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Showing papers by "San Jose State University published in 2017"


Journal ArticleDOI
TL;DR: It is shown that knee OA long existed at low frequencies, but since the mid-20th century, the disease has doubled in prevalence, contradict the view that the recent surge in knee osteoarthritis occurred simply because people live longer and are more commonly obese.
Abstract: Knee osteoarthritis (OA) is believed to be highly prevalent today because of recent increases in life expectancy and body mass index (BMI), but this assumption has not been tested using long-term historical or evolutionary data. We analyzed long-term trends in knee OA prevalence in the United States using cadaver-derived skeletons of people aged ≥50 y whose BMI at death was documented and who lived during the early industrial era (1800s to early 1900s; n = 1,581) and the modern postindustrial era (late 1900s to early 2000s; n = 819). Knee OA among individuals estimated to be ≥50 y old was also assessed in archeologically derived skeletons of prehistoric hunter-gatherers and early farmers (6000-300 B.P.; n = 176). OA was diagnosed based on the presence of eburnation (polish from bone-on-bone contact). Overall, knee OA prevalence was found to be 16% among the postindustrial sample but only 6% and 8% among the early industrial and prehistoric samples, respectively. After controlling for age, BMI, and other variables, knee OA prevalence was 2.1-fold higher (95% confidence interval, 1.5-3.1) in the postindustrial sample than in the early industrial sample. Our results indicate that increases in longevity and BMI are insufficient to explain the approximate doubling of knee OA prevalence that has occurred in the United States since the mid-20th century. Knee OA is thus more preventable than is commonly assumed, but prevention will require research on additional independent risk factors that either arose or have become amplified in the postindustrial era.

567 citations


Journal ArticleDOI
TL;DR: By establishing basic laws governing the successful formation of an aqueous SEI, the in-depth understanding presented in this work will assist the efforts in tailor-designing better interphases that enable more energetic chemistries operating farther away from equilibria in aqueously media.
Abstract: Solid-electrolyte interphase (SEI) is the key component that enables all advanced electrochemical devices, the best representative of which is Li-ion battery (LIB). It kinetically stabilizes electrolytes at potentials far beyond their thermodynamic stability limits, so that cell reactions could proceed reversibly. Its ad hoc chemistry and formation mechanism has been a topic under intensive investigation since the first commercialization of LIB 25 years ago. Traditionally SEI can only be formed in nonaqueous electrolytes. However, recent efforts successfully transplanted this concept into aqueous media, leading to significant expansion in the electrochemical stability window of aqueous electrolytes from 1.23 V to beyond 4.0 V. This not only made it possible to construct a series of high voltage/energy density aqueous LIBs with unprecedented safety, but also brought high flexibility and even “open configurations” that have been hitherto unavailable for any LIB chemistries. While this new class of aqueous e...

310 citations


Journal ArticleDOI
TL;DR: This research trains Hidden Markov Models (HMMs) on both static and dynamic feature sets and compares the resulting detection rates over a substantial number of malware families, finding a fully dynamic approach generally yields the best detection rates.
Abstract: In this research, we compare malware detection techniques based on static, dynamic, and hybrid analysis. Specifically, we train Hidden Markov Models (HMMs) on both static and dynamic feature sets and compare the resulting detection rates over a substantial number of malware families. We also consider hybrid cases, where dynamic analysis is used in the training phase, with static techniques used in the detection phase, and vice versa. In our experiments, a fully dynamic approach generally yields the best detection rates. We discuss the implications of this research for malware detection based on hybrid techniques.

306 citations


Journal ArticleDOI
TL;DR: In this paper, an artificial neural network is trained to identify changes in the collective magnetic properties of electrons on a lattice and predict trends in the transition when some of the electrons are removed.
Abstract: Machine learning has strong potential as a tool for understanding how to classify phases in condensed matter physics. A new investigation shows that an artificial neural network can be trained to identify changes in the collective magnetic properties of electrons on a lattice and predict trends in the transition when some of the electrons are removed.

