Fluidisation characteristics of lactose powders in simple turbulent channel flows

© 2019 Elsevier Inc. A new experimental platform is presented which enables investigation of the effects of turbulence, mean forces and powder properties on the fluidisation of lactose powders as relevant to pharmaceutical applications. The flow consists of a fully developed channel flow which delivers a well-defined velocity profile over a bed of powder. An in-house two beam line of sight attenuation method has been developed to extract quantitative information on powder fluidisation time, time-resolved fluctuations in powder concentration and frequencies associated with the powder fluidisation process. Four lactose powders are examined which have a range of mass mean diameters and cohesiveness. Reynolds numbers from approximately 9000 to 20,000 are examined in this study, representing one of a few quantitative examinations of lactose powder behaviour in a simple canonical flow, where the boundary conditions are well-defined and the flow is intentionally simple. Evacuation times show dependence on the Reynolds number varied both through changing the local velocity and channel dimension, whereas the Reynolds number dependence weakens at higher Reynolds numbers. Frequencies measured show physical consistency with theoretical frequencies defined through the turbulent velocity and characteristic length-scale of the powder pocket

A Comparison of Evoked and Non-evoked Functional Networks

The growing interest in brain networks to study the brain's function in cognition and diseases has produced an increase in methods to extract these networks. Typically, each method yields a different network. Therefore, one may ask what the resulting networks represent. To address this issue we consider electrocorticography (ECoG) data where we compare three methods. We derive networks from on-going ECoG data using two traditional methods: cross-correlation (CC) and Granger causality (GC). Next, connectivity is probed actively using single pulse electrical stimulation (SPES). We compare the overlap in connectivity between these three methods as well as their ability to reveal well-known anatomical connections in the language circuit. We find that strong connections in the CC network form more or less a subset of the SPES network. GC and SPES are related more weakly, although GC connections coincide more frequently with SPES connections compared to non-existing SPES connections. Connectivity between the two major hubs in the language circuit, Broca's and Wernicke's area, is only found in SPES networks. Our results are of interest for the use of patient-specific networks obtained from ECoG. In epilepsy research, such networks form the basis for methods that predict the effect of epilepsy surgery. For this application SPES networks are interesting as they disclose more physiological connections compared to CC and GC networks

A Comparison of Evoked and Non-evoked Functional Networks

The growing interest in brain networks to study the brain’s function in cognition and diseases has produced an increase in methods to extract these networks. Typically, each method yields a different network. Therefore, one may ask what the resulting networks represent. To address this issue we consider electrocorticography (ECoG) data where we compare three methods. We derive networks from on-going ECoG data using two traditional methods: cross-correlation (CC) and Granger causality (GC). Next, connectivity is probed actively using single pulse electrical stimulation (SPES). We compare the overlap in connectivity between these three methods as well as their ability to reveal well-known anatomical connections in the language circuit. We find that strong connections in the CC network form more or less a subset of the SPES network. GC and SPES are related more weakly, although GC connections coincide more frequently with SPES connections compared to non-existing SPES connections. Connectivity between the two major hubs in the language circuit, Broca’s and Wernicke’s area, is only found in SPES networks. Our results are of interest for the use of patient-specific networks obtained from ECoG. In epilepsy research, such networks form the basis for methods that predict the effect of epilepsy surgery. For this application SPES networks are interesting as they disclose more physiological connections compared to CC and GC networks

Single Pulse Electrical Stimulation to identify epileptogenic cortex : Clinical information obtained from early evoked responses

Objective: Single Pulse Electrical Stimulation (SPES) probes epileptogenic cortex during electrocorticography. Two SPES responses are described: pathological delayed responses (DR, >100 ms) associated with the seizure onset zone (SOZ) and physiological early responses (ER, 80 Hz, in the SOZ and seizure propagation areas. Methods: We used data from 12 refractory epilepsy patients. SPES consisted of 10 pulses of 1 ms, 4-mA and 5 s interval on adjacent electrodes pairs. Data were available at 2048 samples/s for six and 512 samples/s (22 bits) for eight patients and analyzed in the time-frequency (TF) and time-domain (TD). Results: Electrodes with ERs were stronger associated with SOZ than non-SOZ electrodes. ERs with frequency content >80 Hz exist and are specific for SOZ channels. ERs evoked by stimulation of seizure onset electrodes were associated with electrodes involved in seizure propagation. Conclusion: Analysis of ERs can reveal aspects of pathology, manifested by association with seizure propagation and areas with high ER numbers that coincide with the SOZ. Significance: Not only DRs, but also ERs could have clinical value for mapping epileptogenic cortex and help to unravel aspects of the epileptic network