Miracle-dz/UniFAR-FTUs huggingface dataset:
Complete answer aggregates for treelike databases: a novel approach to combine querying and navigation

The use of markup languages like SGML, HTML or XML for encoding the strucutre of documents or linguistic data has lead to many databases where entries are adequately described as trees. In this context querying formalisms are interesting that offer the possiblity to refer both to textual content and logical structure. We consider models where the strucutre specified in a query is not only used as a filter, but also for selecting and presenting different parts of the data. If answers are formalized as mapping from query nodes to the database, a simple enumeration of all mappings in the answer set will often suffer from the effect that many answers have common subparts. From a theoretical point of view this may lead to an exponential time complexity of the computation and presentation of all answers. Concentration on the language of so called tree queries—a variant and extension of Kilpeläinen's Tree Matching formalism—we introduce the notion of a “complete answer aggregate” for a given query. This new data strucutre offers a compact view of the set of all answer and supports active exploration of the ansewer space. Since complete answer aggregates use a powerful structure-sharing mechanism their maximal size is of order &sgr;(<italic>d•h•q</italic>) where <italic>d</italic> and <italic>q</italic> respectively denote the size of the database and the query, and <italic>h</italic> is the maximal depth of a path of the database. An algorithm is given that computes a complete answer aggregate for a given treee query in time &sgr;(<italic>d</italic>•log(<italic>d)•h•</italic>). For the sublanguage of so-called rigid tree queries, as well as for so-called “nonrecursive” databases, an improved bound of :&sgr;(<italic>d</iltalic>•log(<italic>d)•q</italic>) is obtained. The algorithm is based on a specific index structure that supports practical efficiency.
An Eulerian-Lagrangian Approach For Large Deformation Fluid StructureInteraction Problems, Part 1 : Algorithm Development

A numerical algorithm for tightly coupled, high-deformation fluid-structure interaction problems is presented. The foundation of the method is the integration of a Lagrangian particle technique (the Material Point Method, or MPM) with a multimaterial Eulerian code. In this approach, each material is described and evolves in its preferred reference frame (e.g., Lagrangian for solids, Eulerian for fluids). The MPM uses a background mesh to update particle states. By using the Eulerian multi-material mesh as the background mesh to update particle states, the solid materials have a dual representation in the Lagrangian and Eulerian frame. It is in this common reference frame that coupling interactions among materials are computed through momentum and energy exchange terms in the multi-field equations. The approach is outlined and results from a numerical order-of-accuracy study are presented. Simulation results are compared with known solutions for the stress distribution in a pressurized cylinder. It is shown that the combined approach has the same order-of accuracy as the stand-alone material point method and gives excellent agreement with exact solutions for this geometry.
Lehr-und Forschungseinheit Für Programmier-und Modellierungssprachen Machine Learning in the Phase Transition Framework

We investigate k-term DNF learning, the task of inducing a propositional DNF formula with at most k terms from a set of positive and negative examples. Though k-term DNF learning is NP-complete, it is at the core of most propositional learning algorithms. The main aim of this thesis is to evaluate stochastic local search algorithms to solve hard k-term DNF learning tasks. As a reference we first design and evaluate a range of systematic search algorithms for the problem. Using those algorithms we can separate soluble from insoluble problem instances and then analyze the problem's average search complexity using the Phase Transition framework. We examine the region of hard problem instances, the so called phase transition, and show that location and extent of this region can be predicted by an equation derived from statistical mechanics. We then evaluate existing stochastic local search algorithms on the hard problem instances from the phase transition region. Our experiments indicate that WalkSAT is able to solve the largest fraction of hard problem instances. Finally, we design and evaluate a range of stochastic local search algorithms searching through the two possible search spaces for k-term DNF learning. A speed-optimized version of a WalkSAT-like search in formula space is able to find solutions to the king-rook-king chess endgame benchmark , which are more compact than the solutions found by a propositional version of the rule learning algorithm FOIL.
Assessment of carotid plaque composition in hypertensive patients by ultrasonic tissue characterization: a validation study

