Miracle-dz/UniFAR-FTUs huggingface dataset:
Effectiveness of Teaching Lazarus Multifaceted Approach on Mental Health of the Elderly

The purpose of the present study was to investigate the effectiveness of teaching Lazarus multifaceted approach on mental health and well-being of elderly people in Tabriz city. The method of this research is applied. For this purpose, among all elderly women covered by health care institutions or in nursing homes of the elderly, 24 women The elderly of Tabriz city in 2012 and in two experimental and control groups (12 people) were selected by random sampling method. The experimental group was trained for 2 months in 10 sessions of 90 minutes in the Lazarus multifaceted training sessions and the control group did not receive any intervention. Oxford Happiness Questionnaire and Mental Health Questionnaire (GHQ) in both groups were performed and the results were reported in SPSS20 software using one-variable covariance test. Findings showed that teaching Lazarus' multifaceted approach on the happiness of elderly women in Tabriz has a significant level of P = 0.012, as well as teaching Lazarus multifaceted approach on mental health of elderly women in Tabriz at a significant level of P Has an impact. Therefore, we conclude that teaching Lazarus' multifaceted approach will increase the health and improve the mental health of the elderly.
Coase, Hotelling and Pigou: The Incidence of a Carbon Tax and Co2 Emissions

A carbon tax has been widely discussed as a way of reducing fossil fuel use and mitigating climate change, generally in a static framework. Unlike standard goods that can be produced, oil is an exhaustible resource. Parts of its price reflects scarcity rents, i.e., the fact that there is limited availability. We highlight important dynamic aspects of a global carbon tax, which will reallocate consumption through time: some of the initial reduction in consumption will be offset through higher consumption later on. Only reserves with high enough extraction cost will be priced out of the market. Using data from a large proprietary database of field-level oil data, we show that carbon prices even as high as 200 dollars per ton of CO2 will only reduce cumulative emissions from oil by 4% as the supply curve is very steep for high oil prices and few reserves drop out. The supply curve flattens out for lower price, and the effect of an increased carbon tax becomes larger. For example, a carbon price of 600 dollars would reduce cumulative emissions by 60%. On the flip side, a global cap and trade system that limits global extraction by a modest amount like 4% expropriates a large fraction of scarcity rents and would imply a high permit price of $200. The tax incidence varies over time: initially, about 75% of the carbon price will be passed on to consumers, but this share declines through time and even becomes negative as oil prices will drop in future years relative to a case of no carbon tax. The net present value of producer and consumer surplus decrease by roughly equal amounts, which are almost entirely offset by increased tax revenues.
Field guide to critical care echocardiography: the UK view

This article provides an overview to the development and current position occupied by critical care echocardiography (CCE) in clinical practice in the UK. We discuss the key clinical and political drivers to the development of the subspecialty and give a detailed outline of the available levels and processes of accreditation in the UK. Discussion of clinical situations from our own practice is used to throw light on how the technique can contribute to clinical practice and how to introduce and maintain quality within that practice.
NEW TECHNOLOGICAL TRENDS IN ENGLISH LANGUAGE LEARNING

In our age, learning a foreign language has become a life-long problem. Good learning of a foreign language from primary school to university and workplace environments is compulsory to compete in the international community. The prominent trends in foreign language learning in the world and in our country have led to many learning styles due to the dazzling development of technology. Together with the developments in technology, it is considered that the borders of the worlds disappear and that the language of science has been transformed into English. For this reason, both in the world of education and in the business world, knowing English carries the person further. This contributes to the fact that those who know English are the most preferred choice in the business world and their personal accomplishments. In spite of this, it is evaluated that there are various difficulties in learning English and the contribution of technology to the learning of English is not discussed enough. There appears to be a gap in this area. New approaches and methods in education also changed the traditional face-to-face English learning and took it to a different level.
Social media influencing as a business – it is all about curatorial logic

