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Signals of opportunity reflectometry (SoOp-R), the re-utilization of non-cooperative satellite transmissions for communication and navigation, is a promising approach to remote sensing of root-zone soil moisture (RZSM). Satellite transmissions in the frequency ranges of 137-138, 240-270, and 360-380 MHz are of interest due to the increased penetration depth. These can be combined with Global Navigation Satellite System Reflectometry (GNSS-R) in L-band (1575.42 MHz) to estimate the subsurface SM profile. The objective is to define requirements (e.g. frequency and polarization combinations, observation error, and temporal coincidence of multi-source observations) for satellite-based remote sensing of RZSM. Our approach is to use synthetic observations generated from multi-year time series of in-situ SM measurements from seven United States Climate Reference Network (USCRN) sites and dynamic vegetation structure based on a simple scaling method. A multi-frequency/polarimetric retrieval algorithm is developed and applied to these synthetic observations and used to predict retrieval errors for a range of changes in system parameters. We found that the use of both high and low frequencies improves retrieval accuracy by limiting uncertainties from vegetation and surface SM and providing sensitivity to deeper layers. Moreover, the retrieval errors were found to increase linearly with the reflectivity error and inter-frequency time delays. A bivariate model derived from this linear relationship will be useful for developing requirements on reflectivity precision based upon science requirements for SM/VWC retrievals. Although orbits of specific transmitter constellations were used to generate realistic distributions of incidence angle combinations, the method and results could be applied more generally.

In this article, coupled electromagnetic-thermal simulations of inductive power transfer (IPT) pads using finite-element simulations are discussed. Derivation of each electrical and thermal parameters required for the modeling process is outlined. Simulation models are used to predict the power loss and the temperature rise of an IPT pad at different ambient temperatures at steady state. Using these simulation methods, the power loss within an IPT pad operating at 50 ${^\circ }$ C ambient temperature is predicted. A 10-KW IPT system is set up within an environmental chamber to validate the predicted losses within the system.

Coherent Raman scattering imaging has provided inherent chemical information of biomolecules without the need for any external labels.1–3 However, its working depth in deep-tissue imaging is extremely shallow because both the intrinsic scattering cross-section and image contrast are so small that even weak perturbation of the pump and Stokes beam focusing by the complex tissue causes the loss of the resolving power.4,5 Here, we propose a deep-tissue coherent Raman scattering (CRS) microscopy equipped with an advanced adaptive optics (AO) system measuring complex tissue aberration from elastic backscattering. Using this label-free AO-CRS microscopy, we demonstrate the vibrational imaging of lipid-rich substances such as myelin inside the mouse brain even through the thick and opaque cranial bones.

A critical aspect of designing an inductive power transfer system is the accurate characterization and prediction of power losses in its magnetic couplers under all operating conditions. Understanding the loss mechanisms and their distribution can help the optimization of the magnetic couplers while also being essential to determining thermal management requirements and optimal control parameters. Previously proposed loss measurement methods are neither able to accurately predict the losses in couplers nor characterize their distribution. As a solution, this article proposes a new experimental method, termed the stepped resonant excitation (SRE) method that can accurately predict the power losses in magnetic couplers operated under practical conditions. In addition, the SRE method is capable of producing better insight to the loss distribution by separately quantifying the winding loss and core loss. Experimental results presented in this article show that the SRE method can predict the core loss of an accurately characterized toroidal inductor with less than 10% error when excited with magnetic fields higher than 50 mT. Additionally, the losses measured using the SRE method in a double-D magnetic coupler match well with finite element analysis simulations conducted using datasheet loss curves at 25 °C.

The functional and optimal expression of genes is crucial for survival of all living organisms. Numerous experiments and efforts have been performed to reveal the mechanisms required for the functional and optimal expression of human genes. The yeast Saccharomyces cerevisiae has evolved independently of humans for billions of years. Nevertheless, S. cerevisiae has many conserved genes and expression mechanisms that are similar to those in humans. Yeast is the most commonly used model organism for studying the function and expression mechanisms of human genes because it has a relatively simple genome structure, which is easy to manipulate. Many previous studies have focused on understanding the functions and mechanisms of human proteins using orthologous genes and biological systems of yeast. In this review, we mainly introduce two recent studies that replaced human genes and nucleosomes with those of yeast. Here, we suggest that, although yeast is a relatively small eukaryotic cell, its humanization is useful for the direct study of human proteins. In addition, yeast can be used as a model organism in a broader range of studies, including drug screening.

We observed that coherent Raman imaging signal enhancement by the aberration correction is approximately proportional to the Strehl ratio enhancement, not its third power. The Raman signal originating from out-of-focus planes explains this discrepancy.

We integrate the wavefront optimization technique with the coherent Raman scattering (CRS) microscopy to enhance signal contrast and penetration depth. The vibrational imaging of myelin inside the mouse brain through cranial bones is domonstrated.

