Modelling Li+ Ion Battery Electrode Properties

We formulated two detailed models for an electrolytic cell with particulate electrodes based on a lithium atom concentration dependent Butler-Volmer condition at the interface between electrode particles and the electrolyte. The first was based on a dilute-ion assumption for the electrolyte, while the second assumed that Li ions are present in excess. For the first, we used the method of multiple scales to homogenize this model over the microstructure, formed by the small lithium particles in the electrodes. For the second, we gave rigorous bounds for the effective electrochemical conductivity for a linearized case. We expect similar results and bounds for the "full nonlinear problem" because variational results are generally not adversely affected by a sinh term. Finally we used the asymptotic methods, based on parameters estimated from the literature, to attain a greatly simplified one-dimensional version of the original homogenized model. This simplified model accounts for the fact that diffusion of lithium atoms within individual electrode particles is relatively much faster than that of lithium ions across the whole cell so that lithium ion diffusion is what limits the performance of the battery. However, since most of the potential drop occurs across the Debye layers surrounding each electrode particle, lithium ion diffusion only significantly affects cell performance if there is more or less complete depletion of lithium ions in some region of the electrolyte which causes a break in the current flowing across the cell. This causes catastrophic failure. Providing such failure does not occur the potential drop across the cell is determined by the concentration of lithium atoms in the electrode particles. Within each electrode lithium atom concentration is, to leading order, a function of time only and not of position within the electrode. The depletion of electrode lithium atom concentration is directly proportional to the current being drawn off the cell. This leads one to expect that the potential of the cell gradually drops as current is drawn of it. We would like to emphasize that all the homogenization methods employed in this work give a systematic approach for investigating the effect that changes in the microstructure have on the behaviour of the battery. However, due to lack of time, we have not used this method to investigate particular particle geometries

The Effect of Lockdown Period during the COVID-19 Pandemic on Air Quality in Sydney Region, Australia.

In early 2020 from April to early June, the metropolitan area of Sydney as well as the rest of New South Wales (NSW, Australia) experienced a period of lockdown to prevent the spread of COVID-19 virus in the community. The effect of reducing anthropogenic activities including transportation had an impact on the urban environment in terms of air quality which is shown to have improved for a number of pollutants, such as Nitrogen Dioxides (NO2) and Carbon Monoxide (CO), based on monitoring data on the ground and from a satellite. In addition to primary pollutants CO and NOx emitted from mobile sources, PM2.5 (primary and secondary) and secondary Ozone (O3) during the lockdown period will also be analyzed using both statistical methods on air quality data and the modelling method with emission and meteorological data input to an air quality model. By estimating the decrease in traffic volume in the Sydney region, the corresponding decrease in emission input to the Weather Research and Forecasting—Community Multiscale Air Quality Modelling System (WRF-CMAQ) air quality model is then used to estimate the effect of lockdown on the air quality especially CO, NO2, O3, and PM2.5 in the Greater Metropolitan Region (GMR) of Sydney. The results from both statistical and modelling methods show that NO2, CO, and PM2.5 levels decreased during the lockdown, but O3 instead increased. However, the change in the concentration levels are small considering the large reduction of ~30% in traffic volum

Prevalence and Factors Associated With Mental Health Symptoms in Adults Undergoing Covid-19 Testing

BACKGROUND AND OBJECTIVE: Understanding the mental health impact of the COVID-19 pandemic on persons receiving COVID-19 testing will help guide mental health interventions. We aimed to determine the association between sociodemographic factors and mental health symptoms at 8 weeks (baseline) after a COVID-19 test, and compare prevalence of mental health symptoms at baseline to those at 16-week follow-up. MATERIALS AND METHODS: Prospective cohort study of adults who received outpatient COVID-19 testing at primary care clinics. Logistic regression analyses were used to assess the association between sociodemographic characteristics and COVID-19 test results with mental health symptoms. Mental health symptoms reported at baseline were compared to symptoms at 16 weeks follow-up using conditional logistic regression analyses. RESULTS: At baseline, a total of 124 (47.51%) participants reported at least mild depressive symptoms, 110 (42.15%) participants endorsed at least mild anxiety symptoms, and 94 participants (35.21%) endorsed hazardous use of alcohol. Females compared to males were at increased risk of at least mild depressive symptoms at baseline (Adjusted Odds Ratio (AOR): 2.08; 95% CI: 1.14-3.79). The odds of at least mild depressive symptoms was significantly lower among those residing in zip codes within the highest quartile compared to lowest quartile of household income (AOR: 0.37; 95% CI: 0.17-0.81). Also, non-Hispanic Whites had significantly higher odds of reporting hazardous alcohol use compared to non-Whites at baseline (AOR: 1.94; 95% CI: 1.05-3.57). The prevalence of mental health symptoms remained elevated after 16 weeks. CONCLUSION AND RELEVANCE: We found a high burden of symptoms of depression and anxiety as well as hazardous alcohol use in a diverse population who received testing for COVID-19 in the primary care setting. Primary care providers need to remain vigilant in screening for symptoms of mental health disorders in patients tested for COVID-19 well after initial testing