The rise of social media influencers (SMIs) across sectors and interest categories is ubiquitous. This is particularly true for lifestyle blogging linking to increased materialism and impact on consumption of fashion products and leisure services. SMIs are mostly defined by academic literature as opinion leaders who are “frequently able to influence others’ attitudes or behaviors” (Tuten and Solomon, 2014). However, SMIs, as opposed to celebrities, journalists and politicians, are ordinary people who have managed to cultivate a following base on a social media platform as a result of knowledge, skill or expertise, or simply passion for certain subjects of interest. Not all SMIs but quite few today (numbers continue growing) are tuning passion for content creation and sharing into profit-making business. SMIs are therefore, entrepreneurial individuals who utlise social media to build a business. In branding literature SMIs are and have been studied as intermediary between audience and brands. However, to our knowledge no studies capture SMIs as business perspective. Hence, in this paper we aim to address this research gap by developing a substantive theory of curatorial logic. This working paper adopts a hybrid exploratory research methodology. Data analysis and discussion represent a work-in-progress phase of this study.
Social Network Mining: A discussion

Social network is model in order to structuring social. In knowledge management, social structures need to be revealed to see social behavior and social change based on the interactions that have taken place. In knowledge technology, the semantic social structure is extracted from information sources to interpret social behavior and its changes, and the meaning is supported by social network analysis. However, social networks do not only reveal social structures and manage them, but social recognition by exploring the potential of social members (social actors) and the community so as to present competitiveness. Competence is defined by the existence of social actors, while the existence of social actors is expressed from the relationship between them whereby the relationship also proves the meaning the competence. By involving artificial intelligence (AI), the meaning can be affirmed in a variety of different ways depending on the treatment given to the source of information so that it is possible to predict and express on the characteristics and behavior of the data. It based on forensic data and information retrieval, for trusty information is generated. Moreover, social network mining is present by considering social network data and the resultant of extraction method so that social networks not only contain information but become knowledge. This serves to bridge the social network analysis gap based on primary and secondary data, so social engineering is possible by exploring all the potential presented by social network extraction.
Fluctuations of Solow economic growth model in the presence of an infectious disease

The economic impact of communicable diseases (mortality, loss of working days, fear of contagion, etc.) leads to a decrease in the demand for goods and services that affects the internal income and employment. In this paper, we propose the Solow model of economic growth in the presence of a communicable disease. Our goal is to study the effects of Kalecki’s time delay and the latent period on long-term economic growth. To do this, we prove that there are two equilibria (diseasefree equilibrium and endemic equilibrium). Then, we investigate their stability. Additionally, we show that the endemic equilibrium can be destabilized through a Hopf bifurcation if the latent period cross some critical value. Finally, we give some numerical simulations to illustrate our results.
Measuring compound flood potential from river discharge and storm surge extremes at the global scale and its implications for flood hazard

Abstract. The interaction between physical drivers from oceanographic, hydrological, and meteorological processes in coastal areas can result in compound flooding. Compound flood events, like Cyclone Idai and Hurricane Harvey, have revealed the devastating consequences of the co-occurrence of coastal and river floods. A number of studies have recently investigated the likelihood of compound flooding at the continental scale based on simulated variables of flood drivers such as storm surge, precipitation, and river discharges. At the global scale, this has only been performed based on observations, thereby excluding a large extent of the global coastline. The purpose of this study is to fill this gap and identify potential hotspots of compound flooding from river discharge and storm surge extremes in river mouths globally. To do so, we use daily time-series of river discharge and storm surge from state-of-the-art global models driven with consistent meteorological forcing from reanalysis datasets. We measure the compound flood potential by analysing both variables with respect to their timing, joint statistical dependence, and joint return period. We find many hotspot regions of compound flooding that could not be identified in previous global studies based on observations alone, such as: Madagascar, Northern Morocco, Vietnam, and Taiwan. We report possible causal mechanisms for the observed spatial patterns based on existing literature. Finally, we provide preliminary insights on the implications of the bivariate dependence behaviour on the flood hazard characterisation using Madagascar as a case study. Our global and local analyses show that the dependence structure between flood drivers can be complex and can significantly impact the joint probability of discharge and storm surge extremes. These emphasise the need to refine global flood risk assessments and emergency planning to account for these potential interactions.
Deep Learning-based Sentiment Analysis: Establishing Customer Dimension as the Lifeblood of Business Management

