Miracle-dz/UniFAR-FTUs huggingface dataset:
Banking Panic Risk and Macroeconomic Uncertainty

We show that systemic risk in the banking sector breeds macroeconomic uncertainty. In a production economy with a banking sector, financial constraints of banks can lead to disastrous banking panics. We find that a higher probability of a banking panic increases uncertainty in the aggregate economy. We explore the implications of this banking panic-driven uncertainty for business cycles, asset prices and macroprudential regulation. Banking panic-driven uncertainty amplifies business cycle volatility, increases risk premia on asset prices and yields a new benefit from countercyclical bank capital buffers.
Teachers and students’ perception of competence-based education in the agricultural higher education system (Case of a student cooperative in Iran)

ABSTRACT Purpose: This quantitative study sought to investigate the perceptions of teachers and students regarding competency-based education (CBE) principles at the College of Agriculture at Razi University. Design: This research is a comparative analysis of two groups. The first group consists of undergraduate and graduate students majoring in agriculture who are members and non-members of student cooperatives (n = 256). The second group consists of agricultural faculty members (n = 59). Findings: The results of this study show that students and teachers have different views with regard to the extent to which CBE principles are practiced in the College of Agriculture. Moreover, students with different learning patterns had different perceptions regarding the extent to which CBE is practiced, whereas teachers with different teaching patterns had the same perception of the application of CBE principles in the College of Agriculture. Practical implications: This study has practical implications for agricultural higher education in general and colleges of agriculture in particular. Colleges of agriculture across Iran could encourage their students to establish and engage in student cooperatives so that the ‘what’ and ‘how’ aspects of CBE are put into practice. Theoretical implications: This study has theoretical implications for CBE principles. For example, student cooperatives can be utilized by faculty members as one of the main strategies for developing CBE in agricultural colleges. Originality/value: This study is original in that it moves from theory to practice when considering CBE.
Essays in empirical economics

This first chapter is co-authored with Nicolás Aragón and examines how participant and market confidence affect the outcomes in an experimental asset market where the fundamental value is known by all participants. Such a market should, in theory, clear at the expected value in each period. However, the literature has shown that bubbles often occur in these markets. We measure the confidence of each participant by asking them to forecast the one-period-ahead price as a discrete probability mass distribution. We find that confidence not only affects price-formation in markets, but is important in explaining the dynamics of bubbles. Moreover, as traders’ confidence grows, they become increasingly more optimistic, thus increasing the likelihood of price bubbles. The second chapter also deals with expectations and uncertainty, but from a different angle. It asks how increased uncertainty affects economic demand in a particular sector, using a discrete-choice demand framework. To investigate this issue I examine empirically to what extent varying uncertainty affects the consumer demand for flight traffic using us micro demand data. I find that the elasticity of uncertainty on demand is economically and statistically significant. The third chapter presents a more practical side to the issue examined in the first chapter. It describes how to elicit participants’ expectations in an economic experiment. The methodology is based on Harrison et al. (2017). The tool makes it easier for participants in economic experiments to forecast the movements of a key variable as discrete values using a discrete probability mass distribution that can be “drawn” on a virtual canvas using the mouse. The module I wrote is general enough that it can be included in other economic experiments.
Population Dynamics of Microbial Communities in Mesotidal Estuarine Sediment of Iko River, Eastern Obolo, Akwa Ibom State, Nigeria

The population dynamics of microbial communities in mesotidal estuarine sediment of Iko River Estuary, Nigeria were investigated using standard microbiological and analytical procedures. The results revealed that the abundance of culturable microbes in the estuary varied between both tides as well as with the different microhabitats. Tidal influence had little or no impact on the heterotrophic and pollution indicator bacterial communities of the estuarine sediment but its influence on the activities of autotrophic bacterial communities was remarkable. The study revealed that 22.64% and 22.28% abundance rates of total heterotrophic bacteria were obtained during the high and low tides respectively. The abundance rates of 5.03% and 17.53% recorded for nitrogen-fixing bacteria and sulphate reducing bacteria respectively during high tide were higher than 4.07% and 10.93% obtained during low tide. Bioaerosols concentrations were found to be higher during high tide than low tide. Geographic Information System (GIS) models of microbial communities revealed marked variation which ranged between tidal influences and locations. The Original Research Article Umana and Udosen; ACRI, 14(2): 1-17, 2018; Article no.ACRI. 37646 2 model revealed high concentrations of microorganisms in the north-west zone during both tides, while fungi were highly concentrated in the north-east zone during high tide. High species richness was observed, but with little or no tidal influences and isolates included known pathogenic species. The total organic carbon content of the sediments during both tides were higher than an optimum value of 1.3%, with a high linear correlation (r = 0.777) between heterotrophic bacteria load and organic content level of the sediment during low tide indicating a relatively high content of organic matter in the sediments can increase the bacterial load. The study therefore calls for effective environmental monitoring.
The Influence Of Mother’s Perception and Attitude Toward Fish Purchasing Behavior in Pekalongan Families

