Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient and Robust Large-Scale Rotation Averaging

In this paper we address the problem of robust and efficient averaging of relative 3D rotations. Apart from having an interesting geometric structure, robust rotation averaging addresses the need for a good initialization for large scale optimization used in structure-from-motion pipelines. Such pipelines often use unstructured image datasets harvested from the internet thereby requiring an initialization method that is robust to outliers. Our approach works on the Lie group structure of 3D rotations and solves the problem of large-scale robust rotation averaging in two ways. Firstly, we use modern ℓ1 optimizers to carry out robust averaging of relative rotations that is efficient, scalable and robust to outliers. In addition, we also develop a two step method that uses the ℓ1 solution as an initialisation for an iteratively reweighted least squares (IRLS) approach. These methods achieve excellent results on large-scale, real world datasets and significantly outperform existing methods, i.e. the state-of-the-art discrete-continuous optimization method of [3] as well as the Weiszfeld method of [8]. We demonstrate the efficacy of our method on two large scale real world datasets and also provide the results of the two aforementioned methods for comparison.
Combinatorial Particle Patterning

The unique properties of solid particles make them a promising element of micro‐ and nanostructure technologies. Solid particles can be used as building blocks for micro and nanostructures, carriers of monomers, or catalysts. The possibility of patterning different kinds of particles on the same substrate opens the pathway for novel combinatorial designs and novel technologies. One of the examples of such technologies is the synthesis of peptide arrays with amino acid particles. This review examines the known methods of combinatorial particle patterning via static electrical and magnetic fields, laser radiation, patterning by synthesis, and particle patterning via chemically modified or microstructured surfaces.
Outer membrane protein subtypes of Haemophilus influenzae type b isolates causing invasive disease in Victoria, Australia, from 1988 to 1990

Outer membrane protein subtyping of 187 isolates of Haemophilus influenzae type b (Hib), isolated from children with invasive Hib disease in Victoria, Australia, showed that a single outer membrane protein subtype (1VA) was responsible for 83% of the infections. It was identical to that responsible for the majority of cases of invasive Hib disease in Europe.
Unobtrusive Estimation of Cardiorespiratory Fitness with Daily Activity in Healthy Young Men

Despite the importance of cardiorespiratory fitness, no practical method exists to estimate maximal oxygen consumption (VO2max) without a specific exercise protocol. We developed an estimation model of VO2max, using maximal activity energy expenditure (aEEmax) as a new feature to represent the level of physical activity. Electrocardiogram (ECG) and acceleration data were recorded for 4 days in 24 healthy young men, and reference VO2max levels were measured using the maximal exercise test. aEE was calculated using the measured acceleration data and body weight, while heart rate (HR) was extracted from the ECG signal. aEEmax was obtained using linear regression, with aEE and HR as input parameters. The VO2max was estimated from the aEEmax using multiple linear regression modeling in the training group (n = 16) and was verified in the test group (n = 8). High correlations between the estimated VO2max and the measured VO2max were identified in both groups, with a 15-hour recording being sufficient to produce a highly accurate VO2max estimate. Additional recording time did not significantly improve the accuracy of the estimation. Our VO2max estimation method provides a robust alternative to traditional approaches while only requiring minimal data acquisition time in daily life.
The Thalamus as a Low Pass Filter: Filtering at the Cellular Level does Not Equate with Filtering at the Network Level

In the mammalian central nervous system, most sensory information passes through primary sensory thalamic nuclei, however the consequence of this remains unclear. Various propositions exist, likening the thalamus to a gate, or a high pass filter. Here, using a simple leaky integrate and fire model based on physiological parameters, we show that the thalamus behaves akin to a low pass filter. Specifically, as individual cells in the thalamus rely on consistent drive to spike, stimuli that is rapidly and continuously changing over time such that it activates sensory cells with different receptive fields are unable to drive thalamic spiking. This means that thalamic encoding is robust to sensory noise, however it induces a lag in sensory representation. Thus, the thalamus stabilizes encoding of sensory information, at the cost of response rate.
Inscribed gasket fractal circular monopole antenna for UWB application

