Start-ups in entrepreneurial ecosystems: the role of relational capacity

Purpose: Entrepreneurial ecosystems provide the context for start-ups to access resources. The authors investigate the reliance of start-ups on their entrepreneurial ecosystem and the driving factors behind the proportion of local actors (belonging to their entrepreneurial ecosystem) within their overall set of relationships (their business ecosystem). Recognizing the limited relational capacity of firms, the authors focus on three differentiating firm characteristics: size, age and innovation of firms. Design/methodology/approach: The authors developed a sample of 163 start-ups located in the entrepreneurial ecosystem of Toulouse, France. The authors investigated the characteristics of their relationship sets using regression analysis. Findings: The results confirm that age is inversely related to the proportion of a start-up's relationships located in its entrepreneurial ecosystem. More surprisingly, for older start-ups, the authors also highlight the presence of a moderating effect of the start-up's size on the relationship between its degree of innovation and the proportion of its relationships in its entrepreneurial ecosystem: Larger and more innovative start-ups appear to rely more on their local entrepreneurial ecosystem. Originality/value: This research increases the understanding of the characteristics driving the interactions of start-ups with their entrepreneurial ecosystems by adopting a relational capacity approach. The authors introduce digital methods as an innovative approach for uncovering firms' ecosystems. Finally, from a practical point of view, the research should provide public authorities seeking to promote the link between local resources and the development of innovative start-ups in their regions with interesting insights

Reference Limits of Plasma Fibrinogen

Peer Reviewe

Earthquake Early Warning System for Structural Drift Prediction Using Machine Learning and Linear Regressors

In this work, we explored the feasibility of predicting the structural drift from the first seconds of P-wave signals for On-site Earthquake Early Warning (EEW) applications. To this purpose, we investigated the performance of both linear least square regression (LSR) and four non-linear machine learning (ML) models: Random Forest, Gradient Boosting, Support Vector Machines and K-Nearest Neighbors. Furthermore, we also explore the applicability of the models calibrated for a region to another one. The LSR and ML models are calibrated and validated using a dataset of ∼6,000 waveforms recorded within 34 Japanese structures with three different type of construction (steel, reinforced concrete, and steel-reinforced concrete), and a smaller one of data recorded at US buildings (69 buildings, 240 waveforms). As EEW information, we considered three P-wave parameters (the peak displacement, Pd, the integral of squared velocity, IV2, and displacement, ID2) using three time-windows (i.e., 1, 2, and 3 s), for a total of nine features to predict the drift ratio as structural response. The Japanese dataset is used to calibrate the LSR and ML models and to study their capability to predict the structural drift. We explored different subsets of the Japanese dataset (i.e., one building, one single type of construction, the entire dataset. We found that the variability of both ground motion and buildings response can affect the drift predictions robustness. In particular, the predictions accuracy worsens with the complexity of the dataset in terms of building and event variability. Our results show that ML techniques perform always better than LSR models, likely due to the complex connections between features and the natural non-linearity of the data. Furthermore, we show that by implementing a residuals analysis, the main sources of drift variability can be identified. Finally, the models trained on the Japanese dataset are applied the US dataset. In our application, we found that the exporting EEW models worsen the prediction variability, but also that by including correction terms as function of the magnitude can strongly mitigate such problem. In other words, our results show that the drift for US buildings can be predicted by minor tweaks to models

A new algorithm for brown and black carbon identification and organic carbon detection in fine atmospheric aerosols by a multi-wavelength Aethalometer

