Harnack's inequality for a class of non-divergent equations in the Heisenberg group

We prove an invariant Harnack's inequality for operators in non-divergence form structured on Heisenberg vector fields when the coefficient matrix is uniformly positive definite, continuous, and symplectic. The method consists in constructing appropriate barriers to obtain pointwise-to-measure estimates for supersolutions in small balls, and then invoking the axiomatic approach from [DGL08] to obtain Harnack's inequality

Attraction, selection, and attrition in online health communities: Initial conversations and their association with subsequent activity levels.

BACKGROUND:The effectiveness of online health communities (OHCs) for improving outcomes for health care consumers, health professionals, and health services has already been well investigated. However, research on determinants of OHC users' activity levels, what is associated with attrition or attraction to these communities, and the impacts of initial posts is limited. OBJECTIVES:We sought to explore topic exchanges in OHCs and determine how users' initial posts and community reactions to them are associated with their subsequent activity levels. We also aimed to extend the theory of Attraction-Selection-Attrition for Online Communities (OCASA) to this area. METHODS:We examined exchanges in a major Australian OHC for cancer patients, analyzing about 2500 messages posted over 2009-18. We developed a novel annotation scheme to examine new members' initial posts and the community's reactions to them. RESULTS:The annotation scheme includes five themes: informational support provision, emotional support provision, requests for help, self-reflection & disclosures, and conversational cues. Initial conversations were associated with future activity levels in terms of active posting versus non-active engagement in the community. We found that most OHC members disclosed personal reflections to bond with the community, and many actively posted to the community solely to provide informational and emotional support to others. CONCLUSION:Our work extends OCASA theory to bond-based contexts, presents a new annotation scheme for OHC support topics, and makes an important contribution to knowledge about the relationship between users' activity levels and their initial posts. The findings help managers and owners understand how members use OHCs and how to encourage active participation. They also suggest how to attract new members and minimize attrition among existing members

Automated Analysis of Mixed Sample Raman Spectra Using Feedforward Neural Networks and One-Vs-All Decomposition

Interest in use of Raman spectrometers in many fields of analytical science has increased due to ability to nondestructively provide information about molecular structures and component materials of a mixed sample. Advancements in Raman spectrometer hardware has allowed for compact instruments to have deployment capabilities directly on interplanetary missions, flexible usage conditions requiring no sample collection/preparation, and no need for daylight radiation shielding. As the amount of science which can be collected from a Raman spectrometer in a given amount of time increases, a bottleneck will be created in data analysis which leaves a need for a faster method of spectral data classification. In this study, a framework to allow for fast automated analysis of mixed sample Raman spectral data is proposed and an implementation of this framework is tested. Analysis of mixed sample Raman spectra was achieved by implementing a model which decomposes an N-class multilabel problem into “N” single class detection problems. The model (consisting of multiple neural networks) was trained with pure sample data and was tasked with analyzing both real and theoretical mixed sample Raman data. Performance of the model is judged by its ability to detect component materials in real mixed sample data at the same level that it is able to in ideal mixed sample data (consisting of linear combinations of training data). The model’s structure, training and testing methodologies, and results will be presented.https://digitalcommons.odu.edu/engineering_batten/1002/thumbnail.jp

The Dark Side of Using Online Social Networks: A Review of Individuals' Negative Experiences

Research on online social networks (OSNs) has focused overwhelmingly on their benefits and potential, with their negative effects overlooked. This study builds on the limited existing work on the so-called ‘dark side’ of using OSNs. The authors conducted a systematic review of selected databases and identified 46 negative effects of using OSNs from the users’ perspective, which is a rich spectrum of users’ negative experiences. This article then proposed nomenclature and taxonomy for the dark side of using OSNs by grouping these negative effects into six themes: cost of social exchange, cyberbullying, low performance, annoying content, privacy concerns and security threats. This study then conducted structured interviews with experts to confirm the sense-making and validity of the proposed taxonomy. This study discusses the confirmed taxonomy and outlines directions for future research.</jats:p

