Dual sampling neural network: Learning without explicit optimization

脳型人工知能の実現に向けた新理論の構築に成功 --ヒントは脳のシナプスの「揺らぎ」--. 京都大学プレスリリース. 2022-10-24.Artificial intelligence using neural networks has achieved remarkable success. However, optimization procedures of the learning algorithms require global and synchronous operations of variables, making it difficult to realize neuromorphic hardware, a promising candidate of low-cost and energy-efficient artificial intelligence. The optimization of learning algorithms also fails to explain the recently observed criticality of the brain. Cortical neurons show a critical power law implying the best balance between expressivity and robustness of the neural code. However, the optimization gives less robust codes without the criticality. To solve these two problems simultaneously, we propose a model neural network, dual sampling neural network, in which both neurons and synapses are commonly represented as a probabilistic bit like in the brain. The network can learn external signals without explicit optimization and stably retain memories while all entities are stochastic because seemingly optimized macroscopic behavior emerges from the microscopic stochasticity. The model reproduces various experimental results, including the critical power law. Providing a conceptual framework for computation by microscopic stochasticity without macroscopic optimization, the model will be a fundamental tool for developing scalable neuromorphic devices and revealing neural computation and learning

有髄神経線維の活動電位の高速伝導に関する軸索液の誘電率を適用した等価回路の検証

首都大学東京, 2019-03-25, 博士（理学）, 甲第856号首都大学東

Made-to-Order Spiking Neuron Model Equipped with a Multi-Timescale Adaptive Threshold

Information is transmitted in the brain through various kinds of neurons that respond differently to the same signal. Full characteristics including cognitive functions of the brain should ultimately be comprehended by building simulators capable of precisely mirroring spike responses of a variety of neurons. Neuronal modeling that had remained on a qualitative level has recently advanced to a quantitative level, but is still incapable of accurately predicting biological data and requires high computational cost. In this study, we devised a simple, fast computational model that can be tailored to any cortical neuron not only for reproducing but also for predicting a variety of spike responses to greatly fluctuating currents. The key features of this model are a multi-timescale adaptive threshold predictor and a nonresetting leaky integrator. This model is capable of reproducing a rich variety of neuronal spike responses, including regular spiking, intrinsic bursting, fast spiking, and chattering, by adjusting only three adaptive threshold parameters. This model can express a continuous variety of the firing characteristics in a three-dimensional parameter space rather than just those identified in the conventional discrete categorization. Both high flexibility and low computational cost would help to model the real brain function faithfully and examine how network properties may be influenced by the distributed characteristics of component neurons

The magnetic structure of the intermelallic compounds in the cubic Laves phase (C15) crystal

Magnetic structure of intermetallic compounds of rare earth and 3d transition metal with the C15 structure is studied on the basis of the classical Heisenberg model. By making use of the Lyons-Kaplan method, magnetic phase diagram is calculated with respect to the states with the modulation wave vector Q equivalent to [0,0,0] to obtain seven types of spin structure, and their stability is compared with screw structures of Q parallel with [0,0,1], [1,1,0] and [1,1,1]. The stable region of the Q = [0,0,0] states is limited most drastically by the modulation of Q ∥ [1,1,0].Article信州大学理学部紀要 30(1): 7-23(1995)departmental bulletin pape

Low cost maize stover biochar as an alternative to inorganic fertilizer for improvement of soil chemical properties, growth and yield of tomatoes on degraded soil of Northern Uganda

