Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing byte-level network intrusion detection signatures with context

Many network intrusion detection systems (NIDS) use byte sequences as signatures to detect malicious activity. While being highly efficient, they tend to suffer from a high false-positive rate. We develop the concept of contextual signatures as an improvement of string-based signature-matching. Rather than matching fixed strings in isolation, we augment the matching process with additional context. When designing an efficient signature engine for the NIDS bro, we provide low-level context by using regular expressions for matching, and high-level context by taking advantage of the semantic information made available by bro's protocol analysis and scripting language. Therewith, we greatly enhance the signature's expressiveness and hence the ability to reduce false positives. We present several examples such as matching requests with replies, using knowledge of the environment, defining dependencies between signatures to model step-wise attacks, and recognizing exploit scans.To leverage existing efforts, we convert the comprehensive signature set of the popular freeware NIDS snort into bro's language. While this does not provide us with improved signatures by itself, we reap an established base to build upon. Consequently, we evaluate our work by comparing to snort, discussing in the process several general problems of comparing different NIDSs.
Towards cinematic internet video-on-demand

Video-on-demand (VoD) is increasingly popular with Internet users. It gives users greater choice and more control than live streaming or file downloading. Systems such as MSN Video and YouTube deliver content at low bitrates. This may suit short clips, but great films and 5-minute bloopers are as different as symphonies and jingles. For cinema, poor quality and high jitter are less acceptable. Combining user control with high bitrate is compelling, but technically challenging. VoD is expensive due to the load it places on video source servers. Many researchers have proposed using peer-to-peer (P2P) techniques to shift load from sources to peers (peer-assistance), yet none have implemented and deployed a system with the first purpose of openly and systematically evaluating this approach. To fill this void, we have built and deployed GridCast1. GridCast doubles the bitrates of current popular internet VoD systems, provides a full set of VCR2 operations, and employs peer-assistance to improve scalability and continuity. GridCast has been live on CERNET3 since May of 2006. In peak months, GridCast has served videos to approximately 23,000 users. From the beginning, we have gathered information to understand GridCast and improve its algorithms. This paper introduces and evaluates GridCast. In May of 2007, we deployed multivideo caching, a major change to the caching algorithms. This paper analyzes scalability and continuity before and after this change. Our results contain several surprises and underline the importance of deployment to validate simulation results. We discuss what improvements can be developed beyond multivideo caching.
Forecast of Stock Index Volatility Using Grey GARCH-Type Models

This paper integrated genetic algorithm (GA) and grey forecasting (GM(1,1)) model into three GARCH- type models and proposed GAGM-GARCH-type models. GM(1,1) model was used to modify the error terms of the GARCH-type models to improve the volatility forecasting performance of the traditional GARCH-type models. Meanwhile, as for the shortcomings on parameters estimation of GM(1,1) model, GA was adopted to find the optimal grey parameters of GM(1,1) model. Using the stock data of China stock market, the paper compared the performance of the GAGAM-GARCH-type models in out-of-sample volatility forecasting with those of the GM-GARCH-type, RGM-GARCH-type, and GARCH-type models. It is indicated by the values of the evaluation criteria that the GAGM-GARCH-type models have better volatility forecasting performances relative to the other three types of GARCH-type models.
Gene Expression from Bronchoscopy Obtained Tumour Samples as a Predictor of Outcome in Advanced Inoperable Lung Cancer

Background Several studies have shown the prognostic and predictive potential of molecular markers in combined therapy for lung cancer. Most of them referred, however, to operable early stage NSCLC. The aim of the present study is to correlate the expression of multiple mRNA markers in bronchoscopy obtained cancer specimens with clinical outcome of advanced lung cancer. Methods Bronchoscopy cancer specimens were taken from 123 patients with radiological diagnosis of advanced lung tumor. Out of 123 patients 50 were diagnosed with squamous cell cancer, 17 with adenocarcinoma, 12 with NOS, 32 with SCLC and one with large cell neuroendocrinal cancer. In 11 patients other tumours were diagnosed. The group was heterogeneous with respect to clinical stage, performance of the patients and treatment. Quantitative real time PCR was carried out by ABI 7900 HT machine, with Universal Probe Library (Roche) fluorescent probes. The genes selected for the analysis were ERCC1, EGFR, BRCA1, CSF1, CA9, DUSP6, STAT1, ERBB3, MMD, FN1, and CDKN1B. Results More than 50 ng of RNA (the amount considered sufficient for the analysis) was isolated in 82 out of 112 lung cancer specimens (73%), including 60/80 (75.0%) of NSCLC specimens and 22/32 (68,7%) of SCLC samples. The highest Cohen’s κ coefficient for discrimination between small cell, squamous cell and adenocarcinoma was found for CDKN1B, CSF and EGFR1 (κ = 0.177, p = 0.0041). A multivariate Cox regression model has shown a significant impact of clinical stage (p<0.001, RR = 4.19), ERCC1 (p = 0.01, RR = 0.43) and CA9 (p = 0.03, RR = 2.11) expression on overall survival in a group of 60 patients with NSCLC. Conclusion These results show the feasibility of multiple gene expression analysis in bronchoscopy obtained cancer specimens as prognostic markers in radiotherapy and chemotherapy for advanced lung cancer. A limiting factor was relatively high proportion of samples from which sufficient amount of RNA could not be isolated.
Postinfancy growth, schooling, and cognitive achievement: Young Lives

