Miracle-dz/UniFAR-FTUs huggingface dataset:
Bottom-Up Interventions Effective in Promoting Work Engagement: A Systematic Review and Meta-Analysis

Background: Promoting work engagement is of interest to organizations across sectors due to the associated positive outcomes. This interest warrants research on the evidence of work engagement interventions. Intervention research increasingly advocates a bottom-up approach, highlighting the role of employees themselves. These workplace interventions often encourage employees to identify, develop, and make use of workplace resources. The aim of this systematic review and meta-analysis is to investigate the effectiveness and potential underlying mechanisms of these bottom-up, resource-developing interventions. Method: Systematic searches were conducted in the online databases Web of Science, Academic Search Complete, Business Source Ultimate, PsycInfo, PsycArticles, SCOPUS, and Google Scholar. Publication year range was 2000–2020. Eligibility criteria were defined using PICOS. To be eligible for the systematic review, the intervention study identified had to aim at promoting working individuals’ work engagement by developing workplace resources from bottom-up. Work engagement had to be measured using the Utrecht Work Engagement Scale. The systematic review included one-, two-, or multiple-armed – randomized or non-randomized – intervention studies with various study designs. Further, a meta-analysis was conducted on a sub-set of the studies included in the systematic review. To be eligible for the meta-analysis, the studies had to be two- or multiple-armed and provide the information necessary to compute effect sizes. Results: Thirty-one studies were included in the systematic review. The majority reported that overall work engagement increased as an effect of the intervention. The evidence regarding the sub-components of work engagement was scattered. Potential underlying mechanisms explored were intervention foci, approach, and format. Dimensions of satisfaction and performance were identified as secondary outcomes. Participant experiences were generally described as positive in most of the studies applying mixed methods. The meta-analysis showed a small but promising intervention effect on work engagement (24 studies, SMD: −0.22, 95% CI: −0.34 to −0.11, with I2=53%, indicating moderate inconsistency in the evidence). Conclusion: The synthesized evidence suggests that bottom-up, resource-developing interventions are effective in the promotion of work engagement. The meta-analysis suggests that focusing on strengths use or mobilizing ego resources and adopting a universal approach increase intervention effectiveness.
The Role of Electrode-Site Placement in the Long-Term Stability of Intracortical Microstimulation

Intracortical microelectrodes are neuroprosthetic devices used in brain-machine interfaces to both record and stimulate neural activity in the brain. These technologies have been improved by advances in microfabrication, which have led to the creation of subcellular and high-density microelectrodes. The greater number of independent stimulation channels in these devices allows for improved neuromodulation selectivity, compared to single-site microelectrodes. Elements of electrode design such as electrode-site placement can influence the long-term performance of neuroprostheses. Previous studies have shown that electrode-sites placed on the edge of a planar microelectrode have greater chronic recording functionality than sites placed in the center. However, the effect of electrode-site placement on long-term intracortical microstimulation (ICMS) is still unknown. Here, we show that, in rats chronically implanted with custom-made planar silicon microelectrodes, electrode-sites on the tip of the device outperformed those on both the edge and center in terms of the effect per charge delivered, though there is still a slight advantage to using edge sites over center sites for ICMS. Longitudinal analysis of ICMS detection thresholds over a 16-week period revealed that while all sites followed a similar trend over time, the tip and edge sites consistently elicited the behavioral response with less charge compared to center sites. Furthermore, we quantified channel activity over time and found that edge sites remained more active than center sites over time, though the rate of decay of active sites for center and edge sites was comparable. Our results demonstrate that electrode-site placement plays an important role in the long-term stability of intracortical microstimulation and could be a potential factor to consider in the design of future intracortical electrodes.
APPLIED CLASSIFICATION RULE MINING TO ENHANCE E-LEARNING IN THE CONTEXT OF EDUCATIONAL DATA

