Artificial neural network application in short-term prediction in an oscillating water column

Oscillating Water Column (OWC) is one type of promising wave energy devices due to its obvious advantage over many other wave energy converters: no moving component in sea water. Two types of OWCs (bottom-fixed and floating) have been widely investigated, and the bottom-fixed OWCs have been very successful in several practical applications. Recently, the proposal of massive wave energy production and the availability of wave energy have pushed OWC applications from near-shore to deeper water regions where floating OWCs are a better choice. For an OWC under sea waves, the air flow driving air turbine to generate electricity is a random process. In such a working condition, single design/operation point is nonexistent. To improve energy extraction, and to optimise the performance of the device, a system capable of controlling the air turbine rotation speed is desirable. To achieve that, this paper presents a short-term prediction of the random, process by an artificial neural network (ANN), which can provide near-future information for the control system. In this research, ANN is explored and tuned for a better prediction of the airflow (as well as the device motions for a wide application). It is found that, by carefully constructing ANN platform and optimizing the relevant parameters, ANN is capable of predicting the random process a few steps ahead of the real, time with a good accuracy. More importantly, the tuned ANN works for a large range of different types of random, process.

Short-term metabolic and growth responses of the cold-water coral lophelia pertusa to ocean acidification

Cold-water corals are amongst the most three-dimensionally complex deep-sea habitats known and are associated with high local biodiversity. Despite their importance as ecosystem engineers, little is known about how these organisms will respond to projected ocean acidification. Since preindustrial times, average ocean pH has already decreased from 8.2 to ~ 8.1. Predicted CO2 emissions will decrease this by up to another 0.3 pH units by the end of the century. This decrease in pH may have a wide range of impacts upon marine life, and in particular upon calcifiers such as cold-water corals. Lophelia pertusa is the most widespread cold-water coral (CWC) species, frequently found in the North Atlantic. Data here relate to a short term data set (21 days) on metabolism and net calcification rates of freshly collected L. pertusa from Mingulay Reef Complex, Scotland. These data from freshly collected L. pertusa from the Mingulay Reef Complex will help define the impact of ocean acidification upon the growth, physiology and structural integrity of this key reef framework forming species.

Effect of enhanced pCO2 levels on the production of dissolved organic carbon and transparent exopolymer particles in short-term bioassay experiments

It has been proposed that increasing levels of pCO2 in the surface ocean will lead to more partitioning of the organic carbon fixed by marine primary production into the dissolved rather than the particulate fraction. This process may result in enhanced accumulation of dissolved organic carbon (DOC) in the surface ocean and/or concurrent accumulation of transparent exopolymer particles (TEPs), with important implications for the functioning of the marine carbon cycle. We investigated this in shipboard bioassay experiments that considered the effect of four different pCO2 scenarios (ambient, 550, 750 and 1000 µatm) on unamended natural phytoplankton communities from a range of locations in the northwest European shelf seas. The environmental settings, in terms of nutrient availability, phytoplankton community structure and growth conditions, varied considerably between locations. We did not observe any strong or consistent effect of pCO2 on DOC production. There was a significant but highly variable effect of pCO2 on the production of TEPs. In three of the five experiments, variation of TEP production between pCO2 treatments was caused by the effect of pCO2 on phytoplankton growth rather than a direct effect on TEP production. In one of the five experiments, there was evidence of enhanced TEP production at high pCO2 (twice as much production over the 96 h incubation period in the 750 ?atm treatment compared with the ambient treatment) independent of indirect effects, as hypothesised by previous studies. Our results suggest that the environmental setting of experiments (community structure, nutrient availability and occurrence of phytoplankton growth) is a key factor determining the TEP response to pCO2 perturbations.

Under-ice export flux measurements by short-term drifting sediment traps at 27 stations in the Arctic Ocean during summer 1995, 1997, and 2012

A critical question regarding the organic carbon cycle in the Arctic Ocean is whether the decline in ice extent and thickness and the associated increase in solar irradiance in the upper ocean will result in increased primary production and particulate organic carbon (POC) export. To assess spatial and temporal variability in POC export, under-ice export fluxes were measured with short-term sediment traps in the northern Laptev Sea in July-August-September 1995, north of the Fram Strait in July 1997, and in the Central Arctic in August-September 2012. Sediment traps were deployed at 2-5 m and 20-25 m under ice for periods ranging from 8.5 to 71 h. In addition to POC fluxes, total particulate matter, chlorophyll a, biogenic particulate silica, phytoplankton, and zooplankton fecal pellet fluxes were measured to evaluate the amount and composition of the material exported in the upper Arctic Ocean. Whereas elevated export fluxes observed on and near the Laptev Sea shelf were likely the combined result of high primary production, resuspension, and release of particulate matter from melting ice, low export fluxes above the central basins despite increased light availability during the record minimum ice extent of 2012 suggest that POC export was limited by nutrient supply during summer. These results suggest that the ongoing decline in ice cover affects export fluxes differently on Arctic shelves and over the deep Arctic Ocean and that POC export is likely to remain low above the central basins unless additional nutrients are supplied to surface waters.

