Miracle-dz/UniFAR-FTUs huggingface dataset:
PPARγ ligands inhibit telomerase activity and hTERT expression through modulation of the Myc/Mad/Max network in colon cancer cells

In human cells the length of telomeres depends on telomerase activity. This activity and the expression of the catalytic subunit of human telomerase reverse transcriptase (hTERT) is strongly up‐regulated in most human cancers. hTERT expression is regulated by different transcription factors, such as c‐Myc, Mad1 and Sp1. In this study, we demonstrated that 15d‐PG J2 and rosiglitazone (an endogenous and synthetic peroxisome proliferators activated receptor γ (PPARγ) ligand, respectively) inhibited hTERT expression and telomerase activity in CaCo‐2 colon cancer cells. Moreover, both ligands inhibited c‐Myc protein expression and its E‐box DNA binding activity. Additionally, Mad1 protein expression and its E‐box DNA binding activity were strongly increased by 15d‐PG J2 and, to a lesser extent, by rosiglitazone. Sp1 transcription factor expression and its GC‐box DNA binding activity were not affected by both PPARγ ligands. Results obtained by transient transfection of CaCo‐2 cells with pmaxFP‐Green‐PRL plasmid constructs containing the functional hTERT core promoter (including one E‐box and five GC‐boxes) and its E‐box deleted sequences, cloned upstream of the green fluorescent protein reporter gene, demonstrated that 15d‐PG J2, and with minor effectiveness, rosiglitazone, strongly reduced hTERT core promoter activity. E‐boxes for Myc/Mad/Max binding showed a higher activity than GC‐boxes for Sp1. By using GW9662, an antagonist of PPARγ, we demonstrated that the effects of 15d‐PG J2 are completely PPARγ independent, whereas the effects of rosiglitazone on hTERT expression seem to be partially PPARγ independent. The regulation of hTERT expression by 15d‐PG J2 and rosiglitazone, through the modulation of the Myc/Max/Mad1 network, may represent a new mechanism of action of these substances in inhibiting cell proliferation.
Identification of behavioral and creational design patterns through dynamic analysis

Design patterns are considered to be a simple and elegant way to solve problems in object-oriented software systems, because their application leads to a wellstructured object-oriented design, and hence, are considered to ease software comprehension and maintenance. However, due to the complexity of large objectoriented software systems nowadays, it is impossible to recover manually the design patterns applied during the design and implementation of a system, which, in turn, impedes its comprehension. In the past few years, the structure and organization among classes were the predominant means of identifying design patterns in object-oriented software systems. In this paper, we show how to describe behavioral and creational design patterns as collaborations among objects and how these representations allow the identification of behavioral and creational design patterns using dynamic analysis and constraint programming.
Cognitive-behavioral therapy for PTSD in children and adolescents: a preliminary randomized controlled trial.

OBJECTIVE To evaluate the efficacy of individual trauma-focused cognitive-behavioral therapy (CBT) for treating posttraumatic stress disorder (PTSD) in children and young people. METHOD Following a 4-week symptom-monitoring baseline period, 24 children and young people (8-18 years old) who met full DSM-IV PTSD diagnostic criteria after experiencing single-incident traumatic events (motor vehicle accidents, interpersonal violence, or witnessing violence) were randomly allocated to a 10-week course of individual CBT or to placement on a waitlist (WL) for 10 weeks. RESULTS Compared to the WL group, participants who received CBT showed significantly greater improvement in symptoms of PTSD, depression, and anxiety, with significantly better functioning. After CBT, 92% of participants no longer met criteria for PTSD; after WL, 42% of participants no longer met criteria. CBT gains were maintained at 6-month follow-up. Effects of CBT were partially mediated by changes in maladaptive cognitions, as predicted by cognitive models of PTSD. CONCLUSIONS Individual trauma-focused CBT is an effective treatment for PTSD in children and young people.
Analysis of multiscale sign series entropy of the young and middle-aged electroencephalogram signals

