Miracle-dz/UniFAR-FTUs huggingface dataset:
Programmable Hardware for Deep Packet Filtering on a Large Signature Set

Damage caused by the recent series of application-level network attacks clearly indicate an immediate need for increased security. Most of these attacks can be more accurately detected by a technique termed Deep Packet Inspection. Deep packet inspection not only examines the packet header, but also looks through the entire payload searching for all of the user specified patterns. Payload pattern search is an expensive process, especially when the set of patterns is large. Current solutions employ software filtering systems that is not practical for bandwidth beyond 100 Mbps. For example, one of the most widely used intrusion detection system, Snort, configured with 845 patterns can sustain a throughput of only 50 Mbps running on a dual 1-GHz Pentium III system. The bottleneck of such system is the dynamic pattern search. Therefore, we implement a fast dynamic pattern search engine on a field programmable gate array. Our system filters and identifies the entire 1,625 unique patterns defined in the most current version of Snort rule set. This system is mapped onto a single 400k Xilinx Spartan 3 FPGA XC3S400 with a filtering rate of 1.6 Gbps.
A new CMOS electronically tunable current conveyor based on translinear circuits

A new CMOS electronically tunable current conveyor (ECCII) based on translinear circuits is presented, with low power voltage (plusmn1.2 V) and continuous programmable current gain and highly linear wide tuning range. The current transfer ratio of the conveyor can be accurately controlled by the ratio of the DC bias currents. HSPICE simulation results using 0.35-mum CMOS process model confirm the expected good performance of the proposed ECCII in terms of linearity, frequency response and tunability.
Evolution of Clonal and Susceptibility Profiles of Serotype 19A Streptococcus pneumoniae among Invasive Isolates from Children in Spain, 1990 to 2008

ABSTRACT The genetic structure and antibiotic nonsusceptibility of all serotype 19A Streptococcus pneumoniae pediatric pneumococcal isolates received at the Spanish Pneumococcal Reference Laboratory (1990 to 2008) were analyzed. Of them, 410 (79.8%) isolates belonged to 14 sequence types (STs) with >10 isolates each, and 104 to 73 STs (with 21 new STs, ST5141 to ST5161, with one isolate each). Time trends in 2000 to 2008 (n = 471) were explored by lineal regression. Serotype 19A increased from 5.7% in 2000 to 16.8% in 2008 (R2 = 0.872; P = 0.001). Decreasing trends (P < 0.03) were found for ST202 (R2 = 0.774) and ST81 (R2 = 0.559), and increasing trends (P < 0.03) for ST878 (R2 = 0.544) and ST320 (R2 = 0.530), both belonging to the clonal complex (CC) Denmark14-32 and first detected in 2003 and 2007, respectively, and ST2013 (R2 = 0.704) and ST4461 (R2 = 0.707), both appearing in 2004. Penicillin nonsusceptibility was clustered in ST81, ST276, ST320, ST878, ST2013, and ST4461 (>90% nonsusceptibility), and amoxicillin and cefotaxime nonsusceptibility in ST320: 87% amoxicillin (MIC50/MIC90 = 8/8 μg/ml) and 43.5% cefotaxime (MIC50/MIC90 = 1/2 μg/ml) nonsusceptibility. No trends were found for erythromycin nonsusceptibility (ranging from 38.5% to 66.7%) and cefotaxime nonsusceptibility (ranging from 0.0% to 7.8%), but increasing trends (P < 0.02) were found for oral penicillin (from 16.7% in 2000 to 56.3% in 2008; R2 = 0.628) and amoxicillin (from 0.0% before 2007 to 13.8% in 2008; R2 = 0.628) nonsusceptibility. This study warns about the emergence of serotype 19A STs associated with high-level antibiotic nonsusceptibility, with a role for ST320 and ST878 occupying the niche left by some pneumococcal 7-valent conjugate vaccine (PCV7)-related resistant STs. The rapid expansion of serotype 19A and STs related to antibiotic resistance indicates that vaccines covering serotype 19A present advantages in countering invasive disease.
Similarity Measures for Comparing Biclusterings

