Miracle-dz/UniFAR-FTUs huggingface dataset:
A qualitative study on barriers and facilitators of quality improvement engagement by frontline nurses and leaders

Aim: This study aimed to understand the facilitators and barriers of quality improvement (QI) from the perspective of nurses and leaders at the frontline. Background: Nurse engagement in QI has been associated with quality care and improved patient outcomes, yet nurse reported participation is low. Methods: A descriptive qualitative design and purposive sampling was used to examine barriers and facilitators of nurse engagement. Results: Facilitators (1) A leader ’ s influence on a QI culture. Subthemes: creating buy-in, support of a just culture and working in partnership with nurses. Barriers (1) Barriers in organizational culture for nurses to lead QI. Subthemes: organizational hierarchy, absence of a just culture, nurses ’ role not valued, lack of accountability for QI in nursing role and resistance to change. (2) Barriers in organisational structure for nurses to lead QI. Subthemes: manager disengagement, time pressures, lack of access to timely data, lack of QI knowledge, siloed departments and lack of QI experts. Conclusion: Barriers to QI engagement prevent nurses from fully engaging in QI. Creating a just culture and building the infrastructure to support nurse engagement is critical for success. Implications for Nursing Management: Specific facilitators and barriers were identified that nurse leaders can assess in their practice setting and use relevant strategies to support engagement in QI.
Transport in heterogeneous porous formations: Spatial moments, ergodicity, and effective dispersion

Transport of inert solutes in natural porous formations is dominated by convection and by the large-scale heterogeneity of permeability. A solute body inserted in the formation spreads because of the variation of velocity among and along the stream tubes which cross the plume. With neglect of the slow effect of pore-scale dispersion the solute particles preserve their initial concentration, but the body as a whole spreads in an irregular manner (Figures 1, 2, and ). The transport theory, based on representation of permeability and velocity as random space functions, can predict the expected value and variance of concentration, but under the above conditions, the coefficient of variation may be large. In contrast, the spatial moments of the solute body are less susceptible to uncertainty, depending on the transverse dimensions of the plume and on the travel time. The first and second spatial moments are regarded as random functions of time, and their expected value and variance are derived in terms of the velocity field. The moments are assumed to satisfy the ergodic hypothesis if their coefficients of variation are negligible. The conditions which ensure the fulfillment of this requirement are examined. The “effective dispersion coefficients” are defined with the aid of the spatial moments and are shown to depend generally on the initial size of the solute body and on travel time. The results are illustrated by an analytical solution of transport in a stratified formation with the average velocity parallel to the bedding.
Linking parameters across scales: Subgrid parameterizations and scale dependent hydrological models.

It is argued that the aggregation approach towards macroscale hydrological modelling, in which it is assumed that a model applicable at small scales can be applied at larger scales using effective parameter values, is an inadequate approach to the scale problem. It is also unlikely that any general scaling theory can be developed due to the dependence of hydrological systems on historical and geological perturbations. Thus a disaggregation approach to developing scale-dependent models is advocated in which a representation of the distribution of hydrological responses is used to reflect hydrological heterogeneity. An appropriate form of distribution may vary with both scale and environment. Such an approach is dependent on the data available to define and calibrate the chosen subgrid parameterization. A parameterization based on a minimum patch representation is suggested and the problems of identification at the larger scale discussed.
Water Use Relationships and Projection Corresponding with Regional Growth, Seattle Region

: The paper outlines both the methods used and the results obtained in a study of the demand for municipal and industrial water for the Seattle region. The study was made as part of a regional water management study program, one objective of which is to “… identify, quantify, and set priorities for all current and future water uses …”. A basic concept in the study of municipal and industrial water use is that the demand for water is derived from the demand for output and the direct services that water provides. Principal characteristics of the study are: (1) Water use is studied by type - residential, commercial, industrial and public -with identification of factors affecting each; (2) Water demands are studied by season as well as on an annual basis; (3) Projections of future water use are tied directly to projections of economic change in the service area; and (4) The effects of alternative policies on water use are estimated. Water use levels are projected under alternative regional growth assumptions provided by the Puget Sound Governmental Conference, a regional planning agency. Thus, the water use planning is consistent with other regional planning programs in this respect. The results can be varied according to changes in specific factors affecting water use. The factors considered in the present study include: single-family residential lot size, distribution of population between single- and multi-family units, per capita water use by multi-family unit residents, and industrial and commercial water use per employee. An income elasticity of demand was estimated for single-family residential water use.
Network Security , Administration and Management : Advancing Technology and Practice

