LLukas22/scidocs huggingface dataset:
Compliance of blood sampling procedures with the CLSI H3-A6 guidelines: An observational study by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) working group for the preanalytical phase (WG-PRE).

BACKGROUND
An observational study was conducted in 12 European countries by the European Federation of Clinical Chemistry and Laboratory Medicine Working Group for the Preanalytical Phase (EFLM WG-PRE) to assess the level of compliance with the CLSI H3-A6 guidelines.


METHODS
A structured checklist including 29 items was created to assess the compliance of European phlebotomy procedures with the CLSI H3-A6 guideline. A risk occurrence chart of individual phlebotomy steps was created from the observed error frequency and severity of harm of each guideline key issue. The severity of errors occurring during phlebotomy was graded using the risk occurrence chart.


RESULTS
Twelve European countries participated with a median of 33 (18-36) audits per country, and a total of 336 audits. The median error rate for the total phlebotomy procedure was 26.9 % (10.6-43.8), indicating a low overall compliance with the recommended CLSI guideline. Patient identification and test tube labelling were identified as the key guideline issues with the highest combination of probability and potential risk of harm. Administrative staff did not adhere to patient identification procedures during phlebotomy, whereas physicians did not adhere to test tube labelling policy.


CONCLUSIONS
The level of compliance of phlebotomy procedures with the CLSI H3-A6 guidelines in 12 European countries was found to be unacceptably low. The most critical steps in need of immediate attention in the investigated countries are patient identification and tube labelling.
On the Cognitive Processes of Human Perception with Emotions, Motivations, and Attitudes

An interactive motivation-attitude theory is developed based on the Layered Reference Model of the Brain (LRMB) and the object-attribute-relation (OAR) model. This paper presents a rigorous model of human perceptual processes such as emotions, motivations, and attitudes. A set of mathematical models and formal cognitive processes of perception is developed. Interactions and relationships between motivation and attitude are formally described in real-time process algebra (RTPA). Applications of the mathematical models of motivations and attitudes in software engineering are demonstrated. This work is a part of the formalization of LRMB, which provides a comprehensive model for explaining the fundamental cognitive processes of the brain and their interactions. This work demonstrates that the complicated human emotional and perceptual phenomena can be rigorously modeled and formally treated based on cognitive informatics theories and denotational mathematics.
Monitoring for Precision Agriculture using Wireless Sensor Network-A review

This paper explores the potential of WSN in the area of agriculture in India. Aiming at the sugarcane crop, a multi-parameter monitoring system is designed based on low-power ZigBee wireless communication technology for system automation and monitoring. Real time data is collected by wireless sensor nodes and transmitted to base station using zigbee. Data is received, saved and displayed at base station to achieve soil temperature, soil moisture and humidity monitoring. The data is continuously monitored at base station and if it exceeds the desired limit, a message is sent to farmer on mobile through GSM network for controlling actions. The implementation of system software and hardware are given, including the design of wireless node and the implementation principle of data transmission and communication modules. This system overcomes the limitations of wired sensor networks and has the advantage of flexible networking for monitoring equipment, convenient installation and removing of equipment, low cost and reliable nodes and high capacity.
Doing It Now or Later

We examine self-control problems — modeled as time-inconsistent, presentbiased preferences—in a model where a person must do an activity exactly once. We emphasize two distinctions: Do activities involve immediate costs or immediate rewards, and are people sophisticated or naive about future self-control problems? Naive people procrastinate immediate-cost activities and preproperate—do too soon—immediate-reward activities. Sophistication mitigates procrastination, but exacerbates preproperation. Moreover, with immediate costs, a small present bias can severely harm only naive people, whereas with immediate rewards it can severely harm only sophisticated people. Lessons for savings, addiction, and elsewhere are discussed. (JEL A12, B49, C70, D11, D60, D74, D91, E21)
A hybrid parallel Delaunay image-to-mesh conversion algorithm scalable on distributed-memory clusters

In this paper, we present a scalable three dimensional hybrid MPI+Threads parallel Delaunay image-to-mesh conversion algorithm. A nested master-worker communication model for parallel mesh generation is implemented which simultaneously explores process-level parallelization and thread-level parallelization: inter-node communication using MPI and inter-core communication inside one node using threads. In order to overlap the communication (task request and data movement) and computation (parallel mesh refinement), the inter-node MPI communication and intra-node local mesh refinement is separated. The master thread that initializes the MPI environment is in charge of the inter-node MPI communication while the worker threads of each process are only responsible for the local mesh refinement within the node. We conducted a set of experiments to test the performance of the algorithm on Turing, a distributed memory cluster at Old Dominion University High Performance Computing Center and observed that the granularity of coarse level data decomposition, which affects the coarse level concurrency, has a significant influence on the performance of the algorithm. With the proper value of granularity, the algorithm expresses impressive performance potential and is scalable to 30 distributed memory compute nodes with 20 cores each (the maximum number of nodes available for us in the experiments). c © 2016 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of organizing committee of the 25th International Meshing Roundtable (IMR25).
Support Vectors Machine-based identification of heart valve diseases using heart sounds