300 citations


Journal ArticleDOI
20 Sep 2017-PLOS ONE
TL;DR: An in-depth analysis of the accident reports filed by different manufacturers that are testing autonomous vehicles in California provides important information on autonomous vehicles accidents’ dynamics, related to the most frequent types of collisions and impacts, accident frequencies, and other contributing factors.
Abstract: Autonomous Vehicle technology is quickly expanding its market and has found in Silicon Valley, California, a strong foothold for preliminary testing on public roads. In an effort to promote safety and transparency to consumers, the California Department of Motor Vehicles has mandated that reports of accidents involving autonomous vehicles be drafted and made available to the public. The present work shows an in-depth analysis of the accident reports filed by different manufacturers that are testing autonomous vehicles in California (testing data from September 2014 to March 2017). The data provides important information on autonomous vehicles accidents' dynamics, related to the most frequent types of collisions and impacts, accident frequencies, and other contributing factors. The study also explores important implications related to future testing and validation of semi-autonomous vehicles, tracing the investigation back to current literature as well as to the current regulatory panorama.

248 citations


Journal ArticleDOI
TL;DR: The interconnected roles of dysregulated pH dynamics in cancer initiation, progression and adaptation are highlighted and ion transporter inhibition as an effective therapeutic approach is suggested, either singly or in combination with targeted therapies.
Abstract: Dysregulated pH is a common characteristic of cancer cells, as they have an increased intracellular pH (pHi) and a decreased extracellular pH (pHe) compared with normal cells. Recent work has expanded our knowledge of how dysregulated pH dynamics influences cancer cell behaviors, including proliferation, metastasis, metabolic adaptation and tumorigenesis. Emerging data suggest that the dysregulated pH of cancers enables these specific cell behaviors by altering the structure and function of selective pH-sensitive proteins, termed pH sensors. Recent findings also show that, by blocking pHi increases, cancer cell behaviors can be attenuated. This suggests ion transporter inhibition as an effective therapeutic approach, either singly or in combination with targeted therapies. In this Cell Science at a Glance article and accompanying poster, we highlight the interconnected roles of dysregulated pH dynamics in cancer initiation, progression and adaptation.

235 citations


Journal ArticleDOI
TL;DR: A bibliometric analysis of the publications of Computers & Industrial Engineering between 1976 and 2015 is developed to identify the leading trends of the journal in terms of impact, topics, universities and countries.

216 citations


Journal ArticleDOI
TL;DR: Novel murine LSCC models driven by loss of Trp53 and Keap1, both of which are frequently mutated in human LSCCs are described, and KEAP1/NRF2 mutations could serve as predictive biomarkers for personalization of therapeutic strategies for NSCLCs.
Abstract: Lung squamous cell carcinomas (LSCC) pathogenesis remains incompletely understood and biomarkers predicting treatment response remain lacking. Here we describe novel murine LSCC models driven by loss of Trp53 and Keap1, both of which are frequently mutated in human LSCCs. Homozygous inactivation of Keap1 or Trp53 promoted airway basal stem cell (ABSC) self-renewal, suggesting that mutations in these genes lead to expansion of mutant stem cell clones. Deletion of Trp53 and Keap1 in ABSCs, but not more differentiated tracheal cells, produced tumors recapitulating histological and molecular features of human LSCCs, indicating that they represent the likely cell of origin in this model. Deletion of Keap1 promoted tumor aggressiveness, metastasis, and resistance to oxidative stress and radiotherapy (RT). KEAP1/NRF2 mutation status predicted risk of local recurrence after RT in non-small lung cancer (NSCLC) patients and could be non-invasively identified in circulating tumor DNA. Thus, KEAP1/NRF2 mutations could serve as predictive biomarkers for personalization of therapeutic strategies for NSCLCs.

215 citations


Journal ArticleDOI
01 Jan 2017
TL;DR: Prototyping is interwoven with nearly all product, service, and system development efforts as discussed by the authors and often predetermines a large portion of resource deployment in development and influences design project success.
Abstract: Prototyping is interwoven with nearly all product, service, and systems development efforts. A prototype is a pre-production representation of some aspect of a concept or final design. Prototyping often predetermines a large portion of resource deployment in development and influences design project success. This review surveys literature sources in engineering, management, design science, and architecture. The study is focused around design prototyping for early stage design. Insights are synthesized from critical review of the literature: key objectives of prototyping, critical review of major techniques, relationships between techniques, and a strategy matrix to connect objectives to techniques. The review is supported with exemplar prototypes provided from industrial design efforts. Techniques are roughly categorized into those that improve the outcomes of prototyping directly, and those that enable prototyping through lowering of cost and time. Compact descriptions of each technique provide a foundation to compare the potential benefits and drawbacks of each. The review concludes with a summary of key observations, highlighted opportunities in the research, and a vision of the future of prototyping. This review aims to provide a resource for designers as well as set a trajectory for continuing innovation in the scientific research of design prototyping.

