The role of impact on the meaning of generic sentences.

Generic sentences (e.g., "Dogs bark") express generalizations about groups or individuals. Accounting for the meaning of generic sentences has been proven challenging, and there is still a very lively debate about which factors matter for whether or not we a willing to endorse a particular generic sentence. In this paper we study the effect of impact on the assertability of generic sentences, where impact refers to the dangerousity of the property the generic is ascribing to a group or individual. We run three preregistered experiments, testing assertability and endorsement of novel generic sentences with visual and textual stimuli. Employing Bayesian statistics we found that impact influences the assertability, and endorsement, of generic statements. However, we observed that the size of the effect impact value may have been previously overestimated by theoretical and experimental works alike. We also run an additional descriptive survey testing standard examples from the linguistic literature and found that at least for some of the examples endorsement appears to be lower than assumed. We end with exploring possible explanations for our results.

Normal but Different: Autistic Adolescents Who Score Within Normal Ranges on Standardized Language Tests Produce Frequent Linguistic Irregularities in Spontaneous Discourse.

Background and aims: A substantial minority of autistic individuals score within typical ranges on standard language tests, suggesting that autism does not necessarily affect language acquisition. This idea is reflected in current diagnostic criteria for autism, wherein language impairment is no longer included. However, some work has suggested that probing autistic speakers' language carefully may reveal subtle differences between autistic and nonautistic people's language that cannot be captured by standardized language testing. The current study aims to test this idea, by determining whether a group of autistic and nonautistic individuals who score similarly on a standardized test show differences in the number of unconventional and erroneous language features they produce in a spontaneous language sample. Methods: Thirty-eight older children and adolescents (19 autistic; 19 nonautistic), between the ages of 10 and 18, were recruited. Both participant groups scored within normal ranges on standardized language and IQ tests. Participants engaged in a "double interview" with an experimenter, during which they were first asked questions by the experimenter about themselves, and then they switched roles, so that it was the participant's turn to ask the experimenter questions. Participants' language during the interview was transcribed and analyzed for linguistic irregularities, including both semantic anomalies and morphosyntactic errors. Results: Group membership accounted for significant variance in irregularity frequency; autistic participants produced more linguistic irregularities than nonautistic participants. Scores on a standardized language test did not improve model fit. Secondary analyses involving irregularity type (semantic vs. morphosyntactic) showed that group differences were primarily driven by relatively high numbers of semantic unconventionalities produced by the autistic group. While the autistic group made more morphosyntactic errors than the nonautistic group, differences in these numbers were only marginally significant. Conclusions and implications: These findings suggest that a commonly used standardized language test does not adequately predict the number and perhaps type of language irregularities produced by some older autistic children and adolescents during spontaneous discourse. Results also suggest that differences in language use, especially semantic differences, may characterize autistic language, even the language produced by people who score within normal ranges on standardized language tests. It is debatable whether differences reflect underlying language impairments and/or a linguistic style adopted/preferred by autistic speakers. In this paper, we discuss both possibilities and offer suggestions to future research for teasing these possibilities apart.

Modification d x 2 - y 2 ${{d}_{{{x}2} - {{y}2}}}$ Orbital Electronic States in Nickel-Based Hydroxides Via Cobalt/Iron Co-Doping for High-Efficiency Methanol Electrooxidation.

