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

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

Iron deficiency without anemia is responsible for decreased left ventricular function and reduced mitochondrial complex I activity in a mouse model

BACKGROUND: Iron deficiency (ID), with or without anemia, is frequent in heart failure patients, and iron supplementation improves patient condition. However, the link between ID (independently of anemia) and cardiac function is poorly understood, but could be explained by an impaired mitochondrial metabolism. Our aim was to explore this hypothesis in a mouse model. METHODS AND RESULTS: We developed a mouse model of ID without anemia, using a blood withdrawal followed by 3-weeks low iron diet. ID was confirmed by low spleen, liver and heart iron contents and the repression of HAMP gene coding for hepcidin. ID was corrected by a single ferric carboxymaltose (FCM) injection (ID + FCM mice). Hemoglobin levels were similar in ID, ID + FCM and control mice. ID mice had impaired physical performances and left ventricular function (echocardiography). Mitochondrial complex I activity of cardiomyocytes was significantly decreased in ID mice, but not complexes II, III and IV activities. ID + FCM mice had improved physical performance, cardiac function and complex I activity compared to ID mice. Using BN-PAGE, we did not observe complex I disassembly, but a reduced quantity of the whole enzyme complex I in ID mice, that was restored in ID + FCM mice. CONCLUSIONS: ID, independently of anemia, is responsible for a decreased left ventricular function, through a reduction in mitochondrial complex I activity, probably secondary to a decrease in complex I quantity. These abnormalities are reversed after iron treatment, and may explain, at least in part, the benefit of iron supplementation in heart failure patients with ID

Estrogen-related receptor α and PGC-1-related coactivator constitute a novel complex mediating the biogenesis of functional mitochondria

Mitochondrial biogenesis, which depends on nuclear as well as mitochondrial genes, occurs in response to increased cellular ATP demand. The nuclear transcriptional factors, estrogen-related receptor α (ERRα) and nuclear respiratory factors 1 and 2, are associated with the coordination of the transcriptional machinery governing mitochondrial biogenesis, whereas coactivators of the peroxisome proliferator-activated receptor γ coactivator-1 (PGC-1) family serve as mediators between the environment and this machinery. In the context of proliferating cells, PGC-1-related coactivator (PRC) is a member of the PGC-1 family, which is known to act in partnership with nuclear respiratory factors, but no functional interference between PRC and ERRα has been described so far. We explored three thyroid cell lines, FTC-133, XTC.UC1 and RO 82 W-1, each characterized by a different mitochondrial content, and studied their behavior towards PRC and ERRα in terms of respiratory efficiency. Overexpression of PRC and ERRα led to increased respiratory chain capacity and mitochondrial mass. The inhibition of ERRα decreased cell growth and respiratory chain capacity in all three cell lines. However, the inhibition of PRC and ERRα produced a greater effect in the oxidative cell model, decreasing the mitochondrial mass and the phosphorylating respiration, whereas the nonphosphorylating respiration remained unchanged. We therefore hypothesize that the ERRα–PRC complex plays a role in arresting the cell cycle through the regulation of oxidative phosphorylation in oxidative cells, and through some other pathway in glycolytic cells

Mechanical Effects in PEM Fuel Cell: Application to Modeling of Assembly Procedure

Mechanical effects can influence significantly electrical performance and life time of PEM fuel cells. A linear elasticplastic 2D model of fuel cell with hardening is used for modeling of assembly procedure of fuel cells. The model simulates mechanical behavior of the main components of real fuel cell (the membrane, the gas diffusion layers, the graphite plates, and the seal joints) and clamping elements (the steel plates, the bolts, the nuts). The stress and plastic deformation in MEA have been calculated using ABAQUS code. The results are presented on the local and the global scales with respect to the realistic clamping conditions. The first one corresponds to the single tooth/channel structure. The global scale deals with features of the entire cell and takes into account the border effects, in particular the influence of seal joints

Estrogenic regulation of claudin 5 and tight junction protein 1 gene expression in zebrafish: A role on blood-brain barrier?

