Large membranes structures for scientific remote sensing and space exploration

As part of the NASA Floyd L.Thompson Fellowship, the author spent four months in the beginning of 2005 at the International Center for Numerical Methods in Engineering (CIMNE) in Barcelona, Spain. During this visit, he had many opportunities to discuss the new NASA Space Exploration Program with graduate students and faculty at CIMNE, and worked closely with several researchers focusing on the modeling and analysis of thin-film membranes. Here, a brief overview of the space exploration technologies that use very large structural membranes is presented, together with some comments related to computational mechanics issues for simulating the response of large membrane structures

Let’s end taxonomic blank slates with molecular morphology

Many known evolutionary lineages have yet to be described formally due to a lack of traditional morphological characters. This is true for genetically distinctive groups within the amoeboid Placozoa animals, the protists in ponds, and the bacteria that cover nearly everything. These taxonomic tabula rasae, or blank slates, are problematic; without names, communication is hampered and other scientific progress is slowed. We suggest that the morphology of molecules be used to help alleviate this issue. Molecules, such as proteins, have structure. Proteins are even visualizable with X-ray crystallography, albeit more easily detected by and easier to work with using genomic sequencing. Given their structured nature, we believe they should not be considered as anything less than traditional morphology. Protein-coding gene content (presence/absence) can also be used easily with genomic sequences, and is a convenient binary character set. With molecular morphology, we believe that each taxonomic tabula rasa can be solved

A Global eDNA Comparison of Freshwater Bacterioplankton Assemblages Focusing on Large-River Floodplain Lakes of Brazil

With its network of lotic and lentic habitats that shift during changes in seasonal connection, the tropical and subtropical large-river systems represent possibly the most dynamic of all aquatic environments. Pelagic water samples were collected from Brazilian floodplain lakes (total n = 58) in four floodpulsed systems (Amazon [n = 21], Araguaia [n = 14], Paraná [n = 15], and Pantanal [n = 8]) in 2011–2012 and sequenced via 454 for bacterial environmental DNA using 16S amplicons; additional abiotic field and laboratory measurements were collected for the assayed lakes.We report here a global comparison of the bacterioplankton makeup of freshwater systems, focusing on a comparison of Brazilian lakes with similar freshwater systems across the globe. The results indicate a surprising similarity at higher taxonomic levels of the bacterioplankton in Brazilian freshwater with global sites. However, substantial novel diversity at the family level was also observed for the Brazilian freshwater systems. Brazilian freshwater bacterioplankton richness was relatively average globally. Ordination results indicate that Brazilian bacterioplankton composition is unique from other areas of the globe. Using Brazil-only ordinations, floodplain system differentiation most strongly correlated with dissolved oxygen, pH, and phosphate. Our data on Brazilian freshwater systems in combination with analysis of a collection of freshwater environmental samples from across the globe offers the first regional picture of bacterioplankton diversity in these important freshwater systems

Luciferin production and luciferase transcription in the bioluminescent copepod Metridia lucens

Bioluminescent copepods are often the most abundant marine zooplankton and play critical roles in oceanic food webs. Metridia copepods exhibit particularly bright bioluminescence, and the molecular basis of their light production has just recently begun to be explored. Here we add to this body of work by transcriptomically profiling Metridia lucens, a common species found in temperate, northern, and southern latitudes. In this previously molecularly-uncharacterized species, we find the typical luciferase paralog gene set found in Metridia. More surprisingly, we recover noteworthy putative luciferase sequences that had not been described from Metridia species, indicating that bioluminescence produced by these copepods may be more complex than previously known. This includes another copepod luciferase, as well as one from a shrimp. Furthermore, feeding experiments using mass spectrometry and 13C labelled L-tyrosine and L-phenylalanine firmly establish that M. lucens produces its own coelenterazine luciferin rather than acquiring it through diet. This coelenterazine synthesis has only been directly confirmed in one other copepod species

The s-process in the Nd-Pm-Sm region: Neutron activation of 147Pm

The Nd-Pm-Sm branching is of interest for the study of the s-process, related to the production of heavy elements in stars. As 148Sm and 150Sm are s-only isotopes, the understanding of the branching allows constraining the s-process neutron density. In this context the key physics input needed is the cross section of the three unstable nuclides in the region: 147Nd (10.98 d half-life), 147Pm (2.62 yr) and 148Pm (5.37 d). This paper reports on the activation measurement of 147Pm, the longest-lived of the three nuclides. The cross section measurement has been carried out by activation at the SARAF LiLiT facility using a 56(2) μg target. Compared to the single previous measurement of 147Pm, the measurement presented herein benefits from a target 2000 times more massive. The resulting Maxwellian Averaged Cross Section (MACS) to the ground and metastable states in 148Pm are 469(50) mb and 357(27) mb. These values are 41% higher (to the ground state) and 15% lower (to the metastable state) than the values reported so far, leading however to a total cross section of 826(107) mb consistent within uncertainties with the previous result and hence leaving unchanged the previous calculation of the s-process neutron density.University of Seville [FPA2013-45083P, FPA2014-53290-C2-2-P, FPA2016-77689-C2-1-R]EC FP7 projects NeutAndalus [334315]CHANDA [605203

A global empirical typology of anthropogenic drivers of environmental change in deltas

It is broadly recognized that river delta systems around the world are under threat from a range of anthropogenic activities. These activities occur at the local delta scale, at the regional river and watershed scale, and at the global scale. Tools are needed to support generalization of results from case studies in specific deltas. Here, we present a methodology for quantitatively constructing an empirical typology of anthropogenic change in global deltas. Utilizing a database of environmental change indicators, each associated with increased relative sea-level rise and coastal wetland loss, a clustering analysis of 48 global deltas provides a quantitative assessment of systems experiencing similar or dissimilar sources and degrees of anthropogenic stress. By identifying quantitatively similar systems, we hope to improve the transferability of scientific results across systems, and increase the effectiveness of delta management best practices. Both K-Means and Affinity Propagation clustering algorithms find similar clusters, with relative stability across small changes in KMeans cluster number. High-latitude deltas appear similar, in terms of anthropogenic environmental stress, to several low-population, low-latitude systems, including the Amazon delta, despite substantially different climatic regimes. Highly urbanized deltas in Southeast Asia form a distinct cluster. By providing a quantitative boundary between groups of delta systems, this approach may also be useful for assessing future delta change and sustainability given projected population growth, urbanization, and economic development trends

Can language models learn from explanations in context?

