114 research outputs found
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Recent advances for flame retardant rubber composites: Mini-review
Flame retardant rubber composites have attracted a great attention during the past decades owing to their irreplaceable roles in complex industrial systems. Large amounts of efforts have been made to improve the flame retardant ability, developing high efficiency flame retardant systems which can reduce the release of heat, smoke and toxic gases while not deteriorate overall properties is becoming more and more important. This review briefly outlines the recent developments of flame retardant natural rubbers, silicon rubbers, some kinds of artificial rubbers and polyurethane elastomer composites, focuses on the design, development, mechanism and applications of advanced high-performance flame-retardant methods. Finally, outlooks the future tendency including more environmental-friendly strategies, higher flame-retardant efficiency and development of multifunctional flame-retardant rubber composites are proposed
The nestin-expressing and non-expressing neurons in rat basal forebrain display different electrophysiological properties and project to hippocampus
<p>Abstract</p> <p>Background</p> <p>Nestin-immunoreactive (nestin-ir) neurons have been identified in the medial septal/diagonal band complex (MS/DBB) of adult rat and human, but the significance of nestin expression in functional neurons is not clear. This study investigated electrophysiological properties and neurochemical phenotypes of nestin-expressing (nestin+) neurons using whole-cell recording combined with single-cell RT-PCR to explore the significance of nestin expression in functional MS/DBB neurons. The retrograde labelling and immunofluorescence were used to investigate the nestin+ neuron related circuit in the septo-hippocampal pathway.</p> <p>Results</p> <p>The results of single-cell RT-PCR showed that 87.5% (35/40) of nestin+ cells expressed choline acetyltransferase mRNA (ChAT+), only 44.3% (35/79) of ChAT+ cells expressed nestin mRNA. Furthermore, none of the nestin+ cells expressed glutamic acid decarboxylases 67 (GAD<sub>67</sub>) or vesicular glutamate transporters (VGLUT) mRNA. All of the recorded nestin+ cells were excitable and demonstrated slow-firing properties, which were distinctive from those of GAD<sub>67 </sub>or VGLUT mRNA-positive neurons. These results show that the MS/DBB cholinergic neurons could be divided into nestin-expressing cholinergic neurons (NEChs) and nestin non-expressing cholinergic neurons (NNChs). Interestingly, NEChs had higher excitability and received stronger spontaneous excitatory synaptic inputs than NNChs. Retrograde labelling combined with choline acetyltransferase and nestin immunofluorescence showed that both of the NEChs and NNChs projected to hippocampus.</p> <p>Conclusions</p> <p>These results suggest that there are two parallel cholinergic septo-hippocampal pathways that may have different functions. The significance of nestin expressing in functional neurons has been discussed.</p
Efficient Temporal Butterfly Counting and Enumeration on Temporal Bipartite Graphs
Bipartite graphs model relationships between two different sets of entities,
like actor-movie, user-item, and author-paper. The butterfly, a 4-vertices
4-edges bi-clique, is the simplest cohesive motif in a bipartite
graph and is the fundamental component of higher-order substructures. Counting
and enumerating the butterflies offer significant benefits across various
applications, including fraud detection, graph embedding, and community search.
While the corresponding motif, the triangle, in the unipartite graphs has been
widely studied in both static and temporal settings, the extension of butterfly
to temporal bipartite graphs remains unexplored. In this paper, we investigate
the temporal butterfly counting and enumeration problem: count and enumerate
the butterflies whose edges establish following a certain order within a given
duration. Towards efficient computation, we devise a non-trivial baseline
rooted in the state-of-the-art butterfly counting algorithm on static graphs,
further, explore the intrinsic property of the temporal butterfly, and develop
a new optimization framework with a compact data structure and effective
priority strategy. The time complexity is proved to be significantly reduced
without compromising on space efficiency. In addition, we generalize our
algorithms to practical streaming settings and multi-core computing
architectures. Our extensive experiments on 11 large-scale real-world datasets
demonstrate the efficiency and scalability of our solutions
Identification of Causal Relationship between Amyloid-beta Accumulation and Alzheimer's Disease Progression via Counterfactual Inference
Alzheimer's disease (AD) is a neurodegenerative disorder that is beginning
with amyloidosis, followed by neuronal loss and deterioration in structure,
function, and cognition. The accumulation of amyloid-beta in the brain,
measured through 18F-florbetapir (AV45) positron emission tomography (PET)
imaging, has been widely used for early diagnosis of AD. However, the
relationship between amyloid-beta accumulation and AD pathophysiology remains
unclear, and causal inference approaches are needed to uncover how amyloid-beta
levels can impact AD development. In this paper, we propose a graph varying
