20 research outputs found

    The rise of micro and small-scale entrepreneurial activity in a melting down economy: a case of Zimbabwe.

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    Ph. D. University of KwaZulu-Natal, Pietermaritzburg 2014.Entrepreneurship is viewed as a pertinent vehicle for economic growth, development, employment creation and income generation (entrepreneurial effects). Small-scale, micro and medium enterprises (SMMEs) are the dominant entrepreneurial activity in Africa, but less than 1% of these SMMEs grow to ten or more employees. A lack of homogeneity among SMMEs, making it difficult for common policies to be effective is the problem most often identified as the cause of this lack of growth. In the period 1997 to 2008, Zimbabwe experienced an economic meltdown which plunged many citizens into poverty. On the other hand, a steep growth in micro and small-scale enterprises (MSEs) was also observed in both formal and informal sectors. Following the meltdown these MSEs are still operational but with minimal contribution to the recovery of the economy. This thesis looked at the micro and macro aspects of micro and small-scale entrepreneurship in Zimbabwe in the wake of the economic meltdown. At the macro level, the objective was to develop a model that best describes the relationship between the economic meltdown and the growth of micro and small-scale enterprises (MSEs) in Zimbabwe, by testing for the presence of refugee effects. Understanding the relationship between entrepreneurship and key macroeconomic growth indicators is critical for generating growth and development in both a normal, and a meltdown economy. Using annual data from 1980 to 2010, a multivariate Vector Error Correction Model (VECM) was run, with the total number of MSEs, unemployment rate, inflation rate, liquidity (proxied by money supply) and real GDP as the dependent variables. The main findings of this study indicate the presence of refugee effects from unemployment, albeit minimal, and that the growth in MSEs was significant because of the shortage of liquidity. The relationship between unemployment and entrepreneurship is not linear, but squared and positive in both instances. At the micro level, three objectives underpinned this study. The first objective was to examine whether there were differences in entrepreneurial attributes between formal sector and informal sector firms, using descriptive statistics and non-parametric t-tests. The second objective was to assess the nature of the growth constraints of existing MSEs (formal and iii informal), and compare them across the two sectors. The constraints were examined from two sources: internal and external. The methodology used in this case was factor analysis and principal component analysis. On the basis of the constraints classifications generated from principal component analysis, a regression was done to test whether the constraints are related to the willingness to formalise by informal MSEs. The contribution of need for achievement (N-Ach) on willingness to formalise was also tested in a logistic regression. Relevant data for the micro level analysis was collected by means of a survey in Harare, Zimbabwe. Using a questionnaire, 150 MSEs operating in both formal and informal sectors were interviewed. The questionnaire had 3 sections: the first section characterised the MSEs; the second section looked at the growth constraints of the MSEs and last section measured the need for achievement (N-Ach) of the business owner, using the Mehrabian scale of achieving tendency. The data collected was analysed using SPSS and STATA. The main findings were that the characteristics of the MSEs in the formal sector are different to those of the informal sector. Formal sectors identified internal factors as hindering the growth of their business more than the external factors, whereas the informal MSEs identified more external factors as constraints to their growth. From the logistic regression analysis, ‘regulatory factors’ and ‘technology factors’ were found to have a significant impact on the willingness by informal MSEs to formalise their business. Improving N-Ach may significantly decrease the odds of the informal MSEs formalising their businesses. The study concluded that MSE growth was in response to the economic meltdown, being driven by the refugee effects from a need for liquidity and rising unemployment. Secondly, uniform policies for MSEs in formal and informal sectors fail to address their individual growth needs because of the differences in the dynamics of entrepreneurs operating in the formal sector and informal sector. Thirdly the odds of willingness to formalise by informal MSEs are positively linked to the regulatory framework around the process of business registration

    Principles of data management and sharing at European Research Infrastructures

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    Under the umbrella of the BioMedBridges project, fourteen research infrastructures in the biological, biomedical and environmental sciences developed commonly agreed principles of data management and sharing. The document makes key recommendations on how data management and sharing via the research infrastructures can be supported and encouraged: The RIs encourage data sharing and reuse and support the notion that public funders should encourage Open Access to data from publicly funded research where possible. Some data may only be shared under certain conditions and with appropriate safekeeping mechanisms in place, such as personally identifiable data, data subject to ethical or legal restrictions, or restrictions for intellectual property protection. To encourage data sharing, systematic reward and recognition mechanisms are necessary. Proposals for publicly funded research at RIs should include a data management plan concerning the deposition of data in long-term archives that addresses specific resources and activities (including standardisation of data production and curation/annotation). Funding for tools and activities connected to data deposition must be available. Systems, services and resources must be in place to facilitate straightforward data deposition by researchers, including support concerning the necessary data use agreements and consent forms for data with data protection or intellectual property requirements. Systems are also needed to capture and track data provenance and use. To ensure necessary trust by data providers or depositors, RIs must guarantee high standards of security and traceability

