Designing a ‘green’ building: expanding ambitions through social learning

The process of creating a specific building – Miljøbygget in Trondheim, Norway – is analyzed in order to understand how the project team's ambitions expanded to embrace ‘green’ issues and create new targets. The decisions and roles of key actors are investigated regarding these goals and criteria. The analysis draws on two concepts. First, translation theory is used to highlight the potential role of new knowledge or technology that originates outside of the project. Second, the concept of social learning is employed to understand the process of expanding ambitions, developing goals and criteria within the project, and how this is related to the collective exploration, discovery and analysis of new practices. The wider implications are considered with respect to innovation in the construction industry. The project's initial moderate energy efficiency ambition was transformed, first into stricter energy efficiency goals, then into broader environmental aims. The resulting innovation is an ambition-enhancing, experience-based and enthusiasm-driven process of social learning in the project team, marked by interpersonal trust, including trust regarding competence and contractual relations. Translation efforts were also found to be important for bringing new knowledge into the project. The conclusion discusses some policy implications.     

Factors explaining adoption and implementation processes for web accessibility standards within eGovernment systems and organizations

Local government organizations such as municipalities often seem unable to fully adopt or implement web accessibility standards even if they are actively pursuing it. Based on existing adoption models, this study identifies factors in five categories that influence the adoption and implementation of accessibility standards for local government websites. Awareness of these factors is important for stakeholders adopting and implementing web accessibility standards. To further develop and understand these factors, this study has identified and interviewed experts in the field of (organizational) accessibility. This has led to an extension of the existing models. The extended model was then validated by interviews with key stakeholders. The outcome of this study places existing adoption models in a new context. The result is an adoption model that contributes better to explaining adoption and implementation processes within eGovernment systems and organizations. This adoption model aims to better help local governments in the identification of factors influencing the actual adoption and implementation of web accessibility standards in their situation. The model explains how factors in the different categories contribute to the adoption and implementation of web accessibility standards. The model may also be applicable to the adoption and implementation of other guidelines and (open) standards within local government.     

Forecasting models for tourism demand in city dominated and coastal areas

The paper uses Structural time series models to forecast the demand for tourism by nationality in coastal and city-dominated Spanish provinces. Intervention variables are introduced to take account of sudden shocks to tourism demand, such as the bombing of Libya and football's World Cup. The model demonstrates the considerable differences in demand by nationality, and in seasonality, which can occur at the subnational level. The Structural model generally provided more accurate forecasts than Box-Jenkins models. The results indicate that, ceteris paribus, the tourism demand growth rates in the Spanish provinces considered are unlikely to revert to their previous high levels.     

Improved training tolerance by supplementation with alpha-Keto acids in untrained young adults: a randomized, double blind, placebo-controlled trial

ABSTRACT: BACKGROUND: Exercise causes a variety of physiological and metabolic changes that can in turn reduce exercise tolerance. One of the potential mechanisms responsible for fatigue is "exercise-induced hyperammonemia". Previous studies have shown that supplementation with amino acids can increase training tolerance. The alpha-keto acids are biochemical analogs of amino acids and can be converted to amino acids through transamination, thus reducing the cellular ammonia level. This double blind, placebo-controlled study was designed to investigate the effects of alpha-keto acid supplementation (KAS) on training tolerance, training effect, and stress-recovery state. METHODS: Thirty-three untrained young male adults underwent four weeks of training (5 sessions/week; 30 minutes running at the individual anaerobic threshold followed by 3 x 3 minute sprints/each session). Throughout the 4 weeks of training and one week of recovery, subjects took alpha-ketoglutarate (AKG group, 0.2 g/kg/d, n=9), branched-chain keto acids (BCKA group, 0.2 g/kg/d, n=12) or isocaloric placebo (control group, n=12) daily. RESULTS: The 4th week training volume, maximum power output and muscle torque were higher in the AKG group (175+/-42 min, 412+/-49 Watts and 293+/-58 Newton meters, respectively, P<0.05) and the BCKA group (158+/-35, 390+/-29 and 273+/-47, P<0.05) than in the control group (92+/-70, 381+/-67 and 233+/-43). The general stress and emotional exhaustion as assessed by the rest-stress-questionnaire-sport after the 3rd week of training increased significantly in the control group (P<0.05), but not in the KAS groups. CONCLUSIONS: Under KAS, subjects could bear a higher training volume and reach a higher power output and peak muscle torque, accompanied by a better stress-recovery-state. Thus, KAS improves exercise tolerance and training effects along with a better stress-recovery state. Whether the improved training tolerance by KAS is associated with effects on ammonia homeostasis requires further observation.     

Seasonal reproductive patterns of female Gambusia holbrooki from two Florida lakes

Lake Apopka in central Florida (USA) is significantly contaminated with a variety of chemicals including anthropogenic nutrients, organochlorine pesticides like dichlorodiphenyltrichloroethane (DDT) and dichlorodiphenyldichloroethylene (DDE), and multiple congeners of polychlorinated biphenyls (PCBs). Our laboratory has previously documented a number of reproductive abnormalities in alligators from Lake Apopka, compared with alligators captured from Lake Woodruff, a nearby reference lake. We conducted the present study to investigate if another native vertebrate, Gambusia holbrooki (eastern mosquitofish), is similarly affected. Adult female mosquitofish were collected from Lake Apopka and Lake Woodruff monthly for 16 months to document seasonal and lake-associated variation in reproductive patterns. In contrast to fish from Lake Woodruff (reference), females from Lake Apopka exhibited earlier and more synchronized spring ovarian recrudescence, increased body size, increased fecundity, increased adjusted hepatic weight, and more extreme fluctuations in muscle estradiol concentrations in most months. Endocrine disruption, consistent with other studies and Lake Apopka's pollution profile, is one explanation for these findings. Other environmental and physiological factors are also addressed. However, the higher fecundity among Apopka females suggests that, unlike Apopka alligators, Apopka mosquitofish are not impacted at the population level.     

A fast neural net training algorithm and its application to speech classification

This paper describes a fast training algorithm for feedforward neural nets, as applied to a two-layer neural network to classify segments of speech as voiced, unvoiced, or silence. The speech classification method is based on five features computed for each speech segment and used as input to the network. The network weights are trained using a new fast training algorithm which minimizes the total least squares error between the actual output of the network and the corresponding desired output. The iterative training algorithm uses a quasi-Newtonian error-minimization method and employs a positive-definite approximation of the Hessian matrix to quickly converge to a locally optimal set of weights. Convergence is fast, with a local minimum typically reached within ten iterations; in terms of convergence speed, the algorithm compares favorably with other training techniques. When used for voiced-unvoiced-silence classification of speech frames, the network performance compares favorably with current approaches. Moreover, the approach used has the advantage of requiring no assumption of a particular probability distribution for the input features.     

Effect of extrusion variables on fermented maize-finger millet blend in the production of uji

The effects of screw speed, feed moisture, glucose, fructose, sucrose and maltose on extrusion of lactic fermented and dried maize-finger millet blend was investigated. Fermentation caused a reduction in sectional expansion index, flour bulk density and water absorption index (WAI) but increased specific volume, water solubility index and darkened the extrudates. Increase in feed moisture (13-25%) reduced sectional expansion index, specific volume and yellowness but increased extrudate moisture content, bulk density and darkness of the extrudates. Increasing screw speed (158-242 rpm) had a negative correlation only with specific volume and lightness (P<0.05). An increase in the content of any of the sugars reduced extrudate moisture content, sectional expansion index, WAI and specific volume but increased bulk density and water solubility index. Extrudates treated with monosaccharides were darker than extrudates treated with disaccharides.