Progeny of Germ Line Knockouts of \u3cem\u3eASI2\u3c/em\u3e, a Gene Encoding a Putative Signal Transduction Receptor in \u3cem\u3eTetrahymena Thermophila\u3c/em\u3e, Fail to Make the Transition from Sexual Reproduction to Vegetative Growth

The ciliated protozoan Tetrahymena has two nuclei: a germ line micronucleus and a somatic macronucleus. The transcriptionally active macronucleus has about 50 copies of each chromosome. At sexual reproduction (conjugation), the parental macronucleus is degraded and new macronucleus develops from a mitotic product of the zygotic micronucleus. Development of the macronucleus involves massive genome remodeling, including deletion of about 6000 specific internal eliminated sequences (IES) and multiple rounds of DNA replication. A gene encoding a putative signal transduction receptor, ASI2, (anlagen stage induced 2) is up-regulated during development of the new macronuclei (anlagen). Macronuclear ASI2 is nonessential for vegetative growth. Homozygous ASI2 germ line knockout cells with wild type parental macronuclei proceed through mating but arrest at late macronuclear anlagen development and die before the first post-conjugation fission. IES elimination occurs in these cells. Two rounds of postzygotic DNA replication occur normally in progeny of ASI2 germ line knockouts, but endoreduplication of the macronuclear genome is arrested. The germ line ASI2 null phenotype is rescued in a mating of a knockout strain with wild type cells

A Novel Family of Mobile Genetic Elements Is Limited to the Germline Genome in \u3cem\u3eTetrahymena Thermophila\u3c/em\u3e

In the ciliated protozoan Tetrahymena thermophila, extensive DNA elimination is associated with differentiation of the somatic macronucleus from the germline micronucleus. This study describes the isolation and complete characterization of Tlr elements, a family of approximately 30 micronuclear DNA sequences that are efficiently eliminated from the developing macronucleus. The data indicate that Tlr elements are comprised of an ~22 kb internal region flanked by complex and variable termini. The Tlr internal region is highly conserved among family members and contains 15 open reading frames, some of which resemble genes encoded by transposons and viruses. The Tlr termini appear to be long inverted repeats consisting of (i) a variable region containing multiple direct repeats which differ in number and sequence from element to element and (ii) a conserved terminal 47 bp sequence. Taken together, these results suggest that Tlr elements comprise a novel family of mobile genetic elements that are confined to the Tetrahymena germline genome. Possible mechanisms of developmentally programmed Tlr elimination are discussed

Multifaceted Analysis of Fine-Tuning in Deep Model for Visual Recognition

In recent years, convolutional neural networks (CNNs) have achieved impressive performance for various visual recognition scenarios. CNNs trained on large labeled datasets can not only obtain significant performance on most challenging benchmarks but also provide powerful representations, which can be used to a wide range of other tasks. However, the requirement of massive amounts of data to train deep neural networks is a major drawback of these models, as the data available is usually limited or imbalanced. Fine-tuning (FT) is an effective way to transfer knowledge learned in a source dataset to a target task. In this paper, we introduce and systematically investigate several factors that influence the performance of fine-tuning for visual recognition. These factors include parameters for the retraining procedure (e.g., the initial learning rate of fine-tuning), the distribution of the source and target data (e.g., the number of categories in the source dataset, the distance between the source and target datasets) and so on. We quantitatively and qualitatively analyze these factors, evaluate their influence, and present many empirical observations. The results reveal insights into what fine-tuning changes CNN parameters and provide useful and evidence-backed intuitions about how to implement fine-tuning for computer vision tasks.Comment: Accepted by ACM Transactions on Data Scienc

Three new spider species of the family Thomisidae from Hong Kong (Arachnida: Araneae)

Three new species of spiders from farmland and nearby non-crop fields at Tai Lung Experimental Station (TLES), Hong Kong, were discovered. All three new species occurred in the family Thomisidae, they are Diaea simplex Xu, Han & Li sp. n., Massuria bellula Xu, Han & Li sp. n. and Mastira tegularis Xu, Han & Li sp. n. Descriptions and illustrations of the new species are provided

Notes on twelve species of jumping spiders from Hainan Island, China (Araneae, Salticidae)

Three new genera and eleven new species are reported from Hainan Island, China. The new genera are Logunattus gen. nov., including L. dufui sp. nov. (♂), and the generotype L. libaii sp. nov. (♂♀), Qiongattus yuanyeae gen. et sp. nov. (♂♀), and Spiralembolus gen. nov., including the generotype S. yinggeling sp. nov. (♂♀), and S. yui sp. nov. (♂♀). Another six new species are Carrhotus qingzhaoae sp. nov. (♂♀), Gedea liangweii sp. nov. (♂♀), Heliophanoides moi sp. nov. (♂), Indopadilla songi sp. nov. (♂♀), Myrmarachne mixiaoqii sp. nov. (♂♀), and Nandicius shihaitaoi sp. nov. (♂♀). The unknown female of the endemic species, Pancorius hainanensis Song & Chai, 1991 is also described for the first time. Diagnostic photos of these species are provided

