Jasmonates (JAs) and abscisic acid (ABA) are phytohormones known play important roles in plant response and adaptation to various abiotic stresses including salinity, drought, wounding, and cold. JAZ ...(JASMONATE ZIM-domain) proteins have been reported to play negative roles in JA signaling. However, direct evidence is still lacking that JAZ proteins regulate drought resistance. In this study, OsJAZ1 was investigated for its role in drought resistance in rice. Expression of
was strongly responsive to JA treatment, and it was slightly responsive to ABA, salicylic acid, and abiotic stresses including drought, salinity, and cold. The
-overexpression rice plants were more sensitive to drought stress treatment than the wild-type (WT) rice Zhonghua 11 (ZH11) at both the seedling and reproductive stages, while the
T-DNA insertion mutant plants showed increased drought tolerance compared to the WT plants. The
-overexpression plants were hyposensitive to MeJA and ABA, whereas the
mutant plants were hypersensitive to MeJA and ABA. In addition, there were significant differences in shoot and root length between the OsJAZ1 transgenic and WT plants under the MeJA and ABA treatments. A subcellular localization assay indicated that OsJAZ1 was localized in both the nucleus and cytoplasm. Transcriptome profiling analysis by RNA-seq revealed that the expression levels of many genes in the ABA and JA signaling pathways exhibited significant differences between the
-overexpression plants and WT ZH11 under drought stress treatment. Quantitative real-time PCR confirmed the expression profiles of some of the differentially expressed genes, including
, and
. These results together suggest that OsJAZ1 plays a role in regulating the drought resistance of rice partially via the ABA and JA pathways.
This paper considers a continuous-time mean-variance portfolio selection with regime-switching and random horizon. Unlike previous works, the dynamic of assets are described by non-Markovian ...regime-switching models in the sense that all the market parameters are predictable with respect to the filtration generated jointly by Markov chain and Brownian motion. The Markov chain is assumed to be independent of Brownian motion, thus the market is incomplete. The authors formulate this problem as a constrained stochastic linear-quadratic optimal control problem. The authors derive closed-form expressions for both the optimal portfolios and the efficient frontier. All the results are different from those in the problem with fixed time horizon.
Titanium and titanium alloys have been restricted in tribology-related field, because of their disadvantages, such as low surface hardness, high friction coefficient and poor wear resistance. Various ...surface modification techniques have been applied to improve their deficiencies. As a new technology of severe surface plastic deformation, ultrasonic nanocrystal surface modification (UNSM) technique has been widely used to realize the surface treatment of various materials, and also has attracted wide attention in many engineering fields. This review begins with a brief introductionof the basic concept and the modification mechanism of the UNSM technique. The specific applications of the UNSM technique for improving the tribological and fatigue properties of titanium and its alloys were reviewed and summarized.
The accurate detection and extraction of roads using remote sensing technology are crucial to the development of the transportation industry and intelligent perception tasks. Recently, in view of the ...advantages of CNNs in feature extraction, its related road extraction methods have been proposed successively. However, due to the limitation of kernel size, they perform less effectively at capturing long-range information and global context, which are crucial for road targets distributed over long distances and highly structured. To deal with this problem, a novel model named RoadFormer with a Swin Transformer as the backbone is developed in this paper. Firstly, to extract long-range information effectively, a Swin Transformer multi-scale encoder is adopted in our model. Secondly, to enhance the feature representation capability of the model, we design an innovative bottleneck module, in which the spatial and channel separable convolution is employed to obtain fine-grained and globe features, and then a dilated block is connected after the spatial convolution module to capture more integrated road structures. Finally, a lightweight decoder consisting of transposed convolution and skip connection generates the final extraction results. Extensive experimental results confirm the advantages of RoadFormer on the Deepglobe and Massachusetts datasets. The comparative results of visualization and quantification demonstrate that our model outperforms comparable methods.
Peptidyl arginine deiminase, type VI (PADI6) is a member of the subcortical maternal complex (SCMC), which plays vital roles in mammalian embryogenesis. Most mutations in SCMC members have been ...reported to cause human embryonic arrest, and a total of 15 mutations in PADI6 have been shown to be responsible for early embryonic arrest according to previous studies. However, the genetic factors behind this phenotype remain to be understood in further detail. Here, we identified 13 novel mutations and 4 previously reported mutations of PADI6 in 14 patients who were diagnosed with abnormal embryonic development caused by early arrest, embryonic fragmentation, and recurrent implantation failure. Most of the mutations were predicted by in silico analysis to be deleterious or damaging to the function of PADI6. In addition, the total and East Asian population frequencies of the mutations were low or absent in the gnomAD database. Our study expands the mutational spectrum in PADI6 and will provide precise targets for genetic counseling in the future.
