Miracle-dz/UniFAR-FTUs huggingface dataset:
Rough set and XCS in classification problems

XCS is known to degrade in classification performance when faced with many features that are redundant for rules discovery. In this paper, we propose a novel system combining of rough sets and XCS to deal with the mentioned problem. Firstly, rough set theory is used to handle inconsistent input datasets. The purpose of feature reduction by rough set is to identify the most significant attributes and eliminate the irrelevant ones to form a good feature subset for classification. Secondly, the reduced datasets are used to create a set of rules by using XCS. The main contribution of XCS to learning theory is its rules generation without experts. Finally, by applying the set of rules, we can classify unseen datasets into their specific classes. Experimental results on real-life datasets show that the proposed method can reduce storage space as well as can preserve and may also improve solution accuracy. Beside that, the rule retrieval time is also greatly reduced because the use of Rough-XCS classifier contains a smaller amount of instances with fewer features. Furthermore, the proposed method has a high potential to be used as a mean to construct a classifier system that copes with incomplete, noisy and chaotic data.
Fear of eyes: triadic relation among social anxiety, trypophobia, and discomfort for eye cluster

Imagine you are being gazed at by multiple individuals simultaneously. Is the provoked anxiety a learned social-specific response or related to a pathological disorder known as trypophobia? A previous study revealed that spectral properties of images induced aversive reactions in observers with trypophobia. However, it is not clear whether individual differences such as social anxiety traits are related to the discomfort associated with trypophobic images. To investigate this issue, we conducted two experiments with social anxiety and trypophobia and images of eyes and faces. In Experiment 1, participants completed a social anxiety scale and trypophobia questionnaire before evaluation of the discomfort experienced upon exposure to pictures of eye. The results showed that social anxiety had a significant indirect effect on the discomfort associated with the eye clusters, and that the effect was mediated by trypophobia. Experiment 2 replicated Experiment 1 using images of human face. The results showed that, as in Experiment 1, a significant mediation effect of trypophobia was obtained, although the relationship between social anxiety and the discomfort rating was stronger than in Experiment 1. Our findings suggest that both social anxiety and trypophobia contribute to the induction of discomfort when one is gazed at by many people.
A Social-Enhanced Data Verification Framework against Pollution Attacks in P2P Live Streaming

With successful deployments of commercial swarm-based P2P streaming systems, peer-to-peer streaming traffic grows rapidly in the last few years. To leverage system-wide bandwidth, peers in P2P streaming systems are expected to exchange their own data with other peers, and this is extremely vulnerable to pollution attacks, where malicious peers inject fake data blocks into the network and those fake data blocks will soon be propagated by the innocent nodes received them. Such attack leads to degradation of data delivery ratio and failure to decode the streaming data. In this paper, we propose a novel Social-Enhanced hash-based Cross-verification framework (SEC) to defense content pollution attacks. That is, the fake data is able to be rapidly identified through the SEC scheme, and thus the malicious nodes are isolated from clean peers. With the assistance of social networks, we can reinforce the resilience of our SEC scheme for multiple colluding malicious peers and improve the data availability by the AIMD-based reputation module. The results show that the SEC framework is able to provide high delivery ratio, (as well as high accuracy, low computational overhead, low communication overhead, and low delay) for fulfilling the stringent requirements of P2P live streaming systems even under a severe or dynamic environment (e.g., when the total capacity of polluters is larger than the source node capacity).
Interactive hybrid recommendation with granule selection

Hybrid recommender systems combine different approaches to provide better recommendations. The most common hybrid algorithms mix collaborative, content-based, demographic filtering among others. However, these hybrid approaches seldom consider the user-recommender interaction. In this paper, we propose a new hybrid recommender system through considering the user-recommender interaction. First, we define the recommender and user behaviors. The recommender system accepts user request, recommends N items to the user and records user choice. Second, we employ the recall metric to evaluate the quality of the recommender. The number of recommendations in each turn essentially serves as the accuracy constraint. Third, we test the random, kNN and our hybrid algorithm with the new metric. Specifically, we study the impact of different granules to the performance of our algorithm. Experiments results on the well-known MovieLens dataset show that the hybrid algorithm performs better, and appropriate granule selection is essential.
Chemokine Sequestration by Viral Chemoreceptors as a Novel Viral Escape Strategy: Withdrawal of Chemokines from the Environment of Cytomegalovirus-infected Cells

