Abstract: In this paper, composition of set-valued decision tables are discussed based on the quasi-order relation on set-valued decision tables. Based on the theory of the three-way decisions, decision method of the set-valued decision tables are discussed, the three-way decisions of the object-composed set-valued decision tables and the three-way decisions of the attribute-composed set-valued decision tables are also discussed. Furthermore, the three-way decisions of composed set-valued decision tables are discussed.
Abstract: Similarity measure is an important uncertainty measurement in intuitionistic fuzzy set (IFS) theory. In this study, a novel similarity measure is presented by the combination of the information carried by hesitancy degree and the endpoint distance of membership and nonmembership, respectively. Moreover, a numerical example is used to verify the reasonable of the proposed similarity measure. After that, the similarity measure is applied to construct the IF decision-theoretic rough set (IF-DTRS) model and multigranulation IF decision-theoretic rough set (MG-IF-DTRS) model. Some properties of IF-DTRS and MG-IF-DTRS are also investigated. Thirdly, based on granular significance, a novel approach of optimal granulation…selection is formulated. Finally, a heuristic algorithm is designed and the effectiveness of this algorithm is demonstrated by an illustrative example.
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Abstract: Change detection in synthetic aperture radar (SAR) images is an important part of remote sensing (RS) image analysis. Contemporary researchers have concentrated on the spatial and deep-layer semantic information while giving little attention to the extraction of multidimensional and shallow-layer feature representations. Furthermore, change detection relies on patch-wise training and pixel-to-pixel prediction while the accuracy of change detection is sensitive to the introduction of edge noise and the availability of original position information. To address these challenges, we propose a new neural network structure that enables spatial-frequency-temporal feature extraction through end-to-end training for change detection between SAR images from two…different points in time. Our method uses image patches fed into three parallel network structures: a densely connected convolutional neural network (CNN), a frequency domain processing network based on a discrete cosine transform (DCT), and a recurrent neural network (RNN). Multi-dimensional feature representations alleviate speckle noise and provide comprehensive consideration of semantic information. We also propose an ensemble multi-region-channel module (MRCM) to emphasize the central region of each feature map, with the most critical information in each channel employed for binary classification. We validate our proposed method on four benchmark SAR datasets. Experimental results demonstrate the competitive performance of our method.
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Abstract: Rough set theory is a powerful tool for handling uncertainty and vagueness in various fields. The hesitant fuzzy rough set, as a generalization of rough sets, can solve more complex problems. However, existing hesitant fuzzy rough sets do not satisfy the inclusive property. To address this issue, a novel hesitant fuzzy rough set model based on dual score functions is proposed. Four generalized hesitant fuzzy rough sets and their discernibility matrices are also presented. Additionally, the lower approximation distribution reductions can be obtained by the discernibility matrix. Meanwhile, hypergraphs provide an accurate description of relationships between multiple objects and offer…a concise operational approach. Then it is discovered that finding the lower approximation distribution reductions of a hesitant fuzzy decision system is equivalent to finding the minimal transversals of its hypergraph. Moreover, an improved algorithm for hesitant fuzzy decision systems based on hypergraphs is presented to accelerate the reduction process. Finally, the proposed algorithm is applied to the hybrid data of Hepatitis C Virus from UCI to demonstrate its feasibility.
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Abstract: BACKGROUND: TGFβ 1 is very important in the synthesis and degradation of extracellular matrix (ECM), and also in the mediation of human pulmonary fibroblasts proliferation, and miR-29 plays an important role in this process. OBJECTIVE: In the present study, the effects of TGFβ 1 on the expression of miR-29 and whether miR-29 is involved in pro-survival signaling pathways mediated by TGFβ 1 were examined in human pulmonary fibroblasts. METHODS AND RESULTS: Treatment of the human IMR-90 cells with TGFβ 1 caused a decrease in the expression of miR-29a/b/c as determined by real-time PCR analysis. TGFβ 1 stimulation increased cell proliferation,…colony formation and up-regulated expression of COL1A1; transfecting with miR-29a/b/c mimics reverse TGFβ 1-induced phenotype changes in IMR-90. Western blot analyses showed that TGFβ 1 treatment unchanged total protein expression levels of β -catenin, but phosphorylation of β -catenin and the expression levels of wnt3a and COL1A1 were increased; and miR-19a/b/c mimics interfering blocked DKK1, wnt3a, and phosphorylation of β -catenin and decreased expression of COL1A1 after TGFβ 1 treatment. Our results showed that TGFβ 1 activated the wnt/β -catenin pathway, and this activation was essential for the expression of miR-29 in IMR-90. CONCLUSIONS: The results indicate a novel biological function of the wnt/β -catenin pathway in IMR-90. Elevated expression of miR-29 may play an important role in the pathogenesis of diseases related to fibrogenic reactions in human IMR-90.
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Abstract: The concentrations of reduced-glutathione (GSH) in liver and ovary of Boleophthalmus pectinirostris are quantified. The concentrations of GSH in the ovary are much higher than that of GSH in the liver(nearly 3 times of the liver). The study also investigates the changes of GSH contents in the two organs while the fishes were exposed to benzo(a)pyrene(BaP) at concentrations of 0, 0.05, 0.2 and 0.5mg/L respectively for up to a week. The concentrations of GSH in the liver of BaP-exposed fish increased significantly with dose, whereas the oncentrations of GSH in the ovary decreased significantly compared to controls. The results suggested…that both the liver and the ovary are the primary organ in BaP metabolism, and that the changes of GSH levels may represent an adaptive response or toxic effect to BaP exposure.
