Miracle-dz/UniFAR-FTUs huggingface dataset:
Crosscutting the Great Divide : Exploring an Aspect-Oriented Approach to OS Code Thesis Proposal

Operating system code is complex. But, while substantial complexity is inherent to this domain, some complexity is caused by modularity problems. The goal of the work proposed here is to explore aspectoriented programming as a means of making this kind of complexity unnecessary. Towards this end, we need to identify aspects of the system, use the proposed mechanisms of AOP to modularize them, and establish the impact this approach has on the code.
The Decline and Dawn of Two-Factor Authentication on Smart Phones

In this paper, we focus on two-factor authenticatio n methods employing smart phones. Regarding this platform, it is well-known there are several risks that shall be evaluated carefully when designing such applicatio ns. It actually turns out this situation probably signaliz es an emerging fall of the two-factor authenticatio n as we know it, for instance, from certain contemporary banking applications. Smart phones, on the other hand, pro vide not only new threats and vulnerabilities. They also pro mise to deliver an excellent mix of computational p ower, rich peripheral devices, and amazing applications right into the client’s palm. After having successfully m astered this part of mobile devices evolution, we can hope to se e a dawn of the two-factor authentication as we nee d it.
Construction of central pattern generator for quadruped locomotion control

Central pattern generators (CPGs) inspired from neural system of animal are widely used for the control of locomotion in robots. Such systems present special characteristics like limit cycle behavior, synchronization, entrainment and to be modulated by external signals. However, one drawback of this kind of CPG is that most of the time these CPGs have to be tailored made for a specific application, and there are very few methodologies to modulate the shape of the rhythmic signals, in particular for online trajectory generation. In this paper, we illustrate a method for generating the rhythmic movement patterns with nonlinear dynamical systems. Using the phase angle of a canonical oscillator with limit cycle properties, we drive a perturbed dynamical system by means of embedding arbitrary smooth target signal, however, without losing the stability properties of the canonical system. The shape of target signal can be adjusted on line by internal parameters. The new kind of CPG is constructed by the coupling of oscillators with locked phase difference and synchronization. The outputs of perturbed dynamical system are used to control the walking of a quadruped robot with 12-DOF. The result of experiment shows the new kind of CPG is suitable for the control of multi-joint robot.
Underwater transportation of multiple fish-like robots using situation based action selection

This paper is concerned with a novel problem of underwater cooperative transportation of multiple fishlike robots. A situation based action selection mechanism is proposed for the robots to transport a floating object to its destination. There are various control methods for cooperation of multi-robot system, but few of them deal with the underwater applications. In this paper, we first present the development of a series of biomimetic fish-like robots. Then, employing these robotic fish, we design and implement a cooperative transportation task utilizing a situation based action selection approach. We fully implement our method on three fish-like robots and make various experiments in a lab environment
The African Union and its institutions

Research on, and about, the African Union lags behind the establishment of its many organs, institutions, mechanisms, protocols and declarations, as well as the AU's activities and influence on Africa's peace and security, governance and development architectures. Consequently, there is a dearth of scholarly work on the new body, and academics, researchers and analysts are still playing catch-up in producing detailed and analytical knowledge about the AU. This volume brings together the analysis and research of 17 largely Pan-African scholars, policy-makers, practitioners and civil society representatives, and thus contributes to filling this gap in the literature. Written by eminent scholars on Africa and practitioners who have worked in or with the African Union, The African Union and its Institutions is a particularly timely and welcome addition to the pioneering literature about this young and potentially powerful institution. It presents a positive but realistic picture of the African Union, while diagnosing several key challenges. The AU has established an impressive array of institutions to deal with Africa's security and governance problems - this title contains robust scholarship that allows reflection on what needs to be done to fulfil the noble objectives that the AU has set for itself.
Bioinformatics Domain Structure Prediction and Homology Modeling of Human Ryanodine Receptor 2

