Combining Data Longevity with High Storage Capacity—Layer‐by‐Layer DNA Encapsulated in Magnetic Nanoparticles

In this paper the practical density of long‐term DNA storage is increased. Specifically, the DNA weight loading of silica sphere DNA storage is increased to 3.4 wt%, a ten‐fold increase compared to the previous state‐of‐the‐art. By applying a Layer‐by‐Layer (LbL) design with alternating layers of DNA and a polycationic molecule, namely polyethyleneimine (PEI), another dimension to DNA surface binding onto magnetic nanoparticles is added. A protective silica layer is grown on top of the multilayered nanoparticles to shield the DNA from external sources of damage. Accelerated aging experiments of the nanoparticles and the subsequent quantification of DNA stability via qPCR show a significantly lower degradation rate compared to unprotected DNA. The novel material is compared to previous DNA storage technologies, outperforming those in DNA storage density as well as stability. Finally, the storage of an 83 kB digital file in DNA through a successful readout of a 4991 oligonucleotide pool is demonstrated from particle encapsulation, through accelerated aging, to sequencing.     

Inverse Solidification Induced by Active Janus Particles

Crystals melt when thermal excitations or the concentration of defects in the lattice is sufficiently high. Upon melting, the crystalline long‐range order vanishes, turning the solid to a fluid. In contrast to this classical scenario of solid melting, here a counter‐intuitive behavior of the occurrence of crystalline long‐range order in an initially disordered matrix is demonstrated. This unusual solidification is demonstrated in a system of passive colloidal particles accommodating chemically active defects—photocatalytic Janus particles. The observed crystallization occurs when the amount of active‐defect‐induced fluctuations (which is the measure of the effective temperature) reaches critical value. The driving mechanism behind this unusual behavior is purely internal and resembles a blast‐induced solidification. Here, the role of “internal micro‐blasts” is played by the photochemical activity of defects residing in the colloidal matrix. The defect‐induced solidification occurs under non‐equilibrium conditions: the resulting solid exists as long as a constant supply of energy in the form of ion flow is provided by the catalytic photochemical reaction at the surface of active Janus particle defects. The findings could be useful for the understanding of the phase transitions of matter under extreme conditions far from thermodynamic equilibrium.     

Paraphrase plagiarism identification with character-level features

Pattern Analysis and Applications - Several methods have been proposed for determining plagiarism between pairs of sentences, passages or even full documents. However, the majority of these methods...     

Mixed Logical Dynamical Nonlinear Model Predictive Controller for Large‐Scale Solar Fields

This paper presents a control algorithm for reducing heat losses caused by clouds in large solar fields. The formulation is based on a Mixed Logical Dynamical (MLD) representation of the solar field plus the application of a Practical Nonlinear Model Predictive Controller (PNMPC) for calculating the optimal control action. The main purpose of the controller is to deactivate fields with inlet temperature greater than outlet temperature and to manipulate the oil flow rate of the activated fields for tracking the reference of the outlet temperature. A simplified lumped parameters model is used for prediction and simulation of the solar fields.     

Interactive web interfaces modeling,simulation and analysis using Colored Petri Nets

Software and Systems Modeling - Interaction modeling is a relevant activity during software development processes. Created relying on Petri Nets theory and aiming to represent discrete time events,...     

Methodology for Evolving Fuzzy Kalman Filter Identification

International Journal of Control, Automation and Systems - A methodology based on the smart combination of evolving fuzzy clustering and OKID (Observer/ Kalman Filter Identification) algorithm, is...     

The effect of diet changes and food loss reduction in reducing the water footprint of an average American

ABSTRACT

We analyzed the consumptive water reduction of diet shifting along with food waste reductions in the case of the United States. We find that a dietary shift to healthy diet will not always lead to reduced water footprint. Dietary shifts to vegan and vegetarian diets provide larger reduction in the consumptive water footprint. Reducing food loss and waste produced the largest potential water footprint reduction in our analysis of the US food system. Our findings suggest that a combination of measures that include dietary shift, reducing caloric intake, and reducing food waste result in a significant decline in water footprint.     

Development and Comparison of Two Fast Surrogate Models for Urban Pluvial Flood Simulations

Detailed full hydrodynamic 1D-2D dual drainage models are a well-established approach to simulate urban pluvial floods. However, despite modelling advances and increasing computational power, this approach remains unsuitable for many real time applications. We propose and test two computationally efficient surrogate models. The first approach links a detailed 1D sewer model to a GIS-based overland flood network. For the second approach, we developed a conceptual sewer and flood model using data-driven and physically based structures, and coupled the model to pre-simulated flood maps. The city of Ghent (Belgium) is used as a test case. Both surrogate models can provide comparable results to the original model in terms of peak surface flood volumes and maximum flood extent and depth maps, with a significant reduction in computing time.     

Resource provisioning in Science Clouds: Requirements and challenges

Cloud computing has permeated into the information technology industry in the last few years, and it is emerging nowadays in scientific environments. Science user communities are demanding a broad range of computing power to satisfy the needs of high‐performance applications, such as local clusters, high‐performance computing systems, and computing grids. Different workloads are needed from different computational models, and the cloud is already considered as a promising paradigm. The scheduling and allocation of resources is always a challenging matter in any form of computation and clouds are not an exception. Science applications have unique features that differentiate their workloads; hence, their requirements have to be taken into consideration to be fulfilled when building a Science Cloud. This paper will discuss what are the main scheduling and resource allocation challenges for any Infrastructure as a Service provider supporting scientific applications.