339 research outputs found
Modeling diurnal hormone profiles by hierarchical state space models.
Adrenocorticotropic hormone (ACTH) diurnal patterns contain both smooth circadian rhythms and pulsatile activities. How to evaluate and compare them between different groups is a challenging statistical task. In particular, we are interested in testing 1) whether the smooth ACTH circadian rhythms in chronic fatigue syndrome and fibromyalgia patients differ from those in healthy controls, and 2) whether the patterns of pulsatile activities are different. In this paper, a hierarchical state space model is proposed to extract these signals from noisy observations. The smooth circadian rhythms shared by a group of subjects are modeled by periodic smoothing splines. The subject level pulsatile activities are modeled by autoregressive processes. A functional random effect is adopted at the pair level to account for the matched pair design. Parameters are estimated by maximizing the marginal likelihood. Signals are extracted as posterior means. Computationally efficient Kalman filter algorithms are adopted for implementation. Application of the proposed model reveals that the smooth circadian rhythms are similar in the two groups but the pulsatile activities in patients are weaker than those in the healthy controls
Government Responses Matter: Predicting Covid-19 cases in US under an empirical Bayesian time series framework
Since the Covid-19 outbreak, researchers have been predicting how the epidemic will evolve, especially the number in each country, through using parametric extrapolations based on the history. In reality, the epidemic progressing in a particular country depends largely on its policy responses and interventions. Since the outbreaks in some countries are earlier than United States, the prediction of US cases can benefit from incorporating the similarity in their trajectories. We propose an empirical Bayesian time series framework to predict US cases using different countries as prior reference. The resultant forecast is based on observed US data and prior information from the reference country while accounting for different population sizes. When Italy is used as prior in the prediction, which the US data resemble the most, the cases in the US will exceed 300,000 by the beginning of April unless strong measures are adopted
fmixed: A SAS Macro for Smoothing-Spline-Based Functional Mixed Effects Models
In this article we implement the smoothing-spline-based functional mixed effects models (Guo 2002) by a SAS macro by exploiting the connection between mixed effects models and smoothing splines. The macro can handle flexible design matrices and is easy to use. Input parameters and output results are described and explained. A numeric example and a real data example are used for illustration
Innovation of China’s Grass-Root Agricultural Extension Team With ICTs
Agricultural extension plays a very important role in the technology transformation. Many researchers are committed to innovate the agriculture extension system with ICTs and there has been a remarkable progress in the use of ICTs in agricultural extension. This paper gave a brief introduction about the chinese agricultural extension system and focused on improving the service capacity of the grass-root agricultural extension team with ICTs. Some experience from what we have done is shared and the problems we have encountered are also discussed
Experimental Determination of Complex Optical Constants of Air-Stable Inorganic CsPbI₃ Perovskite Thin Films
Air‐stable inorganic cesium lead iodide (CsPbI3) perovskite thin films with a bandgap of 1.7 eV are a promising candidate for tandem cell solar cells, comprising a perovskite top cell with a crystalline silicon bottom cell. The device design and simulations are important to develop high‐efficiency photovoltaic devices. However, knowledge of complex optical constants of the CsPbI3 thin films is mandatory to complement such tasks. Herein, air‐stable inorganic CsPbI3 perovskite thin films are prepared using one‐step synthesis through a spin‐coating method. Variable angle spectroscopic ellipsometry (VASE) is then conducted at five angles (43.9°, 48.9°, 53.9°, 58.9°, and 63.9°) to obtain ellipsometric data (Ψ and Δ). The thickness nonuniformity model of the perovskite thin film combined with an effective medium approximation for describing rough surface is adopted to achieve excellent fitting. The complex optical constants of the CsPbI3 thin film are experimentally obtained in the wavelength range of 300–1200 nm. The present results open the door for design and simulations on high‐efficiency CsPbI3/c‐Si tandem solar cells
Fears of Violence During Morning Travel to School
PURPOSE: Children\u27s safety as they travel to school is a concern nationwide. We investigated how safe children felt from the risk of being assaulted during morning travel to school.
METHODS: Children between 10 and 18 years old were recruited in Philadelphia and interviewed with the aid of geographic information system (GIS) mapping software about a recent trip to school, situational characteristics, and how safe they felt as they travelled based on a 10-point item (1 = very unsafe, 10 = very safe). Ordinal regression was used to estimate the probability of perceiving different levels of safety based on transportation mode, companion type, and neighborhood characteristics.
