Diagnostic tools of energy performance for supermarkets using Artificial Neural Network algorithms

Supermarket performance monitoring is of vital importance to ensure systems perform adequately and guarantee operating costs and energy use are kept at a minimum. Furthermore, advanced monitoring techniques can allow early detection of equipment faults that could disrupt store operation. This paper details the development of a tool for performance monitoring and fault detection for supermarkets focusing on evaluating the Store's Total Electricity Consumption as well as individual systems, such as Refrigeration, HVAC, Lighting and Boiler. Artificial Neural Network (ANN) models are developed for each system to provide the energy baseline, which is modelled as a dependency between the energy consumption and suitable explanatory variables. The tool has two diagnostic levels. The first level broadly evaluates the systems performance, in terms of energy consumption, while the second level applies more rigorous criteria for fault detection of supermarket subsystems. A case study, using data from a store in Southeast England, is presented and results show remarkable accuracy for calculating hourly energy use, thus marking the ANN method as a viable tool for diagnosis purposes. Finally, the generic nature of the methodology approach allows the development and application to other stores, effectively offering a valuable analytical tool for better running of supermarkets

Seasonal predictability of the 2010 Russian heat wave

The atmospheric blocking over eastern Europe and western Russia that prevailed during July and August of 2010 led to the development of a devastating Russian heat wave. Therefore the question of whether the event was predictable or not is highly important. The principal aim of this study is to examine the predictability of this high-impact atmospheric event on a seasonal timescale. To this end, a set of dynamical seasonal simulations have been carried out using an atmospheric global circulation model (AGCM). The impact of various model initializations on the predictability of this large-scale event and its sensitivity to the initial conditions has been also investigated. The ensemble seasonal simulations are based on a modified version of the lagged-average forecast method using different lead-time initializations of the model. The results indicated that only a few individual members reproduced the main features of the blocking system 3 months ahead. Most members missed the phase space and the propagation of the system, setting limitations in the predictability of the event

Identification of protein kinase inhibitors with a selective negative effect on the viability of Epstein-Barr virus infected B cell lines

Epstein-Barr virus (EBV) is a human herpesvirus, which is causally associated with the development of several B lymphocytic malignancies that include Burkitt's lymphomas, Hodgkin's disease, AIDS and posttransplant associated lymphomas. The transforming activity of EBV is orchestrated by several latent viral proteins that mimic and modulate cellular growth promoting and antiapoptotic signaling pathways, which involve among others the activity of protein kinases. In an effort to identify small molecule inhibitors of the growth of EBV-transformed B lymphocytes a library of 254 kinase inhibitors was screened. This effort identified two tyrosine kinase inhibitors and two MEK inhibitors that compromised preferentially the viability of EBV-infected human B lymphocytes. Our findings highlight the possible dependence of EBV-infected B lymphocytes on specific kinase-regulated pathways underlining the potential for the development of small molecule-based therapeutics that could target selectively EBV-associated human B lymphocyte malignancies. © 2014 Mavromatidis et al

Photovoltaic panels as a main component of energy sustainable communities : comparative energy analysis of a village under Swiss and South African climatic loads

Paper presented to the 3rd Southern African Solar Energy Conference, South Africa, 11-13 May, 2015.At the community level, it is difficult to rely on a single centralized energy technology when considering renewable energy and the use of a mix of multiple distributed energy systems (DES) seems advantageous. DES, e.g. photovoltaic panels (PV), are typically integrated at building level and account for a small fraction of required energy. Since energy supply from renewables is highly fluctuating over time and dependent on climatic and local conditions, a reliable integration is a challenging task. In this paper, we use a recently developed concept, that allows to sufficiently improve the energy efficiency of the building stock, to manage energy supply from renewables and to optimize the future energy system using the energy hub approach, while effectively integrating DES. Using the same village characteristics, we found that, due to mismatch of available solar potential and the electricity demand, 18% of available solar potential cannot be utilized in Zernez, while in Johannesburg, this mismatch amounts to 22%.cf201

