Miracle-dz/UniFAR-FTUs huggingface dataset:
Small sample performance of bias‐corrected sandwich estimators for cluster‐randomized trials with binary outcomes

The sandwich estimator in generalized estimating equations (GEE) approach underestimates the true variance in small samples and consequently results in inflated type I error rates in hypothesis testing. This fact limits the application of the GEE in cluster‐randomized trials (CRTs) with few clusters. Under various CRT scenarios with correlated binary outcomes, we evaluate the small sample properties of the GEE Wald tests using bias‐corrected sandwich estimators. Our results suggest that the GEE Wald z‐test should be avoided in the analyses of CRTs with few clusters even when bias‐corrected sandwich estimators are used. With t‐distribution approximation, the Kauermann and Carroll (KC)‐correction can keep the test size to nominal levels even when the number of clusters is as low as 10 and is robust to the moderate variation of the cluster sizes. However, in cases with large variations in cluster sizes, the Fay and Graubard (FG)‐correction should be used instead. Furthermore, we derive a formula to calculate the power and minimum total number of clusters one needs using the t‐test and KC‐correction for the CRTs with binary outcomes. The power levels as predicted by the proposed formula agree well with the empirical powers from the simulations. The proposed methods are illustrated using real CRT data. We conclude that with appropriate control of type I error rates under small sample sizes, we recommend the use of GEE approach in CRTs with binary outcomes because of fewer assumptions and robustness to the misspecification of the covariance structure. Copyright © 2014 John Wiley & Sons, Ltd.
Why and How Knowledge Sharing Matters for R&D Engineers

This research explored how and why knowledge sharing matters for R&D engineers by investigating the effects of knowledge sharing on R&D engineer's job performance and job satisfaction. Based on multilevel data of 242 R&D engineers from 55 teams, the results showed that the relationships between knowledge sharing and R&D engineer's job performance/satisfaction were mediated through individual learning and self-efficacy. Individual learning was a necessary step for knowledge sharing to transform into individual knowledge, which in turn enhanced individual level outcomes. At the same time, individual learning enhanced self-efficacy, which subsequently benefited R&D engineer's job performance and job satisfaction. Finally, individual learning was found to be strongly related to individual job satisfaction.
The politics of cutback management in thirteen European countries: statistical evidence on causes and effects

ABSTRACT The politics of fiscal consolidation in thirteen European countries are statistically analysed. Based on the political economy literature, political factors are identified that explain for the consolidation. Variables are selected representing strength of government and political orientation, and fiscal consolidation is distinguished into spending cuts and cuts in administration. The statistical analysis of political explanations for cutbacks hardly yields significant results and nor does the analysis of fiscal and economic effects of consolidation. The analysis of political effects of consolidation does lead to significant results. Some earlier political economic findings are not supported for our sample of thirteen European countries.
An Evolutionary Algorithm based on an outranking relation for sorting problems

A new approach for using the preferences elicited from a Decision Maker (DM) into the operational framework of an Evolutionary Algorithm (EA) is presented. The preference representation is achieved using the parameters and principles of the ELECTRE TRI method devoted to the sorting problem. The outranking relation is used to replace the non-dominance relation in the usual operators in the EA (crossover, mutation and selection operator). The aim of this approach is to focus the search on the region of interest defined by the DM's preferences and consequently restrict the number of solutions in the Pareto-optimal front to be subject to further screening. This aspect is particularly important when dealing with problems that lead to a large number of non-dominated solutions.
Troškovi oporezivanja u Hrvatskoj: troškovi poreznih obveznika i troškovi poreznih vlasti (Operating Costs of Taxation in Croatia: Compliance and Administrative Costs)

