bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel nomogram with preferable capability in predicting the overall survival of patients after radical esophageal cancer resection based on accessible clinical indicators: A comparison with AJCC staging
Authors: Li Xinye , Xu Jinming , Zhu Linhai , Yang Sijia , Yu Li , Lv Wang , Hu Jian 
Published: June 2021

AbstractBackgroundEsophageal cancer (EC) is a malignant tumor with high mortality. Nomogram is an important tool used in clinical prognostic assessment. We aimed to establish a novel nomogram to predict the overall survival (OS) of EC patients after radical esophagectomy.MethodsData pertaining to the survival, demography, and clinicopathology of 311 EC patients who underwent radical esophagectomy were retrospectively investigated. The nomogram was established based on Cox hazard regression analysis. The calibration curves and Harrell's concordance index (C‐index) were used to verify the predictive accuracy and ROC curves were used to assess the efficacy of the nomogram. Kaplan–Meier curves showed the prognostic value of the related risk classification system. Pearson correlation test was performed to determine the correlation between the risk classification system and TNM staging.ResultsThe median OS and 5‐year survival rates in the primary and validation cohorts were 44 months and 29.8%, and 52 months and 27.1%, respectively. We used six independent prognostic factors—age, Sex, AGR, PRL, N stage, and PNI—in the nomogram. The C‐index of nomogram was 0.75 and 0.70 in the primary and validation cohorts, respectively. Calibration curves indicated high consistency between actual and predicted OS. ROC curves showed that nomogram has a better efficacy compared with TNM staging in both cohorts. Patients were divided into three risk groups according to the total nomogram score, the median OS in each group was significantly different in both cohorts. Furthermore, the risk classification system was strongly correlated with the T and N staging system and exhibited a better OS prediction capability.ConclusionsWe established a novel and practical nomogram with a subordinate risk classification system to predict the OS of patients after radical esophagectomy. Compared with AJCC staging, this nomogram had preferable clinical capability in terms of individual prognosis assessment.
Design Thinking im Chemieunterricht
Authors: Wolthaus Petra , Gröger Martin 
Published: June 2021

ZusammenfassungDie für Schüler und Schülerinnen im zukünftigen Berufsleben erforderlichen Fähigkeiten sollten in der Schule gefördert werden. Wie dies theoretisch und praktisch umgesetzt werden kann, zeigt dieser Artikel, indem er die Methode des Design Thinking für den experimentellen Chemieunterricht exemplarisch darstellt. Ausgehend von einer komplexen Problemstellung im Zusammenhang mit Nachhaltigkeit fanden die Schülerteams einfache Lösungswege, die sich an den Bedürfnissen möglicher Nutzer orientierten. Sie entwickelten eigene Versuchsanleitungen, die sie mehrfach optimierten. Ihre „Prototypen“ bewerteten sie kritisch, indem sie sie mit herkömmlichen Produkten verglichen.
Social support in patients with bipolar disorder and differing ages at onset
Authors: Studart‐Bottó Paula , Bezerra‐Filho Severino , Sarmento Stella , Miranda‐Scippa Ângela 
Published: June 2021

AbstractObjectiveThe main purpose of this study was to evaluate the association between age at onset and social support in outpatients with bipolar disorder who were in the recovery phase. We also investigated the association between age at onset and disability.MethodsA total of 180 bipolar disorder I outpatients, of whom 50 had early onset with age at onset ≤18 years old, 108 had middle onset with age at onset between 19 and 39 years old, and 22 had late onset with age at onset ≥40 years old, were assessed with the Medical Outcomes Study Social Support Scale and Sheehan Disability Scale.ResultsThe early onset group had lower tangible social support, longer length of illness, more childless participants, lower income and more suicide attempters than the late onset group.ConclusionsEarly onset seems to have inferior outcomes in tangible social support than late onset, but this trend should be considered as a starting point for future studies.
Spatial modeling increases accuracy of selection for Phytophthora infestans‐resistant tomato genotypes
Authors: Copati Mariane Gonçalves Ferreira , Dariva Françoise Dalprá , Dias Felipe de Oliveira , Rocha João Romero do Amaral Santos de Carvalho , Pessoa Herika Paula , de Almeida Gabriella Queiroz , Carneiro Pedro Crescêncio Souza , Nick Carlos 
Published: June 2021

