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OBJECTIVE: Tobacco use is rarely addressed in community mental healthcare settings, despite its high prevalence among people with serious mental illness. The aim of the current study was to gather stakeholder feedback regarding the feasibility of chronic care management strategies for tobacco dependence in community mental health centers (CMHCs). Chronic care strategies evaluated included the 5 As (Ask about tobacco use, Advise users of tobacco to quit, Assess interest in cessation, Assist with cessation, and Arrange for follow-up) and proactive telephone outreach (reaching out to all users of tobacco to offer connection to tobacco cessation treatment). METHODS: Using a semi-structured interview guide informed by the Practical Robust Implementation and Sustainability Model, we conducted individual semi-structured interviews with providers, leaders, and clients across two CMHCs. Our objectives were to capture their attitudes toward smoking cessation treatment, two chronic care model interventions (i.e., proactive outreach, the 5 As), and to determine the infrastructure needed to implement such interventions in their CMHCs. Thematic analysis was conducted by two independent coders to uncover pertinent themes. RESULTS: Participants (n = 20) included nine providers, six leaders, and five clients. Thematic analysis revealed three major themes: (1) characteristics of recipients, (2) characteristics of the intervention, and (3) infrastructure needed for implementation and sustainability. Providers, leaders, and clients all reported that tobacco cessation treatment was rarely provided in CMHCs and expressed an interest in such treatments becoming more available. The 5 As and proactive outreach were viewed as feasible and acceptable to deliver and receive. Providers, leaders, and clients wanted support to connect clients with smoking cessation treatment. Providers and leaders requested a range of implementation supports, including didactic trainings, decision aids, performance feedback, and coaching on evidence-based tobacco cessation treatments for people with serious mental illness. Clients requested tobacco cessation resources, such as a cessation counseling provided at the CMHC and prescriptions for cessation medication. CONCLUSIONS: CMHC providers, leaders, and clients are interested in making tobacco cessation services more widely accessible and available. The feedback gathered in this study can be used to inform the delivery and implementation of guideline-adherent tobacco dependence care in CMHCs.

A relationship was built between the structure and magnetic properties to investigate the magnetization reversal and magnetic interaction. The result of the magnetic switching effect indicates potential applications in data storage devices.

As the third most important greenhouse gas (GHG) after carbon dioxide (CO2) and methane (CH4), tropospheric ozone (O3) is also an air pollutant causing damage to human health and ecosystems. This study brings together recent research on observations and modeling of tropospheric O3 in the Arctic, a rapidly warming and sensitive environment. At different locations in the Arctic, the observed surface O3 seasonal cycles are quite different. Coastal Arctic locations, for example, have a minimum in the springtime due to O3 depletion events resulting from surface bromine chemistry. In contrast, other Arctic locations have a maximum in the spring. The 12 state-of-the-art models used in this study lack the surface halogen chemistry needed to simulate coastal Arctic surface O3 depletion in the springtime; however, the multi-model median (MMM) has accurate seasonal cycles at non-coastal Arctic locations. There is a large amount of variability among models, which has been previously reported, and we show that there continues to be no convergence among models or improved accuracy in simulating tropospheric O3 and its precursor species. The MMM underestimates Arctic surface O3 by 5 % to 15 % depending on the location. The vertical distribution of tropospheric O3 is studied from recent ozonesonde measurements and the models. The models are highly variable, simulating free-tropospheric O3 within a range of ±50 % depending on the model and the altitude. The MMM performs best, within ±8 % for most locations and seasons. However, nearly all models overestimate O3 near the tropopause (∼300 hPa or ∼8 km), likely due to ongoing issues with underestimating the altitude of the tropopause and excessive downward transport of stratospheric O3 at high latitudes. For example, the MMM is biased high by about 20 % at Eureka. Observed and simulated O3 precursors (CO, NOx, and reservoir PAN) are evaluated throughout the troposphere. Models underestimate wintertime CO everywhere, likely due to a combination of underestimating CO emissions and possibly overestimating OH. Throughout the vertical profile (compared to aircraft measurements), the MMM underestimates both CO and NOx but overestimates PAN. Perhaps as a result of competing deficiencies, the MMM O3 matches the observed O3 reasonably well. Our findings suggest that despite model updates over the last decade, model results are as highly variable as ever and have not increased in accuracy for representing Arctic tropospheric O3.

