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Objectives To describe understanding of the irreversible nature of permanent contraception and knowledge and attitudes about long-acting reversible contraception (LARC) among individuals seeking and not seeking permanent contraception. Methods We performed a cross-sectional survey among patients with Medicaid insurance attending an obstetrics and gynecology clinic in [location]. The survey consisted of 20 true/false and Likert questions assessing knowledge and perceptions about permanent contraception and LARC. Sixty-seven participants were needed to detect a small-to-medium Cohen's effect size f.sup.2 = 0.20, with 95% power and alpha = 0.05. Results Ninety potential participants were contacted and 67 were recruited. Forty-three participants desired permanent contraception and 24 did not. Approximately half of all participants were not aware that permanent contraception is irreversible. Participants who desired permanent contraception had lower LARC knowledge scores (62% correct versus 70%, p = 0.042) and more negative perceptions about LARC (54% versus 38%, p = 0.048). Fewer participants desiring permanent contraception identified LARC efficacy as equal to permanent contraception (32% versus 83%, p < 0.01), and fewer would consider using LARC (intrauterine device: 23% versus 58%, p < 0.01; implant: 16% versus 46%, p < 0.01). These differences persisted in multivariable models adjusting for age, gravidity, and parity. Conclusions for Practice Individuals who desire permanent contraception may not be aware of its permanence, or of equally effective alternatives. They were also found to have more negative perceptions of LARC in our sample. Additional research is needed to understand factors underlying these differences. Counseling practices should be tailored to ensure accurate knowledge about permanent contraception and LARC for all people seeking to avoid pregnancy., Author(s): Andrea Leung [sup.1] , Andrew Loh [sup.1] , Sara Pentlicky [sup.1] , Elizabeth P. Gurney [sup.1] [sup.2] Author Affiliations: (1) grid.239276.b, 0000 0001 2181 6998, Department of Obstetrics & [...]

Micro- and nanoplastics (MNPs) are increasingly found in all realms of the world, including water and soil. Now, there is growing concern over this type of pollution in the air. Many well-established techniques exist for detecting particulate matter (PM) in the air. They are low-cost and handheld, and some of them even allow direct detection from the air. While various MNP detection methods have been demonstrated, airborne MNP detection methods depend on expensive laboratory instruments. This review paper examines the current analytic methods used to identify PM and MNP and discusses their similarities and differences. PM can be detected directly from the air primarily via light scattering, while direct air detection of MNP has not been demonstrated. Sampling steps allow both PM and MNP to be detected from the air. Since PM detection does not require the type identification of materials, mass detection has been utilized, including gravimetric and microbalance methods. Simple optical detection based on absorbance or reflectance and electrical current measurements have also been used for PM detection. However, MNP detection does require type identification, including plastic vs non-plastic or the type of plastic, requiring more sophisticated methods, including spectroscopic and thermal analyses. Microscopic identification has been utilized for both PM and MNP detection since it can identify the size, morphology, autofluorescence, and spectroscopic properties. Machine learning algorithms can also analyze the microscopic images and spectra to identify the type of PM and MNP. While microscopic identification previously required a bulky benchtop microscope, a portable or even handheld microscope has become available, allowing it to detect MNPs in a portable, low-cost manner. [ABSTRACT FROM AUTHOR]

Plotting two-parameter confidence regions is nontrivial. Numerical methods often rely on a computationally expensive grid-like exploration of the parameter space. A recent advance reduces the two-dimensional problem to many one-dimensional problems employing a trigonometric transformation that assigns an angle ϕ from the maximum likelihood estimator, and an unknown radial distance to its confidence region boundary. This paradigm shift can improve computational runtime by orders of magnitude, but it is not robust. Specifically, parameters differing greatly in magnitude and/or challenging nonconvex confidence region shapes make the plot susceptible to inefficiencies and/or inaccuracies. This article improves the technique by (i) keeping confidence region boundary searches in the parameter space, (ii) selectively targeting confidence region boundary points in lieu of uniformly spaced ϕ angles from the maximum likelihood estimator and (iii) enabling access to regions otherwise unreachable due to multiple roots for select ϕ angles. Two heuristics are given for ϕ selection: an elliptic-inspired angle selection heuristic and an intelligent smoothing search heuristic. Finally, a jump-center heuristic permits plotting otherwise inaccessible multiroot regions. This article develops these heuristics for two-parameter likelihood-ratio-based confidence regions associated with univariate probability distributions, and introduces the R conf package, which automates the process and is publicly available via CRAN. [ABSTRACT FROM AUTHOR]

