Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical Analysis on Physico-Chemical Properties of Some Nigerian Clay Deposits

Clays are among the most essential industrial minerals due to their unique physicochemical properties and versatile usage. This paper used Statistical Package for Social Sciences (SPSS) software to characterize five clay deposits for their physical and chemical compositions. The package, was employed to carry out the Analysis of Variance (ANOVA) by Post-Hoctambane multiple comparisons and Kristal Wallis at 5% confidence level for the f- and t-tests respectively. The analysis of variance of the chemical components of the samples by post-hoc (f8, 36 = 52.40, p < 0.05) showed that significant difference exist between the average concentration means. While the Kristal Wallis one sample t-test (T8, 37.38 and p < 0.05) showed a great degree of significant difference in the p-values of the means of SiO2 and Al2O3. Pearson bivariate correlation statistical tool was also used to establish if significant positive interrelationships exist between the parameters in each site of the clay samples at (p < 0.01 and p < 0.05). The result of the correlation indicates a very significant, strong and positive coefficient p-values above 0.900 between the chemical and physicalproperties. Pearson bivariate correlation coefficient between the chemical and physical parameters of the clay samples indicates very significant, strong and positive correlations with p-values above 0.900 at (p < 0.01 and <0.05). The overall physicochemical results indicate that most of the clay samples will meet the requirements for some industrial applications with minimal processing.
Aharonov–Bohm interferences in polycrystalline graphene

Aharonov–Bohm (AB) interferences in the quantum Hall regime can be achieved, provided that electrons are able to transmit between two edge channels in nanostructures. Pioneering approaches include quantum point contacts in 2DEG systems, bipolar graphene p–n junctions, and magnetic field heterostructures. In this work, defect scattering is proposed as an alternative mechanism to achieve AB interferences in polycrystalline graphene. Indeed, due to such scattering, the extended defects across the sample can act as tunneling paths connecting quantum Hall edge channels. Consequently, strong AB oscillations in the conductance are predicted in polycrystalline graphene systems with two parallel grain boundaries. In addition, this general approach is demonstrated to be applicable to nano-systems containing two graphene barriers with functional impurities and perspectively, can also be extended to similar systems of 2D materials beyond graphene.
An Intelligent Storage Optimization Technique for Heterogeneous Hadoop Clusters

Big data storage and processing can be carried out with the help of Hadoop technology. Hadoop distributed file system store data using chunks, whose size is multiple of 64MB. The default storage space occupied by the raw data is always 200% more, as the default configuration uses three-fold technique. The data stored over HDFS may have different priority, formats and redundancies. The data is stored in standard HDFS without applying either compression or encoding and redundancy. This traditional storage system makes the storage resource underutilized. To improve the usage of storage resources in big data platform an intelligent storage system is required. This paper proposes a Machine learning based intelligent storage system called iYARN, Yet Another Resource Negotiator, to maximize the storage capability. The proposed algorithm improves storage allocation for structured data by 20%, unstructured data by 30%, and semi-structured data by 35%.
Numerical calibration of a multicomponent local Lorentz force flowmeter

Local Lorentz force velocimetry is a local velocity measurement technique for liquid metals. Due to the interaction between an electrically conducting liquid and an applied magnetic field, eddy currents and flow-braking Lorentz forces are induced in the fluid. Due to Newton’s third law, a force of the same magnitude acts on the source of the applied magnetic field, which is a permanent magnet in our case. The magnet is attached to a gauge that has been especially developed to record all three force and three torque components acting on the magnet. This new-generation local Lorentz force flowmeter (L2F2) has already been tested in a test stand for continuous casting with a 15mm cubic magnet providing an insight into the three-dimensional velocity distribution of the model melt GaInSn near the wide face of the mold. For better understanding of these results, especially regarding torque sensing, we propose dry experiments which consist in replacing a flowing liquid by a moving solid. Here, as the velocity field is fixed and steady, we are able to decrease considerably the variability and the noise of the measurements providing an accurate calibration of the system. In this paper, we present a numerical study of this dry calibration using a rotating disk made of aluminum and two different magnet systems that can be shifted along the rotation axis as well as in the radial direction.
Contests with Ex-Ante Target Setting

I study contests in which each player is ranked by a scoring rule based on both her performance and how close this performance is to a private target, set before the contest. Each player’s decision problem is to choose her target when performance is subject to a random component. I analyse the incentive properties of target setting, derive conditions on the primitives such that equilibria exist and characterise the players’ behaviour. I show that target setting generates outcome uncertainty under a large class of conditions. In particular, neither private abilities nor perfectly correlated states are necessary. Target setting, therefore, has important implications in contest design as outcome uncertainty is a salient determinant of consumers’ demand for contests. JEL classification numbers: C70 ; D81 ; D82 ; Z20
Some Contributions to Distribution Theory and Applications

