985 resultados para Data share
Resumo:
Ever since Adam Smith, economists have argued that share contracts do not provide proper incentives. This paper uses tenancy data from India to assess the existence of missing incentives in this classical example of moral hazard. Sharecroppers are found to be less productive than owners, but as productive as fixed-rent tenants. Also, the productivity gap between owners and both types of tenants is driven by sample-selection issues. An endogenous selection rule matches tenancy contracts with less-skilled farmers and lower-quality lands. Due to complementarity, such a matching affects tenants’ input choices. Controlling for that, the contract form has no effect on the expected output. Next, I explicitly model farmer’s optimal decisions to test the existence of non-contractible inputs being misused. No evidence of missing incentives is found.
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Sharing sensor data between multiple devices and users can be^challenging for naive users, and requires knowledge of programming and use of different communication channels and/or development tools, leading to non uniform solutions. This thesis proposes a system that allows users to access sensors, share sensor data and manage sensors. With this system we intent to manage devices, share sensor data, compare sensor data, and set policies to act based on rules. This thesis presents the design and implementation of the system, as well as three case studies of its use.
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Despite the abundant availability,of protocols and application for peer-to-peer file sharing, several drawbacks are still present in the field. Among most notable drawbacks is the lack of a simple and interoperable way to share information among independent peer-to-peer networks. Another drawback is the requirement that the shared content can be accessed only by a limited number of compatible applications, making impossible their access to others applications and system. In this work we present a new approach for peer-to-peer data indexing, focused on organization and retrieval of metadata which describes the shared content. This approach results in a common and interoperable infrastructure, which provides a transparent access to data shared on multiple data sharing networks via a simple API. The proposed approach is evaluated using a case study, implemented as a cross-platform extension to Mozilla Fir fox browser; and demonstrates the advantages of such interoperability over conventional distributed data access strategies.
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Despite the abundant availability of protocols and application for peer-to-peer file sharing, several drawbacks are still present in the field. Among most notable drawbacks is the lack of a simple and interoperable way to share information among independent peer-to-peer networks. Another drawback is the requirement that the shared content can be accessed only by a limited number of compatible applications, making impossible their access to others applications and system. In this work we present a new approach for peer-to-peer data indexing, focused on organization and retrieval of metadata which describes the shared content. This approach results in a common and interoperable infrastructure, which provides a transparent access to data shared on multiple data sharing networks via a simple API. The proposed approach is evaluated using a case study, implemented as a cross-platform extension to Mozilla Firefox browser, and demonstrates the advantages of such interoperability over conventional distributed data access strategies. © 2009 IEEE.
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This article analyses the share of total income represented by employment earnings in the countries of Latin America over the last two decades. It first considers the wage share of gross domestic product (gdp) and then adds in the earnings of self-employed workers. The findings indicate that both total wages and total earnings declined as a share of gdp in most of the region’s countries over the period, although there were some exceptions. The reduction in earnings inequality seen over the past decade was not usually accompanied by an increase in the gdp share of earnings. This means that the improvement in personal income distribution was not matched by an improvement in functional distribution.
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Objectives: Limbal stem cells (LSC) are self-renewing, highly proliferative cells in vitro, which express a set of specific markers and in vivo have the capacity to reconstruct the entire corneal epithelium in cases of ocular surface injury. Currently, LSC transplantation is a commonly used procedure in patients with either uni- or bilateral total limbal stem cells deficiency (TLSCD). Although LSC transplantation holds great promise for patients, several problems need to be overcome. In order to find an alternative source of cells that can partially substitute LSC in cornea epithelium reconstruction, we aimed at investigating whether human immature dental pulp stem cells (hIDPSC) would present similar key characteristics as LSC and whether they could be used for corneal surface reconstruction in a rabbit TLSCD model. Materials: We used hIDPSC, which co-express mesenchymal and embryonic stem cell markers and present the capacity to differentiate into derivative cells of the three germinal layers. TLSCD was induced by chemical burn in one eye of rabbits. After 30 days, the opaque tissue formed was removed by superficial keratectomy. Experimental group received undifferentiated hIDPSC, while control group only received amniotic membrane (AM). Both groups were sacrificed after 3 months. Results and conclusions: We have demonstrated, using immunohistochemistry and reverse transcription-polymerase chain reaction, that hIDPSCs express markers in common with LSC, such as ABCG2, integrin beta 1, vimentin, p63, connexin 43 and cytokeratins 3/12. They were also capable of reconstructing the eye surface after induction of unilateral TLSCD in rabbits, as shown by morphological and immunohistochemical analysis using human-specific antibodies against limbal and corneal epithelium. Our data suggest that hIDPSCs share similar characteristics with LSC and might be used as a potential alternative source of cells for corneal reconstruction.
