Miracle-dz/UniFAR-FTUs huggingface dataset:
Utilização do teste de dependência à nicotina de Fagerstrõm como um instrumento de medida do grau de dependência

O tabagismo e considerado a maior causa de morte evitavel. O numero de cigarros consumidos apresenta correlacao com o aumento de incidencia da doenca aterosclerotica, podendo ser o maior contribuinte para o aumento do risco de doenca em combinacao com outros fatores de risco. E classificado como dependencia de nicotina e esta incluido no grupo de transtornos mentais e de comportamentos decorrentes do uso de substâncias psicoativas segundo a classificacao da Organizacao Mundial da Saude. No manejo de pacientes tabagistas, a utilizacao de um instrumento para avaliar o grau de dependencia de nicotina e muito importante. Existe uma correlacao entre nivel de dependencia nicotinica e resposta as diversas terapias. Pacientes com nivel de dependencia baixa poderao ser tratados apenas com abordagem cognitivo-comportamental. Os de grau mais elevado de dependencia necessitarao de terapia farmacologica. Nesta revisao, observa-se que o teste de dependencia a nicotina de Fagerstrom (FTND) e utilizado mundialmente para avaliar a gravidade da dependencia. Esse artigo apresenta uma revisao da literatura sobre o FTND como instrumento de avaliacao no manejo de pacientes tabagistas(AU) Tobacco smoking is considered the leading cause of avoidable death. Use of cigarettes presents correlation with increased incidence of atherosclerotic disease and could be the largest contributor to growth in risk of diseases combined with other factors. It is classified as nicotine dependence and is included in the group of mental disorders and behaviors caused by use of psychoactive substances by the World Health Organization. It is important to have an instrument to evaluate the degree of nicotine dependence in the management of smokers. There is a correlation between degree of nicotine dependence and response to different treatments. Smokers with lower degree of dependence can be treated only with the cognitive behavioral approach. Those with higher degree require pharmacological therapy. This review of literature showed that the Fagerstrom test for nicotine dependence (FTND) is used worldwide to evaluate severity of nicotine dependence. This article presents a review of FTND as an evaluation instrument in the management of smokers(AU)
Measuring Resilience to Climate Change in Ethiopian

Resilience comprises anticipative, mitigative, adaptive, reactive, and transformative capacities. This paper pioneer an approach of measuring resilience using the Resilient Capacity Index (RCI) by considering all the dimensions. Principal Component Analysis (PCA) was used to give relevant weights to the different indicators. OLS and censored regression analysis were used to identify determinants of resilience. The findings indicated that HHs living in the same geographic locations have different levels of resilience. The average RCI for highland, midland and lowland were 0.14, 0.116 and 0.037, respectively, which indicates that HHs in the highland were relatively more resilient. In terms of the specific indicators, the lowland agro climate was better in anticipative, absorptive, and reactive capacities, while those in the highland and midland locations were better in their capacities to mitigate, adapt and transform. Similarly the result indicated that wealth, literacy level, saving behavior, and access to traditional early warning were determinants of resilience in the lowland. Vegetation cover, farm conservation, access to irrigation, and access to credit were determinants of resilience in the highlands, while types of land owned, access to conventional early warning, and access to disaster risk reduction/climate change adaptation (DRR/CCA) learning were important across all climatic zones. This paper is the product of the Vice-Presidency for Economic Governance and Knowledge Management. It is part of a larger effort by the African Development Bank to promote knowledge and learning, share ideas, provide open access to its research, and make a contribution to development policy. The papers featured in the Working Paper Series (WPS) are those considered to have a bearing on the mission of AfDB, its strategic objectives of Inclusive and Green Growth, and its High-5 priority areas—to Power Africa, Feed Africa, Industrialize Africa, Integrate Africa and Improve Living Conditions of Africans. The authors may be contacted at workingpaper@afdb.org. Rights and Permissions All rights reserved. The text and data in this publication may be reproduced as long as the source is cited. Reproduction for commercial purposes is forbidden. The WPS disseminates the findings of work in progress, preliminary research results, and development experience and lessons, to encourage the exchange of ideas and innovative thinking among researchers, development practitioners, policy makers, and donors. The findings, interpretations, and conclusions expressed in the Bank’s WPS are entirely those of the author(s) and do not necessarily represent the view of the African Development Bank Group, its Board of Directors, or the countries they represent. Working Papers are available online at https://www.afdb.org/en/documents/publications/working-paper-series/ Produced by Macroeconomics Policy, Forecasting, and Research Department Coordinator Adeleke O. Salami Correct citation: Boka, G.T. (2017), Measuring Resilience to Climate Change in Ethiopia, Working Paper Series N° 268, African Development Bank, Abidjan, Côte d’Ivoire.
Excess post hypoxic oxygen consumption in Atlantic cod (Gadus morhua)

