Miracle-dz/UniFAR-FTUs huggingface dataset:
EfficientTreeMiner: Mining Frequent Induced Substructures from XML Documents without Candidate Generation

Tree structures are used extensively in domains such as XML databases, computational biology, pattern recognition, computer networks, Web mining, multi-relational data mining and so on. In this paper, we present an EfficientTreeMiner, a computationally efficient algorithm that discovers all frequently occurring induced subtrees in a database of labeled rooted unordered trees. The proposed algorithm mines frequent subtrees without generating any candidate subtrees. Efficiency is achieved by compressing the large database into a condensed data structure, namely prefix string representation, which reduces space complexity and by adopting a frequent immediate descendents method that avoids the costly generation of candidate sets. Experimental results show that our algorithm has less time complexity when compared to existing approaches and is also scalable for mining both long and short frequent subtrees.
What’s your ‘vice?’: a combined approach to drugs and other addictive substances and activities

Abstract A person’s use of addictive substances is generally approached one drug at a time. However, individuals readily report use of many drugs, and interestingly, individuals may also include addictive behaviors or activities (e.g. sex, gambling, computer use or shopping) as being problematic. There is not currently a brief assessment to measure both individuals’ use of drugs and their engaging in addictive behaviors in a single questionnaire; though, one might facilitate scholarly understanding of shared addiction processes and might aid increasingly burdened healthcare systems. The main purpose of this work is to offer a preliminary examination of a brief combined assessment of both drug use and addictive behaviors. Specifically, we asked a sample of n = 306 and a replication sample of n = 173 individuals from the general public to report their ‘choice’ or desired drugs and behaviors, which we termed their ‘vices’, in a single assessment. Findings showed that individuals readily reported having ‘vices’; and individuals reported an average of between 7.09 (SD = 2.66) to 8.09 (SD = 2.52) ‘vices’. Furthermore, a combined approach yielded adequate interitem reliability (Sample 1 α = 0.77, Sample 2 α = 0.79) and construct validity; also, use of the all-encompassing term ‘vices’ did not appear to affect participants’ reporting on other validated measures of drug use. Combined drug and behavior assessments might engage resistant patients and may aid in patient-centered care and lifestyle discussions. Also, offering individuals the opportunity to ‘compare and contrast’ their drugs and addictive behaviors may direct future investigation into cognitive aspects of shared addiction processes.
Transgenesis in Strongyloides and related parasitic nematodes: historical perspectives, current functional genomic applications and progress towards gene disruption and editing

SUMMARY Transgenesis for Strongyloides and Parastrongyloides was accomplished in 2006 and is based on techniques derived for Caenorhabditis elegans over two decades earlier. Adaptation of these techniques has been possible because Strongyloides and related parasite genera carry out at least one generation of free-living development, with adult males and females residing in soil contaminated by feces from an infected host. Transgenesis in this group of parasites is accomplished by microinjecting DNA constructs into the syncytia of the distal gonads of free-living females. In Strongyloides stercoralis, plasmid-encoded transgenes are expressed in promoter-regulated fashion in the F1 generation following gene transfer but are silenced subsequently. Stable inheritance and expression of transgenes in S. stercoralis requires their integration into the genome, and stable lines have been derived from integrants created using the piggyBac transposon system. More direct investigations of gene function involving expression of mutant transgene constructs designed to alter intracellular trafficking and developmental regulation have shed light on the function of the insulin-regulated transcription factor Ss-DAF-16. Transgenesis in Strongyloides and Parastrongyloides opens the possibility of powerful new methods for genome editing and transcriptional manipulation in this group of parasites. Proof of principle for one of these, CRISPR/Cas9, is presented in this review.
Doing Research in Organizational Discourse: The Importance of Researcher Context

