Information content and aerosol property retrieval potential for different types of in situ polar nephelometer data

Polar nephelometers are in situ instruments used to measure the angular distribution of light scattered by aerosol particles. These types of measurements contain substantial information about the properties of the aerosol being probed (e.g. concentrations, sizes, refractive indices, shape parameters), which can be retrieved through inversion algorithms. The aerosol property retrieval potential (i.e. information content) of a given set of measurements depends on the spectral, polarimetric, and angular characteristics of the polar nephelometer that was used to acquire the measurements. To explore this issue quantitatively, we applied Bayesian information content analysis and calculated the metric degrees of freedom for signal (DOFS) for a range of simulated polar nephelometer instrument configurations, aerosol models and test cases, and assumed levels of prior knowledge about the variances of specific aerosol properties. Assuming a low level of prior knowledge consistent with an unconstrained ambient/field measurement setting, we demonstrate that even very basic polar nephelometers (single wavelength, no polarization capability) will provide informative measurements with a very high retrieval potential for the size distribution and refractive index state parameters describing simple unimodal, spherical test aerosols. As expected, assuming a higher level of prior knowledge consistent with well-constrained laboratory applications leads to a reduction in potential for information gain via performing the polarimetric measurement. Nevertheless, we show that in this situation polar nephelometers can still provide informative measurements: e.g. it can be possible to retrieve the imaginary part of the refractive index with high accuracy if the laboratory setting makes it possible to keep the probed aerosol sample simple. The analysis based on a high level of prior knowledge also allows us to better assess the impact of different polar nephelometer instrument design features in a consistent manner for retrieved aerosol parameters. The results indicate that the addition of multi-wavelength and/or polarimetric measurement capabilities always leads to an increase in information content, although in some cases the increase is negligible, e.g. when adding a fourth, near-IR measurement wavelength for the retrieval of unimodal size distribution parameters or if the added polarization component has high measurement uncertainty. By considering a more complex bimodal, non-spherical-aerosol model, we demonstrate that performing more comprehensive spectral and/or polarimetric measurements leads to very large benefits in terms of the achieved information content. We also investigated the impact of angular truncation (i.e. the loss of measurement information at certain scattering angles) on information content. Truncation at extreme angles (i.e. in the near-forward or near-backward directions) results in substantial decreases in information content for coarse-aerosol test cases. However for fine-aerosol test cases, the sensitivity of DOFS to extreme-angle truncation is noticeably smaller and can be further reduced by performing more comprehensive measurements. Side angle truncation has very little effect on information content for both the fine and coarse test cases. Furthermore, we demonstrate that increasing the number of angular measurements generally increases the information content. However, above a certain number of angular measurements (∼20–40) the observed increases in DOFS plateau out. Finally, we demonstrate that the specific placement of angular measurements within a nephelometer can have a large impact on information content. As a proof of concept, we show that a reductive greedy algorithm based on the DOFS metric can be used to find optimal angular configurations for given target aerosols and applications.</p

Myopic regression after photorefractive keratectomy: a retrospective cohort study

Background: Myopic regression is a major complication of photorefractive keratectomy (PRK). The rates and causes vary considerably among different studies. This study aimed to investigate myopic regression at six months after myopic PRK. Methods: In this retrospective cohort study, we included all eligible patients with myopia ranging from - 0.75 to - 9 D, aged 18 to 50 years, who underwent PRK by a single surgeon with the availability of preoperative and postoperative data at six months after the initial procedure. All participants underwent comprehensive ophthalmic examinations preoperatively and at six months post-PRK. Overcorrection was planned based on the participant’s age range to achieve the desired refractive result after PRK. All patients received the same postoperative antibiotic and steroid eye drops in a similar dosage regimen, and the contact lenses were removed after complete corneal epithelial healing. Based on the spherical equivalent of refraction six months after PRK, eyes without and with myopic regression were allocated into groups 1 and 2, respectively. Results: We included 254 eyes of 132 patients who underwent myopic PRK with a mean (standard deviation) age of 30.12 (7.48) years; 82 (62.12%) were women and 50 (37.88%) were men. The frequency of myopic regression was significantly lower in patients with younger age, lower preoperative cylindrical refraction, and lower ablation depth (all P &lt; 0.05). Overcorrection was more successful in eyes with low myopia than in eyes with high myopia (P &lt; 0.05). The highest frequency of myopic regression occurred in eyes with moderate myopia (25.68%), followed by eyes with high myopia (20.0%) and low myopia (6.54%). Among different age groups, patients aged less than or equal to 30 years had a lower frequency of myopic regression. The frequency of myopic regression in the different age groups was 5.0% at 18-20 years, 7.46% at 26-30 years, 12.28% at 21-25 years, 21.31% at 31-35 years, and 26.53% at 36-50 years. Conclusions: Overcorrection was more successful in eyes with low myopia than in eyes with high myopia. The success rate was higher in younger patients with lower astigmatism and ablation depths. Myopic regression was most frequent in eyes with moderate myopia, followed by those with high and low myopia. Further studies should replicate our findings over a longer follow-up period with a larger sample size before generalization is warranted

