Attitudes in Physics Education: An Alternative Approach to Teaching Physics to Non-Science College Students

In this article, we present an alternative way of teaching conceptual physics for non-science majors by depicting the role of physics in today\u27s technology. The goal of this approach is to increase in the minds of non-science students the acceptance of physics as a useful component in general education, and as a major tool in comprehending the present-day technological world experienced by students outside the classroom

Loyalty in Online Communities

Loyalty is an essential component of multi-community engagement. When users have the choice to engage with a variety of different communities, they often become loyal to just one, focusing on that community at the expense of others. However, it is unclear how loyalty is manifested in user behavior, or whether loyalty is encouraged by certain community characteristics. In this paper we operationalize loyalty as a user-community relation: users loyal to a community consistently prefer it over all others; loyal communities retain their loyal users over time. By exploring this relation using a large dataset of discussion communities from Reddit, we reveal that loyalty is manifested in remarkably consistent behaviors across a wide spectrum of communities. Loyal users employ language that signals collective identity and engage with more esoteric, less popular content, indicating they may play a curational role in surfacing new material. Loyal communities have denser user-user interaction networks and lower rates of triadic closure, suggesting that community-level loyalty is associated with more cohesive interactions and less fragmentation into subgroups. We exploit these general patterns to predict future rates of loyalty. Our results show that a user's propensity to become loyal is apparent from their first interactions with a community, suggesting that some users are intrinsically loyal from the very beginning.Comment: Extended version of a paper appearing in the Proceedings of ICWSM 2017 (with the same title); please cite the official ICWSM versio

Precision medicine for suicidality: from universality to subtypes and personalization

Suicide remains a clear, present and increasing public health problem, despite being a potentially preventable tragedy. Its incidence is particularly high in people with overt or un(der)diagnosed psychiatric disorders. Objective and precise identification of individuals at risk, ways of monitoring response to treatments and novel preventive therapeutics need to be discovered, employed and widely deployed. We sought to investigate whether blood gene expression biomarkers for suicide (that is, a ‘liquid biopsy’ approach) can be identified that are more universal in nature, working across psychiatric diagnoses and genders, using larger cohorts than in previous studies. Such markers may reflect and/or be a proxy for the core biology of suicide. We were successful in this endeavor, using a comprehensive stepwise approach, leading to a wealth of findings. Steps 1, 2 and 3 were discovery, prioritization and validation for tracking suicidality, resulting in a Top Dozen list of candidate biomarkers comprising the top biomarkers from each step, as well as a larger list of 148 candidate biomarkers that survived Bonferroni correction in the validation step. Step 4 was testing the Top Dozen list and Bonferroni biomarker list for predictive ability for suicidal ideation (SI) and for future hospitalizations for suicidality in independent cohorts, leading to the identification of completely novel predictive biomarkers (such as CLN5 and AK2), as well as reinforcement of ours and others previous findings in the field (such as SLC4A4 and SKA2). Additionally, we examined whether subtypes of suicidality can be identified based on mental state at the time of high SI and identified four potential subtypes: high anxiety, low mood, combined and non-affective (psychotic). Such subtypes may delineate groups of individuals that are more homogenous in terms of suicidality biology and behavior. We also studied a more personalized approach, by psychiatric diagnosis and gender, with a focus on bipolar males, the highest risk group. Such a personalized approach may be more sensitive to gender differences and to the impact of psychiatric co-morbidities and medications. We compared testing the universal biomarkers in everybody versus testing by subtypes versus personalized by gender and diagnosis, and show that the subtype and personalized approaches permit enhanced precision of predictions for different universal biomarkers. In particular, LHFP appears to be a strong predictor for suicidality in males with depression. We also directly examined whether biomarkers discovered using male bipolars only are better predictors in a male bipolar independent cohort than universal biomarkers and show evidence for a possible advantage of personalization. We identified completely novel biomarkers (such as SPTBN1 and C7orf73), and reinforced previously known biomarkers (such as PTEN and SAT1). For diagnostic ability testing purposes, we also examined as predictors phenotypic measures as apps (for suicide risk (CFI-S, Convergent Functional Information for Suicidality) and for anxiety and mood (SASS, Simplified Affective State Scale)) by themselves, as well as in combination with the top biomarkers (the combination being our a priori primary endpoint), to provide context and enhance precision of predictions. We obtained area under the curves of 90% for SI and 77% for future hospitalizations in independent cohorts. Step 5 was to look for mechanistic understanding, starting with examining evidence for the Top Dozen and Bonferroni biomarkers for involvement in other psychiatric and non-psychiatric disorders, as a mechanism for biological predisposition and vulnerability. The biomarkers we identified also provide a window towards understanding the biology of suicide, implicating biological pathways related to neurogenesis, programmed cell death and insulin signaling from the universal biomarkers, as well as mTOR signaling from the male bipolar biomarkers. In particular, HTR2A increase coupled with ARRB1 and GSK3B decreases in expression in suicidality may provide a synergistic mechanistical corrective target, as do SLC4A4 increase coupled with AHCYL1 and AHCYL2 decrease. Step 6 was to move beyond diagnostics and mechanistical risk assessment, towards providing a foundation for personalized therapeutics. Items scored positive in the CFI-S and subtypes identified by SASS in different individuals provide targets for personalized (psycho)therapy. Some individual biomarkers are targets of existing drugs used to treat mood disorders and suicidality (lithium, clozapine and omega-3 fatty acids), providing a means toward pharmacogenomics stratification of patients and monitoring of response to treatment. Such biomarkers merit evaluation in clinical trials. Bioinformatics drug repurposing analyses with the gene expression biosignatures of the Top Dozen and Bonferroni-validated universal biomarkers identified novel potential therapeutics for suicidality, such as ebselen (a lithium mimetic), piracetam (a nootropic), chlorogenic acid (a polyphenol) and metformin (an antidiabetic and possible longevity promoting drug). Finally, based on the totality of our data and of the evidence in the field to date, a convergent functional evidence score prioritizing biomarkers that have all around evidence (track suicidality, predict it, are reflective of biological predisposition and are potential drug targets) brought to the fore APOE and IL6 from among the universal biomarkers, suggesting an inflammatory/accelerated aging component that may be a targetable common denominator

