Recent progress in the development of a solar neutron tracking device (SONTRAC)

We report the results of recent calibration data analysis of a prototype scintillating fiber tracking detector system designed to perform imaging, spectroscopy and particle identification on 20 to 250 MeV neutrons and protons. We present the neutron imaging concept and briefly review the detection principle and the prototype description. The prototype detector system records ionization track data on an event-by-event basis allowing event selection criteria to be used in the off-line analysis. Images of acrylic phantoms from the analysis of recent proton beam calibrations are presented as demonstrations of the particle identification, imaging and energy measurement capabilities. The measured position resolution is \u3c 500 micrometers . The measured energy resolution is 14.2 percent at 35 MeV. The detection techniques employed can be applied to measurements in a variety of disciplines including solar and atmospheric physics, radiation therapy and nuclear materials monitoring. These applications are discussed briefly as are alternative detector configurations and future development plans

How increasing administrative burdens and means testing in the US safety-net punishes the poor

Millions of Americans rely on safety-net programs such as the Temporary Assistance for Needy Families, the Supplemental Nutrition Assistance Program, and Medicaid. In recent decades, these programs have been reformed with the aim of better targeting those most in need by creating rules and eligibility assessments. In new research. Ashley Fox, Wenhui Feng and Megan Reynolds find that the introduction of these rules has created substantial barriers and often reduced the enrolment of those who need the programs’ support the most. They argue that if we want needy individuals to access benefits, then we need to make it easy for them to do so by relaxing or removing the burdensome rules that serve as barriers to access

Deformation of a Trapped Fermi Gas with Unequal Spin Populations

The real-space densities of a polarized strongly-interacting two-component Fermi gas of $^6$Li atoms reveal two low temperature regimes, both with a fully-paired core. At the lowest temperatures, the unpolarized core deforms with increasing polarization. Sharp boundaries between the core and the excess unpaired atoms are consistent with a phase separation driven by a first-order phase transition. In contrast, at higher temperatures the core does not deform but remains unpolarized up to a critical polarization. The boundaries are not sharp in this case, indicating a partially-polarized shell between the core and the unpaired atoms. The temperature dependence is consistent with a tricritical point in the phase diagram.Comment: Accepted for publication in Physical Review Letter

Oral diabetes medication monotherapy and short-term mortality in individuals with type 2 diabetes and coronary artery disease

Objective To determine whether sulfonylurea use, compared with non-sulfonylurea oral diabetes medication use, was associated with 2-year mortality in individuals with well-controlled diabetes and coronary artery disease (CAD). Research design and methods We studied 5352 US veterans with type 2 diabetes, obstructive CAD on coronary angiography, hemoglobin A1c ≤7.5% at the time of catheterization, and taking zero or one oral diabetes medication (categorized as no medications, non-sulfonylurea medication, or sulfonylurea). We estimated the association between medication category and 2-year mortality using inverse probability of treatment-weighted (IPW) standardized mortality differences and IPW multivariable Cox proportional hazards regression. Results 49%, 35%, and 16% of the participants were on no diabetes medications, non-sulfonylurea medications, and sulfonylureas, respectively. In individuals on no medications, non-sulfonylurea medications, and sulfonylureas, the unadjusted mortality rates were 6.6%, 5.2%, and 11.9%, respectively, and the IPW-standardized mortality rates were 5.9%, 6.5%, and 9.7%, respectively. The standardized absolute 2-year mortality difference between non-sulfonylurea and sulfonylurea groups was 3.2% (95% CI 0.7 to 5.7) (p=0.01). In Cox proportional hazards models, the point estimate suggested that sulfonylurea use might be associated with greater hazard of mortality than non-sulfonylurea medication use, but this finding was not statistically significant (HR 1.38 (95% CI 1.00 to 1.93), p=0.05). We did not observe significant mortality differences between individuals on no diabetes medications and non-sulfonylurea users. Conclusions Sulfonylurea use was common (nearly one-third of those taking medications) and was associated with increased 2-year mortality in individuals with obstructive CAD. The significance of the association between sulfonylurea use and mortality was attenuated in fully adjusted survival models. Caution with sulfonylurea use may be warranted for patients with well-controlled diabetes and CAD, and metformin or newer diabetes medications with cardiovascular safety data could be considered as alternatives when individualizing therapy

PDL: Regularizing Multiple Instance Learning with Progressive Dropout Layers

Multiple instance learning (MIL) was a weakly supervised learning approach that sought to assign binary class labels to collections of instances known as bags. However, due to their weak supervision nature, the MIL methods were susceptible to overfitting and required assistance in developing comprehensive representations of target instances. While regularization typically effectively combated overfitting, its integration with the MIL model has been frequently overlooked in prior studies. Meanwhile, current regularization methods for MIL have shown limitations in their capacity to uncover a diverse array of representations. In this study, we delve into the realm of regularization within the MIL model, presenting a novel approach in the form of a Progressive Dropout Layer (PDL). We aim to not only address overfitting but also empower the MIL model in uncovering intricate and impactful feature representations. The proposed method was orthogonal to existing MIL methods and could be easily integrated into them to boost performance. Our extensive evaluation across a range of MIL benchmark datasets demonstrated that the incorporation of the PDL into multiple MIL methods not only elevated their classification performance but also augmented their potential for weakly-supervised feature localizations.Comment: The code is available in https://github.com/ChongQingNoSubway/PD