Ryanodine receptors (RyRs) are homotetrameric intracellular calcium release channels in the membranes of the endoplasmic (ER) and sarcoplasmic reticulum (SR) (George et al. 2005, Meissner 2002, 2004). Each subunit consists of ~5000 amino acid residues (George et al. 2005). There are three isoforms of the ryanodine receptor: the RyR1 isoform is expressed predominantly in skeletal muscle, the RyR2 isoform predominates in cardiac muscle, and the RyR3 isoform is expressed in a variety of tissues (Sorrentino 1995). In the mammalian heart, the RyR2 isoform is a principal component of the excitation-contraction (E-C) coupling process. Action potential depolarization of the cardiac cell results in injection of calcium ions into the cell via calcium channels (dihydropyridine receptors, DHPRs). This small calcium influx then drives the release of calcium from intracellular calcium stores by triggering the opening of RyR2 channels (Fabiato 1985). The released calcium causes contraction by binding to troponin C (Ebashi and Ogawa 1988). Consequently, precise regulation of RyR activity during heartbeat is essential to proper cardiac function. In several cardiac diseases, such as heart failure and the genetic diseases CVPT (catecholaminergic polymorphic ventricular tachycardia) and ARVD2 (arrhythmogenic right ventricular dysplasia), the function of RyR is compromised. In heart failure, the release of calcium in response to the action potential is decreased, while RyR remains more active during the diastole (Durham et al. 2007, Yano et al. 2006). In CPVT and ARVD2, RyRs contain mutations that lead to altered RyR activity which may result in premature calcium release in the absence of an action potential (Durham et al. 2007, Yano et al. 2006). In this work we present a bioinformatics analysis of the whole of human RyR2 (hRyR2) in context with the available functional information, in order to locate individual domains for further biochemical and structural studies. The reliability of the predictions in the Nterminal region (Bauerova-Hlinkova et al. 2010) was verified experimentally by expressing and characterizing the domains identified. We also describe the results of a CD-
Effect of Gold Nanoparticle on Structure and Fluidity of Lipid Membrane

This paper deals with the effect of different size gold nanoparticles on the fluidity of lipid membrane at different regions of the bilayer. To investigate this, we have considered significantly large bilayer leaflets and incorporated only one nanoparticle each time, which was subjected to all atomistic molecular dynamics simulations. We have observed that, lipid molecules located near to the gold nanoparticle interact directly with it, which results in deformation of lipid structure and slower dynamics of lipid molecules. However, lipid molecules far away from the interaction site of the nanoparticle get perturbed, which gives rise to increase in local ordering of the lipid domains and decrease in fluidity. The bilayer thickness and area per head group in this region also get altered. Similar trend, but with different magnitude is also observed when different size nanoparticle interact with the bilayer.
Dynamic Supply Risk Management with Signal‐Based Forecast, Multi‐Sourcing, and Discretionary Selling

We examine the critical role of advance supply signals—such as suppliers’ financial health and production viability—in dynamic supply risk management. The firm operates an inventory system with multiple demand classes and multiple suppliers. The sales are discretionary and the suppliers are susceptible to both systematic and operational risks. We develop a hierarchical Markov model that captures the essential features of advance supply signals, and integrate it with procurement and selling decisions. We characterize the optimal procurement and selling policy, and the strategic relationship between signal‐based forecast, multi‐sourcing, and discretionary selling. We show that higher demand heterogeneity may reduce the value of discretionary selling, and that the mean value‐based forecast may outperform the stationary distribution‐based forecast. This work advances our understanding on when and how to use advance supply signals in dynamic risk management. Future supply risk erodes profitability but enhances the marginal value of current inventory. A signal of future supply shortage raises both base stock and demand rationing levels, thereby boosting the current production and tightening the current sales. Signal‐based dynamic forecast effectively guides the firm's procurement and selling decisions. Its value critically depends on supply volatility and scarcity. Ignoring advance supply signals can result in misleading recommendations and severe losses. Signal‐based dynamic supply forecast should be used when: (a) supply uncertainty is substantial, (b) supply‐demand ratio is moderate, (c) forecast precision is high, and (d) supplier heterogeneity is high.
Cell-free fetal DNA levels in pregnancies conceived by IVF.

BACKGROUND Increased second-trimester levels of maternal serum HCG in IVF conceptions lead to an increased false-positive rate in Down syndrome screening. Increased levels of cell-free fetal DNA (cffDNA) in maternal plasma have been correlated with increased HCG levels. Our aim was to determine whether cffDNA levels are elevated in IVF pregnancies compared with natural pregnancies. METHODS Sixteen archived second-trimester serum samples from IVF pregnancies were matched with five control samples from naturally conceived pregnancies per case, all carrying a singleton male fetus. cffDNA concentrations were measured by real-time PCR amplification of a Y chromosome sequence and compared with four standard second trimester serum screening markers (alpha-fetoprotein, estriol, HCG and inhibin A). RESULTS Mean cffDNA levels for cases and controls were 57.9 and 57.1 genome equivalents/ml, respectively (P = 0.95). Mean observed rank (from 1 to 6) of cffDNA was 3.625 in the IVF conceived group, compared with an expected value of 3.5 (P = 0.53). No significant correlations were observed between cffDNA and serum markers. CONCLUSIONS IVF does not affect levels of cffDNA, which appears to be independent of traditional screening markers (e.g. HCG). Therefore, cffDNA can be used as an additional serum marker (e.g. Down syndrome screening) without adjustment for IVF pregnancies.
Macromolecular ab initio phasing enforcing secondary and tertiary structure

