MorphIC: A 65-nm 738k-Synapse/mm2^2 Quad-Core Binary-Weight Digital Neuromorphic Processor with Stochastic Spike-Driven Online Learning

Recent trends in the field of neural network accelerators investigate weight quantization as a means to increase the resource- and power-efficiency of hardware devices. As full on-chip weight storage is necessary to avoid the high energy cost of off-chip memory accesses, memory reduction requirements for weight storage pushed toward the use of binary weights, which were demonstrated to have a limited accuracy reduction on many applications when quantization-aware training techniques are used. In parallel, spiking neural network (SNN) architectures are explored to further reduce power when processing sparse event-based data streams, while on-chip spike-based online learning appears as a key feature for applications constrained in power and resources during the training phase. However, designing power- and area-efficient spiking neural networks still requires the development of specific techniques in order to leverage on-chip online learning on binary weights without compromising the synapse density. In this work, we demonstrate MorphIC, a quad-core binary-weight digital neuromorphic processor embedding a stochastic version of the spike-driven synaptic plasticity (S-SDSP) learning rule and a hierarchical routing fabric for large-scale chip interconnection. The MorphIC SNN processor embeds a total of 2k leaky integrate-and-fire (LIF) neurons and more than two million plastic synapses for an active silicon area of 2.86mm$^2$ in 65nm CMOS, achieving a high density of 738k synapses/mm$^2$. MorphIC demonstrates an order-of-magnitude improvement in the area-accuracy tradeoff on the MNIST classification task compared to previously-proposed SNNs, while having no penalty in the energy-accuracy tradeoff.Comment: This document is the paper as accepted for publication in the IEEE Transactions on Biomedical Circuits and Systems journal (2019), the fully-edited paper is available at https://ieeexplore.ieee.org/document/876400

Learning without feedback: Fixed random learning signals allow for feedforward training of deep neural networks

While the backpropagation of error algorithm enables deep neural network training, it implies (i) bidirectional synaptic weight transport and (ii) update locking until the forward and backward passes are completed. Not only do these constraints preclude biological plausibility, but they also hinder the development of low-cost adaptive smart sensors at the edge, as they severely constrain memory accesses and entail buffering overhead. In this work, we show that the one-hot-encoded labels provided in supervised classification problems, denoted as targets, can be viewed as a proxy for the error sign. Therefore, their fixed random projections enable a layerwise feedforward training of the hidden layers, thus solving the weight transport and update locking problems while relaxing the computational and memory requirements. Based on these observations, we propose the direct random target projection (DRTP) algorithm and demonstrate that it provides a tradeoff between accuracy and computational cost that is suitable for adaptive edge computing devices.Comment: This document is the paper as accepted for publication in the Frontiers in Neuroscience journal, the fully-edited paper is available at https://www.frontiersin.org/articles/10.3389/fnins.2021.62989

Interaction of straw amendment and soil NO3- content controls fungal denitrification and denitrification product stoichiometry in a sandy soil

The return of agricultural crop residues are vital to maintain or even enhance soil fertility. However, the influence of application rate of crop residues on denitrification and its related gaseous N emissions is not fully understood. We conducted a fully robotized continuous flow incubation experiment using a Helium/Oxygen atmosphere over 30 days to examine the effect of maize straw application rate on: i) the rate of denitrification, ii) denitrification product stoichiometry N2O/(N2O+N2), and iii) the contribution of fungal denitrification to N2O fluxes. Five treatments were established using sieved, repacked sandy textured soil; i) non-amended control, ii) nitrate only, iii) low rate of straw + nitrate, iv) medium rate of straw + nitrate, and iv) high rate of straw + nitrate (n = 3). We simultaneously measured NO, N2O as well as direct N2 emissions and used the N2O 15N site preference signatures of soil-emitted N2O to distinguish N2O production from fungal and bacterial denitrification. Uniquely, soil NO3− measurements were also made throughout the incubation. Emissions of N2O during the initial phase of the experiment (0–13 days) increased almost linearly with increasing rate of straw incorporation and with (almost) no N2 production. However, the rate of straw amendment was negatively correlated with N2O, but positively correlated with N2 fluxes later in the experimental period (13–30 days). Soil NO3− content, in all treatments, was identified as the main factor responsible for the shift from N2O production to N2O reduction. Straw amendment immediately lowered the proportion of N2O from bacterial denitrification, thus implying that more of the N2O emitted was derived from fungi (18 ± 0.7% in control and up to 40 ± 3.0% in high straw treatments during the first 13 days). However, after day 15 when soil NO3− content decreased to <40 mg NO3−-N kg−1 soil, the N2O 15N site preference values of the N2O produced in the medium straw rate treatment showed a sharp declining trend 15 days after onset of experiment thereby indicating a clear shift towards a more dominant bacterial source of N2O. Our study singularly highlights the complex interrelationship between soil NO3− kinetics, crop residue incorporation, fungal denitrification and N2O/(N2O + N2) ratio. Overall we found that the effect of crop residue applications on soil N2O and N2 emissions depends mainly on soil NO3− content, as NO3− was the primary regulator of the N2O/(N2O + N2) product ratio of denitrification. Furthermore, the application of straw residue enhanced fungal denitrification, but only when the soil NO3− content was sufficient to supply enough electron acceptors to the denitrifiers

