Miracle-dz/UniFAR-FTUs huggingface dataset:
An Approach to Predict Drive-by-Download Attacks by Vulnerability Evaluation and Opcode

Drive-by-download attacks exploit vulnerabilities in Web browsers, and users are unnoticeably downloading malware which accesses to the compromised Web sites. A number of detection approaches and tools against such attacks have been proposed so far. Especially, it is becoming easy to specify vulnerabilities of attacks, because researchers well analyze the trend of various attacks. Unfortunately, in the previous schemes, vulnerability information has not been used in the detection/prediction approaches of drive-by-download attacks. In this paper, we propose a prediction approach of "malware downloading" during drive-by-download attacks (approach-I), which uses vulnerability information. Our experimental results show our approach-I achieves the prediction rate (accuracy) of 92%, FNR of 15% and FPR of 1.0% using Naive Bayes. Furthermore, we propose an enhanced approach (approach-II) which embeds Opcode analysis (dynamic analysis) into our approach-I (static approach). We implement our approach-I and II, and compare the three approaches (approach-I, II and Opcode approaches) using the same datasets in our experiment. As a result, our approach-II has the prediction rate of 92%, and improves FNR to 11% using Random Forest, compared with our approach-I.
Reliability and Validity of a New Method for Isometric Back Extensor Strength Evaluation Using A Hand-Held Dynamometer

Objective To investigate the reliability and validity of a new method for isometric back extensor strength measurement using a portable dynamometer. Methods A chair equipped with a small portable dynamometer was designed (Power Track II Commander Muscle Tester). A total of 15 men (mean age, 34.8±7.5 years) and 15 women (mean age, 33.1±5.5 years) with no current back problems or previous history of back surgery were recruited. Subjects were asked to push the back of the chair while seated, and their isometric back extensor strength was measured by the portable dynamometer. Test-retest reliability was assessed with intraclass correlation coefficient (ICC). For the validity assessment, isometric back extensor strength of all subjects was measured by a widely used physical performance evaluation instrument, BTE PrimusRS system. The limit of agreement (LoA) from the Bland-Altman plot was evaluated between two methods. Results The test-retest reliability was excellent (ICC=0.82; 95% confidence interval, 0.65–0.91). The Bland-Altman plots demonstrated acceptable agreement between the two methods: the lower 95% LoA was −63.1 N and the upper 95% LoA was 61.1 N. Conclusion This study shows that isometric back extensor strength measurement using a portable dynamometer has good reliability and validity.
GASTROINTESTINAL PARASITES OF THE COLOBUS MONKEYS OF UGANDA

From August 1997 to July 2003, we collected 2,103 fecal samples from free-ranging individuals of the 3 colobus monkey species of Uganda—the endangered red colobus (Piliocolobus tephrosceles), the eastern black-and-white colobus (Colobus guereza), and the Angolan black-and-white colobus (C. angolensis)—to identify and determine the prevalence of gastrointestinal parasites. Helminth eggs, larvae, and protozoan cysts were isolated by sodium nitrate flotation and fecal sedimentation. Coprocultures facilitated identification of helminths. Seven nematodes (Strongyloides fulleborni, S. stercoralis, Oesophagostomum sp., an unidentified strongyle, Trichuris sp., Ascaris sp., and Colobenterobius sp.), 1 cestode (Bertiella sp.), 1 trematode (Dicrocoeliidae), and 3 protozoans (Entamoeba coli, E. histolytica, and Giardia lamblia) were detected. Seasonal patterns of infection were not apparent for any parasite species infecting colobus monkeys. Prevalence of S. fulleborni was higher in adult male compared to adult female red colobus, but prevalence did not differ for any other shared parasite species between age and sex classes.
Synchronization of coupled connected neural networks with delays

We investigate synchronization of an array of linearly coupled identical connected neural networks with delays; Variational method is used to investigate local synchronization. Global exponential stability is studied, too. We do not assume that the coupling matrix A is symmetric or irreducible. The linear matrix inequality approach is used to judge synchronization with global convergence property.
Structural Characterization of the Bradyzoite Surface Antigen (BSR4) from Toxoplasma gondii, a Unique Addition to the Surface Antigen Glycoprotein 1-related Superfamily*

