Ten thousand times faster: Classifying multidimensional data on a spiking neuromorphic hardware system.

Discrimination of sensory inputs is a computational task that biological neuronal systems perform very efficiently. Assessing the principles in those systems is a promising approach to develop technical solutions for many problems, such as data classification. A particular problem here is to train a classifier in a supervised fashion to discriminate classes in multidimensional data. We implemented a network of spiking neurons that solves this task using a neuromorphic hardware system, that is, analog neuronal circuits on a silicon substrate. This system enables us to do high-performance computation in a biologically inspired way, with spiking neurons as computational units. In this contribution, we illustrate solutions to technical challenges that occur when implementing a classifier on neuromorphic hardware. 

The network topology of the insect olfactory system provides a well suited template for a neuronal architecture processing multidimensional data. In our classifier network, the value of each dimension of a data vector determines the rate of a stochastically generated spike train. The spike trains are fed into non-overlapping populations of neurons. Those populations project onto an association layer with winner-take-all properties representing the output of the classifier. During classifier training, the weights in this projection are adjusted according to a firing-rate based learning rule. 

The values in multidimensional data sets are typically real numbers, but neuronal firing rates are restricted to values between zero and some maximal value. Hence, the data must be transformed into a positive, bounded representation. We achieved this by representing each data point as a vector of distances to a number of points in data space (“virtual receptors” [1]). The representation by virtual receptors inevitably introduces correlation between input dimensions. We reduced this correlation using lateral inhibition in the first neuronal layer, leading to a significant increase in classifier performance. We found that decorrelation was most efficient when we scaled the inhibitory weights according to the correlation between the connected populations. 

We ran our classifier network on a neuromorphic hardware system that runs at ten thousand times the speed of biological neurons, thus suited for high performance computing [2]. However, the considerable variance of rate-response sensitivity across hardware neurons decreased classification performance. We therefore developed a calibration routine to counteract the neuronal variance.

References

[1] Schmuker, M. and Schneider, G. (2007). Processing and classification of chemical data inspired by insect olfaction. Proc. Natl. Acad. Sci. U S A 104, 20285-20289. 
[2] Brüderle, D., Bill, J., Kaplan, B., Kremkow, J., Meier, K., Müller, E. and Schemmel, J. (2010). Simulator-like exploration of cortical network architectures with a mixed-signal VLSi system. In Proc. of IEEE Intern. Symp. on Circuits and Systems (ISCAS), 2784–8787

A comparison of short-term marking methods for small frogs using a model species, the striped marsh frog (Limnodynastes peronii)

We compared three methods of marking individual small frogs for identification in short-term studies (several days) using a model species, Limnodynastes peronii (the striped marsh frog). We performed a manipulative experiment under laboratory conditions to compare retention times of gentian violet, mercurochrome and powdered fluorescent pigment. Gentian violet produced the most durable marks with retention times between two and four days. Mercurochrome was retained for at least one day by all treated frogs. Fluorescent pigment was either not retained at all or for one day at most, which suggests that this marking method may not be reliable for short-term studies where identification is required. No adverse reactions to any of the marking methods were detected in our study. Our findings indicate that gentian violet represents a promising alternative as a minimally invasive marking technique for studies of small frogs requiring only shortterm retention of identification marks

A predictive framework and review of the ecological impacts of exotic plant invasions on reptiles and amphibians

The invasive spread of exotic plants in native vegetation can pose serious threats to native faunal assemblages. This is of particular concern for reptiles and amphibians because they form a significant component of the world's vertebrate fauna, play a pivotal role in ecosystem functioning and are often neglected in biodiversity research. A framework to predict how exotic plant invasion will affect reptile and amphibian assemblages is imperative for conservation, management and the identification of research priorities. Here, we present a new predictive framework that integrates three mechanistic models. These models are based on exotic plant invasion altering: (1) habitat structure; (2) herbivory and predator-prey interactions; (3) the reproductive success of reptile and amphibian species and assemblages. We present a series of testable predictions from these models that arise from the interplay over time among three exotic plant traits (growth form, area of coverage, taxonomic distinctiveness) and six traits of reptiles and amphibians (body size, lifespan, home range size, habitat specialisation, diet, reproductive strategy). A literature review provided robust empirical evidence of exotic plant impacts on reptiles and amphibians from each of the three model mechanisms. Evidence relating to the role of body size and diet was less clear-cut, indicating the need for further research. The literature provided limited empirical support for many of the other model predictions. This was not, however, because findings contradicted our model predictions but because research in this area is sparse. In particular, the small number of studies specifically examining the effects of exotic plants on amphibians highlights the pressing need for quantitative research in this area. There is enormous scope for detailed empirical investigation of interactions between exotic plants and reptile and amphibian species and assemblages. The framework presented here and further testing of predictions will provide a basis for informing and prioritising environmental management and exotic plant control efforts. © 2010 The Authors. Biological Reviews © 2010 Cambridge Philosophical Society

