Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of social voting patterns on digg

The social Web is transforming the way information is created and distributed. Blog authoring tools enable users to publish content, while sites such as Digg and Del.icio. us are used to distribute content to a wider audience. With content fast becoming a commodity, interest in using social networks to promote and find content has grown, both on the side of content producers (viral marketing) and consumers (recommendation). Here we study the role of social networks in promoting content on Digg, a social news aggregator that allows users to submit links to and vote on news stories. Digg's goal is to feature the most interesting stories on its front page, and it aggregates opinions of its many users to identify them. Like other social networking sites, Digg allows users to designate other users as "friends" and see what stories they found interesting. We studied the spread of interest in news stories submitted to Digg in June 2006. Our results suggest that pattern of the spread of interest in a story on the network is indicative of how popular the story will become. Stories that spread mainly outside of the submitter's neighborhood go on to be very popular, while stories that spread mainly through submitter's social neighborhood prove not to be very popular. This effect is visible already in the early stages of voting, and one can make a prediction about the potential audience of a story simply by analyzing where the initial votes come from.
The solidification of Chineseness in academic mobility: Critical reviews of "intercultural" research articles on Chinese students

€or€often€“cultural€robots”€who€all€share€thesame€characteristics)€by€administrators,€staff€and€other€local€and€international€students€–but€also€by€host€societies€in€general. €My€paper€is€interested€in€how€a€selection€of€recentresearch€ articles€ within€ the€ field€ of€ intercultural€ communication€ deal€ with€ Chinesestudents. €This€article€can€be€considered€as€belonging€to€the€Rhetoric€of€Inquiry€(Billig,1988)€which€takes€academic€discourse€as€an€object€of€study. €Using€a€typology€of€thethree€ approaches€ to€ otherness€ and€ interculturality€ that€ I€ have€ proposed[1)solid/culturalist;€ 2)€ liquid/hermeneutical€ and€ 3)€ Janusian],€ I€ will€ demonstrate€ howresearchers€ themselves€ can€ “fetichize”€ and€ “solidify”€ Chinese€ students,€ and€ thus,contribute€to€creating€a€differentialist€and€often€incoherent€image€of€those€they€consideras€“strangers”
LEVELIW: Learning extreme verification latency with importance weighting

Nonstationary streaming data are characterized by changes in the underlying distribution between subsequent time steps. Learning in such environments becomes even more challenging when labeled data are available only at the initial time step, and the algorithm is provided unlabeled data thereafter, a scenario referred to as extreme verification latency. Our previously introduced COMPOSE framework works very well in such settings. COMPOSE is a semi-supervised approach that iteratively labels strategically chosen instances of the next time step using the instances it labeled in the previous time step. COMPOSE originally assumed a significant distribution overlap at consecutive time steps, allowing instances lying in the center of the feature space to be used as the most representative labeled instances from current time step to help label the new data at the next time step. Such an assumption is also inherent in importance weighting based domain adaptation, but only for a single time step with mismatched train and test data distributions. We explore importance weighting not for a single time step matching training / test distributions, but rather matching distributions between two consecutive time steps, and estimate the posterior distribution of the unlabeled data using importance weighted least squares probabilistic classifier. The estimated labels are then iteratively used as the training data for the next time step. We call this algorithm as LEVELIW, Learning Extreme VErification Latency with Importance Weighting. Our primary goal in doing so is to determine if and when importance weighting provides an advantage over COMPOSE's core support extraction, and whether it provides an alternate solution with reduced parameter sensitivity. Several datasets are used to compare the two approaches, which produced some unique insights.
Procedural knowledge, decision-making and game performance analysis in Female Volleyball’s attack according to the player’s experience and competitive success

