Bacterial culture components activating colorimetric transition in polydiacetylene nanofiber composites

2020 Summer.Includes bibliographical references.Polydiacetylene (PDA) demonstrates colorimetric transition behaviors due to conformational changes in π conjugated backbone of PDA macromolecules at external stimuli of bacteria, suggesting potential applications in biosensors. However, the bacterial culture components activating colorimetric transition in PDAs are still undetermined due to the complexity of the bacterial system. In this study, PU-PDA nanofiber composite was prepared via electrospinning and tested with components from Escherichia coli (E. coli) culture including supernatant fluid, cell pellet, and extracellular polymeric substances (EPS). When PU-PDA nanofiber was tested with supernatant fluid, it changed color from blue to red. In contrast, bacterial cell pellets could not induce a color change, suggesting the color-changing substances (CCS) are not cell-associated, rather can be found in the spent media (supernatant fluid) generated by E. coli during its growth phase. Intense color change in the nanofiber by the autoclaved supernatant fluid indicated that the CCS may not be a protein, DNA, or RNA since they denature in high heat and pressure from the autoclaving process. With an increase in storage time of the supernatant fluid, the color-changing rate was reduced significantly, suggesting a degradation in CCS with time. Free EPS from the supernatant fluid could induce a color change in the nanofibers, which confirmed that EPS contains the CCS. No significant changes were found in the morphology of PU-PDA nanofibers before and after the exposure of E. coli culture components. Critical bacterial concentration (CBC) was found approximately 9 × 108 CFU/ml, suggesting the efficiency of the PU-PDA nanofiber composite to be used as a biosensor. Additionally, solvatochromism of the nanofiber composite was investigated using organic solvents commonly used in extracting bacterial culture components. The results from this study provided a guideline for using PU-PDA nanofiber composite as a biosensor in point-of-care applications

Optimizing the Age-of-Information for Mobile Users in Adversarial and Stochastic Environments

We study a multi-user downlink scheduling problem for optimizing the freshness of information available to users roaming across multiple cells. We consider both adversarial and stochastic settings and design scheduling policies that optimize two distinct information freshness metrics, namely the average age-of-information and the peak age-of-information. We show that a natural greedy scheduling policy is competitive with the optimal offline policy in the adversarial setting. We also derive fundamental lower bounds to the competitive ratio achievable by any online policy. In the stochastic environment, we show that a Max-Weight scheduling policy that takes into account the channel statistics achieves an approximation factor of $2$ for minimizing the average age of information in two extreme mobility scenarios. We conclude the paper by establishing a large-deviation optimality result achieved by the greedy policy for minimizing the peak age of information for static users situated at a single cell.Comment: arXiv admin note: text overlap with arXiv:2001.0547

XploreNAS: Explore Adversarially Robust & Hardware-efficient Neural Architectures for Non-ideal Xbars

Compute In-Memory platforms such as memristive crossbars are gaining focus as they facilitate acceleration of Deep Neural Networks (DNNs) with high area and compute-efficiencies. However, the intrinsic non-idealities associated with the analog nature of computing in crossbars limits the performance of the deployed DNNs. Furthermore, DNNs are shown to be vulnerable to adversarial attacks leading to severe security threats in their large-scale deployment. Thus, finding adversarially robust DNN architectures for non-ideal crossbars is critical to the safe and secure deployment of DNNs on the edge. This work proposes a two-phase algorithm-hardware co-optimization approach called XploreNAS that searches for hardware-efficient & adversarially robust neural architectures for non-ideal crossbar platforms. We use the one-shot Neural Architecture Search (NAS) approach to train a large Supernet with crossbar-awareness and sample adversarially robust Subnets therefrom, maintaining competitive hardware-efficiency. Our experiments on crossbars with benchmark datasets (SVHN, CIFAR10 & CIFAR100) show upto ~8-16% improvement in the adversarial robustness of the searched Subnets against a baseline ResNet-18 model subjected to crossbar-aware adversarial training. We benchmark our robust Subnets for Energy-Delay-Area-Products (EDAPs) using the Neurosim tool and find that with additional hardware-efficiency driven optimizations, the Subnets attain ~1.5-1.6x lower EDAPs than ResNet-18 baseline.Comment: 16 pages, 8 figures, 2 table

HyDe: A Hybrid PCM/FeFET/SRAM Device-search for Optimizing Area and Energy-efficiencies in Analog IMC Platforms

Today, there are a plethora of In-Memory Computing (IMC) devices- SRAMs, PCMs & FeFETs, that emulate convolutions on crossbar-arrays with high throughput. Each IMC device offers its own pros & cons during inference of Deep Neural Networks (DNNs) on crossbars in terms of area overhead, programming energy and non-idealities. A design-space exploration is, therefore, imperative to derive a hybrid-device architecture optimized for accurate DNN inference under the impact of non-idealities from multiple devices, while maintaining competitive area & energy-efficiencies. We propose a two-phase search framework (HyDe) that exploits the best of all worlds offered by multiple devices to determine an optimal hybrid-device architecture for a given DNN topology. Our hybrid models achieve upto 2.30-2.74x higher TOPS/mm^2 at 22-26% higher energy-efficiencies than baseline homogeneous models for a VGG16 DNN topology. We further propose a feasible implementation of the HyDe-derived hybrid-device architectures in the 2.5D design space using chiplets to reduce design effort and cost in the hardware fabrication involving multiple technology processes.Comment: Accepted to IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS

The Role of IPR in Plant Genetic Engineering

The role and status of Patent laws in the protection of plant species which have been genetically modified is currently uncertain in India. Discussions and debates regarding the same are rife and experts have different views regarding the whole aspect concerning economical and ethical considerations. Genetically engineered plants and modified crop plants are of significant economic value. In India, they face critical challenges, for instance, the requirement of dependable public policies and vigorous frameworks for regulatory control. This becomes much more vital since India desires to be an economic superpower primarily based on innovation. It is very important for a person from the legal field, especially those interested in the field of IPR, to have clarity regarding the protection of genetically modified plants. This humble attempt at a research paper seeks to clarify the same and discusses the various aspects on which one should think while concluding their views on the topic