Structural results on convexity relative to cost functions

Mass transportation problems appear in various areas of mathematics, their solutions involving cost convex potentials. Fenchel duality also represents an important concept for a wide variety of optimization problems, both from the theoretical and the computational viewpoints. We drew a parallel to the classical theory of convex functions by investigating the cost convexity and its connections with the usual convexity. We give a generalization of Jensen's inequality for cost convex functions.Comment: 10 page

Fly, Wake-up, Find: UAV-based Energy-efficient Localization for Distributed Sensor Nodes

A challenging application scenario in the field of industrial Unmanned Aerial Vehicles (UAVs) is the capability of a robot to find and query smart sensor nodes deployed at arbitrary locations in the mission area. This work explores the combination of different communication technologies, namely, Ultra-Wideband (UWB) and Wake-Up Radio (WUR), with a UAV that acts as a "ubiquitous local-host"of a Wireless Sensor Network (WSN). First, the UAV performs the localization of the sensor node via multiple UWB range measurements, and then it flies in its proximity to perform energy-efficient data acquisition. We propose an energy-efficient and accurate localization algorithm - based on multi-lateration - that is computationally inexpensive and robust to in-field noise. Aiming at minimizing the sensor node energy consumption, we also present a communication protocol that leverages WUR technology to minimize ON-time of the power-hungry UWB transceiver on the sensors. In-field experimental evaluation demonstrates that our approach achieves a sub-meter localization precision of the sensor nodes - i.e., down to 0.6 m - using only three range measurements, and runs in 4 ms on a low power microcontroller (ARM Cortex-M4F). Due to the presence of the WUR and the proposed lightweight algorithm, the entire localization-acquisition cycle requires only 31 mJ on the sensor node. The approach is suitable for several emerging Industrial Internet of Things application scenarios where a mobile vehicle needs to estimate the location of static objects without any precise knowledge of their position

Moments of the Proton F2 Structure Function at Low Q2

The Q^2 dependence of inclusive electron-proton scattering F_2 structure function data in both the nucleon resonance region and the deep inelastic region, at momentum transfers below 5 (GeV/c)^2, is investigated. Moments of F_2 are constructed, down to momentum transfers of Q^2 ~ 0.1 (GeV/c)^2. The second moment is only slowly varying with Q^2 down to Q^2 ~ 1 (GeV/c)^2, which is a reflection of duality. Below Q^2 of 1 (GeV/c)^2, the Q^2 dependence of the moments is predominantly governed by the elastic contribution, whereas the inelastic channels still seem governed by local duality.Comment: 11 page paper, 1 LaTeX file, 10 postscript figure file

On shock waves and the role of hyperthermal chemistry in the early diffusion of overdense meteor trains

Studies of meteor trails have until now been limited to relatively simple models, with the trail often being treated as a conducting cylinder, and the head (if considered at all) treated as a ball of ionized gas. In this article, we bring the experience gleaned from other fields to the domain of meteor studies, and adapt this prior knowledge to give a much clearer view of the microscale physics and chemistry involved in meteor-trail formation, with particular emphasis on the first 100 or so milliseconds of the trail formation. We discuss and examine the combined physicochemical effects of meteor-generated and ablationally amplified cylindrical shock waves that appear in the ambient atmosphere immediately surrounding the meteor train, as well as the associated hyperthermal chemistry on the boundaries of the high temperature post-adiabatically expanding meteor train. We demonstrate that the cylindrical shock waves produced by overdense meteors are sufficiently strong to dissociate molecules in the ambient atmosphere when it is heated to temperatures in the vicinity of 6000 K, which substantially alters the considerations of the chemical processes in and around the meteor train. We demonstrate that some ambient O-2, along with O-2 that comes from the shock dissociation of O-3, survives the passage of the cylindrical shock wave, and these constituents react thermally with meteor metal ions, thereby subsequently removing electrons from the overdense meteor train boundary through fast, temperature-independent, dissociative recombination governed by the second Damkohler number. Possible implications for trail diffusion and lifetimes are discussed.Peer reviewe

Perturbative QCD Analysis of Local Duality in a fixed W^2 Framework

We study the global Q^2 dependence of large x, F_2 nucleon structure function data, with the aim of providing a perturbative-QCD based, quantitative analysis of parton-hadron duality. As opposed to previous analyses at fixed x, we use a framework in fixed W^2. We uncover a breakdown of the twist-4 approximation with a renormalon type improvement at O(1/Q^4) which, by affecting the initial evolution of parton distributions, will have consequences for pQCD analyses also at large x and very large Q^2.Comment: RevTex4, 8 pages, 3 figure