Miracle-dz/UniFAR-FTUs huggingface dataset:
Facilitating English-Language Reading Performance by a Digital Reading Annotation System with Self-Regulated Learning Mechanisms

Since English has been an international language, how to enhance English levels of people by useful computer assisted learning forms or tools is a critical issue in non-English speaking countries. Past studies confirmed that reading articles with annotated contents enable knowledge sharing and improve the reading comprehension of learners. However, the self-regulated learning (SRL) ability of individual learners when reading learning materials and contributing annotations becomes a key factor affecting reading performance. Thus, this work proposes a SRL mechanism combined with a digital reading annotation system (DRAS) to enhance Grade 7 students to generate rich and high-quality annotations for promoting English-language reading performance. To evaluate the effectiveness of the proposed system, this work adopts a quasi-experimental design to assess an experimental group and control group learners who respectively use the proposed DRAS with and without the SLR mechanisms when reading English-language texts online. Compared with the control group learners, experimental results demonstrate that the reading comprehension and reading annotation abilities of the experimental group learners were significantly improved. Analytical results also confirm that gender differences in reading comprehension and annotation ability existed when using the proposed DRAS with and without the SRL mechanisms to read English-language texts online. Experimental results also show that significant differences existed in the reading comprehension and annotation abilities of learners with good and poor SRL abilities in the experimental group. Additionally, the reading annotation ability of learners in the experimental group was significantly correlated with reading comprehension.
Design and development of analogues of dimers of insulin‐like peptide 3 B‐chain as high‐affinity antagonists of the RXFP2 receptor

Insulin‐like peptide 3 (INSL3) is one of 10 members of the human relaxin–insulin superfamily of peptides. It is a peptide hormone that is expressed by fetal and postnatal testicular Leydig cells and postnatal ovarian thecal cells. It mediates testicular descent during fetal life and suppresses sperm apoptosis in adult males, whereas, in females, it causes oocyte maturation. INSL3 has also been shown to promote thyroid tumor growth and angiogenesis in human. These actions of INSL3 are mediated through its G protein‐coupled receptor, RXFP2. INSL3, a two‐chained peptide, binds to its receptor primarily via its B‐chain, whereas elements of the A‐chain are essential for receptor activation. In an attempt to design a high‐affinity antagonist with potential clinical application as an anticancer agent as well as a contraceptive, we have previously prepared a synthetic parallel dimer of INSL3 B‐chain and demonstrated that it binds to RXFP2 with high affinity. In this work, we undertook full pharmacological characterization of this peptide and show that it can antaogonize INSL3‐mediated cAMP signaling through RXFP2. Further refinement by truncation of 18 residues yielded a minimized analogue that retained full binding affinity and INSL3 antagonism. It is an attractive lead peptide for in vivo evaluation as an inhibitor of male and female fertility and of INSL3‐mediated carcinogenesis. © 2010 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 96: 81–87, 2011.
Supporting Online Material Materials and Methods Som Text Comprehensive Mapping of Long-range Interactions Reveals Folding Principles of the Human Genome

