Miracle-dz/UniFAR-FTUs huggingface dataset:
Cauldron mission-centric cyber situational awareness with defense in depth

The cyber situational awareness of an organization determines its effectiveness in responding to attacks. Mission success is highly dependent on the availability and correct operation of complex computer networks, which are vulnerable to various types of attacks. Today, situational awareness capabilities are limited in many ways, such as inaccurate and incomplete vulnerability analysis, failure to adapt to evolving networks and attacks, inability to transform raw data into cyber intelligence, and inability for handling uncertainty. We describe advanced capabilities for mission-centric cyber situational awareness, based on defense in depth, provided by the Cauldron tool. Cauldron automatically maps all paths of vulnerability through networks, by correlating, aggregating, normalizing, and fusing data from a variety of sources. It provides sophisticated visualization of attack paths, with automatically generated mitigation recommendations. Flexible modeling supports multi-step analysis of firewall rules as well as host-to-host vulnerability, with attack vectors inside the network as well as from the outside. We describe alert correlation based on Caldron attack graphs, along with analysis of mission impact from attacks.
Subjective Evaluation of Software Quality Using Crowdsource Knowledge : An Exploratory Study

While subjective judgments have been heavily used in other areas of research including science, humanities, medical studies, and even in human computer interaction, there has been a marked lack on the use of such human factors in evaluating the quality of a software system. In this paper, we explore an idea of using subjective judgements in evaluating the code quality of a software system by using the available crowdsource knowledge of StackOverflow. We first introduce an algorithm for classifying the StackOverflow content as either promoted or discouraged programming solutions by exploiting available quantitative information such as view counts, votes, comment counts and so on. We then use the classified solutions as a vehicle for studying the code quality of open source projects based on the occurrences of promoted or discouraged solutions. Both using a cross-validation step with machine learning classifiers and a user study, we confirm that the proposed classifier is able capture the technical merits as well as social acceptance (a.k.a., subjective human judgements) of the programming solutions. In order to demonstrate the applicability of the proposed approach, we then conduct a case study with 332,628 StackOverflow posts for determining the subjective quality of 20 target open source software systems. In order to further confirm of whether such an approach makes sense we then also validate the findings with a traditional code quality evaluation tool and two project review sites. Our study shows that while such an ad-hoc nondeterministic approach by no means replaces the state of the art code quality measurements tools, it certainly has the potential to complement the existing well-rounded objective evaluation tools by incorporating a third dimension of subjective evaluation.
Single-Input CMAC Control System with Direct Control Ability

Without the help of any workable controller, a single-input cerebellar model articulation controller (CMAC) control system, which contains only one controller implemented by the one-dimensional CMAC, is proposed in this study. Without requiring a preliminary off-line learning phase, the single-input CMAC controller can still provide the control effort to the plant at each time step. In addition, the proposed controller is also in the learning stage. Hence the single-input CMAC controller is said to have the direct control ability. This study also introduces the adaptive deadzone size into the learning rule to solve the instability caused by the continued learning of the CMAC. Simulations on controlling a nonlinear discrete plant are given to demonstrate the effectiveness of the proposed controller.
StrokeBank: Automating Personalized Chinese Handwriting Generation

Machine learning techniques have been successfully applied to Chinese character recognition; nonetheless, automatic generation of stylized Chinese handwriting remains a challenge. In this paper, we propose StrokeBank, a novel approach to automating personalized Chinese handwriting generation. We use a semi-supervised algorithm to construct a dictionary of component mappings from a small seeding set. Unlike previous work, our approach does not require human supervision in stroke extraction or knowledge of the structure of Chinese characters. This dictionary is used to generate handwriting that preserves stylistic variations, including cursiveness and spatial layout of strokes. We demonstrate the effectiveness of our model by a survey-based evaluation. The results show that our generated characters are nearly indistinguishable from ground truth handwritings.
Geometric Robust Watermarking through Mesh Model Based Correction

While geometric attacks are one of the most challenging problems in watermarking, random bending is the most difficult to handle among all geometric attacks. Such attacks are difficult to correct by traditional parameter estimation or registration approaches. In this paper, we present a watermarking scheme based on a deformable mesh model to combat such attacks. The distortion is corrected using the distortion field (DF) estimated by minimizing the matching error between the meshes of the original and attacked image. A CDMA watermarking method is proposed, which embeds a multibit signature in the DCT domain and uses mesh model based correction to achieve robustness. Experiments show that the proposed scheme can survive wide range of random bending attacks.
A Group For Integrating Treatment Lessons Into Daily Life

