Miracle-dz/UniFAR-FTUs huggingface dataset:
A compact discriminative representation for efficient image-set classification with application to biometric recognition

We present a simple yet compact and discriminative representation for image sets which can efficiently be used for image-set based object classification. For each image-set we compute a global covariance matrix which captures correlated variations in all image-set dimensions. Without loss of information, we compact the covariance matrix into a lower triangular matrix by using Cholesky decomposition. While preserving discrimination capability of the representation, we obtain further compression by applying Multiple Discriminant Analysis. As a result, we are able to represent image sets containing N samples each of dimensionality d by a single vector whose dimensionality is ≪ N d. We apply the proposed representation to various biometric applications such as image-set based face recognition and person identification using image-sets of periocular regions. To show that our representation is generic, we also report results for image-set based object categorization. We observe improved accuracy and significant speedup over the current state-of-the-art techniques on standard datasets.
Run with me: designing storytelling tools for runners

In this paper we explore storytelling tools for runners. We believe sharing third person 360-degree live-streams and stories while running can be a motivational factor to get people more active. To this end, we conducted a couple of initial user tests, exploring if live-streaming runs on popular streaming sites can be engaging for the audience. To make the streams more immersive, we experiment with 360 degree and third person view. We present and evaluate an initial hardware setup for 360-degree video streaming running stories.
Influence of a computer database and problem exercises on students' knowledge of bacteriology

This study compared the performances of students at the University of North Carolina at Chapel Hill School of Medicine who had access to sets of problem exercises and a computer database to support their learning of bacteriology with the performances of students at the University of Iowa College of Medicine who did not have such access. The study also examined the extent of a student's database use as a predictor of posttest performance. The students studied were randomly selected groups of 32–44 first-year students per year at each school; the study was conducted in three academic years (1988–1990) with some modifications in the intervention as the host environment evolved. The criterion measure was a posttest created from the same pool of problems used to generate the problem sets. The students at the intervention school scored significantly higher on the posttest in two of the three years, and overall. Also in two of the three years and overall, there was a significant relationship between the extent of a student's database use and his or her posttest score. Although the observed effects may have been due to other factors in this quasi-experimental design, the authors conclude that the use of problem sets and a computer database had a positive influence on the students' learning.
Development of the estonian speechdat-like database

A new database project has been launched in Estonia last year. It aims the collection of telephone speech from a large number of speakers for speech and speaker recognition purposes. Up to 2000 speakers are expected to participate in recordings. SpeechDat databases, especially Finnish SpeechDat, have been chosen as a prototype for the Estonian database. It means that principles of corpus design, file formats, recording and labelling methods implemented by the SpeechDat consortium will be followed as closely as possible. The paper is a progress report of the project.
Effect of avidin on channel kinetics of biotinylated gramicidin.

Membrane protein functioning basically depends on the supramolecular structure of the proteins which can be modulated by specific interactions with external ligands. The effect of a water-soluble protein bearing specific binding sites on the kinetics of ionic channels formed by gramicidin A (gA) in planar bilayer lipid membranes (BLM) has been studied using three independent approaches: (1) sensitized photoinactivation, (2) single-channel, and (3) autocorrelation measurements of current fluctuations. As shown previously [Rokitskaya, T. I. , et al. (1996) Biochim. Biophys. Acta 1275, 221], the time course of the flash-induced current decrease in most cases follows a single-exponential decay with an exponential factor (tau) that corresponds to the gA single-channel lifetime. Addition of avidin does not affect tau for gA channels, but causes a dramatic increase in tau for channels formed by gA5XB, a biotinylated analogue of gA. This effect is reversed by addition of an excess of biotin to the bathing solution. The average single-channel duration of gA5XB was about 3.6 s as revealed by single-channel recording of the BLM current. After prolonged incubation with avidin, a long-lasting open state of the gA5XB channel appeared which did not close for more than 10 min. The data on gA5XB photoinactivation kinetics and single-channel measurements were confirmed by analysis of the corresponding power spectra of the current fluctuations obtained in the control, in the presence of avidin, and after the addition of biotin. We infer that avidin produces a deceleration of gA5XB channel kinetics by motional restriction of gA5XB monomers and dimers upon the formation of avidin and gA5XB complexes, which would stabilize the channel state and thus increase the single-channel lifetime.
A hybrid COA$ε$-constraint method for solving multi-objective problems

