No Changes in Appetite Stimulating Hormones Following Swimming and Cycling Exercise Interventions

Swimming is a favorable and ideal modality of exercise for individuals with obesity and arthritis as it encompasses a minimal weight-bearing stress and a reduced heat load. However, the available evidence indicates that regular swimming may not be effective in reducing body weight and body fatness. A current hypothesis is that exercise in cold water somehow stimulates appetite. PURPOSE: We determined the effect of swimming exercise training on fasting concentrations of ghrelin, insulin, leptin, and peptide YY in obese individuals with osteoarthritis. Cycling training was included as a non-weight bearing land-based comparison group. METHODS: Thirty-nine obese participants with osteoarthritis (age=59±1 years, BMI=33±1 kg/m2) were randomly assigned to 12 weeks of supervised swimming training (N=19) or cycling training (N=20). In the initial few weeks, participants exercised for 20-30 minutes/day, 3 days/week, at an exercise intensity of 40-50% of heart rate reserve (HRR). Subsequently, the intensity and duration of exercise were progressively increased to 40-45 minutes/day, 3 days/week, at an intensity of 60-70% of HRR. Fasting blood samples were analyzed for ghrelin, insulin, leptin, and peptide YY concentrations using ELISAs. RESULTS: There were no group differences in body weight, BMI, or appetite stimulating hormones prior to the exercise interventions. Fasting plasma concentrations of ghrelin (37±8 vs. 42±11 pg/ml), insulin (1,176±424 vs. 1,179±442 pg/ml), leptin (20,200±2,891 vs. 16,617±2,734 pg/ml), and peptide YY (51±6 vs. 54±7 pg/ml) did not change with the swimming exercise intervention (all p\u3e0.05). Similarly, cycling exercise had no effect on ghrelin (36±10 vs. 44±8 pg/ml), insulin (978±321 vs. 964±311 pg/ml), leptin (29,261±5,438 vs. 26,308±4,771 pg/ml), or peptide YY (58±15 vs. 63±16 pg/ml) concentrations (all p\u3e0.05). CONCLUSION: Our present results indicate that fasting levels of appetite stimulating hormones did not change with 12 weeks of swimming exercise intervention in obese participants with osteoarthritis and that there were no group differences in changes in these hormones between swimming and cycling exercise interventions

A Design and Analytic Strategy for Monitoring Disease Positivity and Case Characteristics in Accessible Closed Populations

We propose a monitoring strategy for efficient and robust estimation of disease prevalence and case numbers within closed and enumerated populations such as schools, workplaces, or retirement communities. The proposed design relies largely on voluntary testing, notoriously biased (e.g., in the case of COVID-19) due to non-representative sampling. The approach yields unbiased and comparatively precise estimates with no assumptions about factors underlying selection of individuals for voluntary testing, building on the strength of what can be a small random sampling component. This component unlocks a previously proposed "anchor stream" estimator, a well-calibrated alternative to classical capture-recapture (CRC) estimators based on two data streams. We show here that this estimator is equivalent to a direct standardization based on "capture", i.e., selection (or not) by the voluntary testing program, made possible by means of a key parameter identified by design. This equivalency simultaneously allows for novel two-stream CRC-like estimation of general means (e.g., of continuous variables such as antibody levels or biomarkers). For inference, we propose adaptations of a Bayesian credible interval when estimating case counts and bootstrapping when estimating means of continuous variables. We use simulations to demonstrate significant precision benefits relative to random sampling alone

Enhanced Inference for Finite Population Sampling-Based Prevalence Estimation with Misclassification Errors

