other active devices, such as On-load Tap Changing Transformer (OLTC) and voltage regulator. The technique has been developed based on the concept of control zone, Line Drop Compensation (LDC), as well as the choice of controller's parameters. Simulations carried out on an Australian system show that the technique is suitable and flexible for any system with multiple regulating devices including DG.

Impact of high PV penetration on distribution transformer insulation life

The reliable operation of distribution systems is critically dependent on detailed understanding of load impacts on distribution transformer insulation systems. This paper estimates the impact of rooftop photovoltaic (PV) generation on a typical 200-kVA, 22/0.415-kV distribution transformer life under different operating conditions. This transformer supplies a suburban area with a high penetration of roof top photovoltaic systems. The transformer loads and the phase distribution of the PV systems are significantly unbalanced. Oil and hot-spot temperature and remnant life of distribution transformer under different PV and balance scenarios are calculated. It is shown that PV can significantly extend the transformer life.

Predicting voltage unbalance impacts of plug-in electric vehicles penetration in residential low-voltage distribution networks

Plug-in electric vehicles will soon be connected to residential distribution networks in high quantities and will add to already overburdened residential feeders. However, as battery technology improves, plug-in electric vehicles will also be able to support networks as small distributed generation units by transferring the energy stored in their battery into the grid. Even though the increase in the plug-in electric vehicle connection is gradual, their connection points and charging/discharging levels are random. Therefore, such single-phase bidirectional power flows can have an adverse effect on the voltage unbalance of a three-phase distribution network. In this article, a voltage unbalance sensitivity analysis based on charging/discharging levels and the connection point of plug-in electric vehicles in a residential low-voltage distribution network is presented. Due to the many uncertainties in plug-in electric vehicle ratings and connection points and the network load, a Monte Carlo-based stochastic analysis is developed to predict voltage unbalance in the network in the presence of plug-in electric vehicles. A failure index is introduced to demonstrate the probability of non-standard voltage unbalance in the network due to plug-in electric vehicles.

The future of the music industry in an age of digital distribution

This is an invited public lecture. The talk will cover how the music industry has changed due to digital technologies. During the talk I will look at how the changing balance between live music, music licensing and recorded music. I will also discuss online music subscription services and whether they might be a future for music distribution in China and elsewhere in the world. It will also look at how music artists and composers are affected by this change.

The distribution of absorptive capacity among construction supply chain participants

The absorptive capacity of organisations is one of the key drivers of innovation performance in any industry. This research seeks to refine our understanding of the relationship between absorptive capacity and innovation performance, with a focus on characterising the absorptive capacity of the different participant groups within the Australian road industry supply chain. One of the largest and most comprehensive surveys ever undertaken of innovation in road construction was completed in 2011 by the Queensland University of Technology (QUT), based on the Australian road industry. The survey of over 200 construction industry participants covered four sectors, comprising suppliers (manufacturers and distributors), consultants (engineering consultants), contractors (head and subcontractors) and clients (state government road agencies). The survey measured the absorptive capacity and innovation activity exhibited by organisations within each of these participant groups, using the perceived importance of addressing innovation obstacles as a proxy for innovation activity. One of the key findings of the survey is about the impact of participant competency on product innovation activity. The survey found that the absorptive capacity of industry participants had a significant and positive relationship with innovation activity. Regarding the distribution of absorptive capacity, the results indicate that suppliers are more likely to have high levels of absorptive capacity than the other participant groups, with 32% of suppliers showing high absorptive capacity, ahead of contractors (18%), consultants (11%), and clients (7%). These results support the findings of previous studies in the literature and suggest the importance of policies to enhance organisational learning, particularly in relation to openness to new product ideas.

Coordinated control of grid connected photovoltaic reactive power and battery energy storage systems to improve the voltage profile of a residential distribution feeder

Increasing penetration of photovoltaic (PV) as well as increasing peak load demand has resulted in poor voltage profile for some residential distribution networks. This paper proposes coordinated use of PV and Battery Energy Storage (BES) to address voltage rise and/or dip problems. The reactive capability of PV inverter combined with droop based BES system is evaluated for rural and urban scenarios (having different R/X ratios). Results show that reactive compensation from PV inverters alone is sufficient to maintain acceptable voltage profile in an urban scenario (low resistance feeder), whereas, coordinated PV and BES support is required for the rural scenario (high resistance feeder). Constant as well as variable droop based BES schemes are analyzed. The required BES sizing and associated cost to maintain the acceptable voltage profile under both schemes is presented. Uncertainties in PV generation and load are considered, with probabilistic estimation of PV generation and randomness in load modeled to characterize the effective utilization of BES. Actual PV generation data and distribution system network data is used to verify the efficacy of the proposed method.

Building adaptable agent-based models – application to the electricity distribution network

Agent-based modelling (ABM), like other modelling techniques, is used to answer specific questions from real world systems that could otherwise be expensive or impractical. Its recent gain in popularity can be attributed to some degree to its capacity to use information at a fine level of detail of the system, both geographically and temporally, and generate information at a higher level, where emerging patterns can be observed. This technique is data-intensive, as explicit data at a fine level of detail is used and it is computer-intensive as many interactions between agents, which can learn and have a goal, are required. With the growing availability of data and the increase in computer power, these concerns are however fading. Nonetheless, being able to update or extend the model as more information becomes available can become problematic, because of the tight coupling of the agents and their dependence on the data, especially when modelling very large systems. One large system to which ABM is currently applied is the electricity distribution where thousands of agents representing the network and the consumers’ behaviours are interacting with one another. A framework that aims at answering a range of questions regarding the potential evolution of the grid has been developed and is presented here. It uses agent-based modelling to represent the engineering infrastructure of the distribution network and has been built with flexibility and extensibility in mind. What distinguishes the method presented here from the usual ABMs is that this ABM has been developed in a compositional manner. This encompasses not only the software tool, which core is named MODAM (MODular Agent-based Model) but the model itself. Using such approach enables the model to be extended as more information becomes available or modified as the electricity system evolves, leading to an adaptable model. Two well-known modularity principles in the software engineering domain are information hiding and separation of concerns. These principles were used to develop the agent-based model on top of OSGi and Eclipse plugins which have good support for modularity. Information regarding the model entities was separated into a) assets which describe the entities’ physical characteristics, and b) agents which describe their behaviour according to their goal and previous learning experiences. This approach diverges from the traditional approach where both aspects are often conflated. It has many advantages in terms of reusability of one or the other aspect for different purposes as well as composability when building simulations. For example, the way an asset is used on a network can greatly vary while its physical characteristics are the same – this is the case for two identical battery systems which usage will vary depending on the purpose of their installation. While any battery can be described by its physical properties (e.g. capacity, lifetime, and depth of discharge), its behaviour will vary depending on who is using it and what their aim is. The model is populated using data describing both aspects (physical characteristics and behaviour) and can be updated as required depending on what simulation is to be run. For example, data can be used to describe the environment to which the agents respond to – e.g. weather for solar panels, or to describe the assets and their relation to one another – e.g. the network assets. Finally, when running a simulation, MODAM calls on its module manager that coordinates the different plugins, automates the creation of the assets and agents using factories, and schedules their execution which can be done sequentially or in parallel for faster execution. Building agent-based models in this way has proven fast when adding new complex behaviours, as well as new types of assets. Simulations have been run to understand the potential impact of changes on the network in terms of assets (e.g. installation of decentralised generators) or behaviours (e.g. response to different management aims). While this platform has been developed within the context of a project focussing on the electricity domain, the core of the software, MODAM, can be extended to other domains such as transport which is part of future work with the addition of electric vehicles.