Quantum Sensing in a Physiological‐Like Cell Niche Using Fluorescent Nanodiamonds Embedded in Electrospun Polymer Nanofibers

Fluorescent nanodiamonds (fNDs) containing nitrogen vacancy (NV) centers are promising candidates for quantum sensing in biological environments. This work describes the fabrication and implementation of electrospun poly lactic‐co‐glycolic acid (PLGA) nanofibers embedded with fNDs for optical quantum sensing in an environment, which recapitulates the nanoscale architecture and topography of the cell niche. A protocol that produces uniformly dispersed fNDs within electrospun nanofibers is demonstrated and the resulting fibers are characterized using fluorescent microscopy and scanning electron microscopy (SEM). Optically detected magnetic resonance (ODMR) and longitudinal spin relaxometry results for fNDs and embedded fNDs are compared. A new approach for fast detection of time varying magnetic fields external to the fND embedded nanofibers is demonstrated. ODMR spectra are successfully acquired from a culture of live differentiated neural stem cells functioning as a connected neural network grown on fND embedded nanofibers. This work advances the current state of the art in quantum sensing by providing a versatile sensing platform that can be tailored to produce physiological‐like cell niches to replicate biologically relevant growth environments and fast measurement protocols for the detection of co‐ordinated endogenous signals from clinically relevant populations of electrically active neuronal circuits.     

Medical Image Encryption Based on Hybrid Chaotic DNA Diffusion

Wireless Personal Communications - We explore the use of two chaotic systems (Bernoulli shift map and Zizag map) coupled with deoxyribonucleic acid coding in an encryption scheme for medical images...     

Investigating fuel-cell transport limitations using hydrogen limiting current

Reducing mass-transport losses in polymer-electrolyte fuel cells (PEFCs) is essential to increase their power density and reduce overall stack cost. At the same time, cost also motivates the reduction in expensive precious-metal catalysts, which results in higher local transport losses in the catalyst layers. In this paper, we use a hydrogen-pump limiting-current setup to explore the gas-phase transport losses through PEFC catalyst layers and various gas-diffusion and microporous layers. It is shown that the effective diffusivity in the gas-diffusion layers is a strong function of liquid saturation. In addition, it is shown how the catalyst layer unexpectedly contributes significantly to the overall measured transport resistance. This is especially true for low catalyst loadings. It is also shown how the various losses can be separated into different mechanisms including diffusional processes and mass-dependent and independent ones, where the data suggests that a large part of the transport resistance in catalyst layers cannot be attributed to a gas-phase diffusional process. The technique is promising for deconvoluting transport losses in PEFCs.     

Complex and dynamic population structures: synthesis, open questions, and future directions

The population structure of an evolutionary algorithm influences the dissemination and mixing of advantageous alleles, and therefore affects search performance. Much recent attention has focused on the analysis of complex population structures, characterized by heterogeneous connectivity distributions, non-trivial clustering properties, and degree–degree correlations. Here, we synthesize the results of these recent studies, discuss their limitations, and highlight several open questions regarding (1) unsolved theoretical issues and (2) the practical utility of complex population structures for evolutionary search. In addition, we will discuss an alternative complex population structure that is known to significantly influence dynamical processes, but has yet to be explored for evolutionary optimization. We then shift our attention toward dynamic population structures, which have received markedly less attention than their static counterparts. We will discuss the strengths and limitations of extant techniques and present open theoretical and experimental questions and directions for future research. In particular, we will focus on the prospects of “active linking,” wherein edges are dynamically rewired according to the genotypic or phenotypic properties of individuals, or according to the success of prior inter-individual interactions.     

The cluster scanning system

Users with severe physical impairment often use computers with one or two switches using a scanning system. Scanning is a technique of successively highlighting portions of screen. This paper presents a new scanning system that works through clustering screen objects. The system is initially calibrated through simulation and later validated through a user trial. Results show that it outperforms existing block scanning systems.     

Oxygen Reduction Reaction Performance of [MTBD][beti]‐Encapsulated Nanoporous NiPt Alloy Nanoparticles

Recent advances in oxygen reduction reaction catalysis for proton exchange membrane fuel cells (PEMFCs) include i) the use of electrochemical dealloying to produce high surface area and sometimes nanoporous catalysts with a Pt‐enriched outer surface, and ii) the observation that oxygen reduction in nanoporous materials can be potentially enhanced by confinement effects, particularly if the chemical environment within the pores can bias the reaction toward completion. Here, these advances are combined by incorporating a hydrophobic, protic ionic liquid, [MTBD][beti], into the pores of high surface‐area NiPt alloy nanoporous nanoparticles (np‐NiPt/C + [MTBD][beti]). The high O₂ solubility of the [MTBD][beti], in conjunction with the confined environment within the pores, biases reactant O₂ toward the catalytic surface, consistent with an increased residence time and enhanced attempt frequencies, resulting in improved reaction kinetics. Half‐cell measurements show the np‐NiPt/C+[MTBD][beti] encapsulated catalyst to be nearly an order of magnitude more active than commercial Pt/C, a result that is directly translated into operational PEMFCs.     

Estimating surface net solar radiation by use of Landsat-5 TM and digital elevation models

The ground surface net solar radiation is the energy that drives physical and chemical processes at the ground surface. In this paper, multi-spectral data from the Landsat-5 TM, topographic data from a gridded digital elevation model, field measurements, and the atmosphere model LOWTRAN 7 are used to estimate surface net solar radiation over the FIFE site. Firstly an improved method is presented and used for calculating total surface incoming radiation. Then, surface albedo is integrated from surface reflectance factors derived from remotely sensed data from Landsat-5 TM. Finally, surface net solar radiation is calculated by subtracting surface upwelling radiation from the total surface incoming radiation.