bluuebunny/crossref_metadata_2025_split huggingface dataset:
A trait‐based model ensemble approach to design rice plant types for future climate
Authors: Paleari Livia , Li Tao , Yang Yubin , Wilson Lloyd T. , Hasegawa Toshihiro , Boote Kenneth J. , Buis Samuel , Hoogenboom Gerrit , Gao Yujing , Movedi Ermes , Ruget Françoise , Singh Upendra , Stöckle Claudio O. , Tang Liang , Wallach Daniel , Zhu Yan , Confalonieri Roberto 
Published: January 2022

AbstractCrop models are powerful tools to support breeding because of their capability to explore genotype × environment×management interactions that can help design promising plant types under climate change. However, relationships between plant traits and model parameters are often model specific and not necessarily direct, depending on how models formulate plant morphological and physiological features. This hinders model application in plant breeding. We developed a novel trait‐based multi‐model ensemble approach to improve the design of rice plant types for future climate projections. We conducted multi‐model simulations targeting enhanced productivity, and aggregated results into model‐ensemble sets of phenotypic traits as defined by breeders rather than by model parameters. This allowed to overcome the limitations due to ambiguities in trait‐parameter mapping from single modelling approaches. Breeders' knowledge and perspective were integrated to provide clear mapping from designed plant types to breeding traits. Nine crop models from the AgMIP‐Rice Project and sensitivity analysis techniques were used to explore trait responses under different climate and management scenarios at four sites. The method demonstrated the potential of yield improvement that ranged from 15.8% to 41.5% compared to the current cultivars under mid‐century climate projections. These results highlight the primary role of phenological traits to improve crop adaptation to climate change, as well as traits involved with canopy development and structure. The variability of plant types derived with different models supported model ensembles to handle related uncertainty. Nevertheless, the models agreed in capturing the effect of the heterogeneity in climate conditions across sites on key traits, highlighting the need for context‐specific breeding programmes to improve crop adaptation to climate change. Although further improvement is needed for crop models to fully support breeding programmes, a trait‐based ensemble approach represents a major step towards the integration of crop modelling and breeding to address climate change challenges and develop adaptation options.
New cities in China: Tracking urban projects in the city fringe
Authors: Woodworth Max D. , Chien Shiuh‐Shen 
Published: January 2022

AbstractIn recent decades, hundreds of new cities have been built in China with a notable acceleration of this trend in the 2000s. Yet despite their numbers and variety, China’s new cities remain marginal to a wave of popular and scholarly attention directed at new towns and new cities globally. This article brings China’s new cities into these conversations through review of extant literature on the topic. Research on China’s new cities has focused on their functions as sites of accumulation, economic restructuring, globalization, territorialization, and innovation. In this article, we introduce these themes in the literature and show areas that remain ripe for future study.
Investigation of microscale fracture mechanisms in glass–ceramics using peridynamics simulations
Authors: Prakash Naveen , Deng Binghui , Stewart Ross J. , Smith Charlene M. , Harris Jason T. 
Published: January 2022

AbstractGlass–ceramics (GCs), obtained by controlled crystallization of a specially formulated precursor glass, are interesting materials that show great promise in obtaining superior properties compared to those of the precursor glass. Controlled crystallization enables creation of a microstructure with multiple phases which impacts macroscale properties in interesting ways. The present work develops microstructure‐scale computational models using the theory of peridynamics to investigate the increase in fracture toughness of GCs compared to traditional glass. Computational modeling is a promising tool to probe microstructural mechanics, but such studies in the literature are scarce. In this work, the theory of peridynamics, a non‐local theory of continuum mechanics, is applied to simulate crack propagation through microstructural realizations of a model lithium‐disilicate glass–ceramic. The crystalline and glassy phases within the microstructure are explicitly considered, with the size and shape of crystals inspired by experimental data. Multiple toughening mechanisms are revealed, which are functions of crystallinity and morphology, and the impact on fracture toughness is demonstrated. Crack path tortuosity is studied, and it is found that an optimum level of crack path tortuosity can be obtained in the range of 0.6–0.8 crystallinity. Numerical results are shown to agree well with previously published experimental and modeling results.
Double cantilever beam fracture toughness measurement method for glass
Authors: Aaldenberg Jared S. , Aaldenberg Emily M. , Picu Catalin R. , Negi Vineet , Lezzi Peter J. 
Published: January 2022

