Idiosyncratic Features Research Articles

COVID-induced economic uncertainty, tasks and occupational demand.

Using monthly online job postings data at the occupation-US-state level in January–December 2020, we provide novel evidence on how COVID-induced economic uncertainty has impacted the occupational composition of US labour demand. The effects are identified by exploiting monthly variation in country-level uncertainty along with pre-COVID differences in shares of occupation-state pairs in occupational country-wide employment and occupational task content. Some of the effects are consistent with the secular and episodic aspects of routine-biased technological change (RBTC) leading to job polarisation and growing complementarity between cognitive analytical and interactive tasks. Interestingly, however, other effects are seemingly at odds with RBTC-induced job polarisation and rather rationalised by idiosyncratic features of the shock (e.g. health emergency) and responses to it (e.g. social distancing, lockdowns). Although additional evidence points to high persistence of most of these effects in 2020, further research in this direction would shed light on whether the effects will persist through the post-COVID era or phase out.

Stimulus-specific random effects inflate false-positive classification accuracy in multivariate-voxel-pattern-analysis: A solution with generalized mixed-effects modelling

When conducting multivariate-voxel pattern analysis (MVPA), researchers typically compute the average accuracy for each subject and statistically test if the average accuracy is different from the chance level across subjects (by-subject analysis). We argue that this traditional by-subject analysis leads to inflated Type-1 error rates, regardless of the type of machine learning method used (e.g., support vector machine). This is because by-subject analysis does not consider the variance attributed to the idiosyncratic features of the stimuli that have a common influence on all subjects (i.e., the random stimulus effect). As a solution, we proposed the use of generalized linear mixed-effects modelling to evaluate average accuracy. This method only requires post-classification data (i.e., it does not consider the type of classification methods used) and is easily implemented in the analysis pipeline with common statistical software (SPSS, R, Python, etc.). Using both statistical simulation and real fMRI data analysis, we demonstrated that the traditional by-subject method indeed increases Type-1 error rates to a considerable degree, while generalized mixed-effects modelling that incorporates random stimulus effects can indeed maintain the nominal Type-1 error rates.

Transgressive Spatiality and Multiple Temporality in Jim Crace’s Arcadia

Arcadia (1992), Jim Crace’s most distinctively urban novel, bears the idiosyncratic features of its author’s writing: it is a deceptively simple story of vague geographical and historical setting conceived as a parable of the current world concerns, it portrays a community in a transitional moment of its existence, and it places special emphasis on spatial representations of its fictitious environment which assume metaphorical properties that convey the story’s rich ideas. Moreover, as a writer focusing on moral issues with a leftist political outlook, Crace has been consistent in his criticism of the neoliberal market economy and its negative impacts on communal values, a view which is also voiced in the novel. This paper makes use of the theoretical premises of Transmodernism as well as analytical tools of phenomenologically focused geocriticism to demonstrate that Arcadia can be subsumed within so-called transmodern fiction. This critique of globalized capitalism is carried out through sites Eric Prieto terms as the entre-deux, the in-between. Accordingly, the paper attempts to demonstrate how the novel’s liminal and heterogeneous places display non-linear and complexly interrelated temporalities which are indicative of their role within the city’s progress.

The Character of the Greek Revolution of 1821

The article explains the social conditions and changes that were taking place in the Balkans during the Ottoman Empire. These changes were slow in the 15th and 16th centuries, became somewhat faster during the 17th, and accelerated in the last quarter of the 18th century. That is the period of the Industrial Revolution and the domination of capitalism in Western Europe. The article details this transformation and the maturation of the rupture conditions within the Ottoman Empire that gave rise to the Greek Revolution of 1821. Particular attention is paid to the emerging social classes and their distinct roles in the revolution. The article concludes by arguing that although the Greek Revolution of 1821 possesses its idiosyncratic features, nevertheless it bears notable similarities to the French Revolution.

How do natural environments shape adaptive cognition across the lifespan?

