Imaging Inter-Edge State Scattering Centers in the Quantum Hall Regime

We use an atomic force microscope tip as a local gate to study the scattering between edge channels in a 2D electron gas in the quantum Hall regime. The scattering is dominated by individual, microscopic scattering centers, which we directly image here for the first time. The tip voltage dependence of the scattering indicates that tunneling occurs through weak links and localized states.Comment: 4 pages, 5 figure

How mobile technologies support business models: Case study-based empirical analysis

[Otros] Les technologies mobiles ont poussé la connectivité des systèmes informatiques à la limite, permettant aux personnes et aux objets de se connecter les uns aux autres à tout moment. La quantité d'informations dont disposent les entreprises a augmenté de façon exponentielle, en grande partie grâce à la géolocalisation et à la vaste gamme de capteurs intégrés dans les appareils mobiles. Ces informations peuvent être utilisées pour améliorer les activités et les processus métier, mais également pour créer de nouveaux modèles d'affaires. En nous concentrant sur les modèles d'affaires, nous analysons les technologies mobiles comme catalyseurs des changements d'activité. Nous examinons les caractéristiques distinctives des technologies mobiles et examinons comment celles¿ci peuvent supporter différentes fonctions de l'entreprise. Une étude basée sur une analyse qualitative comparée d'ensemble floue (fsQCA) de 30 cas, de différents secteurs, a permis d'identifier les facteurs de succès de la technologie mobile pour différentes activités du cœur de métier des firmes. Les résultats montrent que plusieurs combinaisons de technologie mobile procurent un avantage concurrentiel lorsqu'elles correspondent au modèle d'affaire.[EN] Mobile technologies have pushed the connectivity of IT systems to the limit, enabling people and things to connect to one another at all times. The amount of information companies have at their disposal has increased exponentially, thanks largely to geolocation and to the vast array of sensors that have been integrated into mobile devices. This information can be used to enhance business activities and processes, but it can also be used to create new business models. Focusing on business models, we analyze mobile technologies as enablers of activity changes. We consider the differentiating characteristics of mobile technologies and examine how these can support different business functions. A study based on fuzzy-set qualitative comparative analysis (fsQCA) of 30 cases across different industries allows us to identify mobile technology success factors for different core activities. The results show that several combinations of mobile technology initiatives provide a competitive advantage when these initiatives match the business model.Peris-Ortiz, M.; Devece Carañana, CA.; Hikkerova, L. (2020). How mobile technologies support business models: Case study-based empirical analysis. Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration. 37(1):95-105. https://doi.org/10.1002/cjas.1550S95105371Al-Debei, M. M., & Avison, D. (2010). Developing a unified framework of the business model concept. European Journal of Information Systems, 19(3), 359-376. doi:10.1057/ejis.2010.21Arlotto, J., Sahut, J.-M., & Teulon, F. (2011). Le concept de Business Model au travers de la littérature. Gestion 2000, 28(4), 33. doi:10.3917/g2000.284.0033Clemons, E. K. (2009). Business Models for Monetizing Internet Applications and Web Sites: Experience, Theory, and Predictions. Journal of Management Information Systems, 26(2), 15-41. doi:10.2753/mis0742-1222260202Comberg, C., & Velamuri, V. K. (2017). The introduction of a competing business model: the case of eBay. International Journal of Technology Management, 73(1/2/3), 39. doi:10.1504/ijtm.2017.082356Coursaris C. Hassanein H. &Head M. (2006).Mobile technologies and the value chain: Participants activities and value creation(p. 8) sInternational Conference on Mobile Business Copenhagen Denmark.Ehrenhard, M., Wijnhoven, F., van den Broek, T., & Zinck Stagno, M. (2017). Unlocking how start-ups create business value with mobile applications: Development of an App-enabled Business Innovation Cycle. Technological Forecasting and Social Change, 115, 26-36. doi:10.1016/j.techfore.2016.09.011European Parliament(2015).The Internet of things: Opportunities and challenges. Retrieved fromwww.europarl.europa.eu/RegData/etudes/BRIE/2015/557012/EPRS_BRI(2015)557012_EN.pdfGurrin, C., Smeaton, A. F., & Doherty, A. R. (2014). LifeLogging: Personal Big Data. Foundations and Trends® in Information Retrieval, 8(1), 1-125. doi:10.1561/1500000033Hübner, A. H., Kuhn, H., & Wollenburg, J. (2016). Last mile fulfilment and distribution in omni-channel