Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling heterogeneous network traffic in wavelet domain: Part I-temporal correlation

Heterogeneous network traac possesses diverse statistical properties such as (1) complex temporal correlation , (2) higher-order statistics and (3) a certain (such as periodic) structure. The Part I of this work focuses on modeling temporal correlation (the second-order statistics) of heterogeneous traac, and the Part II will be on modeling non-Gaussian (high-order statistics) and periodic traac. A signiicant discovery from this work is that although heterogeneous network traac has the complicated short-and long-range temporal dependence, the corresponding wavelet coeecients are all \short-range" dependent. Therefore, a \short-range" dependent process can be used to model network traac accurately in the wavelet domain. In particular, both independent and (low-order) Markov wavelet models are developed based on investigations of the correlation structure of wavelet coeecients. Empirical results show that independent wavelet models is suuciently accurate in terms of the auto-correlation function and buuer overrow probability. Markov wavelet models which capture additional correlations in the wavelet domain only improves the performance marginally. Theoretical analysis on auto-correlation functions and buuer loss rate provides quantitative assessment on the accuracy of independent wavelet models for Fractional Gaussian Noise traac. The resulting wavelet models are shown to be parsimonious and have the lowest computational complexity attainable in developing a model, and generating synthetic traac with a complex temporal dependence.
Ethnic group institutions and electoral clientelism

Individual electoral clientelism involves the allocation of handouts to voters around elections. Why is this strategy common in some contexts but not in others? This article demonstrates that ethnic group institutional structure helps to explain this variation. Where ethnic groups are organized hierarchically and have centralized leadership, politicians leverage this infrastructure to mobilize voters wholesale. Where they are not, politicians forge linkages directly with voters, resulting in more electoral clientelism. I provide evidence from a set of African countries, where there is variation in the social structure of ethnic and religious groups. I show that electoral clientelism is more widespread in countries where ethnic groups have a decentralized organization. An individual-level analysis of electoral clientelism in 15 African countries further shows that members of decentralized groups are most likely to receive electoral handouts. The findings contribute to the comparative literature on clientelism and highlight how the organizational structure of intermediaries can shape strategies of clientelism.
Exploiting Symmetry in Tensors for High Performance: An Initial Study

Symmetric tensor operations arise in a wide variety of computations. However, the benets of exploiting symmetry in order to reduce storage and computation is in conict with a desire to simplify memory access patterns. In this paper, we propose Blocked Compact Symmetric Storage wherein we consider the tensor by blocks and store only the unique blocks of a symmetric tensor. We propose an algorithm-by-blocks, already shown of benet for matrix computations, that exploits this storage format. A detailed analysis shows that, relative to storing and computing with tensors without taking advantage of symmetry, storage requirements are reduced by a factor O(m! ) and computational requirements by a factor O(m), where m is the order of the tensor. An implementation demonstrates that the complexity introduced by storing and computing with tensors by blocks is manageable and preliminary results demonstrate that computational time is indeed reduced. The paper concludes with a discussion of how the insights point to opportunities for generalizing recent advances for the domain of linear algebra libraries to the eld of multi-linear computation.
Theoretical Improvement of the Image Compression Method Based on Wavelet Transform

Image compression was performed by several techniques for example: JPEG and JPEG2000 are lossy compression methods. These methods performing scalar quantization on the values obtained after transformation. The disadvantage of the scalar quantization is it does not allow exploiting the spatial correlation between pixels in the image. To improve the compression, we quantified together of values simultaneously it is definition of the vector quantization. In this paper, we studied and modeled an approach to images compression by wavelet transform and Kohonen network. We show the role of null moments in wavelet for improve the compression and we calculate the compression ratio based on compression parameters.
A Learning-Based Approach for Biomedical Word Sense Disambiguation

In the biomedical domain, word sense ambiguity is a widely spread problem with bioinformatics research effort devoted to it being not commensurate and allowing for more development. This paper presents and evaluates a learning-based approach for sense disambiguation within the biomedical domain. The main limitation with supervised methods is the need for a corpus of manually disambiguated instances of the ambiguous words. However, the advances in automatic text annotation and tagging techniques with the help of the plethora of knowledge sources like ontologies and text literature in the biomedical domain will help lessen this limitation. The proposed method utilizes the interaction model (mutual information) between the context words and the senses of the target word to induce reliable learning models for sense disambiguation. The method has been evaluated with the benchmark dataset NLM-WSD with various settings and in biomedical entity species disambiguation. The evaluation results showed that the approach is very competitive and outperforms recently reported results of other published techniques.
An enhanced routing metric for ad hoc networks based on real time testbed

