Miracle-dz/UniFAR-FTUs huggingface dataset:
Culture shock, what culture shock? Conceptualizing culture unrest in intercultural tourism and assessing its effect on tourists’ perceptions and travel propensity

Hottola introduced ‘culture confusion’ as a new theoretical model to overcome the inadequacies of Oberg’s ‘culture shock’. This article proposed culture unrest as a new conceptualization whereby culture shock is negotiated at home before the overseas trip begins. In the past years, the growing number of immigrants in some countries has transformed culture shock into culture unrest, defined as the context where two cultures live together, but at a level of acceptance that has developed from a state of interest or curiosity to apathy, annoyance or even antagonism. Based on a background of ‘multicultural drama’, the study examined the perceptions of native Dutch respondents about the Moroccan community resident in the Netherlands and assessed their intentions to visit Morocco in the future. The ‘rapid implosion of the “Third World” into the “First”’ should no longer go unnoticed in tourism studies.
Physics-Based Grasp Planning Through Clutter

We propose a planning method for grasping in cluttered environments, where the robot can make simultaneous contact with multiple objects, manipulating them in a deliberate and controlled fashion. This enables the robot to reach for and grasp the target while simultaneously contacting and moving aside obstacles in order to clear a desired path. We use a physicsbased analysis of pushing to compute the motion of each object in the scene in response to a set of possible robot motions. In order to make the problem computationally tractable, we enable multiple simultaneous robot-object interactions, which we pre-compute and cache, but avoid object-object interactions. Tests on large sets of simulated scenes show that our planner produces more successful grasps in more complex scenes than versions that avoid any interaction with surrounding clutter. Validation on a real robot shows that our grasp evaluation method accurately predicts the outcome of a grasp, and that our approach, in conjunction with state-of-the-art object recognition tools, is applicable in reallife scenes that are highly cluttered and constrained.
Reconstructing the Curve-Skeletons of 3D Shapes Using the Visual Hull

Curve-skeletons are the most important descriptors for shapes, capable of capturing in a synthetic manner the most relevant features. They are useful for many different applications: from shape matching and retrieval, to medical imaging, to animation. This has led, over the years, to the development of several different techniques for extraction, each trying to comply with specific goals. We propose a novel technique which stems from the intuition of reproducing what a human being does to deduce the shape of an object holding it in his or her hand and rotating. To accomplish this, we use the formal definitions of epipolar geometry and visual hull. We show how it is possible to infer the curve-skeleton of a broad class of 3D shapes, along with an estimation of the radii of the maximal inscribed balls, by gathering information about the medial axes of their projections on the image planes of the stereographic vision. It is definitely worth to point out that our method works indifferently on (even unoriented) polygonal meshes, voxel models, and point clouds. Moreover, it is insensitive to noise, pose-invariant, resolution-invariant, and robust when applied to incomplete data sets.
2 Notation , Terminology , and Basics

We study the problem of reaching a consensus in the estimates generated by multiple agents forming a network with time-varying connectivity. Our main focus is on constrained consensus problems where the estimates of different agents are constrained to lie in different constraint sets. We consider a distributed “projected consensus algorithm” in which agents combine their local averaging operation with projection onto their individual constraint sets. This algorithm can be viewed as a version of an alternating projection method with weights that are varying over time and across agents. We establish convergence of the projected consensus algorithm. We also provide convergence rate estimates for the cases when the weights are constant and equal, and when the weights are time-varying but all agents have the same constraint set.
Studies of Association of Variants Near the HHEX, CDKN2A/B, and IGF2BP2 Genes With Type 2 Diabetes and Impaired Insulin Release in 10,705 Danish Subjects

