Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of Functional Networks of Estrogen- and c-Myc-Responsive Genes and Their Relationship to Response to Tamoxifen Therapy in Breast Cancer

Background Estrogen is a pivotal regulator of cell proliferation in the normal breast and breast cancer. Endocrine therapies targeting the estrogen receptor are effective in breast cancer, but their success is limited by intrinsic and acquired resistance. Methodology/Principal Findings With the goal of gaining mechanistic insights into estrogen action and endocrine resistance, we classified estrogen-regulated genes by function, and determined the relationship between functionally-related genesets and the response to tamoxifen in breast cancer patients. Estrogen-responsive genes were identified by transcript profiling of MCF-7 breast cancer cells. Pathway analysis based on functional annotation of these estrogen-regulated genes identified gene signatures with known or predicted roles in cell cycle control, cell growth (i.e. ribosome biogenesis and protein synthesis), cell death/survival signaling and transcriptional regulation. Since inducible expression of c-Myc in antiestrogen-arrested cells can recapitulate many of the effects of estrogen on molecular endpoints related to cell cycle progression, the estrogen-regulated genes that were also targets of c-Myc were identified using cells inducibly expressing c-Myc. Selected genes classified as estrogen and c-Myc targets displayed similar levels of regulation by estrogen and c-Myc and were not estrogen-regulated in the presence of siMyc. Genes regulated by c-Myc accounted for 50% of all acutely estrogen-regulated genes but comprised 85% (110/129 genes) in the cell growth signature. siRNA-mediated inhibition of c-Myc induction impaired estrogen regulation of ribosome biogenesis and protein synthesis, consistent with the prediction that estrogen regulates cell growth principally via c-Myc. The ‘cell cycle’, ‘cell growth’ and ‘cell death’ gene signatures each identified patients with an attenuated response in a cohort of 246 tamoxifen-treated patients. In multivariate analysis the cell death signature was predictive independent of the cell cycle and cell growth signatures. Conclusions/Significance These functionally-based gene signatures can stratify patients treated with tamoxifen into groups with differing outcome, and potentially identify distinct mechanisms of tamoxifen resistance.
Evaluation of the Electronic Transmission of Medical Findings from Hospitals to Practitioners by Triangulation

Summary Objectives: The need for regional, cross-institutional electronic networks in health care is steadily growing to support seamless, cooperative health care. The aim of this study is to evaluate the impact of electronic transmission between hospitals and practitioners in a Tyrolean health care network, and to derive technical and organizational points for improvement. Methods: Between March and August 2004 we carried out a triangulation-based cross-sectional study, combining a qualitative study based on semi-structured, problem-centric interviews with selected practitioners, with a quantitative study based on a standardized questionnaire survey of all the Tyrolean practitioners that receive electronic messages. The survey was designed to confirm the hypotheses which have been systematically derived from the interviews. Results and Conclusions: The results show high satisfaction and positive impact of electronic communication. The triangulation of quantitative and qualitative methods was found to be useful in order to make the definition and confirmation of the hypotheses more transparent.
Mapping and exploration with mobile robots using coverage maps

Exploration and mapping belongs to the fundamental tasks of mobile robots. In the past, many approaches have used occupancy grid maps to represent the environment during the map building process. Occupancy grids, however, are based on the assumption that each cell is either occupied or free. In this paper we introduce coverage maps as an alternative way of representing the environment of a robot. Coverage maps store for each cell of a given grid a posterior about the amount the corresponding cell is covered by an obstacle. We also present a model that allows us to update coverage maps upon input obtained from proximity sensors. We furthermore describe how to use coverage maps for a decision theoretic approach to exploration. Finally we present experimental results illustrating that coverage maps can be used to efficiently learn highly accurate models even if noisy sensors such as ultrasounds are used.
Preparation of ZrO2 Spherical Nanoparticles Used for Photonic Crystal

