Enabling Explainable Fusion in Deep Learning with Fuzzy Integral Neural Networks

Information fusion is an essential part of numerous engineering systems and biological functions, e.g., human cognition. Fusion occurs at many levels, ranging from the low-level combination of signals to the high-level aggregation of heterogeneous decision-making processes. While the last decade has witnessed an explosion of research in deep learning, fusion in neural networks has not observed the same revolution. Specifically, most neural fusion approaches are ad hoc, are not understood, are distributed versus localized, and/or explainability is low (if present at all). Herein, we prove that the fuzzy Choquet integral (ChI), a powerful nonlinear aggregation function, can be represented as a multi-layer network, referred to hereafter as ChIMP. We also put forth an improved ChIMP (iChIMP) that leads to a stochastic gradient descent-based optimization in light of the exponential number of ChI inequality constraints. An additional benefit of ChIMP/iChIMP is that it enables eXplainable AI (XAI). Synthetic validation experiments are provided and iChIMP is applied to the fusion of a set of heterogeneous architecture deep models in remote sensing. We show an improvement in model accuracy and our previously established XAI indices shed light on the quality of our data, model, and its decisions.Comment: IEEE Transactions on Fuzzy System

Coulomb crystal mass spectrometry in a digital ion trap

We present a mass spectrometric technique for identifying the masses and relative abundances of Coulomb-crystallized ions held in a linear Paul trap. A digital radio-frequency wave form is employed to generate the trapping potential, as this can be cleanly switched off, and static dipolar fields are subsequently applied to the trap electrodes for ion ejection. Close to 100% detection efficiency is demonstrated for Ca+ and CaF+ ions from bicomponent Ca+ − CaF+ Coulomb crystals prepared by the reaction of Ca+ with CH3F. A quantitative linear relationship is observed between ion number and the corresponding integrated time-of-flight (TOF) peak, independent of the ionic species. The technique is applicable to a diverse range of multicomponent Coulomb crystals—demonstrated here for Ca+ − NH3+ − NH4+ and Ca+ − CaOH+ − CaOD+ crystals—and will facilitate the measurement of ion-molecule reaction rates and branching ratios in complicated reaction systems

Performance of an Axisymmetric Rocket Based Combined Cycle Engine During Rocket Only Operation Using Linear Regression Analysis

The all rocket mode of operation is shown to be a critical factor in the overall performance of a rocket based combined cycle (RBCC) vehicle. An axisymmetric RBCC engine was used to determine specific impulse efficiency values based upon both full flow and gas generator configurations. Design of experiments methodology was used to construct a test matrix and multiple linear regression analysis was used to build parametric models. The main parameters investigated in this study were: rocket chamber pressure, rocket exit area ratio, injected secondary flow, mixer-ejector inlet area, mixer-ejector area ratio, and mixer-ejector length-to-inlet diameter ratio. A perfect gas computational fluid dynamics analysis, using both the Spalart-Allmaras and k-omega turbulence models, was performed with the NPARC code to obtain values of vacuum specific impulse. Results from the multiple linear regression analysis showed that for both the full flow and gas generator configurations increasing mixer-ejector area ratio and rocket area ratio increase performance, while increasing mixer-ejector inlet area ratio and mixer-ejector length-to-diameter ratio decrease performance. Increasing injected secondary flow increased performance for the gas generator analysis, but was not statistically significant for the full flow analysis. Chamber pressure was found to be not statistically significant

454 sequencing put to the test using the complex genome of barley

BACKGROUND: During the past decade, Sanger sequencing has been used to completely sequence hundreds of microbial and a few higher eukaryote genomes. In recent years, a number of alternative technologies became available, among them adaptations of the pyrosequencing procedure (i.e. "454 sequencing"), promising a ~100-fold increase in throughput over Sanger technology – an advancement which is needed to make large and complex genomes more amenable to full genome sequencing at affordable costs. Although several studies have demonstrated its potential usefulness for sequencing small and compact microbial genomes, it was unclear how the new technology would perform in large and highly repetitive genomes such as those of wheat or barley. RESULTS: To study its performance in complex genomes, we used 454 technology to sequence four barley Bacterial Artificial Chromosome (BAC) clones and compared the results to those from ABI-Sanger sequencing. All gene containing regions were covered efficiently and at high quality with 454 sequencing whereas repetitive sequences were more problematic with 454 sequencing than with ABI-Sanger sequencing. 454 sequencing provided a much more even coverage of the BAC clones than ABI-Sanger sequencing, resulting in almost complete assembly of all genic sequences even at only 9 to 10-fold coverage. To obtain highly advanced working draft sequences for the BACs, we developed a strategy to assemble large parts of the BAC sequences by combining comparative genomics, detailed repeat analysis and use of low-quality reads from 454 sequencing. Additionally, we describe an approach of including small numbers of ABI-Sanger sequences to produce hybrid assemblies to partly compensate the short read length of 454 sequences. CONCLUSION: Our data indicate that 454 pyrosequencing allows rapid and cost-effective sequencing of the gene-containing portions of large and complex genomes and that its combination with ABI-Sanger sequencing and targeted sequence analysis can result in large regions of high-quality finished genomic sequences

