Electricity use in the commercial kitchen

Academic and industrial literature concerning the energy use of commercial kitchens is scarce. Electricity consumption data were collected from distribution board current transformers in a sample of fourteen UK public house-restaurants. This was set up to identify patterns of appliance use as well as to assess the total energy consumption of these establishments. The electricity consumption in the selected commercial kitchens was significantly higher than current literature estimates. On average, 63% of the premises’ electricity consumption was attributed to the catering activity. Key appliances that contributed to the samples average daily electricity consumption of the kitchen were identified as refrigeration (70 kWh, 41%), fryers (11 kWh, 13%), combination ovens (35 kWh, 12%), bain maries (27 kWh, 9%) and grills (37 kWh, 12%). Behavioural factors and poor maintenance were identified as major contributors to excessive electricity usage with potential savings of 70% and 45% respectively. Initiatives are required to influence operator behaviour, such as the expansion of mandatory energy labelling, improved feedback information and the use of behaviour change campaigns. Strict maintenance protocols and more appropriate sizing of refrigeration would be of great benefit to energy reduction.

Relief for the environment? The importance of an increasingly unimportant industrial sector

Deindustrialization, stagnant real incomes of production workers, and increasing inequality are latter day features of many economies. It is common to assume that such developments pressure policymakers to relax environmental standards. However, when heavily polluting industries become less important economically, their political importance also tends to diminish. Consequently, a regulator may increase the stringency of environmental policies. Like some other studies, we find that declining industrial employment translates into stricter environmental standards. In contrast to previous studies, but consistent with our argument, we find that greater income inequality is associated with policies that promote a cleaner environment. (JEL Q58, P16, J31, C23)

Industrial relations in South-Eastern Europe: disaggregating the contexts

This study critically evaluates industrial relations (IR) in South-Eastern Europe and points towards future practical and research-oriented opportunities in the region. A survey of organizational policies and practices has been used to explore the state of IR in both private and public organizations in this region. Specifically, the data, collected in 2009–2010 (including the latest changes due to the economic crisis), cover 840 different organizations located in Slovenia, Serbia, Bulgaria, Greece and Cyprus. We discuss the development of ‘regional-specific’ IR policies, the ‘importing’ of varieties of capitalism models, the diffusion of the European Union social model and the role of foreign MNCs in changing IR in the region.

Draft genome sequence of pseudomonas corrugata, a phytopathogenic bacterium with potential industrial applications

Pseudomonas corrugata was first described as the causal agent of a tomato disease called 'pith necrosis' yet it is considered as a biological resource in various fields such as biocontrol of plant diseases and production of industrially promising microbial biopolymers (mcl-PHA). Here we report the first draft genome sequence of this species.

Visual sensor fusion for active security in robotic industrial environments

This work presents a method of information fusion involving data captured by both a standard CCD camera and a ToF camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time of light information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localization. Further development of these methods will make it possible to identify objects and their position in the real world, and to use this information to prevent possible collisions between the robot and such objects.

Visual sensor fusion for active security in robotic industrial environments

This work presents a method of information fusion involving data captured by both a standard charge-coupled device (CCD) camera and a time-of-flight (ToF) camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time-of-flight information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time, this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localisation. Further development of these methods will make it possible to identify objects and their position in the real world and to use this information to prevent possible collisions between the robot and such objects.

Climate models without pre-industrial volcanic forcing underestimate historical ocean thermal expansion

Episodic explosive volcanic eruptions are a natural part of the climate system but are often omitted from atmosphere-ocean general circulation model (AOGCM) preindustrial spin-up and control experiments. This omission imposes a negative bias on ocean heat uptake in simulations of the historical period. In models of a range of complexity, we find that global-mean sea level rise due to thermal expansion during the last ∼ 150 years is consequently underestimated by 5–30 mm, which is a substantial proportion of the model mean of 50 mm in Coupled Model Intercomparison Project Phase 3 AOGCMs with anthropogenic forcing only, and is therefore important in accounting for 20th century sea level rise. We test and recommend a procedure for removing the bias.

Which factors drive rental depreciation rates for office and industrial properties?

As new buildings are constructed in response to changes in technology or user requirements, the value of the existing stock will decline in relative terms. This is termed economic depreciation and it may be influenced by the age and quality of buildings, amount and timing of expenditure, and wider market and economic conditions. This study tests why individual assets experience different depreciation rates, applying panel regression techniques to 375 UK office and industrial assets. Results suggest that rental value depreciation rates reduce as buildings get older, while a composite measure of age and quality provides more explanation of depreciation than age alone. Furthermore, economic and local real estate market conditions are significant in explaining how depreciation rates change over time.

Volatile profile of Spanish Cistus plants as sources of antimicrobials for industrial applications

Cistus is a plant genus traditionally used in folk medicine as remedy for several microbial disorders and infections. The abundance of Cistus spp. in the Iberian Peninsula together with their ability to renew after wildfire contribute to their profitability as suppliers of functional ingredients. The aim of this study was to provide a comprehensive characterization of the volatile profile of different Cistus plants grown in Spain:Cistus ladanifer L., Cistus albidus L., Cistus salviifolius L., and Cistus clusii Dunal (the latter has not been studied before). A system combining headspace solid-phase microextraction and gas chromatography coupled to mass spectrometry (HS-SPME-GC–MS) was implemented; thereby, the volatile compounds were extracted and analyzed in a fast, reliable and environment-friendly way. A total of 111 volatile compounds were identified, 28 of which were reported in Cistus for the first time. The most abundant components of the samples (mono and sesquiterpenes) have been previously reported as potent antimicrobial agents. Therefore, this work reveals the potential use of the Cistus spp. studied as natural sources of antimicrobial compounds for industrial production of cosmeceuticals, among other applications.

Geoadditive models for regional count data: an application to industrial location

We propose a geoadditive negative binomial model (Geo-NB-GAM) for regional count data that allows us to address simultaneously some important methodological issues, such as spatial clustering, nonlinearities, and overdispersion. This model is applied to the study of location determinants of inward greenfield investments that occurred during 2003–2007 in 249 European regions. After presenting the data set and showing the presence of overdispersion and spatial clustering, we review the theoretical framework that motivates the choice of the location determinants included in the empirical model, and we highlight some reasons why the relationship between some of the covariates and the dependent variable might be nonlinear. The subsequent section first describes the solutions proposed by previous literature to tackle spatial clustering, nonlinearities, and overdispersion, and then presents the Geo-NB-GAM. The empirical analysis shows the good performance of Geo-NB-GAM. Notably, the inclusion of a geoadditive component (a smooth spatial trend surface) permits us to control for spatial unobserved heterogeneity that induces spatial clustering. Allowing for nonlinearities reveals, in keeping with theoretical predictions, that the positive effect of agglomeration economies fades as the density of economic activities reaches some threshold value. However, no matter how dense the economic activity becomes, our results suggest that congestion costs never overcome positive agglomeration externalities.