Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance of One-Step Approximation Relative to Exact Cluster Cook's Distance for GEE

A simulation experiment was conducted to assess the performance of the generalized estimating equations (GEE) approximated cluster Cook’s Distance relative to its fully-iterated exact version. Specific interest was in the eect of clusterdeletion on the overall fit of a model for the marginal mean and on the overall fit of a model for the marginal association, in the context of alternating logistic regressions (ALR). The experiment demonstrated that one-step approximated cluster Cook’s Distance statistics successfully identify clusters having the greatest influence, as measured by their fully iterated exact counterparts. The regression diagnostic identified the cluster with the greatest influence on the fit of the marginal association model 88% of the time. The cluster with the greatest influence on the fit of the marginal mean model was identified 60% of the time, and the probability of detection increased with increasing size of the diagnostic. Cook’s Distance statistics for GEE and recently proposed analogous measures for ALR are useful for the analysis of clustered binary data. Performance of One-Step Approximation Relative to Exact Cluster Cook’s Distance for GEE John S. Preisser, Kunthel By, and Bahjat F. Qaqish Department of Biostatistics University of North Carolina at Chapel Hill Summary Abstract A simulation experiment was conducted to assess the performance of the generalized estimating equations (GEE) approximated cluster Cook’s Distance relative to its fully-iterated exact version. Specific interest was in the effect of cluster-deletion on the overall fit of a model for the marginal mean and on the overall fit of a model for the marginal association, in the context of alternating logistic regressions (ALR). The experiment demonstrated that one-step approximated cluster Cook’s Distance statistics successfully identify clusters having the greatest influence, as measured by their fully iterated exact counterparts. The regression diagnostic identified the cluster with the greatest influence on the fit of the marginal association model 88% of the time. The cluster with the greatest influence on the fit of the marginal mean model was identified 60% of the time, and the probability of detection increased with increasing size of the diagnostic. Cook’s Distance statistics for GEE and recently proposed analogous measures for ALR are useful for the analysis of clustered binary data.
PROBABILISTIC MODEL OF LASER RANGE FINDER FOR THREE DIMENSIONAL GRID CELL IN CLOSE RANGE ENVIRONMENT

The probabilistic model of a laser scanner presents an important aspect for simultaneous localization and map-building (SLAM). However, the characteristic of the beam of the laser range finder under extreme incident angles approaching 900 has not been thoroughly investigated. This research paper reports the characteristic of the density of the range value coming from a laser range finder under close range circumstances where the laser is imposed with a high incident angle. The laser was placed in a controlled environment consisting of walls at a close range and 1000 iteration of scans was collected. The assumption of normal density of the metrical data collapses when the beam traverses across sharp edges in this environment. The data collected also shows multimodal density at instances where the range has discontinuity. The standard deviation of the laser range finder is reported to average at 10.54 mm, with 0.96 of accuracy. This significance suggests that under extreme incident angles, a laser range finder reading behaves differently compared to normal distribution. The use of this information is crucial for SLAM activity in enclosed environments such as inside piping grid or other cluttered environments. ABSTRAK: Model berkebarangkalian pengimbas laser membentangkan aspek penting untuk pemetaan dan penganggaran lokasi (SLAM). Walau bagaimanapun, sifat pancaran laser pada sudut pantulan menghampiri 900 masih belum dikenalpasti dan tidak dikaji secara mendalam. Oleh itu, kertas penyelidikan inibertujuan untuk melaporkan sifat taburan normal yang datang dari pengukur jarak laser di bawah keadaan jarak dekat di mana laser itu dikenakan dengan sudut insiden tinggi. Pengimbas laser diletakkan di tempatterkawal yang terdiri daripada muka diding pada jarak yang dekat dan 1000 imbasan dikumpulkan. Andaian ketumpatan normal data berhubung dengan jarak ukuran runtuh apabila pantulan laser merentasi sudut tajam dalam tempat terkawal. Data yang dikumpul juga menunjukkan kepadatan pasca-modal pada keadaan di mana julat mempunyai ketakselanjaran. Sisihan purata taraf pengukur jarak laser dilaporkan berpurata pada 10.54 mm di bawah ketepatan 0.96. Penemuan menunjukkan bacaan pengimbas laser tidak mempunyai sifat taburan normal.Pengetahuan ini wajar digunakan untuk SLAM di kawasan yang tertutup rapat seperti di dalam grid pempaipan dan persekitaran yang berselerak.
Towards a global land surface climate fiducial reference measurements network

