Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of the reach, effectiveness, adoption, implementation, and maintenance (RE-AIM) framework to guide iterative adaptations: Applications, lessons learned, and future directions

Introduction Implementation science frameworks have been used widely for planning and evaluation, but seldom to guide adaptations during program implementation. There is great potential for these frameworks to be used to inform conceptual and data-driven decisions about adaptations. Methods We summarize recent applications using Iterative RE-AIM to capture and guide adaptations. Iterative RE-AIM can be repeated at multiple time points customized to each project and involves the following activities: identification of key implementation partners; rating importance of and progress on each RE-AIM dimension (reach, effectiveness, adoption, implementation, and maintenance); use of summary data on ratings to identify one or two RE-AIM dimensions for adaptations and implementation strategies; and evaluation of progress and impact of adaptations. We summarize recent and ongoing Iterative RE-AIM applications across multiple care coordination and pain management projects within the Veterans Health Administration, a hypertension control trial in Guatemala, a hospital-based lung ultrasound implementation pilot, and a colorectal cancer screening program in underserved communities. Results Iterative RE-AIM appears feasible, helpful, and broadly applicable across diverse health care issues, interventions, contexts, and populations. In general, the RE-AIM dimension showing the largest gap between importance and progress has been Reach. The dimensions most frequently selected for improvement have been Reach and Implementation. We discuss commonalities, differences and lessons learned across these various applications of Iterative RE-AIM. Challenges include having objective real time data on which to make decisions, having key implementation staff available for all assessments, and rapidly scoring and providing actionable feedback. We discuss print and online resources and materials to support Iterative RE-AIM. Conclusions The use of Iterative RE-AIM to guide and support understanding of adaptations has proven feasible across diverse projects and in multiple case studies, but there are still questions about its strengths, limitations, essential components, efficiency, comparative effectiveness, and delivery details. Future directions include investigating the optimal frequency and timing for iterative applications; adding contextual assessments; developing more continuous and rapid data on which to make adaptation decisions; identifying opportunities to enhance health equity; and determining the level of facilitation that is most cost-effective.
Mergers and acquisitions in Latin America: a literature review

The present study aims to understand the particular characteristics of mergers and acquisitions processes in Latin America. The methodology use is that of literature review. Different categories of analysis were built on the review of academic journals in highimpact databases. It was found that there are some similarities and differences with respect to the experiences of industrialized economies.
Strategic antecedents and organisational consequences of IMC in different economy types

ABSTRACT Successful companies develop competitive advantages over their rivals. Drawing on the dynamic capabilities theory, Integrated Marketing Communications (IMC) can be considered as a source of competitive advantage. Enhanced by the effects of the appropriate strategic orientation, IMC may positively influence customer, market and financial performance. However, these proposals need further empirical analysis. Based on data from surveyed businesses in both developed and emerging economies (Spain and Belarus, respectively), the study uses structural equation modelling (SEM) to analyse the relationships in the theoretical model. The results suggest that while market orientation has a direct relationship with IMC in both countries, the relationship between technology orientation and IMC can only be found in a developed economy. In addition, the potential of IMC for business advantage sustainability is verified; in a developed economy, however, the verification was for customer and market performance, but not for financial performance. Conversely, in an emerging economy only customer performance could be verified, despite IMC having an indirect relationship with financial performance in both types of economies. Thus, the economy type moderation effect analysis clearly supports the differences caused by the implementation of IMC in developed and emerging economies.
BioCirrus : uma nova política de armazenamento para a plataforma BioNimbuZ de Nuvem Federada

This research’s goal is to create and implement a better storage policy for a federated cloud platform, BioNimbuZ. It is focused in federated clouds, environments with many distinct cloud providers interconnected, sharing resources in the form of a single computational resource to the client. Since BioNimbuZ is focused in bioinformatics applications, the usual file size on the platform is very large, up to terabytes. This new policy, BioCirrus, uses bandwidth estimates, file compression, latency and uptime to make decisions where to send the file. The objective was to create a faster policy, with better decisions than the previous ones, and the preliminary results suggests this objective was achieved.
Exploring random regular graphs with IONTW

After clicking New you will see a picture of the complete graph K5 in the World window. In this graph each node i has degree ki = 4; it is a 4-regular graph. More generally, for every N the complete graph KN with N nodes is N − 1-regular. Now choose network-type → Empty Graph and click New again. You will see the empty graph K5. Each node in an empty graph has degree 0. Empty graphs are 0-regular. For a third example, choose network-type → Nearest-neighbor 1 num-nodes: 10 d: 2
The use of learning algorithms for real-time immersive data visualization in buildings

