Miracle-dz/UniFAR-FTUs huggingface dataset:
Trial-Offer Markets with Continuation

Trial-offer markets, where customers can sample a product before deciding whether to buy it, are ubiquitous in the online experience. Their static and dynamic properties are often studied by assuming that consumers follow a multinomial logit model and try exactly one product. In this paper, we study how to generalize existing results to a more realistic setting where consumers can try multiple products. We show that a multinomial logit model with continuation can be reduced to a standard multinomial logit model with different appeal and product qualities. We examine the consequences of this reduction on the performance and predictability of the market, the role of social influence, and the ranking policies.
Tree model guided candidate generation for mining frequent subtrees from XML documents

Due to the inherent flexibilities in both structure and semantics, XML association rules mining faces few challenges, such as: a more complicated hierarchical data structure and ordered data context. Mining frequent patterns from XML documents can be recast as mining frequent tree structures from a database of XML documents. In this study, we model a database of XML documents as a database of rooted labeled ordered subtrees. In particular, we are mainly concerned with mining frequent induced and embedded ordered subtrees. Our main contributions are as follows. We describe our unique embedding list representation of the tree structure, which enables efficient implementation of our Tree Model Guided (TMG) candidate generation. TMG is an optimal, nonredundant enumeration strategy that enumerates all the valid candidates that conform to the structural aspects of the data. We show through a mathematical model and experiments that TMG has better complexity compared to the commonly used join approach. In this article, we propose two algorithms, MB3-Miner and iMB3-Miner. MB3-Miner mines embedded subtrees. iMB3-Miner mines induced and/or embedded subtrees by using the maximum level of embedding constraint. Our experiments with both synthetic and real datasets against two well-known algorithms for mining induced and embedded subtrees, demonstrate the effectiveness and the efficiency of the proposed techniques.
Effect of endogenous estrogen on blood flow through carotid arteries.

BACKGROUND AND PURPOSE Recent evidence suggests that physiological changes in the concentration of endogenous estrogens may influence stroke outcome. The purpose of this study was to determine a menstrual cycle-related profile of blood flow through the carotid arteries and its correlation with estrogen concentration. METHODS The flow velocity and cross-sectional area of the common carotid artery, internal carotid artery (ICA), and external carotid artery (ECA) were measured with duplex Doppler sonography throughout the menstrual cycle in 14 healthy women. Concentration of plasma 17beta-estradiol, progesterone, hematocrit, hemoglobin, and blood pressure were also determined. RESULTS In the follicular phase, the concentration of estrogen increased to reach a peak on day 14, whereas concentration of progesterone remained low. The mean and end-diastolic velocities in the ICA increased on average by 15% of their base values, along with increasing concentrations of estrogen (r=0.59 and 0.65, respectively). The profile of flow velocity changes in this artery corresponded to the profile of estrogen concentration. In contrast to the ICA, flow velocities in the ECA decreased from their base value, reaching their minimum in the luteal phase. The mean flow velocity in the common carotid artery increased on day 14 by just 2% of its base value. The lumen of the carotid arteries was stable throughout the cycle. Hematocrit, hemoglobin, and systolic blood pressure also remained unchanged. CONCLUSIONS Increased concentration of endogenous estrogen correlates with substantial augmentation of flow in the internal carotid artery. This promotion of flow is caused mainly by decreased cerebrovascular resistance with consequent "stealing" of blood from the ECA.
Advanced Data Stream Sharing

Using multi-query optimization for sharing common work among multiple queries requires the identification of shareable query components. This kind of optimization is particularly effective in distributed data stream management systems (DSMSs) with multiple continuous queries running concurrently over long periods of time. In this paper, we introduce an abstract property tree (APT) and its extension, an abstract property forest (APF), for representing, matching, and merging XQuerybased queries and XML data streams in a distributed DSMS to enable the sharing of potentially preprocessed data streams among multiple queries. The presented techniques thus allow for efficient resource usage and provide for an increased number of queries that can be processed concurrently.
Identifying single-ended contact formations from force sensor patterns

