Miracle-dz/UniFAR-FTUs huggingface dataset:
Spontaneous EEG-Functional MRI in Mesial Temporal Lobe Epilepsy: Implications for the Neural Correlates of Consciousness

The combination of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) has been shown to have great potential for providing a greater understanding of normal and diseased states in both human and animal studies. Simultaneous EEG-fMRI is particularly well suited for the study of epilepsy in that it may reveal the neurobiology of ictal and interictal epileptiform discharges and noninvasively localize epileptogenic foci. Spontaneous, coherent fluctuations of neuronal activity and the coupled hemodynamic responses have also been shown to provide diagnostic markers of disease, extending our understanding of intrinsically structured ongoing brain activity. Following a short summary of the hardware and software development of simultaneous EEG-fMRI, this paper reviews a unified framework of integrating neuronal and hemodynamic processes during epileptic seizures and discusses the role and impact of spontaneous activity in the mesial temporal lobe epilepsies with particular emphasis on the neural and physiological correlates of consciousness.
A heuristic approach to optimization of the decision-directed maximum-likelihood feedforward carrier phase error detection algorithm

Using a heuristic approach, the performance of the self-synchronized decision-directed maximum-likelihood (ML) feedforward (FF) carrier phase error detection (PED) algorithm has been optimized. Compared to the original algorithm, it has been shown that for uncoded single channel (O)QPSK modems the optimized algorithm has a better phase error variance at low to medium signal to noise ratio (SNR). Further simulations have shown that the noise performance of the optimized algorithm at medium to high SNRs is superior to that of some well-known algorithms; the noise performance approaches the Cramer-Rao bound (CRB). This proves that the optimized algorithm has less tracking jitter at medium to high SNR which is a desirable feature in improving the BER performance.
Antiviral activity of acidic polysaccharides from Coccomyxa gloeobotrydiformi, a green alga, against an in vitro human influenza A virus infection

The extracts prepared from green algae are reported to possess a variety of biological activities including antioxidant, antitumor and antiviral activities. The acidic polysaccharide fraction from a green alga Coccomyxa gloeobotrydiformi (CmAPS) was isolated and the antiviral action on an in vitro infection of influenza A virus was examined. CmAPS inhibited the growth and yield of all influenza A virus strains tested, such as A/H1N1, A/H2N2, A/H3N2 and A/H1N1 pandemic strains. The 50% inhibitory concentration of CmAPS on the infection of human influenza A virus strains ranged from 26 to 70 µg/mL and the antiviral activity of CmAPS against influenza A/USSR90/77 (H1N1) was the strongest. The antiviral activity of CmAPS was not due to the cytotoxicity against host cells. The antiviral activity of CmAPS required its presence in the inoculation of virus onto MDCK cells. Pretreatment and post-treatment with CmAPS was ineffective for the antiviral activity. CmAPS inhibited influenza A virus-induced erythrocyte hemagglutination and hemolysis. Taken together, CmAPS was suggested to exhibit the anti-influenza virus activity through preventing the interaction of virus and host cells. The detailed antiviral activity of CmAPS is discussed.
Clinicopathologic and prognostic significance of MMP-7 (matrilysin) expression in human rectal cancer.