The comparison of ordinary partitions of a set of objects is well established in the clustering literature, which comprehends several studies on the analysis of the properties of similarity measures for comparing partitions. However, similarity measures for clusterings are not readily applicable to biclusterings, since each bicluster is a tuple of two sets (of rows and columns), whereas a cluster is only a single set (of rows). Some biclustering similarity measures have been defined as minor contributions in papers which primarily report on proposals and evaluation of biclustering algorithms or comparative analyses of biclustering algorithms. The consequence is that some desirable properties of such measures have been overlooked in the literature. We review 14 biclustering similarity measures. We define eight desirable properties of a biclustering measure, discuss their importance, and prove which properties each of the reviewed measures has. We show examples drawn and inspired from important studies in which several biclustering measures convey misleading evaluations due to the absence of one or more of the discussed properties. We also advocate the use of a more general comparison approach that is based on the idea of transforming the original problem of comparing biclusterings into an equivalent problem of comparing clustering partitions with overlapping clusters.
Equilibrium Efficiency and Price Complexity in Sponsored Search Auctions

Modern sponsored search auctions are derived from the Generalized Second Price (GSP) auction. Although the GSP auction is not truthful, results by Edelman, Ostrovsky, and Schwarz [7] and Varian [13] give senses in which its outcome is equivalent to that of the truthful and welfaremaximizing VCG mechanism. The first main message of this paper is that these properties are not unique to the GSP auction: there is a large class of payment rules that, when coupled with the rank-by-bid allocation rule, induce sponsored search auctions with comparable guarantees. The second main message is that the GSP auction is “optimally simple”, subject to possessing a welfare-maximizing Nash equilibrium, when the complexity of a payment rule is measured using the dependencies between bids and slot prices. ∗Microsoft Research, Mountain View, CA 94043. Email moshe@microsoft.com. †Department of Computer Science, Stanford University, 462 Gates Building, 353 Serra Mall, Stanford, CA 94305. Supported in part by NSF CAREER Award CCF-0448664, an ONR Young Investigator Award, an ONR PECASE Award, an AFOSR MURI grant, and an Alfred P. Sloan Fellowship. Email: tim@cs.stanford. edu.
Extended imaging, deconvolution, and two-way wavefields: A comparison

Multiple-scattered waves contain information that is commonly disregarded during imaging and tomography. Marchenko wavefields are superior to time-reverse wavefields by handling primaries together with internal and surface-related multiples. Using all types of waves for imaging can greatly improve the illumination and augment the sensitivity of the data to errors in the background velocity model. We compare extended images computed with reverse time and Marchenko wavefields, and investigate the potential of using multidimensional deconvolution for extended images in order to obtain higher image resolution. Our experiments show that the Marchenko wavefields are sensitive to errors in the background model in a way that is similar to the sensitivity of time-reverse wavefields. The main difference between these imaging strategies is the improved angle illumination with the Marchenko wavefields due to the correct use of multiples; this improvement can eliminate the bias of tomography operators towards lower velocities when the data are contaminated with multiples.
Efficient generation and execution of DAG-structured query graphs

Traditional database management systems use tree-structured query evaluation plans. While easy to implement, a tree-structured query evaluation plan is not expressive enough for some optimizations like factoring common algebraic subexpressions or magic sets. These require directed acyclic graphs (DAGs), i.e. shared subplans. This work covers the different aspects of DAG-structured query graphs. First, it introduces a novel framework to reason about sharing of subplans and thus DAG-structured query evaluation plans. Second, it describes the first plan generator capable of generating optimal DAG-structured query evaluation plans. Third, an efficient framework for reasoning about orderings and groupings used by the plan generator is presented. And fourth, a runtime system capable of executing DAG-structured query evaluation plans with minimal overhead is discussed. The experimental results show that with no or only a modest increase of plan generation time, a major reduction of query execution time can be achieved for common queries. This shows that DAG-structured query evaluation plans are serviceable and should be preferred over tree-structured query plans.
Interactive Algorithms for Unsupervised Machine Learning