Human cytomegalovirus (HCMV), a betaherpesvirus, has developed several ways to evade the immune system, notably downregulation of cell surface expression of major histocompatibility complex class I heavy chains. Here we report that HCMV has devised another means to compromise immune surveillance mechanisms. Extracellular accumulation of both constitutively produced monocyte chemoattractant protein (MCP)-1 and tumor necrosis factor–superinduced RANTES (regulated on activation, normal T cell expressed and secreted) was downregulated in HCMV-infected fibroblasts in the absence of transcriptional repression or the expression of polyadenylated RNA for the cellular chemokine receptors CCR-1, CCR-3, and CCR-5. Competitive binding experiments demonstrated that HCMV-infected cells bind RANTES, MCP-1, macrophage inflammatory protein (MIP)-1β, and MCP-3, but not MCP-2, to the same receptor as does MIP-1α, which is not expressed in uninfected cells. HCMV encodes three proteins with homology to CC chemokine receptors: US27, US28, and UL33. Cells infected with HCMV mutants deleted of US28, or both US27 and US28 genes, failed to downregulate extracellular accumulation of either RANTES or MCP-1. In contrast, cells infected with a mutant deleted of US27 continues to bind and downregulate those chemokines. Depletion of chemokines from the culture medium was at least partially due to continuous internalization of extracellular chemokine, since exogenously added, biotinylated RANTES accumulated in HCMV-infected cells. Thus, HCMV can modify the chemokine environment of infected cells through intense sequestering of CC chemokines, mediated principally by expression of the US28-encoded chemokine receptor.
Risk factors for Echinococcus coproantigen positivity in dogs from the Alay valley, Kyrgyzstan

Abstract Echinococcosis, caused by the zoonotic cestodes Echinococcus granulosus (sensu lato) and Echinococcus multilocularis, is highly endemic in the Central Asian Republic of Kyrgyzstan, and is being identified increasingly as a public health problem, especially amongst pastoral communities. As domestic dogs are considered to be the main source of human infection, the identification of potential transmission pathways is of relevance when considering implementing an echinococcosis control scheme. The current report describes the results of an analytical study of canine Echinococcus coproantigen enzyme-linked immunosorbent assay (ELISA) prevalence in the Alay valley of southern Kyrgyzstan prior to the commencement of regular praziquantel dosing of dogs. A logistic regression model using a form of Bayes modal estimation was used to identify possible risk factors for coproantigen positivity, and the output was interpreted in a Bayesian context (posterior distributions of the coefficients of interest). The study found that sheepdogs had lower odds of coproantigen positivity, as did dogs in households with donkeys, where owners had knowledge of echinococcosis, and households which engaged in home slaughtering. Surprisingly, there was no evidence of an association between free roaming or previous praziquantel dosing and coproantigen positivity, as has been found in previous studies. Possible reasons for these findings are discussed in the context of the epidemiology of echinococcosis and potential intervention approaches.
Identification of Author Personality Traits using Stylistic Features: Notebook for PAN at CLEF 2015

Author profiling is the task of determining the age, gender or type of the author's personality by studying their sociolect aspect, that is, how the language is shared by people. This paper presents the COMSATS Institute of Information Technology, Lahore entry for the PAN 2015 competition on Author Profiling task. Our proposed system is based on stylometry features. We implemented 29 different stylistic features, many of which are language independent. Since the training data was available in multiple languages, one of our main objectives was to explore which language independent features are most effective. The problem of author profiling was casted as a supervised document classification task. Results showed that features (Percentage of Question Sentences, Average Sentence Length, Percentage of Punctuations, Percentage of Comma and Percentage of Full stops) were most effective multilingual features.
Reconciling Reusability and Trustworthinessthrough Self-Adapting Components

can significantly reduce the time and costs involved in software engineering, but it also raises some significant verification and validation challenges. Traditionally, there has been a tension between the trustworthiness of systems (i.e. the level of confidence that can be placed in their correct execution) and the level of flexibility and ease with which they can be assembled from reusable components, especially at run-time. This effectively made it difficult for developers to strive for both at the same time. In this paper we present a strategy for alleviating this problem based on a combination of technologies developed to address each individually – built-in testing, developed to enhance the trust-worthiness of systems, and dynamic interface adaptation, developed to reduce the effort involved in deploying a component in a new context. After first describing the two technologies individually, we then explain the synergy between them and present a vision of how, together, they can be used to make components self-adapting. The overall benefit is to introduce a component paradigm in which the compatibility of components is determined by their behavior (i.e. semantics) rather than the form of their interfaces (i.e. syntax).
The SNARE Vti1a-β Is Localized to Small Synaptic Vesicles and Participates in a Novel SNARE Complex