How does human cognition adapt to idiosyncratic features of our real-world experiences across our lifetimes? The dynamic interaction between individuals and their natural environments is rarely the focus of study within cognitive science, but I argue that a more ecological approach will be critical for advancing developmental science and revealing the adaptive nature of cognition.

Identification and Expression Analysis of LncRNAs Reveal the Immune Mechanism of Visceral White-Nodules Disease Resistance in Large Yellow Croaker.

Long non-coding RNAs (lncRNAs) have several known functions in fish growth processes and signal transduction, but their possible roles in response to bacterial diseases remain largely unresolved. In this study, we report a comprehensive cold-water bacterial disease-responsive lncRNA expression profile for understanding the transcriptional regulatory mechanisms of visceral white-nodules disease resistance in large yellow croaker. A total of 2534 high-confidence lncRNAs were identified by a rigorous filtering pipeline as a basic sequence set for comparative transcriptional analysis. In addition, a total of 10,200 lncRNA-mRNA pairs with high correlation coefficients were identified by expressions level correlation analysis, including non-redundant 381 DE lncRNAs and 2590 differential expressed genes. MSTRG_11084_1 and MSTRG_20402_1 were linked to a large number of target genes and may be involved in important functions in immune regulation. We further revealed the conserved and idiosyncratic features of the disease response process between the technical control strain (TCS) and the resistant strain (RS). Immune-related pathways were enriched in GO terms and KEGG pathways, among which cytokine-cytokine receptor interaction, MAPK signaling pathway, and NF-kappa B signaling pathway may play a key role in VWND resistance in large yellow croaker. Protein-protein interaction network (PPI) analysis revealed that immune-related target genes such as il-10, met, acta2, myc, cav1, and ntrk1, as well as growth and metabolism-related target genes such as pik3r2, igf1, sc5d, hmgcr, and lss were considered the main hub genes. This study represents the first characterization of lncRNAs involved in VWND resistance in large yellow croaker and provides new clues for elucidating the disease response mechanism of large yellow croaker.

Registration based assessment of femoral torsion for rotational osteotomies based on the contralateral anatomy

BackgroundComputer-assisted techniques for surgical treatment of femoral deformities have become increasingly important. In state-of-the-art 3D deformity assessments, the contralateral side is used as template for correction as it commonly represents normal anatomy. Contributing to this, an iterative closest point (ICP) algorithm is used for registration. However, the anatomical sections of the femur with idiosyncratic features, which allow for a consistent deformity assessment with ICP algorithms being unknown. Furthermore, if there is a side-to-side difference, this is not considered in error quantification.The aim of this study was to analyze the influence and value of the different sections of the femur in 3D assessment of femoral deformities based on the contralateral anatomy.Material and methods3D triangular surface models were created from CT of 100 paired femurs (50 cadavers) without pathological anatomy. The femurs were divided into sections of eponymous anatomy of a predefined percentage of the whole femoral length. A surface registration algorithm was applied to superimpose the ipsilateral on the contralateral side. We evaluated 3D femoral contralateral registration (FCR) errors, defined as difference in 3D rotation of the respective femoral section before and after registration to the contralateral side. To compare this method, we quantified the landmark-based femoral torsion (LB FT). This was defined as the intra-individual difference in overall femoral torsion using with a landmark-based method.ResultsContralateral rotational deviation ranged from 0° to 9.3° of the assessed femoral sections, depending on the section. Among the sections, the FCR error using the proximal diaphyseal area for registration was larger than any other sectional error. A combination of the lesser trochanter and the proximal diaphyseal area showed the smallest error. The LB FT error was significantly larger than any sectional error (p < 0.001).ConclusionWe demonstrated that if the contralateral femur is used as reconstruction template, the built-in errors with the registration-based approach are smaller than the intraindividual difference of the femoral torsion between both sides. The errors are depending on the section and their idiosyncratic features used for registration. For rotational osteotomies a combination of the lesser trochanter and the proximal diaphyseal area sections seems to allow for a reconstruction with a minimal error.