Taking into account that heart auscultation remains the dominant method for heart examination in the small health centers of the rural areas and generally in primary healthcare set-ups, the enhancement of this technique would aid significantly in the diagnosis of heart diseases. In this context, the present paper initially surveys the research that has been conducted concerning the exploitation of heart sound signals for automated and semi-automated detection of pathological heart conditions. Then it proposes an automated diagnosis system for the identification of heart valve diseases based on the Support Vector Machines (SVM) classification of heart sounds. This system performs a highly difficult diagnostic task (even for experienced physicians), much more difficult than the basic diagnosis of the existence or not of a heart valve disease (i.e. the classification of a heart sound as 'healthy' or 'having a heart valve disease'): it identifies the particular heart valve disease. The system was applied in a representative global dataset of 198 heart sound signals, which come both from healthy medical cases and from cases suffering from the four most usual heart valve diseases: aortic stenosis (AS), aortic regurgitation (AR), mitral stenosis (MS) and mitral regurgitation (MR). Initially the heart sounds were successfully categorized using a SVM classifier as normal or disease-related and then the corresponding murmurs in the unhealthy cases were classified as systolic or diastolic. For the heart sounds diagnosed as having systolic murmur we used a SVM classifier for performing a more detailed classification of them as having aortic stenosis or mitral regurgitation. Similarly for the heart sounds diagnosed as having diastolic murmur we used a SVM classifier for classifying them as having aortic regurgitation or mitral stenosis. Alternative classifiers have been applied to the same data for comparison (i.e. back-propagation neural networks, k-nearest-neighbour and naïve Bayes classifiers), however their performance for the same diagnostic problems was lower than the SVM classifiers proposed in this work.
A Data Quality in Use model for Big Data

Beyond the hype of Big Data, something within business intelligence projects is indeed changing. This is mainly because Big Data is not only about data, but also about a complete conceptual and technological stack including raw and processed data, storage, ways of managing data, processing and analytics. A challenge that becomes even trickier is the management of the quality of the data in Big Data environments. More than ever before the need for assessing the Quality-in-Use gains importance since the real contribution – business value – of data can be only estimated in its context of use. Although there exists different Data Quality models for assessing the quality of regular data, none of them has been adapted to Big Data. To fill this gap, we propose the ‘‘3As Data Quality-in-Use model’’, which is composed of three Data Quality characteristics for assessing the levels of Data Quality-in-Use in Big Data projects: Contextual Adequacy, Operational Adequacy and Temporal Adequacy. The model can be integrated into any sort of BigData project, as it is independent of anypre-conditions or technologies. Thepaper shows the way to use the model with a working example. The model accomplishes every challenge related to Data Quality program aimed for Big Data. The main conclusion is that the model can be used as an appropriate way to obtain the Quality-in-Use levels of the input data of the Big Data analysis, and those levels can be understood as indicators of trustworthiness and soundness of the results of the Big Data analysis. © 2015 Elsevier B.V. All rights reserved.
Tortoise and Hares Consensus: the Meshcash Framework for Incentive-Compatible, Scalable Cryptocurrencies

We propose Meshcash, a new framework for cryptocurrency protocols that combines a novel, proof-of-work based, permissionless byzantine consensus protocol (the tortoise) that guarantees eventual consensus and irreversibility, with a possibly-faulty but quick consensus protocol (the hare). The construction is modular, allowing any suitable “hare” protocol to be plugged in. The combined protocol enjoys best of both worlds properties: consensus is quick if the hare protocol succeeds, but guaranteed even if it is faulty. Unlike most existing proofof-work based consensus protocols, our tortoise protocol does not rely on leader-election (e.g., the single miner who managed to extend the longest chain). Rather, we use ideas from asynchronous byzantine agreement protocols to gradually converge to a consensus. Meshcash, is designed to be race-free: there is no “race” to generate the next block, hence honestly-generated blocks are always rewarded. This property, which we define formally as a game-theoretic notion, turns out to be useful in analyzing rational miners’ behavior: we prove (using a generalization of the blockchain mining games of Kiayias et al.) that race-free blockchain protocols are incentive-compatible and satisfy linearity of rewards (i.e., a party receives rewards proportional to its computational power). Because Meshcash can tolerate a high block rate regardless of network propagation delays (which will only affect latency), it allows us to lower both the variance and the expected time between blocks for honest miners; together with linearity of rewards, this makes pooled mining far less attractive. Moreover, race-free protocols scale more easily (in terms of transaction rate). This is because the race-free property implies that the network propagation delays are not a factor in terms of rewards, which removes the main impediment to accommodating a larger volume of transactions. We formally prove that all of our guarantees hold in the asynchronous communication model of Pass, Seeman and shelat, and against a constant fraction of byzantine (malicious) miners; not just rational ones.
Applicability of current diagnostic algorithms in geriatric patients suspected of new, slow onset heart failure.

