Pb0.4Bi1.6Sr2Ca1Cu2O8+xPb_{0.4}Bi_{1.6}Sr_{2}Ca_{1}Cu_{2}O_{8+x} and Oxygen Stoichiometry: Structure, Resistivity, Fermi Surface Topology and Normal State Properties

$Pb_{0.4}Bi_{1.6}Sr_2CaCu_2O_{8+x}$ ($Bi(Pb)-$2212) single crystal samples were studied using transmission electron microscopy (TEM), $ab-$plane ($\rho_{ab}$) and $c-$axis ($\rho_c$) resistivity, and high resolution angle-resolved ultraviolet photoemission spectroscopy (ARUPS). TEM reveals that the modulation in the $b-$axis for $Pb(0.4)-$doped $Bi(Pb)-$2212 is dominantly of $Pb-$type that is not sensitive to the oxygen content of the system, and the system clearly shows a structure of orthorhombic symmetry. Oxygen annealed samples exhibit a much lower $c-$axis resistivity and a resistivity minimum at $80-130$K. He-annealed samples exhibit a much higher $c-$axis resistivity and $d\rho_c/dT<0$ behavior below 300K. The Fermi surface (FS) of oxygen annealed $Bi(Pb)-$2212 mapped out by ARUPS has a pocket in the FS around the $\bar{M}$ point and exhibits orthorhombic symmetry. There are flat, parallel sections of the FS, about 60\% of the maximum possible along $k_x = k_y$, and about 30\% along $k_x = - k_y$. The wavevectors connecting the flat sections are about $0.72(\pi, \pi)$ along $k_x = k_y$, and about $0.80(\pi, \pi)$ along $k_x = - k_y$, rather than $(\pi,\pi)$. The symmetry of the near-Fermi-energy dispersing states in the normal state changes between oxygen-annealed and He-annealed samples.Comment: APS_REVTEX 3.0, 49 pages, including 11 figures, available upon request. Submitted to Phys. Rev. B

Cavity-enhanced direct frequency comb spectroscopy

Cavity-enhanced direct frequency comb spectroscopy combines broad spectral bandwidth, high spectral resolution, precise frequency calibration, and ultrahigh detection sensitivity, all in one experimental platform based on an optical frequency comb interacting with a high-finesse optical cavity. Precise control of the optical frequency comb allows highly efficient, coherent coupling of individual comb components with corresponding resonant modes of the high-finesse cavity. The long cavity lifetime dramatically enhances the effective interaction between the light field and intracavity matter, increasing the sensitivity for measurement of optical losses by a factor that is on the order of the cavity finesse. The use of low-dispersion mirrors permits almost the entire spectral bandwidth of the frequency comb to be employed for detection, covering a range of ~10% of the actual optical frequency. The light transmitted from the cavity is spectrally resolved to provide a multitude of detection channels with spectral resolutions ranging from a several gigahertz to hundreds of kilohertz. In this review we will discuss the principle of cavity-enhanced direct frequency comb spectroscopy and the various implementations of such systems. In particular, we discuss several types of UV, optical, and IR frequency comb sources and optical cavity designs that can be used for specific spectroscopic applications. We present several cavity-comb coupling methods to take advantage of the broad spectral bandwidth and narrow spectral components of a frequency comb. Finally, we present a series of experimental measurements on trace gas detections, human breath analysis, and characterization of cold molecular beams.Comment: 36 pages, 27 figure

Effects of rare kidney diseases on kidney failure: a longitudinal analysis of the UK National Registry of Rare Kidney Diseases (RaDaR) cohort

Background Individuals with rare kidney diseases account for 5–10% of people with chronic kidney disease, but constitute more than 25% of patients receiving kidney replacement therapy. The National Registry of Rare Kidney Diseases (RaDaR) gathers longitudinal data from patients with these conditions, which we used to study disease progression and outcomes of death and kidney failure. Methods People aged 0–96 years living with 28 types of rare kidney diseases were recruited from 108 UK renal care facilities. The primary outcomes were cumulative incidence of mortality and kidney failure in individuals with rare kidney diseases, which were calculated and compared with that of unselected patients with chronic kidney disease. Cumulative incidence and Kaplan–Meier survival estimates were calculated for the following outcomes: median age at kidney failure; median age at death; time from start of dialysis to death; and time from diagnosis to estimated glomerular filtration rate (eGFR) thresholds, allowing calculation of time from last eGFR of 75 mL/min per 1·73 m2 or more to first eGFR of less than 30 mL/min per 1·73 m2 (the therapeutic trial window). Findings Between Jan 18, 2010, and July 25, 2022, 27 285 participants were recruited to RaDaR. Median follow-up time from diagnosis was 9·6 years (IQR 5·9–16·7). RaDaR participants had significantly higher 5-year cumulative incidence of kidney failure than 2·81 million UK patients with all-cause chronic kidney disease (28% vs 1%; p<0·0001), but better survival rates (standardised mortality ratio 0·42 [95% CI 0·32–0·52]; p<0·0001). Median age at kidney failure, median age at death, time from start of dialysis to death, time from diagnosis to eGFR thresholds, and therapeutic trial window all varied substantially between rare diseases. Interpretation Patients with rare kidney diseases differ from the general population of individuals with chronic kidney disease: they have higher 5-year rates of kidney failure but higher survival than other patients with chronic kidney disease stages 3–5, and so are over-represented in the cohort of patients requiring kidney replacement therapy. Addressing unmet therapeutic need for patients with rare kidney diseases could have a large beneficial effect on long-term kidney replacement therapy demand. Funding RaDaR is funded by the Medical Research Council, Kidney Research UK, Kidney Care UK, and the Polycystic Kidney Disease Charity

A model-based approach to climate reconstruction using tree-ring data

Quantifying long-term historical climate is fundamental to understanding recent climate change. Most instrumentally recorded climate data are only available for the past 200 years, s o proxy observations from natural archives are often considered. We describe a model-based approach to reconstructing climate defined in terms of raw tree-ring measurement data that simultaneously accounts for non-climatic and climatic variability. In this approach we specify a joint model for the tree-ring data and climate variable that we fit using Bayesian inference. We consider a range of prior densities and compare the modeling approach to current methodology using an example case of Scots pine from Torneträsk, Sweden to reconstruct growing season temperature. We describe how current approaches translate into particular model assumptions. We explore how changes to various components in the model-based approach affect the resulting reconstruction. We show that minor changes in model specification can have little effect on model fit but lead to large changes in the predictions. In particular, the periods of relatively warmer and cooler temperatures are robust between models, but the magnitude of the resulting temperatures are highly model dependent. Such sensitivity may not be apparent with traditional approaches because the underlying statistical model is often hidden or poorly described