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‘Early bursts' of morphological disparity (i.e. diversity of anatomical types) are common in the fossil record. We typically model such bursts as elevated early rates of independent character change. Developmental theory predicts that modules of linked characters can change together, which would mimic the effects of elevated independent rates on disparity. However, correlated change introducing suboptimal states should encourage breakup (parcellation) of character suites allowing new (or primitive) states to evolve until new suites arise (relinkage). Thus, correlated change–breakup–relinkage presents mechanisms for early bursts followed by constrained evolution. Here, I analyse disparity in 257 published character matrices of fossil taxa. For each clade, I use inverse-modelling to infer most probably rates of independent change given both time-homogeneous and separate ‘early versus late' rates. These rates are used to estimate expected disparity given both independent change models. The correlated change–breakup–relinkage model also predicts elevated frequencies of compatible character state-pairs appearing out of order in the fossil record (e.g. 01 appearing after 00 and 11; = low stratigraphic compatibility), as one solution to suboptimal states induced by correlated change is a return to states held before that change. As predicted by the correlated change–breakup–relinkage model, early disparity in the majority of clades both exceeds the expectations of either independent change model and excess early disparity correlates with low stratigraphic compatibility among character-pairs. Although it is possible that other mechanisms for linking characters contribute to these patterns, these results corroborate the idea that reorganization of developmental linkages is often associated with the origin of groups that biologists recognize as new higher taxa and that such reorganization offers a source of new disparity throughout the Phanerozoic.

Convolutional neural networks (CNNs) have had great success with regard to the object classification problem. For character classification, we found that training and testing using accurately segmented character regions with CNNs resulted in higher accuracy than when roughly segmented regions were used. Therefore, we expect to extract complete character regions from scene images. Text in natural scene images has an obvious contrast with its attachments. Many methods attempt to extract characters through different segmentation techniques. However, for blurred, occluded, and complex background cases, those methods may result in adjoined or over segmented characters. In this paper, we propose a scene word recognition model that integrates words from small pieces to entire after-cluster-based segmentation. The segmented connected components are classified as four types: background, individual character proposals, adjoined characters, and stroke proposals. Individual character proposals are directly inputted to a CNN that is trained using accurately segmented character images. The sliding window strategy is applied to adjoined character regions. Stroke proposals are considered as fragments of entire characters whose locations are estimated by a stroke spatial distribution system. Then, the estimated characters from adjoined characters and stroke proposals are classified by a CNN that is trained on roughly segmented character images. Finally, a lexicondriven integration method is performed to obtain the final word recognition results. Compared to other word recognition methods, our method achieves a comparable performance on Street View Text and the ICDAR 2003 and ICDAR 2013 benchmark databases. Moreover, our method can deal with recognizing text images of occlusion and improperly segmented text images.

The study seeks to examine the incorporation of citizenship education into Physical Education (PE) classes in Indonesia to mitigate character degradation. Employing the systematic literature review methodology, the study collected data by searching from Google Scholar, specifically focusing on journal articles indexed in the Scopus databases. In addition, the articles must be published between 2019 and 2024. The keywords were specified as the following: \"Integration AND Civic Education AND Character AND Physical Education AND Junior High School AND Indonesia\". The PRISMA technique was used during the article identification process. The study found 13 articles that aligned with the theme and met the inclusion criteria. The results indicated that incorporating civic education into physical education (PE) at Junior High School (SMP) in Indonesia successfully mitigated student character degradation. Some principles that contribute to this mitigation and helped students cultivate stronger characters were tolerance, collaboration, and responsibility. This integration facilitates the construction of a comprehensive educational curriculum that encompasses not only physical components but also the cultivation of character and civic values. As a result, it contributes to the building of a morally upright and ethically conscious generation of students. Keywords: Integration, Civic Education, Character, Physical Education, Junior High School