9 pags., 5 figs. 1 tab., Oceans are the largest source of biogenic emissions to the atmosphere, including aerosol precursors like marine halocarbons and dimethyl sulfide (DMS). During the last decade, the CAMS-GLOB-OCE dataset has developed an analysis of daily emissions of tribromomethane (CHBr3), dibromomethane (CH2Br2), iodomethane (CH3I), and DMS, due to its increasingly recognized role on tropospheric chemistry and climate dynamics. The potential impacts of these compounds on air quality modeling remain, however, largely unexplored. The lack of a reliable and easy methodology to incorporate these marine emissions into air quality models is probably one of the reasons behind this knowledge gap. Therefore, this study describes a methodology to adapt the CAMS-GLOB-OCE dataset to be used as an input of the preprocessor software Sparse Matrix Operator Kernel Emissions (SMOKE). The method involves nine steps to update file attribute properties and to bilinearly interpolate compound emission fields. The procedure was tested using halocarbon and DMS emissions fields available within the CAMS-GLOB-OCE database for the Southern Ocean around Antarctica. We expect that this methodology will allow more studies to include the marine emissions of halocarbons and DMS in air quality studies., This work was supported by CONICYT-PIA-FONDEQUIP-FUNDACIÓN ALEMANA PARA LA INVESTIGACIÓN D.F.G (DFG190001), FONDECYT-REGULAR 1211338, and the supercomputing infrastructure at NLHPC (ECM-02).

Liquid xenon time projection chambers are promising detectors to search for neutrinoless double beta decay (0$$\nu \beta \beta $$ ν β β ), due to their response uniformity, monolithic sensitive volume, scalability to large target masses, and suitability for extremely low background operations. The nEXO collaboration has designed a tonne-scale time projection chamber that aims to search for 0$$\nu \beta \beta $$ ν β β of $$^{136}$$ 136 Xe with projected half-life sensitivity of $$1.35\times 10^{28}$$ 1.35 × 10 28 yr. To reach this sensitivity, the design goal for nEXO is $$\le $$ ≤ 1% energy resolution at the decay Q-value ($$2458.07\pm 0.31$$ 2458.07 ± 0.31 keV). Reaching this resolution requires the efficient collection of both the ionization and scintillation produced in the detector. The nEXO design employs Silicon Photo-Multipliers (SiPMs) to detect the vacuum ultra-violet, 175 nm scintillation light of liquid xenon. This paper reports on the characterization of the newest vacuum ultra-violet sensitive Fondazione Bruno Kessler VUVHD3 SiPMs specifically designed for nEXO, as well as new measurements on new test samples of previously characterised Hamamatsu VUV4 Multi Pixel Photon Counters (MPPCs). Various SiPM and MPPC parameters, such as dark noise, gain, direct crosstalk, correlated avalanches and photon detection efficiency were measured as a function of the applied over voltage and wavelength at liquid xenon temperature (163 K). The results from this study are used to provide updated estimates of the achievable energy resolution at the decay Q-value for the nEXO design.

We present the v1.0 release of CLMM, an open source Python library for the estimation of the weak lensing masses of clusters of galaxies. CLMM is designed as a standalone toolkit of building blocks to enable end-to-end analysis pipeline validation for upcoming cluster cosmology analyses such as the ones that will be performed by the LSST-DESC. Its purpose is to serve as a flexible, easy-to-install and easy-to-use interface for both weak lensing simulators and observers and can be applied to real and mock data to study the systematics affecting weak lensing mass reconstruction. At the core of CLMM are routines to model the weak lensing shear signal given the underlying mass distribution of galaxy clusters and a set of data operations to prepare the corresponding data vectors. The theoretical predictions rely on existing software, used as backends in the code, that have been thoroughly tested and cross-checked. Combined, theoretical predictions and data can be used to constrain the mass distribution of galaxy clusters as demonstrated in a suite of example Jupyter Notebooks shipped with the software and also available in the extensive online documentation., 21 pages, 6 figures, accepted for publication by MNRAS

