Analytical Stellar Models of Neutron Stars in Teleparallel Gravity

In this paper, we developed three analytical models and obtained a new class of solutions describing compact stellar structures using the theory of teleparallel gravity. We consider the general anisotropic nature of stellar configurations and solve teleparallel gravity equations. In order to thoroughly analyze the various parameters of the stars, we developed three models by choosing various physically acceptable forms of metric potential $e^{d(r)}$ and radial pressure $p_r(r)$. We also analyze the impact of teleparallel gravity's parameters $\beta$ and $\beta_1$ on the description of the stellar structures. We calculated model parameters such that models describing various observed neutron stars obey all physical conditions to be potentially stable and causal. By analyzing the impact of various parameters of teleparallel gravity on the description of anisotropic stellar structures, we found that three models developed in this paper can describe anisotropic neutron stars ranging from low density to high density. Finally, we obtain a quadratic Equation of State for each model describing various neutron stars, which can be utilized to find compositions of the stellar structures. It is very useful to find models that can exhibit quadratic EOS, since material compositions of real neutron stars and strange stars are found to exhibit quadratic EOS by various authors. Non linear $f(T)$ model gives high deviation of EOS from quadratic behaviour, thus, in this paper we work with linear $f(T)$ function by using diagonal tetrad to model realistic compact stars.Comment: made equations more readable and implemented some changes suggested by reviewer

AnyLoc: Towards Universal Visual Place Recognition

Visual Place Recognition (VPR) is vital for robot localization. To date, the most performant VPR approaches are environment- and task-specific: while they exhibit strong performance in structured environments (predominantly urban driving), their performance degrades severely in unstructured environments, rendering most approaches brittle to robust real-world deployment. In this work, we develop a universal solution to VPR -- a technique that works across a broad range of structured and unstructured environments (urban, outdoors, indoors, aerial, underwater, and subterranean environments) without any re-training or fine-tuning. We demonstrate that general-purpose feature representations derived from off-the-shelf self-supervised models with no VPR-specific training are the right substrate upon which to build such a universal VPR solution. Combining these derived features with unsupervised feature aggregation enables our suite of methods, AnyLoc, to achieve up to 4X significantly higher performance than existing approaches. We further obtain a 6% improvement in performance by characterizing the semantic properties of these features, uncovering unique domains which encapsulate datasets from similar environments. Our detailed experiments and analysis lay a foundation for building VPR solutions that may be deployed anywhere, anytime, and across anyview. We encourage the readers to explore our project page and interactive demos: https://anyloc.github.io/.Comment: IEEE RA-L 2023 (Presented at ICRA 2024

Clinical trials and progress with paclitaxel in ovarian cancer

Paclitaxel is a front-line agent for ovarian cancer chemotherapy, along with the platinum agents. Derived from the Pacific yew tree, Taxus brevifolia, paclitaxel has covered significant ground from the initial discovery of its antineoplastic properties to clinical applications in many forms of human cancers, including ovarian cancer. Although much has been published about the unique mechanism of action of this agent, several issues remain to be resolved. Finding the appropriate dosage schedule for paclitaxel in chemo-naïve and recurrent ovarian cancer, defining the role of paclitaxel in maintenance chemotherapy, and elucidating the mechanisms of taxane resistance are areas of intense research. Newer forms of taxanes are being manufactured to avoid troublesome adverse effects and to improve clinical efficacy. These issues are reviewed in detail in this paper with an emphasis on clinically relevant evidence-based information

Estimating and Interpreting Effects from Nonlinear Exposure-Response Curves in Occupational Cohorts Using Truncated Power Basis Expansions and Penalized Splines

Truncated power basis expansions and penalized spline methods are demonstrated for estimating nonlinear exposure-response relationships in the Cox proportional hazards model. R code is provided for fitting models to get point and interval estimates. The method is illustrated using a simulated data set under a known exposure-response relationship and in a data application examining risk of carpal tunnel syndrome in an occupational cohort

