Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence-Based Verbal De-escalation Techniques for the Family Nurse Practitioner: Education and Simulation

Background: Healthcare workers are 4 times more likely to be exposed to workplace violence than workers employed in private industry, with assault rates as high as 7.8 per 10,000 workers. The National Institute for Occupational Safety and Health defines workplace violence as “violent acts, including physical assaults, and or threats of assault, directed toward persons at work or on duty” (OSHA, 2015, p. 2). Verbal de-escalation techniques that assist with care of the agitated patient are not routinely taught to Family Nurse Practitioners (FNPs) throughout their years of advanced coursework, yet it is something they are likely to encounter given the research highlighting the disturbing assault rates against healthcare providers. Methods: In an effort to improve the delivery of patient centered care and enhance the safety of FNPs in the outpatient setting, a verbal de-escalation educational module and live in-person simulation training was created to serve as a resource to guide the behavioral management of an agitated patient. The aim of this evidence-based project was to provide practicing FNP clinicians and FNP students with training in verbal de-escalation techniques designed to promote workplace safety, reduce rates of violence against providers, and ultimately enhance provider comfort and satisfaction when working with an agitated patient. Results: A total of 14 participants, 10 FNP students and 4 FNP clinicians, participated in the educational intervention outlined by this project. Data analysis demonstrated a dramatic increase (117%) in the participant‟s confidence in their ability to implement verbal de-escalation techniques following the educational intervention. Conclusions: Overall, this project was a cost effective way to supplement knowledge and experience with evidence-based interventions aimed to assist the FNP with successful verbal deescalation of an agitated patient.
Assessment of Endovascular Coiling versus Neurosurgical Clipping of IntracranialAneurysms in Patients with Subarachnoid Hemorrhage

Objective: To evaluate the outcome and length of hospitalization of Endovascular Coiling and Surgical Clipping methods in the treatment of intracranial aneurysms in patients with subarachnoid hemorrhage. Method: A total of 200 (n=200) intracranial aneurysms patients with subarachnoid hemorrhage were studied in a retrospective study. The patients were randomly divided into two groups, Group A (n=100) who were treated with neurosurgical clipping and Group B (n=100) who were treated with endovascular coiling. Both groups were followed up during their stay in the hospital and 6 months postoperatively, their clinical outcome was evaluated based on Modified Rankin Scale scoring system six months after operation. Results: The length of hospitalization for Group A patients was median ± IQR (18 ± 14) days and for Group B patients was median ± IQR (14 ± 13). The outcome for Group A patients, 61(61%) achieved good clinical outcome, 31 (31%) dependency and 8 (8%) death. Group B patients, 73 (73%) achieved good short term clinical outcome, 22 (22%) dependency and 5 (5%) death after six months follow up. Conclusion: Our study shows that endovascular coiling treatment of ruptured intracranial aneurysms has short length of hospitalization and better clinical outcome with a relatively low mortality, low dependency and higher good outcome rates than surgical clipping in patients feasible for either method
Country-level Governance and Capital Markets in Asia-Pacific Region

