On Fatigue Detection for Air Traffic Controllers Based on Fuzzy Fusion of Multiple Features

Fatigue detection for air traffic controllers is an important yet challenging problem in aviation safety research. Most of the existing methods for this problem are based on facial features. In this paper, we propose an ensemble learning model that combines both facial features and voice features and design a fatigue detection method through multifeature fusion, referred to as Facial and Voice Stacking (FV-Stacking). Specifically, for facial features, we first use OpenCV and Dlib libraries to extract mouth and eye areas and then employ a combination of M-Convolutional Neural Network (M-CNN) and E-Convolutional Neural Network (E-CNN) to determine the state of mouth and eye closure based on five features, i.e., blinking times, average blinking time, average blinking interval, Percentage of Eyelid Closure over the Pupil over Time (PERCLOS), and Frequency of Open Mouth (FOM). For voice features, we extract the Mel-Frequency Cepstral Coefficients (MFCC) features of speech. Such facial features and voice features are fused through a carefully designed stacking model for fatigue detection. Real-life experiments are conducted on 14 air traffic controllers in Southwest Air Traffic Management Bureau of Civil Aviation of China. The results show that the proposed FV-Stacking method achieves a detection accuracy of 97%, while the best accuracy achieved by a single model is 92% and the best accuracy achieved by the state-of-the-art detection methods is 88%

In-situ synthesis of single-atom Ir by utilizing metal-organic frameworks: An acid-resistant catalyst for hydrogenation of levulinic acid to γ-valerolactone

The hydrogenation of levulinic acid (LA) to gamma-valerolactone (GVL) is a key reaction for the production of renewable chemicals and fuels, wherein acid-resistant and robust catalysts are highly desired for practical usage. Herein, an ultra-stable 0.6 wt% Ir@ZrO2@C single-atom catalyst was prepared via an in-situ synthesis approach during the assembly of UiO-66, followed by confined pyrolysis. The Ir@ZrO2@C offered not only a quantitative LA conversion and an excellent GVL selectivity (>99%), but also an unprecedented stability during recycling runs under harsh conditions (at T= 453 K, P-H2 = 40 bar in pH = 3 or pH =1 aqueous solution). By thorough spectroscopy characterizations, a well-defined structure of atomically dispersed Ir delta+ atoms onto nano-tetragonal ZrO2 confined in the amorphous carbon was identified for the Ir@ZrO2@C. The strong metal-support interaction and the confinement of the amorphous carbon account for the ultra-stability of the Ir@ZrO2@C. (C) 2019 Elsevier Inc. All rights reserved

The Neuroprotective Effects of Brazilian Green Propolis on Neurodegenerative Damage in Human Neuronal SH-SY5Y Cells

Oxidative stress and synapse dysfunction are the major neurodegenerative damage correlated to cognitive impairment in Alzheimer’s disease (AD). We have found that Brazilian green propolis (propolis) improves the cognitive functions of mild cognitive impairment patients living at high altitude; however, mechanism underlying the effects of propolis is unknown. In the present study, we investigated the effects of propolis on oxidative stress, expression of brain-derived neurotrophic factor (BDNF), and activity-regulated cytoskeleton-associated protein (Arc), the critical factors of synapse efficacy, using human neuroblastoma SH-SY5Y cells. Pretreatment with propolis significantly ameliorated the hydrogen peroxide- (H2O2-) induced cytotoxicity in SH-SY5Y cells. Furthermore, propolis significantly reduced the H2O2-generated reactive oxygen species (ROS) derived from mitochondria and 8-oxo-2′-deoxyguanosine (8-oxo-dG, the DNA oxidative damage marker) but significantly reversed the fibrillar β-amyloid and IL-1β-impaired BDNF-induced Arc expression in SH-SY5Y cells. Furthermore, propolis significantly upregulated BDNF mRNA expression in time- and dose-dependent manners. In addition, propolis induced Arc mRNA and protein expression via phosphoinositide-3 kinase (PI3K). These observations strongly suggest that propolis protects from the neurodegenerative damage in neurons through the properties of various antioxidants. The present study provides a potential molecular mechanism of Brazilian green propolis in prevention of cognitive impairment in AD as well as aging

Regulation of Neuronal Cell Death by c-Abl-Hippo/MST2 Signaling Pathway

BACKGROUND: Mammalian Ste20-like kinases (MSTs) are the mammalian homologue of Drosophila hippo and play critical roles in regulation of cell death, organ size control, proliferation and tumorigenesis. MSTs exert pro-apoptotic function through cleavage, autophosphorylation and in turn phosphorylation of downstream targets, such as Histone H2B and FOXO (Forkhead box O). Previously we reported that protein kinase c-Abl mediates oxidative stress-induced neuronal cell death through phosphorylating MST1 at Y433, which is not conserved among mammalian MST2, Drosophila Hippo and C.elegans cst-1/2. METHODOLOGY/PRINCIPAL FINDINGS: Using immunoblotting, in vitro kinase and cell death assay, we demonstrate that c-Abl kinase phosphorylates MST2 at an evolutionarily conserved site, Y81, within the kinase domain. We further show that the phosphorylation of MST2 by c-Abl leads to the disruption of the interaction with Raf-1 proteins and the enhancement of homodimerization of MST2 proteins. It thereby enhances the MST2 activation and induces neuronal cell death. CONCLUSIONS/SIGNIFICANCE: The identification of the c-Abl tyrosine kinase as a novel upstream activator of MST2 suggests that the conserved c-Abl-MST signaling cascade plays an important role in oxidative stress-induced neuronal cell death

Classification of autism spectrum disorder using electroencephalography in Chinese children: a cross-sectional retrospective study