David S. Prescott, LICSW Introduction This article describes an approach to working with people who have sexually abused and who have completed some aspects of treatment but may not be ready to progress to another stage of treatment. For example, many programs offer some type of preparatory work for sexual abuse-specific treatment through one or more cognitive skills curricula. However, simply completing one workbook or curriculum does not mean that the client is successfully applying the skills and insights gained in treatment to their daily life. This can particularly be the case in civil commitment settings, where clients sometimes experience fluctuating levels of motivation.
Device Fingerprinting in Wireless Networks: Challenges and Opportunities

Node forgery or impersonation, in which legitimate cryptographic credentials are captured by an adversary, constitutes one major security threat facing wireless networks. The fact that mobile devices are prone to be compromised and reverse engineered significantly increases the risk of such attacks in which adversaries can obtain secret keys on trusted nodes and impersonate the legitimate node. One promising approach toward thwarting these attacks is through the extraction of unique fingerprints that can provide a reliable and robust means for device identification. These fingerprints can be extracted from transmitted signal by analyzing information across the protocol stack. In this paper, the first unified and comprehensive tutorial in the area of wireless device fingerprinting for security applications is presented. In particular, we aim to provide a detailed treatment on developing novel wireless security solutions using device fingerprinting techniques. The objectives are three-fold: (i) to introduce a comprehensive taxonomy of wireless features that can be used in fingerprinting, (ii) to provide a systematic review on fingerprint algorithms including both white-list based and unsupervised learning approaches, and (iii) to identify key open research problems in the area of device fingerprinting and feature extraction, as applied to wireless security.
Involvement of Complexin 2 in Docking, Locking and Unlocking of Different SNARE Complexes during Sperm Capacitation and Induced Acrosomal Exocytosis

Acrosomal exocytosis (AE) is an intracellular multipoint fusion reaction of the sperm plasma membrane (PM) with the outer acrosomal membrane (OAM). This unique exocytotic event enables the penetration of the sperm through the zona pellucida of the oocyte. We previously observed a stable docking of OAM to the PM brought about by the formation of the trans-SNARE complex (syntaxin 1B, SNAP 23 and VAMP 3). By using electron microscopy, immunochemistry and immunofluorescence techniques in combination with functional studies and proteomic approaches, we here demonstrate that calcium ionophore-induced AE results in the formation of unilamellar hybrid membrane vesicles containing a mixture of components originating from the two fused membranes. These mixed vesicles (MV) do not contain the earlier reported trimeric SNARE complex but instead possess a novel trimeric SNARE complex that contained syntaxin 3, SNAP 23 and VAMP 2, with an additional SNARE interacting protein, complexin 2. Our data indicate that the earlier reported raft and capacitation-dependent docking phenomenon between the PM and OAM allows a specific rearrangement of molecules between the two docked membranes and is involved in (1) recruiting SNAREs and complexin 2 in the newly formed lipid-ordered microdomains, (2) the assembly of a fusion-driving SNARE complex which executes Ca2+-dependent AE, (3) the disassembly of the earlier reported docking SNARE complex, (4) the recruitment of secondary zona binding proteins at the zona interacting sperm surface. The possibility to study separate and dynamic interactions between SNARE proteins, complexin and Ca2+ which are all involved in AE make sperm an ideal model for studying exocytosis.
Control Estimation Error of Sampling Method for Passive Measurement

Sampling is increasingly utilized by passive measurement systems to save the resources consumption. However, the widely adopted static linear sampling selects packets with the same sampling rate (probability) for both large flows and small flows, which leads to intolerably high relative error for small flows. In order to bound the relative error for both small and large flows, we have proposed an adaptive nonlinear sampling method for passive measurement, which dynamically tunes the sampling rate according to the counter value. We have provided the unbiased estimation of the actual number of events n and have demonstrated that the relative error is radic[(1-1/n)a/2] for both large flows and small flows, where a is a constant parameter, and the counter size is bounded by a logarithmic function, log(1+an)/log(1+a). The theoretical and experimental results have shown that the proposed adaptive sampling method obtain a better tradeoff between relative error and memory consumption than existing sampling methods.
The Epstein–Barr virus nuclear antigen-1 promotes genomic instability via induction of reactive oxygen species

The Epstein–Barr virus (EBV) nuclear antigen (EBNA)-1 is the only viral protein expressed in all EBV-carrying malignancies, but its contribution to oncogenesis has remained enigmatic. We show that EBNA-1 induces chromosomal aberrations, DNA double-strand breaks, and engagement of the DNA damage response (DDR). These signs of genomic instability are associated with the production of reactive oxygen species (ROS) and are reversed by antioxidants. The catalytic subunit of the leukocyte NADPH oxidase, NOX2/gp91phox, is transcriptionally activated in EBNA-1–expressing cells, whereas inactivation of the enzyme by chemical inhibitors or RNAi halts ROS production and DDR. These findings highlight a novel function of EBNA-1 and a possible mechanism by which expression of this viral protein could contribute to malignant transformation and tumor progression.
Simulation by BPM and FDTD of new thin heterogeneous optical waveguides on SOI for reconfigurable optical add/drop multiplexers

