Miracle-dz/UniFAR-FTUs huggingface dataset:
WI-ENRE in CLEF eHealth Evaluation Lab 2015: Clinical Named Entity Recognition Based on CRF

Named entity recognition of biomedical text is the shared task 1b of the 2015 CLEF eHealth evaluation lab, which focuses on making biomedical text easier to understand for patients and clinical workers. In this paper, we propose a novel method to recognize clinical entities based on conditional random fields (CRF). The biomedical texts are split into sections and paragraphs. Then the NLP tools are used for POS tagging and parsing, and four groups of features are ex- tracted to train the entity recognition model. In the subsequent phase for entity normalization, the MetaMap of Unified Medical Language System (UMLS) tool is used to search for concept unique identifiers (CUIs) category. In addition, CRF++ package is adopted to recognize clinical entities in another phase for en- tity recognition. The experiments show that our system named as WI-ENRE, is effective in the named entity recognition of biomedical texts. The Fmeasure of EMEA and MEDLINE reach to 0.56 and 0.45 respectively in exact match.
The Electron Transfer System of Syntrophically Grown Desulfovibrio vulgaris

ABSTRACT Interspecies hydrogen transfer between organisms producing and consuming hydrogen promotes the decomposition of organic matter in most anoxic environments. Although syntrophic coupling between hydrogen producers and consumers is a major feature of the carbon cycle, mechanisms for energy recovery at the extremely low free energies of reactions typical of these anaerobic communities have not been established. In this study, comparative transcriptional analysis of a model sulfate-reducing microbe, Desulfovibrio vulgaris Hildenborough, suggested the use of alternative electron transfer systems dependent on growth modality. During syntrophic growth on lactate with a hydrogenotrophic methanogen, numerous genes involved in electron transfer and energy generation were upregulated in D. vulgaris compared with their expression in sulfate-limited monocultures. In particular, genes coding for the putative membrane-bound Coo hydrogenase, two periplasmic hydrogenases (Hyd and Hyn), and the well-characterized high-molecular-weight cytochrome (Hmc) were among the most highly expressed and upregulated genes. Additionally, a predicted operon containing genes involved in lactate transport and oxidation exhibited upregulation, further suggesting an alternative pathway for electrons derived from lactate oxidation during syntrophic growth. Mutations in a subset of genes coding for Coo, Hmc, Hyd, and Hyn impaired or severely limited syntrophic growth but had little effect on growth via sulfate respiration. These results demonstrate that syntrophic growth and sulfate respiration use largely independent energy generation pathways and imply that to understand microbial processes that sustain nutrient cycling, lifestyles not captured in pure culture must be considered.
Evaluating Semantic Relations and Distances in the Associative Concept Dictionary using NIRS-imaging

In this study, we extracted brain activities related to semantic relations and distances to improve the precision of distance calculation among concepts in the Associated Concept Dictionary (ACD). For the experiments, we used a multi-channel Near-infrared Spectroscopy (NIRS) device to measure the response properties of the changes in hemoglobin concentration during word-concept association tasks. The experiments stimuli were selected from pairs of stimulus words and associated words in the ACD and presented in the form of a visual stimulation to the subjects. In our experiments, we obtained subject response data and brain activation data in Broca's area ―a human brain region that is active in linguistic/word-concept decision tasks― and these data imply relations with the length of associative distance. This study showed that it was possible to connect brain activities to the semantic relation among concepts, and that it would improve the method for concept distance calculation in order to build a more human-like ontology model.
Wildfire risk adaptation: propensity of forestland owners to purchase wildfire insurance in the southern United States

