Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Granular Licences to Decentralize Security Administration

There has been for several years a growing interest in defining new access control models and administration facilities for these models. Several models have observed that only structuring the model using the concept of roles as in RBAC is not sufficient to administer decentralized enterprises. These models have suggested to consider new concepts such as organization (as in OrBAC) ordomain(as in GTRBAC) that make it easier to establish secured entreprise communications. In this paper, we suggest a self and decentralized object-oriented administration model built on the concept of organization. This model is merely based on two mechanisms: confinement and licence. Confinement restricts the authority of a subject to the organization (or sub-organizations) to which this subject has been assigned administration privileges. Licence introduces multi grain and contextualadministration facility. It is used to define administration and delegation privileges, to whom they are assigned, in which context they became effective and the scope of each of them.
Comparison of Radical Scavenging Activity, Cytotoxic Effects and Apoptosis Induction in Human Melanoma Cells by Taiwanese Propolis from Different Sources

Propolis is a sticky substance that is collected from plants by honeybees. We previously demonstrated that propolins A, B, C, D, E and F, isolated from Taiwanese propolis (TP), could effectively induce human melanoma cell apoptosis and were strong antioxidant agents. In this study, we evaluated TP for free radical scavenging activity by DPPH (1,2-diphenyl-2-picrylhydrazyl). The phenolic concentrations were quantified by the Folin–Ciocalteu method. The apoptosis trigger activity in human melanoma cells was evaluated. TP contained a higher level of phenolic compounds and showed strong capability to scavenge free radicals. Additionally, TP1g, TP3, TP4 and TP7 exhibited a cytotoxic effect on human melanoma cells, with an IC50 of ∼2.3, 2.0, 3.3 and 3.3 μg/ml, respectively. Flow cytometric analysis for DNA fragmentation indicated that TP1g, TP2, TP3 and TP7 could induce apoptosis in human melanoma cells and there is a marked loss of cells from the G2/M phase of the cell cycle. To address the mechanism of the apoptosis effect of TP, we evaluated its effects on induction of apoptosis-related proteins in human melanoma cells. The levels of procaspase-3 and PARP [poly(ADP-ribose) polymerase] were markedly decreased. Furthermore, propolins A, B, C, D, E and F in TP were determined using HPLC. The results indicate that TP is a rich source of these compounds. The findings suggest that TP induces apoptosis in human melanoma cells due to its high level of propolins.
Conceptual relationships between the ICF and experiences of mealtimes and related tasks among persons with Parkinson’s disease

The aim was to investigate experiences of mealtimes and related tasks among people with Parkinson’s disease (PD) and to link these conceptually to the International Classification of Functioning, Disability and Health (ICF). Data were collected by use of semi-structured interviews of 19 people with PD. Inductive content analysis resulted in five categories: 1) Managing mealtime preparations and related tasks, 2) Compromised physical control, 3) Difficulties enjoying meals, 4) Difficulties eating together with others, and 5) Strategies to maintain conventional norms and independence. Deductive content analysis linked the categories to the ICF categories: body functions (mental, sensory, neuromusculoskeletal and movement-related functions); activities (self-determination and chores); participation (interpersonal interactions and relationships); and environmental factors (conventional norms, attitudes of friends and strangers). Emotional and involuntary movement functions were represented in all five inductively derived categories. Eating difficulties may have negative consequences on participation and the emotional wellbeing of people with Parkinson’s disease.
Structural properties of a flexible-joint robot model with output controllers and some related applications

This paper considers some structural properties of an n-degree-of-freedom flexible-joint robot with a simple stabilizing output controller. It is well known that, in a nonlinear system, global asymptotic stability does not necessarily imply local exponential stability, while the latter property provides an essential tool in studying various control problems. This study shows that for the model under consideration, global asymptotic stability implies local exponential stability. Applications of this result to the topic of small-signal finite-gain Lp stability and to the analysis of the perturbed system are considered. Finally, we show how a local stabilizing controller which is based on position measurements only can be integrated into a strategy that ensures, under some conditions of system uncertainty, set-point regulation (in the global sense) of an uncertain flexible-joint robot. Simulation results, which demonstrate the applications of a control scheme that is presented in this study, are included.
DACS: A dynamic approximative caching scheme for Wireless Sensor Networks

