Four hundred Greek idiomatic expressions: Ratings for subjective frequency, ambiguity, and decomposability.

Idioms differ from other forms of figurative language because of their dimensions of subjective frequency, ambiguity (possibility of having a literal interpretation), and decomposability (possibility of the idiom's words to assist in its figurative interpretation). This study focuses on the Greek language and aims at providing the first corpus of 400 Greek idioms rated for their dimensions by 113 native Greek students, aged 19 to 39 years. The study aimed at (1) rating all idioms for their degree of subjective frequency, ambiguity, and decomposability, and (2) investigating the relationships between these dimensions. Three different assessments were conducted, during which the participants were asked to evaluate the degree of idioms' subjective frequency, ambiguity, and decomposability. The idioms were selected from a dictionary of Greek idioms titled "Dictionary of Idioms in Modern Greek" (Vlaxopoulos, 2007). This study resulted in the first database of Greek idioms assessed for their dimensions. The intraclass correlation coefficient (ICC) (two-way mixed, absolute agreement) demonstrated high internal consistency in the ratings given for each dimension, for the same idiom, by the different individual raters. Correlational analyses showed that subjective frequency was positively moderately correlated with decomposability, and positively weakly correlated with ambiguity, while decomposability was positively moderately correlated with ambiguity.

Impact of Climate on Soil Organic Matter Composition in Soils of Tropical Volcanic Regions Revealed by EGA-MS and Py-GC/MS.

Soil organic matter (SOM) crucially influences the global carbon cycle, yet its molecular composition and determinants are understudied, especially for tropical volcanic regions. We investigated how SOM compounds change in response to climate, vegetation, soil horizon, and soil properties and the relationship between SOM composition and microbial decomposability in Tanzanian and Indonesian volcanic regions. We collected topsoil (0-15 cm) and subsoil (20-40 cm) horizons (n = 22; pH: 4.6-7.6; SOC: 10-152 g kg-1) with undisturbed vegetation and wide mean annual temperature and moisture ranges (14-26 °C; 800-3300 mm) across four elevational transects (340-2210 m asl.). Evolved gas analysis-mass spectrometry (EGA-MS) documented a simultaneous release of SOM compounds and clay mineral dehydroxylation. Subsequently applying double-shot pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) at 200 and 550 °C, we detailed the molecular composition of topsoil and subsoil SOM. A minor portion (2.7 ± 1.9%) of compounds desorbed at 200 °C, limiting its efficacy for investigating overall SOM characteristics. Pyrolyzed SOM closely aligns with the intermediate decomposable SOM pool, with most pyrolysates (550 °C) originating from this pool. Pyrolysates composition suggests tropical SOM is mainly microbial-derived and subsoil contains more degraded compounds. Higher litter inputs and attenuated SOM decomposition due to cooler temperatures and lower soil pH (<5.5) produce less-degraded SOM at higher elevations. Redundancy analyses revealed the crucial role of active Al/Fe (oxalate-extractable Al/Fe), abundant in low-temperature/high-moisture conditions, in stabilizing these less-degraded components. Our findings provide new insights into SOM molecular composition and its determinants, critical for understanding the carbon cycle in tropical ecosystems.

Vaccination-Route-Dependent Adjuvanticity of Antigen-Carrying Nanoparticles for Enhanced Vaccine Efficacy.

Vaccination-route-dependent adjuvanticity was identified as being associated with the specific features of antigen-carrying nanoparticles (NPs) in the present work. Here, we demonstrated that the mechanical properties and the decomposability of NP adjuvants play key roles in determining the antigen accessibility and thus the overall vaccine efficacy in the immune system when different vaccination routes were employed. We showed that soft nano-vaccines were associated with more efficient antigen uptake when administering subcutaneous (S.C.) vaccination, while the slow decomposition of hard nano-vaccines promoted antigen uptake when intravenous (I.V.) vaccination was employed. In comparison to the clinically used aluminum (Alum) adjuvant, the NP adjuvants were found to stimulate both humoral and cellular immune responses efficiently, irrespective of the vaccination route. For vaccination via S.C. and I.V. alike, the NP-based vaccines show excellent protection for mice from Staphylococcus aureus (S. aureus) infection, and their survival rates are 100% after lethal challenge, being much superior to the clinically used Alum adjuvant.

