A systematic review and meta-analysis of data linkage between motor vehicle crash and hospital-based datasets.

Motor vehicle crash data linkage has emerged as a vital tool to better understand the injury outcomes and the factors contributing to crashes. This systematic review and meta-analysis aims to explore the existing knowledge on data linkage between motor vehicle crashes and hospital-based datasets, summarize and highlight the findings of previous studies, and identify gaps in research. A comprehensive and systematic search of the literature yielded 54 studies for a qualitative analysis, and 35 of which were also considered for a quantitative meta-analysis.

A critical review of municipal solid waste hydraulic conductivity: A mini review.

This study is a critical review of municipal solid waste (MSW) hydraulic conductivity that includes investigation of the influence of vertical stress, dry unit weight and degradation. A total of 56 studies were compiled that included laboratory-, pilot- and landfill-scale hydraulic conductivity experiments. Compacting waste and increasing vertical stress reduce MSW hydraulic conductivity via reshaping the pore networks throughout the waste matrix, reducing the void ratio and increasing tortuosity.

Influence of oil and gas exploration and production waste on municipal solid waste hydraulic conductivity.

This study evaluated the effects of addition of oil and gas exploration and production wastes (E&PW) on hydraulic behavior of municipal solid waste (MSW). A series of laboratory experiments were conducted to assess the impacts of vertical stress, waste composition, mixture ratio of MSW to E&PW based on total mass (e.g.

Tractable Maximum Likelihood Estimation for Latent Structure Influence Models With Applications to EEG & ECoG Processing.

Brain signals are nonlinear and nonstationary time series, which provide information about spatiotemporal patterns of electrical activity in the brain. CHMMs are suitable tools for modeling multi-channel time-series dependent on both time and space, but state-space parameters grow exponentially with the number of channels. To cope with this limitation, we consider the influence model as the interaction of hidden Markov chains called Latent Structure Influence Models (LSIMs).

A New Post-Processing Method using Latent Structure Influence Models for Channel Fusion in Automatic Sleep Staging.

Human sleep stage dynamics can be adequately represented using Markov chain models, and the accuracy of sleep stage classification can be improved by considering these dynamics. The present study proposes a new post-processing method based on channel fusion using Latent Structure Influence Models (LSIMs). LSIMs can simultaneously model sequences of different channels to have a nonlinear dynamical fusion based on sleep stage dynamics.

Implications of municipal solid waste co-disposal experiments on biodegradation and biochemical compatibility.

The objective of this study was to evaluate waste biodegradation and biochemical compatibility for different waste co-disposed with municipal solid waste (MSW). Laboratory-scale reactors were operated with MSW co-disposed with special solid waste, liquid waste, or sludge waste. Early and aggressive addition of liquid wastes during reactor startup did not stimulate anaerobic decomposition of fresh MSW.

Modelling bus-pedestrian crash severity in the state of Victoria, Australia.

Understanding the relationship between bus-pedestrian crash severity and factors contributing to such crashes is important. However, there exists a dearth of research on the factors affecting bus-pedestrian crash severity. This study aims to fulfil this gap by investigating the factors affecting the severity of pedestrian injuries.

The influence of moisture enhancement on solid waste biodegradation.

The objective of this study was to assess the influence of moisture enhancement strategies on biodegradation of municipal solid waste (MSW) in laboratory-scale reactors. Moisture enhancement strategies were varied with respect to dose volume (40, 80, 160, and 320 L/Mg-MSW) and dose frequency (dosing every ½, 1, 2, and 4 weeks). Biodegradation was evaluated based on methane generation to assess (i) the lag-time between the start of liquid dosing and onset of methane generation and (ii) the first-order decay rate for methane generation.

Heart Rate monitoring during physical exercise using wrist-type photoplethysmographic (PPG) signals.

Heart rate monitoring using wrist-type using photoplethysmographic (PPG) signals during subjects' intensive exercises is a challenging problem, since signals are strongly affected by motion artifacts caused by unexpected movements. This paper presents a method that uses both time and frequency characteristics of signals; using sparse signal reconstruction for high-resolution spectrum estimation. Experimental results on type data sets recorded from 12 subjects during fast running at peak speed of 15 km/hour.