Evaluation of Social Media Use by Emergency Medicine Residents and Faculty

Introduction Clinicians and residency programs are increasing their use of social media (SM) websites for educational and promotional uses, yet little is known about the use of these sites by residents and faculty. The objective of the study is to assess patterns of SM use for personal and professional purposes among emergency medicine (EM) residents and faculty. Methods In this multi-site study, an 18-question survey was sent by e-mail to the residents and faculty in 14 EM programs and to the Council of Emergency Medicine Residency Directors (CORD) listserv via the online tool SurveyMonkey™. We compiled descriptive statistics, including assessment with the chi-square test or Fisher’s exact test. StatsDirect software (v 2.8.0, StatsDirect, Cheshire, UK) was used for all analyses. Results We received 1,314 responses: 63% of respondents were male, 40% were <30 years of age, 39% were between the ages 31 and 40, and 21% were older than 40. The study group consisted of 772 residents and 542 faculty members (15% were program directors, 21% were assistant or associate PDs, 45% were core faculty, and 19% held other faculty positions. Forty-four percent of respondents completed residency more than 10 years ago. Residents used SM markedly more than faculty for social interactions with family and friends (83% vs 65% [p<0.0001]), entertainment (61% vs 47% [p<0.0001]), and videos (42% vs 23% [p=0.0006]). Residents used Facebook™ and YouTube™ more often than faculty (86% vs 67% [p<0.001]; 53% vs 46% [p=0.01]), whereas residents used Twitter™ (19% vs 26% [p=0.005]) and LinkedIn™ (15% vs 32% [p<0.0001]) less than faculty. Overall, residents used SM sites more than faculty, notably in daily use (30% vs 24% [p<0.001]). For professional use, residents were most interested in its use for open positions/hiring (30% vs 18% [p<0.0001]) and videos (33% vs 26% [p=0.005]) and less interested than faculty with award postings (22% vs 33% [p<0.0001]) or publications (30% vs 38% [p=0.0007]). Conclusion EM residents and faculty have different patterns and interests in the personal and professional uses of social media. Awareness of these utilization patterns could benefit future educational endeavors

First Post-Operative Urinary Kidney Injury Biomarkers and Association with the Duration of AKI in the TRIBE-AKI Cohort

Background: We previously demonstrated that assessment of the duration of AKI, in addition to magnitude of rise in creatinine alone, adds prognostic information for long-term survival. We evaluated whether post-operative kidney injury biomarkers in urine collected immediately after cardiac surgery associate with duration of serum creatinine elevation. Methods: We studied 1199 adults undergoing cardiac surgery in a prospective cohort study (TRIBE-AKI) and examined the association between the levels of five urinary biomarkers individually at 0–6 hours after surgery: interleukin-18 (IL-18), neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), liver fatty acid binding protein (L-FABP) and albumin with duration of serum creatinine-based AKIN criteria for AKI (0 (no AKI), 1–2, 3–6, ≥7 days). Results: Overall, 407 (34%) patients had at least stage 1 AKI, of whom 251 (61.7%) had duration of 1–2 days, 118 (28.9%) had duration 3–6 days, and 38 (9.3%) had duration of ≥7 days. Higher concentrations of all biomarkers (per log increase) were independently associated with a greater odds of a longer duration of AKI; odds ratios and 95% confidence intervals using ordinal logistic regression were the following: IL-18: 1.22, 1.13–1.32; KIM-1: 1.36, 1.21–1.52; albumin 1.20, 1.09–1.32; L-FABP 1.11, 1.04–1.19; NGAL 1.06, 1.00–1.14). AKI duration of 7 days or longer was associated with a 5-fold adjusted risk of mortality at 3 years. Conclusions: There was an independent dose-response association between urinary levels of injury biomarkers immediately after cardiac surgery and longer duration of AKI. Duration of AKI was also associated with long term mortality. Future studies should explore the potential utility of these urinary kidney injury biomarkers to enrich enrollment of patients at risk for longer duration of AKI into trials of interventions to prevent or treat post-operative AKI.</p