The economic and ecological damages caused by wildfires are alarming. Because such damages are expected to increase with changes in wildfire regimes, this calls for more effective wildfire mitigation and adaptation strategies. Wildfire adaptation options for forestland owners include purchasing wildfire insurance, which provides compensation to those insured if a wildfire damages their properties. We attempt to (i) identify factors that influence the decision of family forestland owners in the southern United States to purchase wildfire insurance for their forestlands via logistic regression using landowner survey data and (ii) examine the propensity of these landowners to purchase wildfire insurance under climate change. We find that landowners are much more likely to purchase wildfire insurance if they are female or well educated or if their land is not classed as heirs’ property, has been hit by a hurricane, or has not been burned by wildfire previously. Because climate change is likely to alter future.
Surface Waves Investigation of a Bianisotropic Chiral Substrate Resonator

In this paper we studied the efiect of a chiral-substrate bianisotropy on the surface waves of the microstrip resonator. The efiective technique used to formulate the characteristic equations of the surface waves in a medium equipped with a complex anisotropy is presented and detailed. The equations concerning an evaluation of the cut-ofi frequencies are given in more detailed forms. A simple approximate formula for estimating the wave number of the surface mode TM0 and TE1 are obtained. An estimated maximum value of chiral slab thickness without the excitation of surface waves is given. All of our original results are compared with those published in the literature.
Hierarchical Spatial Process Models for Multiple Traits in Large Genetic Trials

This article expands upon recent interest in Bayesian hierarchical models in quantitative genetics by developing spatial process models for inference on additive and dominance genetic variance within the context of large spatially referenced trial datasets of multiple traits of interest. Direct application of such multivariate models to large spatial datasets is often computationally infeasible because of cubic order matrix algorithms involved in estimation. The situation is even worse in Markov chain Monte Carlo (MCMC) contexts where such computations are performed for several thousand iterations. Here, we discuss approaches that help obviate these hurdles without sacrificing the richness in modeling. For genetic effects, we demonstrate how an initial spectral decomposition of the relationship matrices negates the expensive matrix inversions required in previously proposed MCMC methods. For spatial effects we discuss a multivariate predictive process that reduces the computational burden by projecting the original process onto a subspace generated by realizations of the original process at a specified set of locations (or knots). We illustrate the proposed methods using a synthetic dataset with multivariate additive and dominant genetic effects and anisotropic spatial residuals, and a large dataset from a scots pine (Pinus sylvestris L.) progeny study conducted in northern Sweden. Our approaches enable us to provide a comprehensive analysis of this large trial which amply demonstrates that, in addition to violating basic assumptions of the linear model, ignoring spatial effects can result in downwardly biased measures of heritability.
Hierarchical probabilistic graphical models for large-scale data analysis

Probabilistic graphical models such as Bayesian networks are very useful for exploratory data analysis because of their ability to visualize conditional independencies among random variables. They can also be applied to classification tasks by inferencing necessary conditional probabilities from the joint probability distribution. Thus, they have been adopted for various data mining tasks. However, learning them from large-scale data, consisting of thousands of attributes, still remains a challenge. In real-world problems, there are lots of such cases, e.g., microarray data analysis in bioinformatics. To apply probabilistic graphical models to analysis of such large-scale data, the following two problems should be resolved. The first problem is to learn the model structure consisting of thousands of variables. The second one is about the reliability of learned results. In general, a greedy search algorithm is employed for learning the structure of Bayesian networks, which are a kind of probabilistic graphical models, widely used for data mining. The computational complexity of such structural learning algorithms increases substantially as the number of variables grows. Hence, they are not applicable to the situations involving thousands of variables. Further, it would be nearly impossible to extract useful knowledge about underlying probabilistic nature by vetting the learned structure having thousands of vertices and edges. In this dissertation, we propose the use of hierarchical probabilistic graphical models (HPGMs) based on information compression and constrained structural learning for resolving the above issues. Our hierarchical probabilistic graphical models can be efficiently learned from large-scale data by maximizing the lower bound of the likelihood. The problem of reliability is related to the extremely small number of available data examples, compared to the large number of attribute variables. In such cases,
Characterization of long RNA-cleaving deoxyribozymes with short catalytic cores: the effect of excess sequence elements on the outcome of in vitro selection