A comparative study: long and short term effect of a nutrition sensitive approach to delay the progression of HIV to AIDS among people living with HIV (PLWH) in Nigeria

Background: Malnutrition has a negative impact on optimal immune function, thus increasing susceptibility to morbidity and mortality among HIV positive patients. Evidence indicates that the prevalence of macro and micronutrient deficiencies (particularly magnesium, selenium, zinc, and vitamin C) has a negative impact on optimal immune function, through the progressive depletion of CD4 T-lymphocyte cells, which thereby increases susceptibility to morbidity and mortality among PLWH. Objective: To assess the short and long term effects of a nutrition sensitive intervention to delay the progression of human immune-deficiency virus (HIV) to AIDS among people living with HIV in Abuja, Nigeria. Methods: A randomized control trial was carried out on 400 PLWH (adult, male and female of different religious background) in Nigeria between January and December 2012. Out of these 400 participants, 100 were randomly selected for the pilot study, which took place over six months (January to June, 2012). The participants in the pilot study overlapped to form part of the scale-up participants (n 400) monitored from June to December 2012. The comparative effect of daily 354.92 kcal/d optimized meals consumed for six and twelve months was ascertained through the nutritional status and biochemical indices of the study participants (n=100 pilot interventions), who were and were not taking the intervention meal. The meal consisted of: Glycine max 50g (Soya bean); Pennisetum americanum 20g (Millet); Moringa oleifera 15g (Moringa); Daucus carota spp. sativa 15g (Carrot). Results: At the end of sixth month intervention, mean CD4 cell count (cell/mm3) for Pre-ART and ART Test groups increased by 6.31% and 12.12% respectively. Mean mid upper arm circumference (MUAC) for Pre-ART and ART Test groups increased by 2.72% and 2.52% within the same period (n 400). Comparatively, participants who overlapped from pilot to scale-up intervention (long term use, n 100) were assessed for 12 months. Mean CD4 cell count (cell/mm3) for Pre-ART and ART test groups increased by 2.21% and 12.14%. Mean MUAC for Pre-ART and ART test groups increased by 2.08% and 3.95% respectively. Moreover, student’s t-test analysis suggests a strong association between the intervention meal, MUAC, and CD4 count on long term use of optimized meal in the group of participants being treated with antiretroviral therapy (ART) (P<0.05). Conclusion: Although the achieved results take the form of specific technology, it suggests that a prolong consumption of the intervention meal will be suitable to sustain the gained improvements in the anthropometric and biochemical indices of PLWHIV in Nigeria.

Designing Short Term Wave Traces to Assess Wave Power Devices

In recent years modern numerical methods have been employed in the design of Wave Energy Converters (WECs), however the high computational costs associated with their use makes it prohibitive to undertake simulations involving statistically relevant numbers of wave cycles. Experimental tests in wave tanks could also be performed more efficiently and economically if short time traces, consisting of only a few wave cycles, could be used to evaluate the hydrodynamic characteristics of a particular device or design modification. Ideally, accurate estimations of device performance could be made utilizing results obtained from investigations with a relatively small number of wave cycles. However the difficulty here is that many WECs, such as the Oscillating Wave Surge Converter (OWSC), exhibit significant non-linearity in their response. Thus it is challenging to make accurate predictions of annual energy yield for a given spectral sea state using short duration realisations of that sea. This is because the non-linear device response to particular phase couplings of sinusoidal components within those time traces might influence the estimate of mean power capture obtained. As a result it is generally accepted that the most appropriate estimate of mean power capture for a sea state be obtained over many hundreds (or thousands) of wave cycles. This ensures that the potential influence of phase locking is negligible in comparison to the predictions made. In this paper, potential methods of providing reasonable estimates of relative variations in device performance using short duration sea states are introduced. The aim of the work is to establish the shortness of sea state required to provide statistically significant estimations of the mean power capture of a particular type of Wave Energy Converter. The results show that carefully selected wave traces can be used to reliably assess variations in power output due to changes in the hydrodynamic design or wave climate. 

