bluuebunny/crossref_metadata_2025_split huggingface dataset:
Landscape‐scale habitat characteristics and neonatal white‐tailed deer survival
Authors: Wright Chloe A. , Mcroberts Jon T. , Wiskirchen Kevyn H. , Keller Barbara J. , Millspaugh Joshua J. 
Published: July 2019

ABSTRACTLandscape‐level habitat characteristics affect neonatal white‐tailed deer (Odocoileus virginianus) survival. Little is known, however, about how changes in maternal habitat use after parturition affect neonate survival. We quantified survival rates and determined if neonate survival to 8 weeks was affected by weekly maternal habitat use in the agricultural Glaciated Plains (GP) and forest‐grassland Ozark (OZ) eco‐regions of Missouri, USA. We captured 127 pregnant female deer during 2015–2017, and fitted each with a global positioning system (GPS) radio‐collar and vaginal implant transmitter (VIT). We captured 226 neonatal deer during 2015–2017, fitted each with an expandable radio‐collar, and monitored survival status daily. We estimated weekly maternal home ranges and calculated habitat metrics within these home ranges. We used the Kaplan‐Meier estimator to calculate 8‐week survival estimates and Cox proportional hazards models to investigate the influence of habitat metrics on neonate survival. The 8‐week survival estimates were 0.43 (95% CI = 0.35–0.54) and 0.47 (95% CI = 0.38–0.57) in the GP and OZ, respectively. Both of these survival estimates were lower than expected but particularly so in the GP because it is dominated by agricultural fields, a land cover type typically associated with high survival. Neonate survival in the GP was negatively correlated with the amount of edge and forest patch size within maternal home ranges. In the OZ, female neonate survival was positively correlated with birth mass, male neonate survival was not affected by birth mass, and survival of both sexes was negatively correlated with grassland patch density. We suspect these habitat metrics were related to predator searching efficiency and abundance. In the highly fragmented GP, predators might be able to easily search the largest cover habitat patches, whereas in the more contiguous OZ landscape, where cover habitat patch sizes were > 10 times the size of patches in the GP, large patches might be difficult for predators to search efficiently. Therefore, we recommend managers consider the larger landscape context when making habitat management decisions to increase white‐tailed deer population productivity. © 2019 The Wildlife Society.
Demographic factors affecting population growth in giant gartersnakes
Authors: Rose Jonathan P. , Ersan Julia S. M. , Wylie Glenn D. , Casazza Michael L. , Halstead Brian J. 
Published: July 2019

ABSTRACTDemographic models provide insight into which vital rates and life stages contribute most to population growth. Integral projection models (IPMs) offer flexibility in matching model structure to a species’ demography. For many rare species, data are lacking for key vital rates, and uncertainty might dissuade researchers from attempting to build a demographic model. We present work that highlights how the implications of uncertainties and unknowns can be explored by building and analyzing alternative models. We constructed IPMs for the threatened giant gartersnake (Thamnophis gigas) based on published studies to determine where management efforts could be targeted to have the greatest effect on population persistence and what unknowns remain for future research. Given uncertainty in the survival of snakes during their first year, and in the form of the size‐survival relationship, we modeled a range of scenarios and evaluated where models agree about factors influencing population growth and where discrepancies exist. For most scenarios, the survival of large adult females had the greatest influence on population growth, but the relative importance of juvenile versus adult somatic growth for population growth was dependent on the recruitment probability and the shape of the size‐survival function. More data on temporal variation and covariance among vital rates would improve stochastic models for the giant gartersnake. This paper demonstrates the effectiveness of IPMs for studying the demography of reptiles and the value of the model‐building process for formalizing what is known and unknown about the demography of rare species. Published 2019. This article is a U.S. Government work and is in the public domain in the USA.
Using spotlight observations to predict resource selection and abundance for white‐tailed deer
Authors: Kaminski Dan J. , Harms Tyler M. , Coffey Jim M. 
Published: July 2019

