Miracle-dz/UniFAR-FTUs huggingface dataset:
Chromosome 6p22 locus associated with clinically aggressive neuroblastoma.

BACKGROUND Neuroblastoma is a malignant condition of the developing sympathetic nervous system that most commonly affects young children and is often lethal. Its cause is not known. METHODS We performed a genomewide association study by first genotyping blood DNA samples from 1032 patients with neuroblastoma and 2043 control subjects of European descent using the Illumina HumanHap550 BeadChip. Samples from three independent groups of patients with neuroblastoma (a total of 720 patients) and 2128 control subjects were then genotyped to replicate significant associations. RESULTS We observed a significant association between neuroblastoma and the common minor alleles of three consecutive single-nucleotide polymorphisms (SNPs) at chromosome band 6p22 and containing the predicted genes FLJ22536 and FLJ44180 (P=1.71x10(-9) to 7.01x10(-10); allelic odds ratio, 1.39 to 1.40). Homozygosity for the at-risk G allele of the most significantly associated SNP, rs6939340, resulted in an increased likelihood of the development of neuroblastoma (odds ratio, 1.97; 95% confidence interval, 1.58 to 2.45). Subsequent genotyping of the three 6p22 SNPs in three independent case series confirmed our observation of an association (P=9.33x10(-15) at rs6939340 for joint analysis). Patients with neuroblastoma who were homozygous for the risk alleles at 6p22 were more likely to have metastatic (stage 4) disease (P=0.02), amplification of the MYCN oncogene in the tumor cells (P=0.006), and disease relapse (P=0.01). CONCLUSIONS A common genetic variation at chromosome band 6p22 is associated with susceptibility to neuroblastoma.
Model checking procedures for infinite state systems

The paper depicts experiments and results with predicate abstraction based verification applied to infinite state systems. Predicate abstraction is a method for automatic construction of abstract state space that can be used by any common finite state model checking tool, such as NuSMV. We have used abstract state space and NuSMV tool to verify safety properties of infinite state mutual exclusion protocols. Even though predicate abstraction allows model checking against a restricted class of temporal logic formulas, we have shown that the restricted class is expressive enough to specify basic safety properties. Our experiments were conducted on Bakery and Fischer mutual exclusion protocols
Rearing Room Affects the Non-dominant Chicken Cecum Microbiota, While Diet Affects the Dominant Microbiota

The combined effect of environment and diet in shaping the gut microbiota remains largely unknown. This knowledge, however, is important for animal welfare and safe food production. For these reasons, we determined the effect of experimental units on the chicken cecum microbiota for a full factorial experiment where we tested the combined effect of room, diet, and antimicrobial treatment. By Illumina Deep sequencing of the 16S rRNA gene, we found that diet mainly affected the dominant microbiota, while the room as a proxy for environment had major effects on the non-dominant microbiota (p = 0.006, Kruskal–Wallis test). We, therefore, propose that the dominant and non-dominant microbiotas are shaped by different experimental units. These findings have implications both for our general understanding of the host-associated microbiota and for setting up experiments related to specific targeting of pathogens.
Seeing into a Public Cloud: Monitoring the Massachusetts Open Cloud

Cloud users today have little visibility into the performance characteristics, power consumption, and utilization of cloud resources; and the cloud has little visibility into user application performance requirements and critical metrics such as response time and throughput. This paper outlines new efforts to reduce the information gap between the cloud users and the cloud. We first present a scalable monitoring platform to collect and retain rich information on a regional public cloud. Second, we present two motivating use cases that leverage the collected information: (1) Participation in emerging smart grid demand response programs in order to reduce datacenter energy costs and stabilize power grid demands, (2) budgeting available power to applications via peak shaving. This work is done in the context of the Massachusetts Open Cloud (MOC), a new public cloud project that has a central goal of enabling cloud research.
Autophagy-related gene 12 (ATG12) is a novel determinant of primary resistance to HER2-targeted therapies: Utility of transcriptome analysis of the autophagy interactome to guide breast cancer treatment

