Miracle-dz/UniFAR-FTUs huggingface dataset:
An optimal control of bio-robotic leg for human-like walking

This paper presents an optimal control of bio-robotic leg for human-like walking. A mathematical dynamic model of bio-robotic leg having three links i.e. thigh, shank and foot is considered here. The Lagrange-Euler formulation is used to obtain the dynamic equations of motion for calculating torques at various joints of bio-robotic leg. Polynomial trajectory used as desired trajectory is based on gait cycle of human walking data. The results showed that the proposed optimal controller can be used to control level walking of a bio-robotic leg just like human even with bounded uncertainties. This study will help to improve the quality of life of physically challenged human subject with bio-robotic leg for level walking as well as walking over uneven surfaces and uncertain environmental conditions.
On the Equivalence of CoCoA+ and DisDCA

In this document, we show that the algorithm CoCoA+ (Ma et al., ICML, 2015) under the setting used in their experiments, which is also the best setting suggested by the authors that proposed this algorithm, is equivalent to the practical variant of DisDCA (Yang, NIPS, 2013).
Structural traffic analysis for network security monitoring

Traffic on the Internet is constantly growing more complex and multifaceted. This natural evolution is mirrored by novel kinds of malicious traffic: automated attacks subvert thousands of machines at a time, enabling a wide range of subsequent attacks and nuisances such as distributed denial-of-service attacks and generation of vast amounts of unsolicited electronic mail. Consequently, there is a strong need to be able to tell malicious traffic from the benign. In this dissertation, I take several steps toward this goal. By leveraging structural aspects of network traffic, typical as well as malicious activity on computer networks can be fingerprinted and contrasted. A first avenue is the analysis of application-level flow content. I investigate the suitability of biological sequence alignment algorithms in the adversarial environment of the networking domain, and introduce a novel algorithm that is well over an order of magnitude faster than the commonly used Smith-Waterman algorithm while maintaining much of its flexibility. I introduce a novel and highly flexible model of traffic content based on sequence alignment, Common Substring Graphs, and demonstrate its versatility in a study of application-level protocol classification. Switching focus to the malicious, I pioneer the use of honeypots and sequence analysis algorithms for automated fingerprinting of malware and thus demonstrate the feasibility of fully automated network-based malware signature generation. I propose a second approach to fingerprinting the malicious: Packet Symmetry focuses on network-level structure and leverages the intuition that well-behaved applications do not transmit vastly more packets than they receive. Traffic analysis confirms the feasibility of employing packet symmetry for edge-based, ingress-focused prevention strategies for volume-based attacks.
How Big Is Your Neighborhood? Spatial Implications Of Market Participation By Smallholder Livestock Producers

Identifying ways to increase market participation by smallholder producers requires identifying variables that influence market access. This is usually achieved using probit estimation. An important phenomenon affecting entry decision-making is the entry decision of a 'similar' household, where similarity is measured in terms of 'location. ' When neighborhood influences are significant, it is important to allow for them in discrete decision contexts, such as probit estimation. This paper, therefore, assesses the magnitude of neighborhood influences in smallholder decisions concerning market entry. The empirical model is based on a cross-section of (110) farms situated in northern Philippines, visited (twice) in the 2000-2001 production year (a panel of 220 observations). The vehicle for analysis is a Bayesian formulation of a standard probit model, but one that allows for spatial autoregression in the decision vector. Estimation requires a Metropolis-step addition to a basic Gibbs sampling algorithm and generates useful insights concerning quantities that are important for market-access policy.
Determination of Force Field Parameters for the Octahedral Iron Complex in Lipoxygenase 1 Determination of Force Field Parameters for the Octahedral Iron Complex in Lipoxygenase

Lipoxygenases catalyze the positionand stereospecific dioxygenation of fatty acids and lipids to chiral conjugated hydroperoxy fatty acids. They are found in all higher organisms. Their products are the precursors of a number of physiological effectors. Some details of the catalytic mechanisms of these enzymes are still not known. In particular, it is unclear how molecular oxygen penetrates deep into the binding pocket and how the fatty acid substrate is aligned to the active site containing an octahedral iron complex. To address these important points we plan to perform extensive molecular dynamics (MD) simulations. A necessary prerequisite for these calculations is to determine the force field parameters used in MD describing the molecular interactions regarding the iron complex in a physically reliable manner. In this complex, the iron is coordinated with four histidines, the C-terminal carboxy group and one hydroxy anion pointing into the binding pocket. During the reaction Fe3+ is reduced to Fe2+, consuming one electron which resulted from the abstraction of a hydrogen atom from the lipid substrate. The corresponding proton is taken up by the hydroxide.
Flux vacua and supermanifolds

