Miracle-dz/UniFAR-FTUs huggingface dataset:
Digital Watermarking in Discrete Wavelet Transformation - Survey

In the early days, encryption and control access techniques were used to protect the ownership of media. Recently, the watermark techniques are utilized to keep the copyright of media. Digital watermarking, a concept of embedding a special pattern, uses an algorithm of inserting a watermark to protect the copyright of media. It has recently become important in various application areas. The various of watermark techniques have been proposed by many authors in the last several years. However, there are not enough analysis and comparison on the previous researches. In this paper, for the understanding of the previous works and for the future related research, we try to classify and analyze the conventional watermark techniques from the various points of view. Currently watermark techniques based on the transfer domain, are more popular than those of the spatial domain. DCTbased methods have been most widely used among the transform based methods. However, recently wavelet based watermark techniques are becoming main research topic. With wide use of internet, effective audio and video watermarking researches are also required.
New pseudorandom sequences constructed by quadratic residues and Lehmer numbers

Let p be an odd prime. Define e n ={(-1) n+n , if n is a quadratic residue mod p, (-1) n+n+1 , if n is a quadratic nonresidue mod p, where n is the multiplicative inverse of n modulo p such that 1 < n < p - 1. This paper shows that the sequence {e n ) is a "good" pseudorandom sequence, by using the properties of exponential sums, character sums, Kloosterman sums and mean value theorems of Dirichlet L-functions.
Comparison of traditional and molecular methods of typing isolates of Staphylococcus aureus

Fifty-nine Staphylococcus aureus isolates and 1 isolate of Staphylococcus intermedius were typed by investigators at eight institutions by using either antibiograms, bacteriophage typing, biotyping, immunoblotting, insertion sequence typing with IS257/431, multilocus enzyme electrophoresis, restriction analysis of plasmid DNA, pulsed-field or field inversion gel electrophoresis, restriction analysis of PCR-amplified coagulase gene sequences, restriction fragment length polymorphism typing by using four staphylococcal genes as probes, or ribotyping. Isolates from four well-characterized outbreaks (n = 29) and a collection of organisms from two nursing homes were mixed with epidemiologically unrelated stock strains from the Centers for Disease Control and Prevention. Several isolates were included multiple times either within or between the sets of isolates to analyze the reproducibilities of the typing systems. Overall, the DNA-based techniques and immunoblotting were most effective in grouping outbreak-related strains, recognizing 27 to 29 of the 29 outbreak-related strains; however, they also tended to include 3 to 8 epidemiologically unrelated isolates in the same strain type. Restriction fragment length polymorphism methods with mec gene-associated loci were less useful than other techniques for typing oxacillin-susceptible isolates. Phage typing, plasmid DNA restriction analysis, and antibiogram analysis, the techniques most readily available to clinical laboratories, identified 23 to 26 of 29 outbreak-related isolates and assigned 0 to 6 unrelated isolates to outbreak strain types. No single technique was clearly superior to the others; however, biotyping, because it produced so many subtypes, did not effectively group outbreak-related strains of S. aureus.
Homozygous and heterozygous expression of a novel IGF-I mutation 6

1 Departments of Pediatrics, 2 Department of Endocrinology and Metabolism, 3Center for Human and Clinical Genetics, 8Department of Cardiology, 9 Department of Audiology Leiden University Medical Center, Leiden, The Netherlands 4 Department of Metabolic and Endocrine diseases, University Medical Center Utrecht, Utrecht, The Netherlands 5 Medical Research Laboratories and Medical Department, Aarhus University Hospital, Aarhus, Denmark 6 Department of Medicine, Biochemistry and Physiology, Loma Linda University, Loma Linda, CA, United States 7 Department of Molecular and Biomedical Science, University of Adelaide, Australia
Document Level Time-anchoring for TimeLine Extraction

This paper investigates the contribution of document level processing of timeanchors for TimeLine event extraction. We developed and tested two different systems. The first one is a baseline system that captures explicit time-anchors. The second one extends the baseline system by also capturing implicit time relations. We have evaluated both approaches in the SemEval 2015 task 4 TimeLine: CrossDocument Event Ordering. We empirically demonstrate that the document-based approach obtains a much more complete time anchoring. Moreover, this approach almost doubles the performance of the systems that participated in the task.
Supportive Alignments & Teams in Group Supervision for School Counselors-in-Training

This thesis focuses on the formation of supportive alignments and interactional teams through particular linguistic strategies within the group supervision classroom, especially as participants provide one another with feedback on their professional behaviors. Through discourse analysis of transcripts of a video-recorded group supervision meeting, I illustrate how graduate level school counselors-in-training use language to construct alignments and teams. Discursive features that are identified and explicated include positive assessments of others, repetition, co-narration, constructed dialogue, and matching. In investigating these particular linguistic strategies, I emphasize how some of the major goals of group supervision (including feedback and reflection) are discursively expressed and reinforced amongst the school counselors-in-training. SUPPORTIVE ALIGNMENTS & TEAMS IN GROUP SUPERVISION FOR SCHOOL COUNSELORS-IN-TRAINING
Efficient exact and heuristic minimization of hazard-free logic

