Learning Using Concave and Convex Kernels: Applications in Predicting Quality of Sleep and Level of Fatigue in Fibromyalgia.

Fibromyalgia is a medical condition characterized by widespread muscle pain and tenderness and is often accompanied by fatigue and alteration in sleep, mood, and memory. Poor sleep quality and fatigue, as prominent characteristics of fibromyalgia, have a direct impact on patient behavior and quality of life. As such, the detection of extreme cases of sleep quality and fatigue level is a prerequisite for any intervention that can improve sleep quality and reduce fatigue level for people with fibromyalgia and enhance their daytime functionality. In this study, we propose a new supervised machine learning method called Learning Using Concave and Convex Kernels (LUCCK). This method employs similarity functions whose convexity or concavity can be configured so as to determine a model for each feature separately, and then uses this information to reweight the importance of each feature proportionally during classification. The data used for this study was collected from patients with fibromyalgia and consisted of blood volume pulse (BVP), 3-axis accelerometer, temperature, and electrodermal activity (EDA), recorded by an Empatica E4 wristband over the courses of several days, as well as a self-reported survey. Experiments on this dataset demonstrate that the proposed machine learning method outperforms conventional machine learning approaches in detecting extreme cases of poor sleep and fatigue in people with fibromyalgia.

Oxidative Corrosion of the UO2 (001) Surface by Nonclassical Diffusion.

Uranium oxide is central to every stage of the nuclear fuel cycle, from mining through fuel fabrication and use, to waste disposal and environmental cleanup. Its chemical and mechanical stability are intricately linked to the concentration of interstitial O atoms within the structure and the oxidation state of U. We have previously shown that, during corrosion of the UO2 (111) surface under either 1 atm of O2 gas or oxygenated water at room temperature, oxygen interstitials diffuse into the substrate to form a superlattice with three-layer periodicity. In the current study, we present results from surface X-ray scattering that reveal the structure of the oxygen diffusion profile beneath the (001) surface. The first few layers below the surface oscillate strongly in their surface-normal lattice parameters, suggesting preferential interstitial occupation of every other layer below the surface, which is geometrically consistent with the interstitial network that forms below the oxidized (111) surface. Deeper layers are heavily contracted and indicate that the oxidation front penetrates ∼52 Šbelow the (001) surface after 21 days of dry O2 gas exposure at ambient pressure and temperature. X-ray photoelectron spectroscopy indicates U is present as U(IV), U(V), and U(VI).

Windowed persistent homology: A topological signal processing algorithm applied to clinical obesity data.

Overweight and obesity are highly prevalent in the population of the United States, affecting roughly 2/3 of Americans. These diseases, along with their associated conditions, are a major burden on the healthcare industry in terms of both dollars spent and effort expended. Volitional weight loss is attempted by many, but weight regain is common. The ability to predict which patients will lose weight and successfully maintain the loss versus those prone to regain weight would help ease this burden by allowing clinicians the ability to skip treatments likely to be ineffective. In this paper we introduce a new windowed approach to the persistent homology signal processing algorithm that, when paired with a modified, semimetric version of the Hausdorff distance, can differentiate the two groups where other commonly used methods fail. The novel approach is tested on accelerometer data gathered from an ongoing study at the University of Michigan. While most standard approaches to signal processing show no difference between the two groups, windowed persistent homology and the modified Hausdorff semimetric show a clear separation. This has significant implications for clinical decision making and patient care.

UO(2) Oxidative Corrosion by Nonclassical Diffusion.

Using x-ray scattering, spectroscopy, and density-functional theory, we determine the structure of the oxidation front when a UO(2) (111) surface is exposed to oxygen at ambient conditions. In contrast to classical diffusion and previously reported bulk UO(2+x) structures, we find oxygen interstitials order into a nanoscale superlattice with three-layer periodicity and uranium in three oxidation states: IV, V, and VI. This oscillatory diffusion profile is driven by the nature of the electron transfer process, and has implications for understanding the initial stages of oxidative corrosion in materials at the atomistic level.

The effect of creatine on treadmill running with high-intensity intervals.

To determine whether creatine monohydrate supplementation would improve performance during a submaximal treadmill run interspersed with high-intensity intervals, 15 college soccer players (8 women, 7 men) received either creatine or a maltodextrin placebo at 0.3 g.kg body mass per day for 6 days. The speed of the treadmill was constant at 160.8 m.min, and every 2 minutes the grade was elevated to 15%. Each hill segment was 1 minute long. At the end of the 20-minute protocol, the treadmill was again elevated to 15% and held there until volitional exhaustion occurred. There was a significant treatment effect of creatine supplementation on body mass (p < 0.05) in the men; however, no significant differences were observed in the women (p > 0.05). There were no treatment effects (p > 0.05) on time to exhaustion, ratings of perceived exertion, or blood lactate concentration. There was a tendency for blood lactate levels to be lower after short-term creatine supplementation in the women, but this was not statistically significant. Based on these results, it appears that creatine supplementation does not improve performance in submaximal running interspersed with high-intensity intervals.