As been recently pointed out, physically relevant models derived from string theory require the presence of non-vanishing form fluxes besides the usual geometrical constraints. In the case of NS-NS fluxes, the Generalized Complex Geometry encodes these informations in a beautiful geometrical structure. On the other hand, the R-R fluxes call for supergeometry as the underlying mathematical framework. In this context, we analyze the possibility of constructing interesting supermanifolds recasting the geometrical data and RR fluxes. To characterize these supermanifolds we have been guided by the fact topological strings on supermanifolds require the super-Ricci flatness of the target space. This can be achieved by adding to a given bosonic manifold enough anticommuting coordinates and new constraints on the bosonic sub-manifold. We study these constraints at the linear and non-linear level for a pure geometrical setting and in the presence of p-form field strengths. We find that certain spaces admit several super-extensions and we give a parameterization in a simple case of d bosonic coordinates and two fermionic coordinates. In addition, we comment on the role of the RR field in the construction of the super-metric. We give several examples based on supergroup manifolds and coset supermanifolds.
Modeling of Concrete Airfield Pavements Using Artificial Neural Networks

Airfield pavement design is a decision making process which uses pertinent information available to make required judgments. One of the tools used in the design process is analysis of the pavement system. To be of value, it may be necessary to make many analyses of several pavement systems with different gear configurations and different loading conditions. With the more sophisticated models, such as the finite element models (FEM), this may require considerable time on the part of the designer. Furthermore, many consulting firms and designers do not have the necessary background and/or computational tools needed to make many of the required analyses. This paper specifically focuses on the use of artificial neural networks (ANNs) as design tools to analyze Portland Cement Concrete (PCC) airfield pavements.
Large Signal Bias Dependent Modeling of Avalanche Photodiode Based on Pulsed RF Measurement

This work presents a method for large signal characterization of avalanche photodiode (APD) where measurements were carried out using pulsed RF signal at different DC bias points to extract dispersive parameters of the avalanche photodiode. Pulsed optical excitation on the photodiode were synchronized with the pulsed RF signal using a synchronization circuit and in this way characterization of the photodiode was possible up to 1.3 mW of peak optical power whereas using CW measurement, device heating restricts the characterization up to 0.1 mW of optical input power. A comparison was made between the reflection measurements using CW RF excitation and APD model based on pulsed RF signal to establish the present approach for large signal characterization of the photodiode. Index Terms — Pulse measurement, reflection coefficient measurement, scattering parameters, nonlinearities.
Distinguishing the Functional Roles of Multiple Regions in Distributed Neural Systems for Visual Working Memory

We have investigated the human neural systems for visual working memory using functional magnetic resonance imaging to distinguish sustained activity during memory delays from transient responses related to perceptual and motor operations. These studies have identified six distinct frontal regions that demonstrate sustained activity during memory delays. These regions could be distinguished from brain regions in extrastriate cortex that participate more in perception and from brain regions in medial and lateral frontal cortex that participate more in motor control. Moreover, the working memory regions could be distinguished from each other based on the relative strength of their participation in spatial and face working memory and on the relative strength of sustained activity during memory delays versus transient activity related to stimulus presentation. These results demonstrate that visual working memory performance involves the concerted activity of multiple regions in a widely distributed system. Distinctions between functions, such as perception versus memory maintenance, or spatial versus face working memory, are a matter of the degree of participation of different regions, not the discrete parcellation of different functions to different modules.
Abstract Reduction Semantics for Modular Higher-Order Contract Verification

We contribute a new approach to the modular verification of higherorder programs that leverages behavioral software contracts as a rich source of symbolic values. Our approach is based on the idea of an abstract reduction semantics that gives meaning to programs with missing or opaque components. Such components are approximated by their contract and our semantics gives an operational interpretation of contracts-as-values. The result is a executable semantics that soundly approximates all possible instantiations of opaque components, including contract failures. It enables automated reasoning tools that can verify the contract correctness of components for all possible contexts. We show that our approach scales to an expressive language of contracts including arbitrary programs embedded as predicates, dependent function contracts, and recursive contracts. We argue that handling such a featurerich language of specifications leads to powerful symbolic reasoning that utilizes existing program assertions. Finally, we derive a sound and computable approximation to our semantics that facilitates fully automated contract verification. 1. Behavioral contracts as symbolic values Whether in the context of dynamically loaded JavaScript programs, low-level native C code, widely-distributed libraries, or simply intractably large code bases, automated reasoning tools must cope with access to only part of the program. To handle missing components, the omitted portions are often assumed to have arbitrary behavior, greatly limiting the precision and effectiveness of the tool. However, programmers who use these components do not make such conservative assumptions. Instead, they attach specifications to these components. These specifications increase our ability to reason about programs that are only partially known. But reasoning solely at the level of specification can also make verification and analysis challenging as well as requiring substantial effort to
How to distinguish a nearly flat Universe from a flat Universe using the orientation independence of a comoving standard ruler

