bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel approach for big data processing using message passing interface based on memory mapping
Authors: Dheyab Saad Ahmed , Abdullah Mohammed Najm , Abed Buthainah Fahran 
Published: December 2019

AbstractThe analysis and processing of big data are one of the most important challenges that researchers are working on to find the best approaches to handle it with high performance, low cost and high accuracy. In this paper, a novel approach for big data processing and management was proposed that differed from the existing ones; the proposed method employs not only the memory space to reads and handle big data, it also uses space of memory-mapped extended from memory storage. From a methodological viewpoint, the novelty of this paper is the segmentation stage of big data using memory mapping and broadcasting all segments to a number of processors using a parallel message passing interface. From an application viewpoint, the paper presents a high-performance approach based on a homogenous network which works parallelly to encrypt-decrypt big data using AES algorithm. This approach can be done on Windows Operating System using .NET libraries.
Enhanced renal clearance and impact on vancomycin pharmacokinetic parameters in patients with hemorrhagic stroke
Authors: Morbitzer Kathryn A. , Rhoney Denise H. , Dehne Kelly A. , Jordan J. Dedrick 
Published: December 2019

Abstract
Background
The majority of patients with hemorrhagic stroke experience enhanced renal clearance or augmented renal clearance (ARC). The purpose of this study was to determine the impact of enhanced renal clearance or ARC on vancomycin pharmacokinetic (PK) parameters.

Methods
This was a post hoc analysis of a prospective study of adult patients with aneurysmal subarachnoid hemorrhage (aSAH) or intracerebral hemorrhage (ICH) admitted to the neurosciences intensive care unit who received vancomycin. Creatinine clearance (CrCl) was measured and also estimated using the Cockcroft-Gault equation. Predicted PK parameters were compared with calculated PK parameters using serum peak and trough concentrations.

Results
Seventeen hemorrhagic stroke patients met inclusion criteria. All patients experienced enhanced renal clearance on the day that the vancomycin concentrations were obtained, and 12 patients (71%) experienced ARC. The mean calculated elimination rate constant was significantly higher than the predicted value (0.141 ± 0.02 vs. 0.087 ± 0.01 h−1; p = 0.004) and the mean calculated half-life was significantly lower than the predicted half-life (6.5 ± 0.9 vs. 8.7 ± 0.6 h; p = 0.03).

Conclusions
Patients with hemorrhagic stroke and enhanced renal clearance displayed PK alterations favoring an increased elimination of vancomycin than expected. This may result in underexposure to vancomycin, leading to treatment failure.
Non-convulsive seizures in the encephalopathic critically ill cancer patient does not necessarily portend a poor prognosis
Authors: Gutierrez Cristina , Chen Merry , Feng Lei , Tummala Sudhakar 
Published: December 2019

Abstract
Background
Non-convulsive status epilepticus (NCSE) is present in 10–30% of ICU patients with altered mental status (AMS) and is associated to poor outcomes. To our knowledge, there is no data describing the prevalence and outcomes of critically ill cancer patients with AMS associated to non-convulsive seizures (NCS) or NCSE. We aim to describe the outcomes and risk factors of critically ill cancer patients with encephalopathy associated with non-convulsive seizures (NCS).

Methods
This is a 3-year prospective observational study in a mixed oncological ICU at MD Anderson Cancer Center. Data of ICU patients with moderate to severe encephalopathy (Glasgow Coma Score < 13) that underwent EEG monitoring to rule out NCS were collected. Multivariate logistic regression was performed to identify risk factors and outcomes.

Results
Of the 317 patients with encephalopathy who underwent EEG monitoring, 14.5% had NCS. Known risk factors such as sepsis, CNS infection, antibiotics, and cardiac arrest were not associated with increased risk of NCS. Patients with NCS were more likely to have received recent chemotherapy (41.3% vs 21.4%; p = 0.0036), have a CNS disease (39% vs 24.4%; p = 0.035), and abnormal brain imaging (60.9% vs 44.6%; p = 0.041). Patients with lower SOFA scores, normal renal function, and absence of shock were likely to have NCS as the cause of their encephalopathy (p < 0.03). After multivariate analysis, only abnormal brain imaging and absence of renal failure were associated with NCS. Mortality was significantly lower in patients with non-convulsive seizures when compared to those without seizures (45.7% vs 64%; p = 0.022); however, there was no significant association of seizures and mortality on a multivariable logistic regression analysis.

