Population genetics, diversity and forensic characteristics of Tai–Kadai-speaking Bouyei revealed by insertion/deletions markers

Abstract(#br)China, inhabited by over 1.3 billion people and known for its genetic, cultural and linguistic diversity, is considered to be indispensable for understanding the association between language families and genetic diversity. In order to get a better understanding of the genetic diversity and forensic characteristics of Tai–Kadai-speaking populations in Southwest China, we genotyped 30 insertion/deletion (InDel) markers and amelogenin in 205 individuals from Tai–Kadai-speaking Bouyei people using the Qiagen Investigator DIPplex amplification kit. We carried out a comprehensive population genetic relationship investigation among 14,303 individuals from 84 worldwide populations based on allele frequency correlation and 4907 genotypes of 30 InDels from 36 populations distributed in..

Genomic Insights Into the Admixture History of Mongolic- and Tungusic-Speaking Populations From Southwestern East Asia

As a major part of the modern Trans-Eurasian or Altaic language family, most of the Mongolic and Tungusic languages were mainly spoken in northern China, Mongolia, and southern Siberia, but some were also found in southern China. Previous genetic surveys only focused on the dissection of genetic structure of northern Altaic-speaking populations; however, the ancestral origin and genomic diversification of Mongolic and Tungusic–speaking populations from southwestern East Asia remain poorly understood because of the paucity of high-density sampling and genome-wide data. Here, we generated genome-wide data at nearly 700,000 single-nucleotide polymorphisms (SNPs) in 26 Mongolians and 55 Manchus collected from Guizhou province in southwestern China. We applied principal component analysis (PCA), ADMIXTURE, f statistics, qpWave/qpAdm analysis, qpGraph, TreeMix, Fst, and ALDER to infer the fine-scale population genetic structure and admixture history. We found significant genetic differentiation between northern and southern Mongolic and Tungusic speakers, as one specific genetic cline of Manchu and Mongolian was identified in Guizhou province. Further results from ADMIXTURE and f statistics showed that the studied Guizhou Mongolians and Manchus had a strong genetic affinity with southern East Asians, especially for inland southern East Asians. The qpAdm-based estimates of ancestry admixture proportion demonstrated that Guizhou Mongolians and Manchus people could be modeled as the admixtures of one northern ancestry related to northern Tungusic/Mongolic speakers or Yellow River farmers and one southern ancestry associated with Austronesian, Tai-Kadai, and Austroasiatic speakers. The qpGraph-based phylogeny and neighbor-joining tree further confirmed that Guizhou Manchus and Mongolians derived approximately half of the ancestry from their northern ancestors and the other half from southern Indigenous East Asians. The estimated admixture time ranged from 600 to 1,000 years ago, which further confirmed the admixture events were mediated via the Mongolians Empire expansion during the formation of the Yuan dynasty

A Novel Intravital Method to Evaluate Cerebral Vasospasm in Rat Models of Subarachnoid Hemorrhage: A Study with Synchrotron Radiation Angiography

Precise in vivo evaluation of cerebral vasospasm caused by subarachnoid hemorrhage has remained a critical but unsolved issue in experimental small animal models. In this study, we used synchrotron radiation angiography to study the vasospasm of anterior circulation arteries in two subarachnoid hemorrhage models in rats. Synchrotron radiation angiography, laser Doppler flowmetry-cerebral blood flow measurement, [125I]N-isopropyl-p-iodoamphetamine cerebral blood flow measurement and terminal examinations were applied to evaluate the changes of anterior circulation arteries in two subarachnoid hemorrhage models made by blood injection into cisterna magna and prechiasmatic cistern. Using synchrotron radiation angiography technique, we detected cerebral vasospasm in subarachnoid hemorrhage rats compared to the controls (p<0.05). We also identified two interesting findings: 1) both middle cerebral artery and anterior cerebral artery shrunk the most at day 3 after subarachnoid hemorrhage; 2) the diameter of anterior cerebral artery in the prechiasmatic cistern injection group was smaller than that in the cisterna magna injection group (p<0.05), but not for middle cerebral artery. We concluded that synchrotron radiation angiography provided a novel technique, which could directly evaluate cerebral vasospasm in small animal experimental subarachnoid hemorrhage models. The courses of vasospasm in these two injection models are similar; however, the model produced by prechiasmatic cistern injection is more suitable for study of anterior circulation vasospasm

ACSL : adaptive correlation-driven sparsity learning for deep neural network compression