In this paper, a hybrid method for solving multi-objective problem has been provided. The proposed method is combining the {\epsilon}-Constraint and the Cuckoo algorithm. First the multi objective problem transfers into a single-objective problem using $\epsilon$-Constraint, then the Cuckoo optimization algorithm will optimize the problem in each task. At last the optimized Pareto frontier will be drawn. The advantage of this method is the high accuracy and the dispersion of its Pareto frontier. In order to testing the efficiency of the suggested method, a lot of test problems have been solved using this method. Comparing the results of this method with the results of other similar methods shows that the Cuckoo algorithm is more suitable for solving the multi-objective problems.
Rehabilitation Program for Caregivers about Patients’ Post Autologous Bone Marrow Transplantation

Approximately 50 000 people undergo BMTs each year worldwide. With the move to more outpatient and home care, family caregivers are playing an ever-increasing role. However, there is little information regarding the needs and well-being of caregivers of individuals undergoing BMT. In Egypt, according to medical records of Sheikh Zayed Specialized Hospital, (2013). 390 cases of autologous transplant were carried out during the last 3 years in bone marrow transplantation unit. 75% of individuals receiving autologous transplants were between the ages of 21-50 years. The main source of support for patients is often their family as having access to this support which is important for patient outcomes. The community health nurse role includes assessing patients‟ needs to identify expectations of the patients and anticipate impact on family, providing psychosocial support and education during rehabilitation. Assessment and interventions are needed to support the sexual dysfunction and infertility as are major concern, monitoring the patient‟s condition with thorough physical assessments, assisting the patients and families to take responsibility for establishing, maintaining, and improving their health by adding to their knowledge and ability to influence health determinants. Specific information on how family can carry out these roles during rehabilitation encourages the adoption of health beliefs, attitudes, and behaviors that contribute to the overall health of the population.
IsomiR expression patterns in canonical and Dicer-independent microRNAs

Multiple microRNA (miRNA) variants, known as isomiRs, are extensively distributed in miRNA loci and predominantly derive from the alternative cleavage of Drosha/Dicer and 3′addition events. The present study aimed to investigate the expression patterns of multiple isomiRs in typical miRNA and Dicer-independent miRNA loci by conducting evolutionary and expression analysis using public datasets. Although different miRNA maturation processes exist, multiple isomiRs can be detected by similar expression distributions. However, isomiR expression in Dicer-independent miRNA loci tends to be at a moderate level, particularly for random distribution in the ends that are split by Dicer in the typical miRNA loci. Compared with the mature miRNA locus (dominant miRNA locus), the non-dominant miRNA locus indicates an expression distribution similar to that of the Dicer-independent miRNA locus. These results increase the understanding of multiple isomiRs in the progression of diseases.
Molecular analysis of an odorant-binding protein gene in two sympatric species of Lutzomyia longipalpis s.l.

Lutzomyia longipalpis s.l. is the main vector of American visceral leishmaniasis (AVL) and occurs as a species complex. DNA samples from two Brazilian sympatric species that differ in pheromone and courtship song production were used to analyse molecular polymorphisms in an odorant-binding protein ( obp29 ) gene. OBPs are proteins related to olfaction and are involved in activities fundamental to survival, such as foraging, mating and choice of oviposition site. In this study, the marker obp29 was found to be highly polymorphic in Lu. longipalpis s.l. , with no fixed differences observed between the two species. A pairwise fixation index test indicated a moderate level of genetic differentiation between the samples analysed.
Document compression using rate-distortion optimized segmentation

