Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian texture classification using steerable Riesz wavelets: Application to sonar images

In this paper, the classification and segmentation of seafloor images recorded by sidescan sonar is considered. To address this problem, which can be related to texture analysis, a supervised approach based on the Bayesian framework is proposed. The features of the textured images are obtained through a parametric probabilistic model of the 2D steerable Riesz wavelet coefficients. The generalized Gaussian distribution, which is a well-established model, is used in this contribution. It is also proposed to model the approximation coefficients using the finite Gaussian mixture model to enhance the classification rate between two statistically close classes when considering only the detail coefficients. The classification results using the 2D steerable Riesz wavelets are compared to the results obtained using the classical discrete wavelets. Then, this classification method is used for image segmentation.
Watermarking mesh-based representations of 3-D objects using local moments

A new methodology for fingerprinting and watermarking three-dimensional (3-D) graphical objects is proposed in this paper. The 3-D graphical objects are described by means of polygonal meshes. The information to be embedded is provided as a binary code. A watermarking methodology has two stages: embedding and detecting the information that has been embedded in the given media. The information is embedded by means of local geometrical perturbations while maintaining the local connectivity. A neighborhood localized measure is used for selecting appropriate vertices for watermarking. A study is undertaken in order to verify the suitability of this measure for selecting vertices from regions where geometrical perturbations are less perceptible. Two different watermarking algorithms, that do not require the original 3-D graphical object in the detection stage, are proposed. The two algorithms differ with respect to the type of constraint to be embedded in the local structure: by using parallel planes and bounding ellipsoids, respectively. The information capacity of various 3-D meshes is analyzed when using the proposed 3-D watermarking algorithms. The robustness of the 3-D watermarking algorithms is tested to noise perturbation and to object cropping.
Analysis of Electromagnetic Wave Scattering by Graphene Flakes Using the Generalized Multipole Technique

The generalized multipole method is applied to the analysis of the electromagnetic wave scattered by graphene flakes. In the proposed method, the graphene flakes are modeled as surface current sheets causing a discontinuity in the magnetic field. This method is used to analyze the scattering from isolated islands of the graphene layer. In addition, the field enhancement between two nearby graphene flakes as well as the field distribution of a two dimensional periodic configuration of these flakes are investigated with the proposed method. To validate the developed method, its numerical results are compared with those of the finite element method (FEM). As compared to the model used in the FEM, the surface current model used in the proposed method significantly reduces the computational complexity.
Localizing hotspots of antisense transcription

Analysis of the transcriptome by computational and experimental methods has established that sense–antisense transcriptional units are a common phenomenon. Although the regulatory potential of antisense transcripts has been experimentally verified in a number of studies, the biological importance of sense–antisense regulation of gene expression is still a matter of debate. Here, we report the identification of sequence features that are associated with antisense transcription. We show that the sequence composition of the first exon and the 5′end of the first intron of many human genes is similar to the sequence composition observed in promoter regions as measured by the density of known transcription regulatory motifs. Cloned intron-derived fragments were found to possess bidirectional promoter activity. In agreement with the reported abundance of antisense transcripts overlapping the 5′UTR, mapping of the 5′ends of antisense transcripts to the corresponding sense transcripts revealed that the first exon and the 5′end of the first intron are hotspots of antisense transcription as measured by the number of antisense transcription start sites per unit sequence. CpG dinucleotide suppression that is typically weak in non-methylated promoter regions is similarly weakened upstream as well as downstream of the first exon. In support of antisense transcripts playing a regulatory role, we find that 5′UTRs and first exons of genes with overlapping antisense transcripts are significantly longer than the genomic average. Interestingly, a similar size distribution of 5′UTRs and first exons is observed for genes silenced by CpG island methylation in human cancer.
A New Flexible Algorithm for Random Yield Improvement

This paper presents a new and improved solution for random yield improvement at the post-routing stage. The proposed solution is better suited for current processes, where a clustering effect has been observed resulting in differing particle densities in the metal and empty regions of the chip. To account for this clustering effect, the authors introduce the concept of weighted critical area to serve as a proxy for random yield loss. A new algorithm for weighted critical area, minimization is also introduced. Based on the user-specified particle densities, the proposed optimization solution is driven by the weighted critical area axis dynamically selects the appropriate critical area reduction technique in each local region to guarantee a reduction of the weighted critical area in both the local region and the whole layer. This makes the algorithm flexible and readily applicable to different process lines. It consistently improves the random yield irrespective of the particle densities in the metal and empty regions of the chip
A corpus-based conceptual clustering method for verb frames and ontology

