Morphological Contexts Research Articles

Construction of a Corpus for L2 Derivational Morphology: Based on Construction

This study followed the theoretical framework of Constructional Morphology and proposed a model for constructing an L2 derivational morphology corpus based on affix concordances. This model used morphological series members as keywords and provides examples containing these keywords, aiming to offer rich and systematic language materials for L2 instruction of derivational morphology. Excel and AntConc software were used to analyze the word lists of L2 English textbooks. By examining the distribution of derived words and related affixes, affix concordances that included abundant morphological and syntactic contexts were established. This study suggested that L2 learners should be exposed to more comprehensive and targeted learning resources, so as to deepen their understanding of English derivational morphology.

Deep learning in spatially resolved transcriptfomics: a comprehensive technical view

Spatially resolved transcriptomics (SRT) is a pioneering method for simultaneously studying morphological contexts and gene expression at single-cell precision. Data emerging from SRT are multifaceted, presenting researchers with intricate gene expression matrices, precise spatial details and comprehensive histology visuals. Such rich and intricate datasets, unfortunately, render many conventional methods like traditional machine learning and statistical models ineffective. The unique challenges posed by the specialized nature of SRT data have led the scientific community to explore more sophisticated analytical avenues. Recent trends indicate an increasing reliance on deep learning algorithms, especially in areas such as spatial clustering, identification of spatially variable genes and data alignment tasks. In this manuscript, we provide a rigorous critique of these advanced deep learning methodologies, probing into their merits, limitations and avenues for further refinement. Our in-depth analysis underscores that while the recent innovations in deep learning tailored for SRT have been promising, there remains a substantial potential for enhancement. A crucial area that demands attention is the development of models that can incorporate intricate biological nuances, such as phylogeny-aware processing or in-depth analysis of minuscule histology image segments. Furthermore, addressing challenges like the elimination of batch effects, perfecting data normalization techniques and countering the overdispersion and zero inflation patterns seen in gene expression is pivotal. To support the broader scientific community in their SRT endeavors, we have meticulously assembled a comprehensive directory of readily accessible SRT databases, hoping to serve as a foundation for future research initiatives.

Impacts of high-albedo urban surfaces on outdoor thermal environment across morphological contexts: A case of Tianjin, China

The urban heat island (UHI) effect can exacerbate various environmental challenges related to high temperatures in urban areas. Increasing urban surface albedo is an effective strategy to mitigate UHI. However, the efficacy of high-albedo urban surfaces across varying urban contexts remains poorly understood. In this study, we leverage Urban Weather Generator to systematically simulate the effects of high-albedo roads, walls, and roofs on urban microclimate across Tianjin. Our simulation covers a typical meteorological year, representing typical weather conditions from January to December. Our results reveal that increasing road albedo is more effective in mitigating UHI in fringe areas, whereas increasing wall and roof albedo is more effective in mitigating UHI in central areas. Local climate zones with an urban aspect ratio of about 0.5 can obtain a maximum reduction of road surface temperature (-6 °C) and wall surface temperature (-3 °C). The temperature changes induced by albedo changes show evident seasonal characteristics: the road temperature decreases significantly in summer, while the wall temperature decreases significantly in spring and autumn. Our results could help guide UHI mitigation policies and urban planning in cities hoping to enhance urban surface albedo to balance urban growth and climate resilience.

A platform-independent framework for phenotyping of multiplex tissue imaging data.

Multiplex imaging is a powerful tool to analyze the structural and functional states of cells in their morphological and pathological contexts. However, hypothesis testing with multiplex imaging data is a challenging task due to the extent and complexity of the information obtained. Various computational pipelines have been developed and validated to extract knowledge from specific imaging platforms. A common problem with customized pipelines is their reduced applicability across different imaging platforms: Every multiplex imaging technique exhibits platform-specific characteristics in terms of signal-to-noise ratio and acquisition artifacts that need to be accounted for to yield reliable and reproducible results. We propose a pixel classifier-based image preprocessing step that aims to minimize platform-dependency for all multiplex image analysis pipelines. Signal detection and noise reduction as well as artifact removal can be posed as a pixel classification problem in which all pixels in multiplex images can be assigned to two general classes of either I) signal of interest or II) artifacts and noise. The resulting feature representation maps contain pixel-scale representations of the input data, but exhibit significantly increased signal-to-noise ratios with normalized pixel values as output data. We demonstrate the validity of our proposed image preprocessing approach by comparing the results of two well-accepted and widely-used image analysis pipelines.