Croatian Abstract: U radu se sintetiziraju rezultati kvantitativnih i kvalitativnih istraživanja troskova oporezivanja u Hrvatskoj za godinu 2001/2002, koja su obuhvatila troskove poreznih obveznika i troskove poreznih vlasti. Istraživanje troskova poreznih obveznika bilo je podijeljeno na sljedece dijelove koji su bili obuhvaceni posebnim anketama: građani (porez na dohodak, tj. prijava poreza na dohodak), poslovni subjekti obveznici poreza na dohodak – obrtnici i slobodna zanimanja (svi porezi osim carina i trosarina), poslovni subjekti obveznici poreza na dobit (svi porezi osim carina i trosarina), carine i trosarine. Istra_ivanja troskova poreznih obveznika uglavnom su provedena metodom intervjua licem u licem, a samo je manji broj anketa o trosarinama (za male porezne obveznike) proveden metodom postanske ankete. Mjerenje troskova poreznih vlasti rađeno je na temelju službenih raspoloživih podataka Porezne uprave i Carinske uprave (te Financijske policije). Ukupni troskovi oporezivanja u Hrvatskoj iznose oko 3, 13% BDP-a. Troskovi poreznih obveznika iznose 2, 66% BDP-a, a troskovi poreznih vlasti 0, 47% BDP-a. Udio troskova PDV-a je najveci (0, 81% BDP-a), a slijede ga carine (0, 60% BDP-a) i porezi na place (0, 48% BDP-a). Udio troskova poreznih vlasti u poreznim prihodima – svojevrsni pokazatelj efikasnosti poreznih vlasti iznosi oko 1, 76% poreznih prihoda. Od troskova pojedinih poreza najneefikasniji je porez na dohodak obrtnika, ciji udio troskova u poreznim prihodima iznosi 98%, a slijede ga carine, s udjelom od 31%, i porez na dobit, s udjelom od 12%. Dokazana je regresivnost troskova poreznih obveznika. Dani su prijedlozi poreznoj politici za smanjenje tih troskova.English Abstract: Aggregate operating (administrative and compliance) costs of taxation amount to 3.13% of GDP. As expected, compliance costs are higher than the administrative costs, the latter amounting only to 0.47% of GDP% (and 1.76% of tax revenues (excluding social security contributions)). Among compliance costs of taxation (2,66% of GDP) the highest are, as expected, compliance costs of VAT (0.81% of GDP), compliance of costs customs (0.6% of GDP) and compliance costs of wage taxes (part of personal income tax, including local surtax) together with social security contributions (0.48%) of GDP. The share of compliance costs of personal income tax of businesses that pay personal income tax is 0.25% of GDP – almost the same as of compliance costs of profit tax – 0.23. The reason lies in number of businesses paying personal income tax being for 50% higher than number of business units paying profit tax. The share of compliance costs of excise duties as well as compliance costs of individuals filing the personal income tax returns are almost negligible, being 0.03 and 0.02% respectively. The relatively low percentage of the latter one is the result of the fact that a bulk of income taxes is collected by withholding being final and that the average time spent on income tax return is only 1.7 hours.
Value of Oblique View in Nodular Thyroid Disease; Revisiting Fundamentals

Thyroid scintigraphy plays an important role in the anatomical and functional evaluation of thyroid nodules which carry the risk of malignancy. The presence of multiple nodules carries overall smaller risk of cancer than solitary nodule. Missing nodules, whether solitary or multiple, may mean delaying detection of possible cancer. Therefore, it is important to improve the delectability of thyroid scintigraphy using most optimal imaging techniques. For pinhole thyroid imaging, there is a recent trend to omit oblique projections by some laboratories. The objective of this study was to reevaluate the impact of oblique projections in the detection of thyroid nodules. A total of 92 cases with nodular thyroid disease on routine pinhole thyroid scintigraphy was reviewed retrospectively. Two nuclear medicine physicians recorded the number of nodules based on the anterior view only and another time with adding the oblique views. A total of 192 nodules was detected using the three views. Sixty nodules (31%) were only seen on the oblique views and were missed on the anterior projections. Oblique pinhole projections are mandatory for adequate thyroid scintigraphy since 31% of nodules are missed if only anterior projection was used for interpretation. Following proper techniques will avoid missing of detection of nodule that may harbor cancer.
The role of attention in subliminal semantic processing: A mouse tracking study