The nickel hydroxide-based (Ni(OH)2) methanol-to-formate electrooxidation reaction (MOR) performance is greatly related to the d x 2 - y 2 ${{d}_{{{x}^2} - {{y}^2}}}$ orbital electronic states. Hence, optimizing the d x 2 - y 2 ${{d}_{{{x}^2} - {{y}^2}}}$ orbital electronic states to achieve enhanced MOR activities are highly desired. Here, cobalt (Co) and iron (Fe) doping are used to modify the d x 2 - y 2 ${{d}_{{{x}^2} - {{y}^2}}}$ orbital electronic states. Although both dopants can broaden the d x 2 - y 2 ${{d}_{{{x}^2} - {{y}^2}}}$ orbital; however, Co doping leads to an elevation in the energy level of d x 2 - y 2 ${{d}_{{{x}^2} - {{y}^2}}}$ highest occupied crystal orbital (HOCO), whereas Fe doping results in its reduction. Such a discrepancy in the regulation of d x 2 - y 2 ${{d}_{{{x}^2} - {{y}^2}}}$ orbital electronic states stems from the disparate partial electron transfer mechanisms amongst these transition metal ions, which possess distinct energy level and occupancy of d orbitals. Motivated by this finding, the NiCoFe hydroxide is prepared and exhibited an excellent MOR performance. The results showed that the Co dopants effectively suppress the partial electron transfer from Ni to Fe, combined with the d x 2 - y 2 ${{d}_{{{x}^2} - {{y}^2}}}$ orbital broadening induced by NiO6 octahedra distortion, endowing NiCoFe hydroxide with high d x 2 - y 2 ${{d}_{{{x}^2} - {{y}^2}}}$ HOCO and broad d x 2 - y 2 ${{d}_{{{x}^2} - {{y}^2}}}$ orbital. It is believed that the work gives an in-depth understanding on d x 2 - y 2 ${{d}_{{{x}^2} - {{y}^2}}}$ orbital electronic states regulation in Ni(OH)2, which is beneficial for designing Ni(OH)2-based catalysts with high MOR performance.

Semantic object processing is modulated by prior scene context.

Objects that are congruent with a scene are recognised more efficiently than objects that are incongruent. Further, semantic integration of incongruent objects elicits a stronger N300/N400 EEG component. Yet, the time course and mechanisms of how contextual information supports access to semantic object information is unclear. We used computational modelling and EEG to test how context influences semantic object processing. Using representational similarity analysis, we established that EEG patterns dissociated between objects in congruent or incongruent scenes from around 300 ms. By modelling the semantic processing of objects using independently normed properties, we confirm that the onset of semantic processing of both congruent and incongruent objects is similar (~150 ms). Critically, after ~275 ms, we discover a difference in the duration of semantic integration, lasting longer for incongruent compared to congruent objects. These results constrain our understanding of how contextual information supports access to semantic object information.

Exploring online public survey lifestyle datasets with statistical analysis, machine learning and semantic ontology.

Lifestyle diseases significantly contribute to the global health burden, with lifestyle factors playing a crucial role in the development of depression. The COVID-19 pandemic has intensified many determinants of depression. This study aimed to identify lifestyle and demographic factors associated with depression symptoms among Indians during the pandemic, focusing on a sample from Kolkata, India. An online public survey was conducted, gathering data from 1,834 participants (with 1,767 retained post-cleaning) over three months via social media and email. The survey consisted of 44 questions and was distributed anonymously to ensure privacy. Data were analyzed using statistical methods and machine learning, with principal component analysis (PCA) and analysis of variance (ANOVA) employed for feature selection. K-means clustering divided the pre-processed dataset into five clusters, and a support vector machine (SVM) with a linear kernel achieved 96% accuracy in a multi-class classification problem. The Local Interpretable Model-agnostic Explanations (LIME) algorithm provided local explanations for the SVM model predictions. Additionally, an OWL (web ontology language) ontology facilitated the semantic representation and reasoning of the survey data. The study highlighted a pipeline for collecting, analyzing, and representing data from online public surveys during the pandemic. The identified factors were correlated with depressive symptoms, illustrating the significant influence of lifestyle and demographic variables on mental health. The online survey method proved advantageous for data collection, visualization, and cost-effectiveness while maintaining anonymity and reducing bias. Challenges included reaching the target population, addressing language barriers, ensuring digital literacy, and mitigating dishonest responses and sampling errors. In conclusion, lifestyle and demographic factors significantly impact depression during the COVID-19 pandemic. The study's methodology offers valuable insights into addressing mental health challenges through scalable online surveys, aiding in the understanding and mitigation of depression risk factors.

An Approach to Estimate the Refractive Index and the Electronic Polarizability of the Ternary Ag2O-B2O3-TeO2 Glasses.

