A comparison of multiple approaches to subgroup analysis in clinical trial

textIn randomized clinical trials, medical researchers are interested to determine the effectiveness of a new treatment not only in the overall population but also to some subgroups with possible enhanced treatment effects. However, subgroup analysis may become problematic due to the issue of multiplicities, data dredging etc. Accounting for these issue, we summarized some guidelines on the use and interpretation of subgroup analysis. We reviewed three approaches to subgroup analysis, a tranditional Bayesian regression with interaction terms, the 'Virtual Twins' methods and a Bayesian model selection approach. The advantage and disadvantage of these three approaches are discussed.Statistic

Renewable Energy in China: Market Barriers and Policy Options

With an obvious characteristic of innovation, the development of renewable energy (RE) industry is a process of industry innovation itself. There are serious market failures and barriers in the RE technology innovation process. The reasons for RE innovation’s market failure include “dual information externalities”, “coordination failure” and “lock-in effect”. As an emerging strategic industry, the RE industry has gained sound support from policies in recent years. Nevertheless, industrial development is being impeded by difficulties such as a lack of core technology, disorderly competition and a rupture in market demands, which also brought to the light the deviation of the current industry policies. Combined with industrial innovation theories of Neoclassical Economics, New Institutional Economics, and Evolutionary Economics, and based on the perspective of new industry policies, this paper reexamines the RE industrial policies in China and tries to explore new industry policies that accord with the innovative essence in the RE industry

Using childhood cancer incidence trends over time as a surveillance tool in evaluating the health outcome impact of unconventional shale gas development in PA

Background/Objective: Unconventional natural gas shale drilling (UNGD) development has grown dramatically since 2007, peaking in 2011 thus raising concerns about the health impact on children. Although latency for cancer can be 50 years in adults, some childhood cancers may be sensitive to both in utero and early perinatal exposures. We examined incidence of childhood cancer in fracking and non-fracking counties in Pennsylvania as a possible surveillance tool for environmental exposures from fracking. Method: Three cancer types (childhood Leukemia, Lymphoma and CNS tumor) known to be associated with environmental risk factors were examined. Average age-adjusted incidence rates were calculated for each cancer type in 4 year intervals from 1985-2013 in PA and were compared among exposed and unexposed counties. Correlation matrix and stepwise multivariate regression were used to examine other concomitant risk factors (smoking rate and sociodemographic characteristics by county) that may affect childhood cancer rates along with a measure of fracking density on county level. Results: The total number of childhood cancer cases (ag

S2S-WTV: Seismic Data Noise Attenuation Using Weighted Total Variation Regularized Self-Supervised Learning

Seismic data often undergoes severe noise due to environmental factors, which seriously affects subsequent applications. Traditional hand-crafted denoisers such as filters and regularizations utilize interpretable domain knowledge to design generalizable denoising techniques, while their representation capacities may be inferior to deep learning denoisers, which can learn complex and representative denoising mappings from abundant training pairs. However, due to the scarcity of high-quality training pairs, deep learning denoisers may sustain some generalization issues over various scenarios. In this work, we propose a self-supervised method that combines the capacities of deep denoiser and the generalization abilities of hand-crafted regularization for seismic data random noise attenuation. Specifically, we leverage the Self2Self (S2S) learning framework with a trace-wise masking strategy for seismic data denoising by solely using the observed noisy data. Parallelly, we suggest the weighted total variation (WTV) to further capture the horizontal local smooth structure of seismic data. Our method, dubbed as S2S-WTV, enjoys both high representation abilities brought from the self-supervised deep network and good generalization abilities of the hand-crafted WTV regularizer and the self-supervised nature. Therefore, our method can more effectively and stably remove the random noise and preserve the details and edges of the clean signal. To tackle the S2S-WTV optimization model, we introduce an alternating direction multiplier method (ADMM)-based algorithm. Extensive experiments on synthetic and field noisy seismic data demonstrate the effectiveness of our method as compared with state-of-the-art traditional and deep learning-based seismic data denoising methods

Analysis and properties of carotenoids in vivo and in vitro

The purpose of this study was to develop a deeper understanding of the nature of carotenoid metabolism in the human and primate retina. We have sought to do this from two perspectives (1) through preparation and study of a carotenoid diketone that is a candidate metabolic product and (2) through measurement of the carotenoid distribution in the retinas of neonatal macaques. In this thesis we report the synthesis, purification, and characterization of the product using HPLC, UV/Vis, MS, 1H-NMR. The data obtained are all consistent with the proposed β,β-carotene-3,3\u27-dione. There has been no thorough study of the development of the macular pigment during the earliest stages of life immediately following birth. In this study 30 macaque retinas ranging from 148 days of gestation to 15 years in age were analyzed. The amounts of the carotenoids, lutein, R,R-zeaxanthin, and meso-zeaxanthin were determined using C 18 reversed-phase column and chiral, normal-phase column HPLC