Saving energy in Wireless Sensor Networks is essential to extend the lifetime of in-field deployments. Previous research has shown that communication is generally the most energy consuming task and needs to be reduced in order to build resource-efficient long-term applications. The communication demand for retrieving query results from deep within the sensor network is typically high. As a result, frequent non-continuous data acquisition consumes a lot of energy and shortens the lifetime of the sensor network significantly. In this work we discuss optimizations for processing high amounts of unique queries by using a dynamic adaptive caching scheme: DACS. In DACS query results can be retrieved from caches that are placed nearer to the query source instead of sending queries deep into the network. The communication demand can be significantly reduced and the entire network lifetime is extended. To verify cache coherence in sensor networks with non-reliable communication channels, an approximative update policy is used. To localize the adequate cache adaptively, model-driven queries including a degree of demanded result quality can be defined. The entire logic is thereby processed by DACS and hidden to the user. The significant energy conservation is proven in evaluations that include real sensor node deployments.
The physical activity level in children with asthma based on a survey among 7–16‐year‐old school children

The objective was to compare the physical activity level of children with asthma with that of non‐asthmatic children. A standardized written questionnaire was administered in a survey of school children in three different areas of Norway: Oslo (n=2577), Hallingdal (n=831) and Odda (n= 1177). Response rates were >85% in all areas, and approximately 50% of the respondents were female. No significant differences were found between the distributions in exercise frequency either for children reported ever to have had asthma (P=0.8) or for those with current asthma (P=0.3) compared to non‐asthmatics. Similar results were found for exercise hours a week. More than 50% of all children took part in organized sport. The data suggest that asthmatic children are as physically active as their peers.
Onto-Tools, the toolkit of the modern biologist: Onto-Express, Onto-Compare, Onto-Design and Onto-Translate

Onto-Tools is a set of four seamlessly integrated databases: Onto-Express, Onto-Compare, Onto-Design and Onto-Translate. Onto-Express is able to automatically translate lists of genes found to be differentially regulated in a given condition into functional profiles characterizing the impact of the condition studied upon various biological processes and pathways. OE constructs functional profiles (using Gene Ontology terms) for the following categories: biochemical function, biological process, cellular role, cellular component, molecular function and chromosome location. Statistical significance values are calculated for each category. Once the initial exploratory analysis identified a number of relevant biological processes, specific mechanisms of interactions can be hypothesized for the conditions studied. Currently, many commercial arrays are available for the investigation of specific mechanisms. Each such array is characterized by a biological bias determined by the extent to which the genes present on the array represent specific pathways. Onto-Compare is a tool that allows efficient comparisons of any sets of commercial or custom arrays. Using Onto-Compare, a researcher can determine quickly which array, or set of arrays, covers best the hypotheses studied. In many situations, no commercial arrays are available for specific biological mechanisms. Onto-Design is a tool that allows the user to select genes that represent given functional categories. Onto-Translate allows the user to translate easily lists of accession numbers, UniGene clusters and Affymetrix probes into one another. All tools above are seamlessly integrated. The Onto-Tools are available online at http://vortex.cs. wayne.edu/Projects.html.
Quality of Life in Treatment of Acute Rhinosinusitis with Clarithromycin and Amoxicillin/Clavulanate

Objectives: Clarithromycin and amoxicillin/clavulanate (A/C) are first line antibiotics used to treat uncomplicated acute rhinosinusitis (ARS). This study examined the efficacy of clarithromycin and A/C for the treatment of ARS relative to the patient's quality of life (QOL).
Design and development of a prototype application for intrusion detection using data mining

In the world of communication, security is a big concern. Most of our crucial data is stored in a computer system and in most cases we exchange it over a network. But it's not just our data transmitting over the network but different types of attacks too. These attacks can harm our stored data. Monitoring computer system and its logs (administration logs, security logs, system logs, network logs) and protecting our crucial data is necessary. For these necessities we use intrusion detection system. An intrusion detection system is an application that provides protection from malicious activities or policy violations and generates various rules to defend computer security. Intrusion detection system can be designed and developed on any platform but for its better functionality we are using data mining technique. In past years, many techniques have been introduced to improvise the detection rate. Earlier, in the initial stages of its designing, hardware had to be installed to detect and monitor the system. But, with the help of data mining it has become easier to work with software and algorithm development. In the recent trends, many new algorithms have been introduced to increase its efficiency. They are categorized under machine learning algorithms: supervised, unsupervised and hybrid. Though hybrid has not yet been categorized finely but various authors have used it by merging different machine learning algorithms. Machine learning algorithms provide a process of detecting intrusion and generating rules for its detection and prevention. Rule generation is defined by association rule mining and apriori algorithm. An intrusion detection system is not a new application but developing a prototype which will work for the saved logs (administration logs, security logs and system logs) and monitor network logs on host system as well as on client system, so that the Intrusion detection system can alert the user on regular basis, is. In this paper we are using a hybrid machine learning algorithm following with rule generation algorithm to detect the intrusion in the network logs by training KDD dataset. Training and Testing KDD data set provides the way of analyzing the actual behavior and predicted behavior of the network logs. This paper shows the methodology and results in Netbeans IDE 8.1(Java platform using Weka library). Through the obtained results, it can be interpreted that optimal performance is obtained against most attacks after detection.
A fully integrated self-oscillating switched-capacitor DC-DC converter for near-threshold loads