In 21 century everyone is using internet to avail useful information or to extend their knowledge [8]. Percentage rate of educational contents or knowledge resources are also increasing day by day. In today’s on internet where plentiful information and knowledge resource available but yet learners are not able to get benefits out of it. In this paper, I have introspect different factors that affecting behavior of the learner during online study. We know that at different level of education, learners want to explore online education to get benefits from it but still most of the learners are not able to access internet because some of them do not have experience to surf on Internet, searching skills also affecting the online learning capabilities. Technology and content quality are another issues. Without getting external support learner is unable to access online contents frequently. All these factors affect the way of searching over the WWW. To accomplish this research, we need to judge that how these factors affecting online learning, I have collected data of learners based upon their educational level through questionnaire, then with the help of datamining techniques [4]. I have reached to the productive result. corresponding author 2020 Mathematics Subject Classification. 97C30, 91D15, 91E40.
Sharing economy: Approaches and distances between the notion and the practice of sharing

https://orcid.org/0000-0002-3190-9968 Professor at the School of Administration and at the Postgraduate Center for Administration at the Federal University of Bahia (UFBA). PhD in Administration from the Federal University of Bahia (UFBA). ariadnescalfoni@gmail.com ABSTRACT This work aims to analyze the existing approaches and distances between sharing and what is practiced by users of organizations in the sharing economy. Sharing practices in two organizations were studied: Airbnb and Servas. Mauss' gift theory was used as a lens of analysis. Interviews were conducted with users / members of both organizations and content analysis was undertaken. Results revealed, while in Servas, there is a great similarity between sharing and the practices found in it, in Airbnb there is a certain distance. It is suggested to use terms and expressions that best represent the practices of organizations inserted in the sharing economy.
Tissue factor cytoplasmic domain exacerbates post-infarct left ventricular remodeling via orchestrating cardiac inflammation and angiogenesis

The coagulation protein tissue factor (TF) regulates inflammation and angiogenesis via its cytoplasmic domain in infection, cancer and diabetes. While TF is highly abundant in the heart and is implicated in cardiac pathology, the contribution of its cytoplasmic domain to post-infarct myocardial injury and adverse left ventricular (LV) remodeling remains unknown. Methods: Myocardial infarction was induced in wild-type mice or mice lacking the TF cytoplasmic domain (TF∆CT) by occlusion of the left anterior descending coronary artery. Heart function was monitored with echocardiography. Heart tissue was collected at different time-points for histological, molecular and flow cytometry analysis. Results: Compared with wild-type mice, TF∆CT had a higher survival rate during a 28-day follow-up after myocardial infarction. Among surviving mice, TF∆CT mice had better cardiac function and less LV remodeling than wild-type mice. The overall improvement of post-infarct cardiac performance in TF∆CT mice, as revealed by speckle-tracking strain analysis, was attributed to reduced myocardial deformation in the peri-infarct region. Histological analysis demonstrated that TF∆CT hearts had in the infarct area greater proliferation of myofibroblasts and better scar formation. Compared with wild-type hearts, infarcted TF∆CT hearts showed less infiltration of proinflammatory cells with concomitant lower expression of protease-activated receptor-1 (PAR1) - Rac1 axis. In particular, infarcted TF∆CT hearts displayed markedly lower ratios of inflammatory M1 macrophages and reparative M2 macrophages (M1/M2). In vitro experiment with primary macrophages demonstrated that deletion of the TF cytoplasmic domain inhibited macrophage polarization toward the M1 phenotype. Furthermore, infarcted TF∆CT hearts presented markedly higher peri-infarct vessel density associated with enhanced endothelial cell proliferation and higher expression of PAR2 and PAR2-associated pro-angiogenic pathway factors. Finally, the overall cardioprotective effects observed in TF∆CT mice could be abolished by subcutaneously infusing a cocktail of PAR1-activating peptide and PAR2-inhibiting peptide via osmotic minipumps. Conclusions: Our findings demonstrate that the TF cytoplasmic domain exacerbates post-infarct cardiac injury and adverse LV remodeling via differential regulation of inflammation and angiogenesis. Targeted inhibition of the TF cytoplasmic domain-mediated intracellular signaling may ameliorate post-infarct LV remodeling without perturbing coagulation.
Using Similarity Search to Covid-19 on Northwest Brazilian