Does utilizing smart contracts induce a financial connectedness between Ethereum and non-fungible tokens?

The majority of NFTs utilize the Ethereum blockchain platform to facilitate smart contracts. In this paper, we execute various econometric analyses to determine if this technical dependence induces a financial linkage to the risk, return, and prices of assets. For robustness, we also test the same relation between Bitcoin and NFTs. Empirical analyses are conducted through SADF bubbles test, DCC-GARCH time-varying correlation analysis, Bootstrap causality tests and spillover analysis. According to the results of various price, return, and volatility analyses, we find that NFTs do not demonstrate idiosyncratic features in their price developments and thus they cannot be considered as a separate asset class. Additionally, NFTs do not possess a specific financial linkage with Ethereum from using its infrastructure. Finally, we suggest NFT investors use alternative financial instruments, rather than Ether and Bitcoin in portfolio diversification, due to the presence of significant time-varying relationships and interactions.

Song authorship attribution: a lyrics and rhyme based approach

In this work, we apply authorship attribution to a large-scale corpus of song lyrics. As a sub-category of poetry, song lyrics embody cultural elements as well as stylistic attributes that are not present in prose. We draw attention to special characteristics such as repetitive sound patterns and rhyme based structures in lyrics that can be key to ownership, and present opportunities that cannot be employed for authorship attribution of other types of text such as tweets, emails, and blog posts. We first create a new balanced, large-scale data set of 12,000 song lyrics from 120 different artists. We propose CNN models for authorship attribution on this song lyric data set, in order to use structural information included in the lyrics, similarly to image classification. We conduct experiments at the character and sub-word levels that mostly reflect positional information. In addition, we use phoneme level features, which intrinsically involve attributes such as repetitions, rhyme, and meter, and represent elements unique to verse-based textual compositions. We attempt to discover idiosyncratic features and consequently author and genre associations by working with variants of CNN architectures that have been successfully used in other text classification domains. Our architecture choice results in a particular focus on lyric attributes residing in neighboring regions, since CNNs fail to apprehend long term textual dependencies. Finally, we empirically evaluate our results in comparison with the findings of previous test classification research from different domains.

Within- and between-subject consistency of perceptual segmentation in periodic noise: A combined behavioral tapping and EEG study.

It is remarkable that human listeners can perceive periodicity in noise, as the isochronous repetition of a particular noise segment is not accompanied by salient physical cues in the acoustic signal. Previous research suggested that listeners rely on short temporally local and idiosyncratic features to perceptually segment periodic noise sequences. The present study sought to test this assumption by disentangling consistency of perceptual segmentation within and between listeners. Presented periodic noise sequences either consisted of seamless repetitions of a 500-ms segment or of repetitions of a 200-ms segment that were interleaved with 300-ms portions of random noise. Both within- and between-subject consistency was stronger for interleaved (compared with seamless) periodic sequences. The increased consistency likely resulted from reduced temporal jitter of potential features used for perceptual segmentation when the recurring segment was shorter and occurred interleaved with random noise. These results support the notion that perceptual segmentation of periodic noise relies on subtle temporally local features. However, the finding that some specific noise sequences were segmented more consistently across listeners than others challenges the assumption that the features are necessarily idiosyncratic. Instead, in some specific noise samples, a preference for certain spectral features is shared between individuals.