Conclusions
NCS in critically ill cancer patients is associated with abnormalities on brain imaging and lower prevalence of organ failure. Diagnosis and treatment of NCS should be a priority in encephalopathic cancer patients, as they can have lower mortality than non-seizing patients. Opposite to other populations, NCS should not be considered a poor prognostic factor in critically ill encephalopathic cancer patients as they reflect a reversible cause for altered mentation.
Monitoring of muscle mass in critically ill patients: comparison of ultrasound and two bioelectrical impedance analysis devices
Authors: Nakanishi Nobuto , Tsutsumi Rie , Okayama Yoshihiro , Takashima Takuya , Ueno Yoshitoyo , Itagaki Taiga , Tsutsumi Yasuo , Sakaue Hiroshi , Oto Jun 
Published: December 2019

Abstract
Background
Skeletal muscle atrophy commonly occurs in critically ill patients, and decreased muscle mass is associated with worse clinical outcomes. Muscle mass can be assessed using various tools, including ultrasound and bioelectrical impedance analysis (BIA). However, the effectiveness of muscle mass monitoring is unclear in critically ill patients. This study was conducted to compare ultrasound and BIA for the monitoring of muscle mass in critically ill patients.

Methods
We recruited adult patients who were expected to undergo mechanical ventilation for > 48 h and to remain in the intensive care unit (ICU) for > 5 days. On days 1, 3, 5, 7, and 10, muscle mass was evaluated using an ultrasound and two BIA devices (Bioscan: Malton International, England; Physion: Nippon Shooter, Japan). The influence of fluid balance was also evaluated between each measurement day.

Results
We analyzed 93 images in 21 patients. The age of the patients was 69 (interquartile range, IQR, 59–74) years, with 16 men and 5 women. The length of ICU stay was 11 days (IQR, 9–25 days). The muscle mass, monitored by ultrasound, decreased progressively by 9.2% (95% confidence interval (CI), 5.9–12.5%), 12.7% (95% CI, 9.3–16.1%), 18.2% (95% CI, 14.7–21.6%), and 21.8% (95% CI, 17.9–25.7%) on days 3, 5, 7, and 10 (p <  0.01), respectively, with no influence of fluid balance (r = 0.04, p = 0.74). The muscle mass did not decrease significantly in both the BIA devices (Bioscan, p = 0.14; Physion, p = 0.60), and an influence of fluid balance was observed (Bioscan, r = 0.37, p <  0.01; Physion, r = 0.51, p <  0.01). The muscle mass assessment at one point between ultrasound and BIA was moderately correlated (Bioscan, r = 0.51, p <  0.01; Physion, r = 0.37, p <  0.01), but the change of muscle mass in the same patient did not correlate between these two devices (Bioscan, r = − 0.05, p = 0.69; Physion, r = 0.23, p = 0.07).

Conclusions
Ultrasound is suitable for sequential monitoring of muscle atrophy in critically ill patients. Monitoring by BIA should be carefully interpreted owing to the influence of fluid change.

Trial registration
UMIN000031316. Retrospectively registered on 15 February 2018.
Perceptions of students after implementing peer instruction in an introductory physics course
Authors: Budini Nicolás , Marino Luis , Carreri Ricardo , Cámara Cristina , Giorgi Silvia 
Published: December 2019

AbstractIn the present work we carried out a qualitative educational research to assess the perceptions of a group of students that attended (weekly and non-mandatory) complementary classes of a physics course during 2017. In these classes the teaching method called peer instruction (PI) was implemented, which involves collaborative learning among students. From the students’ responses to a simple questionnaire we assessed some basic aspects of these classes from which we can conclude that, in the first place, students considered that PI had positively influenced their comprehension of physical concepts and that, secondly, they positively valued the activities performed and the dynamics of these classes. These results, which are part of a series of previous works that have been published elsewhere, are relevant in a context were active and collaborative learning strategies are practically non-existent and push us to continue and broaden the implementation of this and other active learning methods in physics courses.
Potential deployment of offshore bottom pressure gauges and adoption of data assimilation for tsunami warning system in the western Mediterranean Sea
Authors: Heidarzadeh Mohammad , Wang Yuchen , Satake Kenji , Mulia Iyan E. 
Published: December 2019