The novel coronavirus (Covid-19) revealed several impacts on the world. In Brazil several problems emerged related the health and economic scenario. Understanding the problem thought big data analysis is a alternative to propose actions for future. We explored similarity search (spatial analysis) between 1794 municipalities in northeastern Brazil. Salvador city was chose as parameter feature. We compare different daily cases (April 01, May 27, and 30 June) to check the similarity. For obtain the results, we select appropriate spatial system. The results strong association in large municipalities, revealing a similar cluster close between adjacent municipalities analyzed. On the future, the result may help decision makers to planning public health policies.
Previous COVID-19 Infection and Antibody Levels After Vaccination

Background: The emergence of new COVID-19 variants of concern coupled with a global inequity in vaccine access and distribution has prompted many public health authorities to circumvent the vaccine shortages by altering vaccination protocols and prioritizing persons at high risk. Individuals with previous COVID-19 infection may not have been prioritized due to existing humoral immunity. Objective: We aimed to study the association between previous COVID-19 infection and antibody levels after COVID-19 vaccination. Methods: A serological analysis to measure SARS-CoV-2 immunoglobulin (Ig)G, IgA, and neutralizing antibodies was performed on individuals who received one or two doses of either BNT162b2 or ChAdOx1 vaccines in Kuwait. A Student t-test was performed and followed by generalized linear regression models adjusted for individual characteristics and comorbidities were fitted to compare the average levels of IgG and neutralizing antibodies between vaccinated individuals with and without previous COVID-19 infection. Results: A total of 1,025 individuals were recruited. The mean levels of IgG, IgA, and neutralizing antibodies were higher in vaccinated subjects with previous COVID-19 infections than in those without previous infection. Regression analysis showed a steeper slope of decline for IgG and neutralizing antibodies in vaccinated individuals without previous COVID-19 infection compared to those with previous COVID-19 infection. Conclusion: Previous COVID-19 infection appeared to elicit robust and sustained levels of SARS-CoV-2 antibodies in vaccinated individuals. Given the inconsistent supply of COVID-19 vaccines in many countries due to inequities in global distribution, our results suggest that even greater efforts should be made to vaccinate more people, especially individuals without previous COVID-19 infection.
Bridging the Financial Gap Among Young People: The Correlation Between Cumulative Debt and Homeownership

Experts have determined that the cost of attending college is rising (Williams, 2006) and as a result, it has altered college graduates’ cumulative debt levels. In addition, research shows that those who attend college are more likely to earn higher salaries (Ma et al., 2016). Consequently, the existence of a low-income college graduate population would be considered a paradox. Simultaneous to such changes mentioned, homeownership among young individuals is declining in the United States (Dettling & Hsu, 2014). As of today, research has focused on the relationship between student loan debt and homeownership but has neglected the relationship between cumulative debt and homeownership. This study will answer the following question: What is the relationship between cumulative debt acquired by lowincome college graduates between the ages of 23-40 in the United States in the 21st century and the corresponding likelihood of homeownership? Through interviews with five low-income college graduates, I collected narratives describing their outlooks on cumulative debt and its influences on homeownership. Through thematic analysis, I drew connections between common themes that indicated how cumulative debt affected one’s actions or thoughts regarding purchasing a home. The results showed that cumulative debt has negative effects on homeownership. Subjects disclosed that their struggle to pay their cumulative debt and inability to accumulate wealth were the two most common hindrances of purchasing a home. This is significant because cumulative debt predetermines how the subject manages their finances to pursue purchasing a home and such data may influence the financial decisions of future generations.
Regional clusters of vulnerability show the need for transboundary cooperation

