Miracle-dz/UniFAR-FTUs huggingface dataset:
No Blog is an Island - Analyzing Connections Across Information Networks

There are multiple information and social networks among individuals, from telephone to email, web, blog, instant message (IM) and chat networks. Prior work has studied each of these individual networks quite extensively, including telephone networks [7], postal network [20], web communities [17], and so on. Still, what is of great interest is how these networks collide and interact with each other. Each individual has presence in multiple networks and it will be of interest to understand how the references and presence in one affects that in the others. Previously such studies would have been difficult to do since each source of data was often “owned” by a specific entity. Blogs now provide a unique, public source of data that naturally provides visibility into multiple networks. For example, blog entries cite web pages, blogs have friends and communities, as well as blog profiles that have links to email, IM and other networks. In this paper, we use the blogs as a starting point to pull in data about these multiple networks and study how these multiple networks interact with each other. While much of the connections are within specific networks, there is still a wealth of information, structure and form to the connections across these networks as our analyses show.
Cooperative Co-Evolution With Differential Grouping for Large Scale Optimization

Cooperative co-evolution has been introduced into evolutionary algorithms with the aim of solving increasingly complex optimization problems through a divide-and-conquer paradigm. In theory, the idea of co-adapted subcomponents is desirable for solving large-scale optimization problems. However, in practice, without prior knowledge about the problem, it is not clear how the problem should be decomposed. In this paper, we propose an automatic decomposition strategy called differential grouping that can uncover the underlying interaction structure of the decision variables and form subcomponents such that the interdependence between them is kept to a minimum. We show mathematically how such a decomposition strategy can be derived from a definition of partial separability. The empirical studies show that such near-optimal decomposition can greatly improve the solution quality on large-scale global optimization problems. Finally, we show how such an automated decomposition allows for a better approximation of the contribution of various subcomponents, leading to a more efficient assignment of the computational budget to various subcomponents.
Phase-sensitive and recognition-boosted speech separation using deep recurrent neural networks

Separation of speech embedded in non-stationary interference is a challenging problem that has recently seen dramatic improvements using deep network-based methods. Previous work has shown that estimating a masking function to be applied to the noisy spectrum is a viable approach that can be improved by using a signal-approximation based objective function. Better modeling of dynamics through deep recurrent networks has also been shown to improve performance. Here we pursue both of these directions. We develop a phase-sensitive objective function based on the signal-to-noise ratio (SNR) of the reconstructed signal, and show that in experiments it yields uniformly better results in terms of signal-to-distortion ratio (SDR). We also investigate improvements to the modeling of dynamics, using bidirectional recurrent networks, as well as by incorporating speech recognition outputs in the form of alignment vectors concatenated with the spectral input features. Both methods yield further improvements, pointing to tighter integration of recognition with separation as a promising future direction.
HCC-1, a novel chemokine from human plasma

A novel CC chemokine, HCC-1, was isolated from the hemofiltrate of patients with chronic renal failure. HCC-1 has a relative molecular mass of 8,673 and consists of 74 amino acids including four cysteines linked to disulfide bonds. HCC-1 cDNA was cloned from human bone marrow and shown to code for the mature protein plus a putative 19-residue leader sequence. Mature HCC-1 has sequence identity of 46% with macrophage inflammatory protein (MIP)-1 alpha and MIP-1 beta, and 29- 37% with the other human CC chemokines. Unlike MIP-1 alpha and the other CC chemokines, HCC-1 is expressed constitutively in several normal tissues (spleen, liver, skeletal and heart muscle, gut, and bone marrow), and is present at high concentrations (1-80 nM) in plasma. HCC- 1 has weak activities on human monocytes and acts via receptors that also recognize MIP-1 alpha. It induced intracellular Ca2+ changes and enzyme release, but no chemotaxis, at concentrations of 100-1,000 nM, and was inactive on T lymphocytes, neutrophils, and eosinophil leukocytes. In addition, HCC-1 enhanced the proliferation of CD34+ myeloid progenitor cells. It was as effective as MIP-1 alpha, but about 100-fold less potent.
Identification of bile acid precursors as endogenous ligands for the nuclear xenobiotic pregnane X receptor

