Miracle-dz/UniFAR-FTUs huggingface dataset:
Each averaging technique yields reliable a posteriori error control in FEM on unstructured grids. Part I: Low order conforming, nonconforming, and mixed FEM

Averaging techniques are popular tools in adaptive finite element methods for the numerical treatment of second order partial differential equations since they provide efficient a posteriori error estimates by a simple postprocessing. In this paper, their reliablility is shown for conforming, nonconforming, and mixed low order finite element methods in a model situation: the Laplace equation with mixed boundary conditions. Emphasis is on possibly unstructured grids, nonsmoothness of exact solutions, and a wide class of averaging techniques. Theoretical and numerical evidence supports that the reliability is up to the smoothness of given right-hand sides.
Development and Evaluation of an Improved Technique for Pulmonary Function Testing Using Electrical Impedance Pneumography Intended for the Diagnosis of Chronic Obstructive Pulmonary Disease Patients

Spirometry is regarded as the only effective method for detecting pulmonary function test (PFT) indices. In this study, a novel impedance pulmonary function measurement system (IPFS) is developed for directly assessing PFT indices. IPFS can obtain high resolution values and remove motion artifacts through real-time base impedance feedback. Feedback enables the detection of PFT indices using only both hands for convenience. IPFS showed no differences in the sitting, supine, and standing postures during the measurements, indicating that patient posture has no effect on IPFS. Mean distance analysis showed good agreement between the volume and flow signal of IPFS (p < 0.05). PFT indices were detected in subjects to differentiate a chronic obstructive pulmonary disease (COPD) patient group from a normal group. The forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), FEV1/FVC, and peak expiratory flow (PEF) in the COPD group were lower than those in the normal group by IPFS (p < 0.05). IPFS is therefore suitable for evaluating pulmonary function in normal and COPD patients. Moreover, IPFS could be useful for periodic monitoring of existing patients diagnosed with obstructive lung disease.
Dynamic miss-counting algorithms: finding implication and similarity rules with confidence pruning

Dynamic miss-counting (DMC) algorithms are proposed which find all implication and similarity rules with confidence pruning but without support pruning. To handle data sets with a large number of columns, we propose dynamic pruning techniques that can be applied during data scanning. DMC counts the numbers of rows in which each pair of columns disagree instead of counting the number of hits. DMC deletes a candidate as soon as the number of misses exceeds the maximum number of misses allowed for that pair. We also propose several optimization techniques that reduce the required memory size significantly. We evaluated our algorithms by using four data sets, viz. Web access logs, a Web page-link graph, news documents and a dictionary. These data sets have between 74,000 and 700,000 items. Experiments show that DMC can find high-confidence rules for such large data sets efficiently.
A comprehensive experimental analysis of standard TCP variants in vehicular environment

Efforts were made to integrate emerging Vehicular Ad-hoc Network (VANETs) with the mobile internet architecture through Road Side Unit (RSU) to enhance its operational capabilities for safety and non safety applications. Transmission Control Protocol (TCP) is one of the prominent protocol that contributes a considerable amount of internet traffic as the vast majority of internet applications such as file transfer, messaging service, mail services, etc. was based on TCP. However, TCP performs poorly under vehicular wireless environment due to its high mobility and wireless errors such as fading and interferences that lead to unpredicted packet drop. In this paper the behavioral aspects of existing standard TCP variants such as Vegas, Compound, Westwood, New Reno, BIC and CUBIC were rigorously tested and analyzed under vehicular environment for variable speed and traffic. This analysis forms a foundation work in designing TCP exclusively for vehicular environment.
The Effect of Pro-Neurogenic Gene Expression on Adult Subventricular Zone Precursor Cell Recruitment and Fate Determination After Excitotoxic Brain Injury

