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38th International Cosmic Ray Conference, ICRC 2023

作者： Hashizume, Masaki Suda, Yusuke Fukazawa, Yasushi Tsuru, Takeshi Go Takeda, Ayaki Physics Program Graduate School of Advanced Science and Engineering Hiroshima University 1-3-1 Kagamiyama Higashi-Hiroshima Hiroshima Japan Kyoto University Graduate School of Science Yoshida-Honmachi Sakyo-ku Kyoto Japan University of Miyazaki Department of Technology 1-1 Gakuen Kibanadai-nishi Miyazaki Japan

Cosmic MeV gamma-ray observations are important for elucidating physics in high-energy objects such as gamma-ray bursts and active galactic nuclear jet blazars, for detecting nuclear gamma-rays in supernova explosions, and for advancing multi-messenger astronomy. However, there has been no progress since the COMPTEL detector on board the CGRO satellites in the 1990s, and a satellite for MeV gamma-ray observations is essential. Compton scattering is the dominant interaction between MeV gamma-rays and matter. The minimal way to reconstruct the arrival direction of an incident gamma-ray is to utilize both the deposit energy and hit position measured in both the scatterer and absorber, giving an event circle. The circle can be reduced to an arc if the initial direction of the Compton scattered electron is measured. Thus such an electron-tracking Compton camera is expected to improve the source sensitivity by reducing background events. Therefore, our goal is to enable more accurate Compton imaging by using an event-driven SOI pixel detector "XRPIX" as a scatterer in an electron-track Compton camera. The pixel size of XRPIX is as small as 36 um square, so it is expected to capture electron trajectories for scattering of gamma-rays of several hundred keV. In this contribution, we report on the evaluation of the depletion layer thickness of XRPIX8.5, which can be fully depleted at room temperature, the sensor response when irradiated with gamma-rays such as 662 keV of Cs-137 and 511 keV of Na-22, and a method for estimating the direction of scattered electrons. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmology

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Chemical Constituents and Bioactive Principles from the Mexican Truffle and Fermented Products of the Derived Fungus Ustilago maydis MZ496986

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Journal of Agricultural and Food Chemistry 2023年第2期71卷 1122-1131页

作者： Wu, Ho-Cheng His, Hsiao-Yang Hsiao, George Yen, Chia-Hung Leu, Jyh-Yih Wu, Chin-Chung Chang, Szu-Hsing Huang, Shu-Jung Lee, Tzong-Huei Graduate Institute of Pharmacognosy College of Pharmacy Taipei Medical University Taipei110 Taiwan Ph.D. Program in Clinical Drug Development of Herbal Medicine College of Pharmacy Taipei Medical University Taipei110 Taiwan Institute of Fisheries Science National Taiwan University Taipei106 Taiwan Graduate Institute of Medical Sciences and Department of Pharmacology School of Medicine College of Medicine Taipei110 Taiwan Graduate Institute of Natural Products College of Pharmacy Kaohsiung Medical University Kaohsiung807 Taiwan Department of Life Science College of Science and Engineering Fu Jen Catholic University New Taipei City242 Taiwan Graduate Institute of Applied Science and Engineering College of Science and Engineering Fu-jen Catholic University New Taipei242 Taiwan

To look in-depth into the traditional Mexican truffle, this study investigated the phytochemical and pharmacological properties of field-collected corn galls and the fermentate of its pathogen Ustilago maydis MZ496986. Here, we established the chemical profiles of both materials via the gradient HPLC-UV method and successfully identified six previously unreported chemical entities, ustilagols A-F (1-6), and 17 known components. Compounds 3, 5, and 9 exhibited potent nitric oxide production inhibitory activities in murine brain microglial BV-2 cells (IC50 = 6.7 ± 0.5, 5.8 ± 0.9, and 3.9 ± 0.1 μM) without cytotoxic effects. DIMBOA (9) also attenuates lipopolysaccharide (LPS)-stimulated NF-κB activation in RAW 264.7 macrophages (IC50 = 58.1 ± 7.2 μM). Ustilagol G (7) showed potent antiplatelet aggregation in U46619-stimulated human platelets (IC50 = 16.5 ± 5.3 μM). These findings highlighted the potential of corn galls and U. maydis MZ496986 fermentate as functional foods for improving inflammation-related discomforts and vascular obstruction. © 2023 American Chemical Society.