ARB: Phase II window of opportunity study of short-term preoperative treatment with enzalutamide in ER-positive and triple-negative breast cancer

The androgen receptor (AR) is expressed in 60-80% of breast cancers (BC) across all molecular phenotypes, with a higher incidence in oestrogen receptor positive (ER+) BC compared to ER negative tumours. In ER+ disease, AR-expression has been linked to endocrine resistance which might be reversed with combined treatment targeting ER and AR. In triple negative BCs (TNBC), preclinical and clinical investigations have described a subset of patients that express the AR and are sensitive to androgen blockade, providing a novel therapeutic target. Enzalutamide, a potent 2nd generation anti-androgen, has demonstrated substantial preclinical and clinical anti-tumour activity in AR+ breast cancer. Short-term preoperative window of opportunity studies are a validated strategy for novel treatments to provide proof-of-concept and define the most appropriate patient population by directly assessing treatment effects in tumour tissue before and after treatment. The ARB study aims to assess the anti-tumour effects of enzalutamide in early ER+ breast cancer and TNBC, to identify the optimal target population for further studies and to directly explore the biologic effects of enzalutamide on BC and stromal cells. Methods: ARB is an international, investigator sponsored WOO phase II study in women with newly diagnosed primary ER+ BC or AR+ TNBC of ≥ 1cm. The study has two cohorts. In the ER+ cohort, postmenopausal patients will be randomised 2:1 to receive either enzalutamide (160mg OD) plus exemestane (50mg OD) or exemestane (25mg OD). In the TNBC cohort, AR+ will receive single agent treatment with enzalutamide (160mg OD). Study treatment is planned for 15–29 days, followed by surgery or neo-adjuvant therapy. Tissue and blood samples are collected before treatment and on the last day of study treatment. The primary endpoint is inhibition of tumour-cell proliferation, as measured by change in Ki67 expression, determined centrally by 2 investigators. Secondary endpoints include induction of apoptosis (Caspase3), circulating hormone levels and safety. ARB aims to recruit ≈235 patients from ≈40 sites in the UK, Germany, Spain and USA. The study is open to recruitment.

Coupling short-term (B2G model) and long-term (g-function) models for ground source heat exchanger simulation in TRNSYS. Application in a real installation

Ground-source heat pump (GSHP) systems represent one of the most promising techniques for heating and cooling in buildings. These systems use the ground as a heat source/sink, allowing a better efficiency thanks to the low variations of the ground temperature along the seasons. The ground-source heat exchanger (GSHE) then becomes a key component for optimizing the overall performance of the system. Moreover, the short-term response related to the dynamic behaviour of the GSHE is a crucial aspect, especially from a regulation criteria perspective in on/off controlled GSHP systems. In this context, a novel numerical GSHE model has been developed at the Instituto de Ingeniería Energética, Universitat Politècnica de València. Based on the decoupling of the short-term and the long-term response of the GSHE, the novel model allows the use of faster and more precise models on both sides. In particular, the short-term model considered is the B2G model, developed and validated in previous research works conducted at the Instituto de Ingeniería Energética. For the long-term, the g-function model was selected, since it is a previously validated and widely used model, and presents some interesting features that are useful for its combination with the B2G model. The aim of the present paper is to describe the procedure of combining these two models in order to obtain a unique complete GSHE model for both short- and long-term simulation. The resulting model is then validated against experimental data from a real GSHP installation.

Short-term wind power forecast based on cluster analysis and artificial neural networks

[EN]In this paper an architecture for an estimator of short-term wind farm power is proposed. The estimator is made up of a Linear Machine classifier and a set of k Multilayer Perceptrons, training each one for a specific subspace of the input space. The splitting of the input dataset into the k clusters is done using a k-means technique, obtaining the equivalent Linear Machine classifier from the cluster centroids...

Short-term Trading in Long-term Funds: Implications for Financial Managers

Most hospitality firms do not consider managing stock portfolios to be a main part of their operations. They are in the service business, using their real assets and the services provided by employees to create valuable experiences for guests. However, the need to focus on stock investments arises through those employees. Employees consistently rank benefits, including retirement benefits, among the top five contributors to job satisfaction and as a key consideration in accepting a job.1 It is not surprising, then, that more than 90 percent of companies with 500 or more employees offer retirement plans. The five largest hotel companies in the U.S. have over $10 billion in assets under management in their retirement plans, making these plans a key component in retirement investment decisions.