This paper presents the new type of heterogeneous optical waveguide on silicon-on-insulator (SOI) and its application for ROADM. The side p-n-doping of 220 nm times 35 mum silicon core provides quasi-single-mode behavior due to small optical losses for fundamental mode with 10 mum mode width and increasing losses for the higher modes.
Semi-supervised Learning of the Hidden Vector State Model for Protein-Protein Interactions Extraction

A major challenge in text mining for biology and biomedicine is automatically extracting protein-protein interactions from the vast amount of biological literature since most knowledge about them still hides in biological publications. Existing approaches can be broadly categorized as rule-based or statistical-based. Rule-based approaches require heavy manual efforts. On the other hand, statistical-based approaches require large-scale, richly annotated corpora in order to reliably estimate model parameters. This is normally difficult to obtain in practical applications. The hidden vector state (HVS) model, an extension of the basic discrete Markov model, has been successfully applied to extract protein-protein interactions. In this paper, we propose a novel approach to train the HVS model on both annotated and un-annotated corpus. Sentences selection algorithm is designed to utilize the semantic parsing results of the un-annotated corpus generated by the HVS model. Experimental results show that the performance of the initial HVS model trained on a small amount of the annotated data can be improved by employing this approach
A Novel Algorithm for Solving the True Coincident Counting Issues in Monte Carlo Simulations for Radiation Spectroscopy

AbstractCoincident counts can be observed in experimental radiation spectroscopy. Accurate quantification of the radiation source requires the detection efficiency of the spectrometer, which is often experimentally determined. However, Monte Carlo analysis can be used to supplement experimental approaches to determine the detection efficiency a priori. The traditional Monte Carlo method overestimates the detection efficiency as a result of omitting coincident counts caused mainly by multiple cascade source particles. In this study, a novel “multi-primary coincident counting” algorithm was developed using the Geant4 Monte Carlo simulation toolkit. A high-purity Germanium detector for 60Co gamma-ray spectroscopy problems was accurately modeled to validate the developed algorithm. The simulated pulse height spectrum agreed well qualitatively with the measured spectrum obtained using the high-purity Germanium detector. The developed algorithm can be extended to other applications, with a particular emphasis on challenging radiation fields, such as counting multiple types of coincident radiations released from nuclear fission or used nuclear fuel.
High spectral efficiency coherent optical OFDM transmission

We show 1-Tb/s single-channel CO-OFDM transmission consisting of continuous 4,104 spectrally-overlapped subcarriers generated using a novel device of recirculating frequency shifter (RFS). The 1-Tb/s CO-OFDM signal with a spectral efficiency of 3.3 bit/s/Hz is successfully received after transmission over 600-km SSMF fiber without either Raman amplification or dispersion compensation.
Genre Classification of Websites Using Search Engine Snippets

Web pages often contain clutter (such as ads, unnecessary images and extraneous links) around the body of an article, which distracts a user from actual content. Automatic extraction of “useful and relevant” content from web pages has many applications, including browsing on small cell phone and PDA screens, speech rendering for the visually impaired, and reducing noise for information retrieval systems. Prior work has led to the development of Crunch, a framework which employs various heuristics in the form of filters and filter settings for content extraction. Crunch allows users to tune these settings, essentially the thresholds for applying each filter. However, in order to reduce human involvement in selecting these heuristic settings, we have extended this work to utilize a website’s classification, defined by its genre and physical layout. In particular, Crunch would then obtain the settings for a previously unknown website by automatically classifying it as sufficiently similar to a cluster of known websites with previously adjusted settings - which in practice produces better content extraction results than a single one-size-fits-all set of setting defaults. In this paper, we present our approach to clustering a large corpus of websites by their genre, utilizing the snippets generated by sending the website’s domain name to search engines as well as the website’s own text. We find that exploiting these snippets not only increased the frequency of function words that directly assist in detecting the genre of a website, but also allow for easier clustering of websites. We use existing techniques like Manhattan distance measure and Hierarchical clustering, with some modifications, to pre-classify websites into genres. Our clustering method does not require prior knowledge of the set of genres that websites fit into, but instead discovers these relationships among websites. Subsequently, we are able to classify newly encountered websites in linear-time, and then apply the corresponding filter settings, with no noticeable delay introduced for the content-extracting web proxy.
Appearance sampling for obtaining a set of basis images for variable illumination

