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Inferring the Effects of Protein Variants on Protein-Protein Interactions with Interpretable Transformer Representations

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Research 2024年第2期2023卷 473-489页

作者： Zhe Liu Wei Qian Wenxiang Cai Weichen Song Weidi Wang Dhruba Tara Maharjan Wenhong Cheng Jue Chen Han Wang Dong Xu Guan Ning Lin Shanghai Mental Health Center Shanghai Jiao Tong University School of MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiChina Shanghai Key Laboratory of Psychotic Disorders ShanghaiChina School of Information Science and Technology Institute of Computational BiologyNortheast Normal UniversityChangchunChina Department of Electrical Engineering and Computer Science University of MissouriColumbiaMO 65211USA Christopher S.Bond Life Sciences Center University of MissouriColumbiaMO 65211USA

Identifying pathogenetic variants and inferring their impact on protein-protein interactions sheds light on their functional consequences on *** by the availability of experimental data on the consequences of protein interaction,most existing methods focus on building models to predict changes in protein binding ***,we introduced MIPPI,an end-to-end,interpretable transformer-based deep learning model that learns features directly from sequences by leveraging the interaction data from *** was specifically trained to determine the types of variant impact(increasing,decreasing,disrupting,and no effect)on protein-protein *** demonstrate the accuracy of MIPPI and provide interpretation through the analysis of learned attention weights,which exhibit correlations with the amino acids interacting with the ***,we showed the practicality of MIPPI in prioritizing de novo mutations associated with complex neurodevelopmental disorders and the potential to determine the pathogenic and driving ***,we experimentally validated the functional impact of several variants identified in patients with such ***,MIPPI emerges as a versatile,robust,and interpretable model,capable of effectively predicting mutation impacts on protein-protein interactions and facilitating the discovery of clinically actionable variants.

关键词： consequences weights versatile

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Preserving Privacy of User Identity Based on Pseudonym Variable in 5G

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computers, Materials & Continua 2022年第3期70卷 5551-5568页

作者： Mamoon M.Saeed Mohammad Kamrul Hasan Rosilah Hassan Rania Mokhtar Rashid A.Saeed Elsadig Saeid Manoj Gupta Electrical Engineering Department Faculty of EngineeringAlzaiem Alazahri UniversityKhartoumSudan Center for Cyber Security Faculty of Information Science and TechnologyUniversiti KebangsaanMalaysia(UKM)43600BangiMalaysia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityPO Box 11099Taif21944Saudi Arabia Department of Electronics Engineering College of EngineeringSudan University of Science and TechnologyKhartoumSudan Department of Electronics and Communication Engineering JECRC UniversityJaipurIndia

The fifth generation(5G)system is the forthcoming generation of the mobile communication *** has numerous additional features and offers an extensively high data rate,more capacity,and low ***,these features and applications have many problems and issues in terms of security,which has become a great challenge in the telecommunication *** paper aimed to propose a solution to preserve the user identity privacy in the 5G system that can identify permanent identity by using Variable Mobile Subscriber Identity,which randomly changes and does not use the permanent identity between the user equipment and home *** this mechanism,the user identity privacy would be secured and ***,it improves the synchronization between mobile users and home ***,its compliance with the Authentication and Key Agreement(AKA)structure was adopted in the previous *** can be deployed efficiently in the preceding generations because the current architecture imposes minimal modifications on the network parties without changes in the authentication vector’s message ***,the addition of any hardware to the AKA carries minor adjustments on the network *** this paper,the ProVerif is used to verify the proposed scheme.

