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Bioinformatics exploration into potential mechanisms of Calamus draco for colorectal cancer treatment

Procedia Computer science 2024年 245卷 127-136页

作者： Christian Kenneth Rudi Nirwantono Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Biotechnology Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program – Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

As one of the cancer types with the highest incidence rates, colorectal cancer (CRC) would benefit from treatments with fewer side effects and reduced treatment-resistant potential. One of the options is to harness the anti-CRC potential of natural products. Previous studies have shown that Calamus draco exudate, dragon's blood, has anticancer activity in liver cancer and acute myeloid leukemia, but its bioactivity has not been studied in CRC. Here we conduct a bioinformatics study based on network pharmacology to explore the anti-CRC potential and mechanism of C. draco -derived compounds. The bioinformatics pipeline is composed of compound and target collection, biological network evaluation, and enrichment analysis. We found that there are 43 bioactive compounds from C. draco targeting 91 CRC-related targets, of which most compounds target MEN1, PTGS2, and IDH1. Further analyses show that the targets of C. draco are involved in the cellular response to hypoxia. By inhibiting those targets, C. draco bioactive compounds can potentially hinder angiogenesis and increase treatment response efficacy.

关键词： bioinformatics network pharmacology Calamus draco colorectal cancer drug discovery

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Comparative Analysis of SAAS Model and NPC Integration for Enhancing VR Shopping Experiences

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Applied sciences (Switzerland) 2024年第15期14卷 6573页

作者： Doungtap, Surasachai Wang, Jenq-Haur Phanichraksaphong, Varinya International Graduate Program of Electrical Engineering and Computer Science National Taipei University of Technology Taipei10608 Taiwan Department of Computer Science and Information Engineering National Taipei University of Technology Taipei10608 Taiwan

This article examines the incorporation of the Shopping Assistance Automatic Suggestion (SAAS) model into Virtual Reality (VR) environments in order to improve the online shopping experience. The SAAS model employs sophisticated deep learning methods to offer customized product recommendations, which are conveyed by non-player characters (NPCs) via voice-based interactions. Our goal is to develop an interactive shopping experience that replicates real-life interactions by integrating AI-powered recommendations with immersive VR technology. We gather and standardize data from several open commerce databases, such as Amazon Product and Customer Reviews. The SAAS model, in conjunction with GPT-3, BERT, and T5, undergoes training and testing to evaluate its effectiveness across multiple criteria. The results demonstrate that the SAAS model surpasses other models in delivering contextually aware and pertinent recommendations. The integration process outlines the specific steps involved in capturing, processing, and transforming user interactions in virtual reality (VR) into vocal suggestions provided by non-player characters (NPCs). This strategy improves customization and utilizes the immersive features of virtual reality to effectively engage people. The results of our research establish a higher standard for e-commerce, with the goal of enhancing the user experience of online purchasing by making it more instinctive, engaging, and pleasurable. © 2024 by the authors.

关键词： Data mining

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T-Cal: an optimal test for the calibration of predictive models

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2023年第1期24卷 15959-16030页

作者： Donghwan Lee Xinmeng Huang Hamed Hassani Edgar Dobriban Graduate Group in Applied Mathematics and Computational Science University of Pennsylvania Philadelphia PA Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia PA Department of Statistics and Data Science University of Pennsylvania Philadelphia PA

The prediction accuracy of machine learning methods is steadily increasing, but the calibration of their uncertainty predictions poses a significant challenge. Numerous works focus on obtaining well-calibrated predictive models, but less is known about reliably assessing model calibration. This limits our ability to know when algorithms for improving calibration have a real effect, and when their improvements are merely artifacts due to random noise in finite datasets. In this work, we consider detecting mis-calibration of predictive models using a finite validation dataset as a hypothesis testing problem. The null hypothesis is that the predictive model is calibrated, while the alternative hypothesis is that the deviation from calibration is sufficiently *** find that detecting mis-calibration is only possible when the conditional probabilities of the classes are sufficiently smooth functions of the predictions. When the conditional class probabilities are Hölder continuous, we propose T-Cal, a minimax optimal test for calibration based on a debiased plug-in estimator of the ℓ2-Expected Calibration Error (ECE). We further propose adaptive T-Cal, a version that is adaptive to unknown smoothness. We verify our theoretical findings with a broad range of experiments, including with several popular deep neural net architectures and several standard post-hoc calibration methods. T-Cal is a practical general-purpose tool, which--combined with classical tests for discrete-valued predictors--can be used to test the calibration of virtually any probabilistic classification method. T-Cal is available at https://***/dh7401/T-Cal.

