An anti-junk food ad from a sports commercial break reduced junk food consumption inclinations, yet junk food ads had minimal to no impact.

Background: In Australia, there are concerns that unrestricted junk food advertising during sports broadcasts increases short-term junk food consumption among viewers. Therefore, the present study aimed to estimate the impact of junk food and anti-junk food advertising on consumption inclinations.

Methods: We conducted a content analysis across a sample (N = 16) of Australian Football League (AFL) and National Rugby League (NRL) matches to determine the prevalence of junk food and anti-junk food advertising video clips.

Spatial analysis of femtosecond laser generated plasma using principal component analysis.

The appearance of plasma generated during femtosecond laser machining depends strongly on the features present on the sample before machining occurs. However, the complexity of femtosecond light-matter interaction means that development of a theoretical understanding of plasma generation is challenging. In this work, principal component analysis is applied to experimental images of plasma generated during femtosecond laser machining of silicon to calculate the orthogonal spatial patterns of the plasma variance (plasma modes), and to identify which sample variance (sample modes) are associated with these plasma modes.

Single-step beam intensity and profile optimization using a 256 × 256 micromirror array and reinforcement learning.

Many optical applications require accurate control over a beam's spatial intensity profile, in particular, achieving uniform irradiance across a target area can be critically important for nonlinear optical processes such as laser machining. This paper introduces a novel control algorithm for Digital Micromirror Devices (DMDs) that simultaneously and adaptively modulates both the intensity and the spatial intensity profile of an incident beam with random and intricate intensity variations in a single step. The algorithm treats each micromirror within the DMD as an independent Bernoulli distribution characterized by a learnable parameter.

Integrating IL-12 mRNA nanotechnology with SBRT eliminates T cell exhaustion in preclinical models of pancreatic cancer.

Pronounced T cell exhaustion characterizes immunosuppressive tumors, with the tumor microenvironment (TME) employing multiple mechanisms to elicit this suppression. Traditional immunotherapies, such as immune checkpoint blockade, often fail due to their focus primarily on T cells. To overcome this, we utilized a proinflammatory cytokine, interleukin (IL)-12, that re-wires the immunosuppressive TME by inducing T cell effector function while also repolarizing immunosuppressive myeloid cells.

Imaging pollen using a Raspberry Pi and LED with deep learning.

The production of low-cost, small footprint imaging sensor would be invaluable for airborne global monitoring of pollen, which could allow for mitigation of hay fever symptoms. We demonstrate the use of a white light LED (light emitting diode) to illuminate pollen grains and capture their scattering pattern using a Raspberry Pi camera. The scattering patterns are transformed into 20× microscope magnification equivalent images using deep learning.