The psychology and policy of overcoming economic inequality.

Recent arguments claim that behavioral science has focused - to its detriment - on the individual over the system when construing behavioral interventions. In this commentary, we argue that tackling economic inequality using both framings in tandem is invaluable. By studying individuals who have overcome inequality, "positive deviants," and the system limitations they navigate, we offer potentially greater policy solutions.

The persistence of cognitive biases in financial decisions across economic groups.

While economic inequality continues to rise within countries, efforts to address it have been largely ineffective, particularly those involving behavioral approaches. It is often implied but not tested that choice patterns among low-income individuals may be a factor impeding behavioral interventions aimed at improving upward economic mobility. To test this, we assessed rates of ten cognitive biases across nearly 5000 participants from 27 countries. Our analyses were primarily focused on 1458 individuals that were either low-income adults or individuals who grew up in disadvantaged households but had above-average financial well-being as adults, known as positive deviants. Using discrete and complex models, we find evidence of no differences within or between groups or countries. We therefore conclude that choices impeded by cognitive biases alone cannot explain why some individuals do not experience upward economic mobility. Policies must combine both behavioral and structural interventions to improve financial well-being across populations.

Monte Carlo simulation of sensitivity and NECR of an entire-body PET scanner.

The current positron emission tomography (PET) design is aimed toward establishing an entire-body PET scanner. An entire-body PET scanner is a scanner whose axial field of view (FOV) covers the whole body of a patient, whereas whole-body PET scanner can be of any axial FOV length, but was designed for a whole-body scan. Despite its high production cost, an entire-body depth-of-interaction PET scanner offers many benefits, such as shorter and dynamic PET time acquisition, as well as higher sensitivity and count rate performance. This PET scanner may be cost-effective for clinical PET scanners with high scan throughput. In this work, we evaluated the sensitivity and count rate performance of a 2-m-long PET scanner with conventional data acquisition (DAQ) architecture, using Monte Carlo simulation, and we evaluated two ring diameters (60 and 80 cm) to reduce the scanner cost. From simulation of scanning with a 2-m axial FOV, the sensitivity for a 2-m-long PET scanner of 60 and 80-cm diameter is around 80 and 68 times higher, respectively, than that of the conventional PET scanner. In addition, for the 2-m-long PET scanner with 60-cm diameter, the peak noise equivalent count rate (NECR) was 843 kcps at 125 MBq, whereas the peak for the 80-cm diameter was 989 kcps at 200 MBq. This shows gains of 15.3 and 17.95, respectively, in comparison with that of the conventional PET scanner. The 2-m-long PET scanner with 60-cm ring diameter could not only reduce the number of detectors by 21 %, but also had a 17 % higher sensitivity compared to that with an 80-cm ring diameter. On the other hand, despite the higher sensitivity, the NECR of the 60-cm ring diameter was smaller than that of the 80-cm ring diameter. This results from the single data loss due to dead time, whereas grouping of axially stacked detectors was used in the conventional DAQ architecture. Parallelization of the DAQ architecture is therefore important for the 2-m-long PET scanner to achieve its optimal performance.

An inter-crystal scatter correction method for DOI PET image reconstruction.

New PET scanners utilize depth-of-interaction (DOI) information to improve image resolution, particularly at the edge of field-of-view while maintaining high detector sensitivity. However, the inter-crystal scatter (ICS) effect cannot be neglected in DOI scanners due to the use of smaller crystals. ICS is the phenomenon wherein there are multiple scintillations for irradiation of a gamma photon due to Compton scatter in detecting crystals. In the case of ICS, only one scintillation position is approximated for detectors with Anger-type logic calculation. This causes an error in position detection and ICS worsens the image contrast, particularly for smaller hotspots. In this study, we propose to model an ICS probability by using a Monte Carlo simulator. The probability is given as a statistical relationship between the gamma photon first interaction crystal pair and the detected crystal pair. It is then used to improve the system matrix of a statistical image reconstruction algorithm, such as ML-EM in order to correct for the position error caused by ICS. We apply the proposed method to simulated data of the jPET-D4, which is a four-layer DOI PET being developed at the National Institute of Radiological Sciences. Our computer simulations show that image contrast is recovered successfully by the proposed method.

Transaxial system models for jPET-D4 image reconstruction.

A high-performance brain PET scanner, jPET-D4, which provides four-layer depth-of-interaction (DOI) information, is being developed to achieve not only high spatial resolution, but also high scanner sensitivity. One technical issue to be dealt with is the data dimensions which increase in proportion to the square of the number of DOI layers. It is, therefore, difficult to apply algebraic or statistical image reconstruction methods directly to DOI-PET, though they improve image quality through accurate system modelling. The process that requires the most computational time and storage space is the calculation of the huge number of system matrix elements. The DOI compression (DOIC) method, which we have previously proposed, reduces data dimensions by a factor of 1/5. In this paper, we propose a transaxial imaging system model optimized for jPET-D4 with the DOIC method. The proposed model assumes that detector response functions (DRFs) are uniform along line-of-responses (LORs). Then each element of the system matrix is calculated as the summed intersection lengths between a pixel and sub-LORs weighted by a value from the DRF look-up-table. 2D numerical simulation results showed that the proposed model cut the calculation time by a factor of several hundred while keeping image quality, compared with the accurate system model. A 3D image reconstruction with the on-the-fly calculation of the system matrix is within the practical limitations by incorporating the proposed model and the DOIC method with one-pass accelerated iterative methods.