The report describes a framework that can be used to identify the most important trade-offs in ecosystem based fisheries management. The framework contains a description of how to identify the border between the science and policy domains, how to identify objectives and set goals for management, and how to communicate the management advice. Consultations with stakeholders showed that multi-species management advice needs to be precautionary, provide yields close to MSY, be in accordance with ecosystem constraints and be possible to communicate clearly to managers and policymakers. The use of the framework is demonstrated through examples from three different ecosystems: the Baltic Sea, the North Sea and the Barents Sea. available the States concerned, maintain or restore population of harvested species at which can produce the maximum sustainable yield, as qualified by relevant environmental and economic factors, including the special requirements of developing States, and taking into account fishing patterns, the interdependence of stocks and any generally recommended international minimum standards, whether subregional, regional or global. ” The report describes a framework that can be used to identify the most important trade-offs in ecosystem based fisheries management. The framework contains a description of how to identify the border between the science and policy domains, how to identify objectives and set goals for management, and how to communicate the management advice. Consultations with stakeholders showed that multi-species management advice needs to be precautionary, provide yields close to MSY, be in accordance with ecosystem constraints and be possible to communicate clearly to managers and policymakers. The use of the framework is demonstrated through examples from three different ecosystems: the Baltic Sea, the North Sea and the Barents Sea.
Polyphonic Bird Sound Event Detection With Convolutional Recurrent Neural Networks

—This thesis investigates the use of machine learning for predicting the onset, duration and species of overlapping bird sounds in ﬁeld recordings. The resulting model - a modiﬁed version of SEDnet - achieves state-of-the-art performance with a frame-wise F-score of 0.94 and an error rate of 0.11 on recordings with up to three overlapping sound sources. It is further shown that the features learned by the model have the capacity to segment bird songs into song phrases. To train and test the model, a novel bird sound dataset was created with 500+ sound event annotations for each of 5 bird species. The model, code and dataset are publicly available 1 .
Adsorption of Methylene Blue on raw and activated Clay: case study of Bengurir clay

K. Allam, K. Gourai, A. EL Bouari, B. Belhorma, L. Bih Laboratory of Physical Chemistry of Applied Materials, department of chemistry, Faculty of Sciences Ben M'sik, Hassan II University Casablanca B.P. 7955 20702, (Morocco) National Centre for Energy, Nuclear Science and Technology, CNESTEN, B.P. 1382 R.P. 10001 Rabat (Morocco) Group of physico-chemical of the Condensed Matter (PCMC), Faculty of sciences Meknes, University Moulay Ismail BP 11201 Zitoune, Meknès (Morocco).
A P ] 1 8 A ug 2 00 4 Inverse conductivity problem with an imperfectly known boundary

We show how to eliminate the error caused by an incorrectly modeled boundary in electrical impedance tomography (EIT). In practical measurements, one usually lacks the exact knowledge of the boundary. Because of this the numerical reconstruction from the measured EIT–data is done using a model domain that represents the best guess for the true domain. However, it has been noticed that the inaccurate model of the boundary causes severe errors for the reconstructions. We introduce a new algorithm to find a deformed image of the original isotropic conductivity based on the theory of Teichmüller spaces and implement it numerically. AMS classification: 35J25, 30C75.
Optimal Monetary Policy in Production Networks

This paper studies the optimal conduct of monetary policy in a multisector economy in which firms buy and sell intermediate goods over a production network. We first provide a necessary and sufficient condition for the monetary policy's ability to implement flexible‐price equilibria in the presence of nominal rigidities and show that, generically, no monetary policy can implement the first‐best allocation. We then characterize the optimal policy in terms of the economy's production network and the extent and nature of nominal rigidities. Our characterization result yields general principles for the optimal conduct of monetary policy in the presence of input‐output linkages: it establishes that optimal policy stabilizes a price index with greater weights assigned to larger, stickier, and more upstream industries, as well as industries with less sticky upstream suppliers but stickier downstream customers. In a calibrated version of the model, we find that implementing the optimal policy can result in quantitatively meaningful welfare gains.
USING THE BOOTSTRAP ALGORITHM FOR DEVELOPING AN INFORMATION SYSTEMS AUDIT PROGRAMME