Each of the static properties such as refractive index (n0), cation ( ∑ α i $$ \sum {\alpha}_i $$ ), and anion ( α O 2 - $$ {\alpha}_O^{2-} $$ ) oxide polarizabilities for the ternary 30Ag2O⋅xB2O3⋅(70 - x)TeO2 (30AgBTe) glasses has been predicted theoretically from those of the binary 30Ag2O-70B2O3 and 30Ag2O-70TeO2 glasses. This can be done based on two assumptions: that each of these static properties (n0, ∑ α i $$ \sum {\upalpha}_i $$ , and α O 2 - $$ {\upalpha}_{\mathrm{O}}^{2-} $$ ) can be considered as an additive property and that ternary 30AgBTe glasses can be treated as a mixture of two binary 30Ag2O-70B2O3 and 30Ag2O-70TeO2 glasses. In addition, n0 values for the ternary 30AgBTe glasses can be predicted in terms of α O 2 - $$ {\upalpha}_{\mathrm{O}}^{2-} $$ and ∑ α i $$ \sum {\upalpha}_i $$ values for the ternary 30AgBTe glasses, and these later properties can be predicted from that of two binaries like as n0 at first stage. The n0 values obtained by using two methods are exactly the same for the corresponding compositions in the studied glasses, confirming the validity of the two assumptions and the procedure described in the present work. This conclusion is valid for the ternary glasses with a fixed content of either basic former/or modifier oxides for all compositions such as xPbO⋅(40 - x)Sb2O3⋅60B2O3 and 30Ag2O⋅xB2O3⋅(70 - x)TeO2 glasses, respectively.

Are all negative words alike? Behavioral differences in processing negative words associated and not associated with physical and social pain.

Studies examining whether stimulus valence affects cognitive processing and motor responses yield mixed results, possibly due to treating negative words as a homogeneous category. Words related to pain may hold distinct status because of their relevance to survival. Thus, they offer a unique opportunity to investigate semantic influences on cognitive processing. This study aims to determine if words related to physical and social pain elicit stronger aversion than general negative words by assessing the Affective Compatibility Effect in implicit and explicit tasks. In Experiment 1, 35 participants performed a lexical decision task on 60 positive words and 60 negative words, of which 20 not related to pain, 20 related to physical pain, and 20 related to social pain. Participants held down the central key of a keyboard and released it to press a key far from the screen (avoidance condition) or close to the screen (approach condition) for words. In Experiment 2, 43 participants performed a valence evaluation task on the same words. They held down the central key and released it to press a key close to the screen for positive words and a key far from the screen for negative words (congruent condition), or the opposite (incongruent condition). In Experiment 1, we found faster RTs for social pain-related words compared to other categories. We also found faster RTs in the approach condition than in the avoidance condition, regardless of whether valence or semantics were considered as independent variables. In Experiment 2, we found faster RTs in the congruent condition than in the incongruent condition when semantics was considered as independent variable. We also found an interaction valence*condition, with faster RTs for negative words in the congruent condition than in the incongruent condition when valence was considered as independent variable. Our findings suggest that, notwithstanding pain-related words do not affect aversive behaviors compared to negative, pain-unrelated words, they are processed faster when conveying social pain. This supports the hypothesis that the cognitive system differentiates and responds congruently not only based on general semantic categories, like pain, but also possibly based on nuances within it.

Parallel transmit hybrid pulse design for controlled on-resonance magnetization transfer in R1 mapping at 7T.

PURPOSE: This work proposes a "hybrid" RF pulse design method for parallel transmit (pTx) systems to simultaneously control flip angle and root-mean-squared B 1 + $$ {\mathrm{B}}_1^{+} $$ ( B 1 rms $$ {B}_1^{\mathrm{rms}} $$ ). These pulses are generally only designed for flip angle, however, this can lead to uncontrolled B 1 rms $$ {B}_1^{\mathrm{rms}} $$ , which then leads to variable magnetization transfer (MT) effects. We demonstrate the hybrid design approach for quantitative imaging where both flip angle and B 1 rms $$ {B}_1^{\mathrm{rms}} $$ are important. THEORY AND METHODS: A dual cost function optimization is performed containing the normalized mean squared errors of the flip angle and B 1 rms $$ {B}_1^{\mathrm{rms}} $$ distributions weighted by a parameter λ $$ \lambda $$ . Simulations were conducted to study the behavior of both properties when simultaneously optimizing them. In vivo experiments on a 7T MRI system with an 8-channel pTx head coil were carried out to study the effect of the hybrid design approach on variable flip angle R 1 $$ {\mathrm{R}}_1 $$ (= 1/T1) mapping. RESULTS: Simulations showed that both flip angle and B 1 rms $$ {B}_1^{\mathrm{rms}} $$ can be homogenized simultaneously without detriment to either when compared to an individual optimization. By homogenizing flip angle and B 1 rms $$ {B}_1^{\mathrm{rms}} $$ , R 1 $$ {\mathrm{R}}_1 $$ maps were more uniform (coefficient of variation 6.6% vs. 13.0%) compared to those acquired with pulses that only homogenized flip angle. CONCLUSION: The proposed hybrid design homogenizes on-resonance MT effects while homogenizing the flip angle distribution, with only a small detriment in the latter compared to a pulse that just homogenizes flip angle. This improved R 1 $$ {\mathrm{R}}_1 $$ mapping by controlling incidental MT effects, yielding more uniform R 1 $$ {\mathrm{R}}_1 $$ maps.

