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A 20-GHz Bandwidth Power Amplifier for Phased Array 5G New Radio Transmitters

A 27-47-GHz differential cascode power amplifier for millimeter-wave 5G new radio applications is presented. The PA is a three-stage design using inductively coupled impedance transformers with 31-dB nominal power gain. A device periphery ratio of 1:2:6 is adopted for predriver, driver, and final stage, respectively. A gain equalization technique was used in the interstage transformers to obtain t

Improved Functional MRI Activation Mapping in White Matter Through Diffusion-Adapted Spatial Filtering

Brain activation mapping using functional MRI (fMRI) based on blood oxygenation level-dependent (BOLD) contrast has been conventionally focused on probing gray matter, the BOLD contrast in white matter having been generally disregarded. Recent results have provided evidence of the functional significance of the white matter BOLD signal, showing at the same time that its correlation structure is hi

Spectral Characterization of Functional MRI Data on Voxel-Resolution Cortical Graphs

The human cortical layer exhibits a convoluted morphology that is unique to each individual. Conventional volumetric fMRI processing schemes take for granted the rich information provided by the underlying anatomy. We present a method to study fMRI data on subject-specific cerebral hemisphere cortex (CHC) graphs, which encode the cortical morphology at the resolution of voxels in 3-D. Using graph

Encoding contexts are incidentally reinstated during competitive retrieval and track the temporal dynamics of memory interference

The ability to remember an episode from our past is often hindered by competition from similar events. For example, if we want to remember the article a colleague recommended during the last lab-meeting, we may need to resolve interference from other article recommendations from the same colleague. This study investigates if the contextual features specifying the encoding episodes are incidentally

Learning of Parameters in Behavior Trees for Movement Skills

Reinforcement Learning (RL) is a powerful mathematical framework that allows robots to learn complex skills by trial-and-error. Despite numerous successes in many applications, RL algorithms still require thousands of trials to converge to high-performing policies, can produce dangerous behaviors while learning, and the optimized policies (usually modeled as neural networks) give almost zero expla

Fundamental Bounds on Cloaking Based on Convex Optimization

A convex optimization framework over contrast current density is developed to calculate fundamental bounds on the performance of linear passive cloaks. The formulation uses the method of moments applied to the electric field integral equation while using extincted power as the optimized metric. The presented results show that high cloaking efficiency requires cloaks made of low-loss and high-contr

Identification of cardiac afterload dynamics from data

The prospect of ex vivo functional evaluation of donor hearts is considered. Particularly, the dynamics of a synthetic cardiac afterload model are compared to those of normal physiology. A method for identification of continuous-time transfer functions from sampled data is developed and verified against results from the literature. The method relies on exact gradients and Hessians obtained through

Prevention of ischemic myocardial contracture through hemodynamically controlled DCD

Purpose—Ischemic myocardial contracture (IMC) or ‘‘stoneheart’’ is a condition with rapid onset following circulatory death. It inhibits transplantability of hearts donated uponcirculatory death (DCD). We investigate the effectiveness of hemodynamic normalization upon withdrawal of life-sustaining therapy (WLST) in a large-animal controlled DCD model, with the hypothesis that reduction in cardiac

Analysis and design of an 1-20 GHz track and hold circuit

This work analyzes the nonlinear effects in the track and hold circuit applied in high-speed ADCs or RF sampling receiver (RX) front-ends. Non-ideal effects inside the main sampling NMOS switch are studied. Parasitic varactor and sampling on-resistance modulation effects are analyzed through frequency domain Volterra series and the EKV MOS transistor model. Polynomial curve fitting is applied show

Baseband Processing for 5G and Beyond: Algorithms, VLSI Architectures, and Co-design

In recent years the number of connected devices and the demand for high data-rates have been significantly increased. This enormous growth is more pronounced by the introduction of the Internet of things (IoT) in which several devices are interconnected to exchange data for various applications like smart homes and smart cities. Moreover, new applications such as eHealth, autonomous vehicles, and c

Integrated Transmitters for Cellular User Equipment–Wideband CMOS Power Amplifiers and Antenna Impedance Tuners

The digital cellular systems era started about thirty years ago with the release of the first digital cellphones. These first digital cellphones were very different from today’s slim and esthetic cellular pocket computers. They were not mass-produced in million units a day, and they were designed for radio performance rather than appearance. Today, all components are integrated inside the mobile p

U Owns the Code That Changes and How Marginal Owners Resolve Issues Slower in Low-Quality Source Code

[Context] Accurate time estimation is a critical aspect of predictable software engineering. Previous work shows that low source code quality increases the uncertainty in issue resolution times. [Objective] Our goal is to evaluate how developers' project experience and file ownership are related to issue resolution times. [Method] We mine 40 proprietary software repositories and conduct an observa

Building Stronger Bridges: Strategies for Improving Communication and Collaboration Between Industry and Academia in Software Engineering

Background: The software engineering community has expressed growing concern regarding the need for more connections between research and practice. Despite the large amount of knowledge researchers generate, its impact on real-world practice is uncertain. Meanwhile, practitioners in industry often struggle to access and utilize relevant research outcomes that could inform and enhance their work. C

On the Challenges of Software Performance Optimization with Statistical Methods

Most recent programming languages, such as Java, Python and Ruby, include a collection framework as part of their standard library (or runtime). The Java Collection Framework provides a number of collection classes, some of which implement the same abstract data type, making them interchangeable. Developers can therefore choose between several functionally equivalent options. Since collections hav

Improving the Thresholds of Generalized LDPC Codes With Convolutional Code Constraints

CC-GLPDC codes are a class of generalized low-density parity-check (GLDPC) codes where the constraint nodes (CNs) represent convolutional codes. This allows for efficient decoding in the trellis with the forward-backward algorithm, and the strength of the component codes easily can be controlled by the encoder memory without changing the graph structure. In this letter, we extend the class of CC-G

Antenna System Design for 5G and Beyond – A Modal Approach

Antennas are one of the key components that empower a new generation of wireless technologies, such as 5G and new radar systems. It has been shown that antenna design strategies based on modal theories represent a powerful systematic approach to design practical antenna systems with high performance. In this thesis, several innovative multi-antenna systems are proposed for wireless applications in

Declarative Specification of Intraprocedural Control-flow and Dataflow Analysis

Static program analysis plays a crucial role in ensuring the quality and security of software applications by detecting and fixing bugs, and potential security vulnerabilities in the code. The use of declarative paradigms in dataflow analysis as part of static program analysis has become increasingly popular in recent years. This is due to its enhanced expressivity and modularity, allowing for a h

Channel Orthogonalization with Reconfigurable Surfaces

Orthogonal multi-user multiple-input multiple-output (MU-MIMO) channels allow for optimum performance with simplified precoding/equalization, and they achieve maximum multiplexing gain which is shared fairly among users. Reconfigurable intelligent surface (RIS) constitutes a promising cost-efficient solution to improve the wireless channel, since they consist of passive reflecting elements able to

Beyond Massive MIMO : Trade-offs and Opportunities with Large Multi-Antenna Systems

After the commercial emergence of 5G, the research community is already putting its focus on proposing innovative solutions to enable the upcoming 6G. One important lesson put forth by 5G research was that scaling up the conventional multiple-input-multiple-output (MIMO) technology by increasing the number of antennas could be extremely beneficial for effectively multiplexing data streams in the s