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by diverse clinical features. EEG biomarkers such as spectral power and functional connectivity have emerged as potential tools for enhancing early diagnosis and understanding of the neural processes underlying ASD. However, existing studies yield conflicting results, necessitating a comprehensive, data-driven analysis. We conducted a retrospective cross-sectional study involving 246 children with ASD and 42 control children. EEG was collected, and diverse EEG features, including spectral power and spectral coherence were extracted. Statistical inference methods, coupled with machine learning models, were employed to identify differences in EEG features between ASD and control groups and develop classification models for diagnostic purposes. Our analysis revealed statistically significant differences in spectral coherence, particularly in gamma and beta frequency bands, indicating elevated long range functional connectivity between frontal and parietal regions in the ASD group. Machine learning models achieved modest classification performance of ROC-AUC at 0.65. While machine learning approaches offer some discriminative power classifying individuals with ASD from controls, they also indicate the need for further refinement

Fractal Dimension of Basalt Fiber Reinforced Concrete (BFRC) and Its Correlations to Pore Structure, Strength and Shrinkage

In this study, we focused on exploring the correlations between the pore surface fractal dimensions and the pore structure parameters, strength and shrinkage properties of basalt fiber-reinforced concrete (BFRC). The pore structure of BFRCs with various fiber contents and fiber lengths was investigated using mercury intrusion porosimetry (MIP) measurements. Through Zhang’s model, the fractal characteristics of BFRCs in the whole pore size range and in different pore size ranges were calculated from the MIP test data. The results showed that the addition of BF increased the total porosity, total pore volume and pore area but decreased the average pore diameter, indicating that BFs refined the pore structure of the concrete. BFRC presented obvious fractal characteristics in the entire pore-size range and individual pore-size ranges; generally, the fractal dimension increased with increasing fiber content. Moreover, correlation analysis suggested that the fractal dimension of BFRC in the whole pore-size range (FD) was closely related to the fractal dimension in the macropore region (Dm) and average pore diameter (APD). The influence of pore structure factors on mechanical strength and shrinkage was studied by grey correlation theory, and the results showed that Dm showed positive correlations with strength and fracture energy, with increasing Dm tending to strengthen and toughen the concrete. An increase in fiber content and length was detrimental to reducing the drying shrinkage strain. In the transition pore region, the fractal dimension (Dt) at diameters ranging from 20 to 50 nm and shrinkage strain exhibited a highly linear relation. These results merit careful consideration in macro-property evaluation by using the pore surface fractal dimension in a specific region instead of the whole region. Finally, grey target theory was applied to evaluate the rank of the mechanical strength and shrinkage of concrete, and the results showed that the overall properties of concrete with a BF length of 18 mm and a BF content of 0.06% ranked the best

Nutrients, Microglia Aging, and Brain Aging

As the life expectancy continues to increase, the cognitive decline associated with Alzheimer’s disease (AD) becomes a big major issue in the world. After cellular activation upon systemic inflammation, microglia, the resident immune cells in the brain, start to release proinflammatory mediators to trigger neuroinflammation. We have found that chronic systemic inflammatory challenges induce differential age-dependent microglial responses, which are in line with the impairment of learning and memory, even in middle-aged animals. We thus raise the concept of “microglia aging.” This concept is based on the fact that microglia are the key contributor to the acceleration of cognitive decline, which is the major sign of brain aging. On the other hand, inflammation induces oxidative stress and DNA damage, which leads to the overproduction of reactive oxygen species by the numerous types of cells, including macrophages and microglia. Oxidative stress-damaged cells successively produce larger amounts of inflammatory mediators to promote microglia aging. Nutrients are necessary for maintaining general health, including the health of brain. The intake of antioxidant nutrients reduces both systemic inflammation and neuroinflammation and thus reduces cognitive decline during aging. We herein review our microglia aging concept and discuss systemic inflammation and microglia aging. We propose that a nutritional approach to controlling microglia aging will open a new window for healthy brain aging

Intelligent Bandwidth Reservation for Big Data Transfer in High-Performance Networks

Many scientific applications are generating extremely large amounts of data at a high speed, which must be transferred to remote collaborating sites for storage and analysis. Such high- demanding data transfer has been increasingly supported by bandwidth reservation services in high-performance networks (HPNs). For each bandwidth reservation request (BRR), most existing scheduling algorithms return either the best-case reservation option or a reject message if the BRR cannot be satisfied. To perform intelligent scheduling, we provide two alternative reservation options in the latter case: schedule the BRR within the closest time intervals before and after the user-specified time interval. We consider two different types of BRRs and for each, we design a flexible bandwidth scheduling algorithm with a rigorous optimality proof to compute both the best and alternative reservation options. For comparison, we also design two heuristics adapted from existing bandwidth scheduling algorithms. Extensive simulations show that the proposed algorithms have superior performance to those in comparison

Practice of Developing Low-carbon Leisure Agriculture in Agricultural Sci-tech Experiment and Demonstration Park: A Case Study of Xinglong Tropical Botanical Park

The Agricultural Science and Technology Experiment and Demonstration Park, as a unique tourist scenic spot, is a new model for the development of low-carbon leisure agriculture. In this paper, with Xinglong Tropical Botanical Park as a study case, the practice of developing a model of low-carbon agricultural science and technology tourism in the park is explored. Main measures for developing low-carbon leisure agriculture in Agricultural Science and Technology Experiment and Demonstration Park are summarized, including development of low carbon attractors, construction of low carbon facilities, strengthening low-carbon management, building low-carbon environment and so on, according to analysis on the models for development of low-carbon agricultural science tourism in this park