Les Wicksell, la population et l’égalité des sexes en Suède

This paper considers Anna Bugge Wicksell use of economic arguments in her fight for gender equality. Specific attention is paid to the intersection of gender issues with the ‘population question’—or the Swedish national preoccupation with fertility rates that dominated popular discussion from the 1880s through the 1930s. We first outline Knut Wicksell’s contributions to the economics of population. Next, we consider Bugge Wicksell’s writings as they relate to population, equal education, marital property rights, and women’s labor conditions. The persistence of the Wicksells’ ideas through to the next generation of social reformers is examined using the specific case of Alva and Gunnar Myrdal’s Kris i befolkningsfrågan (1934). The discussion illustrates several themes common to the historiographic literature on the contributions of women to economic thought. First, that women often worked on practical and gendered issues is one reason their work has gone unrecognized; this effect is compounded when women write solely for the popular press. Second, the ability of women to make recognized contributions to economic thought was often dependent on idiosyncratic features of their personal relationships as well as influenced by the broader socio-cultural context. Third, considering the production of extra-academic knowledge makes clear that women’s contributions to social debates were not peripheral but had a direct influence on policy.

Structural evolution of international crop trade networks

Food security is a critical issue closely linked to human being. With the increasing demand for food, international trade has become the main access to supplementing domestic food shortages, which not only alleviates local food shocks, but also exposes economies to global food crises. In this paper, we construct four temporal international crop trade networks (iCTNs) based on trade values of maize, rice, soybean and wheat, and describe the structural evolution of different iCTNs from 1993 to 2018. We find that the size of all the four iCTNs expanded from 1993 to 2018 with more participants and larger trade values. Our results show that the iCTNs not only become tighter according to the increasing in network density and clustering coefficient, but also get more similar. We also find that the iCTNs are not always disassortative, unlike the world cereal trade networks and other international commodity trade networks. The degree assortative coefficients depend on degree directions and crop types. The analysis about assortativity also indicates that economies with high out-degree tend to connect with economies with low in-degree and low out-degree. Additionally, we compare the structure of the four iCTNs to enhance our understanding of the international food trade system. Although the overall evolutionary patterns of different iCTNs are similar, some crops exhibit idiosyncratic trade patterns. It highlights the need to consider different crop networks’ idiosyncratic features while making food policies. Our findings about the dynamics of the iCTNs play an important role in understanding vulnerabilities in the global food system.

Preservation technology investment and carbon abatement strategies in a supplier-retailer cold chain based on a differential game

Against the background of a low-carbon economy and the rising environmental awareness, extensive attention has been paid to carbon emissions in the cold chain in academic research and practice. In cold chain operations, consumers’ preference for freshness is also growing, which motivates the investment in preservation technology to improve the freshness of perishable products. However, further investment in preservation technology also increases carbon emissions. Considering these idiosyncratic features in cold chains, we apply a differential game model to examine cold chain members’ preservation technology investment and carbon abatement behaviors from a long-term horizon and dynamic perspective. The equilibrium strategies of the cold chain were analyzed and compared under four different scenarios, numerical experiments were implemented to verify the theoretical results, and a sensitivity analysis was performed to identify further insights. The results indicate that the trajectory of the supplier’s preservation technology level is monotonic and that the trajectory of the carbon abatement level changes direction no more than once. Furthermore, when the demand for perishable products is less sensitive to environmental friendliness, an increasing preference for freshness is more conducive to improving cold chain profits, but when the demand for perishable products is more sensitive to environmental friendliness, increasing the preference for freshness does not improve such profits. The cost coefficient of the carbon abatement effort has a more obvious impact on the demand and economic profits of a cold chain. An improved bilateral cost-sharing contract is more effective than a unilateral cost-sharing contract, as the former can simultaneously improve the cold chain’s economic and environmental benefits and achieve perfect coordination. Overall, our research provides a theoretical basis for the long-term optimization and coordination of cold chains in low-carbon environments.

Bias-variance decomposition of overparameterized regression with random linear features.