    Structure and physical properties of the LaBiFe2O6 Perovskite produced by the Modified Pechini Method

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    ABSTRACT: In this paper the synthesis of the LaBiFe2O6 material by the modified Pechini method is reported. Structural, morphologic, magnetic and optic experimental studies were performed. Rietveld refinement of x-ray diffraction patterns revealed that LaBiFe2O6 crystallizes in an orthorhombic perovskite structure (space group Pnma, # 62). Scanning electron microscopy images showed the nanometric feature of grains. X-ray dispersive spectroscopy permitted to infer the obtaining of the LaBiFe2O6 expected stoichiometry. Results of magnetic susceptibility as a function of temperature and field magnetization evidenced mixed ferromagnetism and superparamagnetism behavior at T=300 K. Mössbauer spectroscopy supported the superparamagnetic and ferromagnetic responses as a result of the nanogranular morphology and anisotropy effects. Spectrum of diffuse reflectance suggest that this material behaves as a semiconductor with energy gap Eg=2.13 eV

    DOME: recommendations for supervised machine learning validation in biology

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    Supervised machine learning is widely used in biology and deserves more scrutiny. We present a set of community-wide recommendations (DOME) aiming to help establish standards of supervised machine learning validation in biology. Formulated as questions, the DOME recommendations improve the assessment and reproducibility of papers when included as supplementary material.The work of the Machine Learning Focus Group was funded by ELIXIR, the research infrastructure for life-science data. IW was funded by the A*STAR Career Development Award (project no. C210112057) from the Agency for Science, Technology and Research (A*STAR), Singapore. D.F. was supported by Estonian Research Council grants (PRG1095, PSG59 and ERA-NET TRANSCAN-2 (BioEndoCar)); Project No 2014-2020.4.01.16-0271, ELIXIR and the European Regional Development Fund through EXCITE Center of Excellence. S.C.E.T. has received funding from the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie Grant agreements No. 778247 and No. 823886, and Italian Ministry of University and Research PRIN 2017 grant 2017483NH8.Peer Reviewed"Article signat per 8 autors més 28 autors/es de l' ELIXIR Machine Learning Focus Group: Emidio Capriotti, Rita Casadio, Salvador Capella-Gutierrez, Davide Cirillo, Alessio Del Conte, Alexandros C. Dimopoulos, Victoria Dominguez Del Angel, Joaquin Dopazo, Piero Fariselli, José Maria Fernández, Florian Huber, Anna Kreshuk, Tom Lenaerts, Pier Luigi Martelli, Arcadi Navarro, Pilib Ó Broin, Janet Piñero, Damiano Piovesan, Martin Reczko, Francesco Ronzano, Venkata Satagopam, Castrense Savojardo, Vojtech Spiwok, Marco Antonio Tangaro, Giacomo Tartari, David Salgado, Alfonso Valencia & Federico Zambelli"Postprint (author's final draft

    DataSHIELD: taking the analysis to the data, not the data to the analysis

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    Research in modern biomedicine and social science requires sample sizes so large that they can often only be achieved through a pooled co-analysis of data from several studies. But the pooling of information from individuals in a central database that may be queried by researchers raises important ethico-legal questions and can be controversial. In the UK this has been highlighted by recent debate and controversy relating to the UK's proposed 'care.data' initiative, and these issues reflect important societal and professional concerns about privacy, confidentiality and intellectual property. DataSHIELD provides a novel technological solution that can circumvent some of the most basic challenges in facilitating the access of researchers and other healthcare professionals to individual-level data. Commands are sent from a central analysis computer (AC) to several data computers (DCs) storing the data to be co-analysed. The data sets are analysed simultaneously but in parallel. The separate parallelized analyses are linked by non-disclosive summary statistics and commands transmitted back and forth between the DCs and the AC. This paper describes the technical implementation of DataSHIELD using a modified R statistical environment linked to an Opal database deployed behind the computer firewall of each DC. Analysis is controlled through a standard R environment at the AC. Based on this Opal/R implementation, DataSHIELD is currently used by the Healthy Obese Project and the Environmental Core Project (BioSHaRE-EU) for the federated analysis of 10 data sets across eight European countries, and this illustrates the opportunities and challenges presented by the DataSHIELD approach. DataSHIELD facilitates important research in settings where: (i) a co-analysis of individual-level data from several studies is scientifically necessary but governance restrictions prohibit the release or sharing of some of the required data, and/or render data access unacceptably slow; (ii) a research group (e.g. in a developing nation) is particularly vulnerable to loss of intellectual property-the researchers want to fully share the information held in their data with national and international collaborators, but do not wish to hand over the physical data themselves; and (iii) a data set is to be included in an individual-level co-analysis but the physical size of the data precludes direct transfer to a new site for analysis