ABSTRACTSpotlight surveys for white‐tailed deer (Odocoileus virginianus) can yield large presence‐only datasets applicable to a variety of resource selection modeling procedures. By understanding how populations distribute according to a given resource for a reference area, density and abundance can be predicted across new areas assuming the relationship between habitat quality (measured by an index of selection) and species distribution are equivalent. Habitat‐based density estimators have been applied to wildlife species and are useful for addressing conservation and management concerns. Although achieving reliable population estimates is a primary goal for spotlighting studies, presence‐only models have yet to be applied to spotlight data for estimating habitat selection and abundance for deer. From 2012 to 2017, we conducted spring spotlight surveys in each of 99 counties in Iowa, USA, and collected spatial locations for 20,149 groups of deer (n = 71,323 individuals). We used a resource selection function (RSF) based on deer locations to predict the relative probability of use for deer at the population level and to estimate statewide abundance. The number of deer observed statewide increased significantly with increasing RSF value for all years and the mean RSF value along survey transects explained 59% of the variability in county‐level deer counts, indicating that a functional response between habitat quality and deer distribution existed at landscape scales. We applied our RSF to a habitat‐based density estimator (extrapolation) and zero‐inflated Poisson (ZIP) and negative binomial (ZINB) count models to predict statewide abundance from spotlight counts. Population estimates for 2012 were variable, indicating that atypical weather conditions may affect spotlight counts and population estimates in some years. For 2013–2017, we predicted a mean population of 439,129 (95% CI ∼ ± 55,926), 440,360 (∼ ± 43,676), and 465,959 (∼ ± 51,242) deer across years for extrapolation, ZIP, and ZINB models, respectively. Estimates from all models were not significantly different than estimates from an existing deer population accounting model in Iowa for 2013 and 2016, and differed by <76,000 deer for all models from 2013–2017. Extrapolation and ZIP models performed similarly and differed by <2,897 deer across all years, whereas ZINB models showed inconsistencies in model convergence and precision of estimates. Our results indicate that presence‐only models are capable of producing reliable and precise estimates of resource selection and abundance for deer at broad landscape scales in Iowa and provide a tool for estimating deer abundance in a spatially explicit manner. © 2019 The Wildlife Society.
Radiomics analysis for the differentiation of autoimmune pancreatitis and pancreatic ductal adenocarcinoma in 18F‐FDG PET/CT
Authors: Zhang Yuquan , Cheng Chao , Liu Zhaobang , Wang Lei , Pan Guixia , Sun Gaofeng , Chang Yan , Zuo Changjing , Yang Xiaodong 
Published: July 2019

PurposeTo perform a radiomics analysis with comparisons of multidomain features and a variety of feature selection strategies and classifiers, with the goal of evaluating the value of quantified radiomics method for noninvasively differentiating autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC) in 18F‐fluorodeoxglucose positron emission tomography/computed tomography (18F FDG PET/CT) images.MethodsWe extracted 251 expert‐designed features from 2D and 3D PET/CT images of 111 patients, and recombined these features into five feature sets according to their modalities and dimensions. Among the five feature sets, the optimal one was found leveraging four feature selection strategies and four machine learning classifiers based on the area under the receiver operating characteristic curve (AUC). The feature selection strategies include spearman’s rank correlation coefficient, minimum redundancy maximum relevance, support vector machine recursive feature elimination (SVM‐RFE), and no feature selection, while the classifiers are random forest, adaptive boosting, support vector machine (SVM) with the Gaussian radial basis function, and SVM with the linear kernel function respectively. Based on the optimal feature set, these feature selection strategies and classifiers were comparatively studied to achieve the best differentiation. Finally, the quantified radiomics prediction model was developed based on the best combination of the feature selection strategy and classifier, and it was compared with two clinical factors based prediction models, and human doctors using nested cross‐validation in terms of AUC, accuracy, sensitivity, and specificity.ResultsComparison experiments demonstrated that CT features and three‐dimensional (3D) features performed better than positron emission tomography (PET) features and three‐dimensional (2D) features respectively, and multidomain features were superior to single domain features. In addition, the combination of SVM‐RFE feature selection strategy and Linear SVM classifier had the highest diagnostic performance (i.e., AUC = 0.93 ± 0.01, ACC = 0.85 ± 0.02, SEN = 0.86 ± 0.03, SPE = 0.84 ± 0.03). The quantified radiomics model developed is significantly superior to both human doctors and clinical factors based prediction models in terms of accuracy and specificity.ConclusionsOur preliminary results confirmed that the quantified radiomics method could aid the noninvasive differentiation of AIP and PDAC in 18F FDG PET/CT images and the integration of multidomain features is beneficial for the differentiation.
Ultrathin Glass Substrates for Thin, Lightweight, Flexible OLED Lighting
Authors: Garner Sean , Chowdhury Dipak , Lewis Sue 
Published: July 2019