关键词： 5G privacy and security user identity IMSI authentication and key agreement(AKA)

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A 2.2-3.6 GHz CMOS Reconfigurable Fourth-Order Bandpass Filter With Compact Size and High Selectivity Using Transformer-Type Resonators

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IEEE Transactions on Microwave Theory and Techniques 2023年第1期71卷 218-229页

作者： Li, Kun Liu, Bin Chi, Pei-Ling Wang, Yong Yang, Tao University of Electronic Science and Technology of China School of Electronic Science and Engineering Chengdu Sichuan610054 China National Chiao Tung University Department of Electrical and Computer Engineering Hsinchu300 Taiwan Nanhu Laboratory Research Center of Advanced Rf Chips and Systems Jiaxing Zhejiang314000 China

A compact reconfigurable CMOS bandpass filter (BPF) with high selectivity is proposed using transformer-type resonators in this article. The transformer-type resonator is constructed by a transformer loaded with parallel varactors for frequency tuning, and two varactors are then added across primary wind and secondary wind for coupling tuning. With the transformer-type structure, one resonator is formed inside another resonator, thus fully utilizing the chip area and resulting in a miniaturized structure. Magnetic and electrical couplings are formed within the transformer-type resonator and facilitate the bandwidth (BW) tuning. The quality factor (Q) of each resonator is improved by cross-coupled negative resistance structure. Meanwhile, two pairs of transformer-type resonators are placed side-by-side and naturally form a quadruplet structure;as a result, two transmission zeros (TZs) are introduced at each side of the passband thus significantly improving the selectivity and stopband rejection of the BPF. The proposed tunable on-chip BPF is manufactured by a commercial 55 nm bulk CMOS technology with a core area of 1.48 × 0.54 mm2. The filter center frequency (CF) can be tuned from 2.2 to 3.6 GHz, while the 3 dB fractional BW (FBW) can be tuned from 14% to 33%. The shape factor of the proposed filter is 1.4-1.9. © 1963-2012 IEEE.

关键词： Varactors

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Inhibition of CD82 improves colitis by increasing NLRP3 deubiquitination by BRCC3

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Cellular & Molecular Immunology 2023年第2期20卷 189-200页

作者： Jae-Sung Kim Hyo Keun Kim Joongho Lee Sein Jang Euni Cho Seok-Jun Mun Seokhyun Yoon Chul-Su Yang Department of Bionano Technology Hanyang UniversitySeoul04673Korea Institute of Natural Science&Technology Hanyang UniversityAnsan15588Korea Department of Molecular and Life Science Hanyang UniversityAnsan15588Korea Center for Bionano Intelligence Education and Research Ansan15588Korea Department of Computer Science College of SW ConvergenceDankook UniversityYongin16890Korea Department of Electronics&Electrical Engineering College of EngineeringDankook UniversityYongin16890Korea

CD82 is a transmembrane protein that is involved in cancer suppression and activates immune cells;however, information on the NLRP3 inflammasome is limited. Herein, we show that although CD82 suppressed the activation of the NLRP3 inflammasome in vivo and in vitro, CD82 deficiency decreased the severity of colitis in mice. Furthermore, two binding partners of CD82, NLRP3 and BRCC3, were identified. CD82 binding to these partners increased the degradation of NLRP3 by blocking BRCC3-dependent K63-specific deubiquitination. Previous studies have shown that CD82-specific bacteria in the colon microbiota called Bacteroides vulgatus (B. vulgatus) regulated the expression of CD82 and promoted the activation of the NLRP3 inflammasome. Accordingly, we observed that B. vulgatus administration increased mouse survival by mediating CD82 expression and activating NLRP3 in mice with colitis. Overall, this study showed that CD82 suppression reduced the pathogenesis of colitis by elevating the activation of the NLRP3 inflammasome through BRCC3-dependent K63 deubiquitination. Based on our findings, we propose that B. vulgatus is a novel therapeutic candidate for colitis.

关键词： CD82 NLRP3 BRCC3 Colitis Inflammation

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Frequency Response and Design Based on gm/IDof Amplifier in CNFET technology 6

Frequency Response and Design Based on gm/IDof Amplifier in ...