We describe Hi-C, a method that probes the three-dimensional architecture of whole genomes by coupling proximity-based ligation with massively parallel sequencing. We constructed spatial proximity maps of the human genome with Hi-C at a resolution of 1 megabase. These maps confirm the presence of chromosome territories and the spatial proximity of small, gene-rich chromosomes. We identified an additional level of genome organization that is characterized by the spatial segregation of open and closed chromatin to form two genome-wide compartments. At the megabase scale, the chromatin conformation is consistent with a fractal globule, a knot-free, polymer conformation that enables maximally dense packing while preserving the ability to easily fold and unfold any genomic locus. The fractal globule is distinct from the more commonly used globular equilibrium model. Our results demonstrate the power of Hi-C to map the dynamic conformations of whole genomes. T he three-dimensional (3D) conformation of chromosomes is involved in compartmen-talizing the nucleus and bringing widely separated functional elements into close spatial proximity (1–5). Understanding how chromosomes fold can provide insight into the complex relationships between chromatin structure, gene activity, and the functional state of the cell. Yet beyond the scale of nucleosomes, little is known about chro-matin organization. Long-range interactions between specific pairs of loci can be evaluated with chromosome con-formation capture (3C), using spatially constrained ligation followed by locus-specific polymerase chain reaction (PCR) (6). Adaptations of 3C have extended the process with the use of inverse PCR (4C) (7, 8) or multiplexed ligation-mediated amplification (5C) (9). Still, these techniques require choosing a set of target loci and do not allow unbiased genomewide analysis. Here, we report a method called Hi-C that adapts the above approach to enable purification of ligation products followed by massively parallel sequencing. Hi-C allows unbiased identification of chromatin interactions across an entire genome.We briefly summarize the process: cells are crosslinked with formaldehyde; DNA is digested with a restriction enzyme that leaves a 5′ overhang; the 5′ overhang is filled, including a biotinylated residue; and the resulting blunt-end fragments are ligated under dilute conditions that favor ligation events between the cross-linked DNA fragments. The resulting DNA sample contains ligation products consisting of fragments that were originally in close spatial proximity in the nucleus, marked with biotin at the junction. A Hi-C library is created by shearing the DNA and selecting the biotin-containing fragments with streptavidin beads. The library is then analyzed by using massively …
Reconditioning effect of oligodendrocyte-like cell transplantation in acute spinal cord injury in rats

To observe the reconditioning effect of oligodendrocyte-like cell transplantation in acute spinal cord injury in rats, bone marrow mesenchymal stem cells were differentiated into oligodendrocyte-like cells induced by cytokines including insulin-like growth factor-1(IGF-1). Rats with acute spinal cord injury were treated with the oligodendrocyte-like cells for 8 weeks by local injection. The therapeutic effect was compared with oligodendrocytes transplantation and saline. Regeneration of axon myelin sheath and functional recovery of hind limbs were significantly improved after transplantation with oligodendrocyte-like cells than that with saline. But there was no significant difference between rats treated with oligodendrocyte-like cells and oligodendrocytes. Bone marrow mesenchymal stem cells differentiating into oligodendrocyte-like cells can be induced by cytokines including IGF-1, with similar specific surface markers of oligodendrocytes. These cells can survive in injury sites of the spinal cord for a long duration after transplantation to improve recovery of neural function and reduce cavity area at injury site after acute spinal injury in rats. The possible mechanism may be regeneration of axon myelin sheath, which is helpful for reconstruction of neural reflex function.
A Multi-objective Biogeography-Based Optimization for Virtual Machine Placement

In cloud computing, an important issue is virtual machine placement (VMP), selecting the most suitable set of physical hosts for a set of virtual machines. In this paper, we present a novel solution to the VMP problem called VMPMBBO. Our scheme treats the VMP problem as a complex system, and utilizes the biogeography-based optimization (BBO) technique to optimize the virtual machine placement that minimizes power consumption, resource waste, server unevenness, inter-VM traffic, storage traffic and migration time at the same time. Compared with three existing multi-objective VMP optimization algorithms, VMPMBBO has better convergence characteristics and is more computationally efficient. VMPMBBO is also robust. Extensive experiments are conducted using synthetic data from related literatures. The results confirm the effectiveness, efficiency, and robustness of the proposed approach. To the best of our knowledge, this work is the first approach that applies BBO and complex system optimization to virtual machine placement (VMP).
Serum Level of Macrophage Migration Inhibitory Factor (MIF) in Egyptians With Alopecia Areata and Its Relation to the Clinical Severity of the Disease

Alopecia areata (AA) is a common dermatological problem that manifests as sudden loss of hair without any inflammation or scarring. Various cytokines are implicated in the pathogenesis of this disease. Macrophage migration inhibitory factor (MIF) is located at an upstream position in the events leading to the possible dysregulated immuno‐inflammatory responses, and the high level of this cytokine in AA may suggest a role of MIF in the pathogenesis of AA.
n-confusion: a generalization of k-anonymity