The deployment of wireless ad-hoc networks compared to traditional infrastructure based networks offers several advantages such as fully distributed mobile operation, easy discovery of joining wireless devices and quick cheap network setup. The design of an effective routing protocol is one of the main challenges in the ad-hoc networking paradigm and the utilisation of an adequate link cost metric is essential. In this paper, the validity of ETX (Expected Transmission Count) as a link cost metric is investigated by studying its behaviour in real-time testbeds. In our performance evaluation, the ETX performance was studied in different distance scenarios. Subsequently, the main observation was that ETX values was not steady over time and usually fluctuated for a fixed scenario. Fluctuation in the ETX values affects a routing protocol in wrongly identifying the best path based on current ETX link cost and therefore new methods for ETX calculation are proposed in this paper. These different methods for ETX link cost calculation are compared with each other and the best link cost formula has been proposed as a new method for ETX calculation towards the end of the paper. The new ETX calculation is called AETX that could be used as a link cost in routing protocols that reflects the balance required between the consistency of a link metric value over time for fixed scenarios and the flexibility required to detect actual changes in link metric values. We finally provide conclusions about our research and some avenues for future work.
Distinct triphone modeling by reference model weighting

State tying effectively strikes a balance between detailed modeling and robust parameter estimation for hidden Markov models (HMMs) in automatic speech recognition. However, triphone HMMs that are tied to the same state are not distinguishable in that state. Recently we proposed the idea of distinct acoustic modeling in which no states are tied. In our novel clustered-based eigentriphone modeling method, triphones (or states) are grouped into non-overlapping clusters, from each of which, an orthogonal eigenbasis is derived using weighted PCA. Then all member triphones (or states) of a cluster are projected as distinct points onto the space spanned by its eigenvectors. In this paper, we propose a new simpler training method called reference model weighting (RMW) which removes the requirement of an orthogonal basis in eigentriphone, and directly uses a set of reference model vectors in a cluster as the basis. All member model vectors are then constrained to lie in the space spanned by these reference model vectors. The difference between eigentriphone modeling and reference model weighting is analogous to the difference between eigenvoice and reference speaker weighting in speaker adaptation. The new RMW method shows consistently better performance than eigentriphone and the baseline tied-state HMMs in WSJ0 word recognition and TIMIT phoneme recognition.
Control of Stochastic Gene Expression by Host Factors at the HIV Promoter

The HIV promoter within the viral long terminal repeat (LTR) orchestrates many aspects of the viral life cycle, from the dynamics of viral gene expression and replication to the establishment of a latent state. In particular, after viral integration into the host genome, stochastic fluctuations in viral gene expression amplified by the Tat positive feedback loop can contribute to the formation of either a productive, transactivated state or an inactive state. In a significant fraction of cells harboring an integrated copy of the HIV-1 model provirus (LTR-GFP-IRES-Tat), this bimodal gene expression profile is dynamic, as cells spontaneously and continuously flip between active (Bright) and inactive (Off) expression modes. Furthermore, these switching dynamics may contribute to the establishment and maintenance of proviral latency, because after viral integration long delays in gene expression can occur before viral transactivation. The HIV-1 promoter contains cis-acting Sp1 and NF-κB elements that regulate gene expression via the recruitment of both activating and repressing complexes. We hypothesized that interplay in the recruitment of such positive and negative factors could modulate the stability of the Bright and Off modes and thereby alter the sensitivity of viral gene expression to stochastic fluctuations in the Tat feedback loop. Using model lentivirus variants with mutations introduced in the Sp1 and NF-κB elements, we employed flow cytometry, mRNA quantification, pharmacological perturbations, and chromatin immunoprecipitation to reveal significant functional differences in contributions of each site to viral gene regulation. Specifically, the Sp1 sites apparently stabilize both the Bright and the Off states, such that their mutation promotes noisy gene expression and reduction in the regulation of histone acetylation and deacetylation. Furthermore, the NF-κB sites exhibit distinct properties, with κB site I serving a stronger activating role than κB site II. Moreover, Sp1 site III plays a particularly important role in the recruitment of both p300 and RelA to the promoter. Finally, analysis of 362 clonal cell populations infected with the viral variants revealed that mutations in any of the Sp1 sites yield a 6-fold higher frequency of clonal bifurcation compared to that of the wild-type promoter. Thus, each Sp1 and NF-κB site differentially contributes to the regulation of viral gene expression, and Sp1 sites functionally “dampen” transcriptional noise and thereby modulate the frequency and maintenance of this model of viral latency. These results may have biomedical implications for the treatment of HIV latency.
Novel robot mechanism capable of 3D differential driving inside pipelines

In this paper, novel mechanisms for an in-pipe robot are presented. Multi-axial differential gear mechanism is designed to be driven with only single motor at any elbow-pipe without additional control efforts while all three wheels keep driving power. Brake system was added to prevent slip of wheel. Active wall pressing mechanism allows controlling the contact forces. And additional rescue mechanism is designed for emergency situation. Lastly, their effectiveness is experimentally validated.
Removal of Cd(II), Cu(II) and Zn(II) from aqueous solutions by live Phanerochaete chrysosporium

