NASA Johnson Space Center Small Business Innovation Research (SBIR) Successes, Infusion and Commercializations and Potential International Partnering Opportunities

The NASA Small Business Innovation Research (SBIR) Program has served as a beneficial funding vehicle to both US small technology businesses and the Federal Agencies that participate in the program. This paper, to the extent possible, while observing Intellectual Property (IP) laws, will discuss the many SBIR and STTR (SBIR Technology Transfer) successes in the recent history of the NASA Johnson Space Center (JSC). Many of the participants of the International Conference on Environmental Systems (ICES) have based their research and papers on technologies that were made possible by SBIR/STTR awards and post award funding. Many SBIR/STTR successes have flown on Space Shuttle missions, Space X Dragons, and other spacecraft. SBIR/STTR technologies are currently infused on the International Space Station (ISS) and satellites, one of which was a NASA/JAXA (Japanese Space Agency) joint venture. Many of these companies have commercialized their technologies and grown as businesses while helping the economy through the creation of new jobs. In addition, this paper will explore the opportunity for international partnership with US SBIR/STTR companies as up to 49% of the makeup of the company is not required to be American owned. Although this paper will deal with technical achievements, it does not purport to be technical in nature. It will address the many requests for information on successes and opportunities within NASA SBIR and the virtually untapped potential of international partnering

Innovative solutions for aquaculture: Assessment of in situ monitoring techniques and life history parameters for monogenean skin and gill parasites

First paragraph: External parasitic flukes that infect the skin and gills of yellowtail kingfish are among the most serious health issues for the culture of this species. Fingerlings grown in land-based hatcheries are free of parasites when transferred to sea-cages for grow out. The skin and gill parasites occur naturally and infect wild yellowtail kingfish stocks. Fluke populations proliferate on captive, seacaged stocks due to the direct lifecycle of the two parasite species. Fluke infections require regular monitoring by farm staff throughout the production cycle of yellowtail kingfish. Infections contribute to reduced growth, morbidity and if fluke populations reach sufficient intensity, the parasites can cause kingfish mortality on farms

Paternal nutrient provisioning during male pregnancy in the seahorse Hippocampus abdominalis

Vertebrates that incubate embryos on or within the body cavity exhibit diverse strategies to provide nutrients to developing embryos, ranging from lecithotrophy (solely yolk-provided nutrition) to substantial matrotrophy (supplemental nutrients from the mother before birth). Syngnathid fishes (seahorses, pipefishes and sea dragons) are the only vertebrates to exhibit male pregnancy. Therefore, they provide a unique opportunity for comparative evolutionary research, in examining pregnancy independent of the female reproductive tract. Here, we tested the hypothesis that the most complex form of syngnathid pregnancy involves nutrient transport from father to offspring. We compared the dry masses of newly fertilised Hippocampus abdominalis eggs with those of fully developed neonates to derive a patrotrophy index. The patrotrophy index of H. abdominalis was 1, indicating paternal nutrient supplementation to embryos during gestation. We also measured the lipid content of newly fertilised eggs and neonates and found that there was no significant decrease in lipid mass during embryonic development. Since lipids are likely to be the main source of energy during embryonic development, our results suggest that lipid yolk reserves being depleted by embryonic metabolism are replaced by the brooding father. The results of our study support the hypothesis that nutrient transport occurs in the most advanced form of male pregnancy in vertebrates

Disentangling with Biological Constraints: A Theory of Functional Cell Types

Neurons in the brain are often finely tuned for specific task variables. Moreover, such disentangled representations are highly sought after in machine learning. Here we mathematically prove that simple biological constraints on neurons, namely nonnegativity and energy efficiency in both activity and weights, promote such sought after disentangled representations by enforcing neurons to become selective for single factors of task variation. We demonstrate these constraints lead to disentangling in a variety of tasks and architectures, including variational autoencoders. We also use this theory to explain why the brain partitions its cells into distinct cell types such as grid and object-vector cells, and also explain when the brain instead entangles representations in response to entangled task factors. Overall, this work provides a mathematical understanding of why, when, and how neurons represent factors in both brains and machines, and is a first step towards understanding of how task demands structure neural representations

Disentanglement via Latent Quantization

In disentangled representation learning, a model is asked to tease apart a dataset's underlying sources of variation and represent them independently of one another. Since the model is provided with no ground truth information about these sources, inductive biases take a paramount role in enabling disentanglement. In this work, we construct an inductive bias towards compositionally encoding and decoding data by enforcing a harsh communication bottleneck. Concretely, we do this by (i) quantizing the latent space into learnable discrete codes with a separate scalar codebook per dimension and (ii) applying strong model regularization via an unusually high weight decay. Intuitively, the quantization forces the encoder to use a small number of latent values across many datapoints, which in turn enables the decoder to assign a consistent meaning to each value. Regularization then serves to drive the model towards this parsimonious strategy. We demonstrate the broad applicability of this approach by adding it to both basic data-reconstructing (vanilla autoencoder) and latent-reconstructing (InfoGAN) generative models. In order to reliably assess these models, we also propose InfoMEC, new metrics for disentanglement that are cohesively grounded in information theory and fix well-established shortcomings in previous metrics. Together with regularization, latent quantization dramatically improves the modularity and explicitness of learned representations on a representative suite of benchmark datasets. In particular, our quantized-latent autoencoder (QLAE) consistently outperforms strong methods from prior work in these key disentanglement properties without compromising data reconstruction.Comment: 20 pages, 8 figures, code available at https://github.com/kylehkhsu/disentangl