AbstractAt initial breeding stages, using a replicated check design is a viable alternative to reduce experimental field area as well as financial and operational costs. In this situation, spatial modeling could act to increase prediction accuracy of plant genotypic values. The objectives of this study were to demonstrate how spatially adjusted models can be used to reduce experimental error and how to compare statistical models in order to identify the best model for accurate genotype selection. For this purpose, we assessed 200 F3:4 tomato families for their resistance to Phytophthora infestans isolates. NC1CELBR, NC25P, and the cultivar Santa Clara were used as checks. Under field conditions, plants were inoculated with P. infestans isolates and scored according to their level of disease severity. Nine statistical models were adjusted to estimate family genotypic values. The selection of the fittest model was based on residual variance values, accuracy, Akaike and Bayesian information criteria, and the maximum likelihood ratio test. We observed spatial patterns within the experimental field area. Spatial modeling decreased error, which is indicated by the better experimental variation distribution. Residual variance decreased, while genotypic variance increased ∼10% when spatial analysis was used. Spatial analysis improved selection accuracy by 19% compared with the traditional analysis. Therefore, we recommend incorporating spatial modeling into data analysis in breeding trials for disease resistance because it can provide higher gains from selection compared with traditional modeling approaches, depending on the experimental condition.
Drought legacies mediated by trait trade‐offs in soil microbiomes
Authors: Wang Bin , Allison Steven D. 
Published: June 2021

AbstractSoil microbiomes play a key role in driving biogeochemical cycles of the Earth system. As drought frequency and intensity increase due to climate change, soil microbes and the processes they control will be impacted. Even after a drought ends, microbiomes and other systems take time to recover and may display a memory of previous climate conditions. Still, the mechanisms involved in these legacy effects remain unclear, making it difficult to predict climate and biogeochemical rates in the future. Here, we used a trait‐based microbiome model (DEMENTpy) to implement trade‐off‐mediated mechanisms that may lead to drought legacy effects on litter decomposition. Trade‐offs were assumed to follow the Y‐A‐S framework that defines three primary life‐history strategies of microorganisms: high growth Yield, resource Acquisition, and Stress tolerance. We represented cellular trade‐offs between osmolytes required for drought tolerance and investment in enzymes involved in litter decomposition. Simulations were run under varying levels of drought severity and dispersal. With high levels of dispersal, no legacy effects were predicted by DEMENTpy following drought. With limited dispersal, severe drought resulted in a persistent legacy of altered community‐level traits and reduced litter decomposition. Moderate drought resulted in a transient legacy that disappeared after two years, consistent with recent empirical observations in Southern California ecosystems. These results imply that greater movement along the trade‐off between enzyme investment and osmolyte production resulted in stronger legacy effects. More generally, factors that shift the position of a microbiome in YAS space may alter the legacy outcome following drought. Our trait‐based modeling study motivates additional empirical measurements to quantify YAS traits and trade‐offs that are needed to make accurate predictions of soil microbiome resilience and functioning. Also, our study illustrates an emerging approach for representing trait trade‐offs in microbiomes and vegetation that dictate ecosystem responses to drought and other environmental perturbations.
Financial sustainability strategies of public primary health care centres in the Republic of Srpska, Bosnia and Herzegovina
Authors: Rakic Severin , Djudurovic Aljosa , Antonic Darijana 
Published: June 2021

