L'étendue internationale des nouvelles firmes de hautes technologies: le rôle du capital humain et de l'intention stratégique des fondateurs

De récentes recherches ont mis l’accent sur l’importance pour les nouvelles entreprises internationales de l’existence de ressources et de compétences spécifiques. La présente recherche, qui s’inscrit dans ce courant, montre en particulier l’importance du capital humain acquis par les entrepreneurs sur base de leur expérience internationale passée. Mais nous montrons en même temps que ces organisations sont soutenues par une intention délibérée d’internationalisation dès l’origine. Notre recherche empirique est basée sur l’analyse d’un échantillon de 466 nouvelles entreprises de hautes technologies anglaises et allemandes. Nous montrons que ce capital humain est un actif qui facilite la pénétration rapide des marchés étrangers, et plus encore quand l’entreprise nouvelle est accompagnée d’une intention stratégique délibérée d’internationalisation. Des conclusions similaires peuvent être étendues au niveau des ressources que l’entrepreneur consacre à la start-up : plus ces ressources sont importantes, plus le processus d’internationalisation tend à se faire à grande échelle ; et là aussi, l’influence de ces ressources est augmenté par l’intention stratégique d’internationalisation. Dans le cadre des études empiriques sur les born-globals (entreprises qui démarrent sur un marché globalisé), cette recherche fournit une des premières études empiriques reliant l’influence des conditions initiales de création aux probabilités de croissance internationale rapide.

Relationships between maternal feeding and child weight in younger Australian children – Findings from the NOURISH obesity prevention trial

Studies show that in 3-11 year-olds, parental feeding style is directly associated with child weight [1] and also moderates the association between feeding practices and weight [2]. This cross-sectional study aimed to examine these relationships in younger children. Data from 331 of 698 first-time mothers of healthy term children (151 boys, mean age 24±1 months) enrolled in the NOURISH RCT included (a) measured child weight, (b) self-reported feeding styles and controlling feeding practices, and (c) maternal and child covariates. ANCOVA compared mean child weight-for-age z-score (cWAZ) across 4 feeding styles. Regression examined the associations between cWAZ and 5 controlling feeding practices. Moderated multiple regression analysis was planned to examine effects of feeding style on relationships between feeding practices and cWAZ. Feeding style (indulgent = 38.6%, authoritarian = 35.8%, authoritative = 13.1%, uninvolved = 12.5%) was not independently associated with cWAZ. However, ’pressure to eat’ was negatively associated with cWAZ (�=-0.131, p<0.05) higher pressure associated with lower cWAZ. Given feeding style was not associated with cWAZ, moderation analysis was not performed. Contrary to findings in older children, cWAZ in 2-year-olds was not associated with maternal feeding style. However, the negative association between child weight and pressure feeding found in 6-11year-olds [2] appears to hold in toddlers. Educating mothers about potentially detrimental long-term effects of pressure feeding in early childhood, may be more practical and effective in promoting healthy weight than targeting the less concrete concept of feeding styles. References: [1] Hughes, Appetite, 2005;44:83-92. [2] Hennessy, Appetite, 2010;54:369-377.

Testing the accuracy of luminance maps acquired by smart phone cameras

This paper looks at the accuracy of using the built-in camera of smart phones and free software as an economical way to quantify and analyse light exposure by producing luminance maps from High Dynamic Range (HDR) images. HDR images were captured with an Apple iPhone 4S to capture a wide variation of luminance within an indoor and outdoor scene. The HDR images were then processed using Photosphere software (Ward, 2010.) to produce luminance maps, where individual pixel values were compared with calibrated luminance meter readings. This comparison has shown an average luminance error of ~8% between the HDR image pixel values and luminance meter readings, when the range of luminances in the image is limited to approximately 1,500cd/m2.

