LLukas22/scidocs huggingface dataset:
Influence of order and type of drug (bisoprolol vs. enalapril) on outcome and adverse events in patients with chronic heart failure: a post hoc analysis of the CIBIS-III trial.

AIMS
Angiotensin-converting enzyme inhibitors (ACE-Is) and beta-blockers are associated with improved outcome in patients with chronic heart failure (CHF). In this post hoc analysis of the CIBIS III trial, we examined the influence of the order of drug administration on clinical events and achieved dose. We also assessed the relations between dose levels and baseline variables or adverse events.


METHODS AND RESULTS
In the CIBIS III trial, 1010 patients (mean age: 72.4 years; mean ejection fraction: 28.8%; male: 68.2%) with stable CHF were randomized to up-titration of monotherapy with either bisoprolol (target dose 10 mg o.d.) or enalapril (target dose 10 mg b.i.d.) for 6 months, followed by their combination for 6-24 months. Endpoints were mortality or all-cause hospitalization, mortality alone and mortality or cardiovascular hospitalization. The study drug (ACE-I or beta-blocker) was last prescribed at ≥50% of target dose to significantly more patients for the first initiated drug in both treatment groups (both P< 0.001). Sixty per cent of endpoints were reached during the monotherapy phase and randomized treatment during monotherapy was not a predictor of the three assessed outcomes. Monotherapy phase was the strongest independent predictor of outcome (P< 0.0001 for all endpoints). Older age, NYHA class III, impaired renal function, lower body weight and blood pressure at baseline, and hypotension, bradycardia and heart failure during treatment were associated with the inability to reach high dose of both study drugs.


CONCLUSION
The order of drug administration plays an important role in whether CHF patients reach target doses of bisoprolol and enalapril. For both study drugs, the dose level reached was associated with baseline characteristics and adverse events. In CHF patients not treated with an ACE-I or a beta-blocker, the duration of monotherapy with either type of drug should be shorter than 6 months.
Decision making processes in people with symptoms of acute myocardial infarction: qualitative study.

OBJECTIVE
To identify the themes that influence decision making processes used by patients with symptoms of acute myocardial infarction.


DESIGN
Qualitative study using semistructured interviews.


SETTING
Two district hospitals in North Yorkshire.


PARTICIPANTS
22 patients admitted to hospital with confirmed second, third, or fourth acute myocardial infarction.


MAIN OUTCOME MEASUREMENTS
Patients' perceptions of their experience between the onset of symptoms and the decision to seek medical help.


RESULTS
Six main themes that influence the decision making process were identified: appraisal of symptoms, perceived risk, previous experience, psychological and emotional factors, use of the NHS, and context of the event.


CONCLUSIONS
Knowledge of symptoms may not be enough to promote prompt action in the event of an acute myocardial infarction. Cognitive and emotional processes, individual beliefs and values, and the influence of the context of the event should also be considered in individual interventions designed to reduce delay in the event of symptoms of acute myocardial infarction.
Multilevel Algorithms for Multi-Constraint Graph Partitioning

Traditional graph partitioning algorithms compute a k-way partitioning of a graph such that the number of edges that are cut by the partitioning is minimized and each partition has an equal number of vertices. The task of minimizing the edge-cut can be considered as the objective and the requirement that the partitions will be of the same size can be considered as the constraint. In this paper we extend the partitioning problem by incorporating an arbitrary number of balancing constraints. In our formulation, a vector of weights is assigned to each vertex, and the goal is to produce a k-way partitioning such that the partitioning satisfies a balancing constraint associated with each weight, while attempting to minimize the edge-cut. Applications of this multi-constraint graph partitioning problem include parallel solution of multi-physics and multi-phase computations, that underlay many existing and emerging large-scale scientific simulations. We present new multi-constraint graph partitioning algorithms that are based on the multilevel graph partitioning paradigm. Our work focuses on developing new types of heuristics for coarsening, initial partitioning, and refinement that are capable of successfully handling multiple constraints. We experimentally evaluate the effectiveness of our multi-constraint partitioners on a variety of synthetically generated problems.
Assessing Student Expertise in Introductory Physics with Isomorphic Problems, Part I: Performance on Non-intuitive Problem Pair from Introductory Physics