Recent evidence suggests that top-down attention facilitates unconscious semantic processing. To clarify the role of attention in unconscious semantic processing, we traced trajectories of the computer mouse in a semantic priming task and scrutinized the extent to which top-down attention enhances unconscious semantic processing in four different stimulus-onset asynchrony (SOA: 50, 200, 500, or 1000ms) conditions. Participants judged whether a target digit (e.g., “6”) was larger or smaller than five, preceded by a masked priming digit (e.g., “9”). The pre-prime duration changed randomly from trial to trial to disrupt participants’ top-down attention in an uncued condition (in a cued condition, a green square cue was presented to facilitate participants’ top-down attention). The results show that top-down attention modifies the time course of subliminal semantic processing, and the temporal attention window lasts more than 1000ms; attention facilitated by the cue may amplify semantic priming to some extent, yet the amplification effect of attention is relatively minor.
Analysis of ERASMUS staff and student mobility network within a big European project

The academic mobility is one of key factors that enable the globalization of research and education. In this paper we study the network of ERASMUS staff and student exchange agreements between academic institutions involved in FETCH - a big European project oriented towards future education and training in computer science. The structure of the network was investigated relying on standard metrics and techniques of social network analysis. Obtained results indicate that the network is in a mature phase of the development in which none of the institutions has a critical role to the overall connectedness of the network. Additionally, the network has a clear core-periphery structure with an active core and mostly inactive periphery.
Tailoring of electromagnetic waves by metasurfaces

In the last few years, non-homogeneous metasurfaces captured huge interest in tailoring electromagnetic waves, ranging from microwave to optical frequencies. Several technologies have been proposed, but a general design approach is still missing: the aim of this work is to present a modeling tool for the control of electromagnetic waves propagations. This approach enables to link the meta-surfaces electromagnetic properties with their geometrical and physical characteristics. To validate the proposed approach, two different applications will be reported: a flat Luneburg Lens and a sharp corner guiding structure. Results show good performance in terms of wide bandwidth and source independence.
Local mode-in-state participation factors for nonlinear systems

In this paper, a new definition for modal participation factors for nonlinear systems is proposed and used to obtain a formula for local mode-in-state participation factors. While the definition is general, the obtained formula depends on the assumption made regarding the distribution of the system initial condition. The definition extends work in the linear setting by Hashlamoun, Hassouneh and Abed (2009), and entails taking an average (or expectation) of a modal participation measure over an uncertain set of system initial conditions. As in the linear case, it is found that a symmetry assumption on the distribution of the initial state results in a tractable calculation and an analytical formula for mode-in-state participation factors. While the dichotomy discovered in the linear case between mode-in-state participation factors and state-in-mode participation factors exists also in the nonlinear setting, specific calculations for state-in-mode participation factors is more involved than for mode-in-state participations, and is left for further work.
TLR2 and TLR4 expression in atopic dermatitis, contact dermatitis and psoriasis

The aim of the study was to investigate the expression of Toll‐like receptors (TLRs) 2 and 4 on keratinocytes in atopic dermatitis, contact dermatitis, and psoriasis by PCR and by immunohistochemistry including confocal microscopy. Confocal microscopy revealed a granular intra‐cellular expression pattern for TLR 2 and a homogenous intra‐cellular expression pattern for TLR 4 in normal and diseased skin. TLR 2 was constitutively expressed in the suprabasal layers in normal skin, but limited to the basal epidermis in diseased skin. TLR 4 expression was concentrated to the basal layers in normal skin, whereas it was pronounced in upper layers in diseased skin. The shift in the TLR expression may be related to the disturbed skin barrier and a need for enhanced immune surveillance because of invading microbes. Also, there must be a balance between sufficient immune response and overstimulation.
Drivers of Destination Competitiveness in Tourism

