Miracle-dz/UniFAR-FTUs huggingface dataset:
A Faster Sampling Algorithm for Spherical $k$-means

The Spherical k-means algorithm proposed by (Dhillon and Modha, 2001) is a popular algorithm for clustering high dimensional datasets. Although their algorithm is simple and easy to implement, a drawback of the same is that it doesn’t provide any provable guarantee on the clustering result. (Endo and Miyamoto, 2015) suggest an adaptive sampling based algorithm (Spherical k-means++) which gives near optimal results, with high probability. However, their algorithm requires k sequential passes over the entire dataset, which may not be feasible when the dataset and/or the values of k are large. In this work, we propose a Markov chain based sampling algorithm that takes only one pass over the data, and gives close to optimal clustering similar to Spherical k-means++, i.e., a faster algorithm while maintaining almost the same approximation. We present a theoretical analysis of the algorithm, and complement it with rigorous experiments on real-world datasets. Our proposed algorithm is simple and easy to implement, and can be easily adopted in practice.
Removal of Reactive Dyes from Wastewater using Cyclodextrin Functionalized Polyacrylonitrile Nanofibrous Membranes

Electrospinning of nanofibers with cyclodextrin (CD) is attractive because the produced fibers can potentially increase the efficiency of nanofibrous membranes by facilitating the complex formation with organic compounds and high surface area of the nanofibers. In this work, polyacrylonitrile (PAN) nanofibers functionalized with β– cyclodextrin (βCD) during an electrospinning process were used to treat a reactive dye wastewater stream by dynamic method. It was found that the dye removal efficiency was increased from 15.5% for PAN to 24% for PAN/βCD nanofiber mats. The low efficiency of PAN/βCD membranes was due to the decrease in the βCD content during the filteration process because of the high solubility of βCD in aqueous solutions. By crosslinking βCD through a polycondensation process, the PAN nanofibrous membranes containing βCD polymer (βCDP) were prepared and used for filtration. Compared with PAN nanofibers, it was found that the dye removal efficiency improved more than two times by using PAN/βCDP nanofibers. In such circumstances, due to the decrease in the water solubility of βCDP, the βCDP content in nanofibers didn’t change during filtration; therefore, the dye removal efficiency of the PAN/βCDP nanofibers was higher than that of the PAN/βCD ones. The XRD results also showed that inclusion complexes between the βCD cavities and dye molecules were formed.
Predicting the most common autoimmune diseases An experimental comparison of methods for multi-label learning using three well known classification algorithms

Autoimmune diseases are in the top ten leading causes of all deaths among U.S. women under 65 years[39] and is the fourth-largest cause of disability for these women. [25] Patients spent over 4.5 years with 5 different doctors before getting the correct diagnosis[2]. This research gives an experimental comparison of methods for multi-label learners is done based on three well known classification algorithms. Learners are made in order to predict the most common autoimmune diseases based on patients’ symptoms and conditions. The aim is to assist medical professionals in diagnosing the patient by analyzing his symptoms, conditions and health record and deduce the time until diagnosis. Two methods are used to handle patients having multiple autoimmune diseases. The first is the Problem Transformation method, where multi-label classification problems are converted into single-label problems. This is split into the Label Powerset method and the Binary Relevance method. In the Lapel Powerset method a new class is defined for each unique combination of labels attested in the training set. The Binary Relevance method on the other hand a separate binary problem is created, one for every possible label. The second is the Algorithm Adaptation method where conventional classifiers are implemented in a way that allows for multi-label classification. Based on these methods, three well known algorithms have been used namely, the k-Nearest Neighbors, the Random Forest and the Support Vector Machine. For every combination of algorithm and method models are developed and optimized for the F-measure of this model, while tuning the parameters. The two best parameter settings are chosen, which results in 18 developed models, that are evaluated and compared. Finally, a conclusion can be drawn that an ensemble chain of Binary Relevance methods, overall, works best, especially in combination with the Support Vector Machine. This method uses a Radial kernel, a γ-parameter of 2−10, a cost parameter of 10 and a threshold of 0.3. The F-measure has a 95% confidence interval of [14.83, 21.03] which is not high. But as a result, in almost 50% of the cases at least one autoimmune disease of a patient can be predicted correctly, and the average time before receiving a diagnosis can be deduced significantly.
HCI: Design Guidelines of Mobile Device Games for the Elderly