Reducing vulnerability is essential for adaptation to climate change. Compared to approaches that examine vulnerability to a specific hazard, our analysis offers an alternative perspective that conceptualizes vulnerability to climate change as a phenomenon that is independent of any specific type of hazard but relevant to multiple hazards. Vulnerability is thus a product of structural inequality and systemic in nature. Based on two established index systems, we perform global analyses of specific phenomena—such as poverty, access to basic infrastructure services and forced migration—that influence and determine vulnerability. Our statistical and spatial analyses reveal an emerging pattern of climate vulnerability within regional clusters and shows that vulnerability is a transboundary issue, crossing political, sectorial and geographical borders and impacting shared resources. The spatial statistical hotspot analysis of vulnerability underscores that hotspots, for example of high vulnerability, state fragility, low biodiversity protection or forced migration, emerge in multi-country clusters. This aspect has often been overlooked, most attention to-date having been given to the positioning of individual countries within vulnerability rankings. In hotspots such as in the Sahel, East and Central Africa, as well as in Southern Asia and Central America, vulnerability is interwoven with high levels of state fragility, making adaptation solutions more complex. The recognition of the regional clusters and the transboundary nature of vulnerability calls for new research and action on how to strengthen transboundary approaches for vulnerability reduction, potentially enhancing prospects for successful adaptation.
Matched-Pair Analysis Using Machine Learning to Predict 1-year Mortality in Newborn Twins

Twin pair analysis is a valuable tool for assessing familial risk factors related to several outcomes, including diseases. Machine learning models are standard, powerful tools for prediction, although their use for twin pair analysis is not fully suitable as most models do not account for the existing correlation between twin pairs. In this paper, we have focused on assessing the suitability of machine learning models to predict 1-year mortality using twin data extracted from Brazilian healthcare databases. We have evaluated five models and also used a proposed strategy for matched pair analysis to build an alternative dataset supposed to provide improvements for classification tasks. Our results showed that i) Gradient Boosting was the best classification model, and ii) the matched-pair strategy used did not improve our results as expected. Resumo. A análise de pares de gêmeos é uma ferramenta importante para avaliar fatores de risco familiares relacionados a diversos problemas, inclusve doenças. Modelos de aprendizado de máquina são ferramentas consolidadas utilizadas em diversas tarefas de predição nas mais diversas áreas. Porém, elas não são totalmente adequadas para a análise de conjuntos de dados onde os pares de registros possuem forte correlação entre si, como é o caso de gêmeos. Este artigo avalia a adequabilidade de modelos de aprendizado de máquina para predizer a mortalidade até um ano de gêmeos nascidos no Brasil, utilizando dados extraı́dos de bases de dados públicas. Além disso, também é avaliado um método para análise de dados pareados, criando uma base de dados alternativa para verificar se a aplicação dos modelos de aprendizado de máquina promove ganhos no processo de classificação. OS resultados demonstraram que i) o modelo de aprendizado de máquina Gradient Boosting obteve os melhores resultados na tarefa de classificação e ii) a estratégia para análise de dados pareados não melhorou os resultados conforme esperado.
Model prediction and scenario of urban land use and land cover changes for sustainable spatial planning in Lhokseumawe, Aceh, Indonesia

The purpose of this research is to find the best-fit scenario to support spatial planning, which can optimize the ecological function of urban areas. This study was conducted in Lhokseumawe city, a city which is the center of national activities. The city is also known as an industrial city and special economic zone. Prediction of future growth for this city needs to be done to anticipate the environmental damage that will occur. This prediction uses 2018 land use/cover (LUC) map, to get a prediction of the LUC pattern until 2032. The first stage is to create a raster map for the four variables reviewed in this research, namely a) distance to activity center (DAC), b) distance to road (DRD), c) distance to river (DRV), and d) reserve area (RAR) which are made in the form of a raster layer. The next stage is a scenario model simulation. There are two prediction scenarios assessed in this research to choose the best-fit scenario for 2032, business as usual (BAU) and reserve area interest (RAI). The results showed that the scenario should be chosen is the (RAI) scenario.
Atmospheric Transmission Spectroscopy of Hot Jupiter KELT-10b using Synthetic Telluric Correction Software