ARCIMBOLDO replaces the atomicity constraints required for ab initio phasing by enforcement of model stereochemistry. Small model fragments and local folds are exploited at resolutions up to 2 Å in different contexts, from supercomputers to the standalone ARCIMBOLDO_LITE, which solves straightforward cases on a single multicore machine.
K APATSINSKI 134 Sound Similarity Relations in the Mental Lexicon : Modeling the Lexicon as a Complex Network

The standard definition of neighborhood density defines two words to be neighbors if they differ by one and only one segment (Luce & Pisoni, 1998). This definition assumes that the length of the shared part is irrelevant to sound similarity. However, confusability of non-linguistic sound sequences (Fallon Coble & Robinson, 1992; Kidd & Watson, 1992) as well as judgments of sound similarity between spoken pseudowords (Kapatsinski, in press, b) depend on the proportion of total duration of the word or sound sequence that is mismatched, and not on the absolute duration of the mismatch. To bring the definition of neighborhood into alignment with these results, this paper defines words to be neighbors if they share at least two thirds of their total duration, measured in segments. This simple change reduces the proportion of words with no neighbors to all words in the lexicon from over 58 percent to just 7 percent, increasing the applicability of the Neighborhood Activation Model (Luce & Pisoni, 1998). Lexical decision, naming, and familiarity judgment data indicate that speaker/hearers are sensitive to the more distant neighbors brought in by the new neighborhood definition. The large-scale properties of the network are discussed and future directions are indicated.
Tree Recurrent Neural Networks with Application to Language Modeling

In this paper we develop a recurrent neural network (TreeRNN), which is designed to predict a tree rather than a linear sequence as is the case in conventional recurrent neural networks. Our model defines the probability of a sentence by estimating the generation probability of its dependency tree. We construct the tree incrementally by generating the left and right dependents of a node whose probability is computed using recurrent neural networks with shared hidden layers. Application of our model to two language modeling tasks shows that it outperforms or performs on par with related models.
Monitoring Human Activities : Flexible Calibration of a Wide Area System of Synchronized Cameras

This paper presents an efficient procedure for calibrating a wide area system of synchronized cameras with respect to a global coordinate system. The flexibility of this procedure lies in its use of a hand-held calibration target that is automatically detected in real-time by the system, and also in its capability to provide a feedback on the working volume coverage through a sampling pyramid. In a first stage, the intrinsic parameters are computed separately for each camera, and then the relative positions of the cameras are evaluated through a bundle adjustment. The 3D reconstruction uncertainty of the camera system is assessed locally within the working volume and is verified to be acceptable for monitoring hu-
Yield and performance enhancement through redundancy in VLSI and WSI multiprocessor systems

New challenges have been brought to fault-tolerant computing and processor architecture research because of developments in IC technology. One emerging area is development of architectures, built by interconnecting a large number of processing elements on a single chip or wafer. Two important areas, related to such VLSI processor arrays, are the focus of this paper; they are fault-tolerance and yield improvement techniques. Fault tolerance in these VLSI processor arrays is of real practical significance; it provides for much-needed reliability improvement. Therefore, we first describe the underlying concepts of fault tolerance at work in these multiprocessor systems. These precepts are useful to then present certain techniques that will incorporate fault tolerance integrally into the design. In the second part of the paper we discuss models that evaluate how yield enhancement and reliability improvement may be achieved by certain fault-tolerant techniques.
Self-Triggered Set-Valued Observers

This paper addresses the problem of high computational requirements in the implementation of Set-Valued Observers (SVOs), which places stringent constraints in terms of their use in applications where low computational power is available or the plant is sensitive to delay. It is firstly shown how to determine an overbound for the set-valued estimates, which reduces the overhead by limiting the number of inequalities defining those set-valued state estimates. In the particular setting of distributed gossip problems, the proposed algorithm is shown to have constant complexity. This algorithm is of prime importance to reduce the computational load and enable the use of such estimates for real-time applications. Results are also provided regarding the frequency of the triggers in the worst-case scenario. The performance of the proposed method is evaluated through simulation.
A preliminary investigation on topological properties of technology exchange network

In this paper we study the technology transactions as a complex network, with 40531 contracting parties as the nodes and 76303 contractual relations as the edges. After exploring its topological properties, we observe that this network is characterized by two remarkable features which are already observed in numerous real-world and artificial networks. One is the small-world property, with the small-world index of 606.106, and the other is its scale-free distribution, with the degree exponent of 2.093. We also observe that this network exhibits some features that are not necessarily shared by other networks, such as the anti-correlation between clustering coefficients and degrees. Our work extends the network analysis to the domain of technology exchange and provides a novel approach to study technology exchange systems.
Spatial error concealment based on line segmentation and adaptive edge points matching

