Work performance, productivity and indoor air

Temperature, relative humidity, and air quality all affect the sensory system via thermo receptors in the skin and the olfactory system. Air quality is mainly defined by the contaminants in the air. However, the most persistent memory of any space is often its odor. Strong, emotional, and past experiences are awakened by the olfactory sense. Odors can also influence cognitive processes that affect creative task performance, as well as personal memories and moods. Besides nitrogen and oxygen, the air contains particles and many chemicals that affect the efficiency of the oxygenation process in the blood, and ultimately the air breathed affects thinking and concentration. It is important to show clients the value of spending more capital on high-quality buildings that promote good ventilation. The process of achieving indoor-air quality is a continual one throughout the design, construction, commissioning, and facilities management processes. This paper reviews the evidence.

Detection of pressed hazelnut oil in virgin olive oil by analysis of polar components: improvement and validation of the method

An improved method for the detection of pressed hazelnut oil in admixtures with virgin olive oil by analysis of polar components is described. The method. which is based on the SPE-based isolation of the polar fraction followed by RP-HPLC analysis with UV detection. is able to detect virgin olive oil adulterated with pressed hazelnut oil at levels as low as 5% with accuracy (90.0 +/- 4.2% recovery of internal standard), good reproducibility (4.7% RSD) and linearity (R-2: 0.9982 over the 5-40% adulteration range). An international ring-test of the developed method highlighted its capability as 80% of the samples were, on average, correctly identified despite the fact that no training samples were provided to the participating laboratories. However, the large variability in marker components among the pressed hazelnut oils examined prevents the use of the method for quantification of the level of adulteration. (C) 2003 Elsevier Ltd. All rights reserved.

Prebiotic interventions for the improvement of gut health

The increasing awareness of the role that the colonic microflora plays in maintaining host health within the gastrointestinal tract and systemically through the absorption of metabolites, has attracted a lot of interest, within the nutritional sciences, in developing dietary tools for controlling the colonic microflora. Among those dietary tools, prebiotics aim to improve health by stimulating numbers and/or activities of the beneficial bacteria in the gut, mainly bifidobacteria and lactobacilli. The ability of incorporating prebiotics in various food processes together with recent developments in understanding how prebiotics are metabolised by health promoting bacteria, allow us to specifically aim such dietary interventions towards selected population groups, such as infants and elderly, and disease states, such as colon cancer and irritable bowel disease.

Moderate Champagne consumption promotes an acute improvement in acute endothelial-independent vascular function in healthy human volunteers

Epidemiological studies have suggested an inverse correlation between red wine consumption and the incidence of CVD. However, Champagne wine has not been fully investigated for its cardioprotective potential. In order to assess whether acute and moderate Champagne wine consumption is capable of modulating vascular function, we performed a randomised, placebo-controlled, cross-over intervention trial. We show that consumption of Champagne wine, but not a control matched for alcohol, carbohydrate and fruit-derived acid content, induced an acute change in endothelium-independent vasodilatation at 4 and 8 h post-consumption. Although both Champagne wine and the control also induced an increase in endothelium-dependent vascular reactivity at 4 h, there was no significant difference between the vascular effects induced by Champagne or the control at any time point. These effects were accompanied by an acute decrease in the concentration of matrix metalloproteinase (MMP-9), a significant decrease in plasma levels of oxidising species and an increase in urinary excretion of a number of phenolic metabolites. In particular, the mean total excretion of hippuric acid, protocatechuic acid and isoferulic acid were all significantly greater following the Champagne wine intervention compared with the control intervention. Our data suggest that a daily moderate consumption of Champagne wine may improve vascular performance via the delivery of phenolic constituents capable of improving NO bioavailability and reducing matrix metalloproteinase activity.

Improvement of link failure restoration utilising MPLS as a means to maintain QoS

The availability of a network strongly depends on the frequency of service outages and the recovery time for each outage. The loss of network resources includes complete or partial failure of hardware and software components, power outages, scheduled maintenance such as software and hardware, operational errors such as configuration errors and acts of nature such as floods, tornadoes and earthquakes. This paper proposes a practical approach to the enhancement of QoS routing by means of providing alternative or repair paths in the event of a breakage of a working path. The proposed scheme guarantees that every Protected Node (PN) is connected to a multi-repair path such that no further failure or breakage of single or double repair paths can cause any simultaneous loss of connectivity between an ingress node and an egress node. Links to be protected in an MPLS network are predefined and an LSP request involves the establishment of a working path. The use of multi-protection paths permits the formation of numerous protection paths allowing greater flexibility. Our analysis will examine several methods including single, double and multi-repair routes and the prioritization of signals along the protected paths to improve the Quality of Service (QoS), throughput, reduce the cost of the protection path placement, delay, congestion and collision.