High-resolution spectroscopic visible data were obtained with the Ultraviolet and Visible Echelle Spectrograph on the Very Large Telescope. Our goal was to analyze the data in an effort to detect the presence of sodium in the atmosphere of hot Jupiter exoplanet KELT-10b, as well as characterize the orbit of the planet via the Rossiter-McLaughlin effect. Eighty spectra were collected during a single transit of KELT-10b. After standard spectroscopic calibration using ESO-Reflex, the synthetic telluric modeling software molecfit was applied to remove terrestrial atmospheric effects, and to refine the wavelength calibration. Sodium is recognized by its characteristic absorption doublet located at 5895.924 and 5889.951 Å, which can be seen in the planet atmosphere transmission spectrum and through excess absorption during the transit. The radial velocity of the host star was analyzed by measuring the average shift of absorption features from spectrum to spectrum. Our results indicate a sodium detection in the planet transmission spectrum with a line contrast of 0.66% and 0.43% ± 0.09% for the sodium DII and DI lines, respectively. Excess absorption measurements agree to within one half combined standard deviation between the planet transmission spectrum (0.143% ± 0.020%, a 7σ detection) and during the time series (0.124% ± 0.034%, a 3.6σ detection) in a band 1.25 Å wide. The wavelength grid corrections provided by molecfit were insufficient to determine radial velocities and measure the Rossiter-McLaughlin effect.
Malay heritage: rehabilitation of Uma Kabuong Limo house

Uma Kabuong Limo is an 80-year-old traditional Malay house located in an old village of Pulau Belimbing, Riau Province. This building represents Malay architecture. Currently, the building is experiencing damage to its structural and architectural components. Several factors cause building damage such as building age, weather, usage, and flooding. This damage can lead to collapse and loss of the building as a whole. This study aims to identify the characteristics and see the damage to the building elements of Uma Kabuong Limo. This research method is descriptive qualitative with synchronic reading analysis technique. The research stage was to collect data through field observations and interviews. The next stage is making the model through Building Information Modelling to see the comparison of building damage. The results showed that the architectural knowledge was manifested in construction techniques, building materials, and carvings. Damage to buildings can be seen in structural and architectural elements. The level of damage is in the category of heavy damage, so it is necessary to immediately carry out building rehabilitation. The results of this research will be used further in the stage of preparing the document for the rehabilitation model of the Uma Kabuong Limo.
Understanding Gas Sorption Mechanisms in Metal–Organic Materials via Computational Experimentation

xiii Chapter 1: Introduction . 1 Chapter 2: Simulation of the Mechanism of Gas Sorption in a Metal–Organic Framework with Open Metal Sites: Molecular Hydrogen in PCN61 . 9 2.1 Note to Reader . 9 2.2 Abstract . 9 2.3 Introduction . 10 2.4 Methods . 14 2.4. 1 Simulation Parameters . 14 2.4. 2 Many-Body Polarization . 17 2.4. 3 Iterative Relaxation Methods . 20 2.4. 4 Grand Canonical Monte Carlo . 22 2.5 Results and Discussion . 25 2.6 Conclusions . 36 2.7 Acknowledgments . 37 Chapter 3: Understanding Hydrogen Sorption in a Metal–Organic Framework with Open-Metal Sites and Amide Functional Groups . 38 3.1 Note to Reader . 38 3.2 Abstract . 38 3.3 Introduction . 39 3.4 Computational Methods . 44 3.4. 1 Simulation Parameters . 44 3.4. 2 Hydrogen Potentials . 50 3.4. 3 Grand Canonical Monte Carlo . 52 3.5 Results and Discussion . 53 3.5. 1 Isotherms and Isosteric Heats of Adsorption . 53 3.5. 2 Sorbate Radial Distribution Functions . 58 3.5. 3 Sorbate Induced Dipole Distributions . 63 3.5. 4 Effects from Variant Crystal Structures . 67