Research trends in combinatorial optimization

Acknowledgments This work has been partially funded by the Spanish Ministry of Science, Innovation, and Universities through the project COGDRIVE (DPI2017-86915-C3-3-R). In this context, we would also like to thank the Karlsruhe Institute of Technology. Open access funding enabled and organized by Projekt DEAL.Peer reviewedPublisher PD

Atrasentan and renal events in patients with type 2 diabetes and chronic kidney disease (SONAR): a double-blind, randomised, placebo-controlled trial

Background: Short-term treatment for people with type 2 diabetes using a low dose of the selective endothelin A receptor antagonist atrasentan reduces albuminuria without causing significant sodium retention. We report the long-term effects of treatment with atrasentan on major renal outcomes. Methods: We did this double-blind, randomised, placebo-controlled trial at 689 sites in 41 countries. We enrolled adults aged 18–85 years with type 2 diabetes, estimated glomerular filtration rate (eGFR)25–75 mL/min per 1·73 m 2 of body surface area, and a urine albumin-to-creatinine ratio (UACR)of 300–5000 mg/g who had received maximum labelled or tolerated renin–angiotensin system inhibition for at least 4 weeks. Participants were given atrasentan 0·75 mg orally daily during an enrichment period before random group assignment. Those with a UACR decrease of at least 30% with no substantial fluid retention during the enrichment period (responders)were included in the double-blind treatment period. Responders were randomly assigned to receive either atrasentan 0·75 mg orally daily or placebo. All patients and investigators were masked to treatment assignment. The primary endpoint was a composite of doubling of serum creatinine (sustained for ≥30 days)or end-stage kidney disease (eGFR <15 mL/min per 1·73 m 2 sustained for ≥90 days, chronic dialysis for ≥90 days, kidney transplantation, or death from kidney failure)in the intention-to-treat population of all responders. Safety was assessed in all patients who received at least one dose of their assigned study treatment. The study is registered with ClinicalTrials.gov, number NCT01858532. Findings: Between May 17, 2013, and July 13, 2017, 11 087 patients were screened; 5117 entered the enrichment period, and 4711 completed the enrichment period. Of these, 2648 patients were responders and were randomly assigned to the atrasentan group (n=1325)or placebo group (n=1323). Median follow-up was 2·2 years (IQR 1·4–2·9). 79 (6·0%)of 1325 patients in the atrasentan group and 105 (7·9%)of 1323 in the placebo group had a primary composite renal endpoint event (hazard ratio [HR]0·65 [95% CI 0·49–0·88]; p=0·0047). Fluid retention and anaemia adverse events, which have been previously attributed to endothelin receptor antagonists, were more frequent in the atrasentan group than in the placebo group. Hospital admission for heart failure occurred in 47 (3·5%)of 1325 patients in the atrasentan group and 34 (2·6%)of 1323 patients in the placebo group (HR 1·33 [95% CI 0·85–2·07]; p=0·208). 58 (4·4%)patients in the atrasentan group and 52 (3·9%)in the placebo group died (HR 1·09 [95% CI 0·75–1·59]; p=0·65). Interpretation: Atrasentan reduced the risk of renal events in patients with diabetes and chronic kidney disease who were selected to optimise efficacy and safety. These data support a potential role for selective endothelin receptor antagonists in protecting renal function in patients with type 2 diabetes at high risk of developing end-stage kidney disease. Funding: AbbVie

An investigation of cold cloud formation with a three-dimensional model with explicit microphysics