In classical statistics, the bias-variance trade-off describes how varying a model's complexity (e.g., number of fit parameters) affects its ability to make accurate predictions. According to this trade-off, optimal performance is achieved when a model is expressive enough to capture trends in the data, yet not so complex that it overfits idiosyncratic features of the training data. Recently, it has become clear that this classic understanding of the bias variance must be fundamentally revisited in light of the incredible predictive performance of overparameterized models-models that avoid overfitting even when the number of fit parameters is large enough to perfectly fit the training data. Here, we present results for one of the simplest examples of an overparameterized model: regression with random linear features (i.e., a two-layer neural network with a linear activation function). Using the zero-temperature cavity method, we derive analytic expressions for the training error, test error, bias, and variance. We show that the linear random features model exhibits three phase transitions: two different transitions to an interpolation regime where the training error is zero, along with an additional transition between regimes with large bias and minimal bias. Using random matrix theory, we show how each transition arises due to small nonzero eigenvalues in the Hessian matrix. Finally, we compare and contrast the phase diagram of the random linear features model to the random nonlinear features model and ordinary regression, highlighting the additional phase transitions that result from the use of linear basis functions.

Stock price crash risk and the adoption of poison pills: evidence from Brazil

PurposeThe purpose of this paper is to examine the effect of stock price crash risk on the adoption of poison pills.Design/methodology/approachThe authors estimate logit and probit regressions. Their sample includes 185 Brazilian public firms for the period 2010–2018. Following previous studies, the authors use the negative skewness of firm-specific weekly returns and the down-to-up volatility of firm-specific weekly returns as measures of firm's stock price crash risk. As proxies of poison pills, the authors employ the “conventional” poison pills in their baseline models and the “eternity” poison pills, which prevent the removal of poison pills from bylaws, in additional models.FindingsThe authors find that stock price crash risk measures are not associated with poison pill adoption. However, although stock price crash risk does not lead to poison pill adoption as a complementary corporate governance mechanism that protects firms against hostile takeover attempts, further results show that managers do not draw on stock price crash risk as a pretext to entrench themselves. Additional analyses also highlight that CEO power seems to play a role in moderating the relationship between stock price crash risk and eternity poison pill adoption.Originality/valueThe authors contribute to the literature on stock price crash risk, which calls for research in international contexts to better understand the effect of stock price crash risk on country-specific idiosyncratic features. The authors discuss a controversial anti-takeover mechanism that has been debated by Brazilian policymakers.

The role of the ventrolateral anterior temporal lobes in social cognition.

A key challenge for neurobiological models of social cognition is to elucidate whether brain regions are specialised for that domain. In recent years, discussion surrounding the role of anterior temporal regions epitomises such debates; some argue the anterior temporal lobe (ATL) is part of a domain‐specific network for social processing, while others claim it comprises a domain‐general hub for semantic representation. In the present study, we used ATL‐optimised fMRI to map the contribution of different ATL structures to a variety of paradigms frequently used to probe a crucial social ability, namely ‘theory of mind’ (ToM). Using multiple tasks enables a clearer attribution of activation to ToM as opposed to idiosyncratic features of stimuli. Further, we directly explored whether these same structures are also activated by a non‐social task probing semantic representations. We revealed that common to all of the tasks was activation of a key ventrolateral ATL region that is often invisible to standard fMRI. This constitutes novel evidence in support of the view that the ventrolateral ATL contributes to social cognition via a domain‐general role in semantic processing and against claims of a specialised social function.

Predicting Academic Performance with an Assessment of Students’ Knowledge of the Benefits of High-Level and Low-Level Construal

Metamotivation research suggests that people understand the benefits of engaging in high-level versus low-level construal (i.e., orienting toward the abstract, essential versus concrete, idiosyncratic features of events) in goal-directed behavior. The current research examines the psychometric properties of one assessment of this knowledge and tests whether it predicts consequential outcomes (academic performance). Exploratory and confirmatory factor analyses revealed a two-factor structure, whereby knowledge of the benefits of high-level construal (i.e., high-level knowledge) and low-level construal (i.e., low-level knowledge) were distinct constructs. Participants on average evidenced beliefs about the normative benefits of high-level and low-level knowledge that accord with published research. Critically, individual differences in high-level and low-level knowledge independently predicted grades, controlling for traditional correlates of grades. These findings suggest metamotivational knowledge may be a key antecedent to goal success and lead to novel diagnostic assessments and interventions.

