Miracle-dz/UniFAR-FTUs huggingface dataset:
AF1q is a novel TCF7 co-factor which activates CD44 and promotes breast cancer metastasis

AF1q is an MLL fusion partner that was identified from acute myeloid leukemia (AML) patients with t (1; 11) (q21; q23) chromosomal abnormality. The function of AF1q is not yet fully known, however, elevated AF1q expression is associated with poor clinical outcomes in various malignancies. Here, we show that AF1q specifically binds to T-cell-factor-7 (TCF7) in the Wnt signaling pathway and results in transcriptional activation of CD44 as well as multiple downstream targets of the TCF7/LEF1. In addition, enhanced AF1q expression promotes breast cancer cell proliferation, migration, mammosphere formation, and chemo-resistance. In xenograft models, enforced AF1q expression in breast cancer cells also promotes liver metastasis and lung colonization. In a cohort of 63 breast cancer patients, higher percentages of AF1q-positive cancer cells in primary sites were associated with significantly poorer overall survival (OS), disease-free survival (DFS), and brain metastasis-free survival (b-MFS). Using paired primary/metastatic samples from the same patients, we demonstrate that AF1q-positive breast cancer cells become dynamically dominant in the metastatic sites compared to the primary sites. Our findings indicate that breast cancer cells with a hyperactive AF1q/TCF7/CD44 regulatory axis in the primary sites may represent “metastatic founder cells” which have invasive properties.
Arg753Gln Polymorphisms in Toll-Like Receptor 2 Gene are Associated with Tuberculosis Risk: A Meta-Analysis

Background Numerous epidemiological studies have reported the association between polymorphisms of Toll-like receptor 2 (TLR2) and susceptibility to tuberculosis (TB). However, the results remain inconclusive. Therefore, we performed a quantitative meta-analysis to evaluate associations between the polymorphism of Arg753Gln of the TLR2 gene and susceptibility to TB. Material/Methods Three databases (PubMed, CNKI and Embase) were systematically searched for eligible studies. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) as our index were used to assess the relation between the TLR2 gene Arg753Gln polymorphism and risk of TB. Overall and subgroup analyses were conducted according to the available information. Results With a detailed selection, 7 eligible studies with 1486 cases and 1322 controls were identified in our meta-analysis. There was a significant difference between TLR2 gene Arg753Gln polymorphism and the risk of TB (additive model: P<0.01, OR=2.89, 95% CI: 2.13–3.91; GA vs. GG: P<0.01, OR=2.92, 95% CI: 2.09–4.08). Interestingly, subgroup analysis based on ethnicity indicated that TB risk was significantly increased in Asians (additive model: P<0.01, OR=3.17, 95% CI: 2.31–4.35; GA vs. GG: P<0.01, OR=3.29, 95% CI: 2.32–4.68); by contrast, there was no association found in whites (additive model: P=0.40, OR=0.57, 95% CI: 0.15–2.13; GA vs. GG: P=0.40, OR=0.57, 95% CI: 0.15–2.13). Conclusions Our meta-analysis provides evidence that the TLR2 gene Arg753Gln polymorphism is a risk factor to TB, especially in Asian populations.
Thermally optimal stop-go scheduling of task graphs with real-time constraints

Dynamic thermal management (DTM) techniques to manage the load on a system to avoid thermal hazards are soon becoming mainstream in today's systems. With the increasing percentage of leakage power, switching off the processors is becoming a viable alternative technique to speed scaling. For real-time applications, it is crucial that under such techniques the system still meets the performance constraints. In this paper we study stop-go scheduling to minimize peak temperature when scheduling an application, modeled as a task-graph, within a given makespan constraint. For a given static-ordering of execution of the tasks, we derive the optimal schedule referred to as the JUST schedule. We prove that for periodic task-graphs, the optimal temperature is independent of the chosen static-ordering when following the proposed JUST schedule. Simulation experiments validate the theoretical results.
Accurate Digital Synthesis of Sinewaves

This paper discusses the digital synthesis of spectrally pure sinusoidal signals. A modified Sigma-Delta topology consisting of a digital-to-analog converter (DAC), an analog-to-digital converter (ADC), and an analog filter is adopted to efficiently estimate and compensate the DAC nonidealities while desensitizing the system to those of the remaining elements. The proposed correction procedure was implemented on a digital signal processing board equipped with general-purpose data converters. It is shown that the technique can improve the spurious-free dynamic range of the generated signals without requiring high-performance measurement equipment.
Executive Function Development and Early Mathematics: Examination of Dual Language Learners.

