Miracle-dz/UniFAR-FTUs huggingface dataset:
Post-Filtering for Residual ECHO Suppression in Under-Modeled Acoustic ECHO Cancellers

This paper investigates the use of post-filtering algorithms for suppressing residual echo in adaptive acoustic echo cancellers, which is an important component of hands-free telephone systems. The goal of post-filtering is to enhance near-end speech corrupted by residual echo due to echo canceller under-modeling. In this paper the use of signal subspace enhancement is investigated as a post-filter structure by employing a subspace decomposition of the echo canceller error signal using the Karhunen-Loeve transform (KLT). In particular, the spectral-domain constrained (SDC) linear estimator is employed to enhance the near-end speech subspace while suppressing the residual echo subspace. Practical and low-complexity implementation considerations are discussed. Simulation results are presented comparing the approach to frequency-domain post-filtering in terms of objective near-end speech distortion and quality measures
Isolating neural correlates of conscious perception from neural correlates of reporting one's perception

To isolate neural correlates of conscious perception (NCCs), a standard approach has been to contrast neural activity elicited by identical stimuli of which subjects are aware vs. unaware. Because conscious experience is private, determining whether a stimulus was consciously perceived requires subjective report: e.g., button-presses indicating detection, visibility ratings, verbal reports, etc. This reporting requirement introduces a methodological confound when attempting to isolate NCCs: The neural processes responsible for accessing and reporting one's percept are difficult to distinguish from those underlying the conscious percept itself. Here, we review recent attempts to circumvent this issue via a modified inattentional blindness paradigm (Pitts et al., 2012) and present new data from a backward masking experiment in which task-relevance and visual awareness were manipulated in a 2 × 2 crossed design. In agreement with our previous inattentional blindness results, stimuli that were consciously perceived yet not immediately accessed for report (aware, task-irrelevant condition) elicited a mid-latency posterior ERP negativity (~200–240 ms), while stimuli that were accessed for report (aware, task-relevant condition) elicited additional components including a robust P3b (~380–480 ms) subsequent to the mid-latency negativity. Overall, these results suggest that some of the NCCs identified in previous studies may be more closely linked with accessing and maintaining perceptual information for reporting purposes than with encoding the conscious percept itself. An open question is whether the remaining NCC candidate (the ERP negativity at 200–240 ms) reflects visual awareness or object-based attention.
Does macro-level corporate governance attract foreign direct investment (FDI)? a review of Sub-Saharan African Countries

The performance of the Sub-Saharan Africa (SSA) region in attracting foreign direct investment (FDI) relevant to other developing regions has been poor over the last two decades, especially compared to Asian developing countries. FDI inflows are a catalyst for economic growth, employment and poverty reduction. This study examined whether good macro-level corporate governance, which is the way countries are managed and governed, can assist in promoting countries as potential investment locations. The Worldwide Governance Index, which has been developed by Kaufmann et al (1999, 2008, 2011), was used to objectively measure the performance of the SSA region. The region has generally been perceived to be negatively impacted by political risk, lack of government leadership, weak institutions, ineffective implementation of policies and a region susceptible to corruption. This study examined the relationship between macro-level governance performances of the SSA region and sought to determine whether this is a contributing factor which affects FDI inflows. The study used panel data fixed effect estimator for a sample of 45 SSA countries from 2002 to 2011. The findings have revealed that macro-level corporate governance has a positive impact and is statistically significant in attracting FDI inflows. In addition to the other factors which drive FDI inflows for the region, this provides an incentive to host countries to develop polices which can leverage and promote investment to the region, fundamentally addressing pressing social challenges and sustainable economic development and growth.
Quantification and comparison of degree distributions in complex networks

The degree distribution is an important characteristic in complex networks. In many applications, quantification of degree distribution in the form of a fixed-length feature vector is a necessary step. Additionally, we often need to compare the degree distribution of two given networks and extract the amount of similarity between the two distributions. In this paper, we propose a novel method for quantification of the degree distributions in complex networks. Based on this quantification method, a new distance function is also proposed for degree distributions, which captures the differences in the overall structure of the two given distributions. The proposed method is able to effectively compare networks even with different scales, and outperforms the state of the art methods considerably, with respect to the accuracy of the distance function. The datasets and more detailed evaluations are available upon request.
In Vitro Grown Sheep Preantral Follicles Yield Oocytes with Normal Nuclear-Epigenetic Maturation