An accurate emission inventory is a crucial part of air pollution management and is essential for air quality modelling. One source in an emission inventory, an industrial source, has been known with high uncertainty in both location and magnitude in China. In this study, a new reallocation method based on blue-roof industrial buildings was developed to replace the conventional method of using population density for the Chinese emission development. The new method utilized the zoom level 14 satellite imagery (i.e. Google®) and processed it based on hue, saturation, and value (HSV) colour classification to derive new spatial surrogates for province-level reallocation, providing more realistic spatial patterns of industrial PM2.5 and NO2 emissions in China. The WRF-CMAQ-based PATH-2016 model system was then applied with the new processed industrial emission input in the MIX inventory to simulate air quality in the Greater Bay Area (GBA) area (formerly called Pearl River Delta, PRD). In the study, significant root mean square error (RMSE) improvement was observed in both summer and winter scenarios in 2015 when compared with the population-based approach. The average RMSE reductions (i.e. 75 stations) of PM2.5 and NO2 were found to be 11 µg m−3 and 3 ppb, respectively. Although the new method for allocating industrial sources did not perform as well as the point- and area-based industrial emissions obtained from the local bottom-up dataset, it still showed a large improvement over the existing population-based method. In conclusion, this research demonstrates that the blue-roof industrial allocation method can effectively identify scattered industrial sources in China and is capable of downscaling the industrial emissions from regional to local levels (i.e. 27 to 3 km resolution), overcoming the technical hurdle of ∼ 10 km resolution from the top-down or bottom-up emission approach under the unified framework of emission calculation.

Displacement piles are driven to support a wide range of structures. However, analysis of the stress and strain fields developed during their installation remains one of the most challenging problems in geotechnical engineering. Advances in design methods, particularly for sand sites, have had to rely on an imperfect analogy between pile and CPT cone penetration processes, rather than modelling pile installation itself. Recent physical model experiments provide benchmark datasets that describe the stress and deformation patterns developed around displacement piles penetrating sand masses. Following from large deformation finite element analyses that captured the stresses measured in the Grenoble 3S-R calibration chamber NE34 sand experiments, this paper presents simulations of the displacements measured in equivalent high-quality experiments conducted at Purdue University with dense, angular, #2Q-ROK silica sand. A modified Mohr-Coulomb model with state-dependent parameters was calibrated to match element tests conducted by the Authors and an Arbitrary Lagrangian-Eulerian scheme was applied in the simulations. The evolution and distribution of the deformations induced by pile penetration are compared with the experiments. Predictions for the deformation and strain fields applying during and after pile installation are presented, showing broad agreement between the simulations and experiments. The predicted and measured pile capacities are also compared and contrasted. Points of divergence between the simulations and tests are highlighted and their implications for numerical modelling are discussed.

Although overall use is on the rise, certain patient populations have persistently low technology use.To inform the creation of a proactive tobacco treatment program, we assessed access to, use of, and barriers surrounding information and communication technology (ICT) among patients with COPD who currently smoke, examining associations between key predictors and electronic health (e-health) literacy.Single-center mixed-methods study of Veterans with COPD who smoke. Eligible participants with smoking were identified by the electronic health record and mailed a survey. E-health literacy was assessed by the eHEALS (electronic health literacy scale, 8-40). Low technology use was defined as no internet capable device and use of ICT less than monthly. Qualitative participants were purposively selected from survey respondents and interviewed using a semi-structured guide. Interviews were transcribed and analyzed using directed content analysis. We used a Bayesian three-component joint model to identify predictors of low technology use and low eHEALS.Participants (n=204) were older (mean age 65.8) primarily white (76.4%) men (87.1%) with low income (44.9% income$20,000). Low technology use was reported by 25.5% and many reported low use of specific types of ICT. For example, only 36.3% had reliable in-home internet, fewer than half (46.6%) accessed e-mail at least weekly, 58.3% texted at least weekly, and few used the secure patient portal (13.2% accessed it monthly). Mean eHEALS was 24.6 (+/-8.7), indicating low to moderate e-health literacy. In the Bayesian analysis, low technology use was associated with lower eHEALS (Estimate: -8.5, 95% CI: [-12.13, -4.81]). Attainment of at least a college graduate level education was associated with higher eHEALS (3.83, [0.43, 7.24]). Participants reported barriers to use of ICT including: struggles navigating account security, frequently lost login information, mistrust of providing personal information to the internet and lack of familiarity with processes. Many perceived ICT as not useful or necessary.Many patients with COPD who smoke report barriers to engagement with health promotion programs offered electronically, which may perpetuate health disparities. Health promotion programs must account for low use of ICT and e-health literacy to ensure equitable access across the population.