In this paper we consider the problem of finding minimum and minimal sum of product circuits (PLAs) that correctly implement a given set of transitions without any hazards. In earlier work we introduced an efficient divide and conquer algorithm, the threeway method, that is capable of finding a minimum PLA-implementation for single output functions. We showed that this method was 10 times faster than the exact method proposed by Dill/Nowick. In this paper we extend the threeway method such that it can deal with multiple output functions. We compare the enhanced threeway method again with Dill/Nowick's method. We also propose an efficient heuristic method, derived from the threeway method, that is capable of finding minimal implementations of specifications that cannot be minimized by the exact methods.
Ownership Structure and the Strategic Decision Process: A Comparative Case Study

The article investigates the relationship between ownership structure and the role played by the board of directors in the strategic decision process. A comparative case study of strategic decision processes indicates that ownership concentration, the nature of shareholders' interests and the distribution of relevant knowledge affect the key functions performed by the board of directors, the involvement of the board in the different phases of the strategic decision process, and the most adopted decision mechanisms. Key Words: board of directors, decision making, strategy formulation, politics, ownership structure
Efficient prioritized inverse kinematic solutions for redundant manipulators

In this paper, we explore preprocessing techniques aimed at efficiently mapping the workspace to the configuration space for redundant manipulators. Exploiting the increasing availability of memory we precompute a database for online use that allows fast querying of joint configurations with high manipulability. Such a system is useful for performing reaching and manipulation tasks, online force control, and quickly computing goal configurations for path planning algorithms. We have implemented a prototype system on the digital human version humanoid robot platform 2 (DH-HRP2) which we use to efficiently compute arm inverse kinematic solutions. We demonstrate the benefits of such a system applied to converting workspace trajectories to configuration space trajectories. Although we have applied the technique to finding joint configurations with high manipulability, our approach can be generalized to a variety of different priority measures that may be used for evaluating inverse kinematic solutions for redundant manipulators.
A multicriteria failure mode and effects analysis approach for optimizing human safety

The human operator as the basic postulate of events appearance of catastrophes and failures; however issuing finders of diverse currents have to apply different methods to minimize risks of human errors, some have used combined methods taking counts him personals factors and engineering, others himself are supported on estimations probabilities to calculate trials of workers. Moreover, it is through this synergy that members can achieve better results than they could achieve individually. For all these reasons, many research works have been undertaken to improve the functioning and performance groups in solving a decision problem.
Discrete Serotonin Systems Mediate Memory Enhancement and Escape Latencies after Unpredicted Aversive Experience in Drosophila Place Memory

Feedback mechanisms in operant learning are critical for animals to increase reward or reduce punishment. However, not all conditions have a behavior that can readily resolve an event. Animals must then try out different behaviors to better their situation through outcome learning. This form of learning allows for novel solutions and with positive experience can lead to unexpected behavioral routines. Learned helplessness, as a type of outcome learning, manifests in part as increases in escape latency in the face of repeated unpredicted shocks. Little is known about the mechanisms of outcome learning. When fruit fly Drosophila melanogaster are exposed to unpredicted high temperatures in a place learning paradigm, flies both increase escape latencies and have a higher memory when given control of a place/temperature contingency. Here we describe discrete serotonin neuronal circuits that mediate aversive reinforcement, escape latencies, and memory levels after place learning in the presence and absence of unexpected aversive events. The results show that two features of learned helplessness depend on the same modulatory system as aversive reinforcement. Moreover, changes in aversive reinforcement and escape latency depend on local neural circuit modulation, while memory enhancement requires larger modulation of multiple behavioral control circuits.
Generating hand motion from body motion using key hand poses

In this paper, we propose a method to generate hand motion from full-body motion. We assume that hand pose can be estimated from full-body pose. We use a support vector machine (SVM) to choose one of four key hand poses based on the full-body pose. The training model is constructed from a number of full-body motions with manually specified hand-pose keyframes. The output pose is synthesized to include the generated continuous hand motion. Since our method does not require future poses, it is valid for both on-line and off-line animation. Our experimental results show that our model is applicable to a wide range of motions.
Intelligent Data Analysis to Model and Understand Live Cell Time-lapse Sequences

