Rethinking Alignment and Uniformity in Unsupervised Image Semantic Segmentation

Unsupervised image semantic segmentation(UISS) aims to match low-level visual features with semantic-level representations without outer supervision. In this paper, we address the critical properties from the view of feature alignments and feature uniformity for UISS models. We also make a comparison between UISS and image-wise representation learning. Based on the analysis, we argue that the existing MI-based methods in UISS suffer from representation collapse. By this, we proposed a robust network called Semantic Attention Network(SAN), in which a new module Semantic Attention(SEAT) is proposed to generate pixel-wise and semantic features dynamically. Experimental results on multiple semantic segmentation benchmarks show that our unsupervised segmentation framework specializes in catching semantic representations, which outperforms all the unpretrained and even several pretrained methods.Comment: AAAI2

Potential Application of MicroRNA Profiling to the Diagnosis and Prognosis of HIV-1 Infection

MicroRNAs (miRNAs) were first identified in Caenorhabditis briggsae and later recognized as playing pivotal roles in a vast range of cellular activities. It has been shown that miRNAs are an important mechanism not only for host defense against virus but also for the establishment of viral infection. During human immunodeficiency virus type 1 (HIV-1) infection, host miRNA profiles are altered either as a host response against the virus or alternatively as a mechanism for the virus to facilitate viral replication and infection or to maintain latency. The altered miRNA profiles can be detected and quantified by various advanced assays, and potentially serve as more sensitive, accurate and cost-efficient biomarkers for HIV-1 diagnosis and disease progression than those detected by currently available standard clinical assays. Such new biomarkers are critical for optimizing treatment regimens. In this review, we focus on the potential application of miRNA profiling to the diagnosis of HIV-1 infection and the monitoring of disease progression

Designing Ago2-specific siRNA/shRNA to Avoid Competition with Endogenous miRNAs

Relatively large amounts of transfected siRNA can compete for Ago proteins and thus compromise endogenous miRNA function, potentially leading to toxicities. Here, we show that shRNA can also perturb endogenous miRNA function similarly. More importantly, we also show that the problem can be solved by designing shRNAs in the context of pre-miR-451 structure with completely complementary stem, which significantly improves the Ago2 specificity. This shRNA was shown to be Ago2-specific, and maintain target-silencing ability while avoiding competition with endogenous miRNAs by not competing for Agos 1, 3, and 4. We conclude that modified pre-miR-451 structure provides a general platform to design shRNAs that significantly reduce perturbation of miRNA function

An integrated multi-input single-output buck converter for laterally-arrayed multi-bandgap solar cells

Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019Cataloged from PDF version of thesis.Includes bibliographical references (pages 151-156).Concentrated Photovoltaic (CPV) systems provides a potentially low-cost and high-efficiency alternative to conventional mono-crystalline Si panel PV systems, and a new CPV system with Laterally-Arrayed Multi-Bandgap (LAMB) cells is introduced. In this thesis, an IC-based Multi-Input Single-Output (MISO) power converter, which serves as the small-footprint and self-powered power management module of the CPV system, is designed and tested. The proposed converter shall efficiently harvest energy from 4 types of solar cells and track the Maximum Power Point (MPP) at the cell-block level. First, the circuit topology, MPP Tracking (MPPT) algorithm, and control mechanism are verified with discrete converters, then a qualitative demonstration is conducted outdoors to show the concept of the entire CPV system with power management. Finally, a first-generation integrated converter, with the passive components, Analog/Digital converters and a MPPT-enabling micro-controller off-chip, is implemented.by Haoquan Zhang.S.M.S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienc

A CMOS-Based Energy Harvesting Approach for Laterally-Arrayed Multi-Bandgap Concentrated Photovoltaic Systems

This paper presents an energy harvesting approach for a concentrated photovoltaics (CPV) system based on cell-block-level integrated CMOS converters. The CPV system, built upon the Laterally-Arrayed Multi-Bandgap (LAMB) cell structure, is a potentially higher-efficiency and lower-cost alternative to traditional tandem-based systems. The cells within a sub-module block are connected for approximate voltage matching, and a CMOS-based multi-input single-output (MISO) buck converter harvests and combines the energy while performing maximum power point tracking (MPPT) locally. First, a comparison of modeled performances achievable with traditional tandem CPV and LAMB CPV with a MISO converter is presented using day-long outdoor measured solar spectrum. The model predicts on average >19% more energy can be extracted from LAMB modules on a typical day. Then, a prototype miniaturized MISO dc-dc converter operating at 10MHz is developed in a 130nm CMOS process. For 45-160mW power levels, the prototype converter achieves >92% nominal and >95% peak efficiency in a small form factor designed to fit within available space in a LAMB PV cell block. The results demonstrate the potential of the LAMB CPV architecture for enhanced solar energy capture