ZrO2 spherical nanoparticles were prepared by rheological phase reaction. The crystal structure, morphology and formation mechanism were characterized with X-ray diffraction (XRD), Fourier transform infrared spectrum (FTIR) and scanning electron microscopy (SEM), etc. Then three-dimensional photonic crystal was synthesized by sol-gel method and using surfactant as template. The study showed that well-controlled spherical particle is helpful to preparation of photonic crystal with adjustable apertures. Mesoporous ZrO2 was obtained with narrow pore size distributions.
Example based video filters

Many of the successful multimedia retrieval systems focus on developing efficient and effective video retrieval solutions with the help of appropriate index structures. In these systems, the query is an example video and the retrieved results are similar video clips which are available apriori in the database. In this paper, we address a complementary problem of filtering a video stream based on a set of given examples. By filtering, we mean to detect, accept or reject the part of a video stream matching any of the given examples. This requires matching of example videos with the on-line video stream. Since the concepts of interest could be complex, we avoid explicit learning of a representation from the example videos to characterize the visual event present in the examples. We model the problem as simultaneous on-line spotting of multiple examples in a video stream. We employ a vocabulary trie for the filtering purpose and demonstrate the applicability of the technique in a variety of situations.
Spirituality Index of Well-Being Scale: development and testing of a new measure.

OBJECTIVE To evaluate the reliability and validity of the Spirituality Index of Well-Being (SIWB) Scale in a patient population. STUDY DESIGN Cross-sectional survey. POPULATION Community-dwelling elderly individuals (n = 277) recruited from primary care clinic sites in the Kansas City metropolitan area. OUTCOMES MEASURED Internal consistency, concurrent construct validity, discriminant validity, and factor analysis with Varivax rotation. RESULTS The initial version of the SIWB contained 40 items: 20 from a self-efficacy domain and 20 from a life scheme domain. Factor analysis yielded 6 items loaded most strongly on factor 1 (intrapersonal self-efficacy) and 6 other items loaded strongly on factor 2 (life scheme). The Self-efficacy subscale had an alpha of.83 and the Life Scheme subscale had an alpha of.80; the total 12-item SIWB Scale had an alpha of.87. The SIWB had significant and expected correlations with other quality-of-life measures related to subjective well-being: EuroQol (r =.18), Geriatric Depression Scale (r = -35), the Physical Functioning Index from the Short Form 36 (r =.28), and the Years of Healthy Life Scale (r = -.35). Religiosity did not correlated significantly with the SIWB (r =.12, P =.056). CONCLUSIONS The 12-item SIWB Scale is a valid and reliable measure of subjective well-being in an older patient population.
Lyrics-Based Emotion Classification Using Feature Selection by Partial Syntactic Analysis

Songs feel emotionally different to listeners depending on their lyrical contents, even when melodies are similar. Accordingly, when using features related to melody, like tempo, rhythm, tune, and musical note, it is difficult to classify emotions accurately through the existing music emotion classification methods. This paper therefore proposes a method for lyrics-based emotion classification using feature selection by partial syntactic analysis. Based on the existing emotion ontology, four kinds of syntactic analysis rules were applied to extract emotion features from lyrics. The precision and recall rates of the emotion feature extraction were 73% and 70%, respectively. The extracted emotion features along with the NB, HMM, and SVM machine learning methods were used, showing a maximum accuracy rate of 58.8%.
Design and analysis of multimedia communication system

In this paper, we propose an efficient compression/decompression technology and encryption/decryption technology for a multimedia communication system. In order to reduce the volume of multimedia data over wireless channels, data compression techniques are widely used. Discrete cosine transform (DCT) is one of the major compression Scheme. Hence, we present Dynamic bit-width adaptation scheme in discrete cosine transform (DCT) as an efficient compression technique. We select the appropriate operand bit widths that achieve significant reduction of power consumption. It is essential to protect the confidential image data from unauthorized access for multimedia applications. Hence, in this paper, we present a modification to the Advanced Encryption Standard (MAES) to reflect a high level security and better image encryption. The modification is done by adjusting the Shift Row Transformation.
Periodicity Detection Method for Small-Sample Time Series Datasets