163 citations


Journal ArticleDOI
29 Sep 2017-Science
TL;DR: An experimental study of the two-dimensional Fermi-Hubbard model—a paradigm for strongly correlated fermions on a lattice—in the presence of a Zeeman field and varying doping reveals anisotropic antiferromagnetic correlations, a precursor to long-range canted order.
Abstract: The interplay of strong interactions and magnetic fields gives rise to unusual forms of superconductivity and magnetism in quantum many-body systems. Here, we present an experimental study of the two-dimensional Fermi-Hubbard model—a paradigm for strongly correlated fermions on a lattice—in the presence of a Zeeman field and varying doping. Using site-resolved measurements, we revealed anisotropic antiferromagnetic correlations, a precursor to long-range canted order. We observed nonmonotonic behavior of the local polarization with doping for strong interactions, which we attribute to the evolution from an antiferromagnetic insulator to a metallic phase. Our results pave the way to experimentally mapping the low-temperature phase diagram of the Fermi-Hubbard model as a function of both doping and spin polarization, for which many open questions remain.

140 citations


Journal ArticleDOI
TL;DR: In this paper, an optimal power flow technique of a PV-battery powered fast EV charging station is presented to continuously minimize the operation cost, along with the required constraints and the operating cost function is chosen as a combination of electricity grid prices and the battery degradation cost.
Abstract: The prospective spread of electric vehicles (EV) and plug-in hybrid EV raises the need for fast charging rates. High required charging rates lead to high power demands, which may not be supported by the grid. In this paper, an optimal power flow technique of a PV-battery powered fast EV charging station is presented to continuously minimize the operation cost. The objective is to help the penetration of PV-battery systems into the grid and to support the growing need of fast EV charging. An optimization problem is formulated along with the required constraints and the operating cost function is chosen as a combination of electricity grid prices and the battery degradation cost. In the first stage of the proposed optimization procedure, an offline particle swarm optimization (PSO) is performed as a prediction layer. In the second stage, dynamic programming (DP) is performed as an online reactive management layer. Forecasted system data is utilized in both stages to find the optimal power management solution. In the reactive management layer, the outputs of the PSO are used to limit the available state trajectories used in the DP and, accordingly, improve the system computation time and efficiency. Online error compensation is implemented into the DP and fed back to the prediction layer for necessary prediction adjustments. Simulation and 1 kW prototype experimental results are successfully implemented to validate the system effectiveness and to demonstrate the benefits of using a hybrid grid tied system of PV-battery for fast EVs charging stations.

Journal ArticleDOI
TL;DR: In this paper, a combination of high quality Keck spectroscopy and a new suite of stellar population synthesis models was used to study the radial variation of the initial mass function (IMF) of early-type galaxies.
Abstract: There is good evidence that the centers of massive early-type galaxies have a bottom-heavy stellar initial mass function (IMF) compared to the IMF of the Milky Way. Here we study the radial variation of the IMF within such galaxies, using a combination of high quality Keck spectroscopy and a new suite of stellar population synthesis models that cover a wide range in metallicity. As in the previous studies in this series, the models are fitted directly to the spectra and treat all elemental abundance ratios as free parameters. Using newly obtained spectroscopy for six galaxies, including deep data extending to ~1Re for the galaxies NGC1407, NGC1600, and NGC2695, we find that the IMF varies strongly with galactocentric radius. For all six galaxies the IMF is bottom-heavy in the central regions, with average mass-to-light ratio "mismatch" parameter a~2.5 at R=0. The IMF rapidly becomes more bottom-light with increasing radius, flattening off near the Milky Way value (a~1.1) at R>0.4Re. A consequence is that the luminosity-weighted average IMF depends on the measurement aperture: within R=Re we find =1.3-1.5, consistent with recent lensing and dynamical results from SLACS and ATLAS-3D. Our results are also consistent with several earlier studies that were based on analyses of radial gradients of line indices. The observed IMF gradients support galaxy formation models in which the central regions of massive galaxies had a different formation history than their outer parts. Finally, we make use of the high signal-to-noise central spectra of NGC1407 and NGC2695 to demonstrate how we can disentangle IMF effects and abundance effects.

