Miracle-dz/UniFAR-FTUs huggingface dataset:
Executive Summary: American Association of Clinical Chemistry Laboratory Medicine Practice Guideline-Using Clinical Laboratory Tests to Monitor Drug Therapy in Pain Management Patients.

The AACC Academy, formerly the National Academy of Clinical Biochemistry, has developed a laboratory medicine practice guideline (LMPG)10 for using laboratory tests to monitor drug therapy in pain management patients. The purpose of this guideline was to compile evidence-based recommendations for the use of laboratory and point-of-care (POC) urine drug tests for relevant over-the-counter medications, prescribed and nonprescribed drugs, and illicit substances in pain management patients. The exact process of preparing and publishing the LMPG is shown in Table 1. View this table: Table 1. Process of preparing and publishing a laboratory medicine practice guideline. Briefly, a multidisciplinary LMPG committee was established to include clinical laboratory professionals, clinicians practicing in pain management, and other relevant stakeholders, healthcare professionals, and clinical experts. The experts on the committee are listed in the guideline and represented the AACC Academy (L.J. Langman, P.J. Jannetto); Clinical and Laboratory Standards Institute, which is jointly preparing an expert opinion guideline on laboratory testing for pain management (C.A. Hammett-Stabler, L.J. Langman, G.A. McMillin); College of American Pathologists (S.E. Melanson); Evidence-Based Laboratory Medicine Committee (W.A. Clark); clinical laboratories performing pain management testing (L.J. Langman, P.J. Jannetto, C.A. Hammett-Stabler, G.A. McMillin, S.E. Melanson); AACC (C.A. Kassed); American Academy of Pain Medicine (T.J. Lamer, R.J. Hamill-Ruth, N. Bratanow); active pain management clinicians (T.J. Lamer, R.J. Hamill-Ruth, …
Intelligent Heuristic Construction with Active Learning

Building effective optimization heuristics is a challenging task which often takes developers several months if not years to complete. Predictive modelling has recently emerged as a promising solution, automatically constructing heuristics from training data, however, obtaining this data can take months per platform. This is becoming an ever more critical problem as the pace of change in architecture increases. Indeed, if no solution is found we shall be left with out of date heuristics which cannot extract the best performance from modern machines. In this work, we present a low-cost predictive modelling approach for automatic heuristic construction which significantly reduces this training overhead. Typically in supervised learning the training instances are randomly selected, regardless of how much useful information is present. Our approach, on the other hand, uses active learning to carefully select the more informative examples, thus reducing the training time. We demonstrate this technique by automatically creating a model to determine on which device to execute four parallel programs at differing problem dimensions for a representative Cpu–Gpu based system. Our methodology is remarkably simple and yet effective, making it a strong candidate for wide adoption. At high levels of classification accuracy the average learning speed-up is 3x, as compared to the state-of-the-art.
An approach to non-linear Bayesian forecasting problems with applications

This thesis is devoted to the analysis and modelling of time series and it is concentrated on models and techniques which are of practical value. In particular we developed a wide class of non-linear dynamic models which are useful in the handling of real life problems. Initially we review the basic principles of Bayesian forecasting and the design of Dynamic Linear Models. The main body of the thesis attacks the problem of Normal non-linear estimation and forecasting. Some applications to the seasonal multiplicative model are exhaustively discussed. Following this we present the results of an application of Bayesian transfer response in Market Research. This application worked as the very first stimulus to extend the non-linear models to the exponential family. Finally we discuss the concepts of stochastic transfer response modelling and associated sequential estimation, and we report some applications of the method and models for long term forecasting.
Scaffolding language, scaffolding learning : teaching second language learners in the mainstream classroom

What I wanted was a book like the other book and ye t more. I wanted teachers, both mainstream and EAL specialists to be able to pick it up and experience the clear common sense of Gibbon’s writing. I wanted to extend my thinking, to be challenged by the new wor k. I think Gibbons has managed to give us both of thes e. I also wanted the new book to be more easily availabl e in this country. We have yet to see whether this wi ll be the case.
Mathematical model identifies effective P53 accumulation with target gene binding affinity in DNA damage response for cell fate decision