Sterol 27-hydroxylase (CYP27A1) is required for bile acid synthesis by both the classical and alternate pathways. Cyp27a1−/− mice exhibit a dramatic increase in the activity of cytochrome P450 3A (CYP3A), which catalyzes side-chain hydroxylations of bile acid intermediates, thereby facilitating their excretion in the bile and urine. We examine the role of the nuclear xenobiotic receptor PXR (pregnane X receptor) in this process. We demonstrate that expression of Cyp3a11 and other established PXR target genes is increased in the Cyp27a1−/− mice. WhenCyp27a1−/− mice are fed a diet containing either cholic acid or chenodeoxycholic acid, expression of CYP7A1, which catalyzes the rate-limiting step in bile acid biosynthesis, is strongly suppressed. In parallel, the induction of Cyp3a11 observed in these mice is reversed, suggesting that bile acid intermediates serve as PXR activators. In support of this hypothesis, three potentially toxic sterols (7α-hydroxy-4-cholesten-3-one, 5β-cholestan-3α,7α,12α-triol, and 4-cholesten-3-one), including two that are known to accumulate in Cyp27a1−/− mice, are efficacious activators of mouse PXR. All three compounds are more potent activators of mouse PXR than of human PXR, which may explain in part why humans who lack functional CYP27A1 do not display a corresponding increase in CYP3A activity and are stricken with the disease cerebrotendinous xanthomatosis. Taken together, these results reveal the existence of a feedforward regulatory loop by which potentially toxic bile acid intermediates activate PXR and induce their own metabolism. In addition, this study demonstrates that animal models with alterations in gene expression can be used to identify endogenous ligands for orphan nuclear receptors.
Making Bayesian tracking and matching by the BRISK interest points detector/descriptor cooperate for robust object tracking

Visual Tracking is often hindered by difficulties such as occlusion, abrupt motion and out of view problems. Motivated by the wide range of existing features, search mechanisms and target representations, a cooperation strategy between Bayesian tracking and matching by the Binary Robust Invariant Scalable Key-points (BRISK) is devised in this paper. The Bayesian tracker is considered as the main tracker, while matching by the BRISK is used for lost target recovery. Switching to matching by the BRISK is based on the spatial uncertainty of the particles, whenever the spatial uncertainty is above a threshold indicating a tracking failure, matching by the BRISK is trigged on and executed until the target is recovered. When the target is re-detected, the tracking control is given back to the color based particle filter tracker (PF). Experiment results show the effectiveness of the proposed tracking framework.
Influence of tumor location on the presentation and evolution of craniopharyngiomas.

OBJECT This study was performed to optimize the management of craniopharyngiomas, particularly by identifying factors predicting weight changes to prevent obesity. METHODS A series of 35 patients who had undergone surgery at a mean age of 7.4 +/- 3.7 years (standard deviation [SD]) and had been followed up until 14.9 +/- 5 years of age by the same endocrinologist were assigned to one of three groups according to their hypothalamic involvement: Group 1 (10 patients) had no involvement, Group 2 (eight patients) had compression without involvement, and Group 3 (17 patients) had severe involvement. Abnormal height and/or weight evolution indicated the craniopharyngioma in only 17% of the patients, although these elements were present at diagnosis in 85%. Before surgery, 85% of the patients lacked growth hormone, 24% lacked thyroid-stimulating hormone, 15% lacked adrenocorticotropin hormone, and 12% lacked antidiuretic hormone. All had complete hypothalamic-pituitary deficiencies after surgery. The body mass index (BMI) before surgery (mean SD 1.1 +/- 1.6) was positively correlated with BMI 1 year after surgery (mean SD 3.1 +/- 2), which correlated with the BMI at the last evaluation (mean SD 3.1 +/- 1.9; p < 0.0001 for both). Before surgery, patients in Group 3 had a greater BMI than did Group 1 (p < 0.02). The BMI of Group 1 patients did not change, but those of Groups 2 and 3 patients increased during the 1st year after surgery (p < 0.02 and p = 0.0003, respectively), with no further change. The changes occurred mainly during the first 3 months after surgery in Group 1, during the first 6 months in Group 2, and throughout the year in Group 3. CONCLUSIONS The degree of hypothalamic involvement by the craniopharyngioma determines the presentation and predicts weight changes after surgery.
Large-scale human action recognition with spark