This paper introduces a primary pad for wireless charging applications, which is able to transfer high power over large air gaps and is tolerant to lateral displacements suitable for electric vehicle charging applications. The developed pad is an improved solenoid designed specifically to address issues such as flux leakage and loss while retaining good coupling. It is a hybrid structure that consists of a combination of rectangular- or square-shaped coils and a central solenoid, all connected in series. When energized, it produces a single-sided, polarized flux similar to the flux pattern of the solenoid and double D (DDP) pads. The power transfer capability of this pad is investigated through finite-element analysis simulations. The results are compared first to a similar sized solenoid from which it was derived, and also a DDP primary pad and are verified through measurements on prototype systems in the laboratory. The aim of this paper is to provide an improved hybrid solenoid pad showing higher coupling factors and lower stray field emissions with a performance (coupling and stray field emissions) similar to that of DDPs.

A dynamic inductive power transfer (IPT) system is a safe and convenient solution to address the issues related to the limited battery capacity and travel distance of electric vehicles (EVs). In recent years, practical aspects of dynamic IPT systems have been investigated to advance various IPT technologies from laboratories to roadways. This paper suggests a configuration to mitigate some of the installation and maintenance concerns of IPT roadways by proposing a switchable inductively coupled connector. Besides providing galvanic isolation, the inductively coupled connector helps maintain a constant and load-independent current in the primary coupler. Moreover, each primary coupler is connected to a common H-bridge through a single DC switch minimizing the number of components required to energize each coupler independently. A mathematical analysis and simulation results have been provided to validate a scaled 3.3kW prototype IPT system employing the proposed configuration.

Inductive power transfer (IPT) is a promising method for electric vehicle (EV) charging that is safe and practical. The critical aspects of IPT systems to achieve roadway charging are robustness, reliability, low cost and high power transfer. This paper presents two variations of a primary IPT double-D (DD) coupler that reduce ferrite volume, stray-fields and cost while having increased power rating at the expense of magnetic coupling and higher primary pad currents. A two-step ferrite shaping method is used for optimisation while keeping the primary coil and secondary pad unchanged. The ferrite volume is limited to the high flux density locations in a first step to reduce ferrite volume by 70%. Following this, an additional 14% ferrite volume is added to shape and reduce the stray fields by 23%.

Advances in machine learning (ML) have ignited hardware innovations for efficient execution of the ML models many of which are memory-bound (e.g., long short-term memories, multi-level perceptrons, and recurrent neural networks). Specifically, inference using these ML models with small batches, as would be the case at the Cloud edge, has little reuse of the large filters and is deeply memory-bound. Simultaneously, processing-in or -near memory (PIM or PNM) is promising unprecedented high-bandwidth connection between compute and memory. Fortunately, the memory-bound ML models are a good fit for PIM. We focus on digital PIM which provides higher bandwidth than PNM and does not incur the reliability issues of analog PIM. Previous PIM and PNM approaches advocate full processor cores which do not conform to PIM’s severe area and power constraints. We describe Newton, a major DRAM maker’s upcoming accelerator-in-memory (AiM) product for machine learning, which makes the following contributions: (1) To satisfy PIM’s area constraints, Newton (a) places a minimal compute of only multiply-accumulate units and buffers in the DRAM which avoids the full-core area and power overheads of previous work and thus makes PIM feasible for the first time, and (b) employs a DRAM-like interface for the host to issue commands to the PIM compute. The PIM compute is rate-matched to the internal DRAM bandwidth and employs a non-intuitive, global input vector buffer shared by the entire channel to capture input reuse while amortizing buffer area cost. To the host, Newton’s interface is indistinguishable from regular DRAM without any offloading overheads and PIM/non-PIM mode switching, and with the same deterministic latencies even for floating-point commands. (2) To prevent the PIM-host interface from becoming a bottleneck, we include three optimizations: commands which gang multiple compute operations both within a bank and across banks; complex, multi-step compute commands – both of which save critical command bandwidth; and targeted reduction of t FAW overhead. (3) To capture output vector reuse with reasonable buffering, Newton employs an unusually-wide interleaved layout for the matrix. Our simulations running state-of-the-art neural networks show that building on a realistic HBM2E-like DRAM, Newton achieves 10x and 54x average speedup over a non-PIM system with infinite compute that perfectly uses the external DRAM bandwidth and a realistic GPU, respectively.

Signals of opportunity (SoOp) is a promising technique to measure key geophysical variables at high spatiotemporal scales using multiple microwave frequencies outside bands allocated for science. To better understand spaceborne SoOp observations, an end-to-end mission simulator has been developed. It determines observation geometries of multiple transmitters and receivers and generates SoOp observables for land remote sensing by integrating geophysical data and instrument properties. Using the simulator, the coverage and the instrument data of a hypothetical constellation of spaceborne SoOp receivers were evaluated over different orbital planes. This integrative tool facilitates the spaceborne SoOp mission design by exploring and optimizing the tradespace of a variety of design parameters.