Biodegradation patterns of oil in four distinct phases were compared over a 14-day series of exposures. The dispersibility and stability of oil droplets in the water column were important factors affecting oil biodegradation. Due to the stability of oil droplets with particle interactions, oil-suspended particulate matter aggregates (OSA) showed a five-fold enhancement in biodegradation compared to non-dispersed oil. The reduction of total petroleum hydrocarbons was highest in OSA (51.45%), followed by chemically dispersed oil (33.5%), oil film (21.6%), and water-accommodated fractions (WAF, 14.3%). Polycyclic aromatic hydrocarbon (PAH) profiles and percentage weathering plots showed that reductions in PAHs in WAF, oil film, and chemically dispersed oil were mainly due to evaporation (41.5–69.5%) and only partially due to biodegradation (7.4–16.3%). However, the reduction of PAHs in OSA was driven more by biodegradation (36.8%) than evaporation (29.7%). The strong PAH–particle interactions in OSA inhibited evaporation of PAHs and enhanced microorganism biodegradation in the water column. Unlabelled Image • Effects of suspended particles on biodegradation of oil were investigated using OSA. • Four environmentally feasible forms of oil were compared in terms of biodegradation. • Each form of oil showed distinct biodegradation kinetics and chemical patterns. • Percent weathering plots were used to evaluate biodegradation versus physical weathering. • OSA showed a significant enhancement of biodegradation compared to other forms of oil. [ABSTRACT FROM AUTHOR]

Abstract In this study, the fate of residual oils was investigated during remediation activities for a year after the Wu Yi San oil spill. Microscope observations showed that relatively large amounts of oil-suspended particulate matter aggregate (OSA) were formed. Negatively buoyant OSA was the dominant form (>95%), followed by neutrally (~5%) and positively buoyant (<1%) forms. To elucidate the dominance of negative buoyancy OSA, physicochemical properties of the mineral and residual oils were identified. Chemical analysis showed that the weathering percentage of residual oils was 43.7 ± 2.59%, which was the driving factor for sedimentation of OSA. As the density of oil increased with weathering stages, the density of OSA also increased simultaneously. These results showed that, during mechanical remediation activities, resurfaced residual oils can form negative buoyancy OSA which tends to sink and transfers oil contaminants from intertidal to benthic environments. Highlights • Resuspended residual oils formed oil-suspended particulate matter aggregate (OSA) during remediation activities. • Dominant shape of OSA was oil coated particle with negative buoyancy. • Highly weathered oil was the main cause of negative buoyancy OSA. • Physical remediation activities can transfer residual oil from intertidal to subtidal in the form of OSA. [ABSTRACT FROM AUTHOR]

Abstract Suspended particulate matter (SPM) refers to fine-grained materials that are suspended in water columns. By providing a surface for the adsorption of non-polar organic compounds, SPM is a carrier for persistent and toxic contaminants. A wide range of organic pollutants, including polycyclic aromatic hydrocarbons (PAHs), can be adsorbed onto SPM. The formation of particle-associated PAHs can sequentially increase the potential for exposure to and bioaccumulation by organisms. Until recently, most oil exposure studies were performed using freely dissolved and dispersed forms, and therefore the role of SPM in influencing the bioavailability and bioaccumulation of PAHs has not been considered. This study found that SPM influences the bioavailability of petrogenic PAHs in the water column and their potential for accumulation in oysters. SPM significantly enhanced the water column entrainment of petrogenic PAHs, thus increasing the potentials for uptake by exposed organisms. PAHs in the water column was highest from mechanically dispersed oil (MDO; 2.27 μg/mL) ≥ oil-SPM aggregate (OSA; 1.96 μg/mL) > water accommodated fraction (WAF; 0.19 μg/mL) but the percentage of PAHs accumulated in oysters were highest from WAF (18.3%) > MDO (14.2%) > OSA (9.62%). Despite the high water column available PAHs, oysters exposed to SPM-associated oil accumulated PAHs at half the accumulation efficiency compared with those exposed to PAHs without SPM. Graphical abstract Unlabelled Image Highlights • SPM increased entrainment of dissolved and dispersed PAHs in the water column. • SPM significantly increased uptake of PAHs by oysters through ingestion of particle-bound PAHs. • Strong SPM-PAHs bonds retarded dissolution of PAHs into the water column. • SPM played significant roles on inhibiting accumulation of PAHs by oysters. [ABSTRACT FROM AUTHOR]

