Bayesian modelling and quantification of Raman spectroscopy

Raman spectroscopy can be used to identify molecules such as DNA by the characteristic scattering of light from a laser. It is sensitive at very low concentrations and can accurately quantify the amount of a given molecule in a sample. The presence of a large, nonuniform background presents a major challenge to analysis of these spectra. To overcome this challenge, we introduce a sequential Monte Carlo (SMC) algorithm to separate each observed spectrum into a series of peaks plus a smoothly-varying baseline, corrupted by additive white noise. The peaks are modelled as Lorentzian, Gaussian, or pseudo-Voigt functions, while the baseline is estimated using a penalised cubic spline. This latent continuous representation accounts for differences in resolution between measurements. The posterior distribution can be incrementally updated as more data becomes available, resulting in a scalable algorithm that is robust to local maxima. By incorporating this representation in a Bayesian hierarchical regression model, we can quantify the relationship between molecular concentration and peak intensity, thereby providing an improved estimate of the limit of detection, which is of major importance to analytical chemistry

Senior Recital: Riley Carson, Trumpet & Jake Gearrin, Trumpet

This recital is presented in partial fulfillment of requirements for the degree Bachelor of Music in Music Education. Messrs. Carson and Gearrin study trumpet with Ryan Moser.https://digitalcommons.kennesaw.edu/musicprograms/2275/thumbnail.jp

Mechani-Kits Senior Design Project

Studies suggest that when designed and executed well, hands-on activities can enhance student understanding of key mechanics concepts. Current products are expensive and typically not designed to meet a variety of learning objectives. Through the Mechanics of Inclusion and Inclusivity in Mechanics grant, the Cal Poly Physics and Engineering Departments are seeking to incorporate new hands-on activities into their courses. Our team has designed three inexpensive ”MechaniKits” to be used in physics, statics and dynamics courses [1]. This Final Design Review outlines our findings, objectives, and final designs for this project. It also explains our manufacturing and design verification plans. Although we were not able to build or test our final designs due to the campus closure caused by COVID-19, we completed extensive prototyping and testing prior to the closure and are confident in our designs. Once campus reopens, our sponsors in the Cal Poly Physics and Mechanical Engineering departments plan to have ten sets of each kit produced by the Cal Poly machine shops for classroom use

The bounded coalescent model : conditioning a genealogy on a minimum root date

The coalescent model represents how individuals sampled from a population may have originated from a last common ancestor. The bounded coalescent model is obtained by conditioning the coalescent model such that the last common ancestor must have existed after a certain date. This conditioned model arises in a variety of applications, such as speciation, horizontal gene transfer or transmission analysis, and yet the bounded coalescent model has not been previously analysed in detail. Here we describe a new algorithm to simulate from this model directly, without resorting to rejection sampling. We show that this direct simulation algorithm is more computationally efficient than the rejection sampling approach. We also show how to calculate the probability of the last common ancestor occurring after a given date, which is required to compute the probability density of realisations under the bounded coalescent model. Our results are applicable in both the isochronous (when all samples have the same date) and heterochronous (where samples can have different dates) settings. We explore the effect of setting a bound on the date of the last common ancestor, and show that it affects a number of properties of the resulting phylogenies. All our methods are implemented in a new R package called BoundedCoalescent which is freely available online

Inference of infectious disease transmission through a relaxed bottleneck using multiple genomes per host