Using the interaural time difference and cross-correlation to localise short-term complex noises

The mammalian binaural cue of interaural time difference (ITD) and cross-correlation have long been used to determine the point of origin of a sound source. The ITD can be defined as the different points in time at which a sound from a single location arrives at each individual ear [1]. From this time difference, the brain can calculate the angle of the sound source in relation to the head [2]. Cross-correlation compares the similarity of each channel of a binaural waveform producing the time lag or offset required for both channels to be in phase with one another. This offset corresponds to the maximum value produced by the cross-correlation function and can be used to determine the ITD and thus the azimuthal angle θ of the original sound source. However, in indoor environments, cross-correlation has been known to have problems with both sound reflections and reverberations. Additionally, cross-correlation has difficulties with localising short-term complex noises when they occur during a longer duration waveform, i.e. in the presence of background noise. The crosscorrelation algorithm processes the entire waveform and the short-term complex noise can be ignored. This paper presents a technique using thresholding which enables higher-localisation abilities for short-term complex sounds in the midst of background noise. To determine the success of this thresholding technique, twenty-five sounds were recorded in a dynamic and echoic environment. The twenty-five sounds consist of hand-claps, finger-clicks and speech. The proposed technique was compared to the regular cross-correlation function for the same waveforms, and an average of the azimuthal angles determined for each individual sample. The sound localisation ability for all twenty-five sound samples is as follows: average of the sampled angles using cross-correlation: 44%; cross-correlation technique with thresholding: 84%. From these results, it is clear that this proposed technique is very successful for the localisation of short-term complex sounds in the midst of background noise and in a dynamic and echoic indoor environment.

Role of assessment components and recent adverse outcomes in risk estimation and prediction: use of the Short Term Assessment of Risk and Treatability (START) in an adult secure inpatient mental health service

The Short Term Assessment of Risk and Treatability is a structured judgement tool used to inform risk estimation for multiple adverse outcomes. In research, risk estimates outperform the tool's strength and vulnerability scales for violence prediction. Little is known about what its’component parts contribute to the assignment of risk estimates and how those estimates fare in prediction of non-violent adverse outcomes compared with the structured components. START assessment and outcomes data from a secure mental health service (N=84) was collected. Binomial and multinomial regression analyses determined the contribution of selected elements of the START structured domain and recent adverse risk events to risk estimates and outcomes prediction for violence, self-harm/suicidality, victimisation, and self-neglect. START vulnerabilities and lifetime history of violence, predicted the violence risk estimate; self-harm and victimisation estimates were predicted only by corresponding recent adverse events. Recent adverse events uniquely predicted all corresponding outcomes, with the exception of self-neglect which was predicted by the strength scale. Only for victimisation did the risk estimate outperform prediction based on the START components and recent adverse events. In the absence of recent corresponding risk behaviour, restrictions imposed on the basis of START-informed risk estimates could be unwarranted and may be unethical.

DYNAMICS OF THE SHORT TERM AND LONG TERM AVIAN DISTRIBUTIONS IN NORTH AMERICA - THE ROLES OF VEGETATION HEIGHT HETEROGENEITY AND CLIMATIC FACTORS

Understanding how biodiversity spatially distribute over both the short term and long term, and what factors are affecting the distribution, are critical for modeling the spatial pattern of biodiversity as well as for promoting effective conservation planning and practices. This dissertation aims to examine factors that influence short-term and long-term avian distribution from the geographical sciences perspective. The research develops landscape level habitat metrics to characterize forest height heterogeneity and examines their efficacies in modelling avian richness at the continental scale. Two types of novel vegetation-height-structured habitat metrics are created based on second order texture algorithms and the concepts of patch-based habitat metrics. I correlate the height-structured metrics with the richness of different forest guilds, and also examine their efficacies in multivariate richness models. The results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of two forest bird guilds. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness. The second and the third projects focus on analyzing centroids of avian distributions, and testing hypotheses regarding the direction and speed of these shifts. I first showcase the usefulness of centroids analysis for characterizing the distribution changes of a few case study species. Applying the centroid method on 57 permanent resident bird species, I show that multi-directional distribution shifts occurred in large number of studied species. I also demonstrate, plain birds are not shifting their distribution faster than mountain birds, contrary to the prediction based on climate change velocity hypothesis. By modelling the abundance change rate at regional level, I show that extreme climate events and precipitation measures associate closely with some of the long-term distribution shifts. This dissertation improves our understanding on bird habitat characterization for species richness modelling, and expands our knowledge on how avian populations shifted their ranges in North America responding to changing environments in the past four decades. The results provide an important scientific foundation for more accurate predictive species distribution modeling in future.