OBJECTIVE There is increasing evidence to indicate that MMP-7 plays a more important role in tumor progression than other MMPs. The aim of this study was to detect MMP-7 expression in human rectal cancer and normal rectal tissue and to determine whether it is correlated with invasion and metastasis of human rectal cancer. METHODS Eighty-six paired samples of rectal cancer and distant normal rectal tissue obtained from 100 inpatients were allocated into two groups (cancer group and control group). MMP-7 mRNA was detected by relative quantitative real-time RT-PCR and MMP-7 protein was examined by immunohistochemical staining and computerized image analysis. RESULTS MMP-7 mRNA expression in cancer group was higher than that in control group (P = 0.006), the expression ratios of 31 samples (37.35%) were <1 and 52 (62.65%) were >1. The mRNA expression level was correlated with Dukes Staging, histological differentiation grade and CEA level. The MMP-7 protein expression was in accordance with mRNA expression level. The positive degree of immunohistochemical staining in cancer group (1.82 +/- 0.03) was different from that in control group (1.17 +/- 0.13, P = 0.002). Moreover, in cancer group the positive staining degree in high-level mRNA cancers (2.04 +/- 0.18, n = 52) was higher than that in low-level mRNA ones (1.58 +/- 0.23, n = 31, P = 0.008). CONCLUSIONS Our results suggest that MMP-7 plays an important role in the progression of human rectal cancer. MMP-7 may be selected as a clinical diagnosis and prognosis index in rectal cancer.
Study of the consistency of some discriminatory features used by document examiners in the analysis of handwritten letter 'a'

In this paper a study of some structural features of hand-writtenletter a' is presented. The features under considerationare structural, style and formation features documentexaminer's use when studying a questioned document to determineits authorship or authenticity.Feature extraction algorithms for the feature set were developedto perform the extraction procedure automatically.The estimate of feature consistency is introduced and measuredfor each extracted feature. The extracted feature setis analyzed for linear independency and ability to be usedfor separation of author classes (i.e. authorship decision). The results on a set of 18 authors with approximately 40 letter'a's per author indicates a high level of consistency anddiscrimination ability for most of the features analysed.
Genetic and molecular bases of photoperiod responses of flowering in soybean

Flowering is one of the most important processes involved in crop adaptation and productivity. A number of major genes and quantitative trait loci (QTLs) for flowering have been reported in soybean (Glycine max). These genes and QTLs interact with one another and with the environment to greatly influence not only flowering and maturity but also plant morphology, final yield, and stress tolerance. The information available on the soybean genome sequence and on the molecular bases of flowering in Arabidopsis will undoubtedly facilitate the molecular dissection of flowering in soybean. Here, we review the present status of our understanding of the genetic and molecular mechanisms of flowering in soybean. We also discuss our identification of orthologs of Arabidopsis flowering genes from among the 46,367 genes annotated in the publicly available soybean genome database Phytozome Glyma 1.0. We emphasize the usefulness of a combined approach including QTL analysis, fine mapping, and use of candidate gene information from model plant species in genetic and molecular studies of soybean flowering.
Cardiovascular effects of continuous positive airway pressure in patients with heart failure and obstructive sleep apnea.

BACKGROUND Obstructive sleep apnea subjects the failing heart to adverse hemodynamic and adrenergic loads and may thereby contribute to the progression of heart failure. We hypothesized that treatment of obstructive sleep apnea by continuous positive airway pressure in patients with heart failure would improve left ventricular systolic function. METHODS Twenty-four patients with a depressed left ventricular ejection fraction (45 percent or less) and obstructive sleep apnea who were receiving optimal medical treatment for heart failure underwent polysomnography. On the following morning, their blood pressure and heart rate were measured by digital photoplethysmography, and left ventricular dimensions and left ventricular ejection fraction were assessed by echocardiography. The subjects were then randomly assigned to receive medical therapy either alone (12 patients) or with the addition of continuous positive airway pressure (12 patients) for one month. The assessment protocol was then repeated. RESULTS In the control group of patients who received only medical therapy, there were no significant changes in the severity of obstructive sleep apnea, daytime blood pressure, heart rate, left ventricular end-systolic dimension, or left ventricular ejection fraction during the study. In contrast, continuous positive airway pressure markedly reduced obstructive sleep apnea, reduced the daytime systolic blood pressure from a mean (+/-SE) of 126+/-6 mm Hg to 116+/-5 mm Hg (P=0.02), reduced the heart rate from 68+/-3 to 64+/-3 beats per minute (P=0.007), reduced the left ventricular end-systolic dimension from 54.5+/-1.8 to 51.7+/-1.2 mm (P=0.009), and improved the left ventricular ejection fraction from 25.0+/-2.8 to 33.8+/-2.4 percent (P<0.001). CONCLUSION In medically treated patients with heart failure, treatment of coexisting obstructive sleep apnea by continuous positive airway pressure reduces systolic blood pressure and improves left ventricular systolic function. Obstructive sleep apnea may thus have an adverse effect in heart failure that can be addressed by targeted therapy.
Accelerated processing of historical BGP events for testing new BGP heuristics