AbstractWestern Mediterranean Basin (WMB) is among tsunamigenic zones with numerous historical records of tsunami damage and deaths. Most recently, a moderate tsunami on 21 May 2003 offshore Algeria, North Africa, was a fresh call for strengthening tsunami warning capabilities in this enclosed water basin. Here, we propose to deploy offshore bottom pressure gauges (OBPGs) and to adopt the framework of a tsunami data assimilation (TDA) approach for providing timely tsunami forecasts. We demonstrate the potential enhancement of the tsunami warning system through the case study of the 2003 Algeria tsunami. Four scenarios of OBPG arrangements involving 10, 5, 3 and 2 gauges are considered. The offshore gauges are located at distances of 120–300 km from the North African coast. The warning lead times are 20, 30, 48 and 55 min for four points of interest considered in this study: Ibiza, Palma, Sant Antoni and Barcelona, respectively. The forecast accuracies are in the range of 69–85% for the four OBPG scenarios revealing acceptable accuracies for tsunami warnings. We conclude that installation of OBPGs in the WMB can be helpful for providing successful and timely tsunami forecasts. We note that the OBPG scenarios proposed in this study are applicable only for the case of the 2003 Algeria tsunami. Further studies including sensitivity analyses (e.g., number of OBPG stations; earthquake magnitude, strike, epicenter) are required in order to determine OBPG arrangements that could be useful for various earthquake scenarios in the WMB.
Uncertainty in hourly mean data from classical magnetometers
Authors: Curto J. J. 
Published: December 2019

AbstractHourly mean values obtained from analog magnetometers in what can be considered the “classical” period constitute the largest quantity of data we have on the evolution of the Earth’s magnetic field. They are used for a wide variety of applications such as estimating long-term solar–terrestrial interactions, the production of magnetic indices, or studying geomagnetic secular variation originated in the Earth’s core. However, these data do not have an associated uncertainty that would allow us to quantify the final uncertainty of the results of these models. Hence, our study tries to assess the degree of uncertainty that these data actually have. In this paper, using Ebro Observatory classical instrumentation, we work out these uncertainties by estimating the particular uncertainties of each significant variable involved in the measuring procedure. Although the study is implemented for Ebro, the method can be applied to any other observatory. We found that, in general, uncertainties vary from one magnetic component to another, depending on the nature of the instruments that were used. In each component, we identified the weakest points where the biggest part of the error resides. With our results we can state that total uncertainties ranged from 1 to 4 nT.
Selenium and hydrogen selenide: essential micronutrient and the fourth gasotransmitter?
Authors: Kuganesan Mathun , Samra Kavitej , Evans Eloise , Singer Mervyn , Dyson Alex 
Published: December 2019

AbstractSelenium (Se) is an essential micronutrient required by organisms of diverse lineage. Dietary Se is converted to hydrogen selenide either enzymatically or by endogenous antioxidant proteins. This convergent biochemical step crucially underlies the subsequent biological activity of Se and argues for inclusion of hydrogen selenide as the fourth endogenous gasotransmitter alongside nitric oxide, carbon monoxide and hydrogen sulfide.Endogenously generated hydrogen selenide is incorporated into numerous ‘selenoprotein’ oxidoreductase enzymes, essential for maintaining redox-status homeostasis in health and disease. Direct effects of endogenous hydrogen selenide on cellular and molecular targets are currently unknown. Given exogenously, hydrogen selenide acts as a modulator of metabolism via transient inhibition of mitochondrial cytochrome C oxidase. Here we provide an overview of Se biology, its impact on several physiological systems (immune, endocrine, cardiovascular and metabolic) and its utility as a supplement in acute and critical illness states. We further explore the evidence base supporting its role as the fourth gasotransmitter and propose a strategic case towards generation of novel selenomimetic therapeutics.
An intelligent shopping support robot: understanding shopping behavior from 2D skeleton data using GRU network
Authors: Islam Md Matiqul , Lam Antony , Fukuda Hisato , Kobayashi Yoshinori , Kuno Yoshinori 
Published: December 2019