As a side-effect of recent decades of successful information technology innovation, many organisations are developing complex networks of information systems that are becoming increasingly difficult to manage. There is a growing awareness of how this situation has to be approached through structured means with strong management commitment, but current frameworks for information technology governance, such as COBIT, CMMI and ISO 9001, involve so many factors and audit criteria that audit programmes become costly and difficult to implement. If one looks at the situation from an information infrastructure perspective, one might assume that the audit programme could be bootstrapped into place, but it is also known that this approach is likely to fail in communities that are locked into institutional patterns that reinforce design styles assuming vertical control and complete specifications. Still, the claim of this paper is that a bootstrap strategy is useful for developing ISO 9001-based IT auditing programmes if it is implemented in a prudent manner. This claim is investigated through action research in public administration, focusing on how to implement IT auditing by means of the so-called bootstrap algorithm (BA). What the research indicates is that the bootstrap approach is useful for getting the ISO 9001 auditing running in a way that gets quick results and makes it possible to gradually expand the focus in directions that add value to the process. The study adds evidence to the claim that the bootstrap strategy is an effective approach for responding to challenges in IT governance.
Annotating Domain-Specific Texts with Babelfy: A Case Study

Freely available large knowledge graphs, such as DBpedia, Wikidata, and YAGO, generally provide a very solid representation of general knowledge, making them a good basis for text annotation. However, when it comes to annotating domain-specific text documents, these knowledge graphs need to be used with care. Moreover, publications describing real-world use cases of entity linking based on such knowledge graphs are surprisingly rare. In this paper, we describe the use case of annotating customer feedback texts written in German based on Babelfy as the text annotation service. We perform a manual evaluation of the annotations and show that Babelfy annotates around 85% of all annotations correctly. This makes Babelfy as a text annotation method and BabelNet as its knowledge graph a valid baseline for developing a custom knowledge graph and entity linking method, respectively.
Exploiting Discourse-Level Segmentation for Extractive Summarization

Extractive summarization selects and concatenates the most essential text spans in a document. Most, if not all, neural approaches use sentences as the elementary unit to select content for summarization. However, semantic segments containing supplementary information or descriptive details are often nonessential in the generated summaries. In this work, we propose to exploit discourse-level segmentation as a finer-grained means to more precisely pinpoint the core content in a document. We investigate how the sub-sentential segmentation improves extractive summarization performance when content selection is modeled through two basic neural network architectures and a deep bi-directional transformer. Experiment results on the CNN/Daily Mail dataset show that discourse-level segmentation is effective in both cases. In particular, we achieve state-of-the-art performance when discourse-level segmentation is combined with our adapted contextual representation model.
Leading approaches to project management in steering creative projects

This paper focuses on the principles of successful interaction of project management in steering and leading creative projects and endeavours. Creative economy and all its prerequisites opened the world of immense opportunities for many businesses and enabled open-minded entrepreneurs to implement their ideas without limits. Nevertheless, even in the creative industries, strict application of management principles is required in order for the financial success and growth to be achieved. In this paper, we study and scrutinize various entrepreneurial approaches and project management techniques in steering leading creative projects. Our results demonstrate that creativity enhances the success of business projects provided that they are properly managed and controlled.
Model Testing Based on Regression Spline

Tests based on regression spline are developed in this chapter for testing nonparametric functions in nonparametric, partial linear and varying-coefficient models, respectively. These models are more flexible than linear regression model. However, one important problem is if it is really necessary to use such complex models which contain nonparametric functions. For this purpose, p-values for testing the linearity and constancy of the nonparametric functions are established based on regression spline and fiducial method. In the application of spline-based method, the determination of knots is difficult but plays an important role in inferring regression curve. In order to infer the nonparametric regression at different smoothing levels (scales) and locations, multi-scale smoothing methods based on regression spline are developed to test the structures of the regression curve and compare multiple regression curves. It could sidestep the determination of knots; meanwhile, it could give a more reliable result in using the spline-based method.
ANALYSIS OF AES ENCRYPTION WITH ECC

In present era the requirement of internet for wireless communication is rising day by day and thus there is a need of security to guard such communication on unsecure wireless channels. To defend the data from external threat various cryptography techniques are used such as symmetric, asymmetric and hashing. In this paper analysis of AES which is a symmetric technique is done with ECC. Results obtained are analyzed on the basis of different parameters that include storage, encryption time, decryption time, avalanche effect and correlation. Obtained results demonstrate that the impact of this hybrid approach is significant and better than
Identification and Evolution mechanisms of Dynamic Managerial Capabilities (DMCs) in the Grain Milling Sub-sector By David Rwehikiza

The changes in the business environment necessitates firm capabilities to evolve in responding to the threats and opportunities exposed by the environment (Helfat & Peteraf, 2003a). By studying the evolution of capabilities helps us understand how firms can sustain a competitive advantage over a period of time (Teece, 2007). Over decades strategic management research has been skewed to organizational dynamic capabilities rather than individual ́s or manager ́s dynamic capabilities (Mollick, 2012). Thus explanation of the Dynamic Managerial Capabilities is still missing. DMC signifies “the capacity of managers to purposefully create, or modify the resource base of an organization” (Helfat et al., 2007, p. 24). However, in the latest literature (Helfat & Martin, 2015; Helfat & Peteraf, 2015; Kor & Mesko, 2013; Teece, 2014) DMCs research has started gaining attention.
Our Neural Machine Translation Systems for WAT 2019