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6th Iranian International Conference on Microelectronics, IICM 2024

作者： Zanjani, S. Mohammadali Dolatshahi, Mehdi Dousti, Massoud Alaie, Zahra Jahangir Moshayedi, Ata Mehrabi, Arash Smart Microgrid Research Center Najafabad Branch Islamic Azad University Najafabad Iran Najafabad Branch Islamic Azad University Department of Electrical Engineering Najafabad Iran Science and Research Branch Islamic Azad University Department of Electrical and Computer Engineering Tehran Iran School of Information Engineering Jiangxi University of Science and Technology Jiangxi341000 China

ISBN: (纸本)9798331511371

The downscaling of Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) elements in the nanoscale, leads to the deviation of V-I characteristics compared with the ideal behavior. For instance, in the elements with short channels, Drain voltage considerably impacts the potential barrier in a way that the Source injects the carriers into the channel without any Gate role. This is due to the decrease in the height of the barrier by the Drain. An appropriate alternative for the MOS technology is the Carbon Nanotube Field Effect Transistors (CNFETs). The high mobility of carriers in the CNT results in their higher speed in CNFET transistors. Low power dissipation, nano dimension, low noise figure, the similarity of performance with the MOSFETs, and the ballistic transition of the carriers are their advantages. In this paper, together with the study of CNFET's structure and models, the impact of variations of input voltage, the number of nanotubes, pitches, and chirality on the current, threshold voltage, and V-I characteristics of a common source amplifier are studied. Moreover, it is observed that in the same specifications of the aspect ratio and bias, in the CNFET transistors, the gm/ID figure according to the normalized current in the Weak Inversion and Moderate regions is higher than the MOSFETs, shows that this technology as the fair choice can be an appropriate alternative for the MOSFETs. © 2024 IEEE.

关键词： Chirality

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A Hybrid EEG-EMG Framework for Humanoid Control using Deep Learning Transformers

A Hybrid EEG-EMG Framework for Humanoid Control using Deep L...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Olikkal, Parthan Pillai, Branesh M. Suthakorn, Jackrit Ali, Habib Vinjamuri, Ramana University of Maryland Baltimore County Vinjamuri lab Department of Computer Science and Electrical Engineering BaltimoreMD21220 United States Mahidol University Center for Biomedical and Robotics Technology Nakorm Pathom Salaya Thailand

ISBN: (纸本)9781665481090

Brain-computer interfaces (BCIs) offer promising solutions for upper limb rehabilitation. Despite advancements in deep learning, traditional models for motor rehabilitation using electroencephalography (EEG) or electromyography (EMG) to control assistive devices require enhancement. This study aims to enhance motor control capabilities by integrating EEG and EMG signals using a Transformer-based deep learning model. Ten able-bodies subjects performed center-out tasks on a low-cost upper limb rehabilitation table, capturing 2D kinematic data, EEG, and EMG signals simultaneously. The tasks varied in complexity across four levels. Preprocessed EEG and EMG signals were fused and given as input to the proposed model, which was evaluated using three performance metrics. Results showed that the EEG-EMG combined model achieved 87.27% accuracy across all the four levels. Furthermore, the model's output successfully controlled a humanoid robot to replicate similar movements. These findings highlight the efficacy of combined EEG-EMG data in improving accuracy and performance in BCI applications, advancing assistive technologies and neurorehabilitation interventions. © 2024 IEEE.

关键词： Anthropomorphic robots

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Boosting Monolayer Transition Metal Dichalcogenides Growth by Hydrogen-Free Ramping during Chemical Vapor Deposition

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Nano Letters 2024年第27期24卷 8277-8286页

作者： Liu, Hongwei Zhang, Tianyi Wu, Peng Lee, Hae Won Liu, Zhenjing Tang, Tsz Wing Tang, Shin-Yi Kang, Ting Park, Ji-Hoon Wang, Jun Zhang, Kenan Zheng, Xudong Peng, Yu-Ren Chueh, Yu-Lun Liu, Yuan Palacios, Tomás Kong, Jing Luo, Zhengtang Department of Chemical and Biological Engineering Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology William Mong Institute of Nano Science and Technology and Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction The Hong Kong University of Science and Technology Kowloon999077 Hong Kong Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Materials Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Materials Science and Engineering National Tsing-Hua University Hsinchu30013 Taiwan Department of Materials Science and Engineering Korea University Seoul02841 Korea Republic of Key Laboratory for Micro-Nano Optoelectronic Devices of Ministry of Education School of Physics and Electronics Hunan University Changsha410082 China