Information content and aerosol property retrieval potential for different types of in situ polar nephelometer data

Polar nephelometers are in situ instruments used to measure the angular distribution of light scattered by aerosol particles. These type of measurements contain substantial information about the properties of the aerosol being probed (e.g. concentrations, sizes, refractive indices, shape parameters), which can be retrieved through inversion algorithms. The aerosol property retrieval potential (i.e., information content) of a given set of measurements depends on the spectral, polarimetric and angular characteristics of the polar nephelometer that was used to acquire it. To explore this issue quantitatively, we applied Bayesian information content analysis and calculated the metric Degrees of Freedom for Signal (DOFS) for a range of simulated polar nephelometer instrument configurations, aerosol models and test cases, and assumed levels of prior knowledge about the variances of specific aerosol properties. Assuming a low level of prior knowledge consistent with an unconstrained ambient/field measurement setting, we demonstrate that even very basic polar nephelometers (single wavelength, no polarization capability) will provide informative measurements with very high retrieval potential for the size distribution and refractive index state parameters describing simple unimodal, spherical test aerosols. As expected, assuming a higher level of prior knowledge consistent with well constrained laboratory applications leads to a reduction in potential for information gain via performing the polarimetric measurement. This analysis allows us to better assess the impact of different polar nephelometer instrument design features in a consistent manner for retrieved aerosol parameters. The results indicate that the addition of multi-wavelength and/or polarimetric measurement capabilities always leads to an increase in information content, although in some cases the increase is negligible: e.g. when adding a fourth, near-IR measurement wavelength for the retrieval of unimodal size distribution parameters, or if the added polarization component has high measurement uncertainty. By considering a more complex bimodal, non-spherical aerosol model, we demonstrate that performing the more comprehensive spectral and/or polarimetric measurements leads to very large benefits in terms of the achieved information content. We also investigated the impact of angular truncation (i.e., the loss of measurement information at certain scattering angles) on information content. Truncation at extreme angles (i.e., in the near-forward or &ndash;backward directions) results in substantial decreases in information content for coarse aerosol test cases. However for fine aerosol test cases, the sensitivity of DOFS to extreme angle truncation is noticeably smaller and can be further reduced by performing more comprehensive measurements. Side-angle truncation has very little effect on information content for both the fine and coarse test cases. Furthermore, we demonstrate that increasing the number of angular measurements generally increases the information content. However, above a certain number of angular measurements (~20&ndash;40) the observed increases in DOFS plateau out. Finally, we demonstrate that the specific placement of angular measurements within a nephelometer can have a large impact on information content. As a proof-of-concept, we show that a reductive greedy algorithm based on the DOFS metric can be used to find optimal angular configurations for given target aerosols and applications.</p

