Correlation Structure Research Articles

The cognitive neuroscience and neurocognitive rehabilitation of dance.

Creative movement, in the form of music- and dance-based exercise and rehabilitation, can serve as a model for learning and memory, visuospatial orientation, mental imagery, and multimodal sensory-motor integration. This review summarizes the advancement in cognitive neuroscience aimed at determining cognitive processes and brain structural and functional correlates involved in dance or creative movement, as well as the cognitive processes which accompany such activities. We synthesize the evidence for the use of cognitive, motor, and cognitive-motor function in dance as well as dance's potential application in neurological therapy and neurorehabilitation. Finally, we discuss how partnered interaction and sensorimotor integration in dance, and "dancing robots" could shed light on future application of dance as rehabilitation, of dance used in technology and potential mechanisms of benefit from dance-based activities.

Psychometric Properties of Social Climate in the Classroom Scale for University Students in Chile

Background: Classroom social climate is a significant phenomenon within educational contexts; however, it has predominantly been studied among high school students, with limited evidence available at the university level and, consequently, in the psychometric properties of measurement instruments. This study aimed to analyze the psychometric properties of the University Classroom Social Climate Scale (ECSA-U) among Chilean students from the La Araucanía region. Method: 422 students participated, responding to the adapted version of the ECSA-U and the Motivation subscale of the Motivation and Learning Strategies Questionnaire. Exploratory structural equation modeling (ESEM), reliability analyses, and correlation analyses were conducted to provide valid evidence for the Chilean University Classroom Social Climate Scale (ECSA-UCL). Results: The scale demonstrated a three-factor structure with good fit indicators, excellent reliability indices, and significant positive associations between the ECSA-UCL and the Motivation Subscale. Conclusions: The ECSA-UCL has proven valid and reliable for measuring the perception of Classroom Social Climate among Chilean university students, making it suitable for use as a measurement tool in studies or interventions that include this variable.

A re-sampling statistics based imprecise moment independent global sensitivity analysis methodology with limited data of uncorrelated and correlated geotechnical properties

Traditional Global Sensitivity Analysis (GSA) is often performed using variance-based Sobol’s GSA, considering statistics of inputs estimated from limited data to be precise. This can lead to inaccuracies in the importance ranking of inputs due to negligence of – i) epistemic uncertainties in their statistics, and ii) role of other moments of outputs in Sensitivity Indices (SIs). This study overcomes these limitations by proposing an imprecise moment independent GSA methodology. The methodology couples re-sampling statistical techniques, i.e., Jackknifing and Bootstrapping with Monte-Carlo Simulations based Borgonovo’s moment independent GSA to estimate distributions of SIs. The re-sampling techniques estimate epistemic uncertainties in the statistics of inputs by generating re-constituted samples. These epistemic uncertainties are then propagated via Borgonovo’s GSA to estimate their imprecise moment independent SIs. The methodology is further coupled with Nataf’s transformation and Moving Least Square-Response Surface Methods to deal with problems of correlated inputs and lack of explicit input-output relationships. The generalized nature of methodology is demonstrated for three real case studies (one tunnel and two slopes), with different correlation structures between inputs, input-outputs relationships (explicit/implicit), and failure mechanisms. The methodology estimated the distributions of SIs of inputs instead of their point estimates, indicating the propagation of epistemic uncertainties truthfully. The Jackknife-GSA was significantly efficient (∼99 %) with negligible differences in statistics of SIs as compared to Bootstrap-GSA. The correlation between inputs significantly affects the statistics of SIs. Further, a reduction in the imprecision of SIs of inputs with their increasing sample sizes was observed, which is consistent with the general understanding.

