Miracle-dz/UniFAR-FTUs huggingface dataset:
Semi-Supervised Sequence Classification With Hmms

Using unlabeled data to help supervised learning has become an increasingly attractive methodology and proven to be effective in many applications. This paper applies semi-supervised classification algorithms, based on hidden Markov models, to classify sequences. For model-based classification, semi-supervised learning amounts to using both labeled and unlabeled data to train model parameters. We examine three different strategies of using labeled and unlabeled data in the model training process. These strategies differ in how and when labeled and unlabeled data contribute to the model training process. We also compare regular semi-supervised learning, where there are separate unlabeled training data and unlabeled test data, with transductive learning where we do not differentiate between unlabeled training data and unlabeled test data. Our experimental results on synthetic and real EEG time-series show that substantially improved classification accuracy can be achieved by these semi-supervised learning strategies. The effect of model complexity on semi-supervised learning is also studied in our experiments.
Influence of synthetic superparamagnetic iron oxide on dendritic cells

Background: This study investigated the influence of synthetic superparamagnetic iron oxide (SPIO) on dendritic cells and provides a possible method for labeling these cells. Methods: SPIO nanoparticles were prepared, and their morphology and magnetic properties were characterized. The particles were endocytosed by dendritic cells generated from mouse bone marrow. Labeling efficiency and cellular uptake were analyzed by Prussian blue staining and quantitative spectrophotometric assay. Meanwhile, the surface molecules, cellular apoptosis, and functional properties of the SPIO-labeled dendritic cells were explored by flow cytometry and the mixed lymphocyte reaction assay. Results: The synthetic nanoparticles possessed a spherical shape and good superparamagnetic behavior. The mean concentration of iron in immature and mature dendritic cells was 31.8 ± 0.7 μg and 35.6 ± 1.0 μg per 1 × 106 cells, respectively. After 12 hours of incubation with SPIO at a concentration of 25 μg/mL, nearly all cells were shown to contain iron. Interestingly, cellular apoptosis and surface expression of CD80, CD86, major histocompatibility II, and chemokine receptor 7 in mature dendritic cells were not affected to any significant extent by SPIO labeling. T cell activation was maintained at a low ratio of dendritic cells to T cells. Conclusion: SPIO nanoparticles have good superparamagnetic behavior, highly biocompatible characteristics, and are suitable for use in further study of the migratory behavior and biodistribution of dendritic cells in vivo.
Neural network based intrusion detection using Bayesian with PCA and KPCA feature extraction

In today's digital world use of computer systems, computer networks and internet are increasing rapidly. Due to this, information is processed digitally. So, providing effective security to such digital data is crucial task. There are some tools and systems are available for the security of digital information. From these tools and systems intrusion detection system is an important method. It is necessary to design good intrusion detection system which will give good accuracy rate, less error rate, which will take minimum time and memory in the performance of the system. This paper presents the two techniques of intrusion detection system. Working of these techniques are based on neural network. For feature extraction in first technique, we are using principal component analysis (PCA) method. In second technique, we are using Bayesian for noise reduction and kernel principal component analysis (KPCA) for feature extraction. These both techniques are promising for giving good performance results. Systems are implemented using java technology.
Combination therapy in early rheumatoid arthritis: a randomised, controlled, double blind 52 week clinical trial of sulphasalazine and methotrexate compared with the single components

