A typology of music distribution models

A typology of music distribution models is proposed consisting of the ownership model, the access model, and the context model. These models are not substitutes for each other and may co‐exist serving different market niches. The paper argues that increasingly the economic value created from recorded music is based on con‐text rather than on ownership. During this process, access‐based services temporarily generate economic value, but such services are destined to eventually become commoditised.

Distribution of NMDA and AMPA receptor subunits at thalamo-amygdaloid dendritic spines

Synapses onto dendritic spines in the lateral amygdala formed by afferents from the auditory thalamus represent a site of plasticity in Pavlovian fear conditioning. Previous work has demonstrated that thalamic afferents synapse onto LA spines expressing glutamate receptor (GluR) subunits, but the GluR subunit distribution at the synapse and within the cytoplasm has not been characterized. Therefore, we performed a quantitative analysis for α-amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA) receptor subunits GluR2 and GluR3 and N-methyl-D-aspartate (NMDA) receptor subunits NR1 and NR2B by combining anterograde labeling of thalamo-amygdaloid afferents with postembedding immunoelectron microscopy for the GluRs in adult rats. A high percentage of thalamo- amygdaloid spines was immunoreactive for GluR2 (80%), GluR3 (83%), and NR1 (83%), while a smaller proportion of spines expressed NR2B (59%). To compare across the various subunits, the cytoplasmic to synaptic ratios of GluRs were measured within thalamo-amygdaloid spines. Analyses revealed that the cytoplasmic pool of GluR2 receptors was twice as large compared to the GluR3, NR1, and NR2B subunits. Our data also show that in the adult brain, the NR2B subunit is expressed in the majority of in thalamo-amygdaloid spines and that within these spines, the various GluRs are differentially distributed between synaptic and non-synaptic sites. The prevalence of the NR2B subunit in thalamo-amygdaloid spines provides morphological evidence supporting its role in the fear conditioning circuit while the differential distribution of the GluR subtypes may reflect distinct roles for their involvement in this circuitry and synaptic plasticity.