Epidemiologic screening programs often make use of tests with small, but non-zero probabilities of misdiagnosis. In this article, we assume the target population is finite with a fixed number of true cases, and that we apply an imperfect test with known sensitivity and specificity to a sample of individuals from the population. In this setting, we propose an enhanced inferential approach for use in conjunction with sampling-based bias-corrected prevalence estimation. While ignoring the finite nature of the population can yield markedly conservative estimates, direct application of a standard finite population correction (FPC) conversely leads to underestimation of variance. We uncover a way to leverage the typical FPC indirectly toward valid statistical inference. In particular, we derive a readily estimable extra variance component induced by misclassification in this specific but arguably common diagnostic testing scenario. Our approach yields a standard error estimate that properly captures the sampling variability of the usual bias-corrected maximum likelihood estimator of disease prevalence. Finally, we develop an adapted Bayesian credible interval for the true prevalence that offers improved frequentist properties (i.e., coverage and width) relative to a Wald-type confidence interval. We report the simulation results to demonstrate the enhanced performance of the proposed inferential methods

Tailoring Capture-Recapture Methods to Estimate Registry-Based Case Counts Based on Error-Prone Diagnostic Signals

Surveillance research is of great importance for effective and efficient epidemiological monitoring of case counts and disease prevalence. Taking specific motivation from ongoing efforts to identify recurrent cases based on the Georgia Cancer Registry, we extend recently proposed "anchor stream" sampling design and estimation methodology. Our approach offers a more efficient and defensible alternative to traditional capture-recapture (CRC) methods by leveraging a relatively small random sample of participants whose recurrence status is obtained through a principled application of medical records abstraction. This sample is combined with one or more existing signaling data streams, which may yield data based on arbitrarily non-representative subsets of the full registry population. The key extension developed here accounts for the common problem of false positive or negative diagnostic signals from the existing data stream(s). In particular, we show that the design only requires documentation of positive signals in these non-anchor surveillance streams, and permits valid estimation of the true case count based on an estimable positive predictive value (PPV) parameter. We borrow ideas from the multiple imputation paradigm to provide accompanying standard errors, and develop an adapted Bayesian credible interval approach that yields favorable frequentist coverage properties. We demonstrate the benefits of the proposed methods through simulation studies, and provide a data example targeting estimation of the breast cancer recurrence case count among Metro Atlanta area patients from the Georgia Cancer Registry-based Cancer Recurrence Information and Surveillance Program (CRISP) database

Improving the Performance at Elevated Temperature of High Voltage Graphite/LiNi\u3csub\u3e0.5\u3c/sub\u3eMn\u3csub\u3e1.5\u3c/sub\u3eO\u3csub\u3e4\u3c/sub\u3e Cells with Added Lithium Catechol Dimethyl Borate

Performance of LiNi0.5Mn1.5O4/graphite cells cycled to 4.8 V at 55°C with the 1.2 M LiPF6 in EC/EMC (3/7, STD electrolyte) with and without added lithium catechol dimethyl borate (LiCDMB) has been investigated. The incorporation of 0.5 wt% LiCDMB to the STD electrolyte results in an improved capacity retention and coulombic efficiency upon cycling at 55°C. Ex-situ analysis of the electrode surfaces via a combination of SEM, TEM, and XPS reveals that oxidation of LiCDMB at high potential results in the deposition of a passivation layer on the electrode surface, preventing transition metal ion dissolution from the cathode and subsequent deposition on the anode. NMR investigations of the bulk electrolyte stored at 85°C reveals that added LiCDMB prevents the thermal decomposition of LiPF6

A Facile Synthesis of ZnCo\u3csub\u3e2\u3c/sub\u3eO\u3csub\u3e4\u3c/sub\u3e Nanocluster Particles and the Performance as Anode Materials for Lithium Ion Batteries

ZnCo2O4 nanocluster particles (NCPs) were prepared through a designed hydrothermal method, with the assistance of a surfactant, sodium dodecyl benzene sulfonate. The crystalline structure and surface morphology of ZnCo2O4 were investigated by XRD, XPS, SEM, TEM, and BET analyses. The results of SEM and TEM suggest a clear nanocluster particle structure of cubic ZnCo2O4 (~100 nm in diameter), which consists of aggregated primary nanoparticles (~10 nm in diameter), is achieved. The electrochemical behavior of synthesized ZnCo2O4 NCPs was investigated by galvanostatic discharge/charge measurements and cyclic voltammetry. The ZnCo2O4 NCPs exhibit a high reversible capacity of 700 mAh g−1 over 100 cycles under a current density of 100 mA g−1 with an excellent coulombic efficiency of 98.9% and a considerable cycling stability. This work demonstrates a facile technique designed to synthesize ZnCo2O4 NCPs which show great potential as anode materials for lithium ion batteries

