Constraint and Restoring Force

Long-lived sensor network applications must be able to self-repair and adapt to changing demands. We introduce a new approach for doing so: Constraint and Restoring Force. CRF is a physics-inspired framework for computing scalar fields across a sensor network with occasional changes. We illustrate CRFs usefulness by applying it to gradients, a common building block for sensor network systems. The resulting algorithm, CRF-Gradient, determines locally when to self-repair and when to stop and save energy. CRF-Gradient is self-stabilizing, converges in O(diameter) time, and has been verified experimentally in simulation and on a network of Mica2 motes. Finally we show how CRF can be applied to other algorithms as well, such as the calculation of probability fields

Fast Self-Healing Gradients

We present CRF-Gradient, a self-healing gradient algorithm that provably reconfigures in O(diameter) time. Self-healing gradients are a frequently used building block for distributed self-healing systems, but previous algorithms either have a healing rate limited by the shortest link in the network or must rebuild invalid regions from scratch. We have verified CRF-Gradient in simulation and on a network of Mica2 motes. Our approach can also be generalized and applied to create other self-healing calculations, such as cumulative probability fields

Algal food and fuel coproduction can mitigate greenhouse gas emissions while improving land and water-use efficiency

The goals of ensuring energy, water, food, and climate security can often conflict.Microalgae (algae) are being pursued as a feedstockfor both food and fuels—primarily due to algae’s high areal yield and ability to grow on non-arable land, thus avoiding common bioenergy-food tradeoffs. However, algal cultivation requires significant energy inputs that may limit potential emission reductions.We examine the tradeoffs associated with producing fuel andfood from algae at the energy–food–water–climate nexus.We use the GCAM integrated assessment model to demonstrate that algalfood production can promote reductions in land-use change emissions through the offset of conventional agriculture. However,fuel production, either via co-production of algal food and fuel or complete biomass conversion to fuel, is necessary to ensure long-term emission reductions, due to the high energy costs of cultivation. Cultivation of salt– water algae for food products may lead to substantial freshwater savings; but, nutrients for algae cultivation will need to be sourced from waste streams to ensure sustainability. By reducing the land demand of food production, while simultaneously enhancingfood and energy security, algae can further enable the development of terrestrial bioenergy technologies including those utilizing carbon capture and storage. Our results demonstrate that large-scale algae research and commercialization efforts should focus on developing both food and energy products to achieve environmental goals.https://iopscience.iop.org/article/10.1088/1748-9326/11/11/114006/metaPublished versio

High throughput methodology for synthesis, screening, and optimization of solid state Lithium ion electrolytes

A study of the lithium ion conductor Li3xLa2/3–xTiO3 solid solution and the surrounding composition space was carried out using a high throughput physical vapor deposition system. An optimum total ionic conductivity value of 5.45 × 10–4 S cm–1 was obtained for the composition Li0.17La0.29Ti0.54 (Li3xLa2/3–xTiO3x = 0.11). This optimum value was calculated using an artificial neural network model based on the empirical data. Due to the large scale of the data set produced and the complexity of synthesis, informatics tools were required to analyze the data. Partition analysis was carried out to determine the synthetic parameters of importance and their threshold values. Multivariate curve resolution and principal component analysis were applied to the diffraction data set. This analysis enabled the construction of phase distribution diagrams, illustrating both the phases obtained and the compositional zones in which they occur. The synthetic technique presented has significant advantages over other thin film and bulk methodologies, in terms of both the compositional range covered and the nature of the materials produce

New England Food Vision: Healthy Food for All, Sustainable Farming and Fishing, Thriving Communities

A New England Food Vision proposes changes in food production, distribution, and consumption reaching from the most rural areas to the densest cities—across the entire food system. The New England Food Vision Writing Team has been working since 2011 to produce a bold vision that calls for our region to build the capacity to produce at least 50% of clean, fair, accessible and just food for New Englanders by 2060. The Vision includes a set of guiding assumptions and calculations that sketch a future in which diverse local and state food systems are supported by and in turn support a regional sustainable food system. The roles of the writing team include production of a New England Food Vision document, including input from regional stakeholders at the annual New England Food Summits, discussions at various meetings, presentations, and via an online survey

