Cerebral Blood Flow Monitoring in High-Risk Fetal and Neonatal Populations

Cerebrovascular pressure autoregulation promotes stable cerebral blood flow (CBF) across a range of arterial blood pressures. Cerebral autoregulation (CA) is a developmental process that reaches maturity around term gestation and can be monitored prenatally with both Doppler ultrasound and magnetic resonance imaging (MRI) techniques. Postnatally, there are key advantages and limitations to assessing CA with Doppler ultrasound, MRI, and near-infrared spectroscopy. Here we review these CBF monitoring techniques as well as their application to both fetal and neonatal populations at risk of perturbations in CBF. Specifically, we discuss CBF monitoring in fetuses with intrauterine growth restriction, anemia, congenital heart disease, neonates born preterm and those with hypoxic-ischemic encephalopathy. We conclude the review with insights into the future directions in this field with an emphasis on collaborative science and precision medicine approaches.

Fabrication of 2-D Capacitive Micromachined Ultrasonic Transducer (CMUT) Array through Silicon Wafer Bonding

Capacitive micromachined ultrasound transducers (CMUTs) have broad application prospects in medical imaging, flow monitoring, and nondestructive testing. CMUT arrays are limited by their fabrication process, which seriously restricts their further development and application. In this paper, a vacuum-sealed device for medical applications is introduced, which has the advantages of simple manufacturing process, no static friction, repeatability, and high reliability. The CMUT array suitable for medical imaging frequency band was fabricated by a silicon wafer bonding technology, and the adjacent array devices were isolated by an isolation slot, which was cut through the silicon film. The CMUT device fabricated following this process is a 4 × 16 array with a single element size of 1 mm × 1 mm. Device performance tests were conducted, where the center frequency of the transducer was 3.8 MHz, and the 6 dB fractional bandwidth was 110%. The static capacitance (29.4 pF) and center frequency (3.78 MHz) of each element of the array were tested, and the results revealed that the array has good consistency. Moreover, the transmitting and receiving performance of the transducer was evaluated by acoustic tests, and the receiving sensitivity was −211 dB @ 3 MHz, −213 dB @ 4 MHz. Finally, reflection imaging was performed using the array, which provides certain technical support for the research of two-dimensional CMUT arrays in the field of 3D ultrasound imaging.

A method of pedestrian flow monitoring based on received signal strength

There is a wide demand for people counting and pedestrian flow monitoring in large public places such as scenic tourist areas, shopping malls, stations, squares, and so on. Based on the feedback from the pedestrian flow monitoring system, resources can be optimally allocated to maximize social and economic benefits. Moreover, trampling accidents can be avoided because pedestrian guidance is carried out in time. In order to meet these requirements, we propose a method of pedestrian flow monitoring based on the received signal strength (RSS) of wireless sensor networks. This method mainly utilizes the shadow attenuation effect of pedestrians on radio frequency (RF) signals of effective links. In this paper, a deployment structure of RF wireless sensor network is firstly designed to monitor the pedestrians. Secondly, the features are extracted from the wavelet decomposition of RSS signal series with a short time. Lastly, the support vector machine (SVM) algorithm is trained by an experimental data set to distinguish the instantaneous number of pedestrian passing through the monitoring point. In the case of dense and sparse indoor personnel density, the accuracy of the SVM model is 88.9% and 94.5%, respectively. In the outdoor environment, the accuracy of the SVM model is 92.9%. The experimental results show that this method can realize the high precision monitoring of the flow of people in the context of real-time pedestrian flow monitoring.