A novel planar ultra wideband (UWB) antenna using a third iteration Sierpinski gasket fractal shape with circular boundary is presented in this paper. Size reduction of the antenna is done by Sierpinski gasket fractal concept which offers 24% thinning and provides excellent bandwidth better than a equivalent circular monopole which is around 8 GHz (span from 3 to 11 GHz with VSWR<;2) corresponding to 114% impedance bandwidth. The band-rejection operation achieved at the WLAN (5.15-5.85GHz) band by adding defected ground structure (DGS) or slit in the ground plane. The measured antenna peak gain varies from 1.85 dBi to 6 dBi within the band and radiation patterns of the antenna are nearly omnidirectional. The simulated and measured results show good agreement with the UWB characteristic.
Induction of Host Gene Expression following Infection of Chicken Embryo Fibroblasts with Oncogenic Marek's Disease Virus

ABSTRACT Microarrays containing 1,126 nonredundant cDNAs selected from a chicken activated T-cell expressed sequence tag database (http://chickest.udel.edu ) were used to examine changes in host cell gene expression that accompany infection of chicken embryo fibroblasts (CEF) with Marek's disease virus (MDV). Host genes that were reproducibly induced by infection of CEF with the oncogenic RB1B strain of MDV included macrophage inflammatory protein, interferon response factor 1, interferon-inducible protein, quiescence-specific protein, thymic shared antigen 1, major histocompatibility complex (MHC) class I, MHC class II, β2-microglobulin, clusterin, interleukin-13 receptor alpha chain, ovotransferrin, a serine/threonine kinase, and avian leukosis virus subgroup J glycoprotein.
Lightning current measurement by differential loop for 110kV transmission line

The measurement of lightning current is essential to lightning protection in grid, because only if accurate amplitude and waveform of the lightning current is obtained can the correct lightning protection measures be taken. However, in a high voltage power system, it is almost impossible to measure directly the lightning currents accurately and safely. So aiming at solving the problem of accurate and safe measurement of the lightning current on the overhead transmission lines, the differential loop which has been widely used in the pulse power measurement technique is applied, and a new method of measurement which based on the principle of differential loop can measure the lightning current on overhead transmission lines contactless is used and improved considering the actual running conditions in the 110kV level of transmission line. In this essay, the principle of differential loop for measuring lightning current and the design of the detector are introduced. In laboratory by using the high impulse current generator to simulate the lightning currents, the experiment results show that: for the 1.4m measurement distance, through selecting appropriate size of differential loop and the number of turns, and choosing reasonable shielding, combined with self-integral, the measurement sensor can reflect the waveform and the amplitude of the currents which is produced by the high impulse current generator accurately, and has the advantage of safety, strong anti-interference, well linearity and accuracy.
Hand Tremor Based Biometric Recognition Using Leap Motion Device

In this paper, the applicability of hand tremor-based biometric recognition via leap motion device is investigated. The hypothesis is that the hand tremor is unique for humans and can be utilized as a biometric identification. In order to verify our hypothesis, spatiotemporal hand tremor signals are acquired from subjects. The objective is to establish a live and secure identification system to avoid mimic and cloning of password by attackers. Various feature extraction methods, including statistical, fast Fourier transform, discrete wavelet transform, and 1-D local binary pattern are used. For evaluating recognition performance, Naïve Bayes and Multi-Layer Perceptron are utilized as linear-simple and nonlinear-complex classifiers, respectively. Since the conducted experiments produced promising results (above 95% of classification accuracy rate), it is considered that the proposed approach has the potential to be used as a new biometric identification manner in the field of security.
Role of Lysyl oxidase-like 1 gene polymorphisms in Pakistani patients with pseudoexfoliative glaucoma