Several recent observations using standard rulers and standard candles now suggest, either individually or in combination, that the Universe is close to flat, i.e. that the curvature radius is about as large as the horizon radius (10h 1 Gpc) or larger. Here, a method of distinguishing an almost flat universe from a precisely flat universe using a single observational data set, without using any microwave background information, is presented. The method (i) assumes that a standard ruler should have no preferred orientation (radial versus tangential) to the observer, and (ii) requires that the (comoving) length of the standard ruler be known independently (e.g. from low redshift estimates). The claimed feature at xed comoving length in the power spectrum of density perturbations, detected among quasars, Lyman break galaxies or other high redshift objects, would provide an adequate standard candle to prove that the Universe is curved, if indeed it is curved. For example, a combined intrinsic and measurement uncertainty of 1% in the length of the standard ruler L applied at a redshift of z =3 would distinguish an hyperbolic (m =0 :2; =0 :7) or a spherical (m =0 :4; =0 :7) universe from a flat one to 1 P> 95% condence.
African Swine Fever Virus Uses Macropinocytosis to Enter Host Cells

African swine fever (ASF) is caused by a large and highly pathogenic DNA virus, African swine fever virus (ASFV), which provokes severe economic losses and expansion threats. Presently, no specific protection or vaccine against ASF is available, despite the high hazard that the continued occurrence of the disease in sub-Saharan Africa, the recent outbreak in the Caucasus in 2007, and the potential dissemination to neighboring countries, represents. Although virus entry is a remarkable target for the development of protection tools, knowledge of the ASFV entry mechanism is still very limited. Whereas early studies have proposed that the virus enters cells through receptor-mediated endocytosis, the specific mechanism used by ASFV remains uncertain. Here we used the ASFV virulent isolate Ba71, adapted to grow in Vero cells (Ba71V), and the virulent strain E70 to demonstrate that entry and internalization of ASFV includes most of the features of macropinocytosis. By a combination of optical and electron microscopy, we show that the virus causes cytoplasm membrane perturbation, blebbing and ruffles. We have also found that internalization of the virions depends on actin reorganization, activity of Na+/H+ exchangers, and signaling events typical of the macropinocytic mechanism of endocytosis. The entry of virus into cells appears to directly stimulate dextran uptake, actin polarization and EGFR, PI3K-Akt, Pak1 and Rac1 activation. Inhibition of these key regulators of macropinocytosis, as well as treatment with the drug EIPA, results in a considerable decrease in ASFV entry and infection. In conclusion, this study identifies for the first time the whole pathway for ASFV entry, including the key cellular factors required for the uptake of the virus and the cell signaling involved.
Localization of brain electrical activity via linearly constrained minimum variance spatial filtering

A spatial filtering method for localizing sources of brain electrical activity from surface recordings is described and analyzed. The spatial filters are implemented as a weighted sum of the data recorded at different sites. The weights are chosen to minimize the filter output power subject to a linear constraint. The linear constraint forces the filter to pass brain electrical activity from a specified location, while the power minimization attenuates activity originating at other locations. The estimated output power as a function of location is normalized by the estimated noise power as a function of location to obtain a neural activity index map. Locations of source activity correspond to maxima in the neural activity index map. The method does not require any prior assumptions about the number of active sources of their geometry because it exploits the spatial covariance of the source electrical activity. This paper presents a development and analysis of the method and explores its sensitivity to deviations between actual and assumed data models. The effect on the algorithm of covariance matrix estimation, correlation between sources, and choice of reference is discussed. Simulated and measured data is used to illustrate the efficacy of the approach.
Local Casimir energy for a wedge with a circular outer boundary

The local Casimir energy is investigated for a wedge with and without a circular outer boundary due to the confinement of a massless scalar field with general curvature coupling parameter and satisfying the Dirichlet boundary conditions. Regularization procedure is carried out making use of a variant of the generalized Abel–Plana formula, previously established by one of the authors. The surface divergences in the vacuum expectation values of the energy density near the boundaries are considered. The corresponding results can be applied to the cosmic strings.
Beyond languages, beyond modalities: transforming the study of semiotic repertoires