OBJECTIVES To investigate the potential clinical benefit of a combination therapy. METHODS 205 patients fulfilling the ACR criteria for rheumatoid arthritis (RA), not treated with disease modifying anti-rheumatoid drugs previously, with an early (⩽1 year duration), active (Disease Activity Score (DAS) > 3.0), rheumatoid factor and/or HLA DR 1/4 positive disease were randomised between sulphasalazine (SASP) 2000 (maximum 3000) mg daily (n = 68), or methotrexate (MTX) 7.5 (maximum 15) mg weekly (n = 69) or the combination (SASP + MTX) of both (n = 68). RESULTS The mean changes in the DAS during the one year follow up of the study was −1.15, −0.87, −1.26 in the SASP, MTX, and SASP + MTX group respectively (p = 0.019). However, there was no statistically significant difference in terms of either EULAR good responders 34%, 38%, 38% or ACR criteria responders 59%, 59%, 65% in the SASP, MTX, and SASP + MTX group respectively. Radiological progression evaluated by the modified Sharp score was very modest in the three groups: mean changes in erosion score: +2.4, +2.4, +1.9, in narrowing score: +2.3, +2.1, +1.6 and in total damage score: +4.6, +4.5, +3.5, in the SASP, MTX, and SASP + MTX groups respectively. Adverse events occurred more frequently in the SASP + MTX group 91% versus 75% in the SASP and MTX group (p = 0.025). Nausea was the most frequent side effect: 32%, 23%, 49% in the SASP, MTX, and SASP + MTX groups respectively (p = 0.007). CONCLUSION This study suggests that an early initiation therapy of disease modifying drug seems to be of benefit. However, this study was unable to demonstrate a clinically relevant superiority of the combination therapy although several outcomes were in favour of this observation. The tolerability of the three treatment modalities seems acceptable.
Optical and dc-transport properties of a strongly correlated charge-density-wave system : Exact solution in the ordered phase of the spinless Falicov-Kimball model with dynamical mean-field theory

We derive the dynamical mean-field theory equations for transport in an ordered charge-densitywave phase on a bipartite lattice. The formalism is applied to the spinless Falicov-Kimball model on a hypercubic lattice at half filling. We determine the many-body density of states, the dc charge and heat conductivities, and the optical conductivity. Vertex corrections continue to vanish within the ordered phase, but the density of states and the transport coefficients show anomalous behavior due to the rapid development of thermally activated subgap states. We also examine the optical sum rule and sum rules for the first three moments of the Green’s functions within the ordered phase and see that the total optical spectral weight in the ordered phase either decreases or increases depending on the strength of the interactions.
Lifelong teetotallers, ex-drinkers and drinkers: mortality and the incidence of major coronary heart disease events in middle-aged British men.

BACKGROUND To determine the risk of all cause mortality and the incidence of major coronary heart disease (CHD) events in lifelong teetotallers and in ex-drinkers compared with occasional and regular drinkers. METHODS A prospective study of middle-aged men drawn at random from one general practice in each of 24 British towns. Five years after the screening of 7735 men aged 40-59 years, 7167 provided further information on postal questionnaire enabling separation of non-drinkers into lifelong teetotallers and ex-drinkers. RESULTS During the follow-up period of 9.8 years after the postal questionnaire there were 929 deaths from all causes and 490 major CHD events. Ex-drinkers exhibited increased cardiovascular and non-cardiovascular mortality; lifelong teetotallers showed the lowest cardiovascular mortality but a significantly increased non-cardiovascular mortality. After adjustment for confounding factors and pre-existing disease, the two non-drinking groups did not differ significantly in all cause mortality from occasional and regular drinkers (light, moderate or heavy) but lifelong teetotallers still showed a significant increase in non-cardiovascular mortality. Adjustment considerably attenuated the risk of both cardiovascular and non-cardiovascular mortality in the ex-drinkers. In men without a diagnosis of CHD, lifelong teetotallers and ex-drinkers showed similar increased relative risk (RR) of heart attacks, with regular drinkers (combined) having a significantly decreased risk compared to occasional drinkers (RR = 0.78, 95% confidence interval [CI] : 0.64-0.96) and non-drinkers (RR = 0.69, 95% CI : 0.52-0.91). This decreased risk was small in absolute terms at around 2-3 major CHD events/1000 person-years. CONCLUSIONS Lifelong teetotallers and ex-drinkers showed a significantly increased RR of major CHD events compared with regular drinkers, although this risk is small in absolute terms. Lifelong teetotallers have a low risk of overall cardiovascular mortality and an increased risk of non-cardiovascular mortality. Non-drinkers constitute an unsuitable reference group in alcohol-related studies; occasional or even light drinkers may be more appropriate. Overall, there is no convincing evidence that light or moderate drinking has a protective effect on total or cardiovascular mortality in these middle-aged British men.
Enhancing the BRAS through virtualization