Prediction of MRI R 2 * $$ {\mathrm{R}}_2

To develop Monte Carlo simulations to predict the relationship of R 2 * $$ {\mathrm{R}}_2^{\ast } $$ with liver fat content at 1.5 T and 3.0 T. For various fat fractions (FFs) from 1% to 25%, four types of virtual liver models were developed by incorporating the size and spatial distribution of fat droplets. Magnetic fields were then generated under different fat susceptibilities at 1.5 T and 3.0 T, and proton movement was simulated for phase accrual and MRI signal synthesis. The synthesized signal was fit to single-peak and multi-peak fat signal models for R 2 * $$ {\mathrm{R}}_2^{\ast } $$ and proton density fat fraction (PDFF) predictions. In addition, the relationships between R 2 * $$ {\mathrm{R}}_2^{\ast } $$ and PDFF predictions were compared with in vivo calibrations and Bland-Altman analysis was performed to quantitatively evaluate the effects of these components (type of virtual liver model, fat susceptibility, and fat signal model) on R 2 * $$ {\mathrm{R}}_2^{\ast } $$ predictions. A virtual liver model with realistic morphology of fat droplets was demonstrated, and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ and PDFF values were predicted by Monte Carlo simulations at 1.5 T and 3.0 T. R 2 * $$ {\mathrm{R}}_2^{\ast } $$ predictions were linearly correlated with PDFF, while the slope was unaffected by the type of virtual liver model and increased as fat susceptibility increased. Compared with in vivo calibrations, the multi-peak fat signal model showed superior performance to the single-peak fat signal model, which yielded an underestimation of liver fat. The R 2 * $$ {\mathrm{R}}_2^{\ast } $$ -PDFF relationships by simulations with fat susceptibility of 0.6 ppm and the multi-peak fat signal model were R 2 * = 0.490 × PDFF + 28.0 $$ {\mathrm{R}}_2^{\ast }=0.490\times \mathrm{PDFF}+28.0 $$ ( R 2 = 0.967 $$ {R}^2=0.967 $$ , p < 0.01 $$ p<0.01 $$ ) at 1.5 T and R 2 * = 0.928 × PDFF + 39.4 $$ {\mathrm{R}}_2^{\ast }=0.928\times \mathrm{PDFF}+39.4 $$ ( R 2 = 0.972 $$ {R}^2=0.972 $$ , p < 0.01 $$ p<0.01 $$ ) at 3.0 T. Monte Carlo simulations provide a new means for R 2 * $$ {\mathrm{R}}_2^{\ast } $$ -PDFF prediction, which is primarily determined by fat susceptibility, fat signal model, and magnetic field strength. Accurate R 2 * $$ {\mathrm{R}}_2^{\ast } $$ -PDFF calibration has the potential to correct the effect of fat on R 2 * $$ {\mathrm{R}}_2^{\ast } $$ quantification, and may be helpful for accurate R 2 * $$ {\mathrm{R}}_2^{\ast } $$ measurements in liver iron overload. In this study, a Monte Carlo simulation of hepatic steatosis was developed to predict the relationship between R 2 * $$ {\mathrm{R}}_2^{\ast } $$ and PDFF. Furthermore, the effects of fat droplet morphology, fat susceptibility, fat signal model, and magnetic field strength were evaluated for the R 2 * $$ {\mathrm{R}}_2^{\ast } $$ -PDFF calibration. Our results suggest that Monte Carlo simulations provide a new means for R 2 * $$ {\mathrm{R}}_2^{\ast } $$ -PDFF prediction and this means can be easily generated for various regimes, such as simulations with higher fields and different echo times, as well as correction of magnetic susceptibility measurements for liver iron quantification.