Ballet by Pavel Goncharov and Modernism: at the Intersection of Two Methods of One Style

The article explores the creativity work of Pavel Goncharov (1886–1941) – a ballet artist and a painter who is not as well-known among masters of Russian modernism, but is an interesting author of the late 19th to early 20th century, who created a unique series of graphic works dedicated to Russian ballet. By focusing on the artistic characteristics of the modernist style, the author notes that it began its development in architecture, decorative and applied arts, graphics, and extended to choreography, including classical dance. The interaction of related arts (graphics and ballet) led to the formation of synthetic visual images, which are analyzed in the article in morphological, stylistic, and compositional contexts. Using primarily historical and cultural and typological research methods, the author identifies a number of directions in Pavel Goncharov’s visual creativity: character actor images, sketches for the Firebird ballet, autolithographs for Fyodor Lopukhov’s The Greatness of the Universe dance symphony, and book graphics for ballet publications. Analogies are drawn with the aesthetics of the painters of the World of Art movement, whose graphic works included a theatrical concept, manifested in the drawn silhouette imagery, striking poses and gestures, actorly sensibility, and theatricality of costumes. The conclusion is drawn that the dance plasticity of modernism, borrowing many elements of graphic language at the turn of the 19th and 20th centuries, created versatile artistic and stylistic techniques, one example of which is the figurative format of Pavel Goncharov’s works, possessing an individual system of expressive means.

Relationship between Vegetation, Sky View Factor and Thermal Comfort: A Systematic Literature Review

The relationship between urban morphology and thermal conditions has been subject of several scientific studies and, recently, the role of vegetation in this context has been investigated, aiming to understand its contributions to the improvement of thermal comfort in outdoor environments. This study aimed to understand the relationship between urban vegetation present in the sky view factor (FVC) and thermal comfort. A systematic literature review on the subject was carried out by applying an adaptation of the Preferred Reporting Items methodological approach for Systematic Reviews and Meta-Analyses (PRISMA), seeking to guarantee a transparent and replicable work. The evaluated materials were obtained through database searches using the terms vegetation AND “thermal comfort” AND “sky view factor” and selected by criteria defined by the “PICOS” strategy. parameters referring to the main characteristics of the researches and results achieved, through the reading and tabulation of data with the help of electronic spreadsheets. The results obtained highlight the growing interest in the subject in scientific research, but demonstrate a lack of studies in Latin American countries. It is also observed that most studies indicate a positive relationship between vegetation in the FVC and thermal comfort, with the incidence of negative results at night, winter or interference with wind speed. Such scenarios indicate the need for more studies that seek better understand the particularities of the behavior of urban vegetation in different ways. between climatic and morphological contexts.

Reciprocal cell-ECM dynamics generate supracellular fluidity underlying spontaneous follicle patterning

During vertebrate embryogenesis, cell collectives engage in coordinated behavior to form tissue structures of increasing complexity. In the avian skin, assembly into follicles depends on intrinsic mechanical forces of the dermis, but how cell mechanics initiate pattern formation is not known. Here, we reconstitute the initiation of follicle patterning exvivo using only freshly dissociated avian dermal cells and collagen. We find that contractile cells physically rearrange the extracellular matrix (ECM) and that ECM rearrangement further aligns cells. This exchange transforms a mechanically unlinked collective of dermal cells into a continuum, with coherent, long-range order. Combining theory with experiment, we show that this ordered cell-ECM layer behaves as an active contractile fluid that spontaneously forms regular patterns. Our study illustrates a role for mesenchymal dynamics in generating cell-level ordering and tissue-level patterning through a fluid instability-processes that may be at play across morphological symmetry-breaking contexts.

