Miracle-dz/UniFAR-FTUs huggingface dataset:
Mixture models of endhost network traffic

We model a little studied type of traffic, namely the network traffic generated from endhosts. We introduce a parsimonious model of the marginal distribution for connection arrivals consisting of mixture models with both heavy and light-tailed component distributions. Our methodology assumes that the underlying user data can be fitted to one of several models, and we apply Bayesian model selection criterion to choose the preferred combination of components. Our experiments show that a simple Pareto-exponential mixture model is preferred over more complex alternatives, for a wide range of users. This model has the desirable property of modeling the entire distribution, effectively clustering the traffic into the heavy-tailed as well as the non-heavy-tailed components. Also this method quantifies the wide diversity in the observed endhost traffic.
Single-Nucleotide Polymorphism Bioinformatics: A Comprehensive Review of Resources

Recent years have seen near exponential growth in knowledge regarding genetic and genomic variation as more genomes have been sequenced, and corresponding advances and economies of scale in sequencing and genotyping technologies have reduced their relative costs. In parallel with these developments, discoveries of genes contributing to monogenic and complex diseases have rapidly advanced, and bioinformatics databases and software relating to the collection and analysis of genetic data have increased in number, size, and scope. Single-nucleotide polymorphisms (SNPs), comprising the most abundant type of genetic variation, are now the principal raw material underlying most genetic studies and databases. Although other types of variation, including indels, microsatellites, copy number variants, and epigenetic markers remain important to consider and can impact disease, SNPs are largely the easiest to ascertain and the most useful and widely applied markers in genetic studies in the modern age. Researchers and clinician-researchers are confronted with a dizzying array of software choices and increasingly large and complex datasets and databases relating to SNPs, sometimes working without assistance from a geneticist or a bioinformatician to help guide them. The principle aim of this review is to provide a comprehensive overview of available bioinformatics resources relating to human genetics research, with an emphasis on SNP-centered resources. The review also provides a resource for students seeking an introduction to SNP genetics resources and for wet laboratory molecular biologists conducting SNP-centered research who want to expand their knowledge on ways to apply SNP tools and databases. A number of important issues that affect users and developers of SNP bioinformatics resources are discussed throughout along with practical examples. Although many of the resources described have relevance and origins in the study of nonhuman species, this review focuses on human clinical applications. The review discusses basic SNP bioinformatics issues, critical databases and their uses, basic strategies and queries using APOE examples, software and tools relating to association studies, the prediction and validation of functional SNPs, and miscellaneous SNP resources. The focus is primarily on academic resources that are widely available. Supplemental Table IV provides URL links for all resources described in the text sections in order of their appearance. Readers are encouraged to download the Data Supplement which contains nearly half of the full review article text including sections on practical examples relating to APOE and functional SNP prediction. Key abbreviations and definitions often encountered in this article and other SNP-related articles, databases, and informatics tools are given in the Table.
A Gain of Function Mutation in the Activation Loop of Plateletderived Growth Factor β-Receptor Deregulates Its Kinase Activity*

The platelet-derived growth factor receptors (PDGFRs) are receptor tyrosine kinases implicated in multiple aspects of cell growth, differentiation, and survival. Recently, a gain of function mutation in the activation loop of the human PDGFRα has been found in patients with gastrointestinal stromal tumors. Here we show that a mutation in the corresponding codon in the activation loop of the murine PDGFRβ, namely an exchange of asparagine for aspartic acid at amino acid position 849 (D849N), confers transforming characteristics to embryonic fibroblasts from mutant mice, generated by a knock-in strategy. By comparing the enzymatic properties of the wild-type versus the mutant receptor protein, we demonstrate that the D849N mutation lowers the threshold for kinase activation, causes a dramatic alteration in the pattern of tyrosine phosphorylation kinetics following ligand stimulation, and induces a ligand-independent phosphorylation of several tyrosine residues. These changes result in deregulated recruitment of specific signal transducers. The GTPase-activating protein for Ras (RasGAP), a negative regulator of the Ras mitogenic pathway, displayed a delayed binding to the mutant receptor. Moreover, we have observed enhanced ligand-independent ERK1/2 activation and an increased proliferation of mutant cells. The p85 regulatory subunit of the phosphatidylinositol 3 ′-kinase was constitutively associated with the mutant receptor, and this ligand-independent activation of the phosphatidylinositol 3′-kinase pathway may explain the observed strong protection against apoptosis and increased motility in cellular wounding assays. Our findings support a model whereby an activating point mutation results in a deregulated PDGFRβ with oncogenic predisposition.
Response Set and the California Attitude Scales