Investigations related to expertise in problem solving and ability to transfer learning from one context to another are important for developing strategies to help students perform more expert-like tasks. Here we analyze written responses to a pair of non-intuitive isomorphic problems given to introductory physics students and discussions with a subset of students about them. Students were asked to explain their reasoning for their written responses. We call the paired problems isomorphic because they require the same physics principle to solve them. However, the initial conditions are different and the frictional force is responsible for increasing the linear speed of an object in one of the problems while it is responsible for decreasing the linear speed in the other problem. We categorize student responses and evaluate student performance within the context of their evolving expertise. We compare and contrast the patterns of student categorization for the two isomorphic problems. We discuss why certain incorrect responses were better than others and shed light on the evolution of students’ expertise. We compare the performance of students who worked on both isomorphic problems with those who worked only on one of the problems to understand whether students recognized their underlying similarity and whether isomorphic pairs gave students additional insight in solving each problem.
Processing of Topological BIM Queries using Boundary Representation Based Methods

Building Information Models (BIM) are comprehensive digital representations of buildings, which provide a large set of information originating from the different disciplines involved in the design, construction and operation processes. Moreover, accessing the data needed for a specific downstream application scenario is a challenging task in large-scale BIM projects. Several researchers recently proposed using formal query languages for specifying the desired information in a concise, well-defined manner. One of the main limitations of the languages introduced so far, however, is the inadequate treatment of geometric information. This is a significant drawback, as buildings are inherently spatial objects and qualitative spatial relationships accordingly play an important role in the analysis and verification of building models. In addition, the filters needed in specific data exchange scenarios for selecting the information required can be built by spatial objects and their relations. The lack of spatial functionality in BIM query languages is filled by the Query Language for Building Information Models (QL4BIM) which provides metric, directional and topological operators for defining filter expressions with qualitative spatial semantics. This paper focuses on the topological operators provided by the language. In particular, it presents a new implementation method based on the boundary representation of the operands which outperforms the previously presented octree-based approaches. The paper discusses the developed algorithms in detail and presents extensive performance tests. 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
Quality of life of early stage colorectal cancer patients in Morocco

BACKGROUND
A multicentre cohort study was held in Morocco, designed to evaluate the quality of life of cancer patients. The aim of this paper is to report the assessment of the quality of life of early colorectal cancer patients, before and after cancer treatment, to identify other factors which are related to this quality of life.


METHODS
We used the third version of the QLQ-C30 questionnaire of the European organization for Research and treatment of Cancer (EORTC) after a transcultural validation. The Data collection was done at inclusion and then every twelve weeks to achieve one year of follow up.


RESULTS
Overall 294 patients presented with early colorectal cancer, the median age was 56 years (range: 21-88). The male-female sex ratio was 1.17. At inclusion, the global health status was the most affected functional dimension. For symptoms: financial difficulties and fatigue scores were the highest ones. Emotional and social functions were significantly worse in rectal cancer. Most symptoms were more present in rectal cancer. At inclusion, global health status score was significantly worse in stage III. Anorexia was significantly more important among colorectal female patients. For Patients over 70 years-old, the difference was statistically significant for the physical function item which was lower. Overall, Functional dimensions scores were improved after chemotherapy. The symptoms scores did not differ significantly for patients treated by radiotherapy, between inclusion and at one year.


