DCNFIS: Deep Convolutional Neuro-Fuzzy Inference System

A key challenge in eXplainable Artificial Intelligence is the well-known tradeoff between the transparency of an algorithm (i.e., how easily a human can directly understand the algorithm, as opposed to receiving a post-hoc explanation), and its accuracy. We report on the design of a new deep network that achieves improved transparency without sacrificing accuracy. We design a deep convolutional neuro-fuzzy inference system (DCNFIS) by hybridizing fuzzy logic and deep learning models and show that DCNFIS performs as accurately as three existing convolutional neural networks on four well-known datasets. We furthermore that DCNFIS outperforms state-of-the-art deep fuzzy systems. We then exploit the transparency of fuzzy logic by deriving explanations, in the form of saliency maps, from the fuzzy rules encoded in DCNFIS. We investigate the properties of these explanations in greater depth using the Fashion-MNIST dataset

Coarse Particles and Heart Rate Variability among Older Adults with Coronary Artery Disease in the Coachella Valley, California

Alterations in cardiac autonomic control, assessed by changes in heart rate variability (HRV), provide one plausible mechanistic explanation for consistent associations between exposure to airborne particulate matter (PM) and increased risks of cardiovascular mortality. Decreased HRV has been linked with exposures to PM(10) (PM with aerodynamic diameter ≤ 10 μm) and with fine particles (PM with aerodynamic diameter ≤ 2.5 μm) originating primarily from combustion sources. However, little is known about the relationship between HRV and coarse particles [PM with aerodynamic diameter 10–2.5 μm (PM(10–2.5))], which typically result from entrainment of dust and soil or from mechanical abrasive processes in industry and transportation. We measured several HRV variables in 19 nonsmoking older adults with coronary artery disease residing in the Coachella Valley, California, a desert resort and retirement area in which ambient PM(10) consists predominantly of PM(10–2.5). Study subjects wore Holter monitors for 24 hr once per week for up to 12 weeks during spring 2000. Pollutant concentrations were assessed at nearby fixed-site monitors. We used mixed models that controlled for individual-specific effects to examine relationships between air pollutants and several HRV metrics. Decrements in several measures of HRV were consistently associated with both PM(10) and PM(10–2.5); however, there was little relationship of HRV variables with PM(2.5) concentrations. The magnitude of the associations (~ 1–4% decrease in HRV per 10-μg/m(3) increase in PM(10) or PM(10–2.5)) was comparable with those observed in several other studies of PM. Elevated levels of ambient PM(10–2.5) may adversely affect HRV in older subjects with coronary artery disease

Fine Particulate Air Pollution and Mortality in Nine California Counties: Results from CALFINE

Many epidemiologic studies provide evidence of an association between daily counts of mortality and ambient particulate matter < 10 μm in diameter (PM(10)). Relatively few studies, however, have investigated the relationship of mortality with fine particles [PM < 2.5 μm in diameter (PM(2.5))], especially in a multicity setting. We examined associations between PM(2.5) and daily mortality in nine heavily populated California counties using data from 1999 through 2002. We considered daily counts of all-cause mortality and several cause-specific subcategories (respiratory, cardiovascular, ischemic heart disease, and diabetes). We also examined these associations among several subpopulations, including the elderly (> 65 years of age), males, females, non-high school graduates, whites, and Hispanics. We used Poisson multiple regression models incorporating natural or penalized splines to control for covariates that could affect daily counts of mortality, including time, seasonality, temperature, humidity, and day of the week. We used meta-analyses using random-effects models to pool the observations in all nine counties. The analysis revealed associations of PM(2.5) levels with several mortality categories. Specifically, a 10-μg/m(3) change in 2-day average PM(2.5) concentration corresponded to a 0.6% (95% confidence interval, 0.2–1.0%) increase in all-cause mortality, with similar or greater effect estimates for several other subpopulations and mortality subcategories, including respiratory disease, cardiovascular disease, diabetes, age > 65 years, females, deaths out of the hospital, and non-high school graduates. Results were generally insensitive to model specification and the type of spline model used. This analysis adds to the growing body of evidence linking PM(2.5) with daily mortality