We present two methods of rapidly (less than 1 ms) identifying contact formations from force sensor patterns, including friction and measurement uncertainty. Both principally use force signals instead of positions and detailed geometric models. First, fuzzy sets are used to model patterns and sensor uncertainty; membership functions are generated automatically from training data. Second, a neural network is used to generate confidence levels for each contact formation. Experimental results are presented for both classifiers, showing excellent results. New insights into the data sets are discussed, and a modified training method is presented that further improves the performance. The classification techniques are discussed in the context of robot programming by demonstration.
Determinants of quality of life in patients with fibromyalgia: A structural equation modeling approach

Objective Health-related quality of life (HRQOL) in patients with fibromyalgia (FM) is lower than in patients with other chronic diseases and the general population. Although various factors affect HRQOL, no study has examined a structural equation model of HRQOL as an outcome variable in FM patients. The present study assessed relationships among physical function, social factors, psychological factors, and HRQOL, and the effects of these variables on HRQOL in a hypothesized model using structural equation modeling (SEM). Methods HRQOL was measured using SF-36, and the Fibromyalgia Impact Questionnaire (FIQ) was used to assess physical dysfunction. Social and psychological statuses were assessed using the Beck Depression Inventory (BDI), the State-Trait Anxiety Inventory (STAI), the Arthritis Self-Efficacy Scale (ASES), and the Social Support Scale. SEM analysis was used to test the structural relationships of the model using the AMOS software. Results Of the 336 patients, 301 (89.6%) were women with an average age of 47.9±10.9 years. The SEM results supported the hypothesized structural model (χ2 = 2.336, df = 3, p = 0.506). The final model showed that Physical Component Summary (PCS) was directly related to self-efficacy and inversely related to FIQ, and that Mental Component Summary (MCS) was inversely related to FIQ, BDI, and STAI. Conclusions In our model of FM patients, HRQOL was affected by physical, social, and psychological variables. In these patients, higher levels of physical function and self-efficacy can improve the PCS of HRQOL, while physical function, depression, and anxiety negatively affect the MCS of HRQOL.
Should I consume them ? Dis-identifying the self with dissociative and in-"affective" brands for youth drinking behaviors

Previously, research has shown that negative affect and identity divergence can be used as signals for identity. This research intends to employ affective advertising and the act of dissociating from a brand’s social groups as antecedents for possible identity markers that consumers propagate to the social environment. The signaling of social identities is seen as a way through which consumers signal their usage, interaction and relation with brands to the society. The current research applies this behavior within an anti-consumption context, where consumers avoid certain brands and their reference groups to experience greater positive affect and avoid signaling a negative identity. The role of psychological and sociological variables is also assessed through the lens of regulatory focus, self-construal, norms and wellbeing. The intended research model tests the application of these concepts within the domain of health marketing and alcohol consumption by youngsters.
The Heterogeneous Effects of Transportation Investments: Evidence from sub-Saharan Africa 1960-2010∗

This paper documents the effect of road construction on city population growth in sub-Saharan Africa 1960-2010, through the channel of increasing market access. Using changes in market access due to foreign or otherwise distant road construction as a source of exogenous variation in overall market access, we estimate a 30-year elasticity of city population with respect to market access of 0.05 to 0.20, larger than OLS estimates of 0.02–0.05, but somewhat smaller than estimates for other contexts. The effect is concentrated 10–30 years after road construction, closer to coasts and borders, and farther from a country’s largest cities. JEL classification: F15, O18, R11, R12, R4
Research on Team Faultlines: A Literature Review

Team faultlines, which is based on the diversified features of team members, is a potential line dividing team into several sub-teams. In recent years, more and more researchers pay attention to this new perspective. This paper reviews literature from theoretical foundation, measuring method, effect mechanism and so on several aspects, and advances the research prospect hoping to provide reference for future research.
The inheritance of alcohol sensitivity and of patterns of alcohol use.