In this thesis, we present some new results in distribution theory for both discrete and continuous random variables, together with their motivating applications. We start with some results about the Multivariate Gaussian Distribution and its characterization as a maximizer of the Strichartz Estimates. Then, we present some characterizations of discrete and continuous distributions through ideas coming from optimal transportation. After this, we pass to the Simpson’s Paradox and see that it is ubiquitous and it appears in Quantum Mechanics as well. We conclude with a group of results about discrete and continuous distributions invariant under symmetries, in particular invariant under the groups A1, an elliptical version of O(n) and Tn. As mentioned, all the results proved in this thesis are motivated by their applications in different research areas. The applications will be thoroughly discussed. We have tried to keep each chapter self-contained and recalled results from other chapters when needed. The following is a more precise summary of the results discussed in each chapter. In chapter 1, we discuss a variational characterization of the Multivariate Normal distribution (MVN) as a maximizer of the Strichartz Estimates. Strichartz Estimates appear as a fundamental tool in the proof of wellposedness results for dispersive PDEs. With respect to the characterization of the MVN distribution as a maximizer of the entropy functional, the characterization as a maximizer of the Strichartz Estimate does not require the constraint of fixed variance. In this chapter, we compute the precise optimal constant for the whole range of Strichartz admissible exponents, discuss the connection of this problem to Restriction Theorems in Fourier analysis and give some statistical properties of the family of Gaussian Distributions which maximize the Strichartz estimates, such as Fisher Information, Index of Dispersion and Stochastic Ordering. We conclude this chapter presenting an optimization algorithm to compute numerically the maximizers.
Omnidirectional Dual-Polarized Saber Antenna With Low Wind Drag

In this communication, a compact saber-like antenna with low wind drag is proposed for on-board communication application, under the requirements of polarization diversity and omnidirectional coverage. The proposed antenna consists of a thin resonant cavity for omnidirectional horizontal polarization (HP), and a folded slot is colocated with the cavity to provide omnidirectional vertical polarization (VP). Isolation lower than −20 dB between two feeding ports is achieved in a quite compact dimension of <inline-formula> <tex-math notation="LaTeX">$30 \times 29 \times 9$ </tex-math></inline-formula> mm<sup>3</sup>(<inline-formula> <tex-math notation="LaTeX">$0.24\lambda _{0} \times 0.24\lambda _{0} \times 0.07\lambda _{0}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\lambda _{0}$ </tex-math></inline-formula> is the free-space wavelength at 2.44 GHz), also with the omnidirectional patterns for both polarizations. A prototype of the proposed antenna is fabricated and tested to verify the design strategy. Compared with previous designs, the cross section area for wind drag is reduced for more than 28.5%, exhibiting potential usage for high-speed moving antenna carriers.
Real-world pedestrian detection method enhanced by semantic segmentation

Abstract. Although pedestrian detection has been largely improved with the emergence of convolutional neural networks (CNN), the performance in autonomous driving still faces various challenges, which mainly include large-scale variation, illumination variation, and occlusion of different levels. A robust pedestrian detector enhanced by semantic segmentation is proposed. Inspired by the benefits of multitask learning, our main idea lies in integrating the task of semantic segmentation into the detection framework with auxiliary supervision, inheriting the merits of the two-stream network. Specifically, anchor boxes with various scales are paved on the feature maps of a base CNN; detection is performed based on bounding box classification and regression. On the other stream, semantic segmentation is also performed based on the same feature maps. Extensive experiments on the recently published large-scale pedestrian detection benchmark, i.e., CityPersons, show that the additional supervision from semantic segmentation can significantly improve the detection accuracy without extra computational burdens during inference, which demonstrates the superiority of the proposed method.
Finite‐time consensus of Euler‐Lagrange agents without velocity measurements via energy shaping

Motivated by the energy‐shaping framework and the properties of homogeneous systems, this paper deals with the problem of achieving consensus of multiple Euler‐Lagrange (EL) systems using the energy shaping plus damping injection principles of passivity‐based control. We propose a method to derive a novel family of decentralized controllers that is capable of solving the leaderless and the leader‐follower consensus problems in finite‐time in networks of fully actuated EL systems without employing velocity measurements. As in the energy‐shaping methodology, the controller is another EL system and the plant‐controller interconnection is the gradient of a suitable defined potential function. The potential energy and dissipation functions, of the controller, are provided with some homogeneous properties in order to achieve finite‐time convergence. This paper provides several simulations that corroborate the performance of different controllers.
Hepatitis B Virus infection in HIV infected patients