In this paper, we describe our Neural Machine Translation (NMT) systems for the WAT 2019 translation tasks we focus on. This year we participate in scientific paper tasks and focus on the language pair between English and Japanese. We use Transformer model through our work in this paper to explore and experience the powerful of the Transformer architecture relying on self-attention mechanism. We use different NMT toolkit/library as the implementation of training the Transformer model. For word segmentation, we use different subword segmentation strategies while using different toolkit/library. We not only give the translation accuracy obtained based on absolute position encodings that introduced in the Transformer model, but also report the the improvements in translation accuracy while replacing absolute position encodings with relative position representations. We also ensemble several independent trained Transformer models to further improve the translation accuracy.
The Factors of Information System Success: An Example of Customer Relationship Management Implementation in Food & Beverage Industry

The fierce competition in F&B industry has led companies to look for new tools urgently, and the rapid progress of communication and information technology cause the concept of CRM occurred to assist companies attracting and retaining customers. However the failure rate of IS implementation was reported to be high and the failed reasons were not the same for different companies. For giving assistance to F&B companies for successfully implementing CRM, this study aims to sum factors would impact the success of CRM implementation. By using questionnaire developed based on literatures review, and collecting data from famous F&B companies in Taiwan, 197 valid samples were gathered. Consequently, the EFA statistic technology was used to extract component, and five factors are extracted after an iterative analysis process. These five factors include both negative and positive aspects that respondents indicated that would influence the success of CRM implementation in their companies. Finally, practical and academic implications and recommendations are discussed at the end of this paper.
The Reliability of Quadriceps Muscle Stiffness in Individuals with Osgood–Schlatter Disease

The purpose of this study was to assess the reliability of quadriceps muscle stiffness assessments in individuals with Osgood–Schlatter disease (OSD). Ten subjects were tested for four trials on two occasions within a 2-week period on a Kin-Com dynamometer. A regression coefficient was derived from force-angle data to determine stiffness. Intertriai and interday Intraclass correlations (ICC) and standard error of measurement (SEM) were derived from a repeated-measures ANOVA. Between-trial assessments were more reliable for the outer range 65 to 100° knee flexion (ICC = .95 & .81) than the inner range 35 to 65° knee flexion (ICC = .72 & .57) for both sessions. The average SEMs for outer and inner ranges (over 35°) were 1.1 and 1.3 N, respectively. Assessments between days were less reliable, which may reflect the weekly variation in the presentation of athletes' with- OSD. It remains unclear if the SEM lies within the limits of clinical significance.
A Preliminary Study on Location Estimation without Preparation using Ceiling Signboard

There have been a variety of methods for indoor positioning studied because it is necessary for indoor navigation and other location based useful applications. Most existing methods require infrastructure and/or preparing a database in advance. It is costly and laboring, so that it limits the premises where navigation can be offered. In this paper, aiming to realize indoor localization without any preparation, we propose a novel framework of rough location estimation using an image of ceiling signboard in the subway station. This is an attempt to imitate that human beings can estimate rough positions only from a map and direction signboards. We conducted experiments using scene images including ceiling signboards in Sendai subway station, and confirmed that the framework is promising though it is necessary to improve by considering distance information when making a routing table. Keywords—indoor positioning, smartphone camera, signboard detection, ceiling signboard.
ANALYZING ENERGY EFFICIENT CLUSTERING PROTOCOLS FOR WIRELESS SENSOR NETWORK: A SURVEY

A wireless network consisting of a number of small sensors that communicates with each other. Each sensor collects the data and communicates through the network to a single processing center that is a base station. The communication of node and process of message passing consume energy. A lot of energy consumption by the nodes to transmit data, decrease the network lifetime Clustering is the best solution to save the energy of the network. Clustering divides the Sensors into groups, so that sensors communicate information only to cluster heads and then the cluster heads communicate the aggregated information to the processing center, may save energy. In this paper In this paper, we survey and discuss various dimensions and approaches of some broadly discovered algorithms for clustering. This paper also presents a comparative study of various clustering algorithms and discussion about the potential research areas and the challenges of clustering in WSNs.
The Nurse Educators Perspectives of Clinical Teaching in the Skills Laboratory: A Malawian Experience

• Knowing where you are in the quest for striving for clinical teaching excellence provides the necessary guidance to know where you are, where to go next and what you need to improve for effective clinical teaching and learning RESULTS (b) What to modify • Increasing practise sessions, teaching resources and nurse educators working full time in the skills laboratory to ensure effective clinical teaching.