Miracle-dz/UniFAR-FTUs huggingface dataset:
The Value of Auditor Industry Specialization - Evidence from a Structural Model

This study investigates the value of auditor industry specialization. In the first step, we use a discrete choice model to derive the first-order demand for auditor industry specialization. Our results reveal that clients have a general preference for auditor industry specialization, relating to both audit firm and audit office specialization. Further, we observe that specializations at the audit firm and audit office are substitutes. We also find that larger and more complex clients have a stronger demand for specialization at the audit office but not the audit firm level. In the second step, we use the results from the discrete choice model to quantify the value of auditor industry specialist for clients. We find that the aggregate value of industry specialization for all clients is around 5 million US dollars and that it shapes the audit market as losing it results in the loss of approximately 5% of clients.
Soft Origami: Classification, Constraint, and Actuation of Highly Compliant Origami Structures

Herein we discuss the folding of highly compliant origami structures — “Soft Origami. ” There are benefits to be had in folding compliant sheets (which cannot self-guide their motion) rather than conventional rigid origami. Example applications include scaffolds for artificial tissue generation and foldable substrates for flexible electronic assemblies. Highly compliant origami has not been contemplated by existing theory, which treats origami structures largely as rigid or semi-rigid mechanisms with compliant hinges — “Mechanism-Reliant Origami. ” We present a quantitative metric — the Origami Compliance Metric — that aids in identifying proper modeling of a homogeneous origami structure based upon the compliance regime it falls into (Soft, Hybrid, or Mechanism-Reliant). We discuss the unique properties, applications, and design drivers for practical implementation of Soft Origami. We detail a theory of proper constraint by which an ideal soft structure’s number of degrees of freedom may be approximated as 3n, where n is the number of vertices of the fold pattern. Finally, we introduce a concept for a scalable process in which a few actuators and stretching membranes may be used to simultaneously fold many origami sub-structures that share common degrees of freedom.Copyright © 2015 by ASME
Emotional Intelligence and Leadership in Higher Education Institutions: An Empirical Approach

University Top Management are increasingly expected to be strategic and innovative in their work, whether that be increasing student success, improving teaching and learning, growing enrollments, advancing research efforts, serving the community, and more. Meeting these expectations requires leaders to work with a broad range of students, faculty, staff, and various external constituencies. At the same time, they must navigate fast paced environments, demanding schedules, increasing accountability expectations, declining or stagnated resources, and frustrating bureaucratic hurdles. These challenges can often lead to a range of emotions for the University Top Management and their teams that can include everything from feelings of frustration and disempowerment, to surprise and elation. Leaders across organizational types are coming to understand that working in an emotion-filled context requires a special set of skills, and have recognized the importance of Emotional Intelligence (EI) for leading people. Since universities are primarily people focused organizations, academic leaders can benefit from having an understanding of their own EI and how to use it within their leadership roles. EI is the ability to actively regulate your emotions and the emotions of those around you through self-awareness, self-regulation, motivation, empathy, and social skills. Through our educational preparation, most academics are typically taught to downplay emotions so that they do not interfere with research or teaching. However, being disconnected or unaware of our own emotions and the emotions of others can be problematic when moving into a leadership role and having to work regularly with others on administrative tasks. (There is also increasing recognition that emotional intelligence has a role in teaching and research as well). This paper intends to present an empirical study that will seek to identify the relevance of emotional intelligence for effective higher education academic leadership. This paper analyzes EI and Leadership in HEIs which can be used as a basis for future research while providing a knowledge base for contemporary training of EI in HEIs.
Hybrid Membranes of Polyamide Applied in Treatment of Waste Water

In this work, it was prepared hybrid membranes of polyamide6 (PA6) with montmorillonite (MMT) and porogenic agent (CaCl2). The hybrid membranes with CaCl2 were characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), porosimetry by mercury intrusion (PMI), flux measurements and rejection. By means of X-ray diffraction, it was revealed that the hybrid membranes with CaCl2 have an exfoliated and/or partially exfoliated structure. For FTIR and DSC of hybrid membranes with CaCl2, it was found that the spectra and the crystalline melting temperature remained virtually unchanged compared to PA6 membrane. From the SEM images, it was observed that the addition of the MMT and the CaCl2 in the membrane of PA6 caused an increase in the amount of pores the surface and cross section of these membranes. By PMI, it was observed that the presence of MMT and CaCl2 in the membrane caused an increase in the average diameters of pores. The water-oil separation tests, indicated a significant reduction of oil in the permeate, allowing treatment of wastewater contaminated with oil.
Scarcity, Risk Premiums, and the Pricingof Commodity Futures: The Case of Crude Oil Contracts

