bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of an eight-week smartphone-guided HRV-biofeedback intervention on autonomic function and impulsivity in healthy controls
Authors: Schumann Andy , Köhler Stefanie , Brotte Lisa , Bär Karl-Jürgen 
Published: May 2019

Abstract
A large body of scientific studies suggest a close relationship between increased vagal function and better cognitive performance. Objective: In the current study, we investigated the association between autonomic function and behavioral impulsivity. We hypothesized that heart rate variability (HRV) biofeedback training increases HRV and enhances inhibitory control. Approach: A total of 28 healthy participants were recruited. After drop-out, 14 participants completed an eight-week HRV biofeedback training with five training sessions per week including one session at the clinic’s laboratory and four sessions at home using a mobile application running on their smartphone. Ten control subjects matched with respect to age and gender played a mobile game according to the same schedule as the biofeedback group. The assessment of autonomic status and the stop-signal task were conducted before the beginning of the training (T1) and after finishing the schedule (T2). Main results: We found a relationship of reaction times in the stop-signal task and standard HRV as well as cardiorespiratory indices. After biofeedback training, short-term HRV and baroreflex function significantly increased by 33% (CI [2%, 64%], p   <  0.05) and 21% (CI [5%, 36%], p   <  0.05), respectively. The performance in the stop-signal task was not affected by the biofeedback intervention. Compared to the changes of autonomic indices in the control group, only a decrease of skin conductance levels in the biofeedback group remained statistically significant. Significance: Our results indicate that a smartphone-based HRV biofeedback intervention can be applied to improve cardiovagal function in healthy subjects. Although higher HRV was associated with higher levels of inhibitory control, HRV biofeedback had no effect on measures of impulsivity.
Multi-channel 28-GHz millimeter-wave signal generation on a silicon photonic chip with automated polarization control
Authors: Cao Ruiyuan , He Yu , Zhu Qingming , Li Jingchi , An Shaohua , Zhang Yong , Su Yikai 
Published: May 2019

Abstract
We propose and experimentally demonstrate an integrated silicon photonic scheme to generate multi-channel millimeter-wave (MMW) signals for 5G multi-user applications. The fabricated silicon photonic chip has a footprint of 1.1 × 2.1 mm2 and integrates 7 independent channels each having on-chip polarization control and heterodyne mixing functions. 7 channels of 4-Gb/s QPSK baseband signals are delivered via a 2-km multi-core fiber (MCF) and coupled into the chip with a local oscillator (LO) light. The polarization state of each signal light is automatically adjusted and aligned with that of the LO light, and then 7 channels of 28-GHz MMW carrying 4-Gb/s QPSK signals are generated by optical heterodyne beating. Automated polarization-control function of each channel is also demonstrated with ~7-ms tuning time and ~27-dB extinction ratio.
Research for radiation-hardened high-voltage SOI LDMOS
Authors: Li Yanfei , Zhu Shaoli , Wu Jianwei , Hong Genshen , Xu Zheng 
Published: May 2019

Abstract
Based on the silicon-on-insulator (SOI) technology and radiation-hardened silicon gate (RSG) process, a radiation-hardened high-voltage lateral double-diffused MOSFET (LDMOS) device is presented in this paper. With the gate supply voltage of 30 V, the LDMOS device has a gate oxide thickness of 120 nm, and the RSG process is effective in reducing the total ionizing dose (TID) radiation-induced threshold voltage shift. The p-type ion implantation process and gate-enclosed layout topology are used to prevent radiation-induced leakage current through a parasitic path under the bird's beak and at the deep trench corner, and the device is compatible with high-voltage SOI CMOS process. In the proposed LDMOS, the total ionizing dose radiation degradation for the ON bias is more sensitive than the OFF bias. The experiment results show that the SOI LDMOS has a negative threshold voltage shift of 1.12 V, breakdown voltage of 135 V, and off-state leakage current of 0.92 pA/μm at an accumulated dose level of 100 krad (Si).
Design and analysis of a NMOS triggered LIGBT structure for electrostatic discharge protection
Authors: Tian Li , Cheng Jianbing , Zhang Cairong , Shen Li , Wang Lei 
Published: May 2019

