A Scanned Perturbation Technique For Imaging Electromagnetic Standing Wave Patterns of Microwave Cavities

We have developed a method to measure the electric field standing wave distributions in a microwave resonator using a scanned perturbation technique. Fast and reliable solutions to the Helmholtz equation (and to the Schrodinger equation for two dimensional systems) with arbitrarily-shaped boundaries are obtained. We use a pin perturbation to image primarily the microwave electric field amplitude, and we demonstrate the ability to image broken time-reversal symmetry standing wave patterns produced with a magnetized ferrite in the cavity. The whole cavity, including areas very close to the walls, can be imaged using this technique with high spatial resolution over a broad range of frequencies.Comment: To be published in Review of Scientific Instruments,September, 199

The X-ray variability and the near-IR to X-ray spectral energy distribution of four low luminosity Seyfert 1 galaxies

We present the results from a study of the X-ray variability and the near-IR to X-ray spectral energy distribution of four low-luminosity, Seyfert 1 galaxies. We compared their variability amplitude and broad band spectrum with those of more luminous AGN in order to investigate whether accretion in low-luminosity AGN operates as in their luminous counterparts. We used archival XMM-Newton and, in two cases, ASCA data to estimate their X-ray variability amplitude and determine their X-ray spectral shape and luminosity. We also used archival HST data to measure their optical nuclear luminosity, and near-IR measurements from the literature, in order to construct their near-IR to X-ray spectra. The X-ray variability amplitude of the four Seyferts is what one would expect, given their black hole masses. Their near-IR to X-ray spectrum has the same shape as the spectrum of quasars which are 10^2-10^5 times more luminous. The objects in our sample are optically classified as Seyfert 1-1.5. This implies that they host a relatively unobscured AGN-like nucleus. They are also of low luminosity and accrete at a low rate. They are therefore good candidates to detect radiation from an inefficient accretion process. However, our results suggest that they are similar to AGN which are 10^2-10^5 times more luminous. The combination of a "radiative efficient accretion disc plus an X-ray producing hot corona" may persist at low accretion rates as well.Comment: 11 pages, 8 figures, accepted for publication in A&

The anti-correlation between the hard X-ray photon index and the Eddington ratio in LLAGNs

We find a significant anti-correlation between the hard X-ray photon index and the Eddington ratio L_Bol/L_Edd for a sample of Low-Ionization Nuclear Emission-line Regions (LINERs) and local Seyfert galaxies, compiled from literatures with Chandra or XMM-Newton observations. This result is in contrast with the positive correlation found in luminous active galactic nuclei (AGNs), while it is similar to that of X-ray binaries (XRBs) in low/hard state. Our result is qualitatively consistent with the spectra produced from advection dominated accretion flows (ADAFs). It implies that the X-ray emission of low-luminosity active galactic nuclei (LLAGNs) may originate from the Comptonization process in ADAF, and the accretion process in LLAGNs may be similar to that of XRBs in the low/hard state, which is different from that in luminous AGNs.Comment: 10 pages, 1 figure, accepted to MNRA

Distributed Caching for Complex Querying of Raw Arrays

As applications continue to generate multi-dimensional data at exponentially increasing rates, fast analytics to extract meaningful results is becoming extremely important. The database community has developed array databases that alleviate this problem through a series of techniques. In-situ mechanisms provide direct access to raw data in the original format---without loading and partitioning. Parallel processing scales to the largest datasets. In-memory caching reduces latency when the same data are accessed across a workload of queries. However, we are not aware of any work on distributed caching of multi-dimensional raw arrays. In this paper, we introduce a distributed framework for cost-based caching of multi-dimensional arrays in native format. Given a set of files that contain portions of an array and an online query workload, the framework computes an effective caching plan in two stages. First, the plan identifies the cells to be cached locally from each of the input files by continuously refining an evolving R-tree index. In the second stage, an optimal assignment of cells to nodes that collocates dependent cells in order to minimize the overall data transfer is determined. We design cache eviction and placement heuristic algorithms that consider the historical query workload. A thorough experimental evaluation over two real datasets in three file formats confirms the superiority -- by as much as two orders of magnitude -- of the proposed framework over existing techniques in terms of cache overhead and workload execution time

SAM-dPCR: Real-Time and High-throughput Absolute Quantification of Biological Samples Using Zero-Shot Segment Anything Model

Digital PCR (dPCR) has revolutionized nucleic acid diagnostics by enabling absolute quantification of rare mutations and target sequences. However, current detection methodologies face challenges, as flow cytometers are costly and complex, while fluorescence imaging methods, relying on software or manual counting, are time-consuming and prone to errors. To address these limitations, we present SAM-dPCR, a novel self-supervised learning-based pipeline that enables real-time and high-throughput absolute quantification of biological samples. Leveraging the zero-shot SAM model, SAM-dPCR efficiently analyzes diverse microreactors with over 97.7% accuracy within a rapid processing time of 3.16 seconds. By utilizing commonly available lab fluorescence microscopes, SAM-dPCR facilitates the quantification of sample concentrations. The accuracy of SAM-dPCR is validated by the strong linear relationship observed between known and inferred sample concentrations. Additionally, SAM-dPCR demonstrates versatility through comprehensive verification using various samples and reactor morphologies. This accessible, cost-effective tool transcends the limitations of traditional detection methods or fully supervised AI models, marking the first application of SAM in nucleic acid detection or molecular diagnostics. By eliminating the need for annotated training data, SAM-dPCR holds great application potential for nucleic acid quantification in resource-limited settings.Comment: 23 pages, 6 figure

Random network coding‐based optimal scheme for perfect wireless packet retransmission problems

Solving wireless packet retransmission problems (WPRTPs) using network coding (NC) approach is increasingly attracting research efforts. However, existing researches are almost all focused on solutions in Galois field GF(2), and consequently, the solutions found by these schemes are usually less optimal. In this paper, we focus on optimal NC‐based scheme for perfect WPRTPs (P‐WPRTPs) where, with respect to each receiver, a packet is either requested by or already known to it. The number of retransmitted packets in optimal NC‐based solutions to P‐WPRTPs is firstly analyzed and proved. Then, random network coding‐based optimal scheme (RNCOPT) is proposed for P‐WRPTPs. RNCOPT is optimal in the sense that it guarantees to obtain a valid solution with minimum number of packet retransmissions. Furthermore, in RNCOPT, each coding vector is generated using a publicly known pseudorandom function with a randomly selected seed. The seed, instead of the coding vector, is used as decoding information to be retransmitted together with the coded packet. Thus, packet overhead of RNCOPT is reduced further. Extensive simulations show that RNCOPT distinctively outperforms some previous typical schemes for P‐WPRTPs in saving the number of retransmitted packets. Copyright © 2011 John Wiley & Sons, Ltd. This paper studied Perfect Wireless Packet ReTransmission Problems (P‐WPRTPs) where, with respect to each receiver, a packet is either requested by or already known to it. The number of retransmitted packets in optimal NC‐based solutions to P‐WPRTPs was analyzed and proved. Then, random network coding‐based optimal scheme (RNCOPT) is proposed for P‐WPRTPs. RNCOPT is optimal in the sense that it guarantees to obtain a valid solution with minimum number of packet retransmissions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97523/1/wcm1122.pd