Correlation of structure and luminescence in Ca₃La₂W₂O₁₂: Eu³⁺ phosphors for advanced display technologies validated using Judd-Ofelt theory

Correlation of structure and luminescence in Ca₃La₂W₂O₁₂: Eu³⁺ phosphors for advanced display technologies validated using Judd-Ofelt theory

Characterization of anti-EBNA-1 antibodies and exploration of their molecular mimicry potential in an EBV-infected Sjögren's syndrome patient

There is a potential link between autoimmune diseases and Epstein-Barr virus (EBV) infections, with EBV playing a substantial role in the onset of Sjögren's syndrome (SjS). Some EBV proteins could mimic host self-antigens post-infection, leading to molecular mimicry. This similarity may cause the immune system to attack its tissues mistakenly. Among the various proteins associated with EBV, nuclear antigen 1 (EBNA-1) is essential for the latent replication of infected cells and is prevalent in all EBV-related diseases. In the study, single-chain variable fragment (scFv) antibodies targeting EBNA-1 were isolated using phage display technology from a primary SjS patient who also had a chronic active EBV infection. The specific clones were enriched after panning, and the binding activity of selected scFvs targeting EBNA-1 was confirmed. Sequence analysis indicated that the scFvs exhibiting positive signals could be grouped into five clones, all of which used homologous heavy chain V regions derived from germline Vh4-39, and two types of light chain V regions stemming from germline Vλ1-44 and Vλ3-15. These scFvs were found to exhibit a high degree of somatic mutations, likely indicative of antigen selection. Of the scFvs, P1-3 demonstrated the strongest binding affinity to EBNA-1, exhibiting a determined value of 7.3 x 10-8 M, and showed cross-reactivity to the SjS associated La/SSB self-antigen. The experimental results combined with AlphaFold 3 predictions revealed a potential epitope for scFv P1-3 binding to EBNA-1. Additionally, scFv P1-3 could also cross-bind to the modeled structure of La/SSB. We inferred a possible structural correlation between EBNA-1 and La/SSB involving an X2AX6PG epitope motif. This research contributes to our understanding of the structural basis of the interactions between antibodies and EBNA-1, shedding light on the VH and VL gene usage of anti-EBNA-1 antibodies in EBV-infected SjS patients and the potential origins of autoantibodies.

Computational exploration of naturally derived peptides inhibitory mechanisms against ACE enzyme, from interactions to structural-dynamics

Naturally derived peptides have gained significant attention because of their potential to reduce blood pressure. These peptides can be derived from various sources, including snake venom, marine organisms, cow’s milk, seahorses, and plants. Investigating the underlying mechanisms of these peptides in lowering blood pressure is crucial for replacing synthetic drugs currently in use. In this regard, we conducted in silico studies, such as molecular docking, classical molecular dynamics (MD) simulations, and QM/MM simulation methods, on two naturally derived peptides (PAGPRGPA and WALKGYK) and Angiotensin II (ANGII) as the enzyme substrates for binding to sACE. The results of 500 ns MD calculations showed that the WALKGYK peptide occupies the ACE binding site, similar to the ANGII and BPPb peptides, two distinguished C-domain-specific inhibitors. Furthermore, QM/MM calculations demonstrated that no peptide bond cleavage was mediated by Zn2+ at the catalytic site of the peptides. However, during the 500 ns MD simulation, the backbone oxygens of LYS4 and GLY5 of the WALKGYK peptides were tightly coordinated to the Zn2+ ion. Free energy calculations also confirmed the higher affinity of the WALKGYK peptides for binding to sACE. In addition, structural analysis correlation showed a different pattern in PAGPRGPA compared to WALKGYK and ANGII. Despite the similarity of the peptide PAGPRGPA to typical ACE peptide inhibitors with hydrophobic ends, the electrostatic composition of the WALKGYK peptide showed a higher tendency towards ACE inhibition. Therefore, peptide residue compositions, such as WALKGYK, can be considered for designing new inhibitors with fewer side effects for sACE C-terminal inhibitors.