关键词： Nitric oxide

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Machine learning of organic solvents reveals an extraordinary axis in Hansen space as indicator of spherical precipitation of polymers

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Aggregate 2023年第5期4卷 207-213页

作者： Yuta Ihara Hiroshi Yamagishi Masanobu Naito Yohei Yamamoto Department of Materials Science Faculty of Pure and Applied Sciencesand Tsukuba Research Center for Energy Materials Science(TREMS)University of TsukubaTsukubaJapan Research and Services Division of Materials Data and Integrated System(MaDIS) National Institute for Materials Science(NIMS)TsukubaJapan Program in Materials Science and Engineering Graduate School of Pure and Applied SciencesUniversity of TsukubaTsukubaJapan

Machine learning is an emerging tool in the field of materials chemistry for uncovering a principle from large ***,we focus on the spherical precipitation behavior of polymers and computationally extract a hidden trend that is orthogonal to the availability bias in the chemical *** constructing a dataset,four polymers were precipitated from 416 solvent/nonsolvent combinations,and the morphology of the resulting precipitates were *** dataset was subjected to computational investigations consisting of principal component analysis and machine learning based on random forest model and support vector ***,we eliminated the effect of the availability bias and found a linear combination of Hansen parameters to be the most suitable variable for predicting precipitation *** predicted appropriate solvents are those with low hydrogen bonding capability,low polarity,and small molecular ***,we found that the capability for spherical precipitation is orthogonal to the availability bias and forms an extraordinary axis in Hansen space,which is the origin of the conventional difficulty in identifying the *** extraordinary axis points toward a void region,indicating the potential value of synthesizing novel solvents located therein.

关键词： chemical space computational chemistry machine learning polymers precipitation

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Nanoconfinement effect of nanoporous carbon electrodes for ionic liquid-based aluminum metal anode

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Journal of Energy Chemistry 2022年第11期31卷 121-127,I0005页

作者： Juhee Yoon Seongbak Moon Son Ha Hyung-Kyu Lim Hyoung-Joon Jin Young Soo Yun Program in Environmental and Polymer Engineering Inha UniversityIncheon 22212South Korea Department of Polymer Science and Engineering Inha UniversityIncheon 22212South Korea KU-KIST Graduate School of Converging Science and Technology Korea UniversitySeoul 02841South Korea Division of Chemical Engineering and Bioengineering Kangwon National UniversityGangwon-do 24341South Korea Department of Integrative Energy Engineering Korea UniversitySeoul 02841South Korea

Rechargeable aluminum batteries(RABs),which use earth-abundant and high-volumetric-capacity metal anodes(8040 m Ah cm-3),have great potential as next-generation power sources because they use cheaper resources to deliver higher energies,compared to current lithium ion ***,the mechanism of charge delivery in the newly developed,ionic liquid-based electrolytic system for RABs differs from that in conventional organic ***,targeted research efforts are required to address the large overpotentials and cycling decay encountered in the ionic liquid-based electrolytic *** this study,a nanoporous carbon(NPC)electrode with well-developed nanopores is used to develop a high-performance aluminum *** negatively charged nanopores can provide quenched dynamics of electrolyte molecules in the aluminum deposition process,resulting in an increased collision *** fast chemical equilibrium of anionic species induced by the facilitated anionic collisions leads to more favorable reduction reactions that form aluminum *** nanoconfinement effect causes separated nucleation and growth of aluminum nanoparticles in the multiple confined nanopores,leading to higher coulombic efficiencies and more stable cycling performance compared with macroporous carbon black and 2D stainless steel electrodes.