Journal ArticleDOI
TL;DR: In this article, the authors provide the first direct empirical evidence of the effect of CEO social capital on aggregate corporate risk-taking, and they find a positive association between CEO social networks and aggregate risk taking.

Journal ArticleDOI
TL;DR: A hybrid model based on the Kullback–Leibler divergence and an asymmetric factor are considered to distinguish the rating preference between difference users and improve the reliability of the model output.

Journal ArticleDOI
TL;DR: While organizing efforts by Black Lives Matter and responses to the hate-filled policies and rhetoric of Donald Trump are heightening public discourse of racism, much le... as discussed by the authors, 2017.
Abstract: While organizing efforts by movements such as Black Lives Matter and responses to the hate-filled policies and rhetoric of President Donald Trump are heightening public discourse of racism, much le...

Journal ArticleDOI
TL;DR: In this article, the authors used the Hubble Space Telescope imaging of two ultra diffuse galaxies (UDGs) with measured stellar velocity dispersions in the Coma cluster to identify a striking number of compact objects, tentatively identified as globular clusters.
Abstract: We present Hubble Space Telescope imaging of two ultra diffuse galaxies (UDGs) with measured stellar velocity dispersions in the Coma cluster. The galaxies, Dragonfly 44 and DFX1, have effective radii of 4.7 kpc and 3.5 kpc and velocity dispersions of $47^{+8}_{-6}$ km/s and $30^{+7}_{-7}$ km/s, respectively. Both galaxies are associated with a striking number of compact objects, tentatively identified as globular clusters: $N_{\rm gc}=74\pm 18$ for Dragonfly 44 and $N_{\rm gc}=62\pm 17$ for DFX1. The number of globular clusters is far higher than expected from the luminosities of the galaxies but is consistent with expectations from the empirical relation between dynamical mass and globular cluster count defined by other galaxies. Combining our data for these two objects with previous HST observations of Coma UDGs we find that UDGs have a factor of $6.9^{+1.0}_{-2.4}$ more globular clusters than other galaxies of the same luminosity, in contrast to a recent study of a similar sample by Amorisco et al. (2017), but consistent with earlier results for individual galaxies. The Harris et al. (2017) relation between globular cluster count and dark matter halo mass implies a median halo mass of $M_{\rm halo}\sim 1.5\times 10^{11}\,{\rm M}_{\odot}$ for the sixteen Coma UDGs that have been observed with HST so far, with the largest and brightest having $M_{\rm halo}\sim 5\times 10^{11}\,{\rm M}_{\odot}$.

Journal ArticleDOI
TL;DR: This work analyzed citizen science and satellite data to develop predictive models of bird populations and the availability of wetlands, which were used to determine temporal and spatial gaps in habitat during a vital stage of the annual migration and filled those gaps using a reverse auction marketplace.
Abstract: In an era of unprecedented and rapid global change, dynamic conservation strategies that tailor the delivery of habitat to when and where it is most needed can be critical for the persistence of species, especially those with diverse and dispersed habitat requirements. We demonstrate the effectiveness of such a strategy for migratory waterbirds. We analyzed citizen science and satellite data to develop predictive models of bird populations and the availability of wetlands, which we used to determine temporal and spatial gaps in habitat during a vital stage of the annual migration. We then filled those gaps using a reverse auction marketplace to incent qualifying landowners to create temporary wetlands on their properties. This approach is a cost-effective way of adaptively meeting habitat needs for migratory species, optimizes conservation outcomes relative to investment, and can be applied broadly to other conservation challenges.

