En 1859 les physicien et chimiste allemands G. Kirchhoff et R. Bunsen ont decouvert que chaque element chimique dispose d'une signature spectrale unique. Suite a cela, la spectrometrie s'est imposee comme un outil d'analyse majeur y compris en astrophysique (notamment grâce a l'italien A. Secchi). Ainsi la plus grande partie des informations dont nous disposons sur les objets astrophysiques proviennent de l'analyse spectrale ; la decouverte des premieres planetes extra-solaires est meme due a celle-ci. Depuis ses debuts, cette technique a trouve de nombreuses applications dans des domaines aussi varies que la medecine, la detection de gaz ou encore l'etude des polluants. Dans cette these nous nous proposons d'etudier et de developper un nouveau type de spectrometres nommes SWIFTS (pour Stationary Wave Integrated Fourier Transform Spectrometer) bases sur la detection d'une onde stationnaire obtenue a l'interieur d'un guide optique. Pour ce faire, nous utilisons une technique originale dite de " detection evanescente ". Dans cette these nous etudions et modelisons les performances d'un tel spectrometre notamment en utilisant une methode matricielle et une methode de decomposition dans le domaine de Fourier. Les premiers prototypes ont ete realises dans les bandes I et R du systeme photometrique de Johnson, ces bandes ayant ete choisies pour la facilite d'obtention de detecteurs et guides optiques efficaces. Etant donne les technologies disponibles, ces prototypes ne peuvent atteindre l'efficacite theorique maximale d'un SWIFTS (environ 73%) ; neanmoins elles nous ont permis de mesurer des resolutions de l'ordre du cm-1 sur un large domaine spectral (650 nm a 900 nm).

Etude et réalisation d'un spectromètre intégré à transformée de Fourier (SWIFTS)

Authors writing since the late 1800s have identified political sophistication as a consequence of the requirement to vote Many recent studies in the flourishing empirical literature on the secondary effects of compulsory voting find evidence of this relationship This suggests that the criteria compelled voters use to choose between candidates should differ from those who are not obligated to turn out, with personal qualities such as gender and family background mattering more for voluntary voters To test this, I amalgamate a conjoint experiment with a regression discontinuity design, exploiting age-based cutoffs in the application of compulsory voting This allows me to causally identify the impact of compulsory voting on the attributes individuals take into account when choosing between candidates While I recover compulsory voting's upward impact on turnout, I find no evidence that compelled and voluntary voters differ in how they select candidates

Does Compulsory Voting Affect How Voters Choose? A Test Using a Combined Conjoint and Regression Discontinuity Analysis

<sec> <title>BACKGROUND</title> Improvement in quality and patient safety outcomes have been at the forefront of the U.S. healthcare system. Policies advocate for implementing different electronic health records (EHR) levels to support this effort. Several studies have demonstrated mixed results on the impact of EHR on quality and safety outcomes. </sec> <sec> <title>OBJECTIVE</title> Our study delves deeper into gaining an understanding of this influence on hospitals that have adopted various levels of EHR, especially intermediate and comprehensive. </sec> <sec> <title>METHODS</title> Using a longitudinal study design for general acute care hospitals within the U.S., we examine the relationship between intermediate and comprehensive EHR on quality (readmission rates for pneumonia and COPD) and safety (adverse incident rate) using a random-effects model. Our national sample consisted of 7,084 hospital-year observations from 2014-2016. </sec> <sec> <title>RESULTS</title> : Hospitals with intermediate EHR had about an 8% decrease in 30-day readmission for Pneumonia compared to the hospitals with no intermediate EHR, with comprehensive EHR experienced a decrease of about 1% in adverse incident rate compared to hospitals that did not have comprehensive EHR. </sec> <sec> <title>CONCLUSIONS</title> Our study buttresses prior findings that simply having EHR may not have an effect on outcomes, and a more targeted, meaningful use would need to be ensured. </sec> 

Levels of Electronic Health Records (EHR) Implementation and their Influence on Quality and Safety (Preprint)