Design guidelines are an essential part of human computer interaction, for they provide an outlines of the requirements and needs of a user on how best to interact with technology devices. Our research project focuses on understanding how the elderly interact with current technologies (mobile devices and digital games) and how they can benefit from mobile digital games. The goal is to come up with interface design guidelines to be used by developers when designing mobile games for the elderly. The identification of the guidelines is carried out through a literature survey that includes a literature search based on outlined keywords, and a literature review of the selected research. The evaluation process of the guidelines involves user testing of a prototype based on some of the identified guidelines. Even with minor setbacks, the evaluation process indicates that the guidelines are beneficial for the development of mobile games for the elderly.
ConditionalReachabilityOfUncertainMaxPlusLinear Systems ?

The reachability analysis problem of Max Plus Linear (MPL) systems has been properly solved using the Difference-Bound Matrices approach. In this work, the same approach is considered in order to solve the reachability analysis problem of MPL systems subjected to bounded noise, disturbances and/or modeling errors, called uncertain MPL (uMPL) systems. Moreover, using the previous results on uMPL reachability analysis, we solve the conditional reachability problem, herein defined as the support calculation of the probability density function involved in the stochastic filtering problem.
Bulk plasmon-phonon polaritons in nGaN E

We studied theoretically and experimentally plasmon-phonon polaritons and longitudinal plasmon-phonon oscillations in n-GaN epitaxial layers. The studies were carried out on the epitaxial layers with various doping levels. Simulation of the reflectivity spectra and dispersion relations of plasmon-phonon polaritons was performed in a wide frequency range. Reflectivity spectra transformation associated with phonon damping and electron relaxation processes has been revealed. Experimental studies of the reflectivity spectra have been performed in the spectral range of 8–80 meV. The experimental spectra are well fitted by the simulated ones. Results of the study can be used for contactless determination of the electron concentration and mobility in GaN epitaxal layers.
Discussion Note : The Pacific & PAC Network Learning

Regional Public Accounts Committee (PAC) Learning Networks have been established around the globe as platforms for PACs to convene, as a community of practitioners, to identify common challenges and share information about national, regional and global practice. Each learning network is as different as the community that makes up the network. This Discussion Note provides a comparative snapshot of Pacific PACs and background information on the science of network learning.
Mechanism of Forced Convective Heat Transfer in Al 2 O 3 / Water Nanofluid under Laminar and Turbulent Flow

In this paper, fully developed laminar and turbulent flow convective heat transfer characteristics of Al2O3/water nanofluid flowing through a uniformly heated horizontal tube with and without wire coil inserts is presented. For this purpose, Al2O3 nanoparticles of 43 nm size were synthesized, characterized and dispersed in distilled water to formulate Al2O3/water nanofluid containing 0.1, 0.15 and 0.2% volume concentration of nanoparticles. Two wire coil inserts made of stainless steel with pitch ratios 2 and 3 were used. The results provide experimental evidence that the mechanism of thermophoresis play a pivotal role in explaining the heat transfer enhancement observed with nanofluids. Keywords— Heat transfer enhancements, Nusselt number, Nanofluid, Wire coil insert.
THE ROLE OF SIMPLE COMPONENT ANALYSIS IN THE CONTEXT OF THE EXPLORATORY METHODS. AN HEALTHCARE SERVICES EVALUATION