In this article, risk premiums of commodity futures are directly related to the physical scarcity of commodities. For this purpose the authors propose a simple decomposition of spot prices into a pure asset price plus a scarcity related price component. This replaces the traditional convenience yield that results from an imperfect no-arbitrage relationship of the term structure of commodity futures prices. The empirical tests confirm that two separate commodity-specific risk premiums affect the pricing of crude oil futures contracts: a net hedging pressure premium and a scarcity premium. The two premiums show different cyclical characteristics. The authors also find that asset market risk factors such as exchange rates or stock market shocks affect the term structure of oil futures prices in a much more homogeneous way than commodity-specific hedging pressure or scarcity shocks do.
Egocentric rich images detection in a serious game for Alzheimer’s patients

Alzheimer’s is a progressive neurodegenerative disease, right now irreversible and related with ageing. It is caused by neuronal deterioration which leads to memory loss, intellectual impairment and personality disorders and behavior. Several international reports warn that Alzheimer’s is the most common form of dementia, affecting between 60% and 70% of the total number of cases. In addition, it has been estimated that at least 5% of the world’s population with more than 60 years old will suffer the disease at some point in their life. Despite the social and economic impact of the disease, there is still no treatment that can cure dementia or prevent its evolution. It is for this reason that efforts to find solutions that diminish the progressive development of the disease have been growing increasingly, building a society aware of these problems. The World Health Organization recognized dementia as a public priority in the report: "Dementia: a public health priority"[27]. The TV program L.La Marató de TV3"decided to dedicate the show of the year 2013 to the neurodegenerative diseases. Granted by it, this work has been aimed at reinforcing the inclusion of the new technologies in areas related with health to promote the improvement of Alzheimer’s patients. The framework developed in this project consists on the incorporation of a wearable camera that automatically takes pictures of the day of the patient. Subsequently, a selection is made, through the detection of objects in the images and a classification using Machine Learning algorithms, of those photographs which can bring value to the cognitive reinforcement of the patient. A serious game based on this pictures has been built to enhance this behavior.
Spectrum Combining Technique at Low SNR for the Frequency Selective Channels

To decrease the Inter-Symbol Interference (ISI) for the frequency selective channel at low SNR, a spectrum combining technique based on average phase from the multiple sensors without synchronization is proposed. The combining signal’s phase will converge to the average phase instead of the value of the fixed branch to meliorate adverse effect on the demodulation performance caused by the single nonlinear phase characteristic. Finally the simulations show that the spectrum combining technique can achieve a substantial performance improvement without the symbol timing synchronization. Therefore it could be regarded as a useful combining technique in the frequency selective channels at low SNR, especially when synchronization is difficult to achieve. Keywords-frequency selective channel; spectrum combining; multiple sensors; spatial diversity; Average Phase
Self-standing chitosan films as dielectrics in organic thin-film transistors

Organic thin film transistors, using self-standing 50 ! m thick chitosan films as dielectric, are fabricated using sublimed pentacene or two conjugated polymers deposited by spin coating as semiconductors. Field-effect mobilities are found to be similar to values obtained with other dielectrics and, in the case of pentacene, a value (0.13 cm 2 /(V·s) compara- ble to high performing transistors was determined. In spite of the low On/Off ratios (a maximum value of 600 was obtained for the pentacene-based transistors), these are promising results for the area of sustainable organic electronics in general and for biocompatible electronics in particular.
Perfil da mortalidade neonatal no Rio Grande do Norte (2008-2017)

Objetivo: caracterizar a mortalidade neonatal precoce e tardia no estado do Rio Grande do Norte de 2008 a 2017. Metodologia: estudo epidemiológico descritivo, temporal de abordagem quantitativa retrospectiva, comdados do Departamento de Informática do Sistema Único de Saúde (DATASUS) sobre os óbitos neonatais ocorridos entre janeiro de 2008 e dezembro de 2017 no estado do Rio Grande do Norte por local de moradia. Resultados: a amostra foi composta de um total de 4.531 óbitos, sendo mais prevalente óbito neonatal precoce (79,65 %), sexo masculino (54,71 %), gestação inferior a 27 semanas (34,05 %), parto do tipo vaginal (49,93 %), recém-nascidos com peso menor que 2.500 g (68,57 %) e mães com escolaridade entre 8 e 11 anos de estudo. Entre 2008, ano inicial de coleta, e 2017, ano final, a mortalida-de neonatal apresentou redução de 23,83 %. A mortalidade masculina se apresentou maior que a feminina em todos os anos, com variação entre 0,09 e 0,08 respectivamente. O teste de qui-quadrado de independência mostrou que existe associação entre o tipo de parto e a mortalidade neonatal p < 0,001. Conclusão: os dados da pesquisa evidenciam a redução da mortalidade neonatal no estado, ao mesmo tempo que aponta para a necessidade do fortalecimento de ações no período gestacional a fim de evitar condições favoráveis à mortalidade infantil, como a prematuridade e a desnutrição. Outro dado comprovado refere-se ao preenchimento das declarações de nascido vivo e óbito, visto que muitas variáveis apresentaram o item “ignorado” referente ao preenchimento incorreto ou não preenchimento da informação.
DICE @ TREC-IS 2018: Combining Knowledge Graphs and Deep Learning to Identify Crisis-Relevant Tweets