grocery retailing: a strategic planning framework. International Journal of Retail & Distribution Management, 44(3). doi:10.1108/ijrdm-11-2014-0154Kauffman, R. J., & Wang, B. (2008). Tuning into the digital channel: evaluating business model characteristics for Internet firm survival. Information Technology and Management, 9(3), 215-232. doi:10.1007/s10799-008-0040-3Liang, T., Huang, C., Yeh, Y., & Lin, B. (2007). Adoption of mobile technology in business: a fit‐viability model. Industrial Management & Data Systems, 107(8), 1154-1169. doi:10.1108/02635570710822796Martinez-Simarro, D., Devece, C., & Llopis-Albert, C. (2015). How information systems strategy moderates the relationship between business strategy and performance. Journal of Business Research, 68(7), 1592-1594. doi:10.1016/j.jbusres.2015.01.057Mello P.A.(2012).A critical review of applications in QCA and fuzzy‐set analysis and a ‘toolbox' of proven solutions to frequently encountered problems APSA Annual Meeting Paper. Retrieved fromhttps://ssrn.com/abstract=2105539Melville, Kraemer, & Gurbaxani. (2004). Review: Information Technology and Organizational Performance: An Integrative Model of IT Business Value. MIS Quarterly, 28(2), 283. doi:10.2307/25148636Ngai, E. W. T., & Gunasekaran, A. (2007). Mobile commerce: Strategies, technologies, and applications. Decision Support Systems, 43(1), 1-2. doi:10.1016/j.dss.2005.05.002Palattella, M. R., Dohler, M., Grieco, A., Rizzo, G., Torsner, J., Engel, T., & Ladid, L. (2016). Internet of Things in the 5G Era: Enablers, Architecture, and Business Models. IEEE Journal on Selected Areas in Communications, 34(3), 510-527. doi:10.1109/jsac.2016.2525418Pateli, A. G., & Giaglis, G. M. (2005). Technology innovation‐induced business model change: a contingency approach. Journal of Organizational Change Management, 18(2), 167-183. doi:10.1108/09534810510589589Piccoli, & Ives. (2005). Review: IT-Dependent Strategic Initiatives and Sustained Competitive Advantage: A Review and Synthesis of the Literature. MIS Quarterly, 29(4), 747. doi:10.2307/25148708Porter M. E.(2001).Strategy and the Internet. Harvard Business Review March 63–78.Ragin C. C.(2008).User's Guide to Fuzzy‐Set/Qualitative Comparative Analysis. Working Paper University of Arizona Arizona.Ray, G., Barney, J. B., & Muhanna, W. A. (2003). Capabilities, business processes, and competitive advantage: choosing the dependent variable in empirical tests of the resource-based view. Strategic Management Journal, 25(1), 23-37. doi:10.1002/smj.366Richter, C., Kraus, S., & Syrjä, P. (2015). The shareconomy as a precursor for digital entrepreneurship business models. International Journal of Entrepreneurship and Small Business, 25(1), 18. doi:10.1504/ijesb.2015.068773Schneider, M. R., Schulze-Bentrop, C., & Paunescu, M. (2009). Mapping the institutional capital of high-tech firms: A fuzzy-set analysis of capitalist variety and export performance. Journal of International Business Studies, 41(2), 246-266. doi:10.1057/jibs.2009.36Sheng, H., Nah, F. F.-H., & Siau, K. (2005). Strategic implications of mobile technology: A case study using Value-Focused Thinking. The Journal of Strategic Information Systems, 14(3), 269-290. doi:10.1016/j.jsis.2005.07.004Sorescu, A. (2017). Data-Driven Business Model Innovation. Journal of Product Innovation Management, 34(5), 691-696. doi:10.1111/jpim.12398Tallon, P. P. (2007). A Process-Oriented Perspective on the Alignment of Information Technology and Business Strategy. Journal of Management Information Systems, 24(3), 227-268. doi:10.2753/mis0742-1222240308Tjaden, G. S. (1996). Measuring the information age business. Technology Analysis & Strategic Management, 8(3), 233-246. doi:10.1080/09537329608524248Vilmos A. Kovacs K. &Kutor L. (2007).NFC applications and business model of the ecosystem(pp.1469–1473) 16th IST Mobile and Wireless Communications Summit Budapest Hungary. doi:https://doi.org/10.1109/ISTMWC.2007.4299324.Wirtz, B. W., Schilke, O., & Ullrich, S. (2010). Strategic Development of Business Models. Long Range Planning, 43(2-3), 272-290. doi:10.1016/j.lrp.2010.01.005Woodbridge R.(2010).9 mobile business models that you can use right now to generate revenue. Tether. Retrieved February 2 2019 fromhttp://untether.tv/2010/8‐mobile‐business‐models‐that‐you‐can‐use‐right‐now‐to‐generate‐revenue/Woodside, A. G., & Zhang, M. (2011). Identifying X-Consumers Using Causal Recipes: «Whales» and «Jumbo Shrimps» Casino Gamblers. Journal of Gambling Studies, 28(1), 13-26. doi:10.1007/s10899-011-9241-5Woodside, A. G. (2013). Moving beyond multiple regression analysis to algorithms: Calling for adoption of a paradigm shift from symmetric to asymmetric thinking in data analysis and crafting theory. Journal of Business Research, 66(4), 463-472. doi:10.1016/j.jbusres.2012.12.02