Abstract
A novel NMOS triggered LIGBT (NTLIGBT) structure is proposed for electrostatic discharge (ESD) protection in this paper. The structure utilizes internal NMOS to trigger SCR-like structure in LIGBT. The trigger voltage is significantly reduced because the embedded NMOS causes N+-drain/P-body junction being apt to avalanche breakdown. At the same time, the new parasitic PNP transistor including the newly added P+-region as a collector forms another path to bleed ESD current and then the conductivity modulation in the LIGBT is weakened. As a result, the holding voltage is increased. So, the proposed NTLIGBT structure has a narrow ESD design window. The simulation results show an improvement of 71.5% in trigger voltage and over 50% in holding voltage comparing with the conventional LIGBT structure.
Realizing super-long Cu2O nanowires arrays for high-efficient water splitting applications with a convenient approach
Authors: Nasori Nasori , Dai Tianyi , Jia Xiaohao , Rubiyanto Agus , Cao Dawei , Qu Shengchun , Wang Zhanguo , Wang Zhijie , Lei Yong 
Published: May 2019

Abstract
Nanowire (NW) structures is an alternative candidate for constructing the next generation photoelectrochemical water splitting system, due to the outstanding optical and electrical properties. NW photoelectrodes comparing to traditional semiconductor photoelectrodes shows the comparatively shorter transfer distance of photo-induced carriers and the increase amount of the surface reaction sites, which is beneficial for lowering the recombination probability of charge carriers and improving their photoelectrochemical (PEC) performances. Here, we demonstrate for the first time that super-long Cu2O NWs, more than 4.5 μm, with highly efficient water splitting performance, were synthesized using a cost-effective anodic alumina oxide (AAO) template method. In comparison with the photocathode with planar Cu2O films, the photocathode with Cu2O NWs demonstrates a significant enhancement in photocurrent, from –1.00 to –2.75 mA/cm2 at –0.8 V versus Ag/AgCl. After optimization of the photoelectrochemical electrode through depositing Pt NPs with atomic layer deposition (ALD) technology on the Cu2O NWs, the plateau of photocurrent has been enlarged to –7 mA/cm2 with the external quantum yield up to 34% at 410 nm. This study suggests that the photoelectrode based on Cu2O NWs is a hopeful system for establishing high-efficiency water splitting system under visible light.
Effects of V-pits covering layer position on the optoelectronic performance of InGaN green LEDs
Authors: Xu Chen , Zheng Changda , Wu Xiaoming , Pan Shuan , Jiang Xingan , Liu Junlin , Jiang Fengyi 
Published: May 2019

Abstract
The impact of the V-pits covering layer (VCL) position on the optoelectronic performance of InGaN-based green light-emitting diodes (LEDs) was investigated. It is found that earlier covering of V-pits will hinder the hole injection via the sidewall of V-pits, and then result in less quantum wells (QWs) participating in radioluminescence. The current-voltage characteristics show that the LEDs with earlier covering of V-pits have higher operating voltage at room temperature, and a more dramatic voltage rise with the reduction of temperature. Meanwhile, more manifested emission peaks for sidewall QWs and deeper QWs near to n-type layer was observed in the sample with earlier coveing of V-pits at cryogenic temperatures, for the reason that the holes being injected via V-pits sidewall have higher kinetic energy and could transport to deeper QWs.
A novel 4H-SiC trench MOSFET with double shielding structures and ultralow gate-drain charge
Authors: Luo Xiaorong , Liao Tian , Wei Jie , Fang Jian , Yang Fei , Zhang Bo 
Published: May 2019

Abstract
A new ultralow gate–drain charge (Q
GD) 4H-SiC trench MOSFET is presented and its mechanism is investigated by simulation. The novel MOSFET features double shielding structures (DS-MOS): one is the grounded split gate (SG), the other is the P+ shielding region (PSR). Both the SG and the PSR reduce the coupling effect between the gate and the drain, and transform the most part of the gate–drain capacitance (C
GD) into the gate–source capacitance (C
GS) and drain–source capacitance (C
DS) in series. Thus the C
GD is reduced and the proposed DS-MOS obtains ultralow Q
GD. Compared with the double-trench MOSFET (DT-MOS) and the conventional trench MOSFET (CT-MOS), the proposed DS-MOS decreases the Q
GD by 85% and 81%, respectively. Moreover, the figure of merit (FOM), defined as the product of specific on-resistance (R
on, sp) and Q
GD (R
on, sp
Q
GD), is reduced by 84% and 81%, respectively.
A novel design approach of charge plasma tunnel FET for radio frequency applications
Authors: Yadav Shivendra , Pamnani Alish , Sharma Dheeraj , Gedam Anju , Kumar Atul , Sharma Neeraj 
Published: May 2019

