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arXiv 2024年

作者： Gu, Xinyu Aranganathan, Akashnathan Tiwary, Pratyush Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States Department of Chemistry and Biochemistry University of Maryland College Park20742 United States University of Maryland Institute for Health Computing Bethesda United States Biophysics Program University of Maryland College Park20742 United States

Small molecule drug design hinges on obtaining co-crystallized ligand-protein structures. Despite AlphaFold2’s strides in protein native structure prediction, its focus on apo structures overlooks ligands and associated holo structures. Moreover, designing selective drugs often benefits from the targeting of diverse metastable conformations. Therefore, direct application of AlphaFold2 models in virtual screening and drug discovery remains tentative. Here, we demonstrate an AlphaFold2 based framework combined with all-atom enhanced sampling molecular dynamics and induced fit docking, named AF2RAVE-Glide, to conduct computational model based small molecule binding of metastable protein kinase conformations, initiated from protein sequences. We demonstrate the AF2RAVE-Glide workflow on three different protein kinases and their type I and II inhibitors, with special emphasis on binding of known type II kinase inhibitors which target the metastable classical DFG-out state. These states are not easy to sample from AlphaFold2. Here we demonstrate how with AF2RAVE these metastable conformations can be sampled for different kinases with high enough accuracy to enable subsequent docking of known type II kinase inhibitors with more than 50% success rates across docking calculations. We believe the protocol should be deployable for other kinases and more proteins generally. © 2024, CC BY.

关键词： Ligands

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Multi-Active Multi-Datacenter Distributed Database Architecture Design based-on Secondary Development Zookeeper

Multi-Active Multi-Datacenter Distributed Database Architect...

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2022 International Conference on Emerging Technologies in Electronics, computing and Communication, ICETECC 2022

作者： Yang, Zhen Guang Alejandro, Leonard L. Vergara, Charlene I. Maaliw, Renato R. Alon, Alvin Sarraga Evangelista, Ryan Soriente Rivera, Reden Paul Layug Santos, Ronnel Cabral Delos Adamson University Graduate Program Manila Philippines Adamson University It&is Department Manila Philippines Southern Luzon State University College of Engineering Quezon Lucban Philippines Batangas State University Digital Transformation Center Batangas Philippines Sulu State College School of Graduate Studies Sulu Philippines Don Honorio Ventura State University College of Computing Studies Pampanga Philippines

ISBN: (纸本)9781665490870

Multi-Active Multi-Datacenter zookeeper is a very core basic component of ***. It is equivalent to the database of basic components, including GZS (Global Zone Service, global state coordinator), DAL (Data Access Layer, database middleware software), Huskar (SOA framework that the online publishing system depends on), maxq (*** message queue), Samaritan (load balancer with service discovery), abtest and other basic components. We are based on the apache official zookeeper for the secondary development to enable it to synchronize data in multiple IDCs. Such an important component must improve the stability and efficiency by the way of DevOps. For this reason, we have developed the EZK operation and maintenance management platform. © 2022 IEEE.

关键词： Distributed database systems

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MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods

arXiv

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arXiv 2023年

作者： Taghibakhshi, Ali Nytko, Nicolas Zaman, Tareq Uz MacLachlan, Scott Olson, Luke N. West, Matthew Department of Mechanical Science and Engineering University of Illinois Urbana-Champaign United States Department of Computer Science University of Illinois Urbana-Champaign United States Scientific Computing Program Memorial University of Newfoundland Canada Department of Mathematics and Statistics Memorial University of Newfoundland Canada

Domain decomposition methods (DDMs) are popular solvers for discretized systems of partial differential equations (PDEs), with one-level and multilevel variants. These solvers rely on several algorithmic and mathematical parameters, prescribing overlap, subdomain boundary conditions, and other properties of the DDM. While some work has been done on optimizing these parameters, it has mostly focused on the one-level setting or special cases such as structured-grid discretizations with regular subdomain construction. In this paper, we propose multigrid graph neural networks (MG-GNN), a novel GNN architecture for learning optimized parameters in two-level DDMs. We train MG-GNN using a new unsupervised loss function, enabling effective training on small problems that yields robust performance on unstructured grids that are orders of magnitude larger than those in the training set. We show that MG-GNN outperforms popular hierarchical graph network architectures for this optimization and that our proposed loss function is critical to achieving this improved performance. © 2023, CC BY.