We previously conducted an in vitro selection experiment for RNA-cleaving deoxyribozymes, using a combinatorial DNA library containing 80 random nucleotides. Ultimately, 110 different sequence classes were isolated, but the vast majority contained a short14–15 nt catalytic DNA motif commonly known as 8–17. Herein, we report extensive truncation experiments conducted on multiple sequence classes to confirm the suspected catalytic role played by 8–17 and to determine the effect of excess sequence elements on the activity of this motif and the outcome of selection. Although we observed beneficial, detrimental and neutral consequences for activity, the magnitude of the effect rarely exceeded 2-fold. These deoxyribozymes appear to have survived increasing selection pressure despite the presence of additional sequence elements, rather than because of them. A new deoxyribozyme with comparable activity, called G15–30, was ∼2.5-fold larger and experienced a ∼4-fold greater inhibitory effect from excess sequence elements than the average 8–17 motif. Our results suggest that 8–17 may be less susceptible to the potential inhibitory effects of excess arbitrary sequence than larger motifs, which represents a previously unappreciated selective advantage that may contribute to its widespread recurrence.
Matrix metalloproteinase-1 rs1799750 polymorphism and glaucoma: A meta-analysis

ABSTRACT Purpose: Several studies indicated that -1607 1G/2G (rs1799750) polymorphism in matrix metalloproteinase-1 (MMP-1) promoter was correlated with glaucoma susceptibility, but the results remain controversial. We performed a meta-analysis to assess whether rs1799750 confers glaucoma risk. Methods: Eligible studies were retrieved by systematically searching Pubmed, Embase, Web of Science, and Chinese Biomedical database. The degree of correlation was expressed as odds ratios (ORs) and 95% confidence interval (CI). The measurements were pooled by fixed effect model or random effect model. Results: This meta-analysis included five case-control studies involving 1261 patients with glaucoma and 1089 controls. The pooled results showed a significant association between rs1799750 and glaucoma under the homozygote (OR = 1.71, 95% CI 1.12–2.62, p = 0.014), recessive (OR = 1.64, 95% CI 1.20–2.25, p = 0.002), and allelic (OR = 1.35, 95% CI 1.05–1.72, p = 0.017) models. Subgroup analyses showed that the rs1799750 was significantly associated with primary angle closure glaucoma under homozygote (OR = 2.23, 95% CI 1.03–4.83, p = 0.043) and allelic (OR = 1.61, 95% CI 1.07–2.42, P = 0.021) models, while it was significantly associated with primary open angle glaucoma (OR = 1.64, 95% CI 1.05–2.56, p = 0.030) and exfoliation glaucoma (OR = 1.42, 95% CI 1.02–1.97, p = 0.036) under recessive models. No evidence of publication bias was detected. Conclusions: Meta-analysis of existing data showed that rs1799750 may affect individual susceptibility to glaucoma. Nevertheless, more studies with large sample size and various ethnicities are warranted in light of the limited studies.
A Framework for Amazon EC2 Bidding Strategy under SLA Constraints

With the recent introduction of Spot Instances in the Amazon Elastic Compute Cloud (EC2), users can bid for resources and, thus, control the balance of reliability versus monetary costs. Mechanisms and tools that deal with the cost-reliability tradeoffs under this scheme are of great value for users seeking to reduce their costs while maintaining high reliability. In this paper, we propose a set of bidding strategies under several service-level agreement (SLA) constraints. In particular, we aim to minimize the monetary cost and volatility of resource provisioning. Essentially, to derive an optimal bidding strategy, we formulate this problem as a Constrained Markov Decision Process (CMDP). Based on this model, we are able to obtain an optimal randomized bidding strategy through linear programming. Using real Instance price traces and workload models, we compare several adaptive checkpointing schemes in terms of monetary costs and job completion time. We evaluate our model and demonstrate how users should bid optimally on Spot Instances to reach different objectives with desired levels of confidence.
Nutritional Influences on Skatole Formation and Skatole Metabolism in the Pig