Time series of gene expression often exhibit periodic behavior under the influence of multiple signal pathways, and are represented by a model that incorporates multiple harmonics and noise. Most of these data, which are observed using DNA microarrays, consist of few sampling points in time, but most periodicity detection methods require a relatively large number of sampling points. We have previously developed a detection algorithm based on the discrete Fourier transform and Akaike's information criterion. Here we demonstrate the performance of the algorithm for small-sample time series data through a comparison with conventional and newly proposed periodicity detection methods based on a statistical analysis of the power of harmonics. We show that this method has higher sensitivity for data consisting of multiple harmonics, and is more robust against noise than other methods. Although “combinatorial explosion” occurs for large datasets, the computational time is not a problem for small-sample datasets. The MATLAB/GNU Octave script of the algorithm is available on the author's web site: http://www.cbrc. jp/%7Etominaga/piccolo/.
"Should We Move to Stack Overflow?" Measuring the Utility of Social Media for Developer Support

Stack Overflow is an enormously popular question-and-answer web site intended for software developers to help each other with programming issues. Some software projects aimed at developers (for example, application programming interfaces, application engines, cloud services, development frameworks, and the like) are closing their self-supported developer discussion forums and mailing lists and instead directing developers to use special-purpose tags on Stack Overflow. The goals of this paper are to document the main reasons given for moving developer support to Stack Overflow, and then to collect and analyze data from a group of software projects that have done this, in order to show whether the expected quality of support was actually achieved. The analysis shows that for all four software projects in this study, two of the desired quality indicators, developer participation and response time, did show improvements on Stack Overflow as compared to mailing lists and forums. However, we also found several projects that moved back from Stack Overflow, despite achieving these desired improvements. The results of this study are applicable to a wide variety of software projects that provide developer support using social media.
Atomic depth distribution analysis and growth dynamics of metals on metal-covered Si(111) surfaces studied by incident-angle-dependent RHEED-TRAXS (total-reflection-angle x-ray spectroscopy)

During observation of reflection high-energy electron diffraction, characteristic x-rays are emitted from surfaces. The intensities of these x-rays change with change in the incident glancing angle (θg) of the primary electron beam, since density distribution of electrons near the surface changes with change in θg. By analyzing θg dependence of x-ray intensities, the depth distribution of elements near the surface can be determined without destruction of the surface. Resolution of depth in this method is one monolayer at the uppermost layers. By using this method, various growth motions of elements, such as substitution, alloying and floating were observed during growth of metals on metal-covered Si(111) surfaces. Morphology and growth modes of metals were significantly altered by preadsorption of other metals, and sometimes very flat metal films that would be applicable for fabrication of future electronic nano devices were obtained. In this review, the method for analysis of depth distribution of elements and growth modes of metals (Au, Ag, Ga, In and Sn) on an Si(111) surface precovered by another metal are described. [DOI: 10.1380/ejssnt.2003. 91]
The Lender of Last Resort: A 21st Century Approach

The object of this paper is to analyze rigorously the role of a Lender of Last Resort by providing a framework where the distinction between insolvency and illiquidity is not clearly cut. Determining the optimal Lender of Last Resort policy requires a careful modeling of the structure of the interbank market and of the closure policy. In our set up, the results depend upon the existence of moral hazard. If the main source of moral hazard is the banks’ lack of incentives to screen loans, then the Lender of Last Resort may have to intervene to improve the e¢ciency of an unsecured interbank market; if instead, the main source of moral hazard is loans monitoring, then the interbank market should be secured and the Lender of Last Resort should never intervene.
Data Association in Multi Target Tracking Using Cross Entropy Based Algorithms