PresRecRF: Herbal prescription recommendation via the representation fusion of large TCM semantics and molecular knowledge.

BACKGROUND: Herbal prescription recommendation (HPR) is a hotspot in the research of clinical intelligent decision support. Recently plentiful HPR models based on deep neural networks have been proposed. Owing to insufficient data, e.g., lack of knowledge of molecular, TCM theory, and herbal dosage in HPR modeling, the existing models suffer from challenges, e.g., plain prediction precision, and are far from real-world clinics. PURPOSE: To address these problems, we proposed a novel herbal prescription recommendation model with the representation fusion of large TCM semantics and molecular knowledge (termed PresRecRF). STUDY DESIGN AND METHODS: PresRecRF comprises three key modules. The representation learning module consists of two key components: a molecular knowledge representation component, integrating molecular knowledge into the herb-symptom-protein knowledge graph to enhance representations for herbs and symptoms; and a TCM knowledge representation component, leveraging BERT and ChatGPT to acquire TCM knowledge-enriched semantic representations. We introduced a representation fusion module to effectively merge molecular and TCM semantic representations. In the herb recommendation module, a multi-task objective loss is implemented to predict both herbs and dosages simultaneously. RESULTS: The experimental results on two clinical datasets show that PresRecRF can achieve the optimal performance. Further analysis of ablation, hyper-parameters, and case studies indicate the effectiveness and reliability of the proposed model, suggesting that it can help precision medicine and treatment recommendations. CONCLUSION: The entire process of the proposed PresRecRF model closely mirrors the actual diagnosis and treatment procedures carried out by doctors, which are better applied in real clinical scenarios. The source codes of PresRecRF is available at https://github.com/2020MEAI/PresRecRF.

Muscle fatigue, pedalling technique and the V ̇ O 2 ${{\dot{V}}_{{{{\mathrm{O}}}_{\mathrm{2}}}}}$ slow component during cycling.

Above the first lactate threshold, the steady-state V ̇ O 2 ${{\dot{V}}_{{{{\mathrm{O}}}_{\mathrm{2}}}}}$ is delayed or prevented due to the V ̇ O 2 ${{\dot{V}}_{{{{\mathrm{O}}}_{\mathrm{2}}}}}$ slow component ( V ̇ O 2 SC ${{\dot{V}}_{{{{\mathrm{O}}}_{\mathrm{2}}}{\mathrm{SC}}}}$ ). This phenomenon has been associated with muscle fatigue, but evidence for a causal relationship is equivocal. Moreover, little is known about the contribution of pedalling technique adjustments to V ̇ O 2 SC ${{\dot{V}}_{{{{\mathrm{O}}}_{\mathrm{2}}}{\mathrm{SC}}}}$ during fatiguing cycling exercise. Eleven participants completed constant power trials at 10% above the second lactate threshold. Muscle fatigue was assessed, utilizing femoral nerve stimulation and instrumented pedals, while V ̇ O 2 ${{\dot{V}}_{{{{\mathrm{O}}}_{\mathrm{2}}}}}$ , quadriceps oxygenation, electromyography (EMG) and pedal force components were measured. Correlations between physiological and mechanical variables were estimated at group and individual levels. Group correlations revealed moderate values for V ̇ O 2 SC ${{\dot{V}}_{{{{\mathrm{O}}}_{\mathrm{2}}}{\mathrm{SC}}}}$ with quadriceps twitch force (r = -0.51) and muscle oxygenation (r = -0.52), while weak correlations were observed for EMG amplitude (r = 0.26) and EMG mean power frequency (r = -0.16), and with pedalling mechanical variables such as peak total downstroke force (r = -0.16), minimum total upstroke force (r = -0.16) and upstroke index of effectiveness (r = 0.16). The findings here align with prior literature reporting significant correlations between the magnitude of muscle fatigue and that of V ̇ O 2 SC ${{\dot{V}}_{{{{\mathrm{O}}}_{\mathrm{2}}}{\mathrm{SC}}}}$ , although there was large interindividual variability for all the reported correlations. Considering the heterogeneity in the data, it is difficult to determine the relative impact of pedalling technique adjustments on V ̇ O 2 SC ${{\dot{V}}_{{{{\mathrm{O}}}_{\mathrm{2}}}{\mathrm{SC}}}}$ overall, but the present study opens the possibility that in some cases, increases in V ̇ O 2 ${{\dot{V}}_{{{{\mathrm{O}}}_{\mathrm{2}}}}}$ secondary to technical adjustments may be 'superimposed' on the underlying V ̇ O 2 SC ${{\dot{V}}_{{{{\mathrm{O}}}_{\mathrm{2}}}{\mathrm{SC}}}}$ .