In this paper, Apache Spark, the rising big data processing tool with in-memory computing ability, is explored to address the task of large-scale human action recognition. To achieve this, several advanced key techniques for human action recognition, such as trajectory based feature extraction, Gaussian Mixture Model, Fisher Vector, etc., are realized with parallel distributed computing power on Spark. The theory and implementation details for these distributed applications are presented in this work. The experimental results on the benchmark human action dataset Hollywood-2 show that the proposed Spark based framework which is deployed on a 9-node computer cluster can deal with large-scale video data and can dramatically accelerate the process of human action recognition.
C-Reactive Protein, Lipid-soluble Micronutrients, and Survival in Colorectal Cancer Patients

Background: Identification of biomarkers associated with survival in patients with cancer is important for elucidating the underlying mechanisms of cancer progression and identifying possible interventions to reduce cancer morbidity and mortality. Methods: Using stored patient plasma samples from a multiethnic population-based case–control study of invasive colorectal cancer, we measured posttreatment blood levels of C-reactive protein (CRP) and lipid-soluble micronutrients. Patients (n = 368) were followed after phlebotomy (mean of 8 years), during which time 47% died (25% colorectal cancer specific). HRs were estimated by Cox proportional hazards regression with adjustment for stage, age at diagnosis, ethnicity, sex, smoking status, and month of blood draw. Results: A positive association with overall risk of death was observed for CRP [HR for highest vs. lowest quintile: 1.80; 95% confidence interval (CI), 1.07–3.04; Ptrend = 0.01], whereas inverse associations were generally observed for retinol and carotenoids (HRs for overall risk of death for the highest quintile ranging from 0.5–0.8); these associations were significant for retinol (Ptrend = 0.0002), α-carotene (Ptrend = 0.02), and total carotenoids (Ptrend = 0.02) and were generally consistent across subgroups (sex, ethnicity, cancer anatomical subtype, and stage). HRs for retinol and carotenoids were attenuated somewhat after adjustment for CRP. Similar trends for CRP were observed for colorectal cancer-specific deaths (HR for highest vs. lowest tertile: 2.06; 95% CI, 1.18–3.61; Ptrend = 0.01) as for deaths from all other causes (Pheterogeneity = 0.78). Conclusions: These observations are consistent with a direct relationship between circulating CRP and overall survival among patients with colorectal cancer. Impact: These results, if reproduced, suggest that reduction of inflammation should be explored as a potential complementary treatment strategy. Cancer Epidemiol Biomarkers Prev; 22(7); 1278–88. ©2013 AACR.
Handwritten Persian digit recognition by a structural method

In this paper a structural method for recognizing Persian handwritten digits is proposed. Because of different styles in some Persian digits, in this work they were divided into 18 classes. In recognition algorithm a heuristically designed binary decision tree recognizes the digits via a series of initiative structural features. The research aim was to choose those structural features that were useful both in terms of accuracy and speed. A set of 6180 digits was used for the test. About 93.1 percent of the digits were recognized correctly. The recognition average speed of this algorithm is 24 digits per second on a 486DX4 100 MHZ.
Plan Folding Motion for Rigid Origami via Discrete Domain Sampling

Self-folding robot is usually modeled as rigid origami, a class of origami whose entire surface remains rigid during folding except at crease lines. In this work, we focus on finding valid folding motion that brings the origami from the unfolded state continuously to the folded state. Although recent computational methods allow rapid simulation of folding process of certain rigid origamis, these methods can fail even when the input crease pattern is extremely simple but with implicit folding orders. Moreover, due to the rigidity requirement, the probability of generating a valid configuration via uniform sampling is zero, which greatly hinders that applicability of traditional sampling-based motion planners. We propose a novel sampling strategy that samples in the discrete domain. Our experimental results show that the proposed method could efficiently generate valid configurations. Using those configurations, the planners successfully fold several types of rigid origamis that the existing methods fail to fold and could discover multiple folding paths for Multi-DOF origamis.
Increased Intra-Participant Variability in Children with Autistic Spectrum Disorders: Evidence from Single-Trial Analysis of Evoked EEG