This study examined the convergent validity between a third-party rating scale of executive function (EF) and a task-performance measurement of EF; examined the effects of age, gender, and dual language experience on preschool children‘s EF skills (inhibition, working memory (WM), and shifting) and on early mathematical skills; and investigated the contributions of inhibition, WM, and shifting to early mathematical skills. Ninety-two children attending Head Start were assessed. Correlation analyses revealed a number of relationships between the EF rating scale and the EF taskperformance measure. A multivariate analysis of variance revealed a main effect of age on all EF measures and the math assessment and a significant difference between language groups on the measures of inhibition and shifting. Finally, hierarchal regression analyses revealed that WM and inhibition made unique contributions to children‘s early mathematical skills, and vocabulary scores made more contribution to early mathematical skills than either inhibition or WM. These findings extend previous research by (a) highlighting the issues involved with the assessment of EF in young children; (b) further supporting findings of preschool age-related changes in EF; (c) demonstrating EF differences with a DLL population; and (d) highlighting the importance of WM, inhibition, and language to mathematical learning, demonstrating the effects in early childhood. Implications of these findings for EF assessment in young children and prekindergarten curricula are discussed. iii Acknowledgements I would never have been able to finish my dissertation without the guidance of my advisors, help from my mother, and support from my husband. I would like to express my thanks to my advisor, Dr. Toni Linder, for her guidance, and for providing me with the opportunity to conduct this research project as part of the math grant. I would like to thank my other advisor, Dr. Gloria Miller, for her endless support and effort to nominate me for the Graduate Dissertation Research Award. I also extend my gratitude to my other committee members, Dr. Duan Zhang, who provided wonderful feedback regarding my methodologies, and Dr. Karen Riley, for guidance and support throughout my doctoral program. I would also like to thank Dr. Phil Zelazo for his generous offer to let me use the NIH Toolbox measures and for engaging in a conversation with me about my research. I would especially like to thank my mother, Betsy Allen, for her enduring support of my endeavors to complete my doctoral degree. She has provided feedback on many drafts of my dissertation and engaged in countless thoughtful conversations regarding my research. Finally, I bestow my deepest appreciation to my husband, Brett Harvey, for his encouragement, support, and patience throughout this process. I admire his ability to forge ahead in many outdoor activities without me and to give me the space and time that I have needed to complete this dissertation.
Learning to segment dense cell nuclei with shape prior

We study the problem of segmenting multiple cell nuclei from GFP or Hoechst stained microscope images with a shape prior. This problem is encountered ubiquitously in cell biology and developmental biology. Our work is motivated by the observation that segmentations with loose boundary or shrinking bias not only jeopardize feature extraction for downstream tasks (e.g. cell tracking), but also prevent robust statistical analysis (e.g. modeling of fluorescence distribution). We therefore propose a novel extension to the graph cut framework that incorporates a “blob”-like shape prior. The corresponding energy terms are parameterized via structured learning. Extensive evaluation and comparison on 2D/3D datasets show substantial quantitative improvement over other state-of-the-art methods. For example, our method achieves an 8.2% Rand index increase and a 4.3 Hausdorff distance decrease over the second best method on a public hand-labeled 2D benchmark.
Topical chemoprevention of skin cancer in mice, using combined inhibitors of 5-lipoxygenase and cyclo-oxygenase-2

Abstract Objective: Skin cancer is the most common cancer, and often occurs in the head and neck region. This study aimed to investigate whether a combination of inhibitors of cyclo-oxygenase-2 and 5-lipoxygenase, applied via a microemulsion delivery system, would be effective in topically inhibiting skin carcinogenesis. Study design: Randomised animal study. Methods: Twenty-four nude mice were intradermally inoculated with carcinoma cells and then divided into three groups (eight animals each): group one received no treatment; group two received celecoxib alone; and group three received a combination of zileuton and celecoxib. Tumour incidence and growth were measured for 14 days. Results: Both treatments significantly delayed the onset and development of tumours. However, the combined treatment had the best response (p < 0.01). Conclusion: The results clearly showed that topical treatment with either celecoxib alone or celecoxib plus zileuton significantly inhibited skin carcinogenesis, and that a combination of both agents had the best results.
Semi-supervised Modeling of Social Actions in Online Dialogue

