Miracle-dz/UniFAR-FTUs huggingface dataset:
Plebiscitary leader democracy in theory and practice: Looking at populism through Weberian lenses

The Brexit vote in Great Britain and Donald Trump’s electoral victory in the US presidential elections in 2016 brought a shocking experience for the adherents of liberal democracy. The dramatic political events of 2016 are, however, not without antecedents. The emergence of populism is not a new phenomenon: Cass Mudde (2004) heralded it as a ‘Zeitgeist’ in his 2004 article. Populism and populist leadership first emerged in Latin America, then in East and Central Europe and in Western democracies in the last two decades. Radical and populist parties, movements and politicians have shifted from marginality to mainstream in Austria (Jörg Haider, Norbert Hofer and the Freedom Party), Italy (Silvio Berlusconi, Beppe Grillo), Greece (Syriza), Spain (Podemos), France (Marine Le Pen) and in the Netherlands (Geert Wilders). 1 The concern about the deconsolidation of liberal democracy has characterized the literature dealing with new democracies in East and Central Europe and Latin America. As the vivid public discussion has shown, this concern is now extended to the core states of the Western World (Fukuyama 2016; Foa and Mounk 2016; 2017).
Stable sample delivery in viscous media via a capillary for serial crystallography

Serial crystallography (SX) is an innovative technology in structural biology that enables the visualization of the molecular dynamics of macromolecules at room temperature. SX experiments always require a considerable amount of effort to deliver a crystal sample to the X-ray interaction point continuously and reliably. Here, a sample-delivery method using a capillary and a delivery medium is introduced. The crystals embedded in the delivery medium can pass through the capillary tube, which is aligned with the X-ray beam, at very low flow rates without requiring elaborate delivery techniques, drastically reducing sample consumption. In serial millisecond crystallography using a viscous medium via a capillary, crystals of lysozyme embedded in agarose, which produce an unstable injection stream at atmospheric pressure, and crystals of glucose isomerase embedded in gelatin, which is known to be problematic for open-extruder operation, were stably delivered at a flow rate of 100 nl min−1. The room-temperature crystal structures of lysozyme and glucose isomerase were successfully determined at 1.85 and 1.70 A resolutions, respectively. This simple but highly efficient sample-delivery method can allow researchers to deliver crystals precisely to an X-ray beam in SX experiments.
Why banks fail? The case of the Gambia commercial and development bank

Tel. : +220 9911775 / 3911775 Bank failures are not uncommon, nor limited to developed or developing economies or a particular geographical region. The cost of bank failure can be high, and if this causes instability in the financial system, the effects can be adverse on the country’s growth rate and considerable bailout cost to governments and central banks. Bank failures can be attributable to both internal and external pressures. In this paper, quantitative Multivariate Discriminant Analysis Z-Score and qualitative A-Score were adopted to examine bank failure and in particular, to evaluate why The Gambia Commercial and Development Bank (GCDB) failed. The findings show that GCDB failed due to poor financial performance and weak management systems. The external factors of judicial ineffectiveness, political hijacking and severe macro-economic conditions played a considerable part in GCDB’s failure.
Global Information Assurance Certification Paper

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Running Head: AUTOMATIC THEORY OF MIND 1 Automatic Theory of Mind: Covert Detection via Brain Activity

The present research examined whether people automatically compute others' mental states and predict their actions. We leveraged the event-related brain potential (ERP) P300 component as a covert measure of automatic processing. Participants observed characters' actions in false-belief scenarios (Experiment 1) and in true-belief scenarios (Experiment 2). Participants' task was to identify when characters were at a particular spatial location; for the task, it was unnecessary to consider their mental states, and there were never any overt or implied instructions to do so. On a small proportion of the trials, the characters' movement was inconsistent with their beliefs— and only if one automatically computes the characters' mental states and predict their actions, would one process belief-violating trials as distinct from belief-consistent trials. Indeed, in Experiments 1 and 2, the belief-violating trials elicited a frontal P300 for both falseand truebelief scenarios, which suggests that participants engaged in automatic theory of mind even though they were actively engaged in another task.
CLASSICAL AND CORRELATIVE ANALYTICAL METHODS FOR ORIGIN IDENTIFICATION OF HUNGARIAN HONEYS Short running title: Detection of authenticity of honey

IDENTIFICATION OF HUNGARIAN HONEYS Short running title: Detection of authenticity of honey ZS. BODOR, CS. BENEDEK, T. KASZAB, JL. ZINIA ZAUKUU, I. KERTÉSZ, and Z. KOVACS Department of Physics and Control, Faculty of Food Science, Szent István University, Somlói street 14-16, Hungary Department of Dietetics and Nutrition, Faculty of Health Sciences, Semmelweis University, Vas Street 17, 1088 Budapest, Hungary
Stellar Metamorphosis as Alternative to Nebular Hypothesis The Non-Existence of Stellar Mass Accretion Ockham’s Razor Definition for Planetary System and Star System What a New Solar System Looks Like The Definition of Eclipsing Binary Stars and Confusion of Kepler Telescope