There is overwhelming evidence that the climate system has warmed since the instigation of instrumental meteorological observations. The Fifth Assessment Report of the Intergovernmental Panel on Climate Change concluded that the evidence for warming was unequivocal. However, owing to imperfect measurements and ubiquitous changes in measurement networks and techniques, there remain uncertainties in many of the details of these historical changes. These uncertainties do not call into question the trend or overall magnitude of the changes in the global climate system. Rather, they act to make the picture less clear than it could be, particularly at the local scale where many decisions regarding adaptation choices will be required, both now and in the future. A set of high‐quality long‐term fiducial reference measurements of essential climate variables will enable future generations to make rigorous assessments of future climate change and variability, providing society with the best possible information to support future decisions. Here we propose that by implementing and maintaining a suitably stable and metrologically well‐characterized global land surface climate fiducial reference measurements network, the present‐day scientific community can bequeath to future generations a better set of observations. This will aid future adaptation decisions and help us to monitor and quantify the effectiveness of internationally agreed mitigation steps. This article provides the background, rationale, metrological principles, and practical considerations regarding what would be involved in such a network, and outlines the benefits which may accrue. The challenge, of course, is how to convert such a vision to a long‐term sustainable capability providing the necessary well‐characterized measurement series to the benefit of global science and future generations.
Us Elections Sentimental Analysis

: The United States elections 2016 has seen an unprecedented amount of media coverage, numerous presidential candidates, and acrimonious debates over wide ranging topics from candidates of both the republic and democratic party. In contrast to the expectations Donald Trump surprisingly won the elections. Experts analyzed that the social networking sites like Facebook, Twitter and big data analytics rather than traditional approach helped Donald Trump to win the elections. In this project, Data Science and Big Data Analytics is used to analyze how the tweets in Twitter impacted US Elections. This project is an application of Sentimental Analysis also known as Opinion Mining using R Programming to perform text mining and opinion analysis on tweets collected during the US Election time.
Labeless Immunosensor Assay for Fluoroquinolone Antibiotics Based Upon an AC Impedance Protocol

Abstract This paper describes the construction of a labeless immunosensor for the antibiotic ciprofloxacin and its interrogation using an AC impedance protocol. Commercial screen‐printed carbon electrodes were used as the basis for the sensor. Polyaniline was electrodeposited onto the sensors and then utilized to immobilize a biotinylated antibody for ciprofloxacin using classical avidin‐biotin interactions. Electrodes containing the antibodies were exposed to solutions of antigen and interrogated using an AC impedance protocol. The faradaic component of the impedance of the electrodes was found to increase with increasing concentration of antigen. Control samples containing a non‐specific IgG antibody were also studied and calibration curves obtained by subtraction of the responses for specific and non‐specific antibody‐based sensors, thereby eliminating the effects of non‐specific adsorption of antigen.
Financial Innovations And Endogenous Growth

This paper explores the channels through which innovations in the financial sector lead to economic growth. The channels identified are capital accumulation and technological innovation. The first is fulfilled by financial intermediaries which transform household savings into productive investment by firms, the second by venture capitalists which fund risky technological projects with high potential payoffs. The rate of financial innovation is determined by the amount of labor (or human capital) devoted to the sector as well as by spillovers from existing fi- nancial products. By embedding such a sector into the Romer (1990) - Jones (1995) and Lucas (1988) - Uzawa (1965) frameworks, it is shown that ultimately, financial innovations can only lead to long-run growth through its venture capital role. The transformative role of the financial sector only leads to temporary growth effects on the transitional path to the steady state.
Estimating Daily Evapotranspiration Based on a Model of Evapotranspiration Fraction (EF) for Mixed Pixels

Currently, applications of remote sensing evapotranspiration (ET) products are limited by the coarse resolution of satellite remote sensing data caused by land surface heterogeneities and the temporal scale extrapolation of the instantaneous latent heat flux (LE) based on satellite overpass time. This study proposes a simple but efficient model (EFAF) for estimating 10 the daily ET of remotely sensed mixed pixels using a model of the evapotranspiration fraction (EF) and area fraction (AF). To accomplish this goal, we derive an equation for calculating the EF of mixed pixels based on two key hypotheses. Hypothesis 1 states that the available energy (AE) of each sub-pixel is approximately equal to that of any other sub-pixels in the same mixed pixel within an acceptable margin of bias and is equivalent to the AE of the mixed pixel. This approach simplifies the equation, and uncertainties and errors related to the estimated ET values are minor. Hypothesis 2 states that the EF of each 15 sub-pixel is equal to that of the nearest pure pixel(s) of the same land cover type. This equation is designed to correct spatial scale errors for the EF of mixed pixels; it can be used to calculate daily ET from daily AE data. The model was applied to an artificial oasis located in the midstream area of the Heihe River using HJ-1B satellite data with a 300 m resolution. Results generated before and after making corrections were compared and validated using sites data from eddy covariance systems. The results show that the new model can significantly improve the accuracy of daily ET estimates relative to the lumped 20 method; the coefficient of determination (R2) increased to 0.82 from 0.62, the root mean square error (RMSE) decreased to 1.60 from 2.47 MJ·m2, and the mean bias error (MBE) decreased from 1.92 to 1.18 MJ·m2.
Adaptive control of a wearable exoskeleton for upper-extremity neurorehabilitation