Processing figurative language: Evidence from native and non-native speakers of English.

In recent research on figurative phrases, factors (e.g., familiarity, transparency, meaning, and decomposability) have played a significant influence on how native and non-native English speakers (various L1 and L1 Arabic) acquire, process, and comprehend figurative language. These factors are not always described and operationalized precisely and are frequently considered autonomous. This study explores these factors in terms of language users' ratings and their abilities to accurately infer meaning from a variety of familiar English and translated idioms and novel metaphors. A total of 123 participants from various language groups engaged in this study. The findings showed that familiarity is a strong predictor of transparency. In the ability to infer the meaning correctly, the best-fit model included an interaction between transparency and familiarity. The findings showed that guessing the meaning correctly led to a greater increase in the scores of transparency and decomposability. We explore how these factors work together to enable speakers to infer the meaning of both known and new figurative words at various levels. These results have significant implications for the learning and teaching of figurative phrases in the English as a foreign language (EFL) context, as they indicate variables that may make a figurative phrase valuable in terms of teaching time and effort.

Three source-partitioning of CO2 fluxes based on a dual-isotope approach to investigate interactions between soil organic carbon, glucose and straw.

Inputs of available organic materials into soil alter the decomposition of soil organic matter (SOM), a process called priming effect. Organic carbon (C) inputs in terrestrial ecosystems are common from various sources (e.g. rhizodeposits, plant residues, microbial necromass) simultaneously, but their interactions as well as mutual effects on SOM decomposition are unknown because multisource partitioning of pools and fluxes was not available. A dual-isotope approach (identical materials except for straw being possessed two 13C abundances) was adopted to partition total CO2 emission from three C sources: SOM, glucose and straw. Cumulative CO2 efflux was quantified into straw-derived (558 µg C g-1), glucose-derived (480 µg C g-1) and SOM-derived (58 µg C g-1) CO2 during the first 7 days of incubation. Glucose or straw addition induced positive SOM priming, whereas glucose combined with straw resulted in higher SOC loss than that induced by single addition of glucose or straw after day 7. The Spearman's correlation showed that the interactions between glucose and straw shifted from increased CO2 evolved during their intensive decomposition (days 1 to 3) to mutual constraint on mineralization during the late stage (days 5 to 7). This study provides evidences for the suitability of the dual-isotope approach to partition multiple sources of CO2 fluxes and C pools, and evaluates their individual or mutual contributions to SOM priming, thus, implicating C sequestration in terrestrial ecosystems.

Digging the channels of inheritance: On how to distinguish between cultural and biological inheritance.

Theories of cultural evolution rest on the assumption that cultural inheritance is distinct from biological inheritance. Cultural and biological inheritance are two separate so-called channels of inheritance, two sub-systems of the sum total of developmental resources travelling in distinct ways between individual agents. This paper asks: what justifies this assumption? In reply, a philosophical account is offered that points at three related but distinct criteria that (taken together) make the distinction between cultural and biological inheritance not only precise but also justify it as real, i.e. as ontologically adequate. These three criteria are (i) the autonomy of cultural change, (ii) the near-decomposability of culture and (iii) differences in temporal order between cultural and biological inheritance. This article is part of the theme issue 'Foundations of cultural evolution'.

Secondary metabolites have more influence than morphophysiological traits on litter decomposability across genotypes of Arabidopsis thaliana.

Although interspecific variation in plant phenotype is recognised to impact afterlife processes such as litter decomposability, it is still unclear which traits and selection pressures explain these relationships. Examining intraspecific variation is crucial to identify and compare trait effects on decomposability, and investigate the potential role of natural selection. We studied the genetic variability and relationships between decomposability, plant traits typically related to decomposability at species level (morphophysiological traits), and leaf metabolites among a set of genotypes of Arabidopsis thaliana grown under controlled conditions. We also investigated correlations between decomposability and environmental variables at genotypes collection site. We investigated the genetic architecture of decomposability with genome-wide association studies (GWAS). There was large genetic variability in decomposability that was correlated with precipitation. Morphophysiological traits had a minor effect, while secondary metabolites, especially glucosinolates, were correlated with decomposability. Consistently, GWAS suggested that genes and metabolites related to the composition of cell membranes and envelopes control the variation of decomposability across genotypes. Our study suggests that decomposability varies within species as a result of metabolic adaptation to climate. Our findings highlight that subtle variations of defence-related metabolites like glucosinolates may strongly influence after-life processes such as decomposability.

