bluuebunny/crossref_metadata_2025_split huggingface dataset:
Viral infection can reduce the net nitrogen inputs of legume break crops and cover crops
Authors: Marchetto Katherine M. , Power Alison G. 
Published: October 2020

AbstractLegumes are used in crop rotations by both large‐scale and smallholder farmers alike to increase soil fertility, especially before high‐nitrogen‐demanding crops such as corn (maize). Legume crop residues and green manures are rich in nitrogen due to mutualistic rhizobia, bacteria that live in their roots and convert atmospheric nitrogen into a biologically available form. Growers can obtain recommendations from local extension offices about how much less inorganic nitrogen fertilizer needs to be added to a subsequent crop following different legume break crops for the predominant soil type (the nitrogen fertilizer replacement value, or NFRV). Due to the intimate relationship between legumes and rhizobia, conditions that affect plant health can also affect the rhizobia and how much nitrogen they provide. We use a combination of empirical data and previously published values to estimate reductions in nitrogen inputs under outbreaks of plant viruses of varying severity. We also use historical fertilizer prices to examine the economic impacts of this lost fertilizer for farmers. We find that fertilizer losses are greatest for crops that fix large amounts of nitrogen, such as clover and alfalfa as opposed to common bean. The economic impact on farmers is controlled by the proportion of plants with viral infections and the price of synthetic fertilizer. In a year of high disease prevalence, attention is normally focused on the yield of the diseased crops. We suggest that farmers growing legumes as break crops should be concerned about yields of subsequent crops as well. Viral diseases can be difficult to diagnose in the field, so the easiest way for farmers to prevent unexpected yield losses in subsequent crops is to test their soil when it is feasible to do so.
People who overvalue appearance selectively attend to descriptors of the attractiveness ideal: Findings from an emotional Stroop task
Authors: Tabri Nassim , Palmer Lucas 
Published: October 2020

AbstractObjectiveAttentional biases to stimuli related to stigmatized appearance are theorized to stem from appearance overvaluation, but little research has examined this link. As well, little research has examined whether appearance overvaluation is associated with biases toward stimuli that describe the attractiveness ideal. We addressed these gaps in the literature using the emotional Stroop task and tested whether appearance overvaluation is associated with an attentional bias for words that describe stigmatized appearance (e.g., fat, ugly, shabby), the attractiveness ideal (e.g., thin, beautiful, fashionable), or both.Method and ResultsIn Study 1, a community sample of people (N = 86) completed measures of appearance overvaluation, body dissatisfaction, and body mass index (BMI) followed by an emotional Stroop task. Appearance overvaluation was associated with an attentional bias for attractiveness ideal words—not stigmatized appearance words. Results remained significant when controlling for participants' body dissatisfaction, BMI, and gender. Study 2 (N = 316) replicated these findings. Finally, an integrative data analysis that pooled the data of Studies 1 and 2 (N = 402) provided additional support for our general hypothesis that people who overvalue appearance display an attentional bias to stimuli related to the attractiveness ideal.DiscussionThe results show a robust association between appearance overvaluation and selective attention for attractiveness ideal stimuli. Results are discussed in reference to theory and research on information processing in eating disorders. We also call for research to examine information processing of stimuli related to the attractiveness ideal among people with eating disorders and who place high importance on appearance for self‐definition.
Physics‐based probabilistic seismic hazard and loss assessment in large urban areas: A simplified application to Istanbul
Authors: Stupazzini Marco , Infantino Maria , Allmann Alexander , Paolucci Roberto 
Published: October 2020