Accurate modeling of the complexity of morphological evolution is crucial for morphological phylogenetics and for performing tests on a wide variety of evolutionary scenarios. In this context, morphological integration and the problem of correlated categorical characters represent a major challenge. In particular, the magnitude and implications of correlations among serially homologous structures such as teeth have been much debated but were never tested statistically within a broad phylogenetic context. Here, we present a large-scale empirical study analyzing the serial variation of cingular crests on successive molars (M1, M2, and M3)of 274 placental species in aphylogenetic context. Both likelihood analyses and analysis of phylogenetic co-distributions demonstrated highly correlated evolution in the entire sample and thus the non-independence of these serial features at a macroevolutionary scale. Likelihood analyses show that their serial variation should be better scored within a single composite character model with constrained paths for transitions enabling simultaneous changes on all three molars, which suggests a strong developmental or genetic integration. These results are congruent with current genetic and developmental knowledge related to dental morphological variation and call into question the frequent use of separate characters scored on serially homologous structures of the dentition in phylogenetic analyses. Overall, they provide long-overdue and clear empirical evidence that in-depth studies of patterns of integration constitute an essential step toward more realistic character construction and modeling. This approach is critical for more accurate morphological phylogenetics and, more generally, for testing macroevolutionary scenarios on groups of correlated characters.

Schizophrenia has been primarily conceptualized as a disorder of high-order cognitive functions with deficits in executive brain regions. Yet due to the increasing reports of early sensory processing deficit, recent models focus more on the developmental effects of impaired sensory process on high-order functions. The present study examined whether this pathological interaction relates to an overarching system-level imbalance, specifically a disruption in macroscale hierarchy affecting integration and segregation of unimodal and transmodal networks. We applied a novel combination of connectome gradient and stepwise connectivity analysis to resting-state fMRI to characterize the sensorimotor-to-transmodal cortical hierarchy organization (96 patients 122 controls). We demonstrated compression of the cortical hierarchy organization in schizophrenia, with a prominent compression from the sensorimotor region and a less prominent compression from the frontal-parietal region, resulting in a diminished separation between sensory and fronto-parietal cognitive systems. Further analyses suggested reduced differentiation related to atypical functional connectome transition from unimodal to transmodal brain areas. Specifically, we found hypo-connectivity within unimodal regions and hyper-connectivity between unimodal regions and fronto-parietal and ventral attention regions along the classical sensation-to-cognition continuum (voxel-level corrected, < 0.05). The compression of cortical hierarchy organization represents a novel and integrative system-level substrate underlying the pathological interaction of early sensory and cognitive function in schizophrenia. This abnormal cortical hierarchy organization suggests cascading impairments from the disruption of the somatosensory-motor system and inefficient integration of bottom-up sensory information with attentional demands and executive control processes partially account for high-level cognitive deficits characteristic of schizophrenia.

The neural process of contextual integration has been examined through the phenomenology of semantic incongruence of words. The present study investigated whether the effort of contextual integration would be heightened by the increased demand of selective attention and attention orientation to unfamiliar Chinese stroke style and sequence. It also examined whether visual imagery of unfamiliar stroke style and sequence would mitigate the effort of contextual integration of unfamiliar Chinese stroke. Nineteen participants take part in two cognitive tasks: (a) imagery of Chinese strokes and (b) detection of Chinese familiar and unfamiliar stroke style. An electroencephalogram was concurrently recorded for the analysis of event-related potential (ERP). Results revealed significant differences in attention orientation and effort of contextual integration between familiar and unfamiliar Chinese strokes, as indicated by larger amplitudes of N160 (100–200 ms) & P200 (260–380 ms) components. Furthermore, a larger amplitude of N400 (300–500 ms) component, signifying the neural process of integrating external from the context, was obtained when individuals viewed unfamiliar Chinese strokes. These findings suggest a cognitive effort was needed to process unfamiliar Chinese stimuli, followed by a greater mental effort required for contextual integration of the unfamiliar stimuli. Furthermore, top-down control of visual imagery would facilitate the process of contextual integration via generating internal representation. This finding provides a new insight that the effort expended in contextual integration may be associated with both attentional control and the generation of internal representation from long-term storage across visual stimuli with varying levels of stimulus familiarity. In summary, our study provided insights into the cognitive mechanisms underlying attentional control, contextual integration, and the role of visual imagery in the processing of stimuli with different levels of familiarity. Furthermore, it suggested the potential utility of the N400 component as a biomarker for assessing attention control and memory retrieval functions.