Predictive Value of Depressive Symptoms for All-Cause Mortality: Findings From the PRIME Belfast Study Examining the Role of Inflammation and Cardiovascular Risk Markers.

OBJECTIVES: To improve understanding about the potential underlying biological mechanisms in the link between depression and all-cause mortality and to investigate the role that inflammatory and other cardiovascular risk factors may play in the relationship between depressive symptoms and mortality. METHODS: Depression and blood-based biological markers were assessed in the Belfast PRIME prospective cohort study (N = 2389 men, aged 50-59 years) in which participants were followed up for 18 years. Depression was measured using the 10-item Welsh Pure Depression Inventory. Inflammation markers (C-reactive protein [CRP], neopterin, interleukin [IL]-1 receptor antagonist [IL-1Ra], and IL-18) and cardiovascular-specific risk factors (N-terminal pro-b-type natriuretic peptide, midregion pro-atrial natriuretic peptide, midregion pro-adrenomedullin, C-terminal pro-endothelin-1 [CT-proET]) were obtained at baseline. We used Cox proportional hazards modeling to examine the association between depression and biological measures in relation to all-cause mortality and explore the mediating effects. RESULTS: During follow-up, 418 participants died. Higher levels of depressive symptoms were associated with higher levels of CRP, IL-1Ra, and CT-proET. After adjustment for socioeconomic and life-style risk factors, depressive symptoms were significantly associated with all-cause mortality (hazard ratio = 1.10 per scale unit, 95% confidence interval = 1.04-1.16). This association was partly explained by CRP (7.3%) suggesting a minimal mediation effect. IL-1Ra, N-terminal pro-b-type natriuretic peptide, midregion pro-atrial natriuretic peptide, midregion pro-adrenomedullin, and CT-proET contributed marginally to the association between depression and subsequent mortality. CONCLUSIONS: Inflammatory and cardiovascular risk markers are associated with depression and with increased mortality. However, depression and biological measures show additive effects rather than a pattern of meditation of biological factors in the association between depression and mortality

Scanned Potential Microscopy of Edge and Bulk Currents in the Quantum Hall Regime

Using an atomic force microscope as a local voltmeter, we measure the Hall voltage profile in a 2D electron gas in the quantum Hall (QH) regime. We observe a linear profile in the bulk of the sample in the transition regions between QH plateaus and a distinctly nonlinear profile on the plateaus. In addition, localized voltage drops are observed at the sample edges in the transition regions. We interpret these results in terms of theories of edge and bulk currents in the QH regime.Comment: 4 pages, 5 figure

Scanning Fourier Spectroscopy: A microwave analog study to image transmission paths in quantum dots

We use a microwave cavity to investigate the influence of a movable absorbing center on the wave function of an open quantum dot. Our study shows that the absorber acts as a position-selective probe, which may be used to suppress those wave function states that exhibit an enhancement of their probability density near the region where the impurity is located. For an experimental probe of this wave function selection, we develop a technique that we refer to as scanning Fourier spectroscopy, which allows us to identify, and map out, the structure of the classical trajectories that are important for transmission through the cavity.Comment: 4 pages, 5 figure