Debates about competitiveness and productivity are practically unexplored with respect to tourism. This article posits a productivity-related measure—total tourism contribution to GDP per employee in tourism—in order to examine destination competiveness. Comprehensive results based on a destination competitiveness model are obtained by analyzing tourism-specific and wider economy-based competitiveness factors. These are represented by six destination competitiveness factors measured by 55 indicators for 139 destinations over the period 2007–2011. Study findings demonstrate that tourism-specific factors, such as Tourism Infrastructure and Destination Management, are the major competitiveness drivers in developing countries, while destination competitiveness in developed countries depends on the tourism-specific factor of Destination Management as well as on wider economic conditions such as General Infrastructure, Macro-Environment, and Business Environment. The study offers a novel approach in the operationalization and estimation of a theoretically grounded and empirically validated tourism competitiveness model and discusses the implications for tourism policy.
Analyses Of The Distribution Of Security Market Model Prediction Errors For Daily Returns Data

Many studies in accounting use the (one-factor) market model to examine the effects of firm-specific events on the prices of their securities. Early studies used monthly returns data, but more recently the use of daily data has become popular partly in order to take advantage of more powerful statistical tests available with these data. However, two problems are commonly encountered with the use of daily data: nonsynchronous trading (see Scholes and Williams [1977] and Dimson [1979]) and significant departures of the data from normality (see Fama [1965; 1976], Praetz [1972], Clark [1973], Blattberg and Gonedes [1974], and Marais [1984]). Scholes and Williams have shown that nonsynchronous trading leads to biased and inconsistent estimates of the market model parameters using ordinary least squares (OLS). These deficiencies will obviously affect the distribution of prediction errors (or residuals) and their statistical tests, which are the focus of information content studies. Moreover, nonnormality of returns results in misstatements of the significance levels in statistical tests which typically assume normality. The main purpose of this paper is to report the results of a detailed analysis of daily stock returns in which I compared the actual empirical distributions of standardized prediction errors (abnormal returns) with
Nanotechnology-Based Strategies for Early Cancer Diagnosis Using Circulating Tumor Cells as a Liquid Biopsy

Circulating tumor cells (CTCs) are cancer cells that shed from a primary tumor and circulate in the bloodstream. As a form of “tumor liquid biopsy”, CTCs provide important information for the mechanistic investigation of cancer metastasis and the measurement of tumor genotype evolution during treatment and disease progression. However, the extremely low abundance of CTCs in the peripheral blood and the heterogeneity of CTCs make their isolation and characterization major technological challenges. Recently, nanotechnologies have been developed for sensitive CTC detection; such technologies will enable better cell and molecular characterization and open up a wide range of clinical applications, including early disease detection and evaluation of treatment response and disease progression. In this review, we summarize the nanotechnology-based strategies for CTC isolation, including representative nanomaterials (such as magnetic nanoparticles, gold nanoparticles, silicon nanopillars, nanowires, nanopillars, carbon nanotubes, dendrimers, quantum dots, and graphene oxide) and microfluidic chip technologies that incorporate nanoroughened surfaces and discuss their key challenges and perspectives in CTC downstream analyses, such as protein expression and genetic mutations that may reflect tumor aggressiveness and patient outcome.
Estimating Schooling Effects

School Evaluation § Two broad reasons for estimating a “schooling effect” on student achievement o Research • e.g. What makes one school more or less effective than another? o School Accountability § Three broad methods for estimating school effects o “Snapshot” estimates • e.g. percent proficient o Year-to-year gain-scores • Estimates the gain in student test scores from one year to the next o Longitudinally • Uses multiple years of data to fit a growth function to the entirety students’ data
A Fast Hybrid ε-Approximation Algorithm for Computing Constrained Shortest Paths

Considerable efforts have been dedicated to develop both heuristic and approximation algorithms for the NP-complete delay-constrained least-cost (DCLC) routing problem, but to the best of our knowledge, no prior work has been done to mingle the two tracks of research. In this letter we introduce a novel idea to show how a heuristic method can be used to boost the average performance of an approximation algorithm. Simulations on networks of up to 8192 nodes demonstrate that our new hybrid ε-approximation algorithm is faster than the best known approximation algorithm by one or two orders of magnitude (depending on the network size and ε).
Critical Media Health Literacy in Burma/Myanmar: A Case Study of High School Students

