bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using deep learning to model the biological dose prediction on bulky lung cancer patients of partial stereotactic ablation radiotherapy
Authors: Li Yue , He Kanghui , Ma Mingwei , Qi Xin , Bai Yun , Liu Siwei , Gao Yan , Lyu Feng , Jia Chenghao , Zhao Bo , Gao Xianshu 
Published: October 2020

PurposeTo develop a biological dose prediction model considering tissue bio‐reactions in addition to patient anatomy for achieving a more comprehensive evaluation of tumor control and promoting the automatic planning of bulky lung cancer.MethodsA database containing images and partial stereotactic ablation boost radiotherapy (P‐SABR) plans of 94 bulky lung cancer patients was studied. Patient‐specific parameters of gross tumor boost volume (GTVb), planning gross target volume (PGTV), and identified organs at risk (OARs) were extracted via Numpy and simple ITK. The original dose and structure maps for P‐SABR patients were resampled to have a voxel resolution of 3.9 × 3.9 × 3 mm3. Biological equivalent dose (BED) distributions were reprogrammed based on physical dose volumes. A developed deep learning architecture, Nestnet, was adopted as the training framework. We utilized two approaches for data organization to correlate the structures and BED: (a) BED programming before training model (B‐Nestnet); (b) BED programming after the training process (D‐B Nestnet). The early‐stop mechanism was adopted on the validation set to avoid overfitting. The evaluation criteria of predictive accuracy contain the minimum BED of GTVb and PGTV, the maximum and the mean BED of all targets, BED‐volume metrics. For comparison, we also used the original Unet for BED prediction. The absolute differences were statistically analyzed with the paired‐samples t test.ResultsThe statistical outcomes demonstrate that D‐B Nestnet model predicts biological dose distributions accurately. The average absolute biases of [max, mean] BED for GTVb, PGTV are [2.1%, 3.3%] and [2.1%, 4.7%], respectively. Averaging across most of OARs, the D‐B Nestnet model is capable of predicting the errors of the max and mean BED within 6.3% and 6.1%, respectively. While the compared models performed worse with averaged max and mean BED prediction errors surpassing 10% on some specific OARs.ConclusionsThe study developed a D‐B Nestnet model capable of predicting BED distribution accurately for bulky lung cancer patients in P‐SABR. The predicted BED map enables a quick intuitive evaluation of tumor ablation, modification of the ablation range to improve BED of tumor targets, and quality assessment. It represents a major step forward toward automated P‐SABR planning on bulky lung cancer in real clinical practice.
Potential of contrast agents based on high‐Z elements for contrast‐enhanced photon‐counting computed tomography
Authors: Amato Carlo , Klein Laura , Wehrse Eckhard , Rotkopf Lukas T. , Sawall Stefan , Maier Joscha , Ziener Christian H. , Schlemmer Heinz‐Peter , Kachelrieß Marc 
Published: October 2020

PurposeIn clinics, only iodine‐ and barium‐based contrast agents are currently used for contrast‐enhanced x‐ray computed tomography (CT). Recently, the introduction of new photon‐counting (PC) detectors increased the interest in developing new contrast agents based on heavier elements. These elements may provide more contrast and spectral information compared to iodine and barium thanks to their k‐edges at higher energies. In this paper, the potential of high‐Z elements in contrast‐enhanced CT was evaluated for different patient sizes and x‐ray spectra using a PC detector.MethodsAn adult liver phantom with five high‐Z element solutions (iodine, gadolinium, ytterbium, tungsten, and bismuth) was scanned with a whole‐body photon‐counting computed tomography (PCCT) prototype. For each element, the contrast‐to‐noise ratio at unit concentration and at unit dose (CNRCD) was evaluated in low threshold images () as function of the tube voltage (80, 100, 120, and 140 kV) and in bin images (tube voltage = 120 kV) as function of the higher threshold ( and ). Simulations were performed for validation with measurements and to investigate more elements (cerium and gold), different patient sizes (infant, adult, and obese), and spectrum filtration (with and without 0.4‐mm tin filter). The dose reductions associated with the CNRCD improvements over iodine were quantified as well.ResultsCNRCD improvements and dose reductions depend on the investigated scenario. For the infant phantom, dose reductions around 30% were reached using cerium or gadolinium in combination with the tin filter. For the adult and obese phantom, reductions around 50% were provided by gadolinium or ytterbium in combination with the tin filter. Independently of the high‐Z element, the CNRCD of two optimally combined bin images was higher than the CNRCD of the low threshold image. Good agreement was found between measurements and simulations.ConclusionsBetween the investigated elements, gadolinium resulted to have the highest potential as novel contrast agent in PCCT, providing significant dose reductions for all patient sizes. Compared to the other elements, the implementation of gadolinium as CT contrast agent may be facilitated since it is already deployed as contrast agents for magnetic resonance imaging.
The Influence of Aggregate Sociodemographic Characteristics on Fishing License Sales in Cook County, Illinois
Authors: Zhang Xiaohan , Landon Adam C. , Miller Craig A. 
Published: October 2020