关键词： uncertainty quantification calibration nonparametric statistics hypothesis testing minimax optimality

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A Bioinformatics Analysis and Homology 3D Modeling of Dihydroxy-orotate-dehydrogenase of Plasmodium ovale

A Bioinformatics Analysis and Homology 3D Modeling of Dihydr...

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2023 International Conference on Informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Nirwantono, Rudi Assidqi, Khoirunnisa Hidayat, Alam Ahmad Pebrianto Trinugroho, Joko Pardamean, Bens Bina Nusantara University Faculty of Engineering Bioinformatics and Data Science Research Center Biotechnology Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Food Biotechnology Research Center Biotechnology Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Mathematics Departement Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350307306

The infection of Plasmodium vivax is relatively less virulent than the deathliest Plasmodium falciparum. However, it still can lead to a fatal case and often induces recurring malaria due to dormant parasites in the liver. Thus, the research to study the drug to treat Plasmodium vivax is essential, where the enzyme dihydroorotate dehydrogenase (DHODH) has recently become a new drug target. However, the drug-enzyme interaction study has only recently been conducted in Plasmodium falciparum (pfDHODH) due to the lack of the 3D structure of enzyme DHODH from Plasmodium vivax that is crucial for the study. Therefore, this study aimed to perform the modelling study of Plasmodium vivax DHODH (PvDHODH) to create a 3D structure as a basis for drug-protein interaction study in upcoming studies. Sequence pvDHODH (Accession: SCO68359.1) was used in homology modelling using Modeller 10.2 with the crystal structure of DHODH from DHODH (Accession: 7KZY) as a template. Overall, the model generated from the homology modelling was considered a good model, and the 3D structure was close to the native state according to several parameters, including DOPE score, GA341 score, QMEAN4 value, 3D-1D score, ERRAT2 score, and ProSA score. Ramachandran plot also revealed that almost all amino acids were distributed in the desirable and allowed area (99.1%), and only 0.9% were in generously allowed regions. Superimposition of the model with the template also indicated that the model has an almost similar structure and amino acids positioning, including in the binding pocket and active site. Therefore, the model can be used for downstream analysis in drug-protein interaction studies. Nevertheless, some improvements can still be performed to upgrade the quality of the model by deleting unaligned residues on the C-terminal and realigning the residues at the doubting site. © 2023 IEEE.

关键词： Amino acids

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Multi-Lingual ESG Impact Duration Inference 7

Multi-Lingual ESG Impact Duration Inference

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Joint Workshop of the 7th Financial Technology and Natural Language Processing, 5th Knowledge Discovery from Unstructured Data in Financial Services and 4th Economics and Natural Language Processing, FinNLP-KDF-ECONLP 2024

作者： Chen, Chung-Chi Tseng, Yu-Min Kang, Juyeon Lhuissier, Anaïs Seki, Yohei Lee, Hanwool Day, Min-Yuh Tu, Teng-Tsai Chen, Hsin-Hsi AIST Japan Data Science Degree Program National Taiwan University Academia Sinica Taiwan 3DS Outscale France University of Tsukuba Japan NCSOFT Korea Republic of Graduate Institute of Information Management National Taipei University Taiwan Graduate Institute of International Business National Taipei University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taiwan

ISBN: (纸本)9782493814197

To accurately assess the dynamic impact of a company’s activities on its Environmental, Social, and Governance (ESG) scores, we have initiated a series of shared tasks, named ML-ESG. These tasks adhere to the MSCI guidelines for annotating news articles across various languages. This paper details the third iteration of our series, ML-ESG-3, with a focus on impact duration inference—a task that poses significant challenges in estimating the enduring influence of events, even for human analysts. In ML-ESG-3, we provide datasets in five languages (Chinese, English, French, Korean, and Japanese) and share insights from our experience in compiling such subjective datasets. Additionally, this paper reviews the methodologies proposed by ML-ESG-3 participants and offers a comparative analysis of the models’ performances. Concluding the paper, we introduce the concept for the forthcoming series of shared tasks, namely multi-lingual ESG promise verification, and discuss its potential contributions to the field. © 2024 ELRA Language Resource Association.

关键词： Iterative methods

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Experimentation of Integrating Roadmapping and Sci-Fi Prototyping Methods

Experimentation of Integrating Roadmapping and Sci-Fi Protot...