Purpose Single nucleotide polymorphisms (SNPs) rs1048661 (p.R141L) and rs3825942 (p.G153D) in the lysyl oxidase-like 1 (LOXL1) gene have been previously reported to be associated with pseudoexfoliation glaucoma (PEXG) in various Asian and European populations, but these SNPs have not yet been studied in the Pakistani population. Therefore the aim of the present study was to investigate the association of these two coding LOXL1 SNPs in Pakistani PEXG patients. Methods One hundred twenty-eight Pakistani patients diagnosed with PEXG and 180 healthy controls were recruited for the study. Genomic DNA was extracted and both SNPs were genotyped by direct sequencing. Association of genotype and allele frequencies with PEXG were analyzed using the Chi-square (χ2) test. Results Genotype and allele frequencies of both rs1048661 and rs3825942 were found to be significantly associated with PEXG. The GG genotypes of both LOXL1 SNPs were associated with an increased risk of developing PEXG. In addition the G alleles of rs1048661 and rs3825942 confer an increased risk for PEXG with an odds ratio (OR) of 2.98 (95% CI 1.94–4.57) and OR 6.83 (95% CI 2.94–16.67), respectively. Conclusions A significant association was found for the G allele of rs1048661 and rs3825942 in PEXG patients of Pakistani origin.
Preparation of liposomes encapsulated Epirubicin-gold nanoparticles for Tumor specific delivery and release

Liposome/metal nanoparticle conjugates are found to be a promising carrier tool for effectively delivering wide variety of drugs in a targeted site and without arguing toxic side effects of existing anticancer drugs. In this scenario, the present work was performed to choose Epirubicin-HCl (EPI) as model anticancer drug to formulate citrate stabilized EPI-gold nanoparticles (EPI-GNPs). Further, the biocompatible EPI-GNPs incorporated with lipid bilayer of liposomes formulated to exhibit effective drug delivery system. The biosynthesized EPI-GNPs and its incorporation in a lipid bilayer of liposomes was confirmed by UV-visible spectrophotometer, drug encapsulation, loading capacity, pH stability and drug releasing capacity were studied. Simultaneously, drug and carrier interaction, physical nature, stability, morphological and particle size characteristics were also studied by FTIR, XRD, SEM, TEM and Zeta size analyzer. The obtained characterization data confirmed the properties of EPI-GNPs encapsulated liposomes. The in vitro cytotoxic screening of EPI-GNPs encapsulated liposomes arrest the proliferation of MCF-7 breast cancer cell lines, at 0.1 μg/ml of liposomes displayed 52% of cell death at 24 h. The EPI-GNPs encapsulated liposomes induced time and dose dependent apoptosis compared with untreated control cancer cells.
VC-dimension of exterior visibility

In this paper, we study the Vapnik-Chervonenkis (VC)-dimension of set systems arising in 2D polygonal and 3D polyhedral configurations where a subset consists of all points visible from one camera. In the past, it has been shown that the VC-dimension of planar visibility systems is bounded by 23 if the cameras are allowed to be anywhere inside a polygon without holes. Here, we consider the case of exterior visibility, where the cameras lie on a constrained area outside the polygon and have to observe the entire boundary. We present results for the cases of cameras lying on a circle containing a polygon (VC-dimension=2) or lying outside the convex hull of a polygon (VC-dimension=5). The main result of this paper concerns the 3D case: We prove that the VC-dimension is unbounded if the cameras lie on a sphere containing the polyhedron, hence the term exterior visibility.
Characterization of ZnO Thin Films

ZnO is a strategic material for various photonic applications. We present our results on characterization of thin films of ZnO grown by sol-gel spin and RF sputtering methods. The characterization techniques involved ellipsometry, scanning electron microscopy with energy dispersive analysis, X-ray diffraction and scanning tunneling microscopy. Microstructural characterization of the films using zinc nitrate precursor has delineated many interesting features These morphologies are homogeneous and uniformly distributed on the entire film. The energy dispersive spectroscopic measurements carried out on the both types of morphologies, island and needles, have confirmed that the film composition is ZnO and preserve the crystal symmetry. After the nucleation, the growth lead to preferred crystallographic axes.
DE TRAVAIL THE EFFECT OF THE INCREMENTAL R & D TAX CREDIT ON THE PRIVATE FUNDING OF R & D : AN ECONOMETRIC EVALUATION ON FRENCH FIRM LEVEL DATA