The physiological analysis of electroencephalogram (EEG) signals is of great significance in assessing the activity of the brain function and the physiological state. EEG is a means of clinical examination of brain diseases. Age is one of the important factors that affect the results of the EEG. EEG signal analysis is mainly to analyze the time series of the signal, multiscale entropy (MSE) analysis [1-3] is the method that used to analyze the finite length of the time series. Multiscale sign series entropy (MSSE) method is proposed for the analysis of EEG signals in the young and middle-aged. We use the proposed method to analyze the signals from several aspects of data length, word length, noise, multi scale etc. By analyzing the influence of these factors, we can still distinguish the EEG signals of different ages. Multiscale sign series entropy (MSSE) analysis algorithm can effectively separate the brain electrical signals from the young and middle aged, which is expected to have a certain reference value for the traditional pathological analysis of the EEG signals.
A System for Classification of Propositions of the Indian Supreme Court Judgements

In this work, we describe a system for classification of propositions from legal judgements of the Supreme Court of India. The system was submitted for participation to the Information Access in the Legal Domain track at the Forum for Information Retrieval Evaluation (FIRE) 2013. The system uses a multi-class Maximum Entropy classifier and various specially designed features to capture the underlying characteristics of the legal propositions. The best performing feature set was chosen by 10-fold cross-validation over the training set. The system achieved an accuracy of 65.03% on the training set and an accuracy of 51.02% on the test set.
Robust Multiresolution Estimation of Parametric Motion Models

Abstract This paper describes a method to estimate parametric motion models. Motivations for the use of such models are, on one hand, their efficiency, which has been demonstrated in numerous contexts such as estimation, segmentation, tracking, and interpretation of motion, and on the other hand, their low computational cost compared to optical flow estimation. However, it is important to have the best accuracy for the estimated parameters, and to take into account the problem of multiple motion. We have therefore developed two robust estimators in a multi-resolution framework. Numerical results support this approach, as validated by the use of these algorithms on complex sequences.
Continuous subcutaneous insulin infusion therapy and multiple daily insulin injections in type 1 diabetes mellitus: a comparative overview and future horizons

ABSTRACT Introduction: Continuous subcutaneous insulin infusion (CSII) therapy is currently accepted as a treatment strategy for type 1 diabetes. Transition from multiple daily injection therapy (MDI; including basal-bolus regimens) to CSII is based on expectations of better metabolic control and fewer hypoglycaemic events. Evidence to date has not been always conclusive. Areas covered: Evidence for CSII and MDI in terms of glycaemic control, hypoglycaemia and psychosocial outcomes is reviewed in the adult and paediatric population with type 1 diabetes. Findings from studies on threshold-based insulin pump suspension and predictive low glucose management (PLGM) are outlined. Limitations of current CSII application and future technological developments are discussed. Expert opinion: Glycaemic control and quality of life (QOL) may be improved by CSII compared to MDI depending on baseline HbA1c and hypoglycaemia rates. Future studies are expected to provide evidence on clinical and cost effectiveness in those who will benefit the most. Training, structured education and support are important to benefit from CSII. Novel technological approaches linking continuous glucose monitoring (CGM) and CSII may help mitigate against frequent hypoglycaemia in those at risk. Development of glucose-responsive automated closed-loop insulin delivery systems may reduce the burden of disease management and improve outcomes in type 1 diabetes.
Kinematic parameter calibration of two-wheeled robot

The kinematic parameters of the two-wheeled robot has a great influence on the robot localization and path planning. Since there exist robot systematic errors caused by unequal wheel diameter and uncertainty about the effective wheelbase, it is difficult to acquire the exact kinematic parameters. In order to reduce the errors, researchers introduced the UMBmark to make calibration of robot kinematic parameters. However, the previous studies assume that the two factors influence the robot localization independently, which is not the case in fact. This paper put forward an improved kinematic parameters calibration method based on the UMBmark. Let the robot walk along a straight path and an equilateral triangle path respectively and we can calibrate kinematic parameters by measuring the actual position errors. Then the optimal length of the straight path was given out, and it is proved that the equilateral triangle path has better adaptability than the square path has. Physical experiment has been carried out, and the result verified the effectiveness of the proposed method.
Address Base Creation Using Raster/vector Integration