Abstract
Anglers have been among the major supporters of aquatic conservation activities in the USA through the Dingell–Johnson Act and other programs. Declining rates of participation in fishing have spurred significant efforts to recruit, retain, and reengage anglers, also known as “R3.” To make R3 strategies more effective, it is important to explore the broader sociodemographic patterns that underpin angling participation. Urban areas are variable with respect to residents’ socioeconomic status (SES), and scholars have observed lower rates of angling participation among urban residents. This heterogeneity highlights the need to understand angling participation among urban residents. Therefore, the objective of this study was to explore the influence of aggregate sociodemographic characteristics on fishing license sales in Cook County, Illinois, the main urban center of the state. We assessed the spatial association of sociodemographic characteristics and fishing license purchase and determined the relative influence of three components (SES, household mobility, and age) from principal components analysis on fishing license purchases. We used the bivariate LISA (local indicators of spatial association) method and regression models to test for differences in demographic effect. Results revealed statistically significant spatial dependence in patterns of license sales density and aggregate SES, household mobility, and age. Aggregate SES had a negative relationship with license sales density. Conversely, aggregate household mobility and age positively influenced the density of license sales. Interactions of the three components were also investigated. Census tracts with lower mobility tended to fish more with higher SES. Census tracts with a younger population tended to fish more with higher SES. Census tracts with higher SES tended to fish less with increasing age. Our findings provide assistance in developing R3 strategies aimed at increasing participation in recreational angling by showing how demographic factors influencing license sales can be examined using census data.
A cross‐sectional survey to explore the prevalence and causes of occupational burnout syndrome among perioperative nurses in Saudi Arabia
Authors: Almodibeg Bader Ali , Smith Hazel 
Published: October 2020

AbstractAimTo detect the level of burnout and its most significant causes among perioperative nurses.DesignA descriptive quantitative cross‐sectional survey design.MethodsData on burnout and its most significant causes were collected by surveying 39 perioperative nurses in a regional hospital in Saudi Arabia using the Maslach Burnout Inventory and a self‐developed questionnaire. Descriptive statistics were used to perform statistical analysis.ResultsBurnout was detected in 5% of respondents. A high level of emotional exhaustion was detected in 87.2%. Similarly, a high level of depersonalization was detected in 56.4%, while 15.4% of nurses showed a low sense of personal accomplishment. Several factors were identified as the causes of burnout such as high workload, staff shortage, poor teamwork, insufficient salary and occupational hazards. However, lack of departmental support and undesirable supervision in the workplace seem to be the main causes of burnout.
Nurse‐led group information for patients with breast cancer: Equal to individual information? A comparative study
Authors: Dieperink Karin Brochstedt , Ellegaard Elisabeth , Astrup Anja Langkjær , Hasse Henriette Tind , Elnegaard Caroline Matilde , Jensen Jeanette Dupont 
Published: October 2020