Abstract Manuscript type: An empirical analysis of the relationship between country-level governance and share markets in the Asia-Pacific region was carried out using dynamic value at risk (Dynamic VaR), mixed data sample (MIDAS) and exponential generalised autoregressive conditional heteroskedasticity (EGARCH) models. Research question/issue: Is there a relationship between a country’s governance and stock market in terms of the level of returns and share price volatility? We hypothesise that stock returns for countries with higher levels of governance will have lower ex ante expected returns and less volatility than countries with lower levels of governance. Research findings/insights: It is evident from the empirical findings that there is still significant diversity in both corporate-level governance and country-level governance within the Asia-Pacific region. The results from using mixed data sample-autoregressive distributed lag (MIDAS-ADL) model correlation between world governance index (WGI) and the dynamic VaR suggest that the estimators of high frequency slope for India, China and Malaysia are negative. In addition, their t statistics show that the correlation is significant; meanwhile, their goodness of fit is also very high confirming the explanation power of MIDAS-AD model. Consequently, the capital market performances of India, China and Malaysia are negatively related to their corporate-level governance and country-level governance. However, China has a positive correlation between WGI and corporate-level governance and country-level governance. This uncommon phenomenon may be the result of its special political system and the segregation of the capital market and the real economy. Theoretical/academic implications: The linkage between country-level governance and volatility of stocks in Asia-Pacific markets indicates there is scope to reduce stock price volatility through enhanced national governance. Volatility as an indicator of risk reflects market uncertainty in terms of processing information signals to find the equilibrium return risk nexus. Consequently, researchers have to incorporate the data of different frequency into the same equation using robust methods. Practitioner/policy implications: Regulatory frameworks encompassing stock markets will benefit from a more focussed consideration of the way in which governance and risk are correlated. Findings from the generalised autoregressive conditional heteroskedasticity (GARCH) and VaR analysis are that stock market volatility is a suitable proxy for the governance of a country. As country governance indices are annual at best, volatility measures give more timely readings. An increase in volatility suggests there is a decline in national governance, and this has implications for those involved in trade, donor organisations and international lending agencies such as the World Bank.
Latest Trends in Generalized Multi-Protocol Label Switching Standardization

This paper presents the latest trends in Generalized Multi-Protocol Label Switching (GMPLS) standardization within the Internet Engineering Task Force (IETF). GMPLS, a suite of control and management plane protocols, represents an extension of MPLS to cover any connection-oriented technology, such as packet (or MPLS), Time Division Multiplexing (TDM), lambda and fiber. GMPLS allows automated network operations, distributed at the network equipment level, with multi-vendor and multi-layer interoperability. As such, it is expected that GMPLS will enable control and management of the transport network by standardized mechanisms, rather than proprietary management systems and interfaces. In addition, GMPLS offers opportunities to integrate control and management of multiple network layers. The basic suite of GMPLS protocols, namely signaling, routing and link management, has been already standardized, and has been shown to be stable and functional through several years of testing and early deployments. Now carriers are looking at how they can leverage the protocols to realize revenue and activate advanced services. Accordingly, discussion in the IETF has shifted to how to apply GMPLS protocols to support various scenarios and use cases. After briefly reviewing GMPLS basics, this paper presents the latest trends in GMPLS standardization, with a focus on deployment strategies, service aspects, and operation and management.
Grocery Store Density and Food Waste

We study the impact of grocery-store density on the food waste generated at stores and by households. Food waste is a major contributor to carbon emissions (as big as road transport). Identifying and influencing market conditions that can decrease food waste is thus important to combat global warming. We build and calibrate a stylized two-echelon perishable-inventory model to capture grocery purchases and expiration at competing stores and households in a market. We examine how the equilibrium waste in this model changes with store density. An increase in store density decreases consumer waste due to improved access to groceries, whereas increasing retail waste due to decentralization of inventory increased variability propagation in the supply chain (cycle truncation) and diminished demand by customers. Higher density also induces more competition which further increases (decreases) waste when stores compete on prices (service levels). Overall, consumer waste reductions compete with store waste increases and the effects of increased competition. Our analysis shows that higher density reduces food waste up to a threshold density; it leads to higher food waste beyond this threshold. Put differently, in so far as food waste is concerned, there exists an optimal store density. Calibration using grocery industry, economic, and demographic data reveals that actual store density in most American cities is well below this threshold/optimal level, and modest increases in store density substantially reduce waste; for example, in Chicago, just 3–4 more stores (per 10 sq km) can lead to a 6%–9% waste reduction, and a 1%–4% decrease in grocery expenses. These results arise from the principal role of consumer waste, suggesting that activists and policy makers’ focus on retail waste may be misguided. Store operators, urban planners, and decision makers should aim to increase store densities to make grocery shopping more affordable and sustainable.
Controle Descentralizado de Sistemas Interconectados por Não-Linearidades Setoriais Sujeitos a Saturação nos Atuadores

