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Batteries are essential for the electrification of transport and the replacement of internal combustion engines. Thermodynamics was largely established with the development of the engines, and this knowledge has been applied to batteries for years. In particular, entropy profiles are sensitive to structural changes and are useful for diagnosing and understanding battery ageing. However, entropy profiling of aged batteries is mainly limited to the potentiometric method, which makes the technique in situ and time-consuming. Herein, we rely on optical fiber calorimetry to perform operando entropy profiling of commercial sodium-ion cells. Firstly, we directly compare the entropy profile of sodium-ion Na3V2(PO4)2F3/hard carbon (NVPF/HC) chemistry against those of commercialized lithium-ion chemistries, highlighting the uniqueness of NVPF/HC chemistry in battery thermal management. Operando entropy profiling of NVPF/HC chemistry further elucidates the structural degradations that take place during cycling and provide features that can be important indicators of the battery's state of health. This work reintroduces thermodynamic analyses as a valuable tool for batteries and spotlights the new horizons offered by the convergence of battery sensing, thermodynamics, and other disciplines.

Battery ageing is inevitable for chemistry of any kind and still occupies a central place in battery research and development. However, the operando monitoring of battery ageing under real working conditions remains largely unexplored. Herein, we demonstrate the feasibility of using fiber Bragg grating sensors to operando monitor the thermal (temperature and heat) evolutions of commercial 18650 sodium-ion cells during long-term cycling ageing. With the delicate heat deconvolution, the evolutions of entropy and overpotential heat rates upon the cycling ageing are decoded, while the ageing-driven changes in overpotential components are further analysed. Drawing also on thermodynamics, high-resolution enthalpy profiles are computed from operando heat and voltage profiles, enabling to track and unravel redox variations during the cycling ageing. Collectively, this work shows that fiber optic sensors are essential tools for operando deciphering cell ageing and offer tremendous opportunities for academia and industry alike.

Electronic Theses and Dissertations (ETDs) are digital versions of academic papers of graduate students. ETDs are highly complicated and lengthy texts: these include multimedia elements and other forms of information. A digital library with summaries for each ETD would enable more people to explore all these texts to learn about various domains. However, most chapters of ETDs don’t have summaries so the solution was to create AI generated summaries for users across disciplines to read. Before these summaries are accessible to the public, Bipasha will find researchers in various disciplines to evaluate the summaries. Incorporating human feedback into AI-generated summaries results in improved accuracy, relevance, originality, engagement and satisfaction. Quantitative measures for evaluating AI-generated content are great but qualitative feedback is important too. Subject matter experts can detect errors and inconsistencies in these summaries: this feedback provides guidance. Our team has developed a website that enables users to view and rank AI-generated summaries of texts against the ground truth (provided) chapter summaries. The users will not know beforehand which is which. The scholars (those with an education level of graduate school and beyond) should be able to accurately evaluate the summaries for the ETDs in their field. The purpose of this project is to allow human evaluation of these texts. The ranking feature serves as a form of feedback to perfect the AI generated summaries. The domain experts will use this website to determine the model that serves as a gold standard for summarization. For now, the intended users for this application are subject matter experts at Virginia Tech, so that they can evaluate the summaries. The evaluation will provide an idea of which model performs best to serve as a gold standard for AI generated summaries. Eventually, the final model will be used to serve users outside of Virginia Tech who want to know more about the doma

Background: Anticoagulation (AC) adherence after acute pulmonary embolism (PE) is vital to prevent mortality and future recurrence of venous thromboembolism (VTE). We aimed to analyze factors affecting AC adherence after acute PE. Methods: Consecutive adult patients with CT angiography or V/Q scan confirmed acute PE were included in a single-center retrospective study from April 2016 to May 2020. Adherence data, including AC refill dates, were collected from pharmacies, and adherence measures including Continuous Measure of Medication Acquisition (CMA), Proportion of Days Covered (PDC), and Optimal Medication Adherence (OMA) were calculated per standardized formulas. Univariable and multivariable linear and logistic regression was used to analyze different variables affecting AC adherence. Results: A total of 118 out of 144 patients had sufficient follow-up data to measure adherence and were included in the final analysis. Mean age was 60 ± 15 years, with 64 (54.2%) women; 70 (59.3%) White, 26 (22%) African American, 13 (11%) Hispanic; 58 (49.2%) patients had private insurance, 48 (40.7%) Medicare, 11 (9.3%) Medicaid. Type of AC comprised of 57 (48.3%) apixaban, 17 (14.4%) rivaroxaban, 8 (6.8%) warfarin, 6 (5.1%) enoxaparin, and 30 (25.4%) patients with changing AC. In univariable regression, African American and Medicaid-insured patients had significantly lower adherence, while advancing age, apixaban usage, and 30-day follow-up clinic visit showed a higher adherence. However, in multivariable regression, African American race (PDC -0.135, p = 0.006, CI (−0.231, −0.040) | OMA Adjusted OR 0.166, p = 0.030, CI (0.033, 0.837)) and other non-White, non-Hispanic races (PDC -0.314, p = 0.009, CI (−0.548, −0.080)) were associated with lower AC adherence. Conclusion: In our study, African American and other minority race patients showed lower AC adherence after hospital admission for acute PE. Further studies are needed to address underlying contributors and improve adhere

Base pair mismatches in DNA occur during replication and can result in mutations and certain types of cancer. The exact mechanism by which mismatch repair proteins recognize mismatches is still not well understood. Structures of mismatch recognition proteins bound to a mismatch indicate that the process involves introducing a sharp bend in the DNA and flipping out the mismatched base. Under external torsional stress, an elastic rod with a defect would buckle at the defect, provided the defect reduces the local bending stiffness. In vivo, if the same energetic scenario prevails, it could localize (or pin) the mismatch at the plectoneme end loop (plectoneme refers to a structure formed by the DNA when it buckles, and its helical axis wraps or writhes around itself in the presence of a critical torsional stress) and make the mismatched base pair more accessible to the mismatch repair protein. In genomic DNA, however, the entropic cost associated with plectoneme localization could make pinning unfavorable. Magnetic-tweezers-based studies of DNA supercoiling, performed at high salt concentrations, have shown that in DNA harboring a single mismatch, the plectoneme will always localize at the mismatch. Theoretical studies have predicted that under physiological salt concentrations, plectoneme localization becomes probabilistic, i.e., the plectoneme does not always localize at the mismatch. Plectoneme localization under physiological salt conditions is dependent on the number of mismatches and tension applied to the DNA. However, both experimental and theoretical approaches are currently limited to positively supercoiled DNA. In the current dissertation, we aim to study plectoneme localization, in physiologically relevant conditions, using state-of-the-art molecular dynamics (MD) simulations and single molecule magnetics tweezers-based experiments.In order to simulate plectoneme localization we first develop a framework using the widely available sequence and salt dependent