In this chapter, we deal with the issue of security regarding components that are responsible for provisioning multi-domain network services, either automatically or through some form of administrator interaction. It is evident that a malicious compromise of such a component would have far-reaching implications for the stability of the network. Furthermore, trust between cooperating domains is a delicate issue, and each partner in the multi-domain federation has to have some guarantees that peers in the service are not going to be security compromised. We enumerate some of the related dangers and propose ways to limit the attack surface, reduce the intrusion possibilities, and guarantee the quick resolution of any successful violations. The issue of security is studied in two main parts: Inter-domain security, for the communication between domains and the successful negotiation of resource reservations, and intra-domain security, for the internal communications within a domain for the initiation of a resource reservation and its actual realization in the network devices. Resource reservation is studied both on the level of IP services based on Differentiated Services architectures, and on the level of dynamic circuit reservation based on Layer 2 technologies. The chapter is completed with a case study on the authentication and authorization framework designed in the context of a Pan-European network resource reservation service, in the Geant academic and research network. DOI: 10.4018/978-1-60960-777-7.ch003
Currently active regions of decelerating-accelerating seismic strain in central Asia

[1] Accelerating preshock seismic strain in a broad (critical) region and decelerating preshock seismic strain in a narrower (seismogenic) region constitute a model for intermediate-term prediction of strong main shocks. An effort is made in the present work for a forward test of the Decelerating-Accelerating Seismic Strain (D-AS) model by identifying such patterns and estimating the corresponding, probably ensuing, strong main shocks (M ≥ 7.0) in central Asia (20°N–45°N, 42°E–105°E). Five such patterns have been identified, and the origin time, magnitude, and epicentral geographic coordinates of each of the corresponding main shocks have been estimated (predicted). Model uncertainties of the estimated time, magnitude, and space parameters of these probably ensuing main shocks, as well as appropriate statistical tests against a standard Gutenberg-Richter seismicity distribution, are also presented to allow a future objective evaluation of the model's efficiency for intermediate-term earthquake prediction.
clues: An R Package for Nonparametric Clustering Based on Local Shrinking

Determining the optimal number of clusters appears to be a persistent and controversial issue in cluster analysis. Most existing R packages targeting clustering require the user to specify the number of clusters in advance. However, if this subjectively chosen number is far from optimal, clustering may produce seriously misleading results. In order to address this vexing problem, we develop the R package clues to automate and evaluate the selection of an optimal number of clusters, which is widely applicable in the field of clustering analysis. Package clues uses two main procedures, shrinking and partitioning, to estimate an optimal number of clusters by maximizing an index function, either the CH index or the Silhouette index, rather than relying on guessing a pre-specified number. Five agreement indices (Rand index, Hubert and Arabie's adjusted Rand index, Morey and Agresti's adjusted Rand index, Fowlkes and Mallows index and Jaccard index), which measure the degree of agreement between any two partitions, are also provided in clues. In addition to numerical evidence, clues also supplies a deeper insight into the partitioning process with trajectory plots.
Characterization and Understanding of Bare Soil Respiration Spatial Variability at Plot Scale

Soil respiration is known to be highly variable with time. Less is known, however, about the spatial variability of heterotrophic soil respiration at the plot scale. We simultaneously measured soil heterotrophic respiration, soil temperature, and soil water content at 48 locations with a nested sampling design and at 76 locations with a regular grid plus refinement within a 13‐ by 14‐m bare soil plot for 15 measurement dates. Soil respiration was measured with a closed chamber covering a surface area of 0.032 m2 A geostatistical data analyses indicated a mean range of 2.7 m for heterotrophic soil respiration. We detected rather high coefficients of variation of CO2 respiration between 0.13 and 0.80, with an average of 0.33. The number of observations required to estimate average respiration fluxes at a 5% error level ranged between 5 and 123. The analysis of the temporal persistence revealed that a subset of 17 sampling locations is sufficient to estimate average respiration fluxes at a tolerable root mean square error of 0.15 g C m−2 d−1 Statistical analysis revealed that the spatiotemporal variability of heterotrophic soil respiration could be explained by the state variables soil temperature and water content. The spatial variability of respiration was mainly driven by variability in soil water content; the variability in the soil water content was almost an order of magnitude higher than the variability in soil temperature.
Lateral mixing of the Mediterranean Water in the eastern North Atlantic

