Miracle-dz/UniFAR-FTUs huggingface dataset:
Dependence discovery in modular Bayesian networks

This paper introduces an information theoretic approach to verification of modular causal probabilistic models. We assume systems which are gradually extended by adding new functional modules, each having a limited domain knowledge captured by a local Bayesian network. Different modules originate from independent design processes. We assume that the local models are correct, which, however does not guarantee globally coherent inference in composed systems. The introducedm ethod supports discovery of significant inter-module dependencies which are not captured in the assembled Bayesian network. We demonstrate the principles on a modularized gas detection fusion network.
Single-image super-resolution using sparsity constraints and non-local similarities at multiple resolution scales

Traditional super-resolution methods produce a clean high-resolution image from several observed degraded low-resolution images following an acquisition or degradation model. Such a model describes how each output pixel is related to one or more input pixels and it is called data fidelity term in the regularization framework. Additionally, prior knowledge such as piecewise smoothness can be incorporated to improve the image restoration result. The impact of an observed pixel on the restored pixels is thus local according to the degradation model and the prior knowledge. Therefore, the traditional methods only exploit the spatial redundancy in a local neighborhood and are therefore referred to as local methods. Recently, non-local methods, which make use of similarities between image patches across the whole image, have gained popularity in image restoration in general. In super-resolution literature they are often referred to as exemplarbased methods. In this paper, we exploit the similarity of patches within the same scale (which is related to the class of non-local methods) and across different resolution scales of the same image (which is also related to the fractal-based methods). For patch fusion, we employ a kernel regression algorithm, which yields a blurry and noisy version of the desired high-resolution image. For the final reconstruction step, we develop a novel restoration algorithm. The joint deconvolution/denoising algorithm is based on the split Bregman iterations and, as prior knowledge, the algorithm exploits the sparsity of the image in the shearlet-transformed domain. Initial results indicate an improvement over both classical local and state-of-the art non-local super-resolution methods.
Association between Sex Ratio Distortion and Sexually Antagonistic Fitness Consequences of Female Choice

Genetic variation can be beneficial to one sex yet harmful when expressed in the other—a condition referred to as sexual antagonism. Because X chromosomes are transmitted from fathers to daughters, and sexually antagonistic fitness variation is predicted to often be X-linked, mates of relatively low-fitness males might produce high-fitness daughters whereas mates of high-fitness males produce low-fitness daughters. Such fitness consequences have been predicted to influence the evolution of female mating biases and the offspring sex ratio. Females might evolve to prefer mates that provide good genes for daughters or might adjust offspring sex ratios in favor of the sex with the highest relative fitness. We test these possibilities in a laboratory-adapted population of Drosophila melanogaster, and find that females preferentially mate with males carrying genes that are deleterious for daughters. Preferred males produce equal numbers of sons and daughters, whereas unpreferred males produce female-biased sex ratios. As a consequence, mean offspring fitness of unpreferred males is higher than offspring fitness of preferred males. This observation has several interesting implications for sexual selection and the maintenance of population genetic variation for fitness.
A compact hard real-time operating system for wireless sensor nodes

The paper shows a compact hard real-time operating system for wireless sensor nodes called PAVENET OS. PAVENET OS provides hybrid multithreading: preemptive multithreading and cooperative multithreading. Both of the multithreading is optimized for two kinds of task on wireless sensor networks, and the kinds are real-time tasks and best-effort tasks. PAVENET OS can efficiently perform hard real-time tasks that cannot be performed by TinyOS. The paper demonstrates the hybrid multithreading realizes compactness and low overhead, which are comparable to those of TinyOS, through quantitative evaluation. The results show PAVENET OS performs 100-Hz sensor sampling with 0.01% jitter while performing wireless communication tasks, whereas optimized TinyOS has 0.62% jitter. In addition, PAVENET OS has a small footprint and low overhead (minimum RAM size: 29 bytes, minimum ROM size: 490 bytes, minimum task switch time: 23 cycles).
Reference object processing in on-the-fly garbage collection