Purchase behavior is influenced by several factors such as perception and attitude. This study aims to analyze the influence of perceptions and attitudes on fish purchasing behavior in rural and urban areas. This research use cross sectional study design. This research was conducted in Pekalongan. Kandang Panjang Village, Pekalongan City as urban area and Duwet Village, Pekalongan Regency as rural area. The sample in this study was 100 mothers. Data were analyzed using descriptive test, different test Independent sample T-test, Pearson correlation test, and multiple linear regression test. Perception and mother’s attitude in urban were higher than in rural. Beside that, there were differences on fish expenditure, expenditure of fish in urban was higher than in rural. Regression test showed perception, location, and maternal age have a significant effect on fish purchasing behavior.
‘Strength becomes her’ – resistance training as a route to positive body image in women

ABSTRACT Physical activity has been shown to be an ideal intervention for body image and wellbeing, but very little research has focused on the role of resistance training in women, and more specifically, its role in supporting positive body image. The aim of this study was to identify the role of resistance training to positive body image in women, aged 30–55 as an under-represented demographic in this field. A qualitative approach was used and data included semi-structured interviews with 12 women from UK, USA, and New Zealand, analysed in accordance with constructivist grounded theory. The findings proposed a model of how resistance training works to foster self-efficacy and develop positive body image and psychological wellbeing. Themes that emerged included: Social and Environmental Factors, Characteristics of Resistance Training, Consequences of Resistance Training and Wellbeing Benefits. Ultimately, this research creates a springboard for future positive body image research to refine and develop ways to encourage and support more women to experience the benefits resistance training can bring.
Editorial: the Salamanca Statement: 25 years on

ABSTRACT June 2019 saw the 25th anniversary of the World Conference on Special Needs Education, which was co-organized by UNESCO and the Ministry of Education and Science of Spain, and held in the city of Salamanca. It led to the Salamanca Statement and Framework for Action on Special Needs Education, arguably the most significant international document that has ever appeared in the field of special education. In so doing, it endorsed the idea of inclusive education, which was to become a major influence in subsequent years. The articles in this special issue illustrate the ways in which the Salamanca Statement has and still is influencing the development of policies and practices across the world. In this editorial, we provide readers with some relevant background to these developments.
The relationship between professional autonomy and moral distress in ICU nurses of Guilan University of Medical Sciences in 2017

Background & Aim: Professional autonomy is a key component of decision-making and empowerment of the nurses. However, ICU nurses sometimes experience a degree of moral distress in their decision-making but the relationship of this distress with their autonomous performance in intensive care units is unclear. The aim of this study is determining the relationship between professional autonomy and moral distress of ICU nurses. Methods & Materials: In this correlational cross-sectional study, 180 ICU nurses were selected by census method from educational hospitals of Guilan University of Medical Sciences in 2017. Research tools were Varjuss professional autonomy and Corely et al. moral distress questionnaires. Data were analyzed using SPSS software version 16. Results: Most of the subjects were female (93.89%), full-time nurses (61.67%), with age mean and standard deviation of 35±5.97. Mean and standard deviation of professional autonomy and moral distress were 77.04±4 and 140.85±5.45, respectively. Moral distress of most nurses (55.6%) was moderate. There was a positive and significant correlation between professional autonomy and moral distress scores (p<0.001, r=0.33). Conclusion: This study showed that by increasing the professional autonomy, the moral distress of ICU nurses increases as well. These results, by informing nursing mangers, remind the necessity of using some approaches for reducing the moral distress of nurses along with improving their professional autonomy.
New Generation Model of Word Vector Representation Based on CBOW or Skip-Gram

