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Background Quality improvement in Healthcare is the new fashion actually. Rich countries and developing countries alike are trying to implement quality improvement initiatives to improve their performance and the quality of care. There is evidence in the scientific literature that the existence of a “champion” can play an important role in the successful implementation of quality improvement strategies. Most of the time, people get stuck at the implementation level: they know what to do but they fail to execute it in the organizational setting. That’s where a champion can be useful to facilitate the success of the change. There is a paucity of research on the link between the champion and the implementation of quality improvement programs. The aim of the study was to investigate the perceptions of stakeholders about the characteristics and qualities of the champion that could facilitate the successful implementation of quality improvement programs in health care settings in Haiti. Data collection We used a semi-structured interview guide and a small group discussion guide. Most of the interviews were face to face and were conducted between April and September 2019. Respondents were interviewed about their experience with a champion, their ideas on the qualities and characteristics of successful champions, and what obstacles can prevent them from succeeding in their efforts to facilitate positive change. Most interviews were conducted in Haitian Creole or French by trained qualitative researchers. One interview was conducted in English. Most of the material was audio-recorded and transcribed for analysis, except for one semi-structured interview and the small group discussions, as some participants were not comfortable with the recording. Data analysis We applied a grounded theory approach with Atlas-ti software for the data analysis and interpretation. We predefined two codes that capture the facilitators and the obstacles linked to the champions’ success. All 21 transcripts were revised and compared using the constant comparison method. Then, we considered the themes that emerged from the data (taking into account each category) according to the core meaning of participants. The themes were reviewed several times to make sure they are accurate and grounded in the data. Those data could help you to get a better understanding of the quality and the characteristics of the champions that play a critical role in the implementation of quality improvement programs. The data are transcripts of interviews with stakeholders in the health facilities. In the articles, we extract some quotes from the data in order to illustrate some findings. But the raw data provide more information about the topics of champions and quality improvement.
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In computer security, network botnets still represent a major cyber threat. Concealing techniques such as the dynamic addressing and the Domain Name Generation Algorithms (DGAs) require an improved and more effective detection process. To this extent, this data descriptor presents a collection of over 30 million manually-labelled algorithmically generated domain names decorated with a feature set ready-to-use for Machine Learning analysis. This proposed data set enables researchers to move forward the data collection, organization and pre-processing phases, eventually enabling them to focus on the analysis and the production of Machine-Learning powered solutions for network intrusion detection. To be as exhaustive as possible, 50 among the most important malware variants have been selected. Each family is available both as list of domains and as collection of features. To be more precise, the former is generated by executing the malware DGAs in a controlled environment with fixed parameters, while the latter is generated by extracting a combination of statistical and Natural Language Processing (NLP) metrics.
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In this research we aimed to investigate the correlation between the prolactin hormone level and damage to hippocampus tissue in experimental epilepsy model. In literature some authors found out that prolactin hormone level increase in epileptic seizures and can be protective in terms of hippocampal damage. 24 wistaria-hannover rat were used for experimental epilepsy model induced with pilocarpine. Prolactin hormone levels were decreased with bromocriptine. We found out that prolactin hormone increased after seizure and it was statistically significant. It was seen that, hemorrhages occurred in surface of the brains in lower prolactin level group, but we couldn't found a statistically significant histologic data for more hippocampal damage. This research can give more reliable and significant results when re-planned with larger sample groups.
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The data of 2012 Economic and Social Survey Project in Ethnic Minority Areas of Western China with the macroeconomic data such as the minimum wage.
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Original western blot images for the following publication:
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Data obtained for tungsten sample using MGIXD method (Cu Kalfa radiation, 4 different incident angles)) and ED diffraction with synchrotron radiation. In the used MMXD method [28], the residual stress analysis is based on the ED synchrotron X-ray diffraction measurement performed for multiple hkl reflections. To do this, data were collected for one constant 2θ angle with the white synchrotron beam. Next, data were grouped for strictly chosen penetration depths in order to perform the residual stress analysis layer by layer in the sample and to get much deeper profile than in the case of the MGIXD method. 1. The complementary MGIXD and MMXD methods reveal a significant residual stress gradient present in the subsurface volume of a polished tungsten sample. The compressive stress of about -1000 MPa was determined very close to the polished surface (MGIXD method). Going deeper in the subsurface volume the residual stresses gradually decrease down to zero value at the depth of about 10 μm (MMXD method). 2. The value of lattice parameter remains constant (in the margin of 0.001Å) up to 9-10 μm of the depth, regardless the method used to determine it. 3. The results obtained using classical MGIXD for sample surface are continued by the MMXD results. High energy synchrotron radiation allowed measurements for significantly larger subsurface depths in comparison with a classical laboratory X-rays. 4. The MMXD with synchrotron radiation allowed to determine depth-dependent stress profile with spatial resolution of 1 µm, which is much better than in the case of standard ED measurements. 5. Almost isotropic elastic properties of tungsten crystallites simplifies analysis of the residual stress state.
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Estimation data from a targeted nationally representative sample eliciting consumer willingness to pay for sustainability attributes in beer. Different eco-labels are used to depict different aspects of sustainability including: water use, energy use, and landfill diversion. The survey was constructed in Qualtrics and distributed using Kanter. We collect information on demographic characteristics, beer buying/drinking behavior, and sustainability preferences, alongside a choice experiment. We find that consumers are willing to pay a price premium for sustainability attributes in beer (under all model specifications).
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The clinical, radiomics, adn so on.
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This contains the data for ISFET SPICE Macromodel and the CVCC circuit schematic and netlist. It also contains data for various ML techniques and Bayesian inference for temperature and temporal drift compensation.
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This dataset support our methods publication recently accepted in Ecosystems Manuscript highlights • Stable isotope analysis suggests δ13C-CH4 oxidation and fractionation occurs during transport • Substantial fine-scale vertical and radial heterogeneity identified in tree stem CH4 emissions • Novel smartphone 3D photogrammetry can more accurately estimate the tree stem surface area compared to traditional methods • Fine-scale sampling method shows 86-89% of methane flux emanates from the lower 30cm of wetland forest tree stems   Manuscript Abstract: Tree stem methane emissions are gaining increasing attention as an overlooked atmospheric source pathway. Existing methods for measuring tree stem greenhouse gas fluxes and isotopes may provide robust integrated emission estimates, but due to their coarse resolution, the capacity to derive insights into fine-scale dynamics of tree stem emissions are limited. We demonstrate and field-test an alternative method that is Small, Nimble, In situ and allows for Fine-scale Flux (‘SNIFF’) measurements, on complex and contrasting stem surfaces. It is light weight and therefore suitable to remote field locations enabling real time data observations allowing for field-based data driven sampling regimes. This method facilitated novel results capturing fine-scale vertical and radial methane flux measurements (5cm increments) and revealed: (1) 86-89% of methane emissions emanated from the lower 30cm of sampled wetland tree species; (2) uncovered clear vertical and horizontal trends in δ13C-CH4 possibly due to fractionation associated with oxidation and mass-dependant fractionation during diffusive transport; and (3) demonstrated how substantial radial heterogeneity can occur. We also compared a variety of upscaling approaches to estimate methane flux per tree when using this method, including novel smartphone 3D photogrammetry, that resulted in a substantially higher stem surface area estimation (>16 to 36%) than traditional empirical methods. Utilising small chambers with high radial and vertical resolution capabilities may therefore facilitate future assessments into the drivers, pathways, oxidation sinks and magnitude of various tree stem greenhouse gas emissions, and compliment previous broad-scale sampling techniques.
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