Summary Background: One important aspect of cellular function, which is at the basis of tissue homeostasis, is the delivery of proteins to their correct destinations. Significant advances in live cell microscopy have allowed tracking of these pathways by following the dynamics of fluorescently labelled proteins in living cells. Objectives: This paper explores intelligent data analysis techniques to model the dynamic behavior of proteins in living cells as well as to classify different experimental conditions. Methods: We use a combination of decision tree classification and hidden Markov models. In particular, we introduce a novel approach to “align” hidden Markov models so that hidden states from different models can be cross-compared. Results: Our models capture the dynamics of two experimental conditions accurately with a stable hidden state for control data and multiple (less stable) states for the experimental data recapitulating the behaviour of particle trajectories within live cell time-lapse data. Conclusions: In addition to having successfully developed an automated framework for the classification of protein transport dynamics from live cell time-lapse data our model allows us to understand the dynamics of a complex trafficking pathway in living cells in culture.
Gene Expression Profiles Obtained from Fine-Needle Aspirations of Breast Cancer Reliably Identify Routine Prognostic Markers and Reveal Large-Scale Molecular Differences between Estrogen-negative and Estrogen-positive Tumors 1

Purpose: The purpose of this study was to determine whether comprehensive transcriptional profiles (TPs) can be obtained from single-passage fine-needle aspirations (FNAs) of breast cancer and to explore whether profiles capture routine clinicopathological parameters. Experimental Design: Expression profiles were available on 38 patients with stage I-III breast cancer who underwent FNA at the time of diagnosis. [P]dCTP-labeled cDNA probes were generated and hybridized to cDNA membrane microarrays that contained 30,000 human sequence clones, including 10,890 expressed sequence tags. Results: The median total RNA yield from the biopsies was 2 g (range, 1–25 g). The cellular composition of each biopsy was examined and, on average,, 79% of the cells were cancer cells. TP was successfully performed on all 38 of the biopsies. Unsupervised complete-linkage hierarchical clustering with all of the biopsies revealed an association between estrogen receptor (ER) status and gene expression profiles. There was a strong correlation between ER status determined by TP and measured by routine immunohistochemistry (P 0.001). A similar strong correlation was seen with HER-2 status determined by fluorescent in situ hybridization (P 0.0002). Using the first 18 cases as the discovery set, we established a cutoff of 2.0 and 18.0 for ER and HER-2 mRNA levels, respectively, to distinguish clinically-negative from -positive cases. We also identified 105 genes (excluding the ER gene) the expression of which correlated highly with clinical ER status. Twenty tumors were used for prospective validation. HER-2 status was correctly identified in all 20 of the cases, based on HER-2 mRNA content detected by TP. ER status was correctly identified in 19 of 20 cases. When the marker set of 105 genes was used to prospectively predict ER status, TP-based classification correctly identified 9 of 10 of the ER-positive and 7 of 10 of the ER-negative tumors. We also explored supervised cluster analysis using various functional categories of genes, and we observed a clear separation between ER-negative and ER-positive tumors when genes involved in signal transduction were used for clustering. Conclusions: These results demonstrate that comprehensive TP can be performed on FNA biopsies. TPs reliably measure conventional single-gene prognostic markers such as ER and HER-2. A complex pattern of genes (not including ER) can also be used to predict clinical ER status. These results demonstrate that needle biopsy-based diagnostic microarray tests may be developed that could capture conventional prognostic information but may also contain additional clinical information that cannot currently be measured with other methods.
The Control Basis APIA Layered Software Architecture for Autonomous Robot Learning

Software tools for programming autonomous systems that are embedded in unstructured environments are increasingly important in robotics. We introduce a layered software architecture designed to facilitate the construction of hierarchical models for adaptive control programs that are learned and that can be transferred to related contexts and new robots. We focus on the interface between a robot’s sensory and motor resources and processes that learn autonomously by exploring effects of the robot’s actions. We provide an implementation of this interface called the Control Basis Application Programming Interface (CBAPI) that is designed to create hierarchical behavior and implicit knowledge out of closed-loop control primitives. The CBAPI provides a natural combinatorial means of building closed-loop controllers by combining sensory and motor resources. By so doing, it supports a variety of techniques for structuring stochastic exploration and interactive machine learning. Moreover, it provides for a natural implicit knowledge representation. We believe that the CBAPI represents a programming interface for adaptive control programs that advances the state-of-the-art in robotic software environments.
Routing Symmetric Demands in Directed Minor-Free Graphs with Constant Congestion

The problem of routing in graphs using node-disjoint paths has received a lot of attention and a polylogarithmic approximation algorithm with constant congestion is known for undirected graphs [Chuzhoy and Li 2016] and [Chekuri and Ene 2013]. However, the problem is hard to approximate within polynomial factors on directed graphs, for any constant congestion [Chuzhoy, Kim and Li 2016]. Recently, [Chekuri, Ene and Pilipczuk 2016] have obtained a polylogarithmic approximation with constant congestion on directed planar graphs, for the special case of symmetric demands. We extend their result by obtaining a polylogarithmic approximation with constant congestion on arbitrary directed minor-free graphs, for the case of symmetric demands.
Structural and functional properties of V156K and A158E mutants of apolipoprotein A-I in the lipid-free and lipid-bound states Published, JLR Papers in Press, February 16, 2005. DOI 10.1194/jlr.M400468-JLR200