Computational Fluid Dynamic (CFD) simulations are used to predict indoor thermal environments and assess their response to specific internal/external conditions. Although computing power has increased exponentially in the past decade, CFD simulations are time consuming and their prediction results cannot be used for real-time immersive visualization in buildings. A method that can bypass the time consuming simulations and generate . acceptable. results will allow such visualization to be constructed. This paper discusses a project that utilizes Artificial Neural Network (ANN) as a learning algorithm to predict post-processed CFD data to ensure rapid data visualization. The technique has been integrated with an immersive Augmented Reality (AR) system to visualize CFD results in buildings. ANN was also evaluated against a linear regression model. Both models were tested and validated with datasets to determine their degree of accuracy. Initial tests, conducted to evaluate the user.s experience of the system, indicated satisfactory results.
Universal Cash Transfers Reduce Childhood Obesity Rates

We evaluate the impact of universal income on childhood obesity. While the goals of implementing universal income are many, its influence on childhood obesity is of particular interest given the growing obesity epidemic and its future threat to global public health. We use evidence from Alaska’s universal income program, the Permanent Fund Dividend (PFD), which has provided annual, unconditional, and universal income to Alaskan residents for over thirty-five years. We use both survey and administrative data to evaluate how the availability of unconditional resources at an early developmental stage, in terms of PFD payments to the child, affects a child’s body mass index (BMI). Using date-of-birth eligibility cut-offs as an identification strategy, we find that an additional one thousand dollars in PFD payments decreases the probability of an Alaskan child being obese by as much as 4.5 percentage points. Back-of-the-envelope calculations for Alaska suggest these reduction may avert 500 cases of obesity and achieve medical cost savings of $2-10 million per year. These findings highlight just one of the potential social benefits of universal income and the potential it has as a tool for addressing the obesity epidemic.
Exploring the latent space between brain and behaviour using eigen-decomposition methods

Machine learning methods have been successfully used to analyse neuroimaging data for a variety of applications, including the classification of subjects with different brain disorders. However, most studies still rely on the labelling of the subjects, constraining the study of several brain diseases within a paradigm of pre-defined clinical labels, which have shown to be unreliable in some cases. The lack of understanding regarding the association between brain and behaviour presents itself as an interesting challenge for more exploratory machine learning approaches, which could potentially help in the study of diseases whose clinical labels have shown limitations. The aim of this project is to explore the possibility of using eigen-decomposition approaches to find multivariate associative effects between brain structure and behaviour in an exploratory way. This thesis addresses a number of issues associated with eigen-decomposition methods, in order to enable their application to investigate brain/behaviour relationships in a reliable way. The first contribution was showing the advantages of an alternative matrix deflation approach to be used with Sparse Partial Least Squares (SPLS). The modified SPLS method was later used to model the associations between clinical/demographic data and brain structure, without relying on a priori assumptions on the sparsity of each data source. A novel multiple hold-out SPLS framework was then proposed, which allowed for the detection of robust multivariate associative effects between brain structure and individual questionnaire items. The linearity assumption of most machine learning methods used in neuroimaging might be a limitation, since these methods will not have enough flexibility to detect non-linear associations. In order to address this issue, a novel Sparse Canonical Correlation Analysis (SCCA) method was proposed, which allows one to use sparsity constraints in one data source (e.g. neuroimaging data), with non-linear transformations of the data in the other source (e.g. clinical data).
An Empirical Analysis of U.S. Foreign Direct Investment and Exports of Processed Food Industries

Haque, Mohua; M.S.; Department of Agribusiness and Applied Economics; College of Agriculture, Food Systems, and Natural Resources; North Dakota State University; November 2006. An Empirical Analysis of U.S. Foreign Direct Investment and Exports of Processed Food Industries. Major Professor: Dr. Won W. Koo. This study examined the determinants of U.S. foreign direct investment (FD! ) and exports of processed food. This study also examined the impact of U.S. FD! on U.S. exports on processed food. FDI and export models used for estimation in this study were based on the cost-minimizing production function. The analysis focused on ten countries for the period of 1989-2004. Four of them were Asian countries: India, Japan, South Korea, and Thailand. Six of them were European countries: Belgium, France, Germany, Italy, Spain, and the United Kingdom. The model was estimated using the two-way error component three-stage least squares (EC3SLS) method. Results from this study show that U.S. FD! and U.S. exports of processed food are complements. Major factors affecting U.S. FD! in the processing industry are GDP, GDP per capita, exchange rate, tariff rate, labor compensation cost, interest rate, and distance. Major factors affecting U.S. exports in the processed food industry are GDP, distance, and GDP from the agri-sector.
Survey of Software Defined Network and Mutable Network