AbstractA set of 3D physics‐based numerical simulations (PBS) of possible earthquakes scenarios in Istanbul along the North Anatolian Fault (Turkey) is considered in this article to provide a comprehensive example of application of PBS to probabilistic seismic hazard (PSHA) and loss assessment in a large urban area. To cope with the high‐frequency (HF) limitations of PBS, numerical results are first postprocessed by a recently introduced technique based on Artificial Neural Networks (ANN), providing broadband waveforms with a proper correlation of HF and low‐frequency (LF) portions of ground motion as well as a proper spatial correlation of peak values also at HF, that is a key feature for the seismic risk application at urban scale. Second, before application to PSHA, a statistical analysis of residuals is carried out to ensure that simulated results provide a set of realizations with a realistic within‐ and between‐event variability of ground motion. PBS results are then applied in a PSHA framework, adopting both the “generalized attenuation function” (GAF) approach, and a novel “footprint” (FP)‐based approach aiming at a convenient and direct application of PBS into PSHA. PSHA results from both approaches are then compared with those obtained from a more standard application of PSHA with empirical ground motion models. Finally, the probabilistic loss assessment of an extended simplified portfolio of buildings is investigated, comparing the results obtained adopting the different approaches: (i) GMPE, (ii) GAF, and (iii) FP. Only FP turned out to have the capability to account for the specific features of source and propagation path, while preserving the proper physically based spatial correlation characteristics, as required for a reliable loss estimate on a building portfolio spatially distributed over a large urban area.
Dynamic deformation and fracture characteristics of a deep roadway surrounding rock based on the machine vision monitoring method
Authors: Zhou Rui , Xu Jiankun , Wang Chao , Li Xuelong 
Published: October 2020

AbstractThe deformation and fracture of surrounding rock in deep underground engineering have the characteristics of time mutation and space continuity. In order to monitor and provide early warning of the dynamic deformation and fracture characteristics of deep surrounding rock, a real‐time digital displacement measuring instrument was developed in this paper. The proposed device represented a kind of surrounding rock deformation and fracture monitoring method, which had the continuous and real‐time advantages. Based upon the simulation experiments, the dynamic deformation and fracture of deep roadway surrounding rock were measured synchronously using the digital displacement measuring instrument testing system (DDMITS) and the V‐STARS measurement system. Comparative measurement results indicated that the DDMITS had a higher reliability. The deformation of roadway surrounding rock gradually increased with the increase of loading. The roof deformation and caving changing patterns in coal seam mining were studied using similar simulation experiments based on the DDMITS. The vertical displacement response of rock strata was more obvious than the horizontal displacement. There was a sharp increase in the vertical displacement during the collapse of the rock strata. Additionally, the vertical displacement velocity showed fluctuations. Meanwhile, the fluctuations in the vertical displacement acceleration increased significantly. The DDMITS could achieve full‐field measurement and the noncontact measurement of three‐dimensional deformation.
(τ, m)‐slicedBucket privacy model for sequential anonymization for improving privacy and utility
Authors: Khan Razaullah , Tao Xiaofeng , Anjum Adeel , Malik Saifur Rehman , Yu Shui , Khan Abid , Rehman Waheedur , Malik Hassan 
Published: October 2020

AbstractIn a real‐world scenario for privacy‐preserving data publishing, the original data are anonymized and released periodically. Each release may vary in number of records due to insert, update, and delete operations. An intruder can combine, that is, correlate different releases to compromise the privacy of the individual records. Most of the literature, such as τ‐safety, τ‐safe (l, k)‐diversity, have an inconsistency in record signatures and adds counterfeit tuples with high generalization that causes privacy breach and information loss. In this paper, we propose an improved privacy model (τ, m)‐slicedBucket, having a novel idea of “Cache” table to address these limitations. We indicate that a collusion attack can be performed for breaching the privacy of τ‐safe (l, k)‐diversity privacy model, and demonstrate it through formal modeling. The objective of the proposed (τ, m)‐slicedBucket privacy model is to set a tradeoff between strong privacy and enhanced utility. Furthermore, we formally model and analyze the proposed model to show that the collusion attack is no longer applicable. Extensive experiments reveal that the proposed approach outperforms the existing models.
Effects of upholstery materials on the burning behavior of real‐scale residential upholstered furniture mock‐ups
Authors: Pitts William M. , Werrel Martin , Fernandez Marco , Long Mary A. , Eisenberg Evan A. , Filliben James , Runyon Cory D. 
Published: October 2020