Objective Ultrasonic tissue characterization of epi-aortic vessels may be useful to define the composition of atherosclerotic plaques. Videodensitometry provides a histogram representing the frequency distribution of gray levels corresponding to different compositions of the carotid wall. However, lack of standardization limits the clinical application of this technique. In the present study, the echoreflectivity (ER) pattern of atherosclerotic plaques in vivo was compared with their histological pattern after surgical removal, and the reproducibility of measurement was tested. Design and methods We studied 19 hypertensive patients with a carotid artery stenosis ⩾ 70%, eligible for carotid thromboendarterectomy (TEA). Before TEA, all patients underwent standard high-resolution B-mode carotid ultrasound. ER parameters (mean gray level, broad band, skewness, and kurtosis) were obtained in a region of interest selected along the whole plaque, between the intima–blood and the media–adventitia interfaces. The plaques removed during TEA were examined by a histologist and classified into three groups on the basis of fibrous tissue (FT) content: lipidic (FT < 20%), fibrolipidic (20 ⩽ FT ⩽ 50%), and fibrous (FT > 50%). Discriminant function analysis was used to evaluate classification efficacy of different histological groups based on ER parameters. Results Histologically, five lesions were classified as lipidic, six as fibrolipidic and eight as fibrous. Analysis of variance showed significant between group differences in all ER parameters. The combined use of all ER parameters provided correct classification of plaques in 94.73% of cases (P < 0.0001), improving the classification made using single parameters. Intra-observer and inter-observer variabilities (Bland–Altman method) of mean gray level measurements were small. Conclusions Videodensitometry can discriminate between tissue composition of carotid lesions and complement the quantitative assessment of intima–media thickness by additionally providing a well-reproducible semiquantitative evaluation of vascular wall constituents.
A novel ligand bound ABC transporter, LolCDE, provides insights into the molecular mechanisms underlying membrane detachment of bacterial lipoproteins

The LolCDE complex of Escherichia coli belongs to the ABC transporter superfamily and initiates the lipoprotein sorting to the outer membrane by catalysing their release from the inner membrane. LolC and/or LolE, membrane subunits, recognize lipoproteins anchored to the outer surface of the inner membrane, while LolD hydrolyses ATP on its inner surface. We report here that ligand‐bound LolCDE can be purified from the inner membrane in the absence of ATP. Liganded LolCDE represents an intermediate of the release reaction and exhibits higher affinity for ATP than the unliganded form. ATP binding to LolD weakens the interaction between LolCDE and lipoproteins and causes their dissociation in a detergent solution, while lipoprotein release from membranes requires ATP hydrolysis. Liganded LolCDE thus reveals molecular events brought about through ATP binding and hydrolysis. LolCDE is the first example of an ABC transporter purified with tightly bound native substrates. A single molecule of lipoprotein is found to bind per molecule of the LolCDE complex.
Curvature Interpolation Method for Image Zooming

We introduce a novel image zooming algorithm, called the curvature interpolation method (CIM), which is partial-differential-equation (PDE)-based and easy to implement. In order to minimize artifacts arising in image interpolation such as image blur and the checkerboard effect, the CIM first evaluates the curvature of the low-resolution image. After interpolating the curvature to the high-resolution image domain, the CIM constructs the high-resolution image by solving a linearized curvature equation, incorporating the interpolated curvature as an explicit driving force. It has been numerically verified that the new zooming method can produce clear images of sharp edges which are already denoised and superior to those obtained from linear methods and PDE-based methods of no curvature information. Various results are given to prove effectiveness and reliability of the new method.
Hemoprotein Bach1 regulates enhancer availability of heme oxygenase‐1 gene

Heme oxygenase‐1 (HO‐1) protects cells from various insults including oxidative stress. Transcriptional activators, including the Nrf2/Maf heterodimer, have been the focus of studies on the inducible expression of ho‐1. Here we show that a heme‐binding factor, Bach1, is a critical physiological repressor of ho‐1. Bach1 bound to the multiple Maf recognition elements (MAREs) of ho‐1 enhancers with MafK in vitro and repressed their activity in vivo, while heme abrogated this repressor function of Bach1 by inhibiting its binding to the ho‐1 enhancers. Gene targeting experiments in mice revealed that, in the absence of Bach1, ho‐1 became expressed constitutively at high levels in various tissues under normal physiological conditions. By analyzing bach1/nrf2 compound‐deficient mice, we documented antagonistic activities of Bach1 and Nrf2 in several tissues. Chromatin immunoprecipitation revealed that small Maf proteins participate in both repression and activation of ho‐1. Thus, regulation of ho‐1 involves a direct sensing of heme levels by Bach1 (by analogy to lac repressor sensitivity to lactose), generating a simple feedback loop whereby the substrate effects repressor–activator antagonism.
Identification of a Putative Network of Actin-Associated Cytoskeletal Proteins in Glomerular Podocytes Defined by Co-Purified mRNAs