view of the network (which may include statistics and events). An SDN Controller consists of one or more NBI Agents, the SDN Control Logic, and the Control to Data-Plane Interface (CDPI) driver. Definition as a logically centralized entity neither prescribes nor precludes implementation details such as the federation of multiple controllers, the hierarchical connection of controllers, communication interfaces between controllers, nor virtualization or slicing of network resources. • SDN Datapath: The SDN Datapath is a logical network device that exposes visibility and uncontested control over its advertised forwarding and data processing capabilities. The logical representation may encompass all or a subset of the physical substrate resources. An SDN Datapath comprises a CDPI agent and a set of one or more traffic forwarding engines and zero or more traffic processing functions. These engines and functions may include simple forwarding between the datapath's external interfaces or internal traffic processing or termination functions. One or more SDN Datapaths may be contained in a single (physical) network element—an integrated physical combination of communications resources, managed as a unit. An SDN Datapath may also be defined across multiple physical network elements. This logical definition neither prescribes nor precludes implementation details such as the logical to physical mapping, management of shared physical resources, virtualization or slicing of the SDN Datapath, interoperability with non-SDN networking, nor the data processing functionality, which can include OSI layer 4-7 functions. • SDN Control to Data-Plane Interface (CDPI): The SDN CDPI is the interface defined between an SDN Controller and an SDN Datapath, which provides at least (i) programmatic control of all forwarding operations, (ii) capabilities advertisement, (iii) statistics reporting, and (iv) event notification. One value of SDN lies in the expectation that the CDPI is implemented in an open, vendor-neutral and interoperable way. SDN Northbound Interfaces (NBI) SDN NBIs are interfaces between SDN Applications and SDN Controllers and typically provide abstract network views and enable direct expression of network behavior and requirements. This may occur at any level of abstraction (latitude) and across different sets of functionality (longitude). One value of SDN lies in the expectation that these interfaces are implemented in an open, vendor-neutral and interoperable way. 607 Advances in Engineering Research (AER), volume 116
Quantitative analysis on push/stroke operation by a finger to real-world objects

Finger manipulation analysis is an active area of research for developing medical training system and for designing dexterous robotic manipulators. However, capturing tactile information is not easy because sense of touch is perceived by a direct contact between user and objects. This study aims to classify push/stroke operation by a finger to real-world objects as a first attempt to quantitative analysis on natural finger operation to real-world objects. Through the experiments involving ten subjects, we determined feature values based on finger deformation and its 3D positions. Quantitative analysis showed that their linear decision boundaries could classify push/stroke manipulation at high recognition rate.
Competing interactions in colloidal suspensions

The purpose of colloid science is to understand the underlying mechanisms involved in the formation of ordered arrangements of particles, and to observe the self-assembly process in systems of components larger than molecules. A major focus of colloid science has been on understanding the forces between colloidal particles suspended in a fluid. For a long time, the main obstacle to verifying theories of colloidal forces has been the lack of experimental methods capable of directly measuring the forces between colloidal particles separated by a gap of few nanometers. Recently, advances have been made with new imaging techniques revealing some of the secrets of the spontaneous formation of pattern in homogeneous fluids. During the same time, models of interactions have been developed and tested on macroscopic observations of suspensions after changing their composition. It is clear that a general theory for the forces may not be suitable for all systems, as their characteristics are highly dependent on chemistry and the microscopic environment. In colloidal suspensions, it is now well established that an attractive interaction at distances slightly larger than the particle size is dominated by a repulsive contribution at larger distances. The competition between attraction and repulsion forces is responsible for the appearance of stable clusters of generic aggregation numbers. This paper is intended to provide (i) evidence of the confidence of potential models with competing attractive and repulsive interactions and (ii) appropriate tools for finding intriguing phenomena in the generation of nanostructures.
Problems of psychological well-being and distress of the personality: causes and consequences

The article discusses the study, analysis and systematization of ideas related to psychological well-being (PW) and its levels, models in the context of personal health, free from professional and personal destructions. Employees of the Main Office of the Ministry of Emergency Situations took part in the research. As a result of a series of empirical studies and on the basis of factorization of PW and indicators of personal characteristics, the types of psychological well-being of an individual are highlighted: «socially compensatory productive-passive dysfunctional type», «prosocial productiveactive medium-profit type», «prosocial productive-passive highly prosperous type».
Nonlinear Analysis of Heart Rate Variability: A Comprehensive Review

