LLukas22/scidocs huggingface dataset:
BELMiner: adapting a rule-based relation extraction system to extract biological expression language statements from bio-medical literature evidence sentences

Extracting meaningful relationships with semantic significance from biomedical literature is often a challenging task. BioCreative V track4 challenge for the first time has organized a comprehensive shared task to test the robustness of the text-mining algorithms in extracting semantically meaningful assertions from the evidence statement in biomedical text. In this work, we tested the ability of a rule-based semantic parser to extract Biological Expression Language (BEL) statements from evidence sentences culled out of biomedical literature as part of BioCreative V Track4 challenge. The system achieved an overall best F-measure of 21.29% in extracting the complete BEL statement. For relation extraction, the system achieved an F-measure of 65.13% on test data set. Our system achieved the best performance in five of the six criteria that was adopted for evaluation by the task organizers. Lack of ability to derive semantic inferences, limitation in the rule sets to map the textual extractions to BEL function were some of the reasons for low performance in extracting the complete BEL statement. Post shared task we also evaluated the impact of differential NER components on the ability to extract BEL statements on the test data sets besides making a single change in the rule sets that translate relation extractions into a BEL statement. There is a marked improvement by over 20% in the overall performance of the BELMiner's capability to extract BEL statement on the test set. The system is available as a REST-API at http://54.146.11.205:8484/BELXtractor/finder/.


Database URL
http://54.146.11.205:8484/BELXtractor/finder/.
Using artificial neural networks for pattern recognition of downhole dynamometer card in oil rod pump system

The present paper shows that by using Artificial Neural Network system one can establishes pattern classes and sets standards for training and validation in Dynamometer Card in oil well rod pump systems. Also, the design and the implementation of a features extractor are then possible by the study of descriptors.
Prognostic significance of admission levels of cardiac indicators in patients with acute ischaemic stroke: prospective observational study.

OBJECTIVE
The performance of cardiac indicators as determinants of stroke outcomes remains debatable, therefore the present study focused on the short-term prognostic value of cardiac indicators in patients who had experienced acute ischaemic stroke.


METHODS
Consecutive patients with acute ischaemic stroke were enrolled in a prospective stroke registry. Data on demographics, clinical characteristics and cardiac indicator levels (including troponin I, creatine kinase-MB, myoglobin and brain natriuretic peptide) were prospectively collected. Receiver operating characteristic curves and binary logistic regression models were used to examine the performance of variables in predicting poor functional outcomes (modified Rankin Scale score 2-6).


RESULTS
Out of 337 patients with acute ischaemic stroke, myoglobin had the greatest power for predicting poor outcomes among the cardiac indicators. Forward stepwise multivariate logistic regression analysis revealed that myoglobin could independently predict short-term outcomes. Spearman's rank correlation tests indicated a positive correlation between myoglobin levels and stroke severity.


CONCLUSIONS
Among cardiac indicators, myoglobin may be an independent predictor of short-term outcomes in patients with acute ischaemic stroke.
Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce - Book Review

Dear readers, when you are hunting the new book collection to read this day, ontologies a silver bullet for knowledge management and electronic commerce can be your referred book. Yeah, even many books are offered, this book can steal the reader heart so much. The content and theme of this book really will touch your heart. You can find more and more experience and knowledge how the life is undergone.
Preparation of Wood Adhesives Based on Soybean Meal Modified with PEGDA as a Crosslinker and Viscosity Reducer

To increase the water resistance and reduce the viscosity of soybean meal (SM)-based non-formaldehyde wood adhesives, polyethyleneglycol diacrylate (PEGDA) used as crosslinker and viscosity reducer was introduced into the SM adhesive system. The apparent viscosity was evaluated by rheological measurements; gel content and water absorption of adhesives, the wet shear strength of plywood bonded with these modified adhesives were tested to evaluate their water resistance. In addition, the crosslink structures of modified adhesives were characterized by Fourier transform infrared (FTIR) spectroscopy and solid-state 13 C NMR analysis. The results indicated that all of the SM adhesives were pseudoplastic fluids with the property of shear-thinning. The viscosity of modified SM adhesives effectively decreased by 35% compared with the addition of PEGDA, and the wet shear strength of their bonded plywood increased; the wet shear strength of plywood bonded with 4% PEGDA-modified SM adhesive increased 114.2% compared to SM adhesive. FTIR spectroscopy and solid-state 13 C NMR analysis demonstrated that the crosslinking reaction of the PEGDA occurred successfully during the curing process of PEGDA modified SM adhesive, and no crosslinking reaction between the PEGDA and soy meal adhesive appeared to have occurred. Interpenetrating networks (IPNs) might be formed between the cured PEGDA and SM adhesive system.
Suicidal behaviors in depressed adolescents: role of perceived relationships in the family

CONTEXT
Suicide is the second leading cause of death in adolescents and young adults in Europe. Reducing suicides is therefore a key public health target. Previous studies have shown associations between suicidal behaviors, depression and family factors.