Observations were made that falsify planetary formation via proto-planetary disk. An alternative model is proposed. Observations that Falsify the Proto-planetary Disk/Nebular Hypothesis Model: 1. Older stars are still mislabeled by mainstream as planets/exo-planets. [1] They orbit the opposite direction their host star is rotating. [2] The backwards orbits completely falsifies any notion of a coherent one direction disk forming Earth sized objects. An illustration is provided below of these backwards orbits.
A Novel Hierarchical Hybrid Model for Short-Term Bus Passenger Flow Forecasting

For the increasing travel demands and public transport problems, dynamically adjusting timetable or bus scheduling is necessary based on accurate real-time passenger flow forecasting. In order to get more accurate passenger flow in future, this paper proposes a novel hierarchical hybrid model based on time series model, deep belief networks (DBNs), and improved incremental extreme learning machine (Im-ELM) to forecast short-term passenger flow. The proposed model is named HTSDBNE with two modelling steps. First, referring the idea of parallelization, the hybrid model, constructed by time series model, DBN, and Im-ELM, is used to forecast short-term passenger flow in different time scales hierarchically and parallel. Second, Im-ELM is utilized to analyse the relationship of forecasting results from the first step, and the weighted outputs of Im-ELM are as the final forecasting results. Comparing with single forecasting models and typical hybrid forecasting models, the testing results indicate that HTSDBNE has better performances. The mean absolute percent error of prediction results is around 10% and fully meets the application requirements of bus operation enterprise.
An Overview of The Methodology of Visitor Studies

Reliability The term "reliability" refers to the consistency or stability of measurements. If two observers are observing the same visitor, we expect the same measurements to be reported by both observers (referred to as "interobserver reliability"). Reliable measurement depends upon two things. First, it requires objectivity (not allowing personal feelings or expectations to influence the measures). If behaviors to be measured are precisely defined, there should be less room for subjective measurement. Reliable measurement also depends upon standardization. Each person using the measuring system should use it in the same way. Nonstandardized practices can make interpretation of results difficult. For example, in a survey, if a question is asked in different ways, the answers might vary depending upon the particular wording of the question.
The Classiﬁcation of Posts on Reddit with Binary Network Reduction

Reddit, is an anonymous social media website where users are responsible for all posted content. It has grown to be the 25 most popular website worldwide and 13 in the United States. It has had over 1.5 billion views and over 100 million active users. [1] There is a treasure trove of information to be had inside its database, and countless oppertunities for automation. Inside of the greater umbrella of Reddit, there are organizational structures called subreddits. Each post must be submitted to a single distinct subreddit, and each subreddit has its own rules and content. The subreddit r/Aww, for example, is a subset of Reddit dedicated to images of cute things. It does not allow certain file formats and has limitations on allowable content. The subreddit r/baseball is a subreddit dedicated to the sport of baseball, and does not allow any posts that are not related to such. The people who enforce these rules are volunteers called moderators, and they can often be overwhelmed. The subreddit r/funny has over 21 million active users, but only 20 moderators to enforce the rules. With such daunting numbers there is a need for automation. Thus the creation of ‘bots’ becomes necessary. Bots are automated Reddit users designed to fulfill a specific function. They can perform all of the actions that a normal user can, (comment, post, vote, report, etc) but they are doing so based on a script. This project will be focused on the creation of an algorithm for a bot to help moderate the subreddit r/askscience. Particularly, in the automatic labeling of posts.
Design of a reproducible murine fracture device

Mouse models are commonly used to investigate bone healing and test new treatments. The objectives of this project were to design a fracture device to create a reproducible transverse fracture in the mouse femur and to establish the limits of achieving transverse fractures. Testing with 26.4±6.1g wildtype mice (n=120) developed a model equation of to predict a 95% transverse fracture success rate. These results are useful to researchers who are interested in obtaining a higher transverse fracture success rate. 292 . 0 2 = mv
Milling diagnosis using artificial intelligence approaches

The Industry 4.0 framework needs new intelligent approaches. Thus, the manufacturing industries more and more pay close attention to artificial intelligence (AI). For example, smart monitoring and diagnosis, real time evaluation and optimization of the whole production and raw materials management can be improved by using machine learning and big data tools. An accurate milling process implies a high quality of the obtained material surface (roughness, flatness). With the involvement of AI-based algorithms, milling process is expected to be more accurate during complex operations. In this work, a milling diagnosis using AI approaches has been developed for composite sandwich structures based on honeycomb core. The use of such material has grown considerably in recent years, especially in the aeronautic, aerospace, sporting and automotive industries. But the precise milling of such material presents many difficulties. The objective of this work is to develop a data-driven industrial surface quality diagnosis for the milling of honeycomb material, by using supervised machine learning methods. In this approach cutting forces are online measured in order to predict the resulting surface flatness. The developed diagnosis tool can also be applied to the milling of other materials (metal, polymer, etc.).
TRIBO-CHEMISTRY OF DIAMOND (111) IN CONTACT WITH WATER

