Miracle-dz/UniFAR-FTUs huggingface dataset:
A Fruitful Resolution to Simpson ’ s Paradox via Multi-Resolution Inference

Simpson’s Paradox is really a Simple Paradox if one at all. Peeling away the paradox is as easy (or hard) as avoiding a comparison of apples and oranges, a concept requiring no mention of causality. We show how the commonly adopted notation has committed the gross-ery mistake of tagging unlike fruit with alike labels. Hence, the “fruitful” question to ask is not “Do we condition on the third variable,” but rather “Are two fruits which appear similar, actually similar at their core? ”. We introduce the concept of intrinsic similarity to sort through this mess. The notion of “core” depends on how deep one looks—the multi-resolution inference framework provides a natural way to define intrinsic similarity at the resolution appropriate for the treatment. To harvest the fruits of this insight, we will need to estimate intrinsic similarity, which often results in an indirect conditioning on the “third variable. ” A ripening estimation theory shows that the standard treatment comparisons, unconditional or conditional on the third variable, are low hanging fruit but often rotten. We pose assumptions to pluck away higher resolution (more conditional) comparisons—the multi-resolution framework allows us to rigorously assess the price of these assumptions against the resulting yield. One such assessment gives us Simpson’s Warning: less conditioning is most likely to lead to serious bias when Simpson’s Paradox appears. 1 The Source of Confusions and Debates 1.1 Comparing Apples and Oranges Imagine Ms. Broken going to Dr. Heal to be treated for heart disease. A new treatment was made available to Dr. Heal, who also learned from a clinical trial that it can substantially outperform a standard treatment used as its control. However, its effectiveness depends on a patient’s cholesterol level, which can also be altered significantly by the treatment. Therefore, to determine the appropriate treatment for Ms. Broken, Dr. Heal needs to know how trial subjects with cholesterol level similar to Ms. Broken’s (say about 240 mg/dL) responded to the two treatments. The clinical trial data did include cholesterol measurements for patients. Dr. Heal therefore seems to face a rather simple task: compare the treatment effects and side effects among those in the clinical trial with cholesterol level at 240 mg/dL. Or using the terminology of Dr. Armistead’s stimulating paper, Dr. Heal needs to condition on the third variable, cholesterol level, Z = 240, when comparing the outcome variable Y (e.g., Y = 1 indicates success and Y = 0 otherwise) between the treatment group (indicated by T = 1) and the control group (T = 0). So why all the fuss about whether or not to condition on the third variable Z? Since conditioning always leads to a more refined state space, shouldn’t we always condition, at least in theory? The answer is yes, provided that we condition on the right conditions. In the scenario above, we were deliberately
Prague Dependency Style Treebank for Tamil

Annotated corpora such as treebanks are important for the development of parsers, language applications as well as understanding of the language itself. Only very few languages possess these scarce resources. In this paper, we describe our efforts in syntactically annotating a small corpora (600 sentences) of Tamil language. Our annotation is similar to Prague Dependency Treebank (PDT) and consists of annotation at 2 levels or layers: (i) morphological layer (m-layer) and (ii) analytical layer (a-layer). For both the layers, we introduce annotation schemes i.e. positional tagging for m-layer and dependency relations for a-layers. Finally, we discuss some of the issues in treebank development for Tamil.
The Willingness to Seek Help: A Cross-National Comparison

Building on previous research that provides the basis for treating the willingness to seek help as a stable attitudinal set, present in varying degrees in differentpersons, and predictive of behavior, this study addresses two questions: First, to what extent is the willing ness to seek help associated with culture? Second, how do the factors influencing willingness to seek help differ across cultures? Young adults in Hungary, Israel, and the United States (N = 384) provided sociodemographic information and filled out a questionnaire designed to measure their willingness to seek help. The results of the analyses indicate differences between the three countries in the overall willingness to seek help and in the variables predictive of the willingness to seek help. These differences are attributed to differential features of the cultures from which the three subsamples were drawn.
Photodynamic therapy versus surgical excision to basal cell carcinoma: meta‐analysis

Surgical excision (SE) is a first‐line treatment for basal cell carcinoma (BCC). Topical photodynamic therapy (PDT) has also been used and has cosmetic advantages over surgery. The latest European guidelines for topical PDT recommended that it be used to treat nodular basal cell carcinoma (nBCC) but a consensus has not been reached. Our study was to evaluate the efficacy of PDT versus SE for the treatment for nBCC by a meta‐analysis.
OSMOTIC STRESS-INDUCED CHANGES IN GERMINATION, GROWTH AND SOLUBLE SUGAR CONTENT OF SORGHUM BICOLOR (L.) MOENCH SEEDS