We study, at the firm level, whether the incremental R&D tax credit increases the private funding of R&D. In order to answer this question, we use the yearly surveys of the Ministry of Research over the period 1993-2003, as well as the corresponding firm-level tax files. The main issue is whether the firms would have increased their R&D expenditures without this tax incentive. We make use of the Rubin methodology. In a first step, we study the determinants of the probability to benefit from the R&D tax credit, that is the selection process at work in the recipients’ sample. We find that the probability to obtain a R&D tax credit increases with the R&D/Sales ratio and decreases with the direct R&D subsidies. Once we have evaluated the probability to get the R&D tax credit, we are able to correct for the selection bias. In a second step, we evaluate the effect of the incremental R&D tax credit on the private funding of research (once subtracted the direct subsidies from all the ministries). We find that, overall, the tax credit adds to the private funding of R&D: 1 Euro of tax credit would give slightly more than one Euro of total R&D. We also find that the incremental R&D tax credit increases the growth of the number of researchers.
Land-Use Classification With Compressive Sensing Multifeature Fusion

In this letter, we formulate a land-use (LU) classification problem within a compressive sensing (CS) fusion framework. CS aims at providing a compact representation form after a given query image has been processed with an opportune feature extraction type. In particular, residuals are generated from the image reconstruction with dictionaries associated with the available set of possible LUs and gathered to form a single-feature image pattern. The patterns obtained from different types of features are then fused to provide the final LU estimate. Two simple fusion strategies are adopted for such purpose. As demonstrated by experiments ran on the basis of a public benchmark database, the proposed method can achieve substantial classification accuracy gains over reference methods.
Personalized Web-page Rendering System

Personalized rendering of web pages gives the users greater control to view only what they prefer. The goal of this work is to provide a tool that will let users customize the content on the pages. Our proposed model architecture learns user preferences through interaction and eventually learns to block content that is not of interest, or is ofiensive, to the user. This learning from interaction is achieved through a combination of reinforcement learning and data mining techniques. In this paper we look at customizing the rendering of advertisements. We provide the user a tool that customizes itself to their preferences, and blocks irrelevant advertisements and allow only those that are of interest to the user. We also demonstrate empirically that our tool customizes itself to hypothetical hand crafted users.
Geometric stable processes and related fractional differential equations

We are interested in the differential equations satisfied by the density of the Geometric Stable processes $\mathcal{G}_{\alpha }^{\beta }=\left\{\mathcal{G}_{\alpha }^{\beta }(t);t\geq 0\right\} $, with stability \ index $\alpha \in (0,2]$ and symmetry parameter $\beta \in \lbrack -1,1]$, both in the univariate and in the multivariate cases. We resort to their representation as compositions of stable processes with an independent Gamma subordinator. As a preliminary result, we prove that the latter is governed by a differential equation expressed by means of the shift operator. As a consequence, we obtain the space-fractional equation satisfied by the density of $\mathcal{G}_{\alpha }^{\beta }$. For some particular values of $\alpha $ and $\beta $, we get some interesting results linked to well-known processes, such as the Variance Gamma process and the first passage time of the Brownian motion.
Structural and Mechanical Behaviour of Al-Fe Intermetallics

In this chapter, results of our recent investigations on Al-25%Fe (at.%), Al-30%Fe and Al-34.5%Fe alloys close to Al 3 Fe, Al 5 Fe 2 and Al 2 Fe intermetallic phases have been discussed. The effect of process parameters on structural aspects and mechanical behaviour of Al-Fe intermetallics has been studied. The high melting intermetallics that are difficult to prepare by conventional processing technique are easily synthesized in nanocrystalline state with a homogeneous structure by mechanical means. In this process, we have come out with a single orthorhombic Al 5 Fe 2 nanocrystalline intermetallic phase. Hardness measurements of intermetallic revealed an increase in hardness with a decreasing grain size up to a critical grain size, followed by a decrease. A decrease in hardness with a grain size refinement, an indication of softening behaviour, demonstrating the Inverse Hall-Petch (IHP)-like phenomenon has been observed in intermetallic compounds. The deviation from the regular Hall- Petch (HP) behaviour has been discussed using various deformation models based on the dislocations and grain boundary-mediated processes. The study is focused on investigations of Al-rich iron aluminide intermetallics to understand the structure property correlations.
Pushing the limits of OWL 2 reasoners in ontology alignment repair problems