Background Soil fertility decline due to nutrient mining coupled with low inorganic fertilizer usage is a major cause of low crop yields across sub-Saharan Africa. Recently, biochar potential to improve soil fertility has gained signifcant attention but there are limited studies on the use of biochar as an alternative to inorganic fertilizers. In this study, we determined the efect of maize stover biochar without inorganic fertilizers on soil chemical properties, growth and yield of tomatoes (Solanum lycopersicum L.). A feld experiment was conducted in 2022 for two consecutive seasons in Northern Uganda. The experiment included fve treatments; inorganic fertilizer (control), biochar applied at rates of 3.5, 6.9, 13.8 and 27.6 t ha−1. Results In this study, maize stover biochar improved all the soil chemical properties. Compared to the control, pH signifcantly increased by 27% in the 27.6 t ha−1 while total N increased by 35.6% in the 13.8 t ha−1. Although P was signifcantly low in the 3.5 t ha−1, 6.9 t ha−1 and 13.8 t ha−1, it increased by 3.9% in the 27.6 t ha−1. Exchangeable K was signifcantly increased by 42.7% and 56.7% in the 13.8 t ha−1 and 27.6 t ha−1 respectively. Exchangeable Ca and Mg were also higher in the biochar treatment than the control. Results also showed that plant height, shoot weight, and all yield parameters were signifcantly higher in the inorganic fertilizer treatment than in the 3.5, 6.9, and 13.8 t ha−1 treatments. Interestingly, maize stover biochar at 27. 6 t ha−1 increased fruit yield by 16.1% compared to the control suggesting it could be used as an alternative to inorganic fertilizer. Conclusions Maize stover biochar applied at 27.6 t ha−1 improved soil chemical properties especially pH, N, P and K promoting growth and yield of tomatoes. Therefore, maize stover biochar could be recommended as an alternative to expensive inorganic fertilizers for tomato production in Northern Uganda

Plant Species Diversity along a Precipitation Gradient in Temperate Grasslands of China and Mongolia

Variations in species diversity can be linked to several ecological gradients (Huston 1994). Plant functional type is characterized by an adaption of plants to certain ecological conditions (Galan de Mera et al. 1999). In addition, patterns of species richness along an environmental gradient might be more interpretable by considering both species richness of different functional types and total species richness (Pausas and Austin 2001). Water availability generally signifies total precipitation available to support plant growth (Adler and Levine 2007), and its temporal distribution is the main driver of species composition and species diversity in arid and semi-arid environments (Shmida and Wilson 1985; Kutiel et al. 2000). Therefore, understanding how precipitation influences species diversity at a spatial scale will be critical for predicting the impacts of altered precipitation on vegetation patterns. This study aimed to examine the vegetation response to a spatial precipitation gradient in temperature grassland in China and Mongolia

Initial distribution volume of glucose can be approximated using a conventional glucose analyzer in the intensive care unit

INTRODUCTION: We previously reported that initial distribution volume of glucose (IDVG) reflects central extracellular fluid volume, and that IDVG may represent an indirect measure of cardiac preload that is independent of the plasma glucose values present before glucose injection or infusion of insulin and/or vasoactive drugs. The original IDVG measurement requires an accurate glucose analyzer and repeated arterial blood sampling over a period of 7 min after glucose injection. The purpose of the present study was to compare approximated IDVG, derived from just two blood samples, versus original IDVG, and to test whether approximated IDVG is an acceptable alternative measure of IDVG in the intensive care unit. METHODS: A total of 50 consecutive intensive care unit patients were included, and the first IDVG determination in each patient was analyzed. Glucose (5 g) was injected through the central venous line to calculate IDVG. Original IDVG was calculated using a one-compartment model from serial incremental arterial plasma glucose concentrations above preinjection using a reference glucose analyzer. Approximated IDVG was calculated from glucose concentrations in both plasma and whole blood, using a combined blood gas and glucose analyzer, drawn at two time points: immediately before glucose injection and 3 min after injection. Subsequently, each approximated IDVG was calculated using a formula we proposed previously. RESULTS: The difference (mean ± standard deviation) between approximated IDVG calculated from plasma samples and original IDVG was -0.05 ± 0.54 l, and the difference between approximated IDVG calculated from whole blood samples and original IDVG was -0.04 ± 0.61 l. There was a linear correlation between approximated and original IDVG (r(2 )= 0.92 for plasma samples, and r(2 )= 0.89 for whole blood samples). CONCLUSION: Our findings demonstrate that there was good correlation between each approximated IDVG and original IDVG, although the two measures are not interchangeable. This suggests that approximated IDVG is clinically acceptable as an alternative calculation of IDVG, although approximated and original IDVGs are not equivalent; plasma rather than whole blood measurements are preferable