Multiple-target tracking (MTT) in the presence of spurious measurements poses difficult computational challenges related to the measurement-to-track data association problem. Different approaches have been proposed to tackle this problem, including various approximations and heuristic optimization tools. The Cross Entropy (CE) and the related Parametric MinxEnt (PME) methods are recent optimization heuristics that have proved useful in many combinatorial optimization problems. They are akin to evolutionary algorithms in that a population of solutions is evolved, however generation of new solutions is based on statistical methods of sampling and parameter estimation. In this work we apply the Cross-Entropy method and its recent MinxEnt variant to the multi-scan version of the data association problem in the presence of misdetections, false alarms, and unknown number of targets. We formulate the algorithms, explore via simulation their efficiency and performance compared to other recently proposed techniques, and show that they obtain state-of-the-art performance in hard scenarios.
Improved IBP for Super-resolving Remote Sensing Images

Abstract The research on super-resolution (SR) image recovery has been carried out in the last two decades. With the fast development of computer technology, more and more efficient algorithms have been put forward in recent years. The Iteration Back Projection (IBP) method is one of the popular methods with SR. In this paper, a modified IBP is proposed for remote sensing image processing. This improved IBP can efficiently deal with local affine transformations within images for SR. Experiments and results are presented using both a synthetic set of images generated from a single Landsat ETM+ channel and a set of Advanced Land Observing Satellite (ALOS) imagery.
Coupling of the Proto-oncogene Product c-Cbl to the Epidermal Growth Factor Receptor (*)

The proto-oncogene product, Cbl, is a 120-kDa protein present in lymphocytes that contains numerous PXXP motifs in its COOH-terminal region and constitutively binds the SH3-containing adaptor protein Grb2. Cross-linking of CD3 and CD4 receptors in Jurkat T cells causes tyrosine phosphorylation of Cbl and its association with phosphatidylinositol 3′-kinase (Meisner, H., Conway, B., Hartley, D., and Czech, M. P.(1995) Mol. Cell. Biol. 15, 3571-3578). Here we demonstrate that Cbl is also present in nonlymphoid cells, and that epidermal growth factor (EGF) elicits its rapid tyrosine phosphorylation in human embryonic 293 cells. Immunoprecipitates of Cbl from lysates of these cells contain Grb2 in the basal state, while EGF stimulation causes co-precipitation of tyrosine-phosphorylated EGF receptors. Similarly, EGF receptor immunoprecipitates from EGF-treated 293 cells contain Cbl and Grb2. Both Grb2 and EGF receptors are released from Cbl in the presence of a proline-rich peptide that binds the NH-terminal SH3 domain of Grb2. These results indicate that autophosphorylated EGF receptors associate with the SH2 domain of Grb2, which is complexed through its SH3 domain with proline-rich regions of Cbl. Such recruitment of Cbl to EGF receptors may reflect an important mechanism for its tyrosine phosphorylation and for assembling signaling components that mediate or modulate EGF actions.
A deterministic single exponential time algorithm for most lattice problems based on voronoi cell computations

We give deterministic ~O(22n+o(n))-time algorithms to solve all the most important computational problems on point lattices in NP, including the Shortest Vector Problem (SVP), Closest Vector Problem (CVP), and Shortest Independent Vectors Problem (SIVP). This improves the nO(n) running time of the best previously known algorithms for CVP (Kannan, Math. Operation Research 12(3):415--440, 1987) and SIVP (Micciancio, Proc. of SODA, 2008), and gives a deterministic and asymptotically faster alternative to the 2O(n)-time (and space) randomized algorithm for SVP of (Ajtai, Kumar and Sivakumar, STOC 2001). The core of our algorithm is a new method to solve the closest vector problem with preprocessing (CVPP) that uses the Voronoi cell of the lattice (described as intersection of half-spaces) as the result of the preprocessing function. In the process, we also give algorithms for several other lattice problems, including computing the kissing number of a lattice, and computing the set of all Voronoi relevant vectors. All our algorithms are deterministic, and have 2O(n) time and space complexity.
Canonical Wnt Signaling Promotes Early Hematopoietic Progenitor Formation and Erythroid Specification during Embryonic Stem Cell Differentiation