How to recover geometric transformations is one of the most challenging issues in image registration. To alleviate the effect of large geometric distortion in multimodal remote sensing image ...registration, a scale and rotate transform prediction net is proposed in this paper. First, to reduce the scale between the reference and sensed images, the image scale regression module is constructed via CNN feature extraction and FFT correlation, and the scale of sensed image can be recovered roughly. Second, the rotation estimate module is developed for predicting the rotation angles between the reference and the scale-recovered images. Finally, to obtain the accurate registration results, LoFTR is employed to match the geometric-recovered images. The proposed registration network was evaluated on GoogleEarth, HRMS, VIS-NIR and UAV datasets with contrast differences and geometric distortions. The experimental results show that the number of correct matches of our model reached 74.6%, and the RMSE of the registration results achieved 1.236, which is superior to the related methods.
Organophosphate esters (OPEs) are widely used as flame retardants and plasticizers. OPEs have been released into various environments (e.g., water, sediments, dust and air, and soil). To investigate ...the occurrence and distribution of OPEs in various environments in China, this review collects and discusses the published scientific studies in this field. Chlorinated OPEs, as flame retardants, are the predominant OPEs found in the environment. The analysis of data revealed large concentration variations among microenvironments, including inflowing river water (range: 0.69–10.62 µgL−1), sediments (range: 0.0197–0.234 µg/g), dust (range: 8.706–34.872 µg/g), and open recycling sites’ soil (range: 0.122–2.1 µg/g). Moreover, OPEs can be detected in the air and biota. We highlight the overall view regarding environmental levels of OPEs in different matrices as a starting point to monitor trends for China. The levels of OPEs in the water, sediment, dust, and air of China are still low. However, dust samples from electronic waste workshop sites were more contaminated. Human activities, pesticides, electronics, furniture, paint, plastics and textiles, and wastewater plants are the dominant sources of OPEs. Human exposure routes to OPEs mainly include dermal contact, dust ingestion, inhalation, and dietary intake. The low level of ecological risk and risk to human health indicated a limited threat from OPEs. Furthermore, current challenges and perspectives for future studies are prospected. A criteria inventory of OPEs reflecting the levels of OPEs contamination association among different microenvironments, emerging OPEs, and potential impact of OPEs on human health, particularly for children are needed in China for better investigation.
Road extraction from high-resolution remote sensing images has long been a focal and challenging research topic in the field of computer vision. Accurate extraction of road networks holds extensive ...practical value in various fields, such as urban planning, traffic monitoring, disaster response and environmental monitoring. With rapid development in the field of computational intelligence, particularly breakthroughs in deep learning technology, road extraction technology has made significant progress and innovation. This paper provides a systematic review of deep learning-based methods for road extraction from remote sensing images, focusing on analyzing the application of computational intelligence technologies in improving the precision and efficiency of road extraction. According to the type of annotated data, deep learning-based methods are categorized into fully supervised learning, semi-supervised learning, and unsupervised learning approaches, each further divided into more specific subcategories. They are comparatively analyzed based on their principles, advantages, and limitations. Additionally, this review summarizes the metrics used to evaluate the performance of road extraction models and the high-resolution remote sensing image datasets applied for road extraction. Finally, we discuss the main challenges and prospects for leveraging computational intelligence techniques to enhance the precision, automation, and intelligence of road network extraction.
Abstract
Graph matching problem, also known as quadratic assignment problem (QAP) in a practical context, aims at finding the best correspondence between two given graphs. If two nodes are connected ...in one graph, it would be ideal if their corresponding images are connected in the other. The optimal solution should maximize the number of matches between the two graphs, while minimizing the weight of mismatches. Graph isomorphism is a particular case where an exact correspondence with no mismatches could be found. The quadratic assignment problem itself is hard to solve due to its high computational complexity. In this paper, the researcher analyzes two optimization approaches in detail: convex relaxation and the Fast Approximate QAP algorithm, both trying to solve the problem with lower computational effort. The performances of these two methods are further compared through numerical experiments. This paper focuses on pairs of equal-sized undirected graphs.
ρ
correlated graphs are constructed to simulate the noise in inexact graph matching problems. After comparing two existing methods, we propose an even faster optimization approach with comparable accuracy. This new approach provides a particular way to approximate an ideal initialization for the traditional Fast Approximate QAP algorithm. The significant reduction in the runtime makes obtaining good correspondence between large graphs feasible.
Purpose
“Zygotic cleavage failure” is an embryonic phenotype that causes female infertility and failure of in vitro fertilization and/or intracytoplasmic sperm injection. We aimed to identify ...pathogenic variants in a female infertility patient from a consanguineous family with the “zygotic cleavage failure” phenotype.
Methods
Whole-exome sequencing was performed in the affected patient; Sanger sequencing was used to confirm the identified variant. The functional effect of the identified variant was further investigated in HeLa cells.
Results
We identified a novel homozygous missense mutation in
BTG4
(c.285G > C, p.W95C) in the affected individual. Co-immunoprecipitation in HeLa cells showed the complete loss of the interaction between the p.W95C BTG4 variant protein and CNOT7.
Conclusion
This study confirms our previous research and expands the mutational spectrum of
BTG4.
Our findings complement the diagnostic genetic basis for “zygotic cleavage failure” patients and suggest that
BTG4
may be a good target for future therapeutic strategies.
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