bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Prevalence of Faculty Physician Burnout in Military Graduate Medical Education Training Programs: A Cross-Sectional Study of Academic Physicians in the United States Department of Defense
Authors: Summers Shane M , Nagy Christopher J , April Michael D , Kuiper Brandon W , Rodriguez Rechell G , Jones Woodson S 
Published: April 2019

AbstractIntroductionIn military populations, physician burnout has potential to adversely affect medical readiness to deploy in support of joint operations. Burnout among Graduate Medical Education (GME) faculty may further threaten the welfare of the medical force given the central role these officers have in training and developing junior physicians. The primary aim of this investigation was to estimate the prevalence of burnout among faculty physicians in United States (US) Army, Navy, and Air Force GME programs.Materials and MethodsWe conducted a cross-sectional study of faculty physicians at US military GME training programs between January 2018 and July 2018. Through direct coordination with Designated Institutional Officials, we administered the Maslach Burnout Inventory Health Services Survey (MBI-HSS) via online web link to faculty physicians listed in Accreditation Data System at each sponsoring institution. In addition to the MBI-HSS, we collected demographic data and queried physicians about common occupational stressors in order to assist institutional leaders with identifying at-risk physicians and developing future interventions to address burnout.ResultsSixteen of 21 institutions that currently sponsor military GME programs agreed to distribute the MBI-HSS survey to core faculty. We received completed assessments from 622 of the 1,769 (35.1%) reported physician core faculty at these institutions. Of the 622 physician respondents, 162 demonstrated high levels of emotional exhaustion and depersonalization for an estimated 26% prevalence of burnout. We identified only one independent risk factor for burnout: increasing numbers of deployments (OR 1.38, 95% CI 1.07–1.77). Physicians in our cohort who reported a desire to stay beyond their initial active duty service obligation were less likely to be classified with burnout (OR 0.45, 95% CI 0.26–0.77). The most common drivers of occupational distress were cumbersome bureaucratic tasks, insufficient administrative support, and overemphasis on productivity metrics.ConclusionsWe estimate that 26% of physician faculty in military GME programs are experiencing burnout. No specialty, branch of service, or specific demographic was immune to burnout in our sample. Institutional leaders in the MHS should take action to address physician burnout and consider using our prevalence estimate to assess effectiveness of future interventions.
Medical Encounters During the United States Army Special Forces Assessment and Selection Course
Authors: Knapik Joseph J , Farina Emily K , Ramirez Christian B , Pasiakos Stefan M , McClung James P , Lieberman Harris R 
Published: April 2019

AbstractIntroductionThe Special Forces Assessment and Selection (SFAS) is an extremely physically and mentally demanding 19- to 20-day course designed to determine whether Soldiers are qualified to enter the Special Forces Qualification Course. As a first step to understand medical problems during SFAS, this study examined injuries, illnesses, and activities associated with injuries during the course.Materials and MethodsMedical events during the SFAS course were compiled from Sick Call Trackers (a log of medical encounters maintained by medical personnel in the field) and Chronology of Medical Care (Standard Form 600). Descriptive statistics were calculated for each injury and illness and injuries were compiled by the activities performed when the injuries occurred.ResultsOf the 800 Soldiers who volunteered for the study, 38% (n = 307/800) and 12% (n = 97/800) experienced one or more injuries and/or illnesses, respectively. The most common injuries were blisters and abrasions/lacerations with incidences of 20% (n = 158/800) and 13% (104/800), respectively. The most common illnesses were respiratory infections, other infections, contact dermatitis, and allergies with incidences of 7% (n = 57/800), 2% (n = 14/800), 2% (n = 14/800), and 2% (n = 13/800), respectively. Among all injuries recorded (n = 573), the most common were blisters (46%), abrasions/lacerations (24%), pain (not otherwise specified) (19%), tendonitis (3%), and sprains (3%). Among all illnesses recorded (n = 133), the most common were respiratory infections (56%), allergies (11%), contact dermatitis (11%), and other infections (11%). Most injuries were experienced during land navigation (44%), team events (20%), and foot marching (11%), running (6%), and the obstacle course (5%), but when the estimated time involved for each event was considered, activities with the highest injury rates were the obstacle course (65 injuries/hr), running (27 injuries/hr), the Combat Readiness Assessment (activity involving combat-related tasks) (20 injuries/hr), and foot marching (16 injuries/hr).ConclusionThe major limitations of this investigation were: 1) the low specificity with regard to many of the diagnoses/complaints; and 2) the fact that the medical problems reported here are only those seen by medical care providers and are likely an underestimate of the total morbidity in the SFAS course. Soldiers often self-treat and some may be reluctant to see medical personnel because of how it might affect their rating in the course. Nonetheless, this investigation alerts medical personnel to the injuries and illnesses to expect, and public health workers and leadership with activities to target for injury prevention measures during SFAS.
Comparative Analysis of Subventricular Zone Glioblastoma Contact and Ventricular Entry During Resection in Predicting Dissemination, Hydrocephalus, and Survival
Authors: Mistry Akshitkumar M , Kelly Patrick D , Gallant Jean-Nicolas , Mummareddy Nishit , Mobley Bret C , Thompson Reid C , Chambless Lola B 
Published: April 2019

