Placing the Displaced: Translating the North Korean Characters in Sister Mok-rahn for an American Audience

No two languages are more different from each other than American English and Korean spoken in the Democratic People’s Republic of Korea (North Korea). It goes the same for their speakers. Average theatergoers in New York in 2017 share little with the average North Koreans or North Korean refugees scattered around the world. So how should a translator present North Korean characters for an American audience? This paper discusses dramaturgical issues surrounding translating the North Korean characters in "Sister Mok-rahn" for an American audience

A power study of bivariate LOD score analysis of a complex trait and fear/discomfort with strangers

Complex diseases are often reported along with disease-related traits (DRT). Sometimes investigators consider both disease and DRT phenotypes separately and sometimes they consider individuals as affected if they have either the disease or the DRT, or both. We propose instead to consider the joint distribution of the disease and the DRT and do a linkage analysis assuming a pleiotropic model. We evaluated our results through analysis of the simulated datasets provided by Genetic Analysis Workshop 14. We first conducted univariate linkage analysis of the simulated disease, Kofendrerd Personality Disorder and one of its simulated associated traits, phenotype b (fear/discomfort with strangers). Subsequently, we considered the bivariate phenotype, which combined the information on Kofendrerd Personality Disorder and fear/discomfort with strangers. We developed a program to perform bivariate linkage analysis using an extension to the Elston-Stewart peeling method of likelihood calculation. Using this program we considered the microsatellites within 30 cM of the gene pleiotropic for this simulated disease and DRT. Based on 100 simulations of 300 families we observed excellent power to detect linkage within 10 cM of the disease locus using the DRT and the bivariate trait

Continuous cultivation of mixed-culture microalgae using anaerobic digestion effluent in photobioreactors with different strategies for adjusting nitrogen loading rate

This study examined continuous mixed-culture microalgae cultivation for nutrient removal from anaerobic digestion (AD) effluents in photobioreactors, while altering the NH4+-N loading rate (NLR) by adjusting either the hydraulic retention time (HRT) (reactor set RH) or the influent NH4+-N concentration (reactor set RS). Both RH and RS demonstrated efficient nutrient removal and microalgae cultivation at NLRs of 4-10 mg NH4+-N/L & BULL;d, reaching peak performance at 10 mg NH4+-N/L & BULL;d. Within this range, RH obtained greater biomass yield and productivity, while RS maintained higher microalgal concentrations. The cultivated biomasses obtained from RH and RS had good settleability and suitable fatty acid compositions as a biodiesel feedstock, although their organic composition varied considerably with NLR and HRT. Parachlorella overwhelmingly dominated the reactors' microalgal communities throughout the experiment, co-existing with various microalgae-associated bacteria. Changes in NLR significantly influenced the bacterial community structures, underscoring its critical role in determining reactor performance and microalgal-bacterial community behavior

Photoacoustic imaging of tumor targeting with biotin conjugated nanostructured phthalocyanine assemblies

Visualizing biological markers and delivering bioactive agents to living organisms are important to biological research. In recent decades, photoacoustic imaging (PAI) has been significantly improved in the area of molecular imaging, which provides high-resolution volume imaging with high optical absorption contrast. To demonstrate the ability of nanoprobes to target tumors using PAI, we synthesize convertible nanostructured agents with strong photothermal and photoacoustic properties and linked the nanoprobe with biotin to target tumors in small animal model. Interestingly, these nanoprobes allow partial to disassemble in the presence of targeted proteins that switchable photoactivity, thus the nanoprobes provides a fluorescent-cancer imaging with high signal-to-background ratios. The proposed nanoprobe produce a much stronger PA signal compared to the same concentration of methylene blue (MB), which is widely used in clinical study and contrast agent for PAI. The biotin conjugated nanoprobe has high selectivity for biotin receptor positive cancer cells such as A549 (human lung cancer). Then we subsequently examined the PA properties of the nanoprobe that are inherently suitable for in vivo PAI. After injecting of the nanoprobe via intravenous method, we observed the mice's whole body by PA imaging and acquired the PA signal near the cancer. The PA signal increased linearly with time after injection and the fluorescence signal near the cancer was confirmed by fluorescence imaging. The ability to target a specific cancer of the nanoprobe was well verified by PA imaging. This study provides valuable perspective on the advancement of clinical translations and in the design of tumor-targeting phototheranostic agents that could act as new nanomedicines1

