CMOS plus stochastic nanomagnets enabling heterogeneous computers for probabilistic inference and learning.

Extending Moore's law by augmenting complementary-metal-oxide semiconductor (CMOS) transistors with emerging nanotechnologies (X) has become increasingly important. One important class of problems involve sampling-based Monte Carlo algorithms used in probabilistic machine learning, optimization, and quantum simulation. Here, we combine stochastic magnetic tunnel junction (sMTJ)-based probabilistic bits (p-bits) with Field Programmable Gate Arrays (FPGA) to create an energy-efficient CMOS + X (X = sMTJ) prototype. This setup shows how asynchronously driven CMOS circuits controlled by sMTJs can perform probabilistic inference and learning by leveraging the algorithmic update-order-invariance of Gibbs sampling. We show how the stochasticity of sMTJs can augment low-quality random number generators (RNG). Detailed transistor-level comparisons reveal that sMTJ-based p-bits can replace up to 10,000 CMOS transistors while dissipating two orders of magnitude less energy. Integrated versions of our approach can advance probabilistic computing involving deep Boltzmann machines and other energy-based learning algorithms with extremely high throughput and energy efficiency.

Sources of carbon supporting the fast growth of developing immature moso bamboo (Phyllostachys edulis) culms: inference from carbon isotopes and anatomy.

Phyllostachys edulis is a spectacularly fast-growing species that completes its height growth within 2 months after the shoot emerges without producing leaves (fast-growing period, FGP). This phase was considered heterotrophic, with the carbon necessary for the growth being transferred from the mature culms via the rhizomes, although previous studies observed key enzymes and anatomical features related to C4-carbon fixation in developing culms. We tested whether C4-photosynthesis or dark-CO2 fixation through anaplerotic reactions significantly contributes to the FGP, resulting in differences in the natural abundance of δ13C in bulk organic matter and organic compounds. Further, pulse-13CO2-labelling was performed on developing culms, either from the surface or from the internal hollow, to ascertain whether significant CO2 fixation occurs in developing culms. δ13C of young shoots and developing culms were higher (-26.3 to -26.9 ‰) compared to all organs of mature bamboos (-28.4 to -30.1 ‰). Developing culms contained chlorophylls, most observed in the skin tissues. After pulse-13CO2-labelling, the polar fraction extracted from the skin tissues was slightly enriched in 13C, and only a weak 13C enrichment was observed in inner tissues. Main carbon source sustaining the FGP was not assimilated by the developing culm, while a limited anaplerotic fixation of respired CO2 cannot be excluded and is more likely than C4-photosynthetic carbon fixation.

Estimating divergent forest carbon stocks and sinks via a knife set approach.

Forest carbon stocks and sinks (CSSs) have been widely estimated using climate classification tables and linear regression (LR) models with common independent variables (IVs) such as the average diameter at breast height (DBH) of stems and root shoot ratio. However, this approach is relatively ineffective when the explanatory power of IVs is lower than that of unobservable variables. Various environmental and anthropogenic factors affect target variables that cause the correlation between them to be chaotic. Here, we designed a knife set (KS) approach combining LR models and the wandering through random forests (WTF) algorithm and applied it in a specific case of Phyllostachys edulis (Carrière) J. Houz. (P. edulis) forests, which have an irregular relationship between their belowground carbon (BGC) stocks and average DBH. We then validated the KS approach performed by cluster computing to estimate the aboveground carbon (AGC) and BGC stocks and the total net primary production (TNPP). The estimated CSSs were compared to the benchmark of the methodology that applied Tier 1 in the Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas Inventories via 10-fold cross validation, and the KS approach significantly increased precision and accuracy of estimations. Our approach provides general insights to accurately estimate forest CSSs relying on evidence-based field data, even if some target variables are divergent in specific forest types. We also pointed out the reason why current fancy models containing machine learning (ML) or deep learning algorithms are not effective in predicting the target variables of certain chaotic systems is perhaps that the total explanatory power of observable variables is less than that of the total unobservable variables. Quantifying unobservable variables into observable variables is a linchpin of future works related to chaotic system estimation.

Demography and selection analysis of the incipient adaptive radiation of a Hawaiian woody species.

Ecological divergence in a species provides a valuable opportunity to study the early stages of speciation. We focused on Metrosideros polymorpha, a unique example of the incipient radiation of woody species, to examine how an ecological divergence continues in the face of gene flow. We analyzed the whole genomes of 70 plants collected throughout the island of Hawaii, which is the youngest island with the highest altitude in the archipelago and encompasses a wide range of environments. The continuous M. polymorpha forest stands on the island of Hawaii were differentiated into three genetic clusters, each of which grows in a distinctive environment and includes substantial genetic and phenotypic diversity. The three genetic clusters showed signatures of selection in genomic regions encompassing genes relevant to environmental adaptations, including genes associated with light utilization, oxidative stress, and leaf senescence, which are likely associated with the ecological differentiation of the species. Our demographic modeling suggested that the glaberrima cluster in wet environments maintained a relatively large population size and two clusters split: polymorpha in the subalpine zone and incana in dry and hot conditions. This ecological divergence possibly began before the species colonized the island of Hawaii. Interestingly, the three clusters recovered genetic connectivity coincidentally with a recent population bottleneck, in line with the weak reproductive isolation observed in the species. This study highlights that the degree of genetic differentiation between ecologically-diverged populations can vary depending on the strength of natural selection in the very early phases of speciation.

Leaf trichomes in Metrosideros polymorpha can contribute to avoiding extra water stress by impeding gall formation.

BACKGROUND AND AIMS: Plants inhabiting arid environments tend to have leaf trichomes, but their adaptive significance remains unclear. Leaf trichomes are known to play a role in plant defence against herbivores, including gall makers. Because gall formation can increase water loss partly through increased surface area, we tested the novel hypothesis that leaf trichomes could contribute to avoiding extra water stress by impeding gall formation, which would have adaptive advantages in arid environments. METHODS: We focused on Metrosideros polymorpha, an endemic tree species in the Hawaiian Islands, whose leaves often suffer from galls formed by specialist insects, Hawaiian psyllids (Pariaconus spp.). There is large variation in the amount of leaf trichomes (0-40 % of leaf mass) in M. polymorpha. Three gall types are found on the island of Hawaii: the largest is the 'cone' type, followed by 'flat' and 'pit' types. We conducted laboratory experiments to quantify the extent to which gall formation is associated with leaf water relations. We also conducted a field census of 1779 individuals from 48 populations across the entire range of habitats of M. polymorpha on the island of Hawaii to evaluate associations between gall formation (presence and abundance) and the amount of leaf trichomes. KEY RESULTS: Our laboratory experiment showed that leaf minimum conductance was significantly higher in leaves with a greater number of cone- or flat-type galls but not pit-type galls. Our field census suggested that the amount of trichomes was negatively associated with probabilities of the presence of cone- or flat-type galls but not pit-type galls, irrespective of environmental factors. CONCLUSION: Our results suggest that leaf trichomes in M. polymorpha can contribute to the avoidance of extra water stress through interactions with some gall-making species, and potentially increase the fitness of plants under arid conditions.