: Word vector representation is widely used in natural language processing tasks. Most word vectors are generated based on probability model, its bag-of-words features have two major weaknesses: they lose the ordering of the words and they also ignore semantics of the words. Recently, neural-network language models CBOW and Skip-Gram are developed as continuous-space language models for words representation in high dimensional real-valued vectors. These vector representations have recently demonstrated promising results in various NLP tasks because of their superiority in capturing syntactic and contextual regularities in language. In this paper, we propose a new strategy based on optimization in contiguous subset of documents and regression method in combination of vectors, two of new models CBOW-OR and SkipGram-OR for word vector learning are established. Experimental results show that for some words-pair, the cosine distance obtained by the CBOW-OR (or SkipGram-OR) model is generally larger and is more reasonable than CBOW (or Skip-Gram), the vector space for Skip-Gram and SkipGram-OR keep the same structure property in Euclidean distance, and the model SkipGram-OR keeps higher performance for retrieval the relative words-pair as a whole. Both CBOW-OR and SkipGram-OR model are inherent parallel models and can be expected to apply in large-scale information processing.
Factors influencing Malaysian ESL learners’ engagement in academic writing (in L2)

This paper examines Malaysian learners’ engagement in academic writing (AW) in a second language (L2) in a higher learning institution. A quantitative means of exploring students’ engagement was incorporated as a starting point to capture a broad cross-sectional snapshot of Malaysian learners’ engagement in academic writing and identify pertinent issues of the target population. The quantitative analysis revealed that the majority of the students were highly engaged and that they responded differently in the engagement domains (e.g., high behavioural engagement and low cognitive engagement). The subsequent exploration in the qualitative phase affirmed that the socio-historical aspects of the Malaysian context (e.g., position of English, identity conflicts, and emphasis on education) were also pertinent factors influencing student engagement in the AW class. While a psychological perspective has helped elucidate how engagement dimensions interacted in the learning process, the broader sociocultural aspects helped provide further insights into the role of contextual influences on student engagement in the AW class, and how these were driven by, and also drive motivation towards academic literacy and legitimacy.
Identification of Financial Sector Optimal Depth and Structure from the Perspective of Economic Growth, Macroeconomic and Financial Stability

This paper attempts to estimate financial sector development targets which, other things being equal, provide for the best possible GDP performance while ensuring its growth sustainability along with price and financial stability. To address this task, the hypothesis of nonlinear relationship between GDP dynamics, its volatility, inflation, the frequency of financial crises, on the one hand and the development of key financial sector segments was tested. The study used a standard technique of panel data regression analysis, on the other hand employed in studies examining similar issues and a sample of 63 emerging and advanced economies covering 1980 – 2014.
Potential Competition and Quality Disclosure

This study presents a model of quality disclosure in which an incumbent, through its quality and disclosure choices, influences the potential that a new entrant enters the market. In this regard, we consider a sequential framework in which the incumbent chooses its quality and decides whether to disclose it to the market; subsequently, the entrant makes the same decisions, if it enters the market. We show that the potential competition can create strategic incentives for the incumbent to choose nondisclosure, because the availability of information about the incumbent's quality promotes entry by enhancing the entrant's expected profit from the market. In addition, an analysis of the effects of mandatory disclosure laws suggests that they can be effective in encouraging new market entrants and in improving the product quality of established firms.
Modular Structure of Complex Networks

Complex networks represent the relationships or interactions between entities in a complex system, such as biological interactions between proteins and genes, hyperlinks between web pages, co-authorships between research scholars. Although drawn from a wide range of domains, realworld networks exhibit similar structural properties and evolution patterns. A fundamental property of these networks is their tendency to organize according to an underlying modular structure, commonly referred to as clustering or community structure. This thesis focuses on comparing, quantifying, modeling, and utilizing this common structure in real-world networks. First, it presents generalizations of well-established traditional clustering criteria and propose proper adaptations to make them applicable in the context of networks. This includes generalizations and extensions of 1) the well-known clustering validity criteria that quantify the goodness of a single clustering; and 2) clustering agreement measures that compare two clusterings of the same dataset. The former introduces a new set of measures for quantifying the goodness of a candid community structure, while the latter establishes a new family of clustering distances suitable for comparing two possible community structures of a given network. These adapted measures are useful in both de ning and evaluating the communities in networks. Second, it discusses generative network models and introduces an intuitive and exible model for synthesizing modular networks that closely comply with the characteristics observed for realworld networks. This network synthesizer is particularly useful for generating benchmark datasets with built-in modular structure, which are used in evaluation of community detection algorithms. Lastly, it investigates how the modular structure of networks can be utilized in di erent contexts. In particular, it focuses on an e-learning case study, where the network modules can e ectively outline the collaboration groups of students, as well as the topics of their discussions; which is used to monitor the participation trends of students throughout an online course. Then, it examines the interplay between the attributes of nodes and their memberships in modules, and present how this interplay can be leveraged for predicting (missing) attribute values; where alternative modular structures are derived, each in better alignment with a given attribute.
The Effect of Shape Familiarity on Object-Based Attention

