Sound Region Research Articles

Metabolic Syndrome and Risks of Breast Cancer Outcomes for Luminal, Triple-Negative, and HER2-Overexpressing Subtypes.

We evaluated the association between metabolic syndrome (MetS; obesity plus two metabolic risk factors) and breast cancer outcomes according to molecular subtype. This population-based prospective cohort consisted of 3,267 women ages 20 to 69 years diagnosed with a first primary invasive breast cancer from 2004 to 2015 in the Seattle-Puget Sound region. Breast cancer was categorized into three subtypes based on estrogen receptor (ER), progesterone receptor, and HER2 expression: luminal (ER+), triple-negative (ER-/progesterone receptor negative/HER2-), and HER2-overexpressing (H2E; ER-/HER2+) subtypes. We used time-varying Cox models to assess the association of prevalent and incident MetS with risks of recurrence, breast cancer-specific mortality (BCSM), and all-cause mortality (ACM). MetS was associated with a greater risk of recurrence [HR, 3.24; 95% confidence interval (CI), 1.13-9.33] and BCSM (HR, 5.34; 95% CI, 2.32-12.31) only for the H2E subtype and greater risks of ACM for luminal (HR, 1.92; 95% CI, 1.37-2.68), H2E (HR, 5.09; 95% CI, 2.51-10.32), and all cases combined (HR, 1.90; 95% CI, 1.42-2.53). We also observed heterogeneity in recurrence and mortality outcomes across specific components of MetS and molecular subtypes. MetS is associated with ACM among women with breast cancer and with BCSM among women with the H2E subtype. These results highlight the importance of managing comorbidities to decrease the risk for adverse outcomes among breast cancer survivors.

Voice Analysis in Dogs with Deep Learning: Development of a Fully Automatic Voice Analysis System for Bioacoustics Studies.

Extracting behavioral information from animal sounds has long been a focus of research in bioacoustics, as sound-derived data are crucial for understanding animal behavior and environmental interactions. Traditional methods, which involve manual review of extensive recordings, pose significant challenges. This study proposes an automated system for detecting and classifying animal vocalizations, enhancing efficiency in behavior analysis. The system uses a preprocessing step to segment relevant sound regions from audio recordings, followed by feature extraction using Short-Time Fourier Transform (STFT), Mel-frequency cepstral coefficients (MFCCs), and linear-frequency cepstral coefficients (LFCCs). These features are input into convolutional neural network (CNN) classifiers to evaluate performance. Experimental results demonstrate the effectiveness of different CNN models and feature extraction methods, with AlexNet, DenseNet, EfficientNet, ResNet50, and ResNet152 being evaluated. The system achieves high accuracy in classifying vocal behaviors, such as barking and howling in dogs, providing a robust tool for behavioral analysis. The study highlights the importance of automated systems in bioacoustics research and suggests future improvements using deep learning-based methods for enhanced classification performance.

Research on the dynamic response of semi-enclosed sound barrier on viaduct under train pulsating wind and wheel-rail excitation

This study develops a coupled train-viaduct dynamic analysis model to investigate the dynamic response of semi-enclosed sound barriers on viaducts in light rail transit. During the iterative process of this model, fluctuating wind produced by the train is introduced and combined with wheel-rail loads to analyze the dynamic response of sound barriers. Based on the above model, in the time domain, there are significant differences in the vibration displacement and acceleration under combined excitation when the train head enters and the tail exits the sound barrier region. In the frequency domain, the vibration acceleration level under combined excitation increases significantly within the 0–5 Hz frequency. The parameter analysis results indicate that the total vibration acceleration level is higher at the measuring points close to the direction of travel. As the train speed increases, the effect of fluctuating wind becomes more significant in the low-frequency range (1–3.15 Hz). The smaller number of train formations also improved the vibration acceleration level difference between the combined and wheel-rail excitation.