: The problem of designing decentralized control laws for continuous-time interconnected systems through sector-boundedness nonlinearities subject to state and control input constraints is addressed in this paper. Suﬃcient conditions taking into account state constraints are derived and expressed in terms of Linear Matrix Inequalities (LMIs). It is shown that the closed-loop system can be made asymptotically stable while at the same time, the estimate of the domain of attraction for the closed-loop system is maximized. Finally, the synchronization problem of an electric distribution network composed by generators is considered in order to illustrate the eﬀectiveness of the design approach proposed. Resumo
An Efficient Algorithm for Cardiac Arrhythmia Classification Using Ensemble of Depthwise Separable Convolutional Neural Networks

Many algorithms have been developed for automated electrocardiogram (ECG) classification. Due to the non-stationary nature of the ECG signal, it is rather challenging to use traditional handcraft methods, such as time-based analysis of feature extraction and classification, to pave the way for machine learning implementation. This paper proposed a novel method, i.e., the ensemble of depthwise separable convolutional (DSC) neural networks for the classification of cardiac arrhythmia ECG beats. Using our proposed method, the four stages of ECG classification, i.e., QRS detection, preprocessing, feature extraction, and classification, were reduced to two steps only, i.e., QRS detection and classification. No preprocessing method was required while feature extraction was combined with classification. Moreover, to reduce the computational cost while maintaining its accuracy, several techniques were implemented, including All Convolutional Network (ACN), Batch Normalization (BN), and ensemble convolutional neural networks. The performance of the proposed ensemble CNNs were evaluated using the MIT-BIH arrythmia database. In the training phase, around 22% of the 110,057 beats data extracted from 48 records were utilized. Using only these 22% labeled training data, our proposed algorithm was able to classify the remaining 78% of the database into 16 classes. Furthermore, the sensitivity ( S n ), specificity ( S p ), and positive predictivity ( P p ), and accuracy ( A c c ) are 99.03%, 99.94%, 99.03%, and 99.88%, respectively. The proposed algorithm required around 180 μs, which is suitable for real time application. These results showed that our proposed method outperformed other state of the art methods.
Evaluation of the implementation of Batik-skills training program

The purpose of this study is to evaluate the implementation of batik skills training program as a recommendation for program improvement. The method used in this research is a qualitative approach using Context, Input, Process, and Product evaluation model. Samples were taken from the Institute of Skills and Training in the areas of Jakarta, Bogor, Depok, Bekasi, and Tangerang. The results of the evaluation components that meet the evaluation criteria are all aspects of the context component, discipline and learning process, while the components of batik teachers' education qualifications, the use of educational facilities and infrastructure standards, curriculum components, program financing, evaluation of learning outcomes, mastery of theoretical competencies, practices, and impacts to program participants have not been met. The batik skills training program needs to be continued with some improvement. It is recommended for the product components, especially on the impact aspects felt by graduates, to be improved.
Example‐based image recoloring in an indoor environment

Color structure of a home scene image closely relates to the material properties of its local regions. Existing color migration methods typically fail to fully infer the correlation between the coloring of local home scene regions, leading to a local blur problem. In this paper, we propose a color migration framework for home scene images. It picks the coloring from a template image and transforms such coloring to a home scene image through a simple interaction. Our framework comprises three main parts. First, we carry out an interactive segmentation to divide an image into local regions and extract their corresponding colors. Second, we generate a matching color table by sampling the template image according to the color structure of the original home scene image. Finally, we transform colors from the matching color table to the target home scene image with the boundary transition maintained. Experimental results show that our method can effectively transform the coloring of a scene matching with the color composition of a given natural or interior scenery.
Social Spreading in Complex Networks