SummaryFire spread and growth on real‐scale four cushion mock‐ups of residential upholstered furniture (RUF) were investigated with the goal of identifying whether changes in five classes of materials (barrier, flexible polyurethane foam, polyester fiber wrap, upholstery fabric, and sewing thread), referred to as factors, resulted in statistically significant changes in burning behavior. A fractional factorial experimental design plus practical considerations yielded a test matrix with 20 material combinations. Experiments were repeated a minimum of two times. Measurements included fire spread rates derived from video recordings and heat release rates (HRRs). A total of 13 experimental parameters (3 based on the videos and 10 on the HRR results), referred to as responses, characterized the measurements. Statistical analyses based on Main Effects Plots (main effects) and Block Plots (main effects and factor interactions) were used. The results showed that three of the factors resulted in statistically significant effects on varying numbers of the 13 responses. The Barrier and Fabric factors had the strongest main effects with roughly comparable magnitudes. Foam was statistically significant for fewer of the responses and its overall strength was weaker than for Barrier and Fabric. No statistically significant main effects were identified for Wrap or Thread. Multiple two‐term interactions between factors were identified as being statistically significant. The Barrier*Fabric interaction resulted in the highest number of and strongest statistically significant effects. The existence of two‐term interactions means that it will be necessary to consider their effects in approaches designed to predict the burning behavior of RUF.
Techniques for essential oil extraction from kaffir lime and its application in health care products—A review
Authors: Suresh Anuja , Velusamy Sangeetha , Ayyasamy Sudha , Rathinasamy Menaha 
Published: October 2020

AbstractKaffir lime (Citrus hystrix DC) is a tropical plant with aromatic leaves. It produces fruits that are used in Asian cuisines as a flavoring agent. Essential oil from the leaves and peel of kaffir lime is a complex mixture of volatile and semi‐volatile compounds. It is rich in bioactive molecules that act synergistically to improve the well‐being of an individual. The method of extraction is important as it affects the quality and quantity of essential oil significantly. Kaffir lime oil is used as raw material in many fields, some of which include pharmaceutical, agronomic, food, sanitary, cosmetic, and perfume industries. It is also used extensively in aromatherapy and as an essential ingredient of various cosmetic and beauty products. Hydrodistillation, steam distillation, pressurized liquid extraction, and soxhlet extraction are some of the commonly used methods for extracting essential oil from kaffir lime as they are cost‐effective, environment friendly, and easy to implement on commercial scale. This review discusses about the condition's of extraction, merits, and demerits of various extraction methods used for kaffir lime oil and their application in healthcare products to induce positive effect in humans.
Repeatability and reproducibility of human brain morphometry using three‐dimensional magnetic resonance fingerprinting
Authors: Fujita Shohei , Buonincontri Guido , Cencini Matteo , Fukunaga Issei , Takei Naoyuki , Schulte Rolf F. , Hagiwara Akifumi , Uchida Wataru , Hori Masaaki , Kamagata Koji , Abe Osamu , Aoki Shigeki 
Published: October 2020

AbstractThree‐dimensional (3D) Magnetic resonance fingerprinting (MRF) permits whole‐brain volumetric quantification of T1 and T2 relaxation values, potentially replacing conventional T1‐weighted structural imaging for common brain imaging analysis. The aim of this study was to evaluate the repeatability and reproducibility of 3D MRF in evaluating brain cortical thickness and subcortical volumetric analysis in healthy volunteers using conventional 3D T1‐weighted images as a reference standard. Scan‐rescan tests of both 3D MRF and conventional 3D fast spoiled gradient recalled echo (FSPGR) were performed. For each sequence, the regional cortical thickness and volume of the subcortical structures were measured using standard automatic brain segmentation software. Repeatability and reproducibility were assessed using the within‐subject coefficient of variation (wCV), intraclass correlation coefficient (ICC), and mean percent difference and ICC, respectively. The wCV and ICC of cortical thickness were similar across all regions with both 3D MRF and FSPGR. The percent relative difference in cortical thickness between 3D MRF and FSPGR across all regions was 8.0 ± 3.2%. The wCV and ICC of the volume of subcortical structures across all structures were similar between 3D MRF and FSPGR. The percent relative difference in the volume of subcortical structures between 3D MRF and FSPGR across all structures was 7.1 ± 3.6%. 3D MRF measurements of human brain cortical thickness and subcortical volumes are highly repeatable, and consistent with measurements taken on conventional 3D T1‐weighted images. A slight, consistent bias was evident between the two, and thus careful attention is required when combining data from MRF and conventional acquisitions.
Safety of fibula free flap in patients following total knee replacement
Authors: Harris Brianna N. , Ghazizadeh Shabnam , Bayon Rodrigo , Kejner Alexandra E. , Cannady Steven B. , Greene Benjamin J. , Huang Andrew T. , Curry Joseph , Blackwell Keith E. , Ducic Yadranko , Wax Mark K. 
Published: October 2020