This paper describes a technique for arti- ficially accelerating 'real time' when testing new BGP protocol enhancements using historical real-world data. We show how months of BGP advertisement data may be processed in hours, yet generate outputs that appear to reflect months of actual operation by a network of fully featured BGP speakers. Using Quagga (an operational open-source implementation of BGP) we characterise the performance trade-offs of our technique, and show how 'accelerated time' benefits researchers who are exploring modifications to BGP's dynamic, timer-based behaviours. We consider the impact of our technique when multiple instances of Quagga run on a single host or are distributed across multiple hosts.
DETC 2001 / DAC-21068 FINDING AND REMOVING FEATURES FROM POLYHEDRA

Geometric models of solids often contain small features that we would like to isolate and remove. Examples include bumps, holes, tabs, notches, and decorations. Feature removal can be desirable for numerous reasons, including economical meshing and finite element simulation, analysis of feature purpose, and compact shape representation. In this work, an algorithm is presented that inputs a polyhedral solid, identifies and ranks its candidate features, and outputs solid models of the feature and the original object with the feature removed. Ranking permits a user or higher level software to quickly find the most desirable features for the task at hand. Features are defined in terms of portions of the surface that are classified differently from the rest of the solid’s surface with respect to one or more split planes. This approach to feature definition is more general than many previous methods, and generalizes naturally to quadric surf aces and other implicit surfaces.
Extracting Relevant Structures

A key problem in understanding auditory coding is to identify the acoustic features that neurons at various levels of the system code. If we can map the relevant stimulus features and trace how they change along the processing hierarchy, we can understand the processing properties of the system. A principled approach for extracting relevant features was proposed by Tishby and co-authors [Tishby et al., 1999], with the Information Bottleneck (IB) framework. This powerful approach aims at identifying structures of a variable X that have functional importance, by compressing X in a way that preserves information about another variable Y. In the context of the current problem it can be used to compress acoustic stimuli while preserving information about the distribution of neural responses, and use it to identify the stimulus aspects to which system is sensitive. Unfortunately, the IB approach is insufficient for characterizing the processing that takes place in a brain region like the cortex. To understand the reason why, consider for example a case where one measures cortical activity in response to acoustic stimuli, and maps the acoustic features to which the cortical neurons respond. Such an analysis does not characterize cortical processing but rather the processing performed by the whole chain of processing stations that ends in the cortex. In fact, many of the features that are revealed this way do not reflect cortical processing, but processing that takes place at lower levels. For example, in the visual system, high level cells are often sensitive to the location of an object in the visual field (e.g. [Levy et al., 2001]), but such spatial sensitivity is computed by the narrow spatial sensitivity of the receptors in the retina. Similarly, in the auditory system, cortical neurons are frequency sensitive, but the frequency content of a stimulus is already determined at the receptor level in the cochlea. The conclusion is that when we aim to identify the processing that occurs at the cortex, we should search for features relevant to cortical neurons and not lower level neurons.
Structured sparsity through convex optimization

Sparse estimation methods are aimed at using or obtaining parsimonious representations of data or models. While naturally cast as a combinatorial optimization problem, variable or feature selection admits a convex relaxation through the regularization by the $\ell_1$-norm. In this paper, we consider situations where we are not only interested in sparsity, but where some structural prior knowledge is available as well. We show that the $\ell_1$-norm can then be extended to structured norms built on either disjoint or overlapping groups of variables, leading to a flexible framework that can deal with various structures. We present applications to unsupervised learning, for structured sparse principal component analysis and hierarchical dictionary learning, and to supervised learning in the context of non-linear variable selection.
A Routing-Driven Key Management Scheme for Heterogeneous Sensor Networks