AbstractAlthough OLED enables uniform, efficient, and unique designs for lighting applications, it also presents several challenges, including the need to identify a transparent and flexible substrate that provides an adequate hermetic barrier. Here, three authors from Corning explain their company's approach to these issues.
Anthropometric Measurements and Cognitive Impairment Rather Than Nutrition Status Are Associated With Sarcopenia in Long‐Term Care Residents
Authors: Rodríguez‐Rejón Ana Isabel , Artacho Reyes , Ruiz‐López María Dolores 
Published: July 2019

AbstractBackgroundSarcopenia is an important health problem in older adults. The aim was to study the association of anthropometric measurements, functional capacity, cognitive impairment, and nutrition status with sarcopenia in institutionalized older adults.MethodsA cross‐sectional study was undertaken, determining the calf circumference (CC), mid‐upper arm muscle circumference (MUAMC), and body mass index (BMI) and administering the Pfeiffer test and Mini Nutritional Assessment Short Form (MNA‐SF). Sarcopenia was diagnosed following criteria of the European Working Group on Sarcopenia in Older People. After bivariate analyses, a multivariate logistic regression model was constructed to determine the association of study variables with sarcopenia.ResultsThe study group comprised 249 residents (mean age 84.9 ± 6.7 years). The prevalence of sarcopenia was 63%. The multivariate analysis with adjusted odds ratios (ORs) indicated that the risk of sarcopenia was significantly increased by being female (OR = 2.8; 95% CI 1.3–6.2), having moderate or severe cognitive impairment (Pfeiffer test score of 5–10) (OR = 2.4; 95% CI 0.9–6.4), and having a BMI < 22 kg/m2 (OR = 22.4; 95% CI 6.7–75.0). Moreover, a low CC (OR = 6.5; 95% CI 3.0–14.0) or MUAMC (OR = 3.9; 95% CI 1.7–9.3) also significantly increased the risk of sarcopenia. A negative association was observed between sarcopenia and MNA‐SF, although it did not remain statistically significant in the multivariate analysis.ConclusionsThe variables identified as risk factors for sarcopenia can assist in detecting individuals at higher risk who require special clinical attention.
Design and psychometric properties of an instrument to assess metacognition in moral reasoning in medicine
Authors: Kamali Farahnaz , Yousefy Alireza , Yamani Nikoo 
Published: July 2019

AbstractAimThe present study aims at designing and assessing the psychometric properties of MCMR instruments to lead the medical ethics education to further goals and more definite steps.DesignThis is a cross sectional study.MethodThis study was conducted in two phases; identifying the items and designing the instrument. In the preliminary phase, the qualitative study was carried out using conventional content analysis method. In the second phase, psychometric evaluation of instrument was done using face and content validity, construct validity and reliability.ResultsOn the first phase of this study, 135 items were identified. After determining face and content validity, 111 items reached the stage of exploratory factor analysis. This instrumental analysis indicated the existence of 74 items and ten factors whose variance of the total is explained as 46.883%. Cronbach's alpha value was 0/75. And the intra‐cluster correlation coefficient was 0.808.
Because coconuts do not grow in Canberra: Complexity theory and capacity development in Solomon Islands Police Force
Authors: Curth‐Bibb Jodie 
Published: July 2019