On the Road to Iberia : Sonata Form and Españolismo in "Asturies" from Espagne (Souvenirs) by Isaac Albéniz

This analytical vignette examines Isaac Albéniz's "Asturies" (T. 103B). Drawing on both Caplin's formal-functional and Vande Moortele's two-dimensional approaches, it argues that despite its apparent large-ternary form, "Asturies" uses an unequivocal sonata-form rhetoric combined with characteristic elements of Spanish folklore, a combination that became one of the most idiosyncratic features of Albéniz's musical language in his most famous work,Iberia . My analysis ultimately seeks to contribute to the appreciation of this forgotten composition and to acknowledge its importance in Albéniz's compositional development.

Putative white-naped mangabey (Cercocebus lunulatus) × olive baboon (Papio anubis) hybrids from Comoé National Park in Côte d’Ivoire

Abstract We report the presence of at least one putative hybrid monkey, white-naped mangabey (Cercocebus lunulatus) × olive baboon (Papio anubis), at Comoé National Park (CNP) in north-eastern Côte d’Ivoire. C. lunulatus and P. anubis belong to two separate clades within the African Papionini (Papionina), which is known to display a complex pattern of evolutionary history involving ancient and recent hybridization. CNP is a bushy savanna-dominated protected area home to 12–13 primate species. Only about 9–11 % of the land cover is forest. C. lunulatus is an Endangered species while P. anubis is a Least Concern species. While conducting a reconnaissance survey on June 23, 2019, the first author observed and photographed a mangabey-baboon hybrid-like juvenile male monkey (2019A). At the same area where 2019A was photographed, a camera trap (CT) captured a video of a hybrid-like juvenile male monkey (2021B) on January 14, 2021, and another nearby CT captured a video of a slightly older hybrid-like juvenile male monkey (2021C) on May 23, 2021. Because there are reported cases of hybrids in captivity that occurred between the members of the two separate clades of the Papionini, the discovery of such intergeneric hybrids in the wild would not be surprising. We examine the idiosyncratic features of the putative hybrids and discuss the implication for conservation and future directions for research, considering the potential interacting factors that may lead to intergeneric hybridization. Specifically, to assess genetic population structure within C. lunulatus and P. anubis and to clarify the degree of gene flow among the two species, collecting biological matter from the putative hybrids, mangabeys, and baboons is necessary. Also, to elucidate the circumstances that might have stimulated hybridization, examining changes that might have occurred in the two species’ ecology and demography is essential.

Fractional 2\u2032-O-methylation in the ribosomal RNA of Dictyostelium discoideum supports ribosome heterogeneity in Amoebozoa

A hallmark of ribosomal RNA (rRNA) are 2′-O-methyl groups that are introduced sequence specifically by box C/D small nucleolar RNAs (snoRNAs) in ribonucleoprotein particles. Most data on this chemical modification and its impact on RNA folding and stability are derived from organisms of the Opisthokonta supergroup. Using bioinformatics and RNA-seq data, we identify 30 novel box C/D snoRNAs in Dictyostelium discoideum, many of which are differentially expressed during the multicellular development of the amoeba. By applying RiboMeth-seq, we find 49 positions in the 17S and 26S rRNA 2′-O-methylated. Several of these nucleotides are substoichiometrically modified, with one displaying dynamic modification levels during development. Using homology-based models for the D. discoideum rRNA secondary structures, we localize many modified nucleotides in the vicinity of the ribosomal A, P and E sites. For most modified positions, a guiding box C/D snoRNA could be identified, allowing to determine idiosyncratic features of the snoRNA/rRNA interactions in the amoeba. Our data from D. discoideum represents the first evidence for ribosome heterogeneity in the Amoebozoa supergroup, allowing to suggest that it is a common feature of all eukaryotes.