The emergence of discussion and debate on social media necessitates the development of new models for processing dialogue. Vitally important to inferring the social implicatures of dialogue on social media is to understand the social goals and desires of the participants. Thus, to infer social implicatures methods for capturing the social goals and intentions of the participants must be first developed. In this paper, we propose a set of fifteen social acts to infer the social goals of dialogue participants. Social acts capture the complex social actions individuals signal through their utterances. We present a semi-supervised algorithm called the Social Act Conversation Model (SACM) for the fifteen social acts. The algorithm is based on the premise that linguistic expressions in social dialogue relate directly to the topic being discussed or to the social actions of the participants. We show that incorporating the social acts identified by the SACM with existing pattern-based identification can increase the performance in inferring social implicatures (adversarial behavior, pursuing power, and leadership) for online dialogue communicated in English, Arabic, and Chinese.
How Children Learn the Meaning of Words and How LSA Does It ( Too )

For long psycholinguistics has tried to answer the question “how children learn the meaning of words? ” Paul Bloom answers the question in his book with the same title. He argues that the mind does not have a module for language acquisition. Instead, children learn the meaning of words by a set of general cognitive abilities, including the ability to infer intentions, to perceive the world in terms of objects and events, and the ability to understand syntactic structures. As discourse psychologists we have to emphasize that children likely do not learn the meaning of words through learning words. Instead, it seems more likely that the meaning of words is acquired through discourse. Discourse can take the form of conversations by oneself, with others or by others, situated in time and space. In fact, one could argue that children learn—at least in part—words solely by understanding their relation in context. This is how some computational techniques approximate the meaning of words, sentences, paragraphs and texts. One such common technique is Latent Semantic Analysis (LSA). LSA is a statistical, corpus-based, technique for representing world knowledge. It computes similarity comparisons for terms and documents by taking advantage of the fact that particular words occur in particular documents. LSA takes quantitative information about co-occurrences of words in documents (paragraphs and sentences) and translates this into an multidimensional space. In short, the input of LSA is a large coTHE JOURNAL OF THE LEARNING SCIENCES, 14(2), 301–309 Copyright © 2005, Lawrence Erlbaum Associates, Inc.
MobLab : A Mobility Emulation Platform

Mobility powered systems provide the core routing mechanism in many ad-hoc and delay tolerant networks. Evaluating such systems under real life scenarios is often not practical because they involve multiple moving participants over a wide area. As a result, the principal way these systems are evaluated is though discrete event simulators that are often specific to the system at hand. While these systems provide a valid way to test ideas, and get some numbers, they often require systems to be built towards the simulation platform rather than deployment. As a result, researchers often stop at simulation. MobLab provides a mobility emulation platform for evaluating systems, while still working towards deployment. By providing an easy way to iteratively debug and evaluate production ready code, MobLab enables developers to deploy their mobility powered systems as soon as they are done evaluating them, rather than going through a different phase of implementing a simulation result. Our system can utilize mobility models or recoded traces to drive node mobility in the system, and provides a simple way for aggregating and presenting emulation results. MobLab is built on top of EmuLab, a network emulation platform, and has been successfully used to evaluate two mobility based systems.
Monodisperse hard rods in external potentials.

We consider linear arrays of cells of volume V(c) populated by monodisperse rods of size σV(c),σ=1,2,. , subject to hardcore exclusion interaction. Each rod experiences a position-dependent external potential. In one application we also examine effects of contact forces between rods. We employ two distinct methods of exact analysis with complementary strengths and different limits of spatial resolution to calculate profiles of pressure and density on mesoscopic and microscopic length scales at thermal equilibrium. One method uses density functionals and the other statistically interacting vacancy particles. The applications worked out include gravity, power-law traps, and hard walls. We identify oscillations in the profiles on a microscopic length scale and show how they are systematically averaged out on a well-defined mesoscopic length scale to establish full consistency between the two approaches. The continuum limit, realized as V(c)→0,σ→∞ at nonzero and finite σV(c), connects our highest-resolution results with known exact results for monodisperse rods in a continuum. We also compare the pressure profiles obtained from density functionals with the average microscopic pressure profiles derived from the pair distribution function.
Accelerated cover selection steganography

Information hiding represents a constantly growing field mainly consisting of digital watermarking and steganography. Both deal with inserting additional information into multimedia. Basically, watermarking protects the multimedia content against unauthorized manipulation whereas steganography utilizes multimedia in the role of a cover object for unauthorized secret message transmission. This article deals with additional technique to steganography which can decrease an impact to cover image after an embedding process. The goal is to find an optimal image from a cover image database based on bits of the secret message. With 2,000 image database, cover selection method can decrease impact by 10% in comparison to the same embedding method without cover selection. Disadvantage lays in a time consumption. In this article, there is proposed a novel accelerated cover selection method. Acceleration is achieved by optimal shortening of a secret message for comparative process.
Atomic force microscopy: Studying mechanical properties of a cell