Background: Early life growth failure and resulting cognitive deficits are often assumed to be very difficult to reverse after infancy. Objective: We used data from Young Lives, which is an observational cohort of 8062 children in Ethiopia, India, Peru, and Vietnam, to determine whether changes in growth after infancy are associated with schooling and cognitive achievement at age 8 y. Design: We represented the growth by height-for-age z score at 1 y [HAZ(1)] and height-for-age z score at 8 y that was not predicted by the HAZ(1). We also characterized growth as recovered (stunted at age 1 y and not at age 8 y), faltered (not stunted at age 1 y and stunted at age 8 y), persistently stunted (stunted at ages 1 and 8 y), or never stunted (not stunted at ages 1 and 8 y). Outcome measures were assessed at age 8 y. Results: The HAZ(1) was inversely associated with overage for grade and positively associated with mathematics achievement, reading comprehension, and receptive vocabulary. Unpredicted growth from 1 to 8 y of age was also inversely associated with overage for grade (OR range across countries: 0.80–0.84) and positively associated with mathematics achievement (effect-size range: 0.05–0.10), reading comprehension (0.02–0.10), and receptive vocabulary (0.04–0.08). Children who recovered in linear growth had better outcomes than did children who were persistently stunted but were not generally different from children who experienced growth faltering. Conclusions: Improvements in child growth after early faltering might have significant benefits on schooling and cognitive achievement. Hence, although early interventions remain critical, interventions to improve the nutrition of preprimary and early primary school–age children also merit consideration.
Ieee Transactions on Pattern Analysis and Machine Intelligence 1 Learning Shared, Discriminative, and Compact Representations for Visual Recognition

—Dictionary-based and part-based methods are among the most popular approaches to visual recognition. In both methods, a mid-level representation is built on top of low-level image descriptors and high-level classifiers are trained on top of the mid-level representation. While earlier methods built the mid-level representation without supervision, there is currently great interest in learning both representations jointly to make the mid-level representation more discriminative. In this work we propose a new approach to visual recognition that jointly learns a shared, discriminative, and compact mid-level representation and a compact high-level representation. By using a structured output learning framework, our approach directly handles the multiclass case at both levels of abstraction. Moreover, by using a group-sparse prior in the structured output learning framework, our approach encourages sharing of visual words and thus reduces the number of words used to represent each class. We test our proposed method on several popular benchmarks. Our results show that, by jointly learning mid-and high-level representations, and fostering the sharing of discriminative visual words among target classes, we are able to achieve state-of-the-art recognition performance using far less visual words than previous approaches.
Robust Visual Tracking via Fuzzy Kernel Representation

A r obust v isual k ernel t racking approach is presented for solving the problem of existing background pixels in object model. At first, after definition of fuzzy set on image is given, a fuzzy factor is embedded into object model to form the fuzzy kernel representation. Secondly, a fuzzy membership functions are generated by center-surround approach and log likelihood ratio of feature distributions. Thirdly, details about fuzzy kernel tracking algorithm is provided. After that, methods of parameter selection and performance evaluation for tracking algorithm are proposed. At last, a mass of experimental results are done to show our method can reduce the influence of the incomplete representation of object model via integrat ing both color features and background features.
Design of Low-Density Parity-Check Codes with Optimized Complexity-Rate Tradeoff

The optimal complexity-rate tradeoff for errorcorrecting codes at rates strictly below the Shannon limit is a central question in coding theory. This paper proposes a numerical approach for the joint optimization of rate and decoding complexity for long-block-length irregular low-density parity-check (LDPC) codes. The proposed design methodology is applicable to any binary-input memoryless symmetric channel and any iterative message-passing decoding algorithm with a parallel-update schedule. A key feature of the proposed optimization method is a new complexity measure that incorporates both the number of operations required to carry out a single decoding iteration and the number of iterations required for convergence. This paper shows that the proposed complexity measure can be accurately estimated from a density-evolution and extrinsic-information transfer chart analysis of the code. Under certain mild conditions, the complexity measure is a convex function of the variable edge-degree distribution of the code, allowing an efficient design of complexity-optimized LDPC codes using convex optimization methods. The results presented herein show that when the decoding complexity is constrained, the complexity-optimized codes significantly outperform thresholdoptimized codes at long block lengths.
Message in a Bottle: Stylized Rendering of Sand Movies