Despite the presence of on-going neurogenesis in the adult mammalian brain, neurons are generally not replaced after injury. Using a rodent model of excitotoxic cell loss and retroviral (RV) lineage tracing, we previously demonstrated transient recruitment of precursor cells from the subventricular zone (SVZ) into the lesioned striatum. In the current study we determined that these cells included migratory neuroblasts and oligodendrocyte precursor cells (OPC), with the predominant response from glial cells. We attempted to override this glial response by ectopic expression of the pro-neurogenic genes Pax6 or Dlx2 in the adult rat SVZ following quinolinic acid lesioning. RV-Dlx2 over-expression stimulated repair at a previously non-neurogenic time point by enhancing neuroblast recruitment and the percentage of cells that retained a neuronal fate within the lesioned area, compared to RV-GFP controls. RV-Pax6 expression was unsuccessful at inhibiting glial fate and intriguingly, increased OPC cell numbers with no change in neuronal recruitment. These findings suggest that gene choice is important when attempting to augment endogenous repair as the lesioned environment can overcome pro-neurogenic gene expression. Dlx2 over-expression however was able to partially overcome an anti-neuronal environment and therefore is a promising candidate for further study of striatal regeneration.
Robust Takagi-Sugeno Fuzzy Speed Regulator for DC Series Motors

This paper presents the design of fuzzy logic based speed regulator for DC series motor. A Takagi-Sugeno (TS) fuzzy model of DC series motor considering parametric uncertainty is first constructed using sector nonlinearity and set of operating point techniques. An integral state is then introduced in each fuzzy plant sub-model to guarantee exact tracking of speed commands. A parallel distributed compensation (PDC) controller under H-, decay rate and control input constraints, is finally designed for the augmented system to regulate the motor speed in the presence of load torque and parameter variations. MATLAB simulations are performed to prove the effectiveness of the proposed regulator.
Newly assembled microtubules are concentrated in the proximal and distal regions of growing axons

We have investigated the sites of microtubule (MT) assembly in neurons during axon growth by taking advantage of the relationship between the proportion of tyrosinated alpha-tubulin (tyr-tubulin) in MTs and their age. Specifically, young (newly assembled) MTs contain more tyr-tubulin than older (more long-lived) MTs. To quantify the relative proportion of tyr-tubulin in MTs, cultured rat sympathetic neurons were permeabilized under conditions that stabilize existing MTs and remove unassembled tubulin. The MTs were then double-stained with antibodies to tyr-tubulin (as a measure of the amount of tyr-tubulin in MTs) and to beta-tubulin (as a measure of total MT mass), using immunofluorescence procedures. Cells were imaged with a cooled charge- coupled device camera and the relative proportion of tyr-tubulin in the MTs was quantified by computing the ratio of the tyr-tubulin fluorescence to the beta-tubulin fluorescence using a novel application of digital image processing and analysis techniques. The amount of tyr- tubulin in the MTs was highest in the cell body and at the growth cone; peak ratios in these two regions were approximately 10-fold higher than for the axon shaft. Moving out from the cell body into the axon, the tyr-tubulin content declined over an average distance of 40 microns to reach a constant low value within the axon shaft and then rose again more distally, over an average distance of 110 microns, to reach a peak at the growth cone (average axon length = 358 microns). These observations indicate that newly assembled MTs are concentrated in the proximal and distal regions of growing axons and therefore that the cell body and growth cone are the most active sites of MT assembly dynamics in neurons that are actively extending axons.
Iris Pattern Classification Combining Orientation Recognition