ABSTRACT Functional p53 signaling is essential for appropriate responses to diverse stimuli. P53 dynamics employs the information from the stimulus leading to selective gene expression and cell fate decision. However, the decoding mechanism of p53 dynamics under DNA damage challenge remains poorly understood. Here we mathematically modeled the recently dual-phase p53 dynamics under doxorubicin treatment. We found that p53 could perform sequential pulses followed by a high-amplitude terminal pulse at relatively low doxorubicin treatment, whereas p53 became steadily accumulated when damage level was high. The effective p53 integral above a threshold but not the absolute accumulation of p53 precisely discriminated survival and death. Silencing negative regulators in p53 network might promote the occurrence of terminal pulse. Furthermore, lower binding affinity and degradation rate of p53 target genes could favorably discriminate high and low dose doxorubicin treatment. Grouping by temporal profiles suggested that the p53 dynamics rather than the doxorubicin doses could better discriminate cellular outcomes and confer less variation for effective p53 integral reemphasizing the importance of p53 level regulation. Our model has established a theoretical framework that p53 dynamics can work cooperatively with its binding affinity to target genes leading to cell fate choice, providing new clues of optimized clinical design by manipulating p53 dynamics.
Costs and benefits of acting extraverted: A randomized controlled trial.

Evidence suggests that extraverted (i.e., bold, agentic) behavior increases positive affect (PA), and could be targeted in wellbeing interventions. However, this evidence is either causally ambiguous or has questionable ecological validity, and the potential costs of sustained extraverted behavior have received minimal attention. To address these limitations, we conducted a randomized controlled trial examining the wellbeing benefits and costs of an extraverted behavior intervention conducted in everyday life. Participants (n = 147) were randomly assigned to an "act-extraverted" intervention or a "sham" (active control) intervention for 1 week in everyday life. Additional data for a contact control condition were obtained from a previous study (n = 76). Wellbeing outcomes included PA and negative affect (NA), feelings of authenticity, and tiredness-assessed both in the moment and retrospectively. There was a positive overall effect of the acting extraverted intervention on PA and authenticity. However, wellbeing outcomes also depended on dispositional extraversion: more introverted participants had weaker PA increases, experienced increased NA and tiredness, and decreased feelings of authenticity. Implications for wellbeing interventions and personality theory are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Conversational Interfaces: A Domain-Independent Architecture for Task-Oriented Dialogues

Abstract : This paper motivates and describes a generic framework for dialogue-enabling intelligent agents and devices for task-oriented dialogue. The interface is designed to be a mechanism by which a dialogue front-end can quickly and easily be adapted for use with a wide range of devices or agents. The Conversational Intelligence requisite for participating in a large range of important task-oriented dialogues is identified and decomposed in a modular, device-independent fasion and a specialized recipe scripting language is implemented to encode device-specific information. The recipes in the recipe library compiled from this scripting language are instantiated at run time into Activities, which may be executed by the device (and jointly, by the human operator). In addition, a novel Constraint Management System is implemented in order to exploit the features of natural language which allow humans to naturally expand and restrict the permissible sets of parameters that a particular activity may take on.
Mark-release-recapture meets Species Distribution Models: Identifying micro-habitats of grassland butterflies in agricultural landscapes

Habitat demands and species mobility strongly determine the occurrence of species. Sedentary species with specific habitat requirements are assumed to occur more patchy than mobile habitat generalist species, and thus suffer stronger under habitat fragmentation and habitat deterioration. In this study we measured dispersal and habitat preference of three selected butterfly species using mark-release-recapture technique. We used data on species abundance to calculate Species Distribution Models based on high-resolution aerial photographs taken using RGB / NIR cameras mounted on a UAV. We found that microhabitats for species with specific habitat requirements occur spatially restricted. In contrast, suitable habitats are more interconnected and widespread for mobile habitat generalists. Our models indicate that even managed grassland sites have comparatively little habitat quality, while road verges provide high quality micro-habitats. In addition, dispersal was more restricted for specialist butterfly species, and higher for the two other butterfly species with less ecological specialisation. This study shows synergies arising when combining ecological data with high precision aerial pictures and Species Distribution Models, to identify micro-habitats for butterflies. This approach might be suitable to identify and conserve high quality habitats, and to improve nature conservation at the ground.
Human Error: Cause, Prediction, and Reduction

Contents: E.A. Fleishman, Foreword. Preface. Introduction. Some Queries and Some Definitions. On Taxonomic Issues. On Theories of Error. On the Prediction of Error. On the Reduction or Elimination of Error. On the Proper Classification of Errors. On the Causes of Error. Risk Management and the Control of Error. Epilogue: Further Commentaries on Error. O. Pereira, All the King's Men. J. Wreathall, An Update on Human Error.
Blood Outgrowth and Proliferation of Endothelial Colony Forming Cells are Related to Markers of Disease Severity in Patients with Pulmonary Arterial Hypertension