Characteristics and sources of fluorescent aerosols in the central Arctic Ocean

The Arctic is sensitive to cloud radiative forcing. Due to the limited number of aerosols present throughout much of the year, cloud formation is susceptible to the presence of cloud condensation nuclei and ice nucleating particles (INPs). Primary biological aerosol particles (PBAP) contribute to INPs and can impact cloud phase, lifetime, and radiative properties. We present yearlong observations of hyperfluorescent aerosols (HFA), tracers for PBAP, conducted with a Wideband Integrated Bioaerosol Sensor, New Electronics Option during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition (October 2019–September 2020) in the central Arctic. We investigate the influence of potential anthropogenic and natural sources on the characteristics of the HFA and relate our measurements to INP observations during MOSAiC. Anthropogenic sources influenced HFA during the Arctic haze period. But surprisingly, we also found sporadic “bursts” of HFA with the characteristics of PBAP during this time, albeit with unclear origin. The characteristics of HFA between May and August 2020 and in October 2019 indicate a strong contribution of PBAP to HFA. Notably from May to August, PBAP coincided with the presence of INPs nucleating at elevated temperatures, that is, &amp;gt;−9°C, suggesting that HFA contributed to the “warm INP” concentration. The air mass residence time and area between May and August and in October were dominated by the open ocean and sea ice, pointing toward PBAP sources from within the Arctic Ocean. As the central Arctic changes drastically due to climate warming with expected implications on aerosol–cloud interactions, we recommend targeted observations of PBAP that reveal their nature (e.g., bacteria, diatoms, fungal spores) in the atmosphere and in relevant surface sources, such as the sea ice, snow on sea ice, melt ponds, leads, and open water, to gain further insights into the relevant source processes and how they might change in the future.</jats:p

Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition

The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90ĝ€¯d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and "hotspots"of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean-atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question

A Survey of a Cholera Epidemic in Aran va Bidgol City in Summer 2011

Abstract Background and purpose:Cholera is an endemic disease in Iran and in some cases each year from around the country report. The aim of this study was to evaluate the prevalence of the disease cholera among people suffering from acute diarrhea in the AranvaBidgol. Materials and Methods:In this study, patients with acute diarrhea were examined for cholera detection in the city of AranvaBidgol in summer 2011. All 294 patients with acute diarrhea referred to rectal swabs in the laboratory of health centers and in the specific microbial culture medium of thiosulfate citrate bile sucrose agar. Furthermore, some information about health behaviors, such as drinking water supply, status of food preservation, toilets status, drinks, and food consumption in the outdoors was collected from all participants in this study. Results:Laboratory results showed that Vibrio cholerae isolated from 21 patient stool cultures and these patients were to have cholera disease. About 23.81% of the patients were male and 76.19% were female. Fifteen patients (71.43%) were Nag form of cholera and 6 patients (28.57%) were diagnosed with Eltor form of cholera. According the completed questionnaire by patients the origin of V. cholerae has been announced consumption of raw vegetables (42.85%) and springs and subterranean water (38.59%). Conclusion:Consumption of raw vegetables and water (springs and subterranean) are the important factors for mobility to cholera and it should be more considered prevention and control program and monitoring methods about using of safe water and food

Wideband integrated bioaerosol sensor (WIBS) excited particle normalized size distributions (dN/dlogDp) measured in the Swiss container during MOSAiC 2019/2020

These datasets contain normalized size distributions (dN/dlogDp) of excited particles of sizes 0.5 to 20 μm (optical diameter). The normalized size distribution datasets are split into 20 size bins: 0.5 - 0.6 μm, 0.6 - 0.72 μm, 0.72 - 0.87 μm, 0.87 - 1.05 μm, 1.05 - 1.26 μm, 1.26 - 1.51 μm, 1.51 - 1.82 μm, 1.82 - 2.19 μm, 2.19 - 2.63 μm, 2.63 - 3.16 μm, 3.16 - 3.8 μm, 3.8 - 4.57 μm, 4.57 - 5.5 μm, 5.5 - 6.61 μm, 6.61 - 7.95 μm, 7.95 - 9.56 μm, 9.56 - 11.50 μm, 11.5 - 13.83 μm, 13.83- 16.63 μm and 16.63 - 20 μm. The data were measured by a WIBS-NEO (Wideband Integrated Bioaerosol Sensor, model New Electronics option) by droplet measurement techniques ltd. The data were processed using the IGOR WIBS toolkit V1.36 (DMT) and python version 3.9.7. These datasets have been averaged to 1 hour time resolution. The datasets were cleaned from local pollution sources by applying a pollution flag developed by Beck et al. (2022a,b), which is based on the rate of change in particle number concentration with 1 min time resolution. Data points with more than 10 polluted minutes within an hour were removed from the WIBS datasets. Time periods with zero filter measurements and time periods with unstable flow that affected number concentrations have been removed from the dataset