The controlled vapor-phase synthesis of two-dimensional (2D) transition metal dichalcogenides (TMDs) is essential for functional applications. While chemical vapor deposition (CVD) techniques have been successful for transition metal sulfides, extending these methods to selenides and tellurides often faces challenges due to uncertain roles of hydrogen (H2) in their synthesis. Using CVD growth of MoSe2 as an example, this study illustrates the role of a H2-free environment during temperature ramping in suppressing the reduction of MoO3, which promotes effective vaporization and selenization of the Mo precursor to form MoSe2 monolayers with excellent crystal quality. As-synthesized MoSe2 monolayer-based field-effect transistors show excellent carrier mobility of up to 20.9 cm2/(V·s) with an on-off ratio of 7 × 107. This approach can be extended to other TMDs, such as WSe2, MoTe2, and MoSe2/WSe2 in-plane heterostructures. Our work provides a rational and facile approach to reproducibly synthesize high-quality TMD monolayers, facilitating their translation from laboratory to manufacturing. © 2024 American Chemical Society.

关键词： Monolayers

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Adopting GPU computing to support DL-based Earth science applications

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International Journal of Digital Earth 2023年第1期16卷 2660-2680页

作者： Zifu Wang Yun Li Kevin Wang Jacob Cain Mary Salami Daniel Q.Duffy Michael M.Little Chaowei Yang Department of Geography and Geoinformation Science NSF Spatiotemporal Innovation CenterGeorge Mason UniversityFairfaxVAUSA Department of Electrical Engineering and Computer Science University of CaliforniaBerkeleyCAUSA Department of Geography University of California Santa BarbarGoletaCAUSA NASA Goddard Computational and Information Sciences and Technology OfficeGreenbeltMDUSA

With the advancement of Artificial Intelligence(Al)technologies and accumulation of big Earth data,Deep Learning(DL)has become an important method to discover patterns and understand Earth science processes in the past several *** successful in many Earth science areas,Al/DL applications are often challenging for computing *** recent years,Graphics Processing Unit(GPU)devices have been leveraged to speed up Al/DL applications,yet computational performance still poses a major barrier for DL-based Earth science *** address these computational challenges,we selected five existing sample Earth science Al applications,revised the DL-based models/algorithms,and tested the performance of multiple GPU computing platforms to support the *** softwarepackages,performance comparisonsacross different platforms,along with other results,are *** article can help understand how various Al/ML Earth science applications can be supported by GPU computing and help researchers in the Earth science domain better adopt GPU computing(such as supermicro,GPU clusters,and cloud computing-based)for their Al/ML applications,and to optimize their science applications to better leverage the computing device.

关键词： GPU computing GeoAl open science Earth science artificial intelligence

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A novel deep learning approach for investigating liquid fuel injection in combustion system

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Discover Artificial Intelligence 2025年第1期5卷 1-14页

作者： Inam, Syed Azeem Khan, Abdullah Ayub Ahmed, Noor Mazhar, Tehseen Shahzad, Tariq Khan, Sunawar Saeed, Mamoon M. Hamam, Habib Department of Artificial Intelligence and Mathematical Science Sindh Madressatul Islam University Sindh Karachi Pakistan Department of Computer Science and Information Technology Shaheed Benazir Bhutto University Lyari Karachi Pakistan Department of Computer Science Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology Karachi Pakistan Department of Computer Science School Education Department Government of Punjab Layyah31200 Pakistan School of Computer Science National College of Business Administration and Economics Lahore54000 Pakistan Department of Computer Engineering COMSATS University Islamabad Sahiwal Campus Sahiwal57000 Pakistan Department of Software Engineering Islamia University of Bahawalpur Bahawalnagar62300 Pakistan Sana’a00967 Yemen Faculty of Engineering Uni de Moncton MonctonNBE1A3E9 Canada Department of Electrical and Electronic Engineering Sciences University of Johannesburg Johannesburg South Africa Av. Grandes Ecoles BP 1989 Libreville Gabon Bridges for Academic Excellence Spectrum Center-ville Tunis Tunisia