The scope of the research presented in this thesis is fairly broad, touching upon areas like social network analysis, information and behavioral contagion models, and social data science. As the world becomes increasingly digitalized, it becomes crucial to better understand interactions in the digital sphere. The proliferation of online communication allows interaction between people with more diverse backgrounds more varied areas of knowledge than before. However while increased digitalization carries the potential for an explosion of diversity in communication, that is far from the only conceivable consequence. The same diversity offers anyone online a multitude of different communities and sources of information. This carries the risk of individuals choosing disproportionately often to connect to individuals that are similar to themselves, and to consume exclusively information which supports their preexisting convictions. Fortunately fields such as network science, computational social science, and machine learning are developing rapidly, and an increasing amount of interest is being taking in understanding online interactions. The common theme for the research on which this thesis builds, is a preoccupancy with the aforementioned aspects of online behavior. The reseach includes work on quantitative modeling of information flows in social systems, attention dynamics/economics models, techniques for analysis of polarized discourse/echo chambers, and the influence of language on collective behavior.
List of Birds Sigthed on Livestock Farms in Sucre, Colombia

The rural areas of the Department of Sucre, Colombia, have a considerable bird species richness, but there are not many reports on this. In this work, we classify and record the species we sighted in nine cattle farms in the region. We obtained information on the relative abundance of each species (frequency of observation about the total sample), and biotopes where we observe them. We use chi square to know if there was an association between these parameters and also about to the food guild to which the species belong. We obtained the latter in the specialized bibliography. We use the Sorensen Index, to determine the degree of similarity of the communities of species in each biotope. We spot 103 species of birds. The best-represented order was Passeriformes, with eleven families and 36 species. Most of the species were abundant, and the biotope with the highest sighting was the open area, although many species were present in more than one biotope. We found no association between the abundance of species and the biotope in which we observed them, nor about the food guild. Among the species sighted, 21 are migratory, mostly wintering with permanent breeding populations. In this paper we discuss the importance of livestock farms for wildlife conservation.
Asupan energi dan konsumsi makanan ringan berhubungan dengan kejadian gizi lebih pada remaja di SMA Islam AL-AZHAR 1 Jakarta

Gizi lebih dapat didefinisikan sebagai akumulasi lemak abnormal atau berlebihan sehingga dapat mengganggu kesehatan. Penyebabnya adalah ketidakseimbangan antara asupan energi, konsumsi makanan ringan, dan minuman berperisa. Penelitian ini bertujuan untuk mengetahui hubungan asupan energi, konsumsi makanan ringan, dan konsumsi minuman berperisa dengan kejadian gizi lebih pada remaja usia 16-18 tahun di SMA Islam Al-Azhar 1 Jakarta. Penelitian ini dilakukan secara cross-sectional dengan metode proportionate stratified random sampling. Subjek berjumlah 120 orang, yang sebagian besar adalah laki-laki. Hasil penelitian ini menunjukkan sebagian besar subjek memiliki status gizi lebih (50,8%), asupan energi lebih (60%), konsumsi makanan ringan berlebihan (52,5%), dan konsumsi minuman berperisa dalam jumlah baik (55,8%). Hasil uji statistik chi-square menunjukkan adanya hubungan antara asupan energi (p<0,05) dan konsumsi makanan ringan dengan gizi lebih (p<0,05). Selanjutnya, tidak ada hubungan antara konsumsi minuman berperisa dengan gizi lebih (p>0,05).
Isolasi Bakteri Pendegradasi Minyak Mentah dan Polisiklik Aromatik Hidrokarbon dari Sedimen Mangrove Bintan