Previous studies have demonstrated that the appearance of an object under varying illumination conditions can be represented by a low-dimensional linear subspace. A set of basis images spanning such a linear subspace can be obtained by applying the principal component analysis (PCA) for a large number of images taken under different lighting conditions. While the approaches based on PCA have been used successfully for object recognition under varying illumination conditions, little is known about how many images would be required in order to obtain the basis images correctly. In this study, we present a novel method for analytically obtaining a set of basis images of an object for arbitrary illumination from input images of the object taken under a point light source. The main contribution of our work is that we show that a set of lighting directions can be determined for sampling images of an object depending on the spectrum of the object's BRDF in the angular frequency domain such that a set of harmonic images can be obtained analytically based on the sampling theorem on spherical harmonics. In addition, unlike the previously proposed techniques based on spherical harmonics, our method does not require the 3D shape and reflectance properties of an object used for rendering harmonics images of the object synthetically.
Metabolism and Thermoregulation in Wild and Lab House Mice 945 Introduction Laboratory strains of house mice ( Mus domesticus ) often serve as model systems in behavior , morphology , physiology , and quantitative genetics

We conducted a "common garden" experiment to compare aspects of thermoregulation and metabolism in wild and random-bred laboratory house mice (Mus domesticus) and their reciprocal crosses. Analysis of covariance (ANCOVA) indicated that, after accounting for effects of body mass and other appropriate covariates (e.g., age), wild (N = 12) and hybrid (N = 25) mice together tended to have higher (+9. 7%; P = .0904) maximal nonshivering thermogenesis (max-NST) in response to norepinephrine injection than did lab mice (N = 18). Wild (-17.2%; P = .0941) and hybrid (wild dam: -23.1%; P = .0001; lab dam: 11.2%; P = .0749) mice also tended to have lower basal metabolic rates (BMRs) than did lab mice. As a consequence of these trends, wild and hybrid mice, analyzed together, had significantly higher (+ 18.2%; P = .0263) regulatory NST (max-NST minus BMR) than did lab mice. Paralleling the differences in regulatory NST, wild and hybrid mice together had significantly more (+21.2%; P = .0129) interscapular brown adipose tissue than did lab mice. However, plasma thyroid hormone levels (triiodothyronine [ T3] and thyroxine [T4]) showed no significant differences among groups, and, even for the traits that exhibited significant differences, the overlap of values for individual mice was substantial. Moreover, mean values for max-NST and BMRfor all four groups fell well within the range of values reported in the literature for small mammals. We therefore concluded that random-bred laboratory mice are not necessarily "degenerate" with respect to their metabolic and thermoregulatory capacities. Finally, the two reciprocal cross groups differed in BMR (P = .0314), which thus indicated a maternal influence: wild-dam X lab-sire mice had significantly lower BMRs than did lab-dam X wild-sire mice. * Present address and address for correspondence: D partment of Biology, 5 Cummington St., Boston University, Boston, Massachusetts 02215. Physiological Zoology 67(4):944-975. 1994. c 1994 by The University of Chicago. All rights reserved. 0031-935X/94/6704-9310$02.00 This content downloaded from 138.23.140.49 on Tue, 14 May 2013 18:38:31 PM All use subject to JSTOR Terms and Conditions Metabolism and Thermoregulation in Wild and Lab House Mice 945
L2 ACQUISITION OF PROSODIC PROPERTIES OF SPEECH RHYTHM

This study examines the development of speech rhythm in second language (L2) learners of typologically different first languages (L1s) at different levels of proficiency. An empirical investigation of durational variation in L2 English productions by L1 Mandarin learners and L1 German learners compared to native control values in English and the learners’ L1s showed that the L1 groups followed comparable developmental paths in their acquisition of vocalic variability and accentual lengthening. However, the two L1 groups diverged in the proportion of vocalic materials in their L2 utterances, exhibiting L2 acquisition patterns that are consistent with direct transfer from the L1. The results support a multisystemic model of L2 rhythm acquisition in which the various linguistic-systemic properties that contribute to speech rhythm are acquired at different proficiency levels and depend on different acquisition processes with respect to L1 influence and universal effects. We conclude that theories of L2 phonology need to be able to accommodate the multisystemic nature of L2 prosodic acquisition. Additionally, L2 phonological acquisition theories, and SLA theories more generally, should take into account the nonuniform manner in which the various prosodic properties of the interlanguage reflect L1 transfer effects as well as universal constraints on acquisition.
Obesity: Do Grapes Hold the Answer?

Resveratrol, a small polyphenol, has recently been shown to protect mice from many detrimental effects of diet-induced obesity (1,2). Treated animals are less prone to develop fatty liver or insulin-resistance, have improved motor coordination, and survive nearly as long as lean control animals despite persistent obesity. At higher doses, weight gain is significantly attenuated. Moreover, resveratrol improves aerobic capacity, endurance, and cold tolerance, suggesting that its protective effects are associated with general improvements in metabolism and increased energy expenditure. By many measures, mice fed a high-fat diet plus resveratrol appear as healthy as their lean counterparts.