A Discourse Analysis of Cultural Influences on Alaska Native Successful Aging

ABSTRACT Geographical remoteness, limited resources, and socioeconomic disparities contribute to the migration of rural Alaska Native Elders to urban areas to access medical services and resources, improve economic situations, or reunite with family. We compared the discourse of 12 Elders in Anchorage who previously lived in four remote traditional villages in the Norton Sound region (ages 60–84) and 13 Elders in those villages (ages 48–80). Using Gee’s discourse analysis framework, two patterns emerged detailing cultural effects on identity and Eldership, illuminating differences in the self-evaluation of successful aging based on cultural influences and the role of contextual factors.

A randomized controlled trial evaluation of a smoking cessation and physical activity intervention delivered via telemedicine in the Norton Sound region of Alaska

ObjectivesTobacco use disproportionately affects Alaska Native people. Physical activity may aid quitting smoking and provides health benefits. We tested telemedicine-delivered heart health interventions in Alaska’s Norton Sound region. MethodsAlaska Native adults (N = 299, 51.5 % male, 60.5 % Inupiaq) with hypertension and/or hypercholesterolemia who smoked daily were randomized to intervention on smoking and physical activity (group 1) or traditional diet and medication adherence (group 2). Intention to change was not required for participation. Stage-tailored mailed workbooks and personalized reports were supported by telehealth counseling at baseline, 3, 6, and 12 months. Study outcomes were assessed at baseline, 3-, 6-, 12-, and 18-months (i.e., 6-months after the final counseling session). Smoking outcomes were self-reported 7-day point prevalence abstinence (7d-PPA),11Abbreviations:7d-PPA: 7-day point prevalence abstinenceMET: Metabolic equivalent of taskMVPA: Moderate-to-vigorous physical activityNRT: Nicotine replacement therapy. bioconfirmed with urine anabasine; 24-hour quit attempts; and 50 % reduction in smoking. Self-reported physical activity outcomes were metabolic equivalent of task (MET) minutes and meeting moderate-to-vigorous physical activity (MVPA) guidelines. ResultsAt baseline, participants averaged 12.4 (SD = 10.0) cigarettes/day, with 19.4 % prepared to quit smoking, and 81.6 % meeting MVPA guidelines. During the study, most (70.2 % group 1; 63.5 % group 2) reported a 24-hr quit attempt (p = 0.219), and Group 1 (53.6 %) was more likely than Group 2 (28.4 %) to use nicotine replacement therapy (NRT), OR = 2.92, p < 0.001. At 18-months, 40.5 % (group 1) and 32.5 % (group 2) had reduced their smoking by half or more (p = 0.343), and 10.8 % vs. 7.9 % (group 1 vs. 2) reported 7d-PPA with 4 % vs. 6 % (group 1 vs. 2) bioconfirmed. Time and baseline stage of change predicted 7d-PPA (p’s≤.015), with no group effect (p = 0.325). Activity levels did not significantly differ by group or time. ConclusionsTelemedicine counseling supported NRT use but did not significantly affect behavioral outcomes.

No Longer Seat-Less in Seattle: The Role of Coordinated Transportation and Land Use Planning in Sustaining Transit Ridership through the Pandemic Recovery Period

Transit ridership had been decreasing in major cities across the United States prior to the Covid-19 pandemic, with Seattle as a notable exception. I examine the relationship between travel behavior and Seattle’s land use planning program in conjunction with transit improvements. I use econometric methods to analyze multiple waves of the Puget Sound Regional Council (PSRC) Household Travel Survey from 2014 to 2021. Living in one of Seattle’s Urban Villages is significantly associated with a higher likelihood of taking transit. This relationship holds during the pandemic time period and when controlling for self-selection.