The autophagic process, which can facilitate breast cancer resistance to endocrine, cytotoxic, and molecularly targeted agents, is mainly regulated at the post-translational level. Although recent studies have suggested a possible transcriptome regulation of the autophagic genes, little is known about either the analysis tools that can be applied or the functional importance of putative candidate genes emerging from autophagy-dedicated transcriptome studies. In this context, we evaluated whether the constitutive activation of the autophagy machinery, as revealed by a transcriptome analysis using an autophagy-focused polymerase chain reaction (PCR) array, might allow for the identification of novel autophagy-specific biomarkers for intrinsic (primary) resistance to HER2-targeted therapies. Quantitative real-time PCR (qRT-PCR)-based profiling of 84 genes involved in autophagy revealed that, when compared to trastuzumab-sensitive SKBR3 cells, the positive regulator of autophagic vesicle formation ATG12 (autophagy-related gene 12) was the most differentially up-regulated gene in JIMT1 cells, a model of intrinsic cross-resistance to trastuzumab and other HER1/2-targeting drugs. An analysis of the transcriptional status of ATG12 in > 50 breast cancer cell lines suggested that the ATG12 transcript is commonly upregulated in trastuzumab-unresponsive HER2-overexpressing breast cancer cells. A lentiviral-delivered small hairpin RNA stable knockdown of the ATG12 gene fully suppressed the refractoriness of JIMT1 cells to trastuzumab, erlotinib, gefitinib, and lapatinib in vitro. ATG12 silencing significantly reduced JIMT1 tumor growth induced by subcutaneous injection in nude mice. Remarkably, the outgrowth of trastuzumab-unresponsive tumors was prevented completely when trastuzumab treatment was administered in an ATG12-silenced genetic background. We demonstrate for the first time the usefulness of low-density, autophagy-dedicated qRT-PCR-based platforms for monitoring primary resistance to HER2-targeted therapies by transcriptionally screening the autophagy interactome. The degree of predictive accuracy warrants further investigation in the clinical situation.
Exposure to a Low Pathogenic A/H7N2 Virus in Chickens Protects against Highly Pathogenic A/H7N1 Virus but Not against Subsequent Infection with A/H5N1

Recent evidences have demonstrated that the presence of low pathogenic avian influenza viruses (LPAIV) may play an important role in host ecology and transmission of avian influenza viruses (AIV). While some authors have clearly demonstrated that LPAIV can mutate to render highly pathogenic avian influenza viruses (HPAIV), others have shown that their presence could provide the host with enough immunological memory to resist re-infections with HPAIV. In order to experimentally study the role of pre-existing host immunity, chickens previously infected with H7N2 LPAIV were subsequently challenged with H7N1 HPAIV. Pre-infection of chickens with H7N2 LAPIV conferred protection against the lethal challenge with H7N1 HPAIV, dramatically reducing the viral shedding, the clinical signs and the pathological outcome. Correlating with the protection afforded, sera from chickens primed with H7N2 LPAIV reacted with the H7-AIV subtype in hemagglutination inhibition assay and specifically with the N2-neuraminidase antigen. Conversely, subsequent exposure to H5N1 HPAIV resulted in a two days-delay on the onset of disease but all chickens died by 7 days post-challenge. Lack of protection correlated with the absence of H5-hemagglutining inhibitory antibodies prior to H5N1 HPAIV challenge. Our data suggest that in naturally occurring outbreaks of HPAIV, birds with pre-existing immunity to LPAIV could survive lethal infections with HA-homologous HPAIV but not subsequent re-infections with HA-heterologous HPAIV. These results could be useful to better understand the dynamics of AIV in chickens and might help in future vaccine formulations.
Stereoscopic image generation based on depth images

A depth-image-based rendering system for generating new views is proposed. One important aspect of the proposed system is that the depth maps are pre-processed using an asymmetric filter to smoothen the sharp changes in depth at object boundaries. In addition to ameliorating the effects of blocky artifacts and other distortions contained in the depth maps, the smoothing reduces or completely removes disocclusion areas where potential artifacts can arise from image warping which is needed to generate images from new viewpoints. The asymmetric nature of the filter reduces the amount of geometric distortion that might be perceived otherwise. We present some results to show that the proposed system provides an improvement in image quality of stereoscopic virtual views while maintaining reasonably good depth quality.
4-Hydroxy-nonenal—A Bioactive Lipid Peroxidation Product