Background Assisted reproductive technologies allow to utilize a limited number of fully grown oocytes despite the presence in the ovary of a large pool of meiotically incompetent gametes potentially able to produce live births. In vitro folliculogenesis could be useful to recruit these oocytes by promoting their growth and differentiation. Methodology/Principal Findings In vitro folliculogenesis was performed starting from sheep preantral (PA) follicles to evaluate oocyte nuclear/epigenetic maturation. Chromatin configuration, quantification of global DNA methylation, and epigenetic remodelling enzymes were evaluated with immunocytochemistry, telomere elongation was assessed with the Q-FISH technique, while the DNA methylation status at the DMRs of maternally IGF2R and BEGAIN, and paternally H19 methylated imprinted genes was determined by bisulfite sequencing and COBRA. Specifically, 70% of PA underwent early antrum (EA) differentiation and supported in culture oocyte global DNA methylation, telomere elongation, TERT and Dnmt3a redistribution thus mimicking the physiological events that involve the oocyte during the transition from secondary to tertiary follicle. Dnmt1 anticipated cytoplasmic translocation in in vitro grown oocytes did not impair global and single gene DNA methylation. Indeed, the in vitro grown oocytes acquired a methylation profile of IGF2R and BEGAIN compatible with the follicle/oocyte stage reached, and maintained an unmethylated status of H19. In addition, the percentage of oocytes displaying a condensed chromatin configuration resulted lower in in vitro grown oocytes, however, their ability to undergo meiosis and early embryo development after IVF and parthenogenetic activation was similar to that recorded in EA follicle in vivo grown oocytes. Conclusions/Significance In conclusion, the in vitro folliculogenesis was able to support the intracellular/nuclear mechanisms leading the oocytes to acquire a meiotic and developmental competence. Thus, the in vitro culture may increase the availability of fertilizable oocytes in sheep, and become an in vitro translational model to investigate the mechanisms governing nuclear/epigenetic oocyte maturation.
Soft-in soft-out decoding of Reed-Solomon codes based on Vardy and Be'ery's decomposition

This correspondence presents an optimal soft-in soft-out (SISO) decoding algorithm for the binary image of Reed-Solomon (RS) codes that is based on Vardy and Be'ery's optimal soft-in hard-out algorithm. A novel suboptimal list-based SISO decoder that exploits Vardy and Be'ery's decomposition is also presented. For those codes with very high rate, which allows practical decoding with the proposed algorithms, the proposed suboptimal SISO significantly outperforms standard list-based decoding techniques in iteratively decoded systems.
Quantifying the effect of corpus size on the quality of automatic diacritization of Yorùbá texts

Yorùbá being a tone language requires tone information for the correct pronunciation of words in Text-to-Speech synthesis. Based on standard Yorùbá orthography, such information is held in tone marks, which applied to vowels and syllabic nasals as diacritical markings. However, the tone marks are not always correctly applied in many Yorùbá documents because appropriate input devices for the accurate application of the diacritic marks are not always available. Hence, the absence of tone marks in most written Yorùbá texts presents a major challenge in speech synthesis as the information required for applying the right tone sequences to synthesized Yorùbá speech may not always be available. This study proposes the use of Machine Learning techniques as a basis for the automatic application of tone marks as part of the pre-processing in high level synthesis. Being a resource-scarce language however, there is a lack of sufficiently large Yorùbá corpora for the training of an automatic diacritizer. The study therefore investigated the relationship between corpus size and the quality of automatic diacritization towards estimating the size of corpus required for an ideal level of accuracy.
Towards Unsteady Approach for Future Flutter Calculations

: In prior work to define an improved hydrodynamic approach to flutter calculations, Centrale Nantes, Bureau Veritas Marine & Offshore and Farr Yacht design investigated the possibility of defining a linearized unsteady hydrodynamic model using a fluid response database coming from a series of 2D unsteady RANSE computations. The approach is compared to the Theodorsen theory. The linearized hydrodynamic model was used in a strip theory model for frequency domain flutter analysis. In this latest work, the IMOCA 2006 keel which has been used previously in frequential domain flutter calculation is also analyzed using an alternative and more accurate solution, featuring a fully coupled FSI modal approach with CFD. As described in the literature, the results present a large impact of the unsteadiness on the phase and module for both lift and moment with a fairly good match compared to Theodorsen theory. The implementation of the results on a frequency domain flutter analysis tool reduces the critical speed for the studied model. Thus the results are closer to the 3D modal CFD approach which gave an lower critical speed.
Implications of polygenic risk for personalised colorectal cancer screening

Pfizer. MB has received honoraria from Boehringer Ingelheim and Eli Lilly. TM has received honoraria for serving on advisory board meetings for Astra Zeneca, Boehringer Ingelheim, Roche, Pfizer, Eli Lilly, Novartis, Clovis, Amgen, Janssen, Biomarin, Merck Serono, Bristol Myer Squibb, Aveo, Eisai and Taiho Pharmaceuticals. PAJ has received honoraria for serving as a consultant for Pfizer, Astra Zeneca, Boehringer Ingelheim, Clovis Oncology, Genentech, Merrimack, Lab Corp and has stock ownership in Gatekeeper Pharmaceuticals and receives royalty form a patent licensed to Lab Corp. HZ, JL, IT and EIS are employees of Pfizer Oncology. IT owns stock options in Pfizer Oncology.
Assessing the applicability of the structured expert evaluation method (SEEM) for a wider age group