The Effects of Business Failure Experience on Successive Entrepreneurial Engagements: An Evolutionary Phase Model

This study draws insights from the literatures on entrepreneurial learning from failure and organizational imprinting to develop an evolutionary phase model to explain how prior business failure experience influences successive newly started businesses. Using multiple case studies of entrepreneurs located in an institutionally developing society in Sub-Sahara Africa, we uncover four distinctive phases of post-entrepreneurial business failure: grief and despair, transition, formation and legacy phases. We find that while the grieving and transition phases entailed processes of reflecting and learning lessons from the business failure experiences, the formation and legacy phases involve processes of imprinting entrepreneurs’ experiential knowledge on their successive new start-up firms. We conclude by outlining a number of fruitful avenues for future research

Evidence for the role of EPHX2 gene variants in anorexia nervosa.

Anorexia nervosa (AN) and related eating disorders are complex, multifactorial neuropsychiatric conditions with likely rare and common genetic and environmental determinants. To identify genetic variants associated with AN, we pursued a series of sequencing and genotyping studies focusing on the coding regions and upstream sequence of 152 candidate genes in a total of 1205 AN cases and 1948 controls. We identified individual variant associations in the Estrogen Receptor-ß (ESR2) gene, as well as a set of rare and common variants in the Epoxide Hydrolase 2 (EPHX2) gene, in an initial sequencing study of 261 early-onset severe AN cases and 73 controls (P=0.0004). The association of EPHX2 variants was further delineated in: (1) a pooling-based replication study involving an additional 500 AN patients and 500 controls (replication set P=0.00000016); (2) single-locus studies in a cohort of 386 previously genotyped broadly defined AN cases and 295 female population controls from the Bogalusa Heart Study (BHS) and a cohort of 58 individuals with self-reported eating disturbances and 851 controls (combined smallest single locus P<0.01). As EPHX2 is known to influence cholesterol metabolism, and AN is often associated with elevated cholesterol levels, we also investigated the association of EPHX2 variants and longitudinal body mass index (BMI) and cholesterol in BHS female and male subjects (N=229) and found evidence for a modifying effect of a subset of variants on the relationship between cholesterol and BMI (P<0.01). These findings suggest a novel association of gene variants within EPHX2 to susceptibility to AN and provide a foundation for future study of this important yet poorly understood condition

Mesoscopic models for DNA stretching under force: new results and comparison to experiments

Single molecule experiments on B-DNA stretching have revealed one or two structural transitions, when increasing the external force. They are characterized by a sudden increase of DNA contour length and a decrease of the bending rigidity. It has been proposed that the first transition, at forces of 60--80 pN, is a transition from B to S-DNA, viewed as a stretched duplex DNA, while the second one, at stronger forces, is a strand peeling resulting in single stranded DNAs (ssDNA), similar to thermal denaturation. But due to experimental conditions these two transitions can overlap, for instance for poly(dA-dT). We derive analytical formula using a coupled discrete worm like chain-Ising model. Our model takes into account bending rigidity, discreteness of the chain, linear and non-linear (for ssDNA) bond stretching. In the limit of zero force, this model simplifies into a coupled model already developed by us for studying thermal DNA melting, establishing a connexion with previous fitting parameter values for denaturation profiles. We find that: (i) ssDNA is fitted, using an analytical formula, over a nanoNewton range with only three free parameters, the contour length, the bending modulus and the monomer size; (ii) a surprisingly good fit on this force range is possible only by choosing a monomer size of 0.2 nm, almost 4 times smaller than the ssDNA nucleobase length; (iii) mesoscopic models are not able to fit B to ssDNA (or S to ss) transitions; (iv) an analytical formula for fitting B to S transitions is derived in the strong force approximation and for long DNAs, which is in excellent agreement with exact transfer matrix calculations; (v) this formula fits perfectly well poly(dG-dC) and $\lambda$-DNA force-extension curves with consistent parameter values; (vi) a coherent picture, where S to ssDNA transitions are much more sensitive to base-pair sequence than the B to S one, emerges.Comment: 14 pages, 9 figure