Effective document compression algorithms require that scanned document images be first segmented into regions such as text, pictures, and background. In this paper, we present a multilayer compression algorithm for document images. This compression al- gorithm first segments a scanned document image into different classes, then compresses each class using an algorithm specifically designed for that class. Two algorithms are investigated for seg- menting document images: a direct image segmentation algorithm called the trainable sequential MAP (TSMAP) segmentation algo- rithm, and a rate-distortion optimized segmentation (RDOS) algo- rithm. The RDOS algorithm works in a closed loop fashion by apply- ing each coding method to each region of the document and then selecting the method that yields the best rate-distortion trade-off. Compared with the TSMAP algorithm, the RDOS algorithm can of- ten result in a better rate-distortion trade-off, and produce more ro- bust segmentations by eliminating those misclassifications which can cause severe artifacts. At similar bit rates, the multilayer com- pression algorithm using RDOS can achieve a much higher subjec- tive quality than state-of-the-art compression algorithms, such as DjVu and SPIHT. © 2001 SPIE and IS&T. (DOI: 10.1117/1.1344590)
Novel M-ary coded modulation scheme based on constellation subset selection

In this paper, a novel adaptive coded-modulation scheme, namely M-ary coded modulation, which is spectrally-efficient and can facilitate variable data-rates, is proposed to meet different quality-of-service (QoS) requirements for wireless multimedia applications. An efficient constellation subset selection algorithm incorporated with a novel M-ary coding technique is proposed to generate convolutional codes for different constellation subsets. The studies on the theoretical and practical aspects of our proposed adaptive coded-modulation scheme are presented. Compared with other existing adaptive coded-modulation methods, our scheme offers more flexibilities. According to Monte Carlo simulation results, our new M-ary coded-modulation scheme not only can satisfy the predetermined symbol-error-rate (SER) requirement, but also can significantly enhance the communication quality in terms of bit error rate and throughput.
A SUPERVISORY ROBUST ADAPTIVE FUZZY CONTROLLER

Abstract A fuzzy controller equipped with an adaptive algorithm and two supervisors is developed in this work to achieve tracking performances for a class of uncertain nonlinear single input single output (SISO) systems with external disturbances. The convergence of the training algorithm is guarantied by a gradient projection law. The effect of both the approximation errors and the external disturbances is attenuated to a prescribed level thanks to H∞ control. The convergence of the tracking error toward zero is guarantied by a supervisor where linguistic rules are used to accelerate the convergence speed.
A highly porous nafion membrane templated from polyoxometalates-based supramolecule composite for ion-exchange polymer-metal composite actuator

This paper reports a new technique for fabricating a highly porous hybrid SiO2/Nafion membrane, from which a high electromechanical performance ion-exchange polymer-metal composite (IPMC) actuator is achieved. This technique uses polyoxometalate (POM)-based supramolecule composite carried by amorphous SiO2 particles to form a hybrid membrane with the polar Nafion ionomer. The resultant composite (POM-Nafion) is then incubated and degraded in a base solution, forming a porous membrane. Attenuated total reflectance fourier transform infrared spectroscopy (ATR-FTIR) and scanning electron microscopy (SEM) were used to monitor the degradation process. ATR-FTIR results demonstrated that the POM-based composite was removed while SiO2 remained in the porous membrane after degradation. SEM images showed that there were a great quantity of channels with sizes of 0.4–1.4 μm and pores with sizes of 300–700 nm in the newly-formed porous Si-Nafion membrane. With the same Nafion content, the porous Si-Nafion membrane and self-casting Nafion membrane were both made into IPMC actuators. A laser displacement sensor, a force sensor and a high speed camera were assembled into a measurement system to evaluate the performance of the IPMC actuator. Results showed that the maximum blocking forces from the Si-Nafion membrane actuator were 3.78 g for 2.5 V driving voltage and 2.39 g for 1.5 V, which increase by 2.97 and 4.19 times, respectively, when compared to the self-casting Nafion membrane actuator. The maximum displacement outputs were 7.2 mm for 2.5 V driving voltage and 5.9 mm for 1.5 V. Compared to the self-casting Nafion membrane actuator, these outputs increased by 4.8 and 9.7 times, respectively. When actuated in the air, the Si-Nafion membrane actuator exhibited stable working time of 480 s and 710 s for the voltages of 2.5 V and 1.5 V, respectively. Compared to the self-casting Nafion membrane actuator, these data increased by 4.36 and 2.22 times, respectively.
Development of correlation-based process characteristics visualization method and its application to fault detection