Compared to controls, sons of alcoholics have been reported to exhibit decreased sensitivity to a challenge dose of alcohol (e.g. a smaller increase in body-sway: Schuckit, 1985). We reanalyze alcohol challenge data from a general population sample of Australian twin pairs (Martin et al., 1985a, b). By fitting direction-of-causation models, we show that in males differences in body-sway are largely a consequence, not a cause, of differences in alcohol consumption patterns. In females, direction-of-causation could not be resolved.
Bigger is better: changes in body size explain a maternal effect of food on offspring disease resistance

Abstract Maternal effects triggered by changes in the environment (e.g., nutrition or crowding) can influence the outcome of offspring–parasite interactions, with fitness consequences for the host and parasite. Outside of the classic example of antibody transfer in vertebrates, proximate mechanisms have been little studied, and thus, the adaptive significance of maternal effects on infection is not well resolved. We sought to determine why food‐stressed mothers give birth to offspring that show a low rate of infection when the crustacean Daphnia magna is exposed to an orally infective bacterial pathogen. These more‐resistant offspring are also larger at birth and feed at a lower rate. Thus, reduced disease resistance could result from slow‐feeding offspring ingesting fewer bacterial spores or because their larger size allows for greater immune investment. To distinguish between these theories, we performed an experiment in which we measured body size, feeding rate, and susceptibility, and were able to show that body size is the primary mechanism causing altered susceptibility: Larger Daphnia were less likely to become infected. Contrary to our predictions, there was also a trend that fast‐feeding Daphnia were less likely to become infected. Thus, our results explain how a maternal environmental effect can alter offspring disease resistance (though body size), and highlight the potential complexity of relationship between feeding rate and susceptibility in a host that encounters a parasite whilst feeding.
Understanding crowdworkers’ learning practices

This paper reports findings of a survey exploring how crowdworkers develop their knowledge and skills in the course of their work on digital platforms. The focus is on informal learning initiated and selfregulated by crowdworkers: engaging in challenging tasks; studying professional literature/online resources; sharing knowledge and collaborating with others. The survey was run within two platforms representing two types of crowdwork – microwork (CrowdFlower) and online freelancing (Upwork). The survey uncovered evidence for considerable individual and social learning activity within both types of crowdwork. Findings suggest that both microwork and online freelancing are learning-intensive and both groups of workers are learning-oriented and self-regulated. Crowdwork is a growing form of employment in developed and developing countries. Improved understanding of learning practices within crowdwork would inform the design of crowdwork platforms; empower crowdworkers to direct their own learning and work; and help platforms, employers, and policymakers enhance the learning potential of crowdwork.
Fusion under unknown correlation - covariance intersection as a special case

This paper addresses the problem of fusing several random variables (RVs) with unknown correlations. A family of upper bounds on the resulting covariance matrix is given, and is shown to contain the upper bound offered by the covariance intersection (CI) algorithm proposed by Julier and Uhlmann (2000). For trace minimization, the optimal one in this family is better than the one obtained by CI except in some cases where they are equal. It is further proved that the best pair of combination gains that minimizes the above optimal-trace-in-the-family coincides with the one associated with the best value of omega in CL. Thus, the CI Algorithm provides a convenient one-dimensional parameterization for the optimal solution in the n-square dimensional space. The results are also extended to multiple RVs and partial estimates.
Sparse Solution of Fiber Orientation Distribution Function by Diffusion Decomposition

