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.     

The Metaflow architecture

The Metaflow architecture, a unified approach to maximizing the performance of superscalar microprocessors, is introduced. The Metaflow architecture exploits inherent instruction-level parallelism in conventional sequential programs by hardware means, without relying on optimizing compilers. It is based on a unified structure, the DRIS (deferred-scheduling, register-renaming instruction shelf), that manages out-of-order execution and most of the attendant problems. Coupling the DRIS with a speculative-execution mechanism that avoids conditional branch stalls results in performance limited only be inherent instruction-level parallelism and available execution resources. Although presented in the context of superscalar machines, the technique is equally applicable to a superpipelined implementation. Lightning, the first implementation of the Metaflow architecture, which executes the Sparc RISC instruction set is described     

Self-Organized Monitoring in Ad-Hoc Networks

We propose in this paper a self-organized monitoring architecture for mobile ad-hoc networks based on a selective scheme where subsets of nodes are managed. These nodes are determined based on their network behavior in order to favor subsets of well-connected nodes. The key idea is to relax the requirements of the management plane, and to use these manageable subsets to monitor the performance of the overall network. We therefore propose a new performance metric to be monitored, in order to estimate the capability of ad-hoc nodes to communicate end-to-end in the network. Extensive simulations show how different parameters affect this metric.     

Molecular simulation of temperature-programmed desorption

We use accelerated molecular dynamics to probe the thermal desorption of n-alkanes from the Au(1 1 1) and C(0 0 0 1) surfaces. Studying an alkane series ranging from CH₄ to C₁₆H₃₄, we find that the desorption prefactor increases with increasing chain length for the short chains until a certain chain length is reached when it becomes essentially constant and independent of chain length. We can understand the dependence of the preexponential factor on alkane chain length in terms of conformational changes within the alkane molecules. For the shorter molecules, the desorption temperatures probed in experimental temperature-programmed desorption studies lie below those for which torsional motion is activated. Thus, the short alkanes can be treated as rigid rods, and the loss in translational and rotational entropy upon adsorption leads to a preexponential factor that increases with increasing chain length. As the alkane chain length increases, the binding energy and the experimental desorption temperatures also increase. Thus, torsional motion is activated to an extent that increases with increasing chain length. This torsional activation increases the entropy of adsorption and counteracts the entropy decrease due to a loss of translation and rotation. This leads to a virtually constant prefactor for sufficiently long chains. Our findings are consistent with experimental data for the thermal desorption of alkanes from the Au(1 1 1), Pt(1 1 1), MgO(1 0 0) and C(0 0 0 1) surfaces.     

Multifractal analysis of non-conformal repellers: a model case

For a model class of repellers of non-conformal expanding maps, we obtain sharp lower bounds for the dimension spectra of the Birkhoff averages of a Hölder continuous function. As in the well-studied case of conformal dynamics, the bounds are also expressed here in terms of the thermodynamic formalism.     

Occlusion-resistant camera design for acquiring active environments.

In this article, we present a detailed theoretical analysis and a prototype implementation of a family of cameras designed with the explicit goal of detecting and removing interfering dynamic occluders in real time, during live capture, as opposed to fixing the resulting artifacts a posteriori. Such an early-acquisition approach improves efficiency: more valid samples are acquired faster without worrying about moving occluders. One option for designing a camera to be unaffected by moving occluders is to sample through the occluder, but true x-ray-like vision is technically impractical. Another option is to sample around the occluder using a camera with a large effective aperture, but such an approach requires a bulky acquisition device. Yet another possibility of sampling around an occluder is to rely on second and higher order reflected rays that indirectly sample surfaces not directly visible. However, devising an acquisition device sufficiently sensitive and efficient to capture large environments using reflected rays will remain challenging for the foreseeable future.     

On the variation with flux and frequency of the core loss coefficients in electrical machines

A model of core losses, in which the hysteresis coefficients are variable with the frequency and induction (flux density) and the eddy-current and excess loss coefficients are variable only with the induction, is proposed. A procedure for identifying the model coefficients from multifrequency Epstein tests is described, and examples are provided for three typical grades of non-grain-oriented laminated steel suitable for electric motor manufacturing. Over a wide range of frequencies between 20-400 Hz and inductions from 0.05 to 2 T, the new model yielded much lower errors for the specific core losses than conventional models. The applicability of the model for electric machine analysis is also discussed, and examples from an interior permanent-magnet and an induction motor are included.