The importance of personal authentication is gradually increasing with the development of the information society. Biometrics identification technology plays an important role in cyberspace. Unlike other biometrics such as the face or fingerprints, iris recognition has high reliability for personal identification. Iris recognition methods are classified into four categories: the phase-based method (Daugman, 1993), the zero-crossing representation-based method (Boles and Boashash, 1998; Sanchez-Avila and Sanchez-Reillo, 2005), the texture-based method (Wildes, 1997; Ma et al., 2003), and local intensity variation (Ma et al., 2004, a;b). Using the internal CASIA dataset (CBSR, 2005), Ma et al. evaluates the proposed algorithm by comparing the performance of other iris recognition methods proposed by Daugman, Wildes, and Boles and Boashash (Ma et al., 2004, b). The experimental results show the equal error rates (EER) of respective algorithms (Ma, Daugman, Wildes, and Boles) are 0.07%, 0.08%, 1.76%, and 8.13%, respectively. In other studies, the Daugman’s method which is a representative algorithm of iris recognition is also evaluated using the subset of internal CASIA dataset (Sun et al., 2006) and the CASIA iris image 1.0 database (Wang et al., 2007), which is available from the CASIA web site. The EERs of Daugman’s method reported in Sun et al. and Wang et al. are 0.70% and 0.67%, respectively. These analysis indicate the high accuracy of recognition performance although the EERs of Daugman’s method described in these papers are not the same because the iris segmentation method including eyelid and eyelash detection would not be exactly the same. Iris recognition technology are applied in various fields. Especially, the iris recognition algorithm embedded on a mobile phone requires robustness to rotation changes because capturing the iris pattern by a hand using a camera built in the mobile phone causes the rotation changes. However, the iris recognition methods described above are generally fragile in rotation variation. We previously proposed a rotation spreading neural network (R-SAN net) that focused on spatial recognition/memory systems (parietal cortex(PG)) in the brain and recognized an object’s orientation and shape (Nakamura et al., 1998; Yoshikawa and Nakamura, 2000). The R-SAN net can simultaneously recognize the orientation of the object irrespective of its shape, and the shape irrespective of its orientation. The characteristics of the R-SAN net are to use a two-dimensional input pattern in a polar coordinate system converted from the Cartesian coordinate system. The R-SAN net is suitable for the shape and orientation recognition of concentric circular patterns. The orientation recognition performance of R-SAN net allows the 10
THE ROLE OF HIGHER EDUCATION INSTITUTIONS IN ADDRESSING YOUTH UNEMPLOYMENT IN LEBANON

This qualitative study investigates how higher education institutions address youth unemployment in Lebanon. Using a descriptive study design, it maps out the issues and potential solutions within the environment the universities are embedded from the perspectives of leading policy makers in the field of higher education in the country. The policy perspectives of university rectors, government officials, and private sector employers are charted and then compared in relation to youth unemployment, jobless graduates and the higher education institutional role. The theoretical framework, which has been derived from the human capital literature and higher education institutional theories, guides analysis of interviews with institutional policymakers. The core study finding offers support for the compilation of fundamental data and official demographic statistics, which will influence any potential policy reform to be considered. Results suggest that there are differences and similarities between the different participant groups in identifying the roots, risks and responses to the problem of youth unemployment in the Lebanon. Additional findings point to a centrality of institutional role in the mitigation of the crisis of jobless graduates in the country. Among policy recommendations to follow the data compilation are joint efforts to address policy reform in the higher education subsector in Lebanon.
Unbiasing the Bootstrap — Bootknife Sampling vs . Smoothing

Bootstrap standard errors are generally biased downward, which is a primary reason that traditional bootstrap confidence intervals have coverage probability which is too low. For the sample mean the downward bias is a factor ofn−1 n (for the squared standard error); the same bias holds approximately for asymptotically-linear statistics. In the case of stratified or two-sample bootstrapping, the bias depends on the individual strata or sample sizes, not the combined total; hence the bias is substantial in situations with many small strata. We discuss two remedies. One, specifically for bootstrapping the sample mean, is to do a smoothed bootstrap, sampling from a kernel density estimate of the underlying distribution, with kernel width chosen to correct the bias. The second, more generallyapplicable, is “bootknife sampling,” in which bootstrap samples are drawn from jackknife samples. These provide more accurate inferences than ordinary bootstrap sampling – better confidence interval coverage and less-biased or unbiased standard errors. These methods are implemented in downloadable SPLUS software.
Molecular Cloning, Characterization and Predicted Structure of a Putative Copper-Zinc SOD from the Camel, Camelus dromedarius