Val156 of apolipoprotein A-I (apoA-I) was found to be a key amino acid in the structure and function of high density lipoprotein (HDL) (J. Biol. Chem., 275: 26821–26827, 2000). To determine more precisely the functions of the individual amino acids proximal to Val156, serial point mutants of proapoA-I, including V156K, D157K, and A158E, were overexpressed and purified to at least 95% purity. In the lipid-free state, A158E exhibited the most profound self-associative patterns and the least pronounced dimyristoyl phosphatidylcholine (DMPC) clearance activities. In the lipid-bound state, A158E formed a larger reconstituted HDL (rHDL) with palmitoyloleoyl phosphatidylcholine (POPC), ∼120 Å, whereas other mutants and the wild type (WT) formed 97 Å of POPC-rHDL. Cross-linking analysis revealed that A158E-rHDL harbored at least four protein molecules in the particle, while other rHDL conformations contained only two protein molecules. All of the POPC-rHDL produced smaller HDL, around 78 Å, after 24 h of incubation in the presence of low density lipoprotein at 37°C. V156K and A158E exhibited decreased lecithin:cholesterol acyltransferase activation activity in the POPC-rHDL state, showing <2% of WT reactivity (apparent Vmax/Km). A158E also displayed markedly different properties in secondary structure, and its accessibility to proteolytic enzymes is different. These results suggest that the two amino acids in helix 6, Val156 and Ala158, are critical to both the structure and function of rHDL.
A MODEL OF GROUP TECHNOLOGY ACCEPTANCE: SOME PRELIMINARY FINDINGS

While the literature on the technology acceptance model and its extensions have contributed significantly to our understanding of how individuals accept a technology, little is known about how groups accept technology. Since organizations are moving to collective structures such as groups that are provided with technologies for performing tasks, it is critical to understand how they accept and use technology so as to better guide organizations’ investments and implementation decisions. Drawing on theories of group influence, and prior research on group communication media and conflict, the paper proposes an input-process-output (I-P-O) model for conceptualizing group technology acceptance. We also present some preliminary empirical results that appear to support key aspects of the model.
Angiogenesis-Related Cytokines, RANKL, and Osteoprotegerin in Multiple Myeloma Patients in relation to Clinical Features and Response to Treatment

An essential cytokine system for the osteoclast biology in multiple myeloma (MM) consists of the receptor of activator of NF-κB ligand (RANKL), its receptor (RANK), and the soluble decoy receptor, osteoprotegerin (OPG). Myeloma cells cause imbalance in OPG/RANKL interactions. We measured serum levels of OPG, soluble (s) RANKL, sRANKL/OPG ratio, markers of disease activity [LDH, CRP, interleukin-6 (IL-6), β2-microglobulin (B2M)], and angiogenic factors [hepatocyte growth factor (HGF), vascular endothelial growth factor (VEGF)], in 54 newly diagnosed MM patients and in 25 of them in plateau phase. All the above values were higher in MM patients compared to controls and decreased in plateau phase. sRANKL and RANKL/OPG were higher with advancing disease stage and skeletal grade. Significant correlations were found among RANKL and RANKL/OPG with HGF, LDH, VEGF, IL-6, and B2M. In conclusion, RANKL and OPG play significant roles in MM pathophysiology, as regulators of bone turnover and mediators of angiogenesis.
Robust multi-sensor image alignment

This paper presents a method for alignment of images acquired by sensors of different modalities (e.g., EO and IR). The paper has two main contributions: (i) It identifies an appropriate image representation, for multi-sensor alignment, i.e., a representation which emphasizes the common information between the two multi-sensor images, suppresses the non-common information, and is adequate for coarse-to-fine processing. (ii) It presents a new alignment technique which applies global estimation to any choice of a local similarity measure. In particular, it is shown that when this registration technique is applied to the chosen image representation with a local normalized-correlation similarity measure, it provides a new multi-sensor alignment algorithm which is robust to outliers, and applies to a wide variety of globally complex brightness transformations between the two images. Our proposed image representation does not rely on sparse image features (e.g., edge, contour, or point features). It is continuous and does not eliminate the detailed variations within local image regions. Our method naturally extends to coarse-to-fine processing, and applies even in situations when the multi-sensor signals are globally characterized by low statistical correlation.
Using subcategorization frames to improve French probabilistic parsing

This article introduces results about probabilistic parsing enhanced with a word clustering approach based on a French syntactic lexicon, the Lefff. We show that by applying this clustering method on verbs and adjectives of the French Treebank, we obtain accurate performances on French with a parser based on a Probabilistic Context-Free Grammar.