Toxoplasma gondii is an obligate intracellular protozoan parasite that infects nearly one-third of the human population. The success of T. gondii is based on its complex life cycle; a lytic tachyzoite form disseminates infection, whereas an encysted bradyzoite form establishes a latent, chronic infection. Persistence and transmissibility is central to the survival of the parasite and is, in part, mediated by a family of antigenically distinct surface antigen glycoprotein (SAG)-related sequences (SRS) adhesins that play a dual role in host cell attachment and host immune evasion. More than 160 members of the SRS family have been identified with only the tachyzoite-expressed SAG1 structurally characterized. Here we report the first structural description of the bradyzoite adhesin BSR4 using x-ray crystallography and small angle x-ray scattering. The 1.90-Å crystal structure of BSR4 reveals an architecture comprised of tandem β sandwich domains organized in a head to tail fashion with the N-terminal domain responsible for dimer formation. A restructured topology in BSR4 results in a ligand-binding site that is significantly reorganized in both structure and chemistry relative to SAG1, consistent with BSR4 binding a distinct physiological ligand. The small angle x-ray scattering solution structure of BSR4 highlights a potentially important structural role for the interdomain polymorphic linker that imparts significant flexibility that may promote structural adaptation during ligand binding. This study reveals an unexpected level of structural diversity within the SRS superfamily and provides important insight into the role of these virulence factors.
Comparative Results of Using Finite Difference Method and Finite Element Method for the Load-Balancing Routing Problem of WSNs

A massively-dense wireless sensor network may pose many challenges for efficient load-balancing routing algorithm design due to the problem scale and hardware constraints. One approach to mitigate such a scalability problem is to formulate the load-balancing routing problem as a set of partial differential equations (PDEs) through a geographic model. In this paper, we describe two well-known numerical approaches, namely finite difference method and finite element method, for solving the routing PDEs, and compare the quality of their derived routing directions in achieving routing load-balancing via simulations.
An Interpolative Model for Elevated Temperature Fatigue Crack Propagation

Abstract : A flexible alternative to the familiar Paris equation has been developed for the interpolative analysis of elevated temperature fatigue crack propagation data. The model is based on the hyperbolic sine equation, log(da/ dn) = C1 sinh (C2(log (delta K) + C3)) + C4, and the coefficients are shown to be simple functions of test frequency, stress ratio, and temperature. This methodology has been successfully used to describe crack propagation characteristics of selected nickel-base, titanium, and steel alloys.
PhoNoCMap: An application mapping tool for photonic networks-on-chip

While providing a promising solution for high-performance on-chip communication, photonic networks-on-chip suffer from insertion loss and crosstalk noise, which may severely constrain their scalability. In this paper, we introduce a methodology and a related tool, PhoNoCMap, for the design space exploration of optical NoCs mapping solutions, which automatically assigns application tasks to the nodes of a generic photonic NoC architecture such that the worst-case either insertion loss or crosstalk noise are minimized. The experimental results show significant benefits in terms of insertion loss and crosstalk noise, allowing improved network scalability.
Prediction of the subcellular location of apoptosis proteins based on approximate entropy

A novel approach based on the concept of approximate entropy is proposed here to predict apoptosis protein subcellular localization. By using of support vector machine and tested on a known dataset which includes 317 apoptosis proteins, the overall prediction accuracy is 85.2%, which is better more than the results of the method which used the hydropathy distribution of protein sequences and increment of diversity to predict apoptosis protein subcellular localization. In order to validate the feasibility of the method ulteriorly, we do the same work on a new dataset including 1551 apoptosis proteins, the overall prediction accuracy is 78.9%, these results show that the approximate entropy representation of protein sequences are very useful for predicting subcellular location of apoptosis protein
NEURON and Python

The NEURON simulation program now allows Python to be used, alone or in combination with NEURON's traditional Hoc interpreter. Adding Python to NEURON has the immediate benefit of making available a very extensive suite of analysis tools written for engineering and science. It also catalyzes NEURON software development by offering users a modern programming tool that is recognized for its flexibility and power to create and maintain complex programs. At the same time, nothing is lost because all existing models written in Hoc, including graphical user interface tools, continue to work without change and are also available within the Python context. An example of the benefits of Python availability is the use of the xml module in implementing NEURON's Import3D and CellBuild tools to read MorphML and NeuroML model specifications.
Modelling User Preferences using Word Embeddings for Context-Aware Venue Recommendation

Venue recommendation aims to assist users by making personalised suggestions of venues to visit, building upon data available from location-based social networks (LBSNs) such as Foursquare. A particular challenge for this task is context-aware venue recommendation (CAVR), which additionally takes the surrounding context of the user (e.g. the user’s location and the time of day) into account in order to provide more relevant venue suggestions. To address the challenges of CAVR, we describe two approaches that exploit word embedding techniques to infer the vector-space representations of venues, users’ existing preferences, and users’ contextual preferences. Our evaluation upon the test collection of the TREC 2015 Contextual Suggestion track demonstrates that we can significantly enhance the effectiveness of a state-of-the-art venue recommendation approach, as well as produce context-aware recommendations that are at least as effective as the top TREC 2015 systems.
Assessment of risks related to increasing heavy metal limits for fertilizers in Finland