AbstractA simple method of measuring Mode I fracture toughness, KIC, of glass using the double cantilever beam (DCB) geometry is presented. An inert atmosphere is created at the crack tip to prevent subcritical crack growth and enable “pinning” the crack while the specimen is loaded to failure. This was achieved experimentally using liquid toluene or a glovebox with dry argon. KIC values measured by this method showed good agreement with published literature values for selected glasses. Applicability of the analytical stress intensity factor solution based on crack length, crack front curvature, and the height of the crack guiding groove are confirmed through experimental data and finite element analysis. The experimentally observed crack front curvature, which leads near the edges for small groove heights and leads in the center for larger groove heights, is predicted from the geometry of the DCB specimen for a linear elastic solid through finite element modeling.
Solid‐state formation mechanisms of core–shell microstructures in (Zr,Ta)B2 ceramics
Authors: Dorner Anna N. , Monteverde Frédéric , Fahrenholtz William G. , Hilmas Gregory E. 
Published: January 2022

AbstractTransition metal diborides with core–shell microstructures have demonstrated excellent mechanical properties at elevated temperatures. Previous studies concluded that core–shell microstructures were formed by liquid‐assisted mass transport mechanisms, but in this study, we propose a solid‐state formation mechanism for core‐shell microstructures in (Zr,Ta)B2 ceramics produced by reaction hot pressing and in ZrB2‐TaB2 diffusion couples. Diffusion couple experiments demonstrated that core–shell microstructures developed as a result of Ta diffusion along ZrB2 grain boundaries, which occurred concurrently with lattice diffusion of Ta into ZrB2. These findings suggest that with optimization of batching and processing parameters, core–shell diboride materials may be formed through solid‐state processes rather than liquid‐assisted processes, which could assist in raising the upper temperature limits of use for these materials.
Create Aspire Transform: How can Creative Professional Development (CPD) support Creative Cultural Learning in schools?
Authors: Thomas Judy 
Published: January 2022

AbstractBetween 2018 and 2020, eight teachers were involved in a two‐year programme of visual‐arts focused Creative Professional Development (CPD), delivered in partnership by the organisation Berwick Visual Arts (BVA) and Northumbria University. The overall challenge was to increase cultural leadership; with broader aims to engage North Northumberland schools with BVA and to identify and understand the value of cultural engagement by creating specific artist‐led programmes for teaching and learning. Contributing new insight into teacher learning, along with fresh understanding of the challenges schools face in relation to engagement with cultural learning activities, the research informing this article draws upon individual perspectives during which the provision of cultural learning within Berwick primary settings is explored. Data was collected over a two‐year period, from five CPD sessions, along with action research, a focus group and semi‐structured interviews with the participating teachers. This article includes extracts taken from the teachers’ reflections; these give insight into the programme’s impact and highlight the importance of confidence, along with the barriers that make cultural learning difficult to embed across schools. Their reflections reveal heightened confidence as a result of the CPD along with positive impact for pupils and the wider school community. The article concludes with recognition of the potential of the cultural sector to broker opportunities and to work closely with school leadership to develop approaches that align with curriculum and Ofsted priorities, along with suggestions for future support and best practice that can also be applied in a wider context.
The paradox of island evolution
Authors: Burns K. C. 
Published: January 2022