KERM: Knowledge Enhanced Reasoning for Vision-and-Language Navigation

Vision-and-language navigation (VLN) is the task to enable an embodied agent to navigate to a remote location following the natural language instruction in real scenes. Most of the previous approaches utilize the entire features or object-centric features to represent navigable candidates. However, these representations are not efficient enough for an agent to perform actions to arrive the target location. As knowledge provides crucial information which is complementary to visible content, in this paper, we propose a Knowledge Enhanced Reasoning Model (KERM) to leverage knowledge to improve agent navigation ability. Specifically, we first retrieve facts (i.e., knowledge described by language descriptions) for the navigation views based on local regions from the constructed knowledge base. The retrieved facts range from properties of a single object (e.g., color, shape) to relationships between objects (e.g., action, spatial position), providing crucial information for VLN. We further present the KERM which contains the purification, fact-aware interaction, and instruction-guided aggregation modules to integrate visual, history, instruction, and fact features. The proposed KERM can automatically select and gather crucial and relevant cues, obtaining more accurate action prediction. Experimental results on the REVERIE, R2R, and SOON datasets demonstrate the effectiveness of the proposed method.Comment: Accepted by CVPR 2023. The code is available at https://github.com/XiangyangLi20/KER

A Large-scale Film Style Dataset for Learning Multi-frequency Driven Film Enhancement

Film, a classic image style, is culturally significant to the whole photographic industry since it marks the birth of photography. However, film photography is time-consuming and expensive, necessitating a more efficient method for collecting film-style photographs. Numerous datasets that have emerged in the field of image enhancement so far are not film-specific. In order to facilitate film-based image stylization research, we construct FilmSet, a large-scale and high-quality film style dataset. Our dataset includes three different film types and more than 5000 in-the-wild high resolution images. Inspired by the features of FilmSet images, we propose a novel framework called FilmNet based on Laplacian Pyramid for stylizing images across frequency bands and achieving film style outcomes. Experiments reveal that the performance of our model is superior than state-of-the-art techniques. Our dataset and code will be made publicly available

GridMM: Grid Memory Map for Vision-and-Language Navigation

Vision-and-language navigation (VLN) enables the agent to navigate to a remote location following the natural language instruction in 3D environments. To represent the previously visited environment, most approaches for VLN implement memory using recurrent states, topological maps, or top-down semantic maps. In contrast to these approaches, we build the top-down egocentric and dynamically growing Grid Memory Map (i.e., GridMM) to structure the visited environment. From a global perspective, historical observations are projected into a unified grid map in a top-down view, which can better represent the spatial relations of the environment. From a local perspective, we further propose an instruction relevance aggregation method to capture fine-grained visual clues in each grid region. Extensive experiments are conducted on both the REVERIE, R2R, SOON datasets in the discrete environments, and the R2R-CE dataset in the continuous environments, showing the superiority of our proposed method

Ten new species of the spider genus Althepus Thorell, 1898 from Southeast Asia (Araneae, Ochyroceratidae)

Spiders of the genus Althepus Thorell, 1898 are found throughout Southeast Asia, notable for their long walking legs. Ten new species are reported in this paper from China, Indonesia, Laos and Myanmar: A. chengmenensis Li & Li, sp. n. (♂♀), A. cheni Li & Li, sp. n. (♂♀), A. gouci Li & Li, sp. n. (♂♀), A. hongguangi Li & Li, sp. n. (♂♀), A. phousalao Li & Li, sp. n. (♂♀), A. qianhuang Li & Li, sp. n. (♂♀), A. qingyuani Li & Li, sp. n. (♀), A. sepakuensis Li & Li, sp. n. (♂♀), A. xuae Li & Li, sp. n. (♂♀) and A. yizhuang Li & Li, sp. n. (♂♀). These species were found in cave entrances and among tree-buttresses, indicating the spiders have a preference for dark and moist environments. All types are deposited in the Institute of Zoology, Chinese Academy of Sciences in Beijing, China (IZCAS)

Notes on two Stiphropus species from China (Araneae, Thomisidae)

The spider genus Stiphropus Gerstaecker, 1873 currently includes 21 extant species that are distributed in Africa (12) and Asia (9). Four species, S. falciformus Yang, Zhu & Song, 2006, S. myrmecophilus Huang & Lin, 2020, S. ocellatus Thorell, 1887 and S. soureni Sen, 1964, are currently known from China.The mismatched female of S. falciformus is reported as a new species: S. qianlei sp. n. (♂♀). The unknown male of S. soureni Sen, 1964 is described for the first time. Photos and morphological descriptions are provided