Specific soluble N-ethylmaleimide-sensitive factor attachment protein (SNAP) receptor (SNARE) proteins are required for different membrane transport steps. The SNARE Vti1a has been colocalized with Golgi markers and Vti1b with Golgi and thetrans-Golgi network or endosomal markers in fibroblast cell lines. Here we study the distribution of Vti1a and Vti1b in brain. Vti1b was found in synaptic vesicles but was not enriched in this organelle. A brain-specific splice variant of Vti1a was identified that had an insertion of seven amino acid residues next to the putative SNARE-interacting helix. This Vti1a-β was enriched in small synaptic vesicles and clathrin-coated vesicles isolated from nerve terminals. Vti1a-β also copurified with the synaptic vesicle R-SNARE synaptobrevin during immunoisolation of synaptic vesicles and endosomes. Therefore, both synaptobrevin and Vti1a-β are integral parts of synaptic vesicles throughout their life cycle. Vti1a-β was part of a SNARE complex in nerve terminals, which boundN-ethylmaleimide-sensitive factor and α-SNAP. This SNARE complex was different from the exocytic SNARE complex because Vti1a-β was not coimmunoprecipitated with syntaxin 1 or SNAP-25. These data suggest that Vti1a-β does not function in exocytosis but in a separate SNARE complex in a membrane fusion step during recycling or biogenesis of synaptic vesicles.
A VCO Based Highly Digital Temperature Sensor With 0.034 °C/mV Supply Sensitivity

A self-referenced VCO-based temperature sensor with reduced supply sensitivity is presented. The proposed sensor converts temperature information to frequency and then into digital bits. A novel sensing technique is proposed in which temperature information is acquired by evaluating the ratio of the output frequencies of two ring oscillators, designed to have different temperature sensitivities, thus avoiding the need for an external frequency reference. Reduced supply sensitivity is achieved by employing the voltage dependence of junction capacitance, thus avoiding the overhead of a voltage regulator. Fabricated in a 65 nm CMOS process, the prototype can operate with supply voltages ranging from 0.85 V to 1.1 V. It achieves supply sensitivity of 0.034 °C/mV and an inaccuracy of ±0.9 °C and ±2.3 °C from 0 to 100 °C after 2-point calibration, with and without static nonlinearity correction, respectively. The proposed sensor achieves 0.3 °C resolution, and a resolution FoM of 0.3 nJK2. The prototype occupies a die area of 0.004 mm2.
TOWARDS A FRAMEWORK FOR SECURITY MEASUREMENT

This work aims to devise a framework for measuring system security. We can all agree that the ability to compare, to contrast, and to make quantifiable statements about system security is extremely valuable. It means that we will have a basis to determine where to put our limited resources, where to pay attention, and how to best secure our systems. We also believe that one can obtain a more complete and thorough understanding of a subject through measurements that may not otherwise be possible. “When you can measure what you are speaking about and express it in numbers you know something about it,” wrote Lord Kelvin in 1883. “But when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind. ” This is exactly what motivated our research -to develop the theory and practice of security measurements.
The status and challenge of global fire modelling

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.
Wheat Seed Colonized with Atoxigenic Aspergillus flavus: Characterization and Production of a Biopesticide for Aflatoxin Control

Biocontrol of aflatoxin contamination using atoxigenic Aspergillus flavus to competitively exclude aflatoxin-producing strains has previously been reported, and is currently in the third year of commercial-scale tests (treating 50-200 ha per annum). Wheat seed colonized with atoxigenic A. flavus has been used in the commercial trials. Requirements for production of this colonized wheat seed are described and the spore yield of wheat is compared to other substrates. The study suggests that the most cost-effective inoculum production would require colonization of wheat (106 conidia kg -1 of wheat seed) at 25% (w/w) moisture for 18 h at 31 C. To prevent fungal growth and associated wheat aggregation in storage, seed had to be dried below 15% (w/w) moisture, although a moisture content of 35% (w/w) did not reduce viability in sealed containers stored at 18-25 C over an 8-month period. The dry biopesticide had multi-year stability without refrigeration and withstood temperatures of 70 C for 20 min. Sporulation.
A New Leapfrog Integrator of Rotational Motion. The Revised Angular-Momentum Approach

Abstract A new algorithm is introduced to integrate the equations of rotational motion. The algorithm is derived within a leapfrog framework and the quantities involved into the integration are mid-step angular momenta and on-step orientational positions. Contrary to the standard implicit method by Fincham [Mol. Sim. , 8, 165 (1992)], the revised angular momentum approach presented corresponds completely to the leapfrog idea on interpolation of dynamical variables without using any extrapolations. The proposed scheme intrinsically preserves rigid molecular structures and considerably improves stability properties and energy conservation. As is demonstrated on the basis of simulations for water, it reproduces correct results even with extra large step sizes of order 5fs and 10fs in the cases of energy- and temperature-conserving dynamics, respectively. We show also that iterative solutions can be avoided within our implicit scheme shifting from quaternions to the entire rotation-matrix representation.
Service Composition Issues in Pervasive Computing