Although process monitoring is important for maintaining safety and product quality, it is difficult to understand process characteristics particularly when they are changing. Since the correlation among variables changes due to changes in process characteristics, process data visualization based on the correlation among variables helps process characteristic understanding. In the present work, a new correlation-based data visualization method is proposed by integrating joint decorrelation (JD) and stochastic proximity embedding (SPE). JD is a blind source separation (BSS) method that can separates sample based on the correlation, and SPE is a self-organizing algorithm that can map high-dimensional data to a two-dimensional plane. The proposed method, referred to as JD-SPE, separates samples based on the correlation using JD and the separated samples are visualized in the two-dimensional plane by SPE. Correlation matrices have to be constructed before sample separation for JD; however how to construct them is not clear. The present work also proposes a correlation matrix construction method for JD by using nearest correlation spectral clustering (NCSC), which is a correlation-based clustering method. In addition, a new process monitoring method based on multivariate statistical process control (MSPC) which is a well-known process monitoring algorithm and JD-SPE. This monitoring method is referred to as JD-SPE-r2. The proposed JD-SPE-Γ2 can detect a fault that can not detected by the conventional MSPC. The usefulness of the proposed methods is demonstrated through numerical examples.
Software Evolution Prediction Using Seasonal Time Analysis: A Comparative Study

Prediction models of software change requests are useful for supporting rational and timely resource allocation to the evolution process. In this paper we use a time series forecasting model to predict software maintenance and evolution requests in an open source software project (Eclipse), as an example of projects with seasonal release cycles. We build an ARIMA model based on data collected from Eclipse's change request tracking system since the project's start. A change request may refer to defects found in the software, but also to suggested improvements in the system under scrutiny. Our model includes the identification of seasonal patterns and tendencies, and is validated through the forecast of the change requests evolution for the next 12 months. The usage of seasonal information significantly improves the estimation ability of this model, when compared to other ARIMA models found in the literature, and does so for a much longer estimation period. Being able to accurately forecast the change requests' evolution over a fairly long time period is an important ability for enabling adequate process control in maintenance activities, and facilitates effort estimation and timely resources allocation. The approach presented in this paper is suitable for projects with a relatively long history, as the model building process relies on historic data.
Potential for the Anopheles gambiae Densonucleosis Virus To Act as an “Evolution-Proof” Biopesticide

ABSTRACT “Evolution-proof” or “late-life-acting” insecticides (LLAIs) preferentially kill older adult mosquitoes and are of extreme interest to control vector-borne diseases such as malaria. We used quantitative PCR to assess whether the Anopheles gambiae densonucleosis virus (AgDNV) had potential as an LLAI. After infection, AgDNV titers increased modestly during larval development but replicated slower than the host cells, resulting in a significant decrease in the normalized virus titer during larval and pupal development. Normalized virus titers dramatically increased after adult emergence, peaking in 7- to 10-day-old adults. Unlike other DNVs, AgDNV does not significantly replicate in preadult mosquitoes but rather preferentially replicates in older adults. The natural dynamics of AgDNV make it ideal for expression of insect-specific toxin genes as a biological LLAI.
Inhibition of Protein Palmitoylation, Raft Localization, and T Cell Signaling by 2-Bromopalmitate and Polyunsaturated Fatty Acids*

