Investigation of Solvent Type and Salt Addition in High Transference Number Nonaqueous Polyelectrolyte Solutions for Lithium Ion Batteries

High Li+ transference number electrolytes have attracted recent interest as a means to improve the energy density and rate capabilities of current lithium ion batteries. Here the viscosity and transport properties of a sulfonated polysulfone/poly(ethylene glycol) copolymer that displays both high transference number and high conductivity when dissolved in dimethyl sulfoxide (DMSO) are investigated for the first time in a battery-relevant solvent of nearly equivalent dielectric constant: mixed ethylene carbonate (EC)/dimethyl carbonate (DMC). The addition of a binary salt to each solution is investigated as a means to improve conductivity, and the diffusion coefficient of each species is tracked by pulse field gradient nuclear magnetic resonance (PFG-NMR). Through the 7Li NMR peak width and quantum chemistry calculations of the dissociation constant, it is shown that although the two solvent systems have nearly equivalent dielectric constants, the conductivity and transference number of the EC/DMC solutions are significantly lower as a result of poor dissociation of the sulfonate group on the polymer backbone. These results are the first study of polyelectrolyte properties in a battery-relevant solvent and clearly demonstrate the need to consider solvent properties other than the dielectric constant in the design of these electrolytes

Explicit-Duration Hidden Markov Model Inference of UP-DOWN States from Continuous Signals

Neocortical neurons show UP-DOWN state (UDS) oscillations under a variety of conditions. These UDS have been extensively studied because of the insight they can yield into the functioning of cortical networks, and their proposed role in putative memory formation. A key element in these studies is determining the precise duration and timing of the UDS. These states are typically determined from the membrane potential of one or a small number of cells, which is often not sufficient to reliably estimate the state of an ensemble of neocortical neurons. The local field potential (LFP) provides an attractive method for determining the state of a patch of cortex with high spatio-temporal resolution; however current methods for inferring UDS from LFP signals lack the robustness and flexibility to be applicable when UDS properties may vary substantially within and across experiments. Here we present an explicit-duration hidden Markov model (EDHMM) framework that is sufficiently general to allow statistically principled inference of UDS from different types of signals (membrane potential, LFP, EEG), combinations of signals (e.g., multichannel LFP recordings) and signal features over long recordings where substantial non-stationarities are present. Using cortical LFPs recorded from urethane-anesthetized mice, we demonstrate that the proposed method allows robust inference of UDS. To illustrate the flexibility of the algorithm we show that it performs well on EEG recordings as well. We then validate these results using simultaneous recordings of the LFP and membrane potential (MP) of nearby cortical neurons, showing that our method offers significant improvements over standard methods. These results could be useful for determining functional connectivity of different brain regions, as well as understanding network dynamics

Predicting youth participation in urban agriculture in Malaysia: insights from the theory of planned behavior and the functional approach to volunteer motivation

This study examines factors associated with the decision of Malaysian youth to participate in a voluntary urban agriculture program. Urban agriculture has generated significant interest in developing countries to address concerns over food security, growing urbanization and employment. While an abundance of data shows attracting the participation of young people in traditional agriculture has become a challenge for many countries, few empirical studies have been conducted on youth motivation to participate in urban agriculture programs, particularly in non-Western settings. Drawing on the theories of planned behavior and the functional approach to volunteer motivation, we surveyed 890 students from a public university in Malaysia about their intention to join a new urban agriculture program. Hierarchical regression findings indicated that the strongest predictor of participation was students’ attitude toward urban agriculture, followed by subjective norms, career motives and perceived barriers to participation. The findings from this study may provide useful information to the university program planners in Malaysia in identifying mechanisms for future students’ involvement in the program

Can environmental or occupational hazards alter the sex ratio at birth? A systematic review

More than 100 studies have examined whether environmental or occupational exposures of parents affect the sex ratio of their offspring at birth. For this review, we searched Medline and Web of Science using the terms ‘sex ratio at birth’ and ‘sex ratio and exposure’ for all dates, and reviewed bibliographies of relevant studies to find additional articles. This review focuses on exposures that have been the subject of at least four studies including polychlorinated biphenyls (PCBs), dioxins, pesticides, lead and other metals, radiation, boron, and g-forces. For paternal exposures, only dioxins and PCBs were consistently associated with sex ratios higher or lower than the expected 1.06. Dioxins were associated with a decreased proportion of male births, whereas PCBs were associated with an increased proportion of male births. There was limited evidence for a decrease in the proportion of male births after paternal exposure to DBCP, lead, methylmercury, non-ionizing radiation, ionizing radiation treatment for childhood cancer, boron, or g-forces. Few studies have found higher or lower sex ratios associated with maternal exposures. Studies in humans and animals have found a reduction in the number of male births associated with lower male fertility, but the mechanism by which environmental hazards might change the sex ratio has not yet been established

Theoretical vs. empirical discriminability:the application of ROC methods to eyewitness identification

Abstract ᅟ Receiver operating characteristic (ROC) analysis was introduced to the field of eyewitness identification 5 years ago. Since that time, it has been both influential and controversial, and the debate has raised an issue about measuring discriminability that is rarely considered. The issue concerns the distinction between empirical discriminability (measured by area under the ROC curve) vs. underlying/theoretical discriminability (measured by d’ or variants of it). Under most circumstances, the two measures will agree about a difference between two conditions in terms of discriminability. However, it is possible for them to disagree, and that fact can lead to confusion about which condition actually yields higher discriminability. For example, if the two conditions have implications for real-world practice (e.g., a comparison of competing lineup formats), should a policymaker rely on the area-under-the-curve measure or the theory-based measure? Here, we illustrate the fact that a given empirical ROC yields as many underlying discriminability measures as there are theories that one is willing to take seriously. No matter which theory is correct, for practical purposes, the singular area-under-the-curve measure best identifies the diagnostically superior procedure. For that reason, area under the ROC curve informs policy in a way that underlying theoretical discriminability never can. At the same time, theoretical measures of discriminability are equally important, but for a different reason. Without an adequate theoretical understanding of the relevant task, the field will be in no position to enhance empirical discriminability

Investigation of Solvent Type and Salt Addition in High Transference Number Nonaqueous Polyelectrolyte Solutions for Lithium Ion Batteries

High Li+ transference number electrolytes have attracted recent interest as a means to improve the energy density and rate capabilities of current lithium ion batteries. Here the viscosity and transport properties of a sulfonated polysulfone/poly(ethylene glycol) copolymer that displays both high transference number and high conductivity when dissolved in dimethyl sulfoxide (DMSO) are investigated for the first time in a battery-relevant solvent of nearly equivalent dielectric constant: mixed ethylene carbonate (EC)/dimethyl carbonate (DMC). The addition of a binary salt to each solution is investigated as a means to improve conductivity, and the diffusion coefficient of each species is tracked by pulse field gradient nuclear magnetic resonance (PFG-NMR). Through the 7Li NMR peak width and quantum chemistry calculations of the dissociation constant, it is shown that although the two solvent systems have nearly equivalent dielectric constants, the conductivity and transference number of the EC/DMC solutions are significantly lower as a result of poor dissociation of the sulfonate group on the polymer backbone. These results are the first study of polyelectrolyte properties in a battery-relevant solvent and clearly demonstrate the need to consider solvent properties other than the dielectric constant in the design of these electrolytes