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Spatial data warehouses (SDWs) allow for spatial analysis together with analytical multidimensional queries over huge volumes of data. The challenge is to retrieve data related to ad hoc spatial query windows according to spatial predicates, avoiding the high cost of joining large tables. Therefore, mechanisms to provide efficient query processing over SDWs are essential. In this paper, we propose two efficient indices for SDW: the SB-index and the HSB-index. The proposed indices share the following characteristics. They enable multidimensional queries with spatial predicate for SDW and also support predefined spatial hierarchies. Furthermore, they compute the spatial predicate and transform it into a conventional one, which can be evaluated together with other conventional predicates by accessing a star-join Bitmap index. While the SB-index has a sequential data structure, the HSB-index uses a hierarchical data structure to enable spatial objects clustering and a specialized buffer-pool to decrease the number of disk accesses. The advantages of the SB-index and the HSB-index over the DBMS resources for SDW indexing (i.e. star-join computation and materialized views) were investigated through performance tests, which issued roll-up operations extended with containment and intersection range queries. The performance results showed that improvements ranged from 68% up to 99% over both the star-join computation and the materialized view. Furthermore, the proposed indices proved to be very compact, adding only less than 1% to the storage requirements. Therefore, both the SB-index and the HSB-index are excellent choices for SDW indexing. Choosing between the SB-index and the HSB-index mainly depends on the query selectivity of spatial predicates. While low query selectivity benefits the HSB-index, the SB-index provides better performance for higher query selectivity.
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In the era of the Internet of Everything, a user with a handheld or wearable device equipped with sensing capability has become a producer as well as a consumer of information and services. The more powerful these devices get, the more likely it is that they will generate and share content locally, leading to the presence of distributed information sources and the diminishing role of centralized servers. As of current practice, we rely on infrastructure acting as an intermediary, providing access to the data. However, infrastructure-based connectivity might not always be available or the best alternative. Moreover, it is often the case where the data and the processes acting upon them are of local scopus. Answers to a query about a nearby object, an information source, a process, an experience, an ability, etc. could be answered locally without reliance on infrastructure-based platforms. The data might have temporal validity limited to or bounded to a geographical area and/or the social context where the user is immersed in. In this envisioned scenario users could interact locally without the need for a central authority, hence, the claim of an infrastructure-less, provider-less platform. The data is owned by the users and consulted locally as opposed to the current approach of making them available globally and stay on forever. From a technical viewpoint, this network resembles a Delay/Disruption Tolerant Network where consumers and producers might be spatially and temporally decoupled exchanging information with each other in an adhoc fashion. To this end, we propose some novel data gathering and dissemination strategies for use in urban-wide environments which do not rely on strict infrastructure mediation. While preserving the general aspects of our study and without loss of generality, we focus our attention toward practical applicative scenarios which help us capture the characteristics of opportunistic communication networks.
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The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for modeling these data the Negative Binomial distribution is considered the most adequate one especially because it allows for "over dispersion". However, the estimation of the dispersion parameter is a very delicate issue because few information are usually available for estimating it. Many strategies have been proposed, but they often result in procedures based on plug-in estimates, and in this thesis we show that this discrepancy between the estimation and the testing framework can lead to uncontrolled first-type errors. We propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Afterwards, three consistent statistical tests are developed for differential expression analysis. We show that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it is the best one in reaching the nominal value for the first-type error, while keeping elevate power. The method is finally illustrated on prostate cancer RNA-seq data.