Performance of the 1-ton Prototype Neutrino Detector at CJPL-I

China Jinping Underground Laboratory (CJPL) provides an ideal site for solar, geo-, and supernova neutrino studies. With a prototype neutrino detector running since 2017, containing 1-ton liquid scintillator (LS), we tested its experimental hardware, performed the physics calibration, and measured its radioactive backgrounds, as an early stage of the Jinping Neutrino Experiment (JNE). We investigated the radon background and implemented the nitrogen sealing technology to control it. This paper presents the details of these studies and will serve as a key reference for the construction and optimization of the future large detector at JNE

Mixed-Phoneme BERT: Improving BERT with Mixed Phoneme and Sup-Phoneme Representations for Text to Speech

Recently, leveraging BERT pre-training to improve the phoneme encoder in text to speech (TTS) has drawn increasing attention. However, the works apply pre-training with character-based units to enhance the TTS phoneme encoder, which is inconsistent with the TTS fine-tuning that takes phonemes as input. Pre-training only with phonemes as input can alleviate the input mismatch but lack the ability to model rich representations and semantic information due to limited phoneme vocabulary. In this paper, we propose MixedPhoneme BERT, a novel variant of the BERT model that uses mixed phoneme and sup-phoneme representations to enhance the learning capability. Specifically, we merge the adjacent phonemes into sup-phonemes and combine the phoneme sequence and the merged sup-phoneme sequence as the model input, which can enhance the model capacity to learn rich contextual representations. Experiment results demonstrate that our proposed Mixed-Phoneme BERT significantly improves the TTS performance with 0.30 CMOS gain compared with the FastSpeech 2 baseline. The Mixed-Phoneme BERT achieves 3x inference speedup and similar voice quality to the previous TTS pre-trained model PnG BERTComment: submitted to interspeech 202

Optical and microstructural characterization of Er3+^{3+} doped epitaxial cerium oxide on silicon

Rare-earth ion dopants in solid-state hosts are ideal candidates for quantum communication technologies such as quantum memory, due to the intrinsic spin-photon interface of the rare-earth ion combined with the integration methods available in the solid-state. Erbium-doped cerium oxide (Er:CeO$_2$) is a particularly promising platform for such a quantum memory, as it combines the telecom-wavelength (~1.5 $\mu$m) 4f-4f transition of erbium, a predicted long electron spin coherence time supported by CeO$_2$, and is also near lattice-matched to silicon for heteroepitaxial growth. In this work, we report on the epitaxial growth of Er:CeO$_2$ thin films on silicon using molecular beam epitaxy (MBE), with controlled erbium concentration down to 2 parts per million (ppm). We carry out a detailed microstructural study to verify the CeO$_2$ host structure, and characterize the spin and optical properties of the embedded Er$^{3+}$ ions. In the 2-3 ppm Er regime, we identify EPR linewidths of 245(1) MHz, optical inhomogeneous linewidths of 9.5(2) GHz, optical excited state lifetimes of 3.5(1) ms, and spectral diffusion-limited homogenoeus linewidths as narrow as 4.8(3) MHz in the as-grown material. We test annealing of the Er:CeO$_2$ films up to 900 deg C, which yields modest narrowing of the inhomogeneous linewidth by 20% and extension of the excited state lifetime by 40%. We have also studied the variation of the optical properties as a function of Er doping and find that the results are consistent with the trends expected from inter-dopant charge interactions.Comment: 15 pages, 6 figures (including supplemental information