Sistem Pendukung Keputusan Penentuan Penerimaan Bantuan Sembako Covid-19 Pada Desa Ujung Serdang Menggunakan Metode SMART

Pemberian Sembako Covid_19 pada desa ujung Serdang membutuhkan ketepatan dalam pendistribusian untuk menjaga keadilan serta kesejahtraan masyarakat. Namun dalam pemilihan penerimaan bantuan covid-19 haruslah melihat dari beberapa penilaian yang akurat. Selama ini pemberian bantuan masih menggunakan metode manual yaitu pemerintah desa beserta timnya memilih langsung masyarakat yang layak mererima bantuan sehingga sering sekali terjadi ketidaktepatan serta masih adanya budaya mengutamakan keluarga. Sistem pendukung keputusan dalam pemilihan pemberian bantuan pada masyarakat Desa Ujung Serdang sangat dibutuhkan sehingga pemerintah Desa Ujung Serdang untuk selanjutnya dapat memberikan bantuan kepada masyarakat dengan tepat sasaran dan cepat. Sistem Pendukung keputusan dengan penerapan Metode Simple Multi Attribute Rating Technique (SMART). Metode SMART digunakan untuk menganalisa dalam menentukan masyarakat yang layak mendapatkan bantuan yang dibuat berdasarkan kriteria, sistem pendukung keputusan ini dibangun dengan bahasa pemrograman Visual Basic 2010 dan database menggunakan MySQL. Penelitian ini ditargetkan dapat membantu pemerintah Desa Ujung Serdang dalam menentukan penerima bantuan Covid-19. Dari hasil penelitian yang telah dilakukan bahwa hasil kelayakan penerimaan bantuan sembako Covid-19 pada Desa Ujung Serdang yaitu Hendra Tarigan dengan nilai 92 (Layak), Richard Ginting dengan nilai 85 (Layak), Herman Sembiring dengan nilai 77 (layak), David Ginting dengan nilai 75 (Layak), Efendy Sitepu dengan nilai 68 (Layak), Pilih Ginting dengan nilai 65 (Layak), Imanuel Bukit dengan nilai 43,5 (Tidak Layak), Rejeki Ginting dengan nilai 32 (Tidak Layak), Tamrin Tarigan dengan nilai 30 (Tidak Layak), Mberngap Sembiring dengan nilai 27 Tidak Layak)

A tour of contemporary color vision research

The study of color vision encompasses many disciplines, including art, biochemistry, biophysics, brain imaging, cognitive neuroscience, color preferences, colorimetry, computer modelling, design, electrophysiology, language and cognition, molecular genetics, neuroscience, physiological optics, psychophysics and physiological optics. Coupled with the elusive nature of the subjective experience of color, this wide range of disciplines makes the study of color as challenging as it is fascinating. This overview of the special issue Color: Cone Opponency and Beyond outlines the state of the science of color, and points to some of the many questions that remain to be answered in this exciting field

Selecting low-flammability plants as green firebreaks within sustainable urban garden design

In response to an increasing risk of property loss from wildfires at the urban–wildland interface, there has been growing interest around the world in the plant characteristics of urban gardens that can be manipulated to minimize the chances of property damage or destruction. To date, considerable discussion of this issue can be found in the ‘grey’ literature, covering garden characteristics such as the spatial arrangement of plants in relation to each other, proximity of plants to houses, plant litter and fuel reduction, and the use of low-flammability plants as green firebreaks [1,2,3,4]. Recently, scientific studies from a geographically wide range of fire-prone regions including Europe [5], the USA [6], Australia [7], South Africa [8], and New Zealand [9] have been explicitly seeking to quantify variation among plant species with respect to different aspects of their flammability and to identify low-flammability horticultural species appropriate for implementation as green firebreaks in urban landscapes. The future prospects of this scientific work will ultimately depend on how successfully the results are integrated into the broader context of garden design in fire-prone regions at the urban–wildland interface. Although modern design of urban gardens must consider more than just the issue of green firebreaks, we and others [10,11] believe that selection of low-flammability plants should be high on the priority list of plant selection criteria in fire-prone regions

Protocol for a prospective double-blind, randomised, placebo-controlled feasibility trial of octreotide infusion during liver transplantation

