unconscious priming by illusory figures the role of the salient region

In this study we provide evidence that unconscious priming can be obtained as a result of the processing of the salient region (SR) of illusory figures and without that of illusory contours (ICs). We used a metacontrast masking paradigm where illusory figures were masked by real figures. In Experiment 1 we found a clear priming effect when participants were asked to discriminate between square and diamond masks preceded by congruent or incongruent illusory square or diamond primes. It is likely that metacontrast impairs the processing of ICs but not of the SR; therefore the above result strongly suggests that the priming effect was specifically related to the processing of the SR. In Experiment 2 participants were tested in the same task as in Experiment 1 with additional primes in which the inducers were presented in the same locations but their shapes were changed so as to modify the global configuration. We termed these primes High, Low, and No Salient Region (HSR, LSR, and NSR, respectively). The HSR condition replicated Experiment 1, whereas in the LSR and NSR conditions the priming effect got progressively smaller. The results of Experiment 1 were replicated with the priming effect significantly larger in the HSR than in all other conditions. It was also larger in the HSR than in LSR condition and smallest but still present in the NSR condition. Taken together, these results indicate that the unconscious processing of only the SR yields a priming effect and that a reduction of the saliency of the SR leads to a reduction of the priming effect, while its elimination does not abolish it

B2B digital platform adoption by SMEs and large firms: Pathways and pitfalls

The ongoing paradigm shift towards two-sided and multi-sided platforms is reshaping business transactions and collaborations worldwide. Such digital platforms have found widespread acceptance in business-to-business markets, serving as catalysts for strategic networking, transparency, and traceability, especially in sourcing activities that demand strategic solutions for supplier selection and collaboration. Nonetheless, the variables influencing platform adoption in small and medium-sized enterprises (SMEs) and large firms remain somewhat opaque. In this study, the social network theory (SNT), diffusion of innovation (DOI) theory, and technology–organisation–environment (TOE) framework were used as analytical lenses. Drawing from a sample of 318 responses from supply chain managers, this study employs a fuzzy-set qualitative comparative analysis (fsQCA) to identify 15 configurations related to the adoption of two-sided platforms in both SMEs and large manufacturing firms. The results underscore that SMEs' drive for platform adoption is primarily anchored in their need for flexible, fluid networks, thus reinforcing the value of two-sided platforms in cultivating robust supplier relationships. In contrast, large firms are driven by potential advantages in efficiency and transactional security. However, the low adoption intention in both SMEs and large firms can be attributed to perceived barriers and a lack of perceived benefits, respectively

Parental and peer support and modelling in relation to domain-specific physical activity participation in boys and girls from Germany

Background Physical activity (PA) as a precondition of child development is related with social environmental correlates. However, domain-specific PA and gender issues have been neglected in studies on social support and modelling and PA in school-aged children. The aim of this study was to assess the relationships of parental and peer modelling and social support with domain-specific PA participation in a large sample of school-aged children, taking gender into account. Methods 3,505 school children aged 6 to 17 years old participated in the German nationwide ‘MoMo’ cohort-study. By using the MoMo-PAQ the participants and their parents provided self-report data on perceived social support and social modelling and domain-specific PA participation. Relationships of social environmental variables and the physical outcomes were analysed by logistic regression analyses. Results At secondary school level, girls were less likely than boys to participate in physical activity in and outside of sports clubs, extra-curricular physical activity and in outdoor play (p < 0.05), but at primary school level this pattern only applied to club sport (p < 0.01). Girls also received less social support than boys (p < 0.01). Physical activity participation in all domains was associated with any of the social support and modelling variables and differences between physical activity domains and between boys and girls occurred. Most consistently physical activity in sports clubs was related with the social environmental correlates in boys (primary school: R2 = 0.60; secondary school: R2 = 0.45) and girls (primary school: R2 = 0.53; secondary school: R2 = 0.47). Conclusions In future, reciprocal relationships of social environmental variables and PA should be considered in longitudinal studies to obtain insights into the direction of the associations. Furthermore, interventions encompassing the social environment and focussed particularly on the promotion of domain-specific PA in girls in secondary school-age are warranted

Skeletal anomalies in dusky grouper Epinephelus marginatus (Lowe 1834) juveniles reared with different methodologies and larval densities

