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John Jenkins

Publications and source records attributed to John Jenkins.

3 recordsLinked to original sources

Ionic Liquid Biospheres

Liquid is a fundamental requirement for life as we understand it, but whether that liquid has to be water is not known. We propose the hypothesis that ionic liquids (ILs) and deep eutectic solvents (DES) constitute a class of non-aqueous planetary liquids capable of persisting on a wide range of bodies where stable liquid water cannot exist. This hypothesis is motivated by key physical properties of ILs and DES. Many exhibit vapor pressures orders of magnitude lower than that of water and remain liquid across exceptionally wide temperature ranges, from cryogenic to well above terrestrial temperatures. These properties permit stable liquids to exist where liquid water would rapidly evaporate or freeze and outside of bulk phases as persistent microscale reservoirs-such as thin films and pore-filling droplets. In other words, ILs and DES can persist in environments without requiring oceans, thick atmospheres, or narrowly regulated climate conditions. We further hypothesize that ILs and DES could act as solvents for non-Earth-like life. Our hypothesis ex-tends to the idea that ILs and DES could enable prebiotic chemistry by providing long-lived, protective liquid environments for complex organic molecules on bodies such as comets and asteroids, where liquid water is absent. Based on the occurrence of DES-like mixtures as protective intracellular liquids in desiccation-tolerant plants, we propose that ILs and DES might be solvents that life elsewhere purposefully evolves. We review protein and other biomolecule studies in ILs and DES and outline planetary environments in which ILs and DES might occur by discussing available anions and cations. We present strategies to advance the IL/DES solvent hypothesis using laboratory studies, computational chemistry, planetary missions, analysis of existing spectroscopic datasets, and modeling of liquid microniches and chemical survival on small bodies.

astro-ph.EP

Touch Analysis: An Empirical Evaluation of Machine Learning Classification Algorithms on Touch Data

Our research aims at classifying individuals based on their unique interactions on touchscreen-based smartphones. In this research, we use Touch-Analytics datasets, which include 41 subjects and 30 different behavioral features. Furthermore, we derived new features from the raw data to improve the overall authentication performance. Previous research has already been done on the Touch-Analytics datasets with the state-of-the-art classifiers, including Support Vector Machine (SVM) and k-nearest neighbor (kNN), and achieved equal error rates (EERs) between 0% to 4%. Here, we propose a novel Deep Neural Net (DNN) architecture to classify the individuals correctly. The proposed DNN architecture has three dense layers and uses many-to-many mapping techniques. When we combine the new features with the existing ones, SVM and kNN achieved the classification accuracy of 94.7% and 94.6%, respectively. This research explored seven other classifiers and out of them, the decision tree and our proposed DNN classifiers resulted in the highest accuracy of 100%. The others included: Logistic Regression (LR), Linear Discriminant Analysis (LDA), Gaussian Naive Bayes (NB), Neural Network, and VGGNet with the following accuracy scores of 94.7%, 95.9%, 31.9%, 88.8%, and 96.1%, respectively.

cs.LG

A Software-Defined Approach for QoS Control in High-Performance Computing Storage Systems

High-performance computing (HPC) storage systems become increasingly critical to scientific applications given the data-driven discovery paradigm shift. As a storage solution for large-scale HPC systems, dozens of applications share the same storage system, and will compete and can interfere with each other. Application interference can dramatically degrade the overall storage system performance. Therefore, developing a flexible and effective storage solution to assure a certain level of resources per application, i.e. the Quality-of-Service (QoS) support, is critical. One of the common solution to achieve QoS assurance for storage systems is using provisioning technique~\cite{3}. Provisioning refers to the ability of providing certain amount of resources for applications and expected workloads. However, provisioning has limitations such as requiring the detailed knowledge of the expected workloads. In addition, the storage workloads are transient hence expensive to be satisfied. Due to these limitations, providing QoS storage systems through provisioning is challenging. In this research, a software-defined approach~\cite{0} is proposed as a flexible solution to achieve QoS guarantee for storage systems. The driving force of using a software-defined approach instead of the traditional approaches, is that it has the ability to enable a more flexible, scalable, and efficient platform. For example, if any changes occurred in the system, it does not necessarily need to re-configure thousands of devices; instead, with re-configuring a logically centralized component, other devices will be automatically notified.

cs.DC