Improved liver fat and R 2 * quantification at 0.55 T using locally low-rank denoising.

PURPOSE: To improve liver proton density fat fraction (PDFF) and R 2 * $$ {R}_2^{\ast } $$ quantification at 0.55 T by systematically validating the acquisition parameter choices and investigating the performance of locally low-rank denoising methods. METHODS: A Monte Carlo simulation was conducted to design a protocol for PDFF and R 2 * $$ {R}_2^{\ast } $$ mapping at 0.55 T. Using this proposed protocol, we investigated the performance of robust locally low-rank (RLLR) and random matrix theory (RMT) denoising. In a reference phantom, we assessed quantification accuracy (concordance correlation coefficient [ ρ c $$ {\rho}_c $$ ] vs. reference values) and precision (using SD) across scan repetitions. We performed in vivo liver scans (11 subjects) and used regions of interest to compare means and SDs of PDFF and R 2 * $$ {R}_2^{\ast } $$ measurements. Kruskal-Wallis and Wilcoxon signed-rank tests were performed (p < 0.05 considered significant). RESULTS: In the phantom, RLLR and RMT denoising improved accuracy in PDFF and R 2 * $$ {R}_2^{\ast } $$ with ρ c $$ {\rho}_c $$ >0.992 and improved precision with >67% decrease in SD across 50 scan repetitions versus conventional reconstruction (i.e., no denoising). For in vivo liver scans, the mean PDFF and mean R 2 * $$ {R}_2^{\ast } $$ were not significantly different between the three methods (conventional reconstruction; RLLR and RMT denoising). Without denoising, the SDs of PDFF and R 2 * $$ {R}_2^{\ast } $$ were 8.80% and 14.17 s-1. RLLR denoising significantly reduced the values to 1.79% and 5.31 s-1 (p < 0.001); RMT denoising significantly reduced the values to 2.00% and 4.81 s-1 (p < 0.001). CONCLUSION: We validated an acquisition protocol for improved PDFF and R 2 * $$ {R}_2^{\ast } $$ quantification at 0.55 T. Both RLLR and RMT denoising improved the accuracy and precision of PDFF and R 2 * $$ {R}_2^{\ast } $$ measurements.

Mapping and modeling the semantic space of math concepts.

Mathematics is an underexplored domain of human cognition. While many studies have focused on subsets of math concepts such as numbers, fractions, or geometric shapes, few have ventured beyond these elementary domains. Here, we attempted to map out the full space of math concepts and to answer two specific questions: can distributed semantic models, such a GloVe, provide a satisfactory fit to human semantic judgements in mathematics? And how does this fit vary with education? We first analyzed all of the French and English Wikipedia pages with math contents, and used a semi-automatic procedure to extract the 1000 most frequent math terms in both languages. In a second step, we collected extensive behavioral judgements of familiarity and semantic similarity between them. About half of the variance in human similarity judgements was explained by vector embeddings that attempt to capture latent semantic structures based on cooccurence statistics. Participants' self-reported level of education modulated familiarity and similarity, allowing us to create a partial hierarchy among high-level math concepts. Our results converge onto the proposal of a map of math space, organized as a database of math terms with information about their frequency, familiarity, grade of acquisition, and entanglement with other concepts.

A Novel Method for Nonparametric Statistical Inference for Niche Overlap in Multiple Species.