Most proposals for on-the-fly garbage collection ignore the question of Java's weak and other reference types. However, we show that reference types are heavily used in DaCapo benchmarks. Of the few collectors that do address this issue, most block mutators, either globally or individually, while processing reference types. We introduce a new framework for processing reference types on-the-fly in Jikes RVM. Our framework supports both insertion and deletion write barriers. We have model checked our algorithm and incorporated it in our new implementation of the Sapphire on-the-fly collector. Using a deletion barrier, we process references while mutators are running in less than three times the time that previous approaches take while mutators are halted; our overall execution times are no worse, and often better.
Robust Kalman filter for discrete-time systems with correlated noises

This paper addresses the design of robust one step predictor filter for linear discrete-time systems subject to time-varying and norm bounded uncertainties in every system matrices. The dynamic and measurement noises are allowed to be correlated with unknown time-variant cross-covariance. The proposed filter guarantees a minimal upper bound error variance on the state estimation. A numerical example is given to illustrate the results.
A Semisupervised Approach for Language Identification based on Ladder Networks

In this study we address the problem of training a neuralnetwork for language identification using both labeled and unlabeled speech samples in the form of i-vectors. We propose a neural network architecture that can also handle out-of-set languages. We utilize a modified version of the recently proposed Ladder Network semisupervised training procedure that optimizes the reconstruction costs of a stack of denoising autoencoders. We show that this approach can be successfully applied to the case where the training dataset is composed of both labeled and unlabeled acoustic data. The results show enhanced language identification on the NIST 2015 language identification dataset.
Wavelet Energy-Based Support Vector Machine for Noisy Word Boundary Detection With Speech Recognition Application

Word boundary detection in variable noise-level environments by support vector machine (SVM) using Low-band Wavelet Energy (LWE) and Zero Crossing Rate (ZCR) features is proposed in this paper. The Wavelet Energy is derived based on Wavelet transformation; it can reduce the affection of noise in a speech signal. With the inclusion of ZCR, we can robustly and effectively detect word boundary from noise with only two features. For detector design, a Gaussian-kernel SVM is used. The proposed detection method is applied to detection word boundaries for an isolated word recognition system in variable noisy environments. Experiments with different types of noises and various signal-to-noise ratios are performed. The results show that using the LWE and ZCR parameters-based SVM, good performance is achieved. Comparison with another robust detection method has also verified the performance of the proposed method.
Efficient link discovery for underwater networks

We describe an efficient method to discover the topology of underwater acoustic networks (UWANs). By knowing the network topology, nodes can determine destinations and routing possibilities for their packets, and schedule transmissions accordingly. To detect the network topology, an initial phase is employed. Our algorithm aims to reduce the time overhead of this initial phase while accurately discovering acoustic links. To that end, our algorithm allows simultaneous transmissions from different nodes while controlling the number of possible collisions in an optimized fashion. Experimental results from the 14 days ALOMEx'15 sea expedition show that our algorithm is able to accurately detect the network topology in a much shorter time compared to benchmark methods.
6D frictional contact for rigid bodies

We present a new approach to modeling contact between rigid objects that augments an individual Coulomb friction point-contact model with rolling and spinning friction constraints. Starting from the intersection volume, we compute a contact normal from the volume gradient. We compute a contact position from the first moment of the intersection volume, and approximate the extent of the contact patch from the second moment of the intersection volume. By incorporating knowledge of the contact patch into a point contact Coulomb friction formulation, we produce a 6D constraint that provides appropriate limits on torques to accommodate displacement of the center of pressure within the contact patch, while also providing a rotational torque due to dry friction to resist spinning. A collection of examples demonstrate the power and benefits of this simple formulation.
Does Money Matter for Inflation in Ghana?

Money has only limited information value for future inflation in Ghana over a typical monetary policy implementation horizon (four to eight quarters). On the other hand, currency depreciation and demand pressures (as measured by the output gap) are shown to be important predictors of future price changes. Inflation inertia is high and inflation expectations are largely based on backward-looking information, suggesting that inflation expectations are not well anchored and hence more is needed to strengthen the credibility of Ghana’s inflation-targeting regime.
Serological Characterization of C-type retroviruses endogenous to the C57BL/6 mouse and isolated in tumours induced by radiation leukaemia virus (RadLV-Rs).