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2024 Portland International Conference on Management of engineering and Technology, PICMET 2024

作者： Nishinaka, Miwa Shirahada, Kunio Kishita, Yusuke Miyamoto, Dohjin Osawa, Hirotaka Kiyokawa, Sachiko Takeda, Hideaki The Graduate School of Management Kagawa University Kagawa Takamatsu Japan Ishikawa Nomi Japan The University of Tokyo Department of Precision Engineering Tokyo Japan Communication in Science and Technology Education and Research Program Hokkaido University Sapporo Japan Keio University Faculty of Science and Technology Kanagawa Yokohama Japan Graduate School of Education The University of Tokyo Tokyo Japan National Institute of Informatics Tokyo Japan

ISBN: (纸本)9781890843458

In 2023, we proposed a hypothetical knowledge management framework that incorporates science fiction prototyping (SFP) into the traditional roadmapping (RM) method to make RM more innovative and create a future beyond what we can currently imagine. Our main objective is to create a new organizational knowledge co-creation method for generating innovative ideas by incorporating humanistic factors utilizing SFP into RM. In the current article, we present the exploratory study we conducted to examine the hypothetical framework. Experimental workshops were held in November 2023 to compare the integrated method, in which SFP is applied to RM, with the original RM method. We followed a crossover design in the workshops and analyzed the results qualitatively and quantitatively following the perspectives proposed in the hypothetical framework. The qualitative analysis revealed successful integration regarding diverse and broader perspectives. The quantitative analysis utilizing Wilcoxon signed rank tests showed that the scores of the integrated method were significantly higher than those of RM for variables evaluating the effectiveness of the integration, while not for variables related to participants' feelings and satisfaction with the workshops, and sustainability. These findings indicate that the integration was successful in terms of its effectiveness as a method, while participants' subjective feelings toward the workshops were not different in both methods. As for sustainability, which requires a long-term perspective, no apparent differences were observed in these short-term workshops. © 2024 PICMET.

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NFT-Based Hydroponic Automated Control Using Adaptive Network-Based Fuzzy Inference System 2

NFT-Based Hydroponic Automated Control Using Adaptive Networ...

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2nd International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2022

作者： Surantha, Nico Vincentdo, Vito Bina Nusantara University Binus Graduate Program - Computer Science Jakarta11480 Indonesia Tokyo City University Faculty of Scienc and Engineering Department of Electrical Electronics and Communication Engineering Japan

ISBN: (纸本)9781665459440

The rapid population growth and industrial development in developing countries harm the agricultural sector because many agricultural lands are converted into residential or industrial areas. Applying modern agriculture technologies such as hydroponic could help to overcome the problem. However, hydroponics requires special attention in adjusting the pH and nutrient levels to maximize plant growth, so an automated system is needed to manage the process. In this research, a smart hydroponic system is proposed by applying Adaptive Networkbased Fuzzy Inference System (ANFIS) and Internet-of-Things. The IoT system consists of sensor, actuator, and data processing layer is designed to monitor and control the condition of pH and nutrition of the observed plants. Then, the ANFIS algorithm is designed to control the level of pH and nutrition. The experiment results show that the system can automatically adjust the pH and nutrient levels to the expected range for growing plants, and the fuzzy controller made using ANFIS are more accurate and stable than the fuzzy controller made using Sugeno. This study shows that ANFIS has excellent performance when controlling multiple actuators, as long as the data set has great granularity and well defined. © 2022 IEEE.

关键词： Hydroponics

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Mass transport in a highly immiscible alloy on extended shear deformation

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Journal of Materials science & Technology 2023年第3期134卷 197-208页

作者： Miao Song Jia Liu Xiaolong Ma Qin Pang Matthew J.Olszta Joshua Silverstein Madhusudhan R.Pallaka Peter V.Sushko Suveen N.Mathaudhu Cynthia Powell Arun Devaraj Bharat Gwalani Physical and Computational Sciences Directorate Pacific Northwest National Laboratory902 Battelle BoulevardRichlandWA 99354USA Energy and Environmental Directorate Pacific Northwest National Laboratory902 Battelle BoulevardRichlandWA 99354USA Material Science and Engineering Program University of CaliforniaRiversideCA92521USA Colorado School of Mines 1500 Illinois St.GoldenCO 8040USA Department of Materials Science and Engineering North Carolina State UniversityRaleighNC27695-7907USA State Key Laboratory of Powder Metallurgy Central South Uni-versityChangsha 410083China