The paper describes the implementation and testing of two adaptive controllers developed for a wearable, underactuated upper extremity therapy robot --RUPERT Robotic Upper Extremity Repetitive Trainer. The controllers developed in this study were used to implement two adaptive robotic therapy modes --the adaptive co-operative mode and the adaptive active-assist mode --that are based on two different approaches for providing robotic assistance for task practice. The adaptive active-assist mode completes therapy tasks when a subject is unable to do so voluntarily. This robotic therapy mode is a novel implementation of the idea of an active-assist therapy mode; it utilizes the measure of a subject's motor ability, along with their real-time movement kinematics to initiate robotic assistance at the appropriate time during a movement trial. The adaptive co-operative mode, on the other hand, is based on the idea of enabling task completion instead of completing the task for the subject. Both these therapy modes were designed to adapt to a stroke subject's motor ability, and thus encourage voluntary participation from the stroke subject. The two controllers were tested on three stroke subjects practicing robot-assisted reaching movements. The results from this testing demonstrate that an underactuated wearable exoskeleton, such as RUPERT, can be used for administering robot-assisted therapy, in a manner that encourages voluntary participation from the subject undergoing therapy.
Chemists Who Sell and Chemists Who Don't: Embedding Product Development in Oil Field Services

This paper presents a case study of product development in production chemistry, which is a sector of the upstream petroleum industry concerned broadly with the regular application of chemicals to ensure continuing production from oil and gas fields. Production chemistry companies have a clear science base and offer a hybrid of chemical solutions and services to oil companies. Following recent interest in broadly cognitive, distributed and embedded understandings of both sales (author, 2006) and innovation (Nightingale, 1998, 2003), this paper proposes an understanding of product development that is processual, iterative and suggests a reconsideration of the role of science. The paper finds that agents involved in developing and reproducing the focal company’s chemistry (science/technology) activities and its sales activities develop their understandings and means of articulating product development with respect to different social settings. The paper locates the question of the early involvement of sales personnel in product development in extended cognition. Sales personnel have more to offer in shaping incremental innovation, compared with undertaking routine testing and also radical innovation, but their involvement is not simply a matter of co-location and closer working relations.
GENETIC DIVERSITY OF A BLACK POPLAR POPULATION IN THE MORAVA RIVER BASIN ASSESSED BY MICROSATELLITE ANALYSIS '

Black poplar (Populus nigru L.) is an important pioneer tree species of riparian ecosystems, but it is endangered due to loss of its natural habitats in the west and central Europe at present. The genetic structure of the population from the Morava river basin in the Czech Republic was investigated by microsatellite analysis. 112 adult trees (50-140 years old) were characterised at 12 microsatellite loci. There were identified 8 groups of identical genotypes (altogether 24 trees) among these individuals. All tested loci were highly polymorphic with a mean number of alleles 13.4 per locus, but almost 17 O/o of alleles were rare, appearing only once. The high values of expected heterozygosity and effective number of alleles (0.83 and 6.5, respectively) indicate high diversity in the population as well as the high value of observed heterozygosity (0.79) shows large number of heterozygous individuals. The positive mean of single-locus fixation index values indicates a weak overall excess of homozygotes. In order to study the spatial structure and gene flow within the population, four individual study sites were considered as subpopulations. Low Fs,values confirm the existence of gene flow among study sites and small genetic differentiation among them. However the calculated variation parameters could be loaded by considerable sampling error, since the numbers of trees in the individual study sites were rather
Probability and Variance Score: an Efficient Supervised Feature Selection Method for Text Classification

This paper proposes a new supervised feature selection method termed probability and variance score () for text classification. aims to improve variance score (), a simple unsupervised feature selection method because only evaluates quantity of information of terms but it is not able to evaluate relationships between terms and classes of text documents. not only evaluates quantity of information of terms by measuring variances of terms, the same method as , but also considers relationships between terms and classes by measuring posterior probabilities that terms occur given classes based on Bayesian Theory. Terms selected by tends to be information-rich and highly class-related. Experimental results on three datasets indicate that is efficient in selecting discriminative terms and outperforms .
A Kinase Inhibitor Cocktail as a Prophylaxis in the Syrian Golden Hamster Pirital Virus Model