关键词： Domain decomposition methods

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A Differential Evolution Algorithm for Contrast Optimization 9th

A Differential Evolution Algorithm for Contrast Optimization

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9th Brazilian Conference on Intelligent Systems, BRACIS 2020

作者： da Costa Oliveira, Artur Leandro Britto, André Post-Graduation Program in Computer Science Federal University of Sergipe Sergipe Brazil Departament of Computing Federal University of Sergipe Sergipe Brazil

ISBN: (纸本)9783030613761

Image Enhancement is one of the most important phases of the image processing system. Contrast Enhancement plays a key role in this step. Histogram Equalization (HE) is one of the main tools used to improve the contrast of an image. However, the use of HE causes an increase in the natural brightness of the image, which is not desirable in many types of applications such as consumer electronics products. To solve these limitations, it is proposed in this paper a variation of the Differential Evolution metaheuristic algorithm for Contrast Optimization called DECO. The results obtained were statistically compared with other techniques and metaheuristic algorithms. The results showed that DECO is competitive compared with other techniques. © 2020, Springer Nature Switzerland AG.

关键词： Optimization

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Designing Classical Header Bits for Quantum Wrapper Networking with O-band Quantum Signal

Designing Classical Header Bits for Quantum Wrapper Networki...

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Frontiers in Optics + Laser Science 2023, FiO, LS 203: Part of Frontiers in Optics + Laser Science 2023

作者： Gül, G. Berkay On, M. Singh, S.K. Proietti, R. Kanter, G.S. Yoo, S.J.B. Kumar, P. Graduate Program in Applied Physics Northwestern University 2145 Sheridan Road EvanstonIL60208 United States Department of Electrical and Computer Engineering University of California Davis DavisCA95616 United States Department of Electronics and Communication Eng. Indian Institute of Technology Roorkee247667 India Department of Electronics and Telecommunications Engineering Politecnico di Torino Italy Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States

We investigate the impact of wavelength choice for the classical headers in quantum wrapper networking with O-band quantum payload. We show that a C-band header performs substantially better than an O-band header. ... 详细信息

ISBN: (纸本)9781957171296

关键词： Bandpass filters Beam splitters Bit error rate Entanglement distribution Quantum teleportation Raman scattering

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Modeling Of Mean Tropospheric Temperature From Convolutional Neural Networks

Modeling Of Mean Tropospheric Temperature From Convolutional...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Diego Brum Vinicius Francisco Rofatto Leonardo Scalco Rafaela de Oliveira Pena Luiz Gonzaga Daniel C. Zanotta Luiz Fernando Sapucci Mauricio Roberto Veronez VIZLAB—X-Reality and Geoinformatics Laboratory UNISINOS Sao Leopoldo RS Brazil Graduate Program on Applied Computing UNISINOS Sao Leopoldo RS Brazil Institute of Geography Federal University of Uberlandia Monte Carmelo MG Brazil Graduate Program in Agriculture and Geospatial Information Federal University of Uberlandia Monte Carmelo MG Brazil Brazilian Institute of Space Research (INPE) Cachoeira Paulista SP Brazil

The Mean Tropospheric Temperature (Tm) is important for the sake of the conversion between Zenith Path Delay (ZPD) to Precipitable Water Vapor (PWV) because of the proportionality constant that takes Tm to be calculated. In Brazil, Tm modeling’s been traditionally performed using Multiple Linear Regression Models (MLR). However, recent works suggest the use of Deep Learning methods to model Tm values. In this work, we propose models based on Convolutional Neural Networks (CNN) using radiosonde data from 1961 to 2010. The results show that CNN models can outperform the traditional methods considering different statistic metrics like R, standard deviation, and RMSE.

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Minimizing the Number of Stunting Prevalence Using the Euclid Algorithm Clustering Approach

Minimizing the Number of Stunting Prevalence Using the Eucli...

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International Conference of Computer Science and Information Technology

作者： Muhammad Zarlis Tanty Oktavia Relita Buaton Ferda Ernawan Kevin Andrian Department BINUS Graduate Program - Master of Information System Management Information System Management Bina Nusantara University Jakarta Indonesia Informatics Engineering STMIK Kaputama Binjai Indonesia Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah Pekan Malaysia Department of Information Systems Management BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia

Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrition today. According to a UNICEF report, the number of people suffering from malnutrition in the world will reach 767.9 million people in 2021. The World Health Organization (WHO) said that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster the prevalence of stunting to produce a pattern that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city.

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Scaling laws and spatial effects of Brazilian health regions: A research protocol

Scaling laws and spatial effects of Brazilian health regions...