AbstractAimAfter colonising isolated islands, many types of plants and animals undergo extreme morphological diversification. In stark contrast, other island taxa change more subtly and converge evolutionarily on intermediate body size (the island rule). This paradox of island evolution has gone undetected for decades, perhaps because each pattern has been investigated separately using different analytical tools. Here, I investigate the paradox of island evolution in the endemic floras of four oceanic archipelagos in the Southwest Pacific.LocationChatham, Kermadec, Lord Howe & Norfolk Islands.TaxonWoody plants.MethodsI test whether the sizes of ‘solitary endemics’ (species that evolved anagenetically in the absence of co‐occurring endemic congeners) are correlated with their closest mainland ancestors. I also test whether island–mainland size relationships in 'solitary endemics' differ from isometry, as predicted by the island rule. Next, I test whether the stature of ‘co‐occurring endemics’ (closely related, often cladogenetic species) exhibits exaggerated differentiation.ResultsThe stature of 'solitary endemics' was correlated with their mainland relatives, and two out of the four archipelagos showed evidence of the island rule. On the other hand, the stature of 'co‐occurring endemics' was unrelated to their closest mainland relatives and often highly differentiated.Main conclusionsOverall results suggest that the island paradox arises from two distinct evolutionary pathways. Solitary endemics evolve more slowly and often converge on intermediate morphology, while co‐occurring endemics evolve more rapidly and often exhibit highly differentiated morphology. Future work aimed at a better understanding of the mechanisms underpinning the island paradox could help to further unite phylogenetic work on adaptive radiations and macroecological tests of the island rule under a single conceptual umbrella.
Evidence for niche conservatism in alpine beetles under a climate‐driven species pump model
Authors: Schat Jillian , Weng Yi‐Ming , Dudko Roman Yu. , Kavanaugh David H. , Luo Lan , Schoville Sean D. 
Published: January 2022

AbstractAimPast glacial cycles have generated lineage diversity in alpine habitats, acting as a climate‐driven species pump. It is not clear how much this process contributes to ecological diversification of alpine species. To examine this problem, we test patterns of genetic and phenotypic divergence in two co‐distributed species complexes of flightless alpine ground beetles. Greater differentiation in functional traits would indicate that ecological selection is an outcome of oscillating climate change, whereas greater differentiation in non‐ecological traits would indicate niche conservatism.LocationThe Cascades Range and Trinity Mountains of western North America.TaxonNebria paradisiandN.vandykeispecies complexes (Insecta: Coleoptera: Carabidae: Nebriinae).MethodsWe generated genome‐wide single nucleotide polymorphism data and mitochondrial sequence data, as well as morphological and physiological data, to compare populations spanning the range of both species. Phylogenetic and population genetic analyses were used to infer relationships among taxa and populations in each species complex, as well as historical demography. Support vector machines were used to test for classification of taxa and populations based on ecomorphological, ecophysiological and male reproductive traits. Mantel tests were then used to assess associations between phenotypic and genetic divergence among populations.ResultsTheN.vandykeiandN.paradisispecies complexes are each comprised of genetically distinctive populations exhibiting long‐term demographic declines. Each phylogeny supports multiple monophyletic groups with geographical cohesion. By examining phenotypic traits among populations in both species’ complexes, we show that reproductive trait divergence can discriminate species and population status more effectively than ecomorphological or ecophysiological traits. Reproductive and genetic divergence are significantly correlated in theN.vandykeispecies complex.Main ConclusionsWe found limited evidence of ecological selection acting on functional traits. Instead, reproductive and genetic divergence evolved among isolated populations in both species complexes, suggesting niche conservatism may be a common outcome in alpine species diversification.
For neither heat nor water conservation: Body size variation in Atlantic Forest frogs does not follow a general mechanism
Authors: Servino Leonardo Matheus , Verdade Vanessa Kruth , Sawaya Ricardo J. 
Published: January 2022