Abstract
In this paper, the impact of extra electron source (EES) and dual metal gate engineering on conventional charge plasma TFET (CP-TFET) have been done for improving DC and analog/RF parameters. CP-TFET structure is upgraded to double source CP-TFET (DS-CP-TFET) by placing an EES below the source/channel junction for enhancing the device performance in terms of driving current and RF figures of merit (FOMs). But, in spite of these pros, the approach is having cons of higher leakage current similar to MOSFET and negative conductance (inherent nature of TFET). Both the issues have been resolved in the double source dual gate CP-TFET (DS-DG-CP-TFET) by gate workfunction engineering and drain underlapping respectively. Additionally, for getting the optimum performance of DS-DG-CP-TFET, the device sensitivity has been investigated in terms of position of EES, length of drain electrode and workfunction of gate electrode 1 (GE1).
Realistic volumetric-approach to simulate transcranial electric stimulation—ROAST—a fully automated open-source pipeline
Authors: Huang Yu , Datta Abhishek , Bikson Marom , Parra Lucas C 
Published: May 2019

Abstract

Objective. Research in the area of transcranial electrical stimulation (TES) often relies on computational models of current flow in the brain. Models are built based on magnetic resonance images (MRI) of the human head to capture detailed individual anatomy. To simulate current flow on an individual, the subject’s MRI is segmented, virtual electrodes are placed on this anatomical model, the volume is tessellated into a mesh, and a finite element model (FEM) is solved numerically to estimate the current flow. Various software tools are available for each of these steps, as well as processing pipelines that connect these tools for automated or semi-automated processing. The goal of the present tool—realistic volumetric-approach to simulate transcranial electric simulation (ROAST)—is to provide an end-to-end pipeline that can automatically process individual heads with realistic volumetric anatomy leveraging open-source software and custom scripts to improve segmentation and execute electrode placement. Approach. ROAST combines the segmentation algorithm of SPM12, a Matlab script for touch-up and automatic electrode placement, the finite element mesher iso2mesh and the solver getDP. We compared its performance with commercial FEM software, and SimNIBS, a well-established open-source modeling pipeline. Main results. The electric fields estimated with ROAST differ little from the results obtained with commercial meshing and FEM solving software. We also do not find large differences between the various automated segmentation methods used by ROAST and SimNIBS. We do find bigger differences when volumetric segmentation are converted into surfaces in SimNIBS. However, evaluation on intracranial recordings from human subjects suggests that ROAST and SimNIBS are not significantly different in predicting field distribution, provided that users have detailed knowledge of SimNIBS. Significance. We hope that the detailed comparisons presented here of various choices in this modeling pipeline can provide guidance for future tool development. We released ROAST as an open-source, easy-to-install and fully-automated pipeline for individualized TES modeling.
Immunohistochemical and Ultrastructural Features of Hepatocellular Cytoplasmic Globules in Venous Outflow Impairment
Authors: Buglioni Alessia , Wu Tsung-Teh , Mounajjed Taofic 
Published: May 2019

Abstract

Objectives
To examine the immunohistochemical and ultrastructural features of hepatocellular cytoplasmic globules in venous outflow impairment (VOI).

Methods
Sixty-four liver core biopsies were screened. Patients with α-1 antitrypsin (AAT) deficiency were excluded. All biopsies were stained with H&E, Masson trichrome, periodic acid-Schiff with diastase digestion (PAS-D), phosphotungstic acid hematoxylin (PTAH), complement protein 4d (C4d) immunostain, and AAT immunostain. Electron microscopy was also performed.

Results
Hepatocellular globules were identified in 8% of in-house cases. Causes of VOI included heart failure and Budd-Chiari syndrome. The hepatocellular cytoplasmic globules showed size variability, random distribution, and positivity for PAS-D, PTAH, and AAT. C4d was inconsistently positive. Electron microscopy showed that the globules were lysosome-bound inclusions containing microfibrillar material and fibrinogen.

