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Background: Many open-source skin cancer image datasets are the result of clinical trials conducted in countries with lighter skin tones. Due to this tone imbalance, machine learning models derived from these datasets can perform well at detecting skin cancer for lighter skin tones. Any tone bias in these models could introduce fairness concerns and reduce public trust in the artificial intelligence health field. Methods: We examine a subset of images from the International Skin Imaging Collaboration (ISIC) archive that provide tone information. The subset has a significant tone imbalance. These imbalances could explain a model's tone bias. To address this, we train models using the imbalanced dataset and a balanced dataset to compare against. The datasets are used to train a deep convolutional neural network model to classify the images as malignant or benign. We then evaluate the models' disparate impact, based on selection rate, relative to dark or light skin tone. Results: Using the imbalanced dataset, we found that the model is significantly better at detecting malignant images in lighter tone resulting in a disparate impact of 0.577. Using the balanced dataset, we found that the model is also significantly better at detecting malignant images in lighter versus darker tones with a disparate impact of 0.684. Using the imbalanced or balanced dataset to train the model still results in a disparate impact well below the standard threshold of 0.80 which suggests the model is biased with respect to skin tone. Conclusion: The results show that typical skin cancer machine learning models can be tone biased. These results provide evidence that diagnosis or tone imbalance is not the cause of the bias. Other techniques will be necessary to identify and address the bias in these models, an area of future investigation.

We present nuclear magnetic (NMR) and qudrupole (NQR) resonance and magnetization data in the normal state of the topological crystalline superconductor LaNiGa$_2$. We find no evidence of magnetic fluctuations or enhanced paramagnetism. These results suggest that the time-reversal symmetry breaking previously reported in the superconducting state of this material is not driven by strong electron correlations., Comment: 9 pages, 7 figures

We present nuclear magnetic resonance (NMR), neutron diffraction, magnetization, and transport measurements on a single crystal and powder of CeVGe$_3$. This material exhibits heavy fermion behavior at low temperature, accompanied by antiferromagnetic (AFM) order below 5.8 K. We find that the magnetic structure is incommensurate with AFM helical structure, characterized by a magnetic modulated propagation vector of $(0, 0, 0.49)$ with in-plane moments rotating around the $c$-axis. The NMR Knight shift and spin-lattice relaxation rate reveal a coherence temperature $T^*\sim 15$ K, and the presence of significant antiferromagnetic fluctuations reminiscent of the archetypical heavy fermion compound CeRhIn$_5$. We further identify a metamagnetic transition above $H_m\sim 2.5$ T for magnetic fields perpendicular to $c$. We speculate that the magnetic structure in this field-induced phase consists of a superposition with both ferromagnetic and antiferromagnetic components, which is consistent with the NMR spectrum in this region of the phase diagram. Our results thus indicate that CeVGe$_3$ is a hexagonal structure analog to tetragonal CeRhIn$_5$., Comment: 13 pages, 11 figures

Weyl's conformal gravity theory, which is considered as a compelling alternative to general relativity theory, has been claimed to describe the observed flat rotation curve feature of spiral galaxies without the need of invoking dark matter. However, it is important to examine whether the Weyl theory can also explain the relevant gravitational lensing observations correctly without considering any dark matter. In this regard, the gravitational bending angle in static spherically space-time (Mannheim-Kazanas metric) in Weyl theory has been calculated by several authors over the last two decades, but the results are found largely divergent. In this work, we have revisited the problem and obtain the correct and consistent expression of the deflection angle in conformal gravity. Subsequently we perform the gravitational lensing analysis. We compare the prediction of Weyl gravity with the gravitational lensing observations of the rich galaxy clusters Abell 370 and Abell 2390 and is found that Weyl theory cannot describe the stated lensing observations without considering dark matter., Comment: 9 pages

We report the first direct measurement of differential transfer cross sections using a Recoil Mass Spectrometer. Absolute differential $1p$ and $2p$-stripping cross sections at $\theta_\mathrm{c.m.}=180^\circ$ have been determined for the system $^{16}$O+$^{142}$Ce by detecting the heavier target-like ions at the focal plane of the Heavy Ion Reaction Analyzer. Focal plane spectra have been compared with the results of a semi-microscopic Monte-Carlo simulation to unambiguously identify the transfer channels. Transmission efficiency of the target-like ions through the spectrometer has also been estimated using the simulation. The methodology adopted in this work can be applied to other recoil separators. The measured excitation functions for the reactions $^{142}\mathrm{Ce(}^{16}\mathrm{O,}^{15}\mathrm{N)}^{143}\mathrm{Pr}$ and $^{142}\mathrm{Ce(}^{16}\mathrm{O,}^{14}\mathrm{C)}^{144}\mathrm{Nd}$ have been compared with coupled reaction channel calculations. An excellent matching between measurement and theory has been obtained. For $1p$-stripping, major contribution to the cross section has been found to be the transfer of a proton from $^{16}\mathrm{O}$ to the $2d_{\frac{5}{2}}$ excited state of $^{143}\mathrm{Pr}$, leaving behind $^{15}\mathrm{N}$ in the $1p_{\frac{1}{2}}$ ground state. Transfer of a cluster of two protons from $^{16}\mathrm{O}$ to the $2^{+}$ excited state of $^{144}\mathrm{Nd}$, resulting in $^{14}\mathrm{C}$ in the $0^{+}$ ground state, appears to be the most probable cause for $2p$-stripping. Measured transfer probabilities for $1p$ and $2p$ channels have been compared with Time-Dependent Hartree-Fock calculations. Proton stripping channels are found to be more favourable compared to neutron pick-up channels. However, the theory overpredicts measurement hinting at the need for extended approaches with explicit treatment of pairing correlations in the calculations.

Glacier mapping is key to ecological monitoring in the hkh region. Climate change poses a risk to individuals whose livelihoods depend on the health of glacier ecosystems. In this work, we present a machine learning based approach to support ecological monitoring, with a focus on glaciers. Our approach is based on semi-automated mapping from satellite images. We utilize readily available remote sensing data to create a model to identify and outline both clean ice and debris-covered glaciers from satellite imagery. We also release data and develop a web tool that allows experts to visualize and correct model predictions, with the ultimate aim of accelerating the glacier mapping process., Comment: Accepted for a spotlight talk and a poster at the Tackling Climate Change with Machine Learning workshop at NeurIPS 2020