The Effects of Components of Fine Particulate Air Pollution on Mortality in California: Results from CALFINE

OBJECTIVE: Several epidemiologic studies provide evidence of an association between daily mortality and particulate matter < 2.5 μm in diameter (PM(2.5)). Little is known, however, about the relative effects of PM(2.5) constituents. We examined associations between 19 PM(2.5) components and daily mortality in six California counties. DESIGN: We obtained daily data from 2000 to 2003 on mortality and PM(2.5) mass and components, including elemental and organic carbon (EC and OC), nitrates, sulfates, and various metals. We examined associations of PM(2.5) and its constituents with daily counts of several mortality categories: all-cause, cardiovascular, respiratory, and mortality age > 65 years. Poisson regressions incorporating natural splines were used to control for time-varying covariates. Effect estimates were determined for each component in each county and then combined using a random-effects model. RESULTS: PM(2.5) mass and several constituents were associated with multiple mortality categories, especially cardiovascular deaths. For example, for a 3-day lag, the latter increased by 1.6, 2.1, 1.6, and 1.5% for PM(2.5), EC, OC, and nitrates based on interquartile ranges of 14.6, 0.8, 4.6, and 5.5 μg/m(3), respectively. Stronger associations were observed between mortality and additional pollutants, including sulfates and several metals, during the cool season. CONCLUSION: This multicounty analysis adds to the growing body of evidence linking PM(2.5) with mortality and indicates that excess risks may vary among specific PM(2.5) components. Therefore, the use of regression coefficients based on PM(2.5) mass may underestimate associations with some PM(2.5) components. Also, our findings support the hypothesis that combustion-associated pollutants are particularly important in California

Air Pollution and Lymphocyte Phenotype Proportions in Cord Blood

Effects of air pollution on morbidity and mortality may be mediated by alterations in immune competence. In this study we examined short-term associations of air pollution exposures with lymphocyte immunophenotypes in cord blood among 1,397 deliveries in two districts of the Czech Republic. We measured fine particulate matter < 2.5 μm in diameter (PM(2.5)) and 12 polycyclic aromatic hydrocarbons (PAHs) in 24-hr samples collected by versatile air pollution samplers. Cord blood samples were analyzed using a FACSort flow cytometer to determine phenotypes of CD3(+) T-lymphocytes and their subsets CD4(+) and CD8(+), CD19(+) B-lymphocytes, and natural killer cells. The mothers were interviewed regarding sociodemographic and lifestyle factors, and medical records were abstracted for obstetric, labor and delivery characteristics. During the period 1994 to 1998, the mean daily ambient concentration of PM(2.5) was 24.8 μg/m(3) and that of PAHs was 63.5 ng/m(3). In multiple linear regression models adjusted for temperature, season, and other covariates, average PAH or PM(2.5) levels during the 14 days before birth were associated with decreases in T-lymphocyte phenotype fractions (i.e., CD3(+) CD4(+), and CD8(+)), and a clear increase in the B-lymphocyte (CD19(+)) fraction. For a 100-ng/m(3) increase in PAHs, which represented approximately two standard deviations, the percentage decrease was −3.3% [95% confidence interval (CI), −5.6 to −1.0%] for CD3(+), −3.1% (95% CI, −4.9 to −1.3%) for CD4(+), and −1.0% (95% CI, −1.8 to −0.2%) for CD8(+) cells. The corresponding increase in the CD19(+) cell proportion was 1.7% (95% CI, 0.4 to 3.0%). Associations were similar but slightly weaker for PM(2.5). Ambient air pollution may influence the relative distribution of lymphocyte immunophenotypes of the fetus