coefficient neural network (GVCNet) for estimating the individual treatment
effect with continuous treatment levels using a graph convolutional neural
network. We highlight the potential of causal inference approaches, including
GVCNet, for measuring the regional causal connections between amyloid-beta
accumulation and AD pathophysiology, which may serve as a robust tool for early
diagnosis and tailored care
The effect of Bafa Wubu of Tai Chi on college studentsâ anxiety and depression: A randomized, controlled pilot study
Objective: This pilot study aimed to explore the mechanism of the effects of Bafa Wubu of Tai Chi (BWTC) on anxiety and depression in college students using resting-state functional magnetic resonance imaging (RS-fMRI).Methods: Eighteen college students (5 males and 13 females) with anxiety and depression met the study criteria and were randomly divided into an experimental group (aged 24.20 ± 4.07 years) and a control group (aged 22.50 ± 5.95). The experimental group received an eight-week BWTC intervention five times/week for 60 min/session. The control group maintained normal daily life without any exercise intervention. These students were assessed using RS-fMRI scans, the self-rating anxiety scale (SAS), and the self-rating depression scale (SDS). Spearman correlation analysis was used, and statistical significance was defined as a two-sided p-value of <0.05.Results: After the intervention, the SAS and SDS scores of the BWTC group significantly reduced (p = 0.002; p = 0.001). Compared with the control group, the fALFF values of the right middle frontal gyrus, orbital part (Frontal_Mid_Orb_R) (p = 0.043), right inferior occipital gyrus (Occipital_Inf_R) (p = 0.003), and right middle temporal gyrus of the temporal pole (Temporal_Pole_Mid_R) (p = 0.003) in the BWTC group increased significantly; the fALFF values of the left middle frontal gyrus (Frontal_Mid_L) (p = 0.001) and right supplementary motor area (Supp_Motor_Area_R) (p = 0.010) in BWTC group decreased significantly. The fALFF values of Frontal_Mid_Orb_R were significantly positively correlated with the SDS score (r = 0.852, p = 0.015) and the fALFF values of Frontal_Mid_L were significantly negatively correlated with the SAS score (r = â0.797, p = 0.032).Conclusion: In this pilot study with college students, BWTC alleviated anxiety and depression, potentially through modulating activity in the Frontal_Mid_L and Frontal_Mid_Orb_R, respectively
Outcomes Impacting Quality of Life in Advanced Parkinson's Disease Patients Treated with Levodopa-Carbidopa Intestinal Gel
BACKGROUND: It is believed that motor symptoms, including dyskinesia, and non-motor symptoms impact health-related quality of life (HRQoL) in patients with Parkinsonâs disease (PD), and that improvements in these metrics are correlated. OBJECTIVE: Investigate the relationship between HRQoL and measures of PD severity and treatment efficacy, including motor and non-motor symptoms. METHODS: This was a planned investigation of an international, prospective, single-arm, post-marketing observational study of the long-term effectiveness of levodopa-carbidopa intestinal gel (LCIG) in patients with advanced PD. Pearson correlation coefficients (PCC) were calculated for baseline and change from baseline at 12 months between HRQoL and motor and non-motor symptoms. RESULTS: A total of 195 patients were included. At baseline, HRQoL was moderately positively correlated with Activities of Daily Living (UPDRS II, PCCâ=â0.44), non-motor symptoms (0.48), and measures of sleep (0.50 and 0.40); all pâ<â0.001. After 12 months of treatment with LCIG, improvements in HRQoL were moderately positively correlated with improvement from baseline in non-motor symptoms (PCCâ=â0.42), sleep (0.54), and daytime sleepiness (0.40; all pâ<â0.001), and weakly correlated with improvement in dyskinesia signs and symptoms (PCCâ=â0.23; pâ=â0.011). Improvement in HRQoL was not correlated with improvements in OFF time or dyskinesia time. CONCLUSION: Both at baseline and for change from baseline at 12 months, HRQoL was correlated with baseline and change from baseline in dyskinesia, Activities of Daily Living, and non-motor symptoms, including sleep; but not with baseline or change in OFF time
The large area detector onboard the eXTP mission
The Large Area Detector (LAD) is the high-throughput, spectral-timing instrument onboard the eXTP mission, a flagship
mission of the Chinese Academy of Sciences and the China National Space Administration, with a large European
participation coordinated by Italy and Spain. The eXTP mission is currently performing its phase B study, with a target
launch at the end-2027. The eXTP scientific payload includes four instruments (SFA, PFA, LAD and WFM) offering
unprecedented simultaneous wide-band X-ray timing and polarimetry sensitivity. The LAD instrument is based on the
design originally proposed for the LOFT mission. It envisages a deployed 3.2 m2 effective area in the 2-30 keV energy
range, achieved through the technology of the large-area Silicon Drift Detectors - offering a spectral resolution of up to
200 eV FWHM at 6 keV - and of capillary plate collimators - limiting the field of view to about 1 degree. In this paper
we will provide an overview of the LAD instrument design, its current status of development and anticipated
performance
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