In the framework of the European Union-funded project &quot;Investigation of Cloud by Ground-based and Airborne Radar and Lidar&quot; (CARL) the Regional Atmospheric Modeling System (RAMS) was used in order to study ice crystal formation and evolution in a cold cloud formation during a field program over Palaiseau, France. Sensitivity tests were performed so as to bind the uncertainty from various factors controlling model results. Emphasis is given to the sensitivity of the model with respect to the shape parameter of gamma distribution in the cloud microphysics module. Sensitivity analysis of the model was also performed in relation to the initialization of the simulation. The results are compared to in situ and remote sensing observations of the cloud formation. The analysis revealed that the model was able to reproduce the cloud characteristics (e.g., the spatial and temporal variability of the phenomena and the cloud geometry) in a satisfactory way. A detailed comparison of the model results with aircraft data showed that the model-calculated water content and number concentration deviate significantly for the small-size particle bin (2-47 microns) but are in good agreement for the medium-(25-800 microns) and large-size (200-6400 microns) bins. The differences for the smaller particles can partially be attributed to both poor performance of the microphysical algorithms and instrument inaccuracies. Some differences for the larger particles can be attributed either to the definition of the cloud boundaries by the model or to disturbances caused by the ascent path of the aircraft or both. The time of model initialization is also an important factor affecting cloud formation during the first few hours of the simulation. The performed simulations and model/data intercomparisons showed that RAMS is able to reproduce most of the microphysical parameters of cold cloud formations satisfactorily while utilizing conventional meteorological fields and observations for initial and boundary conditions

Analysis of a two-layer cloud system with RAMS model and comparison to airborne observations

A three-dimensional numerical model (Regional Atmospheric Modeling System - RAMS) was used to study the formation and evolution of water forms in a two-layer cloud structure observed during a field campaign over Brest (France). The model performance in regular operations, using conventional meteorological data as initial and lateral boundary conditions, was also examined. Remote sensing observations of the cloud system and in-situ aircraft data, selected during the campaign, were used to validate the model outputs. The model simulations showed that the lower cloud formation was characterized by high number concentration of pristine ice and snow, while the concentration of aggregates, graupel and hail were considerably lower. Hydrometeors in liquid phase appeared demonstrating high number concentration and water content on the top of this layer. The upper cloud layer consisted only of frozen water substances in lower amounts. The qualitative and quantitative comparison of the model-calculated meteorological and microphysical fields to the available observational data revealed that the model reflected fairly well the cloud structure (e.g., the spatio-temporal variability of the cloud parameters, the geometry of the cloud system). However, there were deviations as far as the model underestimating the ice water content (IWC) and number concentration (Nt) fields is concerned, especially at the atmospheric layer between 2.5 and 4 km of altitude. These deviations of the model simulated quantities from the measured ones may be attributed either to the performance of the model&apos;s microphysics scheme, to instrument inaccuracies and to the local disturbance caused by the aircraft. © Springer Science+Business Media B.V. 2007

Some considerations on the airborne cloud microphysical probing

This paper provides a theoretical calibration of Optical Array Probes (OAP) mounted on a given aircraft, in order to take into account the aerodynamic influence of the entire aircraft on the measurements obtained. The measured parameters are corrected through the computation of the air flow-field around the entire aircraft carrying the probes, for different flight conditions, in order to obtain the corresponding undisturbed values. These undisturbed values have been compared to the microphysical ones computed by an atmospheric model, the Regional Atmospheric Modeling System (RAMS). It was found that the removal of the disturbances made by the aircraft on the atmospheric conditions is feasible and provides data that compare much better to the model results. It is suggested that such kind of airborne data corrections may be performed in order to improve the quality of the observations if the aircraft and probe geometries are known. Further information regarding the best location of the probes on the considered aircraft is also obtained. © Springer-Verlag 2005

Heterogeneous chemical processes and their role on particulate matter formation in the mediterranean region

The impact of particulate matter on air quality and the environment is an important subject for areas like the Greater Mediterranean Region, mostly due to the coexistence of major anthropogenic and natural sources. Such coexistence can create air quality conditions that exceed the imposed air quality limit values. Particulate matter formation and the factors enhancing or reducing such formation in the Mediterranean Region will be the primary focus of the work presented herein. Natural particulate matter appears mainly in the form of desert dust, sea salt and pollen among others and anthropogenic particulate matter appears as particulate sulfate and nitrate. The processes affecting the formation of new types of aerosols are based on the heterogeneous uptake of gases onto dust particles. New model development will be presented referring to the implementation of sea salt production and heterogeneous chemical processes leading to new aerosol formation in the photochemical model CAMx. Results from these simulations showed reasonable agreement with the available measurements. These results also revealed interesting effects of the coexistence of natural and anthropogenic particulate matter concerning the direct and indirect impacts on air quality and the environment. © Springer Science + Business Media B.V. 2008