OBJECTIVE— In the present study, we aimed to validate the type 2 diabetes susceptibility alleles identified in six recent genome-wide association studies in the HHEX/KIF11/IDE (rs1111875), CDKN2A/B (rs10811661), and IGF2BP2 (rs4402960) loci, as well as the intergenic rs9300039 variant. Furthermore, we aimed to characterize quantitative metabolic risk phenotypes of the four variants. RESEARCH DESIGN AND METHODS— The variants were genotyped in the population-based Inter99 cohort (n = 5,970), the ADDITION Study (n = 1,626), a population-based sample of young healthy subjects (n = 377), and in additional type 2 diabetic case (n = 2,111) and glucose-tolerant (n = 521) subjects. The case-control studies involved a total of 4,089 type 2 diabetic patients and 5,043 glucose-tolerant control subjects. RESULTS— We validated association of variants near HHEX/KIF11/IDE, CDKN2A/B, and IGF2BP2 with type 2 diabetes. Interestingly, in middle-aged people, the rs1111875 C-allele of HHEX/KIF11/IDE strongly associated with lower acute insulin response during an oral glucose tolerance test (P = 6 × 10−7). In addition, decreased insulin release following intravenous tolbutamide injection was observed in young healthy subjects (P = 0.02). Also, a reduced insulin release was observed for the CDKN2A/B rs10811661 T-allele after both oral and intravenous glucose challenges (P = 0.001 and P = 0.009, respectively). CONCLUSIONS— We validate that variants in the proximity of the HHEX/KIF11/IDE, CDKN2A/B, and IFG2BP2 loci associate with type 2 diabetes. Importantly, variations within the HHEX/KIF11/IDE and CDKN2A/B loci confer impaired glucose- and tolbutamide-induced insulin release in middle-aged and young healthy subjects, suggesting a role for these variants in the pathogenesis of pancreatic β-cell dysfunction.
Computational prediction and experimental validation of a novel synthesized pan-PIM inhibitor PI003 and its apoptosis-inducing mechanisms in cervical cancer

PIM protein family, short-lived serine/threonine kinases (PIM1, PIM2 and PIM3), are weak oncogenes but contribute to tumorigenesis as cancer targets. Thus, design of a novel pan-PIM inhibitor is still a challenge for current cancer drug discovery. Herein, we used a Naïve Bayesian model to construct the PIM network and identified Bad and Hsp90 to interact with PIMs. Then, we screened a series of candidate small-molecule compounds targeting PIMs, and subsequently synthesized a novel small-molecule compound PI003 with remarkable anti-proliferative activities in cervical cancer cells. Moreover, we found that PI003 induced apoptosis via the death-receptor and mitochondrial pathways by targeting PIMs and affecting Bad and Hsp90. Combined with microRNA microarray analyses, we demonstrated that some microRNAs such as miR-1296 and miR-1299 could affect PIM1-STAT3 pathway in PI003-induced apoptosis. Finally, we reported that PI003 had remarkable anti-tumor activity and apoptosis-inducing effect in in vivo mouse model. In conclusion, these results demonstrate that PI003, as a novel synthesized pan-PIM inhibitor, induces the death-receptor and mitochondrial apoptosis involved in microRNA regulation, and also possessed remarkable anti-tumor activity and apoptosis-inducing effect in vivo. Thus, these findings would shed light on discovering more potential new small-molecule pan-PIM inhibitors in future cervical cancer therapy.
Using randomized sparsification to approximate minimum cuts

We introduce the concept of randomized sparsification of a weighted, undirected graph. Randomized sparsification yields a sparse unweighted graph which closely approximates the minimum cut structure of the original graph. As a consequence, we show that a cut of weight within a (1 + 6) multiplicative factor of the minimum cut in a graph can be found in O(m + n(log3 n)/e*) time; thus any constant factor approximation can be achieved in d(m) time. Similarly, we show that a cut within a multiplicative factor of (Y of the minimum can be found in RNC using m + n21a processors. We also investigate a parametric version of our randomized sparsification approach. Using it, we show that for a graph undergoing a series of edge insertions and deletions, an O(dm)-approximation to the minimum cut value can be maintained at a cost of o(n6+1/2) time per insertion or deletion. If only insertions are allowed, the approximation can be maintained at a cost of O(ne) time per insertion.
Routing Games for Traffic Engineering