Correlation between Discharge Noise and Flow Field Characteristics of Hydraulic Turbine

The water flow within the turbine passage of a hydropower station exhibits high-speed closed-pressure flow. The flow field characteristics will directly affect the turbine’s operational efficiency and safety. To ensure the safe operation of the turbine and accurately monitor its flow state, the relationship between the flow characteristics in the turbine passage and its discharge noise must be established. In this study, the relationship between the flow field and the noise field of the turbine is explored using a combination of a model turbine passage discharge noise test and numerical simulation of flow field characteristics. Results show that the operating parameters are closely related to the discharge noise’s characteristics, in which the operating head and discharge of the unit’s operating parameters greatly influence the discharge noise in the flow passage. Hydrodynamic factors, such as fluctuation pressure and pressure in the flow field, show a strong correlation with the discharge noise characteristics. As the pressure and fluctuation pressure in the inlet area of the spiral case intensify, the sound pressure level (SPL) of the discharge noise increases and the main frequency decreases. A large-scale vortex easily forms in the spiral case and draft tube area, thereby causing low-frequency fluctuation and forming high-decibel noise. Also, the runner area is the main sound source region of the turbine passage. The research results will provide technical and theoretical support for the safe operation and accurate fault diagnosis of hydropower stations.

Using interpenetrating subsampling to incorporate interpreter variability into estimation of the total variance of land cover area estimates

Reference data obtained by interpreters is a key component of sample-based estimation of area of land cover and land cover change. However, interpreters may disagree when assigning the reference class label for a given sample unit and this inconsistency between interpreters contributes to the overall uncertainty of the estimated area. Interpenetrating subsampling (IPS) offers a practical way to incorporate interpreter variability into an unbiased estimator of the total variance. This method requires partitioning the full sample into g nonoverlapping groups with the sample units in each group then evaluated by a different interpreter and each interpreter determines the reference class data for only one group. The total variance is estimated by the among group variability of the g estimates of area. IPS was applied to estimate the total variance of land cover area estimates for a sample of 300 pixels selected from the Puget Sound region of the Northwest United States. The reference land cover data were obtained by seven interpreters who each labeled all 300 pixels. These data provided a unique opportunity to explore properties of IPS such as variability over different random partitions of the sample into groups and variability over different subsets of interpreters. IPS estimates of total variance were produced for each land cover class for group sizes of g = 2 through g = 6 and all possible combinations of the seven interpreters for each group size. The estimated total variance decreased with increasing number of groups. Incorporating interpreter variance increased the estimated total variance by a factor ranging from 1.08 (agriculture) to 7.06 (grass/shrub) in simple random sampling. The total variance estimates varied substantially over the random partitions of the sample into groups, but this variability decreased as the group size increased. Compared with other total variance estimators, the IPS estimator is simpler to compute and is more cost effective because it does not require repeat interpretations

History of the Antarctic Ice Sheet in the McMurdo Sound region at and since the Last Glacial Maximum: Evidence from Miers Valley

Reconstructions of past Antarctic Ice Sheet (AIS) behavior can afford key information about likely ice-sheet response to future climate change. Here, we examine the history of a marine-based ice mass grounded in McMurdo Sound of the western Ross Embayment during the Last Glacial Maximum and termination. Geomorphological mapping and interpretation of stratigraphic sections, as well as 67 radiocarbon dates of algal mats and 16 234U/230Th ages of carbonate and gypsum in glaciolacustrine sediments, indicate that ice from the broader Ross Embayment entered McMurdo Sound by approximately 24,000 yr BP and blocked the seaward mouth of Miers Valley. Maximum thickness of the McMurdo Sound ice was maintained from ∼19,000 yr BP, with fluctuations, until ∼12,600 yr BP. A lake-ice conveyor operated on a large ice-dammed lake that accompanied this advance until dessication at 10,000–7900 yr BP concurrent with ice recession. In contrast to the expansion of grounded marine-based ice in McMurdo Sound, alpine glaciers at the valley head did not advance at the Last Glacial Maximum. This out-of-phase behavior of the marine-based ice sheet vs. independent terrestrial glaciers is consistent with previous studies suggesting that local glaciers respond primarily to accumulation, which rises during warm periods. The long and late maximum of the McMurdo Sound ice (corresponding largely to Termination I) and delayed recession until after the Antarctic Cold Reversal (∼14,700–12,900 yr BP) lends support to the hypothesis that the AIS in the Ross Sea sector is controlled by the competing effects of marine (sea level, ocean temperatures) and accumulation forcing.