Summary Radiation leukaemia virus, Rs strain (RadLV-Rs), is a virus complex derived from radiation-induced lymphoma of the C57BL/6 mouse. Several B-ecotropic retroviruses (T1223/B, T98/B and T128/B) were isolated from the RadLV-Rs and further cloned. They were found to be highly leukaemogenic and polymorphic in terms of XC cell fusion activity. To investigate a possible relationship between their phenotypical and genotypical properties, a serological characterization of their proteins was undertaken by means of interference, neutralization and type-specific radioimmunological experiments. In addition, these viruses were compared on the basis of the electrophoretic mobility of their proteins. They were also compared with the prototype endogenous N-ecotropic (BL6/Ni) and xenotropic (T530/X) retroviruses of the C57BL/6 mouse as well as the AKR-MuLV and the RadLV/VL-3 (thymotropic leukaemogenic retrovirus involved in radio-induced lymphoma). With respect to the p12, T1223/B and T128/B viruses were of xenotropic type as in RadLV/VL-3, whereas T98/B p12 displayed ecotropic and xenotropic type-specific antigenic determinants. The gp71 of all B-ecotropic virus isolates were indistinguishable and of the AKR-MuLV type. This latter result was further supported by interference and neutralization experiments. This supports the view that the B-ecotropic virus isolates originated by recombination (one or two events) between N-ecotropic and xenotropic endogenous retroviruses. The RadLV/VL-3 possesses a unique envelope recombinant glycoprotein of which the antigenicity was not observed in the RadLV-Rs complex. Thus, it may be assumed that the leukaemogenic components of RadLV and RadLV-Rs arose by different recombinational mechanisms.
EVOLVING NANO-SCALE , FEMTOSECOND-SWITCHING CIRCUITS THAT ARE BOTH REVERSIBLE AND ROBUST

This paper introduces conceptual problems that will arise in the next 10-20 years as electronic circuits reach nanometer scale, i.e. the size of molecules. Such circuits will be impossible to make perfectly, due to the inevitable fabrication faults in chips with an Avogadro number of components. Hence they will need to be constructed so that they are robust to faults. They will also need to be (as far as possible) reversible circuits, to avoid the heat dissipation problem if bits of information are routinely wiped out during the computational process. They will also have to be local if the switching times reach femto-seconds, which is possible now with quantum optics. This paper discusses some of the conceptual issues involved in trying to build circuits that satisfy all these criteria, i.e. that they are robust, reversible and local. We propose an evolutionary engineering based model that meets all these criteria, and provide some experimental results to justify it.
Multimarker Risk Assessment Including Osteoprotegerin and CXCL16 in Acute Coronary Syndromes

Objective—CXCL16 and osteoprotegerin (OPG) both predict mortality in acute coronary syndromes. We hypothesized that a combination of CXCL16 and OPG concentrations would add prognostic information to the Global Registry of Acute Coronary Events (GRACE) score in patients hospitalized for acute coronary syndromes. Methods and Results—We assessed the associations between circulating OPG and soluble CXCL16 levels, obtained within 24 hours of admission (day 1) and after 3 months, and mortality, heart failure and reinfarction in 1322 patients admitted with acute coronary syndromes. After adjustment for the GRACE score, medication, diabetes mellitus and sex, the combination of high values (fourth quartile) for OPG and CXCL16 at baseline was associated with increased short-term (3 months) cardiovascular mortality (hazard ratio, 3.28; 95% CI, 1.84–5.82; P<0.0001). The combined high values were also significantly associated with the long-term (median 91 months) prognosis after adjustment, with hazard ratios 2.18 for cardiovascular mortality (95% CI, 1.62–2.92; P<0.0001), and 2.22 for heart failure (95% CI, 1.67–2.96; P<0.0001). These long-term associations remained significant after further adjustment for left ventricular ejection fraction, C-reactive protein, and pro B-type natriuretic peptide. For 635 patients with blood samples within 24 hours and at 3 months, the combination of high CXCL16 and OPG values (fourth quartile) in the early or stable phase was of a similar order associated with mortality and morbidity beyond 3 months. Conclusion—Circulating CXCL16 and OPG are independent predictors of long-term mortality and heart failure development in acute coronary syndromes patients, even after extensive adjustments. Their combination gives more information than either marker alone.
Differentially Expressed Proteins in Chronic Active Hepatitis, Cirrhosis, and HCC Related to HCV Infection in Comparison With HBV Infection: A proteomics study