Calculations of the Temperature and Alloy Composition Effects on the Optical Properties of Alx Ga1-x Asy Sb1-y and Gax In1-x Asy Sb1-y in the Spectral Range 0.5-6 eV

A detailed analysis is presented on the temperature and alloy composition dependence of the optical properties of III-V alloys Alx Ga1-x Asy Sb1-y and Gax In1-x Asy Sb1-y in the energy range 0.5-6 eV. Expressions for the complex dielectric function are based on a semiempirical phenomenological model, which takes under consideration indirect and direct transitions below and above the fundamental absorption edge. Dielectric function and absorption coefficient calculations are in satisfactory agreement with available experimental data. Other dielectric related optical data, such as the refractive index, extinction, and reflection coefficients, can also be obtained from the model. © 2007 American Institute of Physics. (DOI: 10.1063/1.2751406

Predicting knee osteoarthritis severity: comparative modeling based on patient's data and plain X-ray images

Knee osteoarthritis (KOA) is a disease that impairs knee function and causes pain. A radiologist reviews knee X-ray images and grades the severity level of the impairments according to the Kellgren and Lawrence grading scheme; a five-point ordinal scale (0-4). In this study, we used Elastic Net (EN) and Random Forests (RF) to build predictive models using patient assessment data (i.e. signs and symptoms of both knees and medication use) and a convolution neural network (CNN) trained using X-ray images only. Linear mixed effect models (LMM) were used to model the within subject correlation between the two knees. The root mean squared error for the CNN, EN, and RF models was 0.77, 0.97 and 0.94 respectively. The LMM shows similar overall prediction accuracy as the EN regression but correctly accounted for the hierarchical structure of the data resulting in more reliable inference. Useful explanatory variables were identified that could be used for patient monitoring before X-ray imaging. Our analyses suggest that the models trained for predicting the KOA severity levels achieve comparable results when modeling X-ray images and patient data. The subjectivity in the KL grade is still a primary concern

Far-Infrared Blocked Impurity Band Detector Development

DRS Sensors & Targeting Systems, supported by detector materials supplier Lawrence Semiconductor Research Laboratory, is developing far-infrared detectors jointly with NASA Langley under the Far-IR Detector Technology Advancement Partnership (FIDTAP). The detectors are intended for spectral characterization of the Earth's energy budget from space. During the first year of this effort we have designed, fabricated, and evaluated pilot Blocked Impurity Band (BIB) detectors in both silicon and germanium, utilizing pre-existing customized detector materials and photolithographic masks. A second-year effort has prepared improved silicon materials, fabricated custom photolithographic masks for detector process, and begun detector processing. We report the characterization results from the pilot detectors and other progress

Revisiting the reactivity of Ru3(CO)12 with PhC≡CPh (diphenylacetylene)-new findings of a thermic effect towards higher nuclearity

177-184In this paper, we report tri- and tetranuclear ruthenium carbonyl compounds containing PhC≡CPh ligand showing μ3-η2, μ3-η4, μ4-η2 coordination modes. A one-pot reaction between [Ru3(CO)12] and PhC≡CPh in THF (tetrahydrofuran) at 66 °C has given the new trinuclear compound [Ru3(CO)6(μ-CO)2(μ3-η4-C4Ph4)] (2) in 30% yield together with the previously reported [Ru3(CO)8(μ3-η2-C2Ph2)2] (1) in 25% yield. Compound 1 converts to 2 under refluxing condition in THF. A similar reaction involving [Ru3(CO)12] with PhC≡CPh in refluxing benzene (80 °C) afforded previously reported closo-tetraruthenium compounds [Ru4(CO)12(μ4-η2-C2Ph2)] (3) and [Ru4(CO)10(μ-CO)(μ4-η2-C2Ph2)2] (4) in 25 and 16% yields, respectively, along with 2 in 20% yield. Compounds 1, 2 and 4 have been characterized by single-crystal X-ray diffraction analysis in addition to IR and 1H NMR spectroscopic methods