Living Phanerochaete chrysosporium mycelia were used to remove heavy metals of Cd(II), Cu(II) and Zn(II) in auqeous solution. The uptake of heavy metal by the mycelia was dependent on the environmental conditions. The optimum biosorption conditions of Cd(II), Cu(II), and Zn(II) were pH 5.5–6.5 at 37°C, and 6 h. Under these conditions, the fungal biosorbent removed Cd(II), Cu(II), and Zn(II) rapidly and efficiently with maximum metal removal capacities of 59.77 mg/g, 74.78 mg/g, and 54.12 mg/g, respectively. The pseudo second-order kinetic model was superior to the pseudo first-order kinetic model, which indicated that the change of the surface sorption sites number was proportional to the square of the remaining unoccupied surface sites number. Fourier transform infrared (FT-IR) spectra indicated that hydroxyl and carboxyl groups were relevant to biosorption. Some crystal particles were found on the surface of the P. chrysosporium under scanning electron microscopy. Energy dispersive X-ray analysis and FT-IR revealed that amino acids and proteins were involved in binding metal ions. The results demonstrated that P. chrysosporium was a good potential biosorbent for adsorbing heavy metals.
An Approach to Doubletalk Detection Based on Non-Negative Matrix Factorization

In this paper a novel approach to doubletalk detection (DTD) is presented. This approach uses a modified non-negative matrix factorization (NMF) technique originally developed for monaural sound source separation to perform DTD. The efficacy of this approach is demonstrated through experiments using real room impulse responses (RIRs). The properties of this algorithm are then discussed with reference to experimental results.
Influence of food companies' brand mascots and entertainment companies' cartoon media characters on children's diet and health: a systematic review and research needs

Reducing the extent and persuasive power of marketing unhealthy foods to children worldwide are important obesity prevention goals. Research is limited to understand how brand mascots and cartoon media characters influence children's diet. We conducted a systematic review of five electronic databases (2000–2014) to identify experimental studies that measured how food companies' mascots and entertainment companies' media characters influence up to 12 diet‐related cognitive, behavioural and health outcomes for children under 12 years. Eleven studies met the inclusion criteria. Studies used 21 unique popular media characters, but no brand mascots. Results suggest that cartoon media character branding can positively increase children's fruit or vegetable intake compared with no character branding. However, familiar media character branding is a more powerful influence on children's food preferences, choices and intake, especially for energy‐dense and nutrient‐poor foods (e.g. cookies, candy or chocolate) compared with fruits or vegetables. Future research should use a theoretically grounded conceptual model and larger and more diverse samples across settings to produce stronger findings for mediating and moderating factors. Future research can be used to inform the deliberations of policymakers, practitioners and advocates regarding how media character marketing should be used to support healthy food environments for children.
Menin as a hub controlling mixed lineage leukemia

Mixed lineage leukemia (MLL) fusion protein (FP)‐induced acute leukemia is highly aggressive and often refractory to therapy. Recent progress in the field has unraveled novel mechanisms and targets to combat this disease. Menin, a nuclear protein, interacts with wild‐type (WT) MLL, MLL‐FPs, and other partners such as the chromatin‐associated protein LEDGF and the transcription factor C‐Myb to promote leukemogenesis. The newly solved co‐crystal structure illustrating the menin–MLL interaction, coupled with the role of menin in recruiting both WT MLL and MLL‐FPs to target genes, highlights menin as a scaffold protein and a central hub controlling this type of leukemia. The menin/WT MLL/MLL‐FP hub may also cooperate with several signaling pathways, including Wnt, GSK3, and bromodomain‐containing Brd4‐related pathways to sustain MLL‐FP‐induced leukemogenesis, revealing new therapeutic targets to improve the treatment of MLL‐FP leukemias.
Predicting Tropical Dry Forest Successional Attributes from Space: Is the Key Hidden in Image Texture?