Introduction Liver transplantation is a complex operation that can provide significant improvements in quality of life and survival to the recipients. However, serious complications are common and include major haemorrhage, hypotension and renal failure. Blood transfusion and the development of acute kidney injury lead to both short-term and long-term poor patient outcomes, including an increased risk of death, graft failure, length of stay and reduced quality of life. Octreotide may reduce the incidence of renal dysfunction, perioperative haemorrhage and enhance intraoperative blood pressure. However, octreotide does have risks, including resistant bradycardia, hyperglycaemia and hypoglycaemia and QT prolongation. Hence, a randomised controlled trial of octreotide during liver transplantation is needed to determine the cost-efficacy and safety of its use; this study represents a feasibility study prior to this trial. Methods and analysis We describe a multicentre, double-blind, randomised, placebo-controlled feasibility study of continuous infusion of octreotide during liver transplantation surgery. We will recruit 30 adult patients at two liver transplant centres. A blinded infusion during surgery will be administered in a 2:1 ratio of octreotide:placebo. The primary outcomes will determine the feasibility of this study design. These include the recruitment ratio, correct administration of blinded study intervention, adverse event rates, patient and clinician enrolment refusal and completion of data collection. Secondary outcome measures of efficacy and safety will help shape future trials by assessing potential primary outcome measures and monitoring safety end points. No formal statistical tests are planned. This manuscript represents study protocol number 1.3, dated 2 June 2021. Ethics and dissemination This study has received Research Ethics Committee approval. The main study outcomes will be submitted to an open-access journal. Trial sponsor The Joint Research Office, University College London, UK. Neither the sponsor nor the funder have any role in study design, collection, management, analysis and interpretation of data, writing of the study report or the decision to submit the report for publication. Trial registration The study is registered with ClinicalTrials.gov (NCT04941911) with recruitment due to start in August 2021 with anticipated completion in July 2022. Clinical trials unit Surgical and Interventional Group, Division of Surgery & Interventional Science, University College London

Posterior Bearing Overhang Following Medial and Lateral Mobile Bearing Unicompartmental Knee Replacements

This study explores the extent of bearing overhang following mobile bearing Oxford unicompartmental knee replacement (OUKR) (Oxford Phase 3, Zimmer Biomet). The Oxford components are designed to be fully congruent, however knee movements involve femoral rollback, which may result in bearing overhang at the posterior margin of the tibial implant, with potential implications for; pain, wear, and dislocation. Movement is known to be greater, and therefore posterior overhang more likely to occur, with; lateral compared to medial implants, anterior cruciate ligament deficiency, and at extremes of movement. 24 medial, and 20 domed lateral, OUKRs underwent sagittal plane knee fluoroscopy during step‐up and forward lunge exercises. The bearing position was inferred from the relative position of the femoral and tibial components. Based on the individual component sizes and geometry the extent the posterior part of the bearing which overhung the posterior part of the tibial component was calculated. There was no significant posterior overhang in knees with medial implants. Knees with lateral domed implants exhibited overhang at flexion angles beyond 60°, the magnitude of which increased with increasing flexion angle, reaching a maximum of 50% of the bearing length at 140° (range 0‐140°). This demonstrates a clear difference between the kinematics, and prevalence and extent of posterior bearing overhang between medial and lateral OUKRs

Towards a Time-predictable Dual-Issue Microprocessor: The Patmos Approach

Current processors are optimized for average case performance, often leading to a high worst-case execution time (WCET). Many architectural features that increase the average case performance are hard to be modeled for the WCET analysis. In this paper we present Patmos, a processor optimized for low WCET bounds rather than high average case performance. Patmos is a dual-issue, statically scheduled RISC processor. The instruction cache is organized as a method cache and the data cache is organized as a split cache in order to simplify the cache WCET analysis. To fill the dual-issue pipeline with enough useful instructions, Patmos relies on a customized compiler. The compiler also plays a central role in optimizing the application for the WCET instead of average case performance

Large-scale collective action to avoid an Amazon tipping point - key actors and interventions

The destruction of the Amazon is a major global environmental issue, not only because of greenhouse gas emissions or direct impacts on biodiversity and livelihoods, but also due to the forest\u27s role as a tipping element in the Earth System. With nearly a fifth of the Amazon already lost, there are already signs of an imminent forest dieback process that risks transforming much of the rainforest into a drier ecosystem, with climatic implications across the globe. There is a large body of literature on the underlying drivers of Amazon deforestation. However, insufficient attention has been paid to the behavioral and institutional microfoundations of change. Fundamental issues concerning cooperation, as well as the mechanisms facilitating or hampering such actions, can play a much more central role in attempts to unravel and address Amazon deforestation. We thus present the issue of preventing the Amazon biome from crossing a biophysical tipping point as a large-scale collective action problem. Drawing from collective action theory, we apply a novel analytical framework on Amazon conservation, identifying six variables that synthesize relevant collective action stressors and facilitators: information, accountability, harmony of interests, horizontal trust, knowledge about consequences, and sense of responsibility. Drawing upon literature and data, we assess Amazon deforestation and conservation through our heuristic lens, showing that while growing transparency has made information availability a collective action facilitator, lack of accountability, distrust among actors, and little sense of responsibility for halting deforestation remain key stressors. We finalize by discussing interventions that can help break the gridlock