Marine microalgae commercial production improves sustainability of global fisheries and aquaculture

publishedVersio

Metabolomic Profiling in LRRK2-Related Parkinson's Disease

Mutations in LRRK2 gene represent the most common known genetic cause of Parkinson's disease (PD).We used metabolomic profiling to identify biomarkers that are associated with idiopathic and LRRK2 PD. We compared plasma metabolomic profiles of patients with PD due to the G2019S LRRK2 mutation, to asymptomatic family members of these patients either with or without G2019S LRRK2 mutations, and to patients with idiopathic PD, as well as non-related control subjects. We found that metabolomic profiles of both idiopathic PD and LRRK2 PD subjects were clearly separated from controls. LRRK2 PD patients had metabolomic profiles distinguishable from those with idiopathic PD, and the profiles could predict whether the PD was secondary to LRRK2 mutations or idiopathic. Metabolomic profiles of LRRK2 PD patients were well separated from their family members, but there was a slight overlap between family members with and without LRRK2 mutations. Both LRRK2 and idiopathic PD patients showed significantly reduced uric acid levels. We also found a significant decrease in levels of hypoxanthine and in the ratios of major metabolites of the purine pathway in plasma of PD patients.These findings show that LRRK2 patients with the G2019S mutation have unique metabolomic profiles that distinguish them from patients with idiopathic PD. Furthermore, asymptomatic LRRK2 carriers can be separated from gene negative family members, which raises the possibility that metabolomic profiles could be useful in predicting which LRRK2 carriers will eventually develop PD. The results also suggest that there are aberrations in the purine pathway in PD which may occur upstream from uric acid

Communications Biophysics

Contains reports on six research projects.U. S. Air Force under Contract AF19(604)-4112

Neuroprotective Action of Cycloheximide Involves Induction of Bcl-2 and Antioxidant Pathways

The ability of the protein synthesis inhibitor cycloheximide (CHX) to prevent neuronal death in different paradigms has been interpreted to indicate that the cell death process requires synthesis of “killer” proteins. On the other hand, data indicate that neurotrophic factors protect neurons in the same death paradigms by inducing expression of neuroprotective gene products. We now provide evidence that in embryonic rat hippocampal cell cultures, CHX protects neurons against oxidative insults by a mechanism involving induction of neuroprotective gene products including the antiapoptotic gene bcl-2 and antioxidant enzymes. Neuronal survival after exposure to glutamate, FeSO4, and amyloid β-peptide was increased in cultures pretreated with CHX at concentrations of 50–500 nM; higher and lower concentrations were ineffective. Neuroprotective concentrations of CHX caused only a moderate (20–40%) reduction in overall protein synthesis, and induced an increase in c-fos, c-jun, and bcl-2 mRNAs and protein levels as determined by reverse transcription–PCR analysis and immunocytochemistry, respectively. At neuroprotective CHX concentrations, levels of c-fos heteronuclear RNA increased in parallel with c-fos mRNA, indicating that CHX acts by inducing transcription. Neuroprotective concentrations of CHX suppressed accumulation of H2O2 induced by FeSO4, suggesting activation of antioxidant pathways. Treatment of cultures with an antisense oligodeoxynucleotide directed against bcl-2 mRNA decreased Bcl-2 protein levels and significantly reduced the neuroprotective action of CHX, suggesting that induction of Bcl-2 expression was mechanistically involved in the neuroprotective actions of CHX. In addition, activity levels of the antioxidant enzymes Cu/ Zn-superoxide dismutase, Mn-superoxide dismutase, and catalase were significantly increased in cultures exposed to neuroprotective levels of CHX. Our data suggest that low concentrations of CHX can promote neuron survival by inducing increased levels of gene products that function in antioxidant pathways, a neuroprotective mechanism similar to that used by neurotrophic factors