Intra-participant variability in clinical conditions such as autistic spectrum disorder (ASD) is an important indicator of pathophysiological processing. The data reported here illustrate that trial-by-trial variability can be reliably measured from EEG, and that intra-participant EEG variability is significantly greater in those with ASD than in neuro-typical matched controls. EEG recorded at the scalp is a linear mixture of activity arising from muscle artifacts and numerous concurrent brain processes. To minimize these additional sources of variability, EEG data were subjected to two different methods of spatial filtering. (i) The data were decomposed using infomax independent component analysis, a method of blind source separation which un-mixes the EEG signal into components with maximally independent time-courses, and (ii) a surface Laplacian transform was performed (current source density interpolation) in order to reduce the effects of volume conduction. Data are presented from 13 high functioning adolescents with ASD without co-morbid ADHD, and 12 neuro-typical age-, IQ-, and gender-matched controls. Comparison of variability between the ASD and neuro-typical groups indicated that intra-participant variability of P1 latency and P1 amplitude was greater in the participants with ASD, and inter-trial α-band phase coherence was lower in the participants with ASD. These data support the suggestion that individuals with ASD are less able to synchronize the activity of stimulus-related cell assemblies than neuro-typical individuals, and provide empirical evidence in support of theories of increased neural noise in ASD.
Gene Expression Profiling of Ampullary Carcinomas Classifies Ampullary Carcinomas into Biliary-Like and Intestinal-Like Subtypes That Are Prognostic of Outcome

Background Adenocarcinomas of the ampulla of Vater are classified as biliary cancers, though the exact epithelium of origin for these cancers is not known. We sought to molecularly classify ampullary adenocarcinomas in comparison to known adenocarcinomas of the pancreas, bile duct, and duodenum by gene expression analysis. Methods We analyzed 32 fresh-frozen resected, untreated periampullary adenocarcinomas (8 pancreatic, 2 extrahepatic biliary, 8 duodenal, and 14 ampullary) using the Affymetrix U133 Plus 2.0 genome array. Unsupervised and supervised hierarchical clustering identified two subtypes of ampullary carcinomas that were molecularly and histologically characterized. Results Hierarchical clustering of periampullary carcinomas segregated ampullary carcinomas into two subgroups, which were distinctly different from pancreatic carcinomas. Non-pancreatic periampullary adenocarcinomas were segregated into two subgroups with differing prognoses: 5 year RFS (77% vs. 0%, p = 0.007) and 5 year OS (100% vs. 35%, p = 0.005). Unsupervised clustering analysis of the 14 ampullary samples also identified two subgroups: a good prognosis intestinal-like subgroup and a poor prognosis biliary-like subgroup with 5 year OS of 70% vs. 28%, P = 0.09. Expression of CK7+/CK20- but not CDX-2 correlated with these two subgroups. Activation of the AKT and MAPK pathways were both increased in the poor prognostic biliary-like subgroup. In an independent 80 patient ampullary validation dataset only histological subtype (intestinal vs. pancreaticobiliary) was significantly associated with OS in both univariate (p = 0.006) and multivariate analysis (P = 0.04). Conclusions Gene expression analysis discriminated pancreatic adenocarcinomas from other periampullary carcinomas and identified two prognostically relevant subgroups of ampullary adenocarcinomas. Histological subtype was an independent prognostic factor in ampullary adenocarcinomas.
On identifying don't care inputs of test patterns for combinational circuits