RELATIONSHIP BETWEEN METROLOGICAL PARAMETERS AND VECTOR BORNE DENGUE DISEASE USING ONCOLOGICAL FRACTAL TREATMENT

Dengue is the most vital arboviral disease in humans, which is occurring in tropical and subtropical areas around the world. Dengue fever is itemized as an urban human disease as it spreads easily to urban environmental/ morphological contexts because of the uneven increase of urban population and infectious diseases as a result of climate change. Dengue epidemic cases related to climatic parameters are helpful to monitor and prevent the transmission of dengue fever. Many studies have focused on describing the clinical aspects of dengue outbreak. We bring out the epidemiological study to investigate the dengue fever development and prediction in the Karachi city. This study described the oncological treatment by statistical analysis and fractal rescaled range (R/S) method of the dengue epidemics from January 2001 to December 2020, based on the urban morphological patterns, and climatic variables including temperature and ENSO respectively. The R/S method in oncologists has been carried in two ways, basic oncological/statistical analysis and Fractal dimension adapt to the study the nature of the subtleties of dengue epidemic data, another showing the dynamics of oncological process. Climate parameters are shown that the fractal dimension value revealed a persistency behavior i.e. time series is an increasing, Fractal analysis also confirmed the anti-persistent behavior of dengue for months of September to November and the normality tests specified the robust indication of the intricacy of data. This study will be useful for future researchers working on epidemiology and urban environmental oncological fields to improve and rectify the urban infectious diseases.

Memory for affixes in a long-lag priming paradigm.

Psycholinguistic research on the processing of morphologically complex words has largely focused on debates about how/if lexical stems are recognized, stored, and retrieved. Comparatively little processing research has investigated similar issues for functional affixes. In Word or Lexeme Based Morphology (Aronoff 1994), affixes are not representational units on par with stems or roots. This view is in stark contrast to the claims of linguistic theories like Distributed Morphology (Halle & Marantz 1993), which assign rich representational content to affixes. We conducted a series of eight visual lexical decision studies, evaluating effects of derivational affix priming along with stem priming, identity priming, form priming, and semantic priming at long and short lags. We find robust and consistent affix priming (but not semantic or form priming) with lags up to 33 items, supporting the position that affixes are morphemes, i.e., representational units on par with stems. Intriguingly, we find only weaker evidence for the long-lag stem priming effect found in other studies. We interpret this potential asymmetry in terms of the salience of different morphological contexts for recollection memory.

Unsupervised Phenotype-Based Clustering of Clinicopathologic Features in Cutaneous Melanoma

Pathogenic phenotypes in cutaneous melanoma have been vastly cataloged, although these classifications lack concordance and are confined to either morphological or molecular contexts. In this study, we perform unsupervised k-medoids clustering as a machine learning technique of 2,978 primary cutaneous melanomas at Mass General Brigham and apply this information to elucidate computer-defined subsets within the clinicopathologic domain. We identified five optimally separated clusters of melanoma that occupied two distinct clinicopathologic subspaces: a lower-grade partition associated with common or dysplastic nevi (i.e., nevus-associated melanomas) and a higher-grade partition lacking precursor lesions (i.e., de novo melanomas). Our model found de novo melanomas to be more mitogenic, more ulcerative, and thicker than nevus-associated melanomas, in addition to harboring previously unreported differences in radial and vertical growth phase status. The utilization of mixed clinicopathologic variables, reflective of actual clinical data contained in surgical pathology reports, has the potential to increase the biological relevance of existing melanoma classification schemes and facilitate the discovery of new genomic subtypes.

Bayesian modeling of spatial molecular profiling data via Gaussian process.