The epidemiology of basal cell carcinoma

Basal cell carcinoma (BCC) is a skin cancer of particular importance to the Australian community. Its rate of occurrence is highest in Queensland, where 1% to 2% of people are newly affected annually. This is an order of magnitude higher than corresponding incidence estimates in European and North American populations. Individuals with a sun-sensitive complexion are particularly susceptible because sun exposure is the single most important causative agent, as shown by the anatomic distribution of BCC which is in general consistent with the levels of sun exposure across body sites. A distinguishing feature of BCC is the occurrence of multiple primary tumours within individuals, synchronously or over time, and their diagnosis and treatment costs contribute substantially to the major public health burden caused by BCC. A primary knowledge gap about BCC pathogenesis however was an understanding of the true frequency of multiple BCC occurrences and their body distribution, and why a proportion of people do develop more than one BCC in their life. This research project sought to address this gap under an overarching research aim to better understand the detailed epidemiology of BCC with the ultimate goal of reducing the burden of this skin cancer through prevention. The particular aim was to document prospectively the rate of BCC occurrence and its associations with constitutional and environmental (solar) factors, all the while paying special attention to persons affected by more than one BCC. The study built on previous findings and recent developments in the field but set out to confirm and extend these and propose more adequate theories about the complex epidemiology of this cancer. Addressing these goals required a new approach to researching basal cell carcinoma, due to the need to account for the phenomenon of multiple incident BCCs per person. This was enabled by a 20 year community-based study of skin cancer in Australians that provided the methodological foundation for this thesis. Study participants were originally randomly selected in 1986 from the electoral register of all adult residents of the subtropical township of Nambour in Queensland, Australia. On various occasions during the study, participants were fully examined by dermatologists who documented cumulative photodamage as well as skin cancers. Participants completed standard questionnaires about skin cancer-related factors, and consented to have any diagnosed skin cancers notified to the investigators by regional pathology laboratories in Queensland. These methods allowed 100% ascertainment of histologically confirmed BCCs in this study population. 1339 participants had complete follow-up to the end of 2007. Statistical analyses in this thesis were carried out using SAS and SUDAAN statistical software packages. Modelling methods, including multivariate logistic regressions, allowed for repeated measures in terms of multiple BCCs per person. This innovative approach gave new findings on two levels, presented in five chapters as scientific papers: 1. Incidence of basal cell carcinoma multiplicity and detailed anatomic distribution: longitudinal study of an Australian population The incidence of people affected multiple times by BCC was 705 per 100,000 person years compared to an incidence rate of people singly affected of 935 per 100,000 person years. Among multiply and singly affected persons alike, site-specific BCC incidence rates were far highest on facial subsites, followed by upper limbs, trunk, and then lower limbs 2. Melanocytic nevi and basal cell carcinoma: is there an association? BCC risk was significantly increased in those with forearm nevi (Odds Ratios (OR) 1.43, 95% Confidence Intervals (CI) 1.09-1.89) compared to people without forearm nevi, especially among those who spent their time mainly outdoors (OR 1.6, 95%CI 1.1-2.3) compared to those who spent their time mainly indoors. Nevi on the back were not associated with BCC. 3. Clinical signs of photodamage are associated with basal cell carcinoma multiplicity and site: a 16-year longitudinal study Over a 16-year follow-up period, 58% of people affected by BCC developed more than one BCC. Among these people 60% developed BCCs across different anatomic sites. Participants with high numbers of solar keratoses, compared to people without solar keratoses, were most likely to experience the highest BCC counts overall (OR 3.3, 95%CI 1.4-13.5). Occurrences of BCC on the trunk (OR 3.3, 95%CI 1.4-7.6) and on the limbs (OR 3.7, 95%CI 2.0-7.0) were strongly associated with high numbers of solar keratoses on these sites. 4. Occurrence and determinants of basal cell carcinoma by histological subtype in an Australian community Among 1202 BCCs, 77% had a single growth pattern and 23% were of mixed histological composition. Among all BCCs the nodular followed by the superficial growth patterns were commonest. Risk of nodular and superficial BCCs on the head was raised if 5 or more solar keratoses were present on the face (OR 1.8, 95%CI 1.2-2.7 and OR 4.5, 95%CI 2.1-9.7 respectively) and similarly on the trunk in the presence of multiple solar keratoses on the trunk (OR 4.2, 95%CI 1.5-11.9 and OR 2.2, 95%CI 1.1-4.4 respectively). 5. Basal cell carcinoma and measures of cumulative sun exposure: an Australian longitudinal community-based study Dermal elastosis was more likely to be seen adjacent to head and neck BCCs than trunk BCCs (p=0.01). Severity of dermal elastosis increased on each site with increasing clinical signs of cutaneous sun damage on that site. BCCs that occurred without perilesional elastosis per se, were always found in an anatomic region with signs of photodamage. This thesis thus has identified the magnitude of the burden of multiple BCCs. It does not support the view that people affected by more than one BCC represent a distinct group of people who are prone to BCCs on certain body sites. The results also demonstrate that BCCs regardless of site, histology or order of occurrence are strongly associated with cumulative sun exposure causing photodamage to the skin, and hence challenge the view that BCCs occurring on body sites with typically low opportunities for sun exposure or of the superficial growth pattern are different in their association with the sun from those on typically sun-exposed sites, or nodular BCCs, respectively. Through dissemination in the scientific and medical literature, and to the community at large, these findings can ultimately assist in the primary and secondary prevention of BCC, perhaps especially in high-risk populations.