Terrestrial organic carbon storage in a British moorland

Accurate estimates for the size of terrestrial organic carbon (C) stores are needed to determine their importance in regulating atmospheric CO2 concentrations. The C stored in vegetation and soil components of a British moorland was evaluated in order to: (i) investigate the importance of these ecosystems for C storage and (ii) test the accuracy of the United Kingdom's terrestrial C inventory. The area of vegetation and soil types was determined using existing digitized maps and a Geographical Information System (GIS). The importance of evaluating C storage using 2D area projections, as opposed to true surface areas, was investigated and found to be largely insignificant. Vegetation C storage was estimated from published results of productivity studies at the site supplemented by field sampling to evaluate soil C storage. Vegetation was found to be much less important for C storage than soil, with peat soils, particularly Blanket bog, containing the greatest amounts of C. Whilst the total amount of C in vegetation was similar to the UK national C inventory's estimate for the same area, the national inventory estimate for soil C was over three times higher than the value derived in the current study. Because the UK's C inventory can be considered relatively accurate compared to many others, the results imply that current estimates for soil C storage, at national and global scales, should be treated with caution

In Vitro Efficacy of Myxococcus fulvus ANSM068 to Biotransform Aflatoxin B1

Aflatoxin B1 (AFB1) is commonly found in cereals and animal feeds and causes a significant threat to the food industry and animal production. Several microbial isolates with high AFB1 transformation ability have been identified in our previous studies. The aim of this research was to characterize one of those isolates, Myxococcus fulvus ANSM068, and to explore its biotransformation mechanism. The bacterial isolate of M. fulvus ANSM068, isolated from deer feces, was able to transform AFB1 by 80.7% in liquid VY/2 medium after incubation at 30 °C for 72 h. The supernatant of the bacterial culture was more effective in transforming AFB1 as compared to the cells alone and the cell extract. The transformation activity was significantly reduced and eradicated after the culture supernatant was treated with proteinase K, proteinase K plus SDS and heating. Culture conditions, including nitrogen source, initial pH and incubation temperature were evaluated for an optimal AFB1 transformation. Liquid chromatography mass spectrometry (LCMS) analyses showed that AFB1 was transformed to a structurally different compound. Infrared analysis (IR) indicated that the lactone ring on the AFB1 molecule was modified by the culture supernatant. Chromatographies on DEAE-Ion exchange and Sephadex-Molecular sieve and SDS-PAGE electrophoresis were used to determine active components from the culture supernatant, indicating that enzyme(s) were responsible for the AFB1 biotransformation. This is the first report on AFB1 transformation by a strain of myxobacteria through enzymatic reaction(s)

Hyperbaric oxygen therapy for late radiation-induced tissue toxicity: Prospectively patient-reported outcome measures in breast cancer patients

__Introduction:__ This study examines patient reported outcome measures of women undergoing hyperbaric oxygen treatment (HBOT) after breast-conserving therapy. __Method:__ Included were 57 women treated with HBOT for late radiation-induced tissue toxicity (LRITT) referred in the period January 2014-December 2015. HBOT consisted of (on average) 47 sessions. In total, 80 min of 100 % O2 was administered under increased pressure of 2.4 ATA. Quality of life was assessed before and after treatment using the European Organization for Research and Treatment of Cancer (EORTC) QLQ-BR23, and a NRS pain score. __Results:__ Fifty-seven women were available for evaluation before and after treatment. Before HBOT, patients had severe complaints of pain in the arm/shoulder (46 %), swollen arm/hand (14 %), difficulty to raise arm or move it sideways (45 %), pain in the area of the affected breast (67 %), swollen area of the affected breast (45 %), oversensitivity of the affected breast (54 %), and skin problems on/in the area of the affected breast (32 %); post HBOT, severe complaints were still experienced in 17, 7, 22, 15, 13, 15, and 11 % of the women, respectively. Differences were all significant. The NRS pain score improved at least 1 point (range 0-10) in 81 % of the patients (p < 0.05). __Conclusion:__ In these breast cancer patients treated with HBOT for LRITT, the patient-reported outcomes were positive and improvements were observed. HBOT was a well-tolerated treatment for LRITT and its side-effects were both minimal and reversible

Quantitative historical analysis uncovers a single dimension of complexity that structures global variation in human social organization.

Do human societies from around the world exhibit similarities in the way that they are structured, and show commonalities in the ways that they have evolved? These are long-standing questions that have proven difficult to answer. To test between competing hypotheses, we constructed a massive repository of historical and archaeological information known as "Seshat: Global History Databank." We systematically coded data on 414 societies from 30 regions around the world spanning the last 10,000 years. We were able to capture information on 51 variables reflecting nine characteristics of human societies, such as social scale, economy, features of governance, and information systems. Our analyses revealed that these different characteristics show strong relationships with each other and that a single principal component captures around three-quarters of the observed variation. Furthermore, we found that different characteristics of social complexity are highly predictable across different world regions. These results suggest that key aspects of social organization are functionally related and do indeed coevolve in predictable ways. Our findings highlight the power of the sciences and humanities working together to rigorously test hypotheses about general rules that may have shaped human history