关键词： Nanoconfinement effect Nanoporous carbon Ionic liquid electrolyte Metal anode Aluminum batteries Multivalent batteries

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Identify Non-mutational p53 Functional Deficiency in Human Cancers

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Genomics, Proteomics & Bioinformatics 2024年第5期22卷 85-98页

作者： Qianpeng Li Yang Zhang Sicheng Luo Zhang Zhang Ann L.Oberg David E.Kozono Hua Lu Jann N.Sarkaria Lina Ma Liguo Wang National Genomics Data Center China National Center for BioinformationBeijing 100101China Beijing Institute of Genomics Chinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China Division of Computational Biology Mayo Clinic College of Medicine and ScienceRochesterMN 55905USA Department of Radiation Oncology Dana-Farber Cancer Institute and Brigham and Women's HospitalBostonMA 02215USA Department of Biochemistry&Molecular Biology and Tulane Cancer Center Tulane University School of MedicineNew OrleansLA 70112USA Department of Radiation Oncology Mayo Clinic College of Medicine and ScienceRochesterMN 55905USA Department of Biochemistry and Molecular Biology Mayo Clinic College of Medicine and ScienceRochesterMN 55905USA Bioinformatics and Computational Biology Graduate Program University of Minnesota RochesterRochesterMN 55904USA

An accurate assessment of p53's functional statuses is critical for cancer genomic ***,there is a significant challenge in identifying tumors with non-mutational p53 inactivation which is not detectable through DNA *** undetected cases are often misclassified as p53-normal,leading to inaccurate prognosis and downstream association *** address this issue,we built the support vector machine(SVM)models to systematically reassess p53's functional statuses in TP53 wild-type(TP53^(WT))tumors from multiple The Cancer Genome Atlas(TCGA)***-validation demonstrated the good performance of the SVM models with a mean area under the receiver operating characteristic curve(AUROC)of 0.9822,precision of 0.9747,and recall of *** study revealed that a significant proportion(87%-99%)of TP53^(WT) tumors actually had compromised p53 *** analyses uncovered that these genetically intact but functionally impaired(termed as predictively reduced function of p53 or TP53^(WT)-pRF)tumors exhibited genomic and pathophysiologic features akin to TP53-mutant tumors:heightened genomic instability and elevated levels of ***,patients with TP53^(WT)-pRF tumors experienced significantly shortened overall survival or progression-free survival compared to those with predictively normal function of p53(TP53^(WT)-pN)tumors,and these patients also displayed increased sensitivity to platinum-based chemotherapy and radiation therapy.

关键词： Cancer Composite expression DNA mutation Machine learning p53 deficiency

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Machine Learning for Unmanned Aerial Vehicles Navigation: An Overview

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SN Computer science 2024年第2期5卷 256页

作者： Fagundes-Junior, Leonardo A. de Carvalho, Kevin B. Ferreira, Ricardo S. Brandão, Alexandre S. Núcleo de Especialização em Robótica Department of Electrical Engineering Graduate Program in Computer Science Federal University of Viçosa-UFV Av. Petter Henry Rolfs MG Viçosa 36570-900 Brazil

Unmanned aerial vehicles (UAVs) are a valuable source of data for a wide range of real-time applications, due to their functionality, availability, adaptability, and maneuverability. Working as mobile sensors, they can provide a cost-effective solution for extremely complex tasks, such as inspection, air-to-ground communications, search and rescue, surveillance, among others. Nevertheless, the robots needs to navigate in quite distinct environments and in different dynamism levels, usually facing unpredicted situations, very often using limited sensing and computing capabilities. A large number of solutions to this problem has been featured by the scientific community in the last years, some of them based on machine-learning (ML) methods. Due to its great capability to deal with big data and complexity, as well as its speedy and high-accuracy processing, the ML framework has been used to improve existing technologies and control techniques. In this context, its adoption in several UAV navigation strategies is expected to provide solutions for various problems where UAVs are used in real-time applications. Thus, in order to contextualize the most recent advances, this work provides a detailed survey of relevant researches in which ML techniques have been used in UAV navigation to improve some functional aspects, such as energy-efficiency, communication, execution time, resource management, obstacle avoidance, and path planning. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2024.