Neophobia (the fearful reaction to novel stimuli or situations) has a crucial effect on individual fitness and can vary within and across species. However, the factors predicting this variation are still unclear. In this study, we assessed whether individual characteristics (rank, social integration, sex) and species socio-ecological characteristics (dietary breadth, group size, domestication) predicted variation in neophobia. For this purpose, we conducted behavioral observations and experimental tests on 78 captive individuals belonging to 10 different ungulate species—an ideal taxon to study inter-specific variation in neophobia given their variety in socio-ecological characteristics. Individuals were tested in their social groups by providing them with familiar food, half of which had been positioned close to a novel object. We monitored the individual latency to approach and eat food and the proportion of time spent in its proximity. Using a phylogenetic approach and social network analyses, we showed that across ungulate species neophobia was higher in socially more integrated individuals, as compared to less integrated ones. In contrast, rank and sex did not predict inter-individual differences in neophobia. Moreover, species differed in their levels of neophobia, with Barbary sheep being on average less neophobic than all the other study species. As group size in Barbary sheep was larger than in all the other study species, these results support the hypothesis that larger group size predicts lower levels of neophobia, and confirm ungulates as a highly promising taxon to study animal behavior and cognition with a comparative perspective.

Detrimental to individuals and society, online hateful messages have recently become a major social issue. Among them, one new type of hateful message, “hateful meme”, has emerged and brought difficulties in traditional deep learning-based detection. Because hateful memes were formatted with both text captions and images to express users’ intents, they cannot be accurately identified by singularly analyzing embedded text captions or images. In order to effectively detect a hateful meme, the algorithm must possess strong vision and language fusion capability. In this study, we move closer to this goal by feeding a triplet by stacking the visual features, object tags, and text features of memes generated by the object detection model named Visual features in Vision-Language (VinVl) and the optical character recognition (OCR) technology into a Transformer-based Vision-Language Pre-Training Model (VL-PTM) OSCAR+ to perform the cross-modal learning of memes. After fine-tuning and connecting to a random forest (RF) classifier, our model (OSCAR+RF) achieved an average accuracy and AUROC of 0.684 and 0.768, respectively, on the hateful meme detection task in a public test set, which was higher than the other eleven (11) published baselines. In conclusion, this study has demonstrated that VL-PTMs with the addition of anchor points can improve the performance of deep learning-based detection of hateful memes by involving a more substantial alignment between the text caption and visual information.

This study aimed to investigate the functional connectivity in the brain during the cross-modal integration of polyphonic characters in Chinese audio-visual sentences. The visual sentences were all semantically reasonable and the audible pronunciations of the polyphonic characters in corresponding sentences contexts varied in four conditions. To measure the functional connectivity, correlation, coherence and phase synchronization index (PSI) were used, and then multivariate pattern analysis was performed to detect the consensus functional connectivity patterns. These analyses were confined in the time windows of three event-related potential components of P200, N400 and late positive shift (LPS) to investigate the dynamic changes of the connectivity patterns at different cognitive stages. We found that when differentiating the polyphonic characters with abnormal pronunciations from that with the appreciate ones in audio-visual sentences, significant classification results were obtained based on the coherence in the time window of the P200 component, the correlation in the time window of the N400 component and the coherence and PSI in the time window the LPS component. Moreover, the spatial distributions in these time windows were also different, with the recruitment of frontal sites in the time window of the P200 component, the frontal-central-parietal regions in the time window of the N400 component and the central-parietal sites in the time window of the LPS component. These findings demonstrate that the functional interaction mechanisms are different at different stages of audio-visual integration of polyphonic characters.

We study averages involving the Jacobi quadratic symbol ( n m ) in regions where the product mn is bounded by a large parameter. We show that these averages exhibit cancellation whenever the summation is restricted to square-free integers bounded away from the axes.