Inverse Identification of a Constitutive Model for High-Speed Forming Simulation: An Application to Electromagnetic Metal Forming

Forming simulation requires a constitutive model whose parameters are typically determined with tensile tests assumed static. However, this conventional approach is impractical for high-speed forming simulation characterized by high strain rates inducing transient effects. To identify constitutive parameters in relation to high-speed forming simulation, we formulated the problem of constitutive modeling as inverse parameter estimation addressed by regularized nonlinear least squares. Regarding the proposed inverse constitutive modeling, we adopted the L-curve method for proper regularization and model order reduction for rapid simulation. For demonstration, we corroborated the proposed strategy by identifying the modified Johnson–Cook model in the context of a free bulge test with electromagnetic metal forming simulation. The L-curve method allowed us to systematically choose a regularization parameter, and model order reduction brought enormous computational savings. After identifying constitutive parameters, we successfully verified and validated the reduced and original simulation models, respectively, with a manufactured workpiece. In addition, we validated the numerically identified constitutive model with a dynamic material test using a split Hopkinson pressure bar. Overall, we showed that inverse constitutive modeling for high-speed forming simulation can be effectively tackled by regularized nonlinear least squares with the help of an L-curve and a reduced-order model

Circumplex Models with Multivariate Time Series: An Idiographic Approach

The circumplex model posits a circular representation of affect and some personality traits. There is an increasing need to examine the viability of the circumplex model with multivariate time series data collected on the same individuals due to the development of new data collection methods such as smartphone applications and wearable sensors. Estimating the circumplex model with time series data is more complex than with cross-sectional data because scores at nearby time points tend to be correlated. We adapt Browne’s circumplex model to accommodate time series data. We illustrate the proposed method with an empirical data set of daily affect ratings of an individual over 70 days. We conducted a simulation study to explore the statistical properties of the proposed method. The results show that the method provides more satisfactory confidence intervals and test statistics than a method that treats time series data as if they were cross-sectional data.</p

Bioresorbable Electronic Implants: History, Materials, Fabrication, Devices, and Clinical Applications

© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim Medical implants, either passive implants for structural support or implantable devices with active electronics, have been widely used for the diagnosis and treatment of various diseases and clinical issues. These implants offer various functions, including mechanical support of biological structures in orthopedic and dental applications, continuous electrophysiological monitoring and feedback of electrical stimulation in neuronal and cardiac applications, and controlled drug delivery while maintaining arterial structure in drug-eluting stents. Although these implants exhibit long-term biocompatibility, surgery for their retrieval is often required, which imposes physical, biological, and economical burdens on the patients. Therefore, as an alternative to such secondary surgeries, bioresorbable implants that disappear after a certain period of time inside the body, including bioresorbable active electronics, have been highlighted recently. This review first discusses the historical background of medical implants and briefly define related terminology. Representative examples of non-degradable medical implants for passive structural support and/or for diagnosis and therapy with active electronics are also provided. Then, recent progress in bioresorbable active implants composed of biosignal sensors, actuators for therapeutics, wireless power supply components, and their integrated systems are reviewed. Finally, clinical applications of these bioresorbable electronic implants are exemplified with brief conclusion and future outlook11sci

Linkage analysis of disease, DRT, and bivariate trait with the three cities dataset: ELOD (A) and power (percentage (LOD3)) (B)

<p><b>Copyright information:</b></p><p>Taken from "A power study of bivariate LOD score analysis of a complex trait and fear/discomfort with strangers"</p><p></p><p>BMC Genetics 2005;6(Suppl 1):S113-S113.</p><p>Published online 30 Dec 2005</p><p>PMCID:PMC1866825.</p><p></p