Superoxide dismutase (SOD) is the first line of defense against oxidative stress induced by endogenous and/or exogenous factors and thus helps in maintaining the cellular integrity. Its activity is related to many diseases; so, it is of importance to study the structure and expression of SOD gene in an animal naturally exposed most of its life to the direct sunlight as a cause of oxidative stress. Arabian camel (one humped camel, Camelus dromedarius) is adapted to the widely varying desert climatic conditions that extremely changes during daily life in the Arabian Gulf. Studying the cSOD1 in C. dromedarius could help understand the impact of exposure to direct sunlight and desert life on the health status of such mammal. The full coding region of a putative CuZnSOD gene of C. dromedarius (cSOD1) was amplified by reverse transcription PCR and cloned for the first time (gene bank accession number for nucleotides and amino acids are JF758876 and AEF32527, respectively). The cDNA sequencing revealed an open reading frame of 459 nucleotides encoding a protein of 153 amino acids which is equal to the coding region of SOD1 gene and protein from many organisms. The calculated molecular weight and isoelectric point of cSOD1 was 15.7 kDa and 6.2, respectively. The level of expression of cSOD1 in different camel tissues (liver, kidney, spleen, lung and testis) was examined using Real Time-PCR. The highest level of cSOD1 transcript was found in the camel liver (represented as 100%) followed by testis (45%), kidney (13%), lung (11%) and spleen (10%), using 18S ribosomal subunit as endogenous control. The deduced amino acid sequence exhibited high similarity with Cebus apella (90%), Sus scrofa (88%), Cavia porcellus (88%), Mus musculus (88%), Macaca mulatta (87%), Pan troglodytes (87%), Homo sapiens (87%), Canis familiaris (86%), Bos taurus (86%), Pongo abelii (85%) and Equus caballus (82%). Phylogenetic analysis revealed that cSOD1 is grouped together with S. scrofa. The predicted 3D structure of cSOD1 showed high similarity with the human and bovine CuZnSOD homologues. The Root-mean-square deviation (rmsd) between cSOD1/hSOD1 and cSOD1/bSOD1 superimposed structure pairs were 0.557 and 0.425 A. The Q-score of cSOD1-hSOD1 and cSOD1-bSOD1 were 0.948 and 0.961, respectively.
Analysis and Improvement of the Fairness between Long-lived and Short-lived TCP Connections

Short-lived TCP connections, which transmit small documents, suffer from significant low throughput compared with long-lived TCP connections, which transmit large documents, because of an inherent nature of the ACK-based window flow control of TCP. In this paper, we focus on the unfairness problem of TCP connections transmitting differently sized documents. We first confirm the unfairness property through simple simulation results, and show the necessity of fairness improvement algorithms at the router buffer. To improve the fairness, we propose new algorithms, and investigate their effectiveness through simulation results. We show that our proposed algorithms can provide better fairness without degradation of the network utilization.
UNSUPERVISED MORPHOLOGICAL SEGMENTATION FOR STATISTICAL MACHINE TRANSLATION

Statistical Machine Translation (SMT) techniques often assume the word is the basic unit of analysis. These techniques work well when producing output in languages like English, which has simple morphology and hence few word forms, but tend to perform poorly on languages like Finnish with very complex morphological systems with a large vocabulary. This thesis examines various methods of augmenting SMT models to use morphological information to improve the quality of translation into morphologically rich languages, comparing them on an English-Finnish translation task. We investigate the use of the three main methods to integrate morphological awareness into SMT systems: factored models, segmented translation, and morphology generation models. We incorporate previously proposed unsupervised morphological segmentation methods into the translation model and combine this segmentation-based system with a Conditional Random Field morphology prediction model. We find the morphology aware models yield significantly more fluent translation output compared to a baseline word-based model.
Depressed mood and cognitive deficits as distinct mechanisms of subjective memory and executive complaints

background Subjective cognitive decline (SCD) is the sense of deterioration in cognitive functioning in terms of memory, executive function, attention, etc. SCD is reported by nearly 70% of the population. Very intensive research on the predictive role of SCD in the development of dementia and determinants SCD did not bring common solutions. For exploration of the phenomenon, studies were undertaken in order to identify: a) on the basis of which factors a high level of SCD can be predicted, and b) whether these factors have similar prognostic value for two types of SCD, i.e. concerning executive function (SED) and memory (SMD).
Digital forensic of a cloud based snapshot