Abstract : This thesis explores the power of interactivity in unsupervised machine learning problems. Interactive algorithms employ feedback-driven measurements to reduce data acquisition costs and consequently enable statistical analysis in otherwise intractable settings. Unsupervised learning methods are fundamental tools across a variety of domains, and interactive procedures promise to broaden the scope of statistical analysis. We develop interactive learning algorithms for three unsupervised problems: subspace learning, clustering, and tree metric learning. Our theoretical and empirical analysis shows that interactivity can bring both statistical and computational improvements over non-interactive approaches. An over-arching thread of this thesis is that interactive learning is particularly powerful for non-uniform datasets, where non-uniformity is quantified differently in each setting. We first study the subspace learning problem, where the goal is to recover or approximate the principal subspace of a collection of partially observed data points. We propose statistically and computationally appealing interactive algorithms for both the matrix completion problem, where the data points lie on a low dimensional subspace, and the matrix approximation problem, where one must approximate the principal components of a collection of points. We measure uniformity with the notion of incoherence, and we show that our feedback-driven algorithms perform well under much milder incoherence assumptions. We next consider clustering a dataset represented by a partially observed similarity matrix. We propose an interactive procedure for recovering a clustering from a small number of carefully selected similarity measurements. The algorithm exploits non-uniformity of cluster size, using few measurements to recover larger clusters and focusing measurements on the smaller structures.
Painterly rendering controlled by multiscale image features

What we present in this paper is a 2D non-photorealistic, stroke-based image rendering technique, which is a fully automatic template-based painting method controlled by the structure of the model image. Namely it is based on dominant, weighted image edges and ridges extracted by a multiscale edge/ridge detection method. Stroke sizes (scales) and painting directions are both controlled by edge and ridge weights and orientations. This way the painting process becomes more "natural" in the sense that all of its parameters are guided by image features. We also present different painting variations based on this technique.
Poster: Conquering Uncertainty in Java Programming

Uncertainty in programming is one of the challenging issues to be tackled, because it is error-prone for many programmers to temporally avoid uncertain concerns only using simple language constructs such as comments and conditional statements. This paper proposes ucJava, a new Java programming environment for conquering uncertainty. Our environment provides a modular programming style for uncertainty and supports test-driven development taking uncertainty into consideration.
Quantitative Analysis of Lens Nuclear Density Using Optical Coherence Tomography (OCT) with a Liquid Optics Interface: Correlation between OCT Images and LOCS III Grading

Purpose. To quantify whole lens and nuclear lens densities using anterior-segment optical coherence tomography (OCT) with a liquid optics interface and evaluate their correlation with Lens Opacities Classification System III (LOCS III) lens grading and corrected distance visual acuity (BCVA). Methods. OCT images of the whole lens and lens nucleus of eyes with age-related nuclear cataract were analyzed using ImageJ software. The lens grade and nuclear density were represented in pixel intensity units (PIU) and correlations between PIU, BCVA, and LOCS III were assessed. Results. Forty-seven eyes were analyzed. The mean whole lens and lens nuclear densities were 26.99 ± 5.23 and 19.43 ± 6.15 PIU, respectively. A positive linear correlation was observed between lens opacities (R 2 = 0.187, p < 0.01) and nuclear density (R 2 = 0.316, p < 0.01) obtained from OCT images and LOCS III. Preoperative BCVA and LOCS III were also positively correlated (R 2 = 0.454, p < 0.01). Conclusions. Whole lens and lens nuclear densities obtained from OCT correlated with LOCS III. Nuclear density showed a higher positive correlation with LOCS III than whole lens density. OCT with a liquid optics interface is a potential quantitative method for lens grading and can aid in monitoring and managing age-related cataracts.
Autistic Disorder in Patients with Williams-Beuren Syndrome: A Reconsideration of the Williams-Beuren Syndrome Phenotype