Biodiversity conservation and ecosystem-service provision will increasingly depend on the existence of secondary vegetation. Our success in achieving these goals will be determined by our ability to accurately estimate the structure and diversity of such communities at broad geographic scales. We examined whether the texture (the spatial variation of the image elements) of very high-resolution satellite imagery can be used for this purpose. In 14 fallows of different ages and one mature forest stand in a seasonally dry tropical forest landscape, we estimated basal area, canopy cover, stem density, species richness, Shannon index, Simpson index, and canopy height. The first six attributes were also estimated for a subset comprising the tallest plants. We calculated 40 texture variables based on the red and the near infrared bands, and EVI and NDVI, and selected the best-fit linear models describing each vegetation attribute based on them. Basal area (R 2 = 0.93), vegetation height and cover (0.89), species richness (0.87), and stand age (0.85) were the best-described attributes by two-variable models. Cross validation showed that these models had a high predictive power, and most estimated vegetation attributes were highly accurate. The success of this simple method (a single image was used and the models were linear and included very few variables) rests on the principle that image texture reflects the internal heterogeneity of successional vegetation at the proper scale. The vegetation attributes best predicted by texture are relevant in the face of two of the gravest threats to biosphere integrity: climate change and biodiversity loss. By providing reliable basal area and fallow-age estimates, image-texture analysis allows for the assessment of carbon sequestration and diversity loss rates. New and exciting research avenues open by simplifying the analysis of the extent and complexity of successional vegetation through the spatial variation of its spectral information.
Impact of global warming and rising CO2 levels on coral reef fishes: what hope for the future?

Summary Average sea-surface temperature and the amount of CO2 dissolved in the ocean are rising as a result of increasing concentrations of atmospheric CO2. Many coral reef fishes appear to be living close to their thermal optimum, and for some of them, even relatively moderate increases in temperature (2–4°C) lead to significant reductions in aerobic scope. Reduced aerobic capacity could affect population sustainability because less energy can be devoted to feeding and reproduction. Coral reef fishes seem to have limited capacity to acclimate to elevated temperature as adults, but recent research shows that developmental and transgenerational plasticity occur, which might enable some species to adjust to rising ocean temperatures. Predicted increases in PCO2, and associated ocean acidification, can also influence the aerobic scope of coral reef fishes, although there is considerable interspecific variation, with some species exhibiting a decline and others an increase in aerobic scope at near-future CO2 levels. As with thermal effects, there are transgenerational changes in response to elevated CO2 that could mitigate impacts of high CO2 on the growth and survival of reef fishes. An unexpected discovery is that elevated CO2 has a dramatic effect on a wide range of behaviours and sensory responses of reef fishes, with consequences for the timing of settlement, habitat selection, predator avoidance and individual fitness. The underlying physiological mechanism appears to be the interference of acid–base regulatory processes with brain neurotransmitter function. Differences in the sensitivity of species and populations to global warming and rising CO2 have been identified that will lead to changes in fish community structure as the oceans warm and becomes more acidic; however, the prospect for acclimation and adaptation of populations to these threats also needs to be considered. Ultimately, it will be the capacity for species to adjust to environmental change over coming decades that will determine the impact of climate change on marine ecosystems.
Preliminary Version Static Equivalence is Harder than Knowledge

There are two main ways of defining secrecy of cryptographic protocols. The first version checks if the adversary can learn the value of a secret parameter. In the second version, one checks if the adversary can notice any difference between protocol runs with different values of the secret parameter. We give a new proof that when considering more complex equational theories than partially invertible functions, these two kinds of secrecy are not equally difficult to verify. More precisely, we identify a message language equipped with a convergent rewrite system such that after a completed protocol run, the first problem mentioned above (adversary knowledge) is decidable but the second problem (static equivalence) is not. The proof is by reduction of the ambiguity problem for context-free grammars.
Separation of EOG artifacts from EEG signals using bivariate EMD

A problem of eye-movement muscular interference removal from EEG recordings is described. In many experiments in neuroscience it is crucial to separate different sources of electrical activity within human body in a situation when a very limited knowledge about nonlinear and nonstationary nature of the mixing process is available. A new two step extension to bivariate empirical mode decomposition is proposed to remove ocular artifacts from EEG with a use of fractional Gaussian noise as a reference first to preprocess EOG signal, which is next used in the second step as a reference to clean EEG signals. Results with EEG experimental data validate the proposed approach.
Multiple component remediation of developmental reading disabilities: A Controlled factorial evaluation of the influence of IQ, socioeconomic status, and race on outcomes

Results from a controlled evaluation of remedial reading interventions are reported: 279 young disabled readers were randomly assigned to a program according to a 2 × 2 × 2 factorial design (IQ, socioeconomic status [SES], and race). The effectiveness of two multiple-component intervention programs for children with reading disabilities (PHAB + RAVE-O; PHAB + WIST) was evaluated against alternate (CSS, MATH) and phonological control programs. Interventions were taught an hour daily for 70 days on a 1:4 ratio at three different sites. Multiple-component programs showed significant improvements relative to control programs on all basic reading skills after 70 hours and at 1-year follow-up. Equivalent gains were observed for different racial, SES, and IQ groups. These factors did not systematically interact with program. Differential outcomes for word identification, fluency, comprehension, and vocabulary were found between the multidimensional programs, although equivalent long-term outcomes and equal continued growth confirmed that different pathways exist to effective reading remediation.