Brain structural associations of syntactic complexity and diversity across schizophrenia spectrum and major depressive disorders, and healthy controls

Deviations in syntax production have been well documented in schizophrenia spectrum disorders (SSD). Recently, we have shown evidence for transdiagnostic subtypes of syntactic complexity and diversity. However, there is a lack of studies exploring brain structural correlates of syntax across diagnoses. We assessed syntactic complexity and diversity of oral language production using four Thematic Apperception Test pictures in a sample of N = 87 subjects (n = 24 major depressive disorder (MDD), n = 30 SSD patients both diagnosed according to DSM-IV-TR, and n = 33 healthy controls (HC)). General linear models were used to investigate the association of syntax with gray matter volume (GMV), fractional anisotropy (FA), axial (AD), radial (RD), and mean diffusivity (MD). Age, sex, total intracranial volume, group, interaction of group and syntax were covariates of no interest. Syntactic diversity was positively correlated with the GMV of the right medial pre- and postcentral gyri and with the FA of the left superior-longitudinal fasciculus (temporal part). Conversely, the AD of the left cingulum bundle and the forceps minor were negatively correlated with syntactic diversity. The AD of the right inferior-longitudinal fasciculus was positively correlated with syntactic complexity. Negative associations were observed between syntactic complexity and the FA of the left cingulum bundle, the right superior-longitudinal fasciculus, and the AD of the forceps minor and the left uncinate fasciculus. Our study showed brain structural correlates of syntactic complexity and diversity across diagnoses and HC. This contributes to a comprehensive understanding of the interplay between linguistic and neural substrates in syntax production in psychiatric disorders and HC.

Spatial-Spectral Middle Cross-Attention Fusion Network for Hyperspectral Image Superresolution

The spatial and spectral features of hyperspectral images exhibit complementarity, and neglecting them prevents the full exploitation of useful information for superresolution. This article proposes a spatial-spectral middle cross-attention fusion network to explore the spatial-spectral structure correlation. Initially, we learn spatial and spectral features through spatial and spectral branches instead of single ones to reduce information compression. Then, a novel middle-cross attention fusion block that includes middle features fusion strategy and cross-attention is proposed to fuse spatial-spectral features to enhance their mutual effects, which aims to explore the spatial-spectral structural correlations. Finally, we propose a spectral feature compensation mechanism to provide complementary information for adjacent band groups. The experimental results show that the proposed method outperforms state-of-the-art algorithms in object values and visual quality.

Accelerating computation: A pairwise fitting technique for multivariate probit models

Fitting multivariate probit models via maximum likelihood presents considerable computational challenges, particularly in terms of computation time and convergence difficulties, even for small numbers of responses. These issues are exacerbated when dealing with ordinal data. An efficient computational approach is introduced, based on a pairwise fitting technique within a pseudo-likelihood framework. This methodology is applied to clinical case studies, specifically using a trivariate probit model. Additionally, the correlation structure among outcomes is allowed to depend on covariates, enhancing both the flexibility and interpretability of the model. By way of simulation and real data applications, the proposed approach demonstrates superior computational efficiency as the dimension of the outcome vector increases. The method's ability to capture covariate-dependent correlations makes it particularly useful in medical research, where understanding complex associations among health outcomes is of scientific importance.

Structural influences on synaptic plasticity: The role of presynaptic connectivity in the emergence of E/I co-tuning.

Cortical neurons are versatile and efficient coding units that develop strong preferences for specific stimulus characteristics. The sharpness of tuning and coding efficiency is hypothesized to be controlled by delicately balanced excitation and inhibition. These observations suggest a need for detailed co-tuning of excitatory and inhibitory populations. Theoretical studies have demonstrated that a combination of plasticity rules can lead to the emergence of excitation/inhibition (E/I) co-tuning in neurons driven by independent, low-noise signals. However, cortical signals are typically noisy and originate from highly recurrent networks, generating correlations in the inputs. This raises questions about the ability of plasticity mechanisms to self-organize co-tuned connectivity in neurons receiving noisy, correlated inputs. Here, we study the emergence of input selectivity and weight co-tuning in a neuron receiving input from a recurrent network via plastic feedforward connections. We demonstrate that while strong noise levels destroy the emergence of co-tuning in the readout neuron, introducing specific structures in the non-plastic pre-synaptic connectivity can re-establish it by generating a favourable correlation structure in the population activity. We further show that structured recurrent connectivity can impact the statistics in fully plastic recurrent networks, driving the formation of co-tuning in neurons that do not receive direct input from other areas. Our findings indicate that the network dynamics created by simple, biologically plausible structural connectivity patterns can enhance the ability of synaptic plasticity to learn input-output relationships in higher brain areas.