Summary. The effect of osmotic stress on germination, growth and soluble sugar content in Sorghum bicolor (L.) Moench cv. CSH 9 seeds and seedling components (endosperm and embryos) during early germination was investigated. Under stress conditions germination decreased markedly, whereas the control at the same time reached its maximum germination (99%). A high percentage (67%) of ungerminated seeds from mannitol treatment germinated after washing with distilled water. Both water potential and tissue water content of both embryo and endosperm showed a slight recovery after re-watering. As compared to the control, fresh weight was reduced by osmotic stress both in germinated embryos and endosperm after 14 h of development. On the contrary, a substantial increase in dry weight was observed in both embryo and endosperm. Furthermore, a considerable increase in the sugar levels in both embryo and endosperm were detected under stress conditions. Total sugar and reducing sugar content increased markedly after 14 h of stress imposition. These parameters were maintained principally in endosperm after stress was released. The fructose level was always higher than glucose and sucrose in response to mannitol treatment. However, the level of glucose and sucrose was higher in the embryos and endosperm after stress treatments than in the controls. Based upon these results a possible physiological role of sugars in germination of sorghum seeds was suggested.
Functional regulatory variants of MCL1 contribute to enhanced promoter activity and reduced risk of lung cancer in nonsmokers: Implications for context‐dependent phenotype of an antiapoptotic and antiproliferative gene in solid tumor

Dysfunction of molecules that regulate both apoptosis and proliferation is involved in tumorigenesis. A common insertional polymorphism in promoter of MCL1, a member of BCL2 family gene with the dual regulatory functions, has been shown to be functional in leukemia, but its association with cancer predisposition and prognosis has not been well established. We hypothesized that MCL1 promoter variants may modify risk of solid cancer.
Rényi Differential Privacy

We propose a natural relaxation of differential privacy based on the Rényi divergence. Closely related notions have appeared in several recent papers that analyzed composition of differentially private mechanisms. We argue that the useful analytical tool can be used as a privacy definition, compactly and accurately representing guarantees on the tails of the privacy loss.We demonstrate that the new definition shares many important properties with the standard definition of differential privacy, while additionally allowing tighter analysis of composite heterogeneous mechanisms.
UEFA Champions League study: a prospective study of injuries in professional football during the 2001–2002 season

Background: No previous study on adult football involving several different countries has investigated the incidence and pattern of injuries at the highest club competitive level. Objective: To investigate the risk exposure, risk of injury, and injury pattern of footballers involved in UEFA Champions League and international matches during a full football season. Method: Eleven top clubs (266 players) in five European countries were followed prospectively throughout the season of 2001–2002. Time-lost injuries and individual exposure times were recorded during all club and national team training sessions and matches. Results: A total of 658 injuries were recorded. The mean (SD) injury incidence was 9.4 (3.2) injuries per 1000 hours (30.5 (11.0) injuries per 1000 match hours and 5.8 (2.1) injuries per 1000 training hours). The risk of match injury was significantly higher in the English and Dutch teams than in the teams from France, Italy, and Spain (41.8 (3.3) v 24.0 (7.9) injuries per 1000 hours; p = 0.008). Major injuries (absence >4 weeks) constituted 15% of all injuries, and the risk of major injury was also significantly higher among the English and Dutch teams (p = 0.04). National team players had a higher match exposure, with a tendency towards a lower training injury incidence than the rest of the players (p = 0.051). Thigh strain was the most common injury (16%), with posterior strains being significantly more common than anterior ones (67 v 36; p<0.0001). Conclusions: The risk of injury in European professional football is high. The most common injury is the thigh strain typically involving the hamstrings. The results suggest that regional differences may influence injury epidemiology and traumatology, but the factors involved are unclear. National team players have a higher match exposure, but no higher risk of injury than other top level players.
Introducing the 8A Model in Death Education Training: Promoting Planning for End-Of-Life Care for Hong Kong Chinese

Although planning for end-of-life care is crucial, it is underdeveloped in the Hong Kong Chinese context. To review the local experience in death education training, it was found that helping professionals may not be equipped with adequate knowledge and skills to deal with the various needs of clients in death preparation and planning for end-of-life care. In view of this, an 8A model (alienation, avoidance, access, acknowledgment, action, acceptance, appreciation, and actualization) was developed as a framework for providing death education to these professionals. The 8A model adapted the Transtheoretical model for understanding the needs of clients in different phases of behavior change. In this article, details of the 8A model and how it can enhance professionals' work with clients in death education and planning for end-of-life care are discussed.
Cross-pose Face Recognition by Canonical Correlation Analysis

The pose problem is one of the bottlenecks in automatic face recognition. We argue that one of the diffculties in this problem is the severe misalignment in face images or feature vectors with different poses. In this paper, we propose that this problem can be statistically solved or at least mitigated by maximizing the intra-subject across-pose correlations via canonical correlation analysis (CCA). In our method, based on the data set with coupled face images of the same identities and across two different poses, CCA learns simultaneously two linear transforms, each for one pose. In the transformed subspace, the intra-subject correlations between the different poses are maximized, which implies pose-invariance or pose-robustness is achieved. The experimental results show that our approach could considerably improve the recognition performance. And if further enhanced with holistic+local feature representation, the performance could be comparable to the state-of-the-art.
Strategies for rehabilitation professionals to move evidence-based knowledge into practice: a systematic review.