Conclusions
PAS-D–positive hepatocellular globules occur in VOI. They cross-react with AAT but have different appearance, localization, and ultrastructural composition from globules in AAT deficiency.
Ambient Fine Particulate Matter and Preterm Birth in California: Identification of Critical Exposure Windows
Authors: Sheridan Paige , Ilango Sindana , Bruckner Tim A , Wang Qiong , Basu Rupa , Benmarhnia Tarik 
Published: May 2019

AbstractExposure to ambient fine particulate matter (particulate matter ≤2.5 μm in aerodynamic diameter (PM2.5)) during pregnancy is associated with preterm birth (PTB), a leading cause of infant morbidity and mortality. Results from studies attempting to identify etiologically relevant exposure periods of vulnerability have been inconsistent, possibly because of failure to consider the time-to-event nature of the outcome and lagged exposure effects of PM2.5. In this study, we aimed to identify critical exposure windows for weekly PM2.5 exposure and PTB in California using California birth cohort data from 2005–2010. Associations were assessed using distributed-lag Cox proportional hazards models. We assessed effect-measure modification by race/ethnicity by calculating the weekly relative excess risk due to interaction. For a 10-μg/m3 increase in PM2.5 exposure over the entire period of gestation, PTB risk increased by 11% (hazard ratio = 1.11, 95% confidence interval: 1.09, 1.14). Gestational weeks 17–24 and 36 were associated with increased vulnerability to PM2.5 exposure. We find that non-Hispanic black mothers may be more susceptible to effects of PM2.5 exposure than non-Hispanic white mothers, particularly at the end of pregnancy. These findings extend our knowledge about the existence of specific exposure periods during pregnancy that have the greatest impact on preterm birth.
Methodological Challenges When Studying Distance to Care as an Exposure in Health Research
Authors: Caniglia Ellen C , Zash Rebecca , Swanson Sonja A , Wirth Kathleen E , Diseko Modiegi , Mayondi Gloria , Lockman Shahin , Mmalane Mompati , Makhema Joseph , Dryden-Peterson Scott , Kponee-Shovein Kalé Z , John Oaitse , Murray Eleanor J , Shapiro Roger L 
Published: May 2019

Abstract
Distance to care is a common exposure and proposed instrumental variable in health research, but it is vulnerable to violations of fundamental identifiability conditions for causal inference. We used data collected from the Botswana Birth Outcomes Surveillance study between 2014 and 2016 to outline 4 challenges and potential biases when using distance to care as an exposure and as a proposed instrument: selection bias, unmeasured confounding, lack of sufficiently well-defined interventions, and measurement error. We describe how these issues can arise, and we propose sensitivity analyses for estimating the degree of bias.
PRISM: methylation pattern-based, reference-free inference of subclonal makeup
Authors: Lee Dohoon , Lee Sangseon , Kim Sun 
Published: May 2019

Abstract

Motivation
Characterizing cancer subclones is crucial for the ultimate conquest of cancer. Thus, a number of bioinformatic tools have been developed to infer heterogeneous tumor populations based on genomic signatures such as mutations and copy number variations. Despite accumulating evidence for the significance of global DNA methylation reprogramming in certain cancer types including myeloid malignancies, none of the bioinformatic tools are designed to exploit subclonally reprogrammed methylation patterns to reveal constituent populations of a tumor. In accordance with the notion of global methylation reprogramming, our preliminary observations on acute myeloid leukemia (AML) samples implied the existence of subclonally occurring focal methylation aberrance throughout the genome.

Results
We present PRISM, a tool for inferring the composition of epigenetically distinct subclones of a tumor solely from methylation patterns obtained by reduced representation bisulfite sequencing. PRISM adopts DNA methyltransferase 1-like hidden Markov model-based in silico proofreading for the correction of erroneous methylation patterns. With error-corrected methylation patterns, PRISM focuses on a short individual genomic region harboring dichotomous patterns that can be split into fully methylated and unmethylated patterns. Frequencies of such two patterns form a sufficient statistic for subclonal abundance. A set of statistics collected from each genomic region is modeled with a beta-binomial mixture. Fitting the mixture with expectation-maximization algorithm finally provides inferred composition of subclones. Applying PRISM for two AML samples, we demonstrate that PRISM could infer the evolutionary history of malignant samples from an epigenetic point of view.