Deep convolutional neural network compression has attracted lots of attention due to the need to deploy accurate models on resource-constrained edge devices. Existing techniques mostly focus on compressing networks for image-level classification, and it is not clear if they generalize well on network architectures for more challenging pixel-level tasks, e.g., dense crowd counting or semantic segmentation. In this paper, we propose an adaptive correlation-driven sparsity learning (ACSL) framework for channel pruning that outperforms state-of-the-art methods on both image-level and pixel-level tasks. In our ACSL framework, we first quantify the data-dependent channel correlation information with a channel affinity matrix. Next, we leverage these inter-dependencies to induce sparsity into the channels with the introduced adaptive penalty strength. After removing the redundant channels, we obtain compact and efficient models, which have significantly less number of parameters while maintaining comparable performance with the original models. We demonstrate the advantages of our proposed approach on three popular vision tasks, i.e., dense crowd counting, semantic segmentation, and image-level classification. The experimental results demonstrate the superiority of our framework. In particular, for crowd counting on the Mall dataset, the proposed ACSL framework is able to reduce up to 94% parameters (VGG16-Decoder) and 84% FLOPs (ResNet101), while maintaining the same performance of (at times outperforming) the original model.National Research Foundation (NRF)This research project is supported by the National Research Foundation Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme with the Technical University of Munich at TUMCREATE. Prof. Siew-Kei Lam is partially supported under the RIE2020 Industry Alignment Fund – Industry Collaboration Projects (IAFICP) Funding Initiative, as well as cash and in-kind contribution from Singapore Telecommunications Limited (Singtel), through Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU)

Fractal Image Compression on a Pseudo Spiral Architecture

Fractal image compression is a relatively recent image compression method which exploits similarities in different parts of the image. The basic idea is to represent an image by fractals and each of which is the fixed point of an Iterated Function System (IFS). Therefore, an input image can be represented by a series of IFS codes rather than pixels. In this way, an impressive compression ratio 10000:1 can be achieved. The application of fractal image compression presented in this paper is based on a novel image structure, Spiral Architecture, which has hexagonal instead of square pixels as the basic element. In the paper evidence would suggest that introducing Spiral Architecture into fractal image compression will improve the compression performance in compression ratio with little suffering in image quality. There are also much research could be done in this area to further improve the results

CAP : Context-aware Pruning for semantic segmentation

Network pruning for deep convolutional neural networks (CNNs) has recently achieved notable research progress on image-level classification. However, most existing pruning methods are not catered to or evaluated on semantic segmentation networks. In this paper, we advocate the importance of contextual information during channel pruning for semantic segmentation networks by presenting a novel Context-aware Pruning framework. Concretely, we formulate the embedded contextual information by leveraging the layer-wise channels interdependency via the Context-aware Guiding Module (CAGM) and introduce the Context-aware Guided Sparsification (CAGS) to adaptively identify the informative channels on the cumbersome model by inducing channel-wise sparsity on the scaling factors in batch normalization (BN) layers. The resulting pruned models require significantly lesser operations for inference while maintaining comparable performance to (at times outperforming) the original models. We evaluated our framework on widely-used benchmarks and showed its effectiveness on both large and lightweight models. On Cityscapes dataset, our framework reduces the number of parameters by 32%, 47%, 54%, and 63%, on PSPNet101, PSPNet50, ICNet, and SegNet, respectively, while preserving the performance.National Research Foundation (NRF)Published versionThis research project is supported in part by the National Research Foundation Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme with the Technical University of Munich at TUMCREATE

VSA-based fractal image compression

Spiral Architecture (SA) is a novel image structure which has hexagons but not squares as the basic elements. Apart from many other advantages in image processing, SA has shown two unbeatable characters that have potential to improve image compression performance, namely, Locality of Pixel Density and Uniform Image Partitioning. Fractal image compression is a relatively recent image compression method which exploits similarities in different parts of the image. The basic idea is to represent an image as fixed points of Iterated Function Systems (IFS). Therefore, an input image can be represented by a series of IFS codes rather than pixels. In this way, an amazing compression ratio 10000:1 can be achieved. The application of fractal image compression presented in this paper is based on Spiral Architecture. Since there is no mature capture and display device for hexagon-based images, the experiments are implemented on a newly proposed mimic scheme, called Virtual Spiral Architecture (VSA). The experimental results in the paper have shown that introducing Spiral Architecture into fractal image compression will improve the compression performance in image quality with little trade-off in compression ratio. A lot of research work exists in this area to further improve the results

Intercellular Communication during Stomatal Development with a Focus on the Role of Symplastic Connection

Stomata are microscopic pores on the plant epidermis that serve as a major passage for the gas and water exchange between a plant and the atmosphere. The formation of stomata requires a series of cell division and cell-fate transitions and some key regulators including transcription factors and peptides. Monocots have different stomatal patterning and a specific subsidiary cell formation process compared with dicots. Cell-to-cell symplastic trafficking mediated by plasmodesmata (PD) allows molecules including proteins, RNAs and hormones to function in neighboring cells by moving through the channels. During stomatal developmental process, the intercellular communication between stomata complex and adjacent epidermal cells are finely controlled at different stages. Thus, the stomata cells are isolated or connected with others to facilitate their formation or movement. In the review, we summarize the main regulation mechanism underlying stomata development in both dicots and monocots and especially the specific regulation of subsidiary cell formation in monocots. We aim to highlight the important role of symplastic connection modulation during stomata development, including the status of PD presence at different cell–cell interfaces and the function of relevant mobile factors in both dicots and monocots