The location, timing and abundance of gene expression (both mRNA and proteins) within a tissue define the molecular mechanisms of cell functions. Recent technology breakthroughs in spatial molecular profiling, including imaging-based technologies and sequencing-based technologies, have enabled the comprehensive molecular characterization of single cells while preserving their spatial and morphological contexts. This new bioinformatics scenario calls for effective and robust computational methods to identify genes with spatial patterns. We represent a novel Bayesian hierarchical model to analyze spatial transcriptomics data, with several unique characteristics. It models the zero-inflated and over-dispersed counts by deploying a zero-inflated negative binomial model that greatly increases model stability and robustness. Besides, the Bayesian inference framework allows us to borrow strength in parameter estimation in a de novo fashion. As a result, the proposed model shows competitive performances in accuracy and robustness over existing methods in both simulation studies and two real data applications. The related R/C++ source code is available at https://github.com/Minzhe/BOOST-GP. Supplementary data are available at Bioinformatics online.

Discovery of molecular features underlying the morphological landscape by integrating spatial transcriptomic data with deep features of tissue images.

Profiling molecular features associated with the morphological landscape of tissue is crucial for investigating the structural and spatial patterns that underlie the biological function of tissues. In this study, we present a new method, spatial gene expression patterns by deep learning of tissue images (SPADE), to identify important genes associated with morphological contexts by combining spatial transcriptomic data with coregistered images. SPADE incorporates deep learning-derived image patterns with spatially resolved gene expression data to extract morphological context markers. Morphological features that correspond to spatial maps of the transcriptome were extracted by image patches surrounding each spot and were subsequently represented by image latent features. The molecular profiles correlated with the image latent features were identified. The extracted genes could be further analyzed to discover functional terms and exploited to extract clusters maintaining morphological contexts. We apply our approach to spatial transcriptomic data from different tissues, platforms and types of images to demonstrate an unbiased method that is capable of obtaining image-integrated gene expression trends.

Soils as a useful tool for reconstructing geomorphic dynamics in high mountain environments: The case of the Buscagna stream hydrographic basin (Lepontine Alps)

The soil formation, its development, and its preservation in high mountain environments are largely determined by topography and geomorphological dynamic. Therefore, soil development in alpine areas is often non-linear over time, and characterized by phases of progressive and regressive evolution. The interaction among soil-forming factors is preserved in soils as physical/chemical properties and pedological features. In particular, the action of surface geomorphological processes can be observed as stone lines or sequences of buried surfaces. In this light, exhaustive investigation of soils and paleosols could provide enough information to reconstruct past environmental conditions and spatio-temporal changes in denudation/deposition processes.The main aim of this study is to assess the role of soil as a useful archive for retracing the geomorphological processes that are responsible for the landscape evolution during the Late Holocene in a typical alpine catchment such as the Buscagna stream hydrographic basin (Veglia-Devero Natural Park, Lepontine Alps). The asymmetry in valley slopes, due to lithology and structural control, generates a great variety of geomorphic processes and landforms. Therefore, seven soil profiles were selected along the two slopes, in different morphological contexts, to reveal the influence of the different active geomorphic processes in soil development. Soils were investigated by means of field and laboratory analyses, and geomorphological maps of the area surrounding the profiles were made. On the southeastern slope, characterized by calcschist substratum, the soil profiles are composed of two superimposed pedological units, separated by an instability hiatus. On the northwestern slope, characterized by gneiss and ultramafic rocks, and on the valley bottom, the soils record instability phases in different ways, fitting well with the geomorphological context. In this mountain environment, the close relationship between soil development and geomorphic processes allows us to confirm the role of soil as a useful archive to potentially reconstruct the past geomorphological conditions.