OBJECTIVE
To assess the role of family factors in depression and suicidality in a large community-based sample of adolescents and to explore specific contributions (e.g. mother vs. father; conflict vs. no conflict; separation vs. no separation) taking into account other risk factors.


METHODS
A cross-sectional sample of adolescents aged 17 years was recruited in 2008. 36,757 French adolescents (18,593 girls and 18,164 boys) completed a questionnaire including socio-demographic characteristics, drug use, family variables, suicidal ideations and attempts. Current depression was assessed with the Adolescent Depression Rating Scale (ADRS). Adolescents were divided into 4 groups according to suicide risk severity (grade 1 = depressed without suicidal ideation and without suicide attempts, grade 2 = depressed with suicidal ideations and grade 3 = depressed with suicide attempts; grade 0 = control group). Multivariate regressions were applied to assess the Odds Ratio of potential risk factors comparing grade 1, 2 or 3 risk with grade 0.


RESULTS
7.5% of adolescents (10.4% among girls vs. 4.5% among boys) had ADRS scores compatible with depression; 16.2% reported suicidal ideations in the past 12 months and 8.2% reported lifetime suicide attempts. Repeating a year in school was significantly associated to severity grade of suicide risk (1 and 3), as well as all substance use, tobacco use (severity grades 2 and 3) and marijuana use (severity grade 3), for girls and boys. After adjustment, negative relationships with either or both parents, and parents living together but with a negative relationship were significantly associated with suicide risk and/or depression in both genders (all risk grades), and Odds Ratios increased according to risk severity grade.


CONCLUSION
Family discord and negative relationship with parents were associated with an increased suicide risk in depressed adolescents. So it appears essential to take intrafamilial relationships into account in depressed adolescents to prevent suicidal behaviours.
Single-channel multi-talker speech recognition with permutation invariant training

Although great progresses have been made in automatic speech recognition (ASR), significant performance degradation is still observed when recognizing multi-talker mixed speech. In this paper, we propose and evaluate several architectures to address this problem under the assumption that only a single channel of mixed signal is available. Our technique extends permutation invariant training (PIT) by introducing the frontend feature separation module with the minimum mean square error (MSE) criterion and the back-end recognition module with the minimum cross entropy (CE) criterion. More specifically, during training we compute the average MSE or CE over the whole utterance for each possible utterance-level output-target assignment, pick the one with the minimum MSE or CE, and optimize for that assignment. This strategy elegantly solves the label permutation problem observed in the deep learning based multi-talker mixed speech separation and recognition systems. The proposed architectures are evaluated and compared on an artificially mixed AMI dataset with both twoand threetalker mixed speech. The experimental results indicate that our proposed architectures can cut the word error rate (WER) by 45.0% and 25.0% relatively against the state-of-the-art singletalker speech recognition system across all speakers when their energies are comparable, for twoand three-talker mixed speech, respectively. To our knowledge, this is the first work on the multi-talker mixed speech recognition on the challenging speakerindependent spontaneous large vocabulary continuous speech task. Keywords—permutation invariant training, multi-talker mixed speech recognition, feature separation, joint-optimization
What makes great teaching ? Review of the underpinning research

This review set out to address three apparently simple questions:  What makes 'great teaching'?  What kinds of frameworks or tools could help us to capture it?  How could this promote better learning? Question 1: " What makes great teaching? " Great teaching is defined as that which leads to improved student progress We define effective teaching as that which leads to improved student achievement using outcomes that matter to their future success. Defining effective teaching is not easy. The research keeps coming back to this critical point: student progress is the yardstick by which teacher quality should be assessed. Ultimately, for a judgement about whether teaching is effective, to be seen as trustworthy, it must be checked against the progress being made by students. The six components of great teaching Schools currently use a number of frameworks that describe the core elements of effective teaching. The problem is that these attributes are so broadly defined that they can be open to wide and different interpretation whether high quality teaching has been observed in the classroom. It is important to understand these limitations when making assessments about teaching quality. Below we list the six common components suggested by research that teachers should consider when assessing teaching quality. We list these approaches, skills and knowledge in order of how strong the evidence is in showing that focusing on them can improve student outcomes. This should be seen as offering a 'starter kit' for thinking about effective pedagogy. Good quality teaching will likely involve a combination of these attributes manifested at different times; the very best teachers are those that demonstrate all of these features. The most effective teachers have deep knowledge of the subjects they teach, and when teachers' knowledge falls below a certain level it is a significant impediment to students' learning. As well as a strong understanding of the material being taught, teachers must also understand the ways students think about the content, be able to evaluate the thinking behind students' own methods, and identify students' common misconceptions. Includes elements such as effective questioning and use of assessment by teachers. Specific practices, like reviewing previous learning, providing model responses for students, giving adequate time for practice to embed skills securely Executive Summary 3 and progressively introducing new learning (scaffolding) are also elements of high quality instruction. 3. Classroom climate (Moderate evidence of impact on student outcomes) Covers …
PMU-Based Fault Location Using Voltage Measurements in Large Transmission Networks