An important element of the oil spill emergency response is the ability to rapidly identify the properties of oil spilled. Chemometrics provides large numbers of multivariate analysis tools that allow for more extensive use of data. Fourier transformed infrared spectroscopy coupled with classification and prediction models such as partial least square (PLS) and PLS-DA (discriminant analysis) allows the rapid identification of oil type and characteristics. By searching for the maximum covariance with the variables of interest, PLS allows the visualization of relations between samples and variables. The framework of this study is based on two main steps: The first is classification of oil and the second is prediction of physicochemical properties. Separated into four main categories: crude, light fuel, heavy fuel, and lubricant, spectrums of 92 oils were calibrated to predict the oil type and physicochemical properties of 26 oils. The predictability and robustness of the model was further validated using weathered oil. The classification and prediction models have accuracy of >95%. Most of the PLS models have root mean square error of calibration and prediction ranging from 0.10–3.07 and 0.3–2.8, respectively. External cross validations using weathered oils showed high prediction accuracy (relative standard deviations <5%). By increasing the number of oil type and samples, this approach is a promising method and can be included as part of the oil spill fingerprinting protocols. Unlabelled Image • High-throughput oil analysis method was developed using FT-IR with chemometrics. • Tiered approaches were used for setup and validation of the chemometric models. • PLS-DA model allowed highly accurate and robust prediction of oil types. • PLS model provided physicochemical properties of oil with low prediction error. [ABSTRACT FROM AUTHOR]

Oil spills can be environmentally devastating and result in unintended economic and social consequences. An important element of the concerted effort to respond to spills includes the ability to rapidly classify and characterize oil spill samples, preferably on-site. An easy-to-use, handheld sensor is developed and demonstrated in this work, capable of classifying oil spills rapidly on-site. Our device uses the computational power and affordability of a Raspberry Pi microcontroller and a Pi camera, coupled with three ultraviolet light emitting diodes (UV-LEDs), a diffraction grating, and collimation slit, in order to collect a large data set of UV fluorescence fingerprints from various oil samples. Based on a 160-sample (in 5x replicates each with slightly varied dilutions) database this platform is able to classify oil samples into four broad categories: crude oil, heavy fuel oil, light fuel oil, and lubricating oil. The device uses principal component analysis (PCA) to reduce spectral dimensionality (1203 features) and support vector machine (SVM) for classification with 95% accuracy. The device is also able to predict some physiochemical properties, specifically saturate, aromatic, resin, and asphaltene percentages (SARA) based off linear relationships between different principal components (PCs) and the percentages of these residues. Sample preparation for our device is also straightforward and appropriate for field deployment, requiring little more than a Pasteur pipette and not being affected by dilution factors. These properties make our device a valuable field-deployable tool for oil sample analysis. Image 1 • First demonstration of machine learning- and UV fluorescence spectrum-based classification of oil spill samples. • Physicochemical properties (SARA) can also be predicted. • A standalone, Raspberry Pi based handheld device analyzes and classifies oil spill samples. • Classification and analysis are not affected by the dilution factor. [ABSTRACT FROM AUTHOR]

• Effectiveness and stability of mechanically and chemically dispersed oil were tested. • Minerals significantly enhanced effectiveness and stability of dispersed oil. • Long-term stability of dispersed oil was a function of particle size and number. • Combination of minerals and dispersant was suggested as an application option. Oil spill dispersant (OSD) application is one of the preferred cleanup options to cope with oil spills at sea. OSD, in principle, can enhance biodegradation of oil because of its effectiveness in producing relatively small droplets and dispersing them into the water column. Under turbulent conditions, suspended particulate matter (SPM) which are present naturally in the environment can interact with oil to form aggregates known as oil-SPM aggregates (OSA) which also enhances biodegradation of oil. Despite its high dispersion effectiveness, chemically dispersed oil (CDO) has a tendency to resurface with increasing time which decreases the biodegradation potential. Meanwhile, the presence of SPM prevents recoalescence of dispersed oil which can enhance stability of oil droplets. This study focused on the effects of SPM on the dispersion effectiveness and stability of mechanically dispersed oil (MDO) and CDO. Dispersion tests of MDO and CDO extended to 72 h with and without SPM to see the initial effectiveness and the prolonged stability of dispersed oil. In the presence of SPM, the oil dispersed by MDO increased by 14.8–40.7%, while the resurfacing oil by CDO decreased by 8.7–19.4%. Regardless of SPM type, oil dispersion effectiveness and stability of MDO and CDO were significantly increased. Long-term stability test for 3 months showed that stability of OSA increased as the particle size decreased and particle counts increased. [ABSTRACT FROM AUTHOR]