The city of Belo Horizonte, Brazil, which has a population of slightly over 2 million, has formed a vectorial database for GIS using digital restitution of air photos. Even though this database is very detailed and precise, it contains only the representation of physical objects. The next step taken was the creation of an address database, by placing symbols over the vectorial information, and associating these symbols with the building address. This article describes the processes used to create and validate such a database, by using raster images of older and rather imprecise cadastral maps, which contain all the required information. In the approach chosen, the operator is prompted to locate a given address, and is able to do so very quickly by simply looking at the raster image of the cadastral map, which is displayed under the vectorial information. No typing is required, because the addresses to be located come from an existing alphanumeric database. Notice that high precision on the older map is not required, because it is used only as a reference for the identification of the addresses. Results obtained include the placement and verification of about 950,000 symbols (400,000 addresses, 270,000 parcel codes and 280,000 tax codes), along with their associated alphanumeric information, consuming 4,700 man-hours, over a period of four months. So, the overall productivity was around 3.4 symbols placed per minute.
Non-rigid dense correspondence with applications for image enhancement

This paper presents a new efficient method for recovering reliable local sets of dense correspondences between two images with some shared content. Our method is designed for pairs of images depicting similar regions acquired by different cameras and lenses, under non-rigid transformations, under different lighting, and over different backgrounds. We utilize a new coarse-to-fine scheme in which nearest-neighbor field computations using Generalized PatchMatch [Barnes et al. 2010] are interleaved with fitting a global non-linear parametric color model and aggregating consistent matching regions using locally adaptive constraints. Compared to previous correspondence approaches, our method combines the best of two worlds: It is dense, like optical flow and stereo reconstruction methods, and it is also robust to geometric and photometric variations, like sparse feature matching. We demonstrate the usefulness of our method using three applications for automatic example-based photograph enhancement: adjusting the tonal characteristics of a source image to match a reference, transferring a known mask to a new image, and kernel estimation for image deblurring.
Draft Genome Sequence of Lachancea lanzarotensis CBS 12615T, an Ascomycetous Yeast Isolated from Grapes

ABSTRACT We report the genome sequencing of the yeast Lachancea lanzarotensis CBS 12615T. The assembly comprises 24 scaffolds, for a total size of 11.46 Mbp. The annotation revealed 5,058 putative protein-coding genes. Detection of seven centromeres supports a chromosome fusion, which occurred after divergence from Lachancea thermotolerans and Lachancea kluyveri.
Modeling and compensation for angular transmission error in harmonic drive gearings

This paper presents a novel modeling and compensation approach for the angular transmission error in harmonic drive gearings. In the modeling, physical phenomena of the transmission error due to nonlinear elastic deformations in micro‐displacement region are especially dealt with, as well as the synchronous component which has been discussed in a variety of conventional studies. On the basis of the analyses of the phenomena, the nonlinear elastic component is mathematically modeled by applying a modeling framework for the rolling friction with hysteresis attributes. The proposed transmission error model has been adopted to the positioning system as a model‐based feedforward compensation manner. Experimental results using a prototype show the effectiveness of the proposed modeling and compensation. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
A Logarithmic Slow-Start Algorithm of TCP Vegas in IP networks

In numerous TCP congestion control algorithms, TCP Vegas avoids congestion on its own initiative. However, its slow-start ending quickly and growing unsmoothly cause that the congestin window designing too small and bandwidth utilization declining too rapid, furthermore affect network efficiency and throughput dropping.etc. Aimed at the deficiencies, we propose a kind of Loga- rithmic Slow-Start Algorithm of TCP Vegas (LSSA-TCP Vegas) to conduct the dynamics of congestion window. We analyze stability condition from the theory via the Nyquist stability criterion and study the issue such as convergence of the algorithm, configuration parameters. Our goal in this paper is to study and compare the performance of LSSA-TCP Vegas and other TCP congestion control algorithms under various network scenarios. The simulation results demonstrate that the algorithm vs the bug of TCP Vegas contains obvious improvements. We believe that Logarithmic Slow-Start Algorithm can be used to provide the better performance of TCP Vegas.
Case Study on Multi-classifications Based Scientific Data Management and Analysis System

