A84: Factors Influencing Parents\u27 Intention to Involve Autistic Preschoolers in Outdoor Physical Activities

Purpose: Outdoor physical activities (OPA) can not only improve the physical fitness and health of autistic preschool children, but also provide an indispensable opportunity for their social learning and interaction. However, parents’ intentions of providing OPA for their autistic children are complex due to reasons such as potential risk. Theory of Planned Behavior（TPB）has conceptualized that attitude (AT), subjective norms (SN), and perceived behavioral control (PBC) are influential factors of behavioral intention. Perceived risk and perceived usefulness are suggested to associate with one’s intention, therefore, the purpose of this study was to test an extended TPB model on parent’s intention of providing OPA among parents of autistic children. Methods: This was a cross-sectional study. A convenient sample of parents of 301 autistic preschoolers (mean age = 3.45±1.10 years old; boys=219; girls = 68) were recruited. Parents reported to questionnaires assessing their AT, SN, PBC, and intention (Ajzen, 1991; Yang, 2017) as well as perceived risk and perceived usefulness of providing OPA for their autistic children (Davis et al., 1989; Yu, 2016). Structural Equation Modeling (SEM) using SmartPLS software was employed to investigate the extended TPB model by including perceived risk and perceived usefulness (exogenous variables) with AT, SN, PBC to synergistically predict intention (endogenous variable). Results: The results revealed that autistic preschooler parents’ perceived usefulness (p \u3c 0.01, f2= 0.087）had a significant and positive prediction on intention in addition to the significant contributions from AT (p \u3c 0.01, f2=0.053), SN (p \u3c 0.01, f2=0.047), and PBC (p \u3c 0.01, f2=0.060). However, perceived risk (p \u3c 0.01, f2= 0.070) had a significant and negative prediction on intention. Besides, perceived usefulness (p \u3c 0.01, f2= 0.108) was positively correlated with AT and AT partially mediated the association between perceived usefulness and intention (Variance Accounted For= 23.2%). In general, perceived usefulness, PBC, AT, SN and perceived risk had a high explanatory power to intention (R2=0.536). Conclusion: The extended TPB model demonstrated to be a useful framework to explain autistic preschooler parents’ intention of providing OPA for their autistic children. Perceived risk and perceived usefulness are critical to parents’ intention in addition to PBC, AT and SN, which should also be the targets of intervention in practice. This finding also suggests practitioners may help parents’ understand the usefulness of OPA to help autistic preschoolers’ parents form positive attitude of OPA, then boosting their intention to engage their autistic children in OPA

1,3-Dioxo-2,3-dihydro-1H-isoindol-2-yl 2,3,4-tri-O-acetyl-β-d-xyloside

The title compound, C19H19NO10, was obtained from the reaction of α-d-1-bromo-2,3,4-tri-O-acetylxylose with N-hy­droxy­phthalimide in the presence of potassium carbonate. The asymmetric unit contains two independent mol­ecules, in which the O—CH—O—N torsion angles are 73.0 (4) and 65.0 (4)°. The hexa­pyranosyl rings adopt chair conformations and the substituent groups are in equatorial positions. In the crystal, mol­ecules are linked by nonclassical C—H⋯O hydrogen bonds

The Effect of Three Different Meditation Exercises on Hypertension: A Network Meta-Analysis

We aimed to use the pairwise and network meta-analysis to estimate the effects of different meditation exercises on the control of systolic blood pressure (SBP) and diastolic blood pressure (DBP). Randomized controlled trials (RCTs) were retrieved from PubMed and Embase up to June 2016, which are published in English and reported on meditation exercise for hypertensive patients. Risks of bias assessment of the included studies were assessed by Cochrane Collaboration Recommendations and network meta-analysis was performed by ADDIS. Mean difference (MD) and its 95% confidence interval (CI) were used as the effect size. A number of 19 RCTs were included in this study. Results of pairwise comparisons indicated that meditation exercise could significantly decrease the SBP and DBP, compared with other interventions (MD = −7.10, 95% CI: −10.82 to −3.39; MD = −4.02, 95% CI: −6.12 to −1.92). With good consistence and convergence, network meta-analysis showed that there were no significant differences between meditation and other interventions on SBP. For DBP, Qigong was significantly lower than “no intervention” (MD = −11.73, 95% CI: −19.85 to −3.69). Qigong may be the optimal exercise way in lowering SBP and DBP of hypertensive patients, but a detailed long-term clinical research should be needed in the future

Identifying Connectome Module Patterns via New Balanced Multi-Graph Normalized Cut.

