71 research outputs found
HiCu: Leveraging Hierarchy for Curriculum Learning in Automated ICD Coding
There are several opportunities for automation in healthcare that can improve
clinician throughput. One such example is assistive tools to document diagnosis
codes when clinicians write notes. We study the automation of medical code
prediction using curriculum learning, which is a training strategy for machine
learning models that gradually increases the hardness of the learning tasks
from easy to difficult. One of the challenges in curriculum learning is the
design of curricula -- i.e., in the sequential design of tasks that gradually
increase in difficulty. We propose Hierarchical Curriculum Learning (HiCu), an
algorithm that uses graph structure in the space of outputs to design curricula
for multi-label classification. We create curricula for multi-label
classification models that predict ICD diagnosis and procedure codes from
natural language descriptions of patients. By leveraging the hierarchy of ICD
codes, which groups diagnosis codes based on various organ systems in the human
body, we find that our proposed curricula improve the generalization of neural
network-based predictive models across recurrent, convolutional, and
transformer-based architectures. Our code is available at
https://github.com/wren93/HiCu-ICD.Comment: To appear at Machine Learning for Healthcare Conference (MLHC2022
Inter-Calibration of Satellite Passive Microwave Land Observations from AMSR-E and AMSR2 Using Overlapping FY3B-MWRI Sensor Measurements
The development and continuity of consistent long-term data records from similar overlapping satellite observations is critical for global monitoring and environmental change assessments. We developed an empirical approach for inter-calibration of satellite microwave brightness temperature (Tb) records over land from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and Microwave Scanning Radiometer 2 (AMSR2) using overlapping Tb observations from the Microwave Radiation Imager (MWRI). Double Differencing (DD) calculations revealed significant AMSR2 and MWRI biases relative to AMSR-E. Pixel-wise linear relationships were established from overlapping Tb records and used for calibrating MWRI and AMSR2 records to the AMSR-E baseline. The integrated multi-sensor Tb record was largely consistent over the major global vegetation and climate zones; sensor biases were generally well calibrated, though residual Tb differences inherent to different sensor configurations were still present. Daily surface air temperature estimates from the calibrated AMSR2 Tb inputs also showed favorable accuracy against independent measurements from 142 global weather stations (R2 ℠0.75, RMSE †3.64 °C), but with slightly lower accuracy than the AMSR-E baseline (R2 ℠0.78, RMSE †3.46 °C). The proposed method is promising for generating consistent, uninterrupted global land parameter records spanning the AMSR-E and continuing AMSR2 missions
Memristors Based on 2D Monolayer Materials
2D materials have been widely used in various applications due to their remarkable and distinct electronic, optical, mechanical and thermal properties. Memristive effect has been found in several 2D systems. This chapter focuses on the memristors based on 2D materials, e. g. monolayer transition metal dichalcogenides (TMDs) and hexagonal boron nitride (h-BN), as the active layer in vertical MIM (metalâinsulatorâmetal) configuration. Resistive switching behavior under normal DC and pulse waveforms, and current-sweep and constant stress testing methods have been investigated. Unlike the filament model in conventional bulk oxide-based memristors, a new switching mechanism has been proposed with the assistance of metal ion diffusion, featuring conductive-point random access memory (CPRAM) characteristics. The use of 2D material devices in applications such as flexible non-volatile memory (NVM) and emerging zero-power radio frequency (RF) switch will be discussed
From Castor OilâBased Multifunctional Polyols to Waterborne Polyurethanes: Synthesis and Properties
From Castor OilâBased Multifunctional Polyols to Waterborne Polyurethanes: Synthesis and Properties
Abstract A novel castor oilâbased multifunctional polyol (CM) is fabricated through mild thiolâene photo induced reactions using castor oil (CO) and 1âthioglycerol (MPD) as building blocks. The effect of the reaction time, molar ratio of thiol to carbonâcarbon double bond, and the loadings of photoâinitiator are optimized. The resulting CM is combined with CO and employed as crossâlinkers to prepare castor oilâbased waterâborne polyurethane emulsion with desirable mechanical properties and water resistance. Owing to the incorporation of CM crossâlinker with high hydroxyl value of 371 mg KOH/g (which is 2.27 times higher than that of the CO), the prepared castor oilâbased waterborne polyurethane (CMWPU) possesses compacted 3D network structure with high crossâlinking degree, leading to improved glass transition temperature (45 °C), tensile strength (10.8 MPa), water contact angle (87.4°), and decreased water absorption rate (16.12%) with 20% CM additions. Overall, this work illustrates the feasibility of introducing bio renewable CM combined with CO to develop castor oilâbased WPU employing a sustainable development strategy