We provide a formal framework for re-identification in general. We define n-confusion as a concept for modelling the anonymity of a database table and we prove that n-confusion is a generalization of k-anonymity. Finally we present an example to illustrate how this result can be used to augment local variance in k-anonymous protected data.
Evidence for a modest undercount bias in early historical Atlantic tropical cyclone counts

We obtain new insights into the reliability of long‐term historical Atlantic tropical cyclone (‘TC’) counts through the use of a statistical model that relates variations in annual Atlantic TC counts to climate state variables. We find that the existence of a substantial undercount bias in late 19th through mid 20th century TC counts is inconsistent with the statistical relationship between TC counts and climate.
Measurement and analysis of real network tra

We present a platform for collecting and analyzing measurements of real network tra c. The measurements are collected by a high performance PC-based monitor, which can collect detailed tra c statistics on a high speed (155 Mbps) link, without disrupting the operation or a ecting the performance of the network. The analysis is performed by a set of tools that use results from a recent theory of statistical multiplexing, and have the objective of answering important questions related to the management and dimensioning of networks carrying bursty tra c and guaranteeing some level of performance. Finally, we present case studies demonstrating the application of our analysis tools.
Recognition of People Reoccurrences Using Bag-Of-Features Representation and Support Vector Machine

In multi-camera surveillance systems, it is important to track the same person across multiple cameras. It is also desirable to recognize the individuals who have been previously observed in a single-camera system. The method that represents a object image using a bag of visual words has been commonly used in image retrieval applications. For recognizing people, it can outperform the methods mainly based on global appearance like color histogram, and fit better to low-quality images compared to biometric features such as face and gait. In this paper we study the details in feature extraction, vocabulary building and classifier learning of the bag-of-features approach for classifying tracks of different individuals. Based on this approach, we design a online system applying incremental support vector machine learning with a decision scheme to distinguish reoccurrences from new targets. We get promising results from the evaluation with more than 100 tracks of 50 different people.
Illustrative Streamline Placement and Visualization

Inspired by the abstracting, focusing and explanatory qualities of diagram drawing in art, in this paper we propose a novel seeding strategy to generate representative and illustrative streamlines in 2D vector fields to enforce visual clarity and evidence. A particular focus of our algorithm is to depict the underlying flow patterns effectively and succinctly with a minimum set of streamlines. To achieve this goal, 2D distance fields are generated to encode the distances from each grid point in the field to the nearby streamlines. A local metric is derived to measure the dissimilarity between the vectors from the original field and an approximate field computed from the distance fields. A global metric is used to measure the dissimilarity between streamlines based on the local errors to decide whether to drop a new seed at a local point. This process is iterated to generate streamlines until no more streamlines can be found that are dissimilar to the existing ones. We present examples of images generated from our algorithm and report results from qualitative analysis and user studies.
Feature Screening via Distance Correlation Learning

This article is concerned with screening features in ultrahigh-dimensional data analysis, which has become increasingly important in diverse scientific fields. We develop a sure independence screening procedure based on the distance correlation (DC-SIS). The DC-SIS can be implemented as easily as the sure independence screening (SIS) procedure based on the Pearson correlation proposed by Fan and Lv. However, the DC-SIS can significantly improve the SIS. Fan and Lv established the sure screening property for the SIS based on linear models, but the sure screening property is valid for the DC-SIS under more general settings, including linear models. Furthermore, the implementation of the DC-SIS does not require model specification (e.g., linear model or generalized linear model) for responses or predictors. This is a very appealing property in ultrahigh-dimensional data analysis. Moreover, the DC-SIS can be used directly to screen grouped predictor variables and multivariate response variables. We establish the sure screening property for the DC-SIS, and conduct simulations to examine its finite sample performance. A numerical comparison indicates that the DC-SIS performs much better than the SIS in various models. We also illustrate the DC-SIS through a real-data example.
Business Analytics in (a) Blink