The generation of hematopoietic stem cells (HSCs) during development is a complex process linked to morphogenic signals. Understanding this process is important for regenerative medicine applications that require in vitro production of HSC. In this study we investigated the effects of canonical Wnt/β-catenin signaling during early embryonic differentiation and hematopoietic specification using an embryonic stem cell system. Our data clearly demonstrates that following early differentiation induction, canonical Wnt signaling induces a strong mesodermal program whilst maintaining a degree of stemness potential. This involved a complex interplay between β-catenin/TCF/LEF/Brachyury/Nanog. β-catenin mediated up-regulation of TCF/LEF resulted in enhanced brachyury levels, which in-turn lead to Nanog up-regulation. During differentiation, active canonical Wnt signaling also up-regulated key transcription factors and cell specific markers essential for hematopoietic specification, in particular genes involved in establishing primitive erythropoiesis. This led to a significant increase in primitive erythroid colony formation. β-catenin signaling also augmented early hematopoietic and multipotent progenitor (MPP) formation. Following culture in a MPP specific cytokine cocktail, activation of β-catenin suppressed differentiation of the early hematopoietic progenitor population, with cells displaying a higher replating capacity and a propensity to form megakaryocytic erythroid progenitors. This bias towards erythroid lineage commitment was also observed when hematopoietic progenitors were directed to undergo myeloid colony formation. Overall this study underscores the importance of canonical Wnt/β-catenin signaling in mesodermal specification, primitive erythropoiesis and early hematopietic progenitor formation during hematopoietic induction.
Parents of Children with Asperger Syndrome: What is the Cognitive Phenotype?

Two cognitive anomalies have been found in autism: a superiority on the Embedded Figures Task and a deficit in theory of mind. Using adult-level versions of these tasks, the present study investigated if parents of children with Asperger Syndrome might show a mild variant of these anomalies, as might be predicted from a genetic hypothesis. Significant differences were found on both measures. Parents were significantly faster than controls on the Embedded Figures Task and slightly but significantly less accurate at interpreting photographs of the eye region of the face in terms of mental states. The results are discussed in terms of the broader cognitive phenotype of Asperger Syndrome and in terms of their implications for cognitive neuroscientific theories of the condition.
Safely Delegating Data Mining Tasks

Data mining is playing an important role in decision making for business activities and governmental administration. Since many organizations or their divisions do not possess the in-house expertise and infrastructure for data mining, it is beneficial to delegate data mining tasks to external service providers. However, the organizations or divisions may lose of private information during the delegating process. In this paper, we present a Bloom filter based solution to enable organizations or their divisions to delegate the tasks of mining association rules while protecting data privacy. Our approach can achieve high precision in data mining by only trading-off storage requirements, instead of by trading-off the level of privacy preserving.
Applying Regional Level-Set Formulation to Postsawing Four-Element LED Wafer Inspection

With level-set formulation, new contours can emerge during the evolution of contours. A defect inspection system that utilizes the evolution of zero-level contours for segmenting postsawing wafer is proposed in this study. The system utilizes a regional formulation, which improves the level-set segmentation in images with intensity inhomogeneity. An automatic threshold is used to set the initial contour to a contour near the die region. Fewer iterations are thus required to evolve the zero-level set to segment the wafer. Without the needs for filtering in advance, the inspection can be performed directly on the segmented results. The proposed approach outperforms other postsawing inspection methods in terms of accuracy.
Hadoop Based Enhanced Cloud Architecture

Explosion of biological data due to largescale genomic research and advances in high throughput data generation tools result in massive distributed datasets. Analysis of such large nonrelational, heterogeneous, and distributed datasets is emerging challenge in data driven biomedical industries. Highly complex biological data require unconventional computational approaches and knowledge-based solutions. Distributed datasets need to be reduced to smaller datasets that can be efficiently queried. Since genomic and biological data is generated in large volume and is stored in geographically diverse locations, distributed computing on multiple clusters, our objective here is to assess the feasibility of using Cloud based platform to analyze genomic big data. In this paper we report on the limitation of cloud based platform in the analysis of genomic data.