Abstract

BACKGROUND
Ventricular entry during glioblastoma resection and tumor contact with the subventricular zone (SVZ) have both been shown to associate with development of hydrocephalus, leptomeningeal dissemination, distant parenchymal recurrence, and decreased survival. However, prior studies did not analyze these variables together in a single-patient population; therefore, it is unknown which is an independent predictor of these outcomes.

OBJECTIVE
To conduct a comparative outcome analysis of surgical ventricular entry and SVZ contact by glioblastoma in a retrospective cohort of 232 patients.

METHODS
Outcomes studied included hydrocephalus, leptomeningeal dissemination, distant tumor recurrences, and progression-free (PFS) and overall (OS) survival. The Cox proportional regression analyses were adjusted for age at diagnosis, preoperative Karnofsky performance status score, extent of resection, temozolomide and radiation treatments, and tumor molecular status (specifically, IDH1/2 mutation and MGMT promoter methylation).

RESULTS
Surgical ventricular entry, SVZ-contacting glioblastoma, hydrocephalus, leptomeningeal dissemination, and distant recurrences were observed in 85 (36.6%), 114 (49.1%), 19 (8.2%), 78 (33.6%), and 59 (25.4%) patients, respectively. Multivariate, adjusted analysis revealed SVZ tumor contact—but not ventricular entry—associated with hydrocephalus (hazard ratio, HR, 4.20 [1.13-15.7], P = .03), leptomeningeal dissemination (HR 1.93 [1.14-3.28], P = .01), PFS (HR 2.10 [1.53-2.88], P < .001), and OS (HR 1.90 [1.35-2.67], P < .001). Distant recurrences were not associated with either. No interaction between the 2 variables was statistically noted.

CONCLUSION
SVZ contact by glioblastoma was independently associated with the development of hydrocephalus, leptomeningeal dissemination, and decreased survival. SVZ tumor contact was associated with ventricular entry during surgical resections, which did not independently correlate with these outcomes.
Machine Learning Algorithm Identifies Patients at High Risk for Early Complications After Intracranial Tumor Surgery: Registry-Based Cohort Study
Authors: van Niftrik Christiaan H B , van der Wouden Frank , Staartjes Victor E , Fierstra Jorn , Stienen Martin N , Akeret Kevin , Sebök Martina , Fedele Tommaso , Sarnthein Johannes , Bozinov Oliver , Krayenbühl Niklaus , Regli Luca , Serra Carlo 
Published: April 2019

Abstract

INTRODUCTION
Reliable preoperative identification of patients at high risk for early postoperative complications occurring within 24 h (EPC) of intracranial tumor surgery can improve patient safety and postoperative management. Statistical analysis using machine learning algorithms may generate models that predict EPC better than conventional statistical methods.

OBJECTIVE
To train such a model and to assess its predictive ability.

METHODS
This cohort study included patients from an ongoing prospective patient registry at a single tertiary care center with an intracranial tumor that underwent elective neurosurgery between June 2015 and May 2017. EPC were categorized based on the Clavien-Dindo classification score. Conventional statistical methods and different machine learning algorithms were used to predict EPC using preoperatively available patient, clinical, and surgery-related variables. The performance of each model was derived from examining classification performance metrics on an out-of-sample test dataset.