Rethinking Alignment and Uniformity in Unsupervised Image Semantic Segmentation

Unsupervised image segmentation aims to match low-level visual features with semantic-level representations without outer supervision. In this paper, we address the critical properties from the view of feature alignments and feature uniformity for UISS models. We also make a comparison between UISS and image-wise representation learning. Based on the analysis, we argue that the existing MI-based methods in UISS suffer from representation collapse. By this, we proposed a robust network called Semantic Attention Network(SAN), in which a new module Semantic Attention(SEAT) is proposed to generate pixel-wise and semantic features dynamically. Experimental results on multiple semantic segmentation benchmarks show that our unsupervised segmentation framework specializes in catching semantic representations, which outperforms all the unpretrained and even several pretrained methods

Multi-Inverter Discrete Backoff: A High-Efficiency, Wide-Range RF Power Generation Architecture

Industrial radio frequency (rf) power applications, such as plasma generation, require high-frequency rf power over a wide dynamic power range and across variable load impedances. It is desired in these applications to maintain high efficiency and fast dynamic response. This paper introduces a scalable power amplifier (PA) architecture and control approach suitable for such applications. This approach, which we refer to as Multi-Inverter Discrete Backoff (MIDB), losslessly combines the outputs of paralleled switched-mode PAs, and modulates the number of active PAs to provide discrete steps in rf output voltage. It further employs outphasing among sub-groups of PAs for rapid and continuous output power control over a wide range. In doing so, the architecture can maintain high efficiency and fast rf power control across a very wide backoff range. A device selection and loss optimization method for MIDB architectures is discussed for plasma generation applications. We address the use of GaN FET-based, ZVS class-D PA units, and consider dynamic R[subscript ds],on effects and C[subscript oss] losses typical of GaN FETs

Comparison of Radio-Frequency Power Architectures for Plasma Generation

Applications such as plasma generation require the generation and delivery of radio-frequency (rf) power into widely-varying loads while simultaneously demanding high accuracy and speed in controlling the output power across a wide range of power levels. Attaining high efficiency and performance across all operating conditions while meeting these system requirements is challenging, especially at high frequencies (10s of MHz) and power levels (1000s of Watts and above). This paper evaluates different architectures that directly address these challenges and enable efficient high-frequency operation over a wide range of output power levels and load impedances with the capability of fast output power control (e.g., within a few microseconds). We review techniques for achieving fast output power control and evaluate their suitability in efficient rf systems demanding accurate and fast control of output power. Two dc-to-rf system architectures utilizing the discussed power control techniques are presented to illustrate both the achievable performance benefits as well as their robustness to load impedance variation, and are compared using time-domain simulations. The results indicate the ability of the proposed architectures to maintain high efficiency (> 90%) across a very wide range of output power levels (e.g., over a factor of up to 85x) while being robust to load impedance variations

Electrocatalytic Glucose Oxidation at Coral-Like Pd/C3N4-C Nanocomposites in Alkaline Media

Porous coral-like Pd/C3N4-C nanocomposites are fabricated by a simple one-pot chemical reduction method. Their electrocatalytic performance is ~50% higher than a carbon-loaded palladium electrocatalyst (Pd/C) in alkaline media. This confirms that the glucose electrooxidation and sensing performance of a Pd/C can be improved by the synergy of graphitic carbon nitride (C3N4), though C3N4 exhibits poor electrical conductivity. Compared to Pd/C, the size of Pd nanoparticles in Pd/C3N4-C decreases. As a result, the activity of Pd/C3N4-C is enhanced due to the higher dispersion and the synergistic effect. Pd/C3N4-C presents a rapid response and high sensitivity to glucose. The sensitivity for glucose sensing at Pd/C3N4-C is 3.3 times that of at Pd/C in the range of 0.001–10 mM. In the lower range of 0.001–1 mM, the sensitivity at Pd/C3N4-C is ~10 times greater than Pd/C