Evaluation of Fengyun-3C Soil Moisture Products Using In-Situ Data from the Chinese Automatic Soil Moisture Observation Stations: A Case Study in Henan Province, China
Soil moisture (SM) products derived from passive satellite missions are playing an increasingly important role in agricultural applications, especially crop monitoring and disaster warning. Evaluating the dependability of satellite-derived soil moisture products on a large scale is crucial. In this study, we assessed the level 2 (L2) SM product from the Chinese Fengyun-3C (FY-3C) radiometer against in-situ measurements collected from the Chinese Automatic Soil Moisture Observation Stations (CASMOS) during a one-year period from 1 January 2016 to 31 December 2016 across Henan in China. In contrast, we also investigated the skill of the Advanced Microwave Scanning Radiometer 2 (AMSR2) and Soil Moisture Active/Passive (SMAP) SM products simultaneously. Four statistical parameters were used to evaluate these productsâ reliability: mean difference, root-mean-square error (RMSE), unbiased RMSE (ubRMSE), and the correlation coefficient. Our assessment results revealed that the FY-3C L2 SM product generally showed a poor correlation with the in-situ SM data from CASMOS on both temporal and spatial scales. The AMSR2 L3 SM product of JAXA (Japan Aerospace Exploration Agency) algorithm had a similar level of skill as FY-3C in the study area. The SMAP L3 SM product outperformed the FY-3C temporally but showed lower performance in capturing the SM spatial variation. A time-series analysis indicated that the correlations and estimated error varied systematically through the growing periods of the key crops in our study area. FY-3C L2 SM data tended to overestimate soil moisture during May, August, and September when the crops reached maximum vegetation density and tended to underestimate the soil moisture content during the rest of the year. The comparison between the statistical parameters and the ground vegetation water content (VWC) further showed that the FY-3C SM product performed much better under a low VWC condition (0.3 kg/m2), and the performance generally decreased with increased VWC. To improve the accuracy of the FY-3C SM product, an improved algorithm that can better characterize the variations of the ground VWC should be applied in the future
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Electron irradiation-induced defects for reliability improvement in monolayer MoS2-based conductive-point memory devices
Monolayer molybdenum disulïŹde has been previously discovered to exhibit non-volatile resistive switching behavior in a vertical
metal-insulator-metal structure, featuring ultra-thin sub-nanometer active layer thickness. However, the reliability of these nascent
2D-based memory devices was not previously investigated for practical applications. Here, we employ an electron irradiation
treatment on monolayer MoS2 ïŹlm to modify the defect properties. Raman, photoluminescence, and X-ray photoelectron
spectroscopy measurements have been performed to conïŹrm the increasing amount of sulfur vacancies introduced by the e-beam
irradiation process. The statistical electrical studies reveal the reliability can be improved by up to 1.5Ă for yield and 11Ă for average
DC cycling endurance in the devices with a moderate radiation dose compared to unirradiated devices. Based on our previously
proposed virtual conductive-point model with the metal ion substitution into sulfur vacancy, Monte Carlo simulations have been
performed to illustrate the irradiation effect on device reliability, elucidating a clustering failure mechanism. This work provides an
approach by electron irradiation to enhance the reliability of 2D memory devices and inspires further research in defect
engineering to precisely control the switching properties for a wide range of applications from memory computing to radio-
frequency switches.This work was supported in part by the National Science Foundation (NSF) grant
#1809017, and an NSF MRSEC under Cooperative Agreement No. DMR-1720595. The
authors acknowledge use of Texas Nanofabrication Facilities supported by the NSF
NNCI award #1542159. D.A. acknowledges the Presidential Early Career Award for
Scientists and Engineers (PECASE) through the Army Research OfïŹce (W911NF-16-1-
0277).Center for Dynamics and Control of Material
Twenty Novel Disease Group-Specific and 12 New Shared Macrophage Pathways in Eight Groups of 34 Diseases Including 24 Inflammatory Organ Diseases and 10 Types of Tumors.