RESULTS
EPC occurred in 174 (26%) of 668 patients included in the analysis. Gradient boosting machine learning algorithms provided the model best predicting the probability of an EPC. The model scored an accuracy of 0.70 (confidence interval [CI] 0.59-0.79) with an area under the curve (AUC) of 0.73 and a sensitivity and specificity of 0.80 (CI 0.58-0.91) and 0.67 (CI 0.53-0.77) on the test set. The conventional statistical model showed inferior predictive power (test set: accuracy: 0.59 (CI 0.47-0.71); AUC: 0.64; sensitivity: 0.76 (CI 0.64-0.85); specificity: 0.53 (CI 0.41-0.64)).

CONCLUSION
Using gradient boosting machine learning algorithms, it was possible to create a prediction model superior to conventional statistical methods. While conventional statistical methods favor patients’ characteristics, we found the pathology and surgery-related (histology, anatomical localization, surgical access) variables to be better predictors of EPC.
INFLUENCE OF STATIC ELECTRICITY ON RADON MEASUREMENT USING PASSIVE DETECTORS
Authors: Chen B , Zhao C , Fan D , Zhuo W 
Published: April 2019

Abstract
In order to investigate the influence of the static electricity on the measurement using passive radon detector, detectors were charged at the surface of chamber and its CR-39 elements respectively on purpose before the exposure in this study. The results of in-chamber experiments revealed that the static electricity would lead to critical influence on measurement especially when the CR-39 elements were negatively charged. The static charge would remain for several ten hours, which result in more significant influence on the short-term measurement.
MEASUREMENT OF THE POTENTIAL ALPHA ENERGY CONCENTRATION OF RADON PROGENY BY USING LIQUID SCINTILLATION COUNTING METHOD
Authors: Feng Bin , Tang Quan , Zhang Hui , Chen Bo , Qiu Shoukang , Zhuo Weihai 
Published: April 2019

Abstract
For more accurate measurement of the potential alpha energy concentration (PAEC) of radon progeny by the liquid scintillation counting (LSC) method, its counting efficiency was studied in this work. A radon progeny standard source was used to provide different concentrations of radon progeny, and the progeny collected on the sampling filters were measured with a low background liquid scintillation counter. The result showed that the quenching effect could not be ignored, and the counting efficiency was estimated to be 86.12%. The co-comparison experiments showed that the PAECs of radon progeny measured by the LSC methods were in generally consistent with those of other three methods. It indicates that for more accurate measurements of PAEC of radon progeny by using the LSC method, the counting efficiency should be well determined.
RADIATION DOSE TO MALDIVIANS VIA THE CONSUMPTION OF TUNA FISH CAUGHT FROM THE COASTAL WATERS OF INDIAN OCEAN
Authors: Nadhiya Aishath , Khandaker Mayeen Uddin , Mahmud Sultan , Yarima Mudassir Hassan 
Published: April 2019

Abstract
Recognising the consumption of tuna fish as a major foodstuff in Maldivian diet, the presence of naturally occurring radionuclides in Yellowfin and Skipjack tuna are determined by using HPGe gamma-ray spectrometry to evaluate the health hazards to Maldivians. The samples were collected from different atolls of Maldives adjacent to the coastal waters of Indian Ocean. The activity concentrations (Bq kg−1) in Yellowfin tuna for 226Ra, 232Th and 40K are in the ranges of 4.2 ± 1.8–10.5 ± 1.1, 1.3 ± 0.3–3.2 ± 0.7 and 589 ± 29–697 ± 34, respectively while in Skipjack tuna the respective ranges are 3.9 ± 0.5–13.2 ± 1.1, 1.3 ± 0.3–2.7 ± 0.6 and 511 ± 28–681 ± 35. The committed effective dose (mean 263 μSv y−1) received by an individual due to the dietary intake of Yellowfin tuna falling below the UNSCEAR referenced global internal dose limit of 290 μSv y−1; while for Skipjack tuna, the estimated dose (mean 365 μSv y−1) exceeds the world average limiting value. The carcinogenic risk was found to be well below the ICRP referenced acceptable limit of 2.5 × 10−3. The present study indicates that the radiation dose to Maldivian via the consumption of Yellowfin tuna poses an insignificant threat to the public health. However, prolonged consumption of Skipjack tuna fish from the studied areas may pose a cumulative risk to the public health.
FEASIBILITY STUDY ON THE FUSION OF PHITS SIMULATIONS AND THE DLNN ALGORITHM FOR A NEW QUANTITATIVE METHOD OF IN-SITU MULTIPLE-CHANNEL DEPTH DISTRIBUTION SPECTROMETRY
Authors: Sakama M , Fujimoto K , Inoue K , Fukushi M , Imajyo Y , Fukuhara T , Matsuura M , Yajima T , Endo M , Fujisawa M , Matsumoto-Kawaguchi E 
Published: April 2019