AbstractIn supermarkets or grocery, a shopping cart is a necessary tool for shopping. In this paper, we have developed an intelligent shopping support robot that can carry a shopping cart while following its owners and provide the shopping support by observing the customer’s head orientation, body orientation and recognizing different shopping behaviors. Recognizing shopping behavior or the intensity of such action is important for understanding the best way to support the customer without disturbing him or her. This system also liberates elderly and disabled people from the burden of pushing shopping carts, because our proposed shopping cart is essentially a type of autonomous mobile robots that recognizes its owner and following him or her. The proposed system discretizes the head and body orientation of customer into 8 directions to estimate whether the customer is looking or turning towards a merchandise shelf. From the robot’s video stream, a DNN-based human pose estimator called OpenPose is used to extract the skeleton of 18 joints for each detected body. Using this extracted body joints information, we built a dataset and developed a novel Gated Recurrent Neural Network (GRU) topology to classify different actions that are typically performed in front of shelves: reach to shelf, retract from shelf, hand in shelf, inspect product, inspect shelf. Our GRU network model takes series of 32 frames skeleton data then gives the prediction. Using cross-validation tests, our model achieves an overall accuracy of 82%, which is a significant result. Finally, from the customer’s head orientation, body orientation and shopping behavior recognition we develop a complete system for our shopping support robot.
Development of a blood sample detector for multi-tracer positron emission tomography using gamma spectroscopy
Authors: Velasco Carlos , Mota-Cobián Adriana , Mateo Jesús , España Samuel 
Published: December 2019

Abstract
Background
Multi-tracer positron emission tomography (PET) imaging can be accomplished by applying multi-tracer compartment modeling. Recently, a method has been proposed in which the arterial input functions (AIFs) of the multi-tracer PET scan are explicitly derived. For that purpose, a gamma spectroscopic analysis is performed on blood samples manually withdrawn from the patient when at least one of the co-injected tracers is based on a non-pure positron emitter. Alternatively, these blood samples required for the spectroscopic analysis may be obtained and analyzed on site by an automated detection device, thus minimizing analysis time and radiation exposure of the operating personnel. In this work, a new automated blood sample detector based on silicon photomultipliers (SiPMs) for single- and multi-tracer PET imaging is presented, characterized, and tested in vitro and in vivo.

Results
The detector presented in this work stores and analyzes on-the-fly single and coincidence detected events. A sensitivity of 22.6 cps/(kBq/mL) and 1.7 cps/(kBq/mL) was obtained for single and coincidence events respectively. An energy resolution of 35% full-width-half-maximum (FWHM) at 511 keV and a minimum detectable activity of 0.30 ± 0.08 kBq/mL in single mode were obtained. The in vivo AIFs obtained with the detector show an excellent Pearson’s correlation (r = 0.996, p < 0.0001) with the ones obtained from well counter analysis of discrete blood samples. Moreover, in vitro experiments demonstrate the capability of the detector to apply the gamma spectroscopic analysis on a mixture of 68Ga and 18F and separate the individual signal emitted from each one.

Conclusions
Characterization and in vivo evaluation under realistic experimental conditions showed that the detector proposed in this work offers excellent sensibility and stability. The device also showed to successfully separate individual signals emitted from a mixture of radioisotopes. Therefore, the blood sample detector presented in this study allows fully automatic AIFs measurements during single- and multi-tracer PET studies.
Reproducibility of compartmental modelling of 18F-FDG PET/CT to evaluate lung inflammation
Authors: Vass Laurence D. , Lee Sarah , Wilson Frederick J. , Fisk Marie , Cheriyan Joseph , Wilkinson Ian 
Published: December 2019

Abstract
Introduction
Compartmental modelling is an established method of quantifying 18F-FDG uptake; however, only recently has it been applied to evaluate pulmonary inflammation. Implementation of compartmental models remains challenging in the lung, partly due to the low signal-to-noise ratio compared to other organs and the lack of standardisation. Good reproducibility is a key requirement of an imaging biomarker which has yet to be demonstrated in pulmonary compartmental models of 18F-FDG; in this paper, we address this unmet need.