Stylized rendering, usually referred as non-photorealistic rendering, aims to reproduce artistic techniques in renderings, trying to express feelings and moods on the rendered scenes, as opposed to realistic rendering techniques, that aim to produce realistic renderings of artificial scenes. In this paper, we present a stylized rendering technique that aims to create synthetic sand-filled bottles, simulating a typical art craft from the northeastern region of Brazil, that usually depicts landscape images. A method for generating 2D procedural sand textures is presented, and two new techniques that mimic effects created by the artists using their tools are introduced. The technique is also used to generate stylized videos, something close to impossible in real life with this technique. The temporal coherence within these stylized videos can be enforced on individual objects with the aid of a video segmentation algorithm. The techniques were used on synthetic and real videos, and several snapshots from these videos are shown here.
Studying applications for touch-enabled mobile phone keypads

We present a platform to evaluate mobile phone applications that make use of an additional dimension for key presses. Using capacitive sensors on each key, merely touching buttons as well as the force of the press can be measured. A set of applications well known from current mobile phones has been extended with functionality exploiting those new possibilities. The results of a study undertaken with this prototype are presented and conclusions are drawn for the design and implementation of such applications.
Verification of multiplication facts: an investigation using retrospective protocols.

Retrospective verbal protocols collected throughout participants' performance of a multiplication verification task (e.g., "7 x 3 = 28, true or false? ") documented a number of different strategies and changes in strategy use across different problem categories used for this common experimental task. Correct answer retrieval and comparison to the candidate answer was the modal but not the only strategy reported. Experiment 1 results supported the use of a calculation algorithm on some trials and the use of the difference between the candidate and correct answers (i.e., split) on others. Experiment 2 clearly demonstrated that participants sometimes bypassed retrieval by relying on the split information. Implications for mental arithmetic theories and the general efficacy of retrospective protocols are discussed.
Magnetic Resonance and Computed Tomography Imaging for the Evaluation of Pulmonary Hypertension

1. Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 2. Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL 3. Department of Radiology, University of Wisconsin, Madison, WI 4. Division of Pulmonary and Critical Care Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 5. Feinberg Cardiovascular Research Institute, Northwestern University Feinberg School of Medicine, Chicago, IL
KHDC1B Is a Novel CPEB Binding Partner Specifically Expressed in Mouse Oocytes and Early Embryos

The expression and activities of two members of a novel KH domain protein family were tested. KHDC1A and 1B are highly expressed in oocytes. Based on ectopic expression, KHDC1A regulates apoptosis whereas 1B interacts with the cytoplasmic polyadenylation machinery. KHDC1B may serve as a translational repressor during oocyte maturation.
Efficient hexapodal locomotion control based on flow-invariant subspaces

Abstract In this paper the issue of locomotion control in bio-inspired hexapod structures is considered as a problem of convergence toward flow invariant subspaces in networks of mutually and locally coupled neural units. Since the network topologies used refer to undirected diffusive tree graphs, in this case a unique gain value on the graph connection matrix can be found to guarantee exponential convergence to any desired gait (i.e. phase locked) configuration. Such sufficient condition is exploited for the locomotion control in a hexapod structure. In the paper, after dealing with the sufficient condition above mentioned, both simulation and experimental results on a robotic hexapod structure are reported. Moreover the role of key parameters for insect inspired turning strategies is investigated.
Critical Phenomena in Complex Networks

Networks arise in wide variety of contexts across disciplines, from social networks in sociology and transport networks in engineering, to networks for disease spreading in epidemiology and metabolic networks in biology. In this essay we provide an introduction to the systematic study of networks. We discuss a few important network models, focusing particularly on features that are similar to those that arise in statistical physics. We also discuss the application of renormalization group methods to examine the critical properties of a simple network model.
Multi-strategy genetic algorithm for multimodal optimization

Multimodal optimization (MMO) is the problem of finding many or all global and local optima. In recent years many efficient nature-inspired techniques (based on ES, PSO, DE and others) have been proposed for real-valued problems. Many real-world problems contain variables of many different types, including integer, rank, binary and others. In this case, the weakest representation (namely binary representation) is used. Unfortunately, there is a lack of efficient approaches for problems with binary representation. Existing techniques are usually based on general ideas of niching. Moreover, there exists the problem of choosing a suitable algorithm and fine tuning it for a certain problem. In this study, a novel approach based on a metaheuristic for designing multi-strategy genetic algorithm is proposed. The approach controls the interactions of many search techniques (different genetic algorithms for MMO) and leads to the self-configuring solving of problems with a priori unknown structure. The results of numerical experiments for classical benchmark problems and benchmark problems from the CEC competition on MMO are presented. The proposed approach has demonstrated efficiency better than standard niching techniques and comparable to advanced algorithms. The main feature of the approach is that it does not require the participation of the human-expert, because it operates in an automated, self-configuring way.
Whom I Have Called: The Ordain Women Movement and the Narrative of Dissent in the Church of Jesus Christ of Latter-day Saints