Broadband Remote Access Servers (BRASes) are crucial middleboxes in DSL access networks, providing the first IP point in the network for subscribers and enforcing operator policies. The number of functions provided by BRASes, combined with the key role they play in the network, means that these devices are expensive, difficult to change, and constitute a single point of failure. In order to overcome these limitations, we propose to virtualize the BRAS and to enhance it with a control interface that can be exploited by management systems in order to introduce live session migration and higher reliability. Our proof-of-concept implementation shows that our virtual software BRAS is able to handle thousands of sessions while forwarding and shaping traffic at rates of millions of packets per second on commodity hardware, and that the live session migration feature enables the implementation of high-reliability scenarios.
Edge-To-Edge Virtualization and Orchestration in Heterogeneous Transport Networks

Nowadays, Internet services demand for the mobilization of computing and storage resources located in proximity of the final users, and for the support of an agile and programmable network infrastructure. This calls for a holistic vision in which control, management, and optimization of both computing and networking resources are combined, resulting in a progressive blur of the capabilities of the latter towards the edges of the transport segment. However, due to its multi-provider nature, the Internet itself is the main obstacle to this change. In such a context, Network Virtualization (NV) and Software Defined Networking (SDN) solutions can enable business opportunities and provide technical benefits for the operators managing the different domains of a transport infrastructure. In this paper we discuss in detail the technical challenges and outline potential architectural approaches exploiting the above mentioned solutions to provide edge-to-edge virtualization, abstraction, control, and optimization of heterogeneous transport networks composed of both packet- and circuit- switched technologies.
Cognitive Retroactive Transfer (CRT) of Language Skills among Trilingual Arabic-Hebrew and English Learners

This study examined whether helping poor readers improve their reading and writing language skills in English as a third language/foreign language (L3/FL) would also bring about an improvement in those same skills in Arabic (L1) and Hebrew (L2). Transferring linguistic skills from L3/FL to both L1 and L2 is termed “Cognitive Retroactive Transfer” (CRT). A battery of tests, administered to the experiment and control groups, assessed orthographic knowledge, phonological awareness, morphological awareness, syntactic awareness, reading accuracy and reading comprehension in English, Arabic, and Hebrew. The treatment group was provided with an intervention program in English, but not in Arabic or Hebrew, both before and after the experiment. Findings indicated a significant improvement in the treatment group’s achievements in all linguistic and meta-linguistic skills in all study languages after the intervention, except for orthographic knowledge in Arabic and Hebrew. The results are discussed in light of the international data.
Discounting The Equity Premium Puzzle

This paper applies recent tests of stochastic dominance of several orders proposed by Linton, Maasoumi and Whang (2003) to reexamine the equity premium puzzle. An advantage of this nonparametric framework is that it provides a means to assess whether the existence of a premium is due to an incorrect choice of either the utility function or the underlying returns distribution. The approach is applied to a range of data sets including the S&P500
Towards the System-on-Chip Realization of a Sensorless Vector Controller with Microsecond-order Computation Time

The aim of this research is to implement sensorless vector control algorithms on a single, eventually reconfigurable, chip, with a computation timing constraint of, at most, 1-6 microseconds, and a concern for implementation cost. In this article, we discuss the implementation problems and tradeoffs involved in meeting these goals on field-programmable gate arrays (FPGAs). To be able to fit a complete induction motor vector controller on a single, inexpensive FPGA chip, we estimate the area/time requirements of each module involved in sensorless vector control. We discuss, in particular, the tradeoffs of implementing the key modules, the speed and flux observers and the Clarke and Park transformations. The speed and flux observers here under consideration are extended Kalman filter-based
Regulation of the sol Locus Genes for Butanol and Acetone Formation in Clostridium acetobutylicumATCC 824 by a Putative Transcriptional Repressor