Utility of Indocyanine Green Videoangiography with FLOW 800 Analysis in Brain Tumor Resection - Venous Protection Tchnique

Background: When it comes to central nervous system tumor resection, preserving vital venous structures to avoid devastating consequences such as brain edema and hemorrhage is important. Wheras, in clinical practice, it is difficult to obtain clear and vivid intraoperative venous visualization and blood flow analysis.Methods: We retrospectively reviewed patients underwent brain tumor resection through the application of indocyanine green videoangiography (ICG-VA) integrated with FLOW 800 from February 2019 to December 2020 and presented our clinical cases to demonstrate the process of venous preservation. Galen vein, sylvian vein and superior cerebral veins were included in our cases.Results: Clear documentations of the veins from different venous groups were obtained via ICG-VA integrated with FLOW 800, which semiquantitatively analyzed the flow dynamics. ICG-VA integrated with FLOW 800 enabled us to achieve brain tumor resection without venous injury and obstructing the venous flux.Conclusions: ICG-VA integrated with FLOW 800 is an available method for venous preservation, though further comparison between ICG-VA integrated with FLOW 800 and other techniques of intraoperative blood flow monitoring is needed.

PREDIKSI DEBIT ALIRAN MASUK KE TELAGA MENJER MENGGUNAKAN PERSAMAAN NERACA AIR DAN PEMODELAN HEC-HMS

The Menjer lake is the main source for Hydroelectric Power Plant of the PLTA Garung. Information about the water balance and the potential of existing water resources in the Menjer Catchment Area (DTA) is needed to obtain an efficient operating pattern, the sustainability of the Garung hydropower plant, and good management of the Menjer Lake. The purpose of this study was to estimate the inflow of three main rivers in the Menjer catchment area using HEC-HMS hydrological and water balance approach. Simulated results of the HEC-HMS model shows that the average of total the inflows of three main rivers to the Menjer lake in 2017, 2018 and 2019 during rainy season are 0.954 m3/s, 0.944 m3/s, and 1.017 m3/s, and during dry season are 0.820 m3/s, 0.783 m3/s, and 0.80 m3/s, respectively. While the prediction results of the discharge with the equation of the water balance shows that the average of total river inflows to the Menjer lake during rainy season is 2017 is 1.628 m3/s, in 2018 it is 1.579 m3/s, and in 2019 it is 3.296 m3/s and during dry season is 1.893 m3/s in 2017, 1.176 m3/s tahun 2018, and 1.893 m3/s in 2019. These results indicate that the results of discharge modeling with HEC-HMS are smaller than those predicted by the water balance equation. The study concluded that HEC-HMS could be used to predict daily inflows. However, further calibration and validation need to be carried out by recommending installing a river flow monitoring station at each river outlet.Keywords: water balance HEC-HMS, inflow prediction

Assessment of Applicability of Wi-Fi Analytics in Studies of Urban Public Transport Passenger Flow (Moscow Case Study)

The advantages and disadvantages of existing tools for calculating passenger flow are shown using the example of the city of Moscow.The objective of the research was to assess possibilities of using Wi-Fi data as a tool for analysing passenger flow. The authors used two types of Wi-Fi scanners and a tool they developed to analyse the collected data. The primary results of the study demonstrate the possibility of practical application of Wi-Fi data to analyse passenger flow.The described empirical studies, particularly data received from the portable Wi-Fi scanner, have shown that more than 20% of mobile devices in urban public transport and metro are used with Wi-Fi enabled, which is clearly not enough to get results necessary for comprehensive and detailed analysis of passenger flows. Nevertheless, the accumulating data allow to get possibility to forecast general passenger flow.A portable Wi-Fi scanner does not provide an opportunity to extensively capture a large area of the surveyed territory in real time (stops of urban public transport, locations where passengers enter the metro, etc.). Stationary Wi-Fi scanners could increase the amount of data and, accordingly, significantly adjust the results obtained. This enhancement could also be achieved through expansion of adoption of the tool of studying passenger flow to urban railways, i.e., in case of Moscow, to Moscow Central Circle and Moscow Central Diameters, as those routes provide Wi-Fi access at stations and in coaches.Data collected from Wi-Fi scanners can be an additional tool to other data sources, such as validation, automatic systems of passenger flow monitoring, and data obtained from cellular operators. For this reason, the further research in the field of Wi-Fi analytics along with development of technology in the field of existing data sources of passenger flow monitoring may result in better calculation of passenger flow.