Recrystallized parylene as a mask for silicon chemical etching

This paper presents the first use of recrystallized parylene as masking material for silicon chemical etch. Recrystallized parylene was obtained by melting parylene C at 350°C for 2 hours. The masking ability of recrystallized parylene was tested in HNA (hydrofluoric acid, nitric acid and acetic acid) solution of various ratios, KOH (potassium hydroxide) solution and TMAH (tetramethylammonium hydroxide) at different temperatures and concentrations. It is found that interface between parylene and the substrate can be attacked, which results in undercuts. Otherwise, recrystallized parylene exhibited good adhesion to silicon, complete protection of unexposed silicon and silicon etching rates comparable to literature data

Interpretable Clustering on Dynamic Graphs with Recurrent Graph Neural Networks

We study the problem of clustering nodes in a dynamic graph, where the connections between nodes and nodes' cluster memberships may change over time, e.g., due to community migration. We first propose a dynamic stochastic block model that captures these changes, and a simple decay-based clustering algorithm that clusters nodes based on weighted connections between them, where the weight decreases at a fixed rate over time. This decay rate can then be interpreted as signifying the importance of including historical connection information in the clustering. However, the optimal decay rate may differ for clusters with different rates of turnover. We characterize the optimal decay rate for each cluster and propose a clustering method that achieves almost exact recovery of the true clusters. We then demonstrate the efficacy of our clustering algorithm with optimized decay rates on simulated graph data. Recurrent neural networks (RNNs), a popular algorithm for sequence learning, use a similar decay-based method, and we use this insight to propose two new RNN-GCN (graph convolutional network) architectures for semi-supervised graph clustering. We finally demonstrate that the proposed architectures perform well on real data compared to state-of-the-art graph clustering algorithms

Microscopically Visible Internal Surface Area of Earlywood and Latewood of Loblolly Pine

Microscopically visible internal surface (MVIS) areas of earlywood and latewood of loblolly pine were estimated. Steps of calculation for MVIS area described. For the study tree, there was no difference in MVIS area between earlywood and latewood for the same volume in spite of difference in specific gravity. However, on a unit-weight basis, MVIS area decreased with increasing specific gravity

Q-enhanced fold-and-bond MEMS inductors

This work presents a novel coil fabrication technology to enhance quality factor (Q factor) of microfabricated inductors for implanted medical wireless sensing and data/power transfer applications. Using parylene as a flexible thin-film device substrate, a post-microfabrication substrate folding-and-bonding method is developed to effectively increase the metal thickness of the surface-micromachined inductors, resulting in their lower self-resistance so their higher quality factor. One-fold-and-bond coils are successfully demonstrated as an example to verify the feasibility of the fabrication technology with measurement results in good agreements with device simulation. Depending on target specifications, multiple substrate folding-and-bonding can be extensively implemented to facilitate further improved electrical characteristics of the coils from single fabrication batch. Such Q-enhanced inductors can be broadly utilized with great potentials in flexible integrated wireless devices/systems for intraocular prostheses and other biomedical implants

Numerical analysis and design strategy for field emission devices

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.Includes bibliographical references (p. 165-172).by Yao-Joe Yang.Ph.D

Comparison of family centered care with family integrated care and mobile technology (mFICare) on preterm infant and family outcomes: a multi-site quasi-experimental clinical trial protocol.