In this paper, we describe our submissions to the TREC Incident Stream (TREC-IS) challenge 2018. We investigated di ﬀ erent machine learning approaches to classify crisis-related tweets into di ﬀ erent information types. We incorporated knowledge graphs as features into this social media analysis, in addition to bag of words, word embeddings, time data, and event-types. Further, we evaluate state-of-the-art classiﬁcation models on 31 generated features sets. Our TREC-IS re-sults indicate that a model based on combining knowledge graphs (i.e., Babelfy), word embeddings and textual features outperformes classical machine learning models.
Towards More Practical Stochastic Gradient MCMC in Differential Privacy

Concerns related to data security and confidentiality have been raised when applying machine learning to real-world applications. Differential privacy provides a principled and rigorous privacy guarantee for machine learning models. While it is common to inject noise to design a model satisfying a required differential-privacy property, it is generally hard to balance the trade-off between privacy and utility. We show that stochastic gradient Markov chain Monte Carlo (SG-MCMC) – a class of scalable Bayesian posterior sampling algorithms – satisfies strong differential privacy, when carefully chosen stepsizes are employed. We develop theory on the performance of the proposed differentially-private SG-MCMC method. We conduct experiments to support our analysis, and show that a standard SG-MCMC sampler with minor modification can reach state-of-the-art performance in terms of both privacy and utility on Bayesian learning.
PROTOTYPE IMPLEMENTATION OF AN RFID READER SYSTEM İ

In this study, a prototype RF-ID reader system working at 125 KHz frequency was designed and succesfully implemented. Fundemantals of designing a reader systems has also been addressed. For the Radio Frequency interface, EM4095 (Marine Electronics product) has been choosen. In the software side, the reader MCU was programmed using C Programming Language. It is believed that this study will give a systematic approach to design an RF-ID technology based reader device.
A note on tensile instabilities and loss of ellipticity for a fiber-reinforced nonlinearly elastic solid

In this paper we examine the loss of ellipticity and the associated failure of fiber-reinforced compressible nonlinearly elastic solids under deformations leading to fiber extension. In particular, the analysis concerns a material model that consists of an isotropic base material augmented by a reinforcement depending on the fiber direction and referred to as a reinforcing model. We examine a reinforcement that introduces additional stiffness under simple shear deformations in the fiber direction. In previous contributions it was shown for this material that loss of ellipticity under uniaxial tensile loading in the fiber direction requires a non-convex reinforcing model. Here we generalize this result and show that loss of ellipticity under plane deformations not associated with uniaxial loading in the fiber direction but also creating fiber extension may occur for convex reinforcing models.
Optimal design of a flexure hinge-based XYZ atomic force microscopy scanner for minimizing Abbe errors

To establish of standard technique of nanolength measurement in a two-dimensional plane, a new (AFM) system has been designed. In this system, measurement uncertainty is dominantly affected by the Abbe error of the XYZ scanning stage. No linear stage is perfectly straight; in other words, every scanning stage is subject to tilting, pitch, and yaw motion. In this article, an AFM system with minimum offset of XYZ sensing is designed. And, the XYZ scanning stage is designed to minimize the rotation angle because Abbe errors occur through the multiply of offset and rotation angle. For XY stage, optimal design is performed to minimize the rotation angle by maximizing the stiffness ratio of motion direction to the parasitic motion direction of each stage. For the Z stage, the optimal design of maximizing the first-resonant frequency is performed. When the resonant frequency increases, the scan speed is improved, thereby reducing errors caused by sensor drift. This article describes the procedures of selecting p.
EUROPEAN ECONOMY Measuring the Uncertainty in Predicting Public Revenue