Among the exploratory techniques, Principal Component Analysis has the best properties in the study of relations between original variables, but in customer satisfaction applications it provides all positive correlations (the first component is an average or a sum of the scores). This feature entails trivial results of little interest that cannot help in decision-making, or even less, rotations (varimax, etc.) that can improve the interpretation of data structure. The aim of this paper is to highlight, via a comparison of methods, the role of Simple Component Analysis to improve the interpretability, over and above the lack of some desirable property (variance explained, etc.). This comparison will be supported by an application to real data on Patient satisfaction in a hospital in Naples.
Polymer composites on the basis of lignocellulose containing copper sulfide for electromagnetic wave protection

2pressing were established. Modified wood polymer composites possess good physical-mechanical characteristics, low electrical resistivity and high electromagnetic wave protection. Coordinative binding of copper ions with the oxygen atoms of cellulose OH groups and aromatic nucleus in the lignin macromolecule was observed. The new nanocomposites with microwave electromagnetic absorption properties could be used in radiotechnics, electronic industry, automobile building and others.
Library resources, student success and the distance-learning university

Purpose Research at the Open University Library Services has been investigating the relationship between access to online library resources and student success. The purpose of this study/paper is to help to understand whether there is a similar relationship at a distance-learning university to that found in other institutions. Design/methodology/approach A small library data project was established to investigate this area. The study analysed online library resource data from access logs from the EZproxy and OpenAthens systems. A data set of 1.7 million online resource accesses was combined with student success data for around 90,000 undergraduate students and a series of analyses undertaken. Findings The study found a pattern where students who are more successful are accessing more library resources. A chi-square test indicated a statistically significant association between library resource accesses and module result, while an ANOVA test suggests a medium-sized effect. The study also found that 152 (76 per cent) of the 199 modules had a small, medium or large positive correlation between student success, measured by the overall assessment score, and online library resource accesses. Originality/value This study builds on evidence that there is a relationship between library use and student success by showing that this relationship extends to the setting of a non-traditional, innovative library service supporting part-time distance learners.
Simulation of Positional Center of Gravity for Different Human Motions

To locate the center of gravity position, previous studies photographed human body motions and then applied body segmental parameters. This study presents a novel set of algorithm to locate three-dimensional center of gravity position. The purpose of this novel system is to aid establishing the gravity plumb line for rehabilitating patients. Control variables employed in this study were angular positions of ankle joints, knee joints, hip joints, shoulder joints, elbow joints, wrist joints, waist joint, and the neck. The study was grounded in five sources: the human body model by Zatsiorsky and Seluyanov [1], three basic homogeneous rotation matrices, three basic homogeneous translation matrices, a 4×4 identity matrix, and seven homogeneous transformation matrices developed by Chiu [2]. The first step in adopting this novel set of algorithm was to define body joints as 38 degrees of freedom. Then an algorithm was developed to locate the center of gravity position. Three male subjects participated in this study. Two motions were simulated by a computer. The first simulated motion was a subject squatting and then rising. During this squat, both arms swing from position at the sides of the body to a position adjacent to the head. During the second simulated motion, the subject leans horizontally at the waist from left to right, with both arms swinging upward. The experimental results demonstrated that the computer program successfully simulated the angular positions of particular postures, and the algorithm effectively established the relationship between the angular positions and the plumb line of the center of gravity. This novel system can assist paralyzed patients and those with muscular dystrophy by ensuring that correct postures are employed during rehabilitation. Furthermore, this system can also locate the center of gravity position during running, jumping, and walking.
Efficacy of Trichoderma spp. and fungicides against Lasiodiplodia theobromae