We introduce a fully integrated step-down self-oscillating switched-capacitor DC-DC converter that delivers near-threshold (NT) output voltages. The converter is built in 28 nm UTBB FD-SOI and occupies 0.0104 mm2. Back-gate biasing is utilized to increase the load power range. Measurements show a peak efficiency of 87%, self start-up capability, and a minimum efficiency of 75% for 79 nW to 200 μW (ideal) loads. Measurements with an off-chip NT processor load also show high efficiency. The converter's large load power range and high efficiency are a good fit for energy-constrained NT processors.
Closed-Loop Control of Humidification for Artifact Reduction in Capacitive ECG Measurements

Recording biosignals without the need for direct skin contact offers new opportunities for ubiquitous health monitoring. Electrodes with capacitive coupling have been shown to be suitable for the monitoring of electrical potentials on the body surface, in particular ECG. However, due to triboelectric charge generation and motion artifacts, signal and thus diagnostic quality is inferior to galvanic coupling. Active closed-loop humidification of capacitive electrodes is proposed in this work as a new concept to improve signal quality. A capacitive ECG recording system integrated into a common car seat is presented. It can regulate the micro climate at the interface of electrode and patient by actively dispensing water vapour and monitoring humidity in a closed-loop approach. As a regenerative water reservoir, silica gel is used. The system was evaluated with respect to subjective and objective ECG signal quality. Active humidification was found to have a significant positive effect in case of previously poor quality. Also, it had no diminishing effect in case of already good signal quality.
Multiplex Real-Time PCR Assay Using TaqMan Probes for the Identification of Trypanosoma cruzi DTUs in Biological and Clinical Samples

Background Trypanosoma cruzi has been classified into six Discrete Typing Units (DTUs), designated as TcI–TcVI. In order to effectively use this standardized nomenclature, a reproducible genotyping strategy is imperative. Several typing schemes have been developed with variable levels of complexity, selectivity and analytical sensitivity. Most of them can be only applied to cultured stocks. In this context, we aimed to develop a multiplex Real-Time PCR method to identify the six T. cruzi DTUs using TaqMan probes (MTq-PCR). Methods/Principal Findings The MTq-PCR has been evaluated in 39 cultured stocks and 307 biological samples from vectors, reservoirs and patients from different geographical regions and transmission cycles in comparison with a multi-locus conventional PCR algorithm. The MTq-PCR was inclusive for laboratory stocks and natural isolates and sensitive for direct typing of different biological samples from vectors, reservoirs and patients with acute, congenital infection or Chagas reactivation. The first round SL-IR MTq-PCR detected 1 fg DNA/reaction tube of TcI, TcII and TcIII and 1 pg DNA/reaction tube of TcIV, TcV and TcVI reference strains. The MTq-PCR was able to characterize DTUs in 83% of triatomine and 96% of reservoir samples that had been typed by conventional PCR methods. Regarding clinical samples, 100% of those derived from acute infected patients, 62.5% from congenitally infected children and 50% from patients with clinical reactivation could be genotyped. Sensitivity for direct typing of blood samples from chronic Chagas disease patients (32.8% from asymptomatic and 22.2% from symptomatic patients) and mixed infections was lower than that of the conventional PCR algorithm. Conclusions/Significance Typing is resolved after a single or a second round of Real-Time PCR, depending on the DTU. This format reduces carryover contamination and is amenable to quantification, automation and kit production.
Uniform Deviation Bounds for Unbounded Loss Functions like k-Means

Uniform deviation bounds limit the difference between a model's expected loss and its loss on an empirical sample uniformly for all models in a learning problem. As such, they are a critical component to empirical risk minimization. In this paper, we provide a novel framework to obtain uniform deviation bounds for loss functions which are *unbounded*. In our main application, this allows us to obtain bounds for $k$-Means clustering under weak assumptions on the underlying distribution. If the fourth moment is bounded, we prove a rate of $\mathcal{O}\left(m^{-\frac12}\right)$ compared to the previously known $\mathcal{O}\left(m^{-\frac14}\right)$ rate. Furthermore, we show that the rate also depends on the kurtosis - the normalized fourth moment which measures the "tailedness" of a distribution. We further provide improved rates under progressively stronger assumptions, namely, bounded higher moments, subgaussianity and bounded support.
An approach for improvement of avionics reliability assessment based on copula theory

