Expressive probabilistic sampling in recurrent neural networks

In sampling-based Bayesian models of brain function, neural activities are assumed to be samples from probability distributions that the brain uses for probabilistic computation. However, a comprehensive understanding of how mechanistic models of neural dynamics can sample from arbitrary distributions is still lacking. We use tools from functional analysis and stochastic differential equations to explore the minimum architectural requirements for $\textit{recurrent}$ neural circuits to sample from complex distributions. We first consider the traditional sampling model consisting of a network of neurons whose outputs directly represent the samples (sampler-only network). We argue that synaptic current and firing-rate dynamics in the traditional model have limited capacity to sample from a complex probability distribution. We show that the firing rate dynamics of a recurrent neural circuit with a separate set of output units can sample from an arbitrary probability distribution. We call such circuits reservoir-sampler networks (RSNs). We propose an efficient training procedure based on denoising score matching that finds recurrent and output weights such that the RSN implements Langevin sampling. We empirically demonstrate our model's ability to sample from several complex data distributions using the proposed neural dynamics and discuss its applicability to developing the next generation of sampling-based brain models

Predicting taxonomic and functional structure of microbial communities in acid mine drainage.

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities

Temperature-independent ferroelectric property and characterization of high-TC 0.2Bi(Mg1/2Ti1/2)O3-0.8PbTiO3 thin films

Ferroelectric property stability against elevated temperature is significant for ferroelectric film applications, such as non-volatile ferroelectric random access memories. The high-TC 0.2Bi(Mg1/2Ti1/2)O3-0.8PbTiO3 thin films show the temperature-independent ferroelectric properties, which were fabricated on Pt(111)/Ti/SiO2/Si substrates via sol-gel method. The present thin films were well crystallized in a phase-pure perovskite structure with a high (100) orientation and uniform texture. A remanent polarization (2Pr) of 77 μC cm-2 and a local effective piezoelectric coefficient d33* of 60 pm/V were observed in the 0.2Bi(Mg1/2Ti1/2)O3-0.8PbTiO3 thin films. It is interesting to observe a behavior of temperature-independent ferroelectric property in the temperature range of room temperature to 125°C. The remanent polarization, coercive field, and polarization at the maximum field are almost constant in the investigated temperature range. Furthermore, the dielectric loss and fatigue properties of 0.2Bi(Mg 1/2Ti1/2)O3-0.8PbTiO3 thin films have been effectively improved by the Mn-doping

Diversity and aggregation patterns of plant species in a grass community

Abstract Both composition and aggregation patterns of species in a community are the outcome of community self-organizing. In this paper we conducted analysis on species diversity and aggregation patterns of plant species in a grass community, Zhuhai, China. According to the sampling survey, in total of 47 plant species, belonging to 16 families, were found. Compositae had 10 species (21.3%), seconded by Gramineae (9 species, 19.1%), Leguminosae (6 species, 12.8%), Cyperaceae (4 species, 8.5%), and Malvaceae (3 species, 6.4%). The results revealed that the means of aggregation indices I δ , I and m * /m were 21.71, 15.71 and 19.89 respectively and thus individuals of most of plant species strongly followed aggregative distribution. Iwao analysis indicated that both individuals of all species and clumps of all individuals of all species followed aggregative distribution. Taylor's power law indicated that individuals of all species followed aggregative distribution and aggregation intensity strengthened as the increase of mean density. We held that the strong aggregation intensity of a species has been resulted from the strong adaptation ability to the environment, the strong interspecific competition ability and the earlier establishment of the species. Fitting goodness of the mean, I, I δ , m * /m with probability distributions demonstrated that the mean (density), I, I δ , and m * /m over all species followed Weibull distribution rather than normal distribution. Lophatherum gracile, Paederia scandens (Lour.) Merr., Eleusine indica, and Alternanthera philoxeroides (Mart.) Griseb. were mostly aggregative, and Oxalis sp., Eleocharis plantagineiformis, Vernonia cinerea (L.) Less., and Sapium sebiferum (L.) Roxb, were mostly uniform in the spatial distribution. Importance values (IV) showed that Cynodon dactylon was the most important species, seconded by Desmodium triflorum (L.) DC., Cajanus scarabaeoides (L.) Benth., Paspalum scrobiculatum L., and Rhynchelytrum repens. Oxalis sp., Eleocharis plantagineiformis, and Vernonia cinerea (L.) Less. were the least important species in the community. Summed dominance ratio (SDR2) revealed that Cynodon dactylon and Desmodium triflorum (L.) DC. were the most dominant species in the community, followed by Rhynchelytrum repens, Paspalum scrobiculatum L., and Cajanus scarabaeoides (L.) Benth

Giant polarization in super-tetragonal ferroelectric thin films through interphase strain

Strain engineering has emerged as a powerful tool to enhance the performance of known functional materials. Here we demonstrate a general and practical method to obtain super-tetragonality and giant polarization using interphase strain. We use this method to create an out-of-plane–to–in-plane lattice parameter ratio of 1.238 in epitaxial composite thin films of tetragonal lead titanate (PbTiO3), compared to 1.065 in bulk. These thin films with super-tetragonal structure possess a giant remanent polarization, 236.3 microcoulombs per square centimeter, which is almost twice the value of known ferroelectrics. The super-tetragonal phase is stable up to 725°C, compared to the bulk transition temperature of 490°C. The interphase-strain approach could enhance the physical properties of other functional materials.PostprintPeer reviewe

Microalgae Lipid Characterization

To meet the growing interest of utilizing microalgae biomass in the production of biofuels and nutraceutical and pharmaceutical lipids, we need suitable analytical methods and a comprehensive database for their lipid components. The objective of the present work was to demonstrate methodology and provide data on fatty acid composition, lipid class content and composition, characteristics of the unsaponifiables, and type of chlorophylls of five microalgae. Microalgae lipids were fractionated into TAG, FFA, and polar lipids using TLC, and the composition of fatty acids in total lipids and in each lipid class, hydrocarbons, and sterols were determined by GC-MS. Glyco- and phospholipids were profiled by LC/ESI-MS. Chlorophylls and their related metabolites were qualified by LC/APCI-MS. The melting and crystallization profiles of microalgae total lipids and their esters were analyzed by DSC to evaluate their potential biofuel applications. Significant differences and complexities of lipid composition among the algae tested were observed. The compositional information is valuable for strain selection, downstream biomass fractionation, and utilization

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

12118 Freshwater viral genomes

The high-quality and circular genomes from the 231 analyzed freshwater metagenomes