Design Strategy of Community Greenway Connectivity of High-density Urban Asia – A Case Study on Beijing

In the high-density Asian cities which expand rapidly and witness explosive growth in population, the construction of urban community greenways can effectively mitigate the heavy pressure that human beings impose on natural and humanistic environment. In Beijing, poor connectivity is one of the major challenges community greenway construction faces. This paper performs a field survey on the established community greenways in Beijing and their surrounding communities, finding that greenway connectivity is affected by the problems like interference with motorways and unsound greenway planning system in development process. The survey analysis demonstrates that the poor connectivity of community greenways is embodied between greenway, community and surrounding service facilities. To address the problems above, a detailed study on the strategies that improve connectivity of community greenways is conducted

Influence of casting temperature on microstructures and mechanical properties of Cu50Zr45.5Ti2.5Y2 metallic glass prepared using copper mold casting [+ Erratum]

We investigated the influence of casting temperatures on microstructures and mechanical properties of rapidly solidified Cu50Zr45.5Ti2.5Y2 alloy. With casting temperatures increasing, the content of the crystalline phase decreases. At high casting temperature, i.e., 1723 K, glass forming ability (GFA) of the present alloy enhanced. It is implied that adjusting casting temperatures could be used for designing the microstructures of bulk metallic glass matrix composite (BMGC). Nano-indentation tests indicated that CuZr phases is a little softer and can accommodate more plastic deformation than the amorphous matrix. Compression tests confirmed that this kind of the second phase (CuZr) precipitated under lower casting temperatures helps to initiate multiple shear bands, resulting in great improvement of mechanical properties of the samples. Our work indicate that casting temperatures lead a great influence on GFA, microstructures and mechanical properties of rapidly solidified alloy and controlling casting temperatures is crucial to the application of BMGs

Early Autism Diagnosis based on Path Signature and Siamese Unsupervised Feature Compressor

Autism Spectrum Disorder (ASD) has been emerging as a growing public health threat. Early diagnosis of ASD is crucial for timely, effective intervention and treatment. However, conventional diagnosis methods based on communications and behavioral patterns are unreliable for children younger than 2 years of age. Given evidences of neurodevelopmental abnormalities in ASD infants, we resort to a novel deep learning-based method to extract key features from the inherently scarce, class-imbalanced, and heterogeneous structural MR images for early autism diagnosis. Specifically, we propose a Siamese verification framework to extend the scarce data, and an unsupervised compressor to alleviate data imbalance by extracting key features. We also proposed weight constraints to cope with sample heterogeneity by giving different samples different voting weights during validation, and we used Path Signature to unravel meaningful developmental features from the two-time point data longitudinally. Extensive experiments have shown that our method performed well under practical scenarios, transcending existing machine learning methods

Profound Climatic Effects on Two East Asian Black-Throated Tits (Ave: Aegithalidae), Revealed by Ecological Niche Models and Phylogeographic Analysis

Although a number of studies have assessed the effects of geological and climatic changes on species distributions in East Asian, we still have limited knowledge of how these changes have impacted avian species in south-western and southern China. Here, we aim to study paleo-climatic effects on an East Asian bird, two subspecies of black-throated tit (A. c. talifuensis–concinnus) with the combined analysis of phylogeography and Ecological Niche Models (ENMs). We sequenced three mitochondrial DNA markers from 32 populations (203 individuals) and used phylogenetic inferences to reconstruct the intra-specific relationships among haplotypes. Population genetic analyses were undertaken to gain insight into the demographic history of these populations. We used ENMs to predict the distribution of target species during three periods; last inter-glacial (LIG), last glacial maximum (LGM) and present. We found three highly supported, monophyletic MtDNA lineages and different historical demography among lineages in A. c. talifuensis–concinnus. These lineages formed a narrowly circumscribed intra-specific contact zone. The estimated times of lineage divergences were about 2.4 Ma and 0.32 Ma respectively. ENMs predictions were similar between present and LGM but substantially reduced during LIG. ENMs reconstructions and molecular dating suggest that Pleistocene climate changes had triggered and shaped the genetic structure of black-throated tit. Interestingly, in contrast to profound impacts of other glacial cycles, ENMs and phylogeographic analysis suggest that LGM had limited effect on these two subspecies. ENMs also suggest that Pleistocene climatic oscillations enabled the formation of the contact zone and thus support the refuge theory

Males and females of a polygamous songbird respond differently to mating opportunities

Parents are expected to make fine-tuned decisions by weighing the benefits of providing care to increase offspring survival against that of deserting to pursue future mating opportunities. A higher incentive for the rarer sex in the population indicates an impact of mating opportunities on parental care decisions. However, in a dynamic breeding system, deserting the offspring and searching for a new mate would influence mating opportunities for both sexes. Sex-specific costs and benefits are expected to influence males’ and females’ parenting strategies in different ways. Here, we investigated Chinese penduline tits, Remiz consobrinus, which exhibit flexible parental care strategies: uniparental care by the male or female, biparental care, and biparental desertion occur in the same population. We show that male penduline tits change their parental behavior over the breeding season; they desert clutches produced early in the season but care for the late season clutches. The change in male parenting behavior is consistent with the seasonal decline in mating opportunities. In contrast, parenting by females did not change over the breeding season, nor was it associated with seasonal variation in mate availability. Taken together, mating opportunities have different associations with parental behavior of male and female Chinese penduline tits. We recommend an inclusion of mating opportunities for both sexes simultaneously in order to understand one of the fundamental decisions in parental care evolution—care or desert

Path Signature Neural Network of Cortical Features for Prediction of Infant Cognitive Scores

Studies have shown that there is a tight connection between cognition skills and brain morphology during infancy. Nonetheless, it is still a great challenge to predict individual cognitive scores using their brain morphological features, considering issues like the excessive feature dimension, small sample size and missing data. Due to the limited data, a compact but expressive feature set is desirable as it can reduce the dimension and avoid the potential overfitting issue. Therefore, we pioneer the path signature method to further explore the essential hidden dynamic patterns of longitudinal cortical features. To form a hierarchical and more informative temporal representation, in this work, a novel cortical feature based path signature neural network (CF-PSNet) is proposed with stacked differentiable temporal path signature layers for prediction of individual cognitive scores. By introducing the existence embedding in path generation, we can improve the robustness against the missing data. Benefiting from the global temporal receptive field of CF-PSNet, characteristics consisted in the existing data can be fully leveraged. Further, as there is no need for the whole brain to work for a certain cognitive ability, a top K selection module is used to select the most influential brain regions, decreasing the model size and the risk of overfitting. Extensive experiments are conducted on an in-house longitudinal infant dataset within 9 time points. By comparing with several recent algorithms, we illustrate the state-of-the-art performance of our CF-PSNet (i.e., root mean square error of 0.027 with the time latency of 518 milliseconds for each sample)