Ultralow friction of diamond in humid environments is of both scientific and industrial interest [1]. Experimental groups suggested that the surface passivation by H and OH groups plays an important role in ultralow friction of diamond [2]. Zilibotti et al. [3] showed that water molecules undergo chemical reactions with a diamond (001) surface under a high normal pressure by Car-Parrinello molecular dynamics (MD). However, due to their high computational cost, the accessible time scale is still limited to a few picoseconds. Since running-in processes and related phase transitions occur on larger time scales, little is known about the steady-state atomic-scale friction mechanisms of water-lubricated diamond surfaces. We here present the mechanism underlying the ultralow friction of a diamond (111) surface in contact with water molecules using the density-functional tight-binding (DFTB) MD method [4]. To understand the effects of the relative humidity on the friction of diamond, we perform sliding simulations of non-reconstructed diamond (111) surfaces interacting with different numbers n of water molecules. Simulations are carried out by rigidly moving the upper surfaces for 0.1 ns at a constant velocity of 100 ms -1 under an average normal pressure of 5 GPa. Figure 1a shows the friction coefficient as a function of n. The presence of a small amount of water initially induces cold welding and amorphization resulting in high friction. However, during running-in a triboinduced Pandey reconstruction emerges preventing the diamond surfaces from cold welding, thus leading to ultralow friction (Fig. 1b). When the amount of water increases further, diamond surfaces are sufficiently passivated with H and OH groups. The surface passivation occurs via the two reaction mechanisms: (i) the dissociative chemisorption of a water molecule and (ii) Grotthuss-type proton transport [5]. The sliding of H/OH-passivated surfaces also leads to stable and ultralow friction (μ = 0.02). Our models provide microscopic insight into the kinetics at diamond/water interfaces and explain the experimentally observed ultralow friction of diamond at a wide range of relative humidity. 0.01 0.1 1 10 100 0 5 10 15 20 25 Fr ic ti o n c o e ff ie ic n t Number of water molecules a b Cold welding & amorphization Cold welding via ether linkage Sliding of Pandey surface Sliding of H/OH-passivated surface
Urban poverty: Theory and evidence from gentrifying American cities

The proportion of poor people living in neighborhoods where poverty is highly concentrated is widely accepted as a policy-relevant measure of urban poverty in large metro areas. We challenge this view by developing new measures of urban poverty that i) capture aspects of the incidence and distribution of poverty across neighborhoods and ii) are consistent with the idea that poor people living in high-poverty neighborhoods face a double welfare burden of poverty. We demonstrate that there is only a measure that is consistent with a parsimonious axiomatic model for urban poverty. Panel variations of this measure are additively decomposed into the contribution of demographic, spatial and neighborhood-level poverty convergence effects. We collect new evidence of heterogenous patterns and trends of urban poverty across American metro areas over the last 35 years. Reduced form models allow to recover the implications of (income) sorting, affordable housing and of rising gentrification on different components of urban poverty across American cities.
The working conditions of media internships: an empirical study

Introduction. This article describes the conditions of interns in media companies and their degree of satisfaction with such conditions. Methods. The study is based on a survey conducted in 2015 among all journalism students doing internships in newspapers, radio stations and news agencies in the city of Málaga. Data were subjected to statistical analysis. Results. 85% of the interns affirm they systematically work overtime. Their workload is comparable to that of senior professionals. Despite these conditions, satisfaction among interns is high, and it increases when they perceive the company values their overtime. However, interns‘ satisfaction diminishes as their experience increases. Conclusions. The results question the formative role of internships and indicate that students‘ behaviours and attitudes could be explained by their expectations of job placement in the medium.
Modified Glassy Carbon Electrode with Polypyrrole Nanocomposite for the Simultaneous Determination of Ascorbic acid, Dopamine, Uric acid, and Folic Acid