SummaryStatebuilding has been informed and captured by reductionist, linear change models. Defined by technocratic approaches to public sector (re)building and reform—it has been monitored, measured and evaluated by New Public Management artefacts such as log‐frames and Results‐Based Management. Through a case study on the capacity development of the Royal Solomon Islands Police Force, I explore the possibilities for using complexity theory to better understand, manage, and monitor capacity development interventions. The analysis of interview data with police practitioners from both sides of the intervention—advisors and local counterparts—reveals the explanatory power of complexity concepts (such as interconnectedness, emergence, initial conditions, and non‐linear change) in ways that could inform a rethink of how we frame public sector capacity building interventions.
Colorectal cancer in adolescents and young adults: Defining a growing threat
Authors: Levine Oren , Zbuk Kevin 
Published: July 2019

AbstractColorectal cancer (CRC) incidence is rising among adolescents and young adults (AYAs), with the greatest increase occurring in distal colon and rectal cancers. Reasons for this striking trend are not well understood. Genetically linked cases of CRC occur in the context of familial conditions such as Lynch Syndrome, but most AYA cases of CRC are sporadic. Unique biology is suggested, yet limited information is available regarding the molecular underpinnings of CRC in this age group. Young patients are more likely to experience delays in diagnosis and to present with advanced‐stage disease; yet, prognosis by stage is comparable between younger and older adults. Treatment paradigms are based on evidence reflecting the older adult population. Given the concerning rise in CRC rates among AYAs, there is urgent need for further research into the role of screening from a younger age, biology of disease, and optimal therapies in this age group.
SecProMTB: Support Vector Machine‐Based Classifier for Secretory Proteins Using Imbalanced Data Sets Applied to Mycobacterium tuberculosis
Authors: Meng Chaolu , Wei Leyi , Zou Quan 
Published: July 2019

AbstractSecretory proteins of Mycobacterium tuberculosis have created more concern, given their dominant immunogenicity and role in pathogenesis. In view of expensive and time‐consuming traditional biochemical experiments, an advanced support vector machine model named SecProMTB is constructed in this study and the proteins are identified by a bioinformatic approach. First, an improved pseudo‐amino acid composition (PseAAC) algorithm is used to extract features from all entities. Second, a novel imbalanced‐data strategy is proposed and adopted to divide the original data set into train set and test set. Third, to overcome the overfitting problem, feature‐ranking algorithms are applied with an increment feature selection. Finally, the model is trained and optimized. Consequently, a model is obtained with an area under the curve of 0.862 and average accuracy of 86% in the independent test. For the convenience of users, SecProMTB and related data are openly accessible at http://server.malab.cn/SecProMTB/index.jsp.
Digital Assembly of Colloidal Particles for Nanoscale Manufacturing
Authors: Kotnala Abhay , Zheng Yuebing 
Published: July 2019

AbstractFrom unravelling the most fundamental phenomena to enabling applications that impact our everyday lives, the nanoscale world holds great promise for science, technology, and medicine. However, the extent of its practical realization relies on manufacturing at the nanoscale. Among the various nanomanufacturing approaches being investigated, the bottom‐up approach involving assembly of colloidal nanoparticles as building blocks is promising. Compared to a top‐down lithographic approach, particle assembly exhibits advantages such as smaller feature size, finer control of chemical composition, less defects, lower material wastage, and higher scalability. The capability to assemble colloidal particles one by one or “digitally” has been heavily sought as it mimics the natural method of making matter and enables construction of nanomaterials with sophisticated architectures. An insight into the tools and techniques for digital assembly of particles, including their working mechanisms and demonstrated particle assemblies, is provided. Examples of nanomaterials and nanodevices are presented to demonstrate the strength of digital assembly in nanomanufacturing.
Output feedback controller for polytopic systems exploiting the direct searching of the design space
Authors: Abolpour Roozbeh , Dehghani Maryam , Talebi Heidar Ali 
Published: July 2019