Actionable Neural Representations: Grid Cells from Minimal Constraints

To afford flexible behaviour, the brain must build internal representations that mirror the structure of variables in the external world. For example, 2D space obeys rules: the same set of actions combine in the same way everywhere (step north, then south, and you won't have moved, wherever you start). We suggest the brain must represent this consistent meaning of actions across space, as it allows you to find new short-cuts and navigate in unfamiliar settings. We term this representation an `actionable representation'. We formulate actionable representations using group and representation theory, and show that, when combined with biological and functional constraints - non-negative firing, bounded neural activity, and precise coding - multiple modules of hexagonal grid cells are the optimal representation of 2D space. We support this claim with intuition, analytic justification, and simulations. Our analytic results normatively explain a set of surprising grid cell phenomena, and make testable predictions for future experiments. Lastly, we highlight the generality of our approach beyond just understanding 2D space. Our work characterises a new principle for understanding and designing flexible internal representations: they should be actionable, allowing animals and machines to predict the consequences of their actions, rather than just encode

Evolutionary Proteomics Reveals Distinct Patterns of Complexity and Divergence between Lepidopteran Sperm Morphs

This article has been accepted for publication in Genome Biology and Evolution Published by Oxford University Press. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.Spermatozoa are one of the most strikingly diverse animal cell types. One poorly understood example of this diversity is sperm heteromorphism, where males produce multiple distinct morphs of sperm in a single ejaculate. Typically, only one morph is capable of fertilization and the function of the nonfertilizing morph, called parasperm, remains to be elucidated. Sperm heteromorphism has multiple independent origins, including Lepidoptera (moths and butterflies), where males produce a fertilizing eupyrene sperm and an apyrene parasperm, which lacks a nucleus and nuclear DNA. Here we report a comparative proteomic analysis of eupyrene and apyrene sperm between two distantly related lepidopteran species, the monarch butterfly (Danaus plexippus) and Carolina sphinx moth (Manduca sexta). In both species, we identified ∼700 sperm proteins, with half present in both morphs and the majority of the remainder observed only in eupyrene sperm. Apyrene sperm thus have a distinctly less complex proteome. Gene ontology (GO) analysis revealed proteins shared between morphs tend to be associated with canonical sperm cell structures (e.g., flagellum) and metabolism (e.g., ATP production). GO terms for morph-specific proteins broadly reflect known structural differences, but also suggest a role for apyrene sperm in modulating female neurobiology. Comparative analysis indicates that proteins shared between morphs are most conserved between species as components of sperm, whereas morph-specific proteins turn over more quickly, especially in apyrene sperm. The rapid divergence of apyrene sperm content is consistent with a relaxation of selective constraints associated with fertilization and karyogamy. On the other hand, parasperm generally exhibit greater evolutionary lability, and our observations may therefore reflect adaptive responses to shifting regimes of sexual selection.National Science Foundation award OAC-1541396/ACI-1541396NSF award OAC-1541396/ACI-1541396Syracuse UniversityUniversity of KansasKU Gould Fellowship and National Science Foundation award DEB-1701931Syracuse University FellowshipMarilyn Kerr Fellowshi

Human Activity Differentially Redistributes Large Mammals in the Canadian Rockies National Parks

National parks are important for conservation of species such as wolves (Canis lupus) and elk (Cervus canadensis). However, topography, vegetation conditions, and anthropogenic infrastructure within parks may limit available habitat. Human activity on trails and roads may lead to indirect habitat loss, further limiting available habitat. Predators and prey may respond differentially to human activity, potentially disrupting ecological processes. However, research on such impacts to wildlife is incomplete, especially at fine spatial and temporal scales. Our research investigated the relationship between wolf and elk distribution and human activity using fine-scale Global Positioning System (GPS) wildlife telemetry locations and hourly human activity measures on trails and roads in Banff, Kootenay, and Yoho National Parks, Canada. We observed a complex interaction between the distance animals were located from trails and human activity level resulting in species adopting both mutual avoidance and differential response behaviors. In areas \u3c 50 m from trails human activity led to a mutual avoidance response by both wolves and elk. In areas 50 - 400 m from trails low levels of human activity led to differential responses; wolves avoided these areas, whereas elk appeared to use these areas as a predation refugia. These differential impacts on elk and wolves may have important implications for trophic dynamics. As human activity increased above two people/hour, areas 50 - 400 m from trails were mutually avoided by both species, resulting in the indirect loss of important montane habitat. If park managers are concerned with human impacts on wolves and elk, or on these species\u27 trophic interactions with other species, they can monitor locations near trails and roads and consider hourly changes of human activity levels in areas important to wildlife

Generalisation of structural knowledge in the hippocampal-entorhinal system

A central problem to understanding intelligence is the concept of generalisation. This allows previously learnt structure to be exploited to solve tasks in novel situations differing in their particularities. We take inspiration from neuroscience, specifically the hippocampal-entorhinal system known to be important for generalisation. We propose that to generalise structural knowledge, the representations of the structure of the world, i.e. how entities in the world relate to each other, need to be separated from representations of the entities themselves. We show, under these principles, artificial neural networks embedded with hierarchy and fast Hebbian memory, can learn the statistics of memories and generalise structural knowledge. Spatial neuronal representations mirroring those found in the brain emerge, suggesting spatial cognition is an instance of more general organising principles. We further unify many entorhinal cell types as basis functions for constructing transition graphs, and show these representations effectively utilise memories. We experimentally support model assumptions, showing a preserved relationship between entorhinal grid and hippocampal place cells across environments