A fast and simple method for synthesis of Cu x O-ZnO/PPy/RGO nanocomposite by electrochemical manner have been reported in this paper. For testing the utility of this nanocomposite we modified a GCE with the nanocomposite to yield a sensor for simultaneous determination of four analytes namely ascorbic acid (AA), dopamine (DA), uric acid (UA), and folic acid (FA). Cyclic voltammetry (CV) and Differential pulse voltammetry (DPV) selected for the study. The modified electrode cause to enhance electron transfer rate so overcome to overlapping their peaks and consequently having the ability to the simultaneous determination of AA, DA, UA, and FA. To synthesis confirmation of the nanocomposite, Field emission scanning electron microscopy (FE-SEM), Raman spectroscopy, and electrochemical impedance spectroscopy (EIS) were applied. The linearity ranges were 0.07-485 μM, 0.05-430 μM, 0.02-250 μM and 0.022-180 μM for AA, DA, UA, and FA respectively and the detection limits were 22 nM, 10 nM, 5 nM and 6 nM for AA, DA, UA, and FA respectively Also, the obtained electrode can be used for the determination of the AA, DA, UA, and FA in human blood, and human
Performance Counters based Power Modeling of Mobile GPUs using Deep Learning

GPUs have recently become important computational units on mobile devices, resulting in heterogeneous devices that can run a variety of parallel processing applications. While developing and optimizing such applications, estimating power consumption is of immense importance as energy efficiency has become the key design constraint to optimize for on these platforms. In this work, we apply deep learning techniques in building a predictive model for estimating power consumption of parallel applications on a heterogeneous mobile SoC. Our model is an artificial neural network (NN) trained using CPU and GPU hardware performance counters along with measured power data. The model is trained and evaluated with data collected using a set of graphics OpenGL workloads as well as OpenCL compute benchmarks. Our evaluations show that our model can achieve accurate power estimates with a mean relative error of 4.47% with respect to real power measurements. When compared to other models, our NN model is about 3.3x better than a statistical linear regression model and 2x better than a state-of-the-art NN model.
When Does Insider Sales Predict a Crash

Eunyoung Cho Ph.D. Seoul National University Business School Jongoh Kim Professor, Korea National Open University Woojin Kim* Associate Professor, Seoul National University Business School Abstract1) This study documents that predictability of insider trading on future stock price crash varies according to the types of insiders and the timing of the sale. Using insider trading data from Korea between 2005 and 2014, we find that largest shareholders tend to sell far before a stock price crash, while other types of insiders, including other large shareholders and executives, are more likely to sell immediately prior to a crash. Such pattern is more pronounced in firms with low CSR scores and low R-squares, but not observed among firms with high CSR scores or high R-squares. We also find that our results are stronger amongst firms with higher litigation risk. These findings suggest that largest shareholders may be well aware of the potential legal or reputational risk associated with insider trading while the remaining insiders may be less concerned.
Correlation between classroom atmosphere and language competency as academic achievement among Secondary Schools in Arusha District, Tanzania

*Corresponding Author Email: gnzowas@gmail.com This study sought to establish the relationship between English Language competency and classroom atmosphere among secondary schools in Arusha District. Through survey design, a sample of 180 students filled the questionnaire. Analysis of data involved Descriptive statistics, T-test and Pearson Correlation. The study established that female students had significantly higher mean score in language competency than male students. Students in classes with 40 or less members had significantly higher mean score than those in classes with more than 40 students. Teachers give necessary support to students for maximized learning outcome and classrooms are clean and orderly, have ideal sitting arrangement and are free from external and internal noise. Language competency is positively influenced by classroom infrastructure and effective teachers’ support. The more the teachers give support, the more the learners are motivated to support one another in the process of teaching and learning, thus, likelihood for maximized learning outcome. While teachers need to add more effort to enhance language competency to male students, school administration needs to ensure reduced number of students in classrooms and maintain classroom cleanliness and orderliness for maximized learning outcome.
Histological study on the effect of aqueous extract of citron leaf on pancreas of hyperglycemic wistar rats

*Corresponding Author Email: uthmanademola@yahoo.com The present study was carried out to assess some effects of Citrus medica leaf extract treatment on the following parameters in hyperglycemic Wistar rats: diabetic hyperglycaemia and microanatomy of pancreas. The male adult Wistar rats (40) weighing between 160-200g were indiscriminately classified into four consisting of 10 rat namely: (A) normal control, (B) hyperglycemic only, (C) hyperglycemic treated with citron and (D) citron only. Aqueous leaf extracts of citron were administered orally at 400mg/kg body weight daily for 6 weeks. After 6weeks extract of administration, animals were sacrificed by cervical dislocation. Organ weight was also taken while the pancreas was processed for light microscopy. Data were analysed using one way ANOVA. p<0.05 was considered significant. After 6 weeks the glucose level of hyperglycemic+Citron and Citron only groups significantly lowered, increase in body weight and relative pancreatic weight were observed relative to the hyperglycemic group. The histological examination of the pancreas of hyperglycaemic rats showed reduction Islet of Langerhans with fibrotic tissue while hyperglycemic+Citron rats was similar to control rats. Aqueous leaf extract of citronhas the ability to ameliorate the damage initiated by hyperglycemia on the pancreas of adult male Wistar rats.