The Blink project’s ambitious goal is to answer all Business Intelligence (BI) queries in mere seconds, regardless of the database size, with an extremely low total cost of ownership. Blink is a new DBMS aimed primarily at read-mostly BI query processing that exploits scale-out of commodity multi-core processors and cheap DRAM to retain a (copy of a) data mart completely in main memory. Additionally, it exploits proprietary compression technology and cache-conscious algorithms that reduce memory bandwidth consumption and allow most SQL query processing to be performed on the compressed data. Blink always scans (portions of) the data mart in parallel on all nodes, without using any indexes or materialized views, and without any query optimizer to choose among them. The Blink technology has thus far been incorporated into two IBM accelerator products generally available since March 2011. We are now working on the next generation of Blink, which will signiﬁcantly expand the “sweet spot” of the Blink technology to much larger, disk-based warehouses and allow Blink to “own” the data, rather than copies of it.
Effectiveness of antipsychotic treatments for schizophrenia: interim 6-month analysis from a prospective observational study (IC-SOHO) comparing olanzapine, quetiapine, risperidone, and haloperidol.

BACKGROUND The Intercontinental Schizophrenia Outpatient Health Outcomes (IC-SOHO) study was designed to provide information regarding use and outcome of antipsychotic treatments in a large, diverse population in real practice settings. METHOD Outpatients with schizophrenia (ICD-10 or DSM-IV) who initiated or changed to a new antipsychotic entered this 3-year, naturalistic, prospective observational study. Four monotherapy treatment groups were defined according to the antipsychotic prescribed at baseline, namely olanzapine, risperidone, quetiapine, and haloperidol. Efficacy was assessed using the Clinical Global Impressions-Severity of Illness rating scale (CGI-S), inclusive of subscales for positive, negative, depressive, and cognitive symptoms. Tolerability was assessed by adverse event questionnaires and weight measurements. Six-month findings are described. RESULTS At baseline, 5833 participants were prescribed monotherapy and the mean severity of illness was moderate to marked (CGI-S). At 6 months, olanzapine resulted in significantly greater improvements in overall, positive, negative, depressive, and cognitive symptoms compared with quetiapine, risperidone or haloperidol (p <.001). Improvements in overall, negative, and cognitive symptoms were significantly higher for risperidone compared with haloperidol (p <.001), whereas improvements across all symptoms were comparable for quetiapine and haloperidol. Extra-pyramidal symptoms and tardive dyskinesia decreased compared with baseline in the olanzapine, quetiapine, and risperidone groups but increased in the haloperidol group (p <.001, likelihood of extrapyramidal symptoms with haloperidol compared with olanzapine, quetiapine, or risperidone). Sexual function adverse events were most prominent in the haloperidol and risperidone treatment groups. Weight change was significantly greater for olanzapine compared with the other antipsychotics (p <.001). CONCLUSION Our results support the previously reported positive impact of atypical antipsychotics, particularly olanzapine, in patients with schizophrenia.
Reflection on the development of the tool kits of Bertin’s methods

ABSTRACT Bertin’s first book, Semiology of Graphics, was published in 1967. His second book, Graphics and Graphic Information Processing, was subsequently published in 1977. The word “processing” in the title of the second book is interesting because in those days there were no personal computers with an interactive display system. But in Bertin’s laboratory there were many kinds of tool kits – basically manually developed thematic maps and data analysis. Bertin’s methods were concerned with making a thematic map and data visualization. Maps, and more generally graphics, were represented by sets of cartographic symbols. Thus, they are abstractions that demand both theoretical and technical literacy to represent and understand them. If the representation is systematic, a sort of tool kit might be necessary, because the representation demands consistency based on the theory. Otherwise a cartographer faces the risk of an unstable and unintelligible representation. In this paper, we discuss the discrimination between tool kits intended either for an automated system or a process assisting system. The latter process might be useful and necessary to develop a graphic way of thinking. This investigation refers to Bertin’s books, materials conserved at the National Archives in Paris, and other related software developed later. Abbreviation: EHESS: Ecole des Hautes Etudes en Sciences Sociales inherited Ecole Pratique des Hautes Etudes since 1975
10 22 v 2 1 2 Se p 20 05 Shear-free radiating collapse and conformal flatness