Stød in unexpected morphological contexts in Standard Danish: An experimental approach to sound change in progress

AbstractIn recent years stød has appeared in words where the current phonological and morphological principles of its distribution would exclude it. Thus, a disyllable like [ˈsiːðə]side‘page’ is without stød, also in a compound likebagside‘back page’, but it has lately been heard with stød:. In a controlled experiment, speakers were required to produce compounds consisting of an existing initial word succeeded by a final nonce noun. The results indicate that stød may be spreading in this context. Furthermore, its distribution across the 40 nonce nouns was found to be similar to its distribution among existing nouns in the vocabulary: There are more nonce nouns with stød (i) in the definite singular, (ii) especially with short stressed vowels, and (iii) particularly if the initial word is monosyllabic. A change is apparently underway which will eventually partially suspend a non-stød principle which relieves disyllabic lexemes of stød.

Spatial molecular profiling: platforms, applications and analysis tools.

Molecular profiling technologies, such as genome sequencing and proteomics, have transformed biomedical research, but most such technologies require tissue dissociation, which leads to loss of tissue morphology and spatial information. Recent developments in spatial molecular profiling technologies have enabled the comprehensive molecular characterization of cells while keeping their spatial and morphological contexts intact. Molecular profiling data generate deep characterizations of the genetic, transcriptional and proteomic events of cells, while tissue images capture the spatial locations, organizations and interactions of the cells together with their morphology features. These data, together with cell and tissue imaging data, provide unprecedented opportunities to study tissue heterogeneity and cell spatial organization. This review aims to provide an overview of these recent developments in spatial molecular profiling technologies and the corresponding computational methods developed for analyzing such data.

Morphologically conditioned phonology with two triggers

Morphologically conditioned phonology, where a particular phonological alternation or requirement holds only for a subset of lexical items or in a subset of morphological contexts, is well documented. This paper expands on the literature by examining phonological alternations where two independent triggering morphemes must both be present for a phonological alternation to apply. Several cases of doubly morphologically conditioned phonological alternations, from a diverse set of languages, are described. The existence of morphologically conditioned phonology with two triggers informs our models of the interface between morphology and phonology, in that phonological operations must be able to reference the presence of more than one morpheme simultaneously. A range of possible analyses are considered, including those set in Stratal OT, Indexed Constraint Theory, Cophonology Theory and Cophonologies by Phase Theory. A Cophonologies by Phase account is found to be optimal, where multiple morpheme-specific phonological requirements accumulate and co-trigger alternations within a single spell-out domain.

Evolução holocênica das encostas da bacia do riacho Bruscas, Nordeste do Brasil

Localizada na Província Geológica da Borborema, a bacia do Riacho Bruscas constitui importante amostra do contexto geomorfológico e geológico do setor oriental do Nordeste do Brasil, onde a morfogênese e suas implicações paleoclimáticas são particularmente distintas daquelas que afetam áreas do sul e sudeste do país. O presente trabalho tem como objetivo analisar encostas com coberturas coluviais da bacia do Riacho Bruscas, tomando como base as características dos sedimentos, sua cronologia absoluta (LOE), geometria, estrutura e arranjo estratigráfico. Apesar de fragmentários, disjuntos espacialmente, e originários de intensidades distintas, esses materiais podem fornecer informações importantes sobre a dinâmica geomorfológica que, em última instância, reflete a ação dos componentes paleoambientais sobre a organização das unidades agradacionais do relevo. Os resultados foram agrupados em função dos dados coletados em quatros setores distintos da bacia, onde ocorrem depósitos coluviais, de forma a abranger todos os contextos morfológicos que, na área, resultaram na acumulação de sedimentos de encosta. Os depósitos estudados apresentaram-se confinados em intervalo de tempo que alcança desde o limiar Pleistoceno/Holoceno até a Pequena Idade do Gelo. Contudo, enquanto os depósitos resultantes da reumidificação geral observada ao final do Pleistoceno são ubíquos nas demais áreas do Nordeste semiárido, os depósitos do Holoceno médio e superior apontam para ocorrências mais localizadas, provavelmente relacionadas à ação de eventos pluviais orograficamente condicionados, mais intensos sobre o maciço da Serra da Baixa Verde e outros setores elevados do Planalto da Borborema.