Higher limits of metals than currently allowed in Finland are suggested in the proposal for EU regulations. In this report, the effects of increased load of Cd, Hg, Ni, Pb, Cr and As into agricultural soils of Finland are assessed. Mass balance calculations for 100-year scenarios of metal inputs were performed to spring wheat rotation. Cd balances were also calculated for grassland, potato and carrot. Concentration in soil water, annual leaching and erosion, concentration and annual uptake in yield, soil concentration and annual balance are reported. In addition, the effect of increased cereal metal concentrations on the total dietary exposure of Finnish children was calculated. In 100-year time scale, the current metal inputs would lead to a negative (As, Cr and Ni) or at most slightly positive balance (Cd, Pb, Hg), whereas the current maximum level and that of the EU proposal generate positive balances. The inputs allowed in the EU proposal would lead to the following increases in environmental loading and metal concentrations in crops from the level of current realization: As over 13 %, Cr 2 %, Pb 30 %, Hg 64 %, Ni 5.5% and Cd 17–44 % depending on the crop rotation. The increase in total dietary exposure of 3-year-old Finnish children at the age group median level would be 2–5 % for As, 12–13 % for Cd, 9 % for Pb and at least 2 % for Hg. The Finnish environment is vulnerable to metal pollution and any increase in the environmental loading would be negative. Particularly for Cd there is no margin of safety. For the Finnish population, the dietary increases would be harmful as for As, Cd, Ni and Pb even the current exposure levels should be reduced. Publisher Ministry of Agriculture and Forestry Distributed by/ publication sales Distribution by: julkaisut.valtioneuvosto. fi Publication sales: julkaisutilaukset.valtioneuvosto. fi
The design and evaluation of a hybrid sensor network for cane-toad monitoring

This paper investigates a wireless, acoustic sensor network application-monitoring amphibian populations in the monsoonal woodlands of northern Australia. Our goal is to use automatic recognition of animal vocalizations to census the populations of native frogs and the invasive introduced species, the cane toad. This is a challenging application because it requires high frequency acoustic sampling, complex signal processing and wide area sensing coverage. We set up two prototypes of wireless sensor networks that recognize vocalizations of up to 9 frog species found in northern Australia. Our first prototype is simple and consists of only resource-rich Stargate devices. Our second prototype is more complex and consists of a hybrid mixture of Stargates and inexpensive, resource-poor Mica2 devices operating in concert. In the hybrid system, the Mica2s are used to collect acoustic samples, and expand the sensor network coverage. The Stargates are used for resource-intensive tasks such as fast Fourier transforms (FFTs) and machine learning. The hybrid system incorporates three algorithms designed to account for the sampling, processing and communication bottlenecks of the Mica2s (i) high frequency sampling, (ii) compression and noise reduction, to reduce data transmission by up to 90%, and (iii) sampling scheduling, which exploits the sensor network redundancy to increase the effective sample processing rate. We evaluate the performance of both systems over a range of scenarios, and demonstrate that the feasibility and benefits of a hybrid systems approach justify the additional system complexity.
Structural Basis for the Acyltransferase Activity of Lecithin:Retinol Acyltransferase-like Proteins*

Background: The enzymology of aminophospholipid-processing enzymes is not well understood. Results: Structures of HRAS-like tumor suppressors resemble those of thiol proteases with Cys-His-His catalytic triad. Conclusion: An aminophospholipid acyl group first modifies the Cys residue of HRAS-like tumor suppressor enzymes before it is transferred onto a second substrate. Significance: This study provides a structural basis for the enzymatic mechanism of HRAS-like tumor suppressors. Lecithin:retinol acyltransferase-like proteins, also referred to as HRAS-like tumor suppressors, comprise a vertebrate subfamily of papain-like or NlpC/P60 thiol proteases that function as phospholipid-metabolizing enzymes. HRAS-like tumor suppressor 3, a representative member of this group, plays a key role in regulating triglyceride accumulation and energy expenditure in adipocytes and therefore constitutes a novel pharmacological target for treatment of metabolic disorders causing obesity. Here, we delineate a catalytic mechanism common to lecithin:retinol acyltransferase-like proteins and provide evidence for their alternative robust lipid-dependent acyltransferase enzymatic activity. We also determined high resolution crystal structures of HRAS-like tumor suppressor 2 and 3 to gain insight into their active site architecture. Based on this structural analysis, two conformational states of the catalytic Cys-113 were identified that differ in reactivity and thus could define the catalytic properties of these two proteins. Finally, these structures provide a model for the topology of these enzymes and allow identification of the protein-lipid bilayer interface. This study contributes to the enzymatic and structural understanding of HRAS-like tumor suppressor enzymes.
Reducing power consumption for high-associativity data caches in embedded processors