The purpose of this study was to analyse procedural knowledge, decision-making and game performance of the zone 4 attackers in Volleyball, according to the players’ experience and competitive performance. A verbal interview protocol was implemented immediately after randomly chosen live game actions to analyze procedural knowledge. Decision-making and players’ performance were analyzed by video images. Oneway Anova, Independent Samples t-Test, and Pearson Chi-Square were applied to data analysis. The results showed that more experienced and more successful players play more under goal concepts than condition concepts and concern more often with the opponent. Specifically, more experienced players mentioned more goal concepts and less sophisticated conditions, as more successful players mentioned more action concepts. More experienced players also presented fewer condition concepts than the less experienced ones. Successful players tended to make more appropriate decisions. However, as player’s experience and competitive success are multidimensional variables they might not be fully well characterized by the number of years of practice and competitive results. Therefore, future research is required, and it should include other criteria to characterize both variables. Moreover, qualitative analysis is needed, since it will allow a deeper understanding of the tactical development of the players according to the specific nature of the training process, and also considering the competitive success and the player’s experience as multidimensional variables.
Detection, Virulence Gene Assessment and Antibiotic Resistance Pattern of O157 Enterohemorrhagic Escherichia coli in Tabriz, Iran

Background: Shiga toxin-producing Escherichia coli (STEC) is a food-borne pathogen and infection with this organism causes illnesses such as bloody diarrhea, hemorrhagic colitis and hemolytic-uremic syndrome. Objectives: Considering the lack of any information about the prevalence rate and the antibiotic resistance pattern of O157:H7 serotype in Tabriz, finding answers to the above mentioned subjects was among the goals of this study. Materials and Methods: Two hundred E. coli strains from diarrheal or non-diarrheal stools of outpatients and hospitalized cases in Tabriz Imam Reza hospital were isolated between September and December 2014 using MacConkey agar and standard biochemical tests and then cultured on sorbitol MacConkey agar. The sorbitol-negative isolates were confirmed as the O157 serotype using O157 antisera. A multiplex polymerase chain reaction (PCR) method was used for the detection of stx-1, stx-2, eae, and mdh genes and the antibiotic resistance pattern of these isolates was determined using Kirby-Bauer method and clinical and laboratory standards institute (CLSI) standards. Results: Of the isolates 11 (5.5%) were sorbitol-negative, which were later analyzed by multiplex PCR and the results revealed that 2 (18.18%) isolates contained the stx-1 gene, 10 (90.91%) contained the stx-2 gene, and 5 (45.45%) contained the eae gene. The stx-2 and eae genes were the most commonly encountered virulence factors. All or most of the isolates were susceptible to ceftazidime (100%), gentamicin (100%), ciprofloxacin (100%), nalidixic acid (90.9%), trimetoprim sulfamethoxazole (90.9%), chloramphenicol (90.9%), ampicillin (81.8%), and cephalothin (72.7%). On the contrary, moderate susceptibility of the isolates to doxycycline (54.5%) was observed. Conclusions: Due to the low frequency of STEC O157 and the high susceptibility rates of the isolates to the tested antibiotics in this study, STEC O157 has not become a major problem in Tabriz yet, but comprehensive microbiological surveillance programs that provide early warning and limit the scale of possible outbreaks would be essential.
Virus-encoded proteinases of the Togaviridae.

IP: 54.70. 40.11 On: Mon, 10 Dec 2018 21:28:56 Journal of General Virology (1999), 80, 1879–1888. Printed in Great Britain .
On the Largest Distance (Signless Laplacian) Eigenvalue of Non-transmission-regular Graphs