AbstractAimTo investigate outpatients with breast cancer perception of information before and after changed informational practice.DesignThe design was a comparative study.MethodInformation about breast cancer treatment and chemotherapy toxicity changed from individual to nurse‐led group information. Women with early‐stage breast cancer were eligible. To evaluate individual versus group information, the patients completed a questionnaire at their third cycle of chemotherapy, including Knowledge of treatment, Support from healthcare professionals or peers and general self‐efficacy Ability to act in everyday life. The study is registered in OSF https://osf.io/bh7wg.ResultsIn total, 90 participants in two groups were included: (a) individual information (N = 44) and (b) group information (N = 46). Groups were comparable in age and educational level. Both groups found the information satisfactory, with no significant differences regarding perceived knowledge or support. Five of ten questions in self‐efficacy showed significantly better outcomes in patients receiving group information but with no difference in overall self‐efficacy. Group information was non‐inferior compared with individual information. Patients were satisfied in both groups.
Cost‐Effectiveness of a Novel Sleep Intervention in Infancy to Prevent Overweight in Childhood
Authors: Tan Eng Joo , Taylor Rachael W. , Taylor Barry J. , Brown Vicki , Hayes Alison J. 
Published: October 2020

ObjectiveThe purpose of this study was to determine, from a health funder perspective, whether a sleep intervention, delivered in infancy, either alone or in combination with food, activity, and breastfeeding advice was cost‐effective compared with usual care.MethodsA cost‐effectiveness analysis was conducted alongside the Prevention of Overweight in Infancy (POI) randomized controlled trial for outcomes at 5 years and cost‐effectiveness was modeled to age 15 years using the Early Prevention of Obesity in Childhood microsimulation model. Intervention costs for the Sleep (n = 192), Combination (n = 196), and control (n = 209) groups were determined in 2018 Australian dollars. Incremental cost‐effectiveness ratios (ICERs) were determined for BMI outcomes at 5 and 15 years, with the primary outcome being quality‐adjusted life years (QALYs) modeled over 15 years.ResultsThe average costs of the Sleep and Combination interventions were $184 and $601 per child, respectively. The ICER for the Sleep intervention was $18,125 per QALY gained, with a 74% probability of being cost‐effective at a willingness‐to‐pay threshold of $50,000 per QALY. The ICER for the Combination intervention was $94,667 per QALY gained with a 23% probability of being cost‐effective.ConclusionsThe POI Sleep intervention, without additional advice, was a low‐cost and cost‐effective approach to reducing childhood obesity. Sleep modification programs offer a very promising approach to obesity prevention in children.
The effect of dispersion condition on the structure and properties of polystyrene/graphene oxide nanocomposites
Authors: Mohammadsalih Zaid G. , Inkson Beverley J. , Chen Biqiong 
Published: October 2020

AbstractThe realization of an optimum strategy for dispersing graphene nano‐sheets in a thermoplastic matrix is important for obtaining a successful preparation and, consequently, a better enhancement of different properties for the resultant polymer/graphene nanocomposites. In this study, nanocomposites of polystyrene (PS) and graphene oxide (GO) were prepared using solution blending method with tetrahydrofuran as the solvent. Magnetic stirring, water bath sonication, and shear mixing were utilized to disperse GO nano‐sheets in PS. Different periods of mixing for the last two techniques were examined to study their effect on the structure and properties on the PS/GO nanocomposites. For the first sample, water bath sonication and shear mixing were used for 30 and 60 minutes, respectively. For the second sample, both mixing periods were doubled. The results obtained by employing different characterization techniques showed a good dispersion of nano‐sheets in the matrix and enhanced thermal and thermomechanical properties for both samples, with a superiority for the first sample in terms of storage modulus to prevent the nano‐sheets from damage due to the application of sonication and mixing for a shorter period of time.
Flame retardancy and thermal stability of agricultural residue fiber‐reinforced polylactic acid: A Review
Authors: Yiga Vianney Andrew , Lubwama Michael , Pagel Sinja , Benz Johannes , Olupot Peter Wilberforce , Bonten Christian 
Published: October 2020