Background Hepatocellular carcinoma is a highly progressive cancer in the case of late diagnosis which is frequently associated with HBV and HCV viral infections. Objectives To identify differentially expressed serum proteins among three main stages of HCV infection and healthy individuals, and their comparisons with sera from patients with the same stage of HBV infection. Patients and Methods Two-dimensional polyacrylamide gel electrophoresis combined with liquid chromatography-tandem mass spectrometry was performed on 47 sera from healthy volunteers, those with chronic active hepatitis, cirrhosis and HCC patients associated with HBV and HCV infections. Results Among these, 62 spots were differentially expressed (≥ 1.5 fold; P < 0.05), of which 42 spots that corresponded to 15 proteins were identified by liquid chromatography-tandem mass spectrometry. CD5-like antigen (CD5L) was differentially expressed between cirrhosis and HCC patients with HCV infection. Leucine-rich α2-glycoprotein (LRG) and haptoglobin (HP) α2 isoforms differed in the HCC that was associated with either HCV or HBV infections. Conclusions CD5L might be a useful biomarker for early diagnosis of HCC in HCV cirrhotic patients. LRG and HP α2 isoforms could be potential markers for distinguishing viral HCC. Our results also further support the presence of varying molecules involved in hepatocarcinogenesis in HBV when compared with HCV infection.
Distance Structure of Homologous Gene Clusters in Cyanobacteria

Rearrangement of genomes reflects evolutionary history of the genomes, which have left conspicuous traces on the genomes that are detected as conserved adjacency of homologous genes within different genomes. Such conserved ordering of genes are recognized as synteny. To find such conserved genome structure, various methods of comparative genomics are used extensively. These methods are based on the definition of homologous genes within a selected set of genomes, but the increase in evolutionary distance among genomes weakens the evidence of homologous genes. These matters are common unavoidable problems in the comparative genomics research. We focused on the cyanobacterial genomes to establish an efficient handling method for this problem. The cyanobacteria belong to a group of prokaryotes, which has the ability of oxygenic photosynthesis. The current habitat of cyanobacteria covers most of the planet surface from an extreme environment such as hot springs to water stains on cement walls in city and some species also live on deserts. Some of the reasons for their wide distribution can be related to their long evolutional history, which dates from 3.5 Ga by geological evidence. The genomes of cyanobacteria are energetically sequenced by Kazusa DNA Institute and Joint Genome Institute, among others. Currently, 16 genome sequences have been published (as of 2005), and this number is the largest for a single group of prokaryotes. As mentioned above, cyanobacterial evolutionary divergence is so large that the phylogenetic trees generated from molecular evolutionary analyses in 16S rRNA are sometimes inconsistent. In the present study, Gclust database[1], which is designed for analysis of cyanobacteria are used as a source of homologous sequences. We applied approaches of comparative genomics to develop the appropriate data evaluation and to shed light on their complicated evolutional history of cyanobacteria.
Knowledge transfer and expatriation in multinational corporations: The role of disseminative capacity