Availability and implementation
PRISM is freely available on GitHub (https://github.com/dohlee/prism).

Supplementary information
Supplementary data are available at Bioinformatics online.
Block HSIC Lasso: model-free biomarker detection for ultra-high dimensional data
Authors: Climente-González Héctor , Azencott Chloé-Agathe , Kaski Samuel , Yamada Makoto 
Published: May 2019

AbstractMotivationFinding non-linear relationships between biomolecules and a biological outcome is computationally expensive and statistically challenging. Existing methods have important drawbacks, including among others lack of parsimony, non-convexity and computational overhead. Here we propose block HSIC Lasso, a non-linear feature selector that does not present the previous drawbacks.ResultsWe compare block HSIC Lasso to other state-of-the-art feature selection techniques in both synthetic and real data, including experiments over three common types of genomic data: gene-expression microarrays, single-cell RNA sequencing and genome-wide association studies. In all cases, we observe that features selected by block HSIC Lasso retain more information about the underlying biology than those selected by other techniques. As a proof of concept, we applied block HSIC Lasso to a single-cell RNA sequencing experiment on mouse hippocampus. We discovered that many genes linked in the past to brain development and function are involved in the biological differences between the types of neurons.Availability and implementationBlock HSIC Lasso is implemented in the Python 2/3 package pyHSICLasso, available on PyPI. Source code is available on GitHub (https://github.com/riken-aip/pyHSICLasso).Supplementary informationSupplementary data are available at Bioinformatics online.
Deep learning with multimodal representation for pancancer prognosis prediction
Authors: Cheerla Anika , Gevaert Olivier 
Published: May 2019

Abstract

Motivation
Estimating the future course of patients with cancer lesions is invaluable to physicians; however, current clinical methods fail to effectively use the vast amount of multimodal data that is available for cancer patients. To tackle this problem, we constructed a multimodal neural network-based model to predict the survival of patients for 20 different cancer types using clinical data, mRNA expression data, microRNA expression data and histopathology whole slide images (WSIs). We developed an unsupervised encoder to compress these four data modalities into a single feature vector for each patient, handling missing data through a resilient, multimodal dropout method. Encoding methods were tailored to each data type—using deep highway networks to extract features from clinical and genomic data, and convolutional neural networks to extract features from WSIs.

Results
We used pancancer data to train these feature encodings and predict single cancer and pancancer overall survival, achieving a C-index of 0.78 overall. This work shows that it is possible to build a pancancer model for prognosis that also predicts prognosis in single cancer sites. Furthermore, our model handles multiple data modalities, efficiently analyzes WSIs and represents patient multimodal data flexibly into an unsupervised, informative representation. We thus present a powerful automated tool to accurately determine prognosis, a key step towards personalized treatment for cancer patients.

Availability and implementation
https://github.com/gevaertlab/MultimodalPrognosis
Large-scale mammalian genome rearrangements coincide with chromatin interactions
Authors: Swenson Krister M , Blanchette Mathieu 
Published: May 2019

Abstract

Motivation
Genome rearrangements drastically change gene order along great stretches of a chromosome. There has been initial evidence that these apparently non-local events in the 1D sense may have breakpoints that are close in the 3D sense. We harness the power of the Double Cut and Join model of genome rearrangement, along with Hi-C chromosome conformation capture data to test this hypothesis between human and mouse.

Results
We devise novel statistical tests that show that indeed, rearrangement scenarios that transform the human into the mouse gene order are enriched for pairs of breakpoints that have frequent chromosome interactions. This is observed for both intra-chromosomal breakpoint pairs, as well as for inter-chromosomal pairs. For intra-chromosomal rearrangements, the enrichment exists from close (&lt;20 Mb) to very distant (100 Mb) pairs. Further, the pattern exists across multiple cell lines in Hi-C data produced by different laboratories and at different stages of the cell cycle. We show that similarities in the contact frequencies between these many experiments contribute to the enrichment. We conclude that either (i) rearrangements usually involve breakpoints that are spatially close or (ii) there is selection against rearrangements that act on spatially distant breakpoints.

Availability and implementation
Our pipeline is freely available at https://bitbucket.org/thekswenson/locality.

Supplementary information
Supplementary data are available at Bioinformatics online.