Optimizing placement of bioretention systems in the US Puget Sound region

AbstractThe Puget Sound Basin, US Pacific Northwest, is experiencing rapid population and urban growth. This growth adversely impacts local ecosystems, especially the spawning and rearing habitat for several salmonid species. Sustainable urban design strategies such as green stormwater infrastructure (GSI) are required in the region to manage stormwater onsite when new development occurs. However, the effectiveness of any GSI depends on its location relative to where stormwater is produced. This study aimed to develop a Geographic Information System (GIS)‐based framework for the optimal placement of GSI, specifically bioretention systems. We computed the Hydrologic Sensitivity Index (λHSI, indicating runoff generation potential at a landscape location) for the lower Puyallup River Watershed study area. The index and federal and state feasibility criteria were used to identify suitable sites for bioretention systems. The suitability of identified sites was verified through ground‐truthing, including soil sampling and infiltration testing. We found that 2.5% of the watershed area was suitable for bioretention, concentrated in the center and north of the study watershed. The method described in this study can be readily applied to watersheds for which spatial data (topography, soil, and land use) are available. We recommend choosing locations with high λHSI when resources are limited since these locations contribute most to runoff generation and urban flooding.

The fusion of lock-in phase images for the damage investigation in composites materials

Lock-in thermography (LIT) is a type of active thermography capable of detecting and evaluating the subsurface defects in composite materials. The phase or amplitude difference between the defect and sound regions can quantitatively determine the size and depth of defects. One limitation of LIT is that the optimal identification of defects located at specific depths is dispersed within phase images acquired at varying excitation frequencies. If the depth of the defects within the specimen is unknown, it is difficult to determine the excitation frequencies to achieve optimal contrast for all defects and display them in a single image. To address this challenge, a multi-frequency fused method based on lock-in thermography is proposed to improve the quality of defect detection. Initially, the optimal thermal wave excitation frequencies and the number of detection times are determined based on the theoretical solution. Subsequently, phase images at various excitation frequencies are extracted and enhanced using a specified scheme. Finally, we develop an unsupervised encoder-decoder network that combines dense connections and residual modules to fuse these phase images into a single image containing defects at various depths. An experiment is conducted to detect carbon fiber reinforced polymer (CFRP) laminate containing defects with different depths and sizes. The results demonstrate that the proposed method can broaden the detection range of defect depths and improve the quality of the inspected images, providing superior performance compared to traditional sequential image processing methods.

Mesoscale Eddy Effects on Vertical Correlation of Sound Field and Array Gain Performance

To solve the problem of array detection performance in environments with mesoscale eddies, this study utilizes the Gaussian eddy model to describe the sound speed structure disturbed by eddies. Through numerical simulations, the corresponding sound field is obtained, and the transmission loss influenced by the eddy is analyzed. Furthermore, to investigate the relation between the array gain and spatial correlation in the eddy environments, the differences in vertical correlation at different positions and their effects on the vertical array gain of conventional beamforming (CBF) are studied. When the source is around the eddy center, the conclusions drawn are as follows: (1) The presence of an eddy changes the turning-point depth and the sound field distribution, significantly affecting the direct sound region and the first convergence zone, while having a minor impact on the first shadow zone. (2) In different eddy-induced environments, the first convergence zone maintains a high vertical correlation, but the vertical correlation of the direct sound region is greatly influenced by the eddy. (3) The array gain of CBF is consistent with the vertical correlation. When the correlation between each element of the sound field is great, the array gain increases with the number of array elements.

Leveraging low-cost sensors to predict nitrogen dioxide for epidemiologic exposure assessment.