Journal ArticleDOI
TL;DR: The first chiral simple organic molecules capable of simultaneously sustaining significant chemical robustness, high fluorescence quantum yields, and circularly polarized luminescence ellipticity levels comparable to those of similar CPL-SOMs are described.
Abstract: The direct generation of efficient, tunable, and switchable circularly polarized laser emission (CPLE) would have far-reaching implications in photonics and material sciences. In this paper, we describe the first chiral simple organic molecules (SOMs) capable of simultaneously sustaining significant chemical robustness, high fluorescence quantum yields, and circularly polarized luminescence (CPL) ellipticity levels (|glum|) comparable to those of similar CPL-SOMs. All these parameters altogether enable efficient laser emission and CPLE with ellipticity levels 2 orders of magnitude stronger than the intrinsic CPL ones.

Journal ArticleDOI
TL;DR: In this paper, the authors develop a typology of global leadership roles that consider context as a critical contingency factor and propose four ideal-typical global leadership role types (incremental, operational, connective, and integrative).
Abstract: While the global leadership literature has grown rapidly over recent years, the context in which global leadership occurs remains ill-defined and under-conceptualized. This lack of contextualization risks equating global leadership roles that are qualitatively very different and prevents sufficient clarity for empirical sampling. To foster more cohesive theoretical and empirical work, we develop a typology of global leadership roles that considers context as a critical contingency factor. Drawing on role and complexity leadership theories, we propose four ideal–typical global leadership roles (incremental, operational, connective, and integrative global leadership) that differ in their (1) task complexity – characterizing the variety and flux within the task context, and (2) relationship complexity – reflecting the boundaries and interdependencies within the relationship context. We further delineate how these contextual demands relate to specific sets of behaviors and actions that allow global leaders to fulfill the requirements of their corresponding ideal–typical global leadership roles. Our article concludes with a discussion of implications the typology presents for global leadership research and practice, contextualization of the leadership construct more broadly, and the field of international business.

Journal ArticleDOI
TL;DR: This review summary of knowledge accumulated during the last two decades on the composition, structure, and function of the C. albicans biofilm matrix will help pave the way to novel strategies to combat C.AlbicansBiofilm infections.
Abstract: A majority of infections caused by Candida albicans-the most frequent fungal pathogen-are associated with biofilm formation. A salient feature of C. albicans biofilms is the presence of the biofilm matrix. This matrix is composed of exopolymeric materials secreted by sessile cells within the biofilm, in which all classes of macromolecules are represented, and provides protection against environmental challenges. In this review, we summarize the knowledge accumulated during the last two decades on the composition, structure, and function of the C. albicans biofilm matrix. Knowledge of the matrix components, its structure, and function will help pave the way to novel strategies to combat C. albicans biofilm infections.

Journal ArticleDOI
TL;DR: The authors explored the extent to which an 18-day history and writing curriculum intervention, taught over the course of one year, helped culturally and academically diverse adolescents achieve important disciplinary literacy learning in history.
Abstract: This study explored the extent to which an 18-day history and writing curriculum intervention, taught over the course of one year, helped culturally and academically diverse adolescents achieve important disciplinary literacy learning in history. Teachers used a cognitive apprenticeship form of instruction for the integration of historical reading and writing strategies and content learning with the goal of improving students' historical argument writing. The intervention had positive and significant results for each writing outcome. After controlling for variables associated with students' incoming abilities, the researchers found moderate to large effects for all participants. Relative to basic readers in the control condition, those participating in the intervention scored higher in historical writing and writing quality and wrote longer essays; these results translate into effect sizes of .45 on basic readers' historical writing, .32 on their overall writing quality, and .60 on the length of their papers. Teachers implemented the reading and writing curriculum intervention with high levels of implementation fidelity, leading the researchers to explore additional factors that contributed to students' success after accounting for teacher effectiveness. The results indicate further benefits dependent on the degree to which students completed the curriculum.

Journal ArticleDOI
TL;DR: In this paper, the authors discuss the nature of authoritarian character, how authoritarian values develop, and how it is measured, and the factors that make it more likely, its consequences for followers and the moderators of its effects.
Abstract: Despite a long history within the field of leadership, the subject of authoritarianism and how it influences leadership and leadership processes has been neglected in recent decades. However, recent global events make it clear that a better understanding of authoritarianism is needed and that leadership researchers would benefit from a renewed interest in studying why followers embrace autocratic leaders. The nature of authoritarian character, how authoritarian values develop, and how it is measured will be discussed. We will also review autocratic leadership, the factors that make it more likely, its consequences for followers, and the moderators of its effects. A future research agenda for the study of authoritarian character and autocratic leadership will be provided.