AbstractAimAnimal body size is recurrently associated with climate. Bergmann's rule proposes that larger endotherms inhabit higher latitudes because higher latitudes are generally colder, and larger body sizes promote heat conservation. However, body size variation of ectotherms has been associated with other climatic variables as anurans in drier environments reach larger sizes for water conservation. We tested whether body size variation of anuran amphibians can be explained by the heat conservation or water conservation hypotheses.LocationBrazilian Atlantic Forest.TaxonAnuran amphibians.MethodsWe selected anurans from different phylogenetic groups. The size was defined by snout‐vent length (SVL) and stoutness. We implemented spatial regressions including morphological dimensions and variables describing temperature and water availability.ResultsOnlyHaddadus binotatushad SVL size negatively associated with temperature, in accordance with the heat conservation hypothesis (HCH).Itapotihyla langsdorffiihad SVL positively associated with temperature, contrary to the HCH.Cycloramphus eleutherodactylushad SVL negatively associated with potential evapotranspiration, in accordance with the water conservation hypothesis (WCH).Thoropa miliaris+T. taophoraandIschnocnema guentherishowed no associations between SVL and climate. Stoutness was poorly associated with climate, with a negative relationship found only inRhinella crucifer+R. ornatain accordance with the WCH.Main conclusionsThe heat conservation and water conservation hypotheses do not offer general explanations for the body size variation in anurans from the Brazilian Atlantic Forest. Natural history, functional and ecological traits are more likely to affect anuran body size and they should be considered in posterior analyses.
Phylogeography and population genetics reveal ring species patterns in a highly polymorphic California lily
Authors: Hernández Adriana I. , Landis Jacob B. , Specht Chelsea D. 
Published: January 2022

AbstractAimNatural selection typically results in the homogenization of reproductive traits, reducing natural variation within populations; thus, highly polymorphic species present unresolved questions regarding the mechanisms that shape and maintain gene flow given a diversity of phenotypes. We used an integrative framework to characterize phenotypic diversity and assess how evolutionary history and population genetics affect the highly polymorphic nature of a California endemic lily.LocationCalifornia, United States.TaxonButterfly mariposa lily, Calochortus venustus (Liliaceae).MethodsWe summarized phenotypic diversity at both metapopulation and subpopulation scales to explore spatial phenotypic distributions. We sampled 174 individuals across the species range representing multiple samples for each population and each phenotype. We used restriction‐site‐associated DNA sequencing (RAD‐Seq) to detect population clusters, gene flow between phenotypes and between populations, infer haplotype networks, and reconstruct ancestral range evolution to infer historical migration and range expansion.ResultsPolymorphic floral traits within the species such as petal pigmentation and distal spots are geographically structured, and inferred evolutionary history is consistent with a ring species pattern involving a complex of populations having experienced sequential change in genetic and phenotypic variation from the founding population. Populations remain interconnected yet have differentiated from each other along a bifurcating south‐to‐north range expansion, consequently indicating parallel evolution towards the white morphotype in the northern range. Thus, our phylogeographical analyses reveal morphological convergence with population genetic cohesion irrespective of phenotypic diversity.Main conclusionsPhenotypic variation in the highly polymorphic Calochortus venustus is not due to genetic differentiation between phenotypes; rather there is genetic cohesion within six geographically defined populations, some of which maintain a high level of within‐population phenotypic diversity. Our results demonstrate that analyses of polymorphic taxa greatly benefit from disentangling phenotype from genotype at various spatial scales. We discuss results in light of ring species concepts and the need to determine the adaptive significance of the patterns we report.
Identification of a glioma functional network from gene fitness data using machine learning
Authors: Xiang Chun‐xiang , Liu Xi‐guo , Zhou Da‐quan , Zhou Yi , Wang Xu , Chen Feng 
Published: January 2022

AbstractGlioblastoma multiforme (GBM) is an aggressive form of brain tumours that remains incurable despite recent advances in clinical treatments. Previous studies have focused on sub‐categorizing patient samples based on clustering various transcriptomic data. While functional genomics data are rapidly accumulating, there exist opportunities to leverage these data to decipher glioma‐associated biomarkers. We sought to implement a systematic approach to integrating data from high throughput CRISPR‐Cas9 screening studies with machine learning algorithms to infer a glioma functional network. We demonstrated the network significantly enriched various biological pathways and may play roles in glioma tumorigenesis. From densely connected glioma functional modules, we further predicted 12 potential Wnt/β‐catenin signalling pathway targeted genes, including AARSD1, HOXB5, ITGA6, LRRC71, MED19, MED24, METTL11B, SMARCB1, SMARCE1, TAF6L, TENT5A and ZNF281. Cox regression modelling with these targets was significantly associated with glioma overall survival prognosis. Additionally, TRIB2 was identified as a glioma neoplastic cell marker in single‐cell RNA‐seq of GBM samples. This work establishes novel strategies for constructing functional networks to identify glioma biomarkers for the development of diagnosis and treatment in clinical practice.
Insulin–glucagon‐like peptide‐1 receptor agonist relay and glucagon‐like peptide‐1 receptor agonist first regimens in individuals with type 2 diabetes: A randomized, open‐label trial study
Authors: Takeshita Yumie , Kita Yuki , Tanaka Takeo , Goto Hisanori , Nakano Yujiro , Teramura Chisato , Enyama Yasufumi , Takamura Toshinari ,   the Establishment of Rationale for Antiaging Diabetic Medicine (ERA‐DM) Study Group
Published: January 2022

