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Deep learning for peptide identification from metaproteomics datasets

Description: This article explores a proposed deep-learning-based algorithm called DeepFilter for improving peptide identifications from a collection of tandem mass spectra. The authors find that DeepFilter is believed to generalize properly to new, previously unseen peptide-spectrum-matches and can be readily applied in peptide identification from metaproteomics data.
Date: July 8, 2021
Creator: Feng, Shichao; Sterzenbach, Ryan & Guo, Xuan
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open access

Deep Submicron Extended-Gate Field-Effect (EGFET) Based on Transistor Association Technique for Chemical Sensing

Description: This article investigates the design and characterization of a transistor association (TA)-based extended-gate field-effect transistor (EGFET). Prototypes were manufactured using a 130 nm standard complementary metal-oxide semiconductor (CMOS) process and compared with devices presented in recent literature.
Date: March 2, 2019
Creator: Pullano, Salvatore Andrea; Tasneem, Nishat Tarannum; Mahbub, Ifana; Shamsir, Samira; Greco, Marta; Islam, Syed Kamrul et al.
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Deformation behavior and strengthening effects of an eutectic AlCoCrFeNi2.1 high entropy alloy probed by in-situ synchrotron X-ray diffraction and post-mortem EBSD

Description: Article describes how high energy synchrotron X-ray diffraction was used during tensile testing of an as-cast eutectic AlCoCrFeNi2.1 high entropy alloy. The authors determine for the first time the volume fractions of existing phases, and they further detail their role on the alloy deformation behavior.
Date: March 27, 2023
Creator: Shen, Jiajia; Lopes, J.G.; Zeng, Zhi; Choi, Yeon Taek; Maawad, E.; Schell, N. et al.
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Deformation induced intermediate metastable lattice structures facilitate ordered B2 nucleation in a fcc-based high entropy alloy

Description: This article reports a novel mixed-mode coupled displacive-diffusional transformation resulting in homogeneously distributed intra-granular B2 precipitates within the fcc matrix.
Date: December 5, 2018
Creator: Choudhuri, Deep; Shukla, Shivakant; Gwalani, Bharat; Banerjee, Rajarshi & Mishra, R. S.
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open access

Demand Controlled Ventilation using COâ‚‚ Sensors in a Wireless Sensor Network

Description: This report discusses research on demand controlled ventilation using COâ‚‚ sensors in a wireless sensor network. The focus of this research project was to investigate Indoor Air Quality (IAQ) monitoring technologies, government regulations and policies, and best practices to improve IAQ. This research is part of Research Experiences for Teachers (RET) in Sensor Education, a National Science Foundation (NSF) funded grant project.
Date: 2013
Creator: Parsons, David; Jordan, Georgette; Li, Xinrong; Thompson, Ruthanne & Abraham, Sherin
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Demand Controlled Ventilation using CO2 Sensors in a Wireless Sensor Network [Poster]

Description: Poster presented as part of the 2013 Research Experiences for Teachers (RET) in Sensor Education, a National Science Foundation (NSF) funded grant project. This poster discusses research on demand controlled ventilation using COâ‚‚ sensors in a wireless sensor network.
Date: 2013
Creator: Parsons, David; Jordan, Georgette; Li, Xinrong; Thompson, Ruthanne & Abraham, Sherin
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open access

A Dense Stereovision System for 3D Body Imaging

Description: Article presents a 3D body imaging system built upon stereovision technology which utilizes paired, high-resolution single-lens reflex (SLR) cameras to image the front and back body surfaces of a person, and robust and efficient stereo matching algorithms to reconstruct the 3D surface of the body with high-density data clouds.
Date: November 26, 2019
Creator: Yao, Ming & Xu, Bugao
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open access

Design approaches for printability-performance synergy in Al alloys for laser-powder bed additive manufacturing