ABSTRACT The bulk of existing organizational dissent research has focused on corporate environments, theorizing dissent as a means of seeking and enacting change. This study extends the examination of organizational dissent to a large, highly structured and institutionalized faith organization. This study involves a narrative analysis of 315 microstories written by members of the Ordain Women movement, which seeks ordination of Mormon women into the priesthood. Findings suggest a definition of dissent effectiveness that includes a discursive space of voice, and that dissent may serve as a sensemaking tactic where ongoing dissonance is required for organizational membership. Writers of dissent narratives displayed meek, nonvitriolic dissent tactics that served to reinforce the power structures against which the members dissented.
Inconsistency in theories of violent relaxation

We examine an inconsistency in theories of violent relaxation by Lynden-Bell and Nakamura. The inconsistency arises from the non-transitive nature of these theories: a system that undergoes a violent relaxation, relaxes and then, upon an addition of energy, undergoes violent relaxation once again would settle in an equilibrium state that is different from the one that is predicted had the system gone directly from the initial to the final state. We conclude that a proper description of the violent relaxation process cannot be achieved by an equilibrium statistical mechanics approach, but instead a dynamical theory for the coarse-grained phase-space density is needed.
Detection of partial-band noise interference in slow FH/QPSK systems

In this paper, we propose a detection algorithm to detect unknown partial-band noise interference (PBNI) which is frequently encountered in slow frequency-hopped spread spectrum (SFH-SS) systems. The algorithm utilizes a simple hypothesis testing to decide presence of PBNI in any particular hop after dehopping. A suitable threshold level is first derived to detect the PBNI by analyzing the statistical property of the outputs of two correlators used for quadrature phase-shift-keying (QPSK) demodulation. Then, the proposed detector is developed by summing the outputs of the correlators over one hop duration. We also formulate an expression for probability of detection (PD) and use it as a performance measure for detection. Analytical and simulation results show that the proposed detector is able to detect the PBNI very well even at low interference power (8 dB lower than signal power). In addition, numerical results reveal that the proposed algorithm can also be used to detect multitone interference (MTI) encountered in slow FH-SS systems.
Suitability of a Virtual Learning Environment for Higher Education.

The number of virtual learning environments (VLEs) is increasing. Already a few case studies claim that VLEs are more effective as a learning method than traditional lecturing. Many of these case studies are in the area of information and communication technology (ICT). Therefore, the good learning results are not surprising. The aim of this paper is to examine the suitability of a VLE for higher education by comparing learning with a VLE and learning in a traditional lecture on an occupational safety engineering course. We will compare the learning results and the students’ opinions of their learning process The results show that the VLE students outperformed the lecture students. On the basis of these results and previous case studies, the VLE is suitable for higher education. Nevertheless VLEs should be used with caution in higher education. They should add extra value to a course. One possible value would be to use the VLE self-study method to evaluate one’s learning before a final exam.
Combined inhibition of vascular endothelial growth factor (VEGF), fibroblast growth factor and platelet-derived growth factor, but not inhibition of VEGF alone, effectively suppresses angiogenesis and vessel maturation in endometriotic lesions.

BACKGROUND Angiogenesis represents the crucial step in the pathogenesis of endometriosis, because endometriotic lesions require neovascularization to establish, proliferate and invade inside the peritoneal cavity. To elucidate the role of angiogenic factors, we investigated in vivo whether blockade of vascular endothelial growth factor (VEGF), fibroblast growth factor (FGF), and platelet-derived growth factor (PDGF) affects angiogenesis of ectopic endometrium. METHODS Mechanically isolated endometrial fragments were transplanted into the dorsal skinfold chamber of hormonally synchronized hamsters. Subsequently, we analysed the effect of the VEGF inhibitor SU5416 and the combined VEGF, FGF and PDGF inhibitor SU6668 on angiogenesis of the ectopic endometrium over a time-period of 14 days using intravital fluorescence microscopy. RESULTS Selective blockade of VEGF resulted in a slight reduction of microvessel density when compared to control animals. In contrast, combined inhibition of all three growth factors significantly suppressed angiogenesis of endometrial grafts, as indicated by a reduced size of the microvascular network and a decreased microvessel density. This was caused by an inhibition of blood vessel maturation. CONCLUSIONS Vascularization of endometriotic lesions is not solely driven by VEGF, but depends on the cross-talk between VEGF, FGF and PDGF. Thus, the combined inhibition of these growth factors may represent a novel therapeutic strategy in the treatment of endometriosis.