: Humans can pay attention both to particular locations in space (“space-based attention”) and to specific objects (“object-based attention”). The goal of this study was to understand the role of object familiarity and complexity in the control of object-based attention. We used a well-known manifestation of object-based attention known as same-object advantage (SOA) to test this. In SOA, participants are faster at detecting a target event that takes place in a cued object than one that takes place in an uncued object, even when the distance between cue and target is kept fixed. To control shape familiarity, objects in the current study were randomly-generated irregular polygons known as Attneave shapes. Experiment 1 showed that SOA exists for these irregular shapes, even when participants are unfamiliar with them. In Experiment 2, participants first underwent training designed to familiarize them with a subset of the Attneave shapes used in Experiment 1. Again there was a significant SOA. If object-based attention is dependent upon object familiarity, we hypothesized that SOA, measured in terms of reaction time, should be greater in Experiment 2 than Experiment 1. Although there was a numerical increase in the reaction time signature of SOA in Experiment 2, this effect was not significant. While this does not strictly support our hypothesis, several aspects of this study suggest that object familiarity does play some role in mediating object-based attention.
The Epistemology of Measurement: A Model-based Account

Contrary to the claim that measurement standards are absolutely accurate by definition, I argue that unit definitions do not completely fix the referents of unit terms. Instead, idealized models play a crucial semantic role in coordinating the theoretical definition of a unit with its multiple concrete realizations. The accuracy of realizations is evaluated by comparing them to each other in light of their respective models. The epistemic credentials of this method are examined and illustrated through an analysis of the contemporary standardization of time. I distinguish among five senses of ‘measurement accuracy’ and clarify how idealizations enable the assessment of accuracy in each sense.
Einflussfaktoren des Stoffwechsels auf die Entstehung der Trächtigkeitstoxämie des Schafes

Disturbances of glucose metabolism similar to type II diabetes are often accompanied by low extra cellular calcium concentrations, as shown in periparturient ruminants. Hypocalcemia reduces insulin secretion and possibly endogenous glucose production, but whether hypocalcemia also affects peripheral actions of insulin is not clear. The problem was investigated with piglets in this study. Insulinmediated turnover of glucose and the clearance of insulin were measured in 7 control piglets (+D) and in 10 piglets with inherited calcitriol deficiency (-D). The measurements involved continuous intravenous infusions of insulin (1, 2, 5, 7.5 and 10 mU·kg-1·min-1) and glucose to maintain a glucose concentration of 7 mmol·l-1 (combined insulin and glucose clamps). Both groups of piglets were studied under normoand hypocalcemic conditions. During hypocalcemia and with equal insulin infusion rates, -D and +D piglets attained significantly higher (28%–133%) steady state insulin concentrations in plasma than during normocalcemia. This showed that the clearance rates of insulin during hypocalcemia were 48% lower in +D and 20% lower in -D piglets than during normocalcemia. With equivalent insulin infusion rates +D piglets developed significantly higher (15%–48%) steady state insulin concentrations in plasma than -D piglets, indicating that the clearance rate of insulin was higher in the calcitriol-deficient state. The relationship between insulin concentration in plasma and glucose turnover (measured with [3-3H]glucose) was not influenced by the calcemic and vitamin D status of the piglets. This indicated that the peripheral action of insulin on glucose metabolism was not influenced by the extracellular calcium concentration and vitamin D status.
Deep Generative Models for Semi-Supervised Machine Learning

Deep generative models parameterized by neural networks have recently achieved state-ofthe-art performance in unsupervised and semisupervised learning. We extend deep generative models with auxiliary variables which improves the variational approximation. The auxiliary variables leave the generative model unchanged but make the variational distribution more expressive. Inspired by the structure of the auxiliary variable we also propose a model with two stochastic layers and skip connections. Our findings suggest that more expressive and properly specified deep generative models converge faster with better results. We show state-of-theart performance within semi-supervised learning on MNIST, SVHN and NORB datasets.
Design and Use of a Systematic Site Visit Protocol: Implications for Novice Evaluators and Mentors

Site visits are frequently used by evaluators to gain first-hand experience and knowledge about program implementation. However, few peer-reviewed articles describe the procedures used for designing and conducting site visits. This article describes the process of constructing and using a systematic site visit protocol. Theories and concepts of evaluation, including the measurement of fidelity and quality and the importance of context to site-level implementation, guided the construction of this protocol. Using a systematic method for program inquiry can improve the consistency of qualitative observations of program activities by enhancing intentionality, transparency, and emergence within the site visit process. The method presented may be especially helpful to novice evaluators and their mentors in learning about and teaching the process of conducting site visits.