This paper describes a study which examines whether a predictive evaluation method (SEEM) is suitable to assess products for an older age group than for which the evaluation method was originally developed. SEEM stands for Structured Expert Evaluation Method and is an analytical evaluation method especially developed for assessing the fun and usability of young children's educational computer games (children from 5 to 7 years old). In the present study SEEM was applied to assess educational computer games for children between 9 and 11 years old. Outcomes on scores for thoroughness (whether SEEM finds all problems), validity (whether SEEM makes predictions that are likely to be true) and appropriateness (whether SEEM is applied correctly) were compared. The results show that the trends for the thoroughness and the validity are the same for the two different age groups; however SEEM scores a bit better for the oldest age group. The appropriateness scores are about the same for the two age groups. The results indicate that SEEM can also be applied for assessing educational computer games for children between 9 and 11 years old.
ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 3 i j ( b ) ( c ) ( a ) i j Unary Term Pairwise Term Triple Penalty Label Contexts

Semantic segmentation tasks can be well modeled by Markov Random Field (MRF). This paper addresses semantic segmentation by incorporating high-order relations and mixture of label contexts into MRF. Unlike previous works that optimized MRFs using iterative algorithm, we solve MRF by proposing a Convolutional Neural Network (CNN), namely Deep Parsing Network (DPN), which enables deterministic end-to-end computation in a single forward pass. Specifically, DPN extends a contemporary CNN to model unary terms and additional layers are devised to approximate the mean field (MF) algorithm for pairwise terms. It has several appealing properties. First, different from the recent works that required many iterations of MF during back-propagation, DPN is able to achieve high performance by approximating one iteration of MF. Second, DPN represents various types of pairwise terms, making many existing models as its special cases. Furthermore, pairwise terms in DPN provide a unified framework to encode rich contextual information in high-dimensional data, such as images and videos. Third, DPN makes MF easier to be parallelized and speeded up, thus enabling efficient inference. DPN is thoroughly evaluated on standard semantic image/video segmentation benchmarks, where a single DPN model yields state-of-the-art segmentation accuracies on PASCAL VOC 2012, Cityscapes dataset and CamVid dataset.
Image-to-Class Dynamic Time Warping for 3D hand gesture recognition

3D Human Computer Interaction (HCI) becomes more and more popular thanks to the emergence of commercial depth cameras. Moreover, hand gestures provide a natural and attractive alternative to cumbersome interface devices for HCI. In this paper, we present an Image-to-Class Dynamic Time Warping (I2C-DTW) approach for 3D hand gesture recognition. Themain idea is that we divide the time-series curve of a 3D hand gesture into various finger combinations, called `fingerlets', which can either be learned or be set manually to represent each gesture and to capture inter-class variations. Furthermore, the I2C-DTW approach searches for the minimal path to warp two fingerlets, which are fromone test image and the specific class, respectively. Then the gesture recognition is to use the ensemble of multiple image-to-class DTW distance of fingerlets to obtain better performance. The proposed approach is evaluated on two 3D hand gesture datasets and the experiment results show that the proposed I2C-DTW approach significantly improves the recognizing performance.
Gradient based method for cone programming with application to large-scale compressed sensing

In this paper, we study a gradient based method for general cone programming (CP) problems. In particular, we first consider four natural primal-dual convex smooth minimization reformulations for them, and then discuss a variant of Nesterov’s smooth (VNS) method recently proposed by Auslender and Teboulle [1] for solving these reformulations. The associated worst-case major arithmetic operations costs of the VNS method for them are estimated and compared. We show that for a class of CP problems, the VNS method based on the last reformulation generally outperforms that applied to the others. Finally, we discuss the application of the VNS method [1] to some large-scale CP problems arising in compressed sensing, which are highly challenging to simplex and/or interior point (IP) methods. The performance of this method is compared with the IP method [5] that is specially implemented for these problems. Our computational results demonstrate that for these CP problems, the VNS method [1] applied to the mostly suitable reformulation mentioned above substantially outperforms the IP method [5].
A G ] 5 J un 2 00 4 MIRROR SYMMETRY AND GENERALIZED COMPLEX MANIFOLDS