The mechanisms underlying pathophysiological regulation of tissue macrophage (MÏ) subsets remain poorly understood. From the expression of 207 MÏ genes comprising 31 markers for 10 subsets, 45 transcription factors (TFs), 56 immunometabolism enzymes, 23 trained immunity (innate immune memory) enzymes, and 52 other genes in microarray data, we made the following findings. (1) When 34 inflammation diseases and tumor types were grouped into eight categories, there was differential expression of the 31 MÏ markers and 45 MÏ TFs, highlighted by 12 shared and 20 group-specific disease pathways. (2) MÏ in lung, liver, spleen, and intestine (LLSI-MÏ) express higher M1 MÏ markers than lean adipose tissue MÏ (ATMÏ) physiologically. (3) Pro-adipogenic TFs C/EBPα and PPARÎł and proinflammatory adipokine leptin upregulate the expression of M1 MÏ markers. (4) Among 10 immune checkpoint receptors (ICRs), LLSI-MÏ and bone marrow (BM) MÏ express higher levels of CD274 (PDL-1) than ATMÏ, presumably to counteract the M1 dominant status via its reverse signaling behavior. (5) Among 24 intercellular communication exosome mediators, LLSI- and BM- MÏ prefer to use RAB27A and STX3 than RAB31 and YKT6, suggesting new inflammatory exosome mediators for propagating inflammation. (6) MÏ in peritoneal tissue and LLSI-MÏ upregulate higher levels of immunometabolism enzymes than does ATMÏ. (7) MÏ from peritoneum and LLSI-MÏ upregulate more trained immunity enzyme genes than does ATMÏ. Our results suggest that multiple new mechanisms including the cell surface, intracellular immunometabolism, trained immunity, and TFs may be responsible for disease group-specific and shared pathways. Our findings have provided novel insights on the pathophysiological regulation of tissue MÏ, the disease group-specific and shared pathways of MÏ, and novel therapeutic targets for cancers and inflammations
29 m 6 A-RNA Methylation (Epitranscriptomic) Regulators Are Regulated in 41 Diseases including Atherosclerosis and Tumors Potentially via ROS Regulation - 102 Transcriptomic Dataset Analyses
We performed a database mining on 102 transcriptomic datasets for the expressions of 29 m6A-RNA methylation (epitranscriptomic) regulators (m6A-RMRs) in 41 diseases and cancers and made significant findings: (1) a few m6A-RMRs were upregulated; and most m6A-RMRs were downregulated in sepsis, acute respiratory distress syndrome, shock, and trauma; (2) half of 29 m6A-RMRs were downregulated in atherosclerosis; (3) inflammatory bowel disease and rheumatoid arthritis modulated m6A-RMRs more than lupus and psoriasis; (4) some organ failures shared eight upregulated m6A-RMRs; end-stage renal failure (ESRF) downregulated 85% of m6A-RMRs; (5) Middle-East respiratory syndrome coronavirus infections modulated m6A-RMRs the most among viral infections; (6) proinflammatory oxPAPC modulated m6A-RMRs more than DAMP stimulation including LPS and oxLDL; (7) upregulated m6A-RMRs were more than downregulated m6A-RMRs in cancer types; five types of cancers upregulated â„10 m6A-RMRs; (8) proinflammatory M1 macrophages upregulated seven m6A-RMRs; (9) 86% of m6A-RMRs were differentially expressed in the six clusters of CD4+Foxp3+ immunosuppressive Treg, and 8 out of 12 Treg signatures regulated m6A-RMRs; (10) immune checkpoint receptors TIM3, TIGIT, PD-L2, and CTLA4 modulated m6A-RMRs, and inhibition of CD40 upregulated m6A-RMRs; (11) cytokines and interferons modulated m6A-RMRs; (12) NF-ÎșB and JAK/STAT pathways upregulated more than downregulated m6A-RMRs whereas TP53, PTEN, and APC did the opposite; (13) methionine-homocysteine-methyl cycle enzyme Mthfd1 downregulated more than upregulated m6A-RMRs; (14) m6A writer RBM15 and one m6A eraser FTO, H3K4 methyltransferase MLL1, and DNA methyltransferase, DNMT1, regulated m6A-RMRs; and (15) 40 out of 165 ROS regulators were modulated by m6A eraser FTO and two m6A writers METTL3 and WTAP. Our findings shed new light on the functions of upregulated m6A-RMRs in 41 diseases and cancers, nine cellular and molecular mechanisms, novel therapeutic targets for inflammatory disorders, metabolic cardiovascular diseases, autoimmune diseases, organ failures, and cancers
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