Current data network scenario makes traffic engineering (TE) a very challenging task. The ever growing access rates and new applications running on end-hosts result in more variable and unpredictable traffic patterns. By providing origin-destination pairs with several possible paths, load-balancing has proved itself an excellent tool to face this uncertainty. In particular, mechanisms where routers greedily minimize a path cost function (thus requiring minimum coordination) have been studied from a game-theoretic perspective in what is known as a routing game (RG). The contribution of this paper is twofold. We first propose a new RG specifically designed for elastic traffic, where we maximize the total utility through load-balancing only. Secondly, we consider several important RGs from a TE perspective and, using several real topologies and traffic demands, present a thorough comparison of their performance. This paper brings insight into several RGs, which will help one in choosing an adequate dynamic load-balancing mechanism. The comparison shows that the performance gain of the proposed game can be important.
TUMOR SEGMENTATION FROM A MULTISPECTRAL MRI IMAGES BY USING SUPPORT VECTOR MACHINE CLASSIFICATION

The goal of this paper is to present a supervised system aimed at tracking the tumor volume during a therapeutic treatment from multispectral MRI volumes. Four types of MRI are used in our study: T1, T2, proton density (PD) and fluid attenuated inversion recovery (FLAIR). For decreasing the processing time, the proposed method employs a multi-scale scheme to identify firstly the abnormal field and extract then the tumor region. Both steps use support vector machines (SVMs). The training is carried out only on the first MRI examination (at the beginning of the treatment). The tracking process at the time point t takes the tumor region obtained in the examination at t-1 as its initialization. Only the second step is performed for others examinations to extract the tumor region. The results obtained show that the proposed system achieves promising results in terms of effectiveness and time consuming.
Modeling interactome: scale-free or geometric?

MOTIVATION Networks have been used to model many real-world phenomena to better understand the phenomena and to guide experiments in order to predict their behavior. Since incorrect models lead to incorrect predictions, it is vital to have as accurate a model as possible. As a result, new techniques and models for analyzing and modeling real-world networks have recently been introduced. RESULTS One example of large and complex networks involves protein-protein interaction (PPI) networks. We analyze PPI networks of yeast Saccharomyces cerevisiae and fruitfly Drosophila melanogaster using a newly introduced measure of local network structure as well as the standardly used measures of global network structure. We examine the fit of four different network models, including Erdos-Renyi, scale-free and geometric random network models, to these PPI networks with respect to the measures of local and global network structure. We demonstrate that the currently accepted scale-free model of PPI networks fails to fit the data in several respects and show that a random geometric model provides a much more accurate model of the PPI data. We hypothesize that only the noise in these networks is scale-free. CONCLUSIONS We systematically evaluate how well-different network models fit the PPI networks. We show that the structure of PPI networks is better modeled by a geometric random graph than by a scale-free model. SUPPLEMENTARY INFORMATION Supplementary information is available at http://www.cs. utoronto.ca/~juris/data/data/ppiGRG04/
Toll-like receptor 4-mediated growth of endometriosis by human heat-shock protein 70.

BACKGROUND We investigated the role of human heat-shock protein 70 (Hsp70) in Toll-like receptor 4 (TLR4)-mediated growth of endometriosis. METHODS TLR4 expression was examined in macrophages (M) isolated in primary culture from the peritoneal fluid of women with and without endometriosis. The production of a number of macromolecules by non-treated M, Hsp70-treated M and after treatment with anti-TLR4 antibody was examined by enzyme linked immunosorbent assay (ELISA). The single and combined effects of Hsp70 and lipopolysaccharide (LPS) on the growth of endometrial stromal cells were analyzed by 5-bromo-2-deoxyuridine (BrdU) incorporation study. Hsp70 levels in eutopic and ectopic endometria were measured by ELISA. RESULTS TLR4 was detected in isolated M at protein and gene level. Hsp70 (10 microg/ml) significantly stimulated the production of hepatocyte growth factor, vascular endothelial cell growth factor, interleukin-6 and tumor necrosis factor alpha by M derived from women with endometriosis compared with M derived from women with no endometriosis (P < 0.05 for each). This effect of Hsp70 was abrogated after pretreatment of M with anti-TLR4 antibody. BrdU incorporation indicated that Hsp70 significantly enhanced the growth of endometrial stromal cells ( approximately 50% increase) from women with endometriosis compared to non-treated cells. A synergistic effect on cell proliferation was observed between exogenous Hsp70 and LPS and this was significantly suppressed by pretreatment of cells with anti-TLR4 antibody (P < 0.05). Tissue levels of Hsp70 were significantly higher in the eutopic endometria (P < 0.05) and opaque red lesions (P < 0.01) derived from women with endometriosis than from other peritoneal lesions or from women with no endometriosis. CONCLUSIONS A prominent stress reaction was observed in blood-filled opaque red peritoneal lesions. Human Hsp70 induces pelvic inflammation and may be involved in TLR4-mediated growth of endometrial cells derived from women with endometriosis.
Interval query indexing for efficient stream processing