The first attempts to reproduce dusky grouper (Epinephelus marginatus, Lowe 1834) under controlled conditions started in 1995, but the egg and larvae quality was very low. Mass production is still encountering many difficulties, mainly concentrated in the larval period when very high mortality rates are observed, confirming what has been observed in the rearing of other grouper species. The main bottlenecks have been identified as the difficulty to properly nourish the larvae, stress shock syndrome, and the high deformation rates. We analysed 633 dusky grouper larvae and juveniles (0.2–7.2 cm total length, TL), sampled during two larval rearing cycles carried out in 2001 and 2002 in Italy. The specimens at different development stages were stained in toto for bone and cartilage and examined for skeletal anomalies during dusky grouper ontogenesis. The incidence of anomalies in groupers hatched from the same egg batch but reared using two different methods (green waters and semi-intensive rearing) and three stocking densities (8, 16 and 28 larvae/l) was compared, with a view to providing tools for identifying the most appropriate larval rearing method in order to at least limit the onset of skeletal anomalies. Our results suggest that during development no particular skeletal anomaly patterns (or fate) can be clearly identified as a high variability was observed in malformation typologies and the regions affected. No significant differences in the morphological quality between groupers reared using semi-intensive (LV02 lot) and green water (GW02-01 lot) methodologies were observed, whilst groupers reared at the highest stocking density (28 larvae/l) showed the highest frequency of deformed individuals (75.8%), the highest malformation charge (average of 5.5 anomalies per deformed individual), the largest range of anomaly typologies (38), and the highest incidence of individuals with at least one severe anomaly (30.9%). Whilst in green waters no evident effects of larvae density were observed on survival rates, the survival rate in large volume reared individuals (17.5%) was considerably higher with respect to those reared in green waters (0.2%) at 7–8 larvae/l. This indicates that the semi-intensive methodology should be considered more effective in enhancing the survival rate of dusky grouper larvae

Longitudinal study of the effect of a 5-year exercise intervention on structural brain complexity in older adults. A Generation 100 substudy

Physical inactivity has been identified as an important risk factor for dementia. High levels of cardiorespiratory fitness (CRF) have been shown to reduce the risk of dementia. However, the mechanism by which exercise affects brain health is still debated. Fractal dimension (FD) is an index that quantifies the structural complexity of the brain. The purpose of this study was to investigate the effects of a 5-year exercise intervention on the structural complexity of the brain, measured through the FD, in a subset of 105 healthy older adults participating in the randomized controlled trial Generation 100 Study. The subjects were randomized into control, moderate intensity continuous training, and high intensity interval training groups. Both brain MRI and CRF were acquired at baseline and at 1-, 3- and 5-years follow-ups. Cortical thickness and volume data were extracted with FreeSurfer, and FD of the cortical lobes, cerebral and cerebellar gray and white matter were computed. CRF was measured as peak oxygen uptake (VO2peak) using ergospirometry during graded maximal exercise testing. Linear mixed models were used to investigate exercise group differences and possible CRF effects on the brain's structural complexity. Associations between change over time in CRF and FD were performed if there was a significant association between CRF and FD. There were no effects of group membership on the structural complexity. However, we found a positive association between CRF and the cerebral gray matter FD (p &lt; 0.001) and the temporal lobe gray matter FD (p &lt; 0.001). This effect was not present for cortical thickness, suggesting that FD is a more sensitive index of structural changes. The change over time in CRF was associated with the change in temporal lobe gray matter FD from baseline to 5-year follow-up (p &lt; 0.05). No association of the change was found between CRF and cerebral gray matter FD. These results demonstrated that entering old age with high and preserved CRF levels protected against loss of structural complexity in areas sensitive to aging and age-related pathology

Fractal dimension of cerebral white matter : A consistent feature for prediction of the cognitive performance in patients with small vessel disease and mild cognitive impairment

Patients with cerebral small vessel disease (SVD) frequently show decline in cognitive performance. However, neuroimaging in SVD patients discloses a wide range of brain lesions and alterations so that it is often difficult to understand which of these changes are the most relevant for cognitive decline. It has also become evident that visually-rated alterations do not fully explain the neuroimaging correlates of cognitive decline in SVD. Fractal dimension (FD), a unitless feature of structural complexity that can be computed from high-resolution T1-weighted images, has been recently applied to the neuroimaging evaluation of the human brain. Indeed, white matter (WM) and cortical gray matter (GM) exhibit an inherent structural complexity that can be measured through the FD. In our study, we included 64 patients (mean age \ub1 standard deviation, 74.6 \ub1 6.9, education 7.9 \ub1 4.2 years, 53% males) with SVD and mild cognitive impairment (MCI), and a control group of 24 healthy subjects (mean age \ub1 standard deviation, 72.3 \ub1 4.4 years, 50% males). With the aim of assessing whether the FD values of cerebral WM (WM FD) and cortical GM (GM FD) could be valuable structural predictors of cognitive performance in patients with SVD and MCI, we employed a machine learning strategy based on LASSO (least absolute shrinkage and selection operator) regression applied on a set of standard and advanced neuroimaging features in a nested cross-validation (CV) loop. This approach was aimed at 1) choosing the best predictive models, able to reliably predict the individual neuropsychological scores sensitive to attention and executive dysfunctions (prominent features of subcortical vascular cognitive impairment) and 2) identifying a features ranking according to their importance in the model through the assessment of the out-of-sample error. For each neuropsychological test, using 1000 repetitions of LASSO regression and 5000 random permutations, we found that the statistically significant models were those for the Montreal Cognitive Assessment scores (p-value =.039), Symbol Digit Modalities Test scores (p-value =.039), and Trail Making Test Part A scores (p-value =.025). Significant prediction of these scores was obtained using different sets of neuroimaging features in which the WM FD was the most frequently selected feature. In conclusion, we showed that a machine learning approach could be useful in SVD research field using standard and advanced neuroimaging features. Our study results raise the possibility that FD may represent a consistent feature in predicting cognitive decline in SVD that can complement standard imaging