The many-to-one traffic pattern dominates in sensor networks, where a large number of sensor nodes send data to one sink. A sensor node may only communicate with a small portion of its neighbors. Most existing key management schemes for sensor networks are designed to establish shared keys for all pairs of neighbor sensors, no matter whether they communicate with each other or not, and this causes large overhead. To achieve better security and performance, we adopt a heterogeneous sensor network (HSN) model. In this paper, we propose a novel routing-driven key management scheme, which only establishes shared keys for neighbor sensors that may communicate with each other. Work has demonstrated the feasibility of implementing elliptic curve cryptography on small sensor nodes. We utilize elliptic curve cryptography to design an efficient key management scheme for HSN. The performance evaluation and security analysis show that our key management scheme can provide better security with significant saving on sensor storage space and energy consumption than some existing key management schemes.
Stable Human Hepatoma Cell Lines for Efficient Regulated Expression of Nucleoside/Nucleotide Analog Resistant and Vaccine Escape Hepatitis B Virus Variants and Woolly Monkey Hepatitis B Virus

Hepatitis B virus (HBV) causes acute and chronic hepatitis B (CHB). Due to its error-prone replication via reverse transcription, HBV can rapidly evolve variants that escape vaccination and/or become resistant to CHB treatment with nucleoside/nucleotide analogs (NAs). This is particularly problematic for the first generation NAs lamivudine and adefovir. Though now superseded by more potent NAs, both are still widely used. Furthermore, resistance against the older NAs can contribute to cross-resistance against more advanced NAs. For lack of feasible HBV infection systems, the biology of such variants is not well understood. From the recent discovery of Na+-taurocholate cotransporting polypeptide (NTCP) as an HBV receptor new in vitro infection systems are emerging, yet access to the required large amounts of virions, in particular variants, remains a limiting factor. Stably HBV producing cell lines address both issues by allowing to study intracellular viral replication and as a permanent source of defined virions. Accordingly, we generated a panel of new tetracycline regulated TetOFF HepG2 hepatoma cell lines which produce six lamivudine and adefovir resistance-associated and two vaccine escape variants of HBV as well as the model virus woolly monkey HBV (WMHBV). The cell line-borne viruses reproduced the expected NA resistance profiles and all were equally sensitive against a non-NA drug. The new cell lines should be valuable to investigate under standardized conditions HBV resistance and cross-resistance. With titers of secreted virions reaching >3x107 viral genome equivalents per ml they should also facilitate exploitation of the new in vitro infection systems.
Cs224 – Final Project Report a Study on Social Behaviors in Online Communities

In this report we discuss the reputable users in online communities and their behaviors from different perspectives. We investigate how to label reputable users with the online activities of the whole community and compare the result to local communities and different centrality rankings. We discuss the writing behavior of reputable users, how they differ from other users and how they change in writing over time. We also build a predictive model to detect potential reputable users when they just join the community, and a generative model of the network for simulation studies. INTRODUCTION User­contributed content such as posts, comments and votes are essential to the success of any online communities. Prior work has been done on analyzing antisocial behaviors and detecting if a new member would grow into a troll based on their postings. In the paper, we would like to extend the study of antisocial behavior in online communities and perform in­depth studies on the reputable users. First we want to understand their behaviors and use network­based ranking algorithms to identify them for answering questions like: Do they also write differently over time? How do top users gain their reputations? For both reputable users and trolls, we also want to understand how they affect the overall community growth. Finally we use generative models for simulating different communities and evaluating our algorithms. RELATED WORK Prior work has been done on identifying users with expertise automatically using network­based ranking algorithms such as PageRank and HITS [3]. The network's structural characteristics are proven to be valuable for identifying the expertise level of a user. The evaluated algorithms performs almost as well as the human raters. There are pros and cons for different algorithms. Sometimes the simple one could be as good as the more complex ones. Based on simulations, the performance of the evaluated algorithms can vary when the structural characteristics of the online communities are different; therefore, we should first understand the network structure and then determine which algorithm to use for optimally labeling the user expertise level. A big obstacle in data science is obtaining quality real world data. Simulation is very useful for understanding expertise networks and designing algorithms. Without requiring interventions in real organizations and unobtainable experimental conditions, the simulations helped us develop a good understanding of how different algorithms behave. Therefore, we need a generative model for the simulations that can mimic the growth of an online …
Pyridoxine-dependent Epilepsy With Elevated Urinary α-Amino Adipic Semialdehyde in Molybdenum Cofactor Deficiency