A large number of continual range queries can be issued against a data stream. Usually, a main memory-based query index with a small storage cost and a fast search time is needed, especially if the stream is rapid. In this paper, we present a CEI-based query index that meets both criteria for efficient processing of continual interval queries in a streaming environment. This new query index is centered around a set of predefined virtual <i>containment-encoded intervals</i>, or CEIs. The CEIs are used to first decompose query intervals and then perform efficient search operations. The CEIs are defined and labeled such that containment relationships among them are encoded in their IDs. The containment encoding makes decomposition and search operations efficient because integer additions and logical shifts can be used to carry out most of the operations. Simulations are conducted to evaluate the effectiveness of the CEI-based query index and to compare it with alternative approaches. The results show that the CEI-based query index significantly outperforms existing approaches in terms of both storage cost and search time.
New Adhesin of Enteroaggregative Escherichia coli Related to the Afa/Dr/AAF Family

ABSTRACT Enteroaggregative Escherichia coli (EAEC) is an important cause of diarrhea worldwide. We analyzed 17 Danish EAEC strains, isolated in the course of a case control study, for phenotypic and genotypic properties. The strains belonged to at least 14 different serotypes. Using PCR to investigate the prevalence of various putative virulence genes, we found that all but two strains were typical EAEC, as they harbored all or part of the previously described AggR regulon. The majority of the strains harbored genes encoding aggregative adherence fimbriae (AAF). The most common was AAF/I, found in nine strains; eight strains carried no known AAF-related genes. We utilized TnphoA mutagenesis to localize the aggregative adherence (AA) adhesin from one typical EAEC strain, C1010-00, which lacked a known AAF. We identified a TnphoA insertion in a hypothetical Dr-related pilin deposited in GenBank as HdaA. Four additional Danish strains harbored HdaA, and all but one displayed AA to HEp-2 cells. By using PCR primers derived from the pilins and ushers from the three AAF and Hda, we found that 16 of 17 strains exhibited evidence of one of these factors; importantly, the one negative strain also lacked the aggR gene. Cloning of the complete Hda gene cluster and expression in E. coli DH5α resulted in AA and complementation of the C1010-00 nonadherent mutant. Four related adhesins have now been found to confer AA in typical EAEC strains; our data suggest that, together, these variants may account for AA in the large majority of strains.
Predicting Retweet Scale Using Log-Normal Distribution

In social network analysis, retweet scale prediction is one important studying focus. Generally speaking, there are two different approaches to predict the retweet scale: time-series approach and non-time-series approach. In this paper, we conduct a research on the distribution of the reaction time in retweeting activity and introduce a time-series prediction model. We show that in retweeting activity, the reaction time has the feature of heavy-tailed distribution and the log-normal distribution fits the real reaction time data well. Within the framework of time-series prediction, for the direct retweets, we make the prediction by solving the parameter estimation problem of truncated log-normal distribution. For retweets at deeper depths, we make a prediction based on the general information diffusion theory. Experiments are carried out on real data downloaded from SINA weibo. We test the full model on retweet graphs and compare our model with the auto regression model and a perceptron model using tweet text. Our method outperforms the other two models and in experiment, on average, there is a 2% advantage over the auto-regression model when one-hour data are given.
Inhaled Nitric Oxide for Acute Respiratory Distress Syndrome and Acute Lung Injury in Adults and Children: A Systematic Review with Meta-Analysis and Trial Sequential Analysis