Experiments were carried out to find out the bio-efficacy of four Trichoderma species, viz. Trichoderma harzianum , T.koningii , T.viride (green strain), T.viride (yellow strain) against canker pathogen Lasiodiplodia theobromae. Bioassay of antagonist against test pathogens conducted by dual culture techniques at different temperatures; volatile, non volatile and naturally untreated metabolites of isolates were examined. T. koningii and T.viride (yellow strain) exhibited maximum inhibition in controlling the pathogens. Fungicides, viz. Bavistin and Dithane M-45 used where Bavistin found little effective but Dithane M-45 showed no effects on pathogen. Trichoderma viride showed better performance to control Lasiodiplodia theobromae than commercial fungicides used during present investigation. DOI: http://dx.doi. org/10.3329/bjsir.v49i2. 22008 Bangladesh J. Sci. Ind. Res. 49(2) , 125-130, 2014
Evaluation of broad-spectrum antiviral compounds against chikungunya infection using a phenotypic screening strategy

Chikungunya fever is an emerging disease and a significant public health problem in tropical countries. Recently reported outbreaks in Brazil in 2015 drew attention to the need to develop prevention and treatment options, as no antiviral chemotherapy or vaccines are currently available for this disease. Two strategies have been proved to accelerate the discovery of new anti-infectives: phenotypic screening and drug repurposing. Phenotypic screening can support the fast interrogation of compounds without the need for a pre-validated drug target, which is not available for the chikungunya virus (CHIKV) and has the additional advantage of facilitating the discovery of antiviral with novel mechanism of action. Drug repurposing can save time and resources in drug development by enabling secondary uses for drugs that are already approved for human treatment, thus precluding the need for several of the mandatory preclinical and clinical studies necessary for drug approval. A phenotypic screening assay was developed by infecting the human hepatoma Huh-7 cells with CHIKV 181/25 and quantifying infection through indirect immunofluorescence. The compound 6-azauridine was used as a positive control drug. The screening assay was validated by testing a commercial library of 1,280 compounds, including FDA-approved drugs, and used to screen a panel of broad-spectrum antiviral compounds for anti-CHIKV activity. A high content assay was set up in Huh-7 cells-infected with CHIKV. The maximum rate of infection peaked at 48 hours post-infection, after which the host cell number was greatly reduced due to a strong cytopathic effect. Assay robustness was confirmed with Z’-factor values >0.8 and high correlation coefficient between independent runs, demonstrating that the assay is reliable, consistent and reproducible. Among tested compounds, sofosbuvir, an anti-hepatitis C virus drug, exhibited good selectivity against CHIKV with an EC50of 11 µM, suggesting it is a promising candidate for repurposing.
The inverse Born problem in contextual probability theories: quantum spin and continuous random variables

We revise contextual probability theory and the associated inverse Born problem, solved by the Quantum-Like Representation Algorithm (QLRA) in case of two discrete random variables. After pointing out the special feature and limitations of QLRA for two binary random variables, we generalize the QLRA procedure to solve the inverse Born problem to the case of three binary random variables. We analyze the quantum spin model in the light of our results and showed that can be easily obtained from a contextual probability model. We furthermore study the inverse Born problem in the case of two continuous random variables, exploiting the general idea underlying QLRA.
CLUTCHING AND LAYER-SWITCHING : INTERACTION TECHNIQUES FOR PROJECTION-PHONE

We made a prototype cellular phone that incorporates a projection function. This prototype of a projection-phone is a system based on a commercially available portable projector to simulate the projection-phone environment. This system uses a peek technique by using image-based motion estimation to display virtual information. We developed clutching and layer-switching as a way of enabling the user to interact with and manipulate the virtual information projected using the peek technique. We also present some scenarios in which the projection-phone can be used.
Phylogeny of the genus Artemia based on RFLP analysis of mtDNA in IRAN