The glomerular podocyte is a highly specialized and polarized kidney cell type that contains major processes and foot processes that extend from the cell body. Foot processes from adjacent podocytes form interdigitations with those of adjacent cells, thereby creating an essential intercellular junctional domain of the renal filtration barrier known as the slit diaphragm. Interesting parallels have been drawn between the slit diaphragm and other sites of cell-cell contact by polarized cells. Notably mutations in several genes encoding proteins localized to the foot processes can lead to proteinuria and kidney failure. Mutations in the Wilm's tumor gene (WT1) can also lead to kidney disease and one isoform of WT1, WT1(+KTS), has been proposed to regulate gene expression post-transcriptionally. We originally sought to identify mRNAs associated with WT1(+KTS) through an RNA immunoprecipitation and microarray approach, hypothesizing that the proteins encoded by these mRNAs might be important for podocyte morphology and function. We identified a subset of mRNAs that were remarkably enriched for transcripts encoding actin-binding proteins and other cytoskeletal proteins including several that are localized at or near the slit diaphragm. Interestingly, these mRNAs included those of α-actinin-4 and non-muscle myosin IIA that are mutated in genetic forms of kidney disease. However, isolation of the mRNAs occurred independently of the expression of WT1, suggesting that the identified mRNAs were serendipitously co-purified on the basis of co-association in a common subcellular fraction. Mass spectroscopy revealed that other components of the actin cytoskeleton co-purified with these mRNAs, namely actin, tubulin, and elongation factor 1α. We propose that these mRNAs encode a number of proteins that comprise a highly specialized protein interactome underlying the slit diaphragm. Collectively, these gene products and their interactions may prove to be important for the structural integrity of the actin cytoskeleton in podocytes as well as other polarized cell types.
Information Design, Bayesian Persuasion and Bayes Correlated Equilibrium

A set of players have preferences over a set of outcomes. We consider the problem of an "information designer" who can choose an information structure for the players to serve his ends, but has no ability to change the mechanism (or force the players to make particular action choices). We describe a unifying perspective for information design. We consider a simple example of Bayesian persuasion with both an uninformed and informed receiver. We extend information design to many players and relate it to the literature on incomplete information correlated equilibrium.
Pacific Asia Conference on Information Systems ( PACIS ) 2014 THE EFFECTS OF PUSH-PULL-MOORING ON THE SWITCHING MODEL FOR SOCIAL NETWORK SITES MIGRATION Avus

Although the number of users has been growing exponentially in SNSs, some SNSs are facing a financial crisis and might be shut down in the near future. Therefore, understand users' incentives to switch to another SNS has great influence on operators' business performance. The study extended "Push-Pull-Mooring" migratory theory to explain the switching behaviors of users in SNS. Structural equation modeling will applied to analyze data collected from a filed survey. The result can construct a solid switching framework and help operators to understand their customer better.
9-Nitrocamptothecin liposome aerosol treatment of melanoma and osteosarcoma lung metastases in mice.

The response rates of relapsed osteosarcoma and melanoma pulmonary metastases to traditional i.v. chemotherapeutic regimens have been disappointing. Direct drug delivery of chemotherapy to the lungs could increase the drug concentration in the tumor area and may offer a new therapeutic approach for these patients. Previous studies demonstrated that drugs delivered to the respiratory tract in liposomal formulation resulted in high pulmonary drug concentration, reduced systemic toxicity, and reduced dosage requirements compared with parenteral and oral administration. To determine whether this approach has utility against pulmonary metastases, the efficacy of aerosol therapy with liposome-encapsulated 9-nitrocamptothecin (L-9NC) was determined using two different experimental lung metastasis models. C57BL/6 mice were treated the day after the i.v. injection of B16 melanoma cells with aerosol L-9NC for 1 h (153 microg 9-nitrocamptothecin/kg) for 5 days per week for up to 3 weeks. Aerosol L-9NC treatment resulted in a reduction in lung weights (P = 0.005) and number of tumor foci (P < 0.001). Visible tumor nodules were fewer and smaller in the 9-nitrocamptothecin-treated group than in untreated control mice (P < 0.001). Using a newly developed human osteosarcoma experimental metastasis model in nude mice, we demonstrated that aerosol L-9NC was also effective against established lung metastases. Aerosol therapy initiated on the ninth week after i.v. tumor injection and continued for 8 or 10 weeks produced highly significant reductions in the number of animals with both visible and microscopic disease (P < 0.02), the total number of tumor foci in the lungs (P < 0.005), and the size of the individual tumor nodules (P < 0.02). These data suggest that L-9NC aerosol therapy may offer significant advantage over existing methods in the treatment of melanoma and osteosarcoma pulmonary metastases.
Structural design composition for C++ hardware models

This paper addresses the modeling of layout structure in high level C++ models. Researchers agree that the level of abstraction for integrated circuit design needs to be raised. New languages and methodologies are being proposed, most of them from the software engineering domain. However one of the fundamental hardware design challenges is often overlooked as push button synthesis solutions are sought: physical design predictability. In this paper we describe how C++ constructs should be used to capture structural and physical implementation concerns. Our explanation relies on the importance of the floorplan and component placement estimations at high levels of abstraction. We highlight how using object oriented mechanisms eases the structural modeling of circuit components, and we present a C++ class library design to specify these structural concerns.
The relationship of motivation and multiple intelligence preference to achievement from instruction using webquests