ABSTRACT A gene (orf1, now designated solR) previously identified upstream of the aldehyde/alcohol dehydrogenase gene aad (R. V. Nair, G. N. Bennett, and E. T. Papoutsakis, J. Bacteriol. 176:871–885, 1994) was found to encode a repressor of the sol locus (aad,ctfA, ctfB and adc) genes for butanol and acetone formation in Clostridium acetobutylicumATCC 824. Primer extension analysis identified a transcriptional start site 35 bp upstream of the solR start codon. Amino acid comparisons of SolR identified a potential helix-turn-helix DNA-binding motif in the C-terminal half towards the center of the protein, suggesting a regulatory role. Overexpression of SolR in strain ATCC 824(pCO1) resulted in a solvent-negative phenotype owing to its deleterious effect on the transcription of the sol locus genes. Inactivation of solR in C. acetobutylicum via homologous recombination yielded mutants B and H (ATCC 824 solR::pO1X) which exhibited deregulated solvent production characterized by increased flux towards butanol and acetone formation, earlier induction of aad, lower overall acid production, markedly improved yields of solvents on glucose, a prolonged solvent production phase, and increased biomass accumulation compared to those of the wild-type strain.
New Sequential Methods for Detecting Portscanners

In this paper, we propose new sequential methods for detecting port-scan attackers which routinely perform random "portscans" of IP addresses to find vulnerable servers to compromise. In addition to rigorously control the probability of falsely implicating benign remote hosts as malicious, our method performs significantly faster than other current solutions. Moreover, our method guarantees that the maximum amount of observational time is bounded. In contrast to the previous most effective method, Threshold Random Walk Algorithm, which is explicit and analytical in nature, our proposed algorithm involve parameters to be determined by numerical methods. We have developed computational techniques such as iterative minimax optimization for quick determination of the parameters of the new detection algorithm. A framework of multi-valued decision for testing portscanners is also proposed.
Analysis of off-line handwritten text samples of different gender using shape descriptors

The human experience in the analysis of the handwriting of male and female writers indicates that gender affects the appearance of the handwritten text. These differences are usually very difficult to describe numerically. In order to analyze the handwriting differences between male and female writers, several shape description techniques, such as the tangent angle function, curvature function and Fourier descriptors, were used in this paper. As an additional contribution of the paper, a database of 3766 off-line handwritten cursive and capitalized written words has been created. The database consists of male and female handwriting samples, classified by gender and handedness. The experimental results show that typical attributes of male and female handwritings imply certain differences in shape decriptors, and those differences have the potential for usage in gender handwriting discrimination.
Simulation and Optimization of Diode and Insulated Gate Bipolar Transistor Interaction in a Chopper Cell Using MATLAB and Simulink

Recently, a simulation method for power electronic devices has emerged, which has high accuracy and short run times based on a Fourier model of the device physics. This paper describes the use of the Fourier models for diodes and insulated gate bipolar transistors (IGBTs) and implementation in MATLAB and Simulink in a formal optimization strategy. In particular, this paper investigates coupled circuit, diode, and IGBT behavior. Conclusions are drawn concerning device loading and circuit design, particularly the role of stray inductance.
PROGRESSIVE IMAGE TRANSMISSION USING WAVELET AND OTHER FRACTAL TECHNIQUES

This is a digest of the work and research completed thus far in developing a progressive image transmission scheme. Efficient and quick communication of perceptually important image information is desired resulting in this research with wavelet and fractal techniques for the identification and extraction of perceptually important features. This is done with the final goal of interactive control over the panning , zooming, and termination of the image reconstruction with minimal recomputation at progressive steps.
Feature subset selection for irrelevant data removal using Decision Tree Algorithm

