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In this paper, we present and evaluate a novel Bayesian regime-switching zero-inflated multilevel Poisson (RS-ZIMLP) regression model for forecasting alcohol use dynamics. The model partitions individuals’ data into two phases, known as regimes, with: (1) a zero-inflation regime that is used to accommodate high instances of zeros (non-drinking) and (2) a multilevel Poisson regression regime in which variations in individuals’ log-transformed average rates of alcohol use are captured by means of an autoregressive process with exogenous predictors and a person-specific intercept. The times at which individuals are in each regime are unknown, but may be estimated from the data. We assume that the regime indicator follows a first-order Markov process as related to exogenous predictors of interest. The forecast performance of the proposed model was evaluated using a Monte Carlo simulation study and further demonstrated using substance use and spatial covariate data from the Colorado Online Twin Study (CoTwins). Results showed that the proposed model yielded better forecast performance compared to a baseline model which predicted all cases as non-drinking and a reduced ZIMLP model without the RS structure, as indicated by higher AUC (the area under the receiver operating characteristic (ROC) curve) scores, and lower mean absolute errors (MAEs) and root-mean-square errors (RMSEs). The improvements in forecast performance were even more pronounced when we limited the comparisons to participants who showed at least one instance of transition to drinking.
Combinatorial 2-player games can be studied from different perspectives. Traditionally the goal has been to acquire a perfect strategy, and to this purpose an efficient procedure (polynomial in succinct input size) is required. However, most combinatorial games are intrinsically hard to analyze; success is limited to a small number of games with predominant “mathematical structure”. The classical games of Nim (Bouton 1901) and Wythoff Nim (Wythoff 1907) are easy to analyze rigorously, but already seemingly modest variants, like (p, q)-GDWN (Larsson 2012, 2014), appear to withstand log-polynomial descriptions. Therefore, development of new methods is highly desirable.
Here, we use methods from physics, such as renormalization, in an attempt to understand the larger geometry of a game's P-positions (safe positions for the Previous player), rather than their exact configurations (Friedman et al. 2007, 2009). By studying evolution diagrams of a general class of linear extensions of Nim, Wythoff Nim and GDWN, we observe that P-positions often distribute uniformly along lines (a.k.a. P-beams), visually separated from the move lines. Given a fundamental hypothesis, a filling property which generalizes directly from Wythoff Nim, we formulate natural equations on the slopes and densities of P-positions along these lines; here, a key innovation, a reorganization model, guides us in selecting the relevant rules (move lines). The exceptional case of the symmetric (p, q)-GDWN is interesting, because of observed quasi-log repetitive fluctuations, and these games have defied all previous analysis.
1. Introduction to the class Linear Nimhoff
In this paper we study a class of combinatorial games using renormalizationbased techniques from physics in combination with computer simulations. This approach leads to a probabilistic geometric analysis of the underlying structure and behavior of a game. A number of interesting features are revealed, including observations of quasi log-periodic fluctuations. Our class of games, dubbed Linear Nimhoff, is a generalization of the classical Wythoff's game [Wythoff 1907] and the more recent GDWN [Larsson 2012a].
The renormalization approach to games involves:
1) Identifying broad, overall patterns in games (on a course grained level) by focusing on their scaling, asymptotic, and/or global, probabilistic behavior;
2) Analyzing these patterns using scaling/course-graining techniques derived from self-consistency conditions;
3) A novel method for this paper, a reorganization model, which filters out game rules that do not contribute to the broad overall patterns.
Lower paleozoic facies relationships, fossils, and depositional systems of the Northwest Ordos Basin, northern China, are sparsely documented in western world literature (Meng et al., 1997; Kessel, 2005). Recent field work in this area during the summer of 2004 recovered a single specimen of a new chiastoclonellid sponge. That sponge, described here, was collected from a measured section of Lower Paleozoic rocks exposed in the Suhaitu area, in the northern part of the Zhuozi Shan Range, northwestern Ordos Basin (Fig. 1), in southern Inner Mongolia Province. The Zhuozi Shan Range is part of the western Ordos fold and thrust belt, a Late Jurassic–Early Cretaceous tectonic feature, that brought Lower Paleozoic rocks to the surface (Darby and Ritts, 2002; Darby, 2003). Early Paleozoic rocks exposed in the area are dominantly carbonates with minor siliciclastic rocks and they span from the Early Cambrian through the Middle Ordovician (Yang et al., 1992; Meng et al., 1997). They are unconformably overlain by Middle Carboniferous units across the North China Block (Meng et al., 1997).
The cognitive profile of early onset Parkinson’s disease (EOPD) has not been clearly defined. Mutations in the parkin gene are the most common genetic risk factor for EOPD and may offer information about the neuropsychological pattern of performance in both symptomatic and asymptomatic mutation carriers. EOPD probands and their first-degree relatives who did not have Parkinson’s disease (PD) were genotyped for mutations in the parkin gene and administered a comprehensive neuropsychological battery. Performance was compared between EOPD probands with (N = 43) and without (N = 52) parkin mutations. The same neuropsychological battery was administered to 217 first-degree relatives to assess neuropsychological function in individuals who carry parkin mutations but do not have PD. No significant differences in neuropsychological test performance were found between parkin carrier and noncarrier probands. Performance also did not differ between EOPD noncarriers and carrier subgroups (i.e., heterozygotes, compound heterozygotes/homozygotes). Similarly, no differences were found among unaffected family members across genotypes. Mean neuropsychological test performance was within normal range in all probands and relatives. Carriers of parkin mutations, whether or not they have PD, do not perform differently on neuropsychological measures as compared to noncarriers. The cognitive functioning of parkin carriers over time warrants further study. (JINS, 2011, 17, 1–10)
Hepatic fibrosis is a wound-healing response to chronic liver injury, which if persistent can lead to cirrhosis and liver failure. Activation of hepatic stellate cells (HSCs), leading to accumulation of extracellular matrix, is the central event of fibrogenesis. Exciting progress has been made in understanding the molecular basis of this process. Major advances include: (1) elucidation of the effects (and signalling pathways) of key cytokines on HSCs; (2) understanding the transcriptional regulation of HSC activation; (3) characterisation of matrix proteases and their inhibitors; (4) demonstration of apoptosis as an important event in the resolution of hepatic fibrosis, and identification of its mediators; (5) elucidation of the complex and dynamic interaction between HSCs and matrix; and (6) understanding the role of other cellular elements in hepatic fibrosis and their interaction with HSCs. Ongoing research with gene analysis using cDNA or oligonucleotide microarrays, or transcriptional profiling, will further increase our knowledge of the regulation of the process. Ultimately, advances in the understanding of the molecular biology of hepatic fibrosis are critical to the development of effective, targeted antifibrotic therapy that might benefit millions of patients with chronic liver disease worldwide.
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