Methods
Retrospective subject data were obtained from the EVOLVE observational study: Ten COPD patients (age =66±9; 8M/2F), 10 α1ATD patients (age =63±8; 7M/3F) and 10 healthy volunteers (age =68±8; 9M/1F) never smokers. PET and CT images were co-registered, and whole lung regions were extracted from CT using an automated algorithm; the descending aorta was defined using a manually drawn region. Subsequent stages of the compartmental analysis were performed by two independent operators using (i) a MIAKATTM based pipeline and (ii) an in-house developed pipeline. We evaluated the metabolic rate constant of 18F-FDG (Kim) and the fractional blood volume (Vb); Bland-Altman plots were used to compare the results. Further, we adjusted the in-house pipeline to identify the salient features in the analysis which may help improve the standardisation of this technique in the lung.

Results
The initial agreement on a subject level was poor: Bland-Altman coefficients of reproducibility for Kim and Vb were 0.0031 and 0.047 respectively. However, the effect size between the groups (i.e. COPD, α1ATD and healthy subjects) was similar using either pipeline. We identified the key drivers of this difference using an incremental approach: ROI methodology, modelling of the IDIF and time delay estimation. Adjustment of these factors led to improved Bland-Altman coefficients of reproducibility of 0.0015 and 0.027 for Kim and Vb respectively.

Conclusions
Despite similar methodology, differences in implementation can lead to disparate results in the outcome parameters. When reporting the outcomes of lung compartmental modelling, we recommend the inclusion of the details of ROI methodology, input function fitting and time delay estimation to improve reproducibility.
A Nordic survey of CT doses in hybrid PET/CT and SPECT/CT examinations
Authors: Bebbington Natalie A. , Haddock Bryan T. , Bertilsson Henrik , Hippeläinen Eero , Husby Ellen M. , Tunninen Virpi I. , Söderberg Marcus 
Published: December 2019

Abstract
Background
Computed tomography (CT) scans are routinely performed in positron emission tomography (PET) and single photon emission computed tomography (SPECT) examinations globally, yet few surveys have been conducted to gather national diagnostic reference level (NDRL) data for CT radiation doses in positron emission tomography/computed tomography (PET/CT) and single photon emission computed tomography/computed tomography (SPECT/CT). In this first Nordic-wide study of CT doses in hybrid imaging, Nordic NDRL CT doses are suggested for PET/CT and SPECT/CT examinations specific to the clinical purpose of CT, and the scope for optimisation is evaluated. Data on hybrid imaging CT exposures and clinical purpose of CT were gathered for 5 PET/CT and 8 SPECT/CT examinations via designed booklet. For each included dataset for a given facility and scanner type, the computed tomography dose index by volume (CTDIvol) and dose length product (DLP) was interpolated for a 75-kg person (referred to as CTDIvol,75kg and DLP75kg). Suggested NDRL (75th percentile) and achievable doses (50th percentile) were determined for CTDIvol,75kg and DLP75kg according to clinical purpose of CT. Differences in maximum and minimum doses (derived for a 75-kg patient) between facilities were also calculated for each examination and clinical purpose.

Results
Data were processed from 83 scanners from 43 facilities. Data were sufficient to suggest Nordic NDRL CT doses for the following: PET/CT oncology (localisation/characterisation, 15 systems); infection/inflammation (localisation/characterisation, 13 systems); brain (attenuation correction (AC) only, 11 systems); cardiac PET/CT and SPECT/CT (AC only, 30 systems); SPECT/CT lung (localisation/characterisation, 12 systems); bone (localisation/characterisation, 30 systems); and parathyroid (localisation/characterisation, 13 systems). Great variations in dose were seen for all aforementioned examinations. Greatest differences in DLP75kg for each examination, specific to clinical purpose, were as follows: SPECT/CT lung AC only (27.4); PET/CT and SPECT/CT cardiac AC only (19.6); infection/inflammation AC only (18.1); PET/CT brain localisation/characterisation (16.8); SPECT/CT bone localisation/characterisation (10.0); PET/CT oncology AC only (9.0); and SPECT/CT parathyroid localisation/characterisation (7.8).

Conclusions
Suggested Nordic NDRL CT doses are presented according to clinical purpose of CT for PET/CT oncology, infection/inflammation, brain, PET/CT and SPECT/CT cardiac, and SPECT/CT lung, bone, and parathyroid. The large variation in doses suggests great scope for optimisation in all 8 examinations.