In this paper we develop a relative version of T-duality in generalized complex geometry which we propose as a manifestation of mirror symmetry. Let M be an n−dimensional smooth real manifold, V a rank n real vector bundle on M , and ∇ a flat connection on V . We define the notion of a ∇−semi-flat generalized complex structure on the total space of V . We show that there is an explicit bijective correspondence between ∇−semi-flat generalized complex structures on the total space of V and ∇−semi-flat generalized complex structures on the total space of V . Similarly we define semi-flat generalized complex structures on real n−torus bundles with section over an n-dimensional base and establish a similar bijective correspondence between semi-flat generalized complex structures on pair of dual torus bundles. Along the way, we give methods of constructing generalized complex structures on the total spaces of vector bundles and torus bundles with sections. We also show that semi-flat generalized complex structures give rise to a pair of transverse Dirac structures on the base manifold. We give interpretations of these results in terms of relationships between the cohomology of torus bundles and their duals. We also study the ways in which our results generalize some well established aspects of mirror symmetry as well as some recent proposals relating generalized complex geometry to string theory.
Recognition of correct finger placement for photoplethysmographic imaging

In mobile health applications, non-expert users often perform the required medical measurements without supervision. Therefore, it is important that the mobile device guides them through the correct measurement process and automatically detects potential errors that could impact the readings. Camera oximetry provides a non-invasive measurement of heart rate and blood oxygen saturation using the camera of a mobile phone. We describe a novel method to automatically detect the correct finger placement on the camera lens for camera oximetry. Incorrect placement can cause optical shunt and if ignored, lead to low quality oximetry readings. The presented algorithm uses the spectral properties of the pixels to discriminate between correct and incorrect placements. Experimental results demonstrate high mean accuracy (99.06%), sensitivity (98.06%) and specificity (99.30%) with low variability. By sub-sampling pixels, the computational cost of classifying a frame has been reduced by more than three orders of magnitude. The algorithm has been integrated in a newly developed application called OxiCam where it provides real-time user feedback.
TaintPipe: Pipelined Symbolic Taint Analysis

Taint analysis has a wide variety of compelling applications in security tasks, from software attack detection to data lifetime analysis. Static taint analysis propagates taint values following all possible paths with no need for concrete execution, but is generally less accurate than dynamic analysis. Unfortunately, the high performance penalty incurred by dynamic taint analyses makes its deployment impractical in production systems. To ameliorate this performance bottleneck, recent research efforts aim to decouple data flow tracking logic from program execution. We continue this line of research in this paper and propose pipelined symbolic taint analysis, a novel technique for parallelizing and pipelining taint analysis to take advantage of ubiquitous multi-core platforms. We have developed a prototype system called TaintPipe. TaintPipe performs very lightweight runtime logging to produce compact control flow profiles, and spawns multiple threads as different stages of a pipeline to carry out symbolic taint analysis in parallel. Our experiments show that TaintPipe imposes low overhead on application runtime performance and accelerates taint analysis significantly. Compared to a state-of-the-art inlined dynamic data flow tracking tool, TaintPipe achieves 2.38 times speedup for taint analysis on SPEC 2006 and 2.43 times for a set of common utilities, respectively. In addition, we demonstrate the strength of TaintPipe such as natural support of multi-tag taint analysis with several security applications.
Comparative Genomic and Sequence Analysis Provides Insight into the Molecular Functionality of NOD1 and NOD2

Amino acids with functional or key structural roles display higher degrees of conservation through evolution. The comparative analysis of protein sequences from multiple species and/or between homologous proteins can be highly informative in the identification of key structural and functional residues. Residues which in turn provide insight into the molecular mechanisms of protein function. We have explored the genomic and amino acid conservation of the prototypic innate immune genes NOD1 and NOD2. NOD1 orthologs were found in all vertebrate species analyzed, whilst NOD2 was absent from the genomes of avian, reptilian and amphibian species. Evolutionary trace analysis was used to identify highly conserved regions of NOD1 and NOD2 across multiple species. Consistent with the known functions of NOD1 and NOD2 highly conserved patches were identified that matched the Walker A and B motifs and provided interaction surfaces for the adaptor protein RIP2. Other patches of high conservation reflect key structural functions as predicted by homology models. In addition, the pattern of residue conservation within the leucine-rich repeat (LRR) region of NOD1 and NOD2 is indicative of a conserved mechanism of ligand recognition involving the concave surface of the LRRs.
On protection in operating systems

A model of protection mechanisms in computing systems is presented and its appropriateness is demonstrated. The “safety” problem for protection systems under our model is to determine in a given situation whether a subject can acquire a particular right to an object. In restricted cases, one can show that this problem is decidable, i.e., there is an algorithm to determine whether a system in a particular configuration is safe. In general, and under surprisingly weak assumptions, one cannot decide if a situation is safe. Various implications of this fact are discussed.