The traditional techniques for Heart Rate Variability (HRV) analysis in time and frequency domains are often not sufficient to characterize the complex dynamics of the heartbeat, since the mechanisms involved in cardiovascular regulation probably interact with each other in a nonlinear manner. There are already dozens of techniques for non-linear evaluation of HRV. However, until now, systematic studies of large groups of patients using this approach have not been conducted. We present the current state of knowledge in this area based on nonlinear variables more prevalent in existing publications. It can be concluded that the analysis of HRV in the nonlinear domain provides very useful information to characterize the appropriate autonomic balance and is a more reliable marker of complications and mortality in patients with cardiovascular disease.
Modeling Volatility of Asset and Volume of Trade Returns in the Nigerian Stock Market in the Presence of Random Level Shifts

This study investigated the impact of volatility shock persistence on the conditional variance in the Nigerian stock returns using symmetric and asymmetric higher order GARCH family models in the presence of random level shifts and non-Gaussian errors. The study utilised Bai and Perron methodology to detect structural breakpoints in the conditional variance of daily stock and volume of trade returns in the Nigerian stock market from 2nd January, 1998 to 22nd March, 2017. The study employed symmetric GARCH (3,2) and GARCH (2,1)-M models to estimate volatility of asset returns, symmetric GARCH (2,2) and GARCH (2,1)-M to model volatility of volume of trade returns and asymmetric EGARCH (2,2), TGARCH (3,2) and PGARCH (2,3) models to measure the volatility of asset returns as well as asymmetric EGARCH (2,1), TGARCH (1,3) and PGARCH (3,2) models to estimate volatility of volume of trade returns. These models were optimally selected using information criteria and log likelihood as the best fitting symmetric and asymmetric GARCH models to estimate the conditional volatility of asset and volume of trade returns in the Nigerian stock market with and without structural breaks. Results revealed that when random level shifts were ignored in volatility models, the shocks persistence were very high with long memory and variance explosion. But when the random level shifts were incorporated into the GARCH models, there was a significant reduction in the volatility shocks persistence and long memory. Moreover, volatility half-lives also declined drastically while accounting for these sudden level shifts in variance. The study found asymmetry without leverage effects as well as a positive risk-return tradeoff for both asset and volume of trade returns in the Nigerian stock market. The Nigeria banking reform of 2004, the Global Financial and Economic Crises, as well as other local events in Nigeria, were found to have negative and significant impacts on the Nigerian stock market. The study provided some policy recommendations.
ÖRGÜTSEL DESTEK, ÖRGÜTSEL ADALET VE ÖZ KENDİLİK DEĞERLENDİRMESİNİN PSİKOLOJİK SERMAYE ÜZERİNDEKİ ETKİSİ

Bu calisma ile, algilanan orgutsel destek, orgutsel adalet algisi, oz kendilik degerlendirmesinin psikolojik sermayenin onculleri olup olmadigi arastirlmistir. Bu kapsamda calismada calisanlarin; orgutsel destek algilarinin psikolojik sermaye, orgutsel adalet algilarinin psikolojik sermaye ve oz kendilik degerlendirmelerinin psikolojik sermaye uzerindeki etkisi sorgulanmistir. Bu kapsamda 326 calisan uzerinde yapilan arastirmada orgutsel destek, orgutsel adalet algisi ve oz kendilik degerlendirmesinin psikolojik sermayeyi istatistiksel olarak olumlu yonde etkiledigi ve psikolojik sermayenin onculleri oldugu tespit edilmistir.
The Effect Of Iconicity Flash Blindness—An Empirical Study

In our experiment, the Saussurean postulate of arbitrariness has been empirically tested in order to see whether this postulate can be applied to all words to the same extent. Three hundred participants were asked to match Czech words with their Hindi translations. One set of words was randomly chosen from a Hindi corpus (set A); the second set consisted of both randomly chosen words and words categorized as ideophones (set B). The participants were successful in matching both sets (the lower level of the confidence interval is about 7% above random guessing), and their performance showed unexpected patterns: For one, not only iconic properties (the sound qualities) but also iconicity itself is an important distinctive feature and recipients are able to exploit this. Moreover, even words considered to be non-iconic (set A) apparently contain a degree of iconicity, which participants are able to draw upon. However, participants appear to lose this ability when non-iconic words are presented in the context of words with evident and abundant iconicity (set B). The effect resembles the accommodation process which is known for other senses; therefore, we call the effect “Iconicity flash blindness”.
McGilchrist and hemisphere lateralization: a neuroscientific and metaanalytic assessment

IainMcGilchrist offers sweeping claims about how the brain supports human understanding and uses these claims to strongly advance an interpretation of Western cultural history involving oppositional hemispheric asymmetries. This paper assesses several of these neuroscientific claims and one of the implications of how global attentionmight relate to moral formation before turning to novel methods aimed at a more rigorous, comprehensive investigation of McGilchrist’s account. In the end, none of the findings from this study offer support for the broad assertions in the target article or other writings.