Age- and time-of-day dependence of glymphatic function in the human brain measured via two diffusion MRI methods

Advanced age, accompanied by impaired glymphatic function, is a key risk factor for many neurodegenerative diseases. To study age-related differences in the human glymphatic system, we measured the influx and efflux activities of the glymphatic system via two non-invasive diffusion magnetic resonance imaging (MRI) methods, ultra-long echo time and low-b diffusion tensor imaging (DTIlow–b) measuring the subarachnoid space (SAS) flow along the middle cerebral artery and DTI analysis along the perivascular space (DTI-ALPS) along medullary veins in 22 healthy volunteers (aged 21–75 years). We first evaluated the circadian rhythm dependence of the glymphatic activity by repeating the MRI measurements at five time points from 8:00 to 23:00 and found no time-of-day dependence in the awake state under the current sensitivity of MRI measurements. Further test–retest analysis demonstrated high repeatability of both diffusion MRI measurements, suggesting their reliability. Additionally, the influx rate of the glymphatic system was significantly higher in participants aged >45 years than in participants aged 21–38, while the efflux rate was significantly lower in those aged >45 years. The mismatched influx and efflux activities in the glymphatic system might be due to age-related changes in arterial pulsation and aquaporin-4 polarization

Evaluation of the Sustainable Forest Management Performance in Forestry Enterprises Based on a Hybrid Multi-Criteria Decision-Making Model: A Case Study in China

Sustainable Forest Management (SFM) can fully use forest resources and improve the economic, environmental, and social sustainability of forest areas. Forestry enterprises play a crucial role in the implementation of SFM. However, the previous literature on SFM pays little attention to the subject of forestry enterprises. This paper aims to extend research on SFM from a macro perspective to the micro level of forestry enterprises. Taking the Triple Bottom Line (TBL) as a theoretical framework and the Montreal Process Criteria and Indicators (MP C&Is) as a basis, this paper constructs an indicator system to evaluate the performance of SFM of forestry enterprises from economic, social, and environmental aspects. Then, we apply the hybrid Multi-Criteria Decision-Making (MCDM) methods, i.e., the Best–Worst Method (BWM) and the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, to construct the methodological system for SFM performance evaluation of forestry enterprises. Through a questionnaire survey of 68 academics and researchers, we determine the weights of the SFM indicators and select a representative forestry enterprise as a case study. The effectiveness of this SFM performance evaluation model is then demonstrated through its application to the case study of forestry enterprises in China. Through the application of the model, this paper evaluates the enterprise’s SFM performance over the five-year period 2017–2021 and proposes appropriate policy recommendations and improvements. It is found that environmental factors are the primary factors of SFM in forestry enterprises. Forestry enterprises should not only pay attention to economic benefits but also to the use of forest resources and the protection of forest ecosystems to better achieve SFM

Terahertz photoconductive antenna with all-dielectric nanopillars

Photoconductive antennas (PCAs), as a popular terahertz (THz) radiation source, have been widely used in spectroscopy, material characterization, biological imaging and detection of hazardous materials. However, PCAs have a relatively low energy conversion efficiency from femtosecond laser pulses to THz radiation which often limits the signal-to-noise ratio and bandwidth of THz imaging and spectroscopy systems. To address these limitations, here we report a THz photoconductive antenna emitter with all-dielectric nanopillars integrated on top of the SI-GaAs substrate to increase the generated photocarriers, which achieves a broadband and frequency insensitive THz power enhancement factor around 1.25 at frequencies 0.05 - 1.6 THz. Our results reported here provide a new method for increasing the THz power of PCAs, which paves the way for the subsequent researches of next-generation PCAs

Breakdown Characteristics of Ga₂O₃-on-SiC Metal-Oxide-Semiconductor Field-Effect Transistors

Ultra-wide bandgap semiconductor gallium oxide (Ga2O3) features a breakdown strength of 8 MV/cm and bulk mobility of up to 300 cm2V−1s−1, which is considered a promising candidate for next-generation power devices. However, its low thermal conductivity is reckoned to be a severe issue in the thermal management of high-power devices. The epitaxial integration of gallium oxide thin films on silicon carbide (SiC) substrates is a possible solution for tackling the cooling problems, yet premature breakdown at the Ga2O3/SiC interface would be introduced due to the relatively low breakdown strength of SiC (3.2 MV/cm). In this paper, the on-state properties as well as the breakdown characteristics of the Ga2O3-on-SiC metal-oxide-semiconductor field-effect transistor (MOSFET) were investigated by using the technology computer-aided design (TCAD) approach. Compared with the full-Ga2O3 MOSFET, the lattice temperature of the Ga2O3-on-SiC MOSFET was decreased by nearly 100 °C thanks to the high thermal conductivity of SiC. However, a breakdown voltage degradation of >40% was found in an unoptimized Ga2O3-on-SiC MOSFET. Furthermore, by optimizing the device structure, the breakdown voltage degradation of the Ga2O3-on-SiC MOSFET is significantly relieved. As a result, this work demonstrates the existence of premature breakdown in the Ga2O3-on-SiC MOSFET and provides feasible approaches to further enhance the performance of hetero-integrated Ga2O3 power devices

Solving urban electric transit network problem by integrating Pareto artificial fish swarm algorithm and genetic algorithm

This study presents a multi-objective optimization model for the urban electric transit network problem with the aim of simultaneously designing the layout of bus routes, the frequency and the location and size of charging stations by making a tradeoff between two inconsistent objectives from the perspectives of passengers and operators. A Pareto artificial fish swarm algorithm (PAFSA) embedded with the genetic algorithm (GA) is developed to solve the proposed model. The PAFSA is designed to iteratively search for the proper network configuration satisfying two conflicting objectives. During which, the demand assignment with real-time transit information is performed to update the frequency of each newly designed route. The GA embedded into the PAFSA iteratively decides the locations of charging stations and the number of chargers to be installed in each charging station. A case study of the transit network in an urban region of a city in China is implemented, revealing that the proposed approach is able to rationally design a relatively large-scaled transit network with searching for the best fits between two inconsistent objectives

Feature Pyramid Networks and Long Short-Term Memory for EEG Feature Map-Based Emotion Recognition

The original EEG data collected are the 1D sequence, which ignores spatial topology information; Feature Pyramid Networks (FPN) is better at small dimension target detection and insufficient feature extraction in the scale transformation than CNN. We propose a method of FPN and Long Short-Term Memory (FPN-LSTM) for EEG feature map-based emotion recognition. According to the spatial arrangement of brain electrodes, the Azimuth Equidistant Projection (AEP) is employed to generate the 2D EEG map, which preserves the spatial topology information; then, the average power, variance power, and standard deviation power of three frequency bands (α, β, and γ) are extracted as the feature data for the EEG feature map. BiCubic interpolation is employed to interpolate the blank pixel among the electrodes; the three frequency bands EEG feature maps are used as the G, R, and B channels to generate EEG feature maps. Then, we put forward the idea of distributing the weight proportion for channels, assign large weight to strong emotion correlation channels (AF3, F3, F7, FC5, and T7), and assign small weight to the others; the proposed FPN-LSTM is used on EEG feature maps for emotion recognition. The experiment results show that the proposed method can achieve Value and Arousal recognition rates of 90.05% and 90.84%, respectively

Feature Pyramid Networks and Long Short-Term Memory for EEG Feature Map-Based Emotion Recognition

The original EEG data collected are the 1D sequence, which ignores spatial topology information; Feature Pyramid Networks (FPN) is better at small dimension target detection and insufficient feature extraction in the scale transformation than CNN. We propose a method of FPN and Long Short-Term Memory (FPN-LSTM) for EEG feature map-based emotion recognition. According to the spatial arrangement of brain electrodes, the Azimuth Equidistant Projection (AEP) is employed to generate the 2D EEG map, which preserves the spatial topology information; then, the average power, variance power, and standard deviation power of three frequency bands (α, β, and γ) are extracted as the feature data for the EEG feature map. BiCubic interpolation is employed to interpolate the blank pixel among the electrodes; the three frequency bands EEG feature maps are used as the G, R, and B channels to generate EEG feature maps. Then, we put forward the idea of distributing the weight proportion for channels, assign large weight to strong emotion correlation channels (AF3, F3, F7, FC5, and T7), and assign small weight to the others; the proposed FPN-LSTM is used on EEG feature maps for emotion recognition. The experiment results show that the proposed method can achieve Value and Arousal recognition rates of 90.05% and 90.84%, respectively

Minor Non-Disabling Stroke Patients with Large Vessel Severe Stenosis or Occlusion Might Benefit from Thrombolysis

Background: The benefit of alteplase in minor non-disabling acute ischemic stroke (AIS) is unknown. We aimed to explore the clinical efficacy of alteplase-treatment in minor non-disabling stroke in clinical practice. Methods: We used a prospectively collected database of AIS patients who were being assessed for thrombolysis with alteplase. Minor non-disabling AIS was identified as patients with baseline National Institutes of Health Stroke Scale (NIHSS) score ≤ 5 and a score 0 or 1 on each baseline NIHSS score item (items 1a to 1c being 0). Results: A total of 461 patients with minor non-disabling AIS were included and among them 240 (52.1%) patients were treated with alteplase and 113 (24.5%) patients had severe stenosis/occlusion of large vessels. No significant association of 90-day excellent outcome was found with alteplase-treatment (77.1% vs. 80.5%, p 1 = 0.425; OR 0.911, 95% CI 0.428 to 1.940; p 2 = 0.808). However, among patients with severe stenosis/occlusion of large vessels, alteplase-treatment was independently associated with excellent outcome (74.4% vs. 45.7%, p 1 = 0.005; OR 4.709, 95% CI 1.391 to 11.962; p 2 = 0.010). Conclusion: Although alteplase-treatment did not result in an excellent outcome in general minor non-disabling stroke patients, it may work in those specific patients who had severe stenosis/occlusion of large vessels

Impairment of the Glymphatic Pathway and Putative Meningeal Lymphatic Vessels in the Aging Human

OBJECTIVE: Aging is a major risk factor for numerous neurological disorders, and the mechanisms underlying brain aging remain elusive. Recent animal studies demonstrated a tight relationship between impairment of the glymphatic pathway, meningeal lymphatic vessels, and aging. However, the relationship in the human brain remains uncertain. METHODS: In this observational cohort study, patients underwent magnetic resonance imaging before and at multiple time points after intrathecal administration of a contrast agent. Head T1-weighted imaging was performed to assess the function of the glymphatic pathway and head high-resolution T2-fluid attenuated inversion recovery imaging to visualize putative meningeal lymphatic vessels (pMLVs). We measured the signal unit ratio (SUR) of 6 locations in the glymphatic pathway and pMLVs, defined the percentage change in SUR from baseline to 39 hours as the clearance of the glymphatic pathway and pMLVs, and then analyzed their relationships with aging. RESULTS: In all patients (N = 35), the SUR of the glymphatic pathway and pMLVs changed significantly after intrathecal injection of the contrast agent. The clearance of both the glymphatic pathway and pMLVs was related to aging (all p \u3c 0.05). The clearance of pMLVs was significantly related to the clearance of the glymphatic pathway (all p \u3c 0.05), and the clearance of the glymphatic pathway was significantly faster in patients with early filling of pMLVs than those with late filling (all p \u3c 0.05). INTERPRETATION: We revealed that both the glymphatic pathway and pMLVs might be impaired in the aging human brain through the novel, clinically available method to simultaneously visualize their clearance. Our findings also support that in humans, pMLVs are the downstream of the glymphatic pathway. ANN NEUROL 2020