Statistical modelling of district-level residential electricity use in NSW, Australia

Electricity network investment and asset management require accurate estimation of future demand in energy consumption within specified service areas. For this purpose, simple models are typically developed to predict future trends in electricity consumption using various methods and assumptions. This paper presents a statistical model to predict electricity consumption in the residential sector at the Census Collection District (CCD) level over the state of New South Wales, Australia, based on spatial building and household characteristics. Residential household demographic and building data from the Australian Bureau of Statistics (ABS) and actual electricity consumption data from electricity companies are merged for 74 % of the 12,000 CCDs in the state. Eighty percent of the merged dataset is randomly set aside to establish the model using regression analysis, and the remaining 20 % is used to independently test the accuracy of model prediction against actual consumption. In 90 % of the cases, the predicted consumption is shown to be within 5 kWh per dwelling per day from actual values, with an overall state accuracy of -1.15 %. Given a future scenario with a shift in climate zone and a growth in population, the model is used to identify the geographical or service areas that are most likely to have increased electricity consumption. Such geographical representation can be of great benefit when assessing alternatives to the centralised generation of energy; having such a model gives a quantifiable method to selecting the 'most' appropriate system when a review or upgrade of the network infrastructure is required.

Voltage quality improvement in distribution networks containing DERs using UPQC

Single phase distributed energy resources (DERs) can cause voltage rise along distribution feeder and power imbalance among the phases. Usually transformer tap setting are used to mitigate voltage drop along feeders. However this can aggravate the voltage rise problem when DERs are connected. Moreover if the power generation in a phase is more than its load demand, the excess power in that phase will be fed back to the transmission network. In this paper, a unified power quality compensator (UPQC) has been utilized to alleviate the voltage quality excess power circulation problems. Through analysis and simulation results, the mode of operation of UPQC is highlighted. The proposals are validated through extensive digital computer simulation studies using PSCAD and MATLAB.

Distribution tap changer adjustment to improve small-scale embedded generator penetration and mitigate voltage rise

This paper addresses the voltage rise constraints that are initiated from increased renewable generation resources in low voltage distribution networks. In this paper, an approach which is able to mitigate these voltage rise constraints and allow for increased distributed generator penetration is presented. The proposed approach involves utilizing the distribution transformers static tap changer to reduce the distribution feeder voltage setpoint. The proposed approach is modeled on a generic low voltage distribution network using the PSS SINCAL© simulation software package and is also implemented in a real low voltage distribution network to verify its practicality. Results indicate that this approach can be implemented to mitigate the voltage rise constraint and increase small-scale embedded generator penetration in a high proportion of low voltage feeders while avoiding any substantial network costs.

Smart Inter-Phase Switching of Residential Loads in Low Voltage Distribution Feeders

In order to dynamically reduce voltage unbalance along a low voltage distribution feeder, a smart residential load transfer system is discussed. In this scheme, residential loads can be transferred from one phase to another to minimize the voltage unbalance along the feeder. Each house is supplied through a static transfer switch and a controller. The master controller, installed at the transformer, observes the power consumption in each house and will determine which house(s) should be transferred from an initially connected phase to another in order to keep the voltage unbalance minimum. The performance of the smart load transfer scheme is demonstrated by simulations.

On-line Demand Management of Low Voltage Residential Distribution Networks in Smart Grids

A novel intelligent online demand management system is discussed in this chapter for peak load management in low voltage residential distribution networks based on the smart grid concept. The discussed system also regulates the network voltage, balances the power in three phases and coordinates the energy storage within the network. This method uses low cost controllers, with two-way communication interfaces, installed in costumers’ premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by a MATLAB-based simulation which includes detailed modeling of residential loads and the network.

An efficient hybrid evolutionary optimization algorithm for daily volt/var control at distribution system including DGs

This paper presents a new hybrid evolutionary algorithm based on Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) for daily Volt/Var control in distribution system including Distributed Generators (DGs). Due to the small X/R ratio and radial configuration of distribution systems, DGs have much impact on this problem. Since DGs are independent power producers or private ownership, a price based methodology is proposed as a proper signal to encourage owners of DGs in active power generation. Generally, the daily Volt/Var control is a nonlinear optimization problem. Therefore, an efficient hybrid evolutionary method based on Particle Swarm Optimization and Ant Colony Optimization (ACO), called HPSO, is proposed to determine the active power values of DGs, reactive power values of capacitors and tap positions of transformers for the next day. The feasibility of the proposed algorithm is demonstrated and compared with methods based on the original PSO, ACO and GA algorithms on IEEE 34-bus distribution feeder.