Fiber orientation is the key information in diffusion tractography. Several deconvolution methods have been proposed to obtain fiber orientations by estimating a fiber orientation distribution function (ODF). However, the L 2 regularization used in deconvolution often leads to false fibers that compromise the specificity of the results. To address this problem, we propose a method called diffusion decomposition, which obtains a sparse solution of fiber ODF by decomposing the diffusion ODF obtained from q-ball imaging (QBI), diffusion spectrum imaging (DSI), or generalized q-sampling imaging (GQI). A simulation study, a phantom study, and an in-vivo study were conducted to examine the performance of diffusion decomposition. The simulation study showed that diffusion decomposition was more accurate than both constrained spherical deconvolution and ball-and-sticks model. The phantom study showed that the angular error of diffusion decomposition was significantly lower than those of constrained spherical deconvolution at 30° crossing and ball-and-sticks model at 60° crossing. The in-vivo study showed that diffusion decomposition can be applied to QBI, DSI, or GQI, and the resolved fiber orientations were consistent regardless of the diffusion sampling schemes and diffusion reconstruction methods. The performance of diffusion decomposition was further demonstrated by resolving crossing fibers on a 30-direction QBI dataset and a 40-direction DSI dataset. In conclusion, diffusion decomposition can improve angular resolution and resolve crossing fibers in datasets with low SNR and substantially reduced number of diffusion encoding directions. These advantages may be valuable for human connectome studies and clinical research.
High-dimensional asymptotics for percolation of Gaussian free field level sets

We consider the Gaussian free field on $\mathbb{Z}^d$, $d$ greater or equal to $3$, and prove that the critical density for percolation of its level sets behaves like $1/d^{1 + o(1)}$ as $d$ tends to infinity. Our proof gives the principal asymptotic behavior of the corresponding critical level $h_*(d)$. Moreover, it shows that a related parameter $h_{**}(d) \geq h_*(d)$ introduced by Rodriguez and Sznitman in arXiv:1202.5172 is in fact asymptotically equivalent to $h_*(d)$.
Lessons from Mouse Models of High-Fat Diet-Induced NAFLD

Nonalcoholic fatty liver disease (NAFLD) encompasses a clinicopathologic spectrum of diseases ranging from isolated hepatic steatosis to nonalcoholic steatohepatitis (NASH), the more aggressive form of fatty liver disease that may progress to cirrhosis and cirrhosis-related complications, including hepatocellular carcinoma. The prevalence of NAFLD, including NASH, is also increasing in parallel with the growing epidemics of obesity and diabetes. However, the causal relationships between obesity and/or diabetes and NASH or liver tumorigenesis have not yet been clearly elucidated. Animal models of NAFLD/NASH provide crucial information, not only for elucidating the pathogenesis of NAFLD/NASH, but also for examining therapeutic effects of various agents. A high-fat diet is widely used to produce hepatic steatosis and NASH in experimental animals. Several studies, including our own, have shown that long-term high-fat diet loading, which can induce obesity and insulin resistance, can also induce NASH and liver tumorigenesis in C57BL/6J mice. In this article, we discuss the pathophysiology of and treatment strategies for NAFLD and subsequent NAFLD-related complications such as NASH and liver tumorigenesis, mainly based on lessons learned from mouse models of high-fat diet-induced NAFLD/NASH.
Bioinformatics Analysis Reveals Distinct Molecular Characteristics of Hepatitis B-Related Hepatocellular Carcinomas from Very Early to Advanced Barcelona Clinic Liver Cancer Stages

Hepatocellular carcinoma (HCC)is the fifth most common malignancy associated with high mortality. One of the risk factors for HCC is chronic hepatitis B virus (HBV) infection. The treatment strategy for the disease is dependent on the stage of HCC, and the Barcelona clinic liver cancer (BCLC) staging system is used in most HCC cases. However, the molecular characteristics of HBV-related HCC in different BCLC stages are still unknown. Using GSE14520 microarray data from HBV-related HCC cases with BCLC stages from 0 (very early stage) to C (advanced stage) in the gene expression omnibus (GEO) database, differentially expressed genes (DEGs), including common DEGs and unique DEGs in different BCLC stages, were identified. These DEGs were located on different chromosomes. The molecular functions and biology pathways of DEGs were identified by gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and the interactome networks of DEGs were constructed using the NetVenn online tool. The results revealed that both common DEGs and stage-specific DEGs were associated with various molecular functions and were involved in special biological pathways. In addition, several hub genes were found in the interactome networks of DEGs. The identified DEGs and hub genes promote our understanding of the molecular mechanisms underlying the development of HBV-related HCC through the different BCLC stages, and might be used as staging biomarkers or molecular targets for the treatment of HCC with HBV infection.
Triangular-Mesh-Based FDTD Analysis of Two-Dimensional Plasmonic Structures Supporting Backward Waves at Optical Frequencies