Summary Skatole is a tryptophan metabolite with fecal odor. Skatole and the testicular steroid androstenone are regarded as the main compounds leading to ‘boar taint,’ a sex-specific odor from pork taken from entire males, as elevated concentrations of both substances may be found in adipose boars tissue. High skatole concentrations in adipose tissue are the result of a complex process, which includes microbial formation in the colon, absorption, metabolism and accretion in fat. Several of these steps leading to high skatole concentrations are influenced by feed components and additives. The present paper discusses the mechanisms by which effective feeding strategies and feed additives exert their influence in the prevention of high skatole concentrations in adipose pig tissue.
An Evaluation of the “Youth En Route” Program

Youth En Route (YER) is a transition program for youth and young adults with multiple disabilities. It offers a multifaceted approach that includes self-discovery, skill development, and community experience. Underlying the service delivery model is a philosophy of self-determination. This program evaluation measured the self-determination skills, sense of personal control over life choices, and community participation of 34 youth prior to and one year following their involvement with YER. Youth reported statistically and clinically significant improvement from pretest to posttest with respect to both self-determination and sense of personal control. Moreover, youth reported spending significantly more time at posttest than at pretest engaged in volunteer/work activities and community leisure activities. On average, youth reported high satisfaction with YER services. Practical and research implications are discussed.
The Biotin Carboxylase-Biotin Carboxyl Carrier Protein Complex of Escherichia coli Acetyl-CoA Carboxylase*

Escherichia coli acetyl-CoA carboxylase (ACC) is composed of four different protein molecules. These proteins form a large but very unstable complex. Hints of a sub-complex between the biotin carboxylase (BC) and biotin carboxyl carrier protein (BCCP) subunits have been reported in the literature, but the complex was not isolated and thus the protein stoichiometry could not be determined. We report isolation of the BC·BCCP complex. By use of affinity chromatography using two different affinity tags it was shown that the complex consists of a two BCCP molecules per BC molecule. The molar ratio in the complex is the same as the ratio of the subunit proteins synthesized in vivo. We conclude that the complex consists of a dimer of BC plus four BCCP molecules instead of the 2BC·2BCCP complex previously assumed. This subunit ratio allows two conflicting models of the ACC mechanism to be rectified. We also report that the N-terminal 30 or so residues of BCCP are responsible for the interaction of BCCP with BC and that the BC·BCCP complex is a substrate for biotinylation in vitro.
The Peep Diaries: How We're Learning to Love Watching Ourselves and Our Neighbors

"Take a peek at The Peep Diaries, an erudite (but not too erudite) look at the culture that Facebook, Twitter, et al. have spawned. "-Real Simple "It's a great read; it mixes frank interviews with people pushing the boundaries of voyeurism and exhibitionism, alongside a bracing critique of the social context that got us into peep culture and the forces that now exploit our participation in it. "-The Globe and Mail We have entered the age of "peep culture": a tell-all, show-all, know-all digital phenomenon that is dramatically altering notions of privacy, individuality, security, and even humanity. Peep culture is reality TV, YouTube, MySpace, Facebook, Twitter, over-the-counter spy gear, blogs, chat rooms, amateur porn, surveillance technology, Dr. Phil, Borat, cell phone photos of your drunk friend making out with her ex-boyfriend, and more. In the age of peep, core values and rights we once took for granted are rapidly being renegotiated, often without our even noticing. With hilarious, exasperated acuity, social critic Hal Niedzviecki dives into peep, starting his own video blog, joining every social network that will have him, monitoring the movements of his toddler, selling his secrets on Craigslist, hiring a private detective to investigate him, spying on his neighbors, trying out for reality TV shows, and stripping for the pleasure of a web audience he isn't even sure exists. Part travelogue, part diary, part meditation and social history, The Peep Diaries explores a rapidly emerging digital phenomenon that is radically changing not just the entertainment landscape, but also the firmaments of our culture and society. The Peep Diaries introduces the arrival of the age of peep culture and explores its implications for entertainment, society, sex, politics, and everyday life. Mixing first-rate reporting with sociological observations culled from the latest research, this book captures the shift from pop to peep and the way technology is turning gossip into documentary and Peeping Toms into entertainment journalists. Packed with stranger-than-fiction true-life characters and scenarios, The Peep Diaries reflects the aspirations and confusions of the growing number of people willing to trade the details of their private lives for catharsis, attention, and notoriety. Hal Niedzviecki is the editor of Broken Pencil magazine and has published numerous works of social commentary and fiction, including Hello I'm Special: How Individuality Became the New Conformity.
Independent hand-tracking from a single two-dimensional view and its application to South African sign language recognition