Conversion of the Native N-Terminal Domain of TDP-43 into a Monomeric Alternative Fold with Lower Aggregation Propensity

TAR DNA-binding protein 43 (TDP-43) forms intraneuronal cytoplasmic inclusions associated with amyotrophic lateral sclerosis and ubiquitin-positive frontotemporal lobar degeneration. Its N-terminal domain (NTD) can dimerise/oligomerise with the head-to-tail arrangement, which is essential for function but also favours liquid-liquid phase separation and inclusion formation of full-length TDP-43. Using various biophysical approaches, we identified an alternative conforma-tional state of NTD in the presence of Sulfobetaine 3-10 (SB3-10), with higher content of α-helical structure and tryptophan solvent exposure. NMR shows a highly mobile structure, with partially folded regions and β-sheet content decrease, with a concomitant increase of α-helical structure. It is monomeric and reverts to native oligomeric NTD upon SB3-10 dilution. The equilibrium GdnHCl-induced denaturation shows a cooperative folding and a somewhat lower conformational stability. When the aggregation processes were compared with and without pre-incubation with SB3-10, but at the identical final SB3-10 concentration, a slower aggregation was found in the former case, despite the reversible attainment of the native conformation in both cases. This was attributed to protein monomerization and oligomeric seeds disruption by the conditions promoting the alternative con-formation. Overall, the results show a high plasticity of TDP-43 NTD and identify strategies to monomerise TDP-43 NTD for methodological and biomedical applications

Infrared absorption from Charge Density Waves in magnetic manganites

The infrared absorption of charge density waves coupled to a magnetic background is first observed in two manganites La{1-x}Ca{x}MnO{3} with x = 0.5 and x = 0.67. In both cases a BCS-like gap 2 Delta (T), which for x=0.5 follows the hysteretic ferro-antiferromagnetic transition, fully opens at a finite T{0} < T{Neel}, with 2 Delta(T{0})/kT{c} close to 5. These results may also explain the unusual coexistence of charge ordering and ferromagnetism in La{0.5}Ca{0.5}MnO{3}.Comment: File revtex + 3 figs. in epsf. To appear on Phys. Rev. Let

Image resampling and discretization effect on the estimate of myocardial radiomic features from T1 and T2 mapping in hypertrophic cardiomyopathy

Radiomics is emerging as a promising and useful tool in cardiac magnetic resonance (CMR) imaging applications. Accordingly, the purpose of this study was to investigate, for the first time, the effect of image resampling/discretization and filtering on radiomic features estimation from quantitative CMR T1 and T2 mapping. Specifically, T1 and T2 maps of 26 patients with hypertrophic cardiomyopathy (HCM) were used to estimate 98 radiomic features for 7 different resampling voxel sizes (at fixed bin width), 9 different bin widths (at fixed resampling voxel size), and 7 different spatial filters (at fixed resampling voxel size/bin width). While we found a remarkable dependence of myocardial radiomic features from T1 and T2 mapping on image filters, many radiomic features showed a limited sensitivity to resampling voxel size/bin width, in terms of intraclass correlation coefficient (&gt; 0.75) and coefficient of variation (&lt; 30%). The estimate of most textural radiomic features showed a linear significant (p &lt; 0.05) correlation with resampling voxel size/bin width. Overall, radiomic features from T2 maps have proven to be less sensitive to image preprocessing than those from T1 maps, especially when varying bin width. Our results might corroborate the potential of radiomics from T1/T2 mapping in HCM and hopefully in other myocardial diseases

Prediction of the information processing speed performance in multiple sclerosis using a machine learning approach in a large multicenter magnetic resonance imaging data set

Many patients with multiple sclerosis (MS) experience information processing speed (IPS) deficits, and the Symbol Digit Modalities Test (SDMT) has been recommended as a valid screening test. Magnetic resonance imaging (MRI) has markedly improved the understanding of the mechanisms associated with cognitive deficits in MS. However, which structural MRI markers are the most closely related to cognitive performance is still unclear. We used the multicenter 3T-MRI data set of the Italian Neuroimaging Network Initiative to extract multimodal data (i.e., demographic, clinical, neuropsychological, and structural MRIs) of 540 MS patients. We aimed to assess, through machine learning techniques, the contribution of brain MRI structural volumes in the prediction of IPS deficits when combined with demographic and clinical features. We trained and tested the eXtreme Gradient Boosting (XGBoost) model following a rigorous validation scheme to obtain reliable generalization performance. We carried out a classification and a regression task based on SDMT scores feeding each model with different combinations of features. For the classification task, the model trained with thalamus, cortical gray matter, hippocampus, and lesions volumes achieved an area under the receiver operating characteristic curve of 0.74. For the regression task, the model trained with cortical gray matter and thalamus volumes, EDSS, nucleus accumbens, lesions, and putamen volumes, and age reached a mean absolute error of 0.95. In conclusion, our results confirmed that damage to cortical gray matter and relevant deep and archaic gray matter structures, such as the thalamus and hippocampus, is among the most relevant predictors of cognitive performance in MS