ABSTRACT: 175 serum specimens from patients confirmed to have human immunodificiently virus (HIV) infection were tested for the presence of hepatitis B Surface antigen (HBsAg) of the hepatitis B virus (HBV). These 175 patients were from different high risk groups of HIV infection and were classified into asymptomatic, lymphadenopathy associated syndrome (LAS0, AIDS related complex (ARC) and AIDS categories as per CDC criteria. A commercial latex agglutination test for HBsAg was used for its detection. HBsAg was detected in 49 patients. These 49 patients include 11 blood donors, 9 pulmonary tuberculosis patients, 7 sexually transmitted disease (STD) patients, nine AIDS related illness patients, 3 contacts of HIV positive patients, 3 heterosexuals, 4 hepatitis patients and 1 each with candidiasis, Lymphadenopathy associated syndrome (LAS) and blood transfusion related HIV infected patient. We observed that 28 percent of the HIV infected individuals harbour HBV simultaneously in contrast to 2 percent among controls, the difference is statistically significant (p0,00001). The prevalence of HBsAg was observed in all the stages of HIV infection. The prevalence was slightly more in symptomatic group as compared to asymptomatic groups, but the difference was not statistically significant.
Ultra-Miniaturized Wilkinson Power Divider with Harmonics Suppression for Wireless Applications

ABSTRACT In this paper, an ultra-compact size microstrip Wilkinson Power Divider (WPD) has been proposed with nth harmonic suppression. Two symmetrical lowpass filters have been applied to suppress third to 11th harmonics. These cells are replaced by quarter-wavelength transmission lines to achieve desired harmonic suppression. The central frequency of the PD is located in 2.5 GHz, and the physical size is only 9.4×7.2= 67 mm2, which is normalized as 0.06 λg *0.08 λg. The applied lowpass filter has analyzed and then, the proposed PD presented with the insertion loss of less than 0.6 dB and return loss of 35 dB. The measured S-parameters showed a good adaption with the simulated results.
A Modification of the Fast Inverse Square Root Algorithm

We present a new algorithm for the approximate evaluation of the inverse square root for single-precision floating-point numbers. This is a modification of the famous fast inverse square root code. We use the same “magic constant” to compute the seed solution, but then, we apply Newton–Raphson corrections with modified coefficients. As compared to the original fast inverse square root code, the new algorithm is two-times more accurate in the case of one Newton–Raphson correction and almost seven-times more accurate in the case of two corrections. We discuss relative errors within our analytical approach and perform numerical tests of our algorithm for all numbers of the type float.
Evaluating Applied Theatre Using Amateur Community Actors as a Modality for Pedestrian Education Among Primary School Students in Moshi, Tanzania

Evaluating Applied Theatre Using Amateur Community Actors as a Modality for Pedestrian Education Among Primary School Students in Moshi, Tanzania by Christina Dideriksen Duke Global Health Institute Duke University Date:_______________________ Approved: ______________________________ Kearsley Stewart, Co-Chair ______________________________ Chris Woods, Co-Chair ______________________________ Catherine Lynch ______________________________ Kristen Sullivan An abstract of a thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in the Duke Global Health Institute of Duke University 2014 Copyright by Christina Dideriksen 2014
Magnetic shear due to localized toroidal flow shear in tokamaks

We investigate the impact of toroidal rotation on axisymmetric MHD equilibria analytically and numerically, with a focus on the change of the safety factor and magnetic shear induced by the flow. When the toroidal rotation is radially localized by an external momentum source, the pressure due to the flow can change the magnetic configuration and the safety factor significantly, even for subsonic flows. Specifically, when the radial profile of the safety factor is not conserved throughout a discharge, toroidal flow can lead to magnetic shear reversal for the equilibrium magnetic field, and we find that the magnitude of the negative shear is amplified for cross sections with large negative triangularity. This has implications for both magnetohydrodynamic stability and anomalous transport. Furthermore, even when the magnetic flux is conserved and the radial magnetic shear profile does not change, the toroidal flow can modify the local magnetic shear. The poloidal variations of the local magnetic shear due to the flow can stabilize magnetohydrodynamic ballooning modes.
‘Blood is definitely thicker than water!’ ‘but sshht, what will the neighbours say!?’. Social support for black HIV-positive individuals in a resource limited setting in South-Africa