In pulmonary arterial hypertension (PAH), lung-angioproliferation leads to increased pulmonary vascular resistance, while simultaneous myocardial microvessel loss contributes to right ventricular (RV) failure. Endothelial colony forming cells (ECFC) are highly proliferative, angiogenic cells that may contribute to either pulmonary vascular obstruction or to RV microvascular adaptation. We hypothesize ECFC phenotypes (outgrowth, proliferation, tube formation) are related to markers of disease severity in a prospective cohort-study of 33 PAH and 30 healthy subjects. ECFC were transplanted in pulmonary trunk banded rats with RV failure. The presence of ECFC outgrowth in PAH patients was associated with low RV ejection fraction, low central venous saturation and a shorter time to clinical worsening (5.4 months (0.6–29.2) vs. 36.5 months (7.4–63.4), p = 0.032). Functionally, PAH ECFC had higher proliferative rates compared to control in vitro, although inter-patient variability was high. ECFC proliferation was inversely related to RV end diastolic volume (R2 = 0.39, p = 0.018), but not pulmonary vascular resistance. Tube formation-ability was similar among donors. Normal and highly proliferative PAH ECFC were transplanted in pulmonary trunk banded rats. While no effect on hemodynamic measurements was observed, RV vascular density was restored. In conclusion, we found that ECFC outgrowth associates with high clinical severity in PAH, suggesting recruitment. Transplantation of highly proliferative ECFC restored myocardial vascular density in pulmonary trunk banded rats, while RV functional improvements were not observed.
Effectiveness of a Malaria Surveillance Strategy Based on Active Case Detection during High Transmission Season in the Peruvian Amazon

Background: Faced with the resurgence of malaria, malaria surveillance in the Peruvian Amazon incorporated consecutive active case detection (ACD) interventions using light microscopy (LM) as reactive measure in communities with an unusual high number of cases during high transmission season (HTS). We assessed the effectiveness in malaria detection of this local ACD-based strategy. Methods: A cohort study was conducted in June–July 2015 in Mazan, Loreto. Four consecutive ACD interventions at intervals of 10 days were conducted in four riverine communities (Gamitanacocha, Primero de Enero, Libertad and Urco Miraño). In each intervention, all inhabitants were visited at home, and finger-prick blood samples collected for immediate diagnosis by LM and on filter paper for later analysis by quantitative real-time polymerase chain reaction (qPCR). Effectiveness was calculated by dividing the number of malaria infections detected using LM by the number of malaria infections detected by delayed qPCR. Results: Most community inhabitants (88.1%, 822/933) were present in at least one of the four ACD interventions. A total of 451 infections were detected by qPCR in 446 participants (54.3% of total participants); five individuals had two infections. Plasmodium vivax was the predominant species (79.8%), followed by P. falciparum (15.3%) and P. vivax-P. falciparum co-infections (4.9%). Most qPCR-positive infections were asymptomatic (255/448, 56.9%). The ACD-strategy using LM had an effectiveness of 22.8% (detection of 103 of the total qPCR-positive infections). Children aged 5–14 years, and farming as main economic activity were associated with P. vivax infections. Conclusions: Although the ACD-strategy using LM increased the opportunity of detecting and treating malaria infections during HTS, the number of detected infections was considerably lower than the real burden of infections (those detected by qPCR).
Data management in delay tolerant networks

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Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry for the Rapid Detection of Antimicrobial Resistance Mechanisms and Beyond

Matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) has been successfully applied in recent years for first-line identification of pathogens in clinical microbiology because it is simple to use, rapid, and accurate and has economic benefits in hospital management. The range of clinical applications of MALDI-TOF MS for bacterial isolates is increasing constantly, from species identification to the two most promising applications in the near future: detection of antimicrobial resistance and strain typing for epidemiological studies. SUMMARY Matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) has been successfully applied in recent years for first-line identification of pathogens in clinical microbiology because it is simple to use, rapid, and accurate and has economic benefits in hospital management. The range of clinical applications of MALDI-TOF MS for bacterial isolates is increasing constantly, from species identification to the two most promising applications in the near future: detection of antimicrobial resistance and strain typing for epidemiological studies. The aim of this review is to outline the contribution of previous MALDI-TOF MS studies in relation to detection of antimicrobial resistance and to discuss potential future challenges in this field. Three main approaches are ready (or almost ready) for clinical use, including the detection of antibiotic modifications due to the enzymatic activity of bacteria, the detection of antimicrobial resistance by analysis of the peak patterns of bacteria or mass peak profiles, and the detection of resistance by semiquantification of bacterial growth in the presence of a given antibiotic. This review provides an expert guide for MALDI-TOF MS users to new approaches in the field of antimicrobial resistance detection, especially possible applications as a routine diagnostic tool in microbiology laboratories.
Comparison of Muscular Activity and Movement Performance in Robot-Assisted and Freely Performed Exercises