Statistical models of air pollution enable intra-urban characterization of pollutant concentrations, benefiting exposure assessment for environmental epidemiology. The new generation of low-cost sensors facilitate the deployment of dense monitoring networks and can potentially be used to improve intra-urban models of air pollution. Develop and evaluate a spatiotemporal model for nitrogen dioxide (NO2) in the Puget Sound region of WA, USA for the Adult Changes in Thought Air Pollution (ACT-AP) study and assess the contribution of low-cost sensor data to the model's performance through cross-validation. We developed a spatiotemporal NO2 model for the study region incorporating data from 11 agency locations, 364 supplementary monitoring locations, and 117 low-cost sensor (LCS) locations for the 1996-2020 time period. Model features included long-term time trends and dimension-reduced land use regression. We evaluated the contribution of LCS network data by comparing models fit with and without sensor data using cross-validated (CV) summary performance statistics. The best performing model had one time trend and geographic covariates summarized into three partial least squares components. The model, fit with LCS data, performed as well as other recent studies (agency cross-validation: CV- root mean square error (RMSE) = 2.5 ppb NO2; CV- coefficient of determination ( ) = 0.85). Predictions of NO2 concentrations developed with LCS were higher at residential locations compared to a model without LCS, especially in recent years. While LCS did not provide a strong performance gain at agency sites (CV-RMSE = 2.8 ppb NO2; CV- = 0.82 without LCS), at residential locations, the improvement was substantial, with RMSE = 3.8 ppb NO2 and = 0.08 (without LCS), compared to CV-RMSE = 2.8 ppb NO2 and CV- = 0.51 (with LCS). We developed a spatiotemporal model for nitrogen dioxide (NO2) pollution in Washington's Puget Sound region for epidemiologic exposure assessment for the Adult Changes in Thought Air Pollution study. We examined the impact of including low-cost sensor data in the NO2 model and found the additional spatial information the sensors provided predicted NO2 concentrations that were higher than without low-cost sensors, particularly in recent years. We did not observe a clear, substantial improvement in cross-validation performance over a similar model fit without low-cost sensor data; however, the prediction improvement with low-cost sensors at residential locations was substantial. The performance gains from low-cost sensors may have been attenuated due to spatial information provided by other supplementary monitoring data.

Juvenile Pacific salmonid habitat use in two Puget Sound lowland rivers

AbstractObjectiveLarge rivers are complex, productive environments that support numerous species. However, humans have extensively modified these ecosystems, contributing to the decline of Pacific salmonid Oncorhynchus spp. populations. Salmon recovery efforts rely upon an understanding of salmonid habitat needs at different life stages, but data on juvenile salmonid habitat use within large rivers are rare due to the challenges of sampling in large rivers. To help fill this information need, we used a cataraft‐mounted electrofisher to evaluate juvenile salmonid use of natural (bar, backwater, side channel, and unarmored bank) and human‐modified (riprap‐armored bank and biorevetment bank [armored banks with added wood]) channel edge habitats in the Snoqualmie and Green rivers within the Puget Sound region of Washington State.MethodsWe electrofished over 1000 25‐m transects across seven spring rearing seasons (2016–2022) and measured transect water depths and widths of low‐velocity habitat (≤0.45 m/s).ResultBars, backwaters, and side channels were shallower and had wider low‐velocity habitat than armored banks. River flow also influenced water depth and low‐velocity width, but the relationship varied depending on the habitat type. Subyearling Chinook Salmon O. tshawytscha and subyearling Coho Salmon O. kisutch occurred more frequently and were more abundant along natural edge habitats than along armored banks, while their use of biorevetment banks was intermediate between their use of natural edge habitats and armored banks. In contrast, yearling Coho Salmon and trout occurred more frequently and were more abundant along armored, biorevetment, and unarmored banks than along bars and backwaters, but they also used side channels extensively. Habitat use shifted throughout the spring, but specific shifts varied by species or life history stage.ConclusionThese results emphasize the importance of conserving natural edge habitats, removing bank armoring, and reconnecting or restoring side channels. Additionally, our results highlight that a diversity of habitat types and conditions is necessary to support multiple species and life history stages.