Abstract
We have recently have developed an in-situ multiple-channel depth distribution spectrometer (DDS) that can easily acquire on-site measurements of the depth distribution of specific radioactivities of Cs-134 and Cs-137 underground. Despite considerable improvements in the hardware developed for this device, the quantitative method for determining of radioactivities with this DDS device cannot yet achieve satisfactory performance for practical use. For example, this method cannot discriminate each γ-ray spectra of Cs-134 and Cs-137 acquired by the 20 thallium-doped caesium iodine CsI(Tl) scintillation crystal detectors of the DDS device from corresponding depth levels of underground soil. Therefore, we have applied deep learning neural network (DLNN) as a novel radiation measurement technique to discriminate the spectra and to determine the specific radioactivities of Cs-134 and Cs-137. We have developed model soil layers on a virtual space in Monte-Carlo based PHITS simulations and transported γ-ray radiation generated from a particular single soil layer or multiple layers as radiation sources; next, we performed PHITS calculations of those specific radioactivity measurements for each soil layer using DDS device based on machine learning via the DLNN algorithm. In this study, we obtained informative results regarding the feasibility of the proposal innovative radiation measurement method for further practical use in on-site applications.
SPECIATION OF IODINE IN SOIL SOLUTION IN FOREST AND GRASSLAND SOILS IN ROKKASHO, JAPAN
Authors: Takeda A , Unno Y , Tsukada H , Takaku Y , Hisamatsu S 
Published: April 2019

AbstractThe behaviour of I in soil depends on its chemical form in soil solution. Stable I (127I) in the soil solution under actual soil conditions was investigated as a natural analogue of long-lived radioiodine (129I). Soil samples were collected at 5-cm depth intervals down to 20 cm from forests and grasslands in Rokkasho, where the Japanese first commercial nuclear fuel reprocessing plant is located, and the soil solution was extracted by centrifugation. Almost half of total I in the soil solution was iodide, and the other half was dissolved organic I (DOI), with iodate under the detection limit. The proportion of DOI in total I at 0–5 cm depth was larger than the proportions at 5–20 cm depth. The concentration of DOI was positively correlated with that of DOC in the soil solution, suggesting that the behaviour of DOI in the surface soil is affected by labile organic matter dynamics.
ENVIRONMENTAL TRITIUM AROUND A FUSION TEST FACILITY
Authors: Tanaka Masahiro , Akata Naofumi , Iwata Chie 
Published: April 2019

Abstract
Deuterium plasma operations using a large fusion test device have been carried out since 2017 at the National Institute for Fusion Science. A small amount of tritium was produced by the fusion reaction, d(d, p)t. Then, a part of the tritium was released into the environment. Thus, monitoring the level of tritium in the environment around the fusion test facility is important. This is done before starting the deuterium plasma experiment. The environmental tritium concentrations indicated that they are at background levels in Japan. After starting the deuterium plasma experiment, the environmental tritium around the fusion test facility was within the range of environmental variation. This suggests that there was no impact of tritium on the environment during the first deuterium plasma experimental campaign.
NEW DEVELOPMENT OF RADON PROGENY MEASUREMENT METHOD BASED ON ALPHA–BETA SPECTROMETRY
Authors: Zhang Lei , Wang Yunxiang , Guo Qiuju , Ma Xinhua , Wang Shanqiang 
Published: April 2019