This review on recent research advances of the lipid peroxidation product 4-hydroxy-nonenal (HNE) has four major topics: I. the formation of HNE in various organs and tissues, II. the diverse biochemical reactions with Michael adduct formation as the most prominent one, III. the endogenous targets of HNE, primarily peptides and proteins (here the mechanisms of covalent adduct formation are described and the (patho-) physiological consequences discussed), and IV. the metabolism of HNE leading to a great number of degradation products, some of which are excreted in urine and may serve as non-invasive biomarkers of oxidative stress.
Toward Real-Time Continuous System Simulation for Interactive Environments

Algorithms for real-time simulation of continuous physical systems, such as realistic deformable objects, are an important research frontier for the building of complex interactive virtual environments. Many applications stand to benefit including biomedical simulation, virtual assembly (and destructive disassembly), haptic rendering, robotic manipulation, character animation, and virtual training.
Modeling the Tortuosity of Retinal Vessels: Does Caliber Play a Role?

The tortuosity of retinal blood vessels is a diagnostic parameter assessed by ophthalmologists on the basis of examples and experience; no quantitative model is specified in clinical practice. All quantitative measures proposed to date for automatic image analysis purposes are functions of the curvature of the vessel skeleton. We suggest in this paper that curvature may not be the only quantity involved in modeling tortuosity, and that vessel thickness, or caliber, may also play a role. To support this statement, we devise a novel measure of tortuosity, depending on both curvature and thickness, and test it with 200 vessels selected by our clinical author from the public digital retinal images for vessel extraction database. Results are in good accordance with clinical judgment. Comparative experiments show performance similar to or better than that of four measures reported in the literature. We conclude that there is reasonable evidence supporting the investigation of tortuosity models incorporating more measurements than just skeleton curvature, and specifically vessel caliber.
Elitism-based compact genetic algorithms

This paper describes two elitism-based compact genetic algorithms (cGAs)-persistent elitist compact genetic algorithm (pe-cGA), and nonpersistent elitist compact genetic algorithm (ne-cGA). The aim is to design efficient cGAs by treating them as estimation of distribution algorithms (EDAs) for solving difficult optimization problems without compromising on memory and computation costs. The idea is to deal with issues connected with lack of memory by allowing a selection pressure that is high enough to offset the disruptive effect of uniform crossover. The pe-cGA finds a near optimal solution (i.e., a winner) that is maintained as long as other solutions generated from probability vectors are no better. The ne-cGA further improves the performance of the pe-cGA by avoiding strong elitism that may lead to premature convergence. It also maintains genetic diversity. This paper also proposes an analytic model for investigating convergence enhancement.
Incorporation of a variational registration method into a spectroscopy tool

This work describes the incorporation of a variational image registration algorithm into an interactive medical tool to support clin- ical decision about treatment of brain pathologies. Through the com- bination of anatomical (Magnetic Resonance Images, MRI), functional (Positron Emission Tomography, PET) and molecular images (Chem- ical Shift Imaging, CSI) clinicians can determine the best therapeutic strategy in every case. First, MRI images and CSI are co-registered and analysed in order to create colour maps related with the concentration of metabolites in the brain. Then, PET and MRI are also registered since it allows knowing the metabolic functionality of the brain. The improve- ment of the Correlation Ratio (CR), the Structural SIMilarity (SSIM) and the Mutual Information (MI) shows the performance of the varia- tional registration method which is at least two times faster than other approaches in the spatial domain. The goal of this tool is to provide surgeons as much information as possible to perform biopsies and/or surgeries.
Cortical Correlates of Human Motion Perception Biases