Background Williams-Beuren syndrome (WBS), a rare developmental disorder caused by deletion of contiguous genes at 7q11.23, has been characterized by strengths in socialization (overfriendliness) and communication (excessive talkativeness). WBS has been often considered as the polar opposite behavioral phenotype to autism. Our objective was to better understand the range of phenotypic expression in WBS and the relationship between WBS and autistic disorder. Methodology The study was conducted on 9 French individuals aged from 4 to 37 years old with autistic disorder associated with WBS. Behavioral assessments were performed using Autism Diagnostic Interview-Revised (ADI-R) and Autism Diagnostic Observation Schedule (ADOS) scales. Molecular characterization of the WBS critical region was performed by FISH. Findings FISH analysis indicated that all 9 patients displayed the common WBS deletion. All 9 patients met ADI-R and ADOS diagnostic criteria for autism, displaying stereotypies and severe impairments in social interaction and communication (including the absence of expressive language). Additionally, patients showed improvement in social communication over time. Conclusions The results indicate that comorbid autism and WBS is more frequent than expected and suggest that the common WBS deletion can result in a continuum of social communication impairment, ranging from excessive talkativeness and overfriendliness to absence of verbal language and poor social relationships. Appreciation of the possible co-occurrence of WBS and autism challenges the common view that WBS represents the opposite behavioral phenotype of autism, and might lead to improved recognition of WBS in individuals diagnosed with autism.
Synthesis of Silver Nanoparticles by Chemical Reduction Method and Their Antibacterial Activity

Silver nanoparticles were prepd. by chem. redn. method. Silver nitrate was taken as the metal precursor and hydrazine hydrate as a reducing agent. The formation of the silver nanoparticles was monitored using UV-Vis absorption spectroscopy. The UV-Vis spectroscopy revealed the formation of silver nanoparticles by exhibiting the typical surface plasmon absorption maxima at 418-420 nm from the UV-Vis spectrum. Comparison of theor. (Mie light scattering theory) and exptl. results showed that diam. of silver nanoparticles in colloidal soln. is about 60 nm. We have used energy-dispersive spectroscopy (EDX), X-ray diffraction (XRD), transmission electron microscopy (TEM) and, UV-Vis spectroscopy to characterize the nanoparticles obtained. The energy-dispersive spectroscopy (EDX) of the nanoparticles dispersion confirmed the presence of elemental silver signal no peaks of other impurity were detected. The av. size and morphol. of silver nanoparticles were detd. by transmission electron microscopy (TEM). TEM photographs indicate that the nanopowders consist of well dispersed agglomerates of grains with a narrow size distribution (40 and 60 nm), whereas the radius of the individual particles are between 10 and 20 nm. The synthesized nanoparticles have been structurally characterized by X-ray diffraction and transmission high-energy electron diffraction (HEED). The peaks in the XRD pattern are in good agreement with the std. values of the face-centered-cubic form of metallic silver and no peaks of other impurity cryst. phases were detected. Addnl. , the antibacterial activity of the nanoparticles dispersion was measured by Kirby-Bauer method. The nanoparticles of silver showed high antimicrobial and bactericidal activity against gram pos. bacteria such as Escherichia Coli, Pseudimonas aeruginosa and Staphylococcus aureus which is a highly methicillin resistant strain.
Building detection in high spatial resolution remote sensing imagery with the U-Rotation Detection Network

ABSTRACT Building detection in high spatial resolution optical remote sensing images is important for city planning, navigation, population estimation and many other applications. Although many methods have been proposed, building detection is still a challenging problem due to complex scenes and small or arbitrarily orientated buildings. Moreover, most algorithms detect rotated buildings with horizontal bounding boxes leading to many background pixels being preserved in the final detection, which is not beneficial for post-processing. To address these problems, we present the U-Rotation Detection Network (U-RDN), which can effectively detect buildings with arbitrarily orientated detection bounding boxes. First, the U-Rotation Region Proposal Network (U-RRPN) is proposed to generate rotated proposals through rotated anchors. Then, a Rotation Fast-Region Convolutional Neural Network (RFast-RCNN) is performed, which extracts fixed-size features from rotated proposals and utilizes them to obtain fine-detections. For extracting fixed-size features from rotated proposals, we propose Auto Mask Region-Of-Interest Align (AM-ROI Align). The AM-ROI Align not only reduces abundant noise but also preserves the proper information of an object in ROI. Experimental results using the public building dataset, SpaceNet, show that our method can detect buildings with skewed bounding boxes and has a state-of-the-art performance compared with other algorithms.
Overweight, obesity and fat distribution in 50- to 64-year-old participants in the European Prospective Investigation into Cancer and Nutrition (EPIC)