α-Amino adipic semialdehyde (α-AASA) accumulates in body fluids from patients with pyridoxine-dependent epilepsy because of mutations in antiquitin (ALDH7A1) and serves as the biomarker for this condition. We have recently found that the urinary excretion of α-AASA was also increased in molybdenum cofactor and sulfite oxidase deficiencies. The seizures in pyridoxine-dependent epilepsy are caused by lowered cerebral levels of pyridoxal-5-phosphate (PLP), the bioactive form of pyridoxine (vitamin B6), which can be corrected by the supplementation of pyridoxine. The nonenzymatic trapping of PLP by the cyclic form of α-AASA is causative for the lowered cerebral PLP levels. We describe 2 siblings with clinically evident pyridoxine-responsive seizures associated with increased urinary excretion of α-AASA. Subsequent metabolic investigations revealed several metabolic abnormities, all indicative for molybdenum cofactor deficiency. Molecular investigations indeed revealed a known homozygous mutation in the MOCS2 gene. Based upon the clinically evident pyridoxine-responsive seizures in these 2 siblings, we recommend considering pyridoxine supplementation to patients affected with molybdenum cofactor or sulfite oxidase deficiencies.
Hybrid query by humming and metadata search system (HQMS)

Query by humming (QbH) is a technique that is used for audio content retrieval. Many QbH systems are based on a feature of humming comparison to audio files, which can be further improved by accompanying other approaches along with humming. In our study, we propose a Hybrid approach of QbH and Metadata search system as audio files retrieval. The proposed framework is based on the Pipe and Filter architecture that provides a serial structure with two filters in order to efficiently retrieve relevant files. Content Based searching works more swiftly when applied on a small collection of files and by using this quality our framework first filter files by audio file retrieval mechanism which will decrease the collection count to the most relevant files that would be further sieved by a second filter QbH. We find our research to be beneficial to the community, as it works on defining a new idea for audio file retrieval, made hybrid in order to achieve high precision and recall efficiently.
Finding spatial equivalences across multiple RDF datasets

The importance of geospatial information is being reflected on the growing amount of spatial datasets on the Semantic Web. However, the high variability of the data presents challenges for integration. In this paper, we address the problem of finding spatial equivalences between geospatial RDF datasets. First, we present mappings between our NeoGeo vocabulary and the vocabularies used by some well-known spatial RDF datasets. Second, we describe a method to find spatially co-located features across spatial RDF datasets. To find equivalences, we rely on analyzing the Hausdorff distance distribution in the compared datasets, with the objective of finding a sensible criterion that aids the recognition of equivalent regions.
Soft object manipulation by simultaneous control of motion and deformation

One of features of soft object manipulation is motion during deformation of the soft body. We analyze the stability of soft object manipulation by simultaneous control of motion and deformation. We model and formulate manipulation by simultaneous control of the motion and deformation of soft object. We then use the symmetric linear mass-damper-spring model for a simple analysis of its dynamical behavior. Second, we analyze the stability of the system. Thus, we show that an adequate feedback gain stabilized the system in PID control. This adequate feedback gain ranges between two positive values. The object cannot be stably controlled at too high a gain; neither can, it be regulated at too low a gain since the object is movable. Furthermore, we unravel the features of soft object manipulation by simultaneous control of motion and deformation