Researchers in the field of cloud forensics need to move away from insisting on acquiring all data as has historically been the case in computer forensics- and yet still be able to prove the accuracy, sufficiency and soundness of partially acquired data. Virtualization is considered to be one of the main pillars in providing cloud services. In some cases, investigators might end up having to rely on suspect Virtual Machine (VM) snapshots in the form of memory dumps and user activity logs. Then, in these cases the main challenge is to analyse these memory dumps without altering the evidence. In this paper, we propose a forensic process model based on the NIST model to examined the private cloud based VM snapshots (e.g. XenServer). Moreover, we examine snapshots using existing digital forensic tools and were able to successfully acquire data without the need to transform the snapshot files.
Effective antitumor immunity against murine gliomas using dendritic cells transduced with hTERTC27 recombinant adenovirus

hTERTC27, a 27-kDa hTERT C-terminal polypeptide has been demonstrated to cause hTERT-positive HeLa cell apoptosis and inhibits the growth of mouse melanoma. hTERTC27 has been associated with telomere dysfunction, regulation of gene-regulated apoptosis, the cell cycle and activation of natural killer (NK) cells, but its mechanism of action is not fully understood. Here, we report that dendritic cells (DCs) transduced with hTERTC27 can increase T-cell proliferation, and augment the concentration of interleukin-2 (IL-2) and interferon-γ (IFN-γ) in the supernatants of T cells. It can also induce antigen-specific cytotoxic T lymphocytes (CTL) against glioma cells in vitro. Moreover, hTERTC27 gene-transduced DCs exhibit a very potent cytotoxicity to glioma cells in vivo. It could prolong the survival time and inhibit the growth of glioma-bearing mice. These data suggest that hTERTC27 gene-transduced DCs can efficiently enhance immunity against gliomas in vitro and in vivo.
A Practical Algorithm for Rendering All-Frequency

Algorithms for rendering interreflection (or indirect illumination) effects often make assumptions about the frequency range of the materials’ reflectance properties. For example, methods based on Virtual Point Lights (VPLs) and global photon maps perform well for diffuse and semi-glossy materials but not so for highly-glossy or specular materials; the situation is reversed for methods based on ray tracing and caustics photon maps. In this paper, we present a practical algorithm for rendering interreflection effects at all frequency scales. Our method builds upon a Spherical Gaussian representation of the BRDF. Our main contribution is a novel mathematical development of the interreflection equation. This allows us to efficiently compute the one-bounce interreflection from a triangle to a shading point through an analytic formula combined with a piecewise linear approximation. We show through evaluation that this method is accurate for a wide range of BRDF parameters. Our second contribution is a hierarchical integration method to handle a large number of triangles with bounded error. Finally, we have implemented the algorithm on the GPU, achieving nearinteractive rendering speed for a variety of scenes.
Joint Transmitter-Receiver Optimization for Downlink Multiuser MIMO Communications

This paper develops the joint optimization of linear precoding and decoding for the downlink in multiuser multiple-input multiple-output (MIMO) systems. The system under investigation consists of a single transmitter (base station) with multiple antennas that communicates with several users, each with one or more receive antennas, possibly receiving multiple data streams. The goal is to jointly optimize the power allocation and transmit-receive filters for all users. Optimization is performed for two criteria: (1) minimizing total transmitted power while satisfying a set of signal-to-interference-plus-noise ratio (SINR) constraints and (2) minimizing the sum mean squared error (SMSE) given a total power budget. The solutions use an uplink/downlink duality, in SINR and MSE sense. These dualities are proven for the general MIMO case. In this regard, this paper generalizes previous multiple-input single-output (MISO) solutions to the MIMO case. Simulation results prove the efficacy of the proposed solutions. Keywords–Array signal processing, duality, MIMO systems, power control, space division multiplexing.