This paper presents a general fault-location method for large transmission networks which uses phasor measurement unit (PMU) voltage measurements where the injected current at a fault point can be calculated by using the voltage change and its relevant transfer impedance on any bus. A two-stage fault-location optimization model is proposed, along with defining a matching degree index. The first stage is the fault region identification stage, which uses the matching degree index to determine the suspicious fault region in order to reduce the search area. The second stage is used to identify the exact fault line and fault distance. A method to determine optimal PMU placement is also proposed in this paper. Case studies verify that the proposed fault-location algorithm and optimal PMU placement scheme can locate faults in large transmission networks quickly and accurately without requiring fault-type classification or fault phase selection.
A double-blind trial of fluoxetine in pathologic skin picking.

BACKGROUND
Our objective was to determine the efficacy of fluoxetine in the treatment of pathologic skin picking in a double-blind, placebo-controlled, parallel trial.


METHOD
Twenty-one adults with chronic pathologic skin picking agreed to participate and received 10 weeks of placebo or fluoxetine with a flexible dosing schedule up to 80 mg/day. Three skin-picking measures were employed: the Clinical Global Impression-Improvement (CGI-I) scale, the Skin Picking Treatment Scale (SPTS), and a visual analog scale of self-rated change (VAS). In addition, depression, anxiety, and obsessions-compulsions were rated using the Hamilton Rating Scale for Depression (HAM-D), the Hamilton Rating Scale for Anxiety (HAM-A), the Spielberger State-Trait Anxiety Inventory (STAI), and the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) for the duration of the study.


RESULTS
Seventeen subjects (6 treated with fluoxetine and 11 treated with placebo) completed the trial, at a mean fluoxetine dose of 55 mg/day. Fluoxetine was significantly superior to placebo in the treatment of skin picking according to two of the three measures for the completer analysis and to one of the three measures for the intent-to-treat analysis. Neither baseline level nor change in depression, anxiety, or obsessive-compulsive symptoms was significantly related to change in skin picking.


CONCLUSION
This first controlled trial of the treatment of pathologic skin picking suggests that fluoxetine may be of therapeutic benefit. Larger controlled studies are warranted.
Confidence interval or p-value?: part 4 of a series on evaluation of scientific publications.

BACKGROUND
An understanding of p-values and confidence intervals is necessary for the evaluation of scientific articles. This article will inform the reader of the meaning and interpretation of these two statistical concepts.


METHODS
The uses of these two statistical concepts and the differences between them are discussed on the basis of a selective literature search concerning the methods employed in scientific articles.


RESULTS/CONCLUSIONS
P-values in scientific studies are used to determine whether a null hypothesis formulated before the performance of the study is to be accepted or rejected. In exploratory studies, p-values enable the recognition of any statistically noteworthy findings. Confidence intervals provide information about a range in which the true value lies with a certain degree of probability, as well as about the direction and strength of the demonstrated effect. This enables conclusions to be drawn about the statistical plausibility and clinical relevance of the study findings. It is often useful for both statistical measures to be reported in scientific articles, because they provide complementary types of information.
A phase-specific psychological therapy for people with problematic cannabis use following a first episode of psychosis: a randomized controlled trial.

BACKGROUND
Cannabis use is high amongst young people who have recently had their first episode of psychosis, and is associated with worse outcomes. To date, interventions to reduce cannabis consumption have been largely ineffective, and it has been suggested that longer treatment periods are required.


METHOD
In a pragmatic single-blind randomized controlled trial 110 participants were randomly allocated to one of three conditions: a brief motivational interviewing and cognitive behavioural therapy (MI-CBT) intervention (up to 12 sessions over 4.5 months) with standard care from an early intervention service; a long MI-CBT intervention (up to 24 sessions over 9 months) with standard care; or standard care alone. The primary outcome was change in cannabis use as measured by Timeline Followback.


RESULTS
Neither the extended nor the brief interventions conferred benefit over standard care in terms of reductions in frequency or amount of cannabis use. Also the interventions did not result in improvements in the assessed clinical outcomes, including symptoms, functioning, hospital admissions or relapse.


