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Chitosan-polyvinyl alcohol (PVA) based composite biofilm: The effect of solvent and nanofiller

AIP Conference Proceedings 2024年第1期3073卷

作者： Bintang Junita Siom Jayanudin Mekro Permana Pinem Endarto Yudo Wardhono Master’s Program in Chemical Engineering Postgraduate School Universitas Sultan Ageng Tirtayasa Jl. Jenderal Sudirman KM. 3 Cilegon 42435 Indonesia Chemical Engineering Department Universitas Sultan Ageng Tirtayasa Jl. Jenderal Sudirman KM. 3 Cilegon 42435 Indonesia Mechanical Engineering Department Universitas Sultan Ageng Tirtayasa Jl. Jenderal Sudirman KM. 3 Cilegon 42435 Indonesia

Environmental issues are the most critical and urgent factor for the increasing use of biopolymers in broader applications. Research on chitosan as a bioplastic material opens vast opportunities to improve its weak mechanical properties. These include blending with biopolymer/synthetic polymers as a matrix or incorporating with nanofillers. The use of organic solvents in dissolving chitosan is also interesting for further research. In this study, we synthesized a chitosan/PVA-based biofilm composite in five different ratios (100/0, 80/20, 60/40, 40/60, 0/100) in acetic acid and citric acid with the addition of 10% weight glycerol to get the optimum composition of mechanical properties. This optimum film would be conducted with SiO2 nanoparticles (NPs) and Cellulose Nano Crystals (CNCs) to evaluate the reinforcement effects. Various properties, including surface morphology, functional, mechanical properties, and thermal behavior, were characterized. The experimental result showed that the tensile strength of the composite film in acetic acid was higher than in citric acid. With the addition of 2.5% w/w of SiO2 NPs, the tensile strength of the composite film got its maximum value, 21.01 MPa, and the maximum of 25.77 MPa with 10% w/w of CNCs, which was 115,7% higher than with of the pure chitosan/PVA film in the ratio of 80/20 which was the optimum. The effect of adding CNC and SiO2 NPS has the opposite effect. The addition of filler CNCs will improve mechanical properties, while SiO2 NPs tend to decrease mechanical properties. All film characterizations demonstrated that the physicochemical interaction between CNCs and chitosan/PVA molecules improved their mechanical and thermal properties.

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PointAtrousGraph: Deep Hierarchical Encoder-Decoder with Point Atrous Convolution for Unorganized 3D Points

PointAtrousGraph: Deep Hierarchical Encoder-Decoder with Poi...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Liang Pan Chee-Meng Chew Gim Hee Lee Advanced Robotics Centre National University of Singapore Department of Mechanical Engineering National University of Singapore Computer Vision and Robotic Perception (CVRP) Lab National University of Singapore

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

Motivated by the success of encoding multi-scale contextual information for image analysis, we propose our PointAtrousGraph (PAG) - a deep permutation-invariant hierarchical encoder-decoder for efficiently exploiting multi-scale edge features in point clouds. Our PAG is constructed by several novel modules, such as Point Atrous Convolution (PAC), Edgepreserved Pooling (EP) and Edge-preserved Unpooling (EU). Similar with atrous convolution, our PAC can effectively enlarge receptive fields of filters and thus densely learn multi-scale point features. Following the idea of non-overlapping maxpooling operations, we propose our EP to preserve critical edge features during subsampling. Correspondingly, our EU modules gradually recover spatial information for edge features. In addition, we introduce chained skip subsampling/upsampling modules that directly propagate edge features to the final stage. Particularly, our proposed auxiliary loss functions can further improve our performance. Experimental results show that our PAG outperform previous state-of-the-art methods on various 3D semantic perception applications.