关键词： Autonomous navigation Path planning UAV-based solutions Visual-based navigation

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Tungsten Nitride (W5N6): An Ultraresilient 2D Semimetal

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Nano Letters 2024年第1期24卷 67-73页

作者： Chin, Hao-Ting Wang, Deng-Chi Gulo, Desman Perdamaian Yao, Yu-Chi Yeh, Hao-Chen Muthu, Jeyavelan Chen, Ding-Rui Kao, Tzu-Chun Kalbáč, Martin Lin, Ping-Hui Cheng, Cheng-Maw Hofmann, Mario Liang, Chi-Te Liu, Hsiang-Lin Chuang, Feng-Chuan Hsieh, Ya-Ping Molecular Science and Technology Program Taiwan International Graduate Program Academia Sinica Taipei10617 Taiwan International Graduate Program of Molecular Science and Technology National Taiwan University Taipei10617 Taiwan Institute of Atomic and Molecular Sciences Academia Sinica Taipei10617 Taiwan Department of Physics National Sun Yat-Sen University Kaohsiung80424 Taiwan Department of Physics National Taiwan Normal University Taipei11677 Taiwan Department of Physics National Taiwan University Taipei10617 Taiwan Institute of Physics Academia Sinica Taipei115201 Taiwan International Graduate Program of Nano Science and Technology National Taiwan University Taipei10617 Taiwan Graduate Institute of Applied Physics National Taiwan University Taipei10617 Taiwan J. Heyrovský Institute of Physical Chemistry Czech Academy of Sciences Dolejškova 2155/3 Prague182 23 Czech Republic Hsinchu300092 Taiwan Physics Division National Center for Theoretical Sciences Taipei10617 Taiwan Center for Theoretical and Computational Physics National Sun Yat-sen University Kaohsiung80424 Taiwan

Two-dimensional transition metal nitrides offer intriguing possibilities for achieving novel electronic and mechanical functionality owing to their distinctive and tunable bonding characteristics compared to other 2D materials. We demonstrate here the enabling effects of strong bonding on the morphology and functionality of 2D tungsten nitrides. The employed bottom-up synthesis experienced a unique substrate stabilization effect beyond van-der-Waals epitaxy that favored W5N6 over lower metal nitrides. Comprehensive structural and electronic characterization reveals that monolayer W5N6 can be synthesized at large scale and shows semimetallic behavior with an intriguing indirect band structure. Moreover, the material exhibits exceptional resilience against mechanical damage and chemical reactions. Leveraging these electronic properties and robustness, we demonstrate the application of W5N6 as atomic-scale dry etch stops that allow the integration of high-performance 2D materials contacts. These findings highlight the potential of 2D transition metal nitrides for realizing advanced electronic devices and functional interfaces. © 2023 American Chemical Society

关键词： Tungsten compounds

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An Exploratory computational Approach for Elucidating a Nonstructural Protein Interaction in Dengue Virus 2 9th

An Exploratory Computational Approach for Elucidating a Nons...

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9th International Conference on Computer science and computational Intelligence, ICCSCI 2024

作者： Hidayat, Alam Ahmad Nirwantono, Rudi Pardamean, Bens Mathematics Department School of Computer Science Bina Nusantara University 11480 Indonesia Biotechnology Department Faculty of Engineering Bina Nusantara University 11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

As the dengue infection still impacts hundreds of millions of people globally, unprecedented efforts in dengue drug development have been more progressive in recent decades. computational methods provide a fast, sustainable, and efficient screening of active compounds and newly created drug molecules, including those specifically targeting nonstructural proteins (NS) of dengue viruses. In this work, protein modeling for the NS proteins of DENV-2/16681 strain was performed using a template-based homology modeling for the NS3 protein and an Artificial Intelligence (AI)-based prediction via AlphaFold for the NS4B protein. Moreover, the protein-protein interaction between the two structures was predicted using the HADDOCK server, which employs information about active and passive residues of the interaction interface to guide the docking process. After the modeling and its respective refinement process, the predicted structures of NS3 and NS4B improved their steric clashing scoring from MolProbity assessment. The refined models were then docked, and the resulting docking pose was analyzed to extract the interacting residues based on the polar contacts within the interface of the two proteins. Our result presents a preliminary study to create a dataset related to in silico molecular interactions of the NS3-NS4B interaction of different DENV types. It is helpful for building a computational pipeline for elucidating protein-ligand problems in dengue drug screenings. © 2024 The Authors.