This paper provides an assessment of the uncertainty surrounding revenue predictions, through an ex post analysis of European Commission’s forecasts over the last 15 years. It estimates the forecast errors affecting revenue for all 28 Member States, using the different vintages of the autumn and spring Commission forecasts. It analyses both the direction and magnitude of errors, using standard summary statistics. The paper looks into the various components of forecast errors to better understand their drivers (forecasting error related to real GDP, inflation or revenue-to-GDP ratio) and which types of revenues (direct tax, indirect tax or social security contributions) are particularly affected. The paper also examines the pattern of revenue errors over time and in particular how revenue forecasts perform before, during and after the crisis. To further deepen the analysis, a set of tests are carried out on the quality of the prediction (serial correlation, unbiasedness, weak and informational efficiency). The estimator-based tests confirm the sound track record of the European Commission’s forecasts. This is also shown by a comparison with the OECD’s revenue forecasts. Lastly, the paper reviews various possible determinants of forecast errors and examines their significance by means of a pooled time series technique. The econometric study allows for the identification of factors which increase or reduce the risk of over-forecasting revenue. JEL Classification: C1, E60, E66.
Understanding the Relationship between Human Resource Practices and Innovative Work Behavior : Role of Perceived Organizational Support

The main aim of this study is to determine human resource practices for fostering innovative work behavior, to understand the theoretical reasons and to discover the process in the relationship between human resource practices and innovative work behavior. Building on organizational support theory, it is hypothesized that employees will show greater innovative work behavior if they perceive organizational support and the presence of growth opportunities. Analyzing data from a sample of 254 professionals in Turkey, the results indicated that growth opportunities had a positive significant impact on innovative work behavior and perceive organizational support mediated the relationship.
Early-Age Cracking in Concrete: Causes, Consequences, Remedial Measures, and Recommendations

Cracking is a common problem in concrete structures in real-life service conditions. In fact, crack-free concrete structures are very rare to find in real world. Concrete can undergo early-age cracking depending on the mix composition, exposure environment, hydration rate, and curing conditions. Understanding the causes and consequences of cracking thoroughly is essential for selecting proper measures to resolve the early-age cracking problem in concrete. This paper will help to identify the major causes and consequences of the early-age cracking in concrete. Also, this paper will be useful to adopt effective remedial measures for reducing or eliminating the early-age cracking problem in concrete. Different types of early-age crack, the factors affecting the initiation and growth of early-age cracks, the causes of early-age cracking, and the modeling of early-age cracking are discussed in this paper. A number of examples for various early-age cracking problems of concrete found in different structural elements are also shown. Above all, some recommendations are given for minimizing the early-age cracking in concrete. It is hoped that the information conveyed in this paper will be beneficial to improve the service life of concrete structures. Concrete researchers and practitioners may benefit from the contents of this paper.
Costs and benefits of livestock systems and the role of market and nonmarket relationships

In developing countries livestock are kept not only for their physical products, but also for insurance, financing, and to display status. Though this range of purposes is acknowledged, livestock policies nevertheless often emphasize physical production: a limited perspective that hampers the formulation and implementation of effective livestock policies. This article presents a comprehensive appraisal of costs and benefits of livestock systems that takes into account the institutional environment of livestock keepers. Indicators are developed that capture, quantify, and organize not only the benefits resulting from the physical production, but also those from the intangible functions. The method is illustrated by an analysis of cattle in the Western Province of Zambia. The results indicate that the perspective on livestock systems developed more closely reflects the observed decisions of the livestock keepers. Copyright 2005 International Association of Agricultural Economics.
Regret-Based Algorithms for Multi-Armed Bandits

Multi-armed bandits (MABs) are the single step analogs of the full reinforcement learning problem. They are simple but powerful models for studying the exploration/exploitation dilemma in the context of making sequential decisions over time and under uncertainty. There are several notions of optimality in the literature: asymptotic optimality, regret optimality, and PAC optimality. In this work, we examine the multi-armed bandit problem (which is sometimes called the sequential allocation problem) within the context of regret optimality. We cover several groundbreaking algorithms that approach MABs through the frequentist and Bayesian perspective. UCB1 was one of the first algorithms to achieve a logarithmic regret bound and sparked a new field of literature for upper confidence bound based algorithms. UCBV was one of the first works to improve the regret bound for UCB1 but is still not “optimal”. We later introduce KL-UCB, Thompson Sampling, and Bayes UCB, which are all able to achieve regret optimality asymptotically (in the Bernoulli reward setting). We then perform experiments to illustrate their robustness and how well these algorithms perform under different reward distributions and slight perturbations to their respective assumptions.
Anti-Inflammatory Effects of Adrenomedullin on Acute Lung Injury Induced by Carrageenan inMice

1 Department of Pharmacology, School of Pharmacy, University of Seville, 41012 Seville, Spain 2 Department of Clinical and Experimental Medicine and Pharmacology, School of Medicine, University of Messina, Torre Biologica, Policlinico Universitario, Via C. Valeria, Gazzi, 98100 Messina, Italy 3 IRCCS Centro Neurolesi “Bonino-Pulejo”, S.S. 113 Via Palermo, CTR Casazza, 98100 Messina, Italy 4 University of Manchester, Manchester M13 9PL, UK