Research on multinational corporation (MNC) knowledge transfer has argued continuously for the behavior of knowledge senders to be a determinant of knowledge transfer. Although the importance of disseminative capacity regarding knowledge transfer has been illustrated in numerous conceptual studies, substantial empirical support is largely absent. Based on previous studies, re‐operationalizes disseminative capacity as being dependent upon the ability and the willingness of organizational actors to transfer knowledge where and when it is needed in the organization. Using the context of expatriation, suggests that MNCs may apply different mechanisms depending on whether they want to develop expatriates' ability or willingness to transfer knowledge. Suggests that MNCs may enhance expatriates' willingness to transfer knowledge through the employment of long‐term expatriate assignments, whereas expatriates' ability to transfer knowledge may be increased through their involvement in temporary assignments such as short‐term assignments, frequent flyer arrangements, and international commuting. Tests the hypotheses empirically based on data from 92 subsidiaries of Danish MNCs located in 11 countries.
Revealing the Micro-scale Signature of Endemic Zoonotic Disease Transmission in an African Urban Setting

The development of novel approaches that combine epidemiological and genomic data provides new opportunities to reveal the spatiotemporal dynamics of infectious diseases and determine the processes responsible for their spread and maintenance. Taking advantage of detailed epidemiological time series and viral sequence data from more than 20 years reported by the National Reference Centre for Rabies of Bangui, the capital city of Central African Republic, we used a combination of mathematical modeling and phylogenetic analysis to determine the spatiotemporal dynamics of rabies in domestic dogs as well as the frequency of extinction and introduction events in an African city. We show that although dog rabies virus (RABV) appears to be endemic in Bangui, its epidemiology is in fact shaped by the regular extinction of local chains of transmission coupled with the introduction of new lineages, generating successive waves of spread. Notably, the effective reproduction number during each wave was rarely above the critical value of 1, such that rabies is not self-sustaining in Bangui. In turn, this suggests that rabies at local geographic scales is driven by human-mediated dispersal of RABV among sparsely connected peri-urban and rural areas as opposed to dispersion in a relatively large homogenous urban dog population. This combined epidemiological and genomic approach enables development of a comprehensive framework for understanding disease persistence and informing control measures, indicating that control measures are probably best targeted towards areas neighbouring the city that appear as the source of frequent incursions seeding outbreaks in Bangui.
Cell-autonomous axon growth of young motoneurons is triggered by a voltage-gated sodium channel

Spontaneous electrical activity preceding synapse formation contributes to the precise regulation of neuronal development. Examining the origins of spontaneous activity revealed roles for neurotransmitters that depolarize neurons and activate ion channels. Recently, we identified a new molecular mechanism underlying fluctuations in spontaneous neuronal excitability. We found that embryonic motoneurons with a genetic loss of the low-threshold sodium channel NaV1.9 show fewer fluctuations in intracellular calcium in axonal compartments and growth cones than wild-type littermates. As a consequence, axon growth of NaV1.9-deficient motoneurons in cell culture is drastically reduced while dendritic growth and cell survival are not affected. Interestingly, NaV1.9 function is observed under conditions that would hardly allow a ligand- or neurotransmitter-dependent depolarization. Thus, NaV1.9 may serve as a cell-autonomous trigger for neuronal excitation. In this addendum, we discuss a model for the interplay between cell-autonomous local neuronal activity and local cytoskeleton dynamics in growth cone function.
A new Approach to support Fault Simulation of Delay Insensitive Asynchronous Circuits with Synchronous Toolset

Lac ko fgloba lcloc kfo rsynchronizatio nin asynchronouscirc uitsdecreasesthe controllabilityo f thes ecircuitsand thusmakesasynchr onouscircuits hardtotest.Delay Insensitive(DI)c ircuitsexclusive ly useC-elementsand inverters,provid edthatonlysingle outputgatesareus ed.Inthispaperwe presentanew method to conceptually change this class of asynchronouscirc uits.Themainidea istochangeCelementsintoothe relementswhichca nbemodeledby synchronoustools . ThenweuseHOPE,a synchronous sequentialcircui tsfaultsimulator ,andapplyittoDI classofasynchron ouscircuits.Thes tuck-atmodelis usedforfaultsimu lation.Ourobserv ationsshowthat w ecanachievecons iderabl efaultcov erage ,mainly 92.5%,inDIcircui tsbythismethod.T othebestofour knowledge,thisis thefirsteffortin usingsynchronous too lt oachiev efaul tsimulatio nfo rasynchronous circuit class.