Dynamic Modeling of Coastal Compound Flooding Hazards Due to Tides, Extratropical Storms, Waves, and Sea-Level Rise: A Case Study in the Salish Sea, Washington (USA)

The Puget Sound Coastal Storm Modeling System (PS-CoSMoS) is a tool designed to dynamically downscale future climate scenarios (i.e., projected changes in wind and pressure fields and temperature) to compute regional water levels, waves, and compound flooding over large geographic areas (100 s of kilometers) at high spatial resolutions (1 m) pertinent to coastal hazard assessments and planning. This research focuses on advancing robust and computationally efficient approaches to resolving the coastal compound flooding components for complex, estuary environments and their application to the Puget Sound region of Washington State (USA) and the greater Salish Sea. The modeling system provides coastal planners with projections of storm hazards and flood exposure for recurring flood events, spanning the annual to 1-percent annual chance of flooding, necessary to manage public safety and the prioritization and cost-efficient protection of critical infrastructure and valued ecosystems. The tool is applied and validated for Whatcom County, Washington, and includes a cross-shore profile model (XBeach) and overland flooding model (SFINCS) and is nested in a regional tide–surge model and wave model. Despite uncertainties in boundary conditions, hindcast simulations performed with the coupled model system accurately identified areas that were flooded during a recent storm in 2018. Flood hazards and risks are expected to increase exponentially as the sea level rises in the study area of 210 km of shoreline. With 1 m of sea-level rise, annual flood extents are projected to increase from 13 to 33 km2 (5 and 13% of low-lying Whatcom County) and flood risk (defined in USD) is projected to increase fifteenfold (from 14 to USD 206 million). PS-CoSMoS, like its prior iteration in California (CoSMoS), provides valuable coastal hazard projections to help communities plan for the impacts of sea-level rise and storms.

Stable isotopes reveal intertidal fish and crabs use bivalve farms as foraging habitat in Puget Sound, Washington

Bivalves such as oysters and clams have been farmed in intertidal zones across the Puget Sound region of the Salish Sea for thousands of years. The variety of gear types used on bivalve farms creates complex vertical structure and attachment points for aquatic epiphytes and invertebrates which increases habitat structural complexity, but may alter eelgrass cover in areas where bivalve farms and eelgrass meadows overlap. Eelgrass meadows are highly productive and ecologically foundational nearshore habitats that provide valuable ecosystem services including the provision of nursery, refuge, and foraging habitat. Aquaculture has been a key feature of the environment in the Puget Sound for millennia, however, little is known about how well aquaculture practices are integrated into the system, and what services they provide to mobile species assemblages relative to unfarmed eelgrass meadows. We used stable isotope mixing models to estimate, for several species of nearshore fish and crab in two areas of North Puget Sound, Washington, the percent diet originating from either a natural bottom habitat (eelgrass meadows), farm habitat (oyster farms), or pelagic planktonic sources. Our results indicate that several species of nearshore fish such as surf perch and staghorn sculpin derive a significant proportion of their diets from farm areas, while crabs derive most of their diets from eelgrass habitat, and stickleback derive a significant proportion of their diets from planktonic sources. The results indicate that foraging habitat uses are species specific, and that several species that spatially overlap bivalve farms obtained a large percentage of their diets from adjacent bivalve farm habitat.

Enhanced detection algorithm for apple bruises using structured light imaging

Bruising reduces the edibility and marketability of fresh apples, inevitably causing economic losses for the apple industry. However, bruises lack obvious visual symptoms, which makes it challenging to detect them using imaging techniques with uniform or diffuse illumination. This study employed the structured light imaging (SLI) technique to detect apple bruises. First, the grayscale reflection images were captured under phase-shifted sinusoidal illumination at three different wavelengths (600, 650, and 700 nm) and six different spatial frequencies (0.05, 0.10, 0.15, 0.20, 0.25, and 0.30 cycles mm−1). Next, the grayscale reflectance images were demodulated to produce direct component (DC) images representing uniform diffuse illumination and amplitude component (AC) images revealing bruises. Then, by quantifying the contrast between bruised regions and sound regions in all AC images, it was found that bruises exhibited the optimal contrast when subjected to sinusoidal illumination at a wavelength of 700 nm and a spatial frequency of 0.25 mm−1. In the AC image with optimal contrast, the developed h-domes segmentation algorithm to accurately segment the location and range of the bruised regions. Moreover, the algorithm successfully accomplished the task of segmenting central bruised regions while addressing the challenge of segmenting edge bruised regions complicated by vignetting. The average Intersection over Union (IoU) values for the three types of bruises were 0.9422, 0.9231, and 0.9183, respectively. This result demonstrated that the combination of SLI and the h-domes segmentation algorithm was a viable approach for the effective detection of fresh apple bruises.