CONCLUSIONS
Integrated MI and CBT for people with cannabis use and recent-onset psychosis does not reduce cannabis use or improve clinical outcomes. These findings are consistent with those in the published literature, and additionally demonstrate that offering a more extended intervention does not confer any advantage. Many participants were not at an action stage for change and for those not ready to reduce or quit cannabis, targeting associated problems rather than the cannabis use per se may be the best current strategy for mental health services to adopt.
Using motivational interviewing in HIV field outreach with young African American men who have sex with men: a randomized clinical trial.

OBJECTIVES
We sought to determine whether field outreach with motivational interviewing, as compared with traditional field outreach, leads to increases in HIV counseling and testing and rates of return for test results among young African American men who have sex with men (MSM).


METHODS
In a randomized, 2-group, repeated-measures design, 96 young African American MSM completed a motivational interviewing-based field outreach session and 92 young African American MSM completed a traditional field outreach session. The percentages of participants agreeing to traditional HIV counseling and testing (an oral swab of the cheek) and returning for test results were the primary outcome measures.


RESULTS
More of the participants in the motivational interviewing condition than the control condition received HIV counseling and testing (49% versus 20%; chi(2)(1) = 17.94; P = .000) and returned for test results (98% versus 72%; chi(2)(1) = 10.22; P = .001).


CONCLUSIONS
The addition of motivational interviewing to field outreach is effective in encouraging high-risk young African American MSM to learn their HIV status. Also, peer outreach workers can be effectively trained to reduce health disparities by providing evidence-based brief counseling approaches targeting high-risk minority populations.
Radiation exposure and mortality risk from CT and PET imaging of patients with malignant lymphoma

To quantify radiation exposure and mortality risk from computed tomography (CT) and positron emission tomography (PET) imaging with 18F-fluorodeoxyglucose (18F-FDG) in patients with malignant lymphoma (Hodgkin’s disease [HD] or non-Hodgkin’s lymphoma [NHL]). First, organ doses were assessed for a typical diagnostic work-up in children with HD and adults with NHL. Subsequently, life tables were constructed for assessment of radiation risks, also taking into account the disease-related mortality. In children with HD, cumulative effective dose from medical imaging ranged from 66 mSv (newborn) to 113 mSv (15 years old). In adults with NHL the cumulative effective dose from medical imaging was 97 mSv. Average fractions of radiation-induced deaths for children with HD [without correction for disease-related mortality in brackets] were 0.4% [0.6%] for boys and 0.7% [1.1%] for girls, and for adults with NHL 0.07% [0.28%] for men and 0.09% [0.37%] for women. Taking into account the disease-related reduction in life expectancy of patients with malignant lymphoma results in a higher overall mortality but substantial lower incidence of radiation induced deaths. The modest radiation risk that results from imaging with CT and 18F-FDG PET can be considered as justified, but imaging should be performed with care, especially in children. Survival of malignant lymphoma has improved dramatically over the past decades. PET and CT currently play important roles for malignant lymphoma patients. The potential hazard of ionising radiation has become an increasingly important issue. When assessing radiation risks, disease-related reduction in life expectancy should be considered. CT and 18 F-FDG PET create a modest radiation-induced mortality risk. Survival of malignant lymphoma has improved dramatically over the past decades. PET and CT currently play important roles for malignant lymphoma patients. The potential hazard of ionising radiation has become an increasingly important issue. When assessing radiation risks, disease-related reduction in life expectancy should be considered. CT and 18 F-FDG PET create a modest radiation-induced mortality risk.
Discriminant Analysis for Recognition of Human Face Images (Invited Paper)

The discrimination power of various human facial features is studied and a new scheme for automatic face recognition (AFR) is proposed. The first part of the paper focuses on the linear discriminant analysis (LDA) of different aspects of human faces in the spatial as well as in the wavelet domain. This analysis allows objective evaluation of the significance of visual information in different parts (features) of the face for identifying the human subject. The LDA of faces also provides us with a small set of features that carry the most relevant information for classification purposes. The features are obtained through eigenvector analysis of scatter matrices with the objective of maximizing between-class variations and minimizing within-class variations. The result is an efficient projection-based feature-extraction and classification scheme for AFR. Each projection creates a decision axis with a certain level of discrimination power or reliability. Soft decisions made based on each of the projections are combined, and probabilistic or evidential approaches to multisource data analysis are used to provide more reliable recognition results. For a medium-sized database of human faces, excellent classification accuracy is achieved with the use of very-low-dimensional feature vectors. Moreover, the method used is general and is applicable to many other image-recognition tasks. © 1997 Optical Society of America [S0740-3232(97)01008-9]