バフンウニにおけるCRISPR-Cas9を用いた標的遺伝子への変異導入

広島大学(Hiroshima University)博士(理学)Doctor of Sciencedoctora

PL-UNeXt: Per-stage Edge Detail and Line Feature Guided Segmentation for Power Line Detection

Power line detection is a critical inspection task for electricity companies and is also useful in avoiding drone obstacles. Accurately separating power lines from the surrounding area in the aerial image is still challenging due to the intricate background and low pixel ratio. In order to properly capture the guidance of the spatial edge detail prior and line features, we offer PL-UNeXt, a power line segmentation model with a booster training strategy. We design edge detail heads computing the loss in edge space to guide the lower-level detail learning and line feature heads generating auxiliary segmentation masks to supervise higher-level line feature learning. Benefited from this design, our model can reach 70.6 F1 score (+1.9%) on TTPLA and 68.41 mIoU (+5.2%) on VITL (without utilizing IR images), while preserving a real-time performance due to few inference parameters.Comment: Accepted to IEEE ICIP 202

Meteorological drought analysis in the Lower Mekong Basin using satellite-based long-term CHIRPS product

Lower Mekong Basin (LMB) experiences a recurrent drought phenomenon. However, few studies have focused on drought monitoring in this region due to lack of ground observations. The newly released Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) with a long-term record and high resolution has a great potential for drought monitoring. Based on the assessment of CHIRPS for capturing precipitation and monitoring drought, this study aims to evaluate the drought condition in LMB by using satellite-based CHIRPS from January 1981 to July 2016. The Standardized Precipitation Index (SPI) at various time scales (1-12-month) is computed to identify and describe drought events. Results suggest that CHIRPS can properly capture the drought characteristics at various time scales with the best performance at three-month time scale. Based on high-resolution long-term CHIRPS, it is found that LMB experienced four severe droughts during the last three decades with the longest one in 1991-1994 for 38 months and the driest one in 2015-2016 with drought affected area up to 75.6%. Droughts tend to occur over the north and south part of LMB with higher frequency, and Mekong Delta seems to experience more long-term and extreme drought events. Severe droughts have significant impacts on vegetation condition

Modeling the conversion of glucose to hydroxymethylfurfural

Cellulosic biomass materials have three principal components: cellulose, hemicellulose, and lignin. Under mild acid conditions and high temperature, the first two components yield a variety of sugars: hexoses and pentoses, which are subject to decomposition on continued exposure to hot dilute acid. In the process hexoses yield hydroxymethylfurfural (HMF) which, on continued heating, yields levulinic acid and formic acid and some uncharacterized solid products. Biomass hydrolysis research has now progressed to the point where process analysis and optimization requires a generalized kinetic correlation for hexose degradation. The kinetics for the reaction of glucose to HMF has been studied previously. However, not all of the rate constants for the dehydration of glucose and HMF had been modeled to fit the experimental data. This research had two parts. The first was to model the kinetics for the formation of HMF from glucose in the aqueous phase using the three-constant model suggested by S. W. McKibbins et al. (1962). The other was to study the aqueous-phase reaction carried in the presence of an organic solvent, o-nitrotoluene (ONT), for the purpose of extracting HMF as it is produced; thereby minimizing subsequent degradation of HMF to levulinic acid, formic acid, and solid materials. The HMF distribution coefficient for o-nitrotoluene was measured at different temperatures and modeled as the integrated Van't Hoff equation. Predicted glucose, HMF, and organic acids concentration profiles were compared to the experimentally determined values. The predicted concentration profiles are in good agreement with the experimental data, indicating that the proposal three-constant model is consistent with the true reaction system. In the two-phase system case study, the process was diffusion limiting due to lack of agitation of the mixture

Partition of a Binary Matrix into k

A biclustering problem consists of objects and an attribute vector for each object. Biclustering aims at finding a bicluster—a subset of objects that exhibit similar behavior across a subset of attributes, or vice versa. Biclustering in matrices with binary entries (“0”/“1”) can be simplified into the problem of finding submatrices with entries of “1.” In this paper, we consider a variant of the biclustering problem: the k-submatrix partition of binary matrices problem. The input of the problem contains an n×m matrix with entries (“0”/“1”) and a constant positive integer k. The k-submatrix partition of binary matrices problem is to find exactly k submatrices with entries of “1” such that these k submatrices are pairwise row and column exclusive and each row (column) in the matrix occurs in exactly one of the k submatrices. We discuss the complexity of the k-submatrix partition of binary matrices problem and show that the problem is NP-hard for any k≥3 by reduction from a biclustering problem in bipartite graphs