End-effector-based robotic systems are, in particular, suitable for extending physical therapy in stroke rehabilitation. An adequate therapy and thus the recovery of movement can only be guaranteed if the physiological muscular activation and movement performance are influenced as little as possible by the robot itself. Yet, this relation has not been investigated in the literature. Therefore, 20 healthy subjects performed free and robot-assisted exercises under different control settings supported by an end-effector-based system. The control settings differed concerning changes in the end-effector velocity and the stiffness of the robot joints. During the exercises, data from inertial measurement unit sensors, robot kinematics, and surface electromyography were collected for the upper limbs. The results showed an increase in muscular activity during robot-assisted movements compared to freely performed movements and also differences in movement performance. The change of the control setting influenced the muscular activation, but not the movement performance. The results of the study revealed that the robot could not be regarded as only a passive element. This should be kept in mind in future robotic rehabilitation systems in order to reduce the influences of the robot itself and thus to optimize the therapy.
Implicit Learning with Artificial Grammar

본 연구에서는 EPAM(Elementary Perceiver and Memorizer) Ⅳ를 사용하여 인공 문법이 사용된 암묵적 학습에서의 인간 수행을 모사하였다. 암묵 학습(implicit learning) 과제에서 참가자들은 인공문법(artificial grammar)을 사용해 만들어진 ‘문법적’ 문자일과 무선적으로 만들어진 ‘비문법적’ 문자일을 학습하였는데, 이 때 비문법적 문자일보다 문법적 문자열의 학습이 더 우수하였다. 또한 참가자들은 이신에 본 적이 없었던 새로운 문자열에 대해시도 그 문법성을 판단할 수 있었다. 단순 기억 시스템인 EPAM Ⅳ에 항목 내 군집화(within-item chunking) 기능을 추가하여 암묵 학습 과제에서의 인간수행을 모시한 결과, EPAM Ⅳ 또한 무선적인 문자열보다 문법적인 문자열을 보다 잘 학습하였고, 비문법적 문자열과 문법적 문자열을 구별할 수 있었다. 이러한 결과는 인공 문법을 사용한 암묵 학습 과제에서의 수행이 규칙 추상화보다는 군집화(chunking)에 근거한 재인 기억을 바탕으로 이루어짐을 시사한다.
Codesign paradigm in digital/analog tradeoffs

With the growth of system on a chip (SoC), the functionality of analog components must also be considered in the design process. This paper describes some of the design implementation partitioning issues and experiences using analog and digital techniques for embedded systems. To achieve a quick turn around for new embedded system development, a design methodology was extended for analog codesign based on the specify-explore-refine paradigm and system-level design methodology. Many system-level issues were addressed including hardware/software codesign trade-offs.
Homogeneous B 1 + for bilateral breast imaging at 7 T using a five dipole transmit array merged with a high density receive loop array

To explore the use of five meandering dipole antennas in a multi‐transmit setup, combined with a high density receive array for breast imaging at 7 T for improved penetration depth and more homogeneous B1 field. Five meandering dipole antennas and 30 receiver loops were positioned on two cups around the breasts. Finite difference time domain simulations were performed to evaluate RF safety limits of the transmit setup. Scattering parameters of the transmit setup and coupling between the antennas and the detuned loops were measured. In vivo parallel imaging performance was investigated for various acceleration factors. After RF shimming, a B1 map, a T1‐weighted image, and a T2‐weighted image were acquired to assess B1 efficiency, uniformity in contrast weighting, and imaging performance in clinical applications. The maximum achievable local SAR10g value was 7.0 W/kg for 5 × 1 W accepted power. The dipoles were tuned and matched to a maximum reflection of −11.8 dB, and a maximum inter‐element coupling of −14.2 dB. The maximum coupling between the antennas and the receive loops was −18.2 dB and the mean noise correlation for the 30 receive loops 7.83 ± 8.69%. In vivo measurements showed an increased field of view, which reached to the axilla, and a high transmit efficiency. This coil enabled the acquisition of T1‐weighted images with a high spatial resolution of 0.7 mm3 isotropic and T2‐weighted spin echo images with uniformly weighted contrast.
Discrete event systems : concepts and basic results

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Bayesian Sequential Learning for EEG-Based BCI Classification Problems

Non-invasive Brain-Computer Interfaces (BCIs) have been an active research area where several different methods have been developed. They include Electroencephalography (EEG), Near-infrared Spectroscopy (NIRS), functional-MRI (fMRI) among others [1]. Of those BCIs, EEG is one of the most studied methods. This is mainly due to its fine temporal resolution, ease of use, and relatively low set-up cost. Each BCI method naturally has its own advantages and disadvantages. EEG is no exception.