Forced mixing to a single-phase or supersaturated solid solution(SSS)and its prerequisite microstructure evolution in immiscible systems has been a focus of research for fundamental science and practical *** the formation of SSS by shear deformation could enable a material design beyond conventional equilibrium microstructure in immiscible ***,a highly immiscible Cu-50 at.%Cr binary alloy(mixing enthalpy of∼20 kJ mol^(−1))was employed to investigate the microstructure evolution and localized tendencies of SSS during severe shear *** results demonstrate the dislocation mediated microstructural refinement process in each phase of the binary alloy and the mechanisms associated with localized solute supersaturation as a function of shear *** grain refinement in the softer Cu phase occurs owing to the strain localization driving the preferential dynamic *** grain refinement of the Cr phase,however,is enabled by the progressive evolution of grain lamination,splitting,and fragmentation as a function of shear *** solute supersaturation is found to be strongly dependent on the local environments that affect the dislocation activity,including the level of microstructure refinement,the interfacial orientation relationship,the mechanical incompatibility,and the localized preferential phase *** initio simulations confirm that it is more favorable to oxidize Cr than Cu at incoherent Cu/Cr interfaces,limiting the mass transport on an incoherent *** results unveil the mechanism underpinning the non-equilibrium mass transport in immiscible systems upon severe deformation that can be applied to produce immiscible alloys with superior mechanical properties.

关键词： Tribology Immiscible alloys Nanostructures Shear deformation Forced mixing Atom probe

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Recent advances in electronic devices for monitoring and modulation of brain

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Nano Research 2021年第9期14卷 3070-3095页

作者： Yong Won Kwon Yoon Sun Jun Young-Geun Park Jiuk Jang Jang-Ung Park Nano Science Technology Institute Department of Materials Science and EngineeringYonsei UniversitySeoul 03722Republic of Korea Center for Nanomedicine Institute for Basic Science(IBS)Seoul 03722Republic of Korea Graduate Program of Nano Biomedical Engineering(NanoBME) Advanced Science InstituteYonsei UniversitySeoul 03722Republic of Korea

The brain is actuated by billions of neurons with trillions of interconnections that regulate human *** the mechanisms of these systems that induce sensory reactions and respond to disease remains one of the greatest challenges in science,engineering,and *** advances in nanomaterials and nanotechnologies have led to the extensive research of electronic devices for brain interfaces to better understand the neural activities of the brains complex nervous *** development of sensor devices for monitoring the physiological signals of the brain related to traumatic injury status has accompanied by the progress of electronic neural probes in *** addition,these neurological and stereotactic surgical revolutions hold immense potential for clinical analysis of pharmacological systems within cerebral ***,we review the progress of electronic devices interfacing with brain in terms of the materials,fabrication technologies,and device *** activity can be measured and modulated by brain probes based on newly developed nanofabrication ***,in vivo pathological monitoring of the brain and pharmacological assessment has been developed in miniaturized and wireless *** also consider the key challenges and prospects for further development,and explore the future directions emerging in the latest research.

关键词： neural interfaces neural recording neuromodulation intracranial pressure monitoring microfluidic drug delivery

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Lower lumbar vertebrae replacement by FEA based assessment of suitable ceramic polymer composites 2

Lower lumbar vertebrae replacement by FEA based assessment o...

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2nd International Conference on Future Technologies in Manufacturing, Automation, Design and Energy

作者： Prasad, Prakriti Roy, Shatakshi Bhavsar, Kathan Chadha, Utkarsh Kataray, Tarun Vezhavendhan, R. Eticha, Tolera Kuma Tamilnadu Vellore632014 India Tamilnadu Vellore632014 India Department of Materials Science and Engineering School of Graduate Studies University of Toronto TorontoONM5S 1A1 Canada Department of Biology College of Natural and Computational Sciences Ambo University Ambo Ethiopia

ISBN: (纸本)9789819912902

Using bio-materials to develop a safe, secure, and prime substitute as an external entity to interact inside a human environment is a demanding area of research and expertise. The lumbar spine is the most common site for injury in the spinal column as it bears the majority of the human body's weight while also undergoing significant prolonged loading and stress. In the same direction, a cost-effective Artificial Lumbar vertebra is designed and recognized to be implanted in the spinal region of a body to replace injured or disfigured counterparts. By harnessing the power of 3D bioprinting, biomaterials, and FEA, the paper proves that a simple bio-printed flexible lumbar vertebrae can be integrated into the body to work in conjunction with the rest of the spinal cord just as any other of the vertebrae do, thereby working in coordination with humans. The material thus obtained will be capable of replacing the injuries in the vertebrae caused by mechanical failures like compressive loading, vertebral slip, or vertebral joint fusion. An overall lightweight structure consisting of a firm material is looked forward to for the paper's fusion. This insight, research, and design have led to the development of the research paper. © 2023 Elsevier Ltd. All rights reserved.

关键词： Finite element method

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