Structural Insight into Ionogels: A Case Study of 1-Methyl-3-octyl-imidazolium Tetrafluoroborate Confined in Aerosil.

Ionogels were obtained by impregnating Aerosil A380 with 1-methyl-3-octyl-imidazolium tetrafluoroborate (OMIM BF4) ionic liquid (IL). The IL content of the ionogels varied from 16.3 to 79.9 mol %. There was evidence of the confinement of the IL in silica in the shift and broadening of the BF4- 19F NMR signal and in the noticeable (∼50 °C) decrease in the temperature of IL decomposition. For both the ionogels and the pure IL, the frequencies of IR vibrations were different, providing further evidence of the confinement effect. An analysis of textural characteristics revealed that, upon its addition to Aerosil, the IL sequentially adsorbed in the micropores, mesopores and interparticle space. SAXS measurements showed that, in the confined IL, the size of nonpolar correlations substantially increased, from 21.5 Å in the bare IL to 25.6 Å in the ionogel containing 28.1 mol % IL. Unexpectedly, for the ionogel with the lowest IL content (16.3 mol %), no nonpolar correlations were observed, indicating the strong distortion of the structure of the confined ionic liquid. To the best of the authors' knowledge, this is the first report on regular changes in nonpolar correlations in ionic liquids upon confinement in a porous solid. These structural correlations can easily be tuned by simply changing the IL content in the ionogel material.

Boosting FRET Efficiency of Chromophores with Aggregation-Caused Quenching by a Crystallization-Induced Precise Co-assembly Strategy.

Förster resonance energy transfer (FRET) plays a critical role in organic optoelectronic materials. However, developing facile and effective strategies to achieve high-efficiency energy harvesting of chromophores with aggregation-caused quenching (ACQ) remains an appealing yet challenging task, that has not yet been explored. Herein, a subtly strategy, crystallization-induced precise co-assembly (CIPCA) involving a molecular "lightening agent," to effectively improve FRET efficiency of ACQ chromophores is developed. Bis(phenylethynyl)anthracene (BPA) and bis(phenylethynyl)naphthacene (BPN) with significant ACQ effect are chosen as representative FRET donor and acceptor, respectively, and weakly-fluorescent octafluoronaphthalene (OFN) acted as the "lightening agent." Thanks to precise co-assembly with OFN, the PLQY of solid BPA is enhanced by 107%, and the BPN powder can be unprecedentedly lighted. More importantly, through such powerful CIPCA, the monotonous and weak emission for BPA@BPN can be remarkably regulated to colorful and much brighter ones with FRET efficiency improvement of as high as 180-270%. An in-depth understanding of FRET regulation is elucidated through a precise correlation of the supramolecular structures and properties. Such achievements allow to successfully fabricate distinct multi-stimuli-responsive fluorescent patterns and highly-emissive colorful flowers with high flexibility. This research provides an efficient strategy to improve the FRET efficiency of ACQ pairs.

Agroecological Aptitude of the Northeast of Formosa (Argentinean Subtropical Region) for Banana Production Assessed by Multiple Factor Analysis