Successional trajectories of soil bacterial communities in mine tailings: The role of plant functional traits.

Plant species identity is assumed to be a major driver of belowground microbial diversity and composition. However, diagnosing which plant functional traits are responsible for shaping microbial communities remains elusive. Primary succession on barren metalliferous mining substrates was selected as the framework to study above-belowground interactions, and plant functional traits that lead the successional trajectories of soil bacterial communities were identified. The impact of the plant functional group (i.e. trees, shrubs, dwarf shrubs, perennial grasses), a trait integrating the life span and morphological structure, on the bacterial primary succession was monitored. Bacterial diversity and composition was estimated along plant size gradients including over 90 scattered patches ranging from seedlings to mature multispecific patches. Soil bacterial diversity was affected by heavy metals levels and increased towards higher resource availability underneath mature patches, with stress-tolerant heterotrophs and phototrophs being replaced by competitive heterotrophs. The plant functional group modulated these general patterns and shrubs had the greatest impact belowground by inducing the largest increase in soil fertility. Functional traits related to leaf decomposability and root architecture further determined the composition and structure of bacterial communities. These results underline the importance of plant functional traits in the assembly of soil bacterial communities, and can help guiding restoration of degraded lands.

Reusable building blocks in biological systems.

One of the most widely recognized features of biological systems is their modularity. The modules that constitute biological systems are said to be redeployed and combined across several conditions, thus acting as building blocks. In this work, we analyse to what extent are these building blocks reusable as compared with those found in randomized versions of a system. We develop a notion of decompositions of systems into phenotypic building blocks, which allows them to overlap while maximizing the number of times a building block is reused across several conditions. Different biological systems present building blocks whose reusability ranges from single use (e.g. condition specific) to constitutive, although their average reusability is not always higher than random equivalents of the system. These decompositions reveal a distinct distribution of building block sizes in real biological systems. This distribution stems, in part, from the peculiar usage pattern of the elements of biological systems, and constitutes a new angle to study the evolution of modularity.

Relationships among leaf functional traits, litter traits, and mass loss during early phases of leaf litter decomposition in 12 woody plant species.

Litter 'quality' or decomposability has historically been estimated through measuring chemical attributes, such as concentrations of nitrogen or 'lignin'. More recently, foliar functional traits, which may incorporate indications of the physical structures of tissues, have been found to correlate with litter mass loss rates. However, these traits may not be adequate to predict early rates of mass loss, in which two factors are crucial: the amount of material quickly lost through leaching, and the ease of access of decomposer organisms to the more labile tissues in the interior of the litter. We investigated relationships among physical and chemical traits in foliage and litter of 12 species native to British Columbia and then observed how these traits related to mass loss during the first 3 months (Phase I) and between 3 and 12 months (Phase II). Novel traits measured in this study include cuticle thickness, litter leaching loss, and litter water uptake. Foliar and litter traits both co-varied along spectra, but several chemical traits, such as nitrogen concentration, changed from foliage to litter, i.e., during senescence. Phase I mass loss was best predicted by leaching loss and traits relating to leaching, such as cuticle thickness and specific leaf area. Phase II mass loss was predicted by traits that may relate to decomposer access and activity, such as leaf dry matter content and foliar nitrogen. Physical traits predicted mass loss as well or better than chemical traits, suggesting that physical characteristics of litter are important in determining early rates of decomposition.

A spectrum of modularity in multi-functional gene circuits.

A major challenge in systems biology is to understand the relationship between a circuit's structure and its function, but how is this relationship affected if the circuit must perform multiple distinct functions within the same organism? In particular, to what extent do multi-functional circuits contain modules which reflect the different functions? Here, we computationally survey a range of bi-functional circuits which show no simple structural modularity: They can switch between two qualitatively distinct functions, while both functions depend on all genes of the circuit. Our analysis reveals two distinct classes: hybrid circuits which overlay two simpler mono-functional sub-circuits within their circuitry, and emergent circuits, which do not. In this second class, the bi-functionality emerges from more complex designs which are not fully decomposable into distinct modules and are consequently less intuitive to predict or understand. These non-intuitive emergent circuits are just as robust as their hybrid counterparts, and we therefore suggest that the common bias toward studying modular systems may hinder our understanding of real biological circuits.