We describe in this paper the ML system, ASIUM, which learns subcategorization frames of verbs and ontologies from syntactic parsing of technical texts in natural language. The restrictions of selection in the subcategorization frames are filled by the concepts of the ontology. Applications requiring subcategorization frames and ontologies are crucial and numerous. The most direct applications are semantic checking of texts and syntactic parsing improvement but also text generation and translation. The inputs of ASIUM result from syntactic parsing of texts, they are subcategorization examples and basic clusters formed by head words that occur with the same verb after the same preposition (or with the same syntactical role). ASIUM successively aggregates the clusters to form new concepts in the form of a generality graph that represents the ontology of the domain. Subcategorization frames are learned in parallel, so that as concepts are formed, they fill restrictions of selection in the subcategorization frames. ASIUM method is based on conceptual clustering. First experiments have been performed on a corpora of cooking recipes and give very promising results reported here.
Structure, Regulation and Function of Gap Junctions in Liver

Abstract Gap junctions are a specialized group of cell-to-cell junctions that mediate direct intercellular communication between cells. They arise from the interaction of two hemichannels of adjacent cells, which in turn are composed of six connexin proteins. In liver, gap junctions are predominantly found in hepatocytes and play critical roles in virtually all phases of the hepatic life cycle, including cell growth, differentiation, liver-specific functionality and cell death. Liver gap junctions are directed through a broad variety of mechanisms ranging from epigenetic control of connexin expression to post-translational regulation of gap junction activity. This paper reviews established and novel aspects regarding the architecture, control and functional relevance of liver gap junctions.
A framework to quantify karyotype variation associated with CHO cell line instability at a single‐cell level

Chinese hamster ovary (CHO) cells, the major mammalian host cells for biomanufacturing of therapeutic proteins, have been extensively investigated to enhance productivity and product quality. However, cell line instability resulting in unexpected changes in productivity or product quality continues to be a challenge. Based on previous reports about causes and characteristics of production instability, we hypothesized that chromosomal rearrangements due to genomic instability are associated with production instability and that these events can be characterized. We developed a production instability model using secreted alkaline phosphatase (SEAP)‐expressing CHO cells (CHO‐SEAP) as well as a framework to quantify chromosomal rearrangements by karyotyping. In the absence of methotrexate (MTX), CHO‐SEAP cells exhibited a slightly increased growth rate, a significantly decreased specific productivity, and changes in the chromosomal rearrangement ratio of seven chromosomes. In contrast, when MTX was re‐introduced, the growth rate and SEAP productivity reversed to the initial values, demonstrating the reversibility of production instability in CHO‐SEAP cells. Fluorescence in situ hybridization analysis identified that the SEAP genes were incorporated in the chromosomal rearrangement (insertion) part of the der(Z9) chromosome. Karyotype analysis indicated that the insertion ratio of the der(Z9) chromosome decreased in the CHO‐SEAP cells grown without MTX, demonstrating a correlation between chromosomal rearrangement and production instability. Our results support a mechanism for production instability, wherein a randomly generated chromosomal rearrangement (or genotype) results in cells with a growth advantage that is also associated with non (or low)‐producing traits. As a result, the non‐producing cells grow faster and thereby outgrow the producing population. Biotechnol. Bioeng. 2017;114: 1045–1053. © 2016 Wiley Periodicals, Inc.
VASCULAR PATTERN CLASSIFICATION OF COLORECTAL LESIONS WITH NARROW BAND IMAGING MAGNIFYING ENDOSCOPY

Magnifying narrow band imaging (NBI) has enabled to observe the vascular pattern of colorectal lesions. Their broad findings have been divided into six groups according to endoscopical vascular features: normal, faint, network, dense, irregular and sparse. Most hyperplastic polyps show a faint pattern. The vascular patterns of adenomas are mainly network or dense ones. The predominant vascular patterns of cancer were irregular and sparse. Indeed, irregular pattern has found to be characteristic for protruded or flat‐elevated cancer, whereas sparse pattern unique for depressed cancer. Through NBI, neoplastic lesions could be differentiated from those non‐neoplastic with sensitivity of 83.5%, specificity of 98.7% and accuracy of 98.2%. It was able to distinguish between massively submucosal invasive cancers and slightly submucosal invasive cancers by using the vascular pattern with 91.0% sensitivity and 79.4% specificity. The overall accuracy was 88.3%. NBI system has showed to be a valuable technique for distinguishing neoplastic from non‐neoplastic lesions, as well as massively from slightly submucosal invasive cancer. Therefore, vascular pattern analysis might be a promising tool for determining treatment selection, whether endoscopical or surgically.
Computing Upper Bounds on Lengths of Transition Sequences