Feature subset selection is an effective way for reducing dimensionality, removing irrelevant data, and improving result accuracy. Feature subset selection can be viewed as the process of identifying and removing as many irrelevant and redundant features as possible. This is because 1) irrelevant features do not contribute to the predictive accuracy and 2) redundant features do not redound to getting a better predictor for that they provide mostly information which is already present in other feature(s). Irrelevant features, along with redundant features, severely affect the accuracy of the learning machines. In this paper, exceptional vigilance is made on characteristic assortment for classification with data. Here an algorithm is utilized that plans attributes founded on their significance. Then, the organized attributes can be utilized as input one easy algorithm for building decision tree (Oblivious Tree). Outcomes show that this decision tree uses boasted chosen by suggested algorithm outperformed conclusion tree without feature selection. From the experimental outcomes, it is observed that, this procedure develops lesser tree having an agreeable accuracy. The results obtained with decision tree method for selection of datasets has resulted with 85.87% when compared with other techniques.
Synoptic-Scale Convective Environment Climatology byENSO Phase in the North Central United States

The El Niño-Southern Oscillation (ENSO) is known to affect synoptic patterns across the continental United States, particularly by its impact on the upper tropospheric jet stream position. Global circulation patterns influence synoptic weather patterns by impacting the location of mid-tropospheric ridge and trough locations and thus areas favorable for temperature and precipitation anomalies, which in turn influence regional severe weather activity. Though it is one of several factors associated with the potential for severe weather, the synoptic environment plays a key role in severe weather potential by providing favorable ingredients for the development of severe convection (e.g. Miller 1967). While ENSO is one of many factors that influence global circulations, and by distillation may have a less distinguishable influence on the synoptic pattern, coherent signals can be uncovered in the synoptic environment, based on ENSO phase, that would influence the potential for severe convection in the north central United States. Seasonal predictions of severe weather potential are not much aid for daily operations, but they can be used by emergency managers, the media, and forecasters to increase preparedness for seasons that have the potential for above normal convective activity.
Defining a “generic” end-user: An information security perspective

“If you know the enemy and know yourself, you need not fear the results of a hundreds battles” Sun Tzu - Art of War. Security educators should start by knowing the target audience first; and then only should they create and prepare an information-security educational program. Unfortunately, information-security educational programs are often implemented without getting to know the target audience first. This results in programs that are not linguistically appropriate; or else they are not on the same knowledge level as that of the target audience. This could leave end-users bored or confused - without successfully changing the behaviour and knowledge of these end-users. This paper examines the role(s) of information-security end-users, in order to provide a profile of the “generic” end-user.
Dynamic signal mixtures and blind source separation

Methods for blind source separation (BSS) from linear instantaneous signal mixtures have drawn a significant attention due to their ability to recover original independent non-Gaussian sources without analyzing their temporal statistics. Hence, original voices or images (module permutation and linear scaling) are extracted from their mixtures without modeling the dynamics of the signals. The typical methods for performing blind source separation are linear independent component analysis (ICA) and the infomax method. Linear ICA directly penalizes a suitably chosen measure of the statistical dependence between the extracted signals. These measures are either obtained from the information theoretic postulates such as the mutual information or from the cumulant expansion of the associated probability density functions. The infomax method is based on the entropy maximization of the non-linear transformation of the separated signals. This paper analyzes extensions of the instantaneous blind source separation techniques to the case of linear dynamic signal mixtures. Furthermore, the paper introduces a novel method based on combining time delayed decorrelation (TDD) with the minimization of the cumulant cost function. TDD is used to obtain an acceptable initial condition for the cumulant based cost function optimization in order to reduce the numerical complexity of the latter method. This combined approach is illustrated on two examples including a real life cocktail party example.