A novel approach for the analysis of aerosol absorption coefficient measurements is presented. A 7-wavelenghts aethalometer has been employed to identify brown carbon (BrC) and black carbon (BC) and to detect organic carbon (OC) in fine atmospheric aerosols (PM2.5). The Magee Aethalometer estimates the BC content in atmospheric particulate by measuring the light attenuation in the aerosols accumulated on a quartz filter, at the standard wavelength λ = 0.88 μm. The known Magee algorithm is based on the hypothesis of a mass absorption coefficient inversely proportional to the wavelength. The new algorithm has been developed and applied to the whole spectral range; it verifies the spectral absorption behavior and, thus, it distinguishes between black and brown carbon. Moreover, it allows also to correct the absorption estimation at the UV wavelength commonly used to qualitatively detect the presence of mixed hydrocarbons. The algorithm has been applied to data collected in Agri Valley, located in Southern Italy, where torched crude oil undergoes a pre-treatment process. The Magee Aethalometer has been set to measure Aerosol absorption coefficients τaer (λ, t) every 5 min. Wavelength dependence of τaer (λ, t) has been analyzed by a best-fit technique and, excluding UV-wavelengths, both the absorption Angstrom coefficient α and the BC (or BrC) concentration have been determined. Finally, daily histograms of α provide information on optical properties of carbonaceous aerosol, while the extrapolation at UV-wavelengths gives information on the presence of semivolatile organic carbon (OC) particles

Mitochondrial effects of dexamethasone imply both membrane and cytosolic-initiated pathways in HepG2 cells

Glucocorticoid treatment is often linked to increased whole-body energy expenditure and hypermetabolism. Glucocorticoids affect mitochondrial energy production, notably in the liver, where they lead to mitochondrial uncoupling reducing the efficacy of oxidative phosphorylation. However, the signaling pathways involved in these phenomena are poorly understood. Here we treated HepG2 cells with dexamethasone for different times and, by using different combinations of inhibitors, we showed that dexamethasone treatment leads to recruitment of two main signaling pathways. The first one involves a G-protein coupled membrane glucocorticoid binding site and rapidly decreases complexes I and II activities while complex III activity is upregulated in a p38MAPK dependent mechanism. The second one implies the classical cytosolic glucocorticoid receptor and triggers long-term transcriptional increases of respiration rates and of complex IV activity and quantity. We concluded that mitochondria are the target of multiple dexamethasone-induced regulatory pathways that are set up gradually after the beginning of hormone exposure and that durably influence mitochondrial oxidative phosphorylation

3D propagation of the shock-induced vibrations through the whole lower-limb during running

Shock-induced vibrations to the feet have been related to the feel of comfort, the biomechanical control of performance, and the risk of fatigue or injury. Up to recently, the complexity of measuring the human biodynamic response to vibration exposure implied to focus most of the research on the axial acceleration at the tibia. Using wireless three-dimensional accelerometers, this paper investigates the propagation of shock-induced vibrations through the whole lower-limb during running in the temporal and the spectral domains. Results indicated that the vibrations were not consistent across the lower-limb, showing various spatial and spectral distributions of energy. The amount of energy was not constantly decreasing from the distal to the proximal extremity of the runner’s lower-limb, especially regarding the lateral epicondyle of the femur. Vibrations in the transversal plane of the segments were substantial compared to the longitudinal axis regarding the distal extremity of the tibia, and the lateral epicondyle of the femur. Further, the spectral content was wider at the distal than at the proximal end of the lower-limb. Finally, to get a thorough understanding of the risks incurred by the runners, the need to account for shock-induced vibrations up to 50 Hz has been stressed when investigating three-dimensional vibrations. The overall study raises attention on the substantial importance of the transverse components of the acceleration, and their potential relation to shear fatigue and injury during running

The XMM-LSS Survey: A well controlled X-ray cluster sample over the D1 CFHTLS area