What’s involved in doing research in organizational discourse? In this chapter we attempt to answer this question by using five phases of the research process, as identified by Denzin and Lincoln (2000), to guide an examination of the sub-fields of organizational discourse analysis (ODA) (see Table 9.1). Our first aim is to help those new to discourse analysis in organization studies to get started in this field. We also want to encourage researchers who are already using ODA to clarify their own positions and consider a wider repertoire of approaches. The chapter is organized into five sections that address each of Denzin and Lincoln’s five choice points in the research process. At each point we interrogate how one of the sub-fields of organizational discourse undertakes this part of the research process. So, for example, the second choice point involves adopting a theoretical frame or position. Here we discuss frames or positions available in narrative research. In relation to the third choice point – adopting a strategy of inquiry – we discuss strategies used in Foucauldian discourse analysis. As this is a handbook, and not a textbook, we are attempting to strike a balance between helping researchers and engaging critically with the published work itself. In pursuing these aims we have been forced to be highly selective. While we make no apology for this, we would ask the reader to bear this in mind. ‘Organizational discourse’ is not a homogeneous field. It is a series of sub-fields linked together by a substantive concern with language and practice in organizations and organizing. In this chapter we provide particular kinds of ‘snapshot’ of research practice in four of these sub-fields: deconstruction, narrative, linguistic and Foucauldian discourse analysis (see Table 9.1). A key feature of research practice in Denzin and Lincoln’s approach, and one that we strongly support, is developing a reflexive understanding of the context in which researchers find themselves. This practice not only enriches the research practice, it also provides much of the ‘between the lines’ knowledge that can lead to successful research outcomes. The opening section of the chapter – the first choice point – addresses this issue directly. We also open each section with a narrative that profiles the work of different fictional researchers, each named Andy Andrews, as they tackle a different phrase of the work. 1
Ethnicity and Gender Comparisons of Health Consequences in Adults with Alcohol Dependence

The moderating effects of ethnicity and gender on factors associated with physical health consequences in adults manifesting alcohol dependence were examined using data from the 2001–2002 US National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Black and white respondents with a lifetime diagnosis of DSM-IV alcohol dependence were selected for the study (n = 3,852). A multiple-group structural equation model tested ethnicity, gender, and intervening variables as predictors of physical health status in alcohol-dependent men and women. Study findings offer implications for clinical practice with alcohol-dependent individuals by identifying likely target groups and problems for intervention.
Hierarchical Radiosity for Dynamic Environments

This paper extends the hierarchical radiosity method to environments in which geometry and surface attributes can be changed dynamically. New algorithms are presented for maintaining an appropriately‐sized mesh and speeding the construction of the corresponding linear system. Mesh folding, the unrefinement of a mesh, is used to optimize mesh size while maintaining a specified error tolerance. Two new interactions are introduced: shadow links guide local shadow clean up after a change in geometry and ghost links guide global mesh folding after a change in surface attributes. The algorithms stabilize the memory requirements of dynamic scenes. Different types of interactions are analyzed to determine how they are affected by changes in geometry. A dynamic scene‐partitioning scheme called a motion volume, used in conjunction with a three‐dimensional clipping algorithm, provides a fast way to cull interactions that do not need to be updated. The algorithms are demonstrated on several sample scenes.
Limits of Predictability in Human Mobility

Predictable Travel Routines While people rarely perceive their actions to be random, current models of human activity are fundamentally stochastic. Processes that rely on human mobility patterns, like the prediction of new epidemics, traffic engineering, or city planning, could benefit from highly accurate predictive models. To investigate the predictability of human dynamics, Song et al. (p. 1018) used the recorded trajectories of millions of mobile phone users, collected by mobile phone companies and anonymized for research purposes. They hypothesized that given the wide range of travel patterns that different users follow, there would be significant differences between their predictability as well: Users who travel less should be easier to predict than those who are constantly on the road. Surprisingly, there was 93% predictability across the whole user base, and individuals' predictability did not in general fall significantly below 80%. Analysis of the trajectories of people carrying cell phones reveals that human mobility patterns are highly predictable. A range of applications, from predicting the spread of human and electronic viruses to city planning and resource management in mobile communications, depend on our ability to foresee the whereabouts and mobility of individuals, raising a fundamental question: To what degree is human behavior predictable? Here we explore the limits of predictability in human dynamics by studying the mobility patterns of anonymized mobile phone users. By measuring the entropy of each individual’s trajectory, we find a 93% potential predictability in user mobility across the whole user base. Despite the significant differences in the travel patterns, we find a remarkable lack of variability in predictability, which is largely independent of the distance users cover on a regular basis.
A trial of Acceptance and Commitment Therapy to facilitate psychological adjustment after a traumatic brain injury

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Evaluation of Query Transformations without Data: Short paper

Query transformations are ubiquitous in semantic web query processing. For any situation in which transformations are not proved correct by construction, the quality of these transformations has to be evaluated. Usual evaluation measures are either overly syntactic and not very informative the result being: correct or incorrect or dependent from the evaluation sources. Moreover, both approaches do not necessarily yield the same result. We suggest that grounding the evaluation on query containment allows for a data-independent evaluation that is more informative than the usual syntactic evaluation. In addition, such evaluation modalities may take into account ontologies, alignments or different query languages as soon as they are relevant to query evaluation.
Object tracking in thermal imaging using kemelized correlation filters