Let $G=(V(G),E(G))$ be a $k$-connected graph with $n$ vertices and $m$ edges. Let $D(G)$ be the distance matrix of $G$. Suppose $\lambda_1(D)\geq \cdots \geq \lambda_n(D)$ are the $D$-eigenvalues of $G$. The transmission of $v_i \in V(G)$, denoted by $Tr_G(v_i)$ is defined to be the sum of distances from $v_i$ to all other vertices of $G$, i.e., the row sum $D_{i}(G)$ of $D(G)$ indexed by vertex $v_i$ and suppose that $D_1(G)\geq \cdots \geq D_n(G)$. The $Wiener~ index$ of $G$ denoted by $W(G)$ is given by $W(G)=\frac{1}{2}\sum_{i=1}^{n}D_i(G)$. Let $Tr(G)$ be the $n\times n$ diagonal matrix with its $(i,i)$-entry equal to $TrG(v_i)$. The distance signless Laplacian matrix of $G$ is defined as $D^Q(G)=Tr(G)+D(G)$ and its spectral radius is denoted by $\rho_1(D^Q(G))$ or $\rho_1$. A connected graph $G$ is said to be $t$-transmission-regular if $Tr_G(v_i) =t$ for every vertex $v_i\in V(G)$, otherwise, non-transmission-regular. In this paper, we respectively estimate $D_1(G)-\lambda_1(G)$ and $2D_1(G)-\rho_1(G)$ for a $k$-connected non-transmission-regular graph in different ways and compare these obtained results. And we conjecture that $D_1(G)-\lambda_1(G)>\frac{1}{n+1}$. Moreover, we show that the conjecture is valid for trees.
Neural Mechanisms and Psychology of Psychedelic Ego Dissolution and 5-HT2A Receptor Agonist Activity

Signiﬁcance Statement . Abstract—— Neuroimaging studies of psychedelics have advanced our understanding of hierarchical brain organization and the mechanisms underlying their subjective and therapeutic effects. The primary mechanism of action of classic psychedelics is binding to serotonergic 5-HT2A receptors. Agonist activity at these receptors leads to neuromodulatory changes in synaptic efﬁcacy that can have a profound effect on hierarchical message-passing in the brain. Here, we re- view the cognitive and neuroimaging evidence for the effects of psychedelics: in particular, their inﬂuence on selfhood and subject-object boundaries—known as ego dissolution —surmised to underwrite their subjec- tive and therapeutic effects. Agonism of 5-HT2A receptors, located at the apex of the cortical hierarchy, may have a particularly powerful effect on sentience and consciousness. These effects can endure well after the pharmacological half-life, suggesting that psychedelics may have effects on neural plasticity that may play a role in their therapeutic efﬁcacy. Psychologically, this may be accompanied by a disarming of Dissolution of precision of high-level priors ﬂatten the curvature of the free energy landscape, enabling neural dynamics to escape their local minima or basins of attraction, allowing greater attention to the sensory input and prediction errors (computationally expressed as a free energy landscape). The cognitive-therapeutic result of ego dissolution is the reduced precision or commitment to higher-level beliefs in the high levels of the hierarchy that affords an opportunity to explore a landscape of alternative hypotheses of the causes of sensory impressions and the consequences of self-initiated actions. Change to these explanations can be therapeutic by enabling new ways to make sense of the world and lived exchanges with it. This notion of free energy landscapes is endorsed by empirical studies of electrical physiologic responses and functional anatomy (Bastos et al., 2012). Adapted from Carhart-Harris and Friston (2019).
Validation of MODIS liquid water path for oceanic nonraining warm clouds: Implications on the vertical profile of cloud water content

Liquid water path (LWP) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) is validated using the Advanced Microwave Scanning Radiometer–EOS (AMSR‐E) retrievals for global oceanic nonraining warm clouds, with focus on the vertically homogeneous (VH) model and adiabatically stratified (AS) model of liquid water content (LWC) profile used in MODIS retrieval. With respect to AMSR‐E LWP that acts as ground truth under a series of constraints, the global average of MODIS‐LWPVH and MODIS‐LWPAS has a positive (11.8%) and negative (−6.8%) bias, respectively. Most of the oceanic warm clouds tend to have adiabatic origin and correspondingly form AS‐like profiles, which could be well retained if drizzle is absent. Besides, the presence of drizzle, cloud top entrainment seems to be another cause that modifies the original LWC profiles to become VH‐like, which is notable for the very low clouds that have rather small thickness. These factors jointly determine the appearance of LWP profiles and in turn their spatial pattern across global oceans, with AS‐like profiles dominant in the areas where nonraining warm clouds occur very frequently in the form of stratocumulus. The modified MODIS LWP shows significant improvement compared with either MODIS‐LWPVH or MODIS‐LWPAS. This is achieved by using the two physically explicit models flexibly, in which the elementary MODIS retrievals of cloud top temperature, cloud optical thickness, and droplet effective radius play a determinant role. A combined use of VH and AS model in the MODIS retrieval is demonstrated to be effective for improving the LWP estimation for oceanic nonraining warm clouds.
Natural environmental sources of Cryptococcus neoformans var. gattii