CONCLUSION
Our EORTC QLQ C30 scores are overall comparable to the reference values. Neither chemotherapy, nor radiotherapy worsened the quality of life at one year.
Transfer learning for biomedical named entity recognition with neural networks

Motivation
The explosive increase of biomedical literature has made information extraction an increasingly important tool for biomedical research. A fundamental task is the recognition of biomedical named entities in text (BNER) such as genes/proteins, diseases and species. Recently, a domain-independent method based on deep learning and statistical word embeddings, called long short-term memory network-conditional random field (LSTM-CRF), has been shown to outperform state-of-the-art entity-specific BNER tools. However, this method is dependent on gold-standard corpora (GSCs) consisting of hand-labeled entities, which tend to be small but highly reliable. An alternative to GSCs are silver-standard corpora (SSCs), which are generated by harmonizing the annotations made by several automatic annotation systems. SSCs typically contain more noise than GSCs but have the advantage of containing many more training examples. Ideally, these corpora could be combined to achieve the benefits of both, which is an opportunity for transfer learning. In this work, we analyze to what extent transfer learning improves upon state-of-the-art results for BNER.


Results
We demonstrate that transferring a deep neural network (DNN) trained on a large, noisy SSC to a smaller, but more reliable GSC significantly improves upon state-of-the-art results for BNER. Compared to a state-of-the-art baseline evaluated on 23 GSCs covering four different entity classes, transfer learning results in an average reduction in error of approximately 11%. We found transfer learning to be especially beneficial for target datasets with a small number of labels (approximately 6000 or less).


Availability and implementation
Source code for the LSTM-CRF is available at https://github.com/Franck-Dernoncourt/NeuroNER/ and links to the corpora are available at https://github.com/BaderLab/Transfer-Learning-BNER-Bioinformatics-2018/.


Supplementary information
Supplementary data are available at Bioinformatics online.
A Question Answering Approach to Emotion Cause Extraction

Emotion cause extraction aims to identify the reasons behind a certain emotion expressed in text. It is a much more difficult task compared to emotion classification. Inspired by recent advances in using deep memory networks for question answering (QA), we propose a new approach which considers emotion cause identification as a reading comprehension task in QA. Inspired by convolutional neural networks, we propose a new mechanism to store relevant context in different memory slots to model context information. Our proposed approach can extract both word level sequence features and lexical features. Performance evaluation shows that our method achieves the state-of-the-art performance on a recently released emotion cause dataset, outperforming a number of competitive baselines by at least 3.01% in F-measure.
Estimation of cardiac reserve by peak power: validation and initial application of a simplified index.

OBJECTIVES
To validate a simplified estimate of peak power (SPP) against true (invasively measured) peak instantaneous power (TPP), to assess the feasibility of measuring SPP during exercise and to correlate this with functional capacity.


DESIGN
Development of a simplified method of measurement and observational study.


SETTING
Tertiary referral centre for cardiothoracic disease.


SUBJECTS
For validation of SPP with TPP, seven normal dogs and four dogs with dilated cardiomyopathy were studied. To assess feasibility and clinical significance in humans, 40 subjects were studied (26 patients; 14 normal controls).


METHODS
In the animal validation study, TPP was derived from ascending aortic pressure and flow probe, and from Doppler measurements of flow. SPP, calculated using the different flow measures, was compared with peak instantaneous power under different loading conditions. For the assessment in humans, SPP was measured at rest and during maximum exercise. Peak aortic flow was measured with transthoracic continuous wave Doppler, and systolic and diastolic blood pressures were derived from brachial sphygmomanometry. The difference between exercise and rest simplified peak power (Delta SPP) was compared with maximum oxygen uptake (VO(2)max), measured from expired gas analysis.


RESULTS
SPP estimates using peak flow measures correlated well with true peak instantaneous power (r = 0.89 to 0.97), despite marked changes in systemic pressure and flow induced by manipulation of loading conditions. In the human study, VO(2)max correlated with Delta SPP (r = 0.78) better than Delta ejection fraction (r = 0.18) and Delta rate-pressure product (r = 0.59).