Distribution harmonic state estimation based on a modified PSO considering parameters uncertainty

This paper presents a new algorithm based on a Modified Particle Swarm Optimization (MPSO) to estimate the harmonic state variables in a distribution networks. The proposed algorithm performs the estimation for both amplitude and phase of each injection harmonic currents by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as the uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WTs). The main features of the proposed MPSO algorithm are usage of a primary and secondary PSO loop and applying the mutation function. The simulation results on 34-bus IEEE radial and a 70-bus realistic radial test networks are presented. The results demonstrate that the speed and the accuracy of the proposed Distribution Harmonic State Estimation (DHSE) algorithm are very excellent compared to the algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO, and Honey Bees Mating Optimization (HBMO).

Loss reduction experiences in electric power distribution companies of Iran

The experiences of the loss reduction projects in electric power distribution companies (EPDCs) of Iran are presented. The loss reduction methods, which are proposed individually by 14 EPDCs, corresponding energy saving (ES), Investment costs (IC), and loss rate reductions are provided. In order to illustrate the effectiveness and performance of the loss reduction methods, three parameters are proposed as energy saving per investment costs (ESIC), energy saving per quantity (ESPQ), and investment costs per quantity (ICPQ). The overall ESIC of 14 EPDC as well as individual average and standard deviation of the EISC for each method is presented and compared. In addition, the average and standard deviation of the ESPQs and ICPQs for the loss reduction methods, individually, are provided and investigated. These parameters are useful for EPDCs that intend to reduce the electric losses in distribution networks as a benchmark and as a background in the planning purposes.

Loss reduction planning in electric distribution networks of IRAN until 2025

In this paper, a loss reduction planning in electric distribution networks is presented based on the successful experiences in distribution utilities of IRAN and some developed countries. The necessary technical and economical parameters of planning are calculated from related projects in IRAN. Cost, time, and benefits of every sub-program including seven loss reduction approaches are determined. Finally, the loss reduction program, the benefit per cost, and the return of investment in optimistic and pessimistic conditions are introduced.

A novel algorithm based on honey bee mating optimization for distribution harmonic state estimation including distributed generators

This paper presents a new algorithm based on honey-bee mating optimization (HBMO) to estimate harmonic state variables in distribution networks including distributed generators (DGs). The proposed algorithm performs estimation for both amplitude and phase of each harmonics by minimizing the error between the measured values from phasor measurement units (PMUs) and the values computed from the estimated parameters during the estimation process. Simulation results on two distribution test system are presented to demonstrate that the speed and accuracy of proposed distribution harmonic state estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as weight least square (WLS), genetic algorithm (GA) and tabu search (TS).

Load profile based determination of distribution feeder configuration by dynamic programming

This paper presents a new method to determine feeder reconfiguration scheme considering variable load profile. The objective function consists of system losses, reliability costs and also switching costs. In order to achieve an optimal solution the proposed method compares these costs dynamically and determines when and how it is reasonable to have a switching operation. The proposed method divides a year into several equal time periods, then using particle swarm optimization (PSO), optimal candidate configurations for each period are obtained. System losses and customer interruption cost of each configuration during each period is also calculated. Then, considering switching cost from a configuration to another one, dynamic programming algorithm (DPA) is used to determine the annual reconfiguration scheme. Several test systems were used to validate the proposed method. The obtained results denote that to have an optimum solution it is necessary to compare operation costs dynamically.

A novel hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration with regard to DGs

This paper presents an efficient hybrid evolutionary optimization algorithm based on combining Ant Colony Optimization (ACO) and Simulated Annealing (SA), called ACO-SA, for distribution feeder reconfiguration (DFR) considering Distributed Generators (DGs). Due to private ownership of DGs, a cost based compensation method is used to encourage DGs in active and reactive power generation. The objective function is summation of electrical energy generated by DGs and substation bus (main bus) in the next day. The approach is tested on a real distribution feeder. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for solving DFR problem.