‘First mover advantage does not go to the first company that launches, it goes to the first company that scales’ (Reid Hoffman, co-founder of LinkedIn, ScaleIt, 2016). M. Andreesen defines scale-up as a company that has identified its product/market fit and has reached notable proofs of market traction (e.g., profitability, revenues, active users, registered users, market demand). It has been previously established that five interdependent core dimensions can be used to evaluate scale-up: customer, product, team, business model and financials. Most of the business failures result from falling apart of one or more of these dimensions with others. We in our article discuss the ‘customer dimension’ as the essence of scaling up. For running a profitable business, it is crucial to evaluate customers’ reviews, like their perception and expectation from the product and services in terms of service quality, deliverables, staff and management practices and pricing. This will increase customer satisfaction which will further boost the demand and popularity of the brand and business. The customers today are very vocal in sharing their experiences through social media blogs, channels, review sites and so on. These experiences need to be decrypted by the management to understand the customer’s point of view, their apprehensions and expectations. Sentiment analysis is one of the best ways to tap customer feedback. The usual way of analysis involves the bag of words model using ngrams. A more refined version is an ontology-based analysis. Research has also been done using the radial basis function kernel for support vector machines (SVMs) (for recognizing polarity of sentiments). Naïve Bayes algorithms have also been used in some sentiment studies along with linear kernel SVM classifiers. But we realized during the literature review that it is not enough to just classify the text into positive and negative or a few more categories. It is even more important to know which topics are being discussed by the customers, their intention behind the message and further the need to classify them as complaints, suggestions, appreciation or query and so on. Thus, we in our article discuss the solution to all these types of analyses using ‘deep sentiment analysis’. We discuss the case of a few current social topics and introduce ‘recurrent neural networks’ (RNNs) and ‘convolutional neural networks’ (CNNs) for sentiment and intent analysis. These advanced analytical techniques will help in the ‘pivoting’ of businesses by taking desired actions such as improving product quality, improving quality of services and increasing quality checks in areas with maximum negative reviews. This eventually will help start-up ventures in improving customer experience and gradually help in the scaling of ventures.
Streamlined Fabrication of Asymmetric Carbon Molecular Sieve Hollow Fiber Membranes

A microporous polymer, polymer of intrinsic microporosity-1, was utilized as the polymeric precursor to simplify the formation of asymmetric carbon molecular sieve hollow fiber membranes. Unlike other methods, asymmetric carbon membranes were formed directly without cross-linking or other pretreatments. In addition, a facile defect removal treatment was developed that can easily be incorporated into a standard fiber solvent exchange procedure. The resulting asymmetric carbon membranes display extraordinary gas selectivities at or exceeding the upper bound for O2/N2, CO2/CH4, He/N2, and C2H4/C2H6. The simplified, two-step method greatly improves the ease of fabrication of defect-free asymmetric carbon hollow fiber membranes for challenging separations.
Joint optimization of maintenance planning and workforce routing for a geographically distributed networked infrastructure

Abstract It is paramount to perform timely and appropriate maintenance actions on networked infrastructures, such as power transmission, transportation, telecommunications, and so forth, in order to ensure their reliability in satisfying the prescribed demand required by the economic development and social well-being of a society. For this purpose, the time of travelling between the components to be maintained needs to be considered, as the components of a real-world infrastructure are usually geographically widely distributed. To address this problem, we propose a holistic bi-objective optimization approach for the joint optimization of maintenance planning and workforce routing for a networked infrastructure, in order to determine a practical maintenance plan that can simultaneously maximize its reliability and minimize the incurred cost. To deal with the complexity of the proposed problem, we develop a Two-level Pareto Simulated Annealing algorithm to approximate the Pareto-optimal solutions of the proposed problem. Finally, two numerical examples are employed to illustrate the ability of the proposed approach in dealing with the maintenance optimization problem of a geographically distributed networked infrastructure.
Effect of Quantitative Early Feed Restriction on Growth Performances, Meat Quality, Abdominal Fat and Serum Lipid Profile in Broiler Chicken

Excessive fat in modern broiler strains is one of the major problems faced by the broiler industry. This experiment was conducted to study the effect of feed restriction at early age on broiler chicken performance, meat quality, abdominal fat content, and serum lipid prole. Two hundred, Cobb500 day-old broiler chicks were randomly assigned into five treatments; T1: ad-libitum feeding (control), T2 and T3: 75 and 50% of ad-libitum feeding from day 8 - 14, respectively, T4 and T5: 75 and 50% of ad-libitum feeding from day 15 - 21, respectively. All birds were fed with ad-libitum before and after the completion of the respective restriction periods. Total feed intake was significantly lower (p 0.05) were observed in weight gain, feed conversion ratio, and dressing percentage among the treatments. Abdominal fat and muscle crude fat contents in birds fed with restricted diets from day 8 - 14 were significantly lower (p 0.05) of treatments on organ weights, muscle protein contents, and serum lipid profile. In conclusion, 50% feed restriction during day 8 - 14 is a better solution to reduce the fat deposition without interfering on growth performances of broiler chicken with lower cost.
Reconsidering Coastal Archaeological Sites in Late Bronze Age Cyprus: Tochni-Lakkia and the South-Central Coastscape