Improvement of classification accuracy for stochastic discrimination - Multi-class classification

In this paper, an improved stochastic discrimination (SD) is introduced to reduce the error rate of the standard SD in the context of multi-class classification problem. The learning procedure of the improved SD consists of two stages. In the first stage, a standard SD, but with shorter learning period is carried out to identify an important space where all the misclassified samples are located. In the second stage, the standard SD is modified by (i) restricting sampling in the important space; and (ii) introducing a new discriminant function for samples in the important space. It is shown by mathematical derivation that the new discriminant function has the same mean, but smaller variance than that of standard SD for samples in the important space. It is also analyzed that the smaller the variance of the discriminant function, the lower the error rate of the classifier. Consequently, the proposed improved SD improves standard SD by its capability of achieving higher classification accuracy. Illustrative examples axe provided to demonstrate the effectiveness of the proposed improved SD.

Distributed space-time block coding with incremental relay: performance improvement under imperfect synchronisation

This paper addresses the impact of imperfect synchronisation on D-STBC when combined with incremental relay. To suppress such an impact, a novel detection scheme is proposed, which retains the two key features of the STBC principle: simplicity (i.e. linear computational complexity), and optimality (i.e. maximum likelihood). These two features make the new detector very suitable for low power wireless networks (e.g. sensor networks).

On improvement of classification accuracy for stochastic discrimination

Stochastic discrimination (SD) depends on a discriminant function for classification. In this paper, an improved SD is introduced to reduce the error rate of the standard SD in the context of a two-class classification problem. The learning procedure of the improved SD consists of two stages. Initially a standard SD, but with shorter learning period is carried out to identify an important space where all the misclassified samples are located. Then the standard SD is modified by 1) restricting sampling in the important space, and 2) introducing a new discriminant function for samples in the important space. It is shown by mathematical derivation that the new discriminant function has the same mean, but with a smaller variance than that of the standard SD for samples in the important space. It is also analyzed that the smaller the variance of the discriminant function, the lower the error rate of the classifier. Consequently, the proposed improved SD improves standard SD by its capability of achieving higher classification accuracy. Illustrative examples are provided to demonstrate the effectiveness of the proposed improved SD.

The British ‘failure’ that never was? The Anglo-American ‘productivity gap’ in large-scale interwar retailing—evidence from the department store sector

Interwar British retailing has been characterized as having lower productivity, less developed managerial hierarchies and methods, and weaker scale economies than its US counterpart. This article examines comparative productivity for one major segment of large-scale retailing in both countries—the department store sector. Drawing on exceptionally detailed contemporary survey data, we show that British department stores in fact achieved superior performance in terms of operating costs, margins, profits, and stock-turn. While smaller British stores had lower labour productivity than US stores of equivalent size, TFP was generally higher for British stores, which also enjoyed stronger scale economies. We also examine the reasons behind Britain's surprisingly strong relative performance, using surviving original returns from the British surveys. Contrary to arguments that British retailers faced major barriers to the development of large-scale enterprises, that could reap economies of scale and scope and invest in machinery and marketing to support the growth of their primary sales functions, we find that British department stores enthusiastically embraced the retail ‘managerial revolution’—and reaped substantial benefits from this investment.

An analysis of the impact of R&D on productivity using Bayesian model averaging with a reversible jump algorithm.

A Bayesian Model Averaging approach to the estimation of lag structures is introduced, and applied to assess the impact of R&D on agricultural productivity in the US from 1889 to 1990. Lag and structural break coefficients are estimated using a reversible jump algorithm that traverses the model space. In addition to producing estimates and standard deviations for the coe¢ cients, the probability that a given lag (or break) enters the model is estimated. The approach is extended to select models populated with Gamma distributed lags of di¤erent frequencies. Results are consistent with the hypothesis that R&D positively drives productivity. Gamma lags are found to retain their usefulness in imposing a plausible structure on lag coe¢ cients, and their role is enhanced through the use of model averaging.