Description: This article highlights that design of Al alloys for laser-powder bed fusion (L-PBF) can lead to fundamental change in the microstructure evolution, proposed alloy design strategies lead to synergy between and printability and performance, hierarchical and heterogeneous microstructures have potential to overcome the strength-ductility tradeoff, and alloy design incorporating the specific attributes of an AM technology is crucial to maximizing its potential.
Date: March 10, 2021
Creator: Mishra, Rajiv & Thapliyal, Saket
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open access

Design of high SERS sensitive substrates based on branched Ti nanorods

Description: Article reports a rational design of branched titanium (Ti) nanorods formed by glancing angle physical vapor deposition and their applications as substrates for surface-enhanced Raman scattering (SERS). The authors investigation provides a mechanism to fabricate sensitive SERS sensors of Ti nanorods that are known to be thermally and chemically stable and compatible with silicon-based electronics.
Date: July 8, 2022
Creator: Abayomi M. Yussuf, Nosirudeen; Li, Jianlin; Jung, Yung Joon & Huang, Hanchen
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open access

Detecting Negation Cues and Scopes in Spanish

Description: Article addresses the processing of negation in Spanish by presenting a machine learning system that processes negation in Spanish and providing a qualitative error analysis aimed at understanding the limitations of the system and showing which negation cues and scopes are straightforward to predict automatically, and which ones are challenging.
Date: May 2020
Creator: Blanco, Eduardo; Jiménez-Zafra, Salud María; Morante, Roser; Martín-Valdivia, María Teresa & Ureña-López, L. Alfonso
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open access

Detection of DDoS Attack in Software-Defined Networking Environment and Its Protocol-wise Analysis using Machine Learning

Description: Article describes how distributed-denial-of-service (DDoS) attacks can cause a great menace to numerous organizations and their stakeholders. The authors assert that the objective of this research work is to take into account a DDoS afflicted SDN specific dataset and detect the malicious traffic by using various machine learning algorithms namely., K-Nearest Neighbours, Logistic Regression, Multilayer Perceptron, Iterative Dichotomiser 3, and Stochastic Gradient Descent.
Date: January 10, 2022
Creator: Prasad, Ashwani; Prasad, Sanjana; Arockiasamy, Karmel; P, Karthika & Yuan, Xiaohui
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open access

Detection of Parkinson's Disease Through Automated Pupil Tracking of the Post-illumination Pupillary Response

Description: This article describes a system for pupil size estimation with a user interface to allow rapid adjustment of parameters and extraction of pupil parameters of interest in order to identify Parkinson's disease (PD) as early as possible.
Date: March 25, 2021
Creator: Tabashum, Thasina; Zaffer, Adnaan; Yousefzai, Raman; Colletta, Kalea; Jost, Mary Beth; Park, Youngsook et al.
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open access

Detergent-Based Decellularization for Anisotropic Cardiac-Specific Extracellular Matrix Scaffold Generation

Description: Article describes how cell-derived extracellular matrix has become increasingly popular in tissue engineering applications due to its ability to provide tailored signals for desirable cellular responses. The objective of this study was to assess the efficacy of two detergent-based decellularization methods: a combination of ethylenediaminetetraacetic acid and sodium dodecyl sulfate and a combination of sodium deoxycholate and deoxyribonuclease.
Date: November 17, 2023
Creator: Chen, Te-An; Sharma, Dhavan; Jia, Wenkai; Ha, Donggi; Man, Kun; Zhang, Jianhua et al.
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open access

Development and application of a novel precession electron diffraction technique to quantify and map deformation structures in highly deformed materials—as applied to ultrafine-grained titanium

Description: Article describes precession electron diffraction (PED), which makes possible the very accurate and automated quantitative characterization of technically interesting materials that historically have been difficult to analyze due to their dimensions and/or degree of deformation, including specifically ultrafine-grained metallic structures with high dislocation densities.
Date: August 13, 2014
Creator: Ghamarian, Iman; Liu, Yue; Samimi, Peyman & Collins, Peter
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