Human sensory perception is not a faithful reproduction of the sensory environment. For example, at low contrast, objects appear to move slower and flicker faster than veridical. Although these biases have been observed robustly, their neural underpinning is unknown, thus suggesting a possible disconnect of the well established link between motion perception and cortical responses. We used functional imaging to examine the encoding of speed in the human cortex at the scale of neuronal populations and asked where and how these biases are encoded. Decoding, voxel population, and forward-encoding analyses revealed biases toward slow speeds and high temporal frequencies at low contrast in the earliest visual cortical regions, matching perception. These findings thus offer a resolution to the disconnect between cortical responses and motion perception in humans. Moreover, biases in speed perception are considered a leading example of Bayesian inference because they can be interpreted as a prior for slow speeds. Therefore, our data suggest that perceptual priors of this sort can be encoded by neural populations in the same early cortical areas that provide sensory evidence.
Evidence for Representations of Perceptually Similar Natural Categories by 3-Month-Old and 4-Month-Old Infants

The paired-preference procedure was used in a series of experiments to explore the abilities of infants aged 3 and 4 months to categorize photographic exemplars from natural (adult-defined) basic-level categories. The question of whether the categorical representations that were evidenced excluded members of a related, perceptually similar category was also investigated. Experiments 1–3 revealed that infants could form categorical representations for dogs and cats that excluded birds. Experiment 4 showed that the representation for cats also excluded dogs, but that the representation for dogs did not exclude cats. However, a supplementary experiment showed that the representation for dogs did exclude cats when the variability of the dog exemplars was reduced to match that of the cat exemplars. The results are discussed in terms of abilities necessary for the formation of more complex categorical representations.
Incorporating pitch features for tone modeling in automatic recognition of Mandarin Chinese

Tone plays a fundamental role in Mandarin Chinese, as it plays a lexical role in determining the meanings of words in spoken Mandarin. For example, these two sentences R R (I like horses) and R M (I like to scold) differ only in the tone carried by the last syllable. Thus, the inclusion of tone-related information through analysis of pitch data should improve the performance of automatic speech recognition (ASR) systems on Mandarin Chinese. The focus of this thesis is to improve the performance of a non-tonal automatic speech recognition (ASR) system on a Mandarin Chinese corpus by implementing modifications to the system code to incorporate pitch features. We compile and format a Mandarin Chinese broadcast new corpus for use with the ASR system, and implement a pitch feature extraction algorithm. Additionally, we investigate two algorithms for incorporating pitch features in Mandarin Chinese speech recognition. Firstly, we build and test a baseline tonal ASR system with embedded tone modeling by concatenating the cepstral and pitch feature vectors for use as the input to our phonetic model (a Hidden Markov Model, or HMM). We find that our embedded tone modeling algorithm does improve performance on Mandarin Chinese, showing that including tonal information is in fact contributive for Mandarin Chinese speech recognition. Secondly, we implement and test the effectiveness of HMM-based multistream models. VI-A Company Thesis Supervisor: Wade Shen M.I. T. Thesis Supervisor: Robert C. Berwick Title: Professor
On the global stability of periodic Ricker maps

We find the exact region of global stability for the 2-periodic Ricker difference equation, showing that a 2-periodic solution is globally asymptotically stable whenever it is locally asymptotically stable and the equation does not have more 2-periodic solutions. We conjecture that this property holds for the general p-periodic Ricker difference equation, and in particular we prove it for p = 3.
Orthogonal series and limit theorems for canonical U- and V-statistics of stationary connected observations

The limit behavior is studied for the distributions of normalized U and V statistics of an arbitrary order with canonical (degenerate) kernels, based on samples of increasing sizes from a stationary sequence of observations satisfying φor α-mixing. The corresponding limit distributions are represented as infinite multilinear forms of a centered Gaussian sequence with a known covariance matrix. keywords: stationary sequence of random variables, mixing, multiple orthogonal series, canonical U and V -statistics.
Sleep monitoring tools at home and in the hospital: Bridging quantified self and clinical sleep research

