Search results for "verkot"
showing 10 items of 326 documents
Safety and efficacy outcomes after intranasal administration of neural stem cells in cerebral palsy : a randomized phase 1/2 controlled trial
2023
Abstract Background Neural stem cells (NSCs) are believed to have the most therapeutic potential for neurological disorders because they can differentiate into various neurons and glial cells. This research evaluated the safety and efficacy of intranasal administration of NSCs in children with cerebral palsy (CP). The functional brain network (FBN) analysis based on electroencephalogram (EEG) and voxel-based morphometry (VBM) analysis based on T1-weighted images were performed to evaluate functional and structural changes in the brain. Methods A total of 25 CP patients aged 3–12 years were randomly assigned to the treatment group (n = 15), which received an intranasal infusion of NSCs loade…
Tracing the fate of microplastic carbon in the aquatic food web by compound-specific isotope analysis
2019
Increasing abundance of microplastics (MP) in marine and freshwaters is currently one of the greatest environmental concerns. Since plastics are fairly resistant to chemical decomposition, breakdown and reutilization of MP carbon complexes requires microbial activity. Currently, only a few microbial isolates have been shown to degrade MPs, and direct measurements of the fate of the MP carbon are still lacking. We used compound-specific isotope analysis to track the fate of fully labelled 13C-polyethylene (PE) MP carbon across the aquatic microbial-animal interface. Isotopic values of respired CO2 and membrane lipids showed that MP carbon was partly mineralized and partly used for cell growt…
Chlorophyll Concentration Retrieval by Training Convolutional Neural Network for Stochastic Model of Leaf Optical Properties (SLOP) Inversion
2020
Miniaturized hyperspectral imaging techniques have developed rapidly in recent years and have become widely available for different applications. Combining calibrated hyperspectral imagery with inverse physically based reflectance models is an interesting approach for estimating chlorophyll concentrations that are good indicators of vegetation health. The objective of this study was to develop a novel approach for retrieving chlorophyll a and b values from remotely sensed data by inverting the stochastic model of leaf optical properties using a one-dimensional convolutional neural network. The inversion results and retrieved values are validated in two ways: A classical machine learning val…
Using Aerial Platforms in Predicting Water Quality Parameters from Hyperspectral Imaging Data with Deep Neural Networks
2020
In near future it is assumable that automated unmanned aerial platforms are coming more common. There are visions that transportation of different goods would be done with large planes, which can handle over 1000 kg payloads. While these planes are used for transportation they could similarly be used for remote sensing applications by adding sensors to the planes. Hyperspectral imagers are one this kind of sensor types. There is need for the efficient methods to interpret hyperspectral data to the wanted water quality parameters. In this work we survey the performance of neural networks in the prediction of water quality parameters from remotely sensed hyperspectral data in freshwater basin…
SAGECELL: Software-Defined Space-Air-Ground Integrated Moving Cells
2018
Ultra-dense networks (UDNs) provide an effective solution to accommodate the explosively growing data traffic of multimedia services and real-time applications. However, the densification of large numbers of static small cells faces many fundamental challenges, including deployment cost, energy consumption and control, and so on. This motivates us to develop software-defined space-air-ground integrated moving cells (SAGECELL), a programmable, scalable, and flexible framework to integrate space, air, and ground resources for matching dynamic traffic demands with network capacity supplies. First, we provide a comprehensive review of state-of-the-art literature. Then the conceptual architectur…
Analysis and Evaluation of Adaptive RSSI-based Ranging in Outdoor Wireless Sensor Networks
2019
Estimating inter-node distances based on received radio signal strength (RSSI) is the foundation of RSSI-based outdoor localization in wireless sensor networks (WSNs). However, the accuracy of RSSI-based ranging depends on environmental and weather conditions. Therefore, it is important that RSSI-based ranging adapts to prevailing conditions to improve its range and location accuracy. This paper analyzes and evaluates RSSI-based ranging and adaptive techniques in outdoor WSNs to improve the range quality. The findings highlight the effects of path loss exponent (PLE) estimation error and temperature change on RSSI-based ranging. Consequently, we analyze techniques for mitigating these detri…
On optimal deployment of low power nodes for high frequency next generation wireless systems
2018
Recent development of wireless communication systems and standards is characterized by constant increase of allocated spectrum resources. Since lower frequency ranges cannot provide sufficient amount of bandwidth, new bands are allocated at higher frequencies, for which operators resort to deploy more base stations to ensure the same coverage and to utilize more efficiently higher frequencies spectrum. Striving for deployment flexibility, mobile operators can consider deploying low power nodes that could be either small cells connected via the wired backhaul or relays that utilize the same spectrum and the wireless access technology. However, even though low power nodes provide a greater fl…
Incentive Mechanism for Resource Allocation in Wireless Virtualized Networks with Multiple Infrastructure Providers
2020
To accommodate the explosively growing demands for mobile traffic service, wireless network virtualization is proposed as the main evolution towards 5G. In this work, a novel contract theoretic incentive mechanism is proposed to study how to manage the resources and provide services to the users in the wireless virtualized networks. We consider that the infrastructure providers (InPs) own the physical networks and the mobile virtual network operator (MVNO) has the service information of the users and needs to lease the physical radio resources for providing services. In particular, we utilize the contract theoretic approach to model the resource trading process between the MVNO and multiple…
Reducing Power Consumption of Wireless Networks Through Collaborative DMC Mobile Clusters
2017
Reducing the energy consumption of the wireless network is significantly important to the economic and ecological sustainability of the ICT industry, as high energy consumption may limit the performance of wireless networks and is one of the main network costs. To solve energy consumption problem, especially on the terminal side, a scheme known as distributed mobile cloud (DMC) is considered to be a potential solution. Multiple mobile terminals (MTs) can cooperative to take advantage of good quality links among the MTs to save energy when receiving from the Base Station (BS). In this paper, we aim to find the optimal transmit power to further reduce the energy consumption of DMC. From simul…
Dual Connectivity in Non-Stand Alone Deployment mode of 5G in Manhattan Environment
2020
| openaire: EC/H2020/815191/EU//PriMO-5G The main target of this paper is to analyze the performance of an outdoor user in a dense micro cellular Manhattan grid environment using a ray launching simulation tool. The radio propagation simulations are performed using a Shoot and Bouncing Ray (SBR) method. The network performance is analyzed at three different frequencies i.e. 1.8 GHz, 3.5 GHz, and 28 GHz. Additionally, the benefits of combining LTE and potential 5G frequency bands by using feature of Dual Connectivity (DC) in an outdoor scenario has been highlighted. The considered performance metrics are received signal level, SINR, application throughput. The acquired simulation results fro…