Abstract Objective: To describe anthropometric characteristics of participants of the European Prospective Investigation into Cancer and Nutrition (EPIC). Design: A cross-sectional analysis of baseline data of a European prospective cohort study. Subjects: This analysis includes study populations from 25 centres in nine European countries. The British populations comprised both a population-based and a ‘health-conscious’ group. The analysis was restricted to 83 178 men and 163 851 women aged 50–64 years, this group being represented in all centres. Methods: Anthropometric examinations were undertaken by trained observers using standardised methods and included measurements of weight, height, and waist and hip circumferences. In the ‘health-conscious’ group (UK), anthropometric measures were predicted from self-reports. Results: Except in the ‘health-conscious’ group (UK) and in the French centres, mean body mass index (BMI) exceeded 25.0 kg m-2. The prevalence of obesity (BMI≥30 kg m-2) varied from 8% to 40% in men, and from 5% to 53% in women, with high prevalences (>25%) in the centres from Spain, Greece, Ragusa and Naples (Italy) and the lowest prevalences (<10%) in the French centres and the ‘health-conscious’ group (UK). The prevalence of a large waist circumference or a high waist-to-hip ratio was high in centres from Spain, Greece, Ragusa and Naples (Italy) and among women from centres in Germany and Bilthoven (The Netherlands). Conclusions: Anthropometric measures varied considerably within the EPIC population. These data provide a strong base for further investigation of anthropometric measures in relation to the risk of chronic diseases, especially cancer.
An oscillating Min system in Bacillus subtilis influences asymmetrical septation during sporulation

The Min system plays an important role in ensuring that cell division occurs at mid-cell in rod-shaped bacteria. In Escherichia coli, pole-to-pole oscillation of the Min proteins specifically inhibits polar septation. This system also prevents polar division in Bacillus subtilis during vegetative growth; however, the Min proteins do not oscillate in this organism. The Min system of B. subtilis plays a distinct role during sporulation, a process of differentiation which begins with an asymmetrical cell division. Here, we show that oscillation of the E. coli Min proteins can be reproduced following their introduction into B. subtilis cells. Further, we present evidence that the oscillatory behaviour of the Min system inhibits sporulation. We propose that an alternative Min system mechanism avoiding oscillation is evolutionarily important because oscillation of the Min system is incompatible with efficient asymmetrical septum formation and sporulation.
Genome Sequences for Streptomyces spp. Isolated from Disease-Suppressive Soils and Long-Term Ecological Research Sites

ABSTRACT We report here the high-quality genome sequences of three Streptomyces spp. isolated as part of a long-term study of microbial soil ecology. Streptomyces sp. strain GS93-23 was isolated from naturally disease-suppressive soil (DSS) in Grand Rapids, MN, and Streptomyces sp. strains S3-4 and 3211-3 were isolated from experimental plots in the Cedar Creek Ecosystem Science Reserve (CCESR).
Sparse structures : statistical theory and practice , Bristol , June 2010 Abstracts

Alexandre Tsybakov (Paris VI, France) Estimation of high-dimensional low rank matrices Suppose that we observe entries or, more generally, linear combinations of entries of an unknown m× T -matrix A corrupted by noise. We are particularly interested in the high-dimensional setting where the number mT of unknown entries can be much larger than the sample size N . Motivated by several applications, we consider estimation of matrix A under the assumption that it has small rank. This can be viewed as dimension reduction or sparsity assumption. In order to shrink towards a lowrank representation, we investigate penalized least squares estimators with a Schatten-p quasi-norm penalty term, p ≤ 1. We study these estimators under two possible assumptions – a modified version of the restricted isometry condition and a uniform bound on the ratio ”empirical norm induced by the sampling operator/Frobenius norm”. The main results are stated as non-asymptotic upper bounds on the prediction risk and on the Schatten-q risk of the estimators, where q ∈ [p, 2]. The rates that we obtain for the prediction risk are of the form rm/N (for m = T ), up to logarithmic factors, where r is the rank of A. The particular examples of multi-task learning and matrix completion are worked out in detail. The proofs are based on tools from the theory of empirical processes. As a by-product we derive bounds for the kth entropy numbers of the quasi-convex Schatten class embeddings SM p ↪→ SM 2 , p < 1, which are of independent interest. Joint work with A. Rohde.