RESULTS: Among 65 randomly selected subjects, routes to school ranged from 7 to 177 minutes (median = 36) and .1-15.1 street miles (median = 1.9), and included between 1-5 transportation modes (median = 2). Among students interviewed, 58.5% felt less than very safe (i.e.,8, for example, was .99 while in a car and .94 while on foot but was .86 and .87 when on a public bus or trolley. Probability was .98 while with an adult but was .72 while with another child and .71 when alone. Also, perceived safety was lower in areas of high crime and high density of off-premise alcohol outlets.
CONCLUSIONS: Efforts that target situational risk factors are warranted to help children feel safe over their entire travel routes to school
Post-marketing safety surveillance of sacituzumab govitecan: an observational, pharmacovigilance study leveraging FAERS database
Background and objective: Sacituzumab govitecan (SG), the first antibody-drug conjugate targeting human trophoblast cell-surface antigen 2 (Trop-2), has been approved by the Food and Drug Administration (FDA) for the treatment of advanced or metastatic breast cancer and urothelial cancer. However, there is currently a dearth of information regarding the safety profiles of SG in a large sample cohort. The objective of the present study is to investigate SG-related adverse events (AEs) in real-world settings leveraging the FDA Adverse Event Reporting System (FAERS) database to guide the safety management of clinical medication.Methods: The FAERS database was retrospectively queried to extract reports associated with SG from April 2020 to March 2023. To identify and evaluate potential AEs in patients receiving SG, various disproportionality analyses such as reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and the multi-item gamma Poisson shrinker (MGPS) were employed.Results: Overall, 2069 reports of SG as the “primary suspect” were identified. Noteworthy, SG was significantly associated with an increased risk of blood lymphatic system disorders (ROR, 7.18; 95% CI, 6.58–7.84) and hepatobiliary disorders (ROR, 2.68; 95% CI, 2.17–3.30) at the System Organ Class (SOC) level. Meanwhile, 61 significant disproportionality preferred terms (PTs) simultaneously complied with all four algorithms were adopted. Therein, anemia, thrombocytopenia, neutropenia, leukopenia, diarrhea, asthenia, alopecia, and electrolyte imbalance were consistent with the common AEs described in the clinical trials and specification of SG. Furthermore, unexpected significant AEs include colitis (ROR, 12.09; 95% CI, 9.1–16.08), heart rate increased (ROR, 5.11; 95% CI, 3.84–6.79), sepsis (ROR, 4.77; 95% CI, 3.59–6.34), cholestasis (ROR, 6.28; 95% CI, 3.48–11.36), blood bilirubin increased (ROR, 4.65; 95% CI, 2.42–8.94) and meningitis (ROR, 7.23; 95% CI, 2.71–19.29) were also be detected. The median time to onset of SG-related AEs was 14 [interquartile range (IQR), 7–52] days, with the majority occurring within the initial month of SG treatment.Conclusion: Our study validates the commonly known AEs and also found some potentially emerging safety issues related to SG in real-world clinical practice, which could provide valuable vigilance evidence for clinicians and pharmacists to manage the safety issues of SG
Recent Advances on Early Detection of Heat Strain in Dairy Cows Using Animal-Based Indicators: A Review
peer reviewedIn pursuit of precision livestock farming, the real-time measurement for heat strain-related data has been more and more valued. Efforts have been made recently to use more sensitive physiological indicators with the hope to better inform decision-making in heat abatement in dairy farms. To get an insight into the early detection of heat strain in dairy cows, the present review focuses on the recent efforts developing early detection methods of heat strain in dairy cows based on body temperatures and respiratory dynamics. For every candidate animal-based indicator, state-of-the-art measurement methods and existing thresholds were summarized. Body surface temperature and respiration rate were concluded to be the best early indicators of heat strain due to their high feasibility of measurement and sensitivity to heat stress. Future studies should customize heat strain thresholds according to different internal and external factors that have an impact on the sensitivity to heat stress. Wearable devices are most promising to achieve real-time measurement in practical dairy farms. Combined with internet of things technologies, a comprehensive strategy based on both animal- and environment-based indicators is expected to increase the precision of early detection of heat strain in dairy cows
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