The polymorphic, diversified, multi-sources and multi-use scientific data is quite different from the other data, there are many new challenges in building Scientific Data Management and Analysis System (SDMAS), especial one is that the multi-use data requires alternate classifications and mappings between them. Based on the oceanographic data, we present the solutions of multi-classifications problems. We first introduced the data and classificatory criterions of this case, then adopt the classification ontology to represent multi-classifications, use the metadata, query builder and data view mechanisms to support the dynamic cross-classification oriented query. We also prove the purposed solutions by applications and experiments. Theories and practices prove that the proposed solutions are contributed to build multi-classification based SDMAS.
Automated program flaw finding using simulated annealing

One of the major costs in a software project is the construction of test-data. This paper outlines a generalised test-case data generation framework based on optimisation techniques. The framework can incorporate a number of testing criteria, for both functional and non-functional properties. Application of the optimisation framework to testing specification failures and exception conditions is illustrated. The results of a number of small case studies are presented and show the efficiency and effectiveness of this dynamic optimisation-base approach to generating test-data.
Automated Glioblastoma Segmentation Based on a Multiparametric Structured Unsupervised Classification

Automatic brain tumour segmentation has become a key component for the future of brain tumour treatment. Currently, most of brain tumour segmentation approaches arise from the supervised learning standpoint, which requires a labelled training dataset from which to infer the models of the classes. The performance of these models is directly determined by the size and quality of the training corpus, whose retrieval becomes a tedious and time-consuming task. On the other hand, unsupervised approaches avoid these limitations but often do not reach comparable results than the supervised methods. In this sense, we propose an automated unsupervised method for brain tumour segmentation based on anatomical Magnetic Resonance (MR) images. Four unsupervised classification algorithms, grouped by their structured or non-structured condition, were evaluated within our pipeline. Considering the non-structured algorithms, we evaluated K-means, Fuzzy K-means and Gaussian Mixture Model (GMM), whereas as structured classification algorithms we evaluated Gaussian Hidden Markov Random Field (GHMRF). An automated postprocess based on a statistical approach supported by tissue probability maps is proposed to automatically identify the tumour classes after the segmentations. We evaluated our brain tumour segmentation method with the public BRAin Tumor Segmentation (BRATS) 2013 Test and Leaderboard datasets. Our approach based on the GMM model improves the results obtained by most of the supervised methods evaluated with the Leaderboard set and reaches the second position in the ranking. Our variant based on the GHMRF achieves the first position in the Test ranking of the unsupervised approaches and the seventh position in the general Test ranking, which confirms the method as a viable alternative for brain tumour segmentation.
Tradeoffs between Incentive Mechanisms in Boolean Games

Two incentive mechanisms for Boolean games were proposed recently - taxation schemes and side payments. Both mechanisms have been shown to be able to secure a pure Nash equilibrium (PNE) for Boolean games. A complete characterization of outcomes that can be transformed to PNEs is given for each of the two incentive mechanisms. Side payments are proved to be a weaker mechanism in the sense that the outcomes that they can transform to PNEs are a subset of those transformable by taxation. A family of social-network-based Boolean games, which demonstrates the differences between the two mechanisms for securing a PNE, is presented. A distributed search algorithm for finding the side payments needed for securing a PNE is proposed. An empirical evaluation demonstrates the properties of the two mechanisms on the family of social-network-based Boolean games.
Intermittent hypoxia alters gut microbiota diversity in a mouse model of sleep apnoea