A novel spatial error concealment algorithm with low-complexity is proposed in this paper for block losses in image and/or video communications. It is based on one dimensional (1-D) line segmentation and adaptive edge points matching, which can be divided into three steps. 1) A 1-D line growing based method is applied to obtain the edge points from the neighboring pixels of the lost areas. 2) The edge points will be adaptively matched in pairs and then connected to recover the lost edge information. 3) For each pixel in the lost areas, the neighboring intact pixels for interpolation will be searched by an up-down scanning procedure, after which the lost pixel will be interpolated using them. It has been shown that the proposed algorithm can recover the lost edge information efficiently. Compared with the existing algorithms, our proposed algorithm can achieve superior objective and subjective quality with even lower complexity.
Psychological concomitants of crossfit training: does more exercise really make your everyday psychological functioning better?

The research aimed at studying relationships between characteristics of CrossFit training (time elapsed from starting with training, weekly session frequency) and indicators of well-being, self-esteem, body awareness, satisfaction with body image, and perceived body competence. Participants, 186 Norwegian individuals (57.5% female; mean age: 28.9±7.81 years) regularly participating in CrossFit, completed online surveys (WHO-5 Well-being Scale, PANAS, Rosenberg Self-Esteem Scale, Body Awareness Questionnaire, Body Image Ideals Questionnaire, Body Competence Scale, motivations for doing CrossFit). Weekly frequency of CrossFit sessions was not connected with positive affect (Kendall tau_b=-.02, p=.766), negative affect (-.01, p=.861), or well-being (.10, p=.068) in the correlation analysis. Similarly, overall CrossFit experience (duration x frequency) was not related to global self-esteem (Kendall tau_b=.01, p=.778), body awareness (-.04, p=.379), body image dissatisfaction (.04, p=.423), and body competence (-.07, p=.184). In the regression analysis, well-being was connected with male gender (β=-.205, p<.01), time elapsed from starting with CrossFit (β=-0.178, p<.05), dissatisfaction with body image (β=-.218, p<.01), and body awareness (β=.149, p<.05). Global self-esteem was related to age (β=.164, p<.05), body competence (β=.152, p<.05), and body image dissatisfaction (β=-.276, p<.001). CrossFit training was not connected with higher levels of psychological functioning (well-being, affect, body awareness, and self-esteem) and satisfaction with body image.
Knowledge and Skill Representations for Robotized Production

Model-based systems in control are a means to utilize efficiently human knowledge and achieve high performance. While models consisting of formalized knowledge are used during the engineering step, running systems usually do not contain a high-level, symbolic representation of the control and most of its properties, typically named numerical parameters. On a system level and beyond the plant data, there is also a need to represent the meaning of the data such that deployment and fault analysis could be augmented with partly automated inference based on the semantics of the data. To that end, we extended the formalized knowledge traditionally used in control to include the control purpose, engineering assumption, quality, involved state machines, and so on. We then represented the control semantics in a format that allows an easier extraction of information using querying and reasoning. It aims at making knowledge in control engineering reusable so that it can be shipped together with the control systems. We implemented prototypes that include automatic conversion of plant data from AutomationML into RDF triples, as well as the automated extraction of control properties, the conversion of parameters, and their storage in the same triple store. Although these techniques are standard within the semantic web community, we believe that our robotic prototypes for semantic control represent a novel approach.
Neural Network Hedonic Pricing Models in Mass Real Estate Appraisal Authors

Using a large sample of 46,467 residential properties spanning 1999–2005, we demonstrate using matched pairs that, relative to linear hedonic pricing models, artiﬁcial neural networks (ANN) generate signiﬁcantly lower dollar pricing errors, have greater pricing precision out-of-sample, and extrapolate better from more volatile pricing environments. While a single layer ANN is functionally equivalent to OLS, multiple layered ANNs are capable of modeling complex nonlinearities. Moreover, because parameter estimation in ANN does not depend on the rank of the regressor matrix, ANN is better suited to hedonic models that typically utilize large numbers of dummy variables.
Energy-aware Topology Management for 5G dual-hop ultra-high capacity backhaul networks exploiting path diversity

This paper addresses an energy efficient network topology management strategy which exploits the path diversity in a dual-hop backhaul network in order to lessen the power consumption by switching as many underutilized base stations as possible to a dormant mode. This scheme dynamically tunes the various states of the relay nodes and aggregation points in a dual-hop setup to meet a trade-off between Quality of Service (QoS) and energy expense. It is shown that topology management is able to notably reduce the energy consumption by up to 75% at low traffic levels. In addition, the QoS can be improved by up to 45% by mitigating the bottleneck from the second hop using different combinations of path diversity in the network. Furthermore, the path diversity is analysed using directed graph for this dual-hop backhaul scenarios where the traffic load varies both in time and spatial domains.