关键词： Three-dimensional displays Picture archiving and communication systems Convolution Semantics Image edge detection Task analysis Decoding

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Robust and Efficient Estimation of Absolute Camera Pose for Monocular Visual Odometry

Robust and Efficient Estimation of Absolute Camera Pose for ...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Haoang Li Wen Chen Ji Zhao Jean-Charles Bazin Lei Luo Zhe Liu Yun-Hui Liu T Stone Robotics Institute and Department of Mechanical and Automation Engineering The Chinese University of Hong Kong China TuSimple China KAIST South Korea Wuhan University China

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

Given a set of 3D-to-2D point correspondences corrupted by outliers, we aim to robustly estimate the absolute camera pose. Existing methods robust to outliers either fail to guarantee high robustness and efficiency simultaneously, or require an appropriate initial pose and thus lack generality. In contrast, we propose a novel approach based on the robust "L 2 -minimizing estimate" (L 2 E) loss. We first define a novel cost function by integrating the projection constraint into the L 2 E loss. Then to efficiently obtain the global minimum of this function, we propose a hybrid strategy of a local optimizer and branch-and-bound. For branch-and-bound, we derive effective function bounds. Our approach can handle high outlier ratios, leading to high robustness. It can run reliably regardless of whether the initial pose is appropriate, providing high generality. Moreover, given a decent initial pose, it is suitable for real-time applications. Experiments on synthetic and real-world datasets showed that our approach outperforms state-of-the-art methods in terms of robustness and/or efficiency.

关键词： Robustness Pose estimation Cameras Cost function Three-dimensional displays

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Analytical and numerical modeling of a clamped-clamped micro beam under electric actuation 4

Analytical and numerical modeling of a clamped-clamped micro...

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2018 4th International Conference on Smart Material Research, ICSMR 2018

作者： Mustafa, Aalim M Mahgoub, Ahmed K Mechanical Engineering Department Prince Mohammad Bin Fahd University Dhahran Saudi Arabia Engineering Technology Program PSEP King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia

This paper studies the deflection of a clamped-clamped micro beam actuator subjected to an electric voltage. Two approaches were applied to model the micro beam under study: the first one is analytical and the second is numerical. A solution to the analytical model was developed to investigate the mechanical behaviour of the micro beam-based MEMS device under electric actuation and simulations was done using Wolfram Mathematica® software. On the other hand, a finite element model (FEM) simulation was performed using COMSOL Multiphysics® for data validation for the micro beam model, and the results showed very good agreement. The effect of changing beam length, thickness and height from the ground on both the maximum beam displacement and pull-in voltage was also analyzed. © Published under licence by IOP Publishing Ltd.

关键词： Multiphysics

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Gas sensor array to classify the chicken meat with E. coli contaminant by using random forest and support vector machine

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Biosensors and Bioelectronics: X 2021年 9卷

作者： Astuti, Suryani Dyah Tamimi, Mohammad H. Pradhana, Anak A.S. Alamsyah, Kartika A. Purnobasuki, Hery Khasanah, Miratul Susilo, Yunus Triyana, Kuwat Kashif, Muhammad Syahrom, Ardiyansyah Department of Physics Faculty of Science and Technology Universitas Airlangga Surabaya60115 Indonesia Biomedical Engineering Magister Program Faculty of Science and Technology Universitas Airlangga Surabaya60115 Indonesia Department of Biology Faculty of Science and Technology Universitas Airlangga Surabaya60115 Indonesia Department of Chemistry Faculty of Science and Technology Universitas Airlangga Surabaya60115 Indonesia Faculty of Engineering-Universitas Dr Soetomo Indonesia Surabaya60118 Indonesia Department of Physics Faculty of Matematic and Natural Science Universitas Gadjah Mada Yogyakarta Indonesia Department of Applied Mechanics and Design Faculty of Mechanical Engineering Universiti Teknologi Malaysia Johor Bahru81310 Malaysia

Microbes such as Escherichia coli (E. coli) can easily contaminate raw chicken meat in clean conditions, causing decay and unpleasant scents. This study aims to characterize gas patterns by comparing fresh chicken meat and E. coli bacteria contaminated chicken meat based on shelf life using a Gas Sensor Array (GSA) system (MQ2, MQ3, MQ7, MQ8, MQ135, and MQ136) on electronic nose. The findings revealed GSA capability to detect a variety of typical gas patterns formed by the samples. This gas detection property is indicated by the appearance of the variance in the sensors output voltage pattern for each sample variation. The data for fresh and contaminated samples were classified by the random forest (RF) classifier with 99.25% and 98.42% precision, respectively. Furthermore, the support vector machine (SVM) classifier correctly identified the fresh and contaminated samples with 98.61% and 86.66% accuracy, respectively. This finding offers insight for GSA capability in classifying chicken meat contaminated with E. coli using an RF and SVM. © 2021 The Author(s)