We assessed whether intermittent hypoxia, which emulates one of the hallmarks of obstructive sleep apnoea (OSA), leads to altered faecal microbiome in a murine model. In vivo partial pressure of oxygen was measured in colonic faeces during intermittent hypoxia in four anesthetised mice. 10 mice were subjected to a pattern of chronic intermittent hypoxia (20 s at 5% O2 and 40 s at room air for 6 h·day−1) for 6 weeks and 10 mice served as normoxic controls. Faecal samples were obtained and microbiome composition was determined by 16S rRNA pyrosequencing and bioinformatic analysis by Quantitative Insights into Microbial Ecology. Intermittent hypoxia exposures translated into hypoxia/re-oxygenation patterns in the faeces proximal to the bowel epithelium (<200 μm). A significant effect of intermittent hypoxia on global microbial community structure was found. Intermittent hypoxia increased the α-diversity (Shannon index, p<0.05) and induced a change in the gut microbiota (ANOSIM analysis of β-diversity, p<0.05). Specifically, intermittent hypoxia-exposed mice showed a higher abundance of Firmicutes and a smaller abundance of Bacteroidetes and Proteobacteria phyla than controls. Faecal microbiota composition and diversity are altered as a result of intermittent hypoxia realistically mimicking OSA, suggesting the possibility that physiological interplays between host and gut microbiota could be deregulated in OSA. Faecal microbiota composition and diversity are altered due to intermittent hypoxia mimicking OSA in a murine model http://ow.ly/ERjA9
Causes and Consequences of Chromatin Variation between Inbred Mice

Variation at regulatory elements, identified through hypersensitivity to digestion by DNase I, is believed to contribute to variation in complex traits, but the extent and consequences of this variation are poorly characterized. Analysis of terminally differentiated erythroblasts in eight inbred strains of mice identified reproducible variation at approximately 6% of DNase I hypersensitive sites (DHS). Only 30% of such variable DHS contain a sequence variant predictive of site variation. Nevertheless, sequence variants within variable DHS are more likely to be associated with complex traits than those in non-variant DHS, and variants associated with complex traits preferentially occur in variable DHS. Changes at a small proportion (less than 10%) of variable DHS are associated with changes in nearby transcriptional activity. Our results show that whilst DNA sequence variation is not the major determinant of variation in open chromatin, where such variants exist they are likely to be causal for complex traits.
Impaired Axonal Regeneration by Isolectin B4-Binding Dorsal Root Ganglion Neurons In Vitro

The subpopulation of dorsal root ganglion (DRG) neurons recognized by Griffonia simplicifolia isolectin B4 (IB4) differ from other neurons by expressing receptors for glial cell line-derived neurotrophic factor (GDNF) rather than neurotrophins. Additionally, IB4-labeled neurons do not express the laminin receptor, α7-integrin (Gardiner et al., 2005), necessary for optimal axonal regeneration in the peripheral nervous system. In cultures of dissociated DRG neurons of adult mice on laminin, robust spontaneous neurite outgrowth from IB4-negative neurons occurs and is strongly enhanced by previous axotomy. In contrast, IB4-labeled neurons show little neurite outgrowth and do not express GAP 43, even after axotomy or culture with GDNF. Moreover, growth of their axons through collagen gels is impaired compared with other DRG neurons. To determine whether the sparse neurite outgrowth of IB4-labeled neurons is attributable to lack of integrin expression, DRG cultures were infected with a herpes simplex 1 vector encoding α7-integrin, but its forced expression failed to promote neurite outgrowth in either IB4-labeled or other DRG neurons or in cultured adult retinal ganglion cells. Forced coexpression of both α7-integrin and GAP 43 also failed to promote neurite outgrowth in IB4-labeled neurons. In addition, cultured sciatic nerve segments were found to release much lower levels of GDNF, demonstrated by ELISA, than nerve growth factor. These findings together with their impaired intrinsic axonal regeneration capacity may contribute to the known vulnerability of the IB4-labeled population of DRG neurons to peripheral nerve injury.