South-Africa is severely affected by the AIDS epidemic. Several Non Governmental Organizations (NGO‟s) try to suppress replication of the virus by offering programs which supply antiretroviral (ARV) therapy for HIV-positive individuals. A precondition of an effective use of this therapy is that patients stick to sustained medication adherence. Existing literature shows that an important factor associated with medication adherence is social support. This research focuses on social support for HIV-positive individuals within the South-African context. Based on existing literature, social support is distinguished in five forms: emotional, instrumental, financial, informative/advisory and spiritual support. Furthermore, the following support providers are distinguished: kin relations, partners, friends, fellow patients and HIV/AIDS management programs. A qualitative approach is taken in this study in order to answer the following research question: ‘What are the assumptions of (beneficial) social support for black HIV-positive individuals and why might support be lacking, according to patients and professionals of the Tapologo ARV-outreach program around Rustenburg, South-Africa? ’ In order to answer this question, interviews and focus group discussions with 24 HIV/AIDS patients and 16 Tapologo professionals have been conducted. The results show that patients have various support needs. They need emotional support by being accepted and discussing their situation with a confidant. Informative/advisory support needs include getting advice concerning infection, re-infection and living a healthy lifestyle. Instrumental assistance with heavy work and housekeeping activities is necessary during days patients don‟t feel well. Patients often struggle to survive due to a lack of financial resources. This increases the need of financial assistance for healthy food and transportation to the clinics in order to adhere to their treatment. Patients also benefit from spiritual support in the form of singing and discussing bible stories. It gives them hope and it lifts up their spirit.
Efficient Text Classification with Linear Regression Using a Combination of Predictors for Flu Outbreak Detection

Early prediction of disease outbreaks and seasonal epidemics such as Influenza may reduce their impact on daily lives. Today, the web can be used for surveillance of diseases. Search engines and Social Networking Sites can be used to track trends of different diseases more quickly than government agencies such as Center of Disease Control and Prevention (CDC). Today, Social Networking Sites (SNS) are widely used by diverse demographic populations. Thus, SNS data can be used effectively to track disease outbreaks and provide necessary warnings. Although the generated data of microblogging sites is valuable for real time analysis and outbreak predictions, the volume is huge. Therefore, one of the main challenges in analyzing this huge volume of data is to find the best approach for accurate analysis in an efficient time. Regardless of the analysis time, many studies show only the accuracy of applying different machine learning approaches. Current SNS-based flu detection and prediction frameworks apply conventional machine learning approaches that require lengthy training and testing, which is not the optimal solution for new outbreaks with new signs and symptoms. The aim of this study is to propose an efficient and accurate framework that uses SNS data to track disease outbreaks and provide early warnings, even for newest outbreaks accurately. The presented framework of outbreak prediction consists of three main modules: text classification, mapping, and linear regression for weekly flu rate predictions. The text classification module utilizes the features of sentiment analysis and predefined keyword
Consumo de cocaína y psicopatología asociada: una revisión

Analysis of the relationship between cocaine consumption and psychopathological characteristics is a relevant topic at the present time. Cocaine use and the demand for treatment arising from problems associated with cocaine use have increased in the last few years. Certain psychopathological characteristics can interfere with the development of treatment related to cocaine abuse or dependence. The objective of this paper was to review the most relevant research, published at a national and international level, which analysed the relationship between cocaine use and psychopathological characteristics. A review of 41 selected studies leads us to conclude that cocaine use (abuse or dependence), as analysed in the studies, is associated in a large number of cases with several disorders such as alcohol dependence, personality disorders (especially borderline, paranoid, antisocial, histrionic, narcissist and passive-aggressive disorders), depression and anxiety are among the most important. Finally, we expose several limitations in the studies carried out and provide the principal lines that should be followed in the future in this type of studies.
Co-Skewness Across Return Horizons

This paper investigates the sensitivity of higher-order co-moments for different return measurement intervals. The levels of systematic skewness and kurtosis are found to be significantly influenced by the length of return interval. An asset preferred because of its positive co-skewness and low co-kurtosis when measured in one particular interval may have negative co-skewness or high co-kurtosis for another interval. We find the intervaling effect varies according to the level of price adjustment delay as proxied by market capitalization and illiquidity. Findings persist for intervals of up to twelve months, and are consistent during both volatile and stable periods.
Vowel Formant Structure Predicts Metric Position in Hip-hop Lyrics

In order to be heard over the low-frequency energy of a loud orchestra, opera singers adjust their vocal tracts to increase high-frequency energy around 3,000 Hz (known as a “singer's formant”). In rap music, rhymes often coincide with the beat and thus may be masked by loud, low-frequency percussion events. How do emcees (i.e., rappers) avoid masking of on-beat rhymes? If emcees exploit formant structure, this may be reflected in the distribution of on- and off-beat vowels. To test this prediction, we used a sample of words from the MCFlow rap lyric corpus (Condit-Schultz, 2016). Frequency of occurrence of on- and off-beat words was compared. Each word contained one of eight vowel nuclei; population estimates of each vowel's first and second formant (F1 and F2) frequencies were obtained from an existing source. A bias was observed: vowels with higher F2, which are less likely to be masked by percussion, were favored for on-beat words. Words with lower F2 vowels, which may be masked, were more likely to deviate from the beat. Bias was most evident among rhyming words but persisted for nonrhyming words. These findings imply that emcees use formant structure to implicitly or explicitly target the intelligibility of salient lyric events.