This paper seeks to address the drawbacks of the traditional reliability assessment model of avionics products based on failure dependent supposition and the classical reliability assessment method, which is based on copula theory when taking into account the difficulty of calculating and the accuracy of the model. An improved reliability assessment model based on copula theory is proposed to prioritize reliability assessment algorithm when concerned with the situation of correlative failures. In this paper, Cumbel-Hougaard copulas is used to prioritize the model when the failure time variables of avionics products were as the law of Weibull or Exponential distribution, the advantage of this method is also described in this paper. Finally, a case study is presented in this paper. It's obviously that the new reliability assessment approach can resolves the limitations of traditional method and increase the efficiency of the algorithm which based on copula theory. So the new method can increase the precision of reliability analysis and provide more effective data for verification of reliability indicators and design optimization.
Stego-Breaker: Defeating the Steganographic Systems through Genetic-X-Means approach using Image Quality Metrics

Steganography is used to hide the occurrence of communication. This creates a potential problem when this technology is misused for planning criminal activities. Differentiating anomalous images (stego image) from pure images (cover image) is difficult and tedious. This paper investigates the use of a Genetic-X-means classifier, which distinguishes a pure image from the adulterated one. The basic idea is that, the various Image Quality Metrics (IQMs) calculated on cover images and on stego-images vis-a-vis their denoised versions, are statistically different. Our model employs these IQMs to steganalyse the image data. Genetic paradigm is exploited to select the IQMs that are sensitive to various embedding techniques. The classifier between cover and stego-files is built using X-means clustering on the selected feature set. The presented method can not only detect the presence of hidden message but also identify the hiding domains. The experimental results show that the combination strategy (Genetic-X-means) can improve the classification precision even with lesser payload compared to the traditional ANN (Back Propagation Network).
Automatically rating pronunciation through articulatory phonology

Articulatory Phonology’s link between cognitive speech planning and the physical realizations of vocal tract constrictions has implications for speech acoustic and duration modeling that should be useful in assigning subjective ratings of pronunciation quality to nonnative speech. In this work, we compare traditional phoneme models used in automatic speech recognition to similar models for articulatory gestural pattern vectors, each with associated duration models. What we find is that, on the CDT corpus, gestural models outperform the phonemelevel baseline in terms of correlation with listener ratings, and in combination phoneme and gestural models outperform either one alone. This also validates previous findings with a similar (but not gesture-based) pseudo-articulatory representation. Index Terms: pronunciation modeling, nonnative speech, articulatory phonology
A tunable, robust pseudo-resistor with enhanced linearity for scanning ion-conductance microscopy

Fast and high-resolution scanning ion-conductance microscopy (SICM) experiments require a high speed, low noise and low distortion transimpedance amplifier (TIA) as interface circuit. Recent high performance TIAs utilize capacitive feedback. However, their inability to treat DC currents renders them unfavorable for SICM applications and resistive TIAs remain the best choice here. To address this problem, this paper presents an active MOS resistor with improved robustness and linearity to make it suitable for its use as feedback resistor in TIAs for SICM experiments. The presented device features PMOS transistors operating in weak inversion as pseudo-resistors to obtain reduced noise compared to ohmic resistors of the same value. A novel bias circuit is introduced which compensates process variations of the pseudo-resistor. Monte Carlo simulation shows a standard deviation of 3.6 % of the overall resistance. The connection of multiple pseudo-resistors in series, while preserving equal overall resistance, linearizes the I-V characteristic and decreases the total harmonic distortion to 0.26 %. The presented device is incorporated into a low noise and high speed TIA achieving a simulated SNDR of 49 dB over a bandwidth of 1 MHz enabling fast high-resolution topography imaging using SICM.
A graph-based higher-order intermediate representation

Many modern programming languages support both imperative and functional idioms. However, state-of-the-art imperative intermediate representations (IRs) cannot natively represent crucial functional concepts (like higher-order functions). On the other hand, functional IRs employ an explicit scope nesting, which is cumbersome to maintain across certain transformations. In this paper we present Thorin: a higher-order, functional IR based on continuation-passing style that abandons explicit scope nesting in favor of a dependency graph. This makes Thorin an attractive IR for both imperative as well as functional languages. Furthermore, we present a novel program transformation to eliminate the overhead caused by higher-order functions. The main component of this transformation is lambda mangling: an important transformation primitive in Thorin. We demonstrate that lambda mangling subsumes many classic program transformations like tail-recursion elimination, loop unrolling or (partial) inlining. In our experiments we show that higher-order programs translated with Thorin are consistently as fast as C programs.