Bintan dikenal sebagai wilayah dengan kawasan hutan mangrove yang luas, namun berpotensi mengalami cemaran minyak karena letaknya yang berbatasan dengan jalur perairan Internasional. Bakteri indigen pendegradasi minyak memainkan peranan penting dalam proses bioremediasi tumpahan minyak di lingkungan. Pada penelitian ini diisolasi bakteri pendegradasi minyak dan polisiklik aromatik hidrokarbon (PAH) dari sedimen mangrove Bintan. Sampel sedimen mangrove diambil dari jenis mangrove yang berbeda, yaitu Rhizopora apiculata , Xylocarpus granatum, Ceriops tagals dan Lumlitzera littorea. Isolasi bakteri pendegradasi minyak dilakukan menggunakan media pengayaan melalui penambahan crude oil ALCO. Sebanyak 45 isolat bakteri pendegradasi minyak berhasil diisolasi dari sedimen mangrove. Melalui tes degradasi dengan metode sublimasi, sebanyak 13 isolat bakteri diketahui juga menunjukkan kemampuan mendegradasi PAH dengan jenis yang berbeda, diantaranya fenantrena, acenapthrene, dibenzothiophene dan fluorene. Berdasarkan analisis 16s rRNA, ketigabelas isolat bakteri diidentifikasi berasal dari 6 genus, yaitu Rhodococcus, Bacillus , Sphingopyxis , Rhizobium , Mycobacterium , dan Gordonia.
Managing spent nuclear fuel in South Korea: Heterogeneous public attitudes toward different management strategies at individual‐ and segment levels

The management of spent nuclear fuel is a problem shared by countries that are operating nuclear power plants or have done so in the past. To implement socially agreed spent nuclear fuel management policies, it is necessary to recognize public attitudes and preferences toward policies. This study analyzed public preferences at the individual‐ and segment levels toward spent nuclear fuel management strategies in South Korea using a choice experiment and the hierarchical Bayesian normal mixture discrete choice model. Furthermore, it compared public acceptance for different types of management strategies using ex‐ante simulation. Accordingly, the public was categorized into two groups. Segment 1 (31.62%) took a smaller proportion of the population than segment 2 (62.38%) and showed a higher degree of heterogeneity than segment 2. Segment 1 was more sensitive to increased electricity costs than segment 2 because of the implementation of spent nuclear fuel management policies and preferred a democratic process. Based on the results, we expect that the Korean government would receive public support when proceeding with the construction and operation of a permanent spent nuclear fuel repository facility. However, considering the degree of heterogeneity, governmental efforts to achieve social consensus are necessary.
Evidence for RNA editing in the transcriptome of 2019 Novel Coronavirus

The 2019-nCoV outbreak has become a global health risk. Editing by host deaminases is an innate restriction process to counter viruses, and it is not yet known whether it operates against coronaviruses. Here we analyze RNA sequences from bronchoalveolar lavage fluids derived from two Wuhan patients. We identify nucleotide changes that may be signatures of RNA editing: Adenosine-to-Inosine changes from ADAR deaminases and Cytosine-to-Uracil changes from APOBEC ones. A mutational analysis of genomes from different strains of human-hosted Coronaviridae reveals patterns similar to the RNA editing pattern observed in the 2019-nCoV transcriptomes. Our results suggest that both APOBECs and ADARs are involved in Coronavirus genome editing, a process that may shape the fate of both virus and patient.
Women directors on FTSE company boards: An exploration of the factors influencing their appointment

Abstract This study provides analysis and insight into the views and experiences of 12 top executives of FTSE 350 companies about appointing women to their boards, against background growth in the number of female non-executive directors but the number of female executive director appointments showing no progress. Findings showed that the idea of women on boards as non-executive directors is well embedded, yet many barriers to increasing the numbers of women executive directors remain. Lack of robust selection processes, negative views of executive search companies, and views about the shortage of suitably qualified women are reported while most participants did not view the development of the female executive pipeline as a top priority. Findings suggest that public focus on increasing the number of non-executive directors has been effective, attention should be shifted to galvanise efforts in FTSE companies to develop their female talent and increase executive director numbers.