We sought evidence for new environmental sources of Cryptococcus neoformans var. gattii by random amplification of polymorphic DNA (RAPD) analysis of isolates from 29 animals with a restricted territorial range in five Australian states. Twenty-three of the 29 isolates and 45 of 45 eucalypt isolates tested previously exhibited one RAPD profile, VGI. RAPD profile VGII was identified in 6 of 17 isolates from domesticated species but in none of 12 native species. Four VGII isolates originated from an area of Western Australia with no natural stands of known eucalypt host, indicating the existence of at least one unrecognized natural source of C. neoformans var. gattii.
Robust Detection of Two-Dimensional Barcodes in Blurry Images

This report proposes a fast method for detection of two-dimensional barcodes in blurry images of low resolution. Such a method could improve the performance and the usability of a barcode decoding system implemented for example in a mobile phone. Example images show that barcode image quality in some cases can be good enough for detection but still not good enough to be decoded. This indicates that it makes sense to construct a system that first looks for barcodes in an image of rather low resolution and, when one is found, the system acquires an image of the barcode with optimized camera settings for barcode decoding. In this way, the user does not need to press the snapshot key, which further simplifies the handling. To our knowledge, 2D-barcode decoding systems today all use the same image for both detection and decoding. The main purpose of this project is to investigate the possibilities of two-dimensional barcode recognition in blurred, low-resolution images. The focus is on finding the quick response code. We show that it is very hard to search for the pattern that is normally used for detection, when the image is small and of low quality. Therefore a new method, based on global code properties, is proposed. Experiments show that good results can be achieved from a fast method when the code’s property of having high gradient magnitude areas is combined with the code’s property of having the shape of a square.
College Quarterly - Articles - The Roles of Physical Activity and Health in Enhancing Student Engagement: Implications for Leadership in Post Secondary Education

Research demonstrates that student engagement supports academic success (Kuh, 2001). Engagement is broader than the amount of time and effort that students devote to their studies. University curriculum, allocation of resources, educationally purposeful activities, and support services also facilitate the student experience and outcomes. Leaders in post secondary institutions need to take an inclusive approach to student engagement and realize that student success is a shared responsibility with students, faculty, and staff members all contributing to the campus experience. Coordinating programs and services across divisions is essential as "Student success is everybody's business" (Upcraft, Gardner, & Barefoot, 2005, p.87).
GRADED ROOTS AND SINGULARITIES

2 Normal surface singularities. 2 2.1 The link. 2 2.2 The combinatorics of the link. 3 2.3 The topology of the link. The Heegaard Floer homology HF+(−M). 5 2.4 Some analytic invariants of the singularity. 6 2.5 Rational singularities. 7 2.6 Weakly elliptic singularities. 8 2.7 Almost rational singularities. 9
Prediction of posthepatectomy liver failure: Role of SSM and LSPS