Banana (Musa spp.) is an important crop in the economies of many developing countries. In the north of Argentina, a subtropical region, banana plants grow in a suboptimal environment that limits yield because only one harvest per year is achieved. The objective of this work was to characterize the agroecological aptitude of Formosa, Argentina, for banana production through the behavior of three varieties of international use: Williams, Jaffa and Grand Naine, evaluated over five consecutive years. The three-way data analysis technique called Multiple Factor Analysis (MFA) was used for evaluating the varieties’ performances across cycles of production. The results allowed for inferring the existence of a genotype x environment interaction (GEI), corroborated by two-way factorial ANOVA. In order to determine how this suboptimal environment affected the development of each genotype of this perennial crop, Dual Multiple Factor Analysis (DMFA) was applied to jointly analyze the correlation structure between the traits that contributed to the performance of each variety in each year. The correlation structures between variables were different in each population and varied between years. All traits showed great variation between the years and genotypes, with the fruit peel thickness being the most discrepant throughout the years. However, Formosa appeared as a promising subtropical agroecological environment to produce banana because the varieties’ performances were acceptable for large-scale production systems. In addition to evaluating the adequate aptitude for cultivating banana in Formosa considering the significant effect of the GEIs, this research made a methodological contribution by proposing the use of three-way data analysis in Agronomy Science via MFA and DMFA.

Comparison of Subdural and Intracortical Recordings of Somatosensory Evoked Responses

Micro-electrocorticography (µECoG) electrodes have emerged to balance the trade-off between invasiveness and signal quality in brain recordings. However, its large-scale applicability is still hindered by a lack of comparative studies assessing the relationship between ECoG and traditional recording methods such as penetrating electrodes. This study aimed to compare somatosensory evoked potentials (SEPs) through the lenses of a µECoG and an intracortical microelectrode array (MEA). The electrodes were implanted in the pig’s primary somatosensory cortex, while SEPs were generated by applying electrical stimulation to the ulnar nerve. The SEP amplitude, signal-to-noise ratio (SNR), power spectral density (PSD), and correlation structure were analysed. Overall, SEPs resulting from MEA recordings had higher amplitudes and contained significantly more spectral power, especially at higher frequencies. However, the SNRs were similar between the interfaces. These results demonstrate the feasibility of using µECoG to decode SEPs with wide-range applications in physiology monitoring and brain–computer interfaces.

Validating an Internalizing Psychopathology Screener for Use with College Students

Objective College students experience high levels of internalizing psychopathology. The current study evaluated multiple sources of validity evidence for using the Youth Internalizing Problems Screener (YIPS) to identify college students with these concerns. Method We evaluated responses to the YIPS and criterion measures with a sample of N = 454 young adults enrolled in a large public university in the USA (M age = 20.02, female = 74%, White = 60%). Analyses addressed structural and criterion validity evidence. Results Results showed strong levels of validity evidence for the YIPS factor structure and theory-consistent correlations with criterion variables. YIPS scores had moderate to strong accuracy for estimating symptom severity levels for both anxiety and depression. Conclusions Results suggest the YIPS is a psychometrically sound screener for internalizing psychopathology among college students, supported by multiple sources of validity evidence. Significance statement Our findings suggest mental health professionals might use the YIPS in college settings for identifying young adults presenting with varying levels of anxiety and depression symptoms. Given the YIPS is brief, free, and publicly available, it may be more feasible than alternative internalizing screeners available for this purpose.

On the Properties of PLS for Analyzing Two‐Level Factorial Experimental Designs

ABSTRACTWe present here a novel methodology to analyze data from two‐level factorial experimental designs, with or without missing runs, with just one method: partial least squares regression with one response variable (PLS1, hereinafter PLS). This property is very attractive for practitioners because, to the best of our knowledge, no other statistical tool has comparable versatility. In the case of a full and fractional factorial design, the one‐PLS component model yields the same analytical solution as multiple linear regression (MLR), not only in the estimation of the effects but also in their statistical significance. When having missing runs in the factorial design, PLS is of particular interest as it is a powerful tool when dealing with complex correlation structures, as opposed to MLR. Thus, we challenge the widely held view that PLS is useful only when dealing with nonexperimental design (i.e., correlated observational data). The methodology is illustrated by two illustrative examples and synthesized by an easy‐to‐follow route map useful for practitioners.