Here we study some general properties of spherical shear-free collapse. Its general solution when imposing conformal flatness is reobtained [1, 2] and matched to the outgoing Vaidya spacetime. We propose a simple model satisfying these conditions and study its physical consequences. Special attention deserve, the role played by relaxational processes and the conspicuous link betweeen dissipation and density inhomogeneity. e-mail: laherrera@telcel.net. ve e-mail: gele@ccr.jussieu. fr e-mail: nos@cbpf.br e-mail: aw@guava.physics. uiuc.edu 1
A Networking Identity Authentication Scheme Combining Fingerprint Coding and Identity Based Encryption

Current certificate-based information security technologies are facing a challenge of lacking the exact connection between cryptographic key and legitimate users and a problem of comprehensive management of certificates. In this paper we propose a novel networking identity authentication scheme based on fingerprint coding method and Identity-based encryption (IBE). Fingerprint code is a dual-factor authenticator which combines a token, e.g. USB key, with user's fingerprint feature by direct mixing of pseudo-random number generated by token and fingerprint feature. IBE allows for a sender to encrypt a message to a receiver without access to a public key certificate. This scheme can improve the security of user authentication and simplify comprehensive management of certificates, in the meantime, protect against fingerprint data fabrication and stolen. The security and efficiency of our proposed scheme meet the requirements of practical applications.
Robust PCA Methods for Complete and Missing Data

In this paper, we consider and introduce methods for robust principal component analysis (PCA), including also cases where there are missing values in the data. PCA is a widely applied standard statistical method for data preprocessing, compression, and analysis. It is based on the second-order statistics of the data and is optimal for Gaussian data, but is often applied to data sets having unknown or other types of probability distributions. PCA can be derived from minimization of the mean-square representation error or maximization of variances under orthonormality constraints. However, these quadratic criteria are sensitive to outliers in the data and long-tailed distributions, which may degrade the results given by PCA badly. We introduce robust methods for estimation of both the PCA eigenvectors directly or the PCA subspace spanned by them. Experimental results show that our methods provide often better results than standard PCA when outliers are present in the data. Furthermore, we extend our methods to incomplete data with missing values. The problems arising in such cases have several features typical for nonlinear models.
ADir_pNB: A Cost-Effective Way to Implement Full Map Directory-Based Cache Coherence Protocols

Directories have been used to maintain cache coherency in shared memory multiprocessors with private caches. The traditional full map directory tracks the exact caching status for each shared memory block and is designed to be efficient and simple. Unfortunately, the inherent directory size explosion makes it unsuitable for large-scale multiprocessors. In this paper, we propose a new directory scheme, dubbed associative full map directory (ADir/sub p/NB) which reduces the directory storage requirement. The proposed ADir/sub p/NB uses one directory entry to maintain the sharing information for a set of exclusively cached memory blocks in a centralized linked list style. By implementing dynamic cache pointer allocation, reclamation, and replacement hints, ADir/sub p/NB can be implemented as "a full map directory with lower directory memory cost". Our analysis indicates that, on a typical architectural paradigm, ADir/sub p/NB reduces memory overhead of a traditional full map directory by up to 70-80 percent. In addition to the low memory overhead, we show that the proposed scheme can be implemented with appropriate protocol modification and hardware addition. Simulation studies indicate that ADir/sub p/NB can achieve a competitive performance with the Dir/sub p/NB. Compared with limited directory schemes, ADir/sub p/NB shows more stable and robust performance results on applications across a spectrum of memory sharing and access patterns due to the elimination of directory overflows. We believe that ADir/sub p/NB can be employed as a design alternative of full map directory for moderately large-scale and fine-grain shared memory multiprocessors.