Predicting Near-Future Built-Settlement Expansion Using Relative Changes in Small Area Populations

Advances in the availability of multi-temporal, remote sensing-derived global built-/human-settlements datasets can now provide globally consistent definitions of “human-settlement” at unprecedented spatial fineness. Yet, these data only provide a time-series of past extents and urban growth/expansion models have not had parallel advances at high-spatial resolution. Here our goal was to present a globally applicable predictive modelling framework, as informed by a short, preceding time-series of built-settlement extents, capable of producing annual, near-future built-settlement extents. To do so, we integrated a random forest, dasymetric redistribution, and autoregressive temporal models with open and globally available subnational data, estimates of built-settlement population, and environmental covariates. Using this approach, we trained the model on a 11 year time-series (2000–2010) of European Space Agency (ESA) Climate Change Initiative (CCI) Land Cover “Urban Areas” class and predicted annual, 100m resolution, binary settlement extents five years beyond the last observations (2011–2015) within varying environmental, urban morphological, and data quality contexts. We found that our model framework performed consistently across all sampled countries and, when compared to time-specific imagery, demonstrated the capacity to capture human-settlement missed by the input time-series and the withheld validation settlement extents. When comparing manually delineated building footprints of small settlements to the modelled extents, we saw that the modelling framework had a 12 percent increase in accuracy compared to withheld validation settlement extents. However, how this framework performs when using different input definitions of “urban” or settlement remains unknown. While this model framework is predictive and not explanatory in nature, it shows that globally available “off-the-shelf” datasets and relative changes in subnational population can be sufficient for accurate prediction of future settlement expansion. Further, this framework shows promise for predicting near-future settlement extents and provides a foundation for forecasts further into the future.

ShapeMetrics: A userfriendly pipeline for 3D cell segmentation and spatial tissue analysis

The demand for single-cell level data is constantly increasing within life sciences. In order to meet this demand, robust cell segmentation methods that can tackle challenging in vivo tissues with complex morphology are required. However, currently available cell segmentation and volumetric analysis methods perform poorly on 3D images. Here, we generated ShapeMetrics, a MATLAB-based script that segments cells in 3D and, by performing unbiased clustering using a heatmap, separates the cells into subgroups according to their volumetric and morphological differences. The cells can be accurately segregated according to different biologically meaningful features such as cell ellipticity, longest axis, cell elongation, or the ratio between cell volume and surface area. Our machine learning based script enables dissection of a large amount of novel data from microscope images in addition to the traditional information based on fluorescent biomarkers. Furthermore, the cells in different subgroups can be spatially mapped back to their original locations in the tissue image to help elucidate their roles in their respective morphological contexts. In order to facilitate the transition from bulk analysis to single-cell level accuracy, we emphasize the user-friendliness of our method by providing detailed step-by-step instructions through the pipeline hence aiming to reach users with less experience in computational biology.

Assamese vowels and vowel harmony

AbstractBased on impressionistic and acoustic data, Assamese is described as having a phonological tongue root harmony system, with blocking by certain phonological configurations and over-application in certain morphological contexts. This study explores physical properties of the patterns using ultrasonic imaging to determine whether the impressionistic descriptions match what speakers actually do. Principal components analysis (PCA) determines that most participants produce a contrast in tongue root position in the appropriate contexts, though there is less of an impact on tongue root with greater distance from the triggering vowel. Analysis uses the root mean squared distance (RMSD) calculation to determine whether both blocking and over-application take effect. The blocking results conform to the impressionistic descriptions. With over-application, [e] and [o] are expected; while some speakers clearly produce these vowels, others articulate a vowel that is indeterminant between the expected [e]/[o] and an unexpected [ɛ]/[ɔ]. No speaker consistently showed the expected tongue root position in all contexts, and some speakers appeared to have lost the contrast entirely, yet all are considered to be speakers of the same dialect of Assamese. Whether this (apparent) loss is a consequence of crude research methodologies or accurately reflects what is happening within the language community remains an open question.