The Cypriot Late Bronze Age (referred to as Late Cypriot and LBA, 1680/1650–1100 b.c.e.) has attracted particular attention due to textual and material evidence that suggests engagement with the international maritime trade networks of the eastern Mediterranean. A longstanding scholarly preoccupation with interregional trade has encouraged the development of theoretical models that aim to reconstruct the economy of the island and generally view Late Cypriot coastal sites as gateway communities channeling copper to the eastern Mediterranean. Studies have also highlighted the local and regional significance of these communities and have shed light on their complex economic networks. In this paper, we use data from coastal Tochni-Lakkia, an actively eroding site located near two major Late Bronze Age centers (Kalavasos-Ayios Dhimitrios and the Maroni Complex) to add nuance to smaller-scale regional interaction networks along the south-central coast of the island. To do that, we engage evidence from trial excavations and archaeological and geophysical surveys at Tochni-Lakkia in the form of a preliminary report with theoretical approaches that highlight the potential for and role of regional maritime networks and the concept of coastscape.
Producing the Global Classroom: Exploring the Impact of US Study Abroad on Host Communities in San Jose, Costa Rica and Florence, Italy

This project draws attention to a disconnect between US higher education internationalization policy rhetoric which centers ideas of mutual cross-cultural exchange, and study abroad research, which focuses almost exclusively on the educational and experiential outcomes of the US based participant. Using neoliberalism as a theoretical framework, this comparative case study utilizes qualitative interviews with 57 host community members in the popular study abroad destinations of San Jose, Costa Rica and Florence, Italy, to focus on how those who engage with US study abroad students understand and are impacted by those encounters. Each descriptive case explores: a) what motivates locals to engage with US students; b) their modes of educative engagement; c) instances of harmony and dissonance that result; d) how they make meaning of these encounters; e) and what they see as outcomes of US study abroad in the community. Across these two diverse cases the findings suggest that many hosts perceive US students’ aversion to linguistic (and cultural) immersion as a lack of respect for hosts; the presence of US students contributes to foreign (US) imperialism; and that study abroad program design choices have an impact on the study abroad host experience. Producing the Global Classroom: Exploring the Impact of US Study Abroad on Host Communities in San Jose, Costa Rica and Florence, Italy by Julie M. Ficarra B.A. University at Buffalo, 2010 Ed.M. Harvard University, 2011
LANDLOCKED COUNTRIES, NATURAL RESOURCES AND GROWTH: THE DOUBLE ECONOMIC CURSE HYPOTHESIS

In this paper, we discuss the hypothesis of a double effect of economic slowdown on economic growth, resulting by the income of natural resources and being a landlocked country. We considered the problem of heterogeneity as conditioned functions to quantile moments in response of economic growth. To do this, groups of 97 countries are considered for the period 1970-2014. The results suggest that the “double economic curse” presents an annual impact of -3% in quantiles of medium-low growth countries. Subsequently, additive effects between human capital and trade openness are evaluated to mitigate the lag impacts on growth: Decreasing approximately between 20% and 40% of the negative effect for low growth countries and contracting around 10% and 50% for countries with medium growth rates.
Promoting the Effectiveness of Problem-Based Learning

As educators continue to promote student achievement in an ever-changing world, continual review and adjustment of teaching practices are necessary. Incorporating problem-based learning (PBL) can provide opportunities for students to develop 21-century skills while engaging them in authentic learning experiences. In order to be effective, educators must thoughtfully consider and develop the conditions that best promote the success of PBL and understand the expected impacts on student achievement. Research in school settings suggests that certain conditions promote the effective implementation of PBL, and a variety of student impacts can be expected. PBL experiences can show success when the situation is open-ended, related to real-life, and includes multiple disciplines. Students that experience PBL can show improved attitudes, behaviors, satisfaction, creativity, collaboration skills, research abilities, vocabulary development, communication skills, and overall achievement. Some negative impacts can also occur with the use of PBL. Studies note difficulties accessing resources or information, confusing and noisy classrooms, difficulties transitioning away from direct instruction, and delays in results.