Analysis of the salinity distribution along three quasi-meridional hydrographic sections in the eastern North Atlantic shows that different mesoscale processes act to mix the Mediterranean Water with the adjacent water masses. In the region of transition with the Antarctic Intermediate Water in the south, the salt transport by the meddies seems to account for most of the observed lateral diffusive exchanges at the large scale. In the north these exchanges are contributed to by parcels of both Mediterranean Water and Subarctic Intermediate Water travelling on average in opposite directions. Also in the north but at a deeper level, transition with the Labrador Sea Water is characterized by a pronounced thermohaline front. Coherent mesoscale structures carrying deep Mediterranean Water escape northward from that front. A simplified unidirectional mixing model is used diagnostically to relate the basic parameters associated with the mesoscale structures to those characterizing lateral mixing at the large scale.
Lidar measurements of African dust outbreaks

We report in this paper lidar measurements of two events of transport of dust from the Sahara region to the Mediterranean Sea, observed in Lecce, Italy (40°20'N,18°06'E). The observations have been made in the framework of the EARLINET project, in which aerosol measurements are performed in all Europe by 21 stations on a coordinate basis. Lidar measurements are compared with informations available from other sources. General results for the lidar ratio are also presented.
A Data Scientific Approach Towards Predictive Maintenance Application in Manufacturing Industry

Most industries have recently started to harness the power of data to assess their performance and improve their production systems for future competitiveness and sustainability. Therefore, utilization of data for obtaining insights through data-driven approaches is invading every domain of industrial applications. Predictive maintenance (PdM) is one of the highest impacted industrial use cases in data-driven applications due to its ability to predict machine failures by implementing machine learning algorithms. This study aims to propose a systematic data scientiﬁc approach to provide valuable insights by analysing industrial alarm and event log data, which might further be used for investigation in root cause understanding and planning of necessary maintenance activities. To do that, a Cross-Industry Standard Process for Data Mining (CRISP-DM) is followed as a reference model in this study. The results are presented by ﬁrst understanding the relationship between alarms and product types being processed in the selected machines by us-ing exploratory data analysis (EDA). Along with this, the behavior of problematic alarms is identiﬁed. Afterward, a predictive analysis formulated as a multi-class classiﬁcation problem is performed using various Machine Learning (ML) models to predict the category of alarm and generate rules to be used for further investigation in maintenance planning. The performance of the developed models is evaluated based on the different metrics and the decision tree model is selected with the higher accuracy score among them. As a theoretical contribution, this study presents an implementation of predictive modeling in a structured way, which uses a systematic data scientiﬁc approach based on industrial alarm and event log data. On the other hand, as a practical contribution, this study provides a set of decision rules that can act as decision support for further exploration of possible in-depth root causes through the other contextual data, and hence it gives an initial foundation towards PdM application in the case company.
Stabilization of the general two-trailer system

Existing methods for nonholonomic feedback stabilization can only be applied to exactly nilpotentizable or flat systems. In this paper, a car towing two off-hooked trailers is considered as a canonical example of robot that does not fall into the above class. We show that exponential convergence to arbitrary configurations can be obtained by means of an iterative steering technique based on a nonhomogeneous nilpotent approximation of the system. Simulation results illustrate the performance of the method.
The invertebrate faunas of tropical American caves, Part 6: Jumandi Cave, Ecuador

Little is known of the cave faunas of Ecuador. In fact, early cave reconaissance expeditions to Ecuador had difficulty in locating any caves (Gurnee, 1967). However, even though much of the country is covered by Pleistocene volcanic rocks, a surprising troglobitic fauna has been found in lava tube caves in the Ecuadorian Galapagos Islands (Leleup, 1968, 1970). On the east facing slopes of the Andes mountain range lie various outcropings of Cretaceous limestones. In one, in the. Amazonian headwaters of the Rio Pastaza (Province of Morona Santiago), lies the Cuevas de los Tayos (cave of the guacharo, or oilbird, Steatornis caripensis Humboldt). These remote and difficult to reach caves were the focus of an expedition in 1976 of a combined team of Ecuadorian and British scientists, supported by the Ecuadorian and British Armies. British cave biologists on the team were Drs. W.P. Ashmole and J.T. Jefferson. It is hoped that they will soon prepare a report on their cave faunal findings .
Three-dimensional structure of thermohaline circulation steered by bottom topography