CONCLUSIONS
The simple product of mean arterial pressure and peak aortic flow (simplified peak power, SPP) correlates with peak instantaneous power over a range of loading conditions in dogs. In humans, it can be estimated during exercise echocardiography, and correlates with maximum oxygen uptake better than ejection fraction or rate-pressure product.
UTAssistant: A Web Platform Supporting Usability Testing in Italian Public Administrations

Even if the benefits of the usability testing are remarkable, it is scarcely adopted in the software development process. To foster its adoption, this paper presents a Web platform, UTAssistant, that supports people, also without skills in Human-Computer Interaction (HCI), in evaluating Web site usability.
Enumeration Complexity of Logical Query Problems with Second-order Variables

We consider query problems defined by first order formulas of the form Φ(x,T) with free first order and second order variables and study the data complexity of enumerating results of such queries. By considering the number of alternations in the quantifier prefixes of formulas, we show that such query problems either admit a constant delay or a polynomial delay enumeration algorithm or are hard to enumerate. We also exhibit syntactically defined fragments inside the hard cases that still admit good enumeration algorithms and discuss the case of some restricted classes of database structures as inputs. 1998 ACM Subject Classification F.1.3 Complexity Measures and Classes
Providing device integration with OPC UA

OPC UA allows the company wide access and integration of information. One important part of this information system is the automation system and its automation devices. The important issue for presenting devices in such an enterprise system is standardization of device representation. This document provides a proposal on how to standardize the presentation of devices based on a comparison of existing device integration technologies.
Bioresorbable Vascular Scaffolds Versus Metallic Stents in Patients With Coronary Artery Disease: ABSORB China Trial.

BACKGROUND
The everolimus-eluting bioresorbable vascular scaffold (BVS) is designed to achieve results comparable to metallic drug-eluting stents at 1 year, with improved long-term outcomes. Whether the 1-year clinical and angiographic results of BVS are noninferior to current-generation drug-eluting stents has not been established.


OBJECTIVES
This study sought to evaluate the angiographic efficacy and clinical safety and effectiveness of BVS in a randomized trial designed to enable approval of the BVS in China.


METHODS
Eligible patients with 1 or 2 de novo native coronary artery lesions were randomized to BVS or cobalt-chromium everolimus-eluting stents (CoCr-EES) in a 1:1 ratio stratified by diabetes and the number of lesions treated. Angiographic and clinical follow-up were planned at 1 year in all patients. The primary endpoint was angiographic in-segment late loss (LL), powered for noninferiority with a margin of 0.15 mm.


RESULTS
A total of 480 patients were randomized (241 BVS vs. 239 CoCr-EES) at 24 sites. Acute clinical device success (98.0% vs. 99.6%; p = 0.22) and procedural success (97.0% and 98.3%; p = 0.37) were comparable in BVS- and CoCr-EES-treated patients, respectively. The primary endpoint of in-segment LL at 1 year was 0.19 ± 0.38 mm for BVS versus 0.13 ± 0.38 mm for CoCr-EES; the 1-sided 97.5% upper confidence limit of the difference was 0.14 mm, achieving noninferiority of BVS compared with CoCr-EES (pnoninferiority = 0.01). BVS and CoCr-EES also had similar 1-year rates of target lesion failure (cardiac death, target vessel myocardial infarction, or ischemia-driven target lesion revascularization; 3.4% vs. 4.2%, respectively; p = 0.62) and definite/probable scaffold/stent thrombosis (0.4% vs. 0.0%, respectively; p = 1.00).