RESPONSE sets as a source of error variance in pencil and paper tests have been described by Cronbach (6). Response sets may reflect real variables and not merely incidental sources of error (7). In some instances response sets have been related to personality characteristics. Berg and Collier 0) report that “generally neurotic” (high sway) Ss and “anxious” (Taylor Scale of Manifest Anxiety) Ss made significantly more extreme position choices than did “normal” Ss on the Berg and Hunt Perceptual Reactiotz Test (4). Cronbach and others (7) have demonstrated the presence of a response set identified as “acquiescence” in true-false tests, the Bernreuter, Strong Interest Inventory, and a Thurstone attitude scale. The widely employed attitude scales developed in the California studies of prejudice (Ethnocentrism or E scale, AntiSemitism or A-S scale, and the Tendencies Toward Fascism or F scale) ( I ) appear to be particularly susceptible to the operation of a response set. The Likert type scales differ from most attitude scales in that only unidirectional items are used, i.e., agreement with the item indicates acceptance of prejudicial or fascistic statements. The possibility of a set operating in such a scale is recognized by the authors. However, from their discussion the set is simply a consistent mechanical tendency to mark degree of agreement or disagreement apparently without regard to content. Cronbach’s concept of the response set as “. any tendency causing a person to give different responses to test items than he would when the same content was presented in‘ different form” was not considered by the scale authors. Indirect evidence has accumulated to suggest the presence of a response set in the California attitude scales. Cohn (5) reports that the MMPI items having the highest correlation
Cloning of Human Ubiquitin-conjugating Enzymes UbcH6 and UbcH7 (E2-F1) and Characterization of Their Interaction with E6-AP and RSP5 (*)

E6-AP, a 100-kDa cellular protein, was originally identified through its interaction with the E6 protein of the oncogenic human papillomavirus types 16 and 18. The complex of E6-AP and E6 specifically interacts with p53 and mediates ubiquitination of p53 in concert with the E1 ubiquitin-activating enzyme and the E2 ubiquitin-conjugating enzyme UbcH5. Recent results suggest that E6-AP is representative of a family of putative ubiquitin-protein ligases. Members of this family are characterized by a conserved C-terminal region, termed hect domain. In this paper, we describe the isolation of two human E2s, designated as UbcH6 and UbcH7, that in addition to UbcH5 can interact with E6-AP. UbcH6 is a novel member of an evolutionally conserved subfamily of E2s that includes UbcH5 and Saccharomyces cerevisiae UBC4. Although UbcH7 does not appear to be a member of this subfamily, UbcH7 efficiently substitutes for UbcH5 in E6-AP-dependent ubiquitination. Surprisingly, UbcH6 was only weakly active in this particular assay. In addition, UbcH5 but not UbcH6 or UbcH7 efficiently interacts with the hect protein RSP5. These results indicate that E6-AP can interact with at least two species of E2 and that different hect proteins may interact with different E2s.
Landmarks in understanding the central nervous control of the cardiovascular system