BackgroundFamily Centered Care (FCC) has been widely adopted as the framework for caring for infants in the Neonatal Intensive Care Unit (NICU) but it is not uniformly defined or practiced, making it difficult to determine impact. Previous studies have shown that implementing the Family Integrated Care (FICare) intervention program for preterm infants in the NICU setting leads to significant improvements in infant and family outcomes. Further research is warranted to determine feasibility, acceptability and differential impact of FICare in the US context. The addition of a mobile application (app) may be effective in providing supplemental support for parent participation in the FICare program and provide detailed data on program component uptake and outcomes.MethodsThis exploratory multi-site quasi-experimental study will compare usual FCC with mobile enhanced FICare (mFICare) on growth and clinical outcomes of preterm infants born at or before 33 weeks gestational age, as well as the stress, competence and self-efficacy of their parents. The feasibility and acceptability of using mobile technology to gather data about parent involvement in the care of preterm infants receiving FCC or mFICare as well as of the mFICare intervention will be evaluated (Aim 1). The effect sizes for infant growth (primary outcome) and for secondary infant and parent outcomes at NICU discharge and three months after discharge will be estimated (Aim 2).DiscussionThis study will provide new data about the implementation of FICare in the US context within various hospital settings and identify important barriers, facilitators and key processes that may contribute to the effectiveness of FICare. It will also offer insights to clinicians on the feasibility of a new mobile application to support parent-focused research and promote integration of parents into the NICU care team in US hospital settings.Trial registrationClinicalTrials.gov, ID NCT03418870. Retrospectively registered on December 18, 2017

Dynamical modulation of solar flare electron acceleration due to plasmoid-shock interactions in the looptop region

A fast-mode shock can form in the front of reconnection outflows and has been suggested as a promising site for particle acceleration in solar flares. Recent development of magnetic reconnection has shown that numerous plasmoids can be produced in a large-scale current layer. Here we investigate the dynamical modulation of electron acceleration in the looptop region when plasmoids intermittently arrive at the shock by combining magnetohydrodynamics simulations with a particle kinetic model. As plasmoids interact with the shock, the looptop region exhibits various compressible structures that modulate the production of energetic electrons. The energetic electron population varies rapidly in both time and space. The number of 5$-$10 keV electrons correlates well with the area with compression, while that of $>$50 keV electrons shows good correlation with strong compression area but only moderate correlation with shock parameters. We further examine the impacts of the first plasmoid, which marks the transition from a quasi-steady shock front to a distorted and dynamical shock. The number of energetic electrons is reduced by $\sim 20\%$ at 15$-$25 keV and nearly 40\% for 25$-$50 keV, while the number of 5$-$10 keV electrons increases. In addition, the electron energy spectrum above 10 keV evolves softer with time. We also find double or even multiple distinct sources can develop in the looptop region when the plasmoids move across the shock. Our simulations have strong implications to the interpretation of nonthermal looptop sources, as well as the commonly observed fast temporal variations in flare emissions, including the quasi-periodic pulsations.Comment: accepted for publication in ApJ

FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System

Federated Learning trains machine learning models on distributed devices by aggregating local model updates instead of local data. However, privacy concerns arise as the aggregated local models on the server may reveal sensitive personal information by inversion attacks. Privacy-preserving methods, such as homomorphic encryption (HE), then become necessary for FL training. Despite HE's privacy advantages, its applications suffer from impractical overheads, especially for foundation models. In this paper, we present FedML-HE, the first practical federated learning system with efficient HE-based secure model aggregation. FedML-HE proposes to selectively encrypt sensitive parameters, significantly reducing both computation and communication overheads during training while providing customizable privacy preservation. Our optimized system demonstrates considerable overhead reduction, particularly for large foundation models (e.g., ~10x reduction for ResNet-50, and up to ~40x reduction for BERT), demonstrating the potential for scalable HE-based FL deployment

Evaluation of information technology investment: a data envelopment analysis approach

Abstract The increasing use of information technology (IT) has resulted in a need for evaluating the productivity impacts of IT. The contemporary IT evaluation approach has focused on return on investment and return on management. IT investment has impacts on different stages of business operations. For example, in the banking industry, IT plays a key role in effectively generating (i) funds from the customer in the forms of deposits and then (ii) profits by using deposits as investment funds. Existing approaches based upon data envelopment analysis (DEA) only measure the IT efficiency or impact on one specific stage when a multi-stage business process is present. A detailed model is needed to characterize the impact of IT on each stage of the business operation. The current paper develops a DEA non-linear programming model to evaluate the impact of IT on multiple stages along with information on how to distribute the IT-related resources so that the efficiency is maximized. It is shown that this non-linear program can be treated as a parametric linear program. It is also shown that if there is only one intermediate measure, then the non-linear DEA model becomes a linear program. Our approach is illustrated with an example taken from previous studies.