Journal ArticleDOI
TL;DR: In this paper, supermassive black holes were detected in two Virgo ultracompact dwarf galaxies (UCDs), VUCD3 and M59cO, using adaptive optics assisted data from the Gemini/NIFS instrument.
Abstract: We present the detection of supermassive black holes (BHs) in two Virgo ultracompact dwarf galaxies (UCDs), VUCD3 and M59cO. We use adaptive optics assisted data from the Gemini/NIFS instrument to derive radial velocity dispersion profiles for both objects. Mass models for the two UCDs are created using multi-band Hubble Space Telescope imaging, including the modeling of mild color gradients seen in both objects. We then find a best-fit stellar mass-to-light ratio (M/L) and BH mass by combining the kinematic data and the deprojected stellar mass profile using Jeans Anisotropic Models. Assuming axisymmetric isotropic Jeans models, we detect BHs in both objects with masses of M in VUCD3 and M in M59cO (3σ uncertainties). The BH mass is degenerate with the anisotropy parameter, for the data to be consistent with no BH requires and for VUCD3 and M59cO, respectively. Comparing these values with nuclear star clusters shows that, while it is possible that these UCDs are highly radially anisotropic, it seems unlikely. These detections constitute the second and third UCDs known to host supermassive BHs. They both have a high fraction of their total mass in their BH; ∼13% for VUCD3 and ∼18% for M59cO. They also have low best-fit stellar M/Ls, supporting the proposed scenario that most massive UCDs host high-mass fraction BHs. The properties of the BHs and UCDs are consistent with both objects being the tidally stripped remnants of galaxies.

Journal ArticleDOI
J. Abadie1, B. P. Abbott1, Richard J. Abbott1, T. D. Abbott2  +876 moreInstitutions (88)
TL;DR: In this paper, an all-sky search for periodic gravitational waves in the frequency band 20−475 Hz and with a frequency time derivative in the range of [−1.0,+0.1]×10−8
Abstract: We report on an all-sky search for periodic gravitational waves in the frequency band 20–475 Hz and with a frequency time derivative in the range of [−1.0,+0.1]×10−8 Hz/s. Such a signal could be produced by a nearby spinning and slightly nonaxisymmetric isolated neutron star in our galaxy. This search uses the data from Advanced LIGO’s first observational run, O1. No periodic gravitational wave signals were observed, and upper limits were placed on their strengths. The lowest upper limits on worst-case (linearly polarized) strain amplitude h0 are ∼4×10−25 near 170 Hz. For a circularly polarized source (most favorable orientation), the smallest upper limits obtained are ∼1.5×10−25. These upper limits refer to all sky locations and the entire range of frequency derivative values. For a population-averaged ensemble of sky locations and stellar orientations, the lowest upper limits obtained for the strain amplitude are ∼2.5×10−25.

Journal ArticleDOI
TL;DR: Rheological studies demonstrate that the clots formed from platelets stored at 4°C for 5 days are significantly stiffer (higher elastic modulus) and stronger than those formed from RT‐stored platelets.
Abstract: Summary Currently, platelets for transfusion are stored at room temperature (RT) for 5–7 days with gentle agitation, but this is less than optimal because of loss of function and risk of bacterial contamination. We have previously demonstrated that cold (4°C) storage is an attractive alternative because it preserves platelet metabolic reserves, in vitro responses to agonists of activation, aggregation and physiological inhibitors, as well as adhesion to thrombogenic surfaces better than RT storage. Recently, the US Food and Drug Administration clarified that apheresis platelets stored at 4°C for up to 72 h may be used for treating active haemorrhage. In this work, we tested the hypothesis that cold-stored platelets contribute to generating clots with superior mechanical properties compared to RT-stored platelets. Rheological studies demonstrate that the clots formed from platelets stored at 4°C for 5 days are significantly stiffer (higher elastic modulus) and stronger (higher critical stress) than those formed from RT-stored platelets. Morphological analysis shows that clot fibres from cold-stored platelets were denser, thinner, straighter and with more branch points or crosslinks than those from RT-stored platelets. Our results also show that the enhanced clot strength and packed structure is due to cold-induced plasma factor XIII binding to platelet surfaces, and the consequent increase in crosslinking.