BACKGROUND
referral for echocardiography for all geriatric outpatients suspected of heart failure (HF) is not feasible. Diagnostic algorithms could be helpful.


OBJECTIVE
to investigate whether available diagnostic algorithms accurately identify (older) patients (aged 70 years or over) eligible for echocardiography, with acceptable numbers of false-negatives.


METHODS
algorithms (European Society of Cardiology (ESC)) guideline, National Institute for Health and Clinical Excellence (NICE) guideline, multidisciplinary guideline the Netherlands (NL) and algorithm by Mant et al. were validated in 203 geriatric patients (mean age 82 ± 6 years, 30% men) suspected of new, slow onset HF. HF was adjudicated by an outcome panel. Applicability of algorithms was evaluated by calculating proportion of patients (i) referred for echocardiography, (ii) with HF among referred patients and (iii) without HF in the non-referred.


RESULTS
ninety-two (45%) patients had HF. Applying algorithms resulted in referral for echocardiography in 52% (normal NT-proBNP; ESC), 72% (normal ECG; ESC), 56% (NICE), 93% (NL) and 70% (Mant) of all patients, diagnosing HF in 78, 56, 76, 49 and 62% of those referred, respectively. In patients not referred for echocardiography HF was absent in 90, 82, 93, 100 and 95%, respectively.


CONCLUSION
the ESC NT-proBNP (<400 pg/ml)-based algorithm combines the lowest number of referrals for echocardiography (of whom 78% has HF) with a limited number (10%) of false negatives in the non-referred.
Multiplex CRISPR/Cas9-based genome engineering from a single lentiviral vector

Engineered DNA-binding proteins that manipulate the human genome and transcriptome have enabled rapid advances in biomedical research. In particular, the RNA-guided CRISPR/Cas9 system has recently been engineered to create site-specific double-strand breaks for genome editing or to direct targeted transcriptional regulation. A unique capability of the CRISPR/Cas9 system is multiplex genome engineering by delivering a single Cas9 enzyme and two or more single guide RNAs (sgRNAs) targeted to distinct genomic sites. This approach can be used to simultaneously create multiple DNA breaks or to target multiple transcriptional activators to a single promoter for synergistic enhancement of gene induction. To address the need for uniform and sustained delivery of multiplex CRISPR/Cas9-based genome engineering tools, we developed a single lentiviral system to express a Cas9 variant, a reporter gene and up to four sgRNAs from independent RNA polymerase III promoters that are incorporated into the vector by a convenient Golden Gate cloning method. Each sgRNA is efficiently expressed and can mediate multiplex gene editing and sustained transcriptional activation in immortalized and primary human cells. This delivery system will be significant to enabling the potential of CRISPR/Cas9-based multiplex genome engineering in diverse cell types.
Concordance of performance metrics among U.S. trauma centers caring for injured children.

BACKGROUND
Several indicators of quality pediatric trauma care have been proposed including low in-hospital mortality, nonoperative management of blunt splenic injury, use of intracranial pressure monitors after severe traumatic brain injury, and craniotomy for children with severe subdural or epidural hematomas. It is not known if center-level performance is consistent in each of these metrics. We evaluated whether center performance in one area of quality predicted similar performance in other areas of quality.


METHODS
We reviewed patients 18 years or younger who were hospitalized with an injury Abbreviated Injury Scale (AIS) score of 2 or greater from 2010 to 2011 at trauma centers (n = 150) participating in the Trauma Quality Improvement Program. Random-intercept multilevel modeling was used to generate center-specific adjusted odds ratios for each quality indicator. We evaluated correlations between center-specific adjusted odds ratios of each quality indicator and mortality using Pearson correlation coefficients. Weighted κ statistics were used to test multiple pairwise agreements between indicators and the overall agreement across all four indicators.


RESULTS
Among 84,880 children identified for analysis, 3,603 had blunt splenic injury, 3,503 had severe traumatic brain injury, and 1,286 had an epidural or subdural hematoma. A negative correlation between center-specific odds of mortality and craniotomy was present (Pearson correlation coefficient, -0.18; p = 0.03). There were no significant correlations between other indicators. Although κ statistics showed slight agreement for the pairwise comparison of odds of mortality and craniotomy (0.17, 0.02-0.32), there was no agreement for all other pairwise comparisons or the overall comparison of all four indicators (-0.01, -0.07 to 0.06).