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2022 International Conference on ENTERprise Information Systems, CENTERIS 2022 - International Conference on Project MANagement, ProjMAN 2022 and International Conference on Health and Social Care Information Systems and Technologies, HCist 2022

作者： Soares, Giovane Thomazini Yamada, Diego Bettiol Bernardi, Filipe Andrade Neiva, Mariane Barros Lombardi, Luis Pedro Vinci, Andre Luiz Teixeira De Andrade Mioto, Ana Clara Alves, Domingos Ribeirão Preto Medical School University of Sao Paulo Av Bandeirantes 3900SP Ribeirao Preto14049900 Brazil Bioengineering Postgraduate Program Av Trabalhador Sao-Carlense 400SP Sao Carlos13566590 Brazil Institute of Mathematics and Computer Sciences Av Trabalhador Sao-Carlense 400SP Sao Carlos13566590 Brazil Institute of Mathematics Statistics and Scientific Computing State University of Campinas Rua Sergio Buarque de Holanda 651SP Campinas13083859 Brazil

The literature has already consolidated the importance of health regions for Brazilian public health. Complexity properties strongly mark such regions. In this context, there are abundant indications that health regions should be analyzed with approaches linked to the sciences of complexity. One of these approaches, the estimation of scaling laws, can describe important properties of socio-spatial elements. However, no studies estimate the scaling laws of Brazilian health regions. This research protocol can remedy this limitation, proposing the estimation of scaling laws of the previously mentioned regions, mainly considering variables relevant to Brazilian public health. Still, this paper can substantially mitigate other relevant limitations of usual research that estimate scaling laws of socio-spatial elements. These mitigations, which provide advances in the literature on estimating scaling laws, are given by the proposal of modeling (if necessary) spatial effects and estimating scaling laws for the entire population of the socio-spatial elements. According to the theory, the expected results are non-linear scaling laws, which will likely vary with space and time and coexist with relevant spatial effects. From such laws and effects, it will be possible to accurately characterize the performance of each health region through Spatial and Scale Adjusted Metropolitan Indicators and unravel spatio-Temporal properties, stabilities, and instabilities of sets composed of health regions. The expected findings of this paper can help rearrange health regions and improve the quality of information used in Brazilian public health planning. © 2023 Elsevier B.V.. All rights reserved.

关键词： Scaling laws

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GraCo: Granularity-Controllable Interactive Segmentation

arXiv

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arXiv 2024年

作者： Zhao, Yian Li, Kehan Cheng, Zesen Qiao, Pengchong Zheng, Xiawu Ji, Rongrong Liu, Chang Yuan, Li Chen, Jie School of Electronic and Computer Engineering Peking University Shenzhen China Peng Cheng Laboratory Shenzhen China -Preferred Program Peking University Shenzhen Graduate School China Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University China Department of Automation and BNRist Tsinghua University Beijing China

Interactive Segmentation (IS) segments specific objects or parts in the image according to user input. Current IS pipelines fall into two categories: single-granularity output and multi-granularity output. The latter aims to alleviate the spatial ambiguity present in the former. However, the multi-granularity output pipeline suffers from limited interaction flexibility and produces redundant results. In this work, we introduce Granularity-Controllable Interactive Segmentation (GraCo), a novel approach that allows precise control of prediction granularity by introducing additional parameters to input. This enhances the customization of the interactive system and eliminates redundancy while resolving ambiguity. Nevertheless, the exorbitant cost of annotating multi-granularity masks and the lack of available datasets with granularity annotations make it difficult for models to acquire the necessary guidance to control output granularity. To address this problem, we design an any-granularity mask generator that exploits the semantic property of the pre-trained IS model to automatically generate abundant mask-granularity pairs without requiring additional manual annotation. Based on these pairs, we propose a granularity-controllable learning strategy that efficiently imparts the granularity controllability to the IS model. Extensive experiments on intricate scenarios at object and part levels demonstrate that our GraCo has significant advantages over previous methods. This highlights the potential of GraCo to be a flexible annotation tool, capable of adapting to diverse segmentation scenarios. The project page: https://***/GraCo. Copyright © 2024, The Authors. All rights reserved.

关键词： Pipelines

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Designing Classical Header Bits for Quantum Wrapper Networking with O-band Quantum Signal

Designing Classical Header Bits for Quantum Wrapper Networki...

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2023 Laser Science, LS 2023

作者： Gül, G. On, M. Berkay Singh, S.K. Proietti, R. Kanter, G.S. Yoo, S.J.B. Kumar, P. Graduate Program in Applied Physics Northwestern University 2145 Sheridan Road EvanstonIL60208 United States Department of Electrical and Computer Engineering University of California Davis DavisCA95616 United States Department of Electronics and Communication Eng. Indian Institute of Technology Roorkee247667 India Department of Electronics and Telecommunications Engineering Politecnico di Torino Italy Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States

关键词： Quantum electronics

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