The understanding of species interactions and ecosystem dynamics hinges upon the study of ecological niches. Quantifying the overlap of Hutchinsonian-niches has garnered significant attention, with many recent publications addressing the issue. Prior work on estimating niche overlap often did not provide confidence intervals or assumed multivariate normality, seriously limiting applications in ecology, and biodiversity research. This paper extends a nonparametric approach, previously applied to the two-species case, to multiple species. For estimation, a consistent plug-in estimator based on rank sums is proposed and its asymptotic distribution is derived under weak conditions. The novel methodology is then applied to a study comparing the ecological niches of the Eurasian eagle owl, common buzzard, and red kite. These species share a habitat in Central Europe but exhibit distinct population trends. The analysis explores their breeding habitat preferences, considering the intricate competition dynamics and utilizing the nonparametric approach to niche overlap estimation. Our proposed method provides a valuable inferential tool for the quantitative evaluation of differences and overlap between niches.

Multiple dimensions of syntactic structure are resolved earliest in posterior temporal cortex.

How we combine minimal linguistic units into larger structures remains an unresolved topic in neuroscience. Language processing involves the abstract construction of 'vertical' and 'horizontal' information simultaneously (e.g., phrase structure, morphological agreement), but previous paradigms have been constrained in isolating only one type of composition and have utilized poor spatiotemporal resolution. Using intracranial recordings, we report multiple experiments designed to separate phrase structure from morphosyntactic agreement. Epilepsy patients (n = 10) were presented with auditory two-word phrases grouped into pseudoword-verb ('trab run') and pronoun-verb either with or without Person agreement ('they run' vs. 'they runs'). Phrase composition and Person violations both resulted in significant increases in broadband high gamma activity approximately 300 ms after verb onset in posterior middle temporal gyrus (pMTG) and posterior superior temporal sulcus (pSTS), followed by inferior frontal cortex (IFC) at 500 ms. While sites sensitive to only morphosyntactic violations were distributed, those sensitive to both composition types were generally confined to pSTS/pMTG and IFC. These results indicate that posterior temporal cortex shows the earliest sensitivity for hierarchical linguistic structure across multiple dimensions, providing neural resources for distinct windows of composition. This region is comprised of sparsely interwoven heterogeneous constituents that afford cortical search spaces for dissociable syntactic relations.

Kin Cognition and Communication: What Talking, Gesturing, and Drawing About Family Can Tell us About the Way We Think About This Core Social Structure.

When people talk about kinship systems, they often use co-speech gestures and other representations to elaborate. This paper investigates such polysemiotic (spoken, gestured, and drawn) descriptions of kinship relations, to see if they display recurring patterns of conventionalization that capture specific social structures. We present an exploratory hypothesis-generating study of descriptions produced by a lesser-known ethnolinguistic community to the cognitive sciences: the Paamese people of Vanuatu. Forty Paamese speakers were asked to talk about their family in semi-guided kinship interviews. Analyses of the speech, gesture, and drawings produced during these interviews revealed that lineality (i.e., mother's side vs. father's side) is lateralized in the speaker's gesture space. In other words, kinship members of the speaker's matriline are placed on the left side of the speaker's body and those of the patriline are placed on their right side, when they are mentioned in speech. Moreover, we find that the gesture produced by Paamese participants during verbal descriptions of marital relations are performed significantly more often on two diagonal directions of the sagittal axis. We show that these diagonals are also found in the few diagrams that participants drew on the ground to augment their verbo-gestural descriptions of marriage practices with drawing. We interpret this behavior as evidence of a spatial template, which Paamese speakers activate to think and communicate about family relations. We therefore argue that extending investigations of kinship structures beyond kinship terminologies alone can unveil additional key factors that shape kinship cognition and communication and hereby provide further insights into the diversity of social structures.

Spherical echo-planar time-resolved imaging (sEPTI) for rapid 3D quantitative T 2 * and susceptibility imaging.