An investigation based on the expansion in terms of diffusive vertical modes is made on the effect of an isolated seamount on the three-dimensional structure of thermohaline circulation driven by an inflow of deep water. While the circulation has a relatively simple structure dominated by the first baroclinic mode in a flat ocean, it becomes rather complicated in an ocean with a seamount. Nevertheless its three-dimensional structure is reconstructed and understood well by analyzing the dynamics of the vertical modes. It is shown that the vertical modes respond to the topography-induced stretching in a similar way irrespective of the mode number. When synthesized in the deep layer, therefore, the vertical modes interfere constructively to yield the same pattern of circulation as a single vertical mode or the diffusive reduced-gravity model. It is thus confirmed that the abyssal circulation certainly has the features predicted by the diffusive reduced-gravity model such as cyclonic circulation over the mountain or downwelling in the geostrophic island, in which geostrophic contours close on themselves. Close to the surface, however, different modes of different vertical structures interfere destructively so that the horizontal distribution of topography-induced circulation in the deep layer decays, upward shifting its center westward.
Cloud cover analysis with METEOSAT‐5 during INDOEX

During the Indian Ocean Experiment (INDOEX), METEOSAT-5 positioned at 63°E provided observation of the visible and infrared radiance field over the Indian Ocean. A cloud classification process using the dynamic cluster method is applied to these data. For the 3 months of the experiment (January–March 1999), daily maps of the cloud cover type are built for 0730 and 0900 UTC. The occurrence frequency of clear sky, low- and high-level cloud cover is examined. These frequencies are compared to the International Satellite Cloud Climatology Program (ISCCP) D1 data set for the period 1984 to 1994. The Indian Ocean region can be classified in three zones. In the north subtropics, clear sky and small cumulus occur at least 90% of the time. Near the coast of India, clear sky is as frequent as 80 to 100%. The Intertropical Convergence Zone, characterized by the occurrence frequency of high-level clouds greater than 30%, spreads from Indonesia to North Madagascar. Near Indonesia, high-level cloud cover occurs more than 55% of the time. In the south subtropics, low cloud cover is the most frequent. In the eastern part the occurrence frequency reaches 80%. This percentage decreases along the western side of the ocean where low clouds break up. Between the African coast and Madagascar, high-level clouds are frequent. The mean spatial features found are in agreement with the ISCCP climatology, except for the eastern part of the south subtropics. A regional comparison shows the difficulty of making the analysis of interannual variations of cloud cover obtained from various cloud cover retrievals applied to different satellite data sets. This difficulty arises from the nonneglectable percentage of satellite pixels which can contain some very small low clouds.
A Bayesian Approach to parameter estimation and pooling in nonlinear flood event models

A Bayesian procedure is presented for parameter estimation in nonlinear flood event models. We derive a pooling diagnostic using Bayes factors to identify when it is reasonable to pool model parameters across storm events. A case study involving a quasi‐distributed, nonlinear flood event model and five watersheds in the southwest of Western Australia is presented to illustrate the capabilities and utility of the procedure. The results indicate that Markov chain Monte Carlo methods based on the Metropolis‐Hastings algorithm are useful tools for parameter estimation. We find that pooling is not justified for the model and data at hand. This suggests that current practices in nonlinear flood event modeling may be in need of urgent review.
Relating convective and stratiform rain to latent heating.

Abstract The relationship among surface rainfall, its intensity, and its associated stratiform amount is established by examining observed precipitation data from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). The results show that for moderate–high stratiform fractions, rain probabilities are strongly skewed toward light rain intensities. For convective-type rain, the peak probability of occurrence shifts to higher intensities but is still significantly skewed toward weaker rain rates. The main differences between the distributions for oceanic and continental rain are for heavily convective rain. The peak occurrence, as well as the tail of the distribution containing the extreme events, is shifted to higher intensities for continental rain. For rainy areas sampled at 0.5° horizontal resolution, the occurrence of conditional rain rates over 100 mm day−1 is significantly higher over land. Distributions of rain intensity versus stratiform fraction for simulated precipitation data o.