Weather Systems Connecting Modes of Climate Variability to Regional Hydroclimate Extremes

AbstractWeather system clustering provides a high‐level summary of regional meteorological conditions. Most quantitative clustering schemes focus on precipitation alone, which does not sufficiently describe the meteorological conditions driving hydroclimate variability. This study presents the Weather Anomaly Clustering (WAC‐hydro), which extends the existing capability of predicting weather systems to predicting hydroclimate variability. Focusing on both precipitation and temperature predictions, WAC‐hydro identifies 12 clusters of daily weather anomaly modes in the US Pacific Northwest Puget Sound region during 1981–2020. The influence of El Niño‐Southern Oscillation and Madden‐Julian Oscillation on regional precipitation can be well approximated by their modulation on the weather clusters. Within each weather cluster, local factors such as topography only play a secondary role in the hydrologic variability. The weather clusters highlight two types of flood‐inducing regional weather conditions, one causing floods by inducing positive precipitation anomalies and the other causing floods through combined precipitation and temperature‐induced rain‐on‐snow effect.

One sight on sound generation and absorption by vortices

Vortices generate sound and absorb sound. A. Powell and M. S. Howe deduced the equations and showed that the exterior product of vortex and local velocity took part in sound generation and absorption. However, it is difficult to image its physical phenomena. In this paper, as one example, the interaction of sound and vortices at the throat of a cavity with grazing flow is investigated by CFD simulation. As the results, it is found that sound absorbing regions and sound generating regions are locally distributed and moving. It is also found that when counterclockwise vortices turn to the left, they absorb sound and when they turn to the right, they generate sound. Based on these results, 'Floating Vertical Bar Model (FVB Model)' is proposed to image the sound generation and absorption phenomena, in which a vortex is simulated as a bar floating vertically on the water surface, because a vortex has coherent structure along its axis like a bar. When a vortex (a bar) is accelerated perpendicular to its axis, pressure fluctuation (water wave) is easily generated. And when sound wave (water wave) shakes a vortex (a bar), sound energy is absorbed by a vortex (a bar) motion.

Alcohol, Smoking, and Risks of Breast Cancer Recurrence and Mortality among Women with Luminal, Triple-Negative, and HER2-Overexpressing Breast Cancer.

This study evaluates the relationship between smoking, alcohol, and breast cancer outcomes according to molecular subtype. This population-based prospective cohort consisted of 3,876 women ages 20 to 69 diagnosed with a first primary invasive breast cancer from 2004 to 2015 in the Seattle-Puget Sound region. Breast cancer was categorized into three subtypes based on estrogen receptor (ER), progesterone receptor (PR), and HER2 expressions: luminal (ER+), triple-negative (TN; ER-/PR-/HER2-), and HER2-overexpressing (H2E; ER-/HER2+). We fit Cox proportional hazards models to assess the association between alcohol consumption and smoking status at diagnosis and risks of recurrence, breast cancer-specific mortality, and all-cause mortality. Histories of ever smoking [HR, 1.33; 95% confidence interval (CI), 1.01-1.74] and current smoking (HR, 1.59; 95% CI, 1.07-2.35) were associated with greater risk of breast cancer recurrence among TN cases. Smoking was also associated with greater risk of recurrence to bone among all cases and among luminal cases. Elevated risks of breast cancer-specific and all-cause mortality were observed among current smokers across all subtypes. Alcohol use was not positively associated with risk of recurrence or mortality overall; however, TN patients who drank four or more drinks per week had a decreased risk of recurrence (HR, 0.71; 95% CI, 0.51-0.98) and breast cancer-specific mortality (HR, 0.73; 95% CI, 0.55-0.97) compared with non-current drinkers. Patients with breast cancer with a history of smoking at diagnosis have elevated risks of recurrence and mortality. These findings underscore the need to prioritize smoking cessation among women diagnosed with breast cancer.