Normative data for idiomatic expressions.

Idiomatic expressions such as kick the bucket or go down a storm can differ on a number of internal features, such as familiarity, meaning, literality, and decomposability, and these types of features have been the focus of a number of normative studies. In this article, we provide normative data for a set of Bulgarian idioms and their English translations, and by doing so replicate in a Slavic language the relationships between the ratings previously found in Romance and Germanic languages. Additionally, we compared whether collecting these types of ratings in between-subjects or within-subjects designs affects the data and the conclusions drawn, and found no evidence that design type affects the final outcome. Finally, we present the results of a meta-analysis that summarizes the relationships found across the literature. As in many previous individual studies, we found that familiarity correlates with a number of other features; however, such studies have shown conflicting results concerning literality and decomposability ratings. The meta-analysis revealed reliable relationships of decomposability with a number of other measures, such as familiarity, meaning, and predictability. Conversely, literality was shown to have little to no relationship with any of the other subjective ratings. The implications for these relationships in the context of the wider experimental literature are discussed, with a particular focus on the importance of attaining familiarity ratings for each sample of participants in experimental work.

Comparative Analysis of Wavelet-based Feature Extraction for Intramuscular EMG Signal Decomposition.

BACKGROUND: Electromyographic (EMG) signal decomposition is the process by which an EMG signal is decomposed into its constituent motor unit potential trains (MUPTs). A major step in EMG decomposition is feature extraction in which each detected motor unit potential (MUP) is represented by a feature vector. As with any other pattern recognition system, feature extraction has a significant impact on the performance of a decomposition system. EMG decomposition has been studied well and several systems were proposed, but feature extraction step has not been investigated in detail. OBJECTIVE: Several EMG signals were generated using a physiologically-based EMG signal simulation algorithm. For each signal, the firing patterns of motor units (MUs) provided by the simulator were used to extract MUPs of each MU. For feature extraction, different wavelet families including Daubechies (db), Symlets, Coiflets, bi-orthogonal, reverse bi-orthogonal and discrete Meyer were investigated. Moreover, the possibility of reducing the dimensionality of MUP feature vector is explored in this work. The MUPs represented using wavelet-domain features are transformed into a new coordinate system using Principal Component Analysis (PCA). The features were evaluated regarding their capability in discriminating MUPs of individual MUs. RESULTS: Extensive studies on different mother wavelet functions revealed that db2, coif1, sym5, bior2.2, bior4.4, and rbior2.2 are the best ones in differentiating MUPs of different MUs. The best results were achieved at the 4th detail coefficient. Overall, rbior2.2 outperformed all wavelet functions studied; nevertheless for EMG signals composed of more than 12 MUPTs, syms5 wavelet function is the best function. Applying PCA slightly enhanced the results.

Root structure-function relationships in 74 species: evidence of a root economics spectrum related to carbon economy.

Although fine roots are important components of the global carbon cycle, there is limited understanding of root structure-function relationships among species. We determined whether root respiration rate and decomposability, two key processes driving carbon cycling but always studied separately, varied with root morphological and chemical traits, in a coordinated way that would demonstrate the existence of a root economics spectrum (RES). Twelve traits were measured on fine roots (diameter ≤ 2 mm) of 74 species (31 graminoids and 43 herbaceous and dwarf shrub eudicots) collected in three biomes. The findings of this study support the existence of a RES representing an axis of trait variation in which root respiration was positively correlated to nitrogen concentration and specific root length and negatively correlated to the root dry matter content, lignin : nitrogen ratio and the remaining mass after decomposition. This pattern of traits was highly consistent within graminoids but less consistent within eudicots, as a result of an uncoupling between decomposability and morphology, and of heterogeneity of individual roots of eudicots within the fine-root pool. The positive relationship found between root respiration and decomposability is essential for a better understanding of vegetation-soil feedbacks and for improving terrestrial biosphere models predicting the consequences of plant community changes for carbon cycling.

The complexity of divisibility.