Publisher Correction: FGF signalling controls the specification of hair placode-derived SOX9 positive progenitors to Merkel cells.

The originally published version of this Article contained an error in Figure 2. In panel e, the blue bar was incorrectly labelled 'KRT8(+)/TOMATO(-)'. Furthermore, during the process of preparing a correction, the publication date of the Article was inadvertently changed to June 20th 2018. Both of these errors have been corrected in the PDF and HTML versions of the Article

FGF signalling controls the specification of hair placode-derived SOX9 positive progenitors to Merkel cells

Merkel cells are innervated mechanosensory cells responsible for light-touch sensations. In murine dorsal skin, Merkel cells are located in touch domes and found in the epidermis around primary hairs. While it has been shown that Merkel cells are skin epithelial cells, the progenitor cell population that gives rise to these cells is unknown. Here, we show that during embryogenesis, SOX9-positive (+) cells inside hair follicles, which were previously known to give rise to hair follicle stem cells (HFSCs) and cells of the hair follicle lineage, can also give rise to Merkel Cells. Interestingly, while SOX9 is critical for HFSC specification, it is dispensable for Merkel cell formation. Conversely, FGFR2 is required for Merkel cell formation but is dispensable for HFSCs. Together, our studies uncover SOX9(+) cells as precursors of Merkel cells and show the requirement for FGFR2-mediated epithelial signalling in Merkel cell specification.Peer reviewe

Representational oligonucleotide microarray analysis: A high-resolution method to detect genome copy number variation

We have developed a methodology we call ROMA (representational oligonucleotide microarray analysis), for the detection of the genomic aberrations in cancer and normal humans. By arraying oligonucleoticle probes designed from the human genome sequence, and hybridizing with "representations" from cancer and normal cells, we detect regions of the genome with altered "copy number." We achieve an average resolution of 30 kb throughout the genome, and resolutions as high as a probe every 15 kb are practical. We illustrate the characteristics of probes on the array and accuracy of measurements obtained using ROMA. Using this methodology, we identify variation between cancer and normal genomes, as well as between normal human genomes. In cancer genomes, we readily detect amplifications and large and small homozygous and hemizygous deletions. Between normal human genomes, we frequently detect large (100 kb to I Mb) deletions or duplications. Many of these changes encompass known genes. ROMA will assist in the discovery of genes and markers important in cancer, and the discovery of loci that may be important in inherited predispositions to disease

Determination of CP and CPT violation parameters in the neutral kaon system using the Bell-Steinberger relation and data from the KLOE experiment

We present an improved determination of the CP and CPT violation parameters Re(epsilon) and Im(delta) based on the unitarity condition (Bell-Steinberger relation) and on recent results from the KLOE experiment. We find Re(epsilon) = (159.6 \pm 1.3)10^-5 and Im(delta) = (0.4 \pm 2.1)10^-5, consistent with no CPT violation.Comment: Submitted to JHE

Multidrug resistant pulmonary tuberculosis treatment regimens and patient outcomes: an individual patient data meta-analysis of 9,153 patients.

Treatment of multidrug resistant tuberculosis (MDR-TB) is lengthy, toxic, expensive, and has generally poor outcomes. We undertook an individual patient data meta-analysis to assess the impact on outcomes of the type, number, and duration of drugs used to treat MDR-TB