The blood-brain barrier (BBB) is a physical interface between the blood and the brain parenchyma, playing key roles in brain homeostasis. In mammals, the BBB is established thanks to tight junctions between cerebral endothelial cells, involving claudin, occludin, and zonula occludens proteins. Estrogens have been documented to modulate BBB permeability. Interestingly, in the brain of zebrafish, the estrogen-synthesizing activity is strong due to the high expression of Aromatase B protein, encoded by the cyp19a1b gene, in radial glial cells (neural stem cells). Given the roles of estrogens in BBB function, we investigated their impact on the expression of genes involved in BBB tight junctions. We treated zebrafish embryos and adult males with 17β-estradiol and observed an increased cerebral expression of tight junction and claudin 5 genes in adult males only. In females, treatment with the nuclear estrogen receptor antagonist (ICI182,780 ) had no impact. Interestingly, telencephalic injuries performed in males decreased tight junction gene expression that was partially reversed with 17β-estradiol. This was further confirmed by extravasation experiments of Evans blue showing that estrogenic treatment limits BBB leakage. We also highlighted the intimate links between endothelial cells and neural stem cells, suggesting that cholesterol and peripheral steroids could be taken up by endothelial cells and used as precursors for estrogen synthesis by neural stem cells. Together, our results show that zebrafish provides an alternative model to further investigate the role of steroids on the expression of genes involved in BBB integrity, both in constitutive and regenerative physiological conditions. The link we described between capillaries endothelial cells and steroidogenic neural cells encourages the use of this model in understanding the mechanisms by which peripheral steroids get into neural tissue and modulate neurogenic activity

Geological and geophysical characterization of the southeastern side of the High Agri Valley (southern Apennines, Italy)

Abstract. In the frame of a national project funded by Eni S.p.A. and developed by three institutes of the National Research Council (the Institute of Methodologies for Environmental Analysis, the Institute of Research for Hydrogeological Protection and the Institute for Electromagnetic Sensing of the Environment), a multidisciplinary approach based on the integration of satellite, aero-photogrammetric and in situ geophysical techniques was applied to investigate an area located in the Montemurro territory in the southeastern sector of the High Agri Valley (Basilicata Region, southern Italy). This paper reports the results obtained by the joint analysis of in situ geophysical surveys, aerial photos interpretation, morphotectonic investigation, geological field survey and borehole data. The joint analysis of different data allowed us (1) to show the shallow geological and structural setting, (2) to detect the geometry of the different lithological units and their mechanical and dynamical properties, (3) to image a previously unmapped fault beneath suspected scarps/warps and (4) to characterize the geometry of an active landslide affecting the study area

Corrigendum to "Geological and geophysical characterization of the southeastern side of the High Agri Valley (southern Apennines, Italy)" published in Nat. Hazards Earth Syst. Sci., 15, 315–323, 2015

No abstract available

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

Knockout studies reveal an important role of <i>plasmodium</i> lipoic acid protein ligase a1 for asexual blood stage parasite survival

Lipoic acid (LA) is a dithiol-containing cofactor that is essential for the function of a-keto acid dehydrogenase complexes. LA acts as a reversible acyl group acceptor and 'swinging arm' during acyl-coenzyme A formation. The cofactor is post-translationally attached to the acyl-transferase subunits of the multienzyme complexes through the action of octanoyl (lipoyl): &lt;i&gt;N&lt;/i&gt;-octanoyl (lipoyl) transferase (LipB) or lipoic acid protein ligases (LplA). Remarkably, apicomplexan parasites possess LA biosynthesis as well as scavenging pathways and the two pathways are distributed between mitochondrion and a vestigial organelle, the apicoplast. The apicoplast-specific LipB is dispensable for parasite growth due to functional redundancy of the parasite's lipoic acid/octanoic acid ligases/transferases. In this study, we show that &lt;i&gt;LplA1&lt;/i&gt; plays a pivotal role during the development of the erythrocytic stages of the malaria parasite. Gene disruptions in the human malaria parasite &lt;i&gt;P.falciparum&lt;/i&gt; consistently were unsuccessful while in the rodent malaria model parasite &lt;i&gt;P. berghei&lt;/i&gt; the &lt;i&gt;LplA1&lt;/i&gt; gene locus was targeted by knock-in and knockout constructs. However, the &lt;i&gt;LplA1&lt;/i&gt; &lt;sup&gt;(-)&lt;/sup&gt; mutant could not be cloned suggesting a critical role of LplA1 for asexual parasite growth &lt;i&gt;in vitro&lt;/i&gt; and &lt;i&gt;in vivo&lt;/i&gt;. These experimental genetics data suggest that lipoylation during expansion in red blood cells largely occurs through salvage from the host erythrocytes and subsequent ligation of LA to the target proteins of the malaria parasite