CONCLUSION
Our findings demonstrate a lack of concordance in center-level performance across the four pediatric trauma quality indicators we evaluated. These findings should be considered by pediatric trauma quality improvement initiatives to allow for comprehensive measurement of hospital quality as opposed to benchmarking using a single indicator.
Neural correlates of dispositional mindfulness during affect labeling.

OBJECTIVE
Mindfulness is a process whereby one is aware and receptive to present moment experiences. Although mindfulness-enhancing interventions reduce pathological mental and physical health symptoms across a wide variety of conditions and diseases, the mechanisms underlying these effects remain unknown. Converging evidence from the mindfulness and neuroscience literature suggests that labeling affect may be one mechanism for these effects.


METHODS
Participants (n = 27) indicated trait levels of mindfulness and then completed an affect labeling task while undergoing functional magnetic resonance imaging. The labeling task consisted of matching facial expressions to appropriate affect words (affect labeling) or to gender-appropriate names (gender labeling control task).


RESULTS
After controlling for multiple individual difference measures, dispositional mindfulness was associated with greater widespread prefrontal cortical activation, and reduced bilateral amygdala activity during affect labeling, compared with the gender labeling control task. Further, strong negative associations were found between areas of prefrontal cortex and right amygdala responses in participants high in mindfulness but not in participants low in mindfulness.


CONCLUSIONS
The present findings with a dispositional measure of mindfulness suggest one potential neurocognitive mechanism for understanding how mindfulness meditation interventions reduce negative affect and improve health outcomes, showing that mindfulness is associated with enhanced prefrontal cortical regulation of affect through labeling of negative affective stimuli.
Социально-психологические установки как фактор, определяющий моральное сознание личности

The article deals with methodical prerequisites for social and psychological aims in the context of the research made by Georgian school of authors under the direction of D.N. Uznadze. The author shows interrelationship between social and psychological aims, in particular communicative aim in relations, and moral consciousness of the personality.
Detection of bladder cancer using a point-of-care proteomic assay.

CONTEXT
A combination of methods is used for diagnosis of bladder cancer because no single procedure detects all malignancies. Urine tests are frequently part of an evaluation, but have either been nonspecific for cancer or required specialized analysis at a laboratory.


OBJECTIVE
To investigate whether a point-of-care proteomic test that measures the nuclear matrix protein NMP22 in voided urine could enhance detection of malignancy in patients with risk factors or symptoms of bladder cancer.


DESIGN, SETTING, AND PATIENTS
Twenty-three academic, private practice, and veterans' facilities in 10 states prospectively enrolled consecutive patients from September 2001 to May 2002. Participants included 1331 patients at elevated risk for bladder cancer due to factors such as history of smoking or symptoms including hematuria and dysuria. Patients at risk for malignancy of the urinary tract provided a voided urine sample for analysis of NMP22 protein and cytology prior to cystoscopy.


MAIN OUTCOME MEASURES
The diagnosis of bladder cancer, based on cystoscopy with biopsy, was accepted as the reference standard. The performance of the NMP22 test was compared with voided urine cytology as an aid to cancer detection. Testing for the NMP22 tumor marker was conducted in a blinded manner.


RESULTS
Bladder cancer was diagnosed in 79 patients. The NMP22 assay was positive in 44 of 79 patients with cancer (sensitivity, 55.7%; 95% confidence interval [CI], 44.1%-66.7%), whereas cytology test results were positive in 12 of 76 patients (sensitivity, 15.8%; 95% CI, 7.6%-24.0%). The specificity of the NMP22 assay was 85.7% (95% CI, 83.8%-87.6%) compared with 99.2% (95% CI, 98.7%-99.7%) for cytology. The proteomic marker detected 4 cancers that were not visualized during initial endoscopy, including 3 that were muscle invasive and 1 carcinoma in situ.


CONCLUSION
The noninvasive point-of-care assay for elevated urinary NMP22 protein can increase the accuracy of cystoscopy, with test results available during the patient visit.
94%-Effective Policies for a Two-Stage Serial Inventory System with Stochastic Demand

A two-stage inventory system is considered where Poisson demand occurs at Stage 1, and Stage 1 replenishes its inventory from Stage 2, which in turn orders from an outside supplier with unlimited stock. Each shipment, either to Stage 2 or to Stage 1, incurs a fixed setup cost. Under the assumption that the supply leadtime at Stage 2 is zero, we characterize a simple heuristic policy whose long-run average cost is guaranteed to be within 6% of optimality, i.e., a 94%-effective policy. The paper also provides heuristic policies for more general inventory systems and reports computational results. (Multi-Echelon Inventory; Stochastic Demand; Worst Case Analysis; Heuristic Policy)