AbstractBackgroundThe literature on the functioning of public health facilities in health systems with significant arrears is limited. The growing liabilities of health facilities and the accumulating arrears have been a challenge in the Republic of Srpska. Most public primary healthcare (PHC) centres generated a gross loss in 2018.MethodGuided by the ‘positive deviance’ approach, we used an exploratory case study design to identify strategies used by managers to achieve financial sustainability in eight top‐performing PHC centres. Qualitative data were collected through face‐to‐face in‐depth semistructured interviews with key informants from the PHC centres that reported positive financial results in 2018.ResultsSeven organisational goals, comprising 34 financial sustainability strategies, were recognised during the data analysis and were used to build an organisational‐level model for a PHC centre.ConclusionManagers concurrently used multiple strategies to ensure financial sustainability. Each centre tailored its range of strategies to the organisational context, local context, and wider environment of the health system. The strategies were conceived and implemented by managers operating at different organisational levels under the leadership of top‐level managers. Managers of indebted health facilities can learn from the positively deviant peers who manage facilities that achieved satisfactory financial performance.
Modifications on porous absorbable Fe‐based scaffolds for bone applications: A review from corrosion and biocompatibility viewpoints
Authors: Md Yusop Abdul Hakim , Al Sakkaf Ahmed , Nur Hadi 
Published: June 2021

AbstractIron (Fe) and Fe‐based scaffolds have become a research frontier in absorbable materials which is inherent to their promising mechanical properties including fatigue strength and ductility. Nevertheless, their slow corrosion rate and low biocompatibility have been their major obstacles to be applied in clinical applications. Over the last decade, various modifications on porous Fe‐based scaffolds have been performed to ameliorate both properties encompassing surface coating, microstructural alteration via alloying, and advanced topologically order structural design produced by additive manufacturing (AM) techniques. The recent advent of AM produces topologically ordered porous Fe‐based structures with an optimized architecture having controllable pore size and strut thickness, intricate internal design, and larger exposed surface area. This undoubtedly opens up new options for controlling Fe corrosion and its structural strengths. However, the in vitro biocompatibility of the AM porous Fe still needs to be addressed considering its higher corrosion rate due to the larger exposed surface area. This review summarizes the latest progress of the modifications on porous Fe‐based scaffolds with a specific focus on their responses on the corrosion behavior and biocompatibility.
An evaluation of the structure of the labour market, assistance policies and sectoral productivity on the pro‐poor growth for Brazil from 2004 to 2014: A dynamic panel analysis
Authors: Ribeiro Jouse T. , Santolin Roberto 
Published: June 2021

AbstractThe aim of this article is to evaluate pro‐poor growth based on individual labour market attributions and aggregate variables for Brazilian states: inequality, sectoral economic growth (agriculture, industry and services) and social policies, Programa Bolsa Família and the Benefício de Prestação Continuada. The methodology was a two‐step estimation. The first stage, called the ‘first cross‐sectional stage’, involves estimation by binary choice models that relate poverty levels to the individual attributes and positions in the labour market. In the second stage, poverty was assessed in terms of inequality, economic growth and social policies, aggregated for Brazilian states using a dynamic panel. The results obtained showed that sectoral economic growth and assistance policies have a strong impact on extreme poverty; for the other poverty ranges, the most relevant variables were the reduction of inequality and sectoral economic growth.
Anatomically aided PET image reconstruction using deep neural networks
Authors: Xie Zhaoheng , Li Tiantian , Zhang Xuezhu , Qi Wenyuan , Asma Evren , Qi Jinyi 
Published: June 2021