CONCLUSIONS
In the present multicenter randomized trial, BVS was noninferior to CoCr-EES for the primary endpoint of in-segment LL at 1 year. (A Clinical Evaluation of Absorb Bioresorbable Vascular Scaffold [Absorb BVS] System in Chinese Population-ABSORB CHINA Randomized Controlled Trial [RCT]; NCT01923740).
Low Power-Area Designs of 1Bit Full Adder in Cadence Virtuoso Platform

Power consumption has emerged as a primary design constraint for integrated circuits (ICs). In the Nano meter technology regime, leakage power has become a major component of total power. Full adder is the basic functional unit of an ALU. The power consumption of a processor is lowered by lowering the power consumption of an ALU, and the power consumption of an ALU can be lowered by lowering the power consumption of Full adder. So the full adder designs with low power characteristics are becoming more popular these days. This proposed work illustrates the design of the low-power less transistor full adder designs using cadence tool and virtuoso platform, the entire simulations have been done on 180nm single n-well CMOS bulk technology, in virtuoso platform of cadence tool with the supply voltage 1.8V and frequency of 100MHz. These circuits consume less power with maximum (6T design)of 93.1% power saving compare to conventional 28T design and 80.2% power saving compare to SERF design without much delay degradation. The proposed circuit exploits the advantage of GDI technique and pass transistor logic.
Bootstrapping Likelihood for Model Selection with Small Samples

Akaike s Information Criterion AIC derived from asymptotics of the maximum like lihood estimator is widely used in model selection However it has a nite sample bias which produces over tting in linear regression To deal with this problem Ishiguro et al proposed a bootstrap based extension to AIC which they call EIC In this report we compare model selection performance of AIC EIC a bootstrap smoothed likelihood cross validation BCV and its modi cation CV in small sample linear regression logistic regression and Cox regression Simulation results show that EIC largely overcomes AIC s over tting problem and that BCV may be better than EIC Hence the three methods based on bootstrapping the likelihood establish themselves as important alternatives to AIC in model selection with small samples
Urinary protein excretion in humans exposed to arsenic and cadmium.

OBJECTIVE
In mice, the renal toxicity of arsenic (As) and cadmium (Cd) has been shown to be exacerbated by the simultaneous administration of both elements. To verify the existence of such an interaction in humans, cohorts slightly (Belgian) and moderately (Chinese) exposed to both elements were examined.


METHODS
Biological indicators of exposure (Cd in urine and in blood; As in urine) and renal effect parameters (retinol binding protein (RBP); beta(2)-microglobulin (beta(2)M); albumin (ALB); N-acetyl-beta-glucosaminidase (NAG) in urine) were determined and their relationships studied by multiple regression analyses.


RESULTS
Changes in renal effect parameters could be ascribed to Cd body burden. RBP and beta(2)M urinary concentration were influenced by exposure to As only in Chinese women, directly and in interaction with Cd exposure.


CONCLUSION
A synergistic action of As on the tubular effects of Cd is observed in women moderately exposed to these elements and leads to RBP urinary excretion slightly above normal values.
Letter names, letter sounds and phonological awareness: an examination of kindergarten children across letters and of letters across children

In this study 149 kindergarten children were assessed for knowledge of letter names and letter sounds, phonological awareness, and cognitive abilities. Through this it examined child and letter characteristics influencing the acquisition of alphabetic knowledge in a naturalistic context, the relationship between letter-sound knowledge and letter-name knowledge, and the prediction of Grade 1 phonological awareness and word identification from these variables. Knowledge of letter sounds was better for vowels and for letters with consonant–vowel names than for those with vowel–consonant names or names bearing little relationship to their sounds. However, there were anomalies within each category reflecting characteristics of the individual letters. Structural equation modelling showed that cognitive ability, comprising receptive vocabulary, non-verbal reasoning, rapid automatized naming of colours, and phonological memory significantly contributed to alphabetic knowledge and phonological awareness. In turn, letter-name knowledge but not phonological awareness predicted letter-sound knowledge and subsequent reading skill.
Linking Software Development and Business Strategy Through Measurement

The GQM+Strategies approach extends the goal/question/metric paradigm for measuring the success or failure of goals and strategies, adding enterprise-wide support for determining action on the basis of measurement results. An organization can thus integrate its measurement program across all levels.