The intricacies and instability of introducing cryogenic propellants into the combustion system have piqued the curiosity of scientists studying the procedure. The latest innovation is utilizing data-driven machine learning and deep learning approaches to gain deeper insights into the related difficulties. However, the current work serves as a baseline for future research because relatively few studies have used data-driven methodologies to assess the temperature of liquid fuel injections in combustion systems. The performance of Linear Regression (LR), Random Forest (RF), Extra Trees Regressor (ETR), Polynomial Regression (PR), Support Vector Regressor (SVR), Decision Tree Regressor (DTR), Gradient Boost Regressor (GBR), XGB Regressor (XGBoost), AdaBoost Regressor (ABR), K-Neighbors Regressor (KNR), Long-Short Term Memory (LSTM), Bi-LSTM (Bi-directional Long-Short Term Memory) has all been investigated in this study. The study also suggested a Fully Connected Neural Network (FCNN) to examine its performance and paired it with an Extra Tree Regressor (ETR). The coupled FCNN and Extra Tree Regressor outperform the other algorithms with a Mean Square Error (MSE) of 0.0000005062, Root Mean Square Error (RMSE) of 0.00071148, Mean Absolute Error (MAE) of 0.00020672, and R-squared (R2) value of 0.99998689. Linear Regression, Polynomial Regression, and Support Vector Regressor are found to be the least-performing algorithms. The current work uses machine learning and deep learning methods to make data-driven decisions for liquid fuel injection in the combustion system. © The Author(s) 2025.

关键词： Deep learning

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Boosting efficiency and stability of 2D alternating cation perovskite solar cells via rational surface-modification: Marked passivation efficacy of anion

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Journal of Energy Chemistry 2023年第9期84卷 354-362页

作者： Hualin Zheng Xuefeng Peng Tingxi Chen Ting Zhang Shihao Yuan Lei Wang Feng Qian Jiang Huang Xiaodong Liu Zhi David Chen Yanning Zhang Shibin Li State Key Laboratory of Electronic Thin Films and Integrated Devices and School of Optoelectronic Science and EngineeringUniversity of Electronic Science and Technology of China(UESTC)Chengdu 610054SichuanChina Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China(UESTC)Chengdu 610054SichuanChina Department of Electrical&Computer Engineering and Center for Nanoscale Science&EngineeringUniversity of KentuckyLexingtonKY 40506USA Institute of Electronic and Information Engineering of UESTC in Guangdong Dongguan 523808GuangdongChina

Two-dimensional(2D) alternating cation(ACI) perovskite surface defects,especially dominant iodine vacancies(V_Ⅰ) and undercoordinated Pb^(2+),limit the performance of perovskite solar cells(PVSCs).To address the issue,1-butyl-3-methylimidazolium trifluoro-methane-sulfonate(BMIMOTF) and its iodide counterpart(BMIMI) are utilized to modify the perovskite surface *** find that BMIMI can change the perovskite surface,whereas BMIMOTF shows a nondestructive and more effective defect passivation,giving significantly reduced defect density and suppressed charge-carrier nonradiative *** mainly attributes to the marked passivation efficacy of OTF-anion on V_Ⅰ and undercoordinated Pb^(2+),rather than BMIMI^(+) *** from the rational surface-modification of BMMIMOTF,the films exhibit an optimized energy level alignment,enhanced hydrophobicity and suppressed ion ***,the BMIMOTF-modified devices achieve an impressive efficiency of 21.38% with a record open-circuit voltage of 1.195 V,which is among the best efficiencies reported for 2D PVSCs,and display greatly enhanced humidity and thermal stability.

关键词： 2D ACI perovskite solar cells Charge-carrier nonradiative recombination Surface defects passivation Energy level alignment Ionic migration Stability

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