AbstractPurposeThe developments of PET/CT and PET/MR scanners provide opportunities for improving PET image quality by using anatomical information. In this paper, we propose a novel co‐learning three‐dimensional (3D) convolutional neural network (CNN) to extract modality‐specific features from PET/CT image pairs and integrate complementary features into an iterative reconstruction framework to improve PET image reconstruction.MethodsWe used a pretrained deep neural network to represent PET images. The network was trained using low‐count PET and CT image pairs as inputs and high‐count PET images as labels. This network was then incorporated into a constrained maximum likelihood framework to regularize PET image reconstruction. Two different network structures were investigated for the integration of anatomical information from CT images. One was a multichannel CNN, which treated PET and CT volumes as separate channels of the input. The other one was multibranch CNN, which implemented separate encoders for PET and CT images to extract latent features and fed the combined latent features into a decoder. Using computer‐based Monte Carlo simulations and two real patient datasets, the proposed method has been compared with existing methods, including the maximum likelihood expectation maximization (MLEM) reconstruction, a kernel‐based reconstruction and a CNN‐based deep penalty method with and without anatomical guidance.ResultsReconstructed images showed that the proposed constrained ML reconstruction approach produced higher quality images than the competing methods. The tumors in the lung region have higher contrast in the proposed constrained ML reconstruction than in the CNN‐based deep penalty reconstruction. The image quality was further improved by incorporating the anatomical information. Moreover, the liver standard deviation was lower in the proposed approach than all the competing methods at a matched lesion contrast.ConclusionsThe supervised co‐learning strategy can improve the performance of constrained maximum likelihood reconstruction. Compared with existing techniques, the proposed method produced a better lesion contrast versus background standard deviation trade‐off curve, which can potentially improve lesion detection.
Relative Catchability of Channel Catfish and Blue Catfish × Channel Catfish Hybrids by Anglers in Put-and-Take Urban Fisheries
Authors: Hungerford Thomas J. , Bodine Kristopher A. , Tibbs John E. , Myers Randall A. , Prangnell David , Daugherty Daniel J. , Schlechte J. Warren 
Published: June 2021

Abstract
Texas’ Neighborhood Fishin’ Program provides close-to-home angling opportunities within nine large metropolitan areas to increase angling participation among urban constituents. Water bodies (0.4–2.4 ha) are typically stocked with harvestable (≈305 mm TL) Channel Catfish (CCF) Ictalurus punctatus to provide high-catch, successful fishing experiences. However, fish producers have been increasingly rearing and stocking lower-maintenance, faster-growing CCF × Blue Catfish I. furcatus hybrids to reduce costs. Although recent research in put–grow–take fisheries has suggested no differences in catchability, a number of Texas anglers utilizing these put-and-take fisheries have reported lower catch rates of hybrids. Thus, we evaluated relative catchability between the two fish types by stocking equal numbers of uniquely marked CCF and hybrids simultaneously into four Neighborhood Fishin’ Program water bodies on three occasions during 2018. Harvest of each type was measured during five systematic daily creel surveys across a 2-week period, with the first interviews occurring during the day of each stocking event. Nearly five times more CCF were harvested than hybrids during the first daily creel survey after each stocking event, but harvest of CCF declined significantly by the second daily creel survey. There were no significant differences in harvest between types among subsequent daily creels (surveys 2–5) over the 2-week creel periods. Few uniquely marked fish of either type were harvested in daily creel surveys 4 and 5. Despite the varying harvest rates, anglers remained satisfied or extremely satisfied throughout the 2-week creel periods. Our results indicate that CCF are more accessible to anglers than hybrids immediately after stocking. Managers’ choice of which type to stock should depend on relevant fishery objectives. Although CCF will likely produce higher initial catch rates, stocking a mixture of CCF and hybrids may provide a longer-term fishery that still produces catch rates high enough to maintain or enhance angler satisfaction.
Simultaneous monitoring of vegetation dynamics and wildlife activity with camera traps to assess habitat change
Authors: Sun Catherine , Beirne Christopher , Burgar Joanna M. , Howey Thomas , Fisher Jason T. , Burton A. Cole 
Published: June 2021