Ontologies play a key role in the development of the Semantic Web and are being used in many diverse application domains such as biomedicine and e-commerce. An application domain may have been modeled according to different points of view and purposes. This situation usually leads to the development of different ontologies that intuitively overlap, but that use different naming and modeling conventions. The problem of (semi-)automatically integrating independently developed ontologies through mappings, is usually referred to as the ontology matching problem. Ontology matching systems, however, rely on lexical and structural heuristics, and the integration of the input ontologies and the mappings may lead to many undesired logical consequences, which could sensibly diminish their usefulness. The present paper, on the one hand aims at veryfing the hypothesis that classification of large ontologies via mappings still poses a challenge to OWL 2 reasoners. On the other it also explores the applicability of OWL 2 reasoning for the repair of unintended entailments (namely, unsatisfiable concepts or violations of the conservativity principle). In this paper we provide an update on the feasibility of using OWL 2 reasoners to repair the integration of ontologies via mappings, providing a more accurate evaluation of the feasibility of extracting all the justifications. Additionally, the current evaluation also encompasses the analysis of the use of OWL 2 reasoners for solving the violations of the so-called conservativity principle.
A Framework for Genetic Algorithms Based on Hadoop

Genetic Algorithms (GAs) are powerful metaheuristic techniques mostly used in many real-world applications. The sequential execution of GAs requires considerable computational power both in time and resources. Nevertheless, GAs are naturally parallel and accessing a parallel platform such as Cloud is easy and cheap. Apache Hadoop is one of the common services that can be used for parallel applications. However, using Hadoop to develop a parallel version of GAs is not simple without facing its inner workings. Even though some sequential frameworks for GAs already exist, there is no framework supporting the development of GA applications that can be executed in parallel. In this paper is described a framework for parallel GAs on the Hadoop platform, following the paradigm of MapReduce. The main purpose of this framework is to allow the user to focus on the aspects of GA that are specific to the problem to be addressed, being sure that this task is going to be correctly executed on the Cloud with a good performance. The framework has been also exploited to develop an application for Feature Subset Selection problem. A preliminary analysis of the performance of the developed GA application has been performed using three datasets and shown very promising performance.
Tango or Waltz?: Putting Ballroom Dance Style into Tempo Detection

Rhythmic information plays an important role in Music Information Retrieval. Example applications include automatically annotating large databases by genre, meter, ballroom dance style or tempo, fully automated D.J.-ing, and audio segmentation for further retrieval tasks such as automatic chord labeling. In this article, we therefore provide an introductory overview over basic and current principles of tempo detection. Subsequently, we show how to improve on these by inclusion of ballroom dance style recognition. We introduce a feature set of 82 rhythmic features for rhythm analysis on real audio. With this set, data-driven identification of the meter and ballroom dance style, employing support vector machines, is carried out in a first step. Next, this information is used to more robustly detect tempo. We evaluate the suggested method on a large public database containing 1.8 k titles of standard and Latin ballroom dance music. Following extensive test runs, a clear boost in performance can be reported.
A process and temperature tolerant oscillator-based true random number generator with dynamic 0/1 bias correction

This paper presents an oscillator-based true random number generator (TRNG) that dynamically unbiases 0/1 probability. The proposed TRNG automatically adjusts the duty cycle of a fast oscillator to 50 %, and generates unbiased random numbers tolerating process variation and dynamic temperature fluctuation. A prototype chip of the proposed TRNG was fabricated with a 65 nm CMOS process. Measurement results show that the developed duty cycle monitor obtained the probability of `1' 4,100 times faster than the conventional output bit observation, or estimated the probability with 70 times higher accuracy. The proposed TRNG adjusted the probability of `1' to within 50±0.07 % in five chips in the temperature range of 0 °C to 75 °C. Consequently, the proposed TRNG passed the NIST and DIEHARD tests at 7.5 Mbps with 6,670 μm2 area.