Design of an Imaging Payload for Earth Observation from a Nanosatellite

A compact imaging payload consisting of visible-near infrared and short-wave infrared capability is being developed to demonstrate low-cost wildfire monitoring among other Earth observations. Iris is a 1U multispectral push-broom imager that is capable of generating spectral data pertinent for wildfire science and wildfire risk analysis from a CubeSat platform. This payload is slated to fly on-board Ex-Alta 2, the University of Alberta’s second CubeSat and Alberta’s contribution to the Canadian CubeSat Project, to be deployed from the International Space Station in 2022. Iris features four closely integrated designs: optical, structural, electronics, and firmware. The mechanical and electronic interfaces of Iris are suited for modular integration into 1U of other generic CubeSat structures. The design has significant constraints on mass, size, performance, and cost. The current optical design features two compact lightpaths within the housing for imaging in short-wave infrared, near-infrared, blue, and red bands (center wavelengths at 2100, 865, 490, and 665 nm, respectively). Design simulations suggest achievement of a signal-to-noise ratio greater than 20 dB across all bands and a spatial resolution of 360 mor better averaged across the field-of-view. Taken together, this demonstrates significant scientific value for minimized cost and instrument volume. This design uses exclusively commercially available lenses, providing significant overall cost savings. The structural housing of Iris consists of 6061 T6 Aluminum, which provides a light-tight optical path for the visible to near-infrared and short-wave infrared light paths, as well as mounting for the optics and printed circuit board to the CubeSat structure within the required tolerances. A 45-degree folding mirror is employed to provide an extended optical lightpath within 1U with no deployable optics. The lens and mirror mounts are fitted with manual adjustment mechanisms for post-assembly alignment of the optical elements. This feature allows the team to perform small modifications to the axial position of the lenses as well as the folding mirror plane without having to re-manufacture the structure, saving time and cost. Within Iris, a subsystem named Electra features a custom filtered CMV4000 CMOS detector from ams AG integrated alongside a custom filtered G11478-512WB InGaAs linear array from Hamamatsu. Electra is a custom printed circuit board which houses an Intel Cyclone V system-on-chip field-programmable gate array, 512 MB of DDR3 synchronous dynamic random-access memory, and other supporting infrastructure for controlling Iris imaging operations and handling spectral data. An in-house software and VHDL suite is implemented within Electra for sensor control, memory management, and all off-board communications. Software functionality includes data compression and a cloud detection algorithm, wherein images are ranked based on heuristic value of relative cloud content, together increasing scientific value per spacecraft link time. A full proto-flight model of Iris is scheduled for manufacturing and testing in Q4 2021. Following manufacturing, comprehensive validation analysis and characterization will be performed, confirming ability to meet mission requirements

Early Environmental Exposures and Intracellular Th1/Th2 Cytokine Profiles in 24-Month-Old Children Living in an Agricultural Area

BACKGROUND: Children who reside in agricultural settings are potentially exposed to higher levels of organophosphate (OP) pesticides, endotoxin, and allergens than their urban counterparts. Endotoxin and allergens stimulate maturation of the immune response in early childhood, but little is known about the effect of exposures to OPs or to the three combined. OBJECTIVES: In this study, we investigated the relationships between these exposures and T-helper 1 (Th1) and T-helper 2 (Th2) cytokines, biomarkers of allergic asthma, in the subjects of CHAMA-COS (Center for the Health Assessment of Mothers and Children of Salinas), a longitudinal birth cohort in Salinas Valley, California. Exposures were ascertained by interviewer-administered questionnaires and by home visits, and clinical diagnoses were abstracted from medical records. Blood samples were collected at 12 and 24 months of age and analyzed for Th1/Th2 status by flow cytometric detection of intracellular interferon-γ/interleukin-4 cytokine expression. FINDINGS: Mean Th2 levels were significantly higher in children with doctor-diagnosed asthma and children with wheezing at 2 years of age. In a multiple linear regression model, exclusive breast-feeding at 1 month and pet ownership were associated with 35.3% (p < 0.01) and 34.5% (p = 0.01) increases in Th1, respectively. Maternal agricultural work and presence of gas stove in the home were associated with a 25.9% increase (p = 0.04) and 46.5% increase (p < 0.01) in Th2, respectively. CONCLUSIONS: Asthma and wheeze outcomes in children at 24 months of age are associated with elevated Th2 status in children at an early age. Our data further suggest that early exposures to an agricultural environment, breast-feeding, pets, and gas stoves affect the development of children’s Th1/Th2 immune response