SummaryThis paper deals with the problem of designing a robust static output feedback controller for polytopic systems. The current research that tackled this problem is mainly based on LMI method, which is conservative by nature. In this paper, a novel approach is proposed, which considers the design space of the controller parameters and iteratively partitions the space to small simplexes. Then, by assessing the stability in each simplex, the solution space for design parameters is directly determined. It has been theoretically proved that, if there exists a feasible solution in the design space, the algorithm can find it. To validate the result of the proposed approach, comparative simulation examples are given to illustrate the performance of the design methodology as compared to those of previous approaches.
Modelling inundation patterns and sediment dynamics in the extensive floodplain along the Tonle Sap River
Authors: Siev Sokly , Paringit Enrico C. , Yoshimura Chihiro , Hul Seingheng 
Published: July 2019

AbstractThe Tonle Sap River (TSR) serves as a natural medium for the reversal flow between Tonle Sap Lake (TSL) and the Mekong River to sustain productivity and biodiversity in the TSR floodplain and TSL. Understanding the hydrological connectivity and its dynamics in the TSR, including its floodplain, is therefore important to support activities that aim to maintain ecological services in the TSR–TSL system. Thus, the main objective of this study is to examine the hydrological connectivity of the TSR and its floodplain by a modelling approach that integrates inundation patterns and sediment dynamics. The Caesar–Lisflood model was applied to describe inundation, sediment erosion, transport, and deposition in the TSR for the period of 2003–2013. The inundation areas connected to the TSR ranged from 140 to 2,327 km2, whereas the isolated inundation areas from the TSR ranged from 0.27 to 504 km2. Sediment dynamics showed its influence on inundation patterns and hydrological connectivity and could alter the yearly inundation ratio (defined as a normalized inundation frequency with a value ranging from 0 to 1) up to 0.8. Our approach provides a quantitative way to determine key factors (e.g., total inundation areas, seasonality, and connectivity of inundation patterns) for further investigation of ecological processes in relation to the inundation patterns and sediment dynamics in the TSR and TSL.
Effect of restrained shrinkage cracking on chloride penetration of high‐performance concrete containing fly ash and ground‐granulated blast‐furnace slag
Authors: Ma Lina , Zhao Yanhua , Gong Jinxin 
Published: July 2019

AbstractIn this study, the effect of restrained shrinkage cracking on the chloride penetration of high‐performance concrete was investigated. Different shrinkage cracking patterns were first produced on concrete slabs subjected to nonrestrained, two‐side restrained, or four‐side restrained condition. For each restrained condition, four water‐binder (w/b) ratios of 0.25, 0.30, 0.35, and 0.40 were employed, and for each w/b ratio, fly ash and granulated blast‐furnace slag were utilized in a systematic replacement of cement at the levels of 0, 20, 30, 40, and 50%, respectively. Then, rapid chloride penetration (RCP) tests were conducted on samples sliced from concrete slabs for measuring the charge passed through the sample per se ASTM C1202. The experimental results indicate that w/b ratio, replacement level, and restrained condition had significant effects on the chloride penetration, and the charge passed could be well described by a unified expression when taking these three factors into account. Cracking area that could be used is responsible for the variation of the charge passed. More restraints resulted in bigger cracking areas meaning extra passages for chloride ingress, and in turn increased the charge passed during RCP test. Moreover, the inclusion of fly ash and slag proved to be effective in reducing chloride penetration, and small w/b ratio had a similar beneficial effect regarding chloride resistance which could be attributed to an improved pore structure within concrete and reduced cracking area.