In this paper, the periodic analysis of candidate plasmonic topologies for the implementation of left-handed media at optical frequencies is pursued through a triangular-mesh-based finite-difference time-domain (FDTD), equipped with Floquet boundary conditions. The technique is shown to possess excellent convergence and accuracy properties, as opposed to the conventional rectangular-cell-based FDTD. The latter fails to accurately capture the plasmonic resonant modes excited in the lattices under consideration. The studies presented in this paper are particularly aimed at rigorously investigating the possibility of backward-wave propagation in periodic arrays of plasmonic nanoparticles, along with their potential analogy to microwave negative-refractive index transmission-line metamaterials
Sufficient Numbers of Early Germ Cells Are Essential for Female Sex Development in Zebrafish

The sex determination for zebrafish is controlled by a combination of genetic and environmental factors. The determination of sex in zebrafish has been suggested to rely on a mechanism that is affected by germ cell-derived signals. To begin our current study, a simplified and efficient germ cell-specific promoter of the dead end (dnd) gene was identified. Utilizing the metrodinazole (MTZ)/ bacterial nitroreductase (NTR) system for inducible germ cell ablation, several stable Tg (dnd:NTR-EGFP-3'UTR) and Tg (dnd:NTR-EGFP+3'UTR) zebrafish lines were then generated with the identified promoter. A thorough comparison of the expression patterns and tissue distributions of endogenous dnd and ntr-egfp transcripts in vivo revealed that the identified 2032-bp zebrafish dnd promoter can recapitulate dnd expression faithfully in stable transgenic zebrafish. The correlation between the levels of the germ cell-derived signals and requirement for maintaining the female fate has been also explored with different durations of the MTZ treatments. Our results revealed the decreasing ratios of female presented in the treated transgenic group are fairly associated with the reducing levels of the early germ cell-derived signals. After the juvenile transgenic fish treated with 5 mM MTZ for 20 days, all MTZ-treated transgenic fish exclusively developed into males with subfertilities. Taken together, our results identified here a simplified and efficient dnd promoter, and provide clear evidence indicating that it was not the presence but the sufficiency of signals derived from germ cells that is essential for female sex development in zebrafish. Our model also provides a unique system for sex control in zebrafish studies.
Large deviations and over ow probabilities for thegeneral single-server queue , with applicationsN

We consider from a thermodynamic viewpoint queueing systems where the workload process is assumed to have an associated large deviation principle with arbitrary scaling: there exist increasing scaling functions (at; vt; t 2 R+) and a rate function I such that if (Wt; t 2 R+) denotes the workload process, then lim t! 1 v 1 t log P (Wt=at > w) = I(w) on the continuity set of I . In the case that at = vt = t it has been argued heuristically, and recently proved in a fairly general context (for discrete time models) by Glynn and Whitt [8], that the queue-length distribution (that is, the distribution of supremum of the workload process Q = supt 0Wt) decays exponentially: P (Q > b) e b and the decay rate is directly related to the rate function I . We establish conditions for a more general result to hold, where the scaling functions are not necessarily linear in t: we nd that the queue-length distribution has an exponential tail only if limt! 1 at=vt is nite and strictly positive; otherwise, provided our conditions are satis ed, the tail probabilities decay like P (Q > b) e v(a 1(b)): We apply our results to a range of workload processes, including fractional Brownian motion (a model that has been proposed in the literature (see, for example, Leland et al [10] and Norros [15, 16]) to account for self-similarity and long range dependence) and, more generally, Gaussian processes with stationary increments. We show that the martingale upper bound estimates obtained by Kulkarni and Rolski [5], when the workload is modelled as an Ornstein-Uhlenbeck position process, are asymptotically correct. Finally we consider a non-Gaussian example, where the arrivals are modelled by a squared Bessel process. 2