Journal ArticleDOI
TL;DR: In this paper, the adaptive LASSO (least absolute shrinkage and selection operator) was used to select a parsimonious set of default predictor variables. And the adaptive-LASSO selected variables showed superior out-of-sample predictive power over the Altman's Z-score model.

Journal ArticleDOI
TL;DR: Exposure to chronic childhood trauma negatively impacts school achievement when mediated by mental health disorders, and SBHC mental health services have some showed evidence of their ability to reduce, though not eradicate, mental health care disparities.
Abstract: Author(s): Larson, Satu; Chapman, Susan; Spetz, Joanne; Brindis, Claire D | Abstract: BackgroundChildren and adolescents exposed to chronic trauma have a greater risk for mental health disorders and school failure. Children and adolescents of minority racial/ethnic groups and those living in poverty are at greater risk of exposure to trauma and less likely to have access to mental health services. School-based health centers (SBHCs) may be one strategy to decrease health disparities.MethodsEmpirical studies between 2003 and 2013 of US pediatric populations and of US SBHCs were included if research was related to childhood trauma's effects, mental health care disparities, SBHC mental health services, or SBHC impact on academic achievement.ResultsEight studies show a significant risk of mental health disorders and poor academic achievement when exposed to childhood trauma. Seven studies found significant disparities in pediatric mental health care in the US. Nine studies reviewed SBHC mental health service access, utilization, quality, funding, and impact on school achievement.ConclusionExposure to chronic childhood trauma negatively impacts school achievement when mediated by mental health disorders. Disparities are common in pediatric mental health care in the United States. SBHC mental health services have some showed evidence of their ability to reduce, though not eradicate, mental health care disparities.

Journal ArticleDOI
TL;DR: In this paper, the authors used the hyperfine structure of the metastable ammonia inversion lines (J,K) = (1,1) - (6,6) to derive column density, kinematics, opacity and kinetic gas temperature.
Abstract: The Survey of Water and Ammonia in the Galactic Center (SWAG) covers the Central Molecular Zone (CMZ) of the Milky Way at frequencies between 21.2 and 25.4 GHz obtained at the Australia Telescope Compact Array at $\sim 0.9$ pc spatial and $\sim 2.0$ km s$^{-1}$ spectral resolution. In this paper, we present data on the inner $\sim 250$ pc ($1.4^\circ$) between Sgr C and Sgr B2. We focus on the hyperfine structure of the metastable ammonia inversion lines (J,K) = (1,1) - (6,6) to derive column density, kinematics, opacity and kinetic gas temperature. In the CMZ molecular clouds, we find typical line widths of $8-16$ km s$^{-1}$ and extended regions of optically thick ($\tau > 1$) emission. Two components in kinetic temperature are detected at $25-50$ K and $60-100$ K, both being significantly hotter than dust temperatures throughout the CMZ. We discuss the physical state of the CMZ gas as traced by ammonia in the context of the orbital model by Kruijssen et al. (2015) that interprets the observed distribution as a stream of molecular clouds following an open eccentric orbit. This allows us to statistically investigate the time dependencies of gas temperature, column density and line width. We find heating rates between $\sim 50$ and $\sim 100$ K Myr$^{-1}$ along the stream orbit. No strong signs of time dependence are found for column density or line width. These quantities are likely dominated by cloud-to-cloud variations. Our results qualitatively match the predictions of the current model of tidal triggering of cloud collapse, orbital kinematics and the observation of an evolutionary sequence of increasing star formation activity with orbital phase.