AbstractBiocomposites containing natural fibers and biopolymers are an ideal choice for developing substantially biodegradable materials for different applications. Polylactic acid is a biopolymer produced from renewable resources and has drawn numerous interest in packaging, electrical, and automotive application in recent years. However, its potential application in both electrical and automotive industries is limited by its flame retardancy and thermal properties. One way to offset this challenge has been to incorporate natural or synthetic flame retardants in polylactic acid (PLA). The aim of this article is to review the trends in research and development of composites based on agricultural fibers and PLA biopolymers over the past decade. This article highlights recent advances in the fields of flame retardancy and thermal stability of agricultural fiber‐reinforced PLA. Typical fiber‐reinforced PLA processing techniques are mentioned. Over 75% of the studies reported that incorporation of agricultural fibers resulted in enhanced flame retardancy and thermal stability of fiber‐reinforced PLA. These properties are further enhanced with surface modifications on the agricultural fibers prior to use as reinforcement in fiber‐reinforced PLA. From this review it is clear that flame retardancy and thermal stability depends on the type and pretreatment method of the agricultural fibers used in developing fiber‐reinforced PLA. Further research and development is encouraged on the enhancement of the flame retardancy properties of agricultural fiber‐reinforced PLA, especially using agricultural fibers themselves as flame retardants as opposed to synthetic flame retardants that are typically used.
Synthesis of polymeric composites reinforced with short bamboo fibers supported by experiment design
Authors: Cruz‐Riaño Luis Javier , Quintero‐Giraldo Leidy Johana , García‐Guzmán Jaime Alexis , Alcaraz‐Zapata Alejandro , González‐Castrillón Eugenia del Socorro , Osorio‐Saraz Jairo Alexander 
Published: October 2020

AbstractIn this study, short bamboo fibers were obtained using diverse extraction methods. Results obtained by the preliminary fiber traction tests reveal that the fibers obtained using steam explosion equipment possess better mechanical properties than those obtained using other methods. These fibers were used to reinforce a polymeric composite material manufactured using hot compression technique. For this purpose, a 3k factorial experiment design was applied using fiber and coupling agent concentrations as controllable factor and elasticity modulus as response variable to determine their most appropriate level for developing the best natural composite. From this viewpoint, it was found that the best composite material was obtained by combining 50% w/w fiber and 4% w/w coupling agent, as per the corresponding statistical analysis of variance (ANOVA). For the response variable, the elasticity modulus of the compound increased by 322% (2.91 GPa) in comparison with that of the polymer matrix (0.69 GPa).
A monoclonal antibody‐based indirect competitive enzyme‐linked immunosorbent assay to quantify swertiamarin and related compounds in Swertia japonica Makino
Authors: Nuntawong Poomraphie , Horikawa Taiki , Ochi Akihiro , Wada Shinji , Tsuneura Yumi , Tanaka Hiroyuki , Sakamoto Seiichi , Morimoto Satoshi 
Published: October 2020

AbstractIntroductionSwertia japonica Makino (S. japonica) has a long history of use as a folk medicine, and it is one of the three essential Japanese folk medicines. S.japonica has been reported to have various biological activities. The biologically active secoiridoid glycoside swertiamarin (SM) has been isolated from S. japonica. The efficacy of this plant is attributed to SM and related secoiridoid glycosides. To control the quality of S. japonica for medicinal use, a method for the determination of SM and other secoiridoid glycosides in the plant is needed.ObjectiveTo produce an anti‐SM monoclonal antibody (MAb) and develop an indirect competitive enzyme‐linked immunosorbent assay (icELISA) for S. japonica standardisation and quality control.MethodologySM was conjugated to cationised bovine serum albumin (cBSA), and the SM–cBSA conjugate was used to immunise BALB/c mice. Splenocytes from the immunised mice were then fused with SP2/0 myeloma cells to produce hybridoma cells that expressed anti‐SM MAb.ResultsThe developed icELISA was sufficiently sensitive and had a quantitative range of 0.78 to 12.5 μg/mL. Coefficients of variation below 10% indicated good repeatability. Recoveries in a spike and recovery assay ranged from 91.84% to 115.50%, which confirmed that the icELISA was accurate. The SM content measured using the icELISA was in agreement with the results of a high‐performance liquid chromatography‐ultraviolet (HPLC‐UV) assay.ConclusionThe icELISA is suitable for the high‐throughput analysis of SM and other secoiridoid glycosides in S. japonica. The method is fast, economical, and reliable for S. japonica quality control.
Phosphodiesterase type 5 inhibitor use among pregnant and reproductive‐age women in the United States
Authors: Liu Wei , Menzin Talia J. , Woods Corinne M. , Haug Nicole R. , Li Jie , Mathew Justin A. , Nguyen Christine P. , Chai Grace P. , Moeny David G. , Shinde Mayura 
Published: October 2020