Extension of the fuzzy integral for general fuzzy set-valued information

The fuzzy integral (FI) is an extremely flexible aggregation operator. It is used in numerous applications, such as image processing, multicriteria decision making, skeletal age-at-death estimation, and multisource (e.g., feature, algorithm, sensor, and confidence) fusion. To date, a few works have appeared on the topic of generalizing Sugeno's original real-valued integrand and fuzzy measure (FM) for the case of higher order uncertain information (both integrand and measure). For the most part, these extensions are motivated by, and are consistent with, Zadeh's extension principle (EP). Namely, existing extensions focus on fuzzy number (FN), i.e., convex and normal fuzzy set- (FS) valued integrands. Herein, we put forth a new definition, called the generalized FI (gFI), and efficient algorithm for calculation for FS-valued integrands. In addition, we compare the gFI, numerically and theoretically, with our non-EP-based FI extension called the nondirect FI (NDFI). Examples are investigated in the areas of skeletal age-at-death estimation in forensic anthropology and multisource fusion. These applications help demonstrate the need and benefit of the proposed work. In particular, we show there is not one supreme technique. Instead, multiple extensions are of benefit in different contexts and applications

Defining Dysbiosis in Disorders of Movement and Motivation

The gut microbiota has emerged as a critical player in shaping and modulating brain function and has been shown to influence numerous behaviors, including anxiety and depression-like behaviors, sociability, and cognition. However, the effects of the gut microbiota on specific disorders associated with thalamo-cortico-basal ganglia circuits, ranging from compulsive behavior and addiction to altered sensation and motor output, are only recently being explored. Wholesale depletion and alteration of gut microbial communities in rodent models of disorders, such as Parkinson's disease, autism, and addiction, robustly affect movement and motivated behavior. A new frontier therefore lies in identifying specific microbial alterations that affect these behaviors and understanding the underlying mechanisms of action. Comparing alterations in gut microbiota across multiple basal-ganglia associated disease states allows for identification of common mechanistic pathways that may interact with distinct environmental and genetic risk factors to produce disease-specific outcomes

Analysis of Electrodeposited Nickel-Iron Alloy Film Composition Using Particle-Induced X-Ray Emission

The elemental composition of electrodeposited NiFe thin films was analyzed with particle-induced X-ray emission (PIXE). The thin films were electrodeposited on polycrystalline Au substrates from a 100mM NiSO4, 10 mM FeSO4, 0.5M H3BO3, and 1M Na2SO4 solution. PIXE spectra of these films were analyzed to obtain relative amounts of Ni and Fe as a function of deposition potential and deposition time. The results show that PIXE can measure the total deposited metal in a sample over at least four orders of magnitude with similar fractional uncertainties. The technique is also sensitive enough to observe the variations in alloy composition due to sample nonuniformity or variations in deposition parameters

Gene expression differences in relation to age and social environment in queen and worker bumble bees

Eusocial insects provide special insights into the genetic pathways influencing aging because of their long-lived queens and flexible aging schedules. Using qRT-PCR in the primitively eusocial bumble bee Bombus terrestris (Linnaeus), we investigated expression levels of four candidate genes associated with taxonomically widespread age-related pathways (coenzyme Q biosynthesis protein 7, COQ7; DNA methyltransferase 3, Dnmt3; foraging, for; and vitellogenin, vg). In Experiment 1, we tested how expression changes with queen relative age and productivity. We found a significant age-related increase in COQ7 expression in queen ovary. In brain, all four genes showed higher expression with increasing female (queen plus worker) production, with this relationship strengthening as queen age increased, suggesting a link with the positive association of fecundity and longevity found in eusocial insect queens. In Experiment 2, we tested effects of relative age and social environment (worker removal) in foundress queens and effects of age and reproductive status in workers. In this experiment, workerless queens showed significantly higher for expression in brain, as predicted if downregulation of for is associated with the cessation of foraging by foundress queens following worker emergence. Workers showed a significant age-related increase in Dnmt3 expression in fat body, suggesting a novel association between aging and methylation in B. terrestris. Ovary activation was associated with significantly higher vg expression in fat body and, in younger workers, in brain, consistent with vitellogenin's ancestral role in regulating egg production. Overall, our findings reveal a mixture of novel and conserved features in age-related genetic pathways under primitive eusociality

A Fractal Model for the Capacitance of Lunar Dust and Lunar Dust Aggregates

Lunar dust grains and dust aggregates exhibit clumping, with an uneven mass distribution, as well as features that span many spatial scales. It has been observed that these aggregates display an almost fractal repetition of geometry with scale. Furthermore, lunar dust grains typically have sharp protrusions and jagged features that result from the lack of aeolian weathering (as opposed to space weathering) on the Moon. A perfectly spherical geometry, frequently used as a model for lunar dust grains, has none of these characteristics (although a sphere may be a reasonable proxy for the very smallest grains and some glasses). We present a fractal model for a lunar dust grain or aggregate of grains that reproduces (1) the irregular clumpy nature of lunar dust, (2) the presence of sharp points, and (3) dust features that span multiple scale lengths. We calculate the capacitance of the fractal lunar dust analytically assuming fixed dust mass (i.e. volume) for an arbitrary number of fractal levels and compare the capacitance to that of a non-fractal object with the same volume, surface area, and characteristic width. The fractal capacitance is larger than that of the equivalent non-fractal object suggesting that for a given potential, electrostatic forces on lunar dust grains and aggregates are greater than one might infer from assuming dust grains are sphericaL Consequently, electrostatic transport of lunar dust grains, for example lofting, appears more plausible than might be inferred by calculations based on less realistic assumptions about dust shape and associated capacitance