Prediction of Hardness and Residual Stress in Orthogonal Cutting of Inconel 718

Due to its high strength in high temperatures, Inconel 718 is widely used in the aerospace industry. However, Inconel 718 is a difficult-to-cut alloy with poor machinability. For instance, the cutting force is high in cutting Inconel 718, resulting in work-hardening of the machined surface and high residual stress in the machined surface. When residual stress releases, the part deforms and scrapes with error beyond tolerance. Therefore, it is necessary to predict the residual stress in the machined surface under a set of machining conditions. By modifying the machining conditions, the residual stress in the machined surface is under control, and the part deformation is limited. In this research, an analytical approach to the hardness and the residual stress in the machined surface in orthogonal cutting is proposed. This research has advantages over the experiment, the conventional approach and the FEA methods. With this approach, the cutting parameters can be optimized to minimize the residual stress in the machined surface and improve the surface integrity

Malicious Selling Strategies During Livestream Shopping: A Case Study of Alibaba's Taobao and ByteDance's TikTok

Due to the limitations imposed by the COVID-19 pandemic, many users have shifted their shopping patterns from offline to online. Livestream shopping has become popular as one of the online shopping media. However, many streamers' malicious selling behaviors have been reported. In this research, we sought to explore streamers' malicious selling strategies and understand how viewers perceive these strategies. First, we recorded 40 livestream shopping sessions from two popular livestream platforms in China -- Taobao and TikTok (or "Douyin" in Chinese). We identified four categories of malicious selling strategies (i.e., Restrictive, Deceptive, Covert, and Asymmetric) and found that platform designs enhanced these malicious selling strategies. Second, through an interview study with 13 viewers, we provide a rich description of viewers' awareness of malicious selling strategies and the challenges they encountered while trying to overcome malicious selling. We conclude by discussing the policy and design implications of countering malicious selling

Interpreting and exploiting narrative as a sketch design generator for application in VE

The research in this paper focusses on how a narrative text can be the generator of an architectural drawing, or other architectural representation, such as an Architectural Virtual Environment. The drawn physical sketch has traditionally played that role. A particular approach to narrative has been important for some notable architects and their architecture. Ian Ritchie (2014), for instance, celebrates the use of poetry to describe the essential spirit of a scheme before any drawing is done. The work in the paper here describes the proposition to capture such narrative text in a systematic and structured way. We describe foundational work on how the captured narrative text has been translated into a contemporary, computer-mediated, design development environment. Different narrative accounts recalling a now demolished house form the focus case study. This case study is the vehicle through which the initial principles establishing how best to move from narrative to virtual representation are established and tested

Structural characterization of a polysaccharide from Lyophyllum decastes with MAPK-mediated immune regulation ability in mice

Abstract Lyophyllum decastes is a common macrofungi for both medicinal and economic value, and its polysaccharide has excellent development potential as a new immune regulator. In the present study, the bioactive component polysaccharide of L decastes was extracted, and its chain structure was characterized in detail by Fourier transform infrared (FT-IR) spectroscopy, high-performance gel-permeation chromatography (HP-GPC), and gas chromatography–mass spectrometry (GC–MS). LDP-W had a molecular weight of 2.12 × 104 Da, highly branched β type pyranose. At the same time, it exhibited potential immunomodulatory activity, which can modulate the numbers of CD3+, CD4+, CD8+ and CD19+ cells in the spleen; optimize the CD4+/CD8+ ratio; promoted T and B lymphocyte proliferation and it can elevate the levels of IL-2, IL-6, IFN-γ and TNF-α in immunosuppressed mice by influencing the phosphorylation of MAPK signaling-related proteins. These studies fill the gap in the immune regulation mechanism of L decastes polysaccharide, providing a theoretical basis for the potential application of LDP-W as immunomodulatory drugs or functional foods

A Fast and Accurate Pitch Estimation Algorithm Based on the Pseudo Wigner-Ville Distribution

Estimation of fundamental frequency (F0) in voiced segments of speech signals, also known as pitch tracking, plays a crucial role in pitch synchronous speech analysis, speech synthesis, and speech manipulation. In this paper, we capitalize on the high time and frequency resolution of the pseudo Wigner-Ville distribution (PWVD) and propose a new PWVD-based pitch estimation method. We devise an efficient algorithm to compute PWVD faster and use cepstrum-based pre-filtering to avoid cross-term interference. Evaluating our approach on a database with speech and electroglottograph (EGG) recordings yields a state-of-the-art mean absolute error (MAE) of around 4Hz. Our approach is also effective at voiced/unvoiced classification and handling sudden frequency changes