ABSTRACT This paper presents a critical examination of key concepts in the study of (signed and spoken) language and multimodality. It shows how shifts in conceptual understandings of language use, moving from bilingualism to multilingualism and (trans)languaging, have resulted in the revitalisation of the concept of language repertoires. We discuss key assumptions and analytical developments that have shaped the sociolinguistic study of signed and spoken language multilingualism as separate from different strands of multimodality studies. In most multimodality studies, researchers focus on participants using one named spoken language within broader embodied human action. Thus while attending to multimodal communication, they do not attend to multilingual communication. In translanguaging studies the opposite has happened: scholars have attended to multilingual communication without really paying attention to multimodality and simultaneity, and hierarchies within the simultaneous combination of resources. The (socio)linguistics of sign language has paid attention to multimodality but only very recently have started to focus on multilingual contexts where multiple sign and/or multiple spoken languages are used. There is currently little transaction between these areas of research. We argue that the lens of semiotic repertoires enables synergies to be identified and provides a holistic focus on action that is both multilingual and multimodal.
EEG-based vigilance analysis by using fisher score and PCA algorithm

Driving fatigue is the most dangerous killer on the highway. Supervising mental vigilance is able to warn the driver and avoid some disasters. The current study mainly focuses on the power spectrum. The electroencephalography(EEG) activities in the δ(0–4 Hz), θ(4–8 Hz), α(8–13 Hz) and β(13–35Hz) bands, reflect the change of the physiological vigilance. The ratios of (θ + α)/β, α/β, (θ + α)/(α + β), and θ/β, are also used for assessing the vigilance. We make use of PCA algorithm and fisher score to remove background noise and select the significant discriminative features. After that, the sleepy and wakeful selected data are trained and tested by SVM classifier to evaluate the vigilance levels. Compared with the result obtained from non-PCA algorithm, the classification result from PCA algorithm, achieves higher accuracy in the α and β bands, as well as at the ratios of (θ + α)/β and α/β. The significant difference in the cerebral cortex appears at the δ, α and β bands, as well as at the ratios of α/β, (θ + α)/(α + β) and θ/β. These results suggest that estimating vigilance levels is feasible. Measuring the vigilance precisely is helpful to keep drivers away from some dangerous driving behaviors in the proposed system.
Interference-Aware Self-Deploying Femto-Cell

Femto-cells have been proposed as a throughput boosting solution for indoor users, but a key challenge is how to resolve the interference between neighboring cells. This paper proposes a distributed self-deployment solution to improve the indoor throughput. This investigation considers where to optimally place a femto-cell in a multi-room indoor environment. The novelty of the research is that a closed-form Femto-cell placement expression has been derived, which can maximize the throughput of the indoor building given knowledge of a few key statistical network parameters. The benefit compared to blind placement is that it can achieve a throughput improvement of 20 to 50%. The solution has a high placement error tolerance of 10% of building size. Another benefit is that the optimal solution can maintain an approximately constant level of throughput, irrespective of the indoor building size.
Tumor Necrosis Factor-Alpha Polymorphism and Susceptibility to Multiple Sclerosis in the Iranian Population

Background: Multiple sclerosis (MS) is an immune-mediated disease of polygenic etiology. Tumor necrosis factor-α (TNF-α) microsatellite as a proinflammatory cytokine is believed to play an important role in the etiology of this disease. Objectives: The aim of this study was to investigate the association of TNF-α microsatellite sequence variation in patients with MS and its risk factor in the southern Iranian population. Patients and Methods: This polymorphism was investigated in an Iranian population of 163 native southern people [81 patients with MS according to the poser criteria and 82 healthy controls (HC) with the same age, sex, social, ethnical and geographical features (Hormozgan and Fars provinces)]. All the controls were nonimmunological, neurological patients. All the cases and controls were chosen randomly and genotyped for polymorphism of TNF-α microsatellite. Results: The frequencies of TNF-α*11 (0.25, P < 0.005) and TNF-α*10 (P < 0.005) alleles increased in patients with MS compared with controls, showing a significant difference among the studied population. Conclusions: The current study adds evidence to the association of TNF-α gene polymorphism and MS in this southern south Iranian population which is consistent with the genetic analysis of MS in Europeans (GAMES) project reports and these two alleles reported in this study may be one of the genetic risk factor for MS. Furthermore, this data can be used to build the Iranian gene bank for future studies.
Lively Wiki a development environment for creating and sharing active web content

Wikis are Web-based collaborative systems designed to help people share information. Wikis have become popular due to their openness which gives users complete control over the organization and the content of wiki pages. Unfortunately existing wiki engines restrict users to enter only passive content, such as text, graphics, and videos and do not allow users to customize wiki pages. Thus, wikis cannot be used to host or author rich dynamic and interactive content. In this paper we present Lively Wiki, a development and collaboration environment based on the Lively Kernel which enables users to create rich and interactive Web pages and applications - without leaving the Web. Lively Wiki combines the wiki metaphor with a direct-manipulation user interface and adds a concept for Web programming as well as programming tool support to create an easy to use, scalable, and extendable Web authoring tool. Moreover, Lively Wiki is self-supporting, i.e. the development tools were used for creating its own implementation thereby giving users the freedom to customize every aspect of the system.