    ILOG Elixir

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    遠江国 浜松藩 飛地札 浜松領肥シ預 銀1匁

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    日本銀行金融研究所所蔵藩札等資料番号:ⅢAエドa1-11-2イ-2科学研究費助成事業(研究成果公開促進費)で電子化を実施データベースの名称:藩札等に関する統合データベース課題番号:19HP8033利用に関するお問い合わせ:画像の転載(出版物・HP等)に際しては、日本銀行貨幣博物館への申請手続きが必要です。詳しくは貨幣博物館ホームページ(http://www.imes.boj.or.jp/cm/service/)をご覧ください

    Simulación de funciones de transferencia para espectroscopía de impedancia electroquímica (EIS)

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    Different transfer function simulations of electrode-electrolyte interfaces were made using a graphic environment in LabVIEW®, additionally a example set of experimental data were fitted. These transfer functions are analyzed by equivalent electric circuits, including from simple ele-ments like resistors, capacitors and inductors to complicated elements like constant phase elements (CPE) and Warburg element (finite or infinite). The LabVIEW advantages with its programming in a graphic environment, is used to generate equivalent circuit spectra in Nyquist and Bode plots, and quick variations of the properties of each element in the electric circuit. With this work it is wanted to facilitate the phenomena interpretation in electrode-electrolyte interfaces, besides it¿s a support tool for current fitting EIS spectra software such as Zview® from Scribner Associates, Inc and EIS300® from Gamry Echem Analyst¿.Se realizaron simulaciones de funciones de transferencia para diferentes tipos de interfases elec-trodo-electrolito utilizando una presentación gráfica en LabVIEW®, además del ajuste de datos experimentales. Estas funciones de transferencia se analizan a través de circuitos eléctricos equiva-lentes compuestos por elementos simples como resistencias, condensadores e inductores y elemen-tos complejos como los elementos de fase constante (CPE), y Warburg finito e infinito. Las venta-jas que ofrece LabVIEW con su programación en un entorno grafico, se utiliza como una herra-mienta para la generación de los espectros de circuitos equivalentes en diagramas Nyquist y Bode, y para una rápida variación de las propiedades de cada elemento en el circuito eléctrico. Con este trabajo se desea facilitar la interpretación de los fenómenos en las interfases electrodo-electrolito, además de ser una herramienta de apoyo para software de ajuste de espectros EIS como Zview® de Scribner Associates, Inc. y EIS300® de Gamry Echem Analyst¿

    D4.3 The ELIXIR Compute Platform: A Technical Services Roadmap for supporting Life Science Research in Europe

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    This version of the ELIXIR Technical Services Roadmap (ELIXIR-EXCELERATE deliverable D4.3) has been written at the end of PY3 of the ELIXIR-EXCELERATE project (August 2018) and represents an update to the previous version that was established in August 2017 ( Deliverable D4.2) and will be updated again in Summer 2019 before the project ends. This version of the roadmap contains a summary of the technical work undertaken during PY3, an assessment of the Platform’s capability defined through a number of Technical Use Cases (TUCs), and an assessment of the ability of the ELIXIR Compute Platform (through these TUCs) to support scientific community-driven use cases, and the plans for the future evolution of these integrated services during PY4. The ELIXIR Compute Platform (ECP) experts have met twice this year to communicate progress in technical service integration driven by the requirements of the ELIXIR scientific communities. The ELIXIR Technical Services Roadmap focuses on requirements of four ELIXIR communities (i.e. marine metagenomics, plants, rare diseases and human data) and training. As these communities also evolve quickly, the roadmap is a living document that provides advice as to the current and future implementation activities, and is subject to change between versions that is publicly accessible and commentable

    ELIXIR in a Business Model Canvas

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    The Business Model Canvas (BMC) is strategic management tool that is used in handling business models in environments where they need to be created, discussed, challenged and possibly redesigned.<br>The ELIXIR-PT node assembled a team to use this tool in a challenging discussion. The exercise consisted in using perceived information manually extracted from the public websites of the ELIXIR-PT and ELIXIR Hub to populate two improvised BMC. Then, we used group discussions to challenge and refine these models until the majority around the table agreed on the successive modifications.<br>The agreed models represent what is perceived from the websites, if we were to define them as businesses, with terms chosen by the team in an attempt to use a unified language, and to refine the value propositions and the relations with the other elements of the models.<br><br>The ELIXIR-PT Business Model<br>The technique was used to highlight the way in which the identified core values relate with the planned activities, resources and partnerships. <br>Competences in Woody Plants and Elixir Branding emerged as proposed values, while the enhancement of the relations with the Bioengineering and Biomedical communities were identified as important targets for the generation of added value.<br>This model can undergo further refinements, but it can already be used to inform and think strategically about the ongoing building of BIODATA.PT (the major infrastructural support of the node in the scope of the Portuguese Roadmap of Research Infrastructures).<br><br>The ELIXIR Hub Business Mode
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