AbstractBackgroundFibula free flap (FFF) is the preferred osteocutaneous flap for reconstruction of large head and neck composite defects. There is a paucity of data whether FFF can be performed safely in patients with knee replacement (total knee arthroplasty [TKA]).MethodsMulti‐institutional review of outcomes following FFF in patients who had prior TKA.ResultsTen surgeons reported successful FFF in 53 patients with prior TKA. The most common preoperative imaging was a CT angiogram of the bilateral lower extremities. There was no evidence of intraoperative vascular abnormality. Physical therapy began between postoperative day 1 to postoperative day 3. At 1 month postoperatively, 40% of patients were using a cane or walker to ambulate, but by 3 months all had returned to baseline ambulatory status. At >1 year, there were no gait complications.ConclusionFFF appears safe in patients with prior knee replacement without an increased risk of complications compared to baseline.
Cover Image
Authors: Parra Maribel , Baptista Maria Joao , Genescà Eulàlia , Llinàs‐Arias Pere , Esteller Manel 
Published: October 2020

AbstractThe cover image is based on the Invited Review Genetics and Epigenetics of Leukemia and Lymphoma: From Knowledge to Applications, Meeting Report of the Josep Carreras Leukaemia Research Institute by Maribel Parra et al., https://doi.org/10.1002/hon.2725.
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Identification of a methylation panel aid in risk stratification in node‐positive penile squamous cell carcinoma
Authors: Gu Weijie , Wan Fangning , Chen Jun , Gan Hualei , Wang Beihe , Wei Yu , Zhang Guiming , Zhou Jiaquan , Ding Xuefei , Zhang Peipei , Jin Shengming , Xu Qinghua , Ye Dingwei , Zhu Yao 
Published: October 2020

AbstractMolecular prognostic factors for individualized treatment of squamous cell carcinoma (SCC) are poorly defined. Our study developed and validated a novel molecular tools aid in preinguinal and postinguinal lymphadenectomy risk stratification in node‐positive penile SCC. Patients with node‐positive penile SCC who underwent inguinal or ilioinguinal lymphadenectomy were divided into three cohorts: a discovery set, a development set and a validation set. The local ethics committee approved the study. The primary endpoint was cancer‐specific survival (CSS). At the discovery stage, 17 CpG sites were significantly associated with CSS. In the development set, we constructed a 3‐CpG‐based prognostic score for survival prediction. The hazard ratio (HR) of the panel (dichotomized using the optimal cutoff) was 5.8 in the multivariate analyses (P < .001). The addition of the methylation score significantly improved the pN‐stage C‐index from 0.70 to 0.79 (incremental C = 0.09, P < .001). In the validation set, the methylation panel showed a HR of 9.9 in the multivariate analyses. The addition of the molecular marker improved the pN‐stage C‐index from 0.69 to 0.78 (incremental C = 0.09, P < .001). The methylation score remarkably separated survival curves in different pN stages, which indicate that the tool can be applied to tailor the treatment in both preinguinal and postinguinal lymphadenectomy settings. We developed and validated a prognostic methylation panel for node‐positive penile SCC. The tool may aid in the risk stratification of the population with heterogeneous outcomes and needs prospective validation. Patients in high‐risk group may benefit from more aggressive therapy or clinical trials.
Deep chest X‐ray: Detection and classification of lesions based on deep convolutional neural networks
Authors: Cho Yongwon , Lee Sang Min , Cho Young‐Hoon , Lee June‐Goo , Park Beomhee , Lee Gaeun , Kim Namkug , Seo Joon Beom 
Published: October 2020