Arena viruses are negative strand RNA viruses that have the potential to cause a wide spectrum of disease including hemorrhagic fever in humans and experimental animals. There are currently limited therapeutic treatments available for arena virus infection, which includes ribavirin and in some cases immune plasma. Therapeutic research testing the efficacy of products on arena virus infection can be difficult because work with the arena viruses that cause hemorrhagic fever require Biosafety level (BSL)-4 containment. However, surrogate arena virus animal models have been developed that can be utilized as a screening tool to test product efficacy of antivirals that may have broad acting anti-arena viral activity. Because there is a strong need to develop novel prophylaxis and therapeutics, we have utilized the Syrian golden hamster Pirital virus (PIRV) surrogate model to test antiviral efficacy in a BSL-3 environment. PIRV is a New World arena virus that is not known to cause human disease, but it is capable of causing hemorrhagic fever, morbidity, and complete mortality in the Syrian golden hamster. Thus, we infected hamsters with PIRV and treated with two different dosages of a kinase inhibitor cocktail consisting of genistein and tyrphostin AG1478. Drug efficacy was determined by evaluating physical signs of disease, mortality, viral titers in specific tissues, and terminal viremia. In this study, treating PIRV-infected hamsters with a kinase inhibitor cocktail led to a significant survival rate, lower viral titers, and an absence of viremia in survivors. In all, the results demonstrate the potential of the cocktail as an antiviral against arena virus infection.
Challenges of Technological Entrepreneurship in Africa: The Case of Tunisia

Technology parks are a strategic tool to spill over knowledge and skills. The rise of technology parks around the world and especially in developing countries, has addressed concerns on the technopreneurial activity and its impact on developing locations and regions, especially in developing countries in Africa, where private and public sector are joining efforts to create a sustainable ecosystem for technology entrepreneurs. Hence, numbers of challenges are facing Africa, particularly the cross-cultural factors and the ICT infrastructure. This research was conducted on Technology Park El Ghazala in Tunisia. We will try to assess the impact of cross-cultural variables such as age, communication and social networks influence on prospective technology entrepreneurs.
Investor Sentiment Aligned: A Powerful Predictor of Stock Returns

We propose a new investor sentiment index that is aligned with the purpose of predicting the aggregate stock market. By eliminating a common noise component in sentiment proxies, the new index has much greater predictive power than existing sentiment indices have both in and out of sample, and the predictability becomes both statistically and economically significant. In addition, it outperforms well-recognized macroeconomic variables and can also predict cross-sectional stock returns sorted by industry, size, value, and momentum. The driving force of the predictive power appears to stem from investors' biased beliefs about future cash flows.
A homotopy-based moving horizon estimation

ABSTRACT Moving horizon estimation (MHE) solves a constrained dynamic optimisation problem. Including nonlinear dynamics into an optimal estimation problem generally comes at the cost of tackling a non-convex optimisation problem. Here, a particular model formulation is proposed in order to convexify a class of nonlinear MHE problems. It delivers a linear time-varying (LTV) model that is globally equivalent to the nonlinear dynamics in a noise-free environment, hence the optimisation problem becomes convex. On the other hand, in the presence of unknown disturbances, the accuracy of the LTV model degrades and this results in a less accurate solution. For this purpose, some assumptions are imposed and a homotopy-based approach is proposed in order to transform the problem from convex to non-convex, where the sequential implementation of this technique starts with solving the convexified MHE problem. Two simulation studies validate the efficiency and optimality of the proposed approach with unknown disturbances.
Knowledge-Intensive Business Services and R&D Diffusion: a Comparative Assessment of Some EU27 Countries

In this article we develop a measure to approximate the diffusion of product-embodied R&D that takes place by means of the intermediate purchases of KIBS in 19 of the EU27 countries over the period 2000-2005. The results obtained confirm a rising trend in the use of KIBS as intermediate consumptions as well as the predominance of the domestic provision of this type of services with two exceptions: Ireland and, to a lesser extent, Finland. Leaving aside the two countries with the lowest intensities, Estonia and Hungary, four major groups of countries in terms of the R&D intensity of their KIBS sector were distinguished: very high (Finland, Sweden and Austria), high (Ireland, Czech Republic and Spain), medium (Greece, Belgium, Slovakia, Romania, Slovenia and Germany) and low (Portugal, Netherlands, Poland, Italy and Lithuania). Overall, a high correspondence between R&D intensity and product-embodied R&D diffusion was found, although Ireland, Romania, Belgium and the Netherlands displayed a disappointing diffusion per unit of value added in comparison with the R&D expenditures developed. The existence of weak linkages between the KIBS sector and the rest of industries can be identified as the main explanation for this “diffusion gap”. In brief, the results obtained confirm that KIBS are essential industries for improving innovation performance as they carry out strong efforts in R&D that spill over to the rest of the production system. DOI: http://dx.doi. org/10.5755/j01.ee. 24.4. 2081