The ability of the Src family kinases Fyn and Lck to participate in signaling through the T cell receptor is critically dependent on their dual fatty acylation with myristate and palmitate. Here we identify a palmitate analog, 2-bromopalmitate, that effectively blocks Fyn fatty acylation in general and palmitoylation in particular. Treatment of COS-1 cells with 2-bromopalmitate blocked myristoylation and palmitoylation of Fyn and inhibited membrane binding and localization of Fyn to detergent-resistant membranes (DRMs). In Jurkat T cells, 2-bromopalmitate blocked localization of the endogenous palmitoylated proteins Fyn, Lck, and LAT to DRMs. This resulted in impaired signaling through the T cell receptor as evidenced by reductions in tyrosine phosphorylation, calcium release, and activation of mitogen-activated protein kinase. We also examined the ability of long chain polyunsaturated fatty acids (PUFAs) to inhibit protein fatty acylation. PUFAs have been reported to inhibit T cell signaling by excluding Src family kinases from DRMs. Here we show that the PUFAs arachidonic acid and eicosapentaenoic acid inhibit Fyn palmitoylation and consequently block Fyn localization to DRMs. We propose that inhibition of protein palmitoylation represents a novel mechanism by which PUFAs exert their immunosuppressive effects.
Understanding the Influences of EEG Reference: A Large-Scale Brain Network Perspective

The influence of reference is a critical issue for the electroencephalography (EEG) and event-related potentials (ERPs) studies. However, previous investigations concentrated less on the location of source at a systematic neuroscience level. Our goal was to examine the EEG signal associated with the locations from a common network parcellation of the human brain function, offering a system perspective of the influence of EEG reference. In our simulation, vertices uniformly distributed in eight large-scale brain networks were adopted to generate the scalp EEG. The brain networks contain the visual, somatomotor, dorsal attention, ventral attention, limbic, frontoparietal, default networks, and the deep brain structure. The distributions of the most sensitive and neutral electrodes were calculated for each network based on the lead-field matrix. While the most sensitive electrode had a network-specific symmetric pattern, the electrodes in scalp surface had approximately equal chance to be the most neutral electrode. Simulated data were referenced at the FCz, the Oz, the mean mastoids (MM), the average (AVE), and the infinity reference obtained by the reference electrode standardization technique (REST). Intriguingly, the relative error followed the pattern REST<AVE<MM<(FCz, Oz), regardless of the number of electrodes and signal-to-noise ratios. Our findings suggested that REST was a potentially preferable reference for all large-scale networks and AVE virtually performed as REST under several conditions. As EEG and ERPs experiments within the same behavioral domain always have activations in some specific brain networks, the comparisons revealed here may provide a valuable recommendation for reference selection in clinical and basic researches.
Atomistic study of hydrogen distributions around lattice defects and defect energies under hydrogen environment

It is well known that hydrogen atoms and lattice defects have strong interactions and mechanical properties of metals are significantly changed under hydrogen environment. It has been reported that hydrogen stabilizes vacancies [1, 2], and changes the mobility of dislocations [3-5]. Furthermore, the hydrogen distribution is strongly influenced by the stress fields [3-6]. In order to advance our understanding about hydrogen related fractures of metals, it is essentially important to reveal the hydrogen distributions around various lattice defects and the hydrogen effects on defect-formation and defect-motion.
An Adaptive Particle Swarm Optimizer Using Balanced Explorative and Exploitative Behaviors

Particle Swarm Optimization (PSO) has recently emerged as a nature inspired algorithm for real parameter optimization. This article describes a method for improving the final accuracy and the convergence speed of PSO by adding a new coefficient to the position updating equation and modulating the inertia weight. This work also mathematically analyzes the effect of this modification on the PSO algorithm. The new algorithm has been shown to be statistically significantly better than four recent variants of PSO on a six functions test suite.