PURPOSE: To develop a 3D spherical EPTI (sEPTI) acquisition and a comprehensive reconstruction pipeline for rapid high-quality whole-brain submillimeter T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and QSM quantification. METHODS: For the sEPTI acquisition, spherical k-space coverage is utilized with variable echo-spacing and maximum kx ramp-sampling to improve efficiency and signal incoherency compared to existing EPTI approaches. For reconstruction, an iterative rank-shrinking B0 estimation and odd-even high-order phase correction algorithms were incorporated into the reconstruction to better mitigate artifacts from field imperfections. A physics-informed unrolled network was utilized to boost the SNR, where 1-mm and 0.75-mm isotropic whole-brain imaging were performed in 45 and 90 s at 3 T, respectively. These protocols were validated through simulations, phantom, and in vivo experiments. Ten healthy subjects were recruited to provide sufficient data for the unrolled network. The entire pipeline was validated on additional five healthy subjects where different EPTI sampling approaches were compared. Two additional pediatric patients with epilepsy were recruited to demonstrate the generalizability of the unrolled reconstruction. RESULTS: sEPTI achieved 1.4 × $$ \times $$ faster imaging with improved image quality and quantitative map precision compared to existing EPTI approaches. The B0 update and the phase correction provide improved reconstruction performance with lower artifacts. The unrolled network boosted the SNR, achieving high-quality T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and QSM quantification with single average data. High-quality reconstruction was also obtained in the pediatric patients using this network. CONCLUSION: sEPTI achieved whole-brain distortion-free multi-echo imaging and T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and QSM quantification at 0.75 mm in 90 s which has the potential to be useful for wide clinical applications.

Spiral 3DREAM sequence for fast whole-brain B1 mapping.

PURPOSE: This work demonstrates a new variant of the 3DREAM sequence for whole-brain B 1 + $$ {\mathrm{B}}_1^{+} $$ mapping employing a three-dimensional (3D) stack-of-spirals readout. The spiral readout reduces the echo train length after the STEAM preparation in order to overcome the significant blurring in STE* images due to the decreasing STE* signal with each excitation pulse. METHODS: The 3DREAM sequence rapidly acquires two contrasts to calculate whole-brain flip angle maps. In the proposed spiral 3DREAM sequence, the Cartesian readout scheme is replaced by an accelerated 3D stack-of-spirals readout with a CAIPIRINHA sampling scheme. Phantom experiments were conducted to compare flip angle maps of the spiral 3DREAM sequence to a Cartesian 3DREAM sequence, an actual flip-angle-imaging (AFI) sequence, the dual-angle method, and the Bloch-Siegert shift method. Afterwards, the results were validated in vivo acquiring flip angle maps from five subjects. RESULTS: Flip angle maps of the spiral 3DREAM sequences showed high agreement with the reference methods both in phantom and in vivo experiments. Blurring in STE* images and flip angle maps was reduced compared to the Cartesian 3DREAM sequence. CONCLUSION: The spiral 3DREAM sequence utilizes a fast readout minimizing the echo train length of the imaging train. This reduces blurring in STE* images as well as the total acquisition time and increases the effective resolution of B 1 + $$ {\mathrm{B}}_1^{+} $$ maps.

Functional interactions underlying visuospatial orthographic processes in Chinese reading.

As a logographic writing system, Chinese reading involves the processing of visuospatial orthographic (ORT) properties. However, this aspect has received relatively less attention in neuroimaging research, which has tended to emphasize phonological (PHO) and semantic (SEM) aspects in processing Chinese characters. Here, we compared the functional correlates supporting all these three processes in a functional MRI single-character reading study, in which 35 native Chinese adults were asked to make ORT, PHO, and SEM judgments in separate task-specific activation blocks. Our findings revealed increased involvement of the right hemisphere in processing Chinese visuospatial orthography, particularly evident in the right ventral occipito-temporal cortex (vOTC). Additionally, time course analysis revealed that the left superior parietal gyrus (SPG) was initially involved in SEM processing but contributed to the visuospatial processing of words in a later time window. Finally, ORT processing demonstrated stronger recruitment of left vOTC-SPG-middle frontal gyrus (MFG) functional connectivity compared to SEM processing. This functional coupling correlated with reduced regional engagement of the left vOTC and MFG, highlighting that visuospatial ORT processes in reading Chinese rely on functional interactions among key regions rather than local regional processes. In conclusion, these findings underscore visuospatial ORT processes as a distinctive feature of reading logographic characters.