Atomic force microscopy (AFM) is a modern imaging technique that generates height representations of a sample surface with subnanometer resolution. Since 1986 it has evolved into a versatile tool which also provides maps of elastic and viscoelastic properties. AFM offers the opportunity to image samples with or without treatment in various environments. Aim of this work is a short description of the relatively new ways of studying mechanical properties of cells – Peak Force Tapping, Stiffness Tomography. Both represent new approaches to obtaining or analysing force-distance curve which are essential for calculating mechanical characteristic of a sample.
LiU: Hiding Disk Access Latency for HPC Applications with a New SSD-Enabled Data Layout

Unlike in the consumer electronics and personal computing areas, in the HPC environment hard disks can hardly be replaced by SSDs. The reasons include hard disk's large capacity, very low price, and decent peak throughput. However, when latency dominates the I/O performance (e.g., when accessing random data), the hard disk's performance can be compromised. If the issue of high latency could be effectively solved, the HPC community would enjoy a large, affordable and fast storage without having to replace disks completely with expensive SSDs. In this paper, we propose an almost latency-free hard-disk dominated storage system called LiU for HPC. The key technique is leveraging limited amount of SSD storage for its low-latency access, and changing data layout in a hybrid storage hierarchy with low-latency SSD at the top and high-latency hard disk at the bottom. If a segment of data would be randomly accessed, we lift its top part (the head) up in the hierarchy to the SSD and leave the remaining part (the body) untouched on the disk. As a result, the latency of accessing this whole segment can be removed because access latency of the body can be hidden by the access time of the head on the SSD. Combined with the effect of prefetching a large segment, LiU (Lift it Up) can effectively remove disk access latency so disk's high peak throughput can now be fully exploited for data-intensive HPC applications. We have implemented a prototype of LiU in the PVFS parallel file system and evaluated it with representative MPI-IO micro benchmarks, including MPI-IO-test, mpi-tile-io, and ior-mpi-io, and one macro-benchmark BTIO. Our experimental results show that LiU can effectively improve the I/O performance for HPC applications, with the throughput improvement ratio up to 5.8. Furthermore, LiU can bring much more benefits to sequential-I/O MPI applications when the applications are interfered by other workloads. For example, LiU improves the I/O throughput of mpi-io-test, which is under interference, by 1.1-3.4 times, while improving the same workload without interference by 15%.
Mobile Active‐Vision Traffic Surveillance System for Urban Networks

Abstract: This article discusses the development of a mobile bus‐mounted machine vision system for transit and traffic monitoring in urban corridors, as required by intelligent transportation systems. In contrast to earlier machine vision technologies used for traffic management, which rely mainly on fixed‐point detection and simpler algorithms to detect certain traffic characteristics, the new proposed approach makes use of a recent trend in computer vision research; namely, the active vision paradigm. Active vision systems have mechanisms that can actively control camera parameters such as orientation, focus, zoom, and vergence in response to the requirements of the task and external stimuli. Mounting active vision systems on buses will have the advantage of providing real‐time feedback of the current traffic conditions, while possessing the intelligence and visual skills that allow them to interact with a rapidly changing dynamic environment, such as moving traffic and continuously changing image background.
Phylogenetic Analysis of Covariance by Computer Simulation

Biologists often compare average phenotypes of groups of species defined cladistically or on behavioral, ecological, or physiological criteria (e.g., carnivores vs. herbivores, social vs. nonsocial species, endotherms vs. ectotherms). Hypothesis testing typically is accomplished via analysis of variance (ANOVA) or covariance (ANCOVA; often with body size as a covariate). Because of the hierarchical nature of phylogenetic descent, however, species may not represent statistically independent data points, degrees of freedom may be inflated, and significance levels derived from conventional tests cannot be trusted. As one solution to this degrees of freedom problem, we propose using empirically scaled computer simulation models of continuous traits evolving along «known» phylogenetic trees to obtain null distributions of F statistics for ANCOVA of comparative data sets
Skin disease analysis and tracking based on image segmentation

Tracking of the skin disease is a necessary step of diagnostic as well the measure of the wound's surface is very useful in healing's document. To overcome the difficulties of the skin illness's estimation, encountered with the currently used measurement techniques, we propose a novel approach aiming to reduce the time-consuming and the error rate. The proposed method is based on two steps; the first step is a preprocessing one which consists in image segmentation to detect the edge of the infected skin region. In the second one, another proposed method is applied to measure the wound `size' and control the illness evolution. In this work, a comparative study was realized to select the most suitable segmentation technique referred to a proposed criterion based on `edge accuracy' EAC. The new criterion was compared with the `surface accuracy' based on ROC1 space. The experiments show the performance of the proposed criterion and the efficacy of the measurement technique.