We describe an approach to computing upper bounds on the lengths of solutions to reachability problems in transition systems. It is based on a decomposition of state-variable dependency graphs (causal graphs). Our approach is able to find practical upper bounds in a number of planning benchmarks. Computing the bounds is computationally cheap in practice, and in a number of benchmarks our algorithm runs in polynomial time in the number of actions and propositional variables that characterize the problem.
Reconstruction métrique minimale à partir de trois caméras affines

Structure and motion from minimal data is essential to bootstrap robust methods based on random sampling such as RANSAC (RANdom SAmple Consensus) or LMS (Least Median of Squares). Let us consider the affine camera model and make the hypotheses of zero skew and unity aspect ratio. In this case, at least 4 points in 3 images are necessary to recover structure and motion. We propose a parametrization based on metric structure rather than camera motion parameters which have been previously used. The structure of 4 points is computed in closed-form by solving a quadratic equation. Unstable configurations are also investigated. Experimental results on simulated data and real images demonstrate the stability of our algorithm. Computed solutions with minimal data are compared with those obtained after optimization on redundant data.
iNOS activity is critical for the clearance of Burkholderia mallei from infected RAW 264.7 murine macrophages

Burkholderia mallei is a facultative intracellular pathogen that can cause fatal disease in animals and humans. To better understand the role of phagocytic cells in the control of infections caused by this organism, studies were initiated to examine the interactions of B. mallei with RAW 264.7 murine macrophages. Utilizing modified kanamycin‐protection assays, B. mallei was shown to survive and replicate in RAW 264.7 cells infected at multiplicities of infection (moi) of ≤ 1. In contrast, the organism was efficiently cleared by the macrophages when infected at an moi of 10. Interestingly, studies demonstrated that the monolayers only produced high levels of TNF‐α, IL‐6, IL‐10, GM‐CSF, RANTES and IFN‐β when infected at an moi of 10. In addition, nitric oxide assays and inducible nitric oxide synthase (iNOS) immunoblot analyses revealed a strong correlation between iNOS activity and clearance of B. mallei from RAW 264.7 cells. Furthermore, treatment of activated macrophages with the iNOS inhibitor, aminoguanidine, inhibited clearance of B. mallei from infected monolayers. Based upon these results, it appears that moi significantly influence the outcome of interactions between B. mallei and murine macrophages and that iNOS activity is critical for the clearance of B. mallei from activated RAW 264.7 cells.
Negotiating gestalt: artistic expression and coalition formation in multiagent systems

We present a system using semi-autonomous agents to help artists express ideas. The agents control their representation on a canvas via interactions in an agent space by themselves and in coalitions. The artist can take direct control if the resulting image is not satisfactory. We have implemented the Surreal engine that realises these ideas and we present a case study of its usage in producing Mondriaan-like paintings.
Automating Help-desk Responses: A Comparative Study of Information-gathering Approaches

We present a comparative study of corpus-based methods for the automatic synthesis of email responses to help-desk requests. Our methods were developed by considering two operational dimensions: (1) information-gathering technique, and (2) granularity of the information. In particular, we investigate two techniques -- retrieval and prediction -- applied to information represented at two levels of granularity -- sentence-level and document level. We also developed a hybrid method that combines prediction with retrieval. Our results show that the different approaches are applicable in different situations, addressing a combined 72% of the requests with either complete or partial responses.
Techniques for low energy software

The energy consumption of a system depends upon the hardware and software component of a system. Since it is the software which drives the hardware in most systems, decisions taken during software design has significant impact on the energy consumption of the processor. The paper focuses on decreasing energy consumption of a processor using software techniques. A novel compiler technique is proposed which reduces energy consumption by proper register labeling during the compilation phase. The idea behind this technique is to reduce the energy of the processor by reducing the energy of the instruction register (also the instruction data bus) and the register file decoder by encoding the register labels such that the sum of the switching costs between all the register labels in the transition graph is minimized. There is no hardware penalty since this is purely a compiler optimization. Results on benchmarks show that the energy consumption of the DLX processor can be reduced by 9.82% (maximum) and 4.25% (average) (as measured by DLX energy simulator). In addition several compiler techniques such as loop unrolling, software pipelining, recursion elimination and of effects of different algorithms on power and energy consumption are studied. This evaluation methodology is useful for computer architects to evaluate energy improvements of their hardware, compiler writers to evaluate energy of the compiled code and program writers to evaluate energy of data structures and algorithms.
Gut Feelings: Bacteria and the Brain

Editor’s note: The gut-brain axis—an imaginary line between the brain and the gut—is one of the new frontiers of neuroscience. Microbiota in our gut, sometimes referred to as the “second genome” or the “second brain,” may influence our mood in ways that scientists are just now beginning to understand. Unlike with inherited genes, it may be possible to reshape, or even to cultivate, this second genome. As research evolves from mice to people, further understanding of microbiota’s relationship to the human brain could have significant mental health implications.
Mobile Querying of Online Semantic Web Data for Context-Aware Applications