Underwater target detection based on improved YOLOv7

Underwater target detection is a crucial aspect of ocean exploration. However, conventional underwater target detection methods face several challenges such as inaccurate feature extraction, slow detection speed and lack of robustness in complex underwater environments. To address these limitations, this study proposes an improved YOLOv7 network (YOLOv7-AC) for underwater target detection. The proposed network utilizes an ACmixBlock module to replace the 3x3 convolution block in the E-ELAN structure, and incorporates jump connections and 1x1 convolution architecture between ACmixBlock modules to improve feature extraction and network reasoning speed. Additionally, a ResNet-ACmix module is designed to avoid feature information loss and reduce computation, while a Global Attention Mechanism (GAM) is inserted in the backbone and head parts of the model to improve feature extraction. Furthermore, the K-means++ algorithm is used instead of K-means to obtain anchor boxes and enhance model accuracy. Experimental results show that the improved YOLOv7 network outperforms the original YOLOv7 model and other popular underwater target detection methods. The proposed network achieved a mean average precision (mAP) value of 89.6% and 97.4% on the URPC dataset and Brackish dataset, respectively, and demonstrated a higher frame per second (FPS) compared to the original YOLOv7 model. The source code for this study is publicly available at https://github.com/NZWANG/YOLOV7-AC. In conclusion, the improved YOLOv7 network proposed in this study represents a promising solution for underwater target detection and holds great potential for practical applications in various underwater tasks

Ontogenetic development of gonads and external sexual characters of the protandric simultaneous hermaphrodite peppermint shrimp, Lysmata vittata (Caridea: Hippolytidae)

© 2019 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The peppermint shrimp Lysmata vittata (Caridea: Hippolytidae) is a marine caridean shrimp popular in marine aquarium trade. The species is known to display the sexual system of protandric simultaneous hermaphrodite. In this study, based on captive bred specimens, the complete ontogenetic gonad development of L. vittata was studied both morphologically and histologically, from newly settled juveniles until they reached euhermaphrodite phase. It was found that in all specimens examined (carapace length: 1.8-8.5 mm), including the newly settled juveniles, possessed ovotestes, which comprised of an anterior ovarian and a posterior testicular part. Based on both morphological (e.g., size, color and shape) and histological features (e.g., oogenesis and spermatogenesis), four gonadal development stages were defined and described for L. vittata. From Stage I to III, the testicular part of the gonad became gradually mature but the ovarian part was still immature, which is defined as the male phase. At the male phase, cincinulli (5-8 hooks) presented at the tips of the appendix interna on the first pair of pleopods while appendices masculinae (AM), in a form of a stick structure with spines, presented at the inner edge of the appendix interna (AI) on the second pair of pleopods. At Stage IV, both the testicular part and the ovarian part were mature and hence is defined as euhermaphrodite phase. At the euhermaphrodite phase, most individuals lacked cincinulli and appendices masculinae on the first and second pair of pleopods respectively. This is the first time that complete ontogenetic gonadal and external sexual character development have been described and staged for a species from the genus Lysmata from newly settled juveniles to euhermaphrodite phase

Implications of viral infections and oncogenesis in uterine cervical carcinoma etiology and pathogenesis

BackgroundUterine Cervical Carcinoma (UCC) is the most prevalent gynecological malignancy globally, with a rising incidence in recent years. Accumulating evidence indicates that specific viral infections, including human papillomavirus (HPV), Epstein-Barr virus (EBV), Hepatitis B and C viruses (HBV and HCV), and human herpesvirus (HHV), may contribute to UCC development and progression. Understanding the complex interplay between viral infections and UCC risk is crucial for developing novel preventative and therapeutic interventions.MethodsThis comprehensive review investigates the association between viral infections and UCC risk by examining the roles of various viral pathogens in UCC etiology and pathogenesis, and possible molecular mechanisms. Additionally, we evaluate current diagnostic methods and potential therapeutic strategies targeting viral infections for UCC prevention or treatment.ResultsThe prevention of UCC has been significantly advanced by the emergence of self-sampling for HPV testing as a crucial tool, allowing for early detection and intervention. However, an essential challenge in UCC prevention lies in understanding how HPV and other viral coinfections, including EBV, HBV, HCV, HHV, HIV, or their concurrent presence, may potentially contribute to UCC development. The molecular mechanisms implicated in the association between viral infections and cervical cancer development include: (1) interference of viral oncogenes with cellular regulatory proteins, resulting in uncontrolled cell proliferation and malignant transformation; (2) inactivation of tumor suppressor genes by viral proteins; (3) evasion of host immune responses by viruses; (4) induction of a persistent inflammatory response, contributing to a tumor-promoting microenvironment; (5) epigenetic modifications that lead to aberrant gene expression; (6) stimulation of angiogenesis by viruses; and (7) activation of telomerase by viral proteins, leading to cellular immortalization. Additionally, viral coinfections can also enhance oncogenic potential through synergistic interactions between viral oncoproteins, employ immune evasion strategies, contribute to chronic inflammation, modulate host cellular signaling pathways, and induce epigenetic alterations, ultimately leading to cervical carcinogenesis.ConclusionRecognizing the implications of viral oncogenes in UCC etiology and pathogenesis is vital for addressing the escalating burden of UCC. Developing innovative preventative and therapeutic interventions requires a thorough understanding of the intricate relationship between viral infections and UCC risk