关键词： Support vector machines

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High pressure synthesis and characterization of the pyrochlore Dy2Pt2O7:A new spin ice material

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Chinese Physics B 2020年第4期29卷 116-120页

作者： Qi Cui Yun-Qi Cai Xiang Li Zhi-Ling Dun Pei-Jie Sun Jian-Shi Zhou Hai-Dong Zhou Jin-Guang Cheng Beijing National Laboratory for Condensed Matter Physics and Institute of Physics Chinese Academy of SciencesBeijing 100190China School of Physical Sciences University of Chinese Academy of SciencesBeijing 100190China Materials Science and Engineering Program Mechanical EngineeringUniversity of Texas at AustinAustinTexas 78712USA Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement of Ministry of Education School of PhysicsBeijing Institute of TechnologyBeijing 100081China Department of Physics and Astronomy University of TennesseeKnoxvilleTN 37996USA School of Physics Georgia Institute of TechnologyAtlantaGA 30332USA Songshan Lake Materials Laboratory Dongguan 523808China

The cubic pyrochlore Dy2Pt2O7 was synthesized under 4 GPa and 1000℃ and its magnetic and thermodynamic properties were characterized by DC and AC magnetic susceptibility and specific heat down to 0.1 *** found that Dy2Pt2O7 does not form long-range magnetic order,but displays characteristics of canonical spin ice such as Dy2Pt2O7,including(1)a large effective moment 9.64μB close to the theoretical value and a small positive Curie-Weiss temperatureθCW=+0.77 K signaling a dominant ferromagnetic interaction among the Ising spins;(2)a saturation moment ~4.5μB being half of the total moment due to the local<111>Ising anisotropy;(3)thermally activated spin relaxation behaviors in the low(~1 K)and high(~20 K)temperature regions with different energy barriers and characteristic relaxation time;and most importantly,(4)the presence of a residual entropy close to Pauling’s estimation for water ice.

关键词： Dy2Pt2O7 pyrochlore oxide spin ice high-pressure synthesis

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Signature of multilayer graphene strain-controlled domain walls in quantum Hall effect

arXiv

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arXiv 2020年

作者： Anderson, Paul Huang, Yifan Fan, Yuanjun Qubbaj, Sara Coh, Sinisa Zhou, Qin Ojeda-Aristizabal, Claudia Department of Physics and Astronomy California State University Long Beach Long BeachCA90840 United States Department of Mechanical and Materials Engineering University of Nebraska LincolnNE68588-0526 United States Department of Mechanical Engineering and Materials Science and Engineering Program University of California Riverside RiversideCA92521 United States

Domain walls, topological defects that define the frontier between regions of different stacking in multilayer graphene, have proved to host exciting physics. The ability of tuning these topological defects in-situ in an electronic transport experiment brings a wealth of possibilities in terms of fundamental understanding of domain walls as well as for electronic applications. Here, we demonstrate through a MEMS (micro-electromechanical system) actuator and magnetoresistance measurements the effect of domain walls in multilayer graphene quantum Hall effect. Reversible and controlled uniaxial strain triggers these topological defects, manifested as new quantum Hall effect plateaus as well as a discrete and reversible modulation of the current across the device. Our findings are supported by theoretical calculations and constitute the first indication of the in-situ tuning of topological defects in multilayer graphene probed through electronic transport, opening the way to the use of reversible topological defects in electronic applications. Copyright © 2020, The Authors. All rights reserved.

关键词： Graphene

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A simple approach for curcumin extraction from turmeric roots

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AIP Conference Proceedings 2022年第1期2537卷 040016页

作者： Siti Fauziyah Rahman Adella Josephin Ridha Alviny Syakirah Grace Priscilla Nadia Wulandari Nurul Intan Yudan Whulanza Biomedical Engineering Study Program Department of Electrical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia Research Center for Biomedical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia Department of Mechanical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia

Turmeric, particularly its most active ingredient, curcumin, has a long list of scientifically documented health advantages, including the ability to boost heart health and protect against a variety of diseases. Curcumin is one of the most important active components in turmeric, with a wide range of bioactivity and medicinal uses. Preparing samples from biological components is a time-consuming and difficult operation. This study aims to understand the process of extracting curcumin from turmeric and to analyze the appropriate solvent for curcumin extraction. The method used is Soxhlet extraction with acetone and ethanol as solvents. The analysis of curcumin content was carried out using a UV-Vis spectrophotometer. The results showed that the curcumin extracted with acetone solvent had a higher concentration than the extraction with ethanol. Therefore, extracting curcumin from turmeric using the Soxhlet method, acetone is a superior solvent than ethanol.