In this Paton Lecture I have tried to trace the key experiments that have developed ideas on how the brain regulates the cardiovascular system. It is a personal view and inevitably, owing to constraints on space and time, I have not been able to cover areas such as the nucleus tractus solitarius and cardiac vagal neurones, although I acknowledge that some may consider the story is incomplete without them. Starting with the crucial discovery of vasomotor nerves and ‘vasomotor tone’, the patterns of activity in sympathetic nerves which led to the important idea of central oscillating networks of neurones are described. I discuss how this knowledge has informed current controversies on the origin of vasomotor activity in presympathetic neurones in the ventral medulla, which identify intrinsic pacemaker activity or synaptic input from multiple oscillators as prime mechanisms. I present an emerging view that the role of other regions of the brain, in particular supramedullary sites, has been underplayed. These regions are pivotal for the non‐uniform distribution of cardiac output that is unique to each reflex and behavioural state. I discuss the most recent evidence for ‘central command’ neurones that offers a plausible explanation for how these patterns of sympathetic activity are achieved. Finally, I stress the importance of these current ideas to the understanding of pathological changes in sympathetic activity in cardiovascular diseases such as hypertension or congestive heart failure.
Accelerating Boolean satisfiability through application specific processing

This paper presents an application specific multiprocessor system for SAT, utilizing the most recent results such as the development of highly efficient sequential SAT algorithms, the emergence of commercial configurable processor cores and the rapid progress in IC manufacturing techniques. Based on an analysis of the basic SAT search algorithm, we propose a new parallel SAT algorithm that utilizes fine grain parallelism. This is then used to design a multiprocessor architecture in which each processing node consists of a processor and a communication assist node that deals with message processing. Each processor is an application specific processor built from a commercial configurable processor core. All the system configurations are determined based on the characteristics of SAT algorithms, and are supported by simulation results. While this hardware accelerator system does not change the inherent intractability of the SAT problems, it achieves a 30-60x speedup over and above the fastest known SAT solver - Chaff. We believe that this system can be used to expand the practical applicability of SAT in all its application areas.
Oxytocin, vasopressin, and Williams syndrome: epigenetic effects on abnormal social behavior

Williams syndrome (WS) is a condition caused by a deletion of ∼26–28 genes on chromosome 7q11.23 often characterized by abnormal social behavior and disrupted oxytocin (OT) and vasopressin (AVP) functioning. The observation that individuals with WS exhibit OT and AVP dysregulation is compelling. There is currently a lack of evidence that any of the genes typically deleted in WS have any direct effect on either OT or AVP. In this perspective article, we present a novel epigenetic model describing how DNA methylation may impact the expression of key genes within the OT and AVP systems, which may ultimately influence the social behavior observed in WS. We draw support from data pooled from a prior empirical research study (Henrichsen et al., 2011), demonstrating that OXTR is overexpressed in WS. These preliminary findings may create new opportunities to target the OT and AVP systems with the specific goal of improving outcomes in WS and other psychiatric conditions.
Stochastic analysis of genetic promoter architectures with memory

Stochasticity in the gene-expression process can create variability in the level of a given mRNA/protein across a homogenous population of living cells. Random fluctuations between different promoter states have been implicated as a major source of noise in the expression of many genes. These fluctuations are typically modeled through a two-state promoter architecture, where the promoter of a gene transitions between an active (ON) and inactive (OFF) state, spending an exponentially distributed time-interval in each state. High levels of mRNA production occur from the active state, while the inactive state allows for a low basal rate of production. Recent data has shown the existence of three-state promoter architectures with memory, where the time spent in the inactive state is gamma distributed. Here we analyze stochastic models of both two-state and three-state promoter architectures and identify key differences in their stochastic dynamics. Quantifying distance between probability distributions using standard metrics reveals that the difference in the mRNA copy number distributions for both promoter architectures is maximum when the stability of the active promoter state is comparable to the stability of the mRNA transcript. Our results further show that mRNA auto-correlations decay more rapidly for a three-state promoter architecture compared to a two-state promoter architecture. Interestingly, we find that in certain parameter regimes the three-state promoter architecture can yield negative mRNA auto-correlations. Finally, we discuss how these results can be useful for identifying genetic promoter architectures from single-cell mRNA data.
SAR image registration based on extremal scattering regions in multiscale framework