Modern embedded processors use data caches with higher and higher degrees of associativity in order to increase performance. A set-associative data cache consumes a significant fraction of the total power budget in such embedded processors. This paper describes a technique for reducing the D-cache power consumption and shows its impact on power and performance of an embedded processor. The technique utilizes cache line address locality to determine (rather than predict) the cache way prior to the cache access. It thus allows only the desired way to be accessed for both tags and data. The proposed mechanism is shown to reduce the average L1 data cache power consumption when running the MiBench embedded benchmark suite for 8, 16 and 32-way set-associate caches by, respectively, an average of 66%, 72% and 76%. The absolute power savings from this technique increase significantly with associativity. The design has no impact on performance and, given that it does not have mis-prediction penalties, it does not introduce any new non-deterministic behavior in program execution.
Are interferon-&ggr; release assays useful for diagnosing active tuberculosis in a high-burden setting?

Although interferon-&ggr; release assays (IGRAs) are intended for diagnosing latent tuberculosis (TB), we hypothesised that in a high-burden setting: 1) the magnitude of the response when using IGRAs can distinguish active TB from other diagnoses; 2) IGRAs may aid in the diagnosis of smear-negative TB; and 3) IGRAs could be useful as rule-out tests for active TB. We evaluated the accuracy of two IGRAs (QuantiFERON®-TB Gold In-tube (QFT-GIT) and T-SPOT®. TB) in 395 patients (27% HIV-infected) with suspected TB in Cape Town, South Africa. IGRA sensitivity and specificity (95% CI) were 76% (68–83%) and 42% (36–49%) for QFT-GIT and 84% (77–90%) and 47% (40–53%) for T-SPOT®. TB, respectively. Although interferon-&ggr; responses were significantly higher in the TB versus non-TB groups (p<0.0001), varying the cut-offs did not improve discriminatory ability. In culture-negative patients, depending on whether those with clinically diagnosed TB were included or excluded from the analysis, the negative predictive value (NPV) of QFT-GIT, T-SPOT®. TB and chest radiograph in smear-negative patients varied between 85 and 89, 87 and 92, and 98% (for chest radiograph), respectively. Overall accuracy was independent of HIV status and CD4 count. In a high-burden setting, IGRAs alone do not have value as rule-in or -out tests for active TB. In smear-negative patients, chest radiography had better NPV even in HIV-infected patients.
Familiarization to Robot Motion

We study the effect of familiarization on the predictability of robot motion. Predictable motion is motion that matches the observer’s expectation. Because of the difficulty robots have in learning motion from user demonstrations, we explore the idea of having users learn from robot demonstrations – how accurate do users get at predicting how the robot will move? We find that although familiarization significantly increases predictability, its utility depends on how natural the motion is. Overall, familiarization shows great promise, but needs to be combined with other methods that generate appropriate motion with which to be familiarized.
Dense shape reconstruction of a moving object under arbitrary, unknown lighting

We present a method for shape reconstruction from several images of a moving object. The reconstruction is dense (up to image resolution). The method assumes that the motion is known, e.g., by tracking a small number of feature points on the object. The object is assumed Lambertian (completely matte), light sources should not be very close to the object but otherwise arbitrary, and no knowledge of lighting conditions is required. An object changes its appearance significantly when it changes its orientation relative to light sources, causing violation of the common brightness constancy assumption. While a lot of effort is devoted to deal with this violation, we demonstrate how to exploit it to recover 3D structure from 2D images. We propose a new correspondence measure that enables point matching across views of a moving object. The method has been tested both on computer simulated examples and on a real object.
Comparison of the Rhizosphere Bacterial Communities of Zigongdongdou Soybean and a High-Methionine Transgenic Line of This Cultivar

Previous studies have shown that methionine from root exudates affects the rhizosphere bacterial population involved in soil nitrogen fixation. A transgenic line of Zigongdongdou soybean cultivar (ZD91) that expresses Arabidopsis cystathionine γ-synthase resulting in an increased methionine production was examined for its influence to the rhizosphere bacterial population. Using 16S rRNA gene-based pyrosequencing analysis of the V4 region and DNA extracted from bacterial consortia collected from the rhizosphere of soybean plants grown in an agricultural field at the pod-setting stage, we characterized the populational structure of the bacterial community involved. In total, 87,267 sequences (approximately 10,908 per sample) were analyzed. We found that Acidobacteria, Proteobacteria, Bacteroidetes, Actinobacteria, Chloroflexi, Planctomycetes, Gemmatimonadetes, Firmicutes, and Verrucomicrobia constitute the dominant taxonomic groups in either the ZD91 transgenic line or parental cultivar ZD, and that there was no statistically significant difference in the rhizosphere bacterial community structure between the two cultivars.