BACKGROUND: Acute hypoxemic respiratory failure, defined as acute lung injury and acute respiratory distress syndrome, are critical conditions associated with frequent mortality and morbidity in all ages. Inhaled nitric oxide (iNO) has been used to improve oxygenation, but its role remains controversial. We performed a systematic review with meta-analysis and trial sequential analysis of randomized clinical trials (RCTs). We searched CENTRAL, Medline, Embase, International Web of Science, LILACS, the Chinese Biomedical Literature Database, and CINHAL (up to January 31, 2010). Additionally, we hand-searched reference lists, contacted authors and experts, and searched registers of ongoing trials. Two reviewers independently selected all parallel group RCTs comparing iNO with placebo or no intervention and extracted data related to study methods, interventions, outcomes, bias risk, and adverse events. All trials, irrespective of blinding or language status were included. Retrieved trials were evaluated with Cochrane methodology. Disagreements were resolved by discussion. Our primary outcome measure was all-cause mortality. We performed subgroup and sensitivity analyses to assess the effect of iNO in adults and children and on various clinical and physiological outcomes. We assessed the risk of bias through assessment of trial methodological components. We assessed the risk of random error by applying trial sequential analysis. RESULTS: We included 14 RCTs with a total of 1303 participants; 10 of these trials had a high risk of bias. iNO showed no statistically significant effect on overall mortality (40.2%versus 38.6%) (relative risks [RR] 1.06, 95% confidence interval [CI] 0.93 to 1.22; I2 = 0) and in several subgroup and sensitivity analyses, indicating robust results. Limited data demonstrated a statistically insignificant effect of iNO on duration of ventilation, ventilator-free days, and length of stay in the intensive care unit and hospital. We found a statistically significant but transient improvement in oxygenation in the first 24 hours, expressed as the ratio of PO2 to fraction of inspired oxygen (mean difference [MD] 15.91, 95% CI 8.25 to 23.56; I2 = 25%). However, iNO appears to increase the risk of renal impairment among adults (RR 1.59, 95% CI 1.17 to 2.16; I2 = 0) but not the risk of bleeding or methemoglobin or nitrogen dioxide formation. CONCLUSION: iNO cannot be recommended for patients with acute hypoxemic respiratory failure. iNO results in a transient improvement in oxygenation but does not reduce mortality and may be harmful.
Rossby Wave Instability of Keplerian Accretion Disks

We find a linear instability of nonaxisymmetric Rossby waves in a thin nonmagnetized Keplerian disk when there is a local maximum in the radial profile of a key function ℒ(r)≡ℱ(r)S2/Γ(r), where ℱ−1=ẑ·(𝛁×v)/Σ is the potential vorticity, S=P/ΣΓ is the entropy, Σ is the surface mass density, P is the vertically integrated pressure, and Γ is the adiabatic index. We consider in detail the special case where there is a local maximum in the disk entropy profile S(r). This maximum acts to trap the waves in its vicinity if its height-to-width ratio max(S)/Δr is larger than a threshold value. The pressure gradient derived from this entropy variation provides the restoring force for the wave growth. We show that the trapped waves act to transport angular momentum outward. A plausible way to produce an entropy variation is when an accretion disk is starting from negligible mass and temperature, therefore, negligible entropy. As mass accumulates by either tidal torquing, magnetic torquing, or Roche-lobe overflow, confinement of heat will lead to an entropy maximum at the outer boundary of the disk. Possible nonlinear developments from this instability include the formation of Rossby vortices and the formation of spiral shocks. What remains to be determined from hydrodynamic simulations is whether or not Rossby wave packets (or vortices) "hold together" as they propagate radially inward.