Current health literacy research is reconceptualizing health literacy and social learning. Theorists are situating health literacy in the contexts of digital media and critical sociocultural theories (e.g., Wharf Higgins & Begoray, 2012), based on the proposition that literacy is a complex and layered human involvement in socio-political contexts (e.g., Gee, 2000; Lankshear & Knobel, 2011; Levin-Zamir, Lemish, & Gofin, 2011; Nahachewsky & Ward, 2007). Research with adolescents in various contexts around the world has indicated that an empowerment approach to literacy education is effective for health literacy interventions (King, 2007). This study responds to the need to design and facilitate high school curriculum to empower adolescents to develop health literacy, and the study responds to the research participants’ choice of mental health as the topic of an interdisciplinary curriculum. Situated in the traditions of qualitative case study research methods, and positioned to engage the online social media contexts in which adolescents participate, this study explored how Critical Media Health Literacy (Wharf Higgins & Begoray, 2012) is expressed by a particular group of Burmese adolescents. The data reveal how the theoretical concept of Critical Media Health Literacy, when operationalized as a unit of analysis for the case study and a theoretical framework for the data collection methods of the case study, can be facilitated in a way that engages the research participants in specific skills’ practice and in cognitive, emotional reflection on their own health and literacies capacities. Data collection methods involved face-to- face interviews, online social media blogs, web page designs, and face-to-face group discussions. The analysis found optimism, anxiety, and taking action were major themes shaping the conditions for the adolescents’ development of health literacy, showing health literacy to be integral with media literacy and critical capacities, and indicating the concept of Critical Media Health Literacy has relevance for curriculum that engages adolescents who are situated in Burma/Myanmar to take action to improve the health of themselves and others in their social contexts. The findings indicate that this population and the applicability of Critical Media Health Literacy for high school curriculum in this setting requires further exploration to understand why social determinants of health are perceived as inevitable, how social pressures related to health are negotiated, and how digital structures influence the criticality of literacies of adolescents in Burma/Myanmar. Theoretical frameworks for further research are proposed for an exploration of the systems of relations in socio- political and economic contexts that influence the development and enactment of Critical Media Health Literacy and health promoting performances of adolescents in Burma/Myanmar. %%%%Graduate
State Space LSTM Models with Particle MCMC Inference

Long Short-Term Memory (LSTM) is one of the most powerful sequence models. Despite the strong performance, however, it lacks the nice interpretability as in state space models. In this paper, we present a way to combine the best of both worlds by introducing State Space LSTM (SSL), which generalizes the earlier work \cite{zaheer2017latent} of combining topic models with LSTM. However, unlike \cite{zaheer2017latent}, we do not make any factorization assumptions in our inference algorithm. We present an efficient sampler based on sequential Monte Carlo (SMC) method that draws from the joint posterior directly. Experimental results confirms the superiority and stability of this SMC inference algorithm on a variety of domains.
Civic engagement in Kenya: Developing student leadership through service-learning

The purpose of this research study is to develop an approach to research on civic engagement and service learning in Kenya which examines the role of Kenyan Universities in preparing students for civic engagement, active citizenship and leadership. The research seeks to explore historical, political and cultural events, beliefs, attitudes, and policies that have shaped the mission of higher education in Kenya and describes how these influence the perception of role of Kenyan Universities in preparing students for civic engagement, citizenship and leadership through community service. This research is aimed at contributing to knowledge based on the gap identified in the literature review which is characterized by (1) inadequate access to or dissemination of research that addresses concepts of the civic, community service and student leadership in Kenya; (2) limited discourse on the current role of Kenyan Universities in society and (3) limited research on “Kenyan-centric” solutions to social issues. This research thus takes into consideration multiple perspectives of varying University stakeholders and provides an innovative research design to that values the ‘voice’ of the marginalized and other stakeholders who are to varying extents affected by the functions