Some notes on the consequences of pretreatment of multivariate data

With the advent of data technologies, we have various types of data, such as structured, unstructured and semi-structured. Performing certain statistical or machine learning techniques may require careful preprocessing or pretreatment of the data to make them suitable for analysis. For example, given a data matrix X, which represents n multivariate observations or cases on p variables or features, the columns/rows of X may be pretreated before applying statistical or machine learning techniques to the data. While centering and/or scaling the variables do not alter the correlation structure nor the graphical representation of the data, centering/scaling the observations do. We investigate various row pretreatment methods more closely and show with theoretical proofs and numerical examples that centering/scaling the rows of X changes both the graphical structure of the observations in the multi-dimensional space and the correlation structure among the variables. There may be good reasons for performing row centering/scaling on the data and we are not against it, but analysts who use such row operations should be aware of the geometrical and correlation structures one has performed on the data and should also demonstrate that the process results in a new, more appropriate structure for their questions.

Aboveground and belowground sizes are aligned in the unified spectrum of plant form and function

Understanding the global variation of plant strategies is essential for unravelling eco-evolutionary processes and ecosystem functions. Variation in ten fundamental aboveground and fine-root traits is summarised in four dimensions, the first of which relates to aboveground plant size. However, there is no consensus about how root size fits within this scheme. Here, we add rooting depth and lateral spread, compiling a set of twelve key traits that define the fundamental investments of plants in growth, reproduction, and survival. We examine whether the inclusion of root size alters the dimensionality and structure of trait correlations defining plant functional strategies. Our results show that including root size traits does not alter the fundamental structure and dimensionality of the plant functional space, regardless of trait completeness and phylogenetic relatedness. Plant size defines a single continuum of allometric investments at the global scale, independent from leaf and root economic strategies.

A fast temporal multiple sparse Bayesian learning-based channel estimation method for time-varying underwater acoustic OFDM systems

In this paper, a fast temporal multiple sparse Bayesian learning (FTMSBL)-based channel estimation method for underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) systems is proposed, which is optimized using the fast marginalized likelihood maximization method. The algorithm fully uses the consistent sparse structure and time-domain correlation properties of channels to improve the reconstruction performance and computational efficiency, offering better performance and higher computational efficiency than the traditional Bayesian learning algorithms. At the same time, the FTMSBL algorithm does not require computing the inverse of large matrices and consumes very little storage resources in the operation, making it suitable for hardware implementation. Simulation and sea trial results show that the FTMSBL-based underwater channel estimation algorithm achieves higher channel estimation accuracy than the orthogonal matching tracking algorithm, and the system bit error rate (BER) is significantly reduced; specifically, the FTMSBL algorithm can achieve optimal performance in strong time-dependent channels.

Seismic nonlinear interaction and uplifting effects between the nuclear island building and soil

Since the Fukushima nuclear accident, seismic design requirements have increased, necessitating a more refined evaluation of base uplift for weakly anchored nuclear island buildings. The elevated cooling water over 3000 t is a distinguishing feature of third-generation reactor buildings (RBs). To assess potential safety-adverse coupling effects, seismic wave propagation process through viscoelastic soils, discontinuous interfaces, and sloshing water was analysed. To facilitate nonlinear systematic simulation and parametric study, the traditional soil-structure interaction direct methods are improved and programmed on: thickness-independent viscous-spring elements for stable static-dynamic boundary transitions; seismic forces separated from the artificial boundary for flexible mesh planning; elevated water simulated with gravity stacking and hydrodynamic action. A nuclear island region encompassing water-cooled RBs and underlying soil cushion layer was investigated as a typical scenario to reveal rules using the proposed high-precision simulation platform. Non-negligible structural risks and correlations between multiple factors were quantitatively elucidated according to simulation findings. A time-lagged increase in the base overturning moment may occur because of water oscillations. As the water level increases to 85 %, the uplift height increases, adversely affecting the in-structure response spectra. Earthquake-induced intense uplift may lead to an increase in hydrodynamic pressure along the inner wall. The research results support the practical assessment of buildings with water cooling facilities located in soft composite sites with high seismic intensities.