In recent times, pathogen genome sequencing has become increasingly used to investigate infectious disease outbreaks. When genomic data is sampled densely enough amongst infected individuals, it can help resolve who infected whom. However, transmission analysis cannot rely solely on a phylogeny of the genomes but must account for the within-host evolution of the pathogen, which blurs the relationship between phylogenetic and transmission trees. When only a single genome is sampled for each host, the uncertainty about who infected whom can be quite high. Consequently, transmission analysis based on multiple genomes of the same pathogen per host has a clear potential for delivering more precise results, even though it is more laborious to achieve. Here we present a new methodology that can use any number of genomes sampled from a set of individuals to reconstruct their transmission network. Furthermore, we remove the need for the assumption of a complete transmission bottleneck. We use simulated data to show that our method becomes more accurate as more genomes per host are provided, and that it can infer key infectious disease parameters such as the size of the transmission bottleneck, within-host growth rate, basic reproduction number and sampling fraction. We demonstrate the usefulness of our method in applications to real datasets from an outbreak of Pseudomonas aeruginosa amongst cystic fibrosis patients and a nosocomial outbreak of Klebsiella pneumoniae

Toxicidade e produção de maçãs no sul do Brasil.

Explora as conexões entre uma polêmica apreensão de maçãs contaminadas no sul do Brasil, em 1989, e as reações da indústria da maçã às notícias da imprensa sobre o uso do agrotóxico nas plantações brasileiras. A problemática está inserida em análise mais ampla da ideia de toxicidade e de ‘perigo’, que começa a invadir os domínios público e privado quanto ao consumo de alimentos mais sadios e à ‘segurança alimentar’. Afirma que as respostas dos pomicultores ao problema seriam mais bem entendidas com a leitura histórica das interações entre a biologia da macieira, a agroecologia dessa monocultura e estruturas, atores e discursos que envolvem coletivos humanos e não humanos na região produtora de maçãs

Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol:prospective observational cohort study

Objective: To characterise the clinical features of patients admitted to hospital with coronavirus disease 2019 (covid-19) in the United Kingdom during the growth phase of the first wave of this outbreak who were enrolled in the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study, and to explore risk factors associated with mortality in hospital. Design: Prospective observational cohort study with rapid data gathering and near real time analysis. Setting: 208 acute care hospitals in England, Wales, and Scotland between 6 February and 19 April 2020. A case report form developed by ISARIC and WHO was used to collect clinical data. A minimal follow-up time of two weeks (to 3 May 2020) allowed most patients to complete their hospital admission. Participants: 20 133 hospital inpatients with covid-19. Main outcome measures: Admission to critical care (high dependency unit or intensive care unit) and mortality in hospital. Results: The median age of patients admitted to hospital with covid-19, or with a diagnosis of covid-19 made in hospital, was 73 years (interquartile range 58-82, range 0-104). More men were admitted than women (men 60%, n=12 068; women 40%, n=8065). The median duration of symptoms before admission was 4 days (interquartile range 1-8). The commonest comorbidities were chronic cardiac disease (31%, 5469/17 702), uncomplicated diabetes (21%, 3650/17 599), non-asthmatic chronic pulmonary disease (18%, 3128/17 634), and chronic kidney disease (16%, 2830/17 506); 23% (4161/18 525) had no reported major comorbidity. Overall, 41% (8199/20 133) of patients were discharged alive, 26% (5165/20 133) died, and 34% (6769/20 133) continued to receive care at the reporting date. 17% (3001/18 183) required admission to high dependency or intensive care units; of these, 28% (826/3001) were discharged alive, 32% (958/3001) died, and 41% (1217/3001) continued to receive care at the reporting date. Of those receiving mechanical ventilation, 17% (276/1658) were discharged alive, 37% (618/1658) died, and 46% (764/1658) remained in hospital. Increasing age, male sex, and comorbidities including chronic cardiac disease, non-asthmatic chronic pulmonary disease, chronic kidney disease, liver disease and obesity were associated with higher mortality in hospital. Conclusions: ISARIC WHO CCP-UK is a large prospective cohort study of patients in hospital with covid-19. The study continues to enrol at the time of this report. In study participants, mortality was high, independent risk factors were increasing age, male sex, and chronic comorbidity, including obesity. This study has shown the importance of pandemic preparedness and the need to maintain readiness to launch research studies in response to outbreaks. Study registration: ISRCTN66726260

Open source clinical science for emerging infections

International audienc