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The stashR package (a Set of Tools for Administering SHared Repositories) for R implements a simple key-value style database where character string keys are associated with data values. The key-value databases can be either stored locally on the user's computer or accessed remotely via the Internet. Methods specific to the stashR package allow users to share data repositories or access previously created remote data repositories. In particular, methods are available for the S4 classes localDB and remoteDB to insert, retrieve, or delete data from the database as well as to synchronize local copies of the data to the remote version of the database. Users efficiently access information from a remote database by retrieving only the data files indexed by user-specified keys and caching this data in a local copy of the remote database. The local and remote counterparts of the stashR package offer the potential to enhance reproducible research by allowing users of Sweave to cache their R computations for a research paper in a localDB database. This database can then be stored on the Internet as a remoteDB database. When readers of the research paper wish to reproduce the computations involved in creating a specific figure or calculating a specific numeric value, they can access the remoteDB database and obtain the R objects involved in the computation.
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Angiopoietin-1 (Ang-1) and angiopoietin-2 (Ang-2) have been identified as ligands with different effector functions of the vascular assembly and maturation-mediating receptor tyrosine kinase Tie-2. To understand the molecular interactions of the angiopoietins with their receptor, we have studied the binding of Ang-1 and Ang-2 to the Tie-2 receptor. Enzyme-linked immunosorbent assay-based competition assays and co-immunoprecipitation experiments analyzing the binding of Ang-1 and Ang-2 to truncation mutants of the extracellular domain of Tie-2 showed that the first Ig-like loop of Tie-2 in combination with the epidermal growth factor (EGF)-like repeats (amino acids 1-360) is required for angiopoietin binding. The first Ig-like domain or the EGF-like repeats alone are not capable of binding Ang-1 and Ang-2. Concomitantly, we made the surprising finding that Tie-2 exon-2 knockout mice do express a mutated Tie-2 protein that lacks 104 amino acids of the first Ig-like domain. This mutant Tie-2 receptor is functionally inactive as shown by the lack of ligand binding and receptor phosphorylation. Collectively, the data show that the first 104 amino acids of the Tie-2 receptor are essential but not sufficient for angiopoietin binding. Conversely, the first 360 amino acids (Ig-like domain plus EGF-like repeats) of the Tie-2 receptor are necessary and sufficient to bind both Ang-1 and Ang-2, which suggests that differential receptor binding is not likely to be responsible for the different functions of Ang-1 and Ang-2.
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PURPOSE OF REVIEW: Intensive care medicine consumes a high share of healthcare costs, and there is growing pressure to use the scarce resources efficiently. Accordingly, organizational issues and quality management have become an important focus of interest in recent years. Here, we will review current concepts of how outcome data can be used to identify areas requiring action. RECENT FINDINGS: Using recently established models of outcome assessment, wide variability between individual ICUs is found, both with respect to outcome and resource use. Such variability implies that there are large differences in patient care processes not only within the ICU but also in pre-ICU and post-ICU care. Indeed, measures to improve the patient process in the ICU (including care of the critically ill, patient safety, and management of the ICU) have been presented in a number of recently published papers. SUMMARY: Outcome assessment models provide an important framework for benchmarking. They may help the individual ICU to spot appropriate fields of action, plan and initiate quality improvement projects, and monitor the consequences of such activity.