AbstractPurposeTo assess the prevalence and potential indications of PDE5 inhibitor use among pregnant and reproductive‐age women in the United States.MethodsWe identified women 15 to 50 years with a livebirth from January 2001 through March 2018 in Sentinel Database. We assessed the prevalence of PDE5 inhibitor use prior to and during pregnancy by trimester, identified potential on‐ and off‐label indications using predefined diagnosis codes recorded within 90 days before the estimated last menstrual period through delivery. Separately, we used data from IQVIA's National Prescription Audit and Total Patient Tracker to estimate the dispensed prescriptions for PDE5 inhibitors and the number of patients with PDE5 inhibitor prescriptions.ResultsWe identified approximately 3.3 million pregnancies during 2001 to 2018, 96 of which had PDE5 inhibitor use during pregnancy. Prevalence of PDE5 inhibitor use was 2.61, 0.62, and 0.62 per 100, 000 live‐born pregnancies during the first, second, or third trimesters, respectively. Among women exposed to a PDE5 inhibitor from 90 days before conception to the end of pregnancy, 25.0%, 31.1%, and 15.5% had a diagnosis code for fetal growth restriction, preeclampsia, and pulmonary arterial hypertension. In IQVIA data, an estimated 223, 000 prescriptions from July 2015 through June 2018 and 58, 000 women received prescriptions for PDE5 inhibitors in 2017, of whom approximately 15, 000 (26%) were aged 15 to 50 years.ConclusionWe found a low prevalence of PDE5 inhibitor use in pregnant and reproductive‐age women. Given the very low prevalence of use and the inconsistency of neonatal mortality data across STRIDER centers, the risk to public health is low at present.
Development and validation of coding algorithms to identify patients with incident lung cancer in United States healthcare claims data
Authors: Beyrer Julie , Nelson David R. , Sheffield Kristin M. , Huang Yu‐Jing , Ellington Tim , Hincapie Ana L. 
Published: October 2020

AbstractPurposeOur aim was to develop and validate a practical US healthcare claims algorithm for identifying incident lung cancer that improves on positive predictive value (PPV) and sensitivity observed in past studies.MethodsPatients newly diagnosed with lung cancer in Surveillance, Epidemiology, and End Results (SEER) (gold standard) were linked with Medicare claims. A 5% Medicare “other cancer” sample and noncancer sample served as controls. A split‐sample validation approach was used. Rules‐based, regression, and machine learning models for developing algorithms were explored. Algorithms were developed in the model building subset. Rules‐based algorithms and those with the highestFscores were evaluated in the validation subset.Fscores were compared for 1000 bootstrap samples. Misclassification was evaluated by calculating the odds of selection by the algorithm among true positives and true negatives.ResultsA practical single‐score algorithm derived from a logistic regression model had sensitivity = 78.22% and PPV = 78.50% (Fscore: 78.36). The algorithm was most likely to misclassify older patients (ages ≥80 years) or with missing data in the SEER registry, shorter follow‐up time in Medicare (<3 months), insurance through Veterans Affairs, >1 cancer in SEER, or certain Charlson comorbidities (dementia, chronic pulmonary disease, liver disease, or myocardial infarction).ConclusionIn this dataset, a practical point‐based algorithm for identifying incident lung cancer demonstrated significant and substantial improvement (7.9% and 23.9% absolute improvement in sensitivity and PPV, respectively) compared with a current standard.
Efficient Fine Balancing in Two Planes with Laser Ablation
Authors: Hummelt Guenter 
Published: October 2020

AbstractThe need for precision balancing of high‐speed rotors is continually increasing. This can be attributed to several factors: imbalances generate vibrations, which are a source of noise; the applications must operate quietly; imbalances create additional load on the impeller bearings and therefore shorten their lifetime.