AbstractVegetation phenology and productivity drive resource use by wildlife. Vegetation dynamics also reveal patterns of habitat disturbance and recovery. Monitoring these fine‐scale vegetation patterns over large spatiotemporal extents can be difficult, but camera traps (CTs) commonly used to survey wildlife populations also collect data on local habitat conditions. We used CTs (n = 73) from 2016 to 2019 to assess impacts of habitat change in a boreal landscape of northern Canada, where seismic lines for petroleum exploration disturbed wildlife habitat and prompted vegetation restoration efforts. First, we quantified vegetation dynamics from CTs, comparing them to satellite‐based estimates that are typically used to monitor vegetation at broad spatial scales. We then used understory phenology and productivity estimated from CT time‐lapse images to assess vegetation recovery on seismic lines. Finally, we related vegetation dynamics with the habitat use of three wildlife species: sandhill cranes Grus canadensis, woodland caribou Rangifer tarandus, and white‐tailed deer Odocoileus virginianus. CTs provided unique insight into vegetation dynamics that were different from signals measured by satellites, with temporally inconsistent and even some negative correlations between CT and satellite metrics. We found some indication of vegetation recovery on seismic lines that had received restoration treatment, with understory patterns more similar to undisturbed habitat than to seismic lines that did not receive restoration treatment. CTs also provided inferences about wildlife activity related to vegetation resources, which approaches using satellite data failed to detect. Wildlife habitat use tracked vegetation phenology, but did not always increase with vegetation productivity at weekly, 16‐day, or annual intervals. Instead, associations with vegetation productivity depended on species, temporal scale, and productivity metrics. Given the widespread and growing use of CTs to monitor terrestrial wildlife, we recommend their use to simultaneously monitor habitat conditions to better understand the mechanisms that govern wildlife habitat use in changing environments.
A monolithic mixed matrix membrane based on silver nanoparticle/nylon‐6 nanocomposite: A novel coating for stir bar sorptive extraction of organophosphorus pesticides
Authors: Ayazi Zahra , Shekari Esfahlan Fatemeh 
Published: June 2021

AbstractIn this research, a novel monolithic mixed matrix membrane based on silver nanoparticles reinforced nylon 6 was prepared by in situ reduction of silver nitrate salt in a formic acid solution of nylon 6. The phase separation method was employed to deposit prepared nanocomposite onto a stainless steel substrate. The characterization of nylon 6 and silver nanoparticles/nylon 6 nanocomposite coated stir bars were conducted applying scanning electron microscopy, X‐ray diffraction, and energy dispersive X‐ray spectroscopy. The prepared stir bar was employed for the stir bar sorptive extraction of organophosphorus pesticides such as ethion, phosalone, and chlorpyrifos in environmental water samples applying gas chromatography with mass spectrometry. The effect of the silver nanoparticles doping level in the nanocomposite on the extraction efficiency of the monolithic mixed matrix membrane was studied. Multivariate optimization based on the central composite design was employed to study and optimize essential parameters affecting the extraction and elution steps. The limits of detection were 0.2 and 0.3 ng/mL and the linear dynamic ranges were in the concentration range of 0.7‐1000 and 1–1000 ng/mL for all analytes. The method precision based on relative standard deviation by performing six replicates ranged from 2.4 to 7.4% for spiked distilled water (100 ng/mL).
Recurrence Quantification Analysis as a Methodological Innovation for School Improvement Research
Authors: Oude Groote Beverborg Arnoud , Wijnants Maarten , Sleegers Peter J. C. , Feldhoff Tobias 
Published: June 2021

AbstractSchool improvement and educational change can be facilitated by learning through reflection, as this allows teachers to discover ways to develop and adapt to change. Higher levels of engagement in reflection have been found to be beneficial, but it is unclear from which everyday routine in engagement in reflection higher levels arise, and thus whether occasions to make knowledge explicit should be organized with a certain constancy. In this study, we therefore used a conceptualization of teacher learning through reflection as a situated and dynamic process in which available environmental information, learning activities, and professional practices are interconnected, and co-develop. Seventeen Dutch Vocational Education and Training teachers participated over a period of 5 months. We explored the use of daily and monthly logs as measurement instruments and Recurrence Quantification Analysis (RQA) as the analysis technique applied to the time-series generated from the daily logs. The findings indicated that teachers who make information from their working environment explicit more are also able to make new insights explicit more. The routine with which teachers make information explicit was found to be mostly unrelated to making new insights explicit. To reach their levels of engagement in reflection, some teachers organized opportunities to reflect with determined intervals, others seemed to recognize those opportunities as the working environment provided them, and some used a combination thereof. Moreover, the use of daily and monthly logs seemed to fit better to some participants than others. Only sometimes does organizing constancy in engagement in reflection seem to relate to the levels thereof. This study provides an example of how logs and RQA can be adopted to tap into professional learning as a dynamic and situated process in support of school improvement and educational change.