RATIONALE Rehabilitation clinicians need to stay current regarding best practices, especially since adherence to clinical guidelines can significantly improve patient outcomes. However, little is known about the benefits of knowledge translation interventions for these professionals. OBJECTIVES To examine the effectiveness of single or multi-component knowledge translation interventions for improving knowledge, attitudes, and practice behaviors of rehabilitation clinicians. METHODS Systematic review of 7 databases conducted to identify studies evaluating knowledge translation interventions specific to occupational therapists and physical therapists. RESULTS 12 studies met the eligibility criteria. For physical therapists, participation in an active multi-component knowledge translation intervention resulted in improved evidence-based knowledge and practice behaviors compared with passive dissemination strategies. These gains did not translate into change in clinicians' attitudes towards best practices. For occupational therapists, no studies have examined the use of multi-component interventions; studies of single interventions suggest limited evidence of effectiveness for all outcomes measured. CONCLUSION While this review suggests the use of active, multi-component knowledge translation interventions to enhance knowledge and practice behaviors of physical therapists, additional research is needed to understand the impact of these strategies on occupational therapists. Serious research gaps remain regarding which knowledge translation strategies impact positively on patient outcomes.
Job insecurity and change over time in health among older men and women.

OBJECTIVES We estimated associations between job insecurity and change over time in the physical and psychological health of older adult men and women. METHODS We conducted secondary analyses of longitudinal data from men and women (N = 190) born between 1935 and 1952 in the Chicago Health, Aging, and Social Relations Study. We used multivariate regression techniques to test the association of job insecurity with changes in physical health (self-reported global health, resting blood pressure, and urinary catecholamines [epinephrine]) and psychological health (depressive symptoms, hostility, loneliness, and personal stress). We controlled for individual characteristics and baseline measures of the outcomes. RESULTS Men who experience job insecurity rate themselves in significantly poorer physical health and have higher blood pressure and higher levels of urinary catecholamines compared with men who do not experience job insecurity and women who do. Women who experience job insecurity show higher depressive symptoms and report more hostility, loneliness, and personal stress compared with women who do not experience job insecurity and men who do. DISCUSSION The correlation between job insecurity and health is different in men and women but may be clinically significant in both populations and is a potentially important threat to older adults' health and well-being.
Flow-Based Reputation: More than Just Ranking

The last years have seen a growing interest in collaborative systems like electronic marketplaces and P2P file sharing systems where people are intended to interact with other people. Those systems, however, are subject to security and operational risks because of their open and distributed nature. Reputation systems provide a mechanism to reduce such risks by building trust relationships among entities and identifying malicious entities. A popular reputation model is the so-called flow-based model. Most existing reputation systems based on such a model provide only a ranking, without absolute reputation values; this makes it difficult to determine whether entities are actually trustworthy or untrustworthy. In addition, those systems ignore a significant part of the available information; as a consequence, reputation values may not be accurate. In this paper, we present a flow-based reputation metric that gives absolute values instead of merely a ranking. Our metric makes use of all the available information. We study, both analytically and numerically, the properties of the proposed metric and the effect of attacks on reputation values.
A probabilistic model for estimating driver behaviors and vehicle trajectories in traffic environments

This paper presents a filter that is able to simultaneously estimate the behaviors of traffic participants and anticipate their future trajectories. This is achieved by recognizing the type of situation derived from the local situational context, which subsumes all information relevant for the drivers decision making. By explicitly taking into account the interactions between vehicles, it achieves a comprehensive situational understanding, inevitable for autonomous vehicles and driver assistance systems. This provides the necessary information for safe behavior decision making or motion planning. The filter is modeled as a Dynamic Bayesian Network. The factored state space, modeling the causal dependencies, allows to describe the models in a compact fashion and reduces the computational complexity of the inference process. The filter is evaluated in the context of a highway scenario, showing a good performance even with very noisy measurements. The presented framework is intended to be used in traffic environments but can be easily transferred to other robotic domains.
Direct kernel PCA with RBF neural networks for face recognition

The conventional kernel PCA does not really nonlinearly maps an input image into a high-dimensional feature space. Rather, it chooses a kernel function a priori and computes the principal components indirectly within the input space spanned by the image pixels. Thus method does not consider the structural information of the input images in the feature space. Therefore, the computed principal components have less discriminating power. In this paper, a new kernel PCA, referred to as the direct kernel PCA (DKPCA), is proposed for face recognition, which explicitly maps an input image nonlinearly into a feature space and then computes the principal components directly in the mapped space. Therefore, this method considers the structural information of the input images in the feature space for computation of principal components, leading to have higher discriminating power. We have designed RBF neural networks for classification of input images based on the computed principal components. The proposed method is evaluated on the ORL database. The results indicate that the proposed method is able to achieve excellent performance and outperforms some of the reported methods using the conventional kernel PCA.
Effects of chondroitin sulfate and interleukin-1beta on human chondrocyte cultures exposed to pressurization: a biochemical and morphological study.

