Dissociating the Role of the Orbitofrontal Cortex and the Striatum in the Computation of Goal Values and Prediction Errors

To make sound economic decisions, the brain needs to compute several different value-related signals. These include goal values that measure the predicted reward that results from the outcome generated by each of the actions under consideration, decision values that measure the net value of taking the different actions, and prediction errors that measure deviations from individuals' previous reward expectations. We used functional magnetic resonance imaging and a novel decision-making paradigm to dissociate the neural basis of these three computations. Our results show that they are supported by different neural substrates: goal values are correlated with activity in the medial orbitofrontal cortex, decision values are correlated with activity in the central orbitofrontal cortex, and prediction errors are correlated with activity in the ventral striatum

Value Computations in Ventral Medial Prefrontal Cortex during Charitable Decision Making Incorporate Input from Regions Involved in Social Cognition

Little is known about the neural networks supporting value computation during complex social decisions. We investigated this question using functional magnetic resonance imaging while subjects made donations to different charities. We found that the blood oxygenation level-dependent signal in ventral medial prefrontal cortex (VMPFC) correlated with the subjective value of voluntary donations. Furthermore, the region of the VMPFC identified showed considerable overlap with regions that have been shown to encode for the value of basic rewards at the time of choice, suggesting that it might serve as a common valuation system during decision making. In addition, functional connectivity analyses indicated that the value signal in VMPFC might integrate inputs from networks, including the anterior insula and posterior superior temporal cortex, that are thought to be involved in social cognition

Size measurement of dry ice particles produced from liquid carbon dioxide

The formation of dry ice particles in a jet flow has been studied experimentally. The particles were produced by rapid expansion of liquid carbon dioxide through a nozzle, based on the Joule–Thomson effect. Their size distribution was measured by a laser diffraction method. The experimental results showed that the primary dry ice particles ejected from the nozzle were about 1 μm in mass median diameter. However, they grew initially in the jet flow and then became smaller due to sublimation. As a result, a bimodal size distribution was formed at increased distances from the nozzle outlet. The presence of a thermally insulated tube at the outlet of the expansion nozzle enhanced the agglomeration of the particles, whereby agglomerates of about 100 μm in mass median diameter were recorded. The agglomeration process is considered to take place by the simultaneous processes of particle deposition and reentrainment; i.e. agglomerated particles are reentrained from the layer of dry ice particles deposited on the tube walls. The agglomerate size decreased with increasing flow velocity, due to the greater detachment force applied to the deposition layer. Therefore, the flow velocity was found to be an important parameter influencing the agglomeration of dry ice particles

Ball Indentation on Powder Beds for Assessing Powder Flowability: Analysis of Operation Window

The characterisation of bulk behaviour of cohesive powders is very important in processing of particulate solids, e.g. for reliable powder flow out of storage vessels. For filling and dosing of small quantities of powders in capsules and for dispersion in dry powder inhalers, the interest is on the behaviour of loosely-compacted powders in small quantities and under very low applied loads. Furthermore at the early stages of drug development, the quantity of the powder available is often very small and the traditional bulk testing methods are neither possible nor applicable. In this work we evaluate a method to infer powder flowability by ball indentation. This technique provides a measure of flow resistance which can be related to the unconfined yield stress. It can be applied at very low loads and requires only a small sample quantity, typically a few mm3. The operational window in the ball indentation method in terms of minimum sample size, penetration depth and indenter properties (such as size, shape, friction and Young's modulus) has been analysed and reported here

Calibrating Friction Coefficients in Discrete Element Method Simulations with Shear-Cell Experiments

Discrete Element Method (DEM) simulations coupled with shear cell experimental results have been used to investigate the flow behaviour of a dry particle assembly of glass beads in the quasi-static regime. 10 Experimental studies have been undertaken using an FT4 powder shear cell apparatus, in parallel with extensive DEM simulations of both homogeneous simple shear and the FT4 shear cell itself. The findings show that it is not possible to accurately predict the bulk friction coefficient with homogeneous simple shear simulations unless both rolling and sliding friction are considered. There are, however, multiple pairs of sliding and rolling friction coefficients which can reproduce the experimental bulk friction coefficient. Sliding 15 test experiments were conducted to yield the coefficient of sliding friction, and hence minimise the set of potentially correct pairs. Simulations of the full FT4 shear cell with two different calibration pairs, along with a pair without rolling friction, were then undertaken to understand the effect of their selection on realistic wall-bounded shearing conditions. Discrepancies were mainly found in the obtained radial contact number and velocity profiles, with increasing friction coefficients - particularly sliding friction - found to in20 hibit packing and particle velocity in the shear deformation zone. Comparison between homogeneous simple shear and shear cell simulation results showed a significant effect of the wall on the obtained force network, with almost a complete absence of the weakest structures which were seen supporting the strong structures in the simple shear scenario