To the Editor, We read with great interest the paper by Wang et al, where the authors compared the ability of the Child‐Pugh (CP) score, the model for end‐stage liver disease (MELD) score and the indocyanine retention test at 15 minutes (indocyanine green [ICG]‐R15) to assess hepatic functional reserve in patients undergoing to hepatic resection. The authors retrospectively evaluated 185 patients with hepatocellular carcinoma suitable for hepatic resection. Using multivariable analysis they found that platelet count, ICG‐R15, clinically significant portal hypertension (PH) and major resection were independent factors for predicting severe posthepatectomy liver failure (PHLF). The authors concluded that ICG‐R15 was more accurate than the CP and MELD scores in predicting hepatic functional reserve before hepatectomy. These results are very interesting because, apart from major hepatic resection, the other predictors of PHLF were associated to PH. The gold standard method to assess the presence and the degree of PH is the measurement of hepatic venous pressure gradient (HVPG). Moreover, the HVPG can be used before surgery to stratify the risk of PHLF. However, HVPG is an invasive and risky method, not available in all hospitals. On the other hand, in the last decade several noninvasive tests have been evaluated for the prediction of PH in different settings. Indocyanine green retention test (ICG‐R15) is one of these. Lisotti et al documented that ICG‐R15 was also able to directly reflect the alteration of liver blood flow and consequently the presence and grade of PH and esophageal varices of patients with well‐preserved liver function. Furthermore, Cescon et al found that an elevated liver stiffness measurement (LSM), which is also a surrogate marker for PH, was associated with PHLF. More recently, two new noninvasive tests were proposed as good predictors of PH, liver stiffness‐spleen size‐to‐platelet ratio risk score (LSPS) by Kim et al and spleen stiffness measurement (SSM) using transient elastography by our group in 2012. SSM was found to have an higher accuracy than LSM in predicting PH grade. Thus, using Wang’s experience we collected data and analyzed the role of other noninvasive tests such as SSM and LSPS as surrogates for PH in predicting PHLF in a previously published cohort of resected patients for HCC. Among the 90 patients, 26 experienced severe PHLF (grade 2 or 3). Figure 1A and 1B shows SSM and LSPS distributions in no‐PHLF and PHLF, which were significantly different between the two groups (P < 0.01). While LSPS was available for all the patients, SSM data were available in 40 patients, of whom 16 experienced PHLF. Thus, we were able to perform only a univariate analysis for testing the predictive role for PHLF. Accordingly, we found that SSM and LSPS were both significantly associated with PHLF (Table 1). In conclusion, according to Wang’s and our results, PH is the strongest predictor of posthepatectomy liver failure. Thus, we believe it should be routinely assessed by noninvasive tests before hepatic resection.
Novel compartmental models of infectious disease transmission

Many methodologies in disease modeling are invaluable in the evaluation of health interventions. Of these methodologies, one of most fundamental is compartmental modeling. Compartmental models have many different forms with one of the most general characterizations occurring from the description of disease dynamics with nonlinear Volterra integral equations. Despite this generality, the vast majority of disease modellers prefer the special case where nonlinear Volterra integral equations reduce to systems of differential equations through the traditional assumptions that 1) the infectiousness of a disease corresponds to incidence, and 2) the duration of infection follows either an exponential or Erlang distribution. However, these assumptions are not the only ones that simplify nonlinear Volterra integral equations in such a way. In what follows, we illustrate a biologically more accurate description of the total infectivity of a disease that reduces systems of nonlinear Volterra integral equations to a class of novel compartmental models, as described by systems of differential equations. We demonstrate the consistency of these novel compartmental models to their traditional counterparts when the duration of infection follows either an exponential or Erlang distribution, and provide a novel compartmental model for a Pearson distributed duration of infection. Significant outcomes of our work include a compartmental model that captures any Erlang distributed duration of infection with only 3 differential equations, instead of the typical inflated model sizes, and a compartmental models that capture any mean, standard deviation, skewness, and kurtosis of the duration of infection distribution with only 4 differential equations. Author summary Compartmental models are a powerful tool for predicting disease outbreaks, and evaluating public health policies and intervention effectiveness. However, such models typically have an inability to account for many of the biological features of a disease. For instance, the assumptions placed on the duration of infection required by most compartmental models are due to mathematical convenience, and are known to massively effect model behavior and quality of predictions. Our work illustrates a simple solution to these erroneous assumptions by proposing a new simplification of the general model proposed by Kermack and McKendrick. In doing so, we obtain a new class of compartmental models with many of the features that make traditional compartmental the go-to disease model for the vast majority the epidemiological modeling community, such as their formulations as systems of differential equations, while adding the ability to more accurately account for effects of variability in an individual’s duration of infection. As such, our work may be viewed as the starting point for multiple research avenues, as it opens up a new class of compartmental model for investigation under the contexts of mathematics, public health, and evolutionary biology.