We present the XMM-LSS cluster catalogue corresponding to the CFHTLS D1 area. The list contains 13 spectroscopically confirmed, X-ray selected galaxy clusters over 0.8 deg2 to a redshift of unity and so constitutes the highest density sample of clusters to date. Cluster X-ray bolometric luminosities range from 0.03 to 5x10^{44} erg/s. In this study, we describe our catalogue construction procedure: from the detection of X-ray cluster candidates to the compilation of a spectroscopically confirmed cluster sample with an explicit selection function. The procedure further provides basic X-ray products such as cluster temperature, flux and luminosity. We detected slightly more clusters with a (0.5-2.0 keV) X-ray fluxes of >2x10^{-14} erg/s/cm^{-2} than we expected based on expectations from deep ROSAT surveys. We also present the Luminosity-Temperature relation for our 9 brightest objects possessing a reliable temperature determination. The slope is in good agreement with the local relation, yet compatible with a luminosity enhancement for the 0.15 < z< 0.35 objects having 1 < T < 2 keV, a population that the XMM-LSS is identifying systematically for the first time. The present study permits the compilation of cluster samples from XMM images whose selection biases are understood. This allows, in addition to studies of large-scale structure, the systematic investigation of cluster scaling law evolution, especially for low mass X-ray groups which constitute the bulk of our observed cluster population. All cluster ancillary data (images, profiles, spectra) are made available in electronic form via the XMM-LSS cluster database.Comment: 12 pages 5 figures, MNRAS accepted. The paper with full resolution cluster images is available at http://vela.astro.ulg.ac.be/themes/spatial/xmm/LSS/rel_pub_e.htm

The addition of ketone bodies alleviates mitochondrial dysfunction by restoring complex I assembly in a MELAS cellular model

Ketogenic Diet used to treat refractory epilepsy for almost a century may represent a treatment option for mitochondrial disorders for which effective treatments are still lacking. Mitochondrial complex I deficiencies are involved in a broad spectrum of inherited diseases including Mitochondrial Encephalomyopathy, Lactic Acidosis and Stroke-like episodes syndrome leading to recurrent cerebral insults resembling strokes and associated with a severe complex I deficiency caused by mitochondrial DNA (mtDNA) mutations. The analysis of MELAS neuronal cybrid cells carrying the almost homoplasmic m.3243A&gt;G mutation revealed a metabolic switch towards glycolysis with the production of lactic acid, severe defects in respiratory chain activity and complex I disassembly with an accumulation of assembly intermediates. Metabolites, NADH/NAD ratio, mitochondrial enzyme activities, oxygen consumption and BN-PAGE analysis were evaluated in mutant compared to control cells. A severe complex I enzymatic deficiency was identified associated with a major complex I disassembly with an accumulation of assembly intermediates of 400kDa. We showed that Ketone Bodies (KB) exposure for 4weeks associated with glucose deprivation significantly restored complex I stability and activity, increased ATP synthesis and reduced the NADH/NAD+ ratio, a key component of mitochondrial metabolism. In addition, without changing the mutant load, mtDNA copy number was significantly increased with KB, indicating that the absolute amount of wild type mtDNA copy number was higher in treated mutant cells. Therefore KB may constitute an alternative and promising therapy for MELAS syndrome, and could be beneficial for other mitochondrial diseases caused by complex I deficiency

The XMM-LSS catalogue: X-ray sources and associated optical data. Version I

Following the presentation of the XMM-LSS X-ray source detection package by Pacaud et al., we provide the source lists for the first 5.5 surveyed square degrees. The catalogues pertain to the [0.5-2] and [2-10] keV bands and contain in total 3385 point-like or extended sources above a detection likelihood of 15 in either band. The agreement with deep logN-logS is excellent. The main parameters considered are position, countrate, source extent with associated likelihood values. A set of additional quantities such as astrometric corrections and fluxes are further calculated while errors on the position and countrate are deduced from simulations. We describe the construction of the band-merged catalogue allowing rapid sub-sample selection and easy cross-correlation with external multi-wavelength catalogues. A small optical CFHTLS multi-band subset of objects is associated wich each source along with an X-ray/optical overlay. We make the full X-ray images available in FITS format. The data are available at CDS and, in a more extended form, at the Milan XMM-LSS database.Comment: 13 pages, 7 figures and 11 tables (fig. 1 and 6 are enclosed in reduced resolution), MNRAS Latex, accepted by MNRA