Objective This study investigated the in vitro effects of chondroitin sulfate (CS) on human articular chondrocytes cultivated in the presence or in the absence of interleukin-1beta (IL-1beta) during 10 days of culture with and without pressurization cycles. Design The effects of CS (10 and 100 microg/ml) with and without IL-1beta were assessed in the culture medium of cells exposed to pressurization cycles in the form of synusoidal waves (minimum pressure 1 Mpa, maximum pressure 5 Mpa) and a frequency of 0.25 Hz for 3 h by immunoenzymatic method on microplates for the quantitative measurement of human proteoglycans (PG). On the 4th and 10th day of culture the cells were used for morphological analysis by transmission electron microscopy (TEM) and scanning electron microscopy (SEM). Results The presence of IL-1beta determines a significant decrease in PG concentration measured in the culture medium. When the cells are cultured in the presence of IL-1beta and CS, a statistically significant restoration of PG levels is observed. Under pressurization conditions, we observed that PG concentration in the medium of cells presents a significant increase at baseline conditions, in the presence of IL-1beta+CS10 and IL-1beta+CS100, but not with IL-1beta alone. The results concerning metabolic evaluation are confirmed by the morphologic findings obtained by TEM and SEM. Conclusions These in vitro studies confirm the protective role of CS, which counteracts the IL-1beta induced effects and they confirm the importance of pressure on chondrocyte metabolism and morphology.
Genomics and proteomics in stem cell research: the road ahead

Stem cell research has been widely studied over the last few years and has attracted increasing attention from researchers in all fields of medicine due to its potential to treat many previously incurable diseases by replacing damaged cells or tissues. As illustrated by hematopoietic stem research, understanding stem cell differentiation at molecular levels is essential for both basic research and for clinical applications of stem cells. Although multiple integrative analyses, such as genomics, epigenomics, transcriptomics and proteomics, are required to understand stem cell biology, proteomics has a unique position in stem cell research. For example, several major breakthroughs in HSC research were due to the identification of proteins such as colony-stimulating factors (CSFs) and cell-surface CD molecules. In 2007, the Human Proteome Organization (HUPO) and the International Society for Stem Cell Research (ISSCR) launched the joint Proteome Biology of Stem Cells Initiative. A systematic proteomics approach to understanding stem cell differentiation will shed new light on stem cell biology and accelerate clinical applications of stem cells.
An unsupervised approach for sentiment classification

In this paper we propose a new unsupervised and domain independent approach for sentiment classification. It takes a few documents as the training set to build a sentiment vocabulary list which will be used to classify the documents according to their sentiment orientation. The system is self-supervised and domain independent. Experimental results show that the classification accuracy of the approach can reach 85.7% which is better than the previous experiments of unsupervised methods.
Semi-supervised Video Object Segmentation Using Multiple Random Walkers

A semi-supervised video object segmentation algorithm using multiple random walkers (MRW) is proposed in this work. We develop an initial probability estimation scheme that minimizes an objective function to roughly separate the foreground from the background. Then, we simulate MRW by employing the foreground and background agents. During the MRW process, we update restart distributions using a hybrid of inference restart rule and interactive restart rule. By performing these processes from the second to the last frames, we obtain a segment track of the target object. Furthermore, we optionally refine the segment track by performing Markov random field optimization. Experimental results demonstrate that the proposed algorithm significantly outperforms the state-of-the-art conventional algorithms on the SegTrack v2 dataset.
The coarse-grained HiRE-RNA model for de novo calculations of RNA free energy surfaces, folding pathways and complex structure prediction

HiRE-RNA is a simplified, coarse-grained RNA model for the prediction of equilibrium configurations, dynamics and thermodynamics. Using a reduced set of particles and detailed interactions accounting for base-pairing and stacking we show that non-canonical and multiple base interactions are necessary to capture the full physical behavior of complex RNAs. In this paper we give a full account of the model and we present results on the folding, stability and free energy surfaces of 16 systems with 12 to 76 nucleotides of increasingly complex architectures, ranging from monomers to dimers, using a total of 850$\mu$s simulation time.