Mobile devices are increasingly multifunctional and personal, providing mobile applications with the necessary user information to achieve personalization. At the same time, detection technologies let such devices find nearby physical entities and thus map the user's environment. By exploiting existing online Semantic Web sources about these detected entities, mobile applications can further improve personalization. SCOUT is a mobile application framework that supports linking physical entities to online semantic data sources. It provides applications with an integrated, query-able view on these sources and the user's environment. The authors developed a tailored data management approach to efficiently access these distributed online semantic sources.
Preventive intervention as means of clarifying direction of effects in socialization: Anxious-withdrawn preschoolers case

An indicated preventive intervention research program integrating attachment, attributional, and behaviorist perspectives was conducted to test the hypothesis that parent–child relationship disturbances directly effect the child's adjustment to the preschool. Anxious-withdrawn preschool children and their mothers were divided equally into treatment and control groups, and assessed on maternal self-report of parenting stress, behavioral ratings of mother–child interaction, and teacher ratings of the children in the preschool classroom. Results showed significant changes in the treatment group: mothers in the treatment group moderated their level of control to a more appropriate, less intrusive level, while children in the treatment group showed an increase in cooperation and enthusiasm during a problem solving task with mother. Teacher-rated social competence and anxious-withdrawn behavior indicated improvement, although only the former was significant. The demonstration of effects of this home intervention for the mother on the child's behavior in the preschool confirm the transactional model underlying this study and demonstrate the utility of a parent–child interaction training component for the prevention of behavioral–emotional problems in young children.
Analysis of Non-English Majors＇ Individual Differences in Writing Proficiency in Private Colleges

Based on the theory of individual differences, this study is designed to investigate the influence of gender and learners’ L2 proficiency on non-English majors’ writing proficiency. A timed writing test is carried out among 130 participants from Ningbo Dahongying College. After the collection of the writing samples, all valid samples are subjectively rated, and syntactic errors are calculated. Afterwards, with assistance of SPSS 19.0, the major findings of the study are as follows: First, female students excel male students in writing proficiency which is reflected by syntactic accuracy. To be specific, female students do much better in agreement in terms of syntactic accuracy. Second, high L2 proficiency group outperforms low L2 proficiency group in writing proficiency. Specifically, high L2 proficiency group does much better in the following specific aspects in terms of syntactic accuracy: agreement and use of predicate verbs.
A generic framework for monitoring continuous spatial queries over moving objects

This paper proposes a generic framework for monitoring continuous spatial queries over moving objects. The framework distinguishes itself from existing work by being the first to address the location update issue and to provide a common interface for monitoring mixed types of queries. Based on the notion of safe region, the client location update strategy is developed based on the queries being monitored. Thus, it significantly reduces the wireless communication and query reevaluation costs required to maintain the up-to-date query results. We propose algorithms for query evaluation/reevaluation and for safe region computation in this framework. Enhancements are also proposed to take advantage of two practical mobility assumptions: maximum speed and steady movement. The experimental results show that our framework substantially outperforms the traditional periodic monitoring scheme in terms of monitoring accuracy and CPU time while achieving a close-to-optimal wireless communication cost. The framework also can scale up to a large monitoring system and is robust under various object mobility patterns.
Runtime measurements in the cloud

One of the main reasons why cloud computing has gained so much popularity is due to its ease of use and its ability to scale computing resources on demand. As a result, users can now rent computing nodes on large commercial clusters through several vendors, such as Amazon and rackspace. However, despite the attention paid by Cloud providers, performance unpredictability is a major issue in Cloud computing for (1) database researchers performing wall clock experiments, and (2) database applications providing service-level agreements. In this paper, we carry out a study of the performance variance of the most widely used Cloud infrastructure (Amazon EC2) from different perspectives. We use established microbenchmarks to measure performance variance in CPU, I/O, and network. And, we use a multi-node MapReduce application to quantify the impact on real dataintensive applications. We collected data for an entire month and compare it with the results obtained on a local cluster. Our results show that EC2 performance varies a lot and often falls into two bands having a large performance gap in-between --- which is somewhat surprising. We observe in our experiments that these two bands correspond to the different virtual system types provided by Amazon. Moreover, we analyze results considering different availability zones, points in time, and locations. This analysis indicates that, among others, the choice of availability zone also influences the performance variability. A major conclusion of our work is that the variance on EC2 is currently so high that wall clock experiments may only be performed with considerable care. To this end, we provide some hints to users.