This paper propose a novel concept of the Extremal Scattering Regions (ESR) for registration of satellite SAR images without prerequisite acquisition parameters or projection correction. It is implemented in the multiscale framework. First, the ERS is extracted and used for primary registration in the coarse scale. Then, the mutual information is used to fine-tune the registration of the images in the fine scale. The performance of this algorithm is demonstrated in the experiment with TerraSAR-X and Radarsat-2 SAR images, and validated by the results with RMS errors in the range and azimuth directions of 0.338 and 0.134 pixels, respectively.
Unconstrained scene text and video text recognition for Arabic script

Building robust recognizers for Arabic has always been challenging. We demonstrate the effectiveness of an end-to-end trainable CNN-RNN hybrid architecture in recognizing Arabic text in videos and natural scenes. We outperform previous state-of-the-art on two publicly available video text datasets — ALIF and ACTIV. For the scene text recognition task, we introduce a new Arabic scene text dataset and establish baseline results. For scripts like Arabic, a major challenge in developing robust recognizers is the lack of large quantity of annotated data. We overcome this by synthesizing millions of Arabic text images from a large vocabulary of Arabic words and phrases. Our implementation is built on top of the model introduced here [37] which is proven quite effective for English scene text recognition. The model follows a segmentation-free, sequence to sequence transcription approach. The network transcribes a sequence of convolutional features from the input image to a sequence of target labels. This does away with the need for segmenting input image into constituent characters/glyphs, which is often difficult for Arabic script. Further, the ability of RNNs to model contextual dependencies yields superior recognition results.
Sine wave cancellation through a periodic transfer function

This paper presents a method of reducing a sinusoidal disturbance through a periodic transfer function. First, a precise definition of the problem (transfer function and disturbance characteristics) is made. A control strategy that minimizes a quadratic cost function is next elaborated. Its good performances are then compared with a classical adaptive feeforward control method thanks to simulation results. It attenuates 90% of the disturbance power in simulation. The finality of this work is to decrease the vibrations of an electrical synchronous machine, and the method reaches a 60% attenuation rate on real signals. Implementation of this algorithm can then be envisaged.
Rainbow Plots, Bagplots, and Boxplots for Functional Data

We propose new tools for visualizing large amounts of functional data in the form of smooth curves. The proposed tools include functional versions of the bagplot and boxplot, which make use of the first two robust principal component scores, Tukey’s data depth and highest density regions. By-products of our graphical displays are outlier detection methods for functional data. We compare these new outlier detection methods with existing methods for detecting outliers in functional data, and show that our methods are better able to identify outliers. An R-package containing computer code and datasets is available in the online supplements.
Is Postoperative Computed Tomography Evaluation a Prognostic Indicator in Patients with Optimally Debulked Advanced Ovarian Cancer?

Objective: To compare the surgeon's intraoperative assessment of residual tumor (RT) disease with that identified on postoperative computed tomography (CT) in patients undergoing optimal primary surgical cytoreduction (RT <1 cm) and to identify the prognostic significance of postoperative CT scan of RT. Methods: Patients with FIGO stage III-IV ovarian cancer treated at the Gynecologic Oncology Unit of the National Cancer Institute between November 2011 and March 2013, who underwent optimal primary cytoreduction and were entered in prospective controlled clinical trials requiring a baseline postoperative CT evaluation within 30 days, were enrolled. All CT scans were reviewed by a dedicated radiologist to evaluate RT. Median follow-up was 16 months. Results: 64 out of 160 patients met the eligibility criteria. RT = 0, 0.1 < RT < 0.5 cm, and 0.6 < RT < 1 cm was reported in 53 (82.8%), 9 (14.1%) and 2 (3.1%) cases, respectively. Postoperative CT disagreed with RT in 13 out of 64 (20.3%) cases. Progression-free survival (PFS) of patients with a positive and negative postoperative CT scan of RT was 5 months (95% CI 1-15 months) and 28 months (95% CI 2-46 months), respectively (p < 0.0001). Evidence of the disease using postoperative CT was an independent prognostic factor in multivariate analysis (HR = 8.87, 95% CI = 3.23-24.31, p < 0.0001). Conclusions: Evidence of the disease using postoperative CT was associated with a significant decrease in PFS in patients who underwent optimal primary cytoreduction. RT status as evaluated with early postoperative CT may have an important role in prognostic assessment.
Averaged Switch Modeling of Boundary Conduction Mode