Journal ArticleDOI
Melinda T. Owens1, Shannon B. Seidel2, Mike Wong1, Travis E. Bejines2, Susanne Lietz1, Joseph R. Perez2, Shangheng Sit1, Zahur-Saleh Subedar1, Gigi N. Acker3, Gigi N. Acker4, Susan F. Akana5, Brad Balukjian6, Hilary P Benton1, Hilary P Benton7, J R Blair1, Segal M. Boaz8, Katharyn E. Boyer1, Jason B. Bram3, Laura W. Burrus1, Dana T. Byrd1, Natalia Caporale9, Edward J. Carpenter1, Yee-Hung M Chan1, Lily Chen1, Amy Chovnick8, Diana S Chu1, Bryan K. Clarkson10, Sara E. Cooper7, Catherine Creech11, Karen D. Crow1, José R. de la Torre1, Wilfred F. Denetclaw1, Kathleen E. Duncan7, Amy S. Edwards7, Karen L. Erickson7, Megumi Fuse1, Joseph J. Gorga10, Brinda Govindan1, L. Jeanette Green12, Paul Z. Hankamp13, Holly E Harris1, Zheng-Hui He1, Stephen B Ingalls1, Peter Ingmire1, J. Rebecca Jacobs7, Mark Kamakea14, Rhea R. Kimpo15, Rhea R. Kimpo1, Jonathan D. Knight1, Sara K. Krause16, Lori E. Krueger17, Lori E. Krueger18, Terrye L Light1, Lance Lund1, Leticia Márquez-Magaña1, Briana K. McCarthy19, Linda J. McPheron20, Vanessa C Miller-Sims1, Christopher A. Moffatt1, Pamela C. Muick17, Pamela C. Muick21, Paul H. Nagami22, Paul H. Nagami6, Paul H. Nagami1, Gloria Nusse1, Kristine M. Okimura1, Sally G. Pasion1, Robert Patterson1, Pleuni S. Pennings1, Blake Riggs1, Joseph M Romeo1, Scott William Roy1, Tatiane Russo-Tait23, Lisa M. Schultheis7, Lakshmikanta Sengupta13, Rachel Small1, Greg S. Spicer1, Jonathon H. Stillman1, Andrea Swei1, Jennifer M. Wade24, Steven B. Waters19, Steven L. Weinstein1, Julia K. Willsie10, Diana W. Wright4, Colin D Harrison25, Loretta A Kelley, Gloriana Trujillo26, Carmen R. Domingo1, Jeffrey N. Schinske3, Jeffrey N. Schinske7, Kimberly D. Tanner1 
TL;DR: The development and application of the machine-learning–derived algorithm Decibel Analysis for Research in Teaching (DART), which can analyze thousands of hours of STEM course audio recordings quickly, with minimal costs, and without need for human observers is described.
Abstract: Active-learning pedagogies have been repeatedly demonstrated to produce superior learning gains with large effect sizes compared with lecture-based pedagogies. Shifting large numbers of college science, technology, engineering, and mathematics (STEM) faculty to include any active learning in their teaching may retain and more effectively educate far more students than having a few faculty completely transform their teaching, but the extent to which STEM faculty are changing their teaching methods is unclear. Here, we describe the development and application of the machine-learning-derived algorithm Decibel Analysis for Research in Teaching (DART), which can analyze thousands of hours of STEM course audio recordings quickly, with minimal costs, and without need for human observers. DART analyzes the volume and variance of classroom recordings to predict the quantity of time spent on single voice (e.g., lecture), multiple voice (e.g., pair discussion), and no voice (e.g., clicker question thinking) activities. Applying DART to 1,486 recordings of class sessions from 67 courses, a total of 1,720 h of audio, revealed varied patterns of lecture (single voice) and nonlecture activity (multiple and no voice) use. We also found that there was significantly more use of multiple and no voice strategies in courses for STEM majors compared with courses for non-STEM majors, indicating that DART can be used to compare teaching strategies in different types of courses. Therefore, DART has the potential to systematically inventory the presence of active learning with ∼90% accuracy across thousands of courses in diverse settings with minimal effort.

Journal ArticleDOI
TL;DR: This article examined the effect of managerial social capital on the firm's cost of equity capital and found that social ties alleviate information asymmetry and agency problems, which in turn leads to a decrease in the costs of equity.
Abstract: We examine the effect of managerial social capital on the firm's cost of equity capital. We argue that social ties alleviate information asymmetry and agency problems, which in turn leads to a decrease in the cost of equity. Using a large panel of companies from 52 countries over the period 1999–2012, we document that social capital inversely affects the cost of equity. Our evidence suggests that the association between social capital and the cost of equity capital is stronger in underdeveloped financial markets and those characterized by weak legal protection. The marginal effect of social capital is also stronger for constrained firms with profitable investment opportunities. Our results are robust to alternative model specifications and tests for endogeneity.