Phylogenetic relationships among the Iranian populations of Artemia belonging to three species of Artemia parthenogenetica, A. franciscana and A. urmiana were inferred by PCR-RFLP analysis of a 1566 bp segment of the mitochondrial 16S rRNA gene. A total of 270 specimens from 9 Artemia populations inhabiting in the inland Iranian lakes (Urmia, Shoor, Inche-Burun, Maharloo, Bakhtegan, Namak, Hoze-Soltan, Mighan and Nough) was surveyed using 10 restriction enzymes. Twelve different haplotypes were detected in A. parthenogenetica populations, including four haplotypes in Shoor and Inche-Burun, one in Bakhtegan, one in Namak and Hoze-Soltan, three in Mighan and three in Maharloo. Four different haplotypes of A. franciscana were found in Nough population and nine different haplotypes of A. urmiana were found in Urmia population. Phylogenetic analysis showed these nine populations were clustered into three clades: 1Shoor, Inche-Burun, Hoze-Soltan, Namak, Bakhtegan and Maharloo 2Nough and Mighan and 3Urmia. In this study referring to literature and basing on the oldness of A. urmiana, it selected as the outgroupe. Obtained results also show the ability of used technique for division of different populations of Artemia in Iran and parthenogenetic Artemia`s derivation from bisexual populations and high genetically resemblance with those of A. urmiana. Key-word: Artemia, mtDNA, phylogeny, PCR-RFLP, rRNA , IRAN
The role of the singing acoustic cues in the perception of broad affect dimensions

This experiment investigated the role of acoustic correlates of the singing voice in the perception of broad affect dimensions using the two-dimensional model of affect. The dataset consisted of vocal and glottal recordings of a sung vowel interpreted in different singing expressions. Listeners were asked to rate the sounds according to four perceived affect dimensions. A cross-tabulation was done between the singing expressions and affect judgments. A one-way ANOVA was performed for 11 acoustic cues with the affect ratings. It was found that the singing power ratio (SPR), mean intensity, brightness, mean pitch, jitter, shimmer, mean harmonic-to-noise ratio (HNR), and mean autocorrelation discriminate broad affect dimensions. Principal component analysis (PCA) was performed on the acoustic correlates. Two components were retained that explained 78.1% of the total variance of vocal cues and 73.5% of that of the glottal cues.
Mosquito female response to the presence of larvivorous fish does not match threat to larvae

1. Several species with complex life-history traits such as amphibians and insects with aquatic immature stages and terrestrial adults avoid ovipositing in pools containing larvivorous fish. This avoidance response was assumed to be a general one for most fish species. 2. The generality of ovipositing Culex to the presence of three, widespread larvivorous fish species was tested in a set of field experiments with artificial oviposition pools using caged fish. 3. Larval performance was further examined under actual predation by these three fish species. 4. Results show that ovipositing females responded strongly to the presence of caged mosquitofish, Gambusia affinis, while showing no significant response to the presence of caged green sunfish, Lepomis cyanellus, or the pirate perch, Aphredoderus sayanus. All three fish species consumed similar amounts of larvae. 5. This is the first example of species-specific response differences to predators during mosquito oviposition habitat selection. These results point to the existence of predator-released kairomones affecting mosquito behaviour. These kairomones may either be species-specific or vary in concentration among fish, and probably have an important role in the understanding of mosquito spatial distribution.
A nonlinear wavelet density-based importance sampling for reliability analysis

Importance sampling is a commonly used variance reduction technique for estimating reliability of a structural system. The performance of importance sampling is critically dependent on the choice of the sampling density. For the commonly used adaptive importance sampling method, the construction of the sampling density relies on the kernel-based density estimation. However, the choice of the initial bandwidth of the local windows may heavily affect the accuracy of the kernel method, particularly when the number of samples is not very large. To overcome this difficulty, this study develops a new adaptive importance sampling method based on nonlinear wavelet thresholding density estimator. The method utilizes the adaptive Markov chain simulation to generate samples that can adaptively populate the important region. The importance sampling density is then constructed using nonparametric wavelet density to implement the importance sampling. The methods takes advantage of the attractive properties of the Daubechies’ wavelet family (e.g., localization, various degrees of smoothness, and fast implementation) to provide good density estimations. Compared with the kernel density estimator, the nonlinear wavelet thresholding density estimator has a high degree of flexibility in terms of convergence rate and smoothness. Moreover, the choice of the initial parameters slightly affects the accuracy of the method. Two examples are given to demonstrate the proposed method.