AbstractWe investigated whether a convolutional neural network (CNN) can enhance the usability of computer‐aided detection (CAD) of chest radiographs for various pulmonary abnormal lesions. The numbers of normal and abnormal patients were 6055 and 3463, respectively. Two radiologists delineated regions of interest for lesions and labeled the disease types as ground truths. The datasets were split into training, tuning, and testing as 7:1: 2. Total test sets were randomly selected in 1214 normal and 690 abnormal. A 5‐fold, cross‐validation was performed on our datasets. For the classification of normal and abnormal, we developed a CNN based on DenseNet169; for abnormal detection, The You Only Look Once (YOLO) v2 with DenseNet was used. Detection and classification of normal and five classes of diseases (nodule[s], consolidation, interstitial opacity, pleural effusion, and pneumothorax) on chest radiographs were analyzed. Our CNN model classified chest radiographs as normal or abnormal with an accuracy of 97.8%. For the results of the abnormal, F1 score, was 75.2 ± 2.28% for nodules, 55.0 ± 4.3% for consolidation, 78.2 ± 7.85% for interstitial opacity, 81.6 ± 2.07% for pleural effusion, and 70.0 ± 7.97% for pneumothorax, respectively. In addition, we conducted the experiments between our method and RetinaNet with only nodules. The results of our method and RetinaNet at cutoff‐0.5 in the free response operating characteristic curve were 83.45% and 80.55%, respectively. Our algorithm demonstrated viable detection and disease classification capacity and could be used for CAD of lung diseases on chest radiographs.
On the inclusion chromatic index of a graph
Authors: Przybyło Jakub , Kwaśny Jakub 
Published: October 2020

AbstractLet be the least number of colours necessary to properly colour the edges of a graph with minimum degree so that the set of colours incident with any vertex is not contained in a set of colours incident to any of its neighbours. We provide an infinite family of examples of graphs with , where is the maximum degree of , and we conjecture that for every connected graph with which is not isomorphic to . The equality here is attained, for example, for the family of complete bipartite graphs. Using a probabilistic argument we support this conjecture by proving that (for ) for any fixed , which implies that for large enough.
Clusters of pain trajectories among patients with sickle cell disease hospitalized for vaso‐occlusive crisis: A data‐driven approach
Authors: Rodday Angie Mae , Esham Kimberly S. , Savidge Nicole , Parsons Susan K. 
Published: October 2020

AbstractBackgroundVaso‐occlusive crises (VOCs) are the hallmark of sickle cell disease (SCD), with higher severity among hospitalized patients. Clustering hospitalizations with similar pain trajectories could identify vulnerable patient subgroups. Aims were to (a) identify clusters of hospitalizations based on pain trajectories; (b) identify factors associated with these clusters; and (c) determine the association between these clusters and 30‐day readmissions.MethodsWe retrospectively included 350 VOC hospitalizations from 2013 to 2016 among 59 patients. Finite mixture modeling identified clusters of hospitalizations from intercepts and slopes of pain trajectories during the hospitalization. Generalized estimating equations for multinomial and logistic models were used to identify factors associated with clusters of hospitalizations and 30‐day readmissions, respectively, while accounting for multiple hospitalizations per patient.ResultsThree clusters of hospitalizations based on pain trajectories were identified: slow (n = 99), moderate (n = 207), and rapid (n = 44) decrease in pain scores. In multivariable analysis, SCD complications, female gender, and affective disorders were associated with clusters with slow or moderate decrease in pain scores (compared to rapid decrease). Although univariate analysis found that the cluster with moderate decrease in pain scores was associated with lower odds of 30‐day readmissions compared to the cluster with slow decrease, it was nonsignificant in multivariable analysis. SCD complications were associated with higher odds of 30‐day readmissions and older age was associated with lower odds of 30‐day readmissions.ConclusionsOur results highlight variability in pain trajectories among patients with SCD experiencing VOC and provide a novel approach for identifying subgroups of patients that could benefit from more intensive follow‐up.