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Recent advancements in the plant and microbial assisted green synthesis of nanomaterials

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Materials Today: Proceedings 2023年

作者： Soumya Mishra Satyanjib Sahoo Prasanta Kumar Sahoo Naresh Kumar Sahoo Department of Chemistry Environmental Science Program (ITER) Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar 751030 Odisha India Department of Mechanical Engineering (ITER) Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar 751030 Odisha India

Green synthesis is a process of generating nanomaterials that is secure, cost-effective, clean, and beneficial to the environment. Natural extracts derived from plant tissues, for example, roots, leaves, barks, seeds, and fruits, work as capping, functionalizing, and reducing agents. Microbial nanotechnology is an eco-friendly method for synthesis of nanoparticles which has a broad application in environment, agriculture, food and pharmaceutical industries. In this review, various plants and microbial-derived nanomaterials have been discussed elaborately. Generally, in the green synthesis of nanomaterials, various microorganisms (e.g., bacterium, fungus, yeast, virus, and their derived compounds) are used. This study focuses on the most recent advances in plant and microbial-based green synthesis with special focuses on the mechanism of NMs synthesis. This study provides an overview of numerous recent publications on synthesizing advanced nanomaterials utilizing a green synthesis technique with special emphasis on their application in pharmaceutical, agricultural, sensor for energy and environment. Combining the remarkable physicochemical qualities of nanoparticles with the environmental and sustainable characteristics of green synthesis methods has shown to be extremely helpful.

关键词： Green synthesis Nanomaterials Microorganisms Plant extract Reducing agent Application

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Sers Spectroscopy with Machine Learning to Analyze Human Plasma Derived Sevs for Coronary Artery Disease Diagnosis and Prognosis

SSRN

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SSRN 2022年

作者： Huang, Xi Liu, Bo Guo, Shenghan Guo, Weihong Liao, Ke Hu, Guoku Shi, Wen Kuss, Mitchell Duryee, Michael J. Anderson, Daniel R. Lu, Yongfeng Duan, Bin Department of Electrical and Computer Engineering University of Nebraska Lincoln LincolnNE United States Mary & Dick Holland Regenerative Medicine Program University of Nebraska Medical Center OmahaNE United States Division of Cardiovascular Medicine Department of Internal Medicine University of Nebraska Medical Center OmahaNE United States Department of Industrial and Systems Engineering Rutgers The State University of New Jersey PiscatawayNJ United States Department of Pharmacology and Experimental Neuroscience University of Nebraska Medical Center OmahaNE United States Division of Rheumatology Department of Internal Medicine University of Nebraska Medical Center OmahaNE United States Department of Surgery College of Medicine University of Nebraska Medical Center OmahaNE United States Department of Mechanical and Materials Engineering University of Nebraska-Lincoln LincolnNE United States School of Manufacturing Systems and Networks Arizona State University MesaAZ United States

Coronary artery disease (CAD) is one of the major cardiovascular diseases and represents the leading causes of global mortality. Developing new diagnostic and therapeutic approaches for CAD treatment are critically needed, especially for an early accurate CAD detection and further timely intervention. In this study, we successfully isolated human plasma small extracellular vesicles (sEVs) from four stages of CAD patients, i.e., healthy control, stable plaque, non-ST-elevation myocardial infarction, and ST-elevation myocardial infarction. Surface-enhanced Raman scattering (SERS) measurement in conjunction with five machine learning approaches, including Quadratic Discriminant Analysis, Support Vector Machine (SVM), K-Nearest Neighbor, Artificial Neural network, were then applied for the classification and prediction of the sEV samples. Among these five approaches, the overall accuracy of SVM shows the best predication results on both early CAD detection (86.4%) and overall prediction (92.3%). SVM also possesses the highest sensitivity (97.69%) and specificity (95.7%). Thus, our study demonstrates a promising strategy for noninvasive, safe, and high accurate diagnosis for CAD early detection. © 2022, The Authors. All rights reserved.

关键词： Diseases

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