Large language models can perform new tasks by adapting to a few in-context examples. For humans, rapid learning from examples can benefit from explanations that connect examples to task principles. We therefore investigate whether explanations of few-shot examples can allow language models to adapt more effectively. We annotate a set of 40 challenging tasks from BIG-Bench with explanations of answers to a small subset of questions, as well as a variety of matched control explanations. We evaluate the effects of various zero-shot and few-shot prompts that include different types of explanations, instructions, and controls on the performance of a range of large language models. We analyze these results using statistical multilevel modeling techniques that account for the nested dependencies among conditions, tasks, prompts, and models. We find that explanations of examples can improve performance. Adding untuned explanations to a few-shot prompt offers a modest improvement in performance; about 1/3 the effect size of adding few-shot examples, but twice the effect size of task instructions. We then show that explanations tuned for performance on a small validation set offer substantially larger benefits; building a prompt by selecting examples and explanations together substantially improves performance over selecting examples alone. Hand-tuning explanations can substantially improve performance on challenging tasks. Furthermore, even untuned explanations outperform carefully matched controls, suggesting that the benefits are due to the link between an example and its explanation, rather than lower-level features of the language used. However, only large models can benefit from explanations. In summary, explanations can support the in-context learning abilities of large language models o

Fine-tuning language models to find agreement among humans with diverse preferences

Recent work in large language modeling (LLMs) has used fine-tuning to align outputs with the preferences of a prototypical user. This work assumes that human preferences are static and homogeneous across individuals, so that aligning to a a single "generic" user will confer more general alignment. Here, we embrace the heterogeneity of human preferences to consider a different challenge: how might a machine help people with diverse views find agreement? We fine-tune a 70 billion parameter LLM to generate statements that maximize the expected approval for a group of people with potentially diverse opinions. Human participants provide written opinions on thousands of questions touching on moral and political issues (e.g., "should we raise taxes on the rich?"), and rate the LLM's generated candidate consensus statements for agreement and quality. A reward model is then trained to predict individual preferences, enabling it to quantify and rank consensus statements in terms of their appeal to the overall group, defined according to different aggregation (social welfare) functions. The model produces consensus statements that are preferred by human users over those from prompted LLMs (>70%) and significantly outperforms a tight fine-tuned baseline that lacks the final ranking step. Further, our best model's consensus statements are preferred over the best human-generated opinions (>65%). We find that when we silently constructed consensus statements from only a subset of group members, those who were excluded were more likely to dissent, revealing the sensitivity of the consensus to individual contributions. These results highlight the potential to use LLMs to help groups of humans align their values with one another

A liquid crystalline copper phthalocyanine derivative for high performance organic thin film transistors

This journal is © The Royal Society of Chemistry 2012Bottom-gate, bottom-contact organic thin film transistors (OTFTs) were fabricated using solvent soluble copper 1,4,8,11,15,18,22,25-octakis(hexyl)phthalocyanine as the active semiconductor layer. The compound was deposited as 70 nm thick spin-coated films onto gold source–drain electrodes supported on octadecyltrichlorosilane treated 250 nm thick SiO2 gate insulators. The performance of the OTFTs was optimised by investigating the effects of vacuum annealing of the films at temperatures between 50 0C and 200 0C, a range that included the thermotropic mesophase of the bulk material. These effects were monitored by ultraviolet-visible absorption spectroscopy, atomic force microscopy and XRD measurements. Device performance was shown to be dependent upon the annealing temperature due to structural changes of the film. Devices heat treated at 100 0C under vacuum (≥10-7 mbar) were found to exhibit the highest field-effect mobility, 0.7 cm2 V^-1 s^-1, with an on–off current modulation ratio of~107, a reduced threshold voltage of 2.0 V and a sub-threshold swing of 1.11 V per decade.UK Technology Strategy Board (Project no: TP/6/EPH/6/S/K2536J) and UK National Measurement System (Project IRD C02 ‘‘Plastic Electronics’’, 2008–2011)

Luciferin production and luciferase transcription in the bioluminescent copepod Metridia lucens

Bioluminescent copepods are often the most abundant marine zooplankton and play critical roles in oceanic food webs. Metridia copepods exhibit particularly bright bioluminescence, and the molecular basis of their light production has just recently begun to be explored. Here we add to this body of work by transcriptomically profiling Metridia lucens, a common species found in temperate, northern, and southern latitudes. In this previously molecularly-uncharacterized species, we find the typical luciferase paralog gene set found in Metridia. More surprisingly, we recover noteworthy putative luciferase sequences that had not been described from Metridia species, indicating that bioluminescence produced by these copepods may be more complex than previously known. This includes another copepod luciferase, as well as one from a shrimp. Furthermore, feeding experiments using mass spectrometry and 13C labelled L-tyrosine and L-phenylalanine firmly establish that M. lucens produces its own coelenterazine luciferin rather than acquiring it through diet. This coelenterazine synthesis has only been directly confirmed in one other copepod species