Averaged switch approach is extended to the modeling of boundary conduction mode (BCM) dc-to-dc converters that operate at the boundary between continuous conduction mode (CCM) and discontinuous conduction mode (DCM). BCM dc-to-dc converters have smaller inductor size and reduced switching losses compared to CCM, and lower peak current compared to DCM. The large-signal BCM averaged switch model shows that several BCM converters with input voltage feedforward exhibit resistive or nearly resistive input characteristic, which is well suited for realization of power factor correctors. It is shown that BCM converters exhibit simpler dynamics compared to CCM current programmed control (CPM). Small-signal frequency responses predicted by the averaged switch model are verified by simulation and experiments.
Human Parainfluenza Virus Type 1 C Proteins Are Nonessential Proteins That Inhibit the Host Interferon and Apoptotic Responses and Are Required for Efficient Replication in Nonhuman Primates

ABSTRACT Recombinant human parainfluenza virus type 1 (rHPIV1) was modified to create rHPIV1-P(C−), a virus in which expression of the C proteins (C′, C, Y1, and Y2) was silenced without affecting the amino acid sequence of the P protein. Infectious rHPIV1-P(C−) was readily recovered from cDNA, indicating that the four C proteins were not essential for virus replication. Early during infection in vitro, rHPIV1-P(C−) replicated as efficiently as wild-type (wt) HPIV1, but its titer subsequently decreased coincident with the onset of an extensive cytopathic effect not observed with wt rHPIV1. rHPIV1-P(C−) infection, but not wt rHPIV1 infection, induced caspase 3 activation and nuclear fragmentation in LLC-MK2 cells, identifying the HPIV1 C proteins as inhibitors of apoptosis. In contrast to wt rHPIV1, rHPIV1-P(C−) and rHPIV1-CF170S, a mutant encoding an F170S substitution in C, induced interferon (IFN) and did not inhibit IFN signaling in vitro. However, only rHPIV1-P(C−) induced apoptosis. Thus, the anti-IFN and antiapoptosis activities of HPIV1 were separable: both activities are disabled in rHPIV1-P(C−), whereas only the anti-IFN activity is disabled in rHPIV1-CF170S. In African green monkeys (AGMs), rHPIV1-P(C−) was considerably more attenuated than rHPIV1-CF170S, suggesting that disabling the anti-IFN and antiapoptotic activities of HPIV1 had additive effects on attenuation in vivo. Although rHPIV1-P(C−) protected against challenge with wt HPIV1, its highly restricted replication in AGMs and in primary human airway epithelial cell cultures suggests that it might be overattenuated for use as a vaccine. Thus, the C proteins of HPIV1 are nonessential but have anti-IFN and antiapoptosis activities required for virulence in primates.
Development and Psychometric Evaluation of an Instrument to Assess Reinforcer Preferences

The Preferred Items and Experiences Questionnaire (PIEQ) is a new instrument to assess reinforcer preferences in adolescents and adults. Research was conducted with college and high school students to develop the PIEQ, to examine its reliability with test-retest and internal consistency methods, and to test its validity. This research provides support for the PIEQ’s reliability and validity.