Inflammatory Biomarkers Decay After First-Line Antiretroviral Therapy Initiation With Dolutegravir/Lamivudine or Bictegravir/Emtricitabine/Tenofovir Alafenamide in Persons With HIV: A Substudy of a Randomized Clinical Trial. [PDF]
Fernandez A +6 more
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Clinical impact and cost-effectiveness of rapid versus non-rapid antiretroviral therapy initiation in HIV-positive men who have sex with men in China using modelling and 96-week multicenter cohort data. [PDF]
Zhou K, Wang X, Zhou D, Dai L, Tang W.
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Same-territory chronic infarcts are common in intracranial atherosclerosis and are associated with future recurrence. [PDF]
Pavlin Premrl D +9 more
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Concatenation, Conflict, and Complexity: Genealogical Heterogeneity Mimics Substitutional Heterogeneity for Nucleotide Model Selection. [PDF]
Lozano JR +4 more
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Consistency of BIC Model Averaging
Statistica Sinica, 2023Summary: BIC weighting is frequently applied to high-dimensional linear regressions when model averaging is used to address model selection uncertainty. It also plays a central role in model selection diagnostics. However, little research has been done on its consistency or weak consistency, which are crucial properties of model averaging methods.
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We demonstrate lasing with ultralow threshold from small-scale dielectric metasurfaces with only ~10×10 periods operating at a super-BIC regime. Engineered high-Q resonance originates from topological merging of accidental and symmetry-protected bound states in the continuum.
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Proportional BIC Sensor for Current Testing
Journal of Electronic Testing, 1992A new design of a BIC sensor for current testing static CMOS circuits is proposed. It is based on a lateral BJT device which is easy to incorporate in any standard CMOS process. The design diverts a fraction of the iDD current from the cell under test and a resistive component generates a voltage proportional to iDD Additional features are the ...
Josep Rius 0001, Joan Figueras
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The two most commonly used penalized model selection criteria, the Bayesian information criterion (BIC) and Akaike’s information criterion (AIC), are examined and compared. Their motivations as approximations of two different target quantities are discussed, and their performance in estimating those quantities is assessed.
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