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BACKGROUND: In clinical practice a diagnosis is based on a combination of clinical history, physical examination and additional diagnostic tests. At present, studies on diagnostic research often report the accuracy of tests without taking into account the information already known from history and examination. Due to this lack of information, together with variations in design and quality of studies, conventional meta-analyses based on these studies will not show the accuracy of the tests in real practice. By using individual patient data (IPD) to perform meta-analyses, the accuracy of tests can be assessed in relation to other patient characteristics and allows the development or evaluation of diagnostic algorithms for individual patients. In this study we will examine these potential benefits in four clinical diagnostic problems in the field of gynaecology, obstetrics and reproductive medicine. METHODS/DESIGN: Based on earlier systematic reviews for each of the four clinical problems, studies are considered for inclusion. The first authors of the included studies will be invited to participate and share their original data. After assessment of validity and completeness the acquired datasets are merged. Based on these data, a series of analyses will be performed, including a systematic comparison of the results of the IPD meta-analysis with those of a conventional meta-analysis, development of multivariable models for clinical history alone and for the combination of history, physical examination and relevant diagnostic tests and development of clinical prediction rules for the individual patients. These will be made accessible for clinicians. DISCUSSION: The use of IPD meta-analysis will allow evaluating accuracy of diagnostic tests in relation to other relevant information. Ultimately, this could increase the efficiency of the diagnostic work-up, e.g. by reducing the need for invasive tests and/or improving the accuracy of the diagnostic workup. This study will assess whether these benefits of IPD meta-analysis over conventional meta-analysis can be exploited and will provide a framework for future IPD meta-analyses in diagnostic and prognostic research.
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A combinatorial protocol (CP) is introduced here to interface it with the multiple linear regression (MLR) for variable selection. The efficiency of CP-MLR is primarily based on the restriction of entry of correlated variables to the model development stage. It has been used for the analysis of Selwood et al data set [16], and the obtained models are compared with those reported from GFA [8] and MUSEUM [9] approaches. For this data set CP-MLR could identify three highly independent models (27, 28 and 31) with Q2 value in the range of 0.632-0.518. Also, these models are divergent and unique. Even though, the present study does not share any models with GFA [8], and MUSEUM [9] results, there are several descriptors common to all these studies, including the present one. Also a simulation is carried out on the same data set to explain the model formation in CP-MLR. The results demonstrate that the proposed method should be able to offer solutions to data sets with 50 to 60 descriptors in reasonable time frame. By carefully selecting the inter-parameter correlation cutoff values in CP-MLR one can identify divergent models and handle data sets larger than the present one without involving excessive computer time.
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Earth observations (EO) represent a growing and valuable resource for many scientific, research and practical applications carried out by users around the world. Access to EO data for some applications or activities, like climate change research or emergency response activities, becomes indispensable for their success. However, often EO data or products made of them are (or are claimed to be) subject to intellectual property law protection and are licensed under specific conditions regarding access and use. Restrictive conditions on data use can be prohibitive for further work with the data. Global Earth Observation System of Systems (GEOSS) is an initiative led by the Group on Earth Observations (GEO) with the aim to provide coordinated, comprehensive, and sustained EO and information for making informed decisions in various areas beneficial to societies, their functioning and development. It seeks to share data with users world-wide with the fewest possible restrictions on their use by implementing GEOSS Data Sharing Principles adopted by GEO. The Principles proclaim full and open exchange of data shared within GEOSS, while recognising relevant international instruments and national policies and legislation through which restrictions on the use of data may be imposed.The paper focuses on the issue of the legal interoperability of data that are shared with varying restrictions on use with the aim to explore the options of making data interoperable. The main question it addresses is whether the public domain or its equivalents represent the best mechanism to ensure legal interoperability of data. To this end, the paper analyses legal protection regimes and their norms applicable to EO data. Based on the findings, it highlights the existing public law statutory, regulatory, and policy approaches, as well as private law instruments, such as waivers, licenses and contracts, that may be used to place the datasets in the public domain, or otherwise make them publicly available for use and re-use without restrictions. It uses GEOSS and the particular characteristics of it as a system to identify the ways to reconcile the vast possibilities it provides through sharing of data from various sources and jurisdictions on the one hand, and the restrictions on the use of the shared resources on the other. On a more general level the paper seeks to draw attention to the obstacles and potential regulatory solutions for sharing factual or research data for the purposes that go beyond research and education.