关键词： Molecular docking

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Application of 3D Printing and Design in Healthcare: A Focus on Undergraduate Research to Attract Students to Bioengineering and Related Disciplines 54

Application of 3D Printing and Design in Healthcare: A Focus...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Zelada-Quiroz, Cindy M. Reyes-Santiago, Brian L. Ortiz-Rivera, Eduardo I. University of Puerto Rico at Mayagüez Bio-Engineering Graduate Program Mayagüez Puerto Rico University of Puerto Rico at Mayagüez Department of Computer Science and Engineering Mayagüez Puerto Rico University of Puerto Rico at Mayagüez Department of Electrical and Computer Engineering Mayagüez Puerto Rico

ISBN: (纸本)9798350351507

This research-to-practice paper describes developing and analyzing state-of-the-art smart boots created by combining CAD technology and advanced 3D printing techniques to attract students in bio-engineering and related fields. The primary objective of this innovative immobilization boot is to expedite fracture recovery phases through an ergonomic design to ensure optimal patient comfort during its use. Technological solutions are crucial in aiding the rehabilitation process for fractures caused by falls, heavy lifting, or rotational trauma. However, cost and comfort-related issues persist, underscoring the need for alternative approaches. This research addresses these challenges and delves into the broader implications of fracture treatment, catalyzing future projects and investigations in bioengineering. Additionally, this study serves as an educational tool that sparks the interest of high school and engineering students, promoting multidisciplinary collaboration in innovation. By involving students in specialized courses covering 3D design, human bone anatomy, biology, and materials science, this initiative empowers them to deepen their knowledge and develop new technologies to address bone injury problems. Material analyses include evaluating the type of material depending on the fracture site, such as PLA for printing and cotton and silicone gel for the midsection between the splint and the body. This research aims to advance our understanding of the type of fracture, the methods associated with their treatment, and tissue repair processes during bone callus formation. To summarize, this multidisciplinary approach drives advancements in bio-engineering and related fields, aiming to enhance patient outcomes and inspire students to pursue further research in bio-engineering and related fields. As part of this endeavor, a list of university-level courses based on the experience of the University of Puerto Rico at Mayaguez (UPRM), such as biology, bio-materials, 3D

关键词： Students

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Self-Attenuating Graphene-Based Antennas Utilizing Polyvinylidene Fluoride (PVDF) Substrates

Self-Attenuating Graphene-Based Antennas Utilizing Polyvinyl...

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Microwave and Antenna Symposium (IMAS), International

作者： Josef Frankhouse Evans Addo-Mensah Uche Wejinya Department of Mechanical Engineering University of Arkansas - Fayetteville Materials Science and Engineering Graduate Program University of Arkansas - Fayetteville

ISBN: (数字)9798350356359

ISBN: (纸本)9798350356366

In this study, a Terahertz (THz) band antenna which can regulate its own resonant frequency without the requirement of manual adjustment is simulated. A polyvinylidene fluoride (PVDF) substrate is applied onto a rectangular graphene patch antenna. With a voltage potential applied onto the PVDF, the patch antenna can attenuate its frequency by physically changing the shape of the antenna, and in turn its resonant frequency. These antennas are within a 0.1 THz band between 1.32 THz to 1.22 THz measured from a radial bend of a flat surface to r = 75 μm, fitting into a return loss (S11) above -30 dB. Although the return loss did not show consistency, the resonating frequency shifted at a linear rate relative to the cylindrical bending.

关键词： Microwave antennas Patch antennas Graphene Resonant frequency Prototypes Bandwidth Bending Loss measurement Substrates Terahertz communications

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