<sec> <title>BACKGROUND</title> Elevated psychological distress has demonstrated impacts on individuals’ health. Reliable and efficient ways to detect distress are key to early intervention. Artificial Intelligence has the potential to detect states of emotional distress in an accurate, efficient and timely manner. </sec> <sec> <title>OBJECTIVE</title> To automatically classify short segments of speech obtained from callers to national suicide prevention helpline services, according to low versus high psychological distress, using a range of voice biomarkers in combination with machine learning approaches. </sec> <sec> <title>METHODS</title> One hundred and twenty telephone call recordings were initially converted to 16-bit Pulse Code Modulation format. Short variable length segments of each call were rated on psychological distress using the Distress Thermometer by the responding counselor and a second team of psychologists blinded to the initial ratings (n=6). Nineteen voice biomarkers were derived using 40ms speech frames derived from each annotated segment. Candidate biomarkers were reduced using Lasso regression, validated by generalised additive mixed effects regression, accounting for non-linearity, autocorrelation and moderation by sex. Speech frames were then grouped using k-means clustering based on the selected biomarkers. Finally, component-wise gradient boosting was used to classify each speech frame according to low versus high psychological distress. Classification accuracy was confirmed via leave one out cross validation ensuring that speech segments from single callers were not used in both the training and test data. </sec> <sec> <title>RESULTS</title> Using twelve voice biomarkers, 686/747 speech segments were successfully classified, AUCROC = 93.8% (95% CI = 91.47, 94.6) and AUCPR = 94.8 (95% CI = 93.0, 96.5). When experiencing elevations in psychological distress, male speakers spoke with increasing loudness, higher frequencies in the 75th percentile of frequencies, but with poorer clarity of speech. In contrast, when experiencing psychological distress, the frequencies with which female callers spoke decreased in the highest quartile of frequencies, but exhibited increased clarity of speech. </sec> <sec> <title>CONCLUSIONS</title> The high level of accuracy achieved suggests possibilities for real-time detection of psychological distress in helpline settings and has potential uses in pre-emptive triage. </sec> <sec> <title>CLINICALTRIAL</title> ANZCTR, ACTRN12622000486729 </sec> 

Using Voice Biomarkers to Classify Psychological Distress in Adult Helpline Callers: A Retrospective Observational Study (Preprint)

Assessment of quality, readability and endorsement of online information on WeChat official accounts for patients with rare neurological diseases: a cross-sectional study (Preprint)

https://link.springer.com/content/pdf/10.1007/978-3-662-57960-2_207.pdf

16O18O16O Vibrational Energy and Rotational and Centrifugal Distortion Constants for the (011), and (110) Interacting States. Band Centers of the ν2 + ν3 and ν1 + ν2

This chapter provides the Coriolis coupling constants for the (110) and (011) vibrational states of 16O3 measured using Fourier transform spectroscopy.

https://link.springer.com/content/pdf/10.1007%2F978-3-662-57960-2_9.pdf

16 O 3 Coriolis Coupling Constants for the (110) and (011) Vibrational States

/pdf/16o3-band-centers-integrated-band-intensities-and-dipole-2jl0yiy88s.pdf

16O3 Band Centers, Integrated Band Intensities, and Dipole Transition Moment Operator Constants for the 2ν2 + 2ν3, and 2ν1 + 2ν2 B-Type Bands, and the ν1 + 2ν2 + ν3, A-Type Band

/pdf/18o16o18o-resonance-coupling-constants-for-the-dark-016-205-ghclc848uc.pdf

Nathalie Picqué

Papers

16O18O16O Vibrational Energy and Rotational and Centrifugal Distortion Constants for the (011), and (110) Interacting States. Band Centers of the ν2 + ν3 and ν1 + ν2

16 O 3 Coriolis Coupling Constants for the (110) and (011) Vibrational States

16O3 Band Centers, Integrated Band Intensities, and Dipole Transition Moment Operator Constants for the 2ν2 + 2ν3, and 2ν1 + 2ν2 B-Type Bands, and the ν1 + 2ν2 + ν3, A-Type Band

18O16O18O Resonance Coupling Constants for the Dark (016), (205) and Dark (044) Interacting States