Given a test set for stuck at faults, some of primary input values may be changed to opposite logic values without losing fault coverage. We can regard such input values as don't care (X). In this paper, we propose a method for identifying X inputs of test vectors in a given test set. While there are many combinations of X inputs in the test set generally, the proposed method finds one including X inputs as many as possible, by using fault simulation and procedures similar to implication and justification of ATPG algorithms. Experimental results for ISCAS benchmark circuits show that approximately 66% of inputs of un-compacted test sets could be X in average. Even for compacted test sets, the method found that approximately 47% of inputs are X. Finally, we discuss how logic values are reassigned to the identified X inputs where several applications exist to make test vectors more desirable.
Controlled migration of antifog additives from LLDPE compatibilized with LLDPE grafted maleic anhydride

This paper summarizes a study of controlled migration of an antifog (AF) additive; sorbitan monooleate (SMO), from linear low density polyethylene (LLDPE) films containing a compatibilizer, LLDPE grafted maleic anhydride (LLDPE-g-MA). LLDPE/LLDPE-g-MA/SMO blends were prepared by melt compounding. Bulk and surface properties of compression molded LLDPE films containing SMO and LLDPE-g-MA were characterized using Fourier transform infrared spectroscopy and contact angle measurements. Thermal properties were investigated using a thermal gravimetric analyzer. Diffusion coefficient (D) was calculated, and AF properties were characterized using a “hot fog” test. Compression molded films were characterized for their morphology using high-resolution scanning electron microscopy, and rheological properties were measured using a parallel-plate rotational rheometer. It was found that the LLDPE/LLDPE-g-MA/SMO systems are characterized by a slower SMO migration rate, a lower diffusion coefficient, and lower contact angle values compared with LLDPE/SMO blends. These results are well correlated with results of a hot fog test. Morphological studies revealed a very fine dispersion of SMO in the LLDPE films, when 3 phr LLDPE-g-MA was combined with 1 phr SMO. Thermal analysis results show that the incorporation of 3 phr LLDPE-g-MA and 1 phr SMO significantly increases the decomposition temperature of the blend at T > 400°C. At high shear rates, the LLDPE blends show that the AF and the compatibilizer have a lubrication effect on LLDPE. Copyright © 2014 John Wiley & Sons, Ltd.
Degree of differential prioritization

Because of the high dimensionality of the microarray data sets, feature selection (FS) has become an important challenge in molecular classification. Using the degree of differential prioritization (DDP) between relevance and antiredundancy, our proposed DDP-based FS technique is capable of achieving better accuracies than those previously reported, using a smaller predictor set. However, previously, we have neither devised nor used any method for determining the value of the DDP to be used for the data set of interest before the FS process. In this article, we propose a system for predicting the optimal value of the DDP, which costs less computationally than conventional tuning while maintaining the independence of the FS technique from the type of underlying classifier used.
Display-Based Activity in the Workplace

We have developed simple taxonomy of visual display-based activity in office spaces using field data. Three key user values that displays provide are identified and investigated in depth: 1) ready access to information, 2) social orientation, and 3) co-ordination and planning. This analysis also provides a deeper understanding of the mechanisms that people use to make displays useful to them and their activities in-the-large. Implications for the design of digitally enhanced and networked display technologies are derived from the findings and discussed.
Altered mitochondrial gene expression in the nonchromosomal stripe 2 mutant of maize

The genetic and molecular analyses of higher plant mitochondria can be facilitated by studying maternally‐inherited mutations, such as the nonchromosomal stripe (NCS) mutants of maize, that have deleterious effects on plant growth. We have previously demonstrated a correlation between specific alterations in mitochondrial DNA and the expression of NCS phenotypes. In the present studies, the effects of the NCS2 mutation on mitochondrial gene expression are evaluated. Proteins synthesized by mitochondria isolated from NCS2 mutants and from related plants with normal growth have been compared. NCS2 mitochondria synthesize much reduced amounts of a single polypeptide. Probes corresponding to the mitochondrial DNA region altered in NCS2 hybridize to an aberrant set of transcripts in NCS2 mitochondria. Transcripts homologous to several previously characterized plant mitochondrial genes are similar in NCS2 and related non‐mutant mitochondria.