Faculty of Science Department of Computer Science Doctor of Philosophy by Imran Achmed Supervisor: I. M. Venter Co-supervisor: P. Eisert Hand motion provides a natural way of interaction that allows humans to interact not only with the environment, but also with each other. The effectiveness and accuracy of hand-tracking is fundamental to the recognition of sign language. Any inconsistencies in hand-tracking result in a breakdown in sign language communication. Hands are articulated objects, which complicates the tracking thereof. In sign language communication the tracking of hands is often challenged by the occlusion of the other hand, other body parts and the environment in which they are being tracked. The thesis investigates whether a single framework can be developed to track the hands independently of an individual from a single 2D camera in constrained and unconstrained environments without the need for any special device. The framework consists of a three-phase strategy, namely, detection, tracking and learning phases. The detection phase validates whether the object being tracked is a hand, using extended local binary patterns and random forests. The tracking phase tracks the hands independently by extending a novel data-association technique. The learning phase exploits contextual features, using the scale-invariant features transform (SIFT) algorithm and the fast library for approximate nearest neighbours (FLANN) algorithm to assist tracking and the recovering of hands from any form of tracking failure. The framework was evaluated on South African sign language phrases that use a single hand, both hands without occlusion, and both hands with occlusion. These phrases were performed by 20 individuals in constrained and unconstrained environments. The experiments revealed that integrating all three phases to form a single framework is suitable for tracking hands in both constrained and unconstrained environments, where a high average accuracy of 82,08% and 79,83% was achieved respectively.
Lenition and Phonemic Overlap in Rome Italian

Abstract The purpose of this paper is to offer acoustic evidence for an unusual phonemic contrast in Rome Italian. In our corpus, about half of all tokens of intervocalic /p t k/ are realized with uninterrupted voicing (both word-internally and across word boundaries). Furthermore, the voiced realizations of /t/ and /k/ do not significantly differ from /d/ and /g/ in duration and/or degree of constriction (as acoustically determined). Phonemic contrast is maintained under substantial phonetic overlap. Regarding the labials, duration keeps /p/ and /b/ apart. Contrary to the universal tendency, it is /b/ that is considerably longer, due to complex diachronic facts.
Automatic Generation of Starting Positions in Board Games

Board games, like Tic-Tac-Toe and CONNECT-4, play an important role not only in development of mathematical and logical skills, but also in emotional and social development. In this paper, we motivate and address the problem of generating interesting start states for such games. Our algorithm generates starting states of varying difficulty level for player 1, given the rules of a board game, the number of steps required for player 1 to win, and the expertise levels of the two players. Our algorithm leverages symbolic methods and iterative simulation to efficiently search the humongous state space. We present experimental results that discover for the first time such interesting states for several games and demonstrate the feasibility of finding them in an offline mode. The presence of such states for a game like Tic-Tac-Toe 4 4 that was previously thought to be trivial, opens up new games to be played that have been believed to be useless for ages.