We address two sets of long-standing open questions in linear algebra and probability theory, from a computational complexity perspective: stochastic matrix divisibility, and divisibility and decomposability of probability distributions. We prove that finite divisibility of stochastic matrices is an NP-complete problem, and extend this result to nonnegative matrices, and completely-positive trace-preserving maps, i.e. the quantum analogue of stochastic matrices. We further prove a complexity hierarchy for the divisibility and decomposability of probability distributions, showing that finite distribution divisibility is in P, but decomposability is NP-hard. For the former, we give an explicit polynomial-time algorithm. All results on distributions extend to weak-membership formulations, proving that the complexity of these problems is robust to perturbations.

The soil microbial community predicts the importance of plant traits in plant-soil feedback.

Reciprocal interaction between plant and soil (plant-soil feedback, PSF) can determine plant community structure. Understanding which traits control interspecific variation of PSF strength is crucial for plant ecology. Studies have highlighted either plant-mediated nutrient cycling (litter-mediated PSF) or plant-microbe interaction (microbial-mediated PSF) as important PSF mechanisms, each attributing PSF variation to different traits. However, this separation neglects the complex indirect interactions between the two mechanisms. We developed a model coupling litter- and microbial-mediated PSFs to identify the relative importance of traits in controlling PSF strength, and its dependency on the composition of root-associated microbes (i.e. pathogens and/or mycorrhizal fungi). Results showed that although plant carbon: nitrogen (C : N) ratio and microbial nutrient acquisition traits were consistently important, the importance of litter decomposability varied. Litter decomposability was not a major PSF determinant when pathogens are present. However, its importance increased with the relative abundance of mycorrhizal fungi as nutrient released from the mycorrhizal-enhanced litter production to the nutrient-depleted soils result in synergistic increase of soil nutrient and mycorrhizal abundance. Data compiled from empirical studies also supported our predictions. We propose that the importance of litter decomposability depends on the composition of root-associated microbes. Our results provide new perspectives in plant invasion and trait-based ecology.

Experimental evidence that the Ornstein-Uhlenbeck model best describes the evolution of leaf litter decomposability.

Leaf litter decomposability is an important effect trait for ecosystem functioning. However, it is unknown how this effect trait evolved through plant history as a leaf 'afterlife' integrator of the evolution of multiple underlying traits upon which adaptive selection must have acted. Did decomposability evolve in a Brownian fashion without any constraints? Was evolution rapid at first and then slowed? Or was there an underlying mean-reverting process that makes the evolution of extreme trait values unlikely? Here, we test the hypothesis that the evolution of decomposability has undergone certain mean-reverting forces due to strong constraints and trade-offs in the leaf traits that have afterlife effects on litter quality to decomposers. In order to test this, we examined the leaf litter decomposability and seven key leaf traits of 48 tree species in the temperate area of China and fitted them to three evolutionary models: Brownian motion model (BM), Early burst model (EB), and Ornstein-Uhlenbeck model (OU). The OU model, which does not allow unlimited trait divergence through time, was the best fit model for leaf litter decomposability and all seven leaf traits. These results support the hypothesis that neither decomposability nor the underlying traits has been able to diverge toward progressively extreme values through evolutionary time. These results have reinforced our understanding of the relationships between leaf litter decomposability and leaf traits in an evolutionary perspective and may be a helpful step toward reconstructing deep-time carbon cycling based on taxonomic composition with more confidence.

Modular and hierarchically modular organization of brain networks.

Brain networks are increasingly understood as one of a large class of information processing systems that share important organizational principles in common, including the property of a modular community structure. A module is topologically defined as a subset of highly inter-connected nodes which are relatively sparsely connected to nodes in other modules. In brain networks, topological modules are often made up of anatomically neighboring and/or functionally related cortical regions, and inter-modular connections tend to be relatively long distance. Moreover, brain networks and many other complex systems demonstrate the property of hierarchical modularity, or modularity on several topological scales: within each module there will be a set of sub-modules, and within each sub-module a set of sub-sub-modules, etc. There are several general advantages to modular and hierarchically modular network organization, including greater robustness, adaptivity, and evolvability of network function. In this context, we review some of the mathematical concepts available for quantitative analysis of (hierarchical) modularity in brain networks and we summarize some of the recent work investigating modularity of structural and functional brain networks derived from analysis of human neuroimaging data.

Hierarchical modularity in human brain functional networks.

The idea that complex systems have a hierarchical modular organization originated in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or "modules-within-modules") decomposition of human brain functional networks, measured using functional magnetic resonance imaging in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I = 0.63. The largest five modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions.