Parkinson's disease (PD) is a progressive neurological disorder characterized by loss of neurons that synthesize dopamine, and subsequent impaired movement. Umbilical cord mesenchymal stem cells (UC-MSCs) exerted neuroprotection effects in rodent model PD. However, the mechanism underlying UC-MSC-generated was not fully elucidated. In present study, we found intranasal administration UC-MSCs significantly alleviated locomotor deficits rescued dopaminergic inhibiting neuroinflammation PD...

The therapeutic effect of stroke is hampered by the lack neuroprotective drugs against ischemic insults beyond acute phase. Carnitine plays important roles in mitochondrial metabolism and modulating ratio coenzyme A (CoA)/acyl-CoA. Here, we investigate effects l-carnitine (LC) Acetyl-l-carnitine (ALC) pre-treatment on under same experimental conditions. We used a transient middle cerebral artery occlusion (MCAO) model to evaluate protective LC ALC focal ischemia vivo understand possible...

A novel method based on hollow fibre liquid phase microextraction coupled with a hand-held ion mobility spectrometer was developed for determination of seven pesticides in cucumber samples. The (LPME) sample preparation is used to preconcentrate pesticide residues present extracted are detected by IMS under optimized operating conditions. During the tests, instrument operated positive mode at ambient pressure using 63Ni as ionization source, dry, clean air drift gas which circulates closed...

The rapid industrial development has led to the intermittent outbreak of pm2.5 or haze in developing countries, which brought about great environmental issues, especially big cities such as Beijing and New Delhi. We investigated factors mechanisms change present a long-term prediction model episodes using time series analysis. construct dynamic structural measurement daily increment reduce vector autoregressive model. Typical case studies on 886 continuous days indicate that our performs...

Manual annotation of sentiment lexicons costs too much labor and time, it is also difficult to get accurate quantification emotional intensity. Besides, the excessive emphasis on one specific field has greatly limited applicability domain (Wang et al., 2010). This paper implements statistical training for large-scale Chinese corpus through neural network language model proposes an automatic method constructing a multidimensional lexicon based constraints coordinate offset. In order...

In this paper, we propose a model-free unsupervised learning approach to forecast real-time locational marginal prices (RTLMPs) in wholesale electricity markets. By organizing system-wide hourly RTLMP data into 3-dimensional (3D) tensor consisting of series time-indexed matrices, formulate the forecasting problem as generating next matrix with forecasted RTLMPs given historical tensor, and generative adversarial network (GAN) model RTLMPs. The proposed formulation preserves spatio-temporal...

In wholesale electricity markets, locational marginal prices (LMPs) are strongly spatio-temporal correlated. Most previous data-driven studies on LMP forecasting only leveraged temporal correlations among historical LMPs, very few of them learned the spatial to improve accuracy. this paper, a convolutional long-short term memory (CLSTM)-based generative adversarial network (GAN) is proposed forecast LMPs from market participants' perspective. Historical different price nodes organized into...

The locational marginal prices (LMPs), which are jointly determined by demands and generation bids, difficult to be forecasted from the market participants' perspective. In this paper, a special neural network (NN) architecture named decision transformer, is proposed forecast real-time LMPs learning temporal correlations among historical data sequences. LMP forecasting problem formulated as of future actions in model consisting explicit demand implicit bid data. consequence generators'...

Objective: Parkinson’s disease (PD) is a progressive neurodegenerative disorder with symptoms including tremor and bradykinesia, while traditional dopamine replacement therapy hypothalamic deep brain stimulation can temporarily relieve patients’ symptoms, they cannot cure the disease. Hence, discovering new methods crucial to designing more effective therapeutic approaches address condition. In our previous study, we found that exosomes (Exos) derived from human umbilical cord mesenchymal...

In this paper, we propose an unsupervised data-driven approach to predict real-time locational marginal prices (RTLMPs). The proposed is built upon a general data structure for organizing system-wide heterogeneous market streams into the format of images and videos. Leveraging structure, RTLMP prediction problem formulated as video problem. A model based on generative adversarial networks (GAN) learn spatio-temporal correlations among historical RTLMPs next hour. An autoregressive moving...

Locational Marginal Price (LMP) is composed of energy, congestion and loss price components. All these components are comprehensively determined by locational demands generation bids. Due to difficulties accessing updated bid information, previous predictions from market participants' perspective focused only on learning the spatio-temporal correlations among historical load data without using information. In this paper, a two-stage convolutional long short-term memory (CLSTM) approach...

This paper aims to find a mathematical and statistical way express natural words' semantic information by mapping words onto high-dimension continuous space. presents new approach of training word representations which 1) uses Weighted Local Influence language model (WLI model) assigning different weight the on locations, 2) introduces polynomial linear regression into representations, 3) global optimization scheme optimal solution representations. Empirical evidence indicates availability...

The rapid growth of renewable energy resources penetration is bringing more challenges to power system planning and operation. Relevant integration studies, such as the capability dynamic performance inverter-based resources' primary frequency response fast response, require high-resolution generation output data that are representative resources. This paper focuses on creating synthetic but realistic solar irradiance proposes a long short-term memory-based generative adversarial network...

In membrane separation processes, the presence of concentration polarization boundary layer (CPBL) can lead to a decline in flux and an increased risk fouling. This paper describes development capacitive microsensors for real-time in-situ monitoring CPBL growth nanofiltration module using CaSO/sub 4/ solution as feed. The sensors respond changes solute function distance from surface. Detection capability was determined series comprehensive experiments with systematic feed operating...

In this paper, we propose a model-free unsupervised learning approach to forecast real-time locational marginal prices (RTLMPs) in wholesale electricity markets. By organizing system-wide hourly RTLMP data into 3-dimensional (3D) tensor consisting of series time-indexed matrices, formulate the forecasting problem as generating next matrix with forecasted RTLMPs given historical tensor, and generative adversarial network (GAN) model RTLMPs. The proposed formulation preserves spatio-temporal...