Abstract A systematic study of the photooxidation of phenanthrene under simulated environmental conditions was conducted in vitro using polar (methanol, acetonitrile) and non-polar (isooctane, hexane) solvents as media. In all solvents, phenanthrene concentration decreased exponentially as exposure time increased. Fourier-transform infrared spectroscopy (FTIR) and gas chromatography–mass spectrometry (GC–MS) analysis were used to investigate the structural changes induced by photooxidation. After 24 h of photooxidation, FTIR showed the formation of characteristic bands of carboxylic acid in all solvents. In non-polar solvents, characteristic phenanthrene peaks were completely depleted after 48 h. In polar solvents, phenanthrene peaks disappeared at a slower rate, with peaks in acetonitrile disappearing at 72 h and methanol persisting at trace levels at 96 h. The reaction rate was higher in non-polar solvents. The obtained half-lives were observed in the following order: isooctane (13.2 h) > hexane (13.5 h) > methanol (18.0 h) > acetonitrile (22.8 h). FTIR and GC–MS results were in good agreement and showed the formation of carboxylic acids, aldehydes, and ketones in polar solvents and carboxylic acids, alkanes, and alkanoic acids in non-polar solvents. Products such as primary amides induced by solvent effects were observed in acetonitrile. Based on the results, the solvents were rated and a solvent selection guide for photooxidation of PAHs was provided. Graphical abstract Image 1 Highlights • Solvent effects on the photooxidation of phenanthrene were elucidated. • Tiered instrumental analysis was applied to identify photooxidation products. • Photooxidation rate was higher in non-polar solvents than in polar solvents. • Acetonitrile produced photooxidation-interfering compounds. • A solvent selection guide for photooxidation was provided. [ABSTRACT FROM AUTHOR]

Tunnels are the preferred experimental environments for estimating vehicle emission factors (EFs) under real-world driving conditions. In this study, online measurements of traffic-related air pollutants (including CO 2 , NO X , SO 2 , O 3 , particulate matter [PM], and volatile organic compounds [VOCs]) were conducted using a mobile laboratory in the Sujungsan Tunnel in Busan, Korea. Mobile measurements generated concentration profiles of the target exhaust emissions inside the tunnel. These data were used to produce a zonation of the tunnel, i.e., mixing and accumulation zones. There were differences between the CO 2 , SO 2 , and NO X profiles, and a starting point that was free from ambient air mixing effects could be set at 600 m from the tunnel entrance. The EFs of vehicle exhaust emissions were calculated using pollutant concentration gradients. The average EFs for CO 2 , NO, NO 2 , SO 2 , PM 10 , PM 2.5 , and ∑VOCs were 149,000, 380, 55, 29.2, 9.64, 4.33, and 16.7 mg km−1·veh−1, respectively. Among the VOC groups, alkanes contributed more than 70% of the VOC EF. Mobile measurement-derived EFs were validated using the conventional EFs from stationary measurements. The EF results from the mobile measurements matched those from the stationary measurements, while the absolute concentration differences between them implied complex aerodynamic movements of the target pollutants inside the tunnel. This study demonstrated the usefulness and advantages of applying mobile measurements in a tunnel environment and indicated the potential of the approach for observation-based policymaking. [Display omitted] • Tunnel mobile measurement was conducted to estimate the emission factors (EFs) of vehicle exhausts. • The concentration gradient approach was applied, and demonstrated reliabilities for the estimation of EFs. • High time-resolution data enabled zonation of the tunnel as mixing and accumulation zone. • Region-specific pollutants of concern were updated by comparison with national inventory data. [ABSTRACT FROM AUTHOR]

Objective: The goal was to compare the clinical effectiveness of monotherapy with beta-lactams, clindamycin, or trimethoprim-sulfamethoxazole in the outpatient management of nondrained noncultured skin and soft-tissue infections (SSTIs), in a methicillin-resistant Staphylococcus aureus (MRSA)-endemic region., Methods: A retrospective, nested, case-control trial was conducted with a cohort of patients from 5 urban pediatric practices in a community-acquired MRSA-endemic region. All subjects were treated as outpatients with oral monotherapy for nondrained noncultured SSTIs between January 2004 and March 2007. The primary outcome was treatment failure, defined as a drainage procedure, hospitalization, change in antibiotic, or second antibiotic prescription within 28 days., Results: Of 2096 children with nondrained noncultured SSTIs, 104 (5.0%) were identified as experiencing treatment failure and were matched to 480 control subjects. Compared with beta-lactam therapy, clindamycin was equally effective but trimethoprim-sulfamethoxazole was associated with an increased risk of failure. Other factors independently associated with failure included initial treatment in the emergency department, presence or history of fever, and presence of either induration or a small abscess., Conclusions: Compared with beta-lactams, clindamycin monotherapy conferred no benefit, whereas trimethoprim-sulfamethoxazole was associated with an increased risk of treatment failure in a cohort of children with nondrained noncultured SSTIs who were treated as outpatients. Even in regions with endemic community-acquired MRSA, beta-lactams may still be appropriate, first-line, empiric therapy for children presenting with these infections.