Combining existing services to create new pervasive computing services involves special design considerations, including context awareness, contingency management, device heterogeneity, and user empowerment. Service composition is a natural concept around which to structure pervasive systems and individuate parts of them that are suitable for contingency management, application, storage, and so on. The notion of service composition also provides a natural frame for addressing systemic issues such as performance, usability, and security. In this case, such characteristics aren't determined by a particular service but rather by the software architecture-how services are combined.
Large-scale latitudinal distribution of Trichodesmium spp. in the Atlantic Ocean

The Atlantic Meridional Transect (AMT) programme is a series of bi-annual cruises between the Falkland Islands (50°S) and the UK (50°N). Measurements of the abundance of the N2-fixing, colonial cyanobacterium Trichodesmium along this transect in the years 1995–1999 reveal that it is especially abundant between 0 and 15°N, but by contrast almost completely absent between 5 and 30°S. The cruise path between 0 and 15°N lies close to 20°W, on the African (eastern) side of the Atlantic. The maximum colony abundances we observed (100 000 colonies m–2) are greater than those reported in many other studies. The results of different methods for assessing Trichodesmium abundance are compared. Possible correlations between Trichodesmium abundance and several physical and chemical variables were examined to try and elucidate the factors controlling N2 fixer occurrence. High Trichodesmium abundance was found to be correlated with shallow mixed layer depth and high estimated iron deposition to the surface ocean, but not with temperature, nitrate or the concentration of total dissolvable iron in sea water.
Comparison of evolutionary algorithms for LPDA antenna optimization

A novel approach to broadband log‐periodic antenna design is presented, where some of the most powerful evolutionary algorithms are applied and compared for the optimal design of wire log‐periodic dipole arrays (LPDA) using Numerical Electromagnetics Code. The target is to achieve an optimal antenna design with respect to maximum gain, gain flatness, front‐to‐rear ratio (F/R) and standing wave ratio. The parameters of the LPDA optimized are the dipole lengths, the spacing between the dipoles, and the dipole wire diameters. The evolutionary algorithms compared are the Differential Evolution (DE), Particle Swarm (PSO), Taguchi, Invasive Weed (IWO), and Adaptive Invasive Weed Optimization (ADIWO). Superior performance is achieved by the IWO (best results) and PSO (fast convergence) algorithms.
Design of Digital Signal Processing Algorithms Using Tensor Product Formulation

Abstract Many important computation problems can be specified by block recursive algorithms. For example, matrix transposition and fast Fourier transform are block recursive algorithms. In this paper, we present a methodology of VLSI circuit design for block recursive algorithms based on the tensor product theory. Matrix transposition and fast Fourier transform algorithms are designed and implemented following this methodology. First, matrix transposition and fast Fourier transform algorithms are expressed as tensor product formulas. The tensor product formulas are modified to fit into interconnection networks, including the omega network and the hypercube network. The formulas are then used to generate high-level programming language code. Finally, a hardware description language, Verilog, is used to realize the algorithms according to the generated programs. The major goal of this paper is to provide an effective way to design VLSI circuits for block recursive algorithms.
Spatial navigation impairment is proportional to right hippocampal volume

Cognitive deficits in older adults attributable to Alzheimer's disease (AD) pathology are featured early on by hippocampal impairment. Among these individuals, deterioration in spatial navigation, manifested by poor hippocampus-dependent allocentric navigation, may occur well before the clinical onset of dementia. Our aim was to determine whether allocentric spatial navigation impairment would be proportional to right hippocampal volume loss irrespective of general brain atrophy. We also contrasted the respective spatial navigation scores of the real-space human Morris water maze with its corresponding 2D computer version. We included 42 cognitively impaired patients with either amnestic mild cognitive impairment (n = 23) or mild and moderate AD (n = 19), and 14 cognitively intact older controls. All participants underwent 1.5T MRI brain scanning with subsequent automatic measurement of the total brain and hippocampal (right and left) volumes. Allocentric spatial navigation was tested in the real-space version of the human Morris water maze and in its corresponding computer version. Participants used two navigational cues to locate an invisible goal independent of the start position. We found that smaller right hippocampal volume was associated with poorer navigation performance in both the real-space (β = −0.62, P < 0.001) and virtual (β = −0.43, P = 0.026) versions, controlling for demographic variables, total brain and left hippocampal volumes. In subsequent analyses, the results were significant in cognitively impaired (P ≤ 0.05) but not in cognitively healthy (P > 0.59) subjects. The respective real-space and virtual scores strongly correlated with each other. Our findings indicate that the right hippocampus plays a critical role in allocentric navigation, particularly when cognitive impairment is present.