Differential pathologic variables and outcomes across the spectrum of adenocarcinoma of the esophagogastric junction

Background Adenocarcinoma of the esophagogastric junction (AEG) as described by Siewert et al. is classified as one entity in the latest (7th Edition) American Joint Cancer Committee/International Union Against Cancer (AJCC/UICC) manual, compared with the previous mix of esophageal and gastric staging systems. The origin of AEG tumors, esophageal or gastric, and their biology remain controversial, particularly for AEG type II (cardia) tumors. Methods We adapted a large prospective database (n = 520: 180 type I, 182 type II, 158 type III) to compare AEG tumors under the new TNM system Pathological variables associated with prognosis were compared (pT, pN, stage, differentiation, R status, lymphovascular invasion, perineural involvement, number of positive nodes, percent of positive nodes, and tumor length), as well as overall survival. Results Compared with AEG type I tumors, type II and type III tumors had significantly (p\0.05) more advanced pN stages, greater number and percentage of positive nodes, poorer differentiation, more radial margin involvement, and more perineural invasion. In AEG type I, 14/180 patients (8%) had[6 involved nodes (pN3), compared with 16 and 30% of patients classified type II and III, respectively. Median survival was significantly (p = 0.03) improved for type I patients (38 months) compared with those with tumors classified as type II (28 months) and type III (24 months). In multivariate analysis node positivity and pN staging but not AEG site had an impact on survival. Conclusions In this series AEG type I is associated with more favorable pathologic features and improved outcomes compared with AEG type II and III. This may reflect earlier diagnosis, but an alternative possibility, that type I may be a unique paradigm with more favorable biology, requires further study. © Société Internationale de Chirurgie 2010.

Estimation of biodiesel properties from chemical composition – An artificial neural network (ANN) approach

Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Evaluation of a pilot-scale oil extraction from microalgae for biodiesel production

Biodiesel derived from microalgae is one of a suite of potential solutions to meet the increasing demand for a renewable, carbon-neutral energy source. However, there are numerous challenges that must be addressed before algae biodiesel can become commercially viable. These challenges include the economic feasibility of harvesting and dewatering the biomass and the extraction of lipids and their conversion into biodiesel. Therefore, it is essential to find a suitable extraction process given these processes presently contribute significantly to the total production costs which, at this stage, inhibit the ability of biodiesel to compete financially with petroleum diesel. This study focuses on pilot-scale (100 kg dried microalgae) solvent extraction of lipids from microalgae and subsequent transesterification to biodiesel. Three different solvents (hexane, isopropanol (IPA) and hexane + IPA (1:1)) were used with two different extraction methods (static and Soxhlet) at bench-scale to find the most suitable solvent extraction process for the pilot-scale. The Soxhlet method extracted only 4.2% more lipid compared to the static method. However, the fatty acid profiles of different extraction methods with different solvents are similar, suggesting that none of the solvents or extraction processes were biased for extraction of particular fatty acids. Considering the cost and availability of the solvents, hexane was chosen for pilot-scale extraction using static extraction. At pilot-scale the lipid yield was found to be 20.3% of total biomass which is 2.5% less than from bench scale. Extracted fatty acids were dominated by polyunsaturated fatty acids (PUFAs) (68.94±0.17%) including 47.7±0.43 and 17.86±0.42% being docosahexaenoic acid (DHA) (C22:6) and docosapentaenoic acid (DPA) (C22:5, ω-3), respectively. These high amounts of long chain poly unsaturated fatty acids are unique to some marine microalgae and protists and vary with environmental conditions, culture age and nutrient status, as well as with cultivation process. Calculated physical and chemical properties of density, viscosity of transesterified fatty acid methyl esters (FAMEs) were within the limits of the biodiesel standard specifications as per ASTM D6751-2012 and EN 14214. The calculated cetane number was, however, significantly lower (17.8~18.6) compared to ASTM D6751-2012 or EN 14214-specified minimal requirements. We conclude that the obtained microalgal biodiesel would likely only be suitable for blending with petroleum diesel to a maximum of 5 to 20%.