Finding teaching models and strategies that benefit learners while incorporating skills students will need in the future, such as using technology, is important. This study examined the problem of whether Webquests, an inquiry-based teaching strategy where much of the information is found online, are a beneficial way to integrate technology into the curriculum for all learners. The purpose of this study was to further knowledge about the Webquest model and the use of Webquests with students of different ability levels and multiple intelligence preferences. The Attention, Relevance, Confidence, and Satisfaction (ARCS) model of motivational design; the self-determination theory; and multiple intelligences theory comprised the theoretical bases of this study. A concurrent triangulation design of mixed methods research was used to gather quantitative data including pretest-posttest scores, a motivation survey, and the Multiple Intelligences Development Assessment Survey (MIDAS-KIDS). Qualitative data gathered included daily learning logs, rubrics from the final Webquest project, researcher observations, and participant interviews. SPSS software was used to test for correlations between achievement, ability, multiple intelligences, and motivation. The key findings of this study showed that only the gifted and average ability groups had significant gains from the Webquest instruction. No correlation was found between multiple intelligences preference and achievement or motivation. In addition, no ability group was significantly more motivated by the Webquest instruction than another. Results showed that the Webquest was useful form of instruction for gifted and average students, but was not as useful for at-risk learners, who have learning needs that were not met by the Webquest instruction. From this research, positive social change could result if teachers make changes in Webquests to better support the needs of at-risk learners.
Progression in patients with low- and intermediate-1-risk del(5q) myelodysplastic syndromes is predicted by a limited subset of mutations

A high proportion of patients with lower-risk del(5q) myelodysplastic syndromes will respond to treatment with lenalidomide. The median duration of transfusion-independence is 2 years with some long-lasting responses, but almost 40% of patients progress to acute leukemia by 5 years after starting treatment. The mechanisms underlying disease progression other than the well-established finding of small TP53-mutated subclones at diagnosis remain unclear. We studied a longitudinal cohort of 35 low- and intermediate-1-risk del(5q) patients treated with lenalidomide (n=22) or not (n=13) by flow cytometric surveillance of hematopoietic stem and progenitor cell subsets, targeted sequencing of mutational patterns, and changes in the bone marrow microenvironment. All 13 patients with disease progression were identified by a limited number of mutations in TP53, RUNX1, and TET2, respectively, with PTPN11 and SF3B1 occurring in one patient each. TP53 mutations were found in seven of nine patients who developed acute leukemia, and were documented to be present in the earliest sample (n=1) and acquired during lenalidomide treatment (n=6). By contrast, analysis of the microenvironment, and of hematopoietic stem and progenitor cells by flow cytometry was of limited prognostic value. Based on our data, we advocate conducting a prospective study aimed at investigating, in a larger number of cases of del(5q) myelodysplastic syndromes, whether the detection of such mutations before and after lenalidomide treatment can guide clinical decision-making.
High Frame-Rate, High Resolution Ultrasound Imaging With Multi-Line Transmission and Filtered-Delay Multiply And Sum Beamforming

Multi-Line Transmission (MLT) was recently demonstrated as a valuable tool to increase the frame rate of ultrasound images. In this approach, the multiple beams that are simultaneously transmitted may determine cross-talk artifacts that are typically reduced, although not eliminated, by the use of Tukey apodization on both transmission and reception apertures, which unfortunately worsens the image lateral resolution. In this paper we investigate the combination, and related performance, of Filtered-Delay Multiply And Sum (F-DMAS) beamforming with MLT for high frame-rate ultrasound imaging. F-DMAS is a non-linear beamformer based on the computation of the receive aperture spatial autocorrelation, which was recently proposed for use in ultrasound B-mode imaging by some of the authors. The main advantages of such beamformer are the improved contrast resolution, obtained by lowering the beam side lobes and narrowing the main lobe, and the increased noise rejection. This study shows that in MLT images, compared to standard Delay And Sum (DAS) beamforming including Tukey apodization, F-DMAS beamforming yields better suppression of cross-talk and improved lateral resolution. The method's effectiveness is demonstrated by simulations and phantom experiments. Preliminary in vivo cardiac images also show that the frame rate can be improved up to 8-fold by combining F-DMAS and MLT without affecting the image quality.
An Intelligent Approach to Software Cost Prediction

Good software cost prediction is important for effective project management such as budgeting, project planning and control. In this paper, we present an intelligent approach to software cost prediction. By integrating the neuro-fuzzy technique with the well-accepted COCOMO model, our approach can make the best use of both expert knowledge and historical project data. Its major advantages include learning ability, good interpretability, and robustness to imprecise and uncertain inputs. The validation using industry project data shows that the model greatly improves prediction accuracy in comparison with the COCOMO model.