Abstract
Accurate measurement of radon progeny concentration is important for the dose assessment of radon exposure and the study of radon progeny behaviours. For measuring 218Po, 214Pb and 214Bi concentration as well as EEC with high sensitivity, an alpha–beta spectrometry method was developed and applied in a step-advanced filter radon progeny monitor. The derivation details of this method is given in this paper and the uncertainty is discussed. The comparison experiments are carried out in radon chamber and in field. Results show that the alpha–beta spectrometry method can give 218Po, 214Pb and 214Bi concentration as well as EEC with high sensitivity either for 60 min or for 30 min cycle, which leads to low uncertainty. This method can be used as a reference method for radon chamber and is suitable for portable radon progeny monitor.
AN EXPERIMENTAL CHAMBER FOR TESTING ABATEMENT EFFECTS OF RADON EXPOSURE WITH DIFFERENT MEASURES
Authors: Zhuo W , Chen B , He L , Zhang W 
Published: April 2019

Abstract
For more effective testing the abatement effects of radon exposure with different counter measures, an air-conditioned laboratory room was reformed as an experimental chamber. Based on the well control and real time monitoring of concentrations of 222Rn, its attached and unattached progeny and their size distributions, the chamber could provide three modules corresponding to ventilation, source reduction and filtration for abating radon exposure. Preliminary results showed that the chamber was useful for testing the abatement effect of indoor radon exposure.
MEASUREMENT OF URANIUM IN URINE, HAIR AND NAILS IN SUBJECTS OF NISKA BANJA TOWN, A HIGH NATURAL BACKGROUND RADIATION AREA OF SERBIA
Authors: Žunic Z S , Benedik L , Kritsananuwat R , Veselinovic N , Tokonami S , Arae H , Stojanovska Z , Sahoo S K 
Published: April 2019

Abstract
Urine, hair and nail samples were collected from a population of both sex aged from 40 to 87 years in Niška Banja (227 km south of Belgrade, Serbia) with a high level of natural radioactivity (HLNRA). To assess and monitor the public exposure, urine samples for each subject (24 h period) were collected and concentration of uranium (U) was analysed using alpha-particle spectrometry. Human hair and nails considered as bio-indicators of the public exposure to radionuclides over a long period of months or even years and concentration of U was determined using inductively coupled plasma-mass spectrometry. The mean concentrations of U in urine, hair and nail were 123 ng/L, 17 ng/g and 8 ng/g, respectively. There was a large variation and may be due to geological origin.
Functional Brain Networks Underlying Evidence Integration and Delusions in Schizophrenia
Authors: Lavigne Katie M , Menon Mahesh , Woodward Todd S 
Published: April 2019

Abstract
Integrating evidence that contradicts a belief is a fundamental aspect of belief revision and is closely linked to delusions in schizophrenia. In a previous functional magnetic resonance imaging (fMRI) study on healthy individuals, we identified functional brain networks underlying evidence integration as visual attention network (VsAN; dorsal anterior cingulate cortex, insula, occipital regions), default-mode network (DMN), and cognitive evaluation network (CEN; orbitofrontal cortex, inferior frontal gyrus, parietal cortex). In the current clinical fMRI study, we compared network-based activity during evidence integration between healthy controls (n = 41), nondelusional (n = 37), and delusional (n = 33) patients with schizophrenia, and related this activity to cognitive processing involved in evidence integration measured outside the scanner. Task-induced coordinated activation was measured using group-constrained principal component analysis for fMRI. Increased VsAN activation, reduced DMN deactivation, and reduced CEN activation were observed for schizophrenia, with this pattern being most pronounced for the delusional group. Importantly, poor evidence integration comprehensively measured outside the scanner was significantly associated with increased VsAN activation and reduced DMN deactivation when processing confirmatory evidence, and with reduced CEN activation when processing disconfirmatory evidence. This is the first comprehensive study of the functional brain networks associated with evidence integration in schizophrenia and highlights how an imbalance of functional brain networks responding to confirmatory and disconfirmatory evidence may underlie delusions in schizophrenia.