Object tracking algorithms in thermal imaging are very important in both civil and military applications, especially in the domain of surveillance and monitoring. Compared with visual object tracking, thermal infrared tracking has several advantages, but also possesses certain undesirable properties which makes the tracking task more challenging. With the aim of overcoming them, we apply a state-of-the-art Kernelized Correlation Filters (KCF) based tracking algorithm, which demonstrates high accuracy and robustness in visual tracking tasks, with very low computational complexity, and possibility of using almost arbitrary feature representations of the target, as well as nonlinear kernels. The algorithm has been tested on several chosen examples, using two different feature representations (raw pixels and HOG features). The simulation results are promising, with good performance even in the situations considered to be hard for thermal tracking.
3D and 4D modeling for AR and VR app developments

The design of three-dimensional and four-dimensional Apps, running on the leading operating systems Android, iOS and Windows is the next challenge in Architecture, BIM, Civil Engineering, Digital Cultural Heritage (DCH) preservations and many more. Based on experiences developing Apps for archaeology and architecture, the paper introduces with general workflows for 3D data collection, using laser scanning, geometric computer vision and photogrammetry. The resulting point clouds have to be merged, using the most recent developments of laser scanning, computer vision, photogrammetry and statistical inference. 3D and 4D modeling is done using professional software from surveying and computer graphics, such as Leica's Cyclone, Trimble's SketchUp and Autodesk 3ds Max. The fourth dimension, time, is injected onto the 3D contemporary models using the texture of old photos. After homogenization of all 3D models in Autodesk 3ds Max these are exported to the game engine Unity to allow for the creation of the reference surface and finally the 3D urban model. The storyboard creates for the programmer an outline, which features and functions have to be fulfilled. Finally the Apps for Android, iOS and Windows are created and exported for the use on mobile devices.
Outlier detection based on local minima density

Outlier is great concern in machine learning task and the traditional methods based on nearest neighbor outlier detection have some weaknesses: performance is sensitive to parameter k, and interpretability is not strong. In this paper, based on the novel idea that outlier objects have lower density than their neighbors and relatively large distance from objects with higher density, we propose a new algorithm for outlier detection to overcome the weakness above. We compared the proposed method with other existing methods based on various types of synthetic datasets. We also applied the proposed method in real water quality data. The results of the numerical experiments indicated that the proposed method has better effectiveness, stability, and interpretability on the detection of low-density outlier detection.
Adipose Tissue Lactate Clearance but Not Blood Lactate Clearance Is Associated with Clinical Outcome in Sepsis or Septic Shock during the Post-Resuscitation Period

No study has directly measured tissue lactate clearance in patients with sepsis during the post-resuscitation period. In this study we aimed to assess in ICU patients with sepsis (n = 32) or septic shock (n = 79)—during the post-resuscitation phase—the relative kinetics of blood/tissue lactate clearances and to examine whether these are associated with outcome. We measured serially—over a 48-h period—blood and adipose tissue interstitial fluid lactate levels (with microdialysis) and we calculated lactate clearance. Statistics included mixed model analysis, Friedman’s analysis of variance, Wilcoxon’s test, Mann-Whitney’s test, receiver operating characteristics curves and logistic regression. Forty patients died (28-day mortality rate = 28%). Tissue lactate clearance was higher compared to blood lactate clearance at 0–8, 0–12, 0–16, 0–20 and 0–24 h (all p < 0.05). Tissue lactate clearance was higher in survivors compared to non-survivors at 0–12, 0–20 and 0–24 h (all p = 0.02). APACHE II along with tissue lactate clearance <30% at 0–12, 0–20 and 0–24 h were independent outcome predictors. We did not find blood lactate clearance to be related to survival. Thus, in critically ill septic patients, elevated tissue (but not blood) lactate clearance, was associated with a favorable clinical outcome.
How Much Do Innovation Strategies Differ across Firms, Industries and Countries? *

Our aim is to quantify innovation strategies of firms based on evidence from the CIS data. Using exploratory factor analysis on micro data from CIS3 in 13 countries, we identify four factors that that can be interpreted as research based , user-driven, extensive and social responsibility innovation strategies. Since it has been put forward that diversity in the way how firms innovate can be explained by differences across sectors and/or countries, we explore to what extent the innovation strategy of a firm is influenced by this context. We use cross-classified mixed-effects model to partition the variation of innovation strategies into components identified by sectors, countries, and idiosyncrasies at the firm level. The analysis shows that sectors and countries matter to a certain extent, but most of the variance (from 80 to 95%) is given by heterogeneity among firms. Eurostat has no responsibility for the results and conclusions in this paper. The earlier version of the paper was presented at the EU 6 th Framework project MICRO-DYN workshop, Cambridge, 10-12 September 2007. We thank Cristina Chaminade and participants at the workshop for comments and suggestions to the preliminary draft of the paper. All usual caveats apply.
Allergic Lung Inflammation Aggravates Angiotensin II–Induced Abdominal Aortic Aneurysms in Mice