AbstractAims/IntroductionGlucagon‐like peptide‐1 receptor agonists (GLP‐1 RA) might be less effective in patients with severe hyperglycemia, because hyperglycemia downregulated the GLP‐1 receptor in an animal study. To examine this hypothesis clinically, we compared the glucose‐lowering effects of GLP‐1 receptor agonist liraglutide with and without prior glycemic control.Materials and MethodsIn an open‐label, parallel trial, participants with poorly controlled type 2 diabetes were recruited and randomized to receive once‐daily insulin therapy, degludec (Insulin–GLP‐1 RA relay group, mean 16.8 ± 11.4 IU/day), for 12 weeks and then liraglutide for 12 weeks or subcutaneous injections of GLP‐1 RA, liraglutide (GLP‐1 RA first group, 0.9 mg), for 24 weeks. The primary efficacy end‐points consisted of changes in the levels of fasting plasma glucose and glycated hemoglobin (HbA1c).ResultsThe median fasting plasma glucose and HbA1c before the study were 210.0 mg/dL and 9.8%, respectively. The levels of fasting plasma glucose and HbA1c significantly decreased in the Insulin–GLP‐1 RA relay group (P < 0.001) and GLP‐1 RA first group (P < 0.001) by week 24, although no intergroup differences were observed. The reduction of HbA1c in the Insulin–GLP‐1 RA relay group tended to be larger than that in the GLP‐1 RA first group in the lowest CPR (C‐peptide immunoreactivity) quartile (P = 0.072). The adverse events consisted of gastrointestinal problems, followed by hypoglycemia.ConclusionsThe GLP‐1 receptor agonist is overall effective without prior glycemic control with insulin in participants with poorly controlled type 2 diabetes. However, in participants with insulinopenic type 2 diabetes, prior glycemic control with insulin might overcome glucose toxicity‐induced GLP‐1 resistance.
Clustering analysis and machine learning algorithms in the prediction of dietary patterns: Cross‐sectional results of the Brazilian Longitudinal Study of Adult Health (ELSA‐Brasil)
Authors: Silva Vanderlei Carneiro , Gorgulho Bartira , Marchioni Dirce Maria , Araujo Tânia Aparecida de , Santos Itamar de Souza , Lotufo Paulo Andrade , Benseñor Isabela Martins 
Published: January 2022

AbstractBackgroundMachine learning investigates how computers can automatically learn. The present study aimed to predict dietary patterns and compare algorithm performance in making predictions of dietary patterns.MethodsWe analysed the data of public employees (n = 12,667) participating in the Brazilian Longitudinal Study of Adult Health (ELSA‐Brasil). The K‐means clustering algorithm and six other classifiers (support vector machines, naïve Bayes, K‐nearest neighbours, decision tree, random forest and xgboost) were used to predict the dietary patterns.ResultsK‐means clustering identified two dietary patterns. Cluster 1, labelled the Western pattern, was characterised by a higher energy intake and consumption of refined cereals, beans and other legumes, tubers, pasta, processed and red meats, high‐fat milk and dairy products, and sugary beverages; Cluster 2, labelled the Prudent pattern, was characterised by higher intakes of fruit, vegetables, whole cereals, white meats, and milk and reduced‐fat milk derivatives. The most important predictors were age, sex, per capita income, education level and physical activity. The accuracy of the models varied from moderate to good (69%–72%).ConclusionsThe performance of the algorithms in dietary pattern prediction was similar, and the models presented may provide support in screener tasks and guide health professionals in the analysis of dietary data.