The quantified self movement suggests solutions for diverse long-term measurements, including sleep monitoring. However, those solutions do not seem to meet the challenges facing clinical sleep research. Where efforts in the past to describe design frameworks for sleep monitoring tools focused on the sleeper as user, we start from the sleep clinician to find out how sleep monitoring tools can be meaningful in clinical settings. Based on observations in hospital-based sleep centers performing traditional and ambulatory sleep studies, we describe current practices and look at the effect when measurements leave the hospital. We summarize design recommendations for sleep monitoring tools, suitable in and outside the hospital, from the sleep clinician's perspective. Furthermore, we discuss a future for sleep research where quantified self tools and approaches expand clinical sleep research. This would allow hospital-based sleep centers to deploy current practices in a targeted, meaningful, and accountable way.
MULTI-PARAMETER BASED PERFORMANCE EVALUATION OF CLASSIFICATION ALGORITHMS

Diabetes disease is amongst the most common disease in India. It affects patient’s health and also leads to other chronic diseases. Prediction of diabetes plays a significant role in saving of life and cost. Predicting diabetes in human body is a challenging task because it depends on several factors. Few studies have reported the performance of classification algorithms in terms of accuracy. Results in these studies are difficult and complex to understand by medical practitioner and also lack in terms of visual aids as they are presented in pure text format. This reported survey uses ROC and PRC graphical measures to improve understanding of results. A detailed parameter wise discussion of comparison is also presented which lacks in other reported surveys. Execution time, Accuracy, TP Rate, FP Rate, Precision, Recall, F Measure parameters are used for comparative analysis and Confusion Matrix is prepared for quick review of each algorithm. Ten fold cross validation method is used for estimation of prediction model. Different sets of classification algorithms are analyzed on diabetes dataset acquired from UCI repository.
Strategic Decision Models: Multiple Perceptions, Unifying Structure

Real estate involvements include citizenship responsibility, personal and business space use, investment, and for those whose work involvement is directly or indirectly dependent upon real estate markets, employment. Real estate strategies guide participants' decisionmaking in their multiple roles, and both highlight the issues and concerns common to these multiple roles as well as isolate those unique to particular roles. Although certain aspects of the decision processes for different participants in their multiple roles reflect the actions, circumstances and objectives unique to that participant, a meaningful part of everyone's real estate decisionmaking process is subject to common market forces. Strategic decision models provide a means to connect the micro-level tasks of property operations, the negotiation process of real estate transactions, and the larger forces that define space use and place decisions.
Repeated failures that led to the eventual success in human evolution.

The effective population number estimated in humans is 10,000 (Nei and Gram1984; Nei 1987; Takahata 1993 ) . This rather small number may contradict the fact that humans had been occupying vast areas in Africa and Eurasia for a long time since Homo erectus first migrated out of Africa l-2 Mya (e.g., see Lewin 1984; Fagan 1990). One possible cause is a recent bottleneck, or a sudden reduction in population size, but a severe bottleneck is incompatible with the unusual polymorphism at the major histocompatibility complex (Mhc) loci (Takahata 1990; Klein et al. 1993). In this letter, I argue that a more likely cause is frequent extinction and recolonization (turnover) of subpopulations in the lineage leading to modern humans. Wright ( 193 1) introduced the concept of effective population number (N,) in order to reduce complicated breeding structure in actual populations to the equivalent ideal case (Crow and Kimura 1970, p. 345 ) . In an ideal population, N, is equal to the number of breeding individuals, whereas in an actual population N, depends on various factors such as sex ratio, differences in offspring numbers, temporal changes in population size, and overlapping generations (for review, see Wright 1969). Wright ( 1969) also pointed out that if ( 1) a species has subdivided population structure and (2) local populations are liable to frequent extinction with restoration of a few stray immigrants, the species passes repeatedly through extremely reduced states of N,. Slatkin ( 1977), as well as Maruyama and Kimura ( 1980), formulated this problem on the basis of a traditional approach in population genetics: that is, to use the variance of gene frequencies and the probability of identity between two randomly chosen genes. Maruyama and Kimura ( 1980) derived formulas of N, under the finiteisland model of population structure (Malecot 195 1; Maruyama 1970) and the stepping-stone model (Kimura and Weiss 1964). Their approximate formula for a diploid species in the finite-island model is given by