Experimental investigation of heat generation during granular flow in a rotating drum using infrared thermography

Granular flow is common in many industrial applications, and involves heat generation from frictional contacts and inelastic collisions between particles. The self-heating process is still poorly understood despite being intrinsic to many processes. This work, for the first time, explores this problem experimentally by quantifying the temperature rise of granular flows in a rotating drum with a robust methodology based on infrared thermography. Particles of four different materials (lead, steel, plastic and glass) are used in the experiments, at various rotation speeds and drum fill ratios. To assess the mechanical behaviour, the flow regime of every experiment was determined. It was inferred that particles with higher density tend to generate more heat. It was also revealed that increasing the rotation speed favours the temperature rise. At the same time, the fill ratio had the least influence on the thermal response of the particulate systems considered.his project is funded through Marie SKŁODOWSKA-CURIE Innovative Training Network MATHEGRAM, the People Programme (Marie SKŁODOWSKA-CURIE Actions) of the European Union's Horizon 2020 Programme H2020 under REA grant agreement No. 813202. Dr. Franci acknowledges the support from MCIN/AEI/10.13039/501100011033 and FEDER Una manera de hacer Europa for funding his work via project PID2021-122676NB-I00. Prof. Oñate acknowledges the Severo Ochoa Programme through the Grant CEX2018-000797-S funded by MCIN/AEI/10.13039/501100011033.Peer ReviewedPostprint (published version

Fluid-particle energy transfer in spiral jet milling

Spiral jet milling is a size reduction process driven by the fluid energy of high velocity gas jets. Inter-particle and particle-wall interactions are responsible for size reduction. The process is energy intensive, but inefficient. The underlying mechanisms for size reduction in the mill are also not very well understood. The optimum grinding conditions are still currently found by trial and error experimentation. In this work, the Discrete Element Method coupled with Computational Fluid Dynamics is used to investigate the effects of different parameters on the particle collisional behaviour in a spiral jet mill. These include the particle concentration in the grinding chamber, the particle size, and the fluid power input. We report on our work analysing the efficiency of energy transfer and how it can be improved by changing the milling conditions and particle properties

Flowability assessment of weakly consolidated powders

The inability of cohesive powders to flow consistently and reliably is a major cause of process downtime and reduced efficiency across a wide range of powder processing industries. Most methods to assess powder flowability fail at low consolidation pressures (<1 kPa). In this paper, the ball indentation technique is used to assess the flow behaviour of two powders at low stresses by determining the bed hardness. In parallel, the powders are subjected to shear testing in a range of high stresses, with the derived unconfined yield strength used, along with the indentation hardness to define the constraint factor (C). By using the latter, which is considered independent of the preconsolidation stress applied, the unconfined yield strength of the powders at low stresses are inferred from the penetration hardness measurements

A regime map for dry powder coating: the influence of material properties and process parameters

A numerical study is carried out to investigate the combined influence of material properties and process parameters on coating quality in a high shear mixer (specifically an FT4 Powder Rheometer) to construct a regime map. The Discrete Element Method (DEM) is employed to simulate a range of material properties (size, density, and surface energy) and process parameters (impeller speed and mixing time) via Design of Experiments (DoE). A robust regime map is proposed for prediction of dry coating performance based on dimensionless Stokes deformation number (Stdef) and granular Bond number (Bo). The regime map provides insight on the optimal range of material properties and process parameters to achieve high coating levels in a high-shear bladed mixer. Furthermore, the minimum energy required to achieve optimal coating performance as well as regions of poor coating quality due to guest detachment exacerbated by excessive energy input can be identified from the regime map, thus reducing wastage of energy and coating material required. The regime map enables the required mixing time for optimal coating to be determined so long as particle size distributions and surface energies are known