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Abstract: YTNR (Yunnan Tongbiguan Nature Reserve) is located in the westernmost part of China’s tropical regions and is the only area in China with the tropical biota of the Irrawaddy River system. The reserve has abundant tropical flora and fauna resources. In order to realize the real-time detection of wild animals in this area, this paper proposes an improved YOLO (You only look once) network. The original YOLO model can achieve higher detection accuracy, but due to the complex model structure, it cannot achieve a faster detection speed on the CPU detection platform. Therefore, the lightweight network MobileNet is introduced to…replace the backbone feature extraction network in YOLO, which realizes real-time detection on the CPU platform. In response to the difficulty in collecting wild animal image data, the research team deployed 50 high-definition cameras in the study area and conducted continuous observations for more than 1,000 hours. In the end, this research uses 1410 images of wildlife collected in the field and 1577 wildlife images from the internet to construct a research data set combined with the manual annotation of domain experts. At the same time, transfer learning is introduced to solve the problem of insufficient training data and the network is difficult to fit. The experimental results show that our model trained on a training set containing 2419 animal images has a mean average precision of 93.6% and an FPS (Frame Per Second) of 3.8 under the CPU. Compared with YOLO, the mean average precision is increased by 7.7%, and the FPS value is increased by 3.
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Keywords: Wildlife detection, YOLO, transfer learning, MobileNet, PANet
Abstract: Knowledge acquisition in intuitionistic fuzzy information systems is of importance because those fuzzy information systems are often encountered in many real-life problems. Formal concept analysis is a simple and effective tool for knowledge acquisition. However, there is still little work on introducing knowledge acquisition methods based on formal concept analysis into intuitionistic fuzzy information systems. This paper mainly extends the formal concept theory into intuitionistic fuzzy information systems. Firstly, two pairs of adjoint mappings are defined in intuitionistic fuzzy formal contexts. It is verified that both pairs of adjoint mappings form Galois connections. Secondly, two types of intuitionistic fuzzy concept…lattices are constructed. After that, we also present the main theorems and propositions of the intuitionistic fuzzy concept lattices. Thirdly, we deeply discuss the attribute characteristics for type-1 generalized one-sided intuitionistic fuzzy concept lattice. Furthermore, a discernibility matrix-based algorithm is proposed for attribute reduction and the effectiveness of this algorithm is demonstrated by a practical example. The construction of intuitionistic fuzzy conceptS is meaningful for the complex and fuzzy information in real life.
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Abstract: Background: Cognitive impairment is a clinical feature of multiple system atrophy (MSA). However, the prevalence and factors influencing the prevalence of cognitive impairment and dementia in MSA patients remain unclear. Objective: We aim to provide an estimate of the prevalence of cognitive impairment and dementia in patients with MSA and to evaluate the possible effect of demographic, clinical and methodological factors on the prevalence. Methods: We systematically searched the PubMed, Embase, and Web of science databases to identify studies that report the prevalence of cognitive impairment or dementia in MSA published up to February 2022. We computed the estimates of…the pooled prevalence using random-effects models. Heterogeneity was investigated by subgroup analyses and meta-regression. Differences between MSA patients with and without cognitive impairment in demographic and clinical features were explored. Results: A total of 23 studies comprising 2064 MSA patients were included in meta-analysis. The pooled prevalence of cognitive impairment in MSA patients was 37% (95% CI: 29% –45%), the prevalence of dementia was 11% (95% CI: 7% –15%). The subgroup analyses showed the prevalence of dementia in pathologically-confirmed MSA was 7% (95% CI: 0% –12%), in clinically diagnosed MSA was 14% (95% CI: 10% –18%). Cognitive impairment in MSA patients was associated with older age, lower education, longer disease duration and more severe motor symptoms. Conclusion: Cognitive impairment is a common non-motor symptom in MSA. Dementia can develop in a few patients with MSA as well, but usually in the late stage.
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Keywords: Cognitive dysfunction, dementia, multiple system atrophy, prevalence
Abstract: With the continuous extension and deepening of college education reform, the research on the future employment of college students and the evaluation of employment quality has become a major focus topic. The traditional evaluation system for the employment quality of college graduates is relatively outdated and unitary, lacking a vision of the future development status of college graduates, as well as an effective understanding and mastery of the overall feedback and evaluation of the entire employment market for college graduates. Moreover, most colleges and universities mainly focus on the level of competence that college graduates should achieve five years after…graduation from college in terms of talent cultivation goals, The lack of specific evaluation work for long-term employment tracking of graduates has resulted in universities being unable to grasp and understand the degree of fit and matching between the comprehensive abilities of university graduates and the future employment market, and thus unable to provide effective feedback and summary of talent cultivation and innovation strategies. Therefore, it is imperative to comprehensively innovate the employment quality evaluation system and methods for college graduates. The employment quality evaluation of college graduates is a classical multiple attribute group decision making (MAGDM) problems. Recently, the TODIM and VIKOR method has been used to cope with MAGDM issues. The probabilistic linguistic term sets (PLTSs) are used as a tool for characterizing uncertain information during the employment quality evaluation of college graduates. In this manuscript, the probabilistic linguistic TODIM-VIKOR (PL-TODIM-VIKOR) method is built to solve the MAGDM under PLTSs. In the end, a numerical case study for employment quality evaluation of college graduates is given to validate the proposed method.
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Keywords: Multiple attribute group decision making (MAGDM), probabilistic linguistic term sets (PLTSs), information entropy, TODIM, VIKOR, employment quality evaluation