Hesitant Triangular Fuzzy Information Aggregation Operators Based on Bonferroni Means and Their Application to Multiple Attribute Decision Making

We investigate the multiple attribute decision-making (MADM) problems with hesitant triangular fuzzy information. Firstly, definition and some operational laws of hesitant triangular fuzzy elements are introduced. Then, we develop some hesitant triangular fuzzy aggregation operators based on Bonferroni means and discuss their basic properties. Some existing operators can be viewed as their special cases. Next, we apply the proposed operators to deal with multiple attribute decision-making problems under hesitant triangular fuzzy environment. Finally, an illustrative example is given to show the developed method and demonstrate its practicality and effectiveness

Complexity of Wake Electroencephalography Correlates With Slow Wave Activity After Sleep Onset

Sleep electroencephalography (EEG) provides an opportunity to study sleep scientifically, whose chaotic, dynamic, complex, and dissipative nature implies that non-linear approaches could uncover some mechanism of sleep. Based on well-established complexity theories, one hypothesis in sleep medicine is that lower complexity of brain waves at pre-sleep state can facilitate sleep initiation and further improve sleep quality. However, this has never been studied with solid data. In this study, EEG collected from healthy subjects was used to investigate the association between pre-sleep EEG complexity and sleep quality. Multiscale entropy analysis (MSE) was applied to pre-sleep EEG signals recorded immediately after light-off (while subjects were awake) for measuring the complexities of brain dynamics by a proposed index, CI1−30. Slow wave activity (SWA) in sleep, which is commonly used as an indicator of sleep depth or sleep intensity, was quantified based on two methods, traditional Fast Fourier transform (FFT) and ensemble empirical mode decomposition (EEMD). The associations between wake EEG complexity, sleep latency, and SWA in sleep were evaluated. Our results demonstrated that lower complexity before sleep onset is associated with decreased sleep latency, indicating a potential facilitating role of reduced pre-sleep complexity in the wake-sleep transition. In addition, the proposed EEMD-based method revealed an association between wake complexity and quantified SWA in the beginning of sleep (90 min after sleep onset). Complexity metric could thus be considered as a potential indicator for sleep interventions, and further studies are encouraged to examine the application of EEG complexity before sleep onset in populations with difficulty in sleep initiation. Further studies may also examine the mechanisms of the causal relationships between pre-sleep brain complexity and SWA, or conduct comparisons between normal and pathological conditions

Age-Related Alterations in Electroencephalography Connectivity and Network Topology During n-Back Working Memory Task

The study of the healthy brain in elders, especially age-associated alterations in cognition, is important to understand the deficits created by Alzheimer's disease (AD), which imposes a tremendous burden on individuals, families, and society. Although, the changes in synaptic connectivity and reorganization of brain networks that accompany aging are gradually becoming understood, little is known about how normal aging affects brain inter-regional synchronization and functional networks when items are held in working memory (WM). According to the classic Sternberg WM paradigm, we recorded multichannel electroencephalography (EEG) from healthy adults (young and senior) in three different conditions, i.e., the resting state, 0-back (control) task, and 2-back task. The phase lag index (PLI) between EEG channels was computed and then weighted and undirected network was constructed based on the PLI matrix. The effects of aging on network topology were examined using a brain connectivity toolbox. The results showed that age-related alteration was more prominent when the 2-back task was engaged, especially in the theta band. For the younger adults, the WM task evoked a significant increase in the clustering coefficient of the beta-band functional connectivity network, which was absent in the older adults. Furthermore, significant correlations were observed between the behavioral performance of WM and EEG metrics in the theta and gamma bands, suggesting the potential use of those measures as biomarkers for the evaluation of cognitive training, for instance. Taken together, our findings shed further light on the underlying mechanism of WM in physiological aging and suggest that different EEG frequencies appear to have distinct functional correlates in cognitive aging. Analysis of inter-regional synchronization and topological characteristics based on graph theory is thus an appropriate way to explore natural age-related changes in the human brain

Elucidating the complex interplay between natural and anthropogenic factors in the deformation of the Muyubao landslide through time-series InSAR analysis

In the Three Gorges Reservoir area, landslide disasters occur frequently, making scientific monitoring and risk prediction crucial for disaster prevention and mitigation. However, most previous studies have been constrained by analysis of singular influencing factors. In this study, we employed multi-temporal InSAR techniques coupled with multivariate geospatial statistical analysis to monitor and analyze the dynamic evolution of the Muyuba landslide in Zigui County, Hubei Province, China from 2016 to 2023. The findings indicate that the Muyuba landslide was predominantly characterized by continuous, gradual subsidence. Key factors inducing deformation included well-developed drainage networks, gentle slopes of 15–30°, and the orientation of rock strata. Deformation rates in residential areas and along roadways exceeded background levels, implicating anthropogenic activities in the heightened landslide risk. A significant correlation was observed between landslide deformation and reservoir water level fluctuations, as opposed to rainfall patterns, highlighting reservoir regulation disturbances as a critical landslide triggering factor

Botnet Detection Based on Degree Distributions of Node Using Data Mining Scheme

Botnet is most widespread and occurs commonly in today's cyber attacks and they become one of the most serious threats on the Internet. Most of the existing Botnet detection approaches concentrate only on particular Botnet command and control (C&C) protocols and structures, and can become ineffective as Botnets change their structure and C&C techniques. In this paper, we proposed a new general detection strategy. This proposed strategy was based on degree distributions of node and anomaly net flows, and combined data mining technology. In this scheme, we first constructed accurate traffic profile based on packet behavioral mode, and then introduced dialog flow to draw traffic profile of node. Finally we set up degree distributions of node and group and applied the degree distributions of node as input of data mining, which were then classified and distinguished to obtain reliable results with acceptable accuracy. The advantages of our proposed detection method is that there is no need for prior knowledge of Botnets such as Botnet signature and the accuracy of the experiment results is as much as 99%. The FP rate and the FN rate can be controlled within 3%, the best is almost 0

Biocompatibility of the micro-patterned NiTi surface produced by femtosecond laser

Biocompatibility of the micro-patterned NiTi surface produced by femtosecond laser (FSL) was studied in this work. The surface characteristics of the laser treated NiTi alloys were investigated by scanning electron microscopy (SEM), atom force microscopy (AFM), X-ray diffractometry (XRD) and X-ray photoelectron spectrum (XPS). The biocompatibility was evaluated by in vitro cell culture test. The results showed that, grooves, ripples, which covered by nanoparticles were formed on the sample surfaces, and the Ni/Ti ratio on the alloy surface increased with increasing laser energy. The crystal structure was not changed by laser treatment. However, the cell culture test proved that the micro-patterns induced by FSL were beneficial to improve the biocompatibility of NiTi alloys: the growth of osteoblasts oriented along the grooves, a large amount of synapses and filopodias were formed due to the ripples, holes and nanoparticles on the alloy surface, and the proliferation rate and alkaline phosphatase (ALP) content of cells were increased after FSL treatment. However, due to the toxicity of Ni ions on cell growth, the NiTi alloy surface should not be treated by laser fluence of more than 3.82 J/cm(2) to obtain the ideal biocompatibility. (C) 2012 Elsevier B. V. All rights reserved