Computational tools for the analysis of complex biological networks are lacking in human connectome research. Especially, how to discover the brain network patterns shared by a group of subjects is a challenging computational neuroscience problem. Although some single graph clustering methods can be extended to solve the multi-graph cases, the discovered network patterns are often imbalanced, e.g. isolated points. To address these problems, we propose a novel indicator constrained and balanced multi-graph normalized cut method to identify the connectome module patterns from the connectivity brain networks of the targeted subject group. We evaluated our method by analyzing the weighted fiber connectivity networks

Analysis of Metabolic Alterations Related to Pathogenic Process of Diabetic Encephalopathy Rats

Diabetic encephalopathy (DE) is a diabetic complication characterized by alterations in cognitive function and nervous system structure. The pathogenic transition from hyperglycemia to DE is a long-term process accompanied by multiple metabolic disorders. Exploring time-dependent metabolic changes in hippocampus will facilitate our understanding of the pathogenesis of DE. In the present study, we first performed behavioral and histopathological experiments to confirm the appearance of DE in rats with streptozotocin-induced diabetes. We then utilized nuclear magnetic resonance-based metabonomics to analyze metabolic disorders in the hippocampus at different stages of DE. After 1 week, we observed no cognitive or structural impairments in diabetic rats, although some metabolic changes were observed in local hippocampal extracts. At 5 weeks, while cognitive function was still normal, we then examined initial levels of neuronal apoptosis. The characteristic metabolic changes of this stage included elevated levels of energy metabolites (i.e., ATP, ADP, AMP, and creatine phosphate/creatine). At 9 weeks, significant cognitive decline and histopathological brain damage were observed, in conjunction with reduced levels of some amino acids. Thus, this stage was classified as the DE period. Our findings indicated that the pathogenesis of DE is associated with time-dependent alterations in metabolic features in hippocampal regions, such as glycolysis, osmoregulation, energy metabolism, choline metabolism, branched-chain amino acid metabolism, and the glutamate–glutamine cycle. Furthermore, we observed alterations in levels of lactate and its receptor in hippocampal cells, which may be involved in the pathogenesis of DE

Maternal face processing in Mosuo preschool children

Instinctively responding to maternal face is an evolutionary function of enhancing survival and development. However, because of the confounding nature of familiarity, little is known concerning the neural mechanism involved in maternal face recognition. We had a rare opportunity to examine Mosuo preschool children who were raised in a matrilineal society in which mothers and aunts represent equally familiar faces to the children. The participants were exposed to photographs of their mother's face, aunt's face, and an unfamiliar female's faces during electroencephalography (EEG) recording. The EEG results showed that the mother's face elicited a more negative N1 component, a larger left N170 component, and a larger P300 component; both the mother's and aunt's faces elicited a larger right N170 component. These results suggest that the emotional attachment between mother and child has neural ramifications across three successive face processing stages that are distinguished from the neural effects of facial familiarity. (C) 2014 Elsevier B.V. All rights reserved

Evaluation of LAI Estimation of Mangrove Communities Using DLR and ELR Algorithms With UAV, Hyperspectral, and SAR Images

The high-precision estimation of mangrove leaf area index (LAI) using a deep learning regression algorithm (DLR) always requires a large amount of training sample data. However, it is difficult for LAI field measurements to collect a sufficient amount of sample data in mangrove wetlands. To tackle this challenge, this paper proposed an approach for expanding training samples and quantitatively evaluated the performance of estimating LAI for mangrove communities using Deep Neural Networks (DNN) and Transformer algorithms. This study also explored the effects of unmanned aerial vehicle (UAV) and Sentinel-2A multispectral, orbital hyper spectral (OHS), and GF-3 SAR images on LAI estimation of different mangrove communities. Finally, this paper evaluated the LAI estimation ability of mangrove communities using ensemble learning regression (ELR) and DLR algorithms. The results showed that: (1) the UAV images achieved the better LAI estimation of different mangrove communities (R2 = 0.5974–0.6186), and GF-3 SAR images were better for LAI estimation of Avicennia marina with high coverage (R2 = 0.567). The optimal spectral range for estimating LAI for mangroves in the optical images was between 650–680 nm. (2) The ELR model outperformed single base model, and produced the high-accuracy LAI estimation (R2 = 0.5266–0.713) for different mangrove communities. (3) The average accuracy (R2) of the ELR model was higher by 0.0019–0.149 than the DLR models, which demonstrated that the ELR model had a better capability (R2 = 0.5865–0.6416) in LAI estimation. The Transformer-based LAI estimation of A. marina (R2 = 0.6355) was better than the DNN model, while the DNN model produced higher accuracy for Kandelia candel (KC) (R2 = 0.5577). (4) With the increase in the expansion ratio of the training sample (10–50%), the LAI estimation accuracy (R2) of DNN and Transformer models for different mangrove communities increased by 0.1166–0.2037 and 0.1037–0.1644, respectively. Under the same estimation accuracy, the sample enhancement method in this paper could reduce the number of filed measurements by 20–40%