Objective— Asthma and abdominal aortic aneurysms (AAA) both involve inflammation. Patients with asthma have an increased risk of developing AAA or experiencing aortic rupture. This study tests the development of one disease on the progression of the other. Approach and Results— Ovalbumin sensitization and challenge in mice led to the development of allergic lung inflammation (ALI). Subcutaneous infusion of angiotensin II into mice produced AAA. Simultaneous production of ALI in AAA mice doubled abdominal aortic diameter and increased macrophage and mast cell content, arterial media smooth muscle cell loss, cell proliferation, and angiogenesis in AAA lesions. ALI also increased plasma IgE, reduced plasma interleukin-5, and increased bronchioalveolar total inflammatory cell and eosinophil accumulation. Intraperitoneal administration of an anti-IgE antibody suppressed AAA lesion formation and reduced lesion inflammation, plasma IgE, and bronchioalveolar inflammation. Pre-establishment of ALI also increased AAA lesion size, lesion accumulation of macrophages and mast cells, media smooth muscle cell loss, and plasma IgE, reduced plasma interleukin-5, interleukin-13, and transforming growth factor-&bgr;, and increased bronchioalveolar inflammation. Consequent production of ALI also doubled lesion size of pre-established AAA and increased lesion mast cell and T-cell accumulation, media smooth muscle cell loss, lesion cell proliferation and apoptosis, plasma IgE, and bronchioalveolar inflammation. In periaortic CaCl2 injury–induced AAA in mice, production of ALI also increased AAA formation, lesion inflammation, plasma IgE, and bronchioalveolar inflammatory cell accumulation. Conclusions— This study suggests a pathological link between airway allergic disease and AAA. Production of one disease aggravates the progression of the other.
Nonlocal segmentation of point clouds with graphs

In this paper, we propose a nonlocal approach based on graphs to segment raw point clouds as a particular class of graph signals. Using the framework of Partial difference Equations (PdEs), we propose a transcription on graphs of recent continuous global active contours along with a minimization algorithm. To apply it on point clouds, we show how to represent a point cloud as a graph weighted with patches. Experiments show the benefits of the approach on raw colored point clouds obtained from real scans.
Recent and Frequent Nonsuicidal Self-Injury Is Associated With Diminished Implicit and Explicit Aversion Toward Self-Cutting Stimuli

In the present study, we tested the hypothesis that an instinctive barrier to nonsuicidal self-injury (NSSI)—the aversion to self-cutting stimuli—is diminished in people who engage in NSSI. In a sample of 86 noninjurers and 58 people with a history of self-cutting, we found that NSSI was associated with substantially reduced aversion to self-cutting stimuli across measures of both implicit (d = 0.61) and explicit (d = 0.93) affect even after controlling for emotion reactivity and dysregulation. This diminished aversion primarily applied to individuals who had engaged in NSSI within the past year or who had 10 or more lifetime episodes of self-cutting (ds = 0.87–1.23). Implicit identification with NSSI also significantly distinguished between groups (d = 0.67) but was not correlated with affective measures or NSSI recency/frequency. Although previous work has shown that the affective benefits of NSSI are natural and universal, these findings suggest that diminished instinctive barriers to NSSI may be specific NSSI risk factors that can be targeted in novel interventions.
Power Management for Kinetic Energy Harvesting IoT

Human kinetic energy is regarded as a promising sustainable energy source to solve the energy bottleneck of Internet of Things (IoT). The low power harvested from human motion and scarce hardware resource of IoT severely restrain the operation of kinetic energy harvesting IoT and stress the need for power management strategies to improve the energy efficiency. In this paper, we propose a novel power management framework for kinetic energy harvesting IoT, composed of an off-line inertial harvester optimization algorithm and an on-line joint sink selection and transmission power control module. By analyzing the characteristics of human daily motion and the inertial harvester model, the optimal inertial harvester parameters are determined to maximize the power generation from human daily motion. The on-line scheme improves energy efficiency by joint consideration of optimal sink selection (i.e., on-body sink or off-body sink) and transmission power control. The real world human motion data set is used to evaluate the proposed framework. The simulation results indicate that, compared with the existing approach, the proposed kinetic harvester optimization algorithm achieves 83.31% to 135.69% improvement in harvested power from the same human motion trace. In addition, the proposed on-line joint sink selection and transmission power control incurs 7.07% to 34.23% improvement in transmission energy efficiency.